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Sample records for accurate prediction results

  1. Infectious titres of sheep scrapie and bovine spongiform encephalopathy agents cannot be accurately predicted from quantitative laboratory test results.

    PubMed

    González, Lorenzo; Thorne, Leigh; Jeffrey, Martin; Martin, Stuart; Spiropoulos, John; Beck, Katy E; Lockey, Richard W; Vickery, Christopher M; Holder, Thomas; Terry, Linda

    2012-11-01

    It is widely accepted that abnormal forms of the prion protein (PrP) are the best surrogate marker for the infectious agent of prion diseases and, in practice, the detection of such disease-associated (PrP(d)) and/or protease-resistant (PrP(res)) forms of PrP is the cornerstone of diagnosis and surveillance of the transmissible spongiform encephalopathies (TSEs). Nevertheless, some studies question the consistent association between infectivity and abnormal PrP detection. To address this discrepancy, 11 brain samples of sheep affected with natural scrapie or experimental bovine spongiform encephalopathy were selected on the basis of the magnitude and predominant types of PrP(d) accumulation, as shown by immunohistochemical (IHC) examination; contra-lateral hemi-brain samples were inoculated at three different dilutions into transgenic mice overexpressing ovine PrP and were also subjected to quantitative analysis by three biochemical tests (BCTs). Six samples gave 'low' infectious titres (10⁶·⁵ to 10⁶·⁷ LD₅₀ g⁻¹) and five gave 'high titres' (10⁸·¹ to ≥ 10⁸·⁷ LD₅₀ g⁻¹) and, with the exception of the Western blot analysis, those two groups tended to correspond with samples with lower PrP(d)/PrP(res) results by IHC/BCTs. However, no statistical association could be confirmed due to high individual sample variability. It is concluded that although detection of abnormal forms of PrP by laboratory methods remains useful to confirm TSE infection, infectivity titres cannot be predicted from quantitative test results, at least for the TSE sources and host PRNP genotypes used in this study. Furthermore, the near inverse correlation between infectious titres and Western blot results (high protease pre-treatment) argues for a dissociation between infectivity and PrP(res).

  2. New model accurately predicts reformate composition

    SciTech Connect

    Ancheyta-Juarez, J.; Aguilar-Rodriguez, E. )

    1994-01-31

    Although naphtha reforming is a well-known process, the evolution of catalyst formulation, as well as new trends in gasoline specifications, have led to rapid evolution of the process, including: reactor design, regeneration mode, and operating conditions. Mathematical modeling of the reforming process is an increasingly important tool. It is fundamental to the proper design of new reactors and revamp of existing ones. Modeling can be used to optimize operating conditions, analyze the effects of process variables, and enhance unit performance. Instituto Mexicano del Petroleo has developed a model of the catalytic reforming process that accurately predicts reformate composition at the higher-severity conditions at which new reformers are being designed. The new AA model is more accurate than previous proposals because it takes into account the effects of temperature and pressure on the rate constants of each chemical reaction.

  3. Accurate torque-speed performance prediction for brushless dc motors

    NASA Astrophysics Data System (ADS)

    Gipper, Patrick D.

    Desirable characteristics of the brushless dc motor (BLDCM) have resulted in their application for electrohydrostatic (EH) and electromechanical (EM) actuation systems. But to effectively apply the BLDCM requires accurate prediction of performance. The minimum necessary performance characteristics are motor torque versus speed, peak and average supply current and efficiency. BLDCM nonlinear simulation software specifically adapted for torque-speed prediction is presented. The capability of the software to quickly and accurately predict performance has been verified on fractional to integral HP motor sizes, and is presented. Additionally, the capability of torque-speed prediction with commutation angle advance is demonstrated.

  4. Towards more accurate vegetation mortality predictions

    DOE PAGES

    Sevanto, Sanna Annika; Xu, Chonggang

    2016-09-26

    Predicting the fate of vegetation under changing climate is one of the major challenges of the climate modeling community. Here, terrestrial vegetation dominates the carbon and water cycles over land areas, and dramatic changes in vegetation cover resulting from stressful environmental conditions such as drought feed directly back to local and regional climate, potentially leading to a vicious cycle where vegetation recovery after a disturbance is delayed or impossible.

  5. A gene expression biomarker accurately predicts estrogen ...

    EPA Pesticide Factsheets

    The EPA’s vision for the Endocrine Disruptor Screening Program (EDSP) in the 21st Century (EDSP21) includes utilization of high-throughput screening (HTS) assays coupled with computational modeling to prioritize chemicals with the goal of eventually replacing current Tier 1 screening tests. The ToxCast program currently includes 18 HTS in vitro assays that evaluate the ability of chemicals to modulate estrogen receptor α (ERα), an important endocrine target. We propose microarray-based gene expression profiling as a complementary approach to predict ERα modulation and have developed computational methods to identify ERα modulators in an existing database of whole-genome microarray data. The ERα biomarker consisted of 46 ERα-regulated genes with consistent expression patterns across 7 known ER agonists and 3 known ER antagonists. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression data sets from experiments in MCF-7 cells. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% or 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) OECD ER reference chemicals including “very weak” agonists and replicated predictions based on 18 in vitro ER-associated HTS assays. For 114 chemicals present in both the HTS data and the MCF-7 c

  6. You Can Accurately Predict Land Acquisition Costs.

    ERIC Educational Resources Information Center

    Garrigan, Richard

    1967-01-01

    Land acquisition costs were tested for predictability based upon the 1962 assessed valuations of privately held land acquired for campus expansion by the University of Wisconsin from 1963-1965. By correlating the land acquisition costs of 108 properties acquired during the 3 year period with--(1) the assessed value of the land, (2) the assessed…

  7. Can Selforganizing Maps Accurately Predict Photometric Redshifts?

    NASA Technical Reports Server (NTRS)

    Way, Michael J.; Klose, Christian

    2012-01-01

    We present an unsupervised machine-learning approach that can be employed for estimating photometric redshifts. The proposed method is based on a vector quantization called the self-organizing-map (SOM) approach. A variety of photometrically derived input values were utilized from the Sloan Digital Sky Survey's main galaxy sample, luminous red galaxy, and quasar samples, along with the PHAT0 data set from the Photo-z Accuracy Testing project. Regression results obtained with this new approach were evaluated in terms of root-mean-square error (RMSE) to estimate the accuracy of the photometric redshift estimates. The results demonstrate competitive RMSE and outlier percentages when compared with several other popular approaches, such as artificial neural networks and Gaussian process regression. SOM RMSE results (using delta(z) = z(sub phot) - z(sub spec)) are 0.023 for the main galaxy sample, 0.027 for the luminous red galaxy sample, 0.418 for quasars, and 0.022 for PHAT0 synthetic data. The results demonstrate that there are nonunique solutions for estimating SOM RMSEs. Further research is needed in order to find more robust estimation techniques using SOMs, but the results herein are a positive indication of their capabilities when compared with other well-known methods

  8. A predictable and accurate technique with elastomeric impression materials.

    PubMed

    Barghi, N; Ontiveros, J C

    1999-08-01

    A method for obtaining more predictable and accurate final impressions with polyvinylsiloxane impression materials in conjunction with stock trays is proposed and tested. Heavy impression material is used in advance for construction of a modified custom tray, while extra-light material is used for obtaining a more accurate final impression.

  9. Simple Mathematical Models Do Not Accurately Predict Early SIV Dynamics

    PubMed Central

    Noecker, Cecilia; Schaefer, Krista; Zaccheo, Kelly; Yang, Yiding; Day, Judy; Ganusov, Vitaly V.

    2015-01-01

    Upon infection of a new host, human immunodeficiency virus (HIV) replicates in the mucosal tissues and is generally undetectable in circulation for 1–2 weeks post-infection. Several interventions against HIV including vaccines and antiretroviral prophylaxis target virus replication at this earliest stage of infection. Mathematical models have been used to understand how HIV spreads from mucosal tissues systemically and what impact vaccination and/or antiretroviral prophylaxis has on viral eradication. Because predictions of such models have been rarely compared to experimental data, it remains unclear which processes included in these models are critical for predicting early HIV dynamics. Here we modified the “standard” mathematical model of HIV infection to include two populations of infected cells: cells that are actively producing the virus and cells that are transitioning into virus production mode. We evaluated the effects of several poorly known parameters on infection outcomes in this model and compared model predictions to experimental data on infection of non-human primates with variable doses of simian immunodifficiency virus (SIV). First, we found that the mode of virus production by infected cells (budding vs. bursting) has a minimal impact on the early virus dynamics for a wide range of model parameters, as long as the parameters are constrained to provide the observed rate of SIV load increase in the blood of infected animals. Interestingly and in contrast with previous results, we found that the bursting mode of virus production generally results in a higher probability of viral extinction than the budding mode of virus production. Second, this mathematical model was not able to accurately describe the change in experimentally determined probability of host infection with increasing viral doses. Third and finally, the model was also unable to accurately explain the decline in the time to virus detection with increasing viral dose. These results

  10. Turbulence Models for Accurate Aerothermal Prediction in Hypersonic Flows

    NASA Astrophysics Data System (ADS)

    Zhang, Xiang-Hong; Wu, Yi-Zao; Wang, Jiang-Feng

    Accurate description of the aerodynamic and aerothermal environment is crucial to the integrated design and optimization for high performance hypersonic vehicles. In the simulation of aerothermal environment, the effect of viscosity is crucial. The turbulence modeling remains a major source of uncertainty in the computational prediction of aerodynamic forces and heating. In this paper, three turbulent models were studied: the one-equation eddy viscosity transport model of Spalart-Allmaras, the Wilcox k-ω model and the Menter SST model. For the k-ω model and SST model, the compressibility correction, press dilatation and low Reynolds number correction were considered. The influence of these corrections for flow properties were discussed by comparing with the results without corrections. In this paper the emphasis is on the assessment and evaluation of the turbulence models in prediction of heat transfer as applied to a range of hypersonic flows with comparison to experimental data. This will enable establishing factor of safety for the design of thermal protection systems of hypersonic vehicle.

  11. On the Accurate Prediction of CME Arrival At the Earth

    NASA Astrophysics Data System (ADS)

    Zhang, Jie; Hess, Phillip

    2016-07-01

    We will discuss relevant issues regarding the accurate prediction of CME arrival at the Earth, from both observational and theoretical points of view. In particular, we clarify the importance of separating the study of CME ejecta from the ejecta-driven shock in interplanetary CMEs (ICMEs). For a number of CME-ICME events well observed by SOHO/LASCO, STEREO-A and STEREO-B, we carry out the 3-D measurements by superimposing geometries onto both the ejecta and sheath separately. These measurements are then used to constrain a Drag-Based Model, which is improved through a modification of including height dependence of the drag coefficient into the model. Combining all these factors allows us to create predictions for both fronts at 1 AU and compare with actual in-situ observations. We show an ability to predict the sheath arrival with an average error of under 4 hours, with an RMS error of about 1.5 hours. For the CME ejecta, the error is less than two hours with an RMS error within an hour. Through using the best observations of CMEs, we show the power of our method in accurately predicting CME arrival times. The limitation and implications of our accurate prediction method will be discussed.

  12. Accurate stress resultants equations for laminated composite deep thick shells

    SciTech Connect

    Qatu, M.S.

    1995-11-01

    This paper derives accurate equations for the normal and shear force as well as bending and twisting moment resultants for laminated composite deep, thick shells. The stress resultant equations for laminated composite thick shells are shown to be different from those of plates. This is due to the fact the stresses over the thickness of the shell have to be integrated on a trapezoidal-like shell element to obtain the stress resultants. Numerical results are obtained and showed that accurate stress resultants are needed for laminated composite deep thick shells, especially if the curvature is not spherical.

  13. Fast and accurate predictions of covalent bonds in chemical space

    NASA Astrophysics Data System (ADS)

    Chang, K. Y. Samuel; Fias, Stijn; Ramakrishnan, Raghunathan; von Lilienfeld, O. Anatole

    2016-05-01

    We assess the predictive accuracy of perturbation theory based estimates of changes in covalent bonding due to linear alchemical interpolations among molecules. We have investigated σ bonding to hydrogen, as well as σ and π bonding between main-group elements, occurring in small sets of iso-valence-electronic molecules with elements drawn from second to fourth rows in the p-block of the periodic table. Numerical evidence suggests that first order Taylor expansions of covalent bonding potentials can achieve high accuracy if (i) the alchemical interpolation is vertical (fixed geometry), (ii) it involves elements from the third and fourth rows of the periodic table, and (iii) an optimal reference geometry is used. This leads to near linear changes in the bonding potential, resulting in analytical predictions with chemical accuracy (˜1 kcal/mol). Second order estimates deteriorate the prediction. If initial and final molecules differ not only in composition but also in geometry, all estimates become substantially worse, with second order being slightly more accurate than first order. The independent particle approximation based second order perturbation theory performs poorly when compared to the coupled perturbed or finite difference approach. Taylor series expansions up to fourth order of the potential energy curve of highly symmetric systems indicate a finite radius of convergence, as illustrated for the alchemical stretching of H 2+ . Results are presented for (i) covalent bonds to hydrogen in 12 molecules with 8 valence electrons (CH4, NH3, H2O, HF, SiH4, PH3, H2S, HCl, GeH4, AsH3, H2Se, HBr); (ii) main-group single bonds in 9 molecules with 14 valence electrons (CH3F, CH3Cl, CH3Br, SiH3F, SiH3Cl, SiH3Br, GeH3F, GeH3Cl, GeH3Br); (iii) main-group double bonds in 9 molecules with 12 valence electrons (CH2O, CH2S, CH2Se, SiH2O, SiH2S, SiH2Se, GeH2O, GeH2S, GeH2Se); (iv) main-group triple bonds in 9 molecules with 10 valence electrons (HCN, HCP, HCAs, HSiN, HSi

  14. Fast and accurate predictions of covalent bonds in chemical space.

    PubMed

    Chang, K Y Samuel; Fias, Stijn; Ramakrishnan, Raghunathan; von Lilienfeld, O Anatole

    2016-05-07

    We assess the predictive accuracy of perturbation theory based estimates of changes in covalent bonding due to linear alchemical interpolations among molecules. We have investigated σ bonding to hydrogen, as well as σ and π bonding between main-group elements, occurring in small sets of iso-valence-electronic molecules with elements drawn from second to fourth rows in the p-block of the periodic table. Numerical evidence suggests that first order Taylor expansions of covalent bonding potentials can achieve high accuracy if (i) the alchemical interpolation is vertical (fixed geometry), (ii) it involves elements from the third and fourth rows of the periodic table, and (iii) an optimal reference geometry is used. This leads to near linear changes in the bonding potential, resulting in analytical predictions with chemical accuracy (∼1 kcal/mol). Second order estimates deteriorate the prediction. If initial and final molecules differ not only in composition but also in geometry, all estimates become substantially worse, with second order being slightly more accurate than first order. The independent particle approximation based second order perturbation theory performs poorly when compared to the coupled perturbed or finite difference approach. Taylor series expansions up to fourth order of the potential energy curve of highly symmetric systems indicate a finite radius of convergence, as illustrated for the alchemical stretching of H2 (+). Results are presented for (i) covalent bonds to hydrogen in 12 molecules with 8 valence electrons (CH4, NH3, H2O, HF, SiH4, PH3, H2S, HCl, GeH4, AsH3, H2Se, HBr); (ii) main-group single bonds in 9 molecules with 14 valence electrons (CH3F, CH3Cl, CH3Br, SiH3F, SiH3Cl, SiH3Br, GeH3F, GeH3Cl, GeH3Br); (iii) main-group double bonds in 9 molecules with 12 valence electrons (CH2O, CH2S, CH2Se, SiH2O, SiH2S, SiH2Se, GeH2O, GeH2S, GeH2Se); (iv) main-group triple bonds in 9 molecules with 10 valence electrons (HCN, HCP, HCAs, HSiN, HSi

  15. Passive samplers accurately predict PAH levels in resident crayfish.

    PubMed

    Paulik, L Blair; Smith, Brian W; Bergmann, Alan J; Sower, Greg J; Forsberg, Norman D; Teeguarden, Justin G; Anderson, Kim A

    2016-02-15

    Contamination of resident aquatic organisms is a major concern for environmental risk assessors. However, collecting organisms to estimate risk is often prohibitively time and resource-intensive. Passive sampling accurately estimates resident organism contamination, and it saves time and resources. This study used low density polyethylene (LDPE) passive water samplers to predict polycyclic aromatic hydrocarbon (PAH) levels in signal crayfish, Pacifastacus leniusculus. Resident crayfish were collected at 5 sites within and outside of the Portland Harbor Superfund Megasite (PHSM) in the Willamette River in Portland, Oregon. LDPE deployment was spatially and temporally paired with crayfish collection. Crayfish visceral and tail tissue, as well as water-deployed LDPE, were extracted and analyzed for 62 PAHs using GC-MS/MS. Freely-dissolved concentrations (Cfree) of PAHs in water were calculated from concentrations in LDPE. Carcinogenic risks were estimated for all crayfish tissues, using benzo[a]pyrene equivalent concentrations (BaPeq). ∑PAH were 5-20 times higher in viscera than in tails, and ∑BaPeq were 6-70 times higher in viscera than in tails. Eating only tail tissue of crayfish would therefore significantly reduce carcinogenic risk compared to also eating viscera. Additionally, PAH levels in crayfish were compared to levels in crayfish collected 10 years earlier. PAH levels in crayfish were higher upriver of the PHSM and unchanged within the PHSM after the 10-year period. Finally, a linear regression model predicted levels of 34 PAHs in crayfish viscera with an associated R-squared value of 0.52 (and a correlation coefficient of 0.72), using only the Cfree PAHs in water. On average, the model predicted PAH concentrations in crayfish tissue within a factor of 2.4 ± 1.8 of measured concentrations. This affirms that passive water sampling accurately estimates PAH contamination in crayfish. Furthermore, the strong predictive ability of this simple model suggests

  16. Inverter Modeling For Accurate Energy Predictions Of Tracking HCPV Installations

    NASA Astrophysics Data System (ADS)

    Bowman, J.; Jensen, S.; McDonald, Mark

    2010-10-01

    High efficiency high concentration photovoltaic (HCPV) solar plants of megawatt scale are now operational, and opportunities for expanded adoption are plentiful. However, effective bidding for sites requires reliable prediction of energy production. HCPV module nameplate power is rated for specific test conditions; however, instantaneous HCPV power varies due to site specific irradiance and operating temperature, and is degraded by soiling, protective stowing, shading, and electrical connectivity. These factors interact with the selection of equipment typically supplied by third parties, e.g., wire gauge and inverters. We describe a time sequence model accurately accounting for these effects that predicts annual energy production, with specific reference to the impact of the inverter on energy output and interactions between system-level design decisions and the inverter. We will also show two examples, based on an actual field design, of inverter efficiency calculations and the interaction between string arrangements and inverter selection.

  17. Near-infrared reflectance spectroscopy (NIRS) enables the fast and accurate prediction of essential amino acid contents. 2. Results for wheat, barley, corn, triticale, wheat bran/middlings, rice bran, and sorghum.

    PubMed

    Fontaine, Johannes; Schirmer, Barbara; Hörr, Jutta

    2002-07-03

    Further NIRS calibrations were developed for the accurate and fast prediction of the total contents of methionine, cystine, lysine, threonine, tryptophan, and other essential amino acids, protein, and moisture in the most important cereals and brans or middlings for animal feed production. More than 1100 samples of global origin collected over five years were analyzed for amino acids following the Official Methods of the United States and European Union. Detailed data and graphics are given to characterize the obtained calibration equations. NIRS was validated with 98 independent samples for wheat and 78 samples for corn and compared to amino acid predictions using linear crude protein regression equations. With a few exceptions, validation showed that 70-98% of the amino acid variance in the samples could be explained using NIRS. Especially for lysine and methionine, the most limiting amino acids for farm animals, NIRS can predict contents in cereals much better than crude protein regressions. Through low cost and high speed of analysis NIRS enables the amino acid analysis of many samples in order to improve the accuracy of feed formulation and obtain better quality and lower production costs.

  18. IRIS: Towards an Accurate and Fast Stage Weight Prediction Method

    NASA Astrophysics Data System (ADS)

    Taponier, V.; Balu, A.

    2002-01-01

    The knowledge of the structural mass fraction (or the mass ratio) of a given stage, which affects the performance of a rocket, is essential for the analysis of new or upgraded launchers or stages, whose need is increased by the quick evolution of the space programs and by the necessity of their adaptation to the market needs. The availability of this highly scattered variable, ranging between 0.05 and 0.15, is of primary importance at the early steps of the preliminary design studies. At the start of the staging and performance studies, the lack of frozen weight data (to be obtained later on from propulsion, trajectory and sizing studies) leads to rely on rough estimates, generally derived from printed sources and adapted. When needed, a consolidation can be acquired trough a specific analysis activity involving several techniques and implying additional effort and time. The present empirical approach allows thus to get approximated values (i.e. not necessarily accurate or consistent), inducing some result inaccuracy as well as, consequently, difficulties of performance ranking for a multiple option analysis, and an increase of the processing duration. This forms a classical harsh fact of the preliminary design system studies, insufficiently discussed to date. It appears therefore highly desirable to have, for all the evaluation activities, a reliable, fast and easy-to-use weight or mass fraction prediction method. Additionally, the latter should allow for a pre selection of the alternative preliminary configurations, making possible a global system approach. For that purpose, an attempt at modeling has been undertaken, whose objective was the determination of a parametric formulation of the mass fraction, to be expressed from a limited number of parameters available at the early steps of the project. It is based on the innovative use of a statistical method applicable to a variable as a function of several independent parameters. A specific polynomial generator

  19. Basophile: Accurate Fragment Charge State Prediction Improves Peptide Identification Rates

    SciTech Connect

    Wang, Dong; Dasari, Surendra; Chambers, Matthew C.; Holman, Jerry D.; Chen, Kan; Liebler, Daniel; Orton, Daniel J.; Purvine, Samuel O.; Monroe, Matthew E.; Chung, Chang Y.; Rose, Kristie L.; Tabb, David L.

    2013-03-07

    In shotgun proteomics, database search algorithms rely on fragmentation models to predict fragment ions that should be observed for a given peptide sequence. The most widely used strategy (Naive model) is oversimplified, cleaving all peptide bonds with equal probability to produce fragments of all charges below that of the precursor ion. More accurate models, based on fragmentation simulation, are too computationally intensive for on-the-fly use in database search algorithms. We have created an ordinal-regression-based model called Basophile that takes fragment size and basic residue distribution into account when determining the charge retention during CID/higher-energy collision induced dissociation (HCD) of charged peptides. This model improves the accuracy of predictions by reducing the number of unnecessary fragments that are routinely predicted for highly-charged precursors. Basophile increased the identification rates by 26% (on average) over the Naive model, when analyzing triply-charged precursors from ion trap data. Basophile achieves simplicity and speed by solving the prediction problem with an ordinal regression equation, which can be incorporated into any database search software for shotgun proteomic identification.

  20. Basophile: Accurate Fragment Charge State Prediction Improves Peptide Identification Rates

    DOE PAGES

    Wang, Dong; Dasari, Surendra; Chambers, Matthew C.; ...

    2013-03-07

    In shotgun proteomics, database search algorithms rely on fragmentation models to predict fragment ions that should be observed for a given peptide sequence. The most widely used strategy (Naive model) is oversimplified, cleaving all peptide bonds with equal probability to produce fragments of all charges below that of the precursor ion. More accurate models, based on fragmentation simulation, are too computationally intensive for on-the-fly use in database search algorithms. We have created an ordinal-regression-based model called Basophile that takes fragment size and basic residue distribution into account when determining the charge retention during CID/higher-energy collision induced dissociation (HCD) of chargedmore » peptides. This model improves the accuracy of predictions by reducing the number of unnecessary fragments that are routinely predicted for highly-charged precursors. Basophile increased the identification rates by 26% (on average) over the Naive model, when analyzing triply-charged precursors from ion trap data. Basophile achieves simplicity and speed by solving the prediction problem with an ordinal regression equation, which can be incorporated into any database search software for shotgun proteomic identification.« less

  1. Basophile: Accurate Fragment Charge State Prediction Improves Peptide Identification Rates

    PubMed Central

    Wang, Dong; Dasari, Surendra; Chambers, Matthew C.; Holman, Jerry D.; Chen, Kan; Liebler, Daniel C.; Orton, Daniel J.; Purvine, Samuel O.; Monroe, Matthew E.; Chung, Chang Y.; Rose, Kristie L.; Tabb, David L.

    2013-01-01

    In shotgun proteomics, database search algorithms rely on fragmentation models to predict fragment ions that should be observed for a given peptide sequence. The most widely used strategy (Naive model) is oversimplified, cleaving all peptide bonds with equal probability to produce fragments of all charges below that of the precursor ion. More accurate models, based on fragmentation simulation, are too computationally intensive for on-the-fly use in database search algorithms. We have created an ordinal-regression-based model called Basophile that takes fragment size and basic residue distribution into account when determining the charge retention during CID/higher-energy collision induced dissociation (HCD) of charged peptides. This model improves the accuracy of predictions by reducing the number of unnecessary fragments that are routinely predicted for highly-charged precursors. Basophile increased the identification rates by 26% (on average) over the Naive model, when analyzing triply-charged precursors from ion trap data. Basophile achieves simplicity and speed by solving the prediction problem with an ordinal regression equation, which can be incorporated into any database search software for shotgun proteomic identification. PMID:23499924

  2. Prediction of Preoperative Anxiety in Children: Who is Most Accurate?

    PubMed Central

    MacLaren, Jill E.; Thompson, Caitlin; Weinberg, Megan; Fortier, Michelle A.; Morrison, Debra E.; Perret, Danielle; Kain, Zeev N.

    2009-01-01

    Background In this investigation, we sought to assess the ability of pediatric attending anesthesiologists, resident anesthesiologists and mothers to predict anxiety during induction of anesthesia in 2 to 16-year-old children (n=125). Methods Anesthesiologists and mothers provided predictions using a visual analog scale and children's anxiety was assessed using a valid behavior observation tool the Modified Yale Preoperative Anxiety Scale (mYPAS). All mothers were present during anesthetic induction and no child received sedative premedication. Correlational analyses were conducted. Results A total of 125 children aged 2 to 16 years, their mothers, and their attending pediatric anesthesiologists and resident anesthesiologists were studied. Correlational analyses revealed significant associations between attending predictions and child anxiety at induction (rs= 0.38, p<0.001). Resident anesthesiologist and mother predictions were not significantly related to children's anxiety during induction (rs = 0.01 and 0.001, respectively). In terms of accuracy of prediction, 47.2% of predictions made by attending anesthesiologists were within one standard deviation of the observed anxiety exhibited by the child, and 70.4% of predictions were within 2 standard deviations. Conclusions We conclude that attending anesthesiologists who practice in pediatric settings are better than mothers in predicting the anxiety of children during induction of anesthesia. While this finding has significant clinical implications, it is unclear if it can be extended to attending anesthesiologists whose practice is not mostly pediatric anesthesia. PMID:19448201

  3. Mouse models of human AML accurately predict chemotherapy response

    PubMed Central

    Zuber, Johannes; Radtke, Ina; Pardee, Timothy S.; Zhao, Zhen; Rappaport, Amy R.; Luo, Weijun; McCurrach, Mila E.; Yang, Miao-Miao; Dolan, M. Eileen; Kogan, Scott C.; Downing, James R.; Lowe, Scott W.

    2009-01-01

    The genetic heterogeneity of cancer influences the trajectory of tumor progression and may underlie clinical variation in therapy response. To model such heterogeneity, we produced genetically and pathologically accurate mouse models of common forms of human acute myeloid leukemia (AML) and developed methods to mimic standard induction chemotherapy and efficiently monitor therapy response. We see that murine AMLs harboring two common human AML genotypes show remarkably diverse responses to conventional therapy that mirror clinical experience. Specifically, murine leukemias expressing the AML1/ETO fusion oncoprotein, associated with a favorable prognosis in patients, show a dramatic response to induction chemotherapy owing to robust activation of the p53 tumor suppressor network. Conversely, murine leukemias expressing MLL fusion proteins, associated with a dismal prognosis in patients, are drug-resistant due to an attenuated p53 response. Our studies highlight the importance of genetic information in guiding the treatment of human AML, functionally establish the p53 network as a central determinant of chemotherapy response in AML, and demonstrate that genetically engineered mouse models of human cancer can accurately predict therapy response in patients. PMID:19339691

  4. Mouse models of human AML accurately predict chemotherapy response.

    PubMed

    Zuber, Johannes; Radtke, Ina; Pardee, Timothy S; Zhao, Zhen; Rappaport, Amy R; Luo, Weijun; McCurrach, Mila E; Yang, Miao-Miao; Dolan, M Eileen; Kogan, Scott C; Downing, James R; Lowe, Scott W

    2009-04-01

    The genetic heterogeneity of cancer influences the trajectory of tumor progression and may underlie clinical variation in therapy response. To model such heterogeneity, we produced genetically and pathologically accurate mouse models of common forms of human acute myeloid leukemia (AML) and developed methods to mimic standard induction chemotherapy and efficiently monitor therapy response. We see that murine AMLs harboring two common human AML genotypes show remarkably diverse responses to conventional therapy that mirror clinical experience. Specifically, murine leukemias expressing the AML1/ETO fusion oncoprotein, associated with a favorable prognosis in patients, show a dramatic response to induction chemotherapy owing to robust activation of the p53 tumor suppressor network. Conversely, murine leukemias expressing MLL fusion proteins, associated with a dismal prognosis in patients, are drug-resistant due to an attenuated p53 response. Our studies highlight the importance of genetic information in guiding the treatment of human AML, functionally establish the p53 network as a central determinant of chemotherapy response in AML, and demonstrate that genetically engineered mouse models of human cancer can accurately predict therapy response in patients.

  5. 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.

  6. Is Three-Dimensional Soft Tissue Prediction by Software Accurate?

    PubMed

    Nam, Ki-Uk; Hong, Jongrak

    2015-11-01

    The authors assessed whether virtual surgery, performed with a soft tissue prediction program, could correctly simulate the actual surgical outcome, focusing on soft tissue movement. Preoperative and postoperative computed tomography (CT) data for 29 patients, who had undergone orthognathic surgery, were obtained and analyzed using the Simplant Pro software. The program made a predicted soft tissue image (A) based on presurgical CT data. After the operation, we obtained actual postoperative CT data and an actual soft tissue image (B) was generated. Finally, the 2 images (A and B) were superimposed and analyzed differences between the A and B. Results were grouped in 2 classes: absolute values and vector values. In the absolute values, the left mouth corner was the most significant error point (2.36 mm). The right mouth corner (2.28 mm), labrale inferius (2.08 mm), and the pogonion (2.03 mm) also had significant errors. In vector values, prediction of the right-left side had a left-sided tendency, the superior-inferior had a superior tendency, and the anterior-posterior showed an anterior tendency. As a result, with this program, the position of points tended to be located more left, anterior, and superior than the "real" situation. There is a need to improve the prediction accuracy for soft tissue images. Such software is particularly valuable in predicting craniofacial soft tissues landmarks, such as the pronasale. With this software, landmark positions were most inaccurate in terms of anterior-posterior predictions.

  7. Learning regulatory programs that accurately predict differential expression with MEDUSA.

    PubMed

    Kundaje, Anshul; Lianoglou, Steve; Li, Xuejing; Quigley, David; Arias, Marta; Wiggins, Chris H; Zhang, Li; Leslie, Christina

    2007-12-01

    Inferring gene regulatory networks from high-throughput genomic data is one of the central problems in computational biology. In this paper, we describe a predictive modeling approach for studying regulatory networks, based on a machine learning algorithm called MEDUSA. MEDUSA integrates promoter sequence, mRNA expression, and transcription factor occupancy data to learn gene regulatory programs that predict the differential expression of target genes. Instead of using clustering or correlation of expression profiles to infer regulatory relationships, MEDUSA determines condition-specific regulators and discovers regulatory motifs that mediate the regulation of target genes. In this way, MEDUSA meaningfully models biological mechanisms of transcriptional regulation. MEDUSA solves the problem of predicting the differential (up/down) expression of target genes by using boosting, a technique from statistical learning, which helps to avoid overfitting as the algorithm searches through the high-dimensional space of potential regulators and sequence motifs. Experimental results demonstrate that MEDUSA achieves high prediction accuracy on held-out experiments (test data), that is, data not seen in training. We also present context-specific analysis of MEDUSA regulatory programs for DNA damage and hypoxia, demonstrating that MEDUSA identifies key regulators and motifs in these processes. A central challenge in the field is the difficulty of validating reverse-engineered networks in the absence of a gold standard. Our approach of learning regulatory programs provides at least a partial solution for the problem: MEDUSA's prediction accuracy on held-out data gives a concrete and statistically sound way to validate how well the algorithm performs. With MEDUSA, statistical validation becomes a prerequisite for hypothesis generation and network building rather than a secondary consideration.

  8. Standardized EEG interpretation accurately predicts prognosis after cardiac arrest

    PubMed Central

    Rossetti, Andrea O.; van Rootselaar, Anne-Fleur; Wesenberg Kjaer, Troels; Horn, Janneke; Ullén, Susann; Friberg, Hans; Nielsen, Niklas; Rosén, Ingmar; Åneman, Anders; Erlinge, David; Gasche, Yvan; Hassager, Christian; Hovdenes, Jan; Kjaergaard, Jesper; Kuiper, Michael; Pellis, Tommaso; Stammet, Pascal; Wanscher, Michael; Wetterslev, Jørn; Wise, Matt P.; Cronberg, Tobias

    2016-01-01

    Objective: To identify reliable predictors of outcome in comatose patients after cardiac arrest using a single routine EEG and standardized interpretation according to the terminology proposed by the American Clinical Neurophysiology Society. Methods: In this cohort study, 4 EEG specialists, blinded to outcome, evaluated prospectively recorded EEGs in the Target Temperature Management trial (TTM trial) that randomized patients to 33°C vs 36°C. Routine EEG was performed in patients still comatose after rewarming. EEGs were classified into highly malignant (suppression, suppression with periodic discharges, burst-suppression), malignant (periodic or rhythmic patterns, pathological or nonreactive background), and benign EEG (absence of malignant features). Poor outcome was defined as best Cerebral Performance Category score 3–5 until 180 days. Results: Eight TTM sites randomized 202 patients. EEGs were recorded in 103 patients at a median 77 hours after cardiac arrest; 37% had a highly malignant EEG and all had a poor outcome (specificity 100%, sensitivity 50%). Any malignant EEG feature had a low specificity to predict poor prognosis (48%) but if 2 malignant EEG features were present specificity increased to 96% (p < 0.001). Specificity and sensitivity were not significantly affected by targeted temperature or sedation. A benign EEG was found in 1% of the patients with a poor outcome. Conclusions: Highly malignant EEG after rewarming reliably predicted poor outcome in half of patients without false predictions. An isolated finding of a single malignant feature did not predict poor outcome whereas a benign EEG was highly predictive of a good outcome. PMID:26865516

  9. Can numerical simulations accurately predict hydrodynamic instabilities in liquid films?

    NASA Astrophysics Data System (ADS)

    Denner, Fabian; Charogiannis, Alexandros; Pradas, Marc; van Wachem, Berend G. M.; Markides, Christos N.; Kalliadasis, Serafim

    2014-11-01

    Understanding the dynamics of hydrodynamic instabilities in liquid film flows is an active field of research in fluid dynamics and non-linear science in general. Numerical simulations offer a powerful tool to study hydrodynamic instabilities in film flows and can provide deep insights into the underlying physical phenomena. However, the direct comparison of numerical results and experimental results is often hampered by several reasons. For instance, in numerical simulations the interface representation is problematic and the governing equations and boundary conditions may be oversimplified, whereas in experiments it is often difficult to extract accurate information on the fluid and its behavior, e.g. determine the fluid properties when the liquid contains particles for PIV measurements. In this contribution we present the latest results of our on-going, extensive study on hydrodynamic instabilities in liquid film flows, which includes direct numerical simulations, low-dimensional modelling as well as experiments. The major focus is on wave regimes, wave height and wave celerity as a function of Reynolds number and forcing frequency of a falling liquid film. Specific attention is paid to the differences in numerical and experimental results and the reasons for these differences. The authors are grateful to the EPSRC for their financial support (Grant EP/K008595/1).

  10. How Accurately Can We Predict Eclipses for Algol? (Poster abstract)

    NASA Astrophysics Data System (ADS)

    Turner, D.

    2016-06-01

    (Abstract only) beta Persei, or Algol, is a very well known eclipsing binary system consisting of a late B-type dwarf that is regularly eclipsed by a GK subgiant every 2.867 days. Eclipses, which last about 8 hours, are regular enough that predictions for times of minima are published in various places, Sky & Telescope magazine and The Observer's Handbook, for example. But eclipse minimum lasts for less than a half hour, whereas subtle mistakes in the current ephemeris for the star can result in predictions that are off by a few hours or more. The Algol system is fairly complex, with the Algol A and Algol B eclipsing system also orbited by Algol C with an orbital period of nearly 2 years. Added to that are complex long-term O-C variations with a periodicity of almost two centuries that, although suggested by Hoffmeister to be spurious, fit the type of light travel time variations expected for a fourth star also belonging to the system. The AB sub-system also undergoes mass transfer events that add complexities to its O-C behavior. Is it actually possible to predict precise times of eclipse minima for Algol months in advance given such complications, or is it better to encourage ongoing observations of the star so that O-C variations can be tracked in real time?

  11. An Overview of Practical Applications of Protein Disorder Prediction and Drive for Faster, More Accurate Predictions

    PubMed Central

    Deng, Xin; Gumm, Jordan; Karki, Suman; Eickholt, Jesse; Cheng, Jianlin

    2015-01-01

    Protein disordered regions are segments of a protein chain that do not adopt a stable structure. Thus far, a variety of protein disorder prediction methods have been developed and have been widely used, not only in traditional bioinformatics domains, including protein structure prediction, protein structure determination and function annotation, but also in many other biomedical fields. The relationship between intrinsically-disordered proteins and some human diseases has played a significant role in disorder prediction in disease identification and epidemiological investigations. Disordered proteins can also serve as potential targets for drug discovery with an emphasis on the disordered-to-ordered transition in the disordered binding regions, and this has led to substantial research in drug discovery or design based on protein disordered region prediction. Furthermore, protein disorder prediction has also been applied to healthcare by predicting the disease risk of mutations in patients and studying the mechanistic basis of diseases. As the applications of disorder prediction increase, so too does the need to make quick and accurate predictions. To fill this need, we also present a new approach to predict protein residue disorder using wide sequence windows that is applicable on the genomic scale. PMID:26198229

  12. An Overview of Practical Applications of Protein Disorder Prediction and Drive for Faster, More Accurate Predictions.

    PubMed

    Deng, Xin; Gumm, Jordan; Karki, Suman; Eickholt, Jesse; Cheng, Jianlin

    2015-07-07

    Protein disordered regions are segments of a protein chain that do not adopt a stable structure. Thus far, a variety of protein disorder prediction methods have been developed and have been widely used, not only in traditional bioinformatics domains, including protein structure prediction, protein structure determination and function annotation, but also in many other biomedical fields. The relationship between intrinsically-disordered proteins and some human diseases has played a significant role in disorder prediction in disease identification and epidemiological investigations. Disordered proteins can also serve as potential targets for drug discovery with an emphasis on the disordered-to-ordered transition in the disordered binding regions, and this has led to substantial research in drug discovery or design based on protein disordered region prediction. Furthermore, protein disorder prediction has also been applied to healthcare by predicting the disease risk of mutations in patients and studying the mechanistic basis of diseases. As the applications of disorder prediction increase, so too does the need to make quick and accurate predictions. To fill this need, we also present a new approach to predict protein residue disorder using wide sequence windows that is applicable on the genomic scale.

  13. Earthquake prediction; new studies yield promising results

    USGS Publications Warehouse

    Robinson, R.

    1974-01-01

    On Agust 3, 1973, a small earthquake (magnitude 2.5) occurred near Blue Mountain Lake in the Adirondack region of northern New York State. This seemingly unimportant event was of great significance, however, because it was predicted. Seismologsits at the Lamont-Doherty geologcal Observatory of Columbia University accurately foretold the time, place, and magnitude of the event. Their prediction was based on certain pre-earthquake processes that are best explained by a hypothesis known as "dilatancy," a concept that has injected new life and direction into the science of earthquake prediction. Although much mroe reserach must be accomplished before we can expect to predict potentially damaging earthquakes with any degree of consistency, results such as this indicate that we are on a promising road. 

  14. Modeling methodology for the accurate and prompt prediction of symptomatic events in chronic diseases.

    PubMed

    Pagán, Josué; Risco-Martín, José L; Moya, José M; Ayala, José L

    2016-08-01

    Prediction of symptomatic crises in chronic diseases allows to take decisions before the symptoms occur, such as the intake of drugs to avoid the symptoms or the activation of medical alarms. The prediction horizon is in this case an important parameter in order to fulfill the pharmacokinetics of medications, or the time response of medical services. This paper presents a study about the prediction limits of a chronic disease with symptomatic crises: the migraine. For that purpose, this work develops a methodology to build predictive migraine models and to improve these predictions beyond the limits of the initial models. The maximum prediction horizon is analyzed, and its dependency on the selected features is studied. A strategy for model selection is proposed to tackle the trade off between conservative but robust predictive models, with respect to less accurate predictions with higher horizons. The obtained results show a prediction horizon close to 40min, which is in the time range of the drug pharmacokinetics. Experiments have been performed in a realistic scenario where input data have been acquired in an ambulatory clinical study by the deployment of a non-intrusive Wireless Body Sensor Network. Our results provide an effective methodology for the selection of the future horizon in the development of prediction algorithms for diseases experiencing symptomatic crises.

  15. Fast and accurate automatic structure prediction with HHpred.

    PubMed

    Hildebrand, Andrea; Remmert, Michael; Biegert, Andreas; Söding, Johannes

    2009-01-01

    Automated protein structure prediction is becoming a mainstream tool for biological research. This has been fueled by steady improvements of publicly available automated servers over the last decade, in particular their ability to build good homology models for an increasing number of targets by reliably detecting and aligning more and more remotely homologous templates. Here, we describe the three fully automated versions of the HHpred server that participated in the community-wide blind protein structure prediction competition CASP8. What makes HHpred unique is the combination of usability, short response times (typically under 15 min) and a model accuracy that is competitive with those of the best servers in CASP8.

  16. Accurate perception of negative emotions predicts functional capacity in schizophrenia.

    PubMed

    Abram, Samantha V; Karpouzian, Tatiana M; Reilly, James L; Derntl, Birgit; Habel, Ute; Smith, Matthew J

    2014-04-30

    Several studies suggest facial affect perception (FAP) deficits in schizophrenia are linked to poorer social functioning. However, whether reduced functioning is associated with inaccurate perception of specific emotional valence or a global FAP impairment remains unclear. The present study examined whether impairment in the perception of specific emotional valences (positive, negative) and neutrality were uniquely associated with social functioning, using a multimodal social functioning battery. A sample of 59 individuals with schizophrenia and 41 controls completed a computerized FAP task, and measures of functional capacity, social competence, and social attainment. Participants also underwent neuropsychological testing and symptom assessment. Regression analyses revealed that only accurately perceiving negative emotions explained significant variance (7.9%) in functional capacity after accounting for neurocognitive function and symptoms. Partial correlations indicated that accurately perceiving anger, in particular, was positively correlated with functional capacity. FAP for positive, negative, or neutral emotions were not related to social competence or social attainment. Our findings were consistent with prior literature suggesting negative emotions are related to functional capacity in schizophrenia. Furthermore, the observed relationship between perceiving anger and performance of everyday living skills is novel and warrants further exploration.

  17. Accurate Theoretical Prediction of the Properties of Energetic Materials

    DTIC Science & Technology

    2007-11-02

    calculations (e.g. Cheetah ). 8. Sensitivity. The structure prediction and lattice potential work will serve as a platform to examine impact/shock...nitromethane molecules. (In an extension of the present work, we will freeze the internal coordinates of the molecules and assess the extent to which the

  18. An effective method for accurate prediction of the first hyperpolarizability of alkalides.

    PubMed

    Wang, Jia-Nan; Xu, Hong-Liang; Sun, Shi-Ling; Gao, Ting; Li, Hong-Zhi; Li, Hui; Su, Zhong-Min

    2012-01-15

    The proper theoretical calculation method for nonlinear optical (NLO) properties is a key factor to design the excellent NLO materials. Yet it is a difficult task to obatin the accurate NLO property of large scale molecule. In present work, an effective intelligent computing method, as called extreme learning machine-neural network (ELM-NN), is proposed to predict accurately the first hyperpolarizability (β(0)) of alkalides from low-accuracy first hyperpolarizability. Compared with neural network (NN) and genetic algorithm neural network (GANN), the root-mean-square deviations of the predicted values obtained by ELM-NN, GANN, and NN with their MP2 counterpart are 0.02, 0.08, and 0.17 a.u., respectively. It suggests that the predicted values obtained by ELM-NN are more accurate than those calculated by NN and GANN methods. Another excellent point of ELM-NN is the ability to obtain the high accuracy level calculated values with less computing cost. Experimental results show that the computing time of MP2 is 2.4-4 times of the computing time of ELM-NN. Thus, the proposed method is a potentially powerful tool in computational chemistry, and it may predict β(0) of the large scale molecules, which is difficult to obtain by high-accuracy theoretical method due to dramatic increasing computational cost.

  19. Predictive rendering for accurate material perception: modeling and rendering fabrics

    NASA Astrophysics Data System (ADS)

    Bala, Kavita

    2012-03-01

    In computer graphics, rendering algorithms are used to simulate the appearance of objects and materials in a wide range of applications. Designers and manufacturers rely entirely on these rendered images to previsualize scenes and products before manufacturing them. They need to differentiate between different types of fabrics, paint finishes, plastics, and metals, often with subtle differences, for example, between silk and nylon, formaica and wood. Thus, these applications need predictive algorithms that can produce high-fidelity images that enable such subtle material discrimination.

  20. Accurate Prediction of Ligand Affinities for a Proton-Dependent Oligopeptide Transporter

    PubMed Central

    Samsudin, Firdaus; Parker, Joanne L.; Sansom, Mark S.P.; Newstead, Simon; Fowler, Philip W.

    2016-01-01

    Summary Membrane transporters are critical modulators of drug pharmacokinetics, efficacy, and safety. One example is the proton-dependent oligopeptide transporter PepT1, also known as SLC15A1, which is responsible for the uptake of the β-lactam antibiotics and various peptide-based prodrugs. In this study, we modeled the binding of various peptides to a bacterial homolog, PepTSt, and evaluated a range of computational methods for predicting the free energy of binding. Our results show that a hybrid approach (endpoint methods to classify peptides into good and poor binders and a theoretically exact method for refinement) is able to accurately predict affinities, which we validated using proteoliposome transport assays. Applying the method to a homology model of PepT1 suggests that the approach requires a high-quality structure to be accurate. Our study provides a blueprint for extending these computational methodologies to other pharmaceutically important transporter families. PMID:27028887

  1. Objective criteria accurately predict amputation following lower extremity trauma.

    PubMed

    Johansen, K; Daines, M; Howey, T; Helfet, D; Hansen, S T

    1990-05-01

    MESS (Mangled Extremity Severity Score) is a simple rating scale for lower extremity trauma, based on skeletal/soft-tissue damage, limb ischemia, shock, and age. Retrospective analysis of severe lower extremity injuries in 25 trauma victims demonstrated a significant difference between MESS values for 17 limbs ultimately salvaged (mean, 4.88 +/- 0.27) and nine requiring amputation (mean, 9.11 +/- 0.51) (p less than 0.01). A prospective trial of MESS in lower extremity injuries managed at two trauma centers again demonstrated a significant difference between MESS values of 14 salvaged (mean, 4.00 +/- 0.28) and 12 doomed (mean, 8.83 +/- 0.53) limbs (p less than 0.01). In both the retrospective survey and the prospective trial, a MESS value greater than or equal to 7 predicted amputation with 100% accuracy. MESS may be useful in selecting trauma victims whose irretrievably injured lower extremities warrant primary amputation.

  2. Can phenological models predict tree phenology accurately under climate change conditions?

    NASA Astrophysics Data System (ADS)

    Chuine, Isabelle; Bonhomme, Marc; Legave, Jean Michel; García de Cortázar-Atauri, Inaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry

    2014-05-01

    The onset of the growing season of trees has been globally earlier by 2.3 days/decade during the last 50 years because of global warming and this trend is predicted to continue according to climate forecast. The effect of temperature on plant phenology is however not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud dormancy, and on the other hand higher temperatures are necessary to promote bud cells growth afterwards. Increasing phenological changes in temperate woody species have strong impacts on forest trees distribution and productivity, as well as crops cultivation areas. Accurate predictions of trees phenology are therefore a prerequisite to understand and foresee the impacts of climate change on forests and agrosystems. Different process-based models have been developed in the last two decades to predict the date of budburst or flowering of woody species. They are two main families: (1) one-phase models which consider only the ecodormancy phase and make the assumption that endodormancy is always broken before adequate climatic conditions for cell growth occur; and (2) two-phase models which consider both the endodormancy and ecodormancy phases and predict a date of dormancy break which varies from year to year. So far, one-phase models have been able to predict accurately tree bud break and flowering under historical climate. However, because they do not consider what happens prior to ecodormancy, and especially the possible negative effect of winter temperature warming on dormancy break, it seems unlikely that they can provide accurate predictions in future climate conditions. It is indeed well known that a lack of low temperature results in abnormal pattern of bud break and development in temperate fruit trees. An accurate modelling of the dormancy break date has thus become a major issue in phenology modelling. Two-phases phenological models predict that global warming should delay

  3. Improved Ecosystem Predictions of the California Current System via Accurate Light Calculations

    DTIC Science & Technology

    2011-09-30

    System via Accurate Light Calculations Curtis D. Mobley Sequoia Scientific, Inc. 2700 Richards Road, Suite 107 Bellevue, WA 98005 phone: 425...incorporate extremely fast but accurate light calculations into coupled physical-biological-optical ocean ecosystem models as used for operational three...dimensional ecosystem predictions. Improvements in light calculations lead to improvements in predictions of chlorophyll concentrations and other

  4. Generating highly accurate prediction hypotheses through collaborative ensemble learning

    PubMed Central

    Arsov, Nino; Pavlovski, Martin; Basnarkov, Lasko; Kocarev, Ljupco

    2017-01-01

    Ensemble generation is a natural and convenient way of achieving better generalization performance of learning algorithms by gathering their predictive capabilities. Here, we nurture the idea of ensemble-based learning by combining bagging and boosting for the purpose of binary classification. Since the former improves stability through variance reduction, while the latter ameliorates overfitting, the outcome of a multi-model that combines both strives toward a comprehensive net-balancing of the bias-variance trade-off. To further improve this, we alter the bagged-boosting scheme by introducing collaboration between the multi-model’s constituent learners at various levels. This novel stability-guided classification scheme is delivered in two flavours: during or after the boosting process. Applied among a crowd of Gentle Boost ensembles, the ability of the two suggested algorithms to generalize is inspected by comparing them against Subbagging and Gentle Boost on various real-world datasets. In both cases, our models obtained a 40% generalization error decrease. But their true ability to capture details in data was revealed through their application for protein detection in texture analysis of gel electrophoresis images. They achieve improved performance of approximately 0.9773 AUROC when compared to the AUROC of 0.9574 obtained by an SVM based on recursive feature elimination. PMID:28304378

  5. Accurate predictions for the production of vaporized water

    SciTech Connect

    Morin, E.; Montel, F.

    1995-12-31

    The production of water vaporized in the gas phase is controlled by the local conditions around the wellbore. The pressure gradient applied to the formation creates a sharp increase of the molar water content in the hydrocarbon phase approaching the well; this leads to a drop in the pore water saturation around the wellbore. The extent of the dehydrated zone which is formed is the key controlling the bottom-hole content of vaporized water. The maximum water content in the hydrocarbon phase at a given pressure, temperature and salinity is corrected by capillarity or adsorption phenomena depending on the actual water saturation. Describing the mass transfer of the water between the hydrocarbon phases and the aqueous phase into the tubing gives a clear idea of vaporization effects on the formation of scales. Field example are presented for gas fields with temperatures ranging between 140{degrees}C and 180{degrees}C, where water vaporization effects are significant. Conditions for salt plugging in the tubing are predicted.

  6. Generating highly accurate prediction hypotheses through collaborative ensemble learning

    NASA Astrophysics Data System (ADS)

    Arsov, Nino; Pavlovski, Martin; Basnarkov, Lasko; Kocarev, Ljupco

    2017-03-01

    Ensemble generation is a natural and convenient way of achieving better generalization performance of learning algorithms by gathering their predictive capabilities. Here, we nurture the idea of ensemble-based learning by combining bagging and boosting for the purpose of binary classification. Since the former improves stability through variance reduction, while the latter ameliorates overfitting, the outcome of a multi-model that combines both strives toward a comprehensive net-balancing of the bias-variance trade-off. To further improve this, we alter the bagged-boosting scheme by introducing collaboration between the multi-model’s constituent learners at various levels. This novel stability-guided classification scheme is delivered in two flavours: during or after the boosting process. Applied among a crowd of Gentle Boost ensembles, the ability of the two suggested algorithms to generalize is inspected by comparing them against Subbagging and Gentle Boost on various real-world datasets. In both cases, our models obtained a 40% generalization error decrease. But their true ability to capture details in data was revealed through their application for protein detection in texture analysis of gel electrophoresis images. They achieve improved performance of approximately 0.9773 AUROC when compared to the AUROC of 0.9574 obtained by an SVM based on recursive feature elimination.

  7. Hash: a Program to Accurately Predict Protein Hα Shifts from Neighboring Backbone Shifts3

    PubMed Central

    Zeng, Jianyang; Zhou, Pei; Donald, Bruce Randall

    2012-01-01

    Chemical shifts provide not only peak identities for analyzing NMR data, but also an important source of conformational information for studying protein structures. Current structural studies requiring Hα chemical shifts suffer from the following limitations. (1) For large proteins, the Hα chemical shifts can be difficult to assign using conventional NMR triple-resonance experiments, mainly due to the fast transverse relaxation rate of Cα that restricts the signal sensitivity. (2) Previous chemical shift prediction approaches either require homologous models with high sequence similarity or rely heavily on accurate backbone and side-chain structural coordinates. When neither sequence homologues nor structural coordinates are available, we must resort to other information to predict Hα chemical shifts. Predicting accurate Hα chemical shifts using other obtainable information, such as the chemical shifts of nearby backbone atoms (i.e., adjacent atoms in the sequence), can remedy the above dilemmas, and hence advance NMR-based structural studies of proteins. By specifically exploiting the dependencies on chemical shifts of nearby backbone atoms, we propose a novel machine learning algorithm, called Hash, to predict Hα chemical shifts. Hash combines a new fragment-based chemical shift search approach with a non-parametric regression model, called the generalized additive model, to effectively solve the prediction problem. We demonstrate that the chemical shifts of nearby backbone atoms provide a reliable source of information for predicting accurate Hα chemical shifts. Our testing results on different possible combinations of input data indicate that Hash has a wide rage of potential NMR applications in structural and biological studies of proteins. PMID:23242797

  8. Bicluster Sampled Coherence Metric (BSCM) provides an accurate environmental context for phenotype predictions

    PubMed Central

    2015-01-01

    Background Biclustering is a popular method for identifying under which experimental conditions biological signatures are co-expressed. However, the general biclustering problem is NP-hard, offering room to focus algorithms on specific biological tasks. We hypothesize that conditional co-regulation of genes is a key factor in determining cell phenotype and that accurately segregating conditions in biclusters will improve such predictions. Thus, we developed a bicluster sampled coherence metric (BSCM) for determining which conditions and signals should be included in a bicluster. Results Our BSCM calculates condition and cluster size specific p-values, and we incorporated these into the popular integrated biclustering algorithm cMonkey. We demonstrate that incorporation of our new algorithm significantly improves bicluster co-regulation scores (p-value = 0.009) and GO annotation scores (p-value = 0.004). Additionally, we used a bicluster based signal to predict whether a given experimental condition will result in yeast peroxisome induction. Using the new algorithm, the classifier accuracy improves from 41.9% to 76.1% correct. Conclusions We demonstrate that the proposed BSCM helps determine which signals ought to be co-clustered, resulting in more accurately assigned bicluster membership. Furthermore, we show that BSCM can be extended to more accurately detect under which experimental conditions the genes are co-clustered. Features derived from this more accurate analysis of conditional regulation results in a dramatic improvement in the ability to predict a cellular phenotype in yeast. The latest cMonkey is available for download at https://github.com/baliga-lab/cmonkey2. The experimental data and source code featured in this paper is available http://AitchisonLab.com/BSCM. BSCM has been incorporated in the official cMonkey release. PMID:25881257

  9. Fast and Accurate Prediction of Stratified Steel Temperature During Holding Period of Ladle

    NASA Astrophysics Data System (ADS)

    Deodhar, Anirudh; Singh, Umesh; Shukla, Rishabh; Gautham, B. P.; Singh, Amarendra K.

    2017-04-01

    Thermal stratification of liquid steel in a ladle during the holding period and the teeming operation has a direct bearing on the superheat available at the caster and hence on the caster set points such as casting speed and cooling rates. The changes in the caster set points are typically carried out based on temperature measurements at the end of tundish outlet. Thermal prediction models provide advance knowledge of the influence of process and design parameters on the steel temperature at various stages. Therefore, they can be used in making accurate decisions about the caster set points in real time. However, this requires both fast and accurate thermal prediction models. In this work, we develop a surrogate model for the prediction of thermal stratification using data extracted from a set of computational fluid dynamics (CFD) simulations, pre-determined using design of experiments technique. Regression method is used for training the predictor. The model predicts the stratified temperature profile instantaneously, for a given set of process parameters such as initial steel temperature, refractory heat content, slag thickness, and holding time. More than 96 pct of the predicted values are within an error range of ±5 K (±5 °C), when compared against corresponding CFD results. Considering its accuracy and computational efficiency, the model can be extended for thermal control of casting operations. This work also sets a benchmark for developing similar thermal models for downstream processes such as tundish and caster.

  10. Fast and Accurate Prediction of Stratified Steel Temperature During Holding Period of Ladle

    NASA Astrophysics Data System (ADS)

    Deodhar, Anirudh; Singh, Umesh; Shukla, Rishabh; Gautham, B. P.; Singh, Amarendra K.

    2016-12-01

    Thermal stratification of liquid steel in a ladle during the holding period and the teeming operation has a direct bearing on the superheat available at the caster and hence on the caster set points such as casting speed and cooling rates. The changes in the caster set points are typically carried out based on temperature measurements at the end of tundish outlet. Thermal prediction models provide advance knowledge of the influence of process and design parameters on the steel temperature at various stages. Therefore, they can be used in making accurate decisions about the caster set points in real time. However, this requires both fast and accurate thermal prediction models. In this work, we develop a surrogate model for the prediction of thermal stratification using data extracted from a set of computational fluid dynamics (CFD) simulations, pre-determined using design of experiments technique. Regression method is used for training the predictor. The model predicts the stratified temperature profile instantaneously, for a given set of process parameters such as initial steel temperature, refractory heat content, slag thickness, and holding time. More than 96 pct of the predicted values are within an error range of ±5 K (±5 °C), when compared against corresponding CFD results. Considering its accuracy and computational efficiency, the model can be extended for thermal control of casting operations. This work also sets a benchmark for developing similar thermal models for downstream processes such as tundish and caster.

  11. Change in BMI Accurately Predicted by Social Exposure to Acquaintances

    PubMed Central

    Oloritun, Rahman O.; Ouarda, Taha B. M. J.; Moturu, Sai; Madan, Anmol; Pentland, Alex (Sandy); Khayal, Inas

    2013-01-01

    Research has mostly focused on obesity and not on processes of BMI change more generally, although these may be key factors that lead to obesity. Studies have suggested that obesity is affected by social ties. However these studies used survey based data collection techniques that may be biased toward select only close friends and relatives. In this study, mobile phone sensing techniques were used to routinely capture social interaction data in an undergraduate dorm. By automating the capture of social interaction data, the limitations of self-reported social exposure data are avoided. This study attempts to understand and develop a model that best describes the change in BMI using social interaction data. We evaluated a cohort of 42 college students in a co-located university dorm, automatically captured via mobile phones and survey based health-related information. We determined the most predictive variables for change in BMI using the least absolute shrinkage and selection operator (LASSO) method. The selected variables, with gender, healthy diet category, and ability to manage stress, were used to build multiple linear regression models that estimate the effect of exposure and individual factors on change in BMI. We identified the best model using Akaike Information Criterion (AIC) and R2. This study found a model that explains 68% (p<0.0001) of the variation in change in BMI. The model combined social interaction data, especially from acquaintances, and personal health-related information to explain change in BMI. This is the first study taking into account both interactions with different levels of social interaction and personal health-related information. Social interactions with acquaintances accounted for more than half the variation in change in BMI. This suggests the importance of not only individual health information but also the significance of social interactions with people we are exposed to, even people we may not consider as close friends. PMID

  12. Can Self-Organizing Maps Accurately Predict Photometric Redshifts?

    NASA Astrophysics Data System (ADS)

    Way, M. J.; Klose, C. D.

    2012-03-01

    We present an unsupervised machine-learning approach that can be employed for estimating photometric redshifts. The proposed method is based on a vector quantization called the self-organizing-map (SOM) approach. A variety of photometrically derived input values were utilized from the Sloan Digital Sky Survey’s main galaxy sample, luminous red galaxy, and quasar samples, along with the PHAT0 data set from the Photo- z Accuracy Testing project. Regression results obtained with this new approach were evaluated in terms of root-mean-square error (RMSE) to estimate the accuracy of the photometric redshift estimates. The results demonstrate competitive RMSE and outlier percentages when compared with several other popular approaches, such as artificial neural networks and Gaussian process regression. SOM RMSE results (using Δz = zphot - zspec) are 0.023 for the main galaxy sample, 0.027 for the luminous red galaxy sample, 0.418 for quasars, and 0.022 for PHAT0 synthetic data. The results demonstrate that there are nonunique solutions for estimating SOM RMSEs. Further research is needed in order to find more robust estimation techniques using SOMs, but the results herein are a positive indication of their capabilities when compared with other well-known methods.

  13. Rapid and Highly Accurate Prediction of Poor Loop Diuretic Natriuretic Response in Patients With Heart Failure

    PubMed Central

    Testani, Jeffrey M.; Hanberg, Jennifer S.; Cheng, Susan; Rao, Veena; Onyebeke, Chukwuma; Laur, Olga; Kula, Alexander; Chen, Michael; Wilson, F. Perry; Darlington, Andrew; Bellumkonda, Lavanya; Jacoby, Daniel; Tang, W. H. Wilson; Parikh, Chirag R.

    2015-01-01

    Background Removal of excess sodium and fluid is a primary therapeutic objective in acute decompensated heart failure (ADHF) and commonly monitored with fluid balance and weight loss. However, these parameters are frequently inaccurate or not collected and require a delay of several hours after diuretic administration before they are available. Accessible tools for rapid and accurate prediction of diuretic response are needed. Methods and Results Based on well-established renal physiologic principles an equation was derived to predict net sodium output using a spot urine sample obtained one or two hours following loop diuretic administration. This equation was then prospectively validated in 50 ADHF patients using meticulously obtained timed 6-hour urine collections to quantitate loop diuretic induced cumulative sodium output. Poor natriuretic response was defined as a cumulative sodium output of <50 mmol, a threshold that would result in a positive sodium balance with twice-daily diuretic dosing. Following a median dose of 3 mg (2–4 mg) of intravenous bumetanide, 40% of the population had a poor natriuretic response. The correlation between measured and predicted sodium output was excellent (r=0.91, p<0.0001). Poor natriuretic response could be accurately predicted with the sodium prediction equation (AUC=0.95, 95% CI 0.89–1.0, p<0.0001). Clinically recorded net fluid output had a weaker correlation (r=0.66, p<0.001) and lesser ability to predict poor natriuretic response (AUC=0.76, 95% CI 0.63–0.89, p=0.002). Conclusions In patients being treated for ADHF, poor natriuretic response can be predicted soon after diuretic administration with excellent accuracy using a spot urine sample. PMID:26721915

  14. Accurate similarity index based on activity and connectivity of node for link prediction

    NASA Astrophysics Data System (ADS)

    Li, Longjie; Qian, Lvjian; Wang, Xiaoping; Luo, Shishun; Chen, Xiaoyun

    2015-05-01

    Recent years have witnessed the increasing of available network data; however, much of those data is incomplete. Link prediction, which can find the missing links of a network, plays an important role in the research and analysis of complex networks. Based on the assumption that two unconnected nodes which are highly similar are very likely to have an interaction, most of the existing algorithms solve the link prediction problem by computing nodes' similarities. The fundamental requirement of those algorithms is accurate and effective similarity indices. In this paper, we propose a new similarity index, namely similarity based on activity and connectivity (SAC), which performs link prediction more accurately. To compute the similarity between two nodes, this index employs the average activity of these two nodes in their common neighborhood and the connectivities between them and their common neighbors. The higher the average activity is and the stronger the connectivities are, the more similar the two nodes are. The proposed index not only commendably distinguishes the contributions of paths but also incorporates the influence of endpoints. Therefore, it can achieve a better predicting result. To verify the performance of SAC, we conduct experiments on 10 real-world networks. Experimental results demonstrate that SAC outperforms the compared baselines.

  15. How accurate is in vitro prediction of carcinogenicity?

    PubMed

    Walmsley, Richard Maurice; Billinton, Nicholas

    2011-03-01

    Positive genetic toxicity data suggest carcinogenic hazard, and this can stop a candidate pharmaceutical reaching the clinic. However, during the last decade, it has become clear that many non-carcinogens produce misleading positive results in one or other of the regulatory genotoxicity assays. These doubtful conclusions cost a lot of time and money, as they trigger additional testing of apparently genotoxic candidates, both in vitro and in animals, to discover whether the suggested hazard is genuine. This in turn means that clinical trials can be put on hold. This review describes the current approaches to the 'misleading positive' problem as well as efforts to reduce the use of animals in genotoxicity assessment. The following issues are then addressed: the application of genotoxicity testing screens earlier in development; the search for new or improved in vitro genotoxicity tests; proposed changes to the International Committee on Harmonisation guidance on genotoxicity testing [S2(R1)]. Together, developments in all these areas offer good prospects of a more rapid and cost-effective way to understand genetic toxicity concerns.

  16. Prediction of Accurate Thermochemistry of Medium and Large Sized Radicals Using Connectivity-Based Hierarchy (CBH).

    PubMed

    Sengupta, Arkajyoti; Raghavachari, Krishnan

    2014-10-14

    Accurate modeling of the chemical reactions in many diverse areas such as combustion, photochemistry, or atmospheric chemistry strongly depends on the availability of thermochemical information of the radicals involved. However, accurate thermochemical investigations of radical systems using state of the art composite methods have mostly been restricted to the study of hydrocarbon radicals of modest size. In an alternative approach, systematic error-canceling thermochemical hierarchy of reaction schemes can be applied to yield accurate results for such systems. In this work, we have extended our connectivity-based hierarchy (CBH) method to the investigation of radical systems. We have calibrated our method using a test set of 30 medium sized radicals to evaluate their heats of formation. The CBH-rad30 test set contains radicals containing diverse functional groups as well as cyclic systems. We demonstrate that the sophisticated error-canceling isoatomic scheme (CBH-2) with modest levels of theory is adequate to provide heats of formation accurate to ∼1.5 kcal/mol. Finally, we predict heats of formation of 19 other large and medium sized radicals for which the accuracy of available heats of formation are less well-known.

  17. Accurate verification of the conserved-vector-current and standard-model predictions

    SciTech Connect

    Sirlin, A.; Zucchini, R.

    1986-10-20

    An approximate analytic calculation of O(Z..cap alpha../sup 2/) corrections to Fermi decays is presented. When the analysis of Koslowsky et al. is modified to take into account the new results, it is found that each of the eight accurately studied scrFt values differs from the average by approx. <1sigma, thus significantly improving the comparison of experiments with conserved-vector-current predictions. The new scrFt values are lower than before, which also brings experiments into very good agreement with the three-generation standard model, at the level of its quantum corrections.

  18. The MIDAS touch for Accurately Predicting the Stress-Strain Behavior of Tantalum

    SciTech Connect

    Jorgensen, S.

    2016-03-02

    Testing the behavior of metals in extreme environments is not always feasible, so material scientists use models to try and predict the behavior. To achieve accurate results it is necessary to use the appropriate model and material-specific parameters. This research evaluated the performance of six material models available in the MIDAS database [1] to determine at which temperatures and strain-rates they perform best, and to determine to which experimental data their parameters were optimized. Additionally, parameters were optimized for the Johnson-Cook model using experimental data from Lassila et al [2].

  19. Development and Validation of a Multidisciplinary Tool for Accurate and Efficient Rotorcraft Noise Prediction (MUTE)

    NASA Technical Reports Server (NTRS)

    Liu, Yi; Anusonti-Inthra, Phuriwat; Diskin, Boris

    2011-01-01

    A physics-based, systematically coupled, multidisciplinary prediction tool (MUTE) for rotorcraft noise was developed and validated with a wide range of flight configurations and conditions. MUTE is an aggregation of multidisciplinary computational tools that accurately and efficiently model the physics of the source of rotorcraft noise, and predict the noise at far-field observer locations. It uses systematic coupling approaches among multiple disciplines including Computational Fluid Dynamics (CFD), Computational Structural Dynamics (CSD), and high fidelity acoustics. Within MUTE, advanced high-order CFD tools are used around the rotor blade to predict the transonic flow (shock wave) effects, which generate the high-speed impulsive noise. Predictions of the blade-vortex interaction noise in low speed flight are also improved by using the Particle Vortex Transport Method (PVTM), which preserves the wake flow details required for blade/wake and fuselage/wake interactions. The accuracy of the source noise prediction is further improved by utilizing a coupling approach between CFD and CSD, so that the effects of key structural dynamics, elastic blade deformations, and trim solutions are correctly represented in the analysis. The blade loading information and/or the flow field parameters around the rotor blade predicted by the CFD/CSD coupling approach are used to predict the acoustic signatures at far-field observer locations with a high-fidelity noise propagation code (WOPWOP3). The predicted results from the MUTE tool for rotor blade aerodynamic loading and far-field acoustic signatures are compared and validated with a variation of experimental data sets, such as UH60-A data, DNW test data and HART II test data.

  20. Accurate bearing remaining useful life prediction based on Weibull distribution and artificial neural network

    NASA Astrophysics Data System (ADS)

    Ben Ali, Jaouher; Chebel-Morello, Brigitte; Saidi, Lotfi; Malinowski, Simon; Fnaiech, Farhat

    2015-05-01

    Accurate remaining useful life (RUL) prediction of critical assets is an important challenge in condition based maintenance to improve reliability and decrease machine's breakdown and maintenance's cost. Bearing is one of the most important components in industries which need to be monitored and the user should predict its RUL. The challenge of this study is to propose an original feature able to evaluate the health state of bearings and to estimate their RUL by Prognostics and Health Management (PHM) techniques. In this paper, the proposed method is based on the data-driven prognostic approach. The combination of Simplified Fuzzy Adaptive Resonance Theory Map (SFAM) neural network and Weibull distribution (WD) is explored. WD is used just in the training phase to fit measurement and to avoid areas of fluctuation in the time domain. SFAM training process is based on fitted measurements at present and previous inspection time points as input. However, the SFAM testing process is based on real measurements at present and previous inspections. Thanks to the fuzzy learning process, SFAM has an important ability and a good performance to learn nonlinear time series. As output, seven classes are defined; healthy bearing and six states for bearing degradation. In order to find the optimal RUL prediction, a smoothing phase is proposed in this paper. Experimental results show that the proposed method can reliably predict the RUL of rolling element bearings (REBs) based on vibration signals. The proposed prediction approach can be applied to prognostic other various mechanical assets.

  1. A hierarchical approach to accurate predictions of macroscopic thermodynamic behavior from quantum mechanics and molecular simulations

    NASA Astrophysics Data System (ADS)

    Garrison, Stephen L.

    2005-07-01

    The combination of molecular simulations and potentials obtained from quantum chemistry is shown to be able to provide reasonably accurate thermodynamic property predictions. Gibbs ensemble Monte Carlo simulations are used to understand the effects of small perturbations to various regions of the model Lennard-Jones 12-6 potential. However, when the phase behavior and second virial coefficient are scaled by the critical properties calculated for each potential, the results obey a corresponding states relation suggesting a non-uniqueness problem for interaction potentials fit to experimental phase behavior. Several variations of a procedure collectively referred to as quantum mechanical Hybrid Methods for Interaction Energies (HM-IE) are developed and used to accurately estimate interaction energies from CCSD(T) calculations with a large basis set in a computationally efficient manner for the neon-neon, acetylene-acetylene, and nitrogen-benzene systems. Using these results and methods, an ab initio, pairwise-additive, site-site potential for acetylene is determined and then improved using results from molecular simulations using this initial potential. The initial simulation results also indicate that a limited range of energies important for accurate phase behavior predictions. Second virial coefficients calculated from the improved potential indicate that one set of experimental data in the literature is likely erroneous. This prescription is then applied to methanethiol. Difficulties in modeling the effects of the lone pair electrons suggest that charges on the lone pair sites negatively impact the ability of the intermolecular potential to describe certain orientations, but that the lone pair sites may be necessary to reasonably duplicate the interaction energies for several orientations. Two possible methods for incorporating the effects of three-body interactions into simulations within the pairwise-additivity formulation are also developed. A low density

  2. Intermolecular potentials and the accurate prediction of the thermodynamic properties of water

    NASA Astrophysics Data System (ADS)

    Shvab, I.; Sadus, Richard J.

