Science.gov

Sample records for accurate performance predictions

  1. 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.

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

    PubMed

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

    2015-09-01

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

  3. Can medical students accurately predict their learning? A study comparing perceived and actual performance in neuroanatomy.

    PubMed

    Hall, Samuel R; Stephens, Jonny R; Seaby, Eleanor G; Andrade, Matheus Gesteira; Lowry, Andrew F; Parton, Will J C; Smith, Claire F; Border, Scott

    2016-10-01

    It is important that clinicians are able to adequately assess their level of knowledge and competence in order to be safe practitioners of medicine. The medical literature contains numerous examples of poor self-assessment accuracy amongst medical students over a range of subjects however this ability in neuroanatomy has yet to be observed. Second year medical students attending neuroanatomy revision sessions at the University of Southampton and the competitors of the National Undergraduate Neuroanatomy Competition were asked to rate their level of knowledge in neuroanatomy. The responses from the former group were compared to performance on a ten item multiple choice question examination and the latter group were compared to their performance within the competition. In both cohorts, self-assessments of perceived level of knowledge correlated weakly to their performance in their respective objective knowledge assessments (r = 0.30 and r = 0.44). Within the NUNC, this correlation improved when students were instead asked to rate their performance on a specific examination within the competition (spotter, rS = 0.68; MCQ, rS = 0.58). Despite its inherent difficulty, medical student self-assessment accuracy in neuroanatomy is comparable to other subjects within the medical curriculum. Anat Sci Educ 9: 488-495. © 2016 American Association of Anatomists.

  4. 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

  5. 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

  6. 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.

  7. 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

  8. Can Appraisers Rate Work Performance Accurately?

    ERIC Educational Resources Information Center

    Hedge, Jerry W.; Laue, Frances J.

    The ability of individuals to make accurate judgments about others is examined and literature on this subject is reviewed. A wide variety of situational factors affects the appraisal of performance. It is generally accepted that the purpose of the appraisal influences the accuracy of the appraiser. The instrumentation, or tools, available to the…

  9. 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.

  10. Can Scores on an Interim High School Reading Assessment Accurately Predict Low Performance on College Readiness Exams? REL 2016-124

    ERIC Educational Resources Information Center

    Koon, Sharon; Petscher, Yaacov

    2016-01-01

    During the 2013/14 school year two Florida school districts sought to develop an early warning system to identify students at risk of low performance on college readiness measures in grade 11 or 12 (such as the SAT or ACT) in order to support them with remedial coursework prior to high school graduation. The study presented in this report provides…

  11. 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.

  12. 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.

  13. EVA Performance Prediction

    NASA Technical Reports Server (NTRS)

    Peacock, Brian; Maida, James; Rajulu, Sudhakar

    2004-01-01

    Astronaut physical performance capabilities in micro gravity EV A or on planetary surfaces when encumbered by a life support suit and debilitated by a long exposure to micro gravity will be less than unencumbered pre flight capabilities. The big question addressed by human factors engineers is: what can the astronaut be expected to do on EVA or when we arrive at a planetary surface? A second question is: what aids to performance will be needed to enhance the human physical capability? These questions are important for a number of reasons. First it is necessary to carry out accurate planning of human physical demands to ensure that time and energy critical tasks can be carried out with confidence. Second it is important that the crew members (and their ground or planetary base monitors) have a realistic picture of their own capabilities, as excessive fatigue can lead to catastrophic failure. Third it is important to design appropriate equipment to enhance human sensory capabilities, locomotion, materials handling and manipulation. The evidence from physiological research points to musculoskeletal, cardiovascular and neurovestibular degradation during long duration exposure to micro gravity . The evidence from the biomechanics laboratory (and the Neutral Buoyancy Laboratory) points to a reduction in range of motion, strength and stamina when encumbered by a pressurized suit. The evidence from a long history of EVAs is that crewmembers are indeed restricted in their physical capabilities. There is a wealth of evidence in the literature on the causes and effects of degraded human performance in the laboratory, in sports and athletics, in industry and in other physically demanding jobs. One approach to this challenge is through biomechanical and performance modeling. Such models must be based on thorough task analysis, reliable human performance data from controlled studies, and functional extrapolations validated in analog contexts. The task analyses currently carried

  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. 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

  18. 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

  19. 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

  20. 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

  1. 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.

  2. 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

  3. Mouse models of human AML accurately predict chemotherapy response

    PubMed Central

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

    2009-01-01

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

  4. PREVAPORATION PERFORMANCE PREDICTION SOFTWARE

    EPA Science Inventory

    The Pervaporation, Performance, Prediction Software and Database (PPPS&D) computer software program is currently being developed within the USEPA, NRMRL. The purpose of the PPPS&D program is to educate and assist potential users in identifying opportunities for using pervaporati...

  5. 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

  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 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

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

    PubMed Central

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

    2015-01-01

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

  9. 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.

  10. An Accurate Link Correlation Estimator for Improving Wireless Protocol Performance

    PubMed Central

    Zhao, Zhiwei; Xu, Xianghua; Dong, Wei; Bu, Jiajun

    2015-01-01

    Wireless link correlation has shown significant impact on the performance of various sensor network protocols. Many works have been devoted to exploiting link correlation for protocol improvements. However, the effectiveness of these designs heavily relies on the accuracy of link correlation measurement. In this paper, we investigate state-of-the-art link correlation measurement and analyze the limitations of existing works. We then propose a novel lightweight and accurate link correlation estimation (LACE) approach based on the reasoning of link correlation formation. LACE combines both long-term and short-term link behaviors for link correlation estimation. We implement LACE as a stand-alone interface in TinyOS and incorporate it into both routing and flooding protocols. Simulation and testbed results show that LACE: (1) achieves more accurate and lightweight link correlation measurements than the state-of-the-art work; and (2) greatly improves the performance of protocols exploiting link correlation. PMID:25686314

  11. An accurate link correlation estimator for improving wireless protocol performance.

    PubMed

    Zhao, Zhiwei; Xu, Xianghua; Dong, Wei; Bu, Jiajun

    2015-02-12

    Wireless link correlation has shown significant impact on the performance of various sensor network protocols. Many works have been devoted to exploiting link correlation for protocol improvements. However, the effectiveness of these designs heavily relies on the accuracy of link correlation measurement. In this paper, we investigate state-of-the-art link correlation measurement and analyze the limitations of existing works. We then propose a novel lightweight and accurate link correlation estimation (LACE) approach based on the reasoning of link correlation formation. LACE combines both long-term and short-term link behaviors for link correlation estimation. We implement LACE as a stand-alone interface in TinyOS and incorporate it into both routing and flooding protocols. Simulation and testbed results show that LACE: (1) achieves more accurate and lightweight link correlation measurements than the state-of-the-art work; and (2) greatly improves the performance of protocols exploiting link correlation.

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

    PubMed

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

    2016-08-01

    Prediction of symptomatic crises in chronic diseases allows to take decisions before the symptoms occur, such as the intake of drugs to avoid the symptoms or the activation of medical alarms. The prediction horizon is in this case an important parameter in order to fulfill the pharmacokinetics of medications, or the time response of medical services. This paper presents a study about the prediction limits of a chronic disease with symptomatic crises: the migraine. For that purpose, this work develops a methodology to build predictive migraine models and to improve these predictions beyond the limits of the initial models. The maximum prediction horizon is analyzed, and its dependency on the selected features is studied. A strategy for model selection is proposed to tackle the trade off between conservative but robust predictive models, with respect to less accurate predictions with higher horizons. The obtained results show a prediction horizon close to 40min, which is in the time range of the drug pharmacokinetics. Experiments have been performed in a realistic scenario where input data have been acquired in an ambulatory clinical study by the deployment of a non-intrusive Wireless Body Sensor Network. Our results provide an effective methodology for the selection of the future horizon in the development of prediction algorithms for diseases experiencing symptomatic crises. PMID:27260782

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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?

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. Prediction of pump cavitation performance

    NASA Technical Reports Server (NTRS)

    Moore, R. D.

    1974-01-01

    A method for predicting pump cavitation performance with various liquids, liquid temperatures, and rotative speeds is presented. Use of the method requires that two sets of test data be available for the pump of interest. Good agreement between predicted and experimental results of cavitation performance was obtained for several pumps operated in liquids which exhibit a wide range of properties. Two cavitation parameters which qualitatively evaluate pump cavitation performance are also presented.

  3. Program Predicts Nonlinear Inverter Performance

    NASA Technical Reports Server (NTRS)

    Al-Ayoubi, R. R.; Oepomo, T. S.

    1985-01-01

    Program developed for ac power distribution system on Shuttle orbiter predicts total load on inverters and node voltages at each of line replaceable units (LRU's). Mathematical model simulates inverter performance at each change of state in power distribution system.

  4. 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

  5. Predictive performance models and multiple task performance

    NASA Technical Reports Server (NTRS)

    Wickens, Christopher D.; Larish, Inge; Contorer, Aaron

    1989-01-01

    Five models that predict how performance of multiple tasks will interact in complex task scenarios are discussed. The models are shown in terms of the assumptions they make about human operator divided attention. The different assumptions about attention are then empirically validated in a multitask helicopter flight simulation. It is concluded from this simulation that the most important assumption relates to the coding of demand level of different component tasks.

  6. 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.

  7. Action perception predicts action performance

    PubMed Central

    Bailey, Heather R.; Kurby, Christopher A.; Giovannetti, Tania; Zacks, Jeffrey M.

    2013-01-01

    Everyday action impairments often are observed in demented older adults, and they are common potential barriers to functional independence. We evaluated whether the ability to segment and efficiently encode activities is related to the ability to execute activities. Further, we evaluated whether brain regions important for segmentation also were important for action performance. Cognitively healthy older adults and those with very mild or mild dementia of the Alzheimer's type watched and segmented movies of everyday activities and then completed the Naturalistic Action Test. Structural MRI was used to measure volume in the dorsolateral prefrontal cortex (DLPFC), medial temporal lobes (MTL), posterior cortex, and anterior cingulate cortex (ACC). Dementia status and the ability to segment everyday activities strongly predicted naturalistic action performance, and MTL volume largely accounted for this relationship. In addition, the current results supported the Omission-Commission Model: Different cognitive and neurological mechanisms predicted different types of action error. Segmentation, dementia severity, and MTL volume predicted everyday omission errors, DLPFC volume predicted commission errors, and ACC volume predicted action additions. These findings suggest that event segmentation may be critical for effective action production, and that the segmentation and production of activities may recruit the same event representation system. PMID:23851113

  8. Action perception predicts action performance.

    PubMed

    Bailey, Heather R; Kurby, Christopher A; Giovannetti, Tania; Zacks, Jeffrey M

    2013-09-01

    Everyday action impairments often are observed in demented older adults, and they are common potential barriers to functional independence. We evaluated whether the ability to segment and efficiently encode activities is related to the ability to execute activities. Further, we evaluated whether brain regions important for segmentation also were important for action performance. Cognitively healthy older adults and those with very mild or mild dementia of the Alzheimer's type watched and segmented movies of everyday activities and then completed the Naturalistic Action Test. Structural MRI was used to measure volume in the dorsolateral prefrontal cortex (DLPFC), medial temporal lobes (MTL), posterior cortex, and anterior cingulate cortex (ACC). Dementia status and the ability to segment everyday activities strongly predicted naturalistic action performance, and MTL volume largely accounted for this relationship. In addition, the current results supported the Omission-Commission Model: Different cognitive and neurological mechanisms predicted different types of action error. Segmentation, dementia severity, and MTL volume predicted everyday omission errors, DLPFC volume predicted commission errors, and ACC volume predicted action additions. These findings suggest that event segmentation may be critical for effective action production, and that the segmentation and production of activities may recruit the same event representation system.

  9. 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

  10. Towards an Accurate Performance Modeling of Parallel SparseFactorization

    SciTech Connect

    Grigori, Laura; Li, Xiaoye S.

    2006-05-26

    We present a performance model to analyze a parallel sparseLU factorization algorithm on modern cached-based, high-end parallelarchitectures. Our model characterizes the algorithmic behavior bytakingaccount the underlying processor speed, memory system performance, aswell as the interconnect speed. The model is validated using theSuperLU_DIST linear system solver, the sparse matrices from realapplications, and an IBM POWER3 parallel machine. Our modelingmethodology can be easily adapted to study performance of other types ofsparse factorizations, such as Cholesky or QR.

  11. 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.

  12. 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

  13. Prediction of student clinical performance.

    PubMed

    Hobfoll, S E; Benor, D E

    1981-07-01

    The predictive validity of 'traditional' tools utilized in the selection of medical students was evaluated in a 'non-traditional' selection paradigm, where a wide range of previous-academic ability was represented. The validity of the use of pre-academic grades and examination scores in the prediction of success in clinical performance was examined in a medical school which de-emphasizes these indicators and emphasizes personal characteristics assessed via interview ratings in student selection. Grades and examination scores were found to have no relation to clinical ratings which have an added interpersonal and community emphasis during the fourth-sixth years of medical school. A positive trend was found for interview ratings with clinical performance, but the skewed nature of interview scores was seen as limiting investigation of this variable. The meaning of these results vis-à-vis the continued use of academic and examination related selection criteria was discussed. PMID:7253988

  14. 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.

  15. Improving JWST Coronagraphic Performance with Accurate Image Registration

    NASA Astrophysics Data System (ADS)

    Van Gorkom, Kyle; Pueyo, Laurent; Lajoie, Charles-Philippe; JWST Coronagraphs Working Group

    2016-06-01

    The coronagraphs on the James Webb Space Telescope (JWST) will enable high-contrast observations of faint objects at small separations from bright hosts, such as circumstellar disks, exoplanets, and quasar disks. Despite attenuation by the coronagraphic mask, bright speckles in the host’s point spread function (PSF) remain, effectively washing out the signal from the faint companion. Suppression of these bright speckles is typically accomplished by repeating the observation with a star that lacks a faint companion, creating a reference PSF that can be subtracted from the science image to reveal any faint objects. Before this reference PSF can be subtracted, however, the science and reference images must be aligned precisely, typically to 1/20 of a pixel. Here, we present several such algorithms for performing image registration on JWST coronagraphic images. Using both simulated and pre-flight test data (taken in cryovacuum), we assess (1) the accuracy of each algorithm at recovering misaligned scenes and (2) the impact of image registration on achievable contrast. Proper image registration, combined with post-processing techniques such as KLIP or LOCI, will greatly improve the performance of the JWST coronagraphs.

  16. 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.

  17. Blinded by Beauty: Attractiveness Bias and Accurate Perceptions of Academic Performance

    PubMed Central

    Talamas, Sean N.; Mavor, Kenneth I.; Perrett, David I.

    2016-01-01

    Despite the old adage not to ‘judge a book by its cover’, facial cues often guide first impressions and these first impressions guide our decisions. Literature suggests there are valid facial cues that assist us in assessing someone’s health or intelligence, but such cues are overshadowed by an ‘attractiveness halo’ whereby desirable attributions are preferentially ascribed to attractive people. The impact of the attractiveness halo effect on perceptions of academic performance in the classroom is concerning as this has shown to influence students’ future performance. We investigated the limiting effects of the attractiveness halo on perceptions of actual academic performance in faces of 100 university students. Given the ambiguity and various perspectives on the definition of intelligence and the growing consensus on the importance of conscientiousness over intelligence in predicting actual academic performance, we also investigated whether perceived conscientiousness was a more accurate predictor of academic performance than perceived intelligence. Perceived conscientiousness was found to be a better predictor of actual academic performance when compared to perceived intelligence and perceived academic performance, and accuracy was improved when controlling for the influence of attractiveness on judgments. These findings emphasize the misleading effect of attractiveness on the accuracy of first impressions of competence, which can have serious consequences in areas such as education and hiring. The findings also have implications for future research investigating impression accuracy based on facial stimuli. PMID:26885976

  18. Blinded by Beauty: Attractiveness Bias and Accurate Perceptions of Academic Performance.

    PubMed

    Talamas, Sean N; Mavor, Kenneth I; Perrett, David I

    2016-01-01

    Despite the old adage not to 'judge a book by its cover', facial cues often guide first impressions and these first impressions guide our decisions. Literature suggests there are valid facial cues that assist us in assessing someone's health or intelligence, but such cues are overshadowed by an 'attractiveness halo' whereby desirable attributions are preferentially ascribed to attractive people. The impact of the attractiveness halo effect on perceptions of academic performance in the classroom is concerning as this has shown to influence students' future performance. We investigated the limiting effects of the attractiveness halo on perceptions of actual academic performance in faces of 100 university students. Given the ambiguity and various perspectives on the definition of intelligence and the growing consensus on the importance of conscientiousness over intelligence in predicting actual academic performance, we also investigated whether perceived conscientiousness was a more accurate predictor of academic performance than perceived intelligence. Perceived conscientiousness was found to be a better predictor of actual academic performance when compared to perceived intelligence and perceived academic performance, and accuracy was improved when controlling for the influence of attractiveness on judgments. These findings emphasize the misleading effect of attractiveness on the accuracy of first impressions of competence, which can have serious consequences in areas such as education and hiring. The findings also have implications for future research investigating impression accuracy based on facial stimuli.

  19. Blinded by Beauty: Attractiveness Bias and Accurate Perceptions of Academic Performance.

    PubMed

    Talamas, Sean N; Mavor, Kenneth I; Perrett, David I

    2016-01-01

    Despite the old adage not to 'judge a book by its cover', facial cues often guide first impressions and these first impressions guide our decisions. Literature suggests there are valid facial cues that assist us in assessing someone's health or intelligence, but such cues are overshadowed by an 'attractiveness halo' whereby desirable attributions are preferentially ascribed to attractive people. The impact of the attractiveness halo effect on perceptions of academic performance in the classroom is concerning as this has shown to influence students' future performance. We investigated the limiting effects of the attractiveness halo on perceptions of actual academic performance in faces of 100 university students. Given the ambiguity and various perspectives on the definition of intelligence and the growing consensus on the importance of conscientiousness over intelligence in predicting actual academic performance, we also investigated whether perceived conscientiousness was a more accurate predictor of academic performance than perceived intelligence. Perceived conscientiousness was found to be a better predictor of actual academic performance when compared to perceived intelligence and perceived academic performance, and accuracy was improved when controlling for the influence of attractiveness on judgments. These findings emphasize the misleading effect of attractiveness on the accuracy of first impressions of competence, which can have serious consequences in areas such as education and hiring. The findings also have implications for future research investigating impression accuracy based on facial stimuli. PMID:26885976

  20. 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

  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. 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

  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. PMID:27272707

  5. 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.

  6. 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

  7. 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.

  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. A nozzle internal performance prediction method

    NASA Technical Reports Server (NTRS)

    Carlson, John R.

    1992-01-01

    A prediction method was written and incorporated into a three-dimensional Navier-Stokes code (PAB3D) for the calculation of nozzle internal performance. The following quantities are calculated: (1) discharge coefficient; (2) normal, side, and axial thrust ratios; (3) rolling, pitching, and yawing moments; and (4) effective pitch and yaw vector angles. Four different case studies are presented to confirm the applicability of the methodology. Internal and, in most situations, external flow-field regions are required to be modeled. The computed nozzle discharge coefficient matches both the level and the trend of the experimental data within quoted experimental data accuracy (0.5 percent). Moment and force ratios are generally within 1 to 2 percent of the absolute level of experimental data, with the trends of data matched accurately.

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

    SciTech Connect

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

    2004-12-01

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

  11. 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. 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.

  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. 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

  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. PMID:25979264

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. Can Young Children Be More Accurate Predictors of Their Recall Performance?

    ERIC Educational Resources Information Center

    Lipko-Speed, Amanda R.

    2013-01-01

    Preschoolers persistently predict that they will perform better than they actually can perform on a picture recall task. The current investigation sought to explore a condition under which young children might be able to improve their predictive accuracy. Namely, children were asked to predict their recall twice for the same set of items.…

  4. 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

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

    PubMed Central

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

    2016-01-01

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

  6. 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

  7. 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.

  8. 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.

  9. 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

  10. Optimal speed estimation in natural image movies predicts human performance.

    PubMed

    Burge, Johannes; Geisler, Wilson S

    2015-01-01

    Accurate perception of motion depends critically on accurate estimation of retinal motion speed. Here we first analyse natural image movies to determine the optimal space-time receptive fields (RFs) for encoding local motion speed in a particular direction, given the constraints of the early visual system. Next, from the RF responses to natural stimuli, we determine the neural computations that are optimal for combining and decoding the responses into estimates of speed. The computations show how selective, invariant speed-tuned units might be constructed by the nervous system. Then, in a psychophysical experiment using matched stimuli, we show that human performance is nearly optimal. Indeed, a single efficiency parameter accurately predicts the detailed shapes of a large set of human psychometric functions. We conclude that many properties of speed-selective neurons and human speed discrimination performance are predicted by the optimal computations, and that natural stimulus variation affects optimal and human observers almost identically.

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. 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.

  16. 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)

  17. 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

  18. 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

  19. 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.

  20. The Real World Significance of Performance Prediction

    ERIC Educational Resources Information Center

    Pardos, Zachary A.; Wang, Qing Yang; Trivedi, Shubhendu

    2012-01-01

    In recent years, the educational data mining and user modeling communities have been aggressively introducing models for predicting student performance on external measures such as standardized tests as well as within-tutor performance. While these models have brought statistically reliable improvement to performance prediction, the real world…

  1. Influence of accurate and inaccurate 'split-time' feedback upon 10-mile time trial cycling performance.

    PubMed

    Wilson, Mathew G; Lane, Andy M; Beedie, Chris J; Farooq, Abdulaziz

    2012-01-01

    The objective of the study is to examine the impact of accurate and inaccurate 'split-time' feedback upon a 10-mile time trial (TT) performance and to quantify power output into a practically meaningful unit of variation. Seven well-trained cyclists completed four randomised bouts of a 10-mile TT on a SRM™ cycle ergometer. TTs were performed with (1) accurate performance feedback, (2) without performance feedback, (3) and (4) false negative and false positive 'split-time' feedback showing performance 5% slower or 5% faster than actual performance. There were no significant differences in completion time, average power output, heart rate or blood lactate between the four feedback conditions. There were significantly lower (p < 0.001) average [Formula: see text] (ml min(-1)) and [Formula: see text] (l min(-1)) scores in the false positive (3,485 ± 596; 119 ± 33) and accurate (3,471 ± 513; 117 ± 22) feedback conditions compared to the false negative (3,753 ± 410; 127 ± 27) and blind (3,772 ± 378; 124 ± 21) feedback conditions. Cyclists spent a greater amount of time in a '20 watt zone' 10 W either side of average power in the negative feedback condition (fastest) than the accurate feedback (slowest) condition (39.3 vs. 32.2%, p < 0.05). There were no significant differences in the 10-mile TT performance time between accurate and inaccurate feedback conditions, despite significantly lower average [Formula: see text] and [Formula: see text] scores in the false positive and accurate feedback conditions. Additionally, cycling with a small variation in power output (10 W either side of average power) produced the fastest TT. Further psycho-physiological research should examine the mechanism(s) why lower [Formula: see text] and [Formula: see text] scores are observed when cycling in a false positive or accurate feedback condition compared to a false negative or blind feedback condition.

  2. 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.

  3. Cerebral cortical activity associated with non-experts' most accurate motor performance.

    PubMed

    Dyke, Ford; Godwin, Maurice M; Goel, Paras; Rehm, Jared; Rietschel, Jeremy C; Hunt, Carly A; Miller, Matthew W

    2014-10-01

    This study's specific aim was to determine if non-experts' most accurate motor performance is associated with verbal-analytic- and working memory-related cerebral cortical activity during motor preparation. To assess this, EEG was recorded from non-expert golfers executing putts; EEG spectral power and coherence were calculated for the epoch preceding putt execution; and spectral power and coherence for the five most accurate putts were contrasted with that for the five least accurate. Results revealed marked power in the theta frequency bandwidth at all cerebral cortical regions for the most accurate putts relative to the least accurate, and considerable power in the low-beta frequency bandwidth at the left temporal region for the most accurate compared to the least. As theta power is associated with working memory and low-beta power at the left temporal region with verbal analysis, results suggest non-experts' most accurate motor performance is associated with verbal-analytic- and working memory-related cerebral cortical activity during motor preparation. PMID:25058623

  4. 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

  5. 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

  6. 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.

  7. 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

  8. Trends in reservoir performance prediction

    SciTech Connect

    Mackenzie, A.S.

    1994-12-31

    Stronger links between geoscience and petroleum engineering are being fostered by new tools and organizations. These linkages are improving the effectiveness of business decisions concerning reservoir performance, and are generating new challenges for the next generation of tools.

  9. 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

  10. Performance Prediction of Students in Teacher Education.

    ERIC Educational Resources Information Center

    Hoover, Todd

    1979-01-01

    Scores on the Sixteen Personality Factor Questionnaire and grade point average were investigated as predictors of performance in an educational media course. Neither were recommended as tools for predicting course performance. (GDC)

  11. 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

  12. 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.

  13. 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

  14. JCZS: An Intermolecular Potential Database for Performing Accurate Detonation and Expansion Calculations

    SciTech Connect

    Baer, M.R.; Hobbs, M.L.; McGee, B.C.

    1998-11-03

    Exponential-13,6 (EXP-13,6) potential pammeters for 750 gases composed of 48 elements were determined and assembled in a database, referred to as the JCZS database, for use with the Jacobs Cowperthwaite Zwisler equation of state (JCZ3-EOS)~l) The EXP- 13,6 force constants were obtained by using literature values of Lennard-Jones (LJ) potential functions, by using corresponding states (CS) theory, by matching pure liquid shock Hugoniot data, and by using molecular volume to determine the approach radii with the well depth estimated from high-pressure isen- tropes. The JCZS database was used to accurately predict detonation velocity, pressure, and temperature for 50 dif- 3 Accurate predictions were also ferent explosives with initial densities ranging from 0.25 glcm3 to 1.97 g/cm . obtained for pure liquid shock Hugoniots, static properties of nitrogen, and gas detonations at high initial pressures.

  15. 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.

  16. 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).

  17. 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

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. Challenges of Student Selection: Predicting Academic Performance

    ERIC Educational Resources Information Center

    van der Merwe, D.; de Beer, M.

    2006-01-01

    Finding accurate predictors of tertiary academic performance, specifically for disadvantaged students, is essential because of budget constraints and the need of the labour market to address employment equity. Increased retention, throughput and decreased dropout rates are vital. When making admission decisions, the under preparedness of students…

  3. 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

  4. COMPASS: A Framework for Automated Performance Modeling and Prediction

    SciTech Connect

    Lee, Seyong; Meredith, Jeremy S; Vetter, Jeffrey S

    2015-01-01

    Flexible, accurate performance predictions offer numerous benefits such as gaining insight into and optimizing applications and architectures. However, the development and evaluation of such performance predictions has been a major research challenge, due to the architectural complexities. To address this challenge, we have designed and implemented a prototype system, named COMPASS, for automated performance model generation and prediction. COMPASS generates a structured performance model from the target application's source code using automated static analysis, and then, it evaluates this model using various performance prediction techniques. As we demonstrate on several applications, the results of these predictions can be used for a variety of purposes, such as design space exploration, identifying performance tradeoffs for applications, and understanding sensitivities of important parameters. COMPASS can generate these predictions across several types of applications from traditional, sequential CPU applications to GPU-based, heterogeneous, parallel applications. Our empirical evaluation demonstrates a maximum overhead of 4%, flexibility to generate models for 9 applications, speed, ease of creation, and very low relative errors across a diverse set of architectures.

  5. 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.

  6. Predicting Turkish Ninth Grade Students' Algebra Performance

    ERIC Educational Resources Information Center

    Erbas, Ayhan Kursat

    2005-01-01

    The prediction of students' achievement in algebra in eighth and ninth grades has become a research interest for practical issues of placement. A group of simple, easily accessible variables was used to predict student performance in algebra after completion of eighth grade. The three variables of school type, grade level, and previous year…

  7. 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.

  8. 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.

  9. 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

  10. 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

  11. 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.

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

    NASA Technical Reports Server (NTRS)

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

    2001-01-01

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

  14. 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.

  15. A statistical model for predicting muscle performance

    NASA Astrophysics Data System (ADS)

    Byerly, Diane Leslie De Caix

    The objective of these studies was to develop a capability for predicting muscle performance and fatigue to be utilized for both space- and ground-based applications. To develop this predictive model, healthy test subjects performed a defined, repetitive dynamic exercise to failure using a Lordex spinal machine. Throughout the exercise, surface electromyography (SEMG) data were collected from the erector spinae using a Mega Electronics ME3000 muscle tester and surface electrodes placed on both sides of the back muscle. These data were analyzed using a 5th order Autoregressive (AR) model and statistical regression analysis. It was determined that an AR derived parameter, the mean average magnitude of AR poles, significantly correlated with the maximum number of repetitions (designated Rmax) that a test subject was able to perform. Using the mean average magnitude of AR poles, a test subject's performance to failure could be predicted as early as the sixth repetition of the exercise. This predictive model has the potential to provide a basis for improving post-space flight recovery, monitoring muscle atrophy in astronauts and assessing the effectiveness of countermeasures, monitoring astronaut performance and fatigue during Extravehicular Activity (EVA) operations, providing pre-flight assessment of the ability of an EVA crewmember to perform a given task, improving the design of training protocols and simulations for strenuous International Space Station assembly EVA, and enabling EVA work task sequences to be planned enhancing astronaut performance and safety. Potential ground-based, medical applications of the predictive model include monitoring muscle deterioration and performance resulting from illness, establishing safety guidelines in the industry for repetitive tasks, monitoring the stages of rehabilitation for muscle-related injuries sustained in sports and accidents, and enhancing athletic performance through improved training protocols while reducing

  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. 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.

  18. Medical Students' Predictions of Public Opinion Regarding Role Performance of Doctors

    ERIC Educational Resources Information Center

    Congalton, Athol A.

    1971-01-01

    The results of a study of the predictions made by fourth year medical students concerning the public evaluation of doctors' role performance shows that doctors in training do not have an accurate picture of public opinion. (Author)

  19. 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

  20. Effects of environmental uncertainties on sonar detection performance prediction.

    PubMed

    Sha, Liewei; Nolte, Loren W

    2005-04-01

    The development of effective passive sonar systems depends upon the ability to accurately predict the performance of sonar detection algorithms in realistic ocean environments. Such environments are typically characterized by a high degree of uncertainty, thus limiting the usefulness of performance prediction approaches that assume a deterministic environment. Here we derive closed-form receiver operating characteristic (ROC) expressions for an optimal Bayesian detector and for several typical suboptimal detectors, based on a statistical model of environmental uncertainty. Various scenarios extended from an NRL benchmark shallow-water model were used to check the analytical ROC expressions and to illustrate the effect of environmental uncertainty on detection performance. The results showed that (1) optimal detection performance in an uncertain environment in diffuse noise depends primarily on the signal-to-noise ratio at the receivers and the rank of the signal matrix, where the rank is an effective representation of the scale of environmental uncertainty; (2) the ROC expression for the optimal Bayesian detector provides a more realistic performance upper bound than that obtained from conventional sonar equations that do not incorporate environmental uncertainty; and (3) detection performance predictions can be performed much faster than with commonly used numerical methods such as Monte Carlo performance evaluations.

  1. Proactive supply chain performance management with predictive analytics.

    PubMed

    Stefanovic, Nenad

    2014-01-01

    Today's business climate requires supply chains to be proactive rather than reactive, which demands a new approach that incorporates data mining predictive analytics. This paper introduces a predictive supply chain performance management model which combines process modelling, performance measurement, data mining models, and web portal technologies into a unique model. It presents the supply chain modelling approach based on the specialized metamodel which allows modelling of any supply chain configuration and at different level of details. The paper also presents the supply chain semantic business intelligence (BI) model which encapsulates data sources and business rules and includes the data warehouse model with specific supply chain dimensions, measures, and KPIs (key performance indicators). Next, the paper describes two generic approaches for designing the KPI predictive data mining models based on the BI semantic model. KPI predictive models were trained and tested with a real-world data set. Finally, a specialized analytical web portal which offers collaborative performance monitoring and decision making is presented. The results show that these models give very accurate KPI projections and provide valuable insights into newly emerging trends, opportunities, and problems. This should lead to more intelligent, predictive, and responsive supply chains capable of adapting to future business environment.

  2. Proactive Supply Chain Performance Management with Predictive Analytics

    PubMed Central

    Stefanovic, Nenad

    2014-01-01

    Today's business climate requires supply chains to be proactive rather than reactive, which demands a new approach that incorporates data mining predictive analytics. This paper introduces a predictive supply chain performance management model which combines process modelling, performance measurement, data mining models, and web portal technologies into a unique model. It presents the supply chain modelling approach based on the specialized metamodel which allows modelling of any supply chain configuration and at different level of details. The paper also presents the supply chain semantic business intelligence (BI) model which encapsulates data sources and business rules and includes the data warehouse model with specific supply chain dimensions, measures, and KPIs (key performance indicators). Next, the paper describes two generic approaches for designing the KPI predictive data mining models based on the BI semantic model. KPI predictive models were trained and tested with a real-world data set. Finally, a specialized analytical web portal which offers collaborative performance monitoring and decision making is presented. The results show that these models give very accurate KPI projections and provide valuable insights into newly emerging trends, opportunities, and problems. This should lead to more intelligent, predictive, and responsive supply chains capable of adapting to future business environment. PMID:25386605

  3. Proactive supply chain performance management with predictive analytics.

    PubMed

    Stefanovic, Nenad

    2014-01-01

    Today's business climate requires supply chains to be proactive rather than reactive, which demands a new approach that incorporates data mining predictive analytics. This paper introduces a predictive supply chain performance management model which combines process modelling, performance measurement, data mining models, and web portal technologies into a unique model. It presents the supply chain modelling approach based on the specialized metamodel which allows modelling of any supply chain configuration and at different level of details. The paper also presents the supply chain semantic business intelligence (BI) model which encapsulates data sources and business rules and includes the data warehouse model with specific supply chain dimensions, measures, and KPIs (key performance indicators). Next, the paper describes two generic approaches for designing the KPI predictive data mining models based on the BI semantic model. KPI predictive models were trained and tested with a real-world data set. Finally, a specialized analytical web portal which offers collaborative performance monitoring and decision making is presented. The results show that these models give very accurate KPI projections and provide valuable insights into newly emerging trends, opportunities, and problems. This should lead to more intelligent, predictive, and responsive supply chains capable of adapting to future business environment. PMID:25386605

  4. 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.

  5. 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.

  6. 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

  7. Predicting Language Performance in Hearing Impaired Children.

    ERIC Educational Resources Information Center

    Monsees, Edna K.

    The 2-year study evaluated the language performance of 69 hearing impaired, preschool children born following the rubella epidemic of the early 1960's in order to develop an instrument for objectively assessing language achievement and a predictive index of language achievement. Two language rating scales were developed which were tied to the…

  8. Why Do Spatial Abilities Predict Mathematical Performance?

    ERIC Educational Resources Information Center

    Tosto, Maria Grazia; Hanscombe, Ken B.; Haworth, Claire M. A.; Davis, Oliver S. P.; Petrill, Stephen A.; Dale, Philip S.; Malykh, Sergey; Plomin, Robert; Kovas, Yulia

    2014-01-01

    Spatial ability predicts performance in mathematics and eventual expertise in science, technology and engineering. Spatial skills have also been shown to rely on neuronal networks partially shared with mathematics. Understanding the nature of this association can inform educational practices and intervention for mathematical underperformance.…

  9. What predicts performance during clinical psychology training?

    PubMed Central

    Scior, Katrina; Bradley, Caroline E; Potts, Henry W W; Woolf, Katherine; de C Williams, Amanda C

    2014-01-01

    Objectives While the question of who is likely to be selected for clinical psychology training has been studied, evidence on performance during training is scant. This study explored data from seven consecutive intakes of the UK's largest clinical psychology training course, aiming to identify what factors predict better or poorer outcomes. Design Longitudinal cross-sectional study using prospective and retrospective data. Method Characteristics at application were analysed in relation to a range of in-course assessments for 274 trainee clinical psychologists who had completed or were in the final stage of their training. Results Trainees were diverse in age, pre-training experience, and academic performance at A-level (advanced level certificate required for university admission), but not in gender or ethnicity. Failure rates across the three performance domains (academic, clinical, research) were very low, suggesting that selection was successful in screening out less suitable candidates. Key predictors of good performance on the course were better A-levels and better degree class. Non-white students performed less well on two outcomes. Type and extent of pre-training clinical experience on outcomes had varied effects on outcome. Research supervisor ratings emerged as global indicators and predicted nearly all outcomes, but may have been biased as they were retrospective. Referee ratings predicted only one of the seven outcomes examined, and interview ratings predicted none of the outcomes. Conclusions Predicting who will do well or poorly in clinical psychology training is complex. Interview and referee ratings may well be successful in screening out unsuitable candidates, but appear to be a poor guide to performance on the course. Practitioner points While referee and selection interview ratings did not predict performance during training, they may be useful in screening out unsuitable candidates at the application stage High school final academic performance

  10. Accurate Point-of-Care Detection of Ruptured Fetal Membranes: Improved Diagnostic Performance Characteristics with a Monoclonal/Polyclonal Immunoassay

    PubMed Central

    Rogers, Linda C.; Scott, Laurie; Block, Jon E.

