Towards Accurate Ab Initio Predictions of the Spectrum of Methane

NASA Technical Reports Server (NTRS)

Schwenke, David W.; Kwak, Dochan (Technical Monitor)

2001-01-01

We have carried out extensive ab initio calculations of the electronic structure of methane, and these results are used to compute vibrational energy levels. We include basis set extrapolations, core-valence correlation, relativistic effects, and Born- Oppenheimer breakdown terms in our calculations. Our ab initio predictions of the lowest lying levels are superb.

Novel, customizable scoring functions, parameterized using N-PLS, for structure-based drug discovery.

PubMed

Catana, Cornel; Stouten, Pieter F W

2007-01-01

The ability to accurately predict biological affinity on the basis of in silico docking to a protein target remains a challenging goal in the CADD arena. Typically, "standard" scoring functions have been employed that use the calculated docking result and a set of empirical parameters to calculate a predicted binding affinity. To improve on this, we are exploring novel strategies for rapidly developing and tuning "customized" scoring functions tailored to a specific need. In the present work, three such customized scoring functions were developed using a set of 129 high-resolution protein-ligand crystal structures with measured Ki values. The functions were parametrized using N-PLS (N-way partial least squares), a multivariate technique well-known in the 3D quantitative structure-activity relationship field. A modest correlation between observed and calculated pKi values using a standard scoring function (r2 = 0.5) could be improved to 0.8 when a customized scoring function was applied. To mimic a more realistic scenario, a second scoring function was developed, not based on crystal structures but exclusively on several binding poses generated with the Flo+ docking program. Finally, a validation study was conducted by generating a third scoring function with 99 randomly selected complexes from the 129 as a training set and predicting pKi values for a test set that comprised the remaining 30 complexes. Training and test set r2 values were 0.77 and 0.78, respectively. These results indicate that, even without direct structural information, predictive customized scoring functions can be developed using N-PLS, and this approach holds significant potential as a general procedure for predicting binding affinity on the basis of in silico docking.

Comparison of the performance of different DFT methods in the calculations of the molecular structure and vibration spectra of serotonin (5-hydroxytryptamine, 5-HT)

NASA Astrophysics Data System (ADS)

Yang, Yue; Gao, Hongwei

2012-04-01

Serotonin (5-hydroxytryptamine, 5-HT) is a monoamine neurotransmitter which plays an important role in treating acute or clinical stress. The comparative performance of different density functional theory (DFT) methods at various basis sets in predicting the molecular structure and vibration spectra of serotonin was reported. The calculation results of different methods including mPW1PW91, HCTH, SVWN, PBEPBE, B3PW91 and B3LYP with various basis sets including LANL2DZ, SDD, LANL2MB, 6-31G, 6-311++G and 6-311+G* were compared with the experimental data. It is remarkable that the SVWN/6-311++G and SVWN/6-311+G* levels afford the best quality to predict the structure of serotonin. The results also indicate that PBEPBE/LANL2DZ level show better performance in the vibration spectra prediction of serotonin than other DFT methods.

Modeling transit bus fuel consumption on the basis of cycle properties.

PubMed

Delgado, Oscar F; Clark, Nigel N; Thompson, Gregory J

2011-04-01

A method exists to predict heavy-duty vehicle fuel economy and emissions over an "unseen" cycle or during unseen on-road activity on the basis of fuel consumption and emissions data from measured chassis dynamometer test cycles and properties (statistical parameters) of those cycles. No regression is required for the method, which relies solely on the linear association of vehicle performance with cycle properties. This method has been advanced and examined using previously published heavy-duty truck data gathered using the West Virginia University heavy-duty chassis dynamometer with the trucks exercised over limited test cycles. In this study, data were available from a Washington Metropolitan Area Transit Authority emission testing program conducted in 2006. Chassis dynamometer data from two conventional diesel buses, two compressed natural gas buses, and one hybrid diesel bus were evaluated using an expanded driving cycle set of 16 or 17 different driving cycles. Cycle properties and vehicle fuel consumption measurements from three baseline cycles were selected to generate a linear model and then to predict unseen fuel consumption over the remaining 13 or 14 cycles. Average velocity, average positive acceleration, and number of stops per distance were found to be the desired cycle properties for use in the model. The methodology allowed for the prediction of fuel consumption with an average error of 8.5% from vehicles operating on a diverse set of chassis dynamometer cycles on the basis of relatively few experimental measurements. It was found that the data used for prediction should be acquired from a set that must include an idle cycle along with a relatively slow transient cycle and a relatively high speed cycle. The method was also applied to oxides of nitrogen prediction and was found to have less predictive capability than for fuel consumption with an average error of 20.4%.

Materials prediction via classification learning

DOE PAGES

Balachandran, Prasanna V.; Theiler, James; Rondinelli, James M.; ...

2015-08-25

In the paradigm of materials informatics for accelerated materials discovery, the choice of feature set (i.e. attributes that capture aspects of structure, chemistry and/or bonding) is critical. Ideally, the feature sets should provide a simple physical basis for extracting major structural and chemical trends and furthermore, enable rapid predictions of new material chemistries. Orbital radii calculated from model pseudopotential fits to spectroscopic data are potential candidates to satisfy these conditions. Although these radii (and their linear combinations) have been utilized in the past, their functional forms are largely justified with heuristic arguments. Here we show that machine learning methods naturallymore » uncover the functional forms that mimic most frequently used features in the literature, thereby providing a mathematical basis for feature set construction without a priori assumptions. We apply these principles to study two broad materials classes: (i) wide band gap AB compounds and (ii) rare earth-main group RM intermetallics. The AB compounds serve as a prototypical example to demonstrate our approach, whereas the RM intermetallics show how these concepts can be used to rapidly design new ductile materials. In conclusion, our predictive models indicate that ScCo, ScIr, and YCd should be ductile, whereas each was previously proposed to be brittle.« less

Materials Prediction via Classification Learning

PubMed Central

Balachandran, Prasanna V.; Theiler, James; Rondinelli, James M.; Lookman, Turab

2015-01-01

In the paradigm of materials informatics for accelerated materials discovery, the choice of feature set (i.e. attributes that capture aspects of structure, chemistry and/or bonding) is critical. Ideally, the feature sets should provide a simple physical basis for extracting major structural and chemical trends and furthermore, enable rapid predictions of new material chemistries. Orbital radii calculated from model pseudopotential fits to spectroscopic data are potential candidates to satisfy these conditions. Although these radii (and their linear combinations) have been utilized in the past, their functional forms are largely justified with heuristic arguments. Here we show that machine learning methods naturally uncover the functional forms that mimic most frequently used features in the literature, thereby providing a mathematical basis for feature set construction without a priori assumptions. We apply these principles to study two broad materials classes: (i) wide band gap AB compounds and (ii) rare earth-main group RM intermetallics. The AB compounds serve as a prototypical example to demonstrate our approach, whereas the RM intermetallics show how these concepts can be used to rapidly design new ductile materials. Our predictive models indicate that ScCo, ScIr, and YCd should be ductile, whereas each was previously proposed to be brittle. PMID:26304800

Quantum-mechanics-derived 13Cα chemical shift server (CheShift) for protein structure validation

PubMed Central

Vila, Jorge A.; Arnautova, Yelena A.; Martin, Osvaldo A.; Scheraga, Harold A.

2009-01-01

A server (CheShift) has been developed to predict 13Cα chemical shifts of protein structures. It is based on the generation of 696,916 conformations as a function of the φ, ψ, ω, χ1 and χ2 torsional angles for all 20 naturally occurring amino acids. Their 13Cα chemical shifts were computed at the DFT level of theory with a small basis set and extrapolated, with an empirically-determined linear regression formula, to reproduce the values obtained with a larger basis set. Analysis of the accuracy and sensitivity of the CheShift predictions, in terms of both the correlation coefficient R and the conformational-averaged rmsd between the observed and predicted 13Cα chemical shifts, was carried out for 3 sets of conformations: (i) 36 x-ray-derived protein structures solved at 2.3 Å or better resolution, for which sets of 13Cα chemical shifts were available; (ii) 15 pairs of x-ray and NMR-derived sets of protein conformations; and (iii) a set of decoys for 3 proteins showing an rmsd with respect to the x-ray structure from which they were derived of up to 3 Å. Comparative analysis carried out with 4 popular servers, namely SHIFTS, SHIFTX, SPARTA, and PROSHIFT, for these 3 sets of conformations demonstrated that CheShift is the most sensitive server with which to detect subtle differences between protein models and, hence, to validate protein structures determined by either x-ray or NMR methods, if the observed 13Cα chemical shifts are available. CheShift is available as a web server. PMID:19805131

Vibrational spectroscopic study of terbutaline hemisulphate

NASA Astrophysics Data System (ADS)

Ali, H. R. H.; Edwards, H. G. M.; Kendrick, J.; Scowen, I. J.

2009-05-01

The Raman spectrum of terbutaline hemisulphate is reported for the first time, and molecular assignments are proposed on the basis of ab initio BLYP DFT calculations with a 6-31G* basis set and vibrational frequencies predicted within the quasi-harmonic approximation; these predictions compare favourably with the observed vibrational spectra. Comparison with previously published infrared data explains several spectral features. The results from this study provide data that can be used for the preparative process monitoring of terbutaline hemisulphate, an important β 2 agonist drug in various dosage forms and its interaction with excipients and other components.

Electronic and spectroscopic characterizations of SNP isomers

NASA Astrophysics Data System (ADS)

Trabelsi, Tarek; Al Mogren, Muneerah Mogren; Hochlaf, Majdi; Francisco, Joseph S.

2018-02-01

High-level ab initio electronic structure calculations were performed to characterize SNP isomers. In addition to the known linear SNP, cyc-PSN, and linear SPN isomers, we identified a fourth isomer, linear PSN, which is located ˜2.4 eV above the linear SNP isomer. The low-lying singlet and triplet electronic states of the linear SNP and SPN isomers were investigated using a multi-reference configuration interaction method and large basis set. Several bound electronic states were identified. However, their upper rovibrational levels were predicted to pre-dissociate, leading to S + PN, P + NS products, and multi-step pathways were discovered. For the ground states, a set of spectroscopic parameters were derived using standard and explicitly correlated coupled-cluster methods in conjunction with augmented correlation-consistent basis sets extrapolated to the complete basis set limit. We also considered scalar and core-valence effects. For linear isomers, the rovibrational spectra were deduced after generation of their 3D-potential energy surfaces along the stretching and bending coordinates and variational treatments of the nuclear motions.

Towards accurate ab initio predictions of the vibrational spectrum of methane

NASA Technical Reports Server (NTRS)

Schwenke, David W.

2002-01-01

We have carried out extensive ab initio calculations of the electronic structure of methane, and these results are used to compute vibrational energy levels. We include basis set extrapolations, core-valence correlation, relativistic effects, and Born-Oppenheimer breakdown terms in our calculations. Our ab initio predictions of the lowest lying levels are superb.

Benchmarking of density functionals for a soft but accurate prediction and assignment of (1) H and (13)C NMR chemical shifts in organic and biological molecules.

PubMed

Benassi, Enrico

2017-01-15

A number of programs and tools that simulate 1 H and 13 C nuclear magnetic resonance (NMR) chemical shifts using empirical approaches are available. These tools are user-friendly, but they provide a very rough (and sometimes misleading) estimation of the NMR properties, especially for complex systems. Rigorous and reliable ways to predict and interpret NMR properties of simple and complex systems are available in many popular computational program packages. Nevertheless, experimentalists keep relying on these "unreliable" tools in their daily work because, to have a sufficiently high accuracy, these rigorous quantum mechanical methods need high levels of theory. An alternative, efficient, semi-empirical approach has been proposed by Bally, Rablen, Tantillo, and coworkers. This idea consists of creating linear calibrations models, on the basis of the application of different combinations of functionals and basis sets. Following this approach, the predictive capability of a wider range of popular functionals was systematically investigated and tested. The NMR chemical shifts were computed in solvated phase at density functional theory level, using 30 different functionals coupled with three different triple-ζ basis sets. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Solvation effects on chemical shifts by embedded cluster integral equation theory.

PubMed

Frach, Roland; Kast, Stefan M

2014-12-11

The accurate computational prediction of nuclear magnetic resonance (NMR) parameters like chemical shifts represents a challenge if the species studied is immersed in strongly polarizing environments such as water. Common approaches to treating a solvent in the form of, e.g., the polarizable continuum model (PCM) ignore strong directional interactions such as H-bonds to the solvent which can have substantial impact on magnetic shieldings. We here present a computational methodology that accounts for atomic-level solvent effects on NMR parameters by extending the embedded cluster reference interaction site model (EC-RISM) integral equation theory to the prediction of chemical shifts of N-methylacetamide (NMA) in aqueous solution. We examine the influence of various so-called closure approximations of the underlying three-dimensional RISM theory as well as the impact of basis set size and different treatment of electrostatic solute-solvent interactions. We find considerable and systematic improvement over reference PCM and gas phase calculations. A smaller basis set in combination with a simple point charge model already yields good performance which can be further improved by employing exact electrostatic quantum-mechanical solute-solvent interaction energies. A larger basis set benefits more significantly from exact over point charge electrostatics, which can be related to differences of the solvent's charge distribution.

PLS-based quantitative structure-activity relationship for substituted benzamides of clebopride type. Application of experimental design in drug design.

PubMed

Norinder, U; Högberg, T

1992-04-01

The advantageous approach of using an experimentally designed training set as the basis for establishing a quantitative structure-activity relationship with good predictive capability is described. The training set was selected from a fractional factorial design scheme based on a principal component description of physico-chemical parameters of aromatic substituents. The derived model successfully predicts the activities of additional substituted benzamides of 6-methoxy-N-(4-piperidyl)salicylamide type. The major influence on activity of the 3-substituent is demonstrated.

Applicability of effective fragment potential version 2 - Molecular dynamics (EFP2-MD) simulations for predicting excess properties of mixed solvents

NASA Astrophysics Data System (ADS)

Kuroki, Nahoko; Mori, Hirotoshi

2018-02-01

Effective fragment potential version 2 - molecular dynamics (EFP2-MD) simulations, where the EFP2 is a polarizable force field based on ab initio electronic structure calculations were applied to water-methanol binary mixture. Comparing EFP2s defined with (aug-)cc-pVXZ (X = D,T) basis sets, it was found that large sets are necessary to generate sufficiently accurate EFP2 for predicting mixture properties. It was shown that EFP2-MD could predict the excess molar volume. Since the computational cost of EFP2-MD are far less than ab initio MD, the results presented herein demonstrate that EFP2-MD is promising for predicting physicochemical properties of novel mixed solvents.

An unscaled quantum mechanical harmonic force field for p-benzoquinone

NASA Astrophysics Data System (ADS)

Nonella, Marco; Tavan, Paul

1995-10-01

Structure and harmonic vibrational frequencies of p-benzoquinone have been calculated using quantum chemical ab initio and density functional methods. Our calculations show that a satisfactory description of fundamentals and normal mode compositions is achieved upon consideration of correlation effects by means of Møller-Plesset perturbation expansion (MP2) or by density functional theory (DFT). Furthermore, for correct prediction of CO bondlength and force constant, basis sets augmented by polarization functions are required. Applying such basis sets, MP2 and DFT calculations both give results which are generally in reasonable agreement with experimental data. The quantitatively better agreement, however, is achieved with the computationally less demanding DFT method. This method particularly allows very precise prediction of the experimentally important absorptions in the frequency region between 1500 and 1800 cm -1 and of the isotopic shifts of these vibrations due to 13C or 18O substitution.

Planetary Transmission Diagnostics

NASA Technical Reports Server (NTRS)

Lewicki, David G. (Technical Monitor); Samuel, Paul D.; Conroy, Joseph K.; Pines, Darryll J.

2004-01-01

This report presents a methodology for detecting and diagnosing gear faults in the planetary stage of a helicopter transmission. This diagnostic technique is based on the constrained adaptive lifting algorithm. The lifting scheme, developed by Wim Sweldens of Bell Labs, is a time domain, prediction-error realization of the wavelet transform that allows for greater flexibility in the construction of wavelet bases. Classic lifting analyzes a given signal using wavelets derived from a single fundamental basis function. A number of researchers have proposed techniques for adding adaptivity to the lifting scheme, allowing the transform to choose from a set of fundamental bases the basis that best fits the signal. This characteristic is desirable for gear diagnostics as it allows the technique to tailor itself to a specific transmission by selecting a set of wavelets that best represent vibration signals obtained while the gearbox is operating under healthy-state conditions. However, constraints on certain basis characteristics are necessary to enhance the detection of local wave-form changes caused by certain types of gear damage. The proposed methodology analyzes individual tooth-mesh waveforms from a healthy-state gearbox vibration signal that was generated using the vibration separation (synchronous signal-averaging) algorithm. Each waveform is separated into analysis domains using zeros of its slope and curvature. The bases selected in each analysis domain are chosen to minimize the prediction error, and constrained to have the same-sign local slope and curvature as the original signal. The resulting set of bases is used to analyze future-state vibration signals and the lifting prediction error is inspected. The constraints allow the transform to effectively adapt to global amplitude changes, yielding small prediction errors. However, local wave-form changes associated with certain types of gear damage are poorly adapted, causing a significant change in the prediction error. The constrained adaptive lifting diagnostic algorithm is validated using data collected from the University of Maryland Transmission Test Rig and the results are discussed.

Critical taper wedge mechanics of fold-and-thrust belts on Venus - Initial results from Magellan

NASA Technical Reports Server (NTRS)

Suppe, John; Connors, Chris

1992-01-01

Examples of fold-and-thrust belts from a variety of tectonic settings on Venus are introduced. Predictions for the mechanics of fold-and-thrust belts on Venus are examined on the basis of wedge theory, rock mechanics data, and currently known conditions on Venus. The theoretical predictions are then compared with new Magellan data.

Is HO3 minimum cis or trans? An analytic full-dimensional ab initio isomerization path.

PubMed

Varandas, A J C

2011-05-28

The minimum energy path for isomerization of HO(3) has been explored in detail using accurate high-level ab initio methods and techniques for extrapolation to the complete basis set limit. In agreement with other reports, the best estimates from both valence-only and all-electron single-reference methods here utilized predict the minimum of the cis-HO(3) isomer to be deeper than the trans-HO(3) one. They also show that the energy varies by less than 1 kcal mol(-1) or so over the full isomerization path. A similar result is found from valence-only multireference configuration interaction calculations with the size-extensive Davidson correction and a correlation consistent triple-zeta basis, which predict the energy difference between the two isomers to be of only Δ = -0.1 kcal mol(-1). However, single-point multireference calculations carried out at the optimum triple-zeta geometry with basis sets of the correlation consistent family but cardinal numbers up to X = 6 lead upon a dual-level extrapolation to the complete basis set limit of Δ = (0.12 ± 0.05) kcal mol(-1). In turn, extrapolations with the all-electron single-reference coupled-cluster method including the perturbative triples correction yield values of Δ = -0.19 and -0.03 kcal mol(-1) when done from triple-quadruple and quadruple-quintuple zeta pairs with two basis sets of increasing quality, namely cc-cpVXZ and aug-cc-pVXZ. Yet, if added a value of 0.25 kcal mol(-1) that accounts for the effect of triple and perturbative quadruple excitations with the VTZ basis set, one obtains a coupled cluster estimate of Δ = (0.14 ± 0.08) kcal mol(-1). It is then shown for the first time from systematic ab initio calculations that the trans-HO(3) isomer is more stable than the cis one, in agreement with the available experimental evidence. Inclusion of the best reported zero-point energy difference (0.382 kcal mol(-1)) from multireference configuration interaction calculations enhances further the relative stability to ΔE(ZPE) = (0.51 ± 0.08) kcal mol(-1). A scheme is also suggested to model the full-dimensional isomerization potential-energy surface using a quadratic expansion that is parametrically represented by a Fourier analysis in the torsion angle. The method illustrated at the raw and complete basis-set limit coupled-cluster levels can provide a valuable tool for a future analysis of the available (incomplete thus far) experimental rovibrational data. This journal is © the Owner Societies 2011

The dissociation energy of N2

NASA Technical Reports Server (NTRS)

Almloef, Jan; Deleeuw, Bradley J.; Taylor, Peter R.; Bauschlicher, Charles W., Jr.; Siegbahn, Per

1989-01-01

The requirements for very accurate ab initio quantum chemical prediction of dissociation energies are examined using a detailed investigation of the nitrogen molecule. Although agreement with experiment to within 1 kcal/mol is not achieved even with the most elaborate multireference CI (configuration interaction) wave functions and largest basis sets currently feasible, it is possible to obtain agreement to within about 2 kcal/mol, or 1 percent of the dissociation energy. At this level it is necessary to account for core-valence correlation effects and to include up to h-type functions in the basis. The effect of i-type functions, the use of different reference configuration spaces, and basis set superposition error were also investigated. After discussing these results, the remaining sources of error in our best calculations are examined.

Random forest models to predict aqueous solubility.

PubMed

Palmer, David S; O'Boyle, Noel M; Glen, Robert C; Mitchell, John B O

2007-01-01

Random Forest regression (RF), Partial-Least-Squares (PLS) regression, Support Vector Machines (SVM), and Artificial Neural Networks (ANN) were used to develop QSPR models for the prediction of aqueous solubility, based on experimental data for 988 organic molecules. The Random Forest regression model predicted aqueous solubility more accurately than those created by PLS, SVM, and ANN and offered methods for automatic descriptor selection, an assessment of descriptor importance, and an in-parallel measure of predictive ability, all of which serve to recommend its use. The prediction of log molar solubility for an external test set of 330 molecules that are solid at 25 degrees C gave an r2 = 0.89 and RMSE = 0.69 log S units. For a standard data set selected from the literature, the model performed well with respect to other documented methods. Finally, the diversity of the training and test sets are compared to the chemical space occupied by molecules in the MDL drug data report, on the basis of molecular descriptors selected by the regression analysis.

The basis function approach for modeling autocorrelation in ecological data

USGS Publications Warehouse

Hefley, Trevor J.; Broms, Kristin M.; Brost, Brian M.; Buderman, Frances E.; Kay, Shannon L.; Scharf, Henry; Tipton, John; Williams, Perry J.; Hooten, Mevin B.

2017-01-01

Analyzing ecological data often requires modeling the autocorrelation created by spatial and temporal processes. Many seemingly disparate statistical methods used to account for autocorrelation can be expressed as regression models that include basis functions. Basis functions also enable ecologists to modify a wide range of existing ecological models in order to account for autocorrelation, which can improve inference and predictive accuracy. Furthermore, understanding the properties of basis functions is essential for evaluating the fit of spatial or time-series models, detecting a hidden form of collinearity, and analyzing large data sets. We present important concepts and properties related to basis functions and illustrate several tools and techniques ecologists can use when modeling autocorrelation in ecological data.

Conformational stability, structural parameters and vibrational assignment from variable temperature infrared spectra of krypton solutions and ab initio calculations of ethylisothiocyanate.

PubMed

Durig, James R; Zheng, Chao

2007-11-01

Variable temperature (-105 to -150 degrees C) studies of the infrared spectra (3500-400 cm(-1)) of ethylisothiocyanate, CH(3)CH(2)NCS, dissolved in liquid krypton have been recorded. Additionally the infrared spectra of the gas and solid have been re-investigated. These spectroscopic data indicate a single conformer in all physical states with a large number of molecules in the gas phase at ambient temperature in excited states of the CN torsional mode which has a very low barrier to conformational interchange. To aid in the analyses of the vibrational and rotational spectra, ab initio calculations have been carried out by the perturbation method to the second order (MP2) with valence and core electron correlation using a variety of basis sets up to 6-311+G(2df,2pd). With the smaller basis sets up to 6-311+G(d,p) and cc-PVDZ, the cis conformer is indicated as a transition state with all larger basis sets the cis conformer is the only stable form. The predicted energy difference from these calculations between the cis form and the higher energy trans conformer is about 125 cm(-1) which represents essentially the barrier to internal rotation of the NCS group (rotation around NC axis). Density functional theory calculation by the B3LYP method with the same basis sets predicts this barrier to be about 25 cm(-1). By utilizing the previously reported microwave rotational constants with the structural parameters predicted by the ab initio MP2(full)/6-311+G(d,p) calculations, adjusted r(0) structural parameters have been obtained for the cis form. The determined heavy atom parameters are: r(NC)=1.196(5), r(CS)=1.579(5), r(CN)=1.439(5), r(CC)=1.519(5)A for the distances and angles of angleCCN=112.1(5), angleCNC=146.2(5), angleNCS=174.0(5) degrees . The centrifugal distortion constants, dipole moments, conformational stability, vibrational frequencies, infrared intensities and Raman activities have been predicted from ab initio calculations and compared to experimental quantities when available. These results are compared to the corresponding quantities of some similar molecules.

An externally validated model for predicting long-term survival after exercise treadmill testing in patients with suspected coronary artery disease and a normal electrocardiogram.

PubMed

Lauer, Michael S; Pothier, Claire E; Magid, David J; Smith, S Scott; Kattan, Michael W

2007-12-18

The exercise treadmill test is recommended for risk stratification among patients with intermediate to high pretest probability of coronary artery disease. Posttest risk stratification is based on the Duke treadmill score, which includes only functional capacity and measures of ischemia. To develop and externally validate a post-treadmill test, multivariable mortality prediction rule for adults with suspected coronary artery disease and normal electrocardiograms. Prospective cohort study conducted from September 1990 to May 2004. Exercise treadmill laboratories in a major medical center (derivation set) and a separate HMO (validation set). 33,268 patients in the derivation set and 5821 in the validation set. All patients had normal electrocardiograms and were referred for evaluation of suspected coronary artery disease. The derivation set patients were followed for a median of 6.2 years. A nomogram-illustrated model was derived on the basis of variables easily obtained in the stress laboratory, including age; sex; history of smoking, hypertension, diabetes, or typical angina; and exercise findings of functional capacity, ST-segment changes, symptoms, heart rate recovery, and frequent ventricular ectopy in recovery. The derivation data set included 1619 deaths. Although both the Duke treadmill score and our nomogram-illustrated model were significantly associated with death (P < 0.001), the nomogram was better at discrimination (concordance index for right-censored data, 0.83 vs. 0.73) and calibration. We reclassified many patients with intermediate- to high-risk Duke treadmill scores as low risk on the basis of the nomogram. The model also predicted 3-year mortality rates well in the validation set: Based on an optimal cut-point for a negative predictive value of 0.97, derivation and validation rates were, respectively, 1.7% and 2.5% below the cut-point and 25% and 29% above the cut-point. Blood test-based measures or left ventricular ejection fraction were not included. The nomogram can be applied only to patients with a normal electrocardiogram. Clinical utility remains to be tested. A simple nomogram based on easily obtained pretest and exercise test variables predicted all-cause mortality in adults with suspected coronary artery disease and normal electrocardiograms.

Genomic Signal Processing: Predicting Basic Molecular Biological Principles

NASA Astrophysics Data System (ADS)

Alter, Orly

2005-03-01

Advances in high-throughput technologies enable acquisition of different types of molecular biological data, monitoring the flow of biological information as DNA is transcribed to RNA, and RNA is translated to proteins, on a genomic scale. Future discovery in biology and medicine will come from the mathematical modeling of these data, which hold the key to fundamental understanding of life on the molecular level, as well as answers to questions regarding diagnosis, treatment and drug development. Recently we described data-driven models for genome-scale molecular biological data, which use singular value decomposition (SVD) and the comparative generalized SVD (GSVD). Now we describe an integrative data-driven model, which uses pseudoinverse projection (1). We also demonstrate the predictive power of these matrix algebra models (2). The integrative pseudoinverse projection model formulates any number of genome-scale molecular biological data sets in terms of one chosen set of data samples, or of profiles extracted mathematically from data samples, designated the ``basis'' set. The mathematical variables of this integrative model, the pseudoinverse correlation patterns that are uncovered in the data, represent independent processes and corresponding cellular states (such as observed genome-wide effects of known regulators or transcription factors, the biological components of the cellular machinery that generate the genomic signals, and measured samples in which these regulators or transcription factors are over- or underactive). Reconstruction of the data in the basis simulates experimental observation of only the cellular states manifest in the data that correspond to those of the basis. Classification of the data samples according to their reconstruction in the basis, rather than their overall measured profiles, maps the cellular states of the data onto those of the basis, and gives a global picture of the correlations and possibly also causal coordination of these two sets of states. Mapping genome-scale protein binding data using pseudoinverse projection onto patterns of RNA expression data that had been extracted by SVD and GSVD, a novel correlation between DNA replication initiation and RNA transcription during the cell cycle in yeast, that might be due to a previously unknown mechanism of regulation, is predicted. (1) Alter & Golub, Proc. Natl. Acad. Sci. USA 101, 16577 (2004). (2) Alter, Golub, Brown & Botstein, Miami Nat. Biotechnol. Winter Symp. 2004 (www.med.miami.edu/mnbws/alter-.pdf)

Maximum likelihood estimation for predicting the probability of obtaining variable shortleaf pine regeneration densities

Treesearch

Thomas B. Lynch; Jean Nkouka; Michael M. Huebschmann; James M. Guldin

2003-01-01

A logistic equation is the basis for a model that predicts the probability of obtaining regeneration at specified densities. The density of regeneration (trees/ha) for which an estimate of probability is desired can be specified by means of independent variables in the model. When estimating parameters, the dependent variable is set to 1 if the regeneration density (...

The basis function approach for modeling autocorrelation in ecological data.

PubMed

Hefley, Trevor J; Broms, Kristin M; Brost, Brian M; Buderman, Frances E; Kay, Shannon L; Scharf, Henry R; Tipton, John R; Williams, Perry J; Hooten, Mevin B

2017-03-01

Analyzing ecological data often requires modeling the autocorrelation created by spatial and temporal processes. Many seemingly disparate statistical methods used to account for autocorrelation can be expressed as regression models that include basis functions. Basis functions also enable ecologists to modify a wide range of existing ecological models in order to account for autocorrelation, which can improve inference and predictive accuracy. Furthermore, understanding the properties of basis functions is essential for evaluating the fit of spatial or time-series models, detecting a hidden form of collinearity, and analyzing large data sets. We present important concepts and properties related to basis functions and illustrate several tools and techniques ecologists can use when modeling autocorrelation in ecological data. © 2016 by the Ecological Society of America.

Organizational Orientations in an Instructional Setting

ERIC Educational Resources Information Center

Tibbles, David; Richmond, Virginia P.; McCroskey, James C.; Weber, Keith

2008-01-01

Research on organizational orientations has determined that workers can be categorized into three groups on the basis of their trait orientations toward working in organizations: "upward mobiles," "indifferents," and "ambivalents." Because workers' organizational orientation is predictive of their success, we reasoned that students' orientation…

The 3d Rydberg (3A2) electronic state observed by Herzberg and Shoosmith for methylene

NASA Astrophysics Data System (ADS)

Yamaguchi, Yukio; Schaefer, Henry F., III

1997-06-01

In 1959 and 1961 Herzberg and Shoosmith reported the vacuum ultraviolet spectrum of the triplet state of CH2. The present study focuses on a characterization of the upper state, the 3d Rydberg (3A2) state, observed at 1415 Å. The theoretical interpretation of these experiments is greatly complicated by the presence of a lower-lying 3A2 valence state with a very small equilibrium bond angle. Ab initio electronic structure methods involving self-consistent-field (SCF), configuration interaction with single and double excitations (CISD), complete active space (CAS) SCF, state-averaged (SA) CASSCF, coupled cluster with single and double excitations (CCSD), CCSD with perturbative triple excitations [CCSD(T)], CASSCF second-order (SO) CI, and SACASSCF-SOCI have been employed with six distinct basis sets. With the largest basis set, triple zeta plus triple polarization with two sets of higher angular momentum functions and three sets of diffuse functions TZ3P(2 f,2d)+3diff, the CISD level of theory predicts the equilibrium geometry of the 3d Rydberg (3A2) state to be re=1.093 Å and θe=141.3 deg. With the same basis set the energy (Te value) of the 3d Rydberg state relative to the ground (X˜ 3B1) state has been determined to be 201.6 kcal mol-1 (70 500 cm-1) at the CCSD (T) level, 200.92kcal mol-1 (70 270 cm-1) at the CASSCF-SOCI level, and 200.89kcal mol-1 (70 260 cm-1) at the SACASSCF-SOCI level of theory. These predictions are in excellent agreement with the experimental T0 value of 201.95 kcalmol-1 (70 634 cm-1) reported by Herzberg.

Free variable selection QSPR study to predict 19F chemical shifts of some fluorinated organic compounds using Random Forest and RBF-PLS methods

NASA Astrophysics Data System (ADS)

Goudarzi, Nasser

2016-04-01

In this work, two new and powerful chemometrics methods are applied for the modeling and prediction of the 19F chemical shift values of some fluorinated organic compounds. The radial basis function-partial least square (RBF-PLS) and random forest (RF) are employed to construct the models to predict the 19F chemical shifts. In this study, we didn't used from any variable selection method and RF method can be used as variable selection and modeling technique. Effects of the important parameters affecting the ability of the RF prediction power such as the number of trees (nt) and the number of randomly selected variables to split each node (m) were investigated. The root-mean-square errors of prediction (RMSEP) for the training set and the prediction set for the RBF-PLS and RF models were 44.70, 23.86, 29.77, and 23.69, respectively. Also, the correlation coefficients of the prediction set for the RBF-PLS and RF models were 0.8684 and 0.9313, respectively. The results obtained reveal that the RF model can be used as a powerful chemometrics tool for the quantitative structure-property relationship (QSPR) studies.

Application of ab initio many-body perturbation theory with Gaussian basis sets to the singlet and triplet excitations of organic molecules

NASA Astrophysics Data System (ADS)

Hamed, Samia; Rangel, Tonatiuh; Bruneval, Fabien; Neaton, Jeffrey B.

Quantitative understanding of charged and neutral excitations of organic molecules is critical in diverse areas of study that include astrophysics and the development of energy technologies that are clean and efficient. The recent use of local basis sets with ab initio many-body perturbation theory in the GW approximation and the Bethe-Saltpeter equation approach (BSE), methods traditionally applied to periodic condensed phases with a plane-wave basis, has opened the door to detailed study of such excitations for molecules, as well as accurate numerical benchmarks. Here, through a series of systematic benchmarks with a Gaussian basis, we report on the extent to which the predictive power and utility of this approach depend critically on interdependent underlying approximations and choices for molecules, including the mean-field starting point (eg optimally-tuned range separated hybrids, pure DFT functionals, and untuned hybrids), the GW scheme, and the Tamm Dancoff approximation. We demonstrate the effects of these choices in the context of Thiels' set while drawing analogies to linear-response time-dependent DFT and making comparisons to best theoretical estimates from higher-order wavefunction-based theories.

Systematization, condensed description, and prediction of sets of anion exchange extraction constants on the basis of their statistical treatment by computer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mezhov, E.A.; Reimarov, G.A.; Rubisov, V.N.

1987-05-01

On the basis of a statistical treatment of the entire set of published data on anion exchange extraction constants, the authors have refined and expanded the scale of the hydration parameters for the anions ..delta..G/sub hydr/ (the effective free energies of hydration for the anions). The authors have estimated the parameters ..delta..G for 93 anions and the coefficients % for 94 series of extraction systems, which are distinguished within each series only by the nature of the exchanging anions. The series are distinguished from one another by the nature of the cation extraction agent and the diluent.

Resolution of Probabilistic Weather Forecasts with Application in Disease Management.

PubMed

Hughes, G; McRoberts, N; Burnett, F J

2017-02-01

Predictive systems in disease management often incorporate weather data among the disease risk factors, and sometimes this comes in the form of forecast weather data rather than observed weather data. In such cases, it is useful to have an evaluation of the operational weather forecast, in addition to the evaluation of the disease forecasts provided by the predictive system. Typically, weather forecasts and disease forecasts are evaluated using different methodologies. However, the information theoretic quantity expected mutual information provides a basis for evaluating both kinds of forecast. Expected mutual information is an appropriate metric for the average performance of a predictive system over a set of forecasts. Both relative entropy (a divergence, measuring information gain) and specific information (an entropy difference, measuring change in uncertainty) provide a basis for the assessment of individual forecasts.

Use of Biodescriptors and Chemodescriptors in Predictive Toxicology: A Mathematical/Computational Approach

DTIC Science & Technology

2005-01-01

proteomic gel analyses. The research group has explored the use of chemodescriptors calculated using high-level ab initio quantum chemical basis sets...descriptors that characterize the entire proteomics map, local descriptors that characterize a subset of the proteins present in the gel, and spectrum...techniques for analyzing the full set of proteins present in a proteomics map. 14. SUBJECT TERMS 1S. NUMBER OF PAGES Topological indices

Stated choice for transportation demand management models : using a disaggregate truth set to study predictive validity

DOT National Transportation Integrated Search

1997-01-01

Discrete choice models have expanded the ability of transportation planners to forecast future trends. Where new services or policies are proposed, the stated-choice approach can provide an objective basis for forecasts. Stated-choice models are subj...

Scaled Quantum Mechanical scale factors for vibrational calculations using alternate polarized and augmented basis sets with the B3LYP density functional calculation model

NASA Astrophysics Data System (ADS)

Legler, C. R.; Brown, N. R.; Dunbar, R. A.; Harness, M. D.; Nguyen, K.; Oyewole, O.; Collier, W. B.

2015-06-01

The Scaled Quantum Mechanical (SQM) method of scaling calculated force constants to predict theoretically calculated vibrational frequencies is expanded to include a broad array of polarized and augmented basis sets based on the split valence 6-31G and 6-311G basis sets with the B3LYP density functional. Pulay's original choice of a single polarized 6-31G(d) basis coupled with a B3LYP functional remains the most computationally economical choice for scaled frequency calculations. But it can be improved upon with additional polarization functions and added diffuse functions for complex molecular systems. The new scale factors for the B3LYP density functional and the 6-31G, 6-31G(d), 6-31G(d,p), 6-31G+(d,p), 6-31G++(d,p), 6-311G, 6-311G(d), 6-311G(d,p), 6-311G+(d,p), 6-311G++(d,p), 6-311G(2d,p), 6-311G++(2d,p), 6-311G++(df,p) basis sets are shown. The double d polarized models did not perform as well and the source of the decreased accuracy was investigated. An alternate system of generating internal coordinates that uses the out-of plane wagging coordinate whenever it is possible; makes vibrational assignments via potential energy distributions more meaningful. Automated software to produce SQM scaled vibrational calculations from different molecular orbital packages is presented.

[Study on the detection of active ingredient contents of Paecilomyces hepiali mycelium via near infrared spectroscopy].

PubMed

Teng, Wei-Zhuo; Song, Jia; Meng, Fan-Xin; Meng, Qing-Fan; Lu, Jia-Hui; Hu, Shuang; Teng, Li-Rong; Wang, Di; Xie, Jing

2014-10-01

Partial least squares (PLS) and radial basis function neural network (RBFNN) combined with near infrared spectros- copy (NIR) were applied to develop models for cordycepic acid, polysaccharide and adenosine analysis in Paecilomyces hepialid fermentation mycelium. The developed models possess well generalization and predictive ability which can be applied for crude drugs and related productions determination. During the experiment, 214 Paecilomyces hepialid mycelium samples were obtained via chemical mutagenesis combined with submerged fermentation. The contents of cordycepic acid, polysaccharide and adenosine were determined via traditional methods and the near infrared spectroscopy data were collected. The outliers were removed and the numbers of calibration set were confirmed via Monte Carlo partial least square (MCPLS) method. Based on the values of degree of approach (Da), both moving window partial least squares (MWPLS) and moving window radial basis function neural network (MWRBFNN) were applied to optimize characteristic wavelength variables, optimum preprocessing methods and other important variables in the models. After comparison, the RBFNN, RBFNN and PLS models were developed successfully for cordycepic acid, polysaccharide and adenosine detection, and the correlation between reference values and predictive values in both calibration set (R2c) and validation set (R2p) of optimum models was 0.9417 and 0.9663, 0.9803 and 0.9850, and 0.9761 and 0.9728, respectively. All the data suggest that these models possess well fitness and predictive ability.

Spectroscopic properties of Arx-Zn and Arx-Ag+ (x = 1,2) van der Waals complexes

NASA Astrophysics Data System (ADS)

Oyedepo, Gbenga A.; Peterson, Charles; Schoendorff, George; Wilson, Angela K.

2013-03-01

Potential energy curves have been constructed using coupled cluster with singles, doubles, and perturbative triple excitations (CCSD(T)) in combination with all-electron and pseudopotential-based multiply augmented correlation consistent basis sets [m-aug-cc-pV(n + d)Z; m = singly, doubly, triply, n = D,T,Q,5]. The effect of basis set superposition error on the spectroscopic properties of Ar-Zn, Ar2-Zn, Ar-Ag+, and Ar2-Ag+ van der Waals complexes was examined. The diffuse functions of the doubly and triply augmented basis sets have been constructed using the even-tempered expansion. The a posteriori counterpoise scheme of Boys and Bernardi and its generalized variant by Valiron and Mayer has been utilized to correct for basis set superposition error (BSSE) in the calculated spectroscopic properties for diatomic and triatomic species. It is found that even at the extrapolated complete basis set limit for the energetic properties, the pseudopotential-based calculations still suffer from significant BSSE effects unlike the all-electron basis sets. This indicates that the quality of the approximations used in the design of pseudopotentials could have major impact on a seemingly valence-exclusive effect like BSSE. We confirm the experimentally determined equilibrium internuclear distance (re), binding energy (De), harmonic vibrational frequency (ωe), and C1Π ← X1Σ transition energy for ArZn and also predict the spectroscopic properties for the low-lying excited states of linear Ar2-Zn (X1Σg, 3Πg, 1Πg), Ar-Ag+ (X1Σ, 3Σ, 3Π, 3Δ, 1Σ, 1Π, 1Δ), and Ar2-Ag+ (X1Σg, 3Σg, 3Πg, 3Δg, 1Σg, 1Πg, 1Δg) complexes, using the CCSD(T) and MR-CISD + Q methods, to aid in their experimental characterizations.

Locomotion With Loads: Practical Techniques for Predicting Performance Outcomes

DTIC Science & Technology

2015-05-01

running velocities by 13 and 18% for all-out 80- and 400 - meter runs. More recently, Alcaraz et al. (2008) reported only 3% reductions in brief, all... sprint running speeds to be predicted to within 6.0% in both laboratory and field settings. Respective load-carriage algorithms for walking energy...Objective Two: Sprint Running Speed Previous Scientific Efforts: The scientific literature on the basis of brief, all-out running performance is

Locomotion with Loads: Practical Techniques for Predicting Performance Outcomes

DTIC Science & Technology

2014-05-01

out running velocities by 13 and 18% for all-out 80- and 400 - meter runs. More recently, Alcaraz et al. (2008) reported only 3% reductions in brief...induced decrements in all-out sprint running speeds to be predicted to within 6.0% in both laboratory and field settings. Respective load-carriage...model. Objective Two: Sprint Running Speed Previous Scientific Efforts: The scientific literature on the basis of brief, all-out running

Prediction of the space adaptation syndrome

NASA Technical Reports Server (NTRS)

Reschke, M. F.; Homick, J. L.; Ryan, P.; Moseley, E. C.

1984-01-01

The univariate and multivariate relationships of provocative measures used to produce motion sickness symptoms were described. Normative subjects were used to develop and cross-validate sets of linear equations that optimally predict motion sickness in parabolic flights. The possibility of reducing the number of measurements required for prediction was assessed. After describing the variables verbally and statistically for 159 subjects, a factor analysis of 27 variables was completed to improve understanding of the relationships between variables and to reduce the number of measures for prediction purposes. The results of this analysis show that none of variables are significantly related to the responses to parabolic flights. A set of variables was selected to predict responses to KC-135 flights. A series of discriminant analyses were completed. Results indicate that low, moderate, or severe susceptibility could be correctly predicted 64 percent and 53 percent of the time on original and cross-validation samples, respectively. Both the factor analysis and the discriminant analysis provided no basis for reducing the number of tests.

On the structure and spin states of Fe(III)-EDDHA complexes.

PubMed

Gómez-Gallego, Mar; Fernández, Israel; Pellico, Daniel; Gutiérrez, Angel; Sierra, Miguel A; Lucena, Juan J

2006-07-10

DFT methods are suitable for predicting both the geometries and spin states of EDDHA-Fe(III) complexes. Thus, extensive DFT computational studies have shown that the racemic-Fe(III) EDDHA complex is more stable than the meso isomer, regardless of the spin state of the central iron atom. A comparison of the energy values obtained for the complexes under study has also shown that high-spin (S = 5/2) complexes are more stable than low-spin (S = 1/2) ones. These computational results matched the experimental results of the magnetic susceptibility values of both isomers. In both cases, their behavior has been fitted as being due to isolated high-spin Fe(III) in a distorted octahedral environment. The study of the correlation diagram also confirms the high-spin iron in complex 2b. The geometry optimization of these complexes performed with the standard 3-21G* basis set for hydrogen, carbon, oxygen, and nitrogen and the Hay-Wadt small-core effective core potential (ECP) including a double-xi valence basis set for iron, followed by single-point energy refinement with the 6-31G* basis set, is suitable for predicting both the geometries and the spin-states of EDDHA-Fe(III) complexes. The presence of a high-spin iron in Fe(III)-EDDHA complexes could be the key to understanding their lack of reactivity in electron-transfer processes, either chemically or electrochemically induced, and their resistance to photodegradation.

Vibrational spectra, DFT quantum chemical calculations and conformational analysis of P-iodoanisole.

PubMed

Arivazhagan, M; Anitha Rexalin, D; Geethapriya, J

2013-09-01

The solid phase FT-IR and FT-Raman spectra of P-iodoanisole (P-IA) have been recorded in the regions 400-4000 and 50-4000 cm(-1), respectively. The spectra were interpreted in terms of fundamentals modes, combination and overtone bands. The structure of the molecule was optimized and the structural characteristics were determined by ab initio (HF) and density functional theory (B3LYP) methods with LanL2DZ as basis set. The potential energy surface scan for the selected dihedral angle of P-IA has been performed to identify stable conformer. The optimized structure parameters and vibrational wavenumbers of stable conformer have been predicted by density functional B3LYP method with LanL2DZ (with effective core potential representations of electrons near the nuclei for post-third row atoms) basis set. The nucleophilic and electrophilic sites obtained from the molecular electrostatic potential (MEP) surface were calculated. The temperature dependence of thermodynamic properties has been analyzed. Several thermodynamic parameters have been calculated using B3LYP with LanL2DZ basis set. Copyright © 2013 Elsevier B.V. All rights reserved.

Adsorption of Emerging Munitions Contaminants on Cellulose Surface: A Combined Theoretical and Experimental Investigation.

PubMed

Shukla, Manoj K; Poda, Aimee

2016-06-01

This manuscript reports results of an integrated theoretical and experimental investigation of adsorption of two emerging contaminants (DNAN and FOX-7) and legacy compound TNT on cellulose surface. Cellulose was modeled as trimeric form of the linear chain of 1 → 4 linked of β-D-glucopyranos in (4)C1 chair conformation. Geometries of modeled cellulose, munitions compounds and their complexes were optimized at the M06-2X functional level of Density Functional Theory using the 6-31G(d,p) basis set in gas phase and in water solution. The effect of water solution was modeled using the CPCM approach. Nature of potential energy surfaces was ascertained through harmonic vibrational frequency analysis. Interaction energies were corrected for basis set superposition error and the 6-311G(d,p) basis set was used. Molecular electrostatic potential mapping was performed to understand the reactivity of the investigated systems. It was predicted that adsorbates will be weakly adsorbed on the cellulose surface in water solution than in the gas phase.

Gaussian functional regression for output prediction: Model assimilation and experimental design

NASA Astrophysics Data System (ADS)

Nguyen, N. C.; Peraire, J.

2016-03-01

In this paper, we introduce a Gaussian functional regression (GFR) technique that integrates multi-fidelity models with model reduction to efficiently predict the input-output relationship of a high-fidelity model. The GFR method combines the high-fidelity model with a low-fidelity model to provide an estimate of the output of the high-fidelity model in the form of a posterior distribution that can characterize uncertainty in the prediction. A reduced basis approximation is constructed upon the low-fidelity model and incorporated into the GFR method to yield an inexpensive posterior distribution of the output estimate. As this posterior distribution depends crucially on a set of training inputs at which the high-fidelity models are simulated, we develop a greedy sampling algorithm to select the training inputs. Our approach results in an output prediction model that inherits the fidelity of the high-fidelity model and has the computational complexity of the reduced basis approximation. Numerical results are presented to demonstrate the proposed approach.

PREDICTING THE IMPACT OF TROPOSPHERIC OZONE ON PLANTS AND ECOSYSTEMS AS A BASIS FOR SETTING NATIONAL AIR QUALITY STANDARDS

EPA Science Inventory

The Clean Air Act provides for establishing National Ambient Air Quality Standards (NAAQS) to protect public welfare (including crops, forests, ecosystems, and soils) from adverse effects of air pollutants, including tropospheric ozone. The formulation of policies is science-base...

Combining Gene Signatures Improves Prediction of Breast Cancer Survival

PubMed Central

Zhao, Xi; Naume, Bjørn; Langerød, Anita; Frigessi, Arnoldo; Kristensen, Vessela N.; Børresen-Dale, Anne-Lise; Lingjærde, Ole Christian

2011-01-01

Background Several gene sets for prediction of breast cancer survival have been derived from whole-genome mRNA expression profiles. Here, we develop a statistical framework to explore whether combination of the information from such sets may improve prediction of recurrence and breast cancer specific death in early-stage breast cancers. Microarray data from two clinically similar cohorts of breast cancer patients are used as training (n = 123) and test set (n = 81), respectively. Gene sets from eleven previously published gene signatures are included in the study. Principal Findings To investigate the relationship between breast cancer survival and gene expression on a particular gene set, a Cox proportional hazards model is applied using partial likelihood regression with an L2 penalty to avoid overfitting and using cross-validation to determine the penalty weight. The fitted models are applied to an independent test set to obtain a predicted risk for each individual and each gene set. Hierarchical clustering of the test individuals on the basis of the vector of predicted risks results in two clusters with distinct clinical characteristics in terms of the distribution of molecular subtypes, ER, PR status, TP53 mutation status and histological grade category, and associated with significantly different survival probabilities (recurrence: p = 0.005; breast cancer death: p = 0.014). Finally, principal components analysis of the gene signatures is used to derive combined predictors used to fit a new Cox model. This model classifies test individuals into two risk groups with distinct survival characteristics (recurrence: p = 0.003; breast cancer death: p = 0.001). The latter classifier outperforms all the individual gene signatures, as well as Cox models based on traditional clinical parameters and the Adjuvant! Online for survival prediction. Conclusion Combining the predictive strength of multiple gene signatures improves prediction of breast cancer survival. The presented methodology is broadly applicable to breast cancer risk assessment using any new identified gene set. PMID:21423775

Synthesized airfoil data method for prediction of dynamic stall and unsteady airloads

NASA Technical Reports Server (NTRS)

Gangwani, S. T.

1983-01-01

A detailed analysis of dynamic stall experiments has led to a set of relatively compact analytical expressions, called synthesized unsteady airfoil data, which accurately describe in the time-domain the unsteady aerodynamic characteristics of stalled airfoils. An analytical research program was conducted to expand and improve this synthesized unsteady airfoil data method using additional available sets of unsteady airfoil data. The primary objectives were to reduce these data to synthesized form for use in rotor airload prediction analyses and to generalize the results. Unsteady drag data were synthesized which provided the basis for successful expansion of the formulation to include computation of the unsteady pressure drag of airfoils and rotor blades. Also, an improved prediction model for airfoil flow reattachment was incorporated in the method. Application of this improved unsteady aerodynamics model has resulted in an improved correlation between analytic predictions and measured full scale helicopter blade loads and stress data.

Development of a deep convolutional neural network to predict grading of canine meningiomas from magnetic resonance images.

PubMed

Banzato, T; Cherubini, G B; Atzori, M; Zotti, A

2018-05-01

An established deep neural network (DNN) based on transfer learning and a newly designed DNN were tested to predict the grade of meningiomas from magnetic resonance (MR) images in dogs and to determine the accuracy of classification of using pre- and post-contrast T1-weighted (T1W), and T2-weighted (T2W) MR images. The images were randomly assigned to a training set, a validation set and a test set, comprising 60%, 10% and 30% of images, respectively. The combination of DNN and MR sequence displaying the highest discriminating accuracy was used to develop an image classifier to predict the grading of new cases. The algorithm based on transfer learning using the established DNN did not provide satisfactory results, whereas the newly designed DNN had high classification accuracy. On the basis of classification accuracy, an image classifier built on the newly designed DNN using post-contrast T1W images was developed. This image classifier correctly predicted the grading of 8 out of 10 images not included in the data set. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu Kun; Zhao Hongmei; Wang Caixia

Bromoiodomethane photodissociation in the low-lying excited states has been characterized using unrestricted Hartree-Fock, configuration-interaction-singles, and complete active space self-consistent field calculations with the SDB-aug-cc-pVTZ, aug-cc-pVTZ, and 3-21g** basis sets. According to the results of the vertical excited energies and oscillator strengths of these low-lying excited states, bond selectivity is predicted. Subsequently, the minimum energy paths of the first excited singlet state and the third excited state for the dissociation reactions were calculated using the complete active space self-consistent field method with 3-21g** basis set. Good agreement is found between the calculations and experimental data. The relationships of excitations, the electronicmore » structures at Franck-Condon points, and bond selectivity are discussed.« less

Prediction of dissolved oxygen in the Mediterranean Sea along Gaza, Palestine - an artificial neural network approach.

PubMed

Zaqoot, Hossam Adel; Ansari, Abdul Khalique; Unar, Mukhtiar Ali; Khan, Shaukat Hyat

2009-01-01

Artificial Neural Networks (ANNs) are flexible tools which are being used increasingly to predict and forecast water resources variables. The human activities in areas surrounding enclosed and semi-enclosed seas such as the Mediterranean Sea always produce in the long term a strong environmental impact in the form of coastal and marine degradation. The presence of dissolved oxygen is essential for the survival of most organisms in the water bodies. This paper is concerned with the use of ANNs - Multilayer Perceptron (MLP) and Radial Basis Function neural networks for predicting the next fortnight's dissolved oxygen concentrations in the Mediterranean Sea water along Gaza. MLP and Radial Basis Function (RBF) neural networks are trained and developed with reference to five important oceanographic variables including water temperature, wind velocity, turbidity, pH and conductivity. These variables are considered as inputs of the network. The data sets used in this study consist of four years and collected from nine locations along Gaza coast. The network performance has been tested with different data sets and the results show satisfactory performance. Prediction results prove that neural network approach has good adaptability and extensive applicability for modelling the dissolved oxygen in the Mediterranean Sea along Gaza. We hope that the established model will help in assisting the local authorities in developing plans and policies to reduce the pollution along Gaza coastal waters to acceptable levels.

Clinical pharmacology of analgesics assessed with human experimental pain models: bridging basic and clinical research

PubMed Central

Oertel, Bruno Georg; Lötsch, Jörn

2013-01-01

The medical impact of pain is such that much effort is being applied to develop novel analgesic drugs directed towards new targets and to investigate the analgesic efficacy of known drugs. Ongoing research requires cost-saving tools to translate basic science knowledge into clinically effective analgesic compounds. In this review we have re-examined the prediction of clinical analgesia by human experimental pain models as a basis for model selection in phase I studies. The overall prediction of analgesic efficacy or failure of a drug correlated well between experimental and clinical settings. However, correct model selection requires more detailed information about which model predicts a particular clinical pain condition. We hypothesized that if an analgesic drug was effective in an experimental pain model and also a specific clinical pain condition, then that model might be predictive for that particular condition and should be selected for development as an analgesic for that condition. The validity of the prediction increases with an increase in the numbers of analgesic drug classes for which this agreement was shown. From available evidence, only five clinical pain conditions were correctly predicted by seven different pain models for at least three different drugs. Most of these models combine a sensitization method. The analysis also identified several models with low impact with respect to their clinical translation. Thus, the presently identified agreements and non-agreements between analgesic effects on experimental and on clinical pain may serve as a solid basis to identify complex sets of human pain models that bridge basic science with clinical pain research. PMID:23082949

Benchmarking the GW Approximation and Bethe–Salpeter Equation for Groups IB and IIB Atoms and Monoxides

DOE PAGES

Hung, Linda; Bruneval, Fabien; Baishya, Kopinjol; ...

2017-04-07

Energies from the GW approximation and the Bethe–Salpeter equation (BSE) are benchmarked against the excitation energies of transition-metal (Cu, Zn, Ag, and Cd) single atoms and monoxide anions. We demonstrate that best estimates of GW quasiparticle energies at the complete basis set limit should be obtained via extrapolation or closure relations, while numerically converged GW-BSE eigenvalues can be obtained on a finite basis set. Calculations using real-space wave functions and pseudopotentials are shown to give best-estimate GW energies that agree (up to the extrapolation error) with calculations using all-electron Gaussian basis sets. We benchmark the effects of a vertex approximationmore » (ΓLDA) and the mean-field starting point in GW and the BSE, performing computations using a real-space, transition-space basis and scalar-relativistic pseudopotentials. Here, while no variant of GW improves on perturbative G0W0 at predicting ionization energies, G0W0Γ LDA-BSE computations give excellent agreement with experimental absorption spectra as long as off-diagonal self-energy terms are included. We also present G0W0 quasiparticle energies for the CuO –, ZnO –, AgO –, and CdO – anions, in comparison to available anion photoelectron spectra.« less

Benchmarking the GW Approximation and Bethe–Salpeter Equation for Groups IB and IIB Atoms and Monoxides

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hung, Linda; Bruneval, Fabien; Baishya, Kopinjol

Energies from the GW approximation and the Bethe–Salpeter equation (BSE) are benchmarked against the excitation energies of transition-metal (Cu, Zn, Ag, and Cd) single atoms and monoxide anions. We demonstrate that best estimates of GW quasiparticle energies at the complete basis set limit should be obtained via extrapolation or closure relations, while numerically converged GW-BSE eigenvalues can be obtained on a finite basis set. Calculations using real-space wave functions and pseudopotentials are shown to give best-estimate GW energies that agree (up to the extrapolation error) with calculations using all-electron Gaussian basis sets. We benchmark the effects of a vertex approximationmore » (ΓLDA) and the mean-field starting point in GW and the BSE, performing computations using a real-space, transition-space basis and scalar-relativistic pseudopotentials. Here, while no variant of GW improves on perturbative G0W0 at predicting ionization energies, G0W0Γ LDA-BSE computations give excellent agreement with experimental absorption spectra as long as off-diagonal self-energy terms are included. We also present G0W0 quasiparticle energies for the CuO –, ZnO –, AgO –, and CdO – anions, in comparison to available anion photoelectron spectra.« less

Performance of genomic prediction within and across generations in maritime pine.

PubMed

Bartholomé, Jérôme; Van Heerwaarden, Joost; Isik, Fikret; Boury, Christophe; Vidal, Marjorie; Plomion, Christophe; Bouffier, Laurent

2016-08-11

Genomic selection (GS) is a promising approach for decreasing breeding cycle length in forest trees. Assessment of progeny performance and of the prediction accuracy of GS models over generations is therefore a key issue. A reference population of maritime pine (Pinus pinaster) with an estimated effective inbreeding population size (status number) of 25 was first selected with simulated data. This reference population (n = 818) covered three generations (G0, G1 and G2) and was genotyped with 4436 single-nucleotide polymorphism (SNP) markers. We evaluated the effects on prediction accuracy of both the relatedness between the calibration and validation sets and validation on the basis of progeny performance. Pedigree-based (best linear unbiased prediction, ABLUP) and marker-based (genomic BLUP and Bayesian LASSO) models were used to predict breeding values for three different traits: circumference, height and stem straightness. On average, the ABLUP model outperformed genomic prediction models, with a maximum difference in prediction accuracies of 0.12, depending on the trait and the validation method. A mean difference in prediction accuracy of 0.17 was found between validation methods differing in terms of relatedness. Including the progenitors in the calibration set reduced this difference in prediction accuracy to 0.03. When only genotypes from the G0 and G1 generations were used in the calibration set and genotypes from G2 were used in the validation set (progeny validation), prediction accuracies ranged from 0.70 to 0.85. This study suggests that the training of prediction models on parental populations can predict the genetic merit of the progeny with high accuracy: an encouraging result for the implementation of GS in the maritime pine breeding program.

Multipolar Electrostatic Energy Prediction for all 20 Natural Amino Acids Using Kriging Machine Learning.

PubMed

Fletcher, Timothy L; Popelier, Paul L A

2016-06-14

A machine learning method called kriging is applied to the set of all 20 naturally occurring amino acids. Kriging models are built that predict electrostatic multipole moments for all topological atoms in any amino acid based on molecular geometry only. These models then predict molecular electrostatic interaction energies. On the basis of 200 unseen test geometries for each amino acid, no amino acid shows a mean prediction error above 5.3 kJ mol(-1), while the lowest error observed is 2.8 kJ mol(-1). The mean error across the entire set is only 4.2 kJ mol(-1) (or 1 kcal mol(-1)). Charged systems are created by protonating or deprotonating selected amino acids, and these show no significant deviation in prediction error over their neutral counterparts. Similarly, the proposed methodology can also handle amino acids with aromatic side chains, without the need for modification. Thus, we present a generic method capable of accurately capturing multipolar polarizable electrostatics in amino acids.

A new model for the calculation and prediction of solar proton fluences

NASA Technical Reports Server (NTRS)

Feynman, Joan; Gabriel, Stephen B.

1990-01-01

A new predictive engineering model for the energy greater than 10 MeV and greater than 30 MeV solar proton environment at earth is reviewed. The data used are from observations made from 1956 through 1985. In this data set, the distinction between 'ordinary events' and 'anomalously large events' that was required in earlier models disappeared. This permitted the use of statistical analysis methods developed for ordinary events on the entire data set. The greater than 10-MeV fluences with the new model are about twice those expected on the basis of earlier models. At energies greater than 30 MeV, the old and new models agree.

Genetic algorithm based adaptive neural network ensemble and its application in predicting carbon flux

USGS Publications Warehouse

Xue, Y.; Liu, S.; Hu, Y.; Yang, J.; Chen, Q.

2007-01-01

To improve the accuracy in prediction, Genetic Algorithm based Adaptive Neural Network Ensemble (GA-ANNE) is presented. Intersections are allowed between different training sets based on the fuzzy clustering analysis, which ensures the diversity as well as the accuracy of individual Neural Networks (NNs). Moreover, to improve the accuracy of the adaptive weights of individual NNs, GA is used to optimize the cluster centers. Empirical results in predicting carbon flux of Duke Forest reveal that GA-ANNE can predict the carbon flux more accurately than Radial Basis Function Neural Network (RBFNN), Bagging NN ensemble, and ANNE. ?? 2007 IEEE.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jibben, Zechariah Joel; Herrmann, Marcus

Here, we present a Runge-Kutta discontinuous Galerkin method for solving conservative reinitialization in the context of the conservative level set method. This represents an extension of the method recently proposed by Owkes and Desjardins [21], by solving the level set equations on the refined level set grid and projecting all spatially-dependent variables into the full basis used by the discontinuous Galerkin discretization. By doing so, we achieve the full k+1 order convergence rate in the L1 norm of the level set field predicted for RKDG methods given kth degree basis functions when the level set profile thickness is held constantmore » with grid refinement. Shape and volume errors for the 0.5-contour of the level set, on the other hand, are found to converge between first and second order. We show a variety of test results, including the method of manufactured solutions, reinitialization of a circle and sphere, Zalesak's disk, and deforming columns and spheres, all showing substantial improvements over the high-order finite difference traditional level set method studied for example by Herrmann. We also demonstrate the need for kth order accurate normal vectors, as lower order normals are found to degrade the convergence rate of the method.« less

Estimation of Δ R/ R values by benchmark study of the Mössbauer Isomer shifts for Ru, Os complexes using relativistic DFT calculations

NASA Astrophysics Data System (ADS)

Kaneko, Masashi; Yasuhara, Hiroki; Miyashita, Sunao; Nakashima, Satoru

2017-11-01

The present study applies all-electron relativistic DFT calculation with Douglas-Kroll-Hess (DKH) Hamiltonian to each ten sets of Ru and Os compounds. We perform the benchmark investigation of three density functionals (BP86, B3LYP and B2PLYP) using segmented all-electron relativistically contracted (SARC) basis set with the experimental Mössbauer isomer shifts for 99Ru and 189Os nuclides. Geometry optimizations at BP86 theory of level locate the structure in a local minimum. We calculate the contact density to the wavefunction obtained by a single point calculation. All functionals show the good linear correlation with experimental isomer shifts for both 99Ru and 189Os. Especially, B3LYP functional gives a stronger correlation compared to BP86 and B2PLYP functionals. The comparison of contact density between SARC and well-tempered basis set (WTBS) indicated that the numerical convergence of contact density cannot be obtained, but the reproducibility is less sensitive to the choice of basis set. We also estimate the values of Δ R/ R, which is an important nuclear constant, for 99Ru and 189Os nuclides by using the benchmark results. The sign of the calculated Δ R/ R values is consistent with the predicted data for 99Ru and 189Os. We obtain computationally the Δ R/ R values of 99Ru and 189Os (36.2 keV) as 2.35×10-4 and -0.20×10-4, respectively, at B3LYP level for SARC basis set.

Effectiveness of genomic prediction of maize hybrid performance in different breeding populations and environments.

PubMed

Windhausen, Vanessa S; Atlin, Gary N; Hickey, John M; Crossa, Jose; Jannink, Jean-Luc; Sorrells, Mark E; Raman, Babu; Cairns, Jill E; Tarekegne, Amsal; Semagn, Kassa; Beyene, Yoseph; Grudloyma, Pichet; Technow, Frank; Riedelsheimer, Christian; Melchinger, Albrecht E

2012-11-01

Genomic prediction is expected to considerably increase genetic gains by increasing selection intensity and accelerating the breeding cycle. In this study, marker effects estimated in 255 diverse maize (Zea mays L.) hybrids were used to predict grain yield, anthesis date, and anthesis-silking interval within the diversity panel and testcross progenies of 30 F(2)-derived lines from each of five populations. Although up to 25% of the genetic variance could be explained by cross validation within the diversity panel, the prediction of testcross performance of F(2)-derived lines using marker effects estimated in the diversity panel was on average zero. Hybrids in the diversity panel could be grouped into eight breeding populations differing in mean performance. When performance was predicted separately for each breeding population on the basis of marker effects estimated in the other populations, predictive ability was low (i.e., 0.12 for grain yield). These results suggest that prediction resulted mostly from differences in mean performance of the breeding populations and less from the relationship between the training and validation sets or linkage disequilibrium with causal variants underlying the predicted traits. Potential uses for genomic prediction in maize hybrid breeding are discussed emphasizing the need of (1) a clear definition of the breeding scenario in which genomic prediction should be applied (i.e., prediction among or within populations), (2) a detailed analysis of the population structure before performing cross validation, and (3) larger training sets with strong genetic relationship to the validation set.

Vibrational spectroscopic study of fluticasone propionate

NASA Astrophysics Data System (ADS)

Ali, H. R. H.; Edwards, H. G. M.; Kendrick, J.; Scowen, I. J.

2009-03-01

Fluticasone propionate is a synthetic glucocorticoid with potent anti-inflammatory activity that has been used effectively in the treatment of chronic asthma. The present work reports a vibrational spectroscopic study of fluticasone propionate and gives proposed molecular assignments on the basis of ab initio calculations using BLYP density functional theory with a 6-31G* basis set and vibrational frequencies predicted within the quasi-harmonic approximation. Several spectral features and band intensities are explained. This study generated a library of information that can be employed to aid the process monitoring of fluticasone propionate.

Computational and Matrix Isolation Studies of (2- and 3-Furyl)methylene

DTIC Science & Technology

1994-01-01

ynal, (Appendix 3) Simple HF calculations using the 6-31 G basis set + ZPE (zero point energy correction applied) predict 2.2 to be more stable in both...QCISD(T)/6-31 1 G** + ZPE predict the triplet to more stable by 2.9 Kcal/mol. However, calculations using MP4SDTQ/6-31 1 G + ZPE predict the singlet to...calculated frequencies were scaled by a factor of 0.9. 53 Table 2.30 Calculated ZPE for 2-Oxabicyclo(3.1.0]hexa-3,5-diene.a Zero Point Energy 49.9 (KcaVmol

Using L-M BP Algorithm Forecase the 305 Days Production of First-Breed Dairy

NASA Astrophysics Data System (ADS)

Wei, Xiaoli; Qi, Guoqiang; Shen, Weizheng; Jian, Sun

Aiming at the shortage of conventional BP algorithm, a BP neural net works improved by L-M algorithm is put forward. On the basis of the network, a Prediction model for 305 day's milk productions was set up. Traditional methods finish these data must spend at least 305 days, But this model can forecast first-breed dairy's 305 days milk production ahead of 215 days. The validity of the improved BP neural network predictive model was validated through the experiments.

A theoretical study of bond selective photochemistry in CH2BrI

NASA Astrophysics Data System (ADS)

Liu, Kun; Zhao, Hongmei; Wang, Caixia; Zhang, Aihua; Ma, Siyu; Li, Zonghe

2005-01-01

Bromoiodomethane photodissociation in the low-lying excited states has been characterized using unrestricted Hartree-Fock, configuration-interaction-singles, and complete active space self-consistent field calculations with the SDB-aug-cc-pVTZ, aug-cc-pVTZ, and 3-21g** basis sets. According to the results of the vertical excited energies and oscillator strengths of these low-lying excited states, bond selectivity is predicted. Subsequently, the minimum energy paths of the first excited singlet state and the third excited state for the dissociation reactions were calculated using the complete active space self-consistent field method with 3-21g** basis set. Good agreement is found between the calculations and experimental data. The relationships of excitations, the electronic structures at Franck-Condon points, and bond selectivity are discussed.

A DFT and ab initio benchmarking study of metal-alkane interactions and the activation of carbon-hydrogen bonds.

PubMed

Flener-Lovitt, Charity; Woon, David E; Dunning, Thom H; Girolami, Gregory S

2010-02-04

Density functional theory and ab initio methods have been used to calculate the structures and energies of minima and transition states for the reactions of methane coordinated to a transition metal. The reactions studied are reversible C-H bond activation of the coordinated methane ligand to form a transition metal methyl hydride complex and dissociation of the coordinated methane ligand. The reaction sequence can be summarized as L(x)M(CH(3))H <==> L(x)M(CH(4)) <==> L(x)M + CH(4), where L(x)M is the osmium-containing fragment (C(5)H(5))Os(R(2)PCH(2)PR(2))(+) and R is H or CH(3). Three-center metal-carbon-hydrogen interactions play an important role in this system. Both basis sets and functionals have been benchmarked in this work, including new correlation consistent basis sets for a third transition series element, osmium. Double zeta quality correlation consistent basis sets yield energies close to those from calculations with quadruple-zeta basis sets, with variations that are smaller than the differences between functionals. The energies of important species on the potential energy surface, calculated by using 10 DFT functionals, are compared both to experimental values and to CCSD(T) single point calculations. Kohn-Sham natural bond orbital descriptions are used to understand the differences between functionals. Older functionals favor electrostatic interactions over weak donor-acceptor interactions and, therefore, are not particularly well suited for describing systems--such as sigma-complexes--in which the latter are dominant. Newer kinetic and dispersion-corrected functionals such as MPW1K and M05-2X provide significantly better descriptions of the bonding interactions, as judged by their ability to predict energies closer to CCSD(T) values. Kohn-Sham and natural bond orbitals are used to differentiate between bonding descriptions. Our evaluations of these basis sets and DFT functionals lead us to recommend the use of dispersion corrected functionals in conjunction with double-zeta or larger basis sets with polarization functions for calculations involving weak interactions, such as those found in sigma-complexes with transition metals.

Appropriate description of intermolecular interactions in the methane hydrates: an assessment of DFT methods.

PubMed

Liu, Yuan; Zhao, Jijun; Li, Fengyu; Chen, Zhongfang

2013-01-15

Accurate description of hydrogen-bonding energies between water molecules and van der Waals interactions between guest molecules and host water cages is crucial for study of methane hydrates (MHs). Using high-level ab initio MP2 and CCSD(T) results as the reference, we carefully assessed the performance of a variety of exchange-correlation functionals and various basis sets in describing the noncovalent interactions in MH. The functionals under investigation include the conventional GGA, meta-GGA, and hybrid functionals (PBE, PW91, TPSS, TPSSh, B3LYP, and X3LYP), long-range corrected functionals (ωB97X, ωB97, LC-ωPBE, CAM-B3LYP, and LC-TPSS), the newly developed Minnesota class functionals (M06-L, M06-HF, M06, and M06-2X), and the dispersion-corrected density functional theory (DFT) (DFT-D) methods (B97-D, ωB97X-D, PBE-TS, PBE-Grimme, and PW91-OBS). We found that the conventional functionals are not suitable for MH, notably, the widely used B3LYP functional even predicts repulsive interaction between CH(4) and (H(2)O)(6) cluster. M06-2X is the best among the M06-Class functionals. The ωB97X-D outperforms the other DFT-D methods and is recommended for accurate first-principles calculations of MH. B97-D is also acceptable as a compromise of computational cost and precision. Considering both accuracy and efficiency, B97-D, ωB97X-D, and M06-2X functional with 6-311++G(2d,2p) basis set without basis set superposition error (BSSE) correction are recommended. Though a fairly large basis set (e.g., aug-cc-pVTZ) and BSSE correction are necessary for a reliable MP2 calculation, DFT methods are less sensitive to the basis set and BSSE correction if the basis set is sufficient (e.g., 6-311++G(2d,2p)). These assessments provide useful guidance for choosing appropriate methodology of first-principles simulation of MH and related systems. © 2012 Wiley Periodicals, Inc. Copyright © 2012 Wiley Periodicals, Inc.

Basis sets for the calculation of core-electron binding energies

NASA Astrophysics Data System (ADS)

Hanson-Heine, Magnus W. D.; George, Michael W.; Besley, Nicholas A.

2018-05-01

Core-electron binding energies (CEBEs) computed within a Δ self-consistent field approach require large basis sets to achieve convergence with respect to the basis set limit. It is shown that supplementing a basis set with basis functions from the corresponding basis set for the element with the next highest nuclear charge (Z + 1) provides basis sets that give CEBEs close to the basis set limit. This simple procedure provides relatively small basis sets that are well suited for calculations where the description of a core-ionised state is important, such as time-dependent density functional theory calculations of X-ray emission spectroscopy.

Structural, vibrational spectroscopic and quantum chemical studies on indole-3-carboxaldehyde

NASA Astrophysics Data System (ADS)

Premkumar, R.; Asath, R. Mohamed; Mathavan, T.; Benial, A. Milton Franklin

2017-05-01

The potential energy surface (PES) scan was performed for indole-3-carboxaldehyde (ICA) and the most stable optimized conformer was predicted using DFT/B3LYP method with 6-31G basis set. The vibrational frequencies of ICA were theoretically calculated by the DFT/B3LYP method with cc-pVTZ basis set using Gaussian 09 program. The vibrational spectra were experimentally recorded by Fourier transform-infrared (FT-IR) and Fourier transform-Raman spectrometer (FT-Raman). The computed vibrational frequencies were scaled by scaling factors to yield a good agreement with observed vibrational frequencies. The theoretically calculated and experimentally observed vibrational frequencies were assigned on the basis of potential energy distribution (PED) calculation using VEDA 4.0 program. The molecular interaction, stability and intramolecular charge transfer of ICA were studied using frontier molecular orbitals (FMOs) analysis and Mulliken atomic charge distribution shows the distribution of the atomic charges. The presence of intramolecular charge transfer was studied using natural bond orbital (NBO) analysis.