    2013-11-01

    The ability of intermolecular potentials to correctly predict the thermodynamic properties of liquid water at a density of 0.998 g/cm3 for a wide range of temperatures (298-650 K) and pressures (0.1-700 MPa) is investigated. Molecular dynamics simulations are reported for the pressure, thermal pressure coefficient, thermal expansion coefficient, isothermal and adiabatic compressibilities, isobaric and isochoric heat capacities, and Joule-Thomson coefficient of liquid water using the non-polarizable SPC/E and TIP4P/2005 potentials. The results are compared with both experiment data and results obtained from the ab initio-based Matsuoka-Clementi-Yoshimine non-additive (MCYna) [J. Li, Z. Zhou, and R. J. Sadus, J. Chem. Phys. 127, 154509 (2007)] potential, which includes polarization contributions. The data clearly indicate that both the SPC/E and TIP4P/2005 potentials are only in qualitative agreement with experiment, whereas the polarizable MCYna potential predicts some properties within experimental uncertainty. This highlights the importance of polarizability for the accurate prediction of the thermodynamic properties of water, particularly at temperatures beyond 298 K.

  3. Intermolecular potentials and the accurate prediction of the thermodynamic properties of water.

    PubMed

    Shvab, I; Sadus, Richard J

    2013-11-21

    The ability of intermolecular potentials to correctly predict the thermodynamic properties of liquid water at a density of 0.998 g∕cm(3) for a wide range of temperatures (298-650 K) and pressures (0.1-700 MPa) is investigated. Molecular dynamics simulations are reported for the pressure, thermal pressure coefficient, thermal expansion coefficient, isothermal and adiabatic compressibilities, isobaric and isochoric heat capacities, and Joule-Thomson coefficient of liquid water using the non-polarizable SPC∕E and TIP4P∕2005 potentials. The results are compared with both experiment data and results obtained from the ab initio-based Matsuoka-Clementi-Yoshimine non-additive (MCYna) [J. Li, Z. Zhou, and R. J. Sadus, J. Chem. Phys. 127, 154509 (2007)] potential, which includes polarization contributions. The data clearly indicate that both the SPC∕E and TIP4P∕2005 potentials are only in qualitative agreement with experiment, whereas the polarizable MCYna potential predicts some properties within experimental uncertainty. This highlights the importance of polarizability for the accurate prediction of the thermodynamic properties of water, particularly at temperatures beyond 298 K.

  4. Intermolecular potentials and the accurate prediction of the thermodynamic properties of water

    SciTech Connect

    Shvab, I.; Sadus, Richard J.

    2013-11-21

    The ability of intermolecular potentials to correctly predict the thermodynamic properties of liquid water at a density of 0.998 g/cm{sup 3} for a wide range of temperatures (298–650 K) and pressures (0.1–700 MPa) is investigated. Molecular dynamics simulations are reported for the pressure, thermal pressure coefficient, thermal expansion coefficient, isothermal and adiabatic compressibilities, isobaric and isochoric heat capacities, and Joule-Thomson coefficient of liquid water using the non-polarizable SPC/E and TIP4P/2005 potentials. The results are compared with both experiment data and results obtained from the ab initio-based Matsuoka-Clementi-Yoshimine non-additive (MCYna) [J. Li, Z. Zhou, and R. J. Sadus, J. Chem. Phys. 127, 154509 (2007)] potential, which includes polarization contributions. The data clearly indicate that both the SPC/E and TIP4P/2005 potentials are only in qualitative agreement with experiment, whereas the polarizable MCYna potential predicts some properties within experimental uncertainty. This highlights the importance of polarizability for the accurate prediction of the thermodynamic properties of water, particularly at temperatures beyond 298 K.

  5. ILT based defect simulation of inspection images accurately predicts mask defect printability on wafer

    NASA Astrophysics Data System (ADS)

    Deep, Prakash; Paninjath, Sankaranarayanan; Pereira, Mark; Buck, Peter

    2016-05-01

    printability of defects at wafer level and automates the process of defect dispositioning from images captured using high resolution inspection machine. It first eliminates false defects due to registration, focus errors, image capture errors and random noise caused during inspection. For the remaining real defects, actual mask-like contours are generated using the Calibre® ILT solution [1][2], which is enhanced to predict the actual mask contours from high resolution defect images. It enables accurate prediction of defect contours, which is not possible from images captured using inspection machine because some information is already lost due to optical effects. Calibre's simulation engine is used to generate images at wafer level using scanner optical conditions and mask-like contours as input. The tool then analyses simulated images and predicts defect printability. It automatically calculates maximum CD variation and decides which defects are severe to affect patterns on wafer. In this paper, we assess the printability of defects for the mask of advanced technology nodes. In particular, we will compare the recovered mask contours with contours extracted from SEM image of the mask and compare simulation results with AIMSTM for a variety of defects and patterns. The results of printability assessment and the accuracy of comparison are presented in this paper. We also suggest how this method can be extended to predict printability of defects identified on EUV photomasks.

  6. Accurate prediction of wall shear stress in a stented artery: newtonian versus non-newtonian models.

    PubMed

    Mejia, Juan; Mongrain, Rosaire; Bertrand, Olivier F

    2011-07-01

    A significant amount of evidence linking wall shear stress to neointimal hyperplasia has been reported in the literature. As a result, numerical and experimental models have been created to study the influence of stent design on wall shear stress. Traditionally, blood has been assumed to behave as a Newtonian fluid, but recently that assumption has been challenged. The use of a linear model; however, can reduce computational cost, and allow the use of Newtonian fluids (e.g., glycerine and water) instead of a blood analog fluid in an experimental setup. Therefore, it is of interest whether a linear model can be used to accurately predict the wall shear stress caused by a non-Newtonian fluid such as blood within a stented arterial segment. The present work compares the resulting wall shear stress obtained using two linear and one nonlinear model under the same flow waveform. All numerical models are fully three-dimensional, transient, and incorporate a realistic stent geometry. It is shown that traditional linear models (based on blood's lowest viscosity limit, 3.5 Pa s) underestimate the wall shear stress within a stented arterial segment, which can lead to an overestimation of the risk of restenosis. The second linear model, which uses a characteristic viscosity (based on an average strain rate, 4.7 Pa s), results in higher wall shear stress levels, but which are still substantially below those of the nonlinear model. It is therefore shown that nonlinear models result in more accurate predictions of wall shear stress within a stented arterial segment.

  7. Distance scaling method for accurate prediction of slowly varying magnetic fields in satellite missions

    NASA Astrophysics Data System (ADS)

    Zacharias, Panagiotis P.; Chatzineofytou, Elpida G.; Spantideas, Sotirios T.; Capsalis, Christos N.

    2016-07-01

    In the present work, the determination of the magnetic behavior of localized magnetic sources from near-field measurements is examined. The distance power law of the magnetic field fall-off is used in various cases to accurately predict the magnetic signature of an equipment under test (EUT) consisting of multiple alternating current (AC) magnetic sources. Therefore, parameters concerning the location of the observation points (magnetometers) are studied towards this scope. The results clearly show that these parameters are independent of the EUT's size and layout. Additionally, the techniques developed in the present study enable the placing of the magnetometers close to the EUT, thus achieving high signal-to-noise ratio (SNR). Finally, the proposed method is verified by real measurements, using a mobile phone as an EUT.

  8. A fast and accurate method to predict 2D and 3D aerodynamic boundary layer flows

    NASA Astrophysics Data System (ADS)

    Bijleveld, H. A.; Veldman, A. E. P.

    2014-12-01

    A quasi-simultaneous interaction method is applied to predict 2D and 3D aerodynamic flows. This method is suitable for offshore wind turbine design software as it is a very accurate and computationally reasonably cheap method. This study shows the results for a NACA 0012 airfoil. The two applied solvers converge to the experimental values when the grid is refined. We also show that in separation the eigenvalues remain positive thus avoiding the Goldstein singularity at separation. In 3D we show a flow over a dent in which separation occurs. A rotating flat plat is used to show the applicability of the method for rotating flows. The shown capabilities of the method indicate that the quasi-simultaneous interaction method is suitable for design methods for offshore wind turbine blades.

  9. Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model

    PubMed Central

    Li, Zhen; Zhang, Renyu

    2017-01-01

    Motivation Protein contacts contain key information for the understanding of protein structure and function and thus, contact prediction from sequence is an important problem. Recently exciting progress has been made on this problem, but the predicted contacts for proteins without many sequence homologs is still of low quality and not very useful for de novo structure prediction. Method This paper presents a new deep learning method that predicts contacts by integrating both evolutionary coupling (EC) and sequence conservation information through an ultra-deep neural network formed by two deep residual neural networks. The first residual network conducts a series of 1-dimensional convolutional transformation of sequential features; the second residual network conducts a series of 2-dimensional convolutional transformation of pairwise information including output of the first residual network, EC information and pairwise potential. By using very deep residual networks, we can accurately model contact occurrence patterns and complex sequence-structure relationship and thus, obtain higher-quality contact prediction regardless of how many sequence homologs are available for proteins in question. Results Our method greatly outperforms existing methods and leads to much more accurate contact-assisted folding. Tested on 105 CASP11 targets, 76 past CAMEO hard targets, and 398 membrane proteins, the average top L long-range prediction accuracy obtained by our method, one representative EC method CCMpred and the CASP11 winner MetaPSICOV is 0.47, 0.21 and 0.30, respectively; the average top L/10 long-range accuracy of our method, CCMpred and MetaPSICOV is 0.77, 0.47 and 0.59, respectively. Ab initio folding using our predicted contacts as restraints but without any force fields can yield correct folds (i.e., TMscore>0.6) for 203 of the 579 test proteins, while that using MetaPSICOV- and CCMpred-predicted contacts can do so for only 79 and 62 of them, respectively. Our contact

  10. Fast and accurate pressure-drop prediction in straightened atherosclerotic coronary arteries.

    PubMed

    Schrauwen, Jelle T C; Koeze, Dion J; Wentzel, Jolanda J; van de Vosse, Frans N; van der Steen, Anton F W; Gijsen, Frank J H

    2015-01-01

    Atherosclerotic disease progression in coronary arteries is influenced by wall shear stress. To compute patient-specific wall shear stress, computational fluid dynamics (CFD) is required. In this study we propose a method for computing the pressure-drop in regions proximal and distal to a plaque, which can serve as a boundary condition in CFD. As a first step towards exploring the proposed method we investigated ten straightened coronary arteries. First, the flow fields were calculated with CFD and velocity profiles were fitted on the results. Second, the Navier-Stokes equation was simplified and solved with the found velocity profiles to obtain a pressure-drop estimate (Δp (1)). Next, Δp (1) was compared to the pressure-drop from CFD (Δp CFD) as a validation step. Finally, the velocity profiles, and thus the pressure-drop were predicted based on geometry and flow, resulting in Δp geom. We found that Δp (1) adequately estimated Δp CFD with velocity profiles that have one free parameter β. This β was successfully related to geometry and flow, resulting in an excellent agreement between Δp CFD and Δp geom: 3.9 ± 4.9% difference at Re = 150. We showed that this method can quickly and accurately predict pressure-drop on the basis of geometry and flow in straightened coronary arteries that are mildly diseased.

  11. Accurate Prediction of One-Dimensional Protein Structure Features Using SPINE-X.

    PubMed

    Faraggi, Eshel; Kloczkowski, Andrzej

    2017-01-01

    Accurate prediction of protein secondary structure and other one-dimensional structure features is essential for accurate sequence alignment, three-dimensional structure modeling, and function prediction. SPINE-X is a software package to predict secondary structure as well as accessible surface area and dihedral angles ϕ and ψ. For secondary structure SPINE-X achieves an accuracy of between 81 and 84 % depending on the dataset and choice of tests. The Pearson correlation coefficient for accessible surface area prediction is 0.75 and the mean absolute error from the ϕ and ψ dihedral angles are 20(∘) and 33(∘), respectively. The source code and a Linux executables for SPINE-X are available from Research and Information Systems at http://mamiris.com .

  12. Highly Accurate Prediction of Protein-Protein Interactions via Incorporating Evolutionary Information and Physicochemical Characteristics

    PubMed Central

    Li, Zheng-Wei; You, Zhu-Hong; Chen, Xing; Gui, Jie; Nie, Ru

    2016-01-01

    Protein-protein interactions (PPIs) occur at almost all levels of cell functions and play crucial roles in various cellular processes. Thus, identification of PPIs is critical for deciphering the molecular mechanisms and further providing insight into biological processes. Although a variety of high-throughput experimental techniques have been developed to identify PPIs, existing PPI pairs by experimental approaches only cover a small fraction of the whole PPI networks, and further, those approaches hold inherent disadvantages, such as being time-consuming, expensive, and having high false positive rate. Therefore, it is urgent and imperative to develop automatic in silico approaches to predict PPIs efficiently and accurately. In this article, we propose a novel mixture of physicochemical and evolutionary-based feature extraction method for predicting PPIs using our newly developed discriminative vector machine (DVM) classifier. The improvements of the proposed method mainly consist in introducing an effective feature extraction method that can capture discriminative features from the evolutionary-based information and physicochemical characteristics, and then a powerful and robust DVM classifier is employed. To the best of our knowledge, it is the first time that DVM model is applied to the field of bioinformatics. When applying the proposed method to the Yeast and Helicobacter pylori (H. pylori) datasets, we obtain excellent prediction accuracies of 94.35% and 90.61%, respectively. The computational results indicate that our method is effective and robust for predicting PPIs, and can be taken as a useful supplementary tool to the traditional experimental methods for future proteomics research. PMID:27571061

  13. Accurate prediction of adsorption energies on graphene, using a dispersion-corrected semiempirical method including solvation.

    PubMed

    Vincent, Mark A; Hillier, Ian H

    2014-08-25

    The accurate prediction of the adsorption energies of unsaturated molecules on graphene in the presence of water is essential for the design of molecules that can modify its properties and that can aid its processability. We here show that a semiempirical MO method corrected for dispersive interactions (PM6-DH2) can predict the adsorption energies of unsaturated hydrocarbons and the effect of substitution on these values to an accuracy comparable to DFT values and in good agreement with the experiment. The adsorption energies of TCNE, TCNQ, and a number of sulfonated pyrenes are also predicted, along with the effect of hydration using the COSMO model.

  14. ChIP-seq Accurately Predicts Tissue-Specific Activity of Enhancers

    SciTech Connect

    Visel, Axel; Blow, Matthew J.; Li, Zirong; Zhang, Tao; Akiyama, Jennifer A.; Holt, Amy; Plajzer-Frick, Ingrid; Shoukry, Malak; Wright, Crystal; Chen, Feng; Afzal, Veena; Ren, Bing; Rubin, Edward M.; Pennacchio, Len A.

    2009-02-01

    A major yet unresolved quest in decoding the human genome is the identification of the regulatory sequences that control the spatial and temporal expression of genes. Distant-acting transcriptional enhancers are particularly challenging to uncover since they are scattered amongst the vast non-coding portion of the genome. Evolutionary sequence constraint can facilitate the discovery of enhancers, but fails to predict when and where they are active in vivo. Here, we performed chromatin immunoprecipitation with the enhancer-associated protein p300, followed by massively-parallel sequencing, to map several thousand in vivo binding sites of p300 in mouse embryonic forebrain, midbrain, and limb tissue. We tested 86 of these sequences in a transgenic mouse assay, which in nearly all cases revealed reproducible enhancer activity in those tissues predicted by p300 binding. Our results indicate that in vivo mapping of p300 binding is a highly accurate means for identifying enhancers and their associated activities and suggest that such datasets will be useful to study the role of tissue-specific enhancers in human biology and disease on a genome-wide scale.

  15. Accurate load prediction by BEM with airfoil data from 3D RANS simulations

    NASA Astrophysics Data System (ADS)

    Schneider, Marc S.; Nitzsche, Jens; Hennings, Holger

    2016-09-01

    In this paper, two methods for the extraction of airfoil coefficients from 3D CFD simulations of a wind turbine rotor are investigated, and these coefficients are used to improve the load prediction of a BEM code. The coefficients are extracted from a number of steady RANS simulations, using either averaging of velocities in annular sections, or an inverse BEM approach for determination of the induction factors in the rotor plane. It is shown that these 3D rotor polars are able to capture the rotational augmentation at the inner part of the blade as well as the load reduction by 3D effects close to the blade tip. They are used as input to a simple BEM code and the results of this BEM with 3D rotor polars are compared to the predictions of BEM with 2D airfoil coefficients plus common empirical corrections for stall delay and tip loss. While BEM with 2D airfoil coefficients produces a very different radial distribution of loads than the RANS simulation, the BEM with 3D rotor polars manages to reproduce the loads from RANS very accurately for a variety of load cases, as long as the blade pitch angle is not too different from the cases from which the polars were extracted.

  16. Accurately predicting copper interconnect topographies in foundry design for manufacturability flows

    NASA Astrophysics Data System (ADS)

    Lu, Daniel; Fan, Zhong; Tak, Ki Duk; Chang, Li-Fu; Zou, Elain; Jiang, Jenny; Yang, Josh; Zhuang, Linda; Chen, Kuang Han; Hurat, Philippe; Ding, Hua

    2011-04-01

    This paper presents a model-based Chemical Mechanical Polishing (CMP) Design for Manufacturability (DFM) () methodology that includes an accurate prediction of post-CMP copper interconnect topographies at the advanced process technology nodes. Using procedures of extensive model calibration and validation, the CMP process model accurately predicts post-CMP dimensions, such as erosion, dishing, and copper thickness with excellent correlation to silicon measurements. This methodology provides an efficient DFM flow to detect and fix physical manufacturing hotspots related to copper pooling and Depth of Focus (DOF) failures at both block- and full chip level designs. Moreover, the predicted thickness output is used in the CMP-aware RC extraction and Timing analysis flows for better understanding of performance yield and timing impact. In addition, the CMP model can be applied to the verification of model-based dummy fill flows.

  17. Cas9-chromatin binding information enables more accurate CRISPR off-target prediction

    PubMed Central

    Singh, Ritambhara; Kuscu, Cem; Quinlan, Aaron; Qi, Yanjun; Adli, Mazhar

    2015-01-01

    The CRISPR system has become a powerful biological tool with a wide range of applications. However, improving targeting specificity and accurately predicting potential off-targets remains a significant goal. Here, we introduce a web-based CRISPR/Cas9 Off-target Prediction and Identification Tool (CROP-IT) that performs improved off-target binding and cleavage site predictions. Unlike existing prediction programs that solely use DNA sequence information; CROP-IT integrates whole genome level biological information from existing Cas9 binding and cleavage data sets. Utilizing whole-genome chromatin state information from 125 human cell types further enhances its computational prediction power. Comparative analyses on experimentally validated datasets show that CROP-IT outperforms existing computational algorithms in predicting both Cas9 binding as well as cleavage sites. With a user-friendly web-interface, CROP-IT outputs scored and ranked list of potential off-targets that enables improved guide RNA design and more accurate prediction of Cas9 binding or cleavage sites. PMID:26032770

  18. Can radiation therapy treatment planning system accurately predict surface doses in postmastectomy radiation therapy patients?

    SciTech Connect

    Wong, Sharon; Back, Michael; Tan, Poh Wee; Lee, Khai Mun; Baggarley, Shaun; Lu, Jaide Jay

    2012-07-01

    Skin doses have been an important factor in the dose prescription for breast radiotherapy. Recent advances in radiotherapy treatment techniques, such as intensity-modulated radiation therapy (IMRT) and new treatment schemes such as hypofractionated breast therapy have made the precise determination of the surface dose necessary. Detailed information of the dose at various depths of the skin is also critical in designing new treatment strategies. The purpose of this work was to assess the accuracy of surface dose calculation by a clinically used treatment planning system and those measured by thermoluminescence dosimeters (TLDs) in a customized chest wall phantom. This study involved the construction of a chest wall phantom for skin dose assessment. Seven TLDs were distributed throughout each right chest wall phantom to give adequate representation of measured radiation doses. Point doses from the CMS Xio Registered-Sign treatment planning system (TPS) were calculated for each relevant TLD positions and results correlated. There were no significant difference between measured absorbed dose by TLD and calculated doses by the TPS (p > 0.05 (1-tailed). Dose accuracy of up to 2.21% was found. The deviations from the calculated absorbed doses were overall larger (3.4%) when wedges and bolus were used. 3D radiotherapy TPS is a useful and accurate tool to assess the accuracy of surface dose. Our studies have shown that radiation treatment accuracy expressed as a comparison between calculated doses (by TPS) and measured doses (by TLD dosimetry) can be accurately predicted for tangential treatment of the chest wall after mastectomy.

  19. New consensus definition for acute kidney injury accurately predicts 30-day mortality in cirrhosis with infection

    PubMed Central

    Wong, Florence; O’Leary, Jacqueline G; Reddy, K Rajender; Patton, Heather; Kamath, Patrick S; Fallon, Michael B; Garcia-Tsao, Guadalupe; Subramanian, Ram M.; Malik, Raza; Maliakkal, Benedict; Thacker, Leroy R; Bajaj, Jasmohan S

    2015-01-01

    Background & Aims A consensus conference proposed that cirrhosis-associated acute kidney injury (AKI) be defined as an increase in serum creatinine by >50% from the stable baseline value in <6 months or by ≥0.3mg/dL in <48 hrs. We prospectively evaluated the ability of these criteria to predict mortality within 30 days among hospitalized patients with cirrhosis and infection. Methods 337 patients with cirrhosis admitted with or developed an infection in hospital (56% men; 56±10 y old; model for end-stage liver disease score, 20±8) were followed. We compared data on 30-day mortality, hospital length-of-stay, and organ failure between patients with and without AKI. Results 166 (49%) developed AKI during hospitalization, based on the consensus criteria. Patients who developed AKI had higher admission Child-Pugh (11.0±2.1 vs 9.6±2.1; P<.0001), and MELD scores (23±8 vs17±7; P<.0001), and lower mean arterial pressure (81±16mmHg vs 85±15mmHg; P<.01) than those who did not. Also higher amongst patients with AKI were mortality in ≤30 days (34% vs 7%), intensive care unit transfer (46% vs 20%), ventilation requirement (27% vs 6%), and shock (31% vs 8%); AKI patients also had longer hospital stays (17.8±19.8 days vs 13.3±31.8 days) (all P<.001). 56% of AKI episodes were transient, 28% persistent, and 16% resulted in dialysis. Mortality was 80% among those without renal recovery, higher compared to partial (40%) or complete recovery (15%), or AKI-free patients (7%; P<.0001). Conclusions 30-day mortality is 10-fold higher among infected hospitalized cirrhotic patients with irreversible AKI than those without AKI. The consensus definition of AKI accurately predicts 30-day mortality, length of hospital stay, and organ failure. PMID:23999172

  20. Cluster abundance in chameleon f(R) gravity I: toward an accurate halo mass function prediction

    NASA Astrophysics Data System (ADS)

    Cataneo, Matteo; Rapetti, David; Lombriser, Lucas; Li, Baojiu

    2016-12-01

    We refine the mass and environment dependent spherical collapse model of chameleon f(R) gravity by calibrating a phenomenological correction inspired by the parameterized post-Friedmann framework against high-resolution N-body simulations. We employ our method to predict the corresponding modified halo mass function, and provide fitting formulas to calculate the enhancement of the f(R) halo abundance with respect to that of General Relativity (GR) within a precision of lesssim 5% from the results obtained in the simulations. Similar accuracy can be achieved for the full f(R) mass function on the condition that the modeling of the reference GR abundance of halos is accurate at the percent level. We use our fits to forecast constraints on the additional scalar degree of freedom of the theory, finding that upper bounds competitive with current Solar System tests are within reach of cluster number count analyses from ongoing and upcoming surveys at much larger scales. Importantly, the flexibility of our method allows also for this to be applied to other scalar-tensor theories characterized by a mass and environment dependent spherical collapse.

  1. Accurate prediction of band gaps and optical properties of HfO2

    NASA Astrophysics Data System (ADS)

    Ondračka, Pavel; Holec, David; Nečas, David; Zajíčková, Lenka

    2016-10-01

    We report on optical properties of various polymorphs of hafnia predicted within the framework of density functional theory. The full potential linearised augmented plane wave method was employed together with the Tran-Blaha modified Becke-Johnson potential (TB-mBJ) for exchange and local density approximation for correlation. Unit cells of monoclinic, cubic and tetragonal crystalline, and a simulated annealing-based model of amorphous hafnia were fully relaxed with respect to internal positions and lattice parameters. Electronic structures and band gaps for monoclinic, cubic, tetragonal and amorphous hafnia were calculated using three different TB-mBJ parametrisations and the results were critically compared with the available experimental and theoretical reports. Conceptual differences between a straightforward comparison of experimental measurements to a calculated band gap on the one hand and to a whole electronic structure (density of electronic states) on the other hand, were pointed out, suggesting the latter should be used whenever possible. Finally, dielectric functions were calculated at two levels, using the random phase approximation without local field effects and with a more accurate Bethe-Salpether equation (BSE) to account for excitonic effects. We conclude that a satisfactory agreement with experimental data for HfO2 was obtained only in the latter case.

  2. Highly Accurate Structure-Based Prediction of HIV-1 Coreceptor Usage Suggests Intermolecular Interactions Driving Tropism.

    PubMed

    Kieslich, Chris A; Tamamis, Phanourios; Guzman, Yannis A; Onel, Melis; Floudas, Christodoulos A

    2016-01-01

    HIV-1 entry into host cells is mediated by interactions between the V3-loop of viral glycoprotein gp120 and chemokine receptor CCR5 or CXCR4, collectively known as HIV-1 coreceptors. Accurate genotypic prediction of coreceptor usage is of significant clinical interest and determination of the factors driving tropism has been the focus of extensive study. We have developed a method based on nonlinear support vector machines to elucidate the interacting residue pairs driving coreceptor usage and provide highly accurate coreceptor usage predictions. Our models utilize centroid-centroid interaction energies from computationally derived structures of the V3-loop:coreceptor complexes as primary features, while additional features based on established rules regarding V3-loop sequences are also investigated. We tested our method on 2455 V3-loop sequences of various lengths and subtypes, and produce a median area under the receiver operator curve of 0.977 based on 500 runs of 10-fold cross validation. Our study is the first to elucidate a small set of specific interacting residue pairs between the V3-loop and coreceptors capable of predicting coreceptor usage with high accuracy across major HIV-1 subtypes. The developed method has been implemented as a web tool named CRUSH, CoReceptor USage prediction for HIV-1, which is available at http://ares.tamu.edu/CRUSH/.

  3. Accurate prediction of the linear viscoelastic properties of highly entangled mono and bidisperse polymer melts.

    PubMed

    Stephanou, Pavlos S; Mavrantzas, Vlasis G

    2014-06-07

    We present a hierarchical computational methodology which permits the accurate prediction of the linear viscoelastic properties of entangled polymer melts directly from the chemical structure, chemical composition, and molecular architecture of the constituent chains. The method entails three steps: execution of long molecular dynamics simulations with moderately entangled polymer melts, self-consistent mapping of the accumulated trajectories onto a tube model and parameterization or fine-tuning of the model on the basis of detailed simulation data, and use of the modified tube model to predict the linear viscoelastic properties of significantly higher molecular weight (MW) melts of the same polymer. Predictions are reported for the zero-shear-rate viscosity η0 and the spectra of storage G'(ω) and loss G″(ω) moduli for several mono and bidisperse cis- and trans-1,4 polybutadiene melts as well as for their MW dependence, and are found to be in remarkable agreement with experimentally measured rheological data.

  4. Planar Near-Field Phase Retrieval Using GPUs for Accurate THz Far-Field Prediction

    NASA Astrophysics Data System (ADS)

    Junkin, Gary

    2013-04-01

    With a view to using Phase Retrieval to accurately predict Terahertz antenna far-field from near-field intensity measurements, this paper reports on three fundamental advances that achieve very low algorithmic error penalties. The first is a new Gaussian beam analysis that provides accurate initial complex aperture estimates including defocus and astigmatic phase errors, based only on first and second moment calculations. The second is a powerful noise tolerant near-field Phase Retrieval algorithm that combines Anderson's Plane-to-Plane (PTP) with Fienup's Hybrid-Input-Output (HIO) and Successive Over-Relaxation (SOR) to achieve increased accuracy at reduced scan separations. The third advance employs teraflop Graphical Processing Units (GPUs) to achieve practically real time near-field phase retrieval and to obtain the optimum aperture constraint without any a priori information.

  5. Raoult’s law revisited: accurately predicting equilibrium relative humidity points for humidity control experiments

    PubMed Central

    Bowler, Michael G.

    2017-01-01

    The humidity surrounding a sample is an important variable in scientific experiments. Biological samples in particular require not just a humid atmosphere but often a relative humidity (RH) that is in equilibrium with a stabilizing solution required to maintain the sample in the same state during measurements. The controlled dehydration of macromolecular crystals can lead to significant increases in crystal order, leading to higher diffraction quality. Devices that can accurately control the humidity surrounding crystals while monitoring diffraction have led to this technique being increasingly adopted, as the experiments become easier and more reproducible. Matching the RH to the mother liquor is the first step in allowing the stable mounting of a crystal. In previous work [Wheeler, Russi, Bowler & Bowler (2012). Acta Cryst. F68, 111–114], the equilibrium RHs were measured for a range of concentrations of the most commonly used precipitants in macromolecular crystallography and it was shown how these related to Raoult’s law for the equilibrium vapour pressure of water above a solution. However, a discrepancy between the measured values and those predicted by theory could not be explained. Here, a more precise humidity control device has been used to determine equilibrium RH points. The new results are in agreement with Raoult’s law. A simple argument in statistical mechanics is also presented, demonstrating that the equilibrium vapour pressure of a solvent is proportional to its mole fraction in an ideal solution: Raoult’s law. The same argument can be extended to the case where the solvent and solute molecules are of different sizes, as is the case with polymers. The results provide a framework for the correct maintenance of the RH surrounding a sample. PMID:28381983

  6. Raoult's law revisited: accurately predicting equilibrium relative humidity points for humidity control experiments.

    PubMed

    Bowler, Michael G; Bowler, David R; Bowler, Matthew W

    2017-04-01

    The humidity surrounding a sample is an important variable in scientific experiments. Biological samples in particular require not just a humid atmosphere but often a relative humidity (RH) that is in equilibrium with a stabilizing solution required to maintain the sample in the same state during measurements. The controlled dehydration of macromolecular crystals can lead to significant increases in crystal order, leading to higher diffraction quality. Devices that can accurately control the humidity surrounding crystals while monitoring diffraction have led to this technique being increasingly adopted, as the experiments become easier and more reproducible. Matching the RH to the mother liquor is the first step in allowing the stable mounting of a crystal. In previous work [Wheeler, Russi, Bowler & Bowler (2012). Acta Cryst. F68, 111-114], the equilibrium RHs were measured for a range of concentrations of the most commonly used precipitants in macromolecular crystallography and it was shown how these related to Raoult's law for the equilibrium vapour pressure of water above a solution. However, a discrepancy between the measured values and those predicted by theory could not be explained. Here, a more precise humidity control device has been used to determine equilibrium RH points. The new results are in agreement with Raoult's law. A simple argument in statistical mechanics is also presented, demonstrating that the equilibrium vapour pressure of a solvent is proportional to its mole fraction in an ideal solution: Raoult's law. The same argument can be extended to the case where the solvent and solute molecules are of different sizes, as is the case with polymers. The results provide a framework for the correct maintenance of the RH surrounding a sample.

  7. Machine Learning Predictions of Molecular Properties: Accurate Many-Body Potentials and Nonlocality in Chemical Space.

    PubMed

    Hansen, Katja; Biegler, Franziska; Ramakrishnan, Raghunathan; Pronobis, Wiktor; von Lilienfeld, O Anatole; Müller, Klaus-Robert; Tkatchenko, Alexandre

    2015-06-18

    Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and apply a systematic hierarchy of efficient empirical methods to estimate atomization and total energies of molecules. These methods range from a simple sum over atoms, to addition of bond energies, to pairwise interatomic force fields, reaching to the more sophisticated machine learning approaches that are capable of describing collective interactions between many atoms or bonds. In the case of equilibrium molecular geometries, even simple pairwise force fields demonstrate prediction accuracy comparable to benchmark energies calculated using density functional theory with hybrid exchange-correlation functionals; however, accounting for the collective many-body interactions proves to be essential for approaching the “holy grail” of chemical accuracy of 1 kcal/mol for both equilibrium and out-of-equilibrium geometries. This remarkable accuracy is achieved by a vectorized representation of molecules (so-called Bag of Bonds model) that exhibits strong nonlocality in chemical space. In addition, the same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies.

  8. Machine learning predictions of molecular properties: Accurate many-body potentials and nonlocality in chemical space

    DOE PAGES

    Hansen, Katja; Biegler, Franziska; Ramakrishnan, Raghunathan; ...

    2015-06-04

    Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and apply a systematic hierarchy of efficient empirical methods to estimate atomization and total energies of molecules. These methods range from a simple sum over atoms, to addition of bond energies, to pairwise interatomic force fields, reaching to the more sophisticated machine learning approaches that are capable of describing collective interactions between many atoms or bonds. In the case of equilibrium molecular geometries, even simple pairwise force fields demonstratemore » prediction accuracy comparable to benchmark energies calculated using density functional theory with hybrid exchange-correlation functionals; however, accounting for the collective many-body interactions proves to be essential for approaching the “holy grail” of chemical accuracy of 1 kcal/mol for both equilibrium and out-of-equilibrium geometries. This remarkable accuracy is achieved by a vectorized representation of molecules (so-called Bag of Bonds model) that exhibits strong nonlocality in chemical space. The same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies.« less

  9. Machine learning predictions of molecular properties: Accurate many-body potentials and nonlocality in chemical space

    SciTech Connect

    Hansen, Katja; Biegler, Franziska; Ramakrishnan, Raghunathan; Pronobis, Wiktor; von Lilienfeld, O. Anatole; Müller, Klaus -Robert; Tkatchenko, Alexandre

    2015-06-04

    Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and apply a systematic hierarchy of efficient empirical methods to estimate atomization and total energies of molecules. These methods range from a simple sum over atoms, to addition of bond energies, to pairwise interatomic force fields, reaching to the more sophisticated machine learning approaches that are capable of describing collective interactions between many atoms or bonds. In the case of equilibrium molecular geometries, even simple pairwise force fields demonstrate prediction accuracy comparable to benchmark energies calculated using density functional theory with hybrid exchange-correlation functionals; however, accounting for the collective many-body interactions proves to be essential for approaching the “holy grail” of chemical accuracy of 1 kcal/mol for both equilibrium and out-of-equilibrium geometries. This remarkable accuracy is achieved by a vectorized representation of molecules (so-called Bag of Bonds model) that exhibits strong nonlocality in chemical space. The same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies.

  10. A Novel Method for Accurate Operon Predictions in All SequencedProkaryotes

    SciTech Connect

    Price, Morgan N.; Huang, Katherine H.; Alm, Eric J.; Arkin, Adam P.

    2004-12-01

    We combine comparative genomic measures and the distance separating adjacent genes to predict operons in 124 completely sequenced prokaryotic genomes. Our method automatically tailors itself to each genome using sequence information alone, and thus can be applied to any prokaryote. For Escherichia coli K12 and Bacillus subtilis, our method is 85 and 83% accurate, respectively, which is similar to the accuracy of methods that use the same features but are trained on experimentally characterized transcripts. In Halobacterium NRC-1 and in Helicobacterpylori, our method correctly infers that genes in operons are separated by shorter distances than they are in E.coli, and its predictions using distance alone are more accurate than distance-only predictions trained on a database of E.coli transcripts. We use microarray data from sixphylogenetically diverse prokaryotes to show that combining intergenic distance with comparative genomic measures further improves accuracy and that our method is broadly effective. Finally, we survey operon structure across 124 genomes, and find several surprises: H.pylori has many operons, contrary to previous reports; Bacillus anthracis has an unusual number of pseudogenes within conserved operons; and Synechocystis PCC6803 has many operons even though it has unusually wide spacings between conserved adjacent genes.

  11. Accurate prediction of severe allergic reactions by a small set of environmental parameters (NDVI, temperature).

    PubMed

    Notas, George; Bariotakis, Michail; Kalogrias, Vaios; Andrianaki, Maria; Azariadis, Kalliopi; Kampouri, Errika; Theodoropoulou, Katerina; Lavrentaki, Katerina; Kastrinakis, Stelios; Kampa, Marilena; Agouridakis, Panagiotis; Pirintsos, Stergios; Castanas, Elias

    2015-01-01

    Severe allergic reactions of unknown etiology,necessitating a hospital visit, have an important impact in the life of affected individuals and impose a major economic burden to societies. The prediction of clinically severe allergic reactions would be of great importance, but current attempts have been limited by the lack of a well-founded applicable methodology and the wide spatiotemporal distribution of allergic reactions. The valid prediction of severe allergies (and especially those needing hospital treatment) in a region, could alert health authorities and implicated individuals to take appropriate preemptive measures. In the present report we have collecterd visits for serious allergic reactions of unknown etiology from two major hospitals in the island of Crete, for two distinct time periods (validation and test sets). We have used the Normalized Difference Vegetation Index (NDVI), a satellite-based, freely available measurement, which is an indicator of live green vegetation at a given geographic area, and a set of meteorological data to develop a model capable of describing and predicting severe allergic reaction frequency. Our analysis has retained NDVI and temperature as accurate identifiers and predictors of increased hospital severe allergic reactions visits. Our approach may contribute towards the development of satellite-based modules, for the prediction of severe allergic reactions in specific, well-defined geographical areas. It could also probably be used for the prediction of other environment related diseases and conditions.

  12. Microstructure-Dependent Gas Adsorption: Accurate Predictions of Methane Uptake in Nanoporous Carbons

    SciTech Connect

    Ihm, Yungok; Cooper, Valentino R; Gallego, Nidia C; Contescu, Cristian I; Morris, James R

    2014-01-01

    We demonstrate a successful, efficient framework for predicting gas adsorption properties in real materials based on first-principles calculations, with a specific comparison of experiment and theory for methane adsorption in activated carbons. These carbon materials have different pore size distributions, leading to a variety of uptake characteristics. Utilizing these distributions, we accurately predict experimental uptakes and heats of adsorption without empirical potentials or lengthy simulations. We demonstrate that materials with smaller pores have higher heats of adsorption, leading to a higher gas density in these pores. This pore-size dependence must be accounted for, in order to predict and understand the adsorption behavior. The theoretical approach combines: (1) ab initio calculations with a van der Waals density functional to determine adsorbent-adsorbate interactions, and (2) a thermodynamic method that predicts equilibrium adsorption densities by directly incorporating the calculated potential energy surface in a slit pore model. The predicted uptake at P=20 bar and T=298 K is in excellent agreement for all five activated carbon materials used. This approach uses only the pore-size distribution as an input, with no fitting parameters or empirical adsorbent-adsorbate interactions, and thus can be easily applied to other adsorbent-adsorbate combinations.

  13. Accurate Prediction of Severe Allergic Reactions by a Small Set of Environmental Parameters (NDVI, Temperature)

    PubMed Central

    Andrianaki, Maria; Azariadis, Kalliopi; Kampouri, Errika; Theodoropoulou, Katerina; Lavrentaki, Katerina; Kastrinakis, Stelios; Kampa, Marilena; Agouridakis, Panagiotis; Pirintsos, Stergios; Castanas, Elias

    2015-01-01

    Severe allergic reactions of unknown etiology,necessitating a hospital visit, have an important impact in the life of affected individuals and impose a major economic burden to societies. The prediction of clinically severe allergic reactions would be of great importance, but current attempts have been limited by the lack of a well-founded applicable methodology and the wide spatiotemporal distribution of allergic reactions. The valid prediction of severe allergies (and especially those needing hospital treatment) in a region, could alert health authorities and implicated individuals to take appropriate preemptive measures. In the present report we have collecterd visits for serious allergic reactions of unknown etiology from two major hospitals in the island of Crete, for two distinct time periods (validation and test sets). We have used the Normalized Difference Vegetation Index (NDVI), a satellite-based, freely available measurement, which is an indicator of live green vegetation at a given geographic area, and a set of meteorological data to develop a model capable of describing and predicting severe allergic reaction frequency. Our analysis has retained NDVI and temperature as accurate identifiers and predictors of increased hospital severe allergic reactions visits. Our approach may contribute towards the development of satellite-based modules, for the prediction of severe allergic reactions in specific, well-defined geographical areas. It could also probably be used for the prediction of other environment related diseases and conditions. PMID:25794106

  14. SIFTER search: a web server for accurate phylogeny-based protein function prediction

    PubMed Central

    Sahraeian, Sayed M.; Luo, Kevin R.; Brenner, Steven E.

    2015-01-01

    We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access to precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. The SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded. PMID:25979264

  15. SIFTER search: a web server for accurate phylogeny-based protein function prediction

    SciTech Connect

    Sahraeian, Sayed M.; Luo, Kevin R.; Brenner, Steven E.

    2015-05-15

    We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access to precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. Lastly, the SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded.

  16. SIFTER search: a web server for accurate phylogeny-based protein function prediction

    DOE PAGES

    Sahraeian, Sayed M.; Luo, Kevin R.; Brenner, Steven E.

    2015-05-15

    We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access tomore » precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. Lastly, the SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded.« less

  17. Special purpose hybrid transfinite elements and unified computational methodology for accurately predicting thermoelastic stress waves

    NASA Technical Reports Server (NTRS)

    Tamma, Kumar K.; Railkar, Sudhir B.

    1988-01-01

    This paper represents an attempt to apply extensions of a hybrid transfinite element computational approach for accurately predicting thermoelastic stress waves. The applicability of the present formulations for capturing the thermal stress waves induced by boundary heating for the well known Danilovskaya problems is demonstrated. A unique feature of the proposed formulations for applicability to the Danilovskaya problem of thermal stress waves in elastic solids lies in the hybrid nature of the unified formulations and the development of special purpose transfinite elements in conjunction with the classical Galerkin techniques and transformation concepts. Numerical test cases validate the applicability and superior capability to capture the thermal stress waves induced due to boundary heating.

  18. Accurate prediction of human drug toxicity: a major challenge in drug development.

    PubMed

    Li, Albert P

    2004-11-01

    Over the past decades, a number of drugs have been withdrawn or have required special labeling due to adverse effects observed post-marketing. Species differences in drug toxicity in preclinical safety tests and the lack of sensitive biomarkers and nonrepresentative patient population in clinical trials are probable reasons for the failures in predicting human drug toxicity. It is proposed that toxicology should evolve from an empirical practice to an investigative discipline. Accurate prediction of human drug toxicity requires resources and time to be spent in clearly defining key toxic pathways and corresponding risk factors, which hopefully, will be compensated by the benefits of a lower percentage of clinical failure due to toxicity and a decreased frequency of market withdrawal due to unacceptable adverse drug effects.

  19. Size-extensivity-corrected multireference configuration interaction schemes to accurately predict bond dissociation energies of oxygenated hydrocarbons

    SciTech Connect

    Oyeyemi, Victor B.; Krisiloff, David B.; Keith, John A.; Libisch, Florian; Pavone, Michele; Carter, Emily A.

    2014-01-28

    Oxygenated hydrocarbons play important roles in combustion science as renewable fuels and additives, but many details about their combustion chemistry remain poorly understood. Although many methods exist for computing accurate electronic energies of molecules at equilibrium geometries, a consistent description of entire combustion reaction potential energy surfaces (PESs) requires multireference correlated wavefunction theories. Here we use bond dissociation energies (BDEs) as a foundational metric to benchmark methods based on multireference configuration interaction (MRCI) for several classes of oxygenated compounds (alcohols, aldehydes, carboxylic acids, and methyl esters). We compare results from multireference singles and doubles configuration interaction to those utilizing a posteriori and a priori size-extensivity corrections, benchmarked against experiment and coupled cluster theory. We demonstrate that size-extensivity corrections are necessary for chemically accurate BDE predictions even in relatively small molecules and furnish examples of unphysical BDE predictions resulting from using too-small orbital active spaces. We also outline the specific challenges in using MRCI methods for carbonyl-containing compounds. The resulting complete basis set extrapolated, size-extensivity-corrected MRCI scheme produces BDEs generally accurate to within 1 kcal/mol, laying the foundation for this scheme's use on larger molecules and for more complex regions of combustion PESs.

  20. Size-extensivity-corrected multireference configuration interaction schemes to accurately predict bond dissociation energies of oxygenated hydrocarbons

    NASA Astrophysics Data System (ADS)

    Oyeyemi, Victor B.; Krisiloff, David B.; Keith, John A.; Libisch, Florian; Pavone, Michele; Carter, Emily A.

    2014-01-01

    Oxygenated hydrocarbons play important roles in combustion science as renewable fuels and additives, but many details about their combustion chemistry remain poorly understood. Although many methods exist for computing accurate electronic energies of molecules at equilibrium geometries, a consistent description of entire combustion reaction potential energy surfaces (PESs) requires multireference correlated wavefunction theories. Here we use bond dissociation energies (BDEs) as a foundational metric to benchmark methods based on multireference configuration interaction (MRCI) for several classes of oxygenated compounds (alcohols, aldehydes, carboxylic acids, and methyl esters). We compare results from multireference singles and doubles configuration interaction to those utilizing a posteriori and a priori size-extensivity corrections, benchmarked against experiment and coupled cluster theory. We demonstrate that size-extensivity corrections are necessary for chemically accurate BDE predictions even in relatively small molecules and furnish examples of unphysical BDE predictions resulting from using too-small orbital active spaces. We also outline the specific challenges in using MRCI methods for carbonyl-containing compounds. The resulting complete basis set extrapolated, size-extensivity-corrected MRCI scheme produces BDEs generally accurate to within 1 kcal/mol, laying the foundation for this scheme's use on larger molecules and for more complex regions of combustion PESs.

  1. Accurate prediction of the response of freshwater fish to a mixture of estrogenic chemicals.

    PubMed

    Brian, Jayne V; Harris, Catherine A; Scholze, Martin; Backhaus, Thomas; Booy, Petra; Lamoree, Marja; Pojana, Giulio; Jonkers, Niels; Runnalls, Tamsin; Bonfà, Angela; Marcomini, Antonio; Sumpter, John P

    2005-06-01

    Existing environmental risk assessment procedures are limited in their ability to evaluate the combined effects of chemical mixtures. We investigated the implications of this by analyzing the combined effects of a multicomponent mixture of five estrogenic chemicals using vitellogenin induction in male fathead minnows as an end point. The mixture consisted of estradiol, ethynylestradiol, nonylphenol, octylphenol, and bisphenol A. We determined concentration-response curves for each of the chemicals individually. The chemicals were then combined at equipotent concentrations and the mixture tested using fixed-ratio design. The effects of the mixture were compared with those predicted by the model of concentration addition using biomathematical methods, which revealed that there was no deviation between the observed and predicted effects of the mixture. These findings demonstrate that estrogenic chemicals have the capacity to act together in an additive manner and that their combined effects can be accurately predicted by concentration addition. We also explored the potential for mixture effects at low concentrations by exposing the fish to each chemical at one-fifth of its median effective concentration (EC50). Individually, the chemicals did not induce a significant response, although their combined effects were consistent with the predictions of concentration addition. This demonstrates the potential for estrogenic chemicals to act additively at environmentally relevant concentrations. These findings highlight the potential for existing environmental risk assessment procedures to underestimate the hazard posed by mixtures of chemicals that act via a similar mode of action, thereby leading to erroneous conclusions of absence of risk.

  2. Accurate Prediction of the Response of Freshwater Fish to a Mixture of Estrogenic Chemicals

    PubMed Central

    Brian, Jayne V.; Harris, Catherine A.; Scholze, Martin; Backhaus, Thomas; Booy, Petra; Lamoree, Marja; Pojana, Giulio; Jonkers, Niels; Runnalls, Tamsin; Bonfà, Angela; Marcomini, Antonio; Sumpter, John P.

    2005-01-01

    Existing environmental risk assessment procedures are limited in their ability to evaluate the combined effects of chemical mixtures. We investigated the implications of this by analyzing the combined effects of a multicomponent mixture of five estrogenic chemicals using vitellogenin induction in male fathead minnows as an end point. The mixture consisted of estradiol, ethynylestradiol, nonylphenol, octylphenol, and bisphenol A. We determined concentration–response curves for each of the chemicals individually. The chemicals were then combined at equipotent concentrations and the mixture tested using fixed-ratio design. The effects of the mixture were compared with those predicted by the model of concentration addition using biomathematical methods, which revealed that there was no deviation between the observed and predicted effects of the mixture. These findings demonstrate that estrogenic chemicals have the capacity to act together in an additive manner and that their combined effects can be accurately predicted by concentration addition. We also explored the potential for mixture effects at low concentrations by exposing the fish to each chemical at one-fifth of its median effective concentration (EC50). Individually, the chemicals did not induce a significant response, although their combined effects were consistent with the predictions of concentration addition. This demonstrates the potential for estrogenic chemicals to act additively at environmentally relevant concentrations. These findings highlight the potential for existing environmental risk assessment procedures to underestimate the hazard posed by mixtures of chemicals that act via a similar mode of action, thereby leading to erroneous conclusions of absence of risk. PMID:15929895

  3. IDSite: An accurate approach to predict P450-mediated drug metabolism

    PubMed Central

    Li, Jianing; Schneebeli, Severin T.; Bylund, Joseph; Farid, Ramy; Friesner, Richard A.

    2011-01-01

    Accurate prediction of drug metabolism is crucial for drug design. Since a large majority of drugs metabolism involves P450 enzymes, we herein describe a computational approach, IDSite, to predict P450-mediated drug metabolism. To model induced-fit effects, IDSite samples the conformational space with flexible docking in Glide followed by two refinement stages using the Protein Local Optimization Program (PLOP). Sites of metabolism (SOMs) are predicted according to a physical-based score that evaluates the potential of atoms to react with the catalytic iron center. As a preliminary test, we present in this paper the prediction of hydroxylation and O-dealkylation sites mediated by CYP2D6 using two different models: a physical-based simulation model, and a modification of this model in which a small number of parameters are fit to a training set. Without fitting any parameters to experimental data, the Physical IDSite scoring recovers 83% of the experimental observations for 56 compounds with a very low false positive rate. With only 4 fitted parameters, the Fitted IDSite was trained with the subset of 36 compounds and successfully applied to the other 20 compounds, recovering 94% of the experimental observations with high sensitivity and specificity for both sets. PMID:22247702

  4. Combining transcription factor binding affinities with open-chromatin data for accurate gene expression prediction.

    PubMed

    Schmidt, Florian; Gasparoni, Nina; Gasparoni, Gilles; Gianmoena, Kathrin; Cadenas, Cristina; Polansky, Julia K; Ebert, Peter; Nordström, Karl; Barann, Matthias; Sinha, Anupam; Fröhler, Sebastian; Xiong, Jieyi; Dehghani Amirabad, Azim; Behjati Ardakani, Fatemeh; Hutter, Barbara; Zipprich, Gideon; Felder, Bärbel; Eils, Jürgen; Brors, Benedikt; Chen, Wei; Hengstler, Jan G; Hamann, Alf; Lengauer, Thomas; Rosenstiel, Philip; Walter, Jörn; Schulz, Marcel H

    2017-01-09

    The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid costly TF ChIP-seq assays. Thus, it is important to develop computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices. TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq. Additionally, Histone-Marks (HMs) can be used to identify candidate TF binding sites. TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength. Using machine learning, we find low affinity binding sites to improve our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites. Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance. In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq data sets. Finally, these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively.

  5. Combining transcription factor binding affinities with open-chromatin data for accurate gene expression prediction

    PubMed Central

    Schmidt, Florian; Gasparoni, Nina; Gasparoni, Gilles; Gianmoena, Kathrin; Cadenas, Cristina; Polansky, Julia K.; Ebert, Peter; Nordström, Karl; Barann, Matthias; Sinha, Anupam; Fröhler, Sebastian; Xiong, Jieyi; Dehghani Amirabad, Azim; Behjati Ardakani, Fatemeh; Hutter, Barbara; Zipprich, Gideon; Felder, Bärbel; Eils, Jürgen; Brors, Benedikt; Chen, Wei; Hengstler, Jan G.; Hamann, Alf; Lengauer, Thomas; Rosenstiel, Philip; Walter, Jörn; Schulz, Marcel H.

    2017-01-01

    The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid costly TF ChIP-seq assays. Thus, it is important to develop computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices. TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq. Additionally, Histone-Marks (HMs) can be used to identify candidate TF binding sites. TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength. Using machine learning, we find low affinity binding sites to improve our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites. Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance. In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq data sets. Finally, these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively. PMID:27899623

  6. Accurate prediction of cellular co-translational folding indicates proteins can switch from post- to co-translational folding

    NASA Astrophysics Data System (ADS)

    Nissley, Daniel A.; Sharma, Ajeet K.; Ahmed, Nabeel; Friedrich, Ulrike A.; Kramer, Günter; Bukau, Bernd; O'Brien, Edward P.

    2016-02-01

    The rates at which domains fold and codons are translated are important factors in determining whether a nascent protein will co-translationally fold and function or misfold and malfunction. Here we develop a chemical kinetic model that calculates a protein domain's co-translational folding curve during synthesis using only the domain's bulk folding and unfolding rates and codon translation rates. We show that this model accurately predicts the course of co-translational folding measured in vivo for four different protein molecules. We then make predictions for a number of different proteins in yeast and find that synonymous codon substitutions, which change translation-elongation rates, can switch some protein domains from folding post-translationally to folding co-translationally--a result consistent with previous experimental studies. Our approach explains essential features of co-translational folding curves and predicts how varying the translation rate at different codon positions along a transcript's coding sequence affects this self-assembly process.

  7. DisoMCS: Accurately Predicting Protein Intrinsically Disordered Regions Using a Multi-Class Conservative Score Approach

    PubMed Central

    Wang, Zhiheng; Yang, Qianqian; Li, Tonghua; Cong, Peisheng

    2015-01-01

    The precise prediction of protein intrinsically disordered regions, which play a crucial role in biological procedures, is a necessary prerequisite to further the understanding of the principles and mechanisms of protein function. Here, we propose a novel predictor, DisoMCS, which is a more accurate predictor of protein intrinsically disordered regions. The DisoMCS bases on an original multi-class conservative score (MCS) obtained by sequence-order/disorder alignment. Initially, near-disorder regions are defined on fragments located at both the terminus of an ordered region connecting a disordered region. Then the multi-class conservative score is generated by sequence alignment against a known structure database and represented as order, near-disorder and disorder conservative scores. The MCS of each amino acid has three elements: order, near-disorder and disorder profiles. Finally, the MCS is exploited as features to identify disordered regions in sequences. DisoMCS utilizes a non-redundant data set as the training set, MCS and predicted secondary structure as features, and a conditional random field as the classification algorithm. In predicted near-disorder regions a residue is determined as an order or a disorder according to the optimized decision threshold. DisoMCS was evaluated by cross-validation, large-scale prediction, independent tests and CASP (Critical Assessment of Techniques for Protein Structure Prediction) tests. All results confirmed that DisoMCS was very competitive in terms of accuracy of prediction when compared with well-established publicly available disordered region predictors. It also indicated our approach was more accurate when a query has higher homologous with the knowledge database. Availability The DisoMCS is available at http://cal.tongji.edu.cn/disorder/. PMID:26090958

  8. Development of a method to accurately calculate the Dpb and quickly predict the strength of a chemical bond

    NASA Astrophysics Data System (ADS)

    Du, Xia; Zhao, Dong-Xia; Yang, Zhong-Zhi

    2013-02-01

    A new approach to characterize and measure bond strength has been developed. First, we propose a method to accurately calculate the potential acting on an electron in a molecule (PAEM) at the saddle point along a chemical bond in situ, denoted by Dpb. Then, a direct method to quickly evaluate bond strength is established. We choose some familiar molecules as models for benchmarking this method. As a practical application, the Dpb of base pairs in DNA along C-H and N-H bonds are obtained for the first time. All results show that C7-H of A-T and C8-H of G-C are the relatively weak bonds that are the injured positions in DNA damage. The significance of this work is twofold: (i) A method is developed to calculate Dpb of various sizable molecules in situ quickly and accurately; (ii) This work demonstrates the feasibility to quickly predict the bond strength in macromolecules.

  9. An Accurate Heading Solution using MEMS-based Gyroscope and Magnetometer Integrated System (Preliminary Results)

    NASA Astrophysics Data System (ADS)

    El-Diasty, M.

    2014-11-01

    An accurate heading solution is required for many applications and it can be achieved by high grade (high cost) gyroscopes (gyros) which may not be suitable for such applications. Micro-Electro Mechanical Systems-based (MEMS) is an emerging technology, which has the potential of providing heading solution using a low cost MEMS-based gyro. However, MEMS-gyro-based heading solution drifts significantly over time. The heading solution can also be estimated using MEMS-based magnetometer by measuring the horizontal components of the Earth magnetic field. The MEMS-magnetometer-based heading solution does not drift over time, but are contaminated by high level of noise and may be disturbed by the presence of magnetic field sources such as metal objects. This paper proposed an accurate heading estimation procedure based on the integration of MEMS-based gyro and magnetometer measurements that correct gyro and magnetometer measurements where gyro angular rates of changes are estimated using magnetometer measurements and then integrated with the measured gyro angular rates of changes with a robust filter to estimate the heading. The proposed integration solution is implemented using two data sets; one was conducted in static mode without magnetic disturbances and the second was conducted in kinematic mode with magnetic disturbances. The results showed that the proposed integrated heading solution provides accurate, smoothed and undisturbed solution when compared with magnetometerbased and gyro-based heading solutions.

  10. Exchange-Hole Dipole Dispersion Model for Accurate Energy Ranking in Molecular Crystal Structure Prediction.

    PubMed

    Whittleton, Sarah R; Otero-de-la-Roza, A; Johnson, Erin R

    2017-02-14

    Accurate energy ranking is a key facet to the problem of first-principles crystal-structure prediction (CSP) of molecular crystals. This work presents a systematic assessment of B86bPBE-XDM, a semilocal density functional combined with the exchange-hole dipole moment (XDM) dispersion model, for energy ranking using 14 compounds from the first five CSP blind tests. Specifically, the set of crystals studied comprises 11 rigid, planar compounds and 3 co-crystals. The experimental structure was correctly identified as the lowest in lattice energy for 12 of the 14 total crystals. One of the exceptions is 4-hydroxythiophene-2-carbonitrile, for which the experimental structure was correctly identified once a quasi-harmonic estimate of the vibrational free-energy contribution was included, evidencing the occasional importance of thermal corrections for accurate energy ranking. The other exception is an organic salt, where charge-transfer error (also called delocalization error) is expected to cause the base density functional to be unreliable. Provided the choice of base density functional is appropriate and an estimate of temperature effects is used, XDM-corrected density-functional theory is highly reliable for the energetic ranking of competing crystal structures.

  11. Measuring solar reflectance Part I: Defining a metric that accurately predicts solar heat gain

    SciTech Connect

    Levinson, Ronnen; Akbari, Hashem; Berdahl, Paul

    2010-05-14

    Solar reflectance can vary with the spectral and angular distributions of incident sunlight, which in turn depend on surface orientation, solar position and atmospheric conditions. A widely used solar reflectance metric based on the ASTM Standard E891 beam-normal solar spectral irradiance underestimates the solar heat gain of a spectrally selective 'cool colored' surface because this irradiance contains a greater fraction of near-infrared light than typically found in ordinary (unconcentrated) global sunlight. At mainland U.S. latitudes, this metric RE891BN can underestimate the annual peak solar heat gain of a typical roof or pavement (slope {le} 5:12 [23{sup o}]) by as much as 89 W m{sup -2}, and underestimate its peak surface temperature by up to 5 K. Using R{sub E891BN} to characterize roofs in a building energy simulation can exaggerate the economic value N of annual cool-roof net energy savings by as much as 23%. We define clear-sky air mass one global horizontal ('AM1GH') solar reflectance R{sub g,0}, a simple and easily measured property that more accurately predicts solar heat gain. R{sub g,0} predicts the annual peak solar heat gain of a roof or pavement to within 2 W m{sup -2}, and overestimates N by no more than 3%. R{sub g,0} is well suited to rating the solar reflectances of roofs, pavements and walls. We show in Part II that R{sub g,0} can be easily and accurately measured with a pyranometer, a solar spectrophotometer or version 6 of the Solar Spectrum Reflectometer.

  12. Point-of-care cardiac troponin test accurately predicts heat stroke severity in rats.

    PubMed

    Audet, Gerald N; Quinn, Carrie M; Leon, Lisa R

    2015-11-15

    Heat stroke (HS) remains a significant public health concern. Despite the substantial threat posed by HS, there is still no field or clinical test of HS severity. We suggested previously that circulating cardiac troponin (cTnI) could serve as a robust biomarker of HS severity after heating. In the present study, we hypothesized that (cTnI) point-of-care test (ctPOC) could be used to predict severity and organ damage at the onset of HS. Conscious male Fischer 344 rats (n = 16) continuously monitored for heart rate (HR), blood pressure (BP), and core temperature (Tc) (radiotelemetry) were heated to maximum Tc (Tc,Max) of 41.9 ± 0.1°C and recovered undisturbed for 24 h at an ambient temperature of 20°C. Blood samples were taken at Tc,Max and 24 h after heat via submandibular bleed and analyzed on ctPOC test. POC cTnI band intensity was ranked using a simple four-point scale via two blinded observers and compared with cTnI levels measured by a clinical blood analyzer. Blood was also analyzed for biomarkers of systemic organ damage. HS severity, as previously defined using HR, BP, and recovery Tc profile during heat exposure, correlated strongly with cTnI (R(2) = 0.69) at Tc,Max. POC cTnI band intensity ranking accurately predicted cTnI levels (R(2) = 0.64) and HS severity (R(2) = 0.83). Five markers of systemic organ damage also correlated with ctPOC score (albumin, alanine aminotransferase, blood urea nitrogen, cholesterol, and total bilirubin; R(2) > 0.4). This suggests that cTnI POC tests can accurately determine HS severity and could serve as simple, portable, cost-effective HS field tests.

  13. An accurate and efficient method to predict the electronic excitation energies of BODIPY fluorescent dyes.

    PubMed

    Wang, Jia-Nan; Jin, Jun-Ling; Geng, Yun; Sun, Shi-Ling; Xu, Hong-Liang; Lu, Ying-Hua; Su, Zhong-Min

    2013-03-15

    Recently, the extreme learning machine neural network (ELMNN) as a valid computing method has been proposed to predict the nonlinear optical property successfully (Wang et al., J. Comput. Chem. 2012, 33, 231). In this work, first, we follow this line of work to predict the electronic excitation energies using the ELMNN method. Significantly, the root mean square deviation of the predicted electronic excitation energies of 90 4,4-difluoro-4-bora-3a,4a-diaza-s-indacene (BODIPY) derivatives between the predicted and experimental values has been reduced to 0.13 eV. Second, four groups of molecule descriptors are considered when building the computing models. The results show that the quantum chemical descriptions have the closest intrinsic relation with the electronic excitation energy values. Finally, a user-friendly web server (EEEBPre: Prediction of electronic excitation energies for BODIPY dyes), which is freely accessible to public at the web site: http://202.198.129.218, has been built for prediction. This web server can return the predicted electronic excitation energy values of BODIPY dyes that are high consistent with the experimental values. We hope that this web server would be helpful to theoretical and experimental chemists in related research.

  14. Prognostic breast cancer signature identified from 3D culture model accurately predicts clinical outcome across independent datasets

    SciTech Connect

    Martin, Katherine J.; Patrick, Denis R.; Bissell, Mina J.; Fournier, Marcia V.

    2008-10-20

    One of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasets having 295, 286, and 118 samples, respectively. Our results show that the 3D-signature accurately predicts prognosis in three unrelated patient datasets. At 10 years, the probability of positive outcome was 52, 51, and 47 percent in the group with a poor-prognosis signature and 91, 75, and 71 percent in the group with a good-prognosis signature for the three datasets, respectively (Kaplan-Meier survival analysis, p<0.05). Hazard ratios for poor outcome were 5.5 (95% CI 3.0 to 12.2, p<0.0001), 2.4 (95% CI 1.6 to 3.6, p<0.0001) and 1.9 (95% CI 1.1 to 3.2, p = 0.016) and remained significant for the two larger datasets when corrected for estrogen receptor (ER) status. Hence the 3D-signature accurately predicts breast cancer outcome in both ER-positive and ER-negative tumors, though individual genes differed in their prognostic ability in the two subtypes. Genes that were prognostic in ER+ patients are AURKA, CEP55, RRM2, EPHA2, FGFBP1, and VRK1, while genes prognostic in ER patients include ACTB, FOXM1 and SERPINE2 (Kaplan-Meier p<0.05). Multivariable Cox regression analysis in the largest dataset showed that the 3D-signature was a strong independent factor in predicting breast cancer outcome. The 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds prognostic

  15. A Critical Review for Developing Accurate and Dynamic Predictive Models Using Machine Learning Methods in Medicine and Health Care.

    PubMed

    Alanazi, Hamdan O; Abdullah, Abdul Hanan; Qureshi, Kashif Naseer

    2017-04-01

    Recently, Artificial Intelligence (AI) has been used widely in medicine and health care sector. In machine learning, the classification or prediction is a major field of AI. Today, the study of existing predictive models based on machine learning methods is extremely active. Doctors need accurate predictions for the outcomes of their patients' diseases. In addition, for accurate predictions, timing is another significant factor that influences treatment decisions. In this paper, existing predictive models in medicine and health care have critically reviewed. Furthermore, the most famous machine learning methods have explained, and the confusion between a statistical approach and machine learning has clarified. A review of related literature reveals that the predictions of existing predictive models differ even when the same dataset is used. Therefore, existing predictive models are essential, and current methods must be improved.

  16. A Simple and Accurate Model to Predict Responses to Multi-electrode Stimulation in the Retina.

    PubMed

    Maturana, Matias I; Apollo, Nicholas V; Hadjinicolaou, Alex E; Garrett, David J; Cloherty, Shaun L; Kameneva, Tatiana; Grayden, David B; Ibbotson, Michael R; Meffin, Hamish

    2016-04-01

    Implantable electrode arrays are widely used in therapeutic stimulation of the nervous system (e.g. cochlear, retinal, and cortical implants). Currently, most neural prostheses use serial stimulation (i.e. one electrode at a time) despite this severely limiting the repertoire of stimuli that can be applied. Methods to reliably predict the outcome of multi-electrode stimulation have not been available. Here, we demonstrate that a linear-nonlinear model accurately predicts neural responses to arbitrary patterns of stimulation using in vitro recordings from single retinal ganglion cells (RGCs) stimulated with a subretinal multi-electrode array. In the model, the stimulus is projected onto a low-dimensional subspace and then undergoes a nonlinear transformation to produce an estimate of spiking probability. The low-dimensional subspace is estimated using principal components analysis, which gives the neuron's electrical receptive field (ERF), i.e. the electrodes to which the neuron is most sensitive. Our model suggests that stimulation proportional to the ERF yields a higher efficacy given a fixed amount of power when compared to equal amplitude stimulation on up to three electrodes. We find that the model captures the responses of all the cells recorded in the study, suggesting that it will generalize to most cell types in the retina. The model is computationally efficient to evaluate and, therefore, appropriate for future real-time applications including stimulation strategies that make use of recorded neural activity to improve the stimulation strategy.

  17. A Simple and Accurate Model to Predict Responses to Multi-electrode Stimulation in the Retina

    PubMed Central

    Maturana, Matias I.; Apollo, Nicholas V.; Hadjinicolaou, Alex E.; Garrett, David J.; Cloherty, Shaun L.; Kameneva, Tatiana; Grayden, David B.; Ibbotson, Michael R.; Meffin, Hamish

    2016-01-01

    Implantable electrode arrays are widely used in therapeutic stimulation of the nervous system (e.g. cochlear, retinal, and cortical implants). Currently, most neural prostheses use serial stimulation (i.e. one electrode at a time) despite this severely limiting the repertoire of stimuli that can be applied. Methods to reliably predict the outcome of multi-electrode stimulation have not been available. Here, we demonstrate that a linear-nonlinear model accurately predicts neural responses to arbitrary patterns of stimulation using in vitro recordings from single retinal ganglion cells (RGCs) stimulated with a subretinal multi-electrode array. In the model, the stimulus is projected onto a low-dimensional subspace and then undergoes a nonlinear transformation to produce an estimate of spiking probability. The low-dimensional subspace is estimated using principal components analysis, which gives the neuron’s electrical receptive field (ERF), i.e. the electrodes to which the neuron is most sensitive. Our model suggests that stimulation proportional to the ERF yields a higher efficacy given a fixed amount of power when compared to equal amplitude stimulation on up to three electrodes. We find that the model captures the responses of all the cells recorded in the study, suggesting that it will generalize to most cell types in the retina. The model is computationally efficient to evaluate and, therefore, appropriate for future real-time applications including stimulation strategies that make use of recorded neural activity to improve the stimulation strategy. PMID:27035143

  18. Accurate First-Principles Spectra Predictions for Planetological and Astrophysical Applications at Various T-Conditions

    NASA Astrophysics Data System (ADS)

    Rey, M.; Nikitin, A. V.; Tyuterev, V.

    2014-06-01

    Knowledge of near infrared intensities of rovibrational transitions of polyatomic molecules is essential for the modeling of various planetary atmospheres, brown dwarfs and for other astrophysical applications 1,2,3. For example, to analyze exoplanets, atmospheric models have been developed, thus making the need to provide accurate spectroscopic data. Consequently, the spectral characterization of such planetary objects relies on the necessity of having adequate and reliable molecular data in extreme conditions (temperature, optical path length, pressure). On the other hand, in the modeling of astrophysical opacities, millions of lines are generally involved and the line-by-line extraction is clearly not feasible in laboratory measurements. It is thus suggested that this large amount of data could be interpreted only by reliable theoretical predictions. There exists essentially two theoretical approaches for the computation and prediction of spectra. The first one is based on empirically-fitted effective spectroscopic models. Another way for computing energies, line positions and intensities is based on global variational calculations using ab initio surfaces. They do not yet reach the spectroscopic accuracy stricto sensu but implicitly account for all intramolecular interactions including resonance couplings in a wide spectral range. The final aim of this work is to provide reliable predictions which could be quantitatively accurate with respect to the precision of available observations and as complete as possible. All this thus requires extensive first-principles quantum mechanical calculations essentially based on three necessary ingredients which are (i) accurate intramolecular potential energy surface and dipole moment surface components well-defined in a large range of vibrational displacements and (ii) efficient computational methods combined with suitable choices of coordinates to account for molecular symmetry properties and to achieve a good numerical

  19. Optimization of sample preparation for accurate results in quantitative NMR spectroscopy

    NASA Astrophysics Data System (ADS)

    Yamazaki, Taichi; Nakamura, Satoe; Saito, Takeshi

    2017-04-01

    Quantitative nuclear magnetic resonance (qNMR) spectroscopy has received high marks as an excellent measurement tool that does not require the same reference standard as the analyte. Measurement parameters have been discussed in detail and high-resolution balances have been used for sample preparation. However, the high-resolution balances, such as an ultra-microbalance, are not general-purpose analytical tools and many analysts may find those balances difficult to use, thereby hindering accurate sample preparation for qNMR measurement. In this study, we examined the relationship between the resolution of the balance and the amount of sample weighed during sample preparation. We were able to confirm the accuracy of the assay results for samples weighed on a high-resolution balance, such as the ultra-microbalance. Furthermore, when an appropriate tare and amount of sample was weighed on a given balance, accurate assay results were obtained with another high-resolution balance. Although this is a fundamental result, it offers important evidence that would enhance the versatility of the qNMR method.

  20. Does a more precise chemical description of protein-ligand complexes lead to more accurate prediction of binding affinity?

    PubMed

    Ballester, Pedro J; Schreyer, Adrian; Blundell, Tom L

    2014-03-24

    Predicting the binding affinities of large sets of diverse molecules against a range of macromolecular targets is an extremely challenging task. The scoring functions that attempt such computational prediction are essential for exploiting and analyzing the outputs of docking, which is in turn an important tool in problems such as structure-based drug design. Classical scoring functions assume a predetermined theory-inspired functional form for the relationship between the variables that describe an experimentally determined or modeled structure of a protein-ligand complex and its binding affinity. The inherent problem of this approach is in the difficulty of explicitly modeling the various contributions of intermolecular interactions to binding affinity. New scoring functions based on machine-learning regression models, which are able to exploit effectively much larger amounts of experimental data and circumvent the need for a predetermined functional form, have already been shown to outperform a broad range of state-of-the-art scoring functions in a widely used benchmark. Here, we investigate the impact of the chemical description of the complex on the predictive power of the resulting scoring function using a systematic battery of numerical experiments. The latter resulted in the most accurate scoring function to date on the benchmark. Strikingly, we also found that a more precise chemical description of the protein-ligand complex does not generally lead to a more accurate prediction of binding affinity. We discuss four factors that may contribute to this result: modeling assumptions, codependence of representation and regression, data restricted to the bound state, and conformational heterogeneity in data.