    2016-01-01

    OBJECTIVE Accurate and timely diagnosis of rupture of membranes (ROM) is imperative to allow for gestational age-specific interventions. This study compared the diagnostic performance characteristics between two methods used for the detection of ROM as measured in the same patient. METHODS Vaginal secretions were evaluated using the conventional fern test as well as a point-of-care monoclonal/polyclonal immunoassay test (ROM Plus®) in 75 pregnant patients who presented to labor and delivery with complaints of leaking amniotic fluid. Both tests were compared to analytical confirmation of ROM using three external laboratory tests. Diagnostic performance characteristics were calculated including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy. RESULTS Diagnostic performance characteristics uniformly favored ROM detection using the immunoassay test compared to the fern test: sensitivity (100% vs. 77.8%), specificity (94.8% vs. 79.3%), PPV (75% vs. 36.8%), NPV (100% vs. 95.8%), and accuracy (95.5% vs. 79.1%). CONCLUSIONS The point-of-care immunoassay test provides improved diagnostic accuracy for the detection of ROM compared to fern testing. It has the potential of improving patient management decisions, thereby minimizing serious complications and perinatal morbidity. PMID:27199579

  11. 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?

  12. 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

  13. 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

  14. 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.

  15. Accurate simulation of MPPT methods performance when applied to commercial photovoltaic panels.

    PubMed

    Cubas, Javier; Pindado, Santiago; Sanz-Andrés, Ángel

    2015-01-01

    A new, simple, and quick-calculation methodology to obtain a solar panel model, based on the manufacturers' datasheet, to perform MPPT simulations, is described. The method takes into account variations on the ambient conditions (sun irradiation and solar cells temperature) and allows fast MPPT methods comparison or their performance prediction when applied to a particular solar panel. The feasibility of the described methodology is checked with four different MPPT methods applied to a commercial solar panel, within a day, and under realistic ambient conditions.

  16. Accurate simulation of MPPT methods performance when applied to commercial photovoltaic panels.

    PubMed

    Cubas, Javier; Pindado, Santiago; Sanz-Andrés, Ángel

    2015-01-01

    A new, simple, and quick-calculation methodology to obtain a solar panel model, based on the manufacturers' datasheet, to perform MPPT simulations, is described. The method takes into account variations on the ambient conditions (sun irradiation and solar cells temperature) and allows fast MPPT methods comparison or their performance prediction when applied to a particular solar panel. The feasibility of the described methodology is checked with four different MPPT methods applied to a commercial solar panel, within a day, and under realistic ambient conditions. PMID:25874262

  17. Accurate Simulation of MPPT Methods Performance When Applied to Commercial Photovoltaic Panels

    PubMed Central

    2015-01-01

    A new, simple, and quick-calculation methodology to obtain a solar panel model, based on the manufacturers' datasheet, to perform MPPT simulations, is described. The method takes into account variations on the ambient conditions (sun irradiation and solar cells temperature) and allows fast MPPT methods comparison or their performance prediction when applied to a particular solar panel. The feasibility of the described methodology is checked with four different MPPT methods applied to a commercial solar panel, within a day, and under realistic ambient conditions. PMID:25874262

  18. 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

  19. Computer Program Predicts Turbine-Stage Performance

    NASA Technical Reports Server (NTRS)

    Boyle, Robert J.; Haas, Jeffrey E.; Katsanis, Theodore

    1988-01-01

    MTSBL updated version of flow-analysis programs MERIDL and TSONIC coupled to boundary-layer program BLAYER. Method uses quasi-three-dimensional, inviscid, stream-function flow analysis iteratively coupled to calculated losses so changes in losses result in changes in flow distribution. Manner effects both configuration on flow distribution and flow distribution on losses taken into account in prediction of performance of stage. Written in FORTRAN IV.

  20. 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

  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. 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

  4. 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.

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

    SciTech Connect

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

    2013-11-01

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

  6. 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

  7. 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.

  8. 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.

  9. 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

  10. 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

  11. 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.

  12. DKIST Polarization Modeling and Performance Predictions

    NASA Astrophysics Data System (ADS)

    Harrington, David

    2016-05-01

    Calibrating the Mueller matrices of large aperture telescopes and associated coude instrumentation requires astronomical sources and several modeling assumptions to predict the behavior of the system polarization with field of view, altitude, azimuth and wavelength. The Daniel K Inouye Solar Telescope (DKIST) polarimetric instrumentation requires very high accuracy calibration of a complex coude path with an off-axis f/2 primary mirror, time dependent optical configurations and substantial field of view. Polarization predictions across a diversity of optical configurations, tracking scenarios, slit geometries and vendor coating formulations are critical to both construction and contined operations efforts. Recent daytime sky based polarization calibrations of the 4m AEOS telescope and HiVIS spectropolarimeter on Haleakala have provided system Mueller matrices over full telescope articulation for a 15-reflection coude system. AEOS and HiVIS are a DKIST analog with a many-fold coude optical feed and similar mirror coatings creating 100% polarization cross-talk with altitude, azimuth and wavelength. Polarization modeling predictions using Zemax have successfully matched the altitude-azimuth-wavelength dependence on HiVIS with the few percent amplitude limitations of several instrument artifacts. Polarization predictions for coude beam paths depend greatly on modeling the angle-of-incidence dependences in powered optics and the mirror coating formulations. A 6 month HiVIS daytime sky calibration plan has been analyzed for accuracy under a wide range of sky conditions and data analysis algorithms. Predictions of polarimetric performance for the DKIST first-light instrumentation suite have been created under a range of configurations. These new modeling tools and polarization predictions have substantial impact for the design, fabrication and calibration process in the presence of manufacturing issues, science use-case requirements and ultimate system calibration

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. Prediction of 200-m sprint kayaking performance.

    PubMed

    van Someren, Ken A; Palmer, Garry S

    2003-08-01

    The aim of this study was to determine the anthropometric and physiological profile of 200-m sprint kayakers and to examine relationships with 200-m race performance. Twenty-six male kayakers who were categorised in two ability groups, international (Int) and national (Nat) level, underwent a battery of anthropometric and physiological tests and a 200-m race. Race time was significantly lower in Int than Nat (39.9 +/- 0.8 s and 42.6 +/- 0.9 s, respectively). Int demonstrated significantly greater measures of mesomorphy, biepycondylar humeral breadth, circumferences of the upper arm, forearm and chest, peak power and total work in a modified Wingate test, total work in a 2-min ergometry test, peak isokinetic power, and peak isometric force. Significant relationships were found between 200-m time and a number of anthropometric variables and anaerobic and dynamometric parameters. Stepwise multiple regression revealed that total work in the modified Wingate alone predicted 200-m race time (R2 = 0.53, SEE = 1.11 s) for all 26 subjects, while biepycondylar humeral breadth alone predicted race time (R2 = 0.54, SEE = 0.52 s) in Int. These results demonstrate that superior upper body dimensions and anaerobic capacities distinguish international-level kayakers from national-level athletes and may be used to predict 200-m performance.

  18. 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

  19. 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

  20. 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

  1. 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.

  2. 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

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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

  9. Hypersonic Interceptor Performance Evaluation Center aero-optics performance predictions

    NASA Astrophysics Data System (ADS)

    Sutton, George W.; Pond, John E.; Snow, Ronald; Hwang, Yanfang

    1993-06-01

    This paper describes the Hypersonic Interceptor Performance Evaluation Center's (HIPEC) aerooptics performance predictions capability. It includes code results for three dimensional shapes and comparisons to initial experiments. HIPEC consists of a collection of aerothermal, aerodynamic computational codes which are capable of covering the entire flight regime from subsonic to hypersonic flow and include chemical reactions and turbulence. Heat transfer to the various surfaces is calculated as an input to cooling and ablation processes. HIPEC also has aero-optics codes to determine the effect of the mean flowfield and turbulence on the tracking and imaging capability of on-board optical sensors. The paper concentrates on the latter aspects.

  10. An improved method for accurate and rapid measurement of flight performance in Drosophila.

    PubMed

    Babcock, Daniel T; Ganetzky, Barry

    2014-01-01

    Drosophila has proven to be a useful model system for analysis of behavior, including flight. The initial flight tester involved dropping flies into an oil-coated graduated cylinder; landing height provided a measure of flight performance by assessing how far flies will fall before producing enough thrust to make contact with the wall of the cylinder. Here we describe an updated version of the flight tester with four major improvements. First, we added a "drop tube" to ensure that all flies enter the flight cylinder at a similar velocity between trials, eliminating variability between users. Second, we replaced the oil coating with removable plastic sheets coated in Tangle-Trap, an adhesive designed to capture live insects. Third, we use a longer cylinder to enable more accurate discrimination of flight ability. Fourth we use a digital camera and imaging software to automate the scoring of flight performance. These improvements allow for the rapid, quantitative assessment of flight behavior, useful for large datasets and large-scale genetic screens. PMID:24561810

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. 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.

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

    PubMed Central

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

    2015-01-01

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

  17. Comparing theories' performance in predicting violence.

    PubMed

    Haas, Henriette; Cusson, Maurice

    2015-01-01

    The stakes of choosing the best theory as a basis for violence prevention and offender rehabilitation are high. However, no single theory of violence has ever been universally accepted by a majority of established researchers. Psychiatry, psychology and sociology are each subdivided into different schools relying upon different premises. All theories can produce empirical evidence for their validity, some of them stating the opposite of each other. Calculating different models with multivariate logistic regression on a dataset of N = 21,312 observations and ninety-two influences allowed a direct comparison of the performance of operationalizations of some of the most important schools. The psychopathology model ranked as the best model in terms of predicting violence right after the comprehensive interdisciplinary model. Next came the rational choice and lifestyle model and third the differential association and learning theory model. Other models namely the control theory model, the childhood-trauma model and the social conflict and reaction model turned out to have low sensitivities for predicting violence. Nevertheless, all models produced acceptable results in predictions of a non-violent outcome.

  18. Comparing theories' performance in predicting violence.

    PubMed

    Haas, Henriette; Cusson, Maurice

    2015-01-01

    The stakes of choosing the best theory as a basis for violence prevention and offender rehabilitation are high. However, no single theory of violence has ever been universally accepted by a majority of established researchers. Psychiatry, psychology and sociology are each subdivided into different schools relying upon different premises. All theories can produce empirical evidence for their validity, some of them stating the opposite of each other. Calculating different models with multivariate logistic regression on a dataset of N = 21,312 observations and ninety-two influences allowed a direct comparison of the performance of operationalizations of some of the most important schools. The psychopathology model ranked as the best model in terms of predicting violence right after the comprehensive interdisciplinary model. Next came the rational choice and lifestyle model and third the differential association and learning theory model. Other models namely the control theory model, the childhood-trauma model and the social conflict and reaction model turned out to have low sensitivities for predicting violence. Nevertheless, all models produced acceptable results in predictions of a non-violent outcome. PMID:25637261

  19. Texture metric that predicts target detection performance

    NASA Astrophysics Data System (ADS)

    Culpepper, Joanne B.

    2015-12-01

    Two texture metrics based on gray level co-occurrence error (GLCE) are used to predict probability of detection and mean search time. The two texture metrics are local clutter metrics and are based on the statistics of GLCE probability distributions. The degree of correlation between various clutter metrics and the target detection performance of the nine military vehicles in complex natural scenes found in the Search_2 dataset are presented. Comparison is also made between four other common clutter metrics found in the literature: root sum of squares, Doyle, statistical variance, and target structure similarity. The experimental results show that the GLCE energy metric is a better predictor of target detection performance when searching for targets in natural scenes than the other clutter metrics studied.

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

    SciTech Connect

    Margot Gerritsen

    2008-10-31

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

  1. Being aware of own performance: how accurately do children with autism spectrum disorder judge own memory performance?

    PubMed

    Elmose, Mette; Happé, Francesca

    2014-12-01

    Self-awareness was investigated by assessing accuracy of judging own memory performance in a group of children with autism spectrum disorder (ASD) compared with a group of typically developing (TD) children. Effects of stimulus type (social vs. nonsocial), and availability of feedback information as the task progressed, were examined. Results overall showed comparable levels and patterns of accuracy in the ASD and TD groups. A trend level effect (p = 061, d = 0.60) was found, with ASD participants being more accurate in judging own memory for nonsocial than social stimuli and the opposite pattern for TD participants. These findings suggest that awareness of own memory can be good in children with ASD. It is discussed how this finding may be interpreted, and it is suggested that further investigation into the relation between content, frequency, and quality of self-awareness, and the context of self-awareness, is needed.

  2. 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.

  3. Nanoindentation cannot accurately predict the tensile strength of graphene or other 2D materials.

    PubMed

    Han, Jihoon; Pugno, Nicola M; Ryu, Seunghwa

    2015-10-14

    Due to the difficulty of performing uniaxial tensile testing, the strengths of graphene and its grain boundaries have been measured in experiments by nanoindentation testing. From a series of molecular dynamics simulations, we find that the strength measured in uniaxial simulation and the strength estimated from the nanoindentation fracture force can differ significantly. Fracture in tensile loading occurs simultaneously with the onset of crack nucleation near 5-7 defects, while the graphene sheets often sustain the indentation loads after the crack initiation because the sharply concentrated stress near the tip does not give rise to enough driving force for further crack propagation. Due to the concentrated stress, strength estimation is sensitive to the indenter tip position along the grain boundaries. Also, it approaches the strength of pristine graphene if the tip is located slightly away from the grain boundary line. Our findings reveal the limitations of nanoindentation testing in quantifying the strength of graphene, and show that the loading-mode-specific failure mechanism must be taken into account in designing reliable devices from graphene and other technologically important 2D materials.

  4. 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.

  5. 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.

  6. Real-time Tsunami Inundation Prediction Using High Performance Computers

    NASA Astrophysics Data System (ADS)

    Oishi, Y.; Imamura, F.; Sugawara, D.

    2014-12-01

    earthquake occurs took about 2 minutes, which would be sufficient for a practical tsunami inundation predictions. In the presentation, the computational performance of our faster-than-real-time tsunami inundation model will be shown, and preferable tsunami wave source analysis for an accurate inundation prediction will also be discussed.

  7. TankSIM: A Cryogenic Tank Performance Prediction Program

    NASA Technical Reports Server (NTRS)

    Bolshinskiy, L. G.; Hedayat, A.; Hastings, L. J.; Moder, J. P.; Schnell, A. R.; Sutherlin, S. G.

    2015-01-01

    Accurate prediction of the thermodynamic state of the cryogenic propellants in launch vehicle tanks is necessary for mission planning and successful execution. Cryogenic propellant storage and transfer in space environments requires that tank pressure be controlled. The pressure rise rate is determined by the complex interaction of external heat leak, fluid temperature stratification, and interfacial heat and mass transfer. If the required storage duration of a space mission is longer than the period in which the tank pressure reaches its allowable maximum, an appropriate pressure control method must be applied. Therefore, predictions of the pressurization rate and performance of pressure control techniques in cryogenic tanks are required for development of cryogenic fluid long-duration storage technology and planning of future space exploration missions. This paper describes an analytical tool, Tank System Integrated Model (TankSIM), which can be used for modeling pressure control and predicting the behavior of cryogenic propellant for long-term storage for future space missions. It is written in the FORTRAN 90 language and can be compiled with any Visual FORTRAN compiler. A thermodynamic vent system (TVS) is used to achieve tank pressure control. Utilizing TankSIM, the following processes can be modeled: tank self-pressurization, boiloff, ullage venting, and mixing. Details of the TankSIM program and comparisons of its predictions with test data for liquid hydrogen and liquid methane will be presented in the final paper.

  8. 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.

  9. Performance and wake predictions of HAWTs in wind farms

    SciTech Connect

    Leclerc, C.; Masson, C.; Paraschivoiu, I.

    1997-12-31

    The present contribution proposes and describes a promising way towards performance prediction of an arbitrary array of turbines. It is based on the solution of the time-averaged, steady-state, incompressible Navier-Stokes equations with an appropriate turbulence closure model. The turbines are represented by distributions of momentum sources in the Navier-Stokes equations. In this paper, the applicability and viability of the proposed methodology is demonstrated using an axisymmetric implementation. The k-{epsilon} model has been chosen for the closure of the time-averaged, turbulent flow equations and the properties of the incident flow correspond to those of a neutral atmospheric boundary layer. The proposed mathematical model is solved using a Control-Volume Finite Element Method (CVFEM). Detailed results have been obtained using the proposed method for an isolated wind turbine and for two turbines one behind another. In the case of an isolated turbine, accurate wake velocity deficit predictions are obtained and an increase in power due to atmospheric turbulence is found in agreement with measurements. In the case of two turbines, the proposed methodology provides an appropriate modelling of the wind-turbine wake and a realistic prediction of the performance degradation of the downstream turbine.

  10. Machine characterization and benchmark performance prediction

    NASA Technical Reports Server (NTRS)

    Saavedra-Barrera, Rafael H.

    1988-01-01

    From runs of standard benchmarks or benchmark suites, it is not possible to characterize the machine nor to predict the run time of other benchmarks which have not been run. A new approach to benchmarking and machine characterization is reported. The creation and use of a machine analyzer is described, which measures the performance of a given machine on FORTRAN source language constructs. The machine analyzer yields a set of parameters which characterize the machine and spotlight its strong and weak points. Also described is a program analyzer, which analyzes FORTRAN programs and determines the frequency of execution of each of the same set of source language operations. It is then shown that by combining a machine characterization and a program characterization, we are able to predict with good accuracy the run time of a given benchmark on a given machine. Characterizations are provided for the Cray-X-MP/48, Cyber 205, IBM 3090/200, Amdahl 5840, Convex C-1, VAX 8600, VAX 11/785, VAX 11/780, SUN 3/50, and IBM RT-PC/125, and for the following benchmark programs or suites: Los Alamos (BMK8A1), Baskett, Linpack, Livermore Loops, Madelbrot Set, NAS Kernels, Shell Sort, Smith, Whetstone and Sieve of Erathostenes.

  11. 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.

  12. 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

  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

    2016-01-01

    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

  14. Visual Performance Prediction Using Schematic Eye Models

    NASA Astrophysics Data System (ADS)

    Schwiegerling, James Theodore

    The goal of visual modeling is to predict the visual performance or a change in performance of an individual from a model of the human visual system. In designing a model of the human visual system, two distinct functions are considered. The first is the production of an image incident on the retina by the optical system of the eye, and the second is the conversion of this image into a perceived image by the retina and brain. The eye optics are evaluated using raytracing techniques familiar to the optical engineer. The effect of the retinal and brain function are combined with the raytracing results by analyzing the modulation of the retinal image. Each of these processes is important far evaluating the performance of the entire visual system. Techniques for converting the abstract system performance measures used by optical engineers into clinically -applicable measures such as visual acuity and contrast sensitivity are developed in this dissertation. Furthermore, a methodology for applying videokeratoscopic height data to the visual model is outlined. These tools are useful in modeling the visual effects of corrective lenses, ocular maladies and refractive surgeries. The modeling techniques are applied to examples of soft contact lenses, keratoconus, radial keratotomy, photorefractive keratectomy and automated lamellar keratoplasty. The modeling tools developed in this dissertation are meant to be general and modular. As improvements to the measurements of the properties and functionality of the various visual components are made, the new information can be incorporated into the visual system model. Furthermore, the examples discussed here represent only a small subset of the applications of the visual model. Additional ocular maladies and emerging refractive surgeries can be modeled as well.

  15. 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

  16. 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

  17. Collective hormonal profiles predict group performance.

    PubMed

    Akinola, Modupe; Page-Gould, Elizabeth; Mehta, Pranjal H; Lu, Jackson G

    2016-08-30

    Prior research has shown that an individual's hormonal profile can influence the individual's social standing within a group. We introduce a different construct-a collective hormonal profile-which describes a group's hormonal make-up. We test whether a group's collective hormonal profile is related to its performance. Analysis of 370 individuals randomly assigned to work in 74 groups of three to six individuals revealed that group-level concentrations of testosterone and cortisol interact to predict a group's standing across groups. Groups with a collective hormonal profile characterized by high testosterone and low cortisol exhibited the highest performance. These collective hormonal level results remained reliable when controlling for personality traits and group-level variability in hormones. These findings support the hypothesis that groups with a biological propensity toward status pursuit (high testosterone) coupled with reduced stress-axis activity (low cortisol) engage in profit-maximizing decision-making. The current work extends the dual-hormone hypothesis to the collective level and provides a neurobiological perspective on the factors that determine who rises to the top across, not just within, social hierarchies. PMID:27528679

  18. Performance prediction of the LSST secondary mirror

    NASA Astrophysics Data System (ADS)

    Cho, Myung K.; Liang, Ming; Neill, Douglas R.

    2009-08-01

    The Large Synoptic Survey Telescope (LSST) is an 8.4 meter telescope with a field of view of 10 square degrees. This telescope will be capable of mapping the entire visible sky every few nights via sequential 15-second exposures, opening new windows on the universe from dark energy to time variable objects. The LSST optics calls for an annular 3.5 m diameter Secondary Mirror (M2), which is a large meniscus convex asphere (ellipse). The M2 converts the beam reflected from the f/1.2 primary mirror into a beam for the f/0.83 Tertiary Mirror (M3). The M2 has a mass of approximately 1.5 metric tons and the mirror support system will need to maintain the mirror figure at different gravity orientations. The optical performance evaluations were made based on the optimized support systems consisting of 72 axial supports, mounted at the mirror back surface, and 6 tangent link lateral supports mounted around the outer edge. The predicted print-though errors of the M2 supports are 8nm RMS surface for axial gravity and 10nm RMS surface for lateral gravity. The natural frequencies were calculated for the M2 dynamic performance. In addition, thermo-elastic analyses of M2 for thermal gradient cases were conducted. The LSST M2 support system has an active optics capability to maintain optical figure and its performance to correct low-order aberrations has been demonstrated. The optical image qualities and structure functions for the axial and lateral gravity print-through cases, and thermal gradient effects were calculated.

  19. 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.

  20. 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

  1. Why do spatial abilities predict mathematical performance?

    PubMed

    Tosto, Maria Grazia; Hanscombe, Ken B; Haworth, Claire M A; Davis, Oliver S P; Petrill, Stephen A; Dale, Philip S; Malykh, Sergey; Plomin, Robert; Kovas, Yulia

    2014-05-01

    Spatial ability predicts performance in mathematics and eventual expertise in science, technology and engineering. Spatial skills have also been shown to rely on neuronal networks partially shared with mathematics. Understanding the nature of this association can inform educational practices and intervention for mathematical underperformance. Using data on two aspects of spatial ability and three domains of mathematical ability from 4174 pairs of 12-year-old twins, we examined the relative genetic and environmental contributions to variation in spatial ability and to its relationship with different aspects of mathematics. Environmental effects explained most of the variation in spatial ability (~70%) and in mathematical ability (~60%) at this age, and the effects were the same for boys and girls. Genetic factors explained about 60% of the observed relationship between spatial ability and mathematics, with a substantial portion of the relationship explained by common environmental influences (26% and 14% by shared and non-shared environments respectively). These findings call for further research aimed at identifying specific environmental mediators of the spatial-mathematics relationship. PMID:24410830

  2. Program Predicts Performance of Optical Parametric Oscillators

    NASA Technical Reports Server (NTRS)

    Cross, Patricia L.; Bowers, Mark

    2006-01-01

    A computer program predicts the performances of solid-state lasers that operate at wavelengths from ultraviolet through mid-infrared and that comprise various combinations of stable and unstable resonators, optical parametric oscillators (OPOs), and sum-frequency generators (SFGs), including second-harmonic generators (SHGs). The input to the program describes the signal, idler, and pump beams; the SFG and OPO crystals; and the laser geometry. The program calculates the electric fields of the idler, pump, and output beams at three locations (inside the laser resonator, just outside the input mirror, and just outside the output mirror) as functions of time for the duration of the pump beam. For each beam, the electric field is used to calculate the fluence at the output mirror, plus summary parameters that include the centroid location, the radius of curvature of the wavefront leaving through the output mirror, the location and size of the beam waist, and a quantity known, variously, as a propagation constant or beam-quality factor. The program provides a typical Windows interface for entering data and selecting files. The program can include as many as six plot windows, each containing four graphs.

  3. 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…

  4. Pilot Performance With Predictive System Status Information

    NASA Technical Reports Server (NTRS)

    Trujillo, Anna C.

    1997-01-01

    Research has shown a strong pilot preference for predictive information of aircraft system status in the flight deck. However, the benefits of predictive information have not been quantitatively demonstrated. The study described here attempted to identify and quantify these benefits if they existed. In this simulator experiment, three types of predictive information (none, whether a parameter was changing abnormally, and the time for a parameter to reach an alert range) and four initial times to an alert (1 minute, 5 minutes, 15 minutes, and ETA+ 45 minutes) were found to affect when subjects accomplished certain actions, such as accessing pertinent checklists, declaring emergencies, diverting, and calling the flight attendant and dispatch.

  5. 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.

  6. Computational prediction of isolated performance of an axisymmetric nozzle at Mach number 0.90

    NASA Technical Reports Server (NTRS)

    Carlson, John R.

    1994-01-01

    An improved ability to predict external propulsive performance was incorporated into the three-dimensional Navier-Stokes code PAB3D. The improvements are the ability to account for skin friction and external pressure forces. Performance parameters for two axisymmetric supersonic cruise nozzle configurations were calculated to test the improved methodology. Internal and external flow-field regions were computed using a two-equation kappa-epsilon turbulent viscous-stress model. The computed thrust-minus-drag ratios were within 1 percent of the absolute level of experimental data and the trends of data were predicted accurately. The predicted trend of integrated nozzle pressure drag matched the trend of the integrated experimental pressure drag over a range of nozzle pressure ratios, but absolute drag levels were not accurately predicted.

  7. 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.

  8. Accurate low-cost methods for performance evaluation of cache memory systems

    NASA Technical Reports Server (NTRS)

    Laha, Subhasis; Patel, Janak H.; Iyer, Ravishankar K.

    1988-01-01

    Methods of simulation based on statistical techniques are proposed to decrease the need for large trace measurements and for predicting true program behavior. Sampling techniques are applied while the address trace is collected from a workload. This drastically reduces the space and time needed to collect the trace. Simulation techniques are developed to use the sampled data not only to predict the mean miss rate of the cache, but also to provide an empirical estimate of its actual distribution. Finally, a concept of primed cache is introduced to simulate large caches by the sampling-based method.

  9. 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.

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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

  16. A Unified Model of Performance: Validation of its Predictions across Different Sleep/Wake Schedules

    PubMed Central

    Ramakrishnan, Sridhar; Wesensten, Nancy J.; Balkin, Thomas J.; Reifman, Jaques

    2016-01-01

    Study Objectives: Historically, mathematical models of human neurobehavioral performance developed on data from one sleep study were limited to predicting performance in similar studies, restricting their practical utility. We recently developed a unified model of performance (UMP) to predict the effects of the continuum of sleep loss—from chronic sleep restriction (CSR) to total sleep deprivation (TSD) challenges—and validated it using data from two studies of one laboratory. Here, we significantly extended this effort by validating the UMP predictions across a wide range of sleep/wake schedules from different studies and laboratories. Methods: We developed the UMP on psychomotor vigilance task (PVT) lapse data from one study encompassing four different CSR conditions (7 d of 3, 5, 7, and 9 h of sleep/night), and predicted performance in five other studies (from four laboratories), including different combinations of TSD (40 to 88 h), CSR (2 to 6 h of sleep/night), control (8 to 10 h of sleep/night), and nap (nocturnal and diurnal) schedules. Results: The UMP accurately predicted PVT performance trends across 14 different sleep/wake conditions, yielding average prediction errors between 7% and 36%, with the predictions lying within 2 standard errors of the measured data 87% of the time. In addition, the UMP accurately predicted performance impairment (average error of 15%) for schedules (TSD and naps) not used in model development. Conclusions: The unified model of performance can be used as a tool to help design sleep/wake schedules to optimize the extent and duration of neurobehavioral performance and to accelerate recovery after sleep loss. Citation: Ramakrishnan S, Wesensten NJ, Balkin TJ, Reifman J. A unified model of performance: validation of its predictions across different sleep/wake schedules. SLEEP 2016;39(1):249–262. PMID:26518594

  17. 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

  18. Predictions of Performance in Career Education.

    ERIC Educational Resources Information Center

    Novick, M. R.; And Others

    Prediction weights for educational programs in 22 vocational and technical fields are provided using ability scores from the American College Testing Program (ACT) Career Planning Profile and a Bayesian regression theory. The criterion variable studies was first-semester grade-point average. Each vocational-technical program analyzed was…

  19. Specific Mindfulness Skills Differentially Predict Creative Performance.

    PubMed

    Baas, Matthijs; Nevicka, Barbara; Ten Velden, Femke S

    2014-05-23

    Past work has linked mindfulness to improved emotion regulation, interpersonal skills, and basic cognitive abilities, but is unclear about the relation between mindfulness and creativity. Studies examining effects of mindfulness on factors pertinent to creativity suggest a uniform and positive relation, whereas work on specific mindfulness skills suggests that mindfulness skills may differentially predict creativity. To test whether the relation between mindfulness and creativity is positive and uniform (the uniform hypothesis) or differentially depends on particular components of mindfulness (the differential hypothesis), we conducted four studies in which mindfulness skills were measured, extensively trained, or manipulated with a short, incidental meditation session. Results supported a differential relation between mindfulness and creativity: Only the ability to observe and attend to various stimuli consistently and positively predicted creativity. Results regarding other mindfulness skills were less consistent. Implications for theory and practice are discussed.

  20. Investigating the discrepancy between the predicted and actual energy performance of buildings

    NASA Astrophysics Data System (ADS)

    Demanuele, Christine

    The threat of climate change has increased the demand for energy efficiency in buildings, with various stakeholders requesting more accurate predictions of energy consumption, and energy consultants coming under increased pressure to guarantee the energy performance of buildings. This study aims to investigate the factors causing the discrepancy which currently exists between the predicted and actual energy performance of buildings, which will lead to a deeper understanding of this discrepancy and, ultimately, more accurate energy predictions. As part of this study, a non-domestic building in London was modelled and monitored, so as to identify the main contributors to the discrepancy between the predicted and actual energy consumption. In addition, sensitivity analysis was carried out on a number of input variables to establish the set of influential parameters, and to determine whether using such techniques would successfully predict the range in which building energy consumption is likely to fall. The results show that the uncertainty calculated from differential sensitivity analysis encompasses the actual energy performance of the building. The most variable and influential parameters are those which are controlled by occupants, therefore it is paramount that management and occupants are well-informed about the building operation for energy targets to be achieved. Although the sensitivity analysis methods employed are impractical for commercial use, it is possible to develop simpler methods, encompassing all stages of building design and operation, which would decrease the discrepancy between the actual and predicted energy performance of buildings. Such techniques would be invaluable to energy consultants, for whom the cost resting on uncertainties in predictions is substantial due to more demanding clients and fines liable to be paid if energy predictions go wrong. A better understanding of the discrepancy, together with more accurate predictions, would

  1. Rotary-wing aerodynamics. Volume 2: Performance prediction of helicopters

    NASA Technical Reports Server (NTRS)

    Keys, C. N.; Stephniewski, W. Z. (Editor)

    1979-01-01

    Application of theories, as well as, special methods of procedures applicable to performance prediction are illustrated first, on an example of the conventional helicopter and then, winged and tandem configurations. Performance prediction of conventional helicopters in hover and vertical ascent are investigated. Various approaches to performance prediction in forward translation are presented. Performance problems are discussed only this time, a wing is added to the baseline configuration, and both aircraft are compared with respect to their performance. This comparison is extended to a tandem. Appendices on methods for estimating performance guarantees and growth of aircraft concludes this volume.

  2. 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

  3. Performance analysis and prediction in triathlon.

    PubMed

    Ofoghi, Bahadorreza; Zeleznikow, John; Macmahon, Clare; Rehula, Jan; Dwyer, Dan B

    2016-01-01

    Performance in triathlon is dependent upon factors that include somatotype, physiological capacity, technical proficiency and race strategy. Given the multidisciplinary nature of triathlon and the interaction between each of the three race components, the identification of target split times that can be used to inform the design of training plans and race pacing strategies is a complex task. The present study uses machine learning techniques to analyse a large database of performances in Olympic distance triathlons (2008-2012). The analysis reveals patterns of performance in five components of triathlon (three race "legs" and two transitions) and the complex relationships between performance in each component and overall performance in a race. The results provide three perspectives on the relationship between performance in each component of triathlon and the final placing in a race. These perspectives allow the identification of target split times that are required to achieve a certain final place in a race and the opportunity to make evidence-based decisions about race tactics in order to optimise performance.

  4. How to Construct More Accurate Student Models: Comparing and Optimizing Knowledge Tracing and Performance Factor Analysis

    ERIC Educational Resources Information Center

    Gong, Yue; Beck, Joseph E.; Heffernan, Neil T.

    2011-01-01

    Student modeling is a fundamental concept applicable to a variety of intelligent tutoring systems (ITS). However, there is not a lot of practical guidance on how to construct and train such models. This paper compares two approaches for student modeling, Knowledge Tracing (KT) and Performance Factors Analysis (PFA), by evaluating their predictive…

  5. Teacher Performance Pay Signals and Student Achievement: Are Signals Accurate, and How well Do They Work?

    ERIC Educational Resources Information Center

    Manzeske, David; Garland, Marshall; Williams, Ryan; West, Benjamin; Kistner, Alexandra Manzella; Rapaport, Amie

    2016-01-01

    High-performing teachers tend to seek out positions at more affluent or academically challenging schools, which tend to hire more experienced, effective educators. Consequently, low-income and minority students are more likely to attend schools with less experienced and less effective educators (see, for example, DeMonte & Hanna, 2014; Office…

  6. 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

  7. Predicting cycling performance in trained to elite male and female cyclists.

    PubMed

    Lamberts, Robert P

    2014-07-01

    In high-performance cycling, it is important to maintain a healthy balance between training load and recovery. Recently a new submaximal cycle test, known as the Lamberts and Lambert Submaximal Cycle Test (LSCT), has been shown to be able to accurately predict cycling performance in 15 well-trained cyclists. The aim of this study was to determine the predictive value of the LSCT in 102 trained to elite cyclists (82 men and 20 women). All cyclists performed an LSCT test followed by a peak-power-output (PPO) test, which included respiratory-gas analysis for the determination of maximal oxygen consumption (VO(2max)). They then performed the LSCT test followed by a 40-km time trial (TT) 72 h later. Average power output during the 3 stages of the LSCT increased from 31%, 60%, and 79% of PPO, while the ratings of perceived exertion increased from 8 to 13 to 16. Very good relationships were found between actual and LSCT-predicted PPO (r = .98, 95%CI: .97-.98, P < .0001), VO(2max) (r = .96, 95%CI: .97-.99, P < .0001) and 40-km-TT time (r = .98, 95%CI: .94-.97, P < .0001). No gender differences were found when predicting cycling performance from the LSCT (P = .95). The findings of this study show that the LSCT is able to accurately predict cycling performance in trained to elite male and female cyclists and potentially can be used to prescribe and fine-tune training prescription in cycling.

