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Sample records for achieve accurate predictions

  1. Predicting Achievement and Motivation.

    ERIC Educational Resources Information Center

    Uguroglu, Margaret; Walberg, Herbert J.

    1986-01-01

    Motivation and nine other factors were measured for 970 students in grades five through eight in a study of factors predicting achievement and predicting motivation. Results are discussed. (Author/MT)

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

    ERIC Educational Resources Information Center

    Powell, Erica Dion

    2013-01-01

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

  3. Predict amine solution properties accurately

    SciTech Connect

    Cheng, S.; Meisen, A.; Chakma, A.

    1996-02-01

    Improved process design begins with using accurate physical property data. Especially in the preliminary design stage, physical property data such as density viscosity, thermal conductivity and specific heat can affect the overall performance of absorbers, heat exchangers, reboilers and pump. These properties can also influence temperature profiles in heat transfer equipment and thus control or affect the rate of amine breakdown. Aqueous-amine solution physical property data are available in graphical form. However, it is not convenient to use with computer-based calculations. Developed equations allow improved correlations of derived physical property estimates with published data. Expressions are given which can be used to estimate physical properties of methyldiethanolamine (MDEA), monoethanolamine (MEA) and diglycolamine (DGA) solutions.

  4. Accurate Prediction of Docked Protein Structure Similarity.

    PubMed

    Akbal-Delibas, Bahar; Pomplun, Marc; Haspel, Nurit

    2015-09-01

    One of the major challenges for protein-protein docking methods is to accurately discriminate nativelike structures. The protein docking community agrees on the existence of a relationship between various favorable intermolecular interactions (e.g. Van der Waals, electrostatic, desolvation forces, etc.) and the similarity of a conformation to its native structure. Different docking algorithms often formulate this relationship as a weighted sum of selected terms and calibrate their weights against specific training data to evaluate and rank candidate structures. However, the exact form of this relationship is unknown and the accuracy of such methods is impaired by the pervasiveness of false positives. Unlike the conventional scoring functions, we propose a novel machine learning approach that not only ranks the candidate structures relative to each other but also indicates how similar each candidate is to the native conformation. We trained the AccuRMSD neural network with an extensive dataset using the back-propagation learning algorithm. Our method achieved predicting RMSDs of unbound docked complexes with 0.4Å error margin. PMID:26335807

  5. New model accurately predicts reformate composition

    SciTech Connect

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

    1994-01-31

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

  6. Achieving target voriconazole concentrations more accurately in children and adolescents.

    PubMed

    Neely, Michael; Margol, Ashley; Fu, Xiaowei; van Guilder, Michael; Bayard, David; Schumitzky, Alan; Orbach, Regina; Liu, Siyu; Louie, Stan; Hope, William

    2015-01-01

    Despite the documented benefit of voriconazole therapeutic drug monitoring, nonlinear pharmacokinetics make the timing of steady-state trough sampling and appropriate dose adjustments unpredictable by conventional methods. We developed a nonparametric population model with data from 141 previously richly sampled children and adults. We then used it in our multiple-model Bayesian adaptive control algorithm to predict measured concentrations and doses in a separate cohort of 33 pediatric patients aged 8 months to 17 years who were receiving voriconazole and enrolled in a pharmacokinetic study. Using all available samples to estimate the individual Bayesian posterior parameter values, the median percent prediction bias relative to a measured target trough concentration in the patients was 1.1% (interquartile range, -17.1 to 10%). Compared to the actual dose that resulted in the target concentration, the percent bias of the predicted dose was -0.7% (interquartile range, -7 to 20%). Using only trough concentrations to generate the Bayesian posterior parameter values, the target bias was 6.4% (interquartile range, -1.4 to 14.7%; P = 0.16 versus the full posterior parameter value) and the dose bias was -6.7% (interquartile range, -18.7 to 2.4%; P = 0.15). Use of a sample collected at an optimal time of 4 h after a dose, in addition to the trough concentration, resulted in a nonsignificantly improved target bias of 3.8% (interquartile range, -13.1 to 18%; P = 0.32) and a dose bias of -3.5% (interquartile range, -18 to 14%; P = 0.33). With the nonparametric population model and trough concentrations, our control algorithm can accurately manage voriconazole therapy in children independently of steady-state conditions, and it is generalizable to any drug with a nonparametric pharmacokinetic model. (This study has been registered at ClinicalTrials.gov under registration no. NCT01976078.). PMID:25779580

  7. Achieving Target Voriconazole Concentrations More Accurately in Children and Adolescents

    PubMed Central

    Margol, Ashley; Fu, Xiaowei; van Guilder, Michael; Bayard, David; Schumitzky, Alan; Orbach, Regina; Liu, Siyu; Louie, Stan; Hope, William

    2015-01-01

    Despite the documented benefit of voriconazole therapeutic drug monitoring, nonlinear pharmacokinetics make the timing of steady-state trough sampling and appropriate dose adjustments unpredictable by conventional methods. We developed a nonparametric population model with data from 141 previously richly sampled children and adults. We then used it in our multiple-model Bayesian adaptive control algorithm to predict measured concentrations and doses in a separate cohort of 33 pediatric patients aged 8 months to 17 years who were receiving voriconazole and enrolled in a pharmacokinetic study. Using all available samples to estimate the individual Bayesian posterior parameter values, the median percent prediction bias relative to a measured target trough concentration in the patients was 1.1% (interquartile range, −17.1 to 10%). Compared to the actual dose that resulted in the target concentration, the percent bias of the predicted dose was −0.7% (interquartile range, −7 to 20%). Using only trough concentrations to generate the Bayesian posterior parameter values, the target bias was 6.4% (interquartile range, −1.4 to 14.7%; P = 0.16 versus the full posterior parameter value) and the dose bias was −6.7% (interquartile range, −18.7 to 2.4%; P = 0.15). Use of a sample collected at an optimal time of 4 h after a dose, in addition to the trough concentration, resulted in a nonsignificantly improved target bias of 3.8% (interquartile range, −13.1 to 18%; P = 0.32) and a dose bias of −3.5% (interquartile range, −18 to 14%; P = 0.33). With the nonparametric population model and trough concentrations, our control algorithm can accurately manage voriconazole therapy in children independently of steady-state conditions, and it is generalizable to any drug with a nonparametric pharmacokinetic model. (This study has been registered at ClinicalTrials.gov under registration no. NCT01976078.) PMID:25779580

  8. Predicting accurate probabilities with a ranking loss

    PubMed Central

    Menon, Aditya Krishna; Jiang, Xiaoqian J; Vembu, Shankar; Elkan, Charles; Ohno-Machado, Lucila

    2013-01-01

    In many real-world applications of machine learning classifiers, it is essential to predict the probability of an example belonging to a particular class. This paper proposes a simple technique for predicting probabilities based on optimizing a ranking loss, followed by isotonic regression. This semi-parametric technique offers both good ranking and regression performance, and models a richer set of probability distributions than statistical workhorses such as logistic regression. We provide experimental results that show the effectiveness of this technique on real-world applications of probability prediction. PMID:25285328

  9. Predicting Achievement in Foreign Language.

    ERIC Educational Resources Information Center

    Hart, Mary Elizabeth

    A review of research is inconclusive concerning the relationship between intelligence and language proficiency. A study of 10th grade students (n=35) examined scores on a high school entrance exam and achievement in foreign language after 1 year of study. Both math and reading showed a significant correlation with foreign language achievement; the…

  10. You Can Accurately Predict Land Acquisition Costs.

    ERIC Educational Resources Information Center

    Garrigan, Richard

    1967-01-01

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

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

    DOE PAGESBeta

    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

  12. 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.

  13. 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

  14. 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

  15. Predicting First-Grade Reading Achievement.

    ERIC Educational Resources Information Center

    Busch, Robert F.

    The problem investigated in this study was to determine the best combination of tests or subtests in a research battery which, when administered to beginning first-grade students, would enable the most efficient prediction of reading achievement. A total of 1052 children were randomly selected from first-grade classrooms within the State of…

  16. 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.

  17. Predicting Mathematics Achievement: The Influence of Prior Achievement and Attitudes

    ERIC Educational Resources Information Center

    Hemmings, Brian; Grootenboer, Peter; Kay, Russell

    2011-01-01

    Achievement in mathematics is inextricably linked to future career opportunities, and therefore, understanding those factors that influence achievement is important. This study sought to examine the relationships among attitude towards mathematics, ability and mathematical achievement. This examination was also supported by a focus on gender…

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

    NASA Astrophysics Data System (ADS)

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

    2010-10-01

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

  19. 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

  20. A new generalized correlation for accurate vapor pressure prediction

    NASA Astrophysics Data System (ADS)

    An, Hui; Yang, Wenming

    2012-08-01

    An accurate knowledge of the vapor pressure of organic liquids is very important for the oil and gas processing operations. In combustion modeling, the accuracy of numerical predictions is also highly dependent on the fuel properties such as vapor pressure. In this Letter, a new generalized correlation is proposed based on the Lee-Kesler's method where a fuel dependent parameter 'A' is introduced. The proposed method only requires the input parameters of critical temperature, normal boiling temperature and the acentric factor of the fluid. With this method, vapor pressures have been calculated and compared with the data reported in data compilation for 42 organic liquids over 1366 data points, and the overall average absolute percentage deviation is only 1.95%.

  1. 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

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

    PubMed

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

    2009-04-01

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

  3. Turbulence Models for Accurate Aerothermal Prediction in Hypersonic Flows

    NASA Astrophysics Data System (ADS)

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

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

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

    NASA Astrophysics Data System (ADS)

    Junkin, Gary

    2013-04-01

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

  5. Accurate Prediction of Binding Thermodynamics for DNA on Surfaces

    PubMed Central

    Vainrub, Arnold; Pettitt, B. Montgomery

    2011-01-01

    For DNA mounted on surfaces for microarrays, microbeads and nanoparticles, the nature of the random attachment of oligonucleotide probes to an amorphous surface gives rise to a locally inhomogeneous probe density. These fluctuations of the probe surface density are inherent to all common surface or bead platforms, regardless if they exploit either an attachment of pre-synthesized probes or probes synthesized in situ on the surface. Here, we demonstrate for the first time the crucial role of the probe surface density fluctuations in performance of DNA arrays. We account for the density fluctuations with a disordered two-dimensional surface model and derive the corresponding array hybridization isotherm that includes a counter-ion screened electrostatic repulsion between the assayed DNA and probe array. The calculated melting curves are in excellent agreement with published experimental results for arrays with both pre-synthesized and in-situ synthesized oligonucleotide probes. The approach developed allows one to accurately predict the melting curves of DNA arrays using only the known sequence dependent hybridization enthalpy and entropy in solution and the experimental macroscopic surface density of probes. This opens the way to high precision theoretical design and optimization of probes and primers in widely used DNA array-based high-throughput technologies for gene expression, genotyping, next-generation sequencing, and surface polymerase extension. PMID:21972932

  6. Accurate indel prediction using paired-end short reads

    PubMed Central

    2013-01-01

    Background One of the major open challenges in next generation sequencing (NGS) is the accurate identification of structural variants such as insertions and deletions (indels). Current methods for indel calling assign scores to different types of evidence or counter-evidence for the presence of an indel, such as the number of split read alignments spanning the boundaries of a deletion candidate or reads that map within a putative deletion. Candidates with a score above a manually defined threshold are then predicted to be true indels. As a consequence, structural variants detected in this manner contain many false positives. Results Here, we present a machine learning based method which is able to discover and distinguish true from false indel candidates in order to reduce the false positive rate. Our method identifies indel candidates using a discriminative classifier based on features of split read alignment profiles and trained on true and false indel candidates that were validated by Sanger sequencing. We demonstrate the usefulness of our method with paired-end Illumina reads from 80 genomes of the first phase of the 1001 Genomes Project ( http://www.1001genomes.org) in Arabidopsis thaliana. Conclusion In this work we show that indel classification is a necessary step to reduce the number of false positive candidates. We demonstrate that missing classification may lead to spurious biological interpretations. The software is available at: http://agkb.is.tuebingen.mpg.de/Forschung/SV-M/. PMID:23442375

  7. Predicting Academic Achievement with Cognitive Ability

    ERIC Educational Resources Information Center

    Rohde, Treena Eileen; Thompson, Lee Anne

    2007-01-01

    The purpose of the present study is to explain variation in academic achievement with general cognitive ability and specific cognitive abilities. Grade point average, Wide Range Achievement Test III scores, and SAT scores represented academic achievement. The specific cognitive abilities of interest were: working memory, processing speed, and…

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

    NASA Astrophysics Data System (ADS)

    Taponier, V.; Balu, A.