  1. Accurate and Robust Genomic Prediction of Celiac Disease Using Statistical Learning

    PubMed Central

    Abraham, Gad; Tye-Din, Jason A.; Bhalala, Oneil G.; Kowalczyk, Adam; Zobel, Justin; Inouye, Michael

    2014-01-01

    Practical application of genomic-based risk stratification to clinical diagnosis is appealing yet performance varies widely depending on the disease and genomic risk score (GRS) method. Celiac disease (CD), a common immune-mediated illness, is strongly genetically determined and requires specific HLA haplotypes. HLA testing can exclude diagnosis but has low specificity, providing little information suitable for clinical risk stratification. Using six European cohorts, we provide a proof-of-concept that statistical learning approaches which simultaneously model all SNPs can generate robust and highly accurate predictive models of CD based on genome-wide SNP profiles. The high predictive capacity replicated both in cross-validation within each cohort (AUC of 0.87–0.89) and in independent replication across cohorts (AUC of 0.86–0.9), despite differences in ethnicity. The models explained 30–35% of disease variance and up to ∼43% of heritability. The GRS's utility was assessed in different clinically relevant settings. Comparable to HLA typing, the GRS can be used to identify individuals without CD with ≥99.6% negative predictive value however, unlike HLA typing, fine-scale stratification of individuals into categories of higher-risk for CD can identify those that would benefit from more invasive and costly definitive testing. The GRS is flexible and its performance can be adapted to the clinical situation by adjusting the threshold cut-off. Despite explaining a minority of disease heritability, our findings indicate a genomic risk score provides clinically relevant information to improve upon current diagnostic pathways for CD and support further studies evaluating the clinical utility of this approach in CD and other complex diseases. PMID:24550740

  2. Energy expenditure during level human walking: seeking a simple and accurate predictive solution.

    PubMed

    Ludlow, Lindsay W; Weyand, Peter G

    2016-03-01

    Accurate prediction of the metabolic energy that walking requires can inform numerous health, bodily status, and fitness outcomes. We adopted a two-step approach to identifying a concise, generalized equation for predicting level human walking metabolism. Using literature-aggregated values we compared 1) the predictive accuracy of three literature equations: American College of Sports Medicine (ACSM), Pandolf et al., and Height-Weight-Speed (HWS); and 2) the goodness-of-fit possible from one- vs. two-component descriptions of walking metabolism. Literature metabolic rate values (n = 127; speed range = 0.4 to 1.9 m/s) were aggregated from 25 subject populations (n = 5-42) whose means spanned a 1.8-fold range of heights and a 4.2-fold range of weights. Population-specific resting metabolic rates (V̇o2 rest) were determined using standardized equations. Our first finding was that the ACSM and Pandolf et al. equations underpredicted nearly all 127 literature-aggregated values. Consequently, their standard errors of estimate (SEE) were nearly four times greater than those of the HWS equation (4.51 and 4.39 vs. 1.13 ml O2·kg(-1)·min(-1), respectively). For our second comparison, empirical best-fit relationships for walking metabolism were derived from the data set in one- and two-component forms for three V̇o2-speed model types: linear (∝V(1.0)), exponential (∝V(2.0)), and exponential/height (∝V(2.0)/Ht). We found that the proportion of variance (R(2)) accounted for, when averaged across the three model types, was substantially lower for one- vs. two-component versions (0.63 ± 0.1 vs. 0.90 ± 0.03) and the predictive errors were nearly twice as great (SEE = 2.22 vs. 1.21 ml O2·kg(-1)·min(-1)). Our final analysis identified the following concise, generalized equation for predicting level human walking metabolism: V̇o2 total = V̇o2 rest + 3.85 + 5.97·V(2)/Ht (where V is measured in m/s, Ht in meters, and V̇o2 in ml O2·kg(-1)·min(-1)).

  3. A cross-race effect in metamemory: Predictions of face recognition are more accurate for members of our own race

    PubMed Central

    Hourihan, Kathleen L.; Benjamin, Aaron S.; Liu, Xiping

    2012-01-01

    The Cross-Race Effect (CRE) in face recognition is the well-replicated finding that people are better at recognizing faces from their own race, relative to other races. The CRE reveals systematic limitations on eyewitness identification accuracy and suggests that some caution is warranted in evaluating cross-race identification. The CRE is a problem because jurors value eyewitness identification highly in verdict decisions. In the present paper, we explore how accurate people are in predicting their ability to recognize own-race and other-race faces. Caucasian and Asian participants viewed photographs of Caucasian and Asian faces, and made immediate judgments of learning during study. An old/new recognition test replicated the CRE: both groups displayed superior discriminability of own-race faces, relative to other-race faces. Importantly, relative metamnemonic accuracy was also greater for own-race faces, indicating that the accuracy of predictions about face recognition is influenced by race. This result indicates another source of concern when eliciting or evaluating eyewitness identification: people are less accurate in judging whether they will or will not recognize a face when that face is of a different race than they are. This new result suggests that a witness’s claim of being likely to recognize a suspect from a lineup should be interpreted with caution when the suspect is of a different race than the witness. PMID:23162788

  4. Towards more accurate wind and solar power prediction by improving NWP model physics

    NASA Astrophysics Data System (ADS)

    Steiner, Andrea; Köhler, Carmen; von Schumann, Jonas; Ritter, Bodo

    2014-05-01

    nighttime to well mixed conditions during the day presents a big challenge to NWP models. Fast decrease and successive increase in hub-height wind speed after sunrise, and the formation of nocturnal low level jets will be discussed. For PV, the life cycle of low stratus clouds and fog is crucial. Capturing these processes correctly depends on the accurate simulation of diffusion or vertical momentum transport and the interaction with other atmospheric and soil processes within the numerical weather model. Results from Single Column Model simulations and 3d case studies will be presented. Emphasis is placed on wind forecasts; however, some references to highlights concerning the PV-developments will also be given. *) ORKA: Optimierung von Ensembleprognosen regenerativer Einspeisung für den Kürzestfristbereich am Anwendungsbeispiel der Netzsicherheitsrechnungen **) EWeLiNE: Erstellung innovativer Wetter- und Leistungsprognosemodelle für die Netzintegration wetterabhängiger Energieträger, www.projekt-eweline.de

  5. Structure-based constitutive model can accurately predict planar biaxial properties of aortic wall tissue.

    PubMed

    Polzer, S; Gasser, T C; Novak, K; Man, V; Tichy, M; Skacel, P; Bursa, J

    2015-03-01

    Structure-based constitutive models might help in exploring mechanisms by which arterial wall histology is linked to wall mechanics. This study aims to validate a recently proposed structure-based constitutive model. Specifically, the model's ability to predict mechanical biaxial response of porcine aortic tissue with predefined collagen structure was tested. Histological slices from porcine thoracic aorta wall (n=9) were automatically processed to quantify the collagen fiber organization, and mechanical testing identified the non-linear properties of the wall samples (n=18) over a wide range of biaxial stretches. Histological and mechanical experimental data were used to identify the model parameters of a recently proposed multi-scale constitutive description for arterial layers. The model predictive capability was tested with respect to interpolation and extrapolation. Collagen in the media was predominantly aligned in circumferential direction (planar von Mises distribution with concentration parameter bM=1.03 ± 0.23), and its coherence decreased gradually from the luminal to the abluminal tissue layers (inner media, b=1.54 ± 0.40; outer media, b=0.72 ± 0.20). In contrast, the collagen in the adventitia was aligned almost isotropically (bA=0.27 ± 0.11), and no features, such as families of coherent fibers, were identified. The applied constitutive model captured the aorta biaxial properties accurately (coefficient of determination R(2)=0.95 ± 0.03) over the entire range of biaxial deformations and with physically meaningful model parameters. Good predictive properties, well outside the parameter identification space, were observed (R(2)=0.92 ± 0.04). Multi-scale constitutive models equipped with realistic micro-histological data can predict macroscopic non-linear aorta wall properties. Collagen largely defines already low strain properties of media, which explains the origin of wall anisotropy seen at this strain level. The structure and mechanical

  6. Predicting accurate fluorescent spectra for high molecular weight polycyclic aromatic hydrocarbons using density functional theory

    NASA Astrophysics Data System (ADS)

    Powell, Jacob; Heider, Emily C.; Campiglia, Andres; Harper, James K.

    2016-10-01

    The ability of density functional theory (DFT) methods to predict accurate fluorescence spectra for polycyclic aromatic hydrocarbons (PAHs) is explored. Two methods, PBE0 and CAM-B3LYP, are evaluated both in the gas phase and in solution. Spectra for several of the most toxic PAHs are predicted and compared to experiment, including three isomers of C24H14 and a PAH containing heteroatoms. Unusually high-resolution experimental spectra are obtained for comparison by analyzing each PAH at 4.2 K in an n-alkane matrix. All theoretical spectra visually conform to the profiles of the experimental data but are systematically offset by a small amount. Specifically, when solvent is included the PBE0 functional overestimates peaks by 16.1 ± 6.6 nm while CAM-B3LYP underestimates the same transitions by 14.5 ± 7.6 nm. These calculated spectra can be empirically corrected to decrease the uncertainties to 6.5 ± 5.1 and 5.7 ± 5.1 nm for the PBE0 and CAM-B3LYP methods, respectively. A comparison of computed spectra in the gas phase indicates that the inclusion of n-octane shifts peaks by +11 nm on average and this change is roughly equivalent for PBE0 and CAM-B3LYP. An automated approach for comparing spectra is also described that minimizes residuals between a given theoretical spectrum and all available experimental spectra. This approach identifies the correct spectrum in all cases and excludes approximately 80% of the incorrect spectra, demonstrating that an automated search of theoretical libraries of spectra may eventually become feasible.

  7. A Weibull statistics-based lignocellulose saccharification model and a built-in parameter accurately predict lignocellulose hydrolysis performance.

    PubMed

    Wang, Mingyu; Han, Lijuan; Liu, Shasha; Zhao, Xuebing; Yang, Jinghua; Loh, Soh Kheang; Sun, Xiaomin; Zhang, Chenxi; Fang, Xu

    2015-09-01

    Renewable energy from lignocellulosic biomass has been deemed an alternative to depleting fossil fuels. In order to improve this technology, we aim to develop robust mathematical models for the enzymatic lignocellulose degradation process. By analyzing 96 groups of previously published and newly obtained lignocellulose saccharification results and fitting them to Weibull distribution, we discovered Weibull statistics can accurately predict lignocellulose saccharification data, regardless of the type of substrates, enzymes and saccharification conditions. A mathematical model for enzymatic lignocellulose degradation was subsequently constructed based on Weibull statistics. Further analysis of the mathematical structure of the model and experimental saccharification data showed the significance of the two parameters in this model. In particular, the λ value, defined the characteristic time, represents the overall performance of the saccharification system. This suggestion was further supported by statistical analysis of experimental saccharification data and analysis of the glucose production levels when λ and n values change. In conclusion, the constructed Weibull statistics-based model can accurately predict lignocellulose hydrolysis behavior and we can use the λ parameter to assess the overall performance of enzymatic lignocellulose degradation. Advantages and potential applications of the model and the λ value in saccharification performance assessment were discussed.

  8. Fast and Accurate Prediction of Numerical Relativity Waveforms from Binary Black Hole Coalescences Using Surrogate Models.

    PubMed

    Blackman, Jonathan; Field, Scott E; Galley, Chad R; Szilágyi, Béla; Scheel, Mark A; Tiglio, Manuel; Hemberger, Daniel A

    2015-09-18

    Simulating a binary black hole coalescence by solving Einstein's equations is computationally expensive, requiring days to months of supercomputing time. Using reduced order modeling techniques, we construct an accurate surrogate model, which is evaluated in a millisecond to a second, for numerical relativity (NR) waveforms from nonspinning binary black hole coalescences with mass ratios in [1, 10] and durations corresponding to about 15 orbits before merger. We assess the model's uncertainty and show that our modeling strategy predicts NR waveforms not used for the surrogate's training with errors nearly as small as the numerical error of the NR code. Our model includes all spherical-harmonic _{-2}Y_{ℓm} waveform modes resolved by the NR code up to ℓ=8. We compare our surrogate model to effective one body waveforms from 50M_{⊙} to 300M_{⊙} for advanced LIGO detectors and find that the surrogate is always more faithful (by at least an order of magnitude in most cases).

  9. A high order accurate finite element algorithm for high Reynolds number flow prediction

    NASA Technical Reports Server (NTRS)

    Baker, A. J.

    1978-01-01

    A Galerkin-weighted residuals formulation is employed to establish an implicit finite element solution algorithm for generally nonlinear initial-boundary value problems. Solution accuracy, and convergence rate with discretization refinement, are quantized in several error norms, by a systematic study of numerical solutions to several nonlinear parabolic and a hyperbolic partial differential equation characteristic of the equations governing fluid flows. Solutions are generated using selective linear, quadratic and cubic basis functions. Richardson extrapolation is employed to generate a higher-order accurate solution to facilitate isolation of truncation error in all norms. Extension of the mathematical theory underlying accuracy and convergence concepts for linear elliptic equations is predicted for equations characteristic of laminar and turbulent fluid flows at nonmodest Reynolds number. The nondiagonal initial-value matrix structure introduced by the finite element theory is determined intrinsic to improved solution accuracy and convergence. A factored Jacobian iteration algorithm is derived and evaluated to yield a consequential reduction in both computer storage and execution CPU requirements while retaining solution accuracy.

  10. Accurate prediction of V1 location from cortical folds in a surface coordinate system

    PubMed Central

    Hinds, Oliver P.; Rajendran, Niranjini; Polimeni, Jonathan R.; Augustinack, Jean C.; Wiggins, Graham; Wald, Lawrence L.; Rosas, H. Diana; Potthast, Andreas; Schwartz, Eric L.; Fischl, Bruce

    2008-01-01

    Previous studies demonstrated substantial variability of the location of primary visual cortex (V1) in stereotaxic coordinates when linear volume-based registration is used to match volumetric image intensities (Amunts et al., 2000). However, other qualitative reports of V1 location (Smith, 1904; Stensaas et al., 1974; Rademacher et al., 1993) suggested a consistent relationship between V1 and the surrounding cortical folds. Here, the relationship between folds and the location of V1 is quantified using surface-based analysis to generate a probabilistic atlas of human V1. High-resolution (about 200 μm) magnetic resonance imaging (MRI) at 7 T of ex vivo human cerebral hemispheres allowed identification of the full area via the stria of Gennari: a myeloarchitectonic feature specific to V1. Separate, whole-brain scans were acquired using MRI at 1.5 T to allow segmentation and mesh reconstruction of the cortical gray matter. For each individual, V1 was manually identified in the high-resolution volume and projected onto the cortical surface. Surface-based intersubject registration (Fischl et al., 1999b) was performed to align the primary cortical folds of individual hemispheres to those of a reference template representing the average folding pattern. An atlas of V1 location was constructed by computing the probability of V1 inclusion for each cortical location in the template space. This probabilistic atlas of V1 exhibits low prediction error compared to previous V1 probabilistic atlases built in volumetric coordinates. The increased predictability observed under surface-based registration suggests that the location of V1 is more accurately predicted by the cortical folds than by the shape of the brain embedded in the volume of the skull. In addition, the high quality of this atlas provides direct evidence that surface-based intersubject registration methods are superior to volume-based methods at superimposing functional areas of cortex, and therefore are better

  11. Accurate prediction of unsteady and time-averaged pressure loads using a hybrid Reynolds-Averaged/large-eddy simulation technique

    NASA Astrophysics Data System (ADS)

    Bozinoski, Radoslav

    Significant research has been performed over the last several years on understanding the unsteady aerodynamics of various fluid flows. Much of this work has focused on quantifying the unsteady, three-dimensional flow field effects which have proven vital to the accurate prediction of many fluid and aerodynamic problems. Up until recently, engineers have predominantly relied on steady-state simulations to analyze the inherently three-dimensional ow structures that are prevalent in many of today's "real-world" problems. Increases in computational capacity and the development of efficient numerical methods can change this and allow for the solution of the unsteady Reynolds-Averaged Navier-Stokes (RANS) equations for practical three-dimensional aerodynamic applications. An integral part of this capability has been the performance and accuracy of the turbulence models coupled with advanced parallel computing techniques. This report begins with a brief literature survey of the role fully three-dimensional, unsteady, Navier-Stokes solvers have on the current state of numerical analysis. Next, the process of creating a baseline three-dimensional Multi-Block FLOw procedure called MBFLO3 is presented. Solutions for an inviscid circular arc bump, laminar at plate, laminar cylinder, and turbulent at plate are then presented. Results show good agreement with available experimental, numerical, and theoretical data. Scalability data for the parallel version of MBFLO3 is presented and shows efficiencies of 90% and higher for processes of no less than 100,000 computational grid points. Next, the description and implementation techniques used for several turbulence models are presented. Following the successful implementation of the URANS and DES procedures, the validation data for separated, non-reattaching flows over a NACA 0012 airfoil, wall-mounted hump, and a wing-body junction geometry are presented. Results for the NACA 0012 showed significant improvement in flow predictions

  12. Accurate prediction of the optical rotation and NMR properties for highly flexible chiral natural products.

    PubMed

    Hashmi, Muhammad Ali; Andreassend, Sarah K; Keyzers, Robert A; Lein, Matthias

    2016-09-21

    Despite advances in electronic structure theory the theoretical prediction of spectroscopic properties remains a computational challenge. This is especially true for natural products that exhibit very large conformational freedom and hence need to be sampled over many different accessible conformations. We report a strategy, which is able to predict NMR chemical shifts and more elusive properties like the optical rotation with great precision, through step-wise incremental increases of the conformational degrees of freedom. The application of this method is demonstrated for 3-epi-xestoaminol C, a chiral natural compound with a long, linear alkyl chain of 14 carbon atoms. Experimental NMR and [α]D values are reported to validate the results of the density functional theory calculations.

  13. FastRNABindR: Fast and Accurate Prediction of Protein-RNA Interface Residues.

    PubMed

    El-Manzalawy, Yasser; Abbas, Mostafa; Malluhi, Qutaibah; Honavar, Vasant

    2016-01-01

    A wide range of biological processes, including regulation of gene expression, protein synthesis, and replication and assembly of many viruses are mediated by RNA-protein interactions. However, experimental determination of the structures of protein-RNA complexes is expensive and technically challenging. Hence, a number of computational tools have been developed for predicting protein-RNA interfaces. Some of the state-of-the-art protein-RNA interface predictors rely on position-specific scoring matrix (PSSM)-based encoding of the protein sequences. The computational efforts needed for generating PSSMs severely limits the practical utility of protein-RNA interface prediction servers. In this work, we experiment with two approaches, random sampling and sequence similarity reduction, for extracting a representative reference database of protein sequences from more than 50 million protein sequences in UniRef100. Our results suggest that random sampled databases produce better PSSM profiles (in terms of the number of hits used to generate the profile and the distance of the generated profile to the corresponding profile generated using the entire UniRef100 data as well as the accuracy of the machine learning classifier trained using these profiles). Based on our results, we developed FastRNABindR, an improved version of RNABindR for predicting protein-RNA interface residues using PSSM profiles generated using 1% of the UniRef100 sequences sampled uniformly at random. To the best of our knowledge, FastRNABindR is the only protein-RNA interface residue prediction online server that requires generation of PSSM profiles for query sequences and accepts hundreds of protein sequences per submission. Our approach for determining the optimal BLAST database for a protein-RNA interface residue classification task has the potential of substantially speeding up, and hence increasing the practical utility of, other amino acid sequence based predictors of protein-protein and protein

  14. Robust and Accurate Modeling Approaches for Migraine Per-Patient Prediction from Ambulatory Data.

    PubMed

    Pagán, Josué; De Orbe, M Irene; Gago, Ana; Sobrado, Mónica; Risco-Martín, José L; Mora, J Vivancos; Moya, José M; Ayala, José L

    2015-06-30

    Migraine is one of the most wide-spread neurological disorders, and its medical treatment represents a high percentage of the costs of health systems. In some patients, characteristic symptoms that precede the headache appear. However, they are nonspecific, and their prediction horizon is unknown and pretty variable; hence, these symptoms are almost useless for prediction, and they are not useful to advance the intake of drugs to be effective and neutralize the pain. To solve this problem, this paper sets up a realistic monitoring scenario where hemodynamic variables from real patients are monitored in ambulatory conditions with a wireless body sensor network (WBSN). The acquired data are used to evaluate the predictive capabilities and robustness against noise and failures in sensors of several modeling approaches. The obtained results encourage the development of per-patient models based on state-space models (N4SID) that are capable of providing average forecast windows of 47 min and a low rate of false positives.

  15. Accurate structure prediction of peptide–MHC complexes for identifying highly immunogenic antigens

    SciTech Connect

    Park, Min-Sun; Park, Sung Yong; Miller, Keith R.; Collins, Edward J.; Lee, Ha Youn

    2013-11-01

    Designing an optimal HIV-1 vaccine faces the challenge of identifying antigens that induce a broad immune capacity. One factor to control the breadth of T cell responses is the surface morphology of a peptide–MHC complex. Here, we present an in silico protocol for predicting peptide–MHC structure. A robust signature of a conformational transition was identified during all-atom molecular dynamics, which results in a model with high accuracy. A large test set was used in constructing our protocol and we went another step further using a blind test with a wild-type peptide and two highly immunogenic mutants, which predicted substantial conformational changes in both mutants. The center residues at position five of the analogs were configured to be accessible to solvent, forming a prominent surface, while the residue of the wild-type peptide was to point laterally toward the side of the binding cleft. We then experimentally determined the structures of the blind test set, using high resolution of X-ray crystallography, which verified predicted conformational changes. Our observation strongly supports a positive association of the surface morphology of a peptide–MHC complex to its immunogenicity. Our study offers the prospect of enhancing immunogenicity of vaccines by identifying MHC binding immunogens.

  16. Robust and Accurate Modeling Approaches for Migraine Per-Patient Prediction from Ambulatory Data

    PubMed Central

    Pagán, Josué; Irene De Orbe, M.; Gago, Ana; Sobrado, Mónica; Risco-Martín, José L.; Vivancos Mora, J.; Moya, José M.; Ayala, José L.

    2015-01-01

    Migraine is one of the most wide-spread neurological disorders, and its medical treatment represents a high percentage of the costs of health systems. In some patients, characteristic symptoms that precede the headache appear. However, they are nonspecific, and their prediction horizon is unknown and pretty variable; hence, these symptoms are almost useless for prediction, and they are not useful to advance the intake of drugs to be effective and neutralize the pain. To solve this problem, this paper sets up a realistic monitoring scenario where hemodynamic variables from real patients are monitored in ambulatory conditions with a wireless body sensor network (WBSN). The acquired data are used to evaluate the predictive capabilities and robustness against noise and failures in sensors of several modeling approaches. The obtained results encourage the development of per-patient models based on state-space models (N4SID) that are capable of providing average forecast windows of 47 min and a low rate of false positives. PMID:26134103

  17. Accurate prediction of cellular co-translational folding indicates proteins can switch from post- to co-translational folding

    PubMed Central

    Nissley, Daniel A.; Sharma, Ajeet K.; Ahmed, Nabeel; Friedrich, Ulrike A.; Kramer, Günter; Bukau, Bernd; O'Brien, Edward P.

    2016-01-01

    The rates at which domains fold and codons are translated are important factors in determining whether a nascent protein will co-translationally fold and function or misfold and malfunction. Here we develop a chemical kinetic model that calculates a protein domain's co-translational folding curve during synthesis using only the domain's bulk folding and unfolding rates and codon translation rates. We show that this model accurately predicts the course of co-translational folding measured in vivo for four different protein molecules. We then make predictions for a number of different proteins in yeast and find that synonymous codon substitutions, which change translation-elongation rates, can switch some protein domains from folding post-translationally to folding co-translationally—a result consistent with previous experimental studies. Our approach explains essential features of co-translational folding curves and predicts how varying the translation rate at different codon positions along a transcript's coding sequence affects this self-assembly process. PMID:26887592

  18. Neural network and SVM classifiers accurately predict lipid binding proteins, irrespective of sequence homology.

    PubMed

    Bakhtiarizadeh, Mohammad Reza; Moradi-Shahrbabak, Mohammad; Ebrahimi, Mansour; Ebrahimie, Esmaeil

    2014-09-07

    Due to the central roles of lipid binding proteins (LBPs) in many biological processes, sequence based identification of LBPs is of great interest. The major challenge is that LBPs are diverse in sequence, structure, and function which results in low accuracy of sequence homology based methods. Therefore, there is a need for developing alternative functional prediction methods irrespective of sequence similarity. To identify LBPs from non-LBPs, the performances of support vector machine (SVM) and neural network were compared in this study. Comprehensive protein features and various techniques were employed to create datasets. Five-fold cross-validation (CV) and independent evaluation (IE) tests were used to assess the validity of the two methods. The results indicated that SVM outperforms neural network. SVM achieved 89.28% (CV) and 89.55% (IE) overall accuracy in identification of LBPs from non-LBPs and 92.06% (CV) and 92.90% (IE) (in average) for classification of different LBPs classes. Increasing the number and the range of extracted protein features as well as optimization of the SVM parameters significantly increased the efficiency of LBPs class prediction in comparison to the only previous report in this field. Altogether, the results showed that the SVM algorithm can be run on broad, computationally calculated protein features and offers a promising tool in detection of LBPs classes. The proposed approach has the potential to integrate and improve the common sequence alignment based methods.

  19. Accurate Prediction of the Dynamical Changes within the Second PDZ Domain of PTP1e

    PubMed Central

    Cilia, Elisa; Vuister, Geerten W.; Lenaerts, Tom

    2012-01-01

    Experimental NMR relaxation studies have shown that peptide binding induces dynamical changes at the side-chain level throughout the second PDZ domain of PTP1e, identifying as such the collection of residues involved in long-range communication. Even though different computational approaches have identified subsets of residues that were qualitatively comparable, no quantitative analysis of the accuracy of these predictions was thus far determined. Here, we show that our information theoretical method produces quantitatively better results with respect to the experimental data than some of these earlier methods. Moreover, it provides a global network perspective on the effect experienced by the different residues involved in the process. We also show that these predictions are consistent within both the human and mouse variants of this domain. Together, these results improve the understanding of intra-protein communication and allostery in PDZ domains, underlining at the same time the necessity of producing similar data sets for further validation of thses kinds of methods. PMID:23209399

  20. Combining Structural Modeling with Ensemble Machine Learning to Accurately Predict Protein Fold Stability and Binding Affinity Effects upon Mutation

    PubMed Central

    Garcia Lopez, Sebastian; Kim, Philip M.

    2014-01-01

    Advances in sequencing have led to a rapid accumulation of mutations, some of which are associated with diseases. However, to draw mechanistic conclusions, a biochemical understanding of these mutations is necessary. For coding mutations, accurate prediction of significant changes in either the stability of proteins or their affinity to their binding partners is required. Traditional methods have used semi-empirical force fields, while newer methods employ machine learning of sequence and structural features. Here, we show how combining both of these approaches leads to a marked boost in accuracy. We introduce ELASPIC, a novel ensemble machine learning approach that is able to predict stability effects upon mutation in both, domain cores and domain-domain interfaces. We combine semi-empirical energy terms, sequence conservation, and a wide variety of molecular details with a Stochastic Gradient Boosting of Decision Trees (SGB-DT) algorithm. The accuracy of our predictions surpasses existing methods by a considerable margin, achieving correlation coefficients of 0.77 for stability, and 0.75 for affinity predictions. Notably, we integrated homology modeling to enable proteome-wide prediction and show that accurate prediction on modeled structures is possible. Lastly, ELASPIC showed significant differences between various types of disease-associated mutations, as well as between disease and common neutral mutations. Unlike pure sequence-based prediction methods that try to predict phenotypic effects of mutations, our predictions unravel the molecular details governing the protein instability, and help us better understand the molecular causes of diseases. PMID:25243403

  1. Can tritiated water-dilution space accurately predict total body water in chukar partridges

    SciTech Connect

    Crum, B.G.; Williams, J.B.; Nagy, K.A.

    1985-11-01

    Total body water (TBW) volumes determined from the dilution space of injected tritiated water have consistently overestimated actual water volumes (determined by desiccation to constant mass) in reptiles and mammals, but results for birds are controversial. We investigated potential errors in both the dilution method and the desiccation method in an attempt to resolve this controversy. Tritiated water dilution yielded an accurate measurement of water mass in vitro. However, in vivo, this method yielded a 4.6% overestimate of the amount of water (3.1% of live body mass) in chukar partridges, apparently largely because of loss of tritium from body water to sites of dissociable hydrogens on body solids. An additional source of overestimation (approximately 2% of body mass) was loss of tritium to the solids in blood samples during distillation of blood to obtain pure water for tritium analysis. Measuring tritium activity in plasma samples avoided this problem but required measurement of, and correction for, the dry matter content in plasma. Desiccation to constant mass by lyophilization or oven-drying also overestimated the amount of water actually in the bodies of chukar partridges by 1.4% of body mass, because these values included water adsorbed onto the outside of feathers. When desiccating defeathered carcasses, oven-drying at 70 degrees C yielded TBW values identical to those obtained from lyophilization, but TBW was overestimated (0.5% of body mass) by drying at 100 degrees C due to loss of organic substances as well as water.

  2. TIMP2•IGFBP7 biomarker panel accurately predicts acute kidney injury in high-risk surgical patients

    PubMed Central

    Gunnerson, Kyle J.; Shaw, Andrew D.; Chawla, Lakhmir S.; Bihorac, Azra; Al-Khafaji, Ali; Kashani, Kianoush; Lissauer, Matthew; Shi, Jing; Walker, Michael G.; Kellum, John A.

    2016-01-01

    BACKGROUND Acute kidney injury (AKI) is an important complication in surgical patients. Existing biomarkers and clinical prediction models underestimate the risk for developing AKI. We recently reported data from two trials of 728 and 408 critically ill adult patients in whom urinary TIMP2•IGFBP7 (NephroCheck, Astute Medical) was used to identify patients at risk of developing AKI. Here we report a preplanned analysis of surgical patients from both trials to assess whether urinary tissue inhibitor of metalloproteinase 2 (TIMP-2) and insulin-like growth factor–binding protein 7 (IGFBP7) accurately identify surgical patients at risk of developing AKI. STUDY DESIGN We enrolled adult surgical patients at risk for AKI who were admitted to one of 39 intensive care units across Europe and North America. The primary end point was moderate-severe AKI (equivalent to KDIGO [Kidney Disease Improving Global Outcomes] stages 2–3) within 12 hours of enrollment. Biomarker performance was assessed using the area under the receiver operating characteristic curve, integrated discrimination improvement, and category-free net reclassification improvement. RESULTS A total of 375 patients were included in the final analysis of whom 35 (9%) developed moderate-severe AKI within 12 hours. The area under the receiver operating characteristic curve for [TIMP-2]•[IGFBP7] alone was 0.84 (95% confidence interval, 0.76–0.90; p < 0.0001). Biomarker performance was robust in sensitivity analysis across predefined subgroups (urgency and type of surgery). CONCLUSION For postoperative surgical intensive care unit patients, a single urinary TIMP2•IGFBP7 test accurately identified patients at risk for developing AKI within the ensuing 12 hours and its inclusion in clinical risk prediction models significantly enhances their performance. LEVEL OF EVIDENCE Prognostic study, level I. PMID:26816218

  3. A Foundation for the Accurate Prediction of the Soft Error Vulnerability of Scientific Applications

    SciTech Connect

    Bronevetsky, G; de Supinski, B; Schulz, M

    2009-02-13

    Understanding the soft error vulnerability of supercomputer applications is critical as these systems are using ever larger numbers of devices that have decreasing feature sizes and, thus, increasing frequency of soft errors. As many large scale parallel scientific applications use BLAS and LAPACK linear algebra routines, the soft error vulnerability of these methods constitutes a large fraction of the applications overall vulnerability. This paper analyzes the vulnerability of these routines to soft errors by characterizing how their outputs are affected by injected errors and by evaluating several techniques for predicting how errors propagate from the input to the output of each routine. The resulting error profiles can be used to understand the fault vulnerability of full applications that use these routines.

  4. Fast and Accurate Accessible Surface Area Prediction Without a Sequence Profile.

    PubMed

    Faraggi, Eshel; Kouza, Maksim; Zhou, Yaoqi; Kloczkowski, Andrzej

    2017-01-01

    A fast accessible surface area (ASA) predictor is presented. In this new approach no residue mutation profiles generated by multiple sequence alignments are used as inputs. Instead, we use only single sequence information and global features such as single-residue and two-residue compositions of the chain. The resulting predictor is both highly more efficient than sequence alignment based predictors and of comparable accuracy to them. Introduction of the global inputs significantly helps achieve this comparable accuracy. The predictor, termed ASAquick, is found to perform similarly well for so-called easy and hard cases indicating generalizability and possible usability for de-novo protein structure prediction. The source code and a Linux executables for ASAquick are available from Research and Information Systems at http://mamiris.com and from the Battelle Center for Mathematical Medicine at http://mathmed.org .

  5. Sequence features accurately predict genome-wide MeCP2 binding in vivo

    PubMed Central

    Rube, H. Tomas; Lee, Wooje; Hejna, Miroslav; Chen, Huaiyang; Yasui, Dag H.; Hess, John F.; LaSalle, Janine M.; Song, Jun S.; Gong, Qizhi

    2016-01-01

    Methyl-CpG binding protein 2 (MeCP2) is critical for proper brain development and expressed at near-histone levels in neurons, but the mechanism of its genomic localization remains poorly understood. Using high-resolution MeCP2-binding data, we show that DNA sequence features alone can predict binding with 88% accuracy. Integrating MeCP2 binding and DNA methylation in a probabilistic graphical model, we demonstrate that previously reported genome-wide association with methylation is in part due to MeCP2's affinity to GC-rich chromatin, a result replicated using published data. Furthermore, MeCP2 co-localizes with nucleosomes. Finally, MeCP2 binding downstream of promoters correlates with increased expression in Mecp2-deficient neurons. PMID:27008915

  6. Combining multiple regression and principal component analysis for accurate predictions for column ozone in Peninsular Malaysia

    NASA Astrophysics Data System (ADS)

    Rajab, Jasim M.; MatJafri, M. Z.; Lim, H. S.

    2013-06-01

    This study encompasses columnar ozone modelling in the peninsular Malaysia. Data of eight atmospheric parameters [air surface temperature (AST), carbon monoxide (CO), methane (CH4), water vapour (H2Ovapour), skin surface temperature (SSKT), atmosphere temperature (AT), relative humidity (RH), and mean surface pressure (MSP)] data set, retrieved from NASA's Atmospheric Infrared Sounder (AIRS), for the entire period (2003-2008) was employed to develop models to predict the value of columnar ozone (O3) in study area. The combined method, which is based on using both multiple regressions combined with principal component analysis (PCA) modelling, was used to predict columnar ozone. This combined approach was utilized to improve the prediction accuracy of columnar ozone. Separate analysis was carried out for north east monsoon (NEM) and south west monsoon (SWM) seasons. The O3 was negatively correlated with CH4, H2Ovapour, RH, and MSP, whereas it was positively correlated with CO, AST, SSKT, and AT during both the NEM and SWM season periods. Multiple regression analysis was used to fit the columnar ozone data using the atmospheric parameter's variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to acquire subsets of the predictor variables to be comprised in the linear regression model of the atmospheric parameter's variables. It was found that the increase in columnar O3 value is associated with an increase in the values of AST, SSKT, AT, and CO and with a drop in the levels of CH4, H2Ovapour, RH, and MSP. The result of fitting the best models for the columnar O3 value using eight of the independent variables gave about the same values of the R (≈0.93) and R2 (≈0.86) for both the NEM and SWM seasons. The common variables that appeared in both regression equations were SSKT, CH4 and RH, and the principal precursor of the columnar O3 value in both the NEM and SWM seasons was SSKT.

  7. How Accurate Is the Prediction of Maximal Oxygen Uptake with Treadmill Testing?

    PubMed Central

    Wicks, John R.; Oldridge, Neil B.

    2016-01-01

    Background Cardiorespiratory fitness measured by treadmill testing has prognostic significance in determining mortality with cardiovascular and other chronic disease states. The accuracy of a recently developed method for estimating maximal oxygen uptake (VO2peak), the heart rate index (HRI), is dependent only on heart rate (HR) and was tested against oxygen uptake (VO2), either measured or predicted from conventional treadmill parameters (speed, incline, protocol time). Methods The HRI equation, METs = 6 x HRI– 5, where HRI = maximal HR/resting HR, provides a surrogate measure of VO2peak. Forty large scale treadmill studies were identified through a systematic search using MEDLINE, Google Scholar and Web of Science in which VO2peak was either measured (TM-VO2meas; n = 20) or predicted (TM-VO2pred; n = 20) based on treadmill parameters. All studies were required to have reported group mean data of both resting and maximal HRs for determination of HR index-derived oxygen uptake (HRI-VO2). Results The 20 studies with measured VO2 (TM-VO2meas), involved 11,477 participants (median 337) with a total of 105,044 participants (median 3,736) in the 20 studies with predicted VO2 (TM-VO2pred). A difference of only 0.4% was seen between mean (±SD) VO2peak for TM- VO2meas and HRI-VO2 (6.51±2.25 METs and 6.54±2.28, respectively; p = 0.84). In contrast, there was a highly significant 21.1% difference between mean (±SD) TM-VO2pred and HRI-VO2 (8.12±1.85 METs and 6.71±1.92, respectively; p<0.001). Conclusion Although mean TM-VO2meas and HRI-VO2 were almost identical, mean TM-VO2pred was more than 20% greater than mean HRI-VO2. PMID:27875547

  8. Integrative subcellular proteomic analysis allows accurate prediction of human disease-causing genes

    PubMed Central

    Zhao, Li; Chen, Yiyun; Bajaj, Amol Onkar; Eblimit, Aiden; Xu, Mingchu; Soens, Zachry T.; Wang, Feng; Ge, Zhongqi; Jung, Sung Yun; He, Feng; Li, Yumei; Wensel, Theodore G.; Qin, Jun; Chen, Rui

    2016-01-01

    Proteomic profiling on subcellular fractions provides invaluable information regarding both protein abundance and subcellular localization. When integrated with other data sets, it can greatly enhance our ability to predict gene function genome-wide. In this study, we performed a comprehensive proteomic analysis on the light-sensing compartment of photoreceptors called the outer segment (OS). By comparing with the protein profile obtained from the retina tissue depleted of OS, an enrichment score for each protein is calculated to quantify protein subcellular localization, and 84% accuracy is achieved compared with experimental data. By integrating the protein OS enrichment score, the protein abundance, and the retina transcriptome, the probability of a gene playing an essential function in photoreceptor cells is derived with high specificity and sensitivity. As a result, a list of genes that will likely result in human retinal disease when mutated was identified and validated by previous literature and/or animal model studies. Therefore, this new methodology demonstrates the synergy of combining subcellular fractionation proteomics with other omics data sets and is generally applicable to other tissues and diseases. PMID:26912414

  9. A machine learning approach to the accurate prediction of multi-leaf collimator positional errors

    NASA Astrophysics Data System (ADS)

    Carlson, Joel N. K.; Park, Jong Min; Park, So-Yeon; In Park, Jong; Choi, Yunseok; Ye, Sung-Joon

    2016-03-01

    Discrepancies between planned and delivered movements of multi-leaf collimators (MLCs) are an important source of errors in dose distributions during radiotherapy. In this work we used machine learning techniques to train models to predict these discrepancies, assessed the accuracy of the model predictions, and examined the impact these errors have on quality assurance (QA) procedures and dosimetry. Predictive leaf motion parameters for the models were calculated from the plan files, such as leaf position and velocity, whether the leaf was moving towards or away from the isocenter of the MLC, and many others. Differences in positions between synchronized DICOM-RT planning files and DynaLog files reported during QA delivery were used as a target response for training of the models. The final model is capable of predicting MLC positions during delivery to a high degree of accuracy. For moving MLC leaves, predicted positions were shown to be significantly closer to delivered positions than were planned positions. By incorporating predicted positions into dose calculations in the TPS, increases were shown in gamma passing rates against measured dose distributions recorded during QA delivery. For instance, head and neck plans with 1%/2 mm gamma criteria had an average increase in passing rate of 4.17% (SD  =  1.54%). This indicates that the inclusion of predictions during dose calculation leads to a more realistic representation of plan delivery. To assess impact on the patient, dose volumetric histograms (DVH) using delivered positions were calculated for comparison with planned and predicted DVHs. In all cases, predicted dose volumetric parameters were in closer agreement to the delivered parameters than were the planned parameters, particularly for organs at risk on the periphery of the treatment area. By incorporating the predicted positions into the TPS, the treatment planner is given a more realistic view of the dose distribution as it will truly be

  10. Accurate prediction of the refractive index of polymers using first principles and data modeling

    NASA Astrophysics Data System (ADS)

    Afzal, Mohammad Atif Faiz; Cheng, Chong; Hachmann, Johannes

    Organic polymers with a high refractive index (RI) have recently attracted considerable interest due to their potential application in optical and optoelectronic devices. The ability to tailor the molecular structure of polymers is the key to increasing the accessible RI values. Our work concerns the creation of predictive in silico models for the optical properties of organic polymers, the screening of large-scale candidate libraries, and the mining of the resulting data to extract the underlying design principles that govern their performance. This work was set up to guide our experimentalist partners and allow them to target the most promising candidates. Our model is based on the Lorentz-Lorenz equation and thus includes the polarizability and number density values for each candidate. For the former, we performed a detailed benchmark study of different density functionals, basis sets, and the extrapolation scheme towards the polymer limit. For the number density we devised an exceedingly efficient machine learning approach to correlate the polymer structure and the packing fraction in the bulk material. We validated the proposed RI model against the experimentally known RI values of 112 polymers. We could show that the proposed combination of physical and data modeling is both successful and highly economical to characterize a wide range of organic polymers, which is a prerequisite for virtual high-throughput screening.

  11. The human skin/chick chorioallantoic membrane model accurately predicts the potency of cosmetic allergens.

    PubMed

    Slodownik, Dan; Grinberg, Igor; Spira, Ram M; Skornik, Yehuda; Goldstein, Ronald S

    2009-04-01

    The current standard method for predicting contact allergenicity is the murine local lymph node assay (LLNA). Public objection to the use of animals in testing of cosmetics makes the development of a system that does not use sentient animals highly desirable. The chorioallantoic membrane (CAM) of the chick egg has been extensively used for the growth of normal and transformed mammalian tissues. The CAM is not innervated, and embryos are sacrificed before the development of pain perception. The aim of this study was to determine whether the sensitization phase of contact dermatitis to known cosmetic allergens can be quantified using CAM-engrafted human skin and how these results compare with published EC3 data obtained with the LLNA. We studied six common molecules used in allergen testing and quantified migration of epidermal Langerhans cells (LC) as a measure of their allergic potency. All agents with known allergic potential induced statistically significant migration of LC. The data obtained correlated well with published data for these allergens generated using the LLNA test. The human-skin CAM model therefore has great potential as an inexpensive, non-radioactive, in vivo alternative to the LLNA, which does not require the use of sentient animals. In addition, this system has the advantage of testing the allergic response of human, rather than animal skin.

  12. Towards Relaxing the Spherical Solar Radiation Pressure Model for Accurate Orbit Predictions

    NASA Astrophysics Data System (ADS)

    Lachut, M.; Bennett, J.

    2016-09-01

    The well-known cannonball model has been used ubiquitously to capture the effects of atmospheric drag and solar radiation pressure on satellites and/or space debris for decades. While it lends itself naturally to spherical objects, its validity in the case of non-spherical objects has been debated heavily for years throughout the space situational awareness community. One of the leading motivations to improve orbit predictions by relaxing the spherical assumption, is the ongoing demand for more robust and reliable conjunction assessments. In this study, we explore the orbit propagation of a flat plate in a near-GEO orbit under the influence of solar radiation pressure, using a Lambertian BRDF model. Consequently, this approach will account for the spin rate and orientation of the object, which is typically determined in practice using a light curve analysis. Here, simulations will be performed which systematically reduces the spin rate to demonstrate the point at which the spherical model no longer describes the orbital elements of the spinning plate. Further understanding of this threshold would provide insight into when a higher fidelity model should be used, thus resulting in improved orbit propagations. Therefore, the work presented here is of particular interest to organizations and researchers that maintain their own catalog, and/or perform conjunction analyses.

  13. Towards Accurate Prediction of Turbulent, Three-Dimensional, Recirculating Flows with the NCC

    NASA Technical Reports Server (NTRS)

    Iannetti, A.; Tacina, R.; Jeng, S.-M.; Cai, J.

    2001-01-01

    The National Combustion Code (NCC) was used to calculate the steady state, nonreacting flow field of a prototype Lean Direct Injection (LDI) swirler. This configuration used nine groups of eight holes drilled at a thirty-five degree angle to induce swirl. These nine groups created swirl in the same direction, or a corotating pattern. The static pressure drop across the holes was fixed at approximately four percent. Computations were performed on one quarter of the geometry, because the geometry is considered rotationally periodic every ninety degrees. The final computational grid used was approximately 2.26 million tetrahedral cells, and a cubic nonlinear k - epsilon model was used to model turbulence. The NCC results were then compared to time averaged Laser Doppler Velocimetry (LDV) data. The LDV measurements were performed on the full geometry, but four ninths of the geometry was measured. One-, two-, and three-dimensional representations of both flow fields are presented. The NCC computations compare both qualitatively and quantitatively well to the LDV data, but differences exist downstream. The comparison is encouraging, and shows that NCC can be used for future injector design studies. To improve the flow prediction accuracy of turbulent, three-dimensional, recirculating flow fields with the NCC, recommendations are given.

  14. A Support Vector Machine model for the prediction of proteotypic peptides for accurate mass and time proteomics

    SciTech Connect

    Webb-Robertson, Bobbie-Jo M.; Cannon, William R.; Oehmen, Christopher S.; Shah, Anuj R.; Gurumoorthi, Vidhya; Lipton, Mary S.; Waters, Katrina M.

    2008-07-01

    Motivation: The standard approach to identifying peptides based on accurate mass and elution time (AMT) compares these profiles obtained from a high resolution mass spectrometer to a database of peptides previously identified from tandem mass spectrometry (MS/MS) studies. It would be advantageous, with respect to both accuracy and cost, to only search for those peptides that are detectable by MS (proteotypic). Results: We present a Support Vector Machine (SVM) model that uses a simple descriptor space based on 35 properties of amino acid content, charge, hydrophilicity, and polarity for the quantitative prediction of proteotypic peptides. Using three independently derived AMT databases (Shewanella oneidensis, Salmonella typhimurium, Yersinia pestis) for training and validation within and across species, the SVM resulted in an average accuracy measure of ~0.8 with a standard deviation of less than 0.025. Furthermore, we demonstrate that these results are achievable with a small set of 12 variables and can achieve high proteome coverage. Availability: http://omics.pnl.gov/software/STEPP.php

  15. Sensor data fusion for accurate cloud presence prediction using Dempster-Shafer evidence theory.

    PubMed

    Li, Jiaming; Luo, Suhuai; Jin, Jesse S

    2010-01-01

    Sensor data fusion technology can be used to best extract useful information from multiple sensor observations. It has been widely applied in various applications such as target tracking, surveillance, robot navigation, signal and image processing. This paper introduces a novel data fusion approach in a multiple radiation sensor environment using Dempster-Shafer evidence theory. The methodology is used to predict cloud presence based on the inputs of radiation sensors. Different radiation data have been used for the cloud prediction. The potential application areas of the algorithm include renewable power for virtual power station where the prediction of cloud presence is the most challenging issue for its photovoltaic output. The algorithm is validated by comparing the predicted cloud presence with the corresponding sunshine occurrence data that were recorded as the benchmark. Our experiments have indicated that comparing to the approaches using individual sensors, the proposed data fusion approach can increase correct rate of cloud prediction by ten percent, and decrease unknown rate of cloud prediction by twenty three percent.

  16. How Accurate Are the Anthropometry Equations in in Iranian Military Men in Predicting Body Composition?

    PubMed Central

    Shakibaee, Abolfazl; Faghihzadeh, Soghrat; Alishiri, Gholam Hossein; Ebrahimpour, Zeynab; Faradjzadeh, Shahram; Sobhani, Vahid; Asgari, Alireza

    2015-01-01

    Background: The body composition varies according to different life styles (i.e. intake calories and caloric expenditure). Therefore, it is wise to record military personnel’s body composition periodically and encourage those who abide to the regulations. Different methods have been introduced for body composition assessment: invasive and non-invasive. Amongst them, the Jackson and Pollock equation is most popular. Objectives: The recommended anthropometric prediction equations for assessing men’s body composition were compared with dual-energy X-ray absorptiometry (DEXA) gold standard to develop a modified equation to assess body composition and obesity quantitatively among Iranian military men. Patients and Methods: A total of 101 military men aged 23 - 52 years old with a mean age of 35.5 years were recruited and evaluated in the present study (average height, 173.9 cm and weight, 81.5 kg). The body-fat percentages of subjects were assessed both with anthropometric assessment and DEXA scan. The data obtained from these two methods were then compared using multiple regression analysis. Results: The mean and standard deviation of body fat percentage of the DEXA assessment was 21.2 ± 4.3 and body fat percentage obtained from three Jackson and Pollock 3-, 4- and 7-site equations were 21.1 ± 5.8, 22.2 ± 6.0 and 20.9 ± 5.7, respectively. There was a strong correlation between these three equations and DEXA (R² = 0.98). Conclusions: The mean percentage of body fat obtained from the three equations of Jackson and Pollock was very close to that of body fat obtained from DEXA; however, we suggest using a modified Jackson-Pollock 3-site equation for volunteer military men because the 3-site equation analysis method is simpler and faster than other methods. PMID:26715964

  17. Toward accurate prediction of pKa values for internal protein residues: the importance of conformational relaxation and desolvation energy.

    PubMed

    Wallace, Jason A; Wang, Yuhang; Shi, Chuanyin; Pastoor, Kevin J; Nguyen, Bao-Linh; Xia, Kai; Shen, Jana K

    2011-12-01

    Proton uptake or release controls many important biological processes, such as energy transduction, virus replication, and catalysis. Accurate pK(a) prediction informs about proton pathways, thereby revealing detailed acid-base mechanisms. Physics-based methods in the framework of molecular dynamics simulations not only offer pK(a) predictions but also inform about the physical origins of pK(a) shifts and provide details of ionization-induced conformational relaxation and large-scale transitions. One such method is the recently developed continuous constant pH molecular dynamics (CPHMD) method, which has been shown to be an accurate and robust pK(a) prediction tool for naturally occurring titratable residues. To further examine the accuracy and limitations of CPHMD, we blindly predicted the pK(a) values for 87 titratable residues introduced in various hydrophobic regions of staphylococcal nuclease and variants. The predictions gave a root-mean-square deviation of 1.69 pK units from experiment, and there were only two pK(a)'s with errors greater than 3.5 pK units. Analysis of the conformational fluctuation of titrating side-chains in the context of the errors of calculated pK(a) values indicate that explicit treatment of conformational flexibility and the associated dielectric relaxation gives CPHMD a distinct advantage. Analysis of the sources of errors suggests that more accurate pK(a) predictions can be obtained for the most deeply buried residues by improving the accuracy in calculating desolvation energies. Furthermore, it is found that the generalized Born implicit-solvent model underlying the current CPHMD implementation slightly distorts the local conformational environment such that the inclusion of an explicit-solvent representation may offer improvement of accuracy.

  18. NESmapper: accurate prediction of leucine-rich nuclear export signals using activity-based profiles.

    PubMed

    Kosugi, Shunichi; Yanagawa, Hiroshi; Terauchi, Ryohei; Tabata, Satoshi

    2014-09-01

    The nuclear export of proteins is regulated largely through the exportin/CRM1 pathway, which involves the specific recognition of leucine-rich nuclear export signals (NESs) in the cargo proteins, and modulates nuclear-cytoplasmic protein shuttling by antagonizing the nuclear import activity mediated by importins and the nuclear import signal (NLS). Although the prediction of NESs can help to define proteins that undergo regulated nuclear export, current methods of predicting NESs, including computational tools and consensus-sequence-based searches, have limited accuracy, especially in terms of their specificity. We found that each residue within an NES largely contributes independently and additively to the entire nuclear export activity. We created activity-based profiles of all classes of NESs with a comprehensive mutational analysis in mammalian cells. The profiles highlight a number of specific activity-affecting residues not only at the conserved hydrophobic positions but also in the linker and flanking regions. We then developed a computational tool, NESmapper, to predict NESs by using profiles that had been further optimized by training and combining the amino acid properties of the NES-flanking regions. This tool successfully reduced the considerable number of false positives, and the overall prediction accuracy was higher than that of other methods, including NESsential and Wregex. This profile-based prediction strategy is a reliable way to identify functional protein motifs. NESmapper is available at http://sourceforge.net/projects/nesmapper.

  19. Multi-omics integration accurately predicts cellular state in unexplored conditions for Escherichia coli

    PubMed Central

    Kim, Minseung; Rai, Navneet; Zorraquino, Violeta; Tagkopoulos, Ilias

    2016-01-01

    A significant obstacle in training predictive cell models is the lack of integrated data sources. We develop semi-supervised normalization pipelines and perform experimental characterization (growth, transcriptional, proteome) to create Ecomics, a consistent, quality-controlled multi-omics compendium for Escherichia coli with cohesive meta-data information. We then use this resource to train a multi-scale model that integrates four omics layers to predict genome-wide concentrations and growth dynamics. The genetic and environmental ontology reconstructed from the omics data is substantially different and complementary to the genetic and chemical ontologies. The integration of different layers confers an incremental increase in the prediction performance, as does the information about the known gene regulatory and protein-protein interactions. The predictive performance of the model ranges from 0.54 to 0.87 for the various omics layers, which far exceeds various baselines. This work provides an integrative framework of omics-driven predictive modelling that is broadly applicable to guide biological discovery. PMID:27713404

  20. Empirical approaches to more accurately predict benthic-pelagic coupling in biogeochemical ocean models

    NASA Astrophysics Data System (ADS)

    Dale, Andy; Stolpovsky, Konstantin; Wallmann, Klaus

    2016-04-01

    The recycling and burial of biogenic material in the sea floor plays a key role in the regulation of ocean chemistry. Proper consideration of these processes in ocean biogeochemical models is becoming increasingly recognized as an important step in model validation and prediction. However, the rate of organic matter remineralization in sediments and the benthic flux of redox-sensitive elements are difficult to predict a priori. In this communication, examples of empirical benthic flux models that can be coupled to earth system models to predict sediment-water exchange in the open ocean are presented. Large uncertainties hindering further progress in this field include knowledge of the reactivity of organic carbon reaching the sediment, the importance of episodic variability in bottom water chemistry and particle rain rates (for both the deep-sea and margins) and the role of benthic fauna. How do we meet the challenge?

  1. An endometrial gene expression signature accurately predicts recurrent implantation failure after IVF

    PubMed Central

    Koot, Yvonne E. M.; van Hooff, Sander R.; Boomsma, Carolien M.; van Leenen, Dik; Groot Koerkamp, Marian J. A.; Goddijn, Mariëtte; Eijkemans, Marinus J. C.; Fauser, Bart C. J. M.; Holstege, Frank C. P.; Macklon, Nick S.

    2016-01-01

    The primary limiting factor for effective IVF treatment is successful embryo implantation. Recurrent implantation failure (RIF) is a condition whereby couples fail to achieve pregnancy despite consecutive embryo transfers. Here we describe the collection of gene expression profiles from mid-luteal phase endometrial biopsies (n = 115) from women experiencing RIF and healthy controls. Using a signature discovery set (n = 81) we identify a signature containing 303 genes predictive of RIF. Independent validation in 34 samples shows that the gene signature predicts RIF with 100% positive predictive value (PPV). The strength of the RIF associated expression signature also stratifies RIF patients into distinct groups with different subsequent implantation success rates. Exploration of the expression changes suggests that RIF is primarily associated with reduced cellular proliferation. The gene signature will be of value in counselling and guiding further treatment of women who fail to conceive upon IVF and suggests new avenues for developing intervention. PMID:26797113

  2. Accurate ab initio prediction of NMR chemical shifts of nucleic acids and nucleic acids/protein complexes

    PubMed Central

    Victora, Andrea; Möller, Heiko M.; Exner, Thomas E.

    2014-01-01

    NMR chemical shift predictions based on empirical methods are nowadays indispensable tools during resonance assignment and 3D structure calculation of proteins. However, owing to the very limited statistical data basis, such methods are still in their infancy in the field of nucleic acids, especially when non-canonical structures and nucleic acid complexes are considered. Here, we present an ab initio approach for predicting proton chemical shifts of arbitrary nucleic acid structures based on state-of-the-art fragment-based quantum chemical calculations. We tested our prediction method on a diverse set of nucleic acid structures including double-stranded DNA, hairpins, DNA/protein complexes and chemically-modified DNA. Overall, our quantum chemical calculations yield highly/very accurate predictions with mean absolute deviations of 0.3–0.6 ppm and correlation coefficients (r2) usually above 0.9. This will allow for identifying misassignments and validating 3D structures. Furthermore, our calculations reveal that chemical shifts of protons involved in hydrogen bonding are predicted significantly less accurately. This is in part caused by insufficient inclusion of solvation effects. However, it also points toward shortcomings of current force fields used for structure determination of nucleic acids. Our quantum chemical calculations could therefore provide input for force field optimization. PMID:25404135

  3. The development and verification of a highly accurate collision prediction model for automated noncoplanar plan delivery

    SciTech Connect

    Yu, Victoria Y.; Tran, Angelia; Nguyen, Dan; Cao, Minsong; Ruan, Dan; Low, Daniel A.; Sheng, Ke

    2015-11-15

    Purpose: Significant dosimetric benefits had been previously demonstrated in highly noncoplanar treatment plans. In this study, the authors developed and verified an individualized collision model for the purpose of delivering highly noncoplanar radiotherapy and tested the feasibility of total delivery automation with Varian TrueBeam developer mode. Methods: A hand-held 3D scanner was used to capture the surfaces of an anthropomorphic phantom and a human subject, which were positioned with a computer-aided design model of a TrueBeam machine to create a detailed virtual geometrical collision model. The collision model included gantry, collimator, and couch motion degrees of freedom. The accuracy of the 3D scanner was validated by scanning a rigid cubical phantom with known dimensions. The collision model was then validated by generating 300 linear accelerator orientations corresponding to 300 gantry-to-couch and gantry-to-phantom distances, and comparing the corresponding distance measurements to their corresponding models. The linear accelerator orientations reflected uniformly sampled noncoplanar beam angles to the head, lung, and prostate. The distance discrepancies between measurements on the physical and virtual systems were used to estimate treatment-site-specific safety buffer distances with 0.1%, 0.01%, and 0.001% probability of collision between the gantry and couch or phantom. Plans containing 20 noncoplanar beams to the brain, lung, and prostate optimized via an in-house noncoplanar radiotherapy platform were converted into XML script for automated delivery and the entire delivery was recorded and timed to demonstrate the feasibility of automated delivery. Results: The 3D scanner measured the dimension of the 14 cm cubic phantom within 0.5 mm. The maximal absolute discrepancy between machine and model measurements for gantry-to-couch and gantry-to-phantom was 0.95 and 2.97 cm, respectively. The reduced accuracy of gantry-to-phantom measurements was

  4. The development and verification of a highly accurate collision prediction model for automated noncoplanar plan delivery

    PubMed Central

    Yu, Victoria Y.; Tran, Angelia; Nguyen, Dan; Cao, Minsong; Ruan, Dan; Low, Daniel A.; Sheng, Ke

    2015-01-01

    Purpose: Significant dosimetric benefits had been previously demonstrated in highly noncoplanar treatment plans. In this study, the authors developed and verified an individualized collision model for the purpose of delivering highly noncoplanar radiotherapy and tested the feasibility of total delivery automation with Varian TrueBeam developer mode. Methods: A hand-held 3D scanner was used to capture the surfaces of an anthropomorphic phantom and a human subject, which were positioned with a computer-aided design model of a TrueBeam machine to create a detailed virtual geometrical collision model. The collision model included gantry, collimator, and couch motion degrees of freedom. The accuracy of the 3D scanner was validated by scanning a rigid cubical phantom with known dimensions. The collision model was then validated by generating 300 linear accelerator orientations corresponding to 300 gantry-to-couch and gantry-to-phantom distances, and comparing the corresponding distance measurements to their corresponding models. The linear accelerator orientations reflected uniformly sampled noncoplanar beam angles to the head, lung, and prostate. The distance discrepancies between measurements on the physical and virtual systems were used to estimate treatment-site-specific safety buffer distances with 0.1%, 0.01%, and 0.001% probability of collision between the gantry and couch or phantom. Plans containing 20 noncoplanar beams to the brain, lung, and prostate optimized via an in-house noncoplanar radiotherapy platform were converted into XML script for automated delivery and the entire delivery was recorded and timed to demonstrate the feasibility of automated delivery. Results: The 3D scanner measured the dimension of the 14 cm cubic phantom within 0.5 mm. The maximal absolute discrepancy between machine and model measurements for gantry-to-couch and gantry-to-phantom was 0.95 and 2.97 cm, respectively. The reduced accuracy of gantry-to-phantom measurements was

  5. High IFIT1 expression predicts improved clinical outcome, and IFIT1 along with MGMT more accurately predicts prognosis in newly diagnosed glioblastoma.

    PubMed

    Zhang, Jin-Feng; Chen, Yao; Lin, Guo-Shi; Zhang, Jian-Dong; Tang, Wen-Long; Huang, Jian-Huang; Chen, Jin-Shou; Wang, Xing-Fu; Lin, Zhi-Xiong

    2016-06-01

    Interferon-induced protein with tetratricopeptide repeat 1 (IFIT1) plays a key role in growth suppression and apoptosis promotion in cancer cells. Interferon was reported to induce the expression of IFIT1 and inhibit the expression of O-6-methylguanine-DNA methyltransferase (MGMT).This study aimed to investigate the expression of IFIT1, the correlation between IFIT1 and MGMT, and their impact on the clinical outcome in newly diagnosed glioblastoma. The expression of IFIT1 and MGMT and their correlation were investigated in the tumor tissues from 70 patients with newly diagnosed glioblastoma. The effects on progression-free survival and overall survival were evaluated. Of 70 cases, 57 (81.4%) tissue samples showed high expression of IFIT1 by immunostaining. The χ(2) test indicated that the expression of IFIT1 and MGMT was negatively correlated (r = -0.288, P = .016). Univariate and multivariate analyses confirmed high IFIT1 expression as a favorable prognostic indicator for progression-free survival (P = .005 and .017) and overall survival (P = .001 and .001), respectively. Patients with 2 favorable factors (high IFIT1 and low MGMT) had an improved prognosis as compared with others. The results demonstrated significantly increased expression of IFIT1 in newly diagnosed glioblastoma tissue. The negative correlation between IFIT1 and MGMT expression may be triggered by interferon. High IFIT1 can be a predictive biomarker of favorable clinical outcome, and IFIT1 along with MGMT more accurately predicts prognosis in newly diagnosed glioblastoma.

  6. Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance

    PubMed Central

    Hong, Ha; Solomon, Ethan A.; DiCarlo, James J.

    2015-01-01

    To go beyond qualitative models of the biological substrate of object recognition, we ask: can a single ventral stream neuronal linking hypothesis quantitatively account for core object recognition performance over a broad range of tasks? We measured human performance in 64 object recognition tests using thousands of challenging images that explore shape similarity and identity preserving object variation. We then used multielectrode arrays to measure neuronal population responses to those same images in visual areas V4 and inferior temporal (IT) cortex of monkeys and simulated V1 population responses. We tested leading candidate linking hypotheses and control hypotheses, each postulating how ventral stream neuronal responses underlie object recognition behavior. Specifically, for each hypothesis, we computed the predicted performance on the 64 tests and compared it with the measured pattern of human performance. All tested hypotheses based on low- and mid-level visually evoked activity (pixels, V1, and V4) were very poor predictors of the human behavioral pattern. However, simple learned weighted sums of distributed average IT firing rates exactly predicted the behavioral pattern. More elaborate linking hypotheses relying on IT trial-by-trial correlational structure, finer IT temporal codes, or ones that strictly respect the known spatial substructures of IT (“face patches”) did not improve predictive power. Although these results do not reject those more elaborate hypotheses, they suggest a simple, sufficient quantitative model: each object recognition task is learned from the spatially distributed mean firing rates (100 ms) of ∼60,000 IT neurons and is executed as a simple weighted sum of those firing rates. SIGNIFICANCE STATEMENT We sought to go beyond qualitative models of visual object recognition and determine whether a single neuronal linking hypothesis can quantitatively account for core object recognition behavior. To achieve this, we designed a

  7. Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance.

    PubMed

    Majaj, Najib J; Hong, Ha; Solomon, Ethan A; DiCarlo, James J

    2015-09-30

    To go beyond qualitative models of the biological substrate of object recognition, we ask: can a single ventral stream neuronal linking hypothesis quantitatively account for core object recognition performance over a broad range of tasks? We measured human performance in 64 object recognition tests using thousands of challenging images that explore shape similarity and identity preserving object variation. We then used multielectrode arrays to measure neuronal population responses to those same images in visual areas V4 and inferior temporal (IT) cortex of monkeys and simulated V1 population responses. We tested leading candidate linking hypotheses and control hypotheses, each postulating how ventral stream neuronal responses underlie object recognition behavior. Specifically, for each hypothesis, we computed the predicted performance on the 64 tests and compared it with the measured pattern of human performance. All tested hypotheses based on low- and mid-level visually evoked activity (pixels, V1, and V4) were very poor predictors of the human behavioral pattern. However, simple learned weighted sums of distributed average IT firing rates exactly predicted the behavioral pattern. More elaborate linking hypotheses relying on IT trial-by-trial correlational structure, finer IT temporal codes, or ones that strictly respect the known spatial substructures of IT ("face patches") did not improve predictive power. Although these results do not reject those more elaborate hypotheses, they suggest a simple, sufficient quantitative model: each object recognition task is learned from the spatially distributed mean firing rates (100 ms) of ∼60,000 IT neurons and is executed as a simple weighted sum of those firing rates. Significance statement: We sought to go beyond qualitative models of visual object recognition and determine whether a single neuronal linking hypothesis can quantitatively account for core object recognition behavior. To achieve this, we designed a

  8. Dynamics of Flexible MLI-type Debris for Accurate Orbit Prediction

    DTIC Science & Technology

    2014-09-01

    SUBJECT TERMS EOARD, orbital debris , HAMR objects, multi-layered insulation, orbital dynamics, orbit predictions, orbital propagation 16. SECURITY...illustration are orbital debris [Souce: NASA...piece of space junk (a paint fleck) during the STS-7 mission (Photo: NASA Orbital Debris Program Office

  9. Hippocampus neuronal metabolic gene expression outperforms whole tissue data in accurately predicting Alzheimer's disease progression.

    PubMed

    Stempler, Shiri; Waldman, Yedael Y; Wolf, Lior; Ruppin, Eytan

    2012-09-01

    Numerous metabolic alterations are associated with the impairment of brain cells in Alzheimer's disease (AD). Here we use gene expression microarrays of both whole hippocampus tissue and hippocampal neurons of AD patients to investigate the ability of metabolic gene expression to predict AD progression and its cognitive decline. We find that the prediction accuracy of different AD stages is markedly higher when using neuronal expression data (0.9) than when using whole tissue expression (0.76). Furthermore, the metabolic genes' expression is shown to be as effective in predicting AD severity as the entire gene list. Remarkably, a regression model from hippocampal metabolic gene expression leads to a marked correlation of 0.57 with the Mini-Mental State Examination cognitive score. Notably, the expression of top predictive neuronal genes in AD is significantly higher than that of other metabolic genes in the brains of healthy subjects. All together, the analyses point to a subset of metabolic genes that is strongly associated with normal brain functioning and whose disruption plays a major role in AD.

  10. Predicting repeat self-harm in children--how accurate can we expect to be?

    PubMed

    Chitsabesan, Prathiba; Harrington, Richard; Harrington, Valerie; Tomenson, Barbara

    2003-01-01

    The main objective of the study was to find which variables predict repetition of deliberate self-harm in children. The study is based on a group of children who took part in a randomized control trial investigating the effects of a home-based family intervention for children who had deliberately poisoned themselves. These children had a range of baseline and outcome measures collected on two occasions (two and six months follow-up). Outcome data were collected from 149 (92 %) of the initial 162 children over the six months. Twenty-three children made a further deliberate self-harm attempt within the follow-up period. A number of variables at baseline were found to be significantly associated with repeat self-harm. Parental mental health and a history of previous attempts were the strongest predictors. A model of prediction of further deliberate self-harm combining these significant individual variables produced a high positive predictive value (86 %) but had low sensitivity (28 %). Predicting repeat self-harm in children is difficult, even with a comprehensive series of assessments over multiple time points, and we need to adapt services with this in mind. We propose a model of service provision which takes these findings into account.

  11. Molecular Dynamics in Mixed Solvents Reveals Protein-Ligand Interactions, Improves Docking, and Allows Accurate Binding Free Energy Predictions.

    PubMed

    Arcon, Juan Pablo; Defelipe, Lucas A; Modenutti, Carlos P; López, Elias D; Alvarez-Garcia, Daniel; Barril, Xavier; Turjanski, Adrián G; Martí, Marcelo A

    2017-03-31

    One of the most important biological processes at the molecular level is the formation of protein-ligand complexes. Therefore, determining their structure and underlying key interactions is of paramount relevance and has direct applications in drug development. Because of its low cost relative to its experimental sibling, molecular dynamics (MD) simulations in the presence of different solvent probes mimicking specific types of interactions have been increasingly used to analyze protein binding sites and reveal protein-ligand interaction hot spots. However, a systematic comparison of different probes and their real predictive power from a quantitative and thermodynamic point of view is still missing. In the present work, we have performed MD simulations of 18 different proteins in pure water as well as water mixtures of ethanol, acetamide, acetonitrile and methylammonium acetate, leading to a total of 5.4 μs simulation time. For each system, we determined the corresponding solvent sites, defined as space regions adjacent to the protein surface where the probability of finding a probe atom is higher than that in the bulk solvent. Finally, we compared the identified solvent sites with 121 different protein-ligand complexes and used them to perform molecular docking and ligand binding free energy estimates. Our results show that combining solely water and ethanol sites allows sampling over 70% of all possible protein-ligand interactions, especially those that coincide with ligand-based pharmacophoric points. Most important, we also show how the solvent sites can be used to significantly improve ligand docking in terms of both accuracy and precision, and that accurate predictions of ligand binding free energies, along with relative ranking of ligand affinity, can be performed.

  12. Industrial Compositional Streamline Simulation for Efficient and Accurate Prediction of Gas Injection and WAG Processes

    SciTech Connect

    Margot Gerritsen

    2008-10-31

    Gas-injection processes are widely and increasingly used for enhanced oil recovery (EOR). In the United States, for example, EOR production by gas injection accounts for approximately 45% of total EOR production and has tripled since 1986. The understanding of the multiphase, multicomponent flow taking place in any displacement process is essential for successful design of gas-injection projects. Due to complex reservoir geometry, reservoir fluid properties and phase behavior, the design of accurate and efficient numerical simulations for the multiphase, multicomponent flow governing these processes is nontrivial. In this work, we developed, implemented and tested a streamline based solver for gas injection processes that is computationally very attractive: as compared to traditional Eulerian solvers in use by industry it computes solutions with a computational speed orders of magnitude higher and a comparable accuracy provided that cross-flow effects do not dominate. We contributed to the development of compositional streamline solvers in three significant ways: improvement of the overall framework allowing improved streamline coverage and partial streamline tracing, amongst others; parallelization of the streamline code, which significantly improves wall clock time; and development of new compositional solvers that can be implemented along streamlines as well as in existing Eulerian codes used by industry. We designed several novel ideas in the streamline framework. First, we developed an adaptive streamline coverage algorithm. Adding streamlines locally can reduce computational costs by concentrating computational efforts where needed, and reduce mapping errors. Adapting streamline coverage effectively controls mass balance errors that mostly result from the mapping from streamlines to pressure grid. We also introduced the concept of partial streamlines: streamlines that do not necessarily start and/or end at wells. This allows more efficient coverage and avoids

  13. Fast and accurate numerical method for predicting gas chromatography retention time.

    PubMed

    Claumann, Carlos Alberto; Wüst Zibetti, André; Bolzan, Ariovaldo; Machado, Ricardo A F; Pinto, Leonel Teixeira

    2015-08-07

    Predictive modeling for gas chromatography compound retention depends on the retention factor (ki) and on the flow of the mobile phase. Thus, different approaches for determining an analyte ki in column chromatography have been developed. The main one is based on the thermodynamic properties of the component and on the characteristics of the stationary phase. These models can be used to estimate the parameters and to optimize the programming of temperatures, in gas chromatography, for the separation of compounds. Different authors have proposed the use of numerical methods for solving these models, but these methods demand greater computational time. Hence, a new method for solving the predictive modeling of analyte retention time is presented. This algorithm is an alternative to traditional methods because it transforms its attainments into root determination problems within defined intervals. The proposed approach allows for tr calculation, with accuracy determined by the user of the methods, and significant reductions in computational time; it can also be used to evaluate the performance of other prediction methods.

  14. Revisiting the blind tests in crystal structure prediction: accurate energy ranking of molecular crystals.

    PubMed

    Asmadi, Aldi; Neumann, Marcus A; Kendrick, John; Girard, Pascale; Perrin, Marc-Antoine; Leusen, Frank J J

    2009-12-24

    In the 2007 blind test of crystal structure prediction hosted by the Cambridge Crystallographic Data Centre (CCDC), a hybrid DFT/MM method correctly ranked each of the four experimental structures as having the lowest lattice energy of all the crystal structures predicted for each molecule. The work presented here further validates this hybrid method by optimizing the crystal structures (experimental and submitted) of the first three CCDC blind tests held in 1999, 2001, and 2004. Except for the crystal structures of compound IX, all structures were reminimized and ranked according to their lattice energies. The hybrid method computes the lattice energy of a crystal structure as the sum of the DFT total energy and a van der Waals (dispersion) energy correction. Considering all four blind tests, the crystal structure with the lowest lattice energy corresponds to the experimentally observed structure for 12 out of 14 molecules. Moreover, good geometrical agreement is observed between the structures determined by the hybrid method and those measured experimentally. In comparison with the correct submissions made by the blind test participants, all hybrid optimized crystal structures (apart from compound II) have the smallest calculated root mean squared deviations from the experimentally observed structures. It is predicted that a new polymorph of compound V exists under pressure.