  8. Analysis of factors that predict clinical performance in medical school.

    PubMed

    White, Casey B; Dey, Eric L; Fantone, Joseph C

    2009-10-01

    Academic achievement indices including GPAs and MCAT scores are used to predict the spectrum of medical student academic performance types. However, use of these measures ignores two changes influencing medical school admissions: student diversity and affirmative action, and an increased focus on communication skills. To determine if GPA and MCAT predict performance in medical school consistently across students, and whether either predicts clinical performance in clerkships. A path model was developed to examine relationships among indices of medical student performance during the first three years of medical school for five cohorts of medical students. A structural equation approach was used to calculate the coefficients hypothesized in the model for majority and minority students. Significant differences between majority and minority students were observed. MCAT scores, for example, did not predict performance of minority students in the first year of medical school but did predict performance of majority students. This information may be of use to medical school admissions and resident selection committees. PMID:18030590

  9. Dichotic listening performance predicts language comprehension.

    PubMed

    Asbjørnsen, Arve E; Helland, Turid

    2006-05-01

    Dichotic listening performance is considered a reliable and valid procedure for the assessment of language lateralisation in the brain. However, the documentation of a relationship between language functions and dichotic listening performance is sparse, although it is accepted that dichotic listening measures language perception. In particular, language comprehension should show close correspondence to perception of language stimuli. In the present study, we tested samples of reading-impaired and normally achieving children between 10 and 13 years of age with tests of reading skills, language comprehension, and dichotic listening to consonant-vowel (CV) syllables. A high correlation between the language scores and the dichotic listening performance was expected. However, since the left ear score is believed to be an error when assessing language laterality, covariation was expected for the right ear scores only. In addition, directing attention to one ear input was believed to reduce the influence of random factors, and thus show a more concise estimate of left hemisphere language capacity. Thus, a stronger correlation between language comprehension skills and the dichotic listening performance when attending to the right ear was expected. The analyses yielded a positive correlation between the right ear score in DL and language comprehension, an effect that was stronger when attending to the right ear. The present results confirm the assumption that dichotic listening with CV syllables measures an aspect of language perception and language skills that is related to general language comprehension.

  10. Numerical simulation of turbulence flow in a Kaplan turbine -Evaluation on turbine performance prediction accuracy-

    NASA Astrophysics Data System (ADS)

    Ko, P.; Kurosawa, S.

    2014-03-01

    The understanding and accurate prediction of the flow behaviour related to cavitation and pressure fluctuation in a Kaplan turbine are important to the design work enhancing the turbine performance including the elongation of the operation life span and the improvement of turbine efficiency. In this paper, high accuracy turbine and cavitation performance prediction method based on entire flow passage for a Kaplan turbine is presented and evaluated. Two-phase flow field is predicted by solving Reynolds-Averaged Navier-Stokes equations expressed by volume of fluid method tracking the free surface and combined with Reynolds Stress model. The growth and collapse of cavitation bubbles are modelled by the modified Rayleigh-Plesset equation. The prediction accuracy is evaluated by comparing with the model test results of Ns 400 Kaplan model turbine. As a result that the experimentally measured data including turbine efficiency, cavitation performance, and pressure fluctuation are accurately predicted. Furthermore, the cavitation occurrence on the runner blade surface and the influence to the hydraulic loss of the flow passage are discussed. Evaluated prediction method for the turbine flow and performance is introduced to facilitate the future design and research works on Kaplan type turbine.

  11. Goal Setting and Expectancy Theory Predictions of Effort and Performance.

    ERIC Educational Resources Information Center

    Dossett, Dennis L.; Luce, Helen E.

    Neither expectancy (VIE) theory nor goal setting alone are effective determinants of individual effort and task performance. To test the combined ability of VIE and goal setting to predict effort and performance, 44 real estate agents and their managers completed questionnaires. Quarterly income goals predicted managers' ratings of agents' effort,…

  12. Third Graders' Performance Predictions: Calibration Deflections and Academic Success

    ERIC Educational Resources Information Center

    Ots, Aivar

    2013-01-01

    This study focuses on third grade pupils' (9 to 10 years old) ability to predict their performance in a given task and on the correspondence between the accuracy and adequacy of the predictions on the one hand, and the academic achievement on the other. The study involved 713 pupils from 29 Estonian schools. The pupils' performance predictions…

  13. Does finger sense predict addition performance?

    PubMed

    Newman, Sharlene D

    2016-05-01

    The impact of fingers on numerical and mathematical cognition has received a great deal of attention recently. However, the precise role that fingers play in numerical cognition is unknown. The current study explores the relationship between finger sense, arithmetic and general cognitive ability. Seventy-six children between the ages of 5 and 12 participated in the study. The results of stepwise multiple regression analyses demonstrated that while general cognitive ability including language processing was a predictor of addition performance, finger sense was not. The impact of age on the relationship between finger sense, and addition was further examined. The participants were separated into two groups based on age. The results showed that finger gnosia score impacted addition performance in the older group but not the younger group. These results appear to support the hypothesis that fingers provide a scaffold for calculation and that if that scaffold is not properly built, it has continued differential consequences to mathematical cognition. PMID:26993292

  14. Human vision model to predict observer performance: detection of microcalcifications as a function of monitor phosphor

    NASA Astrophysics Data System (ADS)

    Krupinski, Elizabeth A.; Johnson, Jeffrey P.; Roehrig, Hans; Lubin, Jeffrey; Engstrom, Michael

    2003-05-01

    The goal was to develop an efficient method of optimizing CRT monitor performance for digital mammography. The Sarnoff JNDmetrix vision model is based on just-noticeable difference measurement and frequency-channel vision-modeling principles. Given 2 images as input the model returns accurate, robust estimates of discriminability. Model predictions are compared with human performance. Mammographic images with microcalcifications were viewed by six radiologists, once on a monitor with P45 and once on one with P104 phosphor. Results were compared with output of the model used to predict differences in perceptibility of calcifications using luminance data measured with a high-resolution CCD camera. Human performance was best with high contrast clusters and got worse with each decrease in contrast. Performance was better with the P45 than the P104 for targets at all contrast levels. The JNDmetrix model predicted the same pattern of results. Correlation between human and model observer performance was very high. We have demonstrated the utility of using a vision model to accurately predict human detection performance. The type of phosphor in a monitor influences observer performance at least for the detection of microcalcifications. The main reason is that the P104 has a higher luminance, but the P45 has a higher signal-to-noise ratio.

  15. 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.

  16. Predicted thermal performance of triple vacuum glazing

    SciTech Connect

    Fang, Yueping; Hyde, Trevor J.; Hewitt, Neil

    2010-12-15

    The simulated triple vacuum glazing (TVG) consists of three 4 mm thick glass panes with two vacuum gaps, with each internal glass surface coated with a low-emittance coating with an emittance of 0.03. The two vacuum gaps are sealed by an indium based sealant and separated by a stainless steel pillar array with a height of 0.12 mm and a pillar diameter of 0.3 mm spaced at 25 mm. The thermal transmission at the centre-of-glazing area of the TVG was predicted to be 0.26 W m{sup -2} K{sup -1}. The simulation results show that although the thermal conductivity of solder glass (1 W m{sup -1} K{sup -1}) and indium (83.7 W m{sup -1} K{sup -1}) are very different, the difference in thermal transmission of TVGs resulting from the use of an indium and a solder glass edge seal was 0.01 W m{sup -2} K{sup -1}. This is because the edge seal is so thin (0.12 mm), consequently there is a negligible temperature drop across it irrespective of the material that the seal is made from relative to the total temperature difference across the glazing. The results also show that there is a relatively large increase in the overall thermal conductance of glazings without a frame when the width of the indium edge seal is increased. Increasing the rebate depth in a solid wood frame decreased the heat transmission of the TVG. The overall heat transmission of the simulated 0.5 m by 0.5 m TVG was 32.6% greater than that of the 1 m by 1 m TVG, since heat conduction through the edge seal of the small glazing has a larger contribution to the total glazing heat transfer than that of the larger glazing system. (author)

  17. Short-term retention of relational memory in amnesia revisited: accurate performance depends on hippocampal integrity.

    PubMed

    Yee, Lydia T S; Hannula, Deborah E; Tranel, Daniel; Cohen, Neal J

    2014-01-01

    Traditionally, it has been proposed that the hippocampus and adjacent medial temporal lobe cortical structures are selectively critical for long-term declarative memory, which entails memory for inter-item and item-context relationships. Whether the hippocampus might also contribute to short-term retention of relational memory representations has remained controversial. In two experiments, we revisit this question by testing memory for relationships among items embedded in scenes using a standard working memory trial structure in which a sample stimulus is followed by a brief delay and the corresponding test stimulus. In each experimental block, eight trials using different exemplars of the same scene were presented. The exemplars contained the same items but with different spatial relationships among them. By repeating the pictures across trials, any potential contributions of item or scene memory to performance were minimized, and relational memory could be assessed more directly than has been done previously. When test displays were presented, participants indicated whether any of the item-location relationships had changed. Then, regardless of their responses (and whether any item did change its location), participants indicated on a forced-choice test, which item might have moved, guessing if necessary. Amnesic patients were impaired on the change detection test, and were frequently unable to specify the change after having reported correctly that a change had taken place. Comparison participants, by contrast, frequently identified the change even when they failed to report the mismatch, an outcome that speaks to the sensitivity of the change specification measure. These results confirm past reports of hippocampal contributions to short-term retention of relational memory representations, and suggest that the role of the hippocampus in memory has more to do with relational memory requirements than the length of a retention interval.

  18. Short-term retention of relational memory in amnesia revisited: accurate performance depends on hippocampal integrity

    PubMed Central

    Yee, Lydia T. S.; Hannula, Deborah E.; Tranel, Daniel; Cohen, Neal J.

    2014-01-01

    Traditionally, it has been proposed that the hippocampus and adjacent medial temporal lobe cortical structures are selectively critical for long-term declarative memory, which entails memory for inter-item and item-context relationships. Whether the hippocampus might also contribute to short-term retention of relational memory representations has remained controversial. In two experiments, we revisit this question by testing memory for relationships among items embedded in scenes using a standard working memory trial structure in which a sample stimulus is followed by a brief delay and the corresponding test stimulus. In each experimental block, eight trials using different exemplars of the same scene were presented. The exemplars contained the same items but with different spatial relationships among them. By repeating the pictures across trials, any potential contributions of item or scene memory to performance were minimized, and relational memory could be assessed more directly than has been done previously. When test displays were presented, participants indicated whether any of the item-location relationships had changed. Then, regardless of their responses (and whether any item did change its location), participants indicated on a forced-choice test, which item might have moved, guessing if necessary. Amnesic patients were impaired on the change detection test, and were frequently unable to specify the change after having reported correctly that a change had taken place. Comparison participants, by contrast, frequently identified the change even when they failed to report the mismatch, an outcome that speaks to the sensitivity of the change specification measure. These results confirm past reports of hippocampal contributions to short-term retention of relational memory representations, and suggest that the role of the hippocampus in memory has more to do with relational memory requirements than the length of a retention interval. PMID:24478681

  19. Does IQ Really Predict Job Performance?

    PubMed Central

    Richardson, Ken; Norgate, Sarah H.

    2015-01-01

    IQ has played a prominent part in developmental and adult psychology for decades. In the absence of a clear theoretical model of internal cognitive functions, however, construct validity for IQ tests has always been difficult to establish. Test validity, therefore, has always been indirect, by correlating individual differences in test scores with what are assumed to be other criteria of intelligence. Job performance has, for several reasons, been one such criterion. Correlations of around 0.5 have been regularly cited as evidence of test validity, and as justification for the use of the tests in developmental studies, in educational and occupational selection and in research programs on sources of individual differences. Here, those correlations are examined together with the quality of the original data and the many corrections needed to arrive at them. It is concluded that considerable caution needs to be exercised in citing such correlations for test validation purposes. PMID:26405429

  20. Measured and predicted rotor performance for the SERI advanced wind turbine blades

    NASA Astrophysics Data System (ADS)

    Tangler, J.; Smith, B.; Kelley, N.; Jager, D.

    1992-02-01

    Measured and predicted rotor performance for the Solar Energy Research Institute (SERI) advanced wind turbine blades were compared to assess the accuracy of predictions and to identify the sources of error affecting both predictions and measurements. An awareness of these sources of error contributes to improved prediction and measurement methods that will ultimately benefit future rotor design efforts. Propeller/vane anemometers were found to underestimate the wind speed in turbulent environments such as the San Gorgonio Pass wind farm area. Using sonic or cup anemometers, good agreement was achieved between predicted and measured power output for wind speeds up to 8 m/sec. At higher wind speeds an optimistic predicted power output and the occurrence of peak power at wind speeds lower than measurements resulted from the omission of turbulence and yaw error. In addition, accurate two-dimensional (2-D) airfoil data prior to stall and a post stall airfoil data synthesization method that reflects three-dimensional (3-D) effects were found to be essential for accurate performance prediction.

  1. Performance prediction of the Wells self-rectifying air turbine

    NASA Astrophysics Data System (ADS)

    Raghunathan, S.; Tan, C. P.

    An experimental and analytical study of the effects of geometric and aerodynamic variables on the performance of the Wells self-rectifying axial flow air turbine is presented. Experiments were performed in a unidirectional flow rig. Two approaches to the prediction of the performance of the Wells turbine were described, both of which were based on two-dimensional cascade theory and isolated aerofoil data. Finally, comparisons of the predicted results with the experimental results were made.

  2. Reliable predictions of waste performance in a geologic repository

    SciTech Connect

    Pigford, T.H.; Chambre, P.L.

    1985-08-01

    Establishing reliable estimates of long-term performance of a waste repository requires emphasis upon valid theories to predict performance. Predicting rates that radionuclides are released from waste packages cannot rest upon empirical extrapolations of laboratory leach data. Reliable predictions can be based on simple bounding theoretical models, such as solubility-limited bulk-flow, if the assumed parameters are reliably known or defensibly conservative. Wherever possible, performance analysis should proceed beyond simple bounding calculations to obtain more realistic - and usually more favorable - estimates of expected performance. Desire for greater realism must be balanced against increasing uncertainties in prediction and loss of reliability. Theoretical predictions of release rate based on mass-transfer analysis are bounding and the theory can be verified. Postulated repository analogues to simulate laboratory leach experiments introduce arbitrary and fictitious repository parameters and are shown not to agree with well-established theory. 34 refs., 3 figs., 2 tabs.

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

    PubMed

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

    2015-08-01

    Preclinical development of new biological entities (NBEs), such as human protein therapeutics, requires considerable expenditure of time and costs. Poor prediction of pharmacokinetics in humans further reduces net efficiency. In this study, we show for the first time that pharmacokinetic data of NBEs in humans can be successfully obtained early in the drug development process by the use of microdosing in a small group of healthy subjects combined with ultrasensitive accelerator mass spectrometry (AMS). After only minimal preclinical testing, we performed a first-in-human phase 0/phase 1 trial with a human recombinant therapeutic protein (RESCuing Alkaline Phosphatase, human recombinant placental alkaline phosphatase [hRESCAP]) to assess its safety and kinetics. Pharmacokinetic analysis showed dose linearity from microdose (53 μg) [(14) C]-hRESCAP to therapeutic doses (up to 5.3 mg) of the protein in healthy volunteers. This study demonstrates the value of a microdosing approach in a very small cohort for accelerating the clinical development of NBEs. PMID:25869840

  4. 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.

  5. Performance Reports: Mirror alignment system performance prediction comparison between SAO and EKC

    NASA Technical Reports Server (NTRS)

    Tananbaum, H. D.; Zhang, J. P.

    1994-01-01

    The objective of this study is to perform an independent analysis of the residual high resolution mirror assembly (HRMA) mirror distortions caused by force and moment errors in the mirror alignment system (MAS) to statistically predict the HRMA performance. These performance predictions are then compared with those performed by Kodak to verify their analysis results.

  6. The level of detail required in a deformable phantom to accurately perform quality assurance of deformable image registration

    NASA Astrophysics Data System (ADS)

    Saenz, Daniel L.; Kim, Hojin; Chen, Josephine; Stathakis, Sotirios; Kirby, Neil

    2016-09-01

    The primary purpose of the study was to determine how detailed deformable image registration (DIR) phantoms need to adequately simulate human anatomy and accurately assess the quality of DIR algorithms. In particular, how many distinct tissues are required in a phantom to simulate complex human anatomy? Pelvis and head-and-neck patient CT images were used for this study as virtual phantoms. Two data sets from each site were analyzed. The virtual phantoms were warped to create two pairs consisting of undeformed and deformed images. Otsu’s method was employed to create additional segmented image pairs of n distinct soft tissue CT number ranges (fat, muscle, etc). A realistic noise image was added to each image. Deformations were applied in MIM Software (MIM) and Velocity deformable multi-pass (DMP) and compared with the known warping. Images with more simulated tissue levels exhibit more contrast, enabling more accurate results. Deformation error (magnitude of the vector difference between known and predicted deformation) was used as a metric to evaluate how many CT number gray levels are needed for a phantom to serve as a realistic patient proxy. Stabilization of the mean deformation error was reached by three soft tissue levels for Velocity DMP and MIM, though MIM exhibited a persisting difference in accuracy between the discrete images and the unprocessed image pair. A minimum detail of three levels allows a realistic patient proxy for use with Velocity and MIM deformation algorithms.

  7. The level of detail required in a deformable phantom to accurately perform quality assurance of deformable image registration.

    PubMed

    Saenz, Daniel L; Kim, Hojin; Chen, Josephine; Stathakis, Sotirios; Kirby, Neil

    2016-09-01

    The primary purpose of the study was to determine how detailed deformable image registration (DIR) phantoms need to adequately simulate human anatomy and accurately assess the quality of DIR algorithms. In particular, how many distinct tissues are required in a phantom to simulate complex human anatomy? Pelvis and head-and-neck patient CT images were used for this study as virtual phantoms. Two data sets from each site were analyzed. The virtual phantoms were warped to create two pairs consisting of undeformed and deformed images. Otsu's method was employed to create additional segmented image pairs of n distinct soft tissue CT number ranges (fat, muscle, etc). A realistic noise image was added to each image. Deformations were applied in MIM Software (MIM) and Velocity deformable multi-pass (DMP) and compared with the known warping. Images with more simulated tissue levels exhibit more contrast, enabling more accurate results. Deformation error (magnitude of the vector difference between known and predicted deformation) was used as a metric to evaluate how many CT number gray levels are needed for a phantom to serve as a realistic patient proxy. Stabilization of the mean deformation error was reached by three soft tissue levels for Velocity DMP and MIM, though MIM exhibited a persisting difference in accuracy between the discrete images and the unprocessed image pair. A minimum detail of three levels allows a realistic patient proxy for use with Velocity and MIM deformation algorithms. PMID:27494827

  8. "Too Complex for Me!" Why Do Performance-Approach and Performance-Avoidance Goals Predict Exam Performance?

    ERIC Educational Resources Information Center

    Darnon, Celine; Butera, Fabrizio; Mugny, Gabriel; Quiamzade, Alain; Hulleman, Chris S.

    2009-01-01

    Classroom research on achievement goals has revealed that performance-approach goals (goals to outperform others) positively predict exam performance whereas performance-avoidance goals (goals not to perform more poorly than others) negatively predict it. Because prior classroom research has primarily utilized multiple-choice exam performance, the…

  9. 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}.

  10. Mastery and Performance Goals Predict Epistemic and Relational Conflict Regulation

    ERIC Educational Resources Information Center

    Darnon, Celine; Muller, Dominique; Schrager, Sheree M.; Pannuzzo, Nelly; Butera, Fabrizio

    2006-01-01

    The present research examines whether mastery and performance goals predict different ways of reacting to a sociocognitive conflict with another person over materials to be learned, an issue not yet addressed by the achievement goal literature. Results from 2 studies showed that mastery goals predicted epistemic conflict regulation (a conflict…

  11. Thermal system field performance predictions from laboratory and field measurements

    NASA Astrophysics Data System (ADS)

    Burks, Stephen D.; Haefner, David P.; Teaney, Brian P.; Doe, Joshua M.

    2016-05-01

    Laboratory measurements on thermal imaging systems are critical to understanding their performance in a field environment. However, it is rarely a straightforward process to directly inject thermal measurements into thermal performance modeling software to acquire meaningful results. Some of the sources of discrepancies between laboratory and field measurements are sensor gain and level, dynamic range, sensor display and display brightness, and the environment where the sensor is operating. If measurements for the aforementioned parameters could be performed, a more accurate description of sensor performance in a particular environment is possible. This research will also include the procedure for turning both laboratory and field measurements into a system model.

  12. The engine performance prediction by quasi-steady method

    NASA Astrophysics Data System (ADS)

    Ye, Ai-Yun; Zhang, Yanqin

    1995-01-01

    In this paper, the theory of Quasi-steady is applied to the calculations of turbochargers matching to the diesel engines and performance prediction. The engine performance prediction programs written in language C have been used for calculations of various turbocharged diesel engines. It has been confirmed by the comparisons with experimental data that the results of the calculation are reasonable, reliable and satisfied for the engineering applications.

  13. Predicting Performance on Academic and Non-Academic Tasks: A Comparison of Adolescents with and without Learning Disabilities

    ERIC Educational Resources Information Center

    Job, Jenelle M.; Klassen, Robert M.

    2012-01-01

    Previous research suggests that adolescents with learning disabilities (LD) are less accurate in predicting academic performance than normally achieving (NA) adolescents and display a tendency to overestimate their level of performance (e.g., Klassen, 2007). However, no studies have been conducted investigating whether this overestimation is…

  14. The Impact of Trajectory Prediction Uncertainty on Air Traffic Controller Performance and Acceptability

    NASA Technical Reports Server (NTRS)

    Mercer, Joey S.; Bienert, Nancy; Gomez, Ashley; Hunt, Sarah; Kraut, Joshua; Martin, Lynne; Morey, Susan; Green, Steven M.; Prevot, Thomas; Wu, Minghong G.

    2013-01-01

    A Human-In-The-Loop air traffic control simulation investigated the impact of uncertainties in trajectory predictions on NextGen Trajectory-Based Operations concepts, seeking to understand when the automation would become unacceptable to controllers or when performance targets could no longer be met. Retired air traffic controllers staffed two en route transition sectors, delivering arrival traffic to the northwest corner-post of Atlanta approach control under time-based metering operations. Using trajectory-based decision-support tools, the participants worked the traffic under varying levels of wind forecast error and aircraft performance model error, impacting the ground automations ability to make accurate predictions. Results suggest that the controllers were able to maintain high levels of performance, despite even the highest levels of trajectory prediction errors.

  15. 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

  16. Predicting the performance of belt filter presses using the Crown Press for laboratory simulation

    SciTech Connect

    Graham, T.M.

    1999-07-26

    Belt filter presses (BFPs) are among the most commonly used devices to dewater wastewater sludge. The concept used by a BFP to achieve dewatered cake solids is relatively simple; however, replicating this performance in the laboratory in order to predict the performance of a BFP with reasonable reliability has proven to be a challenge. The Crown Press is one tool that has been shown to replicate the performance of anaerobically digested sludge on a BFP. This study used the Crown Press to replicate and predict the performance of waste activated sludge (WAS) from the Mauldin Road wastewater treatment plant on BFPs. Several operational variables, including belt speed, belt tension, polymer type, and polymer dose, were changed on the Crown Press to predict how the changes on the BFP would affect performance. Two polymers were chosen to be tested on the BFPs at Mauldin Road based on Crown Press predictions. The first polymer performed the same as the plant`s current polymer in the lab, and the second performed better (achieved higher final cake solids) than the current polymer. These predictions were borne out in the BFP tests, showing that the Crown Press predictions were accurate. The Crown Press predictions were also compared to the predictions made by the capillary suction time (CST) and specific resistance to filtration (SRF) tests. The Crown Press provided more information regarding the affect of polymer type and dose on cake solids than either CST or SRF. The Crown Press was shown to be a viable tool to assess potential changes in BFP performance with WAS when operational variables change.

  17. Predicting dynamic performance limits for servosystems with saturating nonlinearities

    NASA Technical Reports Server (NTRS)

    Webb, J. A., Jr.; Blech, R. A.

    1979-01-01

    A generalized treatment for a system with a single saturating nonlinearity is presented and compared with frequency response plots obtained from an analog model of the system. Once the amplitude dynamics are predicted with the limit lines, an iterative technique is employed to determine the system phase response. The saturation limit line technique is used in conjunction with velocity and acceleration limits to predict the performance of an electro-hydraulic servosystem containing a single-stage servovalve. Good agreement was obtained between predicted performance and experimental data.

  18. Feedback about More Accurate versus Less Accurate Trials: Differential Effects on Self-Confidence and Activation

    ERIC Educational Resources Information Center

    Badami, Rokhsareh; VaezMousavi, Mohammad; Wulf, Gabriele; Namazizadeh, Mahdi

    2012-01-01

    One purpose of the present study was to examine whether self-confidence or anxiety would be differentially affected by feedback from more accurate rather than less accurate trials. The second purpose was to determine whether arousal variations (activation) would predict performance. On Day 1, participants performed a golf putting task under one of…

  19. Allometric scaling and predicting cycling performance in (well-) trained female cyclists.

    PubMed

    Lamberts, R P; Davidowitz, K J

    2014-03-01

    As female cycling attains greater professionalism, a larger emphasis is placed on the ability to predict and monitor changes in their cycling performance. The main aim of this study was to determine if peak power output (PPO) adjusted for body mass (W · kg-0.32) accurately predicts flat 40-km time trial performance (40 km TT) in female cyclists as found in men. 20 (well-) trained female cyclists completed a PPO test including maximal oxygen consumption (VO2max) and a flat 40 km TT test. Relationships between cycling performance parameters were also compared to the cycling performance of 45 male cyclists. Allometrically scaled PPW (W · kg(-0.32)) most accurately predicted 40 km TT performance in the female cyclists (r = -0.87, p<0.0001) compared to any other method, however different slopes between the parameters were found in the female and male cyclists (p=0.000115). In addition gender differences were also found between the relationship between relative PPO (W · kg-1) and relative VO2max (ml · min-1 · kg(-1))(p<0.0001), while no gender differences were found between actual and predicted cycling performance based on the Lamberts and Lambert Submaximal Cycle Test (LSCT), which was used a standardized warm-up. In conclusion, relationships between relative cycling parameters seem to differ between genders, while relationships between absolute cycling parameters seem to be similar. Therefore gender specific regression equations should be used when predicting relative cycling performance parameters.

  20. 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.

  1. Prediction of Gymnastic Performance from Arousal and Anxiety Measures.

    ERIC Educational Resources Information Center

    Basler, Marilyn L.; And Others

    This study predicts gymnastic performance, arousal, and anxiety measures from past performances. Pulse rate and the Palmar Sweat Index were utilized as indicants of arousal. Anxiety was assessed by means of the State-Trait Anxiety Inventory. Eighteen members of the Ithaca College women's varsity gymnastic team were tested throughout the 1973-74…

  2. Prediction of Muscle Performance During Dynamic Repetitive Exercise

    NASA Technical Reports Server (NTRS)

    Byerly, D. L.; Byerly, K. A.; Sognier, M. A.; Squires, W. G.

    2002-01-01

    A method for predicting human muscle performance was developed. Eight test subjects performed a repetitive dynamic exercise to failure using a Lordex spinal machine. Electromyography (EMG) data was collected from the erector spinae. Evaluation of the EMG data using a 5th order Autoregressive (AR) model and statistical regression analysis revealed that an AR parameter, the mean average magnitude of AR poles, can predict performance to failure as early as the second repetition of the exercise. Potential applications to the space program include evaluating on-orbit countermeasure effectiveness, maximizing post-flight recovery, and future real-time monitoring capability during Extravehicular Activity.

  3. SEMICONDUCTOR INTEGRATED CIRCUITS: Accurate metamodels of device parameters and their applications in performance modeling and optimization of analog integrated circuits

    NASA Astrophysics Data System (ADS)

    Tao, Liang; Xinzhang, Jia; Junfeng, Chen

    2009-11-01

    Techniques for constructing metamodels of device parameters at BSIM3v3 level accuracy are presented to improve knowledge-based circuit sizing optimization. Based on the analysis of the prediction error of analytical performance expressions, operating point driven (OPD) metamodels of MOSFETs are introduced to capture the circuit's characteristics precisely. In the algorithm of metamodel construction, radial basis functions are adopted to interpolate the scattered multivariate data obtained from a well tailored data sampling scheme designed for MOSFETs. The OPD metamodels can be used to automatically bias the circuit at a specific DC operating point. Analytical-based performance expressions composed by the OPD metamodels show obvious improvement for most small-signal performances compared with simulation-based models. Both operating-point variables and transistor dimensions can be optimized in our nesting-loop optimization formulation to maximize design flexibility. The method is successfully applied to a low-voltage low-power amplifier.

  4. Using individual differences to predict job performance: correcting for direct and indirect restriction of range.

    PubMed

    Sjöberg, Sofia; Sjöberg, Anders; Näswall, Katharina; Sverke, Magnus

    2012-08-01

    The present study investigates the relationship between individual differences, indicated by personality (FFM) and general mental ability (GMA), and job performance applying two different methods of correction for range restriction. The results, derived by analyzing meta-analytic correlations, show that the more accurate method of correcting for indirect range restriction increased the operational validity of individual differences in predicting job performance and that this increase primarily was due to general mental ability being a stronger predictor than any of the personality traits. The estimates for single traits can be applied in practice to maximize prediction of job performance. Further, differences in the relative importance of general mental ability in relation to overall personality assessment methods was substantive and the estimates provided enables practitioners to perform a correct utility analysis of their overall selection procedure. PMID:22612634

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

    ERIC Educational Resources Information Center

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

    2007-01-01

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

  6. 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

  7. 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.

  8. Evaluation of performance of predictive models for deoxynivalenol in wheat.

    PubMed

    van der Fels-Klerx, H J

    2014-02-01

    The aim of this study was to evaluate the performance of two predictive models for deoxynivalenol contamination of wheat at harvest in the Netherlands, including the use of weather forecast data and external model validation. Data were collected in a different year and from different wheat fields than data used for model development. The two models were run for six preset scenarios, varying in the period for which weather forecast data were used, from zero-day (historical data only) to a 13-day period around wheat flowering. Model predictions using forecast weather data were compared to those using historical data. Furthermore, model predictions using historical weather data were evaluated against observed deoxynivalenol contamination of the wheat fields. Results showed that the use of weather forecast data rather than observed data only slightly influenced model predictions. The percent of correct model predictions, given a threshold of 1,250 μg/kg (legal limit in European Union), was about 95% for the two models. However, only three samples had a deoxynivalenol concentration above this threshold, and the models were not able to predict these samples correctly. It was concluded that two- week weather forecast data can reliable be used in descriptive models for deoxynivalenol contamination of wheat, resulting in more timely model predictions. The two models are able to predict lower deoxynivalenol contamination correctly, but model performance in situations with high deoxynivalenol contamination needs to be further validated. This will need years with conducive environmental conditions for deoxynivalenol contamination of wheat.

  9. 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

  10. Comparative assessment of psychomotor performance - Target prediction by humans and macaques (Macaca mulatta)

    NASA Technical Reports Server (NTRS)

    Washburn, David A.; Rumbaugh, Duane M.

    1992-01-01

    Although nonhuman primates such as rhesus monkeys (Macaca mulatta) have been useful models of many aspects of cognition and performance, it has been argued that, unlike humans, they may lack the capacity to respond as predictor-operators. Data from the present series of experiments undermine this claim, suggesting instead a continuity of predictive competency between humans and nonhuman primates. A prediction coefficient was devised to examine the degree to which each subject's response path approximated the optimal predictive strategy. Whereas human subjects (N= 30) generally predicted more accurately, rhesus monkeys (N= 10) also significantly anticipated the movements of the target in all conditions. It appears that humans and rhesus monkeys both exhibit the capacity to respond to where a stimulus is going.

  11. 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

  12. Recent progress towards predicting aircraft ground handling performance

    NASA Technical Reports Server (NTRS)

    Yager, T. J.; White, E. J.

    1981-01-01

    Capability implemented in simulating aircraft ground handling performance is reviewed and areas for further expansion and improvement are identified. Problems associated with providing necessary simulator input data for adequate modeling of aircraft tire/runway friction behavior are discussed and efforts to improve tire/runway friction definition, and simulator fidelity are described. Aircraft braking performance data obtained on several wet runway surfaces are compared to ground vehicle friction measurements. Research to improve methods of predicting tire friction performance are discussed.

  13. Predicting Performance in Higher Education Using Proximal Predictors.

    PubMed

    Niessen, A Susan M; Meijer, Rob R; Tendeiro, Jorge N

    2016-01-01

    We studied the validity of two methods for predicting academic performance and student-program fit that were proximal to important study criteria. Applicants to an undergraduate psychology program participated in a selection procedure containing a trial-studying test based on a work sample approach, and specific skills tests in English and math. Test scores were used to predict academic achievement and progress after the first year, achievement in specific course types, enrollment, and dropout after the first year. All tests showed positive significant correlations with the criteria. The trial-studying test was consistently the best predictor in the admission procedure. We found no significant differences between the predictive validity of the trial-studying test and prior educational performance, and substantial shared explained variance between the two predictors. Only applicants with lower trial-studying scores were significantly less likely to enroll in the program. In conclusion, the trial-studying test yielded predictive validities similar to that of prior educational performance and possibly enabled self-selection. In admissions aimed at student-program fit, or in admissions in which past educational performance is difficult to use, a trial-studying test is a good instrument to predict academic performance.

  14. Predicting Performance in Higher Education Using Proximal Predictors

    PubMed Central

    Niessen, A. Susan M.; Meijer, Rob R.; Tendeiro, Jorge N.

    2016-01-01

    We studied the validity of two methods for predicting academic performance and student-program fit that were proximal to important study criteria. Applicants to an undergraduate psychology program participated in a selection procedure containing a trial-studying test based on a work sample approach, and specific skills tests in English and math. Test scores were used to predict academic achievement and progress after the first year, achievement in specific course types, enrollment, and dropout after the first year. All tests showed positive significant correlations with the criteria. The trial-studying test was consistently the best predictor in the admission procedure. We found no significant differences between the predictive validity of the trial-studying test and prior educational performance, and substantial shared explained variance between the two predictors. Only applicants with lower trial-studying scores were significantly less likely to enroll in the program. In conclusion, the trial-studying test yielded predictive validities similar to that of prior educational performance and possibly enabled self-selection. In admissions aimed at student-program fit, or in admissions in which past educational performance is difficult to use, a trial-studying test is a good instrument to predict academic performance. PMID:27073859

  15. A Free Wake Numerical Simulation for Darrieus Vertical Axis Wind Turbine Performance Prediction

    NASA Astrophysics Data System (ADS)

    Belu, Radian

    2010-11-01

    In the last four decades, several aerodynamic prediction models have been formulated for the Darrieus wind turbine performances and characteristics. We can identified two families: stream-tube and vortex. The paper presents a simplified numerical techniques for simulating vertical axis wind turbine flow, based on the lifting line theory and a free vortex wake model, including dynamic stall effects for predicting the performances of a 3-D vertical axis wind turbine. A vortex model is used in which the wake is composed of trailing stream-wise and shedding span-wise vortices, whose strengths are equal to the change in the bound vortex strength as required by the Helmholz and Kelvin theorems. Performance parameters are computed by application of the Biot-Savart law along with the Kutta-Jukowski theorem and a semi-empirical stall model. We tested the developed model with an adaptation of the earlier multiple stream-tube performance prediction model for the Darrieus turbines. Predictions by using our method are shown to compare favorably with existing experimental data and the outputs of other numerical models. The method can predict accurately the local and global performances of a vertical axis wind turbine, and can be used in the design and optimization of wind turbines for built environment applications.

  16. 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.

  17. 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

  18. 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

  19. 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.

  20. 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

  1. 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

  2. Predicting Road Test Performance in Drivers With Stroke

    PubMed Central

    Barco, Peggy P.; Wallendorf, Michael J.; Snellgrove, Carol A.; Ott, Brian R.