    2002-01-01

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

  9. 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

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

    PubMed

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

    2016-03-01

    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

  11. School Achievement Strongly Predicts Midlife IQ

    ERIC Educational Resources Information Center

    Spinks, Ruth; Arndt, Stephan; Caspers, Kristin; Yucuis, Rebecca; McKirgan, L. William; Pfalzgraf, Christopher; Waterman, Elijah

    2007-01-01

    The relationship between measures of IQ and standardized school achievement tests is well established at around r~0.5 when the two are measured in close proximity. The current paper examined the stability of this correlation when comparing elementary school achievement (grades 3-8) and midlife IQ. Iowa Adoption Study participants who had…

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

    PubMed

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

    2015-01-01

    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

  13. 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

  14. Predicting genetics achievement in nonmajors college biology

    NASA Astrophysics Data System (ADS)

    Mitchell, Angela; Lawson, Anton E.

    Students enrolled in a non-majors college biology course were pretested to determine their level of intellectual development, degree of field independence, mental capacity, amount of prior genetics knowledge, and amount of fluid intelligence. They were then taught a unit on Mendelian genetics. The only student variables found to not account for a significant amount of variance on a test of reading comprehension and/or a test of genetics achievement was amount of prior genetics knowledge. Developmental level was found to be the most consistent predictor of performance, suggesting that a lack of general hypothetico-deductive reasoning ability is a major factor limiting achievement among these students.

  15. Prediction of Achievement in Clinical Pharmacy Courses

    ERIC Educational Resources Information Center

    Simon, Lee S.

    1978-01-01

    A study sought to identify student characteristics which account for academic achievement in clinical pharmacy courses. Preclinical grade point average was the best predictor. Subscales of the California Personality Inventory and the Myers-Briggs Type Indicator, work experience, sex, and age were the other predictor variables. (SW)

  16. Predicting Undergraduate Music Education Majors' Collegiate Achievement

    ERIC Educational Resources Information Center

    Rohwer, Debbie

    2012-01-01

    In order for teachers to guide students in their preparation to be music majors, it would be useful to know those musical components that best predict overall collegiate success. The purpose of this study was to measure the relationship of predictor variables (Lessons, Music History, Music Theory, and Piano) to collegiate grade point average (GPA)…

  17. Predicting Achievement in Community College Science Students.

    ERIC Educational Resources Information Center

    Dettloff, Janet May

    This study was designed to formulate a predictive equation to identify community college biology students (N=420) who most probably would not succeed in science courses. A College Biology Student Survey (developed for the study), Nelson Denny Reading Test (Form-F), College Guidance Placement (CGP) Arithmetic Test, and An Inventory of Piaget's…

  18. Accurate prediction of helix interactions and residue contacts in membrane proteins.

    PubMed

    Hönigschmid, Peter; Frishman, Dmitrij

    2016-04-01

    Accurate prediction of intra-molecular interactions from amino acid sequence is an important pre-requisite for obtaining high-quality protein models. Over the recent years, remarkable progress in this area has been achieved through the application of novel co-variation algorithms, which eliminate transitive evolutionary connections between residues. In this work we present a new contact prediction method for α-helical transmembrane proteins, MemConP, in which evolutionary couplings are combined with a machine learning approach. MemConP achieves a substantially improved accuracy (precision: 56.0%, recall: 17.5%, MCC: 0.288) compared to the use of either machine learning or co-evolution methods alone. The method also achieves 91.4% precision, 42.1% recall and a MCC of 0.490 in predicting helix-helix interactions based on predicted contacts. The approach was trained and rigorously benchmarked by cross-validation and independent testing on up-to-date non-redundant datasets of 90 and 30 experimental three dimensional structures, respectively. MemConP is a standalone tool that can be downloaded together with the associated training data from http://webclu.bio.wzw.tum.de/MemConP. PMID:26851352

  19. What Specific Preschool Math Skills Predict Later Math Achievement?

    ERIC Educational Resources Information Center

    Nguyen, Tutrang; Watts, Tyler W.; Duncan, Greg J.; Clements, Douglas H.; Sarama, Julie; Wolfe, Christopher B.; Spitler, Mary Elaine

    2015-01-01

    The widespread concern about mathematics achievement has drawn extensive research attention to what skills predict later academic achievement. There is clear and consistent evidence that math achievement at school entry is the strongest predictor of later school success and educational attainment. Early childhood math achievement can thus have…

  20. 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.

  1. How to achieve a predictable basal insulin?

    PubMed

    Kurtzhals, P

    2005-09-01

    The development of insulin analogues over the last two decades have aimed at optimising the pharmacokinetic profile of subcutaneously injected insulin for therapeutic use in diabetes mellitus. Rapid acting analogues were successfully engineered and marketed in the late 1990's. In engineering long-acting analogues it has been a particular challenge to obtain action profiles that would be predictable from day to day in the same person. The most recent approach has been to acylate the insulin molecule with a fatty acid which provides the insulin molecule with a specific affinity for albumin. The first clinically available agent of this type is insulin detemir. Pharmacological studies have shown that reversible albumin binding will protract absorption following subcutaneous injection but still allow the insulin molecule to be recognised by the insulin receptor following dissociation from the carrier protein. Moreover, the molecular features of insulin detemir are attractive in that the molecule can be formulated as a neutral aqueous solution and does not precipitate after injection. Together with an important buffering mechanism effected by plasma albumin binding, this explains a highly significant reduction of within-subject variability of pharmacodynamic response observed in repeat isoglycaemic clamp studies where insulin detemir was compared to other basal insulin products. No safety considerations have been identified in using albumin as an insulin carrier to protract and buffer insulin action. In assessing the clinical attractiveness of insulin analogues, it is furthermore critically important to consider how the molecular modifications impact efficacy and safety. A number of pharmacological studies have shown that insulin detemir overall retains the molecular pharmacological properties of native human insulin, including a physiological balance between metabolic and mitogenic potencies. Taken together, insulin detemir provides an attractive novel approach for

  2. 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. PMID:26594988

  3. High Order Schemes in Bats-R-US for Faster and More Accurate Predictions

    NASA Astrophysics Data System (ADS)

    Chen, Y.; Toth, G.; Gombosi, T. I.

    2014-12-01

    BATS-R-US is a widely used global magnetohydrodynamics model that originally employed second order accurate TVD schemes combined with block based Adaptive Mesh Refinement (AMR) to achieve high resolution in the regions of interest. In the last years we have implemented fifth order accurate finite difference schemes CWENO5 and MP5 for uniform Cartesian grids. Now the high order schemes have been extended to generalized coordinates, including spherical grids and also to the non-uniform AMR grids including dynamic regridding. We present numerical tests that verify the preservation of free-stream solution and high-order accuracy as well as robust oscillation-free behavior near discontinuities. We apply the new high order accurate schemes to both heliospheric and magnetospheric simulations and show that it is robust and can achieve the same accuracy as the second order scheme with much less computational resources. This is especially important for space weather prediction that requires faster than real time code execution.

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

    PubMed

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

    2014-04-30

    Several studies suggest facial affect perception (FAP) deficits in schizophrenia are linked to poorer social functioning. However, whether reduced functioning is associated with inaccurate perception of specific emotional valence or a global FAP impairment remains unclear. The present study examined whether impairment in the perception of specific emotional valences (positive, negative) and neutrality were uniquely associated with social functioning, using a multimodal social functioning battery. A sample of 59 individuals with schizophrenia and 41 controls completed a computerized FAP task, and measures of functional capacity, social competence, and social attainment. Participants also underwent neuropsychological testing and symptom assessment. Regression analyses revealed that only accurately perceiving negative emotions explained significant variance (7.9%) in functional capacity after accounting for neurocognitive function and symptoms. Partial correlations indicated that accurately perceiving anger, in particular, was positively correlated with functional capacity. FAP for positive, negative, or neutral emotions were not related to social competence or social attainment. Our findings were consistent with prior literature suggesting negative emotions are related to functional capacity in schizophrenia. Furthermore, the observed relationship between perceiving anger and performance of everyday living skills is novel and warrants further exploration. PMID:24524947

  5. Towards Accurate Ab Initio Predictions of the Spectrum of Methane

    NASA Technical Reports Server (NTRS)

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

    2001-01-01

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

  6. 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

  7. 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

  8. 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?

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

    DOE PAGESBeta

    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

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

    SciTech Connect

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

    2015-06-04

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

  11. Using the 2 x 2 Framework of Achievement Goals to Predict Achievement Emotions and Academic Performance

    ERIC Educational Resources Information Center

    Putwain, David W.; Sander, Paul; Larkin, Derek

    2013-01-01

    Previous work has established how achievement emotions are related to the trichotomous model of achievement goals, and how they predict academic performance. In our study we examine relations using an additional, mastery-avoidance goal, and whether outcome-focused emotions are predicted by mastery as well as performance goals. Results showed that…

  12. Competence with Fractions Predicts Gains in Mathematics Achievement

    ERIC Educational Resources Information Center

    Bailey, Drew H.; Hoard, Mary K.; Nugent, Lara; Geary, David C.

    2012-01-01

    Competence with fractions predicts later mathematics achievement, but the codevelopmental pattern between fractions knowledge and mathematics achievement is not well understood. We assessed this codevelopment through examination of the cross-lagged relation between a measure of conceptual knowledge of fractions and mathematics achievement in sixth…

  13. 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.

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

    PubMed Central

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

    2013-01-01

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

  15. NMRDSP: an accurate prediction of protein shape strings from NMR chemical shifts and sequence data.

    PubMed

    Mao, Wusong; Cong, Peisheng; Wang, Zhiheng; Lu, Longjian; Zhu, Zhongliang; Li, Tonghua

    2013-01-01

    Shape string is structural sequence and is an extremely important structure representation of protein backbone conformations. Nuclear magnetic resonance chemical shifts give a strong correlation with the local protein structure, and are exploited to predict protein structures in conjunction with computational approaches. Here we demonstrate a novel approach, NMRDSP, which can accurately predict the protein shape string based on nuclear magnetic resonance chemical shifts and structural profiles obtained from sequence data. The NMRDSP uses six chemical shifts (HA, H, N, CA, CB and C) and eight elements of structure profiles as features, a non-redundant set (1,003 entries) as the training set, and a conditional random field as a classification algorithm. For an independent testing set (203 entries), we achieved an accuracy of 75.8% for S8 (the eight states accuracy) and 87.8% for S3 (the three states accuracy). This is higher than only using chemical shifts or sequence data, and confirms that the chemical shift and the structure profile are significant features for shape string prediction and their combination prominently improves the accuracy of the predictor. We have constructed the NMRDSP web server and believe it could be employed to provide a solid platform to predict other protein structures and functions. The NMRDSP web server is freely available at http://cal.tongji.edu.cn/NMRDSP/index.jsp. PMID:24376713

  16. NMRDSP: An Accurate Prediction of Protein Shape Strings from NMR Chemical Shifts and Sequence Data

    PubMed Central

    Mao, Wusong; Cong, Peisheng; Wang, Zhiheng; Lu, Longjian; Zhu, Zhongliang; Li, Tonghua

    2013-01-01

    Shape string is structural sequence and is an extremely important structure representation of protein backbone conformations. Nuclear magnetic resonance chemical shifts give a strong correlation with the local protein structure, and are exploited to predict protein structures in conjunction with computational approaches. Here we demonstrate a novel approach, NMRDSP, which can accurately predict the protein shape string based on nuclear magnetic resonance chemical shifts and structural profiles obtained from sequence data. The NMRDSP uses six chemical shifts (HA, H, N, CA, CB and C) and eight elements of structure profiles as features, a non-redundant set (1,003 entries) as the training set, and a conditional random field as a classification algorithm. For an independent testing set (203 entries), we achieved an accuracy of 75.8% for S8 (the eight states accuracy) and 87.8% for S3 (the three states accuracy). This is higher than only using chemical shifts or sequence data, and confirms that the chemical shift and the structure profile are significant features for shape string prediction and their combination prominently improves the accuracy of the predictor. We have constructed the NMRDSP web server and believe it could be employed to provide a solid platform to predict other protein structures and functions. The NMRDSP web server is freely available at http://cal.tongji.edu.cn/NMRDSP/index.jsp. PMID:24376713

  17. Recommendations for Achieving Accurate Numerical Simulation of Tip Clearance Flows in Transonic Compressor Rotors

    NASA Technical Reports Server (NTRS)

    VanZante, Dale E.; Strazisar, Anthony J.; Wood, Jerry R,; Hathaway, Michael D.; Okiishi, Theodore H.

    2000-01-01

    The tip clearance flows of transonic compressor rotors are important because they have a significant impact on rotor and stage performance. While numerical simulations of these flows are quite sophisticated. they are seldom verified through rigorous comparisons of numerical and measured data because these kinds of measurements are rare in the detail necessary to be useful in high-speed machines. In this paper we compare measured tip clearance flow details (e.g. trajectory and radial extent) with corresponding data obtained from a numerical simulation. Recommendations for achieving accurate numerical simulation of tip clearance flows are presented based on this comparison. Laser Doppler Velocimeter (LDV) measurements acquired in a transonic compressor rotor, NASA Rotor 35, are used. The tip clearance flow field of this transonic rotor was simulated using a Navier-Stokes turbomachinery solver that incorporates an advanced k-epsilon turbulence model derived for flows that are not in local equilibrium. Comparison between measured and simulated results indicates that simulation accuracy is primarily dependent upon the ability of the numerical code to resolve important details of a wall-bounded shear layer formed by the relative motion between the over-tip leakage flow and the shroud wall. A simple method is presented for determining the strength of this shear layer.