A global quality assurance system for personalized radiation therapy treatment planning for the prostate (or other sites)

NASA Astrophysics Data System (ADS)

Nwankwo, Obioma; Sihono, Dwi Seno K.; Schneider, Frank; Wenz, Frederik

2014-09-01

Introduction: the quality of radiotherapy treatment plans varies across institutions and depends on the experience of the planner. For the purpose of intra- and inter-institutional homogenization of treatment plan quality, we present an algorithm that learns the organs-at-risk (OARs) sparing patterns from a database of high quality plans. Thereafter, the algorithm predicts the dose that similar organs will receive in future radiotherapy plans prior to treatment planning on the basis of the anatomies of the organs. The predicted dose provides the basis for the individualized specification of planning objectives, and for the objective assessment of the quality of radiotherapy plans. Materials and method: one hundred and twenty eight (128) Volumetric Modulated Arc Therapy (VMAT) plans were selected from a database of prostate cancer plans. The plans were divided into two groups, namely a training set that is made up of 95 plans and a validation set that consists of 33 plans. A multivariate analysis technique was used to determine the relationships between the positions of voxels and their dose. This information was used to predict the likely sparing of the OARs of the plans of the validation set. The predicted doses were visually and quantitatively compared to the reference data using dose volume histograms, the 3D dose distribution, and a novel evaluation metric that is based on the dose different test. Results: a voxel of the bladder on the average receives a higher dose than a voxel of the rectum in optimized radiotherapy plans for the treatment of prostate cancer in our institution if both voxels are at the same distance to the PTV. Based on our evaluation metric, the predicted and reference dose to the bladder agree to within 5% of the prescribed dose to the PTV in 18 out of 33 cases, while the predicted and reference doses to the rectum agree to within 5% in 28 out of the 33 plans of the validation set. Conclusion: We have described a method to predict the likely dose that OARs will receive before treatment planning. This prospective knowledge could be used to implement a global quality assurance system for personalized radiation therapy treatment planning.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Papajak, Ewa; Truhlar, Donald G.

We present sets of convergent, partially augmented basis set levels corresponding to subsets of the augmented “aug-cc-pV(n+d)Z” basis sets of Dunning and co-workers. We show that for many molecular properties a basis set fully augmented with diffuse functions is computationally expensive and almost always unnecessary. On the other hand, unaugmented cc-pV(n+d)Z basis sets are insufficient for many properties that require diffuse functions. Therefore, we propose using intermediate basis sets. We developed an efficient strategy for partial augmentation, and in this article, we test it and validate it. Sequentially deleting diffuse basis functions from the “aug” basis sets yields the “jul”,more » “jun”, “may”, “apr”, etc. basis sets. Tests of these basis sets for Møller-Plesset second-order perturbation theory (MP2) show the advantages of using these partially augmented basis sets and allow us to recommend which basis sets offer the best accuracy for a given number of basis functions for calculations on large systems. Similar truncations in the diffuse space can be performed for the aug-cc-pVxZ, aug-cc-pCVxZ, etc. basis sets.« less

Fuzzy cluster analysis of simple physicochemical properties of amino acids for recognizing secondary structure in proteins.

PubMed Central

Mocz, G.

1995-01-01

Fuzzy cluster analysis has been applied to the 20 amino acids by using 65 physicochemical properties as a basis for classification. The clustering products, the fuzzy sets (i.e., classical sets with associated membership functions), have provided a new measure of amino acid similarities for use in protein folding studies. This work demonstrates that fuzzy sets of simple molecular attributes, when assigned to amino acid residues in a protein's sequence, can predict the secondary structure of the sequence with reasonable accuracy. An approach is presented for discriminating standard folding states, using near-optimum information splitting in half-overlapping segments of the sequence of assigned membership functions. The method is applied to a nonredundant set of 252 proteins and yields approximately 73% matching for correctly predicted and correctly rejected residues with approximately 60% overall success rate for the correctly recognized ones in three folding states: alpha-helix, beta-strand, and coil. The most useful attributes for discriminating these states appear to be related to size, polarity, and thermodynamic factors. Van der Waals volume, apparent average thickness of surrounding molecular free volume, and a measure of dimensionless surface electron density can explain approximately 95% of prediction results. hydrogen bonding and hydrophobicity induces do not yet enable clear clustering and prediction. PMID:7549882

Effect of 3-D viscoelastic structure on post-seismic relaxation from the 2004 M = 9.2 Sumatra earthquake

USGS Publications Warehouse

Pollitz, F.; Banerjee, P.; Grijalva, K.; Nagarajan, B.; Burgmann, R.

2008-01-01

The 2004 M=9.2 Sumatra-Andaman earthquake profoundly altered the state of stress in a large volume surrounding the ???1400 km long rupture. Induced mantle flow fields and coupled surface deformation are sensitive to the 3-D rheology structure. To predict the post-seismic motions from this earthquake, relaxation of a 3-D spherical viscoelastic earth model is simulated using the theory of coupled normal modes. The quasi-static deformation basis set and solution on the 3-D model is constructed using: a spherically stratified viscoelastic earth model with a linear stress-strain relation; an aspherical perturbation in viscoelastic structure; a 'static'mode basis set consisting of Earth's spheroidal and toroidal free oscillations; a "viscoelastic" mode basis set; and interaction kernels that describe the coupling among viscoelastic and static modes. Application to the 2004 Sumatra-Andaman earthquake illustrates the profound modification of the post-seismic flow field at depth by a slab structure and similarly large effects on the near-field post-seismic deformation field at Earth's surface. Comparison with post-seismic GPS observations illustrates the extent to which viscoelastic relaxation contributes to the regional post-seismic deformation. ?? Journal compilation ?? 2008 RAS.

Estimating the CCSD basis-set limit energy from small basis sets: basis-set extrapolations vs additivity schemes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Spackman, Peter R.; Karton, Amir, E-mail: amir.karton@uwa.edu.au

Coupled cluster calculations with all single and double excitations (CCSD) converge exceedingly slowly with the size of the one-particle basis set. We assess the performance of a number of approaches for obtaining CCSD correlation energies close to the complete basis-set limit in conjunction with relatively small DZ and TZ basis sets. These include global and system-dependent extrapolations based on the A + B/L{sup α} two-point extrapolation formula, and the well-known additivity approach that uses an MP2-based basis-set-correction term. We show that the basis set convergence rate can change dramatically between different systems(e.g.it is slower for molecules with polar bonds and/ormore » second-row elements). The system-dependent basis-set extrapolation scheme, in which unique basis-set extrapolation exponents for each system are obtained from lower-cost MP2 calculations, significantly accelerates the basis-set convergence relative to the global extrapolations. Nevertheless, we find that the simple MP2-based basis-set additivity scheme outperforms the extrapolation approaches. For example, the following root-mean-squared deviations are obtained for the 140 basis-set limit CCSD atomization energies in the W4-11 database: 9.1 (global extrapolation), 3.7 (system-dependent extrapolation), and 2.4 (additivity scheme) kJ mol{sup –1}. The CCSD energy in these approximations is obtained from basis sets of up to TZ quality and the latter two approaches require additional MP2 calculations with basis sets of up to QZ quality. We also assess the performance of the basis-set extrapolations and additivity schemes for a set of 20 basis-set limit CCSD atomization energies of larger molecules including amino acids, DNA/RNA bases, aromatic compounds, and platonic hydrocarbon cages. We obtain the following RMSDs for the above methods: 10.2 (global extrapolation), 5.7 (system-dependent extrapolation), and 2.9 (additivity scheme) kJ mol{sup –1}.« less

Estimating the CCSD basis-set limit energy from small basis sets: basis-set extrapolations vs additivity schemes

NASA Astrophysics Data System (ADS)

Spackman, Peter R.; Karton, Amir

2015-05-01

Coupled cluster calculations with all single and double excitations (CCSD) converge exceedingly slowly with the size of the one-particle basis set. We assess the performance of a number of approaches for obtaining CCSD correlation energies close to the complete basis-set limit in conjunction with relatively small DZ and TZ basis sets. These include global and system-dependent extrapolations based on the A + B/Lα two-point extrapolation formula, and the well-known additivity approach that uses an MP2-based basis-set-correction term. We show that the basis set convergence rate can change dramatically between different systems(e.g.it is slower for molecules with polar bonds and/or second-row elements). The system-dependent basis-set extrapolation scheme, in which unique basis-set extrapolation exponents for each system are obtained from lower-cost MP2 calculations, significantly accelerates the basis-set convergence relative to the global extrapolations. Nevertheless, we find that the simple MP2-based basis-set additivity scheme outperforms the extrapolation approaches. For example, the following root-mean-squared deviations are obtained for the 140 basis-set limit CCSD atomization energies in the W4-11 database: 9.1 (global extrapolation), 3.7 (system-dependent extrapolation), and 2.4 (additivity scheme) kJ mol-1. The CCSD energy in these approximations is obtained from basis sets of up to TZ quality and the latter two approaches require additional MP2 calculations with basis sets of up to QZ quality. We also assess the performance of the basis-set extrapolations and additivity schemes for a set of 20 basis-set limit CCSD atomization energies of larger molecules including amino acids, DNA/RNA bases, aromatic compounds, and platonic hydrocarbon cages. We obtain the following RMSDs for the above methods: 10.2 (global extrapolation), 5.7 (system-dependent extrapolation), and 2.9 (additivity scheme) kJ mol-1.

An arbitrary-order Runge–Kutta discontinuous Galerkin approach to reinitialization for banded conservative level sets

DOE PAGES

Jibben, Zechariah Joel; Herrmann, Marcus

2017-08-24

Here, we present a Runge-Kutta discontinuous Galerkin method for solving conservative reinitialization in the context of the conservative level set method. This represents an extension of the method recently proposed by Owkes and Desjardins [21], by solving the level set equations on the refined level set grid and projecting all spatially-dependent variables into the full basis used by the discontinuous Galerkin discretization. By doing so, we achieve the full k+1 order convergence rate in the L1 norm of the level set field predicted for RKDG methods given kth degree basis functions when the level set profile thickness is held constantmore » with grid refinement. Shape and volume errors for the 0.5-contour of the level set, on the other hand, are found to converge between first and second order. We show a variety of test results, including the method of manufactured solutions, reinitialization of a circle and sphere, Zalesak's disk, and deforming columns and spheres, all showing substantial improvements over the high-order finite difference traditional level set method studied for example by Herrmann. We also demonstrate the need for kth order accurate normal vectors, as lower order normals are found to degrade the convergence rate of the method.« less

Demystifying Multitask Deep Neural Networks for Quantitative Structure-Activity Relationships.

PubMed

Xu, Yuting; Ma, Junshui; Liaw, Andy; Sheridan, Robert P; Svetnik, Vladimir

2017-10-23

Deep neural networks (DNNs) are complex computational models that have found great success in many artificial intelligence applications, such as computer vision1,2 and natural language processing.3,4 In the past four years, DNNs have also generated promising results for quantitative structure-activity relationship (QSAR) tasks.5,6 Previous work showed that DNNs can routinely make better predictions than traditional methods, such as random forests, on a diverse collection of QSAR data sets. It was also found that multitask DNN models-those trained on and predicting multiple QSAR properties simultaneously-outperform DNNs trained separately on the individual data sets in many, but not all, tasks. To date there has been no satisfactory explanation of why the QSAR of one task embedded in a multitask DNN can borrow information from other unrelated QSAR tasks. Thus, using multitask DNNs in a way that consistently provides a predictive advantage becomes a challenge. In this work, we explored why multitask DNNs make a difference in predictive performance. Our results show that during prediction a multitask DNN does borrow "signal" from molecules with similar structures in the training sets of the other tasks. However, whether this borrowing leads to better or worse predictive performance depends on whether the activities are correlated. On the basis of this, we have developed a strategy to use multitask DNNs that incorporate prior domain knowledge to select training sets with correlated activities, and we demonstrate its effectiveness on several examples.

Lanthanide complex coordination polyhedron geometry prediction accuracies of ab initio effective core potential calculations.

PubMed

Freire, Ricardo O; Rocha, Gerd B; Simas, Alfredo M

2006-03-01

lanthanide coordination compounds efficiently and accurately is central for the design of new ligands capable of forming stable and highly luminescent complexes. Accordingly, we present in this paper a report on the capability of various ab initio effective core potential calculations in reproducing the coordination polyhedron geometries of lanthanide complexes. Starting with all combinations of HF, B3LYP and MP2(Full) with STO-3G, 3-21G, 6-31G, 6-31G* and 6-31+G basis sets for [Eu(H2O)9]3+ and closing with more manageable calculations for the larger complexes, we computed the fully predicted ab initio geometries for a total of 80 calculations on 52 complexes of Sm(III), Eu(III), Gd(III), Tb(III), Dy(III), Ho(III), Er(III) and Tm(III), the largest containing 164 atoms. Our results indicate that RHF/STO-3G/ECP appears to be the most efficient model chemistry in terms of coordination polyhedron crystallographic geometry predictions from isolated lanthanide complex ion calculations. Moreover, both augmenting the basis set and/or including electron correlation generally enlarged the deviations and aggravated the quality of the predicted coordination polyhedron crystallographic geometry. Our results further indicate that Cosentino et al.'s suggestion of using RHF/3-21G/ECP geometries appears to be indeed a more robust, but not necessarily, more accurate recommendation to be adopted for the general lanthanide complex case. [Figure: see text].

An Extended Ab Initio and Theoretical Thermodynamics Studies of the Bergman Reaction and the Energy Splitting of the Singlet Ortho-, Meta-, and Para-Benzynes

NASA Technical Reports Server (NTRS)

Lindh, Roland; Lee, Timothy J.; Bernhardsson, Anders; Persson, B. Joakim; Karlstroem, Gunnar; Langhoff, Stephen R. (Technical Monitor)

1995-01-01

The autoaromatization of (Z)-hex-3-ene-1,5-diyne to the singlet biradical para-benzyne has been reinvestigated by state of the art ab initio methods. Previous CCSD(T)/6-31G(d,p) and CASPT2[0]/ANO[C(5s4p2d1f)/H(3s2p)] calculations estimated the the reaction heat at 298 K to be 8-10 and 4.9 plus or minus 3.2 kcal/mol, respectively. Recent NO- and oxygen-dependent trapping experiments and collision-induced dissociation threshold energy experiments estimate the heat of reaction to be 8.5 plus or minus 1.0 at 470 K (recomputed to 9.5 plus or minus 1.0 at 298 K) and 8.4 plus or minus 3.0 kcal/mol at 298 K, respectively. New theoretical estimates at 298 K predict the values at the basis set limit for the CCSD(T) and CASPT2(g1) methods to be 12.7 plus or minus 2.0 and 5.4 plus or minus 2.0 kcal/mol, respectively. The experimentally predicted electronic contribution to the heat of activation is 28.6 kcal/mol. This can be compared with 25.5 and 29.8 kcal/mol from the CASPT2[g1] and the CCSD(T) methods, respectively. The new study has in particular improved on the one-particle basis set for the CCSD(T) method as compared to earlier studies. For the CASPT2 investigation the better suited CASPT2[g1] approximation is utilized. The original CASPT2 method, CASPT2[0], systematically favors open shell systems relative to closed shell systems. This was previously corrected empirically. The study shows that the energy difference between CCSD(T) and CASPT2[g1] at the basis set limit is estimated to be 7 plus or minus 2 kcal/mol. The study also demonstrates that the estimated heat of reaction is very sensitive to the quality of the basis set.

78 FR 69825 - Takes of Marine Mammals Incidental to Specified Activities; Taking Marine Mammals Incidental to a...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-21

... availability of the species or stock(s) for subsistence uses (where relevant). Further, the permissible methods... (ITA) under section 101(a)(5)(D) of the MMPA, we must set forth the permissible methods of taking... basis of predicted distances to relevant thresholds in post-processing of observational and acoustic...

Approximating recreation site choice: the predictive capability of a lexicographic semi-order model

Treesearch

Alan E. Watson; Joseph W. Roggenbuck

1985-01-01

The relevancy of a lexicographic semi-order model, as a basis for development of a microcomputer-based decision aid for backcountry hikers, was investigated. In an interactive microcomputer exercise, it was found that a decision aid based upon this model may assist recreationists in reduction of an alternative set to a cognitively manageable number.

Predictiveness of Disease Risk in a Global Outreach Tourist Setting in Thailand Using Meteorological Data and Vector-Borne Disease Incidences

PubMed Central

Ninphanomchai, Suwannapa; Chansang, Chitti; Hii, Yien Ling; Rocklöv, Joacim; Kittayapong, Pattamaporn

2014-01-01

Dengue and malaria are vector-borne diseases and major public health problems worldwide. Changes in climatic factors influence incidences of these diseases. The objective of this study was to investigate the relationship between vector-borne disease incidences and meteorological data, and hence to predict disease risk in a global outreach tourist setting. The retrospective data of dengue and malaria incidences together with local meteorological factors (temperature, rainfall, humidity) registered from 2001 to 2011 on Koh Chang, Thailand were used in this study. Seasonal distribution of disease incidences and its correlation with local climatic factors were analyzed. Seasonal patterns in disease transmission differed between dengue and malaria. Monthly meteorological data and reported disease incidences showed good predictive ability of disease transmission patterns. These findings provide a rational basis for identifying the predictive ability of local meteorological factors on disease incidence that may be useful for the implementation of disease prevention and vector control programs on the tourism island, where climatic factors fluctuate. PMID:25325356

Predictiveness of disease risk in a global outreach tourist setting in Thailand using meteorological data and vector-borne disease incidences.

PubMed

Ninphanomchai, Suwannapa; Chansang, Chitti; Hii, Yien Ling; Rocklöv, Joacim; Kittayapong, Pattamaporn

2014-10-16

Dengue and malaria are vector-borne diseases and major public health problems worldwide. Changes in climatic factors influence incidences of these diseases. The objective of this study was to investigate the relationship between vector-borne disease incidences and meteorological data, and hence to predict disease risk in a global outreach tourist setting. The retrospective data of dengue and malaria incidences together with local meteorological factors (temperature, rainfall, humidity) registered from 2001 to 2011 on Koh Chang, Thailand were used in this study. Seasonal distribution of disease incidences and its correlation with local climatic factors were analyzed. Seasonal patterns in disease transmission differed between dengue and malaria. Monthly meteorological data and reported disease incidences showed good predictive ability of disease transmission patterns. These findings provide a rational basis for identifying the predictive ability of local meteorological factors on disease incidence that may be useful for the implementation of disease prevention and vector control programs on the tourism island, where climatic factors fluctuate.

Effectiveness of Genomic Prediction of Maize Hybrid Performance in Different Breeding Populations and Environments

PubMed Central

Windhausen, Vanessa S.; Atlin, Gary N.; Hickey, John M.; Crossa, Jose; Jannink, Jean-Luc; Sorrells, Mark E.; Raman, Babu; Cairns, Jill E.; Tarekegne, Amsal; Semagn, Kassa; Beyene, Yoseph; Grudloyma, Pichet; Technow, Frank; Riedelsheimer, Christian; Melchinger, Albrecht E.

2012-01-01

Genomic prediction is expected to considerably increase genetic gains by increasing selection intensity and accelerating the breeding cycle. In this study, marker effects estimated in 255 diverse maize (Zea mays L.) hybrids were used to predict grain yield, anthesis date, and anthesis-silking interval within the diversity panel and testcross progenies of 30 F2-derived lines from each of five populations. Although up to 25% of the genetic variance could be explained by cross validation within the diversity panel, the prediction of testcross performance of F2-derived lines using marker effects estimated in the diversity panel was on average zero. Hybrids in the diversity panel could be grouped into eight breeding populations differing in mean performance. When performance was predicted separately for each breeding population on the basis of marker effects estimated in the other populations, predictive ability was low (i.e., 0.12 for grain yield). These results suggest that prediction resulted mostly from differences in mean performance of the breeding populations and less from the relationship between the training and validation sets or linkage disequilibrium with causal variants underlying the predicted traits. Potential uses for genomic prediction in maize hybrid breeding are discussed emphasizing the need of (1) a clear definition of the breeding scenario in which genomic prediction should be applied (i.e., prediction among or within populations), (2) a detailed analysis of the population structure before performing cross validation, and (3) larger training sets with strong genetic relationship to the validation set. PMID:23173094

Development of many-body polarizable force fields for Li-battery components: 1. Ether, alkane, and carbonate-based solvents.

PubMed

Borodin, Oleg; Smith, Grant D

2006-03-30

Classical many-body polarizable force fields were developed for n-alkanes, perflouroalkanes, polyethers, ketones, and linear and cyclic carbonates on the basis of quantum chemistry dimer energies of model compounds and empirical thermodynamic liquid-state properties. The dependence of the electron correlation contribution to the dimer binding energy on basis-set size and level of theory was investigated as a function of molecular separation for a number of alkane, ether, and ketone dimers. Molecular dynamics (MD) simulations of the force fields accurately predicted structural, dynamic, and transport properties of liquids and unentangled polymer melts. On average, gas-phase dimer binding energies predicted with the force field were between those from MP2/aug-cc-pvDz and MP2/aug-cc-pvTz quantum chemistry calculations.

Radial basis function network learns ceramic processing and predicts related strength and density

NASA Technical Reports Server (NTRS)

Cios, Krzysztof J.; Baaklini, George Y.; Vary, Alex; Tjia, Robert E.

1993-01-01

Radial basis function (RBF) neural networks were trained using the data from 273 Si3N4 modulus of rupture (MOR) bars which were tested at room temperature and 135 MOR bars which were tested at 1370 C. Milling time, sintering time, and sintering gas pressure were the processing parameters used as the input features. Flexural strength and density were the outputs by which the RBF networks were assessed. The 'nodes-at-data-points' method was used to set the hidden layer centers and output layer training used the gradient descent method. The RBF network predicted strength with an average error of less than 12 percent and density with an average error of less than 2 percent. Further, the RBF network demonstrated a potential for optimizing and accelerating the development and processing of ceramic materials.

Application of Hyperspectral Imaging to Detect Sclerotinia sclerotiorum on Oilseed Rape Stems

PubMed Central

Kong, Wenwen; Zhang, Chu; Huang, Weihao

2018-01-01

Hyperspectral imaging covering the spectral range of 384–1034 nm combined with chemometric methods was used to detect Sclerotinia sclerotiorum (SS) on oilseed rape stems by two sample sets (60 healthy and 60 infected stems for each set). Second derivative spectra and PCA loadings were used to select the optimal wavelengths. Discriminant models were built and compared to detect SS on oilseed rape stems, including partial least squares-discriminant analysis, radial basis function neural network, support vector machine and extreme learning machine. The discriminant models using full spectra and optimal wavelengths showed good performance with classification accuracies of over 80% for the calibration and prediction set. Comparing all developed models, the optimal classification accuracies of the calibration and prediction set were over 90%. The similarity of selected optimal wavelengths also indicated the feasibility of using hyperspectral imaging to detect SS on oilseed rape stems. The results indicated that hyperspectral imaging could be used as a fast, non-destructive and reliable technique to detect plant diseases on stems. PMID:29300315

Impact of domain knowledge on blinded predictions of binding energies by alchemical free energy calculations

NASA Astrophysics Data System (ADS)

Mey, Antonia S. J. S.; Jiménez, Jordi Juárez; Michel, Julien

2018-01-01

The Drug Design Data Resource (D3R) consortium organises blinded challenges to address the latest advances in computational methods for ligand pose prediction, affinity ranking, and free energy calculations. Within the context of the second D3R Grand Challenge several blinded binding free energies predictions were made for two congeneric series of Farsenoid X Receptor (FXR) inhibitors with a semi-automated alchemical free energy calculation workflow featuring FESetup and SOMD software tools. Reasonable performance was observed in retrospective analyses of literature datasets. Nevertheless, blinded predictions on the full D3R datasets were poor due to difficulties encountered with the ranking of compounds that vary in their net-charge. Performance increased for predictions that were restricted to subsets of compounds carrying the same net-charge. Disclosure of X-ray crystallography derived binding modes maintained or improved the correlation with experiment in a subsequent rounds of predictions. The best performing protocols on D3R set1 and set2 were comparable or superior to predictions made on the basis of analysis of literature structure activity relationships (SAR)s only, and comparable or slightly inferior, to the best submissions from other groups.

Relative congener scaling of Polychlorinated dibenzo-p-dioxins and dibenzofurans to estimate building fire contributions in air, surface wipes, and dust samples.

PubMed

Pleil, Joachim D; Lorber, Matthew N

2007-11-01

The United States Environmental Protection Agency collected ambient air samples in lower Manhattan for about 9 months following the September 11, 2001 World Trade Center (WTC) attacks. Measurements were made of a host of airborne contaminants including volatile organic compounds, polycyclic aromatic hydrocarbons, asbestos, lead, and other contaminants of concern. The present study focuses on the broad class of polychlorinated dibenzo-p-dioxins (CDDs) and dibenzofurans (CDFs) with specific emphasis on the 17 CDD/CDF congeners that exhibit mammalian toxicity. This work is a statistical study comparing the internal patterns of CDD/CDFs using data from an unambiguous fire event (WTC) and other data sets to help identify their sources. A subset of 29 samples all taken between September 16 and October 31, 2001 were treated as a basis set known to be heavily impacted by the WTC building fire source. A second basis set was created using data from Los Angeles and Oakland, CA as published by the California Air Resources Board (CARB) and treated as the archetypical background pattern for CDD/CDFs. The CARB data had a congener profile appearing similar to background air samples from different locations in America and around the world and in different matrices, such as background soils. Such disparate data would normally be interpreted with a qualitative pattern recognition based on congener bar graphs or other forms of factor or cluster analysis that group similar samples together graphically. The procedure developed here employs aspects of those statistical methods to develop a single continuous output variable per sample. Specifically, a form of variance structure-based cluster analysis is used to group congeners within samples to reduce collinearity in the basis sets, new variables are created based on these groups, and multivariate regression is applied to the reduced variable set to determine a predictive equation. This equation predicts a value for an output variable, OPT: the predicted value of OPT is near zero (0.00) for a background congener profile and near one (1.00) forthe profile characterized by the WTC air profile. Although this empirical method is calibrated with relatively small sets of airborne samples, it is shown to be generalizable to other WTC, fire source, and background air samples as well as other sample matrices including soils, window films and other dust wipes, and bulk dusts. However, given the limited data set examined, the method does not allow further discrimination between the WTC data and the other fire sources. This type of analysis is demonstrated to be useful for complex trace-level data sets with limited data and some below-detection entries.

Electronic Structure and Bonding in Transition Metal Inorganic and Organometallic Complexes: New Basis Sets, Linear Semibridging Carbonyls and Thiocarbonyls, and Oxidative Addition of Molecular Hydrogen to Square - Iridium Complexes.

NASA Astrophysics Data System (ADS)

Sargent, Andrew Landman

Approximate molecular orbital and ab initio quantum chemical techniques are used to investigate the electronic structure, bonding and reactivity of several transition metal inorganic and organometallic complexes. Modest-sized basis sets are developed for the second-row transition metal atoms and are designed for use in geometry optimizations of inorganic and organometallic complexes incorporating these atoms. The basis sets produce optimized equilibrium geometries which are slightly better than those produced with standard 3-21G basis sets, and which are significantly better than those produced with effective core potential basis sets. Linear semibridging carbonyl ligands in heterobimetallic complexes which contain a coordinatively unsaturated late transition metal center are found to accept electron density from, rather than donate electron density to, these centers. Only when the secondary metal center is a coordinatively unsaturated early transition metal center does the semibridging ligand donate electron density to this center. Large holes in the d shell around the metal center are more prominent and prevalent in early than in late transition metal centers, and the importance of filling in these holes outweighs the importance of mitigating the charge imbalance due to the dative metal-metal interaction. Semibridging thiocarbonyl ligands are more effective donors of electron density than the carbonyl ligands since the occupied donor orbitals of pi symmetry are higher in energy. The stereoselectivity of H_2 addition to d^8 square-planar transition metal complexes is controlled by the interactions between the ligands in the plane of addition and the concentrations of electronic charge around the metal center as the complex evolves from a four-coordinate to a six-coordinate species. Electron -withdrawing ligands help stabilize the five-coordinate species while strong electron donor ligands contribute only to the destabilizing repulsive interactions. The relative thermodynamic stabilities of the final complexes can be predicted based on the relative orientations of the strongest sigma-donor ligands.

Ab initio Potential Energy Surface for H-H2

NASA Technical Reports Server (NTRS)

Partridge, Harry; Bauschlicher, Charles W., Jr.; Stallcop, James R.; Levin, Eugene

1993-01-01

Ab initio calculations employing large basis sets are performed to determine an accurate potential energy surface for H-H2 interactions for a broad range of separation distances. At large distances, the spherically averaged potential determined from the calculated energies agrees well with the corresponding results determined from dispersion coefficients; the van der Waals well depth is predicted to be 75 +/- (mu)E(sub h). Large basis sets have also been applied to reexamine the accuracy of theoretical repulsive potential energy surfaces. Multipolar expansions of the computed H-H2 potential energy surface are reported for four internuclear separation distances (1.2, 1.401, 1.449, and 1.7a(sub 0) of the hydrogen molecule. The differential elastic scattering cross section calculated from the present results is compared with the measurements from a crossed beam experiment.

Dynamic sensitivity analysis of long running landslide models through basis set expansion and meta-modelling

NASA Astrophysics Data System (ADS)

Rohmer, Jeremy

2016-04-01

Predicting the temporal evolution of landslides is typically supported by numerical modelling. Dynamic sensitivity analysis aims at assessing the influence of the landslide properties on the time-dependent predictions (e.g., time series of landslide displacements). Yet two major difficulties arise: 1. Global sensitivity analysis require running the landslide model a high number of times (> 1000), which may become impracticable when the landslide model has a high computation time cost (> several hours); 2. Landslide model outputs are not scalar, but function of time, i.e. they are n-dimensional vectors with n usually ranging from 100 to 1000. In this article, I explore the use of a basis set expansion, such as principal component analysis, to reduce the output dimensionality to a few components, each of them being interpreted as a dominant mode of variation in the overall structure of the temporal evolution. The computationally intensive calculation of the Sobol' indices for each of these components are then achieved through meta-modelling, i.e. by replacing the landslide model by a "costless-to-evaluate" approximation (e.g., a projection pursuit regression model). The methodology combining "basis set expansion - meta-model - Sobol' indices" is then applied to the La Frasse landslide to investigate the dynamic sensitivity analysis of the surface horizontal displacements to the slip surface properties during the pore pressure changes. I show how to extract information on the sensitivity of each main modes of temporal behaviour using a limited number (a few tens) of long running simulations. In particular, I identify the parameters, which trigger the occurrence of a turning point marking a shift between a regime of low values of landslide displacements and one of high values.

2018 update to the HIV-TRePS system: the development of new computational models to predict HIV treatment outcomes, with or without a genotype, with enhanced usability for low-income settings.

PubMed

Revell, Andrew D; Wang, Dechao; Perez-Elias, Maria-Jesus; Wood, Robin; Cogill, Dolphina; Tempelman, Hugo; Hamers, Raph L; Reiss, Peter; van Sighem, Ard I; Rehm, Catherine A; Pozniak, Anton; Montaner, Julio S G; Lane, H Clifford; Larder, Brendan A

2018-06-08

Optimizing antiretroviral drug combination on an individual basis can be challenging, particularly in settings with limited access to drugs and genotypic resistance testing. Here we describe our latest computational models to predict treatment responses, with or without a genotype, and compare their predictive accuracy with that of genotyping. Random forest models were trained to predict the probability of virological response to a new therapy introduced following virological failure using up to 50 000 treatment change episodes (TCEs) without a genotype and 18 000 TCEs including genotypes. Independent data sets were used to evaluate the models. This study tested the effects on model accuracy of relaxing the baseline data timing windows, the use of a new filter to exclude probable non-adherent cases and the addition of maraviroc, tipranavir and elvitegravir to the system. The no-genotype models achieved area under the receiver operator characteristic curve (AUC) values of 0.82 and 0.81 using the standard and relaxed baseline data windows, respectively. The genotype models achieved AUC values of 0.86 with the new non-adherence filter and 0.84 without. Both sets of models were significantly more accurate than genotyping with rules-based interpretation, which achieved AUC values of only 0.55-0.63, and were marginally more accurate than previous models. The models were able to identify alternative regimens that were predicted to be effective for the vast majority of cases in which the new regimen prescribed in the clinic failed. These latest global models predict treatment responses accurately even without a genotype and have the potential to help optimize therapy, particularly in resource-limited settings.

Correlation consistent basis sets for the atoms In–Xe

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mahler, Andrew; Wilson, Angela K., E-mail: akwilson@unt.edu

In this work, the correlation consistent family of Gaussian basis sets has been expanded to include all-electron basis sets for In–Xe. The methodology for developing these basis sets is described, and several examples of the performance and utility of the new sets have been provided. Dissociation energies and bond lengths for both homonuclear and heteronuclear diatomics demonstrate the systematic convergence behavior with respect to increasing basis set quality expected by the family of correlation consistent basis sets in describing molecular properties. Comparison with recently developed correlation consistent sets designed for use with the Douglas-Kroll Hamiltonian is provided.

Predicting Language Teachers' Classroom Management Orientations on the Basis of Their Computer Attitude and Demographic Characteristics

ERIC Educational Resources Information Center

Jalali, Sara; Panahzade, Vahid

2014-01-01

The advent of modern technologies has had a remarkable role in revolutionizing the classroom setting. It is, therefore, incumbent on teachers to utilize strategies for effective managing of the change. The aim of the present study was to find out English as a Foreign Language (EFL) teachers' beliefs regarding classroom management. In so doing, the…

A multiscale numerical study into the cascade of kinetic energy leading to severe local storms

NASA Technical Reports Server (NTRS)

Paine, D. A.; Kaplan, M. L.

1977-01-01

The cascade of kinetic energy from macro- through mesoscales is studied on the basis of a nested grid system used to solve a set of nonlinear differential equations. The kinetic energy cascade and the concentration of vorticity through the hydrodynamic spectrum provide a means for predicting the location and intensity of severe weather from large-scale data sets. A mechanism described by the surface pressure tendency equation proves to be important in explaining how initial middle-tropospheric mass-momentum imbalances alter the low-level pressure field.

Molecular conformational analysis, vibrational spectra and normal coordinate analysis of trans-1,2-bis(3,5-dimethoxy phenyl)-ethene based on density functional theory calculations.

PubMed

Joseph, Lynnette; Sajan, D; Chaitanya, K; Isac, Jayakumary

2014-03-25

The conformational behavior and structural stability of trans-1,2-bis(3,5-dimethoxy phenyl)-ethene (TDBE) were investigated by using density functional theory (DFT) method with the B3LYP/6-311++G(d,p) basis set combination. The vibrational wavenumbers of TDBE were computed at DFT level and complete vibrational assignments were made on the basis of normal coordinate analysis calculations (NCA). The DFT force field transformed to natural internal coordinates was corrected by a well-established set of scale factors that were found to be transferable to the title compound. The infrared and Raman spectra were also predicted from the calculated intensities. The observed Fourier transform infrared (FTIR) and Fourier transform (FT) Raman vibrational wavenumbers were analyzed and compared with the theoretically predicted vibrational spectra. Comparison of the simulated spectra with the experimental spectra provides important information about the ability of the computational method to describe the vibrational modes. Information about the size, shape, charge density distribution and site of chemical reactivity of the molecules has been obtained by mapping electron density isosurface with electrostatic potential surfaces (ESP). Copyright © 2013 Elsevier B.V. All rights reserved.

The leap-frog effect of ring currents in benzene.

PubMed

Ligabue, Andrea; Soncini, Alessandro; Lazzeretti, Paolo

2002-03-06

Symmetry arguments show that the ring-current model proposed by Pauling, Lonsdale, and London to explain the enhanced diamagnetism of benzene is flawed by an intrinsic drawback. The minimal basis set of six atomic 2p orbitals taken into account to develop such a model is inherently insufficient to predict a paramagnetic contribution to the perpendicular component of magnetic susceptibility in planar ring systems such as benzene. Analogous considerations can be made for the hypothetical H(6) cyclic molecule. A model allowing for extended basis sets is necessary to rationalize the magnetism of aromatics. According to high-quality coupled Hartree-Fock calculations, the trajectories of the current density vector field induced by a magnetic field perpendicular to the skeletal plane of benzene in the pi electrons are noticeably different from those typical of a Larmor diamagnetic circulation, in that (i) significant deformation of the orbits from circular to hexagonal symmetry occurs, which is responsible for a paramagnetic contribution of pi electrons to the out-of-plane component of susceptibility, and (ii) a sizable component of the pi current density vector parallel to the inducing field is predicted. This causes a waving motion of pi electrons; streamlines are characterized by a "leap-frog effect".

Ab-Initio Description and Prediction of Properties of Carbon-Based and Other Non-Metallic Materials

NASA Technical Reports Server (NTRS)

Bagayoko, D.; Zhao, G. L.; Hasan, S.

2001-01-01

We have resolved the long-standing problem consisting of 30%-50% theoretical underestimates of the band gaps of non-metallic materials. We describe the Bagayoko, Zhao, and Williams (BZW) method that rigorously circumvents the basis-set and variational effect presumed to be a cause of these underestimates. We present ab-initio, computational results that are in agreement with experiment for diamond (C), silicon (Si), silicon carbides (3C-SiC and 4H-SiC), and other semiconductors (GaN, BaTiO3, AlN, ZnSe, ZnO). We illustrate the predictive capability of the BZW method in the case of the newly discovered cubic phase of silicon nitride (c-Si3N4) and of selected carbon nanotabes [(10,0), and (8,4)]. Our conclusion underscores the inescapable need for the BZW method in ab-initio calculations that employ a basis set in a variational approach. Current nanoscale trends amplify this need. We estimate that the potential impact of applications of the BZW method in advancing our understanding of nonmetallic materials, in informing experiment, and particularly in guiding device design and fabrication is simply priceless.

Neural network approach to quantum-chemistry data: accurate prediction of density functional theory energies.

PubMed

Balabin, Roman M; Lomakina, Ekaterina I

2009-08-21

Artificial neural network (ANN) approach has been applied to estimate the density functional theory (DFT) energy with large basis set using lower-level energy values and molecular descriptors. A total of 208 different molecules were used for the ANN training, cross validation, and testing by applying BLYP, B3LYP, and BMK density functionals. Hartree-Fock results were reported for comparison. Furthermore, constitutional molecular descriptor (CD) and quantum-chemical molecular descriptor (QD) were used for building the calibration model. The neural network structure optimization, leading to four to five hidden neurons, was also carried out. The usage of several low-level energy values was found to greatly reduce the prediction error. An expected error, mean absolute deviation, for ANN approximation to DFT energies was 0.6+/-0.2 kcal mol(-1). In addition, the comparison of the different density functionals with the basis sets and the comparison of multiple linear regression results were also provided. The CDs were found to overcome limitation of the QD. Furthermore, the effective ANN model for DFT/6-311G(3df,3pd) and DFT/6-311G(2df,2pd) energy estimation was developed, and the benchmark results were provided.

A Computational Study on the Ground and Excited States of Nickel Silicide.

PubMed

Schoendorff, George; Morris, Alexis R; Hu, Emily D; Wilson, Angela K

2015-09-17

Nickel silicide has been studied with a range of computational methods to determine the nature of the Ni-Si bond. Additionally, the physical effects that need to be addressed within calculations to predict the equilibrium bond length and bond dissociation energy within experimental error have been determined. The ground state is predicted to be a (1)Σ(+) state with a bond order of 2.41 corresponding to a triple bond with weak π bonds. It is shown that calculation of the ground state equilibrium geometry requires a polarized basis set and treatment of dynamic correlation including up to triple excitations with CR-CCSD(T)L resulting in an equilibrium bond length of only 0.012 Å shorter than the experimental bond length. Previous calculations of the bond dissociation energy resulted in energies that were only 34.8% to 76.5% of the experimental bond dissociation energy. It is shown here that use of polarized basis sets, treatment of triple excitations, correlation of the valence and subvalence electrons, and a Λ coupled cluster approach is required to obtain a bond dissociation energy that deviates as little as 1% from experiment.

Spectroscopic and DFT studies of bis-3-hydroxypyridinium and bis-3-hydroxymethylpyridinium dibromides with tetramethylene linker

NASA Astrophysics Data System (ADS)

Komasa, Anna

2018-01-01

Experimental and theoretical IR, Raman, UV-Vis, 1H and 13C NMR spectra of 1,4-di(3-hydroxypyridinium)butane dibromide and 1,4-di(3-hydroxymethylpyridinium)butane dibromide were obtained and analyzed. Optimized geometrical structures of the studied compounds were calculated by B3LYP method using 6-311++G(d,p) basis set and employed to determine the theoretical wavenumbers and intensities of IR and Raman spectra. The frequency assignments were supported by the potential energy distribution (PED) analysis. The significant role of the intermolecular interactions and the hydrogen bond was revealed on the basis of IR spectra. The calculated GIAO/B3LYP/6-311++G(d,p) isotropic magnetic shielding constants were used to predict the 1H and 13C chemical shifts for the optimized structures. Accuracy of the prediction of 1H and 13C chemical shifts was significantly improved by a simulation of the solvent in calculations. On the basis of UV-Vis spectra the acid-base equilibrium in the water solution of 1,4-di(3-hydroxypyridinium)butane dibromide was found.

Theoretical prediction of nuclear magnetic shieldings and indirect spin-spin coupling constants in 1,1-, cis-, and trans-1,2-difluoroethylenes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nozirov, Farhod, E-mail: teobaldk@gmail.com, E-mail: farhod.nozirov@gmail.com; Stachów, Michał, E-mail: michal.stachow@gmail.com; Kupka, Teobald, E-mail: teobaldk@gmail.com, E-mail: farhod.nozirov@gmail.com

2014-04-14

A theoretical prediction of nuclear magnetic shieldings and indirect spin-spin coupling constants in 1,1-, cis- and trans-1,2-difluoroethylenes is reported. The results obtained using density functional theory (DFT) combined with large basis sets and gauge-independent atomic orbital calculations were critically compared with experiment and conventional, higher level correlated electronic structure methods. Accurate structural, vibrational, and NMR parameters of difluoroethylenes were obtained using several density functionals combined with dedicated basis sets. B3LYP/6-311++G(3df,2pd) optimized structures of difluoroethylenes closely reproduced experimental geometries and earlier reported benchmark coupled cluster results, while BLYP/6-311++G(3df,2pd) produced accurate harmonic vibrational frequencies. The most accurate vibrations were obtained using B3LYP/6-311++G(3df,2pd)more » with correction for anharmonicity. Becke half and half (BHandH) density functional predicted more accurate {sup 19}F isotropic shieldings and van Voorhis and Scuseria's τ-dependent gradient-corrected correlation functional yielded better carbon shieldings than B3LYP. A surprisingly good performance of Hartree-Fock (HF) method in predicting nuclear shieldings in these molecules was observed. Inclusion of zero-point vibrational correction markedly improved agreement with experiment for nuclear shieldings calculated by HF, MP2, CCSD, and CCSD(T) methods but worsened the DFT results. The threefold improvement in accuracy when predicting {sup 2}J(FF) in 1,1-difluoroethylene for BHandH density functional compared to B3LYP was observed (the deviations from experiment were −46 vs. −115 Hz)« less

Predicting hydrofacies and hydraulic conductivity from direct-push data using a data-driven relevance vector machine approach: Motivations, algorithms, and application

NASA Astrophysics Data System (ADS)

Paradis, Daniel; Lefebvre, René; Gloaguen, Erwan; Rivera, Alfonso

2015-01-01

The spatial heterogeneity of hydraulic conductivity (K) exerts a major control on groundwater flow and solute transport. The heterogeneous spatial distribution of K can be imaged using indirect geophysical data as long as reliable relations exist to link geophysical data to K. This paper presents a nonparametric learning machine approach to predict aquifer K from cone penetrometer tests (CPT) coupled with a soil moisture and resistivity probe (SMR) using relevance vector machines (RVMs). The learning machine approach is demonstrated with an application to a heterogeneous unconsolidated littoral aquifer in a 12 km2 subwatershed, where relations between K and multiparameters CPT/SMR soundings appear complex. Our approach involved fuzzy clustering to define hydrofacies (HF) on the basis of CPT/SMR and K data prior to the training of RVMs for HFs recognition and K prediction on the basis of CPT/SMR data alone. The learning machine was built from a colocated training data set representative of the study area that includes K data from slug tests and CPT/SMR data up-scaled at a common vertical resolution of 15 cm with K data. After training, the predictive capabilities of the learning machine were assessed through cross validation with data withheld from the training data set and with K data from flowmeter tests not used during the training process. Results show that HF and K predictions from the learning machine are consistent with hydraulic tests. The combined use of CPT/SMR data and RVM-based learning machine proved to be powerful and efficient for the characterization of high-resolution K heterogeneity for unconsolidated aquifers.

Computer-generated predictions of the structure and of the IR and Raman spectra of VX. Final report, May-August 1992

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hameka, H.F.; Jensen, J.O.

1993-05-01

This report presents the computed optimized geometry and vibrational IR and Raman frequencies of the V-agent VX. The computations are performed with the Gaussian 90 Program Package using 6-31G* basis sets. We assign the vibrational frequencies and correct each frequency by multiplying it with a previously derived 6-31G* correction factor. The result is a computer-generated prediction of the IR and Raman spectra of VX. This study was intended as a blind test of the utility of IR spectral prediction. Therefore, we intentionally did not look at experimental data on the IR and Raman spectra of VX.... IR Spectra, VX, Ramanmore » spectra, Computer predictions.« less

Gaussian Process Regression (GPR) Representation in Predictive Model Markup Language (PMML)

PubMed Central

Lechevalier, D.; Ak, R.; Ferguson, M.; Law, K. H.; Lee, Y.-T. T.; Rachuri, S.

2017-01-01

This paper describes Gaussian process regression (GPR) models presented in predictive model markup language (PMML). PMML is an extensible-markup-language (XML) -based standard language used to represent data-mining and predictive analytic models, as well as pre- and post-processed data. The previous PMML version, PMML 4.2, did not provide capabilities for representing probabilistic (stochastic) machine-learning algorithms that are widely used for constructing predictive models taking the associated uncertainties into consideration. The newly released PMML version 4.3, which includes the GPR model, provides new features: confidence bounds and distribution for the predictive estimations. Both features are needed to establish the foundation for uncertainty quantification analysis. Among various probabilistic machine-learning algorithms, GPR has been widely used for approximating a target function because of its capability of representing complex input and output relationships without predefining a set of basis functions, and predicting a target output with uncertainty quantification. GPR is being employed to various manufacturing data-analytics applications, which necessitates representing this model in a standardized form for easy and rapid employment. In this paper, we present a GPR model and its representation in PMML. Furthermore, we demonstrate a prototype using a real data set in the manufacturing domain. PMID:29202125

Gaussian Process Regression (GPR) Representation in Predictive Model Markup Language (PMML).

PubMed

Park, J; Lechevalier, D; Ak, R; Ferguson, M; Law, K H; Lee, Y-T T; Rachuri, S

2017-01-01

This paper describes Gaussian process regression (GPR) models presented in predictive model markup language (PMML). PMML is an extensible-markup-language (XML) -based standard language used to represent data-mining and predictive analytic models, as well as pre- and post-processed data. The previous PMML version, PMML 4.2, did not provide capabilities for representing probabilistic (stochastic) machine-learning algorithms that are widely used for constructing predictive models taking the associated uncertainties into consideration. The newly released PMML version 4.3, which includes the GPR model, provides new features: confidence bounds and distribution for the predictive estimations. Both features are needed to establish the foundation for uncertainty quantification analysis. Among various probabilistic machine-learning algorithms, GPR has been widely used for approximating a target function because of its capability of representing complex input and output relationships without predefining a set of basis functions, and predicting a target output with uncertainty quantification. GPR is being employed to various manufacturing data-analytics applications, which necessitates representing this model in a standardized form for easy and rapid employment. In this paper, we present a GPR model and its representation in PMML. Furthermore, we demonstrate a prototype using a real data set in the manufacturing domain.

SWAT system performance predictions

NASA Astrophysics Data System (ADS)

Parenti, Ronald R.; Sasiela, Richard J.

1993-03-01

In the next phase of Lincoln Laboratory's SWAT (Short-Wavelength Adaptive Techniques) program, the performance of a 241-actuator adaptive-optics system will be measured using a variety of synthetic-beacon geometries. As an aid in this experimental investigation, a detailed set of theoretical predictions has also been assembled. The computational tools that have been applied in this study include a numerical approach in which Monte-Carlo ray-trace simulations of accumulated phase error are developed, and an analytical analysis of the expected system behavior. This report describes the basis of these two computational techniques and compares their estimates of overall system performance. Although their regions of applicability tend to be complementary rather than redundant, good agreement is usually obtained when both sets of results can be derived for the same engagement scenario.

Push it to the limit: Characterizing the convergence of common sequences of basis sets for intermolecular interactions as described by density functional theory

NASA Astrophysics Data System (ADS)

Witte, Jonathon; Neaton, Jeffrey B.; Head-Gordon, Martin

2016-05-01

With the aim of systematically characterizing the convergence of common families of basis sets such that general recommendations for basis sets can be made, we have tested a wide variety of basis sets against complete-basis binding energies across the S22 set of intermolecular interactions—noncovalent interactions of small and medium-sized molecules consisting of first- and second-row atoms—with three distinct density functional approximations: SPW92, a form of local-density approximation; B3LYP, a global hybrid generalized gradient approximation; and B97M-V, a meta-generalized gradient approximation with nonlocal correlation. We have found that it is remarkably difficult to reach the basis set limit; for the methods and systems examined, the most complete basis is Jensen's pc-4. The Dunning correlation-consistent sequence of basis sets converges slowly relative to the Jensen sequence. The Karlsruhe basis sets are quite cost effective, particularly when a correction for basis set superposition error is applied: counterpoise-corrected def2-SVPD binding energies are better than corresponding energies computed in comparably sized Dunning and Jensen bases, and on par with uncorrected results in basis sets 3-4 times larger. These trends are exhibited regardless of the level of density functional approximation employed. A sense of the magnitude of the intrinsic incompleteness error of each basis set not only provides a foundation for guiding basis set choice in future studies but also facilitates quantitative comparison of existing studies on similar types of systems.

Benchmark calculations with correlated molecular wavefunctions. XIII. Potential energy curves for He2, Ne2 and Ar2 using correlation consistent basis sets through augmented sextuple zeta

NASA Astrophysics Data System (ADS)

van Mourik, Tanja

1999-02-01

The potential energy curves of the rare gas dimers He2, Ne2, and Ar2 have been computed using correlation consistent basis sets ranging from singly augmented aug-cc-pVDZ sets through triply augmented t-aug-cc-pV6Z sets, with the augmented sextuple basis sets being reported herein. Several methods for including electron correlation were investigated, namely Moller-Plesset perturbation theory (MP2, MP3 and MP4) and coupled cluster theory [CCSD and CCSD(T)]. For He2CCSD(T)/d-aug-cc-pV6Z calculations yield a well depth of 7.35cm-1 (10.58K), with an estimated complete basis set (CBS) limit of 7.40cm-1 (10.65K). The latter is smaller than the 'exact' well depth (Aziz, R. A., Janzen, A. R., and Moldover, M. R., 1995, Phys. Rev. Lett., 74, 1586) by about 0.2cm-1 (0.35K). The Ne well depth, computed with the CCSD(T)/d-aug-cc-pV6Z method, is 28.31cm-1 and the estimated CBS limit is 28.4cm-1, approximately 1cm-1 smaller than the empirical potential of Aziz, R. A., and Slaman, M., J., 1989, Chem. Phys., 130, 187. Inclusion of core and core-valence correlation effects has a negligible effect on the Ne well depth, decreasing it by only 0.04cm-1. For Ar2, CCSD(T)/ d-aug-cc-pV6Z calculations yield a well depth of 96.2cm-1. The corresponding HFDID potential of Aziz, R. A., 1993, J. chem. Phys., 99, 4518 predicts of D of 99.7cm-1. Inclusion of core and core-valence effects in Ar increases the well depth and decreases the discrepancy by approximately 1cm-1.

Using GPS, GIS, and Accelerometer Data to Predict Transportation Modes.

PubMed

Brondeel, Ruben; Pannier, Bruno; Chaix, Basile

2015-12-01

Active transportation is a substantial source of physical activity, which has a positive influence on many health outcomes. A survey of transportation modes for each trip is challenging, time-consuming, and requires substantial financial investments. This study proposes a passive collection method and the prediction of modes at the trip level using random forests. The RECORD GPS study collected real-life trip data from 236 participants over 7 d, including the transportation mode, global positioning system, geographical information systems, and accelerometer data. A prediction model of transportation modes was constructed using the random forests method. Finally, we investigated the performance of models on the basis of a limited number of participants/trips to predict transportation modes for a large number of trips. The full model had a correct prediction rate of 90%. A simpler model of global positioning system explanatory variables combined with geographical information systems variables performed nearly as well. Relatively good predictions could be made using a model based on the 991 trips of the first 30 participants. This study uses real-life data from a large sample set to test a method for predicting transportation modes at the trip level, thereby providing a useful complement to time unit-level prediction methods. By enabling predictions on the basis of a limited number of observations, this method may decrease the workload for participants/researchers and provide relevant trip-level data to investigate relations between transportation and health.

Simultaneous determination of three herbicides by differential pulse voltammetry and chemometrics.

PubMed

Ni, Yongnian; Wang, Lin; Kokot, Serge

2011-01-01

A novel differential pulse voltammetry method (DPV) was researched and developed for the simultaneous determination of Pendimethalin, Dinoseb and sodium 5-nitroguaiacolate (5NG) with the aid of chemometrics. The voltammograms of these three compounds overlapped significantly, and to facilitate the simultaneous determination of the three analytes, chemometrics methods were applied. These included classical least squares (CLS), principal component regression (PCR), partial least squares (PLS) and radial basis function-artificial neural networks (RBF-ANN). A separately prepared verification data set was used to confirm the calibrations, which were built from the original and first derivative data matrices of the voltammograms. On the basis relative prediction errors and recoveries of the analytes, the RBF-ANN and the DPLS (D - first derivative spectra) models performed best and are particularly recommended for application. The DPLS calibration model was applied satisfactorily for the prediction of the three analytes from market vegetables and lake water samples.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moore, Keith; McLaughlin, Brendan M.; Lane, Ian C., E-mail: i.lane@qub.ac.uk

BaH (and its isotopomers) is an attractive molecular candidate for laser cooling to ultracold temperatures and a potential precursor for the production of ultracold gases of hydrogen and deuterium. The theoretical challenge is to simulate the laser cooling cycle as reliably as possible and this paper addresses the generation of a highly accurate ab initio {sup 2}Σ{sup +} potential for such studies. The performance of various basis sets within the multi-reference configuration-interaction (MRCI) approximation with the Davidson correction is tested and taken to the Complete Basis Set (CBS) limit. It is shown that the calculated molecular constants using a 46more » electron effective core-potential and even-tempered augmented polarized core-valence basis sets (aug-pCVnZ-PP, n = 4 and 5) but only including three active electrons in the MRCI calculation are in excellent agreement with the available experimental values. The predicted dissociation energy D{sub e} for the X{sup 2}Σ{sup +} state (extrapolated to the CBS limit) is 16 895.12 cm{sup −1} (2.094 eV), which agrees within 0.1% of a revised experimental value of <16 910.6 cm{sup −1}, while the calculated r{sub e} is within 0.03 pm of the experimental result.« less

Microarray-based cancer prediction using soft computing approach.

PubMed

Wang, Xiaosheng; Gotoh, Osamu

2009-05-26

One of the difficulties in using gene expression profiles to predict cancer is how to effectively select a few informative genes to construct accurate prediction models from thousands or ten thousands of genes. We screen highly discriminative genes and gene pairs to create simple prediction models involved in single genes or gene pairs on the basis of soft computing approach and rough set theory. Accurate cancerous prediction is obtained when we apply the simple prediction models for four cancerous gene expression datasets: CNS tumor, colon tumor, lung cancer and DLBCL. Some genes closely correlated with the pathogenesis of specific or general cancers are identified. In contrast with other models, our models are simple, effective and robust. Meanwhile, our models are interpretable for they are based on decision rules. Our results demonstrate that very simple models may perform well on cancerous molecular prediction and important gene markers of cancer can be detected if the gene selection approach is chosen reasonably.

Comparison of Multiple Linear Regressions and Neural Networks based QSAR models for the design of new antitubercular compounds.

PubMed

Ventura, Cristina; Latino, Diogo A R S; Martins, Filomena

2013-01-01

The performance of two QSAR methodologies, namely Multiple Linear Regressions (MLR) and Neural Networks (NN), towards the modeling and prediction of antitubercular activity was evaluated and compared. A data set of 173 potentially active compounds belonging to the hydrazide family and represented by 96 descriptors was analyzed. Models were built with Multiple Linear Regressions (MLR), single Feed-Forward Neural Networks (FFNNs), ensembles of FFNNs and Associative Neural Networks (AsNNs) using four different data sets and different types of descriptors. The predictive ability of the different techniques used were assessed and discussed on the basis of different validation criteria and results show in general a better performance of AsNNs in terms of learning ability and prediction of antitubercular behaviors when compared with all other methods. MLR have, however, the advantage of pinpointing the most relevant molecular characteristics responsible for the behavior of these compounds against Mycobacterium tuberculosis. The best results for the larger data set (94 compounds in training set and 18 in test set) were obtained with AsNNs using seven descriptors (R(2) of 0.874 and RMSE of 0.437 against R(2) of 0.845 and RMSE of 0.472 in MLRs, for test set). Counter-Propagation Neural Networks (CPNNs) were trained with the same data sets and descriptors. From the scrutiny of the weight levels in each CPNN and the information retrieved from MLRs, a rational design of potentially active compounds was attempted. Two new compounds were synthesized and tested against M. tuberculosis showing an activity close to that predicted by the majority of the models. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Witte, Jonathon; Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, California 94720; Neaton, Jeffrey B.

With the aim of systematically characterizing the convergence of common families of basis sets such that general recommendations for basis sets can be made, we have tested a wide variety of basis sets against complete-basis binding energies across the S22 set of intermolecular interactions—noncovalent interactions of small and medium-sized molecules consisting of first- and second-row atoms—with three distinct density functional approximations: SPW92, a form of local-density approximation; B3LYP, a global hybrid generalized gradient approximation; and B97M-V, a meta-generalized gradient approximation with nonlocal correlation. We have found that it is remarkably difficult to reach the basis set limit; for the methodsmore » and systems examined, the most complete basis is Jensen’s pc-4. The Dunning correlation-consistent sequence of basis sets converges slowly relative to the Jensen sequence. The Karlsruhe basis sets are quite cost effective, particularly when a correction for basis set superposition error is applied: counterpoise-corrected def2-SVPD binding energies are better than corresponding energies computed in comparably sized Dunning and Jensen bases, and on par with uncorrected results in basis sets 3-4 times larger. These trends are exhibited regardless of the level of density functional approximation employed. A sense of the magnitude of the intrinsic incompleteness error of each basis set not only provides a foundation for guiding basis set choice in future studies but also facilitates quantitative comparison of existing studies on similar types of systems.« less

An extrapolation method for compressive strength prediction of hydraulic cement products

DOE Office of Scientific and Technical Information (OSTI.GOV)

Siqueira Tango, C.E. de

1998-07-01

The basis for the AMEBA Method is presented. A strength-time function is used to extrapolate the predicted cementitious material strength for a late (ALTA) age, based on two earlier age strengths--medium (MEDIA) and low (BAIXA) ages. The experimental basis for the method is data from the IPT-Brazil laboratory and the field, including a long-term study on concrete, research on limestone, slag, and fly-ash additions, and quality control data from a cement factory, a shotcrete tunnel lining, and a grout for structural repair. The method applicability was also verified for high-performance concrete with silica fume. The formula for predicting late agemore » (e.g., 28 days) strength, for a given set of involved ages (e.g., 28,7, and 2 days) is normally a function only of the two earlier ages` (e.g., 7 and 2 days) strengths. This equation has been shown to be independent on materials variations, including cement brand, and is easy to use also graphically. Using the AMEBA method, and only needing to know the type of cement used, it has been possible to predict strengths satisfactorily, even without the preliminary tests which are required in other methods.« less

Prediction of lymph node parasite load from clinical data in dogs with leishmaniasis: An application of radial basis artificial neural networks.

PubMed

Torrecilha, Rafaela Beatriz Pintor; Utsunomiya, Yuri Tani; Batista, Luís Fábio da Silva; Bosco, Anelise Maria; Nunes, Cáris Maroni; Ciarlini, Paulo César; Laurenti, Márcia Dalastra

2017-01-30

Quantification of Leishmania infantum load via real-time quantitative polymerase chain reaction (qPCR) in lymph node aspirates is an accurate tool for diagnostics, surveillance and therapeutics follow-up in dogs with leishmaniasis. However, qPCR requires infrastructure and technical training that is not always available commercially or in public services. Here, we used a machine learning technique, namely Radial Basis Artificial Neural Network, to assess whether parasite load could be learned from clinical data (serological test, biochemical markers and physical signs). By comparing 18 different combinations of input clinical data, we found that parasite load can be accurately predicted using a relatively small reference set of 35 naturally infected dogs and 20 controls. In the best case scenario (use of all clinical data), predictions presented no bias or inflation and an accuracy (i.e., correlation between true and predicted values) of 0.869, corresponding to an average error of ±38.2 parasites per unit of volume. We conclude that reasonable estimates of L. infantum load from lymph node aspirates can be obtained from clinical records when qPCR services are not available. Copyright © 2016 Elsevier B.V. All rights reserved.

Experimental and theoretical study on DPPH radical scavenging mechanism of some chalcone quinoline derivatives

NASA Astrophysics Data System (ADS)

Hamlaoui, Ikram; Bencheraiet, Reguia; Bensegueni, Rafik; Bencharif, Mustapha

2018-03-01

In this study, the antioxidant capacity of three chalcone derivatives was evaluated by DPPH free radical scavenging. Experimental data showed low antioxidant activity (IC50±SD) of these molecules in comparison with BHT. The mechanism of DPPH radical scavenging elucidated by means of density functional theory (DFT) calculations. The tested compounds and their corresponding radicals and anions were optimized using B3LYP functional with 6-31G (d,p) basis set in the gas phase. The C-PCM model was used to perform solvent medium calculations. On the basis of theoretical calculations, it was shown that HAT mechanism was predominant in the gas phase, whereas SET-PT and SPLET mechanisms were favored in the presence of the solvent. Moreover, the HOMO orbitals and spin density distribution was evaluated to predict the probable sites for free radical attack.

A theoretical study of potentially observable chirality-sensitive NMR effects in molecules.

PubMed

Garbacz, Piotr; Cukras, Janusz; Jaszuński, Michał

2015-09-21

Two recently predicted nuclear magnetic resonance effects, the chirality-induced rotating electric polarization and the oscillating magnetization, are examined for several experimentally available chiral molecules. We discuss in detail the requirements for experimental detection of chirality-sensitive NMR effects of the studied molecules. These requirements are related to two parameters: the shielding polarizability and the antisymmetric part of the nuclear magnetic shielding tensor. The dominant second contribution has been computed for small molecules at the coupled cluster and density functional theory levels. It was found that DFT calculations using the KT2 functional and the aug-cc-pCVTZ basis set adequately reproduce the CCSD(T) values obtained with the same basis set. The largest values of parameters, thus most promising from the experimental point of view, were obtained for the fluorine nuclei in 1,3-difluorocyclopropene and 1,3-diphenyl-2-fluoro-3-trifluoromethylcyclopropene.

Theoretical study of the diatomic alkali and alkaline-earth oxides

NASA Technical Reports Server (NTRS)

Langhoff, S. R.; Bauschlicher, C. W., Jr.; Partridge, H.

1986-01-01

Theoretical dissociation energies for the ground states of the alkali and alkaline earth oxides are presented that are believed to be accurate to 0.1 eV. The 2 Pi - 2 Sigma + separations for the alkali oxides are found to be more sensitive to basis set than to electron correlation. Predicted 2 Pi ground states for LiO and NaO and 2 Sigma + ground states for RbO and CsO are found to be in agreement with previous theoretical and experimental work. For KO, a 2 Sigma + state is found at both the numerical Hartree-Fock (NHF) level and at the singles plus doubles configuration interaction level using a Slater basis set that is within 0.02 eV of the NHF limit. It is found that an accurate balanced treatment of the two states requires correlating the electrons on both the metal and oxide ion.

A Bayesian spatial model for neuroimaging data based on biologically informed basis functions.

PubMed

Huertas, Ismael; Oldehinkel, Marianne; van Oort, Erik S B; Garcia-Solis, David; Mir, Pablo; Beckmann, Christian F; Marquand, Andre F

2017-11-01

The dominant approach to neuroimaging data analysis employs the voxel as the unit of computation. While convenient, voxels lack biological meaning and their size is arbitrarily determined by the resolution of the image. Here, we propose a multivariate spatial model in which neuroimaging data are characterised as a linearly weighted combination of multiscale basis functions which map onto underlying brain nuclei or networks or nuclei. In this model, the elementary building blocks are derived to reflect the functional anatomy of the brain during the resting state. This model is estimated using a Bayesian framework which accurately quantifies uncertainty and automatically finds the most accurate and parsimonious combination of basis functions describing the data. We demonstrate the utility of this framework by predicting quantitative SPECT images of striatal dopamine function and we compare a variety of basis sets including generic isotropic functions, anatomical representations of the striatum derived from structural MRI, and two different soft functional parcellations of the striatum derived from resting-state fMRI (rfMRI). We found that a combination of ∼50 multiscale functional basis functions accurately represented the striatal dopamine activity, and that functional basis functions derived from an advanced parcellation technique known as Instantaneous Connectivity Parcellation (ICP) provided the most parsimonious models of dopamine function. Importantly, functional basis functions derived from resting fMRI were more accurate than both structural and generic basis sets in representing dopamine function in the striatum for a fixed model order. We demonstrate the translational validity of our framework by constructing classification models for discriminating parkinsonian disorders and their subtypes. Here, we show that ICP approach is the only basis set that performs well across all comparisons and performs better overall than the classical voxel-based approach. This spatial model constitutes an elegant alternative to voxel-based approaches in neuroimaging studies; not only are their atoms biologically informed, they are also adaptive to high resolutions, represent high dimensions efficiently, and capture long-range spatial dependencies, which are important and challenging objectives for neuroimaging data. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Accuracy of Lagrange-sinc functions as a basis set for electronic structure calculations of atoms and molecules

DOE Office of Scientific and Technical Information (OSTI.GOV)

Choi, Sunghwan; Hong, Kwangwoo; Kim, Jaewook

2015-03-07

We developed a self-consistent field program based on Kohn-Sham density functional theory using Lagrange-sinc functions as a basis set and examined its numerical accuracy for atoms and molecules through comparison with the results of Gaussian basis sets. The result of the Kohn-Sham inversion formula from the Lagrange-sinc basis set manifests that the pseudopotential method is essential for cost-effective calculations. The Lagrange-sinc basis set shows faster convergence of the kinetic and correlation energies of benzene as its size increases than the finite difference method does, though both share the same uniform grid. Using a scaling factor smaller than or equal tomore » 0.226 bohr and pseudopotentials with nonlinear core correction, its accuracy for the atomization energies of the G2-1 set is comparable to all-electron complete basis set limits (mean absolute deviation ≤1 kcal/mol). The same basis set also shows small mean absolute deviations in the ionization energies, electron affinities, and static polarizabilities of atoms in the G2-1 set. In particular, the Lagrange-sinc basis set shows high accuracy with rapid convergence in describing density or orbital changes by an external electric field. Moreover, the Lagrange-sinc basis set can readily improve its accuracy toward a complete basis set limit by simply decreasing the scaling factor regardless of systems.« less

The harmonic frequencies of benzene

NASA Astrophysics Data System (ADS)

Handy, Nicholas C.; Maslen, Paul E.; Amos, Roger D.; Andrews, Jamie S.; Murray, Christopher W.; Laming, Gregory J.

1992-09-01

We report calculations for the harmonic frequencies of C 6H 6 and C 6D 6. Our most sophisticated quantum chemistry values are obtained with the MP2 method and a TZ2P+f basis set (288 basis functions), which are the largest such calculations reported on benzene to date. Using the SCF density, we also calculate the frequencies using the exchange and correlation expressions of density functional theory. We compare our calculated harmonic frequencies with those deduced from experiment by Goodman, Ozkabak and Thakur. The density functional frequencies appear to be more reliable predictions than the MP2 frequencies and they are obtained at significantly less cost.

Prediction of mandibular rotation: an empirical test of clinician performance.

PubMed

Baumrind, S; Korn, E L; West, E E

1984-11-01

An experiment was conducted in an attempt to determine empirically how effective a number of expert clinicians were at differentiating "backward rotators" from "forward rotators" on the basis of head-film information which might reasonably have been available to them prior to instituting treatment for the correction of Class II malocclusion. As a result of a previously reported ongoing study, pre- and posttreatment head films were available for 188 patients treated in the mixed dentition for the correction of Class II malocclusion and for 50 untreated Class II subjects. These subjects were divided into 14 groups (average size of group, 17; range, 6 to 23) solely on the basis of type of treatment and the clinician from whose clinic the records had originated. From within each group, we selected the two or three subjects who had exhibited the most extreme backward rotation and the two or three subjects who had exhibited the most extreme forward rotation of the mandible during the interval between films. The sole criterion for classification was magnitude of change in the mandibular plane angle of Downs between the pre- and posttreatment films of each patient. The resulting sample contained 32 backward-rotator subjects and 32 forward-rotator subjects. Five expert judges (mean clinical experience, 28 years) were asked to identify the backward-rotator subjects by examination of the pretreatment films. The findings may be summarized as follows: (1) No judge performed significantly better than chance. (2) There was strong evidence that the judges used a shared, though relatively ineffective, set of rules in making their discriminations between forward and backward rotators. (3) Statistical analysis of the predictive power of a set of standard cephalometric measurements which had previously been made for this set of subjects indicated that the numerical data also failed to identify potential backward rotators at a rate significantly better than chance. We infer from these findings that the ability of clinicians to identify backward rotators on the basis of information available at the outset of treatment is poor. Hence, we believe that it is unlikely that such predictions play any consequential operational role in the planning of successful orthodontic therapy at the present state of the art.

Optimization of selected molecular orbitals in group basis sets.

PubMed

Ferenczy, György G; Adams, William H

2009-04-07

We derive a local basis equation which may be used to determine the orbitals of a group of electrons in a system when the orbitals of that group are represented by a group basis set, i.e., not the basis set one would normally use but a subset suited to a specific electronic group. The group orbitals determined by the local basis equation minimize the energy of a system when a group basis set is used and the orbitals of other groups are frozen. In contrast, under the constraint of a group basis set, the group orbitals satisfying the Huzinaga equation do not minimize the energy. In a test of the local basis equation on HCl, the group basis set included only 12 of the 21 functions in a basis set one might ordinarily use, but the calculated active orbital energies were within 0.001 hartree of the values obtained by solving the Hartree-Fock-Roothaan (HFR) equation using all 21 basis functions. The total energy found was just 0.003 hartree higher than the HFR value. The errors with the group basis set approximation to the Huzinaga equation were larger by over two orders of magnitude. Similar results were obtained for PCl(3) with the group basis approximation. Retaining more basis functions allows an even higher accuracy as shown by the perfect reproduction of the HFR energy of HCl with 16 out of 21 basis functions in the valence basis set. When the core basis set was also truncated then no additional error was introduced in the calculations performed for HCl with various basis sets. The same calculations with fixed core orbitals taken from isolated heavy atoms added a small error of about 10(-4) hartree. This offers a practical way to calculate wave functions with predetermined fixed core and reduced base valence orbitals at reduced computational costs. The local basis equation can also be used to combine the above approximations with the assignment of local basis sets to groups of localized valence molecular orbitals and to derive a priori localized orbitals. An appropriately chosen localization and basis set assignment allowed a reproduction of the energy of n-hexane with an error of 10(-5) hartree, while the energy difference between its two conformers was reproduced with a similar accuracy for several combinations of localizations and basis set assignments. These calculations include localized orbitals extending to 4-5 heavy atoms and thus they require to solve reduced dimension secular equations. The dimensions are not expected to increase with increasing system size and thus the local basis equation may find use in linear scaling electronic structure calculations.

Prediction of resource volumes at untested locations using simple local prediction models

USGS Publications Warehouse

Attanasi, E.D.; Coburn, T.C.; Freeman, P.A.

2006-01-01

This paper shows how local spatial nonparametric prediction models can be applied to estimate volumes of recoverable gas resources at individual undrilled sites, at multiple sites on a regional scale, and to compute confidence bounds for regional volumes based on the distribution of those estimates. An approach that combines cross-validation, the jackknife, and bootstrap procedures is used to accomplish this task. Simulation experiments show that cross-validation can be applied beneficially to select an appropriate prediction model. The cross-validation procedure worked well for a wide range of different states of nature and levels of information. Jackknife procedures are used to compute individual prediction estimation errors at undrilled locations. The jackknife replicates also are used with a bootstrap resampling procedure to compute confidence bounds for the total volume. The method was applied to data (partitioned into a training set and target set) from the Devonian Antrim Shale continuous-type gas play in the Michigan Basin in Otsego County, Michigan. The analysis showed that the model estimate of total recoverable volumes at prediction sites is within 4 percent of the total observed volume. The model predictions also provide frequency distributions of the cell volumes at the production unit scale. Such distributions are the basis for subsequent economic analyses. ?? Springer Science+Business Media, LLC 2007.

Predictive analysis of beer quality by correlating sensory evaluation with higher alcohol and ester production using multivariate statistics methods.

PubMed

Dong, Jian-Jun; Li, Qing-Liang; Yin, Hua; Zhong, Cheng; Hao, Jun-Guang; Yang, Pan-Fei; Tian, Yu-Hong; Jia, Shi-Ru

2014-10-15

Sensory evaluation is regarded as a necessary procedure to ensure a reproducible quality of beer. Meanwhile, high-throughput analytical methods provide a powerful tool to analyse various flavour compounds, such as higher alcohol and ester. In this study, the relationship between flavour compounds and sensory evaluation was established by non-linear models such as partial least squares (PLS), genetic algorithm back-propagation neural network (GA-BP), support vector machine (SVM). It was shown that SVM with a Radial Basis Function (RBF) had a better performance of prediction accuracy for both calibration set (94.3%) and validation set (96.2%) than other models. Relatively lower prediction abilities were observed for GA-BP (52.1%) and PLS (31.7%). In addition, the kernel function of SVM played an essential role of model training when the prediction accuracy of SVM with polynomial kernel function was 32.9%. As a powerful multivariate statistics method, SVM holds great potential to assess beer quality. Copyright © 2014 Elsevier Ltd. All rights reserved.