    2014-01-01

    OBJECTIVE. The aim of this study was to develop a brief screening battery to predict the on-road performance of drivers who had experienced a stroke. METHOD. We examined 72 people with stroke referred by community physicians to an academic rehabilitation center. The outcome variable was pass or fail on the modified Washington University Road Test. Predictor measures were tests of visual, motor, and cognitive functioning. RESULTS. The best predictive model for failure on the road test included Trail Making Test Part A and the Snellgrove Maze Task®. CONCLUSION. A screening battery that can be performed in less than 5 min was able to assist in the prediction of road test performance in a sample of drivers with stroke. A probability of failure calculator may be useful for clinicians in their decision to refer clients with stroke for a comprehensive driving evaluation. PMID:24581409

  3. Thermal Conductivity of UO2 Fuel: Predicting Fuel Performance from Simulation

    SciTech Connect

    Phillpot, Simon R.; El-Azab, Anter; Chernatynskiy, Aleksandr; Tulenko, James S.

    2011-08-19

    Recent progress in understanding the thermal-transport properties of UO₂ for fission reactors is reviewed from the perspective of computer simulations. A path to incorporating more accurate materials models into fuel performance codes is outlined. In particular, it is argued that a judiciously integrated program of atomic-level simulations and mesoscale simulations offers the possibility of both better predicting the thermal-transport properties of UO₂ in light-water reactors and enabling the assessment of the thermal performances of novel fuel systems for which extensive experimental databases are not available.

  4. Cardiovascular indices of challenge and threat states predict competitive performance.

    PubMed

    Turner, Martin J; Jones, Marc V; Sheffield, David; Cross, Sophie L

    2012-10-01

    Cardiovascular (CV) reactivity is proposed by both the Biopsychosocial Model and the Theory of Challenge and Threat States in Athletes to predict competitive performance. The association between CV reactivity and competitive performance was examined in cognitive (Study 1) and motor (Study 2) tasks. In Study 1, 25 participants (9 female) completed a modified Stroop Test, and in Study 2, 21 female netballers completed a netball shooting task, under competition. Measures of CV reactivity, self-report measures of self-efficacy, control, achievement-goals and emotions along with baseline and competitive task performance were taken. CV reactivity indicative of a challenge state predicted superior performance in both tasks compared to CV reactivity indicative of a threat state. In both studies the purported relationships between CV reactivity and the psychological and emotional responses were weak or absent. The mechanisms for the observed association between CV reactivity and task performance are discussed alongside implications of the findings for future research and practice.

  5. A free wake method for performance prediction of VAWT

    NASA Astrophysics Data System (ADS)

    Ilin, S.; Dumitrescu, H.; Cardos, V.; Dumitrache, A.

    2012-09-01

    Based on the lifting line theory and a free vortex wake model, a method including dynamic stall effects is presented for predicting the performance of a three-dimensional vertical-axis wind turbine (VAWT). A vortex model is used in which the wake is composed of trailing streamwise and shedding spanwise vortices, whose strengths are equal to the change in the bound vortex strength as dictated by Helmholtz and Kelvin's theorems. Performance parameters are calculated by application of the Biot-Savart law along with the Kutta-Joukowski theorem and a semi-empirical dynamic stall model. Predictions are shown to compare favorably with existing experimental data.

  6. Predicting course performance in freshman and sophomore physics courses: Women are more predictable than men

    NASA Astrophysics Data System (ADS)

    McCammon, Susan; Golden, Jeannie; Wuensch, Karl L.

    This study investigated the extent to which thinking skills and mathematical competency would predict the course performance of freshman and sophomore science majors enrolled in physics courses. Multiple-regression equations revealed that algebra and critical thinking skills were the best overall predictors across several physics courses. Although arithmetic skills, math anxiety, and primary mental abilities scores also correlated with performance, they were redundant with the algebra and critical thinking. The most surprising finding of the study was the differential validity by sex; predictor variables were successful in predicting course performance for women but not for men.

  7. 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

  8. 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.

  9. 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

  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. Predicting poor physical performance after total knee arthroplasty.

    PubMed

    Bade, Michael J; Wolfe, Pamela; Zeni, Joseph A; Stevens-Lapsley, Jennifer E; Snyder-Mackler, Lynn

    2012-11-01

    The purpose of this study was to develop a preliminary decision algorithm predicting functional performance outcomes to aid in the decision of when to undergo total knee arthroplasty (TKA). One hundred and nineteen patients undergoing primary unilateral TKA were evaluated before and 6 months after TKA. A regression tree analysis using a recursive partitioning function was performed with the Timed Up and Go (TUG) time, Six-Minute Walk (6MW) distance, and Stair Climbing Test (SCT) time as measured 6 months after TKA as the primary outcomes. Preoperative measures of functional performance, joint performance, anthropometrics, demographics, and self-reported status were evaluated as predictors of the primary outcomes 6 months after surgery. Individuals taking ≥10.1 s on the TUG and aged 72 years or older before surgery had the poorest performance on the TUG 6 months after surgery. Individuals walking <314 meters on the 6MW before surgery had the poorest performance on the 6MW test 6 months after surgery. Individuals taking ≥17 s to complete the SCT and scoring <40 on the SF-36 mental component score before surgery had the poorest performance on the SCT 6 months after surgery. Poorer performance preoperatively on the 6MW, SCT, and TUG, was related to poorer performance in the same measure after TKA. Age and decreased mental health were secondary predictors of poorer performance at 6 months on the TUG and SCT, respectively. These measures may help further develop models predicting thresholds for poor outcomes after TKA.

  12. Predicting Poor Physical Performance after Total Knee Arthroplasty

    PubMed Central

    Bade, Michael J; Wolfe, Pamela; Zeni, Joseph A; Stevens-Lapsley, Jennifer E.; Snyder-Mackler, Lynn

    2012-01-01

    The purpose of this study was to develop a preliminary decision algorithm predicting functional performance outcomes to aid in the decision of when to undergo total knee arthroplasty (TKA). One hundred nineteen patients undergoing primary unilateral TKA were evaluated before and 6 months after TKA. A regression tree analysis using a recursive partitioning function was performed with the Timed Up and Go (TUG) time, Six-Minute Walk (6MW) distance, and Stair Climbing Test (SCT) time as measured 6 months after TKA as the primary outcomes. Preoperative measures of functional performance, joint performance, anthropometrics, demographics, and self reported status were evaluated as predictors of the primary outcomes 6 months after surgery. Individuals taking ≥ 10.1 seconds on the TUG and aged 72 years or older before surgery had the poorest performance on the TUG 6 months after surgery. Individuals walking < 314 meters on the 6MW before surgery had the poorest performance on the 6MW test 6 months after surgery. Individuals taking ≥ 17 seconds to complete the SCT and scoring < 40 on the SF-36 mental component score before surgery had the poorest performance on the SCT 6 months after surgery. Poorer performance preoperatively on the 6MW, SCT, and TUG, was related to poorer performance in the same measure after TKA. Age and decreased mental health were secondary predictors of poorer performance at 6 months on the TUG and SCT, respectively. These measures may help further develop models predicting thresholds for poor outcomes after TKA. PMID:22539338

  13. Prediction of muscle performance during dynamic repetitive movement

    NASA Technical Reports Server (NTRS)

    Byerly, D. L.; Byerly, K. A.; Sognier, M. A.; Squires, W. G.

    2003-01-01

    BACKGROUND: During long-duration spaceflight, astronauts experience progressive muscle atrophy and often perform strenuous extravehicular activities. Post-flight, there is a lengthy recovery period with an increased risk for injury. Currently, there is a critical need for an enabling tool to optimize muscle performance and to minimize the risk of injury to astronauts while on-orbit and during post-flight recovery. Consequently, these studies were performed to develop a method to address this need. METHODS: Eight test subjects performed a repetitive dynamic exercise to failure at 65% of their upper torso weight using a Lordex spinal machine. Surface electromyography (SEMG) data was collected from the erector spinae back muscle. The SEMG data was evaluated using a 5th order autoregressive (AR) model and linear regression analysis. RESULTS: The best predictor found was an AR parameter, the mean average magnitude of AR poles, with r = 0.75 and p = 0.03. This parameter can predict performance to failure as early as the second repetition of the exercise. CONCLUSION: A method for predicting human muscle performance early during dynamic repetitive exercise was developed. The capability to predict performance to failure has many potential applications to the space program including evaluating countermeasure effectiveness on-orbit, optimizing post-flight recovery, and potential future real-time monitoring capability during extravehicular activity.

  14. [The quality control based on the predictable performance].

    PubMed

    Zheng, D X

    2016-09-01

    The clinical performance can only be evaluated when it comes to the last step in the conventional way of prosthesis. However, it often causes the failure because of the unconformity between the expectation and final performance. Resulting from this kind of situation, quality control based on the predictable results has been suggested. It is a new idea based on the way of reverse thinking, and focuses on the need of patient and puts the final performance of the prosthesis to the first place. With the prosthodontically driven prodedure, dentists can complete the unification with the expectation and the final performance. PMID:27596338

  15. The Predictive Performance and Stability of Six Species Distribution Models

    PubMed Central

    Huang, Min-Yi; Fan, Wei-Yi; Wang, Zhi-Gao

    2014-01-01

    Background Predicting species’ potential geographical range by species distribution models (SDMs) is central to understand their ecological requirements. However, the effects of using different modeling techniques need further investigation. In order to improve the prediction effect, we need to assess the predictive performance and stability of different SDMs. Methodology We collected the distribution data of five common tree species (Pinus massoniana, Betula platyphylla, Quercus wutaishanica, Quercus mongolica and Quercus variabilis) and simulated their potential distribution area using 13 environmental variables and six widely used SDMs: BIOCLIM, DOMAIN, MAHAL, RF, MAXENT, and SVM. Each model run was repeated 100 times (trials). We compared the predictive performance by testing the consistency between observations and simulated distributions and assessed the stability by the standard deviation, coefficient of variation, and the 99% confidence interval of Kappa and AUC values. Results The mean values of AUC and Kappa from MAHAL, RF, MAXENT, and SVM trials were similar and significantly higher than those from BIOCLIM and DOMAIN trials (p<0.05), while the associated standard deviations and coefficients of variation were larger for BIOCLIM and DOMAIN trials (p<0.05), and the 99% confidence intervals for AUC and Kappa values were narrower for MAHAL, RF, MAXENT, and SVM. Compared to BIOCLIM and DOMAIN, other SDMs (MAHAL, RF, MAXENT, and SVM) had higher prediction accuracy, smaller confidence intervals, and were more stable and less affected by the random variable (randomly selected pseudo-absence points). Conclusions According to the prediction performance and stability of SDMs, we can divide these six SDMs into two categories: a high performance and stability group including MAHAL, RF, MAXENT, and SVM, and a low performance and stability group consisting of BIOCLIM, and DOMAIN. We highlight that choosing appropriate SDMs to address a specific problem is an important

  16. 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.

  17. Performance evaluation of ocean color satellite models for deriving accurate chlorophyll estimates in the Gulf of Saint Lawrence

    NASA Astrophysics Data System (ADS)

    Montes-Hugo, M.; Bouakba, H.; Arnone, R.

    2014-06-01

    The understanding of phytoplankton dynamics in the Gulf of the Saint Lawrence (GSL) is critical for managing major fisheries off the Canadian East coast. In this study, the accuracy of two atmospheric correction techniques (NASA standard algorithm, SA, and Kuchinke's spectral optimization, KU) and three ocean color inversion models (Carder's empirical for SeaWiFS (Sea-viewing Wide Field-of-View Sensor), EC, Lee's quasi-analytical, QAA, and Garver- Siegel-Maritorena semi-empirical, GSM) for estimating the phytoplankton absorption coefficient at 443 nm (aph(443)) and the chlorophyll concentration (chl) in the GSL is examined. Each model was validated based on SeaWiFS images and shipboard measurements obtained during May of 2000 and April 2001. In general, aph(443) estimates derived from coupling KU and QAA models presented the smallest differences with respect to in situ determinations as measured by High Pressure liquid Chromatography measurements (median absolute bias per cruise up to 0.005, RMSE up to 0.013). A change on the inversion approach used for estimating aph(443) values produced up to 43.4% increase on prediction error as inferred from the median relative bias per cruise. Likewise, the impact of applying different atmospheric correction schemes was secondary and represented an additive error of up to 24.3%. By using SeaDAS (SeaWiFS Data Analysis System) default values for the optical cross section of phytoplankton (i.e., aph(443) = aph(443)/chl = 0.056 m2mg-1), the median relative bias of our chl estimates as derived from the most accurate spaceborne aph(443) retrievals and with respect to in situ determinations increased up to 29%.

  18. Predictive Bias and Sensitivity in NRC Fuel Performance Codes

    SciTech Connect

    Geelhood, Kenneth J.; Luscher, Walter G.; Senor, David J.; Cunningham, Mitchel E.; Lanning, Donald D.; Adkins, Harold E.

    2009-10-01

    The latest versions of the fuel performance codes, FRAPCON-3 and FRAPTRAN were examined to determine if the codes are intrinsically conservative. Each individual model and type of code prediction was examined and compared to the data that was used to develop the model. In addition, a brief literature search was performed to determine if more recent data have become available since the original model development for model comparison.

  19. Application of regression and neural models to predict competitive swimming performance.

    PubMed

    Maszczyk, Adam; Roczniok, Robert; Waśkiewicz, Zbigniew; Czuba, Miłosz; Mikołajec, Kazimierz; Zajac, Adam; Stanula, Arkadiusz

    2012-04-01

    This research problem was indirectly but closely connected with the optimization of an athlete-selection process, based on predictions viewed as determinants of future successes. The research project involved a group of 249 competitive swimmers (age 12 yr., SD = 0.5) who trained and competed for four years. Measures involving fitness (e.g., lung capacity), strength (e.g., standing long jump), swimming technique (turn, glide, distance per stroke cycle), anthropometric variables (e.g., hand and foot size), as well as specific swimming measures (speeds in particular distances), were used. The participants (n = 189) trained from May 2008 to May 2009, which involved five days of swimming workouts per week, and three additional 45-min. sessions devoted to measurements necessary for this study. In June 2009, data from two groups of 30 swimmers each (n = 60) were used to identify predictor variables. Models were then constructed from these variables to predict final swimming performance in the 50 meter and 800 meter crawl events. Nonlinear regression models and neural models were built for the dependent variable of sport results (performance at 50m and 800m). In May 2010, the swimmers' actual race times for these events were compared to the predictions created a year prior to the beginning of the experiment. Results for the nonlinear regression models and perceptron networks structured as 8-4-1 and 4-3-1 indicated that the neural models overall more accurately predicted final swimming performance from initial training, strength, fitness, and body measurements. Differences in the sum of absolute error values were 4:11.96 (n = 30 for 800m) and 20.39 (n = 30 for 50m), for models structured as 8-4-1 and 4-3-1, respectively, with the neural models being more accurate. It seems possible that such models can be used to predict future performance, as well as in the process of recruiting athletes for specific styles and distances in swimming. PMID:22755464

  20. Performance prediction for 3D filtering of multichannel images

    NASA Astrophysics Data System (ADS)

    Rubel, Oleksii; Kozhemiakin, Ruslan A.; Abramov, Sergey K.; Lukin, Vladimir V.; Vozel, Benoit; Chehdi, Kacem

    2015-10-01

    Performance of denoising based on discrete cosine transform applied to multichannel remote sensing images corrupted by additive white Gaussian noise is analyzed. Images obtained by satellite Earth Observing-1 (EO-1) mission using hyperspectral imager instrument (Hyperion) that have high input SNR are taken as test images. Denoising performance is characterized by improvement of PSNR. For hard-thresholding 3D DCT-based denoising, simple statistics (probabilities to be less than a certain threshold) are used to predict denoising efficiency using curves fitted into scatterplots. It is shown that the obtained curves (approximations) provide prediction of denoising efficiency with high accuracy. Analysis is carried out for different numbers of channels processed jointly. Universality of prediction for different number of channels is proven.

  1. Predicting waste stabilization pond performance using an ecological simulation model

    SciTech Connect

    New, G.R.

    1987-01-01

    Waste stabilization ponds (lagoons) are often favored in small communities because of their low cost and ease of operation. Most models currently used to predict performance are empirical or fail to address the primary lagoon cell. Empirical methods for predicting lagoon performance have been found to be off as much as 248 percent when used on a system other than the one they were developed for. Also, the present models developed for the primary cell lack the ability to predict parameters other than biochemical oxygen demand (BOD) and nitrogen. Oxygen consumption is usually estimated from BOD utilization. LAGOON is a fortran program which models the biogeochemical processes characteristic of the primary cell of facultative lagoons. Model parameters can be measured from lagoons in the vicinity of a proposed lagoon or estimated from laboratory studies. The model was calibrated utilizing a subset of the Corinne Utah lagoon data then validated utilizing a subset of the Corinne Utah data.

  2. Internal performance predictions for Langley scramjet engine module

    NASA Technical Reports Server (NTRS)

    Pinckney, S. Z.

    1978-01-01

    A one dimensional theoretical method for the prediction of the internal performance of a scramjet engine is presented. The effects of changes in vehicle forebody flow parameters and characteristics on predicted thrust for the scramjet engine were evaluated using this method, and results are presented. A theoretical evaluation of the effects of changes in the scramjet engine's internal parameters is also presented. Theoretical internal performance predictions, in terms thrust coefficient and specific impulse, are provided for the scramjet engine for free stream Mach numbers of 5, 6, and 7 free stream dynamic pressure of 23,940 N/sq m forebody surface angles of 4.6 deg to 14.6 deg, and fuel equivalence ratio of 1.0.

  3. Performance and evaluation of the Viking lander camera performance prediction program

    NASA Technical Reports Server (NTRS)

    Huck, F. O.; Taylor, E. J.; Jobson, D. J.; Rowland, C. W.

    1975-01-01

    A computer program is described for predicting the performance of the Viking lander cameras. The predictions are primarily concerned with two objectives: (1) the picture quality of a reference test chart (of which there are three on each lander) to aid in diagnosing camera performance; and (2) the picture quality of cones with surface properties of a natural terrain to aid in predicting favorable illumination and viewing geometries and operational camera commands. Predictions made with this program are verified by experimental data obtained with a Viking-like laboratory facsimile camera.

  4. Gesture Performance in Schizophrenia Predicts Functional Outcome After 6 Months

    PubMed Central

    Walther, Sebastian; Eisenhardt, Sarah; Bohlhalter, Stephan; Vanbellingen, Tim; Müri, René; Strik, Werner; Stegmayer, Katharina

    2016-01-01

    The functional outcome of schizophrenia is heterogeneous and markers of the course are missing. Functional outcome is associated with social cognition and negative symptoms. Gesture performance and nonverbal social perception are critically impaired in schizophrenia. Here, we tested whether gesture performance or nonverbal social perception could predict functional outcome and the ability to adequately perform relevant skills of everyday function (functional capacity) after 6 months. In a naturalistic longitudinal study, 28 patients with schizophrenia completed tests of nonverbal communication at baseline and follow-up. In addition, functional outcome, social and occupational functioning, as well as functional capacity at follow-up were assessed. Gesture performance and nonverbal social perception at baseline predicted negative symptoms, functional outcome, and functional capacity at 6-month follow-up. Gesture performance predicted functional outcome beyond the baseline measure of functioning. Patients with gesture deficits at baseline had stable negative symptoms and experienced a decline in social functioning. While in patients without gesture deficits, negative symptom severity decreased and social functioning remained stable. Thus, a simple test of hand gesture performance at baseline may indicate favorable outcomes in short-term follow-up. The results further support the importance of nonverbal communication skills in subjects with schizophrenia. PMID:27566843

  5. Classification performance prediction using parametric scattering feature models

    NASA Astrophysics Data System (ADS)

    Chiang, Hung-Chih; Moses, Randolph L.; Potter, Lee C.

    2000-08-01

    We consider a method for estimating classification performance of a model-based synthetic aperture radar (SAR) automatic target recognition system. Target classification is performed by comparing an unordered feature set extracted from a measured SAR image chip with an unordered feature set predicted from a hypothesized target class and pose. A Bayes likelihood metric that incorporates uncertainty in both the predicted and extracted feature vectors is used to compute the match score. Evaluation of the match likelihoods requires a correspondence between the unordered predicted and extracted feature sets. This is a bipartite graph matching problem with insertions and deletions; we show that the optimal match can be found in polynomial time. We extend the results in 1 to estimate classification performance for a ten-class SAR ATR problem. We consider a synthetic classification problem to validate the classifier and to address resolution and robustness questions in the likelihood scoring method. Specifically, we consider performance versus SAR resolution, performance degradation due to mismatch between the assumed and actual feature statistics, and performance impact of correlated feature attributes.

  6. Numerical predictions of EML (electromagnetic launcher) system performance

    SciTech Connect

    Schnurr, N.M.; Kerrisk, J.F.; Davidson, R.F.

    1987-01-01

    The performance of an electromagnetic launcher (EML) depends on a large number of parameters, including the characteristics of the power supply, rail geometry, rail and insulator material properties, injection velocity, and projectile mass. EML system performance is frequently limited by structural or thermal effects in the launcher (railgun). A series of computer codes has been developed at the Los Alamos National Laboratory to predict EML system performance and to determine the structural and thermal constraints on barrel design. These codes include FLD, a two-dimensional electrostatic code used to calculate the high-frequency inductance gradient and surface current density distribution for the rails; TOPAZRG, a two-dimensional finite-element code that simultaneously analyzes thermal and electromagnetic diffusion in the rails; and LARGE, a code that predicts the performance of the entire EML system. Trhe NIKE2D code, developed at the Lawrence Livermore National Laboratory, is used to perform structural analyses of the rails. These codes have been instrumental in the design of the Lethality Test System (LTS) at Los Alamos, which has an ultimate goal of accelerating a 30-g projectile to a velocity of 15 km/s. The capabilities of the individual codes and the coupling of these codes to perform a comprehensive analysis is discussed in relation to the LTS design. Numerical predictions are compared with experimental data and presented for the LTS prototype tests.

  7. 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

  8. A model for analytical performance prediction of hypervapotron

    SciTech Connect

    Baxi, C.B.; Falter, H.

    1992-07-01

    A hypervapotron is a water-cooled device which combines the advantages of finned surfaces with the large heat transfer rates possible during boiling heat transfer. Hypervapotrons have been used as beam dumps in the past and plans are under way to use them for divertor cooling in the Joint European Torus (JET). Experiments at JET have shows that a surface heat flux of 25 MW/m{sup 2} can be achieved in hypervapotrons. This performance makes such a device very attractive for cooling of divertor of the International Thermonuclear Experimental Reactor (ITER). This paper presents an analytical method to predict the thermal performance of the hypervapotrons. Preliminary results show an excellent agreement between experimental results and analytical prediction over a wide range of flow velocities, pressures, subcooling temperatures and heat fluxes. This paper also presents the predicted performance of hypervapotron made of materials other than copper. After further development and verification, the analytical method could be used for optimizing designs and performance prediction.

  9. Image processing system performance prediction and product quality evaluation

    NASA Technical Reports Server (NTRS)

    Stein, E. K.; Hammill, H. B. (Principal Investigator)

    1976-01-01

    The author has identified the following significant results. A new technique for image processing system performance prediction and product quality evaluation was developed. It was entirely objective, quantitative, and general, and should prove useful in system design and quality control. The technique and its application to determination of quality control procedures for the Earth Resources Technology Satellite NASA Data Processing Facility are described.

  10. Process for predicting structural performance of mechanical systems

    DOEpatents

    Gardner, David R.; Hendrickson, Bruce A.; Plimpton, Steven J.; Attaway, Stephen W.; Heinstein, Martin W.; Vaughan, Courtenay T.

    1998-01-01

    A process for predicting the structural performance of a mechanical system represents the mechanical system by a plurality of surface elements. The surface elements are grouped according to their location in the volume occupied by the mechanical system so that contacts between surface elements can be efficiently located. The process is well suited for efficient practice on multiprocessor computers.

  11. Process for predicting structural performance of mechanical systems

    DOEpatents

    Gardner, D.R.; Hendrickson, B.A.; Plimpton, S.J.; Attaway, S.W.; Heinstein, M.W.; Vaughan, C.T.

    1998-05-19

    A process for predicting the structural performance of a mechanical system represents the mechanical system by a plurality of surface elements. The surface elements are grouped according to their location in the volume occupied by the mechanical system so that contacts between surface elements can be efficiently located. The process is well suited for efficient practice on multiprocessor computers. 12 figs.

  12. The Role of Means Efficacy When Predicting Creative Performance

    ERIC Educational Resources Information Center

    Simmons, Aneika L.; Payne, Stephanie C.; Pariyothorn, Matthew M.

    2014-01-01

    According to the "Internal-External Efficacy model", self-efficacy is an insufficient explanation for self-regulated behavior because it ignores the influence of external resources. Applying this theory of motivation to the prediction of creative performance, the extent to which means efficacy or the belief in the utility of external…

  13. Predicting School Performance with the Early Screening Inventory.

    ERIC Educational Resources Information Center

    Meisels, Samuel J.; And Others

    1984-01-01

    Proposes criteria for defining and selecting preschool developmental screening instruments and describes the Early Screening Inventory (ESI), a developmental screening instrument designed to satisfy these criteria. Presents results of several studies demonstrating that the ESI predicts school performance with moderate to excellent accuracy through…

  14. Analysis of Factors that Predict Clinical Performance in Medical School

    ERIC Educational Resources Information Center

    White, Casey B.; Dey, Eric L.; Fantone, Joseph C.

    2009-01-01

    Academic achievement indices including GPAs and MCAT scores are used to predict the spectrum of medical student academic performance types. However, use of these measures ignores two changes influencing medical school admissions: student diversity and affirmative action, and an increased focus on communication skills. To determine if GPA and MCAT…

  15. Prediction of Nine Month Performance from Neonatal and Developmental Criteria.

    ERIC Educational Resources Information Center

    Sweet, John F., Jr.; And Others

    This study investigated the ability of the Neonatal Behavioral Assessment Scale (NBAS), in combination with neonatal histories and developmental assessments, to predict mental and motor performance of 9-month-old infants on the Bayley Scales of Infant Development (BSID). Fourteen normal, full-term infants and 10 average-for-gestational-age,…

  16. Prediction and Quantification of Individual Athletic Performance of Runners

    PubMed Central

    2016-01-01

    We present a novel, quantitative view on the human athletic performance of individual runners. We obtain a predictor for running performance, a parsimonious model and a training state summary consisting of three numbers by application of modern validation techniques and recent advances in machine learning to the thepowerof10 database of British runners’ performances (164,746 individuals, 1,417,432 performances). Our predictor achieves an average prediction error (out-of-sample) of e.g. 3.6 min on elite Marathon performances and 0.3 seconds on 100 metres performances, and a lower error than the state-of-the-art in performance prediction (30% improvement, RMSE) over a range of distances. We are also the first to report on a systematic comparison of predictors for running performance. Our model has three parameters per runner, and three components which are the same for all runners. The first component of the model corresponds to a power law with exponent dependent on the runner which achieves a better goodness-of-fit than known power laws in the study of running. Many documented phenomena in quantitative sports science, such as the form of scoring tables, the success of existing prediction methods including Riegel’s formula, the Purdy points scheme, the power law for world records performances and the broken power law for world record speeds may be explained on the basis of our findings in a unified way. We provide strong evidence that the three parameters per runner are related to physiological and behavioural parameters, such as training state, event specialization and age, which allows us to derive novel physiological hypotheses relating to athletic performance. We conjecture on this basis that our findings will be vital in exercise physiology, race planning, the study of aging and training regime design. PMID:27336162

  17. Prediction and Quantification of Individual Athletic Performance of Runners.

    PubMed

    Blythe, Duncan A J; Király, Franz J

    2016-01-01

    We present a novel, quantitative view on the human athletic performance of individual runners. We obtain a predictor for running performance, a parsimonious model and a training state summary consisting of three numbers by application of modern validation techniques and recent advances in machine learning to the thepowerof10 database of British runners' performances (164,746 individuals, 1,417,432 performances). Our predictor achieves an average prediction error (out-of-sample) of e.g. 3.6 min on elite Marathon performances and 0.3 seconds on 100 metres performances, and a lower error than the state-of-the-art in performance prediction (30% improvement, RMSE) over a range of distances. We are also the first to report on a systematic comparison of predictors for running performance. Our model has three parameters per runner, and three components which are the same for all runners. The first component of the model corresponds to a power law with exponent dependent on the runner which achieves a better goodness-of-fit than known power laws in the study of running. Many documented phenomena in quantitative sports science, such as the form of scoring tables, the success of existing prediction methods including Riegel's formula, the Purdy points scheme, the power law for world records performances and the broken power law for world record speeds may be explained on the basis of our findings in a unified way. We provide strong evidence that the three parameters per runner are related to physiological and behavioural parameters, such as training state, event specialization and age, which allows us to derive novel physiological hypotheses relating to athletic performance. We conjecture on this basis that our findings will be vital in exercise physiology, race planning, the study of aging and training regime design. PMID:27336162

  18. 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

  19. Ultra-performance liquid chromatography/tandem mass spectrometry for accurate quantification of global DNA methylation in human sperms.

    PubMed

    Wang, Xiaoli; Suo, Yongshan; Yin, Ruichuan; Shen, Heqing; Wang, Hailin

    2011-06-01

    Aberrant DNA methylation in human sperms has been proposed to be a possible mechanism associated with male infertility. We developed an ultra-performance liquid chromatography/tandem mass spectrometry (UPLC-MS/MS) method for rapid, sensitive, and specific detection of global DNA methylation level in human sperms. Multiple-reaction monitoring (MRM) mode was used in MS/MS detection for accurate quantification of DNA methylation. The intra-day and inter-day precision values of this method were within 1.50-5.70%. By using 2-deoxyguanosine as an internal standard, UPLC-MS/MS method was applied for the detection of global DNA methylation levels in three cultured cell lines. DNA methyltransferases inhibitor 5-aza-2'-deoxycytidine can significantly reduce global DNA methylation levels in treated cell lines, showing the reliability of our method. We further examined global DNA methylation levels in human sperms, and found that global methylation values varied from 3.79% to 4.65%. The average global DNA methylation level of sperm samples washed only by PBS (4.03%) was relatively lower than that of sperm samples in which abnormal and dead sperm cells were removed by density gradient centrifugation (4.25%), indicating the possible aberrant DNA methylation level in abnormal sperm cells. Clinical application of UPLC-MS/MS method in global DNA methylation detection of human sperms will be useful in human sperm quality evaluation and the study of epigenetic mechanisms responsible for male infertility.

  20. Toward accurate molecular identification of species in complex environmental samples: testing the performance of sequence filtering and clustering methods

    PubMed Central

    Flynn, Jullien M; Brown, Emily A; Chain, Frédéric J J; MacIsaac, Hugh J; Cristescu, Melania E

    2015-01-01

    Metabarcoding has the potential to become a rapid, sensitive, and effective approach for identifying species in complex environmental samples. Accurate molecular identification of species depends on the ability to generate operational taxonomic units (OTUs) that correspond to biological species. Due to the sometimes enormous estimates of biodiversity using this method, there is a great need to test the efficacy of data analysis methods used to derive OTUs. Here, we evaluate the performance of various methods for clustering length variable 18S amplicons from complex samples into OTUs using a mock community and a natural community of zooplankton species. We compare analytic procedures consisting of a combination of (1) stringent and relaxed data filtering, (2) singleton sequences included and removed, (3) three commonly used clustering algorithms (mothur, UCLUST, and UPARSE), and (4) three methods of treating alignment gaps when calculating sequence divergence. Depending on the combination of methods used, the number of OTUs varied by nearly two orders of magnitude for the mock community (60–5068 OTUs) and three orders of magnitude for the natural community (22–22191 OTUs). The use of relaxed filtering and the inclusion of singletons greatly inflated OTU numbers without increasing the ability to recover species. Our results also suggest that the method used to treat gaps when calculating sequence divergence can have a great impact on the number of OTUs. Our findings are particularly relevant to studies that cover taxonomically diverse species and employ markers such as rRNA genes in which length variation is extensive. PMID:26078860

  1. Prediction of Warfarin Dose in Pediatric Patients: An Evaluation of the Predictive Performance of Several Models

    PubMed Central

    Marek, Elizabeth; Momper, Jeremiah D.; Hines, Ronald N.; Takao, Cheryl M.; Gill, Joan C.; Pravica, Vera; Gaedigk, Andrea; Neville, Kathleen A.

    2016-01-01

    OBJECTIVES: The objective of this study was to evaluate the performance of pediatric pharmacogenetic-based dose prediction models by using an independent cohort of pediatric patients from a multicenter trial. METHODS: Clinical and genetic data (CYP2C9 [cytochrome P450 2C9] and VKORC1 [vitamin K epoxide reductase]) were collected from pediatric patients aged 3 months to 17 years who were receiving warfarin as part of standard care at 3 separate clinical sites. The accuracy of 8 previously published pediatric pharmacogenetic-based dose models was evaluated in the validation cohort by comparing predicted maintenance doses to actual stable warfarin doses. The predictive ability was assessed by using the proportion of variance (R2), mean prediction error (MPE), and the percentage of predictions that fell within 20% of the actual maintenance dose. RESULTS: Thirty-two children reached a stable international normalized ratio and were included in the validation cohort. The pharmacogenetic-based warfarin dose models showed a proportion of variance ranging from 35% to 78% and an MPE ranging from −2.67 to 0.85 mg/day in the validation cohort. Overall, the model developed by Hamberg et al showed the best performance in the validation cohort (R2 = 78%; MPE = 0.15 mg/day) with 38% of the predictions falling within 20% of observed doses. CONCLUSIONS: Pharmacogenetic-based algorithms provide better predictions than a fixed-dose approach, although an optimal dose algorithm has not yet been developed. PMID:27453700

  2. Use of Boundary Layer Transition Detection to Validate Full-Scale Flight Performance Predictions

    NASA Technical Reports Server (NTRS)

    Hamner, Marvine; Owens, L. R., Jr.; Wahls, R. A.; Yeh, David

    1999-01-01

    Full-scale flight performance predictions can be made using CFD or a combination of CFD and analytical skin-friction predictions. However, no matter what method is used to obtain full-scale flight performance predictions knowledge of the boundary layer state is critical. The implementation of CFD codes solving the Navier-Stokes equations to obtain these predictions is still a time consuming, expensive process. In addition, to ultimately obtain accurate performance predictions the transition location must be fixed in the CFD model. An example, using the M2.4-7A geometry, of the change in Navier-Stokes solution with changes in transition and in turbulence model will be shown. Oil flow visualization using the M2.4-7A 4.0% scale model in the 14'x22' wind tunnel shows that fixing transition at 10% x/c in the CFD model best captures the flow physics of the wing flow field. A less costly method of obtaining full-scale performance predictions is the use of non-linear Euler codes or linear CFD codes, such as panel methods, combined with analytical skin-friction predictions. Again, knowledge of the boundary layer state is critical to the accurate determination of full-scale flight performance. Boundary layer transition detection has been performed at 0.3 and 0.9 Mach numbers over an extensive Reynolds number range using the 2.2% scale Reference H model in the NTF. A temperature sensitive paint system was used to determine the boundary layer state for these conditions. Data was obtained for three configurations: the baseline, undeflected flaps configuration; the transonic cruise configuration; and, the high-lift configuration. It was determined that at low Reynolds number conditions, in the 8 to 10 million Reynolds number range, the baseline configuration has extensive regions of laminar flow, in fact significantly more than analytical skin-friction methods predict. This configuration is fully turbulent at about 30 million Reynolds number for both 0.3 and 0.9, Mach numbers

  3. 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

  4. Task-free MRI predicts individual differences in brain activity during task performance.

    PubMed

    Tavor, I; Parker Jones, O; Mars, R B; Smith, S M; Behrens, T E; Jbabdi, S

    2016-04-01

    When asked to perform the same task, different individuals exhibit markedly different patterns of brain activity. This variability is often attributed to volatile factors, such as task strategy or compliance. We propose that individual differences in brain responses are, to a large degree, inherent to the brain and can be predicted from task-independent measurements collected at rest. Using a large set of task conditions, spanning several behavioral domains, we train a simple model that relates task-independent measurements to task activity and evaluate the model by predicting task activation maps for unseen subjects using magnetic resonance imaging. Our model can accurately predict individual differences in brain activity and highlights a coupling between brain connectivity and function that can be captured at the level of individual subjects. PMID:27124457

  5. Task-free MRI predicts individual differences in brain activity during task performance.

    PubMed

    Tavor, I; Parker Jones, O; Mars, R B; Smith, S M; Behrens, T E; Jbabdi, S

    2016-04-01

    When asked to perform the same task, different individuals exhibit markedly different patterns of brain activity. This variability is often attributed to volatile factors, such as task strategy or compliance. We propose that individual differences in brain responses are, to a large degree, inherent to the brain and can be predicted from task-independent measurements collected at rest. Using a large set of task conditions, spanning several behavioral domains, we train a simple model that relates task-independent measurements to task activity and evaluate the model by predicting task activation maps for unseen subjects using magnetic resonance imaging. Our model can accurately predict individual differences in brain activity and highlights a coupling between brain connectivity and function that can be captured at the level of individual subjects.

