Science.gov

Sample records for accurately predict experimental

  1. 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.

  2. 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

  3. 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

  4. 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…

  5. 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.

  6. 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.

  7. 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

  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. 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.

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

    NASA Astrophysics Data System (ADS)

    Taponier, V.; Balu, A.

    2002-01-01

    , validated on several technical and econometrical cases, has been used for this purpose. A database of several conventional stages, operated with either solid or liquid propellants, has been made up, in conjunction with an evolutionary set of geometrical, physical and functional parameters likely to contribute to the description of the mass fraction and presumably known at the early steps of the preliminary design. After several iterations aiming at selecting the most influential parameters, polynomial expressions of the mass fraction have been made up, associated to a confidence level. The outcome highlights the real possibility of a parametric formulation of the mass fraction for conventional stages on the basis of a limited number of descriptive parameters and with a high degree of accuracy, lower than 10%. The formulas have been later on tested on existing or preliminary stages not included in the initial database, for validation purposes. Their mass faction is assessed with a comparable accuracy. The polynomial generation method in use allows also for a search of the influence of each parameter. The devised method, suitable for the preliminary design phase, represents, compared to the classical empirical approach, a significant way of improvement of the mass fraction prediction. It enables a rapid dissemination of more accurate and consistent weight data estimates to support system studies. It makes also possible the upstream processing of the preliminary design tasks through a global system approach. This method, currently in the experimental phase, is already in use as a complementary means at the technical underdirectorate of CNES-DLA. * IRIS :Instrument de Recherche des Indices Structuraux

  13. 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

  14. 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.

  15. 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.

  16. 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

  17. 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

  18. 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

  19. 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.

  20. 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).

  1. 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.

  2. 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

  3. 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

  4. 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

  5. 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].

  6. 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

  7. 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.

  8. 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

  9. 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.

  10. 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

  11. 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.

  12. 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

  13. 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.

  14. 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.

  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. 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.

  18. 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

  19. 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

  20. 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?

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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

  9. 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

  10. 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

  11. 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.

  12. 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.

  13. Theory of High-TC Superconductivity: Accurate Predictions of TC

    NASA Astrophysics Data System (ADS)

    Harshman, Dale; Fiory, Anthony

    2012-02-01

    The superconducting transition temperatures of high-TC compounds based on copper, iron, ruthenium and certain organic molecules is discovered to be dependent on bond lengths, ionic valences, and Coulomb coupling between electronic bands in adjacent, spatially separated layers [1]. Optimal transition temperature, denoted as TC0, is given by the universal expression kBTC0 = e^2λ/lζ; l is the spacing between interacting charges within the layers, ζ is the distance between interacting layers and λ is a universal constant, equal to about twice the reduced electron Compton wavelength (suggesting that Compton scattering plays a role in pairing). Non-optimum compounds in which sample degradation is evident typically exhibit TC < TC0. For the 31+ optimum compounds tested, the theoretical and experimental TC0 agree statistically to within ± 1.4 K. The elemental high-TC building block comprises two adjacent and spatially separated charge layers; the factor e^2/ζ arises from Coulomb forces between them. The theoretical charge structure representing a room-temperature superconductor is also presented. * 1. doi:10.1088/0953-8984/23/29/295701

  14. 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.

  15. 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

  16. 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

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. Predictability and Prediction for an Experimental Cultural Market

    NASA Astrophysics Data System (ADS)

    Colbaugh, Richard; Glass, Kristin; Ormerod, Paul

    Individuals are often influenced by the behavior of others, for instance because they wish to obtain the benefits of coordinated actions or infer otherwise inaccessible information. In such situations this social influence decreases the ex ante predictability of the ensuing social dynamics. We claim that, interestingly, these same social forces can increase the extent to which the outcome of a social process can be predicted very early in the process. This paper explores this claim through a theoretical and empirical analysis of the experimental music market described and analyzed in [1]. We propose a very simple model for this music market, assess the predictability of market outcomes through formal analysis of the model, and use insights derived through this analysis to develop algorithms for predicting market share winners, and their ultimate market shares, in the very early stages of the market. The utility of these predictive algorithms is illustrated through analysis of the experimental music market data sets [2].

  7. 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

  8. 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 .

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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

  1. 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/.

  2. 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.

  3. Experimental and theoretical oscillator strengths of Mg i for accurate abundance analysis

    NASA Astrophysics Data System (ADS)

    Pehlivan Rhodin, A.; Hartman, H.; Nilsson, H.; Jönsson, P.

    2017-02-01

    Context. With the aid of stellar abundance analysis, it is possible to study the galactic formation and evolution. Magnesium is an important element to trace the α-element evolution in our Galaxy. For chemical abundance analysis, such as magnesium abundance, accurate and complete atomic data are essential. Inaccurate atomic data lead to uncertain abundances and prevent discrimination between different evolution models. Aims: We study the spectrum of neutral magnesium from laboratory measurements and theoretical calculations. Our aim is to improve the oscillator strengths (f-values) of Mg i lines and to create a complete set of accurate atomic data, particularly for the near-IR region. Methods: We derived oscillator strengths by combining the experimental branching fractions with radiative lifetimes reported in the literature and computed in this work. A hollow cathode discharge lamp was used to produce free atoms in the plasma and a Fourier transform spectrometer recorded the intensity-calibrated high-resolution spectra. In addition, we performed theoretical calculations using the multiconfiguration Hartree-Fock program ATSP2K. Results: This project provides a set of experimental and theoretical oscillator strengths. We derived 34 experimental oscillator strengths. Except from the Mg i optical triplet lines (3p 3P°0,1,2-4s 3S1), these oscillator strengths are measured for the first time. The theoretical oscillator strengths are in very good agreement with the experimental data and complement the missing transitions of the experimental data up to n = 7 from even and odd parity terms. We present an evaluated set of oscillator strengths, gf, with uncertainties as small as 5%. The new values of the Mg i optical triplet line (3p 3P°0,1,2-4s 3S1) oscillator strength values are 0.08 dex larger than the previous measurements.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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.

  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. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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

  20. 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

  1. 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

    At advanced technology nodes mask complexity has been increased because of large-scale use of resolution enhancement technologies (RET) which includes Optical Proximity Correction (OPC), Inverse Lithography Technology (ILT) and Source Mask Optimization (SMO). The number of defects detected during inspection of such mask increased drastically and differentiation of critical and non-critical defects are more challenging, complex and time consuming. Because of significant defectivity of EUVL masks and non-availability of actinic inspection, it is important and also challenging to predict the criticality of defects for printability on wafer. This is one of the significant barriers for the adoption of EUVL for semiconductor manufacturing. Techniques to decide criticality of defects from images captured using non actinic inspection images is desired till actinic inspection is not available. High resolution inspection of photomask images detects many defects which are used for process and mask qualification. Repairing all defects is not practical and probably not required, however it's imperative to know which defects are severe enough to impact wafer before repair. Additionally, wafer printability check is always desired after repairing a defect. AIMSTM review is the industry standard for this, however doing AIMSTM review for all defects is expensive and very time consuming. Fast, accurate and an economical mechanism is desired which can predict defect printability on wafer accurately and quickly from images captured using high resolution inspection machine. Predicting defect printability from such images is challenging due to the fact that the high resolution images do not correlate with actual mask contours. The challenge is increased due to use of different optical condition during inspection other than actual scanner condition, and defects found in such images do not have correlation with actual impact on wafer. Our automated defect simulation tool predicts

  2. Accurate rotational constants for linear interstellar carbon chains: achieving experimental accuracy

    NASA Astrophysics Data System (ADS)

    Etim, Emmanuel E.; Arunan, Elangannan

    2017-01-01

    Linear carbon chain molecular species remain the dominant theme in interstellar chemistry. Their continuous astronomical observation depends on the availability of accurate spectroscopic parameters. Accurate rotational constants are reported for hundreds of molecular species of astrophysical, spectroscopy and chemical interests from the different linear carbon chains; C_{{n}}H, C_{{n}}H-, C_{{n}}N, C_{{n}}N-, C_{{n}}O, C_{{n}}S, HC_{{n}}S, C_{{n}}Si, CH3(CC)_{{n}}H, HC_{{n}}N, DC_{2{n}+1}N, HC_{2{n}}NC, and CH3(C≡C)_{{n}}CN using three to four moments of inertia calculated from the experimental rotational constants coupled with those obtained from the optimized geometries at the Hartree Fock level. The calculated rotational constants are obtained from the corrected moments of inertia at the Hartfree Fock geometries. The calculated rotational constants show accuracy of few kHz below irrespective of the chain length and terminating groups. The obtained accuracy of few kHz places these rotational constants as excellent tools for both astronomical and laboratory detection of these molecular species of astrophysical interest. From the numerous unidentified lines from different astronomical surveys, transitions corresponding to known and new linear carbon chains could be found using these rotational constants. The astrophysical, spectroscopic and chemical implications of these results are discussed.

  3. Identification and Evaluation of Reference Genes for Accurate Transcription Normalization in Safflower under Different Experimental Conditions

    PubMed Central

    Li, Dandan; Hu, Bo; Wang, Qing; Liu, Hongchang; Pan, Feng; Wu, Wei

    2015-01-01

    Safflower (Carthamus tinctorius L.) has received a significant amount of attention as a medicinal plant and oilseed crop. Gene expression studies provide a theoretical molecular biology foundation for improving new traits and developing new cultivars. Real-time quantitative PCR (RT-qPCR) has become a crucial approach for gene expression analysis. In addition, appropriate reference genes (RGs) are essential for accurate and rapid relative quantification analysis of gene expression. In this study, fifteen candidate RGs involved in multiple metabolic pathways of plants were finally selected and validated under different experimental treatments, at different seed development stages and in different cultivars and tissues for real-time PCR experiments. These genes were ABCS, 60SRPL10, RANBP1, UBCL, MFC, UBCE2, EIF5A, COA, EF1-β, EF1, GAPDH, ATPS, MBF1, GTPB and GST. The suitability evaluation was executed by the geNorm and NormFinder programs. Overall, EF1, UBCE2, EIF5A, ATPS and 60SRPL10 were the most stable genes, and MBF1, as well as MFC, were the most unstable genes by geNorm and NormFinder software in all experimental samples. To verify the validation of RGs selected by the two programs, the expression analysis of 7 CtFAD2 genes in safflower seeds at different developmental stages under cold stress was executed using different RGs in RT-qPCR experiments for normalization. The results showed similar expression patterns when the most stable RGs selected by geNorm or NormFinder software were used. However, the differences were detected using the most unstable reference genes. The most stable combination of genes selected in this study will help to achieve more accurate and reliable results in a wide variety of samples in safflower. PMID:26457898

  4. 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

  5. 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

  6. 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.

  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. 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.

  9. 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.

  10. 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

  11. Experimental design in phylogenetics: testing predictions from expected information.

    PubMed

    San Mauro, Diego; Gower, David J; Cotton, James A; Zardoya, Rafael; Wilkinson, Mark; Massingham, Tim

    2012-07-01

    Taxon and character sampling are central to phylogenetic experimental design; yet, we lack general rules. Goldman introduced a method to construct efficient sampling designs in phylogenetics, based on the calculation of expected Fisher information given a probabilistic model of sequence evolution. The considerable potential of this approach remains largely unexplored. In an earlier study, we applied Goldman's method to a problem in the phylogenetics of caecilian amphibians and made an a priori evaluation and testable predictions of which taxon additions would increase information about a particular weakly supported branch of the caecilian phylogeny by the greatest amount. We have now gathered mitogenomic and rag1 sequences (some newly determined for this study) from additional caecilian species and studied how information (both expected and observed) and bootstrap support vary as each new taxon is individually added to our previous data set. This provides the first empirical test of specific predictions made using Goldman's method for phylogenetic experimental design. Our results empirically validate the top 3 (more intuitive) taxon addition predictions made in our previous study, but only information results validate unambiguously the 4th (less intuitive) prediction. This highlights a complex relationship between information and support, reflecting that each measures different things: Information is related to the ability to estimate branch length accurately and support to the ability to estimate the tree topology accurately. Thus, an increase in information may be correlated with but does not necessitate an increase in support. Our results also provide the first empirical validation of the widely held intuition that additional taxa that join the tree proximal to poorly supported internal branches are more informative and enhance support more than additional taxa that join the tree more distally. Our work supports the view that adding more data for a single (well

  12. Prediction of catastrophes: an experimental model.

    PubMed

    Peters, Randall D; Le Berre, Martine; Pomeau, Yves

    2012-08-01

    Catastrophes of all kinds can be roughly defined as short-duration, large-amplitude events following and followed by long periods of "ripening." Major earthquakes surely belong to the class of "catastrophic" events. Because of the space-time scales involved, an experimental approach is often difficult, not to say impossible, however desirable it could be. Described in this article is a "laboratory" setup that yields data of a type that is amenable to theoretical methods of prediction. Observations are made of a critical slowing down in the noisy signal of a solder wire creeping under constant stress. This effect is shown to be a fair signal of the forthcoming catastrophe in two separate dynamical models. The first is an "abstract" model in which a time-dependent quantity drifts slowly but makes quick jumps from time to time. The second is a realistic physical model for the collective motion of dislocations (the Ananthakrishna set of equations for unstable creep). Hope thus exists that similar changes in the response to noise could forewarn catastrophes in other situations, where such precursor effects should manifest early enough.

  13. 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.

  14. 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.

  15. Theory of bi-molecular association dynamics in 2D for accurate model and experimental parameterization of binding rates

    PubMed Central

    Yogurtcu, Osman N.; Johnson, Margaret E.

    2015-01-01

    The dynamics of association between diffusing and reacting molecular species are routinely quantified using simple rate-equation kinetics that assume both well-mixed concentrations of species and a single rate constant for parameterizing the binding rate. In two-dimensions (2D), however, even when systems are well-mixed, the assumption of a single characteristic rate constant for describing association is not generally accurate, due to the properties of diffusional searching in dimensions d ≤ 2. Establishing rigorous bounds for discriminating between 2D reactive systems that will be accurately described by rate equations with a single rate constant, and those that will not, is critical for both modeling and experimentally parameterizing binding reactions restricted to surfaces such as cellular membranes. We show here that in regimes of intrinsic reaction rate (ka) and diffusion (D) parameters ka/D > 0.05, a single rate constant cannot be fit to the dynamics of concentrations of associating species independently of the initial conditions. Instead, a more sophisticated multi-parametric description than rate-equations is necessary to robustly characterize bimolecular reactions from experiment. Our quantitative bounds derive from our new analysis of 2D rate-behavior predicted from Smoluchowski theory. Using a recently developed single particle reaction-diffusion algorithm we extend here to 2D, we are able to test and validate the predictions of Smoluchowski theory and several other theories of reversible reaction dynamics in 2D for the first time. Finally, our results also mean that simulations of reactive systems in 2D using rate equations must be undertaken with caution when reactions have ka/D > 0.05, regardless of the simulation volume. We introduce here a simple formula for an adaptive concentration dependent rate constant for these chemical kinetics simulations which improves on existing formulas to better capture non-equilibrium reaction dynamics from dilute

  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. 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.

  18. 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

  19. 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.

  20. 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.

  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. Protein design algorithms predict viable resistance to an experimental antifolate.

    PubMed

    Reeve, Stephanie M; Gainza, Pablo; Frey, Kathleen M; Georgiev, Ivelin; Donald, Bruce R; Anderson, Amy C

    2015-01-20

    Methods to accurately predict potential drug target mutations in response to early-stage leads could drive the design of more resilient first generation drug candidates. In this study, a structure-based protein design algorithm (K* in the OSPREY suite) was used to prospectively identify single-nucleotide polymorphisms that confer resistance to an experimental inhibitor effective against dihydrofolate reductase (DHFR) from Staphylococcus aureus. Four of the top-ranked mutations in DHFR were found to be catalytically competent and resistant to the inhibitor. Selection of resistant bacteria in vitro reveals that two of the predicted mutations arise in the background of a compensatory mutation. Using enzyme kinetics, microbiology, and crystal structures of the complexes, we determined the fitness of the mutant enzymes and strains, the structural basis of resistance, and the compensatory relationship of the mutations. To our knowledge, this work illustrates the first application of protein design algorithms to prospectively predict viable resistance mutations that arise in bacteria under antibiotic pressure.

  3. 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

  4. 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)).

  5. 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.

  6. 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.

  7. 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

  8. 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

  9. 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).

  10. 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.

  11. 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.

  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. 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

  14. Accurate modeling of antennas for radiating short pulses, FDTD analysis and experimental measurements

    NASA Astrophysics Data System (ADS)

    Maloney, James G.; Smith, Glenn S.

    1993-01-01

    Antennas used to radiate short pulses often require different design rules that those that are used to radiate essentially time-harmonic signals. The finite-difference time-domain (FDTD) method is a very flexible numerical approach that can be used to treat a variety of electromagnetic problems in the time domain. It is well suited to the analysis and design of antennas for radiating short pulses; however, several advances had to be made before the method could be applied to this problem. In this paper, we will illustrate the use of the FDTD method with two antennas designed for the radiation of short pulses. The first is a simple, two-dimensional geometry, and open-ended parallel-plate waveguide, while the second is a three-dimensional, rotationally symmetric geometry, a conical monopole fed through an image by a coaxial transmission line. Both antennas are 'optimized' according to given criteria by adjusting geometrical parameters and including resistive loading that varies continuously with position along the antenna. The predicted performance for the conical monopole antenna is compared with experimental measurements; this verifies the optimization and demonstrates the practicality of the design.

  15. 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.

  16. 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

  17. 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.

  18. 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

  19. 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.

  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. 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.

  2. 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

    The growing importance and successive expansion of renewable energies raise new challenges for decision makers, economists, transmission system operators, scientists and many more. In this interdisciplinary field, the role of Numerical Weather Prediction (NWP) is to reduce the errors and provide an a priori estimate of remaining uncertainties associated with the large share of weather-dependent power sources. For this purpose it is essential to optimize NWP model forecasts with respect to those prognostic variables which are relevant for wind and solar power plants. An improved weather forecast serves as the basis for a sophisticated power forecasts. Consequently, a well-timed energy trading on the stock market, and electrical grid stability can be maintained. The German Weather Service (DWD) currently is involved with two projects concerning research in the field of renewable energy, namely ORKA*) and EWeLiNE**). Whereas the latter is in collaboration with the Fraunhofer Institute (IWES), the project ORKA is led by energy & meteo systems (emsys). Both cooperate with German transmission system operators. The goal of the projects is to improve wind and photovoltaic (PV) power forecasts by combining optimized NWP and enhanced power forecast models. In this context, the German Weather Service aims to improve its model system, including the ensemble forecasting system, by working on data assimilation, model physics and statistical post processing. This presentation is focused on the identification of critical weather situations and the associated errors in the German regional NWP model COSMO-DE. First steps leading to improved physical parameterization schemes within the NWP-model are presented. Wind mast measurements reaching up to 200 m height above ground are used for the estimation of the (NWP) wind forecast error at heights relevant for wind energy plants. One particular problem is the daily cycle in wind speed. The transition from stable stratification during

  3. Hybrid experimental/analytical models of structural dynamics - Creation and use for predictions

    NASA Technical Reports Server (NTRS)

    Balmes, Etienne

    1993-01-01

    An original complete methodology for the construction of predictive models of damped structural vibrations is introduced. A consistent definition of normal and complex modes is given which leads to an original method to accurately identify non-proportionally damped normal mode models. A new method to create predictive hybrid experimental/analytical models of damped structures is introduced, and the ability of hybrid models to predict the response to system configuration changes is discussed. Finally a critical review of the overall methodology is made by application to the case of the MIT/SERC interferometer testbed.

  4. 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

  5. Material response mechanisms are needed to obtain highly accurate experimental shock wave data

    NASA Astrophysics Data System (ADS)

    Forbes, Jerry W.

    2017-01-01

    The field of shock wave compression of matter has provided a simple set of equations relating thermodynamic and kinematic parameters that describe the conservation of mass, momentum and energy across a steady plane shock wave with one-dimensional flow. Well-known condensed matter shock wave experimental results will be reviewed to see whether the assumptions required for deriving these simple R-H equations are satisfied. Note that the material compression model is not required for deriving the 1-D conservation flow equations across a steady plane shock front. However, this statement is misleading from a practical experimental viewpoint since obtaining small systematic errors in shock wave measured parameters requires the material compression and release mechanisms to be known. A review will be presented on errors in shock wave data from common experimental techniques for elastic-plastic solids. Issues related to time scales of experiments, steady waves with long rise times and detonations will also be discussed

  6. 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.

  7. 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.

  8. Experimental prediction of the wavelength-dependent path-length factor for optical intrinsic signal analysis.

    PubMed

    Sakaguchi, Koichiro; Tachibana, Tomoya; Furukawa, Shunsuke; Katsura, Takushige; Yamazaki, Kyoko; Kawaguchi, Hideo; Maki, Atsushi; Okada, Eiji

    2007-05-10

    Analysis of the optical intrinsic signal of an exposed cortex has been applied to measurement of functional brain activation. It is important for accurate measurement of concentration changes in oxygenated hemoglobin and deoxygenated hemoglobin to consider the wavelength dependence of the mean optical path lengths for the reflectance of cortical tissue. A method is proposed to experimentally estimate the wavelength dependence of the mean optical path length in cortical tissue from the multispectral reflectance of the exposed cortex without any additional instruments. The trend in the wavelength dependence of the mean optical path length estimated by the proposed method agrees with that estimated by the model-based prediction, whereas the magnitude of the wavelength dependence predicted by the proposed method is greater than that of the model-based prediction. The experimentally predicted mean optical path length minimizes the difference in the measured changes in the concentrations of the oxygenated hemoglobin and deoxygenated hemoglobin calculated from different wavelength pairs.

  9. 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.

  10. 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?

  11. 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

  12. 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

  13. The accurate measurement of second virial coefficients using self-interaction chromatography: experimental considerations.

    PubMed

    Quigley, A; Heng, J Y Y; Liddell, J M; Williams, D R

    2013-11-01

    Measurement of B22, the second virial coefficient, is an important technique for describing the solution behaviour of proteins, especially as it relates to precipitation, aggregation and crystallisation phenomena. This paper describes the best practise for calculating B22 values from self-interaction chromatograms (SIC) for aqueous protein solutions. Detailed analysis of SIC peak shapes for lysozyme shows that non-Gaussian peaks are commonly encountered for SIC, with typical peak asymmetries of 10%. This asymmetry reflects a non-linear chromatographic retention process, in this case heterogeneity of the protein-protein interactions. Therefore, it is important to use the centre of mass calculations for determining accurate retention volumes and thus B22 values. Empirical peak maximum chromatogram analysis, often reported in the literature, can result in errors of up to 50% in B22 values. A methodology is reported here for determining both the mean and the variance in B22 from SIC experiments, includes a correction for normal longitudinal peak broadening. The variance in B22 due to chemical effects is quantified statistically and is a measure of the heterogeneity of protein-protein interactions in solution. In the case of lysozyme, a wide range of B22 values are measured which can vary significantly from the average B22 values.

  14. 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

  15. 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.

  16. 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.

  17. Structural Prediction and Experimental Verification of Three New Ferroelectric Materials

    NASA Astrophysics Data System (ADS)

    Arbogast, D. J.; Foster, M. C.; Nielson, R. M.; Photinos, P. J.; Abrahams, S. C.

    1999-05-01

    Aminoguanidinium hexafluorozirconate, potassium niobyl silicate and fresnoite are typical members of a growing group of materials predicted to be new ferroelectrics by the application of structural criteria. Following prediction, undergraduate chemistry majors prepare and physics majors measure the dielectric properties of each. Experimental results will be presented for the three title materials in verification of their predicted property. In addition to the structural criteria on which the predictions depend, the circuits built locally and other instrumentation used for measuring ac and dc hysteresis, the thermal and frequency dependence of the dielectric permittivity, the thermal dependence of the spontaneous polarization and also the pyroelectric coefficient will be presented.

  18. 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 the relative frame of reference; the boundary conditions for the computations were obtained from inlet flow measurements performed in the AFTRF. A complete turbine stage, including an NGV and a rotor row was simulated using the RANS solver with the SST kappa -- o turbulence model, with two different computational models for the interface between the rotating component and the stationary component. The first interface model, the circumferentially averaged mixing plane model, was solved for a fixed position of the rotor blades relative to the NGV in the stationary frame of reference. The information transferred between the NGV and rotor domains is obtained by averaging across the entire interface. The quasi-steady state flow characteristics of the AFTRF can be obtained from this interface model. After the model was validated with the existing experimental data, this model was not only used to investigate the flow characteristics in the turbine stage but also the effects of using pressure side rotor tip extensions. The tip leakage flow fields simulated from this model and from the linear cascade model show similar trends. More detailed understanding of unsteady characteristics of a turbine flow field can be obtained using the second type of interface model, the time accurate sliding mesh model. The potential flow interactions, wake characteristics, their effects on secondary flow formation, and the wake mixing process in a rotor passage were examined using this model. Furthermore, turbine stage efficiency and effects of tip clearance height on the turbine stage efficiency were also investigated. A comparison between the results from the circumferential average model and the time accurate flow model results is presented. It was found that the circumferential average model cannot accurately simulate flow interaction characteristics on the interface plane between the NGV trailing edge and the rotor leading edge. However, the circumferential average model does give

  19. 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

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. Disorder Prediction Methods, Their Applicability to Different Protein Targets and Their Usefulness for Guiding Experimental Studies

    PubMed Central

    Atkins, Jennifer D.; Boateng, Samuel Y.; Sorensen, Thomas; McGuffin, Liam J.