  15. Accurate prediction of drug-induced liver injury using stem cell-derived populations.

    PubMed

    Szkolnicka, Dagmara; Farnworth, Sarah L; Lucendo-Villarin, Baltasar; Storck, Christopher; Zhou, Wenli; Iredale, John P; Flint, Oliver; Hay, David C

    2014-02-01

    Despite major progress in the knowledge and management of human liver injury, there are millions of people suffering from chronic liver disease. Currently, the only cure for end-stage liver disease is orthotopic liver transplantation; however, this approach is severely limited by organ donation. Alternative approaches to restoring liver function have therefore been pursued, including the use of somatic and stem cell populations. Although such approaches are essential in developing scalable treatments, there is also an imperative to develop predictive human systems that more effectively study and/or prevent the onset of liver disease and decompensated organ function. We used a renewable human stem cell resource, from defined genetic backgrounds, and drove them through developmental intermediates to yield highly active, drug-inducible, and predictive human hepatocyte populations. Most importantly, stem cell-derived hepatocytes displayed equivalence to primary adult hepatocytes, following incubation with known hepatotoxins. In summary, we have developed a serum-free, scalable, and shippable cell-based model that faithfully predicts the potential for human liver injury. Such a resource has direct application in human modeling and, in the future, could play an important role in developing renewable cell-based therapies.

  16. PSSP-RFE: accurate prediction of protein structural class by recursive feature extraction from PSI-BLAST profile, physical-chemical property and functional annotations.

    PubMed

    Li, Liqi; Cui, Xiang; Yu, Sanjiu; Zhang, Yuan; Luo, Zhong; Yang, Hua; Zhou, Yue; Zheng, Xiaoqi

    2014-01-01

    Protein structure prediction is critical to functional annotation of the massively accumulated biological sequences, which prompts an imperative need for the development of high-throughput technologies. As a first and key step in protein structure prediction, protein structural class prediction becomes an increasingly challenging task. Amongst most homological-based approaches, the accuracies of protein structural class prediction are sufficiently high for high similarity datasets, but still far from being satisfactory for low similarity datasets, i.e., below 40% in pairwise sequence similarity. Therefore, we present a novel method for accurate and reliable protein structural class prediction for both high and low similarity datasets. This method is based on Support Vector Machine (SVM) in conjunction with integrated features from position-specific score matrix (PSSM), PROFEAT and Gene Ontology (GO). A feature selection approach, SVM-RFE, is also used to rank the integrated feature vectors through recursively removing the feature with the lowest ranking score. The definitive top features selected by SVM-RFE are input into the SVM engines to predict the structural class of a query protein. To validate our method, jackknife tests were applied to seven widely used benchmark datasets, reaching overall accuracies between 84.61% and 99.79%, which are significantly higher than those achieved by state-of-the-art tools. These results suggest that our method could serve as an accurate and cost-effective alternative to existing methods in protein structural classification, especially for low similarity datasets.

  17. Does preoperative cross-sectional imaging accurately predict main duct involvement in intraductal papillary mucinous neoplasm?

    PubMed

    Barron, M R; Roch, A M; Waters, J A; Parikh, J A; DeWitt, J M; Al-Haddad, M A; Ceppa, E P; House, M G; Zyromski, N J; Nakeeb, A; Pitt, H A; Schmidt, C Max

    2014-03-01

    Main pancreatic duct (MPD) involvement is a well-demonstrated risk factor for malignancy in intraductal papillary mucinous neoplasm (IPMN). Preoperative radiographic determination of IPMN type is heavily relied upon in oncologic risk stratification. We hypothesized that radiographic assessment of MPD involvement in IPMN is an accurate predictor of pathological MPD involvement. Data regarding all patients undergoing resection for IPMN at a single academic institution between 1992 and 2012 were gathered prospectively. Retrospective analysis of imaging and pathologic data was undertaken. Preoperative classification of IPMN type was based on cross-sectional imaging (MRI/magnetic resonance cholangiopancreatography (MRCP) and/or CT). Three hundred sixty-two patients underwent resection for IPMN. Of these, 334 had complete data for analysis. Of 164 suspected branch duct (BD) IPMN, 34 (20.7%) demonstrated MPD involvement on final pathology. Of 170 patients with suspicion of MPD involvement, 50 (29.4%) demonstrated no MPD involvement. Of 34 patients with suspected BD-IPMN who were found to have MPD involvement on pathology, 10 (29.4%) had invasive carcinoma. Alternatively, 2/50 (4%) of the patients with suspected MPD involvement who ultimately had isolated BD-IPMN demonstrated invasive carcinoma. Preoperative radiographic IPMN type did not correlate with final pathology in 25% of the patients. In addition, risk of invasive carcinoma correlates with pathologic presence of MPD involvement.

  18. Computational methods toward accurate RNA structure prediction using coarse-grained and all-atom models.

    PubMed

    Krokhotin, Andrey; Dokholyan, Nikolay V

    2015-01-01

    Computational methods can provide significant insights into RNA structure and dynamics, bridging the gap in our understanding of the relationship between structure and biological function. Simulations enrich and enhance our understanding of data derived on the bench, as well as provide feasible alternatives to costly or technically challenging experiments. Coarse-grained computational models of RNA are especially important in this regard, as they allow analysis of events occurring in timescales relevant to RNA biological function, which are inaccessible through experimental methods alone. We have developed a three-bead coarse-grained model of RNA for discrete molecular dynamics simulations. This model is efficient in de novo prediction of short RNA tertiary structure, starting from RNA primary sequences of less than 50 nucleotides. To complement this model, we have incorporated additional base-pairing constraints and have developed a bias potential reliant on data obtained from hydroxyl probing experiments that guide RNA folding to its correct state. By introducing experimentally derived constraints to our computer simulations, we are able to make reliable predictions of RNA tertiary structures up to a few hundred nucleotides. Our refined model exemplifies a valuable benefit achieved through integration of computation and experimental methods.

  19. A time accurate prediction of the viscous flow in a turbine stage including a rotor in motion

    NASA Astrophysics Data System (ADS)

    Shavalikul, Akamol

    In this current study, the flow field in the Pennsylvania State University Axial Flow Turbine Research Facility (AFTRF) was simulated. This study examined four sets of simulations. The first two sets are for an individual NGV and for an individual rotor. The last two sets use a multiple reference frames approach for a complete turbine stage with two different interface models: a steady circumferential average approach called a mixing plane model, and a time accurate flow simulation approach called a sliding mesh model. The NGV passage flow field was simulated using a three-dimensional Reynolds Averaged Navier-Stokes finite volume solver (RANS) with a standard kappa -- epsilon turbulence model. The mean flow distributions on the NGV surfaces and endwall surfaces were computed. The numerical solutions indicate that two passage vortices begin to be observed approximately at the mid axial chord of the NGV suction surface. The first vortex is a casing passage vortex which occurs at the corner formed by the NGV suction surface and the casing. This vortex is created by the interaction of the passage flow and the radially inward flow, while the second vortex, the hub passage vortex, is observed near the hub. These two vortices become stronger towards the NGV trailing edge. By comparing the results from the X/Cx = 1.025 plane and the X/Cx = 1.09 plane, it can be concluded that the NGV wake decays rapidly within a short axial distance downstream of the NGV. For the rotor, a set of simulations was carried out to examine the flow fields associated with different pressure side tip extension configurations, which are designed to reduce the tip leakage flow. The simulation results show that significant reductions in tip leakage mass flow rate and aerodynamic loss reduction are possible by using suitable tip platform extensions located near the pressure side corner of the blade tip. The computations used realistic turbine rotor inlet flow conditions in a linear cascade arrangement

  20. Simplified versus geometrically accurate models of forefoot anatomy to predict plantar pressures: A finite element study.

    PubMed

    Telfer, Scott; Erdemir, Ahmet; Woodburn, James; Cavanagh, Peter R

    2016-01-25

    Integration of patient-specific biomechanical measurements into the design of therapeutic footwear has been shown to improve clinical outcomes in patients with diabetic foot disease. The addition of numerical simulations intended to optimise intervention design may help to build on these advances, however at present the time and labour required to generate and run personalised models of foot anatomy restrict their routine clinical utility. In this study we developed second-generation personalised simple finite element (FE) models of the forefoot with varying geometric fidelities. Plantar pressure predictions from barefoot, shod, and shod with insole simulations using simplified models were compared to those obtained from CT-based FE models incorporating more detailed representations of bone and tissue geometry. A simplified model including representations of metatarsals based on simple geometric shapes, embedded within a contoured soft tissue block with outer geometry acquired from a 3D surface scan was found to provide pressure predictions closest to the more complex model, with mean differences of 13.3kPa (SD 13.4), 12.52kPa (SD 11.9) and 9.6kPa (SD 9.3) for barefoot, shod, and insole conditions respectively. The simplified model design could be produced in <1h compared to >3h in the case of the more detailed model, and solved on average 24% faster. FE models of the forefoot based on simplified geometric representations of the metatarsal bones and soft tissue surface geometry from 3D surface scans may potentially provide a simulation approach with improved clinical utility, however further validity testing around a range of therapeutic footwear types is required.

  1. Fast and accurate prediction for aerodynamic forces and moments acting on satellites flying in Low-Earth Orbit

    NASA Astrophysics Data System (ADS)

    Jin, Xuhon; Huang, Fei; Hu, Pengju; Cheng, Xiaoli

    2016-11-01

    A fundamental prerequisite for satellites operating in a Low Earth Orbit (LEO) is the availability of fast and accurate prediction of non-gravitational aerodynamic forces, which is characterised by the free molecular flow regime. However, conventional computational methods like the analytical integral method and direct simulation Monte Carlo (DSMC) technique are found failing to deal with flow shadowing and multiple reflections or computationally expensive. This work develops a general computer program for the accurate calculation of aerodynamic forces in the free molecular flow regime using the test particle Monte Carlo (TPMC) method, and non-gravitational aerodynamic forces actiong on the Gravity field and steady-state Ocean Circulation Explorer (GOCE) satellite is calculated for different freestream conditions and gas-surface interaction models by the computer program.

  2. Simplified risk score models accurately predict the risk of major in-hospital complications following percutaneous coronary intervention.

    PubMed

    Resnic, F S; Ohno-Machado, L; Selwyn, A; Simon, D I; Popma, J J

    2001-07-01

    The objectives of this analysis were to develop and validate simplified risk score models for predicting the risk of major in-hospital complications after percutaneous coronary intervention (PCI) in the era of widespread stenting and use of glycoprotein IIb/IIIa antagonists. We then sought to compare the performance of these simplified models with those of full logistic regression and neural network models. From January 1, 1997 to December 31, 1999, data were collected on 4,264 consecutive interventional procedures at a single center. Risk score models were derived from multiple logistic regression models using the first 2,804 cases and then validated on the final 1,460 cases. The area under the receiver operating characteristic (ROC) curve for the risk score model that predicted death was 0.86 compared with 0.85 for the multiple logistic model and 0.83 for the neural network model (validation set). For the combined end points of death, myocardial infarction, or bypass surgery, the corresponding areas under the ROC curves were 0.74, 0.78, and 0.81, respectively. Previously identified risk factors were confirmed in this analysis. The use of stents was associated with a decreased risk of in-hospital complications. Thus, risk score models can accurately predict the risk of major in-hospital complications after PCI. Their discriminatory power is comparable to those of logistic models and neural network models. Accurate bedside risk stratification may be achieved with these simple models.

  3. Searching for Computational Strategies to Accurately Predict pKas of Large Phenolic Derivatives.

    PubMed

    Rebollar-Zepeda, Aida Mariana; Campos-Hernández, Tania; Ramírez-Silva, María Teresa; Rojas-Hernández, Alberto; Galano, Annia

    2011-08-09

    Twenty-two reaction schemes have been tested, within the cluster-continuum model including up to seven explicit water molecules. They have been used in conjunction with nine different methods, within the density functional theory and with second-order Møller-Plesset. The quality of the pKa predictions was found to be strongly dependent on the chosen scheme, while only moderately influenced by the method of calculation. We recommend the E1 reaction scheme [HA + OH(-) (3H2O) ↔ A(-) (H2O) + 3H2O], since it yields mean unsigned errors (MUE) lower than 1 unit of pKa for most of the tested functionals. The best pKa values obtained from this reaction scheme are those involving calculations with PBE0 (MUE = 0.77), TPSS (MUE = 0.82), BHandHLYP (MUE = 0.82), and B3LYP (MUE = 0.86) functionals. This scheme has the additional advantage, compared to the proton exchange method, which also gives very small values of MUE, of being experiment independent. It should be kept in mind, however, that these recommendations are valid within the cluster-continuum model, using the polarizable continuum model in conjunction with the united atom Hartree-Fock cavity and the strategy based on thermodynamic cycles. Changes in any of these aspects of the used methodology may lead to different outcomes.

  4. Deformation, Failure, and Fatigue Life of SiC/Ti-15-3 Laminates Accurately Predicted by MAC/GMC

    NASA Technical Reports Server (NTRS)

    Bednarcyk, Brett A.; Arnold, Steven M.

    2002-01-01

    NASA Glenn Research Center's Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) (ref.1) has been extended to enable fully coupled macro-micro deformation, failure, and fatigue life predictions for advanced metal matrix, ceramic matrix, and polymer matrix composites. Because of the multiaxial nature of the code's underlying micromechanics model, GMC--which allows the incorporation of complex local inelastic constitutive models--MAC/GMC finds its most important application in metal matrix composites, like the SiC/Ti-15-3 composite examined here. Furthermore, since GMC predicts the microscale fields within each constituent of the composite material, submodels for local effects such as fiber breakage, interfacial debonding, and matrix fatigue damage can and have been built into MAC/GMC. The present application of MAC/GMC highlights the combination of these features, which has enabled the accurate modeling of the deformation, failure, and life of titanium matrix composites.

  5. How accurately can subject-specific finite element models predict strains and strength of human femora? Investigation using full-field measurements.

    PubMed

    Grassi, Lorenzo; Väänänen, Sami P; Ristinmaa, Matti; Jurvelin, Jukka S; Isaksson, Hanna

    2016-03-21

    Subject-specific finite element models have been proposed as a tool to improve fracture risk assessment in individuals. A thorough laboratory validation against experimental data is required before introducing such models in clinical practice. Results from digital image correlation can provide full-field strain distribution over the specimen surface during in vitro test, instead of at a few pre-defined locations as with strain gauges. The aim of this study was to validate finite element models of human femora against experimental data from three cadaver femora, both in terms of femoral strength and of the full-field strain distribution collected with digital image correlation. The results showed a high accuracy between predicted and measured principal strains (R(2)=0.93, RMSE=10%, 1600 validated data points per specimen). Femoral strength was predicted using a rate dependent material model with specific strain limit values for yield and failure. This provided an accurate prediction (<2% error) for two out of three specimens. In the third specimen, an accidental change in the boundary conditions occurred during the experiment, which compromised the femoral strength validation. The achieved strain accuracy was comparable to that obtained in state-of-the-art studies which validated their prediction accuracy against 10-16 strain gauge measurements. Fracture force was accurately predicted, with the predicted failure location being very close to the experimental fracture rim. Despite the low sample size and the single loading condition tested, the present combined numerical-experimental method showed that finite element models can predict femoral strength by providing a thorough description of the local bone mechanical response.

  6. SnowyOwl: accurate prediction of fungal genes by using RNA-Seq and homology information to select among ab initio models

    PubMed Central

    2014-01-01

    Background Locating the protein-coding genes in novel genomes is essential to understanding and exploiting the genomic information but it is still difficult to accurately predict all the genes. The recent availability of detailed information about transcript structure from high-throughput sequencing of messenger RNA (RNA-Seq) delineates many expressed genes and promises increased accuracy in gene prediction. Computational gene predictors have been intensively developed for and tested in well-studied animal genomes. Hundreds of fungal genomes are now or will soon be sequenced. The differences of fungal genomes from animal genomes and the phylogenetic sparsity of well-studied fungi call for gene-prediction tools tailored to them. Results SnowyOwl is a new gene prediction pipeline that uses RNA-Seq data to train and provide hints for the generation of Hidden Markov Model (HMM)-based gene predictions and to evaluate the resulting models. The pipeline has been developed and streamlined by comparing its predictions to manually curated gene models in three fungal genomes and validated against the high-quality gene annotation of Neurospora crassa; SnowyOwl predicted N. crassa genes with 83% sensitivity and 65% specificity. SnowyOwl gains sensitivity by repeatedly running the HMM gene predictor Augustus with varied input parameters and selectivity by choosing the models with best homology to known proteins and best agreement with the RNA-Seq data. Conclusions SnowyOwl efficiently uses RNA-Seq data to produce accurate gene models in both well-studied and novel fungal genomes. The source code for the SnowyOwl pipeline (in Python) and a web interface (in PHP) is freely available from http://sourceforge.net/projects/snowyowl/. PMID:24980894

  7. Easy-to-use, general, and accurate multi-Kinect calibration and its application to gait monitoring for fall prediction.

    PubMed

    Staranowicz, Aaron N; Ray, Christopher; Mariottini, Gian-Luca

    2015-01-01

    Falls are the most-common causes of unintentional injury and death in older adults. Many clinics, hospitals, and health-care providers are urgently seeking accurate, low-cost, and easy-to-use technology to predict falls before they happen, e.g., by monitoring the human walking pattern (or "gait"). Despite the wide popularity of Microsoft's Kinect and the plethora of solutions for gait monitoring, no strategy has been proposed to date to allow non-expert users to calibrate the cameras, which is essential to accurately fuse the body motion observed by each camera in a single frame of reference. In this paper, we present a novel multi-Kinect calibration algorithm that has advanced features when compared to existing methods: 1) is easy to use, 2) it can be used in any generic Kinect arrangement, and 3) it provides accurate calibration. Extensive real-world experiments have been conducted to validate our algorithm and to compare its performance against other multi-Kinect calibration approaches, especially to show the improved estimate of gait parameters. Finally, a MATLAB Toolbox has been made publicly available for the entire research community.

  8. Prediction of unsteady loads on maneuvering delta wings using time-accurate Euler schemes

    NASA Technical Reports Server (NTRS)

    Kandil, Osama A.; Chuang, H. Andrew

    1988-01-01

    Three-dimensional steady and unsteady vortex-dominated flows around sharp-edged delta wings are considered in this paper. The problem is formulated by using the unsteady conservative Euler equations for the flow relative motion with respect to a moving frame of reference. An implicit approximately-factored finite volume scheme is used to solve the resulting equations on a three-dimensional computational grid which is generated by using a modified Joukowski transformation in cross-flow planes at the grid chord stations. The scheme is applied to a delta wing undergoing pitching oscillation around a large angle of attack. The initial conditions correspond to a steady flow around a delta wing of aspect ratio of one, freestream Mach number of 0.3 and mean angle of attack of 20.5. The steady flow results are compared with those of an explicit computational scheme and the experimental data, and they are in good agreement.

  9. Accurate Prediction of the Statistics of Repetitions in Random Sequences: A Case Study in Archaea Genomes

    PubMed Central

    Régnier, Mireille; Chassignet, Philippe

    2016-01-01

    Repetitive patterns in genomic sequences have a great biological significance and also algorithmic implications. Analytic combinatorics allow to derive formula for the expected length of repetitions in a random sequence. Asymptotic results, which generalize previous works on a binary alphabet, are easily computable. Simulations on random sequences show their accuracy. As an application, the sample case of Archaea genomes illustrates how biological sequences may differ from random sequences. PMID:27376057

  10. The Dirac equation in electronic structure calculations: Accurate evaluation of DFT predictions for actinides

    SciTech Connect

    Wills, John M; Mattsson, Ann E

    2012-06-06

    Brooks, Johansson, and Skriver, using the LMTO-ASA method and considerable insight, were able to explain many of the ground state properties of the actinides. In the many years since this work was done, electronic structure calculations of increasing sophistication have been applied to actinide elements and compounds, attempting to quantify the applicability of DFT to actinides and actinide compounds and to try to incorporate other methodologies (i.e. DMFT) into DFT calculations. Through these calculations, the limits of both available density functionals and ad hoc methodologies are starting to become clear. However, it has also become clear that approximations used to incorporate relativity are not adequate to provide rigorous tests of the underlying equations of DFT, not to mention ad hoc additions. In this talk, we describe the result of full-potential LMTO calculations for the elemental actinides, comparing results obtained with a full Dirac basis with those obtained from scalar-relativistic bases, with and without variational spin-orbit. This comparison shows that the scalar relativistic treatment of actinides does not have sufficient accuracy to provide a rigorous test of theory and that variational spin-orbit introduces uncontrolled errors in the results of electronic structure calculations on actinide elements.

  11. Shrinking the Psoriasis Assessment Gap: Early Gene-Expression Profiling Accurately Predicts Response to Long-Term Treatment.

    PubMed

    Correa da Rosa, Joel; Kim, Jaehwan; Tian, Suyan; Tomalin, Lewis E; Krueger, James G; Suárez-Fariñas, Mayte

    2017-02-01

    There is an "assessment gap" between the moment a patient's response to treatment is biologically determined and when a response can actually be determined clinically. Patients' biochemical profiles are a major determinant of clinical outcome for a given treatment. It is therefore feasible that molecular-level patient information could be used to decrease the assessment gap. Thanks to clinically accessible biopsy samples, high-quality molecular data for psoriasis patients are widely available. Psoriasis is therefore an excellent disease for testing the prospect of predicting treatment outcome from molecular data. Our study shows that gene-expression profiles of psoriasis skin lesions, taken in the first 4 weeks of treatment, can be used to accurately predict (>80% area under the receiver operating characteristic curve) the clinical endpoint at 12 weeks. This could decrease the psoriasis assessment gap by 2 months. We present two distinct prediction modes: a universal predictor, aimed at forecasting the efficacy of untested drugs, and specific predictors aimed at forecasting clinical response to treatment with four specific drugs: etanercept, ustekinumab, adalimumab, and methotrexate. We also develop two forms of prediction: one from detailed, platform-specific data and one from platform-independent, pathway-based data. We show that key biomarkers are associated with responses to drugs and doses and thus provide insight into the biology of pathogenesis reversion.

  12. A stationary wavelet entropy-based clustering approach accurately predicts gene expression.

    PubMed

    Nguyen, Nha; Vo, An; Choi, Inchan; Won, Kyoung-Jae

    2015-03-01

    Studying epigenetic landscapes is important to understand the condition for gene regulation. Clustering is a useful approach to study epigenetic landscapes by grouping genes based on their epigenetic conditions. However, classical clustering approaches that often use a representative value of the signals in a fixed-sized window do not fully use the information written in the epigenetic landscapes. Clustering approaches to maximize the information of the epigenetic signals are necessary for better understanding gene regulatory environments. For effective clustering of multidimensional epigenetic signals, we developed a method called Dewer, which uses the entropy of stationary wavelet of epigenetic signals inside enriched regions for gene clustering. Interestingly, the gene expression levels were highly correlated with the entropy levels of epigenetic signals. Dewer separates genes better than a window-based approach in the assessment using gene expression and achieved a correlation coefficient above 0.9 without using any training procedure. Our results show that the changes of the epigenetic signals are useful to study gene regulation.

  13. NIBBS-search for fast and accurate prediction of phenotype-biased metabolic systems.

    PubMed

    Schmidt, Matthew C; Rocha, Andrea M; Padmanabhan, Kanchana; Shpanskaya, Yekaterina; Banfield, Jill; Scott, Kathleen; Mihelcic, James R; Samatova, Nagiza F

    2012-01-01

    Understanding of genotype-phenotype associations is important not only for furthering our knowledge on internal cellular processes, but also essential for providing the foundation necessary for genetic engineering of microorganisms for industrial use (e.g., production of bioenergy or biofuels). However, genotype-phenotype associations alone do not provide enough information to alter an organism's genome to either suppress or exhibit a phenotype. It is important to look at the phenotype-related genes in the context of the genome-scale network to understand how the genes interact with other genes in the organism. Identification of metabolic subsystems involved in the expression of the phenotype is one way of placing the phenotype-related genes in the context of the entire network. A metabolic system refers to a metabolic network subgraph; nodes are compounds and edges labels are the enzymes that catalyze the reaction. The metabolic subsystem could be part of a single metabolic pathway or span parts of multiple pathways. Arguably, comparative genome-scale metabolic network analysis is a promising strategy to identify these phenotype-related metabolic subsystems. Network Instance-Based Biased Subgraph Search (NIBBS) is a graph-theoretic method for genome-scale metabolic network comparative analysis that can identify metabolic systems that are statistically biased toward phenotype-expressing organismal networks. We set up experiments with target phenotypes like hydrogen production, TCA expression, and acid-tolerance. We show via extensive literature search that some of the resulting metabolic subsystems are indeed phenotype-related and formulate hypotheses for other systems in terms of their role in phenotype expression. NIBBS is also orders of magnitude faster than MULE, one of the most efficient maximal frequent subgraph mining algorithms that could be adjusted for this problem. Also, the set of phenotype-biased metabolic systems output by NIBBS comes very close to

  14. Population Synthesis in the Blue. IV. Accurate Model Predictions for Lick Indices and UBV Colors in Single Stellar Populations

    NASA Astrophysics Data System (ADS)

    Schiavon, Ricardo P.

    2007-07-01

    We present a new set of model predictions for 16 Lick absorption line indices from Hδ through Fe5335 and UBV colors for single stellar populations with ages ranging between 1 and 15 Gyr, [Fe/H] ranging from -1.3 to +0.3, and variable abundance ratios. The models are based on accurate stellar parameters for the Jones library stars and a new set of fitting functions describing the behavior of line indices as a function of effective temperature, surface gravity, and iron abundance. The abundances of several key elements in the library stars have been obtained from the literature in order to characterize the abundance pattern of the stellar library, thus allowing us to produce model predictions for any set of abundance ratios desired. We develop a method to estimate mean ages and abundances of iron, carbon, nitrogen, magnesium, and calcium that explores the sensitivity of the various indices modeled to those parameters. The models are compared to high-S/N data for Galactic clusters spanning the range of ages, metallicities, and abundance patterns of interest. Essentially all line indices are matched when the known cluster parameters are adopted as input. Comparing the models to high-quality data for galaxies in the nearby universe, we reproduce previous results regarding the enhancement of light elements and the spread in the mean luminosity-weighted ages of early-type galaxies. When the results from the analysis of blue and red indices are contrasted, we find good consistency in the [Fe/H] that is inferred from different Fe indices. Applying our method to estimate mean ages and abundances from stacked SDSS spectra of early-type galaxies brighter than L*, we find mean luminosity-weighed ages of the order of ~8 Gyr and iron abundances slightly below solar. Abundance ratios, [X/Fe], tend to be higher than solar and are positively correlated with galaxy luminosity. Of all elements, nitrogen is the more strongly correlated with galaxy luminosity, which seems to indicate

  15. Accurate prediction of polarised high order electrostatic interactions for hydrogen bonded complexes using the machine learning method kriging

    NASA Astrophysics Data System (ADS)

    Hughes, Timothy J.; Kandathil, Shaun M.; Popelier, Paul L. A.

    2015-02-01

    As intermolecular interactions such as the hydrogen bond are electrostatic in origin, rigorous treatment of this term within force field methodologies should be mandatory. We present a method able of accurately reproducing such interactions for seven van der Waals complexes. It uses atomic multipole moments up to hexadecupole moment mapped to the positions of the nuclear coordinates by the machine learning method kriging. Models were built at three levels of theory: HF/6-31G**, B3LYP/aug-cc-pVDZ and M06-2X/aug-cc-pVDZ. The quality of the kriging models was measured by their ability to predict the electrostatic interaction energy between atoms in external test examples for which the true energies are known. At all levels of theory, >90% of test cases for small van der Waals complexes were predicted within 1 kJ mol-1, decreasing to 60-70% of test cases for larger base pair complexes. Models built on moments obtained at B3LYP and M06-2X level generally outperformed those at HF level. For all systems the individual interactions were predicted with a mean unsigned error of less than 1 kJ mol-1.

  16. Accurate prediction of polarised high order electrostatic interactions for hydrogen bonded complexes using the machine learning method kriging.

    PubMed

    Hughes, Timothy J; Kandathil, Shaun M; Popelier, Paul L A

    2015-02-05

    As intermolecular interactions such as the hydrogen bond are electrostatic in origin, rigorous treatment of this term within force field methodologies should be mandatory. We present a method able of accurately reproducing such interactions for seven van der Waals complexes. It uses atomic multipole moments up to hexadecupole moment mapped to the positions of the nuclear coordinates by the machine learning method kriging. Models were built at three levels of theory: HF/6-31G(**), B3LYP/aug-cc-pVDZ and M06-2X/aug-cc-pVDZ. The quality of the kriging models was measured by their ability to predict the electrostatic interaction energy between atoms in external test examples for which the true energies are known. At all levels of theory, >90% of test cases for small van der Waals complexes were predicted within 1 kJ mol(-1), decreasing to 60-70% of test cases for larger base pair complexes. Models built on moments obtained at B3LYP and M06-2X level generally outperformed those at HF level. For all systems the individual interactions were predicted with a mean unsigned error of less than 1 kJ mol(-1).

  17. Predictions for diffraction at the LHC compared to experimental results

    NASA Astrophysics Data System (ADS)

    Goulianos, Konstantin

    2014-04-01

    Diffractive proton-proton cross sections at the LHC, as well as the total and total-inelastic proton-proton cross sections, are predicted in a simple model obeying all unitarity constraints. The model has been implemented in the PYTHIA8-MBR event generator for single diffraction, double diffraction, and central diffraction processes. Predictions of the model are compared to recent LHC results.

  18. Accurate and computationally efficient prediction of thermochemical properties of biomolecules using the generalized connectivity-based hierarchy.

    PubMed

    Sengupta, Arkajyoti; Ramabhadran, Raghunath O; Raghavachari, Krishnan

    2014-08-14

    In this study we have used the connectivity-based hierarchy (CBH) method to derive accurate heats of formation of a range of biomolecules, 18 amino acids and 10 barbituric acid/uracil derivatives. The hierarchy is based on the connectivity of the different atoms in a large molecule. It results in error-cancellation reaction schemes that are automated, general, and can be readily used for a broad range of organic molecules and biomolecules. Herein, we first locate stable conformational and tautomeric forms of these biomolecules using an accurate level of theory (viz. CCSD(T)/6-311++G(3df,2p)). Subsequently, the heats of formation of the amino acids are evaluated using the CBH-1 and CBH-2 schemes and routinely employed density functionals or wave function-based methods. The calculated heats of formation obtained herein using modest levels of theory and are in very good agreement with those obtained using more expensive W1-F12 and W2-F12 methods on amino acids and G3 results on barbituric acid derivatives. Overall, the present study (a) highlights the small effect of including multiple conformers in determining the heats of formation of biomolecules and (b) in concurrence with previous CBH studies, proves that use of the more effective error-cancelling isoatomic scheme (CBH-2) results in more accurate heats of formation with modestly sized basis sets along with common density functionals or wave function-based methods.

  19. A novel fibrosis index comprising a non-cholesterol sterol accurately predicts HCV-related liver cirrhosis.

    PubMed

    Ydreborg, Magdalena; Lisovskaja, Vera; Lagging, Martin; Brehm Christensen, Peer; Langeland, Nina; Buhl, Mads Rauning; Pedersen, Court; Mørch, Kristine; Wejstål, Rune; Norkrans, Gunnar; Lindh, Magnus; Färkkilä, Martti; Westin, Johan

    2014-01-01

    Diagnosis of liver cirrhosis is essential in the management of chronic hepatitis C virus (HCV) infection. Liver biopsy is invasive and thus entails a risk of complications as well as a potential risk of sampling error. Therefore, non-invasive diagnostic tools are preferential. The aim of the present study was to create a model for accurate prediction of liver cirrhosis based on patient characteristics and biomarkers of liver fibrosis, including a panel of non-cholesterol sterols reflecting cholesterol synthesis and absorption and secretion. We evaluated variables with potential predictive significance for liver fibrosis in 278 patients originally included in a multicenter phase III treatment trial for chronic HCV infection. A stepwise multivariate logistic model selection was performed with liver cirrhosis, defined as Ishak fibrosis stage 5-6, as the outcome variable. A new index, referred to as Nordic Liver Index (NoLI) in the paper, was based on the model: Log-odds (predicting cirrhosis) = -12.17+ (age × 0.11) + (BMI (kg/m(2)) × 0.23) + (D7-lathosterol (μg/100 mg cholesterol)×(-0.013)) + (Platelet count (x10(9)/L) × (-0.018)) + (Prothrombin-INR × 3.69). The area under the ROC curve (AUROC) for prediction of cirrhosis was 0.91 (95% CI 0.86-0.96). The index was validated in a separate cohort of 83 patients and the AUROC for this cohort was similar (0.90; 95% CI: 0.82-0.98). In conclusion, the new index may complement other methods in diagnosing cirrhosis in patients with chronic HCV infection.

  20. Experimental results of a predictive neural network HVAC controller

    SciTech Connect

    Jeannette, E.; Assawamartbunlue, K.; Kreider, J.F.; Curtiss, P.S.

    1998-12-31

    Proportional, integral, and derivative (PID) control is widely used in many HVAC control processes and requires constant attention for optimal control. Artificial neural networks offer the potential for improved control of processes through predictive techniques. This paper introduces and shows experimental results of a predictive neural network (PNN) controller applied to an unstable hot water system in an air-handling unit. Actual laboratory testing of the PNN and PID controllers show favorable results for the PNN controller.

  1. Estimating the state of a geophysical system with sparse observations: time delay methods to achieve accurate initial states for prediction

    NASA Astrophysics Data System (ADS)

    An, Zhe; Rey, Daniel; Ye, Jingxin; Abarbanel, Henry D. I.

    2017-01-01

    The problem of forecasting the behavior of a complex dynamical system through analysis of observational time-series data becomes difficult when the system expresses chaotic behavior and the measurements are sparse, in both space and/or time. Despite the fact that this situation is quite typical across many fields, including numerical weather prediction, the issue of whether the available observations are "sufficient" for generating successful forecasts is still not well understood. An analysis by Whartenby et al. (2013) found that in the context of the nonlinear shallow water equations on a β plane, standard nudging techniques require observing approximately 70 % of the full set of state variables. Here we examine the same system using a method introduced by Rey et al. (2014a), which generalizes standard nudging methods to utilize time delayed measurements. We show that in certain circumstances, it provides a sizable reduction in the number of observations required to construct accurate estimates and high-quality predictions. In particular, we find that this estimate of 70 % can be reduced to about 33 % using time delays, and even further if Lagrangian drifter locations are also used as measurements.

  2. Accurate X-Ray Spectral Predictions: An Advanced Self-Consistent-Field Approach Inspired by Many-Body Perturbation Theory

    NASA Astrophysics Data System (ADS)

    Liang, Yufeng; Vinson, John; Pemmaraju, Sri; Drisdell, Walter S.; Shirley, Eric L.; Prendergast, David

    2017-03-01

    Constrained-occupancy delta-self-consistent-field (Δ SCF ) methods and many-body perturbation theories (MBPT) are two strategies for obtaining electronic excitations from first principles. Using the two distinct approaches, we study the O 1 s core excitations that have become increasingly important for characterizing transition-metal oxides and understanding strong electronic correlation. The Δ SCF approach, in its current single-particle form, systematically underestimates the pre-edge intensity for chosen oxides, despite its success in weakly correlated systems. By contrast, the Bethe-Salpeter equation within MBPT predicts much better line shapes. This motivates one to reexamine the many-electron dynamics of x-ray excitations. We find that the single-particle Δ SCF approach can be rectified by explicitly calculating many-electron transition amplitudes, producing x-ray spectra in excellent agreement with experiments. This study paves the way to accurately predict x-ray near-edge spectral fingerprints for physics and materials science beyond the Bethe-Salpether equation.

  3. Recent Results on the Accurate Measurements of the Dielectric Constant of Seawater at 1.413GHZ

    NASA Technical Reports Server (NTRS)

    Lang, R.H.; Tarkocin, Y.; Utku, C.; Le Vine, D.M.

    2008-01-01

    Measurements of the complex. dielectric constant of seawater at 30.00 psu, 35.00 psu and 38.27 psu over the temperature range from 5 C to 3 5 at 1.413 GHz are given and compared with the Klein-Swift results. A resonant cavity technique is used. The calibration constant used in the cavity perturbation formulas is determined experimentally using methanol and ethanediol (ethylene glycol) as reference liquids. Analysis of the data shows that the measurements are accurate to better than 1.0% in almost all cases studied.

  4. An Accurate GPS-IMU/DR Data Fusion Method for Driverless Car Based on a Set of Predictive Models and Grid Constraints.

    PubMed

    Wang, Shiyao; Deng, Zhidong; Yin, Gang

    2016-02-24

    A high-performance differential global positioning system (GPS)  receiver with real time kinematics provides absolute localization for driverless cars. However, it is not only susceptible to multipath effect but also unable to effectively fulfill precise error correction in a wide range of driving areas. This paper proposes an accurate GPS-inertial measurement unit (IMU)/dead reckoning (DR) data fusion method based on a set of predictive models and occupancy grid constraints. First, we employ a set of autoregressive and moving average (ARMA) equations that have different structural parameters to build maximum likelihood models of raw navigation. Second, both grid constraints and spatial consensus checks on all predictive results and current measurements are required to have removal of outliers. Navigation data that satisfy stationary stochastic process are further fused to achieve accurate localization results. Third, the standard deviation of multimodal data fusion can be pre-specified by grid size. Finally, we perform a lot of field tests on a diversity of real urban scenarios. The experimental results demonstrate that the method can significantly smooth small jumps in bias and considerably reduce accumulated position errors due to DR. With low computational complexity, the position accuracy of our method surpasses existing state-of-the-arts on the same dataset and the new data fusion method is practically applied in our driverless car.

  5. An Accurate GPS-IMU/DR Data Fusion Method for Driverless Car Based on a Set of Predictive Models and Grid Constraints

    PubMed Central

    Wang, Shiyao; Deng, Zhidong; Yin, Gang

    2016-01-01

    A high-performance differential global positioning system (GPS)  receiver with real time kinematics provides absolute localization for driverless cars. However, it is not only susceptible to multipath effect but also unable to effectively fulfill precise error correction in a wide range of driving areas. This paper proposes an accurate GPS–inertial measurement unit (IMU)/dead reckoning (DR) data fusion method based on a set of predictive models and occupancy grid constraints. First, we employ a set of autoregressive and moving average (ARMA) equations that have different structural parameters to build maximum likelihood models of raw navigation. Second, both grid constraints and spatial consensus checks on all predictive results and current measurements are required to have removal of outliers. Navigation data that satisfy stationary stochastic process are further fused to achieve accurate localization results. Third, the standard deviation of multimodal data fusion can be pre-specified by grid size. Finally, we perform a lot of field tests on a diversity of real urban scenarios. The experimental results demonstrate that the method can significantly smooth small jumps in bias and considerably reduce accumulated position errors due to DR. With low computational complexity, the position accuracy of our method surpasses existing state-of-the-arts on the same dataset and the new data fusion method is practically applied in our driverless car. PMID:26927108

  6. Integrating metabolic performance, thermal tolerance, and plasticity enables for more accurate predictions on species vulnerability to acute and chronic effects of global warming.

    PubMed

    Magozzi, Sarah; Calosi, Piero

    2015-01-01

    Predicting species vulnerability to global warming requires a comprehensive, mechanistic understanding of sublethal and lethal thermal tolerances. To date, however, most studies investigating species physiological responses to increasing temperature have focused on the underlying physiological traits of either acute or chronic tolerance in isolation. Here we propose an integrative, synthetic approach including the investigation of multiple physiological traits (metabolic performance and thermal tolerance), and their plasticity, to provide more accurate and balanced predictions on species and assemblage vulnerability to both acute and chronic effects of global warming. We applied this approach to more accurately elucidate relative species vulnerability to warming within an assemblage of six caridean prawns occurring in the same geographic, hence macroclimatic, region, but living in different thermal habitats. Prawns were exposed to four incubation temperatures (10, 15, 20 and 25 °C) for 7 days, their metabolic rates and upper thermal limits were measured, and plasticity was calculated according to the concept of Reaction Norms, as well as Q10 for metabolism. Compared to species occupying narrower/more stable thermal niches, species inhabiting broader/more variable thermal environments (including the invasive Palaemon macrodactylus) are likely to be less vulnerable to extreme acute thermal events as a result of their higher upper thermal limits. Nevertheless, they may be at greater risk from chronic exposure to warming due to the greater metabolic costs they incur. Indeed, a trade-off between acute and chronic tolerance was apparent in the assemblage investigated. However, the invasive species P. macrodactylus represents an exception to this pattern, showing elevated thermal limits and plasticity of these limits, as well as a high metabolic control. In general, integrating multiple proxies for species physiological acute and chronic responses to increasing

  7. Accurate Predictions of Mean Geomagnetic Dipole Excursion and Reversal Frequencies, Mean Paleomagnetic Field Intensity, and the Radius of Earth's Core Using McLeod's Rule

    NASA Technical Reports Server (NTRS)

    Voorhies, Coerte V.; Conrad, Joy

    1996-01-01

    The geomagnetic spatial power spectrum R(sub n)(r) is the mean square magnetic induction represented by degree n spherical harmonic coefficients of the internal scalar potential averaged over the geocentric sphere of radius r. McLeod's Rule for the magnetic field generated by Earth's core geodynamo says that the expected core surface power spectrum (R(sub nc)(c)) is inversely proportional to (2n + 1) for 1 less than n less than or equal to N(sub E). McLeod's Rule is verified by locating Earth's core with main field models of Magsat data; the estimated core radius of 3485 kn is close to the seismologic value for c of 3480 km. McLeod's Rule and similar forms are then calibrated with the model values of R(sub n) for 3 less than or = n less than or = 12. Extrapolation to the degree 1 dipole predicts the expectation value of Earth's dipole moment to be about 5.89 x 10(exp 22) Am(exp 2)rms (74.5% of the 1980 value) and the expected geomagnetic intensity to be about 35.6 (mu)T rms at Earth's surface. Archeo- and paleomagnetic field intensity data show these and related predictions to be reasonably accurate. The probability distribution chi(exp 2) with 2n+1 degrees of freedom is assigned to (2n + 1)R(sub nc)/(R(sub nc). Extending this to the dipole implies that an exceptionally weak absolute dipole moment (less than or = 20% of the 1980 value) will exist during 2.5% of geologic time. The mean duration for such major geomagnetic dipole power excursions, one quarter of which feature durable axial dipole reversal, is estimated from the modern dipole power time-scale and the statistical model of excursions. The resulting mean excursion duration of 2767 years forces us to predict an average of 9.04 excursions per million years, 2.26 axial dipole reversals per million years, and a mean reversal duration of 5533 years. Paleomagnetic data show these predictions to be quite accurate. McLeod's Rule led to accurate predictions of Earth's core radius, mean paleomagnetic field

  8. Adsorption of lactate dehydrogenase enzyme on carbon nanotubes: how to get accurate results for the cytotoxicity of these nanomaterials.

    PubMed

    Forest, Valérie; Figarol, Agathe; Boudard, Delphine; Cottier, Michèle; Grosseau, Philippe; Pourchez, Jérémie

    2015-03-31

    Carbon nanotube (CNT) cytotoxicity is frequently investigated using in vitro classical toxicology assays. However, these cellular tests, usually based on the use of colorimetric or fluorimetric dyes, were designed for chemicals and may not be suitable for nanosized materials. Indeed, because of their unique physicochemical properties CNT can interfere with the assays and bias the results. To get accurate data and draw reliable conclusions, these artifacts should be carefully taken into account. The aim of this study was to evaluate qualitatively and quantitatively the interferences occurring between CNT and the commonly used lactate dehydrogenase (LDH) assay. Experiments under cell-free conditions were performed, and it was clearly demonstrated that artifacts occurred. They were due to the intrinsic absorbance of CNT on one hand and the adsorption of LDH at the CNT surface on the other hand. The adsorption of LDH on CNT was modeled and was found to fit the Langmuir model. The K(ads) and n(eq) constants were defined, allowing the correction of results obtained from cellular experiments to get more accurate data and lead to proper conclusions on the cytotoxicity of CNT.

  9. Can the conventional sextant prostate biopsy accurately predict unilateral prostate cancer in low-risk, localized, prostate cancer?

    PubMed

    Mayes, Janice M; Mouraviev, Vladimir; Sun, Leon; Tsivian, Matvey; Madden, John F; Polascik, Thomas J

    2011-01-01

    We evaluate the reliability of routine sextant prostate biopsy to detect unilateral lesions. A total of 365 men with complete records including all clinical and pathologic variables who underwent a preoperative sextant biopsy and subsequent radical prostatectomy (RP) for clinically localized prostate cancer at our medical center between January 1996 and December 2006 were identified. When the sextant biopsy detects unilateral disease, according to RP results, the NPV is high (91%) with a low false negative rate (9%). However, the sextant biopsy has a PPV of 28% with a high false positive rate (72%). Therefore, a routine sextant prostate biopsy cannot provide reliable, accurate information about the unilaterality of tumor lesion(s).

  10. Attenuation of auditory N1 results from identity-specific action-effect prediction.

    PubMed

    Hughes, Gethin; Desantis, Andrea; Waszak, Florian

    2013-04-01

    The auditory N1 event-related potential has previously been observed to be attenuated for tones that are triggered by human actions. This attenuation is thought to be generated by motor prediction mechanisms and is considered to be important for agency attribution. The present study was designed to rigorously test the notion of action prediction-based sensory attenuation. Participants performed one of four voluntary actions on each trial, with each button associated with either predictable or unpredictable action effects. In addition, actions with each hand could result in action effects that were either congruent or incongruent with hand-specific prediction. We observed no significant differences in N1 amplitude between predictable and unpredictable tones. When contrasting action effects that were congruent or incongruent with hand-specific prediction, we observed significant attenuation for prediction-congruent compared to prediction-incongruent action-effects. These novel findings suggest that accurate action-effect prediction drives sensory attenuation of auditory stimuli. These findings have important implications for understanding the mechanisms of action-effect prediction and sensory attenuation, and may have clinical implications for studies investigating action awareness and agency in schizophrenia.

  11. Spatial agreement of predicted results in landslide susceptibility maps

    NASA Astrophysics Data System (ADS)

    Sterlacchini, Simone; Ballabio, Cristiano; Blahut, Jan; Masetti, Marco; Sorichetta, Alessandro

    2010-05-01

    Landslides occur worldwide in response to a broad variety of natural predisposing conditions and triggering factors that include heavy rainfalls, earthquakes, and human activity. Landslides constitute a serious source of danger causing environmental damage and substantial human and financial losses. At a regional scale, landslide susceptibility zonation constitutes the first effective step to achieve a thorough risk assessment and management and contribute to public safety. For this reason, the predicted susceptibility maps must be carefully analysed and critically reviewed before disseminating the results. The tuning of statistical techniques and the independent validation of the results are already recognized as fundamental steps in any natural hazard study to assess model accuracy and predictive power. Validation also may permit to establish the degree of confidence in the model and to compare results from different models. For this reason, the spatial agreement among susceptibility maps, produced by different models, should also be tested, especially if these models have similar prediction power. This is usually a rather common occurrence as it may happen that two or more maps with similar predictive power may not have the same agreement in term of predicted spatial patterns. This study is aimed at assessing the degree of spatial agreement among different patterns of predicted values in susceptibility maps with almost similar success and prediction rate curves and areas under curves (AUC). A data-driven Bayesian method (Weights of Evidence modelling technique) is applied and the output maps reclassified to compare the predicted results. A relative classification, based on the proportion of area classified as susceptible, is performed. Maps are investigated by Kappa Statistic, Principal Component Analysis, and Distance Weighted Entropy procedures. The results show great differences within the output spatial patterns of the predicted maps and also within the

  12. Accurate ab initio predictions of ionization energies and heats of formation for the 2-propyl, phenyl, and benzyl radicals

    NASA Astrophysics Data System (ADS)

    Lau, K.-C.; Ng, C. Y.

    2006-01-01

    The ionization energies (IEs) for the 2-propyl (2-C3H7), phenyl (C6H5), and benzyl (C6H5CH2) radicals have been calculated by the wave-function-based ab initio CCSD(T)/CBS approach, which involves the approximation to the complete basis set (CBS) limit at the coupled cluster level with single and double excitations plus quasiperturbative triple excitation [CCSD(T)]. The zero-point vibrational energy correction, the core-valence electronic correction, and the scalar relativistic effect correction have been also made in these calculations. Although a precise IE value for the 2-C3H7 radical has not been directly determined before due to the poor Franck-Condon factor for the photoionization transition at the ionization threshold, the experimental value deduced indirectly using other known energetic data is found to be in good accord with the present CCSD(T)/CBS prediction. The comparison between the predicted value through the focal-point analysis and the highly precise experimental value for the IE(C6H5CH2) determined in the previous pulsed field ionization photoelectron (PFI-PE) study shows that the CCSD(T)/CBS method is capable of providing an accurate IE prediction for C6H5CH2, achieving an error limit of 35 meV. The benchmarking of the CCSD(T)/CBS IE(C6H5CH2) prediction suggests that the CCSD(T)/CBS IE(C6H5) prediction obtained here has a similar accuracy of 35 meV. Taking into account this error limit for the CCSD(T)/CBS prediction and the experimental uncertainty, the CCSD(T)/CBS IE(C6H5) value is also consistent with the IE(C6H5) reported in the previous HeI photoelectron measurement. Furthermore, the present study provides support for the conclusion that the CCSD(T)/CBS approach with high-level energy corrections can be used to provide reliable IE predictions for C3-C7 hydrocarbon radicals with an uncertainty of +/-35 meV. Employing the atomization scheme, we have also computed the 0 K (298 K) heats of formation in kJ/mol at the CCSD(T)/CBS level for 2-C3H7

  13. Profile-QSAR: a novel meta-QSAR method that combines activities across the kinase family to accurately predict affinity, selectivity, and cellular activity.

    PubMed

    Martin, Eric; Mukherjee, Prasenjit; Sullivan, David; Jansen, Johanna

    2011-08-22

    Profile-QSAR is a novel 2D predictive model building method for kinases. This "meta-QSAR" method models the activity of each compound against a new kinase target as a linear combination of its predicted activities against a large panel of 92 previously studied kinases comprised from 115 assays. Profile-QSAR starts with a sparse incomplete kinase by compound (KxC) activity matrix, used to generate Bayesian QSAR models for the 92 "basis-set" kinases. These Bayesian QSARs generate a complete "synthetic" KxC activity matrix of predictions. These synthetic activities are used as "chemical descriptors" to train partial-least squares (PLS) models, from modest amounts of medium-throughput screening data, for predicting activity against new kinases. The Profile-QSAR predictions for the 92 kinases (115 assays) gave a median external R²(ext) = 0.59 on 25% held-out test sets. The method has proven accurate enough to predict pairwise kinase selectivities with a median correlation of R²(ext) = 0.61 for 958 kinase pairs with at least 600 common compounds. It has been further expanded by adding a "C(k)XC" cellular activity matrix to the KxC matrix to predict cellular activity for 42 kinase driven cellular assays with median R²(ext) = 0.58 for 24 target modulation assays and R²(ext) = 0.41 for 18 cell proliferation assays. The 2D Profile-QSAR, along with the 3D Surrogate AutoShim, are the foundations of an internally developed iterative medium-throughput screening (IMTS) methodology for virtual screening (VS) of compound archives as an alternative to experimental high-throughput screening (HTS). The method has been applied to 20 actual prospective kinase projects. Biological results have so far been obtained in eight of them. Q² values ranged from 0.3 to 0.7. Hit-rates at 10 uM for experimentally tested compounds varied from 25% to 80%, except in K5, which was a special case aimed specifically at finding "type II" binders, where none of the compounds were predicted to be

  14. Herbivore-induced plant volatiles accurately predict history of coexistence, diet breadth, and feeding mode of herbivores.

    PubMed

    Danner, Holger; Desurmont, Gaylord A; Cristescu, Simona M; van Dam, Nicole M

    2017-01-30

    Herbivore-induced plant volatiles (HIPVs) serve as specific cues to higher trophic levels. Novel, exotic herbivores entering native foodwebs may disrupt the infochemical network as a result of changes in HIPV profiles. Here, we analysed HIPV blends of native Brassica rapa plants infested with one of 10 herbivore species with different coexistence histories, diet breadths and feeding modes. Partial least squares (PLS) models were fitted to assess whether HIPV blends emitted by Dutch B. rapa differ between native and exotic herbivores, between specialists and generalists, and between piercing-sucking and chewing herbivores. These models were used to predict the status of two additional herbivores. We found that HIPV blends predicted the evolutionary history, diet breadth and feeding mode of the herbivore with an accuracy of 80% or higher. Based on the HIPVs, the PLS models reliably predicted that Trichoplusia ni and Spodoptera exigua are perceived as exotic, leaf-chewing generalists by Dutch B. rapa plants. These results indicate that there are consistent and predictable differences in HIPV blends depending on global herbivore characteristics, including coexistence history. Consequently, native organisms may be able to rapidly adapt to potentially disruptive effects of exotic herbivores on the infochemical network.

  15. Multireference correlation consistent composite approach [MR-ccCA]: toward accurate prediction of the energetics of excited and transition state chemistry.

    PubMed

    Oyedepo, Gbenga A; Wilson, Angela K

    2010-08-26

    The correlation consistent Composite Approach, ccCA [ Deyonker , N. J. ; Cundari , T. R. ; Wilson , A. K. J. Chem. Phys. 2006 , 124 , 114104 ] has been demonstrated to predict accurate thermochemical properties of chemical species that can be described by a single configurational reference state, and at reduced computational cost, as compared with ab initio methods such as CCSD(T) used in combination with large basis sets. We have developed three variants of a multireference equivalent of this successful theoretical model. The method, called the multireference correlation consistent composite approach (MR-ccCA), is designed to predict the thermochemical properties of reactive intermediates, excited state species, and transition states to within chemical accuracy (e.g., 1 kcal/mol for enthalpies of formation) of reliable experimental values. In this study, we have demonstrated the utility of MR-ccCA: (1) in the determination of the adiabatic singlet-triplet energy separations and enthalpies of formation for the ground states for a set of diradicals and unsaturated compounds, and (2) in the prediction of energetic barriers to internal rotation, in ethylene and its heavier congener, disilene. Additionally, we have utilized MR-ccCA to predict the enthalpies of formation of the low-lying excited states of all the species considered. MR-ccCA is shown to give quantitative results without reliance upon empirically derived parameters, making it suitable for application to study novel chemical systems with significant nondynamical correlation effects.

  16. Genomic Models of Short-Term Exposure Accurately Predict Long-Term Chemical Carcinogenicity and Identify Putative Mechanisms of Action

    PubMed Central

    Gusenleitner, Daniel; Auerbach, Scott S.; Melia, Tisha; Gómez, Harold F.; Sherr, David H.; Monti, Stefano

    2014-01-01

    Background Despite an overall decrease in incidence of and mortality from cancer, about 40% of Americans will be diagnosed with the disease in their lifetime, and around 20% will die of it. Current approaches to test carcinogenic chemicals adopt the 2-year rodent bioassay, which is costly and time-consuming. As a result, fewer than 2% of the chemicals on the market have actually been tested. However, evidence accumulated to date suggests that gene expression profiles from model organisms exposed to chemical compounds reflect underlying mechanisms of action, and that these toxicogenomic models could be used in the prediction of chemical carcinogenicity. Results In this study, we used a rat-based microarray dataset from the NTP DrugMatrix Database to test the ability of toxicogenomics to model carcinogenicity. We analyzed 1,221 gene-expression profiles obtained from rats treated with 127 well-characterized compounds, including genotoxic and non-genotoxic carcinogens. We built a classifier that predicts a chemical's carcinogenic potential with an AUC of 0.78, and validated it on an independent dataset from the Japanese Toxicogenomics Project consisting of 2,065 profiles from 72 compounds. Finally, we identified differentially expressed genes associated with chemical carcinogenesis, and developed novel data-driven approaches for the molecular characterization of the response to chemical stressors. Conclusion Here, we validate a toxicogenomic approach to predict carcinogenicity and provide strong evidence that, with a larger set of compounds, we should be able to improve the sensitivity and specificity of the predictions. We found that the prediction of carcinogenicity is tissue-dependent and that the results also confirm and expand upon previous studies implicating DNA damage, the peroxisome proliferator-activated receptor, the aryl hydrocarbon receptor, and regenerative pathology in the response to carcinogen exposure. PMID:25058030

  17. Predictive aging results for cable materials in nuclear power plants

    SciTech Connect

    Gillen, K.T.; Clough, R.L.

    1990-11-01

    In this report, we provide a detailed discussion of methodology of predicting cable degradation versus dose rate, temperature, and exposure time and its application to data obtained on a number of additional nuclear power plant cable insulation (a hypalon, a silicon rubber and two ethylenetetrafluoroethylenes) and jacket (a hypalon) materials. We then show that the predicted, low-dose-rate results for our materials are in excellent agreement with long-term (7 to 9 years), low dose-rate results recently obtained for the same material types actually aged under nuclear power plant conditions. Based on a combination of the modelling and long-term results, we find indications of reasonably similar degradation responses among several different commercial formulations for each of the following generic'' materials: hypalon, ethylenetetrafluoroethylene, silicone rubber and PVC. If such generic'' behavior can be further substantiated through modelling and long-term results on additional formulations, predictions of cable life for other commercial materials of the same generic types would be greatly facilitated. Finally, to aid utilities in their cable life extension decisions, we utilize our modelling results to generate lifetime prediction curves for the materials modelled to data. These curves plot expected material lifetime versus dose rate and temperature down to the levels of interest to nuclear power plant aging. 18 refs., 30 figs., 3 tabs.

  18. Visual Mapping of Sedimentary Facies Can Yield Accurate And Geomorphically Meaningful Results at Morphological Unit to River Segment Scales

    NASA Astrophysics Data System (ADS)

    Pasternack, G. B.; Wyrick, J. R.; Jackson, J. R.

    2014-12-01

    Long practiced in fisheries, visual substrate mapping of coarse-bedded rivers is eschewed by geomorphologists for inaccuracy and limited sizing data. Geomorphologists perform time-consuming measurements of surficial grains, with the few locations precluding spatially explicit mapping and analysis of sediment facies. Remote sensing works for bare land, but not vegetated or subaqueous sediments. As visual systems apply the log2 Wentworth scale made for sieving, they suffer from human inability to readily discern those classes. We hypothesized that size classes centered on the PDF of the anticipated sediment size distribution would enable field crews to accurately (i) identify presence/absence of each class in a facies patch and (ii) estimate the relative amount of each class to within 10%. We first tested 6 people using 14 measured samples with different mixtures. Next, we carried out facies mapping for ~ 37 km of the lower Yuba River in California. Finally, we tested the resulting data to see if it produced statistically significant hydraulic-sedimentary-geomorphic results. Presence/absence performance error was 0-4% for four people, 13% for one person, and 33% for one person. The last person was excluded from further effort. For the abundance estimation performance error was 1% for one person, 7-12% for three people, and 33% for one person. This last person was further trained and re-tested. We found that the samples easiest to visually quantify were unimodal and bimodal, while those most difficult had nearly equal amounts of each size. This confirms psychological studies showing that humans have a more difficult time quantifying abundances of subgroups when confronted with well-mixed groups. In the Yuba, mean grain size decreased downstream, as is typical for an alluvial river. When averaged by reach, mean grain size and bed slope were correlated with an r2 of 0.95. At the morphological unit (MU) scale, eight in-channel bed MU types had an r2 of 0.90 between mean

  19. Predicting Next Year's Resources--Short-Term Enrollment Forecasting for Accurate Budget Planning. AIR Forum Paper 1978.

    ERIC Educational Resources Information Center

    Salley, Charles D.

    Accurate enrollment forecasts are a prerequisite for reliable budget projections. This is because tuition payments make up a significant portion of a university's revenue, and anticipated revenue is the immediate constraint on current operating expenditures. Accurate forecasts are even more critical to revenue projections when a university's…

  20. An Optimized Method for Accurate Fetal Sex Prediction and Sex Chromosome Aneuploidy Detection in Non-Invasive Prenatal Testing

    PubMed Central

    Li, Haibo; Ding, Jie; Wen, Ping; Zhang, Qin; Xiang, Jingjing; Li, Qiong; Xuan, Liming; Kong, Lingyin; Mao, Yan; Zhu, Yijun; Shen, Jingjing; Liang, Bo; Li, Hong

    2016-01-01

    Massively parallel sequencing (MPS) combined with bioinformatic analysis has been widely applied to detect fetal chromosomal aneuploidies such as trisomy 21, 18, 13 and sex chromosome aneuploidies (SCAs) by sequencing cell-free fetal DNA (cffDNA) from maternal plasma, so-called non-invasive prenatal testing (NIPT). However, many technical challenges, such as dependency on correct fetal sex prediction, large variations of chromosome Y measurement and high sensitivity to random reads mapping, may result in higher false negative rate (FNR) and false positive rate (FPR) in fetal sex prediction as well as in SCAs detection. Here, we developed an optimized method to improve the accuracy of the current method by filtering out randomly mapped reads in six specific regions of the Y chromosome. The method reduces the FNR and FPR of fetal sex prediction from nearly 1% to 0.01% and 0.06%, respectively and works robustly under conditions of low fetal DNA concentration (1%) in testing and simulation of 92 samples. The optimized method was further confirmed by large scale testing (1590 samples), suggesting that it is reliable and robust enough for clinical testing. PMID:27441628

  1. Fast and accurate multivariate Gaussian modeling of protein families: predicting residue contacts and protein-interaction partners.

    PubMed

    Baldassi, Carlo; Zamparo, Marco; Feinauer, Christoph; Procaccini, Andrea; Zecchina, Riccardo; Weigt, Martin; Pagnani, Andrea

    2014-01-01

    In the course of evolution, proteins show a remarkable conservation of their three-dimensional structure and their biological function, leading to strong evolutionary constraints on the sequence variability between homologous proteins. Our method aims at extracting such constraints from rapidly accumulating sequence data, and thereby at inferring protein structure and function from sequence information alone. Recently, global statistical inference methods (e.g. direct-coupling analysis, sparse inverse covariance estimation) have achieved a breakthrough towards this aim, and their predictions have been successfully implemented into tertiary and quaternary protein structure prediction methods. However, due to the discrete nature of the underlying variable (amino-acids), exact inference requires exponential time in the protein length, and efficient approximations are needed for practical applicability. Here we propose a very efficient multivariate Gaussian modeling approach as a variant of direct-coupling analysis: the discrete amino-acid variables are replaced by continuous Gaussian random variables. The resulting statistical inference problem is efficiently and exactly solvable. We show that the quality of inference is comparable or superior to the one achieved by mean-field approximations to inference with discrete variables, as done by direct-coupling analysis. This is true for (i) the prediction of residue-residue contacts in proteins, and (ii) the identification of protein-protein interaction partner in bacterial signal transduction. An implementation of our multivariate Gaussian approach is available at the website http://areeweb.polito.it/ricerca/cmp/code.

  2. Unprecedently Large-Scale Kinase Inhibitor Set Enabling the Accurate Prediction of Compound–Kinase Activities: A Way toward Selective Promiscuity by Design?

    PubMed Central

    2016-01-01

    Drug discovery programs frequently target members of the human kinome and try to identify small molecule protein kinase inhibitors, primarily for cancer treatment, additional indications being increasingly investigated. One of the challenges is controlling the inhibitors degree of selectivity, assessed by in vitro profiling against panels of protein kinases. We manually extracted, compiled, and standardized such profiles published in the literature: we collected 356 908 data points corresponding to 482 protein kinases, 2106 inhibitors, and 661 patents. We then analyzed this data set in terms of kinome coverage, results reproducibility, popularity, and degree of selectivity of both kinases and inhibitors. We used the data set to create robust proteochemometric models capable of predicting kinase activity (the ligand–target space was modeled with an externally validated RMSE of 0.41 ± 0.02 log units and R02 0.74 ± 0.03), in order to account for missing or unreliable measurements. The influence on the prediction quality of parameters such as number of measurements, Murcko scaffold frequency or inhibitor type was assessed. Interpretation of the models enabled to highlight inhibitors and kinases properties correlated with higher affinities, and an analysis in the context of kinases crystal structures was performed. Overall, the models quality allows the accurate prediction of kinase-inhibitor activities and their structural interpretation, thus paving the way for the rational design of compounds with a targeted selectivity profile. PMID:27482722

  3. Knowledge-guided docking: accurate prospective prediction of bound configurations of novel ligands using Surflex-Dock

    NASA Astrophysics Data System (ADS)

    Cleves, Ann E.; Jain, Ajay N.

    2015-06-01

    Prediction of the bound configuration of small-molecule ligands that differ substantially from the cognate ligand of a protein co-crystal structure is much more challenging than re-docking the cognate ligand. Success rates for cross-docking in the range of 20-30 % are common. We present an approach that uses structural information known prior to a particular cutoff-date to make predictions on ligands whose bounds structures were determined later. The knowledge-guided docking protocol was tested on a set of ten protein targets using a total of 949 ligands. The benchmark data set, called PINC ("PINC Is Not Cognate"), is publicly available. Protein pocket similarity was used to choose representative structures for ensemble-docking. The docking protocol made use of known ligand poses prior to the cutoff-date, both to help guide the configurational search and to adjust the rank of predicted poses. Overall, the top-scoring pose family was correct over 60 % of the time, with the top-two pose families approaching a 75 % success rate. Correct poses among all those predicted were identified nearly 90 % of the time. The largest improvements came from the use of molecular similarity to improve ligand pose rankings and the strategy for identifying representative protein structures. With the exception of a single outlier target, the knowledge-guided docking protocol produced results matching the quality of cognate-ligand re-docking, but it did so on a very challenging temporally-segregated cross-docking benchmark.

  4. Knowledge-guided docking: accurate prospective prediction of bound configurations of novel ligands using Surflex-Dock.

    PubMed

    Cleves, Ann E; Jain, Ajay N

    2015-06-01

    Prediction of the bound configuration of small-molecule ligands that differ substantially from the cognate ligand of a protein co-crystal structure is much more challenging than re-docking the cognate ligand. Success rates for cross-docking in the range of 20-30 % are common. We present an approach that uses structural information known prior to a particular cutoff-date to make predictions on ligands whose bounds structures were determined later. The knowledge-guided docking protocol was tested on a set of ten protein targets using a total of 949 ligands. The benchmark data set, called PINC ("PINC Is Not Cognate"), is publicly available. Protein pocket similarity was used to choose representative structures for ensemble-docking. The docking protocol made use of known ligand poses prior to the cutoff-date, both to help guide the configurational search and to adjust the rank of predicted poses. Overall, the top-scoring pose family was correct over 60 % of the time, with the top-two pose families approaching a 75 % success rate. Correct poses among all those predicted were identified nearly 90 % of the time. The largest improvements came from the use of molecular similarity to improve ligand pose rankings and the strategy for identifying representative protein structures. With the exception of a single outlier target, the knowledge-guided docking protocol produced results matching the quality of cognate-ligand re-docking, but it did so on a very challenging temporally-segregated cross-docking benchmark.

  5. Accurate prediction of the electronic properties of low-dimensional graphene derivatives using a screened hybrid density functional.

    PubMed

    Barone, Veronica; Hod, Oded; Peralta, Juan E; Scuseria, Gustavo E

    2011-04-19

    Over the last several years, low-dimensional graphene derivatives, such as carbon nanotubes and graphene nanoribbons, have played a central role in the pursuit of a plausible carbon-based nanotechnology. Their electronic properties can be either metallic or semiconducting depending purely on morphology, but predicting their electronic behavior has proven challenging. The combination of experimental efforts with modeling of these nanometer-scale structures has been instrumental in gaining insight into their physical and chemical properties and the processes involved at these scales. Particularly, approximations based on density functional theory have emerged as a successful computational tool for predicting the electronic structure of these materials. In this Account, we review our efforts in modeling graphitic nanostructures from first principles with hybrid density functionals, namely the Heyd-Scuseria-Ernzerhof (HSE) screened exchange hybrid and the hybrid meta-generalized functional of Tao, Perdew, Staroverov, and Scuseria (TPSSh). These functionals provide a powerful tool for quantitatively studying structure-property relations and the effects of external perturbations such as chemical substitutions, electric and magnetic fields, and mechanical deformations on the electronic and magnetic properties of these low-dimensional carbon materials. We show how HSE and TPSSh successfully predict the electronic properties of these materials, providing a good description of their band structure and density of states, their work function, and their magnetic ordering in the cases in which magnetism arises. Moreover, these approximations are capable of successfully predicting optical transitions (first and higher order) in both metallic and semiconducting single-walled carbon nanotubes of various chiralities and diameters with impressive accuracy. This versatility includes the correct prediction of the trigonal warping splitting in metallic nanotubes. The results predicted

  6. Can Community Health Workers Report Accurately on Births and Deaths? Results of Field Assessments in Ethiopia, Malawi and Mali

    PubMed Central

    Silva, Romesh; Amouzou, Agbessi; Munos, Melinda; Marsh, Andrew; Hazel, Elizabeth; Victora, Cesar; Black, Robert; Bryce, Jennifer

    2016-01-01

    Introduction Most low-income countries lack complete and accurate vital registration systems. As a result, measures of under-five mortality rates rely mostly on household surveys. In collaboration with partners in Ethiopia, Ghana, Malawi, and Mali, we assessed the completeness and accuracy of reporting of births and deaths by community-based health workers, and the accuracy of annualized under-five mortality rate estimates derived from these data. Here we report on results from Ethiopia, Malawi and Mali. Method In all three countries, community health workers (CHWs) were trained, equipped and supported to report pregnancies, births and deaths within defined geographic areas over a period of at least fifteen months. In-country institutions collected these data every month. At each study site, we administered a full birth history (FBH) or full pregnancy history (FPH), to women of reproductive age via a census of households in Mali and via household surveys in Ethiopia and Malawi. Using these FBHs/FPHs as a validation data source, we assessed the completeness of the counts of births and deaths and the accuracy of under-five, infant, and neonatal mortality rates from the community-based method against the retrospective FBH/FPH for rolling twelve-month periods. For each method we calculated total cost, average annual cost per 1,000 population, and average cost per vital event reported. Results On average, CHWs submitted monthly vital event reports for over 95 percent of catchment areas in Ethiopia and Malawi, and for 100 percent of catchment areas in Mali. The completeness of vital events reporting by CHWs varied: we estimated that 30%-90% of annualized expected births (i.e. the number of births estimated using a FPH) were documented by CHWs and 22%-91% of annualized expected under-five deaths were documented by CHWs. Resulting annualized under-five mortality rates based on the CHW vital events reporting were, on average, under-estimated by 28% in Ethiopia, 32% in

  7. Absolute Measurements of Macrophage Migration Inhibitory Factor and Interleukin-1-β mRNA Levels Accurately Predict Treatment Response in Depressed Patients

    PubMed Central

    Ferrari, Clarissa; Uher, Rudolf; Bocchio-Chiavetto, Luisella; Riva, Marco Andrea; Pariante, Carmine M.

    2016-01-01

    Background: Increased levels of inflammation have been associated with a poorer response to antidepressants in several clinical samples, but these findings have had been limited by low reproducibility of biomarker assays across laboratories, difficulty in predicting response probability on an individual basis, and unclear molecular mechanisms. Methods: Here we measured absolute mRNA values (a reliable quantitation of number of molecules) of Macrophage Migration Inhibitory Factor and interleukin-1β in a previously published sample from a randomized controlled trial comparing escitalopram vs nortriptyline (GENDEP) as well as in an independent, naturalistic replication sample. We then used linear discriminant analysis to calculate mRNA values cutoffs that best discriminated between responders and nonresponders after 12 weeks of antidepressants. As Macrophage Migration Inhibitory Factor and interleukin-1β might be involved in different pathways, we constructed a protein-protein interaction network by the Search Tool for the Retrieval of Interacting Genes/Proteins. Results: We identified cutoff values for the absolute mRNA measures that accurately predicted response probability on an individual basis, with positive predictive values and specificity for nonresponders of 100% in both samples (negative predictive value=82% to 85%, sensitivity=52% to 61%). Using network analysis, we identified different clusters of targets for these 2 cytokines, with Macrophage Migration Inhibitory Factor interacting predominantly with pathways involved in neurogenesis, neuroplasticity, and cell proliferation, and interleukin-1β interacting predominantly with pathways involved in the inflammasome complex, oxidative stress, and neurodegeneration. Conclusion: We believe that these data provide a clinically suitable approach to the personalization of antidepressant therapy: patients who have absolute mRNA values above the suggested cutoffs could be directed toward earlier access to more

  8. Do Skilled Elementary Teachers Hold Scientific Conceptions and Can They Accurately Predict the Type and Source of Students' Preconceptions of Electric Circuits?

    ERIC Educational Resources Information Center

    Lin, Jing-Wen

    2016-01-01

    Holding scientific conceptions and having the ability to accurately predict students' preconceptions are a prerequisite for science teachers to design appropriate constructivist-oriented learning experiences. This study explored the types and sources of students' preconceptions of electric circuits. First, 438 grade 3 (9 years old) students were…

  9. Improved prediction of accessible surface area results in efficient energy function application.

    PubMed

    Iqbal, Sumaiya; Mishra, Avdesh; Hoque, Md Tamjidul

    2015-09-07

    An accurate prediction of real value accessible surface area (ASA) from protein sequence alone has wide application in the field of bioinformatics and computational biology. ASA has been helpful in understanding the 3-dimensional structure and function of a protein, acting as high impact feature in secondary structure prediction, disorder prediction, binding region identification and fold recognition applications. To enhance and support broad applications of ASA, we have made an attempt to improve the prediction accuracy of absolute accessible surface area by developing a new predictor paradigm, namely REGAd(3)p, for real value prediction through classical Exact Regression with Regularization and polynomial kernel of degree 3 which was further optimized using Genetic Algorithm. ASA assisting effective energy function, motivated us to enhance the accuracy of predicted ASA for better energy function application. Our ASA prediction paradigm was trained and tested using a new benchmark dataset, proposed in this work, consisting of 1001 and 298 protein chains, respectively. We achieved maximum Pearson Correlation Coefficient (PCC) of 0.76 and 1.45% improved PCC when compared with existing top performing predictor, SPINE-X, in ASA prediction on independent test set. Furthermore, we modeled the error between actual and predicted ASA in terms of energy and combined this energy linearly with the energy function 3DIGARS which resulted in an effective energy function, namely 3DIGARS2.0, outperforming all the state-of-the-art energy functions. Based on Rosetta and Tasser decoy-sets 3DIGARS2.0 resulted 80.78%, 73.77%, 141.24%, 16.52%, and 32.32% improvement over DFIRE, RWplus, dDFIRE, GOAP and 3DIGARS respectively.