  6. 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).

  7. Entity versus incremental theories predict older adults' memory performance.

    PubMed

    Plaks, Jason E; Chasteen, Alison L

    2013-12-01

    The authors examined whether older adults' implicit theories regarding the modifiability of memory in particular (Studies 1 and 3) and abilities in general (Study 2) would predict memory performance. In Study 1, individual differences in older adults' endorsement of the "entity theory" (a belief that one's ability is fixed) or "incremental theory" (a belief that one's ability is malleable) of memory were measured using a version of the Implicit Theories Measure (Dweck, 1999). Memory performance was assessed with a free-recall task. Results indicated that the higher the endorsement of the incremental theory, the better the free recall. In Study 2, older and younger adults' theories were measured using a more general version of the Implicit Theories Measure that focused on the modifiability of abilities in general. Again, for older adults, the higher the incremental endorsement, the better the free recall. Moreover, as predicted, implicit theories did not predict younger adults' memory performance. In Study 3, participants read mock news articles reporting evidence in favor of either the entity or incremental theory. Those in the incremental condition outperformed those in the entity condition on reading span and free-recall tasks. These effects were mediated by pretask worry such that, for those in the entity condition, higher worry was associated with lower performance. Taken together, these studies suggest that variation in entity versus incremental endorsement represents a key predictor of older adults' memory performance. PMID:24128076

  8. Entity versus incremental theories predict older adults' memory performance.

    PubMed

    Plaks, Jason E; Chasteen, Alison L

    2013-12-01

    The authors examined whether older adults' implicit theories regarding the modifiability of memory in particular (Studies 1 and 3) and abilities in general (Study 2) would predict memory performance. In Study 1, individual differences in older adults' endorsement of the "entity theory" (a belief that one's ability is fixed) or "incremental theory" (a belief that one's ability is malleable) of memory were measured using a version of the Implicit Theories Measure (Dweck, 1999). Memory performance was assessed with a free-recall task. Results indicated that the higher the endorsement of the incremental theory, the better the free recall. In Study 2, older and younger adults' theories were measured using a more general version of the Implicit Theories Measure that focused on the modifiability of abilities in general. Again, for older adults, the higher the incremental endorsement, the better the free recall. Moreover, as predicted, implicit theories did not predict younger adults' memory performance. In Study 3, participants read mock news articles reporting evidence in favor of either the entity or incremental theory. Those in the incremental condition outperformed those in the entity condition on reading span and free-recall tasks. These effects were mediated by pretask worry such that, for those in the entity condition, higher worry was associated with lower performance. Taken together, these studies suggest that variation in entity versus incremental endorsement represents a key predictor of older adults' memory performance.

  9. High-speed running performance: a new approach to assessment and prediction.

    PubMed

    Bundle, Matthew W; Hoyt, Reed W; Weyand, Peter G

    2003-11-01

    We hypothesized that all-out running speeds for efforts lasting from a few seconds to several minutes could be accurately predicted from two measurements: the maximum respective speeds supported by the anaerobic and aerobic powers of the runner. To evaluate our hypothesis, we recruited seven competitive runners of different event specialties and tested them during treadmill and overground running on level surfaces. The maximum speed supported by anaerobic power was determined from the fastest speed that subjects could attain for a burst of eight steps (approximately 3 s or less). The maximum speed supported by aerobic power, or the velocity at maximal oxygen uptake, was determined from a progressive, discontinuous treadmill test to failure. All-out running speeds for trials of 3-240 s were measured during 10-13 constant-speed treadmill runs to failure and 4 track runs at specified distances. Measured values of the maximum speeds supported by anaerobic and aerobic power, in conjunction with an exponential constant, allowed us to predict the speeds of all-out treadmill trials to within an average of 2.5% (R2 = 0.94; n = 84) and track trials to within 3.4% (R2 = 0.86; n = 28). An algorithm using this exponent and only two of the all-out treadmill runs to predict the remaining treadmill trials was nearly as accurate (average = 3.7%; R2 = 0.93; n = 77). We conclude that our technique 1) provides accurate predictions of high-speed running performance in trained runners and 2) offers a performance assessment alternative to existing tests of anaerobic power and capacity.

  10. Immune biomarkers are more accurate in prediction of survival in ulcerated than in non-ulcerated primary melanomas

    PubMed Central

    de Moll, Ellen H.; Fu, Yichun; Qian, Yingzhi; Perkins, Sara H.; Wieder, Shira; Gnjatic, Sacha; Remark, Romain; Bernardo, Sebastian G.; Moskalenko, Marina; Yao, Jonathan; Ferringer, Tammie; Chang, Rui; Chipuk, Jerry; Horst, Basil A.; Birge, Miriam B.; Phelps, Robert G.

    2015-01-01

    Introduction Ulcerated melanomas may have a unique biology and microenvironment. We test whether markers of immune infiltration correlate with clinical outcome in ulcerated compared to non-ulcerated primary melanoma tumors. Methods Sixty-two stage II–III cutaneous melanomas, 32 ulcerated and 30 non-ulcerated, were analyzed for tumor-infiltrating lymphocytes (TILs). Immunohistochemistry (IHC) was performed for CD2, a marker previously shown to correlate with overall survival (OS) and recurrence-free survival (RFS) in this patient population. IHC using antibody, VE1, to BRAF V600E was also performed on a subset of 41 tumors to assess the relationship of BRAF mutation to immune markers. Results We found, using Cox regression models, that the presence of TILs was associated with improved OS (p = 0.034) and RFS (p = 0.002) in ulcerated melanoma tumors, but not in non-ulcerated melanoma (p = 0.632, 0.416). CD2 expression also was correlated with improved OS (p = 0.021) and RFS (p = 0.001) in ulcerated melanoma, but no relationship was seen in non-ulcerated melanoma (p = 0.427, 0.682). In this small population, BRAF status did not correlate with TILs or CD2+ count. Conclusion Our data show that immune markers including TILs and CD2 count correlate more closely with survival in ulcerated melanomas than that in non-ulcerated melanomas. We propose that immune biomarkers may be particularly relevant to ulcerated, as compared to non-ulcerated, melanomas and that this merits study in larger populations. PMID:26076664

  11. 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

  12. Performance predictions for an SSME configuration with an enlarged throat

    NASA Technical Reports Server (NTRS)

    Nickerson, G. R.; Dang, L. D.

    1985-01-01

    The Two Dimensional Kinetics (TDK) computer program that was recently developed for NASA was used to predict the performance of a Large Throat Configuration of the Space Shuttle Main Engine (SSME). Calculations indicate that the current design SSME contains a shock wave that is induced by the nozzle wall shape. In the Large Throat design an even stronger shock wave is predicted. Because of the presence of this shock wave, earlier performance predictions that have neglected shock wave effects have been questioned. The JANNAF thrust chamber performance prediction procedures given in a reference were applied. The analysis includes the effects of two dimensional reacting flow with a shock wave. The effects of the boundary layer with a regenatively cooled wall are also included. A Purdue computer program was used to compute axially symmetric supersonic nozzle flows with an induced shock, but is restricted to flows with a constant ratio of specific heats. Thus, the TDK program was also run with ths assumption and the results of the two programs were compared.

  13. Long‐Term Post‐CABG Survival: Performance of Clinical Risk Models Versus Actuarial Predictions

    PubMed Central

    Carr, Brendan M.; Romeiser, Jamie; Ruan, Joyce; Gupta, Sandeep; Seifert, Frank C.; Zhu, Wei

    2015-01-01

    Abstract Background/aim Clinical risk models are commonly used to predict short‐term coronary artery bypass grafting (CABG) mortality but are less commonly used to predict long‐term mortality. The added value of long‐term mortality clinical risk models over traditional actuarial models has not been evaluated. To address this, the predictive performance of a long‐term clinical risk model was compared with that of an actuarial model to identify the clinical variable(s) most responsible for any differences observed. Methods Long‐term mortality for 1028 CABG patients was estimated using the Hannan New York State clinical risk model and an actuarial model (based on age, gender, and race/ethnicity). Vital status was assessed using the Social Security Death Index. Observed/expected (O/E) ratios were calculated, and the models' predictive performances were compared using a nested c‐index approach. Linear regression analyses identified the subgroup of risk factors driving the differences observed. Results Mortality rates were 3%, 9%, and 17% at one‐, three‐, and five years, respectively (median follow‐up: five years). The clinical risk model provided more accurate predictions. Greater divergence between model estimates occurred with increasing long‐term mortality risk, with baseline renal dysfunction identified as a particularly important driver of these differences. Conclusions Long‐term mortality clinical risk models provide enhanced predictive power compared to actuarial models. Using the Hannan risk model, a patient's long‐term mortality risk can be accurately assessed and subgroups of higher‐risk patients can be identified for enhanced follow‐up care. More research appears warranted to refine long‐term CABG clinical risk models. doi: 10.1111/jocs.12665 (J Card Surg 2016;31:23–30) PMID:26543019

  14. A comparison of SAR ATR performance with information theoretic predictions

    NASA Astrophysics Data System (ADS)

    Blacknell, David

    2003-09-01

    Performance assessment of automatic target detection and recognition algorithms for SAR systems (or indeed any other sensors) is essential if the military utility of the system / algorithm mix is to be quantified. This is a relatively straightforward task if extensive trials data from an existing system is used. However, a crucial requirement is to assess the potential performance of novel systems as a guide to procurement decisions. This task is no longer straightforward since a hypothetical system cannot provide experimental trials data. QinetiQ has previously developed a theoretical technique for classification algorithm performance assessment based on information theory. The purpose of the study presented here has been to validate this approach. To this end, experimental SAR imagery of targets has been collected using the QinetiQ Enhanced Surveillance Radar to allow algorithm performance assessments as a number of parameters are varied. In particular, performance comparisons can be made for (i) resolutions up to 0.1m, (ii) single channel versus polarimetric (iii) targets in the open versus targets in scrubland and (iv) use versus non-use of camouflage. The change in performance as these parameters are varied has been quantified from the experimental imagery whilst the information theoretic approach has been used to predict the expected variation of performance with parameter value. A comparison of these measured and predicted assessments has revealed the strengths and weaknesses of the theoretical technique as will be discussed in the paper.

  15. Prediction of Gas Lubricated Foil Journal Bearing Performance

    NASA Technical Reports Server (NTRS)

    Carpino, Marc; Talmage, Gita

    2003-01-01

    This report summarizes the progress in the first eight months of the project. The objectives of this research project are to theoretically predict the steady operating conditions and the rotor dynamic coefficients of gas foil journal bearings. The project is currently on or ahead of schedule with the development of a finite element code that predicts steady bearing performance characteristics such as film thickness, pressure, load, and drag. Graphical results for a typical bearing are presented in the report. Project plans for the next year are discussed.

  16. Predictive Measures of Locomotor Performance on an Unstable Walking Surface

    NASA Technical Reports Server (NTRS)

    Bloomberg, J. J.; Peters, B. T.; Mulavara, A. P.; Caldwell, E. E.; Batson, C. D.; De Dios, Y. E.; Gadd, N. E.; Goel, R.; Wood, S. J.; Cohen, H. S.; Oddsson, L. I.; Seidler, R. D.

    2016-01-01

    Locomotion requires integration of visual, vestibular, and somatosensory information to produce the appropriate motor output to control movement. The degree to which these sensory inputs are weighted and reorganized in discordant sensory environments varies by individual and may be predictive of the ability to adapt to novel environments. The goals of this project are to: 1) develop a set of predictive measures capable of identifying individual differences in sensorimotor adaptability, and 2) use this information to inform the design of training countermeasures designed to enhance the ability of astronauts to adapt to gravitational transitions improving balance and locomotor performance after a Mars landing and enhancing egress capability after a landing on Earth.

  17. Navier-Stokes and Comprehensive Analysis Performance Predictions of the NREL Phase VI Experiment

    NASA Technical Reports Server (NTRS)

    Duque, Earl P. N.; Burklund, Michael D.; Johnson, Wayne

    2003-01-01

    A vortex lattice code, CAMRAD II, and a Reynolds-Averaged Navier-Stoke code, OVERFLOW-D2, were used to predict the aerodynamic performance of a two-bladed horizontal axis wind turbine. All computations were compared with experimental data that was collected at the NASA Ames Research Center 80- by 120-Foot Wind Tunnel. Computations were performed for both axial as well as yawed operating conditions. Various stall delay models and dynamics stall models were used by the CAMRAD II code. Comparisons between the experimental data and computed aerodynamic loads show that the OVERFLOW-D2 code can accurately predict the power and spanwise loading of a wind turbine rotor.

  18. 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.

  19. Improved Helicopter Rotor Performance Prediction through Loose and Tight CFD/CSD Coupling

    NASA Astrophysics Data System (ADS)

    Ickes, Jacob C.

    Helicopters and other Vertical Take-Off or Landing (VTOL) vehicles exhibit an interesting combination of structural dynamic and aerodynamic phenomena which together drive the rotor performance. The combination of factors involved make simulating the rotor a challenging and multidisciplinary effort, and one which is still an active area of interest in the industry because of the money and time it could save during design. Modern tools allow the prediction of rotorcraft physics from first principles. Analysis of the rotor system with this level of accuracy provides the understanding necessary to improve its performance. There has historically been a divide between the comprehensive codes which perform aeroelastic rotor simulations using simplified aerodynamic models, and the very computationally intensive Navier-Stokes Computational Fluid Dynamics (CFD) solvers. As computer resources become more available, efforts have been made to replace the simplified aerodynamics of the comprehensive codes with the more accurate results from a CFD code. The objective of this work is to perform aeroelastic rotorcraft analysis using first-principles simulations for both fluids and structural predictions using tools available at the University of Toledo. Two separate codes are coupled together in both loose coupling (data exchange on a periodic interval) and tight coupling (data exchange each time step) schemes. To allow the coupling to be carried out in a reliable and efficient way, a Fluid-Structure Interaction code was developed which automatically performs primary functions of loose and tight coupling procedures. Flow phenomena such as transonics, dynamic stall, locally reversed flow on a blade, and Blade-Vortex Interaction (BVI) were simulated in this work. Results of the analysis show aerodynamic load improvement due to the inclusion of the CFD-based airloads in the structural dynamics analysis of the Computational Structural Dynamics (CSD) code. Improvements came in the form

  20. Temporal prediction errors modulate task-switching performance.

    PubMed

    Limongi, Roberto; Silva, Angélica M; Góngora-Costa, Begoña

    2015-01-01

    We have previously shown that temporal prediction errors (PEs, the differences between the expected and the actual stimulus' onset times) modulate the effective connectivity between the anterior cingulate cortex and the right anterior insular cortex (rAI), causing the activity of the rAI to decrease. The activity of the rAI is associated with efficient performance under uncertainty (e.g., changing a prepared behavior when a change demand is not expected), which leads to hypothesize that temporal PEs might disrupt behavior-change performance under uncertainty. This hypothesis has not been tested at a behavioral level. In this work, we evaluated this hypothesis within the context of task switching and concurrent temporal predictions. Our participants performed temporal predictions while observing one moving ball striking a stationary ball which bounced off with a variable temporal gap. Simultaneously, they performed a simple color comparison task. In some trials, a change signal made the participants change their behaviors. Performance accuracy decreased as a function of both the temporal PE and the delay. Explaining these results without appealing to ad hoc concepts such as "executive control" is a challenge for cognitive neuroscience. We provide a predictive coding explanation. We hypothesize that exteroceptive and proprioceptive minimization of PEs would converge in a fronto-basal ganglia network which would include the rAI. Both temporal gaps (or uncertainty) and temporal PEs would drive and modulate this network respectively. Whereas the temporal gaps would drive the activity of the rAI, the temporal PEs would modulate the endogenous excitatory connections of the fronto-striatal network. We conclude that in the context of perceptual uncertainty, the system is not able to minimize perceptual PE, causing the ongoing behavior to finalize and, in consequence, disrupting task switching. PMID:26379568

  1. Temporal prediction errors modulate task-switching performance

    PubMed Central

    Limongi, Roberto; Silva, Angélica M.; Góngora-Costa, Begoña

    2015-01-01

    We have previously shown that temporal prediction errors (PEs, the differences between the expected and the actual stimulus’ onset times) modulate the effective connectivity between the anterior cingulate cortex and the right anterior insular cortex (rAI), causing the activity of the rAI to decrease. The activity of the rAI is associated with efficient performance under uncertainty (e.g., changing a prepared behavior when a change demand is not expected), which leads to hypothesize that temporal PEs might disrupt behavior-change performance under uncertainty. This hypothesis has not been tested at a behavioral level. In this work, we evaluated this hypothesis within the context of task switching and concurrent temporal predictions. Our participants performed temporal predictions while observing one moving ball striking a stationary ball which bounced off with a variable temporal gap. Simultaneously, they performed a simple color comparison task. In some trials, a change signal made the participants change their behaviors. Performance accuracy decreased as a function of both the temporal PE and the delay. Explaining these results without appealing to ad hoc concepts such as “executive control” is a challenge for cognitive neuroscience. We provide a predictive coding explanation. We hypothesize that exteroceptive and proprioceptive minimization of PEs would converge in a fronto-basal ganglia network which would include the rAI. Both temporal gaps (or uncertainty) and temporal PEs would drive and modulate this network respectively. Whereas the temporal gaps would drive the activity of the rAI, the temporal PEs would modulate the endogenous excitatory connections of the fronto-striatal network. We conclude that in the context of perceptual uncertainty, the system is not able to minimize perceptual PE, causing the ongoing behavior to finalize and, in consequence, disrupting task switching. PMID:26379568

  2. Temporal prediction errors modulate task-switching performance.

    PubMed

    Limongi, Roberto; Silva, Angélica M; Góngora-Costa, Begoña

    2015-01-01

    We have previously shown that temporal prediction errors (PEs, the differences between the expected and the actual stimulus' onset times) modulate the effective connectivity between the anterior cingulate cortex and the right anterior insular cortex (rAI), causing the activity of the rAI to decrease. The activity of the rAI is associated with efficient performance under uncertainty (e.g., changing a prepared behavior when a change demand is not expected), which leads to hypothesize that temporal PEs might disrupt behavior-change performance under uncertainty. This hypothesis has not been tested at a behavioral level. In this work, we evaluated this hypothesis within the context of task switching and concurrent temporal predictions. Our participants performed temporal predictions while observing one moving ball striking a stationary ball which bounced off with a variable temporal gap. Simultaneously, they performed a simple color comparison task. In some trials, a change signal made the participants change their behaviors. Performance accuracy decreased as a function of both the temporal PE and the delay. Explaining these results without appealing to ad hoc concepts such as "executive control" is a challenge for cognitive neuroscience. We provide a predictive coding explanation. We hypothesize that exteroceptive and proprioceptive minimization of PEs would converge in a fronto-basal ganglia network which would include the rAI. Both temporal gaps (or uncertainty) and temporal PEs would drive and modulate this network respectively. Whereas the temporal gaps would drive the activity of the rAI, the temporal PEs would modulate the endogenous excitatory connections of the fronto-striatal network. We conclude that in the context of perceptual uncertainty, the system is not able to minimize perceptual PE, causing the ongoing behavior to finalize and, in consequence, disrupting task switching.

  3. Prediction and performance of radome-covered reflector antennas

    NASA Astrophysics Data System (ADS)

    Clarricoats, P. J. B.; Parini, C. G.; Rizk, M. S. A. S.

    1981-11-01

    The return loss (reflection coefficient) of a paraboloidal reflector antenna covered by a paraboloidal radome is predicted using a physical-optics method based on the power-coupling theorem. An asymptotic form of the expression is found to be a good approximation. The performance of the antenna has been measured and results are in good agreement with those predicted theoretically. A method for reducing the return loss is investigated using a hemispherical iris-loaded sandwich section at the center of the radome. An improvement in return loss of approximately 5 dB is observed over a useful frequency bandwidth. Contributions of the radome to the radiation pattern of the antenna have been identified and those near to boresight have been predicted. Computed values in that region agree well with measurements.

  4. Roadmap Toward a Predictive Performance-based Commercial Energy Code

    SciTech Connect

    Rosenberg, Michael I.; Hart, Philip R.

    2014-10-01

    Energy codes have provided significant increases in building efficiency over the last 38 years, since the first national energy model code was published in late 1975. The most commonly used path in energy codes, the prescriptive path, appears to be reaching a point of diminishing returns. The current focus on prescriptive codes has limitations including significant variation in actual energy performance depending on which prescriptive options are chosen, a lack of flexibility for designers and developers, and the inability to handle control optimization that is specific to building type and use. This paper provides a high level review of different options for energy codes, including prescriptive, prescriptive packages, EUI Target, outcome-based, and predictive performance approaches. This paper also explores a next generation commercial energy code approach that places a greater emphasis on performance-based criteria. A vision is outlined to serve as a roadmap for future commercial code development. That vision is based on code development being led by a specific approach to predictive energy performance combined with building specific prescriptive packages that are designed to be both cost-effective and to achieve a desired level of performance. Compliance with this new approach can be achieved by either meeting the performance target as demonstrated by whole building energy modeling, or by choosing one of the prescriptive packages.

  5. 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

  6. Genomic Prediction of Testcross Performance in Canola (Brassica napus).

    PubMed

    Jan, Habib U; Abbadi, Amine; Lücke, Sophie; Nichols, Richard A; Snowdon, Rod J

    2016-01-01

    Genomic selection (GS) is a modern breeding approach where genome-wide single-nucleotide polymorphism (SNP) marker profiles are simultaneously used to estimate performance of untested genotypes. In this study, the potential of genomic selection methods to predict testcross performance for hybrid canola breeding was applied for various agronomic traits based on genome-wide marker profiles. A total of 475 genetically diverse spring-type canola pollinator lines were genotyped at 24,403 single-copy, genome-wide SNP loci. In parallel, the 950 F1 testcross combinations between the pollinators and two representative testers were evaluated for a number of important agronomic traits including seedling emergence, days to flowering, lodging, oil yield and seed yield along with essential seed quality characters including seed oil content and seed glucosinolate content. A ridge-regression best linear unbiased prediction (RR-BLUP) model was applied in combination with 500 cross-validations for each trait to predict testcross performance, both across the whole population as well as within individual subpopulations or clusters, based solely on SNP profiles. Subpopulations were determined using multidimensional scaling and K-means clustering. Genomic prediction accuracy across the whole population was highest for seed oil content (0.81) followed by oil yield (0.75) and lowest for seedling emergence (0.29). For seed yieId, seed glucosinolate, lodging resistance and days to onset of flowering (DTF), prediction accuracies were 0.45, 0.61, 0.39 and 0.56, respectively. Prediction accuracies could be increased for some traits by treating subpopulations separately; a strategy which only led to moderate improvements for some traits with low heritability, like seedling emergence. No useful or consistent increase in accuracy was obtained by inclusion of a population substructure covariate in the model. Testcross performance prediction using genome-wide SNP markers shows considerable

  7. Genomic Prediction of Testcross Performance in Canola (Brassica napus)

    PubMed Central

    Jan, Habib U.; Abbadi, Amine; Lücke, Sophie; Nichols, Richard A.; Snowdon, Rod J.

    2016-01-01

    Genomic selection (GS) is a modern breeding approach where genome-wide single-nucleotide polymorphism (SNP) marker profiles are simultaneously used to estimate performance of untested genotypes. In this study, the potential of genomic selection methods to predict testcross performance for hybrid canola breeding was applied for various agronomic traits based on genome-wide marker profiles. A total of 475 genetically diverse spring-type canola pollinator lines were genotyped at 24,403 single-copy, genome-wide SNP loci. In parallel, the 950 F1 testcross combinations between the pollinators and two representative testers were evaluated for a number of important agronomic traits including seedling emergence, days to flowering, lodging, oil yield and seed yield along with essential seed quality characters including seed oil content and seed glucosinolate content. A ridge-regression best linear unbiased prediction (RR-BLUP) model was applied in combination with 500 cross-validations for each trait to predict testcross performance, both across the whole population as well as within individual subpopulations or clusters, based solely on SNP profiles. Subpopulations were determined using multidimensional scaling and K-means clustering. Genomic prediction accuracy across the whole population was highest for seed oil content (0.81) followed by oil yield (0.75) and lowest for seedling emergence (0.29). For seed yieId, seed glucosinolate, lodging resistance and days to onset of flowering (DTF), prediction accuracies were 0.45, 0.61, 0.39 and 0.56, respectively. Prediction accuracies could be increased for some traits by treating subpopulations separately; a strategy which only led to moderate improvements for some traits with low heritability, like seedling emergence. No useful or consistent increase in accuracy was obtained by inclusion of a population substructure covariate in the model. Testcross performance prediction using genome-wide SNP markers shows considerable

  8. Contextual predictability enhances reading performance in patients with schizophrenia.

    PubMed

    Fernández, Gerardo; Guinjoan, Salvador; Sapognikoff, Marcelo; Orozco, David; Agamennoni, Osvaldo

    2016-07-30

    In the present work we analyzed fixation duration in 40 healthy individuals and 18 patients with chronic, stable SZ during reading of regular sentences and proverbs. While they read, their eye movements were recorded. We used lineal mixed models to analyze fixation durations. The predictability of words N-1, N, and N+1 exerted a strong influence on controls and SZ patients. The influence of the predictabilities of preceding, current, and upcoming words on SZ was clearly reduced for proverbs in comparison to regular sentences. Both controls and SZ readers were able to use highly predictable fixated words for an easier reading. Our results suggest that SZ readers might compensate attentional and working memory deficiencies by using stored information of familiar texts for enhancing their reading performance. The predictabilities of words in proverbs serve as task-appropriate cues that are used by SZ readers. To the best of our knowledge, this is the first study using eyetracking for measuring how patients with SZ process well-defined words embedded in regular sentences and proverbs. Evaluation of the resulting changes in fixation durations might provide a useful tool for understanding how SZ patients could enhance their reading performance. PMID:27236087

  9. The Development and Prediction of Athletic Performance in Freestyle Swimming

    PubMed Central

    Stanula, Arkadiusz; Maszczyk, Adam; Roczniok, Robert; Pietraszewski, Przemysław; Ostrowski, Andrzej; Zając, Adam; Strzała, Marek

    2012-01-01

    This paper analyses the dynamics of changes between the performances of elite freestyle swimmers recorded at particular Olympic Games. It also uses a set of chronologically ordered results to predict probable times of swimmers at the 2012 Olympic Games in London. The analysis of past performances of freestyle swimmers and their prediction have revealed a number of interesting tendencies within separately examined results of men and women. Women’s results improve more dynamically compared with men’s. Moreover, the difference between women’s and men’s results is smaller, the longer the swimming distance. As both male and female athletes tend to compete more and more vigorously within their groups, the gap between the gold medallist and the last finisher in the final is constantly decreasing, which provides significant evidence that this sport discipline continues to develop. PMID:23486223

  10. The ensemble performance index: an improved measure for assessing ensemble pose prediction performance.

    PubMed

    Korb, Oliver; McCabe, Patrick; Cole, Jason

    2011-11-28

    We present a theoretical study on the performance of ensemble docking methodologies considering multiple protein structures. We perform a theoretical analysis of pose prediction experiments which is completely unbiased, as we make no assumptions about specific scoring functions, search paradigms, protein structures, or ligand data sets. We introduce a novel interpretable measure, the ensemble performance index (EPI), for the assessment of scoring performance in ensemble docking, which will be applied to simulated and real data sets. PMID:21962010

  11. Performance predictions for the Keck telescope adaptive optics system

    SciTech Connect

    Gavel, D.T.; Olivier, S.S.

    1995-08-07

    The second Keck ten meter telescope (Keck-11) is slated to have an infrared-optimized adaptive optics system in the 1997--1998 time frame. This system will provide diffraction-limited images in the 1--3 micron region and the ability to use a diffraction-limited spectroscopy slit. The AO system is currently in the preliminary design phase and considerable analysis has been performed in order to predict its performance under various seeing conditions. In particular we have investigated the point-spread function, energy through a spectroscopy slit, crowded field contrast, object limiting magnitude, field of view, and sky coverage with natural and laser guide stars.

  12. MiRduplexSVM: A High-Performing MiRNA-Duplex Prediction and Evaluation Methodology.

    PubMed

    Karathanasis, Nestoras; Tsamardinos, Ioannis; Poirazi, Panayiota

    2015-01-01

    We address the problem of predicting the position of a miRNA duplex on a microRNA hairpin via the development and application of a novel SVM-based methodology. Our method combines a unique problem representation and an unbiased optimization protocol to learn from mirBase19.0 an accurate predictive model, termed MiRduplexSVM. This is the first model that provides precise information about all four ends of the miRNA duplex. We show that (a) our method outperforms four state-of-the-art tools, namely MaturePred, MiRPara, MatureBayes, MiRdup as well as a Simple Geometric Locator when applied on the same training datasets employed for each tool and evaluated on a common blind test set. (b) In all comparisons, MiRduplexSVM shows superior performance, achieving up to a 60% increase in prediction accuracy for mammalian hairpins and can generalize very well on plant hairpins, without any special optimization. (c) The tool has a number of important applications such as the ability to accurately predict the miRNA or the miRNA*, given the opposite strand of a duplex. Its performance on this task is superior to the 2nts overhang rule commonly used in computational studies and similar to that of a comparative genomic approach, without the need for prior knowledge or the complexity of performing multiple alignments. Finally, it is able to evaluate novel, potential miRNAs found either computationally or experimentally. In relation with recent confidence evaluation methods used in miRBase, MiRduplexSVM was successful in identifying high confidence potential miRNAs.

  13. MiRduplexSVM: A High-Performing MiRNA-Duplex Prediction and Evaluation Methodology.

    PubMed

    Karathanasis, Nestoras; Tsamardinos, Ioannis; Poirazi, Panayiota

    2015-01-01

    We address the problem of predicting the position of a miRNA duplex on a microRNA hairpin via the development and application of a novel SVM-based methodology. Our method combines a unique problem representation and an unbiased optimization protocol to learn from mirBase19.0 an accurate predictive model, termed MiRduplexSVM. This is the first model that provides precise information about all four ends of the miRNA duplex. We show that (a) our method outperforms four state-of-the-art tools, namely MaturePred, MiRPara, MatureBayes, MiRdup as well as a Simple Geometric Locator when applied on the same training datasets employed for each tool and evaluated on a common blind test set. (b) In all comparisons, MiRduplexSVM shows superior performance, achieving up to a 60% increase in prediction accuracy for mammalian hairpins and can generalize very well on plant hairpins, without any special optimization. (c) The tool has a number of important applications such as the ability to accurately predict the miRNA or the miRNA*, given the opposite strand of a duplex. Its performance on this task is superior to the 2nts overhang rule commonly used in computational studies and similar to that of a comparative genomic approach, without the need for prior knowledge or the complexity of performing multiple alignments. Finally, it is able to evaluate novel, potential miRNAs found either computationally or experimentally. In relation with recent confidence evaluation methods used in miRBase, MiRduplexSVM was successful in identifying high confidence potential miRNAs. PMID:25961860

  14. Predicting BCI subject performance using probabilistic spatio-temporal filters.

    PubMed

    Suk, Heung-Il; Fazli, Siamac; Mehnert, Jan; Müller, Klaus-Robert; Lee, Seong-Whan

    2014-01-01

    Recently, spatio-temporal filtering to enhance decoding for Brain-Computer-Interfacing (BCI) has become increasingly popular. In this work, we discuss a novel, fully Bayesian-and thereby probabilistic-framework, called Bayesian Spatio-Spectral Filter Optimization (BSSFO) and apply it to a large data set of 80 non-invasive EEG-based BCI experiments. Across the full frequency range, the BSSFO framework allows to analyze which spatio-spectral parameters are common and which ones differ across the subject population. As expected, large variability of brain rhythms is observed between subjects. We have clustered subjects according to similarities in their corresponding spectral characteristics from the BSSFO model, which is found to reflect their BCI performances well. In BCI, a considerable percentage of subjects is unable to use a BCI for communication, due to their missing ability to modulate their brain rhythms-a phenomenon sometimes denoted as BCI-illiteracy or inability. Predicting individual subjects' performance preceding the actual, time-consuming BCI-experiment enhances the usage of BCIs, e.g., by detecting users with BCI inability. This work additionally contributes by using the novel BSSFO method to predict the BCI-performance using only 2 minutes and 3 channels of resting-state EEG data recorded before the actual BCI-experiment. Specifically, by grouping the individual frequency characteristics we have nicely classified them into the subject 'prototypes' (like μ - or β -rhythm type subjects) or users without ability to communicate with a BCI, and then by further building a linear regression model based on the grouping we could predict subjects' performance with the maximum correlation coefficient of 0.581 with the performance later seen in the actual BCI session.

  15. 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.

  16. Predictions of H-mode performance in ITER

    SciTech Connect

    Budny, R. V.; Andre, R.; Bateman, G.; Halpern, F.; Kessel, C. E.; Kritz, A.; McCune, D.

    2008-03-03

    Time-dependent integrated predictive modeling is carried out using the PTRANSP code to predict fusion power and parameters such as alpha particle density and pressure in ITER H-mode plasmas. Auxiliary heating by negative ion neutral beam injection and ion cyclotron heating of He3 minority ions are modeled, and the GLF23 transport model is used in the prediction of the evolution of plasma temperature profiles. Effects of beam steering, beam torque, plasma rotation, beam current drive, pedestal temperatures, sawtooth oscillations, magnetic diffusion, and accumulation of He ash are treated self-consistently. Variations in assumptions associated with physics uncertainties for standard base-line DT H-mode plasmas (with Ip=15 MA, BTF=5.3 T, and Greenwald fraction=0.86) lead to a range of predictions for DT fusion power PDT and quasi-steady state fusion QDT (≡ PDT/Paux). Typical predictions assuming Paux = 50-53 MW yield PDT = 250- 720 MW and QDT = 5 - 14. In some cases where Paux is ramped down or shut off after initial flat-top conditions, quasi-steady QDT can be considerably higher, even infinite. Adverse physics assumptions such as existence of an inward pinch of the helium ash and an ash recycling coefficient approaching unity lead to very low values for PDT. Alternative scenarios with different heating and reduced performance regimes are also considered including plasmas with only H or D isotopes, DT plasmas with toroidal field reduced 10 or 20%, and discharges with reduced beam voltage. In full-performance D-only discharges, tritium burn-up is predicted to generate central tritium densities up to 1016/m3 and DT neutron rates up to 5×1016/s, compared with the DD neutron rates of 6×1017/s. Predictions with the toroidal field reduced 10 or 20% below the planned 5.3 T and keeping the same q98, Greenwald fraction, and Βη indicate that the fusion yield PDT and QDT will be lower by about a factor of two (scaling as B3.5).

  17. Fuzzy regression modeling for tool performance prediction and degradation detection.

    PubMed

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

    2010-10-01

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

  18. Foraging Ecology Predicts Learning Performance in Insectivorous Bats

    PubMed Central

    Clarin, Theresa M. A.; Ruczyński, Ireneusz; Page, Rachel A.

    2013-01-01

    Bats are unusual among mammals in showing great ecological diversity even among closely related species and are thus well suited for studies of adaptation to the ecological background. Here we investigate whether behavioral flexibility and simple- and complex-rule learning performance can be predicted by foraging ecology. We predict faster learning and higher flexibility in animals hunting in more complex, variable environments than in animals hunting in more simple, stable environments. To test this hypothesis, we studied three closely related insectivorous European bat species of the genus Myotis that belong to three different functional groups based on foraging habitats: M. capaccinii, an open water forager, M. myotis, a passive listening gleaner, and M. emarginatus, a clutter specialist. We predicted that M. capaccinii would show the least flexibility and slowest learning reflecting its relatively unstructured foraging habitat and the stereotypy of its natural foraging behavior, while the other two species would show greater flexibility and more rapid learning reflecting the complexity of their natural foraging tasks. We used a purposefully unnatural and thus species-fair crawling maze to test simple- and complex-rule learning, flexibility and re-learning performance. We found that M. capaccinii learned a simple rule as fast as the other species, but was slower in complex rule learning and was less flexible in response to changes in reward location. We found no differences in re-learning ability among species. Our results corroborate the hypothesis that animals’ cognitive skills reflect the demands of their ecological niche. PMID:23755146

  19. Development of a massively parallel parachute performance prediction code

    SciTech Connect

    Peterson, C.W.; Strickland, J.H.; Wolfe, W.P.; Sundberg, W.D.; McBride, D.D.