  18. 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.

  19. Teachers as Researchers: Does the DRP Predict Student Achievement?

    ERIC Educational Resources Information Center

    Miller, R. Harvey; Pennington, Susan C.

    In order to test claims made regarding the Degrees of Reading Power Test (DRP), a study posed two research questions: (1) How well does the DRP correlate with the more venerable Stanford Achievement Test (SAT)? and (2) How well do these instruments predict students' academic classroom achievement? Three hundred sixty-nine students from two middle…

  20. Predicting Engineering Major Status from Mathematics Achievement and Interest Congruence

    ERIC Educational Resources Information Center

    Leuwerke, Wade C.; Robbins, Steven; Sawyer, Richard; Hovland, Michael

    2004-01-01

    This study proposed that precollege students' standardized mathematics achievement score and the congruence between their occupational interests and engineering tasks would predict their second-year retention in college and the stability of their major. Binary response models were used to predict second-year major status (i.e., continue, transfer…

  1. Competence with fractions predicts gains in mathematics achievement.

    PubMed

    Bailey, Drew H; Hoard, Mary K; Nugent, Lara; Geary, David C

    2012-11-01

    Competence with fractions predicts later mathematics achievement, but the codevelopmental pattern between fractions knowledge and mathematics achievement is not well understood. We assessed this codevelopment through examination of the cross-lagged relation between a measure of conceptual knowledge of fractions and mathematics achievement in sixth and seventh grades (N=212). The cross-lagged effects indicated that performance on the sixth grade fractions concepts measure predicted 1-year gains in mathematics achievement (ß=.14, p<.01), controlling for the central executive component of working memory and intelligence, but sixth grade mathematics achievement did not predict gains on the fractions concepts measure (ß=.03, p>.50). In a follow-up assessment, we demonstrated that measures of fluency with computational fractions significantly predicted seventh grade mathematics achievement above and beyond the influence of fluency in computational whole number arithmetic, performance on number fluency and number line tasks, central executive span, and intelligence. Results provide empirical support for the hypothesis that competence with fractions underlies, in part, subsequent gains in mathematics achievement. PMID:22832199

  2. Achieving accurate simulations of urban impacts on ozone at high resolution

    NASA Astrophysics Data System (ADS)

    Li, J.; Georgescu, M.; Hyde, P.; Mahalov, A.; Moustaoui, M.

    2014-11-01

    The effects of urbanization on ozone levels have been widely investigated over cities primarily located in temperate and/or humid regions. In this study, nested WRF-Chem simulations with a finest grid resolution of 1 km are conducted to investigate ozone concentrations [O3] due to urbanization within cities in arid/semi-arid environments. First, a method based on a shape preserving Monotonic Cubic Interpolation (MCI) is developed and used to downscale anthropogenic emissions from the 4 km resolution 2005 National Emissions Inventory (NEI05) to the finest model resolution of 1 km. Using the rapidly expanding Phoenix metropolitan region as the area of focus, we demonstrate the proposed MCI method achieves ozone simulation results with appreciably improved correspondence to observations relative to the default interpolation method of the WRF-Chem system. Next, two additional sets of experiments are conducted, with the recommended MCI approach, to examine impacts of urbanization on ozone production: (1) the urban land cover is included (i.e., urbanization experiments) and, (2) the urban land cover is replaced with the region’s native shrubland. Impacts due to the presence of the built environment on [O3] are highly heterogeneous across the metropolitan area. Increased near surface [O3] due to urbanization of 10-20 ppb is predominantly a nighttime phenomenon while simulated impacts during daytime are negligible. Urbanization narrows the daily [O3] range (by virtue of increasing nighttime minima), an impact largely due to the region’s urban heat island. Our results demonstrate the importance of the MCI method for accurate representation of the diurnal profile of ozone, and highlight its utility for high-resolution air quality simulations for urban areas.

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

    PubMed Central

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

    2013-01-01

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

  4. Direct pressure monitoring accurately predicts pulmonary vein occlusion during cryoballoon ablation.

    PubMed

    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

  5. Predicting Reading Achievement for the Gifted Upper Grade Student.

    ERIC Educational Resources Information Center

    Osen, Deborah K.

    A study was conducted to determine how well gifted students in grades 4-6 should be reading and whether traditional reading expectancy formulas are useful in predicting reading achievement of gifted students in the upper elementary grades. The total reading scores on the Comprehensive Test of Basic Skills (Form Q2) for 624 fourth and sixth graders…

  6. Preschool Executive Functioning Abilities Predict Early Mathematics Achievement

    ERIC Educational Resources Information Center

    Clark, Caron A. C.; Pritchard, Verena E.; Woodward, Lianne J.

    2010-01-01

    Impairments in executive function have been documented in school-age children with mathematical learning difficulties. However, the utility and specificity of preschool executive function abilities in predicting later mathematical achievement are poorly understood. This study examined linkages between children's developing executive function…

  7. Predicting Student Achievement in Ohio: The Role of Expenditure Distribution

    ERIC Educational Resources Information Center

    De Luca, Barbara M.; Hinshaw, Steven A.

    2013-01-01

    The purpose of this research was to investigate the role of school district expenditures in predicting student achievement in Ohio for the school year 2009-2010. Building upon the concept of the "65 percent solution," the research questions that guided this study were: (1) What percentage of Ohio's school district's operating…

  8. Accurate multimodal probabilistic prediction of conversion to Alzheimer's disease in patients with mild cognitive impairment☆

    PubMed Central

    Young, Jonathan; Modat, Marc; Cardoso, Manuel J.; Mendelson, Alex; Cash, Dave; Ourselin, Sebastien

    2013-01-01

    Accurately identifying the patients that have mild cognitive impairment (MCI) who will go on to develop Alzheimer's disease (AD) will become essential as new treatments will require identification of AD patients at earlier stages in the disease process. Most previous work in this area has centred around the same automated techniques used to diagnose AD patients from healthy controls, by coupling high dimensional brain image data or other relevant biomarker data to modern machine learning techniques. Such studies can now distinguish between AD patients and controls as accurately as an experienced clinician. Models trained on patients with AD and control subjects can also distinguish between MCI patients that will convert to AD within a given timeframe (MCI-c) and those that remain stable (MCI-s), although differences between these groups are smaller and thus, the corresponding accuracy is lower. The most common type of classifier used in these studies is the support vector machine, which gives categorical class decisions. In this paper, we introduce Gaussian process (GP) classification to the problem. This fully Bayesian method produces naturally probabilistic predictions, which we show correlate well with the actual chances of converting to AD within 3 years in a population of 96 MCI-s and 47 MCI-c subjects. Furthermore, we show that GPs can integrate multimodal data (in this study volumetric MRI, FDG-PET, cerebrospinal fluid, and APOE genotype with the classification process through the use of a mixed kernel). The GP approach aids combination of different data sources by learning parameters automatically from training data via type-II maximum likelihood, which we compare to a more conventional method based on cross validation and an SVM classifier. When the resulting probabilities from the GP are dichotomised to produce a binary classification, the results for predicting MCI conversion based on the combination of all three types of data show a balanced accuracy

  9. 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

  10. How Accurately Can We Predict the Melting Points of Drug-like Compounds?

    PubMed Central

    2014-01-01

    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

  11. 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

  12. Discriminant and Criterion-Related Validity of Achievement Goals in Predicting Academic Achievement: A Meta-Analysis

    ERIC Educational Resources Information Center

    Huang, Chiungjung

    2012-01-01

    This study examined the discriminant and criterion-related validity of achievement goals in predicting academic achievement. Analysis of 151 studies yielded 172 independent samples (N = 52,986) with correlations among achievement goals and between achievement goals and academic achievement. The discriminant validity of achievement goals in the 2-,…

  13. Achieving accurate nuetron-multiplicity analysis of metals and oxides with weighted point model equations.

    SciTech Connect

    Burward-Hoy, J. M.; Geist, W. H.; Krick, M. S.; Mayo, D. R.

    2004-01-01

    Neutron multiplicity counting is a technique for the rapid, nondestructive measurement of plutonium mass in pure and impure materials. This technique is very powerful because it uses the measured coincidence count rates to determine the sample mass without requiring a set of representative standards for calibration. Interpreting measured singles, doubles, and triples count rates using the three-parameter standard point model accurately determines plutonium mass, neutron multiplication, and the ratio of ({alpha},n) to spontaneous-fission neutrons (alpha) for oxides of moderate mass. However, underlying standard point model assumptions - including constant neutron energy and constant multiplication throughout the sample - cause significant biases for the mass, multiplication, and alpha in measurements of metal and large, dense oxides.

  14. Incremental validity of emotional intelligence ability in predicting academic achievement.

    PubMed

    Lanciano, Tiziana; Curci, Antonietta

    2014-01-01

    We tested the incremental validity of an ability measure of emotional intelligence (El) in predicting academic achievement in undergraduate students, controlling for cognitive abilities and personality traits. Academic achievement has been conceptualized in terms of the number of exams, grade point average, and study time taken to prepare for each exam. Additionally, gender differences were taken into account in these relationships. Participants filled in the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT), the Raven's Advanced Progressive Matrices, the reduced version of the Eysenck Personality Questionnaire, and academic achievement measures. Results showed that El abilities were positively related to academic achievement indices, such as the number of exams and grade point average; total El ability and the Perceiving branch were negatively associated with the study time spent preparing for exams. Furthermore, El ability adds a percentage of incremental variance with respect to cognitive ability and personality variables in explaining scholastic success. The magnitude of the associations between El abilities and academic achievement measures was generally higher for men than for women. Jointly considered, the present findings support the incremental validity of the MSCEIT and provide positive indications of the importance of El in students' academic development. The helpfulness of El training in the context of academic institutions is discussed. PMID:25603581

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

    PubMed Central

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

    2015-01-01

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

  16. 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

  17. Accurate rotor loads prediction using the FLAP (Force and Loads Analysis Program) dynamics code

    SciTech Connect

    Wright, A.D.; Thresher, R.W.

    1987-10-01

    Accurately predicting wind turbine blade loads and response is very important in predicting the fatigue life of wind turbines. There is a clear need in the wind turbine community for validated and user-friendly structural dynamics codes for predicting blade loads and response. At the Solar Energy Research Institute (SERI), a Force and Loads Analysis Program (FLAP) has been refined and validated and is ready for general use. Currently, FLAP is operational on an IBM-PC compatible computer and can be used to analyze both rigid- and teetering-hub configurations. The results of this paper show that FLAP can be used to accurately predict the deterministic loads for rigid-hub rotors. This paper compares analytical predictions to field test measurements for a three-bladed, upwind turbine with a rigid-hub configuration. The deterministic loads predicted by FLAP are compared with 10-min azimuth averages of blade root flapwise bending moments for different wind speeds. 6 refs., 12 figs., 3 tabs.

  18. Accurate prediction of protein–protein interactions from sequence alignments using a Bayesian method

    PubMed Central

    Burger, Lukas; van Nimwegen, Erik

    2008-01-01

    Accurate and large-scale prediction of protein–protein interactions directly from amino-acid sequences is one of the great challenges in computational biology. Here we present a new Bayesian network method that predicts interaction partners using only multiple alignments of amino-acid sequences of interacting protein domains, without tunable parameters, and without the need for any training examples. We first apply the method to bacterial two-component systems and comprehensively reconstruct two-component signaling networks across all sequenced bacteria. Comparisons of our predictions with known interactions show that our method infers interaction partners genome-wide with high accuracy. To demonstrate the general applicability of our method we show that it also accurately predicts interaction partners in a recent dataset of polyketide synthases. Analysis of the predicted genome-wide two-component signaling networks shows that cognates (interacting kinase/regulator pairs, which lie adjacent on the genome) and orphans (which lie isolated) form two relatively independent components of the signaling network in each genome. In addition, while most genes are predicted to have only a small number of interaction partners, we find that 10% of orphans form a separate class of ‘hub' nodes that distribute and integrate signals to and from up to tens of different interaction partners. PMID:18277381

  19. An accurate modeling, simulation, and analysis tool for predicting and estimating Raman LIDAR system performance

    NASA Astrophysics Data System (ADS)

    Grasso, Robert J.; Russo, Leonard P.; Barrett, John L.; Odhner, Jefferson E.; Egbert, Paul I.