    2015-01-01

    The role and function of a given protein is dependent on its structure. In recent years, however, numerous studies have highlighted the importance of unstructured, or disordered regions in governing a protein’s function. Disordered proteins have been found to play important roles in pivotal cellular functions, such as DNA binding and signalling cascades. Studying proteins with extended disordered regions is often problematic as they can be challenging to express, purify and crystallise. This means that interpretable experimental data on protein disorder is hard to generate. As a result, predictive computational tools have been developed with the aim of predicting the level and location of disorder within a protein. Currently, over 60 prediction servers exist, utilizing different methods for classifying disorder and different training sets. Here we review several good performing, publicly available prediction methods, comparing their application and discussing how disorder prediction servers can be used to aid the experimental solution of protein structure. The use of disorder prediction methods allows us to adopt a more targeted approach to experimental studies by accurately identifying the boundaries of ordered protein domains so that they may be investigated separately, thereby increasing the likelihood of their successful experimental solution. PMID:26287166

  5. Experimental validation of boundary element methods for noise prediction

    NASA Technical Reports Server (NTRS)

    Seybert, A. F.; Oswald, Fred B.

    1992-01-01

    Experimental validation of methods to predict radiated noise is presented. A combined finite element and boundary element model was used to predict the vibration and noise of a rectangular box excited by a mechanical shaker. The predicted noise was compared to sound power measured by the acoustic intensity method. Inaccuracies in the finite element model shifted the resonance frequencies by about 5 percent. The predicted and measured sound power levels agree within about 2.5 dB. In a second experiment, measured vibration data was used with a boundary element model to predict noise radiation from the top of an operating gearbox. The predicted and measured sound power for the gearbox agree within about 3 dB.

  6. The use of experimental bending tests to more accurate numerical description of TBC damage process

    NASA Astrophysics Data System (ADS)

    Sadowski, T.; Golewski, P.

    2016-04-01

    Thermal barrier coatings (TBCs) have been extensively used in aircraft engines to protect critical engine parts such as blades and combustion chambers, which are exposed to high temperatures and corrosive environment. The blades of turbine engines are additionally exposed to high mechanical loads. These loads are created by the high rotational speed of the rotor (30 000 rot/min), causing the tensile and bending stresses. Therefore, experimental testing of coated samples is necessary in order to determine strength properties of TBCs. Beam samples with dimensions 50×10×2 mm were used in those studies. The TBC system consisted of 150 μm thick bond coat (NiCoCrAlY) and 300 μm thick top coat (YSZ) made by APS (air plasma spray) process. Samples were tested by three-point bending test with various loads. After bending tests, the samples were subjected to microscopic observation to determine the quantity of cracks and their depth. The above mentioned results were used to build numerical model and calibrate material data in Abaqus program. Brittle cracking damage model was applied for the TBC layer, which allows to remove elements after reaching criterion. Surface based cohesive behavior was used to model the delamination which may occur at the boundary between bond coat and top coat.

  7. An experimental device for accurate ultrasounds measurements in liquid foods at high pressure

    NASA Astrophysics Data System (ADS)

    Hidalgo-Baltasar, E.; Taravillo, M.; Baonza, V. G.; Sanz, P. D.; Guignon, B.

    2012-12-01

    The use of high hydrostatic pressure to ensure safe and high-quality product has markedly increased in the food industry during the last decade. Ultrasonic sensors can be employed to control such processes in an equivalent way as they are currently used in processes carried out at room pressure. However, their installation, calibration and use are particularly challenging in the context of a high pressure environment. Besides, data about acoustic properties of food under pressure and even for water are quite scarce in the pressure range of interest for food treatment (namely, above 200 MPa). The objective of this work was to establish a methodology to determine the speed of sound in foods under pressure. An ultrasonic sensor using the multiple reflections method was adapted to a lab-scale HHP equipment to determine the speed of sound in water between 253.15 and 348.15 K, and at pressures up to 700 MPa. The experimental speed-of-sound data were compared to the data calculated from the equation of state of water (IAPWS-95 formulation). From this analysis, the way to calibrate cell path was validated. After this calibration procedure, the speed of sound could be determined in liquid foods by using this sensor with a relative uncertainty between (0.22 and 0.32) % at a confidence level of 95 % over the whole pressure domain.

  8. 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.

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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

  18. Combining computer algorithms with experimental approaches permits the rapid and accurate identification of T cell epitopes from defined antigens.

    PubMed

    Schirle, M; Weinschenk, T; Stevanović, S

    2001-11-01

    The identification of T cell epitopes from immunologically relevant antigens remains a critical step in the development of vaccines and methods for monitoring of T cell responses. This review presents an overview of strategies that employ computer algorithms for the selection of candidate peptides from defined proteins and subsequent verification of their in vivo relevance by experimental approaches. Several computer algorithms are currently being used for epitope prediction of various major histocompatibility complex (MHC) class I and II molecules, based either on the analysis of natural MHC ligands or on the binding properties of synthetic peptides. Moreover, the analysis of proteasomal digests of peptides and whole proteins has led to the development of algorithms for the prediction of proteasomal cleavages. In order to verify the generation of the predicted peptides during antigen processing in vivo as well as their immunogenic potential, several experimental approaches have been pursued in the recent past. Mass spectrometry-based bioanalytical approaches have been used specifically to detect predicted peptides among isolated natural ligands. Other strategies employ various methods for the stimulation of primary T cell responses against the predicted peptides and subsequent testing of the recognition pattern towards target cells that express the antigen.

  19. 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.

  20. 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 .

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Prediction uncertainty and optimal experimental design for learning dynamical systems.

    PubMed

    Letham, Benjamin; Letham, Portia A; Rudin, Cynthia; Browne, Edward P

    2016-06-01

    Dynamical systems are frequently used to model biological systems. When these models are fit to data, it is necessary to ascertain the uncertainty in the model fit. Here, we present prediction deviation, a metric of uncertainty that determines the extent to which observed data have constrained the model's predictions. This is accomplished by solving an optimization problem that searches for a pair of models that each provides a good fit for the observed data, yet has maximally different predictions. We develop a method for estimating a priori the impact that additional experiments would have on the prediction deviation, allowing the experimenter to design a set of experiments that would most reduce uncertainty. We use prediction deviation to assess uncertainty in a model of interferon-alpha inhibition of viral infection, and to select a sequence of experiments that reduces this uncertainty. Finally, we prove a theoretical result which shows that prediction deviation provides bounds on the trajectories of the underlying true model. These results show that prediction deviation is a meaningful metric of uncertainty that can be used for optimal experimental design.

  8. Prediction uncertainty and optimal experimental design for learning dynamical systems

    NASA Astrophysics Data System (ADS)

    Letham, Benjamin; Letham, Portia A.; Rudin, Cynthia; Browne, Edward P.

    2016-06-01

    Dynamical systems are frequently used to model biological systems. When these models are fit to data, it is necessary to ascertain the uncertainty in the model fit. Here, we present prediction deviation, a metric of uncertainty that determines the extent to which observed data have constrained the model's predictions. This is accomplished by solving an optimization problem that searches for a pair of models that each provides a good fit for the observed data, yet has maximally different predictions. We develop a method for estimating a priori the impact that additional experiments would have on the prediction deviation, allowing the experimenter to design a set of experiments that would most reduce uncertainty. We use prediction deviation to assess uncertainty in a model of interferon-alpha inhibition of viral infection, and to select a sequence of experiments that reduces this uncertainty. Finally, we prove a theoretical result which shows that prediction deviation provides bounds on the trajectories of the underlying true model. These results show that prediction deviation is a meaningful metric of uncertainty that can be used for optimal experimental design.

  9. Experimental Study on Elliott Wave Theory for Handoff Prediction

    NASA Astrophysics Data System (ADS)

    Vishvaksenan, K. S.; Mithra, K.; Kalidoss, R.; Karthipan, R.

    2016-07-01

    The main objective for the next generation wireless network is the offer of a high data rate when the user is on the move. The key element that offers continuous connectivity is the handoff. In this paper, we propose a handoff prediction model, which can predict handoff behavior of the user well in advance and reduce the latency in the handoff operation. The prediction model is validated with real life scenario both for the pedestrian user and the vehicle user, traveling at a speed of 80km/h. The experimental result verifies the capability of the proposed algorithm to predict the future sample with accuracy and minimum latency. Simulation results demonstrate the proposed system outperforming the existing system compared to the probability of the handoff detection and minimizing the false alarm probability. There is also the fact of the proposed algorithm not requiring any additional hardware for predicting the mobility of the user.

  10. 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.

  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. 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.

  13. 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.

  14. 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.

  15. Comparison of Experimental Diagnostic Signals with Numerical Predictions

    NASA Astrophysics Data System (ADS)

    Comer, K.; Turnbull, A. D.

    1997-11-01

    A new code has been written to compare experimental diagnostic signals with those predicted by stability code output and experimental equilibrium diagnostic signals such as SXR, ECE, BSE, and reflectometry. Comparison of expected and actual diagnostic signals will help distinguish or identify modes by the signals they produce, and will also help validate stability codes. Predicted diagnostic signals are obtained by taking the total time derivative of S, the signal amplitude, and assuming steady state conditions so that the partial time derivative can be set to zero. Multiplying by delta-time (Dt) results in δ S = tilde\\underlineξ \\cdot \\underlinenablaS, where δ S is the predicted diagnostic signal, tilde\\underlineξ is the plasma displacement predicted by various equilibrium codes (such as GATO or MARS), and \\underlinenablaS is the gradient of the equilibrium diagnostic signal. \\underlinenablaS may be obtained from an experimental equilibrium signal amplitude profile, or from a functional dependence of the signal amplitude on equilibrium temperature and density. Comparisons of predicted and actual signals from linear ideal and resistive codes show reasonable agreement with the measured signals in some cases, but there are also some significant discrepancies.

  16. 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

    attributed to phantom setup errors due to the slightly deformable and flexible phantom extremities. The estimated site-specific safety buffer distance with 0.001% probability of collision for (gantry-to-couch, gantry-to-phantom) was (1.23 cm, 3.35 cm), (1.01 cm, 3.99 cm), and (2.19 cm, 5.73 cm) for treatment to the head, lung, and prostate, respectively. Automated delivery to all three treatment sites was completed in 15 min and collision free using a digital Linac. Conclusions: An individualized collision prediction model for the purpose of noncoplanar beam delivery was developed and verified. With the model, the study has demonstrated the feasibility of predicting deliverable beams for an individual patient and then guiding fully automated noncoplanar treatment delivery. This work motivates development of clinical workflows and quality assurance procedures to allow more extensive use and automation of noncoplanar beam geometries.

  17. 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

    attributed to phantom setup errors due to the slightly deformable and flexible phantom extremities. The estimated site-specific safety buffer distance with 0.001% probability of collision for (gantry-to-couch, gantry-to-phantom) was (1.23 cm, 3.35 cm), (1.01 cm, 3.99 cm), and (2.19 cm, 5.73 cm) for treatment to the head, lung, and prostate, respectively. Automated delivery to all three treatment sites was completed in 15 min and collision free using a digital Linac. Conclusions: An individualized collision prediction model for the purpose of noncoplanar beam delivery was developed and verified. With the model, the study has demonstrated the feasibility of predicting deliverable beams for an individual patient and then guiding fully automated noncoplanar treatment delivery. This work motivates development of clinical workflows and quality assurance procedures to allow more extensive use and automation of noncoplanar beam geometries. PMID:26520735

  18. 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

  19. 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.

  20. 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

  1. Vibration Prediction Method of Electric Machines by using Experimental Transfer Function and Magnetostatic Finite Element Analysis

    NASA Astrophysics Data System (ADS)

    Saito, A.; Kuroishi, M.; Nakai, H.

    2016-09-01

    This paper concerns the noise and structural vibration caused by rotating electric machines. Special attention is given to the magnetic-force induced vibration response of interior-permanent magnet machines. In general, to accurately predict and control the vibration response caused by the electric machines, it is inevitable to model not only the magnetic force induced by the fluctuation of magnetic fields, but also the structural dynamic characteristics of the electric machines and surrounding structural components. However, due to complicated boundary conditions and material properties of the components, such as laminated magnetic cores and varnished windings, it has been a challenge to compute accurate vibration response caused by the electric machines even after their physical models are available. In this paper, we propose a highly-accurate vibration prediction method that couples experimentally-obtained discrete structural transfer functions and numerically-obtained distributed magnetic-forces. The proposed vibration synthesis methodology has been applied to predict vibration responses of an interior permanent magnet machine. The results show that the predicted vibration response of the electric machine agrees very well with the measured vibration response for several load conditions, for wide frequency ranges.

  2. 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.

  3. 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

  4. 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

  5. Predictions of Cockpit Simulator Experimental Outcome Using System Models

    NASA Technical Reports Server (NTRS)

    Sorensen, J. A.; Goka, T.

    1984-01-01

    This study involved predicting the outcome of a cockpit simulator experiment where pilots used cockpit displays of traffic information (CDTI) to establish and maintain in-trail spacing behind a lead aircraft during approach. The experiments were run on the NASA Ames Research Center multicab cockpit simulator facility. Prior to the experiments, a mathematical model of the pilot/aircraft/CDTI flight system was developed which included relative in-trail and vertical dynamics between aircraft in the approach string. This model was used to construct a digital simulation of the string dynamics including response to initial position errors. The model was then used to predict the outcome of the in-trail following cockpit simulator experiments. Outcome included performance and sensitivity to different separation criteria. The experimental results were then used to evaluate the model and its prediction accuracy. Lessons learned in this modeling and prediction study are noted.

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. 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).

  12. 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.

  13. 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

  14. 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.

  15. A prediction model for ocular damage - Experimental validation.

    PubMed

    Heussner, Nico; Vagos, Márcia; Spitzer, Martin S; Stork, Wilhelm

    2015-08-01

    With the increasing number of laser applications in medicine and technology, accidental as well as intentional exposure of the human eye to laser sources has become a major concern. Therefore, a prediction model for ocular damage (PMOD) is presented within this work and validated for long-term exposure. This model is a combination of a raytracing model with a thermodynamical model of the human and an application which determines the thermal damage by the implementation of the Arrhenius integral. The model is based on our earlier work and is here validated against temperature measurements taken with porcine eye samples. For this validation, three different powers were used: 50mW, 100mW and 200mW with a spot size of 1.9mm. Also, the measurements were taken with two different sensing systems, an infrared camera and a fibre optic probe placed within the tissue. The temperatures were measured up to 60s and then compared against simulations. The measured temperatures were found to be in good agreement with the values predicted by the PMOD-model. To our best knowledge, this is the first model which is validated for both short-term and long-term irradiations in terms of temperature and thus demonstrates that temperatures can be accurately predicted within the thermal damage regime.

  16. Predictions of experimentally observed stochastic ground vibrations induced by blasting.

    PubMed

    Kostić, Srđan; Perc, Matjaž; Vasović, Nebojša; Trajković, Slobodan

    2013-01-01

    In the present paper, we investigate the blast induced ground motion recorded at the limestone quarry "Suva Vrela" near Kosjerić, which is located in the western part of Serbia. We examine the recorded signals by means of surrogate data methods and a determinism test, in order to determine whether the recorded ground velocity is stochastic or deterministic in nature. Longitudinal, transversal and the vertical ground motion component are analyzed at three monitoring points that are located at different distances from the blasting source. The analysis reveals that the recordings belong to a class of stationary linear stochastic processes with Gaussian inputs, which could be distorted by a monotonic, instantaneous, time-independent nonlinear function. Low determinism factors obtained with the determinism test further confirm the stochastic nature of the recordings. Guided by the outcome of time series analysis, we propose an improved prediction model for the peak particle velocity based on a neural network. We show that, while conventional predictors fail to provide acceptable prediction accuracy, the neural network model with four main blast parameters as input, namely total charge, maximum charge per delay, distance from the blasting source to the measuring point, and hole depth, delivers significantly more accurate predictions that may be applicable on site. We also perform a sensitivity analysis, which reveals that the distance from the blasting source has the strongest influence on the final value of the peak particle velocity. This is in full agreement with previous observations and theory, thus additionally validating our methodology and main conclusions.

  17. 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.

  18. 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.

  19. 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.

  20. Internally electrodynamic particle model: Its experimental basis and its predictions

    SciTech Connect

    Zheng-Johansson, J. X.

    2010-03-15

    The internally electrodynamic (IED) particle model was derived based on overall experimental observations, with the IED process itself being built directly on three experimental facts: (a) electric charges present with all material particles, (b) an accelerated charge generates electromagnetic waves according to Maxwell's equations and Planck energy equation, and (c) source motion produces Doppler effect. A set of well-known basic particle equations and properties become predictable based on first principles solutions for the IED process; several key solutions achieved are outlined, including the de Broglie phase wave, de Broglie relations, Schroedinger equation, mass, Einstein mass-energy relation, Newton's law of gravity, single particle self interference, and electromagnetic radiation and absorption; these equations and properties have long been broadly experimentally validated or demonstrated. A conditioned solution also predicts the Doebner-Goldin equation which emerges to represent a form of long-sought quantum wave equation including gravity. A critical review of the key experiments is given which suggests that the IED process underlies the basic particle equations and properties not just sufficiently but also necessarily.

  1. 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.

  2. A fast experimental beam hardening correction method for accurate bone mineral measurements in 3D μCT imaging system.

    PubMed

    Koubar, Khodor; Bekaert, Virgile; Brasse, David; Laquerriere, Patrice

    2015-06-01

    Bone mineral density plays an important role in the determination of bone strength and fracture risks. Consequently, it is very important to obtain accurate bone mineral density measurements. The microcomputerized tomography system provides 3D information about the architectural properties of bone. Quantitative analysis accuracy is decreased by the presence of artefacts in the reconstructed images, mainly due to beam hardening artefacts (such as cupping artefacts). In this paper, we introduced a new beam hardening correction method based on a postreconstruction technique performed with the use of off-line water and bone linearization curves experimentally calculated aiming to take into account the nonhomogeneity in the scanned animal. In order to evaluate the mass correction rate, calibration line has been carried out to convert the reconstructed linear attenuation coefficient into bone masses. The presented correction method was then applied on a multimaterial cylindrical phantom and on mouse skeleton images. Mass correction rate up to 18% between uncorrected and corrected images were obtained as well as a remarkable improvement of a calculated mouse femur mass has been noticed. Results were also compared to those obtained when using the simple water linearization technique which does not take into account the nonhomogeneity in the object.

  3. Development and experimental verification of a finite element method for accurate analysis of a surface acoustic wave device

    NASA Astrophysics Data System (ADS)

    Mohibul Kabir, K. M.; Matthews, Glenn I.; Sabri, Ylias M.; Russo, Salvy P.; Ippolito, Samuel J.; Bhargava, Suresh K.

    2016-03-01

    Accurate analysis of surface acoustic wave (SAW) devices is highly important due to their use in ever-growing applications in electronics, telecommunication and chemical sensing. In this study, a novel approach for analyzing the SAW devices was developed based on a series of two-dimensional finite element method (FEM) simulations, which has been experimentally verified. It was found that the frequency response of the two SAW device structures, each having slightly different bandwidth and center lobe characteristics, can be successfully obtained utilizing the current density of the electrodes via FEM simulations. The two SAW structures were based on XY Lithium Niobate (LiNbO3) substrates and had two and four electrode finger pairs in both of their interdigital transducers, respectively. Later, SAW devices were fabricated in accordance with the simulated models and their measured frequency responses were found to correlate well with the obtained simulations results. The results indicated that better match between calculated and measured frequency response can be obtained when one of the input electrode finger pairs was set at zero volts and all the current density components were taken into account when calculating the frequency response of the simulated SAW device structures.

  4. 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

    database of images for evaluating object recognition performance. We used multielectrode arrays to characterize hundreds of neurons in the visual ventral stream of nonhuman primates and measured the object recognition performance of >100 human observers. Remarkably, we found that simple learned weighted sums of firing rates of neurons in monkey inferior temporal (IT) cortex accurately predicted human performance. Although previous work led us to expect that IT would outperform V4, we were surprised by the quantitative precision with which simple IT-based linking hypotheses accounted for human behavior. PMID:26424887

  5. 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

    database of images for evaluating object recognition performance. We used multielectrode arrays to characterize hundreds of neurons in the visual ventral stream of nonhuman primates and measured the object recognition performance of >100 human observers. Remarkably, we found that simple learned weighted sums of firing rates of neurons in monkey inferior temporal (IT) cortex accurately predicted human performance. Although previous work led us to expect that IT would outperform V4, we were surprised by the quantitative precision with which simple IT-based linking hypotheses accounted for human behavior.

  6. Computational/Experimental Aeroheating Predictions for X-33. Phase 2; Vehicle

    NASA Technical Reports Server (NTRS)

    Hamilton, H. Harris, II; Weilmuenster, K. James; Horvath, Thomas J.; Berry, Scott A.

    1998-01-01

    Laminar and turbulent heating-rate calculations from an "engineering" code and laminar calculations from a "benchmark" Navier-Stokes code are compared with experimental wind-tunnel data obtained on several candidate configurations for the X-33 Phase 2 flight vehicle. The experimental data were obtained at a Mach number of 6 and a freestream Reynolds number ranging from 1 to 8 x 10(exp 6)/ft. Comparisons are presented along the windward symmetry plane and in a circumferential direction around the body at several axial stations at angles of attack from 20 to 40 deg. The experimental results include both laminar and turbulent flow. For the highest angle of attack some of the measured heating data exhibited a "non-laminar" behavior which caused the heating to increase above the laminar level long before "classical" transition to turbulent flow was observed. This trend was not observed at the lower angles of attack. When the flow was laminar, both codes predicted the heating along the windward symmetry plane reasonably well but under-predicted the heating in the chine region. When the flow was turbulent the LATCH code accurately predicted the measured heating rates. Both codes were used to calculate heating rates over the X-33 vehicle at the peak heating point on the design trajectory and they were found to be in very good agreement over most of the vehicle windward surface.

  7. Predictions of Experimentally Observed Stochastic Ground Vibrations Induced by Blasting

    PubMed Central

    Kostić, Srđan; Perc, Matjaž; Vasović, Nebojša; Trajković, Slobodan

    2013-01-01

    In the present paper, we investigate the blast induced ground motion recorded at the limestone quarry “Suva Vrela” near Kosjerić, which is located in the western part of Serbia. We examine the recorded signals by means of surrogate data methods and a determinism test, in order to determine whether the recorded ground velocity is stochastic or deterministic in nature. Longitudinal, transversal and the vertical ground motion component are analyzed at three monitoring points that are located at different distances from the blasting source. The analysis reveals that the recordings belong to a class of stationary linear stochastic processes with Gaussian inputs, which could be distorted by a monotonic, instantaneous, time-independent nonlinear function. Low determinism factors obtained with the determinism test further confirm the stochastic nature of the recordings. Guided by the outcome of time series analysis, we propose an improved prediction model for the peak particle velocity based on a neural network. We show that, while conventional predictors fail to provide acceptable prediction accuracy, the neural network model with four main blast parameters as input, namely total charge, maximum charge per delay, distance from the blasting source to the measuring point, and hole depth, delivers significantly more accurate predictions that may be applicable on site. We also perform a sensitivity analysis, which reveals that the distance from the blasting source has the strongest influence on the final value of the peak particle velocity. This is in full agreement with previous observations and theory, thus additionally validating our methodology and main conclusions. PMID:24358140

  8. Prediction of permeability of regular scaffolds for skeletal tissue engineering: a combined computational and experimental study.

    PubMed

    Truscello, S; Kerckhofs, G; Van Bael, S; Pyka, G; Schrooten, J; Van Oosterwyck, H

    2012-04-01

    Scaffold permeability is a key parameter combining geometrical features such as pore shape, size and interconnectivity, porosity and specific surface area. It can influence the success of bone tissue engineering scaffolds, by affecting oxygen and nutrient transport, cell seeding efficiency, in vitro three-dimensional (3D) cell culture and, ultimately, the amount of bone formation. An accurate and efficient prediction of scaffold permeability would be highly useful as part of a scaffold design process. The aim of this study was (i) to determine the accuracy of computational fluid dynamics (CFD) models for prediction of the permeability coefficient of three different regular Ti6Al4V scaffolds (each having a different porosity) by comparison with experimentally measured values and (ii) to verify the validity of the semi-empirical Kozeny equation to calculate the permeability analytically. To do so, five CFD geometrical models per scaffold porosity were built, based on different geometrical inputs: either based on the scaffold's computer-aided design (CAD) or derived from 3D microfocus X-ray computed tomography (micro-CT) data of the additive manufactured (AM) scaffolds. For the latter the influence of the spatial image resolution and the image analysis algorithm used to determine the scaffold's architectural features on the predicted permeability was analysed. CFD models based on high-resolution micro-CT images could predict the permeability coefficients of the studied scaffolds: depending on scaffold porosity and image analysis algorithm, relative differences between measured and predicted permeability values were between 2% and 27%. Finally, the analytical Kozeny equation was found to be valid. A linear correlation between the ratio Φ(3)/S(s)(2) and the permeability coefficient k was found for the predicted (by means of CFD) as well as measured values (relative difference of 16.4% between respective Kozeny coefficients), thus resulting in accurate and efficient

  9. 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

  10. 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.