    1997-04-01

    The Department of Energy has given Sandia full responsibility for the complete life cycle (cradle to grave) of all nuclear weapon parachutes. Sandia National Laboratories is initiating development of a complete numerical simulation of parachute performance, beginning with parachute deployment and continuing through inflation and steady state descent. The purpose of the parachute performance code is to predict the performance of stockpile weapon parachutes as these parachutes continue to age well beyond their intended service life. A new massively parallel computer will provide unprecedented speed and memory for solving this complex problem, and new software will be written to treat the coupled fluid, structure and trajectory calculations as part of a single code. Verification and validation experiments have been proposed to provide the necessary confidence in the computations.

  20. A fully automatic tool to perform accurate flood mapping by merging remote sensing imagery and ancillary data

    NASA Astrophysics Data System (ADS)

    D'Addabbo, Annarita; Refice, Alberto; Lovergine, Francesco; Pasquariello, Guido

    2016-04-01

    Flooding is one of the most frequent and expansive natural hazard. High-resolution flood mapping is an essential step in the monitoring and prevention of inundation hazard, both to gain insight into the processes involved in the generation of flooding events, and from the practical point of view of the precise assessment of inundated areas. Remote sensing data are recognized to be useful in this respect, thanks to the high resolution and regular revisit schedules of state-of-the-art satellites, moreover offering a synoptic overview of the extent of flooding. In particular, Synthetic Aperture Radar (SAR) data present several favorable characteristics for flood mapping, such as their relative insensitivity to the meteorological conditions during acquisitions, as well as the possibility of acquiring independently of solar illumination, thanks to the active nature of the radar sensors [1]. However, flood scenarios are typical examples of complex situations in which different factors have to be considered to provide accurate and robust interpretation of the situation on the ground: the presence of many land cover types, each one with a particular signature in presence of flood, requires modelling the behavior of different objects in the scene in order to associate them to flood or no flood conditions [2]. Generally, the fusion of multi-temporal, multi-sensor, multi-resolution and/or multi-platform Earth observation image data, together with other ancillary information, seems to have a key role in the pursuit of a consistent interpretation of complex scenes. In the case of flooding, distance from the river, terrain elevation, hydrologic information or some combination thereof can add useful information to remote sensing data. Suitable methods, able to manage and merge different kind of data, are so particularly needed. In this work, a fully automatic tool, based on Bayesian Networks (BNs) [3] and able to perform data fusion, is presented. It supplies flood maps

  1. A simplified model for hybrid rocket performance prediction

    NASA Astrophysics Data System (ADS)

    Wolf, Robert S.; Wagner, John W.

    1992-02-01

    A computer code to predict hybrid rocket performance was developed and validated. The algorithm used is a simplification of the model derived by Marxman and Wooldridge. This model assumes the fuel regression rate to be controlled by convective heat transfer to the solid fuel from a relatively thin diffusion flame in a turbulent boundary layer. The model further assumes that the Reynolds analogy applies with mass addition at the wall. The computer code incorporates variable combustion product properties (temperature, molecular weight, and ratio of specific heats) as a function of the instantaneous global oxidizer/fuel ratio. The code was validated by constructing and firing a hybrid rocket motor. This motor used gaseous oxygen and hydroxyl-terminated polybutadiene as propellants. The oxygen flow rate used in the test was given as an input to the computer code, which then calculated chamber pressures and thrust. The agreement between test data and computer predictions was excellent.

  2. Predicting introductory programming performance: A multi-institutional multivariate study

    NASA Astrophysics Data System (ADS)

    Bergin, Susan; Reilly, Ronan

    2006-12-01

    A model for predicting student performance on introductory programming modules is presented. The model uses attributes identified in a study carried out at four third-level institutions in the Republic of Ireland. Four instruments were used to collect the data and over 25 attributes were examined. A data reduction technique was applied and a logistic regression model using 10-fold stratified cross validation was developed. The model used three attributes: Leaving Certificate Mathematics result (final mathematics examination at second level), number of hours playing computer games while taking the module and programming self-esteem. Prediction success was significant with 80% of students correctly classified. The model also works well on a per-institution level. A discussion on the implications of the model is provided and future work is outlined.

  3. Fundamental SAR ATR performance predictions for design trade-offs

    NASA Astrophysics Data System (ADS)

    Horowitz, Larry L.; Brendel, Gary F.

    1997-07-01

    This paper discusses work toward a fundamental, algorithm- independent view of the ATR performance that can be achieved using SAR data. Such ATR performance predictions are intended to enable evaluation of performance tradeoffs for SAR designs, including both parameter selections and added domains of SAR observation, such as 3D, full polarimetry, multiaspect and/or multifrequency. In the paper we evaluate the classification error for two tactical targets using a Monte Carlo technique. A number of approximations are made and are detailed in the paper. Data on target signatures come from pencil-beam laser data and target photographs, which determine shadowing of the ground clutter. A single aspect angle is used for each target in the initial results. A layer of radar netting is modeled on both targets. This information is used as 'ground truth', to compute the average power that would be seen in each pixel of a SAR image, for each target. SAR image trials are then generated using independent Rayleigh amplitude fades in each pixel. In an optimal Bayesian fashion, the smaller of the probabilities of target (T1) or T2 given the trial image data is the error probability for that trial. An average over the Monte Carlo image trials yields the overall classification error probability. Comments are given on reducing the number of required trials in such a Monte Carlo. THree results of the work are shown. First, a tradeoff is made of ATR performance versus SAR resolution. ATR improves as the resolution is made finer, and physical reasons for this are discussed. Second, the relative ATR utility is determined for those pixels where at least one target has scatterer as compared with those pixels where the targets differ only in the degree to which they shadow the ground clutter. Third, an early analytical result is given for interferometric SAR, showing the physical reason behind the potential of height-sensing SAR to improve ATR - the possibility of canceling the background

  4. In vitro models for the prediction of in vivo performance of oral dosage forms.

    PubMed

    Kostewicz, Edmund S; Abrahamsson, Bertil; Brewster, Marcus; Brouwers, Joachim; Butler, James; Carlert, Sara; Dickinson, Paul A; Dressman, Jennifer; Holm, René; Klein, Sandra; Mann, James; McAllister, Mark; Minekus, Mans; Muenster, Uwe; Müllertz, Anette; Verwei, Miriam; Vertzoni, Maria; Weitschies, Werner; Augustijns, Patrick

    2014-06-16

    Accurate prediction of the in vivo biopharmaceutical performance of oral drug formulations is critical to efficient drug development. Traditionally, in vitro evaluation of oral drug formulations has focused on disintegration and dissolution testing for quality control (QC) purposes. The connection with in vivo biopharmaceutical performance has often been ignored. More recently, the switch to assessing drug products in a more biorelevant and mechanistic manner has advanced the understanding of drug formulation behavior. Notwithstanding this evolution, predicting the in vivo biopharmaceutical performance of formulations that rely on complex intraluminal processes (e.g. solubilization, supersaturation, precipitation…) remains extremely challenging. Concomitantly, the increasing demand for complex formulations to overcome low drug solubility or to control drug release rates urges the development of new in vitro tools. Development and optimizing innovative, predictive Oral Biopharmaceutical Tools is the main target of the OrBiTo project within the Innovative Medicines Initiative (IMI) framework. A combination of physico-chemical measurements, in vitro tests, in vivo methods, and physiology-based pharmacokinetic modeling is expected to create a unique knowledge platform, enabling the bottlenecks in drug development to be removed and the whole process of drug development to become more efficient. As part of the basis for the OrBiTo project, this review summarizes the current status of predictive in vitro assessment tools for formulation behavior. Both pharmacopoeia-listed apparatus and more advanced tools are discussed. Special attention is paid to major issues limiting the predictive power of traditional tools, including the simulation of dynamic changes in gastrointestinal conditions, the adequate reproduction of gastrointestinal motility, the simulation of supersaturation and precipitation, and the implementation of the solubility-permeability interplay. It is

  5. In vitro models for the prediction of in vivo performance of oral dosage forms.

    PubMed

    Kostewicz, Edmund S; Abrahamsson, Bertil; Brewster, Marcus; Brouwers, Joachim; Butler, James; Carlert, Sara; Dickinson, Paul A; Dressman, Jennifer; Holm, René; Klein, Sandra; Mann, James; McAllister, Mark; Minekus, Mans; Muenster, Uwe; Müllertz, Anette; Verwei, Miriam; Vertzoni, Maria; Weitschies, Werner; Augustijns, Patrick

    2014-06-16

    Accurate prediction of the in vivo biopharmaceutical performance of oral drug formulations is critical to efficient drug development. Traditionally, in vitro evaluation of oral drug formulations has focused on disintegration and dissolution testing for quality control (QC) purposes. The connection with in vivo biopharmaceutical performance has often been ignored. More recently, the switch to assessing drug products in a more biorelevant and mechanistic manner has advanced the understanding of drug formulation behavior. Notwithstanding this evolution, predicting the in vivo biopharmaceutical performance of formulations that rely on complex intraluminal processes (e.g. solubilization, supersaturation, precipitation…) remains extremely challenging. Concomitantly, the increasing demand for complex formulations to overcome low drug solubility or to control drug release rates urges the development of new in vitro tools. Development and optimizing innovative, predictive Oral Biopharmaceutical Tools is the main target of the OrBiTo project within the Innovative Medicines Initiative (IMI) framework. A combination of physico-chemical measurements, in vitro tests, in vivo methods, and physiology-based pharmacokinetic modeling is expected to create a unique knowledge platform, enabling the bottlenecks in drug development to be removed and the whole process of drug development to become more efficient. As part of the basis for the OrBiTo project, this review summarizes the current status of predictive in vitro assessment tools for formulation behavior. Both pharmacopoeia-listed apparatus and more advanced tools are discussed. Special attention is paid to major issues limiting the predictive power of traditional tools, including the simulation of dynamic changes in gastrointestinal conditions, the adequate reproduction of gastrointestinal motility, the simulation of supersaturation and precipitation, and the implementation of the solubility-permeability interplay. It is

  6. The Influence of Viscous Effects on Ice Accretion Prediction and Airfoil Performance Predictions

    NASA Technical Reports Server (NTRS)

    Kreeger, Richard E.; Wright, William B.

    2005-01-01

    A computational study was conducted to evaluate the effectiveness of using a viscous flow solution in an ice accretion code and the resulting accuracy of aerodynamic performance prediction. Ice shapes were obtained for one single-element and one multi-element airfoil using both potential flow and Navier-Stokes flowfields in the LEWICE ice accretion code. Aerodynamics were then calculated using a Navier-Stokes flow solver.

  7. System performance predictions for Space Station Freedom's electric power system

    NASA Technical Reports Server (NTRS)

    Kerslake, Thomas W.; Hojnicki, Jeffrey S.; Green, Robert D.; Follo, Jeffrey C.

    1993-01-01

    Space Station Freedom Electric Power System (EPS) capability to effectively deliver power to housekeeping and user loads continues to strongly influence Freedom's design and planned approaches for assembly and operations. The EPS design consists of silicon photovoltaic (PV) arrays, nickel-hydrogen batteries, and direct current power management and distribution hardware and cabling. To properly characterize the inherent EPS design capability, detailed system performance analyses must be performed for early stages as well as for the fully assembled station up to 15 years after beginning of life. Such analyses were repeatedly performed using the FORTRAN code SPACE (Station Power Analysis for Capability Evaluation) developed at the NASA Lewis Research Center over a 10-year period. SPACE combines orbital mechanics routines, station orientation/pointing routines, PV array and battery performance models, and a distribution system load-flow analysis to predict EPS performance. Time-dependent, performance degradation, low earth orbit environmental interactions, and EPS architecture build-up are incorporated in SPACE. Results from two typical SPACE analytical cases are presented: (1) an electric load driven case and (2) a maximum EPS capability case.

  8. Prediction of Suicide Ideation and Attempts Among Adolescents Using a Brief Performance-Based Test

    PubMed Central

    Nock, Matthew K.; Banaji, Mahzarin R.

    2007-01-01

    Suicide is a leading cause of death that is difficult to predict because clinical assessment has relied almost exclusively on individuals' self-report of suicidal thoughts. This is problematic because there often is motivation to conceal such thoughts. The authors tested the ability of the Self-Injury Implicit Association Test (SI-IAT), a reaction-time measure of implicit associations between self-injury and oneself, to detect and predict suicide ideation and attempts. Participants were adolescents who were nonsuicidal (n = 38), suicide ideators (n = 37), or recent suicide attempters (n = 14). Analyses revealed large between-group differences on the SI-IAT, with nonsuicidal adolescents showing large negative associations between self-injury and themselves, suicide ideators showing small positive associations, and suicide attempters showing large positive associations on this performance-based test. The SI-IAT accurately predicted current suicide ideation and attempt status as well as future suicide ideation, and it incrementally improved prediction of these outcomes above and beyond the use of known risk factors. Future research is needed to refine this assessment method and to further develop and examine performance-based assessment of suicide risk in clinical settings. PMID:17907852

  9. Cortical structure predicts success in performing musical transformation judgments.

    PubMed

    Foster, Nicholas E V; Zatorre, Robert J

    2010-10-15

    Recognizing melodies by their interval structure, or "relative pitch," is a fundamental aspect of musical perception. By using relative pitch, we are able to recognize tunes regardless of the key in which they are played. We sought to determine the cortical areas important for relative pitch processing using two morphometric techniques. Cortical differences have been reported in musicians within right auditory cortex (AC), a region considered important for pitch-based processing, and we have previously reported a functional correlation between relative pitch processing in the anterior intraparietal sulcus (IPS). We addressed the hypothesis that regional variation of cortical structure within AC and IPS is related to relative pitch ability using two anatomical techniques, cortical thickness (CT) analysis and voxel-based morphometry (VBM) of magnetic resonance imaging data. Persons with variable amounts of formal musical training were tested on a melody transposition task, as well as two musical control tasks and a speech control task. We found that gray matter concentration and cortical thickness in right Heschl's sulcus and bilateral IPS both predicted relative pitch task performance and correlated to a lesser extent with performance on the two musical control tasks. After factoring out variance explained by musical training, only relative pitch performance was predicted by cortical structure in these regions. These results directly demonstrate the functional relevance of previously reported anatomical differences in the auditory cortex of musicians. The findings in the IPS provide further support for the existence of a multimodal network for systematic transformation of stimulus information in this region. PMID:20600982

  10. Numerical simulation of a twin screw expander for performance prediction

    NASA Astrophysics Data System (ADS)

    Papes, Iva; Degroote, Joris; Vierendeels, Jan

    2015-08-01

    With the increasing use of twin screw expanders in waste heat recovery applications, the performance prediction of these machines plays an important role. This paper presents a mathematical model for calculating the performance of a twin screw expander. From the mass and energy conservation laws, differential equations are derived which are then solved together with the appropriate Equation of State in the instantaneous control volumes. Different flow processes that occur inside the screw expander such as filling (accompanied by a substantial pressure loss) and leakage flows through the clearances are accounted for in the model. The mathematical model employs all geometrical parameters such as chamber volume, suction and leakage areas. With R245fa as working fluid, the Aungier Redlich-Kwong Equation of State has been used in order to include real gas effects. To calculate the mass flow rates through the leakage paths formed inside the screw expander, flow coefficients are considered as constant and they are derived from 3D Computational Fluid Dynamic calculations at given working conditions and applied to all other working conditions. The outcome of the mathematical model is the P-V indicator diagram which is compared to CFD results of the same twin screw expander. Since CFD calculations require significant computational time, developed mathematical model can be used for the faster performance prediction.

  11. Neighborhood Integration and Connectivity Predict Cognitive Performance and Decline

    PubMed Central

    Watts, Amber; Ferdous, Farhana; Moore, Keith Diaz; Burns, Jeffrey M.

    2015-01-01

    Objective Neighborhood characteristics may be important for promoting walking, but little research has focused on older adults, especially those with cognitive impairment. We evaluated the role of neighborhood characteristics on cognitive function and decline over a 2-year period adjusting for measures of walking. Method In a study of 64 older adults with and without mild Alzheimer's disease (AD), we evaluated neighborhood integration and connectivity using geographical information systems data and space syntax analysis. In multiple regression analyses, we used these characteristics to predict 2-year declines in factor analytically derived cognitive scores (attention, verbal memory, mental status) adjusting for age, sex, education, and self-reported walking. Results Neighborhood integration and connectivity predicted cognitive performance at baseline, and changes in cognitive performance over 2 years. The relationships between neighborhood characteristics and cognitive performance were not fully explained by self-reported walking. Discussion Clearer definitions of specific neighborhood characteristics associated with walkability are needed to better understand the mechanisms by which neighborhoods may impact cognitive outcomes. These results have implications for measuring neighborhood characteristics, design and maintenance of living spaces, and interventions to increase walking among older adults. We offer suggestions for future research measuring neighborhood characteristics and cognitive function. PMID:26504889

  12. Theoretical Approach to Predict the Performance of Thermoelectric Generator Modules

    NASA Astrophysics Data System (ADS)

    Elarusi, Abdulmunaem H.; Fagehi, Hassan; Lee, Hosung; Attar, Alaa

    2016-10-01

    The aim of this work was to examine the validity of the thermoelectric modules' performance predicted by formulating the effective thermoelectric material properties. The three maximum parameters (output power, current, and efficiency) are defined in terms of the average temperature of the thermoelectric generator (TEG). These three maximum parameters, which are either taken from commercial TEG modules or measurements for particular operating conditions, are used to define the effective material properties (Seebeck coefficient, thermal conductivity, and electrical resistivity). The commercial performance curves provided by the manufacturer were compared with the results obtained here by the effective material properties with the simple standard thermoelectric equations. It has been found that this technique predicts the performance of four commercial thermoelectric modules with fair to good accuracy. The characteristics of the TEGs were represented using the normalized charts constructed by formulating the parameters as a fraction of over the maximum parameters. The normalized charts would be universal for any given TEG module once the thermoelectric material is known.

  13. 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

  14. 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

  15. WRF Performance Skills in Predicting Rainfall Over the Philippines

    NASA Astrophysics Data System (ADS)

    Perez, G. J. P.; Combinido, J. S.

    2014-12-01

    The Weather Research and Forecasting (WRF) model has been used for predicting rainfall over the Philippines. The period of October 2013 to May 2014 is chosen for the evaluation because of the unprecedented number of new ground instruments (300 to 500 automated rain gauges). It also gives us a good statistical representation of wet and dry seasons in the country. The WRF model configuration makes use of NCEP FNL for the initial boundary condition. Hindcasts are produced at 12-km resolution with 12 hours up to 144 hours lead-time. To assess the predictability of rainfall, we look at the dichotomous case, wherein we evaluate if the model is able to predict correctly the number of rainfall events. The left column in Figure 1 shows the monthly Percent Correct and Critical Success Index (CSI) for different lead-time. Percent Correct represents how well the model performs, 1 being the highest score, with equal bearing on correct positives and correct negatives. On the other hand, CSI is a balanced score that accounts for false alarm and missed events - it has a range of 0 to 1, where 1 means perfect forecast. Results show that during the wet season (October, November and December), PC is approximately 0.7 while in dry season (January, February and March), PC reaches values of around 0.9, which suggests improvement in the performance from wet to dry season. The increase in performance is attributed to the increase in number of correct negatives during the dry season. The CSI score, which excludes the correct negatives, shows that the ability of WRF to predict rainfall events drastically decline in December or during the transition from wet to dry season. This is due to the inability of WRF to pinpoint exact locations of small convective rainfall events. The predictability of actual rainfall values is indicated by the Mean Absolute Errors (MAE) and Root Mean Square Errors (RMSE) in Figure 1. The MAE for 3-hour accumulated rainfall is smallest during the dry season.

  16. Thermal Model Predictions of Advanced Stirling Radioisotope Generator Performance

    NASA Technical Reports Server (NTRS)

    Wang, Xiao-Yen J.; Fabanich, William Anthony; Schmitz, Paul C.

    2014-01-01

    This paper presents recent thermal model results of the Advanced Stirling Radioisotope Generator (ASRG). The three-dimensional (3D) ASRG thermal power model was built using the Thermal Desktop(trademark) thermal analyzer. The model was correlated with ASRG engineering unit test data and ASRG flight unit predictions from Lockheed Martin's (LM's) I-deas(trademark) TMG thermal model. The auxiliary cooling system (ACS) of the ASRG is also included in the ASRG thermal model. The ACS is designed to remove waste heat from the ASRG so that it can be used to heat spacecraft components. The performance of the ACS is reported under nominal conditions and during a Venus flyby scenario. The results for the nominal case are validated with data from Lockheed Martin. Transient thermal analysis results of ASRG for a Venus flyby with a representative trajectory are also presented. In addition, model results of an ASRG mounted on a Cassini-like spacecraft with a sunshade are presented to show a way to mitigate the high temperatures of a Venus flyby. It was predicted that the sunshade can lower the temperature of the ASRG alternator by 20 C for the representative Venus flyby trajectory. The 3D model also was modified to predict generator performance after a single Advanced Stirling Convertor failure. The geometry of the Microtherm HT insulation block on the outboard side was modified to match deformation and shrinkage observed during testing of a prototypic ASRG test fixture by LM. Test conditions and test data were used to correlate the model by adjusting the thermal conductivity of the deformed insulation to match the post-heat-dump steady state temperatures. Results for these conditions showed that the performance of the still-functioning inboard ACS was unaffected.

  17. Evaluation of Turbulence-Model Performance as Applied to Jet-Noise Prediction

    NASA Technical Reports Server (NTRS)

    Woodruff, S. L.; Seiner, J. M.; Hussaini, M. Y.; Erlebacher, G.

    1998-01-01

    The accurate prediction of jet noise is possible only if the jet flow field can be predicted accurately. Predictions for the mean velocity and turbulence quantities in the jet flowfield are typically the product of a Reynolds-averaged Navier-Stokes solver coupled with a turbulence model. To evaluate the effectiveness of solvers and turbulence models in predicting those quantities most important to jet noise prediction, two CFD codes and several turbulence models were applied to a jet configuration over a range of jet temperatures for which experimental data is available.

  18. Predictions of airfoil aerodynamic performance degradation due to icing

    NASA Technical Reports Server (NTRS)

    Shaw, Robert J.; Potapezuk, Mark G.; Bidwell, Colin S.

    1988-01-01

    An overview of NASA's ongoing efforts to develop an airfoil icing analysis capability is developed. An indication is given to the approaches being followed to calculate the water droplet trajectories past the airfoil, the buildup of ice on the airfoil, and the resultant changes in aerodynamic performance due to the leading edge ice accretion. Examples are given of current code capabilities/limitations through comparisons of predictions with experimental data gathered in various calibration/validation experiments. A brief discussion of future efforts to extend the analysis to handle three dimensional components is included.

  19. Prediction of Gas Injection Performance for Heterogeneous Reservoirs

    SciTech Connect

    Franklin M. Orr, Jr; Martin J. Blunt

    1998-03-31

    This project performs research in four main areas: laboratory experiments to measure three-phase relative permeability; network modeling to predict three-phase relative perme- ability; benchmark simulations of gas injection and waterfl ooding at the field scale; and the development of fast streamline techniques to study field-scale oil. The aim of the work is to achieve a comprehensive description of gas injection processes from the pore to the core to the reservoir scale. In this report we provide a detailed description of our measurements of three-phase relative permeability.

  20. Accurate screening for synthetic preservatives in beverage using high performance liquid chromatography with time-of-flight mass spectrometry.

    PubMed

    Li, Xiu Qin; Zhang, Feng; Sun, Yan Yan; Yong, Wei; Chu, Xiao Gang; Fang, Yan Yan; Zweigenbaum, Jerry

    2008-02-11

    In this study, liquid chromatography time-of-flight mass spectrometry (HPLC/TOF-MS) is applied to qualitation and quantitation of 18 synthetic preservatives in beverage. The identification by HPLC/TOF-MS is accomplished with the accurate mass (the subsequent generated empirical formula) of the protonated molecules [M+H]+ or the deprotonated molecules [M-H]-, along with the accurate mass of their main fragment ions. In order to obtain sufficient sensitivity for quantitation purposes (using the protonated or deprotonated molecule) and additional qualitative mass spectrum information provided by the fragments ions, segment program of fragmentor voltages is designed in positive and negative ion mode, respectively. Accurate mass measurements are highly useful in the complex sample analyses since they allow us to achieve a high degree of specificity, often needed when other interferents are present in the matrix. The mass accuracy typically obtained is routinely better than 3 ppm. The 18 compounds behave linearly in the 0.005-5.0mg.kg(-1) concentration range, with correlation coefficient >0.996. The recoveries at the tested concentrations of 1.0mg.kg(-1)-100mg.kg(-1) are 81-106%, with coefficients of variation <7.5%. Limits of detection (LODs) range from 0.0005 to 0.05 mg.kg(-1), which are far below the required maximum residue level (MRL) for these preservatives in foodstuff. The method is suitable for routine quantitative and qualitative analyses of synthetic preservatives in foodstuff.

  1. 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

  2. Feedback about more accurate versus less accurate trials: differential effects on self-confidence and activation.

    PubMed

    Badami, Rokhsareh; VaezMousavi, Mohammad; Wulf, Gabriele; Namazizadeh, Mahdi

    2012-06-01

    One purpose of the present study was to examine whether self-confidence or anxiety would be differentially affected byfeedback from more accurate rather than less accurate trials. The second purpose was to determine whether arousal variations (activation) would predict performance. On day 1, participants performed a golf putting task under one of two conditions: one group received feedback on the most accurate trials, whereas another group received feedback on the least accurate trials. On day 2, participants completed an anxiety questionnaire and performed a retention test. Shin conductance level, as a measure of arousal, was determined. The results indicated that feedback about more accurate trials resulted in more effective learning as well as increased self-confidence. Also, activation was a predictor of performance. PMID:22808705

  3. Planetary Suit Hip Bearing Model for Predicting Design vs. Performance

    NASA Technical Reports Server (NTRS)

    Cowley, Matthew S.; Margerum, Sarah; Harvil, Lauren; Rajulu, Sudhakar

    2011-01-01

    , the suited performance trends were comparable between the model and the suited subjects. With the three off-nominal bearing configurations compared to the nominal bearing configurations, human subjects showed decreases in hip flexion of 64%, 6%, and 13% and in hip abduction of 59%, 2%, and 20%. Likewise the solid model showed decreases in hip flexion of 58%, 1%, and 25% and in hip abduction of 56%, 0%, and 30%, under the same condition changes from the nominal configuration. Differences seen between the model predictions and the human subject performance data could be attributed to the model lacking dynamic elements and performing kinematic analysis only, the level of fit of the subjects with the suit, the levels of the subject s suit experience.

  4. Prediction of Gas Injection Performance for Heterogeneous Reservoirs

    SciTech Connect

    Blunt, Martin J.; Orr, Jr., Franklin M.

    1999-12-20

    This report describes research carried out in the Department of Petroleum Engineering at Stanford University from September 1998 - September 1998 under the third year of a three-year Department of Energy (DOE) grant on the ''Prediction of Gas Injection Performance for Heterogeneous Reservoirs''. The research effort is an integrated study of the factors affecting gas injection, from the pore scale to the field scale, and involves theoretical analysis, laboratory experiments and numerical simulation. The research is divided into four main areas: (1) Pore scale modeling of three-phase flow in porous media; (2) Laboratory experiments and analysis of factors influencing gas injection performance at the core scale with an emphasis on the fundamentals of three-phase flow; (3) Benchmark simulations of gas injection at the field scale; and (4) Development of streamline-based reservoir simulator.

  5. Performance and Prediction: Bayesian Modelling of Fallible Choice in Chess

    NASA Astrophysics Data System (ADS)

    Haworth, Guy; Regan, Ken; di Fatta, Giuseppe

    Evaluating agents in decision-making applications requires assessing their skill and predicting their behaviour. Both are well developed in Poker-like situations, but less so in more complex game and model domains. This paper addresses both tasks by using Bayesian inference in a benchmark space of reference agents. The concepts are explained and demonstrated using the game of chess but the model applies generically to any domain with quantifiable options and fallible choice. Demonstration applications address questions frequently asked by the chess community regarding the stability of the rating scale, the comparison of players of different eras and/or leagues, and controversial incidents possibly involving fraud. The last include alleged under-performance, fabrication of tournament results, and clandestine use of computer advice during competition. Beyond the model world of games, the aim is to improve fallible human performance in complex, high-value tasks.

  6. 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

  7. 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

  8. The prediction of the hydrodynamic performance of tidal current turbines

    NASA Astrophysics Data System (ADS)

    Y Xiao, B.; Zhou, L. J.; Xiao, Y. X.; Wang, Z. W.

    2013-12-01

    Nowadays tidal current energy is considered to be one of the most promising alternative green energy resources and tidal current turbines are used for power generation. Prediction of the open water performance around tidal turbines is important for the reason that it can give some advice on installation and array of tidal current turbines. This paper presents numerical computations of tidal current turbines by using a numerical model which is constructed to simulate an isolated turbine. This paper aims at studying the installation of marine current turbine of which the hydro-environmental impacts influence by means of numerical simulation. Such impacts include free-stream velocity magnitude, seabed and inflow direction of velocity. The results of the open water performance prediction show that the power output and efficiency of marine current turbine varies from different marine environments. The velocity distribution should be clearly and the suitable unit installation depth and direction be clearly chosen, which can ensure the most effective strategy for energy capture before installing the marine current turbine. The findings of this paper are expected to be beneficial in developing tidal current turbines and array in the future.

  9. Performance predictions of RF heated plasma in EAST

    NASA Astrophysics Data System (ADS)

    Ding, S.; Wan, B.; Zhang, X.; Budny, R. V.; Guo, Y.; McCune, D.; Xu, P.; Yang, J.; Qian, J.; Shi, Y.; Wang, F.; Kaye, S. M.

    2011-01-01

    Scenario development of high power L- and H-mode plasmas in the Experimental Advanced Superconducting Tokamak (EAST) tokamak is reported. The simulations use PTRANSP in combination with TSC to explore EAST plasmas with various radio frequency (RF) auxiliary heating methods, including ion cyclotron resonant heating (ICRH) and lower hybrid current drive. The GLF23 transport model is found to give a better fit to temperature measurements compared with the MMM95 and MMM08 models. A series of ICRH simulations are performed to optimize parameters of a new ICRH system in EAST. The highest plasma stored energy and other related plasma parameters using the current auxiliary power limits are predicted. The discharge length of high power plasma can be 8-200 s, depending on the volt-second consumption in different scenarios. Various phenomena are reported including the influence of different fractions of RF power on their deposition behavior, and on thermal diffusivity, the linear relation between q0 and LHW power fraction, different behavior of fast ions between L- and H-mode plasmas. The scenario development is predicted to improve the performance of EAST.

  10. Performance Prediction of a Synchronization Link for Distributed Aerospace Wireless Systems

    PubMed Central

    Shao, Huaizong

    2013-01-01

    For reasons of stealth and other operational advantages, distributed aerospace wireless systems have received much attention in recent years. In a distributed aerospace wireless system, since the transmitter and receiver placed on separated platforms which use independent master oscillators, there is no cancellation of low-frequency phase noise as in the monostatic cases. Thus, high accurate time and frequency synchronization techniques are required for distributed wireless systems. The use of a dedicated synchronization link to quantify and compensate oscillator frequency instability is investigated in this paper. With the mathematical statistical models of phase noise, closed-form analytic expressions for the synchronization link performance are derived. The possible error contributions including oscillator, phase-locked loop, and receiver noise are quantified. The link synchronization performance is predicted by utilizing the knowledge of the statistical models, system error contributions, and sampling considerations. Simulation results show that effective synchronization error compensation can be achieved by using this dedicated synchronization link. PMID:23970828

  11. Performance prediction of a synchronization link for distributed aerospace wireless systems.

    PubMed

    Wang, Wen-Qin; Shao, Huaizong

    2013-01-01

    For reasons of stealth and other operational advantages, distributed aerospace wireless systems have received much attention in recent years. In a distributed aerospace wireless system, since the transmitter and receiver placed on separated platforms which use independent master oscillators, there is no cancellation of low-frequency phase noise as in the monostatic cases. Thus, high accurate time and frequency synchronization techniques are required for distributed wireless systems. The use of a dedicated synchronization link to quantify and compensate oscillator frequency instability is investigated in this paper. With the mathematical statistical models of phase noise, closed-form analytic expressions for the synchronization link performance are derived. The possible error contributions including oscillator, phase-locked loop, and receiver noise are quantified. The link synchronization performance is predicted by utilizing the knowledge of the statistical models, system error contributions, and sampling considerations. Simulation results show that effective synchronization error compensation can be achieved by using this dedicated synchronization link.

  12. 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

  13. 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

  14. Predicting performance in competitive apnea diving. Part III: deep diving.

    PubMed

    Schagatay, Erika

    2011-12-01

    The first of these reviews described the physiological factors defining the limits of static apnea, while the second examined performance in apneic distance swimming. This paper reviews the factors determining performance in depth disciplines, where hydrostatic pressure is added to the stressors associated with apnea duration and physical work. Apneic duration is essential for performance in all disciplines, and is prolonged by any means that increases gas storage or tolerance to asphyxia or reduces metabolic rate. For underwater distance swimming, the main challenge is to restrict metabolism despite the work of swimming, and to redirect blood flow to allow the most vital functions. Here, work economy, local tissue energy and oxygen stores, anaerobic capacity of the muscles, and possibly technical improvements will be essential for further development. In the depth disciplines, direct pressure effects causing barotrauma, the narcotic effects of gases, decompression sickness (DCS) and possibly air embolism during ascent need to be taken into account, as does the risk of hypoxia when the dive cannot be rapidly interrupted before the surface is reached again. While in most deep divers apneic duration is not the main limitation thus far, greater depths may call for exceptionally long apneas and slower ascents to avoid DCS. Narcotic effects may also affect the ultimate depth limit, which the divers currently performing 'constant weight with fins' dives predict to be around 156 metres' sea water. To reach these depths, serious physiological challenges have to be met, technical developments needed and safety procedures developed concomitantly.

  15. 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.

  16. Predicting the Impacts of Intravehicular Displays on Driving Performance with Human Performance Modeling

    NASA Technical Reports Server (NTRS)

    Mitchell, Diane Kuhl; Wojciechowski, Josephine; Samms, Charneta

    2012-01-01

    A challenge facing the U.S. National Highway Traffic Safety Administration (NHTSA), as well as international safety experts, is the need to educate car drivers about the dangers associated with performing distraction tasks while driving. Researchers working for the U.S. Army Research Laboratory have developed a technique for predicting the increase in mental workload that results when distraction tasks are combined with driving. They implement this technique using human performance modeling. They have predicted workload associated with driving combined with cell phone use. In addition, they have predicted the workload associated with driving military vehicles combined with threat detection. Their technique can be used by safety personnel internationally to demonstrate the dangers of combining distracter tasks with driving and to mitigate the safety risks.

  17. Burst muscle performance predicts the speed, acceleration, and turning performance of Anna's hummingbirds.

    PubMed

    Segre, Paolo S; Dakin, Roslyn; Zordan, Victor B; Dickinson, Michael H; Straw, Andrew D; Altshuler, Douglas L

    2015-11-19

    Despite recent advances in the study of animal flight, the biomechanical determinants of maneuverability are poorly understood. It is thought that maneuverability may be influenced by intrinsic body mass and wing morphology, and by physiological muscle capacity, but this hypothesis has not yet been evaluated because it requires tracking a large number of free flight maneuvers from known individuals. We used an automated tracking system to record flight sequences from 20 Anna's hummingbirds flying solo and in competition in a large chamber. We found that burst muscle capacity predicted most performance metrics. Hummingbirds with higher burst capacity flew with faster velocities, accelerations, and rotations, and they used more demanding complex turns. In contrast, body mass did not predict variation in maneuvering performance, and wing morphology predicted only the use of arcing turns and high centripetal accelerations. Collectively, our results indicate that burst muscle capacity is a key predictor of maneuverability.

