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Sample records for accurately predict experimental

  1. Hounsfield unit density accurately predicts ESWL success.

    PubMed

    Magnuson, William J; Tomera, Kevin M; Lance, Raymond S

    2005-01-01

    Extracorporeal shockwave lithotripsy (ESWL) is a commonly used non-invasive treatment for urolithiasis. Helical CT scans provide much better and detailed imaging of the patient with urolithiasis including the ability to measure density of urinary stones. In this study we tested the hypothesis that density of urinary calculi as measured by CT can predict successful ESWL treatment. 198 patients were treated at Alaska Urological Associates with ESWL between January 2002 and April 2004. Of these 101 met study inclusion with accessible CT scans and stones ranging from 5-15 mm. Follow-up imaging demonstrated stone freedom in 74.2%. The overall mean Houndsfield density value for stone-free compared to residual stone groups were significantly different ( 93.61 vs 122.80 p < 0.0001). We determined by receiver operator curve (ROC) that HDV of 93 or less carries a 90% or better chance of stone freedom following ESWL for upper tract calculi between 5-15mm.

  2. 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.

  3. PredictSNP: robust and accurate consensus classifier for prediction of disease-related mutations.

    PubMed

    Bendl, Jaroslav; Stourac, Jan; Salanda, Ondrej; Pavelka, Antonin; Wieben, Eric D; Zendulka, Jaroslav; Brezovsky, Jan; Damborsky, Jiri

    2014-01-01

    Single nucleotide variants represent a prevalent form of genetic variation. Mutations in the coding regions are frequently associated with the development of various genetic diseases. Computational tools for the prediction of the effects of mutations on protein function are very important for analysis of single nucleotide variants and their prioritization for experimental characterization. Many computational tools are already widely employed for this purpose. Unfortunately, their comparison and further improvement is hindered by large overlaps between the training datasets and benchmark datasets, which lead to biased and overly optimistic reported performances. In this study, we have constructed three independent datasets by removing all duplicities, inconsistencies and mutations previously used in the training of evaluated tools. The benchmark dataset containing over 43,000 mutations was employed for the unbiased evaluation of eight established prediction tools: MAPP, nsSNPAnalyzer, PANTHER, PhD-SNP, PolyPhen-1, PolyPhen-2, SIFT and SNAP. The six best performing tools were combined into a consensus classifier PredictSNP, resulting into significantly improved prediction performance, and at the same time returned results for all mutations, confirming that consensus prediction represents an accurate and robust alternative to the predictions delivered by individual tools. A user-friendly web interface enables easy access to all eight prediction tools, the consensus classifier PredictSNP and annotations from the Protein Mutant Database and the UniProt database. The web server and the datasets are freely available to the academic community at http://loschmidt.chemi.muni.cz/predictsnp.

  4. 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.

  5. PredictSNP: Robust and Accurate Consensus Classifier for Prediction of Disease-Related Mutations

    PubMed Central

    Bendl, Jaroslav; Stourac, Jan; Salanda, Ondrej; Pavelka, Antonin; Wieben, Eric D.; Zendulka, Jaroslav; Brezovsky, Jan; Damborsky, Jiri

    2014-01-01

    Single nucleotide variants represent a prevalent form of genetic variation. Mutations in the coding regions are frequently associated with the development of various genetic diseases. Computational tools for the prediction of the effects of mutations on protein function are very important for analysis of single nucleotide variants and their prioritization for experimental characterization. Many computational tools are already widely employed for this purpose. Unfortunately, their comparison and further improvement is hindered by large overlaps between the training datasets and benchmark datasets, which lead to biased and overly optimistic reported performances. In this study, we have constructed three independent datasets by removing all duplicities, inconsistencies and mutations previously used in the training of evaluated tools. The benchmark dataset containing over 43,000 mutations was employed for the unbiased evaluation of eight established prediction tools: MAPP, nsSNPAnalyzer, PANTHER, PhD-SNP, PolyPhen-1, PolyPhen-2, SIFT and SNAP. The six best performing tools were combined into a consensus classifier PredictSNP, resulting into significantly improved prediction performance, and at the same time returned results for all mutations, confirming that consensus prediction represents an accurate and robust alternative to the predictions delivered by individual tools. A user-friendly web interface enables easy access to all eight prediction tools, the consensus classifier PredictSNP and annotations from the Protein Mutant Database and the UniProt database. The web server and the datasets are freely available to the academic community at http://loschmidt.chemi.muni.cz/predictsnp. PMID:24453961

  6. Accurately Predicting Complex Reaction Kinetics from First Principles

    NASA Astrophysics Data System (ADS)

    Green, William

    Many important systems contain a multitude of reactive chemical species, some of which react on a timescale faster than collisional thermalization, i.e. they never achieve a Boltzmann energy distribution. Usually it is impossible to fully elucidate the processes by experiments alone. Here we report recent progress toward predicting the time-evolving composition of these systems a priori: how unexpected reactions can be discovered on the computer, how reaction rates are computed from first principles, and how the many individual reactions are efficiently combined into a predictive simulation for the whole system. Some experimental tests of the a priori predictions are also presented.

  7. 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

  8. Plant diversity accurately predicts insect diversity in two tropical landscapes.

    PubMed

    Zhang, Kai; Lin, Siliang; Ji, Yinqiu; Yang, Chenxue; Wang, Xiaoyang; Yang, Chunyan; Wang, Hesheng; Jiang, Haisheng; Harrison, Rhett D; Yu, Douglas W

    2016-09-01

    Plant diversity surely determines arthropod diversity, but only moderate correlations between arthropod and plant species richness had been observed until Basset et al. (Science, 338, 2012 and 1481) finally undertook an unprecedentedly comprehensive sampling of a tropical forest and demonstrated that plant species richness could indeed accurately predict arthropod species richness. We now require a high-throughput pipeline to operationalize this result so that we can (i) test competing explanations for tropical arthropod megadiversity, (ii) improve estimates of global eukaryotic species diversity, and (iii) use plant and arthropod communities as efficient proxies for each other, thus improving the efficiency of conservation planning and of detecting forest degradation and recovery. We therefore applied metabarcoding to Malaise-trap samples across two tropical landscapes in China. We demonstrate that plant species richness can accurately predict arthropod (mostly insect) species richness and that plant and insect community compositions are highly correlated, even in landscapes that are large, heterogeneous and anthropogenically modified. Finally, we review how metabarcoding makes feasible highly replicated tests of the major competing explanations for tropical megadiversity. PMID:27474399

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

    DOE PAGES

    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.; et al

    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

  10. 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.

  11. 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

  12. 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

  13. Mind-set and close relationships: when bias leads to (In)accurate predictions.

    PubMed

    Gagné, F M; Lydon, J E

    2001-07-01

    The authors investigated whether mind-set influences the accuracy of relationship predictions. Because people are more biased in their information processing when thinking about implementing an important goal, relationship predictions made in an implemental mind-set were expected to be less accurate than those made in a more impartial deliberative mind-set. In Study 1, open-ended thoughts of students about to leave for university were coded for mind-set. In Study 2, mind-set about a major life goal was assessed using a self-report measure. In Study 3, mind-set was experimentally manipulated. Overall, mind-set interacted with forecasts to predict relationship survival. Forecasts were more accurate in a deliberative mind-set than in an implemental mind-set. This effect was more pronounced for long-term than for short-term relationship survival. Finally, deliberatives were not pessimistic; implementals were unduly optimistic.

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

    PubMed

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

    2016-05-01

    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 H2 (+). Results are presented for (i) covalent bonds to hydrogen in 12 molecules with 8 valence electrons (CH4, NH3, H2O, HF, SiH4, PH3, H2S, HCl, GeH4, AsH3, H2Se, HBr); (ii) main-group single bonds in 9 molecules with 14 valence electrons (CH3F, CH3Cl, CH3Br, SiH3F, SiH3Cl, SiH3Br, GeH3F, GeH3Cl, GeH3Br); (iii) main-group double bonds in 9 molecules with 12 valence electrons (CH2O, CH2S, CH2Se, SiH2O, SiH2S, SiH2Se, GeH2O, GeH2S, GeH2Se); (iv) main-group triple bonds in 9 molecules with 10 valence electrons (HCN, HCP, HCAs, HSiN, HSi

  15. 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

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

    PubMed

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

    2016-05-01

    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 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

  17. The Experimental MJO Prediction Project

    NASA Technical Reports Server (NTRS)

    Waliser, Duane; Weickmann, Klaus; Dole, Randall; Schubert, Siegfried; Alves, Oscar; Jones, Charles; Newman, Matthew; Pan, Hua-Lu; Roubicek, Andres; Saha, Suranjana; Smith, Cathy; VanDenDool, Huug; Vitart, Frederic; Wheeler, Matthew; Whitaker, Jeffrey

    2006-01-01

    Weather prediction is typically concerned with lead times of hours to days, while seasonal-to-interannual climate prediction is concerned with lead times of months to seasons. Recently, there has been growing interest in 'subseasonal' forecasts---those that have lead times on the order of weeks (e.g., Schubert et al. 2002; Waliser et al. 2003; Waliser et al. 2005). The basis for developing and exploiting subseasonal predictions largely resides with phenomena such as the Pacific North American (PNA) pattern, the North Atlantic oscillation (NAO), the Madden-Julian Oscillation (MJO), mid-latitude blocking, and the memory associated with soil moisture, as well as modeling techniques that rely on both initial conditions and slowly varying boundary conditions (e.g., tropical Pacific SST). An outgrowth of this interest has been the development of an Experimental MJO Prediction Project (EMPP). Th project provides real-time weather and climate information and predictions for a variety of applications, broadly encompassing the subseasonal weather-climate connection. Th focus is on the MJO because it represents a repeatable, low-frequency phenomenon. MJO's importance among the subseasonal phenomena is very similar to that of El Nino-Southern Oscillation(ENSO) among the interannual phenomena. This note describes the history and objectives of EMPP, its status,capabilities, and plans.

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

    PubMed

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

    2015-07-01

    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.

  19. 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

  20. Can Contemporary Density Functional Theory Predict Energy Spans in Molecular Catalysis Accurately Enough To Be Applicable for in Silico Catalyst Design? A Computational/Experimental Case Study for the Ruthenium-Catalyzed Hydrogenation of Olefins.

    PubMed

    Rohmann, Kai; Hölscher, Markus; Leitner, Walter

    2016-01-13

    The catalytic hydrogenation of cyclohexene and 1-methylcyclohexene is investigated experimentally and by means of density functional theory (DFT) computations using novel ruthenium Xantphos(Ph) (4,5-bis(diphenylphosphino)-9,9-dimethylxanthene) and Xantphos(Cy) (4,5-bis(dicyclohexylphosphino)-9,9-dimethylxanthene) precatalysts [Ru(Xantphos(Ph))(PhCO2)(Cl)] (1) and [Ru(Xantphos(Cy))(PhCO2)(Cl)] (2), the synthesis, characterization, and crystal structures of which are reported. The intention of this work is to (i) understand the reaction mechanisms on the microscopic level and (ii) compare experimentally observed activation barriers with computed barriers. The Gibbs free activation energy ΔG(⧧) was obtained experimentally with precatalyst 1 from Eyring plots for the hydrogenation of cyclohexene (ΔG(⧧) = 17.2 ± 1.0 kcal/mol) and 1-methylcyclohexene (ΔG(⧧) = 18.8 ± 2.4 kcal/mol), while the Gibbs free activation energy ΔG(⧧) for the hydrogenation of cyclohexene with precatalyst 2 was determined to be 21.1 ± 2.3 kcal/mol. Plausible activation pathways and catalytic cycles were computed in the gas phase (M06-L/def2-SVP). A variety of popular density functionals (ωB97X-D, LC-ωPBE, CAM-B3LYP, B3LYP, B97-D3BJ, B3LYP-D3, BP86-D3, PBE0-D3, M06-L, MN12-L) were used to reoptimize the turnover determining states in the solvent phase (DF/def2-TZVP; IEF-PCM and/or SMD) to investigate how well the experimentally obtained activation barriers can be reproduced by the calculations. The density functionals B97-D3BJ, MN12-L, M06-L, B3LYP-D3, and CAM-B3LYP reproduce the experimentally observed activation barriers for both olefins very well with very small (0.1 kcal/mol) to moderate (3.0 kcal/mol) mean deviations from the experimental values indicating for the field of hydrogenation catalysis most of these functionals to be useful for in silico catalyst design prior to experimental work. PMID:26713773

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

    PubMed

    Stephanou, Pavlos S; Mavrantzas, Vlasis G

    2014-06-01

    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. PMID:24908037

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

    NASA Astrophysics Data System (ADS)

    Stephanou, Pavlos S.; Mavrantzas, Vlasis G.

    2014-06-01

    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.

  3. Does more accurate exposure prediction necessarily improve health effect estimates?

    PubMed

    Szpiro, Adam A; Paciorek, Christopher J; Sheppard, Lianne

    2011-09-01

    A unique challenge in air pollution cohort studies and similar applications in environmental epidemiology is that exposure is not measured directly at subjects' locations. Instead, pollution data from monitoring stations at some distance from the study subjects are used to predict exposures, and these predicted exposures are used to estimate the health effect parameter of interest. It is usually assumed that minimizing the error in predicting the true exposure will improve health effect estimation. We show in a simulation study that this is not always the case. We interpret our results in light of recently developed statistical theory for measurement error, and we discuss implications for the design and analysis of epidemiologic research.

  4. Change in heat capacity accurately predicts vibrational coupling in enzyme catalyzed reactions.

    PubMed

    Arcus, Vickery L; Pudney, Christopher R

    2015-08-01

    The temperature dependence of kinetic isotope effects (KIEs) have been used to infer the vibrational coupling of the protein and or substrate to the reaction coordinate, particularly in enzyme-catalyzed hydrogen transfer reactions. We find that a new model for the temperature dependence of experimentally determined observed rate constants (macromolecular rate theory, MMRT) is able to accurately predict the occurrence of vibrational coupling, even where the temperature dependence of the KIE fails. This model, that incorporates the change in heat capacity for enzyme catalysis, demonstrates remarkable consistency with both experiment and theory and in many respects is more robust than models used at present.

  5. Differential contribution of visual and auditory information to accurately predict the direction and rotational motion of a visual stimulus.

    PubMed

    Park, Seoung Hoon; Kim, Seonjin; Kwon, MinHyuk; Christou, Evangelos A

    2016-03-01

    Vision and auditory information are critical for perception and to enhance the ability of an individual to respond accurately to a stimulus. However, it is unknown whether visual and auditory information contribute differentially to identify the direction and rotational motion of the stimulus. The purpose of this study was to determine the ability of an individual to accurately predict the direction and rotational motion of the stimulus based on visual and auditory information. In this study, we recruited 9 expert table-tennis players and used table-tennis service as our experimental model. Participants watched recorded services with different levels of visual and auditory information. The goal was to anticipate the direction of the service (left or right) and the rotational motion of service (topspin, sidespin, or cut). We recorded their responses and quantified the following outcomes: (i) directional accuracy and (ii) rotational motion accuracy. The response accuracy was the accurate predictions relative to the total number of trials. The ability of the participants to predict the direction of the service accurately increased with additional visual information but not with auditory information. In contrast, the ability of the participants to predict the rotational motion of the service accurately increased with the addition of auditory information to visual information but not with additional visual information alone. In conclusion, this finding demonstrates that visual information enhances the ability of an individual to accurately predict the direction of the stimulus, whereas additional auditory information enhances the ability of an individual to accurately predict the rotational motion of stimulus.

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

    PubMed

    Nam, Ki-Uk; Hong, Jongrak

    2015-11-01

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

  7. 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.

  8. 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.

  9. 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

  10. Accurate theoretical and experimental characterization of optical grating coupler.

    PubMed

    Fesharaki, Faezeh; Hossain, Nadir; Vigne, Sebastien; Chaker, Mohamed; Wu, Ke

    2016-09-01

    Periodic structures, acting as reflectors, filters, and couplers, are a fundamental building block section in many optical devices. In this paper, a three-dimensional simulation of a grating coupler, a well-known periodic structure, is conducted. Guided waves and leakage characteristics of an out-of-plane grating coupler are studied in detail, and its coupling efficiency is examined. Furthermore, a numerical calibration analysis is applied through a commercial software package on the basis of a full-wave finite-element method to calculate the complex propagation constant of the structure and to evaluate the radiation pattern. For experimental evaluation, an optimized grating coupler is fabricated using electron-beam lithography technique and plasma etching. An excellent agreement between simulations and measurements is observed, thereby validating the demonstrated method. PMID:27607706

  11. Accurate contact predictions using covariation techniques and machine learning

    PubMed Central

    Kosciolek, Tomasz

    2015-01-01

    ABSTRACT Here we present the results of residue–residue contact predictions achieved in CASP11 by the CONSIP2 server, which is based around our MetaPSICOV contact prediction method. On a set of 40 target domains with a median family size of around 40 effective sequences, our server achieved an average top‐L/5 long‐range contact precision of 27%. MetaPSICOV method bases on a combination of classical contact prediction features, enhanced with three distinct covariation methods embedded in a two‐stage neural network predictor. Some unique features of our approach are (1) the tuning between the classical and covariation features depending on the depth of the input alignment and (2) a hybrid approach to generate deepest possible multiple‐sequence alignments by combining jackHMMer and HHblits. We discuss the CONSIP2 pipeline, our results and show that where the method underperformed, the major factor was relying on a fixed set of parameters for the initial sequence alignments and not attempting to perform domain splitting as a preprocessing step. Proteins 2016; 84(Suppl 1):145–151. © 2015 The Authors. Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc. PMID:26205532

  12. 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?

  13. 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.

  14. Accurate and predictive antibody repertoire profiling by molecular amplification fingerprinting

    PubMed Central

    Khan, Tarik A.; Friedensohn, Simon; de Vries, Arthur R. Gorter; Straszewski, Jakub; Ruscheweyh, Hans-Joachim; Reddy, Sai T.

    2016-01-01

    High-throughput antibody repertoire sequencing (Ig-seq) provides quantitative molecular information on humoral immunity. However, Ig-seq is compromised by biases and errors introduced during library preparation and sequencing. By using synthetic antibody spike-in genes, we determined that primer bias from multiplex polymerase chain reaction (PCR) library preparation resulted in antibody frequencies with only 42 to 62% accuracy. Additionally, Ig-seq errors resulted in antibody diversity measurements being overestimated by up to 5000-fold. To rectify this, we developed molecular amplification fingerprinting (MAF), which uses unique molecular identifier (UID) tagging before and during multiplex PCR amplification, which enabled tagging of transcripts while accounting for PCR efficiency. Combined with a bioinformatic pipeline, MAF bias correction led to measurements of antibody frequencies with up to 99% accuracy. We also used MAF to correct PCR and sequencing errors, resulting in enhanced accuracy of full-length antibody diversity measurements, achieving 98 to 100% error correction. Using murine MAF-corrected data, we established a quantitative metric of recent clonal expansion—the intraclonal diversity index—which measures the number of unique transcripts associated with an antibody clone. We used this intraclonal diversity index along with antibody frequencies and somatic hypermutation to build a logistic regression model for prediction of the immunological status of clones. The model was able to predict clonal status with high confidence but only when using MAF error and bias corrected Ig-seq data. Improved accuracy by MAF provides the potential to greatly advance Ig-seq and its utility in immunology and biotechnology. PMID:26998518

  15. 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.

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

    DOE PAGES

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

    2015-05-15

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

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

    PubMed

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

    2015-07-01

    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

  18. 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.

  19. 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.

  20. Change in BMI accurately predicted by social exposure to acquaintances.

    PubMed

    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 R(2). 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.

  1. 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.

  2. 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

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

    PubMed

    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

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

    PubMed

    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.

  5. 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.

  6. 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.

  7. A survey of factors contributing to accurate theoretical predictions of atomization energies and molecular structures

    NASA Astrophysics Data System (ADS)

    Feller, David; Peterson, Kirk A.; Dixon, David A.

    2008-11-01

    High level electronic structure predictions of thermochemical properties and molecular structure are capable of accuracy rivaling the very best experimental measurements as a result of rapid advances in hardware, software, and methodology. Despite the progress, real world limitations require practical approaches designed for handling general chemical systems that rely on composite strategies in which a single, intractable calculation is replaced by a series of smaller calculations. As typically implemented, these approaches produce a final, or "best," estimate that is constructed from one major component, fine-tuned by multiple corrections that are assumed to be additive. Though individually much smaller than the original, unmanageable computational problem, these corrections are nonetheless extremely costly. This study presents a survey of the widely varying magnitude of the most important components contributing to the atomization energies and structures of 106 small molecules. It combines large Gaussian basis sets and coupled cluster theory up to quadruple excitations for all systems. In selected cases, the effects of quintuple excitations and/or full configuration interaction were also considered. The availability of reliable experimental data for most of the molecules permits an expanded statistical analysis of the accuracy of the approach. In cases where reliable experimental information is currently unavailable, the present results are expected to provide some of the most accurate benchmark values available.

  8. 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.

  9. 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.

  10. 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].

  11. Accurate prediction of solvent accessibility using neural networks-based regression.

    PubMed

    Adamczak, Rafał; Porollo, Aleksey; Meller, Jarosław

    2004-09-01

    Accurate prediction of relative solvent accessibilities (RSAs) of amino acid residues in proteins may be used to facilitate protein structure prediction and functional annotation. Toward that goal we developed a novel method for improved prediction of RSAs. Contrary to other machine learning-based methods from the literature, we do not impose a classification problem with arbitrary boundaries between the classes. Instead, we seek a continuous approximation of the real-value RSA using nonlinear regression, with several feed forward and recurrent neural networks, which are then combined into a consensus predictor. A set of 860 protein structures derived from the PFAM database was used for training, whereas validation of the results was carefully performed on several nonredundant control sets comprising a total of 603 structures derived from new Protein Data Bank structures and had no homology to proteins included in the training. Two classes of alternative predictors were developed for comparison with the regression-based approach: one based on the standard classification approach and the other based on a semicontinuous approximation with the so-called thermometer encoding. Furthermore, a weighted approximation, with errors being scaled by the observed levels of variability in RSA for equivalent residues in families of homologous structures, was applied in order to improve the results. The effects of including evolutionary profiles and the growth of sequence databases were assessed. In accord with the observed levels of variability in RSA for different ranges of RSA values, the regression accuracy is higher for buried than for exposed residues, with overall 15.3-15.8% mean absolute errors and correlation coefficients between the predicted and experimental values of 0.64-0.67 on different control sets. The new method outperforms classification-based algorithms when the real value predictions are projected onto two-class classification problems with several commonly

  12. 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

  13. How accurately can we predict the melting points of drug-like compounds?

    PubMed

    Tetko, Igor V; Sushko, Yurii; Novotarskyi, Sergii; Patiny, Luc; Kondratov, Ivan; Petrenko, Alexander E; Charochkina, Larisa; Asiri, Abdullah M

    2014-12-22

    This article contributes a highly accurate model for predicting the melting points (MPs) of medicinal chemistry compounds. The model was developed using the largest published data set, comprising more than 47k compounds. The distributions of MPs in drug-like and drug lead sets showed that >90% of molecules melt within [50,250]°C. The final model calculated an RMSE of less than 33 °C for molecules from this temperature interval, which is the most important for medicinal chemistry users. This performance was achieved using a consensus model that performed calculations to a significantly higher accuracy than the individual models. We found that compounds with reactive and unstable groups were overrepresented among outlying compounds. These compounds could decompose during storage or measurement, thus introducing experimental errors. While filtering the data by removing outliers generally increased the accuracy of individual models, it did not significantly affect the results of the consensus models. Three analyzed distance to models did not allow us to flag molecules, which had MP values fell outside the applicability domain of the model. We believe that this negative result and the public availability of data from this article will encourage future studies to develop better approaches to define the applicability domain of models. The final model, MP data, and identified reactive groups are available online at http://ochem.eu/article/55638.

  14. How accurately can we predict the melting points of drug-like compounds?

    PubMed

    Tetko, Igor V; Sushko, Yurii; Novotarskyi, Sergii; Patiny, Luc; Kondratov, Ivan; Petrenko, Alexander E; Charochkina, Larisa; Asiri, Abdullah M

    2014-12-22

    This article contributes a highly accurate model for predicting the melting points (MPs) of medicinal chemistry compounds. The model was developed using the largest published data set, comprising more than 47k compounds. The distributions of MPs in drug-like and drug lead sets showed that >90% of molecules melt within [50,250]°C. The final model calculated an RMSE of less than 33 °C for molecules from this temperature interval, which is the most important for medicinal chemistry users. This performance was achieved using a consensus model that performed calculations to a significantly higher accuracy than the individual models. We found that compounds with reactive and unstable groups were overrepresented among outlying compounds. These compounds could decompose during storage or measurement, thus introducing experimental errors. While filtering the data by removing outliers generally increased the accuracy of individual models, it did not significantly affect the results of the consensus models. Three analyzed distance to models did not allow us to flag molecules, which had MP values fell outside the applicability domain of the model. We believe that this negative result and the public availability of data from this article will encourage future studies to develop better approaches to define the applicability domain of models. The final model, MP data, and identified reactive groups are available online at http://ochem.eu/article/55638. PMID:25489863

  15. 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. PMID:27260782

  16. Accurate and Rigorous Prediction of the Changes in Protein Free Energies in a Large-Scale Mutation Scan.

    PubMed

    Gapsys, Vytautas; Michielssens, Servaas; Seeliger, Daniel; de Groot, Bert L

    2016-06-20

    The prediction of mutation-induced free-energy changes in protein thermostability or protein-protein binding is of particular interest in the fields of protein design, biotechnology, and bioengineering. Herein, we achieve remarkable accuracy in a scan of 762 mutations estimating changes in protein thermostability based on the first principles of statistical mechanics. The remaining error in the free-energy estimates appears to be due to three sources in approximately equal parts, namely sampling, force-field inaccuracies, and experimental uncertainty. We propose a consensus force-field approach, which, together with an increased sampling time, leads to a free-energy prediction accuracy that matches those reached in experiments. This versatile approach enables accurate free-energy estimates for diverse proteins, including the prediction of changes in the melting temperature of the membrane protein neurotensin receptor 1. PMID:27122231

  17. 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.

  18. Evaluation of new reference genes in papaya for accurate transcript normalization under different experimental conditions.

    PubMed

    Zhu, Xiaoyang; Li, Xueping; Chen, Weixin; Chen, Jianye; Lu, Wangjin; Chen, Lei; Fu, Danwen

    2012-01-01

    Real-time reverse transcription PCR (RT-qPCR) is a preferred method for rapid and accurate quantification of gene expression studies. Appropriate application of RT-qPCR requires accurate normalization though the use of reference genes. As no single reference gene is universally suitable for all experiments, thus reference gene(s) validation under different experimental conditions is crucial for RT-qPCR analysis. To date, only a few studies on reference genes have been done in other plants but none in papaya. In the present work, we selected 21 candidate reference genes, and evaluated their expression stability in 246 papaya fruit samples using three algorithms, geNorm, NormFinder and RefFinder. The samples consisted of 13 sets collected under different experimental conditions, including various tissues, different storage temperatures, different cultivars, developmental stages, postharvest ripening, modified atmosphere packaging, 1-methylcyclopropene (1-MCP) treatment, hot water treatment, biotic stress and hormone treatment. Our results demonstrated that expression stability varied greatly between reference genes and that different suitable reference gene(s) or combination of reference genes for normalization should be validated according to the experimental conditions. In general, the internal reference genes EIF (Eukaryotic initiation factor 4A), TBP1 (TATA binding protein 1) and TBP2 (TATA binding protein 2) genes had a good performance under most experimental conditions, whereas the most widely present used reference genes, ACTIN (Actin 2), 18S rRNA (18S ribosomal RNA) and GAPDH (Glyceraldehyde-3-phosphate dehydrogenase) were not suitable in many experimental conditions. In addition, two commonly used programs, geNorm and Normfinder, were proved sufficient for the validation. This work provides the first systematic analysis for the selection of superior reference genes for accurate transcript normalization in papaya under different experimental conditions.

  19. A Single Linear Prediction Filter that Accurately Predicts the AL Index

    NASA Astrophysics Data System (ADS)

    McPherron, R. L.; Chu, X.

    2015-12-01

    The AL index is a measure of the strength of the westward electrojet flowing along the auroral oval. It has two components: one from the global DP-2 current system and a second from the DP-1 current that is more localized near midnight. It is generally believed that the index a very poor measure of these currents because of its dependence on the distance of stations from the source of the two currents. In fact over season and solar cycle the coupling strength defined as the steady state ratio of the output AL to the input coupling function varies by a factor of four. There are four factors that lead to this variation. First is the equinoctial effect that modulates coupling strength with peaks (strongest coupling) at the equinoxes. Second is the saturation of the polar cap potential which decreases coupling strength as the strength of the driver increases. Since saturation occurs more frequently at solar maximum we obtain the result that maximum coupling strength occurs at equinox at solar minimum. A third factor is ionospheric conductivity with stronger coupling at summer solstice as compared to winter. The fourth factor is the definition of a solar wind coupling function appropriate to a given index. We have developed an optimum coupling function depending on solar wind speed, density, transverse magnetic field, and IMF clock angle which is better than previous functions. Using this we have determined the seasonal variation of coupling strength and developed an inverse function that modulates the optimum coupling function so that all seasonal variation is removed. In a similar manner we have determined the dependence of coupling strength on solar wind driver strength. The inverse of this function is used to scale a linear prediction filter thus eliminating the dependence on driver strength. Our result is a single linear filter that is adjusted in a nonlinear manner by driver strength and an optimum coupling function that is seasonal modulated. Together this

  20. Nonempirically Tuned Range-Separated DFT Accurately Predicts Both Fundamental and Excitation Gaps in DNA and RNA Nucleobases

    PubMed Central

    2012-01-01

    Using a nonempirically tuned range-separated DFT approach, we study both the quasiparticle properties (HOMO–LUMO fundamental gaps) and excitation energies of DNA and RNA nucleobases (adenine, thymine, cytosine, guanine, and uracil). Our calculations demonstrate that a physically motivated, first-principles tuned DFT approach accurately reproduces results from both experimental benchmarks and more computationally intensive techniques such as many-body GW theory. Furthermore, in the same set of nucleobases, we show that the nonempirical range-separated procedure also leads to significantly improved results for excitation energies compared to conventional DFT methods. The present results emphasize the importance of a nonempirically tuned range-separation approach for accurately predicting both fundamental and excitation gaps in DNA and RNA nucleobases. PMID:22904693

  1. A review of the kinetic detail required for accurate predictions of normal shock waves

    NASA Technical Reports Server (NTRS)

    Muntz, E. P.; Erwin, Daniel A.; Pham-Van-diep, Gerald C.

    1991-01-01

    Several aspects of the kinetic models used in the collision phase of Monte Carlo direct simulations have been studied. Accurate molecular velocity distribution function predictions require a significantly increased number of computational cells in one maximum slope shock thickness, compared to predictions of macroscopic properties. The shape of the highly repulsive portion of the interatomic potential for argon is not well modeled by conventional interatomic potentials; this portion of the potential controls high Mach number shock thickness predictions, indicating that the specification of the energetic repulsive portion of interatomic or intermolecular potentials must be chosen with care for correct modeling of nonequilibrium flows at high temperatures. It has been shown for inverse power potentials that the assumption of variable hard sphere scattering provides accurate predictions of the macroscopic properties in shock waves, by comparison with simulations in which differential scattering is employed in the collision phase. On the other hand, velocity distribution functions are not well predicted by the variable hard sphere scattering model for softer potentials at higher Mach numbers.

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  3. Can phenological models predict tree phenology accurately in the future? The unrevealed hurdle of endodormancy break.

    PubMed

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

    2016-10-01

    The onset of the growing season of trees has been earlier by 2.3 days per decade during the last 40 years in temperate Europe because of global warming. 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 endodormancy, and, on the other hand, higher temperatures are necessary to promote bud cell growth afterward. Different process-based models have been developed in the last decades to predict the date of budbreak of woody species. They predict that global warming should delay or compromise endodormancy break at the species equatorward range limits leading to a delay or even impossibility to flower or set new leaves. These models are classically parameterized with flowering or budbreak dates only, with no information on the endodormancy break date because this information is very scarce. Here, we evaluated the efficiency of a set of phenological models to accurately predict the endodormancy break dates of three fruit trees. Our results show that models calibrated solely with budbreak dates usually do not accurately predict the endodormancy break date. Providing endodormancy break date for the model parameterization results in much more accurate prediction of this latter, with, however, a higher error than that on budbreak dates. Most importantly, we show that models not calibrated with endodormancy break dates can generate large discrepancies in forecasted budbreak dates when using climate scenarios as compared to models calibrated with endodormancy break dates. This discrepancy increases with mean annual temperature and is therefore the strongest after 2050 in the southernmost regions. Our results claim for the urgent need of massive measurements of endodormancy break dates in forest and fruit trees to yield more robust projections of phenological changes in a near future. PMID:27272707

  4. Can phenological models predict tree phenology accurately in the future? The unrevealed hurdle of endodormancy break.

    PubMed

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

    2016-10-01

    The onset of the growing season of trees has been earlier by 2.3 days per decade during the last 40 years in temperate Europe because of global warming. 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 endodormancy, and, on the other hand, higher temperatures are necessary to promote bud cell growth afterward. Different process-based models have been developed in the last decades to predict the date of budbreak of woody species. They predict that global warming should delay or compromise endodormancy break at the species equatorward range limits leading to a delay or even impossibility to flower or set new leaves. These models are classically parameterized with flowering or budbreak dates only, with no information on the endodormancy break date because this information is very scarce. Here, we evaluated the efficiency of a set of phenological models to accurately predict the endodormancy break dates of three fruit trees. Our results show that models calibrated solely with budbreak dates usually do not accurately predict the endodormancy break date. Providing endodormancy break date for the model parameterization results in much more accurate prediction of this latter, with, however, a higher error than that on budbreak dates. Most importantly, we show that models not calibrated with endodormancy break dates can generate large discrepancies in forecasted budbreak dates when using climate scenarios as compared to models calibrated with endodormancy break dates. This discrepancy increases with mean annual temperature and is therefore the strongest after 2050 in the southernmost regions. Our results claim for the urgent need of massive measurements of endodormancy break dates in forest and fruit trees to yield more robust projections of phenological changes in a near future.

  5. The Compensatory Reserve For Early and Accurate Prediction Of Hemodynamic Compromise: A Review of the Underlying Physiology.

    PubMed

    Convertino, Victor A; Wirt, Michael D; Glenn, John F; Lein, Brian C

    2016-06-01

    Shock is deadly and unpredictable if it is not recognized and treated in early stages of hemorrhage. Unfortunately, measurements of standard vital signs that are displayed on current medical monitors fail to provide accurate or early indicators of shock because of physiological mechanisms that effectively compensate for blood loss. As a result of new insights provided by the latest research on the physiology of shock using human experimental models of controlled hemorrhage, it is now recognized that measurement of the body's reserve to compensate for reduced circulating blood volume is the single most important indicator for early and accurate assessment of shock. We have called this function the "compensatory reserve," which can be accurately assessed by real-time measurements of changes in the features of the arterial waveform. In this paper, the physiology underlying the development and evaluation of a new noninvasive technology that allows for real-time measurement of the compensatory reserve will be reviewed, with its clinical implications for earlier and more accurate prediction of shock. PMID:26950588

  6. 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.