  11. Prediction of vibration characteristics in beam structure using sub-scale modeling with experimental validation

    NASA Astrophysics Data System (ADS)

    Zai, Behzad Ahmed; Sami, Saad; Khan, M. Amir; Ahmad, Furqan; Park, Myung Kyun

    2015-09-01

    Geometric or sub-scale modeling techniques are used for the evaluation of large and complex dynamic structures to ensure accurate reproduction of load path and thus leading to true dynamic characteristics of such structures. The sub-scale modeling technique is very effective in the prediction of vibration characteristics of original large structure when the experimental testing is not feasible due to the absence of a large testing facility. Previous researches were more focused on free and harmonic vibration case with little or no consideration for readily encountered random vibration. A sub-scale modeling technique is proposed for estimating the vibration characteristics of any large scale structure such as Launch vehicles, Mega structures, etc., under various vibration load cases by utilizing precise scaled-down model of that dynamic structure. In order to establish an analytical correlation between the original structure and its scaled models, different scale models of isotropic cantilever beam are selected and analyzed under various vibration conditions( i.e. free, harmonic and random) using finite element package ANSYS. The developed correlations are also validated through experimental testing. The prediction made from the vibratory response of the scaled-down beam through the established sets of correlation are found similar to the response measured from the testing of original beam structure. The established correlations are equally applicable in the prediction of dynamic characteristics of any complex structure through its scaled-down models. This paper presents modified sub-scale modeling technique that enables accurate prediction of vibration characteristics of large and complex structure under not only sinusoidal but also for random vibrations.

  12. 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.

  13. 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

  14. 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

  15. Comparison of NTF Experimental Data with CFD Predictions from the Third AIAA CFD Drag Prediction Workshop

    NASA Technical Reports Server (NTRS)

    Vassberg, John C.; Tinoco, Edward N.; Mani, Mori; Levy, David; Zickuhr, Tom; Mavriplis, Dimitri J.; Wahls, Richard A.; Morrison, Joseph H.; Brodersen, Olaf P.; Eisfeld, Bernhard; Murayama, Mitsuhiro

    2008-01-01

    Recently acquired experimental data for the DLR-F6 wing-body transonic transport con figuration from the National Transonic Facility (NTF) are compared with the database of computational fluid dynamics (CFD) predictions generated for the Third AIAA CFD Drag Prediction Workshop (DPW-III). The NTF data were collected after the DPW-III, which was conducted with blind test cases. These data include both absolute drag levels and increments associated with this wing-body geometry. The baseline DLR-F6 wing-body geometry is also augmented with a side-of-body fairing which eliminates the flow separation in this juncture region. A comparison between computed and experimentally observed sizes of the side-of-body flow-separation bubble is included. The CFD results for the drag polars and separation bubble sizes are computed on grids which represent current engineering best practices for drag predictions. In addition to these data, a more rigorous attempt to predict absolute drag at the design point is provided. Here, a series of three grid densities are utilized to establish an asymptotic trend of computed drag with respect to grid convergence. This trend is then extrapolated to estimate a grid-converged absolute drag level.

  16. Prediction of Multipreform Shapes in Warm Forming with Experimental Verification

    NASA Astrophysics Data System (ADS)

    Kong, T. F.; Chan, L. C.

    2015-02-01

    This study uses a computer-aided simulation approach to predict the multipreform shapes of warm-forming intricate components. Nearly 100% of the scraps of primary hollow preforms are used to make secondary hollow preforms. This study simultaneously fabricates the AISI 316L stainless steel watch bezel by using scraps from the corresponding watch case. The appropriate preforms are designed with the aid of computer simulation such that die filling is completed, flash is reduced, and forming load is decreased. The specimens were prepared by custom-made tooling to verify the simulation results. Furthermore, the forming facilities are specially configured to carry out the physical experiments. Engineers eventually gain a better understanding of the warm-forming process using computer simulation. Moreover, they are able to design accurate preforms and fully utilize the material, which leads to a 50% improvement of the material utilization rate. The full material utilization also saves 40% and 20% of the total production cost and time, respectively.

  17. Spatiotemporal properties of microsaccades: Model predictions and experimental tests

    NASA Astrophysics Data System (ADS)

    Zhou, Jian-Fang; Yuan, Wu-Jie; Zhou, Zhao

    2016-10-01

    Microsaccades are involuntary and very small eye movements during fixation. Recently, the microsaccade-related neural dynamics have been extensively investigated both in experiments and by constructing neural network models. Experimentally, microsaccades also exhibit many behavioral properties. It’s well known that the behavior properties imply the underlying neural dynamical mechanisms, and so are determined by neural dynamics. The behavioral properties resulted from neural responses to microsaccades, however, are not yet understood and are rarely studied theoretically. Linking neural dynamics to behavior is one of the central goals of neuroscience. In this paper, we provide behavior predictions on spatiotemporal properties of microsaccades according to microsaccade-induced neural dynamics in a cascading network model, which includes both retinal adaptation and short-term depression (STD) at thalamocortical synapses. We also successfully give experimental tests in the statistical sense. Our results provide the first behavior description of microsaccades based on neural dynamics induced by behaving activity, and so firstly link neural dynamics to behavior of microsaccades. These results indicate strongly that the cascading adaptations play an important role in the study of microsaccades. Our work may be useful for further investigations of the microsaccadic behavioral properties and of the underlying neural dynamical mechanisms responsible for the behavioral properties.

  18. Reflectance spectroscopy of gold nanoshells: computational predictions and experimental measurements

    NASA Astrophysics Data System (ADS)

    Lin, Alex W. H.; Lewinski, Nastassja A.; Lee, Min-Ho; Drezek, Rebekah A.

    2006-10-01

    Gold nanoshells are concentric spherical constructs that possess highly desirable optical responses in the near infrared. Gold nanoshells consist of a thin outer gold shell and a silica core and can be used for both diagnostic and therapeutic purposes by tuning the optical response through changing the core-shell ratio as well as the overall size. Although optical properties of gold nanoshells have already been well documented, the reflectance characteristics are not well understood and have not yet been elucidated by experimental measurements. Yet, in order to use gold nanoshells as an optical contrast agent for scattering-based optical methods such as reflectance spectroscopy, it is critical to characterize the reflectance behavior. With this in mind, we used a fiber-optic-based spectrometer to measure diffuse reflectance of gold nanoshell suspensions from 500 nm to 900 nm. Experimental results show that gold nanoshells cause a significant increase in the measured reflectance. Spectral features associated with scattering from large angles ( 180°) were observed at low nanoshell concentrations. Monte Carlo modeling of gold nanoshells reflectance demonstrated the efficacy of using such methods to predict diffuse reflectance. Our studies suggest that gold nanoshells are an excellent candidate as optical contrast agents and that Monte Carlo methods are a useful tool for optimizing nanoshells best suited for scattering-based optical methods.

  19. 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

  20. 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.

  1. 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…

  2. 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

  3. 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).

  4. 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…

  5. Multitrophic functional diversity predicts ecosystem functioning in experimental assemblages of estuarine consumers.

    PubMed

    Lefcheck, Jonathan S; Duffy, J Emmett

    2015-11-01

    The use of functional traits to explain how biodiversity affects ecosystem functioning has attracted intense interest, yet few studies have a priori altered functional diversity, especially in multitrophic communities. Here, we manipulated multivariate functional diversity of estuarine grazers and predators within multiple levels of species richness to test how species richness and functional diversity predicted ecosystem functioning in a multitrophic food web. Community functional diversity was a better predictor than species richness for the majority of ecosystem properties, based on generalized linear mixed-effects models. Combining inferences from eight traits into a single multivariate index increased prediction accuracy of these models relative to any individual trait. Structural equation modeling revealed that functional diversity of both grazers and predators was important in driving final biomass within trophic levels, with stronger effects observed for predators. We also show that different species drove different ecosystem responses, with evidence for both sampling effects and complementarity. Our study extends experimental investigations of functional trait diversity to a multilevel food web, and demonstrates that functional diversity can be more accurate and effective than species richness in predicting community biomass in a food web context.

  6. Predicted and experimental structures of integrins and beta-propellers.

    PubMed

    Springer, Timothy A

    2002-12-01

    Integrins and other cell surface receptors have been fertile grounds for structure prediction experiments. Recently determined structures show remarkable successes, especially with beta-propeller domain predictions, and also reveal how ligand binding by integrins is conformationally regulated.

  7. Refined method for predicting electrochemical windows of ionic liquids and experimental validation studies.

    PubMed

    Zhang, Yong; Shi, Chaojun; Brennecke, Joan F; Maginn, Edward J

    2014-06-12

    A combined classical molecular dynamics (MD) and ab initio MD (AIMD) method was developed for the calculation of electrochemical windows (ECWs) of ionic liquids. In the method, the liquid phase of ionic liquid is explicitly sampled using classical MD. The electrochemical window, estimated by the energy difference between the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO), is calculated at the density functional theory (DFT) level based on snapshots obtained from classical MD trajectories. The snapshots were relaxed using AIMD and quenched to their local energy minima, which assures that the HOMO/LUMO calculations are based on stable configurations on the same potential energy surface. The new procedure was applied to a group of ionic liquids for which the ECWs were also experimentally measured in a self-consistent manner. It was found that the predicted ECWs not only agree with the experimental trend very well but also the values are quantitatively accurate. The proposed method provides an efficient way to compare ECWs of ionic liquids in the same context, which has been difficult in experiments or simulation due to the fact that ECW values sensitively depend on experimental setup and conditions.

  8. 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.

  9. Theoretical Predictions and Experimental Assessments of the Performance of Alumina RF Windows

    SciTech Connect

    Karen Ann Cummings

    1998-07-01

    Radio frequency (RF) windows are the most likely place for catastrophic failure to occur in input power couplers for particle accelerators. Reliable RF windows are essential for the success of the Accelerator Production of Tritium (APT) program because there are over 1000 windows on the accelerator, and it takes more than one day to recover from a window failure. The goals of this research are to analytically predict the lifetime of the windows, to develop a conditioning procedure, and to evaluate the performance of the RF windows. The analytical goal is to predict the lifetime of the windows. The probability of failure is predicted by the combination of a finite element model of the window, Weibull probabilistic analysis, and fracture mechanics. The window assembly is modeled in a finite element electromagnetic code in order to calculate the electric fields in the window. The geometry (i.e. mesh) and electric fields are input into a translator program to generate the mesh and boundary conditions for a finite element thermal structural code. The temperatures and stresses are determined in the thermal/structural code. The geometry and thermal structural results are input into another translator program to generate an input file for the reliability code. Material, geometry and service data are also input into the reliability code. To obtain accurate Weibull and fatigue data for the analytical model, four point bend tests were done. The analytical model is validated by comparing the measurements to the calculations. The lifetime of the windows is then determined using the reliability code. The analytical model shows the window has a good thermal mechanical design and that fast fracture is unlikely to occur below a power level of 9 Mw. The experimental goal is to develop a conditioning procedure and evaluate the performance of RF windows. During the experimental evaluation, much was learned about processing of the windows to improve the RF performance. Methods of

  10. 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.

  11. 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.

  12. 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).

  13. 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.

  14. 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

  15. 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.

  16. 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…

  17. 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

  18. 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.

  19. 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

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. Experimental Verification of Predicted Oscillations Near a Spin Resonance

    SciTech Connect

    Morozov, V.S.; Chao, A.W.; Krisch, A.D.; Leonova, M.A.; Raymond, R.S.; Sivers, D.W.; Wong, V.K.; Ganshvili, A.; Gebel, R.; Lehrach, A.; Lorentz, B.; Maier, R.; Prasuhn, D.; Stockhorst, H.; Welsch, D.; Hinterberger, F.; Ulbrich, K.; Schnase, A.; Stephenson, E.J.; Brantjes, N.P.M.; Onderwater, C.J.G.; /Groningen U.

    2011-12-06

    The Chao matrix formalism allows analytic calculations of a beam's polarization behavior inside a spin resonance. We recently tested its prediction of polarization oscillations occurring in a stored beam of polarized particles near a spin resonance. Using a 1.85?GeV/c polarized deuteron beam stored in COSY, we swept a new rf solenoid's frequency rather rapidly through 400 Hz during 100 ms, while varying the distance between the sweep's end frequency and the central frequency of an rf-induced spin resonance. Our measurements of the deuteron's polarization for sweeps ending near and inside the resonance agree with the Chao formalism's predicted oscillations.

  11. 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.

  12. Learning Political Science with Prediction Markets: An Experimental Study

    ERIC Educational Resources Information Center

    Ellis, Cali Mortenson; Sami, Rahul

    2012-01-01

    Prediction markets are designed to aggregate the information of many individuals to forecast future events. These markets provide participants with an incentive to seek information and a forum for interaction, making markets a promising tool to motivate student learning. We carried out a quasi-experiment in an introductory political science class…

  13. An integrated approach for non-periodic dynamic response prediction of complex structures: Numerical and experimental analysis

    NASA Astrophysics Data System (ADS)

    Rahneshin, Vahid; Chierichetti, Maria

    2016-09-01

    In this paper, a combined numerical and experimental method, called Extended Load Confluence Algorithm, is presented to accurately predict the dynamic response of non-periodic structures when little or no information about the applied loads is available. This approach, which falls into the category of Shape Sensing methods, inputs limited experimental information acquired from sensors to a mapping algorithm that predicts the response at unmeasured locations. The proposed algorithm consists of three major cores: an experimental core for data acquisition, a numerical core based on Finite Element Method for modeling the structure, and a mapping algorithm that improves the numerical model based on a modal approach in the frequency domain. The robustness and precision of the proposed algorithm are verified through numerical and experimental examples. The results of this paper demonstrate that without a precise knowledge of the loads acting on the structure, the dynamic behavior of the system can be predicted in an effective and precise manner after just a few iterations.

  14. 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

  15. 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.

  16. 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.

  17. 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.

  18. 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

  19. Experimental Investigations of Generalized Predictive Control for Tiltrotor Stability Augmentation

    NASA Technical Reports Server (NTRS)

    Nixon, Mark W.; Langston, Chester W.; Singleton, Jeffrey D.; Piatak, David J.; Kvaternik, Raymond G.; Bennett, Richard L.; Brown, Ross K.

    2001-01-01

    A team of researchers from the Army Research Laboratory, NASA Langley Research Center (LaRC), and Bell Helicopter-Textron, Inc. have completed hover-cell and wind-tunnel testing of a 1/5-size aeroelastically-scaled tiltrotor model using a new active control system for stability augmentation. The active system is based on a generalized predictive control (GPC) algorithm originally developed at NASA LaRC in 1997 for un-known disturbance rejection. Results of these investigations show that GPC combined with an active swashplate can significantly augment the damping and stability of tiltrotors in both hover and high-speed flight.

  20. 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

  1. 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

  2. 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…

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. Predicting the Unpredictable: 75 Years of Experimental Evidence

    NASA Astrophysics Data System (ADS)

    Radin, Dean I.

    2011-11-01

    From time immemorial, people have reported foreknowledge of future events. To determine whether such experiences are best understood via conventional explanations, or whether a retrocausal phenomenon might be involved in some instances, researchers have conducted hundreds of controlled laboratory experiments over the past 75 years. These studies fall into four general classes, and each class has generated repeatable evidence consistent with retrocausation. The statistical results for a class of forced-choice studies is associated with odds against chance of about 1024; for a class of free-response studies, odds about 1020; for psychophysiological-based studies, odds about 1017; and for implicit decision studies, odds about 1010. Effect sizes observed in the latter three classes are nearly identical, indicating replication of similar underlying effects. These effects are also in close agreement with the average effect size across 25,000 conventional social psychology experiments conducted over the last century, suggesting that retrocausal phenomena may not be especially unique, at least not in terms of the magnitude of effect. Bayesian analyses of the most recent classes of experiments confirm that the evidence is strongly in favor of a genuine effect, with Bayes Factors ranging from 13,669 to 1 for implicit decision experiments, to 2.9×1013 to 1 for psychophysiological designs. For the two most recent classes of studies examining retrocausal effects via unconscious physiological or behavioral measures, 85 of 101 studies (84%) reported by 25 different laboratories from the United States, Italy, Spain, Holland, Austria, Sweden, England, Scotland, Iran, Japan, and Australia, have produced results in the direction predicted by a retrocausal effect (odds against chance = 1.3×1012, via a sign test). Assessment of the methodologies used in these studies has not identified plausible conventional alternatives for the observed outcomes, suggesting the existence of a

  8. A comparison between theoretical prediction and experimental measurement of the dynamic behavior of spur gears

    NASA Astrophysics Data System (ADS)

    Rebbechi, Brian; Forrester, B. David; Oswald, Fred B.; Townsend, Dennis P.

    A comparison was made between computer model predictions of gear dynamics behavior and experimental results. The experimental data were derived from the NASA gear noise rig, which was used to record dynamic tooth loads and vibration. The experimental results were compared with predictions from the DSTO Aeronautical Research Laboratory's gear dynamics code for a matrix of 28 load speed points. At high torque the peak dynamic load predictions agree with the experimental results with an average error of 5 percent in the speed range 800 to 6000 rpm. Tooth separation (or bounce), which was observed in the experimental data for light torque, high speed conditions, was simulated by the computer model. The model was also successful in simulating the degree of load sharing between gear teeth in the multiple tooth contact region.

  9. A comparison between theoretical prediction and experimental measurement of the dynamic behavior of spur gears

    NASA Technical Reports Server (NTRS)

    Rebbechi, Brian; Forrester, B. David; Oswald, Fred B.; Townsend, Dennis P.

    1992-01-01

    A comparison was made between computer model predictions of gear dynamics behavior and experimental results. The experimental data were derived from the NASA gear noise rig, which was used to record dynamic tooth loads and vibration. The experimental results were compared with predictions from the DSTO Aeronautical Research Laboratory's gear dynamics code for a matrix of 28 load speed points. At high torque the peak dynamic load predictions agree with the experimental results with an average error of 5 percent in the speed range 800 to 6000 rpm. Tooth separation (or bounce), which was observed in the experimental data for light torque, high speed conditions, was simulated by the computer model. The model was also successful in simulating the degree of load sharing between gear teeth in the multiple tooth contact region.

  10. Predictive and Construct Validity of Six Experimental Measures of Career Maturity.

    ERIC Educational Resources Information Center

    Westbrook, Bert W.; And Others

    1985-01-01

    Investigated the predictive and construct validity of six experimental measures of career maturity among high school students. Data provide some support for the construct and predictive validity of four of the six career maturity scales. Some technical issues and possible sources of invalidity are discussed, and recommedations are made for future…

  11. Comparison of a tension leg platform response prediction model with experimental data

    SciTech Connect

    Gurley, K.R.; Kareem, A.

    1996-12-31

    A numerical model developed to efficiently predict the response of a tension leg platform under wind and wave loads in the frequency domain is examined in light of experimental data. Three studies are conducted in which model performance is compared to current state-of-the-art models, a simplified model, and two sets of experimental data. The wave diffraction and response analysis codes of the model under consideration are applied to a benchmark study in the literature and are found to be in close agreement with the state-of-the-art codes. The model is then applied to two sets of experimental data, the first of which accompanies the results of a simplified model to predict the experimental response. The current model compares favorably with the other response analysis codes under consideration. The model also matches well with experimental data, within the limitations of uncertainties in experimental procedures.

  12. 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.

  13. 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

  14. 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.

  15. 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

  16. 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

  17. Experimental validation of finite element and boundary element methods for predicting structural vibration and radiated noise

    NASA Technical Reports Server (NTRS)

    Seybert, A. F.; Wu, T. W.; Wu, X. F.

    1994-01-01

    This research report is presented in three parts. In the first part, acoustical analyses were performed on modes of vibration of the housing of a transmission of a gear test rig developed by NASA. The modes of vibration of the transmission housing were measured using experimental modal analysis. The boundary element method (BEM) was used to calculate the sound pressure and sound intensity on the surface of the housing and the radiation efficiency of each mode. The radiation efficiency of each of the transmission housing modes was then compared to theoretical results for a finite baffled plate. In the second part, analytical and experimental validation of methods to predict structural vibration and radiated noise are presented. A rectangular box excited by a mechanical shaker was used as a vibrating structure. Combined finite element method (FEM) and boundary element method (BEM) models of the apparatus were used to predict the noise level radiated from the box. The FEM was used to predict the vibration, while the BEM was used to predict the sound intensity and total radiated sound power using surface vibration as the input data. Vibration predicted by the FEM model was validated by experimental modal analysis; noise predicted by the BEM was validated by measurements of sound intensity. Three types of results are presented for the total radiated sound power: sound power predicted by the BEM model using vibration data measured on the surface of the box; sound power predicted by the FEM/BEM model; and sound power measured by an acoustic intensity scan. In the third part, the structure used in part two was modified. A rib was attached to the top plate of the structure. The FEM and BEM were then used to predict structural vibration and radiated noise respectively. The predicted vibration and radiated noise were then validated through experimentation.

  18. 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

  19. 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.

  20. 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

  1. 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

  2. Gain scheduled continuous-time model predictive controller with experimental validation on AC machine

    NASA Astrophysics Data System (ADS)

    Wang, Liuping; Gan, Lu

    2013-08-01

    Linear controllers with gain scheduling have been successfully used in the control of nonlinear systems for the past several decades. This paper proposes the design of gain scheduled continuous-time model predictive controller with constraints. Using induction machine as an illustrative example, the paper will show the four steps involved in the design of a gain scheduled predictive controller: (i) linearisation of a nonlinear plant according to operating conditions; (ii) the design of linear predictive controllers for the family of linear models; (iii) gain scheduled predictive control law that will optimise a multiple model objective function with constraints, which will also ensure smooth transitions (i.e. bumpless transfer) between the predictive controllers; (iv) experimental validation of the gain scheduled predictive control system with constraints.

  3. Experimental evaluation of a flat wake theory for predicting rotor inflow-wake velocities

    NASA Technical Reports Server (NTRS)

    Wilson, John C.

    1992-01-01

    The theory for predicting helicopter inflow-wake velocities called flat wake theory was correlated with several sets of experimental data. The theory was developed by V. E. Baskin of the USSR, and a computer code known as DOWN was developed at Princeton University to implement the theory. The theory treats the wake geometry as rigid without interaction between induced velocities and wake structure. The wake structure is assumed to be a flat sheet of vorticity composed of trailing elements whose strength depends on the azimuthal and radial distributions of circulation on a rotor blade. The code predicts the three orthogonal components of flow velocity in the field surrounding the rotor. The predictions can be utilized in rotor performance and helicopter real-time flight-path simulation. The predictive capability of the coded version of flat wake theory provides vertical inflow patterns similar to experimental patterns.

  4. Clathrate Structure Determination by Combining Crystal Structure Prediction with Computational and Experimental (129) Xe NMR Spectroscopy.

    PubMed

    Selent, Marcin; Nyman, Jonas; Roukala, Juho; Ilczyszyn, Marek; Oilunkaniemi, Raija; Bygrave, Peter J; Laitinen, Risto; Jokisaari, Jukka; Day, Graeme M; Lantto, Perttu

    2017-01-23

    An approach is presented for the structure determination of clathrates using NMR spectroscopy of enclathrated xenon to select from a set of predicted crystal structures. Crystal structure prediction methods have been used to generate an ensemble of putative structures of o- and m-fluorophenol, whose previously unknown clathrate structures have been studied by (129) Xe NMR spectroscopy. The high sensitivity of the (129) Xe chemical shift tensor to the chemical environment and shape of the crystalline cavity makes it ideal as a probe for porous materials. The experimental powder NMR spectra can be used to directly confirm or reject hypothetical crystal structures generated by computational prediction, whose chemical shift tensors have been simulated using density functional theory. For each fluorophenol isomer one predicted crystal structure was found, whose measured and computed chemical shift tensors agree within experimental and computational error margins and these are thus proposed as the true fluorophenol xenon clathrate structures.

  5. 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.

  6. 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.

  7. Experimental verification of the Neuber relation at room and elevated temperatures. M.S. Thesis; [to predict stress-strain behavior in notched specimens of hastelloy x

    NASA Technical Reports Server (NTRS)

    Lucas, L. J.

    1982-01-01

    The accuracy of the Neuber equation at room temperature and 1,200 F as experimentally determined under cyclic load conditions with hold times. All strains were measured with an interferometric technique at both the local and remote regions of notched specimens. At room temperature, strains were obtained for the initial response at one load level and for cyclically stable conditions at four load levels. Stresses in notched members were simulated by subjecting smooth specimens to he same strains as were recorded on the notched specimen. Local stress-strain response was then predicted with excellent accuracy by subjecting a smooth specimen to limits established by the Neuber equation. Data at 1,200 F were obtained with the same experimental techniques but only in the cyclically stable conditions. The Neuber prediction at this temperature gave relatively accurate results in terms of predicting stress and strain points.

  8. 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.

  9. Hybrid predictions of railway induced ground vibration using a combination of experimental measurements and numerical modelling

    NASA Astrophysics Data System (ADS)

    Kuo, K. A.; Verbraken, H.; Degrande, G.; Lombaert, G.

    2016-07-01

    Along with the rapid expansion of urban rail networks comes the need for accurate predictions of railway induced vibration levels at grade and in buildings. Current computational methods for making predictions of railway induced ground vibration rely on simplifying modelling assumptions and require detailed parameter inputs, which lead to high levels of uncertainty. It is possible to mitigate against these issues using a combination of field measurements and state-of-the-art numerical methods, known as a hybrid model. In this paper, two hybrid models are developed, based on the use of separate source and propagation terms that are quantified using in situ measurements or modelling results. These models are implemented using term definitions proposed by the Federal Railroad Administration and assessed using the specific illustration of a surface railway. It is shown that the limitations of numerical and empirical methods can be addressed in a hybrid procedure without compromising prediction accuracy.