    2007-09-01

    BAE Systems presents the results of a program to model the performance of Raman LIDAR systems for the remote detection of atmospheric gases, air polluting hydrocarbons, chemical and biological weapons, and other molecular species of interest. Our model, which integrates remote Raman spectroscopy, 2D and 3D LADAR, and USAF atmospheric propagation codes permits accurate determination of the performance of a Raman LIDAR system. The very high predictive performance accuracy of our model is due to the very accurate calculation of the differential scattering cross section for the specie of interest at user selected wavelengths. We show excellent correlation of our calculated cross section data, used in our model, with experimental data obtained from both laboratory measurements and the published literature. In addition, the use of standard USAF atmospheric models provides very accurate determination of the atmospheric extinction at both the excitation and Raman shifted wavelengths.

  20. Developmental gains in visuospatial memory predict gains in mathematics achievement.

    PubMed

    Li, Yaoran; Geary, David C

    2013-01-01

    Visuospatial competencies are related to performance in mathematical domains in adulthood, but are not consistently related to mathematics achievement in children. We confirmed the latter for first graders and demonstrated that children who show above average first-to-fifth grade gains in visuospatial memory have an advantage over other children in mathematics. The study involved the assessment of the mathematics and reading achievement of 177 children in kindergarten to fifth grade, inclusive, and their working memory capacity and processing speed in first and fifth grade. Intelligence was assessed in first grade and their second to fourth grade teachers reported on their in-class attentive behavior. Developmental gains in visuospatial memory span (d = 2.4) were larger than gains in the capacity of the central executive (d = 1.6) that in turn were larger than gains in phonological memory span (d = 1.1). First to fifth grade gains in visuospatial memory and in speed of numeral processing predicted end of fifth grade mathematics achievement, as did first grade central executive scores, intelligence, and in-class attentive behavior. The results suggest there are important individual differences in the rate of growth of visuospatial memory during childhood and that these differences become increasingly important for mathematics learning. PMID:23936154

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

    PubMed

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

    2016-02-18

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

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

    PubMed Central

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

    2016-01-01

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

  3. 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

  4. 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.

  5. 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

  6. 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

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

    PubMed Central

    2015-01-01

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

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

    PubMed Central

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

    2016-01-01

    HIV-1 entry into host cells is mediated by interactions between the V3-loop of viral glycoprotein gp120 and chemokine receptor CCR5 or CXCR4, collectively known as HIV-1 coreceptors. Accurate genotypic prediction of coreceptor usage is of significant clinical interest and determination of the factors driving tropism has been the focus of extensive study. We have developed a method based on nonlinear support vector machines to elucidate the interacting residue pairs driving coreceptor usage and provide highly accurate coreceptor usage predictions. Our models utilize centroid-centroid interaction energies from computationally derived structures of the V3-loop:coreceptor complexes as primary features, while additional features based on established rules regarding V3-loop sequences are also investigated. We tested our method on 2455 V3-loop sequences of various lengths and subtypes, and produce a median area under the receiver operator curve of 0.977 based on 500 runs of 10-fold cross validation. Our study is the first to elucidate a small set of specific interacting residue pairs between the V3-loop and coreceptors capable of predicting coreceptor usage with high accuracy across major HIV-1 subtypes. The developed method has been implemented as a web tool named CRUSH, CoReceptor USage prediction for HIV-1, which is available at http://ares.tamu.edu/CRUSH/. PMID:26859389

  9. Highly accurate prediction of emotions surrounding the attacks of September 11, 2001 over 1-, 2-, and 7-year prediction intervals.

    PubMed

    Doré, Bruce P; Meksin, Robert; Mather, Mara; Hirst, William; Ochsner, Kevin N

    2016-06-01

    In the aftermath of a national tragedy, important decisions are predicated on judgments of the emotional significance of the tragedy in the present and future. Research in affective forecasting has largely focused on ways in which people fail to make accurate predictions about the nature and duration of feelings experienced in the aftermath of an event. Here we ask a related but understudied question: can people forecast how they will feel in the future about a tragic event that has already occurred? We found that people were strikingly accurate when predicting how they would feel about the September 11 attacks over 1-, 2-, and 7-year prediction intervals. Although people slightly under- or overestimated their future feelings at times, they nonetheless showed high accuracy in forecasting (a) the overall intensity of their future negative emotion, and (b) the relative degree of different types of negative emotion (i.e., sadness, fear, or anger). Using a path model, we found that the relationship between forecasted and actual future emotion was partially mediated by current emotion and remembered emotion. These results extend theories of affective forecasting by showing that emotional responses to an event of ongoing national significance can be predicted with high accuracy, and by identifying current and remembered feelings as independent sources of this accuracy. (PsycINFO Database Record PMID:27100309

  10. 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

  11. conSSert: Consensus SVM Model for Accurate Prediction of Ordered Secondary Structure.

    PubMed

    Kieslich, Chris A; Smadbeck, James; Khoury, George A; Floudas, Christodoulos A

    2016-03-28

    Accurate prediction of protein secondary structure remains a crucial step in most approaches to the protein-folding problem, yet the prediction of ordered secondary structure, specifically beta-strands, remains a challenge. We developed a consensus secondary structure prediction method, conSSert, which is based on support vector machines (SVM) and provides exceptional accuracy for the prediction of beta-strands with QE accuracy of over 0.82 and a Q2-EH of 0.86. conSSert uses as input probabilities for the three types of secondary structure (helix, strand, and coil) that are predicted by four top performing methods: PSSpred, PSIPRED, SPINE-X, and RAPTOR. conSSert was trained/tested using 4261 protein chains from PDBSelect25, and 8632 chains from PISCES. Further validation was performed using targets from CASP9, CASP10, and CASP11. Our data suggest that poor performance in strand prediction is likely a result of training bias and not solely due to the nonlocal nature of beta-sheet contacts. conSSert is freely available for noncommercial use as a webservice: http://ares.tamu.edu/conSSert/ . PMID:26928531

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

    PubMed Central

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

    2015-01-01

    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. PMID:26713437

  13. Accurate microRNA target prediction correlates with protein repression levels

    PubMed Central

    Maragkakis, Manolis; Alexiou, Panagiotis; Papadopoulos, Giorgio L; Reczko, Martin; Dalamagas, Theodore; Giannopoulos, George; Goumas, George; Koukis, Evangelos; Kourtis, Kornilios; Simossis, Victor A; Sethupathy, Praveen; Vergoulis, Thanasis; Koziris, Nectarios; Sellis, Timos; Tsanakas, Panagiotis; Hatzigeorgiou, Artemis G

    2009-01-01

    Background MicroRNAs are small endogenously expressed non-coding RNA molecules that regulate target gene expression through translation repression or messenger RNA degradation. MicroRNA regulation is performed through pairing of the microRNA to sites in the messenger RNA of protein coding genes. Since experimental identification of miRNA target genes poses difficulties, computational microRNA target prediction is one of the key means in deciphering the role of microRNAs in development and disease. Results DIANA-microT 3.0 is an algorithm for microRNA target prediction which is based on several parameters calculated individually for each microRNA and combines conserved and non-conserved microRNA recognition elements into a final prediction score, which correlates with protein production fold change. Specifically, for each predicted interaction the program reports a signal to noise ratio and a precision score which can be used as an indication of the false positive rate of the prediction. Conclusion Recently, several computational target prediction programs were benchmarked based on a set of microRNA target genes identified by the pSILAC method. In this assessment DIANA-microT 3.0 was found to achieve the highest precision among the most widely used microRNA target prediction programs reaching approximately 66%. The DIANA-microT 3.0 prediction results are available online in a user friendly web server at PMID:19765283

  14. 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.

  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. LOCUSTRA: accurate prediction of local protein structure using a two-layer support vector machine approach.

    PubMed

    Zimmermann, Olav; Hansmann, Ulrich H E

    2008-09-01

    Constraint generation for 3d structure prediction and structure-based database searches benefit from fine-grained prediction of local structure. In this work, we present LOCUSTRA, a novel scheme for the multiclass prediction of local structure that uses two layers of support vector machines (SVM). Using a 16-letter structural alphabet from de Brevern et al. (Proteins: Struct., Funct., Bioinf. 2000, 41, 271-287), we assess its prediction ability for an independent test set of 222 proteins and compare our method to three-class secondary structure prediction and direct prediction of dihedral angles. The prediction accuracy is Q16=61.0% for the 16 classes of the structural alphabet and Q3=79.2% for a simple mapping to the three secondary classes helix, sheet, and coil. We achieve a mean phi(psi) error of 24.74 degrees (38.35 degrees) and a median RMSDA (root-mean-square deviation of the (dihedral) angles) per protein chain of 52.1 degrees. These results compare favorably with related approaches. The LOCUSTRA web server is freely available to researchers at http://www.fz-juelich.de/nic/cbb/service/service.php. PMID:18763837

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

    PubMed

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

    2015-07-01

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

  18. 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

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

  1. 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.

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

    DOE PAGESBeta

    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

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

    NASA Technical Reports Server (NTRS)

    Tamma, Kumar K.; Railkar, Sudhir B.

    1988-01-01

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

  4. 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.

  5. Viewing men's faces does not lead to accurate predictions of trustworthiness

    PubMed Central

    Efferson, Charles; Vogt, Sonja

    2013-01-01

    The evolution of cooperation requires some mechanism that reduces the risk of exploitation for cooperative individuals. Recent studies have shown that men with wide faces are anti-social, and they are perceived that way by others. This suggests that people could use facial width to identify anti-social men and thus limit the risk of exploitation. To see if people can make accurate inferences like this, we conducted a two-part experiment. First, males played a sequential social dilemma, and we took photographs of their faces. Second, raters then viewed these photographs and guessed how second movers behaved. Raters achieved significant accuracy by guessing that second movers exhibited reciprocal behaviour. Raters were not able to use the photographs to further improve accuracy. Indeed, some raters used the photographs to their detriment; they could have potentially achieved greater accuracy and earned more money by ignoring the photographs and assuming all second movers reciprocate. PMID:23308340

  6. Accurate Structure Prediction and Conformational Analysis of Cyclic Peptides with Residue-Specific Force Fields.

    PubMed

    Geng, Hao; Jiang, Fan; Wu, Yun-Dong

    2016-05-19

    Cyclic peptides (CPs) are promising candidates for drugs, chemical biology tools, and self-assembling nanomaterials. However, the development of reliable and accurate computational methods for their structure prediction has been challenging. Here, 20 all-trans CPs of 5-12 residues selected from Cambridge Structure Database have been simulated using replica-exchange molecular dynamics with four different force fields. Our recently developed residue-specific force fields RSFF1 and RSFF2 can correctly identify the crystal-like conformations of more than half CPs as the most populated conformation. The RSFF2 performs the best, which consistently predicts the crystal structures of 17 out of 20 CPs with rmsd < 1.1 Å. We also compared the backbone (ϕ, ψ) sampling of residues in CPs with those in short linear peptides and in globular proteins. In general, unlike linear peptides, CPs have local conformational free energies and entropies quite similar to globular proteins. PMID:27128113

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

    PubMed Central

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

    2016-01-01

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

  8. Accurate First-Principles Spectra Predictions for Ethylene and its Isotopologues from Full 12D AB Initio Surfaces

    NASA Astrophysics Data System (ADS)

    Delahaye, Thibault; Rey, Michael; Tyuterev, Vladimir; Nikitin, Andrei V.; Szalay, Peter

    2015-06-01

    Hydrocarbons such as ethylene (C_2H_4) and methane (CH_4) are of considerable interest for the modeling of planetary atmospheres and other astrophysical applications. Knowledge of rovibrational transitions of hydrocarbons is of primary importance in many fields but remains a formidable challenge for the theory and spectral analysis. Essentially two theoretical approaches for the computation and prediction of spectra exist. The first one is based on empirically-fitted effective spectroscopic models. Several databases aim at collecting the corresponding data but the information about C_2H_4 spectrum present in these databases remains limited, only some spectral ranges around 1000, 3000 and 6000 cm-1 being available. Another way for computing energies, line positions and intensities is based on global variational calculations using ab initio surfaces. Although they do not yet reach the spectroscopic accuracy, they could 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 two necessary ingredients: (i) accurate intramolecular potential energy surface and dipole moment surface components and (ii) efficient computational methods to achieve a good numerical convergence. We report predictions of vibrational and rovibrational energy levels of C_2H_4 using our new ground state potential energy surface obtained from extended ab initio calculations. Additionally we will introduce line positions and line intensities predictions based on a new dipole moment surface for ethylene. These results will be compared with previous works on ethylene and its isotopologues.

  9. 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

  10. Base-resolution methylation patterns accurately predict transcription factor bindings in vivo

    PubMed Central

    Xu, Tianlei; Li, Ben; Zhao, Meng; Szulwach, Keith E.; Street, R. Craig; Lin, Li; Yao, Bing; Zhang, Feiran; Jin, Peng; Wu, Hao; Qin, Zhaohui S.