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

    PubMed

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

    2015-09-01

    Renewable energy from lignocellulosic biomass has been deemed an alternative to depleting fossil fuels. In order to improve this technology, we aim to develop robust mathematical models for the enzymatic lignocellulose degradation process. By analyzing 96 groups of previously published and newly obtained lignocellulose saccharification results and fitting them to Weibull distribution, we discovered Weibull statistics can accurately predict lignocellulose saccharification data, regardless of the type of substrates, enzymes and saccharification conditions. A mathematical model for enzymatic lignocellulose degradation was subsequently constructed based on Weibull statistics. Further analysis of the mathematical structure of the model and experimental saccharification data showed the significance of the two parameters in this model. In particular, the λ value, defined the characteristic time, represents the overall performance of the saccharification system. This suggestion was further supported by statistical analysis of experimental saccharification data and analysis of the glucose production levels when λ and n values change. In conclusion, the constructed Weibull statistics-based model can accurately predict lignocellulose hydrolysis behavior and we can use the λ parameter to assess the overall performance of enzymatic lignocellulose degradation. Advantages and potential applications of the model and the λ value in saccharification performance assessment were discussed. PMID:26121186

  8. 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. PMID:26588131

  9. 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.

  10. 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. PMID:19950907

  11. 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.

  12. 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.

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

    DOE PAGES

    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 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

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

    PubMed Central

    2015-01-01

    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. PMID:26113956

  15. 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

  16. 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.

  17. 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

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

    PubMed

    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.

  19. 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

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

    PubMed

    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

  1. 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

  2. Toward an Accurate Prediction of the Arrival Time of Geomagnetic-Effective Coronal Mass Ejections

    NASA Astrophysics Data System (ADS)

    Shi, T.; Wang, Y.; Wan, L.; Cheng, X.; Ding, M.; Zhang, J.

    2015-12-01

    Accurately predicting the arrival of coronal mass ejections (CMEs) to the Earth based on remote images is of critical significance for the study of space weather. Here we make a statistical study of 21 Earth-directed CMEs, specifically exploring the relationship between CME initial speeds and transit times. The initial speed of a CME is obtained by fitting the CME with the Graduated Cylindrical Shell model and is thus free of projection effects. We then use the drag force model to fit results of the transit time versus the initial speed. By adopting different drag regimes, i.e., the viscous, aerodynamics, and hybrid regimes, we get similar results, with a least mean estimation error of the hybrid model of 12.9 hr. CMEs with a propagation angle (the angle between the propagation direction and the Sun-Earth line) larger than their half-angular widths arrive at the Earth with an angular deviation caused by factors other than the radial solar wind drag. The drag force model cannot be reliably applied to such events. If we exclude these events in the sample, the prediction accuracy can be improved, i.e., the estimation error reduces to 6.8 hr. This work suggests that it is viable to predict the arrival time of CMEs to the Earth based on the initial parameters with fairly good accuracy. Thus, it provides a method of forecasting space weather 1-5 days following the occurrence of CMEs.

  3. Direct Pressure Monitoring Accurately Predicts Pulmonary Vein Occlusion During Cryoballoon Ablation

    PubMed Central

    Kosmidou, Ioanna; Wooden, Shannnon; Jones, Brian; Deering, Thomas; Wickliffe, Andrew; Dan, Dan

    2013-01-01

    Cryoballoon ablation (CBA) is an established therapy for atrial fibrillation (AF). Pulmonary vein (PV) occlusion is essential for achieving antral contact and PV isolation and is typically assessed by contrast injection. We present a novel method of direct pressure monitoring for assessment of PV occlusion. Transcatheter pressure is monitored during balloon advancement to the PV antrum. Pressure is recorded via a single pressure transducer connected to the inner lumen of the cryoballoon. Pressure curve characteristics are used to assess occlusion in conjunction with fluoroscopic or intracardiac echocardiography (ICE) guidance. PV occlusion is confirmed when loss of typical left atrial (LA) pressure waveform is observed with recordings of PA pressure characteristics (no A wave and rapid V wave upstroke). Complete pulmonary vein occlusion as assessed with this technique has been confirmed with concurrent contrast utilization during the initial testing of the technique and has been shown to be highly accurate and readily reproducible. We evaluated the efficacy of this novel technique in 35 patients. A total of 128 veins were assessed for occlusion with the cryoballoon utilizing the pressure monitoring technique; occlusive pressure was demonstrated in 113 veins with resultant successful pulmonary vein isolation in 111 veins (98.2%). Occlusion was confirmed with subsequent contrast injection during the initial ten procedures, after which contrast utilization was rapidly reduced or eliminated given the highly accurate identification of occlusive pressure waveform with limited initial training. Verification of PV occlusive pressure during CBA is a novel approach to assessing effective PV occlusion and it accurately predicts electrical isolation. Utilization of this method results in significant decrease in fluoroscopy time and volume of contrast. PMID:23485956

  4. 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.

  5. In vitro transcription accurately predicts lac repressor phenotype in vivo in Escherichia coli

    PubMed Central

    2014-01-01

    A multitude of studies have looked at the in vivo and in vitro behavior of the lac repressor binding to DNA and effector molecules in order to study transcriptional repression, however these studies are not always reconcilable. Here we use in vitro transcription to directly mimic the in vivo system in order to build a self consistent set of experiments to directly compare in vivo and in vitro genetic repression. A thermodynamic model of the lac repressor binding to operator DNA and effector is used to link DNA occupancy to either normalized in vitro mRNA product or normalized in vivo fluorescence of a regulated gene, YFP. An accurate measurement of repressor, DNA and effector concentrations were made both in vivo and in vitro allowing for direct modeling of the entire thermodynamic equilibrium. In vivo repression profiles are accurately predicted from the given in vitro parameters when molecular crowding is considered. Interestingly, our measured repressor–operator DNA affinity differs significantly from previous in vitro measurements. The literature values are unable to replicate in vivo binding data. We therefore conclude that the repressor-DNA affinity is much weaker than previously thought. This finding would suggest that in vitro techniques that are specifically designed to mimic the in vivo process may be necessary to replicate the native system. PMID:25097824

  6. 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.

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

    SciTech Connect

    Levinson, Ronnen; Akbari, Hashem; Berdahl, Paul

    2010-09-15

    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 US latitudes, this metric R{sub E891BN} can underestimate the annual peak solar heat gain of a typical roof or pavement (slope {<=} 5:12 [23 ]) 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. (author)

  8. 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

  9. 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

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

    PubMed

    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. Accurate, conformation-dependent predictions of solvent effects on protein ionization constants

    PubMed Central

    Barth, P.; Alber, T.; Harbury, P. B.

    2007-01-01

    Predicting how aqueous solvent modulates the conformational transitions and influences the pKa values that regulate the biological functions of biomolecules remains an unsolved challenge. To address this problem, we developed FDPB_MF, a rotamer repacking method that exhaustively samples side chain conformational space and rigorously calculates multibody protein–solvent interactions. FDPB_MF predicts the effects on pKa values of various solvent exposures, large ionic strength variations, strong energetic couplings, structural reorganizations and sequence mutations. The method achieves high accuracy, with root mean square deviations within 0.3 pH unit of the experimental values measured for turkey ovomucoid third domain, hen lysozyme, Bacillus circulans xylanase, and human and Escherichia coli thioredoxins. FDPB_MF provides a faithful, quantitative assessment of electrostatic interactions in biological macromolecules. PMID:17360348

  12. 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. PMID:27035143

  13. 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.

  14. 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

  15. 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.

  16. Predicted and experimental aerodynamic forces on the Darrieus rotor

    NASA Astrophysics Data System (ADS)

    Paraschivoiu, I.

    1983-12-01

    The present paper compares the aerodynamic loads predicted by a double-multiple-streamtube model with wind tunnel measurements for a straight-bladed Darrieus rotor. Thus the CARDAA computer code uses two constant-interference factors in the induced velocity for estimating the aerodynamic loads. This code has been improved by considering the variation in the upwind and downwind induced velocities as a function of the blade position, and, in this case, the CARDAAV code is used. The Boeing-Vertol dynamic-stall model is incorporated in both the CARDAA and CARDAAV codes, and a better approach is obtained. The transient normal- and tangential-force coefficients predicted with and without dynamic-stall effects are compared with wind tunnel data for one and two NACA 0018 straight-bladed rotors. The results are given for a rotor with a large solidity (chord-to-radius ratio of 0.20) at two tip-speed ratios (X = 1.5 and 3.0) and at a low Reynolds number of 3.8 x 10 to the 4th. The comparisons between experimental data and theoretical results show the CARDAAV predictions to be more accurate than those estimated by the CARDAA code.

  17. Development of a New Model for Accurate Prediction of Cloud Water Deposition on Vegetation

    NASA Astrophysics Data System (ADS)

    Katata, G.; Nagai, H.; Wrzesinsky, T.; Klemm, O.; Eugster, W.; Burkard, R.

    2006-12-01

    Scarcity of water resources in arid and semi-arid areas is of great concern in the light of population growth and food shortages. Several experiments focusing on cloud (fog) water deposition on the land surface suggest that cloud water plays an important role in water resource in such regions. A one-dimensional vegetation model including the process of cloud water deposition on vegetation has been developed to better predict cloud water deposition on the vegetation. New schemes to calculate capture efficiency of leaf, cloud droplet size distribution, and gravitational flux of cloud water were incorporated in the model. Model calculations were compared with the data acquired at the Norway spruce forest at the Waldstein site, Germany. High performance of the model was confirmed by comparisons of calculated net radiation, sensible and latent heat, and cloud water fluxes over the forest with measurements. The present model provided a better prediction of measured turbulent and gravitational fluxes of cloud water over the canopy than the Lovett model, which is a commonly used cloud water deposition model. Detailed calculations of evapotranspiration and of turbulent exchange of heat and water vapor within the canopy and the modifications are necessary for accurate prediction of cloud water deposition. Numerical experiments to examine the dependence of cloud water deposition on the vegetation species (coniferous and broad-leaved trees, flat and cylindrical grasses) and structures (Leaf Area Index (LAI) and canopy height) are performed using the presented model. The results indicate that the differences of leaf shape and size have a large impact on cloud water deposition. Cloud water deposition also varies with the growth of vegetation and seasonal change of LAI. We found that the coniferous trees whose height and LAI are 24 m and 2.0 m2m-2, respectively, produce the largest amount of cloud water deposition in all combinations of vegetation species and structures in the

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

    NASA Astrophysics Data System (ADS)

    Yogurtcu, Osman N.; Johnson, Margaret E.

    2015-08-01

    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

  19. 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.

  20. 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.

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

    PubMed Central

    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

  2. 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

  3. 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).

  4. 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). PMID:26430979

  5. nuMap: a web platform for accurate prediction of nucleosome positioning.

    PubMed

    Alharbi, Bader A; Alshammari, Thamir H; Felton, Nathan L; Zhurkin, Victor B; Cui, Feng

    2014-10-01

    Nucleosome positioning is critical for gene expression and of major biological interest. The high cost of experimentally mapping nucleosomal arrangement signifies the need for computational approaches to predict nucleosome positions at high resolution. Here, we present a web-based application to fulfill this need by implementing two models, YR and W/S schemes, for the translational and rotational positioning of nucleosomes, respectively. Our methods are based on sequence-dependent anisotropic bending that dictates how DNA is wrapped around a histone octamer. This application allows users to specify a number of options such as schemes and parameters for threading calculation and provides multiple layout formats. The nuMap is implemented in Java/Perl/MySQL and is freely available for public use at http://numap.rit.edu. The user manual, implementation notes, description of the methodology and examples are available at the site. PMID:25220945

  6. 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

  7. Prediction of velopharyngeal orifice area: a re-examination of model experimentation.

    PubMed

    Smith, B E; Weinberg, B

    1980-10-01

    Warren has advanced a modification of the hydrokinetic equation for predicting velopharyngeal orifice area (Warren and DuBois, 1964). In the present work, this equation was subjected to extensive controlled model experimentation. The results of this experimentation show that, given the pressure differential across the orifice and the rate of airflow through the orifice, accurate predictions can be made of the area of the velopharyngeal port. These results were interpreted to provide strong support for both clinical and research use of the hydrokinetic equation for predicting velopharyngeal orifice area.

  8. Prediction of velopharyngeal orifice area: a re-examination of model experimentation.

    PubMed

    Smith, B E; Weinberg, B

    1980-10-01

    Warren has advanced a modification of the hydrokinetic equation for predicting velopharyngeal orifice area (Warren and DuBois, 1964). In the present work, this equation was subjected to extensive controlled model experimentation. The results of this experimentation show that, given the pressure differential across the orifice and the rate of airflow through the orifice, accurate predictions can be made of the area of the velopharyngeal port. These results were interpreted to provide strong support for both clinical and research use of the hydrokinetic equation for predicting velopharyngeal orifice area. PMID:6934041

  9. 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. PMID:26944687

  10. Unilateral Prostate Cancer Cannot be Accurately Predicted in Low-Risk Patients

    SciTech Connect

    Isbarn, Hendrik; Karakiewicz, Pierre I.; Vogel, Susanne

    2010-07-01

    Purpose: Hemiablative therapy (HAT) is increasing in popularity for treatment of patients with low-risk prostate cancer (PCa). The validity of this therapeutic modality, which exclusively treats PCa within a single prostate lobe, rests on accurate staging. We tested the accuracy of unilaterally unremarkable biopsy findings in cases of low-risk PCa patients who are potential candidates for HAT. Methods and Materials: The study population consisted of 243 men with clinical stage {<=}T2a, a prostate-specific antigen (PSA) concentration of <10 ng/ml, a biopsy-proven Gleason sum of {<=}6, and a maximum of 2 ipsilateral positive biopsy results out of 10 or more cores. All men underwent a radical prostatectomy, and pathology stage was used as the gold standard. Univariable and multivariable logistic regression models were tested for significant predictors of unilateral, organ-confined PCa. These predictors consisted of PSA, %fPSA (defined as the quotient of free [uncomplexed] PSA divided by the total PSA), clinical stage (T2a vs. T1c), gland volume, and number of positive biopsy cores (2 vs. 1). Results: Despite unilateral stage at biopsy, bilateral or even non-organ-confined PCa was reported in 64% of all patients. In multivariable analyses, no variable could clearly and independently predict the presence of unilateral PCa. This was reflected in an overall accuracy of 58% (95% confidence interval, 50.6-65.8%). Conclusions: Two-thirds of patients with unilateral low-risk PCa, confirmed by clinical stage and biopsy findings, have bilateral or non-organ-confined PCa at radical prostatectomy. This alarming finding questions the safety and validity of HAT.

  11. Improving DOE-2's RESYS routine: User defined functions to provide more accurate part load energy use and humidity predictions

    SciTech Connect

    Henderson, Hugh I.; Parker, Danny; Huang, Yu J.

    2000-08-04

    In hourly energy simulations, it is important to properly predict the performance of air conditioning systems over a range of full and part load operating conditions. An important component of these calculations is to properly consider the performance of the cycling air conditioner and how it interacts with the building. This paper presents improved approaches to properly account for the part load performance of residential and light commercial air conditioning systems in DOE-2. First, more accurate correlations are given to predict the degradation of system efficiency at part load conditions. In addition, a user-defined function for RESYS is developed that provides improved predictions of air conditioner sensible and latent capacity at part load conditions. The user function also provides more accurate predictions of space humidity by adding ''lumped'' moisture capacitance into the calculations. The improved cooling coil model and the addition of moisture capacitance predicts humidity swings that are more representative of the performance observed in real buildings.

  12. 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.

  13. Computational finite element bone mechanics accurately predicts mechanical competence in the human radius of an elderly population.

    PubMed

    Mueller, Thomas L; Christen, David; Sandercott, Steve; Boyd, Steven K; van Rietbergen, Bert; Eckstein, Felix; Lochmüller, Eva-Maria; Müller, Ralph; van Lenthe, G Harry

    2011-06-01

    High-resolution peripheral quantitative computed tomography (HR-pQCT) is clinically available today and provides a non-invasive measure of 3D bone geometry and micro-architecture with unprecedented detail. In combination with microarchitectural finite element (μFE) models it can be used to determine bone strength using a strain-based failure criterion. Yet, images from only a relatively small part of the radius are acquired and it is not known whether the region recommended for clinical measurements does predict forearm fracture load best. Furthermore, it is questionable whether the currently used failure criterion is optimal because of improvements in image resolution, changes in the clinically measured volume of interest, and because the failure criterion depends on the amount of bone present. Hence, we hypothesized that bone strength estimates would improve by measuring a region closer to the subchondral plate, and by defining a failure criterion that would be independent of the measured volume of interest. To answer our hypotheses, 20% of the distal forearm length from 100 cadaveric but intact human forearms was measured using HR-pQCT. μFE bone strength was analyzed for different subvolumes, as well as for the entire 20% of the distal radius length. Specifically, failure criteria were developed that provided accurate estimates of bone strength as assessed experimentally. It was shown that distal volumes were better in predicting bone strength than more proximal ones. Clinically speaking, this would argue to move the volume of interest for the HR-pQCT measurements even more distally than currently recommended by the manufacturer. Furthermore, new parameter settings using the strain-based failure criterion are presented providing better accuracy for bone strength estimates.

  14. Lateral impact validation of a geometrically accurate full body finite element model for blunt injury prediction.

    PubMed

    Vavalle, Nicholas A; Moreno, Daniel P; Rhyne, Ashley C; Stitzel, Joel D; Gayzik, F Scott

    2013-03-01

    This study presents four validation cases of a mid-sized male (M50) full human body finite element model-two lateral sled tests at 6.7 m/s, one sled test at 8.9 m/s, and a lateral drop test. Model results were compared to transient force curves, peak force, chest compression, and number of fractures from the studies. For one of the 6.7 m/s impacts (flat wall impact), the peak thoracic, abdominal and pelvic loads were 8.7, 3.1 and 14.9 kN for the model and 5.2 ± 1.1 kN, 3.1 ± 1.1 kN, and 6.3 ± 2.3 kN for the tests. For the same test setup in the 8.9 m/s case, they were 12.6, 6, and 21.9 kN for the model and 9.1 ± 1.5 kN, 4.9 ± 1.1 kN, and 17.4 ± 6.8 kN for the experiments. The combined torso load and the pelvis load simulated in a second rigid wall impact at 6.7 m/s were 11.4 and 15.6 kN, respectively, compared to 8.5 ± 0.2 kN and 8.3 ± 1.8 kN experimentally. The peak thorax load in the drop test was 6.7 kN for the model, within the range in the cadavers, 5.8-7.4 kN. When analyzing rib fractures, the model predicted Abbreviated Injury Scale scores within the reported range in three of four cases. Objective comparison methods were used to quantitatively compare the model results to the literature studies. The results show a good match in the thorax and abdomen regions while the pelvis results over predicted the reaction loads from the literature studies. These results are an important milestone in the development and validation of this globally developed average male FEA model in lateral impact.

  15. Accurate prediction model of bead geometry in crimping butt of the laser brazing using generalized regression neural network

    NASA Astrophysics Data System (ADS)

    Rong, Y. M.; Chang, Y.; Huang, Y.; Zhang, G. J.; Shao, X. Y.

    2015-12-01

    There are few researches that concentrate on the prediction of the bead geometry for laser brazing with crimping butt. This paper addressed the accurate prediction of the bead profile by developing a generalized regression neural network (GRNN) algorithm. Firstly GRNN model was developed and trained to decrease the prediction error that may be influenced by the sample size. Then the prediction accuracy was demonstrated by comparing with other articles and back propagation artificial neural network (BPNN) algorithm. Eventually the reliability and stability of GRNN model were discussed from the points of average relative error (ARE), mean square error (MSE) and root mean square error (RMSE), while the maximum ARE and MSE were 6.94% and 0.0303 that were clearly less than those (14.28% and 0.0832) predicted by BPNN. Obviously, it was proved that the prediction accuracy was improved at least 2 times, and the stability was also increased much more.

  16. 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

  17. 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.

  18. A simple accurate method to predict time of ponding under variable intensity rainfall

    NASA Astrophysics Data System (ADS)

    Assouline, S.; Selker, J. S.; Parlange, J.-Y.

    2007-03-01

    The prediction of the time to ponding following commencement of rainfall is fundamental to hydrologic prediction of flood, erosion, and infiltration. Most of the studies to date have focused on prediction of ponding resulting from simple rainfall patterns. This approach was suitable to rainfall reported as average values over intervals of up to a day but does not take advantage of knowledge of the complex patterns of actual rainfall now commonly recorded electronically. A straightforward approach to include the instantaneous rainfall record in the prediction of ponding time and excess rainfall using only the infiltration capacity curve is presented. This method is tested against a numerical solution of the Richards equation on the basis of an actual rainfall record. The predicted time to ponding showed mean error ≤7% for a broad range of soils, with and without surface sealing. In contrast, the standard predictions had average errors of 87%, and worst-case errors exceeding a factor of 10. In addition to errors intrinsic in the modeling framework itself, errors that arise from averaging actual rainfall records over reporting intervals were evaluated. Averaging actual rainfall records observed in Israel over periods of as little as 5 min significantly reduced predicted runoff (75% for the sealed sandy loam and 46% for the silty clay loam), while hourly averaging gave complete lack of prediction of ponding in some of the cases.

  19. Combining Evolutionary Information and an Iterative Sampling Strategy for Accurate Protein Structure Prediction.

    PubMed

    Braun, Tatjana; Koehler Leman, Julia; Lange, Oliver F

    2015-12-01

    Recent work has shown that the accuracy of ab initio structure prediction can be significantly improved by integrating evolutionary information in form of intra-protein residue-residue contacts. Following this seminal result, much effort is put into the improvement of contact predictions. However, there is also a substantial need to develop structure prediction protocols tailored to the type of restraints gained by contact predictions. Here, we present a structure prediction protocol that combines evolutionary information with the resolution-adapted structural recombination approach of Rosetta, called RASREC. Compared to the classic Rosetta ab initio protocol, RASREC achieves improved sampling, better convergence and higher robustness against incorrect distance restraints, making it the ideal sampling strategy for the stated problem. To demonstrate the accuracy of our protocol, we tested the approach on a diverse set of 28 globular proteins. Our method is able to converge for 26 out of the 28 targets and improves the average TM-score of the entire benchmark set from 0.55 to 0.72 when compared to the top ranked models obtained by the EVFold web server using identical contact predictions. Using a smaller benchmark, we furthermore show that the prediction accuracy of our method is only slightly reduced when the contact prediction accuracy is comparatively low. This observation is of special interest for protein sequences that only have a limited number of homologs.

  20. 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

  1. 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?

  2. 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

  3. 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

  4. Change in body mass accurately and reliably predicts change in body water after endurance exercise.

    PubMed

    Baker, Lindsay B; Lang, James A; Kenney, W Larry

    2009-04-01

    This study tested the hypothesis that the change in body mass (DeltaBM) accurately reflects the change in total body water (DeltaTBW) after prolonged exercise. Subjects (4 men, 4 women; 22-36 year; 66 +/- 10 kg) completed 2 h of interval running (70% VO(2max)) in the heat (30 degrees C), followed by a run to exhaustion (85% VO(2max)), and then sat for a 1 h recovery period. During exercise and recovery, subjects drank fluid or no fluid to maintain their BM, increase BM by 2%, or decrease BM by 2 or 4% in separate trials. Pre- and post-experiment TBW were determined using the deuterium oxide (D(2)O) dilution technique and corrected for D(2)O lost in urine, sweat, breath vapor, and nonaqueous hydrogen exchange. The average difference between DeltaBM and DeltaTBW was 0.07 +/- 1.07 kg (paired t test, P = 0.29). The slope and intercept of the relation between DeltaBM and DeltaTBW were not significantly different from 1 and 0, respectively. The intraclass correlation coefficient between DeltaBM and DeltaTBW was 0.76, which is indicative of excellent reliability between methods. Measuring pre- to post-exercise DeltaBM is an accurate and reliable method to assess the DeltaTBW.

  5. Towards Accurate Residue-Residue Hydrophobic Contact Prediction for Alpha Helical Proteins Via Integer Linear Optimization

    PubMed Central

    Rajgaria, R.; McAllister, S. R.; Floudas, C. A.

    2008-01-01

    A new optimization-based method is presented to predict the hydrophobic residue contacts in α-helical proteins. The proposed approach uses a high resolution distance dependent force field to calculate the interaction energy between different residues of a protein. The formulation predicts the hydrophobic contacts by minimizing the sum of these contact energies. These residue contacts are highly useful in narrowing down the conformational space searched by protein structure prediction algorithms. The proposed algorithm also offers the algorithmic advantage of producing a rank ordered list of the best contact sets. This model was tested on four independent α-helical protein test sets and was found to perform very well. The average accuracy of the predictions (separated by at least six residues) obtained using the presented method was approximately 66% for single domain proteins. The average true positive and false positive distances were also calculated for each protein test set and they are 8.87 Å and 14.67 Å respectively. PMID:18767158

  6. Accurate prediction of kidney allograft outcome based on creatinine course in the first 6 months posttransplant.

    PubMed

    Fritsche, L; Hoerstrup, J; Budde, K; Reinke, P; Neumayer, H-H; Frei, U; Schlaefer, A

    2005-03-01

    Most attempts to predict early kidney allograft loss are based on the patient and donor characteristics at baseline. We investigated how the early posttransplant creatinine course compares to baseline information in the prediction of kidney graft failure within the first 4 years after transplantation. Two approaches to create a prediction rule for early graft failure were evaluated. First, the whole data set was analysed using a decision-tree building software. The software, rpart, builds classification or regression models; the resulting models can be represented as binary trees. In the second approach, a Hill-Climbing algorithm was applied to define cut-off values for the median creatinine level and creatinine slope in the period between day 60 and 180 after transplantation. Of the 497 patients available for analysis, 52 (10.5%) experienced an early graft loss (graft loss within the first 4 years after transplantation). From the rpart algorithm, a single decision criterion emerged: Median creatinine value on days 60 to 180 higher than 3.1 mg/dL predicts early graft failure (accuracy 95.2% but sensitivity = 42.3%). In contrast, the Hill-Climbing algorithm delivered a cut-off of 1.8 mg/dL for the median creatinine level and a cut-off of 0.3 mg/dL per month for the creatinine slope (sensitivity = 69.5% and specificity 79.0%). Prediction rules based on median and slope of creatinine levels in the first half year after transplantation allow early identification of patients who are at risk of loosing their graft early after transplantation. These patients may benefit from therapeutic measures tailored for this high-risk setting. PMID:15848516

  7. Accurate Prediction of Transposon-Derived piRNAs by Integrating Various Sequential and Physicochemical Features

    PubMed Central

    Luo, Longqiang; Li, Dingfang; Zhang, Wen; Tu, Shikui; Zhu, Xiaopeng; Tian, Gang

    2016-01-01

    Background Piwi-interacting RNA (piRNA) is the largest class of small non-coding RNA molecules. The transposon-derived piRNA prediction can enrich the research contents of small ncRNAs as well as help to further understand generation mechanism of gamete. Methods In this paper, we attempt to differentiate transposon-derived piRNAs from non-piRNAs based on their sequential and physicochemical features by using machine learning methods. We explore six sequence-derived features, i.e. spectrum profile, mismatch profile, subsequence profile, position-specific scoring matrix, pseudo dinucleotide composition and local structure-sequence triplet elements, and systematically evaluate their performances for transposon-derived piRNA prediction. Finally, we consider two approaches: direct combination and ensemble learning to integrate useful features and achieve high-accuracy prediction models. Results We construct three datasets, covering three species: Human, Mouse and Drosophila, and evaluate the performances of prediction models by 10-fold cross validation. In the computational experiments, direct combination models achieve AUC of 0.917, 0.922 and 0.992 on Human, Mouse and Drosophila, respectively; ensemble learning models achieve AUC of 0.922, 0.926 and 0.994 on the three datasets. Conclusions Compared with other state-of-the-art methods, our methods can lead to better performances. In conclusion, the proposed methods are promising for the transposon-derived piRNA prediction. The source codes and datasets are available in S1 File. PMID:27074043

  8. Accurate metal-site structures in proteins obtained by combining experimental data and quantum chemistry.

    PubMed

    Ryde, Ulf

    2007-02-14

    The use of molecular mechanics calculations to supplement experimental data in standard X-ray crystallography and NMR refinements is discussed and it is shown that structures can be locally improved by the use of quantum chemical calculations. Such calculations can also be used to interpret the structures, e.g. to decide the protonation state of metal-bound ligands. They have shown that metal sites in crystal structures are frequently photoreduced or disordered, which makes the interpretation of the structures hard. Similar methods can be used for EXAFS refinements to obtain a full atomic structure, rather than a set of metal-ligand distances.

  9. 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

  10. 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

  11. 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

    2015-08-01

    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.

  12. HAAD: A quick algorithm for accurate prediction of hydrogen atoms in protein structures.

    PubMed

    Li, Yunqi; Roy, Ambrish; Zhang, Yang

    2009-08-20

    Hydrogen constitutes nearly half of all atoms in proteins and their positions are essential for analyzing hydrogen-bonding interactions and refining atomic-level structures. However, most protein structures determined by experiments or computer prediction lack hydrogen coordinates. We present a new algorithm, HAAD, to predict the positions of hydrogen atoms based on the positions of heavy atoms. The algorithm is built on the basic rules of orbital hybridization followed by the optimization of steric repulsion and electrostatic interactions. We tested the algorithm using three independent data sets: ultra-high-resolution X-ray structures, structures determined by neutron diffraction, and NOE proton-proton distances. Compared with the widely used programs CHARMM and REDUCE, HAAD has a significantly higher accuracy, with the average RMSD of the predicted hydrogen atoms to the X-ray and neutron diffraction structures decreased by 26% and 11%, respectively. Furthermore, hydrogen atoms placed by HAAD have more matches with the NOE restraints and fewer clashes with heavy atoms. The average CPU cost by HAAD is 18 and 8 times lower than that of CHARMM and REDUCE, respectively. The significant advantage of HAAD in both the accuracy and the speed of the hydrogen additions should make HAAD a useful tool for the detailed study of protein structure and function. Both an executable and the source code of HAAD are freely available at http://zhang.bioinformatics.ku.edu/HAAD.

  13. Accurate single-sequence prediction of solvent accessible surface area using local and global features.

    PubMed

    Faraggi, Eshel; Zhou, Yaoqi; Kloczkowski, Andrzej

    2014-11-01

    We present a new approach for predicting the Accessible Surface Area (ASA) using a General Neural Network (GENN). The novelty of the new approach lies in not using residue mutation profiles generated by multiple sequence alignments as descriptive inputs. Instead we use solely sequential window 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 tested on predicting the ASA of globular proteins and 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 GENN and ASAquick are available from Research and Information Systems at http://mamiris.com, from the SPARKS Lab at http://sparks-lab.org, and from the Battelle Center for Mathematical Medicine at http://mathmed.org. PMID:25204636

  14. 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.

  15. Accurate prediction of interfacial residues in two-domain proteins using evolutionary information: implications for three-dimensional modeling.

    PubMed

    Bhaskara, Ramachandra M; Padhi, Amrita; Srinivasan, Narayanaswamy

    2014-07-01

    With the preponderance of multidomain proteins in eukaryotic genomes, it is essential to recognize the constituent domains and their functions. Often function involves communications across the domain interfaces, and the knowledge of the interacting sites is essential to our understanding of the structure-function relationship. Using evolutionary information extracted from homologous domains in at least two diverse domain architectures (single and multidomain), we predict the interface residues corresponding to domains from the two-domain proteins. We also use information from the three-dimensional structures of individual domains of two-domain proteins to train naïve Bayes classifier model to predict the interfacial residues. Our predictions are highly accurate (∼85%) and specific (∼95%) to the domain-domain interfaces. This method is specific to multidomain proteins which contain domains in at least more than one protein architectural context. Using predicted residues to constrain domain-domain interaction, rigid-body docking was able to provide us with accurate full-length protein structures with correct orientation of domains. We believe that these results can be of considerable interest toward rational protein and interaction design, apart from providing us with valuable information on the nature of interactions.

  16. An experimental correction proposed for an accurate determination of mass diffusivity of wood in steady regime

    NASA Astrophysics Data System (ADS)

    Zohoun, Sylvain; Agoua, Eusèbe; Degan, Gérard; Perre, Patrick

    2002-08-01

    This paper presents an experimental study of the mass diffusion in the hygroscopic region of four temperate species and three tropical ones. In order to simplify the interpretation of the phenomena, a dimensionless parameter called reduced diffusivity is defined. This parameter varies from 0 to 1. The method used is firstly based on the determination of that parameter from results of the measurement of the mass flux which takes into account the conditions of operating standard device (tightness, dimensional variations and easy installation of samples of wood, good stability of temperature and humidity). Secondly the reasons why that parameter has to be corrected are presented. An abacus for this correction of mass diffusivity of wood in steady regime has been plotted. This work constitutes an advanced deal nowadays for characterising forest species.

  17. Comparative motif discovery combined with comparative transcriptomics yields accurate targetome and enhancer predictions.

    PubMed

    Naval-Sánchez, Marina; Potier, Delphine; Haagen, Lotte; Sánchez, Máximo; Munck, Sebastian; Van de Sande, Bram; Casares, Fernando; Christiaens, Valerie; Aerts, Stein

    2013-01-01

    The identification of transcription factor binding sites, enhancers, and transcriptional target genes often relies on the integration of gene expression profiling and computational cis-regulatory sequence analysis. Methods for the prediction of cis-regulatory elements can take advantage of comparative genomics to increase signal-to-noise levels. However, gene expression data are usually derived from only one species. Here we investigate tissue-specific cross-species gene expression profiling by high-throughput sequencing, combined with cross-species motif discovery. First, we compared different methods for expression level quantification and cross-species integration using Tag-seq data. Using the optimal pipeline, we derived a set of genes with conserved expression during retinal determination across Drosophila melanogaster, Drosophila yakuba, and Drosophila virilis. These genes are enriched for binding sites of eye-related transcription factors including the zinc-finger Glass, a master regulator of photoreceptor differentiation. Validation of predicted Glass targets using RNA-seq in homozygous glass mutants confirms that the majority of our predictions are expressed downstream from Glass. Finally, we tested nine candidate enhancers by in vivo reporter assays and found eight of them to drive GFP in the eye disc, of which seven colocalize with the Glass protein, namely, scrt, chp, dpr10, CG6329, retn, Lim3, and dmrt99B. In conclusion, we show for the first time the combined use of cross-species expression profiling with cross-species motif discovery as a method to define a core developmental program, and we augment the candidate Glass targetome from a single known target gene, lozenge, to at least 62 conserved transcriptional targets. PMID:23070853

  18. PSI: A Comprehensive and Integrative Approach for Accurate Plant Subcellular Localization Prediction

    PubMed Central

    Chen, Ming

    2013-01-01

    Predicting the subcellular localization of proteins conquers the major drawbacks of high-throughput localization experiments that are costly and time-consuming. However, current subcellular localization predictors are limited in scope and accuracy. In particular, most predictors perform well on certain locations or with certain data sets while poorly on others. Here, we present PSI, a novel high accuracy web server for plant subcellular localization prediction. PSI derives the wisdom of multiple specialized predictors via a joint-approach of group decision making strategy and machine learning methods to give an integrated best result. The overall accuracy obtained (up to 93.4%) was higher than best individual (CELLO) by ∼10.7%. The precision of each predicable subcellular location (more than 80%) far exceeds that of the individual predictors. It can also deal with multi-localization proteins. PSI is expected to be a powerful tool in protein location engineering as well as in plant sciences, while the strategy employed could be applied to other integrative problems. A user-friendly web server, PSI, has been developed for free access at http://bis.zju.edu.cn/psi/. PMID:24194827

  19. CRYSpred: accurate sequence-based protein crystallization propensity prediction using sequence-derived structural characteristics.