  10. 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.

  11. Experimental verification of bremsstrahlung production and dosimetry predictions as a function of energy and angle

    SciTech Connect

    Beutler, D.E.; Halbleib, J.A.; Sanford, T.W.L. ); Knott, D.P. )

    1994-12-01

    The integrated TIGER series (ITS) of coupled electron/photon Monte Carlo transport codes is widely used to predict the radiation output from flash x-ray sources and for the design of bremsstrahlung converters. The codes are also used to predict the response of radiation diagnostics (e.g., thermoluminescent dosimeters (TLD's)) and the response of electronic components and subsystems. Hence, the demonstration of the validity of the ITS codes for these applications is important. Here, measurements of energy deposition from bremsstrahlung production as a function of angle and beam energy (5-25 MeV) are shown to be in excellent agreement with Monte Carlo predictions. Dosimetry measurements are made and predicted in both equilibrated and under equilibrated radiation environments. In the latter case the quality of the agreement requires an accurate prediction of both the photon and electron spectra produced by the primary electron beam. An improved empirical equation for predicting bremsstrahlung production is also presented. This empirical relation can be used to estimate doses without resorting to expensive calculational efforts. It also gives an analytical relationship for dose as a function of energy and angle for a converter optimized for bremsstrahlung production using 15.5 MeV electrons.

  12. Experimental evidence for allosteric modifier saturation as predicted by the bi-substrate Hill equation.

    PubMed

    Hanekom, A J; Hofmeyr, J H S; Snoep, J L; Rohwer, J M

    2006-09-01

    The cooperative enzyme reaction rates predicted by the bi-substrate Hill equation and the bi-substrate Monod-Wyman-Changeux (MWC) equation when allosterically inhibited are compared in silico. Theoretically, the Hill equation predicts that when the maximum inhibitory effect at a certain substrate condition has been reached, an increase in allosteric inhibitor concentration will have no effect on reaction rate, that is the Hill equation shows allosteric inhibitor saturation. This saturating inhibitory effect is not present in the MWC equation. Experimental in vitro data for pyruvate kinase, a bi-substrate cooperative enzyme that is allosterically inhibited, are presented. This enzyme also shows inhibitor saturation, and therefore serves as experimental evidence that the bi-substrate Hill equation predicts more realistic allosteric inhibitor behaviour than the bi-substrate MWC equation.

  13. First accurate experimental study of Mu reactivity from a state-selected reactant in the gas phase: the Mu + H2{1} reaction rate at 300 K

    NASA Astrophysics Data System (ADS)

    Bakule, Pavel; Sukhorukov, Oleksandr; Ishida, Katsuhiko; Pratt, Francis; Fleming, Donald; Momose, Takamasa; Matsuda, Yasuyuki; Torikai, Eiko

    2015-02-01

    This paper reports on the experimental background and methodology leading to recent results on the first accurate measurement of the reaction rate of the muonium (Mu) atom from a state-selected reactant in the gas phase: the Mu + H2\\{1\\}\\to MuH + H reaction at 300 K, and its comparison with rigorous quantum rate theory, Bakule et al (2012 J. Phys. Chem. Lett. 3 2755). Stimulated Raman pumping, induced by 532 nm light from the 2nd harmonic of a Nd:YAG laser, was used to produce H2 in its first vibrational (v = 1) state, H2\\{1\\}, in a single Raman/reaction cell. A pulsed muon beam (from ‘ISIS’, at 50 Hz) matched the 25 Hz repetition rate of the laser, allowing data taking in equal ‘Laser-On/Laser-Off’ modes of operation. The signal to noise was improved by over an order of magnitude in comparison with an earlier proof-of-principle experiment. The success of the present experiment also relied on optimizing the overlap of the laser profile with the extended stopping distribution of the muon beam at 50 bar H2 pressure, in which Monte Carlo simulations played a central role. The rate constant, found from the analysis of three separate measurements, which includes a correction for the loss of {{H}2}\\{1\\} concentration due to collisional relaxation with unpumped H2 during the time of each measurement, is {{k}Mu}\\{1\\} = 9.9[(-1.4)(+1.7)] × 10-13 cm3 s-1 at 300 K. This is in good to excellent agreement with rigorous quantum rate calculations on the complete configuration interaction/Born-Huang surface, as reported earlier by Bakule et al, and which are also briefly commented on herein.

  14. 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

  15. 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

  16. Numerical predictions versus experimental findings on the power-harvesting output of a NiMnGa alloy

    NASA Astrophysics Data System (ADS)

    Nelson, Isaac; Dikes, Jason; Feigenbaum, Heidi; Ciocanel, Constantin

    2014-03-01

    Magnetic shape memory alloys (MSMAs) can display up to 10% recoverable strain in response to the application of a magnetic field or compressive mechanical stress. The amount of recoverable strain depends on the amount and direction of the applied stress and magnetic field as well as manufacturing, chemical composition, and training of the material. Due to their relatively large strains and fast response, MSMAs are suitable for a wide range of applications, including power harvesting, sensing, and actuation. The response of MSMAs is primarily driven by the reorientation of martensite variants. Power harvesting is possible due to this reorientation process and the accompanying change in material's magnetization, which can be changed into an electric potential/voltage using a pick-up coil placed around (or on the side of) the specimen. The magnitude of the output voltage depends on the number of turns of the pick-up coil, the amplitude of the reorientation strain, the magnitude and direction of the biased magnetic field, and the frequency at which the reorientation occurs. This paper focuses on the ability of a two dimensional constitutive model, developed by the group to capture the magnetomechanical response of MSMAs under general two dimensional loading conditions, to predict the power harvesting output of a Ni2MnGa specimen. Comparison between model predictions of voltage output and experimental measurements of the same indicate that, while the model is able to replicate the stress-strain response of the material during power harvesting, it is unable to accurately predict the magnitude of the experimentally measured voltage output. This indicates that additional features still need to be included in the model to better capture the change in magnetization that occurs during variant reorientation.

  17. 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.

  18. 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

  19. 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.

  20. Computational ecotoxicology: simultaneous prediction of ecotoxic effects of nanoparticles under different experimental conditions.

    PubMed

    Kleandrova, Valeria V; Luan, Feng; González-Díaz, Humberto; Ruso, Juan M; Melo, André; Speck-Planche, Alejandro; Cordeiro, M Natália D S

    2014-12-01

    Nanotechnology has brought great advances to many fields of modern science. A manifold of applications of nanoparticles have been found due to their interesting optical, electrical, and biological/chemical properties. However, the potential toxic effects of nanoparticles to different ecosystems are of special concern nowadays. Despite the efforts of the scientific community, the mechanisms of toxicity of nanoparticles are still poorly understood. Quantitative-structure activity/toxicity relationships (QSAR/QSTR) models have just started being useful computational tools for the assessment of toxic effects of nanomaterials. But most QSAR/QSTR models have been applied so far to predict ecotoxicity against only one organism/bio-indicator such as Daphnia magna. This prevents having a deeper knowledge about the real ecotoxic effects of nanoparticles, and consequently, there is no possibility to establish an efficient risk assessment of nanomaterials in the environment. In this work, a perturbation model for nano-QSAR problems is introduced with the aim of simultaneously predicting the ecotoxicity of different nanoparticles against several assay organisms (bio-indicators), by considering also multiple measures of ecotoxicity, as well as the chemical compositions, sizes, conditions under which the sizes were measured, shapes, and the time during which the diverse assay organisms were exposed to nanoparticles. The QSAR-perturbation model was derived from a database containing 5520 cases (nanoparticle-nanoparticle pairs), and it was shown to exhibit accuracies of ca. 99% in both training and prediction sets. In order to demonstrate the practical applicability of our model, three different nickel-based nanoparticles (Ni) with experimental values reported in the literature were predicted. The predictions were found to be in very good agreement with the experimental evidences, confirming that Ni-nanoparticles are not ecotoxic when compared with other nanoparticles. The results

  1. 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.

  2. Multiaxial deformation and life prediction model and experimental data for advanced silicon nitride ceramics

    SciTech Connect

    Ding, J.L.; Liu, K.C.; Brinkman, C.R.

    1993-06-01

    This paper summarizes recent experimental results on creep and creep rupture behavior of a commercial grade of Si{sub 3}N{sub 4} ceramic in the temperature range of 1150 to 1300C obtained at ORNL; and introduces a tentative multiaxial deformation and life prediction model for ceramic materials under general thermomechanical loadings. Issues related to the possible standardization of the data analysis methodology and possible future research needs for high temperature structural ceramics in the area of development of data base and life prediction methodology are also discussed.

  3. Why savannah monitor lizards hyperventilate during activity: a comparison of model predictions and experimental data.

    PubMed

    Wang, Tobias; Hicks, James W

    2004-12-15

    The functional and structural factors that limit maximal oxygen uptake (VO2 max) in lizards are not completely understood. Using an integrative model describing the interactive nature of the individual oxygen transport conductances, we performed an analysis of the oxygen transport system in the highly aerobic lizard Varanus exanthematicus with specific reference to the sensitivity of VO2 max to potential limitations in the ventilatory system. Our analysis predicts that DLO2 must increase more than three-fold at VO2 max and even with this increase in DLO2 , the VO2 max may be sensitive to factors that alter lung ventilation and/or lower lung PO2. To test the predictions of the model analysis, we experimentally determined the effects of reducing inspired O2 on VO2 max during treadmill exercise. We conclude from both our theoretical and experimental analyses that V. exanthematicus operates near the functional limits of its lung.

  4. Viscosities of Binary Mixtures Containing Isomeric Chlorobutanes and Diisopropylether: Experimental and Predicted Values

    NASA Astrophysics Data System (ADS)

    Montaño, D.; Guerrero, H.; Bandrés, I.; López, M. C.; Lafuente, Carlos

    2010-03-01

    In this work, viscosities of binary mixtures of isomeric chlorobutanes with diisopropylether have been determined as a function of composition under atmospheric pressure and in the temperature range from 283.15 K to 313.15 K with steps of 5 K. Kinematics viscosities were measured using an Ubbelohde viscosimeter; absolute viscosities were obtained from kinematic viscosities and densities. Finally, we have used the Asfour method for predicting the dependence of viscosity with composition and comparing it with our experimental data.

  5. Pulse-echo ultrasound transit time spectroscopy: A comparison of experimental measurement and simulation prediction.

    PubMed

    Wille, Marie-Luise; Almualimi, Majdi A; Langton, Christian M

    2016-01-01

    Considering ultrasound propagation through complex composite media as an array of parallel sonic rays, a comparison of computer-simulated prediction with experimental data has previously been reported for transmission mode (where one transducer serves as transmitter, the other as receiver) in a series of 10 acrylic step-wedge samples, immersed in water, exhibiting varying degrees of transit time inhomogeneity. In this study, the same samples were used but in pulse-echo mode, where the same ultrasound transducer served as both transmitter and receiver, detecting both 'primary' (internal sample interface) and 'secondary' (external sample interface) echoes. A transit time spectrum was derived, describing the proportion of sonic rays with a particular transit time. A computer simulation was performed to predict the transit time and amplitude of various echoes created, and compared with experimental data. Applying an amplitude-tolerance analysis, 91.7% ± 3.7% of the simulated data were within ±1 standard deviation of the experimentally measured amplitude-time data. Correlation of predicted and experimental transit time spectra provided coefficients of determination (R(2)%) ranging from 100.0% to 96.8% for the various samples tested. The results acquired from this study provide good evidence for the concept of parallel sonic rays. Furthermore, deconvolution of experimental input and output signals has been shown to provide an effective method to identify echoes otherwise lost due to phase cancellation. Potential applications of pulse-echo ultrasound transit time spectroscopy include improvement of ultrasound image fidelity by improving spatial resolution and reducing phase interference artefacts.

  6. Experimental verification of ion stopping power prediction from dual energy CT data in tissue surrogates.

    PubMed

    Hünemohr, Nora; Krauss, Bernhard; Tremmel, Christoph; Ackermann, Benjamin; Jäkel, Oliver; Greilich, Steffen

    2014-01-06

    We present an experimental verification of stopping-power-ratio (SPR) prediction from dual energy CT (DECT) with potential use for dose planning in proton and ion therapy. The approach is based on DECT images converted to electron density relative to water ϱe/ϱe, w and effective atomic number Zeff. To establish a parameterization of the I-value by Zeff, 71 tabulated tissue compositions were used. For the experimental assessment of the method we scanned 20 materials (tissue surrogates, polymers, aluminum, titanium) at 80/140Sn kVp and 100/140Sn kVp (Sn: additional tin filtration) and computed the ϱe/ϱe, w and Zeff with a purely image based algorithm. Thereby, we found that ϱe/ϱe, w (Zeff) could be determined with an accuracy of 0.4% (1.7%) for the tissue surrogates with known elemental compositions. SPRs were predicted from DECT images for all 20 materials using the presented approach and were compared to measured water-equivalent path lengths (closely related to SPR). For the tissue surrogates the presented DECT approach was found to predict the experimental values within 0.6%, for aluminum and titanium within an accuracy of 1.7% and 9.4% (from 16-bit reconstructed DECT images).

  7. Development of a radial ventricular assist device using numerical predictions and experimental haemolysis.

    PubMed

    Carswell, Dave; Hilton, Andy; Chan, Chris; McBride, Diane; Croft, Nick; Slone, Avril; Cross, Mark; Foster, Graham

    2013-08-01

    The objective of this study was to demonstrate the potential of Computational Fluid Dynamics (CFD) simulations in predicting the levels of haemolysis in ventricular assist devices (VADs). Three different prototypes of a radial flow VAD have been examined experimentally and computationally using CFD modelling to assess device haemolysis. Numerical computations of the flow field were computed using a CFD model developed with the use of the commercial software Ansys CFX 13 and a set of custom haemolysis analysis tools. Experimental values for the Normalised Index of Haemolysis (NIH) have been calculated as 0.020 g/100 L, 0.014 g/100 L and 0.0042 g/100 L for the three designs. Numerical analysis predicts an NIH of 0.021 g/100 L, 0.017 g/100 L and 0.0057 g/100 L, respectively. The actual differences between experimental and numerical results vary between 0.0012 and 0.003 g/100 L, with a variation of 5% for Pump 1 and slightly larger percentage differences for the other pumps. The work detailed herein demonstrates how CFD simulation and, more importantly, the numerical prediction of haemolysis may be used as an effective tool in order to help the designers of VADs manage the flow paths within pumps resulting in a less haemolytic device.

  8. Suspended Sediment Load Prediction Using Support Vector Machines in the Goodwin Creek Experimental Watershed

    NASA Astrophysics Data System (ADS)

    Chiang, Jie-Lun; Tsai, Kuang-Jung; Chen, Yie-Ruey; Lee, Ming-Hsi; Sun, Jai-Wei

    2014-05-01

    Strong correlation exists between river discharge and suspended sediment load. The relationship of discharge and suspended sediment load was used to estimate suspended sediment load by using regression model, artificial neural network and support vector machine in this study. Records of river discharges and suspended sediment loads in the Goodwin Creek Experimental Watershed in United States were investigated as a case study. Seventy percent of the records were used as training data set to develop prediction models. The other thirty percent records were used as verification data set. The performances of those models were evaluated by mean absolute percentage error (MAPE). The MAPEs show that support vector machine outperforms the artificial neural network and regression model. The results show that the MAPE of the proposed SVM can achieve less than 14% for 120 minutes prediction (four time steps). As a result, we believe that the proposed SVM model has high potential for predicting suspended sediment load.

  9. 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.

  10. Predicting epistasis: an experimental test of metabolic control theory with bacterial transcription and translation.

    PubMed

    MacLean, R C

    2010-03-01

    Epistatic interactions between mutations are thought to play a crucial role in a number of evolutionary processes, including adaptation and sex. Evidence for epistasis is abundant, but tests of general theoretical models that can predict epistasis are lacking. In this study, I test the ability of metabolic control theory to predict epistasis using a novel experimental approach that combines phenotypic and genetic perturbations of enzymes involved in gene expression and protein synthesis in the bacterium Pseudomonas aeruginosa. These experiments provide experimental support for two key predictions of metabolic control theory: (i) epistasis between genes involved in the same pathway is antagonistic; (ii) epistasis becomes increasingly antagonistic as mutational severity increases. Metabolic control theory is a general theory that applies to any set of genes that are involved in the same linear processing chain, not just metabolic pathways, and I argue that this theory is likely to have important implications for predicting epistasis between functionally coupled genes, such as those involved in antibiotic resistance. Finally, this study highlights the fact that phenotypic manipulations of gene activity provide a powerful method for studying epistasis that complements existing genetic methods.

  11. 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.

  12. Metabolic regio- and stereoselectivity of cytochrome P450 2D6 towards 3,4-methylenedioxy-N-alkylamphetamines: in silico predictions and experimental validation.

    PubMed

    Keizers, Peter H J; de Graaf, Chris; de Kanter, Frans J J; Oostenbrink, Chris; Feenstra, K Anton; Commandeur, Jan N M; Vermeulen, Nico P E

    2005-09-22

    A series of 3,4-methylenedioxy-N-alkylamphetamines (MDAAs) were automatically docked and subjected to molecular dynamics (MD) simulations in a cytochrome P450 2D6 (CYP2D6) protein model. The predicted substrate binding orientations, sites of oxidation, and relative reactivities were compared to the experimental data of wild-type and Phe120Ala mutant CYP2D6. Automated docking results were not sufficient to accurately rationalize experimental binding orientations of 3,4-methylenedioxy-N-methylamphetamine (MDMA) in the two enzymes as measured with spin lattice relaxation NMR. Nevertheless, the docking results could be used as starting structures for MD simulations. Predicted binding orientations of MDMA and sites of oxidation of the MDAAs derived from MD simulations matched well with the experimental data. It appeared the experimental results were best described in MD simulations considering the nitrogen atoms of the MDAAs in neutral form. Differences in regioselectivity and stereoselectivity in the oxidative metabolism of the MDAAs by the Phe120Ala mutant CYP2D6 were correctly predicted, and the effects of the Phe120Ala mutation could be rationalized as well.

  13. The impact of incomplete knowledge on evaluation: an experimental benchmark for protein function prediction

    PubMed Central

    Huttenhower, Curtis; Hibbs, Matthew A.; Myers, Chad L.; Caudy, Amy A.; Hess, David C.; Troyanskaya, Olga G.

    2009-01-01

    Motivation: Rapidly expanding repositories of highly informative genomic data have generated increasing interest in methods for protein function prediction and inference of biological networks. The successful application of supervised machine learning to these tasks requires a gold standard for protein function: a trusted set of correct examples, which can be used to assess performance through cross-validation or other statistical approaches. Since gene annotation is incomplete for even the best studied model organisms, the biological reliability of such evaluations may be called into question. Results: We address this concern by constructing and analyzing an experimentally based gold standard through comprehensive validation of protein function predictions for mitochondrion biogenesis in Saccharomyces cerevisiae. Specifically, we determine that (i) current machine learning approaches are able to generalize and predict novel biology from an incomplete gold standard and (ii) incomplete functional annotations adversely affect the evaluation of machine learning performance. While computational approaches performed better than predicted in the face of incomplete data, relative comparison of competing approaches—even those employing the same training data—is problematic with a sparse gold standard. Incomplete knowledge causes individual methods' performances to be differentially underestimated, resulting in misleading performance evaluations. We provide a benchmark gold standard for yeast mitochondria to complement current databases and an analysis of our experimental results in the hopes of mitigating these effects in future comparative evaluations. Availability: The mitochondrial benchmark gold standard, as well as experimental results and additional data, is available at http://function.princeton.edu/mitochondria Contact: ogt@cs.princeton.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19561015

  14. Experimental evolution of phenotypic plasticity: how predictive are cross-environment genetic correlations?

    PubMed

    Czesak, Mary Ellen; Fox, Charles W; Wolf, Jason B

    2006-09-01

    Genetic correlations are often predictive of correlated responses of one trait to selection on another trait. There are examples, however, in which genetic correlations are not predictive of correlated responses. We examine how well a cross-environment genetic correlation predicts correlated responses to selection and the evolution of phenotypic plasticity in the seed beetle Stator limbatus. This beetle exhibits adaptive plasticity in egg size by laying large eggs on a resistant host and small eggs on a high-quality host. From a half-sib analysis, the cross-environment genetic correlation estimate was large and positive (rA=0.99). However, an artificial-selection experiment on egg size found that the realized genetic correlations were positive but asymmetrical; that is, they depended on both the host on which selection was imposed and the direction of selection. The half-sib estimate poorly predicted the evolution of egg size plasticity; plasticity evolved when selection was imposed on one host but did not evolve when selection was imposed on the other host. We use a simple two-locus additive genetic model to explore the conditions that can generate the observed realized genetic correlation and the observed pattern of plasticity evolution. Our model and experimental results indicate that the ability of genetic correlations to predict correlated responses to selection depends on the underlying genetic architecture producing the genetic correlation.

  15. On the experimental prediction of the stability threshold speed caused by rotating damping

    NASA Astrophysics Data System (ADS)

    Vervisch, B.; Derammelaere, S.; Stockman, K.; De Baets, P.; Loccufier, M.

    2016-08-01

    An ever increasing demand for lighter rotating machinery and higher operating speeds results in a raised probability of instabilities. Rotating damping is one of the reasons, instability occurs. Rotating damping, or rotor internal damping, is the damping related to all rotating parts while non-rotating damping appearing in the non-rotating parts. The present study describes a rotating setup, designed to investigate rotating damping experimentally. An efficient experimental procedure is presented to predict the stability threshold of a rotating machine. The setup consists of a long thin shaft with a disk in the middle and clamped boundary conditions. The goal is to extract the system poles as a function of the rotating speed. The real parts of these poles are used to construct the decay rate plot, which is an indication for the stability. The efficiency of the experimental procedure relies on the model chosen for the rotating shaft. It is shown that the shaft behavior can be approximated by a single degree of freedom model that incorporates a speed dependent damping. As such low measurement effort and only one randomly chosen measurement location are needed to construct the decay rate plot. As an excitation, an automated impact hammer is used and the response is measured by eddy current probes. The proposed method yields a reliable prediction of the stability threshold speed which is validated through measurements.

  16. Experimental predictions drawn from a computational model of sign-trackers and goal-trackers

    PubMed Central

    Lesaint, Florian; Sigaud, Olivier; Clark, Jeremy J.; Flagel, Shelly B.; Khamassi, Mehdi

    2014-01-01

    Gaining a better understanding of the biological mechanisms underlying the individual variation observed in response to rewards and reward cues could help to identify and treat individuals more prone to disorders of impulsive control, such as addiction. Variation in response to reward cues is captured in rats undergoing autoshaping experiments where the appearance of a lever precedes food delivery. Although no response is required for food to be delivered, some rats (goal-trackers) learn to approach and avidly engage the magazine until food delivery, whereas other rats (sign-trackers) come to approach and engage avidly the lever. The impulsive and often maladaptive characteristics of the latter response are reminiscent of addictive behaviour in humans. In a previous article, we developed a computational model accounting for a set of experimental data regarding sign-trackers and goal-trackers. Here we show new simulations of the model to draw experimental predictions that could help further validate or refute the model. In particular, we apply the model to new experimental protocols such as injecting flupentixol locally into the core of the nucleus accumbens rather than systemically, and lesioning of the core of the nucleus accumbens before or after conditioning. In addition, we discuss the possibility of removing the food magazine during the inter-trial interval. The predictions from this revised model will help us better understand the role of different brain regions in the behaviours expressed by sign-trackers and goal-trackers. PMID:24954026

  17. Experimental predictions drawn from a computational model of sign-trackers and goal-trackers.

    PubMed

    Lesaint, Florian; Sigaud, Olivier; Clark, Jeremy J; Flagel, Shelly B; Khamassi, Mehdi

    2015-01-01

    Gaining a better understanding of the biological mechanisms underlying the individual variation observed in response to rewards and reward cues could help to identify and treat individuals more prone to disorders of impulsive control, such as addiction. Variation in response to reward cues is captured in rats undergoing autoshaping experiments where the appearance of a lever precedes food delivery. Although no response is required for food to be delivered, some rats (goal-trackers) learn to approach and avidly engage the magazine until food delivery, whereas other rats (sign-trackers) come to approach and engage avidly the lever. The impulsive and often maladaptive characteristics of the latter response are reminiscent of addictive behaviour in humans. In a previous article, we developed a computational model accounting for a set of experimental data regarding sign-trackers and goal-trackers. Here we show new simulations of the model to draw experimental predictions that could help further validate or refute the model. In particular, we apply the model to new experimental protocols such as injecting flupentixol locally into the core of the nucleus accumbens rather than systemically, and lesioning of the core of the nucleus accumbens before or after conditioning. In addition, we discuss the possibility of removing the food magazine during the inter-trial interval. The predictions from this revised model will help us better understand the role of different brain regions in the behaviours expressed by sign-trackers and goal-trackers.

  18. Vibrations inside buildings due to subway railway traffic. Experimental validation of a comprehensive prediction model.