  10. An accurate method to predict the stress concentration in composite laminates with a circular hole under tensile loading

    NASA Astrophysics Data System (ADS)

    Russo, A.; Zuccarello, B.

    2007-07-01

    The paper presents a theoretical-numerical hybrid method for determining the stresses distribution in composite laminates containing a circular hole and subjected to uniaxial tensile loading. The method is based upon an appropriate corrective function allowing a simple and rapid evaluation of stress distributions in a generic plate of finite width with a hole based on the theoretical stresses distribution in an infinite plate with the same hole geometry and material. In order to verify the accuracy of the method proposed, various numerical and experimental tests have been performed by considering different laminate lay-ups; in particular, the experimental results have shown that a combined use of the method proposed and the well-know point-stress criterion leads to reliable strength predictions for GFRP or CFRP laminates with a circular hole.

  11. Accurate prediction of secreted substrates and identification of a conserved putative secretion signal for type III secretion systems

    SciTech Connect

    Samudrala, Ram; Heffron, Fred; McDermott, Jason E.

    2009-04-24

    The type III secretion system is an essential component for virulence in many Gram-negative bacteria. Though components of the secretion system apparatus are conserved, its substrates, effector proteins, are not. We have used a machine learning approach to identify new secreted effectors. The method integrates evolutionary measures, such as the pattern of homologs in a range of other organisms, and sequence-based features, such as G+C content, amino acid composition and the N-terminal 30 residues of the protein sequence. The method was trained on known effectors from Salmonella typhimurium and validated on a corresponding set of effectors from Pseudomonas syringae, after eliminating effectors with detectable sequence similarity. The method was able to identify all of the known effectors in P. syringae with a specificity of 84% and sensitivity of 82%. The reciprocal validation, training on P. syringae and validating on S. typhimurium, gave similar results with a specificity of 86% when the sensitivity level was 87%. These results show that type III effectors in disparate organisms share common features. We found that maximal performance is attained by including an N-terminal sequence of only 30 residues, which agrees with previous studies indicating that this region contains the secretion signal. We then used the method to define the most important residues in this putative secretion signal. Finally, we present novel predictions of secreted effectors in S. typhimurium, some of which have been experimentally validated, and apply the method to predict secreted effectors in the genetically intractable human pathogen Chlamydia trachomatis. This approach is a novel and effective way to identify secreted effectors in a broad range of pathogenic bacteria for further experimental characterization and provides insight into the nature of the type III secretion signal.

  12. Automated antibody structure prediction using Accelrys tools: results and best practices.

    PubMed

    Fasnacht, Marc; Butenhof, Ken; Goupil-Lamy, Anne; Hernandez-Guzman, Francisco; Huang, Hongwei; Yan, Lisa

    2014-08-01

    We describe the methodology and results from our participation in the second Antibody Modeling Assessment experiment. During the experiment we predicted the structure of eleven unpublished antibody Fv fragments. Our prediction methods centered on template-based modeling; potential templates were selected from an antibody database based on their sequence similarity to the target in the framework regions. Depending on the quality of the templates, we constructed models of the antibody framework regions either using a single, chimeric or multiple template approach. The hypervariable loop regions in the initial models were rebuilt by grafting the corresponding regions from suitable templates onto the model. For the H3 loop region, we further refined models using ab initio methods. The final models were subjected to constrained energy minimization to resolve severe local structural problems. The analysis of the models submitted show that Accelrys tools allow for the construction of quite accurate models for the framework and the canonical CDR regions, with RMSDs to the X-ray structure on average below 1 Å for most of these regions. The results show that accurate prediction of the H3 hypervariable loops remains a challenge. Furthermore, model quality assessment of the submitted models show that the models are of quite high quality, with local geometry assessment scores similar to that of the target X-ray structures.

  13. Genomic inference accurately predicts the timing and severity of a recent bottleneck in a non-model insect population

    PubMed Central

    McCoy, Rajiv C.; Garud, Nandita R.; Kelley, Joanna L.; Boggs, Carol L.; Petrov, Dmitri A.

    2015-01-01

    The analysis of molecular data from natural populations has allowed researchers to answer diverse ecological questions that were previously intractable. In particular, ecologists are often interested in the demographic history of populations, information that is rarely available from historical records. Methods have been developed to infer demographic parameters from genomic data, but it is not well understood how inferred parameters compare to true population history or depend on aspects of experimental design. Here we present and evaluate a method of SNP discovery using RNA-sequencing and demographic inference using the program δaδi, which uses a diffusion approximation to the allele frequency spectrum to fit demographic models. We test these methods in a population of the checkerspot butterfly Euphydryas gillettii. This population was intentionally introduced to Gothic, Colorado in 1977 and has since experienced extreme fluctuations including bottlenecks of fewer than 25 adults, as documented by nearly annual field surveys. Using RNA-sequencing of eight individuals from Colorado and eight individuals from a native population in Wyoming, we generate the first genomic resources for this system. While demographic inference is commonly used to examine ancient demography, our study demonstrates that our inexpensive, all-in-one approach to marker discovery and genotyping provides sufficient data to accurately infer the timing of a recent bottleneck. This demographic scenario is relevant for many species of conservation concern, few of which have sequenced genomes. Our results are remarkably insensitive to sample size or number of genomic markers, which has important implications for applying this method to other non-model systems. PMID:24237665

  14. Towards more accurate isoscapes encouraging results from wine, water and marijuana data/model and model/model comparisons.

    NASA Astrophysics Data System (ADS)

    West, J. B.; Ehleringer, J. R.; Cerling, T.

    2006-12-01

    Understanding how the biosphere responds to change it at the heart of biogeochemistry, ecology, and other Earth sciences. The dramatic increase in human population and technological capacity over the past 200 years or so has resulted in numerous, simultaneous changes to biosphere structure and function. This, then, has lead to increased urgency in the scientific community to try to understand how systems have already responded to these changes, and how they might do so in the future. Since all biospheric processes exhibit some patchiness or patterns over space, as well as time, we believe that understanding the dynamic interactions between natural systems and human technological manipulations can be improved if these systems are studied in an explicitly spatial context. We present here results of some of our efforts to model the spatial variation in the stable isotope ratios (δ2H and δ18O) of plants over large spatial extents, and how these spatial model predictions compare to spatially explicit data. Stable isotopes trace and record ecological processes and as such, if modeled correctly over Earth's surface allow us insights into changes in biosphere states and processes across spatial scales. The data-model comparisons show good agreement, in spite of the remaining uncertainties (e.g., plant source water isotopic composition). For example, inter-annual changes in climate are recorded in wine stable isotope ratios. Also, a much simpler model of leaf water enrichment driven with spatially continuous global rasters of precipitation and climate normals largely agrees with complex GCM modeling that includes leaf water δ18O. Our results suggest that modeling plant stable isotope ratios across large spatial extents may be done with reasonable accuracy, including over time. These spatial maps, or isoscapes, can now be utilized to help understand spatially distributed data, as well as to help guide future studies designed to understand ecological change across

  15. How Accurately Can Extended X-ray Absorption Spectra Be Predicted from First Principles? Implications for Modeling the Oxygen-Evolving Complex in Photosystem II.

    PubMed

    Beckwith, Martha A; Ames, William; Vila, Fernando D; Krewald, Vera; Pantazis, Dimitrios A; Mantel, Claire; Pécaut, Jacques; Gennari, Marcello; Duboc, Carole; Collomb, Marie-Noëlle; Yano, Junko; Rehr, John J; Neese, Frank; DeBeer, Serena

    2015-10-14

    First principle calculations of extended X-ray absorption fine structure (EXAFS) data have seen widespread use in bioinorganic chemistry, perhaps most notably for modeling the Mn4Ca site in the oxygen evolving complex (OEC) of photosystem II (PSII). The logic implied by the calculations rests on the assumption that it is possible to a priori predict an accurate EXAFS spectrum provided that the underlying geometric structure is correct. The present study investigates the extent to which this is possible using state of the art EXAFS theory. The FEFF program is used to evaluate the ability of a multiple scattering-based approach to directly calculate the EXAFS spectrum of crystallographically defined model complexes. The results of these parameter free predictions are compared with the more traditional approach of fitting FEFF calculated spectra to experimental data. A series of seven crystallographically characterized Mn monomers and dimers is used as a test set. The largest deviations between the FEFF calculated EXAFS spectra and the experimental EXAFS spectra arise from the amplitudes. The amplitude errors result from a combination of errors in calculated S0(2) and Debye-Waller values as well as uncertainties in background subtraction. Additional errors may be attributed to structural parameters, particularly in cases where reliable high-resolution crystal structures are not available. Based on these investigations, the strengths and weaknesses of using first-principle EXAFS calculations as a predictive tool are discussed. We demonstrate that a range of DFT optimized structures of the OEC may all be considered consistent with experimental EXAFS data and that caution must be exercised when using EXAFS data to obtain topological arrangements of complex clusters.

  16. A single bioavailability model can accurately predict Ni toxicity to green microalgae in soft and hard surface waters.

    PubMed

    Deleebeeck, Nele M E; De Laender, Frederik; Chepurnov, Victor A; Vyverman, Wim; Janssen, Colin R; De Schamphelaere, Karel A C

    2009-04-01

    The major research questions addressed in this study were (i) whether green microalgae living in soft water (operationally defined water hardness<10mg CaCO(3)/L) are intrinsically more sensitive to Ni than green microalgae living in hard water (operationally defined water hardness >25mg CaCO(3)/L), and (ii) whether a single bioavailability model can be used to predict the effect of water hardness on the toxicity of Ni to green microalgae in both soft and hard water. Algal growth inhibition tests were conducted with clones of 10 different species collected in soft and hard water lakes in Sweden. Soft water algae were tested in a 'soft' and a 'moderately hard' test medium (nominal water hardness=6.25 and 16.3mg CaCO(3)/L, respectively), whereas hard water algae were tested in a 'moderately hard' and a 'hard' test medium (nominal water hardness=16.3 and 43.4 mg CaCO(3)/L, respectively). The results from the growth inhibition tests in the 'moderately hard' test medium revealed no significant sensitivity differences between the soft and the hard water algae used in this study. Increasing water hardness significantly reduced Ni toxicity to both soft and hard water algae. Because it has previously been demonstrated that Ca does not significantly protect the unicellular green alga Pseudokirchneriella subcapitata against Ni toxicity, it was assumed that the protective effect of water hardness can be ascribed to Mg alone. The logK(MgBL) (=5.5) was calculated to be identical for the soft and the hard water algae used in this study. A single bioavailability model can therefore be used to predict Ni toxicity to green microalgae in soft and hard surface waters as a function of water hardness.

  17. Numerical predictions and experimental results of a dry bay fire environment.

    SciTech Connect

    Suo-Anttila, Jill Marie; Gill, Walter; Black, Amalia Rebecca

    2003-11-01

    The primary objective of the Safety and Survivability of Aircraft Initiative is to improve the safety and survivability of systems by using validated computational models to predict the hazard posed by a fire. To meet this need, computational model predictions and experimental data have been obtained to provide insight into the thermal environment inside an aircraft dry bay. The calculations were performed using the Vulcan fire code, and the experiments were completed using a specially designed full-scale fixture. The focus of this report is to present comparisons of the Vulcan results with experimental data for a selected test scenario and to assess the capability of the Vulcan fire field model to accurately predict dry bay fire scenarios. Also included is an assessment of the sensitivity of the fire model predictions to boundary condition distribution and grid resolution. To facilitate the comparison with experimental results, a brief description of the dry bay fire test fixture and a detailed specification of the geometry and boundary conditions are included. Overall, the Vulcan fire field model has shown the capability to predict the thermal hazard posed by a sustained pool fire within a dry bay compartment of an aircraft; although, more extensive experimental data and rigorous comparison are required for model validation.

  18. The VACS Index Accurately Predicts Mortality and Treatment Response among Multi-Drug Resistant HIV Infected Patients Participating in the Options in Management with Antiretrovirals (OPTIMA) Study

    PubMed Central

    Brown, Sheldon T.; Tate, Janet P.; Kyriakides, Tassos C.; Kirkwood, Katherine A.; Holodniy, Mark; Goulet, Joseph L.; Angus, Brian J.; Cameron, D. William; Justice, Amy C.

    2014-01-01

    Objectives The VACS Index is highly predictive of all-cause mortality among HIV infected individuals within the first few years of combination antiretroviral therapy (cART). However, its accuracy among highly treatment experienced individuals and its responsiveness to treatment interventions have yet to be evaluated. We compared the accuracy and responsiveness of the VACS Index with a Restricted Index of age and traditional HIV biomarkers among patients enrolled in the OPTIMA study. Methods Using data from 324/339 (96%) patients in OPTIMA, we evaluated associations between indices and mortality using Kaplan-Meier estimates, proportional hazards models, Harrel’s C-statistic and net reclassification improvement (NRI). We also determined the association between study interventions and risk scores over time, and change in score and mortality. Results Both the Restricted Index (c = 0.70) and VACS Index (c = 0.74) predicted mortality from baseline, but discrimination was improved with the VACS Index (NRI = 23%). Change in score from baseline to 48 weeks was more strongly associated with survival for the VACS Index than the Restricted Index with respective hazard ratios of 0.26 (95% CI 0.14–0.49) and 0.39(95% CI 0.22–0.70) among the 25% most improved scores, and 2.08 (95% CI 1.27–3.38) and 1.51 (95%CI 0.90–2.53) for the 25% least improved scores. Conclusions The VACS Index predicts all-cause mortality more accurately among multi-drug resistant, treatment experienced individuals and is more responsive to changes in risk associated with treatment intervention than an index restricted to age and HIV biomarkers. The VACS Index holds promise as an intermediate outcome for intervention research. PMID:24667813

  19. Generalized spin-ratio scaled MP2 method for accurate prediction of intermolecular interactions for neutral and ionic species

    NASA Astrophysics Data System (ADS)

    Tan, Samuel; Barrera Acevedo, Santiago; Izgorodina, Ekaterina I.

    2017-02-01

    The accurate calculation of intermolecular interactions is important to our understanding of properties in large molecular systems. The high computational cost of the current "gold standard" method, coupled cluster with singles and doubles and perturbative triples (CCSD(T), limits its application to small- to medium-sized systems. Second-order Møller-Plesset perturbation (MP2) theory is a cheaper alternative for larger systems, although at the expense of its decreased accuracy, especially when treating van der Waals complexes. In this study, a new modification of the spin-component scaled MP2 method was proposed for a wide range of intermolecular complexes including two well-known datasets, S22 and S66, and a large dataset of ionic liquids consisting of 174 single ion pairs, IL174. It was found that the spin ratio, ɛΔ s=E/INT O SEIN T S S , calculated as the ratio of the opposite-spin component to the same-spin component of the interaction correlation energy fell in the range of 0.1 and 1.6, in contrast to the range of 3-4 usually observed for the ratio of absolute correlation energy, ɛs=E/OSES S , in individual molecules. Scaled coefficients were found to become negative when the spin ratio fell in close proximity to 1.0, and therefore, the studied intermolecular complexes were divided into two groups: (1) complexes with ɛΔ s< 1 and (2) complexes with ɛΔ s≥ 1 . A separate set of coefficients was obtained for both groups. Exclusion of counterpoise correction during scaling was found to produce superior results due to decreased error. Among a series of Dunning's basis sets, cc-pVTZ and cc-pVQZ were found to be the best performing ones, with a mean absolute error of 1.4 kJ mol-1 and maximum errors below 6.2 kJ mol-1. The new modification, spin-ratio scaled second-order Møller-Plesset perturbation, treats both dispersion-driven and hydrogen-bonded complexes equally well, thus validating its robustness with respect to the interaction type ranging from ionic

  20. Transcription factor regulation can be accurately predicted from the presence of target gene signatures in microarray gene expression data

    PubMed Central

    Essaghir, Ahmed; Toffalini, Federica; Knoops, Laurent; Kallin, Anders; van Helden, Jacques; Demoulin, Jean-Baptiste

    2010-01-01

    Deciphering transcription factor networks from microarray data remains difficult. This study presents a simple method to infer the regulation of transcription factors from microarray data based on well-characterized target genes. We generated a catalog containing transcription factors associated with 2720 target genes and 6401 experimentally validated regulations. When it was available, a distinction between transcriptional activation and inhibition was included for each regulation. Next, we built a tool (www.tfacts.org) that compares submitted gene lists with target genes in the catalog to detect regulated transcription factors. TFactS was validated with published lists of regulated genes in various models and compared to tools based on in silico promoter analysis. We next analyzed the NCI60 cancer microarray data set and showed the regulation of SOX10, MITF and JUN in melanomas. We then performed microarray experiments comparing gene expression response of human fibroblasts stimulated by different growth factors. TFactS predicted the specific activation of Signal transducer and activator of transcription factors by PDGF-BB, which was confirmed experimentally. Our results show that the expression levels of transcription factor target genes constitute a robust signature for transcription factor regulation, and can be efficiently used for microarray data mining. PMID:20215436

  1. Duplicate portion sampling combined with spectrophotometric analysis affords the most accurate results when assessing daily dietary phosphorus intake.

    PubMed

    Navarro-Alarcon, Miguel; Zambrano, Esmeralda; Moreno-Montoro, Miriam; Agil, Ahmad; Olalla, Manuel

    2012-08-01

    The assessment of daily dietary phosphorus (P) intake is a major concern in human nutrition because of its relationship with Ca and Mg metabolism and osteoporosis. Within this context, we hypothesized that several of the methods available for the assessment of daily dietary intake of P are equally accurate and reliable, although few studies have been conducted to confirm this. The aim of this study then was to evaluate daily dietary P intake, which we did by 3 methods: duplicate portion sampling of 108 hospital meals, combined either with spectrophotometric analysis or the use of food composition tables, and 24-hour dietary recall for 3 consecutive days plus the use of food composition tables. The mean P daily dietary intakes found were 1106 ± 221, 1480 ± 221, and 1515 ± 223 mg/d, respectively. Daily dietary intake of P determined by spectrophotometric analysis was significantly lower (P < .001) and closer to dietary reference intakes for adolescents aged from 14 to 18 years (88.5%) and adult subjects (158.1%) compared with the other 2 methods. Duplicate portion sampling with P analysis takes into account the influence of technological and cooking processes on the P content of foods and meals and therefore afforded the most accurate and reliable P daily dietary intakes. The use of referred food composition tables overestimated daily dietary P intake. No adverse effects in relation to P nutrition (deficiencies or toxic effects) were encountered.

  2. Toward Relatively General and Accurate Quantum Chemical Predictions of Solid-State (17)O NMR Chemical Shifts in Various Biologically Relevant Oxygen-Containing Compounds.

    PubMed

    Rorick, Amber; Michael, Matthew A; Yang, Liu; Zhang, Yong

    2015-09-03

    Oxygen is an important element in most biologically significant molecules, and experimental solid-state (17)O NMR studies have provided numerous useful structural probes to study these systems. However, computational predictions of solid-state (17)O NMR chemical shift tensor properties are still challenging in many cases, and in particular, each of the prior computational works is basically limited to one type of oxygen-containing system. This work provides the first systematic study of the effects of geometry refinement, method, and basis sets for metal and nonmetal elements in both geometry optimization and NMR property calculations of some biologically relevant oxygen-containing compounds with a good variety of XO bonding groups (X = H, C, N, P, and metal). The experimental range studied is of 1455 ppm, a major part of the reported (17)O NMR chemical shifts in organic and organometallic compounds. A number of computational factors toward relatively general and accurate predictions of (17)O NMR chemical shifts were studied to provide helpful and detailed suggestions for future work. For the studied kinds of oxygen-containing compounds, the best computational approach results in a theory-versus-experiment correlation coefficient (R(2)) value of 0.9880 and a mean absolute deviation of 13 ppm (1.9% of the experimental range) for isotropic NMR shifts and an R(2) value of 0.9926 for all shift-tensor properties. These results shall facilitate future computational studies of (17)O NMR chemical shifts in many biologically relevant systems, and the high accuracy may also help the refinement and determination of active-site structures of some oxygen-containing substrate-bound proteins.

  3. Is Demography Destiny? Application of Machine Learning Techniques to Accurately Predict Population Health Outcomes from a Minimal Demographic Dataset

    PubMed Central

    Luo, Wei; Nguyen, Thin; Nichols, Melanie; Tran, Truyen; Rana, Santu; Gupta, Sunil; Phung, Dinh; Venkatesh, Svetha; Allender, Steve

    2015-01-01

    For years, we have relied on population surveys to keep track of regional public health statistics, including the prevalence of non-communicable diseases. Because of the cost and limitations of such surveys, we often do not have the up-to-date data on health outcomes of a region. In this paper, we examined the feasibility of inferring regional health outcomes from socio-demographic data that are widely available and timely updated through national censuses and community surveys. Using data for 50 American states (excluding Washington DC) from 2007 to 2012, we constructed a machine-learning model to predict the prevalence of six non-communicable disease (NCD) outcomes (four NCDs and two major clinical risk factors), based on population socio-demographic characteristics from the American Community Survey. We found that regional prevalence estimates for non-communicable diseases can be reasonably predicted. The predictions were highly correlated with the observed data, in both the states included in the derivation model (median correlation 0.88) and those excluded from the development for use as a completely separated validation sample (median correlation 0.85), demonstrating that the model had sufficient external validity to make good predictions, based on demographics alone, for areas not included in the model development. This highlights both the utility of this sophisticated approach to model development, and the vital importance of simple socio-demographic characteristics as both indicators and determinants of chronic disease. PMID:25938675

  4. Is demography destiny? Application of machine learning techniques to accurately predict population health outcomes from a minimal demographic dataset.

    PubMed

    Luo, Wei; Nguyen, Thin; Nichols, Melanie; Tran, Truyen; Rana, Santu; Gupta, Sunil; Phung, Dinh; Venkatesh, Svetha; Allender, Steve

    2015-01-01

    For years, we have relied on population surveys to keep track of regional public health statistics, including the prevalence of non-communicable diseases. Because of the cost and limitations of such surveys, we often do not have the up-to-date data on health outcomes of a region. In this paper, we examined the feasibility of inferring regional health outcomes from socio-demographic data that are widely available and timely updated through national censuses and community surveys. Using data for 50 American states (excluding Washington DC) from 2007 to 2012, we constructed a machine-learning model to predict the prevalence of six non-communicable disease (NCD) outcomes (four NCDs and two major clinical risk factors), based on population socio-demographic characteristics from the American Community Survey. We found that regional prevalence estimates for non-communicable diseases can be reasonably predicted. The predictions were highly correlated with the observed data, in both the states included in the derivation model (median correlation 0.88) and those excluded from the development for use as a completely separated validation sample (median correlation 0.85), demonstrating that the model had sufficient external validity to make good predictions, based on demographics alone, for areas not included in the model development. This highlights both the utility of this sophisticated approach to model development, and the vital importance of simple socio-demographic characteristics as both indicators and determinants of chronic disease.

  5. A Maximal Graded Exercise Test to Accurately Predict VO2max in 18-65-Year-Old Adults

    ERIC Educational Resources Information Center

    George, James D.; Bradshaw, Danielle I.; Hyde, Annette; Vehrs, Pat R.; Hager, Ronald L.; Yanowitz, Frank G.

    2007-01-01

    The purpose of this study was to develop an age-generalized regression model to predict maximal oxygen uptake (VO sub 2 max) based on a maximal treadmill graded exercise test (GXT; George, 1996). Participants (N = 100), ages 18-65 years, reached a maximal level of exertion (mean plus or minus standard deviation [SD]; maximal heart rate [HR sub…

  6. Accurate Prediction of Protein Functional Class From Sequence in the Mycobacterium Tuberculosis and Escherichia Coli Genomes Using Data Mining

    PubMed Central

    Karwath, Andreas; Clare, Amanda; Dehaspe, Luc

    2000-01-01

    The analysis of genomics data needs to become as automated as its generation. Here we present a novel data-mining approach to predicting protein functional class from sequence. This method is based on a combination of inductive logic programming clustering and rule learning. We demonstrate the effectiveness of this approach on the M. tuberculosis and E. coli genomes, and identify biologically interpretable rules which predict protein functional class from information only available from the sequence. These rules predict 65% of the ORFs with no assigned function in M. tuberculosis and 24% of those in E. coli, with an estimated accuracy of 60–80% (depending on the level of functional assignment). The rules are founded on a combination of detection of remote homology, convergent evolution and horizontal gene transfer. We identify rules that predict protein functional class even in the absence of detectable sequence or structural homology. These rules give insight into the evolutionary history of M. tuberculosis and E. coli. PMID:11119305

  7. DSS1/DSS2 astrometry for 1101 First Byurakan Survey blue stellar objects: Accurate positions and other results

    NASA Astrophysics Data System (ADS)

    Mickaelian, A. M.

    2004-10-01

    Accurate measurements of the positions of 1101 First Byurakan Survey (FBS) blue stellar objects (the Second part of the FBS) have been carried out on the DSS1 and DSS2 (red and blue images). To establish the accuracy of the DSS1 and DSS2, measurements have been made for 153 AGN for which absolute VLBI coordinates have been published. The rms errors are: 0.45 arcsec for DSS1, 0.33 arcsec for DSS2 red, and 0.59 arcsec for DSS2 blue in each coordinate, the corresponding total positional errors being 0.64 arcsec, 0.46 arcsec, and 0.83 arcsec, respectively. The highest accuracy (0.42 arcsec) is obtained by weighted averaging of the DSS1 and DSS2 red positions. It is shown that by using all three DSS images accidental errors can be significantly reduced. The comparison of DSS2 and DSS1 images made it possible to reveal positional differences and proper motions for 78 objects (for 62 of these for the first time), including new high-probability candidate white dwarfs, and to find objects showing strong variability, i.e. high-probability candidate cataclysmic variables. Table 1 is only available in electronic form at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsweb.u-strasbg.fr/cgi-bin/qcat?J/A+A/426/367

  8. Aircraft Weight Prediction Capability. Volume 1: Weight Study and Results

    DTIC Science & Technology

    1993-05-01

    the specification performance normally is based on. As indicated above, this study focused upon the application of the Parametric Estimation technique...with an occasional reference relative to other techniques used at other times in development. Parametric Estimation Prediction is far more...complex as that required to do a Parametric Estimation Prediction in which 100 or more Input parameters may be and often are required. These

  9. Accurate and efficient prediction of fine-resolution hydrologic and carbon dynamic simulations from coarse-resolution models

    NASA Astrophysics Data System (ADS)

    Pau, George Shu Heng; Shen, Chaopeng; Riley, William J.; Liu, Yaning

    2016-02-01

    The topography, and the biotic and abiotic parameters are typically upscaled to make watershed-scale hydrologic-biogeochemical models computationally tractable. However, upscaling procedure can produce biases when nonlinear interactions between different processes are not fully captured at coarse resolutions. Here we applied the Proper Orthogonal Decomposition Mapping Method (PODMM) to downscale the field solutions from a coarse (7 km) resolution grid to a fine (220 m) resolution grid. PODMM trains a reduced-order model (ROM) with coarse-resolution and fine-resolution solutions, here obtained using PAWS+CLM, a quasi-3-D watershed processes model that has been validated for many temperate watersheds. Subsequent fine-resolution solutions were approximated based only on coarse-resolution solutions and the ROM. The approximation errors were efficiently quantified using an error estimator. By jointly estimating correlated variables and temporally varying the ROM parameters, we further reduced the approximation errors by up to 20%. We also improved the method's robustness by constructing multiple ROMs using different set of variables, and selecting the best approximation based on the error estimator. The ROMs produced accurate downscaling of soil moisture, latent heat flux, and net primary production with O(1000) reduction in computational cost. The subgrid distributions were also nearly indistinguishable from the ones obtained using the fine-resolution model. Compared to coarse-resolution solutions, biases in upscaled ROM solutions were reduced by up to 80%. This method has the potential to help address the long-standing spatial scaling problem in hydrology and enable long-time integration, parameter estimation, and stochastic uncertainty analysis while accurately representing the heterogeneities.

  10. An Electroacoustic Hearing Protector Simulator That Accurately Predicts Pressure Levels in the Ear Based on Standard Performance Metrics

    DTIC Science & Technology

    2013-08-01

    24 Figure 20. ABQ experiment showing five volunteers located 1.0 m from source in upper-left panel wearing...study (Royster et al.,1996) in which users self-fit hearing protectors (ANSI S12.6- 2008 method B: user fit) with no experimenter instruction gives an...values provided by the experimenters and simulator fits for the intact and modified muffs. Figure 22 (upper panel) shows the simulator prediction

  11. A highly accurate protein structural class prediction approach using auto cross covariance transformation and recursive feature elimination.

    PubMed

    Li, Xiaowei; Liu, Taigang; Tao, Peiying; Wang, Chunhua; Chen, Lanming

    2015-12-01

    Structural class characterizes the overall folding type of a protein or its domain. Many methods have been proposed to improve the prediction accuracy of protein structural class in recent years, but it is still a challenge for the low-similarity sequences. In this study, we introduce a feature extraction technique based on auto cross covariance (ACC) transformation of position-specific score matrix (PSSM) to represent a protein sequence. Then support vector machine-recursive feature elimination (SVM-RFE) is adopted to select top K features according to their importance and these features are input to a support vector machine (SVM) to conduct the prediction. Performance evaluation of the proposed method is performed using the jackknife test on three low-similarity datasets, i.e., D640, 1189 and 25PDB. By means of this method, the overall accuracies of 97.2%, 96.2%, and 93.3% are achieved on these three datasets, which are higher than those of most existing methods. This suggests that the proposed method could serve as a very cost-effective tool for predicting protein structural class especially for low-similarity datasets.

  12. How many clinic BP readings are needed to predict cardiovascular events as accurately as ambulatory BP monitoring?

    PubMed

    Eguchi, K; Hoshide, S; Shimada, K; Kario, K

    2014-12-01

    We tested the hypothesis that multiple clinic blood pressure (BP) readings over an extended baseline period would be as predictive as ambulatory BP (ABP) for cardiovascular disease (CVD). Clinic and ABP monitoring were performed in 457 hypertensive patients at baseline. Clinic BP was measured monthly and the means of the first 3, 5 and 10 clinic BP readings were taken as the multiple clinic BP readings. The subjects were followed up, and stroke, HARD CVD, and ALL CVD events were determined as outcomes. In multivariate Cox regression analyses, ambulatory systolic BP (SBP) best predicted three outcomes independently of baseline and multiple clinic SBP readings. The mean of 10 clinic SBP readings predicted stroke (hazards ratio (HR)=1.39, 95% confidence interval (CI)=1.02-1.90, P=0.04) and ALL CVD (HR=1.41, 95% CI=1.13-1.74, P=0.002) independently of baseline clinic SBP. Clinic SBPs by three and five readings were not associated with any CVD events, except that clinic SBP by three readings was associated with ALL CVD (P=0.015). Besides ABP values, the mean of the first 10 clinic SBP values was a significant predictor of stroke and ALL CVD events. It is important to take more than several clinic BP readings early after the baseline period for the risk stratification of future CVD events.

  13. Dual X-ray absorptiometry accurately predicts carcass composition from live sheep and chemical composition of live and dead sheep.

    PubMed

    Pearce, K L; Ferguson, M; Gardner, G; Smith, N; Greef, J; Pethick, D W

    2009-01-01

    Fifty merino wethers (liveweight range from 44 to 81kg, average of 58.6kg) were lot fed for 42d and scanned through a dual X-ray absorptiometry (DXA) as both a live animal and whole carcass (carcass weight range from 15 to 32kg, average of 22.9kg) producing measures of total tissue, lean, fat and bone content. The carcasses were subsequently boned out into saleable cuts and the weights and yield of boned out muscle, fat and bone recorded. The relationship between chemical lean (protein+water) was highly correlated with DXA carcass lean (r(2)=0.90, RSD=0.674kg) and moderately with DXA live lean (r(2)=0.72, RSD=1.05kg). The relationship between the chemical fat was moderately correlated with DXA carcass fat (r(2)=0.86, RSD=0.42kg) and DXA live fat (r(2)=0.70, RSD=0.71kg). DXA carcass and live animal bone was not well correlated with chemical ash (both r(2)=0.38, RSD=0.3). DXA carcass lean was moderately well predicted from DXA live lean with the inclusion of bodyweight in the regression (r(2)=0.82, RSD=0.87kg). DXA carcass fat was well predicted from DXA live fat (r(2)=0.86, RSD=0.54kg). DXA carcass lean and DXA carcass fat with the inclusion of carcass weight in the regression significantly predicted boned out muscle (r(2)=0.97, RSD=0.32kg) and fat weight, respectively (r(2)=0.92, RSD=0.34kg). The use of DXA live lean and DXA live fat with the inclusion of bodyweight to predict boned out muscle (r(2)=0.83, RSD=0.75kg) and fat (r(2)=0.86, RSD=0.46kg) weight, respectively, was moderate. The use of DXA carcass and live lean and fat to predict boned out muscle and fat yield was not correlated as weight. The future for the DXA will exist in the determination of body composition in live animals and carcasses in research experiments but there is potential for the DXA to be used as an online carcass grading system.

  14. A novel, integrated PET-guided MRS technique resulting in more accurate initial diagnosis of high-grade glioma.

    PubMed

    Kim, Ellen S; Satter, Martin; Reed, Marilyn; Fadell, Ronald; Kardan, Arash

    2016-06-01

    Glioblastoma multiforme (GBM) is the most common and lethal malignant glioma in adults. Currently, the modality of choice for diagnosing brain tumor is high-resolution magnetic resonance imaging (MRI) with contrast, which provides anatomic detail and localization. Studies have demonstrated, however, that MRI may have limited utility in delineating the full tumor extent precisely. Studies suggest that MR spectroscopy (MRS) can also be used to distinguish high-grade from low-grade gliomas. However, due to operator dependent variables and the heterogeneous nature of gliomas, the potential for error in diagnostic accuracy with MRS is a concern. Positron emission tomography (PET) imaging with (11)C-methionine (MET) and (18)F-fluorodeoxyglucose (FDG) has been shown to add additional information with respect to tumor grade, extent, and prognosis based on the premise of biochemical changes preceding anatomic changes. Combined PET/MRS is a technique that integrates information from PET in guiding the location for the most accurate metabolic characterization of a lesion via MRS. We describe a case of glioblastoma multiforme in which MRS was initially non-diagnostic for malignancy, but when MRS was repeated with PET guidance, demonstrated elevated choline/N-acetylaspartate (Cho/NAA) ratio in the right parietal mass consistent with a high-grade malignancy. Stereotactic biopsy, followed by PET image-guided resection, confirmed the diagnosis of grade IV GBM. To our knowledge, this is the first reported case of an integrated PET/MRS technique for the voxel placement of MRS. Our findings suggest that integrated PET/MRS may potentially improve diagnostic accuracy in high-grade gliomas.

  15. A Comparison Between The NORCAT Rover Test Results and the ISRU Excavation System Model Predictions Results

    NASA Technical Reports Server (NTRS)

    Gallo, Christopher A.; Agui, Juan H.; Creager, Colin M.; Oravec, Heather A.

    2012-01-01

    An Excavation System Model has been written to simulate the collection and transportation of regolith on the moon. The calculations in this model include an estimation of the forces on the digging tool as a result of excavation into the regolith. Verification testing has been performed and the forces recorded from this testing were compared to the calculated theoretical data. The Northern Centre for Advanced Technology Inc. rovers were tested at the NASA Glenn Research Center Simulated Lunar Operations facility. This testing was in support of the In-Situ Resource Utilization program Innovative Partnership Program. Testing occurred in soils developed at the Glenn Research Center which are a mixture of different types of sands and whose soil properties have been well characterized. This testing is part of an ongoing correlation of actual field test data to the blade forces calculated by the Excavation System Model. The results from this series of tests compared reasonably with the predicted values from the code.

  16. Network Biomarkers Constructed from Gene Expression and Protein-Protein Interaction Data for Accurate Prediction of Leukemia

    PubMed Central

    Yuan, Xuye; Chen, Jiajia; Lin, Yuxin; Li, Yin; Xu, Lihua; Chen, Luonan; Hua, Haiying; Shen, Bairong

    2017-01-01

    Leukemia is a leading cause of cancer deaths in the developed countries. Great efforts have been undertaken in search of diagnostic biomarkers of leukemia. However, leukemia is highly complex and heterogeneous, involving interaction among multiple molecular components. Individual molecules are not necessarily sensitive diagnostic indicators. Network biomarkers are considered to outperform individual molecules in disease characterization. We applied an integrative approach that identifies active network modules as putative biomarkers for leukemia diagnosis. We first reconstructed the leukemia-specific PPI network using protein-protein interactions from the Protein Interaction Network Analysis (PINA) and protein annotations from GeneGo. The network was further integrated with gene expression profiles to identify active modules with leukemia relevance. Finally, the candidate network-based biomarker was evaluated for the diagnosing performance. A network of 97 genes and 400 interactions was identified for accurate diagnosis of leukemia. Functional enrichment analysis revealed that the network biomarkers were enriched in pathways in cancer. The network biomarkers could discriminate leukemia samples from the normal controls more effectively than the known biomarkers. The network biomarkers provide a useful tool to diagnose leukemia and also aids in further understanding the molecular basis of leukemia. PMID:28243332

  17. A 3D-CFD code for accurate prediction of fluid flows and fluid forces in seals

    NASA Technical Reports Server (NTRS)

    Athavale, M. M.; Przekwas, A. J.; Hendricks, R. C.

    1994-01-01

    Current and future turbomachinery requires advanced seal configurations to control leakage, inhibit mixing of incompatible fluids and to control the rotodynamic response. In recognition of a deficiency in the existing predictive methodology for seals, a seven year effort was established in 1990 by NASA's Office of Aeronautics Exploration and Technology, under the Earth-to-Orbit Propulsion program, to develop validated Computational Fluid Dynamics (CFD) concepts, codes and analyses for seals. The effort will provide NASA and the U.S. Aerospace Industry with advanced CFD scientific codes and industrial codes for analyzing and designing turbomachinery seals. An advanced 3D CFD cylindrical seal code has been developed, incorporating state-of-the-art computational methodology for flow analysis in straight, tapered and stepped seals. Relevant computational features of the code include: stationary/rotating coordinates, cylindrical and general Body Fitted Coordinates (BFC) systems, high order differencing schemes, colocated variable arrangement, advanced turbulence models, incompressible/compressible flows, and moving grids. This paper presents the current status of code development, code demonstration for predicting rotordynamic coefficients, numerical parametric study of entrance loss coefficients for generic annular seals, and plans for code extensions to labyrinth, damping, and other seal configurations.

  18. IrisPlex: a sensitive DNA tool for accurate prediction of blue and brown eye colour in the absence of ancestry information.

    PubMed

    Walsh, Susan; Liu, Fan; Ballantyne, Kaye N; van Oven, Mannis; Lao, Oscar; Kayser, Manfred

    2011-06-01

    A new era of 'DNA intelligence' is arriving in forensic biology, due to the impending ability to predict externally visible characteristics (EVCs) from biological material such as those found at crime scenes. EVC prediction from forensic samples, or from body parts, is expected to help concentrate police investigations towards finding unknown individuals, at times when conventional DNA profiling fails to provide informative leads. Here we present a robust and sensitive tool, termed IrisPlex, for the accurate prediction of blue and brown eye colour from DNA in future forensic applications. We used the six currently most eye colour-informative single nucleotide polymorphisms (SNPs) that previously revealed prevalence-adjusted prediction accuracies of over 90% for blue and brown eye colour in 6168 Dutch Europeans. The single multiplex assay, based on SNaPshot chemistry and capillary electrophoresis, both widely used in forensic laboratories, displays high levels of genotyping sensitivity with complete profiles generated from as little as 31pg of DNA, approximately six human diploid cell equivalents. We also present a prediction model to correctly classify an individual's eye colour, via probability estimation solely based on DNA data, and illustrate the accuracy of the developed prediction test on 40 individuals from various geographic origins. Moreover, we obtained insights into the worldwide allele distribution of these six SNPs using the HGDP-CEPH samples of 51 populations. Eye colour prediction analyses from HGDP-CEPH samples provide evidence that the test and model presented here perform reliably without prior ancestry information, although future worldwide genotype and phenotype data shall confirm this notion. As our IrisPlex eye colour prediction test is capable of immediate implementation in forensic casework, it represents one of the first steps forward in the creation of a fully individualised EVC prediction system for future use in forensic DNA intelligence.

  19. Report: EPA Needs Accurate Data on Results of Pollution Prevention Grants to Maintain Program Integrity and Measure Effectiveness of Grants

    EPA Pesticide Factsheets

    Report #15-P-0276, September 4, 2015. Inaccurate reporting of results misrepresents the impacts of pollution prevention activities provided to the public, and misinforms EPA management on the effectiveness of its investment in the program.

  20. Cosmological constraints from the CFHTLenS shear measurements using a new, accurate, and flexible way of predicting non-linear mass clustering

    NASA Astrophysics Data System (ADS)

    Angulo, Raul E.; Hilbert, Stefan

    2015-03-01

    We explore the cosmological constraints from cosmic shear using a new way of modelling the non-linear matter correlation functions. The new formalism extends the method of Angulo & White, which manipulates outputs of N-body simulations to represent the 3D non-linear mass distribution in different cosmological scenarios. We show that predictions from our approach for shear two-point correlations at 1-300 arcmin separations are accurate at the ˜10 per cent level, even for extreme changes in cosmology. For moderate changes, with target cosmologies similar to that preferred by analyses of recent Planck data, the accuracy is close to ˜5 per cent. We combine this approach with a Monte Carlo Markov chain sampler to explore constraints on a Λ cold dark matter model from the shear correlation functions measured in the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS). We obtain constraints on the parameter combination σ8(Ωm/0.27)0.6 = 0.801 ± 0.028. Combined with results from cosmic microwave background data, we obtain marginalized constraints on σ8 = 0.81 ± 0.01 and Ωm = 0.29 ± 0.01. These results are statistically compatible with previous analyses, which supports the validity of our approach. We discuss the advantages of our method and the potential it offers, including a path to model in detail (i) the effects of baryons, (ii) high-order shear correlation functions, and (iii) galaxy-galaxy lensing, among others, in future high-precision cosmological analyses.

  1. FDG-PET measurement is more accurate than neuropsychological assessments to predict global cognitive deterioration in patients with mild cognitive impairment.

    PubMed

    Chételat, Gaël; Eustache, Francis; Viader, Fausto; De La Sayette, Vincent; Pélerin, Alice; Mézenge, Florence; Hannequin, Didier; Dupuy, Benoît; Baron, Jean-Claude; Desgranges, Béatrice

    2005-02-01

    The accurate prediction, at a pre-dementia stage of Alzheimer's disease (AD), of the subsequent clinical evolution of patients would be a major breakthrough from both therapeutic and research standpoints. Amnestic mild cognitive impairment (MCI) is presently the most common reference to address the pre-dementia stage of AD. However, previous longitudinal studies on patients with MCI assessing neuropsychological and PET markers of future conversion to AD are sparse and yield discrepant findings, while a comprehensive comparison of the relative accuracy of these two categories of measure is still lacking. In the present study, we assessed the global cognitive decline as measured by the Mattis scale in 18 patients with amnestic MCI over an 18-month follow-up period, studying which subtest of this scale showed significant deterioration over time. Using baseline measurements from neuropsychological evaluation of memory and PET, we then assessed significant markers of global cognitive change, that is, percent annual change in the Mattis scale total score, and searched for the best predictor of this global cognitive decline. Altogether, our results revealed significant decline over the 18-month follow-up period in the total score and the verbal initiation and memory-recall subscores of the Mattis scale. The percent annual change in the total Mattis score significantly correlated with age and baseline performances in delayed episodic memory recall as well as semantic autobiographical and category word fluencies. Regarding functional imaging, significant correlations were also found with baseline PET values in the right temporo-parietal and medial frontal areas. Age and right temporo-parietal PET values were the most significant predictors of subsequent global cognitive decline, and the only ones to survive stepwise regression analyses. Our findings are consistent with previous works showing predominant delayed recall and semantic memory impairment at a pre-dementia stage

  2. A comparison of hypersonic vehicle flight and prediction results

    NASA Technical Reports Server (NTRS)

    Iliff, Kenneth W.; Shafer, Mary F.

    1995-01-01

    Aerodynamic and aerothermodynamic comparisons between flight and ground test for four hypersonic vehicles are discussed. The four vehicles are the X-15, the Reentry F, the Sandia Energetic Reentry Vehicle Experiment (SWERVE), and the Space Shuttle. The comparisons are taken from papers published by researchers active in the various programs. Aerodynamic comparisons include reaction control jet interaction on the Space Shuttle. Various forms of heating including catalytic, boundary layer, shock interaction and interference, and vortex impingement are compared. Predictions were significantly exceeded for the heating caused by vortex impingement (on the Space Shuttle OMS pods) and for heating caused by shock interaction and interference on the X-15 and the Space Shuttle. Predictions of boundary-layer state were in error on the X-15, the SWERVE, and the Space Shuttle vehicles.

  3. Re-Entry Predictions for Uncontrolled Satellites: Results and Challenges

    NASA Astrophysics Data System (ADS)

    Pardini, Carmen; Anselmo, Luciano

    2013-09-01

    Currently, approximately 70% of the re-entries of intact orbital objects are uncontrolled, corresponding to about 50% of the returning mass, i.e. ˜100 metric tons per year. On average, there is one spacecraft or rocket body uncontrolled re-entry every week, with an average mass around 2000 kg. Even though a detailed demise analysis is available only occasionally, in many cases the alert casualty expectancy threshold of 1:10,000 is probably violated.Re-entry predictions are affected by various sources of inevitable uncertainty and, in spite of decades of efforts, mean relative errors of 20% often occur. This means that even predictions issued 3 hours before re-entry may be affected by an along-track uncertainty of 40,000 km (corresponding to one orbital path), possibly halved during the last hour. However, specific methods and procedures have been developed to provide understandable and unambiguous information useful for civil protection planning and applications.

  4. A comparison of hypersonic flight and prediction results

    NASA Technical Reports Server (NTRS)

    Iliff, Kenneth W.; Shafer, Mary F.

    1993-01-01

    Aerodynamic and aerothermodynamic comparisons between flight and ground test for four hypersonic vehicles are discussed. The four vehicles are the X-15, the Reentry F, the Sandia Energetic Reentry Vehicle Experiment (SWERVE), and the Space Shuttle. The comparisons are taken from papers published by researchers active in the various programs. Aerodynamic comparisons include reaction control jet interaction on the Space Shuttle. Various forms of heating including catalytic, boundary layer, shock interaction and interference, and vortex impingement are compared. Predictions were significantly exceeded for the heating caused by vortex impingement (on the Space Shuttle OMS pods) and for heating caused by shock interaction and interference on the X-15 and the Space Shuttle. Predictions of boundary-layer state were in error on the X-15, the SWERVE, and the Space Shuttle vehicles.

  5. Predicting College Students' First Year Success: Should Soft Skills Be Taken into Consideration to More Accurately Predict the Academic Achievement of College Freshmen?

    ERIC Educational Resources Information Center

    Powell, Erica Dion

    2013-01-01

    This study presents a survey developed to measure the skills of entering college freshmen in the areas of responsibility, motivation, study habits, literacy, and stress management, and explores the predictive power of this survey as a measure of academic performance during the first semester of college. The survey was completed by 334 incoming…

  6. Microdosing of a Carbon-14 Labeled Protein in Healthy Volunteers Accurately Predicts Its Pharmacokinetics at Therapeutic Dosages.

    PubMed

    Vlaming, M L H; van Duijn, E; Dillingh, M R; Brands, R; Windhorst, A D; Hendrikse, N H; Bosgra, S; Burggraaf, J; de Koning, M C; Fidder, A; Mocking, J A J; Sandman, H; de Ligt, R A F; Fabriek, B O; Pasman, W J; Seinen, W; Alves, T; Carrondo, M; Peixoto, C; Peeters, P A M; Vaes, W H J

    2015-08-01

    Preclinical development of new biological entities (NBEs), such as human protein therapeutics, requires considerable expenditure of time and costs. Poor prediction of pharmacokinetics in humans further reduces net efficiency. In this study, we show for the first time that pharmacokinetic data of NBEs in humans can be successfully obtained early in the drug development process by the use of microdosing in a small group of healthy subjects combined with ultrasensitive accelerator mass spectrometry (AMS). After only minimal preclinical testing, we performed a first-in-human phase 0/phase 1 trial with a human recombinant therapeutic protein (RESCuing Alkaline Phosphatase, human recombinant placental alkaline phosphatase [hRESCAP]) to assess its safety and kinetics. Pharmacokinetic analysis showed dose linearity from microdose (53 μg) [(14) C]-hRESCAP to therapeutic doses (up to 5.3 mg) of the protein in healthy volunteers. This study demonstrates the value of a microdosing approach in a very small cohort for accelerating the clinical development of NBEs.

  7. Women's age and embryo developmental speed accurately predict clinical pregnancy after single vitrified-warmed blastocyst transfer.

    PubMed

    Kato, Keiichi; Ueno, Satoshi; Yabuuchi, Akiko; Uchiyama, Kazuo; Okuno, Takashi; Kobayashi, Tamotsu; Segawa, Tomoya; Teramoto, Shokichi

    2014-10-01

    The aim of this study was to establish a simple, objective blastocyst grading system using women's age and embryo developmental speed to predict clinical pregnancy after single vitrified-warmed blastocyst transfer. A 6-year retrospective cohort study was conducted in a private infertility centre. A total of 7341 single vitrified-armed blastocyst transfer cycles were included, divided into those carried out between 2006 and 2011 (6046 cycles) and 2012 (1295 cycles). Clinical pregnancy rate, ongoing pregnancy rate and delivery rates were stratified by women's age (<35, 35-37, 38-39, 40-41, 42-45 years) and time to blastocyst expansion (<120, 120-129, 130-139, 140-149, >149 h) as embryo developmental speed. In all the age groups, clinical pregnancy rate, ongoing pregnancy rate and delivery rates decreased as the embryo developmental speed decreased (P < 0.0001). A simple five-grade score based on women's age and embryo developmental speed was determined by actual clinical pregnancy rates observed in the 2006-2011 cohort. Subsequently, the novel grading score was validated in the 2012 cohort (1295 cycles), finding an excellent association. In conclusion, we established a novel blastocyst grading system using women's age and embryo developmental speed as objective parameters.

  8. Experimental results for labyrinth gas seals with honeycomb stators - Comparisons to smooth-stator seals and theoretical predictions

    NASA Technical Reports Server (NTRS)

    Hawkins, Larry; Childs, Dara; Hale, Keith

    1989-01-01

    Experimental measurements are presented for the rotordynamic stiffness and damping coefficients of a teeth-on-rotor labyrinth seal with a honeycomb stator. Inlet circumferential velocity, inlet pressure, rotor speed, and seal clearance are primary variables. Results are compared to data for teeth-on-rotor labyrinth seals with smooth stators and to analytical predictions from a two-control-volume compressible flow model. The experimental results show that the honeycomb-stator configuration is more stable than the smooth-stator configuration at low rator speeds. At high rotor speeds, the stator surface does not affect stability. The theoretical model predicts the cross-coupled stiffness of the honeycomb-stator seal correctly within 25 percent of measured values. The model provides accurate predictions of direct damping for large clearance seals; however, the model predictions and test results diverge with increasing running speed. Overall, the model does not perform as well for low clearance seals as for high clearance seals.

  9. IMPre: An Accurate and Efficient Software for Prediction of T- and B-Cell Receptor Germline Genes and Alleles from Rearranged Repertoire Data

    PubMed Central

    Zhang, Wei; Wang, I-Ming; Wang, Changxi; Lin, Liya; Chai, Xianghua; Wu, Jinghua; Bett, Andrew J.; Dhanasekaran, Govindarajan; Casimiro, Danilo R.; Liu, Xiao

    2016-01-01

    Large-scale study of the properties of T-cell receptor (TCR) and B-cell receptor (BCR) repertoires through next-generation sequencing is providing excellent insights into the understanding of adaptive immune responses. Variable(Diversity)Joining [V(D)J] germline genes and alleles must be characterized in detail to facilitate repertoire analyses. However, most species do not have well-characterized TCR/BCR germline genes because of their high homology. Also, more germline alleles are required for humans and other species, which limits the capacity for studying immune repertoires. Herein, we developed “Immune Germline Prediction” (IMPre), a tool for predicting germline V/J genes and alleles using deep-sequencing data derived from TCR/BCR repertoires. We developed a new algorithm, “Seed_Clust,” for clustering, produced a multiway tree for assembly and optimized the sequence according to the characteristics of rearrangement. We trained IMPre on human samples of T-cell receptor beta (TRB) and immunoglobulin heavy chain and then tested it on additional human samples. Accuracy of 97.7, 100, 92.9, and 100% was obtained for TRBV, TRBJ, IGHV, and IGHJ, respectively. Analyses of subsampling performance for these samples showed IMPre to be robust using different data quantities. Subsequently, IMPre was tested on samples from rhesus monkeys and human long sequences: the highly accurate results demonstrated IMPre to be stable with animal and multiple data types. With rapid accumulation of high-throughput sequence data for TCR and BCR repertoires, IMPre can be applied broadly for obtaining novel genes and a large number of novel alleles. IMPre is available at https://github.com/zhangwei2015/IMPre. PMID:27867380

  10. Noncontrast computed tomography can predict the outcome of shockwave lithotripsy via accurate stone measurement and abdominal fat distribution determination.

    PubMed

    Geng, Jiun-Hung; Tu, Hung-Pin; Shih, Paul Ming-Chen; Shen, Jung-Tsung; Jang, Mei-Yu; Wu, Wen-Jen; Li, Ching-Chia; Chou, Yii-Her; Juan, Yung-Shun

    2015-01-01

    Urolithiasis is a common disease of the urinary system. Extracorporeal shockwave lithotripsy (SWL) has become one of the standard treatments for renal and ureteral stones; however, the success rates range widely and failure of stone disintegration may cause additional outlay, alternative procedures, and even complications. We used the data available from noncontrast abdominal computed tomography (NCCT) to evaluate the impact of stone parameters and abdominal fat distribution on calculus-free rates following SWL. We retrospectively reviewed 328 patients who had urinary stones and had undergone SWL from August 2012 to August 2013. All of them received pre-SWL NCCT; 1 month after SWL, radiography was arranged to evaluate the condition of the fragments. These patients were classified into stone-free group and residual stone group. Unenhanced computed tomography variables, including stone attenuation, abdominal fat area, and skin-to-stone distance (SSD) were analyzed. In all, 197 (60%) were classified as stone-free and 132 (40%) as having residual stone. The mean ages were 49.35 ± 13.22 years and 55.32 ± 13.52 years, respectively. On univariate analysis, age, stone size, stone surface area, stone attenuation, SSD, total fat area (TFA), abdominal circumference, serum creatinine, and the severity of hydronephrosis revealed statistical significance between these two groups. From multivariate logistic regression analysis, the independent parameters impacting SWL outcomes were stone size, stone attenuation, TFA, and serum creatinine. [Adjusted odds ratios and (95% confidence intervals): 9.49 (3.72-24.20), 2.25 (1.22-4.14), 2.20 (1.10-4.40), and 2.89 (1.35-6.21) respectively, all p < 0.05]. In the present study, stone size, stone attenuation, TFA and serum creatinine were four independent predictors for stone-free rates after SWL. These findings suggest that pretreatment NCCT may predict the outcomes after SWL. Consequently, we can use these predictors for selecting

  11. The route to MBxNyCz molecular wheels: II. Results using accurate functionals and basis sets

    NASA Astrophysics Data System (ADS)

    Güthler, A.; Mukhopadhyay, S.; Pandey, R.; Boustani, I.

    2014-04-01

    Applying ab initio quantum chemical methods, molecular wheels composed of metal and light atoms were investigated. High quality basis sets 6-31G*, TZPV, and cc-pVTZ as well as exchange and non-local correlation functionals B3LYP, BP86 and B3P86 were used. The ground-state energy and structures of cyclic planar and pyramidal clusters TiBn (for n = 3-10) were computed. In addition, the relative stability and electronic structures of molecular wheels TiBxNyCz (for x, y, z = 0-10) and MBnC10-n (for n = 2 to 5 and M = Sc to Zn) were determined. This paper sustains a follow-up study to the previous one of Boustani and Pandey [Solid State Sci. 14 (2012) 1591], in which the calculations were carried out at the HF-SCF/STO3G/6-31G level of theory to determine the initial stability and properties. The results show that there is a competition between the 2D planar and the 3D pyramidal TiBn clusters (for n = 3-8). Different isomers of TiB10 clusters were also studied and a structural transition of 3D-isomer into 2D-wheel is presented. Substitution boron in TiB10 by carbon or/and nitrogen atoms enhances the stability and leads toward the most stable wheel TiB3C7. Furthermore, the computations show that Sc, Ti and V at the center of the molecular wheels are energetically favored over other transition metal atoms of the first row.

  12. Nucleic Acids Research Group (NRG): The Importance of DNA Extraction in Metagenomics: The Gatekeeper to Accurate Results!

    PubMed Central

    Carmical, R.; Nadella, V.; Herbert, Z.; Beckloff, N.; Chittur, S.; Rosato, C.; Perera, A.; Auer, H.; Robinson, M.; Tighe, S.; Holbrook, Jennifer

    2013-01-01

    It is well recognized that the field of metagenomics is becoming a critical tool for studying previously unobtainable population dynamics at both an identification of species level and a functional or transcriptional level. Because the power to resolve microbial information is so important for identifying the components in an mixed sample, metagenomics can be used to study nearly any possible environment or system including clinical, environmental, and industrial, to name a few. Clinically, it may be used to determine sub-populations colonizing regions of the body or determining a rare infection to assist in treatment strategies. Environmentally it may be used to identify microbial populations within a soil, water or air sample, or within a bioreactor to characterize a population- based functional process. The possibilities are endless. However, the accuracy of a metagenomics dataset relies on three important “gatekeepers” including 1) The ability to effectively extract all DNA or RNA from every cell within a sample, 2) The reliability of the methods used for deep or high-throughput sequencing, and 3) The software used to analyze the data. Since DNA extraction is the first step in the technical process of metagenomics, the Nucleic Acid Research Group (NARG) conducted a study to evaluate extraction methods using a synthetic microbial sample. The synthetic microbial sample was prepared from 10 known bacteria at specific concentrations and ranging in diversity. Samples were extracted in duplicate using various popular kit based methods as well as several homebrew protocols then analyzed by NextGen sequencing on an Illumina HiSeq. Results of the study include determining the percent recovery of those organisms by comparing to the known quantity in the original synthetic mix.

  13. Why Don't We Learn to Accurately Forecast Feelings? How Misremembering Our Predictions Blinds Us to Past Forecasting Errors

    ERIC Educational Resources Information Center

    Meyvis, Tom; Ratner, Rebecca K.; Levav, Jonathan

    2010-01-01

    Why do affective forecasting errors persist in the face of repeated disconfirming evidence? Five studies demonstrate that people misremember their forecasts as consistent with their experience and thus fail to perceive the extent of their forecasting error. As a result, people do not learn from past forecasting errors and fail to adjust subsequent…

  14. A theoretical prediction of hydrogen molecule dissociation-recombination rates including an accurate treatment of internal state nonequilibrium effects

    NASA Technical Reports Server (NTRS)

    Schwenke, David W.

    1990-01-01

    The dissociation and recombination of H2 over the temperature range 1000-5000 K are calculated in a nonempirical manner. The computation procedure involves the calculation of the state-to-state energy transfer rate coefficients, the solution of the 349 coupled equations which form the master equation, and the determination of the phenomenological rate coefficients. The nonempirical results presented here are in good agreement with experimental data at 1000 and 3000 K.

  15. Accurate prediction of death by serial determination of galactose elimination capacity in primary biliary cirrhosis: a comparison with the Mayo model.

    PubMed

    Reichen, J; Widmer, T; Cotting, J

    1991-09-01

    We retrospectively analyzed the predictive accuracy of serial determinations of galactose elimination capacity in 61 patients with primary biliary cirrhosis. Death was predicted from the time that the regression line describing the decline in galactose elimination capacity vs. time intersected a value of 4 mg.min-1.kg-1. Thirty-one patients exhibited decreasing galactose elimination capacity; in 11 patients it remained stable and in 19 patients only one value was available. Among those patients with decreasing galactose elimination capacity, 10 died and three underwent liver transplantation; prediction of death was accurate to 7 +/- 19 mo. This criterion incorrectly predicted death in two patients with portal-vein thrombosis; otherwise, it did better than or as well as the Mayo clinic score. The latter was also tested on our patients and was found to adequately describe risk in yet another independent population of patients with primary biliary cirrhosis. Cox regression analysis selected only bilirubin and galactose elimination capacity, however, as independent predictors of death. We submit that serial determination of galactose elimination capacity in patients with primary biliary cirrhosis may be a useful adjunct to optimize the timing of liver transplantation and to evaluate new pharmacological treatment modalities of this disease.

  16. Nanoarray of polycyclic aromatic hydrocarbons and carbon nanotubes for accurate and predictive detection in real-world environmental humidity.

    PubMed

    Zilberman, Yael; Ionescu, Radu; Feng, Xinliang; Müllen, Klaus; Haick, Hossam

    2011-08-23

    In the present work, we introduce a cross-reactive array of synthetically designed polycyclic aromatic hydrocarbons (PAH) and single-walled carbon nanotube (SWCNT) bilayers and demonstrate the huge potential of the array in discriminating between polar and nonpolar volatile organic compounds (VOCs), as well as between the different VOCs from each subgroup. Using appropriate combinations of PAH/SWCNT sensors, we demonstrate that high sensitivity and accuracy values can be obtained for discriminating polar and nonpolar VOCs in samples with variable humidity levels (5-80% RH). The same array of sensors exhibited self-learning capabilities that facilitated exchanging information about environmental properties under observation. The results presented here could lead to the development of a cost-effective, lightweight, low-power, and non-invasive tool for a widespread detection of VOCs in real-world environmental, security, food, health, and other applications.

  17. Discussion of the indicators used in developing an early and accurate judgemental prediction of weak recovery or depression

    SciTech Connect

    Santini, D.J.

    1983-04-01

    A theory is developed which asserts that energy-price-induced innovation causes depression and recessions. Recessions result from promptly adopted successful innovation, which caused declining demand for the products replaced by the successful innovation. A series of partially successful costly innovations occurs during the years of collapse into a depression. Consumers withdraw from the market because of the cost and uncertainty resulting from the innovation process. This theory is compared to and logically related to those of Schumpeter, Keynes, Mench, Freeman, and Marchetti. The theory is tested for the transportation sector of the economy, the most energy intensive economic sector. It is shown that vehicle innovation starts just before major US depressions and extends through each depression. The cycles of vehicle innovation are linked to collapses in vehicle output and to declines in GNP. Three depressions are studied in detail. These are the Debt Repudiation Depression of 1839 to 1843, the Depression of the Nineties, and the Great Depression. Characteristics of these depressions are contrasted with recessions since 1890 and with current US conditions. Proper actions by the US auto industry, e.g., introduction of new low priced models, will not occur during this year. A fuel tax whose revenues would be used to promote the sales of new, fuel efficient domestic automobiles is suggested for consideration as a means of assuring a recovery rather than a depression. In April of 1983 an increase of gasoline taxes, differential sales incentives increases on fuel efficient cars, and government payments to individual consumers (tax refunds) all combined to lead to increases in auto sales, record stock price levels and general optimism about economic recovery.

  18. FRONTIER FIELDS: HIGH-REDSHIFT PREDICTIONS AND EARLY RESULTS

    SciTech Connect

    Coe, Dan; Bradley, Larry; Zitrin, Adi

    2015-02-20

    The Frontier Fields program is obtaining deep Hubble and Spitzer Space Telescope images of new ''blank'' fields and nearby fields gravitationally lensed by massive galaxy clusters. The Hubble images of the lensed fields are revealing nJy sources (AB mag > 31), the faintest galaxies yet observed. The full program will transform our understanding of galaxy evolution in the first 600 million years (z > 9). Previous programs have yielded a dozen or so z > 9 candidates, including perhaps fewer than expected in the Ultra Deep Field and more than expected in shallower Hubble images. In this paper, we present high-redshift (z > 6) number count predictions for the Frontier Fields and candidates in three of the first Hubble images. We show the full Frontier Fields program may yield up to ∼70 z > 9 candidates (∼6 per field). We base this estimate on an extrapolation of luminosity functions observed between 4 < z < 8 and gravitational lensing models submitted by the community. However, in the first two deep infrared Hubble images obtained to date, we find z ∼ 8 candidates but no strong candidates at z > 9. We defer quantitative analysis of the z > 9 deficit (including detection completeness estimates) to future work including additional data. At these redshifts, cosmic variance (field-to-field variation) is expected to be significant (greater than ±50%) and include clustering of early galaxies formed in overdensities. The full Frontier Fields program will significantly mitigate this uncertainty by observing six independent sightlines each with a lensing cluster and nearby blank field.

  19. Identification of fidgety movements and prediction of CP by the use of computer-based video analysis is more accurate when based on two video recordings.

    PubMed

    Adde, Lars; Helbostad, Jorunn; Jensenius, Alexander R; Langaas, Mette; Støen, Ragnhild

    2013-08-01

    This study evaluates the role of postterm age at assessment and the use of one or two video recordings for the detection of fidgety movements (FMs) and prediction of cerebral palsy (CP) using computer vision software. Recordings between 9 and 17 weeks postterm age from 52 preterm and term infants (24 boys, 28 girls; 26 born preterm) were used. Recordings were analyzed using computer vision software. Movement variables, derived from differences between subsequent video frames, were used for quantitative analysis. Sensitivities, specificities, and area under curve were estimated for the first and second recording, or a mean of both. FMs were classified based on the Prechtl approach of general movement assessment. CP status was reported at 2 years. Nine children developed CP of whom all recordings had absent FMs. The mean variability of the centroid of motion (CSD) from two recordings was more accurate than using only one recording, and identified all children who were diagnosed with CP at 2 years. Age at assessment did not influence the detection of FMs or prediction of CP. The accuracy of computer vision techniques in identifying FMs and predicting CP based on two recordings should be confirmed in future studies.

  20. Reduction of computer usage costs in predicting unsteady aerodynamic loadings caused by control surface motions: Analysis and results

    NASA Technical Reports Server (NTRS)

    Rowe, W. S.; Sebastian, J. D.; Petrarca, J. R.

    1979-01-01

    Results of theoretical and numerical investigations conducted to develop economical computing procedures were applied to an existing computer program that predicts unsteady aerodynamic loadings caused by leading and trailing edge control surface motions in subsonic compressible flow. Large reductions in computing costs were achieved by removing the spanwise singularity of the downwash integrand and evaluating its effect separately in closed form. Additional reductions were obtained by modifying the incremental pressure term that account for downwash singularities at control surface edges. Accuracy of theoretical predictions of unsteady loading at high reduced frequencies was increased by applying new pressure expressions that exactly satisified the high frequency boundary conditions of an oscillating control surface. Comparative computer result indicated that the revised procedures provide more accurate predictions of unsteady loadings as well as providing reduction of 50 to 80 percent in computer usage costs.

  1. Dose Addition Models Based on Biologically Relevant Reductions in Fetal Testosterone Accurately Predict Postnatal Reproductive Tract Alterations by a Phthalate Mixture in Rats

    PubMed Central

    Howdeshell, Kembra L.; Rider, Cynthia V.; Wilson, Vickie S.; Furr, Johnathan R.; Lambright, Christy R.; Gray, L. Earl

    2015-01-01

    Challenges in cumulative risk assessment of anti-androgenic phthalate mixtures include a lack of data on all the individual phthalates and difficulty determining the biological relevance of reduction in fetal testosterone (T) on postnatal development. The objectives of the current study were 2-fold: (1) to test whether a mixture model of dose addition based on the fetal T production data of individual phthalates would predict the effects of a 5 phthalate mixture on androgen-sensitive postnatal male reproductive tract development, and (2) to determine the biological relevance of the reductions in fetal T to induce abnormal postnatal reproductive tract development using data from the mixture study. We administered a dose range of the mixture (60, 40, 20, 10, and 5% of the top dose used in the previous fetal T production study consisting of 300 mg/kg per chemical of benzyl butyl (BBP), di(n)butyl (DBP), diethyl hexyl phthalate (DEHP), di-isobutyl phthalate (DiBP), and 100 mg dipentyl (DPP) phthalate/kg; the individual phthalates were present in equipotent doses based on their ability to reduce fetal T production) via gavage to Sprague Dawley rat dams on GD8-postnatal day 3. We compared observed mixture responses to predictions of dose addition based on the previously published potencies of the individual phthalates to reduce fetal T production relative to a reference chemical and published postnatal data for the reference chemical (called DAref). In addition, we predicted DA (called DAall) and response addition (RA) based on logistic regression analysis of all 5 individual phthalates when complete data were available. DA ref and DA all accurately predicted the observed mixture effect for 11 of 14 endpoints. Furthermore, reproductive tract malformations were seen in 17–100% of F1 males when fetal T production was reduced by about 25–72%, respectively. PMID:26350170

  2. Discovery of a general method of solving the Schrödinger and dirac equations that opens a way to accurately predictive quantum chemistry.

    PubMed

    Nakatsuji, Hiroshi

    2012-09-18

    Just as Newtonian law governs classical physics, the Schrödinger equation (SE) and the relativistic Dirac equation (DE) rule the world of chemistry. So, if we can solve these equations accurately, we can use computation to predict chemistry precisely. However, for approximately 80 years after the discovery of these equations, chemists believed that they could not solve SE and DE for atoms and molecules that included many electrons. This Account reviews ideas developed over the past decade to further the goal of predictive quantum chemistry. Between 2000 and 2005, I discovered a general method of solving the SE and DE accurately. As a first inspiration, I formulated the structure of the exact wave function of the SE in a compact mathematical form. The explicit inclusion of the exact wave function's structure within the variational space allows for the calculation of the exact wave function as a solution of the variational method. Although this process sounds almost impossible, it is indeed possible, and I have published several formulations and applied them to solve the full configuration interaction (CI) with a very small number of variables. However, when I examined analytical solutions for atoms and molecules, the Hamiltonian integrals in their secular equations diverged. This singularity problem occurred in all atoms and molecules because it originates from the singularity of the Coulomb potential in their Hamiltonians. To overcome this problem, I first introduced the inverse SE and then the scaled SE. The latter simpler idea led to immediate and surprisingly accurate solution for the SEs of the hydrogen atom, helium atom, and hydrogen molecule. The free complement (FC) method, also called the free iterative CI (free ICI) method, was efficient for solving the SEs. In the FC method, the basis functions that span the exact wave function are produced by the Hamiltonian of the system and the zeroth-order wave function. These basis functions are called complement

  3. The Need for Accurate Risk Prediction Models for Road Mapping, Shared Decision Making and Care Planning for the Elderly with Advanced Chronic Kidney Disease.

    PubMed

    Stryckers, Marijke; Nagler, Evi V; Van Biesen, Wim

    2016-11-01

    As people age, chronic kidney disease becomes more common, but it rarely leads to end-stage kidney disease. When it does, the choice between dialysis and conservative care can be daunting, as much depends on life expectancy and personal expectations of medical care. Shared decision making implies adequately informing patients about their options, and facilitating deliberation of the available information, such that decisions are tailored to the individual's values and preferences. Accurate estimations of one's risk of progression to end-stage kidney disease and death with or without dialysis are essential for shared decision making to be effective. Formal risk prediction models can help, provided they are externally validated, well-calibrated and discriminative; include unambiguous and measureable variables; and come with readily applicable equations or scores. Reliable, externally validated risk prediction models for progression of chronic kidney disease to end-stage kidney disease or mortality in frail elderly with or without chronic kidney disease are scant. Within this paper, we discuss a number of promising models, highlighting both the strengths and limitations physicians should understand for using them judiciously, and emphasize the need for external validation over new development for further advancing the field.

  4. A comparative study between experimental results and numerical predictions of multi-wall structural response to hypervelocity impact

    NASA Technical Reports Server (NTRS)

    Schonberg, William P.; Peck, Jeffrey A.

    1992-01-01

    Over the last three decades, multiwall structures have been analyzed extensively, primarily through experiment, as a means of increasing the protection afforded to spacecraft structure. However, as structural configurations become more varied, the number of tests required to characterize their response increases dramatically. As an alternative, numerical modeling of high-speed impact phenomena is often being used to predict the response of a variety of structural systems under impact loading conditions. This paper presents the results of a preliminary numerical/experimental investigation of the hypervelocity impact response of multiwall structures. The results of experimental high-speed impact tests are compared against the predictions of the HULL hydrodynamic computer code. It is shown that the hypervelocity impact response characteristics of a specific system cannot be accurately predicted from a limited number of HULL code impact simulations. However, if a wide range of impact loadings conditions are considered, then the ballistic limit curve of the system based on the entire series of numerical simulations can be used as a relatively accurate indication of actual system response.