    PubMed

    Mizianty, Marcin J; Kurgan, Lukasz A

    2012-01-01

    Relatively low success rates of X-ray crystallography, which is the most popular method for solving proteins structures, motivate development of novel methods that support selection of tractable protein targets. This aspect is particularly important in the context of the current structural genomics efforts that allow for a certain degree of flexibility in the target selection. We propose CRYSpred, a novel in-silico crystallization propensity predictor that uses a set of 15 novel features which utilize a broad range of inputs including charge, hydrophobicity, and amino acid composition derived from the protein chain, and the solvent accessibility and disorder predicted from the protein sequence. Our method outperforms seven modern crystallization propensity predictors on three, independent from training dataset, benchmark test datasets. The strong predictive performance offered by the CRYSpred is attributed to the careful design of the features, utilization of the comprehensive set of inputs, and the usage of the Support Vector Machine classifier. The inputs utilized by CRYSpred are well-aligned with the existing rules-of-thumb that are used in the structural genomics studies. PMID:21919861

  20. CRYSpred: accurate sequence-based protein crystallization propensity prediction using sequence-derived structural characteristics.

    PubMed

    Mizianty, Marcin J; Kurgan, Lukasz A

    2012-01-01

    Relatively low success rates of X-ray crystallography, which is the most popular method for solving proteins structures, motivate development of novel methods that support selection of tractable protein targets. This aspect is particularly important in the context of the current structural genomics efforts that allow for a certain degree of flexibility in the target selection. We propose CRYSpred, a novel in-silico crystallization propensity predictor that uses a set of 15 novel features which utilize a broad range of inputs including charge, hydrophobicity, and amino acid composition derived from the protein chain, and the solvent accessibility and disorder predicted from the protein sequence. Our method outperforms seven modern crystallization propensity predictors on three, independent from training dataset, benchmark test datasets. The strong predictive performance offered by the CRYSpred is attributed to the careful design of the features, utilization of the comprehensive set of inputs, and the usage of the Support Vector Machine classifier. The inputs utilized by CRYSpred are well-aligned with the existing rules-of-thumb that are used in the structural genomics studies.

  1. Numerical prediction of freezing fronts in cryosurgery: comparison with experimental results.

    PubMed

    Fortin, André; Belhamadia, Youssef

    2005-08-01

    Recent developments in scientific computing now allow to consider realistic applications of numerical modelling to medicine. In this work, a numerical method is presented for the simulation of phase change occurring in cryosurgery applications. The ultimate goal of these simulations is to accurately predict the freezing front position and the thermal history inside the ice ball which is essential to determine if cancerous cells have been completely destroyed. A semi-phase field formulation including blood flow considerations is employed for the simulations. Numerical results are enhanced by the introduction of an anisotropic remeshing strategy. The numerical procedure is validated by comparing the predictions of the model with experimental results. PMID:16298846

  2. 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.

  3. Accurate predictions of dielectrophoretic force and torque on particles with strong mutual field, particle, and wall interactions

    NASA Astrophysics Data System (ADS)

    Liu, Qianlong; Reifsnider, Kenneth

    2012-11-01

    The basis of dielectrophoresis (DEP) is the prediction of the force and torque on particles. The classical approach to the prediction is based on the effective moment method, which, however, is an approximate approach, assumes infinitesimal particles. Therefore, it is well-known that for finite-sized particles, the DEP approximation is inaccurate as the mutual field, particle, wall interactions become strong, a situation presently attracting extensive research for practical significant applications. In the present talk, we provide accurate calculations of the force and torque on the particles from first principles, by directly resolving the local geometry and properties and accurately accounting for the mutual interactions for finite-sized particles with both dielectric polarization and conduction in a sinusoidally steady-state electric field. Since the approach has a significant advantage, compared to other numerical methods, to efficiently simulate many closely packed particles, it provides an important, unique, and accurate technique to investigate complex DEP phenomena, for example heterogeneous mixtures containing particle chains, nanoparticle assembly, biological cells, non-spherical effects, etc. This study was supported by the Department of Energy under funding for an EFRC (the HeteroFoaM Center), grant no. DE-SC0001061.

  4. 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.

  5. 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.

  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. A novel method to predict visual field progression more accurately, using intraocular pressure measurements in glaucoma patients

    PubMed Central

    Asaoka, Ryo; Fujino, Yuri; Murata, Hiroshi; Miki, Atsuya; Tanito, Masaki; Mizoue, Shiro; Mori, Kazuhiko; Suzuki, Katsuyoshi; Yamashita, Takehiro; Kashiwagi, Kenji; Shoji, Nobuyuki

    2016-01-01

    Visual field (VF) data were retrospectively obtained from 491 eyes in 317 patients with open angle glaucoma who had undergone ten VF tests (Humphrey Field Analyzer, 24-2, SITA standard). First, mean of total deviation values (mTD) in the tenth VF was predicted using standard linear regression of the first five VFs (VF1-5) through to using all nine preceding VFs (VF1-9). Then an ‘intraocular pressure (IOP)-integrated VF trend analysis’ was carried out by simply using time multiplied by IOP as the independent term in the linear regression model. Prediction errors (absolute prediction error or root mean squared error: RMSE) for predicting mTD and also point wise TD values of the tenth VF were obtained from both approaches. The mTD absolute prediction errors associated with the IOP-integrated VF trend analysis were significantly smaller than those from the standard trend analysis when VF1-6 through to VF1-8 were used (p < 0.05). The point wise RMSEs from the IOP-integrated trend analysis were significantly smaller than those from the standard trend analysis when VF1-5 through to VF1-9 were used (p < 0.05). This was especially the case when IOP was measured more frequently. Thus a significantly more accurate prediction of VF progression is possible using a simple trend analysis that incorporates IOP measurements. PMID:27562553

  8. A novel method to predict visual field progression more accurately, using intraocular pressure measurements in glaucoma patients.

    PubMed

    2016-01-01

    Visual field (VF) data were retrospectively obtained from 491 eyes in 317 patients with open angle glaucoma who had undergone ten VF tests (Humphrey Field Analyzer, 24-2, SITA standard). First, mean of total deviation values (mTD) in the tenth VF was predicted using standard linear regression of the first five VFs (VF1-5) through to using all nine preceding VFs (VF1-9). Then an 'intraocular pressure (IOP)-integrated VF trend analysis' was carried out by simply using time multiplied by IOP as the independent term in the linear regression model. Prediction errors (absolute prediction error or root mean squared error: RMSE) for predicting mTD and also point wise TD values of the tenth VF were obtained from both approaches. The mTD absolute prediction errors associated with the IOP-integrated VF trend analysis were significantly smaller than those from the standard trend analysis when VF1-6 through to VF1-8 were used (p < 0.05). The point wise RMSEs from the IOP-integrated trend analysis were significantly smaller than those from the standard trend analysis when VF1-5 through to VF1-9 were used (p < 0.05). This was especially the case when IOP was measured more frequently. Thus a significantly more accurate prediction of VF progression is possible using a simple trend analysis that incorporates IOP measurements. PMID:27562553

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. Four-protein signature accurately predicts lymph node metastasis and survival in oral squamous cell carcinoma.

    PubMed

    Zanaruddin, Sharifah Nurain Syed; Saleh, Amyza; Yang, Yi-Hsin; Hamid, Sharifah; Mustafa, Wan Mahadzir Wan; Khairul Bariah, A A N; Zain, Rosnah Binti; Lau, Shin Hin; Cheong, Sok Ching

    2013-03-01

    The presence of lymph node (LN) metastasis significantly affects the survival of patients with oral squamous cell carcinoma (OSCC). Successful detection and removal of positive LNs are crucial in the treatment of this disease. Current evaluation methods still have their limitations in detecting the presence of tumor cells in the LNs, where up to a third of clinically diagnosed metastasis-negative (N0) patients actually have metastasis-positive LNs in the neck. We developed a molecular signature in the primary tumor that could predict LN metastasis in OSCC. A total of 211 cores from 55 individuals were included in the study. Eleven proteins were evaluated using immunohistochemical analysis in a tissue microarray. Of the 11 biomarkers evaluated using receiver operating curve analysis, epidermal growth factor receptor (EGFR), v-erb-b2 erythroblastic leukemia viral oncogene homolog 2 (HER-2/neu), laminin, gamma 2 (LAMC2), and ras homolog family member C (RHOC) were found to be significantly associated with the presence of LN metastasis. Unsupervised hierarchical clustering-demonstrated expression patterns of these 4 proteins could be used to differentiate specimens that have positive LN metastasis from those that are negative for LN metastasis. Collectively, EGFR, HER-2/neu, LAMC2, and RHOC have a specificity of 87.5% and a sensitivity of 70%, with a prognostic accuracy of 83.4% for LN metastasis. We also demonstrated that the LN signature could independently predict disease-specific survival (P = .036). The 4-protein LN signature validated in an independent set of samples strongly suggests that it could reliably distinguish patients with LN metastasis from those who were metastasis-free and therefore could be a prognostic tool for the management of patients with OSCC.

  14. Four-protein signature accurately predicts lymph node metastasis and survival in oral squamous cell carcinoma.

    PubMed

    Zanaruddin, Sharifah Nurain Syed; Saleh, Amyza; Yang, Yi-Hsin; Hamid, Sharifah; Mustafa, Wan Mahadzir Wan; Khairul Bariah, A A N; Zain, Rosnah Binti; Lau, Shin Hin; Cheong, Sok Ching

    2013-03-01

    The presence of lymph node (LN) metastasis significantly affects the survival of patients with oral squamous cell carcinoma (OSCC). Successful detection and removal of positive LNs are crucial in the treatment of this disease. Current evaluation methods still have their limitations in detecting the presence of tumor cells in the LNs, where up to a third of clinically diagnosed metastasis-negative (N0) patients actually have metastasis-positive LNs in the neck. We developed a molecular signature in the primary tumor that could predict LN metastasis in OSCC. A total of 211 cores from 55 individuals were included in the study. Eleven proteins were evaluated using immunohistochemical analysis in a tissue microarray. Of the 11 biomarkers evaluated using receiver operating curve analysis, epidermal growth factor receptor (EGFR), v-erb-b2 erythroblastic leukemia viral oncogene homolog 2 (HER-2/neu), laminin, gamma 2 (LAMC2), and ras homolog family member C (RHOC) were found to be significantly associated with the presence of LN metastasis. Unsupervised hierarchical clustering-demonstrated expression patterns of these 4 proteins could be used to differentiate specimens that have positive LN metastasis from those that are negative for LN metastasis. Collectively, EGFR, HER-2/neu, LAMC2, and RHOC have a specificity of 87.5% and a sensitivity of 70%, with a prognostic accuracy of 83.4% for LN metastasis. We also demonstrated that the LN signature could independently predict disease-specific survival (P = .036). The 4-protein LN signature validated in an independent set of samples strongly suggests that it could reliably distinguish patients with LN metastasis from those who were metastasis-free and therefore could be a prognostic tool for the management of patients with OSCC. PMID:23026198

  15. 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.

  16. Accurate predictions of C-SO2R bond dissociation enthalpies using density functional theory methods.

    PubMed

    Yu, Hai-Zhu; Fu, Fang; Zhang, Liang; Fu, Yao; Dang, Zhi-Min; Shi, Jing

    2014-10-14

    The dissociation of the C-SO2R bond is frequently involved in organic and bio-organic reactions, and the C-SO2R bond dissociation enthalpies (BDEs) are potentially important for understanding the related mechanisms. The primary goal of the present study is to provide a reliable calculation method to predict the different C-SO2R bond dissociation enthalpies (BDEs). Comparing the accuracies of 13 different density functional theory (DFT) methods (such as B3LYP, TPSS, and M05 etc.), and different basis sets (such as 6-31G(d) and 6-311++G(2df,2p)), we found that M06-2X/6-31G(d) gives the best performance in reproducing the various C-S BDEs (and especially the C-SO2R BDEs). As an example for understanding the mechanisms with the aid of C-SO2R BDEs, some primary mechanistic studies were carried out on the chemoselective coupling (in the presence of a Cu-catalyst) or desulfinative coupling reactions (in the presence of a Pd-catalyst) between sulfinic acid salts and boryl/sulfinic acid salts.

  17. 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.

  18. An improved method for accurate prediction of mass flows through combustor liner holes

    SciTech Connect

    Adkins, R.C.; Gueroui, D.

    1986-01-01

    The objective of this paper is to present a simple approach to the solution of flow through combustor liner holes which can be used by practicing combustor engineers as well as providing the specialist modeler with a convenient boundary condition. For modeling, suppose that all relevant details of the incoming jets can be readily predicted, then the computational boundary can be limited to the inner wall of the liner and to the jets themselves. The scope of this paper is limited to the derivation of a simple analysis, the development of a reliable test technique, and to the correlation of data for plane holes having a diameter which is large when compared to the liner wall thickness. The effect of internal liner flow on the performance of the holes is neglected; this is considered to be justifiable because the analysis terminates at a short distance downstream of the hole and the significantly lower velocities inside the combustor have had little opportunity to have taken any effect. It is intended to extend the procedure to more complex hole forms and flow configurations in later papers.

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

    NASA Astrophysics Data System (ADS)

    Balabin, Roman M.; Lomakina, Ekaterina I.

    2009-08-01

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

  20. Line Shape Parameters for CO_2 Transitions: Accurate Predictions from Complex Robert-Bonamy Calculations

    NASA Astrophysics Data System (ADS)

    Lamouroux, Julien; Gamache, Robert R.

    2013-06-01

    A model for the prediction of the vibrational dependence of CO_2 half-widths and line shifts for several broadeners, based on a modification of the model proposed by Gamache and Hartmann, is presented. This model allows the half-widths and line shifts for a ro-vibrational transition to be expressed in terms of the number of vibrational quanta exchanged in the transition raised to a power p and a reference ro-vibrational transition. Complex Robert-Bonamy calculations were made for 24 bands for lower rotational quantum numbers J'' from 0 to 160 for N_2-, O_2-, air-, and self-collisions with CO_2. In the model a Quantum Coordinate is defined by (c_1 Δν_1 + c_2 Δν_2 + c_3 Δν_3)^p where a linear least-squares fit to the data by the model expression is made. The model allows the determination of the slope and intercept as a function of rotational transition, broadening gas, and temperature. From these fit data, the half-width, line shift, and the temperature dependence of the half-width can be estimated for any ro-vibrational transition, allowing spectroscopic CO_2 databases to have complete information for the line shape parameters. R. R. Gamache, J.-M. Hartmann, J. Quant. Spectrosc. Radiat. Transfer. {{83}} (2004), 119. R. R. Gamache, J. Lamouroux, J. Quant. Spectrosc. Radiat. Transfer. {{117}} (2013), 93.

  1. 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.

  2. Mathematical model accurately predicts protein release from an affinity-based delivery system.

    PubMed

    Vulic, Katarina; Pakulska, Malgosia M; Sonthalia, Rohit; Ramachandran, Arun; Shoichet, Molly S

    2015-01-10

    Affinity-based controlled release modulates the delivery of protein or small molecule therapeutics through transient dissociation/association. To understand which parameters can be used to tune release, we used a mathematical model based on simple binding kinetics. A comprehensive asymptotic analysis revealed three characteristic regimes for therapeutic release from affinity-based systems. These regimes can be controlled by diffusion or unbinding kinetics, and can exhibit release over either a single stage or two stages. This analysis fundamentally changes the way we think of controlling release from affinity-based systems and thereby explains some of the discrepancies in the literature on which parameters influence affinity-based release. The rate of protein release from affinity-based systems is determined by the balance of diffusion of the therapeutic agent through the hydrogel and the dissociation kinetics of the affinity pair. Equations for tuning protein release rate by altering the strength (KD) of the affinity interaction, the concentration of binding ligand in the system, the rate of dissociation (koff) of the complex, and the hydrogel size and geometry, are provided. We validated our model by collapsing the model simulations and the experimental data from a recently described affinity release system, to a single master curve. Importantly, this mathematical analysis can be applied to any single species affinity-based system to determine the parameters required for a desired release profile. PMID:25449806

  3. 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.

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

    PubMed Central

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

    2015-01-01

    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

  5. 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.

  6. 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

  7. 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

  8. An Accurate Method for Prediction of Protein-Ligand Binding Site on Protein Surface Using SVM and Statistical Depth Function

    PubMed Central

    Wang, Kui; Gao, Jianzhao; Shen, Shiyi; Tuszynski, Jack A.; Ruan, Jishou

    2013-01-01

    Since proteins carry out their functions through interactions with other molecules, accurately identifying the protein-ligand binding site plays an important role in protein functional annotation and rational drug discovery. In the past two decades, a lot of algorithms were present to predict the protein-ligand binding site. In this paper, we introduce statistical depth function to define negative samples and propose an SVM-based method which integrates sequence and structural information to predict binding site. The results show that the present method performs better than the existent ones. The accuracy, sensitivity, and specificity on training set are 77.55%, 56.15%, and 87.96%, respectively; on the independent test set, the accuracy, sensitivity, and specificity are 80.36%, 53.53%, and 92.38%, respectively. PMID:24195070

  9. 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.

  10. 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

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

    PubMed

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

    2012-09-01

    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.

  12. Why don't we learn to accurately forecast feelings? How misremembering our predictions blinds us to past forecasting errors.

    PubMed

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

    2010-11-01

    Why do affective forecasting errors persist in the face of repeated disconfirming evidence? Five studies demonstrate that people misremember their forecasts as consistent with their experience and thus fail to perceive the extent of their forecasting error. As a result, people do not learn from past forecasting errors and fail to adjust subsequent forecasts. In the context of a Super Bowl loss (Study 1), a presidential election (Studies 2 and 3), an important purchase (Study 4), and the consumption of candies (Study 5), individuals mispredicted their affective reactions to these experiences and subsequently misremembered their predictions as more accurate than they actually had been. The findings indicate that this recall error results from people's tendency to anchor on their current affective state when trying to recall their affective forecasts. Further, those who showed larger recall errors were less likely to learn to adjust their subsequent forecasts and reminding people of their actual forecasts enhanced learning. These results suggest that a failure to accurately recall one's past predictions contributes to the perpetuation of forecasting errors.

  13. 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.

  14. 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

  15. 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

    2016-01-01

    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

  16. Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions.

    PubMed

    Zuñiga, Cristal; Li, Chien-Ting; Huelsman, Tyler; Levering, Jennifer; Zielinski, Daniel C; McConnell, Brian O; Long, Christopher P; Knoshaug, Eric P; Guarnieri, Michael T; Antoniewicz, Maciek R; Betenbaugh, Michael J; Zengler, Karsten

    2016-09-01

    The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. PMID:27372244

  17. A simple yet accurate correction for winner's curse can predict signals discovered in much larger genome scans

    PubMed Central

    Bigdeli, T. Bernard; Lee, Donghyung; Webb, Bradley Todd; Riley, Brien P.; Vladimirov, Vladimir I.; Fanous, Ayman H.; Kendler, Kenneth S.; Bacanu, Silviu-Alin

    2016-01-01

    Motivation: For genetic studies, statistically significant variants explain far less trait variance than ‘sub-threshold’ association signals. To dimension follow-up studies, researchers need to accurately estimate ‘true’ effect sizes at each SNP, e.g. the true mean of odds ratios (ORs)/regression coefficients (RRs) or Z-score noncentralities. Naïve estimates of effect sizes incur winner’s curse biases, which are reduced only by laborious winner’s curse adjustments (WCAs). Given that Z-scores estimates can be theoretically translated on other scales, we propose a simple method to compute WCA for Z-scores, i.e. their true means/noncentralities. Results:WCA of Z-scores shrinks these towards zero while, on P-value scale, multiple testing adjustment (MTA) shrinks P-values toward one, which corresponds to the zero Z-score value. Thus, WCA on Z-scores scale is a proxy for MTA on P-value scale. Therefore, to estimate Z-score noncentralities for all SNPs in genome scans, we propose FDR Inverse Quantile Transformation (FIQT). It (i) performs the simpler MTA of P-values using FDR and (ii) obtains noncentralities by back-transforming MTA P-values on Z-score scale. When compared to competitors, realistic simulations suggest that FIQT is more (i) accurate and (ii) computationally efficient by orders of magnitude. Practical application of FIQT to Psychiatric Genetic Consortium schizophrenia cohort predicts a non-trivial fraction of sub-threshold signals which become significant in much larger supersamples. Conclusions: FIQT is a simple, yet accurate, WCA method for Z-scores (and ORs/RRs, via simple transformations). Availability and Implementation: A 10 lines R function implementation is available at https://github.com/bacanusa/FIQT. Contact: sabacanu@vcu.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27187203

  18. Small-scale field experiments accurately scale up to predict density dependence in reef fish populations at large scales.

    PubMed

    Steele, Mark A; Forrester, Graham E

    2005-09-20

    Field experiments provide rigorous tests of ecological hypotheses but are usually limited to small spatial scales. It is thus unclear whether these findings extrapolate to larger scales relevant to conservation and management. We show that the results of experiments detecting density-dependent mortality of reef fish on small habitat patches scale up to have similar effects on much larger entire reefs that are the size of small marine reserves and approach the scale at which some reef fisheries operate. We suggest that accurate scaling is due to the type of species interaction causing local density dependence and the fact that localized events can be aggregated to describe larger-scale interactions with minimal distortion. Careful extrapolation from small-scale experiments identifying species interactions and their effects should improve our ability to predict the outcomes of alternative management strategies for coral reef fishes and their habitats.

  19. Effects of the inlet conditions and blood models on accurate prediction of hemodynamics in the stented coronary arteries

    NASA Astrophysics Data System (ADS)

    Jiang, Yongfei; Zhang, Jun; Zhao, Wanhua

    2015-05-01

    Hemodynamics altered by stent implantation is well-known to be closely related to in-stent restenosis. Computational fluid dynamics (CFD) method has been used to investigate the hemodynamics in stented arteries in detail and help to analyze the performances of stents. In this study, blood models with Newtonian or non-Newtonian properties were numerically investigated for the hemodynamics at steady or pulsatile inlet conditions respectively employing CFD based on the finite volume method. The results showed that the blood model with non-Newtonian property decreased the area of low wall shear stress (WSS) compared with the blood model with Newtonian property and the magnitude of WSS varied with the magnitude and waveform of the inlet velocity. The study indicates that the inlet conditions and blood models are all important for accurately predicting the hemodynamics. This will be beneficial to estimate the performances of stents and also help clinicians to select the proper stents for the patients.

  20. 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

  1. 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.

  2. 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. PMID:26267496

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

    NASA Astrophysics Data System (ADS)

    Zheng-Johansson, J. X.

    2010-03-01

    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, Schrödinger 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.

  4. 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.

  5. Evaluation of CFD Turbulent Heating Prediction Techniques and Comparison With Hypersonic Experimental Data

    NASA Technical Reports Server (NTRS)

    Dilley, Arthur D.; McClinton, Charles R. (Technical Monitor)

    2001-01-01

    Results from a study to assess the accuracy of turbulent heating and skin friction prediction techniques for hypersonic applications are presented. The study uses the original and a modified Baldwin-Lomax turbulence model with a space marching code. Grid converged turbulent predictions using the wall damping formulation (original model) and local damping formulation (modified model) are compared with experimental data for several flat plates. The wall damping and local damping results are similar for hot wall conditions, but differ significantly for cold walls, i.e., T(sub w) / T(sub t) < 0.3, with the wall damping heating and skin friction 10-30% above the local damping results. Furthermore, the local damping predictions have reasonable or good agreement with the experimental heating data for all cases. The impact of the two formulations on the van Driest damping function and the turbulent eddy viscosity distribution for a cold wall case indicate the importance of including temperature gradient effects. Grid requirements for accurate turbulent heating predictions are also studied. These results indicate that a cell Reynolds number of 1 is required for grid converged heating predictions, but coarser grids with a y(sup +) less than 2 are adequate for design of hypersonic vehicles. Based on the results of this study, it is recommended that the local damping formulation be used with the Baldwin-Lomax and Cebeci-Smith turbulence models in design and analysis of Hyper-X and future hypersonic vehicles.

  6. Accurate electrical prediction of memory array through SEM-based edge-contour extraction using SPICE simulation

    NASA Astrophysics Data System (ADS)

    Shauly, Eitan; Rotstein, Israel; Peltinov, Ram; Latinski, Sergei; Adan, Ofer; Levi, Shimon; Menadeva, Ovadya

    2009-03-01

    The continues transistors scaling efforts, for smaller devices, similar (or larger) drive current/um and faster devices, increase the challenge to predict and to control the transistor off-state current. Typically, electrical simulators like SPICE, are using the design intent (as-drawn GDS data). At more sophisticated cases, the simulators are fed with the pattern after lithography and etch process simulations. As the importance of electrical simulation accuracy is increasing and leakage is becoming more dominant, there is a need to feed these simulators, with more accurate information extracted from physical on-silicon transistors. Our methodology to predict changes in device performances due to systematic lithography and etch effects was used in this paper. In general, the methodology consists on using the OPCCmaxTM for systematic Edge-Contour-Extraction (ECE) from transistors, taking along the manufacturing and includes any image distortions like line-end shortening, corner rounding and line-edge roughness. These measurements are used for SPICE modeling. Possible application of this new metrology is to provide a-head of time, physical and electrical statistical data improving time to market. In this work, we applied our methodology to analyze a small and large array's of 2.14um2 6T-SRAM, manufactured using Tower Standard Logic for General Purposes Platform. 4 out of the 6 transistors used "U-Shape AA", known to have higher variability. The predicted electrical performances of the transistors drive current and leakage current, in terms of nominal values and variability are presented. We also used the methodology to analyze an entire SRAM Block array. Study of an isolation leakage and variability are presented.

  7. Experimental bound on the maximum predictive power of physical theories.

    PubMed

    Stuart, Terence E; Slater, Joshua A; Colbeck, Roger; Renner, Renato; Tittel, Wolfgang

    2012-07-13

    The question of whether the probabilistic nature of quantum mechanical predictions can be alleviated by supplementing the wave function with additional information has received a lot of attention during the past century. A few specific models have been suggested and subsequently falsified. Here we give a more general answer to this question: We provide experimental data that, as well as falsifying these models, cannot be explained within any alternative theory that could predict the outcomes of measurements on maximally entangled particles with significantly higher probability than quantum theory. Our conclusion is based on the assumptions that all measurement settings have been chosen freely (within a causal structure compatible with relativity theory), and that the presence of the detection loophole did not affect the measurement outcomes.

  8. Toward Relatively General and Accurate Quantum Chemical Predictions of Solid-State 17O NMR Chemical Shifts in Various Biologically Relevant Oxygen-containing Compounds

    PubMed Central

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

    2015-01-01

    Oxygen is an important element in most biologically significant molecules and experimental solid-state 17O NMR studies have provided numerous useful structural probes to study these systems. However, computational predictions of solid-state 17O NMR chemical shift tensor properties are still challenging in many cases and in particular each of the prior computational work is basically limited to one type of oxygen-containing systems. This work provides the first systematic study of the effects of geometry refinement, method and basis sets for metal and non-metal 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 17O NMR chemical shifts in organic and organometallic compounds. A number of computational factors towards relatively general and accurate predictions of 17O NMR chemical shifts were studied to provide helpful and detailed suggestions for future work. For the studied various kinds of oxygen-containing compounds, the best computational approach results in a theory-versus-experiment correlation coefficient R2 of 0.9880 and mean absolute deviation of 13 ppm (1.9% of the experimental range) for isotropic NMR shifts and R2 of 0.9926 for all shift tensor properties. These results shall facilitate future computational studies of 17O NMR chemical shifts in many biologically relevant systems, and the high accuracy may also help refinement and determination of active-site structures of some oxygen-containing substrate bound proteins. PMID:26274812

  9. 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

    2015-09-01

    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.

  10. Experimental investigation of condensation predictions for dust-enriched systems

    NASA Astrophysics Data System (ADS)

    Ustunisik, Gokce; Ebel, Denton S.; Walker, David; Boesenberg, Joseph S.

    2014-10-01

    Condensation models describe the equilibrium distribution of elements between coexisting phases (mineral solid solutions, silicate liquid, and vapor) in a closed chemical system, where the vapor phase is always present, using equations of state of the phases involved at a fixed total pressure (<1 bar) and temperature (T). The VAPORS code uses a CaO-MgO-Al2O3-SiO2 (CMAS) liquid model at T above the stability field of olivine, and the MELTS thermodynamics algorithm at lower T. Quenched high-T crystal + liquid assemblages are preserved in meteorites as Type B Ca-, Al-rich inclusions (CAIs), and olivine-rich ferromagnesian chondrules. Experimental tests of compositional regions within 100 K of the predicted T of olivine stability may clarify the nature of the phases present, the phase boundaries, and the partition of trace elements among these phases. Twenty-three Pt-loop equilibrium experiments in seven phase fields on twelve bulk compositions at specific T and dust enrichment factors tested the predicted stability fields of forsteritic olivine (Mg2SiO4), enstatite (MgSiO3), Cr-bearing spinel (MgAl2O4), perovskite (CaTiO3), melilite (Ca2Al2SiO7-Ca2Mg2Si2O7) and/or grossite (CaAl4O7) crystallizing from liquid. Experimental results for forsterite, enstatite, and grossite are in very good agreement with predictions, both in chemistry and phase abundances. On the other hand the stability of spinel with olivine, and stability of perovskite and gehlenite are quite different from predictions. Perovskite is absent in all experiments. Even at low oxygen fugacity (IW-3.4), the most TiO2-rich experiments do not crystallize Al-, Ti-bearing calcic pyroxene. The stability of spinel and olivine together is limited to a smaller phase field than is predicted. The melilite stability field is much larger than predicted, indicating a deficiency of current liquid or melilite activity models. In that respect, these experiments contribute to improving the data for calibrating thermodynamic

  11. Theoretical prediction of the onset of thermoacoustic instability from the experimental transfer matrix of a thermoacoustic core.

    PubMed

    Guedra, Matthieu; Penelet, Guillaume; Lotton, Pierrick; Dalmont, Jean-Pierre

    2011-07-01

    The aim of this paper is to propose a method to predict the onset conditions of the thermoacoustic instability for various thermoacoustic engines. As an accurate modeling of the heat exchangers and the stack submitted to a temperature gradient is a difficult task, an experimental approach for the characterization of the amplifying properties of the thermoacoustic core is proposed. An experimental apparatus is presented which allows to measure the transfer matrix of a thermoacoustic core under various heating conditions by means of a four-microphone method. An analytical model for the prediction of the onset conditions from this measured transfer matrix is developed. The experimental data are introduced in the model and theoretical predictions of the onset conditions are compared with those actually observed in standing-wave and traveling-wave engines. The results show good agreement between predictions from the model and experiments.

  12. 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.

  13. 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.

  14. 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

  15. 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.

  16. 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. PMID:26424887

  17. 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

  18. 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.

  19. 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

  20. 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.

  1. 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. PMID:26980050

  2. 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.

  3. 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.

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

    PubMed Central

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

    2016-01-01

    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. PMID:27739541

  5. A Systematic Review of Predictions of Survival in Palliative Care: How Accurate Are Clinicians and Who Are the Experts?

    PubMed Central

    Harris, Adam; Harries, Priscilla

    2016-01-01

    overall accuracy being reported. Data were extracted using a standardised tool, by one reviewer, which could have introduced bias. Devising search terms for prognostic studies is challenging. Every attempt was made to devise search terms that were sufficiently sensitive to detect all prognostic studies; however, it remains possible that some studies were not identified. Conclusion Studies of prognostic accuracy in palliative care are heterogeneous, but the evidence suggests that clinicians’ predictions are frequently inaccurate. No sub-group of clinicians was consistently shown to be more accurate than any other. Implications of Key Findings Further research is needed to understand how clinical predictions are formulated and how their accuracy can be improved. PMID:27560380

  6. Accurate ab initio prediction of propagation rate coefficients in free-radical polymerization: Acrylonitrile and vinyl chloride

    NASA Astrophysics Data System (ADS)

    Izgorodina, Ekaterina I.; Coote, Michelle L.

    2006-05-01

    A systematic methodology for calculating accurate propagation rate coefficients in free-radical polymerization was designed and tested for vinyl chloride and acrylonitrile polymerization. For small to medium-sized polymer systems, theoretical reaction barriers are calculated using G3(MP2)-RAD. For larger systems, G3(MP2)-RAD barriers can be approximated (to within 1 kJ mol -1) via an ONIOM-based approach in which the core is studied at G3(MP2)-RAD and the substituent effects are modeled with ROMP2/6-311+G(3df,2p). DFT methods (including BLYP, B3LYP, MPWB195, BB1K and MPWB1K) failed to reproduce the correct trends in the reaction barriers and enthalpies with molecular size, though KMLYP showed some promise as a low cost option for very large systems. Reaction rates are calculated via standard transition state theory in conjunction with the one-dimensional hindered rotor model. The harmonic oscillator approximation was shown to introduce an error of a factor of 2-3, and would be suitable for "order-of-magnitude" estimates. A systematic study of chain length effects indicated that rate coefficients had largely converged to their long chain limit at the dimer radical stage, and the inclusion of the primary substituent of the penultimate unit was sufficient for practical purposes. Solvent effects, as calculated using the COSMO model, were found to be relatively minor. The overall methodology reproduced the available experimental data for both of these monomers within a factor of 2.

  7. Comparison of GLIMPS and HFAST Stirling engine code predictions with experimental data

    NASA Technical Reports Server (NTRS)

    Geng, Steven M.; Tew, Roy C.

    1992-01-01

    Predictions from GLIMPS and HFAST design codes are compared with experimental data for the RE-1000 and SPRE free piston Stirling engines. Engine performance and available power loss predictions are compared. Differences exist between GLIMPS and HFAST loss predictions. Both codes require engine specific calibration to bring predictions and experimental data into agreement.

  8. 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).

  9. 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. PMID:27070016

  10. Accurate Prediction of Hyperfine Coupling Constants in Muoniated and Hydrogenated Ethyl Radicals: Ab Initio Path Integral Simulation Study with Density Functional Theory Method.