    PubMed

    Lopes, Patrícia; Ruiz, Jésus Fernández; Alves Costa, Pedro; Medina Rodríguez, L; Cardoso, António Silva

    2016-10-15

    The present paper focuses on the experimental validation of a numerical approach previously proposed by the authors for the prediction of vibrations inside buildings due to railway traffic in tunnels. The numerical model is based on the concept of dynamic substructuring and is composed by three autonomous models to simulate the following main parts of the problem: i) generation of vibrations (train-track interaction); ii) propagation of vibrations (track-tunnel-ground system); iii) reception of vibrations (building coupled to the ground). The experimental validation consists in the comparison between the results predicted by the proposed numerical model and the measurements performed inside a building due to the railway traffic in a shallow tunnel located in Madrid. Apart from the brief description of the numerical model and of the case study, the main options and simplifications adopted on the numerical modeling strategy are discussed. The balance adopted between accuracy and simplicity of the numerical approach proved to be a path to follow in order to transfer knowledge to engineering practice. Finally, the comparison between numerical and experimental results allowed finding a good agreement between both, fact that ensures the ability of the proposed modeling strategy to deal with real engineering practical problems.

  19. Dynamical Model of Drug Accumulation in Bacteria: Sensitivity Analysis and Experimentally Testable Predictions

    PubMed Central

    Vesselinova, Neda; Wall, Michael E.

    2016-01-01

    We present a dynamical model of drug accumulation in bacteria. The model captures key features in experimental time courses on ofloxacin accumulation: initial uptake; two-phase response; and long-term acclimation. In combination with experimental data, the model provides estimates of import and export rates in each phase, the time of entry into the second phase, and the decrease of internal drug during acclimation. Global sensitivity analysis, local sensitivity analysis, and Bayesian sensitivity analysis of the model provide information about the robustness of these estimates, and about the relative importance of different parameters in determining the features of the accumulation time courses in three different bacterial species: Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa. The results lead to experimentally testable predictions of the effects of membrane permeability, drug efflux and trapping (e.g., by DNA binding) on drug accumulation. A key prediction is that a sudden increase in ofloxacin accumulation in both E. coli and S. aureus is accompanied by a decrease in membrane permeability. PMID:27824914

  20. Confronting model predictions of carbon fluxes with measurements of Amazon forests subjected to experimental drought.

    PubMed

    Powell, Thomas L; Galbraith, David R; Christoffersen, Bradley O; Harper, Anna; Imbuzeiro, Hewlley M A; Rowland, Lucy; Almeida, Samuel; Brando, Paulo M; da Costa, Antonio Carlos Lola; Costa, Marcos Heil; Levine, Naomi M; Malhi, Yadvinder; Saleska, Scott R; Sotta, Eleneide; Williams, Mathew; Meir, Patrick; Moorcroft, Paul R

    2013-10-01

    Considerable uncertainty surrounds the fate of Amazon rainforests in response to climate change. Here, carbon (C) flux predictions of five terrestrial biosphere models (Community Land Model version 3.5 (CLM3.5), Ecosystem Demography model version 2.1 (ED2), Integrated BIosphere Simulator version 2.6.4 (IBIS), Joint UK Land Environment Simulator version 2.1 (JULES) and Simple Biosphere model version 3 (SiB3)) and a hydrodynamic terrestrial ecosystem model (the Soil-Plant-Atmosphere (SPA) model) were evaluated against measurements from two large-scale Amazon drought experiments. Model predictions agreed with the observed C fluxes in the control plots of both experiments, but poorly replicated the responses to the drought treatments. Most notably, with the exception of ED2, the models predicted negligible reductions in aboveground biomass in response to the drought treatments, which was in contrast to an observed c. 20% reduction at both sites. For ED2, the timing of the decline in aboveground biomass was accurate, but the magnitude was too high for one site and too low for the other. Three key findings indicate critical areas for future research and model development. First, the models predicted declines in autotrophic respiration under prolonged drought in contrast to measured increases at one of the sites. Secondly, models lacking a phenological response to drought introduced bias in the sensitivity of canopy productivity and respiration to drought. Thirdly, the phenomenological water-stress functions used by the terrestrial biosphere models to represent the effects of soil moisture on stomatal conductance yielded unrealistic diurnal and seasonal responses to drought.

  1. Adolescents' implicit theories predict desire for vengeance after peer conflicts: correlational and experimental evidence.

    PubMed

    Yeager, David S; Trzesniewski, Kali H; Tirri, Kirsi; Nokelainen, Petri; Dweck, Carol S

    2011-07-01

    Why do some adolescents respond to interpersonal conflicts vengefully, whereas others seek more positive solutions? Three studies investigated the role of implicit theories of personality in predicting violent or vengeful responses to peer conflicts among adolescents in Grades 9 and 10. They showed that a greater belief that traits are fixed (an entity theory) predicted a stronger desire for revenge after a variety of recalled peer conflicts (Study 1) and after a hypothetical conflict that specifically involved bullying (Study 2). Study 3 experimentally induced a belief in the potential for change (an incremental theory), which resulted in a reduced desire to seek revenge. This effect was mediated by changes in bad-person attributions about the perpetrators, feelings of shame and hatred, and the belief that vengeful ideation is an effective emotion-regulation strategy. Together, the findings illuminate the social-cognitive processes underlying reactions to conflict and suggest potential avenues for reducing violent retaliation in adolescents.

  2. Predicted and experimental performance of large-bore high-speed ball and roller bearings

    NASA Technical Reports Server (NTRS)

    Coe, H. H.

    1983-01-01

    The values of inner and outer race temperature, cage speed, and heat transferred to the lubricant or bearing power loss, calculated using the computer programs Shaberth and Cybean, with the corresponding experimental data for the large bore ball and roller bearings were compared. After the development of computer program, it is important that values calculated using such program are compared with actual bearing performance data to assess the programs predictive capability. Several comprehensive computer programs currently in use are capable of predicting rolling bearing operating and performance characteristics. These programs accept input data of bearing internal geometry, bearing material and lubricant properties, and bearing operating conditions. The programs solve several sets of equations that characterize rolling element bearings. The output produced typically consists of rolling element loads and Hertz stresses, operating contact angles, component speed, heat generation, local temperatures, bearing fatigue life, and power loss. Two of these programs, Shaberth and Cybean were developed.

  3. Prediction of asphaltene deposition during production - Model description and experimental details

    SciTech Connect

    Takhar, S.; Ravenscroft, P.D.; Nicoll, D.C.A.

    1995-12-31

    Asphaltene deposition can arise during normal production causing formation damage, precipitation in tubing, difficulties in wireline operations, stuck valves and lost production. Identifying which type of crudes will display this behavior, prior to full production, enables the operator to make remedial plans. A short description of a thermodynamic model to predict the onset parameters (temperature, pressure) will be described along with the essential experimental data required as input for subsequent modelling studies. This will be supported via model validation from real field data from two of BPX`s North Sea fields. A key conclusion of the findings is the ability to predict the deposition of asphaltenes downhole without the need for generating data from expensive single phase downhole samples.

  4. Data analysis and noise prediction for the QF-1B experimental fan stage

    NASA Technical Reports Server (NTRS)

    Bliss, D. B.; Chandiramani, K. L.; Piersol, A. G.

    1976-01-01

    The results of a fan noise data analysis and prediction effort using experimental data obtained from tests on the QF-1B research fan are described. Surface pressure measurements were made with flush mounted sensors installed on selected rotor blades and stator vanes and noise measurements were made by microphones located at the far field. Power spectral density analysis, time history studies, and calculation of coherence functions were made. The emphasis of these studies was on the characteristics of tones in the spectra. The amplitude behavior of spectral tones was found to have a large, often predominant, random component, suggesting that turbulent processes play an important role in the generation of tonal as well as broadband noise. Inputs from the data analysis were used in a prediction method which assumes that acoustic dipoles, produced by unsteady blade and van forces, are the important source of fan noise.

  5. Reduction of SEM noise and extended application to prediction of CD uniformity and its experimental validation

    NASA Astrophysics Data System (ADS)

    Kim, Hoyeon; Hwang, Chan; Oh, Seok-hwan; Yeo, Jeongho; Kim, Young hee

    2011-03-01

    As the design rule of Integrated Circuits(IC) becomes smaller, the precise measurement of Critical Dimension (CD) of features and minimization of deviation in CD measured becomes a vital issue. In this paper, a simple frequency analysis method to extract the noise from SEM images was used to evaluate the contribution of SEM noise in CD Uniformity. Multiple SEM images of simple Line and Space (L/S) patterns were analyzed and a model of frequency profile (Power Spectrum Density (PSD) model) was made using an offline analyzing tool based on Matlab®. From this profile, white noise and 1/f profile were separated. Noises are eliminated to generate a noise reduced PSD profile to make CD results. The contribution of white noise on CD measurement can be assessed using Line Width Roughness (LWR) measurement. Furthermore, CD uniformity can be also predicted from the model. This prediction is based on an assumption that CD uniformity is equal to LWR if the inspection area is extended to infinity and appropriate sampling method is applied. The results showed that the contribution of white noise on LWR can be up to around 70% (in power) without any noise reduction measures (sum line averaging) after imaging in photo resist image. For experimental validation, CD uniformity is predicted from the model for different measurement conditions and compared with real measurement. For a result, CD uniformity prediction (3sigma) from the model shows within 20% in accuracy with real CD uniformity value measured from the photo resist image.

  6. Computational and experimental prediction of dust production in pebble bed reactors, Part II

    SciTech Connect

    Mie Hiruta; Gannon Johnson; Maziar Rostamian; Gabriel P. Potirniche; Abderrafi M. Ougouag; Massimo Bertino; Louis Franzel; Akira Tokuhiro

    2013-10-01

    This paper is the continuation of Part I, which describes the high temperature and high pressure helium environment wear tests of graphite–graphite in frictional contact. In the present work, it has been attempted to simulate a Pebble Bed Reactor core environment as compared to Part I. The experimental apparatus, which is a custom-designed tribometer, is capable of performing wear tests at PBR relevant higher temperatures and pressures under a helium environment. This environment facilitates prediction of wear mass loss of graphite as dust particulates from the pebble bed. The experimental results of high temperature helium environment are used to anticipate the amount of wear mass produced in a pebble bed nuclear reactor.

  7. Experimental quadrotor flight performance using computationally efficient and recursively feasible linear model predictive control

    NASA Astrophysics Data System (ADS)

    Jaffery, Mujtaba H.; Shead, Leo; Forshaw, Jason L.; Lappas, Vaios J.

    2013-12-01

    A new linear model predictive control (MPC) algorithm in a state-space framework is presented based on the fusion of two past MPC control laws: steady-state optimal MPC (SSOMPC) and Laguerre optimal MPC (LOMPC). The new controller, SSLOMPC, is demonstrated to have improved feasibility, tracking performance and computation time than its predecessors. This is verified in both simulation and practical experimentation on a quadrotor unmanned air vehicle in an indoor motion-capture testbed. The performance of the control law is experimentally compared with proportional-integral-derivative (PID) and linear quadratic regulator (LQR) controllers in an unconstrained square manoeuvre. The use of soft control output and hard control input constraints is also examined in single and dual constrained manoeuvres.

  8. Phenotypic plasticity is not affected by experimental evolution in constant, predictable or unpredictable fluctuating thermal environments.

    PubMed

    Manenti, T; Loeschcke, V; Moghadam, N N; Sørensen, J G

    2015-11-01

    The selective past of populations is presumed to affect the levels of phenotypic plasticity. Experimental evolution at constant temperatures is generally expected to lead to a decreased level of plasticity due to presumed costs associated with phenotypic plasticity when not needed. In this study, we investigated the effect of experimental evolution in constant, predictable and unpredictable daily fluctuating temperature regimes on the levels of phenotype plasticity in several life history and stress resistance traits in Drosophila simulans. Contrary to the expectation, evolution in the different regimes did not affect the levels of plasticity in any of the traits investigated even though the populations from the different thermal regimes had evolved different stress resistance and fitness trait means. Although costs associated with phenotypic plasticity are known, our results suggest that the maintenance of phenotypic plasticity might come at low and negligible costs, and thus, the potential of phenotypic plasticity to evolve in populations exposed to different environmental conditions might be limited.

  9. Comparison of predicted and experimental thermal performance of angular-contact ball bearings

    NASA Technical Reports Server (NTRS)

    Parker, R. J.

    1984-01-01

    Predicted bearing heat generation and bearing temperature were verified by experimental data for ball bearings over a range of sizes, shaft speeds, and lubricant flow rates. The computer program Shaberth requires, as input, a factor which describes the air-oil mixture in the bearing cavity for calculation of the ball drag contribution to bearing heat generation. An equation for this lubricant percent volume in the bearing cavity was derived and appears to be valid over the range of test conditions including bearing bore sizes from 35 to 167 mm and shaft speeds from 1.0 to 3.0 million DN.

  10. Photorespiratory Bypasses Lead to Increased Growth in Arabidopsis thaliana: Are Predictions Consistent with Experimental Evidence?

    PubMed Central

    Basler, Georg; Küken, Anika; Fernie, Alisdair R.; Nikoloski, Zoran

    2016-01-01

    Arguably, the biggest challenge of modern plant systems biology lies in predicting the performance of plant species, and crops in particular, upon different intracellular and external perturbations. Recently, an increased growth of Arabidopsis thaliana plants was achieved by introducing two different photorespiratory bypasses via metabolic engineering. Here, we investigate the extent to which these findings match the predictions from constraint-based modeling. To determine the effect of the employed metabolic network model on the predictions, we perform a comparative analysis involving three state-of-the-art metabolic reconstructions of A. thaliana. In addition, we investigate three scenarios with respect to experimental findings on the ratios of the carboxylation and oxygenation reactions of Ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO). We demonstrate that the condition-dependent growth phenotypes of one of the engineered bypasses can be qualitatively reproduced by each reconstruction, particularly upon considering the additional constraints with respect to the ratio of fluxes for the RuBisCO reactions. Moreover, our results lend support for the hypothesis of a reduced photorespiration in the engineered plants, and indicate that specific changes in CO2 exchange as well as in the proxies for co-factor turnover are associated with the predicted growth increase in the engineered plants. We discuss our findings with respect to the structure of the used models, the modeling approaches taken, and the available experimental evidence. Our study sets the ground for investigating other strategies for increase of plant biomass by insertion of synthetic reactions. PMID:27092301

  11. Experimentally calibrated population of models predicts and explains intersubject variability in cardiac cellular electrophysiology

    PubMed Central

    Britton, Oliver J.; Bueno-Orovio, Alfonso; Van Ammel, Karel; Lu, Hua Rong; Towart, Rob; Gallacher, David J.; Rodriguez, Blanca

    2013-01-01

    Cellular and ionic causes of variability in the electrophysiological activity of hearts from individuals of the same species are unknown. However, improved understanding of this variability is key to enable prediction of the response of specific hearts to disease and therapies. Limitations of current mathematical modeling and experimental techniques hamper our ability to provide insight into variability. Here, we describe a methodology to unravel the ionic determinants of intersubject variability exhibited in experimental recordings, based on the construction and calibration of populations of models. We illustrate the methodology through its application to rabbit Purkinje preparations, because of their importance in arrhythmias and safety pharmacology assessment. We consider a set of equations describing the biophysical processes underlying rabbit Purkinje electrophysiology, and we construct a population of over 10,000 models by randomly assigning specific parameter values corresponding to ionic current conductances and kinetics. We calibrate the model population by closely comparing simulation output and experimental recordings at three pacing frequencies. We show that 213 of the 10,000 candidate models are fully consistent with the experimental dataset. Ionic properties in the 213 models cover a wide range of values, including differences up to ±100% in several conductances. Partial correlation analysis shows that particular combinations of ionic properties determine the precise shape, amplitude, and rate dependence of specific action potentials. Finally, we demonstrate that the population of models calibrated using data obtained under physiological conditions quantitatively predicts the action potential duration prolongation caused by exposure to four concentrations of the potassium channel blocker dofetilide. PMID:23690584

  12. Experimental and numerical life prediction of thermally cycled thermal barrier coatings

    NASA Astrophysics Data System (ADS)

    Liu, Y.; Persson, C.; Wigren, J.

    2004-09-01

    This article addresses the predominant degradation modes and life prediction of a plasma-sprayed thermal barrier coating (TBC). The studied TBC system consists of an air-plasma-sprayed bond coat and an air-plasma-sprayed, yttria partially stabilized zirconia top layer on a conventional Hastelloy X substrate. Thermal shock tests of as-sprayed TBC and pre-oxidized TBC specimens were conducted under different burner flame conditions at Volvo Aero Corporation (Trollhättan, Sweden). Finite element models were used to simulate the thermal shock tests. Transient temperature distributions and thermal mismatch stresses in different layers of the coatings during thermal cycling were calculated. The roughness of the interface between the ceramic top coat and the bond coat was modeled through an ideally sinusoidal wavy surface. Bond coat oxidation was simulated through adding an aluminum oxide layer between the ceramic top coat and the bond coat. The calculated stresses indicated that interfacial delamination cracks, initiated in the ceramic top coat at the peak of the asperity of the interface, together with surface cracking, are the main reasons for coating failure. A phenomenological life prediction model for the coating was proposed. This model is accurate within a factor of 3.

  13. 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

  14. Combined Experimental and Computational Approach to Predict the Glass-Water Reaction

    SciTech Connect

    Pierce, Eric M.; Bacon, Diana H.

    2011-10-01

    The use of mineral and glass dissolution rates measured in laboratory experiments to predict the weathering of primary minerals and volcanic and nuclear waste glasses in field studies requires the construction of rate models that accurately describe the weathering process over geologic timescales. Additionally, the need to model the long-term behavior of nuclear waste glass for the purpose of estimating radionuclide release rates requires that rate models be validated with long-term experiments. Several long-term test methods have been developed to accelerate the glass-water reaction [drip test, vapor hydration test, product consistency test B, and pressurized unsaturated flow (PUF)], thereby reducing the duration required to evaluate long-term performance. Currently, the PUF test is the only method that mimics the unsaturated hydraulic properties expected in a subsurface disposal facility and simultaneously monitors the glass-water reaction. PUF tests are being conducted to accelerate the weathering of glass and validate the model parameters being used to predict long-term glass behavior. A one-dimensional reactive chemical transport simulation of glass dissolution and secondary phase formation during a 1.5-year-long PUF experiment was conducted with the Subsurface Transport Over Reactive Multiphases (STORM) code. Results show that parameterization of the computer model by combining direct bench scale laboratory measurements and thermodynamic data provides an integrated approach to predicting glass behavior over the length of the experiment. Over the 1.5-year-long test duration, the rate decreased from 0.2 to 0.01 g/(m2 day) based on B release for low-activity waste glass LAWA44. The observed decrease is approximately two orders of magnitude higher than the decrease observed under static conditions with the SON68 glass (estimated to be a decrease by four orders of magnitude) and suggests that the gel-layer properties are less protective under these dynamic

  15. Combined Experimental and Computational Approach to Predict the Glass-Water Reaction

    SciTech Connect

    Pierce, Eric M; Bacon, Diana

    2011-01-01

    The use of mineral and glass dissolution rates measured in laboratory experiments to predict the weathering of primary minerals and volcanic and nuclear waste glasses in field studies requires the construction of rate models that accurately describe the weathering process over geologic time-scales. Additionally, the need to model the long-term behavior of nuclear waste glass for the purpose of estimating radionuclide release rates requires that rate models are validated with long-term experiments. Several long-term test methods have been developed to accelerate the glass-water reaction [drip test, vapor hydration test, product consistency test-B, and pressurized unsaturated flow (PUF)], thereby reducing the duration required to evaluate long-term performance. Currently, the PUF test is the only method that mimics the unsaturated hydraulic properties expected in a subsurface disposal facility and simultaneously monitors the glass-water reaction. PUF tests are being conducted to accelerate the weathering of glass and validate the model parameters being used to predict long-term glass behavior. A one-dimensional reactive chemical transport simulation of glass dissolution and secondary phase formation during a 1.5-year long PUF experiment was conducted with the subsurface transport over reactive multi-phases code. Results show that parameterization of the computer model by combining direct bench-scale laboratory measurements and thermodynamic data provides an integrated approach to predicting glass behavior over the length of the experiment. Over the 1.5-year long test duration, the rate decreased from 0.2 to 0.01 g/(m2 d) base on B release. The observed decrease is approximately two orders of magnitude higher than the decrease observed under static conditions with the SON68 glass (estimated to be a decrease by 4 orders of magnitude) and suggest the gel-layer properties are less protective under these dynamic conditions.

  16. Experimental and theoretical analysis of a method to predict thermal runaway in Li-ion cells

    NASA Astrophysics Data System (ADS)

    Shah, Krishna; Chalise, Divya; Jain, Ankur

    2016-10-01

    Thermal runaway is a well-known safety concern in Li-ion cells. Methods to predict and prevent thermal runaway are critically needed for enhanced safety and performance. While much work has been done on understanding the kinetics of various heat generation processes during thermal runaway, relatively lesser work exists on understanding how heat removal from the cell influences thermal runaway. Through a unified analysis of heat generation and heat removal, this paper derives and experimentally validates a non-dimensional parameter whose value governs whether or not thermal runaway will occur in a Li-ion cell. This parameter is named the Thermal Runaway Number (TRN), and comprises contributions from thermal transport within and outside the cell, as well as the temperature dependence of heat generation rate. Experimental data using a 26650 thermal test cell are in good agreement with the model, and demonstrate the dependence of thermal runaway on various thermal transport and heat generation parameters. This parameter is used to predict the thermal design space in which the cell will or will not experience thermal runaway. By combining all thermal processes contributing to thermal runaway in a single parameter, this work contributes towards a unified understanding of thermal runaway, and provides the fundamental basis for design tools for safe, high-performance Li-ion batteries.

  17. Assessment of aquatic experimental versus predicted and extrapolated chronic toxicity data of four structural analogues.

    PubMed

    Dom, Nathalie; Knapen, Dries; Blust, Ronny

    2012-01-01

    The present study was developed to assess the chronic toxicity predictions and extrapolations for a set of chlorinated anilines (aniline (AN), 4-chloroaniline (CA), 3,5-dichloroaniline (DCA) and 2,3,4-trichloroaniline (TCA)). Daphnia magna 21 d chronic experimental data was compared to the chronic toxicity predictions made by the US EPA ECOSAR QSAR tools and to acute-to-chronic extrapolations. Additionally, Species Sensitivity Distributions (SSDs) were constructed to assess the chronic toxicity variability among different species and to investigate the acute versus chronic toxicity in a multi-species context. Since chlorinated anilines are structural analogues with a designated polar narcotic mode of action, similar toxicity responses were assumed. However, rather large interchemical and interspecies differences in toxicity were observed. Compared to the other three test compounds, TCA exposure had a significantly larger impact on growth and reproduction of D. magna. Furthermore, this study illustrated that QSARs or a fixed ACR are not able to account for these interchemical and interspecies differences. Consequently, ECOSAR was found to be inadequate to predict the chronic toxicity of the anilines and the use of a fixed ACR (of 10) led to under of certain species. The experimental ACRs determined in D. magna were substantially different among the four aromatic amines (ACR of 32 for AN, 16.9 for CA, 5.7 for DCA and 60.8 for TCA). Furthermore, the SSDs illustrated that Danio rerio was rather insensitive to AN in comparison to another fish species, Phimphales promelas. It was therefore suggested that available toxicity data should be used in an integrative multi-species way, rather than using individual-based toxicity extrapolations. In this way, a relevant overview of the differences in species sensitivity is given, which in turn can serve as the basis for acute to chronic extrapolations.

  18. 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.

  19. Predicting acidification recovery at the Hubbard Brook Experimental Forest, New Hampshire: evaluation of four models.

    PubMed

    Tominaga, Koji; Aherne, Julian; Watmough, Shaun A; Alveteg, Mattias; Cosby, Bernard J; Driscoll, Charles T; Posch, Maximilian; Pourmokhtarian, Afshin

    2010-12-01

    The performance and prediction uncertainty (owing to parameter and structural uncertainties) of four dynamic watershed acidification models (MAGIC, PnET-BGC, SAFE, and VSD) were assessed by systematically applying them to data from the Hubbard Brook Experimental Forest (HBEF), New Hampshire, where long-term records of precipitation and stream chemistry were available. In order to facilitate systematic evaluation, Monte Carlo simulation was used to randomly generate common model input data sets (n = 10,000) from parameter distributions; input data were subsequently translated among models to retain consistency. The model simulations were objectively calibrated against observed data (streamwater: 1963-2004, soil: 1983). The ensemble of calibrated models was used to assess future response of soil and stream chemistry to reduced sulfur deposition at the HBEF. Although both hindcast (1850-1962) and forecast (2005-2100) predictions were qualitatively similar across the four models, the temporal pattern of key indicators of acidification recovery (stream acid neutralizing capacity and soil base saturation) differed substantially. The range in predictions resulted from differences in model structure and their associated posterior parameter distributions. These differences can be accommodated by employing multiple models (ensemble analysis) but have implications for individual model applications.

  20. 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.