    2015-01-01

    Detecting in vivo transcription factor (TF) binding is important for understanding gene regulatory circuitries. ChIP-seq is a powerful technique to empirically define TF binding in vivo. However, the multitude of distinct TFs makes genome-wide profiling for them all labor-intensive and costly. Algorithms for in silico prediction of TF binding have been developed, based mostly on histone modification or DNase I hypersensitivity data in conjunction with DNA motif and other genomic features. However, technical limitations of these methods prevent them from being applied broadly, especially in clinical settings. We conducted a comprehensive survey involving multiple cell lines, TFs, and methylation types and found that there are intimate relationships between TF binding and methylation level changes around the binding sites. Exploiting the connection between DNA methylation and TF binding, we proposed a novel supervised learning approach to predict TF–DNA interaction using data from base-resolution whole-genome methylation sequencing experiments. We devised beta-binomial models to characterize methylation data around TF binding sites and the background. Along with other static genomic features, we adopted a random forest framework to predict TF–DNA interaction. After conducting comprehensive tests, we saw that the proposed method accurately predicts TF binding and performs favorably versus competing methods. PMID:25722376

  11. A fast but accurate excitonic simulation of the electronic circular dichroism of nucleic acids: how can it be achieved?

    PubMed

    Loco, Daniele; Jurinovich, Sandro; Di Bari, Lorenzo; Mennucci, Benedetta

    2016-01-14

    We present and discuss a simple and fast computational approach to the calculation of electronic circular dichroism spectra of nucleic acids. It is based on a exciton model in which the couplings are obtained in terms of the full transition-charge distributions, as resulting from TDDFT methods applied on the individual nucleobases. We validated the method on two systems, a DNA G-quadruplex and a RNA β-hairpin whose solution structures have been accurately determined by means of NMR. We have shown that the different characteristics of composition and structure of the two systems can lead to quite important differences in the dependence of the accuracy of the simulation on the excitonic parameters. The accurate reproduction of the CD spectra together with their interpretation in terms of the excitonic composition suggest that this method may lend itself as a general computational tool to both predict the spectra of hypothetic structures and define clear relationships between structural and ECD properties. PMID:26646952

  12. Prediction of Music Achievement in the Elementary School.

    ERIC Educational Resources Information Center

    Hedden, Steven K.

    1982-01-01

    Reports results of a study which examined predictors of music achievement for general music students in the upper elementary grades. Predictors examined were attitude toward music, self-concept in music, music background, academic achievement, and gender. (RM)

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

    NASA Astrophysics Data System (ADS)

    Garrison, Stephen L.

    2005-07-01

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

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

    PubMed

    Shvab, I; Sadus, Richard J

    2013-11-21

    The ability of intermolecular potentials to correctly predict the thermodynamic properties of liquid water at a density of 0.998 g∕cm(3) for a wide range of temperatures (298-650 K) and pressures (0.1-700 MPa) is investigated. Molecular dynamics simulations are reported for the pressure, thermal pressure coefficient, thermal expansion coefficient, isothermal and adiabatic compressibilities, isobaric and isochoric heat capacities, and Joule-Thomson coefficient of liquid water using the non-polarizable SPC∕E and TIP4P∕2005 potentials. The results are compared with both experiment data and results obtained from the ab initio-based Matsuoka-Clementi-Yoshimine non-additive (MCYna) [J. Li, Z. Zhou, and R. J. Sadus, J. Chem. Phys. 127, 154509 (2007)] potential, which includes polarization contributions. The data clearly indicate that both the SPC∕E and TIP4P∕2005 potentials are only in qualitative agreement with experiment, whereas the polarizable MCYna potential predicts some properties within experimental uncertainty. This highlights the importance of polarizability for the accurate prediction of the thermodynamic properties of water, particularly at temperatures beyond 298 K. PMID:24320337

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

    NASA Astrophysics Data System (ADS)

    Shvab, I.; Sadus, Richard J.

    2013-11-01

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

  16. 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.

  17. Towards first-principles based prediction of highly accurate electrochemical Pourbiax diagrams

    NASA Astrophysics Data System (ADS)

    Zeng, Zhenhua; Chan, Maria; Greeley, Jeff

    2015-03-01

    Electrochemical Pourbaix diagrams lie at the heart of aqueous electrochemical processes and are central to the identification of stable phases of metals for processes ranging from electrocatalysis to corrosion. Even though standard DFT calculations are potentially powerful tools for the prediction of such Pourbaix diagrams, inherent errors in the description of strongly-correlated transition metal (hydr)oxides, together with neglect of weak van der Waals (vdW) interactions, has limited the reliability of the predictions for even the simplest bulk systems; corresponding predictions for more complex alloy or surface structures are even more challenging . Through introduction of a Hubbard U correction, employment of a state-of-the-art van der Waals functional, and use of pure water as a reference state for the calculations, these errors are systematically corrected. The strong performance is illustrated on a series of bulk transition metal (Mn, Fe, Co and Ni) hydroxide, oxyhydroxide, binary and ternary oxides where the corresponding thermodynamics of oxidation and reduction can be accurately described with standard errors of less than 0.04 eV in comparison with experiment.

  18. 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.

  19. 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

  20. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

    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 -2Yℓm waveform modes resolved by the NR code up to ℓ=8 . We compare our surrogate model to effective one body waveforms from 50 M⊙ to 300 M⊙ for advanced LIGO detectors and find that the surrogate is always more faithful (by at least an order of magnitude in most cases).

  2. 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.

  3. 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)

  4. Predicting Student Achievement and Attrition in a Proprietary Technical College.

    ERIC Educational Resources Information Center

    Taube, Sylvia R.; Taube, Paul M.

    1991-01-01

    Analysis of data on 101 entering proprietary college students found that (1) predictors of initial achievement were entrance exam scores, gender, race, age, grade point average, and expectations; (2) dropout predictors were marital status, work hours, prior achievement, absences, and faculty interaction; and (3) age, gender, race, and children did…

  5. 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

  6. A novel approach for accurate prediction of spontaneous passage of ureteral stones: support vector machines.

    PubMed

    Dal Moro, F; Abate, A; Lanckriet, G R G; Arandjelovic, G; Gasparella, P; Bassi, P; Mancini, M; Pagano, F

    2006-01-01

    The objective of this study was to optimally predict the spontaneous passage of ureteral stones in patients with renal colic by applying for the first time support vector machines (SVM), an instance of kernel methods, for classification. After reviewing the results found in the literature, we compared the performances obtained with logistic regression (LR) and accurately trained artificial neural networks (ANN) to those obtained with SVM, that is, the standard SVM, and the linear programming SVM (LP-SVM); the latter techniques show an improved performance. Moreover, we rank the prediction factors according to their importance using Fisher scores and the LP-SVM feature weights. A data set of 1163 patients affected by renal colic has been analyzed and restricted to single out a statistically coherent subset of 402 patients. Nine clinical factors are used as inputs for the classification algorithms, to predict one binary output. The algorithms are cross-validated by training and testing on randomly selected train- and test-set partitions of the data and reporting the average performance on the test sets. The SVM-based approaches obtained a sensitivity of 84.5% and a specificity of 86.9%. The feature ranking based on LP-SVM gives the highest importance to stone size, stone position and symptom duration before check-up. We propose a statistically correct way of employing LR, ANN and SVM for the prediction of spontaneous passage of ureteral stones in patients with renal colic. SVM outperformed ANN, as well as LR. This study will soon be translated into a practical software toolbox for actual clinical usage. PMID:16374437

  7. Predicting Mathematics Achievement by Motivation and Self-Efficacy across Gender and Achievement Levels

    ERIC Educational Resources Information Center

    Sartawi, AbdelAziz; Alsawaie, Othman N.; Dodeen, Hamzeh; Tibi, Sana; Alghazo, Iman M.

    2012-01-01

    This study investigated the extent to which self-efficacy and motivation served as a predictor for mathematics achievement of fifth grade students in United Arab Emirates (UAE) across gender and achievement levels. Self-efficacy was measured by two scales, which differed in levels of specificity--Category Specific and Task Specific. Motivation was…

  8. 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.

  9. 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

  10. Can CO2 assimilation in maize leaves be predicted accurately from chlorophyll fluorescence analysis?

    PubMed

    Edwards, G E; Baker, N R

    1993-08-01

    Analysis is made of the energetics of CO2 fixation, the photochemical quantum requirement per CO2 fixed, and sinks for utilising reductive power in the C4 plant maize. CO2 assimilation is the primary sink for energy derived from photochemistry, whereas photorespiration and nitrogen assimilation are relatively small sinks, particularly in developed leaves. Measurement of O2 exchange by mass spectrometry and CO2 exchange by infrared gas analysis under varying levels of CO2 indicate that there is a very close relationship between the true rate of O2 evolution from PS II and the net rate of CO2 fixation. Consideration is given to measurements of the quantum yields of PS II (φ PS II) from fluorescence analysis and of CO2 assimilation ([Formula: see text]) in maize over a wide range of conditions. The[Formula: see text] ratio was found to remain reasonably constant (ca. 12) over a range of physiological conditions in developed leaves, with varying temperature, CO2 concentrations, light intensities (from 5% to 100% of full sunlight), and following photoinhibition under high light and low temperature. A simple model for predicting CO2 assimilation from fluorescence parameters is presented and evaluated. It is concluded that under a wide range of conditions fluorescence parameters can be used to predict accurately and rapidly CO2 assimilation rates in maize. PMID:24317706

  11. 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

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed Central

    Faraggi, Eshel; Zhou, Yaoqi; Kloczkowski, Andrzej

    2014-01-01

    We present a new approach for predicting the Accessible Surface Area (ASA) using a General Neural Network (GENN). The novelty of the new approach lies in not using residue mutation profiles generated by multiple sequence alignments as descriptive inputs. Instead we use solely sequential window information and global features such as single-residue and two-residue compositions of the chain. The resulting predictor is both highly more efficient than sequence alignment based predictors and of comparable accuracy to them. Introduction of the global inputs significantly helps achieve this comparable accuracy. The predictor, termed ASAquick, is tested on predicting the ASA of globular proteins and found to perform similarly well for so-called easy and hard cases indicating generalizability and possible usability for de-novo protein structure prediction. The source code and a Linux executables for GENN and ASAquick are available from Research and Information Systems at http://mamiris.com, from the SPARKS Lab at http://sparks-lab.org, and from the Battelle Center for Mathematical Medicine at http://mathmed.org. PMID:25204636

  14. 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

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

    PubMed

    Ludlow, Lindsay W; Weyand, Peter G

    2016-03-01

    Accurate prediction of the metabolic energy that walking requires can inform numerous health, bodily status, and fitness outcomes. We adopted a two-step approach to identifying a concise, generalized equation for predicting level human walking metabolism. Using literature-aggregated values we compared 1) the predictive accuracy of three literature equations: American College of Sports Medicine (ACSM), Pandolf et al., and Height-Weight-Speed (HWS); and 2) the goodness-of-fit possible from one- vs. two-component descriptions of walking metabolism. Literature metabolic rate values (n = 127; speed range = 0.4 to 1.9 m/s) were aggregated from 25 subject populations (n = 5-42) whose means spanned a 1.8-fold range of heights and a 4.2-fold range of weights. Population-specific resting metabolic rates (V̇o2 rest) were determined using standardized equations. Our first finding was that the ACSM and Pandolf et al. equations underpredicted nearly all 127 literature-aggregated values. Consequently, their standard errors of estimate (SEE) were nearly four times greater than those of the HWS equation (4.51 and 4.39 vs. 1.13 ml O2·kg(-1)·min(-1), respectively). For our second comparison, empirical best-fit relationships for walking metabolism were derived from the data set in one- and two-component forms for three V̇o2-speed model types: linear (∝V(1.0)), exponential (∝V(2.0)), and exponential/height (∝V(2.0)/Ht). We found that the proportion of variance (R(2)) accounted for, when averaged across the three model types, was substantially lower for one- vs. two-component versions (0.63 ± 0.1 vs. 0.90 ± 0.03) and the predictive errors were nearly twice as great (SEE = 2.22 vs. 1.21 ml O2·kg(-1)·min(-1)). Our final analysis identified the following concise, generalized equation for predicting level human walking metabolism: V̇o2 total = V̇o2 rest + 3.85 + 5.97·V(2)/Ht (where V is measured in m/s, Ht in meters, and V̇o2 in ml O2·kg(-1)·min(-1)). PMID:26679617

  16. 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

  17. 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.