    PubMed

    Yamada, Kenta; Kawashima, Yukio; Tachikawa, Masanori

    2014-05-13

    We performed ab initio path integral molecular dynamics (PIMD) simulations with a density functional theory (DFT) method to accurately predict hyperfine coupling constants (HFCCs) in the ethyl radical (CβH3-CαH2) and its Mu-substituted (muoniated) compound (CβH2Mu-CαH2). The substitution of a Mu atom, an ultralight isotope of the H atom, with larger nuclear quantum effect is expected to strongly affect the nature of the ethyl radical. The static conventional DFT calculations of CβH3-CαH2 find that the elongation of one Cβ-H bond causes a change in the shape of potential energy curve along the rotational angle via the imbalance of attractive and repulsive interactions between the methyl and methylene groups. Investigation of the methyl-group behavior including the nuclear quantum and thermal effects shows that an unbalanced CβH2Mu group with the elongated Cβ-Mu bond rotates around the Cβ-Cα bond in a muoniated ethyl radical, quite differently from the CβH3 group with the three equivalent Cβ-H bonds in the ethyl radical. These rotations couple with other molecular motions such as the methylene-group rocking motion (inversion), leading to difficulties in reproducing the corresponding barrier heights. Our PIMD simulations successfully predict the barrier heights to be close to the experimental values and provide a significant improvement in muon and proton HFCCs given by the static conventional DFT method. Further investigation reveals that the Cβ-Mu/H stretching motion, methyl-group rotation, methylene-group rocking motion, and HFCC values deeply intertwine with each other. Because these motions are different between the radicals, a proper description of the structural fluctuations reflecting the nuclear quantum and thermal effects is vital to evaluate HFCC values in theory to be comparable to the experimental ones. Accordingly, a fundamental difference in HFCC between the radicals arises from their intrinsic molecular motions at a finite temperature, in

  11. Experimental testing of quantum mechanical predictions of mutagenicity: aminopyrazoles.

    PubMed

    Leach, Andrew G; McCoull, William; Bailey, Andrew; Barton, Peter; Mee, Christine; Rosevere, Eleanor

    2013-05-20

    A computational method for predicting the likelihood of aromatic amines being active in the Ames test for mutagenicity was trialed on a set of aminopyrazoles. A virtual array of compounds was generated from the available sets of hydrazines and α-cyanoaldehydes (or ketones) and quantum mechanical calculations used to compute a probability of being active in the Ames test. The compounds selected for synthesis and testing were not based on the predictions and so spanned the range of predicted probabilities. The subsequently generated results of the Ames test were in good correspondence with the predictions and confirm this approach as a useful means of predicting likely mutagenic risk. PMID:23541044

  12. 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

  13. Importance of the gas phase role to the prediction of energetic material behavior: An experimental study

    SciTech Connect

    Ali, A.N.; Son, S.F.; Asay, B.W.; Sander, R.K.

    2005-03-15

    Various thermal (radiative, conductive, and convective) initiation experiments are performed to demonstrate the importance of the gas phase role in combustion modeling of energetic materials (EM). A previously published condensed phase model that includes a predicted critical irradiance above which ignition is not possible is compared to experimental laser ignition results for octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) and 2,4,6-trinitrotoluene (TNT). Experimental results conflict with the predicted critical irradiance concept. The failure of the model is believed to result from a misconception about the role of the gas phase in the ignition process of energetic materials. The model assumes that ignition occurs at the surface and that evolution of gases inhibits ignition. High speed video of laser ignition, oven cook-off and hot wire ignition experiments captures the ignition of HMX and TNT in the gas phase. A laser ignition gap test is performed to further evaluate the effect of gas phase laser absorption and gas phase disruption on the ignition process. Results indicate that gas phase absorption of the laser energy is probably not the primary factor governing the gas phase ignition observations. It is discovered that a critical gap between an HMX pellet and a salt window of 6 mm{+-}0.4 mm exists below which ignition by CO{sub 2} laser is not possible at the tested irradiances of 29 W/cm{sup 2} and 38 W/cm{sup 2} for HMX ignition. These observations demonstrate that a significant disruption of the gas phase, in certain scenarios, will inhibit ignition, independent of any condensed phase processes. These results underscore the importance of gas phase processes and illustrate that conditions can exist where simple condensed phase models are inadequate to accurately predict the behavior of energetic materials.

  14. PSSP-RFE: Accurate Prediction of Protein Structural Class by Recursive Feature Extraction from PSI-BLAST Profile, Physical-Chemical Property and Functional Annotations

    PubMed Central

    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. PMID:24675610

  15. Accurate prediction of explicit solvent atom distribution in HIV-1 protease and F-ATP synthase by statistical theory of liquids

    NASA Astrophysics Data System (ADS)

    Sindhikara, Daniel; Yoshida, Norio; Hirata, Fumio

    2012-02-01

    We have created a simple algorithm for automatically predicting the explicit solvent atom distribution of biomolecules. The explicit distribution is coerced from the 3D continuous distribution resulting from a 3D-RISM calculation. This procedure predicts optimal location of solvent molecules and ions given a rigid biomolecular structure. We show examples of predicting water molecules near KNI-275 bound form of HIV-1 protease and predicting both sodium ions and water molecules near the rotor ring of F-ATP synthase. Our results give excellent agreement with experimental structure with an average prediction error of 0.45-0.65 angstroms. Further, unlike experimental methods, this method does not suffer from the partial occupancy limit. Our method can be performed directly on 3D-RISM output within minutes. It is useful not only as a location predictor but also as a convenient method for generating initial structures for MD calculations.

  16. An evolutionary model-based algorithm for accurate phylogenetic breakpoint mapping and subtype prediction in HIV-1.

    PubMed

    Kosakovsky Pond, Sergei L; Posada, David; Stawiski, Eric; Chappey, Colombe; Poon, Art F Y; Hughes, Gareth; Fearnhill, Esther; Gravenor, Mike B; Leigh Brown, Andrew J; Frost, Simon D W

    2009-11-01

    Genetically diverse pathogens (such as Human Immunodeficiency virus type 1, HIV-1) are frequently stratified into phylogenetically or immunologically defined subtypes for classification purposes. Computational identification of such subtypes is helpful in surveillance, epidemiological analysis and detection of novel variants, e.g., circulating recombinant forms in HIV-1. A number of conceptually and technically different techniques have been proposed for determining the subtype of a query sequence, but there is not a universally optimal approach. We present a model-based phylogenetic method for automatically subtyping an HIV-1 (or other viral or bacterial) sequence, mapping the location of breakpoints and assigning parental sequences in recombinant strains as well as computing confidence levels for the inferred quantities. Our Subtype Classification Using Evolutionary ALgorithms (SCUEAL) procedure is shown to perform very well in a variety of simulation scenarios, runs in parallel when multiple sequences are being screened, and matches or exceeds the performance of existing approaches on typical empirical cases. We applied SCUEAL to all available polymerase (pol) sequences from two large databases, the Stanford Drug Resistance database and the UK HIV Drug Resistance Database. Comparing with subtypes which had previously been assigned revealed that a minor but substantial (approximately 5%) fraction of pure subtype sequences may in fact be within- or inter-subtype recombinants. A free implementation of SCUEAL is provided as a module for the HyPhy package and the Datamonkey web server. Our method is especially useful when an accurate automatic classification of an unknown strain is desired, and is positioned to complement and extend faster but less accurate methods. Given the increasingly frequent use of HIV subtype information in studies focusing on the effect of subtype on treatment, clinical outcome, pathogenicity and vaccine design, the importance of accurate

  17. 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.

  18. Conformations of 1,2-dimethoxypropane and 5-methoxy-1,3-dioxane: are ab initio quantum chemistry predictions accurate?

    NASA Astrophysics Data System (ADS)

    Smith, Grant D.; Jaffe, Richard L.; Yoon, Do. Y.

    1998-06-01

    High-level ab initio quantum chemistry calculations are shown to predict conformer populations of 1,2-dimethoxypropane and 5-methoxy-1,3-dioxane that are consistent with gas-phase NMR vicinal coupling constant measurements. The conformational energies of the cyclic ether 5-methoxy-1,3-dioxane are found to be consistent with those predicted by a rotational isomeric state (RIS) model based upon the acyclic analog 1,2-dimethoxypropane. The quantum chemistry and RIS calculations indicate the presence of strong attractive 1,5 C(H 3)⋯O electrostatic interactions in these molecules, similar to those found in 1,2-dimethoxyethane.

  19. 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…

  20. Survival outcomes scores (SOFT, BAR, and Pedi-SOFT) are accurate in predicting post-liver transplant survival in adolescents.

    PubMed

    Conjeevaram Selvakumar, Praveen Kumar; Maksimak, Brian; Hanouneh, Ibrahim; Youssef, Dalia H; Lopez, Rocio; Alkhouri, Naim

    2016-09-01

    SOFT and BAR scores utilize recipient, donor, and graft factors to predict the 3-month survival after LT in adults (≥18 years). Recently, Pedi-SOFT score was developed to predict 3-month survival after LT in young children (≤12 years). These scoring systems have not been studied in adolescent patients (13-17 years). We evaluated the accuracy of these scoring systems in predicting the 3-month post-LT survival in adolescents through a retrospective analysis of data from UNOS of patients aged 13-17 years who received LT between 03/01/2002 and 12/31/2012. Recipients of combined organ transplants, donation after cardiac death, or living donor graft were excluded. A total of 711 adolescent LT recipients were included with a mean age of 15.2±1.4 years. A total of 100 patients died post-LT including 33 within 3 months. SOFT, BAR, and Pedi-SOFT scores were all found to be good predictors of 3-month post-transplant survival outcome with areas under the ROC curve of 0.81, 0.80, and 0.81, respectively. All three scores provided good accuracy for predicting 3-month survival post-LT in adolescents and may help clinical decision making to optimize survival rate and organ utilization. PMID:27478012

  1. 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.

  2. 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

  3. Length of sick leave – Why not ask the sick-listed? Sick-listed individuals predict their length of sick leave more accurately than professionals

    PubMed Central

    Fleten, Nils; Johnsen, Roar; Førde, Olav Helge

    2004-01-01

    Background The knowledge of factors accurately predicting the long lasting sick leaves is sparse, but information on medical condition is believed to be necessary to identify persons at risk. Based on the current practice, with identifying sick-listed individuals at risk of long-lasting sick leaves, the objectives of this study were to inquire the diagnostic accuracy of length of sick leaves predicted in the Norwegian National Insurance Offices, and to compare their predictions with the self-predictions of the sick-listed. Methods Based on medical certificates, two National Insurance medical consultants and two National Insurance officers predicted, at day 14, the length of sick leave in 993 consecutive cases of sick leave, resulting from musculoskeletal or mental disorders, in this 1-year follow-up study. Two months later they reassessed 322 cases based on extended medical certificates. Self-predictions were obtained in 152 sick-listed subjects when their sick leave passed 14 days. Diagnostic accuracy of the predictions was analysed by ROC area, sensitivity, specificity, likelihood ratio, and positive predictive value was included in the analyses of predictive validity. Results The sick-listed identified sick leave lasting 12 weeks or longer with an ROC area of 80.9% (95% CI 73.7–86.8), while the corresponding estimates for medical consultants and officers had ROC areas of 55.6% (95% CI 45.6–65.6%) and 56.0% (95% CI 46.6–65.4%), respectively. The predictions of sick-listed males were significantly better than those of female subjects, and older subjects predicted somewhat better than younger subjects. Neither formal medical competence, nor additional medical information, noticeably improved the diagnostic accuracy based on medical certificates. Conclusion This study demonstrates that the accuracy of a prognosis based on medical documentation in sickness absence forms, is lower than that of one based on direct communication with the sick-listed themselves

  4. 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.

  5. Prognostic models and risk scores: can we accurately predict postoperative nausea and vomiting in children after craniotomy?

    PubMed

    Neufeld, Susan M; Newburn-Cook, Christine V; Drummond, Jane E

    2008-10-01

    Postoperative nausea and vomiting (PONV) is a problem for many children after craniotomy. Prognostic models and risk scores help identify who is at risk for an adverse event such as PONV to help guide clinical care. The purpose of this article is to assess whether an existing prognostic model or risk score can predict PONV in children after craniotomy. The concepts of transportability, calibration, and discrimination are presented to identify what is required to have a valid tool for clinical use. Although previous work may inform clinical practice and guide future research, existing prognostic models and risk scores do not appear to be options for predicting PONV in children undergoing craniotomy. However, until risk factors are further delineated, followed by the development and validation of prognostic models and risk scores that include children after craniotomy, clinical judgment in the context of current research may serve as a guide for clinical care in this population. PMID:18939320

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

    PubMed

    Wang, Ting; He, Quanze; 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.

  7. Coronary Computed Tomographic Angiography Does Not Accurately Predict the Need of Coronary Revascularization in Patients with Stable Angina

    PubMed Central

    Hong, Sung-Jin; Her, Ae-Young; Suh, Yongsung; Won, Hoyoun; Cho, Deok-Kyu; Cho, Yun-Hyeong; Yoon, Young-Won; Lee, Kyounghoon; Kang, Woong Chol; Kim, Yong Hoon; Kim, Sang-Wook; Shin, Dong-Ho; Kim, Jung-Sun; Kim, Byeong-Keuk; Ko, Young-Guk; Choi, Byoung-Wook; Choi, Donghoon; Jang, Yangsoo

    2016-01-01

    Purpose To evaluate the ability of coronary computed tomographic angiography (CCTA) to predict the need of coronary revascularization in symptomatic patients with stable angina who were referred to a cardiac catheterization laboratory for coronary revascularization. Materials and Methods Pre-angiography CCTA findings were analyzed in 1846 consecutive symptomatic patients with stable angina, who were referred to a cardiac catheterization laboratory at six hospitals and were potential candidates for coronary revascularization between July 2011 and December 2013. The number of patients requiring revascularization was determined based on the severity of coronary stenosis as assessed by CCTA. This was compared to the actual number of revascularization procedures performed in the cardiac catheterization laboratory. Results Based on CCTA findings, coronary revascularization was indicated in 877 (48%) and not indicated in 969 (52%) patients. Of the 877 patients indicated for revascularization by CCTA, only 600 (68%) underwent the procedure, whereas 285 (29%) of the 969 patients not indicated for revascularization, as assessed by CCTA, underwent the procedure. When the coronary arteries were divided into 15 segments using the American Heart Association coronary tree model, the sensitivity, specificity, positive predictive value, and negative predictive value of CCTA for therapeutic decision making on a per-segment analysis were 42%, 96%, 40%, and 96%, respectively. Conclusion CCTA-based assessment of coronary stenosis severity does not sufficiently differentiate between coronary segments requiring revascularization versus those not requiring revascularization. Conventional coronary angiography should be considered to determine the need of revascularization in symptomatic patients with stable angina. PMID:27401637

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

    PubMed

    Wang, Ting; He, Quanze; 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

  9. 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

  10. 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.

  11. Predicting experimentally stable allotropes: Instability of penta-graphene

    PubMed Central

    Ewels, Christopher P.; Rocquefelte, Xavier; Kroto, Harold W.; Rayson, Mark J.; Briddon, Patrick R.; Heggie, Malcolm I.

    2015-01-01

    In recent years, a plethora of theoretical carbon allotropes have been proposed, none of which has been experimentally isolated. We discuss here criteria that should be met for a new phase to be potentially experimentally viable. We take as examples Haeckelites, 2D networks of sp2-carbon–containing pentagons and heptagons, and “penta-graphene,” consisting of a layer of pentagons constructed from a mixture of sp2- and sp3-coordinated carbon atoms. In 2D projection appearing as the “Cairo pattern,” penta-graphene is elegant and aesthetically pleasing. However, we dispute the author’s claims of its potential stability and experimental relevance. PMID:26644554

  12. 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.

  13. Blast-induced biomechanical loading of the rat: an experimental and anatomically accurate computational blast injury model.

    PubMed

    Sundaramurthy, Aravind; Alai, Aaron; Ganpule, Shailesh; Holmberg, Aaron; Plougonven, Erwan; Chandra, Namas

    2012-09-01

    Blast waves generated by improvised explosive devices (IEDs) cause traumatic brain injury (TBI) in soldiers and civilians. In vivo animal models that use shock tubes are extensively used in laboratories to simulate field conditions, to identify mechanisms of injury, and to develop injury thresholds. In this article, we place rats in different locations along the length of the shock tube (i.e., inside, outside, and near the exit), to examine the role of animal placement location (APL) in the biomechanical load experienced by the animal. We found that the biomechanical load on the brain and internal organs in the thoracic cavity (lungs and heart) varied significantly depending on the APL. When the specimen is positioned outside, organs in the thoracic cavity experience a higher pressure for a longer duration, in contrast to APL inside the shock tube. This in turn will possibly alter the injury type, severity, and lethality. We found that the optimal APL is where the Friedlander waveform is first formed inside the shock tube. Once the optimal APL was determined, the effect of the incident blast intensity on the surface and intracranial pressure was measured and analyzed. Noticeably, surface and intracranial pressure increases linearly with the incident peak overpressures, though surface pressures are significantly higher than the other two. Further, we developed and validated an anatomically accurate finite element model of the rat head. With this model, we determined that the main pathway of pressure transmission to the brain was through the skull and not through the snout; however, the snout plays a secondary role in diffracting the incoming blast wave towards the skull.

  14. Blast-induced biomechanical loading of the rat: an experimental and anatomically accurate computational blast injury model.

    PubMed

    Sundaramurthy, Aravind; Alai, Aaron; Ganpule, Shailesh; Holmberg, Aaron; Plougonven, Erwan; Chandra, Namas

    2012-09-01

    Blast waves generated by improvised explosive devices (IEDs) cause traumatic brain injury (TBI) in soldiers and civilians. In vivo animal models that use shock tubes are extensively used in laboratories to simulate field conditions, to identify mechanisms of injury, and to develop injury thresholds. In this article, we place rats in different locations along the length of the shock tube (i.e., inside, outside, and near the exit), to examine the role of animal placement location (APL) in the biomechanical load experienced by the animal. We found that the biomechanical load on the brain and internal organs in the thoracic cavity (lungs and heart) varied significantly depending on the APL. When the specimen is positioned outside, organs in the thoracic cavity experience a higher pressure for a longer duration, in contrast to APL inside the shock tube. This in turn will possibly alter the injury type, severity, and lethality. We found that the optimal APL is where the Friedlander waveform is first formed inside the shock tube. Once the optimal APL was determined, the effect of the incident blast intensity on the surface and intracranial pressure was measured and analyzed. Noticeably, surface and intracranial pressure increases linearly with the incident peak overpressures, though surface pressures are significantly higher than the other two. Further, we developed and validated an anatomically accurate finite element model of the rat head. With this model, we determined that the main pathway of pressure transmission to the brain was through the skull and not through the snout; however, the snout plays a secondary role in diffracting the incoming blast wave towards the skull. PMID:22620716

  15. 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…

  16. 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.

  17. aPPRove: An HMM-Based Method for Accurate Prediction of RNA-Pentatricopeptide Repeat Protein Binding Events.

    PubMed

    Harrison, Thomas; Ruiz, Jaime; Sloan, Daniel B; Ben-Hur, Asa; Boucher, Christina

    2016-01-01

    Pentatricopeptide repeat containing proteins (PPRs) bind to RNA transcripts originating from mitochondria and plastids. There are two classes of PPR proteins. The [Formula: see text] class contains tandem [Formula: see text]-type motif sequences, and the [Formula: see text] class contains alternating [Formula: see text], [Formula: see text] and [Formula: see text] type sequences. In this paper, we describe a novel tool that predicts PPR-RNA interaction; specifically, our method, which we call aPPRove, determines where and how a [Formula: see text]-class PPR protein will bind to RNA when given a PPR and one or more RNA transcripts by using a combinatorial binding code for site specificity proposed by Barkan et al. Our results demonstrate that aPPRove successfully locates how and where a PPR protein belonging to the [Formula: see text] class can bind to RNA. For each binding event it outputs the binding site, the amino-acid-nucleotide interaction, and its statistical significance. Furthermore, we show that our method can be used to predict binding events for [Formula: see text]-class proteins using a known edit site and the statistical significance of aligning the PPR protein to that site. In particular, we use our method to make a conjecture regarding an interaction between CLB19 and the second intronic region of ycf3. The aPPRove web server can be found at www.cs.colostate.edu/~approve. PMID:27560805

  18. 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.

  19. aPPRove: An HMM-Based Method for Accurate Prediction of RNA-Pentatricopeptide Repeat Protein Binding Events

    PubMed Central

    Harrison, Thomas; Ruiz, Jaime; Sloan, Daniel B.; Ben-Hur, Asa; Boucher, Christina

    2016-01-01

    Pentatricopeptide repeat containing proteins (PPRs) bind to RNA transcripts originating from mitochondria and plastids. There are two classes of PPR proteins. The P class contains tandem P-type motif sequences, and the PLS class contains alternating P, L and S type sequences. In this paper, we describe a novel tool that predicts PPR-RNA interaction; specifically, our method, which we call aPPRove, determines where and how a PLS-class PPR protein will bind to RNA when given a PPR and one or more RNA transcripts by using a combinatorial binding code for site specificity proposed by Barkan et al. Our results demonstrate that aPPRove successfully locates how and where a PPR protein belonging to the PLS class can bind to RNA. For each binding event it outputs the binding site, the amino-acid-nucleotide interaction, and its statistical significance. Furthermore, we show that our method can be used to predict binding events for PLS-class proteins using a known edit site and the statistical significance of aligning the PPR protein to that site. In particular, we use our method to make a conjecture regarding an interaction between CLB19 and the second intronic region of ycf3. The aPPRove web server can be found at www.cs.colostate.edu/~approve. PMID:27560805

  20. 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.

  1. Predicting Accurate Electronic Excitation Transfer Rates via Marcus Theory with Boys or Edmiston-Ruedenberg Localized Diabatization

    SciTech Connect

    Subotnik, Joseph E.; Vura-Weis, Josh; Sodt, Alex J.; Ratner, Mark A.

    2010-05-06

    We model the triplet-triplet energy-transfer experiments from the Closs group [Closs, G. L.; et al. J. Am. Chem. Soc. 1988, 110, 2652.] using a combination of Marcus theory and either Boys or Edmiston-Ruedenberg localized diabatization, and we show that relative and absolute rates of electronic excitation transfer may be computed successfully. For the case where both the donor and acceptor occupy equatorial positions on a rigid cyclohexane bridge, we find βcalc = 2.8 per C-C bond, compared with the experimental value βexp = 2.6. This work highlights the power of using localized diabatization methods as a tool for modeling nonequilibrium processes.

  2. 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.

  3. Theoretical Prediction and Experimental Realization of Missing Materials

    SciTech Connect

    Zakutayev, A.; Zhang, X.; Nagaraja, A.; Yu, L.; Lany, S.; Mason, T. O.; Ginley, D. S.; Zunger, A.

    2013-01-01

    Many chemically reasonable inorganic materials are missing from databases or literature. Two possible reasons are: (1) these materials are unstable; (2) they have been simply overlooked. Here we applied Inverse Design approach to systematically screen V-IX-IV group of 45 ternary ABX materials. High-throughput theory revealed 9 hitherto missing stable materials in this family. Combinatorial experiment synthesized one of them TaCoSn and discovered another one TaCo2Sn, the first two reported ternaries in this chemical system. This example illustrates the promise of computationally driven experimental inorganic materials chemistry.

  4. Automatic Earthquake Shear Stress Measurement Method Developed for Accurate Time- Prediction Analysis of Forthcoming Major Earthquakes Along Shallow Active Faults

    NASA Astrophysics Data System (ADS)

    Serata, S.

    2006-12-01

    The Serata Stressmeter has been developed to measure and monitor earthquake shear stress build-up along shallow active faults. The development work made in the past 25 years has established the Stressmeter as an automatic stress measurement system to study timing of forthcoming major earthquakes in support of the current earthquake prediction studies based on statistical analysis of seismological observations. In early 1982, a series of major Man-made earthquakes (magnitude 4.5-5.0) suddenly occurred in an area over deep underground potash mine in Saskatchewan, Canada. By measuring underground stress condition of the mine, the direct cause of the earthquake was disclosed. The cause was successfully eliminated by controlling the stress condition of the mine. The Japanese government was interested in this development and the Stressmeter was introduced to the Japanese government research program for earthquake stress studies. In Japan the Stressmeter was first utilized for direct measurement of the intrinsic lateral tectonic stress gradient G. The measurement, conducted at the Mt. Fuji Underground Research Center of the Japanese government, disclosed the constant natural gradients of maximum and minimum lateral stresses in an excellent agreement with the theoretical value, i.e., G = 0.25. All the conventional methods of overcoring, hydrofracturing and deformation, which were introduced to compete with the Serata method, failed demonstrating the fundamental difficulties of the conventional methods. The intrinsic lateral stress gradient determined by the Stressmeter for the Japanese government was found to be the same with all the other measurements made by the Stressmeter in Japan. The stress measurement results obtained by the major international stress measurement work in the Hot Dry Rock Projects conducted in USA, England and Germany are found to be in good agreement with the Stressmeter results obtained in Japan. Based on this broad agreement, a solid geomechanical

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

    ERIC Educational Resources Information Center

    Powell, Erica Dion

    2013-01-01

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

  6. Predicting Antimicrobial Resistance Prevalence and Incidence from Indicators of Antimicrobial Use: What Is the Most Accurate Indicator for Surveillance in Intensive Care Units?

    PubMed Central

    Fortin, Élise; Platt, Robert W.; Fontela, Patricia S.; Buckeridge, David L.; Quach, Caroline

    2015-01-01

    Objective The optimal way to measure antimicrobial use in hospital populations, as a complement to surveillance of resistance is still unclear. Using respiratory isolates and antimicrobial prescriptions of nine intensive care units (ICUs), this study aimed to identify the indicator of antimicrobial use that predicted prevalence and incidence rates of resistance with the best accuracy. Methods Retrospective cohort study including all patients admitted to three neonatal (NICU), two pediatric (PICU) and four adult ICUs between April 2006 and March 2010. Ten different resistance / antimicrobial use combinations were studied. After adjustment for ICU type, indicators of antimicrobial use were successively tested in regression models, to predict resistance prevalence and incidence rates, per 4-week time period, per ICU. Binomial regression and Poisson regression were used to model prevalence and incidence rates, respectively. Multiplicative and additive models were tested, as well as no time lag and a one 4-week-period time lag. For each model, the mean absolute error (MAE) in prediction of resistance was computed. The most accurate indicator was compared to other indicators using t-tests. Results Results for all indicators were equivalent, except for 1/20 scenarios studied. In this scenario, where prevalence of carbapenem-resistant Pseudomonas sp. was predicted with carbapenem use, recommended daily doses per 100 admissions were less accurate than courses per 100 patient-days (p = 0.0006). Conclusions A single best indicator to predict antimicrobial resistance might not exist. Feasibility considerations such as ease of computation or potential external comparisons could be decisive in the choice of an indicator for surveillance of healthcare antimicrobial use. PMID:26710322

  7. 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. PMID:25869840

  8. A new accurate ground-state potential energy surface of ethylene and predictions for rotational and vibrational energy levels

    NASA Astrophysics Data System (ADS)

    Delahaye, Thibault; Nikitin, Andrei; Rey, Michaël; Szalay, Péter G.; Tyuterev, Vladimir G.

    2014-09-01

    In this paper we report a new ground state potential energy surface for ethylene (ethene) C2H4 obtained from extended ab initio calculations. The coupled-cluster approach with the perturbative inclusion of the connected triple excitations CCSD(T) and correlation consistent polarized valence basis set cc-pVQZ was employed for computations of electronic ground state energies. The fit of the surface included 82 542 nuclear configurations using sixth order expansion in curvilinear symmetry-adapted coordinates involving 2236 parameters. A good convergence for variationally computed vibrational levels of the C2H4 molecule was obtained with a RMS(Obs.-Calc.) deviation of 2.7 cm-1 for fundamental bands centers and 5.9 cm-1 for vibrational bands up to 7800 cm-1. Large scale vibrational and rotational calculations for 12C2H4, 13C2H4, and 12C2D4 isotopologues were performed using this new surface. Energy levels for J = 20 up to 6000 cm-1 are in a good agreement with observations. This represents a considerable improvement with respect to available global predictions of vibrational levels of 13C2H4 and 12C2D4 and rovibrational levels of 12C2H4.

  9. 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

  10. 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

  11. Experimental analysis and prediction of antisymmetric wave motion in a tapered anisotropic waveguide.

    PubMed

    Moll, Jochen; Wandowski, Tomasz; Malinowski, Pawel; Radzienski, Maciej; Opoka, Szymon; Ostachowicz, Wieslaw

    2015-07-01

    This paper presents experimental results for wave propagation in an anisotropic multilayered structure with linearly varying cross section. Knowing the dispersion and wave propagation properties in such a structure is of great importance for non-destructive material testing and structural health monitoring applications for accurate damage detection and localization. In the proposed study, the wavefield is generated by a circular piezoelectric wafer active sensor and measured by a scanning laser-Doppler-vibrometer. The measurements are compared with a theoretical group delay estimation and a signal prediction for the antisymmetric wave motion along the non-uniform propagation path. The required dispersion curves are derived from the well-known global matrix method for segments of constant thickness. A multidimensional frequency-wavenumber analysis of linescan data and the full wavefield provides further insight of the adiabatic wave motion because the wavenumber changes along the tapered geometry of the waveguide. In addition, it is demonstrated that a terahertz time-domain system can be used in glass-fiber reinforced plastic structures as a tool to estimate the thickness profile of thin structures by means of time-of-flight measurements. This information is particularly important for guided wave-based diagnostics of structures with unknown thickness. PMID:26233030

  12. Experimentally derived model to predict permeability behavior of mudstones

    NASA Astrophysics Data System (ADS)

    Schneider, J.; Flemings, P. B.; Day-Stirrat, R.; Germaine, J. T.

    2010-12-01

    We use uniaxial consolidation experiments to analyze the permeability evolution during consolidation for mudstones with varying composition to develop a predictive permeability model for mudstones. We admixed silt-sized silica to dry, natural Boston Blue Clay (BBC) powder in five different mass ratios. The result is mixtures of silty clay and clayey silt with percentages of clay-sized particles varying between 36 % and 57 %. To recreate natural conditions yet remove variability and soil disturbance, we resedimented all mixtures to a total stress of 100 kPa. We then loaded them to a vertical effective stress of 2.4 MPa in an uniaxial, constant-rate-of-strain consolidation device. We show that vertical permeability increases exponentially with void ratio and decreasing clay content. There is an order of magnitude difference in permeability at a given void ratio for clay contents varying from 36 % to 57 % (by mass). We developed a model that predicts the permeability of silt-clay mixtures based on knowledge of the composition and void ratio alone. The model assumes that flow occurs through the clay-matrix. Thus, the effective permeability is controlled by the void ratio of the clay fraction. At a given stress level, the clay void ratio increases with silt content: large pores are preserved in silty samples due to stress-bridging which does not allow the clay particles to consolidate. Mudstones are important to practical and fundamental programs. They are a key cap rock for subsurface hydrocarbons and geologic storage of CO2. Over the last decade, large amounts of natural gas have been produced from mudstone (shale) gas fields.

  13. A new accurate ground-state potential energy surface of ethylene and predictions for rotational and vibrational energy levels

    SciTech Connect

    Delahaye, Thibault Rey, Michaël Tyuterev, Vladimir G.; Nikitin, Andrei; Szalay, Péter G.

    2014-09-14

    In this paper we report a new ground state potential energy surface for ethylene (ethene) C{sub 2}H{sub 4} obtained from extended ab initio calculations. The coupled-cluster approach with the perturbative inclusion of the connected triple excitations CCSD(T) and correlation consistent polarized valence basis set cc-pVQZ was employed for computations of electronic ground state energies. The fit of the surface included 82 542 nuclear configurations using sixth order expansion in curvilinear symmetry-adapted coordinates involving 2236 parameters. A good convergence for variationally computed vibrational levels of the C{sub 2}H{sub 4} molecule was obtained with a RMS(Obs.–Calc.) deviation of 2.7 cm{sup −1} for fundamental bands centers and 5.9 cm{sup −1} for vibrational bands up to 7800 cm{sup −1}. Large scale vibrational and rotational calculations for {sup 12}C{sub 2}H{sub 4}, {sup 13}C{sub 2}H{sub 4}, and {sup 12}C{sub 2}D{sub 4} isotopologues were performed using this new surface. Energy levels for J = 20 up to 6000 cm{sup −1} are in a good agreement with observations. This represents a considerable improvement with respect to available global predictions of vibrational levels of {sup 13}C{sub 2}H{sub 4} and {sup 12}C{sub 2}D{sub 4} and rovibrational levels of {sup 12}C{sub 2}H{sub 4}.

  14. Experimental Verification of the Strain Non-Uniformity Index (SNI) based Failure Prediction

    NASA Astrophysics Data System (ADS)

    Dhumal, D. A.; Kulkarni, Pratik; Date, P. P.; Nandedkar, V. M.

    2016-08-01

    Formability of the sheet metal depends upon the uniformity of strain distribution, which depends on material properties, tooling and process parameters. Nakazima Test was conducted to study the strain distribution and establish the forming limits of AA 6016. The experimental conditions were simulated using AUTOFORM 5.2 Plus software and the failure predicted using the SNI based methodology. The failure predictions were correlated with the state of the experimentally deformed Nakazima samples, and also with the FLD based forming limits. The failure prediction from the SNI based methodology was found to correlate well with the state of the experimental Nakazima sample.

  15. 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

  16. Longitudinal mixing in meandering channels: new experimental data set and verification of a predictive technique.

    PubMed

    Boxall, J B; Guymer, I

    2007-01-01

    Evaluation of longitudinal mixing processes in open channel flows is important in environmental management, requiring the quantification of mixing coefficients. Estimates of these coefficients sufficiently accurate for environmental impact assessments cannot be achieved using current theoretical or semi-empirical methods for natural channels. This inaccuracy is caused by a limited understanding and quantification of the interaction of the dominant mechanisms resulting from natural channel features, such as plan form curvature and changes in cross-sectional shape. Experimental results are presented here from studies conducted in three self-formed channels, developed by known discharges. Longitudinal mixing was investigated at various flow rates within each of the channels by monitoring the development of tracer plumes during transit through the channels. Using an optimisation procedure, coefficients required for solution of the one-dimensional advection dispersion equation (1D-ADE) were found in the range 0.02-0.2m(2)/s. The coefficients were found to vary as functions of longitudinal meander location, channel form and discharge. Predictions of these longitudinal mixing coefficients were made using a mathematical technique requiring only channel form properties and flow rate as inputs. Predicted values were typically within 20% of the measured values, although deviation of up to 50% was found for the lowest discharge in each channel. This large error is likely to have been caused by increased dead zone effects associated with channel bathymetry at low discharges that are not captured by the method. The method was shown to be capable of capturing the variation in the longitudinal mixing coefficient with longitudinal meander location, with channel form and with discharge.

  17. Experimental support for a predictive osmotic model of clay membranes

    SciTech Connect

    Fritz, S.J.; Marine, I.W.

    1983-01-01

    Osmosis has been cited as a mechanism for explaining anomalously high fluid pressures in the subsurface. Clays and shales act as membranes, and osmotic flux across these units may result in pressures sufficiently high to explain these anomalies. The theoretical osmotic pressures as calculated solely from solution properties can be quite large; however, it is not yet resolved whether these geologic membranes are sufficiently ideal to generate such pressures. Osmotic efficiencies of a Na-bentonite membrane were measured by a series of hyperfiltration experiments using various molarities of NaCl at two different porosities. The highest osmotic efficiency (0.8912) occurred at the lower porosity and the lowest NaCl input solution. The lowest measured osmotic efficiency (0.0423) occurred at the high porosity and the highest NaCl input concentration. The osmotic efficiencies obtained from the hyperfiltration experiments correlate very favorably with the Fritz-Marine Membrane Model. This model predicts that the maximum osmotically-induced hydraulic pressures in the subsurface should occur across shales having low porosities and high cation exchange capacities in which the unit separates solutions of brackish waters. 25 references, 2 figures, 2 tables.