  1. Mössbauer Spectroscopy of Iron Carbides: From Prediction to Experimental Confirmation

    PubMed Central

    Liu, Xing-Wu; Zhao, Shu; Meng, Yu; Peng, Qing; Dearden, Albert K.; Huo, Chun-Fang; Yang, Yong; Li, Yong-Wang; Wen, Xiao-Dong

    2016-01-01

    The Mössbauer spectroscopy of iron carbides (α-Fe, γ'-FeC, η-Fe2C, ζ-Fe2C, χ-Fe5C2, h-Fe7C3, θ-Fe3C, o-Fe7C3, γ'-Fe4C, γ''-Fe4C, and α'-Fe16C2) is predicted utilizing the all electron full-potential linearized augmented plane wave (FLAPW) approach across various functionals from LDA to GGA (PBE, PBEsol, and GGA + U) to meta-GGA to hybrid functionals. To validate the predicted MES from different functionals, the single-phase χ-Fe5C2 and θ-Fe3C are synthesized in experiment and their experimental MES under different temperature (from 13 K to 298 K) are determined. The result indicates that the GGA functional (especially, the PBEsol) shows remarkable success on the prediction of Mössbauer spectroscopy of α-Fe, χ-Fe5C2 and θ-Fe3C with delocalized d electrons. From the reliable simulations, we propose a linear relationship between Bhf and μB with a slope of 12.81 T/μB for iron carbide systems and that the proportionality constant may vary from structure to structure. PMID:27189083

  2. 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.

  3. An experimental and computational investigation of electrical resistivity imaging for prediction ahead of tunnel boring machines

    NASA Astrophysics Data System (ADS)

    Schaeffer, Kevin P.

    Tunnel boring machines (TBMs) are routinely used for the excavation of tunnels across a range of ground conditions, from hard rock to soft ground. In complex ground conditions and in urban environments, the TBM susceptible to damage due to uncertainty of what lies ahead of the tunnel face. The research presented here explores the application of electrical resistivity theory for use in the TBM tunneling environment to detect changing conditions ahead of the machine. Electrical resistivity offers a real-time and continuous imaging solution to increase the resolution of information along the tunnel alignment and may even unveil previously unknown geologic or man-made features ahead of the TBM. The studies presented herein, break down the tunneling environment and the electrical system to understand how its fundamental parameters can be isolated and tested, identifying how they influence the ability to predict changes ahead of the tunnel face. A proof-of-concept, scaled experimental model was constructed in order assess the ability of the model to predict a metal pipe (or rod) ahead of face as the TBM excavates through a saturated sand. The model shows that a prediction of up to three tunnel diameters could be achieved, but the unique presence of the pipe (or rod) could not be concluded with certainty. Full scale finite element models were developed in order evaluate the various influences on the ability to detect changing conditions ahead of the face. Results show that TBM/tunnel geometry, TBM type, and electrode geometry can drastically influence prediction ahead of the face by tens of meters. In certain conditions (i.e., small TBM diameter, low cover depth, large material contrasts), changes can be detected over 100 meters in front of the TBM. Various electrode arrays were considered and show that in order to better detect more finite differences (e.g., boulder, lens, pipe), the use of individual cutting tools as electrodes is highly advantageous to increase spatial

  4. Classical Mathematical Models for Description and Prediction of Experimental Tumor Growth

    PubMed Central

    Benzekry, Sébastien; Lamont, Clare; Beheshti, Afshin; Tracz, Amanda; Ebos, John M. L.; Hlatky, Lynn; Hahnfeldt, Philip

    2014-01-01

    Despite internal complexity, tumor growth kinetics follow relatively simple laws that can be expressed as mathematical models. To explore this further, quantitative analysis of the most classical of these were performed. The models were assessed against data from two in vivo experimental systems: an ectopic syngeneic tumor (Lewis lung carcinoma) and an orthotopically xenografted human breast carcinoma. The goals were threefold: 1) to determine a statistical model for description of the measurement error, 2) to establish the descriptive power of each model, using several goodness-of-fit metrics and a study of parametric identifiability, and 3) to assess the models' ability to forecast future tumor growth. The models included in the study comprised the exponential, exponential-linear, power law, Gompertz, logistic, generalized logistic, von Bertalanffy and a model with dynamic carrying capacity. For the breast data, the dynamics were best captured by the Gompertz and exponential-linear models. The latter also exhibited the highest predictive power, with excellent prediction scores (≥80%) extending out as far as 12 days in the future. For the lung data, the Gompertz and power law models provided the most parsimonious and parametrically identifiable description. However, not one of the models was able to achieve a substantial prediction rate (≥70%) beyond the next day data point. In this context, adjunction of a priori information on the parameter distribution led to considerable improvement. For instance, forecast success rates went from 14.9% to 62.7% when using the power law model to predict the full future tumor growth curves, using just three data points. These results not only have important implications for biological theories of tumor growth and the use of mathematical modeling in preclinical anti-cancer drug investigations, but also may assist in defining how mathematical models could serve as potential prognostic tools in the clinic. PMID:25167199

  5. 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.

  6. 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.

  7. Scaling and Predicting the Geotechnical Resistance Provided by Alfalfa in Experimental Studies of Alluvial-Channel Morphology and Planform

    NASA Astrophysics Data System (ADS)

    Bankhead, N.; Simon, A.

    2008-12-01

    were then used in conjunction with the Bank Stability and Toe Erosion Model (BSTEM), and a series of laboratory experiments, to evaluate if the factor of safety (FS) of experimental channels lined with different densities of alfalfa could be predicted. Sand banks ranging in height from 1.25 to 3.75 cm were modeled and tested experimentally for cases with different groundwater heights and flow depths in the channel, and with cohesion due to roots being scaled appropriately using a length reduction factor. Model results showed that for alfalfa stem densities ranging from 0 to 10 stems/cm2, bank FS ranged from 0.60 to 1.87 and from 0.60 to 1.12 for 1.25 cm and 3.75 cm-high banks respectively. Preliminary results of the laboratory experiments have successfully shown that if cohesion due to roots calculated from the RipRoot model is scaled appropriately, the stability of experimental channels lined with alfalfa of different densities can be predicted. By quantifying the geotechnical resistance of banks during such studies, more accurate predictions of the conditions necessary to create meandering versus braided channel planforms, and the feedback between channel planform and vegetation density in both experimental and real-world scenarios may now be possible.

  8. Comparison Between Predicted and Experimentally Measured Flow Fields at the Exit of the SSME HPFTP Impeller

    NASA Technical Reports Server (NTRS)

    Bache, George

    1993-01-01

    Validation of CFD codes is a critical first step in the process of developing CFD design capability. The MSFC Pump Technology Team has recognized the importance of validation and has thus funded several experimental programs designed to obtain CFD quality validation data. The first data set to become available is for the SSME High Pressure Fuel Turbopump Impeller. LDV Data was taken at the impeller inlet (to obtain a reliable inlet boundary condition) and three radial positions at the impeller discharge. Our CFD code, TASCflow, is used within the Propulsion and Commercial Pump industry as a tool for pump design. The objective of this work, therefore, is to further validate TASCflow for application in pump design. TASCflow was used to predict flow at the impeller discharge for flowrates of 80, 100 and 115 percent of design flow. Comparison to data has been made with encouraging results.

  9. Experimental and predicted cavitation performance of an 80.6 deg helical inducer in high temperature water

    NASA Technical Reports Server (NTRS)

    Kovich, G.

    1972-01-01

    The cavitating performance of a stainless steel 80.6 degree flat-plate helical inducer was investigated in water over a range of liquid temperatures and flow coefficients. A semi-empirical prediction method was used to compare predicted values of required net positive suction head in water with experimental values obtained in water. Good agreement was obtained between predicted and experimental data in water. The required net positive suction head in water decreased with increasing temperature and increased with flow coefficient, similar to that observed for a like inducer in liquid hydrogen.

  10. Predictive Framework and Experimental Tests of the Kinetic Isotope Effect at Redox-Active Interfaces

    NASA Astrophysics Data System (ADS)

    Kavner, A.; John, S.; Black, J. R.

    2013-12-01

    Electrochemical reactions provide a compelling framework to study kinetic isotope effects because redox-related processes are important for a wide variety of geological and environmental processes. In the laboratory, electrochemical reaction rates can be electronically controlled and measured in the laboratory using a potentiostat. This enables variation of redox reactions rates independent of changes in chemistry and, and the resulting isotope compositions of reactants and products can be separated and analyzed. In the past years, a series of experimental studies have demonstrated a large, light, and tunable kinetic isotope effect during electrodeposition of metal Fe, Zn, Li, Cu, and Mo from a variety of solutions (e.g. Black et al., 2009, 2010, 2011). A theoretical framework based on Marcus kinetic theory predicts a voltage-dependent kinetic isotope effect (Kavner et al., 2005, 2008), however while this framework was able to predict the tunable nature of the effect, it was not able to simultaneously predict absolute reaction rates and relative isotope rates. Here we present a more complete development of a statistical mechanical framework for simple interfacial redox reactions, which includes isotopic behavior. The framework is able to predict a kinetic isotope effect as a function of temperature and reaction rate, starting with three input parameters: a single reorganization energy which describes the overall kinetics of the electron transfer reaction, and the equilibrium reduced partition function ratios for heavy and light isotopes in the product and reactant phases. We show the framework, elucidate some of the predictions, and show direct comparisons against isotope fractionation data obtained during laboratory and natural environment redox processes. A. Kavner, A. Shahar, F. Bonet, J. Simon and E. Young (2005) Geochim. Cosmochim. Acta, 69(12), 2971-2979. A. Kavner, S. G. John, S. Sass, and E. A. Boyle (2008), Geochim. Cosmochim. Acta, vol 72, pp. 1731

  11. 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

  12. 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

  13. Computational tools for experimental determination and theoretical prediction of protein structure

    SciTech Connect

    O`Donoghue, S.; Rost, B.

    1995-12-31

    This tutorial was one of eight tutorials selected to be presented at the Third International Conference on Intelligent Systems for Molecular Biology which was held in the United Kingdom from July 16 to 19, 1995. The authors intend to review the state of the art in the experimental determination of protein 3D structure (focus on nuclear magnetic resonance), and in the theoretical prediction of protein function and of protein structure in 1D, 2D and 3D from sequence. All the atomic resolution structures determined so far have been derived from either X-ray crystallography (the majority so far) or Nuclear Magnetic Resonance (NMR) Spectroscopy (becoming increasingly more important). The authors briefly describe the physical methods behind both of these techniques; the major computational methods involved will be covered in some detail. They highlight parallels and differences between the methods, and also the current limitations. Special emphasis will be given to techniques which have application to ab initio structure prediction. Large scale sequencing techniques increase the gap between the number of known proteins sequences and that of known protein structures. They describe the scope and principles of methods that contribute successfully to closing that gap. Emphasis will be given on the specification of adequate testing procedures to validate such methods.

  14. Predicted and experimental crystal structures of ethyl-tert-butyl ether.

    PubMed

    Hammer, Sonja M; Alig, Edith; Fink, Lothar; Schmidt, Martin U

    2011-04-01

    Possible crystal structures of ethyl-tert-butyl ether (ETBE) were predicted by global lattice-energy minimizations using the force-field approach. 33 structures were found within an energy range of 2 kJmol(-1) above the global minimum. Low-temperature crystallization experiments were carried out at 80-160 K. The crystal structure was determined from X-ray powder data. ETBE crystallizes in C2/m, Z = 4, with molecules on mirror planes. The ETBE molecule adopts a trans conformation with a (CH(3))(3)C-O-C-C torsion angle of 180°. The experimental structure corresponds with high accuracy to the predicted structure with energy rank 2, which has an energy of 0.54 kJmol(-1) above the global minimum and is the most dense low-energy structure. In some crystallization experiments a second polymorph was observed, but the quality of the powder data did not allow the determination of the crystal structure. Possibilities and limitations are discussed for solving crystal structures from powder diffraction data by real-space methods and lattice-energy minimizations.

  15. Survey of computer programs for prediction of crash response and of its experimental validation

    NASA Technical Reports Server (NTRS)

    Kamat, M. P.

    1976-01-01

    The author seeks to critically assess the potentialities of the mathematical and hybrid simulators which predict post-impact response of transportation vehicles. A strict rigorous numerical analysis of a complex phenomenon like crash may leave a lot to be desired with regard to the fidelity of mathematical simulation. Hybrid simulations on the other hand which exploit experimentally observed features of deformations appear to hold a lot of promise. MARC, ANSYS, NONSAP, DYCAST, ACTION, WHAM II and KRASH are among some of the simulators examined for their capabilities with regard to prediction of post impact response of vehicles. A review of these simulators reveals that much more by way of an analysis capability may be desirable than what is currently available. NASA's crashworthiness testing program in conjunction with similar programs of various other agencies, besides generating a large data base, will be equally useful in the validation of new mathematical concepts of nonlinear analysis and in the successful extension of other techniques in crashworthiness.

  16. Experimental and predicted approaches for biomass gasification with enriched air-steam in a fluidised bed.

    PubMed

    Fu, Qirang; Huang, Yaji; Niu, Miaomiao; Yang, Gaoqiang; Shao, Zhiwei

    2014-10-01

    Thermo-chemical gasification of sawdust refuse-derived fuel was performed on a bench-scale fluidised bed gasifier with enriched air and steam as fluidising and oxidising agents. Dolomite as a natural mineral catalyst was used as bed material to reform tars and hydrocarbons. A series of experiments were carried out under typical operating conditions for gasification, as reported in the article. A modified equilibrium model, based on equilibrium constants, was developed to predict the gasification process. The sensitivity analysis of operating parameters, such as the fluidisation velocity, oxygen percentage of the enriched air and steam to biomass ratios on the produced gas composition, lower heating value, carbon conversion and cold gas efficiency was investigated. The results showed that the predicted syngas composition was in better agreement with the experimental data compared with the original equilibrium model. The higher fluidisation velocity enhanced gas-solid mixing, heat and mass transfers, and carbon fines elutriation, simultaneously. With the increase of oxygen percentage from 21% to 45%, the lower heating value of syngas increased from 5.52 MJ m(-3) to 7.75 MJ m(-3) and cold gas efficiency from 49.09% to 61.39%. The introduction of steam improved gas quality, but a higher steam to biomass ratio could decrease carbon conversion and gasification efficiency owing to a low steam temperature. The optimal value of steam to biomass ratio in this work was 1.0.

  17. Computational prediction and experimental selectivity coefficients for hydroxyzine and cetirizine molecularly imprinted polymer based potentiometric sensors.

    PubMed

    Azimi, Abolfazl; Javanbakht, Mehran

    2014-02-17

    In spite of the increasing usages number of molecularly imprinted polymers (MIPs) in many scientific applications, the theoretical aspects of participating intra molecular forces are not fully understood. This work investigates effects of the electrostatic force, the Mulliken charge and the role of cavity's backbone atoms on the selectivity of MIPs. Moreover, charge distribution, which is a computational parameter, was proposed for the prediction of the selectivity coefficients of MIP-based sensors. In the computational approaches and experimental study, methacrylic acid (MAA) was chosen as the functional monomer and ethylene glycol dimethacrylate (EGDMA) as the cross linker for hydroxyzine and cetirizine imprinted polymers. Ab initio, DFT B3LYP method was carried out on molecular optimization. With regard to results obtained from molecules optimization and hydrogen bonding properties, possible configurations of 1:n (n≤5) template/monomer complexes were designed and optimized. The binding energy for each complex in gas phase was calculated. Depending on the most stable configuration, hydroxyzine and cetirizine imprinted polymer models were designed. The calculations including the porogen were also investigated. The theoretical charge distributions for the template and some potential interfering molecules were calculated. The results showed a correlation between the selectivity coefficients and the theoretical charge distributions. The results surprisingly show that charge distribution based model was able to predict the selectivity coefficients of MIP based potentiometric sensors.

  18. Theoretical Prediction of Experimental Jump and Pull-In Dynamics in a MEMS Sensor

    PubMed Central

    Ruzziconi, Laura; Ramini, Abdallah H.; Younis, Mohammad I.; Lenci, Stefano

    2014-01-01

    The present research study deals with an electrically actuated MEMS device. An experimental investigation is performed, via frequency sweeps in a neighbourhood of the first natural frequency. Resonant behavior is explored, with special attention devoted to jump and pull-in dynamics. A theoretical single degree-of-freedom spring-mass model is derived. Classical numerical simulations are observed to properly predict the main nonlinear features. Nevertheless, some discrepancies arise, which are particularly visible in the resonant branch. They mainly concern the practical range of existence of each attractor and the final outcome after its disappearance. These differences are likely due to disturbances, which are unavoidable in practice, but have not been included in the model. To take disturbances into account, in addition to the classical local investigations, we consider the global dynamics and explore the robustness of the obtained results by performing a dynamical integrity analysis. Our aim is that of developing an applicable confident estimate of the system response. Integrity profiles and integrity charts are built to detect the parameter range where reliability is practically strong and where it becomes weak. Integrity curves exactly follow the experimental data. They inform about the practical range of actuality. We discuss the combined use of integrity charts in the engineering design. Although we refer to a particular case-study, the approach is very general. PMID:25225873

  19. 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

  20. New experimental methodology, setup and LabView program for accurate absolute thermoelectric power and electrical resistivity measurements between 25 and 1600 K: Application to pure copper, platinum, tungsten, and nickel at very high temperatures

    NASA Astrophysics Data System (ADS)

    Abadlia, L.; Gasser, F.; Khalouk, K.; Mayoufi, M.; Gasser, J. G.

    2014-09-01

    In this paper we describe an experimental setup designed to measure simultaneously and very accurately the resistivity and the absolute thermoelectric power, also called absolute thermopower or absolute Seebeck coefficient, of solid and liquid conductors/semiconductors over a wide range of temperatures (room temperature to 1600 K in present work). A careful analysis of the existing experimental data allowed us to extend the absolute thermoelectric power scale of platinum to the range 0-1800 K with two new polynomial expressions. The experimental device is controlled by a LabView program. A detailed description of the accurate dynamic measurement methodology is given in this paper. We measure the absolute thermoelectric power and the electrical resistivity and deduce with a good accuracy the thermal conductivity using the relations between the three electronic transport coefficients, going beyond the classical Wiedemann-Franz law. We use this experimental setup and methodology to give new very accurate results for pure copper, platinum, and nickel especially at very high temperatures. But resistivity and absolute thermopower measurement can be more than an objective in itself. Resistivity characterizes the bulk of a material while absolute thermoelectric power characterizes the material at the point where the electrical contact is established with a couple of metallic elements (forming a thermocouple). In a forthcoming paper we will show that the measurement of resistivity and absolute thermoelectric power characterizes advantageously the (change of) phase, probably as well as DSC (if not better), since the change of phases can be easily followed during several hours/days at constant temperature.

  1. New experimental methodology, setup and LabView program for accurate absolute thermoelectric power and electrical resistivity measurements between 25 and 1600 K: application to pure copper, platinum, tungsten, and nickel at very high temperatures.

    PubMed

    Abadlia, L; Gasser, F; Khalouk, K; Mayoufi, M; Gasser, J G

    2014-09-01

    In this paper we describe an experimental setup designed to measure simultaneously and very accurately the resistivity and the absolute thermoelectric power, also called absolute thermopower or absolute Seebeck coefficient, of solid and liquid conductors/semiconductors over a wide range of temperatures (room temperature to 1600 K in present work). A careful analysis of the existing experimental data allowed us to extend the absolute thermoelectric power scale of platinum to the range 0-1800 K with two new polynomial expressions. The experimental device is controlled by a LabView program. A detailed description of the accurate dynamic measurement methodology is given in this paper. We measure the absolute thermoelectric power and the electrical resistivity and deduce with a good accuracy the thermal conductivity using the relations between the three electronic transport coefficients, going beyond the classical Wiedemann-Franz law. We use this experimental setup and methodology to give new very accurate results for pure copper, platinum, and nickel especially at very high temperatures. But resistivity and absolute thermopower measurement can be more than an objective in itself. Resistivity characterizes the bulk of a material while absolute thermoelectric power characterizes the material at the point where the electrical contact is established with a couple of metallic elements (forming a thermocouple). In a forthcoming paper we will show that the measurement of resistivity and absolute thermoelectric power characterizes advantageously the (change of) phase, probably as well as DSC (if not better), since the change of phases can be easily followed during several hours/days at constant temperature.

  2. New experimental methodology, setup and LabView program for accurate absolute thermoelectric power and electrical resistivity measurements between 25 and 1600 K: Application to pure copper, platinum, tungsten, and nickel at very high temperatures

    SciTech Connect

    Abadlia, L.; Mayoufi, M.; Gasser, F.; Khalouk, K.; Gasser, J. G.

    2014-09-15

    In this paper we describe an experimental setup designed to measure simultaneously and very accurately the resistivity and the absolute thermoelectric power, also called absolute thermopower or absolute Seebeck coefficient, of solid and liquid conductors/semiconductors over a wide range of temperatures (room temperature to 1600 K in present work). A careful analysis of the existing experimental data allowed us to extend the absolute thermoelectric power scale of platinum to the range 0-1800 K with two new polynomial expressions. The experimental device is controlled by a LabView program. A detailed description of the accurate dynamic measurement methodology is given in this paper. We measure the absolute thermoelectric power and the electrical resistivity and deduce with a good accuracy the thermal conductivity using the relations between the three electronic transport coefficients, going beyond the classical Wiedemann-Franz law. We use this experimental setup and methodology to give new very accurate results for pure copper, platinum, and nickel especially at very high temperatures. But resistivity and absolute thermopower measurement can be more than an objective in itself. Resistivity characterizes the bulk of a material while absolute thermoelectric power characterizes the material at the point where the electrical contact is established with a couple of metallic elements (forming a thermocouple). In a forthcoming paper we will show that the measurement of resistivity and absolute thermoelectric power characterizes advantageously the (change of) phase, probably as well as DSC (if not better), since the change of phases can be easily followed during several hours/days at constant temperature.

  3. Experimental and predicted crystal structures of Pigment Red 168 and other dihalogenated anthanthrones.

    PubMed

    Schmidt, Martin U; Paulus, Erich F; Rademacher, Nadine; Day, Graeme M

    2010-10-01

    The crystal structures of 4,10-dibromo-anthanthrone (Pigment Red 168; 4,10-dibromo-dibenzo[def,mno]chrysene-6,12-dione), 4,10-dichloro- and 4,10-diiodo-anthanthrone have been determined by single-crystal X-ray analyses. The dibromo and diiodo derivatives crystallize in P2(1)/c, Z = 2, the dichloro derivative in P1, Z = 1. The molecular structures are almost identical and the unit-cell parameters show some similarities for all three compounds, but the crystal structures are neither isotypic to another nor to the unsubstituted anthanthrone, which crystallizes in P2(1)/c, Z = 8. In order to explain why the four anthanthrone derivatives have four different crystal structures, lattice-energy minimizations were performed using anisotropic atom-atom model potentials as well as using the semi-classical density sums (SCDS-Pixel) approach. The calculations showed the crystal structures of the dichloro and the diiodo derivatives to be the most stable ones for the corresponding compound; whereas for dibromo-anthanthrone the calculations suggest that the dichloro and diiodo structure types should be more stable than the experimentally observed structure. An experimental search for new polymorphs of dibromo-anthanthrone was carried out, but the experiments were hampered by the remarkable insolubility of the compound. A metastable nanocrystalline second polymorph of the dibromo derivative does exist, but it is not isostructural to the dichloro or diiodo compound. In order to determine the crystal structure of this phase, crystal structure predictions were performed in various space groups, using anisotropic atom-atom potentials. For all low-energy structures, X-ray powder patterns were calculated and compared with the experimental diagram, which consisted of a few broad lines only. It turned out that the crystallinity of this phase was not sufficient to determine which of the calculated structures corresponds to the actual structure of this nanocrystalline polymorph.

  4. 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

  5. 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

  6. 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.

  7. 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.

  8. The dynamical integrity concept for interpreting/ predicting experimental behaviour: from macro- to nano-mechanics.

    PubMed

    Lenci, Stefano; Rega, Giuseppe; Ruzziconi, Laura

    2013-06-28

    The dynamical integrity, a new concept proposed by J.M.T. Thompson, and developed by the authors, is used to interpret experimental results. After reviewing the main issues involved in this analysis, including the proposal of a new integrity measure able to capture in an easy way the safe part of basins, attention is dedicated to two experiments, a rotating pendulum and a micro-electro-mechanical system, where the theoretical predictions are not fulfilled. These mechanical systems, the former at the macro-scale and the latter at the micro-scale, permit a comparative analysis of different mechanical and dynamical behaviours. The fact that in both cases the dynamical integrity permits one to justify the difference between experimental and theoretical results, which is the main achievement of this paper, shows the effectiveness of this new approach and suggests its use in practical situations. The men of experiment are like the ant, they only collect and use; the reasoners resemble spiders, who make cobwebs out of their own substance. But the bee takes the middle course: it gathers its material from the flowers of the garden and field, but transforms and digests it by a power of its own. Not unlike this is the true business of philosophy (science); for it neither relies solely or chiefly on the powers of the mind, nor does it take the matter which it gathers from natural history and mechanical experiments and lay up in the memory whole, as it finds it, but lays it up in the understanding altered and digested. Therefore, from a closer and purer league between these two faculties, the experimental and the rational (such as has never been made), much may be hoped. (Francis Bacon 1561-1626) But are we sure of our observational facts? Scientific men are rather fond of saying pontifically that one ought to be quite sure of one's observational facts before embarking on theory. Fortunately those who give this advice do not practice what they preach. Observation and theory get

  9. 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.

  10. 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

  11. 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.

  12. Fluid force predictions and experimental measurements for a magnetically levitated pediatric ventricular assist device.