Predictive Genomic Analyses Inform the Basis for Vitamin Metabolism and Provisioning in Bacteria-Arthropod Endosymbioses

PubMed Central

Serbus, Laura R.; Rodriguez, Brian Garcia; Sharmin, Zinat; Momtaz, A. J. M. Zehadee; Christensen, Steen

2017-01-01

The requirement of vitamins for core metabolic processes creates a unique set of pressures for arthropods subsisting on nutrient-limited diets. While endosymbiotic bacteria carried by arthropods have been widely implicated in vitamin provisioning, the underlying molecular mechanisms are not well understood. To address this issue, standardized predictive assessment of vitamin metabolism was performed in 50 endosymbionts of insects and arachnids. The results predicted that arthropod endosymbionts overall have little capacity for complete de novo biosynthesis of conventional or active vitamin forms. Partial biosynthesis pathways were commonly predicted, suggesting a substantial role in vitamin provisioning. Neither taxonomic relationships between host and symbiont, nor the mode of host-symbiont interaction were clear predictors of endosymbiont vitamin pathway capacity. Endosymbiont genome size and the synthetic capacity of nonsymbiont taxonomic relatives were more reliable predictors. We developed a new software application that also predicted that last-step conversion of intermediates into active vitamin forms may contribute further to vitamin biosynthesis by endosymbionts. Most instances of predicted vitamin conversion were paralleled by predictions of vitamin use. This is consistent with achievement of provisioning in some cases through upregulation of pathways that were retained for endosymbiont benefit. The predicted absence of other enzyme classes further suggests a baseline of vitamin requirement by the majority of endosymbionts, as well as some instances of putative mutualism. Adaptation of this workflow to analysis of other organisms and metabolic pathways will provide new routes for considering the molecular basis for symbiosis on a comprehensive scale. PMID:28455417

Accurate Methods for Large Molecular Systems (Preprint)

DTIC Science & Technology

2009-01-06

tensor, EFP calculations are basis set dependent. The smallest recommended basis set is 6- 31++G( d , p )52 The dependence of the computational cost of...and second order perturbation theory (MP2) levels with the 6-31G( d , p ) basis set. Additional SFM tests are presented for a small set of alpha...helices using the 6-31++G( d , p ) basis set. The larger 6-311++G(3df,2p) basis set is employed for creating all EFPs used for non- bonded interactions, since

Qualification Testing Versus Quantitative Reliability Testing of PV - Gaining Confidence in a Rapidly Changing Technology: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kurtz, Sarah; Repins, Ingrid L; Hacke, Peter L

Continued growth of PV system deployment would be enhanced by quantitative, low-uncertainty predictions of the degradation and failure rates of PV modules and systems. The intended product lifetime (decades) far exceeds the product development cycle (months), limiting our ability to reduce the uncertainty of the predictions for this rapidly changing technology. Yet, business decisions (setting insurance rates, analyzing return on investment, etc.) require quantitative risk assessment. Moving toward more quantitative assessments requires consideration of many factors, including the intended application, consequence of a possible failure, variability in the manufacturing, installation, and operation, as well as uncertainty in the measured accelerationmore » factors, which provide the basis for predictions based on accelerated tests. As the industry matures, it is useful to periodically assess the overall strategy for standards development and prioritization of research to provide a technical basis both for the standards and the analysis related to the application of those. To this end, this paper suggests a tiered approach to creating risk assessments. Recent and planned potential improvements in international standards are also summarized.« less

Predicting breast cancer using an expression values weighted clinical classifier.

PubMed

Thomas, Minta; De Brabanter, Kris; Suykens, Johan A K; De Moor, Bart

2014-12-31

Clinical data, such as patient history, laboratory analysis, ultrasound parameters-which are the basis of day-to-day clinical decision support-are often used to guide the clinical management of cancer in the presence of microarray data. Several data fusion techniques are available to integrate genomics or proteomics data, but only a few studies have created a single prediction model using both gene expression and clinical data. These studies often remain inconclusive regarding an obtained improvement in prediction performance. To improve clinical management, these data should be fully exploited. This requires efficient algorithms to integrate these data sets and design a final classifier. LS-SVM classifiers and generalized eigenvalue/singular value decompositions are successfully used in many bioinformatics applications for prediction tasks. While bringing up the benefits of these two techniques, we propose a machine learning approach, a weighted LS-SVM classifier to integrate two data sources: microarray and clinical parameters. We compared and evaluated the proposed methods on five breast cancer case studies. Compared to LS-SVM classifier on individual data sets, generalized eigenvalue decomposition (GEVD) and kernel GEVD, the proposed weighted LS-SVM classifier offers good prediction performance, in terms of test area under ROC Curve (AUC), on all breast cancer case studies. Thus a clinical classifier weighted with microarray data set results in significantly improved diagnosis, prognosis and prediction responses to therapy. The proposed model has been shown as a promising mathematical framework in both data fusion and non-linear classification problems.

Approaching the theoretical limit in periodic local MP2 calculations with atomic-orbital basis sets: the case of LiH.

PubMed

Usvyat, Denis; Civalleri, Bartolomeo; Maschio, Lorenzo; Dovesi, Roberto; Pisani, Cesare; Schütz, Martin

2011-06-07

The atomic orbital basis set limit is approached in periodic correlated calculations for solid LiH. The valence correlation energy is evaluated at the level of the local periodic second order Møller-Plesset perturbation theory (MP2), using basis sets of progressively increasing size, and also employing "bond"-centered basis functions in addition to the standard atom-centered ones. Extended basis sets, which contain linear dependencies, are processed only at the MP2 stage via a dual basis set scheme. The local approximation (domain) error has been consistently eliminated by expanding the orbital excitation domains. As a final result, it is demonstrated that the complete basis set limit can be reached for both HF and local MP2 periodic calculations, and a general scheme is outlined for the definition of high-quality atomic-orbital basis sets for solids. © 2011 American Institute of Physics

An expanded calibration study of the explicitly correlated CCSD(T)-F12b method using large basis set standard CCSD(T) atomization energies.

PubMed

Feller, David; Peterson, Kirk A

2013-08-28

The effectiveness of the recently developed, explicitly correlated coupled cluster method CCSD(T)-F12b is examined in terms of its ability to reproduce atomization energies derived from complete basis set extrapolations of standard CCSD(T). Most of the standard method findings were obtained with aug-cc-pV7Z or aug-cc-pV8Z basis sets. For a few homonuclear diatomic molecules it was possible to push the basis set to the aug-cc-pV9Z level. F12b calculations were performed with the cc-pVnZ-F12 (n = D, T, Q) basis set sequence and were also extrapolated to the basis set limit using a Schwenke-style, parameterized formula. A systematic bias was observed in the F12b method with the (VTZ-F12/VQZ-F12) basis set combination. This bias resulted in the underestimation of reference values associated with small molecules (valence correlation energies <0.5 E(h)) and an even larger overestimation of atomization energies for bigger systems. Consequently, caution should be exercised in the use of F12b for high accuracy studies. Root mean square and mean absolute deviation error metrics for this basis set combination were comparable to complete basis set values obtained with standard CCSD(T) and the aug-cc-pVDZ through aug-cc-pVQZ basis set sequence. However, the mean signed deviation was an order of magnitude larger. Problems partially due to basis set superposition error were identified with second row compounds which resulted in a weak performance for the smaller VDZ-F12/VTZ-F12 combination of basis sets.

Children reading spoken words: interactions between vocabulary and orthographic expectancy.

PubMed

Wegener, Signy; Wang, Hua-Chen; de Lissa, Peter; Robidoux, Serje; Nation, Kate; Castles, Anne

2018-05-01

There is an established association between children's oral vocabulary and their word reading but its basis is not well understood. Here, we present evidence from eye movements for a novel mechanism underlying this association. Two groups of 18 Grade 4 children received oral vocabulary training on one set of 16 novel words (e.g., 'nesh', 'coib'), but no training on another set. The words were assigned spellings that were either predictable from phonology (e.g., nesh) or unpredictable (e.g., koyb). These were subsequently shown in print, embedded in sentences. Reading times were shorter for orally familiar than unfamiliar items, and for words with predictable than unpredictable spellings but, importantly, there was an interaction between the two: children demonstrated a larger benefit of oral familiarity for predictable than for unpredictable items. These findings indicate that children form initial orthographic expectations about spoken words before first seeing them in print. A video abstract of this article can be viewed at: https://youtu.be/jvpJwpKMM3E. © 2017 John Wiley & Sons Ltd.

From Molecular Docking to 3D-Quantitative Structure-Activity Relationships (3D-QSAR): Insights into the Binding Mode of 5-Lipoxygenase Inhibitors.

PubMed

Eren, Gokcen; Macchiarulo, Antonio; Banoglu, Erden

2012-02-01

Pharmacological intervention with 5-Lipoxygenase (5-LO) is a promising strategy for treatment of inflammatory and allergic ailments, including asthma. With the aim of developing predictive models of 5-LO affinity and gaining insights into the molecular basis of ligand-target interaction, we herein describe QSAR studies of 59 diverse nonredox-competitive 5-LO inhibitors based on the use of molecular shape descriptors and docking experiments. These studies have successfully yielded a predictive model able to explain much of the variance in the activity of the training set compounds while predicting satisfactorily the 5-LO inhibitory activity of an external test set of compounds. The inspection of the selected variables in the QSAR equation unveils the importance of specific interactions which are observed from docking experiments. Collectively, these results may be used to design novel potent and selective nonredox 5-LO inhibitors. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Metabolomics for organic food authentication: Results from a long-term field study in carrots.

PubMed

Cubero-Leon, Elena; De Rudder, Olivier; Maquet, Alain

2018-01-15

Increasing demand for organic products and their premium prices make them an attractive target for fraudulent malpractices. In this study, a large-scale comparative metabolomics approach was applied to investigate the effect of the agronomic production system on the metabolite composition of carrots and to build statistical models for prediction purposes. Orthogonal projections to latent structures-discriminant analysis (OPLS-DA) was applied successfully to predict the origin of the agricultural system of the harvested carrots on the basis of features determined by liquid chromatography-mass spectrometry. When the training set used to build the OPLS-DA models contained samples representative of each harvest year, the models were able to classify unknown samples correctly (100% correct classification). If a harvest year was left out of the training sets and used for predictions, the correct classification rates achieved ranged from 76% to 100%. The results therefore highlight the potential of metabolomic fingerprinting for organic food authentication purposes. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Predictability of machine learning techniques to forecast the trends of market index prices: Hypothesis testing for the Korean stock markets.

PubMed

Pyo, Sujin; Lee, Jaewook; Cha, Mincheol; Jang, Huisu

2017-01-01

The prediction of the trends of stocks and index prices is one of the important issues to market participants. Investors have set trading or fiscal strategies based on the trends, and considerable research in various academic fields has been studied to forecast financial markets. This study predicts the trends of the Korea Composite Stock Price Index 200 (KOSPI 200) prices using nonparametric machine learning models: artificial neural network, support vector machines with polynomial and radial basis function kernels. In addition, this study states controversial issues and tests hypotheses about the issues. Accordingly, our results are inconsistent with those of the precedent research, which are generally considered to have high prediction performance. Moreover, Google Trends proved that they are not effective factors in predicting the KOSPI 200 index prices in our frameworks. Furthermore, the ensemble methods did not improve the accuracy of the prediction.

Predictability of machine learning techniques to forecast the trends of market index prices: Hypothesis testing for the Korean stock markets

PubMed Central

Pyo, Sujin; Lee, Jaewook; Cha, Mincheol

2017-01-01

The prediction of the trends of stocks and index prices is one of the important issues to market participants. Investors have set trading or fiscal strategies based on the trends, and considerable research in various academic fields has been studied to forecast financial markets. This study predicts the trends of the Korea Composite Stock Price Index 200 (KOSPI 200) prices using nonparametric machine learning models: artificial neural network, support vector machines with polynomial and radial basis function kernels. In addition, this study states controversial issues and tests hypotheses about the issues. Accordingly, our results are inconsistent with those of the precedent research, which are generally considered to have high prediction performance. Moreover, Google Trends proved that they are not effective factors in predicting the KOSPI 200 index prices in our frameworks. Furthermore, the ensemble methods did not improve the accuracy of the prediction. PMID:29136004

Statistical prediction of dynamic distortion of inlet flow using minimum dynamic measurement. An application to the Melick statistical method and inlet flow dynamic distortion prediction without RMS measurements

NASA Technical Reports Server (NTRS)

Schweikhard, W. G.; Chen, Y. S.

1986-01-01

The Melick method of inlet flow dynamic distortion prediction by statistical means is outlined. A hypothetic vortex model is used as the basis for the mathematical formulations. The main variables are identified by matching the theoretical total pressure rms ratio with the measured total pressure rms ratio. Data comparisons, using the HiMAT inlet test data set, indicate satisfactory prediction of the dynamic peak distortion for cases with boundary layer control device vortex generators. A method for the dynamic probe selection was developed. Validity of the probe selection criteria is demonstrated by comparing the reduced-probe predictions with the 40-probe predictions. It is indicated that the the number of dynamic probes can be reduced to as few as two and still retain good accuracy.

Endoscopic third ventriculostomy in the treatment of childhood hydrocephalus.

PubMed

Kulkarni, Abhaya V; Drake, James M; Mallucci, Conor L; Sgouros, Spyros; Roth, Jonathan; Constantini, Shlomi

2009-08-01

To develop a model to predict the probability of endoscopic third ventriculostomy (ETV) success in the treatment for hydrocephalus on the basis of a child's individual characteristics. We analyzed 618 ETVs performed consecutively on children at 12 international institutions to identify predictors of ETV success at 6 months. A multivariable logistic regression model was developed on 70% of the dataset (training set) and validated on 30% of the dataset (validation set). In the training set, 305/455 ETVs (67.0%) were successful. The regression model (containing patient age, cause of hydrocephalus, and previous cerebrospinal fluid shunt) demonstrated good fit (Hosmer-Lemeshow, P = .78) and discrimination (C statistic = 0.70). In the validation set, 105/163 ETVs (64.4%) were successful and the model maintained good fit (Hosmer-Lemeshow, P = .45), discrimination (C statistic = 0.68), and calibration (calibration slope = 0.88). A simplified ETV Success Score was devised that closely approximates the predicted probability of ETV success. Children most likely to succeed with ETV can now be accurately identified and spared the long-term complications of CSF shunting.

Evaluating structures, properties and vibrational and electronic spectra of the potassium 2-isonicotinoyltrifluoroborate salt

NASA Astrophysics Data System (ADS)

Iramain, Maximiliano A.; Davies, Lilian; Brandán, Silvia Antonia

2018-07-01

The potassium 2-isonicotinoyltrifluorborate salt has been characterized by using FT-IR, FT-Raman and UV-Visible spectroscopies while its structural properties were studied by using B3LYP/6-31G* and B3LYP/6-311++G** calculations in gas and aqueous solution phases. Four conformers with CS and C1 symmetries were found in the potential energy surfaces but only one of them presents the minimum energy. Two dimeric species of this salt were also optimized in accordance to the layered architectures suggested for trifluoroborate potassium salts in the solid phase. Here, the experimental Raman bands at 796, 748 and 676 cm-1 clearly support the presence of both dimers. On the other hand, the 2-isonicotinoyltrifluorborate anion was optimized because its presence is expected in solution. Reasonable correlations were observed between the predicted FTIR, Raman and UV-visible spectra with the corresponding experimental ones. The solvation energies for the salt in aqueous solution were predicted by using both methods. Here, it is observed that the change of furane by pyridine ring generates an increase in the solvation energies of the potassium 2-isonicotinoyltrifluorborate salt in relation to potassium 3-furoyltrifluoroborate salt. The study of the charges has revealed that there is an effect of the size of the basis set on the Mulliken charges while the AIM analyses suggest that the F⋯H and O⋯K interactions are also strongly dependent of the medium and the size of the basis sets. The bond orders for the F and K atoms evidence their higher ionic characteristics in solution with both basis sets. The NBO and AIM results clearly support the higher stability of this salt in both media. The studies by using the frontier orbitals indicate that the change of furane by pyridine ring decreases the reactivity of this salt by using 6-31G* basis set but increases when the other one is employed. Another effect of change of furane by pyridine ring is observed in the increase of the f(νCdbnd O) and f(νBF3) force constants. In addition, the force fields for the salt in both media were reported together to their complete vibrational assignments and force constants by using both levels of theory.

Data-driven forecasting algorithms for building energy consumption

NASA Astrophysics Data System (ADS)

Noh, Hae Young; Rajagopal, Ram

2013-04-01

This paper introduces two forecasting methods for building energy consumption data that are recorded from smart meters in high resolution. For utility companies, it is important to reliably forecast the aggregate consumption profile to determine energy supply for the next day and prevent any crisis. The proposed methods involve forecasting individual load on the basis of their measurement history and weather data without using complicated models of building system. The first method is most efficient for a very short-term prediction, such as the prediction period of one hour, and uses a simple adaptive time-series model. For a longer-term prediction, a nonparametric Gaussian process has been applied to forecast the load profiles and their uncertainty bounds to predict a day-ahead. These methods are computationally simple and adaptive and thus suitable for analyzing a large set of data whose pattern changes over the time. These forecasting methods are applied to several sets of building energy consumption data for lighting and heating-ventilation-air-conditioning (HVAC) systems collected from a campus building at Stanford University. The measurements are collected every minute, and corresponding weather data are provided hourly. The results show that the proposed algorithms can predict those energy consumption data with high accuracy.

Optimized auxiliary basis sets for density fitted post-Hartree-Fock calculations of lanthanide containing molecules

NASA Astrophysics Data System (ADS)

Chmela, Jiří; Harding, Michael E.

2018-06-01

Optimised auxiliary basis sets for lanthanide atoms (Ce to Lu) for four basis sets of the Karlsruhe error-balanced segmented contracted def2 - series (SVP, TZVP, TZVPP and QZVPP) are reported. These auxiliary basis sets enable the use of the resolution-of-the-identity (RI) approximation in post Hartree-Fock methods - as for example, second-order perturbation theory (MP2) and coupled cluster (CC) theory. The auxiliary basis sets are tested on an enlarged set of about a hundred molecules where the test criterion is the size of the RI error in MP2 calculations. Our tests also show that the same auxiliary basis sets can be used together with different effective core potentials. With these auxiliary basis set calculations of MP2 and CC quality can now be performed efficiently on medium-sized molecules containing lanthanides.

Correlation consistent basis sets for actinides. II. The atoms Ac and Np-Lr

NASA Astrophysics Data System (ADS)

Feng, Rulin; Peterson, Kirk A.

2017-08-01

New correlation consistent basis sets optimized using the all-electron third-order Douglas-Kroll-Hess (DKH3) scalar relativistic Hamiltonian are reported for the actinide elements Ac and Np through Lr. These complete the series of sets reported previously for Th-U [K. A. Peterson, J. Chem. Phys. 142, 074105 (2015); M. Vasiliu et al., J. Phys. Chem. A 119, 11422 (2015)]. The new sets range in size from double- to quadruple-zeta and encompass both those optimized for valence (6s6p5f7s6d) and outer-core electron correlations (valence + 5s5p5d). The final sets have been contracted for both the DKH3 and eXact 2-component (X2C) Hamiltonians, yielding cc-pVnZ-DK3/cc-pVnZ-X2C sets for valence correlation and cc-pwCVnZ-DK3/cc-pwCVnZ-X2C sets for outer-core correlation (n = D, T, Q in each case). In order to test the effectiveness of the new basis sets, both atomic and molecular benchmark calculations have been carried out. In the first case, the first three atomic ionization potentials (IPs) of all the actinide elements Ac-Lr have been calculated using the Feller-Peterson-Dixon (FPD) composite approach, primarily with the multireference configuration interaction (MRCI) method. Excellent convergence towards the respective complete basis set (CBS) limits is achieved with the new sets, leading to good agreement with experiment, where these exist, after accurately accounting for spin-orbit effects using the 4-component Dirac-Hartree-Fock method. For a molecular test, the IP and atomization energy (AE) of PuO2 have been calculated also using the FPD method but using a coupled cluster approach with spin-orbit coupling accounted for using the 4-component MRCI. The present calculations yield an IP0 for PuO2 of 159.8 kcal/mol, which is in excellent agreement with the experimental electron transfer bracketing value of 162 ± 3 kcal/mol. Likewise, the calculated 0 K AE of 305.6 kcal/mol is in very good agreement with the currently accepted experimental value of 303.1 ± 5 kcal/mol. The ground state of PuO2 is predicted to be the 0 g +5Σ state.

Correlation consistent basis sets for actinides. II. The atoms Ac and Np-Lr.

PubMed

Feng, Rulin; Peterson, Kirk A

2017-08-28

New correlation consistent basis sets optimized using the all-electron third-order Douglas-Kroll-Hess (DKH3) scalar relativistic Hamiltonian are reported for the actinide elements Ac and Np through Lr. These complete the series of sets reported previously for Th-U [K. A. Peterson, J. Chem. Phys. 142, 074105 (2015); M. Vasiliu et al., J. Phys. Chem. A 119, 11422 (2015)]. The new sets range in size from double- to quadruple-zeta and encompass both those optimized for valence (6s6p5f7s6d) and outer-core electron correlations (valence + 5s5p5d). The final sets have been contracted for both the DKH3 and eXact 2-component (X2C) Hamiltonians, yielding cc-pVnZ-DK3/cc-pVnZ-X2C sets for valence correlation and cc-pwCVnZ-DK3/cc-pwCVnZ-X2C sets for outer-core correlation (n = D, T, Q in each case). In order to test the effectiveness of the new basis sets, both atomic and molecular benchmark calculations have been carried out. In the first case, the first three atomic ionization potentials (IPs) of all the actinide elements Ac-Lr have been calculated using the Feller-Peterson-Dixon (FPD) composite approach, primarily with the multireference configuration interaction (MRCI) method. Excellent convergence towards the respective complete basis set (CBS) limits is achieved with the new sets, leading to good agreement with experiment, where these exist, after accurately accounting for spin-orbit effects using the 4-component Dirac-Hartree-Fock method. For a molecular test, the IP and atomization energy (AE) of PuO 2 have been calculated also using the FPD method but using a coupled cluster approach with spin-orbit coupling accounted for using the 4-component MRCI. The present calculations yield an IP 0 for PuO 2 of 159.8 kcal/mol, which is in excellent agreement with the experimental electron transfer bracketing value of 162 ± 3 kcal/mol. Likewise, the calculated 0 K AE of 305.6 kcal/mol is in very good agreement with the currently accepted experimental value of 303.1 ± 5 kcal/mol. The ground state of PuO 2 is predicted to be the Σ0g+5 state.

Quantitative structure-activation barrier relationship modeling for Diels-Alder ligations utilizing quantum chemical structural descriptors.

PubMed

Nandi, Sisir; Monesi, Alessandro; Drgan, Viktor; Merzel, Franci; Novič, Marjana

2013-10-30

In the present study, we show the correlation of quantum chemical structural descriptors with the activation barriers of the Diels-Alder ligations. A set of 72 non-catalysed Diels-Alder reactions were subjected to quantitative structure-activation barrier relationship (QSABR) under the framework of theoretical quantum chemical descriptors calculated solely from the structures of diene and dienophile reactants. Experimental activation barrier data were obtained from literature. Descriptors were computed using Hartree-Fock theory using 6-31G(d) basis set as implemented in Gaussian 09 software. Variable selection and model development were carried out by stepwise multiple linear regression methodology. Predictive performance of the quantitative structure-activation barrier relationship (QSABR) model was assessed by training and test set concept and by calculating leave-one-out cross-validated Q2 and predictive R2 values. The QSABR model can explain and predict 86.5% and 80% of the variances, respectively, in the activation energy barrier training data. Alternatively, a neural network model based on back propagation of errors was developed to assess the nonlinearity of the sought correlations between theoretical descriptors and experimental reaction barriers. A reasonable predictability for the activation barrier of the test set reactions was obtained, which enabled an exploration and interpretation of the significant variables responsible for Diels-Alder interaction between dienes and dienophiles. Thus, studies in the direction of QSABR modelling that provide efficient and fast prediction of activation barriers of the Diels-Alder reactions turn out to be a meaningful alternative to transition state theory based computation.

Ab Initio Density Fitting: Accuracy Assessment of Auxiliary Basis Sets from Cholesky Decompositions.

PubMed

Boström, Jonas; Aquilante, Francesco; Pedersen, Thomas Bondo; Lindh, Roland

2009-06-09

The accuracy of auxiliary basis sets derived by Cholesky decompositions of the electron repulsion integrals is assessed in a series of benchmarks on total ground state energies and dipole moments of a large test set of molecules. The test set includes molecules composed of atoms from the first three rows of the periodic table as well as transition metals. The accuracy of the auxiliary basis sets are tested for the 6-31G**, correlation consistent, and atomic natural orbital basis sets at the Hartree-Fock, density functional theory, and second-order Møller-Plesset levels of theory. By decreasing the decomposition threshold, a hierarchy of auxiliary basis sets is obtained with accuracies ranging from that of standard auxiliary basis sets to that of conventional integral treatments.

Accurate bond energies of hydrocarbons from complete basis set extrapolated multi-reference singles and doubles configuration interaction.

PubMed

Oyeyemi, Victor B; Pavone, Michele; Carter, Emily A

2011-12-09

Quantum chemistry has become one of the most reliable tools for characterizing the thermochemical underpinnings of reactions, such as bond dissociation energies (BDEs). The accurate prediction of these particular properties (BDEs) are challenging for ab initio methods based on perturbative corrections or coupled cluster expansions of the single-determinant Hartree-Fock wave function: the processes of bond breaking and forming are inherently multi-configurational and require an accurate description of non-dynamical electron correlation. To this end, we present a systematic ab initio approach for computing BDEs that is based on three components: 1) multi-reference single and double excitation configuration interaction (MRSDCI) for the electronic energies; 2) a two-parameter scheme for extrapolating MRSDCI energies to the complete basis set limit; and 3) DFT-B3LYP calculations of minimum-energy structures and vibrational frequencies to account for zero point energy and thermal corrections. We validated our methodology against a set of reliable experimental BDE values of CC and CH bonds of hydrocarbons. The goal of chemical accuracy is achieved, on average, without applying any empirical corrections to the MRSDCI electronic energies. We then use this composite scheme to make predictions of BDEs in a large number of hydrocarbon molecules for which there are no experimental data, so as to provide needed thermochemical estimates for fuel molecules. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Designing an artificial neural network using radial basis function to model exergetic efficiency of nanofluids in mini double pipe heat exchanger

NASA Astrophysics Data System (ADS)

Ghasemi, Nahid; Aghayari, Reza; Maddah, Heydar

2018-06-01

The present study aims at predicting and optimizing exergetic efficiency of TiO2-Al2O3/water nanofluid at different Reynolds numbers, volume fractions and twisted ratios using Artificial Neural Networks (ANN) and experimental data. Central Composite Design (CCD) and cascade Radial Basis Function (RBF) were used to display the significant levels of the analyzed factors on the exergetic efficiency. The size of TiO2-Al2O3/water nanocomposite was 20-70 nm. The parameters of ANN model were adapted by a training algorithm of radial basis function (RBF) with a wide range of experimental data set. Total mean square error and correlation coefficient were used to evaluate the results which the best result was obtained from double layer perceptron neural network with 30 neurons in which total Mean Square Error(MSE) and correlation coefficient (R2) were equal to 0.002 and 0.999, respectively. This indicated successful prediction of the network. Moreover, the proposed equation for predicting exergetic efficiency was extremely successful. According to the optimal curves, the optimum designing parameters of double pipe heat exchanger with inner twisted tape and nanofluid under the constrains of exergetic efficiency 0.937 are found to be Reynolds number 2500, twisted ratio 2.5 and volume fraction( v/v%) 0.05.

Ordering of the O-O stretching vibrational frequencies in ozone

NASA Technical Reports Server (NTRS)

Scuseria, Gustavo E.; Lee, Timothy J.; Scheiner, Andrew C.; Schaefer, Henry F., III

1989-01-01

The ordering of nu1 and nu3 for O3 is incorrectly predicted by most theoretical methods, including some very high level methods. The first systematic electron correlation method based on one-reference configuration to solve this problem is the coupled cluster single and double excitation method. However, a relatively large basis set, triple zeta plus double polarization is required. Comparison with other theoretical methods is made.

Analysis of Hydrogen Atom Abstraction from Ethylbenzene by an FeVO(TAML) Complex.

PubMed

Shen, Longzhu Q; Kundu, Soumen; Collins, Terrence J; Bominaar, Emile L

2017-04-17

It was shown previously (Chem. Eur. J. 2015, 21, 1803) that the rate of hydrogen atom abstraction, k, from ethylbenzene (EB) by TAML complex [Fe V (O)B*] - (1) in acetonitrile exhibits a large kinetic isotope effect (KIE ∼ 26) in the experimental range 233-243 K. The extrapolated tangents of ln(k/T) vs T -1 plots for EB-d 10 and EB gave a large, negative intercept difference, Int(EB) - Int(EB-d 10 ) = -34.5 J mol -1 K -1 for T -1 → 0, which is shown to be exclusively due to an isotopic mass effect on tunneling. A decomposition of the apparent activation barrier in terms of electronic, ZPE, thermal enthalpic, tunneling, and entropic contributions is presented. Tunneling corrections to ΔH ⧧ and ΔS ⧧ are estimated to be large. The DFT prediction, using functional B3LYP and basis set 6-311G, for the electronic contribution is significantly smaller than suggested by experiment. However, the agreement improves after correction for the basis set superposition error in the interaction between EB and 1. The kinetic model employed has been used to predict rate constants outside the experimental temperature range, which enabled us to compare the reactivity of 1 with those of other hydrogen abstracting complexes.

The Fatigue Approach to Vibration and Health: is it a Practical and Viable way of Predicting the Effects on People?

NASA Astrophysics Data System (ADS)

Sandover, J.

1998-08-01

The fatigue approach assumes that the vertebral end-plates are the weak link in the spine subjected to shock and vibration, and fail as a result of material fatigue. The theory assumes that end-plate damage leads to degeneration and pain in the lumbar spine. There is evidence for both the damage predicted and the fatigue mode of failure so that the approach may provide a basis for predictive methods for use in epidemiology and standards. An available data set from a variety of heavy vehicles in practical situations was used for predictions of spinal stress and fatigue life. Although there was some disparity between the predictive methods used, the more developed methods indicated fatigue lives that appeared reasonable, taking into account the vehicles tested and our knowledge of spinal degeneration. It is argued that the modelling and fatigue approaches combined offer a basis for estimating the effects of vibration and shock on health. Although the human variables are such that the approach, as yet, only offers rough estimates, it offers a good basis for understanding. The approach indicates that peak values are important and large peaks dominate risk. The method indicates that long term r.m.s. methods probably underestimate the risk of injury. The BS 6841Wband ISO 2631Wkweightings have shortcomings when used where peak values are important. A simple model may be more appropriate. The principle can be applied to continuous vibration as well as high acceleration events so that one method can be applied universally to continuous vibrations, high acceleration events and mixtures of these. An endurance limit can be hypothesised and, if this limit is sufficiently high, then the need for many measurements can be reduced.

Exploring the genetic architecture and improving genomic prediction accuracy for mastitis and milk production traits in dairy cattle by mapping variants to hepatic transcriptomic regions responsive to intra-mammary infection.

PubMed

Fang, Lingzhao; Sahana, Goutam; Ma, Peipei; Su, Guosheng; Yu, Ying; Zhang, Shengli; Lund, Mogens Sandø; Sørensen, Peter

2017-05-12

A better understanding of the genetic architecture of complex traits can contribute to improve genomic prediction. We hypothesized that genomic variants associated with mastitis and milk production traits in dairy cattle are enriched in hepatic transcriptomic regions that are responsive to intra-mammary infection (IMI). Genomic markers [e.g. single nucleotide polymorphisms (SNPs)] from those regions, if included, may improve the predictive ability of a genomic model. We applied a genomic feature best linear unbiased prediction model (GFBLUP) to implement the above strategy by considering the hepatic transcriptomic regions responsive to IMI as genomic features. GFBLUP, an extension of GBLUP, includes a separate genomic effect of SNPs within a genomic feature, and allows differential weighting of the individual marker relationships in the prediction equation. Since GFBLUP is computationally intensive, we investigated whether a SNP set test could be a computationally fast way to preselect predictive genomic features. The SNP set test assesses the association between a genomic feature and a trait based on single-SNP genome-wide association studies. We applied these two approaches to mastitis and milk production traits (milk, fat and protein yield) in Holstein (HOL, n = 5056) and Jersey (JER, n = 1231) cattle. We observed that a majority of genomic features were enriched in genomic variants that were associated with mastitis and milk production traits. Compared to GBLUP, the accuracy of genomic prediction with GFBLUP was marginally improved (3.2 to 3.9%) in within-breed prediction. The highest increase (164.4%) in prediction accuracy was observed in across-breed prediction. The significance of genomic features based on the SNP set test were correlated with changes in prediction accuracy of GFBLUP (P < 0.05). GFBLUP provides a framework for integrating multiple layers of biological knowledge to provide novel insights into the biological basis of complex traits, and to improve the accuracy of genomic prediction. The SNP set test might be used as a first-step to improve GFBLUP models. Approaches like GFBLUP and SNP set test will become increasingly useful, as the functional annotations of genomes keep accumulating for a range of species and traits.

Receptor-based 3D QSAR analysis of estrogen receptor ligands - merging the accuracy of receptor-based alignments with the computational efficiency of ligand-based methods

NASA Astrophysics Data System (ADS)

Sippl, Wolfgang

2000-08-01

One of the major challenges in computational approaches to drug design is the accurate prediction of binding affinity of biomolecules. In the present study several prediction methods for a published set of estrogen receptor ligands are investigated and compared. The binding modes of 30 ligands were determined using the docking program AutoDock and were compared with available X-ray structures of estrogen receptor-ligand complexes. On the basis of the docking results an interaction energy-based model, which uses the information of the whole ligand-receptor complex, was generated. Several parameters were modified in order to analyze their influence onto the correlation between binding affinities and calculated ligand-receptor interaction energies. The highest correlation coefficient ( r 2 = 0.617, q 2 LOO = 0.570) was obtained considering protein flexibility during the interaction energy evaluation. The second prediction method uses a combination of receptor-based and 3D quantitative structure-activity relationships (3D QSAR) methods. The ligand alignment obtained from the docking simulations was taken as basis for a comparative field analysis applying the GRID/GOLPE program. Using the interaction field derived with a water probe and applying the smart region definition (SRD) variable selection, a significant and robust model was obtained ( r 2 = 0.991, q 2 LOO = 0.921). The predictive ability of the established model was further evaluated by using a test set of six additional compounds. The comparison with the generated interaction energy-based model and with a traditional CoMFA model obtained using a ligand-based alignment ( r 2 = 0.951, q 2 LOO = 0.796) indicates that the combination of receptor-based and 3D QSAR methods is able to improve the quality of the underlying model.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rossi, Tuomas P., E-mail: tuomas.rossi@alumni.aalto.fi; Sakko, Arto; Puska, Martti J.

We present an approach for generating local numerical basis sets of improving accuracy for first-principles nanoplasmonics simulations within time-dependent density functional theory. The method is demonstrated for copper, silver, and gold nanoparticles that are of experimental interest but computationally demanding due to the semi-core d-electrons that affect their plasmonic response. The basis sets are constructed by augmenting numerical atomic orbital basis sets by truncated Gaussian-type orbitals generated by the completeness-optimization scheme, which is applied to the photoabsorption spectra of homoatomic metal atom dimers. We obtain basis sets of improving accuracy up to the complete basis set limit and demonstrate thatmore » the performance of the basis sets transfers to simulations of larger nanoparticles and nanoalloys as well as to calculations with various exchange-correlation functionals. This work promotes the use of the local basis set approach of controllable accuracy in first-principles nanoplasmonics simulations and beyond.« less

Statistical Approaches for Spatiotemporal Prediction of Low Flows

NASA Astrophysics Data System (ADS)

Fangmann, A.; Haberlandt, U.

2017-12-01

An adequate assessment of regional climate change impacts on streamflow requires the integration of various sources of information and modeling approaches. This study proposes simple statistical tools for inclusion into model ensembles, which are fast and straightforward in their application, yet able to yield accurate streamflow predictions in time and space. Target variables for all approaches are annual low flow indices derived from a data set of 51 records of average daily discharge for northwestern Germany. The models require input of climatic data in the form of meteorological drought indices, derived from observed daily climatic variables, averaged over the streamflow gauges' catchments areas. Four different modeling approaches are analyzed. Basis for all pose multiple linear regression models that estimate low flows as a function of a set of meteorological indices and/or physiographic and climatic catchment descriptors. For the first method, individual regression models are fitted at each station, predicting annual low flow values from a set of annual meteorological indices, which are subsequently regionalized using a set of catchment characteristics. The second method combines temporal and spatial prediction within a single panel data regression model, allowing estimation of annual low flow values from input of both annual meteorological indices and catchment descriptors. The third and fourth methods represent non-stationary low flow frequency analyses and require fitting of regional distribution functions. Method three is subject to a spatiotemporal prediction of an index value, method four to estimation of L-moments that adapt the regional frequency distribution to the at-site conditions. The results show that method two outperforms successive prediction in time and space. Method three also shows a high performance in the near future period, but since it relies on a stationary distribution, its application for prediction of far future changes may be problematic. Spatiotemporal prediction of L-moments appeared highly uncertain for higher-order moments resulting in unrealistic future low flow values. All in all, the results promote an inclusion of simple statistical methods in climate change impact assessment.

Updated Prognostic Model for Predicting Overall Survival in First-Line Chemotherapy for Patients With Metastatic Castration-Resistant Prostate Cancer

PubMed Central

Halabi, Susan; Lin, Chen-Yen; Kelly, W. Kevin; Fizazi, Karim S.; Moul, Judd W.; Kaplan, Ellen B.; Morris, Michael J.; Small, Eric J.

2014-01-01

Purpose Prognostic models for overall survival (OS) for patients with metastatic castration-resistant prostate cancer (mCRPC) are dated and do not reflect significant advances in treatment options available for these patients. This work developed and validated an updated prognostic model to predict OS in patients receiving first-line chemotherapy. Methods Data from a phase III trial of 1,050 patients with mCRPC were used (Cancer and Leukemia Group B CALGB-90401 [Alliance]). The data were randomly split into training and testing sets. A separate phase III trial served as an independent validation set. Adaptive least absolute shrinkage and selection operator selected eight factors prognostic for OS. A predictive score was computed from the regression coefficients and used to classify patients into low- and high-risk groups. The model was assessed for its predictive accuracy using the time-dependent area under the curve (tAUC). Results The model included Eastern Cooperative Oncology Group performance status, disease site, lactate dehydrogenase, opioid analgesic use, albumin, hemoglobin, prostate-specific antigen, and alkaline phosphatase. Median OS values in the high- and low-risk groups, respectively, in the testing set were 17 and 30 months (hazard ratio [HR], 2.2; P < .001); in the validation set they were 14 and 26 months (HR, 2.9; P < .001). The tAUCs were 0.73 (95% CI, 0.70 to 0.73) and 0.76 (95% CI, 0.72 to 0.76) in the testing and validation sets, respectively. Conclusion An updated prognostic model for OS in patients with mCRPC receiving first-line chemotherapy was developed and validated on an external set. This model can be used to predict OS, as well as to better select patients to participate in trials on the basis of their prognosis. PMID:24449231

Effective empirical corrections for basis set superposition error in the def2-SVPD basis: gCP and DFT-C

NASA Astrophysics Data System (ADS)

Witte, Jonathon; Neaton, Jeffrey B.; Head-Gordon, Martin

2017-06-01

With the aim of mitigating the basis set error in density functional theory (DFT) calculations employing local basis sets, we herein develop two empirical corrections for basis set superposition error (BSSE) in the def2-SVPD basis, a basis which—when stripped of BSSE—is capable of providing near-complete-basis DFT results for non-covalent interactions. Specifically, we adapt the existing pairwise geometrical counterpoise (gCP) approach to the def2-SVPD basis, and we develop a beyond-pairwise approach, DFT-C, which we parameterize across a small set of intermolecular interactions. Both gCP and DFT-C are evaluated against the traditional Boys-Bernardi counterpoise correction across a set of 3402 non-covalent binding energies and isomerization energies. We find that the DFT-C method represents a significant improvement over gCP, particularly for non-covalently-interacting molecular clusters. Moreover, DFT-C is transferable among density functionals and can be combined with existing functionals—such as B97M-V—to recover large-basis results at a fraction of the cost.

Hierarchical representation and machine learning from faulty jet engine behavioral examples to detect real time abnormal conditions

NASA Technical Reports Server (NTRS)

Gupta, U. K.; Ali, M.

1988-01-01

The theoretical basis and operation of LEBEX, a machine-learning system for jet-engine performance monitoring, are described. The behavior of the engine is modeled in terms of four parameters (the rotational speeds of the high- and low-speed sections and the exhaust and combustion temperatures), and parameter variations indicating malfunction are transformed into structural representations involving instances and events. LEBEX extracts descriptors from a set of training data on normal and faulty engines, represents them hierarchically in a knowledge base, and uses them to diagnose and predict faults on a real-time basis. Diagrams of the system architecture and printouts of typical results are shown.

The Anharmonic Force Field of Ethylene, C2H4, by Means of Accurate Ab Initio Calculations

NASA Technical Reports Server (NTRS)

Martin, Jan M. L.; Lee, Timothy J.; Taylor, Peter R.; Francois, Jean-Pierre; Langhoff, Stephen R. (Technical Monitor)

1995-01-01

The quartic force field of ethylene, C2H4, has been calculated ab initio using augmented coupled cluster, CCSD(T), methods and correlation consistent basis sets of spdf quality. For the C-12 isotopomers C2H4, C2H3D, H2CCD2, cis-C2H2D2, trans-C2H2D2, C2HD3, and C2D4, all fundamentals could be reproduced to better than 10 per centimeter, except for three cases of severe Fermi type 1 resonance. The problem with these three bands is identified as a systematic overestimate of the Kiij Fermi resonance constants by a factor of two or more; if this is corrected for, the predicted fundamentals come into excellent agreement with experiment. No such systematic overestimate is seen for Fermi type 2 resonances. Our computed harmonic frequencies suggest a thorough revision of the accepted experimentally derived values. Our computed and empirically corrected re geometry differs substantially from experimentally derived values: both the predicted rz geometry and the ground-state rotational constants are, however, in excellent agreement with experiment, suggesting revision of the older values. Anharmonicity constants agree well with experiment for stretches, but differ substantially for stretch-bend interaction constants, due to equality constraints in the experimental analysis that do not hold. Improved criteria for detecting Fermi and Coriolis resonances are proposed and found to work well, contrary to the established method based on harmonic frequency differences that fails to detect several important resonances for C2H4 and its isotopomers. Surprisingly good results are obtained with a small spd basis at the CCSD(T) level. The well-documented strong basis set effect on the v8 out-of-plane motion is present to a much lesser extent when correlation-optimized polarization functions are used. Complete sets of anharmonic, rovibrational coupling, and centrifugal distortion constants for the isotopomers are available as supplementary material to the paper.

A density-functional theory investigation of 3-nitro-1,2,4-triazole-5-one dimers and crystal

NASA Astrophysics Data System (ADS)

Xiao, He-Ming; Ju, Xue-Hai; Xu, Li-Na; Fang, Guo-Yong

2004-12-01

Density-functional method with different basis sets was applied to the study of the highly efficient and low sensitive explosive 3-nitro-1,2,4-triazole-5-one (NTO) in both gaseous dimer and its bulk state. The binding energies have been corrected for the basis set superposition errors. Six stable dimers (II-VII) were located. The corrected binding energy of the most stable dimer VII is predicted to be -53.66 kJ/mol at the B3LYP/6-311++G** level. It was found that the structures of the more stable dimers (V-VII) are through the hydrogen bonding interaction between the carbonyl oxygen and the azole hydrogen of 3-nitro-1,2,4-triazole-5-one. The changes of Gibbs free energies (ΔG) in the processes from the monomer to the dimers at 298.15 K are 8.51, 0.90, 0.35, -8.74, -10.67, and -11.06 kJ/mol for dimers from II to VII, respectively. Dimers V-VII, possessing cyclic structures, can be spontaneously produced from the isolated monomer at room temperature. The lattice energy is -156.14 kJ/mol, and this value becomes to -150.43 kJ/mol when a 50% correction of the basis set superposition error was adopted. The frontier bands are quite flat. Judged from the value of band gap of 4.0 eV, it may be predicted that 3-nitro-1,2,4-triazole-5-one is an insulator. Most atoms in NTO, with the exception of C5 atom and the nitro atoms, make up the upper valence bands. In contrast, the lower conduction bands mainly consist of the nitro N and O atoms. The population of the C-NO2 bond is much less than those of the other bonds and the detonation may be initiated by the breakdown of this bond.

A density-functional theory investigation of 3-nitro-1,2,4-triazole-5-one dimers and crystal.

PubMed

Xiao, He-Ming; Ju, Xue-Hai; Xu, Li-Na; Fang, Guo-Yong

2004-12-22

Density-functional method with different basis sets was applied to the study of the highly efficient and low sensitive explosive 3-nitro-1,2,4-triazole-5-one (NTO) in both gaseous dimer and its bulk state. The binding energies have been corrected for the basis set superposition errors. Six stable dimers (II-VII) were located. The corrected binding energy of the most stable dimer VII is predicted to be -53.66 kJ/mol at the B3LYP/6-311++G(**) level. It was found that the structures of the more stable dimers (V-VII) are through the hydrogen bonding interaction between the carbonyl oxygen and the azole hydrogen of 3-nitro-1,2,4-triazole-5-one. The changes of Gibbs free energies (DeltaG) in the processes from the monomer to the dimers at 298.15 K are 8.51, 0.90, 0.35, -8.74, -10.67, and -11.06 kJ/mol for dimers from II to VII, respectively. Dimers V-VII, possessing cyclic structures, can be spontaneously produced from the isolated monomer at room temperature. The lattice energy is -156.14 kJ/mol, and this value becomes to -150.43 kJ/mol when a 50% correction of the basis set superposition error was adopted. The frontier bands are quite flat. Judged from the value of band gap of 4.0 eV, it may be predicted that 3-nitro-1,2,4-triazole-5-one is an insulator. Most atoms in NTO, with the exception of C(5) atom and the nitro atoms, make up the upper valence bands. In contrast, the lower conduction bands mainly consist of the nitro N and O atoms. The population of the C-NO(2) bond is much less than those of the other bonds and the detonation may be initiated by the breakdown of this bond. (c) 2004 American Institute of Physics.

Predictive Genomic Analyses Inform the Basis for Vitamin Metabolism and Provisioning in Bacteria-Arthropod Endosymbioses.

PubMed

Serbus, Laura R; Rodriguez, Brian Garcia; Sharmin, Zinat; Momtaz, A J M Zehadee; Christensen, Steen

2017-06-07

The requirement of vitamins for core metabolic processes creates a unique set of pressures for arthropods subsisting on nutrient-limited diets. While endosymbiotic bacteria carried by arthropods have been widely implicated in vitamin provisioning, the underlying molecular mechanisms are not well understood. To address this issue, standardized predictive assessment of vitamin metabolism was performed in 50 endosymbionts of insects and arachnids. The results predicted that arthropod endosymbionts overall have little capacity for complete de novo biosynthesis of conventional or active vitamin forms. Partial biosynthesis pathways were commonly predicted, suggesting a substantial role in vitamin provisioning. Neither taxonomic relationships between host and symbiont, nor the mode of host-symbiont interaction were clear predictors of endosymbiont vitamin pathway capacity. Endosymbiont genome size and the synthetic capacity of nonsymbiont taxonomic relatives were more reliable predictors. We developed a new software application that also predicted that last-step conversion of intermediates into active vitamin forms may contribute further to vitamin biosynthesis by endosymbionts. Most instances of predicted vitamin conversion were paralleled by predictions of vitamin use. This is consistent with achievement of provisioning in some cases through upregulation of pathways that were retained for endosymbiont benefit. The predicted absence of other enzyme classes further suggests a baseline of vitamin requirement by the majority of endosymbionts, as well as some instances of putative mutualism. Adaptation of this workflow to analysis of other organisms and metabolic pathways will provide new routes for considering the molecular basis for symbiosis on a comprehensive scale. Copyright © 2017 Serbus et al.

Development of Artificial Neural Network Model for Diesel Fuel Properties Prediction using Vibrational Spectroscopy.

PubMed

Bolanča, Tomislav; Marinović, Slavica; Ukić, Sime; Jukić, Ante; Rukavina, Vinko

2012-06-01

This paper describes development of artificial neural network models which can be used to correlate and predict diesel fuel properties from several FTIR-ATR absorbances and Raman intensities as input variables. Multilayer feed forward and radial basis function neural networks have been used to rapid and simultaneous prediction of cetane number, cetane index, density, viscosity, distillation temperatures at 10% (T10), 50% (T50) and 90% (T90) recovery, contents of total aromatics and polycyclic aromatic hydrocarbons of commercial diesel fuels. In this study two-phase training procedures for multilayer feed forward networks were applied. While first phase training algorithm was constantly the back propagation one, two second phase training algorithms were varied and compared, namely: conjugate gradient and quasi Newton. In case of radial basis function network, radial layer was trained using K-means radial assignment algorithm and three different radial spread algorithms: explicit, isotropic and K-nearest neighbour. The number of hidden layer neurons and experimental data points used for the training set have been optimized for both neural networks in order to insure good predictive ability by reducing unnecessary experimental work. This work shows that developed artificial neural network models can determine main properties of diesel fuels simultaneously based on a single and fast IR or Raman measurement.

BCI Competition IV – Data Set I: Learning Discriminative Patterns for Self-Paced EEG-Based Motor Imagery Detection

PubMed Central

Zhang, Haihong; Guan, Cuntai; Ang, Kai Keng; Wang, Chuanchu

2012-01-01

Detecting motor imagery activities versus non-control in brain signals is the basis of self-paced brain-computer interfaces (BCIs), but also poses a considerable challenge to signal processing due to the complex and non-stationary characteristics of motor imagery as well as non-control. This paper presents a self-paced BCI based on a robust learning mechanism that extracts and selects spatio-spectral features for differentiating multiple EEG classes. It also employs a non-linear regression and post-processing technique for predicting the time-series of class labels from the spatio-spectral features. The method was validated in the BCI Competition IV on Dataset I where it produced the lowest prediction error of class labels continuously. This report also presents and discusses analysis of the method using the competition data set. PMID:22347153

3D-QSAR analysis of MCD inhibitors by CoMFA and CoMSIA.

PubMed

Pourbasheer, Eslam; Aalizadeh, Reza; Ebadi, Amin; Ganjali, Mohammad Reza

2015-01-01

Three-dimensional quantitative structure-activity relationship was developed for the series of compounds as malonyl-CoA decarboxylase antagonists (MCD) using the CoMFA and CoMSIA methods. The statistical parameters for CoMFA (q(2)=0.558, r(2)=0.841) and CoMSIA (q(2)= 0.615, r(2) = 0.870) models were derived based on 38 compounds as training set in the basis of the selected alignment. The external predictive abilities of the built models were evaluated by using the test set of nine compounds. From obtained results, the CoMSIA method was found to have highly predictive capability in comparison with CoMFA method. Based on the given results by CoMSIA and CoMFA contour maps, some features that can enhance the activity of compounds as MCD antagonists were introduced and used to design new compounds with better inhibition activity.

Artificial neural network study on organ-targeting peptides

NASA Astrophysics Data System (ADS)

Jung, Eunkyoung; Kim, Junhyoung; Choi, Seung-Hoon; Kim, Minkyoung; Rhee, Hokyoung; Shin, Jae-Min; Choi, Kihang; Kang, Sang-Kee; Lee, Nam Kyung; Choi, Yun-Jaie; Jung, Dong Hyun

2010-01-01

We report a new approach to studying organ targeting of peptides on the basis of peptide sequence information. The positive control data sets consist of organ-targeting peptide sequences identified by the peroral phage-display technique for four organs, and the negative control data are prepared from random sequences. The capacity of our models to make appropriate predictions is validated by statistical indicators including sensitivity, specificity, enrichment curve, and the area under the receiver operating characteristic (ROC) curve (the ROC score). VHSE descriptor produces statistically significant training models and the models with simple neural network architectures show slightly greater predictive power than those with complex ones. The training and test set statistics indicate that our models could discriminate between organ-targeting and random sequences. We anticipate that our models will be applicable to the selection of organ-targeting peptides for generating peptide drugs or peptidomimetics.

QSAR Modeling and Prediction of Drug-Drug Interactions.

PubMed

Zakharov, Alexey V; Varlamova, Ekaterina V; Lagunin, Alexey A; Dmitriev, Alexander V; Muratov, Eugene N; Fourches, Denis; Kuz'min, Victor E; Poroikov, Vladimir V; Tropsha, Alexander; Nicklaus, Marc C

2016-02-01

Severe adverse drug reactions (ADRs) are the fourth leading cause of fatality in the U.S. with more than 100,000 deaths per year. As up to 30% of all ADRs are believed to be caused by drug-drug interactions (DDIs), typically mediated by cytochrome P450s, possibilities to predict DDIs from existing knowledge are important. We collected data from public sources on 1485, 2628, 4371, and 27,966 possible DDIs mediated by four cytochrome P450 isoforms 1A2, 2C9, 2D6, and 3A4 for 55, 73, 94, and 237 drugs, respectively. For each of these data sets, we developed and validated QSAR models for the prediction of DDIs. As a unique feature of our approach, the interacting drug pairs were represented as binary chemical mixtures in a 1:1 ratio. We used two types of chemical descriptors: quantitative neighborhoods of atoms (QNA) and simplex descriptors. Radial basis functions with self-consistent regression (RBF-SCR) and random forest (RF) were utilized to build QSAR models predicting the likelihood of DDIs for any pair of drug molecules. Our models showed balanced accuracy of 72-79% for the external test sets with a coverage of 81.36-100% when a conservative threshold for the model's applicability domain was applied. We generated virtually all possible binary combinations of marketed drugs and employed our models to identify drug pairs predicted to be instances of DDI. More than 4500 of these predicted DDIs that were not found in our training sets were confirmed by data from the DrugBank database.

Quantum Dynamics with Short-Time Trajectories and Minimal Adaptive Basis Sets.

PubMed

Saller, Maximilian A C; Habershon, Scott

2017-07-11

Methods for solving the time-dependent Schrödinger equation via basis set expansion of the wave function can generally be categorized as having either static (time-independent) or dynamic (time-dependent) basis functions. We have recently introduced an alternative simulation approach which represents a middle road between these two extremes, employing dynamic (classical-like) trajectories to create a static basis set of Gaussian wavepackets in regions of phase-space relevant to future propagation of the wave function [J. Chem. Theory Comput., 11, 8 (2015)]. Here, we propose and test a modification of our methodology which aims to reduce the size of basis sets generated in our original scheme. In particular, we employ short-time classical trajectories to continuously generate new basis functions for short-time quantum propagation of the wave function; to avoid the continued growth of the basis set describing the time-dependent wave function, we employ Matching Pursuit to periodically minimize the number of basis functions required to accurately describe the wave function. Overall, this approach generates a basis set which is adapted to evolution of the wave function while also being as small as possible. In applications to challenging benchmark problems, namely a 4-dimensional model of photoexcited pyrazine and three different double-well tunnelling problems, we find that our new scheme enables accurate wave function propagation with basis sets which are around an order-of-magnitude smaller than our original trajectory-guided basis set methodology, highlighting the benefits of adaptive strategies for wave function propagation.

Polarization functions for the modified m6-31G basis sets for atoms Ga through Kr.

PubMed

Mitin, Alexander V

2013-09-05

The 2df polarization functions for the modified m6-31G basis sets of the third-row atoms Ga through Kr (Int J Quantum Chem, 2007, 107, 3028; Int J. Quantum Chem, 2009, 109, 1158) are proposed. The performances of the m6-31G, m6-31G(d,p), and m6-31G(2df,p) basis sets were examined in molecular calculations carried out by the density functional theory (DFT) method with B3LYP hybrid functional, Møller-Plesset perturbation theory of the second order (MP2), quadratic configuration interaction method with single and double substitutions and were compared with those for the known 6-31G basis sets as well as with the other similar 641 and 6-311G basis sets with and without polarization functions. Obtained results have shown that the performances of the m6-31G, m6-31G(d,p), and m6-31G(2df,p) basis sets are better in comparison with the performances of the known 6-31G, 6-31G(d,p) and 6-31G(2df,p) basis sets. These improvements are mainly reached due to better approximations of different electrons belonging to the different atomic shells in the modified basis sets. Applicability of the modified basis sets in thermochemical calculations is also discussed. © 2013 Wiley Periodicals, Inc.

The structure and energetics of the HCN → HNC transition state

NASA Astrophysics Data System (ADS)

Lee, Timothy J.; Rendell, Alistair P.

1991-03-01

The optimum geometries and quadratic force constants of HCN, HNC and the transition state connecting them have been determined at the single and double excitation coupled-cluster (CCSD) and CCSD(T) levels of theory. Energy differences were evaluated using the CCSD and CCSD(T) methods in conjunction with large atomic natural orbital basis sets containing g-type basis functions on the heavy atoms and f-type functions on hydrogen. The most reliable structure obtained for the transition state has bond distances of 1.194, 1.188 and 1.389 Å for rCN, rCH and rNH, respectively. Including a correction for zero-point vibrational energies, the transition state is predicted to be 44.6 ± 1.0 kcal/mol above the HCN isomer, while HNC is predicted to be 14.4 ± 1.0 kcal/mol above HCN. The latter value is in excellent agreement with the most recent experimental determination (14.8 ± 2.0 kcal/mol).

RWEN: Response-Weighted Elastic Net For Prediction of Chemosensitivity of Cancer Cell Lines. | Office of Cancer Genomics

Cancer.gov

Motivation: In recent years there have been several efforts to generate sensitivity profiles of collections of genomically characterized cell lines to panels of candidate therapeutic compounds. These data provide the basis for the development of in silico models of sensitivity based on cellular, genetic, or expression biomarkers of cancer cells. However, a remaining challenge is an efficient way to identify accurate sets of biomarkers to validate.

A deep learning classifier for prediction of pathological complete response to neoadjuvant chemotherapy from baseline breast DCE-MRI

NASA Astrophysics Data System (ADS)

Ravichandran, Kavya; Braman, Nathaniel; Janowczyk, Andrew; Madabhushi, Anant

2018-02-01

Neoadjuvant chemotherapy (NAC) is routinely used to treat breast tumors before surgery to reduce tumor size and improve outcome. However, no current clinical or imaging metrics can effectively predict before treatment which NAC recipients will achieve pathological complete response (pCR), the absence of residual invasive disease in the breast or lymph nodes following surgical resection. In this work, we developed and applied a convolu- tional neural network (CNN) to predict pCR from pre-treatment dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) scans on a per-voxel basis. In this study, DCE-MRI data for a total of 166 breast cancer pa- tients from the ISPY1 Clinical Trial were split into a training set of 133 patients and a testing set of 33 patients. A CNN consisting of 6 convolutional blocks was trained over 30 epochs. The pre-contrast and post-contrast DCE-MRI phases were considered in isolation and conjunction. A CNN utilizing a combination of both pre- and post-contrast images best distinguished responders, with an AUC of 0.77; 82% of the patients in the testing set were correctly classified based on their treatment response. Within the testing set, the CNN was able to produce probability heatmaps that visualized tumor regions that most strongly predicted therapeutic response. Multi- variate analysis with prognostic clinical variables (age, largest diameter, hormone receptor and HER2 status), revealed that the network was an independent predictor of response (p=0.05), and that the inclusion of HER2 status could further improve capability to predict response (AUC = 0.85, accuracy = 85%).

The short- to medium-term predictive accuracy of static and dynamic risk assessment measures in a secure forensic hospital.

PubMed

Chu, Chi Meng; Thomas, Stuart D M; Ogloff, James R P; Daffern, Michael

2013-04-01

Although violence risk assessment knowledge and practice has advanced over the past few decades, it remains practically difficult to decide which measures clinicians should use to assess and make decisions about the violence potential of individuals on an ongoing basis, particularly in the short to medium term. Within this context, this study sought to compare the predictive accuracy of dynamic risk assessment measures for violence with static risk assessment measures over the short term (up to 1 month) and medium term (up to 6 months) in a forensic psychiatric inpatient setting. Results showed that dynamic measures were generally more accurate than static measures for short- to medium-term predictions of inpatient aggression. These findings highlight the necessity of using risk assessment measures that are sensitive to important clinical risk state variables to improve the short- to medium-term prediction of aggression within the forensic inpatient setting. Such knowledge can assist with the development of more accurate and efficient risk assessment procedures, including the selection of appropriate risk assessment instruments to manage and prevent the violence of offenders with mental illnesses during inpatient treatment.

Probable flood predictions in ungauged coastal basins of El Salvador

USGS Publications Warehouse

Friedel, M.J.; Smith, M.E.; Chica, A.M.E.; Litke, D.

2008-01-01

A regionalization procedure is presented and used to predict probable flooding in four ungauged coastal river basins of El Salvador: Paz, Jiboa, Grande de San Miguel, and Goascoran. The flood-prediction problem is sequentially solved for two regions: upstream mountains and downstream alluvial plains. In the upstream mountains, a set of rainfall-runoff parameter values and recurrent peak-flow discharge hydrographs are simultaneously estimated for 20 tributary-basin models. Application of dissimilarity equations among tributary basins (soft prior information) permitted development of a parsimonious parameter structure subject to information content in the recurrent peak-flow discharge values derived using regression equations based on measurements recorded outside the ungauged study basins. The estimated joint set of parameter values formed the basis from which probable minimum and maximum peak-flow discharge limits were then estimated revealing that prediction uncertainty increases with basin size. In the downstream alluvial plain, model application of the estimated minimum and maximum peak-flow hydrographs facilitated simulation of probable 100-year flood-flow depths in confined canyons and across unconfined coastal alluvial plains. The regionalization procedure provides a tool for hydrologic risk assessment and flood protection planning that is not restricted to the case presented herein. ?? 2008 ASCE.

QSAR studies on triazole derivatives as sglt inhibitors via CoMFA and CoMSIA

NASA Astrophysics Data System (ADS)

Zhi, Hui; Zheng, Junxia; Chang, Yiqun; Li, Qingguo; Liao, Guochao; Wang, Qi; Sun, Pinghua

2015-10-01

Forty-six sodium-dependent glucose cotransporters-2 (SGLT-2) inhibitors with hypoglycemic activity were selected to develop three-dimensional quantitative structure-activity relationship (3D-QSAR) using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models. A training set of 39 compounds were used to build up the models, which were then evaluated by a series of internal and external cross-validation techniques. A test set of 7 compounds was used for the external validation. The CoMFA model predicted a q2 value of 0.792 and an r2 value of 0.985. The best CoMSIA model predicted a q2 value of 0.633 and an r2 value of 0.895 based on a combination of steric, electrostatic, hydrophobic and hydrogen-bond acceptor effects. The predictive correlation coefficients (rpred2) of CoMFA and CoMSIA models were 0.872 and 0.839, respectively. The analysis of the contour maps from each model provided insight into the structural requirements for the development of more active sglt inhibitors, and on the basis of the models 8 new sglt inhibitors were designed and predicted.

Approaching the basis set limit for DFT calculations using an environment-adapted minimal basis with perturbation theory: Formulation, proof of concept, and a pilot implementation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mao, Yuezhi; Horn, Paul R.; Mardirossian, Narbe

2016-07-28

Recently developed density functionals have good accuracy for both thermochemistry (TC) and non-covalent interactions (NC) if very large atomic orbital basis sets are used. To approach the basis set limit with potentially lower computational cost, a new self-consistent field (SCF) scheme is presented that employs minimal adaptive basis (MAB) functions. The MAB functions are optimized on each atomic site by minimizing a surrogate function. High accuracy is obtained by applying a perturbative correction (PC) to the MAB calculation, similar to dual basis approaches. Compared to exact SCF results, using this MAB-SCF (PC) approach with the same large target basis set producesmore » <0.15 kcal/mol root-mean-square deviations for most of the tested TC datasets, and <0.1 kcal/mol for most of the NC datasets. The performance of density functionals near the basis set limit can be even better reproduced. With further improvement to its implementation, MAB-SCF (PC) is a promising lower-cost substitute for conventional large-basis calculations as a method to approach the basis set limit of modern density functionals.« less

Simple and efficient LCAO basis sets for the diffuse states in carbon nanostructures.

PubMed

Papior, Nick R; Calogero, Gaetano; Brandbyge, Mads

2018-06-27

We present a simple way to describe the lowest unoccupied diffuse states in carbon nanostructures in density functional theory calculations using a minimal LCAO (linear combination of atomic orbitals) basis set. By comparing plane wave basis calculations, we show how these states can be captured by adding long-range orbitals to the standard LCAO basis sets for the extreme cases of planar sp 2 (graphene) and curved carbon (C 60 ). In particular, using Bessel functions with a long range as additional basis functions retain a minimal basis size. This provides a smaller and simpler atom-centered basis set compared to the standard pseudo-atomic orbitals (PAOs) with multiple polarization orbitals or by adding non-atom-centered states to the basis.

Simple and efficient LCAO basis sets for the diffuse states in carbon nanostructures

NASA Astrophysics Data System (ADS)

Papior, Nick R.; Calogero, Gaetano; Brandbyge, Mads

2018-06-01

We present a simple way to describe the lowest unoccupied diffuse states in carbon nanostructures in density functional theory calculations using a minimal LCAO (linear combination of atomic orbitals) basis set. By comparing plane wave basis calculations, we show how these states can be captured by adding long-range orbitals to the standard LCAO basis sets for the extreme cases of planar sp 2 (graphene) and curved carbon (C60). In particular, using Bessel functions with a long range as additional basis functions retain a minimal basis size. This provides a smaller and simpler atom-centered basis set compared to the standard pseudo-atomic orbitals (PAOs) with multiple polarization orbitals or by adding non-atom-centered states to the basis.

Automated diagnoses of attention deficit hyperactive disorder using magnetic resonance imaging.

PubMed

Eloyan, Ani; Muschelli, John; Nebel, Mary Beth; Liu, Han; Han, Fang; Zhao, Tuo; Barber, Anita D; Joel, Suresh; Pekar, James J; Mostofsky, Stewart H; Caffo, Brian

2012-01-01

Successful automated diagnoses of attention deficit hyperactive disorder (ADHD) using imaging and functional biomarkers would have fundamental consequences on the public health impact of the disease. In this work, we show results on the predictability of ADHD using imaging biomarkers and discuss the scientific and diagnostic impacts of the research. We created a prediction model using the landmark ADHD 200 data set focusing on resting state functional connectivity (rs-fc) and structural brain imaging. We predicted ADHD status and subtype, obtained by behavioral examination, using imaging data, intelligence quotients and other covariates. The novel contributions of this manuscript include a thorough exploration of prediction and image feature extraction methodology on this form of data, including the use of singular value decompositions (SVDs), CUR decompositions, random forest, gradient boosting, bagging, voxel-based morphometry, and support vector machines as well as important insights into the value, and potentially lack thereof, of imaging biomarkers of disease. The key results include the CUR-based decomposition of the rs-fc-fMRI along with gradient boosting and the prediction algorithm based on a motor network parcellation and random forest algorithm. We conjecture that the CUR decomposition is largely diagnosing common population directions of head motion. Of note, a byproduct of this research is a potential automated method for detecting subtle in-scanner motion. The final prediction algorithm, a weighted combination of several algorithms, had an external test set specificity of 94% with sensitivity of 21%. The most promising imaging biomarker was a correlation graph from a motor network parcellation. In summary, we have undertaken a large-scale statistical exploratory prediction exercise on the unique ADHD 200 data set. The exercise produced several potential leads for future scientific exploration of the neurological basis of ADHD.

Automated diagnoses of attention deficit hyperactive disorder using magnetic resonance imaging

PubMed Central

Eloyan, Ani; Muschelli, John; Nebel, Mary Beth; Liu, Han; Han, Fang; Zhao, Tuo; Barber, Anita D.; Joel, Suresh; Pekar, James J.; Mostofsky, Stewart H.; Caffo, Brian

2012-01-01

Successful automated diagnoses of attention deficit hyperactive disorder (ADHD) using imaging and functional biomarkers would have fundamental consequences on the public health impact of the disease. In this work, we show results on the predictability of ADHD using imaging biomarkers and discuss the scientific and diagnostic impacts of the research. We created a prediction model using the landmark ADHD 200 data set focusing on resting state functional connectivity (rs-fc) and structural brain imaging. We predicted ADHD status and subtype, obtained by behavioral examination, using imaging data, intelligence quotients and other covariates. The novel contributions of this manuscript include a thorough exploration of prediction and image feature extraction methodology on this form of data, including the use of singular value decompositions (SVDs), CUR decompositions, random forest, gradient boosting, bagging, voxel-based morphometry, and support vector machines as well as important insights into the value, and potentially lack thereof, of imaging biomarkers of disease. The key results include the CUR-based decomposition of the rs-fc-fMRI along with gradient boosting and the prediction algorithm based on a motor network parcellation and random forest algorithm. We conjecture that the CUR decomposition is largely diagnosing common population directions of head motion. Of note, a byproduct of this research is a potential automated method for detecting subtle in-scanner motion. The final prediction algorithm, a weighted combination of several algorithms, had an external test set specificity of 94% with sensitivity of 21%. The most promising imaging biomarker was a correlation graph from a motor network parcellation. In summary, we have undertaken a large-scale statistical exploratory prediction exercise on the unique ADHD 200 data set. The exercise produced several potential leads for future scientific exploration of the neurological basis of ADHD. PMID:22969709

Measurement of airfoil heat transfer coefficients on a turbine stage

NASA Technical Reports Server (NTRS)

Dring, R. P.; Blair, M. F.

1984-01-01

The primary basis for heat transfer analysis of turbine airfoils is experimental data obtained in linear cascades. A detailed set of heat transfer coefficients was obtained along the midspan of a stator and a rotor in a rotating turbine stage. The data are to be compared to standard analyses of blade boundary layer heat transfer. A detailed set of heat transfer coefficients was obtained along the midspan of a stator located in the wake of a full upstream turbine stage. Two levels of inlet turbulence (1 and 10 percent) were used. The analytical capability will be examined to improve prediction of the experimental data.

Spectroscopy of exotic hadrons formed from dynamical diquarks

NASA Astrophysics Data System (ADS)

Lebed, Richard F.

2017-12-01

The dynamical diquark picture asserts that exotic hadrons can be formed from widely separated colored diquark or triquark components. We use the Born-Oppenheimer (BO) approximation to study the spectrum of states thus constructed, both in the basis of diquark spins and in the basis of heavy quark-antiquark spins. We develop a compact notation for naming these states, and use the results of lattice simulations for hybrid mesons to predict the lowest expected BO potentials for both tetraquarks and pentaquarks. We then compare to the set of exotic candidates with experimentally determined quantum numbers, and find that all of them can be accommodated. Once decay modes are also considered, one can develop selection rules of both exact (JP C conservation) and approximate (within the context of the BO approximation) types and test their effectiveness. We find that the most appealing way to satisfy both sets of selection rules requires including additional low-lying BO potentials, a hypothesis that can be checked on the lattice.

A combined experimental and DFT investigation of disazo dye having pyrazole skeleton

NASA Astrophysics Data System (ADS)

Şener, Nesrin; Bayrakdar, Alpaslan; Kart, Hasan Hüseyin; Şener, İzzet

2017-02-01

Disazo dye containing pyrazole skeleton has been synthesized. The structure of the dye has been confirmed by using FT-IR, 1H NMR, 13C NMR, HRMS spectral technique and elemental analysis. The molecular geometry and infrared spectrum are also calculated by the Density Functional Theory (DFT) employing B3LYP level with 6-311G (d,p) basis set. The chemical shifts calculation for 1H NMR of the title molecule is done by using by Gauge-Invariant Atomic Orbital (GIAO) method by utilizing the same basis sets. The total density of state, the partial density of state and the overlap population density of state diagram analysis are done via Gauss Sum 3.0 program. Frontier molecular orbitals such as highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) and molecular electrostatic potential surface on the title molecule are predicted for various intramolecular interactions that are responsible for the stabilization of the molecule. The experimental results and theoretical values have been compared.

Predicting category intuitiveness with the rational model, the simplicity model, and the generalized context model.

PubMed

Pothos, Emmanuel M; Bailey, Todd M

2009-07-01

Naïve observers typically perceive some groupings for a set of stimuli as more intuitive than others. The problem of predicting category intuitiveness has been historically considered the remit of models of unsupervised categorization. In contrast, this article develops a measure of category intuitiveness from one of the most widely supported models of supervised categorization, the generalized context model (GCM). Considering different category assignments for a set of instances, the authors asked how well the GCM can predict the classification of each instance on the basis of all the other instances. The category assignment that results in the smallest prediction error is interpreted as the most intuitive for the GCM-the authors refer to this way of applying the GCM as "unsupervised GCM." The authors systematically compared predictions of category intuitiveness from the unsupervised GCM and two models of unsupervised categorization: the simplicity model and the rational model. The unsupervised GCM compared favorably with the simplicity model and the rational model. This success of the unsupervised GCM illustrates that the distinction between supervised and unsupervised categorization may need to be reconsidered. However, no model emerged as clearly superior, indicating that there is more work to be done in understanding and modeling category intuitiveness.

Machine learning approaches for estimation of prediction interval for the model output.

PubMed

Shrestha, Durga L; Solomatine, Dimitri P

2006-03-01

A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the prediction interval) of the underlying distribution of prediction errors. The idea is to partition the input space into different zones or clusters having similar model errors using fuzzy c-means clustering. The prediction interval is constructed for each cluster on the basis of empirical distributions of the errors associated with all instances belonging to the cluster under consideration and propagated from each cluster to the examples according to their membership grades in each cluster. Then a regression model is built for in-sample data using computed prediction limits as targets, and finally, this model is applied to estimate the prediction intervals (limits) for out-of-sample data. The method was tested on artificial and real hydrologic data sets using various machine learning techniques. Preliminary results show that the method is superior to other methods estimating the prediction interval. A new method for evaluating performance for estimating prediction interval is proposed as well.

Derivation of a formula for the resonance integral for a nonorthogonal basis set

PubMed Central

Yim, Yung-Chang; Eyring, Henry

1981-01-01

In a self-consistent field calculation, a formula for the off-diagonal matrix elements of the core Hamiltonian is derived for a nonorthogonal basis set by a polyatomic approach. A set of parameters is then introduced for the repulsion integral formula of Mataga-Nishimoto to fit the experimental data. The matrix elements computed for the nonorthogonal basis set in the π-electron approximation are transformed to those for an orthogonal basis set by the Löwdin symmetrical orthogonalization. PMID:16593009

Molecular structure and vibrational assignments of 2,4-dichlorophenoxyacetic acid herbicide

NASA Astrophysics Data System (ADS)

Badawi, Hassan M.