  18. Elevated ghrelin predicts food intake during experimental sleep restriction

    PubMed Central

    Broussard, Josiane L.; Kilkus, Jennifer M.; Delebecque, Fanny; Abraham, Varghese; Day, Andrew; Whitmore, Harry R.; Tasali, Esra

    2015-01-01

    Objective Sleep curtailment has been linked to obesity, but underlying mechanisms remain to be elucidated. We assessed whether sleep restriction alters 24-hour profiles of appetite-regulating hormones ghrelin, leptin and pancreatic polypeptide during a standardized diet, and whether these hormonal alterations predict food intake during ad libitum feeding. Methods Nineteen healthy, lean men were studied under normal sleep and sleep restriction in a randomized crossover design. Blood samples were collected for 24-hours during standardized meals. Subsequently, participants had an ad libitum feeding opportunity (buffet meals and snacks) and caloric intake was measured. Results Ghrelin levels were increased after sleep restriction as compared to normal sleep (p<0.01). Overall, sleep restriction did not alter leptin or pancreatic polypeptide profiles. Sleep restriction was associated with an increase in total calories from snacks by 328 ± 140 Kcal (p=0.03), primarily from carbohydrates (p=0.02). The increase in evening ghrelin during sleep restriction was correlated with higher consumption of calories from sweets (r=0.48, p=0.04). Conclusions Sleep restriction as compared to normal sleep significantly increases ghrelin levels. The increase in ghrelin is associated with more consumption of calories. Elevated ghrelin may be a mechanism by which sleep loss leads to increased food intake and the development of obesity. PMID:26467988

  19. 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

  20. 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.

  1. Refinement of the experimental energy levels of higher {sup 2}D Rydberg states of the lithium atom with very accurate quantum mechanical calculations

    SciTech Connect

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

    2011-05-21

    Very accurate variational non-relativistic calculations are performed for four higher Rydberg {sup 2}D states (1s{sup 2}nd{sup 1}, n= 8, ..., 11) of the lithium atom ({sup 7}Li). The wave functions of the states are expanded in terms of all-electron explicitly correlated Gaussian functions and finite nuclear mass is used. The exponential parameters of the Gaussians are optimized using the variational method with the aid of the analytical energy gradient determined with respect to those parameters. The results of the calculations allow for refining the experimental energy levels determined with respect to the {sup 2}S 1s{sup 2}2s{sup 1} ground state.

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

    PubMed

    Christmann-Franck, Serge; van Westen, Gerard J P; Papadatos, George; Beltran Escudie, Fanny; Roberts, Alexander; Overington, John P; Domine, Daniel

    2016-09-26

    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.

  3. 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

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

    PubMed

    Christmann-Franck, Serge; van Westen, Gerard J P; Papadatos, George; Beltran Escudie, Fanny; Roberts, Alexander; Overington, John P; Domine, Daniel

    2016-09-26

    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

  5. 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.

  6. PredPPCrys: Accurate Prediction of Sequence Cloning, Protein Production, Purification and Crystallization Propensity from Protein Sequences Using Multi-Step Heterogeneous Feature Fusion and Selection

    PubMed Central

    Wang, Huilin; Wang, Mingjun; Tan, Hao; Li, Yuan; Zhang, Ziding; Song, Jiangning

    2014-01-01

    X-ray crystallography is the primary approach to solve the three-dimensional structure of a protein. However, a major bottleneck of this method is the failure of multi-step experimental procedures to yield diffraction-quality crystals, including sequence cloning, protein material production, purification, crystallization and ultimately, structural determination. Accordingly, prediction of the propensity of a protein to successfully undergo these experimental procedures based on the protein sequence may help narrow down laborious experimental efforts and facilitate target selection. A number of bioinformatics methods based on protein sequence information have been developed for this purpose. However, our knowledge on the important determinants of propensity for a protein sequence to produce high diffraction-quality crystals remains largely incomplete. In practice, most of the existing methods display poorer performance when evaluated on larger and updated datasets. To address this problem, we constructed an up-to-date dataset as the benchmark, and subsequently developed a new approach termed ‘PredPPCrys’ using the support vector machine (SVM). Using a comprehensive set of multifaceted sequence-derived features in combination with a novel multi-step feature selection strategy, we identified and characterized the relative importance and contribution of each feature type to the prediction performance of five individual experimental steps required for successful crystallization. The resulting optimal candidate features were used as inputs to build the first-level SVM predictor (PredPPCrys I). Next, prediction outputs of PredPPCrys I were used as the input to build second-level SVM classifiers (PredPPCrys II), which led to significantly enhanced prediction performance. Benchmarking experiments indicated that our PredPPCrys method outperforms most existing procedures on both up-to-date and previous datasets. In addition, the predicted crystallization targets of

  7. PredictSNP2: A Unified Platform for Accurately Evaluating SNP Effects by Exploiting the Different Characteristics of Variants in Distinct Genomic Regions.

    PubMed

    Bendl, Jaroslav; Musil, Miloš; Štourač, Jan; Zendulka, Jaroslav; Damborský, Jiří; Brezovský, Jan

    2016-05-01

    An important message taken from human genome sequencing projects is that the human population exhibits approximately 99.9% genetic similarity. Variations in the remaining parts of the genome determine our identity, trace our history and reveal our heritage. The precise delineation of phenotypically causal variants plays a key role in providing accurate personalized diagnosis, prognosis, and treatment of inherited diseases. Several computational methods for achieving such delineation have been reported recently. However, their ability to pinpoint potentially deleterious variants is limited by the fact that their mechanisms of prediction do not account for the existence of different categories of variants. Consequently, their output is biased towards the variant categories that are most strongly represented in the variant databases. Moreover, most such methods provide numeric scores but not binary predictions of the deleteriousness of variants or confidence scores that would be more easily understood by users. We have constructed three datasets covering different types of disease-related variants, which were divided across five categories: (i) regulatory, (ii) splicing, (iii) missense, (iv) synonymous, and (v) nonsense variants. These datasets were used to develop category-optimal decision thresholds and to evaluate six tools for variant prioritization: CADD, DANN, FATHMM, FitCons, FunSeq2 and GWAVA. This evaluation revealed some important advantages of the category-based approach. The results obtained with the five best-performing tools were then combined into a consensus score. Additional comparative analyses showed that in the case of missense variations, protein-based predictors perform better than DNA sequence-based predictors. A user-friendly web interface was developed that provides easy access to the five tools' predictions, and their consensus scores, in a user-understandable format tailored to the specific features of different categories of variations. To

  8. PredictSNP2: A Unified Platform for Accurately Evaluating SNP Effects by Exploiting the Different Characteristics of Variants in Distinct Genomic Regions

    PubMed Central

    Brezovský, Jan

    2016-01-01

    An important message taken from human genome sequencing projects is that the human population exhibits approximately 99.9% genetic similarity. Variations in the remaining parts of the genome determine our identity, trace our history and reveal our heritage. The precise delineation of phenotypically causal variants plays a key role in providing accurate personalized diagnosis, prognosis, and treatment of inherited diseases. Several computational methods for achieving such delineation have been reported recently. However, their ability to pinpoint potentially deleterious variants is limited by the fact that their mechanisms of prediction do not account for the existence of different categories of variants. Consequently, their output is biased towards the variant categories that are most strongly represented in the variant databases. Moreover, most such methods provide numeric scores but not binary predictions of the deleteriousness of variants or confidence scores that would be more easily understood by users. We have constructed three datasets covering different types of disease-related variants, which were divided across five categories: (i) regulatory, (ii) splicing, (iii) missense, (iv) synonymous, and (v) nonsense variants. These datasets were used to develop category-optimal decision thresholds and to evaluate six tools for variant prioritization: CADD, DANN, FATHMM, FitCons, FunSeq2 and GWAVA. This evaluation revealed some important advantages of the category-based approach. The results obtained with the five best-performing tools were then combined into a consensus score. Additional comparative analyses showed that in the case of missense variations, protein-based predictors perform better than DNA sequence-based predictors. A user-friendly web interface was developed that provides easy access to the five tools’ predictions, and their consensus scores, in a user-understandable format tailored to the specific features of different categories of variations

  9. 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

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

    PubMed

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

    2015-12-01

    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

  11. A Risk Prediction Model for Smoking Experimentation in Mexican American Youth

    PubMed Central

    Talluri, Rajesh; Wilkinson, Anna V.; Spitz, Margaret R.; Shete, Sanjay

    2014-01-01

    Background Smoking experimentation in Mexican American youth is problematic. In light of the research showing that preventing smoking experimentation is a valid strategy for smoking prevention, there is a need to identify Mexican American youth at high risk for experimentation. Methods A prospective population-based cohort of 1179 adolescents of Mexican descent was followed for 5 years starting in 2005–06. Participants completed a baseline interview at a home visit followed by three telephone interviews at intervals of approximately 6 months and additional interviews at two home visits in 2008–09 and 2010–11. The primary end point of interest in this study was smoking experimentation. Information regarding social, cultural, and behavioral factors (e.g., acculturation, susceptibility to experimentation, home characteristics, household influences) was collected at baseline using validated questionnaires. Results Age, sex, cognitive susceptibility, household smoking behavior, peer influence, neighborhood influence, acculturation, work characteristics, positive outcome expectations, family cohesion, degree of tension, ability to concentrate, and school discipline were found to be associated with smoking experimentation. In a validation dataset, the proposed risk prediction model had an AUC of 0.719 (95% confidence interval, 0.637 to 0.801)for predicting absolute risk for smoking experimentation within 1 year. Conclusions The proposed risk prediction model is able to quantify the risk of smoking experimentation in Mexican American adolescents. PMID:25063521

  12. 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.

  13. Experimental study on the application of a compressed-sensing (CS) algorithm to dental cone-beam CT (CBCT) for accurate, low-dose image reconstruction

    NASA Astrophysics Data System (ADS)

    Oh, Jieun; Cho, Hyosung; Je, Uikyu; Lee, Minsik; Kim, Hyojeong; Hong, Daeki; Park, Yeonok; Lee, Seonhwa; Cho, Heemoon; Choi, Sungil; Koo, Yangseo

    2013-03-01

    In practical applications of three-dimensional (3D) tomographic imaging, there are often challenges for image reconstruction from insufficient data. In computed tomography (CT); for example, image reconstruction from few views would enable fast scanning with reduced doses to the patient. In this study, we investigated and implemented an efficient reconstruction method based on a compressed-sensing (CS) algorithm, which exploits the sparseness of the gradient image with substantially high accuracy, for accurate, low-dose dental cone-beam CT (CBCT) reconstruction. We applied the algorithm to a commercially-available dental CBCT system (Expert7™, Vatech Co., Korea) and performed experimental works to demonstrate the algorithm for image reconstruction in insufficient sampling problems. We successfully reconstructed CBCT images from several undersampled data and evaluated the reconstruction quality in terms of the universal-quality index (UQI). Experimental demonstrations of the CS-based reconstruction algorithm appear to show that it can be applied to current dental CBCT systems for reducing imaging doses and improving the image quality.

  14. Experimental evaluation of a mathematical model for predicting transfer efficiency of a high volume-low pressure air spray gun.

    PubMed

    Tan, Y M; Flynn, M R

    2000-10-01

    The transfer efficiency of a spray-painting gun is defined as the amount of coating applied to the workpiece divided by the amount sprayed. Characterizing this transfer process allows for accurate estimation of the overspray generation rate, which is important for determining a spray painter's exposure to airborne contaminants. This study presents an experimental evaluation of a mathematical model for predicting the transfer efficiency of a high volume-low pressure spray gun. The effects of gun-to-surface distance and nozzle pressure on the agreement between the transfer efficiency measurement and prediction were examined. Wind tunnel studies and non-volatile vacuum pump oil in place of commercial paint were used to determine transfer efficiency at nine gun-to-surface distances and four nozzle pressure levels. The mathematical model successfully predicts transfer efficiency within the uncertainty limits. The least squares regression between measured and predicted transfer efficiency has a slope of 0.83 and an intercept of 0.12 (R2 = 0.98). Two correction factors were determined to improve the mathematical model. At higher nozzle pressure settings, 6.5 psig and 5.5 psig, the correction factor is a function of both gun-to-surface distance and nozzle pressure level. At lower nozzle pressures, 4 psig and 2.75 psig, gun-to-surface distance slightly influences the correction factor, while nozzle pressure has no discernible effect. PMID:11036729

  15. 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

  16. Tuning of Strouhal number for high propulsive efficiency accurately predicts how wingbeat frequency and stroke amplitude relate and scale with size and flight speed in birds.

    PubMed Central

    Nudds, Robert L.; Taylor, Graham K.; Thomas, Adrian L. R.

    2004-01-01

    The wing kinematics of birds vary systematically with body size, but we still, after several decades of research, lack a clear mechanistic understanding of the aerodynamic selection pressures that shape them. Swimming and flying animals have recently been shown to cruise at Strouhal numbers (St) corresponding to a regime of vortex growth and shedding in which the propulsive efficiency of flapping foils peaks (St approximately fA/U, where f is wingbeat frequency, U is cruising speed and A approximately bsin(theta/2) is stroke amplitude, in which b is wingspan and theta is stroke angle). We show that St is a simple and accurate predictor of wingbeat frequency in birds. The Strouhal numbers of cruising birds have converged on the lower end of the range 0.2 < St < 0.4 associated with high propulsive efficiency. Stroke angle scales as theta approximately 67b-0.24, so wingbeat frequency can be predicted as f approximately St.U/bsin(33.5b-0.24), with St0.21 and St0.25 for direct and intermittent fliers, respectively. This simple aerodynamic model predicts wingbeat frequency better than any other relationship proposed to date, explaining 90% of the observed variance in a sample of 60 bird species. Avian wing kinematics therefore appear to have been tuned by natural selection for high aerodynamic efficiency: physical and physiological constraints upon wing kinematics must be reconsidered in this light. PMID:15451698

  17. 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

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

    PubMed

    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.

  19. The Model for End-stage Liver Disease accurately predicts 90-day liver transplant wait-list mortality in Atlantic Canada

    PubMed Central

    Renfrew, Paul Douglas; Quan, Hude; Doig, Christopher James; Dixon, Elijah; Molinari, Michele

    2011-01-01

    OBJECTIVE: To determine the generalizability of the predictions for 90-day mortality generated by Model for End-stage Liver Disease (MELD) and the serum sodium augmented MELD (MELDNa) to Atlantic Canadian adults with end-stage liver disease awaiting liver transplantation (LT). METHODS: The predictive accuracy of the MELD and the MELDNa was evaluated by measurement of the discrimination and calibration of the respective models’ estimates for the occurrence of 90-day mortality in a consecutive cohort of LT candidates accrued over a five-year period. Accuracy of discrimination was measured by the area under the ROC curves. Calibration accuracy was evaluated by comparing the observed and model-estimated incidences of 90-day wait-list failure for the total cohort and within quantiles of risk. RESULTS: The area under the ROC curve for the MELD was 0.887 (95% CI 0.705 to 0.978) – consistent with very good accuracy of discrimination. The area under the ROC curve for the MELDNa was 0.848 (95% CI 0.681 to 0.965). The observed incidence of 90-day wait-list mortality in the validation cohort was 7.9%, which was not significantly different from the MELD estimate of 6.6% (95% CI 4.9% to 8.4%; P=0.177) or the MELDNa estimate of 5.8% (95% CI 3.5% to 8.0%; P=0.065). Global goodness-of-fit testing found no evidence of significant lack of fit for either model (Hosmer-Lemeshow χ2 [df=3] for MELD 2.941, P=0.401; for MELDNa 2.895, P=0.414). CONCLUSION: Both the MELD and the MELDNa accurately predicted the occurrence of 90-day wait-list mortality in the study cohort and, therefore, are generalizable to Atlantic Canadians with end-stage liver disease awaiting LT. PMID:21876856

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. Prediction of calcite morphology from computational and experimental studies of mutations of a de novo-designed peptide.

    PubMed

    Schrier, Sarah B; Sayeg, Marianna K; Gray, Jeffrey J

    2011-09-20

    Many organisms use macromolecules, often proteins or peptides, to control the growth of inorganic crystals into complex materials. The ability to model peptide-mineral interactions accurately could allow for the design of novel peptides to produce materials with desired properties. Here, we tested a computational algorithm developed to predict the structure of peptides on mineral surfaces. Using this algorithm, we analyzed energetic and structural differences between a 16-residue peptide (bap4) designed to interact with a calcite growth plane and single- and double-point mutations of the charged residues. Currently, no experimental method is available to resolve the structures of proteins on solid surfaces, which precludes benchmarking for computational models. Therefore, to test the models, we chemically synthesized each peptide and analyzed its effects on calcite crystal growth. Whereas bap4 affected the crystal growth by producing heavily stepped corners and edges, point mutants had variable influences on morphology. Calculated residue-specific binding energies correlated with experimental observations; point mutations of residues predicted to be crucial to surface interactions produced morphologies most similar to unmodified calcite. These results suggest that peptide conformation plays a role in mineral interactions and that the computational model supplies valid energetic and structural data that can provide information about expected crystal morphology.

  5. A holistic numerical model to predict strain hardening and damage of UHMWPE under multiple total knee replacement kinematics and experimental validation.

    PubMed

    Willing, Ryan; Kim, Il Yong

    2009-11-13

    Experimental wear testing is an essential step in the evaluation of total knee replacement (TKR) design. Unfortunately, experiments can be prohibitively expensive and time consuming, which has made computational wear simulation a more desirable alternative for screening designs. While previous attempts have demonstrated positive results, few models have fully incorporated the affect of strain hardening (or cross shear), or tested the model under more than one loading condition. The objective of this study was to develop and evaluate the performance of a new holistic TKR damage model, capable of predicting damage caused by wear, including the effects of strain hardening and creep. For the first time, a frictional work-based damage model was compared against multiple sets of experimental TKR wear testing data using different input kinematics. The wear model was tuned using experimental measurements and was then able to accurately predict the volumetric polyethylene wear volume during experiments with different kinematic inputs. The size and shape of the damage patch on the surface of the polyethylene inserts were also accurately predicted under multiple input kinematics. The ability of this model to predict implant damage under multiple loading profiles by accounting for strain hardening makes it ideal for screening new implant designs, since implant kinematics are largely a function of the shape of the components. PMID:19647828

  6. Accurate experimental determination of the isotope effects on the triple point temperature of water. I. Dependence on the 2H abundance

    NASA Astrophysics Data System (ADS)

    Faghihi, V.; Peruzzi, A.; Aerts-Bijma, A. T.; Jansen, H. G.; Spriensma, J. J.; van Geel, J.; Meijer, H. A. J.

    2015-12-01

    Variation in the isotopic composition of water is one of the major contributors to uncertainty in the realization of the triple point of water (TPW). Although the dependence of the TPW on the isotopic composition of the water has been known for years, there is still a lack of a detailed and accurate experimental determination of the values for the correction constants. This paper is the first of two articles (Part I and Part II) that address quantification of isotope abundance effects on the triple point temperature of water. In this paper, we describe our experimental assessment of the 2H isotope effect. We manufactured five triple point cells with prepared water mixtures with a range of 2H isotopic abundances encompassing widely the natural abundance range, while the 18O and 17O isotopic abundance were kept approximately constant and the 18O  -  17O ratio was close to the Meijer-Li relationship for natural waters. The selected range of 2H isotopic abundances led to cells that realised TPW temperatures between approximately  -140 μK to  +2500 μK with respect to the TPW temperature as realized by VSMOW (Vienna Standard Mean Ocean Water). Our experiment led to determination of the value for the δ2H correction parameter of A2H  =  673 μK / (‰ deviation of δ2H from VSMOW) with a combined uncertainty of 4 μK (k  =  1, or 1σ).

  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. Fission barriers of hot rotating nuclei: Theoretical predictions and experimental tests

    SciTech Connect

    Mustafa, M.G.

    1987-07-07

    Recent theoretical developments in calculating fission barriers of hot rotating nuclei and their experimental tests are reviewed. The discussions are limited to macroscopic fission models (no shell effects), since experimental tests come primarily from heavy-ion induced reactions involving large angular momenta and internal excitation energies. The physics of the rotating finite range models with temperature is emphasized and the predictions of our model are compared with those of other macroscopic models and with statistically deduced experimental results. The difficulties associated with the statistical model analysis at high temperatures are discussed. 43 refs., 8 figs., 1 tab.

  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. Prediction of sonic boom from experimental near-field overpressure data. Volume 2: Data base construction

    NASA Technical Reports Server (NTRS)

    Glatt, C. R.; Reiners, S. J.; Hague, D. S.

    1975-01-01

    A computerized method for storing, updating and augmenting experimentally determined overpressure signatures has been developed. A data base of pressure signatures for a shuttle type vehicle has been stored. The data base has been used for the prediction of sonic boom with the program described in Volume I.

  11. Deep vein thrombosis is accurately predicted by comprehensive analysis of the levels of microRNA-96 and plasma D-dimer

    PubMed Central

    Xie, Xuesheng; Liu, Changpeng; Lin, Wei; Zhan, Baoming; Dong, Changjun; Song, Zhen; Wang, Shilei; Qi, Yingguo; Wang, Jiali; Gu, Zengquan

    2016-01-01

    The aim of the present study was to investigate the association between platelet microRNA-96 (miR-96) expression levels and the occurrence of deep vein thrombosis (DVT) in orthopedic patients. A total of consecutive 69 orthopedic patients with DVT and 30 healthy individuals were enrolled. Ultrasonic color Doppler imaging was performed on lower limb veins after orthopedic surgery to determine the occurrence of DVT. An enzyme-linked fluorescent assay was performed to detect the levels of D-dimer in plasma. A quantitative polymerase chain reaction assay was performed to determine the expression levels of miR-96. Expression levels of platelet miR-96 were significantly increased in orthopedic patients after orthopedic surgery. miR-96 expression levels in orthopedic patients with DVT at days 1, 3 and 7 after orthopedic surgery were significantly increased when compared with those in the control group. The increased miR-96 expression levels were correlated with plasma D-dimer levels in orthopedic patients with DVT. However, for the orthopedic patients in the non-DVT group following surgery, miR-96 expression levels were correlated with plasma D-dimer levels. In summary, the present results suggest that the expression levels of miR-96 may be associated with the occurrence of DVT. The occurrence of DVT may be accurately predicted by comprehensive analysis of the levels of miR-96 and plasma D-dimer. PMID:27588107

  12. Predicting experimental properties of proteins from sequence by machine learning techniques.

    PubMed

    Smialowski, Pawel; Martin-Galiano, Antonio J; Cox, Jürgen; Frishman, Dmitrij

    2007-04-01

    Efficient target selection methods are an important prerequisite for increasing the success rate and reducing the cost of high-throughput structural genomics efforts. There is a high demand for sequence-based methods capable of predicting experimentally tractable proteins and filtering out potentially difficult targets at different stages of the structural genomic pipeline. Simple empirical rules based on anecdotal evidence are being increasingly superseded by rigorous machine-learning algorithms. Although the simplicity of less advanced methods makes them more human understandable, more sophisticated formalized algorithms possess superior classification power. The quickly growing corpus of experimental success and failure data gathered by structural genomics consortia creates a unique opportunity for retrospective data mining using machine learning techniques and results in increased quality of classifiers. For example, the current solubility prediction methods are reaching the accuracy of over 70%. Furthermore, automated feature selection leads to better insight into the nature of the correlation between amino acid sequence and experimental outcome. In this review we summarize methods for predicting experimental success in cloning, expression, soluble expression, purification and crystallization of proteins with a special focus on publicly available resources. We also describe experimental data repositories and machine learning techniques used for classification and feature selection. PMID:17430194

  13. Comparison of kinetic theory predictions with experimental results for a vibrated three-dimensional granular bed

    NASA Astrophysics Data System (ADS)

    Viswanathan, H.; Wildman, R. D.; Huntley, J. M.; Martin, T. W.

    2006-11-01

    The three-dimensional conservation equations relating energy and momentum transfer in a vibrated three-dimensional granular bed have been solved numerically by the finite element method. Two closures based on granular kinetic theory were used: one, the standard Fourier law relating heat flux to temperature gradient and the other, including an additional concentration gradient term. Each prediction of the two-dimensional axisymmetric granular temperature and packing fraction fields was compared against a one-dimensional model and three-dimensional experimental results, acquired using the technique of positron emission particle tracking. Both closures resulted in solutions that were in reasonable agreement with the experimental results, but it was found that differences between the predictions of each of the closures were relatively small in comparison to the anisotropy of the experimentally determined temperature distribution.

  14. Predictive algorithms for determination of reflectance data from quantity of pigments within experimental dental resin composites

    PubMed Central

    2015-01-01

    Background Being able to estimate (predict) the final spectrum of reflectance of a biomaterial, especially when the final color and appearance are fundamental for their clinical success (as is the case of dental resin composites), could be a very useful tool for the industrial development of these type of materials. The main objective of this study was the development of predictive models which enable the determination of the reflectance spectrum of experimental dental resin composites based on type and quantity of pigments used in their chemical formulation. Methods 49 types of experimental dental resin composites were formulated as a mixture of organic matrix, inorganic filler, photo activator and other components in minor quantities (accelerator, inhibitor, fluorescent agent and 4 types of pigments). Spectral reflectance of all samples were measured, before and after artificial chromatic aging, using a spectroradiometer. A Multiple Nonlinear Regression Model (MNLR) was used to predict the values of the Reflectance Factors values in the visible range (380 nm-780 nm), before and after aging, from % Pigment (%P1, %P2, %P3 and %P4) within the formulation. Results The average value of the prediction error of the model was 3.46% (SD: 1.82) across all wavelengths for samples before aging and 3.54% (SD: 1.17) for samples after aging. The differences found between the predicted and measured values of the chromatic coordinates are smaller than the acceptability threshold and, in some cases, are even below the perceptibility threshold. Conclusions Within the framework of this pilot study, the nonlinear predictive models developed allow the prediction, with a high degree of accuracy, of the reflectance spectrum of the experimental dental resin composites. PMID:26329369

  15. 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.

  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. Hazards Response of Energetic Materials - Initiation Mechanisms, Experimental Characterization, and Development of Predictive Capability

    SciTech Connect

    Maienschein, J; Nichols III, A; Reaugh, J; McClelland, M; Hsu, P C

    2005-04-15

    We present our approach to develop a predictive capability for hazards -- thermal and non-shock impact -- response of energetic material systems based on: (A) identification of relevant processes; (B) characterization of the relevant properties; (C) application of property data to predictive models; and (D) application of the models into predictive simulation. This paper focuses on the first two elements above, while a companion paper by Nichols et al focuses on the final two elements. We outline the underlying mechanisms of hazards response and their interactions, and present our experimental work to characterize the necessary material parameters, including thermal ignition, thermal and mechanical properties, fracture/fragmentation behavior, deflagration rates, and the effect of material damage. We also describe our validation test, the Scaled Thermal Explosion Experiment. Finally, we integrate the entire collection of data into a qualitative understanding that is useful until such time as the predictive models become available.

  18. 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. PMID:24076520

  19. 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.

  20. Improved correlation of predicted and experimental initial buckling stresses of composite stiffened panels

    NASA Astrophysics Data System (ADS)

    Ishikawa, Takashi; Matsushima, Masamichi; Hayashi, Yoichi

    Experimental and numerical investigations are conducted for rigorous correlation of initial buckling properties of stiffened panels made of carbon fiber/poly-ether-ether-ketone (CF/PEEK) and CF/epoxy. Decreasing longitudinal elastic modulus of unidirectional CF composites lamina in compression plays a key role for better numerical predictions. A consideration of end fixtures in finite element modeling plays another key role in correlation and both initial buckling stress and mode for the short panels used here. A quarter finite element model with an end fixture by hypothetical symmetry is considered as the irreducible minimum in the modeling. A careful setting of lamina thickness is also important for better predictions. Initial imperfection close to the real shape of CF/PEEK panels is taken into account and an improvement in correlation of predicted and experimental results is reached. A conventional Rayleigh-Ritz approach considering only a local buckling mode of skin is developed. This analytical prediction compares fairly well with the numerical and experimental results in the preceding work in which their stringers are stiff enough.

  1. Experimental and Computational Prediction of the Hydrogen Transport Properties of Pd4S

    SciTech Connect

    Morreale, B.D.; Howard, B.H.; Iyoha, O.; Enick, R.M.; Ling, C.; Sholl, D.S.

    2007-09-12

    Computational and experimental methods were used to quantify the apparent influence of a Pd4S corrosion product resulting from flux testing of 100-micron thick pure palladium membranes in a 0.1%H2S-10%He-H2 retentate gas mixture. The permeability of Pd4S was estimated to be approximately 20 times less than that of pure palladium from the results obtained through sulfide growth kinetics using gravimetric methods and the observed H2 flux decay during permeability characterization from 623 to 908 K. To complement experimental analysis, density functional theory was used to predict the hydrogen permeability of Pd4S by examining diffusivity and solubility of H in bulk Pd4S. Results are in good agreement between the experimental and computational prediction of the activation energy of permeation, while only in moderate agreement when comparing the hydrogen permeability of Pd4S. The permeability values obtained through experimentation were approximately 7 times greater than the computational predictions.

  2. 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

  3. 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.

  4. Experimental verification of a prediction model for hydrate-bearing sand

    NASA Astrophysics Data System (ADS)

    Pinkert, S.; Grozic, J. L. H.

    2016-06-01

    This paper presents an experimental verification of a prediction model for the mechanical properties of hydrate-bearing sand. The model is examined using experimental drained triaxial test results of three independent data sets, which are associated with different hydrate formations and testing conditions. For each data set, an optimization process is applied based on numerical modeling of the testing conditions in order to evaluate the pure sand properties. Based on these properties, the model forecasts the stress-stain curves for different hydrate saturations, based on an advanced hydrate simulator. Although the model does not show a fair forecast with "ice-seeding" hydrate formation samples and for specimens tested under gas saturation, it predicts the mechanical behavior of samples with "partly saturated" hydrate formation tested under water saturation.

  5. Activated sludge pilot plant: comparison between experimental and predicted concentration profiles using three different modelling approaches.

    PubMed

    Le Moullec, Y; Potier, O; Gentric, C; Leclerc, J P

    2011-05-01

    This paper presents an experimental and numerical study of an activated sludge channel pilot plant. Concentration profiles of oxygen, COD, NO(3) and NH(4) have been measured for several operating conditions. These profiles have been compared to the simulated ones with three different modelling approaches, namely a systemic approach, CFD and compartmental modelling. For these three approaches, the kinetics model was the ASM-1 model (Henze et al., 2001). The three approaches allowed a reasonable simulation of all the concentration profiles except for ammonium for which the simulations results were far from the experimental ones. The analysis of the results showed that the role of the kinetics model is of primary importance for the prediction of activated sludge reactors performance. The fact that existing kinetics parameters in the literature have been determined by parametric optimisation using a systemic model limits the reliability of the prediction of local concentrations and of the local design of activated sludge reactors. PMID:21489593

  6. VALIDATION OF CFD PREDICTIONS OF FLOW IN A 3D ALVEOLATED BEND WITH EXPERIMENTAL DATA

    PubMed Central

    VAN ERTBRUGGEN, C.; CORIERI, P.; THEUNISSEN, R.; RIETHMULLER, M.L.; DARQUENNE, C.

    2008-01-01

    Verifying numerical predictions with experimental data is an important aspect of any modeling studies. In the case of the lung, the absence of direct in-vivo flow measurements makes such verification almost impossible. We performed computational fluid dynamics (CFD) simulations in a 3D scaled-up model of an alveolated bend with rigid walls that incorporated essential geometrical characteristics of human alveolar structures and compared numerical predictions with experimental flow measurements made in the same model by Particle Image Velocimetry (PIV). Flow in both models was representative of acinar flow during normal breathing (0.82 ml/s). The experimental model was built in silicone and silicone oil was used as the carrier fluid. Flow measurements were obtained by an ensemble averaging procedure. CFD simulation was performed with STAR-CCM+ (CD-Adapco) using a polyhedral unstructured mesh. Velocity profiles in the central duct were parabolic and no bulk convection existed between the central duct and the alveoli. Velocities inside the alveoli were ∼2 orders of magnitude smaller than the mean velocity in the central duct. CFD data agreed well with those obtained by PIV. In the central duct, data agreed within 1%. The maximum simulated velocity along the centerline of the model was 0.5% larger than measured experimentally. In the alveolar cavities, data agreed within 15% on average. This suggests that CFD techniques can satisfactorily predict acinar-type flow. Such a validation ensure a great degree of confidence in the accuracy of predictions made in more complex models of the alveolar region of the lung using similar CFD techniques. PMID:17915225

  7. 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.

  8. Accurate calculation of mutational effects on the thermodynamics of inhibitor binding to p38α MAP kinase: a combined computational and experimental study.

    PubMed

    Zhu, Shun; Travis, Sue M; Elcock, Adrian H

    2013-07-01

    A major current challenge for drug design efforts focused on protein kinases is the development of drug resistance caused by spontaneous mutations in the kinase catalytic domain. The ubiquity of this problem means that it would be advantageous to develop fast, effective computational methods that could be used to determine the effects of potential resistance-causing mutations before they arise in a clinical setting. With this long-term goal in mind, we have conducted a combined experimental and computational study of the thermodynamic effects of active-site mutations on a well-characterized and high-affinity interaction between a protein kinase and a small-molecule inhibitor. Specifically, we developed a fluorescence-based assay to measure the binding free energy of the small-molecule inhibitor, SB203580, to the p38α MAP kinase and used it measure the inhibitor's affinity for five different kinase mutants involving two residues (Val38 and Ala51) that contact the inhibitor in the crystal structure of the inhibitor-kinase complex. We then conducted long, explicit-solvent thermodynamic integration (TI) simulations in an attempt to reproduce the experimental relative binding affinities of the inhibitor for the five mutants; in total, a combined simulation time of 18.5 μs was obtained. Two widely used force fields - OPLS-AA/L and Amber ff99SB-ILDN - were tested in the TI simulations. Both force fields produced excellent agreement with experiment for three of the five mutants; simulations performed with the OPLS-AA/L force field, however, produced qualitatively incorrect results for the constructs that contained an A51V mutation. Interestingly, the discrepancies with the OPLS-AA/L force field could be rectified by the imposition of position restraints on the atoms of the protein backbone and the inhibitor without destroying the agreement for other mutations; the ability to reproduce experiment depended, however, upon the strength of the restraints' force constant

  9. Exacting predictions by cybernetic model confirmed experimentally: steady state multiplicity in the chemostat.

    PubMed

    Kim, Jin Il; Song, Hyun-Seob; Sunkara, Sunil R; Lali, Arvind; Ramkrishna, Doraiswami

    2012-01-01

    We demonstrate strong experimental support for the cybernetic model based on maximizing carbon uptake rate in describing the microorganism's regulatory behavior by verifying exacting predictions of steady state multiplicity in a chemostat. Experiments with a feed mixture of glucose and pyruvate show multiple steady state behavior as predicted by the cybernetic model. When multiplicity occurs at a dilution (growth) rate, it results in hysteretic behavior following switches in dilution rate from above and below. This phenomenon is caused by transient paths leading to different steady states through dynamic maximization of the carbon uptake rate. Thus steady state multiplicity is a manifestation of the nonlinearity arising from cybernetic mechanisms rather than of the nonlinear kinetics. The predicted metabolic multiplicity would extend to intracellular states such as enzyme levels and fluxes to be verified in future experiments.