  18. Do Creativity Self-Beliefs Predict Literacy Achievement and Motivation?

    ERIC Educational Resources Information Center

    Putwain, David W.; Kearsley, Rebecca; Symes, Wendy

    2012-01-01

    Previous work has suggested that creativity self-beliefs show only small relations with academic achievement and may only be related to intrinsic, not extrinsic motivation. We set out to re-examine these relationships accounting for the multifaceted and process embedded nature of creativity self-beliefs and the full domain range of extrinsic…

  19. The Prediction, from Infancy, of Adult IQ and Achievement

    ERIC Educational Resources Information Center

    Fagan, Joseph F.; Holland, Cynthia R.; Wheeler, Karyn

    2007-01-01

    Young adults, originally tested as infants for their ability to process information as measured by selective attention to novelty (an operational definition of visual recognition memory), were revisited. A current estimate of IQ was obtained as well as a measure of academic achievement. Information processing ability at 6-12 months was predictive…

  20. Do Intelligence and Sustained Attention Interact in Predicting Academic Achievement?

    ERIC Educational Resources Information Center

    Steinmayr, Ricarda; Ziegler, Mattias; Trauble, Birgit

    2010-01-01

    Research in clinical samples suggests that the relationship between intelligence and academic achievement might be moderated by sustained attention. The present study aimed to explore whether this interaction could be observed in a non-clinical sample. We investigated a sample of 11th and 12th grade students (N = 231). An overall performance score…

  1. Longitudinal Prediction of School Achievement for Metis and Eskimo Pupils.

    ERIC Educational Resources Information Center

    MacArthur, R.S.

    Research in this effort attempted to review evidence of the construct validity of certain measures of intellectual potential for Canadian native pupils, and to examine the relative predictive validity, over a four-year period, of several measures of general intellectual ability for a sample of Metis pupils at Faust, Alberta, and 2 samples of…

  2. The Prediction of Reading Achievement in Grade One.

    ERIC Educational Resources Information Center

    Morrison, James B., Jr.

    The purpose of this study was to devise a simple instrument that could be helpful in predicting reading success by classroom teachers and school administrators who are not experts in the field of reading. The subjects, 190 randomly selected first graders, were given "Alphabet" and "Numbers" of the Metropolitan Readiness Tests and "Information" and…

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

    PubMed Central

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

    2015-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Baker, A. J.

    1978-01-01

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

  5. 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

  6. More accurate predictions with transonic Navier-Stokes methods through improved turbulence modeling

    NASA Technical Reports Server (NTRS)

    Johnson, Dennis A.

    1989-01-01

    Significant improvements in predictive accuracies for off-design conditions are achievable through better turbulence modeling; and, without necessarily adding any significant complication to the numerics. One well established fact about turbulence is it is slow to respond to changes in the mean strain field. With the 'equilibrium' algebraic turbulence models no attempt is made to model this characteristic and as a consequence these turbulence models exaggerate the turbulent boundary layer's ability to produce turbulent Reynolds shear stresses in regions of adverse pressure gradient. As a consequence, too little momentum loss within the boundary layer is predicted in the region of the shock wave and along the aft part of the airfoil where the surface pressure undergoes further increases. Recently, a 'nonequilibrium' algebraic turbulence model was formulated which attempts to capture this important characteristic of turbulence. This 'nonequilibrium' algebraic model employs an ordinary differential equation to model the slow response of the turbulence to changes in local flow conditions. In its original form, there was some question as to whether this 'nonequilibrium' model performed as well as the 'equilibrium' models for weak interaction cases. However, this turbulence model has since been further improved wherein it now appears that this turbulence model performs at least as well as the 'equilibrium' models for weak interaction cases and for strong interaction cases represents a very significant improvement. The performance of this turbulence model relative to popular 'equilibrium' models is illustrated for three airfoil test cases of the 1987 AIAA Viscous Transonic Airfoil Workshop, Reno, Nevada. A form of this 'nonequilibrium' turbulence model is currently being applied to wing flows for which similar improvements in predictive accuracy are being realized.

  7. 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

  8. 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.

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

    PubMed

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

    2016-05-01

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

  10. Predicting Achievable Fundamental Frequency Ranges in Vocalization Across Species.

    PubMed

    Titze, Ingo; Riede, Tobias; Mau, Ted

    2016-06-01

    Vocal folds are used as sound sources in various species, but it is unknown how vocal fold morphologies are optimized for different acoustic objectives. Here we identify two main variables affecting range of vocal fold vibration frequency, namely vocal fold elongation and tissue fiber stress. A simple vibrating string model is used to predict fundamental frequency ranges across species of different vocal fold sizes. While average fundamental frequency is predominantly determined by vocal fold length (larynx size), range of fundamental frequency is facilitated by (1) laryngeal muscles that control elongation and by (2) nonlinearity in tissue fiber tension. One adaptation that would increase fundamental frequency range is greater freedom in joint rotation or gliding of two cartilages (thyroid and cricoid), so that vocal fold length change is maximized. Alternatively, tissue layers can develop to bear a disproportionate fiber tension (i.e., a ligament with high density collagen fibers), increasing the fundamental frequency range and thereby vocal versatility. The range of fundamental frequency across species is thus not simply one-dimensional, but can be conceptualized as the dependent variable in a multi-dimensional morphospace. In humans, this could allow for variations that could be clinically important for voice therapy and vocal fold repair. Alternative solutions could also have importance in vocal training for singing and other highly-skilled vocalizations. PMID:27309543

  11. Predicting Achievable Fundamental Frequency Ranges in Vocalization Across Species

    PubMed Central

    Titze, Ingo; Riede, Tobias; Mau, Ted

    2016-01-01

    Vocal folds are used as sound sources in various species, but it is unknown how vocal fold morphologies are optimized for different acoustic objectives. Here we identify two main variables affecting range of vocal fold vibration frequency, namely vocal fold elongation and tissue fiber stress. A simple vibrating string model is used to predict fundamental frequency ranges across species of different vocal fold sizes. While average fundamental frequency is predominantly determined by vocal fold length (larynx size), range of fundamental frequency is facilitated by (1) laryngeal muscles that control elongation and by (2) nonlinearity in tissue fiber tension. One adaptation that would increase fundamental frequency range is greater freedom in joint rotation or gliding of two cartilages (thyroid and cricoid), so that vocal fold length change is maximized. Alternatively, tissue layers can develop to bear a disproportionate fiber tension (i.e., a ligament with high density collagen fibers), increasing the fundamental frequency range and thereby vocal versatility. The range of fundamental frequency across species is thus not simply one-dimensional, but can be conceptualized as the dependent variable in a multi-dimensional morphospace. In humans, this could allow for variations that could be clinically important for voice therapy and vocal fold repair. Alternative solutions could also have importance in vocal training for singing and other highly-skilled vocalizations. PMID:27309543

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

    PubMed

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

    2014-01-01

    Protein structure prediction is critical to functional annotation of the massively accumulated biological sequences, which prompts an imperative need for the development of high-throughput technologies. As a first and key step in protein structure prediction, protein structural class prediction becomes an increasingly challenging task. Amongst most homological-based approaches, the accuracies of protein structural class prediction are sufficiently high for high similarity datasets, but still far from being satisfactory for low similarity datasets, i.e., below 40% in pairwise sequence similarity. Therefore, we present a novel method for accurate and reliable protein structural class prediction for both high and low similarity datasets. This method is based on Support Vector Machine (SVM) in conjunction with integrated features from position-specific score matrix (PSSM), PROFEAT and Gene Ontology (GO). A feature selection approach, SVM-RFE, is also used to rank the integrated feature vectors through recursively removing the feature with the lowest ranking score. The definitive top features selected by SVM-RFE are input into the SVM engines to predict the structural class of a query protein. To validate our method, jackknife tests were applied to seven widely used benchmark datasets, reaching overall accuracies between 84.61% and 99.79%, which are significantly higher than those achieved by state-of-the-art tools. These results suggest that our method could serve as an accurate and cost-effective alternative to existing methods in protein structural classification, especially for low similarity datasets. PMID:24675610

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

    PubMed

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

    2015-09-30

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

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

    PubMed Central

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  17. 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

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

    PubMed

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

    2016-03-21

    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

  19. Sensor Data Fusion for Accurate Cloud Presence Prediction Using Dempster-Shafer Evidence Theory

    PubMed Central

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

    2010-01-01

    Sensor data fusion technology can be used to best extract useful information from multiple sensor observations. It has been widely applied in various applications such as target tracking, surveillance, robot navigation, signal and image processing. This paper introduces a novel data fusion approach in a multiple radiation sensor environment using Dempster-Shafer evidence theory. The methodology is used to predict cloud presence based on the inputs of radiation sensors. Different radiation data have been used for the cloud prediction. The potential application areas of the algorithm include renewable power for virtual power station where the prediction of cloud presence is the most challenging issue for its photovoltaic output. The algorithm is validated by comparing the predicted cloud presence with the corresponding sunshine occurrence data that were recorded as the benchmark. Our experiments have indicated that comparing to the approaches using individual sensors, the proposed data fusion approach can increase correct rate of cloud prediction by ten percent, and decrease unknown rate of cloud prediction by twenty three percent. PMID:22163414

  20. DISPLAR: an accurate method for predicting DNA-binding sites on protein surfaces

    PubMed Central

    Tjong, Harianto; Zhou, Huan-Xiang

    2007-01-01

    Structural and physical properties of DNA provide important constraints on the binding sites formed on surfaces of DNA-targeting proteins. Characteristics of such binding sites may form the basis for predicting DNA-binding sites from the structures of proteins alone. Such an approach has been successfully developed for predicting protein–protein interface. Here this approach is adapted for predicting DNA-binding sites. We used a representative set of 264 protein–DNA complexes from the Protein Data Bank to analyze characteristics and to train and test a neural network predictor of DNA-binding sites. The input to the predictor consisted of PSI-blast sequence profiles and solvent accessibilities of each surface residue and 14 of its closest neighboring residues. Predicted DNA-contacting residues cover 60% of actual DNA-contacting residues and have an accuracy of 76%. This method significantly outperforms previous attempts of DNA-binding site predictions. Its application to the prion protein yielded a DNA-binding site that is consistent with recent NMR chemical shift perturbation data, suggesting that it can complement experimental techniques in characterizing protein–DNA interfaces. PMID:17284455

  1. Using complete genome comparisons to identify sequences whose presence accurately predicts clinically important phenotypes.

    PubMed

    Hall, Barry G; Cardenas, Heliodoro; Barlow, Miriam

    2013-01-01

    In clinical settings it is often important to know not just the identity of a microorganism, but also the danger posed by that particular strain. For instance, Escherichia coli can range from being a harmless commensal to being a very dangerous enterohemorrhagic (EHEC) strain. Determining pathogenic phenotypes can be both time consuming and expensive. Here we propose a simple, rapid, and inexpensive method of predicting pathogenic phenotypes on the basis of the presence or absence of short homologous DNA segments in an isolate. Our method compares completely sequenced genomes without the necessity of genome alignments in order to identify the presence or absence of the segments to produce an automatic alignment of the binary string that describes each genome. Analysis of the segment alignment allows identification of those segments whose presence strongly predicts a phenotype. Clinical application of the method requires nothing more that PCR amplification of each of the set of predictive segments. Here we apply the method to identifying EHEC strains of E. coli and to distinguishing E. coli from Shigella. We show in silico that with as few as 8 predictive sequences, if even three of those predictive sequences are amplified the probability of being EHEC or Shigella is >0.99. The method is thus very robust to the occasional amplification failure for spurious reasons. Experimentally, we apply the method to screening a set of 98 isolates to distinguishing E. coli from Shigella, and EHEC from non-EHEC E. coli strains and show that all isolates are correctly identified. PMID:23935901

  2. 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

  3. 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?

  4. Accurate and inexpensive prediction of the color optical properties of anthocyanins in solution.

    PubMed

    Ge, Xiaochuan; Timrov, Iurii; Binnie, Simon; Biancardi, Alessandro; Calzolari, Arrigo; Baroni, Stefano

    2015-04-23

    The simulation of the color optical properties of molecular dyes in liquid solution requires the calculation of time evolution of the solute absorption spectra fluctuating in the solvent at finite temperature. Time-averaged spectra can be directly evaluated by combining ab initio Car-Parrinello molecular dynamics and time-dependent density functional theory calculations. The inclusion of hybrid exchange-correlation functionals, necessary for the prediction of the correct transition frequencies, prevents one from using these techniques for the simulation of the optical properties of large realistic systems. Here we present an alternative approach for the prediction of the color of natural dyes in solution with a low computational cost. We applied this approach to representative anthocyanin dyes: the excellent agreement between the simulated and the experimental colors makes this method a straightforward and inexpensive tool for the high-throughput prediction of colors of molecules in liquid solvents. PMID:25830823

  5. 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

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

    PubMed

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

    2014-12-16

    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 (r(2)) 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

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

    ERIC Educational Resources Information Center

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

    2010-01-01

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

  8. Predicting College Grades: The Value of Achievement Goals in Supplementing Ability Measures

    ERIC Educational Resources Information Center

    Young, John W.