2010-09-01

The structural stability of 2,4-dichlorophenoxyacetic acid was investigated by the DFT-B3LYP and the ab initio MP2 calculations with the 6-311G** basis set. From the calculations at both levels of theory the Cgcpp structure was predicted to be the lowest energy minimum for the acid. The DFT and the MP2 levels disagreed about the nature of the second stable structure of 2,4-dichlorophenoxyacetic acid. At the DFT-B3LYP level of calculation the planar Tttp ( transoid O dbnd C sbnd O sbnd H) and the non-planar Tgcpp ( cisoid O dbnd C sbnd O sbnd H) forms were predicted to be 0.7 and 1.5 kcal/mol, respectively higher in energy than the Cgcpp conformation. At the MP2 level the two high energy Tttp and Tgcpp forms were predicted to be 2.7 and 1.4 kcal/mol, respectively higher in energy than the ground state Cgcpp structure. The Tgcpp form was adopted as the second possible structure of 2,4-dichlorophenoxyacetic acid on the basis of the fact that the Møller-Plesset calculations account better than the DFT ones for the non-bonding O⋯H interactions. The vibrational frequencies of the lowest energy Cgcpp conformer were computed at the B3LYP level of theory and tentative vibrational assignments were provided on the basis of normal coordinate analysis and experimental infrared and Raman data.

Evaluating predictive modeling’s potential to improve teleretinal screening participation in urban safety net clinics

PubMed Central

Ogunyemi, Omolola; Teklehaimanot, Senait; Patty, Lauren; Moran, Erin; George, Sheba

2013-01-01

Introduction Screening guidelines for diabetic patients recommend yearly eye examinations to detect diabetic retinopathy and other forms of diabetic eye disease. However, annual screening rates for retinopathy in US urban safety net settings remain low. Methods Using data gathered from a study of teleretinal screening in six urban safety net clinics, we assessed whether predictive modeling could be of value in identifying patients at risk of developing retinopathy. We developed and examined the accuracy of two predictive modeling approaches for diabetic retinopathy in a sample of 513 diabetic individuals, using routinely available clinical variables from retrospective medical record reviews. Bayesian networks and radial basis function (neural) networks were learned using ten-fold cross-validation. Results The predictive models were modestly predictive with the best model having an AUC of 0.71. Discussion Using routinely available clinical variables to predict patients at risk of developing retinopathy and to target them for annual eye screenings may be of some usefulness to safety net clinics. PMID:23920536

Evaluating predictive modeling's potential to improve teleretinal screening participation in urban safety net clinics.

PubMed

Ogunyemi, Omolola; Teklehaimanot, Senait; Patty, Lauren; Moran, Erin; George, Sheba

2013-01-01

Screening guidelines for diabetic patients recommend yearly eye examinations to detect diabetic retinopathy and other forms of diabetic eye disease. However, annual screening rates for retinopathy in US urban safety net settings remain low. Using data gathered from a study of teleretinal screening in six urban safety net clinics, we assessed whether predictive modeling could be of value in identifying patients at risk of developing retinopathy. We developed and examined the accuracy of two predictive modeling approaches for diabetic retinopathy in a sample of 513 diabetic individuals, using routinely available clinical variables from retrospective medical record reviews. Bayesian networks and radial basis function (neural) networks were learned using ten-fold cross-validation. The predictive models were modestly predictive with the best model having an AUC of 0.71. Using routinely available clinical variables to predict patients at risk of developing retinopathy and to target them for annual eye screenings may be of some usefulness to safety net clinics.

Patent Analysis for Supporting Merger and Acquisition (M&A) Prediction: A Data Mining Approach

NASA Astrophysics Data System (ADS)

Wei, Chih-Ping; Jiang, Yu-Syun; Yang, Chin-Sheng

M&A plays an increasingly important role in the contemporary business environment. Companies usually conduct M&A to pursue complementarity from other companies for preserving and/or extending their competitive advantages. For the given bidder company, a critical first step to the success of M&A activities is the appropriate selection of target companies. However, existing studies on M&A prediction incur several limitations, such as the exclusion of technological variables in M&A prediction models and the omission of the profile of the respective bidder company and its compatibility with candidate target companies. In response to these limitations, we propose an M&A prediction technique which not only encompasses technological variables derived from patent analysis as prediction indictors but also takes into account the profiles of both bidder and candidate target companies when building an M&A prediction model. We collect a set of real-world M&A cases to evaluate the proposed technique. The evaluation results are encouraging and will serve as a basis for future studies.

3D-QSAR comparative molecular field analysis on opioid receptor antagonists: pooling data from different studies.

PubMed

Peng, Youyi; Keenan, Susan M; Zhang, Qiang; Kholodovych, Vladyslav; Welsh, William J

2005-03-10

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were constructed using comparative molecular field analysis (CoMFA) on a series of opioid receptor antagonists. To obtain statistically significant and robust CoMFA models, a sizable data set of naltrindole and naltrexone analogues was assembled by pooling biological and structural data from independent studies. A process of "leave one data set out", similar to the traditional "leave one out" cross-validation procedure employed in partial least squares (PLS) analysis, was utilized to study the feasibility of pooling data in the present case. These studies indicate that our approach yields statistically significant and highly predictive CoMFA models from the pooled data set of delta, mu, and kappa opioid receptor antagonists. All models showed excellent internal predictability and self-consistency: q(2) = 0.69/r(2) = 0.91 (delta), q(2) = 0.67/r(2) = 0.92 (mu), and q(2) = 0.60/r(2) = 0.96 (kappa). The CoMFA models were further validated using two separate test sets: one test set was selected randomly from the pooled data set, while the other test set was retrieved from other published sources. The overall excellent agreement between CoMFA-predicted and experimental binding affinities for a structurally diverse array of ligands across all three opioid receptor subtypes gives testimony to the superb predictive power of these models. CoMFA field analysis demonstrated that the variations in binding affinity of opioid antagonists are dominated by steric rather than electrostatic interactions with the three opioid receptor binding sites. The CoMFA steric-electrostatic contour maps corresponding to the delta, mu, and kappa opioid receptor subtypes reflected the characteristic similarities and differences in the familiar "message-address" concept of opioid receptor ligands. Structural modifications to increase selectivity for the delta over mu and kappa opioid receptors have been predicted on the basis of the CoMFA contour maps. The structure-activity relationships (SARs) together with the CoMFA models should find utility for the rational design of subtype-selective opioid receptor antagonists.

Evaluation of the structural properties of powerful pesticide dieldrin in different media and their complete vibrational assignment

NASA Astrophysics Data System (ADS)

Castillo, María V.; Iramain, Maximiliano A.; Davies, Lilian; Manzur, María E.; Brandán, Silvia Antonia

2018-02-01

Dieldrin was characterized by using Fourier Transform infrared (FT-IR) and Raman (FT-Raman), Ultraviolet-Visible (UV-Visible) spectroscopies. The structural and vibrational properties for dieldrin in gas phase and in aqueous solution were computed combining those experimental spectra with hybrids B3LYP and WB97XD calculations by using the 6-31G* and 6-311++G** basis sets. Here, the experimental available Hydrogen and Carbon Nuclear Magnetic Resonance (1H and 13C NMR) for dieldrin were also used and compared with those predicted by calculations. The B3LYP/6-311++G** method generates the most stable structures while the results have demonstrated certain dependence of the volume and dipole moment values with the method, size of the basis set and, with the studied media. The lower solvation energy for dieldrin (-32.94 kJ/mol) is observed for the higher contraction volume (-2.4 Å3) by using the B3LYP/6-31G* method. The NBO studies suggest a high stability of dieldrin in gas phase by using the WB97XD/6-31G* method due to the n→π* and n*→π* interactions while the AIM analyses support this high stability by the C18⋯H26 and C14⋯O7 contacts. The different topological properties observed in the R5 ring suggest that probably this ring plays a very important role in the toxics properties of dieldrin. The frontier orbitals show that when dieldrin is compared with other toxics substances the reactivity increases in the following order: CO < STX < dieldrin < C6Cl6

Potential energy surface and vibrational band origins of the triatomic lithium cation

NASA Astrophysics Data System (ADS)

Searles, Debra J.; Dunne, Simon J.; von Nagy-Felsobuki, Ellak I.

The 104 point CISD Li +3 potential energy surface and its analytical representation is reported. The calculations predict the minimum energy geometry to be an equilateral triangle of side RLiLi = 3.0 Å and of energy - 22.20506 E h. A fifth-order Morse—Dunham type analytical force field is used in the Carney—Porter normal co-ordinate vibrational Hamiltonian, the corresponding eigenvalue problem being solved variationally using a 560 configurational finite-element basis set. The predicted assignment of the vibrational band origins is in accord with that reported for H +3. Moreover, for 6Li +3 and 7Li +3 the lowest i.r. accessible band origin is the overlineν0,1,±1 predicted to be at 243.6 and 226.0 cm -1 respectively.

Using an optimal CC-PLSR-RBFNN model and NIR spectroscopy for the starch content determination in corn

NASA Astrophysics Data System (ADS)

Jiang, Hao; Lu, Jiangang

2018-05-01

Corn starch is an important material which has been traditionally used in the fields of food and chemical industry. In order to enhance the rapidness and reliability of the determination for starch content in corn, a methodology is proposed in this work, using an optimal CC-PLSR-RBFNN calibration model and near-infrared (NIR) spectroscopy. The proposed model was developed based on the optimal selection of crucial parameters and the combination of correlation coefficient method (CC), partial least squares regression (PLSR) and radial basis function neural network (RBFNN). To test the performance of the model, a standard NIR spectroscopy data set was introduced, containing spectral information and chemical reference measurements of 80 corn samples. For comparison, several other models based on the identical data set were also briefly discussed. In this process, the root mean square error of prediction (RMSEP) and coefficient of determination (Rp2) in the prediction set were used to make evaluations. As a result, the proposed model presented the best predictive performance with the smallest RMSEP (0.0497%) and the highest Rp2 (0.9968). Therefore, the proposed method combining NIR spectroscopy with the optimal CC-PLSR-RBFNN model can be helpful to determine starch content in corn.

Fisher's geometric model predicts the effects of random mutations when tested in the wild.

PubMed

Stearns, Frank W; Fenster, Charles B

2016-02-01

Fisher's geometric model of adaptation (FGM) has been the conceptual foundation for studies investigating the genetic basis of adaptation since the onset of the neo Darwinian synthesis. FGM describes adaptation as the movement of a genotype toward a fitness optimum due to beneficial mutations. To date, one prediction of FGM, the probability of improvement is related to the distance from the optimum, has only been tested in microorganisms under laboratory conditions. There is reason to believe that results might differ under natural conditions where more mutations likely affect fitness, and where environmental variance may obscure the expected pattern. We chemically induced mutations into a set of 19 Arabidopsis thaliana accessions from across the native range of A. thaliana and planted them alongside the premutated founder lines in two habitats in the mid-Atlantic region of the United States under field conditions. We show that FGM is able to predict the outcome of a set of random induced mutations on fitness in a set of A. thaliana accessions grown in the wild: mutations are more likely to be beneficial in relatively less fit genotypes. This finding suggests that FGM is an accurate approximation of the process of adaptation under more realistic ecological conditions. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Robust prediction of three-dimensional spinal curve from back surface for non-invasive follow-up of scoliosis

NASA Astrophysics Data System (ADS)

Bergeron, Charles; Labelle, Hubert; Ronsky, Janet; Zernicke, Ronald

2005-04-01

Spinal curvature progression in scoliosis patients is monitored from X-rays, and this serial exposure to harmful radiation increases the incidence of developing cancer. With the aim of reducing the invasiveness of follow-up, this study seeks to relate the three-dimensional external surface to the internal geometry, having assumed that that the physiological links between these are sufficiently regular across patients. A database was used of 194 quasi-simultaneous acquisitions of two X-rays and a 3D laser scan of the entire trunk. Data was processed to sets of datapoints representing the trunk surface and spinal curve. Functional data analyses were performed using generalized Fourier series using a Haar basis and functional minimum noise fractions. The resulting coefficients became inputs and outputs, respectively, to an array of support vector regression (SVR) machines. SVR parameters were set based on theoretical results, and cross-validation increased confidence in the system's performance. Predicted lateral and frontal views of the spinal curve from the back surface demonstrated average L2-errors of 6.13 and 4.38 millimetres, respectively, across the test set; these compared favourably with measurement error in data. This constitutes a first robust prediction of the 3D spinal curve from external data using learning techniques.

Reassessment of the positive predictive value and specificity of Xpert MTB/RIF: a diagnostic accuracy study in the context of community-wide screening for tuberculosis.

PubMed

Ho, Jennifer; Nguyen, Phuong Thi Bich; Nguyen, Thu Anh; Tran, Khoa Hien; Van Nguyen, Son; Nguyen, Nhung Viet; Nguyen, Hoa Binh; Luu, Khanh Boi; Fox, Greg J; Marks, Guy B

2016-09-01

Community-wide screening for tuberculosis with Xpert MTB/RIF as a primary screening tool overcomes some of the limitations of conventional screening. However, concerns exist about the low positive predictive value of this test in screening settings. We did a cross-sectional assessment of this diagnostic test to directly estimate the actual positive predictive value of Xpert MTB/RIF when used in the setting of community-wide screening for tuberculosis, and to draw an inference about the specificity of the test for tuberculosis detection. Field staff visited households in 60 randomly selected villages in Ca Mau province, Vietnam. We included people aged 15 years or older who provided written informed consent and were able to produce 0·5 mL or more of sputum, irrespective of reported symptoms. Participants were tested with Xpert MTB/RIF, then those with positive results had two further sputum samples tested for smear microscopy and culture, and underwent chest radiography at the provincial TB Health Center. The positive predictive value of Xpert MTB/RIF was compared against two reference standards for tuberculosis diagnosis-a positive sputum culture for Mycobacterium tuberculosis, and a positive sputum culture or a chest radiograph consistent with active pulmonary tuberculosis. We then calculated the specificity of Xpert MTB/RIF for tuberculosis detection on the basis of these positive predictive values and disease prevalence in this setting. 43 435 adults consented to screening with Xpert MTB/RIF. Sputum samples of 0·5 mL or greater were collected from 23 202 participants, producing 22 673 valid results. 169 participants had positive Xpert MTB/RIF results (0·39% of those screened and 0·75% of those with valid sputum results). The positive predictive value of Xpert MTB/RIF was 61·0% (95% CI 52·8-68·7) when compared against a positive sputum culture and 83·9% (76·8-89·2) when compared against a positive sputum culture or chest radiograph consistent with active tuberculosis. On the basis of these positive predictive values, the specificity of Xpert MTB/RIF was determined to be between 99·78% (95% CI 99·71-99·84) and 99·93% (99·88-99·96). The positive predictive value and specificity of Xpert MTB/RIF in the context of community-wide screening for tuberculosis is substantially higher than that predicted in previous studies. Our findings support the potential role of Xpert MTB/RIF as a primary screening tool to detect prevalent cases of tuberculosis in the community. Australian National Health and Medical Research Council. Copyright © 2016 Elsevier Ltd. All rights reserved.

NMR, FT-IR, Raman and UV-Vis spectroscopic investigation and DFT study of 6-Bromo-3-Pyridinyl Boronic Acid

NASA Astrophysics Data System (ADS)

Dikmen, Gökhan; Alver, Özgür

2015-11-01

Possible stable conformers and geometrical molecular structures of 6-Bromo-3-Pyridinyl Boronic acid (6B3PBA; C5H5BBrNO2) were studied experimentally and theoretically using FT-IR and Raman spectroscopic methods. FT-IR and Raman spectra were recorded in the region of 4000-400 cm-1 and 3700-400 cm-1, respectively. The structural properties were investigated further, using 1H, 13C, 1H coupled 13C, HETCOR, COSY and APT NMR techniques. The optimized geometric structures were searched by Becke-3-Lee-Yang-Parr (B3LYP) hybrid density functional theory method with 6-311++G(d, p) basis set. Vibrational wavenumbers of 6B3PBA were calculated whereby B3LYP density functional methods including 6-311++G(d, p), 6-311G(d, p), 6-311G(d), 6-31G(d, p) and 6-31G(d) basis sets. The comparison of the experimentally and theoretically obtained results using mean absolute error and experimental versus calculated correlation coefficients for the vibrational wavenumbers indicates that B3LYP method with 6-311++G(d, p) gives more satisfactory results for predicting vibrational wavenumbers when compared to the 6-311G(d, p), 6-311G(d), 6-31G(d, p) and 6-31G(d) basis sets. However, this method and none of the mentioned methods here seem suitable for the calculations of OH stretching modes, most likely because increasing unharmonicity in the high wave number region and possible intra and inter molecular interactions at OH edges lead some deviations between experimental and theoretical results. Moreover, reliable vibrational assignments were made on the basis of total energy distribution (TED) calculated using scaled quantum mechanical (SQM) method.

Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM). I: Model intercomparison with current land use

USGS Publications Warehouse

Breuer, L.; Huisman, J.A.; Willems, P.; Bormann, H.; Bronstert, A.; Croke, B.F.W.; Frede, H.-G.; Graff, T.; Hubrechts, L.; Jakeman, A.J.; Kite, G.; Lanini, J.; Leavesley, G.; Lettenmaier, D.P.; Lindstrom, G.; Seibert, J.; Sivapalan, M.; Viney, N.R.

2009-01-01

This paper introduces the project on 'Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM)' that aims at investigating the envelope of predictions on changes in hydrological fluxes due to land use change. As part of a series of four papers, this paper outlines the motivation and setup of LUCHEM, and presents a model intercomparison for the present-day simulation results. Such an intercomparison provides a valuable basis to investigate the effects of different model structures on model predictions and paves the ground for the analysis of the performance of multi-model ensembles and the reliability of the scenario predictions in companion papers. In this study, we applied a set of 10 lumped, semi-lumped and fully distributed hydrological models that have been previously used in land use change studies to the low mountainous Dill catchment, Germany. Substantial differences in model performance were observed with Nash-Sutcliffe efficiencies ranging from 0.53 to 0.92. Differences in model performance were attributed to (1) model input data, (2) model calibration and (3) the physical basis of the models. The models were applied with two sets of input data: an original and a homogenized data set. This homogenization of precipitation, temperature and leaf area index was performed to reduce the variation between the models. Homogenization improved the comparability of model simulations and resulted in a reduced average bias, although some variation in model data input remained. The effect of the physical differences between models on the long-term water balance was mainly attributed to differences in how models represent evapotranspiration. Semi-lumped and lumped conceptual models slightly outperformed the fully distributed and physically based models. This was attributed to the automatic model calibration typically used for this type of models. Overall, however, we conclude that there was no superior model if several measures of model performance are considered and that all models are suitable to participate in further multi-model ensemble set-ups and land use change scenario investigations. ?? 2008 Elsevier Ltd. All rights reserved.

Accurate potential energy, dipole moment curves, and lifetimes of vibrational states of heteronuclear alkali dimers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fedorov, Dmitry A.; Varganov, Sergey A., E-mail: svarganov@unr.edu; Derevianko, Andrei

2014-05-14

We calculate the potential energy curves, the permanent dipole moment curves, and the lifetimes of the ground and excited vibrational states of the heteronuclear alkali dimers XY (X, Y = Li, Na, K, Rb, Cs) in the X{sup 1}Σ{sup +} electronic state using the coupled cluster with singles doubles and triples method. All-electron quadruple-ζ basis sets with additional core functions are used for Li and Na, and small-core relativistic effective core potentials with quadruple-ζ quality basis sets are used for K, Rb, and Cs. The inclusion of the coupled cluster non-perturbative triple excitations is shown to be crucial for obtainingmore » the accurate potential energy curves. A large one-electron basis set with additional core functions is needed for the accurate prediction of permanent dipole moments. The dissociation energies are overestimated by only 14 cm{sup −1} for LiNa and by no more than 114 cm{sup −1} for the other molecules. The discrepancies between the experimental and calculated harmonic vibrational frequencies are less than 1.7 cm{sup −1}, and the discrepancies for the anharmonic correction are less than 0.1 cm{sup −1}. We show that correlation between atomic electronegativity differences and permanent dipole moment of heteronuclear alkali dimers is not perfect. To obtain the vibrational energies and wave functions the vibrational Schrödinger equation is solved with the B-spline basis set method. The transition dipole moments between all vibrational states, the Einstein coefficients, and the lifetimes of the vibrational states are calculated. We analyze the decay rates of the vibrational states in terms of spontaneous emission, and stimulated emission and absorption induced by black body radiation. In all studied heteronuclear alkali dimers the ground vibrational states have much longer lifetimes than any excited states.« less

Estimating the intrinsic limit of the Feller-Peterson-Dixon composite approach when applied to adiabatic ionization potentials in atoms and small molecules

NASA Astrophysics Data System (ADS)

Feller, David

2017-07-01

Benchmark adiabatic ionization potentials were obtained with the Feller-Peterson-Dixon (FPD) theoretical method for a collection of 48 atoms and small molecules. In previous studies, the FPD method demonstrated an ability to predict atomization energies (heats of formation) and electron affinities well within a 95% confidence level of ±1 kcal/mol. Large 1-particle expansions involving correlation consistent basis sets (up to aug-cc-pV8Z in many cases and aug-cc-pV9Z for some atoms) were chosen for the valence CCSD(T) starting point calculations. Despite their cost, these large basis sets were chosen in order to help minimize the residual basis set truncation error and reduce dependence on approximate basis set limit extrapolation formulas. The complementary n-particle expansion included higher order CCSDT, CCSDTQ, or CCSDTQ5 (coupled cluster theory with iterative triple, quadruple, and quintuple excitations) corrections. For all of the chemical systems examined here, it was also possible to either perform explicit full configuration interaction (CI) calculations or to otherwise estimate the full CI limit. Additionally, corrections associated with core/valence correlation, scalar relativity, anharmonic zero point vibrational energies, non-adiabatic effects, and other minor factors were considered. The root mean square deviation with respect to experiment for the ionization potentials was 0.21 kcal/mol (0.009 eV). The corresponding level of agreement for molecular enthalpies of formation was 0.37 kcal/mol and for electron affinities 0.20 kcal/mol. Similar good agreement with experiment was found in the case of molecular structures and harmonic frequencies. Overall, the combination of energetic, structural, and vibrational data (655 comparisons) reflects the consistent ability of the FPD method to achieve close agreement with experiment for small molecules using the level of theory applied in this study.

Near Identifiability of Dynamical Systems

NASA Technical Reports Server (NTRS)

Hadaegh, F. Y.; Bekey, G. A.

1987-01-01

Concepts regarding approximate mathematical models treated rigorously. Paper presents new results in analysis of structural identifiability, equivalence, and near equivalence between mathematical models and physical processes they represent. Helps establish rigorous mathematical basis for concepts related to structural identifiability and equivalence revealing fundamental requirements, tacit assumptions, and sources of error. "Structural identifiability," as used by workers in this field, loosely translates as meaning ability to specify unique mathematical model and set of model parameters that accurately predict behavior of corresponding physical system.

Communication: A novel implementation to compute MP2 correlation energies without basis set superposition errors and complete basis set extrapolation.

PubMed

Dixit, Anant; Claudot, Julien; Lebègue, Sébastien; Rocca, Dario

2017-06-07

By using a formulation based on the dynamical polarizability, we propose a novel implementation of second-order Møller-Plesset perturbation (MP2) theory within a plane wave (PW) basis set. Because of the intrinsic properties of PWs, this method is not affected by basis set superposition errors. Additionally, results are converged without relying on complete basis set extrapolation techniques; this is achieved by using the eigenvectors of the static polarizability as an auxiliary basis set to compactly and accurately represent the response functions involved in the MP2 equations. Summations over the large number of virtual states are avoided by using a formalism inspired by density functional perturbation theory, and the Lanczos algorithm is used to include dynamical effects. To demonstrate this method, applications to three weakly interacting dimers are presented.

Sweetness prediction of natural compounds.

PubMed

Chéron, Jean-Baptiste; Casciuc, Iuri; Golebiowski, Jérôme; Antonczak, Serge; Fiorucci, Sébastien

2017-04-15

Based on the most exhaustive database of sweeteners with known sweetness values, a new quantitative structure-activity relationship model for sweetness prediction has been set up. Analysis of the physico-chemical properties of sweeteners in the database indicates that the structure of most potent sweeteners combines a hydrophobic scaffold functionalized by a limited number of hydrogen bond sites (less than 4 hydrogen bond donors and 10 acceptors), with a moderate molecular weight ranging from 350 to 450g·mol -1 . Prediction of sweetness, bitterness and toxicity properties of the largest database of natural compounds have been performed. In silico screening reveals that the majority of the predicted natural intense sweeteners comprise saponin or stevioside scaffolds. The model highlights that their sweetness potency is comparable to known natural sweeteners. The identified compounds provide a rational basis to initiate the design and chemosensory analysis of new low-calorie sweeteners. Copyright © 2016 Elsevier Ltd. All rights reserved.

Correlation consistent valence basis sets for use with the Stuttgart-Dresden-Bonn relativistic effective core potentials: The atoms Ga-Kr and In-Xe

NASA Astrophysics Data System (ADS)

Martin, Jan M. L.; Sundermann, Andreas

2001-02-01

We propose large-core correlation-consistent (cc) pseudopotential basis sets for the heavy p-block elements Ga-Kr and In-Xe. The basis sets are of cc-pVTZ and cc-pVQZ quality, and have been optimized for use with the large-core (valence-electrons only) Stuttgart-Dresden-Bonn (SDB) relativistic pseudopotentials. Validation calculations on a variety of third-row and fourth-row diatomics suggest them to be comparable in quality to the all-electron cc-pVTZ and cc-pVQZ basis sets for lighter elements. Especially the SDB-cc-pVQZ basis set in conjunction with a core polarization potential (CPP) yields excellent agreement with experiment for compounds of the later heavy p-block elements. For accurate calculations on Ga (and, to a lesser extent, Ge) compounds, explicit treatment of 13 valence electrons appears to be desirable, while it seems inevitable for In compounds. For Ga and Ge, we propose correlation consistent basis sets extended for (3d) correlation. For accurate calculations on organometallic complexes of interest to homogenous catalysis, we recommend a combination of the standard cc-pVTZ basis set for first- and second-row elements, the presently derived SDB-cc-pVTZ basis set for heavier p-block elements, and for transition metals, the small-core [6s5p3d] Stuttgart-Dresden basis set-relativistic effective core potential combination supplemented by (2f1g) functions with exponents given in the Appendix to the present paper.

Monitoring and Control of an Adsorption System Using Electrical Properties of the Adsorbent for Organic Compound Abatement.

PubMed

Hu, Ming-Ming; Emamipour, Hamidreza; Johnsen, David L; Rood, Mark J; Song, Linhua; Zhang, Zailong

2017-07-05

Adsorption systems typically need gas and temperature sensors to monitor their adsorption/regeneration cycles to separate gases from gas streams. Activated carbon fiber cloth (ACFC)-electrothermal swing adsorption (ESA) is an adsorption system that has the potential to be controlled with the electrical properties of the adsorbent and is studied here to monitor and control the adsorption/regeneration cycles without the use of gas and temperature sensors and to predict breakthrough before it occurs. The ACFC's electrical resistance was characterized on the basis of the amount of adsorbed organic gas/vapor and the adsorbent temperature. These relationships were then used to develop control logic to monitor and control ESA cycles on the basis of measured resistance and applied power values. Continuous sets of adsorption and regeneration cycles were performed sequentially entirely on the basis of remote electrical measurements and achieved ≥95% capture efficiency at inlet concentrations of 2000 and 4000 ppm v for isobutane, acetone, and toluene in dry and elevated relative humidity gas streams, demonstrating a novel cyclic ESA system that does not require gas or temperature sensors. This contribution is important because it reduces the cost and simplifies the system, predicts breakthrough before its occurrence, and reduces emissions to the atmosphere.

Hybrid Grid and Basis Set Approach to Quantum Chemistry DMRG

NASA Astrophysics Data System (ADS)

Stoudenmire, Edwin Miles; White, Steven

We present a new approach for using DMRG for quantum chemistry that combines the advantages of a basis set with that of a grid approximation. Because DMRG scales linearly for quasi-one-dimensional systems, it is feasible to approximate the continuum with a fine grid in one direction while using a standard basis set approach for the transverse directions. Compared to standard basis set methods, we reach larger systems and achieve better scaling when approaching the basis set limit. The flexibility and reduced costs of our approach even make it feasible to incoporate advanced DMRG techniques such as simulating real-time dynamics. Supported by the Simons Collaboration on the Many-Electron Problem.

Factors affecting length of stay in forensic hospital setting: need for therapeutic security and course of admission.

PubMed

Davoren, Mary; Byrne, Orla; O'Connell, Paul; O'Neill, Helen; O'Reilly, Ken; Kennedy, Harry G

2015-11-23

Patients admitted to a secure forensic hospital are at risk of a long hospital stay. Forensic hospital beds are a scarce and expensive resource and ability to identify the factors predicting length of stay at time of admission would be beneficial. The DUNDRUM-1 triage security scale and DUNDRUM-2 triage urgency scale are designed to assess need for therapeutic security and urgency of that need while the HCR-20 predicts risk of violence. We hypothesized that items on the DUNDRUM-1 and DUNDRUM-2 scales, rated at the time of pre-admission assessment, would predict length of stay in a medium secure forensic hospital setting. This is a prospective study. All admissions to a medium secure forensic hospital setting were collated over a 54 month period (n = 279) and followed up for a total of 66 months. Each patient was rated using the DUNDRUM-1 triage security scale and DUNDRUM-2 triage urgency scale as part of a pre-admission assessment (n = 279) and HCR-20 within 2 weeks of admission (n = 187). Episodes of harm to self, harm to others and episodes of seclusion whilst an in-patient were collated. Date of discharge was noted for each individual. Diagnosis at the time of pre-admission assessment (adjustment disorder v other diagnosis), predicted legal status (sentenced v mental health order) and items on the DUNDRUM-1 triage security scale and the DUNDRUM-2 triage urgency scale, also rated at the time of pre-admission assessment, predicted length of stay in the forensic hospital setting. Need for seclusion following admission also predicted length of stay. These findings may form the basis for a structured professional judgment instrument, rated prior to or at time of admission, to assist in estimating length of stay for forensic patients. Such a tool would be useful to clinicians, service planners and commissioners given the high cost of secure psychiatric care.

Antihydrogen-hydrogen elastic scattering at thermal energies using an atomic-orbital technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sinha, Prabal K.; Chaudhuri, Puspitapallab; Ghosh, A.S.

2003-05-01

In view of the recent interest in the trapping of antihydrogen atom H(bar sign), at very low temperatures, H-bar-H scattering has been investigated at low incident energies using a close-coupling model with the basis set H-bar(1s,2s,2p-bar)+H(1s,2s,2p-bar). The predicted s-wave elastic phase shifts, scattering length, and effective range are in a good agreement with the other recent predictions of Jonsell et al. and of Armour and Chamberlain. The results indicate that the atomic orbital expansion model is suitable to study the H-bar-H scattering at ultracold temperatures.

The Physics Basis of ITER Confinement

NASA Astrophysics Data System (ADS)

Wagner, F.

2009-02-01

ITER will be the first fusion reactor and the 50 year old dream of fusion scientists will become reality. The quality of magnetic confinement will decide about the success of ITER, directly in the form of the confinement time and indirectly because it decides about the plasma parameters and the fluxes, which cross the separatrix and have to be handled externally by technical means. This lecture portrays some of the basic principles which govern plasma confinement, uses dimensionless scaling to set the limits for the predictions for ITER, an approach which also shows the limitations of the predictions, and describes briefly the major characteristics and physics behind the H-mode—the preferred confinement regime of ITER.

DFT calculation and vibrational spectroscopic studies of 2-(tert-butoxycarbonyl (Boc) -amino)-5-bromopyridine

NASA Astrophysics Data System (ADS)

Premkumar, S.; Jawahar, A.; Mathavan, T.; Kumara Dhas, M.; Sathe, V. G.; Milton Franklin Benial, A.

2014-08-01

The molecular structure of 2-(tert-butoxycarbonyl (Boc) -amino)-5-bromopyridine (BABP) was optimized by the DFT/B3LYP method with 6-311G (d,p), 6-311++G (d,p) and cc-pVTZ basis sets using the Gaussian 09 program. The most stable optimized structure of the molecule was predicted by the DFT/B3LYP method with cc-pVTZ basis set. The vibrational frequencies, Mulliken atomic charge distribution, frontier molecular orbitals and thermodynamical parameters were calculated. These calculations were done at the ground state energy level of BABP without applying any constraint on the potential energy surface. The vibrational spectra were experimentally recorded using Fourier Transform-Infrared (FT-IR) and micro-Raman spectrometer. The computed vibrational frequencies were scaled by scale factors to yield a good agreement with observed experimental vibrational frequencies. The complete theoretically calculated and experimentally observed vibrational frequencies were assigned on the basis of Potential Energy Distribution (PED) calculation using the VEDA 4.0 program. The vibrational modes assignments were performed by using the animation option of GaussView 05 graphical interface for Gaussian program. The Mulliken atomic charge distribution was calculated for BABP molecule. The molecular reactivity and stability of BABP were also studied by frontier molecular orbitals (FMOs) analysis.

Feasibility Analysis of Incorporating In-Vitro Toxicokinetic Data ...

EPA Pesticide Factsheets

The underlying principle of read-across is that biological activity is a function of physical and structural properties of chemicals. Analogs are typically identified on the basis of structural similarity and subsequently evaluated for their use in read-across on the basis of their bioavailability, reactivity and metabolic similarity. While the concept of similarity is the major tenet in grouping chemicals for read-across, a critical consideration is to evaluate if structural differences significantly impact toxicological activity. This is a key source of uncertainty in read-across predictions. We hypothesize that inclusion of toxicokinetic (TK) information will reduce the uncertainty in read-across predictions. TK information can help substantiate whether chemicals within a category have similar ADME properties and, hence, increase the likelihood of exhibiting similar toxicological properties. This current case study is part of a larger study aimed at performing a systematic assessment of the extent to which in-vitro TK data can obviate in-vivo TK data, while maintaining or increasing scientific confidence in read-across predictions. The analysis relied on a dataset of ~7k chemicals with predicted exposure data (chemical inventory), of which 819 chemicals had rat and/or human in-vitro TK data (analog inventory), and 33 chemicals had rat in-vivo TK data (target inventory). The set of chemicals with human in vitro TK data was investigated to determine whether str

CpG island methylation profile in non-invasive oral rinse samples is predictive of oral and pharyngeal carcinoma.

PubMed

Langevin, Scott M; Eliot, Melissa; Butler, Rondi A; Cheong, Agnes; Zhang, Xiang; McClean, Michael D; Koestler, Devin C; Kelsey, Karl T

2015-01-01

There are currently no screening tests in routine use for oral and pharyngeal cancer beyond visual inspection and palpation, which are provided on an opportunistic basis, indicating a need for development of novel methods for early detection, particularly in high-risk populations. We sought to address this need through comprehensive interrogation of CpG island methylation in oral rinse samples. We used the Infinium HumanMethylation450 BeadArray to interrogate DNA methylation in oral rinse samples collected from 154 patients with incident oral or pharyngeal carcinoma prior to treatment and 72 cancer-free control subjects. Subjects were randomly allocated to either a training or a testing set. For each subject, average methylation was calculated for each CpG island represented on the array. We applied a semi-supervised recursively partitioned mixture model to the CpG island methylation data to identify a classifier for prediction of case status in the training set. We then applied the resultant classifier to the testing set for validation and to assess the predictive accuracy. We identified a methylation classifier comprised of 22 CpG islands, which predicted oral and pharyngeal carcinoma with a high degree of accuracy (AUC = 0.92, 95 % CI 0.86, 0.98). This novel methylation panel is a strong predictor of oral and pharyngeal carcinoma case status in oral rinse samples and may have utility in early detection and post-treatment follow-up.

Prediction of physical-chemical properties of crude oils by 1H NMR analysis of neat samples and chemometrics.

PubMed

Masili, Alice; Puligheddu, Sonia; Sassu, Lorenzo; Scano, Paola; Lai, Adolfo

2012-11-01

In this work, we report the feasibility study to predict the properties of neat crude oil samples from 300-MHz NMR spectral data and partial least squares (PLS) regression models. The study was carried out on 64 crude oil samples obtained from 28 different extraction fields and aims at developing a rapid and reliable method for characterizing the crude oil in a fast and cost-effective way. The main properties generally employed for evaluating crudes' quality and behavior during refining were measured and used for calibration and testing of the PLS models. Among these, the UOP characterization factor K (K(UOP)) used to classify crude oils in terms of composition, density (D), total acidity number (TAN), sulfur content (S), and true boiling point (TBP) distillation yields were investigated. Test set validation with an independent set of data was used to evaluate model performance on the basis of standard error of prediction (SEP) statistics. Model performances are particularly good for K(UOP) factor, TAN, and TPB distillation yields, whose standard error of calibration and SEP values match the analytical method precision, while the results obtained for D and S are less accurate but still useful for predictions. Furthermore, a strategy that reduces spectral data preprocessing and sample preparation procedures has been adopted. The models developed with such an ample crude oil set demonstrate that this methodology can be applied with success to modern refining process requirements. Copyright © 2012 John Wiley & Sons, Ltd.

Design of novel quinazolinone derivatives as inhibitors for 5HT7 receptor.

PubMed

Chitta, Aparna; Jatavath, Mohan Babu; Fatima, Sabiha; Manga, Vijjulatha

2012-02-01

To study the pharmacophore properties of quinazolinone derivatives as 5HT(7) inhibitors, 3D QSAR methodologies, namely Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) were applied, partial least square (PLS) analysis was performed and QSAR models were generated. The derived model showed good statistical reliability in terms of predicting the 5HT(7) inhibitory activity of the quinazolione derivative, based on molecular property fields like steric, electrostatic, hydrophobic, hydrogen bond donor and hydrogen bond acceptor fields. This is evident from statistical parameters like q(2) (cross validated correlation coefficient) of 0.642, 0.602 and r(2) (conventional correlation coefficient) of 0.937, 0.908 for CoMFA and CoMSIA respectively. The predictive ability of the models to determine 5HT(7) antagonistic activity is validated using a test set of 26 molecules that were not included in the training set and the predictive r(2) obtained for the test set was 0.512 & 0.541. Further, the results of the derived model are illustrated by means of contour maps, which give an insight into the interaction of the drug with the receptor. The molecular fields so obtained served as the basis for the design of twenty new ligands. In addition, ADME (Adsorption, Distribution, Metabolism and Elimination) have been calculated in order to predict the relevant pharmaceutical properties, and the results are in conformity with required drug like properties.

Single-cell RNA-seq of human induced pluripotent stem cells reveals cellular heterogeneity and cell state transitions between subpopulations.

PubMed

Nguyen, Quan; Lukowski, Samuel; Chiu, Han; Senabouth, Anne; Bruxner, Timothy; Christ, Angelika; Palpant, Nathan; Powell, Joseph

2018-05-11

Heterogeneity of cell states represented in pluripotent cultures have not been described at the transcriptional level. Since gene expression is highly heterogeneous between cells, single-cell RNA sequencing can be used to identify how individual pluripotent cells function. Here, we present results from the analysis of single-cell RNA sequencing data from 18,787 individual WTC CRISPRi human induced pluripotent stem cells. We developed an unsupervised clustering method, and through this identified four subpopulations distinguishable on the basis of their pluripotent state including: a core pluripotent population (48.3%), proliferative (47.8%), early-primed for differentiation (2.8%) and late-primed for differentiation (1.1%). For each subpopulation we were able to identify the genes and pathways that define differences in pluripotent cell states. Our method identified four discrete predictor gene sets comprised of 165 unique genes that denote the specific pluripotency states; and using these sets, we developed a multigenic machine learning prediction method to accurately classify single cells into each of the subpopulations. Compared against a set of established pluripotency markers, our method increases prediction accuracy by 10%, specificity by 20%, and explains a substantially larger proportion of deviance (up to 3-fold) from the prediction model. Finally, we developed an innovative method to predict cells transitioning between subpopulations, and support our conclusions with results from two orthogonal pseudotime trajectory methods. Published by Cold Spring Harbor Laboratory Press.

Localized basis sets for unbound electrons in nanoelectronics.

PubMed

Soriano, D; Jacob, D; Palacios, J J

2008-02-21

It is shown how unbound electron wave functions can be expanded in a suitably chosen localized basis sets for any desired range of energies. In particular, we focus on the use of Gaussian basis sets, commonly used in first-principles codes. The possible usefulness of these basis sets in a first-principles description of field emission or scanning tunneling microscopy at large bias is illustrated by studying a simpler related phenomenon: The lifetime of an electron in a H atom subjected to a strong electric field.

3D QSAR based design of novel oxindole derivative as 5HT7 inhibitors.

PubMed

Chitta, Aparna; Sivan, Sree Kanth; Manga, Vijjulatha

2014-06-01

To understand the structural requirements of 5-hydroxytryptamine (5HT7) receptor inhibitors and to design new ligands against 5HT7 receptor with enhanced inhibitory potency, a three-dimensional quantitative structure-activity relationship study with comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) for a data set of 56 molecules consisting of oxindole, tetrahydronaphthalene, aryl ketone substituted arylpiperazinealkylamide derivatives was performed. Derived model showed good statistical reliability in terms of predicting 5HT7 inhibitory activity of the molecules, based on molecular property fields like steric, electrostatic, hydrophobic, hydrogen bond donor and hydrogen bond acceptor fields. This is evident from statistical parameters like conventional r2 and a cross validated (q2) values of 0.985, 0.743 for CoMFA and 0.970, 0.608 for CoMSIA, respectively. Predictive ability of the models to determine 5HT7 antagonistic activity is validated using a test set of 16 molecules that were not included in the training set. Predictive r2 obtained for the test set was 0.560 and 0.619 for CoMFA and CoMSIA, respectively. Steric, electrostatic fields majorly contributed toward activity which forms the basis for design of new molecules. Absorption, distribution, metabolism and elimination (ADME) calculation using QikProp 2.5 (Schrodinger 2010, Portland, OR) reveals that the molecules confer to Lipinski's rule of five in majority of the cases.

Fuzzy regression modeling for tool performance prediction and degradation detection.

PubMed

Li, X; Er, M J; Lim, B S; Zhou, J H; Gan, O P; Rutkowski, L

2010-10-01

In this paper, the viability of using Fuzzy-Rule-Based Regression Modeling (FRM) algorithm for tool performance and degradation detection is investigated. The FRM is developed based on a multi-layered fuzzy-rule-based hybrid system with Multiple Regression Models (MRM) embedded into a fuzzy logic inference engine that employs Self Organizing Maps (SOM) for clustering. The FRM converts a complex nonlinear problem to a simplified linear format in order to further increase the accuracy in prediction and rate of convergence. The efficacy of the proposed FRM is tested through a case study - namely to predict the remaining useful life of a ball nose milling cutter during a dry machining process of hardened tool steel with a hardness of 52-54 HRc. A comparative study is further made between four predictive models using the same set of experimental data. It is shown that the FRM is superior as compared with conventional MRM, Back Propagation Neural Networks (BPNN) and Radial Basis Function Networks (RBFN) in terms of prediction accuracy and learning speed.

Probability-based collaborative filtering model for predicting gene-disease associations.

PubMed

Zeng, Xiangxiang; Ding, Ningxiang; Rodríguez-Patón, Alfonso; Zou, Quan

2017-12-28

Accurately predicting pathogenic human genes has been challenging in recent research. Considering extensive gene-disease data verified by biological experiments, we can apply computational methods to perform accurate predictions with reduced time and expenses. We propose a probability-based collaborative filtering model (PCFM) to predict pathogenic human genes. Several kinds of data sets, containing data of humans and data of other nonhuman species, are integrated in our model. Firstly, on the basis of a typical latent factorization model, we propose model I with an average heterogeneous regularization. Secondly, we develop modified model II with personal heterogeneous regularization to enhance the accuracy of aforementioned models. In this model, vector space similarity or Pearson correlation coefficient metrics and data on related species are also used. We compared the results of PCFM with the results of four state-of-arts approaches. The results show that PCFM performs better than other advanced approaches. PCFM model can be leveraged for predictions of disease genes, especially for new human genes or diseases with no known relationships.

Near Hartree-Fock quality GTO basis sets for the second-row atoms

NASA Technical Reports Server (NTRS)

Partridge, Harry

1987-01-01

Energy optimized, near Hartree-Fock quality Gaussian basis sets ranging in size from (17s12p) to (20s15p) are presented for the ground states of the second-row atoms for Na(2P), Na(+), Na(-), Mg(3P), P(-), S(-), and Cl(-). In addition, optimized supplementary functions are given for the ground state basis sets to describe the negative ions, and the excited Na(2P) and Mg(3P) atomic states. The ratios of successive orbital exponents describing the inner part of the 1s and 2p orbitals are found to be nearly independent of both nuclear charge and basis set size. This provides a method of obtaining good starting estimates for other basis set optimizations.

Relativistic Prolapse-Free Gaussian Basis Sets of Quadruple-ζ Quality: (aug-)RPF-4Z. III. The f-Block Elements.

PubMed

Teodoro, Tiago Quevedo; Visscher, Lucas; da Silva, Albérico Borges Ferreira; Haiduke, Roberto Luiz Andrade

2017-03-14

The f-block elements are addressed in this third part of a series of prolapse-free basis sets of quadruple-ζ quality (RPF-4Z). Relativistic adapted Gaussian basis sets (RAGBSs) are used as primitive sets of functions while correlating/polarization (C/P) functions are chosen by analyzing energy lowerings upon basis set increments in Dirac-Coulomb multireference configuration interaction calculations with single and double excitations of the valence spinors. These function exponents are obtained by applying the RAGBS parameters in a polynomial expression. Moreover, through the choice of C/P characteristic exponents from functions of lower angular momentum spaces, a reduction in the computational demand is attained in relativistic calculations based on the kinetic balance condition. The present study thus complements the RPF-4Z sets for the whole periodic table (Z ≤ 118). The sets are available as Supporting Information and can also be found at http://basis-sets.iqsc.usp.br .

Combination of large and small basis sets in electronic structure calculations on large systems

NASA Astrophysics Data System (ADS)

Røeggen, Inge; Gao, Bin

2018-04-01

Two basis sets—a large and a small one—are associated with each nucleus of the system. Each atom has its own separate one-electron basis comprising the large basis set of the atom in question and the small basis sets for the partner atoms in the complex. The perturbed atoms in molecules and solids model is at core of the approach since it allows for the definition of perturbed atoms in a system. It is argued that this basis set approach should be particularly useful for periodic systems. Test calculations are performed on one-dimensional arrays of H and Li atoms. The ground-state energy per atom in the linear H array is determined versus bond length.

Computational Prediction of the Protonation Sites of Ac-Lys-(Ala)n-Lys-NH2 Peptides through Conceptual DFT Descriptors.

PubMed

Sastre, Sebastián; Frau, Juan; Glossman-Mitnik, Daniel

2017-03-13

Six density functionals (M11, M11L, MN12L, MN12SX, N12, and N12SX) in connection with the Def2TZVP basis set and the SMD solvation model (water as a solvent) have been assessed for the calculation of the molecular structure and properties of several peptides with the general formulaAc-Lys-(Ala)n-Lys-NH2,withn=0to5  [...].

Optical modeling of stratopheric aerosols - Present status

NASA Technical Reports Server (NTRS)

Rosen, J. M.; Hofmann, D. J.

1986-01-01

A stratospheric aerosol optical model is developed which is based on a size distribution conforming to direct measurements. Additional constraints are consistent with large data sets of independently measured macroscopic aerosol properties such as mass and backscatter. The period under study covers background as well as highly disturbed volcanic conditions and an altitude interval ranging from the tropopause to about 30 km. The predictions of the model are used to form a basis for interpreting and intercomparing several diverse types of stratospheric aerosol measurement.

Predicting the Underwater Sound of Moderate and Heavy Rainfall from Laboratory Measurements of Radiation from Single Large Raindrops

DTIC Science & Technology

1992-03-01

Elementary Linear Algebra with Applications, pp. 301- 323, John Wiley and Sons Inc., 1987. Atlas, D., and Ulbrich, C. E. W., "The Physical Basis for...vector drd In this case, the linear system is said to be inconsistent ( Anton and Rorres, 1987). In contrast, for an underdetermined system (where the...ocean acoustical tomography and seismology. In simplest terms, the general linear inverse problem consists of fimding the desired solution to a set of m

On the Selection of Models for Runtime Prediction of System Resources

NASA Astrophysics Data System (ADS)

Casolari, Sara; Colajanni, Michele

Applications and services delivered through large Internet Data Centers are now feasible thanks to network and server improvement, but also to virtualization, dynamic allocation of resources and dynamic migrations. The large number of servers and resources involved in these systems requires autonomic management strategies because no amount of human administrators would be capable of cloning and migrating virtual machines in time, as well as re-distributing or re-mapping the underlying hardware. At the basis of most autonomic management decisions, there is the need of evaluating own global behavior and change it when the evaluation indicates that they are not accomplishing what they were intended to do or some relevant anomalies are occurring. Decisions algorithms have to satisfy different time scales constraints. In this chapter we are interested to short-term contexts where runtime prediction models work on the basis of time series coming from samples of monitored system resources, such as disk, CPU and network utilization. In similar environments, we have to address two main issues. First, original time series are affected by limited predictability because measurements are characterized by noises due to system instability, variable offered load, heavy-tailed distributions, hardware and software interactions. Moreover, there is no existing criteria that can help us to choose a suitable prediction model and related parameters with the purpose of guaranteeing an adequate prediction quality. In this chapter, we evaluate the impact that different choices on prediction models have on different time series, and we suggest how to treat input data and whether it is convenient to choose the parameters of a prediction model in a static or dynamic way. Our conclusions are supported by a large set of analyses on realistic and synthetic data traces.

Prediction of pH of cola beverage using Vis/NIR spectroscopy and least squares-support vector machine

NASA Astrophysics Data System (ADS)

Liu, Fei; He, Yong

2008-02-01

Visible and near infrared (Vis/NIR) transmission spectroscopy and chemometric methods were utilized to predict the pH values of cola beverages. Five varieties of cola were prepared and 225 samples (45 samples for each variety) were selected for the calibration set, while 75 samples (15 samples for each variety) for the validation set. The smoothing way of Savitzky-Golay and standard normal variate (SNV) followed by first-derivative were used as the pre-processing methods. Partial least squares (PLS) analysis was employed to extract the principal components (PCs) which were used as the inputs of least squares-support vector machine (LS-SVM) model according to their accumulative reliabilities. Then LS-SVM with radial basis function (RBF) kernel function and a two-step grid search technique were applied to build the regression model with a comparison of PLS regression. The correlation coefficient (r), root mean square error of prediction (RMSEP) and bias were 0.961, 0.040 and 0.012 for PLS, while 0.975, 0.031 and 4.697x10 -3 for LS-SVM, respectively. Both methods obtained a satisfying precision. The results indicated that Vis/NIR spectroscopy combined with chemometric methods could be applied as an alternative way for the prediction of pH of cola beverages.

Andean microrefugia: testing the Holocene to predict the Anthropocene.

PubMed

Valencia, Bryan G; Matthews-Bird, Frazer; Urrego, Dunia H; Williams, Joseph J; Gosling, William D; Bush, Mark

2016-10-01

Microrefugia are important for supporting populations during periods of unfavourable climate change and in facilitating rapid migration as conditions ameliorate. With ongoing anthropogenic climate change, microrefugia could have an important conservation value; however, a simple tool has not been developed and tested to predict which settings are microrefugial. We provide a tool based on terrain ruggedness modelling of individual catchments to predict Andean microrefugia. We tested the predictions using nine Holocene Polylepis pollen records. We used the mid-Holocene dry event, a period of peak aridity for the last 100 000 yr, as an analogue climate scenario for the near future. The results suggest that sites with high terrain rugosity have the greatest chance of sustaining mesic conditions under drier-than-modern climates. Fire is a feature of all catchments; however, an increase in fire is only recorded in settings with low rugosity. Owing to rising temperatures and greater precipitation variability, Andean ecosystems are threatened by increasing moisture stress. Our results suggest that high terrain rugosity helps to create more resilient catchments by trapping moisture through orographic rainfall and providing firebreaks that shelter forest from fire. On this basis, conservation policy should target protection and management of catchments with high terrain rugosity. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Subsidence monitoring and prediction of high-speed railway in Beijing with multitemporal TerraSAR-X data

NASA Astrophysics Data System (ADS)

Fan, Zelin; Zhang, Yonghong; Wu, Hong'an; Kang, Yonghui; Jiang, Decai

2018-02-01

The uneven settlement of high-speed railway (HSR) brings about great threat to the safe operation of trains. Therefore, the subsidence monitoring and prediction of HSR has important significance. In this paper, an improved multitemporal InSAR method combing PS-InSAR and SBAS-InSAR, Multiple-master Coherent Target Small-Baseline InSAR (MCTSB-InSAR), is used to monitor the subsidence of partial section of the Beijing-Tianjin HSR (BTHSR) and the Beijing-Shanghai HSR (BSHSR) in Beijing area. Thirty-one TerraSAR-X images from June 2011 to December 2016 are processed with the MCTSB-InSAR, and the subsidence information of the region covering 56km*32km in Beijing is dug out. Moreover, the monitoring results is validated by the leveling measurements in this area, with the accuracy of 4.4 mm/year. On the basis of above work, we extract the subsidence information of partial section of BTHSR and BSHSR in the research area. Finally, we adopt the idea of timing analysis, and employ the back-propagation (BP) neural network to simulate the relationship between former settlement and current settlement. Training data sets and test data sets are constructed respectively based on the monitoring results. The experimental results show that the prediction model has good prediction accuracy and applicability.

Quantitative prediction of oral cancer risk in patients with oral leukoplakia.

PubMed

Liu, Yao; Li, Yicheng; Fu, Yue; Liu, Tong; Liu, Xiaoyong; Zhang, Xinyan; Fu, Jie; Guan, Xiaobing; Chen, Tong; Chen, Xiaoxin; Sun, Zheng

2017-07-11

Exfoliative cytology has been widely used for early diagnosis of oral squamous cell carcinoma. We have developed an oral cancer risk index using DNA index value to quantitatively assess cancer risk in patients with oral leukoplakia, but with limited success. In order to improve the performance of the risk index, we collected exfoliative cytology, histopathology, and clinical follow-up data from two independent cohorts of normal, leukoplakia and cancer subjects (training set and validation set). Peaks were defined on the basis of first derivatives with positives, and modern machine learning techniques were utilized to build statistical prediction models on the reconstructed data. Random forest was found to be the best model with high sensitivity (100%) and specificity (99.2%). Using the Peaks-Random Forest model, we constructed an index (OCRI2) as a quantitative measurement of cancer risk. Among 11 leukoplakia patients with an OCRI2 over 0.5, 4 (36.4%) developed cancer during follow-up (23 ± 20 months), whereas 3 (5.3%) of 57 leukoplakia patients with an OCRI2 less than 0.5 developed cancer (32 ± 31 months). OCRI2 is better than other methods in predicting oral squamous cell carcinoma during follow-up. In conclusion, we have developed an exfoliative cytology-based method for quantitative prediction of cancer risk in patients with oral leukoplakia.

Validation of a physically based catchment model for application in post-closure radiological safety assessments of deep geological repositories for solid radioactive wastes.

PubMed

Thorne, M C; Degnan, P; Ewen, J; Parkin, G

2000-12-01

The physically based river catchment modelling system SHETRAN incorporates components representing water flow, sediment transport and radionuclide transport both in solution and bound to sediments. The system has been applied to simulate hypothetical future catchments in the context of post-closure radiological safety assessments of a potential site for a deep geological disposal facility for intermediate and certain low-level radioactive wastes at Sellafield, west Cumbria. In order to have confidence in the application of SHETRAN for this purpose, various blind validation studies have been undertaken. In earlier studies, the validation was undertaken against uncertainty bounds in model output predictions set by the modelling team on the basis of how well they expected the model to perform. However, validation can also be carried out with bounds set on the basis of how well the model is required to perform in order to constitute a useful assessment tool. Herein, such an assessment-based validation exercise is reported. This exercise related to a field plot experiment conducted at Calder Hollow, west Cumbria, in which the migration of strontium and lanthanum in subsurface Quaternary deposits was studied on a length scale of a few metres. Blind predictions of tracer migration were compared with experimental results using bounds set by a small group of assessment experts independent of the modelling team. Overall, the SHETRAN system performed well, failing only two out of seven of the imposed tests. Furthermore, of the five tests that were not failed, three were positively passed even when a pessimistic view was taken as to how measurement errors should be taken into account. It is concluded that the SHETRAN system, which is still being developed further, is a powerful tool for application in post-closure radiological safety assessments.

Vibrational spectroscopic, structural and nonlinear optical activity studies on 6-aminonicotinamide: A DFT approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Asath, R. Mohamed; Premkumar, S.; Mathavan, T.

2016-05-23

The conformational analysis was carried out for 6-aminonicotinamide (ANA) using potential energy surface scan method and the most stable optimized conformer was predicted. The theoretical vibrational frequencies were calculated for the optimized geometry using DFT/B3LYP cc-pVQZ basis set by Gaussian 09 Program. The vibrational frequencies were assigned on the basis of potential energy distribution calculation using VEDA 4.0 program. The Mulliken atomic charge values were calculated. In the Frontier molecular orbitals analysis, the molecular reactivity, kinetic stability, intermolecular charge transfer studies and the related molecular properties were calculated. The ultraviolet-visible spectrum was simulated for both in the gas phase andmore » liquid phase (ethanol) and the π to π* electronic transition was predicted. The nonlinear optical (NLO) activity was studied by means of the first order hyperpolarizability value, which was 8.61 times greater than the urea and the natural bond orbital analysis was also performed to confirm the NLO activity of the molecule. Hence, the ANA molecule is a promising candidate for the NLO materials.« less

Vibrational spectroscopic, structural and nonlinear optical activity studies on 6-aminonicotinamide: A DFT approach

NASA Astrophysics Data System (ADS)

Asath, R. Mohamed; Premkumar, S.; Rekha, T. N.; Jawahar, A.; Mathavan, T.; Benial, A. Milton Franklin

2016-05-01

The conformational analysis was carried out for 6-aminonicotinamide (ANA) using potential energy surface scan method and the most stable optimized conformer was predicted. The theoretical vibrational frequencies were calculated for the optimized geometry using DFT/B3LYP cc-pVQZ basis set by Gaussian 09 Program. The vibrational frequencies were assigned on the basis of potential energy distribution calculation using VEDA 4.0 program. The Mulliken atomic charge values were calculated. In the Frontier molecular orbitals analysis, the molecular reactivity, kinetic stability, intermolecular charge transfer studies and the related molecular properties were calculated. The ultraviolet-visible spectrum was simulated for both in the gas phase and liquid phase (ethanol) and the л to л* electronic transition was predicted. The nonlinear optical (NLO) activity was studied by means of the first order hyperpolarizability value, which was 8.61 times greater than the urea and the natural bond orbital analysis was also performed to confirm the NLO activity of the molecule. Hence, the ANA molecule is a promising candidate for the NLO materials.

DFT calculations on spectroscopic and structural properties of a NLO chromophore

NASA Astrophysics Data System (ADS)

Altürk, Sümeyye; Avci, Davut; Tamer, Ömer; Atalay, Yusuf

2016-03-01

The molecular geometry optimization, vibrational frequencies and gauge including atomic orbital (GIAO) 1H and 13C NMR chemical shift values of 2-(1'-(4'''-Methoxyphenyl)-5'-(thien-2″-yl)pyrrol-2'-yl)-1,3-benzothiazole as potential nonlinear optical (NLO) material were calculated using density functional theory (DFT) HSEh1PBE method with 6-311G(d,p) basis set. The best of our knowledge, this study have not been reported to date. Additionally, a detailed vibrational study was performed on the basis of potential energy distribution (PED) using VEDA program. It is noteworthy that NMR chemical shifts are quite useful for understanding the relationship between the molecular structure and electronic properties of molecules. The computed IR and NMR spectra were used to determine the types of the experimental bands observed. Predicted values of structural and spectroscopic parameters of the chromophore were compared with each other so as to display the effects of the different substituents on the spectroscopic and structural properties. Obtained data showed that there is an agreement between the predicted and experimental data.

Authentication of vegetable oils on the basis of their physico-chemical properties with the aid of chemometrics.

PubMed

Zhang, Guowen; Ni, Yongnian; Churchill, Jane; Kokot, Serge

2006-09-15

In food production, reliable analytical methods for confirmation of purity or degree of spoilage are required by growers, food quality assessors, processors, and consumers. Seven parameters of physico-chemical properties, such as acid number, colority, density, refractive index, moisture and volatility, saponification value and peroxide value, were measured for quality and adulterated soybean, as well as quality and rancid rapeseed oils. Chemometrics methods were then applied for qualitative and quantitative discrimination and prediction of the oils by methods such exploratory principal component analysis (PCA), partial least squares (PLS), radial basis function-artificial neural networks (RBF-ANN), and multi-criteria decision making methods (MCDM), PROMETHEE and GAIA. In general, the soybean and rapeseed oils were discriminated by PCA, and the two spoilt oils behaved differently with the rancid rapeseed samples exhibiting more object scatter on the PC-scores plot, than the adulterated soybean oil. For the PLS and RBF-ANN prediction methods, suitable training models were devised, which were able to predict satisfactorily the category of the four different oil samples in the verification set. Rank ordering with the use of MCDM models indicated that the oil types can be discriminated on the PROMETHEE II scale. For the first time, it was demonstrated how ranking of oil objects with the use of PROMETHEE and GAIA could be utilized as a versatile indicator of quality performance of products on the basis of a standard selected by the stakeholder. In principle, this approach provides a very flexible method for assessment of product quality directly from the measured data.

BAC-MP4 predictions of thermochemistry for the gas-phase tin compounds in the Sn-H-C-Cl system.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Allendorf, Mark D.; Melius, Carl F.

2004-09-01

In this work, the BAC-MP4 method is extended for the first time to compounds in the fourth row of the periodic table, resulting in a self-consistent set of thermochemical data for 56 tin-containing molecules in the Sn-H-C-Cl system. The BAC-MP4 method combines ab initio electronic structure calculations with empirical corrections to obtain accurate heats of formation. To obtain electronic energies for tin-containing species, the standard 6-31G(d,p) basis set used in BAC-MP4 calculations is augmented with a relativistic effective core potential to describe the electronic structure of the tin atom. Both stable compounds and radical species are included in this study.more » Trends within homologous series and calculated bond dissociation energies are consistent with previous BAC-MP4 predictions for group 14 compounds and the limited data available from the literature, indicating that the method is performing well for these compounds.« less

Application of class-modelling techniques to infrared spectra for analysis of pork adulteration in beef jerkys.

PubMed

Kuswandi, Bambang; Putri, Fitra Karima; Gani, Agus Abdul; Ahmad, Musa

2015-12-01

The use of chemometrics to analyse infrared spectra to predict pork adulteration in the beef jerky (dendeng) was explored. In the first step, the analysis of pork in the beef jerky formulation was conducted by blending the beef jerky with pork at 5-80 % levels. Then, they were powdered and classified into training set and test set. The second step, the spectra of the two sets was recorded by Fourier Transform Infrared (FTIR) spectroscopy using atenuated total reflection (ATR) cell on the basis of spectral data at frequency region 4000-700 cm(-1). The spectra was categorised into four data sets, i.e. (a) spectra in the whole region as data set 1; (b) spectra in the fingerprint region (1500-600 cm(-1)) as data set 2; (c) spectra in the whole region with treatment as data set 3; and (d) spectra in the fingerprint region with treatment as data set 4. The third step, the chemometric analysis were employed using three class-modelling techniques (i.e. LDA, SIMCA, and SVM) toward the data sets. Finally, the best result of the models towards the data sets on the adulteration analysis of the samples were selected and the best model was compared with the ELISA method. From the chemometric results, the LDA model on the data set 1 was found to be the best model, since it could classify and predict 100 % accuracy of the sample tested. The LDA model was applied toward the real samples of the beef jerky marketed in Jember, and the results showed that the LDA model developed was in good agreement with the ELISA method.

Dynamical basis sets for algebraic variational calculations in quantum-mechanical scattering theory

NASA Technical Reports Server (NTRS)

Sun, Yan; Kouri, Donald J.; Truhlar, Donald G.; Schwenke, David W.

1990-01-01

New basis sets are proposed for linear algebraic variational calculations of transition amplitudes in quantum-mechanical scattering problems. These basis sets are hybrids of those that yield the Kohn variational principle (KVP) and those that yield the generalized Newton variational principle (GNVP) when substituted in Schlessinger's stationary expression for the T operator. Trial calculations show that efficiencies almost as great as that of the GNVP and much greater than the KVP can be obtained, even for basis sets with the majority of the members independent of energy.

On basis set superposition error corrected stabilization energies for large n-body clusters.

PubMed

Walczak, Katarzyna; Friedrich, Joachim; Dolg, Michael

2011-10-07

In this contribution, we propose an approximate basis set superposition error (BSSE) correction scheme for the site-site function counterpoise and for the Valiron-Mayer function counterpoise correction of second order to account for the basis set superposition error in clusters with a large number of subunits. The accuracy of the proposed scheme has been investigated for a water cluster series at the CCSD(T), CCSD, MP2, and self-consistent field levels of theory using Dunning's correlation consistent basis sets. The BSSE corrected stabilization energies for a series of water clusters are presented. A study regarding the possible savings with respect to computational resources has been carried out as well as a monitoring of the basis set dependence of the approximate BSSE corrections. © 2011 American Institute of Physics

Predicting genotypes environmental range from genome-environment associations.

PubMed

Manel, Stéphanie; Andrello, Marco; Henry, Karine; Verdelet, Daphné; Darracq, Aude; Guerin, Pierre-Edouard; Desprez, Bruno; Devaux, Pierre

2018-05-17

Genome-environment association methods aim to detect genetic markers associated with environmental variables. The detected associations are usually analysed separately to identify the genomic regions involved in local adaptation. However, a recent study suggests that single-locus associations can be combined and used in a predictive way to estimate environmental variables for new individuals on the basis of their genotypes. Here, we introduce an original approach to predict the environmental range (values and upper and lower limits) of species genotypes from the genetic markers significantly associated with those environmental variables in an independent set of individuals. We illustrate this approach to predict aridity in a database constituted of 950 individuals of wild beets and 299 individuals of cultivated beets genotyped at 14,409 random Single Nucleotide Polymorphisms (SNPs). We detected 66 alleles associated with aridity and used them to calculate the fraction (I) of aridity-associated alleles in each individual. The fraction I correctly predicted the values of aridity in an independent validation set of wild individuals and was then used to predict aridity in the 299 cultivated individuals. Wild individuals had higher median values and a wider range of values of aridity than the cultivated individuals, suggesting that wild individuals have higher ability to resist to stress-aridity conditions and could be used to improve the resistance of cultivated varieties to aridity. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

High quality Gaussian basis sets for fourth-row atoms

NASA Technical Reports Server (NTRS)

Partridge, Harry; Faegri, Knut, Jr.

1992-01-01

Energy optimized Gaussian basis sets of triple-zeta quality for the atoms Rb-Xe have been derived. Two series of basis sets are developed: (24s 16p 10d) and (26s 16p 10d) sets which were expanded to 13d and 19p functions as the 4d and 5p shells become occupied. For the atoms lighter than Cd, the (24s 16p 10d) sets with triple-zeta valence distributions are higher in energy than the corresponding double-zeta distribution. To ensure a triple-zeta distribution and a global energy minimum, the (26s 16p 10d) sets were derived. Total atomic energies from the largest basis sets are between 198 and 284 (mu)E(sub H) above the numerical Hartree-Fock energies.

Integrating Genetic, Neuropsychological and Neuroimaging Data to Model Early-Onset Obsessive Compulsive Disorder Severity

PubMed Central

Mas, Sergi; Gassó, Patricia; Morer, Astrid; Calvo, Anna; Bargalló, Nuria; Lafuente, Amalia; Lázaro, Luisa

2016-01-01

We propose an integrative approach that combines structural magnetic resonance imaging data (MRI), diffusion tensor imaging data (DTI), neuropsychological data, and genetic data to predict early-onset obsessive compulsive disorder (OCD) severity. From a cohort of 87 patients, 56 with complete information were used in the present analysis. First, we performed a multivariate genetic association analysis of OCD severity with 266 genetic polymorphisms. This association analysis was used to select and prioritize the SNPs that would be included in the model. Second, we split the sample into a training set (N = 38) and a validation set (N = 18). Third, entropy-based measures of information gain were used for feature selection with the training subset. Fourth, the selected features were fed into two supervised methods of class prediction based on machine learning, using the leave-one-out procedure with the training set. Finally, the resulting model was validated with the validation set. Nine variables were used for the creation of the OCD severity predictor, including six genetic polymorphisms and three variables from the neuropsychological data. The developed model classified child and adolescent patients with OCD by disease severity with an accuracy of 0.90 in the testing set and 0.70 in the validation sample. Above its clinical applicability, the combination of particular neuropsychological, neuroimaging, and genetic characteristics could enhance our understanding of the neurobiological basis of the disorder. PMID:27093171

Ab Initio and Analytic Intermolecular Potentials for Ar–CH3OH

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tasic, Uros; Alexeev, Yuri; Vayner, Grigoriy

2006-09-20

Ab initio calculations at the CCSD(T)/aug-cc-pVTZ level of theory were used to characterize the Ar–CH₃y6tOH intermolecular potential energy surface (PES). Potential energy curves were calculated for four different Ar + CH₃OH orientations and used to derive an analytic function for the intermolecular PES. A sum of Ar–C, Ar–O, Ar–H(C), and Ar–H(O) two-body potentials gives an excellent fit to these potential energy curves up to 100 kcal mol¯¹, and adding an additional r¯¹n term to the Buckingham two-body potential results in only a minor improvement in the fit. Three Ar–CH₃OH van der Waals minima were found from the CCSD(T)/aug-cc-pVTZ//MP2/aug-cc-pVTZ calculations. Themore » structure of the global minimum is in overall good agreement with experiment (X.-C. Tan, L. Sun and R. L. Kuczkowski, J. Mol. Spectrosc., 1995, 171, 248). It is T-shaped with the hydroxyl H-atom syn with respect to Ar. Extrapolated to the complete basis set (CBS) limit, the global minimum has a well depth of 0.72 kcal mol¯¹ with basis set superposition error (BSSE) correction. The aug-cc-pVTZ basis set gives a well depth only 0.10 kcal mol¯¹ smaller than this value. The well depths of the other two minima are within 0.16 kcal mol¯¹ of the global minimum. The analytic Ar–CH₃OH intermolecular potential also identifies these three minima as the only van der Waals minima and the structures predicted by the analytic potential are similar to the ab initio structures. The analytic potential identifies the same global minimum and the predicted well depths for the minima are within 0.05 kcal mol¯1 of the ab initio values. Combining this Ar–CH₃OH intermolecular potential with a potential for a OH-terminated alkylthiolate self-assembled monolayer surface (i.e., HO-SAM) provides a potential to model Ar + HO-SAM collisions.« less

The electron affinities of C{sub 3}O and C{sub 4}O

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rienstra-Kiracofe, J.C.; Ellison, G.B.; Hoffman, B.C.

The authors predict the adiabatic electron affinities of C{sub 3}O and C{sub 4}O based on electronic structure calculations, using a large triple-{zeta} basis set with polarization and diffuse functions (TZ2Pf+diff) with the SCF, CCSD, and CCSD(T) methods as well as with the aug-cc-pVDZ and aug-cc-pVTZ basis sets. The results imply electron affinities for C{sub 3}O and C{sub 4}O; EA(C{sub 3}O) = 0.93 eV {+-} 0.10 and EA(C{sub 4}O) = 2.99 {+-} 0.10. The EA(C{sub 3}O) is 0.41 eV lower than the experimental value of 1.34 {+-} 0.15 eV, while the EA(C{sub 4}O) is 0.94 eV higher than the experimental valuemore » of 2.05 {+-} 0.15 eV. Optimized geometries for all species at each level of theory are given, and harmonic vibrational frequencies are reported at the SCF/TZ2Pf+diff and CCSD/aug-cc-pVDZ levels.« less

Experimental and DFT studies on the vibrational spectra of 1H-indene-2-boronic acid

NASA Astrophysics Data System (ADS)

Alver, Özgur; Kaya, Mehmet Fatih

2014-11-01

Stable conformers and geometrical molecular structures of 1H-indene-2-boronic acid (I-2B(OH)2) were studied experimentally and theoretically using FT-IR and FT-Raman spectroscopic methods. FT-IR and FT-Raman spectra were recorded in the region of 4000-400 cm-1, and 3700-400 cm-1, respectively. The optimized geometric structures were searched by Becke-3-Lee-Yang-Parr (B3LYP) hybrid density functional theory method with 6-31++G(d,p) basis set. Vibrational wavenumbers of I-2B(OH)2 were calculated using B3LYP density functional methods including 6-31++G(d,p) basis set. Experimental and theoretical results show that density functional B3LYP method gives satisfactory results for predicting vibrational wavenumbers except OH stretching modes which is probably due to increasing unharmonicity in the high wave number region and possible intra and inter molecular interaction at OH edges. To support the assigned vibrational wavenumbers, the potential energy distribution (PED) values were also calculated using VEDA 4 (Vibrational Energy Distribution Analysis) program.

3-Iodobenzaldehyde: XRD, FT-IR, Raman and DFT studies.

PubMed

Kumar, Chandraju Sadolalu Chidan; Parlak, Cemal; Tursun, Mahir; Fun, Hoong-Kun; Rhyman, Lydia; Ramasami, Ponnadurai; Alswaidan, Ibrahim A; Keşan, Gürkan; Chandraju, Siddegowda; Quah, Ching Kheng

2015-06-15

The structure of 3-iodobenzaldehyde (3IB) was characterized by FT-IR, Raman and single-crystal X-ray diffraction techniques. The conformational isomers, optimized geometric parameters, normal mode frequencies and corresponding vibrational assignments of 3IB were examined using density functional theory (DFT) method, with the Becke-3-Lee-Yang-Parr (B3LYP) functional and the 6-311+G(3df,p) basis set for all atoms except for iodine. The LANL2DZ effective core basis set was used for iodine. Potential energy distribution (PED) analysis of normal modes was performed to identify characteristic frequencies. 3IB crystallizes in monoclinic space group P21/c with the O-trans form. There is a good agreement between the theoretically predicted structural parameters, and vibrational frequencies and those obtained experimentally. In order to understand halogen effect, 3-halogenobenzaldehyde [XC6H4CHO; X=F, Cl and Br] was also studied theoretically. The free energy difference between the isomers is small but the rotational barrier is about 8kcal/mol. An atypical behavior of fluorine affecting conformational preference is observed. Copyright © 2015 Elsevier B.V. All rights reserved.

Development of many-body polarizable force fields for Li-battery applications: 2. LiTFSI-doped Oligoether, polyether, and carbonate-based electrolytes.

PubMed

Borodin, Oleg; Smith, Grant D

2006-03-30

A quantum chemistry study of Li(+) interactions with ethers, carbonates, alkanes, and a trifluoromethanesulfonylimide anion (TFSI(-)) was performed at the MP2, B3LYP, and HF levels using the aug-cc-pvDz basis set for solvents and TFSI(-) anion, and [8s4p3d/5s3p2d]-type basis set for Li. A classical many-polarizable force field was developed for the LiTFSI salt interacting with ethylene carbonate (EC), gamma-butyrolactone (GBL), dimethyl carbonate (DMC), acetone, oligoethers, n-alkanes, and perfluoroalkanes. Molecular dynamics (MD) simulations were performed for EC/LiTFSI, PC/LiTFSI, GBL/LiTFSI, DMC/LiTFSI, 1,2-dimethoxyethane/LiTFSI, pentaglyme/LiTFSI, and poly(ethylene oxide) (MW = 2380)/LiTFSI electrolytes at temperatures from 298 to 423 K and salt concentrations from 0.3 to 5 M. The ion and solvent self-diffusion coefficients, electrolyte conductivity, electrolyte density, LiTFSI apparent molar volumes, and structure of the Li(+) cation environment predicted by MD simulations were found in good agreement with experimental data.