  10. PPARgene: A Database of Experimentally Verified and Computationally Predicted PPAR Target Genes.

    PubMed

    Fang, Li; Zhang, Man; Li, Yanhui; Liu, Yan; Cui, Qinghua; Wang, Nanping

    2016-01-01

    The peroxisome proliferator-activated receptors (PPARs) are ligand-activated transcription factors of the nuclear receptor superfamily. Upon ligand binding, PPARs activate target gene transcription and regulate a variety of important physiological processes such as lipid metabolism, inflammation, and wound healing. Here, we describe the first database of PPAR target genes, PPARgene. Among the 225 experimentally verified PPAR target genes, 83 are for PPARα, 83 are for PPARβ/δ, and 104 are for PPARγ. Detailed information including tissue types, species, and reference PubMed IDs was also provided. In addition, we developed a machine learning method to predict novel PPAR target genes by integrating in silico PPAR-responsive element (PPRE) analysis with high throughput gene expression data. Fivefold cross validation showed that the performance of this prediction method was significantly improved compared to the in silico PPRE analysis method. The prediction tool is also implemented in the PPARgene database.

  11. 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.

  12. Radionuclides in fruit systems: model prediction-experimental data intercomparison study.

    PubMed

    Ould-Dada, Z; Carini, F; Eged, K; Kis, Z; Linkov, I; Mitchell, N G; Mourlon, C; Robles, B; Sweeck, L; Venter, A

    2006-08-01

    This paper presents results from an international exercise undertaken to test model predictions against an independent data set for the transfer of radioactivity to fruit. Six models with various structures and complexity participated in this exercise. Predictions from these models were compared against independent experimental measurements on the transfer of 134Cs and 85Sr via leaf-to-fruit and soil-to-fruit in strawberry plants after an acute release. Foliar contamination was carried out through wet deposition on the plant at two different growing stages, anthesis and ripening, while soil contamination was effected at anthesis only. In the case of foliar contamination, predicted values are within the same order of magnitude as the measured values for both radionuclides, while in the case of soil contamination models tend to under-predict by up to three orders of magnitude for 134Cs, while differences for 85Sr are lower. Performance of models against experimental data is discussed together with the lessons learned from this exercise.

  13. 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.

  14. Shewregdb: Database and visualization environment for experimental and predicted regulatory information in Shewanella oneidensis mr-1

    SciTech Connect

    Syed, Mustafa; Karpinets, Tatiana V.; Leuze, Mike; Kora, Guruprasad; Romine, Margaret F.; Uberbacher, Edward

    2009-10-15

    Shewanella oneidensis MR-1 is an important model organism for environmental research as it has an exceptional metabolic and respiratory versatility regulated by a complex regulatory network. We have developed a database to collect experimental and computational data relating to regulation of gene and protein expression and a visualization environment that enables integration of these data types. The regulatory information in the database was collected from the published literature and different Internet resources. It includes predictions of DNA regulator binding sites, sigma factor binding sites, transcription units, operons, promoters, and RNA regulators including non-coding RNAs, riboswitches, and different types of terminators. A visualization environment based on GBrowser was developed for accessing the collected information and for its overlaying with experimental data (experimental results from studies employing microarrays, proteomics, and/or gene mutagenesis) and other genome annotations.

  15. Prediction of glutathionylation sites in proteins using minimal sequence information and their experimental validation.

    PubMed

    Pal, Debojyoti; Sharma, Deepak; Kumar, Mukesh; Sandur, Santosh K

    2016-09-01

    S-glutathionylation of proteins plays an important role in various biological processes and is known to be protective modification during oxidative stress. Since, experimental detection of S-glutathionylation is labor intensive and time consuming, bioinformatics based approach is a viable alternative. Available methods require relatively longer sequence information, which may prevent prediction if sequence information is incomplete. Here, we present a model to predict glutathionylation sites from pentapeptide sequences. It is based upon differential association of amino acids with glutathionylated and non-glutathionylated cysteines from a database of experimentally verified sequences. This data was used to calculate position dependent F-scores, which measure how a particular amino acid at a particular position may affect the likelihood of glutathionylation event. Glutathionylation-score (G-score), indicating propensity of a sequence to undergo glutathionylation, was calculated using position-dependent F-scores for each amino-acid. Cut-off values were used for prediction. Our model returned an accuracy of 58% with Matthew's correlation-coefficient (MCC) value of 0.165. On an independent dataset, our model outperformed the currently available model, in spite of needing much less sequence information. Pentapeptide motifs having high abundance among glutathionylated proteins were identified. A list of potential glutathionylation hotspot sequences were obtained by assigning G-scores and subsequent Protein-BLAST analysis revealed a total of 254 putative glutathionable proteins, a number of which were already known to be glutathionylated. Our model predicted glutathionylation sites in 93.93% of experimentally verified glutathionylated proteins. Outcome of this study may assist in discovering novel glutathionylation sites and finding candidate proteins for glutathionylation. PMID:27454891

  16. Ion exchange chromatography of proteins-predictions of elution curves and operating conditions. II. Experimental verification.

    PubMed

    Yamamoto, S; Nakanishi, K; Matsuno, R; Kamijubo, T

    1983-05-01

    The applicability and validity of the model developed in Part I were confirmed experimentally. In this article, various proteins were eluted both by stepwise and linear gradient elution on DEAE ion exchangers under a variety of experimental conditions. Adsorption isotherms were measured as a function of ionic strength in batch experiments. The moment method was employed for the determination of various parameters such as the gel-phase diffusion coefficient and the longitudinal dispersion coefficient. By use of these parameters and the experimentally measured ionic strength of the peak position, the number of plates was determined according to the method described in Part I. Theoretical elution curves were calculated with the experimentally measured adsorption equilibria and the number of plates. Good agreement was observed between theory an experiments. Various factors affecting the separation were investigated. It was found that the effect of the number of plates for salts, N'(p), was negligible except the case of stepwise elution of high ionic strength buffer. When elution curves were symmetrical, the widths of the elution curves were inversely proportional to the square root of the number of plates of proteins, N(p), as in other chromatographic techniques. A simple graphical method for prediction of the peak position in linear gradient elution described in Part I was found applicable when the elution curves were symmetrical. A useful correlation of prediction of the peak width in a linear gradient elution was proposed on the basis of the approximate solution derived in Part I of this study. This graphical method and correlation permit easy prediction of the peak position and peak width in linear gradient elution in the case of symmetrical elution curves.

  17. 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.

  18. Protein structure prediction: combining de novo modeling with sparse experimental data.

    PubMed

    Latek, Dorota; Ekonomiuk, Dariusz; Kolinski, Andrzej

    2007-07-30

    Routine structure prediction of new folds is still a challenging task for computational biology. The challenge is not only in the proper determination of overall fold but also in building models of acceptable resolution, useful for modeling the drug interactions and protein-protein complexes. In this work we propose and test a comprehensive approach to protein structure modeling supported by sparse, and relatively easy to obtain, experimental data. We focus on chemical shift-based restraints from NMR, although other sparse restraints could be easily included. In particular, we demonstrate that combining the typical NMR software with artificial intelligence-based prediction of secondary structure enhances significantly the accuracy of the restraints for molecular modeling. The computational procedure is based on the reduced representation approach implemented in the CABS modeling software, which proved to be a versatile tool for protein structure prediction during the CASP (CASP stands for critical assessment of techniques for protein structure prediction) experiments (see http://predictioncenter/CASP6/org). The method is successfully tested on a small set of representative globular proteins of different size and topology, including the two CASP6 targets, for which the required NMR data already exist. The method is implemented in a semi-automated pipeline applicable to a large scale structural annotation of genomic data. Here, we limit the computations to relatively small set. This enabled, without a loss of generality, a detailed discussion of various factors determining accuracy of the proposed approach to the protein structure prediction.

  19. 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. PMID:24954026

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. 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. PMID:21604865

  6. Theoretical predictions and experimental observations of genomic mapping by anchoring random clones

    SciTech Connect

    Grigoriev, A.V. )

    1993-02-01

    Genome mapping by anchoring random clones has recently been the subject of intensive theoretical study. In this paper, differences between published predictions of properties of anchored groups of clones ( contigs') are analyzed and simplifications of the mathematical formulae describing these properties are presented. The theoretical predictions are compared with the experimental results from the physical mapping of the genome of Schizosaccharomyces pombe. Information about the number of genome sections with no anchored clone on them ( oceans') and the number of undetected overlaps between the contigs at a given stage of the experiment is required for the decision to change from the random strategy to that of a directed closure of gaps. We demonstrate that the expected number of oceans can be approximated by the number of groups of clones anchored by a single probe ( singletons'), as can the expected number of undetected overlaps between contigs by the number of contigs containing more than one anchor. 14 refs., 4 figs.

  7. 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.

  8. Simplified procedures for correlation of experimentally measured and predicted thrust chamber performance

    NASA Technical Reports Server (NTRS)

    Powell, W. B.

    1973-01-01

    Thrust chamber performance is evaluated in terms of an analytical model incorporating all the loss processes that occur in a real rocket motor. The important loss processes in the real thrust chamber were identified, and a methodology and recommended procedure for predicting real thrust chamber vacuum specific impulse were developed. Simplified equations for the calculation of vacuum specific impulse are developed to relate the delivered performance (both vacuum specific impulse and characteristic velocity) to the ideal performance as degraded by the losses corresponding to a specified list of loss processes. These simplified equations enable the various performance loss components, and the corresponding efficiencies, to be quantified separately (except that interaction effects are arbitrarily assigned in the process). The loss and efficiency expressions presented can be used to evaluate experimentally measured thrust chamber performance, to direct development effort into the areas most likely to yield improvements in performance, and as a basis to predict performance of related thrust chamber configurations.

  9. 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.

  10. Experimental Test of Momentum Cooling Model Predictions at COSY and Conclusions for WASA and HESR

    SciTech Connect

    Stockhorst, H.; Stassen, R.; Maier, R.; Prasuhn, D.; Katayama, T.; Thorndahl, L

    2007-11-07

    The High-Energy Storage Ring (HESR) of the future International Facility for Antiproton and Ion Research (FAIR) at GSI in Darmstadt is planned as an anti-proton cooler ring in the momentum range from 1.5 to 15 GeV/c. An important and challenging feature of the new facility is the combination of highly dense phase space cooled beams with internal targets. A detailed numerical and analytical approach to the Fokker-Planck equation for longitudinal filter cooling including the beam-target interaction has been carried out to demonstrate the stochastic cooling capability. To gain confidence in the model predictions a series of experimental stochastic cooling studies with the internal target ANKE at COSY have been carried out. A remarkable agreement between model and experiment was achieved. On this basis longitudinal stochastic cooling simulations were performed to predict the possibilities and limits of cooling when the newly installed WASA Pellet-target is operated.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. Comparison of modeling predictions with experimental data from plastic lithium ion cells

    SciTech Connect

    Doyle, M.; Newman, J. |; Gozdz, A.S.; Schmutz, C.N.; Tarascon, J.M.

    1996-06-01

    Modeling results for a lithium-ion battery based on the couple Li{sub x}C{sub 6} {vert_bar} Li{sub y}Mn{sub 2}O{sub 4} are presented and compared to experimental data. Good agreement between simulation and experiment exists for several different experimental cell configurations on both charge and discharge. Simulations indicate that the battery in its present design is ohmically limited. Additional internal resistance in the cells, beyond that initially predicted by the model, could be described using either a contact resistance between cell layers or a film resistance on the negative electrode particles. Modest diffusion limitations in the carbon electrode arising at moderate discharge rates are used to fit the diffusion coefficient of lithium in the carbon electrode, giving D{sub s{sub {delta}}{sup {minus}}} = 3.9 {times} 10{sup {minus}10} cm{sup 2}/s. Cells with a 1 M (mol/dm{sup 3}) LiPF{sub 6} initial salt concentration become solution-phase diffusion limited at high rates. The low-rate specific energy calculated for the experimental cells ranges from 70 to 90 Wh/kg, with this mass based on the composite electrodes, electrolyte, separator, and current collectors. The peak specific power for a 30 s current pulse to a 2.8 V cutoff potential is predicted to fall from about 360 W/kg at the beginning of discharge to 100 W/kg at 80% depth of discharge for one particular experimental cell. Different system designs are explored using the mathematical model with the objective of a higher specific energy. Configurations optimized for a 6 h discharge time should obtain over 100 Wh/kg.

  17. 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.

  18. 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

  19. 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.

  20. 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

  1. 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.

  2. Experimental tests and predictive model of an adsorptive air conditioning unit

    SciTech Connect

    Poyelle, F.; Guilleminot, J.J.; Meunier, F.

    1999-01-01

    An adsorption air conditioning unit has been built operating with a heat nd mass recovery cycle and a zeolite-water pair. A new consolidated adsorbent composite with good heat transfer properties has been developed and implemented in the adsorber. At an evaporating temperature of 4 C, the experimental specific cooling power (SCP) of 97 W/kg achieved represents a real improvement in comparison with those measured with a packed bed technology. At this evaporating pressure, the mass transfer resistance controls the process. Therefore, at higher evaporating temperature a COP of 0.68 and a SCP of 135 W/kg were experimentally achieved. A new model has been developed to take into account the mass transfer limitations. The model has been validated and can predict the average pressure inside the adsorber and the components temperature of the unit. A new high conductive material with enhanced mass transfer properties has been developed. The predictive model shows that a SCP of 600 W/kg and a COP of 0.74 could be achieved with this new material.

  3. Prediction of Symptom Change in Placebo Versus No-Treatment Group in Experimentally Induced Motion Sickness.

    PubMed

    Horing, Bjoern; Weimer, Katja; Muth, Eric R; Enck, Paul

    2015-09-01

    The long-standing question of who responds to placebo and who does not is of great theoretical and clinical relevance and has received increasing attention in recent years. We therefore performed a post hoc analysis of one of our previously published studies on placebo responses (PRs). In the analysis, fourteen potential predictors for the PR on experimentally induced motion sickness in 32 healthy volunteers were explored using moderated multiple regression. Generalized self-efficacy, generalized self, internal locus of control and cognitive flexibility were significantly associated with symptom improvement in the placebo group, as compared to the untreated control group. Notably, the directions of the associations were such that the "unfavorable" side of the constructs (e.g. low self-efficacy) predicted a higher PR. Instead, the "favorable" side predicted symptom improvement in the control group. Results fit well with prior research into psychological influences on motion sickness. Although PRs in motion sickness are not well established, it is suggested to include the identified constructs in future research involving motion sickness-related symptoms such as nausea and vertigo. Concerning PRs in general, the results may have implications for clinical as well as experimental research on other symptoms and disorders, such as pain or depression. PMID:25912825

  4. NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8-11.

    PubMed

    Lundegaard, Claus; Lamberth, Kasper; Harndahl, Mikkel; Buus, Søren; Lund, Ole; Nielsen, Morten

    2008-07-01

    NetMHC-3.0 is trained on a large number of quantitative peptide data using both affinity data from the Immune Epitope Database and Analysis Resource (IEDB) and elution data from SYFPEITHI. The method generates high-accuracy predictions of major histocompatibility complex (MHC): peptide binding. The predictions are based on artificial neural networks trained on data from 55 MHC alleles (43 Human and 12 non-human), and position-specific scoring matrices (PSSMs) for additional 67 HLA alleles. As only the MHC class I prediction server is available, predictions are possible for peptides of length 8-11 for all 122 alleles. artificial neural network predictions are given as actual IC(50) values whereas PSSM predictions are given as a log-odds likelihood scores. The output is optionally available as download for easy post-processing. The training method underlying the server is the best available, and has been used to predict possible MHC-binding peptides in a series of pathogen viral proteomes including SARS, Influenza and HIV, resulting in an average of 75-80% confirmed MHC binders. Here, the performance is further validated and benchmarked using a large set of newly published affinity data, non-redundant to the training set. The server is free of use and available at: http://www.cbs.dtu.dk/services/NetMHC.

  5. Modeling the effect of cell-associated polymeric fluid layers on force spectroscopy measurements. Part II: experimental results and comparison with model predictions.

    PubMed

    Coldren, Faith M; Foteinopoulou, Katerina; Verbeeten, Wilco M H; Carroll, David L; Laso, Manuel

    2008-09-01

    In this paper, experimentally obtained force curves on Staphylococcus aureus are compared with a previously developed model that incorporates hydrodynamic effects of extracellular polysaccharides together with the elastic response of the bacterium and cantilever. Force-displacement curves were predicted without any adjustable parameters. It is demonstrated that experimental results can be accurately described by our model, especially if viscoelastic effects of the extracellular polysaccharide layer are taken into account. Polysaccharide layer viscoelasticity was treated by means of a multimode Phan-Thien/Tanner (PTT) constitutive equation. Typical maximum relaxation times range from 0.2 to 2 s, whereas the corresponding zero-shear-rate viscosities are 6-9 Pa.s, based on published, steady-state rheological measurements on Staphylococcus aureus polysaccharide extracted from its native environment. The bacterial elastic constant is found to be in the range 0.02-0.4 N/m, corresponding to bacterial wall Young's moduli in the range of a few hundred MPa. Repeatability of measurements performed on different bacteria is found to be only fair, due to large individuum variability, whereas repetitions of measurements on the same bacterium showed high reproducibility. Improved force-indentation curve predictions are expected if transient rheological characterization of extracellular polysaccharides is available. More desirable however is the direct, in vivo rheological characterization of the extracellular polysaccharide. A model-based analysis of experimental force-indentation curves shows that appreciable further experimental improvements are still necessary to achieve this goal. PMID:18666789

  6. Uranium speciation in moorland river water samples: a comparison of experimental results and computer model predictions.

    PubMed

    Unsworth, Emily R; Jones, Phil; Cook, Jennifer M; Hill, Steve J

    2005-06-01

    An on-line method has been developed for separating inorganic and organic bound uranium species present in river water samples. The method utilised a small chelating resin (Hyphan) column incorporated into the sample introduction manifold of an ICP-MS instrument. The method was evaluated for samples from rivers on Dartmoor (Devon, UK), an area of granite overlain with peat bogs. The results indicate that organic-uranium species form a major proportion (80%) of the total dissolved uranium present. Further work with synthetic water samples indicated that the level of dissolved organic carbon played a greater role in determining the level of organic-uranium species than did sample pH. Computer models for the water samples were constructed using the WHAM program (incorporating uranium data from the Nuclear Energy Agency Thermochemical Database project) in order to predict the levels of organic-uranium species that would form. By varying the proportion of humic and fulvic acids used in the humic component, predictions within 10% of the experimental results were obtained. The program did exhibit a low bias at higher pH values (7.5) and low organic carbon concentrations (0.5 microg ml(-1)), but under the natural conditions prevalent in the Dartmoor water samples, the model predictions were successful.

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

    PubMed

    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

  8. Model predictions and experimental characterization of Co-Pt alloy clusters

    NASA Astrophysics Data System (ADS)

    Moskovkin, P.; Pisov, S.; Hou, M.; Raufast, C.; Tournus, F.; Favre, L.; Dupuis, V.

    2007-07-01

    Model and real cobalt-platinum alloy clusters are compared in terms of structure, composition and segregation. Canonical and semi grand canonical Metropolis Monte Carlo simulations are performed to model these clusters, using embedded atom (EAM) and modified embedded atom (MEAM) potentials. All of them correctly predict the bulk L12 Co3Pt and CoPt3 structures as well as the L10 CoPt phase. However, the lattice parameters, phase stability and the L10-fcc order-disorder transition temperature are at variance. Segregation predictions with EAM and MEAM potentials are contradictory. Experimentally, mixed clusters with various compositions were deposited by Low Energy Cluster Beam on amorphous carbon at room temperature. Their size distribution, crystalline structure and composition were examined by Transmission Electron Microscopy (TEM). Clusters with the same size distributions were modelled. Both experiment and modelling show their crystallographic parameters to continuously correspond to the fcc CoPt chemically disordered phase. Diffraction measurements indicate surface segregation of the specie in excess, in agreement with EAM predictions for the Co-rich phase. The consequences on magnetic properties are discussed.

  9. 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.

  10. 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

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

    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.

  12. Modeling and simulation of organophosphate-induced neurotoxicity: Prediction and validation by experimental studies.

    PubMed

    Greget, Renaud; Dadak, Selma; Barbier, Laure; Lauga, Fabien; Linossier-Pierre, Sandra; Pernot, Fabien; Legendre, Arnaud; Ambert, Nicolas; Bouteiller, Jean-Marie; Dorandeu, Frédéric; Bischoff, Serge; Baudry, Michel; Fagni, Laurent; Moussaoui, Saliha

    2016-05-01

    Exposure to organophosphorus (OP) compounds, either pesticides or chemical warfare agents, represents a major health problem. As potent irreversible inhibitors of cholinesterase, OP may induce seizures, as in status epilepticus, and occasionally brain lesions. Although these compounds are extremely toxic agents, the search for novel antidotes remains extremely limited. In silico modeling constitutes a useful tool to identify pharmacological targets and to develop efficient therapeutic strategies. In the present work, we developed a new in silico simulator in order to predict the neurotoxicity of irreversible inhibitors of acetyl- and/or butyrylcholinesterase (ChE) as well as the potential neuroprotection provided by antagonists of cholinergic muscarinic and glutamate N-methyl-d-aspartate (NMDA) receptors. The simulator reproduced firing of CA1 hippocampal neurons triggered by exposure to paraoxon (POX), as found in patch-clamp recordings in in vitro mouse hippocampal slices. In the case of POX intoxication, it predicted a preventing action of the muscarinic receptor antagonist atropine sulfate, as well as a synergistic action with the non-competitive NMDA receptor antagonist memantine. These in silico predictions relative to beneficial effects of atropine sulfate combined with memantine were recapitulated experimentally in an in vivo model of POX in adult male Swiss mice using electroencephalic (EEG) recordings. Thus, our simulator is a new powerful tool to identify protective therapeutic strategies against OP central effects, by screening various combinations of muscarinic and NMDA receptor antagonists. PMID:27108687

  13. 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

  14. 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

  15. Molecular dynamics prediction and experimental evidence for density of normal and metastable liquid zirconium

    NASA Astrophysics Data System (ADS)

    Wang, H. P.; Yang, S. J.; Hu, L.; Wei, B.

    2016-06-01

    The density of normal and metastable undercooled liquid zirconium was predicted by performing molecular dynamics calculation with a system consisting of 4000 atoms and measured by electrostatic levitation experiments. The results show that the density increases linearly with the descending of temperature, including a maximum undercooling of 928 K. The density is 6.00 g cm-3 at the melting temperature, which agrees well with the experimental result of 6.06 g cm-3. Furthermore, the atomic number is increased to 32,000 on the basis of 4000 atoms and there appears only 0.02% difference. Besides, the pair distribution function was applied to display the atomic structure, which indicates the liquid structure change occurs at the first neighbor distance.

  16. Optimization of microalgal photobioreactor system using model predictive control with experimental validation.

    PubMed

    Yoo, Sung Jin; Jeong, Dong Hwi; Kim, Jung Hun; Lee, Jong Min

    2016-08-01

    To maximize biomass and lipid concentrations, various optimization methods were investigated in microalgal photobioreactor systems under mixotrophic conditions. Lipid concentration was estimated using unscented Kalman filter (UKF) with other measurable sources and subsequently used as lipid data for performing model predictive control (MPC). In addition, the maximized biomass and lipid trajectory obtained by open-loop optimization were used as target trajectory for tracking by MPC. Simulation studies and experimental validation were performed and significant improvements in biomass and lipid productivity were achieved in the case where MPC was applied. However, occurence of a lag phase was observed while manipulating the feed flow rates, which is induced by large amount of inputs. This is an important phenomenon that can lead to model-plant mismatch and requires further study for the optimization of microalgal photobioreactors. PMID:27094678

  17. Prediction and experimental confirmation of the response function for neutron detection using superheated drops

    NASA Astrophysics Data System (ADS)

    Lo, Yuan-Chyuan; Apfel, Robert E.

    1988-11-01

    Neutrons can be detected with a suspension of superheated drops in an immiscible and compliant holding medium. The mechanism of this radiation-induced bubble nucleation has been studied. A model to predict the minimum neutron energy required to nucleate a vapor bubble in superheated liquids has previously been reported [R.E. Apfel, S. C. Roy, and Y.-C. Lo, Phys. Rev. A 31, 3194 (1985)]. Now, the energy-dependent response function for the detector has been calculated based on the model and a detailed consideration of the possible interactions of neutrons with superheated materials. The response of the detector has been measured with monoenergetic neutrons (from 0.025 eV to 14 MeV) at facilities of the National Bureau of Standards and the Radiological Research Accelerator Facility at the Nevis Laboratories of Columbia University. The experimental results agree reasonably well with that of the calculations.

  18. 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

  19. 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.

  20. Thermally induced damage in composite space structure: Predictive methodology and experimental correlation

    NASA Technical Reports Server (NTRS)

    Park, Cecelia; Mcmanus, Hugh L.

    1994-01-01

    A general analysis method is presented to predict matrix cracks in all plies of a composite laminate, and resulting degraded laminate properties, as functions of temperature or thermal cycles. A shear lag solution of the stresses in the vicinity of cracks and a fracture mechanics crack formation criteria are used to predict cracks. Damage is modeled incrementally, which allows the inclusion of the effects of temperature dependent material properties and softening of the laminate due to previous cracking. The analysis is incorporated into an easy-to-use computer program. The analysis is correlated with experimentally measured crack densities in a variety of laminates exposed to monotonically decreasing temperatures. Crack densities are measured at the edges of specimens by microscopic inspection, and throughout the specimen volumes by x-ray and sanding down of the edges. Correlation between the analytical results and the crack densities in the interiors of the specimens was quite good. Crack densities measured at specimen edges did not agree with internal crack densities (or analyses) in some cases. A free-edge stress analysis clarified the reasons for these discrepancies.

  1. Computational and Experimental Prediction of Human C-Type Lectin Receptor Druggability

    PubMed Central

    Aretz, Jonas; Wamhoff, Eike-Christian; Hanske, Jonas; Heymann, Dario; Rademacher, Christoph

    2014-01-01

    Mammalian C-type lectin receptors (CTLRS) are involved in many aspects of immune cell regulation such as pathogen recognition, clearance of apoptotic bodies, and lymphocyte homing. Despite a great interest in modulating CTLR recognition of carbohydrates, the number of specific molecular probes is limited. To this end, we predicted the druggability of a panel of 22 CTLRs using DoGSiteScorer. The computed druggability scores of most structures were low, characterizing this family as either challenging or even undruggable. To further explore these findings, we employed a fluorine-based nuclear magnetic resonance screening of fragment mixtures against DC-SIGN, a receptor of pharmacological interest. To our surprise, we found many fragment hits associated with the carbohydrate recognition site (hit rate = 13.5%). A surface plasmon resonance-based follow-up assay confirmed 18 of these fragments (47%) and equilibrium dissociation constants were determined. Encouraged by these findings we expanded our experimental druggability prediction to Langerin and MCL and found medium to high hit rates as well, being 15.7 and 10.0%, respectively. Our results highlight limitations of current in silico approaches to druggability assessment, in particular, with regard to carbohydrate-binding proteins. In sum, our data indicate that small molecule ligands for a larger panel of CTLRs can be developed. PMID:25071783

  2. 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. PMID:25265865

  3. Experimental data and theoretical predictions for the rate of electrophoretic clarification of colloidal suspensions

    SciTech Connect

    Johnson, T.J.; Davis, E.J.

    2000-05-01

    An experimental and theoretical investigation of the electrophoretic clarification rate of colloidal suspensions was conducted. The suspensions included a coal-washing effluent and a model system of TiO{sub 2} particles. A parametric study of TiO{sub 2} suspensions was performed to validate and analysis of the electrophoretic motion of the clarification front formed between a clear zone and the suspension. To measure the electric field strength needed in the prediction of the location of the front, a moveable probe and salt bridge were connected to a reference electrode. Using the measured electric field strengths, it was found that the numerical solution to the unit cell electrophoresis model agrees with the measured clarification rates. For suspensions with moderately thick electric double layers and high particle volume fractions the deviations from classical Smoluchowski theory are substantial, and the numerical analysis is in somewhat better agreement with the data than a prior solution of the problem. The numerical model reduces to the predictions of previous theories as the thickness of the electric double layer decreases, and it is in good agreement with the clarification rate measured for a coal-washing effluent suspension with thin electric double layers.

  4. 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.

  5. Integrated Experimental and Modeling Studies to Predict the Impact Response of Explosives and Propellants

    SciTech Connect

    Maienschein, J L; Nichols III, A L; Reaugh, J E; McClelland, M E; Hsu, P C

    2005-05-25

    Understanding and predicting the impact response of explosives and propellants remains a challenging area in the energetic materials field. Efforts are underway at LLNL (and other laboratories) to apply modern diagnostic tools and computational analysis to move beyond the current level of imprecise approximations towards a predictive approach more closely based on fundamental understanding of the relevant mechanisms. In this paper we will discuss a set of underlying mechanisms that govern the impact response of explosives and propellants: (a) mechanical insult (impact) leading to material damage and/or direct ignition; (b) ignition leading to flame spreading; (c) combustion being driven by flame spreading, perhaps in damaged materials; (d) combustion causing further material damage; (e) combustion leading to pressure build-up or relief; (f) pressure changes driving the rates of combustion and flame spread; (g) pressure buildup leading to structural response and damage, which causes many of the physical hazards. We will briefly discuss our approach to modeling up these mechanistic steps using ALE 3D, the LLNL hydrodynamic code with fully coupled chemistry, heat flow, mass transfer, and slow mechanical motion as well as hydrodynamic processes. We will identify the necessary material properties needed for our models, and will discuss our experimental efforts to characterize these properties and the overall mechanistic steps, in order to develop and parameterize the models in ALE 3D and to develop a qualitative understanding of impact response.

  6. 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.

  7. Comparison of Thermal Performances Predicted and Experimental of Solar Air Collector

    NASA Astrophysics Data System (ADS)

    Sencan, Arzu; Ozdemir, Gokhan

    In this study, thermal performance of solar air collector system which was experimentally constructed was obtained for different operating conditions. Experiments were conducted under Turkey/Mersin climatic conditions. Then, Neural Network (NN) models have been developed for the prediction the thermal performance of solar air collectors. Experimental data were used for training and testing of the networks. The inputs of the network are inlet and outlet air temperature to collector, solar radiation and air mass flow rate and the output is thermal performance of solar air collector. Using the weights obtained from the trained network a new formulation is presented for the calculation of the performance; the use of NN is proliferating with high speed in simulation. The R2-values obtained when unknown data were used to the networks was 0.9985 which is very satisfactory. The use of this new formulation, which can be employed with any programming language or spreadsheet program for the estimation of the thermal performance of solar air collectors, as described in this paper, may make the use of dedicated NN software unnecessary.

  8. 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

  9. Use of quantitative shape-activity relationships to model the photoinduced toxicity of polycyclic aromatic hydrocarbons: Electron density shape features accurately predict toxicity

    SciTech Connect

    Mezey, P.G.; Zimpel, Z.; Warburton, P.; Walker, P.D.; Irvine, D.G.; Huang, X.D.; Dixon, D.G.; Greenberg, B.M.

    1998-07-01

    The quantitative shape-activity relationship (QShAR) methodology, based on accurate three-dimensional electron densities and detailed shape analysis methods, has been applied to a Lemna gibba photoinduced toxicity data set of 16 polycyclic aromatic hydrocarbon (PAH) molecules. In the first phase of the studies, a shape fragment QShAR database of PAHs was developed. The results provide a very good match to toxicity based on a combination of the local shape features of single rings in comparison to the central ring of anthracene and a more global shape feature involving larger molecular fragments. The local shape feature appears as a descriptor of the susceptibility of PAHs to photomodification and the global shape feature is probably related to photosensitization activity.

  10. Experimental validation of DXA-based finite element models for prediction of femoral strength.

    PubMed

    Dall'Ara, E; Eastell, R; Viceconti, M; Pahr, D; Yang, L

    2016-10-01

    Osteoporotic fractures are a major clinical problem and current diagnostic tools have an accuracy of only 50%. The aim of this study was to validate dual energy X-rays absorptiometry (DXA)-based finite element (FE) models to predict femoral strength in two loading configurations. Thirty-six pairs of fresh frozen human proximal femora were scanned with DXA and quantitative computed tomography (QCT). For each pair one femur was tested until failure in a one-legged standing configuration (STANCE) and one by replicating the position of the femur in a fall onto the greater trochanter (SIDE). Subject-specific 2D DXA-based linear FE models and 3D QCT-based nonlinear FE models were generated for each specimen and used to predict the measured femoral strength. The outcomes of the models were compared to standard DXA-based areal bone mineral density (aBMD) measurements. For the STANCE configuration the DXA-based FE models (R(2)=0.74, SEE=1473N) outperformed the best densitometric predictor (Neck_aBMD, R(2)=0.66, SEE=1687N) but not the QCT-based FE models (R(2)=0.80, SEE=1314N). For the SIDE configuration both QCT-based FE models (R(2)=0.85, SEE=455N) and DXA neck aBMD (R(2)=0.80, SEE=502N) outperformed DXA-based FE models (R(2)=0.77, SEE=529N). In both configurations the DXA-based FE model provided a good 1:1 agreement with the experimental data (CC=0.87 for SIDE and CC=0.86 for STANCE), with proper optimization of the failure criteria. In conclusion we found that the DXA-based FE models are a good predictor of femoral strength as compared with experimental data ex vivo. However, it remains to be investigated whether this novel approach can provide good predictions of the risk of fracture in vivo. PMID:27341287

  11. 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

  12. 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.

  13. 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.

  14. 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. PMID:26216230

  15. 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

  16. 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

  17. Stable, high-order SBP-SAT finite difference operators to enable accurate simulation of compressible turbulent flows on curvilinear grids, with application to predicting turbulent jet noise

    NASA Astrophysics Data System (ADS)

    Byun, Jaeseung; Bodony, Daniel; Pantano, Carlos

    2014-11-01

    Improved order-of-accuracy discretizations often require careful consideration of their numerical stability. We report on new high-order finite difference schemes using Summation-By-Parts (SBP) operators along with the Simultaneous-Approximation-Terms (SAT) boundary condition treatment for first and second-order spatial derivatives with variable coefficients. In particular, we present a highly accurate operator for SBP-SAT-based approximations of second-order derivatives with variable coefficients for Dirichlet and Neumann boundary conditions. These terms are responsible for approximating the physical dissipation of kinetic and thermal energy in a simulation, and contain grid metrics when the grid is curvilinear. Analysis using the Laplace transform method shows that strong stability is ensured with Dirichlet boundary conditions while weaker stability is obtained for Neumann boundary conditions. Furthermore, the benefits of the scheme is shown in the direct numerical simulation (DNS) of a Mach 1.5 compressible turbulent supersonic jet using curvilinear grids and skew-symmetric discretization. Particularly, we show that the improved methods allow minimization of the numerical filter often employed in these simulations and we discuss the qualities of the simulation.

  18. 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.

  19. Accurate theoretical prediction of vibrational frequencies in an inhomogeneous dynamic environment: A case study of a glutamate molecule in water solution and in a protein-bound form

    NASA Astrophysics Data System (ADS)

    Speranskiy, Kirill; Kurnikova, Maria

    2004-07-01

    We propose a hierarchical approach to model vibrational frequencies of a ligand in a strongly fluctuating inhomogeneous environment such as a liquid solution or when bound to a macromolecule, e.g., a protein. Vibrational frequencies typically measured experimentally are ensemble averaged quantities which result (in part) from the influence of the strongly fluctuating solvent. Solvent fluctuations can be sampled effectively by a classical molecular simulation, which in our model serves as the first, low level of the hierarchy. At the second high level of the hierarchy a small subset of system coordinates is used to construct a patch of the potential surface (ab initio) relevant to the vibration in question. This subset of coordinates is under the influence of an instantaneous external force exerted by the environment. The force is calculated at the lower level of the hierarchy. The proposed methodology is applied to model vibrational frequencies of a glutamate in water and when bound to the Glutamate receptor protein and its mutant. Our results are in close agreement with the experimental values and frequency shifts measured by the Jayaraman group by the Fourier transform infrared spectroscopy [Q. Cheng et al., Biochem. 41, 1602 (2002)]. Our methodology proved useful in successfully reproducing vibrational frequencies of a ligand in such a soft, flexible, and strongly inhomogeneous protein as the Glutamate receptor.