  18. The Hurricane Imaging Radiometer (HIRAD): Instrument Status and Performance Predictions

    NASA Technical Reports Server (NTRS)

    Ruf, Christopher; Bailey, M. C.; Gross, Steven; Hood, Robbie; James, Mark; Johnson, James; Jones, Linwood; Miller, Timothy; Uhlhorn, Eric

    2009-01-01

    The Hurricane Imaging Radiometer (HIRAD) is an innovative radiometer which offers new and unique remotely sensed observations of both extreme oceanic wind events and strong precipitation. It is based on the airborne Stepped Frequency Microwave Radiometer (SFMR) [Uhlhorn and Black, 2004]. The HIRAD instrument advances beyond the current nadir viewing SFMR to an equivalent wide-swath SFMR imager using passive microwave synthetic thinned aperture radiometer (STAR) technology [Ruf et al., 1988]. This sensor operates over 4-7 GHz, where the required tropical cyclone remote sensing physics has been validated by both SFMR and WindSat radiometer [Bettenhausen et al., 2006; Brown et al., 2006]. HIRAD incorporates a new and unique array antenna design along with several technologies successfully demonstrated by the Lightweight Rain Radiometer instrument [Ruf et al., 2002; Ruf and Principe, 2003]. HIRAD will be a compact, lightweight, low-power instrument with no moving parts that will produce wide-swath imagery of ocean winds and rain in hurricane conditions. Accurate observations of surface ocean vector winds (OVW) with high spatial and temporal resolution are required for understanding and predicting tropical cyclones. The Hurricane Imaging Radiometer (HIRAD) is an innovative architecture which offers new and unique remotely sensed observations of both extreme oceanic wind events and strong precipitation. It is based on the airborne Stepped Frequency Microwave Radiometer (SFMR), which is a proven remote sensing technique for observing tropical cyclone (TC) ocean surface wind speeds and rain rates. The proposed HIRAD instrument advances beyond the current nadir viewing SFMR to an equivalent wide-swath SFMR imager using passive microwave synthetic thinned aperture radiometer (STAR) technology combined with a a unique array antenna design. The overarching design concept of HIRAD is to combine the multi-frequency C-band observing strategy of the SFMR with STAR technology to

  19. Resin-based composite performance: Are there some things we can’t predict?

    PubMed Central

    Ferracane, Jack L.

    2012-01-01

    Objective The objective of this manuscript is to address the following questions: Why do direct dental composite restorative materials fail clinically? What tests may be appropriate for predicting clinical performance? Does in vitro testing correlate with clinical performance? Materials and methods The literature relating to the clinical and laboratory performance of dental composite restorative materials was reviewed. The main reasons for failure and replacement of dental composite restorations provided the guidance for identifying specific material’s properties that were likely to have the greatest impact on clinical outcomes. Results There are few examples of studies showing correlation between laboratory tests of physical or mechanical properties and clinical performance of dental composites. Evidence does exist to relate clinical wear to flexure strength, fracture toughness and degree of conversion of the polymer matrix. There is evidence relating marginal breakdown to fracture toughness. Despite the fact that little confirmatory evidence exists, there is the expectation that clinical fracture and wear relates to resistance to fatigue. Only minimal evidence exists to correlate marginal quality and bond strength in the laboratory with clinical performance of bonded dental composites. Conclusions The use of clinical trials to evaluate new dental composite formulations for their performance is expensive and time consuming, and it would be ideal to be able to predict clinical outcomes based on a single or multiple laboratory tests. However, though certain correlations exist, the overall clinical success of dental composites is multi-factorial and therefore is unlikely to be predicted accurately by even a battery of in vitro test methods. PMID:22809582

  20. Predicting performance for ecological restoration: A case study using Spartina altemiflora

    USGS Publications Warehouse

    Travis, S.E.; Grace, J.B.

    2010-01-01

    The success of population-based ecological restoration relies on the growth and reproductive performance of selected donor materials, whether consisting of whole plants or seed. Accurately predicting performance requires an understanding of a variety of underlying processes, particularly gene flow and selection, which can be measured, at least in part, using surrogates such as neutral marker genetic distances and simple latitudinal effects. Here we apply a structural equation modeling approach to understanding and predicting performance in a widespread salt marsh grass, Spartina alterniflora, commonly used for ecological restoration throughout its native range in North America. We collected source materials from throughout this range, consisting of eight clones each from 23 populations, for transplantation to a common garden site in coastal Louisiana and monitored their performance. We modeled performance as a latent process described by multiple indicator variables (e.g., clone diameter, stem number) and estimated direct and indirect influences of geographic and genetic distances on performance. Genetic distances were determined by comparison of neutral molecular markers with those from a local population at the common garden site. Geographic distance metrics included dispersal distance (the minimum distance over water between donor and experimental sites) and latitude. Model results indicate direct effects of genetic distance and latitude on performance variation among the donor sites. Standardized effect strengths indicate that performance was roughly twice as sensitive to variation in genetic distance as to latitudinal variation. Dispersal distance had an indirect influence on performance through effects on genetic distance, indicating a typical pattern of genetic isolation by distance. Latitude also had an indirect effect on genetic distance through its linear relationship with dispersal distance. Three performance indicators had significant loadings on

  1. Resilience does not predict academic performance in gross anatomy.

    PubMed

    Elizondo-Omaña, Rodrigo Enrique; García-Rodríguez, María de los Angeles; Hinojosa-Amaya, José Miguel; Villarreal-Silva, Eliud Enrique; Avilan, Rosa Ivette Guzmán; Cruz, Juan José Bazaldúa; Guzmán-López, Santos

    2010-01-01

    Few studies have evaluated resilience in an academic environment as it relates to academic success or failure. This work sought to assess resilience in regular and remedial students of gross anatomy during the first and second semesters of medical school and to correlate this personal trait with academic performance. Two groups of students were compared: the first group included first-year medical students in the regular course, and the second group included first-year medical students who did not pass the regular anatomy course and so were enrolled in the remedial course. Both groups completed anonymous surveys designed to gather demographic data and establish scores on the Connor-Davidson resilience scale, which includes 25 statements rated zero to four on a Likert scale (maximum score 100). The average resilience score was the same for both groups, 80 +/- 9. The average anatomy grades differed significantly between regular students (67+/- 15.0) and remedial students (61 +/- 12.0). While there was no overall correlation between resilience score and anatomy grade, regular students with resilience scores of 75 or greater showed slightly better academic performance than their classmates. Similarly, remedial students with resilience scores of 87 or greater faired better academically. Resilience does not predict academic performance in gross anatomy, and further work is necessary to identify those intrinsic and extrinsic factors that influence students' achievements.

  2. Geoscience Laser Ranging System design and performance predictions

    NASA Technical Reports Server (NTRS)

    Anderson, Kent L.

    1991-01-01

    The Geoscience Laser System (GLRS) will be a high-precision distance-measuring instrument planned for deployment on the EOS-B platform. Its primary objectives are to perform ranging measurements to ground targets to monitor crustal deformation and tectonic plate motions, and nadir-looking altimetry to determine ice sheet thicknesses, surface topography, and vertical profiles of clouds and aerosols. The system uses a mode-locked, 3-color Nd:YAG laser source, a Microchannel Plate-PMT for absolute time-of-flight (TOF) measurement (at 532 nm), a streak camera for TOF 2-color dispersion measurement (532 nm and 355 nm), and a Si avalanche photodiode for altimeter waveform detection (1064 nm). The performance goals are to make ranging measurements to ground targets with about 1 cm accuracy, and altimetry height measurements over ice with 10 cm accuracy. This paper presents an overview of the design concept developed during a phase B study. System engineering issues and trade studies are discussed, with particular attention to error budgets and performance predictions.

  3. Individual Differences in Nonsymbolic Ratio Processing Predict Symbolic Math Performance.

    PubMed

    Matthews, Percival G; Lewis, Mark Rose; Hubbard, Edward M

    2016-02-01

    What basic capacities lay the foundation for advanced numerical cognition? Are there basic nonsymbolic abilities that support the understanding of advanced numerical concepts, such as fractions? To date, most theories have posited that previously identified core numerical systems, such as the approximate number system (ANS), are ill-suited for learning fraction concepts. However, recent research in developmental psychology and neuroscience has revealed a ratio-processing system (RPS) that is sensitive to magnitudes of nonsymbolic ratios and may be ideally suited for supporting fraction concepts. We provide evidence for this hypothesis by showing that individual differences in RPS acuity predict performance on four measures of mathematical competence, including a university entrance exam in algebra. We suggest that the nonsymbolic RPS may support symbolic fraction understanding much as the ANS supports whole-number concepts. Thus, even abstract mathematical concepts, such as fractions, may be grounded not only in higher-order logic and language, but also in basic nonsymbolic processing abilities.

  4. Zero-G Thermodynamic Venting System (TVS) Performance Prediction Program

    NASA Technical Reports Server (NTRS)

    Nguyen, Han

    1994-01-01

    This report documents the Zero-g Thermodynamic Venting System (TVS) performance prediction computer program. The zero-g TVS is a device that destratifies and rejects environmentally induced zero-g thermal gradients in the LH2 storage transfer system. A recirculation pump and spray injection manifold recirculates liquid throughout the length of the tank thereby destratifying both the ullage gas and liquid bulk. Heat rejection is accomplished by the opening of the TVS control valve which allows a small flow rate to expand to a low pressure thereby producing a low temperature heat sink which is used to absorb heat from the recirculating liquid flow. The program was written in FORTRAN 77 language on the HP-9000 and IBM PC computers. It can be run on various platforms with a FORTRAN compiler.

  5. Mining Behavior Based Safety Data to Predict Safety Performance

    SciTech Connect

    Jeffrey C. Joe

    2010-06-01

    The Idaho National Laboratory (INL) operates a behavior based safety program called Safety Observations Achieve Results (SOAR). This peer-to-peer observation program encourages employees to perform in-field observations of each other's work practices and habits (i.e., behaviors). The underlying premise of conducting these observations is that more serious accidents are prevented from occurring because lower level “at risk” behaviors are identified and corrected before they can propagate into culturally accepted “unsafe” behaviors that result in injuries or fatalities. Although the approach increases employee involvement in safety, the premise of the program has not been subject to sufficient empirical evaluation. The INL now has a significant amount of SOAR data on these lower level “at risk” behaviors. This paper describes the use of data mining techniques to analyze these data to determine whether they can predict if and when a more serious accident will occur.

  6. Coded aperture imaging - Predicted performance of uniformly redundant arrays

    NASA Technical Reports Server (NTRS)

    Fenimore, E. E.

    1978-01-01

    It is noted that uniformly redundant arrays (URAs) have autocorrelation functions with perfectly flat sidelobes. A generalized signal-to-noise equation has been developed to predict URA performance. The signal-to-noise value is formulated as a function of aperture transmission or density, the ratio of the intensity of a resolution element to the integrated source intensity, and the ratio of detector background noise to the integrated intensity. It is shown that the only two-dimensional URAs known have a transmission of one half. This is not a great limitation because a nonoptimum transmission of one half never reduces the signal-to-noise ratio more than 30%. The reconstructed URA image contains practically uniform noise, regardless of the object structure. URA's improvement over the single-pinhole camera is much larger for high-intensity points than for low-intensity points.

  7. An improved methodology for individualized performance prediction of sleep-deprived individuals with the two-process model.

    PubMed

    Rajaraman, Srinivasan; Gribok, Andrei V; Wesensten, Nancy J; Balkin, Thomas J; Reifman, Jaques

    2009-10-01

    We present a method based on the two-process model of sleep regulation for developing individualized biomathematical models that predict performance impairment for individuals subjected to total sleep loss. This new method advances our previous work in two important ways. First, it enables model customization to start as soon as the first performance measurement from an individual becomes available. This was achieved by optimally combining the performance information obtained from the individual's performance measurements with a priori performance information using a Bayesian framework, while retaining the strategy of transforming the nonlinear optimization problem of finding the optimal estimates of the two-process model parameters into a series of linear optimization problems. Second, by taking advantage of the linear representation of the two-process model, this new method enables the analytical computation of statistically based measures of reliability for the model predictions in the form of prediction intervals. Two distinct data sets were used to evaluate the proposed method. Results using simulated data with superimposed white Gaussian noise showed that the new method yielded 50% to 90% improvement in parameter-estimate accuracy over the previous method. Moreover, the accuracy of the analytically computed prediction intervals was validated through Monte Carlo simulations. Results for subjects representing three sleep-loss phenotypes who participated in a laboratory study (82 h of total sleep loss) indicated that the proposed method yielded individualized predictions that were up to 43% more accurate than group-average prediction models and, on average, 10% more accurate than individualized predictions based on our previous method.

  8. High-temperature performance prediction of iron ore fines and the ore-blending programming problem in sintering

    NASA Astrophysics Data System (ADS)

    Yan, Bing-ji; Zhang, Jian-liang; Guo, Hong-wei; Chen, Ling-kun; Li, Wei

    2014-08-01

    The high-temperature performance of iron ore fines is an important factor in optimizing ore blending in sintering. However, the application of linear regression analysis and the linear combination method in most other studies always leads to a large deviation from the desired results. In this study, the fuzzy membership functions of the assimilation ability temperature and the liquid fluidity were proposed based on the fuzzy mathematics theory to construct a model for predicting the high-temperature performance of mixed iron ore. Comparisons of the prediction model and experimental results were presented. The results illustrate that the prediction model is more accurate and effective than previously developed models. In addition, fuzzy constraints for the high-temperature performance of iron ore in this research make the results of ore blending more comparable. A solution for the quantitative calculation as well as the programming of fuzzy constraints is also introduced.

  9. 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

  10. 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.

  11. Prediction of motor imagery based brain computer interface performance using a reaction time test.

    PubMed

    Darvishi, Sam; Abbott, Derek; Baumert, Mathias

    2015-08-01

    Brain computer interfaces (BCIs) enable human brains to interact directly with machines. Motor imagery based BCI (MI-BCI) encodes the motor intentions of human agents and provides feedback accordingly. However, 15-30% of people are not able to perform vivid motor imagery. To save time and monetary resources, a number of predictors have been proposed to screen for users with low BCI aptitude. While the proposed predictors provide some level of correlation with MI-BCI performance, simple, objective and accurate predictors are currently not available. Thus, in this study we have examined the utility of a simple reaction time (SRT) test for predicting MI-BCI performance. We enrolled 10 subjects and measured their motor imagery performance with either visual or proprioceptive feedback. Their reaction time was also measured using a SRT test. The results show a significant negative correlation (r ≈ -0.67) between SRT and MI-BCI performance. Therefore SRT may be used as a simple and reliable predictor of MI-BCI performance. PMID:26736893

  12. 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

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

    NASA Astrophysics Data System (ADS)

    Arockia Bazil Raj, A.; Padmavathi, S.

    2016-07-01

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

  14. A computer program for performance prediction of tripropellant rocket engines with tangential slot injection

    NASA Technical Reports Server (NTRS)

    Dang, Anthony; Nickerson, Gary R.

    1987-01-01

    For the development of a Heavy Lift Launch Vehicle (HLLV) several engines with different operating cycles and using LOX/Hydrocarbon propellants are presently being examined. Some concepts utilize hydrogen for thrust chamber wall cooling followed by a gas generator turbine drive cycle with subsequent dumping of H2/O2 combustion products into the nozzle downstream of the throat. In the Space Transportation Booster Engine (STBE) selection process the specific impulse will be one of the optimization criteria; however, the current performance prediction programs do not have the capability to include a third propellant in this process, nor to account for the effect of dumping the gas-generator product tangentially inside the nozzle. The purpose is to describe a computer program for accurately predicting the performance of such an engine. The code consists of two modules; one for the inviscid performance, and the other for the viscous loss. For the first module, the two-dimensional kinetics program (TDK) was modified to account for tripropellant chemistry, and for the effect of tangential slot injection. For the viscous loss, the Mass Addition Boundary Layer program (MABL) was modified to include the effects of the boundary layer-shear layer interaction, and tripropellant chemistry. Calculations were made for a real engine and compared with available data.

  15. Predicted NETD performance of a polarized infrared imaging sensor

    NASA Astrophysics Data System (ADS)

    Preece, Bradley; Hodgkin, Van A.; Thompson, Roger; Leonard, Kevin; Krapels, Keith

    2014-05-01

    Polarization filters are commonly used as a means of increasing the contrast of a scene thereby increasing sensor range performance. The change in the signal to noise ratio (SNR) is a function of the polarization of the target and background, the type and orientation of the polarization filter(s), and the overall transparency of the filter. However, in the mid-wave and longwave infrared bands (MWIR and LWIR), the noise equivalent temperature difference (NETD), which directly affects the SNR, is a function of the filter's re-emission and its reflected temperature radiance. This paper presents a model, by means of a Stokes vector input, that can be incorporated into the Night Vision Integrated Performance Model (NV-IPM) in order to predict the change in SNR, NETD, and noise equivalent irradiance (NEI) for infrared polarimeter imaging systems. The model is then used to conduct a SNR trade study, using a modeled Stokes vector input, for a notional system looking at a reference target. Future laboratory and field measurements conducted at Night Vision Electronic Sensors Directorate (NVESD) will be used to update, validate, and mature the model of conventional infrared systems equipped with polarization filters.

  16. Prediction of Gas Injection Performance for Heterogeneous Reservoirs

    SciTech Connect

    Blunt, Michael J.; Orr, Franklin M.

    1999-05-26

    This report describes research carried out in the Department of Petroleum Engineering at Stanford University from September 1996 - September 1997 under the first year of a three-year Department of Energy grant on the Prediction of Gas Injection Performance for Heterogeneous Reservoirs. The research effort is an integrated study of the factors affecting gas injection, from the pore scale to the field scale, and involves theoretical analysis, laboratory experiments and numerical simulation. The original proposal described research in four main areas; (1) Pore scale modeling of three phase flow in porous media; (2) Laboratory experiments and analysis of factors influencing gas injection performance at the core scale with an emphasis on the fundamentals of three phase flow; (3) Benchmark simulations of gas injection at the field scale; and (4) Development of streamline-based reservoir simulator. Each stage of the research is planned to provide input and insight into the next stage, such that at the end we should have an integrated understanding of the key factors affecting field scale displacements.

  17. Prediction of Gas Injection Performance for Heterogeneous Reservoirs

    SciTech Connect

    Blunt, Martin J.; Orr, Franklin M.

    1999-05-17

    This report describes research carried out in the Department of Petroleum Engineering at Stanford University from September 1997 - September 1998 under the second year of a three-year grant from the Department of Energy on the "Prediction of Gas Injection Performance for Heterogeneous Reservoirs." The research effort is an integrated study of the factors affecting gas injection, from the pore scale to the field scale, and involves theoretical analysis, laboratory experiments, and numerical simulation. The original proposal described research in four areas: (1) Pore scale modeling of three phase flow in porous media; (2) Laboratory experiments and analysis of factors influencing gas injection performance at the core scale with an emphasis on the fundamentals of three phase flow; (3) Benchmark simulations of gas injection at the field scale; and (4) Development of streamline-based reservoir simulator. Each state of the research is planned to provide input and insight into the next stage, such that at the end we should have an integrated understanding of the key factors affecting field scale displacements.

  18. Computational Predictions of the Performance Wright 'Bent End' Propellers

    NASA Technical Reports Server (NTRS)

    Wang, Xiang-Yu; Ash, Robert L.; Bobbitt, Percy J.; Prior, Edwin (Technical Monitor)

    2002-01-01

    Computational analysis of two 1911 Wright brothers 'Bent End' wooden propeller reproductions have been performed and compared with experimental test results from the Langley Full Scale Wind Tunnel. The purpose of the analysis was to check the consistency of the experimental results and to validate the reliability of the tests. This report is one part of the project on the propeller performance research of the Wright 'Bent End' propellers, intend to document the Wright brothers' pioneering propeller design contributions. Two computer codes were used in the computational predictions. The FLO-MG Navier-Stokes code is a CFD (Computational Fluid Dynamics) code based on the Navier-Stokes Equations. It is mainly used to compute the lift coefficient and the drag coefficient at specified angles of attack at different radii. Those calculated data are the intermediate results of the computation and a part of the necessary input for the Propeller Design Analysis Code (based on Adkins and Libeck method), which is a propeller design code used to compute the propeller thrust coefficient, the propeller power coefficient and the propeller propulsive efficiency.

  19. Predictions of boiler performance when firing fine grind coal fuels

    SciTech Connect

    Hargrove, M.J.; Liljedahl, G.N.; Miemiec, L.S.

    1996-12-31

    The development of advanced coal beneficiation and utilization technologies is being sponsored by the US Department of Energy`s Pittsburgh Energy Technology Center, to encourage the use of the abundant coal reserves. A comprehensive program is being conducted by Combustion Engineering, Inc. (ABB CE), regarding the use of these fuels in existing utility boilers. The preparation process can change the original fuel particle size distribution and hence can affect the combustion and ash deposition behaviors. To evaluate the effects of fine particles independent of the beneficiation process, a Pittsburgh No. 8 coal at three degrees of fineness was selected. Physical, chemical, combustion and fireside characteristics of these fuels were evaluated in laboratory testing. Characterization tests provide the information required to predict the performance and economic impacts of firing these fuels in existing coal and oil-designed utility boilers. Two utility steam generators designed for either coal or oil-firing were selected for performance evaluation. The study units were selected to be representative of a large portion of the current boiler population: a 560 MW coal-designed boiler purchased in 1973; and a 600 MW oil-designed boiler purchased in 1970. Each of these units was previously studied in the DOE Beneficiated Coal Fuels (BCF) evaluation of Spherical Oil Agglomeration Products (SOAP). Both of these units were built by ABB CE, but the fuel related design parameters are similar to those used by other manufacturers. This paper summarizes the results of the performance analysis and describes the economic impacts that can be expected when firing this coal ground to different fineness levels in two utility steam generators.

  20. Predicting Student Academic Performance in an Engineering Dynamics Course: A Comparison of Four Types of Predictive Mathematical Models

    ERIC Educational Resources Information Center

    Huang, Shaobo; Fang, Ning

    2013-01-01

    Predicting student academic performance has long been an important research topic in many academic disciplines. The present study is the first study that develops and compares four types of mathematical models to predict student academic performance in engineering dynamics--a high-enrollment, high-impact, and core course that many engineering…

  1. The Berlin Brain--Computer Interface: accurate performance from first-session in BCI-naïve subjects.

    PubMed

    Blankertz, Benjamin; Losch, Florian; Krauledat, Matthias; Dornhege, Guido; Curio, Gabriel; Müller, Klaus-Robert

    2008-10-01

    The Berlin Brain--Computer Interface (BBCI) project develops a noninvasive BCI system whose key features are: 1) the use of well-established motor competences as control paradigms; 2) high-dimensional features from multichannel EEG; and 3) advanced machine-learning techniques. Spatio-spectral changes of sensorimotor rhythms are used to discriminate imagined movements (left hand, right hand, and foot). A previous feedback study [M. Krauledat, K.-R. MUller, and G. Curio. (2007) The non-invasive Berlin brain--computer Interface: Fast acquisition of effective performance in untrained subjects. NeuroImage. [Online]. 37(2), pp. 539--550. Available: http://dx.doi.org/10.1016/j.neuroimage.2007.01.051] with ten subjects provided preliminary evidence that the BBCI system can be operated at high accuracy for subjects with less than five prior BCI exposures. Here, we demonstrate in a group of 14 fully BCI-naIve subjects that 8 out of 14 BCI novices can perform at >84% accuracy in their very first BCI session, and a further four subjects at >70%. Thus, 12 out of 14 BCI-novices had significant above-chance level performances without any subject training even in the first session, as based on an optimized EEG analysis by advanced machine-learning algorithms. PMID:18838371

  2. Frontoparietal white matter integrity predicts haptic performance in chronic stroke.

    PubMed

    Borstad, Alexandra L; Choi, Seongjin; Schmalbrock, Petra; Nichols-Larsen, Deborah S

    2016-01-01

    strongly correlated with the shared variance across tracts in the control, but not in the poststroke participants. A moderate to good relationship was found between ipsilesional T-M1 MD and affected hand HASTe score (r = - 0.62, p = 0.006) and less affected hand HASTe score (r = - 0.53, p = 0.022). Regression analysis revealed approximately 90% of the variance in affected hand HASTe score was predicted by the white matter integrity in the frontoparietal network (as indexed by MD) in poststroke participants while 87% of the variance in HASTe score was predicted in control participants. This study demonstrates the importance of frontoparietal white matter in mediating haptic performance and specifically identifies that T-M1 and precuneus interhemispheric tracts may be appropriate targets for piloting rehabilitation interventions, such as noninvasive brain stimulation, when the goal is to improve poststroke haptic performance.

  3. Performance prediction of the TMT secondary mirror support system

    NASA Astrophysics Data System (ADS)

    Cho, Myung K.

    2008-07-01

    The Ritchey-Chretien (RC) design of the Thirty Meter Telescope (TMT) optics calls for a 3.1 m diameter Secondary Mirror (M2), which is a large meniscus convex hyperboloid. The M2 converts the beam reflected from the f/1 primary mirror into an f/15 beam for the science instruments. The M2 Mirror (M2M) has a mass of approximately two metric tons and the mirror support system will need to maintain the mirror figure at different gravity orientations. Recent changes in the telescope configuration to RC from Aplanatic Gregorian (AG) prescription and reduction of the fully-illuminated field of view to 15 arc minutes required a design change in the M2 mirror figure from a concave radius to a convex radius, with a significant reduction in diameter, which in turn requires re-optimization of the mirror support systems. The optical performance evaluations were made based on the optimized support systems resulting from the change from AG to RC. The M2 optimized support system consists of 60 axial supports, mounted at the mirror back surface, and 24 lateral supports mounted along the outer edge. The predicted print-though errors of the M2M supports are 10nm RMS surface for axial gravity and 2nm RMS surface for lateral gravity. This M2M support system has an active optics capability to accommodate potential mechanical or thermal errors; its performance to correct low-order aberrations has been analyzed. A structure function of the axial gravity support print-through was calculated.

  4. A Performance Prediction Model for a Fault-Tolerant Computer During Recovery and Restoration

    NASA Technical Reports Server (NTRS)

    Obando, Rodrigo A.; Stoughton, John W.

    1995-01-01

    The modeling and design of a fault-tolerant multiprocessor system is addressed. Of interest is the behavior of the system during recovery and restoration after a fault has occurred. The multiprocessor systems are based on the Algorithm to Architecture Mapping Model (ATAMM) and the fault considered is the death of a processor. The developed model is useful in the determination of performance bounds of the system during recovery and restoration. The performance bounds include time to recover from the fault, time to restore the system, and determination of any permanent delay in the input to output latency after the system has regained steady state. Implementation of an ATAMM based computer was developed for a four-processor generic VHSIC spaceborne computer (GVSC) as the target system. A simulation of the GVSC was also written on the code used in the ATAMM Multicomputer Operating System (AMOS). The simulation is used to verify the new model for tracking the propagation of the delay through the system and predicting the behavior of the transient state of recovery and restoration. The model is shown to accurately predict the transient behavior of an ATAMM based multicomputer during recovery and restoration.

  5. Two tests of approach-iron golf skill and their ability to predict tournament performance.

    PubMed

    Robertson, Sam; Burnett, Angus F; Gupta, Ritu

    2014-01-01

    The aim of this study was to investigate the convergent and predictive validity of two skill tests that examine the ability of golfers to hit accurate approach-iron shots. Twenty-four high-level golfers (handicap = 2.6 ± 1.7) performed the Nine-Ball Skills Test (assesses the ability to shape/control ball trajectory with high accuracy) and the Approach-Iron Skill Test (assesses the ability to hit straight shots from varying distances with high accuracy). Participants then completed at least eight rounds of tournament golf over the following 90 days and reported an indicator of approach-iron accuracy (per cent error index). A moderate correlation (r = 0.50, P < 0.05) was noted between scores for both tests. Generalised estimating equations, using two covariates (lie of the ball and distance to hole), were used to determine model fit and the amount of variance explained for tournament per cent error index. Results showed that the Approach-Iron Skill Test was the slightly stronger predictor of on-course per cent error index. With both test scores considered together, a minimal amount of additional variance was explained. These findings suggest that either of the tests used individually or combined may be used to predict tournament approach iron performance in high-level golfers.

  6. Performance predictions of VAWTs with NLF airfoil blades

    SciTech Connect

    Masson, C.; Leclerc, C.; Paraschivoiu, I.

    1997-02-01

    The successful design of an efficient Vertical Axis Wind Turbine (VAWT) can be obtained only when appropriate airfoil sections have been selected. Most VAWTs currently operating worldwide use blades of symmetrical NACA airfoil series. As these blades were designed for aviation applications, Sandia National Laboratories developed a family of airfoils specifically designed for VAWTs in order to decrease the Cost of Energy (COE) of the VAWT (Berg, 1990). Objectives formulated for the blade profile were: modest values of maximum lift coefficient, low drag at low angle of attack, high drag at high angle of attack, sharp stall, and low thickness-to-chord ratio. These features are similar to those of Natural Laminar Flow airfoils (NLF) and gave birth to the SNLA airfoil series. This technical brief illustrates the benefits and losses resulting from using NLF airfoils on VAWT blades. To achieve this goal, the streamtube model of Paraschivoiu (1988) is used to predict the performance of VAWTs equipped with blades of various airfoil shapes. The airfoil shapes considered are the conventional airfoils NACA 0018 and NACA 0021, and the SNLA 0018/50 airfoil designed at Sandia. Furthermore, the potential benefit of reducing the airfoil drag is clearly illustrated by the presentation of the individual contributions of lift and drag to power.

  7. Individual Differences in Nonsymbolic Ratio Processing Predict Symbolic Math Performance.

    PubMed

    Matthews, Percival G; Lewis, Mark Rose; Hubbard, Edward M

    2016-02-01

    What basic capacities lay the foundation for advanced numerical cognition? Are there basic nonsymbolic abilities that support the understanding of advanced numerical concepts, such as fractions? To date, most theories have posited that previously identified core numerical systems, such as the approximate number system (ANS), are ill-suited for learning fraction concepts. However, recent research in developmental psychology and neuroscience has revealed a ratio-processing system (RPS) that is sensitive to magnitudes of nonsymbolic ratios and may be ideally suited for supporting fraction concepts. We provide evidence for this hypothesis by showing that individual differences in RPS acuity predict performance on four measures of mathematical competence, including a university entrance exam in algebra. We suggest that the nonsymbolic RPS may support symbolic fraction understanding much as the ANS supports whole-number concepts. Thus, even abstract mathematical concepts, such as fractions, may be grounded not only in higher-order logic and language, but also in basic nonsymbolic processing abilities. PMID:26710824

  8. Hydrogen recombination kinetics and nuclear thermal rocket performance prediction

    SciTech Connect

    Wetzel, K.K.; Solomon, W.C.

    1994-07-01

    The rate constants for the hydrogen three-body collisional recombination reaction with atomic and molecular hydrogen acting as third bodies have been determined by numerous investigators during the past 30 yr, but these rates exhibit significant scatter. The discrepancies in the rate constants determined by different investigators are as great as two orders of magnitude in the temperature range of interest for nuclear thermal rocket (NTR) operation, namely, 2000-3300 K. The impact of this scatter on our ability to predict the specific impulse (I(sub sp)) delivered by a 30-klbf NTR has been determined for chamber pressures and temperatures from, respectively, 20-1000 psia and 2700-3300 K. The variation in I(sub sp) produced by using the different rate constants is as great as 10%, or 100 s. This variation also obscures the influence of chamber pressure on I(sub sp); using fast kinetics, low pressures yield significantly improved performance, while using slow or nominal kinetics, the pressure dependence of I(sub sp) is negligible. Because the flow composition freezes at very small area ratios, optimization of the nozzle contour in the near-throat region maximizes recombination. Vibrational relaxation is found to produce negligible losses in I(sub sp). 36 refs.

  9. Hydrogen recombination kinetics and nuclear thermal rocket performance prediction

    NASA Astrophysics Data System (ADS)

    Wetzel, Kyle K.; Solomon, Wayne C.

    1994-07-01

    The rate constants for the hydrogen three-body collisional recombination reaction with atomic and molecular hydrogen acting as third bodies have been determined by numerous investigators during the past 30 yr, but these rates exhibit significant scatter. The discrepancies in the rate constants determined by different investigators are as great as two orders of magnitude in the temperature range of interest for nuclear thermal rocket (NTR) operation, namely, 2000-3300 K. The impact of this scatter on our ability to predict the specific impulse (I(sub sp)) delivered by a 30-klbf NTR has been determined for chamber pressures and temperatures from, respectively, 20-1000 psia and 2700-3300 K. The variation in I(sub sp) produced by using the different rate constants is as great as 10%, or 100 s. This variation also obscures the influence of chamber pressure on I(sub sp); using fast kinetics, low pressures yield significantly improved performance, while using slow or nominal kinetics, the pressure dependence of I(sub sp) is negligible. Because the flow composition freezes at very small area ratios, optimization of the nozzle contour in the near-throat region maximizes recombination. Vibrational relaxation is found to produce negligible losses in I(sub sp).

  10. Prediction of Slot Shape and Slot Size for Improving the Performance of Microstrip Antennas Using Knowledge-Based Neural Networks.

    PubMed

    Khan, Taimoor; De, Asok

    2014-01-01

    In the last decade, artificial neural networks have become very popular techniques for computing different performance parameters of microstrip antennas. The proposed work illustrates a knowledge-based neural networks model for predicting the appropriate shape and accurate size of the slot introduced on the radiating patch for achieving desired level of resonance, gain, directivity, antenna efficiency, and radiation efficiency for dual-frequency operation. By incorporating prior knowledge in neural model, the number of required training patterns is drastically reduced. Further, the neural model incorporated with prior knowledge can be used for predicting response in extrapolation region beyond the training patterns region. For validation, a prototype is also fabricated and its performance parameters are measured. A very good agreement is attained between measured, simulated, and predicted results. PMID:27382616

  11. Prediction of Slot Shape and Slot Size for Improving the Performance of Microstrip Antennas Using Knowledge-Based Neural Networks

    PubMed Central

    De, Asok

    2014-01-01

    In the last decade, artificial neural networks have become very popular techniques for computing different performance parameters of microstrip antennas. The proposed work illustrates a knowledge-based neural networks model for predicting the appropriate shape and accurate size of the slot introduced on the radiating patch for achieving desired level of resonance, gain, directivity, antenna efficiency, and radiation efficiency for dual-frequency operation. By incorporating prior knowledge in neural model, the number of required training patterns is drastically reduced. Further, the neural model incorporated with prior knowledge can be used for predicting response in extrapolation region beyond the training patterns region. For validation, a prototype is also fabricated and its performance parameters are measured. A very good agreement is attained between measured, simulated, and predicted results. PMID:27382616

  12. Prediction of Slot Shape and Slot Size for Improving the Performance of Microstrip Antennas Using Knowledge-Based Neural Networks.

    PubMed

    Khan, Taimoor; De, Asok

    2014-01-01

    In the last decade, artificial neural networks have become very popular techniques for computing different performance parameters of microstrip antennas. The proposed work illustrates a knowledge-based neural networks model for predicting the appropriate shape and accurate size of the slot introduced on the radiating patch for achieving desired level of resonance, gain, directivity, antenna efficiency, and radiation efficiency for dual-frequency operation. By incorporating prior knowledge in neural model, the number of required training patterns is drastically reduced. Further, the neural model incorporated with prior knowledge can be used for predicting response in extrapolation region beyond the training patterns region. For validation, a prototype is also fabricated and its performance parameters are measured. A very good agreement is attained between measured, simulated, and predicted results.