  5. Integrating trans-abdominal ultrasonography with fecal steroid metabolite monitoring to accurately diagnose pregnancy and predict the timing of parturition in the red panda (Ailurus fulgens styani).

    PubMed

    Curry, Erin; Browning, Lissa J; Reinhart, Paul; Roth, Terri L

    2017-02-23

    Red pandas (Ailurus fulgens styani) exhibit a variable gestation length and may experience a pseudopregnancy indistinguishable from true pregnancy; therefore, it is not possible to deduce an individual's true pregnancy status and parturition date based on breeding dates or fecal progesterone excretion patterns alone. The goal of this study was to evaluate the use of transabdominal ultrasonography for pregnancy diagnosis in red pandas. Two to three females were monitored over 4 consecutive years, generating a total of seven profiles (four pregnancies, two pseudopregnancies, and one lost pregnancy). Fecal samples were collected and assayed for progesterone (P4) and estrogen conjugate (EC) to characterize patterns associated with breeding activity and parturition events. Animals were trained for voluntary transabdominal ultrasound and examinations were performed weekly. Breeding behaviors and fecal EC data suggest that the estrus cycle of this species is 11-12 days in length. Fecal steroid metabolite analyses also revealed that neither P4 nor EC concentrations were suitable indicators of pregnancy in this species; however, a secondary increase in P4 occurred 69-71 days prior to parturition in all pregnant females, presumably coinciding with embryo implantation. Using ultrasonography, embryos were detected as early as 62 days post-breeding/50 days pre-partum and serial measurements of uterine lumen diameter were documented throughout four pregnancies. Advances in reproductive diagnostics, such as the implementation of ultrasonography, may facilitate improved husbandry of pregnant females and allow for the accurate prediction of parturition.

  6. Accurate quantum chemical calculations

    NASA Technical Reports Server (NTRS)

    Bauschlicher, Charles W., Jr.; Langhoff, Stephen R.; Taylor, Peter R.

    1989-01-01

    An important goal of quantum chemical calculations is to provide an understanding of chemical bonding and molecular electronic structure. A second goal, the prediction of energy differences to chemical accuracy, has been much harder to attain. First, the computational resources required to achieve such accuracy are very large, and second, it is not straightforward to demonstrate that an apparently accurate result, in terms of agreement with experiment, does not result from a cancellation of errors. Recent advances in electronic structure methodology, coupled with the power of vector supercomputers, have made it possible to solve a number of electronic structure problems exactly using the full configuration interaction (FCI) method within a subspace of the complete Hilbert space. These exact results can be used to benchmark approximate techniques that are applicable to a wider range of chemical and physical problems. The methodology of many-electron quantum chemistry is reviewed. Methods are considered in detail for performing FCI calculations. The application of FCI methods to several three-electron problems in molecular physics are discussed. A number of benchmark applications of FCI wave functions are described. Atomic basis sets and the development of improved methods for handling very large basis sets are discussed: these are then applied to a number of chemical and spectroscopic problems; to transition metals; and to problems involving potential energy surfaces. Although the experiences described give considerable grounds for optimism about the general ability to perform accurate calculations, there are several problems that have proved less tractable, at least with current computer resources, and these and possible solutions are discussed.

  7. Prediction of {sup 2}D Rydberg energy levels of {sup 6}Li and {sup 7}Li based on very accurate quantum mechanical calculations performed with explicitly correlated Gaussian functions

    SciTech Connect

    Bubin, Sergiy; Sharkey, Keeper L.; Adamowicz, Ludwik

    2013-04-28

    Very accurate variational nonrelativistic finite-nuclear-mass calculations employing all-electron explicitly correlated Gaussian basis functions are carried out for six Rydberg {sup 2}D states (1s{sup 2}nd, n= 6, Horizontal-Ellipsis , 11) of the {sup 7}Li and {sup 6}Li isotopes. The exponential parameters of the Gaussian functions are optimized using the variational method with the aid of the analytical energy gradient determined with respect to these parameters. The experimental results for the lower states (n= 3, Horizontal-Ellipsis , 6) and the calculated results for the higher states (n= 7, Horizontal-Ellipsis , 11) fitted with quantum-defect-like formulas are used to predict the energies of {sup 2}D 1s{sup 2}nd states for {sup 7}Li and {sup 6}Li with n up to 30.

  8. Use of dose-dependent absorption into target tissues to more accurately predict cancer risk at low oral doses of hexavalent chromium.

    PubMed

    Haney, J

    2015-02-01

    The mouse dose at the lowest water concentration used in the National Toxicology Program hexavalent chromium (CrVI) drinking water study (NTP, 2008) is about 74,500 times higher than the approximate human dose corresponding to the 35-city geometric mean reported in EWG (2010) and over 1000 times higher than that based on the highest reported tap water concentration. With experimental and environmental doses differing greatly, it is a regulatory challenge to extrapolate high-dose results to environmental doses orders of magnitude lower in a meaningful and toxicologically predictive manner. This seems particularly true for the low-dose extrapolation of results for oral CrVI-induced carcinogenesis since dose-dependent differences in the dose fraction absorbed by mouse target tissues are apparent (Kirman et al., 2012). These data can be used for a straightforward adjustment of the USEPA (2010) draft oral slope factor (SFo) to be more predictive of risk at environmentally-relevant doses. More specifically, the evaluation of observed and modeled differences in the fraction of dose absorbed by target tissues at the point-of-departure for the draft SFo calculation versus lower doses suggests that the draft SFo be divided by a dose-specific adjustment factor of at least an order of magnitude to be less over-predictive of risk at more environmentally-relevant doses.

  9. Accurate prediction of higher-level electronic structure energies for large databases using neural networks, Hartree-Fock energies, and small subsets of the database.

    PubMed

    Malshe, M; Pukrittayakamee, A; Raff, L M; Hagan, M; Bukkapatnam, S; Komanduri, R

    2009-09-28

    A novel method is presented that significantly reduces the computational bottleneck of executing high-level, electronic structure calculations of the energies and their gradients for a large database that adequately samples the configuration space of importance for systems containing more than four atoms that are undergoing multiple, simultaneous reactions in several energetically open channels. The basis of the method is the high-degree of correlation that generally exists between the Hartree-Fock (HF) and higher-level electronic structure energies. It is shown that if the input vector to a neural network (NN) includes both the configuration coordinates and the HF energies of a small subset of the database, MP4(SDQ) energies with the same basis set can be predicted for the entire database using only the HF and MP4(SDQ) energies for the small subset and the HF energies for the remainder of the database. The predictive error is shown to be less than or equal to the NN fitting error if a NN is fitted to the entire database of higher-level electronic structure energies. The general method is applied to the computation of MP4(SDQ) energies of 68,308 configurations that comprise the database for the simultaneous, unimolecular decomposition of vinyl bromide into six different reaction channels. The predictive accuracy of the method is investigated by employing successively smaller subsets of the database to train the NN to predict the MP4(SDQ) energies of the remaining configurations of the database. The results indicate that for this system, the subset can be as small as 8% of the total number of configurations in the database without loss of accuracy beyond that expected if a NN is employed to fit the higher-level energies for the entire database. The utilization of this procedure is shown to save about 78% of the total computational time required for the execution of the MP4(SDQ) calculations. The sampling error involved with selection of the subset is shown to be

  10. Accurate prediction of higher-level electronic structure energies for large databases using neural networks, Hartree-Fock energies, and small subsets of the database

    NASA Astrophysics Data System (ADS)

    Malshe, M.; Pukrittayakamee, A.; Raff, L. M.; Hagan, M.; Bukkapatnam, S.; Komanduri, R.

    2009-09-01

    A novel method is presented that significantly reduces the computational bottleneck of executing high-level, electronic structure calculations of the energies and their gradients for a large database that adequately samples the configuration space of importance for systems containing more than four atoms that are undergoing multiple, simultaneous reactions in several energetically open channels. The basis of the method is the high-degree of correlation that generally exists between the Hartree-Fock (HF) and higher-level electronic structure energies. It is shown that if the input vector to a neural network (NN) includes both the configuration coordinates and the HF energies of a small subset of the database, MP4(SDQ) energies with the same basis set can be predicted for the entire database using only the HF and MP4(SDQ) energies for the small subset and the HF energies for the remainder of the database. The predictive error is shown to be less than or equal to the NN fitting error if a NN is fitted to the entire database of higher-level electronic structure energies. The general method is applied to the computation of MP4(SDQ) energies of 68 308 configurations that comprise the database for the simultaneous, unimolecular decomposition of vinyl bromide into six different reaction channels. The predictive accuracy of the method is investigated by employing successively smaller subsets of the database to train the NN to predict the MP4(SDQ) energies of the remaining configurations of the database. The results indicate that for this system, the subset can be as small as 8% of the total number of configurations in the database without loss of accuracy beyond that expected if a NN is employed to fit the higher-level energies for the entire database. The utilization of this procedure is shown to save about 78% of the total computational time required for the execution of the MP4(SDQ) calculations. The sampling error involved with selection of the subset is shown to be

  11. Correlation of clinical predictions and surgical results in maxillary superior repositioning.

    PubMed

    Tabrizi, Reza; Zamiri, Barbad; Kazemi, Hamidreza

    2014-05-01

    This is a prospective study to evaluate the accuracy of clinical predictions related to surgical results in subjects who underwent maxillary superior repositioning without anterior-posterior movement. Surgeons' predictions according to clinical (tooth show at rest and at the maximum smile) and cephalometric evaluation were documented for the amount of maxillary superior repositioning. Overcorrection or undercorrection was documented for every subject 1 year after the operations. Receiver operating characteristic curve test was used to find a cutoff point in prediction errors and to determine positive predictive value (PPV) and negative predictive value. Forty subjects (14 males and 26 females) were studied. Results showed a significant difference between changes in the tooth show at rest and at the maximum smile line before and after surgery. Analysis of the data demonstrated no correlation between the predictive data and the surgical results. The incidence of undercorrection (25%) was more common than overcorrection (7.5%). The cutoff point for errors in predictions was 5 mm for tooth show at rest and 15 mm at the maximum smile. When the amount of the presurgical tooth show at rest was more than 5 mm, 50.5% of clinical predictions did not match the clinical results (PPV), and 75% of clinical predictions showed the same results when the tooth show was less than 5 mm (negative predictive value). When the amount of presurgical tooth shown in the maximum smile line was more than 15 mm, 75% of clinical predictions did not match with clinical results (PPV), and 25% of the predictions had the same results because the tooth show at the maximum smile was lower than 15 mm. Clinical predictions according to the tooth show at rest and at the maximum smile have a poor correlation with clinical results in maxillary superior repositioning for vertical maxillary excess. The risk of errors in predictions increased when the amount of superior repositioning of the maxilla increased

  12. Closed-loop spontaneous baroreflex transfer function is inappropriate for system identification of neural arc but partly accurate for peripheral arc: predictability analysis.

    PubMed

    Kamiya, Atsunori; Kawada, Toru; Shimizu, Shuji; Sugimachi, Masaru

    2011-04-01

    Although the dynamic characteristics of the baroreflex system have been described by baroreflex transfer functions obtained from open-loop analysis, the predictability of time-series output dynamics from input signals, which should confirm the accuracy of system identification, remains to be elucidated. Moreover, despite theoretical concerns over closed-loop system identification, the accuracy and the predictability of the closed-loop spontaneous baroreflex transfer function have not been evaluated compared with the open-loop transfer function. Using urethane and α-chloralose anaesthetized, vagotomized and aortic-denervated rabbits (n = 10), we identified open-loop baroreflex transfer functions by recording renal sympathetic nerve activity (SNA) while varying the vascularly isolated intracarotid sinus pressure (CSP) according to a binary random (white-noise) sequence (operating pressure ± 20 mmHg), and using a simplified equation to calculate closed-loop-spontaneous baroreflex transfer function while matching CSP with systemic arterial pressure (AP). Our results showed that the open-loop baroreflex transfer functions for the neural and peripheral arcs predicted the time-series SNA and AP outputs from measured CSP and SNA inputs, with r2 of 0.8 ± 0.1 and 0.8 ± 0.1, respectively. In contrast, the closed-loop-spontaneous baroreflex transfer function for the neural arc was markedly different from the open-loop transfer function (enhanced gain increase and a phase lead), and did not predict the time-series SNA dynamics (r2; 0.1 ± 0.1). However, the closed-loop-spontaneous baroreflex transfer function of the peripheral arc partially matched the open-loop transfer function in gain and phase functions, and had limited but reasonable predictability of the time-series AP dynamics (r2, 0.7 ± 0.1). A numerical simulation suggested that a noise predominantly in the neural arc under resting conditions might be a possible mechanism responsible for our findings. Furthermore

  13. Statistical analysis of accurate prediction of local atmospheric optical attenuation with a new model according to weather together with beam wandering compensation system: a season-wise experimental investigation

    NASA Astrophysics Data System (ADS)

    Arockia Bazil Raj, A.; Padmavathi, S.

    2016-07-01

    Atmospheric parameters strongly affect the performance of Free Space Optical Communication (FSOC) system when the optical wave is propagating through the inhomogeneous turbulent medium. Developing a model to get an accurate prediction of optical attenuation according to meteorological parameters becomes significant to understand the behaviour of FSOC channel during different seasons. A dedicated free space optical link experimental set-up is developed for the range of 0.5 km at an altitude of 15.25 m. The diurnal profile of received power and corresponding meteorological parameters are continuously measured using the developed optoelectronic assembly and weather station, respectively, and stored in a data logging computer. Measured meteorological parameters (as input factors) and optical attenuation (as response factor) of size [177147 × 4] are used for linear regression analysis and to design the mathematical model that is more suitable to predict the atmospheric optical attenuation at our test field. A model that exhibits the R2 value of 98.76% and average percentage deviation of 1.59% is considered for practical implementation. The prediction accuracy of the proposed model is investigated along with the comparative results obtained from some of the existing models in terms of Root Mean Square Error (RMSE) during different local seasons in one-year period. The average RMSE value of 0.043-dB/km is obtained in the longer range dynamic of meteorological parameters variations.

  14. Normal Tissue Complication Probability Estimation by the Lyman-Kutcher-Burman Method Does Not Accurately Predict Spinal Cord Tolerance to Stereotactic Radiosurgery

    SciTech Connect

    Daly, Megan E.; Luxton, Gary; Choi, Clara Y.H.; Gibbs, Iris C.; Chang, Steven D.; Adler, John R.; Soltys, Scott G.

    2012-04-01

    Purpose: To determine whether normal tissue complication probability (NTCP) analyses of the human spinal cord by use of the Lyman-Kutcher-Burman (LKB) model, supplemented by linear-quadratic modeling to account for the effect of fractionation, predict the risk of myelopathy from stereotactic radiosurgery (SRS). Methods and Materials: From November 2001 to July 2008, 24 spinal hemangioblastomas in 17 patients were treated with SRS. Of the tumors, 17 received 1 fraction with a median dose of 20 Gy (range, 18-30 Gy) and 7 received 20 to 25 Gy in 2 or 3 sessions, with cord maximum doses of 22.7 Gy (range, 17.8-30.9 Gy) and 22.0 Gy (range, 20.2-26.6 Gy), respectively. By use of conventional values for {alpha}/{beta}, volume parameter n, 50% complication probability dose TD{sub 50}, and inverse slope parameter m, a computationally simplified implementation of the LKB model was used to calculate the biologically equivalent uniform dose and NTCP for each treatment. Exploratory calculations were performed with alternate values of {alpha}/{beta} and n. Results: In this study 1 case (4%) of myelopathy occurred. The LKB model using radiobiological parameters from Emami and the logistic model with parameters from Schultheiss overestimated complication rates, predicting 13 complications (54%) and 18 complications (75%), respectively. An increase in the volume parameter (n), to assume greater parallel organization, improved the predictive value of the models. Maximum-likelihood LKB fitting of {alpha}/{beta} and n yielded better predictions (0.7 complications), with n = 0.023 and {alpha}/{beta} = 17.8 Gy. Conclusions: The spinal cord tolerance to the dosimetry of SRS is higher than predicted by the LKB model using any set of accepted parameters. Only a high {alpha}/{beta} value in the LKB model and only a large volume effect in the logistic model with Schultheiss data could explain the low number of complications observed. This finding emphasizes that radiobiological models

  15. Admission Laboratory Results to Enhance Prediction Models of Postdischarge Outcomes in Cardiac Care.

    PubMed

    Pine, Michael; Fry, Donald E; Hannan, Edward L; Naessens, James M; Whitman, Kay; Reband, Agnes; Qian, Feng; Schindler, Joseph; Sonneborn, Mark; Roland, Jaclyn; Hyde, Linda; Dennison, Barbara A

    Predictive modeling for postdischarge outcomes of inpatient care has been suboptimal. This study evaluated whether admission numerical laboratory data added to administrative models from New York and Minnesota hospitals would enhance the prediction accuracy for 90-day postdischarge deaths without readmission (PD-90) and 90-day readmissions (RA-90) following inpatient care for cardiac patients. Risk-adjustment models for the prediction of PD-90 and RA-90 were designed for acute myocardial infarction, percutaneous cardiac intervention, coronary artery bypass grafting, and congestive heart failure. Models were derived from hospital claims data and were then enhanced with admission laboratory predictive results. Case-level discrimination, goodness of fit, and calibration were used to compare administrative models (ADM) and laboratory predictive models (LAB). LAB models for the prediction of PD-90 were modestly enhanced over ADM, but negligible benefit was seen for RA-90. A consistent predictor of PD-90 and RA-90 was prolonged length of stay outliers from the index hospitalization.

  16. Initial Comparison of Single Cylinder Stirling Engine Computer Model Predictions with Test Results

    NASA Technical Reports Server (NTRS)

    Tew, R. C., Jr.; Thieme, L. G.; Miao, D.

    1979-01-01

    A Stirling engine digital computer model developed at NASA Lewis Research Center was configured to predict the performance of the GPU-3 single-cylinder rhombic drive engine. Revisions to the basic equations and assumptions are discussed. Model predictions with the early results of the Lewis Research Center GPU-3 tests are compared.

  17. The CUPIC algorithm: an accurate model for the prediction of sustained viral response under telaprevir or boceprevir triple therapy in cirrhotic patients.

    PubMed

    Boursier, J; Ducancelle, A; Vergniol, J; Veillon, P; Moal, V; Dufour, C; Bronowicki, J-P; Larrey, D; Hézode, C; Zoulim, F; Fontaine, H; Canva, V; Poynard, T; Allam, S; De Lédinghen, V

    2015-12-01

    Triple therapy using boceprevir or telaprevir remains the reference treatment for genotype 1 chronic hepatitis C in countries where new interferon-free regimens have not yet become available. Antiviral treatment is highly required in cirrhotic patients, but they represent a difficult-to-treat population. We aimed to develop a simple algorithm for the prediction of sustained viral response (SVR) in cirrhotic patients treated with triple therapy. A total of 484 cirrhotic patients from the ANRS CO20 CUPIC cohort treated with triple therapy were randomly distributed into derivation and validation sets. A total of 52.1% of patients achieved SVR. In the derivation set, a D0 score for the prediction of SVR before treatment initiation included the following independent predictors collected at day 0: prior treatment response, gamma-GT, platelets, telaprevir treatment, viral load. To refine the prediction at the early phase of the treatment, a W4 score included as additional parameter the viral load collected at week 4. The D0 and W4 scores were combined in the CUPIC algorithm defining three subgroups: 'no treatment initiation or early stop at week 4', 'undetermined' and 'SVR highly probable'. In the validation set, the rates of SVR in these three subgroups were, respectively, 11.1%, 50.0% and 82.2% (P < 0.001). By replacing the variable 'prior treatment response' with 'IL28B genotype', another algorithm was derived for treatment-naïve patients with similar results. The CUPIC algorithm is an easy-to-use tool that helps physicians weigh their decision between immediately treating cirrhotic patients using boceprevir/telaprevir triple therapy or waiting for new drugs to become available in their country.

  18. Lost in translation: preclinical studies on 3,4-methylenedioxymethamphetamine provide information on mechanisms of action, but do not allow accurate prediction of adverse events in humans

    PubMed Central

    Green, AR; King, MV; Shortall, SE; Fone, KCF

    2012-01-01

    3,4-Methylenedioxymethamphetamine (MDMA) induces both acute adverse effects and long-term neurotoxic loss of brain 5-HT neurones in laboratory animals. However, when choosing doses, most preclinical studies have paid little attention to the pharmacokinetics of the drug in humans or animals. The recreational use of MDMA and current clinical investigations of the drug for therapeutic purposes demand better translational pharmacology to allow accurate risk assessment of its ability to induce adverse events. Recent pharmacokinetic studies on MDMA in animals and humans are reviewed and indicate that the risks following MDMA ingestion should be re-evaluated. Acute behavioural and body temperature changes result from rapid MDMA-induced monoamine release, whereas long-term neurotoxicity is primarily caused by metabolites of the drug. Therefore acute physiological changes in humans are fairly accurately mimicked in animals by appropriate dosing, although allometric dosing calculations have little value. Long-term changes require MDMA to be metabolized in a similar manner in experimental animals and humans. However, the rate of metabolism of MDMA and its major metabolites is slower in humans than rats or monkeys, potentially allowing endogenous neuroprotective mechanisms to function in a species specific manner. Furthermore acute hyperthermia in humans probably limits the chance of recreational users ingesting sufficient MDMA to produce neurotoxicity, unlike in the rat. MDMA also inhibits the major enzyme responsible for its metabolism in humans thereby also assisting in preventing neurotoxicity. These observations question whether MDMA alone produces long-term 5-HT neurotoxicity in human brain, although when taken in combination with other recreational drugs it may induce neurotoxicity. LINKED ARTICLES This article is commented on by Parrott, pp. 1518–1520 of this issue. To view this commentary visit http://dx.doi.org/10.1111/j.1476-5381.2012.01941.x and to view the the

  19. Ab initio molecular dynamics of liquid water using embedded-fragment second-order many-body perturbation theory towards its accurate property prediction

    PubMed Central

    Willow, Soohaeng Yoo; Salim, Michael A.; Kim, Kwang S.; Hirata, So

    2015-01-01

    A direct, simultaneous calculation of properties of a liquid using an ab initio electron-correlated theory has long been unthinkable. Here we present structural, dynamical, and response properties of liquid water calculated by ab initio molecular dynamics using the embedded-fragment spin-component-scaled second-order many-body perturbation method with the aug-cc-pVDZ basis set. This level of theory is chosen as it accurately and inexpensively reproduces the water dimer potential energy surface from the coupled-cluster singles, doubles, and noniterative triples with the aug-cc-pVQZ basis set, which is nearly exact. The calculated radial distribution function, self-diffusion coefficient, coordinate number, and dipole moment, as well as the infrared and Raman spectra are in excellent agreement with experimental results. The shapes and widths of the OH stretching bands in the infrared and Raman spectra and their isotropic-anisotropic Raman noncoincidence, which reflect the diverse local hydrogen-bond environment, are also reproduced computationally. The simulation also reveals intriguing dynamic features of the environment, which are difficult to probe experimentally, such as a surprisingly large fluctuation in the coordination number and the detailed mechanism by which the hydrogen donating water molecules move across the first and second shells, thereby causing this fluctuation. PMID:26400690

  20. Accurate Prediction of Glucuronidation of Structurally Diverse Phenolics by Human UGT1A9 Using Combined Experimental and In Silico Approaches

    PubMed Central

    Wu, Baojian; Wang, Xiaoqiang; Zhang, Shuxing; Hu, Ming

    2012-01-01

    Purpose The catalytic selectivity of human UGT1A9, an important membrane-bound enzyme catalyzing glucuronidation of xenobiotics were determined experimentally using 145 phenolics, and analyzed by 3D-QSAR methods. Methods The catalytic efficiency of UGT1A9 was determined by kinetic profiling. Quantitative structure activity relationships were analyzed using the CoMFA and CoMSIA techniques. Molecular alignment of the substrate structures was made by superimposing the glucuronidation site and its adjacent aromatic ring to achieve maximal steric overlap. For a substrate with multiple active glucuronidation sites, each site was considered as a separate substrate. Results The 3D-QSAR analyses produced statistically reliable models with good predictive power (CoMFA: q2 = 0.548, r2= 0.949, r2pred = 0.775; CoMSIA: q2 = 0.579, r2= 0.876, r2pred = 0.700). The contour coefficient maps were applied to elucidate structural features among substrates that are responsible for the selectivity differences. Furthermore, the contour coefficient maps were overlaid in the catalytic pocket of a homology model of UGT1A9; this enabled us to identify the UGT1A9 catalytic pocket with a high degree of confidence. Conclusion The CoMFA/CoMSIA models can predict the substrate selectivity and in vitro clearance of UGT1A9. Our findings also provide a possible molecular basis for understanding UGT1A9 functions and its substrate selectivity. PMID:22302521

  1. Stereotactic hypofractionated accurate radiotherapy of the prostate (SHARP), 33.5 Gy in five fractions for localized disease: First clinical trial results

    SciTech Connect

    Madsen, Berit L. . E-mail: ronblm@vmmc.org; Hsi, R. Alex; Pham, Huong T.; Fowler, Jack F.; Esagui, Laura C.; Corman, John

    2007-03-15

    Purpose: To evaluate the feasibility and toxicity of stereotactic hypofractionated accurate radiotherapy (SHARP) for localized prostate cancer. Methods and Materials: A Phase I/II trial of SHARP performed for localized prostate cancer using 33.5 Gy in 5 fractions, calculated to be biologically equivalent to 78 Gy in 2 Gy fractions ({alpha}/{beta} ratio of 1.5 Gy). Noncoplanar conformal fields and daily stereotactic localization of implanted fiducials were used for treatment. Genitourinary (GU) and gastrointestinal (GI) toxicity were evaluated by American Urologic Association (AUA) score and Common Toxicity Criteria (CTC). Prostate-specific antigen (PSA) values and self-reported sexual function were recorded at specified follow-up intervals. Results: The study includes 40 patients. The median follow-up is 41 months (range, 21-60 months). Acute toxicity Grade 1-2 was 48.5% (GU) and 39% (GI); 1 acute Grade 3 GU toxicity. Late Grade 1-2 toxicity was 45% (GU) and 37% (GI). No late Grade 3 or higher toxicity was reported. Twenty-six patients reported potency before therapy; 6 (23%) have developed impotence. Median time to PSA nadir was 18 months with the majority of nadirs less than 1.0 ng/mL. The actuarial 48-month biochemical freedom from relapse is 70% for the American Society for Therapeutic Radiology and Oncology definition and 90% by the alternative nadir + 2 ng/mL failure definition. Conclusions: SHARP for localized prostate cancer is feasible with minimal acute or late toxicity. Dose escalation should be possible.

  2. Regression shrinkage and neural models in predicting the results of 400-metres hurdles races

    PubMed Central

    Iskra, J; Maszczyk, A; Nawrocka, M

    2016-01-01

    This study presents the application of regression shrinkage and artificial neural networks in predicting the results of 400-metres hurdles races. The regression models predict the results for suggested training loads in the selected three-month training period. The material of the research was based on training data of 21 Polish hurdlers from the Polish National Athletics Team Association. The athletes were characterized by a high level of performance. To assess the predictive ability of the constructed models a method of leave-one-out cross-validation was used. The analysis showed that the method generating the smallest prediction error was the LASSO regression extended by quadratic terms. The optimal model generated the prediction error of 0.59 s. Otherwise the optimal set of input variables (by reducing 8 of the 27 predictors) was defined. The results obtained justify the use of regression shrinkage in predicting sports outcomes. The resulting model can be used as a tool to assist the coach in planning training loads in a selected training period. PMID:28090147

  3. Is scoring system of computed tomography based metric parameters can accurately predicts shock wave lithotripsy stone-free rates and aid in the development of treatment strategies?

    PubMed Central

    Badran, Yasser Ali; Abdelaziz, Alsayed Saad; Shehab, Mohamed Ahmed; Mohamed, Hazem Abdelsabour Dief; Emara, Absel-Aziz Ali; Elnabtity, Ali Mohamed Ali; Ghanem, Maged Mohammed; ELHelaly, Hesham Abdel Azim

    2016-01-01

    Objective: The objective was to determine the predicting success of shock wave lithotripsy (SWL) using a combination of computed tomography based metric parameters to improve the treatment plan. Patients and Methods: Consecutive 180 patients with symptomatic upper urinary tract calculi 20 mm or less were enrolled in our study underwent extracorporeal SWL were divided into two main groups, according to the stone size, Group A (92 patients with stone ≤10 mm) and Group B (88 patients with stone >10 mm). Both groups were evaluated, according to the skin to stone distance (SSD) and Hounsfield units (≤500, 500–1000 and >1000 HU). Results: Both groups were comparable in baseline data and stone characteristics. About 92.3% of Group A rendered stone-free, whereas 77.2% were stone-free in Group B (P = 0.001). Furthermore, in both group SWL success rates was a significantly higher for stones with lower attenuation <830 HU than with stones >830 HU (P < 0.034). SSD were statistically differences in SWL outcome (P < 0.02). Simultaneous consideration of three parameters stone size, stone attenuation value, and SSD; we found that stone-free rate (SFR) was 100% for stone attenuation value <830 HU for stone <10 mm or >10 mm but total number SWL sessions and shock waves required for the larger stone group were higher than in the smaller group (P < 0.01). Furthermore, SFR was 83.3% and 37.5% for stone <10 mm, mean HU >830, SSD 90 mm and SSD >120 mm, respectively. On the other hand, SFR was 52.6% and 28.57% for stone >10 mm, mean HU >830, SSD <90 mm and SSD >120 mm, respectively. Conclusion: Stone size, stone density (HU), and SSD is simple to calculate and can be reported by radiologists to applying combined score help to augment predictive power of SWL, reduce cost, and improving of treatment strategies. PMID:27141192

  4. SNP development from RNA-seq data in a nonmodel fish: how many individuals are needed for accurate allele frequency prediction?

    PubMed

    Schunter, C; Garza, J C; Macpherson, E; Pascual, M

    2014-01-01

    Single nucleotide polymorphisms (SNPs) are rapidly becoming the marker of choice in population genetics due to a variety of advantages relative to other markers, including higher genomic density, data quality, reproducibility and genotyping efficiency, as well as ease of portability between laboratories. Advances in sequencing technology and methodologies to reduce genomic representation have made the isolation of SNPs feasible for nonmodel organisms. RNA-seq is one such technique for the discovery of SNPs and development of markers for large-scale genotyping. Here, we report the development of 192 validated SNP markers for parentage analysis in Tripterygion delaisi (the black-faced blenny), a small rocky-shore fish from the Mediterranean Sea. RNA-seq data for 15 individual samples were used for SNP discovery by applying a series of selection criteria. Genotypes were then collected from 1599 individuals from the same population with the resulting loci. Differences in heterozygosity and allele frequencies were found between the two data sets. Heterozygosity was lower, on average, in the population sample, and the mean difference between the frequencies of particular alleles in the two data sets was 0.135 ± 0.100. We used bootstrap resampling of the sequence data to predict appropriate sample sizes for SNP discovery. As cDNA library production is time-consuming and expensive, we suggest that using seven individuals for RNA sequencing reduces the probability of discarding highly informative SNP loci, due to lack of observed polymorphism, whereas use of more than 12 samples does not considerably improve prediction of true allele frequencies.

  5. Accurate prediction of hard-sphere virial coefficients B6 to B12 from a compressibility-based equation of state

    NASA Astrophysics Data System (ADS)

    Hansen-Goos, Hendrik

    2016-04-01

    We derive an analytical equation of state for the hard-sphere fluid that is within 0.01% of computer simulations for the whole range of the stable fluid phase. In contrast, the commonly used Carnahan-Starling equation of state deviates by up to 0.3% from simulations. The derivation uses the functional form of the isothermal compressibility from the Percus-Yevick closure of the Ornstein-Zernike relation as a starting point. Two additional degrees of freedom are introduced, which are constrained by requiring the equation of state to (i) recover the exact fourth virial coefficient B4 and (ii) involve only integer coefficients on the level of the ideal gas, while providing best possible agreement with the numerical result for B5. Virial coefficients B6 to B10 obtained from the equation of state are within 0.5% of numerical computations, and coefficients B11 and B12 are within the error of numerical results. We conjecture that even higher virial coefficients are reliably predicted.

  6. Accurate prediction of hard-sphere virial coefficients B6 to B12 from a compressibility-based equation of state.

    PubMed

    Hansen-Goos, Hendrik

    2016-04-28

    We derive an analytical equation of state for the hard-sphere fluid that is within 0.01% of computer simulations for the whole range of the stable fluid phase. In contrast, the commonly used Carnahan-Starling equation of state deviates by up to 0.3% from simulations. The derivation uses the functional form of the isothermal compressibility from the Percus-Yevick closure of the Ornstein-Zernike relation as a starting point. Two additional degrees of freedom are introduced, which are constrained by requiring the equation of state to (i) recover the exact fourth virial coefficient B4 and (ii) involve only integer coefficients on the level of the ideal gas, while providing best possible agreement with the numerical result for B5. Virial coefficients B6 to B10 obtained from the equation of state are within 0.5% of numerical computations, and coefficients B11 and B12 are within the error of numerical results. We conjecture that even higher virial coefficients are reliably predicted.

  7. TU-EF-204-01: Accurate Prediction of CT Tube Current Modulation: Estimating Tube Current Modulation Schemes for Voxelized Patient Models Used in Monte Carlo Simulations

    SciTech Connect

    McMillan, K; Bostani, M; McNitt-Gray, M; McCollough, C

    2015-06-15

    Purpose: Most patient models used in Monte Carlo-based estimates of CT dose, including computational phantoms, do not have tube current modulation (TCM) data associated with them. While not a problem for fixed tube current simulations, this is a limitation when modeling the effects of TCM. Therefore, the purpose of this work was to develop and validate methods to estimate TCM schemes for any voxelized patient model. Methods: For 10 patients who received clinically-indicated chest (n=5) and abdomen/pelvis (n=5) scans on a Siemens CT scanner, both CT localizer radiograph (“topogram”) and image data were collected. Methods were devised to estimate the complete x-y-z TCM scheme using patient attenuation data: (a) available in the Siemens CT localizer radiograph/topogram itself (“actual-topo”) and (b) from a simulated topogram (“sim-topo”) derived from a projection of the image data. For comparison, the actual TCM scheme was extracted from the projection data of each patient. For validation, Monte Carlo simulations were performed using each TCM scheme to estimate dose to the lungs (chest scans) and liver (abdomen/pelvis scans). Organ doses from simulations using the actual TCM were compared to those using each of the estimated TCM methods (“actual-topo” and “sim-topo”). Results: For chest scans, the average differences between doses estimated using actual TCM schemes and estimated TCM schemes (“actual-topo” and “sim-topo”) were 3.70% and 4.98%, respectively. For abdomen/pelvis scans, the average differences were 5.55% and 6.97%, respectively. Conclusion: Strong agreement between doses estimated using actual and estimated TCM schemes validates the methods for simulating Siemens topograms and converting attenuation data into TCM schemes. This indicates that the methods developed in this work can be used to accurately estimate TCM schemes for any patient model or computational phantom, whether a CT localizer radiograph is available or not

  8. Full-Dimensional Potential Energy and Dipole Moment Surfaces of GeH4 Molecule and Accurate First-Principle Rotationally Resolved Intensity Predictions in the Infrared.

    PubMed

    Nikitin, A V; Rey, M; Rodina, A; Krishna, B M; Tyuterev, Vl G

    2016-11-17

    Nine-dimensional potential energy surface (PES) and dipole moment surface (DMS) of the germane molecule are constructed using extended ab initio CCSD(T) calculations at 19 882 points. PES analytical representation is determined as an expansion in nonlinear symmetry adapted products of orthogonal and internal coordinates involving 340 parameters up to eighth order. Minor empirical refinement of the equilibrium geometry and of four quadratic parameters of the PES computed at the CCSD(T)/aug-cc-pVQZ-DK level of the theory yielded the accuracy below 1 cm(-1) for all experimentally known vibrational band centers of five stable isotopologues of (70)GeH4, (72)GeH4, (73)GeH4, (74)GeH4, and (76)GeH4 up to 8300 cm(-1). The optimized equilibrium bond re = 1.517 594 Å is very close to best ab initio values. Rotational energies up to J = 15 are calculated using potential expansion in normal coordinate tensors with maximum errors of 0.004 and 0.0006 cm(-1) for (74)GeH4 and (76)GeH4. The DMS analytical representation is determined through an expansion in symmetry-adapted products of internal nonlinear coordinates involving 967 parameters up to the sixth order. Vibration-rotation line intensities of five stable germane isotopologues were calculated from purely ab initio DMS using nuclear motion variational calculations with a full account of the tetrahedral symmetry of the molecules. For the first time a good overall agreement of main absorption features with experimental rotationally resolved Pacific Northwest National Laboratory spectra was achieved in the entire range of 700-5300 cm(-1). It was found that very accurate description of state-dependent isotopic shifts is mandatory to correctly describe complex patterns of observed spectra at natural isotopic abundance resulting from the superposition of five stable isotopologues. The data obtained in this work will be made available through the TheoReTS information system.

  9. Sound absorption of porous substrates covered by foliage: experimental results and numerical predictions.

    PubMed

    Ding, Lei; Van Renterghem, Timothy; Botteldooren, Dick; Horoshenkov, Kirill; Khan, Amir

    2013-12-01

    The influence of loose plant leaves on the acoustic absorption of a porous substrate is experimentally and numerically studied. Such systems are typical in vegetative walls, where the substrate has strong acoustical absorbing properties. Both experiments in an impedance tube and theoretical predictions show that when a leaf is placed in front of such a porous substrate, its absorption characteristics markedly change (for normal incident sound). Typically, there is an unaffected change in the low frequency absorption coefficient (below 250 Hz), an increase in the middle frequency absorption coefficient (500-2000 Hz) and a decrease in the absorption at higher frequencies. The influence of leaves becomes most pronounced when the substrate has a low mass density. A combination of the Biot's elastic frame porous model, viscous damping in the leaf boundary layers and plate vibration theory is implemented via a finite-difference time-domain model, which is able to predict accurately the absorption spectrum of a leaf above a porous substrate system. The change in the absorption spectrum caused by the leaf vibration can be modeled reasonably well assuming the leaf and porous substrate properties are uniform.

  10. Correlation of FEM/BEM Vibroacoustic Prediction to System-Level Acoustic Test Results

    NASA Astrophysics Data System (ADS)

    Rodrigues, G.; Ngan, I.; Santiago-Prowald, J.

    2014-06-01

    Coupled FEM/BEM vibroacoustic analyses are employed for deriving spacecraft random vibration environments and supporting the design of low aerial density structures. They offer deterministic predictions which are very accurate at low-frequency and meaningful across all the spectrum of interest for vibroacoustic response.An assessment of the standard procedure of FEM/BEM vibroacoustic analyses was carried out by correlation to measurements from system-level tests of several spacecraft. This allowed a quantification of the typical errors committed, and concluded on the adequacy of applying the standard factor of safety +4dB to the predictions. It was observed that a major source of error is the lack of representativeness of the models of the spacecraft, which adds to the diffuse field idealization made on the acoustic environment inside the fairing and the test chambers. In particular, it was observed a clear impact from a lack of detail of the damping of the structure, and an often crude lumped representation of units and equipment as well as tanks and fixations.

  11. A machine-learning approach reveals that alignment properties alone can accurately predict inference of lateral gene transfer from discordant phylogenies.

    PubMed

    Roettger, Mayo; Martin, William; Dagan, Tal

    2009-09-01

    Among the methods currently used in phylogenomic practice to detect the presence of lateral gene transfer (LGT), one of the most frequently employed is the comparison of gene tree topologies for different genes. In cases where the phylogenies for different genes are incompatible, or discordant, for well-supported branches there are three simple interpretations for the result: 1) gene duplications (paralogy) followed by many independent gene losses have occurred, 2) LGT has occurred, or 3) the phylogeny is well supported but for reasons unknown is nonetheless incorrect. Here, we focus on the third possibility by examining the properties of 22,437 published multiple sequence alignments, the Bayesian maximum likelihood trees for which either do or do not suggest the occurrence of LGT by the criterion of discordant branches. The alignments that produce discordant phylogenies differ significantly in several salient alignment properties from those that do not. Using a support vector machine, we were able to predict the inference of discordant tree topologies with up to 80% accuracy from alignment properties alone.

  12. Accurate measurements of vadose zone fluxes using automated equilibrium tension plate lysimeters: A synopsis of results from the Spydia research facility, New Zealand.

    NASA Astrophysics Data System (ADS)

    Wöhling, Thomas; Barkle, Greg; Stenger, Roland; Moorhead, Brian; Wall, Aaron; Clague, Juliet

    2014-05-01

    Automated equilibrium tension plate lysimeters (AETLs) are arguably the most accurate method to measure unsaturated water and contaminant fluxes below the root zone at the scale of up to 1 m². The AETL technique utilizes a porous sintered stainless-steel plate to provide a comparatively large sampling area with a continuously controlled vacuum that is in "equilibrium" with the surrounding vadose zone matric pressure to ensure measured fluxes represent those under undisturbed conditions. This novel lysimeter technique was used at an intensive research site for investigations of contaminant pathways from the land surface to the groundwater on a sheep and beef farm under pastoral land use in the Tutaeuaua subcatchment, New Zealand. The Spydia research facility was constructed in 2005 and was fully operational between 2006 and 2011. Extending from a central access caisson, 15 separately controlled AETLs with 0.2 m² surface area were installed at five depths between 0.4 m and 5.1 m into the undisturbed volcanic vadose zone materials. The unique setup of the facility ensured minimum interference of the experimental equipment and external factors with the measurements. Over the period of more than five years, a comprehensive data set was collected at each of the 15 AETL locations which comprises of time series of soil water flux, pressure head, volumetric water contents, and soil temperature. The soil water was regularly analysed for EC, pH, dissolved carbon, various nitrogen compounds (including nitrate, ammonia, and organic N), phosphorus, bromide, chloride, sulphate, silica, and a range of other major ions, as well as for various metals. Climate data was measured directly at the site (rainfall) and a climate station at 500m distance. The shallow groundwater was sampled at three different depths directly from the Spydia caisson and at various observation wells surrounding the facility. Two tracer experiments were conducted at the site in 2009 and 2010. In the 2009

  13. Variability in the Propagation Phase of CFD-Based Noise Prediction: Summary of Results From Category 8 of the BANC-III Workshop

    NASA Technical Reports Server (NTRS)

    Lopes, Leonard; Redonnet, Stephane; Imamura, Taro; Ikeda, Tomoaki; Zawodny, Nikolas; Cunha, Guilherme

    2015-01-01

    The usage of Computational Fluid Dynamics (CFD) in noise prediction typically has been a two part process: accurately predicting the flow conditions in the near-field and then propagating the noise from the near-field to the observer. Due to the increase in computing power and the cost benefit when weighed against wind tunnel testing, the usage of CFD to estimate the local flow field of complex geometrical structures has become more routine. Recently, the Benchmark problems in Airframe Noise Computation (BANC) workshops have provided a community focus on accurately simulating the local flow field near the body with various CFD approaches. However, to date, little effort has been given into assessing the impact of the propagation phase of noise prediction. This paper includes results from the BANC-III workshop which explores variability in the propagation phase of CFD-based noise prediction. This includes two test cases: an analytical solution of a quadrupole source near a sphere and a computational solution around a nose landing gear. Agreement between three codes was very good for the analytic test case, but CFD-based noise predictions indicate that the propagation phase can introduce 3dB or more of variability in noise predictions.

  14. Prediction of Asthma Exacerbations in Children by Innovative Exhaled Inflammatory Markers: Results of a Longitudinal Study

    PubMed Central

    van Vliet, Dillys; Alonso, Ariel; Rijkers, Ger; Heynens, Jan; Rosias, Philippe; Muris, Jean; Jöbsis, Quirijn; Dompeling, Edward

    2015-01-01

    Background In asthma management guidelines the primary goal of treatment is asthma control. To date, asthma control, guided by symptoms and lung function, is not optimal in many children and adults. Direct monitoring of airway inflammation in exhaled breath may improve asthma control and reduce the number of exacerbations. Aim 1) To study the use of fractional exhaled nitric oxide (FeNO) and inflammatory markers in exhaled breath condensate (EBC), in the prediction of asthma exacerbations in a pediatric population. 2) To study the predictive power of these exhaled inflammatory markers combined with clinical parameters. Methods 96 asthmatic children were included in this one-year prospective observational study, with clinical visits every 2 months. Between visits, daily symptom scores and lung function were recorded using a home monitor. During clinical visits, asthma control and FeNO were assessed. Furthermore, lung function measurements were performed and EBC was collected. Statistical analysis was performed using a test dataset and validation dataset for 1) conditionally specified models, receiver operating characteristic-curves (ROC-curves); 2) k-nearest neighbors algorithm. Results Three conditionally specified predictive models were constructed. Model 1 included inflammatory markers in EBC alone, model 2 included FeNO plus clinical characteristics and the ACQ score, and model 3 included all the predictors used in model 1 and 2. The area under the ROC-curves was estimated as 47%, 54% and 59% for models 1, 2 and 3 respectively. The k-nearest neighbors predictive algorithm, using the information of all the variables in model 3, produced correct predictions for 52% of the exacerbations in the validation dataset. Conclusion The predictive power of FeNO and inflammatory markers in EBC for prediction of an asthma exacerbation was low, even when combined with clinical characteristics and symptoms. Qualitative improvement of the chemical analysis of EBC may lead to a

  15. Beam-waveguide antenna performance predictions with comparisons to experimental results

    NASA Technical Reports Server (NTRS)

    Bathker, Dan A.; Veruttipong, Watt; Otoshi, Tom Y.; Cramer, Paul W., Jr.

    1992-01-01

    An overview of a NASA/JPL antenna project is presented, with specific focus on the methodology used to predict the microwave performance of a 34-m-diameter beam-waveguide (BWG) reflector antenna, designated DSS 13 (Deep Space Station 13). DSS 13 is the R&D facility serving the NASA/JPL Deep Space Network. Microwave performance predictions as well as a summary of test results for the antenna are given. The antenna has Cassegrain and centerline BWG operating modes at X-band (8.450-GHz) and Ka-band (32-GHz) frequencies. The performance predictions regarding antenna area efficiencies, corresponding beampeak gains, and for several (but not all) operating noise temperatures are found to agree reasonably well with the corresponding experimental results.

  16. The M. D. Anderson Symptom Inventory-Head and Neck Module, a Patient-Reported Outcome Instrument, Accurately Predicts the Severity of Radiation-Induced Mucositis

    SciTech Connect

    Rosenthal, David I. Mendoza, Tito R.; Chambers, Mark; Burkett, V. Shannon; Garden, Adam S.; Hessell, Amy C.; Lewin, Jan S.; Ang, K. Kian; Kies, Merrill S.

    2008-12-01

    Purpose: To compare the M. D. Anderson Symptom Inventory-Head and Neck (MDASI-HN) module, a symptom burden instrument, with the Functional Assessment of Cancer Therapy-Head and Neck (FACT-HN) module, a quality-of-life instrument, for the assessment of mucositis in patients with head-and-neck cancer treated with radiotherapy and to identify the most distressing symptoms from the patient's perspective. Methods and Materials: Consecutive patients with head-and-neck cancer (n = 134) completed the MDASI-HN and FACT-HN before radiotherapy (time 1) and after 6 weeks of radiotherapy or chemoradiotherapy (time 2). The mean global and subscale scores for each instrument were compared with the objective mucositis scores determined from the National Cancer Institute Common Terminology Criteria for Adverse Events, version 3.0. Results: The global and subscale scores for each instrument showed highly significant changes from time 1 to time 2 and a significant correlation with the objective mucositis scores at time 2. Only the MDASI scores, however, were significant predictors of objective Common Terminology Criteria for Adverse Events mucositis scores on multivariate regression analysis (standardized regression coefficient, 0.355 for the global score and 0.310 for the head-and-neck cancer-specific score). Most of the moderate and severe symptoms associated with mucositis as identified on the MDASI-HN are not present on the FACT-HN. Conclusion: Both the MDASI-HN and FACT-HN modules can predict the mucositis scores. However, the MDASI-HN, a symptom burden instrument, was more closely associated with the severity of radiation-induced mucositis than the FACT-HN on multivariate regression analysis. This greater association was most likely related to the inclusion of a greater number of face-valid mucositis-related items in the MDASI-HN compared with the FACT-HN.

  17. Interspecies scaling of urinary excretory amounts of nine drugs belonging to different therapeutic areas with diverse chemical structures - accurate prediction of the human urinary excretory amounts.

    PubMed

    Bhamidipati, Ravi Kanth; Mullangi, Ramesh; Srinivas, Nuggehally R

    2017-02-01

    1. The human urinary excretory amounts of total drug (parent + metabolites) were predicted for nine drugs with diverse chemical structures using simple allometry. The drugs used for scaling were cephapirin, olanzapine, labetolol, carisbamate, voriconazole, tofacitinib, nevirapine, ropinirole, and cyclindole. 2. The traditional allometric scaling was attempted using Y = aW(b) relationship. The corresponding predicted urinary amounts were converted into % recovery by using appropriate human dose. Appropriate statistical tests comprising of fold-difference (predicted/observed values) and error calculations (MAE and RMSE) were performed. 3. The interspecies scaling of all nine drugs tested showed excellent correlation (r > 0.9672). The predictions for eight out of nine drugs (exception was cephaphirin) were contained within 0.80-1.25 fold-differences. The MAE and RMSE were within ± 18% and 14.64%, respectively. 4. The present work supported the potential application of prospective allometry scaling to predict the urinary excretory amounts of the total drug and gauge any issues for the renal handling of the total drug.

  18. Results of Instrument Observations and Adaptive Prediction of Thermoabrasion of Banks of the Vilyui Reservoir

    SciTech Connect

    Velikin, S. A.; Sobol', I. S.; Sobol', S. V.; Khokhlov, D. N.

    2013-11-15

    Quantitative data derived from observations of reformation of the thermoabrasive banks of the Viliyui Reservoir in Yakutia during the service period from 1972 through 2011, and results of analytical prediction of bank formations over the next 20 years for purposes of monitoring the ecological safety of this water body are presented.

  19. Renal parenchymal histopathology predicts life-threatening chronic kidney disease as a result of radical nephrectomy.

    PubMed

    Sejima, Takehiro; Honda, Masashi; Takenaka, Atsushi

    2015-01-01

    The preoperative prediction of post-radical nephrectomy renal insufficiency plays an important role in the decision-making process regarding renal surgery options. Furthermore, the prediction of both postoperative renal insufficiency and postoperative cardiovascular disease occurrence, which is suggested to be an adverse consequence caused by renal insufficiency, contributes to the preoperative policy decision as well as the precise informed consent for a renal cell carcinoma patient. Preoperative nomograms for the prediction of post-radical nephrectomy renal insufficiency, calculated using patient backgrounds, are advocated. The use of these nomograms together with other types of nomograms predicting oncological outcome is beneficial. Post-radical nephrectomy attending physicians can predict renal insufficiency based on the normal renal parenchymal pathology in addition to preoperative patient characteristics. It is suggested that a high level of global glomerulosclerosis in nephrectomized normal renal parenchyma is closely associated with severe renal insufficiency. Some studies showed that post-radical nephrectomy severe renal insufficiency might have an association with increased mortality as a result of cardiovascular disease. Therefore, such pathophysiology should be recognized as life-threatening, surgically-related chronic kidney disease. On the contrary, the investigation of the prediction of mild post-radical nephrectomy renal insufficiency, which is not related to adverse consequences in the postoperative long-term period, is also promising because the prediction of mild renal insufficiency might be the basis for the substitution of radical nephrectomy for nephron-sparing surgery in technically difficult or compromised cases. The deterioration of quality of life caused by post-radical nephrectomy renal insufficiency should be investigated in conjunction with life-threatening matters.

  20. Link prediction in a MeSH co-occurrence network: preliminary results.

    PubMed

    Kastrin, Andrej; Rindflesch, Thomas C; Hristovski, Dimitar

    2014-01-01

    Literature-based discovery (LBD) refers to automatic discovery of implicit relations from the scientific literature. Co-occurrence associations between biomedical concepts are commonly used in LBD. These co-occurrences can be represented as a network that consists of a set of nodes representing concepts and a set of edges representing their relationships (or links). In this paper we propose and evaluate a methodology for link prediction of implicit connections in a network of co-occurring Medical Subject Headings (MeSH®). The proposed approach is complementary to, and may augment, existing LBD methods. Link prediction was performed using Jaccard and Adamic-Adar similarity measures. The preliminary results showed high prediction performance, with area under the ROC curve of 0.78 and 0.82 for the two similarity measures, respectively.

  1. New numerical results and novel effective string predictions for Wilson loops

    NASA Astrophysics Data System (ADS)

    Billó, M.; Caselle, M.; Pellegrini, R.

    2012-01-01

    We compute the prediction of the Nambu-Goto effective string model for a rectangular Wilson loop up to three loops. This is done through the use of an operatorial, first order formulation and of the open string analogues of boundary states. This result is interesting since there are universality theorems stating that the predictions up to three loops are common to all effective string models. To test the effective string prediction, we use a Montecarlo evaluation, in the 3 d Ising gauge model, of an observable (the ratio of two Wilson loops with the same perimeter) for which boundary effects are relatively small. Our simulation attains a level of precision which is sufficient to test the two-loop correction. The three-loop correction seems to go in the right direction, but is actually yet beyond the reach of our simulation, since its effect is comparable with the statistical errors of the latter.

  2. Prognosis of locally advanced rectal cancer can be predicted more accurately using pre- and post-chemoradiotherapy neutrophil-lymphocyte ratios in patients who received preoperative chemoradiotherapy

    PubMed Central

    Sung, SooYoon; Park, Eun Young; Kay, Chul Seung

    2017-01-01

    Purpose The neutrophil-lymphocyte ratio (NLR) has been suggested as an inflammation-related factor, but also as an indicator of systemic anti-tumor immunity. We aimed to evaluate the prognostic value of the NLR and to propose a proper cut-off value in patients with locally advanced rectal cancer who received preoperative chemoradiation (CRT) followed by curative total mesorectal excision (TME). Methods A total of 110 rectal cancer patients with clinical T3-4 or node-positive disease were retrospectively analyzed. The NLR value before preoperative CRT (pre-CRT NLR) and the NLR value between preoperative CRT and surgery (post-CRT NLR) were obtained. Using a maximally selected log-rank test, cut-off values were determined as 1.75 for the pre-CRT NLR and 5.14 for the post-CRT NLR. Results Patients were grouped as follows: group A, pre-CRT NLR ≤ 1.75 and post-CRT NLR ≤ 5.14 (n = 29); group B, pre-CRT NLR > 1.75 and post-CRT NLR ≤ 5.14, or pre-CRT NLR ≤ 1.75 and post-CRT NLR > 5.14 (n = 61); group C, pre-CRT NLR > 1.75 and post-CRT NLR > 5.14 (n = 20). The median follow-up time was 31.1 months. The 3-year disease-free survival (DFS) and overall survival (OS) rates showed significant differences between the NLR groups (3-year DFS rate: 92.7% vs. 73.0% vs. 47.3%, for group A, B, and C, respectively, p = 0.018; 3-year OS rate: 96.0% vs. 85.5% vs. 59.8%, p = 0.034). Multivariate analysis revealed that the NLR was an independent prognostic factor for DFS (p = 0.028). Conclusion Both the pre-CRT NLR and the post-CRT NLR have a predictive value for the prognosis of patients with locally advanced rectal cancer treated with preoperative CRT followed by curative TME and adjuvant chemotherapy. A persistently elevated post-CRT NLR may be an indicator of an increased risk of distant metastasis. PMID:28291841

  3. Results from baseline tests of the SPRE I and comparison with code model predictions

    SciTech Connect

    Cairelli, J.E.; Geng, S.M.; Skupinski, R.C.

    1994-09-01

    The Space Power Research Engine (SPRE), a free-piston Stirling engine with linear alternator, is being tested at the NASA Lewis Research Center as part of the Civil Space Technology Initiative (CSTI) as a candidate for high capacity space power. This paper presents results of base-line engine tests at design and off-design operating conditions. The test results are compared with code model predictions.

  4. Thermal conductivity of silicic tuffs: predictive formalism and comparison with preliminary experimental results

    SciTech Connect

    Lappin, A. R.

    1980-07-01

    Performance of both near- and far-field thermomechanical calculations to assess the feasibility of waste disposal in silicic tuffs requires a formalism for predicting thermal conductivity of a broad range of tuffs. This report summarizes the available thermal conductivity data for silicate phases that occur in tuffs and describes several grain-density and conductivity trends which may be expected to result from post-emplacement alteration. A bounding curve is drawn that predicts the minimum theoretical matrix (zero-porosity) conductivity for most tuffs as a function of grain density. Comparison of experimental results with this curve shows that experimental conductivities are consistently lower at any given grain density. Use of the lowered bounding curve and an effective gas conductivity of 0.12 W/m{sup 0}C allows conservative prediction of conductivity for a broad range of tuff types. For the samples measured here, use of the predictive curve allows estimation of conductivity to within 15% or better, with one exception. Application and possible improvement of the formalism are also discussed.

  5. Analyzing Medical Image Search Behavior: Semantics and Prediction of Query Results.

    PubMed

    De-Arteaga, Maria; Eggel, Ivan; Kahn, Charles E; Müller, Henning

    2015-10-01

    Log files of information retrieval systems that record user behavior have been used to improve the outcomes of retrieval systems, understand user behavior, and predict events. In this article, a log file of the ARRS GoldMiner search engine containing 222,005 consecutive queries is analyzed. Time stamps are available for each query, as well as masked IP addresses, which enables to identify queries from the same person. This article describes the ways in which physicians (or Internet searchers interested in medical images) search and proposes potential improvements by suggesting query modifications. For example, many queries contain only few terms and therefore are not specific; others contain spelling mistakes or non-medical terms that likely lead to poor or empty results. One of the goals of this report is to predict the number of results a query will have since such a model allows search engines to automatically propose query modifications in order to avoid result lists that are empty or too large. This prediction is made based on characteristics of the query terms themselves. Prediction of empty results has an accuracy above 88%, and thus can be used to automatically modify the query to avoid empty result sets for a user. The semantic analysis and data of reformulations done by users in the past can aid the development of better search systems, particularly to improve results for novice users. Therefore, this paper gives important ideas to better understand how people search and how to use this knowledge to improve the performance of specialized medical search engines.

  6. Accurate Finite Difference Algorithms

    NASA Technical Reports Server (NTRS)

    Goodrich, John W.

    1996-01-01

    Two families of finite difference algorithms for computational aeroacoustics are presented and compared. All of the algorithms are single step explicit methods, they have the same order of accuracy in both space and time, with examples up to eleventh order, and they have multidimensional extensions. One of the algorithm families has spectral like high resolution. Propagation with high order and high resolution algorithms can produce accurate results after O(10(exp 6)) periods of propagation with eight grid points per wavelength.

  7. Comparison of fission product release predictions using PARFUME with results from the AGR-1 safety tests

    SciTech Connect

    Collin, Blaise P.; Petti, David A.; Demkowicz, Paul A.; Maki, John T.

    2016-04-07

    Safety tests were conducted on fuel compacts from AGR-1, the first irradiation experiment of the Advanced Gas Reactor (AGR) Fuel Development and Qualification program, at temperatures ranging from 1600 to 1800 °C to determine fission product release at temperatures that bound reactor accident conditions. The PARFUME (PARticle FUel ModEl) code was used to predict the release of fission products silver, cesium, strontium, and krypton from fuel compacts containing tristructural isotropic (TRISO) coated particles during 15 of these safety tests. Comparisons between PARFUME predictions and post-irradiation examination results of the safety tests were conducted on two types of AGR-1 compacts: compacts containing only intact particles and compacts containing one or more particles whose SiC layers failed during safety testing. In both cases, PARFUME globally over-predicted the experimental release fractions by several orders of magnitude: more than three (intact) and two (failed SiC) orders of magnitude for silver, more than three and up to two orders of magnitude for strontium, and up to two and more than one orders of magnitude for krypton. The release of cesium from intact particles was also largely over-predicted (by up to five orders of magnitude) but its release from particles with failed SiC was only over-predicted by a factor of about 3. These over-predictions can be largely attributed to an over-estimation of the diffusivities used in the modeling of fission product transport in TRISO-coated particles. The integral release nature of the data makes it difficult to estimate the individual over-estimations in the kernel or each coating layer. Nevertheless, a tentative assessment of correction factors to these diffusivities was performed to enable a better match between the modeling predictions and the safety testing results. The method could only be successfully applied to silver and cesium. In the case of strontium, correction factors could not be assessed because

  8. Comparison of fission product release predictions using PARFUME with results from the AGR-1 safety tests

    DOE PAGES

    Collin, Blaise P.; Petti, David A.; Demkowicz, Paul A.; ...

    2016-04-07

    Safety tests were conducted on fuel compacts from AGR-1, the first irradiation experiment of the Advanced Gas Reactor (AGR) Fuel Development and Qualification program, at temperatures ranging from 1600 to 1800 °C to determine fission product release at temperatures that bound reactor accident conditions. The PARFUME (PARticle FUel ModEl) code was used to predict the release of fission products silver, cesium, strontium, and krypton from fuel compacts containing tristructural isotropic (TRISO) coated particles during 15 of these safety tests. Comparisons between PARFUME predictions and post-irradiation examination results of the safety tests were conducted on two types of AGR-1 compacts: compactsmore » containing only intact particles and compacts containing one or more particles whose SiC layers failed during safety testing. In both cases, PARFUME globally over-predicted the experimental release fractions by several orders of magnitude: more than three (intact) and two (failed SiC) orders of magnitude for silver, more than three and up to two orders of magnitude for strontium, and up to two and more than one orders of magnitude for krypton. The release of cesium from intact particles was also largely over-predicted (by up to five orders of magnitude) but its release from particles with failed SiC was only over-predicted by a factor of about 3. These over-predictions can be largely attributed to an over-estimation of the diffusivities used in the modeling of fission product transport in TRISO-coated particles. The integral release nature of the data makes it difficult to estimate the individual over-estimations in the kernel or each coating layer. Nevertheless, a tentative assessment of correction factors to these diffusivities was performed to enable a better match between the modeling predictions and the safety testing results. The method could only be successfully applied to silver and cesium. In the case of strontium, correction factors could not be assessed

  9. Race-specific genetic risk score is more accurate than nonrace-specific genetic risk score for predicting prostate cancer and high-grade diseases.

    PubMed

    Na, Rong; Ye, Dingwei; Qi, Jun; Liu, Fang; Lin, Xiaoling; Helfand, Brian T; Brendler, Charles B; Conran, Carly; Gong, Jian; Wu, Yishuo; Gao, Xu; Chen, Yaqing; Zheng, S Lilly; Mo, Zengnan; Ding, Qiang; Sun, Yinghao; Xu, Jianfeng

    2016-01-01

    Genetic risk score (GRS) based on disease risk-associated single nucleotide polymorphisms (SNPs) is an informative tool that can be used to provide inherited information for specific diseases in addition to family history. However, it is still unknown whether only SNPs that are implicated in a specific racial group should be used when calculating GRSs. The objective of this study is to compare the performance of race-specific GRS and nonrace-specific GRS for predicting prostate cancer (PCa) among 1338 patients underwent prostate biopsy in Shanghai, China. A race-specific GRS was calculated with seven PCa risk-associated SNPs implicated in East Asians (GRS7), and a nonrace-specific GRS was calculated based on 76 PCa risk-associated SNPs implicated in at least one racial group (GRS76). The means of GRS7 and GRS76 were 1.19 and 1.85, respectively, in the study population. Higher GRS7 and GRS76 were independent predictors for PCa and high-grade PCa in univariate and multivariate analyses. GRS7 had a better area under the receiver-operating curve (AUC) than GRS76 for discriminating PCa (0.602 vs 0.573) and high-grade PCa (0.603 vs 0.575) but did not reach statistical significance. GRS7 had a better (up to 13% at different cutoffs) positive predictive value (PPV) than GRS76. In conclusion, a race-specific GRS is more robust and has a better performance when predicting PCa in East Asian men than a GRS calculated using SNPs that are not shown to be associated with East Asians.

  10. Results on three predictions for July 2012 federal elections in Mexico based on past regularities.

    PubMed

    Hernández-Saldaña, H

    2013-01-01

    The Presidential Election in Mexico of July 2012 has been the third time that PREP, Previous Electoral Results Program works. PREP gives voting outcomes based in electoral certificates of each polling station that arrive to capture centers. In previous ones, some statistical regularities had been observed, three of them were selected to make predictions and were published in arXiv:1207.0078 [physics.soc-ph]. Using the database made public in July 2012, two of the predictions were completely fulfilled, while, the third one was measured and confirmed using the database obtained upon request to the electoral authorities. The first two predictions confirmed by actual measures are: (ii) The Partido Revolucionario Institucional, PRI, is a sprinter and has a better performance in polling stations arriving late to capture centers during the process. (iii) Distribution of vote of this party is well described by a smooth function named a Daisy model. A Gamma distribution, but compatible with a Daisy model, fits the distribution as well. The third prediction confirms that errare humanum est, since the error distributions of all the self-consistency variables appeared as a central power law with lateral lobes as in 2000 and 2006 electoral processes. The three measured regularities appeared no matter the political environment.

  11. Initial comparison of single cylinder Stirling engine computer model predictions with test results

    NASA Technical Reports Server (NTRS)

    Tew, R. C., Jr.; Thieme, L. G.; Miao, D.

    1979-01-01

    A NASA developed digital computer code for a Stirling engine, modelling the performance of a single cylinder rhombic drive ground performance unit (GPU), is presented and its predictions are compared to test results. The GPU engine incorporates eight regenerator/cooler units and the engine working space is modelled by thirteen control volumes. The model calculates indicated power and efficiency for a given engine speed, mean pressure, heater and expansion space metal temperatures and cooler water inlet temperature and flow rate. Comparison of predicted and observed powers implies that the reference pressure drop calculations underestimate actual pressure drop, possibly due to oil contamination in the regenerator/cooler units, methane contamination in the working gas or the underestimation of mechanical loss. For a working gas of hydrogen, the predicted values of brake power are from 0 to 6% higher than experimental values, and brake efficiency is 6 to 16% higher, while for helium the predicted brake power and efficiency are 2 to 15% higher than the experimental.

  12. Transdermal flux predictions for selected selective oestrogen receptor modulators (SERMs): comparison with experimental results.

    PubMed

    Güngör, Sevgi; Delgado-Charro, M Begoña; Masini-Etévé, Valérie; Potts, Russell O; Guy, Richard H

    2013-12-28

    The aim of this work was to evaluate the feasibility of delivering transdermally a series of highly lipophilic compounds (log P ~4-7), comprising several selective oestrogen receptor modulators and a modified testosterone (danazol). The maximum fluxes of the drugs were predicted theoretically using the modified Potts & Guy algorithm (to determine the permeability coefficient (kp) from water) and the calculated aqueous solubilities. The correction provided by Cleek & Bunge took into account the contribution of the viable epidermal barrier to the skin permeation of highly lipophilic compounds. Experimental measurements of drug fluxes from saturated hydroalcoholic solutions were determined in vitro through excised pig skin. Overall, the predicted fluxes were in good general agreement (within a factor of 10) with the experimental results. Most of the experimental fluxes were greater than those predicted theoretically suggesting that the 70:30 v/v ethanol-water vehicle employed may have had a modest skin penetration enhancement effect. This investigation shows that the transdermal fluxes of highly lipophilic compounds can be reasonably predicted from first principles provided that the viable epidermis, underlying the stratum corneum, is included as a potentially important contributor to the skin's overall barrier function. Furthermore, the absolute values of the measured fluxes, when considered in parallel with previous clinical studies, indicate that it might be feasible to topically deliver a therapeutically useful amount of some of the compounds considered to treat cancerous breast tissue.

  13. Cooled-turbine aerodynamic performance prediction from reduced primary to coolant total-temperature-ratio results

    NASA Technical Reports Server (NTRS)

    Goldman, L. J.

    1976-01-01

    The prediction of the cooled aerodynamic performance, for both stators and turbines, at actual primary to coolant inlet total temperature ratios from the results obtained at a reduced total temperature ratio is described. Theoretical and available experimental results were compared for convection film and transpiration cooled stator vanes and for a film cooled, single stage core turbine. For these tests the total temperature ratio varied from near 1.0 to about 2.7. The agreement between the theoretical and the experimental results was, in general, reasonable.

  14. Accurate prediction of diradical chemistry from a single-reference density-matrix method: Model application to the bicyclobutane to gauche-1,3-butadiene isomerization

    SciTech Connect

    Bertels, Luke W.; Mazziotti, David A.

    2014-07-28

    Multireference correlation in diradical molecules can be captured by a single-reference 2-electron reduced-density-matrix (2-RDM) calculation with only single and double excitations in the 2-RDM parametrization. The 2-RDM parametrization is determined by N-representability conditions that are non-perturbative in their treatment of the electron correlation. Conventional single-reference wave function methods cannot describe the entanglement within diradical molecules without employing triple- and potentially even higher-order excitations of the mean-field determinant. In the isomerization of bicyclobutane to gauche-1,3-butadiene the parametric 2-RDM (p2-RDM) method predicts that the diradical disrotatory transition state is 58.9 kcal/mol above bicyclobutane. This barrier is in agreement with previous multireference calculations as well as recent Monte Carlo and higher-order coupled cluster calculations. The p2-RDM method predicts the Nth natural-orbital occupation number of the transition state to be 0.635, revealing its diradical character. The optimized geometry from the p2-RDM method differs in important details from the complete-active-space self-consistent-field geometry used in many previous studies including the Monte Carlo calculation.

  15. The Las Cruces Trench Site: Characterization, Experimental Results, and One-Dimensional Flow Predictions

    NASA Astrophysics Data System (ADS)

    Wierenga, P. J.; Hills, R. G.; Hudson, D. B.

    1991-10-01

    A comprehensive field trench study was conducted in a semiarid area of southern New Mexico to provide data to test deterministic and stochastic models of vadose zone flow and transport. A 4 m by 9 m area was irrigated with water containing a tracer using a carefully controlled drip irrigation system. The area was heavily instrumented with tensiometers and neutron probe access tubes to monitor water movement and with suction tubes to monitor solute transport. Approximately 600 disturbed and 600 core samples of soil were taken to support deterministic and stochastic characterization of the soil water hydraulic parameters. The core sample-based saturated hydraulic conductivities ranged from 1.4 to 6731 cm/d with a mean of 533 cm/d and a standard deviation of 647 cm/d, indicating significant spatial variability. However, visual observation of the wetting front on the trench wall shows no indication of preferential flow or water flow through visible root channels and cracks. The tensiometer readings and the neutron probe measurements also suggest that the wetting front moves in a fairly homogeneous fashion despite the significant spatial variability of the saturated hydraulic conductivity. In addition to the description of the experiment and the presentation of the experimental results, predictions of simple one-dimensional uniform and layered soil deterministic models for infiltration are presented and compared to field observations. These models are presented here to provide a base case against which more sophisticated deterministic and stochastic models can be compared in the future. The results indicate that the simple models give adequate predictions of the overall movement of the wetting front through the soil during infiltration. However, the models give poor predictions of point values for water content due to the spatial variability of the soil. Comparisons between the one-dimensional infiltration model predictions and field observations show that the use of

  16. Prediction Markets and Beliefs about Climate: Results from Agent-Based Simulations

    NASA Astrophysics Data System (ADS)

    Gilligan, J. M.; John, N. J.; van der Linden, M.

    2015-12-01

    Climate scientists have long been frustrated by persistent doubts a large portion of the public expresses toward the scientific consensus about anthropogenic global warming. The political and ideological polarization of this doubt led Vandenbergh, Raimi, and Gilligan [1] to propose that prediction markets for climate change might influence the opinions of those who mistrust the scientific community but do trust the power of markets.We have developed an agent-based simulation of a climate prediction market in which traders buy and sell future contracts that will pay off at some future year with a value that depends on the global average temperature at that time. The traders form a heterogeneous population with different ideological positions, different beliefs about anthropogenic global warming, and different degrees of risk aversion. We also vary characteristics of the market, including the topology of social networks among the traders, the number of traders, and the completeness of the market. Traders adjust their beliefs about climate according to the gains and losses they and other traders in their social network experience. This model predicts that if global temperature is predominantly driven by greenhouse gas concentrations, prediction markets will cause traders' beliefs to converge toward correctly accepting anthropogenic warming as real. This convergence is largely independent of the structure of the market and the characteristics of the population of traders. However, it may take considerable time for beliefs to converge. Conversely, if temperature does not depend on greenhouse gases, the model predicts that traders' beliefs will not converge. We will discuss the policy-relevance of these results and more generally, the use of agent-based market simulations for policy analysis regarding climate change, seasonal agricultural weather forecasts, and other applications.[1] MP Vandenbergh, KT Raimi, & JM Gilligan. UCLA Law Rev. 61, 1962 (2014).

  17. Tucumán ionospheric model (TIM): Initial results for STEC predictions

    NASA Astrophysics Data System (ADS)

    Scidá, L. A.; Ezquer, R. G.; Cabrera, M. A.; Jadur, C.; Sfer, A. M.