    PubMed

    Throckmorton, Amy L; Untaroiu, Alexandrina; Lim, D Scott; Wood, Houston G; Allaire, Paul E

    2007-05-01

    The latest generation of artificial blood pumps incorporates the use of magnetic bearings to levitate the rotating component of the pump, the impeller. A magnetic suspension prevents the rotating impeller from contacting the internal surfaces of the pump and reduces regions of stagnant and high shear flow that surround fluid or mechanical bearings. Applying this third-generation technology, the Virginia Artificial Heart Institute has developed a ventricular assist device (VAD) to support infants and children. In consideration of the suspension design, the axial and radial fluid forces exerted on the rotor of the pediatric VAD were estimated using computational fluid dynamics (CFD) such that fluid perturbations would be counterbalanced. In addition, a prototype was built for experimental measurements of the axial fluid forces and estimations of the radial fluid forces during operation using a blood analog mixture. The axial fluid forces for a centered impeller position were found to range from 0.5 +/- 0.01 to 1 +/- 0.02 N in magnitude for 0.5 +/- 0.095 to 3.5 +/- 0.164 Lpm over rotational speeds of 6110 +/- 0.39 to 8030 +/- 0.57% rpm. The CFD predictions for the axial forces deviated from the experimental data by approximately 8.5% with a maximum difference of 18% at higher flow rates. Similarly for the off-centered impeller conditions, the maximum radial fluid force along the y-axis was found to be -0.57 +/- 0.17 N. The maximum cross-coupling force in the x direction was found to be larger with a maximum value of 0.74 +/- 0.22 N. This resulted in a 25-35% overestimate of the radial fluid force as compared to the CFD predictions; this overestimation will lead to a far more robust magnetic suspension design. The axial and radial forces estimated from the computational results are well within a range over which a compact magnetic suspension can compensate for flow perturbations. This study also serves as an effective and novel design methodology for blood pump

  13. Curiosity Predicts Smoking Experimentation Independent of Susceptibility in a US National Sample

    PubMed Central

    Nodora, Jesse; Hartman, Sheri J.; Strong, David R.; Messer, Karen; Vera, Lisa E.; White, Martha M.; Portnoy, David B.; Choiniere, Conrad J.; Vullo, Genevieve C.; Pierce, John P.

    2014-01-01

    Purpose To improve smoking prevention efforts, better methods for identifying at-risk youth are needed. The widely used measure of susceptibility to smoking identifies at-risk adolescents; however, it correctly identifies only about one third of future smokers. Adding curiosity about smoking to this susceptibility index may allow us to identify a greater proportion of future smokers while they are still pre-teens. Methods We use longitudinal data from a recent national study on parenting to prevent problem behaviors. Only oldest children between 10-13 years of age were eligible. Participants were identified by RDD survey and followed for 6 years. All baseline never smokers with at least one follow-up assessment were included (n=878). The association of curiosity about smoking with future smoking behavior was assessed. Then, curiosity was added to form an enhanced susceptibility index and sensitivity, specificity and positive predictive value were calculated. Results Among committed never smokers at baseline, those who were ‘definitely not curious’ were less likely to progress towards smoking than both those who were ‘probably not curious’ (ORadj =1.89; 95% CI=1.03-3.47) or ‘probably/definitely curious’ (ORadj=2.88; 95% CI=1.11-7.45). Incorporating curiosity into the susceptibility index increased the proportion identified as at-risk to smoke from 25.1% to 46.9%., The sensitivity (true positives) for this enhanced susceptibility index for both experimentation and established smoking increased from 37-40% to over 50%., although the positive predictive value did not improve. Conclusion The addition of curiosity significantly improves the identification and classification of which adolescents will experiment with smoking or become established smokers. PMID:25117844

  14. Can personality traits and gender predict the response to morphine? An experimental cold pain study.

    PubMed

    Pud, Dorit; Yarnitsky, David; Sprecher, Elliot; Rogowski, Zeev; Adler, Rivka; Eisenberg, Elon

    2006-02-01

    The aim of the present study was to examine the possible role of personality traits, in accordance with Cloninger's theory, and gender, in the variability of responsiveness to opioids. Specifically, it was intended to test whether or not the three personality dimensions - harm avoidance (HA), reward dependence (RD) and novelty seeking (NS) - as suggested by Cloninger, can predict inter-personal differences in responsiveness to morphine after exposure to experimental cold pain. Thirty-four healthy volunteers (15 females, 19 males) were given the cold pressor test (CPT). Pain threshold, tolerance, and magnitude (VAS) were measured before and after (six measures, 30 min apart) the administration of either 0.5 mg/kg oral morphine sulphate (n=21) or 0.33 mg/kg oral active placebo (diphenhydramine) (n=13) in a randomized, double blind design. Assessment of the three personality traits, according to Cloninger's Tridimensional Personality Questionnaire, was performed before the CPT. A high HA score (but not RD, NS, or baseline values of the three pain parameters) predicted a significantly larger pain relief following the administration of morphine sulphate (but not of the placebo). Women exhibited a larger response in response to both treatments, as indicated by a significantly increased threshold and tolerance following morphine sulphate as well as significantly increased tolerance and decreased magnitude following placebo administration. The present study confirms the existence of individual differences in response to analgesic treatment. It suggests that high HA personality trait is associated with better responsiveness to morphine treatment, and that females respond better than men to both morphine and placebo.

  15. Introduction: Assessment of aerothermodynamic flight prediction tools through ground and flight experimentation

    NASA Astrophysics Data System (ADS)

    Schmisseur, John D.; Erbland, Peter

    2012-01-01

    This article provides an introduction and overview to the efforts of NATO Research and Technology Organization Task Group AVT-136, Assessment of Aerothermodynamic Flight Prediction Tools through Ground and Flight Experimentation. During the period of 2006-2010, AVT-136 coordinated international contributions to assess the state-of-the-art and research challenges for the prediction of critical aerothermodynamic flight phenomena based on the extrapolation of ground test and numerical simulation. To achieve this goal, efforts were organized around six scientific topic areas: (1) Noses and leading edges, (2) Shock Interactions and Control Surfaces, (3) Shock Layers and Radiation, (4) Boundary Layer Transition, (5) Gas-Surface Interactions, and (6) Base and Afterbody Flows. A key component of the AVT-136 strategy was comparison of state-of-the-art numerical simulations with data to be acquired from planned flight research programs. Although it was recognized from the onset of AVT-136 activities that reliance on flight research data yet to be collected posed a significant risk, the group concluded the substantial benefit to be derived from comparison of computational simulations with flight data warranted pursuit of such a program of work. Unfortunately, program delays and failures in the flight programs contributing to the AVT-136 effort prevented timely access to flight research data. Despite this setback, most of the scientific topic areas developed by the Task Group made significant progress in the assessment of current capabilities. Additionally, the activities of AVT-136 generated substantial interest within the international scientific research community and the work of the Task Group was prominently featured in a total of six invited sessions in European and American technical conferences. In addition to this overview, reviews of the state-of-the-art and research challenges identified by the six research thrusts of AVT-136 are also included in this special

  16. HSP70 mediates survival in apoptotic cells—Boolean network prediction and experimental validation

    PubMed Central

    Vasaikar, Suhas V.; Ghosh, Sourish; Narain, Priyam; Basu, Anirban; Gomes, James

    2015-01-01

    Neuronal stress or injury results in the activation of proteins, which regulate the balance between survival and apoptosis. However, the complex mechanism of cell signaling involving cell death and survival, activated in response to cellular stress is not yet completely understood. To bring more clarity about these mechanisms, a Boolean network was constructed that represented the apoptotic pathway in neuronal cells. FasL and neurotrophic growth factor (NGF) were considered as inputs in the absence and presence of heat shock proteins known to shift the balance toward survival by rescuing pro-apoptotic cells. The probabilities of survival, DNA repair and apoptosis as cellular fates, in the presence of either the growth factor or FasL, revealed a survival bias encoded in the network. Boolean predictions tested by measuring the mRNA level of caspase-3, caspase-8, and BAX in neuronal Neuro2a (N2a) cell line with NGF and FasL as external input, showed positive correlation with the observed experimental results for survival and apoptotic states. It was observed that HSP70 contributed more toward rescuing cells from apoptosis in comparison to HSP27, HSP40, and HSP90. Overexpression of HSP70 in N2a transfected cells showed reversal of cellular fate from FasL-induced apoptosis to survival. Further, the pro-survival role of the proteins BCL2, IAP, cFLIP, and NFκB determined by vertex perturbation analysis was experimentally validated through protein inhibition experiments using EM20-25, Embelin and Wedelolactone, which resulted in 1.27-, 1.26-, and 1.46-fold increase in apoptosis of N2a cells. The existence of a one-to-one correspondence between cellular fates and attractor states shows that Boolean networks may be employed with confidence in qualitative analytical studies of biological networks. PMID:26379495

  17. HSP70 mediates survival in apoptotic cells-Boolean network prediction and experimental validation.

    PubMed

    Vasaikar, Suhas V; Ghosh, Sourish; Narain, Priyam; Basu, Anirban; Gomes, James

    2015-01-01

    Neuronal stress or injury results in the activation of proteins, which regulate the balance between survival and apoptosis. However, the complex mechanism of cell signaling involving cell death and survival, activated in response to cellular stress is not yet completely understood. To bring more clarity about these mechanisms, a Boolean network was constructed that represented the apoptotic pathway in neuronal cells. FasL and neurotrophic growth factor (NGF) were considered as inputs in the absence and presence of heat shock proteins known to shift the balance toward survival by rescuing pro-apoptotic cells. The probabilities of survival, DNA repair and apoptosis as cellular fates, in the presence of either the growth factor or FasL, revealed a survival bias encoded in the network. Boolean predictions tested by measuring the mRNA level of caspase-3, caspase-8, and BAX in neuronal Neuro2a (N2a) cell line with NGF and FasL as external input, showed positive correlation with the observed experimental results for survival and apoptotic states. It was observed that HSP70 contributed more toward rescuing cells from apoptosis in comparison to HSP27, HSP40, and HSP90. Overexpression of HSP70 in N2a transfected cells showed reversal of cellular fate from FasL-induced apoptosis to survival. Further, the pro-survival role of the proteins BCL2, IAP, cFLIP, and NFκB determined by vertex perturbation analysis was experimentally validated through protein inhibition experiments using EM20-25, Embelin and Wedelolactone, which resulted in 1.27-, 1.26-, and 1.46-fold increase in apoptosis of N2a cells. The existence of a one-to-one correspondence between cellular fates and attractor states shows that Boolean networks may be employed with confidence in qualitative analytical studies of biological networks.

  18. Structural disorder within Henipavirus nucleoprotein and phosphoprotein: from predictions to experimental assessment.

    PubMed

    Habchi, Johnny; Mamelli, Laurent; Darbon, Hervé; Longhi, Sonia

    2010-07-21

    Henipaviruses are newly emerged viruses within the Paramyxoviridae family. Their negative-strand RNA genome is packaged by the nucleoprotein (N) within alpha-helical nucleocapsid that recruits the polymerase complex made of the L protein and the phosphoprotein (P). To date structural data on Henipaviruses are scarce, and their N and P proteins have never been characterized so far. Using both computational and experimental approaches we herein show that Henipaviruses N and P proteins possess large intrinsically disordered regions. By combining several disorder prediction methods, we show that the N-terminal domain of P (PNT) and the C-terminal domain of N (NTAIL) are both mostly disordered, although they contain short order-prone segments. We then report the cloning, the bacterial expression, purification and characterization of Henipavirus PNT and NTAIL domains. By combining gel filtration, dynamic light scattering, circular dichroism and nuclear magnetic resonance, we show that both NTAIL and PNT belong to the premolten globule sub-family within the class of intrinsically disordered proteins. This study is the first reported experimental characterization of Henipavirus P and N proteins. The evidence that their respective N-terminal and C-terminal domains are highly disordered under native conditions is expected to be invaluable for future structural studies by helping to delineate N and P protein domains amenable to crystallization. In addition, following previous hints establishing a relationship between structural disorder and protein interactivity, the present results suggest that Henipavirus PNT and NTAIL domains could be involved in manifold protein-protein interactions.

  19. Structural Disorder within Henipavirus Nucleoprotein and Phosphoprotein: From Predictions to Experimental Assessment

    PubMed Central

    Darbon, Hervé; Longhi, Sonia

    2010-01-01

    Henipaviruses are newly emerged viruses within the Paramyxoviridae family. Their negative-strand RNA genome is packaged by the nucleoprotein (N) within α-helical nucleocapsid that recruits the polymerase complex made of the L protein and the phosphoprotein (P). To date structural data on Henipaviruses are scarce, and their N and P proteins have never been characterized so far. Using both computational and experimental approaches we herein show that Henipaviruses N and P proteins possess large intrinsically disordered regions. By combining several disorder prediction methods, we show that the N-terminal domain of P (PNT) and the C-terminal domain of N (NTAIL) are both mostly disordered, although they contain short order-prone segments. We then report the cloning, the bacterial expression, purification and characterization of Henipavirus PNT and NTAIL domains. By combining gel filtration, dynamic light scattering, circular dichroism and nuclear magnetic resonance, we show that both NTAIL and PNT belong to the premolten globule sub-family within the class of intrinsically disordered proteins. This study is the first reported experimental characterization of Henipavirus P and N proteins. The evidence that their respective N-terminal and C-terminal domains are highly disordered under native conditions is expected to be invaluable for future structural studies by helping to delineate N and P protein domains amenable to crystallization. In addition, following previous hints establishing a relationship between structural disorder and protein interactivity, the present results suggest that Henipavirus PNT and NTAIL domains could be involved in manifold protein-protein interactions. PMID:20657787

  20. 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

  1. An Update on Experimental Climate Prediction and Analysis Products Being Developed at NASA's Global Modeling and Assimilation Office

    NASA Technical Reports Server (NTRS)

    Schubert, Siegfried

    2011-01-01

    The Global Modeling and Assimilation Office at NASA's Goddard Space Flight Center is developing a number of experimental prediction and analysis products suitable for research and applications. The prediction products include a large suite of subseasonal and seasonal hindcasts and forecasts (as a contribution to the US National MME), a suite of decadal (10-year) hindcasts (as a contribution to the IPCC decadal prediction project), and a series of large ensemble and high resolution simulations of selected extreme events, including the 2010 Russian and 2011 US heat waves. The analysis products include an experimental atlas of climate (in particular drought) and weather extremes. This talk will provide an update on those activities, and discuss recent efforts by WCRP to leverage off these and similar efforts at other institutions throughout the world to develop an experimental global drought early warning system.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Theoretical and experimental study of a new method for prediction of profile drag of airfoil sections

    NASA Technical Reports Server (NTRS)

    Goradia, S. H.; Lilley, D. E.

    1975-01-01

    Theoretical and experimental studies are described which were conducted for the purpose of developing a new generalized method for the prediction of profile drag of single component airfoil sections with sharp trailing edges. This method aims at solution for the flow in the wake from the airfoil trailing edge to the large distance in the downstream direction; the profile drag of the given airfoil section can then easily be obtained from the momentum balance once the shape of velocity profile at a large distance from the airfoil trailing edge has been computed. Computer program subroutines have been developed for the computation of the profile drag and flow in the airfoil wake on CDC6600 computer. The required inputs to the computer program consist of free stream conditions and the characteristics of the boundary layers at the airfoil trailing edge or at the point of incipient separation in the neighborhood of airfoil trailing edge. The method described is quite generalized and hence can be extended to the solution of the profile drag for multi-component airfoil sections.

  9. 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.

  10. Experimental study of tyre/road contact forces in rolling conditions for noise prediction

    NASA Astrophysics Data System (ADS)

    Cesbron, Julien; Anfosso-Lédée, Fabienne; Duhamel, Denis; Ping Yin, Hai; Le Houédec, Donatien

    2009-02-01

    This paper deals with the experimental study of dynamical tyre/road contact for noise prediction. In situ measurements of contact forces and close proximity noise levels were carried out for a slick tyre rolling on six different road surfaces between 30 and 50 km/h. Additional texture profiles of the tested surfaces were taken on the wheel track. Normal contact stresses were measured at a sampling frequency of 10752 Hz using a line of pressure sensitive cells placed both along and perpendicular to the rolling direction. The contact areas obtained during rolling were smaller than in static conditions. This is mainly explained by the dynamical properties of tyre compounds, like the viscoelastic behaviour of the rubber. Additionally the root-mean-square of the resultant contact forces at various speeds was in the same order for a given road surface, while their spectra were quite different. This is certainly due to a spectral influence of bending waves propagating in the tyre during rolling, especially when the wavelength is small in comparison with the size of the contact patch. Finally, the levels of contact forces and close proximity noise measured at 30 km/h were correlated. Additional correlations with texture levels were performed. The results show that the macro-texture generates contact forces linearly around 800 Hz and consequently noise levels between 500 and 1000 Hz via the vibrations transmitted to the tyre.

  11. 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.

  12. 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.

  13. Predicting the effects of magnesium oxide nanoparticles and temperature on the thermal conductivity of water using artificial neural network and experimental data

    NASA Astrophysics Data System (ADS)

    Afrand, Masoud; Hemmat Esfe, Mohammad; Abedini, Ehsan; Teimouri, Hamid

    2017-03-01

    The current paper first presents an empirical correlation based on experimental results for estimating thermal conductivity enhancement of MgO-water nanofluid using curve fitting method. Then, artificial neural networks (ANNs) with various numbers of neurons have been assessed by considering temperature and MgO volume fraction as the inputs variables and thermal conductivity enhancement as the output variable to select the most appropriate and optimized network. Results indicated that the network with 7 neurons had minimum error. Eventually, the output of artificial neural network was compared with the results of the proposed empirical correlation and those of the experiments. Comparisons revealed that ANN modeling was more accurate than curve-fitting method in the predicting the thermal conductivity enhancement of the nanofluid.

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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).

  20. Flight effects on exhaust noise for turbojet and turbofan engines: Comparison of experimental data with prediction

    NASA Technical Reports Server (NTRS)

    Stone, J. R.

    1976-01-01

    It was demonstrated that static and in flight jet engine exhaust noise can be predicted with reasonable accuracy when the multiple source nature of the problem is taken into account. Jet mixing noise was predicted from the interim prediction method. Provisional methods of estimating internally generated noise and shock noise flight effects were used, based partly on existing prediction methods and partly on recent reported engine data.

  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. Absorbed Dose Determination Using Experimental and Analytical Predictions of X-Ray Spectra

    NASA Technical Reports Server (NTRS)

    Edwards, D. L.; Carruth, Ralph (Technical Monitor)

    2001-01-01

    Electron beam welding in a vacuum is a technology that NASA is investigating as a joining technique for manufacture of space structures. This investigation characterizes the x-ray environment due to operation of an in-vacuum electron beam welding tool and provides recommendations for adequate shielding for astronauts performing the in-vacuum electron beam welding. NASA, in a joint venture with the Russian Space Agency, was scheduled to perform a series of welding in space experiments on board the U.S. Space Shuttle. This series of experiments was named the international space welding experiment (ISWE). The hardware associated with the ISWE was leased to NASA by the Paton Welding Institute (PWI) in Ukraine for ground-based welding experiments in preparation for flight. Two ground tests were scheduled, using the ISWE electron beam welding tool, to characterize the radiation exposure to an astronaut during the operation of the ISWE. These radiation exposure tests used thermoluminescence dosimeters (TLD's) shielded with material currently used by astronauts during extravehicular activities to measure the radiation dose. The TLD's were exposed to x-ray radiation generated by operation of the ISWE in-vacuum electron beam welding tool. This investigation was the first known application of TLD's to measure absorbed dose from x rays of energy less than 10 keV. The ISWE hardware was returned to Ukraine before the issue of adequate shielding for the astronauts was completely verified. Therefore, alternate experimental and analytical methods were developed to measure and predict the x-ray spectral and intensity distribution generated by ISWE electron beam impact with metal. These x-ray spectra were normalized to an equivalent ISWE exposure, then used to calculate the absorbed radiation dose to astronauts. These absorbed dose values were compared to TLD measurements obtained during actual operation of the ISWE in-vacuum electron beam welding tool. The calculated absorbed dose

  3. Accurately measuring dynamic coefficient of friction in ultraform finishing

    NASA Astrophysics Data System (ADS)

    Briggs, Dennis; Echaves, Samantha; Pidgeon, Brendan; Travis, Nathan; Ellis, Jonathan D.

    2013-09-01

    UltraForm Finishing (UFF) is a deterministic sub-aperture computer numerically controlled grinding and polishing platform designed by OptiPro Systems. UFF is used to grind and polish a variety of optics from simple spherical to fully freeform, and numerous materials from glasses to optical ceramics. The UFF system consists of an abrasive belt around a compliant wheel that rotates and contacts the part to remove material. This work aims to accurately measure the dynamic coefficient of friction (μ), how it changes as a function of belt wear, and how this ultimately affects material removal rates. The coefficient of friction has been examined in terms of contact mechanics and Preston's equation to determine accurate material removal rates. By accurately predicting changes in μ, polishing iterations can be more accurately predicted, reducing the total number of iterations required to meet specifications. We have established an experimental apparatus that can accurately measure μ by measuring triaxial forces during translating loading conditions or while manufacturing the removal spots used to calculate material removal rates. Using this system, we will demonstrate μ measurements for UFF belts during different states of their lifecycle and assess the material removal function from spot diagrams as a function of wear. Ultimately, we will use this system for qualifying belt-wheel-material combinations to develop a spot-morphing model to better predict instantaneous material removal functions.

  4. Development of Prediction Model and Experimental Validation in Predicting the Curcumin Content of Turmeric (Curcuma longa L.).

    PubMed

    Akbar, Abdul; Kuanar, Ananya; Joshi, Raj K; Sandeep, I S; Mohanty, Sujata; Naik, Pradeep K; Mishra, Antaryami; Nayak, Sanghamitra

    2016-01-01

    The drug yielding potential of turmeric (Curcuma longa L.) is largely due to the presence of phyto-constituent 'curcumin.' Curcumin has been found to possess a myriad of therapeutic activities ranging from anti-inflammatory to neuroprotective. Lack of requisite high curcumin containing genotypes and variation in the curcumin content of turmeric at different agro climatic regions are the major stumbling blocks in commercial production of turmeric. Curcumin content of turmeric is greatly influenced by environmental factors. Hence, a prediction model based on artificial neural network (ANN) was developed to map genome environment interaction basing on curcumin content, soli and climatic factors from different agroclimatic regions for prediction of maximum curcumin content at various sites to facilitate the selection of suitable region for commercial cultivation of turmeric. The ANN model was developed and tested using a data set of 119 generated by collecting samples from 8 different agroclimatic regions of Odisha. The curcumin content from these samples was measured that varied from 7.2% to 0.4%. The ANN model was trained with 11 parameters of soil and climatic factors as input and curcumin content as output. The results showed that feed-forward ANN model with 8 nodes (MLFN-8) was the most suitable one with R(2) value of 0.91. Sensitivity analysis revealed that minimum relative humidity, altitude, soil nitrogen content and soil pH had greater effect on curcumin content. This ANN model has shown proven efficiency for predicting and optimizing the curcumin content at a specific site.

  5. Development of Prediction Model and Experimental Validation in Predicting the Curcumin Content of Turmeric (Curcuma longa L.)

    PubMed Central

    Akbar, Abdul; Kuanar, Ananya; Joshi, Raj K.; Sandeep, I. S.; Mohanty, Sujata; Naik, Pradeep K.; Mishra, Antaryami; Nayak, Sanghamitra

    2016-01-01

    The drug yielding potential of turmeric (Curcuma longa L.) is largely due to the presence of phyto-constituent ‘curcumin.’ Curcumin has been found to possess a myriad of therapeutic activities ranging from anti-inflammatory to neuroprotective. Lack of requisite high curcumin containing genotypes and variation in the curcumin content of turmeric at different agro climatic regions are the major stumbling blocks in commercial production of turmeric. Curcumin content of turmeric is greatly influenced by environmental factors. Hence, a prediction model based on artificial neural network (ANN) was developed to map genome environment interaction basing on curcumin content, soli and climatic factors from different agroclimatic regions for prediction of maximum curcumin content at various sites to facilitate the selection of suitable region for commercial cultivation of turmeric. The ANN model was developed and tested using a data set of 119 generated by collecting samples from 8 different agroclimatic regions of Odisha. The curcumin content from these samples was measured that varied from 7.2% to 0.4%. The ANN model was trained with 11 parameters of soil and climatic factors as input and curcumin content as output. The results showed that feed-forward ANN model with 8 nodes (MLFN-8) was the most suitable one with R2 value of 0.91. Sensitivity analysis revealed that minimum relative humidity, altitude, soil nitrogen content and soil pH had greater effect on curcumin content. This ANN model has shown proven efficiency for predicting and optimizing the curcumin content at a specific site. PMID:27766103

  6. Central Functions of the Lumenal and Peripheral Thylakoid Proteome of Arabidopsis Determined by Experimentation and Genome-Wide Prediction

    PubMed Central

    Peltier, Jean-Benoît; Emanuelsson, Olof; Kalume, Dário E.; Ytterberg, Jimmy; Friso, Giulia; Rudella, Andrea; Liberles, David A.; Söderberg, Linda; Roepstorff, Peter; von Heijne, Gunnar; van Wijk, Klaas J.