  20. 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.

  1. 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

  2. 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

  3. 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.

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

    PubMed

    Schunter, C; Garza, J C; Macpherson, E; Pascual, M

    2014-01-01

    Single nucleotide polymorphisms (SNPs) are rapidly becoming the marker of choice in population genetics due to a variety of advantages relative to other markers, including higher genomic density, data quality, reproducibility and genotyping efficiency, as well as ease of portability between laboratories. Advances in sequencing technology and methodologies to reduce genomic representation have made the isolation of SNPs feasible for nonmodel organisms. RNA-seq is one such technique for the discovery of SNPs and development of markers for large-scale genotyping. Here, we report the development of 192 validated SNP markers for parentage analysis in Tripterygion delaisi (the black-faced blenny), a small rocky-shore fish from the Mediterranean Sea. RNA-seq data for 15 individual samples were used for SNP discovery by applying a series of selection criteria. Genotypes were then collected from 1599 individuals from the same population with the resulting loci. Differences in heterozygosity and allele frequencies were found between the two data sets. Heterozygosity was lower, on average, in the population sample, and the mean difference between the frequencies of particular alleles in the two data sets was 0.135 ± 0.100. We used bootstrap resampling of the sequence data to predict appropriate sample sizes for SNP discovery. As cDNA library production is time-consuming and expensive, we suggest that using seven individuals for RNA sequencing reduces the probability of discarding highly informative SNP loci, due to lack of observed polymorphism, whereas use of more than 12 samples does not considerably improve prediction of true allele frequencies.

  5. 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

  6. 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.

  7. 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. PMID:24597773

  8. Motion effects on an IFR hovering task: Analytical predictions and experimental results

    NASA Technical Reports Server (NTRS)

    Ringland, R. F.; Stapleford, R. L.; Magdaleno, R. E.

    1971-01-01

    An analytical pilot model incorporating the effects of motion cues and display scanning and sampling is tested by comparing predictions against experimental results on a moving base simulator. The simulated task is that of precision hovering of a VTOL having varying amounts of rate damping, and using separated instrument displays. Motion cue effects are investigated by running the experiment under fixed and moving base conditions, the latter in two modes; full motion, and angular motion only. Display scanning behavior is measured on some of the runs. The results of the program show that performance is best with angular motion only, most probably because a g-vector tilt cue is available to the pilot in this motion condition. This provides an attitude indication even when not visually fixating the attitude display. Vestibular threshold effects are also present in the results because of the display scaling used to permit hovering position control within the motion simulator limits; no washouts are used in the simulator drive signals. The IFR nature of the task results in large decrements in pilot opinion and performance relative to VFR conditions because of the scanning workload. Measurements of scanning behavior are sensitive to motion conditions and show more attention to attitude control under fixed base conditions.

  9. Bioinformatic prediction and experimental verification of Fur-regulated genes in the extreme acidophile Acidithiobacillus ferrooxidans

    PubMed Central

    Quatrini, Raquel; Lefimil, Claudia; Veloso, Felipe A.; Pedroso, Inti; Holmes, David S.; Jedlicki, Eugenia

    2007-01-01

    The γ-proteobacterium Acidithiobacillus ferrooxidans lives in extremely acidic conditions (pH 2) and, unlike most organisms, is confronted with an abundant supply of soluble iron. It is also unusual in that it oxidizes iron as an energy source. Consequently, it faces the challenging dual problems of (i) maintaining intracellular iron homeostasis when confronted with extremely high environmental loads of iron and (ii) of regulating the use of iron both as an energy source and as a metabolic micronutrient. A combined bioinformatic and experimental approach was undertaken to identify Fur regulatory sites in the genome of A. ferrooxidans and to gain insight into the constitution of its Fur regulon. Fur regulatory targets associated with a variety of cellular functions including metal trafficking (e.g. feoPABC, tdr, tonBexbBD, copB, cdf), utilization (e.g. fdx, nif), transcriptional regulation (e.g. phoB, irr, iscR) and redox balance (grx, trx, gst) were identified. Selected predicted Fur regulatory sites were confirmed by FURTA, EMSA and in vitro transcription analyses. This study provides the first model for a Fur-binding site consensus sequence in an acidophilic iron-oxidizing microorganism and lays the foundation for future studies aimed at deepening our understanding of the regulatory networks that control iron uptake, homeostasis and oxidation in extreme acidophiles. PMID:17355989

  10. 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.

  11. 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.

  12. 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.

  13. Comparison of experimental surface pressures with theoretical predictions on twin two-dimensional convergent-divergent nozzles

    NASA Technical Reports Server (NTRS)

    Carlson, J. R.; Pendergraft, O. C., Jr.; Burley, J. R., II

    1986-01-01

    A three-dimensional subsonic aerodynamic panel code (VSAERO) was used to predict the effects of upper and lower external nozzle flap geometry on the external afterbody/nozzle pressure coefficient distributions and external nozzle drag of nonaxisymmetric convergent-divergent exhaust nozzles having parallel external sidewalls installed on a generic twin-engine high performance aircraft model. Nozzle static pressure coefficient distributions along the upper and lower surfaces near the model centerline and near the outer edges (corner) of the two surfaces were calculated, and nozzle drag was predicted using these surface pressure distributions. A comparison between the theoretical predictions and experimental wind tunnel data is made to evaluate the utility of the code in calculating the flow about these types of non-axisymmetric afterbody configurations. For free-stream Mach numbers of 0.60 and 0.90, the conditions where the flows were attached on the boattails yielded the best comparison between the theoretical predictions and the experimental data. For the Boattail terminal angles of greater than 15 deg., the experimental data for M = 0.60 and 0.90 indicated areas of separated flow, so the theoretical predictions failed to match the experimental data. Even though calculations of regions of separated flows are within the capabilities of the theoretical method, acceptable solutions were not obtained.

  14. The Value of Accurate Magnetic Resonance Characterization of Posterior Cruciate Ligament Tears in the Setting of Multiligament Knee Injury: Imaging Features Predictive of Early Repair vs Reconstruction.

    PubMed

    Goiney, Christoper C; Porrino, Jack; Twaddle, Bruce; Richardson, Michael L; Mulcahy, Hyojeong; Chew, Felix S

    2016-01-01

    Multiligament knee injury (MLKI) represents a complex set of pathologies treated with a wide variety of surgical approaches. If early surgical intervention is performed, the disrupted posterior cruciate ligament (PCL) can be treated with primary repair or reconstruction. The purpose of our study was to retrospectively identify a critical length of the distal component of the torn PCL on magnetic resonance imaging (MRI) that may predict the ability to perform early proximal femoral repair of the ligament, as opposed to reconstruction. A total of 50 MLKIs were managed at Harborview Medical Center from May 1, 2013, through July 15, 2014, by an orthopedic surgeon. Following exclusions, there were 27 knees with complete disruption of the PCL that underwent either early reattachment to the femoral insertion or reconstruction and were evaluated using preoperative MRI. In a consensus fashion, 2 radiologists measured the proximal and distal fragments of each disrupted PCL using preoperative MRI in multiple planes, as needed. MRI findings were correlated with what was performed at surgery. Those knees with a distal fragment PCL length of ≥41mm were capable of, and underwent, early proximal femoral repair. With repair, the distal stump was attached to the distal femur. Alternatively, those with a distal PCL length of ≤32mm could not undergo repair because of insufficient length and as such, were reconstructed. If early surgical intervention for an MLKI involving disruption of the PCL is considered, attention should be given to the length of the distal PCL fragment on MRI to plan appropriately for proximal femoral reattachment vs reconstruction. If the distal PCL fragment measures ≥41mm, surgical repair is achievable and can be considered as a surgical option.

  15. Rescoring Docking Hit Lists for Model Cavity Sites: Predictions And Experimental Testing

    SciTech Connect

    Graves, A.P.; Shivakumar, D.M.; Boyce, S.E.; Jacobson, M.P.; Case, D.A.; Shoichet, B.K.

    2009-05-19

    Molecular docking computationally screens thousands to millions of organic molecules against protein structures, looking for those with complementary fits. Many approximations are made, often resulting in low 'hit rates'. A strategy to overcome these approximations is to rescore top-ranked docked molecules using a better but slower method. One such is afforded by molecular mechanics-generalized Born surface area (MM-GBSA) techniques. These more physically realistic methods have improved models for solvation and electrostatic interactions and conformational change compared to most docking programs. To investigate MM-GBSA rescoring, we re-ranked docking hit lists in three small buried sites: a hydrophobic cavity that binds apolar ligands, a slightly polar cavity that binds aryl and hydrogen-bonding ligands, and an anionic cavity that binds cationic ligands. These sites are simple; consequently, incorrect predictions can be attributed to particular errors in the method, and many likely ligands may actually be tested. In retrospective calculations, MM-GBSA techniques with binding-site minimization better distinguished the known ligands for each cavity from the known decoys compared to the docking calculation alone. This encouraged us to test rescoring prospectively on molecules that ranked poorly by docking but that ranked well when rescored by MM-GBSA. A total of 33 molecules highly ranked by MM-GBSA for the three cavities were tested experimentally. Of these, 23 were observed to bind-these are docking false negatives rescued by rescoring. The 10 remaining molecules are true negatives by docking and false positives by MM-GBSA. X-ray crystal structures were determined for 21 of these 23 molecules. In many cases, the geometry prediction by MM-GBSA improved the initial docking pose and more closely resembled the crystallographic result; yet in several cases, the rescored geometry failed to capture large conformational changes in the protein. Intriguingly, rescoring not

  16. 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

  17. 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

  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. 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

  20. Quantitative comparison between theoretical predictions and experimental results for Bragg spectroscopy of a strongly interacting Fermi superfluid

    SciTech Connect

    Zou Peng; Kuhnle, Eva D.; Vale, Chris J.; Hu Hui

    2010-12-15

    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.

  1. 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.

  2. 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.

  3. Comprehensive predictions of target proteins based on protein-chemical interaction using virtual screening and experimental verifications

    PubMed Central

    2012-01-01

    Background Identification of the target proteins of bioactive compounds is critical for elucidating the mode of action; however, target identification has been difficult in general, mostly due to the low sensitivity of detection using affinity chromatography followed by CBB staining and MS/MS analysis. Results We applied our protocol of predicting target proteins combining in silico screening and experimental verification for incednine, which inhibits the anti-apoptotic function of Bcl-xL by an unknown mechanism. One hundred eighty-two target protein candidates were computationally predicted to bind to incednine by the statistical prediction method, and the predictions were verified by in vitro binding of incednine to seven proteins, whose expression can be confirmed in our cell system. As a result, 40% accuracy of the computational predictions was achieved successfully, and we newly found 3 incednine-binding proteins. Conclusions This study revealed that our proposed protocol of predicting target protein combining in silico screening and experimental verification is useful, and provides new insight into a strategy for identifying target proteins of small molecules. PMID:22480302

  4. Absorbed dose determination using experimental and analytical predictions of x-ray spectra

    NASA Astrophysics Data System (ADS)

    Edwards, David Lee

    1999-10-01

    Electron beam welding in a vacuum is a technology that NASA is investigating as a joining technique for manufacture of space structures. The interaction of energetic electrons with metal produces x-rays. This investigation characterizes the x-ray environment due to operation of an in-vacuum electron beam welding tool and provides recommendations for adequate radiation 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 United States 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 Extra Vehicular Activities (EVA) 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

  5. 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

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

    PubMed

    Ferguson, Jake M; Ponciano, José M

    2014-02-01

    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.

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

    PubMed

    Ferguson, Jake M; Ponciano, José M

    2014-02-01

    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

  8. 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

  9. 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.

  10. Improved prediction of RNA secondary structure by integrating the free energy model with restraints derived from experimental probing data

    PubMed Central

    Wu, Yang; Shi, Binbin; Ding, Xinqiang; Liu, Tong; Hu, Xihao; Yip, Kevin Y.; Yang, Zheng Rong; Mathews, David H.; Lu, Zhi John

    2015-01-01

    Recently, several experimental techniques have emerged for probing RNA structures based on high-throughput sequencing. However, most secondary structure prediction tools that incorporate probing data are designed and optimized for particular types of experiments. For example, RNAstructure-Fold is optimized for SHAPE data, while SeqFold is optimized for PARS data. Here, we report a new RNA secondary structure prediction method, restrained MaxExpect (RME), which can incorporate multiple types of experimental probing data and is based on a free energy model and an MEA (maximizing expected accuracy) algorithm. We first demonstrated that RME substantially improved secondary structure prediction with perfect restraints (base pair information of known structures). Next, we collected structure-probing data from diverse experiments (e.g. SHAPE, PARS and DMS-seq) and transformed them into a unified set of pairing probabilities with a posterior probabilistic model. By using the probability scores as restraints in RME, we compared its secondary structure prediction performance with two other well-known tools, RNAstructure-Fold (based on a free energy minimization algorithm) and SeqFold (based on a sampling algorithm). For SHAPE data, RME and RNAstructure-Fold performed better than SeqFold, because they markedly altered the energy model with the experimental restraints. For high-throughput data (e.g. PARS and DMS-seq) with lower probing efficiency, the secondary structure prediction performances of the tested tools were comparable, with performance improvements for only a portion of the tested RNAs. However, when the effects of tertiary structure and protein interactions were removed, RME showed the highest prediction accuracy in the DMS-accessible regions by incorporating in vivo DMS-seq data. PMID:26170232

  11. Improved prediction of RNA secondary structure by integrating the free energy model with restraints derived from experimental probing data.

    PubMed

    Wu, Yang; Shi, Binbin; Ding, Xinqiang; Liu, Tong; Hu, Xihao; Yip, Kevin Y; Yang, Zheng Rong; Mathews, David H; Lu, Zhi John

    2015-09-01

    Recently, several experimental techniques have emerged for probing RNA structures based on high-throughput sequencing. However, most secondary structure prediction tools that incorporate probing data are designed and optimized for particular types of experiments. For example, RNAstructure-Fold is optimized for SHAPE data, while SeqFold is optimized for PARS data. Here, we report a new RNA secondary structure prediction method, restrained MaxExpect (RME), which can incorporate multiple types of experimental probing data and is based on a free energy model and an MEA (maximizing expected accuracy) algorithm. We first demonstrated that RME substantially improved secondary structure prediction with perfect restraints (base pair information of known structures). Next, we collected structure-probing data from diverse experiments (e.g. SHAPE, PARS and DMS-seq) and transformed them into a unified set of pairing probabilities with a posterior probabilistic model. By using the probability scores as restraints in RME, we compared its secondary structure prediction performance with two other well-known tools, RNAstructure-Fold (based on a free energy minimization algorithm) and SeqFold (based on a sampling algorithm). For SHAPE data, RME and RNAstructure-Fold performed better than SeqFold, because they markedly altered the energy model with the experimental restraints. For high-throughput data (e.g. PARS and DMS-seq) with lower probing efficiency, the secondary structure prediction performances of the tested tools were comparable, with performance improvements for only a portion of the tested RNAs. However, when the effects of tertiary structure and protein interactions were removed, RME showed the highest prediction accuracy in the DMS-accessible regions by incorporating in vivo DMS-seq data.

  12. 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.

  13. 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.

  14. An assessment of biodegradability of quaternary carbon-containing fragrance compounds: comparison of experimental OECD screening test results and in silico prediction data.

    PubMed

    Seyfried, Markus; Boschung, Alain

    2014-05-01

    An assessment of biodegradability was carried out for fragrance substances containing quaternary carbons by using data obtained from Organisation for Economic Co-operation and Development (OECD) 301F screening tests for ready biodegradation and from Biowin and Catalogic prediction models. Despite an expected challenging profile, a relatively high percentage of common-use fragrance substances showed significant biodegradation under the stringent conditions applied in the OECD 301F test. Among 27 test compounds, 37% met the pass level criteria after 28 d, while another 26% indicated partial breakdown (≥20% biodegradation). For several compounds for which structural analogs were available, the authors found that structures that were rendered less water soluble by either the presence of an acetate ester or the absence of oxygen tended to degrade to a lesser extent compared to the primary alcohols or oxygenated counterparts under the test conditions applied. Difficulties were encountered when attempting to correlate experimental with in silico data. Whereas the Biowin model combinations currently recommended by regulatory agencies did not allow for a reliable discrimination between readily and nonbiodegradable compounds, only a comparably small proportion of the chemicals studied (30% and 63% depending on the model) fell within the applicability domain of Catalogic, a factor that critically reduced its predictive power. According to these results, currently neither Biowin nor Catalogic accurately reflects the potential for biodegradation of fragrance compounds containing quaternary carbons.

  15. 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.

  16. Toward Accurate and Quantitative Comparative Metagenomics.

    PubMed

    Nayfach, Stephen; Pollard, Katherine S

    2016-08-25

    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

  17. 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

  18. 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

  19. 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.

  20. Theoretical and experimental {alpha} decay half-lives of the heaviest odd-Z elements and general predictions

    SciTech Connect

    Zhang, H. F.; Royer, G.

    2007-10-15

    Theoretical {alpha} decay half-lives of the heaviest odd-Z nuclei are calculated using the experimental Q{sub {alpha}} value. The barriers in the quasimolecular shape path are determined within a Generalized Liquid Drop Model (GLDM) and the WKB approximation is used. The results are compared with calculations using the Density-Dependent M3Y (DDM3Y) effective interaction and the Viola-Seaborg-Sobiczewski (VSS) formulas. The calculations provide consistent estimates for the half-lives of the {alpha} decay chains of these superheavy elements. The experimental data stand between the GLDM calculations and VSS ones in the most time. Predictions are provided for the {alpha} decay half-lives of other superheavy nuclei within the GLDM and VSS approaches using the recent extrapolated Q{sub {alpha}} of Audi, Wapstra, and Thibault [Nucl. Phys. A729, 337 (2003)], which may be used for future experimental assignment and identification.

  1. Theoretical and experimental α decay half-lives of the heaviest odd-Z elements and general predictions

    NASA Astrophysics Data System (ADS)

    Zhang, H. F.; Royer, G.

    2007-10-01

    Theoretical α decay half-lives of the heaviest odd-Z nuclei are calculated using the experimental Qα value. The barriers in the quasimolecular shape path are determined within a Generalized Liquid Drop Model (GLDM) and the WKB approximation is used. The results are compared with calculations using the Density-Dependent M3Y (DDM3Y) effective interaction and the Viola-Seaborg-Sobiczewski (VSS) formulas. The calculations provide consistent estimates for the half-lives of the α decay chains of these superheavy elements. The experimental data stand between the GLDM calculations and VSS ones in the most time. Predictions are provided for the α decay half-lives of other superheavy nuclei within the GLDM and VSS approaches using the recent extrapolated Qα of Audi, Wapstra, and Thibault [Nucl. Phys. A729, 337 (2003)], which may be used for future experimental assignment and identification.

  2. 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.

  3. 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.

  4. 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.

  5. Incremental Validity of Thinking Styles in Predicting Academic Achievements: An Experimental Study in Hypermedia Learning Environments

    ERIC Educational Resources Information Center

    Fan, Weiqiao; Zhang, Li-Fang; Watkins, David

    2010-01-01

    The study examined the incremental validity of thinking styles in predicting academic achievement after controlling for personality and achievement motivation in the hypermedia-based learning environment. Seventy-two Chinese college students from Shanghai, the People's Republic of China, took part in this instructional experiment. The…

  6. Adolescents' Implicit Theories Predict Desire for Vengeance after Peer Conflicts: Correlational and Experimental Evidence

    ERIC Educational Resources Information Center

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

    2011-01-01

    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…

  7. 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...

  8. Using experimental human influenza infections to validate a viral dynamic model and the implications for prediction.

    PubMed

    Chen, S C; You, S H; Liu, C Y; Chio, C P; Liao, C M

    2012-09-01

    The aim of this work was to use experimental infection data of human influenza to assess a simple viral dynamics model in epithelial cells and better understand the underlying complex factors governing the infection process. The developed study model expands on previous reports of a target cell-limited model with delayed virus production. Data from 10 published experimental infection studies of human influenza was used to validate the model. Our results elucidate, mechanistically, the associations between epithelial cells, human immune responses, and viral titres and were supported by the experimental infection data. We report that the maximum total number of free virions following infection is 10(3)-fold higher than the initial introduced titre. Our results indicated that the infection rates of unprotected epithelial cells probably play an important role in affecting viral dynamics. By simulating an advanced model of viral dynamics and applying it to experimental infection data of human influenza, we obtained important estimates of the infection rate. This work provides epidemiologically meaningful results, meriting further efforts to understand the causes and consequences of influenza A infection.

  9. Prediction of hip joint load and translation using musculoskeletal modelling with force-dependent kinematics and experimental validation.

    PubMed

    Zhang, Xuan; Chen, Zhenxian; Wang, Ling; Yang, Wenjian; Li, Dichen; Jin, Zhongmin

    2015-07-01

    Musculoskeletal lower limb models are widely used to predict the resultant contact force in the hip joint as a non-invasive alternative to instrumented implants. Previous musculoskeletal models based on rigid body assumptions treated the hip joint as an ideal sphere with only three rotational degrees of freedom. An musculoskeletal model that considered force-dependent kinematics with three additional translational degrees of freedom was developed and validated in this study by comparing it with a previous experimental measurement. A 32-mm femoral head against a polyethylene cup was considered in the musculoskeletal model for calculating the contact forces. The changes in the main modelling parameters were found to have little influence on the hip joint forces (relative deviation of peak value < 10 BW%, mean trial deviation < 20 BW%). The centre of the hip joint translation was more sensitive to the changes in the main modelling parameters, especially muscle recruitment type (relative deviation of peak value < 20%, mean trial deviation < 0.02 mm). The predicted hip contact forces showed consistent profiles, compared with the experimental measurements, except in the lateral-medial direction. The ratio-average analysis, based on the Bland-Altman's plots, showed better limits of agreement in climbing stairs (mean limits of agreement: -2.0 to 6.3 in walking, mean limits of agreement: -0.5 to 3.1 in climbing stairs). Better agreement of the predicted hip contact forces was also found during the stance phase. The force-dependent kinematics approach underestimated the maximum hip contact force by a mean value of 6.68 ± 1.75% BW compared with the experimental measurements. The predicted maximum translations of the hip joint centres were 0.125 ± 0.03 mm in level walking and 0.123 ± 0.005 mm in climbing stairs.

  10. Experimental and CFD analysis for prediction of vortex and swirl angle in the pump sump station model

    NASA Astrophysics Data System (ADS)

    Kim, C. G.; Kim, B. H.; Bang, B. H.; Lee, Y. H.

    2015-01-01

    Sump model testing is mainly used to check flow conditions around the intake structure. In present paper, numerical simulation with SST turbulence model for a scaled sump model was carried out with air entrainment and two phases for prediction of locations of vortex generation. The sump model used for the CFD and experimental analysis was scaled down by a ratio of 1:10. The experiment was performed in Korea Maritime and Ocean University (KMOU) and the flow conditions around pump's intake structure were investigated. In this study, uniformity of flow distribution in the pump intake channel was examined to find out the specific causes of vortex occurrence. Furthermore, the effectiveness of an Anti Vortex Device (AVD) to suppress the vortex occurrence in a single intake pump sump model was examined. CFD and experimental analysis carried out with and without AVDs produced very similar results. Without the AVDs, the maximum swirl angle obtained for experimental and CFD analysis were 10.9 and 11.3 degree respectively. Similarly, with AVDs, the maximum swirl angle obtained for experimental and CFD analysis was 2.7 and 0.2 degree respectively. So, with reference to the ANSI/HI 98 standard that permits a maximum swirl angle of 5 degree, the use of AVDs in experimental and CFD analysis produced very desirable results which is well within the limit.

  11. Tumor site prediction using spatiotemporal detection of subclinical hyperemia in experimental photocarcinogenesis

    NASA Astrophysics Data System (ADS)

    Konger, Raymond L.; Xu, Zhengbin; Sahu, Ravi P.; Kim, Young L.

    2014-03-01

    We demonstrate that a spatial and temporal analysis of subclinical hyperemia reliably predicts specific areas at high risk for skin tumor development during photocarcinogenesis. To determine detailed spatiotemporal patterns of inflammatory angiogenesis foci in a relatively large area, we developed a mesoscopic (between microscopic and macroscopic) imaging approach. This method relies on our earlier finding that the combination of a spectral analysis of hemoglobin with diffuse-light-suppressed imaging can increase the image resolution, contrast and penetration depth to visualize microvasculature Hgb content in the large tissue area. In our recent study, SKH1 hairless albino mice were irradiated for 10 weeks with a carcinogen dose of UVB. Using our newly developed mesoscopic imaging methods, we imaged the mice over 20 - 30 weeks after stopping UVB, and excised hyperemic/non-hyperemic areas at several different timepoints. We show that persistent hyperemic foci can predict future tumor formation. In particular, our imaging approach allows us to assess the spatial and temporal extent of subclinical inflammatory foci, which in turn can predict sites of future overlying tumor formation. In addition, although COX-2 inhibitors are known to suppress skin cancer development in humans, it remains unclear whether the chemopreventive activity of COX-2 inhibitors are chiefly attributable to their anti-inflammatory effects. Our study provides evidence that subclinical subepithelial inflammatory foci occur prior to overt tumor formation, and that these areas are highly predictive for future tumor formation, that celecoxib's ability to suppress tumorigenesis is tightly linked to its ability to reduce the area of subclinical inflammatory foci.

  12. Experimental and predicted heating distributions for biconics at incidence in air at Mach 10

    NASA Technical Reports Server (NTRS)

    Miller, C. G., III

    1984-01-01

    Heating distributions were measured on a 1.9-percent-scale model of a generic aeroassisted vehicle proposed for missions to a number of planets and for use as a moderate lift-drag ratio Earth orbital transfer vehicle. This vehicle is spherically blunted, 12.84 deg/7 deg biconic with the fore-cone bent upward 7 deg to provide self-trim capability. A straight biconic with the same nose radius and the same half-angles was also tested. The free-stream Reynolds numbers based on model length were equal to about 2 x 10(5) or 9 x 10 (5). The angle of attack, referenced to the aft-cone, was varied from 0 deg to 20 deg. Heating distributions predicted with a parabolized Navier-Stokes (PNS) code are compared with the measurements for the present Reynolds numbers and range of angles of attack. Leeward heating was greatly affected by Reynolds number, with the heating increasing with decreasing Reynolds number for attached flow (low incidence). The opposite was true for separated flow, which occurred when the fore-cone angle of attack exceeded 0.8 times the fore-cone half-angle. Windward heating distributions were predicted to within 10 percent with the PNS code. Leeward heating distributions were predicted qualitatively for both Reynolds numbers, but quantitative agreement was poorer than on the windward side.

  13. Experimental and predicted heating distributions for biconics at incidence in air at Mach 10

    NASA Astrophysics Data System (ADS)

    Miller, C. G., III

    1984-11-01

    Heating distributions were measured on a 1.9-percent-scale model of a generic aeroassisted vehicle proposed for missions to a number of planets and for use as a moderate lift-drag ratio Earth orbital transfer vehicle. This vehicle is spherically blunted, 12.84 deg/7 deg biconic with the fore-cone bent upward 7 deg to provide self-trim capability. A straight biconic with the same nose radius and the same half-angles was also tested. The free-stream Reynolds numbers based on model length were equal to about 2 x 10(5) or 9 x 10 (5). The angle of attack, referenced to the aft-cone, was varied from 0 deg to 20 deg. Heating distributions predicted with a parabolized Navier-Stokes (PNS) code are compared with the measurements for the present Reynolds numbers and range of angles of attack. Leeward heating was greatly affected by Reynolds number, with the heating increasing with decreasing Reynolds number for attached flow (low incidence). The opposite was true for separated flow, which occurred when the fore-cone angle of attack exceeded 0.8 times the fore-cone half-angle. Windward heating distributions were predicted to within 10 percent with the PNS code. Leeward heating distributions were predicted qualitatively for both Reynolds numbers, but quantitative agreement was poorer than on the windward side.

  14. Pain-related fear predicts reduced spinal motion following experimental back injury.

    PubMed

    Trost, Zina; France, Christopher R; Sullivan, Michael J; Thomas, James S

    2012-05-01

    The current study examined the prospective relationship between pain-related fear and altered motor behavior, as well as perceived interference, among 51 healthy participants following induction of delayed-onset muscle soreness (DOMS) to the trunk extensor muscles. Healthy participants without history of back pain completed standardized reaches to high and low targets at self-paced and rapid speeds before and after induction of acute low back pain using a DOMS paradigm. Pain-related fear was assessed prior to DOMS induction. Three-dimensional joint motions of the thoracic spine, lumbar spine, and hip were recorded using an electromagnetic tracking device. DOMS-induced differences between high- and low-fear participants were observed for lumbar spine flexion, but not for thoracic or hip flexion. Pain-related fear scores were not predictive of lumbar flexion during baseline, but predicted reduced lumbar flexion during self- and fast-paced trials to low target locations once DOMS was induced. Pain-related fear was likewise predictive of perceived interference in life activities following DOMS induction. The findings suggest that initially pain-free individuals with high pain-related fear adopt avoidant spinal strategies during common reaching movements shortly after injury is sustained, which may comprise a risk factor for future pain and disability. PMID:22377437

  15. Predictive simulation and experimental confirmation of the onset of instability of explosively driven shells

    SciTech Connect

    Potocki, Mark L; Hull, Lawrence M

    2010-01-01

    The detonation of explosives with thin shells can cause the shells to expand to over 200% strain at strain rates on the order of 10{sup 4} s{sup -1} before failure. Experimental data indicate the development and growth of multiple plastic instabilities lead to the formation of failure and fragmentation in the near periodic pattern. Presented are comparisons of the onset of instabilities from simulations and experimental data. At Los Alamos National Laboratory material models have been evolving for several years to simulate high strain-rate behavior. Our models include the effects of shock heating and damage evolutions as well as failure. The current edition of one of our models uses a tabular EOS, the PTW strength model, a modified Gurson yield surface to compute damage evolution, and a Johnson-Cook failure model. Presented are some of the details of these models. An experiment confirmed the temperature discontinuities.

  16. Experimental study of rigorous nonlinear model predictive control for a packed distillation column

    SciTech Connect

    Junesam Lin; Shi-Shang Jang; Junghui Chen

    1996-12-31

    Dynamic modeling of distillation processes has been substantial in the recently years. In this work, a rigorous model for packed bed distillation system is solved using the method of collocation polynomial. The control methodology used is the two-phase approach that devises an on-line identification phase and an on-line optimization phase. The experimental studies show that the on-line control using this approach is feasible and performs better than traditional controllers. 7 refs., 3 figs.

  17. Identification of tumor-associated cassette exons in human cancer through EST-based computational prediction and experimental validation

    PubMed Central

    2010-01-01

    Background Many evidences report that alternative splicing, the mechanism which produces mRNAs and proteins with different structures and functions from the same gene, is altered in cancer cells. Thus, the identification and characterization of cancer-specific splice variants may give large impulse to the discovery of novel diagnostic and prognostic tumour biomarkers, as well as of new targets for more selective and effective therapies. Results We present here a genome-wide analysis of the alternative splicing pattern of human genes through a computational analysis of normal and cancer-specific ESTs from seventeen anatomical groups, using data available in AspicDB, a database resource for the analysis of alternative splicing in human. By using a statistical methodology, normal and cancer-specific genes, splice sites and cassette exons were predicted in silico. The condition association of some of the novel normal/tumoral cassette exons was experimentally verified by RT-qPCR assays in the same anatomical system where they were predicted. Remarkably, the presence in vivo of the predicted alternative transcripts, specific for the nervous system, was confirmed in patients affected by glioblastoma. Conclusion This study presents a novel computational methodology for the identification of tumor-associated transcript variants to be used as cancer molecular biomarkers, provides its experimental validation, and reports specific biomarkers for glioblastoma. PMID:20813049

  18. Small Crack Growth and Fatigue Life Predictions for High-Strength Aluminium Alloys. Part 1; Experimental and Fracture Mechanics Analysis

    NASA Technical Reports Server (NTRS)

    Wu, X. R.; Newman, J. C.; Zhao, W.; Swain, M. H.; Ding, C. F.; Phillips, E. P.

    1998-01-01

    The small crack effect was investigated in two high-strength aluminium alloys: 7075-T6 bare and LC9cs clad alloy. Both experimental and analytical investigations were conducted to study crack initiation and growth of small cracks. In the experimental program, fatigue tests, small crack and large crack tests A,ere conducted under constant amplitude and Mini-TWIST spectrum loading conditions. A pronounced small crack effect was observed in both materials, especially for the negative stress ratios. For all loading conditions, most of the fatigue life of the SENT specimens was shown to be crack propagation from initial material defects or from the cladding layer. In the analysis program, three-dimensional finite element and A weight function methods were used to determine stress intensity factors and to develop SIF equations for surface and corner cracks at the notch in the SENT specimens. A plastisity-induced crack-closure model was used to correlate small and large crack data, and to make fatigue life predictions, Predicted crack-growth rates and fatigue lives agreed well with experiments. A total fatigue life prediction method for the aluminum alloys was developed and demonstrated using the crack-closure model.

  19. Perspectives on Prediction Variance and Bias in Developing, Assessing, and Comparing Experimental Designs

    SciTech Connect

    Piepel, Gregory F.

    2010-12-01

    The vast majority of response surface methods used in practice to develop, assess, and compare experimental designs focus on variance properties of designs. Because response surface models only approximate the true unknown relationships, models are subject to bias errors as well as variance errors. Beginning with the seminal paper of Box and Draper (1959) and over the subsequent 50 years, methods that consider bias and mean-squared-error (variance and bias) properties of designs have been presented in the literature. However, these methods are not widely implemented in software and are not routinely used to develop, assess, and compare experimental designs in practice. Methods for developing, assessing, and comparing response surface designs that account for variance properties are reviewed. Brief synopses of publications that consider bias or mean-squared-error properties are provided. The difficulties and approaches for addressing bias properties of designs are summarized. Perspectives on experimental design methods that account for bias and/or variance properties and on future needs are presented.

  20. Validation of the thermal transport model used for ITER startup scenario predictions with DIII-D experimental data

    DOE PAGES

    Casper, T. A.; Meyer, W. H.; Jackson, G. L.; Luce, T. C.; Hyatt, A. W.; Humphreys, D. A.; Turco, F.