    2016-09-01

    Most ionospheric models can calculate vertical total electron content (VTEC) predictions, but only a few are suitable for calculating slant total electron content (STEC). This ionospheric magnitude is generally measured for electron content determinations, with VTEC particularly corresponding to an elevation of 90°. This is generally obtained by applying a mapping function to STEC measurements, which leads to important calculation errors. Moreover, the equatorial region has unique characteristics, such as the fountain effect and the equatorial electrojet, which lead to significant errors in the model's calculations. In this paper, the Tucumán ionospheric model (TIM) is presented as a novel alternative for calculating the STEC in low-latitude regions (-24 to 24 dip latitude). The model is based on spatial geometry where the considered trajectory is segmented, and the corresponding electron density calculations for the resulting segment end points are determined using the semi-empirical low-latitude ionospheric model (SLIM) with reference to their corresponding magnetic coordinates and height. Finally, the electron density values are integrated along the path to obtain the STEC. This work describes the TIM and tests their STEC predictions for five ray paths around the world (totaling 16 cases under study), which are compared with experimental data from satellites and with those calculated by the NeQuick model. Moreover, the TIM performance for VTEC predictions is also checked and compared with VTEC data obtained from Global Positioning System (GPS) signals, IRI model, and NeQuick model predictions, for six GPS receiver stations during the equinox and solstice (totaling 12 cases studied). Comparisons of the TIM predictions with experimental data show that 53% of the calculation has, in general, deviations <30%. For the considered cases, TIM reproduces the experimental data better than the other models.

  18. Results from an ensemble prediction study of the East Australian Current (EAC)

    NASA Astrophysics Data System (ADS)

    O'Kane, Terence

    2010-05-01

    We present results from an ensemble prediction study of the East Australian Current (EAC) with a specific focus on the examination of the role of dynamical instabilities and flow dependent errors of the day. We frame our experiment in an operational setting utilizing the Australian Bureau of Meteorology's Ocean Model Analysis and Prediction System (OceanMAPS) comprising both global and nested regional ocean forecast models based on MOM4p1 initialized by the Bluelink Ocean Data Assimilation System (BODAS). The forecast ensemble perturbations are generated using the method of bred vectors allowing the identification of those perturbations to a given initial state which grow most rapidly. We consider a 6 month period spanning the Australian summer beginning in mid November through to mid May which corresponds to the period of maximum eddy variability. We find that the bred vector structures align with and anticorrelate with the forecast errors and that these structures typically occur in known areas of instability and in particular where the EAC boundary current separates. The forecast error for the ensemble average are substantially reduced, even for very small numbers of realizations, and in many cases the vertical extent of the forecast error is reduced by an order of magnitude. Our results suggest that one may augment the static background error covariances typically used in operational ocean data assimilation systems with flow dependent background errors from a relatively cheap ensemble prediction system.

  19. Sparse basis selection: new results and application to adaptive prediction of video source traffic.

    PubMed

    Atiya, Amir F; Aly, Mohamed A; Parlos, Alexander G

    2005-09-01

    Real-time prediction of video source traffic is an important step in many network management tasks such as dynamic bandwidth allocation and end-to-end quality-of-service (QoS) control strategies. In this paper, an adaptive prediction model for MPEG-coded traffic is developed. A novel technology is used, first developed in the signal processing community, called sparse basis selection. It is based on selecting a small subset of inputs (basis) from among a large dictionary of possible inputs. A new sparse basis selection algorithm is developed that is based on efficiently updating the input selection adaptively. When a new measurement is received, the proposed algorithm updates the selected inputs in a recursive manner. Thus, adaptability is not only in the weight adjustment, but also in the dynamic update of the inputs. The algorithm is applied to the problem of single-step-ahead prediction of MPEG-coded video source traffic, and the developed method achieves improved results, as compared to the published results in the literature. The present analysis indicates that the adaptive feature of the developed algorithm seems to add significant overall value.

  20. Endovascular Treatment of Malignant Superior Vena Cava Syndrome: Results and Predictive Factors of Clinical Efficacy

    SciTech Connect

    Fagedet, Dorothee; Thony, Frederic; Timsit, Jean-Francois; Rodiere, Mathieu; Monnin-Bares, Valerie; Ferretti, Gilbert R.; Vesin, Aurelien; Moro-Sibilot, Denis

    2013-02-15

    To demonstrate the effectiveness of endovascular treatment (EVT) with self-expandable bare stents for malignant superior vena cava syndrome (SVCS) and to analyze predictive factors of EVT efficacy. Retrospective review of the 164 patients with malignant SVCS treated with EVT in our hospital from August 1992 to December 2007 and followed until February 2009. Endovascular treatment includes angioplasty before and after stent placement. We used self-expandable bare stents. We studied results of this treatment and looked for predictive factors of clinical efficacy, recurrence, and complications by statistical analysis. Endovascular treatment was clinically successful in 95% of cases, with an acceptable rate of early mortality (2.4%). Thrombosis of the superior vena cava was the only independent factor for EVT failure. The use of stents over 16 mm in diameter was a predictive factor for complications (P = 0.008). Twenty-one complications (12.8%) occurred during the follow-up period. Relapse occurred in 36 patients (21.9%), with effective restenting in 75% of cases. Recurrence of SVCS was significantly increased in cases of occlusion (P = 0.01), initial associated thrombosis (P = 0.006), or use of steel stents (P = 0.004). Long-term anticoagulant therapy did not influence the risk of recurrence or complications. In malignancy, EVT with self-expandable bare stents is an effective SVCS therapy. These results prompt us to propose treatment with stents earlier in the clinical course of patients with SVCS and to avoid dilatation greater than 16 mm.

  1. Preliminary analytical results using surface current integration for predicting effects of surface pillows on RF performance

    NASA Technical Reports Server (NTRS)

    Farrell, C. E.; Strange, D. A.

    1982-01-01

    An overview of the fast integral RF evaluation (FIRE) program is presented. This program uses surface current integration to evaluate RF performance of antenna systems. It requires modeling of surfaces in X, Y, Z coordinates along equally spaced X and Y grids with Z in the focal directon. The far field contribution of each surface point includes the effects of the Z-component of surface current which is not included in the aperture integration technique. Because of this, surface current integration is the most effective and inclusive technique for predicting RF performance on non-ideal reflectors. Results obtained from use of the FIRE program and an aperture integration program to predict RF performance of a LSS antenna concept are presented.

  2. Thermodynamic prediction of glycine polymerization as a function of temperature and pH consistent with experimentally obtained results.

    PubMed

    Kitadai, Norio

    2014-04-01

    Prediction of the thermodynamic behaviors of biomolecules at high temperature and pressure is fundamental to understanding the role of hydrothermal systems in the origin and evolution of life on the primitive Earth. However, available thermodynamic dataset for amino acids, essential components for life, cannot represent experimentally observed polymerization behaviors of amino acids accurately under hydrothermal conditions. This report presents the thermodynamic data and the revised HKF parameters for the simplest amino acid "Gly" and its polymers (GlyGly, GlyGlyGly and DKP) based on experimental thermodynamic data from the literature. Values for the ionization states of Gly (Gly(+) and Gly(-)) and Gly peptides (GlyGly(+), GlyGly(-), GlyGlyGly(+), and GlyGlyGly(-)) were also retrieved from reported experimental data by combining group additivity algorithms. The obtained dataset enables prediction of the polymerization behavior of Gly as a function of temperature and pH, consistent with experimentally obtained results in the literature. The revised thermodynamic data for zwitterionic Gly, GlyGly, and DKP were also used to estimate the energetics of amino acid polymerization into proteins. Results show that the Gibbs energy necessary to synthesize a mole of peptide bond is more than 10 kJ mol(-1) less than previously estimated over widely various temperatures (e.g., 28.3 kJ mol(-1) → 17.1 kJ mol(-1) at 25 °C and 1 bar). Protein synthesis under abiotic conditions might therefore be more feasible than earlier studies have shown.

  3. Clinical Validation of an Epigenetic Assay to Predict Negative Histopathological Results in Repeat Prostate Biopsies

    PubMed Central

    Partin, Alan W.; Van Neste, Leander; Klein, Eric A.; Marks, Leonard S.; Gee, Jason R.; Troyer, Dean A.; Rieger-Christ, Kimberly; Jones, J. Stephen; Magi-Galluzzi, Cristina; Mangold, Leslie A.; Trock, Bruce J.; Lance, Raymond S.; Bigley, Joseph W.; Van Criekinge, Wim; Epstein, Jonathan I.

    2015-01-01

    Purpose The DOCUMENT multicenter trial in the United States validated the performance of an epigenetic test as an independent predictor of prostate cancer risk to guide decision making for repeat biopsy. Confirming an increased negative predictive value could help avoid unnecessary repeat biopsies. Materials and Methods We evaluated the archived, cancer negative prostate biopsy core tissue samples of 350 subjects from a total of 5 urological centers in the United States. All subjects underwent repeat biopsy within 24 months with a negative (controls) or positive (cases) histopathological result. Centralized blinded pathology evaluation of the 2 biopsy series was performed in all available subjects from each site. Biopsies were epigenetically profiled for GSTP1, APC and RASSF1 relative to the ACTB reference gene using quantitative methylation specific polymerase chain reaction. Predetermined analytical marker cutoffs were used to determine assay performance. Multivariate logistic regression was used to evaluate all risk factors. Results The epigenetic assay resulted in a negative predictive value of 88% (95% CI 85–91). In multivariate models correcting for age, prostate specific antigen, digital rectal examination, first biopsy histopathological characteristics and race the test proved to be the most significant independent predictor of patient outcome (OR 2.69, 95% CI 1.60–4.51). Conclusions The DOCUMENT study validated that the epigenetic assay was a significant, independent predictor of prostate cancer detection in a repeat biopsy collected an average of 13 months after an initial negative result. Due to its 88% negative predictive value adding this epigenetic assay to other known risk factors may help decrease unnecessary repeat prostate biopsies. PMID:24747657

  4. Accurate predictions of spectroscopic and molecular properties of 27 Λ-S and 73 Ω states of AsS radical.

    PubMed

    Shi, Deheng; Song, Ziyue; Niu, Xianghong; Sun, Jinfeng; Zhu, Zunlue

    2016-01-15

    The PECs are calculated for the 27 Λ-S states and their corresponding 73 Ω states of AsS radical. Of these Λ-S states, only the 2(2)Δ and 5(4)Π states are replulsive. The 1(2)Σ(+), 2(2)Σ(+), 4(2)Π, 3(4)Δ, 3(4)Σ(+), and 4(4)Π states possess double wells. The 3(2)Σ(+) state possesses three wells. The A(2)Π, 3(2)Π, 1(2)Φ, 2(4)Π, 3(4)Π, 2(4)Δ, 3(4)Δ, 1(6)Σ(+), and 1(6)Π states are inverted with the SO coupling effect included. The 1(4)Σ(+), 2(4)Σ(+), 2(4)Σ(-), 2(4)Δ, 1(4)Φ, 1(6)Σ(+), and 1(6)Π states, the second wells of 1(2)Σ(+), 3(4)Σ(+), 4(2)Π, 4(4)Π, and 3(4)Δ states, and the third well of 3(2)Σ(+) state are very weakly-bound states. The PECs are extrapolated to the CBS limit. The effect of SO coupling on the PECs is discussed. The spectroscopic parameters are evaluated, and compared with available measurements and other theoretical ones. The vibrational properties of several weakly-bound states are determined. The spectroscopic properties reported here can be expected to be reliably predicted ones.

  5. Accurate predictions of spectroscopic and molecular properties of 27 Λ-S and 73 Ω states of AsS radical

    NASA Astrophysics Data System (ADS)

    Shi, Deheng; Song, Ziyue; Niu, Xianghong; Sun, Jinfeng; Zhu, Zunlue

    2016-01-01

    The PECs are calculated for the 27 Λ-S states and their corresponding 73 Ω states of AsS radical. Of these Λ-S states, only the 22Δ and 54Π states are replulsive. The 12Σ+, 22Σ+, 42Π, 34Δ, 34Σ+, and 44Π states possess double wells. The 32Σ+ state possesses three wells. The A2Π, 32Π, 12Φ, 24Π, 34Π, 24Δ, 34Δ, 16Σ+, and 16Π states are inverted with the SO coupling effect included. The 14Σ+, 24Σ+, 24Σ-, 24Δ, 14Φ, 16Σ+, and 16Π states, the second wells of 12Σ+, 34Σ+, 42Π, 44Π, and 34Δ states, and the third well of 32Σ+ state are very weakly-bound states. The PECs are extrapolated to the CBS limit. The effect of SO coupling on the PECs is discussed. The spectroscopic parameters are evaluated, and compared with available measurements and other theoretical ones. The vibrational properties of several weakly-bound states are determined. The spectroscopic properties reported here can be expected to be reliably predicted ones.

  6. Surface roughness prediction model and experimental results based on multi-wavelength fiber optic sensors.

    PubMed

    Zhu, Nan-Nan; Zhang, Jun

    2016-10-31

    The surface roughness prediction model based on a support vector machine was proposed and the multi-wavelength fiber optic sensor was established. The specimens with different surface roughness selected as the test samples were analyzed by using the prediction model when the incident wavelengths were 650 nm and 1310 nm, respectively. The working distance of 2.5 mm ~3.5 mm was chosen as the optimum measurement distance. The experimental results indicate that the error range of surface roughness is 0.74% ~7.56% at 650 nm, and the error range of surface roughness is 1.03% ~5.92% at 1310 nm. The average relative error is about 2.669% at 650 nm, while it is about 2.431% at 1310 nm. The error of roughness measurement is less than 3% by using the model, which is acceptable. The error of surface roughness based on the prediction model is smaller than that by using the characteristic curves between surface roughness and the scattering intensity ratio.

  7. Does folic acid supplementation prevent or promote colorectal cancer? Results from model-based predictions.

    PubMed

    Luebeck, E Georg; Moolgavkar, Suresh H; Liu, Amy Y; Boynton, Alanna; Ulrich, Cornelia M

    2008-06-01

    Folate is essential for nucleotide synthesis, DNA replication, and methyl group supply. Low-folate status has been associated with increased risks of several cancer types, suggesting a chemopreventive role of folate. However, recent findings on giving folic acid to patients with a history of colorectal polyps raise concerns about the efficacy and safety of folate supplementation and the long-term health effects of folate fortification. Results suggest that undetected precursor lesions may progress under folic acid supplementation, consistent with the role of folate role in nucleotide synthesis and cell proliferation. To better understand the possible trade-offs between the protective effects due to decreased mutation rates and possibly concomitant detrimental effects due to increased cell proliferation of folic acid, we used a biologically based mathematical model of colorectal carcinogenesis. We predict changes in cancer risk based on timing of treatment start and the potential effect of folic acid on cell proliferation and mutation rates. Changes in colorectal cancer risk in response to folic acid supplementation are likely a complex function of treatment start, duration, and effect on cell proliferation and mutations rates. Predicted colorectal cancer incidence rates under supplementation are mostly higher than rates without folic acid supplementation unless supplementation is initiated early in life (before age 20 years). To the extent to which this model predicts reality, it indicates that the effect on cancer risk when starting folic acid supplementation late in life is small, yet mostly detrimental. Experimental studies are needed to provide direct evidence for this dual role of folate in colorectal cancer and to validate and improve the model predictions.

  8. Poor Gait Performance and Prediction of Dementia: Results From a Meta-Analysis

    PubMed Central

    Beauchet, Olivier; Annweiler, Cédric; Callisaya, Michele L.; De Cock, Anne-Marie; Helbostad, Jorunn L.; Kressig, Reto W.; Srikanth, Velandai; Steinmetz, Jean-Paul; Blumen, Helena M.; Verghese, Joe; Allali, Gilles

    2017-01-01

    Background Poor gait performance predicts risk of developing dementia. No structured critical evaluation has been conducted to study this association yet. The aim of this meta-analysis was to systematically examine the association of poor gait performance with incidence of dementia. Methods An English and French Medline search was conducted in June 2015, with no limit of date, using the medical subject headings terms “Gait” OR “Gait Disorders, Neurologic” OR “Gait Apraxia” OR “Gait Ataxia” AND “Dementia” OR “Frontotemporal Dementia” OR “Dementia, Multi-Infarct” OR “Dementia, Vascular” OR “Alzheimer Disease” OR “Lewy Body Disease” OR “Frontotemporal Dementia With Motor Neuron Disease” (Supplementary Concept). Poor gait performance was defined by standardized tests of walking, and dementia was diagnosed according to international consensus criteria. Four etiologies of dementia were identified: any dementia, Alzheimer disease (AD), vascular dementia (VaD), and non-AD (ie, pooling VaD, mixed dementias, and other dementias). Fixed effects meta-analyses were performed on the estimates in order to generate summary values. Results Of the 796 identified abstracts, 12 (1.5%) were included in this systematic review and meta-analysis. Poor gait performance predicted dementia [pooled hazard ratio (HR) combined with relative risk and odds ratio = 1.53 with P < .001 for any dementia, pooled HR = 1.79 with P < .001 for VaD, HR = 1.89 with P value < .001 for non-AD]. Findings were weaker for predicting AD (HR = 1.03 with P value = .004). Conclusions This meta-analysis provides evidence that poor gait performance predicts dementia. This association depends on the type of dementia; poor gait performance is a stronger predictor of non-AD dementias than AD. PMID:26852960

  9. The Second Las Cruces Trench Experiment: Experimental Results and Two-Dimensional Flow Predictions

    NASA Astrophysics Data System (ADS)

    Hills, R. G.; Wierenga, P. J.; Hudson, D. B.; Kirkland, M. R.

    1991-10-01

    As part of a comprehensive field study designed to provide data to test stochastic and deterministic models of water flow and contaminant transport in the vadose zone, several trench experiments were performed in the semiarid region of southern New Mexico. The first trench experiment is discussed by Wierenga et al. (this issue). During the second trench experiment, a 1.2 m wide by 12 m long area on the north side of and parallel to a 26.4 m long by 4.8 m wide by 6m deep trench was irrigated with water containing tracers using a carefully controlled drip irrigation system. The irrigated area was heavily instrumented with tensiometers and neutron probe access tubes to monitor water movement, and with suction samplers to monitor solute transport. Water containing tritium and bromide was. applied during the first 11.5 days of the study. Thereafter, water was applied without tracers for an additional 64 days. Both water movement and tracer movement were monitored in the subsoil during infiltration and redistribution. The experimental results indicate that water and bromide moved fairly uniformly during infiltration and the bromide moved ahead of the tritium due to anion exclusion during redistribution. Comparisons between measurements and predictions made with a two-dimensional model show qualitative agreement for two of the three water content measurement planes. Model predictions of tritium and bromide transport were not as satisfactory. Measurements of both tritium and bromide show localized areas of high relative concentrations and a large downward motion of bromide relative to tritium during redistribution. While the simple deterministic model does show larger downward motions for bromide than for tritium during redistribution, it does not predict the high concentrations of solute observed during infiltration, nor can it predict the heterogeneous behavior observed for tritium during infiltration and for bromide during redistribution.

  10. Quantifying Uncertainty in Model Predictions for the Pliocene (Plio-QUMP): Initial results

    USGS Publications Warehouse

    Pope, J.O.; Collins, M.; Haywood, A.M.; Dowsett, H.J.; Hunter, S.J.; Lunt, D.J.; Pickering, S.J.; Pound, M.J.

    2011-01-01

    Examination of the mid-Pliocene Warm Period (mPWP; ~. 3.3 to 3.0. Ma BP) provides an excellent opportunity to test the ability of climate models to reproduce warm climate states, thereby assessing our confidence in model predictions. To do this it is necessary to relate the uncertainty in model simulations of mPWP climate to uncertainties in projections of future climate change. The uncertainties introduced by the model can be estimated through the use of a Perturbed Physics Ensemble (PPE). Developing on the UK Met Office Quantifying Uncertainty in Model Predictions (QUMP) Project, this paper presents the results from an initial investigation using the end members of a PPE in a fully coupled atmosphere-ocean model (HadCM3) running with appropriate mPWP boundary conditions. Prior work has shown that the unperturbed version of HadCM3 may underestimate mPWP sea surface temperatures at higher latitudes. Initial results indicate that neither the low sensitivity nor the high sensitivity simulations produce unequivocally improved mPWP climatology relative to the standard. Whilst the high sensitivity simulation was able to reconcile up to 6 ??C of the data/model mismatch in sea surface temperatures in the high latitudes of the Northern Hemisphere (relative to the standard simulation), it did not produce a better prediction of global vegetation than the standard simulation. Overall the low sensitivity simulation was degraded compared to the standard and high sensitivity simulations in all aspects of the data/model comparison. The results have shown that a PPE has the potential to explore weaknesses in mPWP modelling simulations which have been identified by geological proxies, but that a 'best fit' simulation will more likely come from a full ensemble in which simulations that contain the strengths of the two end member simulations shown here are combined. ?? 2011 Elsevier B.V.

  11. Experimental results and wear predictions of petal tools that freely rotate.

    PubMed

    Cordero-Dávila, Alberto; Cabrera-Peláez, Víctor; Cuautle-Cortés, Jorge; González-García, Jorge; Robledo-Sánchez, Carlos; Bautista-Elivar, Nazario

    2005-03-10

    It is difficult to calculate the wear produced by free-pinned tools because their angular movement is not entirely predictable. We analyze the wear produced with free-pinned ring tools, using both simulations and experiments. We conclude that the wear of an incomplete ring is directly proportional to the ring's angular size, independently of the mean radius of the ring. We present an algorithm for calculation of the wear produced by free-pinned petal tools, as they can be considered a linear combination of incomplete free-pinned ring tools. Finally, we apply this result to the enhancement of a defective flat surface and to making a concave spheric surface.

  12. Gas separation in a membrane unit: Experimental results and theoretical predictions

    SciTech Connect

    Tranchino, L.; Santarossa, R.; Carta, F. ); Fabiani, C.; Bimbi, L. )

    1989-11-01

    A laboratory membrane separation unit was assembled by using composite hollow fibers. It was tested in an automated apparatus for gas separation measurements. The performances of the system were measured for CH{sub 4}/CO{sub 2} mixtures as functions of temperature, pressure, stage cut, feed gas composition, and flow regime. The results were analyzed on the basis of a predictive mathematical model of the process. A good fitting of the data was obtained in most cases except at high pressure, probably as a consequence of structural changes of the active layer of the fibers under pressurization.

  13. The allele distribution in next-generation sequencing data sets is accurately described as the result of a stochastic branching process.

    PubMed

    Heinrich, Verena; Stange, Jens; Dickhaus, Thorsten; Imkeller, Peter; Krüger, Ulrike; Bauer, Sebastian; Mundlos, Stefan; Robinson, Peter N; Hecht, Jochen; Krawitz, Peter M

    2012-03-01

    With the availability of next-generation sequencing (NGS) technology, it is expected that sequence variants may be called on a genomic scale. Here, we demonstrate that a deeper understanding of the distribution of the variant call frequencies at heterozygous loci in NGS data sets is a prerequisite for sensitive variant detection. We model the crucial steps in an NGS protocol as a stochastic branching process and derive a mathematical framework for the expected distribution of alleles at heterozygous loci before measurement that is sequencing. We confirm our theoretical results by analyzing technical replicates of human exome data and demonstrate that the variance of allele frequencies at heterozygous loci is higher than expected by a simple binomial distribution. Due to this high variance, mutation callers relying on binomial distributed priors are less sensitive for heterozygous variants that deviate strongly from the expected mean frequency. Our results also indicate that error rates can be reduced to a greater degree by technical replicates than by increasing sequencing depth.

  14. Low power underwater acoustic DPSK detection: Theoretical prediction and experimental results

    NASA Astrophysics Data System (ADS)

    Dunne, Andrew

    This thesis presents two methods of analyzing the effectiveness of a prototype differential phase-shift keying (DPSK) detection circuit. The first method is to make modifications to the existing hardware to reliably output and record the cross-correlation values of the DPSK detection process. The second method is to write a MATLAB detection algorithm which accurately simulates the detection results of the hardware system without the need of any electronics. These two systems were tested and verified with a bench test using computer generated DPSK signals. The hardware system was tested using real acoustic data from shallow and deep water at-sea tests to determine the effectiveness of the DPSK detection circuit in different ocean environments. The hydrophone signals from the tests were recorded so that the cross-correlation values could be verified using the MATLAB detector. As a result of this study, these two systems provided more insight into how well the DPSK detection prototype works and helped to identify ways of improving the detection reliability and overall performance of the prototype DPSK detection circuit.

  15. Using leg muscles as shock absorbers: theoretical predictions and experimental results of drop landing performance.

    PubMed

    Minetti, A E; Ardigò, L P; Susta, D; Cotelli, F

    1998-12-01

    The use of muscles as power dissipators is investigated in this study, both from the modellistic and the experimental points of view. Theoretical predictions of the drop landing manoeuvre for a range of initial conditions have been obtained by accounting for the mechanical characteristics of knee extensor muscles, the limb geometry and assuming maximum neural activation. Resulting dynamics have been represented in the phase plane (vertical displacement versus speed) to better classify the damping performance. Predictions of safe landing in sedentary subjects were associated to dropping from a maximum (feet) height of 1.6-2.0 m (about 11 m on the moon). Athletes can extend up to 2.6-3.0 m, while for obese males (m = 100 kg, standard stature) the limit should reduce to 0.9-1.3 m. These results have been calculated by including in the model the estimated stiffness of the 'global elastic elements' acting below the squat position. Experimental landings from a height of 0.4, 0.7, 1.1 m (sedentary males (SM) and male (AM) and female (AF) athletes from the alpine ski national team) showed dynamics similar to the model predictions. While the peak power (for a drop height of about 0.7 m) was similar in SM and AF (AM shows a +40% increase, about 33 W/kg), AF stopped the downward movement after a time interval (0.219 +/- 0.030 s) from touch-down 20% significantly shorter than SM. Landing strategy and the effect of anatomical constraints are discussed in the paper.

  16. ICGA-PSO-ELM approach for accurate multiclass cancer classification resulting in reduced gene sets in which genes encoding secreted proteins are highly represented.

    PubMed

    Saraswathi, Saras; Sundaram, Suresh; Sundararajan, Narasimhan; Zimmermann, Michael; Nilsen-Hamilton, Marit

    2011-01-01

    A combination of Integer-Coded Genetic Algorithm (ICGA) and Particle Swarm Optimization (PSO), coupled with the neural-network-based Extreme Learning Machine (ELM), is used for gene selection and cancer classification. ICGA is used with PSO-ELM to select an optimal set of genes, which is then used to build a classifier to develop an algorithm (ICGA_PSO_ELM) that can handle sparse data and sample imbalance. We evaluate the performance of ICGA-PSO-ELM and compare our results with existing methods in the literature. An investigation into the functions of the selected genes, using a systems biology approach, revealed that many of the identified genes are involved in cell signaling and proliferation. An analysis of these gene sets shows a larger representation of genes that encode secreted proteins than found in randomly selected gene sets. Secreted proteins constitute a major means by which cells interact with their surroundings. Mounting biological evidence has identified the tumor microenvironment as a critical factor that determines tumor survival and growth. Thus, the genes identified by this study that encode secreted proteins might provide important insights to the nature of the critical biological features in the microenvironment of each tumor type that allow these cells to thrive and proliferate.

  17. Two-Phase Thermal Transport in Microgap Channels—Theory, Experimental Results, and Predictive Relations

    NASA Astrophysics Data System (ADS)

    Bar-Cohen, Avram; Sheehan, Jessica R.; Rahim, Emil

    2012-01-01

    A comprehensive literature review and analysis of recent microchannel/microgap heat transfer data for two-phase flow of refrigerants and dielectric liquids is presented. The flow regime progression in such a microgap channel is shown to be predicted by the traditional flow regime maps. Moreover, Annular flow is shown to be the dominant regime for this thermal transport configuration and to grow in importance as the channel diameter decreases. The results of heat transfer studies of single miniature channels, as well as the analysis and inverse calculation of IR images of a heated microgap channel wall, are used to identify the existence of a characteristic M-shaped heat transfer coefficient variation with quality (or superficial velocity), with inflection points corresponding to transitions in the two-phase cooling modalities. For the high-quality, Annular flow conditions, the venerable Chen correlation is shown to yield predictive agreement for microgap channels that is comparable to that attained for macrochannels and to provide a mechanistic context for the thermal transport rates attained in microgap channels. Results obtained from infrared imaging, revealing previously undetected, large surface temperature variations in Annular flow, are also reviewed and related to the termination of the favorable thin-film evaporation mode in such channels.

  18. SMART empirical approaches for predicting field performance of PV modules from results of reliability tests

    NASA Astrophysics Data System (ADS)

    Hardikar, Kedar Y.; Liu, Bill J. J.; Bheemreddy, Venkata

    2016-09-01

    Gaining an understanding of degradation mechanisms and their characterization are critical in developing relevant accelerated tests to ensure PV module performance warranty over a typical lifetime of 25 years. As newer technologies are adapted for PV, including new PV cell technologies, new packaging materials, and newer product designs, the availability of field data over extended periods of time for product performance assessment cannot be expected within the typical timeframe for business decisions. In this work, to enable product design decisions and product performance assessment for PV modules utilizing newer technologies, Simulation and Mechanism based Accelerated Reliability Testing (SMART) methodology and empirical approaches to predict field performance from accelerated test results are presented. The method is demonstrated for field life assessment of flexible PV modules based on degradation mechanisms observed in two accelerated tests, namely, Damp Heat and Thermal Cycling. The method is based on design of accelerated testing scheme with the intent to develop relevant acceleration factor models. The acceleration factor model is validated by extensive reliability testing under different conditions going beyond the established certification standards. Once the acceleration factor model is validated for the test matrix a modeling scheme is developed to predict field performance from results of accelerated testing for particular failure modes of interest. Further refinement of the model can continue as more field data becomes available. While the demonstration of the method in this work is for thin film flexible PV modules, the framework and methodology can be adapted to other PV products.

  19. Predicting Heavy Drug Use. Results of a Longitudinal Study, Youth Characteristics Describing and Predicting Heavy Drug Use by Adults

    ERIC Educational Resources Information Center

    Schildhaus, Sam; Shaw-Taylor, Yoku; Pedlow, Steven; Pergamit, Michael R.

    2004-01-01

    The primary aim of this study was to describe the movement of adolescents and young adults into and out of drug use and to predict heavy drug use. The data source is the Department of Labor's National Longitudinal Survey of Youth, which began in 1979 with a sample of 12,686 adolescents aged 14-21. After 17 rounds and 19 years, the response rate in…

  20. Cardiac mechanics and dysfunction with anthracyclines in the community: results from the PREDICT study

    PubMed Central

    Narayan, Hari K; Wei, Wei; Feng, Ziding; Lenihan, Daniel; Plappert, Ted; Englefield, Virginia; Fisch, Michael; Ky, Bonnie

    2017-01-01

    Background Our objective was to determine the relevance of changes in myocardial mechanics in diagnosing and predicting cancer therapeutics-related cardiac dysfunction (CTRCD) in a community-based population treated with anthracyclines. Methods Quantitative measures of cardiac mechanics were derived from 493 echocardiograms in 165 participants enrolled in the PREDICT study (A Multicenter Study in Patients Undergoing AnthRacycline-Based Chemotherapy to Assess the Effectiveness of Using Biomarkers to Detect and Identify Cardiotoxicity and Describe Treatment). Echocardiograms were obtained primarily at baseline (prior to anthracyclines), 6 and 12 months. Predictors included changes in strain; strain rate; indices of contractile function derived from the end-systolic pressure–volume relationship (end-systolic elastance (Eessb) and the left ventricular (LV) volume at an end-systolic pressure of 100 mm Hg (V100)); total arterial load (effective arterial elastance (Ea)) and ventricular–arterial coupling (Ea/Eessb). Logistic regression models determined the diagnostic and prognostic associations of changes in these measures and CTRCD, defined as a LV ejection fraction decline ≥10 to <50%. Results By 12 months, 31 participants developed CTRCD. Longitudinal and circumferential strain and strain rate, V100, Ea, and Ea/Eessb each demonstrated significant diagnostic associations, with a 1–7% increased odds of CTRCD (p<0.05). Changes in longitudinal strain rate (area under the curve (AUC) 0.719 (95% CI 0.595 to 0.843)), V100 (AUC 0.796 (95% CI 0.686 to 0.903)) and Ea (AUC 0.742 (95% CI 0.632 to 0.852)) from baseline to 6 months were individually predictive of CTRCD at 12 months. Conclusions Changes in non-invasively derived measures of myocardial mechanics are diagnostic and predictive of cardiac dysfunction with anthracycline chemotherapy in community populations. Our findings support the non-invasive assessment of measures of myocardial mechanics more

  1. Implementing the Effects of Changing Landscape by the Recent Bark Beetle Infestation on Snow Accumulation and Ablation to More Accurately Predict Stream Flow in the Upper Little Laramie River, Wyoming watershed.

    NASA Astrophysics Data System (ADS)

    Heward, J.; Ohara, N.

    2014-12-01

    In many alpine regions, especially in the western United States, the snow pack is the cause of the peak discharge and most of the annual flow. A distributed snow melt model with a point-scale snow melt theory is used to estimate the timing and intensity of both snow accumulation and ablation. The type and distribution of vegetation across a watershed influences timing and intensity of snow melt processes. Efforts are being made to understand how a changing landscape will ultimately affect stream flow in a mountainous environment. This study includes an analysis of the effects of the recent bark beetle infestation, using leaf area index (LAI) data acquired from MODIS data sets. These changes were incorporated into the snow model to more accurately predict snow melt timing and intensity. It was observed through the primary model implementation that snowmelt was intensified by the LAI reduction. The radiation change and turbulent flux effects were separately quantified by the vegetation parameterization in the snow model. This distributed snow model will be used to more accurately predict stream flow in the Upper Little Laramie River, Wyoming watershed.

  2. Predicting mosaics and wildlife diversity resulting from fire disturbance to a forest ecosystem

    NASA Astrophysics Data System (ADS)

    Potter, Meredith W.; Kessell, Stephen R.

    1980-05-01

    A model for predicting community mosaics and wildlife diversity resulting from fire disturbance to a forest ecosystem is presented. It applies an algorithm that delineates the size and shape of each patch from grid-based input data and calculates standard diversity measures for the entire mosaic of community patches and their included animal species. The user can print these diversity calculations, maps of the current community-type-age-class mosaic, and maps of habitat utilization by each animal species. Furthermore, the user can print estimates of changes in each resulting from natural disturbance. Although data and resolution level independent, the model is demonstrated and tested with data from the Lewis and Clark National Forest in Montana.

  3. Impulse propagation over a complex site: a comparison of experimental results and numerical predictions.

    PubMed

    Dragna, Didier; Blanc-Benon, Philippe; Poisson, Franck

    2014-03-01

    Results from outdoor acoustic measurements performed in a railway site near Reims in France in May 2010 are compared to those obtained from a finite-difference time-domain solver of the linearized Euler equations. During the experiments, the ground profile and the different ground surface impedances were determined. Meteorological measurements were also performed to deduce mean vertical profiles of wind and temperature. An alarm pistol was used as a source of impulse signals and three microphones were located along a propagation path. The various measured parameters are introduced as input data into the numerical solver. In the frequency domain, the numerical results are in good accordance with the measurements up to a frequency of 2 kHz. In the time domain, except a time shift, the predicted waveforms match the measured waveforms with a close agreement.

  4. The Predictive Value of the EWGSOP Definition of Sarcopenia: Results From the InCHIANTI Study

    PubMed Central

    Bianchi, Lara; Ferrucci, Luigi; Cherubini, Antonio; Maggio, Marcello; Bandinelli, Stefania; Savino, Elisabetta; Brombo, Gloria; Zuliani, Giovanni; Guralnik, Jack M.; Landi, Francesco

    2016-01-01

    Background. Sarcopenia is associated with increased risk of adverse outcomes in older people. Aim of the study was to explore the predictive value of the European Working Group on Sarcopenia in Older People (EWGSOP) diagnostic algorithm in terms of disability, hospitalization, and mortality and analyze the specific role of grip strength and walking speed as diagnostic criteria for sarcopenia. Methods. Longitudinal analysis of 538 participants enrolled in the InCHIANTI study. Sarcopenia was defined as having low muscle mass plus low grip strength or low gait speed (EWGSOP criteria). Muscle mass was assessed using bioimpedance analysis. Cox proportional and logistic regression models were used to assess risk of death, hospitalization, and disability for sarcopenic people and to investigate the individual contributions of grip strength and walking speed to the predictive value of the EWGSOP’s algorithm. Results. Prevalence of EWGSOP-defined sarcopenia at baseline was 10.2%. After adjusting for potential confounders, sarcopenia was associated with disability (odds ratio 3.15; 95% confidence interval [CI] 1.41–7.05), hospitalization (hazard ratio [HR] 1.57; 95% CI 1.03–2.41), and mortality (HR 1.88; 95% CI 0.91–3.91). The association between an alternative sarcopenic phenotype, defined only by the presence of low muscle mass and low grip strength, and both disability and mortality were similar to the association with the phenotypes defined by low muscle mass and low walking speed or by the EWGSOP algorithm. Conclusions. The EWGSOP’s phenotype is a good predictor of incident disability, hospitalization and death. Assessment of only muscle weakness, in addition to low muscle mass, provided similar predictive value as compared to the original algorithm. PMID:26333772

  5. Genetic testing in Tunisian families with heritable retinoblastoma using a low cost approach permits accurate risk prediction in relatives and reveals incomplete penetrance in adults.

    PubMed

    Ayari Jeridi, Hajer; Bouguila, Hédi; Ansperger-Rescher, Birgit; Baroudi, Olfa; Mdimegh, Imen; Omran, Ines; Charradi, Khaoula; Bouzayene, Hssan; Benammar-Elgaaïed, Amel; Lohmann, Dietmar R

    2014-07-01

    Heritable retinoblastoma is caused by oncogenic mutations in the RB1 tumor suppressor gene. Identification of these mutations in patients is important for genetic counseling and clinical management of relatives at risk. In order to lower analytical efforts, we designed a stepwise mutation detection strategy that was adapted to the spectrum of oncogenic RB1 gene mutations. We applied this strategy on 20 unrelated patients with familial and/or de novo bilateral retinoblastoma from Tunisia. In 19 (95%) patients, we detected oncogenic mutations including base substitutions, small length mutations, and large deletions. Further analyses on the origin of the mutations showed mutational mosaicism in one unilaterally affected father of a bilateral proband and incomplete penetrance in two mothers. In a large family with several retinoblastoma patients, the mutation identified in the index patient was also detected in several non-penetrant relatives. RNA analyses showed that this mutation results in an in-frame loss of exon 9. In summary, our strategy can serve as a model for RB1 mutation identification with high analytical sensitivity. Our results point out that genetic testing is needed to reveal or exclude incomplete penetrance specifically in parents of patients with sporadic disease.

  6. Integrating monitor alarms with laboratory test results to enhance patient deterioration prediction.

    PubMed

    Bai, Yong; Do, Duc H; Harris, Patricia Rae Eileen; Schindler, Daniel; Boyle, Noel G; Drew, Barbara J; Hu, Xiao

    2015-02-01

    Patient monitors in modern hospitals have become ubiquitous but they generate an excessive number of false alarms causing alarm fatigue. Our previous work showed that combinations of frequently co-occurring monitor alarms, called SuperAlarm patterns, were capable of predicting in-hospital code blue events at a lower alarm frequency. In the present study, we extend the conceptual domain of a SuperAlarm to incorporate laboratory test results along with monitor alarms so as to build an integrated data set to mine SuperAlarm patterns. We propose two approaches to integrate monitor alarms with laboratory test results and use a maximal frequent itemsets mining algorithm to find SuperAlarm patterns. Under an acceptable false positive rate FPRmax, optimal parameters including the minimum support threshold and the length of time window for the algorithm to find the combinations of monitor alarms and laboratory test results are determined based on a 10-fold cross-validation set. SuperAlarm candidates are generated under these optimal parameters. The final SuperAlarm patterns are obtained by further removing the candidates with false positive rate>FPRmax. The performance of SuperAlarm patterns are assessed using an independent test data set. First, we calculate the sensitivity with respect to prediction window and the sensitivity with respect to lead time. Second, we calculate the false SuperAlarm ratio (ratio of the hourly number of SuperAlarm triggers for control patients to that of the monitor alarms, or that of regular monitor alarms plus laboratory test results if the SuperAlarm patterns contain laboratory test results) and the work-up to detection ratio, WDR (ratio of the number of patients triggering any SuperAlarm patterns to that of code blue patients triggering any SuperAlarm patterns). The experiment results demonstrate that when varying FPRmax between 0.02 and 0.15, the SuperAlarm patterns composed of monitor alarms along with the last two laboratory test results

  7. Psychological and Functional Vulnerability Predicts Fraud Cases in Older Adults: Results of a Longitudinal Study

    PubMed Central

    Sugarman, Michael A.; Paulson, Daniel; Ficker, Lisa J; Rahman-Filipiak, Annalise

    2016-01-01

    Using cross sectional data Psychological vulnerability was identified as a correlate of older adult’s being defrauded. We extend that research by examining fraud prevalence using longitudinal data from the Health and Retirement Study, and to identify the best predictors of fraud longitudinally across a 4-year time frame. Whereas reported fraud prevalence was 5.0% in a 5-year look-back period in 2008, it increased to 6.1% in 2012. The rate of new-incident fraud across only a 4-year look-back was 4.3%. Being younger-old, having a higher level of education, and having more depression significantly predicted the new cases of fraud reported in 2012. Psychological vulnerability was a potent longitudinal predictor of fraud, with the most vulnerable individuals being more than twice as likely to be defrauded. Results indicate that fraud victimization among older adults is rising, and that vulnerability variables, along with some demographic variables, predict new cases of fraud. PMID:27065511

  8. Granular Activated Carbon Treatment May Result in Higher Predicted Genotoxicity in the Presence of Bromide.

    PubMed

    Krasner, Stuart W; Lee, Tiffany Chih Fen; Westerhoff, Paul; Fischer, Natalia; Hanigan, David; Karanfil, Tanju; Beita-Sandí, Wilson; Taylor-Edmonds, Liz; Andrews, Robert C

    2016-09-06

    Certain unregulated disinfection byproducts (DBPs) are more of a health concern than regulated DBPs. Brominated species are typically more cytotoxic and genotoxic than their chlorinated analogs. The impact of granular activated carbon (GAC) on controlling the formation of regulated and selected unregulated DBPs following chlorine disinfection was evaluated. The predicted cyto- and genotoxicity of DBPs was calculated using published potencies based on the comet assay for Chinese hamster ovary cells (assesses the level of DNA strand breaks). Additionally, genotoxicity was measured using the SOS-Chromotest (detects DNA-damaging agents). The class sum concentrations of trihalomethanes, haloacetic acids, and unregulated DBPs, and the SOS genotoxicity followed the breakthrough of dissolved organic carbon (DOC), however the formation of brominated species did not. The bromide/DOC ratio was higher than the influent through much of the breakthrough curve (GAC does not remove bromide), which resulted in elevated brominated DBP concentrations in the effluent. Based on the potency of the haloacetonitriles and halonitromethanes, these nitrogen-containing DBPs were the driving agents of the predicted genotoxicity. GAC treatment of drinking or reclaimed waters with appreciable levels of bromide and dissolved organic nitrogen may not control the formation of unregulated DBPs with higher genotoxicity potencies.

  9. Accurate prediction of H3O+ and D3O+ sensitivity coefficients to probe a variable proton-to-electron mass ratio

    NASA Astrophysics Data System (ADS)

    Owens, A.; Yurchenko, S. N.; Polyansky, O. L.; Ovsyannikov, R. I.; Thiel, W.; Špirko, V.

    2015-12-01

    The mass sensitivity of the vibration-rotation-inversion transitions of H316O+, H318O+, and D316O+ is investigated variationally using the nuclear motion program TROVE (Yurchenko, Thiel & Jensen). The calculations utilize new high-level ab initio potential energy and dipole moment surfaces. Along with the mass dependence, frequency data and Einstein A coefficients are computed for all transitions probed. Particular attention is paid to the Δ|k| = 3 and Δ|k - l| = 3 transitions comprising the accidentally coinciding |J, K = 0, v2 = 0+> and |J, K = 3, v2 = 0-> rotation-inversion energy levels. The newly computed probes exhibit sensitivities comparable to their ammonia and methanol counterparts, thus demonstrating their potential for testing the cosmological stability of the proton-to-electron mass ratio. The theoretical TROVE results are in close agreement with sensitivities obtained using the non-rigid and rigid inverter approximate models, confirming that the ab initio theory used in the present study is adequate.

  10. Prediction of Toxic Pollution Resulting From Warfare Chemical Munitions Dumped In The Sea

    NASA Astrophysics Data System (ADS)

    Korotenko, K. A.

    A 3-D high-resolution Hydrodynamic/Transport model was developed to predict chemical pollution in marine environment with a special reference to warfare chem- icals dumped in the Baltic Sea. The Flow module was developed on the basis of the Princeton Ocean Model (POM). The grid step is chosen at 1/15Deg and 1/30/Deg along x- and y-axes (that is, about 4.0 km and 3.7 km, respectively). The model grid covers the Baltic from 9.3 to 24.6E and from 53.0 to 60.2N. The Transport module of the model takes the predetermined velocity field and uses the random walk technique to predict the motion of individual particles, the sum of which constitutes a consid- ered chemical agent. Several different approaches for modeling are used for different kind of chemical agents. Basic processes affecting the chemicals to be modeled are hydrolysis, solubility, and microbiological destruction. All available toxicity data re- garding the chemical warfare agents of primary concern and the expected degradation products in the Baltic environment were gathered and summarized. This information was used to compare the toxicities of the different agents and their degradation prod- ucts and to decide which chemicals may represent a toxic threat to the environment. The model was adapted to be used for chemical agents with various characteristics and behavior (as Sarin, Lewsite, Musturd, etc.) in seawaters. Special algorithms are developed to describe nonlinear reactions producing toxic and nontoxic products in result of the warfare agent destruction. Sources of chemical pollution in the sea are considered as steady state (chronic) point and/or distributed releases because princi- pally different two methods were used in dumping CW: 1) concentrated dumping of containers, shells, and bombs together with ships; 2) dispersed dumping of individual containers, shells and aircraft bombs from moving vessels. The model was run with four most recurrent climatic wind fields for the Bornholm and Gotland

  11. Accurate ab initio dipole moment surfaces of ozone: First principle intensity predictions for rotationally resolved spectra in a large range of overtone and combination bands.

    PubMed

    Tyuterev, Vladimir G; Kochanov, Roman V; Tashkun, Sergey A

    2017-02-14

    Ab initio dipole moment surfaces (DMSs) of the ozone molecule are computed using the MRCI-SD method with AVQZ, AV5Z, and VQZ-F12 basis sets on a dense grid of about 1950 geometrical configurations. The analytical DMS representation used for the fit of ab initio points provides better behavior for large nuclear displacements than that of previous studies. Various DMS models were derived and tested. Vibration-rotation line intensities of (16)O3 were calculated from these ab initio surfaces by the variational method using two different potential functions determined in our previous works. For the first time, a very good agreement of first principle calculations with the experiment was obtained for the line-by-line intensities in rotationally resolved ozone spectra in a large far- and mid-infrared range. This includes high overtone and combination bands up to ΔV = 6. A particular challenge was a correct description of the B-type bands (even ΔV3 values) that represented major difficulties for the previous ab initio investigations and for the empirical spectroscopic models. The major patterns of various B-type bands were correctly described without empirically adjusted dipole moment parameters. For the 10 μm range, which is of key importance for the atmospheric ozone retrievals, our ab initio intensity results are within the experimental error margins. The theoretical values for the strongest lines of the ν3 band lie in general between two successive versions of HITRAN (HIgh-resolution molecular TRANsmission) empirical database that corresponded to most extended available sets of observations. The overall qualitative agreement in a large wavenumber range for rotationally resolved cold and hot ozone bands up to about 6000 cm(-1) is achieved here for the first time. These calculations reveal that several weak bands are yet missing from available spectroscopic databases.

  12. Accurate ab initio dipole moment surfaces of ozone: First principle intensity predictions for rotationally resolved spectra in a large range of overtone and combination bands

    NASA Astrophysics Data System (ADS)

    Tyuterev, Vladimir G.; Kochanov, Roman V.; Tashkun, Sergey A.

    2017-02-01

    Ab initio dipole moment surfaces (DMSs) of the ozone molecule are computed using the MRCI-SD method with AVQZ, AV5Z, and VQZ-F12 basis sets on a dense grid of about 1950 geometrical configurations. The analytical DMS representation used for the fit of ab initio points provides better behavior for large nuclear displacements than that of previous studies. Various DMS models were derived and tested. Vibration-rotation line intensities of 16O3 were calculated from these ab initio surfaces by the variational method using two different potential functions determined in our previous works. For the first time, a very good agreement of first principle calculations with the experiment was obtained for the line-by-line intensities in rotationally resolved ozone spectra in a large far- and mid-infrared range. This includes high overtone and combination bands up to Δ V = 6. A particular challenge was a correct description of the B-type bands (even Δ V3 values) that represented major difficulties for the previous ab initio investigations and for the empirical spectroscopic models. The major patterns of various B-type bands were correctly described without empirically adjusted dipole moment parameters. For the 10 μ m range, which is of key importance for the atmospheric ozone retrievals, our ab initio intensity results are within the experimental error margins. The theoretical values for the strongest lines of the ν3 band lie in general between two successive versions of HITRAN (HIgh-resolution molecular TRANsmission) empirical database that corresponded to most extended available sets of observations. The overall qualitative agreement in a large wavenumber range for rotationally resolved cold and hot ozone bands up to about 6000 cm-1 is achieved here for the first time. These calculations reveal that several weak bands are yet missing from available spectroscopic databases.

  13. Comparison of fission product release predictions using PARFUME with results from the AGR-1 safety tests

    SciTech Connect

    Blaise Collin

    2014-09-01

    Safety tests were conducted on fourteen fuel compacts from AGR-1, the first irradiation experiment of the Advanced Gas Reactor (AGR) Fuel Development and Qualification program, at temperatures ranging from 1600 to 1800°C to determine fission product release at temperatures that bound reactor accident conditions. The PARFUME (PARticle FUel ModEl) code was used to predict the release of fission products silver, cesium, strontium, and krypton from fuel compacts containing tristructural isotropic (TRISO) coated particles during the safety tests, and the predicted values were compared with experimental results. Preliminary comparisons between PARFUME predictions and post-irradiation examination (PIE) results of the safety tests show different trends in the prediction of the fractional release depending on the species, and it leads to different conclusions regarding the diffusivities used in the modeling of fission product transport in TRISO-coated particles: • For silver, the diffusivity in silicon carbide (SiC) might be over-estimated by a factor of at least 102 to 103 at 1600°C and 1700°C, and at least 10 to 102 at 1800°C. The diffusivity of silver in uranium oxy-carbide (UCO) might also be over-estimated, but the available data are insufficient to allow definitive conclusions to be drawn. • For cesium, the diffusivity in UCO might be over-estimated by a factor of at least 102 to 103 at 1600°C, 105 at 1700°C, and 103 at 1800°C. The diffusivity of cesium in SiC might also over-estimated, by a factor of 10 at 1600°C and 103 at 1700°C, based upon the comparisons between calculated and measured release fractions from intact particles. There is no available estimate at 1800°C since all the compacts heated up at 1800°C contain particles with failed SiC layers whose release dominates the release from intact particles. • For strontium, the diffusivity in SiC might be over-estimated by a factor of 10 to 102 at 1600 and 1700°C, and 102 to 103 at 1800°C. These

  14. Predicting children's short-term exposure to pesticides: results of a questionnaire screening approach.

    PubMed Central

    Sexton, Ken; Adgate, John L; Eberly, Lynn E; Clayton, C Andrew; Whitmore, Roy W; Pellizzari, Edo D; Lioy, Paul J; Quackenboss, James J

    2003-01-01

    The ability of questionnaires to predict children's exposure to pesticides was examined as part of the Minnesota Children's Pesticide Exposure Study (MNCPES). The MNCPES focused on a probability sample of 102 children between the ages of 3 and 13 years living in either urban (Minneapolis and St. Paul, MN) or nonurban (Rice and Goodhue Counties in Minnesota) households. Samples were collected in a variety of relevant media (air, food, beverages, tap water, house dust, soil, urine), and chemical analyses emphasized three organophosphate insecticides (chlorpyrifos, diazinon, malathion) and a herbicide (atrazine). Results indicate that the residential pesticide-use questions and overall screening approach used in the MNCPES were ineffective for identifying and oversampling children/households with higher levels of individual target pesticides. PMID:12515690

  15. Evidence-based genetic counselling implications for Huntington disease intermediate allele predictive test results.

    PubMed

    Semaka, A; Hayden, M R

    2014-04-01

    Intermediate alleles (IAs) for Huntington disease (HD) contain 27-35 CAG repeats, a range that falls just below the disease threshold of 36 repeats. While there is no firm evidence that IAs confer the HD phenotype, they are prone to germline CAG repeat instability, particularly repeat expansion when paternally transmitted. Consequently, offspring may inherit a new mutation and develop the disease later in life. Over the last 5 years there has been a renewed interest in IAs. This article provides an overview of the latest research on IAs, including their clinical implications, frequency, haplotype, and likelihood of CAG repeat expansion, as well as patient understanding and current genetic counselling practices. The implications of this growing evidence base for clinical practice are also highlighted. These evidence-based genetic counselling implications may help ensure individuals with an IA predictive test result receive appropriate support, education, and counselling.

  16. Predicting saturated hydraulic conductivity from percolation test results in layered silt loam soils.

    PubMed

    Jabro, Jay D

    2009-12-01

    The objectives of the study discussed in this article were to develop an empirical relationship between the saturated hydraulic conductivity (Ks) of layered soils and their percolation times (PT) in order to understand the influence of individual layers and compare this with the equations developed by Winneberger (1974) and Fritton, Ratvasky, and Petersen (1986). Field research was conducted on three silt loam soils. Six holes were spaced evenly in two parallel rows of three holes. The Ks was measured at three different layers for each soil using a constant head well permeameter. After completion of the second Ks measurement, the percolation test was conducted. Three linear equations for the upper, middle, and lower layers were developed between the Ks values of each individual layer in all three sites and the corresponding PT. Significant differences were found between the author's results and those predicted by Winneberger (1974) and Fritton and co-authors (1986).

  17. Accurate sperm morphology assessment predicts sperm function.

    PubMed

    Abu Hassan Abu, D; Franken, D R; Hoffman, B; Henkel, R

    2012-05-01

    Sperm morphology has been associated with in vitro as well as in vivo fertilisation. The study aimed to evaluate the possible relation between the percentage of spermatozoa with normal morphology and the following sperm functional assays: (i) zona-induced acrosome reaction (ZIAR); (ii) DNA integrity; (iii) chromatin condensation; (iv) sperm apoptosis; and (v) fertilisation rates. Regression analysis was employed to calculate the association between morphology and different functional tests. Normal sperm morphology correlated significantly with the percentages of live acrosome-reacted spermatozoa in the ZIAR (r = 0.518; P < 0.0001; n = 92), DNA integrity (r = -0.515; P = 0.0018; n = 34), CMA(3) -positive spermatozoa (r = -0.745; P < 0.0001; n = 92), sperm apoptosis (r = -0.395; P = 0.0206; n = 34) and necrosis (r = -0.545; P = 0.0009; n = 34). Negative correlations existed between for the acrosome reaction, and DNA integrity, while negative associations were recorded with the percentages of CMA(3) -positive spermatozoa, apoptotic and necrotic spermatozoa. Sperm morphology is related to sperm dysfunction such as poor chromatin condensation, acrosome reaction and DNA integrity. Negative and significant correlations existed between normal sperm morphology and chromatin condensation, the percentage of spermatozoa with abnormal DNA and spermatozoa with apoptotic activity. The authors do not regard sperm morphology as the only test for the diagnosis of male fertility, but sperm morphology can serve as a valuable indicator of underlying dysfunction.

  18. Predicting Visual Semantic Descriptive Terms from Radiological Image Data: Preliminary Results with Liver Lesions in CT

    PubMed Central

    Depeursinge, Adrien; Kurtz, Camille; Beaulieu, Christopher F.; Napel, Sandy; Rubin, Daniel L.

    2014-01-01

    We describe a framework to model visual semantics of liver lesions in CT images in order to predict the visual semantic terms (VST) reported by radiologists in describing these lesions. Computational models of VST are learned from image data using high–order steerable Riesz wavelets and support vector machines (SVM). The organization of scales and directions that are specific to every VST are modeled as linear combinations of directional Riesz wavelets. The models obtained are steerable, which means that any orientation of the model can be synthesized from linear combinations of the basis filters. The latter property is leveraged to model VST independently from their local orientation. In a first step, these models are used to predict the presence of each semantic term that describes liver lesions. In a second step, the distances between all VST models are calculated to establish a non–hierarchical computationally–derived ontology of VST containing inter–term synonymy and complementarity. A preliminary evaluation of the proposed framework was carried out using 74 liver lesions annotated with a set of 18 VSTs from the RadLex ontology. A leave–one–patient–out cross–validation resulted in an average area under the ROC curve of 0.853 for predicting the presence of each VST when using SVMs in a feature space combining the magnitudes of the steered models with CT intensities. Likelihood maps are created for each VST, which enables high transparency of the information modeled. The computationally–derived ontology obtained from the VST models was found to be consistent with the underlying semantics of the visual terms. It was found to be complementary to the RadLex ontology, and constitutes a potential method to link the image content to visual semantics. The proposed framework is expected to foster human–computer synergies for the interpretation of radiological images while using rotation–covariant computational models of VSTs to (1) quantify their

  19. Does cognitive functioning predict chronic pain? Results from a prospective surgical cohort.

    PubMed

    Attal, Nadine; Masselin-Dubois, Anne; Martinez, Valéria; Jayr, Christian; Albi, Aline; Fermanian, Jacques; Bouhassira, Didier; Baudic, Sophie

    2014-03-01

    It is well established that chronic pain impairs cognition, particularly memory, attention and mental flexibility. Overlaps have been found between the brain regions involved in pain modulation and cognition, including in particular the prefrontal cortex and the anterior cingulate cortex, which are involved in executive function, attention and memory. However, whether cognitive function may predict chronic pain has not been investigated. We addressed this question in surgical patients, because such patients can be followed prospectively and may have no pain before surgery. In this prospective longitudinal study, we investigated the links between executive function, visual memory and attention, as assessed by clinical measurements and the development of chronic pain, its severity and neuropathic symptoms (based on the 'Douleur Neuropathique 4' questionnaire), 6 and 12 months after surgery (total knee arthroplasty for osteoarthritis or breast surgery for cancer). Neuropsychological tests included the Trail-Making Test A and B, and the Rey-Osterrieth Complex Figure copy and immediate recall, which assess cognitive flexibility, visuospatial processing and visual memory. Anxiety, depression and coping strategies were also evaluated. In total, we investigated 189 patients before surgery: 96% were re-evaluated at 6 months, and 88% at 12 months. Multivariate logistic regression (stepwise selection) for the total group of patients indicated that the presence of clinical meaningful pain at 6 and 12 months (pain intensity ≥ 3/10) was predicted by poorer cognitive performance in the Trail Making Test B (P = 0.0009 and 0.02 for pain at 6 and 12 months, respectively), Rey-Osterrieth Complex Figure copy (P = 0.015 and 0.006 for pain at 6 and 12 months, respectively) and recall (P = 0.016 for pain at 12 months), independently of affective variables. Linear regression analyses indicated that impaired scores on these tests predicted pain intensity (P < 0.01) and neuropathic

  20. Temperature Fields in Soft Tissue during LPUS Treatment: Numerical Prediction and Experiment Results

    SciTech Connect

    Kujawska, Tamara; Wojcik, Janusz; Nowicki, Andrzej

    2010-03-09

    Recent research has shown that beneficial therapeutic effects in soft tissues can be induced by the low power ultrasound (LPUS). For example, increasing of cells immunity to stress (among others thermal stress) can be obtained through the enhanced heat shock proteins (Hsp) expression induced by the low intensity ultrasound. The possibility to control the Hsp expression enhancement in soft tissues in vivo stimulated by ultrasound can be the potential new therapeutic approach to the neurodegenerative diseases which utilizes the known feature of cells to increase their immunity to stresses through the Hsp expression enhancement. The controlling of the Hsp expression enhancement by adjusting of exposure level to ultrasound energy would allow to evaluate and optimize the ultrasound-mediated treatment efficiency. Ultrasonic regimes are controlled by adjusting the pulsed ultrasound waves intensity, frequency, duration, duty cycle and exposure time. Our objective was to develop the numerical model capable of predicting in space and time temperature fields induced by a circular focused transducer generating tone bursts in multilayer nonlinear attenuating media and to compare the numerically calculated results with the experimental data in vitro. The acoustic pressure field in multilayer biological media was calculated using our original numerical solver. For prediction of temperature fields the Pennes' bio-heat transfer equation was employed. Temperature field measurements in vitro were carried out in a fresh rat liver using the 15 mm diameter, 25 mm focal length and 2 MHz central frequency transducer generating tone bursts with the spatial peak temporal average acoustic intensity varied between 0.325 and 1.95 W/cm{sup 2}, duration varied from 20 to 500 cycles at the same 20% duty cycle and the exposure time varied up to 20 minutes. The measurement data were compared with numerical simulation results obtained under experimental boundary conditions. Good agreement between

  1. Temperature Fields in Soft Tissue during LPUS Treatment: Numerical Prediction and Experiment Results

    NASA Astrophysics Data System (ADS)

    Kujawska, Tamara; Wójcik, Janusz; Nowicki, Andrzej

    2010-03-01

    Recent research has shown that beneficial therapeutic effects in soft tissues can be induced by the low power ultrasound (LPUS). For example, increasing of cells immunity to stress (among others thermal stress) can be obtained through the enhanced heat shock proteins (Hsp) expression induced by the low intensity ultrasound. The possibility to control the Hsp expression enhancement in soft tissues in vivo stimulated by ultrasound can be the potential new therapeutic approach to the neurodegenerative diseases which utilizes the known feature of cells to increase their immunity to stresses through the Hsp expression enhancement. The controlling of the Hsp expression enhancement by adjusting of exposure level to ultrasound energy would allow to evaluate and optimize the ultrasound-mediated treatment efficiency. Ultrasonic regimes are controlled by adjusting the pulsed ultrasound waves intensity, frequency, duration, duty cycle and exposure time. Our objective was to develop the numerical model capable of predicting in space and time temperature fields induced by a circular focused transducer generating tone bursts in multilayer nonlinear attenuating media and to compare the numerically calculated results with the experimental data in vitro. The acoustic pressure field in multilayer biological media was calculated using our original numerical solver. For prediction of temperature fields the Pennes' bio-heat transfer equation was employed. Temperature field measurements in vitro were carried out in a fresh rat liver using the 15 mm diameter, 25 mm focal length and 2 MHz central frequency transducer generating tone bursts with the spatial peak temporal average acoustic intensity varied between 0.325 and 1.95 W/cm2, duration varied from 20 to 500 cycles at the same 20% duty cycle and the exposure time varied up to 20 minutes. The measurement data were compared with numerical simulation results obtained under experimental boundary conditions. Good agreement between the

  2. Accurate Evaluation of Quantum Integrals

    NASA Technical Reports Server (NTRS)

    Galant, D. C.; Goorvitch, D.; Witteborn, Fred C. (Technical Monitor)

    1995-01-01

    Combining an appropriate finite difference method with Richardson's extrapolation results in a simple, highly accurate numerical method for solving a Schrodinger's equation. Important results are that error estimates are provided, and that one can extrapolate expectation values rather than the wavefunctions to obtain highly accurate expectation values. We discuss the eigenvalues, the error growth in repeated Richardson's extrapolation, and show that the expectation values calculated on a crude mesh can be extrapolated to obtain expectation values of high accuracy.

  3. Numerical Predictions and Experimental Results of Air Flow in a Smooth Quarter-Scale Nacelle

    SciTech Connect

    BLACK, AMALIA R.; SUO-ANTTILA, JILL M.; GRITZO, LOUIS A.; DISIMILE, PETER J.; TUCKER, JAMES R.

    2002-06-01

    Fires in aircraft engine nacelles must be rapidly suppressed to avoid loss of life and property. The design of new and retrofit suppression systems has become significantly more challenging due to the ban on production of Halon 1301 for environmental concerns. Since fire dynamics and the transport of suppressants within the nacelle are both largely determined by the available air flow, efforts to define systems using less effective suppressants greatly benefit from characterization of nacelle air flow fields. A combined experimental and computational study of nacelle air flow therefore has been initiated. Calculations have been performed using both CFD-ACE (a Computational Fluid Dynamics (CFD) model with a body-fitted coordinate grid) and WLCAN (a CFD-based fire field model with a Cartesian ''brick'' shaped grid). The flow conditions examined in this study correspond to the same Reynolds number as test data from the full-scale nacelle simulator at the 46 Test Wing. Pre-test simulations of a quarter-scale test fixture were performed using CFD-ACE and WLCAN prior to fabrication. Based on these pre-test simulations, a quarter-scale test fixture was designed and fabricated for the purpose of obtaining spatially-resolved measurements of velocity and turbulence intensity in a smooth nacelle. Post-test calculations have been performed for the conditions of the experiment and compared with experimental results obtained from the quarter-scale test fixture. In addition, several different simulations were performed to assess the sensitivity of the predictions to the grid size, to the turbulence models, and to the use of wall functions. In general, the velocity predictions show very good agreement with the data in the center of the channel but deviate near the walls. The turbulence intensity results tend to amplify the differences in velocity, although most of the trends are in agreement. In addition, there were some differences between WLCAN and CFD-ACE results in the angled

  4. Polyvalent display and packing of peptides and proteins on semiconductor quantum dots: predicted versus experimental results.

    PubMed

    Prasuhn, Duane E; Deschamps, Jeffrey R; Susumu, Kimihiro; Stewart, Michael H; Boeneman, Kelly; Blanco-Canosa, Juan B; Dawson, Philip E; Medintz, Igor L

    2010-02-22

    Quantum dots (QDs) are loaded with a series of peptides and proteins of increasing size, including a <20 residue peptide, myoglobin, mCherry, and maltose binding protein, which together cover a range of masses from <2.2 to approximately 44 kDa. Conjugation to the surface of dihydrolipoic acid-functionalized QDs is facilitated by polyhistidine metal affinity coordination. Increasing ratios of dye-labeled peptides and proteins are self-assembled to the QDs and then the bioconjugates are separated and analyzed using agarose gel electrophoresis. Fluorescent visualization of both conjugated and unbound species allows determination of an experimentally derived maximum loading number. Molecular modeling utilizing crystallographic coordinates or space-filling structures of the peptides and proteins also allow the predicted maximum loadings to the QDs to be estimated. Comparison of the two sets of results provides insight into the nature of the QD surface and reflects the important role played by the nanoparticle's hydrophilic solubilizing surface ligands. It is found that for the larger protein molecules steric hindrance is the major packing constraint. In contrast, for the smaller peptides, the number of available QD binding sites is the principal determinant. These results can contribute towards an overall understanding of how to engineer designer bioconjugates for both QDs and other nanoparticle materials.

  5. Prediction of full-scale dewatering results of sewage sludges by the physical water distribution.

    PubMed

    Kopp, J; Dichtl, N

    2001-01-01

    The dewaterability of sewage sludge can be described by the total solids concentration of the sludge cake and the polymer-demand for conditioning. The total solids concentration of the sludge cake depends on the physical water distribution. The various types of water in sewage sludge are mainly distinguished by the type and the intensity of their physical bonding to the solids. In a sewage sludge suspension four different types of water can be distinguished. These are the free water, which is not bound to the particles, the interstitial water, which is bound by capillary forces between the sludge flocs, the surface water, which is bound by adhesive forces and intracellular water. Only the share of free water can be separated during mechanical dewatering. It can be shown, that by thermo-gravimeteric measurement of the free water content, an exact prediction of full-scale dewatering results is possible. By separation of all free water during centrifugation the maximum dewatering result is reached. Polymer conditioning increases the velocity of the sludge water release, but the free water content is not influenced by this process. Furthermore it is not possible, to replace the measuring of the water distribution by other individual parameters such as ignition loss.

  6. Comparisons of Observations with Results from 3D Simulations and Implications for Predictions of Ozone Recovery

    NASA Technical Reports Server (NTRS)

    Douglass, Anne R.; Stolarski, Richard S.; Strahan, Susan E.; Steenrod, Stephen D.; Polarsky, Brian C.

    2004-01-01

    Although chemistry and transport models (CTMs) include the same basic elements (photo- chemical mechanism and solver, photolysis scheme, meteorological fields, numerical transport scheme), they produce different results for the future recovery of stratospheric ozone as chlorofluorcarbons decrease. Three simulations will be contrasted: the Global Modeling Initiative (GMI) CTM driven by a single year\\'s winds from a general circulation model; the GMI CTM driven by a single year\\'s winds from a data assimilation system; the NASA GSFC CTM driven by a winds from a multi-year GCM simulation. CTM results for ozone and other constituents will be compared with each other and with observations from ground-based and satellite platforms to address the following: Does the simulated ozone tendency and its latitude, altitude and seasonal dependence match that derived from observations? Does the balance from analysis of observations? Does the balance among photochemical processes match that expected from observations? Can the differences in prediction for ozone recovery be anticipated from these comparisons?

  7. Dispositional Optimism and Perceived Risk Interact to Predict Intentions to Learn Genome Sequencing Results

    PubMed Central

    Taber, Jennifer M.; Klein, William M. P.; Ferrer, Rebecca A.; Lewis, Katie L.; Biesecker, Leslie G.; Biesecker, Barbara B.

    2015-01-01

    Objective Dispositional optimism and risk perceptions are each associated with health-related behaviors and decisions and other outcomes, but little research has examined how these constructs interact, particularly in consequential health contexts. The predictive validity of risk perceptions for health-related information seeking and intentions may be improved by examining dispositional optimism as a moderator, and by testing alternate types of risk perceptions, such as comparative and experiential risk. Method Participants (n = 496) had their genomes sequenced as part of a National Institutes of Health pilot cohort study (ClinSeq®). Participants completed a cross-sectional baseline survey of various types of risk perceptions and intentions to learn genome sequencing results for differing disease risks (e.g., medically actionable, nonmedically actionable, carrier status) and to use this information to change their lifestyle/health behaviors. Results Risk perceptions (absolute, comparative, and experiential) were largely unassociated with intentions to learn sequencing results. Dispositional optimism and comparative risk perceptions interacted, however, such that individuals higher in optimism reported greater intentions to learn all 3 types of sequencing results when comparative risk was perceived to be higher than when it was perceived to be lower. This interaction was inconsistent for experiential risk and absent for absolute risk. Independent of perceived risk, participants high in dispositional optimism reported greater interest in learning risks for nonmedically actionable disease and carrier status, and greater intentions to use genome information to change their lifestyle/health behaviors. Conclusions The relationship between risk perceptions and intentions may depend on how risk perceptions are assessed and on degree of optimism. PMID:25313897

  8. Improving risk prediction for depression via Elastic Net regression - Results from Korea National Health Insurance Services Data

    PubMed Central

    Kim, Min-hyung; Banerjee, Samprit; Park, Sang Min; Pathak, Jyotishman

    2016-01-01

    Depression, despite its high prevalence, remains severely under-diagnosed across the healthcare system. This demands the development of data-driven approaches that can help screen patients who are at a high risk of depression. In this work, we develop depression risk prediction models that incorporate disease co-morbidities using logistic regression with Elastic Net. Using data from the one million twelve-year longitudinal cohort from Korean National Health Insurance Services (KNHIS), our model achieved an Area Under the Curve (AUC) of the Receiver Operating Characteristic (ROC) of 0.7818, compared to a traditional logistic regression model without co-morbidity analysis (AUC of 0.6992). We also showed co-morbidity adjusted Odds Ratios (ORs), which may be more accurate independent estimate of each predictor variable. In conclusion, inclusion of co-morbidity analysis improved the performance of depression risk prediction models. PMID:28269945

  9. Improving risk prediction for depression via Elastic Net regression - Results from Korea National Health Insurance Services Data.

    PubMed

    Kim, Min-Hyung; Banerjee, Samprit; Park, Sang Min; Pathak, Jyotishman

    2016-01-01

    Depression, despite its high prevalence, remains severely under-diagnosed across the healthcare system. This demands the development of data-driven approaches that can help screen patients who are at a high risk of depression. In this work, we develop depression risk prediction models that incorporate disease co-morbidities using logistic regression with Elastic Net. Using data from the one million twelve-year longitudinal cohort from Korean National Health Insurance Services (KNHIS), our model achieved an Area Under the Curve (AUC) of the Receiver Operating Characteristic (ROC) of 0.7818, compared to a traditional logistic regression model without co-morbidity analysis (AUC of 0.6992). We also showed co-morbidity adjusted Odds Ratios (ORs), which may be more accurate independent estimate of each predictor variable. In conclusion, inclusion of co-morbidity analysis improved the performance of depression risk prediction models.

  10. Predicting changes in aquatic toxicity of chemicals resulting from solvent or dispersant use as vehicle.

    PubMed

    Kikuchi, Mikio; Nakagawa, Masamitsu; Tone, Suguru; Saito, Hotaka; Niino, Tatsuhiro; Nagasawa, Natsumi; Sawai, Jun

    2016-07-01

    The influence of two vehicles (N,N-dimethylformamide [DMF] as solvent and polyoxyethylene hydrogenated castor oil [HCO-40] as a dispersant) on the acute toxicity of eight hydrophobic chemicals with a non-specific mode of action to Daphnia magna was investigated according to the OECD Guidelines for the Testing of Chemicals, No. 202. An increased 48-h EC50 value for D. magna or reduced toxicity resulting from the addition of HCO-40 to the test medium was observed for five of the eight chemicals examined. Each of eight chemicals was dissolved in water at a concentration of either 10 mg/L or 1.0 mg/L, with or without DMF or HCO-40. Silicone film as a model of a biological membrane was then immersed in each solution, and the concentration of each chemical in the water was monitored until equilibrium was reached for each test substance, after which the adsorbed amount of each chemical was determined. The amounts of p-pentylphenol and four other substances with log Pow (1-octanol/water partition coefficient) values greater than 3.4 adsorbed onto the silicone film decreased with increasing concentrations of HCO-40. However, 3-chloro-4-fluoronitrobenzene and two other substances with log Pow values less than 2.6 demonstrated no changes in adsorption with either increasing HCO-40 concentration or the addition of DMF. The reduced adsorption in the presence of a vehicle on the silicone film correlated closely with changes in toxicity. These results indicate that the methodology developed in this study enables the prediction of changes in toxicity resulting from the addition of vehicles to a test system.