Ab Initio Potential Energy Surface for H-H2

NASA Technical Reports Server (NTRS)

Patridge, Harry; Bauschlicher, Charles W., Jr.; Stallcop, James R.; Levin, Eugene

1993-01-01

Ab initio calculations employing large basis sets are performed to determine an accurate potential energy surface for H-H2 interactions for a broad range of separation distances. At large distances, the spherically averaged potential determined from the calculated energies agrees well with the corresponding results determined from dispersion coefficients; the van der Waals well depth is predicted to be 75 +/- 3 micro E(h). Large basis sets have also been applied to reexamine the accuracy of theoretical repulsive potential energy surfaces (25-70 kcal/mol above the H-H2 asymptote) at small interatomic separations; the Boothroyd, Keogh, Martin, and Peterson (BKMP) potential energy surface is found to agree with results of the present calculations within the expected uncertainty (+/- 1 kcal/mol) of the fit. Multipolar expansions of the computed H-H2 potential energy surface are reported for four internuclear separation distances (1.2, 1.401, 1.449, and 1.7a(0)) of the hydrogen molecule. The differential elastic scattering cross section calculated from the present results is compared with the measurements from a crossed beam experiment.

Electron affinities of polycyclic aromatic hydrocarbons by means of B3LYP/6-31+G* calculations.

PubMed

Modelli, Alberto; Mussoni, Laura; Fabbri, Daniele

2006-05-25

The gas-phase experimental adiabatic electron affinities (AEAs) of the polycyclic aromatic hydrocarbons (PAHs) anthracene, tetracene, pentacene, chrysene, pyrene, benzo[a]pyrene, benzo[e]pyrene, and fluoranthene are well reproduced using the hybrid density functional method B3LYP with the 6-31+G* basis set, indicating that the smallest addition of diffuse functions to the basis set is suitable for a correct description of the stable PAH anion states. The calculated AEAs also give a very good linear correlation with available reduction potentials measured in solution. The AEAs (not experimentally available) of the isomeric benzo[ghi]fluoranthene and cyclopenta[cd]pyrene, commonly found in the environment, are predicted to be 0.817 and 1.108 eV, respectively, confirming the enhancement of the electron-acceptor properties associated with fusion of a peripheral cyclopenta ring. The calculated localization properties of the lowest unoccupied MO of cyclopenta[cd]pyrene, together with its relatively high electron affinity, account for a high reactivity at the ethene double bond of this PAH in reductive processes.

Exploring metabolic pathways in genome-scale networks via generating flux modes.

PubMed

Rezola, A; de Figueiredo, L F; Brock, M; Pey, J; Podhorski, A; Wittmann, C; Schuster, S; Bockmayr, A; Planes, F J

2011-02-15

The reconstruction of metabolic networks at the genome scale has allowed the analysis of metabolic pathways at an unprecedented level of complexity. Elementary flux modes (EFMs) are an appropriate concept for such analysis. However, their number grows in a combinatorial fashion as the size of the metabolic network increases, which renders the application of EFMs approach to large metabolic networks difficult. Novel methods are expected to deal with such complexity. In this article, we present a novel optimization-based method for determining a minimal generating set of EFMs, i.e. a convex basis. We show that a subset of elements of this convex basis can be effectively computed even in large metabolic networks. Our method was applied to examine the structure of pathways producing lysine in Escherichia coli. We obtained a more varied and informative set of pathways in comparison with existing methods. In addition, an alternative pathway to produce lysine was identified using a detour via propionyl-CoA, which shows the predictive power of our novel approach. The source code in C++ is available upon request.

Relativistic well-tempered Gaussian basis sets for helium through mercury

DOE Office of Scientific and Technical Information (OSTI.GOV)

Okada, S.; Matsuoka, O.

1989-10-01

Exponent parameters of the nonrelativistically optimized well-tempered Gaussian basis sets of Huzinaga and Klobukowski have been employed for Dirac--Fock--Roothaan calculations without their reoptimization. For light atoms He (atomic number {ital Z}=2)--Rh ({ital Z}=45), the number of exponent parameters used has been the same as the nonrelativistic basis sets and for heavier atoms Pd ({ital Z}=46)--Hg({ital Z}=80), two 2{ital p} (and three 3{ital d}) Gaussian basis functions have been augmented. The scheme of kinetic energy balance and the uniformly charged sphere model of atomic nuclei have been adopted. The qualities of the calculated basis sets are close to the Dirac--Fock limit.

Performance assessment of density functional methods with Gaussian and Slater basis sets using 7σ orbital momentum distributions of N2O

NASA Astrophysics Data System (ADS)

Wang, Feng; Pang, Wenning; Duffy, Patrick

2012-12-01

Performance of a number of commonly used density functional methods in chemistry (B3LYP, Bhandh, BP86, PW91, VWN, LB94, PBe0, SAOP and X3LYP and the Hartree-Fock (HF) method) has been assessed using orbital momentum distributions of the 7σ orbital of nitrous oxide (NNO), which models electron behaviour in a chemically significant region. The density functional methods are combined with a number of Gaussian basis sets (Pople's 6-31G*, 6-311G**, DGauss TZVP and Dunning's aug-cc-pVTZ as well as even-tempered Slater basis sets, namely, et-DZPp, et-QZ3P, et-QZ+5P and et-pVQZ). Orbital momentum distributions of the 7σ orbital in the ground electronic state of NNO, which are obtained from a Fourier transform into momentum space from single point electronic calculations employing the above models, are compared with experimental measurement of the same orbital from electron momentum spectroscopy (EMS). The present study reveals information on performance of (a) the density functional methods, (b) Gaussian and Slater basis sets, (c) combinations of the density functional methods and basis sets, that is, the models, (d) orbital momentum distributions, rather than a group of specific molecular properties and (e) the entire region of chemical significance of the orbital. It is found that discrepancies of this orbital between the measured and the calculated occur in the small momentum region (i.e. large r region). In general, Slater basis sets achieve better overall performance than the Gaussian basis sets. Performance of the Gaussian basis sets varies noticeably when combining with different Vxc functionals, but Dunning's augcc-pVTZ basis set achieves the best performance for the momentum distributions of this orbital. The overall performance of the B3LYP and BP86 models is similar to newer models such as X3LYP and SAOP. The present study also demonstrates that the combinations of the density functional methods and the basis sets indeed make a difference in the quality of the calculated orbitals.

On the validity of the basis set superposition error and complete basis set limit extrapolations for the binding energy of the formic acid dimer

NASA Astrophysics Data System (ADS)

Miliordos, Evangelos; Xantheas, Sotiris S.

2015-03-01

We report the variation of the binding energy of the Formic Acid Dimer with the size of the basis set at the Coupled Cluster with iterative Singles, Doubles and perturbatively connected Triple replacements [CCSD(T)] level of theory, estimate the Complete Basis Set (CBS) limit, and examine the validity of the Basis Set Superposition Error (BSSE)-correction for this quantity that was previously challenged by Kalescky, Kraka, and Cremer (KKC) [J. Chem. Phys. 140, 084315 (2014)]. Our results indicate that the BSSE correction, including terms that account for the substantial geometry change of the monomers due to the formation of two strong hydrogen bonds in the dimer, is indeed valid for obtaining accurate estimates for the binding energy of this system as it exhibits the expected decrease with increasing basis set size. We attribute the discrepancy between our current results and those of KKC to their use of a valence basis set in conjunction with the correlation of all electrons (i.e., including the 1s of C and O). We further show that the use of a core-valence set in conjunction with all electron correlation converges faster to the CBS limit as the BSSE correction is less than half than the valence electron/valence basis set case. The uncorrected and BSSE-corrected binding energies were found to produce the same (within 0.1 kcal/mol) CBS limits. We obtain CCSD(T)/CBS best estimates for De = - 16.1 ± 0.1 kcal/mol and for D0 = - 14.3 ± 0.1 kcal/mol, the later in excellent agreement with the experimental value of -14.22 ± 0.12 kcal/mol.

Characterizing and Understanding the Remarkably Slow Basis Set Convergence of Several Minnesota Density Functionals for Intermolecular Interaction Energies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mardirossian, Narbe; Head-Gordon, Martin

2013-08-22

For a set of eight equilibrium intermolecular complexes, it is discovered in this paper that the basis set limit (BSL) cannot be reached by aug-cc-pV5Z for three of the Minnesota density functionals: M06-L, M06-HF, and M11-L. In addition, the M06 and M11 functionals exhibit substantial, but less severe, difficulties in reaching the BSL. By using successively finer grids, it is demonstrated that this issue is not related to the numerical integration of the exchange-correlation functional. In addition, it is shown that the difficulty in reaching the BSL is not a direct consequence of the structure of the augmented functions inmore » Dunning’s basis sets, since modified augmentation yields similar results. By using a very large custom basis set, the BSL appears to be reached for the HF dimer for all of the functionals. As a result, it is concluded that the difficulties faced by several of the Minnesota density functionals are related to an interplay between the form of these functionals and the structure of standard basis sets. It is speculated that the difficulty in reaching the basis set limit is related to the magnitude of the inhomogeneity correction factor (ICF) of the exchange functional. A simple modification of the M06-L exchange functional that systematically reduces the basis set superposition error (BSSE) for the HF dimer in the aug-cc-pVQZ basis set is presented, further supporting the speculation that the difficulty in reaching the BSL is caused by the magnitude of the exchange functional ICF. In conclusion, the BSSE is plotted with respect to the internuclear distance of the neon dimer for two of the examined functionals.« less

In silico prediction of Tetrahymena pyriformis toxicity for diverse industrial chemicals with substructure pattern recognition and machine learning methods.

PubMed

Cheng, Feixiong; Shen, Jie; Yu, Yue; Li, Weihua; Liu, Guixia; Lee, Philip W; Tang, Yun

2011-03-01

There is an increasing need for the rapid safety assessment of chemicals by both industries and regulatory agencies throughout the world. In silico techniques are practical alternatives in the environmental hazard assessment. It is especially true to address the persistence, bioaccumulative and toxicity potentials of organic chemicals. Tetrahymena pyriformis toxicity is often used as a toxic endpoint. In this study, 1571 diverse unique chemicals were collected from the literature and composed of the largest diverse data set for T. pyriformis toxicity. Classification predictive models of T. pyriformis toxicity were developed by substructure pattern recognition and different machine learning methods, including support vector machine (SVM), C4.5 decision tree, k-nearest neighbors and random forest. The results of a 5-fold cross-validation showed that the SVM method performed better than other algorithms. The overall predictive accuracies of the SVM classification model with radial basis functions kernel was 92.2% for the 5-fold cross-validation and 92.6% for the external validation set, respectively. Furthermore, several representative substructure patterns for characterizing T. pyriformis toxicity were also identified via the information gain analysis methods. Copyright © 2010 Elsevier Ltd. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miliordos, Evangelos; Aprà, Edoardo; Xantheas, Sotiris S.

We establish a new estimate for the binding energy between two benzene molecules in the parallel-displaced (PD) conformation by systematically converging (i) the intra- and intermolecular geometry at the minimum, (ii) the expansion of the orbital basis set, and (iii) the level of electron correlation. The calculations were performed at the second-order Møller–Plesset perturbation (MP2) and the coupled cluster including singles, doubles, and a perturbative estimate of triples replacement [CCSD(T)] levels of electronic structure theory. At both levels of theory, by including results corrected for basis set superposition error (BSSE), we have estimated the complete basis set (CBS) limit bymore » employing the family of Dunning’s correlation-consistent polarized valence basis sets. The largest MP2 calculation was performed with the cc-pV6Z basis set (2772 basis functions), whereas the largest CCSD(T) calculation was with the cc-pV5Z basis set (1752 basis functions). The cluster geometries were optimized with basis sets up to quadruple-ζ quality, observing that both its intra- and intermolecular parts have practically converged with the triple-ζ quality sets. The use of converged geometries was found to play an important role for obtaining accurate estimates for the CBS limits. Our results demonstrate that the binding energies with the families of the plain (cc-pVnZ) and augmented (aug-cc-pVnZ) sets converge [within <0.01 kcal/mol for MP2 and <0.15 kcal/mol for CCSD(T)] to the same CBS limit. In addition, the average of the uncorrected and BSSE-corrected binding energies was found to converge to the same CBS limit much faster than either of the two constituents (uncorrected or BSSE-corrected binding energies). Due to the fact that the family of augmented basis sets (especially for the larger sets) causes serious linear dependency problems, the plain basis sets (for which no linear dependencies were found) are deemed as a more efficient and straightforward path for obtaining an accurate CBS limit. We considered extrapolations of the uncorrected (ΔE) and BSSE-corrected (ΔE cp) binding energies, their average value (ΔE ave), as well as the average of the latter over the plain and augmented sets (Δ~E ave) with the cardinal number of the basis set n. Our best estimate of the CCSD(T)/CBS limit for the π–π binding energy in the PD benzene dimer is D e = -2.65 ± 0.02 kcal/mol. The best CCSD(T)/cc-pV5Z calculated value is -2.62 kcal/mol, just 0.03 kcal/mol away from the CBS limit. For comparison, the MP2/CBS limit estimate is -5.00 ± 0.01 kcal/mol, demonstrating a 90% overbinding with respect to CCSD(T). Finally, the spin-component-scaled (SCS) MP2 variant was found to closely reproduce the CCSD(T) results for each basis set, while scaled opposite spin (SOS) MP2 yielded results that are too low when compared to CCSD(T).« less

Raman spectra of thiolated arsenicals with biological importance.

PubMed

Yang, Mingwei; Sun, Yuzhen; Zhang, Xiaobin; McCord, Bruce; McGoron, Anthony J; Mebel, Alexander; Cai, Yong

2018-03-01

Surface enhanced Raman scattering (SERS) has great potential as an alternative tool for arsenic speciation in biological matrices. SERS measurements have advantages over other techniques due to its ability to maintain the integrity of arsenic species and its minimal requirements for sample preparation. Up to now, very few Raman spectra of arsenic compounds have been reported. This is particularly true for thiolated arsenicals, which have recently been found to be widely present in humans. The lack of data for Raman spectra in arsenic speciation hampers the development of new tools using SERS. Herein, we report the results of a study combining the analysis of experimental Raman spectra with that obtained from density functional calculations for some important arsenic metabolites. The results were obtained with a hybrid functional B3LYP approach using different basis sets to calculate Raman spectra of the selected arsenicals. By comparing experimental and calculated spectra of dimethylarsinic acid (DMA V ), the basis set 6-311++G** was found to provide computational efficiency and precision in vibrational frequency prediction. The Raman frequencies for the rest of organoarsenicals were studied using this basis set, including monomethylarsonous acid (MMA III ), dimethylarsinous acid (DMA III ), dimethylmonothioarinic acid (DMMTA V ), dimethyldithioarsinic acid (DMDTA V ), S-(Dimethylarsenic) cysteine (DMA III (Cys)) and dimethylarsinous glutathione (DMA III GS). The results were compared with fingerprint Raman frequencies from As─O, As─C, and As─S obtained under different chemical environments. These fingerprint vibrational frequencies should prove useful in future measurements of different species of arsenic using SERS. Copyright © 2017 Elsevier B.V. All rights reserved.

Angle-dependent strong-field molecular ionization rates with tuned range-separated time-dependent density functional theory.

PubMed

Sissay, Adonay; Abanador, Paul; Mauger, François; Gaarde, Mette; Schafer, Kenneth J; Lopata, Kenneth

2016-09-07

Strong-field ionization and the resulting electronic dynamics are important for a range of processes such as high harmonic generation, photodamage, charge resonance enhanced ionization, and ionization-triggered charge migration. Modeling ionization dynamics in molecular systems from first-principles can be challenging due to the large spatial extent of the wavefunction which stresses the accuracy of basis sets, and the intense fields which require non-perturbative time-dependent electronic structure methods. In this paper, we develop a time-dependent density functional theory approach which uses a Gaussian-type orbital (GTO) basis set to capture strong-field ionization rates and dynamics in atoms and small molecules. This involves propagating the electronic density matrix in time with a time-dependent laser potential and a spatial non-Hermitian complex absorbing potential which is projected onto an atom-centered basis set to remove ionized charge from the simulation. For the density functional theory (DFT) functional we use a tuned range-separated functional LC-PBE*, which has the correct asymptotic 1/r form of the potential and a reduced delocalization error compared to traditional DFT functionals. Ionization rates are computed for hydrogen, molecular nitrogen, and iodoacetylene under various field frequencies, intensities, and polarizations (angle-dependent ionization), and the results are shown to quantitatively agree with time-dependent Schrödinger equation and strong-field approximation calculations. This tuned DFT with GTO method opens the door to predictive all-electron time-dependent density functional theory simulations of ionization and ionization-triggered dynamics in molecular systems using tuned range-separated hybrid functionals.

Angle-dependent strong-field molecular ionization rates with tuned range-separated time-dependent density functional theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sissay, Adonay; Abanador, Paul; Mauger, François

2016-09-07

Strong-field ionization and the resulting electronic dynamics are important for a range of processes such as high harmonic generation, photodamage, charge resonance enhanced ionization, and ionization-triggered charge migration. Modeling ionization dynamics in molecular systems from first-principles can be challenging due to the large spatial extent of the wavefunction which stresses the accuracy of basis sets, and the intense fields which require non-perturbative time-dependent electronic structure methods. In this paper, we develop a time-dependent density functional theory approach which uses a Gaussian-type orbital (GTO) basis set to capture strong-field ionization rates and dynamics in atoms and small molecules. This involves propagatingmore » the electronic density matrix in time with a time-dependent laser potential and a spatial non-Hermitian complex absorbing potential which is projected onto an atom-centered basis set to remove ionized charge from the simulation. For the density functional theory (DFT) functional we use a tuned range-separated functional LC-PBE*, which has the correct asymptotic 1/r form of the potential and a reduced delocalization error compared to traditional DFT functionals. Ionization rates are computed for hydrogen, molecular nitrogen, and iodoacetylene under various field frequencies, intensities, and polarizations (angle-dependent ionization), and the results are shown to quantitatively agree with time-dependent Schrödinger equation and strong-field approximation calculations. This tuned DFT with GTO method opens the door to predictive all-electron time-dependent density functional theory simulations of ionization and ionization-triggered dynamics in molecular systems using tuned range-separated hybrid functionals.« less

Atomization Energies of SO and SO2; Basis Set Extrapolation Revisted

NASA Technical Reports Server (NTRS)

Bauschlicher, Charles W., Jr.; Ricca, Alessandra; Arnold, James (Technical Monitor)

1998-01-01

The addition of tight functions to sulphur and extrapolation to the complete basis set limit are required to obtain accurate atomization energies. Six different extrapolation procedures are tried. The best atomization energies come from the series of basis sets that yield the most consistent results for all extrapolation techniques. In the variable alpha approach, alpha values larger than 4.5 or smaller than 3, appear to suggest that the extrapolation may not be reliable. It does not appear possible to determine a reliable basis set series using only the triple and quadruple zeta based sets. The scalar relativistic effects reduce the atomization of SO and SO2 by 0.34 and 0.81 kcal/mol, respectively, and clearly must be accounted for if a highly accurate atomization energy is to be computed. The magnitude of the core-valence (CV) contribution to the atomization is affected by missing diffuse valence functions. The CV contribution is much more stable if basis set superposition errors are accounted for. A similar study of SF, SF(+), and SF6 shows that the best family of basis sets varies with the nature of the S bonding.

Design prediction for long term stress rupture service of composite pressure vessels

NASA Technical Reports Server (NTRS)

Robinson, Ernest Y.

1992-01-01

Extensive stress rupture studies on glass composites and Kevlar composites were conducted by the Lawrence Radiation Laboratory beginning in the late 1960's and extending to about 8 years in some cases. Some of the data from these studies published over the years were incomplete or were tainted by spurious failures, such as grip slippage. Updated data sets were defined for both fiberglass and Kevlar composite stand test specimens. These updated data are analyzed in this report by a convenient form of the bivariate Weibull distribution, to establish a consistent set of design prediction charts that may be used as a conservative basis for predicting the stress rupture life of composite pressure vessels. The updated glass composite data exhibit an invariant Weibull modulus with lifetime. The data are analyzed in terms of homologous service load (referenced to the observed median strength). The equations relating life, homologous load, and probability are given, and corresponding design prediction charts are presented. A similar approach is taken for Kevlar composites, where the updated stand data do show a turndown tendency at long life accompanied by a corresponding change (increase) of the Weibull modulus. The turndown characteristic is not present in stress rupture test data of Kevlar pressure vessels. A modification of the stress rupture equations is presented to incorporate a latent, but limited, strength drop, and design prediction charts are presented that incorporate such behavior. The methods presented utilize Cartesian plots of the probability distributions (which are a more natural display for the design engineer), based on median normalized data that are independent of statistical parameters and are readily defined for any set of test data.

Calculating Interaction Energies Using First Principle Theories: Consideration of Basis Set Superposition Error and Fragment Relaxation

ERIC Educational Resources Information Center

Bowen, J. Philip; Sorensen, Jennifer B.; Kirschner, Karl N.

2007-01-01

The analysis explains the basis set superposition error (BSSE) and fragment relaxation involved in calculating the interaction energies using various first principle theories. Interacting the correlated fragment and increasing the size of the basis set can help in decreasing the BSSE to a great extent.

Confronting uncertainty in flood damage predictions

NASA Astrophysics Data System (ADS)

Schröter, Kai; Kreibich, Heidi; Vogel, Kristin; Merz, Bruno

2015-04-01

Reliable flood damage models are a prerequisite for the practical usefulness of the model results. Oftentimes, traditional uni-variate damage models as for instance depth-damage curves fail to reproduce the variability of observed flood damage. Innovative multi-variate probabilistic modelling approaches are promising to capture and quantify the uncertainty involved and thus to improve the basis for decision making. In this study we compare the predictive capability of two probabilistic modelling approaches, namely Bagging Decision Trees and Bayesian Networks. For model evaluation we use empirical damage data which are available from computer aided telephone interviews that were respectively compiled after the floods in 2002, 2005 and 2006, in the Elbe and Danube catchments in Germany. We carry out a split sample test by sub-setting the damage records. One sub-set is used to derive the models and the remaining records are used to evaluate the predictive performance of the model. Further we stratify the sample according to catchments which allows studying model performance in a spatial transfer context. Flood damage estimation is carried out on the scale of the individual buildings in terms of relative damage. The predictive performance of the models is assessed in terms of systematic deviations (mean bias), precision (mean absolute error) as well as in terms of reliability which is represented by the proportion of the number of observations that fall within the 95-quantile and 5-quantile predictive interval. The reliability of the probabilistic predictions within validation runs decreases only slightly and achieves a very good coverage of observations within the predictive interval. Probabilistic models provide quantitative information about prediction uncertainty which is crucial to assess the reliability of model predictions and improves the usefulness of model results.

Symbiotic theory of the origin of eukaryotic organelles; criteria for proof.

PubMed

Margulis, L

1975-01-01

The purpose of a scientific theory is to unite apparently disparate observations into a coherent set of generalizations with predictive power. Historical theories, which necessarily treat complex irreversible events, can never be directly tested. However they certainly can lead to predictions. The 'extreme' version of the serial endosymbiotic theory argues that three classes of eukaryotic organelles had free-living ancestors: mitochondria, basal bodies/flagella/cilia [(9 + 2) homologues] and photosynthetic plastids. Many lines of evidence support this theory and can be interpreted in relation to one another on the basis of this theory. Even if this theory should eventually be proved wrong it has the real advantage of generating a large number of unique experimentally verifiable hypotheses.

Ganymede - A relationship between thermal history and crater statistics

NASA Technical Reports Server (NTRS)

Phillips, R. J.; Malin, M. C.

1980-01-01

An approach for factoring the effects of a planetary thermal history into a predicted set of crater statistics for an icy satellite is developed and forms the basis for subsequent data inversion studies. The key parameter is a thermal evolution-dependent critical time for which craters of a particular size forming earlier do not contribute to present-day statistics. An example is given for the satellite Ganymede and the effect of the thermal history is easily seen in the resulting predicted crater statistics. A preliminary comparison with the data, subject to the uncertainties in ice rheology and impact flux history, suggests a surface age of 3.8 x 10 to the 9th years and a radionuclide abundance of 0.3 times the chondritic value.

All-electron molecular Dirac-Hartree-Fock calculations - The group IV tetrahydrides CH4, SiH4, GeH4, SnH4, and PbH4

NASA Technical Reports Server (NTRS)

Dyall, Kenneth G.; Taylor, Peter R.; Faegri, Knut, Jr.; Partridge, Harry

1991-01-01

A basis-set-expansion Dirac-Hartree-Fock program for molecules is described. Bond lengths and harmonic frequencies are presented for the ground states of the group 4 tetrahydrides, CH4, SiH4, GeH4, SnH4, and PbH4. The results are compared with relativistic effective core potential (RECP) calculations, first-order perturbation theory (PT) calculations and with experimental data. The bond lengths are well predicted by first-order perturbation theory for all molecules, but none of the RECP's considered provides a consistent prediction. Perturbation theory overestimates the relativistic correction to the harmonic frequencies; the RECP calculations underestimate the correction.

All-electron molecular Dirac-Hartree-Fock calculations: The group 4 tetrahydrides CH4, SiH4, GeH4, SnH4 and PbH4

NASA Technical Reports Server (NTRS)

Dyall, Kenneth G.; Taylor, Peter R.; Faegri, Knut, Jr.; Partridge, Harry

1990-01-01

A basis-set-expansion Dirac-Hartree-Fock program for molecules is described. Bond lengths and harmonic frequencies are presented for the ground states of the group 4 tetrahydrides, CH4, SiH4, GeH4, SnH4, and PbH4. The results are compared with relativistic effective core potential (RECP) calculations, first-order perturbation theory (PT) calculations and with experimental data. The bond lengths are well predicted by first-order perturbation theory for all molecules, but non of the RECP's considered provides a consistent prediction. Perturbation theory overestimates the relativistic correction to the harmonic frequencies; the RECP calculations underestimate the correction.

Human Frontal Lobes and AI Planning Systems

NASA Technical Reports Server (NTRS)

Levinson, Richard; Lum, Henry Jr. (Technical Monitor)

1994-01-01

Human frontal lobes are essential for maintaining a self-regulating balance between predictive and reactive behavior. This paper describes a system that integrates prediction and reaction based on neuropsychological theories of frontal lobe function. In addition to enhancing our understanding of deliberate action in humans' the model is being used to develop and evaluate the same properties in machines. First, the paper presents some background neuropsychology in order to set a general context. The role of frontal lobes is then presented by summarizing three theories which formed the basis for this work. The components of an artificial frontal lobe are then discussed from both neuropsychological and AI perspectives. The paper concludes by discussing issues and methods for evaluating systems that integrate planning and reaction.

The effect of diffuse basis functions on valence bond structural weights

NASA Astrophysics Data System (ADS)

Galbraith, John Morrison; James, Andrew M.; Nemes, Coleen T.

2014-03-01

Structural weights and bond dissociation energies have been determined for H-F, H-X, and F-X molecules (-X = -OH, -NH2, and -CH3) at the valence bond self-consistent field (VBSCF) and breathing orbital valence bond (BOVB) levels of theory with the aug-cc-pVDZ and 6-31++G(d,p) basis sets. At the BOVB level, the aug-cc-pVDZ basis set yields a counterintuitive ordering of ionic structural weights when the initial heavy atom s-type basis functions are included. For H-F, H-OH, and F-X, the ordering follows chemical intuition when these basis functions are not included. These counterintuitive weights are shown to be a result of the diffuse polarisation function on one VB fragment being spatially located, in part, on the other VB fragment. Except in the case of F-CH3, this problem is corrected with the 6-31++G(d,p) basis set. The initial heavy atom s-type functions are shown to make an important contribution to the VB orbitals and bond dissociation energies and, therefore, should not be excluded. It is recommended to not use diffuse basis sets in valence bond calculations unless absolutely necessary. If diffuse basis sets are needed, the 6-31++G(d,p) basis set should be used with caution and the structural weights checked against VBSCF values which have been shown to follow the expected ordering in all cases.

Lymph nodes ratio based nomogram predicts survival of resectable gastric cancer regardless of the number of examined lymph nodes.

PubMed

Chen, Shangxiang; Rao, Huamin; Liu, Jianjun; Geng, Qirong; Guo, Jing; Kong, Pengfei; Li, Shun; Liu, Xuechao; Sun, Xiaowei; Zhan, Youqing; Xu, Dazhi

2017-07-11

To develop a nomogram to predict the prognosis of gastric cancer patients on the basis of metastatic lymph nodes ratio (mLNR), especially in the patients with total number of examined lymph nodes (TLN) less than 15. The nomogram was constructed based on a retrospective database that included 2,205 patients underwent curative resection in Cancer Center, Sun Yat-sen University (SYSUCC). Resectable gastric cancer (RGC) patients underwent curative resection before December 31, 2008 were assigned as the training set (n=1,470) and those between January 1, 2009 and December 31, 2012 were selected as the internal validation set (n=735). Additional external validations were also performed separately by an independent data set (n=602) from Jiangxi Provincial Cancer Hospital (JXCH) in Jiangxi, China and a data set (n=3,317) from the Surveillance, Epidemiology, and End Results (SEER) database. The Independent risk factors were identified by Multivariate Cox Regression. In the SYSUCC set, TNM (Tumor-node-metastasis) and TRM-based (Tumor-Positive Nodes Ratio-Metastasis) nomograms were constructed respectively. The TNM-based nomogram showed better discrimination than the AJCC-TNM staging system (C-index: 0.73 versus 0.69, p<0.01). When the mLNR was included in the nomogram, the C-index increased to 0.76. Furthermore, the C-index in the TRM-based nomogram was similar between TLN ≥16 (C-index: 0.77) and TLN ≤15 (C-index: 0.75). The discrimination was further ascertained by internal and external validations. We developed and validated a novel TRM-based nomogram that provided more accurate prediction of survival for gastric cancer patients who underwent curative resection, regardless of the number of examined lymph nodes.

Training a cell-level classifier for detecting basal-cell carcinoma by combining human visual attention maps with low-level handcrafted features

PubMed Central

Corredor, Germán; Whitney, Jon; Arias, Viviana; Madabhushi, Anant; Romero, Eduardo

2017-01-01

Abstract. Computational histomorphometric approaches typically use low-level image features for building machine learning classifiers. However, these approaches usually ignore high-level expert knowledge. A computational model (M_im) combines low-, mid-, and high-level image information to predict the likelihood of cancer in whole slide images. Handcrafted low- and mid-level features are computed from area, color, and spatial nuclei distributions. High-level information is implicitly captured from the recorded navigations of pathologists while exploring whole slide images during diagnostic tasks. This model was validated by predicting the presence of cancer in a set of unseen fields of view. The available database was composed of 24 cases of basal-cell carcinoma, from which 17 served to estimate the model parameters and the remaining 7 comprised the evaluation set. A total of 274 fields of view of size 1024×1024  pixels were extracted from the evaluation set. Then 176 patches from this set were used to train a support vector machine classifier to predict the presence of cancer on a patch-by-patch basis while the remaining 98 image patches were used for independent testing, ensuring that the training and test sets do not comprise patches from the same patient. A baseline model (M_ex) estimated the cancer likelihood for each of the image patches. M_ex uses the same visual features as M_im, but its weights are estimated from nuclei manually labeled as cancerous or noncancerous by a pathologist. M_im achieved an accuracy of 74.49% and an F-measure of 80.31%, while M_ex yielded corresponding accuracy and F-measures of 73.47% and 77.97%, respectively. PMID:28382314

PRIME – PRocess modelling in ImpleMEntation research: selecting a theoretical basis for interventions to change clinical practice

PubMed Central

Walker, Anne E; Grimshaw, Jeremy; Johnston, Marie; Pitts, Nigel; Steen, Nick; Eccles, Martin

2003-01-01

Background Biomedical research constantly produces new findings but these are not routinely translated into health care practice. One way to address this problem is to develop effective interventions to translate research findings into practice. Currently a range of empirical interventions are available and systematic reviews of these have demonstrated that there is no single best intervention. This evidence base is difficult to use in routine settings because it cannot identify which intervention is most likely to be effective (or cost effective) in a particular situation. We need to establish a scientific rationale for interventions. As clinical practice is a form of human behaviour, theories of human behaviour that have proved useful in other similar settings may provide a basis for developing a scientific rationale for the choice of interventions to translate research findings into clinical practice. The objectives of the study are: to amplify and populate scientifically validated theories of behaviour with evidence from the experience of health professionals; to use this as a basis for developing predictive questionnaires using replicable methods; to identify which elements of the questionnaire (i.e., which theoretical constructs) predict clinical practice and distinguish between evidence compliant and non-compliant practice; and on the basis of these results, to identify variables (based on theoretical constructs) that might be prime targets for behaviour change interventions. Methods We will develop postal questionnaires measuring two motivational, three action and one stage theory to explore five behaviours with 800 general medical and 600 general dental practitioners. We will collect data on performance for each of the behaviours. The relationships between predictor variables (theoretical constructs) and outcome measures (data on performance) in each survey will be assessed using multiple regression analysis and structural equation modelling. In the final phase of the project, the findings from all surveys will be analysed simultaneously adopting a random effects approach to investigate whether the relationships between predictor variables and outcome measures are modified by behaviour, professional group or geographical location. PMID:14683530

The Heterogeneous Dynamics of Economic Complexity

PubMed Central

Cristelli, Matthieu; Tacchella, Andrea; Pietronero, Luciano

2015-01-01

What will be the growth of the Gross Domestic Product (GDP) or the competitiveness of China, United States, and Vietnam in the next 3, 5 or 10 years? Despite this kind of questions has a large societal impact and an extreme value for economic policy making, providing a scientific basis for economic predictability is still a very challenging problem. Recent results of a new branch—Economic Complexity—have set the basis for a framework to approach such a challenge and to provide new perspectives to cast economic prediction into the conceptual scheme of forecasting the evolution of a dynamical system as in the case of weather dynamics. We argue that a recently introduced non-monetary metrics for country competitiveness (fitness) allows for quantifying the hidden growth potential of countries by the means of the comparison of this measure for intangible assets with monetary figures, such as GDP per capita. This comparison defines the fitness-income plane where we observe that country dynamics presents strongly heterogeneous patterns of evolution. The flow in some zones is found to be laminar while in others a chaotic behavior is instead observed. These two regimes correspond to very different predictability features for the evolution of countries: in the former regime, we find strong predictable pattern while the latter scenario exhibits a very low predictability. In such a framework, regressions, the usual tool used in economics, are no more the appropriate strategy to deal with such a heterogeneous scenario and new concepts, borrowed from dynamical systems theory, are mandatory. We therefore propose a data-driven method—the selective predictability scheme—in which we adopt a strategy similar to the methods of analogues, firstly introduced by Lorenz, to assess future evolution of countries. PMID:25671312

The heterogeneous dynamics of economic complexity.

PubMed

Cristelli, Matthieu; Tacchella, Andrea; Pietronero, Luciano

2015-01-01

What will be the growth of the Gross Domestic Product (GDP) or the competitiveness of China, United States, and Vietnam in the next 3, 5 or 10 years? Despite this kind of questions has a large societal impact and an extreme value for economic policy making, providing a scientific basis for economic predictability is still a very challenging problem. Recent results of a new branch--Economic Complexity--have set the basis for a framework to approach such a challenge and to provide new perspectives to cast economic prediction into the conceptual scheme of forecasting the evolution of a dynamical system as in the case of weather dynamics. We argue that a recently introduced non-monetary metrics for country competitiveness (fitness) allows for quantifying the hidden growth potential of countries by the means of the comparison of this measure for intangible assets with monetary figures, such as GDP per capita. This comparison defines the fitness-income plane where we observe that country dynamics presents strongly heterogeneous patterns of evolution. The flow in some zones is found to be laminar while in others a chaotic behavior is instead observed. These two regimes correspond to very different predictability features for the evolution of countries: in the former regime, we find strong predictable pattern while the latter scenario exhibits a very low predictability. In such a framework, regressions, the usual tool used in economics, are no more the appropriate strategy to deal with such a heterogeneous scenario and new concepts, borrowed from dynamical systems theory, are mandatory. We therefore propose a data-driven method--the selective predictability scheme--in which we adopt a strategy similar to the methods of analogues, firstly introduced by Lorenz, to assess future evolution of countries.

On the effects of basis set truncation and electron correlation in conformers of 2-hydroxy-acetamide

NASA Astrophysics Data System (ADS)

Szarecka, A.; Day, G.; Grout, P. J.; Wilson, S.

Ab initio quantum chemical calculations have been used to study the differences in energy between two gas phase conformers of the 2-hydroxy-acetamide molecule that possess intramolecular hydrogen bonding. In particular, rotation around the central C-C bond has been considered as a factor determining the structure of the hydrogen bond and stabilization of the conformer. Energy calculations include full geometiy optimization using both the restricted matrix Hartree-Fock model and second-order many-body perturbation theory with a number of commonly used basis sets. The basis sets employed ranged from the minimal STO-3G set to [`]split-valence' sets up to 6-31 G. The effects of polarization functions were also studied. The results display a strong basis set dependence.

Copy number variation signature to predict human ancestry

PubMed Central

2012-01-01

Background Copy number variations (CNVs) are genomic structural variants that are found in healthy populations and have been observed to be associated with disease susceptibility. Existing methods for CNV detection are often performed on a sample-by-sample basis, which is not ideal for large datasets where common CNVs must be estimated by comparing the frequency of CNVs in the individual samples. Here we describe a simple and novel approach to locate genome-wide CNVs common to a specific population, using human ancestry as the phenotype. Results We utilized our previously published Genome Alteration Detection Analysis (GADA) algorithm to identify common ancestry CNVs (caCNVs) and built a caCNV model to predict population structure. We identified a 73 caCNV signature using a training set of 225 healthy individuals from European, Asian, and African ancestry. The signature was validated on an independent test set of 300 individuals with similar ancestral background. The error rate in predicting ancestry in this test set was 2% using the 73 caCNV signature. Among the caCNVs identified, several were previously confirmed experimentally to vary by ancestry. Our signature also contains a caCNV region with a single microRNA (MIR270), which represents the first reported variation of microRNA by ancestry. Conclusions We developed a new methodology to identify common CNVs and demonstrated its performance by building a caCNV signature to predict human ancestry with high accuracy. The utility of our approach could be extended to large case–control studies to identify CNV signatures for other phenotypes such as disease susceptibility and drug response. PMID:23270563

The effect of psychological distance on automatic goal contagion

PubMed Central

Wessler, Janet; Hansen, Jochim

2016-01-01

ABSTRACT We investigated how psychological distance influences goal contagion (the extent to which people automatically adopt another person’s goals). On the basis of construal-level theory, we predicted people would be more prone to goal contagion when primed with psychological distance (vs. closeness) because they would construe the other person’s behavior in terms of its underlying goal. Alternatively, we predicted people primed with psychological closeness (vs. distance) would be more prone to goal contagion because closeness may increase the personal relevance of another’s goals – a process not mediated by construal level. In two preregistered studies, participants read about a student whose behavior implied either an academic or a social goal. We manipulated (a) participants’ level of mental construal with a mind-set task (Study 1) and (b) their social distance from another person who showed academic or social behaviors (Study 2). We measured performance on an anagram task as an indicator of academic goal contagion. For Study 1, we predicted that participants reading about academic (vs. social) behaviors would show a better anagram performance, especially when primed with an abstract mind-set. For Study 2, we predicted that construal level and relevance effects might cancel each other out, because distance triggers both high-level construal and less relevance. In contrast to the construal-level hypothesis, the mind-set manipulation did not affect goal contagion in Study 1. In accordance with the relevance hypothesis, psychological proximity increased goal contagion in Study 2. We discuss how the findings relate to previous findings on goal contagion and imitation. PMID:29098177

Reynolds averaged turbulence modelling using deep neural networks with embedded invariance

DOE PAGES

Ling, Julia; Kurzawski, Andrew; Templeton, Jeremy

2016-10-18

There exists significant demand for improved Reynolds-averaged Navier–Stokes (RANS) turbulence models that are informed by and can represent a richer set of turbulence physics. This paper presents a method of using deep neural networks to learn a model for the Reynolds stress anisotropy tensor from high-fidelity simulation data. A novel neural network architecture is proposed which uses a multiplicative layer with an invariant tensor basis to embed Galilean invariance into the predicted anisotropy tensor. It is demonstrated that this neural network architecture provides improved prediction accuracy compared with a generic neural network architecture that does not embed this invariance property.more » Furthermore, the Reynolds stress anisotropy predictions of this invariant neural network are propagated through to the velocity field for two test cases. For both test cases, significant improvement versus baseline RANS linear eddy viscosity and nonlinear eddy viscosity models is demonstrated.« less

Reynolds averaged turbulence modelling using deep neural networks with embedded invariance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ling, Julia; Kurzawski, Andrew; Templeton, Jeremy

There exists significant demand for improved Reynolds-averaged Navier–Stokes (RANS) turbulence models that are informed by and can represent a richer set of turbulence physics. This paper presents a method of using deep neural networks to learn a model for the Reynolds stress anisotropy tensor from high-fidelity simulation data. A novel neural network architecture is proposed which uses a multiplicative layer with an invariant tensor basis to embed Galilean invariance into the predicted anisotropy tensor. It is demonstrated that this neural network architecture provides improved prediction accuracy compared with a generic neural network architecture that does not embed this invariance property.more » Furthermore, the Reynolds stress anisotropy predictions of this invariant neural network are propagated through to the velocity field for two test cases. For both test cases, significant improvement versus baseline RANS linear eddy viscosity and nonlinear eddy viscosity models is demonstrated.« less

High Fidelity Ion Beam Simulation of High Dose Neutron Irradiation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Was, Gary; Wirth, Brian; Motta, Athur

The objective of this proposal is to demonstrate the capability to predict the evolution of microstructure and properties of structural materials in-reactor and at high doses, using ion irradiation as a surrogate for reactor irradiations. “Properties” includes both physical properties (irradiated microstructure) and the mechanical properties of the material. Demonstration of the capability to predict properties has two components. One is ion irradiation of a set of alloys to yield an irradiated microstructure and corresponding mechanical behavior that are substantially the same as results from neutron exposure in the appropriate reactor environment. Second is the capability to predict the irradiatedmore » microstructure and corresponding mechanical behavior on the basis of improved models, validated against both ion and reactor irradiations and verified against ion irradiations. Taken together, achievement of these objectives will yield an enhanced capability for simulating the behavior of materials in reactor irradiations.« less

A spatially adaptive spectral re-ordering technique for lossless coding of hyper-spectral images

NASA Technical Reports Server (NTRS)

Memon, Nasir D.; Galatsanos, Nikolas

1995-01-01

In this paper, we propose a new approach, applicable to lossless compression of hyper-spectral images, that alleviates some limitations of linear prediction as applied to this problem. According to this approach, an adaptive re-ordering of the spectral components of each pixel is performed prior to prediction and encoding. This re-ordering adaptively exploits, on a pixel-by pixel basis, the presence of inter-band correlations for prediction. Furthermore, the proposed approach takes advantage of spatial correlations, and does not introduce any coding overhead to transmit the order of the spectral bands. This is accomplished by using the assumption that two spatially adjacent pixels are expected to have similar spectral relationships. We thus have a simple technique to exploit spectral and spatial correlations in hyper-spectral data sets, leading to compression performance improvements as compared to our previously reported techniques for lossless compression. We also look at some simple error modeling techniques for further exploiting any structure that remains in the prediction residuals prior to entropy coding.

Prediction of chemical biodegradability using support vector classifier optimized with differential evolution.

PubMed

Cao, Qi; Leung, K M

2014-09-22

Reliable computer models for the prediction of chemical biodegradability from molecular descriptors and fingerprints are very important for making health and environmental decisions. Coupling of the differential evolution (DE) algorithm with the support vector classifier (SVC) in order to optimize the main parameters of the classifier resulted in an improved classifier called the DE-SVC, which is introduced in this paper for use in chemical biodegradability studies. The DE-SVC was applied to predict the biodegradation of chemicals on the basis of extensive sample data sets and known structural features of molecules. Our optimization experiments showed that DE can efficiently find the proper parameters of the SVC. The resulting classifier possesses strong robustness and reliability compared with grid search, genetic algorithm, and particle swarm optimization methods. The classification experiments conducted here showed that the DE-SVC exhibits better classification performance than models previously used for such studies. It is a more effective and efficient prediction model for chemical biodegradability.

On the optimization of Gaussian basis sets

NASA Astrophysics Data System (ADS)

Petersson, George A.; Zhong, Shijun; Montgomery, John A.; Frisch, Michael J.

2003-01-01

A new procedure for the optimization of the exponents, αj, of Gaussian basis functions, Ylm(ϑ,φ)rle-αjr2, is proposed and evaluated. The direct optimization of the exponents is hindered by the very strong coupling between these nonlinear variational parameters. However, expansion of the logarithms of the exponents in the orthonormal Legendre polynomials, Pk, of the index, j: ln αj=∑k=0kmaxAkPk((2j-2)/(Nprim-1)-1), yields a new set of well-conditioned parameters, Ak, and a complete sequence of well-conditioned exponent optimizations proceeding from the even-tempered basis set (kmax=1) to a fully optimized basis set (kmax=Nprim-1). The error relative to the exact numerical self-consistent field limit for a six-term expansion is consistently no more than 25% larger than the error for the completely optimized basis set. Thus, there is no need to optimize more than six well-conditioned variational parameters, even for the largest sets of Gaussian primitives.

DFT calculation and vibrational spectroscopic studies of 2-(tert-butoxycarbonyl (Boc) -amino)-5-bromopyridine.

PubMed

Premkumar, S; Jawahar, A; Mathavan, T; Kumara Dhas, M; Sathe, V G; Milton Franklin Benial, A

2014-08-14

The molecular structure of 2-(tert-butoxycarbonyl (Boc) -amino)-5-bromopyridine (BABP) was optimized by the DFT/B3LYP method with 6-311G (d,p), 6-311++G (d,p) and cc-pVTZ basis sets using the Gaussian 09 program. The most stable optimized structure of the molecule was predicted by the DFT/B3LYP method with cc-pVTZ basis set. The vibrational frequencies, Mulliken atomic charge distribution, frontier molecular orbitals and thermodynamical parameters were calculated. These calculations were done at the ground state energy level of BABP without applying any constraint on the potential energy surface. The vibrational spectra were experimentally recorded using Fourier Transform-Infrared (FT-IR) and micro-Raman spectrometer. The computed vibrational frequencies were scaled by scale factors to yield a good agreement with observed experimental vibrational frequencies. The complete theoretically calculated and experimentally observed vibrational frequencies were assigned on the basis of Potential Energy Distribution (PED) calculation using the VEDA 4.0 program. The vibrational modes assignments were performed by using the animation option of GaussView 05 graphical interface for Gaussian program. The Mulliken atomic charge distribution was calculated for BABP molecule. The molecular reactivity and stability of BABP were also studied by frontier molecular orbitals (FMOs) analysis. Copyright © 2014 Elsevier B.V. All rights reserved.

Accurate and balanced anisotropic Gaussian type orbital basis sets for atoms in strong magnetic fields.

PubMed

Zhu, Wuming; Trickey, S B

2017-12-28

In high magnetic field calculations, anisotropic Gaussian type orbital (AGTO) basis functions are capable of reconciling the competing demands of the spherically symmetric Coulombic interaction and cylindrical magnetic (B field) confinement. However, the best available a priori procedure for composing highly accurate AGTO sets for atoms in a strong B field [W. Zhu et al., Phys. Rev. A 90, 022504 (2014)] yields very large basis sets. Their size is problematical for use in any calculation with unfavorable computational cost scaling. Here we provide an alternative constructive procedure. It is based upon analysis of the underlying physics of atoms in B fields that allow identification of several principles for the construction of AGTO basis sets. Aided by numerical optimization and parameter fitting, followed by fine tuning of fitting parameters, we devise formulae for generating accurate AGTO basis sets in an arbitrary B field. For the hydrogen iso-electronic sequence, a set depends on B field strength, nuclear charge, and orbital quantum numbers. For multi-electron systems, the basis set formulae also include adjustment to account for orbital occupations. Tests of the new basis sets for atoms H through C (1 ≤ Z ≤ 6) and ions Li + , Be + , and B + , in a wide B field range (0 ≤ B ≤ 2000 a.u.), show an accuracy better than a few μhartree for single-electron systems and a few hundredths to a few mHs for multi-electron atoms. The relative errors are similar for different atoms and ions in a large B field range, from a few to a couple of tens of millionths, thereby confirming rather uniform accuracy across the nuclear charge Z and B field strength values. Residual basis set errors are two to three orders of magnitude smaller than the electronic correlation energies in multi-electron atoms, a signal of the usefulness of the new AGTO basis sets in correlated wavefunction or density functional calculations for atomic and molecular systems in an external strong B field.

Accurate and balanced anisotropic Gaussian type orbital basis sets for atoms in strong magnetic fields

NASA Astrophysics Data System (ADS)

Zhu, Wuming; Trickey, S. B.

2017-12-01

In high magnetic field calculations, anisotropic Gaussian type orbital (AGTO) basis functions are capable of reconciling the competing demands of the spherically symmetric Coulombic interaction and cylindrical magnetic (B field) confinement. However, the best available a priori procedure for composing highly accurate AGTO sets for atoms in a strong B field [W. Zhu et al., Phys. Rev. A 90, 022504 (2014)] yields very large basis sets. Their size is problematical for use in any calculation with unfavorable computational cost scaling. Here we provide an alternative constructive procedure. It is based upon analysis of the underlying physics of atoms in B fields that allow identification of several principles for the construction of AGTO basis sets. Aided by numerical optimization and parameter fitting, followed by fine tuning of fitting parameters, we devise formulae for generating accurate AGTO basis sets in an arbitrary B field. For the hydrogen iso-electronic sequence, a set depends on B field strength, nuclear charge, and orbital quantum numbers. For multi-electron systems, the basis set formulae also include adjustment to account for orbital occupations. Tests of the new basis sets for atoms H through C (1 ≤ Z ≤ 6) and ions Li+, Be+, and B+, in a wide B field range (0 ≤ B ≤ 2000 a.u.), show an accuracy better than a few μhartree for single-electron systems and a few hundredths to a few mHs for multi-electron atoms. The relative errors are similar for different atoms and ions in a large B field range, from a few to a couple of tens of millionths, thereby confirming rather uniform accuracy across the nuclear charge Z and B field strength values. Residual basis set errors are two to three orders of magnitude smaller than the electronic correlation energies in multi-electron atoms, a signal of the usefulness of the new AGTO basis sets in correlated wavefunction or density functional calculations for atomic and molecular systems in an external strong B field.

Basis set limit and systematic errors in local-orbital based all-electron DFT

NASA Astrophysics Data System (ADS)

Blum, Volker; Behler, Jörg; Gehrke, Ralf; Reuter, Karsten; Scheffler, Matthias

2006-03-01

With the advent of efficient integration schemes,^1,2 numeric atom-centered orbitals (NAO's) are an attractive basis choice in practical density functional theory (DFT) calculations of nanostructured systems (surfaces, clusters, molecules). Though all-electron, the efficiency of practical implementations promises to be on par with the best plane-wave pseudopotential codes, while having a noticeably higher accuracy if required: Minimal-sized effective tight-binding like calculations and chemically accurate all-electron calculations are both possible within the same framework; non-periodic and periodic systems can be treated on equal footing; and the localized nature of the basis allows in principle for O(N)-like scaling. However, converging an observable with respect to the basis set is less straightforward than with competing systematic basis choices (e.g., plane waves). We here investigate the basis set limit of optimized NAO basis sets in all-electron calculations, using as examples small molecules and clusters (N2, Cu2, Cu4, Cu10). meV-level total energy convergence is possible using <=50 basis functions per atom in all cases. We also find a clear correlation between the errors which arise from underconverged basis sets, and the system geometry (interatomic distance). ^1 B. Delley, J. Chem. Phys. 92, 508 (1990), ^2 J.M. Soler et al., J. Phys.: Condens. Matter 14, 2745 (2002).

What do we gain with Probabilistic Flood Loss Models?

NASA Astrophysics Data System (ADS)

Schroeter, K.; Kreibich, H.; Vogel, K.; Merz, B.; Lüdtke, S.

2015-12-01

The reliability of flood loss models is a prerequisite for their practical usefulness. Oftentimes, traditional uni-variate damage models as for instance depth-damage curves fail to reproduce the variability of observed flood damage. Innovative multi-variate probabilistic modelling approaches are promising to capture and quantify the uncertainty involved and thus to improve the basis for decision making. In this study we compare the predictive capability of two probabilistic modelling approaches, namely Bagging Decision Trees and Bayesian Networks and traditional stage damage functions which are cast in a probabilistic framework. For model evaluation we use empirical damage data which are available from computer aided telephone interviews that were respectively compiled after the floods in 2002, 2005, 2006 and 2013 in the Elbe and Danube catchments in Germany. We carry out a split sample test by sub-setting the damage records. One sub-set is used to derive the models and the remaining records are used to evaluate the predictive performance of the model. Further we stratify the sample according to catchments which allows studying model performance in a spatial transfer context. Flood damage estimation is carried out on the scale of the individual buildings in terms of relative damage. The predictive performance of the models is assessed in terms of systematic deviations (mean bias), precision (mean absolute error) as well as in terms of reliability which is represented by the proportion of the number of observations that fall within the 95-quantile and 5-quantile predictive interval. The reliability of the probabilistic predictions within validation runs decreases only slightly and achieves a very good coverage of observations within the predictive interval. Probabilistic models provide quantitative information about prediction uncertainty which is crucial to assess the reliability of model predictions and improves the usefulness of model results.

Predicting acute aquatic toxicity of structurally diverse chemicals in fish using artificial intelligence approaches.

PubMed

Singh, Kunwar P; Gupta, Shikha; Rai, Premanjali

2013-09-01

The research aims to develop global modeling tools capable of categorizing structurally diverse chemicals in various toxicity classes according to the EEC and European Community directives, and to predict their acute toxicity in fathead minnow using set of selected molecular descriptors. Accordingly, artificial intelligence approach based classification and regression models, such as probabilistic neural networks (PNN), generalized regression neural networks (GRNN), multilayer perceptron neural network (MLPN), radial basis function neural network (RBFN), support vector machines (SVM), gene expression programming (GEP), and decision tree (DT) were constructed using the experimental toxicity data. Diversity and non-linearity in the chemicals' data were tested using the Tanimoto similarity index and Brock-Dechert-Scheinkman statistics. Predictive and generalization abilities of various models constructed here were compared using several statistical parameters. PNN and GRNN models performed relatively better than MLPN, RBFN, SVM, GEP, and DT. Both in two and four category classifications, PNN yielded a considerably high accuracy of classification in training (95.85 percent and 90.07 percent) and validation data (91.30 percent and 86.96 percent), respectively. GRNN rendered a high correlation between the measured and model predicted -log LC50 values both for the training (0.929) and validation (0.910) data and low prediction errors (RMSE) of 0.52 and 0.49 for two sets. Efficiency of the selected PNN and GRNN models in predicting acute toxicity of new chemicals was adequately validated using external datasets of different fish species (fathead minnow, bluegill, trout, and guppy). The PNN and GRNN models showed good predictive and generalization abilities and can be used as tools for predicting toxicities of structurally diverse chemical compounds. Copyright © 2013 Elsevier Inc. All rights reserved.

Basis set construction for molecular electronic structure theory: natural orbital and Gauss-Slater basis for smooth pseudopotentials.

PubMed

Petruzielo, F R; Toulouse, Julien; Umrigar, C J

2011-02-14

A simple yet general method for constructing basis sets for molecular electronic structure calculations is presented. These basis sets consist of atomic natural orbitals from a multiconfigurational self-consistent field calculation supplemented with primitive functions, chosen such that the asymptotics are appropriate for the potential of the system. Primitives are optimized for the homonuclear diatomic molecule to produce a balanced basis set. Two general features that facilitate this basis construction are demonstrated. First, weak coupling exists between the optimal exponents of primitives with different angular momenta. Second, the optimal primitive exponents for a chosen system depend weakly on the particular level of theory employed for optimization. The explicit case considered here is a basis set appropriate for the Burkatzki-Filippi-Dolg pseudopotentials. Since these pseudopotentials are finite at nuclei and have a Coulomb tail, the recently proposed Gauss-Slater functions are the appropriate primitives. Double- and triple-zeta bases are developed for elements hydrogen through argon. These new bases offer significant gains over the corresponding Burkatzki-Filippi-Dolg bases at various levels of theory. Using a Gaussian expansion of the basis functions, these bases can be employed in any electronic structure method. Quantum Monte Carlo provides an added benefit: expansions are unnecessary since the integrals are evaluated numerically.

Auxiliary basis sets for density-fitting second-order Møller-Plesset perturbation theory: weighted core-valence correlation consistent basis sets for the 4d elements Y-Pd.

PubMed

Hill, J Grant

2013-09-30

Auxiliary basis sets (ABS) specifically matched to the cc-pwCVnZ-PP and aug-cc-pwCVnZ-PP orbital basis sets (OBS) have been developed and optimized for the 4d elements Y-Pd at the second-order Møller-Plesset perturbation theory level. Calculation of the core-valence electron correlation energies for small to medium sized transition metal complexes demonstrates that the error due to the use of these new sets in density fitting is three to four orders of magnitude smaller than that due to the OBS incompleteness, and hence is considered negligible. Utilizing the ABSs in the resolution-of-the-identity component of explicitly correlated calculations is also investigated, where it is shown that i-type functions are important to produce well-controlled errors in both integrals and correlation energy. Benchmarking at the explicitly correlated coupled cluster with single, double, and perturbative triple excitations level indicates impressive convergence with respect to basis set size for the spectroscopic constants of 4d monofluorides; explicitly correlated double-ζ calculations produce results close to conventional quadruple-ζ, and triple-ζ is within chemical accuracy of the complete basis set limit. Copyright © 2013 Wiley Periodicals, Inc.

Adaptive local basis set for Kohn–Sham density functional theory in a discontinuous Galerkin framework II: Force, vibration, and molecular dynamics calculations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Gaigong; Lin, Lin, E-mail: linlin@math.berkeley.edu; Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720

Recently, we have proposed the adaptive local basis set for electronic structure calculations based on Kohn–Sham density functional theory in a pseudopotential framework. The adaptive local basis set is efficient and systematically improvable for total energy calculations. In this paper, we present the calculation of atomic forces, which can be used for a range of applications such as geometry optimization and molecular dynamics simulation. We demonstrate that, under mild assumptions, the computation of atomic forces can scale nearly linearly with the number of atoms in the system using the adaptive local basis set. We quantify the accuracy of the Hellmann–Feynmanmore » forces for a range of physical systems, benchmarked against converged planewave calculations, and find that the adaptive local basis set is efficient for both force and energy calculations, requiring at most a few tens of basis functions per atom to attain accuracies required in practice. Since the adaptive local basis set has implicit dependence on atomic positions, Pulay forces are in general nonzero. However, we find that the Pulay force is numerically small and systematically decreasing with increasing basis completeness, so that the Hellmann–Feynman force is sufficient for basis sizes of a few tens of basis functions per atom. We verify the accuracy of the computed forces in static calculations of quasi-1D and 3D disordered Si systems, vibration calculation of a quasi-1D Si system, and molecular dynamics calculations of H{sub 2} and liquid Al–Si alloy systems, where we show systematic convergence to benchmark planewave results and results from the literature.« less

Adaptive local basis set for Kohn–Sham density functional theory in a discontinuous Galerkin framework II: Force, vibration, and molecular dynamics calculations

DOE PAGES

Zhang, Gaigong; Lin, Lin; Hu, Wei; ...

2017-01-27

Recently, we have proposed the adaptive local basis set for electronic structure calculations based on Kohn–Sham density functional theory in a pseudopotential framework. The adaptive local basis set is efficient and systematically improvable for total energy calculations. In this paper, we present the calculation of atomic forces, which can be used for a range of applications such as geometry optimization and molecular dynamics simulation. We demonstrate that, under mild assumptions, the computation of atomic forces can scale nearly linearly with the number of atoms in the system using the adaptive local basis set. We quantify the accuracy of the Hellmann–Feynmanmore » forces for a range of physical systems, benchmarked against converged planewave calculations, and find that the adaptive local basis set is efficient for both force and energy calculations, requiring at most a few tens of basis functions per atom to attain accuracies required in practice. Sin ce the adaptive local basis set has implicit dependence on atomic positions, Pulay forces are in general nonzero. However, we find that the Pulay force is numerically small and systematically decreasing with increasing basis completeness, so that the Hellmann–Feynman force is sufficient for basis sizes of a few tens of basis functions per atom. We verify the accuracy of the computed forces in static calculations of quasi-1D and 3D disordered Si systems, vibration calculation of a quasi-1D Si system, and molecular dynamics calculations of H 2 and liquid Al–Si alloy systems, where we show systematic convergence to benchmark planewave results and results from the literature.« less

Adaptive local basis set for Kohn–Sham density functional theory in a discontinuous Galerkin framework II: Force, vibration, and molecular dynamics calculations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Gaigong; Lin, Lin; Hu, Wei

Recently, we have proposed the adaptive local basis set for electronic structure calculations based on Kohn–Sham density functional theory in a pseudopotential framework. The adaptive local basis set is efficient and systematically improvable for total energy calculations. In this paper, we present the calculation of atomic forces, which can be used for a range of applications such as geometry optimization and molecular dynamics simulation. We demonstrate that, under mild assumptions, the computation of atomic forces can scale nearly linearly with the number of atoms in the system using the adaptive local basis set. We quantify the accuracy of the Hellmann–Feynmanmore » forces for a range of physical systems, benchmarked against converged planewave calculations, and find that the adaptive local basis set is efficient for both force and energy calculations, requiring at most a few tens of basis functions per atom to attain accuracies required in practice. Sin ce the adaptive local basis set has implicit dependence on atomic positions, Pulay forces are in general nonzero. However, we find that the Pulay force is numerically small and systematically decreasing with increasing basis completeness, so that the Hellmann–Feynman force is sufficient for basis sizes of a few tens of basis functions per atom. We verify the accuracy of the computed forces in static calculations of quasi-1D and 3D disordered Si systems, vibration calculation of a quasi-1D Si system, and molecular dynamics calculations of H 2 and liquid Al–Si alloy systems, where we show systematic convergence to benchmark planewave results and results from the literature.« less

Adaptive local basis set for Kohn-Sham density functional theory in a discontinuous Galerkin framework II: Force, vibration, and molecular dynamics calculations

NASA Astrophysics Data System (ADS)

Zhang, Gaigong; Lin, Lin; Hu, Wei; Yang, Chao; Pask, John E.

2017-04-01

Recently, we have proposed the adaptive local basis set for electronic structure calculations based on Kohn-Sham density functional theory in a pseudopotential framework. The adaptive local basis set is efficient and systematically improvable for total energy calculations. In this paper, we present the calculation of atomic forces, which can be used for a range of applications such as geometry optimization and molecular dynamics simulation. We demonstrate that, under mild assumptions, the computation of atomic forces can scale nearly linearly with the number of atoms in the system using the adaptive local basis set. We quantify the accuracy of the Hellmann-Feynman forces for a range of physical systems, benchmarked against converged planewave calculations, and find that the adaptive local basis set is efficient for both force and energy calculations, requiring at most a few tens of basis functions per atom to attain accuracies required in practice. Since the adaptive local basis set has implicit dependence on atomic positions, Pulay forces are in general nonzero. However, we find that the Pulay force is numerically small and systematically decreasing with increasing basis completeness, so that the Hellmann-Feynman force is sufficient for basis sizes of a few tens of basis functions per atom. We verify the accuracy of the computed forces in static calculations of quasi-1D and 3D disordered Si systems, vibration calculation of a quasi-1D Si system, and molecular dynamics calculations of H2 and liquid Al-Si alloy systems, where we show systematic convergence to benchmark planewave results and results from the literature.

Kinetic balance and variational bounds failure in the solution of the Dirac equation in a finite Gaussian basis set

NASA Technical Reports Server (NTRS)

Dyall, Kenneth G.; Faegri, Knut, Jr.

1990-01-01

The paper investigates bounds failure in calculations using Gaussian basis sets for the solution of the one-electron Dirac equation for the 2p1/2 state of Hg(79+). It is shown that bounds failure indicates inadequacies in the basis set, both in terms of the exponent range and the number of functions. It is also shown that overrepresentation of the small component space may lead to unphysical results. It is concluded that it is important to use matched large and small component basis sets with an adequate size and exponent range.

Ab Initio and Analytic Intermolecular Potentials for Ar-CF₄

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vayner, Grigoriy; Alexeev, Yuri; Wang, Jiangping

2006-03-09

Ab initio calculations at the CCSD(T) level of theory are performed to characterize the Ar + CF ₄ intermolecular potential. Extensive calculations, with and without a correction for basis set superposition error (BSSE), are performed with the cc-pVTZ basis set. Additional calculations are performed with other correlation consistent (cc) basis sets to extrapolate the Ar---CF₄potential energy minimum to the complete basis set (CBS) limit. Both the size of the basis set and BSSE have substantial effects on the Ar + CF₄ potential. Calculations with the cc-pVTZ basis set and without a BSSE correction, appear to give a good representation ofmore » the potential at the CBS limit and with a BSSE correction. In addition, MP2 theory is found to give potential energies in very good agreement with those determined by the much higher level CCSD(T) theory. Two analytic potential energy functions were determined for Ar + CF₄by fitting the cc-pVTZ calculations both with and without a BSSE correction. These analytic functions were written as a sum of two body potentials and excellent fits to the ab initio potentials were obtained by representing each two body interaction as a Buckingham potential.« less

On the performance of large Gaussian basis sets for the computation of total atomization energies

NASA Technical Reports Server (NTRS)

Martin, J. M. L.

1992-01-01

The total atomization energies of a number of molecules have been computed using an augmented coupled-cluster method and (5s4p3d2f1g) and 4s3p2d1f) atomic natural orbital (ANO) basis sets, as well as the correlation consistent valence triple zeta plus polarization (cc-pVTZ) correlation consistent valence quadrupole zeta plus polarization (cc-pVQZ) basis sets. The performance of ANO and correlation consistent basis sets is comparable throughout, although the latter can result in significant CPU time savings. Whereas the inclusion of g functions has significant effects on the computed Sigma D(e) values, chemical accuracy is still not reached for molecules involving multiple bonds. A Gaussian-1 (G) type correction lowers the error, but not much beyond the accuracy of the G1 model itself. Using separate corrections for sigma bonds, pi bonds, and valence pairs brings down the mean absolute error to less than 1 kcal/mol for the spdf basis sets, and about 0.5 kcal/mol for the spdfg basis sets. Some conclusions on the success of the Gaussian-1 and Gaussian-2 models are drawn.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Megala, M.; Rajkumar, Beulah J. M., E-mail: beulah-rajkumar@yahoo.co.in

The electronic and optical transfer properties of Benzene, Benzoic Acid (BA), Nitrobenzene (NB) and Para Nitro Benzoic Acid (PNBA) at ground and first excited state has been investigated by the Density functional theory (DFT)and Time Dependent Density Functional Theory (TDDFT) using SVWN functional/3-21G basis set respectively. Possible intra-molecular charge transfer and n to π* transitions in the ground and the first excitation states have been predicted by the molecular orbitals and the Natural Bond Orbital (NBO) analysis. The simulated absorption spectra have been generated and the result compared with existing experimental results.

Unusual structures of MgF5- superhalogen anion

NASA Astrophysics Data System (ADS)

Anusiewicz, Iwona; Skurski, Piotr

2007-05-01

The vertical electron detachment energies (VDE) of three MgF5- anions were calculated at the outer valence Green function level with the 6-311 + G(3df) basis sets. This species was found to form unusual geometrical structures each of which corresponds to an anionic state exhibiting superhalogen nature. The global minimum structure was described as a system in which two central magnesium atoms are linked via symmetrical triangle formed by three fluorine atoms. Extremely large electron binding energies of these anions (exceeding 8.5 eV in all cases) were predicted and discussed.

Early identification of atopy in the prediction of persistent asthma in children.

PubMed

Sly, Peter D; Boner, Attilio L; Björksten, Bengt; Bush, Andy; Custovic, Adnan; Eigenmann, Philippe A; Gern, James E; Gerritsen, Jorrit; Hamelmann, Eckard; Helms, Peter J; Lemanske, Robert F; Martinez, Fernando; Pedersen, Soren; Renz, Harald; Sampson, Hugh; von Mutius, Erika; Wahn, Ulrich; Holt, Patrick G

2008-09-20

The long-term solution to the asthma epidemic is thought to be prevention, and not treatment of established disease. Atopic asthma arises from gene-environment interactions, which mainly take place during a short period in prenatal and postnatal development. These interactions are not completely understood, and hence primary prevention remains an elusive goal. We argue that primary-care physicians, paediatricians, and specialists lack knowledge of the role of atopy in early life in the development of persistent asthma in children. In this review, we discuss how early identification of children at high risk is feasible on the basis of available technology and important for potential benefits to the children. Identification of an asthmatic child's atopic status in early life has practical clinical and prognostic implications, and sets the basis for future preventative strategies.

Design and prediction of new acetylcholinesterase inhibitor via quantitative structure activity relationship of huprines derivatives.

PubMed

Zhang, Shuqun; Hou, Bo; Yang, Huaiyu; Zuo, Zhili

2016-05-01

Acetylcholinesterase (AChE) is an important enzyme in the pathogenesis of Alzheimer's disease (AD). Comparative quantitative structure-activity relationship (QSAR) analyses on some huprines inhibitors against AChE were carried out using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and hologram QSAR (HQSAR) methods. Three highly predictive QSAR models were constructed successfully based on the training set. The CoMFA, CoMSIA, and HQSAR models have values of r (2) = 0.988, q (2) = 0.757, ONC = 6; r (2) = 0.966, q (2) = 0.645, ONC = 5; and r (2) = 0.957, q (2) = 0.736, ONC = 6. The predictabilities were validated using an external test sets, and the predictive r (2) values obtained by the three models were 0.984, 0.973, and 0.783, respectively. The analysis was performed by combining the CoMFA and CoMSIA field distributions with the active sites of the AChE to further understand the vital interactions between huprines and the protease. On the basis of the QSAR study, 14 new potent molecules have been designed and six of them are predicted to be more active than the best active compound 24 described in the literature. The final QSAR models could be helpful in design and development of novel active AChE inhibitors.

Theoretical Prediction of Am(III)/Eu(III) Selectivity to Aid the Design of Actinide-Lanthanide Separation Agents

DOE PAGES

Bryantsev, Vyacheslav S.; Hay, Benjamin P.

2015-03-20

Selective extraction of minor actinides from lanthanides is a critical step in the reduction of radiotoxicity of spent nuclear fuels. However, the design of suitable ligands for separating chemically similar 4f- and 5f-block trivalent metal ions poses a significant challenge. Furthermore, first-principles calculations should play an important role in the design of new separation agents, but their ability to predict metal ion selectivity has not been systematically evaluated. We examine the ability of several density functional theory methods to predict selectivity of Am(III) and Eu(III) with oxygen, mixed oxygen–nitrogen, and sulfur donor ligands. The results establish a computational method capablemore » of predicting the correct order of selectivities obtained from liquid–liquid extraction and aqueous phase complexation studies. To allow reasonably accurate predictions, it was critical to employ sufficiently flexible basis sets and provide proper account of solvation effects. The approach is utilized to estimate the selectivity of novel amide-functionalized diazine and 1,2,3-triazole ligands.« less

Peak-flow frequency for tributaries of the Colorado River downstream of Austin, Texas

USGS Publications Warehouse

Asquith, William H.

1998-01-01

Peak-flow frequency for 38 stations with at least 8 years of data in natural (unregulated and nonurbanized) basins was estimated on the basis of annual peak-streamflow data through water year 1995. Peak-flow frequency represents the peak discharges for recurrence intervals of 2, 5, 10, 25, 50, 100, 250, and 500 years. The peak-flow frequency and drainage basin characteristics for the stations were used to develop two sets of regression equations to estimate peak-flow frequency for tributaries of the Colorado River in the study area. One set of equations was developed for contributing drainage areas less than 32 square miles, and another set was developed for contributing drainage areas greater than 32 square miles. A procedure is presented to estimate the peak discharge at sites where both sets of equations are considered applicable. Additionally, procedures are presented to compute the 50-, 67-, and 90-percent prediction interval for any estimation from the equations.

Polarized atomic orbitals for self-consistent field electronic structure calculations

NASA Astrophysics Data System (ADS)

Lee, Michael S.; Head-Gordon, Martin

1997-12-01

We present a new self-consistent field approach which, given a large "secondary" basis set of atomic orbitals, variationally optimizes molecular orbitals in terms of a small "primary" basis set of distorted atomic orbitals, which are simultaneously optimized. If the primary basis is taken as a minimal basis, the resulting functions are termed polarized atomic orbitals (PAO's) because they are valence (or core) atomic orbitals which have distorted or polarized in an optimal way for their molecular environment. The PAO's derive their flexibility from the fact that they are formed from atom-centered linear-combinations of the larger set of secondary atomic orbitals. The variational conditions satisfied by PAO's are defined, and an iterative method for performing a PAO-SCF calculation is introduced. We compare the PAO-SCF approach against full SCF calculations for the energies, dipoles, and molecular geometries of various molecules. The PAO's are potentially useful for studying large systems that are currently intractable with larger than minimal basis sets, as well as offering potential interpretative benefits relative to calculations in extended basis sets.

Structure alerts for carcinogenicity, and the Salmonella assay system: a novel insight through the chemical relational databases technology.

PubMed

Benigni, Romualdo; Bossa, Cecilia

2008-01-01

In the past decades, chemical carcinogenicity has been the object of mechanistic studies that have been translated into valuable experimental (e.g., the Salmonella assays system) and theoretical (e.g., compilations of structure alerts for chemical carcinogenicity) models. These findings remain the basis of the science and regulation of mutagens and carcinogens. Recent advances in the organization and treatment of large databases consisting of both biological and chemical information nowadays allows for a much easier and more refined view of data. This paper reviews recent analyses on the predictive performance of various lists of structure alerts, including a new compilation of alerts that combines previous work in an optimized form for computer implementation. The revised compilation is part of the Toxtree 1.50 software (freely available from the European Chemicals Bureau website). The use of structural alerts for the chemical biological profiling of a large database of Salmonella mutagenicity results is also reported. Together with being a repository of the science on the chemical biological interactions at the basis of chemical carcinogenicity, the SAs have a crucial role in practical applications for risk assessment, for: (a) description of sets of chemicals; (b) preliminary hazard characterization; (c) formation of categories for e.g., regulatory purposes; (d) generation of subsets of congeneric chemicals to be analyzed subsequently with QSAR methods; (e) priority setting. An important aspect of SAs as predictive toxicity tools is that they derive directly from mechanistic knowledge. The crucial role of mechanistic knowledge in the process of applying (Q)SAR considerations to risk assessment should be strongly emphasized. Mechanistic knowledge provides a ground for interaction and dialogue between model developers, toxicologists and regulators, and permits the integration of the (Q)SAR results into a wider regulatory framework, where different types of evidence and data concur or complement each other as a basis for making decisions and taking actions.