    2007-01-01

    Achievement goal theory is an important theoretical framework for understanding achievement motivation. In previous studies, a mastery orientation has been shown to be related to students' interest, while a performance orientation has been found to be predictive of academic performance outcomes such as course grades. In this study, the two mastery…

  9. Predicting Pre-Service Teachers' Intention of Implementing Peer Assessment for Low-Achieving Students

    ERIC Educational Resources Information Center

    Yim, Su Yon; Cho, Young Hoan

    2016-01-01

    Despite the benefits of peer assessment, many teachers are not willing to implement it, particularly for low-achieving students. This study used the theory of planned behaviour to predict pre-service teachers' intention to use peer assessment for low-achieving students. A total of 229 pre-service teachers in Singapore participated in the survey…

  10. Predicting Achievement in Mathematics in Adolescent Students: The Role of Individual and Social Factors

    ERIC Educational Resources Information Center

    Levpuscek, Melita Puklek; Zupancic, Maja; Socan, Gregor

    2013-01-01

    The study examined individual factors and social factors that influence adolescent students' achievement in mathematics. The predictive model suggested direct positive effects of student intelligence, self-rated openness and parental education on achievement in mathematics, whereas direct effects of extraversion on measures of achievement…

  11. Predicting Science Achievement: The Role of Developmental Level, Disembedding Ability, Mental Capacity, Prior Knowledge, and Beliefs.

    ERIC Educational Resources Information Center

    Lawson, Anton E.

    1983-01-01

    Ability of five cognitive characteristics to predict students' (N=96) achievement of evolution and natural selection concepts was measured. Results, among others, indicate that disembedding ability, prior knowledge, and evolutionary belief were significantly related to achievement while developmental level and mental capacity were not. (JN)

  12. Predicting Examination Performance Using an Expanded Integrated Hierarchical Model of Test Emotions and Achievement Goals

    ERIC Educational Resources Information Center

    Putwain, Dave; Deveney, Carolyn

    2009-01-01

    The aim of this study was to examine an expanded integrative hierarchical model of test emotions and achievement goal orientations in predicting the examination performance of undergraduate students. Achievement goals were theorised as mediating the relationship between test emotions and performance. 120 undergraduate students completed…

  13. Predicting the Academic Achievement of Gifted Students with Autism Spectrum Disorder

    ERIC Educational Resources Information Center

    Assouline, Susan G.; Foley Nicpon, Megan; Dockery, Lori

    2012-01-01

    We are not well informed regarding the ability-achievement relationship for twice-exceptional individuals (very high cognitive ability and a diagnosed disability, e.g., autism spectrum disorder [ASD]). The research question for this investigation (N = 59) focused on the predictability of achievement among variables related to ability and education…

  14. Correlates of Achievement: Prediction and Cross-Validation for Intermediate Grade Levels.

    ERIC Educational Resources Information Center

    Marshall, Jon C.; Powers, Jerry M.

    A study was conducted to: (1) determine the simple and multiple correlation coefficients between selected educational/personal variables and academic achievement at intermediate grade levels as measured by the Iowa Tests of Basic Skills; (2) determine the multiple linear regression equations for predicting individual student achievement as…

  15. Autonomic Regulation on the Stroop Predicts Reading Achievement in School Age Children

    ERIC Educational Resources Information Center

    Becker, Derek R.; Carrere, Sybil; Siler, Chelsea; Jones, Stephanie; Bowie, Bonnie; Cooke, Cheryl

    2012-01-01

    In this study we examined high frequency heart rate variability (HF-HRV, a parasympathetic index) both at rest and during challenge, to assess if variations in cardiovascular activity measured during a Stroop task could be used to predict reading achievement in typically developing children. Reading achievement was examined using the Peabody…

  16. Predicting Seventh Grade Students' Engagement in Science by Their Achievement Goals

    ERIC Educational Resources Information Center

    Hidiroglu, Melike; Sungur, Semra

    2015-01-01

    The aim of this study was to examine how well seventh grade students' engagement in science can be predicted by their achievement goals. For the specified purpose, a correlational research design was utilized. Data were obtained from 153 seventh grade students through administration of Achievement Goal Questionnaire and Engagement Questionnaire.…

  17. An Accurate, Clinically Feasible Multi-Gene Expression Assay for Predicting Metastasis in Uveal Melanoma

    PubMed Central

    Onken, Michael D.; Worley, Lori A.; Tuscan, Meghan D.; Harbour, J. William

    2010-01-01

    Uveal (ocular) melanoma is an aggressive cancer that often forms undetectable micrometastases before diagnosis of the primary tumor. These micrometastases later multiply to generate metastatic tumors that are resistant to therapy and are uniformly fatal. We have previously identified a gene expression profile derived from the primary tumor that is extremely accurate for identifying patients at high risk of metastatic disease. Development of a practical clinically feasible platform for analyzing this expression profile would benefit high-risk patients through intensified metastatic surveillance, earlier intervention for metastasis, and stratification for entry into clinical trials of adjuvant therapy. Here, we migrate the expression profile from a hybridization-based microarray platform to a robust, clinically practical, PCR-based 15-gene assay comprising 12 discriminating genes and three endogenous control genes. We analyze the technical performance of the assay in a prospective study of 609 tumor samples, including 421 samples sent from distant locations. We show that the assay can be performed accurately on fine needle aspirate biopsy samples, even when the quantity of RNA is below detectable limits. Preliminary outcome data from the prospective study affirm the prognostic accuracy of the assay. This prognostic assay provides an important addition to the armamentarium for managing patients with uveal melanoma, and it provides a proof of principle for the development of similar assays for other cancers. PMID:20413675

  18. The Role of Teachers' Support in Predicting Students' Motivation and Achievement Outcomes in Physical Education

    ERIC Educational Resources Information Center

    Zhang, Tao; Solmon, Melinda A.; Gu, Xiangli

    2012-01-01

    Examining how teachers' beliefs and behaviors predict students' motivation and achievement outcomes in physical education is an area of increasing research interest. Guided by the expectancy-value model and self-determination theory, the major purpose of this study was to examine the predictive strength of teachers' autonomy, competence, and…

  19. Accurate prediction of the ammonia probes of a variable proton-to-electron mass ratio

    NASA Astrophysics Data System (ADS)

    Owens, A.; Yurchenko, S. N.; Thiel, W.; Špirko, V.

    2015-07-01

    A comprehensive study of the mass sensitivity of the vibration-rotation-inversion transitions of 14NH3, 15NH3, 14ND3 and 15ND3 is carried out variationally using the TROVE approach. Variational calculations are robust and accurate, offering a new way to compute sensitivity coefficients. Particular attention is paid to the Δk = ±3 transitions between the accidentally coinciding rotation-inversion energy levels of the ν2 = 0+, 0-, 1+ and 1- states, and the inversion transitions in the ν4 = 1 state affected by the `giant' l-type doubling effect. These transitions exhibit highly anomalous sensitivities, thus appearing as promising probes of a possible cosmological variation of the proton-to-electron mass ratio μ. Moreover, a simultaneous comparison of the calculated sensitivities reveals a sizeable isotopic dependence which could aid an exclusive ammonia detection.

  20. 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

  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. Accurate Fault Prediction of BlueGene/P RAS Logs Via Geometric Reduction

    SciTech Connect

    Jones, Terry R; Kirby, Michael; Ladd, Joshua S; Dreisigmeyer, David; Thompson, Joshua

    2010-01-01

    The authors are building two algorithms for fault prediction using raw system-log data. This work is preliminary, and has only been applied to a limited dataset, however the results seem promising. The conclusions are that: (1) obtaining useful data from RAS-logs is challenging; (2) extracting concentrated information improves efficiency and accuracy; and (3) function evaluation algorithms are fast and lend well to scaling.

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

    PubMed

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

    2015-01-01

    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. PMID:19950907

  5. Accurate Prediction of Drug-Induced Liver Injury Using Stem Cell-Derived Populations

    PubMed Central

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

    2014-01-01

    Despite major progress in the knowledge and management of human liver injury, there are millions of people suffering from chronic liver disease. Currently, the only cure for end-stage liver disease is orthotopic liver transplantation; however, this approach is severely limited by organ donation. Alternative approaches to restoring liver function have therefore been pursued, including the use of somatic and stem cell populations. Although such approaches are essential in developing scalable treatments, there is also an imperative to develop predictive human systems that more effectively study and/or prevent the onset of liver disease and decompensated organ function. We used a renewable human stem cell resource, from defined genetic backgrounds, and drove them through developmental intermediates to yield highly active, drug-inducible, and predictive human hepatocyte populations. Most importantly, stem cell-derived hepatocytes displayed equivalence to primary adult hepatocytes, following incubation with known hepatotoxins. In summary, we have developed a serum-free, scalable, and shippable cell-based model that faithfully predicts the potential for human liver injury. Such a resource has direct application in human modeling and, in the future, could play an important role in developing renewable cell-based therapies. PMID:24375539

  6. 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

  7. 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.

  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. PMID:24375512

  9. Accurate dosimetry with GafChromic EBT film of a 6 MV photon beam in water: What level is achievable?

    SciTech Connect

    Battum, L. J. van; Hoffmans, D.; Piersma, H.; Heukelom, S.

    2008-02-15

    This paper focuses on the accuracy, in absolute dose measurements, with GafChromic EBT film achievable in water for a 6 MV photon beam up to a dose of 2.3 Gy. Motivation is to get an absolute dose detection system to measure up dose distributions in a (water) phantom, to check dose calculations. An Epson 1680 color (red green blue) transmission flatbed scanner has been used as film scanning system, where the response in the red color channel has been extracted and used for the analyses. The influence of the flatbed film scanner on the film based dose detection process was investigated. The scan procedure has been optimized; i.e. for instance a lateral correction curve was derived to correct the scan value, up to 10%, as a function of optical density and lateral position. Sensitometric curves of different film batches were evaluated in portrait and landscape scan mode. Between various batches important variations in sensitometric curve were observed. Energy dependence of the film is negligible, while a slight variation in dose response is observed for very large angles between film surface and incident photon beam. Improved accuracy in absolute dose detection can be obtained by repetition of a film measurement to tackle at least the inherent presence of film inhomogeneous construction. We state that the overall uncertainty is random in absolute EBT film dose detection and of the order of 1.3% (1 SD) under the condition that the film is scanned in a limited centered area on the scanner and at least two films have been applied. At last we advise to check a new film batch on its characteristics compared to available information, before using that batch for absolute dose measurements.

  10. 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.

  11. Predicting Children's Reading and Mathematics Achievement from Early Quantitative Knowledge and Domain-General Cognitive Abilities

    PubMed Central

    Chu, Felicia W.; vanMarle, Kristy; Geary, David C.

    2016-01-01

    One hundred children (44 boys) participated in a 3-year longitudinal study of the development of basic quantitative competencies and the relation between these competencies and later mathematics and reading achievement. The children's preliteracy knowledge, intelligence, executive functions, and parental educational background were also assessed. The quantitative tasks assessed a broad range of symbolic and nonsymbolic knowledge and were administered four times across 2 years of preschool. Mathematics achievement was assessed at the end of each of 2 years of preschool, and mathematics and word reading achievement were assessed at the end of kindergarten. Our goals were to determine how domain-general abilities contribute to growth in children's quantitative knowledge and to determine how domain-general and domain-specific abilities contribute to children's preschool mathematics achievement and kindergarten mathematics and reading achievement. We first identified four core quantitative competencies (e.g., knowledge of the cardinal value of number words) that predict later mathematics achievement. The domain-general abilities were then used to predict growth in these competencies across 2 years of preschool, and the combination of domain-general abilities, preliteracy skills, and core quantitative competencies were used to predict mathematics achievement across preschool and mathematics and word reading achievement at the end of kindergarten. Both intelligence and executive functions predicted growth in the four quantitative competencies, especially across the first year of preschool. A combination of domain-general and domain-specific competencies predicted preschoolers' mathematics achievement, with a trend for domain-specific skills to be more strongly related to achievement at the beginning of preschool than at the end of preschool. Preschool preliteracy skills, sensitivity to the relative quantities of collections of objects, and cardinal knowledge predicted

  12. Predicting Children's Reading and Mathematics Achievement from Early Quantitative Knowledge and Domain-General Cognitive Abilities.

    PubMed

    Chu, Felicia W; vanMarle, Kristy; Geary, David C

    2016-01-01

    One hundred children (44 boys) participated in a 3-year longitudinal study of the development of basic quantitative competencies and the relation between these competencies and later mathematics and reading achievement. The children's preliteracy knowledge, intelligence, executive functions, and parental educational background were also assessed. The quantitative tasks assessed a broad range of symbolic and nonsymbolic knowledge and were administered four times across 2 years of preschool. Mathematics achievement was assessed at the end of each of 2 years of preschool, and mathematics and word reading achievement were assessed at the end of kindergarten. Our goals were to determine how domain-general abilities contribute to growth in children's quantitative knowledge and to determine how domain-general and domain-specific abilities contribute to children's preschool mathematics achievement and kindergarten mathematics and reading achievement. We first identified four core quantitative competencies (e.g., knowledge of the cardinal value of number words) that predict later mathematics achievement. The domain-general abilities were then used to predict growth in these competencies across 2 years of preschool, and the combination of domain-general abilities, preliteracy skills, and core quantitative competencies were used to predict mathematics achievement across preschool and mathematics and word reading achievement at the end of kindergarten. Both intelligence and executive functions predicted growth in the four quantitative competencies, especially across the first year of preschool. A combination of domain-general and domain-specific competencies predicted preschoolers' mathematics achievement, with a trend for domain-specific skills to be more strongly related to achievement at the beginning of preschool than at the end of preschool. Preschool preliteracy skills, sensitivity to the relative quantities of collections of objects, and cardinal knowledge predicted

  13. Accurate prediction of lattice energies and structures of molecular crystals with molecular quantum chemistry methods.