    2002-01-01

    Experimental proteome analysis was combined with a genome-wide prediction screen to characterize the protein content of the thylakoid lumen of Arabidopsis chloroplasts. Soluble thylakoid proteins were separated by two-dimensional electrophoresis and identified by mass spectrometry. The identities of 81 proteins were established, and N termini were sequenced to validate localization prediction. Gene annotation of the identified proteins was corrected by experimental data, and an interesting case of alternative splicing was discovered. Expression of a surprising number of paralogs was detected. Expression of five isomerases of different classes suggests strong (un)folding activity in the thylakoid lumen. These isomerases possibly are connected to a network of peripheral and lumenal proteins involved in antioxidative response, including peroxiredoxins, m-type thioredoxins, and a lumenal ascorbate peroxidase. Characteristics of the experimentally identified lumenal proteins and their orthologs were used for a genome-wide prediction of the lumenal proteome. Lumenal proteins with a typical twin-arginine translocation motif were predicted with good accuracy and sensitivity and included additional isomerases and proteases. Thus, prime functions of the lumenal proteome include assistance in the folding and proteolysis of thylakoid proteins as well as protection against oxidative stress. Many of the predicted lumenal proteins must be present at concentrations at least 10,000-fold lower than proteins of the photosynthetic apparatus. PMID:11826309

  7. Predicting hydration Gibbs energies of alkyl-aromatics using molecular simulation: a comparison of current force fields and the development of a new parameter set for accurate solvation data.

    PubMed

    Garrido, Nuno M; Jorge, Miguel; Queimada, António J; Gomes, José R B; Economou, Ioannis G; Macedo, Eugénia A

    2011-10-14

    The Gibbs energy of hydration is an important quantity to understand the molecular behavior in aqueous systems at constant temperature and pressure. In this work we review the performance of some popular force fields, namely TraPPE, OPLS-AA and Gromos, in reproducing the experimental Gibbs energies of hydration of several alkyl-aromatic compounds--benzene, mono-, di- and tri-substituted alkylbenzenes--using molecular simulation techniques. In the second part of the paper, we report a new model that is able to improve such hydration energy predictions, based on Lennard Jones parameters from the recent TraPPE-EH force field and atomic partial charges obtained from natural population analysis of density functional theory calculations. We apply a scaling factor determined by fitting the experimental hydration energy of only two solutes, and then present a simple rule to generate atomic partial charges for different substituted alkyl-aromatics. This rule has the added advantages of eliminating the unnecessary assumption of fixed charge on every substituted carbon atom and providing a simple guideline for extrapolating the charge assignment to any multi-substituted alkyl-aromatic molecule. The point charges derived here yield excellent predictions of experimental Gibbs energies of hydration, with an overall absolute average deviation of less than 0.6 kJ mol(-1). This new parameter set can also give good predictive performance for other thermodynamic properties and liquid structural information.

  8. 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.

  9. Volumetric study of the mixtures n-hexane + isomeric chlorobutane: experimental characterization and volume translated Peng-Robinson predictions.

    PubMed

    Guerrero, Hernando; Cea, Pilar; Gascón, Ignacio; Royo, Félix M; Lafuente, Carlos

    2013-09-05

    The pρTx behavior of the binary mixtures n-hexane + isomeric chlorobutane has been studied over the whole composition range at temperatures between 283.15 and 323.15 K and pressures from 0.1 to 65.0 MPa. Experimental densities have been used to obtain different excess properties: excess molar volume, excess isobaric expansibility, excess isothermal compressibility, and excess internal pressure. These excess properties have been analyzed in terms of molecular interactions and structural effects. Finally, experimental densities of the binary mixtures have been compared with the predictions of the volume translated Peng-Robinson (VTPR) model. The overall average deviation between experimental and calculated densities is 0.00427 g·cm(-3), which can be considered reasonably good predictions.

  10. Prediction Markets: A Review with an Experimentally Based Recommendation for Navy Force-shaping Application

    DTIC Science & Technology

    2009-12-01

    as the success of new products, future profitability, or mergers / acquisitions within their industry. One previously noted example is that of Hewlett...Private firms are using prediction markets to help forecast key events, such as the success of new products, future profitability, or mergers ... acquisitions within their industry. Prediction markets also have been popular as an alternative to polls or surveys. The growing popularity of prediction

  11. 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

  12. 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.

  13. Predicting the process of extinction in experimental microcosms and accounting for interspecific interactions in single-species time series

    PubMed Central

    Ferguson, Jake M; Ponciano, José M

    2014-01-01

    Predicting population extinction risk is a fundamental application of ecological theory to the practice of conservation biology. Here, we compared the prediction performance of a wide array of stochastic, population dynamics models against direct observations of the extinction process from an extensive experimental data set. By varying a series of biological and statistical assumptions in the proposed models, we were able to identify the assumptions that affected predictions about population extinction. We also show how certain autocorrelation structures can emerge due to interspecific interactions, and that accounting for the stochastic effect of these interactions can improve predictions of the extinction process. We conclude that it is possible to account for the stochastic effects of community interactions on extinction when using single-species time series. PMID:24304946

  14. 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.

  15. Predicting gaseous reaction rates of short chain chlorinated paraffins with ·OH: overcoming the difficulty in experimental determination.

    PubMed

    Li, Chao; Xie, Hong-Bin; Chen, Jingwen; Yang, Xianhai; Zhang, Yifei; Qiao, Xianliang

    2014-12-02

    Short chain chlorinated paraffins (SCCPs) are under evaluation for inclusion in the Stockholm Convention on persistent organic pollutants. However, information on their reaction rate constants with gaseous ·OH (kOH) is unavailable, limiting the evaluation of their persistence in the atmosphere. Experimental determination of kOH is confined by the unavailability of authentic chemical standards for some SCCP congeners. In this study, we evaluated and selected density functional theory (DFT) methods to predict kOH of SCCPs, by comparing the experimental kOH values of six polychlorinated alkanes (PCAs) with those calculated by the different theoretical methods. We found that the M06-2X/6-311+G(3df,2pd)//B3LYP/6-311 +G(d,p) method is time-effective and can be used to predict kOH of PCAs. Moreover, based on the calculated kOH of nine SCCPs and available experimental kOH values of 22 PCAs with low carbon chain, a quantitative structure-activity relationship (QSAR) model was developed. The molecular structural characteristics determining the ·OH reaction rate were discussed. logkOH was found to negatively correlate with the percentage of chlorine substitutions (Cl%). The DFT calculation method and the QSAR model are important alternatives to the conventional experimental determination of kOH for SCCPs, and are prospective in predicting their persistence in the atmosphere.

  16. Virtual Diagnostics Interface: Real Time Comparison of Experimental Data and CFD Predictions for a NASA Ares I-Like Vehicle

    NASA Technical Reports Server (NTRS)

    Schwartz, Richard J.; Fleming, Gary A.

    2007-01-01

    Virtual Diagnostics Interface technology, or ViDI, is a suite of techniques utilizing image processing, data handling and three-dimensional computer graphics. These techniques aid in the design, implementation, and analysis of complex aerospace experiments. LiveView3D is a software application component of ViDI used to display experimental wind tunnel data in real-time within an interactive, three-dimensional virtual environment. The LiveView3D software application was under development at NASA Langley Research Center (LaRC) for nearly three years. LiveView3D recently was upgraded to perform real-time (as well as post-test) comparisons of experimental data with pre-computed Computational Fluid Dynamics (CFD) predictions. This capability was utilized to compare experimental measurements with CFD predictions of the surface pressure distribution of the NASA Ares I Crew Launch Vehicle (CLV) - like vehicle when tested in the NASA LaRC Unitary Plan Wind Tunnel (UPWT) in December 2006 - January 2007 timeframe. The wind tunnel tests were conducted to develop a database of experimentally-measured aerodynamic performance of the CLV-like configuration for validation of CFD predictive codes.

  17. Integrated computational prediction and experimental validation identifies promiscuous T cell epitopes in the proteome of Mycobacterium bovis

    PubMed Central

    Farrell, Damien; Jones, Gareth; Pirson, Christopher; Malone, Kerri; Rue-Albrecht, Kevin; Chubb, Anthony J.; Vordermeier, Martin

    2016-01-01

    The discovery of novel antigens is an essential requirement in devising new diagnostics or vaccines for use in control programmes against human tuberculosis (TB) and bovine tuberculosis (bTB). Identification of potential epitopes recognised by CD4+ T cells requires prediction of peptide binding to MHC class-II, an obligatory prerequisite for T cell recognition. To comprehensively prioritise potential MHC-II-binding epitopes from Mycobacterium bovis, the agent of bTB and zoonotic TB in humans, we integrated three binding prediction methods with the M. bovisproteome using a subset of human HLA alleles to approximate the binding of epitope-containing peptides to the bovine MHC class II molecule BoLA-DRB3. Two parallel strategies were then applied to filter the resulting set of binders: identification of the top-scoring binders or clusters of binders. Our approach was tested experimentally by assessing the capacity of predicted promiscuous peptides to drive interferon-γ secretion from T cells of M. bovis infected cattle. Thus, 376 20-mer peptides, were synthesised (270 predicted epitopes, 94 random peptides with low predictive scores and 12 positive controls of known epitopes). The results of this validation demonstrated significant enrichment (>24 %) of promiscuously recognised peptides predicted in our selection strategies, compared with randomly selected peptides with low prediction scores. Our strategy offers a general approach to the identification of promiscuous epitopes tailored to target populations where there is limited knowledge of MHC allelic diversity. PMID:28348866

  18. Predicting the sensitivity of the beryllium/scintillator layer neutron detector using Monte Carlo and experimental response functions

    SciTech Connect

    Styron, J. D. Cooper, G. W.; Carpenter, Ken; Bonura, M. A.; Ruiz, C. L.; Hahn, K. D.; Chandler, G. A.; Nelson, A. J.; Torres, J. A.; McWatters, B. R.

    2014-11-15

    A methodology for obtaining empirical curves relating absolute measured scintillation light output to beta energy deposited is presented. Output signals were measured from thin plastic scintillator using NIST traceable beta and gamma sources and MCNP5 was used to model the energy deposition from each source. Combining the experimental and calculated results gives the desired empirical relationships. To validate, the sensitivity of a beryllium/scintillator-layer neutron activation detector was predicted and then exposed to a known neutron fluence from a Deuterium-Deuterium fusion plasma (DD). The predicted and the measured sensitivity were in statistical agreement.

  19. Toward Accurate and Quantitative Comparative Metagenomics

    PubMed Central

    Nayfach, Stephen; Pollard, Katherine S.

    2016-01-01

    Shotgun metagenomics and computational analysis are used to compare the taxonomic and functional profiles of microbial communities. Leveraging this approach to understand roles of microbes in human biology and other environments requires quantitative data summaries whose values are comparable across samples and studies. Comparability is currently hampered by the use of abundance statistics that do not estimate a meaningful parameter of the microbial community and biases introduced by experimental protocols and data-cleaning approaches. Addressing these challenges, along with improving study design, data access, metadata standardization, and analysis tools, will enable accurate comparative metagenomics. We envision a future in which microbiome studies are replicable and new metagenomes are easily and rapidly integrated with existing data. Only then can the potential of metagenomics for predictive ecological modeling, well-powered association studies, and effective microbiome medicine be fully realized. PMID:27565341

  20. A Computational Model for Predicting Experimental RNA Nearest-Neighbor Free Energy Rankings: Inosine•Uridine Pairs.

    PubMed

    Jolley, Elizabeth A; Lewis, Michael; Znosko, Brent M

    2015-10-16

    A computational model for predicting RNA nearest neighbor free energy rankings has been expanded to include the nonstandard nucleotide inosine. The model uses average fiber diffraction data and molecular dynamic simulations to generate input geometries for Quantum mechanic calculations. This resulted in calculated intrastrand stacking, interstrand stacking, and hydrogen bonding energies that were combined to give total binding energies. Total binding energies for RNA dimer duplexes containing inosine were ranked and compared to experimentally determined free energy ranks for RNA duplexes containing inosine. Statistical analysis showed significant agreement between the computationally determined ranks and the experimentally determined ranks.

  1. Experimental Validation of Stochastic Wireless Urban Channel Model: Estimation and Prediction

    SciTech Connect

    Kuruganti, Phani Teja; Ma, Xiao; Djouadi, Seddik M

    2012-01-01

    Stochastic differential equations (SDE) can be used to describe the time-varying nature of wireless channels. This paper validates a long-term fading channel model for estimation and prediction from solely using measured received signal strength measurements. Such channel models can be used for optimizing wireless networks deployed for industrial automation, public access, and communication. This paper uses two different sets of received signal measurement data to estimate an predict the signal strength based on past measurements. The realworld performance of the estimation and prediction algorithm is demonstrated.

  2. Prediction of experimentally unavailable product branching ratios for biofuel combustion: the role of anharmonicity in the reaction of isobutanol with OH.

    PubMed

    Zheng, Jingjing; Meana-Pañeda, Rubén; Truhlar, Donald G

    2014-04-02

    Isobutanol is a prototype biofuel, and sorting out the mechanism of its combustion is an important objective where theoretical modeling can provide information that is unavailable and not easily obtained by experiment. In the present work the rate constants and branching ratios for the hydrogen abstraction reactions from isobutanol by hydroxyl radical have been calculated using multi-path variational transition-state theory with small-curvature tunneling. We use hybrid degeneracy-corrected vibrational perturbation theory to show that it is critical to consider the anharmonicity difference of high-frequency modes between reactants and transition states. To obtain accurate rate constants, we must apply different scaling factors to the calculated harmonic vibrational frequencies at the reactants and at the transition states. The factors determining the reaction rate constants have been analyzed in detail, including variational effects, tunneling contributions, the effect of multiple reaction paths on transmission coefficients, and anharmonicities of low- and high-frequency vibrational modes. The analysis quantifies the uncertainties in the rate calculations. A key result of the paper is a prediction for the site dependence of hydrogen abstraction from isobutanol by hydroxyl radical. This is very hard to measure experimentally, although it is critical for combustion mechanism modeling. The present prediction differs considerably from previous theoretical work.

  3. The recent absolute total np and pp cross section determinations: quality of data description and prediction of experimental observables

    SciTech Connect

    Laptev, Alexander B; Haight, Robert C; Arndt, Richard A; Briscoe, William J; Paris, Mark W; Strakovsky, Igor I; Workman, Ron L

    2010-01-01

    The absolute total cross sections for np and pp scattering below 1000 MeV are determined based on partial-wave analyses (PWAs) of nucleon-nucleon scattering data. These cross sections are compared with the most recent ENDF/B-VII.0 and JENDL-3.3 data files, and the Nijmegen PWA. Systematic deviations from the ENDF/B-VII.0 and JENDL-3.3 evaluations are found to exist in the low-energy region. Comparison of the np evaluation with the result of most recent np total and differential cross section measurements will be discussed. Results of those measurements were not used in the evaluation database. A comparison was done to check a quality of evaluation and its capabilities to predict experimental observables. Excellent agreement was found between the new experimental data and our PWA predictions.

  4. Target Highlights in CASP9: Experimental Target Structures for the Critical Assessment of Techniques for Protein Structure Prediction

    PubMed Central

    Kryshtafovych, Andriy; Moult, John; Bartual, Sergio G.; Bazan, J. Fernando; Berman, Helen; Casteel, Darren E.; Christodoulou, Evangelos; Everett, John K.; Hausmann, Jens; Heidebrecht, Tatjana; Hills, Tanya; Hui, Raymond; Hunt, John F.; Jayaraman, Seetharaman; Joachimiak, Andrzej; Kennedy, Michael A.; Kim, Choel; Lingel, Andreas; Michalska, Karolina; Montelione, Gaetano T.; Otero, José M.; Perrakis, Anastassis; Pizarro, Juan C.; van Raaij, Mark J.; Ramelot, Theresa A.; Rousseau, Francois; Tong, Liang; Wernimont, Amy K.; Young, Jasmine; Schwede, Torsten

    2011-01-01

    One goal of the CASP Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction is to identify the current state of the art in protein structure prediction and modeling. A fundamental principle of CASP is blind prediction on a set of relevant protein targets, i.e. the participating computational methods are tested on a common set of experimental target proteins, for which the experimental structures are not known at the time of modeling. Therefore, the CASP experiment would not have been possible without broad support of the experimental protein structural biology community. In this manuscript, several experimental groups discuss the structures of the proteins which they provided as prediction targets for CASP9, highlighting structural and functional peculiarities of these structures: the long tail fibre protein gp37 from bacteriophage T4, the cyclic GMP-dependent protein kinase Iβ (PKGIβ) dimerization/docking domain, the ectodomain of the JTB (Jumping Translocation Breakpoint) transmembrane receptor, Autotaxin (ATX) in complex with an inhibitor, the DNA-Binding J-Binding Protein 1 (JBP1) domain essential for biosynthesis and maintenance of DNA base-J (β-D-glucosyl-hydroxymethyluracil) in Trypanosoma and Leishmania, an so far uncharacterized 73 residue domain from Ruminococcus gnavus with a fold typical for PDZ-like domains, a domain from the Phycobilisome (PBS) core-membrane linker (LCM) phycobiliprotein ApcE from Synechocystis, the Heat shock protein 90 (Hsp90) activators PFC0360w and PFC0270w from Plasmodium falciparum, and 2-oxo-3-deoxygalactonate kinase from Klebsiella pneumoniae. PMID:22020785

  5. Accurate thermoelastic tensor and acoustic velocities of NaCl

    NASA Astrophysics Data System (ADS)

    Marcondes, Michel L.; Shukla, Gaurav; da Silveira, Pedro; Wentzcovitch, Renata M.

    2015-12-01

    Despite the importance of thermoelastic properties of minerals in geology and geophysics, their measurement at high pressures and temperatures are still challenging. Thus, ab initio calculations are an essential tool for predicting these properties at extreme conditions. Owing to the approximate description of the exchange-correlation energy, approximations used in calculations of vibrational effects, and numerical/methodological approximations, these methods produce systematic deviations. Hybrid schemes combining experimental data and theoretical results have emerged as a way to reconcile available information and offer more reliable predictions at experimentally inaccessible thermodynamics conditions. Here we introduce a method to improve the calculated thermoelastic tensor by using highly accurate thermal equation of state (EoS). The corrective scheme is general, applicable to crystalline solids with any symmetry, and can produce accurate results at conditions where experimental data may not exist. We apply it to rock-salt-type NaCl, a material whose structural properties have been challenging to describe accurately by standard ab initio methods and whose acoustic/seismic properties are important for the gas and oil industry.

  6. Accurate thermoelastic tensor and acoustic velocities of NaCl

    SciTech Connect

    Marcondes, Michel L.; Shukla, Gaurav; Silveira, Pedro da; Wentzcovitch, Renata M.

    2015-12-15

    Despite the importance of thermoelastic properties of minerals in geology and geophysics, their measurement at high pressures and temperatures are still challenging. Thus, ab initio calculations are an essential tool for predicting these properties at extreme conditions. Owing to the approximate description of the exchange-correlation energy, approximations used in calculations of vibrational effects, and numerical/methodological approximations, these methods produce systematic deviations. Hybrid schemes combining experimental data and theoretical results have emerged as a way to reconcile available information and offer more reliable predictions at experimentally inaccessible thermodynamics conditions. Here we introduce a method to improve the calculated thermoelastic tensor by using highly accurate thermal equation of state (EoS). The corrective scheme is general, applicable to crystalline solids with any symmetry, and can produce accurate results at conditions where experimental data may not exist. We apply it to rock-salt-type NaCl, a material whose structural properties have been challenging to describe accurately by standard ab initio methods and whose acoustic/seismic properties are important for the gas and oil industry.

  7. Mining Proteins with Non-Experimental Annotations Based on an Active Sample Selection Strategy for Predicting Protein Subcellular Localization.

    PubMed

    Cao, Junzhe; Liu, Wenqi; He, Jianjun; Gu, Hong

    2013-01-01

    Subcellular localization of a protein is important to understand proteins' functions and interactions. There are many techniques based on computational methods to predict protein subcellular locations, but it has been shown that many prediction tasks have a training data shortage problem. This paper introduces a new method to mine proteins with non-experimental annotations, which are labeled by non-experimental evidences of protein databases to overcome the training data shortage problem. A novel active sample selection strategy is designed, taking advantage of active learning technology, to actively find useful samples from the entire data pool of candidate proteins with non-experimental annotations. This approach can adequately estimate the "value" of each sample, automatically select the most valuable samples and add them into the original training set, to help to retrain the classifiers. Numerical experiments with for four popular multi-label classifiers on three benchmark datasets show that the proposed method can effectively select the valuable samples to supplement the original training set and significantly improve the performances of predicting classifiers.

  8. Mining Proteins with Non-Experimental Annotations Based on an Active Sample Selection Strategy for Predicting Protein Subcellular Localization

    PubMed Central

    Cao, Junzhe; Liu, Wenqi; He, Jianjun; Gu, Hong

    2013-01-01

    Subcellular localization of a protein is important to understand proteins’ functions and interactions. There are many techniques based on computational methods to predict protein subcellular locations, but it has been shown that many prediction tasks have a training data shortage problem. This paper introduces a new method to mine proteins with non-experimental annotations, which are labeled by non-experimental evidences of protein databases to overcome the training data shortage problem. A novel active sample selection strategy is designed, taking advantage of active learning technology, to actively find useful samples from the entire data pool of candidate proteins with non-experimental annotations. This approach can adequately estimate the “value” of each sample, automatically select the most valuable samples and add them into the original training set, to help to retrain the classifiers. Numerical experiments with for four popular multi-label classifiers on three benchmark datasets show that the proposed method can effectively select the valuable samples to supplement the original training set and significantly improve the performances of predicting classifiers. PMID:23840667

  9. Influence of delayed muscle reflexes on spinal stability: model-based predictions allow alternative interpretations of experimental data.

    PubMed

    Liebetrau, Anne; Puta, Christian; Anders, Christoph; de Lussanet, Marc H E; Wagner, Heiko

    2013-10-01

    Model-based calculations indicate that reflex delay and reflex gain are both important for spinal stability. Experimental results demonstrate that chronic low back pain is associated with delayed muscle reflex responses of trunk muscles. The aim of the present study was to analyze the influence of such time-delayed reflexes on the stability using a simple biomechanical model. Additionally, we compared the model-based predictions with experimental data from chronic low back pain patients and healthy controls using surface-electromyography. Linear stability methods were applied to the musculoskeletal model, which was extended with a time-delayed reflex model. Lateral external perturbations were simulated around equilibrium to investigate the effects of reflex delay and gain on the stability of the human lumbar spine. The model simulations predicted that increased reflex delays require a reduction of the reflex gain to avoid spinal instability. The experimental data support this dependence for the investigated abdominal muscles in chronic low back pain patients and healthy control subjects. Reflex time-delay and gain dependence showed that a delayed reflex latency could have relevant influence on spinal stability, if subjects do not adapt their reflex amplitudes. Based on the model and the experimental results, the relationship between muscle reflex response latency and the maximum of the reflex amplitude should be considered for evaluation of (patho) physiological data. We recommend that training procedures should focus on speeding up the delayed reflex response as well as on increasing the amplitude of these reflexes.

  10. Influence of Corrosion Damage on Prediction of Residual Strength Capacities - An Experimental Analysis

    NASA Astrophysics Data System (ADS)

    Appuhamy, Jayasinghe Mudalige Ruwan Sanjeewa; Ohga, Mitao; Kaita, Tatsumasa; Chun, Pang-Jo; Fujii, Katashi; Dissanayake, Ranjith

    Civil infrastructure systems are prone to age related deterioration due to the exposure to aggressive environmental conditions and inadequate maintenance, and often causes reduction of their carrying capacities. Designing these systems for a particular service life and maintaining them in a safe condition during their entire service life have been recognized as very critical issues worldwide. There have been many damage examples of older steel bridge structures due to corrosion around the world during past few decades and they intensified the importance of attention to the careful evaluation of existing structures for the feasibility of current usage and strengthening them by retrofitting some selected corroded members to ensure the public safety. Therefore, a simple and accurate method to calculate the remaining yield and tensile strength by using a concept of representative effective thickness with correlation of initial thickness and the maximum corroded depth is proposed in this study, based on the results of many tensile coupon tests conducted on corroded specimens cut from a steel girder used for about hundred years with severe corrosion. The proposed methodology revealed more accurate and reliable estimation for the maintenance management of existing corroded steel structures.

  11. 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.

  12. The EPA Online Database of Experimental and Predicted Data to Support Environmental Scientists (ACS Fall meeting)

    EPA Science Inventory

    As part of our efforts to develop a public platform to provide access to predictive models we have attempted to disentangle the influence of the quality versus quantity of data available to develop and validate QSAR models. Using a thorough manual review of the data underlying t...

  13. Validation of the experimental hindcasts produced by the GloSea4 seasonal prediction system

    NASA Astrophysics Data System (ADS)

    Lee, Myong-In; Kang, Hyun-Suk; Kim, Daehyun; Kim, Dongmin; Kim, Hyerim; Kang, Daehyun

    2014-05-01

    Using 14 year (1996-2009) ensemble hindcast runs produced with the Global Seasonal Forecasting System version 4 (GloSea4), this study evaluates the spatial and temporal structure of the hindcast climatology and the prediction skill of major climate variability. A special focus is on the fidelity of the system to reproduce and to forecast phenomena that are closely related to the East Asian climate. Overall the GloSea4 system exhibits realistic representations of the basic climate even though a few model deficiencies are identified in the sea surface temperature and precipitation. In particular, the capability of GloSea4 to capture the seasonal migration of rain belt associated with