Longitudinal histories as predictors of future diagnoses of domestic abuse: modelling study

PubMed Central

Kohane, Isaac S; Mandl, Kenneth D

2009-01-01

Objective To determine whether longitudinal data in patients’ historical records, commonly available in electronic health record systems, can be used to predict a patient’s future risk of receiving a diagnosis of domestic abuse. Design Bayesian models, known as intelligent histories, used to predict a patient’s risk of receiving a future diagnosis of abuse, based on the patient’s diagnostic history. Retrospective evaluation of the model’s predictions using an independent testing set. Setting A state-wide claims database covering six years of inpatient admissions to hospital, admissions for observation, and encounters in emergency departments. Population All patients aged over 18 who had at least four years between their earliest and latest visits recorded in the database (561 216 patients). Main outcome measures Timeliness of detection, sensitivity, specificity, positive predictive values, and area under the ROC curve. Results 1.04% (5829) of the patients met the narrow case definition for abuse, while 3.44% (19 303) met the broader case definition for abuse. The model achieved sensitive, specific (area under the ROC curve of 0.88), and early (10-30 months in advance, on average) prediction of patients’ future risk of receiving a diagnosis of abuse. Analysis of model parameters showed important differences between sexes in the risks associated with certain diagnoses. Conclusions Commonly available longitudinal diagnostic data can be useful for predicting a patient’s future risk of receiving a diagnosis of abuse. This modelling approach could serve as the basis for an early warning system to help doctors identify high risk patients for further screening. PMID:19789406

Selecting an Informative/Discriminating Multivariate Response for Inverse Prediction

DOE PAGES

Thomas, Edward V.; Lewis, John R.; Anderson-Cook, Christine M.; ...

2017-11-21

nverse prediction is important in a wide variety of scientific and engineering contexts. One might use inverse prediction to predict fundamental properties/characteristics of an object using measurements obtained from it. This can be accomplished by “inverting” parameterized forward models that relate the measurements (responses) to the properties/characteristics of interest. Sometimes forward models are science based; but often, forward models are empirically based, using the results of experimentation. For empirically-based forward models, it is important that the experiments provide a sound basis to develop accurate forward models in terms of the properties/characteristics (factors). While nature dictates the causal relationship between factorsmore » and responses, experimenters can influence control of the type, accuracy, and precision of forward models that can be constructed via selection of factors, factor levels, and the set of trials that are performed. Whether the forward models are based on science, experiments or both, researchers can influence the ability to perform inverse prediction by selecting informative response variables. By using an errors-in-variables framework for inverse prediction, this paper shows via simple analysis and examples how the capability of a multivariate response (with respect to being informative and discriminating) can vary depending on how well the various responses complement one another over the range of the factor-space of interest. Insights derived from this analysis could be useful for selecting a set of response variables among candidates in cases where the number of response variables that can be acquired is limited by difficulty, expense, and/or availability of material.« less

Selecting an Informative/Discriminating Multivariate Response for Inverse Prediction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thomas, Edward V.; Lewis, John R.; Anderson-Cook, Christine M.

nverse prediction is important in a wide variety of scientific and engineering contexts. One might use inverse prediction to predict fundamental properties/characteristics of an object using measurements obtained from it. This can be accomplished by “inverting” parameterized forward models that relate the measurements (responses) to the properties/characteristics of interest. Sometimes forward models are science based; but often, forward models are empirically based, using the results of experimentation. For empirically-based forward models, it is important that the experiments provide a sound basis to develop accurate forward models in terms of the properties/characteristics (factors). While nature dictates the causal relationship between factorsmore » and responses, experimenters can influence control of the type, accuracy, and precision of forward models that can be constructed via selection of factors, factor levels, and the set of trials that are performed. Whether the forward models are based on science, experiments or both, researchers can influence the ability to perform inverse prediction by selecting informative response variables. By using an errors-in-variables framework for inverse prediction, this paper shows via simple analysis and examples how the capability of a multivariate response (with respect to being informative and discriminating) can vary depending on how well the various responses complement one another over the range of the factor-space of interest. Insights derived from this analysis could be useful for selecting a set of response variables among candidates in cases where the number of response variables that can be acquired is limited by difficulty, expense, and/or availability of material.« less

Genomic Bayesian functional regression models with interactions for predicting wheat grain yield using hyper-spectral image data.

PubMed

Montesinos-López, Abelardo; Montesinos-López, Osval A; Cuevas, Jaime; Mata-López, Walter A; Burgueño, Juan; Mondal, Sushismita; Huerta, Julio; Singh, Ravi; Autrique, Enrique; González-Pérez, Lorena; Crossa, José

2017-01-01

Modern agriculture uses hyperspectral cameras that provide hundreds of reflectance data at discrete narrow bands in many environments. These bands often cover the whole visible light spectrum and part of the infrared and ultraviolet light spectra. With the bands, vegetation indices are constructed for predicting agronomically important traits such as grain yield and biomass. However, since vegetation indices only use some wavelengths (referred to as bands), we propose using all bands simultaneously as predictor variables for the primary trait grain yield; results of several multi-environment maize (Aguate et al. in Crop Sci 57(5):1-8, 2017) and wheat (Montesinos-López et al. in Plant Methods 13(4):1-23, 2017) breeding trials indicated that using all bands produced better prediction accuracy than vegetation indices. However, until now, these prediction models have not accounted for the effects of genotype × environment (G × E) and band × environment (B × E) interactions incorporating genomic or pedigree information. In this study, we propose Bayesian functional regression models that take into account all available bands, genomic or pedigree information, the main effects of lines and environments, as well as G × E and B × E interaction effects. The data set used is comprised of 976 wheat lines evaluated for grain yield in three environments (Drought, Irrigated and Reduced Irrigation). The reflectance data were measured in 250 discrete narrow bands ranging from 392 to 851 nm (nm). The proposed Bayesian functional regression models were implemented using two types of basis: B-splines and Fourier. Results of the proposed Bayesian functional regression models, including all the wavelengths for predicting grain yield, were compared with results from conventional models with and without bands. We observed that the models with B × E interaction terms were the most accurate models, whereas the functional regression models (with B-splines and Fourier basis) and the conventional models performed similarly in terms of prediction accuracy. However, the functional regression models are more parsimonious and computationally more efficient because the number of beta coefficients to be estimated is 21 (number of basis), rather than estimating the 250 regression coefficients for all bands. In this study adding pedigree or genomic information did not increase prediction accuracy.

Choosing a model to predict hospital admission: an observational study of new variants of predictive models for case finding

PubMed Central

Billings, John; Georghiou, Theo; Blunt, Ian; Bardsley, Martin

2013-01-01

Objectives To test the performance of new variants of models to identify people at risk of an emergency hospital admission. We compared (1) the impact of using alternative data sources (hospital inpatient, A&E, outpatient and general practitioner (GP) electronic medical records) (2) the effects of local calibration on the performance of the models and (3) the choice of population denominators. Design Multivariate logistic regressions using person-level data adding each data set sequentially to test value of additional variables and denominators. Setting 5 Primary Care Trusts within England. Participants 1 836 099 people aged 18–95 registered with GPs on 31 July 2009. Main outcome measures Models to predict hospital admission and readmission were compared in terms of the positive predictive value and sensitivity for various risk strata and with the receiver operating curve C statistic. Results The addition of each data set showed moderate improvement in the number of patients identified with little or no loss of positive predictive value. However, even with inclusion of GP electronic medical record information, the algorithms identified only a small number of patients with no emergency hospital admissions in the previous 2 years. The model pooled across all sites performed almost as well as the models calibrated to local data from just one site. Using population denominators from GP registers led to better case finding. Conclusions These models provide a basis for wider application in the National Health Service. Each of the models examined produces reasonably robust performance and offers some predictive value. The addition of more complex data adds some value, but we were unable to conclude that pooled models performed less well than those in individual sites. Choices about model should be linked to the intervention design. Characteristics of patients identified by the algorithms provide useful information in the design/costing of intervention strategies to improve care coordination/outcomes for these patients. PMID:23980068

Promises of Machine Learning Approaches in Prediction of Absorption of Compounds.

PubMed

Kumar, Rajnish; Sharma, Anju; Siddiqui, Mohammed Haris; Tiwari, Rajesh Kumar

2018-01-01

The Machine Learning (ML) is one of the fastest developing techniques in the prediction and evaluation of important pharmacokinetic properties such as absorption, distribution, metabolism and excretion. The availability of a large number of robust validation techniques for prediction models devoted to pharmacokinetics has significantly enhanced the trust and authenticity in ML approaches. There is a series of prediction models generated and used for rapid screening of compounds on the basis of absorption in last one decade. Prediction of absorption of compounds using ML models has great potential across the pharmaceutical industry as a non-animal alternative to predict absorption. However, these prediction models still have to go far ahead to develop the confidence similar to conventional experimental methods for estimation of drug absorption. Some of the general concerns are selection of appropriate ML methods and validation techniques in addition to selecting relevant descriptors and authentic data sets for the generation of prediction models. The current review explores published models of ML for the prediction of absorption using physicochemical properties as descriptors and their important conclusions. In addition, some critical challenges in acceptance of ML models for absorption are also discussed. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Prediction of future uniform milk prices in Florida federal milk marketing order 6 from milk futures markets.

PubMed

De Vries, A; Feleke, S

2008-12-01

This study assessed the accuracy of 3 methods that predict the uniform milk price in Federal Milk Marketing Order 6 (Florida). Predictions were made for 1 to 12 mo into the future. Data were from January 2003 to May 2007. The CURRENT method assumed that future uniform milk prices were equal to the last announced uniform milk price. The F+BASIS and F+UTIL methods were based on the milk futures markets because the futures prices reflect the market's expectation of the class III and class IV cash prices that are announced monthly by USDA. The F+BASIS method added an exponentially weighted moving average of the difference between the class III cash price and the historical uniform milk price (also known as basis) to the class III futures price. The F+UTIL method used the class III and class IV futures prices, the most recently announced butter price, and historical utilizations to predict the skim milk prices, butterfat prices, and utilizations in all 4 classes. Predictions of future utilizations were made with a Holt-Winters smoothing method. Federal Milk Marketing Order 6 had high class I utilization (85 +/- 4.8%). Mean and standard deviation of the class III and class IV cash prices were $13.39 +/- 2.40/cwt (1 cwt = 45.36 kg) and $12.06 +/- 1.80/cwt, respectively. The actual uniform price in Tampa, Florida, was $16.62 +/- 2.16/cwt. The basis was $3.23 +/- 1.23/cwt. The F+BASIS and F+UTIL predictions were generally too low during the period considered because the class III cash prices were greater than the corresponding class III futures prices. For the 1- to 6-mo-ahead predictions, the root of the mean squared prediction errors from the F+BASIS method were $1.12, $1.20, $1.55, $1.91, $2.16, and $2.34/cwt, respectively. The root of the mean squared prediction errors ranged from $2.50 to $2.73/cwt for predictions up to 12 mo ahead. Results from the F+UTIL method were similar. The accuracies of the F+BASIS and F+UTIL methods for all 12 fore-cast horizons were not significantly different. Application of the modified Mariano-Diebold tests showed that no method included all the information contained in the other methods. In conclusion, both F+BASIS and F+UTIL methods tended to more accurately predict the future uniform milk prices than the CURRENT method, but prediction errors could be substantial even a few months into the future. The majority of the prediction error was caused by the inefficiency of the futures markets to predict the class III cash prices.

[Discriminant Analysis of Lavender Essential Oil by Attenuated Total Reflectance Infrared Spectroscopy].

PubMed

Tang, Jun; Wang, Qing; Tong, Hong; Liao, Xiang; Zhang, Zheng-fang

2016-03-01

This work aimed to use attenuated total reflectance Fourier transform infrared spectroscopy to identify the lavender essential oil by establishing a Lavender variety and quality analysis model. So, 96 samples were tested. For all samples, the raw spectra were pretreated as second derivative, and to determine the 1 750-900 cm(-1) wavelengths for pattern recognition analysis on the basis of the variance calculation. The results showed that principal component analysis (PCA) can basically discriminate lavender oil cultivar and the first three principal components mainly represent the ester, alcohol and terpenoid substances. When the orthogonal partial least-squares discriminant analysis (OPLS-DA) model was established, the 68 samples were used for the calibration set. Determination coefficients of OPLS-DA regression curve were 0.959 2, 0.976 4, and 0.958 8 respectively for three varieties of lavender essential oil. Three varieties of essential oil's the root mean square error of prediction (RMSEP) in validation set were 0.142 9, 0.127 3, and 0.124 9, respectively. The discriminant rate of calibration set and the prediction rate of validation set had reached 100%. The model has the very good recognition capability to detect the variety and quality of lavender essential oil. The result indicated that a model which provides a quick, intuitive and feasible method had been built to discriminate lavender oils.

Modeling and Prediction of Monthly Total Ozone Concentrations by Use of an Artificial Neural Network Based on Principal Component Analysis

NASA Astrophysics Data System (ADS)

Chattopadhyay, Surajit; Chattopadhyay, Goutami

2012-10-01

In the work discussed in this paper we considered total ozone time series over Kolkata (22°34'10.92″N, 88°22'10.92″E), an urban area in eastern India. Using cloud cover, average temperature, and rainfall as the predictors, we developed an artificial neural network, in the form of a multilayer perceptron with sigmoid non-linearity, for prediction of monthly total ozone concentrations from values of the predictors in previous months. We also estimated total ozone from values of the predictors in the same month. Before development of the neural network model we removed multicollinearity by means of principal component analysis. On the basis of the variables extracted by principal component analysis, we developed three artificial neural network models. By rigorous statistical assessment it was found that cloud cover and rainfall can act as good predictors for monthly total ozone when they are considered as the set of input variables for the neural network model constructed in the form of a multilayer perceptron. In general, the artificial neural network has good potential for predicting and estimating monthly total ozone on the basis of the meteorological predictors. It was further observed that during pre-monsoon and winter seasons, the proposed models perform better than during and after the monsoon.

A Thermodynamically-consistent FBA-based Approach to Biogeochemical Reaction Modeling

NASA Astrophysics Data System (ADS)

Shapiro, B.; Jin, Q.

2015-12-01

Microbial rates are critical to understanding biogeochemical processes in natural environments. Recently, flux balance analysis (FBA) has been applied to predict microbial rates in aquifers and other settings. FBA is a genome-scale constraint-based modeling approach that computes metabolic rates and other phenotypes of microorganisms. This approach requires a prior knowledge of substrate uptake rates, which is not available for most natural microbes. Here we propose to constrain substrate uptake rates on the basis of microbial kinetics. Specifically, we calculate rates of respiration (and fermentation) using a revised Monod equation; this equation accounts for both the kinetics and thermodynamics of microbial catabolism. Substrate uptake rates are then computed from the rates of respiration, and applied to FBA to predict rates of microbial growth. We implemented this method by linking two software tools, PHREEQC and COBRA Toolbox. We applied this method to acetotrophic methanogenesis by Methanosarcina barkeri, and compared the simulation results to previous laboratory observations. The new method constrains acetate uptake by accounting for the kinetics and thermodynamics of methanogenesis, and predicted well the observations of previous experiments. In comparison, traditional methods of dynamic-FBA constrain acetate uptake on the basis of enzyme kinetics, and failed to reproduce the experimental results. These results show that microbial rate laws may provide a better constraint than enzyme kinetics for applying FBA to biogeochemical reaction modeling.

In situ genetic association for serotiny, a fire-related trait, in Mediterranean maritime pine (Pinus pinaster).

PubMed

Budde, Katharina B; Heuertz, Myriam; Hernández-Serrano, Ana; Pausas, Juli G; Vendramin, Giovanni G; Verdú, Miguel; González-Martínez, Santiago C

2014-01-01

Wildfire is a major ecological driver of plant evolution. Understanding the genetic basis of plant adaptation to wildfire is crucial, because impending climate change will involve fire regime changes worldwide. We studied the molecular genetic basis of serotiny, a fire-related trait, in Mediterranean maritime pine using association genetics. A single nucleotide polymorphism (SNP) set was used to identify genotype : phenotype associations in situ in an unstructured natural population of maritime pine (eastern Iberian Peninsula) under a mixed-effects model framework. RR-BLUP was used to build predictive models for serotiny in this region. Model prediction power outside the focal region was tested using independent range-wide serotiny data. Seventeen SNPs were potentially associated with serotiny, explaining approximately 29% of the trait phenotypic variation in the eastern Iberian Peninsula. Similar prediction power was found for nearby geographical regions from the same maternal lineage, but not for other genetic lineages. Association genetics for ecologically relevant traits evaluated in situ is an attractive approach for forest trees provided that traits are under strong genetic control and populations are unstructured, with large phenotypic variability. This will help to extend the research focus to ecological keystone non-model species in their natural environments, where polymorphisms acquired their adaptive value. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

42 CFR 415.170 - Conditions for payment on a fee schedule basis for physician services in a teaching setting.

Code of Federal Regulations, 2010 CFR

2010-10-01

... physician services in a teaching setting. 415.170 Section 415.170 Public Health CENTERS FOR MEDICARE... BY PHYSICIANS IN PROVIDERS, SUPERVISING PHYSICIANS IN TEACHING SETTINGS, AND RESIDENTS IN CERTAIN SETTINGS Physician Services in Teaching Settings § 415.170 Conditions for payment on a fee schedule basis...

Third-order Douglas-Kroll Relativistic Coupled-Cluster Theory through Connected Single, Double, Triple, and Quadruple Substitutions: Applications to Diatomic and Triatomic Hydrides

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hirata, So; Yanai, Takeshi; De Jong, Wibe A.

Coupled-cluster methods including through and up to the connected single, double, triple, and quadruple substitutions (CCSD, CCSDT, and CCSDTQ) have been automatically derived and implemented for sequential and parallel executions for use in conjunction with a one-component third-order Douglas-Kroll (DK3) approximation for relativistic corrections. A combination of the converging electron-correlation methods, the accurate relativistic reference wave functions, and the use of systematic basis sets tailored to the relativistic approximation has been shown to predict the experimental singlet-triplet separations within 0.02 eV (0.5 kcal/mol) for five triatomic hydrides (CH2, NH2+, SiH2, PH2+, and AsH2+), the experimental bond lengths within 0.002 angstroms,more » rotational constants within 0.02 cm-1, vibration-rotation constants within 0.01 cm-1, centrifugal distortion constants within 2 %, harmonic vibration frequencies within 9 cm-1 (0.4 %), anharmonic vibrational constants within 2 cm-1, and dissociation energies within 0.03 eV (0.8 kcal/mol) for twenty diatomic hydrides (BH, CH, NH, OH, FH, AlH, SiH, PH, SH, ClH, GaH, GeH, AsH, SeH, BrH, InH, SnH, SbH, TeH, and IH) containing main-group elements across the second through fifth periods of the periodic table. In these calculations, spin-orbit effects on dissociation energies, which were assumed to be additive, were estimated from the measured spin-orbit coupling constants of atoms and diatomic molecules, and an electronic energy in the complete-basis-set, complete-electron-correlation limit has been extrapolated by the formula which was in turn based on the exponential-Gaussian extrapolation formula of the basis set dependence.« less

Development and validation of a casemix classification to predict costs of specialist palliative care provision across inpatient hospice, hospital and community settings in the UK: a study protocol

PubMed Central

Guo, Ping; Dzingina, Mendwas; Firth, Alice M; Davies, Joanna M; Douiri, Abdel; O’Brien, Suzanne M; Pinto, Cathryn; Pask, Sophie; Higginson, Irene J; Eagar, Kathy; Murtagh, Fliss E M

2018-01-01

Introduction Provision of palliative care is inequitable with wide variations across conditions and settings in the UK. Lack of a standard way to classify by case complexity is one of the principle obstacles to addressing this. We aim to develop and validate a casemix classification to support the prediction of costs of specialist palliative care provision. Methods and analysis Phase I: A cohort study to determine the variables and potential classes to be included in a casemix classification. Data are collected from clinicians in palliative care services across inpatient hospice, hospital and community settings on: patient demographics, potential complexity/casemix criteria and patient-level resource use. Cost predictors are derived using multivariate regression and then incorporated into a classification using classification and regression trees. Internal validation will be conducted by bootstrapping to quantify any optimism in the predictive performance (calibration and discrimination) of the developed classification. Phase II: A mixed-methods cohort study across settings for external validation of the classification developed in phase I. Patient and family caregiver data will be collected longitudinally on demographics, potential complexity/casemix criteria and patient-level resource use. This will be triangulated with data collected from clinicians on potential complexity/casemix criteria and patient-level resource use, and with qualitative interviews with patients and caregivers about care provision across difference settings. The classification will be refined on the basis of its performance in the validation data set. Ethics and dissemination The study has been approved by the National Health Service Health Research Authority Research Ethics Committee. The results are expected to be disseminated in 2018 through papers for publication in major palliative care journals; policy briefs for clinicians, commissioning leads and policy makers; and lay summaries for patients and public. Trial registration number ISRCTN90752212. PMID:29550781

Development and validation of a casemix classification to predict costs of specialist palliative care provision across inpatient hospice, hospital and community settings in the UK: a study protocol.

PubMed

Guo, Ping; Dzingina, Mendwas; Firth, Alice M; Davies, Joanna M; Douiri, Abdel; O'Brien, Suzanne M; Pinto, Cathryn; Pask, Sophie; Higginson, Irene J; Eagar, Kathy; Murtagh, Fliss E M

2018-03-17

Provision of palliative care is inequitable with wide variations across conditions and settings in the UK. Lack of a standard way to classify by case complexity is one of the principle obstacles to addressing this. We aim to develop and validate a casemix classification to support the prediction of costs of specialist palliative care provision. Phase I: A cohort study to determine the variables and potential classes to be included in a casemix classification. Data are collected from clinicians in palliative care services across inpatient hospice, hospital and community settings on: patient demographics, potential complexity/casemix criteria and patient-level resource use. Cost predictors are derived using multivariate regression and then incorporated into a classification using classification and regression trees. Internal validation will be conducted by bootstrapping to quantify any optimism in the predictive performance (calibration and discrimination) of the developed classification. Phase II: A mixed-methods cohort study across settings for external validation of the classification developed in phase I. Patient and family caregiver data will be collected longitudinally on demographics, potential complexity/casemix criteria and patient-level resource use. This will be triangulated with data collected from clinicians on potential complexity/casemix criteria and patient-level resource use, and with qualitative interviews with patients and caregivers about care provision across difference settings. The classification will be refined on the basis of its performance in the validation data set. The study has been approved by the National Health Service Health Research Authority Research Ethics Committee. The results are expected to be disseminated in 2018 through papers for publication in major palliative care journals; policy briefs for clinicians, commissioning leads and policy makers; and lay summaries for patients and public. ISRCTN90752212. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Structures of cage, prism, and book isomers of water hexamer from broadband rotational spectroscopy.

PubMed

Pérez, Cristóbal; Muckle, Matt T; Zaleski, Daniel P; Seifert, Nathan A; Temelso, Berhane; Shields, George C; Kisiel, Zbigniew; Pate, Brooks H

2012-05-18

Theory predicts the water hexamer to be the smallest water cluster with a three-dimensional hydrogen-bonding network as its minimum energy structure. There are several possible low-energy isomers, and calculations with different methods and basis sets assign them different relative stabilities. Previous experimental work has provided evidence for the cage, book, and cyclic isomers, but no experiment has identified multiple coexisting structures. Here, we report that broadband rotational spectroscopy in a pulsed supersonic expansion unambiguously identifies all three isomers; we determined their oxygen framework structures by means of oxygen-18-substituted water (H(2)(18)O). Relative isomer populations at different expansion conditions establish that the cage isomer is the minimum energy structure. Rotational spectra consistent with predicted heptamer and nonamer structures have also been identified.

Discovery of the Electronic Spectra of Hps and Dps

NASA Astrophysics Data System (ADS)

Grimminger, Robert A.; Wei, Jie; Ellis, Blaine; Clouthier, Dennis J.; Wang, Zhong; Sears, Trevor

2009-06-01

The hitherto unknown electronic spectrum of the closed shell transient molecule HPS has been observed in the 685 - 846 nm region by laser-induced fluorescence and single vibronic level emission techniques. HPS (and DPS) were produced in a pulsed electric discharge jet using a precursor mixture of 3% PH_3 and 1% H_2S (or PD_3 and D_2S) in high pressure argon. The weak set of observed bands are assigned to the à ^1A^''-X˜ ^1A^' electronic transition on the basis of chemical evidence, isotope shifts and the correspondence of the vibrational frequencies, excitation energy, and band contours with predictions based on our own high level ab initio calculations. Theory predicts that the HPS bond angle decreases on electronic excitation, contrary to expectations based on Walsh diagrams.

Identification of tissue-specific targeting peptide

NASA Astrophysics Data System (ADS)

Jung, Eunkyoung; Lee, Nam Kyung; Kang, Sang-Kee; Choi, Seung-Hoon; Kim, Daejin; Park, Kisoo; Choi, Kihang; Choi, Yun-Jaie; Jung, Dong Hyun

2012-11-01

Using phage display technique, we identified tissue-targeting peptide sets that recognize specific tissues (bone-marrow dendritic cell, kidney, liver, lung, spleen and visceral adipose tissue). In order to rapidly evaluate tissue-specific targeting peptides, we performed machine learning studies for predicting the tissue-specific targeting activity of peptides on the basis of peptide sequence information using four machine learning models and isolated the groups of peptides capable of mediating selective targeting to specific tissues. As a representative liver-specific targeting sequence, the peptide "DKNLQLH" was selected by the sequence similarity analysis. This peptide has a high degree of homology with protein ligands which can interact with corresponding membrane counterparts. We anticipate that our models will be applicable to the prediction of tissue-specific targeting peptides which can recognize the endothelial markers of target tissues.

Vibrational analysis, NBO analysis, NMR, UV-VIS, hyperpolarizability analysis of Trimethadione by density functional theory

NASA Astrophysics Data System (ADS)

Vijayachamundeeswari, S. P.; Yagna Narayana, B.; Jone Pradeepa, S.; Sundaraganesan, N.

2015-11-01

Trimethadione (TMD) is an anticonvulsant drug widely used against absences seizures. We have characterised the TMD by various spectra including UV-VIS, IR, Raman, GC-MS and NMR. In this work, we made use of Density Functional Theory (DFT) B3LYP method with 6-31G (d, p) basis set, to calculate the molecular structure of TMD, and predicted its infrared, Raman and ultraviolet spectra for the first time. FT-IR and FT-Raman spectra were recorded in the region 4000-400 cm-1 and 3500-50 cm-1, respectively. The vibrational frequencies were calculated and scaled values were compared with the experimental FT-IR and FT-Raman spectra. The observed and calculated frequencies are found to be in good agreement. The complete assignments were performed on the basis of the total energy distribution (TED) of the vibrational modes. The optimized geometry parameters were calculated. NMR chemical shifts of the molecule were calculated using the gauge independent atomic orbital (GIAO) method. The predicted first hyperpolarizibility also shows that the molecule might have convincingly good nonlinear optical (NLO) activities. The calculated HOMO-LUMO energy gap discloses that charge transfer occurs within the molecule.

Projected Hybrid Orbitals: A General QM/MM Method

PubMed Central

2015-01-01

A projected hybrid orbital (PHO) method was described to model the covalent boundary in a hybrid quantum mechanical and molecular mechanical (QM/MM) system. The PHO approach can be used in ab initio wave function theory and in density functional theory with any basis set without introducing system-dependent parameters. In this method, a secondary basis set on the boundary atom is introduced to formulate a set of hybrid atomic orbtials. The primary basis set on the boundary atom used for the QM subsystem is projected onto the secondary basis to yield a representation that provides a good approximation to the electron-withdrawing power of the primary basis set to balance electronic interactions between QM and MM subsystems. The PHO method has been tested on a range of molecules and properties. Comparison with results obtained from QM calculations on the entire system shows that the present PHO method is a robust and balanced QM/MM scheme that preserves the structural and electronic properties of the QM region. PMID:25317748

Characterization Approaches to Place Invariant Sites on SI-Traceable Scales

NASA Technical Reports Server (NTRS)

Thome, Kurtis

2012-01-01

The effort to understand the Earth's climate system requires a complete integration of remote sensing imager data across time and multiple countries. Such an integration necessarily requires ensuring inter-consistency between multiple sensors to create the data sets needed to understand the climate system. Past efforts at inter-consistency have forced agreement between two sensors using sources that are viewed by both sensors at nearly the same time, and thus tend to be near polar regions over snow and ice. The current work describes a method that would provide an absolute radiometric calibration of a sensor rather than an inter-consistency of a sensor relative to another. The approach also relies on defensible error budgets that eventually provides a cross comparison of sensors without systematic errors. The basis of the technique is a model-based, SI-traceable prediction of at-sensor radiance over selected sites. The predicted radiance would be valid for arbitrary view and illumination angles and for any date of interest that is dominated by clear-sky conditions. The effort effectively works to characterize the sites as sources with known top-of-atmosphere radiance allowing accurate intercomparison of sensor data that without the need for coincident views. Data from the Advanced Spaceborne Thermal Emission and Reflection and Radiometer (ASTER), Enhanced Thematic Mapper Plus (ETM+), and Moderate Resolution Imaging Spectroradiometer (MODIS) are used to demonstrate the difficulties of cross calibration as applied to current sensors. Special attention is given to the differences caused in the cross-comparison of sensors in radiance space as opposed to reflectance space. The radiance comparisons lead to significant differences created by the specific solar model used for each sensor. The paper also proposes methods to mitigate the largest error sources in future systems. The results from these historical intercomparisons provide the basis for a set of recommendations to ensure future SI-traceable cross calibration using future missions such as CLARREO and TRUTHS. The paper describes a proposed approach that relies on model-based, SI-traceable predictions of at-sensor radiance over selected sites. The predicted radiance would be valid for arbitrary view and illumination angles and for any date of interest that is dominated by clear-sky conditions. The basis of the method is highly accurate measurements of at-sensor radiance of sufficient quality to understand the spectral and BRDF characteristics of the site and sufficient historical data to develop an understanding of temporal effects from changing surface and atmospheric conditions.

A novel Gaussian-Sinc mixed basis set for electronic structure calculations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jerke, Jonathan L.; Lee, Young; Tymczak, C. J.

2015-08-14

A Gaussian-Sinc basis set methodology is presented for the calculation of the electronic structure of atoms and molecules at the Hartree–Fock level of theory. This methodology has several advantages over previous methods. The all-electron electronic structure in a Gaussian-Sinc mixed basis spans both the “localized” and “delocalized” regions. A basis set for each region is combined to make a new basis methodology—a lattice of orthonormal sinc functions is used to represent the “delocalized” regions and the atom-centered Gaussian functions are used to represent the “localized” regions to any desired accuracy. For this mixed basis, all the Coulomb integrals are definablemore » and can be computed in a dimensional separated methodology. Additionally, the Sinc basis is translationally invariant, which allows for the Coulomb singularity to be placed anywhere including on lattice sites. Finally, boundary conditions are always satisfied with this basis. To demonstrate the utility of this method, we calculated the ground state Hartree–Fock energies for atoms up to neon, the diatomic systems H{sub 2}, O{sub 2}, and N{sub 2}, and the multi-atom system benzene. Together, it is shown that the Gaussian-Sinc mixed basis set is a flexible and accurate method for solving the electronic structure of atomic and molecular species.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hill, J. Grant, E-mail: grant.hill@sheffield.ac.uk, E-mail: kipeters@wsu.edu; Peterson, Kirk A., E-mail: grant.hill@sheffield.ac.uk, E-mail: kipeters@wsu.edu

New correlation consistent basis sets, cc-pVnZ-PP-F12 (n = D, T, Q), for all the post-d main group elements Ga–Rn have been optimized for use in explicitly correlated F12 calculations. The new sets, which include not only orbital basis sets but also the matching auxiliary sets required for density fitting both conventional and F12 integrals, are designed for correlation of valence sp, as well as the outer-core d electrons. The basis sets are constructed for use with the previously published small-core relativistic pseudopotentials of the Stuttgart-Cologne variety. Benchmark explicitly correlated coupled-cluster singles and doubles with perturbative triples [CCSD(T)-F12b] calculations of themore » spectroscopic properties of numerous diatomic molecules involving 4p, 5p, and 6p elements have been carried out and compared to the analogous conventional CCSD(T) results. In general the F12 results obtained with a n-zeta F12 basis set were comparable to conventional aug-cc-pVxZ-PP or aug-cc-pwCVxZ-PP basis set calculations obtained with x = n + 1 or even x = n + 2. The new sets used in CCSD(T)-F12b calculations are particularly efficient at accurately recovering the large correlation effects of the outer-core d electrons.« less

Comparison of fMRI analysis methods for heterogeneous BOLD responses in block design studies

PubMed Central

Bernal-Casas, David; Fang, Zhongnan; Lee, Jin Hyung

2017-01-01

A large number of fMRI studies have shown that the temporal dynamics of evoked BOLD responses can be highly heterogeneous. Failing to model heterogeneous responses in statistical analysis can lead to significant errors in signal detection and characterization and alter the neurobiological interpretation. However, to date it is not clear that, out of a large number of options, which methods are robust against variability in the temporal dynamics of BOLD responses in block-design studies. Here, we used rodent optogenetic fMRI data with heterogeneous BOLD responses and simulations guided by experimental data as a means to investigate different analysis methods’ performance against heterogeneous BOLD responses. Evaluations are carried out within the general linear model (GLM) framework and consist of standard basis sets as well as independent component analysis (ICA). Analyses show that, in the presence of heterogeneous BOLD responses, conventionally used GLM with a canonical basis set leads to considerable errors in the detection and characterization of BOLD responses. Our results suggest that the 3rd and 4th order gamma basis sets, the 7th to 9th order finite impulse response (FIR) basis sets, the 5th to 9th order B-spline basis sets, and the 2nd to 5th order Fourier basis sets are optimal for good balance between detection and characterization, while the 1st order Fourier basis set (coherence analysis) used in our earlier studies show good detection capability. ICA has mostly good detection and characterization capabilities, but detects a large volume of spurious activation with the control fMRI data. PMID:27993672

Uncertainties in scaling factors for ab initio vibrational zero-point energies

NASA Astrophysics Data System (ADS)

Irikura, Karl K.; Johnson, Russell D.; Kacker, Raghu N.; Kessel, Rüdiger

2009-03-01

Vibrational zero-point energies (ZPEs) determined from ab initio calculations are often scaled by empirical factors. An empirical scaling factor partially compensates for the effects arising from vibrational anharmonicity and incomplete treatment of electron correlation. These effects are not random but are systematic. We report scaling factors for 32 combinations of theory and basis set, intended for predicting ZPEs from computed harmonic frequencies. An empirical scaling factor carries uncertainty. We quantify and report, for the first time, the uncertainties associated with scaling factors for ZPE. The uncertainties are larger than generally acknowledged; the scaling factors have only two significant digits. For example, the scaling factor for B3LYP/6-31G(d) is 0.9757±0.0224 (standard uncertainty). The uncertainties in the scaling factors lead to corresponding uncertainties in predicted ZPEs. The proposed method for quantifying the uncertainties associated with scaling factors is based upon the Guide to the Expression of Uncertainty in Measurement, published by the International Organization for Standardization. We also present a new reference set of 60 diatomic and 15 polyatomic "experimental" ZPEs that includes estimated uncertainties.

Cocrystals to facilitate delivery of poorly soluble compounds beyond-rule-of-5.

PubMed

Kuminek, Gislaine; Cao, Fengjuan; Bahia de Oliveira da Rocha, Alanny; Gonçalves Cardoso, Simone; Rodríguez-Hornedo, Naír

2016-06-01

Besides enhancing aqueous solubilities, cocrystals have the ability to fine-tune solubility advantage over drug, supersaturation index, and bioavailability. This review presents important facts about cocrystals that set them apart from other solid-state forms of drugs, and a quantitative set of rules for the selection of additives and solution/formulation conditions that predict cocrystal solubility, supersaturation index, and transition points. Cocrystal eutectic constants are shown to be the most important cocrystal property that can be measured once a cocrystal is discovered, and simple relationships are presented that allow for prediction of cocrystal behavior as a function of pH and drug solubilizing agents. Cocrystal eutectic constant is a stability or supersatuation index that: (a) reflects how close or far from equilibrium a cocrystal is, (b) establishes transition points, and (c) provides a quantitative scale of cocrystal true solubility changes over drug. The benefit of this strategy is that a single measurement, that requires little material and time, provides a principled basis to tailor cocrystal supersaturation index by the rational selection of cocrystal formulation, dissolution, and processing conditions. Copyright © 2016 Elsevier B.V. All rights reserved.

Comment on "The Predicted Size of Cycle 23 Based on the Inferred three-cycle Quasiperiodicity of the Planetary Index Ap"

NASA Technical Reports Server (NTRS)

Wilson, Robert M.; Hathaway, David H.

1999-01-01

Recently, Ahluwalia reviewed the solar and geomagnetic data for the last 6 decades and remarked that these data "indicate the existence of a three-solar-activity-cycle quasiperiodicity in them." Furthermore, on the basis of this inferred quasiperiodicity, he asserted that cycle 23 represents the initial cycle in a new three-cycle string, implying that it "will be more modest (a la cycle 17) with an annual mean sunspot number count of 119.3 +/- 30 at the maximum", a prediction that is considerably below the consensus prediction of 160 +/- 30 by Joselin et al. and of similar predictions by others based on a variety of predictive techniques. Several major sticking points of Ahluwalia's presentation, however, must be readdressed, and these issues form the basis of this comment. First, Ahluwalia appears to have based his analysis on a data set of Ap index values that is erroneous. For example, he depicts for the interval of 1932-1997 the variation of the Ap index in terms of annual averages, contrasting them against annual averages of sunspot number (SSN), and he lists for cycles 17-23 the minimum and maximum value of each, as well as the years in which they occur and a quantity which he calls "Amplitude" (defined as the numeric difference between the maximum and minimum values). In particular, he identifies the minimum Ap index (i.e., the minimum value of the Ap index in the vicinity of sunspot cycle minimum, which usually occurs in the year following sunspot minimum and which will be called hereafter, simply, Ap min) and the year in which it occur for cycles 17 - 23 respectively.

Blood glucose level prediction based on support vector regression using mobile platforms.

PubMed

Reymann, Maximilian P; Dorschky, Eva; Groh, Benjamin H; Martindale, Christine; Blank, Peter; Eskofier, Bjoern M

2016-08-01

The correct treatment of diabetes is vital to a patient's health: Staying within defined blood glucose levels prevents dangerous short- and long-term effects on the body. Mobile devices informing patients about their future blood glucose levels could enable them to take counter-measures to prevent hypo or hyper periods. Previous work addressed this challenge by predicting the blood glucose levels using regression models. However, these approaches required a physiological model, representing the human body's response to insulin and glucose intake, or are not directly applicable to mobile platforms (smart phones, tablets). In this paper, we propose an algorithm for mobile platforms to predict blood glucose levels without the need for a physiological model. Using an online software simulator program, we trained a Support Vector Regression (SVR) model and exported the parameter settings to our mobile platform. The prediction accuracy of our mobile platform was evaluated with pre-recorded data of a type 1 diabetes patient. The blood glucose level was predicted with an error of 19 % compared to the true value. Considering the permitted error of commercially used devices of 15 %, our algorithm is the basis for further development of mobile prediction algorithms.

Structure and spectral features of H+(H2O)7: Eigen versus Zundel forms.

PubMed

Shin, Ilgyou; Park, Mina; Min, Seung Kyu; Lee, Eun Cheol; Suh, Seung Bum; Kim, Kwang S

2006-12-21

The two dimensional (2D) to three dimensional (3D) transition for the protonated water cluster has been controversial, in particular, for H(+)(H(2)O)(7). For H(+)(H(2)O)(7) the 3D structure is predicted to be lower in energy than the 2D structure at most levels of theory without zero-point energy (ZPE) correction. On the other hand, with ZPE correction it is predicted to be either 2D or 3D depending on the calculational levels. Although the ZPE correction favors the 3D structure at the level of coupled cluster theory with singles, doubles, and perturbative triples excitations [CCSD(T)] using the aug-cc-pVDZ basis set, the result based on the anharmonic zero-point vibrational energy correction favors the 2D structure. Therefore, the authors investigated the energies based on the complete basis set limit scheme (which we devised in an unbiased way) at the resolution of the identity approximation Moller-Plesset second order perturbation theory and CCSD(T) levels, and found that the 2D structure has the lowest energy for H(+)(H(2)O)(7) [though nearly isoenergetic to the 3D structure for D(+)(D(2)O)(7)]. This structure has the Zundel-type configuration, but it shows the quantum probabilistic distribution including some of the Eigen-type configuration. The vibrational spectra of MP2/aug-cc-pVDZ calculations and Car-Parrinello molecular dynamics simulations, taking into account the thermal and dynamic effects, show that the 2D Zundel-type form is in good agreement with experiments.

Structure and spectral features of H+(H2O)7: Eigen versus Zundel forms

NASA Astrophysics Data System (ADS)

Shin, Ilgyou; Park, Mina; Min, Seung Kyu; Lee, Eun Cheol; Suh, Seung Bum; Kim, Kwang S.

2006-12-01

The two dimensional (2D) to three dimensional (3D) transition for the protonated water cluster has been controversial, in particular, for H+(H2O)7. For H+(H2O)7 the 3D structure is predicted to be lower in energy than the 2D structure at most levels of theory without zero-point energy (ZPE) correction. On the other hand, with ZPE correction it is predicted to be either 2D or 3D depending on the calculational levels. Although the ZPE correction favors the 3D structure at the level of coupled cluster theory with singles, doubles, and perturbative triples excitations [CCSD(T)] using the aug-cc-pVDZ basis set, the result based on the anharmonic zero-point vibrational energy correction favors the 2D structure. Therefore, the authors investigated the energies based on the complete basis set limit scheme (which we devised in an unbiased way) at the resolution of the identity approximation Møller-Plesset second order perturbation theory and CCSD(T) levels, and found that the 2D structure has the lowest energy for H+(H2O)7 [though nearly isoenergetic to the 3D structure for D+(D2O)7]. This structure has the Zundel-type configuration, but it shows the quantum probabilistic distribution including some of the Eigen-type configuration. The vibrational spectra of MP2/aug-cc-pVDZ calculations and Car-Parrinello molecular dynamics simulations, taking into account the thermal and dynamic effects, show that the 2D Zundel-type form is in good agreement with experiments.

Data Mining in the U.S. National Toxicology Program (NTP) Database Reveals a Potential Bias Regarding Liver Tumors in Rodents Irrespective of the Test Agent

PubMed Central

Ring, Matthias; Eskofier, Bjoern M.

2015-01-01

Long-term studies in rodents are the benchmark method to assess carcinogenicity of single substances, mixtures, and multi-compounds. In such a study, mice and rats are exposed to a test agent at different dose levels for a period of two years and the incidence of neoplastic lesions is observed. However, this two-year study is also expensive, time-consuming, and burdensome to the experimental animals. Consequently, various alternatives have been proposed in the literature to assess carcinogenicity on basis of short-term studies. In this paper, we investigated if effects on the rodents’ liver weight in short-term studies can be exploited to predict the incidence of liver tumors in long-term studies. A set of 138 paired short- and long-term studies was compiled from the database of the U.S. National Toxicology Program (NTP), more precisely, from (long-term) two-year carcinogenicity studies and their preceding (short-term) dose finding studies. In this set, data mining methods revealed patterns that can predict the incidence of liver tumors with accuracies of over 80%. However, the results simultaneously indicated a potential bias regarding liver tumors in two-year NTP studies. The incidence of liver tumors does not only depend on the test agent but also on other confounding factors in the study design, e.g., species, sex, type of substance. We recommend considering this bias if the hazard or risk of a test agent is assessed on basis of a NTP carcinogenicity study. PMID:25658102

Structure and stability of the N-hydroxyurea dimer: Post-Hartree-Fock quantum mechanical study

NASA Astrophysics Data System (ADS)

Jabalameli, Ali; Venkatraman, Ramaiyer; Nowek, Andrzej; Sullivan, Richard H.

2000-10-01

The potential energy surface (PES) search of the N-hydroxyurea dimer was searched with second-order Møller-Plesset perturbation theory (MP2) and the 6-31G(d,p) basis set. Eight local minimum energy structures have been found. Four of them have relatively strong (ΔE˜-10 to -13 kcal/mol) intermolecular interactions and the others are moderately strongly interacting species (ΔE˜-3 to -7 kcal/mol). Final estimation of interaction energies was performed using the larger 6-311G(df,pd) and 6-311G(2df,2pd) basis sets. The predicted interaction energies are ΔE=-14.26 kcal/mol and -3.43 kcal/mol for the strongest and the weakest interacting forms of the studied complex, respectively, at the MP2/6-311G(2df,2pd)//MP2/6-31G(d,p) level of theory. The self-consistent field (SCF) interaction energy decomposition indicates the important influence of the deformation term magnitude on ΔE(SCF). The calculated electron correlation contribution to ΔE(MP2) depends on the geometry of the system and varies from -0.5 to -5 kcal/mol. The estimated influence of water on the stability (free energy of hydration) of N-hydroxyurea dimers using the self-consistent isodensity polarized continuum (SCI-PCM) model of solvation varies from ˜-11 kcal/mol to ˜-21 kcal/mol. The forms predicted to be more strongly interacting species in gas phase are less influenced by hydration than the more weakly interacting ones.

Prediction of pKa Values for Neutral and Basic Drugs based on Hybrid Artificial Intelligence Methods.

PubMed

Li, Mengshan; Zhang, Huaijing; Chen, Bingsheng; Wu, Yan; Guan, Lixin

2018-03-05

The pKa value of drugs is an important parameter in drug design and pharmacology. In this paper, an improved particle swarm optimization (PSO) algorithm was proposed based on the population entropy diversity. In the improved algorithm, when the population entropy was higher than the set maximum threshold, the convergence strategy was adopted; when the population entropy was lower than the set minimum threshold the divergence strategy was adopted; when the population entropy was between the maximum and minimum threshold, the self-adaptive adjustment strategy was maintained. The improved PSO algorithm was applied in the training of radial basis function artificial neural network (RBF ANN) model and the selection of molecular descriptors. A quantitative structure-activity relationship model based on RBF ANN trained by the improved PSO algorithm was proposed to predict the pKa values of 74 kinds of neutral and basic drugs and then validated by another database containing 20 molecules. The validation results showed that the model had a good prediction performance. The absolute average relative error, root mean square error, and squared correlation coefficient were 0.3105, 0.0411, and 0.9685, respectively. The model can be used as a reference for exploring other quantitative structure-activity relationships.

The vibrational spectrum of H2O3: An ab initio investigation

NASA Technical Reports Server (NTRS)

Jackels, Charles F.

1991-01-01

Theoretically determined frequencies and absorption intensities are reported for the vibrational spectrum of the covalent HOOOH and hydrogen bonded HO---HOO intermediates that may form in the reaction of the hydroxyl and hydroperoxyl radicals. Basis sets of DZP quality, augmented by diffuse and second sets of polarization functions have been used with CASSCF wave functions. The calculated harmonic vibrational frequencies of HOOOH have been corrected with empirical factors and presented in the form of a 'stick' spectrum. The oxygen backbone vibrations, predicted to occur at 519, 760, and 870 cm(exp -1), are well separated from most interferences, and may be the most useful for the species' identification. In the case of the hydrogen bonded isomer, emphasis has been placed upon prediction of the shifts in the intramolecular vibrational frequencies that take place upon formation of the complex. In particular, the HO stretch and HOO bend of HO2 are predicted to have shifts of -59 and 53 cm(exp -1), respectively, which should facilitate their identification. It is also noted that the antisymmetric stretching frequency of the oxygen backbone in HOOOH exhibits a strong sensitivity to the degree of electron correlation, such as has been previously observed for the same mode in ozone.

Neuroanatomical basis of paroxysmal sympathetic hyperactivity: A diffusion tensor imaging analysis

PubMed Central

Hinson, Holly E.; Puybasset, Louis; Weiss, Nicolas; Perlbarg, Vincent; Benali, Habib; Galanaud, Damien; Lasarev, Mike; Stevens, Robert D.

2015-01-01

Primary objective Paroxysmal sympathetic hyperactivity (PSH) is observed in a sub-set of patients with moderate-to-severe traumatic brain injury (TBI). The neuroanatomical basis of PSH is poorly understood. It is hypothesized that PSH is linked to changes in connectivity within the central autonomic network. Research design Retrospective analysis in a sub-set of patients from a multi-centre, prospective cohort study Methods and procedures Adult patients who were <3 weeks after severe TBI were enrolled and screened for PSH using a standard definition. Patients underwent multimodal MRI, which included quantitative diffusion tensor imaging. Main outcomes and results Principal component analysis (PCA) was used to resolve the set of tracts into components. Ability to predict PSH was evaluated via area under the receiver operating characteristic (AUROC) and tree-based classification analyses. Among 102 enrolled patients, 16 met criteria for PSH. The first principle component was significantly associated (p = 0.024, AUROC = 0.867) with PSH status even after controlling for age and admission GCS. In a classification tree analysis, age, GCS and decreased FA in the splenium of the corpus callosum and in the right posterior limb of the internal capsule discriminated PSH vs no PSH with an AUROC of 0.933. Conclusions Disconnection involving the posterior corpus callosum and of the posterior limb of the internal capsule may play a role in the pathogenesis or expression of PSH. PMID:25565392

Computational studies of molecular charge transfer complexes of heterocyclic 4-methylepyridine-2-azomethine-p-benzene derivatives with picric acid and m-dinitrobenzene.

PubMed

Al-Harbi, L M; El-Mossalamy, E H; Obaid, A Y; Al-Jedaani, A H

2014-01-01

Charge transfer complexes of substituted aryl Schiff bases as donors with picric acid and m-dinitrobenzene as acceptors were investigated by using computational analysis calculated by Configuration Interaction Singles Hartree-Fock (CIS-HF) at standard 6-31G∗ basis set and Time-Dependent Density-Functional Theory (TD-DFT) levels of theory at standard 6-31G∗∗ basis set, infrared spectra, visible and nuclear magnetic resonance spectra are investigated. The optimized geometries and vibrational frequencies were evaluated. The energy and oscillator strength were calculated by Configuration Interaction Singles Hartree-Fock method (CIS-HF) and the Time-Dependent Density-Functional Theory (TD-DFT) results. Electronic properties, such as HOMO and LUMO energies and band gaps of CTCs set, were studied by the Time-Dependent density functional theory with Becke-Lee-Young-Parr (B3LYP) composite exchange correlation functional and by Configuration Interaction Singles Hartree-Fock method (CIS-HF). The ionization potential Ip and electron affinity EA were calculated by PM3, HF and DFT methods. The columbic force was calculated theoretically by using (CIS-HF and TD-DFT) methods. This study confirms that the theoretical calculation of vibrational frequencies for (aryl Schiff bases--(m-dinitrobenzene and picric acid)) complexes are quite useful for the vibrational assignment and for predicting new vibrational frequencies. Copyright © 2013 Elsevier B.V. All rights reserved.

Conventional and Explicitly Correlated ab Initio Benchmark Study on Water Clusters: Revision of the BEGDB and WATER27 Data Sets.

PubMed

Manna, Debashree; Kesharwani, Manoj K; Sylvetsky, Nitai; Martin, Jan M L

2017-07-11

Benchmark ab initio energies for BEGDB and WATER27 data sets have been re-examined at the MP2 and CCSD(T) levels with both conventional and explicitly correlated (F12) approaches. The basis set convergence of both conventional and explicitly correlated methods has been investigated in detail, both with and without counterpoise corrections. For the MP2 and CCSD-MP2 contributions, rapid basis set convergence observed with explicitly correlated methods is compared to conventional methods. However, conventional, orbital-based calculations are preferred for the calculation of the (T) term, since it does not benefit from F12. CCSD(F12*) converges somewhat faster with the basis set than CCSD-F12b for the CCSD-MP2 term. The performance of various DFT methods is also evaluated for the BEGDB data set, and results show that Head-Gordon's ωB97X-V and ωB97M-V functionals outperform all other DFT functionals. Counterpoise-corrected DSD-PBEP86 and raw DSD-PBEPBE-NL also perform well and are close to MP2 results. In the WATER27 data set, the anionic (deprotonated) water clusters exhibit unacceptably slow basis set convergence with the regular cc-pVnZ-F12 basis sets, which have only diffuse s and p functions. To overcome this, we have constructed modified basis sets, denoted aug-cc-pVnZ-F12 or aVnZ-F12, which have been augmented with diffuse functions on the higher angular momenta. The calculated final dissociation energies of BEGDB and WATER27 data sets are available in the Supporting Information. Our best calculated dissociation energies can be reproduced through n-body expansion, provided one pushes to the basis set and electron correlation limit for the two-body term; for the three-body term, post-MP2 contributions (particularly CCSD-MP2) are important for capturing the three-body dispersion effects. Terms beyond four-body can be adequately captured at the MP2-F12 level.

Intramolecular BSSE and dispersion affect the structure of a dipeptide conformer

NASA Astrophysics Data System (ADS)

Hameed, Rabia; Khan, Afsar; van Mourik, Tanja

2018-05-01

B3LYP and MP2 calculations with the commonly-used 6-31+G(d) basis set predict qualitatively different structures for the Tyr-Gly conformer book1, which is the most stable conformer identified in a previous study. The structures differ mainly in the ψtyr Ramachandran angle (138° in the B3LYP structure and 120° in the MP2 structure). The causes for the discrepant structures are attributed to missing dispersion in the B3LYP calculations and large intramolecular BSSE in the MP2 calculations. The correct ψtyr value is estimated to be 130°. The MP2/6-31+G(d) profile identified an additional conformer, not present on the B3LYP surface, with a ψtyr value of 96° and a more folded structure. This minimum is, however, likely an artefact of large intramolecular BSSE values. We recommend the use of basis sets of at least quadruple-zeta quality in density functional theory (DFT), DFTaugmented with an empirical dispersion term (DFT-D) and second-order Møller-Plesset perturbation theory (MP2 ) calculations in cases where intramolecular BSSE is expected to be large.

Molecular structure, vibrational spectra, NBO analysis and molecular packing prediction of 3-nitroacetanilide by ab initio HF and density functional theory.

PubMed

Li, Xiao-Hong; Li, Tong-Wei; Ju, Wei-Wei; Yong, Yong-Liang; Zhang, Xian-Zhou

2014-01-24

Quantum chemical calculations of geometries and vibrational wavenumbers of 3-nitroacetanilide (C8H8N2O3) in the ground state were carried out by using ab initio HF and density functional theory (DFT/B3LYP) methods with 6-31+G(*) basis set. The -311++G(**) basis set is also used for B3LYP level. The scaled harmonic vibrational frequencies have been compared with experimental FT-IR spectra. Theoretical vibrational spectra of the title compound were interpreted by means of potential energies distributions (PEDs) using MOLVIB program. The theoretical spectrograms for IR spectra of the title compound have been constructed. The shortening of C-H bond length and the elongation of N-H bond length suggest the existence of weak C-H⋯O and N-H⋯O hydrogen bonds, which is confirmed by the natural bond orbital analysis. In addition, the crystal structure obtained by molecular mechanics belongs to the P2(1) space group, with lattice parameters Z=4, a=14.9989 Å, b=4.0367 Å, c=12.9913 Å, ρ=0.998 g cm(-3). Copyright © 2013 Elsevier B.V. All rights reserved.

Molecular structure, vibrational spectra, NBO analysis and molecular packing prediction of 3-nitroacetanilide by ab initio HF and density functional theory

NASA Astrophysics Data System (ADS)

Li, Xiao-Hong; Li, Tong-Wei; Ju, Wei-Wei; Yong, Yong-Liang; Zhang, Xian-Zhou

2014-01-01

Quantum chemical calculations of geometries and vibrational wavenumbers of 3-nitroacetanilide (C8H8N2O3) in the ground state were carried out by using ab initio HF and density functional theory (DFT/B3LYP) methods with 6-31+G* basis set. The -311++G** basis set is also used for B3LYP level. The scaled harmonic vibrational frequencies have been compared with experimental FT-IR spectra. Theoretical vibrational spectra of the title compound were interpreted by means of potential energies distributions (PEDs) using MOLVIB program. The theoretical spectrograms for IR spectra of the title compound have been constructed. The shortening of Csbnd H bond length and the elongation of Nsbnd H bond length suggest the existence of weak Csbnd H⋯O and Nsbnd H⋯O hydrogen bonds, which is confirmed by the natural bond orbital analysis. In addition, the crystal structure obtained by molecular mechanics belongs to the P21 space group, with lattice parameters Z = 4, a = 14.9989 Å, b = 4.0367 Å, c = 12.9913 Å, ρ = 0.998 g cm-3.

Comparison of some dispersion-corrected and traditional functionals as applied to peptides and conformations of cyclohexane derivatives

NASA Astrophysics Data System (ADS)

Marianski, Mateusz; Asensio, Amparo; Dannenberg, J. J.

2012-07-01

We compare the energetic and structural properties of fully optimized α-helical and antiparallel β-sheet polyalanines and the energetic differences between axial and equatorial conformations of three cyclohexane derivatives (methyl, fluoro, and chloro) as calculated using several functionals designed to treat dispersion (B97-D, ωB97x-D, M06, M06L, and M06-2X) with other traditional functionals not specifically parametrized to treat dispersion (B3LYP, X3LYP, and PBE1PBE) and with experimental results. Those functionals developed to treat dispersion significantly overestimate interaction enthalpies of folding for the α-helix and predict unreasonable structures that contain Ramachandran ϕ and ψ and C = O…N H-bonding angles that are out of the bounds of databases compiled the β-sheets. These structures are consistent with overestimation of the interaction energies. For the cyclohexanes, these functionals overestimate the stabilities of the axial conformation, especially when used with smaller basis sets. Their performance improves when the basis set is improved from D95** to aug-cc-pVTZ (which would not be possible with systems as large as the peptides).

Comparison of some dispersion-corrected and traditional functionals as applied to peptides and conformations of cyclohexane derivatives

PubMed Central

Marianski, Mateusz; Asensio, Amparo; Dannenberg, J. J.

2012-01-01

We compare the energetic and structural properties of fully optimized α-helical and antiparallel β-sheet polyalanines and the energetic differences between axial and equatorial conformations of three cyclohexane derivatives (methyl, fluoro, and chloro) as calculated using several functionals designed to treat dispersion (B97-D, ωB97x-D, M06, M06L, and M06-2X) with other traditional functionals not specifically parametrized to treat dispersion (B3LYP, X3LYP, and PBE1PBE) and with experimental results. Those functionals developed to treat dispersion significantly overestimate interaction enthalpies of folding for the α-helix and predict unreasonable structures that contain Ramachandran ϕ and ψ and C = O…N H-bonding angles that are out of the bounds of databases compiled the β-sheets. These structures are consistent with overestimation of the interaction energies. For the cyclohexanes, these functionals overestimate the stabilities of the axial conformation, especially when used with smaller basis sets. Their performance improves when the basis set is improved from D95** to aug-cc-pVTZ (which would not be possible with systems as large as the peptides). PMID:22852599

Comparison of some dispersion-corrected and traditional functionals as applied to peptides and conformations of cyclohexane derivatives.

PubMed

Marianski, Mateusz; Asensio, Amparo; Dannenberg, J J

2012-07-28

We compare the energetic and structural properties of fully optimized α-helical and antiparallel β-sheet polyalanines and the energetic differences between axial and equatorial conformations of three cyclohexane derivatives (methyl, fluoro, and chloro) as calculated using several functionals designed to treat dispersion (B97-D, ωB97x-D, M06, M06L, and M06-2X) with other traditional functionals not specifically parametrized to treat dispersion (B3LYP, X3LYP, and PBE1PBE) and with experimental results. Those functionals developed to treat dispersion significantly overestimate interaction enthalpies of folding for the α-helix and predict unreasonable structures that contain Ramachandran φ and ψ and C = O...N H-bonding angles that are out of the bounds of databases compiled the β-sheets. These structures are consistent with overestimation of the interaction energies. For the cyclohexanes, these functionals overestimate the stabilities of the axial conformation, especially when used with smaller basis sets. Their performance improves when the basis set is improved from D95∗∗ to aug-cc-pVTZ (which would not be possible with systems as large as the peptides).

Theoretical study on the structure and stabilities of molecular clusters of oxalic acid with water.

PubMed

Weber, Kevin H; Morales, Francisco J; Tao, Fu-Ming

2012-11-29

The importance of aerosols to humankind is well-known, playing an integral role in determining Earth's climate and influencing human health. Despite this fact, much remains unknown about the initial events of nucleation. In this work, the molecular properties of common organic atmospheric pollutant oxalic acid and its gas phase interactions with water have been thoroughly examined. Local minima single-point energies for the monomer conformations were calculated at the B3LYP and MP2 level of theory with both 6-311++G(d,p) and aug-cc-pVDZ basis sets and are compared with previous works. Optimized geometries, relative energies, and free energy changes for the stable clusters of oxalic acid conformers with up to six waters were then obtained from B3LYP calculations with 6-31+G(d) and 6-311++G(d,p) basis sets. Initially, cooperative binding is predicted to be the most important factor in nucleation, but as the clusters grow, dipole cancellations are found to play a pivotal role. The clusters of oxalic acid hydrated purely with water tend to produce extremely stable and neutral core systems. Free energies of formation and atmospheric implications are discussed.

A full-dimensional ab initio potential energy surface and rovibrational energies of the Ar–HF complex

NASA Astrophysics Data System (ADS)

Huang, Jing; Zhou, Yanzi; Xie, Daiqian

2018-04-01

We report a new full-dimensional ab initio potential energy surface for the Ar-HF van der Waals complex at the level of coupled-cluster singles and doubles with noniterative inclusion of connected triples levels [CCSD(T)] using augmented correlation-consistent quintuple-zeta basis set (aV5Z) plus bond functions. Full counterpoise correction was employed to correct the basis-set superposition error. The hypersurface was fitted using artificial neural network method with a root mean square error of 0.1085 cm-1 for more than 8000 ab initio points. The complex was found to prefer a linear Ar-H-F equilibrium structure. The three-dimensional discrete variable representation method and the Lanczos propagation algorithm were then employed to calculate the rovibrational states without separating inter- and intra- molecular nuclear motions. The calculated vibrational energies of Ar-HF differ from the experiment values within about 1 cm-1 on the first four HF vibrational states, and the predicted pure rotational energies on (0000) and (1000) vibrational states are deviated from the observed value by about 1%, which shows the accuracy of our new PES.

In silico models for predicting ready biodegradability under REACH: a comparative study.

PubMed

Pizzo, Fabiola; Lombardo, Anna; Manganaro, Alberto; Benfenati, Emilio

2013-10-01

REACH (Registration Evaluation Authorization and restriction of Chemicals) legislation is a new European law which aims to raise the human protection level and environmental health. Under REACH all chemicals manufactured or imported for more than one ton per year must be evaluated for their ready biodegradability. Ready biodegradability is also used as a screening test for persistent, bioaccumulative and toxic (PBT) substances. REACH encourages the use of non-testing methods such as QSAR (quantitative structure-activity relationship) models in order to save money and time and to reduce the number of animals used for scientific purposes. Some QSAR models are available for predicting ready biodegradability. We used a dataset of 722 compounds to test four models: VEGA, TOPKAT, BIOWIN 5 and 6 and START and compared their performance on the basis of the following parameters: accuracy, sensitivity, specificity and Matthew's correlation coefficient (MCC). Performance was analyzed from different points of view. The first calculation was done on the whole dataset and VEGA and TOPKAT gave the best accuracy (88% and 87% respectively). Then we considered the compounds inside and outside the training set: BIOWIN 6 and 5 gave the best results for accuracy (81%) outside training set. Another analysis examined the applicability domain (AD). VEGA had the highest value for compounds inside the AD for all the parameters taken into account. Finally, compounds outside the training set and in the AD of the models were considered to assess predictive ability. VEGA gave the best accuracy results (99%) for this group of chemicals. Generally, START model gave poor results. Since BIOWIN, TOPKAT and VEGA models performed well, they may be used to predict ready biodegradability. Copyright © 2013 Elsevier B.V. All rights reserved.

A Gene Signature to Determine Metastatic Behavior in Thymomas

PubMed Central

Gökmen-Polar, Yesim; Wilkinson, Jeff; Maetzold, Derek; Stone, John F.; Oelschlager, Kristen M.; Vladislav, Ioan Tudor; Shirar, Kristen L.; Kesler, Kenneth A.; Loehrer, Patrick J.; Badve, Sunil

2013-01-01

Purpose Thymoma represents one of the rarest of all malignancies. Stage and completeness of resection have been used to ascertain postoperative therapeutic strategies albeit with limited prognostic accuracy. A molecular classifier would be useful to improve the assessment of metastatic behaviour and optimize patient management. Methods qRT-PCR assay for 23 genes (19 test and four reference genes) was performed on multi-institutional archival primary thymomas (n = 36). Gene expression levels were used to compute a signature, classifying tumors into classes 1 and 2, corresponding to low or high likelihood for metastases. The signature was validated in an independent multi-institutional cohort of patients (n = 75). Results A nine-gene signature that can predict metastatic behavior of thymomas was developed and validated. Using radial basis machine modeling in the training set, 5-year and 10-year metastasis-free survival rates were 77% and 26% for predicted low (class 1) and high (class 2) risk of metastasis (P = 0.0047, log-rank), respectively. For the validation set, 5-year metastasis-free survival rates were 97% and 30% for predicted low- and high-risk patients (P = 0.0004, log-rank), respectively. The 5-year metastasis-free survival rates for the validation set were 49% and 41% for Masaoka stages I/II and III/IV (P = 0.0537, log-rank), respectively. In univariate and multivariate Cox models evaluating common prognostic factors for thymoma metastasis, the nine-gene signature was the only independent indicator of metastases (P = 0.036). Conclusion A nine-gene signature was established and validated which predicts the likelihood of metastasis more accurately than traditional staging. This further underscores the biologic determinants of the clinical course of thymoma and may improve patient management. PMID:23894276

On the Use of a Mixed Gaussian/Finite-Element Basis Set for the Calculation of Rydberg States

NASA Technical Reports Server (NTRS)

Thuemmel, Helmar T.; Langhoff, Stephen (Technical Monitor)

1996-01-01

Configuration-interaction studies are reported for the Rydberg states of the helium atom using mixed Gaussian/finite-element (GTO/FE) one particle basis sets. Standard Gaussian valence basis sets are employed, like those, used extensively in quantum chemistry calculations. It is shown that the term values for high-lying Rydberg states of the helium atom can be obtained accurately (within 1 cm -1), even for a small GTO set, by augmenting the n-particle space with configurations, where orthonormalized interpolation polynomials are singly occupied.

Satellite Remote Sensing is Key to Water Cycle Integrator

NASA Astrophysics Data System (ADS)

Koike, T.

2016-12-01

To promote effective multi-sectoral, interdisciplinary collaboration based on coordinated and integrated efforts, the Global Earth Observation System of Systems (GEOSS) is now developing a "GEOSS Water Cycle Integrator (WCI)", which integrates "Earth observations", "modeling", "data and information", "management systems" and "education systems". GEOSS/WCI sets up "work benches" by which partners can share data, information and applications in an interoperable way, exchange knowledge and experiences, deepen mutual understanding and work together effectively to ultimately respond to issues of both mitigation and adaptation. (A work bench is a virtual geographical or phenomenological space where experts and managers collaborate to use information to address a problem within that space). GEOSS/WCI enhances the coordination of efforts to strengthen individual, institutional and infrastructure capacities, especially for effective interdisciplinary coordination and integration. GEOSS/WCI archives various satellite data to provide various hydrological information such as cloud, rainfall, soil moisture, or land-surface snow. These satellite products were validated using land observation in-situ data. Water cycle models can be developed by coupling in-situ and satellite data. River flows and other hydrological parameters can be simulated and validated by in-situ data. Model outputs from weather-prediction, seasonal-prediction, and climate-prediction models are archived. Some of these model outputs are archived on an online basis, but other models, e.g., climate-prediction models are archived on an offline basis. After models are evaluated and biases corrected, the outputs can be used as inputs into the hydrological models for predicting the hydrological parameters. Additionally, we have already developed a data-assimilation system by combining satellite data and the models. This system can improve our capability to predict hydrological phenomena. The WCI can provide better predictions of the hydrological parameters for integrated water resources management (IWRM) and also assess the impact of climate change and calculate adaptation needs.

Perturbation corrections to Koopmans' theorem. V - A study with large basis sets

NASA Technical Reports Server (NTRS)

Chong, D. P.; Langhoff, S. R.

1982-01-01

The vertical ionization potentials of N2, F2 and H2O were calculated by perturbation corrections to Koopmans' theorem using six different basis sets. The largest set used includes several sets of polarization functions. Comparison is made with measured values and with results of computations using Green's functions.

[Determination of Carbaryl in Rice by Using FT Far-IR and THz-TDS Techniques].

PubMed

Sun, Tong; Zhang, Zhuo-yong; Xiang, Yu-hong; Zhu, Ruo-hua

2016-02-01

Determination of carbaryl in rice by using Fourier transform far-infrared (FT- Far-IR) and terahertz time-domain spectroscopy (THz-TDS) combined with chemometrics was studied and the spectral characteristics of carbaryl in terahertz region was investigated. Samples were prepared by mixing carbaryl at different amounts with rice powder, and then a 13 mm diameter, and about 1 mm thick pellet with polyethylene (PE) as matrix was compressed under the pressure of 5-7 tons. Terahertz time domain spectra of the pellets were measured at 0.5~1.5 THz, and the absorption spectra at 1.6. 3 THz were acquired with Fourier transform far-IR spectroscopy. The method of sample preparation is so simple that it does not need separation and enrichment. The absorption peaks in the frequency range of 1.8-6.3 THz have been found at 3.2 and 5.2 THz by Far-IR. There are several weak absorption peaks in the range of 0.5-1.5 THz by THz-TDS. These two kinds of characteristic absorption spectra were randomly divided into calibration set and prediction set by leave-N-out cross-validation, respectively. Finally, the partial least squares regression (PLSR) method was used to establish two quantitative analysis models. The root mean square error (RMSECV), the root mean square errors of prediction (RMSEP) and the correlation coefficient of the prediction are used as a basis for the model of performance evaluation. For the R,, a higher value is better; for the RMSEC and RMSEP, lower is better. The obtained results demonstrated that the predictive accuracy of. the two models with PLSR method were satisfactory. For the FT-Far-IR model, the correlation between actual and predicted values of prediction samples (Rv) was 0.99. The root mean square error of prediction set (RMSEP) was 0.008 6, and for calibration set (RMSECV) was 0.007 7. For the THz-TDS model, R. was 0. 98, RMSEP was 0.004 4, and RMSECV was 0.002 5. Results proved that the technology of FT-Far-IR and THz- TDS can be a feasible tool for quantitative determination of carbaryl in rice. This paper provides a new method for the quantitative determination pesticide in other grain samples.

A new basis set for molecular bending degrees of freedom.

PubMed

Jutier, Laurent

2010-07-21

We present a new basis set as an alternative to Legendre polynomials for the variational treatment of bending vibrational degrees of freedom in order to highly reduce the number of basis functions. This basis set is inspired from the harmonic oscillator eigenfunctions but is defined for a bending angle in the range theta in [0:pi]. The aim is to bring the basis functions closer to the final (ro)vibronic wave functions nature. Our methodology is extended to complicated potential energy surfaces, such as quasilinearity or multiequilibrium geometries, by using several free parameters in the basis functions. These parameters allow several density maxima, linear or not, around which the basis functions will be mainly located. Divergences at linearity in integral computations are resolved as generalized Legendre polynomials. All integral computations required for the evaluation of molecular Hamiltonian matrix elements are given for both discrete variable representation and finite basis representation. Convergence tests for the low energy vibronic states of HCCH(++), HCCH(+), and HCCS are presented.

Dispersion-correcting potentials can significantly improve the bond dissociation enthalpies and noncovalent binding energies predicted by density-functional theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

DiLabio, Gino A., E-mail: Gino.DiLabio@nrc.ca; Department of Chemistry, University of British Columbia, Okanagan, 3333 University Way, Kelowna, British Columbia V1V 1V7; Koleini, Mohammad

2014-05-14

Dispersion-correcting potentials (DCPs) are atom-centered Gaussian functions that are applied in a manner that is similar to effective core potentials. Previous work on DCPs has focussed on their use as a simple means of improving the ability of conventional density-functional theory methods to predict the binding energies of noncovalently bonded molecular dimers. We show in this work that DCPs developed for use with the LC-ωPBE functional along with 6-31+G(2d,2p) basis sets are capable of simultaneously improving predicted noncovalent binding energies of van der Waals dimer complexes and covalent bond dissociation enthalpies in molecules. Specifically, the DCPs developed herein for themore » C, H, N, and O atoms provide binding energies for a set of 66 noncovalently bonded molecular dimers (the “S66” set) with a mean absolute error (MAE) of 0.21 kcal/mol, which represents an improvement of more than a factor of 10 over unadorned LC-ωPBE/6-31+G(2d,2p) and almost a factor of two improvement over LC-ωPBE/6-31+G(2d,2p) used in conjunction with the “D3” pairwise dispersion energy corrections. In addition, the DCPs reduce the MAE of calculated X-H and X-Y (X,Y = C, H, N, O) bond dissociation enthalpies for a set of 40 species from 3.2 kcal/mol obtained with unadorned LC-ωPBE/6-31+G(2d,2p) to 1.6 kcal/mol. Our findings demonstrate that broad improvements to the performance of DFT methods may be achievable through the use of DCPs.« less

Regression Trees Identify Relevant Interactions: Can This Improve the Predictive Performance of Risk Adjustment?

PubMed

Buchner, Florian; Wasem, Jürgen; Schillo, Sonja

2017-01-01

Risk equalization formulas have been refined since their introduction about two decades ago. Because of the complexity and the abundance of possible interactions between the variables used, hardly any interactions are considered. A regression tree is used to systematically search for interactions, a methodologically new approach in risk equalization. Analyses are based on a data set of nearly 2.9 million individuals from a major German social health insurer. A two-step approach is applied: In the first step a regression tree is built on the basis of the learning data set. Terminal nodes characterized by more than one morbidity-group-split represent interaction effects of different morbidity groups. In the second step the 'traditional' weighted least squares regression equation is expanded by adding interaction terms for all interactions detected by the tree, and regression coefficients are recalculated. The resulting risk adjustment formula shows an improvement in the adjusted R 2 from 25.43% to 25.81% on the evaluation data set. Predictive ratios are calculated for subgroups affected by the interactions. The R 2 improvement detected is only marginal. According to the sample level performance measures used, not involving a considerable number of morbidity interactions forms no relevant loss in accuracy. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

The Linear Interaction Energy Method for the Prediction of Protein Stability Changes Upon Mutation

PubMed Central

Wickstrom, Lauren; Gallicchio, Emilio; Levy, Ronald M.