  11. Small Engine Technology (SET) - Task 13 ANOPP Noise Prediction for Small Engines: Jet Noise Prediction Module, Wing Shielding Module, and System Studies Results

    NASA Technical Reports Server (NTRS)

    Lieber, Lysbeth; Golub, Robert (Technical Monitor)

    2000-01-01

    This Final Report has been prepared by AlliedSignal Engines and Systems, Phoenix, Arizona, documenting work performed during the period May 1997 through June 1999, under the Small Engines Technology Program, Contract No. NAS3-27483, Task Order 13, ANOPP Noise Prediction for Small Engines. The report specifically covers the work performed under Subtasks 4, 5 and 6. Subtask 4 describes the application of a semi-empirical procedure for jet noise prediction, subtask 5 describes the development of a procedure to predict the effects of wing shielding, and subtask 6 describes the results of system studies of the benefits of the new noise technology on business and regional aircraft.

  12. Control of Warm Compression Stations Using Model Predictive Control: Simulation and Experimental Results

    NASA Astrophysics Data System (ADS)

    Bonne, F.; Alamir, M.; Bonnay, P.

    2017-02-01

    This paper deals with multivariable constrained model predictive control for Warm Compression Stations (WCS). WCSs are subject to numerous constraints (limits on pressures, actuators) that need to be satisfied using appropriate algorithms. The strategy is to replace all the PID loops controlling the WCS with an optimally designed model-based multivariable loop. This new strategy leads to high stability and fast disturbance rejection such as those induced by a turbine or a compressor stop, a key-aspect in the case of large scale cryogenic refrigeration. The proposed control scheme can be used to achieve precise control of pressures in normal operation or to avoid reaching stopping criteria (such as excessive pressures) under high disturbances (such as a pulsed heat load expected to take place in future fusion reactors, expected in the cryogenic cooling systems of the International Thermonuclear Experimental Reactor ITER or the Japan Torus-60 Super Advanced fusion experiment JT-60SA). The paper details the simulator used to validate this new control scheme and the associated simulation results on the SBTs WCS. This work is partially supported through the French National Research Agency (ANR), task agreement ANR-13-SEED-0005.

  13. Ionizing radiation-induced mutagenesis: radiation studies in Neurospora predictive for results in mammalian cells

    NASA Technical Reports Server (NTRS)

    Evans, H. H.; DeMarini, D. M.

    1999-01-01

    Ionizing radiation was the first mutagen discovered and was used to develop the first mutagenicity assay. In the ensuing 70+ years, ionizing radiation became a fundamental tool in understanding mutagenesis and is still a subject of intensive research. Frederick de Serres et al. developed and used the Neurospora crassa ad-3 system initially to explore the mutagenic effects of ionizing radiation. Using this system, de Serres et al. demonstrated the dependence of the frequency and spectra of mutations induced by ionizing radiation on the dose, dose rate, radiation quality, repair capabilities of the cells, and the target gene employed. This work in Neurospora predicted the subsequent observations of the mutagenic effects of ionizing radiation in mammalian cells. Modeled originally on the mouse specific-locus system developed by William L. Russell, the N. crassa ad-3 system developed by de Serres has itself served as a model for interpreting the results in subsequent systems in mammalian cells. This review describes the primary findings on the nature of ionizing radiation-induced mutagenesis in the N. crassa ad-3 system and the parallel observations made years later in mammalian cells.

  14. Colloid filtration in surface dense vegetation: experimental results and theoretical predictions.

    PubMed

    Wu, Lei; Muñoz-Carpena, Rafael; Gao, Bin; Yang, Wen; Pachepsky, Yakov A

    2014-04-01

    Understanding colloid and colloid-facilitated contaminant transport in overland flow through dense vegetation is important to protect water quality in the environment, especially for water bodies receiving agricultural and urban runoff. In previous studies, a single-stem efficiency theory for rigid and clean stem systems was developed to predict colloid filtration by plant stems of vegetation in laminar overland flow. Hence, in order to improve the accuracy of the single-stem efficiency theory to real dense vegetation system, we incorporated the effect of natural organic matter (NOM) on the filtration of colloids by stems. Laboratory dense vegetation flow chamber experiments and model simulations were used to determine the kinetic deposition (filtration) rate of colloids under various conditions. The results show that, in addition to flow hydrodynamics and solution chemistry, steric repulsion afforded by NOM layer on the plants stem surface also plays a significant role in controlling colloid deposition on vegetation in overland flow. For the first time, a refined single-stem efficiency theory with considerations of the NOM effect is developed that describes the experimental data with good accuracy. This theory can be used to not only help construct and refine mathematical models of colloid transport in real vegetation systems in overland flow, but also inform the development of theories of colloid deposition on NOM-coated surfaces in natural, engineered, and biomedical systems.

  15. Verification of Numerical Weather Prediction Model Results for Energy Applications in Latvia

    NASA Astrophysics Data System (ADS)

    Sīle, Tija; Cepite-Frisfelde, Daiga; Sennikovs, Juris; Bethers, Uldis

    2014-05-01

    A resolution to increase the production and consumption of renewable energy has been made by EU governments. Most of the renewable energy in Latvia is produced by Hydroelectric Power Plants (HPP), followed by bio-gas, wind power and bio-mass energy production. Wind and HPP power production is sensitive to meteorological conditions. Currently the basis of weather forecasting is Numerical Weather Prediction (NWP) models. There are numerous methodologies concerning the evaluation of quality of NWP results (Wilks 2011) and their application can be conditional on the forecast end user. The goal of this study is to evaluate the performance of Weather Research and Forecast model (Skamarock 2008) implementation over the territory of Latvia, focusing on forecasting of wind speed and quantitative precipitation forecasts. The target spatial resolution is 3 km. Observational data from Latvian Environment, Geology and Meteorology Centre are used. A number of standard verification metrics are calculated. The sensitivity to the model output interpretation (output spatial interpolation versus nearest gridpoint) is investigated. For the precipitation verification the dichotomous verification metrics are used. Sensitivity to different precipitation accumulation intervals is examined. Skamarock, William C. and Klemp, Joseph B. A time-split nonhydrostatic atmospheric model for weather research and forecasting applications. Journal of Computational Physics. 227, 2008, pp. 3465-3485. Wilks, Daniel S. Statistical Methods in the Atmospheric Sciences. Third Edition. Academic Press, 2011.

  16. LNG fires: a review of experimental results, models and hazard prediction challenges.

    PubMed

    Raj, Phani K

    2007-02-20

    A number of experimental investigations of LNG fires (of sizes 35 m diameter and smaller) were undertaken, world wide, during the 1970s and 1980s to study their physical and radiative characteristics. This paper reviews the published data from several of these tests including from the largest test to date, the 35 m, Montoir tests. Also reviewed in this paper is the state of the art in modeling LNG pool and vapor fires, including thermal radiation hazard modeling. The review is limited to considering the integral and semi-empirical models (solid flame and point source); CFD models are not reviewed. Several aspects of modeling LNG fires are reviewed including, the physical characteristics, such as the (visible) fire size and shape, tilt and drag in windy conditions, smoke production, radiant thermal output, etc., and the consideration of experimental data in the models. Comparisons of model results with experimental data are indicated and current deficiencies in modeling are discussed. The requirements in the US and European regulations related to LNG fire hazard assessment are reviewed, in brief, in the light of model inaccuracies, criteria for hazards to people and structures, and the effects of mitigating circumstances. The paper identifies: (i) critical parameters for which there exist no data, (ii) uncertainties and unknowns in modeling and (iii) deficiencies and gaps in current regulatory recipes for predicting hazards.

  17. Magnetic properties of a Kramers doublet. An univocal bridge between experimental results and theoretical predictions.

    PubMed

    Alonso, P J; Martínez, J I

    2015-06-01

    The magnetic response of a Kramers doublet is analyzed in a general case taking into account only the formal properties derived from time reversal operation. It leads to a definition of a matrix G (gyromagnetic matrix) whose expression depends on the chosen reference frame and on the Kramers conjugate basis used to describe the physical system. It is shown that there exists a reference frame and a suitable Kramers conjugate basis that gives a diagonal form for the G-matrix with all non-null elements having the same sign. A detailed procedure for obtaining this canonical expression of G is presented when the electronic structure of the KD is known regardless the level of the used theory. This procedure provides a univocal way to compare the theoretical predictions with the experimental results obtained from a complete set of magnetic experiments. In this way the problems arising from ambiguities in the g-tensor definition are overcome. This procedure is extended to find a spin-Hamiltonian suitable for describing the magnetic behavior of a pair of weakly coupled Kramers systems in the multispin scheme when the interaction between the two moieties as well as the individual Zeeman interaction are small enough as compared with ligand field splitting. Explicit relations between the physical interaction and the parameters of such a spin-Hamiltonian are also obtained.

  18. Comparison of RAGE Hydrocode Mars Impact Model Results to Scaling Law Predictions

    NASA Astrophysics Data System (ADS)

    Plesko, Catherine S.; Wohletz, K. H.; Coker, R. F.; Asphaug, E.; Gittings, M. L.

    2007-10-01

    Impact devolatilization has been proposed by Segura et al. (2002) and Carr (1996) as a mechanism for triggering sporadic, intense precipitation on Mars. We seek to examine this hypothesis, specifically to determine the lower bound on possible energy/size scales, and thus an upper bound on the frequency of such events. To do this, we employ various analytical and numerical modeling techniques including the RAGE hydrocode. RAGE (Baltrusaitis et al. 1996) is an Eulerian Hydrocode that runs in up to three dimensions and incorporates a variety of detailed equations of state including the temperature-based SESAME tables maintained by LANL. In order to validate RAGE hydrocode results at the scale of moderate to large asteroid impacts, we compare simplified models of vertical impacts of objects of diameter 10 -100 km into homogeneous basalt targets under Martian conditions to pressure scaling law predictions (Holsapple 1993, e.g. Tables 3-4) for the same scenario. Peak pressures are important to the volatile mobilization question (Stewart and Ahrens, 2005), thus it is of primary importance for planned future modeling efforts to confirm that pressures in RAGE are well behaved. Knowledge of the final crater geometry and the fate of ejecta are not required to understand our main question: to what depth and radius are subsurface volatiles are mobilized, for a given impact and target? This effort is supported by LANL/IGPP (CSP, RFC, KHW, MLG) and by NASA PG&G "Small Bodies and Planetary Collisions" (EA).

  19. Local lung deposition of ultrafine particles in healthy adults: experimental results and theoretical predictions

    PubMed Central

    2016-01-01

    Background Ultrafine particles (UFP) of biogenic and anthropogenic origin occur in high numbers in the ambient atmosphere. In addition, aerosols containing ultrafine powders are used for the inhalation therapy of various diseases. All these facts make it necessary to obtain comprehensive knowledge regarding the exact behavior of UFP in the respiratory tract. Methods Theoretical simulations of local UFP deposition are based on previously conducted inhalation experiments, where particles with various sizes (0.04, 0.06, 0.08, and 0.10 µm) were administered to the respiratory tract by application of the aerosol bolus technique. By the sequential change of the lung penetration depth of the inspired bolus, different volumetric lung regions could be generated and particle deposition in these regions could be evaluated. The model presented in this contribution adopted all parameters used in the experiments. Besides the obligatory comparison between practical and theoretical data, also advanced modeling predictions including the effect of varying functional residual capacity (FRC) and respiratory flow rate were conducted. Results Validation of the UFP deposition model shows that highest deposition fractions occur in those volumetric lung regions corresponding to the small and partly alveolated airways of the tracheobronchial tree. Particle deposition proximal to the trachea is increased in female probands with respect to male subjects. Decrease of both the FRC and the respiratory flow rate results in an enhancement of UFP deposition. Conclusions The study comes to the conclusion that deposition of UFP taken up via bolus inhalation is influenced by a multitude of factors, among which lung morphometry and breathing conditions play a superior role. PMID:27942511

  20. Bankruptcy prediction for credit risk using neural networks: a survey and new results.

    PubMed

    Atiya, A F

    2001-01-01

    The prediction of corporate bankruptcies is an important and widely studied topic since it can have significant impact on bank lending decisions and profitability. This work presents two contributions. First we review the topic of bankruptcy prediction, with emphasis on neural-network (NN) models. Second, we develop an NN bankruptcy prediction model. Inspired by one of the traditional credit risk models developed by Merton (1974), we propose novel indicators for the NN system. We show that the use of these indicators in addition to traditional financial ratio indicators provides a significant improvement in the (out-of-sample) prediction accuracy (from 81.46% to 85.5% for a three-year-ahead forecast).

  1. Prediction of psychological functioning one year after the predictive test for Huntington's disease and impact of the test result on reproductive decision making.

    PubMed

    Decruyenaere, M; Evers-Kiebooms, G; Boogaerts, A; Cassiman, J J; Cloostermans, T; Demyttenaere, K; Dom, R; Fryns, J P; Van den Berghe, H

    1996-09-01

    For people at risk for Huntington's disease, the anxiety and uncertainty about the future may be very burdensome and may be an obstacle to personal decision making about important life issues, for example, procreation. For some at risk persons, this situation is the reason for requesting predictive DNA testing. The aim of this paper is two-fold. First, we want to evaluate whether knowing one's carrier status reduces anxiety and uncertainty and whether it facilitates decision making about procreation. Second, we endeavour to identify pretest predictors of psychological adaptation one year after the predictive test (psychometric evaluation of general anxiety, depression level, and ego strength). The impact of the predictive test result was assessed in 53 subjects tested, using pre- and post-test psychometric measurement and self-report data of follow up interviews. Mean anxiety and depression levels were significantly decreased one year after a good test result; there was no significant change in the case of a bad test result. The mean personality profile, including ego strength, remained unchanged one year after the test. The study further shows that the test result had a definite impact on reproductive decision making. Stepwise multiple regression analyses were used to select the best predictors of the subject's post-test reactions. The results indicate that a careful evaluation of pretest ego strength, depression level, and coping strategies may be helpful in predicting post-test reactions, independently of the carrier status. Test result (carrier/ non-carrier), gender, and age did not significantly contribute to the prediction. About one third of the variance of post-test anxiety and depression level and more than half of the variance of ego strength was explained, implying that other psychological or social aspects should also be taken into account when predicting individual post-test reactions.

  2. Predictive factors for a severe clinical course in ulcerative colitis: Results from population-based studies

    PubMed Central

    Wanderås, Magnus Hofrenning; Moum, Bjørn A; Høivik, Marte Lie; Hovde, Øistein

    2016-01-01

    Ulcerative colitis (UC) is characterized by chronic inflammation of the large bowel in genetically susceptible individuals exposed to environmental risk factors. The disease course can be difficult to predict, with symptoms ranging from mild to severe. There is no generally accepted definition of severe UC, and no single outcome is sufficient to classify a disease course as severe. There are several outcomes indicating a severe disease course, including progression of the disease’s extension, a high relapse rate, the development of acute severe colitis, colectomy, the occurrence of colorectal cancer and UC-related mortality. When evaluating a patient’s prognosis, it is helpful to do so in relation to these outcomes. Using these outcomes also makes it easier to isolate factors predictive of severe disease. The aims of this article are to evaluate different disease outcomes and to present predictive factors for these outcomes. PMID:27158539

  3. Imprecision in predicted dose from /sup 137/Cs resulting from biological variability

    SciTech Connect

    Dunning, D.E. Jr.; Schwarz, G.

    1981-01-01

    The variability of observed values of human metabolic and physiological characteristics which influence estimates of dose from ingestion of a unit of Cesium-137 activity, and the subsequent predicted total-body dose commitment is analyzed. The analysis is based on extensive literature review and statistical comparison of parameter variability, correlation and reliability. (PSB)

  4. Colloid filtration in surface dense vegetation: Experimental results and theoretical predictions

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Understanding colloid and colloid-facilitated contaminant transport in overland flow through dense vegetation is essential to protect water quality for the environment. In previous studies, a single-stem efficiency theory for rigid and clean stem systems has been developed to predict colloid filtrat...

  5. Norming of a Basic Learning Exam and Its Use to Predict GED Results.

    ERIC Educational Resources Information Center

    Waggener, Robert; And Others

    A large scale study of local norms that are directly related to the interests of military education counselors is described. In a cooperative effort, the U.S. Armed Forces Institute and the Test Department of Harcourt Brace Jovanovich, Inc. normed the Adult Basic Learning Examination (ABLE) and validated its utility in predicting success on the…

  6. Modelling Study at Kutlular Copper FIELD with Spat This Study, Evaluation Steps of Copper Mine Field SP Data Are Shown How to Reach More Accurate Results for SP Inversion Method.

    NASA Astrophysics Data System (ADS)

    Sahin, O. K.; Asci, M.

    2014-12-01

    At this study, determination of theoretical parameters for inversion process of Trabzon-Sürmene-Kutlular ore bed anomalies was examined. Making a decision of which model equation can be used for inversion is the most important step for the beginning. It is thought that will give a chance to get more accurate results. So, sections were evaluated with sphere-cylinder nomogram. After that, same sections were analyzed with cylinder-dike nomogram to determine the theoretical parameters for inversion process for every single model equations. After comparison of results, we saw that only one of them was more close to parameters of nomogram evaluations. But, other inversion result parameters were different from their nomogram parameters.

  7. Accurate spectral color measurements

    NASA Astrophysics Data System (ADS)

    Hiltunen, Jouni; Jaeaeskelaeinen, Timo; Parkkinen, Jussi P. S.

    1999-08-01

    Surface color measurement is of importance in a very wide range of industrial applications including paint, paper, printing, photography, textiles, plastics and so on. For a demanding color measurements spectral approach is often needed. One can measure a color spectrum with a spectrophotometer using calibrated standard samples as a reference. Because it is impossible to define absolute color values of a sample, we always work with approximations. The human eye can perceive color difference as small as 0.5 CIELAB units and thus distinguish millions of colors. This 0.5 unit difference should be a goal for the precise color measurements. This limit is not a problem if we only want to measure the color difference of two samples, but if we want to know in a same time exact color coordinate values accuracy problems arise. The values of two instruments can be astonishingly different. The accuracy of the instrument used in color measurement may depend on various errors such as photometric non-linearity, wavelength error, integrating sphere dark level error, integrating sphere error in both specular included and specular excluded modes. Thus the correction formulas should be used to get more accurate results. Another question is how many channels i.e. wavelengths we are using to measure a spectrum. It is obvious that the sampling interval should be short to get more precise results. Furthermore, the result we get is always compromise of measuring time, conditions and cost. Sometimes we have to use portable syste or the shape and the size of samples makes it impossible to use sensitive equipment. In this study a small set of calibrated color tiles measured with the Perkin Elmer Lamda 18 and the Minolta CM-2002 spectrophotometers are compared. In the paper we explain the typical error sources of spectral color measurements, and show which are the accuracy demands a good colorimeter should have.

  8. The effect of ocean tides on the earth's rotation as predicted by the results of an ocean tide model

    NASA Technical Reports Server (NTRS)

    Gross, Richard S.

    1993-01-01

    The published ocean tidal angular momentum results of Seiler (1991) are used to predict the effects of the most important semidiurnal, diurnal, and long period ocean tides on the earth's rotation. The separate, as well as combined, effects of ocean tidal currents and sea level height changes on the length-of-day, UT1, and polar motion are computed. The predicted polar motion results reported here account for the presence of the free core nutation and are given in terms of the motion of the celestial ephemeris pole so that they can be compared directly to the results of observations. Outside the retrograde diurnal tidal band, the summed effect of the semidiurnal and diurnal ocean tides studied here predict peak-to-peak polar motion amplitudes as large as 2 mas. Within the retrograde diurnal tidal band, the resonant enhancement caused by the free core nutation leads to predicted polar motion amplitudes as large as 9 mas.

  9. Synthesising empirical results to improve predictions of post-wildfire runoff and erosion response

    USGS Publications Warehouse

    Shakesby, Richard A.; Moody, John A.; Martin, Deborah A.; Robichaud, Peter R.

    2016-01-01

    Advances in research into wildfire impacts on runoff and erosion have demonstrated increasing complexity of controlling factors and responses, which, combined with changing fire frequency, present challenges for modellers. We convened a conference attended by experts and practitioners in post-wildfire impacts, meteorology and related research, including modelling, to focus on priority research issues. The aim was to improve our understanding of controls and responses and the predictive capabilities of models. This conference led to the eight selected papers in this special issue. They address aspects of the distinctiveness in the controls and responses among wildfire regions, spatiotemporal rainfall variability, infiltration, runoff connectivity, debris flow formation and modelling applications. Here we summarise key findings from these papers and evaluate their contribution to improving understanding and prediction of post-wildfire runoff and erosion under changes in climate, human intervention and population pressure on wildfire-prone areas.

  10. Hamilton-Jacobi approach for quasi-exponential inflation: predictions and constraints after Planck 2015 results

    NASA Astrophysics Data System (ADS)

    Videla, Nelson

    2017-03-01

    In the present work we study the consequences of considering an inflationary universe model in which the Hubble rate has a quasi-exponential dependence in the inflaton field, given by H(φ )=H_{inf}\\exp [{φ /m_p}/{p( 1+φ /m_p) }]. We analyze the inflation dynamics under the Hamilton-Jacobi approach, which allows us to consider H(φ ), rather than V(φ ), as the fundamental quantity to be specified. By comparing the theoretical predictions of the model together with the allowed contour plots in the n_s-r plane and the amplitude of primordial scalar perturbations from the latest Planck data, the parameters charactering this model are constrained. The model predicts values for the tensor-to-scalar ratio r and for the running of the scalar spectral index dn_s/ d ln k consistent with the current bounds imposed by Planck, and we conclude that the model is viable.

  11. Plans and Example Results for the 2nd AIAA Aeroelastic Prediction Workshop

    NASA Technical Reports Server (NTRS)

    Heeg, Jennifer; Chwalowski, Pawel; Schuster, David M.; Raveh, Daniella; Jirasek, Adam; Dalenbring, Mats

    2015-01-01

    This paper summarizes the plans for the second AIAA Aeroelastic Prediction Workshop. The workshop is designed to assess the state-of-the-art of computational methods for predicting unsteady flow fields and aeroelastic response. The goals are to provide an impartial forum to evaluate the effectiveness of existing computer codes and modeling techniques, and to identify computational and experimental areas needing additional research and development. This paper provides guidelines and instructions for participants including the computational aerodynamic model, the structural dynamic properties, the experimental comparison data and the expected output data from simulations. The Benchmark Supercritical Wing (BSCW) has been chosen as the configuration for this workshop. The analyses to be performed will include aeroelastic flutter solutions of the wing mounted on a pitch-and-plunge apparatus.

  12. Prediction of subsidence resulting from creep closure of solutioned-mined caverns in salt domes

    SciTech Connect

    Neal, J.T.

    1991-01-01

    The prediction of subsidence rates over a range of areal configurations of solution-mined caverns in salt domes is possible, based on some fifty years of history in solution mining. Several approaches contribute to predictions: site-specific observations obtained from subsidence monitoring; numerical modeling, now becoming more practicable and credible; salt-creep data from testing; and rule-of-thumb methods, based on experience. All of these approaches contribute to understanding subsidence but none are totally reliable alone. The example of subsidence occurring at the Strategic Petroleum Reserve sites demonstrates several principles of cavern creep closure, the main cause of the subsidence, and shows that reliable projections of future subsidence are possible. 13 refs., 6 figs.

  13. Prediction of sonic boom from experimental near-field overpressure data. Volume 1: Method and results

    NASA Technical Reports Server (NTRS)

    Glatt, C. R.; Hague, D. S.; Reiners, S. J.

    1975-01-01

    A computerized procedure for predicting sonic boom from experimental near-field overpressure data has been developed. The procedure extrapolates near-field pressure signatures for a specified flight condition to the ground by the Thomas method. Near-field pressure signatures are interpolated from a data base of experimental pressure signatures. The program is an independently operated ODIN (Optimal Design Integration) program which obtains flight path information from other ODIN programs or from input.

  14. Advanced Durability Analysis. Volume 2. Analytical Predictions, Test Results and Analytical Correlations

    DTIC Science & Technology

    1989-02-27

    used for the back-extrapolation. Recommendations for durability analysis are as follows: (1) define the equivalent initial flaw size distribution ...WAFXHR4 Data Set) for Cumulative Distribution of Service Time to Reach Crack Size x1 -0.59" Based on DCGA- DCGA. xiv List of Figures (Continued) Fiaur. ag ...be used to make predictions for the probability bf crack exceedance at any service time, 7’ , and the cumulative distribution of service time to

  15. Latest COBE results, large-scale data, and predictions of inflation

    NASA Technical Reports Server (NTRS)

    Kashlinsky, A.

    1992-01-01

    One of the predictions of the inflationary scenario of cosmology is that the initial spectrum of primordial density fluctuations (PDFs) must have the Harrison-Zeldovich (HZ) form. Here, in order to test the inflationary scenario, predictions of the microwave background radiation (MBR) anisotropies measured by COBE are computed based on large-scale data for the universe and assuming Omega-1 and the HZ spectrum on large scales. It is found that the minimal scale where the spectrum can first enter the HZ regime is found, constraining the power spectrum of the mass distribution to within the bias factor b. This factor is determined and used to predict parameters of the MBR anisotropy field. For the spectrum of PDFs that reaches the HZ regime immediately after the scale accessible to the APM catalog, the numbers on MBR anisotropies are consistent with the COBE detections and thus the standard inflation can indeed be considered a viable theory for the origin of the large-scale structure in the universe.

  16. Sensitivity and dependence of mesoscale downscaled prediction results on different parameterizations of convection and cloud microphysics

    NASA Astrophysics Data System (ADS)

    Remesan, R.; Bellerby, T.

    2012-04-01

    These days as operational real-time flood forecasting and warning systems rely more on high resolution mesoscale models employed with coupling system of hydrological models. So it is inevitable to assess prediction sensitivity or disparity in collection with selection of different cumulus and microphysical parameterization schemes, to assess the possible uncertainties associated with mesoscale downscaling. This study investigates the role of physical parameterization in mesoscale model simulations on simulation of unprecedented heavy rainfall over Yorkshire-Humberside in United Kingdom during 1-14th March, 1999. The study has used a popular mesoscale numerical weather prediction model named Advanced Research Weather Research Forecast model (version 3.3) which was developed at the National Center for Atmospheric Research (NCAR) in the USA. This study has performed a comprehensive evaluation of four cumulus parameterization schemes (CPSs) [Kian-Fritsch (KF), Betts-Miller-Janjic (BMJ) and Grell-Devenyi ensemble (GD)] and five microphysical schemes Lin et al scheme, older Thompson scheme, new Thompson scheme, WRF Single Moment - 6 class scheme, and WRF Single Moment - 5 class scheme] to identify how their inclusion influences the mesoscale model's meteorological parameter estimation capabilities and related uncertainties in prediction. The case study was carried out at the Upper River Derwent catchment in Northern Yorkshire, England using both the ERA-40 reanalysis data and the land based observation data.

  17. Au Lα x-rays induced by photons from 241Am: Comparison of experimental results and the predictions of PENELOPE.

    PubMed

    Gonzales, D; Requena, S; Williams, S

    2012-01-01

    The results of experiments performed, measuring the Lα x-rays emitted by Au due to excitation by photons of various energies from an (241)Am sample at forward-scattered angles in the range 0° to 65°, are compared to the predictions of the Monte Carlo code, PENELOPE. The experimental data are in good agreement with the predictions of the program. A comparison of the angular distributions of the probability densities (as predicted by the program) related to the Au Lα and Lβ x-rays suggests that PENELOPE does not simulate the phenomena described by Flügge et al. (1972).

  18. Beam hardening artifacts in micro-computed tomography scanning can be reduced by X-ray beam filtration and the resulting images can be used to accurately measure BMD.

    PubMed

    Meganck, Jeffrey A; Kozloff, Kenneth M; Thornton, Michael M; Broski, Stephen M; Goldstein, Steven A

    2009-12-01

    Bone mineral density (BMD) measurements are critical in many research studies investigating skeletal integrity. For pre-clinical research, micro-computed tomography (microCT) has become an essential tool in these studies. However, the ability to measure the BMD directly from microCT images can be biased by artifacts, such as beam hardening, in the image. This three-part study was designed to understand how the image acquisition process can affect the resulting BMD measurements and to verify that the BMD measurements are accurate. In the first part of this study, the effect of beam hardening-induced cupping artifacts on BMD measurements was examined. In the second part of this study, the number of bones in the X-ray path and the sampling process during scanning was examined. In the third part of this study, microCT-based BMD measurements were compared with ash weights to verify the accuracy of the measurements. The results indicate that beam hardening artifacts of up to 32.6% can occur in sample sizes of interest in studies investigating mineralized tissue and affect mineral density measurements. Beam filtration can be used to minimize these artifacts. The results also indicate that, for murine femora, the scan setup can impact densitometry measurements for both cortical and trabecular bone and morphologic measurements of trabecular bone. Last, when a scan setup that minimized all of these artifacts was used, the microCT-based measurements correlated well with ash weight measurements (R(2)=0.983 when air was excluded), indicating that microCT can be an accurate tool for murine bone densitometry.

  19. Review of ESOC re-entry prediction results of Salyut-7/Kosmos-1686

    NASA Technical Reports Server (NTRS)

    Klinkrad, H.

    1991-01-01

    An overview of activities at ESA/ESOC during the followup of the Salyut-7/Kosmos-1686 decay, and of related cooperations with space agencies, research institutes, and national bodies within the ESA Member States, within the U.S. and within the USSR, is presented. A postflight analysis indicated areas for improvement in the forecast procedures, especially during the last day of the orbital lifetime. Corresponding revised decay predictions are presented for Salyut-7/Kosmos-1686, and the improved procedures are verified by an analysis of the reentries of Kosmos-1402A and Kosmos-1402C.

  20. Procalcitonin for the early prediction of renal parenchymal involvement in children with UTI: preliminary results.

    PubMed

    Kotoula, Aggeliki; Gardikis, Stefanos; Tsalkidis, Aggelos; Mantadakis, Elpis; Zissimopoulos, Athanassios; Kambouri, Katerina; Deftereos, Savvas; Tripsianis, Gregorios; Manolas, Konstantinos; Chatzimichael, Athanassios; Vaos, George

    2009-01-01

    In order to establish the most reliable marker for distinguishing urinary tract infections (UTI) with and without renal parenchymal involvement (RPI), we recorded the clinical features and admission leukocyte count, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and serum procalcitonin (PCT) in 57 children (including 43 girls) aged 2-108 months admitted with a first episode of UTI. RPI was evaluated by Tc-99m dimercaptosuccinic acid (DMSA) scintigraphy within 7 days of admission. To establish cut-off points for ESR, CRP, and PCT, we used receiver operating characteristics curves and compared the area under the curve for ESR, CRP, and PCT. Twenty-seven children were diagnosed as having RPI based on positive renal scintigraphy. A body temperature of >38 degrees C, a history of diarrhea, and poor oral intake were more common in patients with RPI. ESR, CRP, and PCT, but not leukocyte count, were significantly higher in patients with RPI (P < 0.001). PCT was more sensitive and specific for the diagnosis of upper versus lower UTI than ESR and CRP. Using a cut-off value of 0.85 ng/ml, PCT had the best performance, with sensitivity, specificity, and positive and negative predictive values of 89%, 97%, 96%, and 91% respectively. Serum PCT is a better marker than ESR, CRP, and leukocyte count for the early prediction of RPI in children with a first episode of UTI.

  1. Elder Mistreatment Predicts Later Physical and Psychological Health: Results from a National Longitudinal Study

    PubMed Central

    Wong, Jaclyn S.; Waite, Linda J.

    2017-01-01

    Stress process theory predicts that elder mistreatment leads to declines in health, and that social support buffers its ill effects. We test this theory using nationally representative, longitudinal data from 2,261 older adults in the National Social Life Health and Aging Project. We regress psychological and physical health in 2010/2011 on verbal and financial mistreatment experience in 2005/2006 and find that the mistreated have more anxiety symptoms, greater feelings of loneliness, and worse physical and functional health five years later, than those who did not report mistreatment. In particular, we show a novel association between financial mistreatment and functional health. Contrary to the stress buffering hypothesis, we find little evidence that social support moderates the relationship between mistreatment and health. Our findings point to the lasting impact of mistreatment on health, but show little evidence of a buffering role of social support in this process. PMID:27636657

  2. Daytime continuous polysomnography predicts MSLT results in hypersomnias of central origin.

    PubMed

    Pizza, Fabio; Moghadam, Keivan K; Vandi, Stefano; Detto, Stefania; Poli, Francesca; Mignot, Emmanuel; Ferri, Raffaele; Plazzi, Giuseppe

    2013-02-01

    In the diagnostic work-up of hypersomnias of central origin, the complaint of excessive daytime sleepiness should be objectively confirmed by MSLT findings. Indeed, the features and diagnostic utility of spontaneous daytime sleep at 24 h continuous polysomnography (PSG) have never been investigated. We compared daytime PSG features to MSLT data in 98 consecutive patients presenting with excessive daytime sleepiness and with a final diagnosis of narcolepsy with cataplexy/hypocretin deficiency (n = 39), narcolepsy without cataplexy (n = 7), idiopathic hypersomnia without long sleep time (n = 19), and 'hypersomnia' with normal sleep latency at MSLT (n = 33). Daytime sleep time was significantly higher in narcolepsy-cataplexy but similar in the other groups. Receiver operating characteristics (ROC) curves showed that the number of naps during daytime PSG predicted a mean sleep latency ≤8 min at MSLT with an area under the curve of 0.67 ± 0.05 (P = 0.005). The number of daytime sleep-onset REM periods (SOREMPs) in spontaneous naps strikingly predicted the scheduled occurrence of two or more SOREMPs at MSLT, with an area under the ROC curve of 0.93 ± 0.03 (P < 10(-12) ). One spontaneous SOREMP during daytime had a sensitivity of 96% with specificity of 74%, whereas two SOREMPs had a sensitivity of 75%, with a specificity of 95% for a pathological REM sleep propensity at MSLT. The features of spontaneous daytime sleep well correlated with MSLT findings. Notably, the occurrence of multiple spontaneous SOREMPs during daytime clearly identified patients with narcolepsy, as well as during the MSLT.

  3. Investigations of Fluid-Structure-Coupling and Turbulence Model Effects on the DLR Results of the Fifth AIAA CFD Drag Prediction Workshop

    NASA Technical Reports Server (NTRS)

    Keye, Stefan; Togiti, Vamish; Eisfeld, Bernhard; Brodersen, Olaf P.; Rivers, Melissa B.

    2013-01-01

    The accurate calculation of aerodynamic forces and moments is of significant importance during the design phase of an aircraft. Reynolds-averaged Navier-Stokes (RANS) based Computational Fluid Dynamics (CFD) has been strongly developed over the last two decades regarding robustness, efficiency, and capabilities for aerodynamically complex configurations. Incremental aerodynamic coefficients of different designs can be calculated with an acceptable reliability at the cruise design point of transonic aircraft for non-separated flows. But regarding absolute values as well as increments at off-design significant challenges still exist to compute aerodynamic data and the underlying flow physics with the accuracy required. In addition to drag, pitching moments are difficult to predict because small deviations of the pressure distributions, e.g. due to neglecting wing bending and twisting caused by the aerodynamic loads can result in large discrepancies compared to experimental data. Flow separations that start to develop at off-design conditions, e.g. in corner-flows, at trailing edges, or shock induced, can have a strong impact on the predictions of aerodynamic coefficients too. Based on these challenges faced by the CFD community a working group of the AIAA Applied Aerodynamics Technical Committee initiated in 2001 the CFD Drag Prediction Workshop (DPW) series resulting in five international workshops. The results of the participants and the committee are summarized in more than 120 papers. The latest, fifth workshop took place in June 2012 in conjunction with the 30th AIAA Applied Aerodynamics Conference. The results in this paper will evaluate the influence of static aeroelastic wing deformations onto pressure distributions and overall aerodynamic coefficients based on the NASA finite element structural model and the common grids.

  4. Comparison of the Johnson-Ettinger vapor intrusion screening model predictions with full three-dimensional model results.

    PubMed

    Yao, Yijun; Shen, Rui; Pennell, Kelly G; Suuberg, Eric M

    2011-03-15

    The Johnson-Ettinger vapor intrusion model (J-E model) is the most widely used screening tool for evaluating vapor intrusion potential because of its simplicity and convenience of use. Since its introduction about twenty years ago, the J-E model has become a cornerstone in guidance related to the potential for significant vapor intrusion-related exposures. A few papers have been published that claim it is a conservative predictor of exposure, but there has not been a systematic comparison in the open literature of the J-E model predictions with the results of more complete full three-dimensional descriptions of the phenomenon. In this paper, predictions from a three-dimensional model of vapor intrusion, based upon finite element calculations of homogeneous soil scenarios, are directly compared with the results of the J-E model. These results suggest that there are conditions under which the J-E model predictions might be quite reasonable but that there are also others in which the predictions are low as well as high. Some small modifications to the J-E model are also suggested that can bring its predictions into excellent agreement with those of the much more elaborate 3-D models, in some specific cases of homogeneous soils. Finally, both models were compared with actual field data.

  5. Comparison of the Johnson-Ettinger Vapor Intrusion Screening Model Predictions with Full Three-Dimensional Model Results

    PubMed Central

    Yao, Yijun; Shen, Rui; Pennell, Kelly G.; Suuberg, Eric M.

    2013-01-01

    The Johnson-Ettinger vapor intrusion model (J-E model) is the most widely used screening tool for evaluating vapor intrusion potential because of its simplicity and convenience of use. Since its introduction about twenty years ago, the J-E model has become a cornerstone in guidance related to the potential for significant vapor intrusion-related exposures. A few papers have been published that claim it is a conservative predictor of exposure, but there has not been a systematic comparison in the open literature of the J-E model predictions with the results of more complete full three-dimensional descriptions of the phenomenon. In this paper, predictions from a three-dimensional model of vapor intrusion, based upon finite element calculations of homogeneous soil scenarios, are directly compared with the results of the J-E model. These results suggest conditions under which the J-E model predictions might be quite reasonable, but others in which the predictions are low as well as high. Some small modifications to the J-E model are also suggested that can bring its predictions into excellent agreement with those of the much more elaborate 3-D models, in some specific cases of homogeneous soils. Finally, both models were compared with actual field data. PMID:21344848

  6. Results.

    ERIC Educational Resources Information Center

    Zemsky, Robert; Shaman, Susan; Shapiro, Daniel B.

    2001-01-01

    Describes the Collegiate Results Instrument (CRI), which measures a range of collegiate outcomes for alumni 6 years after graduation. The CRI was designed to target alumni from institutions across market segments and assess their values, abilities, work skills, occupations, and pursuit of lifelong learning. (EV)

  7. Complex-shaped hardened parts fatigue limit prediction according to the witness sample study results

    NASA Astrophysics Data System (ADS)

    Surgutanova, Yu N.; Mikushev, N. N.; Surgutanov, N. A.; Kiselev, P. E.; Shlyapnikov, P. A.; Meshcheryakova, A. A.

    2016-11-01

    The aim of this study is to investigate the possibility of assessment of the effect of preparatory surface plastic deformation by hydraulic shot blasting on the fatigue strength of cylindrical parts of different diameters (10-40 mm) of D16T alloy with circular notches of semicircular section, based on measurements of residual stress (initial deformations) of a witness sample. The residual stresses of smooth parts were used to calculate the residual stresses of parts with stress raisers. These were used to predict the increment of these parts fatigue limit caused by hardening hydraulic shot blasting. It was found that the highest compressive residual stresses in the smooth parts obtained through calculations differ from the observed values not more than by 7%, and in notched parts by 8%. Using the criterion of mean integral residual stresses, we calculate the increments of the fatigue limit of parts due to superficial hardening. The discrepancy between the experimental and calculated increment values of the fatigue limit of hardened parts with raisers does not exceed 17%.

  8. Predictive Comprehensive Geriatric Assessment in elderly prostate cancer patients: the prospective observational scoop trial results.

    PubMed

    Della Pepa, Chiara; Cavaliere, Carla; Rossetti, Sabrina; Di Napoli, Marilena; Cecere, Sabrina C; Crispo, Anna; De Sangro, Carlo; Rossi, Emanuela; Turitto, Dino; Germano, Domenico; Iovane, Gelsomina; Berretta, Massimiliano; D'Aniello, Carmine; Pisconti, Salvatore; Maiorino, Luigi; Daniele, Bruno; Gridelli, Cesare; Pignata, Sandro; Facchini, Gaetano

    2017-01-01

    The Comprehensive Geriatric Assessment (CGA) represents the future of the geriatric oncology to reduce toxicities and treatment-related hospitalization in the elderly. Most patients receiving docetaxel for metastatic castration-resistant prostate cancer are in their seventies or older. We explored the efficacy of the CGA in predicting chemotherapy feasibility and response to docetaxel in a cohort of 24 patients aged at least 70. This was an observational, prospective study involving 24 patients who were 70 years of age or older and about to start chemotherapy with docetaxel for metastatic castration-resistant prostate cancer; we performed a CGA including five domains and divided our patients into 'healthy' and 'frail'; the relations between general condition and (i) early chemotherapy discontinuation and (ii) response to docetaxel were explored. We found a statistically significant relationship between frailty assessed by CGA and early docetaxel discontinuation; we also found an association between frailty and response to chemotherapy, but this did not reach statistical significance. A geriatric assessment before starting chemotherapy may help clinicians to recognize frail patients, and hence to reduce toxicities and early treatment discontinuation. Further analyses are required to simplify the CGA tools and to facilitate its incorporation into routine clinical practice.

  9. Technique for predicting ground-water discharge to surface coal mines and resulting changes in head

    USGS Publications Warehouse

    Weiss, L.S.; Galloway, D.L.; Ishii, Audrey

    1986-01-01

    Changes in seepage flux and head (groundwater level) from groundwater drainage into a surface coal mine can be predicted by a technique that considers drainage from the unsaturated zone. The user applies site-specific data to precalculated head and seepage-flux profiles. Groundwater flow through hypothetical aquifer cross sections was simulated using the U.S. Geological Survey finite-difference model, VS2D, which considers variably saturated two-dimensional flow. Conceptual models considered were (1) drainage to a first cut, and (2) drainage to multiple cuts, which includes drainage effects of an area surface mine. Dimensionless head and seepage flux profiles from 246 simulations are presented. Step-by-step instructions and examples are presented. Users are required to know aquifer characteristics and to estimate size and timing of the mine operation at a proposed site. Calculated groundwater drainage to the mine is from one excavated face only. First cut considers confined and unconfined aquifers of a wide range of permeabilities; multiple cuts considers unconfined aquifers of higher permeabilities only. The technique, developed for Illinois coal-mining regions that use area surface mining and evaluated with an actual field example, will be useful in assessing potential hydrologic impacts of mining. Application is limited to hydrogeologic settings and mine operations similar to those considered. Fracture flow, recharge, and leakage are nor considered. (USGS)

  10. Accurate monotone cubic interpolation

    NASA Technical Reports Server (NTRS)

    Huynh, Hung T.

    1991-01-01

    Monotone piecewise cubic interpolants are simple and effective. They are generally third-order accurate, except near strict local extrema where accuracy degenerates to second-order due to the monotonicity constraint. Algorithms for piecewise cubic interpolants, which preserve monotonicity as well as uniform third and fourth-order accuracy are presented. The gain of accuracy is obtained by relaxing the monotonicity constraint in a geometric framework in which the median function plays a crucial role.

  11. Factors to predict positive results of gonadotropin releasing hormone stimulation test in girls with suspected precocious puberty.

    PubMed

    Nam, Hyo-Kyoung; Rhie, Young Jun; Son, Chang Sung; Park, Sang Hee; Lee, Kee-Hyoung

    2012-02-01

    Sometimes, the clinical findings and the results of the gonadotropin-releasing hormone (GnRH) stimulation test are inconsistent in girls with early breast development and bone age advancement. We aimed to investigate the factors predicting positive results of the GnRH stimulation test in girls with suspected central precocious puberty (CPP). We reviewed the records of 574 girls who developed breast budding before the age of 8 yr and underwent the GnRH stimulation test under the age of 9 yr. Positive results of the GnRH stimulated peak luteinizing hormone (LH) level were defined as 5 IU/L and over. Girls with the initial positive results (n = 375) showed accelerated growth, advanced bone age and higher serum basal LH, follicle-stimulating hormone, and estradiol levels, compared to those with the initial negative results (n = 199). Girls with the follow-up positive results (n = 64) showed accelerated growth and advanced bone age, compared to those with the follow-up negative results. In the binary logistic regression, the growth velocity ratio was the most significant predictive factor of positive results. We suggest that the rapid growth velocity is the most useful predictive factor for positive results in the GnRH stimulation test in girls with suspected precocious puberty.

  12. Psychoneuroimmunology: an interpretation of experimental and case study evidence towards a paradigm for predictable results.

    PubMed

    Kalt, H W

    2000-07-01

    This paper surveys a number of key experiments and case studies relating to psychoneuroimmunology. It finds that most techniques to influence or even direct the immune system via the mind fall into a series of theoretical categories called passive, active and targeted effects. By examining the results of experiments and studies in the light of these categories a number of important conclusions are drawn. These conclusions explain differences in experimental results, describe those variables that appear to be central to obtaining results, and describe in detail where experimentation should be concentrated to further knowledge of psychoneuroimmunology.

  13. Predicted and flight test results of the performance, stability and control of the space shuttle from reentry to landing

    NASA Technical Reports Server (NTRS)

    Kirsten, P. W.; Richardson, D. F.; Wilson, C. M.

    1983-01-01

    Aerodynaic performance, stability and control data obtained from the first five reentries of the Space Shuttle orbiter are given. Flight results are compared to pedicted data from Mach 26.4 to Mach 0.4. Differences between flight and predicted data as well as probable causes for the discrepancies are given.

  14. Corticoid injection as a predictive factor of results of carpal tunnel release

    PubMed Central

    de Miranda, Giselly Veríssimo; Fernandes, Carlos Henrique; Raduan, Jorge; Meirelles, Lia Miyamoto; dos Santos, João Baptista Gomes; Faloppa, Flávio

    2015-01-01

    OBJECTIVE: To evaluate whether the symptoms relief after local corticoid injection correlate with better results of surgical treatment in carpal tunnel syndrome. METHODS: Between February 2011 and June 2013, 100 wrists of 88 patients were included in the study. All patients were subjected to corticoid injections in the carpal tunnel and evaluated before and after infiltration and surgery. The following parameters were evaluated: visual analog scale (VAS) for pain, Boston questionnaire, sensitivity and strength. RESULTS: Only 28 out of 100 wrists subjected to injection were symptom-free after six months follow up. Sixty out of the 72 patients who did not present relief or relapse symptoms were treated surgically. Surgical results were better regarding VAS, Boston questionnaire and sensitivity in a specific group of patients, which had a longer relief of symptoms after the corticoid injection, with statistical significance. CONCLUSION: Longer relief of symptoms after corticoid injection correlated with better results of surgical treatment. Level of Evidence II, Prognostic Study. PMID:26405432

  15. Comparison of silver, cesium, and strontium release predictions using PARFUME with results from the AGR-1 irradiation experiment

    NASA Astrophysics Data System (ADS)

    Collin, Blaise P.; Petti, David A.; Demkowicz, Paul A.; Maki, John T.

    2015-11-01

    The PARFUME (PARticle FUel ModEl) code was used to predict the release of fission products silver, cesium, and strontium from tristructural isotropic coated fuel particles and compacts during the first irradiation experiment (AGR-1) of the Advanced Gas Reactor Fuel Development and Qualification program. The PARFUME model for the AGR-1 experiment used the fuel compact volume average temperature for each of the 620 days of irradiation to calculate the release of silver, cesium, and strontium from a representative particle for a select number of AGR-1 compacts. Post-irradiation examination (PIE) measurements provided data on release of these fission products from fuel compacts and fuel particles, and retention of silver in the compacts outside of the silicon carbide (SiC) layer. PARFUME-predicted fractional release of silver, cesium, and strontium was determined and compared to the PIE measurements. For silver, comparisons show a trend of over-prediction at low burnup and under-prediction at high burnup. PARFUME has limitations in the modeling of the temporal and spatial distributions of the temperature and burnup across the compacts, which affects the accuracy of its predictions. Nevertheless, the comparisons on silver release lie in the same order of magnitude. Results show an overall over-prediction of the fractional release of cesium by PARFUME. For particles with failed SiC layers, the over-prediction is by a factor of up to 3, corresponding to a potential over-estimation of the diffusivity in uranium oxycarbide (UCO) by a factor of up to 250. For intact particles, whose release is much lower, the over-prediction is by a factor of up to 100, which could be attributed to an over-estimated diffusivity in SiC by about 40% on average. The release of strontium from intact particles is also over-predicted by PARFUME, which also points towards an over-estimated diffusivity of strontium in either SiC or UCO, or possibly both. The measured strontium fractional release

  16. Comparison of silver, cesium, and strontium release predictions using PARFUME with results from the AGR-1 irradiation experiment

    DOE PAGES

    Collin, Blaise P.; Petti, David A.; Demkowicz, Paul A.; ...

    2015-08-22

    The PARFUME (PARticle FUel ModEl) code was used to predict the release of fission products silver, cesium, and strontium from tristructural isotropic coated fuel particles and compacts during the first irradiation experiment (AGR-1) of the Advanced Gas Reactor Fuel Development and Qualification program. The PARFUME model for the AGR-1 experiment used the fuel compact volume average temperature for each of the 620 days of irradiation to calculate the release of silver, cesium, and strontium from a representative particle for a select number of AGR-1 compacts. Post-irradiation examination measurements provided data on release of these fission products from fuel compacts andmore » fuel particles, and retention of silver in the compacts outside of the silicon carbide (SiC) layer. PARFUME-predicted fractional release of silver, cesium, and strontium was determined and compared to the PIE measurements. For silver, comparisons show a trend of over-prediction at low burnup and under-prediction at high burnup. PARFUME has limitations in the modeling of the temporal and spatial distributions of the temperature and burnup across the compacts, which affects the accuracy of its predictions. Nevertheless, the comparisons on silver release lie in the same order of magnitude. Results show an overall over-prediction of the fractional release of cesium by PARFUME. For particles with failed SiC layers, the over-prediction is by a factor of up to 3, corresponding to a potential over-estimation of the diffusivity in uranium oxycarbide (UCO) by a factor of up to 250. For intact particles, whose release is much lower, the over-prediction is by a factor of up to 100, which could be attributed to an over-estimated diffusivity in SiC by about 40% on average. The release of strontium from intact particles is also over-predicted by PARFUME, which also points towards an over-estimated diffusivity of strontium in either SiC or UCO, or possibly both. The measured strontium fractional release

  17. Comparison of silver, cesium, and strontium release predictions using PARFUME with results from the AGR-1 irradiation experiment

    SciTech Connect

    Collin, Blaise P.; Petti, David A.; Demkowicz, Paul A.; Maki, John T.

    2015-08-22

    The PARFUME (PARticle FUel ModEl) code was used to predict the release of fission products silver, cesium, and strontium from tristructural isotropic coated fuel particles and compacts during the first irradiation experiment (AGR-1) of the Advanced Gas Reactor Fuel Development and Qualification program. The PARFUME model for the AGR-1 experiment used the fuel compact volume average temperature for each of the 620 days of irradiation to calculate the release of silver, cesium, and strontium from a representative particle for a select number of AGR-1 compacts. Post-irradiation examination measurements provided data on release of these fission products from fuel compacts and fuel particles, and retention of silver in the compacts outside of the silicon carbide (SiC) layer. PARFUME-predicted fractional release of silver, cesium, and strontium was determined and compared to the PIE measurements. For silver, comparisons show a trend of over-prediction at low burnup and under-prediction at high burnup. PARFUME has limitations in the modeling of the temporal and spatial distributions of the temperature and burnup across the compacts, which affects the accuracy of its predictions. Nevertheless, the comparisons on silver release lie in the same order of magnitude. Results show an overall over-prediction of the fractional release of cesium by PARFUME. For particles with failed SiC layers, the over-prediction is by a factor of up to 3, corresponding to a potential over-estimation of the diffusivity in uranium oxycarbide (UCO) by a factor of up to 250. For intact particles, whose release is much lower, the over-prediction is by a factor of up to 100, which could be attributed to an over-estimated diffusivity in SiC by about 40% on average. The release of strontium from intact particles is also over-predicted by PARFUME, which also points towards an over-estimated diffusivity of strontium in either SiC or UCO, or possibly both. The measured strontium fractional release from

  18. Comparison of fission product release predictions using PARFUME with results from the AGR-1 irradiation experiment

    SciTech Connect

    Blaise Collin

    2014-09-01

    This report documents comparisons between post-irradiation examination measurements and model predictions of silver (Ag), cesium (Cs), and strontium (Sr) release from selected tristructural isotropic (TRISO) fuel particles and compacts during the first irradiation test of the Advanced Gas Reactor program that occurred from December 2006 to November 2009 in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). The modeling was performed using the particle fuel model computer code PARFUME (PARticle FUel ModEl) developed at INL. PARFUME is an advanced gas-cooled reactor fuel performance modeling and analysis code (Miller 2009). It has been developed as an integrated mechanistic code that evaluates the thermal, mechanical, and physico-chemical behavior of fuel particles during irradiation to determine the failure probability of a population of fuel particles given the particle-to-particle statistical variations in physical dimensions and material properties that arise from the fuel fabrication process, accounting for all viable mechanisms that can lead to particle failure. The code also determines the diffusion of fission products from the fuel through the particle coating layers, and through the fuel matrix to the coolant boundary. The subsequent release of fission products is calculated at the compact level (release of fission products from the compact) but it can be assessed at the particle level by adjusting the diffusivity in the fuel matrix to very high values. Furthermore, the diffusivity of each layer can be individually set to a high value (typically 10-6 m2/s) to simulate a failed layer with no capability of fission product retention. In this study, the comparison to PIE focused on fission product release and because of the lack of failure in the irradiation, the probability of particle failure was not calculated. During the AGR-1 irradiation campaign, the fuel kernel produced and released fission products, which migrated through the successive

  19. Feedback about More Accurate versus Less Accurate Trials: Differential Effects on Self-Confidence and Activation

    ERIC Educational Resources Information Center

    Badami, Rokhsareh; VaezMousavi, Mohammad; Wulf, Gabriele; Namazizadeh, Mahdi

    2012-01-01

    One purpose of the present study was to examine whether self-confidence or anxiety would be differentially affected by feedback from more accurate rather than less accurate trials. The second purpose was to determine whether arousal variations (activation) would predict performance. On Day 1, participants performed a golf putting task under one of…

  20. Concepts and Results of New Method for Accurate Ground and In-Flight Calibration of the Particle Spectrometers of the Fast Plasma Investigation on NASA's Magnetospheric MultiScale Mission

    NASA Astrophysics Data System (ADS)

    Gliese, U.; Gershman, D. J.; Dorelli, J.; Avanov, L. A.; Barrie, A. C.; Clark, G. B.; Kujawski, J. T.; Mariano, A. J.; Coffey, V. N.; Tucker, C. J.; Chornay, D. J.; Cao, N. T.; Zeuch, M. A.; Dickson, C.; Smith, D. L.; Salo, C.; MacDonald, E.; Kreisler, S.; Jacques, A. D.; Giles, B. L.; Pollock, C. J.

    2015-12-01

    The Fast Plasma Investigation (FPI) on NASA's Magnetospheric MultiScale (MMS) mission employs 16 Dual Electron Spectrometers and 16 Dual Ion Spectrometers with 4 of each type on each of 4 spacecraft to enable fast (30 ms for electrons; 150 ms for ions) and spatially differentiated measurements of the full 3D particle velocity distributions. This approach presents a new and challenging aspect to the calibration and operation of these instruments on ground and in flight. The response uniformity, the reliability of their calibration and the approach to handling any temporal evolution of these calibrated characteristics all assume enhanced importance in this application, where we attempt to understand the meaning of particle distributions within the ion and electron diffusion regions of magnetically reconnecting plasmas. We have developed a detailed model of the spectrometer detection system, its behavior and its signal, crosstalk and noise sources. Based on this, we have devised a new calibration method that enables accurate and repeatable measurement of micro-channel plate (MCP) gain, signal loss due to variation in MCP gain and crosstalk effects in one single measurement. The foundational concepts of this new calibration method, named threshold scan, are presented. It is shown how this method has been successfully applied both on ground and in-flight to achieve highly accurate and precise calibration of all 64 spectrometers. Calibration parameters that will evolve in flight are determined daily providing a robust characterization of sensor suite performance, as a basis for both in-situ hardware adjustment and data processing to scientific units, throughout mission lifetime. This is shown to be very desirable as the instruments will produce higher quality raw science data that will require smaller post-acquisition data-corrections using results from in-flight derived pitch angle distribution measurements and ground calibration measurements. The practical application

  1. Ceramic material life prediction: A program to translate ANSYS results to CARES/LIFE reliability analysis

    NASA Technical Reports Server (NTRS)

    Vonhermann, Pieter; Pintz, Adam

    1994-01-01

    This manual describes the use of the ANSCARES program to prepare a neutral file of FEM stress results taken from ANSYS Release 5.0, in the format needed by CARES/LIFE ceramics reliability program. It is intended for use by experienced users of ANSYS and CARES. Knowledge of compiling and linking FORTRAN programs is also required. Maximum use is made of existing routines (from other CARES interface programs and ANSYS routines) to extract the finite element results and prepare the neutral file for input to the reliability analysis. FORTRAN and machine language routines as described are used to read the ANSYS results file. Sub-element stresses are computed and written to a neutral file using FORTRAN subroutines which are nearly identical to those used in the NASCARES (MSC/NASTRAN to CARES) interface.

  2. Predictions of the equation of state of cerium yield interesting insights into experimental results

    SciTech Connect

    Cherne, Frank J; Jensen, Brian J; Rigg, Paulo A; Elkin, Vyacheslav M

    2009-01-01

    There has been much interest in the past in understanding the dynamic properties of phase changing materials. In this paper we begin to explore the dynamic properties of the complex material of cerium. Cerium metal is a good candidate material to explore capabilities in determining a dynamic phase diagram on account of its low dynamic phase boundaries, namely, the {gamma}-{alpha}, and {alpha}-liquid phase boundaries. Here we present a combination of experimental results with calculated results to try to understand the dynamic behavior of the material. Using the front surface impact technique, we performed a series of experiments which displayed a rarefaction shock upon release. These experiments show that the reversion shock stresses occur at different magnitudes, allowing us to plot out the {gamma}-{alpha} phase boundary. Applying a multiphase equation of state a broader understanding of the experimental results will be discussed.

  3. Quantitative comparison between theoretical predictions and experimental results for Bragg spectroscopy of a strongly interacting Fermi superfluid

    NASA Astrophysics Data System (ADS)

    Zou, Peng; Kuhnle, Eva D.; Vale, Chris J.; Hu, Hui

    2010-12-01

    Theoretical predictions for the dynamic structure factor of a harmonically trapped Fermi superfluid near the Bose-Einstein condensate-Bardeen-Cooper-Schrieffer (BEC-BCS) crossover are compared with recent Bragg spectroscopy measurements at large transferred momenta. The calculations are based on a random-phase (or time-dependent Hartree-Fock-Gorkov) approximation generalized to the strongly interacting regime. Excellent agreement with experimental spectra at low temperatures is obtained, with no free parameters. Theoretical predictions for zero-temperature static structure factor are also found to agree well with the experimental results and independent theoretical calculations based on the exact Tan relations. The temperature dependence of the structure factors at unitarity is predicted.

  4. Word List Memory Predicts Everyday Function and Problem-Solving in the Elderly: Results from the ACTIVE Cognitive Intervention Trial

    PubMed Central

    Gross, Alden L.; Rebok, George W.; Unverzagt, Frederick W.; Willis, Sherry L.; Brandt, Jason

    2011-01-01

    Data from the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) trial (N=2,802) were analyzed to examine whether word list learning predicts future everyday functioning. Using stepwise random effects modeling, measures from the modified administrations of the Hopkins Verbal Learning Test (HVLT) and the Auditory Verbal Learning Test (AVLT) were independently predictive of everyday IADL functioning, problem-solving, and psychomotor speed. Associations between memory scores and everyday functioning outcomes remained significant across follow-up intervals spanning five years. HVLT total recall score was consistently the strongest predictor of each functional outcome. Results suggest that verbal memory measures are uniquely associated with both current and future functioning and that specific verbal memory tests like the HVLT and AVLT have important clinical utility in predicting future functional ability among older adults. PMID:21069610

  5. Prediction of Asbestos Exposure Resulting From Asbestos Aerosolization Determined Using the Releasable Asbestos Field Sampler (RAFS)

    EPA Science Inventory

    Activity-based sampling (ABS) used to evaluate breathing zone exposure to a contaminant present in soil resulting from various activities, involves breathing zone sampling for contaminants while that activity is performed. A probabilistic model based upon aerosol physics and flui...

  6. Improving Program Results through the Use of Predictive Operational Performance Indicators: A Canadian Case Study

    ERIC Educational Resources Information Center

    Barrados, Maria; Blain, J. S.

    2013-01-01

    In Canada, in-depth evaluations of federal programs are intended to occur every 5 years. As such, evaluation is a periodic retrospective (lag) indicator examining results achieved versus program objectives. In a Canadian context, stand-alone evaluations have proved challenging to implement, time consuming, and not well adapted to annual management…

  7. Is the Presence of a Results-Oriented Professional Learning Community Predictive of Student Achievement?

    ERIC Educational Resources Information Center

    Sullivan, Michael E.

    2013-01-01

    This study investigated the relationships between teacher collaboration practices known as working as a professional learning community (PLC) and student performance. Through a review of the current literature, an operational framework of PLCs was developed that distinguished results-oriented from inquiry-oriented PLCs. The study considered the…

  8. Rapid and accurate evaluation of the quality of commercial organic fertilizers using near infrared spectroscopy.

    PubMed

    Wang, Chang; Huang, Chichao; Qian, Jian; Xiao, Jian; Li, Huan; Wen, Yongli; He, Xinhua; Ran, Wei; Shen, Qirong; Yu, Guanghui

    2014-01-01

    The composting industry has been growing rapidly in China because of a boom in the animal industry. Therefore, a rapid and accurate assessment of the quality of commercial organic fertilizers is of the utmost importance. In this study, a novel technique that combines near infrared (NIR) spectroscopy with partial least squares (PLS) analysis is developed for rapidly and accurately assessing commercial organic fertilizers quality. A total of 104 commercial organic fertilizers were collected from full-scale compost factories in Jiangsu Province, east China. In general, the NIR-PLS technique showed accurate predictions of the total organic matter, water soluble organic nitrogen, pH, and germination index; less accurate results of the moisture, total nitrogen, and electrical conductivity; and the least accurate results for water soluble organic carbon. Our results suggested the combined NIR-PLS technique could be applied as a valuable tool to rapidly and accurately assess the quality of commercial organic fertilizers.

  9. First results on bilepton production based on LHC collision data and predictions for run II

    NASA Astrophysics Data System (ADS)

    Nepomuceno, A. A.; Eccard, F. L.; Meirose, B.

    2016-09-01

    The LHC potential for discovering doubly charged vector bileptons is investigated considering the measurable process p p →μ+μ+μ-μ-X . The study is performed assuming different bilepton and leptoquark masses. The process cross section is calculated at leading order using the Calchep package. Combining the calculation with the latest ATLAS experiment results at a center-of-mass energy of 7 TeV, bounds on bilepton masses based on LHC data are derived for the first time. The results exclude bilepton masses in the range of 250 GeV to 500 GeV at 95% C.L., depending on the leptoquark mass. Moreover, minimal LHC integrated luminosities needed for discovering and for setting limits on bilepton masses are obtained for 13 TeV center-of-mass energy. Simulated events are passed through a fast parametric detector simulation using the Delphes package.

  10. Prediction of external corrosion for UF{sub 6} cylinders: Results of an empirical method

    SciTech Connect

    Lyon, B.F.

    1995-06-01

    Wall thickness data for depleted LTF, (DU) cylinders in above-ground storage at three Department of Energy (DOE) sites (Oak Ridge, TN; Paducah, KY; Portsmouth, OH) were analyzed in order to address the following questions: How many cylinders may have breaches now? and, What will the conditions be like in 2020? This report summarizes preliminary results of the analyses conducted. These results are to be used as input into models for estimating risks and hazards associated with the cylinders in the various conditions. These models will then be used as a basis for implementing engineering fixes where possible and for management decisions on corrective actions. This is part of the overall assessment of the risks and hazards within the DU management program.

  11. Lay perceptions of predictive testing for diabetes based on DNA test results versus family history assessment: a focus group study

    PubMed Central

    2011-01-01

    Background This study assessed lay perceptions of issues related to predictive genetic testing for multifactorial diseases. These perceived issues may differ from the "classic" issues, e.g. autonomy, discrimination, and psychological harm that are considered important in predictive testing for monogenic disorders. In this study, type 2 diabetes was used as an example, and perceptions with regard to predictive testing based on DNA test results and family history assessment were compared. Methods Eight focus group interviews were held with 45 individuals aged 35-70 years with (n = 3) and without (n = 1) a family history of diabetes, mixed groups of these two (n = 2), and diabetes patients (n = 2). All interviews were transcribed and analysed using Atlas-ti. Results Most participants believed in the ability of a predictive test to identify people at risk for diabetes and to motivate preventive behaviour. Different reasons underlying motivation were considered when comparing DNA test results and a family history risk assessment. A perceived drawback of DNA testing was that diabetes was considered not severe enough for this type of risk assessment. In addition, diabetes family history assessment was not considered useful by some participants, since there are also other risk factors involved, not everyone has a diabetes family history or knows their family history, and it might have a negative influence on family relations. Respect for autonomy of individuals was emphasized more with regard to DNA testing than family history assessment. Other issues such as psychological harm, discrimination, and privacy were only briefly mentioned for both tests. Conclusion The results suggest that most participants believe a predictive genetic test could be used in the prevention of multifactorial disorders, such as diabetes, but indicate points to consider before both these tests are applied. These considerations differ with regard to the method of assessment (DNA test or obtaining

  12. Deriving In-Use PHEV Fuel Economy Predictions from Standardized Test Cycle Results

    SciTech Connect

    John Smart; Richard "Barney" Carlson; Jeff Gonder; Aaron Brooker

    2009-09-01

    Plug-in hybrid electric vehicles (PHEVs) have potential to reduce or eliminate the U.S. dependence on foreign oil. Quantifying the amount of petroleum each uses, however, is challenging. To estimate in-use fuel economy for conventional vehicles the Environmental Protection Agency (EPA) conducts chassis dynamometer tests on standard historic drive cycles and then adjusts the resulting “raw” fuel economy measurements downward. Various publications, such as the forthcoming update to the SAE J1711 recommended practice for PHEV fuel economy testing, address the challenges of applying standard test procedures to PHEVs. This paper explores the issue of how to apply an adjustment method to such “raw” PHEV dynamometer test results in order to more closely estimate the in-use fuel and electricity consumption characteristics of these vehicles. The paper discusses two possible adjustment methods, and evaluates one method by applying it to dynamometer data and comparing the result to in-use fleet data (on an aftermarket conversion PHEV). The paper will also present the methodologies used to collect the data needed for this comparison.

  13. Predicting episodic memory performance using different biomarkers: results from Argentina-Alzheimer’s Disease Neuroimaging Initiative

    PubMed Central

    Russo, María Julieta; Cohen, Gabriela; Chrem Mendez, Patricio; Campos, Jorge; Nahas, Federico E; Surace, Ezequiel I; Vazquez, Silvia; Gustafson, Deborah; Guinjoan, Salvador; Allegri, Ricardo F; Sevlever, Gustavo

    2016-01-01

    Purpose Argentina-Alzheimer’s Disease Neuroimaging Initiative (Arg-ADNI) is the first ADNI study to be performed in Latin America at a medical center with the appropriate infrastructure. Our objective was to describe baseline characteristics and to examine whether biomarkers related to Alzheimer’s disease (AD) physiopathology were associated with worse memory performance. Patients and methods Fifteen controls and 28 mild cognitive impairment and 13 AD dementia subjects were included. For Arg-ADNI, all biomarker parameters and neuropsychological tests of ADNI-II were adopted. Results of positron emission tomography (PET) with fluorodeoxyglucose and 11C-Pittsburgh compound-B (PIB-PET) were available from all participants. Cerebrospinal fluid biomarker results were available from 39 subjects. Results A total of 56 participants were included and underwent baseline evaluation. The three groups were similar with respect to years of education and sex, and they differed in age (F=5.10, P=0.01). Mean scores for the baseline measurements of the neuropsychological evaluation differed significantly among the three groups at P<0.001, showing a continuum in their neuropsychological performance. No significant correlations were found between the principal measures (long-delay recall, C-Pittsburgh compound-B scan, left hippocampal volume, and APOEε4) and either age, sex, or education (P>0.1). Baseline amyloid deposition and left hippocampal volume separated the three diagnostic groups and correlated with the memory performance (P<0.001). Conclusion Cross-sectional analysis of baseline data revealed links between cognition, structural changes, and biomarkers. Follow-up of a larger and more representative cohort, particularly analyzing cerebrospinal fluid and brain biomarkers, will allow better characterization of AD in our country. PMID:27695331

  14. Pancreatectomy Predicts Improved Survival for Pancreatic Adenocarcinoma: Results of an Instrumental Variable Analysis

    PubMed Central

    McDowell, Bradley D.; Chapman, Cole G.; Smith, Brian J.; Button, Anna M.; Chrischilles, Elizabeth A.; Mezhir, James J.

    2014-01-01

    Background and Objective Pancreatic resection is the standard therapy for patients with stage I/II pancreatic ductal adenocarcinoma (PDA), yet many studies demonstrate low rates of resection. The objective of this study is to evaluate whether increasing resection rates would result in an increase in average survival in patients with stage I/II PDA. Methods SEER data were analyzed for patients with stage I/II pancreatic head cancers treated from 2004–2009. Pancreatectomy rates were examined within Health Service Areas (HSA) across 18 SEER regions. An instrumental variables (IV) analysis was performed, using HSA rates as an instrument, to determine the impact of increasing resection rates on survival. Results Pancreatectomy was performed in 4,322 of the 8,323 patients evaluated with stage I/II PDA (overall resection rate=51.9%). The resection rate across HSAs ranged from an average of 38.6% in the lowest quintile to 67.3% in the highest quintile. Median survival was improved in HSAs with higher resection rates. IV analysis revealed that, for patients whose treatment choices were influenced by the rates of resection in their geographic region, pancreatectomy was associated with a statistically significant increase in overall survival. Conclusions When controlling for confounders using IV analysis, pancreatectomy is associated with a statistically significant increase in survival for patients with resectable PDA. Based on these results, if resection rates were to increase in select patients, then average survival would also be expected to increase. It is important that this information be provided to physicians and patients so they can properly weigh the risks and advantages of pancreatectomy as treatment for PDA. PMID:24979599

  15. Comparison of Analytical Predictions and Experimental Results for a Dual Brayton Power System

    NASA Technical Reports Server (NTRS)

    Johnson, Paul

    2007-01-01

    NASA Glenn Research Center (GRC) contracted Barber- Nichols, Arvada, CO to construct a dual Brayton power conversion system for use as a hardware proof of concept and to validate results from a computational code known as the Closed Cycle System Simulation (CCSS). Initial checkout tests were performed at Barber- Nichols to ready the system for delivery to GRC. This presentation describes the system hardware components and lists the types of checkout tests performed along with a couple issues encountered while conducting the tests. A description of the CCSS model is also presented. The checkout tests did not focus on generating data, therefore, no test data or model analyses are presented.

  16. Experimental Results and Predictive Calculations for Pinhole Collimators Used in Small Animal Nuclear Imaging*

    NASA Astrophysics Data System (ADS)

    Ng, Luke; Welsh, Robert E.; Bradley, Eric L.; Saha, Margaret S.; Kross, Brian; Majewski, Stan; Popov, Vladimir; Smith, Mark F.; Weisenberger, Andrew G.; Wojcik, Randolph

    2001-04-01

    Biological ligands tagged with ^125 I have been used in studies including comparisons between normal and diabetic mice in vivo. In order to enhance the image of the mouse pancreas we have tested a number of pinhole collimators coupled to two types of position sensitive photomultiplier tube. Various shapes of pinhole have been tested. Results will be described and discussed. *Supported in part by The Department of Energy, The National Science Foundation, The American Diabetes Association, The Howard Hughes Foundation, The Virginia Commonwealth Health Research Board and the Thomas F. and Kate Miller Jeffress Memorial Trust.

  17. Mini-Nutritional Assessment predicts functional decline of elderly Taiwanese: result of a population-representative sample.

    PubMed

    Lee, Li-Chin; Tsai, Alan C

    2012-06-01

    Nutrition is a key element in geriatric health and is important for functional ability. The present study examined the functional status-predictive ability of the Mini-Nutritional Assessment (MNA). We analysed the dataset of the 'Survey of Health and Living Status of the Elderly in Taiwan', a population-based study conducted by the Bureau of Health Promotion of Taiwan. Study subjects (≥65 years old) who completed both the 1999 and 2003 surveys were rated with the long form and short form of the MNA at baseline and with the Activities of Daily Living (ADL) and the Instrument Activities of Daily Living (IADL) scales 4 years later (end-point). The ability of the MNA to predict ADL or IADL dependency was evaluated with logistic regression models. The results showed that the elderly who were rated malnourished or at risk of malnutrition at baseline generally had significantly higher ADL or IADL scores 4 years later. Lower baseline MNA scores also predicted a greater risk of ADL or IADL dependency. These associations exist even among th