  13. 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

  14. 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

  15. Burst muscle performance predicts the speed, acceleration, and turning performance of Anna’s hummingbirds

    PubMed Central

    Segre, Paolo S; Dakin, Roslyn; Zordan, Victor B; Dickinson, Michael H; Straw, Andrew D; Altshuler, Douglas L

    2015-01-01

    Despite recent advances in the study of animal flight, the biomechanical determinants of maneuverability are poorly understood. It is thought that maneuverability may be influenced by intrinsic body mass and wing morphology, and by physiological muscle capacity, but this hypothesis has not yet been evaluated because it requires tracking a large number of free flight maneuvers from known individuals. We used an automated tracking system to record flight sequences from 20 Anna's hummingbirds flying solo and in competition in a large chamber. We found that burst muscle capacity predicted most performance metrics. Hummingbirds with higher burst capacity flew with faster velocities, accelerations, and rotations, and they used more demanding complex turns. In contrast, body mass did not predict variation in maneuvering performance, and wing morphology predicted only the use of arcing turns and high centripetal accelerations. Collectively, our results indicate that burst muscle capacity is a key predictor of maneuverability. DOI: http://dx.doi.org/10.7554/eLife.11159.001 PMID:26583753

  16. Salivary concentrations of cortisol and testosterone and prediction of performance in a professional triathlon competition.

    PubMed

    Balthazar, Cláudio Heitor; Garcia, Marcia Carvalho; Spadari-Bratfisch, Regina Celia

    2012-09-01

    The aim of this study was to examine salivary cortisol and testosterone concentrations in professional male athletes during a short triathlon competition using non-invasive methods, and to determine whether these hormone concentrations could be accurate predictors of performance. Eight adult male athletes (age, mean ± SEM: 27.8 ± 3.2 years; body mass index: 21.66 ± 0.42) in a professional triathlon team volunteered to participate in this study. Saliva samples were taken on the competition day and 7 days after competition on a rest day. The performance of the athletes was assessed by their rank order in the competition. Salivary cortisol concentrations were greater on the competition day than on the rest day in the early morning, immediately after waking up, 30 min later, immediately before the start of the competition, and later in the evening. Testosterone concentrations were greater on the competition day in the morning and in the evening. The diurnal rhythm of both cortisol and testosterone concentrations was maintained on both days and the testosterone/cortisol ratio (T/C ratio) was similar between days. The performance of the athletes was positively correlated with salivary cortisol concentration in the early morning of the competition day, but was not correlated with testosterone concentrations at any of the time points. In conclusion, early morning salivary cortisol concentration, but not T/C ratio, could be used to predict performance in athletes during a professional triathlon competition. PMID:22128832

  17. Salivary concentrations of cortisol and testosterone and prediction of performance in a professional triathlon competition.

    PubMed

    Balthazar, Cláudio Heitor; Garcia, Marcia Carvalho; Spadari-Bratfisch, Regina Celia

    2012-09-01

    The aim of this study was to examine salivary cortisol and testosterone concentrations in professional male athletes during a short triathlon competition using non-invasive methods, and to determine whether these hormone concentrations could be accurate predictors of performance. Eight adult male athletes (age, mean ± SEM: 27.8 ± 3.2 years; body mass index: 21.66 ± 0.42) in a professional triathlon team volunteered to participate in this study. Saliva samples were taken on the competition day and 7 days after competition on a rest day. The performance of the athletes was assessed by their rank order in the competition. Salivary cortisol concentrations were greater on the competition day than on the rest day in the early morning, immediately after waking up, 30 min later, immediately before the start of the competition, and later in the evening. Testosterone concentrations were greater on the competition day in the morning and in the evening. The diurnal rhythm of both cortisol and testosterone concentrations was maintained on both days and the testosterone/cortisol ratio (T/C ratio) was similar between days. The performance of the athletes was positively correlated with salivary cortisol concentration in the early morning of the competition day, but was not correlated with testosterone concentrations at any of the time points. In conclusion, early morning salivary cortisol concentration, but not T/C ratio, could be used to predict performance in athletes during a professional triathlon competition.

  18. A robust and accurate center-frequency estimation (RACE) algorithm for improving motion estimation performance of SinMod on tagged cardiac MR images without known tagging parameters.

    PubMed

    Liu, Hong; Wang, Jie; Xu, Xiangyang; Song, Enmin; Wang, Qian; Jin, Renchao; Hung, Chih-Cheng; Fei, Baowei

    2014-11-01

    A robust and accurate center-frequency (CF) estimation (RACE) algorithm for improving the performance of the local sine-wave modeling (SinMod) method, which is a good motion estimation method for tagged cardiac magnetic resonance (MR) images, is proposed in this study. The RACE algorithm can automatically, effectively and efficiently produce a very appropriate CF estimate for the SinMod method, under the circumstance that the specified tagging parameters are unknown, on account of the following two key techniques: (1) the well-known mean-shift algorithm, which can provide accurate and rapid CF estimation; and (2) an original two-direction-combination strategy, which can further enhance the accuracy and robustness of CF estimation. Some other available CF estimation algorithms are brought out for comparison. Several validation approaches that can work on the real data without ground truths are specially designed. Experimental results on human body in vivo cardiac data demonstrate the significance of accurate CF estimation for SinMod, and validate the effectiveness of RACE in facilitating the motion estimation performance of SinMod.

  19. Appraisal of Artificial Screening Techniques of Tomato to Accurately Reflect Field Performance of the Late Blight Resistance

    PubMed Central

    Nowakowska, Marzena; Nowicki, Marcin; Kłosińska, Urszula; Maciorowski, Robert; Kozik, Elżbieta U.

    2014-01-01

    Late blight (LB) caused by the oomycete Phytophthora infestans continues to thwart global tomato production, while only few resistant cultivars have been introduced locally. In order to gain from the released tomato germplasm with LB resistance, we compared the 5-year field performance of LB resistance in several tomato cultigens, with the results of controlled conditions testing (i.e., detached leaflet/leaf, whole plant). In case of these artificial screening techniques, the effects of plant age and inoculum concentration were additionally considered. In the field trials, LA 1033, L 3707, L 3708 displayed the highest LB resistance, and could be used for cultivar development under Polish conditions. Of the three methods using controlled conditions, the detached leaf and the whole plant tests had the highest correlation with thefield experiments. The plant age effect on LB resistance in tomato reported here, irrespective of the cultigen tested or inoculum concentration used, makes it important to standardize the test parameters when screening for resistance. Our results help show why other reports disagree on LB resistance in tomato. PMID:25279467

  20. Pallidal spiking activity reflects learning dynamics and predicts performance

    PubMed Central

    Noblejas, Maria Imelda; Mizrahi, Aviv D.; Dauber, Omer; Bergman, Hagai

    2016-01-01

    The basal ganglia (BG) network has been divided into interacting actor and critic components, modulating the probabilities of different state–action combinations through learning. Most models of learning and decision making in the BG focus on the roles of the striatum and its dopaminergic inputs, commonly overlooking the complexities and interactions of BG downstream nuclei. In this study, we aimed to reveal the learning-related activity of the external segment of the globus pallidus (GPe), a downstream structure whose computational role has remained relatively unexplored. Recording from monkeys engaged in a deterministic three-choice reversal learning task, we found that changes in GPe discharge rates predicted subsequent behavioral shifts on a trial-by-trial basis. Furthermore, the activity following the shift encoded whether it resulted in reward or not. The frequent changes in stimulus–outcome contingencies (i.e., reversals) allowed us to examine the learning-related neural activity and show that GPe discharge rates closely matched across-trial learning dynamics. Additionally, firing rates exhibited a linear decrease in sequences of correct responses, possibly reflecting a gradual shift from goal-directed execution to automaticity. Thus, modulations in GPe spiking activity are highest for attention-demanding aspects of behavior (i.e., switching choices) and decrease as attentional demands decline (i.e., as performance becomes automatic). These findings are contrasted with results from striatal tonically active neurons, which show none of these task-related modulations. Our results demonstrate that GPe, commonly studied in motor contexts, takes part in cognitive functions, in which movement plays a marginal role. PMID:27671661

  1. Does High School Performance Predict College Math Placement?

    ERIC Educational Resources Information Center

    Kowski, Lynne E.

    2013-01-01

    Predicting student success has long been a question of interest for postsecondary admission counselors throughout the United States. Past research has examined the validity of several methods designed for predicting undergraduate success. High school record, standardized test scores, extracurricular activities, and combinations of all three have…

  2. Performance evaluation of NCEP climate forecast system for the prediction of winter temperatures over India

    NASA Astrophysics Data System (ADS)

    Nageswararao, M. M.; Mohanty, U. C.; Kiran Prasad, S.; Osuri, Krishna K.; Ramakrishna, S. S. V. S.

    2015-08-01

    The surface air temperature during the winter season (December-February) in India adversely affects agriculture as well as day-to-day life. Therefore, the accurate prediction of winter temperature in extended range is of utmost importance. The National Center for Environmental Prediction (NCEP) has been providing climatic variables from the fully coupled global climate model, known as Climate Forecast System version 1 (CFSv1) on monthly to seasonal scale since 2004, and it has been upgraded to CFSv2 subsequently in 2011. In the present study, the performance of CFSv1 and CFSv2 in simulating the winter 2 m maximum, minimum, and mean temperatures (T max, T min, and T mean, respectively) over India is evaluated with respect to India Meteorological Department (IMD) 1° × 1° observations. The hindcast data obtained from both versions of CFS from 1982 to 2009 (27 years) with November initial conditions (lead-1) are used. The analyses of winter (T max, T min, and T mean) temperatures revealed that CFSv1 and CFSv2 are able to replicate the patterns of observed climatology, interannual variability, and coefficient of variation with a slight negative bias. Of the two, CFSv2 is appreciable in capturing increasing trends of winter temperatures like observed. The T max, T min, and T mean correlations from CFSv2 is significantly high (0.35, 0.53, and 0.51, respectively), while CFSv1 correlations are less (0.29, 0.15, and 0.12) and insignificant. This performance of CFSv2 may be due to the better estimation of surface heat budget terms and realistic CO2 concentration, which were absent in CFSv1. CFSv2 proved to have a high probability of detection in predicting different categories (below, near, and above normal) for winter T min, which are required for crop yield and public utility services, over north India.

  3. Diagnostic Performance 1 H after Simulation Training Predicts Learning

    ERIC Educational Resources Information Center

    Consoli, Anna; Fraser, Kristin; Ma, Irene; Sobczak, Matthew; Wright, Bruce; McLaughlin, Kevin

    2013-01-01

    Although simulation training improves post-training performance, it is unclear how well performance soon after simulation training predicts longer term outcomes (i.e., learning). Here our objective was to assess the predictive value of performance 1 h post-training of performance 6 weeks later. We trained 84 first year medical students a simulated…

  4. 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.

  5. Performance prediction of four-contact vertical Hall-devices using a conformal mapping technique

    NASA Astrophysics Data System (ADS)

    Yang, Huang; Yue, Xu; Yufeng, Guo

    2015-12-01

    Instead of the conventional design with five contacts in the sensor active area, innovative vertical Hall devices (VHDs) with four contacts and six contacts are asymmetrical in structural design but symmetrical in the current flow that can be well fit for the spinning current technique for offset elimination. In this article, a conformal mapping calculation method is used to predict the performance of asymmetrical VHD embedded in a deep n-well with four contacts. Furthermore, to make the calculation more accurate, the junction field effect is also involved into the conformal mapping method. The error between calculated and simulated results is less than 5% for the current-related sensitivity, and approximately 13% for the voltage-related sensitivity. This proves that such calculations can be used to predict the optimal structure of the vertical Hall-devices. Project supported by the Natural Science Foundation of Jiangsu Province, China (Nos. BK20131379, BK20141431) and the Graduate Research and Innovation Projects of Jiangsu Province (No. SJLX_0373).

  6. First Assessments of Predicted ICESat-2 Performance Using Aircraft Data

    NASA Technical Reports Server (NTRS)

    Neumann, Thomas; Markus, Thorsten; Cook, William; Hancock, David; Brenner, Anita; Kelly, Brunt; DeMarco, Eugenia; Reed, Daniel; Walsh, Kaitlin

    2012-01-01

    The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) is a next-generation laser altimeter designed to continue key observations of ice sheet elevation change, sea ice freeboard, vegetation canopy height, earth surface elevation, and sea surface height. Scheduled for launch in mid-2016, ICESat-2 will use a high repetition rate (10 kHz), small footprint (10 m nominal ground diameter) laser, and a single-photon-sensitive detection strategy (photon counting) to measure precise range to the earth's surface. Using green light (532 nm), the six beams of ICESat-2 will provide improved spatial coverage compared with the single beam of ICESat, while the differences in transmit energy among the beams provide a large dynamic range. The six beams are arranged into three pairs of beams which allow slopes to measured on an orbit-by-orbit basis. In order to evaluate models of predicted ICESat-2 performance and provide ICESat-2-like data for algorithm development, an airborne ICESat-2 simulator was developed and first flown in 2010. This simulator, the Multiple Altimeter Beam Experimental Lidar (MABEL) was most recently deployed to Iceland in April 2012 and collected approx 85 hours of science data over land ice, sea ice, and calibration targets. MABEL uses a similar photon-counting measurement strategy to what will be used on ICESat-2. MABEL collects data in 16 green channels and an additional 8 channels in the infrared aligned across the direction of flight. By using NASA's ER-2 aircraft flying at 20km altitude, MABEL flies as close to space as is practical, and collects data through approx 95% of the atmosphere. We present background on the MABEL instrument, and data from the April 2012 deployment to Iceland. Among the 13 MABEL flights, we collected data over the Greenland ice sheet interior and outlet glaciers in the southwest and western Greenland, sea ice data over the Nares Strait and Greenland Sea, and a number of small glaciers and ice caps in Iceland and Svalbard

  7. Accurately measuring MPI broadcasts in a computational grid

    SciTech Connect

    Karonis N T; de Supinski, B R

    1999-05-06

    An MPI library's implementation of broadcast communication can significantly affect the performance of applications built with that library. In order to choose between similar implementations or to evaluate available libraries, accurate measurements of broadcast performance are required. As we demonstrate, existing methods for measuring broadcast performance are either inaccurate or inadequate. Fortunately, we have designed an accurate method for measuring broadcast performance, even in a challenging grid environment. Measuring broadcast performance is not easy. Simply sending one broadcast after another allows them to proceed through the network concurrently, thus resulting in inaccurate per broadcast timings. Existing methods either fail to eliminate this pipelining effect or eliminate it by introducing overheads that are as difficult to measure as the performance of the broadcast itself. This problem becomes even more challenging in grid environments. Latencies a long different links can vary significantly. Thus, an algorithm's performance is difficult to predict from it's communication pattern. Even when accurate pre-diction is possible, the pattern is often unknown. Our method introduces a measurable overhead to eliminate the pipelining effect, regardless of variations in link latencies. choose between different available implementations. Also, accurate and complete measurements could guide use of a given implementation to improve application performance. These choices will become even more important as grid-enabled MPI libraries [6, 7] become more common since bad choices are likely to cost significantly more in grid environments. In short, the distributed processing community needs accurate, succinct and complete measurements of collective communications performance. Since successive collective communications can often proceed concurrently, accurately measuring them is difficult. Some benchmarks use knowledge of the communication algorithm to predict the

  8. Aerodynamic Performance Predictions of Single and Twin Jet Afterbodies

    NASA Technical Reports Server (NTRS)

    Carlson, John R.; Pao, S. Paul; Abdol-Hamid, Khaled S.; Jones, William T.

    1995-01-01

    The multiblock three-dimensional Navier-Stokes method PAB3D was utilized by the Component Integration Branch (formerly Propulsion Aerodynamics Branch) at the NASA-Langley Research Center in an international study sponsored by AGARD Working Group #17 for the assessment of the state-of-the-art of propulsion-airframe integration testing techniques and CFD prediction technologies. Three test geometries from ONERA involving fundamental flow physics and four geometries from NASA-LaRC involving realistic flow interactions of wing, body, tail, and jet plumes were chosen by the Working Group. An overview of results on four (1 ONERA and 3 LaRC) of the seven test cases is presented. External static pressures, integrated pressure drag and total drag were calculated for the Langley test cases and jet plume velocity profiles and turbulent viscous stresses were calculated for the ONERA test case. Only selected data from these calculations are presented in this paper. The complete data sets calculated by the participants will be presented in an AGARD summary report. Predicted surface static pressures compared favorably with experimental data for the Langley geometries. Predicted afterbody drag compared well with experiment. Predicted nozzle drag was typically low due to over-compression of the flow near the trailing edge. Total drag was typically high. Predicted jet plume quantities on the ONERA case compared generally well with data.

  9. How accurately can students estimate their performance on an exam and how does this relate to their actual performance on the exam?

    NASA Astrophysics Data System (ADS)

    Rebello, N. Sanjay

    2012-02-01

    Research has shown students' beliefs regarding their own abilities in math and science can influence their performance in these disciplines. I investigated the relationship between students' estimated performance and actual performance on five exams in a second semester calculus-based physics class. Students in a second-semester calculus-based physics class were given about 72 hours after the completion of each of five exams, to estimate their individual and class mean score on each exam. Students were given extra credit worth 1% of the exam points for estimating their score correct within 2% of the actual score and another 1% extra credit for estimating the class mean score within 2% of the correct value. I compared students' individual and mean score estimations with the actual scores to investigate the relationship between estimation accuracies and exam performance of the students as well as trends over the semester.

  10. Holland Type as a Moderator of Personality-Performance Predictions.

    ERIC Educational Resources Information Center

    Fritzsche, Barbara A.; McIntire, Sandra A.; Yost, Amy Powell

    2002-01-01

    Data from 559 undergraduates provided modest evidence that Holland's taxonomy of work environments moderated the relationship between personality and performance. The traits of agreeableness and conscientiousness were better predictors of performance in certain environments. The important relationship between personality and performance may be…

  11. Diagnostic and predictive performance and standardized threshold of traditional biomarkers for drug-induced liver injury in rats.

    PubMed

    Tonomura, Yutaka; Kato, Yuki; Hanafusa, Hiroyuki; Morikawa, Yuji; Matsuyama, Keigo; Uehara, Takeki; Ueno, Motonobu; Torii, Mikinori

    2015-02-01

    Traditional biomarkers such as alanine and aspartate aminotransferase (ALT, AST) and total bilirubin (TBIL) have been widely used for detecting drug-induced liver injury (DILI). Although the Food and Drug Administration (FDA) proposed standardized thresholds for human as Hy's law, those for animals have not been determined, and predictability of these biomarkers for future onset of hepatic lesions remains unclear. In this study, we investigated these diagnostic and predictive performance of 10 traditional biomarkers for liver injury by receiver-operating characteristic (ROC) curve, using a free-access database where 142 hepatotoxic or non-hepatotoxic compounds were administrated to male rats (n=5253). Standardization of each biomarker value was achieved by calculating the ratio to control mean value, and the thresholds were determined under the condition of permitting 5% false positive. Of these 10 biomarkers, AST showed the best diagnostic performance. Furthermore, ALT and TBIL also showed high performance under the situation of hepatocellular necrosis and bile duct injury, respectively. Additionally, the availability of the diagnostic thresholds in difference testing facility was confirmed by the application of these thresholds to in-house prepared dataset. Meanwhile, incorrect diagnosis by the thresholds was also observed. Regarding prediction, all 10 biomarkers showed insufficient performance for future onset of hepatic lesions. In conclusion, the standardized diagnostic thresholds enable consistent evaluation of traditional biomarkers among different facilities, whereas it was suggested that novel biomarker is required for more accurate diagnosis and prediction of DILI.

  12. Accuracy of the actuator disc-RANS approach for predicting the performance and wake of tidal turbines.

    PubMed

    Batten, W M J; Harrison, M E; Bahaj, A S

    2013-02-28

    The actuator disc-RANS model has widely been used in wind and tidal energy to predict the wake of a horizontal axis turbine. The model is appropriate where large-scale effects of the turbine on a flow are of interest, for example, when considering environmental impacts, or arrays of devices. The accuracy of the model for modelling the wake of tidal stream turbines has not been demonstrated, and flow predictions presented in the literature for similar modelled scenarios vary significantly. This paper compares the results of the actuator disc-RANS model, where the turbine forces have been derived using a blade-element approach, to experimental data measured in the wake of a scaled turbine. It also compares the results with those of a simpler uniform actuator disc model. The comparisons show that the model is accurate and can predict up to 94 per cent of the variation in the experimental velocity data measured on the centreline of the wake, therefore demonstrating that the actuator disc-RANS model is an accurate approach for modelling a turbine wake, and a conservative approach to predict performance and loads. It can therefore be applied to similar scenarios with confidence.

  13. Accuracy of the actuator disc-RANS approach for predicting the performance and wake of tidal turbines.

    PubMed

    Batten, W M J; Harrison, M E; Bahaj, A S

    2013-02-28

    The actuator disc-RANS model has widely been used in wind and tidal energy to predict the wake of a horizontal axis turbine. The model is appropriate where large-scale effects of the turbine on a flow are of interest, for example, when considering environmental impacts, or arrays of devices. The accuracy of the model for modelling the wake of tidal stream turbines has not been demonstrated, and flow predictions presented in the literature for similar modelled scenarios vary significantly. This paper compares the results of the actuator disc-RANS model, where the turbine forces have been derived using a blade-element approach, to experimental data measured in the wake of a scaled turbine. It also compares the results with those of a simpler uniform actuator disc model. The comparisons show that the model is accurate and can predict up to 94 per cent of the variation in the experimental velocity data measured on the centreline of the wake, therefore demonstrating that the actuator disc-RANS model is an accurate approach for modelling a turbine wake, and a conservative approach to predict performance and loads. It can therefore be applied to similar scenarios with confidence. PMID:23319711

  14. Predicting Student Performance in a Collaborative Learning Environment

    ERIC Educational Resources Information Center

    Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol

    2015-01-01

    Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…

  15. Academic Performance, Popularity, and Depression Predict Adolescent Substance Use.

    ERIC Educational Resources Information Center

    Diego, Miguel A.; Field, Tiffany M.; Sanders, Christopher E.

    2003-01-01

    Eighty-nine high school seniors completed a questionnaire on their feelings and activities, including their use of drugs. Adolescents with a low grade point average, high popularity, and high depression were more likely to smoke cigarettes, drink alcohol, and smoke marijuana than were their peers. Cigarette and alcohol use predicted marijuana use,…

  16. Predictive Effects of Online Peer Feedback Types on Performance Quality

    ERIC Educational Resources Information Center

    Yu, Fu-Yun; Wu, Chun-Ping

    2013-01-01

    This study examined the individual and combined predictive effects of two types of feedback (i.e., quantitative ratings and descriptive comments) in online peer-assessment learning systems on the quality of produced work. A total of 233 students participated in the study for six weeks. An online learning system that allows students to contribute…

  17. Prediction of performance of centrifugal pumps during starts under pressure

    NASA Technical Reports Server (NTRS)

    Rostafinski, W.

    1969-01-01

    Method which calculates start-up characteristics of centrifugal pumps reveals a capacity to predict pressure drop characteristics of pumps with vaned diffusers. Calculations are based on pump geometry, design-point flow, speed, and pressure rise, and the pump characteristic within range of approximately ten percent of the design-point flow.

  18. Assessing Discriminative Performance at External Validation of Clinical Prediction Models

    PubMed Central

    Nieboer, Daan; van der Ploeg, Tjeerd; Steyerberg, Ewout W.

    2016-01-01

    Introduction External validation studies are essential to study the generalizability of prediction models. Recently a permutation test, focusing on discrimination as quantified by the c-statistic, was proposed to judge whether a prediction model is transportable to a new setting. We aimed to evaluate this test and compare it to previously proposed procedures to judge any changes in c-statistic from development to external validation setting. Methods We compared the use of the permutation test to the use of benchmark values of the c-statistic following from a previously proposed framework to judge transportability of a prediction model. In a simulation study we developed a prediction model with logistic regression on a development set and validated them in the validation set. We concentrated on two scenarios: 1) the case-mix was more heterogeneous and predictor effects were weaker in the validation set compared to the development set, and 2) the case-mix was less heterogeneous in the validation set and predictor effects were identical in the validation and development set. Furthermore we illustrated the methods in a case study using 15 datasets of patients suffering from traumatic brain injury. Results The permutation test indicated that the validation and development set were homogenous in scenario 1 (in almost all simulated samples) and heterogeneous in scenario 2 (in 17%-39% of simulated samples). Previously proposed benchmark values of the c-statistic and the standard deviation of the linear predictors correctly pointed at the more heterogeneous case-mix in scenario 1 and the less heterogeneous case-mix in scenario 2. Conclusion The recently proposed permutation test may provide misleading results when externally validating prediction models in the presence of case-mix differences between the development and validation population. To correctly interpret the c-statistic found at external validation it is crucial to disentangle case-mix differences from incorrect

  19. TankSIM: A Cryogenic Tank Performance Prediction Program

    NASA Technical Reports Server (NTRS)

    Bolshinskiy, L. G.; Hedayat, A.; Hastings, L. J.; Moder, J. P.; Schnell, A. R.; Sutherlin, S. G.

    2015-01-01

    Developed for predicting the behavior of cryogenic liquids inside propellant tanks under various environmental and operating conditions. Provides a multi-node analysis of pressurization, ullage venting and thermodynamic venting systems (TVS) pressure control using axial jet or spray bar TVS. Allows user to combine several different phases for predicting the liquid behavior for the entire flight mission timeline or part of it. Is a NASA in-house code, based on FORTRAN 90-95 and Intel Visual FORTRAN compiler, but can be used on any other platform (Unix-Linux, Compaq Visual FORTRAN, etc.). The last Version 7, released on December 2014, included detailed User's Manual. Includes the use of several RefPROP subroutines for calculating fluid properties.

  20. Work Ethic and Academic Performance: Predicting Citizenship and Counterproductive Behavior

    ERIC Educational Resources Information Center

    Meriac, John P.

    2012-01-01

    In this study, work ethic was examined as a predictor of academic performance, compared with standardized test scores and high school grade point average (GPA). Academic performance was expanded to include student organizational citizenship behavior (OCB) and student counterproductive behavior, comprised of cheating and disengagement, in addition…

  1. Performance Prediction For Multi-Sensor Tracking Systems: Kinematic Accuracy And Data Association Performance

    NASA Astrophysics Data System (ADS)

    Broida, Ted J.

    1990-03-01

    This paper addresses some of the performance issues encountered in the use of multiple sensors for surveillance and tracking in aerospace and defense applications. These problems generally involve detecting the presence of an unknown number of objects of interest (often referred to as "targets"), and estimating their position and motion from periodic measurements (tracking). Measurements zk = z(tk) are received from one or more sensors at times tk and are classified (labelled) as arising either from one of the objects currently being tracked, from a new or previously undetected object, or as a false alarm or clutter. Typically, measurement models involve nonlinear functions of true object kinematics in additive zero-mean white noise, z(tk) = h[x(tk)] n(tk). Estimates of object kinematics (e.g. position, velocity, acceleration) x are formed from each labelled measurement sequence {zk}, with the objective of keeping an accurate and complete awareness of the external environment. In addition to additive measurement noise, a number of uncertainties are present: (1) objects can maneuver between measurements ("random" acceleration), (2) some measurements (threshold crossings) are due to noise alone (false alarms), or due to non-zero-mean interference, with unknown spatial and temporal covariance ("clutter"), and can be misclassified as being from an object of interest, (3) some measurements actually from an object of interest can be misclassified as being from a different object, or as being noise or clutter, (4) object detection is not guaranteed, so that a sensor can "observe" a region containing an object but fail to detect it (PD < 1), whether or not it is being tracked, and (5) there are errors in knowledge of the relative position and attitude of different sensors, particularly if sensors are moving independently (different platforms). The functions of data association (labelling measurements from different sensors, at different times, that corre-spond to the same

  2. A New Submaximal Rowing Test to Predict 2,000-m Rowing Ergometer Performance.

    PubMed

    Otter, Ruby T A; Brink, Michel S; Lamberts, Robert P; Lemmink, Koen A P M

    2015-09-01

    The purpose of this study was to assess predictive value of a new submaximal rowing test (SmRT) on 2,000-m ergometer rowing time-trial performance in competitive rowers. In addition, the reliability of the SmRT was investigated. Twenty-four competitive male rowers participated in this study. After determining individual HRmax, all rowers performed an SmRT followed by a 2,000-m rowing ergometer time trial. In addition, the SmRT was performed 4 times (2 days in between) to determine the reliability. The SmRT consists of two 6-minute stages of rowing at 70 and 80% HRmax, followed by a 3-minute stage at 90% HRmax. Power was captured during the 3 stages, and 60 seconds of heart rate recovery (HRR60s) was measured directly after the third stage. Results showed that predictive value of power during the SmRT on 2,000-m rowing time also increased with stages. CVTEE% is 2.4, 1.9, and 1.3%. Pearson correlations (95% confidence interval [95% CI]) were -0.73 (-0.88 to -0.45), -0.80 (-0.94 to -0.67), and -0.93 (-0.97 to -0.84). 2,000-m rowing time and HRR60s showed no relationship. Reliability of power during the SmRT improved with the increasing intensity of the stages. The coefficient of variation (CVTEM%) was 9.2, 5.6, and 0.4%. Intraclass correlation coefficients (ICC) and 95% CI were 0.91 (0.78-0.97), 0.92 (0.81-0.97), and 0.99 (0.97-1.00). The CVTEM% and ICC of HRR60s were 8.1% and 0.93 (0.82-0.98). In conclusion, the data of this study shows that the SmRT is a reliable test that it is able to accurately predict 2,000-m rowing time on an ergometer. The SmRT is a practical and valuable submaximal test for rowers, which can potentially assist with monitoring, fine-tuning and optimizing training prescription in rowers. PMID:25774627

  3. Thermal Model Predictions of Advanced Stirling Radioisotope Generator Performance

    NASA Technical Reports Server (NTRS)

    Wang, Xiao-Yen J.; Fabanich, William Anthony; Schmitz, Paul C.

    2014-01-01

    This presentation describes the capabilities of three-dimensional thermal power model of advanced stirling radioisotope generator (ASRG). The performance of the ASRG is presented for different scenario, such as Venus flyby with or without the auxiliary cooling system.

  4. Nursing students' confidence in medication calculations predicts math exam performance.

    PubMed

    Andrew, Sharon; Salamonson, Yenna; Halcomb, Elizabeth J

    2009-02-01

    The aim of this study was to examine the psychometric properties, including predictive validity, of the newly-developed nursing self-efficacy for mathematics (NSE-Math). The NSE-Math is a 12 item scale that comprises items related to mathematic and arithmetic concepts underpinning medication calculations. The NSE-Math instrument was administered to second year Bachelor of Nursing students enrolled in a nursing practice subject. Students' academic results for a compulsory medication calculation examination for this subject were collected. One-hundred and twelve students (73%) completed both the NSE-Math instrument and the drug calculation assessment task. The NSE-Math demonstrated two factors 'Confidence in application of mathematic concepts to nursing practice' and 'Confidence in arithmetic concepts' with 63.5% of variance explained. Cronbach alpha for the scale was 0.90. The NSE-Math demonstrated predictive validity with the medication calculation examination results (p=0.009). Psychometric testing suggests the NSE-Math is a valid measure of mathematics self-efficacy of second year nursing students.

  5. Automated Performance Prediction of Message-Passing Parallel Programs

    NASA Technical Reports Server (NTRS)

    Block, Robert J.; Sarukkai, Sekhar; Mehra, Pankaj; Woodrow, Thomas S. (Technical Monitor)

    1995-01-01

    The increasing use of massively parallel supercomputers to solve large-scale scientific problems has generated a need for tools that can predict scalability trends of applications written for these machines. Much work has been done to create simple models that represent important characteristics of parallel programs, such as latency, network contention, and communication volume. But many of these methods still require substantial manual effort to represent an application in the model's format. The NIK toolkit described in this paper is the result of an on-going effort to automate the formation of analytic expressions of program execution time, with a minimum of programmer assistance. In this paper we demonstrate the feasibility of our approach, by extending previous work to detect and model communication patterns automatically, with and without overlapped computations. The predictions derived from these models agree, within reasonable limits, with execution times of programs measured on the Intel iPSC/860 and Paragon. Further, we demonstrate the use of MK in selecting optimal computational grain size and studying various scalability metrics.

  6. Accurate mass analysis of ethanesulfonic acid degradates of acetochlor and alachlor using high-performance liquid chromatography and time-of-flight mass spectrometry

    USGS Publications Warehouse

    Thurman, E.M.; Ferrer, I.; Parry, R.

    2002-01-01

    Degradates of acetochlor and alachlor (ethanesulfonic acids, ESAs) were analyzed in both standards and in a groundwater sample using high-performance liquid chromatography-time-of-flight mass spectrometry with electrospray ionization. The negative pseudomolecular ion of the secondary amide of acetochlor ESA and alachlor ESA gave average masses of 256.0750??0.0049 amu and 270.0786??0.0064 amu respectively. Acetochlor and alachlor ESA gave similar masses of 314.1098??0.0061 amu and 314.1153??0.0048 amu; however, they could not be distinguished by accurate mass because they have the same empirical formula. On the other hand, they may be distinguished using positive-ion electrospray because of different fragmentation spectra, which did not occur using negative-ion electrospray.

  7. Could the deep squat jump predict weightlifting performance?

    PubMed

    Vizcaya, Francisco J; Viana, Oscar; del Olmo, Miguel Fernandez; Acero, Rafael Martin

    2009-05-01

    This research was carried out with the aim of describing the deep squat jump (DSJ) and comparing it with the squat (SJ) and countermovement (CMJ) jumps, to introduce it as a strength testing tool in the monitoring and control of training in strength and power sports. Forty-eight male subjects (21 weightlifters, 12 triathletes, and 15 physical education students) performed 3 trials of DSJ, SJ, and CMJ with a 1-minute rest among them. For the weightlifters, snatch and clean and jerk results during the Spanish Championship 2004 and the 35th EU Championships 2007 were collected to study the relationship among vertical jumps and weightlifters' performance. A 1-way analysis of variance (ANOVA) showed significant differences between groups in the vertical jumps, with the highest jumps for the weightlifters and the lowest for the triathletes. An ANOVA for repeated measures (type of jump) showed better results for DSJ and CMJ than SJ in all groups. A linear regression analysis was performed to determine the association between weightlifting and vertical jump performances. Correlations among the weightlifting performance and the vertical jumps were also calculated and determined using Pearson r. Results have shown that both CMJ and DSJ are strongly correlated with weightlifting ability. Therefore, both measures can be useful for coaches as a strength testing tool in the monitoring and control of training in weightlifting.

  8. What Predicts Changes in Useful Field of View Test Performance?

    PubMed Central

    Lunsman, Melissa; Edwards, Jerri D.; Andel, Ross; Small, Brent J.; Ball, Karlene K.; Roenker, Daniel L.

    2015-01-01

    The Useful Field of View Test (UFOV1) has been used to examine age-related changes in visual processing and cognition and as an indicator of everyday performance outcomes, particularly driving, for over 20 years. How UFOV performance changes with age and what may impact such changes have not previously been investigated longitudinally. Predictors of change in UFOV performance over a five-year period among control-group participants (n = 690) from the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) study were examined. Random effects models were estimated with four-subtest total UFOV as the outcome and baseline age, education, gender, race, visual acuity, depressive symptoms, mental status, and self-rated health, as well as attrition, as predictors. UFOV performance generally followed a curvilinear pattern, improving and then declining over time. Only increased age was consistently related to greater declines in UFOV performance over time. UFOV and WAIS-R Digit Symbol Substitution (DSS), a standard measure of cognitive speed, had similar trajectories of change. The implications of these results are discussed. PMID:19140660

  9. Predicted performance of an integrated modular engine system

    NASA Technical Reports Server (NTRS)

    Binder, Michael; Felder, James L.

    1993-01-01

    Space vehicle propulsion systems are traditionally comprised of a cluster of discrete engines, each with its own set of turbopumps, valves, and a thrust chamber. The Integrated Modular Engine (IME) concept proposes a vehicle propulsion system comprised of multiple turbopumps, valves, and thrust chambers which are all interconnected. The IME concept has potential advantages in fault-tolerance, weight, and operational efficiency compared with the traditional clustered engine configuration. The purpose of this study is to examine the steady-state performance of an IME system with various components removed to simulate fault conditions. An IME configuration for a hydrogen/oxygen expander cycle propulsion system with four sets of turbopumps and eight thrust chambers has been modeled using the Rocket Engine Transient Simulator (ROCETS) program. The nominal steady-state performance is simulated, as well as turbopump thrust chamber and duct failures. The impact of component failures on system performance is discussed in the context of the system's fault tolerant capabilities.

  10. Performance Prediction of Cross-finned Tube Heat Exchangers