2011-01-01

The coupling of protein energetics and sequence changes is a critical aspect of computational protein design, as well as for the understanding of protein evolution, human disease, and drug resistance. In order to study the molecular basis for this coupling, computational tools must be sufficiently accurate and computationally inexpensive enough to handle large amounts of sequence data. We have developed a computational approach based on the linear interaction energy (LIE) approximation to predict the changes in the free energy of the native state induced by a single mutation. This approach was applied to a set of 822 mutations in 10 proteins which resulted in an average unsigned error of 0.82 kcal/mol and a correlation coefficient of 0.72 between the calculated and experimental ΔΔG values. The method is able to accurately identify destabilizing hot spot mutations however it has difficulty in distinguishing between stabilizing and destabilizing mutations due to the distribution of stability changes for the set of mutations used to parameterize the model. In addition, the model also performs quite well in initial tests on a small set of double mutations. Based on these promising results, we can begin to examine the relationship between protein stability and fitness, correlated mutations, and drug resistance. PMID:22038697

Spectroscopy and heats of formation of CXI (X = Br, Cl, F) iodocarbenes: quantum chemical characterisation of the ?, ? and ? states

NASA Astrophysics Data System (ADS)

Bacskay, George B.

2015-07-01

The equilibrium energies of the iodocarbenes CXI (X = Br, Cl, F) in their ?, ? and ? states and their atomisation and dissociation energies in the complete basis limit were determined by extrapolating valence correlated (R/U)CCSD(T) and Davidson corrected multi-reference configuration interaction (MRCI) energies calculated with the aug-cc-pVxZ (x = T,Q,5) basis sets and the ECP28MDF pseudopotential of iodine plus corrections for core and core-valence correlation, scalar relativity, spin-orbit coupling and zero-point energies. Spin-orbit energies were computed in a large basis of configurations chosen so as to accurately describe dissociation to the 3P and 2P states of C and of the halogens X and I, respectively. The computed singlet-triplet splittings are 13.6, 14.4 and 27.3 kcal mol-1 for X = Br, Cl and F, respectively. The enthalpies of formation at 0 K are predicted to be 97.4, 82.6 and 38.1 kcal mol-1 with estimated errors of ±1.0 kcal mol-1. The ? excitation energies (T00) in CBrI and CClI are calculated to be 41.1 and 41.7 kcal mol-1, respectively. The Renner-Teller intersections in both molecules are predicted to be substantially higher than the dissociation barriers on the ? surfaces. By contrast, in CFI the ? state is found to be unbound with respect to dissociation.

Moderator's view: Predictive models: a prelude to precision nephrology.

PubMed

Zoccali, Carmine

2017-05-01

Appropriate diagnosis is fundamental in medicine because it sets the basis for the prediction of disease outcome at the single patient level (prognosis) and decisions regarding the most appropriate therapy. However, given the large series of social, clinical and biological factors that determine the likelihood of an individual's future outcome, prognosis only partly depends on diagnosis and aetiology and treatment is not decided solely on the basis of the underlying diagnosis. This issue is crucial in multifactorial diseases like atherosclerosis, where the use of statins has now shifted from 'treating hypercholesterolaemia' to 'treating the risk of adverse cardiovascular events'. Approaches that take due account of prognosis limit the lingering risk of over-diagnosis and maximize the value of prognostic information in the clinical decision process. In the nephrology realm, the application of a well-validated risk equation for kidney failure in Canada led to a 35% reduction in new referrals. Prognostic models based on simple clinical data extractable from clinical files have recently been developed to predict all-cause and cardiovascular mortality in end-stage kidney disease patients. However, research on predictive models in renal diseases remains suboptimal and non-accounting for competing events and measurement errors, and a lack of calibration analyses and external validation are common fallacies in currently available studies. More focus on this blossoming research area is desirable. The nephrology community may now start to apply the best validated risk scores and further test their potential usefulness in chronic kidney disease patients in diverse clinical situations and geographical areas. © The Author 2017. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

On the phase space structure of IP3 induced Ca2+ signalling and concepts for predictive modeling

NASA Astrophysics Data System (ADS)

Falcke, Martin; Moein, Mahsa; TilÅ«naitÄ--, Agne; Thul, Rüdiger; Skupin, Alexander

2018-04-01

The correspondence between mathematical structures and experimental systems is the basis of the generalizability of results found with specific systems and is the basis of the predictive power of theoretical physics. While physicists have confidence in this correspondence, it is less recognized in cellular biophysics. On the one hand, the complex organization of cellular dynamics involving a plethora of interacting molecules and the basic observation of cell variability seem to question its possibility. The practical difficulties of deriving the equations describing cellular behaviour from first principles support these doubts. On the other hand, ignoring such a correspondence would severely limit the possibility of predictive quantitative theory in biophysics. Additionally, the existence of functional modules (like pathways) across cell types suggests also the existence of mathematical structures with comparable universality. Only a few cellular systems have been sufficiently investigated in a variety of cell types to follow up these basic questions. IP3 induced Ca2+signalling is one of them, and the mathematical structure corresponding to it is subject of ongoing discussion. We review the system's general properties observed in a variety of cell types. They are captured by a reaction diffusion system. We discuss the phase space structure of its local dynamics. The spiking regime corresponds to noisy excitability. Models focussing on different aspects can be derived starting from this phase space structure. We discuss how the initial assumptions on the set of stochastic variables and phase space structure shape the predictions of parameter dependencies of the mathematical models resulting from the derivation.

Extrapolating MP2 and CCSD explicitly correlated correlation energies to the complete basis set limit with first and second row correlation consistent basis sets

NASA Astrophysics Data System (ADS)

Hill, J. Grant; Peterson, Kirk A.; Knizia, Gerald; Werner, Hans-Joachim

2009-11-01

Accurate extrapolation to the complete basis set (CBS) limit of valence correlation energies calculated with explicitly correlated MP2-F12 and CCSD(T)-F12b methods have been investigated using a Schwenke-style approach for molecules containing both first and second row atoms. Extrapolation coefficients that are optimal for molecular systems containing first row elements differ from those optimized for second row analogs, hence values optimized for a combined set of first and second row systems are also presented. The new coefficients are shown to produce excellent results in both Schwenke-style and equivalent power-law-based two-point CBS extrapolations, with the MP2-F12/cc-pV(D,T)Z-F12 extrapolations producing an average error of just 0.17 mEh with a maximum error of 0.49 for a collection of 23 small molecules. The use of larger basis sets, i.e., cc-pV(T,Q)Z-F12 and aug-cc-pV(Q,5)Z, in extrapolations of the MP2-F12 correlation energy leads to average errors that are smaller than the degree of confidence in the reference data (˜0.1 mEh). The latter were obtained through use of very large basis sets in MP2-F12 calculations on small molecules containing both first and second row elements. CBS limits obtained from optimized coefficients for conventional MP2 are only comparable to the accuracy of the MP2-F12/cc-pV(D,T)Z-F12 extrapolation when the aug-cc-pV(5+d)Z and aug-cc-pV(6+d)Z basis sets are used. The CCSD(T)-F12b correlation energy is extrapolated as two distinct parts: CCSD-F12b and (T). While the CCSD-F12b extrapolations with smaller basis sets are statistically less accurate than those of the MP2-F12 correlation energies, this is presumably due to the slower basis set convergence of the CCSD-F12b method compared to MP2-F12. The use of larger basis sets in the CCSD-F12b extrapolations produces correlation energies with accuracies exceeding the confidence in the reference data (also obtained in large basis set F12 calculations). It is demonstrated that the use of the 3C(D) Ansatz is preferred for MP2-F12 CBS extrapolations. Optimal values of the geminal Slater exponent are presented for the diagonal, fixed amplitude Ansatz in MP2-F12 calculations, and these are also recommended for CCSD-F12b calculations.

Nuclear spin/parity dependent spectroscopy and predissociation dynamics in vOH = 2 ← 0 overtone excited Ne-H2O clusters: Theory and experiment

NASA Astrophysics Data System (ADS)

Ziemkiewicz, Michael P.; Pluetzer, Christian; Loreau, Jérôme; van der Avoird, Ad; Nesbitt, David J.

2017-12-01

Vibrationally state selective overtone spectroscopy and state- and nuclear spin-dependent predissociation dynamics of weakly bound ortho- and para-Ne-H2O complexes (D0(ortho) = 34.66 cm-1 and D0(para) = 31.67 cm-1) are reported, based on near-infrared excitation of van der Waals cluster bands correlating with vOH = 2 ← 0 overtone transitions (|02-〉 and |02+〉) out of the ortho (101) and para (000) internal rotor states of the H2O moiety. Quantum theoretical calculations for nuclear motion on a high level potential energy surface [CCSD(T)/VnZf12 (n = 3, 4)], corrected for basis set superposition error and extrapolated to the complete basis set (CBS) limit, are employed to successfully predict and assign Π-Σ, Σ-Σ, and Σ-Π infrared bands in the spectra, where Σ or Π represent approximate projections of the body-fixed H2O angular momentum along the Ne-H2O internuclear axis. IR-UV pump-probe experimental capabilities permit real-time measurements of the vibrational predissociation dynamics, which indicate facile intramolecular vibrational energy transfer from the H2O vOH = 2 overtone vibrations into the VdWs (van der Waals) dissociation coordinate on the τprediss = 15-25 ns time scale. Whereas all predicted strong transitions in the ortho-Ne-H2O complexes are readily detected and assigned, vibrationally mediated photolysis spectra for the corresponding para-Ne-H2O bands are surprisingly absent despite ab initio predictions of Q-branch intensities with S/N > 20-40. Such behavior signals the presence of highly selective nuclear spin ortho-para predissociation dynamics in the upper state, for which we offer a simple mechanism based on Ne-atom mediated intramolecular vibrational relaxation in the H2O subunit (i.e., |02±〉 → {|01±〉; v2 = 2}), which is confirmed by the ab initio energy level predictions and the nascent OH rotational (N), spin orbit (Π1/2,3/2), and lambda doublet product distributions.

Sensitivity of Aerosol Mass and Microphysics to Treatments of Condensational Growth of Secondary Organic Compounds in a Regional Model

NASA Astrophysics Data System (ADS)

Topping, D. O.; Lowe, D.; McFiggans, G.; Zaveri, R. A.

2016-12-01

Gas to particle partitioning of atmospheric compounds occurs through disequilibrium mass transfer rather than through instantaneous equilibrium. However, it is common to treat only the inorganic compounds as partitioning dynamically whilst organic compounds, represented by the Volatility Basis Set (VBS), are partitioned instantaneously. In this study we implement a more realistic dynamic partitioning of organic compounds in a regional framework and assess impact on aerosol mass and microphysics. It is also common to assume condensed phase water is only associated with inorganic components. We thus also assess sensitivity to assuming all organics are hygroscopic according to their prescribed molecular weight.For this study we use WRF-Chem v3.4.1, focusing on anthropogenic dominated North-Western Europe. Gas-phase chemistry is represented using CBM-Z whilst aerosol dynamics are simulated using the 8-section MOSAIC scheme, including a 9-bin volatility basis set (VBS) treatment of organic aerosol. Results indicate that predicted mass loadings can vary significantly. Without gas phase ageing of higher volatility compounds, dynamic partitioning always results in lower mass loadings downwind of emission sources. The inclusion of condensed phase water in both partitioning models increases the predicted PM mass, resulting from a larger contribution from higher volatility organics, if present. If gas phase ageing of VBS compounds is allowed to occur in a dynamic model, this can often lead to higher predicted mass loadings, contrary to expected behaviour from a simple non-reactive gas phase box model. As descriptions of aerosol phase processes improve within regional models, the baseline descriptions of partitioning should retain the ability to treat dynamic partitioning of organic compounds. Using our simulations, we discuss whether derived sensitivities to aerosol processes in existing models may be inherently biased.This work was supported by the Nature Environment Research Council within the RONOCO (NE/F004656/1) and CCN-Vol (NE/L007827/1) projects.

An Alternate Set of Basis Functions for the Electromagnetic Solution of Arbitrarily-Shaped, Three-Dimensional, Closed, Conducting Bodies Using Method of Moments

NASA Technical Reports Server (NTRS)

Mackenzie, Anne I.; Baginski, Michael E.; Rao, Sadasiva M.

2008-01-01

In this work, we present an alternate set of basis functions, each defined over a pair of planar triangular patches, for the method of moments solution of electromagnetic scattering and radiation problems associated with arbitrarily-shaped, closed, conducting surfaces. The present basis functions are point-wise orthogonal to the pulse basis functions previously defined. The prime motivation to develop the present set of basis functions is to utilize them for the electromagnetic solution of dielectric bodies using a surface integral equation formulation which involves both electric and magnetic cur- rents. However, in the present work, only the conducting body solution is presented and compared with other data.

Correction of energy-dependent systematic errors in dual-energy X-ray CT using a basis material coefficients transformation method

NASA Astrophysics Data System (ADS)

Goh, K. L.; Liew, S. C.; Hasegawa, B. H.

1997-12-01

Computer simulation results from our previous studies showed that energy dependent systematic errors exist in the values of attenuation coefficient synthesized using the basis material decomposition technique with acrylic and aluminum as the basis materials, especially when a high atomic number element (e.g., iodine from radiographic contrast media) was present in the body. The errors were reduced when a basis set was chosen from materials mimicking those found in the phantom. In the present study, we employed a basis material coefficients transformation method to correct for the energy-dependent systematic errors. In this method, the basis material coefficients were first reconstructed using the conventional basis materials (acrylic and aluminum) as the calibration basis set. The coefficients were then numerically transformed to those for a more desirable set materials. The transformation was done at the energies of the low and high energy windows of the X-ray spectrum. With this correction method using acrylic and an iodine-water mixture as our desired basis set, computer simulation results showed that accuracy of better than 2% could be achieved even when iodine was present in the body at a concentration as high as 10% by mass. Simulation work had also been carried out on a more inhomogeneous 2D thorax phantom of the 3D MCAT phantom. The results of the accuracy of quantitation were presented here.

Comparison of fMRI analysis methods for heterogeneous BOLD responses in block design studies.

PubMed

Liu, Jia; Duffy, Ben A; Bernal-Casas, David; Fang, Zhongnan; Lee, Jin Hyung

2017-02-15

A large number of fMRI studies have shown that the temporal dynamics of evoked BOLD responses can be highly heterogeneous. Failing to model heterogeneous responses in statistical analysis can lead to significant errors in signal detection and characterization and alter the neurobiological interpretation. However, to date it is not clear that, out of a large number of options, which methods are robust against variability in the temporal dynamics of BOLD responses in block-design studies. Here, we used rodent optogenetic fMRI data with heterogeneous BOLD responses and simulations guided by experimental data as a means to investigate different analysis methods' performance against heterogeneous BOLD responses. Evaluations are carried out within the general linear model (GLM) framework and consist of standard basis sets as well as independent component analysis (ICA). Analyses show that, in the presence of heterogeneous BOLD responses, conventionally used GLM with a canonical basis set leads to considerable errors in the detection and characterization of BOLD responses. Our results suggest that the 3rd and 4th order gamma basis sets, the 7th to 9th order finite impulse response (FIR) basis sets, the 5th to 9th order B-spline basis sets, and the 2nd to 5th order Fourier basis sets are optimal for good balance between detection and characterization, while the 1st order Fourier basis set (coherence analysis) used in our earlier studies show good detection capability. ICA has mostly good detection and characterization capabilities, but detects a large volume of spurious activation with the control fMRI data. Copyright © 2016 Elsevier Inc. All rights reserved.

Point Set Denoising Using Bootstrap-Based Radial Basis Function.

PubMed

Liew, Khang Jie; Ramli, Ahmad; Abd Majid, Ahmad

2016-01-01

This paper examines the application of a bootstrap test error estimation of radial basis functions, specifically thin-plate spline fitting, in surface smoothing. The presence of noisy data is a common issue of the point set model that is generated from 3D scanning devices, and hence, point set denoising is one of the main concerns in point set modelling. Bootstrap test error estimation, which is applied when searching for the smoothing parameters of radial basis functions, is revisited. The main contribution of this paper is a smoothing algorithm that relies on a bootstrap-based radial basis function. The proposed method incorporates a k-nearest neighbour search and then projects the point set to the approximated thin-plate spline surface. Therefore, the denoising process is achieved, and the features are well preserved. A comparison of the proposed method with other smoothing methods is also carried out in this study.

Computational study of the electronic spectra of the rare gas fluorohydrides HRgF (Rg = Ar, Kr, Xe, Rn)

NASA Astrophysics Data System (ADS)

van Hoeve, Miriam D.; Klobukowski, Mariusz

2018-03-01

Simulation of the electronic spectra of HRgF (Rg = Ar, Kr, Xe, Rn) was carried out using the time-dependent density functional method, with the CAMB3LYP functional and several basis sets augmented with even-tempered diffuse functions. A full spectral assignment for the HRgF systems was done. The effect of the rare gas matrix on the HRgF (Rg = Ar and Kr) spectra was investigated and it was found that the matrix blue-shifted the spectra. Scalar relativistic effects on the spectra were also studied and it was found that while the excitation energies of HArF and HKrF were insignificantly affected by relativistic effects, most of the excitation energies of HXeF and HRnF were red-shifted. Spin-orbit coupling was found to significantly affect excitation energies in HRnF. Analysis of performance of the model core potential basis set relative to all-electron (AE) basis sets showed that the former basis set increased computational efficiency and gave results similar to those obtained with the AE basis set.

Midbond basis functions for weakly bound complexes

NASA Astrophysics Data System (ADS)

Shaw, Robert A.; Hill, J. Grant

2018-06-01

Weakly bound systems present a difficult problem for conventional atom-centred basis sets due to large separations, necessitating the use of large, computationally expensive bases. This can be remedied by placing a small number of functions in the region between molecules in the complex. We present compact sets of optimised midbond functions for a range of complexes involving noble gases, alkali metals and small molecules for use in high accuracy coupled -cluster calculations, along with a more robust procedure for their optimisation. It is shown that excellent results are possible with double-zeta quality orbital basis sets when a few midbond functions are added, improving both the interaction energy and the equilibrium bond lengths of a series of noble gas dimers by 47% and 8%, respectively. When used in conjunction with explicitly correlated methods, near complete basis set limit accuracy is readily achievable at a fraction of the cost that using a large basis would entail. General purpose auxiliary sets are developed to allow explicitly correlated midbond function studies to be carried out, making it feasible to perform very high accuracy calculations on weakly bound complexes.

Opportunities of probabilistic flood loss models

NASA Astrophysics Data System (ADS)

Schröter, Kai; Kreibich, Heidi; Lüdtke, Stefan; Vogel, Kristin; Merz, Bruno

2016-04-01

Oftentimes, traditional uni-variate damage models as for instance depth-damage curves fail to reproduce the variability of observed flood damage. However, reliable flood damage models are a prerequisite for the practical usefulness of the model results. Innovative multi-variate probabilistic modelling approaches are promising to capture and quantify the uncertainty involved and thus to improve the basis for decision making. In this study we compare the predictive capability of two probabilistic modelling approaches, namely Bagging Decision Trees and Bayesian Networks and traditional stage damage functions. For model evaluation we use empirical damage data which are available from computer aided telephone interviews that were respectively compiled after the floods in 2002, 2005, 2006 and 2013 in the Elbe and Danube catchments in Germany. We carry out a split sample test by sub-setting the damage records. One sub-set is used to derive the models and the remaining records are used to evaluate the predictive performance of the model. Further we stratify the sample according to catchments which allows studying model performance in a spatial transfer context. Flood damage estimation is carried out on the scale of the individual buildings in terms of relative damage. The predictive performance of the models is assessed in terms of systematic deviations (mean bias), precision (mean absolute error) as well as in terms of sharpness of the predictions the reliability which is represented by the proportion of the number of observations that fall within the 95-quantile and 5-quantile predictive interval. The comparison of the uni-variable Stage damage function and the multivariable model approach emphasises the importance to quantify predictive uncertainty. With each explanatory variable, the multi-variable model reveals an additional source of uncertainty. However, the predictive performance in terms of precision (mbe), accuracy (mae) and reliability (HR) is clearly improved in comparison to uni-variable Stage damage function. Overall, Probabilistic models provide quantitative information about prediction uncertainty which is crucial to assess the reliability of model predictions and improves the usefulness of model results.

A reexamination of age-related variation in body weight and morphometry of Maryland nutria

USGS Publications Warehouse

Sherfy, M.H.; Mollett, T.A.; McGowan, K.R.; Daugherty, S.L.

2006-01-01

Age-related variation in morphometry has been documented for many species. Knowledge of growth patterns can be useful for modeling energetics, detecting physiological influences on populations, and predicting age. These benefits have shown value in understanding population dynamics of invasive species, particularly in developing efficient control and eradication programs. However, development and evaluation of descriptive and predictive models is a critical initial step in this process. Accordingly, we used data from necropsies of 1,544 nutria (Myocastor coypus) collected in Maryland, USA, to evaluate the accuracy of previously published models for prediction of nutria age from body weight. Published models underestimated body weights of our animals, especially for ages <3. We used cross-validation procedures to develop and evaluate models for describing nutria growth patterns and for predicting nutria age. We derived models from a randomly selected model-building data set (n = 192-193 M, 217-222 F) and evaluated them with the remaining animals (n = 487-488 M, 642-647 F). We used nonlinear regression to develop Gompertz growth-curve models relating morphometric variables to age. Predicted values of morphometric variables fell within the 95% confidence limits of their true values for most age classes. We also developed predictive models for estimating nutria age from morphometry, using linear regression of log-transformed age on morphometric variables. The evaluation data set corresponded with 95% prediction intervals from the new models. Predictive models for body weight and length provided greater accuracy and less bias than models for foot length and axillary girth. Our growth models accurately described age-related variation in nutria morphometry, and our predictive models provided accurate estimates of ages from morphometry that will be useful for live-captured individuals. Our models offer better accuracy and precision than previously published models, providing a capacity for modeling energetics and growth patterns of Maryland nutria as well as an empirical basis for determining population age structure from live-captured animals.

Collaboration between a human group and artificial intelligence can improve prediction of multiple sclerosis course: a proof-of-principle study

PubMed Central

Ferraldeschi, Michela; Salvetti, Marco; Zaccaria, Andrea; Crisanti, Andrea; Grassi, Francesca

2017-01-01

Background: Multiple sclerosis has an extremely variable natural course. In most patients, disease starts with a relapsing-remitting (RR) phase, which proceeds to a secondary progressive (SP) form. The duration of the RR phase is hard to predict, and to date predictions on the rate of disease progression remain suboptimal. This limits the opportunity to tailor therapy on an individual patient's prognosis, in spite of the choice of several therapeutic options. Approaches to improve clinical decisions, such as collective intelligence of human groups and machine learning algorithms are widely investigated. Methods: Medical students and a machine learning algorithm predicted the course of disease on the basis of randomly chosen clinical records of patients that attended at the Multiple Sclerosis service of Sant'Andrea hospital in Rome. Results: A significant improvement of predictive ability was obtained when predictions were combined with a weight that depends on the consistence of human (or algorithm) forecasts on a given clinical record. Conclusions: In this work we present proof-of-principle that human-machine hybrid predictions yield better prognoses than machine learning algorithms or groups of humans alone. To strengthen this preliminary result, we propose a crowdsourcing initiative to collect prognoses by physicians on an expanded set of patients. PMID:29904574

Prediction of adolescent and adult adiposity outcomes from early life anthropometrics.

PubMed

Graversen, Lise; Sørensen, Thorkild I A; Gerds, Thomas A; Petersen, Liselotte; Sovio, Ulla; Kaakinen, Marika; Sandbaek, Annelli; Laitinen, Jaana; Taanila, Anja; Pouta, Anneli; Järvelin, Marjo-Riitta; Obel, Carsten

2015-01-01

Maternal body mass index (BMI), birth weight, and preschool BMI may help identify children at high risk of overweight as they are (1) similarly linked to adolescent overweight at different stages of the obesity epidemic, (2) linked to adult obesity and metabolic alterations, and (3) easily obtainable in health examinations in young children. The aim was to develop early childhood prediction models of adolescent overweight, adult overweight, and adult obesity. Prediction models at various ages in the Northern Finland Birth Cohort born in 1966 (NFBC1966) were developed. Internal validation was tested using a bootstrap design, and external validation was tested for the model predicting adolescent overweight using the Northern Finland Birth Cohort born in 1986 (NFBC1986). A prediction model developed in the NFBC1966 to predict adolescent overweight, applied to the NFBC1986, and aimed at labelling 10% as "at risk" on the basis of anthropometric information collected until 5 years of age showed that half of those at risk in fact did become overweight. This group constituted one-third of all who became overweight. Our prediction model identified a subgroup of children at very high risk of becoming overweight, which may be valuable in public health settings dealing with obesity prevention. © 2014 The Obesity Society.

Collaboration between a human group and artificial intelligence can improve prediction of multiple sclerosis course: a proof-of-principle study.

PubMed

Tacchella, Andrea; Romano, Silvia; Ferraldeschi, Michela; Salvetti, Marco; Zaccaria, Andrea; Crisanti, Andrea; Grassi, Francesca

2017-01-01

Background: Multiple sclerosis has an extremely variable natural course. In most patients, disease starts with a relapsing-remitting (RR) phase, which proceeds to a secondary progressive (SP) form. The duration of the RR phase is hard to predict, and to date predictions on the rate of disease progression remain suboptimal. This limits the opportunity to tailor therapy on an individual patient's prognosis, in spite of the choice of several therapeutic options. Approaches to improve clinical decisions, such as collective intelligence of human groups and machine learning algorithms are widely investigated. Methods: Medical students and a machine learning algorithm predicted the course of disease on the basis of randomly chosen clinical records of patients that attended at the Multiple Sclerosis service of Sant'Andrea hospital in Rome. Results: A significant improvement of predictive ability was obtained when predictions were combined with a weight that depends on the consistence of human (or algorithm) forecasts on a given clinical record. Conclusions: In this work we present proof-of-principle that human-machine hybrid predictions yield better prognoses than machine learning algorithms or groups of humans alone. To strengthen this preliminary result, we propose a crowdsourcing initiative to collect prognoses by physicians on an expanded set of patients.

Convex Regression with Interpretable Sharp Partitions

PubMed Central

Petersen, Ashley; Simon, Noah; Witten, Daniela

2016-01-01

We consider the problem of predicting an outcome variable on the basis of a small number of covariates, using an interpretable yet non-additive model. We propose convex regression with interpretable sharp partitions (CRISP) for this task. CRISP partitions the covariate space into blocks in a data-adaptive way, and fits a mean model within each block. Unlike other partitioning methods, CRISP is fit using a non-greedy approach by solving a convex optimization problem, resulting in low-variance fits. We explore the properties of CRISP, and evaluate its performance in a simulation study and on a housing price data set. PMID:27635120

Reports of the second All-Union conference on the chemistry of transplutonium elements (Dmitrovgrad, June 21-23, 1963)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1987-05-01

The nine papers presented at this conference cover the following topics: the systematization, condensed description, and prediction of sets of anion exchange extraction constants on the basis of their statistical computer treatment; characteristics and uses of solid extractants containing D2EHPA and TBP for separating the transplutonium elements; enrichment of americium 242m and americium 242 by the Szilard-Chalmers method; an x-ray diffraction pattern analysis for transplutonium compounds; the radiation chemistry of americium; and the effects of alpha irradiation on the behavior of americium in perchlorate solutions.

Precision Interval Estimation of the Response Surface by Means of an Integrated Algorithm of Neural Network and Linear Regression

NASA Technical Reports Server (NTRS)

Lo, Ching F.

1999-01-01

The integration of Radial Basis Function Networks and Back Propagation Neural Networks with the Multiple Linear Regression has been accomplished to map nonlinear response surfaces over a wide range of independent variables in the process of the Modem Design of Experiments. The integrated method is capable to estimate the precision intervals including confidence and predicted intervals. The power of the innovative method has been demonstrated by applying to a set of wind tunnel test data in construction of response surface and estimation of precision interval.

Identifying Effective Signals to Predict Deleted and Suspended Accounts on Twitter across Languages

DOE Office of Scientific and Technical Information (OSTI.GOV)

Volkova, Svitlana; Bell, Eric B.

Social networks have an ephemerality to them where accounts and messages are constantly being edited, deleted, or marked as private. This continuous change comes from concerns around privacy, a potential desire for deception, and spam-like behavior. In this study we analyze multiple large datasets of thousands of active and deleted Twitter accounts to produce a series of predictive features for the removal or shutdown of an account. We have selected these accounts from speakers of three languages -- Russian, Spanish, and English to evaluate if speakers of various languages behave differently with regards to deleting accounts. We find that unlikemore » previously used profile and network features, the discourse of deleted vs. active accounts forms the basis for highly accurate account deletion prediction. More precisely, we observed that the presence of a certain set of terms in user tweets leads to a higher likelihood for that user's account deletion. We show that the predictive power of profile, language, affect, and network features is not consistent across speakers of the three evaluated languages.« less

Exact exchange-correlation potentials of singlet two-electron systems

NASA Astrophysics Data System (ADS)

Ryabinkin, Ilya G.; Ospadov, Egor; Staroverov, Viktor N.

2017-10-01

We suggest a non-iterative analytic method for constructing the exchange-correlation potential, v XC ( r ) , of any singlet ground-state two-electron system. The method is based on a convenient formula for v XC ( r ) in terms of quantities determined only by the system's electronic wave function, exact or approximate, and is essentially different from the Kohn-Sham inversion technique. When applied to Gaussian-basis-set wave functions, the method yields finite-basis-set approximations to the corresponding basis-set-limit v XC ( r ) , whereas the Kohn-Sham inversion produces physically inappropriate (oscillatory and divergent) potentials. The effectiveness of the procedure is demonstrated by computing accurate exchange-correlation potentials of several two-electron systems (helium isoelectronic series, H2, H3 + ) using common ab initio methods and Gaussian basis sets.

Bootstrap study of genome-enabled prediction reliabilities using haplotype blocks across Nordic Red cattle breeds.

PubMed

Cuyabano, B C D; Su, G; Rosa, G J M; Lund, M S; Gianola, D

2015-10-01

This study compared the accuracy of genome-enabled prediction models using individual single nucleotide polymorphisms (SNP) or haplotype blocks as covariates when using either a single breed or a combined population of Nordic Red cattle. The main objective was to compare predictions of breeding values of complex traits using a combined training population with haplotype blocks, with predictions using a single breed as training population and individual SNP as predictors. To compare the prediction reliabilities, bootstrap samples were taken from the test data set. With the bootstrapped samples of prediction reliabilities, we built and graphed confidence ellipses to allow comparisons. Finally, measures of statistical distances were used to calculate the gain in predictive ability. Our analyses are innovative in the context of assessment of predictive models, allowing a better understanding of prediction reliabilities and providing a statistical basis to effectively calibrate whether one prediction scenario is indeed more accurate than another. An ANOVA indicated that use of haplotype blocks produced significant gains mainly when Bayesian mixture models were used but not when Bayesian BLUP was fitted to the data. Furthermore, when haplotype blocks were used to train prediction models in a combined Nordic Red cattle population, we obtained up to a statistically significant 5.5% average gain in prediction accuracy, over predictions using individual SNP and training the model with a single breed. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Predicting two-year survival versus non-survival after first myocardial infarction using machine learning and Swedish national register data.

PubMed

Wallert, John; Tomasoni, Mattia; Madison, Guy; Held, Claes

2017-07-05

Machine learning algorithms hold potential for improved prediction of all-cause mortality in cardiovascular patients, yet have not previously been developed with high-quality population data. This study compared four popular machine learning algorithms trained on unselected, nation-wide population data from Sweden to solve the binary classification problem of predicting survival versus non-survival 2 years after first myocardial infarction (MI). This prospective national registry study for prognostic accuracy validation of predictive models used data from 51,943 complete first MI cases as registered during 6 years (2006-2011) in the national quality register SWEDEHEART/RIKS-HIA (90% coverage of all MIs in Sweden) with follow-up in the Cause of Death register (> 99% coverage). Primary outcome was AUROC (C-statistic) performance of each model on the untouched test set (40% of cases) after model development on the training set (60% of cases) with the full (39) predictor set. Model AUROCs were bootstrapped and compared, correcting the P-values for multiple comparisons with the Bonferroni method. Secondary outcomes were derived when varying sample size (1-100% of total) and predictor sets (39, 10, and 5) for each model. Analyses were repeated on 79,869 completed cases after multivariable imputation of predictors. A Support Vector Machine with a radial basis kernel developed on 39 predictors had the highest complete cases performance on the test set (AUROC = 0.845, PPV = 0.280, NPV = 0.966) outperforming Boosted C5.0 (0.845 vs. 0.841, P = 0.028) but not significantly higher than Logistic Regression or Random Forest. Models converged to the point of algorithm indifference with increased sample size and predictors. Using the top five predictors also produced good classifiers. Imputed analyses had slightly higher performance. Improved mortality prediction at hospital discharge after first MI is important for identifying high-risk individuals eligible for intensified treatment and care. All models performed accurately and similarly and because of the superior national coverage, the best model can potentially be used to better differentiate new patients, allowing for improved targeting of limited resources. Future research should focus on further model development and investigate possibilities for implementation.

Evaluation of SARs for the prediction of eye irritation/corrosion potential: structural inclusion rules in the BfR decision support system.

PubMed

Tsakovska, I; Saliner, A Gallegos; Netzeva, T; Pavan, M; Worth, A P

2007-01-01

The proposed REACH regulation within the European Union (EU) aims to minimise the number of laboratory animals used for human hazard and risk assessment while ensuring adequate protection of human health and the environment. One way to achieve this goal is to develop non-testing methods, such as (quantitative) structure-activity relationships ([Q]SARs), suitable for identifying toxicological hazard from chemical structure and physicochemical properties alone. A database containing data submitted within the EU New Chemicals Notification procedure was compiled by the German Bundesinstitut für Risikobewertung (BfR). On the basis of these data, the BfR built a decision support system (DSS) for the prediction of several toxicological endpoints. For the prediction of eye irritation and corrosion potential, the DSS contains 31 physicochemical exclusion rules evaluated previously by the European Chemicals Bureau (ECB), and 27 inclusion rules that define structural alerts potentially responsible for eye irritation and/or corrosion. This work summarises the results of a study carried out by the ECB to assess the performance of the BfR structural rulebase. The assessment included: (a) evaluation of the structural alerts by using the training set of 1341 substances with experimental data for eye irritation and corrosion; and (b) external validation by using an independent test set of 199 chemicals. Recommendations are made for the further development of the structural rules in order to increase the overall predictivity of the DSS.

A model for national outcome audit in vascular surgery.

PubMed

Prytherch, D R; Ridler, B M; Beard, J D; Earnshaw, J J

2001-06-01

The aim was to model vascular surgical outcome in a national study using POSSUM scoring. One hundred and twenty-one British and Irish surgeons completed data questionnaires on patients undergoing arterial surgery under their care (mean 12 patients, range 1-49) in May/June 1998. A total of 1480 completed data records were available for logistic regression analysis using P-POSSUM methodology. Information collected included all POSSUM data items plus other factors thought to have a significant bearing on patient outcome: "extra items". The main outcome measures were death and major postoperative complications. The data were checked and inconsistent records were excluded. The remaining 1313 were divided into two sets for analysis. The first "training" set was used to obtain logistic regression models that were applied prospectively to the second "test" dataset. using POSSUM data items alone, it was possible to predict both mortality and morbidity after vascular reconstruction using P-POSSUM analysis. The addition of the "extra items" found significant in regression analysis did not significantly improve the accuracy of prediction. It was possible to predict both mortality and morbidity derived from the preoperative physiology components of the POSSUM data items alone. this study has shown that P-POSSUM methodology can be used to predict outcome after arterial surgery across a range of surgeons in different hospitals and could form the basis of a national outcome audit. It was also possible to obtain accurate models for both mortality and major morbidity from the POSSUM physiology scores alone. Copyright 2001 Harcourt Publishers Limited.

MINS2: revisiting the molecular code for transmembrane-helix recognition by the Sec61 translocon.

PubMed

Park, Yungki; Helms, Volkhard

2008-08-15

To be fully functional, membrane proteins should not only fold, but also get inserted into the membrane, which is mediated by the Sec61 translocon. Recent experimental studies have attempted to elucidate how the Sec61 translocon accomplishes this delicate task by measuring the translocon-mediated membrane insertion free energies of 357 systematically designed peptides. On the basis of this data set, we have developed MINS2, a novel sequence-based computational method for predicting the membrane insertion free energies of protein sequences. A benchmark analysis of MINS2 shows that MINS2 signi.cantly outperforms previously proposed methods. Importantly, the application of MINS2 to known membrane protein structures shows that a better prediction of membrane insertion free energies does not lead to a better prediction of transmembrane segments of polytopic membrane proteins. A web server for MINS2 is publicly available at http://service.bioinformatik.uni-saarland.de/mins. Supplementary data are available at Bioinformatics online.

Deadline rush: a time management phenomenon and its mathematical description.

PubMed

König, Cornelius J; Kleinmann, Martin

2005-01-01

A typical time management phenomenon is the rush before a deadline. Behavioral decision making research can be used to predict how behavior changes before a deadline. People are likely not to work on a project with a deadline in the far future because they generally discount future outcomes. Only when the deadline is close are people likely to work. On the basis of recent intertemporal choice experiments, the authors argue that a hyperbolic function should provide a more accurate description of the deadline rush than an exponential function predicted by an economic model of discounted utility. To show this, the fit of the hyperbolic and the exponential function were compared with data sets that describe when students study for exams. As predicted, the hyperbolic function fit the data significantly better than the exponential function. The implication for time management decisions is that they are most likely to be inconsistent over time (i.e., people make a plan how to use their time but do not follow it).

Correlation consistent basis sets for actinides. I. The Th and U atoms.

PubMed

Peterson, Kirk A

2015-02-21

New correlation consistent basis sets based on both pseudopotential (PP) and all-electron Douglas-Kroll-Hess (DKH) Hamiltonians have been developed from double- to quadruple-zeta quality for the actinide atoms thorium and uranium. Sets for valence electron correlation (5f6s6p6d), cc - pV nZ - PP and cc - pV nZ - DK3, as well as outer-core correlation (valence + 5s5p5d), cc - pwCV nZ - PP and cc - pwCV nZ - DK3, are reported (n = D, T, Q). The -PP sets are constructed in conjunction with small-core, 60-electron PPs, while the -DK3 sets utilized the 3rd-order Douglas-Kroll-Hess scalar relativistic Hamiltonian. Both series of basis sets show systematic convergence towards the complete basis set limit, both at the Hartree-Fock and correlated levels of theory, making them amenable to standard basis set extrapolation techniques. To assess the utility of the new basis sets, extensive coupled cluster composite thermochemistry calculations of ThFn (n = 2 - 4), ThO2, and UFn (n = 4 - 6) have been carried out. After accurately accounting for valence and outer-core correlation, spin-orbit coupling, and even Lamb shift effects, the final 298 K atomization enthalpies of ThF4, ThF3, ThF2, and ThO2 are all within their experimental uncertainties. Bond dissociation energies of ThF4 and ThF3, as well as UF6 and UF5, were similarly accurate. The derived enthalpies of formation for these species also showed a very satisfactory agreement with experiment, demonstrating that the new basis sets allow for the use of accurate composite schemes just as in molecular systems composed only of lighter atoms. The differences between the PP and DK3 approaches were found to increase with the change in formal oxidation state on the actinide atom, approaching 5-6 kcal/mol for the atomization enthalpies of ThF4 and ThO2. The DKH3 atomization energy of ThO2 was calculated to be smaller than the DKH2 value by ∼1 kcal/mol.

In-flight thrust determination on a real-time basis

NASA Technical Reports Server (NTRS)

Ray, R. J.; Carpenter, T.; Sandlin, T.

1984-01-01

A real time computer program was implemented on a F-15 jet fighter to monitor in-flight engine performance of a Digital Electronic Engine Controlled (DEES) F-100 engine. The application of two gas generator methods to calculate in-flight thrust real time is described. A comparison was made between the actual results and those predicted by an engine model simulation. The percent difference between the two methods was compared to the predicted uncertainty based on instrumentation and model uncertainty and agreed closely with the results found during altitude facility testing. Data was obtained from acceleration runs of various altitudes at maximum power settings with and without afterburner. Real time in-flight thrust measurement was a major advancement to flight test productivity and was accomplished with no loss in accuracy over previous post flight methods.

Ab initio multireference study of the BN molecule

NASA Technical Reports Server (NTRS)

Martin, J. M. L.; Lee, Timothy J.; Scuseria, Gustavo E.; Taylor, Peter R.

1992-01-01

The lowest 1Sigma(+) and 3Pi states of the BN molecule are studied using multireference configuration interaction (MRCI) and averaged coupled-pair functional (ACPF) methods and large atomic natural orbital (ANO) basis sets, as well as several coupled cluster methods. Our calculations strongly support a 3Pi ground state, but the a1Sigma(+) state lies only 381 +/- 100/cm higher. The a1Sigma(+) state wave function exhibits strong multireference character and, consequently, the predictions of the perturbationally-based single-reference CCSD(T) coupled cluster method are not as reliable in this case as the multireference results. The theoretical predictions for the spectroscopic constants of BN are in good agreement with experiment for the Chi3Pi state, but strongly suggest a misassignment of the fundamental vibrational frequency for the a1Sigma(+) state.

On the basis set convergence of electron–electron entanglement measures: helium-like systems

PubMed Central

Hofer, Thomas S.

2013-01-01

A systematic investigation of three different electron–electron entanglement measures, namely the von Neumann, the linear and the occupation number entropy at full configuration interaction level has been performed for the four helium-like systems hydride, helium, Li+ and Be2+ using a large number of different basis sets. The convergence behavior of the resulting energies and entropies revealed that the latter do in general not show the expected strictly monotonic increase upon increase of the one–electron basis. Overall, the three different entanglement measures show good agreement among each other, the largest deviations being observed for small basis sets. The data clearly demonstrates that it is important to consider the nature of the chemical system when investigating entanglement phenomena in the framework of Gaussian type basis sets: while in case of hydride the use of augmentation functions is crucial, the application of core functions greatly improves the accuracy in case of cationic systems such as Li+ and Be2+. In addition, numerical derivatives of the entanglement measures with respect to the nucleic charge have been determined, which proved to be a very sensitive probe of the convergence leading to qualitatively wrong results (i.e., the wrong sign) if too small basis sets are used. PMID:24790952

On the basis set convergence of electron-electron entanglement measures: helium-like systems.

PubMed

Hofer, Thomas S

2013-01-01

A systematic investigation of three different electron-electron entanglement measures, namely the von Neumann, the linear and the occupation number entropy at full configuration interaction level has been performed for the four helium-like systems hydride, helium, Li(+) and Be(2+) using a large number of different basis sets. The convergence behavior of the resulting energies and entropies revealed that the latter do in general not show the expected strictly monotonic increase upon increase of the one-electron basis. Overall, the three different entanglement measures show good agreement among each other, the largest deviations being observed for small basis sets. The data clearly demonstrates that it is important to consider the nature of the chemical system when investigating entanglement phenomena in the framework of Gaussian type basis sets: while in case of hydride the use of augmentation functions is crucial, the application of core functions greatly improves the accuracy in case of cationic systems such as Li(+) and Be(2+). In addition, numerical derivatives of the entanglement measures with respect to the nucleic charge have been determined, which proved to be a very sensitive probe of the convergence leading to qualitatively wrong results (i.e., the wrong sign) if too small basis sets are used.

Orbital-Dependent Density Functionals for Chemical Catalysis

DTIC Science & Technology

2014-10-17

noncollinear density functional theory to show that the low-spin state of Mn3 in a model of the oxygen -evolving complex of photosystem II avoids...DK, which denotes the cc-pV5Z-DK basis set for 3d metals and hydrogen and the ma-cc- pV5Z-DK basis set for oxygen ) and to nonrelativistic all...cc-pV5Z basis set for oxygen ). As compared to NCBS-DK results, all ECP calculations perform worse than def2-TZVP all-electron relativistic

Electric dipole moment of diatomic molecules by configuration interaction. IV.

NASA Technical Reports Server (NTRS)

Green, S.

1972-01-01

The theory of basis set dependence in configuration interaction calculations is discussed, taking into account a perturbation model which is valid for small changes in the self-consistent field orbitals. It is found that basis set corrections are essentially additive through first order. It is shown that an error found in a previously published dipole moment calculation by Green (1972) for the metastable first excited state of CO was indeed due to an inadequate basis set as claimed.

Quantitative prediction of radio frequency induced local heating derived from measured magnetic field maps in magnetic resonance imaging: A phantom validation at 7 T

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Xiaotong; Liu, Jiaen; Van de Moortele, Pierre-Francois

2014-12-15

Electrical Properties Tomography (EPT) technique utilizes measurable radio frequency (RF) coil induced magnetic fields (B1 fields) in a Magnetic Resonance Imaging (MRI) system to quantitatively reconstruct the local electrical properties (EP) of biological tissues. Information derived from the same data set, e.g., complex numbers of B1 distribution towards electric field calculation, can be used to estimate, on a subject-specific basis, local Specific Absorption Rate (SAR). SAR plays a significant role in RF pulse design for high-field MRI applications, where maximum local tissue heating remains one of the most constraining limits. The purpose of the present work is to investigate themore » feasibility of such B1-based local SAR estimation, expanding on previously proposed EPT approaches. To this end, B1 calibration was obtained in a gelatin phantom at 7 T with a multi-channel transmit coil, under a particular multi-channel B1-shim setting (B1-shim I). Using this unique set of B1 calibration, local SAR distribution was subsequently predicted for B1-shim I, as well as for another B1-shim setting (B1-shim II), considering a specific set of parameter for a heating MRI protocol consisting of RF pulses plaid at 1% duty cycle. Local SAR results, which could not be directly measured with MRI, were subsequently converted into temperature change which in turn were validated against temperature changes measured by MRI Thermometry based on the proton chemical shift.« less

New Basis Functions for the Electromagnetic Solution of Arbitrarily-shaped, Three Dimensional Conducting Bodies Using Method of Moments

NASA Technical Reports Server (NTRS)

Mackenzie, Anne I.; Baginski, Michael E.; Rao, Sadasiva M.

2007-01-01

In this work, we present a new set of basis functions, de ned over a pair of planar triangular patches, for the solution of electromagnetic scattering and radiation problems associated with arbitrarily-shaped surfaces using the method of moments solution procedure. The basis functions are constant over the function subdomain and resemble pulse functions for one and two dimensional problems. Further, another set of basis functions, point-wise orthogonal to the first set, is also de ned over the same function space. The primary objective of developing these basis functions is to utilize them for the electromagnetic solution involving conducting, dielectric, and composite bodies. However, in the present work, only the conducting body solution is presented and compared with other data.

New Basis Functions for the Electromagnetic Solution of Arbitrarily-shaped, Three Dimensional Conducting Bodies using Method of Moments

NASA Technical Reports Server (NTRS)

Mackenzie, Anne I.; Baginski, Michael E.; Rao, Sadasiva M.

2008-01-01

In this work, we present a new set of basis functions, defined over a pair of planar triangular patches, for the solution of electromagnetic scattering and radiation problems associated with arbitrarily-shaped surfaces using the method of moments solution procedure. The basis functions are constant over the function subdomain and resemble pulse functions for one and two dimensional problems. Further, another set of basis functions, point-wise orthogonal to the first set, is also defined over the same function space. The primary objective of developing these basis functions is to utilize them for the electromagnetic solution involving conducting, dielectric, and composite bodies. However, in the present work, only the conducting body solution is presented and compared with other data.

Prediction of Drug-Target Interactions and Drug Repositioning via Network-Based Inference

PubMed Central

Jiang, Jing; Lu, Weiqiang; Li, Weihua; Liu, Guixia; Zhou, Weixing; Huang, Jin; Tang, Yun

2012-01-01

Drug-target interaction (DTI) is the basis of drug discovery and design. It is time consuming and costly to determine DTI experimentally. Hence, it is necessary to develop computational methods for the prediction of potential DTI. Based on complex network theory, three supervised inference methods were developed here to predict DTI and used for drug repositioning, namely drug-based similarity inference (DBSI), target-based similarity inference (TBSI) and network-based inference (NBI). Among them, NBI performed best on four benchmark data sets. Then a drug-target network was created with NBI based on 12,483 FDA-approved and experimental drug-target binary links, and some new DTIs were further predicted. In vitro assays confirmed that five old drugs, namely montelukast, diclofenac, simvastatin, ketoconazole, and itraconazole, showed polypharmacological features on estrogen receptors or dipeptidyl peptidase-IV with half maximal inhibitory or effective concentration ranged from 0.2 to 10 µM. Moreover, simvastatin and ketoconazole showed potent antiproliferative activities on human MDA-MB-231 breast cancer cell line in MTT assays. The results indicated that these methods could be powerful tools in prediction of DTIs and drug repositioning. PMID:22589709

Potential habitat distribution for the freshwater diatom Didymosphenia geminata in the continental US

USGS Publications Warehouse

Kumar, S.; Spaulding, S.A.; Stohlgren, T.J.; Hermann, K.A.; Schmidt, T.S.; Bahls, L.L.

2009-01-01

The diatom Didymosphenia geminata is a single-celled alga found in lakes, streams, and rivers. Nuisance blooms of D geminata affect the diversity, abundance, and productivity of other aquatic organisms. Because D geminata can be transported by humans on waders and other gear, accurate spatial prediction of habitat suitability is urgently needed for early detection and rapid response, as well as for evaluation of monitoring and control programs. We compared four modeling methods to predict D geminata's habitat distribution; two methods use presence-absence data (logistic regression and classification and regression tree [CART]), and two involve presence data (maximum entropy model [Maxent] and genetic algorithm for rule-set production [GARP]). Using these methods, we evaluated spatially explicit, bioclimatic and environmental variables as predictors of diatom distribution. The Maxent model provided the most accurate predictions, followed by logistic regression, CART, and GARP. The most suitable habitats were predicted to occur in the western US, in relatively cool sites, and at high elevations with a high base-flow index. The results provide insights into the factors that affect the distribution of D geminata and a spatial basis for the prediction of nuisance blooms. ?? The Ecological Society of America.

Prediction of body lipid change in pregnancy and lactation.

PubMed

Friggens, N C; Ingvartsen, K L; Emmans, G C

2004-04-01

A simple method to predict the genetically driven pattern of body lipid change through pregnancy and lactation in dairy cattle is proposed. The rationale and evidence for genetically driven body lipid change have their basis in evolutionary considerations and in the homeorhetic changes in lipid metabolism through the reproductive cycle. The inputs required to predict body lipid change are body lipid mass at calving (kg) and the date of conception (days in milk). Body lipid mass can be derived from body condition score and live weight. A key assumption is that there is a linear rate of change of the rate of body lipid change (dL/dt) between calving and a genetically determined time in lactation (T') at which a particular level of body lipid (L') is sought. A second assumption is that there is a linear rate of change of the rate of body lipid change (dL/dt) between T' and the next calving. The resulting model was evaluated using 2 sets of data. The first was from Holstein cows with 3 different levels of body fatness at calving. The second was from Jersey cows in first, second, and third parity. The model was found to reproduce the observed patterns of change in body lipid reserves through lactation in both data sets. The average error of prediction was low, less than the variation normally associated with the recording of condition score, and was similar for the 2 data sets. When the model was applied using the initially suggested parameter values derived from the literature the average error of prediction was 0.185 units of condition score (+/- 0.086 SD). After minor adjustments to the parameter values, the average error of prediction was 0.118 units of condition score (+/- 0.070 SD). The assumptions on which the model is based were sufficient to predict the changes in body lipid of both Holstein and Jersey cows under different nutritional conditions and parities. Thus, the model presented here shows that it is possible to predict genetically driven curves of body lipid change through lactation in a simple way that requires few parameters and inputs that can be derived in practice. It is expected that prediction of the cow's energy requirements can be substantially improved, particularly in early lactation, by incorporating a genetically driven body energy mobilization.

Performance of in silico prediction tools for the classification of rare BRCA1/2 missense variants in clinical diagnostics.

PubMed

Ernst, Corinna; Hahnen, Eric; Engel, Christoph; Nothnagel, Michael; Weber, Jonas; Schmutzler, Rita K; Hauke, Jan

2018-03-27

The use of next-generation sequencing approaches in clinical diagnostics has led to a tremendous increase in data and a vast number of variants of uncertain significance that require interpretation. Therefore, prediction of the effects of missense mutations using in silico tools has become a frequently used approach. Aim of this study was to assess the reliability of in silico prediction as a basis for clinical decision making in the context of hereditary breast and/or ovarian cancer. We tested the performance of four prediction tools (Align-GVGD, SIFT, PolyPhen-2, MutationTaster2) using a set of 236 BRCA1/2 missense variants that had previously been classified by expert committees. However, a major pitfall in the creation of a reliable evaluation set for our purpose is the generally accepted classification of BRCA1/2 missense variants using the multifactorial likelihood model, which is partially based on Align-GVGD results. To overcome this drawback we identified 161 variants whose classification is independent of any previous in silico prediction. In addition to the performance as stand-alone tools we examined the sensitivity, specificity, accuracy and Matthews correlation coefficient (MCC) of combined approaches. PolyPhen-2 achieved the lowest sensitivity (0.67), specificity (0.67), accuracy (0.67) and MCC (0.39). Align-GVGD achieved the highest values of specificity (0.92), accuracy (0.92) and MCC (0.73), but was outperformed regarding its sensitivity (0.90) by SIFT (1.00) and MutationTaster2 (1.00). All tools suffered from poor specificities, resulting in an unacceptable proportion of false positive results in a clinical setting. This shortcoming could not be bypassed by combination of these tools. In the best case scenario, 138 families would be affected by the misclassification of neutral variants within the cohort of patients of the German Consortium for Hereditary Breast and Ovarian Cancer. We show that due to low specificities state-of-the-art in silico prediction tools are not suitable to predict pathogenicity of variants of uncertain significance in BRCA1/2. Thus, clinical consequences should never be based solely on in silico forecasts. However, our data suggests that SIFT and MutationTaster2 could be suitable to predict benignity, as both tools did not result in false negative predictions in our analysis.

Structure and binding energy of the H2S dimer at the CCSD(T) complete basis set limit.

PubMed

Lemke, Kono H

2017-06-21

This study presents results for the binding energy and geometry of the H 2 S dimer which have been computed using Møller-Plesset perturbation theory (MP2, MP4) and coupled cluster (CCSD, CCSD(T)) calculations with basis sets up to aug-cc-pV5Z. Estimates of D e , E ZPE , D o , and dimer geometry have been obtained at each level of theory by taking advantage of the systematic convergence behavior toward the complete basis set (CBS) limit. The CBS limit binding energy values of D e are 1.91 (MP2), 1.75 (MP4), 1.41 (CCSD), and 1.69 kcal/mol (CCSD[T]). The most accurate values for the equilibrium S-S distance r SS (without counterpoise correction) are 4.080 (MP2/aug-cc-pV5Z), 4.131 (MP4/aug-cc-pVQZ), 4.225 (CCSD/aug-cc-pVQZ), and 4.146 Å (CCSD(T)/aug-cc-pVQZ). This study also evaluates the effect of counterpoise correction on the H 2 S dimer geometry and binding energy. As regards the structure of (H 2 S) 2 , MPn, CCSD, and CCSD(T) level values of r SS , obtained by performing geometry optimizations on the counterpoise-corrected potential energy surface, converge systematically to CBS limit values of 4.099 (MP2), 4.146 (MP4), 4.233 (CCSD), and 4.167 Å (CCSD(T)). The corresponding CBS limit values of the equilibrium binding energy D e are 1.88 (MP2), 1.76 (MP4), 1.41 (CCSD), and 1.69 kcal/mol (CCSD(T)), the latter in excellent agreement with the measured binding energy value of 1.68 ± 0.02 kcal/mol reported by Ciaffoni et al. [Appl. Phys. B 92, 627 (2008)]. Combining CBS electronic binding energies D e with E ZPE predicted by CCSD(T) vibrational second-order perturbation theory calculations yields D o = 1.08 kcal/mol, which is around 0.6 kcal/mol smaller than the measured value of 1.7 ± 0.3 kcal/mol. Overall, the results presented here demonstrate that the application of high level calculations, in particular CCSD(T), in combination with augmented correlation consistent basis sets provides valuable insight into the structure and energetics of the hydrogen sulfide dimer.

Structure and binding energy of the H2S dimer at the CCSD(T) complete basis set limit

NASA Astrophysics Data System (ADS)

Lemke, Kono H.

2017-06-01

This study presents results for the binding energy and geometry of the H2S dimer which have been computed using Møller-Plesset perturbation theory (MP2, MP4) and coupled cluster (CCSD, CCSD(T)) calculations with basis sets up to aug-cc-pV5Z. Estimates of De, EZPE, Do, and dimer geometry have been obtained at each level of theory by taking advantage of the systematic convergence behavior toward the complete basis set (CBS) limit. The CBS limit binding energy values of De are 1.91 (MP2), 1.75 (MP4), 1.41 (CCSD), and 1.69 kcal/mol (CCSD[T]). The most accurate values for the equilibrium S-S distance rSS (without counterpoise correction) are 4.080 (MP2/aug-cc-pV5Z), 4.131 (MP4/aug-cc-pVQZ), 4.225 (CCSD/aug-cc-pVQZ), and 4.146 Å (CCSD(T)/aug-cc-pVQZ). This study also evaluates the effect of counterpoise correction on the H2S dimer geometry and binding energy. As regards the structure of (H2S)2, MPn, CCSD, and CCSD(T) level values of rSS, obtained by performing geometry optimizations on the counterpoise-corrected potential energy surface, converge systematically to CBS limit values of 4.099 (MP2), 4.146 (MP4), 4.233 (CCSD), and 4.167 Å (CCSD(T)). The corresponding CBS limit values of the equilibrium binding energy De are 1.88 (MP2), 1.76 (MP4), 1.41 (CCSD), and 1.69 kcal/mol (CCSD(T)), the latter in excellent agreement with the measured binding energy value of 1.68 ± 0.02 kcal/mol reported by Ciaffoni et al. [Appl. Phys. B 92, 627 (2008)]. Combining CBS electronic binding energies De with EZPE predicted by CCSD(T) vibrational second-order perturbation theory calculations yields Do = 1.08 kcal/mol, which is around 0.6 kcal/mol smaller than the measured value of 1.7 ± 0.3 kcal/mol. Overall, the results presented here demonstrate that the application of high level calculations, in particular CCSD(T), in combination with augmented correlation consistent basis sets provides valuable insight into the structure and energetics of the hydrogen sulfide dimer.

A comparison of skin endpoint titration and skin-prick testing in the diagnosis of allergic rhinitis.

PubMed

Gungor, Anil; Houser, Steven M; Aquino, Benjamin F; Akbar, Imran; Moinuddin, Rizwan; Mamikoglu, Bulent; Corey, Jacquelynne P

2004-01-01

Among the many methods of allergy diagnosis are intradermal testing (IDT) and skin-prick testing (SPT). The usefulness of IDT has been called into question by some authors, while others believe that studies demonstrating that SPT was superior might have been subject to bias. We conducted a study to compare the validity of SPT and IDT--specifically, the skin endpoint titration (SET) type of IDT--in diagnosing allergic rhinitis. We performed nasal provocation testing on 62 patients to establish an unbiased screening criterion for study entry. Acoustic rhinometric measurements of the nasal responses revealed that 34 patients tested positive and 28 negative. All patients were subsequently tested by SET and SPT. We found that SPT was more sensitive (85.3 vs 79.4%) and more specific (78.6 vs 67.9%) than SET as a screening procedure. The positive predictive value of SPT was greater than that of SET (82.9 vs 75.0%), as was the negative predictive value (81.5 vs 73.0%). None of these differences was statistically significant; because of the relatively small sample size, our study was powered to show only equivalency. The results of our study suggest that the information obtained by the SET method of IDT is comparable to that obtained by SPT in terms of sensitivity, specificity, and overall performance and that both SET and SPT correlate well with nasal provocation testing for ragweed. Therefore, the decision as to which to use can be based on other factors, such as the practitioner's training, the desire for quantitative results, the desire for rapid results, and the type of treatment (i.e., immunotherapy or pharmacotherapy) that is likely to be chosen on the basis of test results.

Atomic Cholesky decompositions: a route to unbiased auxiliary basis sets for density fitting approximation with tunable accuracy and efficiency.

PubMed

Aquilante, Francesco; Gagliardi, Laura; Pedersen, Thomas Bondo; Lindh, Roland

2009-04-21

Cholesky decomposition of the atomic two-electron integral matrix has recently been proposed as a procedure for automated generation of auxiliary basis sets for the density fitting approximation [F. Aquilante et al., J. Chem. Phys. 127, 114107 (2007)]. In order to increase computational performance while maintaining accuracy, we propose here to reduce the number of primitive Gaussian functions of the contracted auxiliary basis functions by means of a second Cholesky decomposition. Test calculations show that this procedure is most beneficial in conjunction with highly contracted atomic orbital basis sets such as atomic natural orbitals, and that the error resulting from the second decomposition is negligible. We also demonstrate theoretically as well as computationally that the locality of the fitting coefficients can be controlled by means of the decomposition threshold even with the long-ranged Coulomb metric. Cholesky decomposition-based auxiliary basis sets are thus ideally suited for local density fitting approximations.

Atomic Cholesky decompositions: A route to unbiased auxiliary basis sets for density fitting approximation with tunable accuracy and efficiency

NASA Astrophysics Data System (ADS)

Aquilante, Francesco; Gagliardi, Laura; Pedersen, Thomas Bondo; Lindh, Roland

2009-04-01

Cholesky decomposition of the atomic two-electron integral matrix has recently been proposed as a procedure for automated generation of auxiliary basis sets for the density fitting approximation [F. Aquilante et al., J. Chem. Phys. 127, 114107 (2007)]. In order to increase computational performance while maintaining accuracy, we propose here to reduce the number of primitive Gaussian functions of the contracted auxiliary basis functions by means of a second Cholesky decomposition. Test calculations show that this procedure is most beneficial in conjunction with highly contracted atomic orbital basis sets such as atomic natural orbitals, and that the error resulting from the second decomposition is negligible. We also demonstrate theoretically as well as computationally that the locality of the fitting coefficients can be controlled by means of the decomposition threshold even with the long-ranged Coulomb metric. Cholesky decomposition-based auxiliary basis sets are thus ideally suited for local density fitting approximations.

Non-invasive prediction of hemoglobin levels by principal component and back propagation artificial neural network

PubMed Central

Ding, Haiquan; Lu, Qipeng; Gao, Hongzhi; Peng, Zhongqi

2014-01-01

To facilitate non-invasive diagnosis of anemia, specific equipment was developed, and non-invasive hemoglobin (HB) detection method based on back propagation artificial neural network (BP-ANN) was studied. In this paper, we combined a broadband light source composed of 9 LEDs with grating spectrograph and Si photodiode array, and then developed a high-performance spectrophotometric system. By using this equipment, fingertip spectra of 109 volunteers were measured. In order to deduct the interference of redundant data, principal component analysis (PCA) was applied to reduce the dimensionality of collected spectra. Then the principal components of the spectra were taken as input of BP-ANN model. On this basis we obtained the optimal network structure, in which node numbers of input layer, hidden layer, and output layer was 9, 11, and 1. Calibration and correction sample sets were used for analyzing the accuracy of non-invasive hemoglobin measurement, and prediction sample set was used for testing the adaptability of the model. The correlation coefficient of network model established by this method is 0.94, standard error of calibration, correction, and prediction are 11.29g/L, 11.47g/L, and 11.01g/L respectively. The result proves that there exist good correlations between spectra of three sample sets and actual hemoglobin level, and the model has a good robustness. It is indicated that the developed spectrophotometric system has potential for the non-invasive detection of HB levels with the method of BP-ANN combined with PCA. PMID:24761296

An internally consistent set of thermodynamic data for twentyone CaO-Al2O3-SiO2- H2O phases by linear parametric programming

NASA Astrophysics Data System (ADS)

Halbach, Heiner; Chatterjee, Niranjan D.

1984-11-01

The technique of linear parametric programming has been applied to derive sets of internally consistent thermodynamic data for 21 condensed phases of the quaternary system CaO-Al2O3-SiO2-H2O (CASH) (Table 4). This was achieved by simultaneously processing: a) calorimetric data for 16 of these phases (Table 1), and b) experimental phase equilibria reversal brackets for 27 reactions (Table 3) involving these phases. Calculation of equilibrium P-T curves of several arbitrarily picked reactions employing the preferred set of internally consistent thermodynamic data from Table 4 shows that the input brackets are invariably satisfied by the calculations (Fig. 2a). By contrast, the same equilibria calculated on the basis of a set of thermodynamic data derived by applying statistical methods to a large body of comparable input data (Haas et al. 1981; Hemingway et al. 1982) do not necessarily agree with the experimental reversal brackets. Prediction of some experimentally investigated phase relations not included into the linear programming input database also appears to be remarkably successful. Indications are, therefore, that the thermodynamic data listed in Table 4 may be used with confidence to predict geologic phase relations in the CASH system with considerable accuracy. For such calculated phase diagrams and their petrological implications, the reader's attention is drawn to the paper by Chatterjee et al. (1984).

Anharmonic vibrational analysis of s-trans and s-cis conformers of acryloyl fluoride using numerical-analytic Van Vleck operator perturbation theory

NASA Astrophysics Data System (ADS)

Krasnoshchekov, Sergey V.; Craig, Norman C.; Koroleva, Lidiya A.; Stepanov, Nikolay F.

2018-01-01

A new gas-phase infrared (IR) spectrum of acryloyl fluoride (ACRF, CH2dbnd CHsbnd CFdbnd O) with a resolution of 0.1 cm- 1 in the range 4000-450 cm- 1 was measured. Theoretical ab initio molecular structures, full quartic potential energy surfaces (PES), and cubic surfaces of dipole moments and polarizability tensor components (electro-optical properties, EOP) of the s-trans and s-cis conformers of the ACRF were calculated by the second-order Møller-Plesset electronic perturbation theory with a correlation consistent Dunning triple-ζ basis set. The numerical-analytic implementation of the second-order operator canonical Van Vleck perturbation theory was employed for predicting anharmonic IR and Raman scattering (RS) spectra of ACRF. To improve the anharmonic predictions, harmonic frequencies were replaced by their counterparts evaluated with the higher-level CCSD(T)/cc-pVTZ model, to form a ;hybrid; PES. The original operator representation of the Hamiltonian is analytically reduced to a quasi-diagonal form, integrated in the harmonic oscillator basis and diagonalized to account for strong resonance couplings. Double canonical transformations of EOP expansions enabled prediction of integral intensities of both fundamental and multi-quanta transitions in IR/RS spectra. Enhanced band shape analysis reinforced the assignments. A thorough interpretation of the new IR experimental spectra and existing matrix-isolation literature data for the mixture of two conformers of ACRF was accomplished, and a number of assignments clarified.

Shear Resistance between Concrete-Concrete Surfaces

NASA Astrophysics Data System (ADS)

Kovačovic, Marek

2013-12-01

The application of precast beams and cast-in-situ structural members cast at different times has been typical of bridges and buildings for many years. A load-bearing frame consists of a set of prestressed precast beams supported by columns and diaphragms joined with an additionally cast slab deck. This article is focused on the theoretical and experimental analyses of the shear resistance at an interface. The first part of the paper deals with the state-of-art knowledge of the composite behaviour of concrete-concrete structures and a comparison of the numerical methods introduced in the relevant standards. In the experimental part, a set of specimens with different interface treatments was tested until failure in order to predict the composite behaviour of coupled beams. The experimental part was compared to the numerical analysis performed by means of FEM basis nonlinear software.

Systematically convergent basis sets for transition metals. I. All-electron correlation consistent basis sets for the 3d elements Sc-Zn

NASA Astrophysics Data System (ADS)

Balabanov, Nikolai B.; Peterson, Kirk A.

2005-08-01

Sequences of basis sets that systematically converge towards the complete basis set (CBS) limit have been developed for the first-row transition metal elements Sc-Zn. Two families of basis sets, nonrelativistic and Douglas-Kroll-Hess (-DK) relativistic, are presented that range in quality from triple-ζ to quintuple-ζ. Separate sets are developed for the description of valence (3d4s) electron correlation (cc-pVnZ and cc-pVnZ-DK; n =T,Q, 5) and valence plus outer-core (3s3p3d4s) correlation (cc-pwCVnZ and cc-pwCVnZ-DK; n =T,Q, 5), as well as these sets augmented by additional diffuse functions for the description of negative ions and weak interactions (aug-cc-pVnZ and aug-cc-pVnZ-DK). Extensive benchmark calculations at the coupled cluster level of theory are presented for atomic excitation energies, ionization potentials, and electron affinities, as well as molecular calculations on selected hydrides (TiH, MnH, CuH) and other diatomics (TiF, Cu2). In addition to observing systematic convergence towards the CBS limits, both 3s3p electron correlation and scalar relativity are calculated to strongly impact many of the atomic and molecular properties investigated for these first-row transition metal species.

Gaussian basis sets for use in correlated molecular calculations. XI. Pseudopotential-based and all-electron relativistic basis sets for alkali metal (K-Fr) and alkaline earth (Ca-Ra) elements

NASA Astrophysics Data System (ADS)

Hill, J. Grant; Peterson, Kirk A.

2017-12-01

New correlation consistent basis sets based on pseudopotential (PP) Hamiltonians have been developed from double- to quintuple-zeta quality for the late alkali (K-Fr) and alkaline earth (Ca-Ra) metals. These are accompanied by new all-electron basis sets of double- to quadruple-zeta quality that have been contracted for use with both Douglas-Kroll-Hess (DKH) and eXact 2-Component (X2C) scalar relativistic Hamiltonians. Sets for valence correlation (ms), cc-pVnZ-PP and cc-pVnZ-(DK,DK3/X2C), in addition to outer-core correlation [valence + (m-1)sp], cc-p(w)CVnZ-PP and cc-pwCVnZ-(DK,DK3/X2C), are reported. The -PP sets have been developed for use with small-core PPs [I. S. Lim et al., J. Chem. Phys. 122, 104103 (2005) and I. S. Lim et al., J. Chem. Phys. 124, 034107 (2006)], while the all-electron sets utilized second-order DKH Hamiltonians for 4s and 5s elements and third-order DKH for 6s and 7s. The accuracy of the basis sets is assessed through benchmark calculations at the coupled-cluster level of theory for both atomic and molecular properties. Not surprisingly, it is found that outer-core correlation is vital for accurate calculation of the thermodynamic and spectroscopic properties of diatomic molecules containing these elements.

The Evidential Basis of Decision Making in Plant Disease Management.

PubMed

Hughes, Gareth

2017-08-04

The evidential basis for disease management decision making is provided by data relating to risk factors. The decision process involves an assessment of the evidence leading to taking (or refraining from) action on the basis of a prediction. The primary objective of the decision process is to identify-at the time the decision is made-the control action that provides the best predicted end-of-season outcome, calculated in terms of revenue or another appropriate metric. Data relating to disease risk factors may take a variety of forms (e.g., continuous, discrete, categorical) on measurement scales in a variety of units. Log 10 -likelihood ratios provide a principled basis for the accumulation of evidence based on such data and allow predictions to be made via Bayesian updating of prior probabilities.

A crash-prediction model for multilane roads.

PubMed

Caliendo, Ciro; Guida, Maurizio; Parisi, Alessandra

2007-07-01

Considerable research has been carried out in recent years to establish relationships between crashes and traffic flow, geometric infrastructure characteristics and environmental factors for two-lane rural roads. Crash-prediction models focused on multilane rural roads, however, have rarely been investigated. In addition, most research has paid but little attention to the safety effects of variables such as stopping sight distance and pavement surface characteristics. Moreover, the statistical approaches have generally included Poisson and Negative Binomial regression models, whilst Negative Multinomial regression model has been used to a lesser extent. Finally, as far as the authors are aware, prediction models involving all the above-mentioned factors have still not been developed in Italy for multilane roads, such as motorways. Thus, in this paper crash-prediction models for a four-lane median-divided Italian motorway were set up on the basis of accident data observed during a 5-year monitoring period extending between 1999 and 2003. The Poisson, Negative Binomial and Negative Multinomial regression models, applied separately to tangents and curves, were used to model the frequency of accident occurrence. Model parameters were estimated by the Maximum Likelihood Method, and the Generalized Likelihood Ratio Test was applied to detect the significant variables to be included in the model equation. Goodness-of-fit was measured by means of both the explained fraction of total variation and the explained fraction of systematic variation. The Cumulative Residuals Method was also used to test the adequacy of a regression model throughout the range of each variable. The candidate set of explanatory variables was: length (L), curvature (1/R), annual average daily traffic (AADT), sight distance (SD), side friction coefficient (SFC), longitudinal slope (LS) and the presence of a junction (J). Separate prediction models for total crashes and for fatal and injury crashes only were considered. For curves it is shown that significant variables are L, 1/R and AADT, whereas for tangents they are L, AADT and junctions. The effect of rain precipitation was analysed on the basis of hourly rainfall data and assumptions about drying time. It is shown that a wet pavement significantly increases the number of crashes. The models developed in this paper for Italian motorways appear to be useful for many applications such as the detection of critical factors, the estimation of accident reduction due to infrastructure and pavement improvement, and the predictions of accidents counts when comparing different design options. Thus this research may represent a point of reference for engineers in adjusting or designing multilane roads.

High-level ab initio calculations for the four low-lying families of minima of (H2O)(20): 1. Estimates of MP2/CBS binding energies and comparison with empirical potentials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fanourgakis, Georgios S.; Apra, Edoardo; Xantheas, Sotiris S.

2004-08-08

We report estimates of complete basis set (CBS) limits at the second-order Møller-Plesset perturbation level of theory (MP2) for the binding energies of the lowest lying isomers within each of the four major families of minima of (H2O)20. These were obtained by performing MP2 calculations with the family of correlation-consistent basis sets up to quadruple zeta quality, augmented with additional diffuse functions (aug-cc-pVnZ, n=D, T, Q). The MP2/CBS estimates are: -200.1 kcal/mol (dodecahedron, 30 hydrogen bonds), -212.6 kcal/mol (fused cubes, 36 hydrogen bonds), -215.0 (face-sharing pentagonal prisms, 35 hydrogen bonds) and –217.9 kcal/mol (edge-sharing pentagonal prisms, 34 hydrogen bonds). Themore » energetic ordering of the various (H2O)20 isomers does not follow monotonically the number of hydrogen bonds as in the case of smaller clusters such as the different isomers of the water hexamer. The dodecahedron lies ca. 18 kcal/mol higher in energy than the most stable edge-sharing pentagonal prism isomer. The TIP4P, ASP-W4, TTM2-R, AMOEBA and TTM2-F empirical potentials also predict the energetic stabilization of the edge-sharing pentagonal prisms with respect to the dodecahedron, albeit they universally underestimate the cluster binding energies with respect to the MP2/CBS result. Among them, the TTM2-F potential was found to predict the absolute cluster binding energies to within < 1% from the corresponding MP2/CBS values, whereas the error for the rest of the potentials considered in this study ranges from 3-5%.« less

Ab initio anharmonic vibrational frequency predictions for linear proton-bound complexes OC-H(+)-CO and N(2)-H(+)-N(2).