    2010-12-08

    We are exploring characteristics of ITER startup scenarios in similarity experiments conducted on the DIII-D Tokamak. In these experiments, we have validated scenarios for the ITER current ramp up to full current and developed methods to control the plasma parameters to achieve stability. Predictive simulations of ITER startup using 2D free-boundary equilibrium and 1D transport codes rely on accurate estimates of the electron and ion temperature profiles that determine the electrical conductivity and pressure profiles during the current rise. Here we present results of validation studies that apply the transport model used by the ITER team to DIII-D discharge evolutionmore » and comparisons with data from our similarity experiments.« less

  1. The impact of information order on intentions to undergo predictive genetic testing: an experimental study.

    PubMed

    Morrison, Val; Henderson, Bethan J; Taylor, Caroline; A'Ch Dafydd, Nonn; Unwin, Abbie

    2010-10-01

    As predictive genetic testing availability increases so does our need to understand factors associated with test uptake. This study tests whether the order positive and negative information about genetic testing for breast cancer is presented in affects intention to take a genetic test. Eighty-four women were randomly allocated into three groups: (1) positive then negative information; (2) negative then positive information; and (3) a control group. A significant effect was found in relation to perceived risk, attitudes towards genetic testing, perceived disadvantages of testing and intention. Our findings point to a primacy effect, whereby information presented first has the greatest effect.

  2. Experimental results and wear predictions of petal tools that freely rotate.

    PubMed

    Cordero-Dávila, Alberto; Cabrera-Peláez, Víctor; Cuautle-Cortés, Jorge; González-García, Jorge; Robledo-Sánchez, Carlos; Bautista-Elivar, Nazario

    2005-03-10

    It is difficult to calculate the wear produced by free-pinned tools because their angular movement is not entirely predictable. We analyze the wear produced with free-pinned ring tools, using both simulations and experiments. We conclude that the wear of an incomplete ring is directly proportional to the ring's angular size, independently of the mean radius of the ring. We present an algorithm for calculation of the wear produced by free-pinned petal tools, as they can be considered a linear combination of incomplete free-pinned ring tools. Finally, we apply this result to the enhancement of a defective flat surface and to making a concave spheric surface.

  3. Low power underwater acoustic DPSK detection: Theoretical prediction and experimental results

    NASA Astrophysics Data System (ADS)

    Dunne, Andrew

    This thesis presents two methods of analyzing the effectiveness of a prototype differential phase-shift keying (DPSK) detection circuit. The first method is to make modifications to the existing hardware to reliably output and record the cross-correlation values of the DPSK detection process. The second method is to write a MATLAB detection algorithm which accurately simulates the detection results of the hardware system without the need of any electronics. These two systems were tested and verified with a bench test using computer generated DPSK signals. The hardware system was tested using real acoustic data from shallow and deep water at-sea tests to determine the effectiveness of the DPSK detection circuit in different ocean environments. The hydrophone signals from the tests were recorded so that the cross-correlation values could be verified using the MATLAB detector. As a result of this study, these two systems provided more insight into how well the DPSK detection prototype works and helped to identify ways of improving the detection reliability and overall performance of the prototype DPSK detection circuit.

  4. Experimental Observations and Numerical Prediction of Induction Heating in a Graphite Test Article

    SciTech Connect

    Jankowski, Todd A; Johnson, Debra P; Jurney, James D; Freer, Jerry E; Dougherty, Lisa M; Stout, Stephen A

    2009-01-01

    The induction heating coils used in the plutonium casting furnaces at the Los Alamos National Laboratory are studied here. A cylindrical graphite test article has been built, instrumented with thermocouples, and heated in the induction coil that is normally used to preheat the molds during casting operations. Preliminary results of experiments aimed at understanding the induction heating process in the mold portion of the furnaces are reported. The experiments have been modeled in COMSOL Multiphysics and the numerical and experimental results are compared to one another. These comparisons provide insight into the heating process and provide a benchmark for COMSOL calculations of induction heating in the mold portion of the plutonium casting furnaces.

  5. Highly porous thermal protection materials: Modelling and prediction of the methodical experimental errors

    NASA Astrophysics Data System (ADS)

    Cherepanov, Valery V.; Alifanov, Oleg M.; Morzhukhina, Alena V.; Budnik, Sergey A.

    2016-11-01

    The formation mechanisms and the main factors affecting the systematic error of thermocouples were investigated. According to the results of experimental studies and mathematical modelling it was established that in highly porous heat resistant materials for aerospace application the thermocouple errors are determined by two competing mechanisms provided correlation between the errors and the difference between radiation and conduction heat fluxes. The comparative analysis was carried out and some features of the methodical error formation related to the distances from the heated surface were established.

  6. Numerical and experimental predictions of fine-soil erosion, transport and trapping in embankment dam

    NASA Astrophysics Data System (ADS)

    Kanarska, Y.; Lomov, I.; Ezzedine, S. M.; Antoun, T. H.; Glascoe, L. G.

    2011-12-01

    A determination of the safety of dam structures requires the characterization of fine-soil erosion processes and the ability of filter layers to capture fine-soil particles to prevent dam failure. We investigated numerically and experimentally different aspects of this problem at a grain scale. The numerical method was based on Lagrange multiplier technique (Kanarska et al., 2011). The particle-particle interactions were implemented using explicit force-displacement interactions for frictional inelastic particles similar to the distinct element method (DEM) (Cundall and Strack, 1979), with some modifications using the volume of the overlapping region as the input to the contact forces. The first set of numerical tests was performed to describe the response of a granular bed to forcing by a fluid, which flows over the crack surface. We investigated how particle properties, such as size and shape, affect threshold values for critical shear stresses and mean velocities. A good agreement between numerical results and experiments was found. A general constitutive erosion law, critical shear stresses, and erosion velocities were derived and validated against the available experimental range of conditions for different particle sizes, particle shapes, and flow conditions. We confirmed that a linear relationship between particle mass fluxes and shear stresses well describes soil behavior. A second set of numerical and experimental tests to investigate sediment trapping in the filter layers was also performed. The laboratory experiments on soil transport and trapping in granular media were conducted in constant-head flow chamber filled with filter media. We investigated how particle properties and amplitude of the applied hydraulic gradient affect clogging criteria and changes in hydraulic conductivity of the medium. The numerical results were validated against available experimental data. We started with spherical particles. In the future, we are planning to investigate

  7. Mechanism of alkoxy groups substitution by Grignard reagents on aromatic rings and experimental verification of theoretical predictions of anomalous reactions.

    PubMed

    Jiménez-Osés, Gonzalo; Brockway, Anthony J; Shaw, Jared T; Houk, K N

    2013-05-01

    The mechanism of direct displacement of alkoxy groups in vinylogous and aromatic esters by Grignard reagents, a reaction that is not observed with expectedly better tosyloxy leaving groups, is elucidated computationally. The mechanism of this reaction has been determined to proceed through the inner-sphere attack of nucleophilic alkyl groups from magnesium to the reacting carbons via a metalaoxetane transition state. The formation of a strong magnesium chelate with the reacting alkoxy and carbonyl groups dictates the observed reactivity and selectivity. The influence of ester, ketone, and aldehyde substituents was investigated. In some cases, the calculations predicted the formation of products different than those previously reported; these predictions were then verified experimentally. The importance of studying the actual system, and not simplified models as computational systems, is demonstrated. PMID:23601086

  8. Optimal control model predictions of system performance and attention allocation and their experimental validation in a display design study

    NASA Technical Reports Server (NTRS)

    Johannsen, G.; Govindaraj, T.

    1980-01-01

    The influence of different types of predictor displays in a longitudinal vertical takeoff and landing (VTOL) hover task is analyzed in a theoretical study. Several cases with differing amounts of predictive and rate information are compared. The optimal control model of the human operator is used to estimate human and system performance in terms of root-mean-square (rms) values and to compute optimized attention allocation. The only part of the model which is varied to predict these data is the observation matrix. Typical cases are selected for a subsequent experimental validation. The rms values as well as eye-movement data are recorded. The results agree favorably with those of the theoretical study in terms of relative differences. Better matching is achieved by revised model input data.

  9. Mechanism of Alkoxy Groups Substitution by Grignard Reagents on Aromatic Rings and Experimental Verification of Theoretical Predictions of Anomalous Reactions

    PubMed Central

    Jiménez-Osés, Gonzalo; Brockway, Anthony J.; Shaw, Jared T.; Houk, K. N.

    2013-01-01

    The mechanism of direct displacement of alkoxy groups in vinylogous and aromatic esters by Grignard reagents, a reaction that is not observed with expectedly better tosyloxy leaving groups, is elucidated computationally. The mechanism of this reaction has been determined to proceed through the inner-sphere attack of nucleophilic alkyl groups from magnesium to the reacting carbons via a metalaoxetane transition state. The formation of a strong magnesium chelate with the reacting alkoxy and carbonyl groups dictates the observed reactivity and selectivity. The influence of ester, ketone and aldehyde substituents was investigated. In some cases, the calculations predicted the formation of products different than those previously reported; these predictions were then verified experimentally. The importance of studying the actual system, and not simplified models as computational systems, is demonstrated. PMID:23601086

  10. MHD seawater thruster performance: A comparison of predictions with experimental results from a two Tesla test facility

    SciTech Connect

    Picologlou, B.F.; Doss, E.D.; Geyer, H.K. ); Sikes, W.C.; Ranellone, R.F. )

    1992-01-01

    A two Tesla test facility was designed, built, and operated to investigate the performance of magnetohydrodynamic (MHD) seawater thrusters. The results of this investigation are used to validate a design oriented MHD thruster performance computer code. The thruster performance code consists of a one-dimensional MHD hydrodynamic model coupled to a two-dimensional electrical model. The code includes major loss mechanisms affecting the performance of the thruster. Among these losses are the joule dissipation losses, frictional losses, electrical end losses, and single electrode potential losses. The facility test loop, its components, and their design are presented in detail. Additionally, the test matrix and its rationale are discussed. Representative experimental results of the test program are presented, and are compared to pretest computer model predictions. Good agreement between predicted and measured data has served to validate the thruster performance computer models.

  11. Prediction and experimental validation of enzyme substrate specificity in protein structures

    PubMed Central

    Amin, Shivas R.; Erdin, Serkan; Ward, R. Matthew; Lua, Rhonald C.; Lichtarge, Olivier

    2013-01-01

    Structural Genomics aims to elucidate protein structures to identify their functions. Unfortunately, the variation of just a few residues can be enough to alter activity or binding specificity and limit the functional resolution of annotations based on sequence and structure; in enzymes, substrates are especially difficult to predict. Here, large-scale controls and direct experiments show that the local similarity of five or six residues selected because they are evolutionarily important and on the protein surface can suffice to identify an enzyme activity and substrate. A motif of five residues predicted that a previously uncharacterized Silicibacter sp. protein was a carboxylesterase for short fatty acyl chains, similar to hormone-sensitive-lipase–like proteins that share less than 20% sequence identity. Assays and directed mutations confirmed this activity and showed that the motif was essential for catalysis and substrate specificity. We conclude that evolutionary and structural information may be combined on a Structural Genomics scale to create motifs of mixed catalytic and noncatalytic residues that identify enzyme activity and substrate specificity. PMID:24145433

  12. An experimentally based approach for predicting skin permeability of chemicals and drugs using a membrane-coated fiber array

    SciTech Connect

    Xia Xinrui . E-mail: xia@cctrp.ncsu.edu; Baynes, Ronald E.; Monteiro-Riviere, Nancy A.; Riviere, Jim E.

    2007-06-15

    A membrane-coated fiber (MCF) array approach is proposed for predicting the percutaneous absorption of chemicals and drugs from chemical or biological mixtures. Multiple MCFs were used to determine the partition coefficients of compounds (logK {sub MCF}). We hypothesized that one MCF will characterize one pattern of molecular interactions and therefore the skin absorption process can be simulated by a multiple MCF array having diverse patterns of molecular interactions. Three MCFs, polydimethylsiloxane (PDMS), polyacrylate (PA) and CarboWax (Wax), were used to determine the logK {sub MCF} values for a set of calibration compounds. The skin permeability log(kp) of the compounds was measured by diffusion experiments using porcine skin. The feasibility of the MCF array approach for predicting skin permeability was demonstrated with the three MCFs. A mathematical model was established by multiple linear regression analysis of the log(kp) and logK {sub MCF} data set: log(kp) = - 2.34-0.124 logK {sub pdms} + 1.91 logK {sub pa} - 1.17 logK {sub wax} (n = 25, R {sup 2} = 0.93). The MCF array approach is an alternative animal model for skin permeability measurement. It is an experimentally based, high throughput approach that provides high prediction confidence and does not require literature data nor molecular structure information in contrast to the existing predictive models.

  13. Prediction of redox potentials of adrenaline and its supramolecular complex with glycine: theoretical and experimental studies.

    PubMed

    Liu, Tao; Du, Chunmei; Yu, Zhangyu; Han, Lingli; Zhang, Dongju

    2013-02-21

    Protonated adrenaline (PAd) can be oxidized to protonated adrenaline quinone (PAdquinone) through a one-step, two-electron redox reaction. The electron-transfer property of PAd and its supramolecular complex with glycine has been investigated by cyclic voltammetry (CV) experiment and theoretical calculations. From CV curves, the conditional formal redox potential E°' of PAd/PAdquinone couple at the pH value of 0.29 is determined to be 0.540 V. The calculated E°' using the G3MP2//B3LYP method and the B3LYP method with 6-31G(d,p), 6-31+G(d,p), 6-311G(d,p), and B3LYP/6-311+G(d,p) basis sets are in reasonable agreement with the experimental value. PAd can form supramolecular complex (PAd-Gly) with glycine (Gly) through hydrogen bond (H-bond), and the calculated E°' values of PAd-Gly/PAdquinone-Gly redox couple are larger than those of PAd/PAdquinone couple. The theoretical results are in good agreement with the experimental finding that the formation of H-bonds weaken the electron-donating ability of PAd.

  14. Experimentally testing and assessing the predictive power of species assembly rules for tropical canopy ants

    PubMed Central

    Fayle, Tom M; Eggleton, Paul; Manica, Andrea; Yusah, Kalsum M; Foster, William A

    2015-01-01

    Understanding how species assemble into communities is a key goal in ecology. However, assembly rules are rarely tested experimentally, and their ability to shape real communities is poorly known. We surveyed a diverse community of epiphyte-dwelling ants and found that similar-sized species co-occurred less often than expected. Laboratory experiments demonstrated that invasion was discouraged by the presence of similarly sized resident species. The size difference for which invasion was less likely was the same as that for which wild species exhibited reduced co-occurrence. Finally we explored whether our experimentally derived assembly rules could simulate realistic communities. Communities simulated using size-based species assembly exhibited diversities closer to wild communities than those simulated using size-independent assembly, with results being sensitive to the combination of rules employed. Hence, species segregation in the wild can be driven by competitive species assembly, and this process is sufficient to generate observed species abundance distributions for tropical epiphyte-dwelling ants. PMID:25622647

  15. An experimental paradigm for the prediction of Post-Operative Pain (PPOP).

    PubMed

    Landau, Ruth; Kraft, John C; Flint, Lisa Y; Carvalho, Brendan; Richebé, Philippe; Cardoso, Monica; Lavand'homme, Patricia; Granot, Michal; Yarnitsky, David; Cahana, Alex

    2010-01-01

    Many women undergo cesarean delivery without problems, however some experience significant pain after cesarean section. Pain is associated with negative short-term and long-term effects on the mother. Prior to women undergoing surgery, can we predict who is at risk for developing significant postoperative pain and potentially prevent or minimize its negative consequences? These are the fundamental questions that a team from the University of Washington, Stanford University, the Catholic University in Brussels, Belgium, Santa Joana Women's Hospital in São Paulo, Brazil, and Rambam Medical Center in Israel is currently evaluating in an international research collaboration. The ultimate goal of this project is to provide optimal pain relief during and after cesarean section by offering individualized anesthetic care to women who appear to be more 'susceptible' to pain after surgery. A significant number of women experience moderate or severe acute post-partum pain after vaginal and cesarean deliveries. (1) Furthermore, 10-15% of women suffer chronic persistent pain after cesarean section. (2) With constant increase in cesarean rates in the US (3) and the already high rate in Brazil, this is bound to create a significant public health problem. When questioning women's fears and expectations from cesarean section, pain during and after it is their greatest concern. (4) Individual variability in severity of pain after vaginal or operative delivery is influenced by multiple factors including sensitivity to pain, psychological factors, age, and genetics. The unique birth experience leads to unpredictable requirements for analgesics, from 'none at all' to 'very high' doses of pain medication. Pain after cesarean section is an excellent model to study post-operative pain because it is performed on otherwise young and healthy women. Therefore, it is recommended to attenuate the pain during the acute phase because this may lead to chronic pain disorders. The impact of

  16. Main magnetic focus ion source: Basic principles, theoretical predictions and experimental confirmations

    NASA Astrophysics Data System (ADS)

    Ovsyannikov, V. P.; Nefiodov, A. V.

    2016-03-01

    It is proposed to produce highly charged ions in the local potential traps formed by the rippled electron beam in a focusing magnetic field. In this method, extremely high electron current densities can be attained on short length of the ion trap. The design of very compact ion sources of the new generation is presented. The computer simulations predict that for such ions as, for example, Ne8+ and Xe44+, the intensities of about 109 and 106 ions per second, respectively, can be obtained. The experiments with pilot example of the ion source confirm efficiency of the suggested method. The X-ray emission from Ir59+, Xe44+ and Ar16+ ions was detected. The control over depth of the local ion trap is shown to be feasible.

  17. Experimental investigation of the predictive capabilities of data driven modeling techniques in hydrology - Part 2: Application

    NASA Astrophysics Data System (ADS)

    Elshorbagy, A.; Corzo, G.; Srinivasulu, S.; Solomatine, D. P.

    2010-10-01

    In this second part of the two-part paper, the data driven modeling (DDM) experiment, presented and explained in the first part, is implemented. Inputs for the five case studies (half-hourly actual evapotranspiration, daily peat soil moisture, daily till soil moisture, and two daily rainfall-runoff datasets) are identified, either based on previous studies or using the mutual information content. Twelve groups (realizations) were randomly generated from each dataset by randomly sampling without replacement from the original dataset. Neural networks (ANNs), genetic programming (GP), evolutionary polynomial regression (EPR), Support vector machines (SVM), M5 model trees (M5), K-nearest neighbors (K-nn), and multiple linear regression (MLR) techniques are implemented and applied to each of the 12 realizations of each case study. The predictive accuracy and uncertainties of the various techniques are assessed using multiple average overall error measures, scatter plots, frequency distribution of model residuals, and the deterioration rate of prediction performance during the testing phase. Gamma test is used as a guide to assist in selecting the appropriate modeling technique. Unlike two nonlinear soil moisture case studies, the results of the experiment conducted in this research study show that ANNs were a sub-optimal choice for the actual evapotranspiration and the two rainfall-runoff case studies. GP is the most successful technique due to its ability to adapt the model complexity to the modeled data. EPR performance could be close to GP with datasets that are more linear than nonlinear. SVM is sensitive to the kernel choice and if appropriately selected, the performance of SVM can improve. M5 performs very well with linear and semi linear data, which cover wide range of hydrological situations. In highly nonlinear case studies, ANNs, K-nn, and GP could be more successful than other modeling techniques. K-nn is also successful in linear situations, and it should

  18. Experimental investigation of the predictive capabilities of data driven modeling techniques in hydrology - Part 2: Application

    NASA Astrophysics Data System (ADS)

    Elshorbagy, A.; Corzo, G.; Srinivasulu, S.; Solomatine, D. P.

    2009-11-01

    In this second part of the two-part paper, the data driven modeling (DDM) experiment, presented and explained in the first part, is implemented. Inputs for the five case studies (half-hourly actual evapotranspiration, daily peat soil moisture, daily till soil moisture, and two daily rainfall-runoff datasets) are identified, either based on previous studies or using the mutual information content. Twelve groups (realizations) were randomly generated from each dataset by randomly sampling without replacement from the original dataset. Neural networks (ANNs), genetic programming (GP), evolutionary polynomial regression (EPR), Support vector machines (SVM), M5 model trees (M5), K nearest neighbors (K-nn), and multiple linear regression (MLR) techniques are implemented and applied to each of the 12 realizations of each case study. The predictive accuracy and uncertainties of the various techniques are assessed using multiple average overall error measures, scatter plots, frequency distribution of model residuals, and the deterioration rate of prediction performance during the testing phase. Gamma test is used as a guide to assist in selecting the appropriate modeling technique. Unlike the two nonlinear soil moisture case studies, the results of the experiment conducted in this research study show that ANNs were a sub-optimal choice for the actual evapotranspiration and the two rainfall-runoff case studies. GP is the most successful technique due to its ability to adapt the model complexity to the modeled data. EPR performance could be close to GP with datasets that are more linear than nonlinear. SVM is sensitive to the kernel choice and if appropriately selected, the performance of SVM can improve. M5 performs very well with linear and semi linear data, which cover wide range of hydrological situations. In highly nonlinear case studies, ANNs, K-nn, and GP could be more successful than other modeling techniques. K-nn is also successful in linear situations, and it

  19. An accurate potential energy curve for helium based on ab initio calculations

    NASA Astrophysics Data System (ADS)

    Janzen, A. R.; Aziz, R. A.

    1997-07-01

    Korona, Williams, Bukowski, Jeziorski, and Szalewicz [J. Chem. Phys. 106, 1 (1997)] constructed a completely ab initio potential for He2 by fitting their calculations using infinite order symmetry adapted perturbation theory at intermediate range, existing Green's function Monte Carlo calculations at short range and accurate dispersion coefficients at long range to a modified Tang-Toennies potential form. The potential with retardation added to the dipole-dipole dispersion is found to predict accurately a large set of microscopic and macroscopic experimental data. The potential with a significantly larger well depth than other recent potentials is judged to be the most accurate characterization of the helium interaction yet proposed.

  20. Edge Length and Surface Area of a Blank: Experimental Assessment of Measures, Size Predictions and Utility

    PubMed Central

    Dogandžić, Tamara; Braun, David R.; McPherron, Shannon P.

    2015-01-01

    Blank size and form represent one of the main sources of variation in lithic assemblages. They reflect economic properties of blanks and factors such as efficiency and use life. These properties require reliable measures of size, namely edge length and surface area. These measures, however, are not easily captured with calipers. Most attempts to quantify these features employ estimates; however, the efficacy of these estimations for measuring critical features such as blank surface area and edge length has never been properly evaluated. In addition, these parameters are even more difficult to acquire for retouched implements as their original size and hence indication of their previous utility have been lost. It has been suggested, in controlled experimental conditions, that two platform variables, platform thickness and exterior platform angle, are crucial in determining blank size and shape meaning that knappers can control the interaction between size and efficiency by selecting specific core angles and controlling where fracture is initiated. The robustness of these models has rarely been tested and confirmed in context other than controlled experiments. In this paper, we evaluate which currently employed caliper measurement methods result in the highest accuracy of size estimations of blanks, and we evaluate how platform variables can be used to indirectly infer aspects of size on retouched artifacts. Furthermore, we investigate measures of different platform management strategies that control the shape and size of artifacts. To investigate these questions, we created an experimental lithic assemblage, we digitized images to calculate 2D surface area and edge length, which are used as a point of comparison for the caliper measurements and additional analyses. The analysis of aspects of size determinations and the utility of blanks contributes to our understanding of the technological strategies of prehistoric knappers and what economic decisions they made

  1. Prognosis Can Be Predicted More Accurately Using Pre- and Postchemoradiotherapy Carcinoembryonic Antigen Levels Compared to Only Prechemoradiotherapy Carcinoembryonic Antigen Level in Locally Advanced Rectal Cancer Patients Who Received Neoadjuvant Chemoradiotherapy

    PubMed Central

    Sung, SooYoon; Son, Seok Hyun; Kay, Chul Seung; Lee, Yoon Suk

    2016-01-01

    Abstract We aimed to evaluate the prognostic value of a change in the carcinoembryonic antigen (CEA) level during neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer. A total of 110 patients with clinical T3/T4 or node-positive disease underwent nCRT and curative total mesorectal resection from February 2006 to December 2013. Serum CEA level was measured before nCRT, after nCRT, and then again after surgery. A cut-off value for CEA level to predict prognosis was determined using the maximally selected log-rank test. According to the test, patients were classified into 3 groups, based on their CEA levels (Group A: pre-CRT CEA ≤3.2; Group B: pre-CRT CEA level >3.2 and post-CRT CEA ≤2.8; and Group C: pre-CRT CEA >3.2 and post-CRT CEA >2.8). The median follow-up time was 31.1 months. The 3-year disease-free survival (DFS) rates of Group A and Group B were similar, while Group C showed a significantly lower 3-year DFS rate (82.5% vs. 89.5% vs. 55.1%, respectively, P = 0.001). Other clinicopathological factors that showed statistical significance on univariate analysis were pre-CRT CEA, post-CRT CEA, tumor distance from the anal verge, surgery type, downstage, pathologic N stage, margin status and perineural invasion. The CEA group (P = 0.001) and tumor distance from the anal verge (P = 0.044) were significant prognostic factors for DFS on multivariate analysis. Post-CRT CEA level may be a useful prognostic factor in patients whose prognosis cannot be predicted exactly by pre-CRT CEA levels alone in the neoadjuvant treatment era. Combined pre-CRT CEA and post-CRT CEA levels enable us to predict prognosis more accurately and determine treatment and follow-up policies. Further large-scale studies are necessary to validate the prognostic value of CEA levels. PMID:26962798

  2. Flow of variably fluidized granular masses across three-dimensional terrain 2. Numerical predictions and experimental tests

    USGS Publications Warehouse

    Denlinger, R.P.; Iverson, R.M.

    2001-01-01

    Numerical solutions of the equations describing flow of variably fluidized Coulomb mixtures predict key features of dry granular avalanches and water-saturated debris flows measured in physical experiments. These features include time-dependent speeds, depths, and widths of flows as well as the geometry of resulting deposits. Threedimensional (3-D) boundary surfaces strongly influence flow dynamics because transverse shearing and cross-stream momentum transport occur where topography obstructs or redirects motion. Consequent energy dissipation can cause local deceleration and deposition, even on steep slopes. Velocities of surge fronts and other discontinuities that develop as flows cross 3-D terrain are predicted accurately by using a Riemann solution algorithm. The algorithm employs a gravity wave speed that accounts for different intensities of lateral stress transfer in regions of extending and compressing flow and in regions with different degrees of fluidization. Field observations and experiments indicate that flows in which fluid plays a significant role typically have high-friction margins with weaker interiors partly fluidized by pore pressure. Interaction of the strong perimeter and weak interior produces relatively steep-sided, flat-topped deposits. To simulate these effects, we compute pore pressure distributions using an advection-diffusion model with enhanced diffusivity near flow margins. Although challenges remain in evaluating pore pressure distributions in diverse geophysical flows, Riemann solutions of the depthaveraged 3-D Coulomb mixture equations provide a powerful tool for interpreting and predicting flow behavior. They provide a means of modeling debris flows, rock avalanches, pyroclastic flows, and related phenomena without invoking and calibrating Theological parameters that have questionable physical significance.

  3. Quality assessment of maize assembled genomic islands (MAGIs) and large-scale experimental verification of predicted genes.

    PubMed

    Fu, Yan; Emrich, Scott J; Guo, Ling; Wen, Tsui-Jung; Ashlock, Daniel A; Aluru, Srinivas; Schnable, Patrick S

    2005-08-23

    Recent sequencing efforts have targeted the gene-rich regions of the maize (Zea mays L.) genome. We report the release of an improved assembly of maize assembled genomic islands (MAGIs). The 114,173 resulting contigs have been subjected to computational and physical quality assessments. Comparisons to the sequences of maize bacterial artificial chromosomes suggest that at least 97% (160 of 165) of MAGIs are correctly assembled. Because the rates at which junction-testing PCR primers for genomic survey sequences (90-92%) amplify genomic DNA are not significantly different from those of control primers ( approximately 91%), we conclude that a very high percentage of genic MAGIs accurately reflect the structure of the maize genome. EST alignments, ab initio gene prediction, and sequence similarity searches of the MAGIs are available at the Iowa State University MAGI web site. This assembly contains 46,688 ab initio predicted genes. The expression of almost half (628 of 1,369) of a sample of the predicted genes that lack expression evidence was validated by RT-PCR. Our analyses suggest that the maize genome contains between approximately 33,000 and approximately 54,000 expressed genes. Approximately 5% (32 of 628) of the maize transcripts discovered do not have detectable paralogs among maize ESTs or detectable homologs from other species in the GenBank NR nucleotide/protein database. Analyses therefore suggest that this assembly of the maize genome contains approximately 350 previously uncharacterized expressed genes. We hypothesize that these "orphans" evolved quickly during maize evolution and/or domestication.

  4. SUBA3: a database for integrating experimentation and prediction to define the SUBcellular location of proteins in Arabidopsis

    PubMed Central

    Tanz, Sandra K.; Castleden, Ian; Hooper, Cornelia M.; Vacher, Michael; Small, Ian; Millar, Harvey A.

    2013-01-01

    The subcellular location database for Arabidopsis proteins (SUBA3, http://suba.plantenergy.uwa.edu.au) combines manual literature curation of large-scale subcellular proteomics, fluorescent protein visualization and protein–protein interaction (PPI) datasets with subcellular targeting calls from 22 prediction programs. More than 14 500 new experimental locations have been added since its first release in 2007. Overall, nearly 650 000 new calls of subcellular location for 35 388 non-redundant Arabidopsis proteins are included (almost six times the information in the previous SUBA version). A re-designed interface makes the SUBA3 site more intuitive and easier to use than earlier versions and provides powerful options to search for PPIs within the context of cell compartmentation. SUBA3 also includes detailed localization information for reference organelle datasets and incorporates green fluorescent protein (GFP) images for many proteins. To determine as objectively as possible where a particular protein is located, we have developed SUBAcon, a Bayesian approach that incorporates experimental localization and targeting prediction data to best estimate a protein’s location in the cell. The probabilities of subcellular location for each protein are provided and displayed as a pictographic heat map of a plant cell in SUBA3. PMID:23180787

  5. Computational Prediction and Experimental Validation of Signal Peptide Cleavage in the Extracellular Proteome of a Natural Microbial Community

    SciTech Connect

    Erickson, Brian K; Mueller, Ryan; Verberkmoes, Nathan C; Shah, Manesh B; Singer, Steven; Thelen, Michael P.; Banfield, Jillian F.; Hettich, Robert {Bob} L

    2010-01-01

    An integrated computational/experimental approach was used to predict and identify signal peptide cleavages among microbial proteins of environmental biofilm communities growing in acid mine drainage (AMD). SignalP-3.0 was employed to computationally query the AMD protein database of >16,000 proteins, which resulted in 1,480 predicted signal peptide cleaved proteins. LC-MS/MS analyses of extracellular (secretome) microbial preparations from different locations and developmental states empirically confirmed 531 of these signal peptide cleaved proteins. The majority of signal-cleavage proteins (58.4%) are annotated to have unknown functions; however, Pfam domain analysis revealed that many may be involved in extracellular functions expected within the AMD system. Examination of the abundances of signal-cleaved proteins across 28 proteomes from biofilms collected over a 4-year period demonstrated a strong correlation with the developmental state of the biofilm. For example, class I cytochromes are abundant in early growth states, whereas cytochrome oxidases from the same organism increase in abundance later in development. These results likely reflect shifts in metabolism that occur as biofilms thicken and communities diversify. In total, these results provide experimental confirmation of proteins that are designed to function in the extreme acidic extracellular environment and will serve as targets for future biochemical analysis.

  6. Prediction and Validation of Transcription Factors Modulating the Expression of Sestrin3 Gene Using an Integrated Computational and Experimental Approach.

    PubMed

    Srivastava, Rajneesh; Zhang, Yang; Xiong, Xiwen; Zhang, Xiaoning; Pan, Xiaoyan; Dong, X Charlie; Liangpunsakul, Suthat; Janga, Sarath Chandra

    2016-01-01

    SESN3 has been implicated in multiple biological processes including protection against oxidative stress, regulation of glucose and lipid metabolism. However, little is known about the factors and mechanisms controlling its gene expression at the transcriptional level. We performed in silico phylogenetic footprinting analysis of 5 kb upstream regions of a diverse set of human SESN3 orthologs for the identification of high confidence conserved binding motifs (BMo). We further analyzed the predicted BMo by a motif comparison tool to identify the TFs likely to bind these discovered motifs. Predicted TFs were then integrated with experimentally known protein-protein interactions and experimentally validated to delineate the important transcriptional regulators of SESN3. Our study revealed high confidence set of BMos (integrated with DNase I hypersensitivity sites) in the upstream regulatory regions of SESN3 that could be bound by transcription factors from multiple families including FOXOs, SMADs, SOXs, TCFs and HNF4A. TF-TF network analysis established hubs of interaction that include SMAD3, TCF3, SMAD2, HDAC2, SOX2, TAL1 and TCF12 as well as the likely protein complexes formed between them. We show using ChIP-PCR as well as over-expression and knock out studies that FOXO3 and SOX2 transcriptionally regulate the expression of SESN3 gene. Our findings provide an important roadmap to further our understanding on the regulation of SESN3. PMID:27466818

  7. Prediction and Validation of Transcription Factors Modulating the Expression of Sestrin3 Gene Using an Integrated Computational and Experimental Approach

    PubMed Central

    Srivastava, Rajneesh; Zhang, Yang; Xiong, Xiwen; Zhang, Xiaoning; Pan, Xiaoyan; Dong, X. Charlie; Liangpunsakul, Suthat; Janga, Sarath Chandra

    2016-01-01

    SESN3 has been implicated in multiple biological processes including protection against oxidative stress, regulation of glucose and lipid metabolism. However, little is known about the factors and mechanisms controlling its gene expression at the transcriptional level. We performed in silico phylogenetic footprinting analysis of 5 kb upstream regions of a diverse set of human SESN3 orthologs for the identification of high confidence conserved binding motifs (BMo). We further analyzed the predicted BMo by a motif comparison tool to identify the TFs likely to bind these discovered motifs. Predicted TFs were then integrated with experimentally known protein-protein interactions and experimentally validated to delineate the important transcriptional regulators of SESN3. Our study revealed high confidence set of BMos (integrated with DNase I hypersensitivity sites) in the upstream regulatory regions of SESN3 that could be bound by transcription factors from multiple families including FOXOs, SMADs, SOXs, TCFs and HNF4A. TF-TF network analysis established hubs of interaction that include SMAD3, TCF3, SMAD2, HDAC2, SOX2, TAL1 and TCF12 as well as the likely protein complexes formed between them. We show using ChIP-PCR as well as over-expression and knock out studies that FOXO3 and SOX2 transcriptionally regulate the expression of SESN3 gene. Our findings provide an important roadmap to further our understanding on the regulation of SESN3. PMID:27466818

  8. X-33 Computational Aeroheating/Aerodynamic Predictions and Comparisons With Experimental Data

    NASA Technical Reports Server (NTRS)

    Hollis, Brian R.; Thompson, Richard A.; Berry, Scott A.; Horvath, Thomas J.; Murphy, Kelly J.; Nowak, Robert J.; Alter, Stephen J.

    2003-01-01

    This report details a computational fluid dynamics study conducted in support of the phase II development of the X-33 vehicle. Aerodynamic and aeroheating predictions were generated for the X-33 vehicle at both flight and wind-tunnel test conditions using two finite-volume, Navier-Stokes solvers. Aerodynamic computations were performed at Mach 6 and Mach 10 wind-tunnel conditions for angles of attack from 10 to 50 with body-flap deflections of 0 to 20. Additional aerodynamic computations were performed over a parametric range of free-stream conditions at Mach numbers of 4 to 10 and angles of attack from 10 to 50. Laminar and turbulent wind-