PubMed

Terrill, Kasia; Nesbitt, David J

2010-08-01

Ab initio anharmonic transition frequencies are calculated for strongly coupled (i) asymmetric and (ii) symmetric proton stretching modes in the X-H(+)-X linear ionic hydrogen bonded complexes for OCHCO(+) and N(2)HN(2)(+). The optimized potential surface is calculated in these two coordinates for each molecular ion at CCSD(T)/aug-cc-pVnZ (n = 2-4) levels and extrapolated to the complete-basis-set limit (CBS). Slices through both 2D surfaces reveal a relatively soft potential in the asymmetric proton stretching coordinate at near equilibrium geometries, which rapidly becomes a double minimum potential with increasing symmetric proton acceptor center of mass separation. Eigenvalues are obtained by solution of the 2D Schrödinger equation with potential/kinetic energy coupling explicity taken into account, converged in a distributed Gaussian basis set as a function of grid density. The asymmetric proton stretch fundamental frequency for N(2)HN(2)(+) is predicted at 848 cm(-1), with strong negative anharmonicity in the progression characteristic of a shallow "particle in a box" potential. The corresponding proton stretch fundamental for OCHCO(+) is anomalously low at 386 cm(-1), but with a strong alternation in the vibrational spacing due to the presence of a shallow D(infinityh) transition state barrier (Delta = 398 cm(-1)) between the two equivalent minimum geometries. Calculation of a 2D dipole moment surface and transition matrix elements reveals surprisingly strong combination and difference bands with appreciable intensity throughout the 300-1500 cm(-1) region. Corrected for zero point (DeltaZPE) and thermal vibrational excitation (DeltaE(vib)) at 300 K, the single and double dissociation energies in these complexes are in excellent agreement with thermochemical gas phase ion data.

Spatiotemporal progression of metastatic breast cancer: a Markov chain model highlighting the role of early metastatic sites

PubMed Central

Newton, Paul K; Mason, Jeremy; Venkatappa, Neethi; Jochelson, Maxine S; Hurt, Brian; Nieva, Jorge; Comen, Elizabeth; Norton, Larry; Kuhn, Peter

2015-01-01

Background: Cancer cell migration patterns are critical for understanding metastases and clinical evolution. Breast cancer spreads from one organ system to another via hematogenous and lymphatic routes. Although patterns of spread may superficially seem random and unpredictable, we explored the possibility that this is not the case. Aims: Develop a Markov based model of breast cancer progression that has predictive capability. Methods: On the basis of a longitudinal data set of 446 breast cancer patients, we created a Markov chain model of metastasis that describes the probabilities of metastasis occurring at a given anatomic site together with the probability of spread to additional sites. Progression is modeled as a random walk on a directed graph, where nodes represent anatomical sites where tumors can develop. Results: We quantify how survival depends on the location of the first metastatic site for different patient subcategories. In addition, we classify metastatic sites as “sponges” or “spreaders” with implications regarding anatomical pathway prediction and long-term survival. As metastatic tumors to the bone (main spreader) are most prominent, we focus in more detail on differences between groups of patients who form subsequent metastases to the lung as compared with the liver. Conclusions: We have found that spatiotemporal patterns of metastatic spread in breast cancer are neither random nor unpredictable. Furthermore, the novel concept of classifying organ sites as sponges or spreaders may motivate experiments seeking a biological basis for these phenomena and allow us to quantify the potential consequences of therapeutic targeting of sites in the oligometastatic setting and shed light on organotropic aspects of the disease. PMID:28721371

Straightening the Hierarchical Staircase for Basis Set Extrapolations: A Low-Cost Approach to High-Accuracy Computational Chemistry

NASA Astrophysics Data System (ADS)

Varandas, António J. C.

2018-04-01

Because the one-electron basis set limit is difficult to reach in correlated post-Hartree-Fock ab initio calculations, the low-cost route of using methods that extrapolate to the estimated basis set limit attracts immediate interest. The situation is somewhat more satisfactory at the Hartree-Fock level because numerical calculation of the energy is often affordable at nearly converged basis set levels. Still, extrapolation schemes for the Hartree-Fock energy are addressed here, although the focus is on the more slowly convergent and computationally demanding correlation energy. Because they are frequently based on the gold-standard coupled-cluster theory with single, double, and perturbative triple excitations [CCSD(T)], correlated calculations are often affordable only with the smallest basis sets, and hence single-level extrapolations from one raw energy could attain maximum usefulness. This possibility is examined. Whenever possible, this review uses raw data from second-order Møller-Plesset perturbation theory, as well as CCSD, CCSD(T), and multireference configuration interaction methods. Inescapably, the emphasis is on work done by the author's research group. Certain issues in need of further research or review are pinpointed.

Deciphering the distance to antibiotic resistance for the pneumococcus using genome sequencing data

PubMed Central

Mobegi, Fredrick M.; Cremers, Amelieke J. H.; de Jonge, Marien I.; Bentley, Stephen D.; van Hijum, Sacha A. F. T.; Zomer, Aldert

2017-01-01

Advances in genome sequencing technologies and genome-wide association studies (GWAS) have provided unprecedented insights into the molecular basis of microbial phenotypes and enabled the identification of the underlying genetic variants in real populations. However, utilization of genome sequencing in clinical phenotyping of bacteria is challenging due to the lack of reliable and accurate approaches. Here, we report a method for predicting microbial resistance patterns using genome sequencing data. We analyzed whole genome sequences of 1,680 Streptococcus pneumoniae isolates from four independent populations using GWAS and identified probable hotspots of genetic variation which correlate with phenotypes of resistance to essential classes of antibiotics. With the premise that accumulation of putative resistance-conferring SNPs, potentially in combination with specific resistance genes, precedes full resistance, we retrogressively surveyed the hotspot loci and quantified the number of SNPs and/or genes, which if accumulated would confer full resistance to an otherwise susceptible strain. We name this approach the ‘distance to resistance’. It can be used to identify the creep towards complete antibiotics resistance in bacteria using genome sequencing. This approach serves as a basis for the development of future sequencing-based methods for predicting resistance profiles of bacterial strains in hospital microbiology and public health settings. PMID:28205635

DOE Office of Scientific and Technical Information (OSTI.GOV)

McKemmish, Laura K., E-mail: laura.mckemmish@gmail.com; Research School of Chemistry, Australian National University, Canberra

Algorithms for the efficient calculation of two-electron integrals in the newly developed mixed ramp-Gaussian basis sets are presented, alongside a Fortran90 implementation of these algorithms, RAMPITUP. These new basis sets have significant potential to (1) give some speed-up (estimated at up to 20% for large molecules in fully optimised code) to general-purpose Hartree-Fock (HF) and density functional theory quantum chemistry calculations, replacing all-Gaussian basis sets, and (2) give very large speed-ups for calculations of core-dependent properties, such as electron density at the nucleus, NMR parameters, relativistic corrections, and total energies, replacing the current use of Slater basis functions or verymore » large specialised all-Gaussian basis sets for these purposes. This initial implementation already demonstrates roughly 10% speed-ups in HF/R-31G calculations compared to HF/6-31G calculations for large linear molecules, demonstrating the promise of this methodology, particularly for the second application. As well as the reduction in the total primitive number in R-31G compared to 6-31G, this timing advantage can be attributed to the significant reduction in the number of mathematically complex intermediate integrals after modelling each ramp-Gaussian basis-function-pair as a sum of ramps on a single atomic centre.« less

The Effect of Basis Selection on Thermal-Acoustic Random Response Prediction Using Nonlinear Modal Simulation

NASA Technical Reports Server (NTRS)

Rizzi, Stephen A.; Przekop, Adam

2004-01-01

The goal of this investigation is to further develop nonlinear modal numerical simulation methods for prediction of geometrically nonlinear response due to combined thermal-acoustic loadings. As with any such method, the accuracy of the solution is dictated by the selection of the modal basis, through which the nonlinear modal stiffness is determined. In this study, a suite of available bases are considered including (i) bending modes only; (ii) coupled bending and companion modes; (iii) uncoupled bending and companion modes; and (iv) bending and membrane modes. Comparison of these solutions with numerical simulation in physical degrees-of-freedom indicates that inclusion of any membrane mode variants (ii - iv) in the basis affects the bending displacement and stress response predictions. The most significant effect is on the membrane displacement, where it is shown that only the type (iv) basis accurately predicts its behavior. Results are presented for beam and plate structures in the thermally pre-buckled regime.

Pollen Deposition Is More Important than Species Richness for Seed Set in Luffa Gourd.

PubMed

Ali, M; Saeed, S; Sajjad, A

2016-10-01

In the context of global biodiversity decline, it is imperative to understand the different aspects of bee communities for sustaining the vital ecosystem service of pollination. Bee species can be assigned to functional groups (average difference among species in functionally related traits) on the basis of complementarity (trait variations exhibited by individual organisms) in their behavior but is not yet known which functional group trait is most important for seed set. In this study, first, the functional groups of bees were made based on their five selected traits (pollen deposition, visitation rate, stay time, visiting time of the day, body size) and then related to the seed set of obligate cross-pollinated Luffa gourd (Luffa aegyptiaca). We found that bee diversity and abundance differed significantly among the studied plots, but only the bee species richness was positively related to the seed set. Functional group diversity in terms of pollen deposition explained even more of the variance in seed set (r 2  = 0.74) than did the species richness (r 2  = 0.53) making it the most important trait of bee species for predicting the crop reproductive success.

Localization and prediction of malignant potential in recurrent pheochromocytoma/paraganglioma (PCC/PGL) using 18F-FDG PET/CT.

PubMed

Fikri, Ahmad Saad Fathinul; Kroiss, A; Ahmad, A Z F; Zanariah, H; Lau, W F E; Uprimny, C; Donnemiller, E; Kendler, D; Nordin, A J; Virgolini, I J

2014-06-01

To our knowledge, data are lacking on the role of 18F-FDG PET/CT in the localization and prediction of neuroendocrine tumors, in particular the pheochromocytoma/paraganglioma (PCC/PGL) group. To evaluate the role of 18F-FDG PET/CT in localizing and predicting the malignant potential of PCC/PGL. Twenty-three consecutive patients with a history of PCC/PGL, presenting with symptoms related to catecholamine excess, underwent 18F-FDG PET/CT. Final confirmation of the diagnosis was made using the composite references. PET/CT findings were analyzed on a per-lesion basis and a per-patient basis. Tumor SUVmax was analyzed to predict the dichotomization of patient endpoints for the local disease and metastatic groups. We investigated 23 patients (10 men, 13 women) with a mean age of 46.43 ± 3.70 years. Serum catecholamine levels were elevated in 82.60% of these patients. There were 136 sites (mean SUVmax: 16.39 ± 3.47) of validated disease recurrence. The overall sensitivities for diagnostic CT, FDG PET, and FDG PET/CT were 86.02%, 87.50%, and 98.59%, respectively. Based on the composite references, 39.10% of patients had local disease. There were significant differences in the SUVmax distribution between the local disease and metastatic groups; a significant correlation was noted when a SUVmax cut-off was set at 9.2 (P<0.05). In recurrent PCC/PGL, diagnostic 18F-FDG PET/CT is a superior tool in the localization of recurrent tumors. Tumor SUVmax is a potentially useful predictor of malignant tumor potential. © The Foundation Acta Radiologica 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Plant functional traits in relation to fire in crown-fire ecosystems

USGS Publications Warehouse

Pausas, Juli G.; Bradstock, Ross A.; Keith, David A.; Keeley, Jon E.

2004-01-01

Disturbance is a dominant factor in many ecosystems, and the disturbance regime is likely to change over the next decades in response to land-use changes and global warming. We assume that predictions of vegetation dynamics can be made on the basis of a set of life-history traits that characterize the response of a species to disturbance. For crown-fire ecosystems, the main plant traits related to postfire persistence are the ability to resprout (persistence of individuals) and the ability to retain a persistent seed bank (persistence of populations). In this context, we asked (1) to what extent do different life-history traits co-occur with the ability to resprout and/or the ability to retain a persistent seed bank among differing ecosystems and (2) to what extent do combinations of fire-related traits (fire syndromes) change in a fire regime gradient? We explored these questions by reviewing the literature and analyzing databases compiled from different crown-fire ecosystems (mainly eastern Australia, California, and the Mediterranean basin). The review suggests that the pattern of correlation between the two basic postfire persistent traits and other plant traits varies between continents and ecosystems. From these results we predict, for instance, that not all resprouters respond in a similar way everywhere because the associated plant traits of resprouter species vary in different places. Thus, attempts to generalize predictions on the basis of the resprouting capacity may have limited power at a global scale. An example is presented for Australian heathlands. Considering the combination of persistence at individual (resprouting) and at population (seed bank) level, the predictive power at local scale was significantly increased.

Quantum Mechanical Calculations of Monoxides of Silicon Carbide Molecules

DTIC Science & Technology

2003-03-01

Data for CO Final Energy Charge Mult Basis Set (hart) EA (eV) ZPE (hart) EA (eV) w/ ZPE 0 1 DVZ -112.6850703739 2.02121 -1 2 DVZ...Energy Charge Mult Basis Set (hart) EA (eV) ZPE (hart) EA (eV) w/ ZPE 0 1 DVZ -363.7341927429 0.617643 -1 2 DVZ -363.7114852831 0 3 DVZ...Input Geometry Output Geometry Basis Set Final Energy (hart) EA (eV) ZPE (hart) EA (eV) w/ ZPE -1 2 O-C-Si Linear O-C-Si Linear DZV -401.5363

Relativistic well-tempered Gaussian basis sets for helium through mercury. Breit interaction included

DOE Office of Scientific and Technical Information (OSTI.GOV)

Okada, S.; Shinada, M.; Matsuoka, O.

1990-10-01

A systematic calculation of new relativistic Gaussian basis sets is reported. The new basis sets are similar to the previously reported ones (J. Chem. Phys. {bold 91}, 4193 (1989)), but, in the calculation, the Breit interaction has been explicitly included besides the Dirac--Coulomb Hamiltonian. They have been adopted for the calculation of the self-consistent field effect on the Breit interaction energies and are expected to be useful for the studies on higher-order effects such as the electron correlations and other quantum electrodynamical effects.

Parallel Douglas-Kroll Energy and Gradients in NWChem. Estimating Scalar Relativistic Effects Using Douglas-Kroll Contracted Basis Sets.

DOE Office of Scientific and Technical Information (OSTI.GOV)

De Jong, Wibe A.; Harrison, Robert J.; Dixon, David A.

A parallel implementation of the spin-free one-electron Douglas-Kroll(-Hess) Hamiltonian (DKH) in NWChem is discussed. An efficient and accurate method to calculate DKH gradients is introduced. It is shown that the use of standard (non-relativistic) contracted basis set can produce erroneous results for elements beyond the first row elements. The generation of DKH contracted cc-pVXZ (X = D, T, Q, 5) basis sets for H, He, B - Ne, Al - Ar, and Ga - Br will be discussed.

Structure-activity relationships to estimate the effective Henry's law coefficients of organics of atmospheric interest

NASA Astrophysics Data System (ADS)

Raventos-Duran, Teresa; Valorso, Richard; Aumont, Bernard; Camredon, Marie

2010-05-01

The oxidation of volatile organic compounds emitted in the atmosphere involves complex reaction mechanisms which leads to the formation of oxygenated organic intermediates, usually denoted as secondary organics. The fate of these secondary organics remains poorly quantified due to a lack of information about their speciation, distribution and evolution in the gas and condensed phases. A significant fraction of secondary organics may dissolve into the tropospheric aqueous phase owing to the presence of polar moieties generated during the oxidation processes. The partitioning of organics between the gas and the aqueous atmospheric phases is usually described in the basis of Henry's law. Atmospheric models require a knowledge of the Henry's law coefficient (H) for every water soluble organic species described in the chemical mechanism. Methods that can predict reliable H values for the vast number of organic compounds are therefore required. We have compiled a data set of experimental Henry's law constants for compounds bearing functional groups of atmospheric relevance. This data set was then used to develop GROMHE, a structure activity relationship to predict H values based on a group contribution approach. We assessed its performance with two other available estimation methods. The results show that for all these methods the reliability of the estimates decreases with increasing solubility. We discuss differences between methods and found that GROMHE had greater prediction ability.

Does staff-patient agreement on needs for care predict a better mental health outcome? A 4-year follow-up in a community service.

PubMed

Lasalvia, A; Bonetto, C; Tansella, M; Stefani, B; Ruggeri, M

2008-01-01

Patients treated in primary care settings report better mental outcomes when they agree with practitioners about the nature of their core presenting problems. However, no study has examined the impact of staff-patient agreement on treatment outcomes in specialist mental health services. We investigated whether a better staff-patient agreement on needs for care predicts more favourable outcome in patients receiving community-based psychiatric care. A 3-month prevalence cohort of 188 patients with the full spectrum of psychiatric conditions was assessed at baseline and at 4 years using the Camberwell Assessment of Need (CAN), both staff (CAN-S) and patient versions (CAN-P), and a set of standardized outcome measures. Baseline staff-patient agreement on needs was included among predictors of outcome. Both clinician-rated (psychopathology, social disability, global functioning) and patient-rated (subjective quality of life and satisfaction with services) outcomes were considered. Controlling for the effect of sociodemographics, service utilization and changes in clinical status, better staff-patient agreement makes a significant additional contribution in predicting treatment outcomes not only on patient-rated but also on clinician-rated measures. Mental health care should be provided on the basis of a negotiation process involving both professionals and service users to ensure effective interventions; every effort should be made by services to implement strategies aiming to increase consensus between staff and patients.

Toxicology ontology perspectives.

PubMed

Hardy, Barry; Apic, Gordana; Carthew, Philip; Clark, Dominic; Cook, David; Dix, Ian; Escher, Sylvia; Hastings, Janna; Heard, David J; Jeliazkova, Nina; Judson, Philip; Matis-Mitchell, Sherri; Mitic, Dragana; Myatt, Glenn; Shah, Imran; Spjuth, Ola; Tcheremenskaia, Olga; Toldo, Luca; Watson, David; White, Andrew; Yang, Chihae

2012-01-01

The field of predictive toxicology requires the development of open, public, computable, standardized toxicology vocabularies and ontologies to support the applications required by in silico, in vitro, and in vivo toxicology methods and related analysis and reporting activities. In this article we review ontology developments based on a set of perspectives showing how ontologies are being used in predictive toxicology initiatives and applications. Perspectives on resources and initiatives reviewed include OpenTox, eTOX, Pistoia Alliance, ToxWiz, Virtual Liver, EU-ADR, BEL, ToxML, and Bioclipse. We also review existing ontology developments in neighboring fields that can contribute to establishing an ontological framework for predictive toxicology. A significant set of resources is already available to provide a foundation for an ontological framework for 21st century mechanistic-based toxicology research. Ontologies such as ToxWiz provide a basis for application to toxicology investigations, whereas other ontologies under development in the biological, chemical, and biomedical communities could be incorporated in an extended future framework. OpenTox has provided a semantic web framework for the implementation of such ontologies into software applications and linked data resources. Bioclipse developers have shown the benefit of interoperability obtained through ontology by being able to link their workbench application with remote OpenTox web services. Although these developments are promising, an increased international coordination of efforts is greatly needed to develop a more unified, standardized, and open toxicology ontology framework.

Improving accuracy and power with transfer learning using a meta-analytic database.

PubMed

Schwartz, Yannick; Varoquaux, Gaël; Pallier, Christophe; Pinel, Philippe; Poline, Jean-Baptiste; Thirion, Bertrand

2012-01-01

Typical cohorts in brain imaging studies are not large enough for systematic testing of all the information contained in the images. To build testable working hypotheses, investigators thus rely on analysis of previous work, sometimes formalized in a so-called meta-analysis. In brain imaging, this approach underlies the specification of regions of interest (ROIs) that are usually selected on the basis of the coordinates of previously detected effects. In this paper, we propose to use a database of images, rather than coordinates, and frame the problem as transfer learning: learning a discriminant model on a reference task to apply it to a different but related new task. To facilitate statistical analysis of small cohorts, we use a sparse discriminant model that selects predictive voxels on the reference task and thus provides a principled procedure to define ROIs. The benefits of our approach are twofold. First it uses the reference database for prediction, i.e., to provide potential biomarkers in a clinical setting. Second it increases statistical power on the new task. We demonstrate on a set of 18 pairs of functional MRI experimental conditions that our approach gives good prediction. In addition, on a specific transfer situation involving different scanners at different locations, we show that voxel selection based on transfer learning leads to higher detection power on small cohorts.

On the Usage of Locally Dense Basis Sets in the Calculation of NMR Indirect Nuclear Spin-Spin Coupling Constants

NASA Astrophysics Data System (ADS)

Sanchez, Marina; Provasi, Patricio F.; Aucar, Gustavo A.; Sauer, Stephan P. A.

Locally dense basis sets (

Near Hartree-Fock quality GTO basis sets for the first- and third-row atoms

NASA Technical Reports Server (NTRS)

Partridge, Harry

1989-01-01

Energy-optimized Gaussian-type-orbital (GTO) basis sets of accuracy approaching that of numerical Hartree-Fock computations are compiled for the elements of the first and third rows of the periodic table. The methods employed in calculating the sets are explained; the applicability of the sets to electronic-structure calculations is discussed; and the results are presented in tables and briefly characterized.

Computational tests of quantum chemical models for excited and ionized states of molecules with phosphorus and sulfur atoms.

PubMed

Hahn, David K; RaghuVeer, Krishans; Ortiz, J V

2014-05-15

Time-dependent density functional theory (TD-DFT) and electron propagator theory (EPT) are used to calculate the electronic transition energies and ionization energies, respectively, of species containing phosphorus or sulfur. The accuracy of TD-DFT and EPT, in conjunction with various basis sets, is assessed with data from gas-phase spectroscopy. TD-DFT is tested using 11 prominent exchange-correlation functionals on a set of 37 vertical and 19 adiabatic transitions. For vertical transitions, TD-CAM-B3LYP calculations performed with the MG3S basis set are lowest in overall error, having a mean absolute deviation from experiment of 0.22 eV, or 0.23 eV over valence transitions and 0.21 eV over Rydberg transitions. Using a larger basis set, aug-pc3, improves accuracy over the valence transitions via hybrid functionals, but improved accuracy over the Rydberg transitions is only obtained via the BMK functional. For adiabatic transitions, all hybrid functionals paired with the MG3S basis set perform well, and B98 is best, with a mean absolute deviation from experiment of 0.09 eV. The testing of EPT used the Outer Valence Green's Function (OVGF) approximation and the Partial Third Order (P3) approximation on 37 vertical first ionization energies. It is found that OVGF outperforms P3 when basis sets of at least triple-ζ quality in the polarization functions are used. The largest basis set used in this study, aug-pc3, obtained the best mean absolute error from both methods -0.08 eV for OVGF and 0.18 eV for P3. The OVGF/6-31+G(2df,p) level of theory is particularly cost-effective, yielding a mean absolute error of 0.11 eV.

Prediction of Drug-Plasma Protein Binding Using Artificial Intelligence Based Algorithms.

PubMed

Kumar, Rajnish; Sharma, Anju; Siddiqui, Mohammed Haris; Tiwari, Rajesh Kumar

2018-01-01

Plasma protein binding (PPB) has vital importance in the characterization of drug distribution in the systemic circulation. Unfavorable PPB can pose a negative effect on clinical development of promising drug candidates. The drug distribution properties should be considered at the initial phases of the drug design and development. Therefore, PPB prediction models are receiving an increased attention. In the current study, we present a systematic approach using Support vector machine, Artificial neural network, k- nearest neighbor, Probabilistic neural network, Partial least square and Linear discriminant analysis to relate various in vitro and in silico molecular descriptors to a diverse dataset of 736 drugs/drug-like compounds. The overall accuracy of Support vector machine with Radial basis function kernel came out to be comparatively better than the rest of the applied algorithms. The training set accuracy, validation set accuracy, precision, sensitivity, specificity and F1 score for the Suprort vector machine was found to be 89.73%, 89.97%, 92.56%, 87.26%, 91.97% and 0.898, respectively. This model can potentially be useful in screening of relevant drug candidates at the preliminary stages of drug design and development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Systematic study on the TD-DFT calculated electronic circular dichroism spectra of chiral aromatic nitro compounds: A comparison of B3LYP and CAM-B3LYP.

PubMed

Komjáti, Balázs; Urai, Ákos; Hosztafi, Sándor; Kökösi, József; Kováts, Benjámin; Nagy, József; Horváth, Péter

2016-02-15

B3LYP is one of the most widely used functional for the prediction of electronic circular dichroism spectra, however if the studied molecule contains aromatic nitro group computations may fail to produce reliable results. A test set of molecules of known stereochemistry were synthesized to study this phenomenon in detail. Spectra were computed by B3LYP and CAM-B3LYP functionals with 6-311++G(2d,2p) basis set. It was found that the range separated CAM-B3LYP gives better predictions than B3LYP for all test molecules. Fragment population analysis revealed that the nitro groups form highly localized molecule orbitals but the exact composition depends on the functional. CAM-B3LYP allows sufficient spatial overlap between the nitro group and distant parts of the molecule, which is necessary for the accurate description of excited states especially for charge transfer states. This phenomenon and the synthesized test molecules can be used to benchmark theoretical methods as well as to help the development of new functionals intended for spectroscopical studies. Copyright © 2015 Elsevier B.V. All rights reserved.

Predicting passenger seat comfort and discomfort on the basis of human, context and seat characteristics: a literature review.

PubMed

Hiemstra-van Mastrigt, Suzanne; Groenesteijn, Liesbeth; Vink, Peter; Kuijt-Evers, Lottie F M

2017-07-01

This literature review focused on passenger seat comfort and discomfort in a human-product-context interaction. The relationships between anthropometric variables (human level), activities (context level), seat characteristics (product level) and the perception of comfort and discomfort were studied through mediating variables, such as body posture, movement and interface pressure. It is concluded that there are correlations between anthropometric variables and interface pressure variables, and that this relationship is affected by body posture. The results of studies on the correlation between pressure variables and passenger comfort and discomfort are not in line with each other. Only associations were found between the other variables (e.g. activities and seat characteristics). A conceptual model illustrates the results of the review, but relationships could not be quantified due to a lack of statistical evidence and large differences in research set-ups between the reviewed papers. Practitioner Summary: This literature review set out to quantify the relationships between human, context and seat characteristics, and comfort and discomfort experience of passenger seats, in order to build a predictive model that can support seat designers and purchasers to make informed decisions. However, statistical evidence is lacking from existing literature.

No need for external orthogonality in subsystem density-functional theory.

PubMed

Unsleber, Jan P; Neugebauer, Johannes; Jacob, Christoph R

2016-08-03

Recent reports on the necessity of using externally orthogonal orbitals in subsystem density-functional theory (SDFT) [Annu. Rep. Comput. Chem., 8, 2012, 53; J. Phys. Chem. A, 118, 2014, 9182] are re-investigated. We show that in the basis-set limit, supermolecular Kohn-Sham-DFT (KS-DFT) densities can exactly be represented as a sum of subsystem densities, even if the subsystem orbitals are not externally orthogonal. This is illustrated using both an analytical example and in basis-set free numerical calculations for an atomic test case. We further show that even with finite basis sets, SDFT calculations using accurate reconstructed potentials can closely approach the supermolecular KS-DFT density, and that the deviations between SDFT and KS-DFT decrease as the basis-set limit is approached. Our results demonstrate that formally, there is no need to enforce external orthogonality in SDFT, even though this might be a useful strategy when developing projection-based DFT embedding schemes.

Open-ended recursive calculation of single residues of response functions for perturbation-dependent basis sets.

PubMed

Friese, Daniel H; Ringholm, Magnus; Gao, Bin; Ruud, Kenneth

2015-10-13

We present theory, implementation, and applications of a recursive scheme for the calculation of single residues of response functions that can treat perturbations that affect the basis set. This scheme enables the calculation of nonlinear light absorption properties to arbitrary order for other perturbations than an electric field. We apply this scheme for the first treatment of two-photon circular dichroism (TPCD) using London orbitals at the Hartree-Fock level of theory. In general, TPCD calculations suffer from the problem of origin dependence, which has so far been solved by using the velocity gauge for the electric dipole operator. This work now enables comparison of results from London orbital and velocity gauge based TPCD calculations. We find that the results from the two approaches both exhibit strong basis set dependence but that they are very similar with respect to their basis set convergence.

Core-core and core-valence correlation

NASA Technical Reports Server (NTRS)

Bauschlicher, Charles W., Jr.; Langhoff, Stephen R.; Taylor, Peter R.

1988-01-01

The effect of (1s) core correlation on properties and energy separations was analyzed using full configuration-interaction (FCI) calculations. The Be 1 S - 1 P, the C 3 P - 5 S and CH+ 1 Sigma + or - 1 Pi separations, and CH+ spectroscopic constants, dipole moment and 1 Sigma + - 1 Pi transition dipole moment were studied. The results of the FCI calculations are compared to those obtained using approximate methods. In addition, the generation of atomic natural orbital (ANO) basis sets, as a method for contracting a primitive basis set for both valence and core correlation, is discussed. When both core-core and core-valence correlation are included in the calculation, no suitable truncated CI approach consistently reproduces the FCI, and contraction of the basis set is very difficult. If the (nearly constant) core-core correlation is eliminated, and only the core-valence correlation is included, CASSCF/MRCI approached reproduce the FCI results and basis set contraction is significantly easier.

Ab initio electronic structure calculations for metallic intermediate band formation in photovoltaic materials

NASA Astrophysics Data System (ADS)

Wahnón, P.; Tablero, C.

2002-04-01

A metallic isolated band in the middle of the band gap of several III-V semiconductors has been predicted as photovoltaic materials with the possibility of providing substantially enhanced efficiencies. We have investigated the electronic band structures and lattice constants of GanAsmM and GanPmM with M=Sc, Ti, V, and Cr, to identify whether this isolated band is likely to exist by means of accurate calculations. For this task, we use the SIESTA program, an ab initio periodic density-functional method, fully self consistent in the local-density approximation. Norm-conserving, nonlocal pseudopotentials and confined linear combination of atomic orbitals have been used. We have carried out a case study of GanAsmTi and GanPmTi energy-band structure including analyses of the effect of the basis set, fine k-point mesh to ensure numerical convergence, structural parameters, and generalized gradient approximation for exchange and correlation corrections. We find the isolated intermediate band when one Ti atom replaces the position of one As (or P) atom in the crystal structure. For this kind of compound we show that the intermediate band relative position inside the band gap and width are sensitive to the dynamic relaxation of the crystal and the size of the basis set.

Theoretical study on Curcumin: A comparison of calculated spectroscopic properties with NMR, UV vis and IR experimental data

NASA Astrophysics Data System (ADS)

Benassi, Rois; Ferrari, Erika; Lazzari, Sandra; Spagnolo, Ferdinando; Saladini, Monica

2008-12-01

The main target of this study is a high-level computational analysis of Curcumin, employing DFT approach with two different sets of basis functions (B3LYP/6-31G ∗ and B3LYP/6-311G ∗∗). Accurate quantum mechanical studies, both in vacuum and in methanol medium, are carried out with the aim to analyze the conformational equilibria, to find the most stable equilibrium structure and to define the nature of the molecular orbitals, fundamental to explain Curcumin binding characteristic. Our theoretical calculations, performed at B3LYP/6-31G ∗ and B3LYP/6-311G ∗∗ levels both in vacuum and in methanol medium, confirm that the keto-enolic forms are more stable than the di-keto one, whose extremely low population suggests that this structure should not influence Curcumin properties. Keto-enolic form C results the most stable, independently on calculation level and solvent (methanol) effect. HOMO and LUMO molecular orbitals are calculated for all the structures with the two sets of basis with very similar results. MEPs show that the negative charge is localized on the oxygen atoms, which, in the keto-enolic forms, point in the same direction enabling metal coordination. NMR, UV-vis and FT-IR experimental data are employed in the comparison with electronic and conformational properties of Curcumin resulting from theoretical calculations. The two different calculation levels (B3LYP/6-31G ∗ and B3LYP/6-311G ∗∗) give very similar results. Good linear correlations between the experimental 1H and 13C NMR chemical shifts ( δexp), in methanol- d4 (MeOD) and DMSO- d6 (DMSO), and calculated magnetic isotropic shielding tensors ( σcalc) are found ( δexp = a · σcalc + b). A good prediction of UV-vis experimental maximum absorption ( λmax) on the basis of conformer populations is obtained. A linear relation with a good correlation coefficient is observed plotting the FT-IR experimental wavenumbers vs . the calculated ones, allowing to predict FT-IR spectra.

Numerical judgments by chimpanzees (Pan troglodytes) in a token economy.

PubMed

Beran, Michael J; Evans, Theodore A; Hoyle, Daniel

2011-04-01

We presented four chimpanzees with a series of tasks that involved comparing two token sets or comparing a token set to a quantity of food. Selected tokens could be exchanged for food items on a one-to-one basis. Chimpanzees successfully selected the larger numerical set for comparisons of 1 to 5 items when both sets were visible and when sets were presented through one-by-one addition of tokens into two opaque containers. Two of four chimpanzees used the number of tokens and food items to guide responding in all conditions, rather than relying on token color, size, total amount, or duration of set presentation. These results demonstrate that judgments of simultaneous and sequential sets of stimuli are made by some chimpanzees on the basis of the numerousness of sets rather than other non-numerical dimensions. The tokens were treated as equivalent to food items on the basis of their numerousness, and the chimpanzees maximized reward by choosing the larger number of items in all situations.

Correlation consistent basis sets for actinides. I. The Th and U atoms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peterson, Kirk A., E-mail: kipeters@wsu.edu

New correlation consistent basis sets based on both pseudopotential (PP) and all-electron Douglas-Kroll-Hess (DKH) Hamiltonians have been developed from double- to quadruple-zeta quality for the actinide atoms thorium and uranium. Sets for valence electron correlation (5f6s6p6d), cc − pV nZ − PP and cc − pV nZ − DK3, as well as outer-core correlation (valence + 5s5p5d), cc − pwCV nZ − PP and cc − pwCV nZ − DK3, are reported (n = D, T, Q). The -PP sets are constructed in conjunction with small-core, 60-electron PPs, while the -DK3 sets utilized the 3rd-order Douglas-Kroll-Hess scalar relativistic Hamiltonian. Bothmore » series of basis sets show systematic convergence towards the complete basis set limit, both at the Hartree-Fock and correlated levels of theory, making them amenable to standard basis set extrapolation techniques. To assess the utility of the new basis sets, extensive coupled cluster composite thermochemistry calculations of ThF{sub n} (n = 2 − 4), ThO{sub 2}, and UF{sub n} (n = 4 − 6) have been carried out. After accurately accounting for valence and outer-core correlation, spin-orbit coupling, and even Lamb shift effects, the final 298 K atomization enthalpies of ThF{sub 4}, ThF{sub 3}, ThF{sub 2}, and ThO{sub 2} are all within their experimental uncertainties. Bond dissociation energies of ThF{sub 4} and ThF{sub 3}, as well as UF{sub 6} and UF{sub 5}, were similarly accurate. The derived enthalpies of formation for these species also showed a very satisfactory agreement with experiment, demonstrating that the new basis sets allow for the use of accurate composite schemes just as in molecular systems composed only of lighter atoms. The differences between the PP and DK3 approaches were found to increase with the change in formal oxidation state on the actinide atom, approaching 5-6 kcal/mol for the atomization enthalpies of ThF{sub 4} and ThO{sub 2}. The DKH3 atomization energy of ThO{sub 2} was calculated to be smaller than the DKH2 value by ∼1 kcal/mol.« less

Segmented all-electron Gaussian basis sets of double and triple zeta qualities for Fr, Ra, and Ac

NASA Astrophysics Data System (ADS)

Campos, C. T.; de Oliveira, A. Z.; Ferreira, I. B.; Jorge, F. E.; Martins, L. S. C.

2017-05-01

Segmented all-electron basis sets of valence double and triple zeta qualities plus polarization functions for the elements Fr, Ra, and Ac are generated using non-relativistic and Douglas-Kroll-Hess (DKH) Hamiltonians. The sets are augmented with diffuse functions with the purpose to describe appropriately the electrons far from the nuclei. At the DKH-B3LYP level, first atomic ionization energies and bond lengths, dissociation energies, and polarizabilities of a sample of diatomics are calculated. Comparison with theoretical and experimental data available in the literature is carried out. It is verified that despite the small sizes of the basis sets, they are yet reliable.

Basis set and electron correlation effects on the polarizability and second hyperpolarizability of model open-shell π-conjugated systems

NASA Astrophysics Data System (ADS)

Champagne, Benoı̂t; Botek, Edith; Nakano, Masayoshi; Nitta, Tomoshige; Yamaguchi, Kizashi

2005-03-01

The basis set and electron correlation effects on the static polarizability (α) and second hyperpolarizability (γ) are investigated ab initio for two model open-shell π-conjugated systems, the C5H7 radical and the C6H8 radical cation in their doublet state. Basis set investigations evidence that the linear and nonlinear responses of the radical cation necessitate the use of a less extended basis set than its neutral analog. Indeed, double-zeta-type basis sets supplemented by a set of d polarization functions but no diffuse functions already provide accurate (hyper)polarizabilities for C6H8 whereas diffuse functions are compulsory for C5H7, in particular, p diffuse functions. In addition to the 6-31G*+pd basis set, basis sets resulting from removing not necessary diffuse functions from the augmented correlation consistent polarized valence double zeta basis set have been shown to provide (hyper)polarizability values of similar quality as more extended basis sets such as augmented correlation consistent polarized valence triple zeta and doubly augmented correlation consistent polarized valence double zeta. Using the selected atomic basis sets, the (hyper)polarizabilities of these two model compounds are calculated at different levels of approximation in order to assess the impact of including electron correlation. As a function of the method of calculation antiparallel and parallel variations have been demonstrated for α and γ of the two model compounds, respectively. For the polarizability, the unrestricted Hartree-Fock and unrestricted second-order Møller-Plesset methods bracket the reference value obtained at the unrestricted coupled cluster singles and doubles with a perturbative inclusion of the triples level whereas the projected unrestricted second-order Møller-Plesset results are in much closer agreement with the unrestricted coupled cluster singles and doubles with a perturbative inclusion of the triples values than the projected unrestricted Hartree-Fock results. Moreover, the differences between the restricted open-shell Hartree-Fock and restricted open-shell second-order Møller-Plesset methods are small. In what concerns the second hyperpolarizability, the unrestricted Hartree-Fock and unrestricted second-order Møller-Plesset values remain of similar quality while using spin-projected schemes fails for the charged system but performs nicely for the neutral one. The restricted open-shell schemes, and especially the restricted open-shell second-order Møller-Plesset method, provide for both compounds γ values close to the results obtained at the unrestricted coupled cluster level including singles and doubles with a perturbative inclusion of the triples. Thus, to obtain well-converged α and γ values at low-order electron correlation levels, the removal of spin contamination is a necessary but not a sufficient condition. Density-functional theory calculations of α and γ have also been carried out using several exchange-correlation functionals. Those employing hybrid exchange-correlation functionals have been shown to reproduce fairly well the reference coupled cluster polarizability and second hyperpolarizability values. In addition, inclusion of Hartree-Fock exchange is of major importance for determining accurate polarizability whereas for the second hyperpolarizability the gradient corrections are large.

A needs index for mental health care.

PubMed

Glover, G R; Robin, E; Emami, J; Arabscheibani, G R

1998-02-01

The study aimed to develop a mental illness needs index to help local managers, district purchasers and national policy makers in allocating resources. Formulae were developed by regression analysis using 1991 census data to predict the period prevalence of acute psychiatric admission from electoral wards. Census variables used were chosen on the basis of an established association with mental illness rates. Data from one English Health Service region were analysed for patterns common to wards at hospital catchment area level and patterns common to district health authorities at regional level. The North East Thames region was chosen as the setting for the study, with 7096 patients being admitted during 1991. In most, but not all, catchment areas reasonable prediction of the pattern of admission prevalence was possible using the variables chosen. However, different population characteristics predicted admission prevalence in rural and urban areas. Prediction methods based on one or two variables are thus unlikely to work in both settings. A Mental Illness Needs Index (MINI) based on social isolation, poverty, unemployment, permanent sickness and temporary and insecure housing predicted differences in admission prevalence between wards at catchment area level better than Jarman's Underprivileged Area (UPA) score [1] and between districts at regional level better than the UPA score and comparably to the York Psychiatric Index [2] (adjusted r2 at regional level (MINI 0.82, UPA 0.53, York index 0.70). District admission prevalence rates vary by a factor of three between rural and inner city areas; this difference may not fully reflect the variation in the cost of providing care. It did not prove possible to incorporate factors related to bed availability in the models used; reasons for this are discussed. Data covering other aspects of mental health care in addition to hospital admission are needed for more satisfactory modelling.

Multi-dimensional classification of GABAergic interneurons with Bayesian network-modeled label uncertainty.

PubMed

Mihaljević, Bojan; Bielza, Concha; Benavides-Piccione, Ruth; DeFelipe, Javier; Larrañaga, Pedro

2014-01-01

Interneuron classification is an important and long-debated topic in neuroscience. A recent study provided a data set of digitally reconstructed interneurons classified by 42 leading neuroscientists according to a pragmatic classification scheme composed of five categorical variables, namely, of the interneuron type and four features of axonal morphology. From this data set we now learned a model which can classify interneurons, on the basis of their axonal morphometric parameters, into these five descriptive variables simultaneously. Because of differences in opinion among the neuroscientists, especially regarding neuronal type, for many interneurons we lacked a unique, agreed-upon classification, which we could use to guide model learning. Instead, we guided model learning with a probability distribution over the neuronal type and the axonal features, obtained, for each interneuron, from the neuroscientists' classification choices. We conveniently encoded such probability distributions with Bayesian networks, calling them label Bayesian networks (LBNs), and developed a method to predict them. This method predicts an LBN by forming a probabilistic consensus among the LBNs of the interneurons most similar to the one being classified. We used 18 axonal morphometric parameters as predictor variables, 13 of which we introduce in this paper as quantitative counterparts to the categorical axonal features. We were able to accurately predict interneuronal LBNs. Furthermore, when extracting crisp (i.e., non-probabilistic) predictions from the predicted LBNs, our method outperformed related work on interneuron classification. Our results indicate that our method is adequate for multi-dimensional classification of interneurons with probabilistic labels. Moreover, the introduced morphometric parameters are good predictors of interneuron type and the four features of axonal morphology and thus may serve as objective counterparts to the subjective, categorical axonal features.

Insights into multimodal imaging classification of ADHD

PubMed Central

Colby, John B.; Rudie, Jeffrey D.; Brown, Jesse A.; Douglas, Pamela K.; Cohen, Mark S.; Shehzad, Zarrar

2012-01-01

Attention deficit hyperactivity disorder (ADHD) currently is diagnosed in children by clinicians via subjective ADHD-specific behavioral instruments and by reports from the parents and teachers. Considering its high prevalence and large economic and societal costs, a quantitative tool that aids in diagnosis by characterizing underlying neurobiology would be extremely valuable. This provided motivation for the ADHD-200 machine learning (ML) competition, a multisite collaborative effort to investigate imaging classifiers for ADHD. Here we present our ML approach, which used structural and functional magnetic resonance imaging data, combined with demographic information, to predict diagnostic status of individuals with ADHD from typically developing (TD) children across eight different research sites. Structural features included quantitative metrics from 113 cortical and non-cortical regions. Functional features included Pearson correlation functional connectivity matrices, nodal and global graph theoretical measures, nodal power spectra, voxelwise global connectivity, and voxelwise regional homogeneity. We performed feature ranking for each site and modality using the multiple support vector machine recursive feature elimination (SVM-RFE) algorithm, and feature subset selection by optimizing the expected generalization performance of a radial basis function kernel SVM (RBF-SVM) trained across a range of the top features. Site-specific RBF-SVMs using these optimal feature sets from each imaging modality were used to predict the class labels of an independent hold-out test set. A voting approach was used to combine these multiple predictions and assign final class labels. With this methodology we were able to predict diagnosis of ADHD with 55% accuracy (versus a 39% chance level in this sample), 33% sensitivity, and 80% specificity. This approach also allowed us to evaluate predictive structural and functional features giving insight into abnormal brain circuitry in ADHD. PMID:22912605

A Bayesian antedependence model for whole genome prediction.

PubMed

Yang, Wenzhao; Tempelman, Robert J

2012-04-01

Hierarchical mixed effects models have been demonstrated to be powerful for predicting genomic merit of livestock and plants, on the basis of high-density single-nucleotide polymorphism (SNP) marker panels, and their use is being increasingly advocated for genomic predictions in human health. Two particularly popular approaches, labeled BayesA and BayesB, are based on specifying all SNP-associated effects to be independent of each other. BayesB extends BayesA by allowing a large proportion of SNP markers to be associated with null effects. We further extend these two models to specify SNP effects as being spatially correlated due to the chromosomally proximal effects of causal variants. These two models, that we respectively dub as ante-BayesA and ante-BayesB, are based on a first-order nonstationary antedependence specification between SNP effects. In a simulation study involving 20 replicate data sets, each analyzed at six different SNP marker densities with average LD levels ranging from r(2) = 0.15 to 0.31, the antedependence methods had significantly (P < 0.01) higher accuracies than their corresponding classical counterparts at higher LD levels (r(2) > 0. 24) with differences exceeding 3%. A cross-validation study was also conducted on the heterogeneous stock mice data resource (http://mus.well.ox.ac.uk/mouse/HS/) using 6-week body weights as the phenotype. The antedependence methods increased cross-validation prediction accuracies by up to 3.6% compared to their classical counterparts (P < 0.001). Finally, we applied our method to other benchmark data sets and demonstrated that the antedependence methods were more accurate than their classical counterparts for genomic predictions, even for individuals several generations beyond the training data.

Risk-adjusted predictive models of mortality after index arterial operations using a minimal data set.

PubMed

Prytherch, D R; Ridler, B M F; Ashley, S

2005-06-01

Reducing the data required for a national vascular database (NVD) without compromising the statistical basis of comparative audit is an important goal. This work attempted to model outcomes (mortality and morbidity) from a small and simple subset of the NVD data items, specifically urea, sodium, potassium, haemoglobin, white cell count, age and mode of admission. Logistic regression models of risk of adverse outcome were built from the 2001 submission to the NVD using all records that contained the complete data required by the models. These models were applied prospectively against the equivalent data from the 2002 submission to the NVD. As had previously been found using the P-POSSUM (Portsmouth POSSUM) approach, although elective abdominal aortic aneurysm (AAA) repair and infrainguinal bypass (IIB) operations could be described by the same model, separate models were required for carotid endarterectomy (CEA) and emergency AAA repair. For CEA there were insufficient adverse events recorded to allow prospective testing of the models. The overall mean predicted risk of death in 530 patients undergoing elective AAA repair or IIB operations was 5.6 per cent, predicting 30 deaths. There were 28 reported deaths (chi(2) = 2.75, 4 d.f., P = 0.600; no evidence of lack of fit). Similarly, accurate predictions were obtained across a range of predicted risks as well as for patients undergoing repair of ruptured AAA and for morbidity. A 'data economic' model for risk stratification of national data is feasible. The ability to use a minimal data set may facilitate the process of comparative audit within the NVD. Copyright (c) 2005 British Journal of Surgery Society Ltd. Published by John Wiley & Sons, Ltd.

Rational Density Functional Selection Using Game Theory.

PubMed

McAnanama-Brereton, Suzanne; Waller, Mark P

2018-01-22

Theoretical chemistry has a paradox of choice due to the availability of a myriad of density functionals and basis sets. Traditionally, a particular density functional is chosen on the basis of the level of user expertise (i.e., subjective experiences). Herein we circumvent the user-centric selection procedure by describing a novel approach for objectively selecting a particular functional for a given application. We achieve this by employing game theory to identify optimal functional/basis set combinations. A three-player (accuracy, complexity, and similarity) game is devised, through which Nash equilibrium solutions can be obtained. This approach has the advantage that results can be systematically improved by enlarging the underlying knowledge base, and the deterministic selection procedure mathematically justifies the density functional and basis set selections.

Assessment of multireference approaches to explicitly correlated full configuration interaction quantum Monte Carlo

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kersten, J. A. F., E-mail: jennifer.kersten@cantab.net; Alavi, Ali, E-mail: a.alavi@fkf.mpg.de; Max Planck Institute for Solid State Research, Heisenbergstraße 1, 70569 Stuttgart

2016-08-07

The Full Configuration Interaction Quantum Monte Carlo (FCIQMC) method has proved able to provide near-exact solutions to the electronic Schrödinger equation within a finite orbital basis set, without relying on an expansion about a reference state. However, a drawback to the approach is that being based on an expansion of Slater determinants, the FCIQMC method suffers from a basis set incompleteness error that decays very slowly with the size of the employed single particle basis. The FCIQMC results obtained in a small basis set can be improved significantly with explicitly correlated techniques. Here, we present a study that assesses andmore » compares two contrasting “universal” explicitly correlated approaches that fit into the FCIQMC framework: the [2]{sub R12} method of Kong and Valeev [J. Chem. Phys. 135, 214105 (2011)] and the explicitly correlated canonical transcorrelation approach of Yanai and Shiozaki [J. Chem. Phys. 136, 084107 (2012)]. The former is an a posteriori internally contracted perturbative approach, while the latter transforms the Hamiltonian prior to the FCIQMC simulation. These comparisons are made across the 55 molecules of the G1 standard set. We found that both methods consistently reduce the basis set incompleteness, for accurate atomization energies in small basis sets, reducing the error from 28 mE{sub h} to 3-4 mE{sub h}. While many of the conclusions hold in general for any combination of multireference approaches with these methodologies, we also consider FCIQMC-specific advantages of each approach.« less

Detailed Wave Function Analysis for Multireference Methods: Implementation in the Molcas Program Package and Applications to Tetracene.

PubMed

Plasser, Felix; Mewes, Stefanie A; Dreuw, Andreas; González, Leticia

2017-11-14

High-level multireference computations on electronically excited and charged states of tetracene are performed, and the results are analyzed using an extensive wave function analysis toolbox that has been newly implemented in the Molcas program package. Aside from verifying the strong effect of dynamic correlation, this study reveals an unexpected critical influence of the atomic orbital basis set. It is shown that different polarized double-ζ basis sets produce significantly different results for energies, densities, and overall wave functions, with the best performance obtained for the atomic natural orbital (ANO) basis set by Pierloot et al. Strikingly, the ANO basis set not only reproduces the energies but also performs exceptionally well in terms of describing the diffuseness of the different states and of their attachment/detachment densities. This study, thus, not only underlines the fact that diffuse basis functions are needed for an accurate description of the electronic wave functions but also shows that, at least for the present example, it is enough to include them implicitly in the contraction scheme.

A Model-Based Prioritisation Exercise for the European Water Framework Directive

PubMed Central

Daginnus, Klaus; Gottardo, Stefania; Payá-Pérez, Ana; Whitehouse, Paul; Wilkinson, Helen; Zaldívar, José-Manuel

2011-01-01

A model-based prioritisation exercise has been carried out for the Water Framework Directive (WFD) implementation. The approach considers two aspects: the hazard of a certain chemical and its exposure levels, and focuses on aquatic ecosystems, but also takes into account hazards due to secondary poisoning, bioaccumulation through the food chain and potential human health effects. A list provided by EU Member States, Stakeholders and Non-Governmental Organizations comprising 2,034 substances was evaluated according to hazard and exposure criteria. Then 78 substances classified as “of high concern” where analysed and ranked in terms of risk ratio (Predicted Environmental Concentration/Predicted No-Effect Concentration). This exercise has been complemented by a monitoring-based prioritization exercise using data provided by Member States. The proposed approach constitutes the first step in setting the basis for an open modular screening tool that could be used for the next prioritization exercises foreseen by the WFD. PMID:21556195

Theory of quantized systems: formal basis for DEVS/HLA distributed simulation environment

NASA Astrophysics Data System (ADS)

Zeigler, Bernard P.; Lee, J. S.

1998-08-01

In the context of a DARPA ASTT project, we are developing an HLA-compliant distributed simulation environment based on the DEVS formalism. This environment will provide a user- friendly, high-level tool-set for developing interoperable discrete and continuous simulation models. One application is the study of contract-based predictive filtering. This paper presents a new approach to predictive filtering based on a process called 'quantization' to reduce state update transmission. Quantization, which generates state updates only at quantum level crossings, abstracts a sender model into a DEVS representation. This affords an alternative, efficient approach to embedding continuous models within distributed discrete event simulations. Applications of quantization to message traffic reduction are discussed. The theory has been validated by DEVSJAVA simulations of test cases. It will be subject to further test in actual distributed simulations using the DEVS/HLA modeling and simulation environment.

Principles of assembly reveal a periodic table of protein complexes.

PubMed

Ahnert, Sebastian E; Marsh, Joseph A; Hernández, Helena; Robinson, Carol V; Teichmann, Sarah A

2015-12-11

Structural insights into protein complexes have had a broad impact on our understanding of biological function and evolution. In this work, we sought a comprehensive understanding of the general principles underlying quaternary structure organization in protein complexes. We first examined the fundamental steps by which protein complexes can assemble, using experimental and structure-based characterization of assembly pathways. Most assembly transitions can be classified into three basic types, which can then be used to exhaustively enumerate a large set of possible quaternary structure topologies. These topologies, which include the vast majority of observed protein complex structures, enable a natural organization of protein complexes into a periodic table. On the basis of this table, we can accurately predict the expected frequencies of quaternary structure topologies, including those not yet observed. These results have important implications for quaternary structure prediction, modeling, and engineering. Copyright © 2015, American Association for the Advancement of Science.

Prediction of human errors by maladaptive changes in event-related brain networks.

PubMed

Eichele, Tom; Debener, Stefan; Calhoun, Vince D; Specht, Karsten; Engel, Andreas K; Hugdahl, Kenneth; von Cramon, D Yves; Ullsperger, Markus

2008-04-22

Humans engaged in monotonous tasks are susceptible to occasional errors that may lead to serious consequences, but little is known about brain activity patterns preceding errors. Using functional MRI and applying independent component analysis followed by deconvolution of hemodynamic responses, we studied error preceding brain activity on a trial-by-trial basis. We found a set of brain regions in which the temporal evolution of activation predicted performance errors. These maladaptive brain activity changes started to evolve approximately 30 sec before the error. In particular, a coincident decrease of deactivation in default mode regions of the brain, together with a decline of activation in regions associated with maintaining task effort, raised the probability of future errors. Our findings provide insights into the brain network dynamics preceding human performance errors and suggest that monitoring of the identified precursor states may help in avoiding human errors in critical real-world situations.

Prediction of human errors by maladaptive changes in event-related brain networks

PubMed Central

Eichele, Tom; Debener, Stefan; Calhoun, Vince D.; Specht, Karsten; Engel, Andreas K.; Hugdahl, Kenneth; von Cramon, D. Yves; Ullsperger, Markus

2008-01-01

Humans engaged in monotonous tasks are susceptible to occasional errors that may lead to serious consequences, but little is known about brain activity patterns preceding errors. Using functional MRI and applying independent component analysis followed by deconvolution of hemodynamic responses, we studied error preceding brain activity on a trial-by-trial basis. We found a set of brain regions in which the temporal evolution of activation predicted performance errors. These maladaptive brain activity changes started to evolve ≈30 sec before the error. In particular, a coincident decrease of deactivation in default mode regions of the brain, together with a decline of activation in regions associated with maintaining task effort, raised the probability of future errors. Our findings provide insights into the brain network dynamics preceding human performance errors and suggest that monitoring of the identified precursor states may help in avoiding human errors in critical real-world situations. PMID:18427123

Imaging Heterogeneity in Lung Cancer: Techniques, Applications, and Challenges.

PubMed

Bashir, Usman; Siddique, Muhammad Musib; Mclean, Emma; Goh, Vicky; Cook, Gary J

2016-09-01

Texture analysis involves the mathematic processing of medical images to derive sets of numeric quantities that measure heterogeneity. Studies on lung cancer have shown that texture analysis may have a role in characterizing tumors and predicting patient outcome. This article outlines the mathematic basis of and the most recent literature on texture analysis in lung cancer imaging. We also describe the challenges facing the clinical implementation of texture analysis. Texture analysis of lung cancer images has been applied successfully to FDG PET and CT scans. Different texture parameters have been shown to be predictive of the nature of disease and of patient outcome. In general, it appears that more heterogeneous tumors on imaging tend to be more aggressive and to be associated with poorer outcomes and that tumor heterogeneity on imaging decreases with treatment. Despite these promising results, there is a large variation in the reported data and strengths of association.

Terahertz laser spectroscopy of the water dimer intermolecular vibrations. I. (D2O)2

NASA Astrophysics Data System (ADS)

Braly, L. B.; Cruzan, J. D.; Liu, K.; Fellers, R. S.; Saykally, R. J.

2000-06-01

Terahertz laser VRT spectra of the water dimer consisting of 731 transitions measured with an average precision of 2 MHz and involving four (D2O)2 intermolecular vibrations (one previously published) have been measured between 65 and 104 cm-1. The precisely determined energy level patterns differ both qualitatively and quantitatively from the predictions of several dimer potentials tested, and reveal an ordering of the intermolecular vibrations which differs dramatically from that predicted by standard normal mode analysis. Strong coupling is indicated between the low barrier tunneling motions and the intermolecular vibrations as well as among different vibrations. Particularly, the 83 cm-1 (acceptor wag) and 90 cm-1 (D2O)2 (acceptor twist) vibrations interact through a Coriolis perturbation. These spectra provide the basis for our recent determination of the water pair potential. The corresponding data set for (H2O)2 is presented in an accompanying paper.

Real-time flight conflict detection and release based on Multi-Agent system

NASA Astrophysics Data System (ADS)

Zhang, Yifan; Zhang, Ming; Yu, Jue

2018-01-01

This paper defines two-aircrafts, multi-aircrafts and fleet conflict mode, sets up space-time conflict reservation on the basis of safety interval and conflict warning time in three-dimension. Detect real-time flight conflicts combined with predicted flight trajectory of other aircrafts in the same airspace, and put forward rescue resolutions for the three modes respectively. When accorded with the flight conflict conditions, determine the conflict situation, and enter the corresponding conflict resolution procedures, so as to avoid the conflict independently, as well as ensure the flight safety of aimed aircraft. Lastly, the correctness of model is verified with numerical simulation comparison.

Modeling electrochromic poly-dioxythiophene-containing materials through TDDFT.

PubMed

Wheeler, D L; Rainwater, L E; Green, A R; Tomlinson, A L

2017-08-02

A DFT/TDDFT model was developed to predict the chemical properties for three colored to nearly transmissive electrochromic polymers synthesized by the John Reynolds's group. Using a functional-basis set pairing of mPW1PBE/cc-PVDZ along with the conductor polarizable calculation model (CPCM), simulated neutral spectra showed a strong correlation to the experimental UV-Vis data where the largest absolute peak maximum difference was 14 nm. Frontier molecular orbitals, electronic transitions, and ground-state geometries of these systems were evaluated to provide further information about the oxidative process the polymers undergo. Here we report the first colorimetric model using this level of theory.

A control system for orbiting tethered-body operations

NASA Technical Reports Server (NTRS)

Eades, J. B., Jr.

1975-01-01

This paper shows that through proper control logic the transfer of men and cargo between spacecrafts, or the 'positioning of packages' adjacent to orbiters, can be accomodated safely and predictably using tethers. Also, these systems may be adapted to rescue and retrieval operations where 'controlled motions' must be maintained. Shown here is a method which illustrates how tethered-body motions are controlled for 'reel-in' and 'reel-out' operations, and for precise 'positioning' purposes. Three control modes are examined; from these are derived sets of universal control parameters capable of predescribing systems of similar types. In addition, these parameters form a basis for designing tethered-body systems and operations.

Callanish, a Scottish Stonehenge: A group of standing stones was used by Stone Age man to mark the seasons and perhaps to predict eclipse seasons.

PubMed

Hawkins, G S

1965-01-08

On the basis of the stone record it appears that the Callanish people were as precise as the Stonehengers in setting up their megalithic structure, but not as scientifically advanced. Callanish is, however, a structure that could have been used much as Stonehenge was. It would be interesting to obtain a date, by the radiocarbon method, for the peat in the area of Callanish, to determine how much older, or more recent, than Stonehenge this structure is. Perhaps the knowledge gained at Callanish was later used in the design of Stonehenge.

UK-5 Van Allen belt radiation exposure: A special study to determine the trapped particle intensities on the UK-5 satellite with spatial mapping of the ambient flux environment

NASA Technical Reports Server (NTRS)

Stassinopoulos, E. G.

1972-01-01

Vehicle encountered electron and proton fluxes were calculated for a set of nominal UK-5 trajectories with new computational methods and new electron environment models. Temporal variations in the electron data were considered and partially accounted for. Field strength calculations were performed with an extrapolated model on the basis of linear secular variation predictions. Tabular maps for selected electron and proton energies were constructed as functions of latitude and longitude for specified altitudes. Orbital flux integration results are presented in graphical and tabular form; they are analyzed, explained, and discussed.

Geodetic measurement of deformation in the Loma Prieta, California earthquake with very long baseline interferometry

NASA Technical Reports Server (NTRS)

Clark, T. A.; Ma, C.; Sauber, J. M.; Ryan, J. W.; Gordon, D.; Shaffer, D. B.; Carprette, D. S.; Vandenberg, N. R.

1990-01-01

VLBI measurements were conducted immediately after the Loma Prieta earthquake and compared with VLBI gathered at Monterey, San Francisco, and Point Reyes since 1983 to obtain preearthquake deformation rates with respect to a North American reference frame. The estimated displacements at Monterey and San Francisco are consistent with the static displacements predicted on the basis of a coseismic slip model in which slip on the southern segment is shallower than slip on the northern segment of the fault rupture. Cartesian positions are presented at epoch 1990.0 of a set of VLBI fiducial stations and the three mobile sites in the earthquake's vicinity.

Dynamic least-squares kernel density modeling of Fokker-Planck equations with application to neural population.

PubMed

Shotorban, Babak

2010-04-01

The dynamic least-squares kernel density (LSQKD) model [C. Pantano and B. Shotorban, Phys. Rev. E 76, 066705 (2007)] is used to solve the Fokker-Planck equations. In this model the probability density function (PDF) is approximated by a linear combination of basis functions with unknown parameters whose governing equations are determined by a global least-squares approximation of the PDF in the phase space. In this work basis functions are set to be Gaussian for which the mean, variance, and covariances are governed by a set of partial differential equations (PDEs) or ordinary differential equations (ODEs) depending on what phase-space variables are approximated by Gaussian functions. Three sample problems of univariate double-well potential, bivariate bistable neurodynamical system [G. Deco and D. Martí, Phys. Rev. E 75, 031913 (2007)], and bivariate Brownian particles in a nonuniform gas are studied. The LSQKD is verified for these problems as its results are compared against the results of the method of characteristics in nondiffusive cases and the stochastic particle method in diffusive cases. For the double-well potential problem it is observed that for low to moderate diffusivity the dynamic LSQKD well predicts the stationary PDF for which there is an exact solution. A similar observation is made for the bistable neurodynamical system. In both these problems least-squares approximation is made on all phase-space variables resulting in a set of ODEs with time as the independent variable for the Gaussian function parameters. In the problem of Brownian particles in a nonuniform gas, this approximation is made only for the particle velocity variable leading to a set of PDEs with time and particle position as independent variables. Solving these PDEs, a very good performance by LSQKD is observed for a wide range of diffusivities.

An automated benchmarking platform for MHC class II binding prediction methods.

PubMed

Andreatta, Massimo; Trolle, Thomas; Yan, Zhen; Greenbaum, Jason A; Peters, Bjoern; Nielsen, Morten

2018-05-01

Computational methods for the prediction of peptide-MHC binding have become an integral and essential component for candidate selection in experimental T cell epitope discovery studies. The sheer amount of published prediction methods-and often discordant reports on their performance-poses a considerable quandary to the experimentalist who needs to choose the best tool for their research. With the goal to provide an unbiased, transparent evaluation of the state-of-the-art in the field, we created an automated platform to benchmark peptide-MHC class II binding prediction tools. The platform evaluates the absolute and relative predictive performance of all participating tools on data newly entered into the Immune Epitope Database (IEDB) before they are made public, thereby providing a frequent, unbiased assessment of available prediction tools. The benchmark runs on a weekly basis, is fully automated, and displays up-to-date results on a publicly accessible website. The initial benchmark described here included six commonly used prediction servers, but other tools are encouraged to join with a simple sign-up procedure. Performance evaluation on 59 data sets composed of over 10 000 binding affinity measurements suggested that NetMHCIIpan is currently the most accurate tool, followed by NN-align and the IEDB consensus method. Weekly reports on the participating methods can be found online at: http://tools.iedb.org/auto_bench/mhcii/weekly/. mniel@bioinformatics.dtu.dk. Supplementary data are available at Bioinformatics online.

On the vibrational spectra and structural parameters of methyl, silyl, and germyl azide from theoretical predictions and experimental data.

PubMed

Durig, Douglas T; Durig, M S; Durig, James R

2005-05-01

The infrared and Raman spectra of methyl, silyl, and germyl azide (XN3 where X=CH3, SiH3 and GeH3) have been predicted from ab initio calculations with full electron correlation by second order perturbation theory (MP2) and hybrid density function theory (DFT) by the B3LYP method with a variety of basis sets. These predicted data are compared to previously reported experimental data and complete vibrational assignments are provided for all three molecules. It is shown that several of the assignments recently proposed [J. Mol. Struct. (Theochem.) 434 (1998) 1] for methyl azide are not correct. Structural parameters for CH3N3 and GeH3N3 have been obtained by combining the previously reported microwave rotational constants with the ab initio MP2/6-311+G(d,p) predicted values. These "adjusted r0" parameters have very small uncertainties of +/-0.003 A for the XH distances and a maximum of +/-0.005 A for the heavy atom distances and +/-0.5 degrees for the angles. The predicted distance for the terminal NN bond which is nearly a triple bond is much better predicted by the B3LYP calculations, whereas the fundamental frequencies are better predicted by the scaled ab initio calculations. The results are discussed and compared to those obtained for some similar molecules.

Improved Outcome Prediction Using CT Angiography in Addition to Standard Ischemic Stroke Assessment: Results from the STOPStroke Study

PubMed Central

González, R. Gilberto; Lev, Michael H.; Goldmacher, Gregory V.; Smith, Wade S.; Payabvash, Seyedmehdi; Harris, Gordon J.; Halpern, Elkan F.; Koroshetz, Walter J.; Camargo, Erica C. S.; Dillon, William P.; Furie, Karen L.

2012-01-01

Purpose To improve ischemic stroke outcome prediction using imaging information from a prospective cohort who received admission CT angiography (CTA). Methods In a prospectively designed study, 649 stroke patients diagnosed with acute ischemic stroke had admission NIH stroke scale scores, noncontrast CT (NCCT), CTA, and 6-month outcome assessed using the modified Rankin scale (mRS) scores. Poor outcome was defined as mRS>2. Strokes were classified as “major” by the (1) Alberta Stroke Program Early CT Score (ASPECTS+) if NCCT ASPECTS was≤7; (2) Boston Acute Stroke Imaging Scale (BASIS+) if they were ASPECTS+ or CTA showed occlusion of the distal internal carotid, proximal middle cerebral, or basilar arteries; and (3) NIHSS for scores>10. Results Of 649 patients, 253 (39.0%) had poor outcomes. NIHSS, BASIS, and age, but not ASPECTS, were independent predictors of outcome. BASIS and NIHSS had similar sensitivities, both superior to ASPECTS (p<0.0001). Combining NIHSS with BASIS was highly predictive: 77.6% (114/147) classified as NIHSS>10/BASIS+ had poor outcomes, versus 21.5% (77/358) with NIHSS≤10/BASIS− (p<0.0001), regardless of treatment. The odds ratios for poor outcome is 12.6 (95% CI: 7.9 to 20.0) in patients who are NIHSS>10/BASIS+ compared to patients who are NIHSS≤10/BASIS−; the odds ratio is 5.4 (95% CI: 3.5 to 8.5) when compared to patients who are only NIHSS>10 or BASIS+. Conclusions BASIS and NIHSS are independent outcome predictors. Their combination is stronger than either instrument alone in predicting outcomes. The findings suggest that CTA is a significant clinical tool in routine acute stroke assessment. PMID:22276182

Composite thermochemistry of gas phase U(VI)-containing molecules

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bross, David H.; Peterson, Kirk A., E-mail: kipeters@wsu.edu

Reaction energies have been calculated for a series of reactions involving UF{sub 6}, UO{sub 3}, UO{sub 2}(OH){sub 2}, and UO{sub 2}F{sub 2} using coupled cluster singles and doubles with perturbative triples, CCSD(T), with a series of correlation consistent basis sets, including newly developed pseudopotential (PP)- and all-electron (AE) Douglas-Kroll-Hess-based sets for the U atom. The energies were calculated using a Feller-Peterson-Dixon composite approach in which CCSD(T) complete basis set (CBS) limits were combined with a series of additive contributions for spin-orbit coupling, outer-core correlation, and quantum electrodynamics effects. The calculated reaction enthalpies (both PP and AE) were combined with themore » accurately known heat of formation of UF{sub 6} to determine the enthalpies of formation of UO{sub 3}, UO{sub 2}(OH){sub 2}, and UO{sub 2}F{sub 2}. The contribution to the reaction enthalpies due to correlation of the 5s5p5d electrons of U was observed to be very slowly convergent with basis set and at the CBS limit their impact on the final enthalpies was on the order of 1 kcal/mol or less. For these closed shell molecules, spin-orbit effects contributed about 1 kcal/mol to the final enthalpies. Interestingly, the PP and AE approaches yielded quite different spin-orbit contributions (similar magnitude but opposite in sign), but the total scalar plus spin-orbit results from the two approaches agreed to within ∼1 kcal/mol of each other. The final composite heat of formation for UO{sub 2}F{sub 2} was in excellent agreement with experiment, while the two results obtained for UO{sub 3} were just outside the ±2.4 kcal/mol error bars of the currently recommended experimental value. An improved enthalpy of formation (298 K) for UO{sub 2}(OH){sub 2} is predicted from this work to be −288.7 ± 3 kcal/mol, compared to the currently accepted experimental value of −292.7 ± 6 kcal/mol.« less

Computational prediction of human salivary proteins from blood circulation and application to diagnostic biomarker identification.

PubMed

Wang, Jiaxin; Liang, Yanchun; Wang, Yan; Cui, Juan; Liu, Ming; Du, Wei; Xu, Ying

2013-01-01

Proteins can move from blood circulation into salivary glands through active transportation, passive diffusion or ultrafiltration, some of which are then released into saliva and hence can potentially serve as biomarkers for diseases if accurately identified. We present a novel computational method for predicting salivary proteins that come from circulation. The basis for the prediction is a set of physiochemical and sequence features we found to be discerning between human proteins known to be movable from circulation to saliva and proteins deemed to be not in saliva. A classifier was trained based on these features using a support-vector machine to predict protein secretion into saliva. The classifier achieved 88.56% average recall and 90.76% average precision in 10-fold cross-validation on the training data, indicating that the selected features are informative. Considering the possibility that our negative training data may not be highly reliable (i.e., proteins predicted to be not in saliva), we have also trained a ranking method, aiming to rank the known salivary proteins from circulation as the highest among the proteins in the general background, based on the same features. This prediction capability can be used to predict potential biomarker proteins for specific human diseases when coupled with the information of differentially expressed proteins in diseased versus healthy control tissues and a prediction capability for blood-secretory proteins. Using such integrated information, we predicted 31 candidate biomarker proteins in saliva for breast cancer.

Computational Prediction of Human Salivary Proteins from Blood Circulation and Application to Diagnostic Biomarker Identification

PubMed Central

Wang, Jiaxin; Liang, Yanchun; Wang, Yan; Cui, Juan; Liu, Ming; Du, Wei; Xu, Ying

2013-01-01

Proteins can move from blood circulation into salivary glands through active transportation, passive diffusion or ultrafiltration, some of which are then released into saliva and hence can potentially serve as biomarkers for diseases if accurately identified. We present a novel computational method for predicting salivary proteins that come from circulation. The basis for the prediction is a set of physiochemical and sequence features we found to be discerning between human proteins known to be movable from circulation to saliva and proteins deemed to be not in saliva. A classifier was trained based on these features using a support-vector machine to predict protein secretion into saliva. The classifier achieved 88.56% average recall and 90.76% average precision in 10-fold cross-validation on the training data, indicating that the selected features are informative. Considering the possibility that our negative training data may not be highly reliable (i.e., proteins predicted to be not in saliva), we have also trained a ranking method, aiming to rank the known salivary proteins from circulation as the highest among the proteins in the general background, based on the same features. This prediction capability can be used to predict potential biomarker proteins for specific human diseases when coupled with the information of differentially expressed proteins in diseased versus healthy control tissues and a prediction capability for blood-secretory proteins. Using such integrated information, we predicted 31 candidate biomarker proteins in saliva for breast cancer. PMID:24324552

A novel stock forecasting model based on High-order-fuzzy-fluctuation Trends and Back Propagation Neural Network

PubMed Central

Dai, Zongli; Zhao, Aiwu; He, Jie

2018-01-01

In this paper, we propose a hybrid method to forecast the stock prices called High-order-fuzzy-fluctuation-Trends-based Back Propagation(HTBP)Neural Network model. First, we compare each value of the historical training data with the previous day's value to obtain a fluctuation trend time series (FTTS). On this basis, the FTTS blur into fuzzy time series (FFTS) based on the fluctuation of the increasing, equality, decreasing amplitude and direction. Since the relationship between FFTS and future wave trends is nonlinear, the HTBP neural network algorithm is used to find the mapping rules in the form of self-learning. Finally, the results of the algorithm output are used to predict future fluctuations. The proposed model provides some innovative features:(1)It combines fuzzy set theory and neural network algorithm to avoid overfitting problems existed in traditional models. (2)BP neural network algorithm can intelligently explore the internal rules of the actual existence of sequential data, without the need to analyze the influence factors of specific rules and the path of action. (3)The hybrid modal can reasonably remove noises from the internal rules by proper fuzzy treatment. This paper takes the TAIEX data set of Taiwan stock exchange as an example, and compares and analyzes the prediction performance of the model. The experimental results show that this method can predict the stock market in a very simple way. At the same time, we use this method to predict the Shanghai stock exchange composite index, and further verify the effectiveness and universality of the method. PMID:29420584

A novel stock forecasting model based on High-order-fuzzy-fluctuation Trends and Back Propagation Neural Network.

PubMed

Guan, Hongjun; Dai, Zongli; Zhao, Aiwu; He, Jie

2018-01-01

In this paper, we propose a hybrid method to forecast the stock prices called High-order-fuzzy-fluctuation-Trends-based Back Propagation(HTBP)Neural Network model. First, we compare each value of the historical training data with the previous day's value to obtain a fluctuation trend time series (FTTS). On this basis, the FTTS blur into fuzzy time series (FFTS) based on the fluctuation of the increasing, equality, decreasing amplitude and direction. Since the relationship between FFTS and future wave trends is nonlinear, the HTBP neural network algorithm is used to find the mapping rules in the form of self-learning. Finally, the results of the algorithm output are used to predict future fluctuations. The proposed model provides some innovative features:(1)It combines fuzzy set theory and neural network algorithm to avoid overfitting problems existed in traditional models. (2)BP neural network algorithm can intelligently explore the internal rules of the actual existence of sequential data, without the need to analyze the influence factors of specific rules and the path of action. (3)The hybrid modal can reasonably remove noises from the internal rules by proper fuzzy treatment. This paper takes the TAIEX data set of Taiwan stock exchange as an example, and compares and analyzes the prediction performance of the model. The experimental results show that this method can predict the stock market in a very simple way. At the same time, we use this method to predict the Shanghai stock exchange composite index, and further verify the effectiveness and universality of the method.