    PubMed

    Fang, Tao; Li, Wei; Gu, Fangwei; Li, Shuhua

    2015-01-13

    We extend the generalized energy-based fragmentation (GEBF) approach to molecular crystals under periodic boundary conditions (PBC), and we demonstrate the performance of the method for a variety of molecular crystals. With this approach, the lattice energy of a molecular crystal can be obtained from the energies of a series of embedded subsystems, which can be computed with existing advanced molecular quantum chemistry methods. The use of the field compensation method allows the method to take long-range electrostatic interaction of the infinite crystal environment into account and make the method almost translationally invariant. The computational cost of the present method scales linearly with the number of molecules in the unit cell. Illustrative applications demonstrate that the PBC-GEBF method with explicitly correlated quantum chemistry methods is capable of providing accurate descriptions on the lattice energies and structures for various types of molecular crystals. In addition, this approach can be employed to quantify the contributions of various intermolecular interactions to the theoretical lattice energy. Such qualitative understanding is very useful for rational design of molecular crystals. PMID:26574207

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

    PubMed Central

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

    2015-01-01

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

  15. 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.

  16. 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.

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

    PubMed

    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. PMID:25669533

  18. 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.

  19. PSI: a comprehensive and integrative approach for accurate plant subcellular localization prediction.

    PubMed

    Liu, Lili; Zhang, Zijun; Mei, Qian; 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

  20. 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

  1. 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

  2. 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

  3. 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.

  4. 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

  5. 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.

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

    PubMed

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

    2016-01-01

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

  7. 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

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

    PubMed Central

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

    2016-01-01

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

  9. 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. PMID:26708965

  10. An accurate and efficient method for prediction of the long-term evolution of space debris in the geosynchronous region

    NASA Astrophysics Data System (ADS)

    McNamara, Roger P.; Eagle, C. D.

    1992-08-01

    Planetary Observer High Accuracy Orbit Prediction Program (POHOP), an existing numerical integrator, was modified with the solar and lunar formulae developed by T.C. Van Flandern and K.F. Pulkkinen to provide the accuracy required to evaluate long-term orbit characteristics of objects on the geosynchronous region. The orbit of a 1000 kg class spacecraft is numerically integrated over 50 years using both the original and the more accurate solar and lunar ephemerides methods. Results of this study demonstrate that, over the long term, for an object located in the geosynchronous region, the more accurate solar and lunar ephemerides effects on the objects's position are significantly different than using the current POHOP ephemeris.

  11. BgN-Score and BsN-Score: Bagging and boosting based ensemble neural networks scoring functions for accurate binding affinity prediction of protein-ligand complexes

    PubMed Central

    2015-01-01

    Background Accurately predicting the binding affinities of large sets of protein-ligand complexes is a key challenge in computational biomolecular science, with applications in drug discovery, chemical biology, and structural biology. Since a scoring function (SF) is used to score, rank, and identify drug leads, the fidelity with which it predicts the affinity of a ligand candidate for a protein's binding site has a significant bearing on the accuracy of virtual screening. Despite intense efforts in developing conventional SFs, which are either force-field based, knowledge-based, or empirical, their limited predictive power has been a major roadblock toward cost-effective drug discovery. Therefore, in this work, we present novel SFs employing a large ensemble of neural networks (NN) in conjunction with a diverse set of physicochemical and geometrical features characterizing protein-ligand complexes to predict binding affinity. Results We assess the scoring accuracies of two new ensemble NN SFs based on bagging (BgN-Score) and boosting (BsN-Score), as well as those of conventional SFs in the context of the 2007 PDBbind benchmark that encompasses a diverse set of high-quality protein families. We find that BgN-Score and BsN-Score have more than 25% better Pearson's correlation coefficient (0.804 and 0.816 vs. 0.644) between predicted and measured binding affinities compared to that achieved by a state-of-the-art conventional SF. In addition, these ensemble NN SFs are also at least 19% more accurate (0.804 and 0.816 vs. 0.675) than SFs based on a single neural network that has been traditionally used in drug discovery applications. We further find that ensemble models based on NNs surpass SFs based on the decision-tree ensemble technique Random Forests. Conclusions Ensemble neural networks SFs, BgN-Score and BsN-Score, are the most accurate in predicting binding affinity of protein-ligand complexes among the considered SFs. Moreover, their accuracies are even higher

  12. A Stationary Wavelet Entropy-Based Clustering Approach Accurately Predicts Gene Expression

    PubMed Central

    Nguyen, Nha; Vo, An; Choi, Inchan

    2015-01-01

    Abstract Studying epigenetic landscapes is important to understand the condition for gene regulation. Clustering is a useful approach to study epigenetic landscapes by grouping genes based on their epigenetic conditions. However, classical clustering approaches that often use a representative value of the signals in a fixed-sized window do not fully use the information written in the epigenetic landscapes. Clustering approaches to maximize the information of the epigenetic signals are necessary for better understanding gene regulatory environments. For effective clustering of multidimensional epigenetic signals, we developed a method called Dewer, which uses the entropy of stationary wavelet of epigenetic signals inside enriched regions for gene clustering. Interestingly, the gene expression levels were highly correlated with the entropy levels of epigenetic signals. Dewer separates genes better than a window-based approach in the assessment using gene expression and achieved a correlation coefficient above 0.9 without using any training procedure. Our results show that the changes of the epigenetic signals are useful to study gene regulation. PMID:25383910

  13. 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.

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

    NASA Technical Reports Server (NTRS)

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

    2001-01-01

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

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

    PubMed

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

    2009-04-01

    The current standard method for predicting contact allergenicity is the murine local lymph node assay (LLNA). Public objection to the use of animals in testing of cosmetics makes the development of a system that does not use sentient animals highly desirable. The chorioallantoic membrane (CAM) of the chick egg has been extensively used for the growth of normal and transformed mammalian tissues. The CAM is not innervated, and embryos are sacrificed before the development of pain perception. The aim of this study was to determine whether the sensitization phase of contact dermatitis to known cosmetic allergens can be quantified using CAM-engrafted human skin and how these results compare with published EC3 data obtained with the LLNA. We studied six common molecules used in allergen testing and quantified migration of epidermal Langerhans cells (LC) as a measure of their allergic potency. All agents with known allergic potential induced statistically significant migration of LC. The data obtained correlated well with published data for these allergens generated using the LLNA test. The human-skin CAM model therefore has great potential as an inexpensive, non-radioactive, in vivo alternative to the LLNA, which does not require the use of sentient animals. In addition, this system has the advantage of testing the allergic response of human, rather than animal skin. PMID:19054059

  16. 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.

  17. 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

  18. 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.

  19. 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

  20. Openness to Experience and Intellect Differentially Predict Creative Achievement in the Arts and Sciences.

    PubMed

    Kaufman, Scott Barry; Quilty, Lena C; Grazioplene, Rachael G; Hirsh, Jacob B; Gray, Jeremy R; Peterson, Jordan B; DeYoung, Colin G

    2016-04-01

    The Big Five personality dimension Openness/Intellect is the trait most closely associated with creativity and creative achievement. Little is known, however, regarding the discriminant validity of its two aspects-Openness to Experience (reflecting cognitive engagement with perception, fantasy, aesthetics, and emotions) and Intellect (reflecting cognitive engagement with abstract and semantic information, primarily through reasoning)-in relation to creativity. In four demographically diverse samples totaling 1,035 participants, we investigated the independent predictive validity of Openness and Intellect by assessing the relations among cognitive ability, divergent thinking, personality, and creative achievement across the arts and sciences. We confirmed the hypothesis that whereas Openness predicts creative achievement in the arts, Intellect predicts creative achievement in the sciences. Inclusion of performance measures of general cognitive ability and divergent thinking indicated that the relation of Intellect to scientific creativity may be due at least in part to these abilities. Lastly, we found that Extraversion additionally predicted creative achievement in the arts, independently of Openness. Results are discussed in the context of dual-process theory. PMID:25487993

  1. Why achievement motivation predicts success in business but failure in politics: the importance of personal control.

    PubMed

    Winter, David G

    2010-12-01

    Several decades of research have established that implicit achievement motivation (n Achievement) is associated with success in business, particularly in entrepreneurial or sales roles. However, several political psychology studies have shown that achievement motivation is not associated with success in politics; rather, implicit power motivation often predicts political success. Having versus lacking control may be a key difference between business and politics. Case studies suggest that achievement-motivated U.S. presidents and other world leaders often become frustrated and thereby fail because of lack of control, whereas power-motivated presidents develop ways to work with this inherent feature of politics. A reevaluation of previous research suggests that, in fact, relationships between achievement motivation and business success only occur when control is high. The theme of control is also prominent in the development of achievement motivation. Cross-national data are also consistent with this analysis: In democratic industrialized countries, national levels of achievement motivation are associated with strong executive control. In countries with low opportunity for education (thus fewer opportunities to develop a sense of personal control), achievement motivation is associated with internal violence. Many of these manifestations of frustrated achievement motivation in politics resemble authoritarianism. This conclusion is tested by data from a longitudinal study of 113 male college students, showing that high initial achievement motivation combined with frustrated desires for control is related to increases in authoritarianism (F-scale scores) during the college years. Implications for the psychology of leadership and practical politics are discussed. PMID:21039527

  2. Accurate prediction of interference minima in linear molecular harmonic spectra by a modified two-center model

    NASA Astrophysics Data System (ADS)

    Xin, Cui; Di-Yu, Zhang; Gao, Chen; Ji-Gen, Chen; Si-Liang, Zeng; Fu-Ming, Guo; Yu-Jun, Yang

    2016-03-01

    We demonstrate that the interference minima in the linear molecular harmonic spectra can be accurately predicted by a modified two-center model. Based on systematically investigating the interference minima in the linear molecular harmonic spectra by the strong-field approximation (SFA), it is found that the locations of the harmonic minima are related not only to the nuclear distance between the two main atoms contributing to the harmonic generation, but also to the symmetry of the molecular orbital. Therefore, we modify the initial phase difference between the double wave sources in the two-center model, and predict the harmonic minimum positions consistent with those simulated by SFA. Project supported by the National Basic Research Program of China (Grant No. 2013CB922200) and the National Natural Science Foundation of China (Grant Nos. 11274001, 11274141, 11304116, 11247024, and 11034003), and the Jilin Provincial Research Foundation for Basic Research, China (Grant Nos. 20130101012JC and 20140101168JC).

  3. 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.

  4. Evaluating Mesoscale Numerical Weather Predictions and Spatially Distributed Meteorologic Forcing Data for Developing Accurate SWE Forecasts over Large Mountain Basins

    NASA Astrophysics Data System (ADS)

    Hedrick, A. R.; Marks, D. G.; Winstral, A. H.; Marshall, H. P.

    2014-12-01

    The ability to forecast snow water equivalent, or SWE, in mountain catchments would benefit many different communities ranging from avalanche hazard mitigation to water resource management. Historical model runs of Isnobal, the physically based energy balance snow model, have been produced over the 2150 km2 Boise River Basin for water years 2012 - 2014 at 100-meter resolution. Spatially distributed forcing parameters such as precipitation, wind, and relative humidity are generated from automated weather stations located throughout the watershed, and are supplied to Isnobal at hourly timesteps. Similarly, the Weather Research & Forecasting (WRF) Model provides hourly predictions of the same forcing parameters from an atmospheric physics perspective. This work aims to quantitatively compare WRF model output to the spatial meteorologic fields developed to force Isnobal, with the hopes of eventually using WRF predictions to create accurate hourly forecasts of SWE over a large mountainous basin.

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

    PubMed Central

    Wang, Shiyao; Deng, Zhidong; Yin, Gang

    2016-01-01

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

  6. 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

  7. Does a More Precise Chemical Description of Protein–Ligand Complexes Lead to More Accurate Prediction of Binding Affinity?

    PubMed Central

    2014-01-01

    Predicting the binding affinities of large sets of diverse molecules against a range of macromolecular targets is an extremely challenging task. The scoring functions that attempt such computational prediction are essential for exploiting and analyzing the outputs of docking, which is in turn an important tool in problems such as structure-based drug design. Classical scoring functions assume a predetermined theory-inspired functional form for the relationship between the variables that describe an experimentally determined or modeled structure of a protein–ligand complex and its binding affinity. The inherent problem of this approach is in the difficulty of explicitly modeling the various contributions of intermolecular interactions to binding affinity. New scoring functions based on machine-learning regression models, which are able to exploit effectively much larger amounts of experimental data and circumvent the need for a predetermined functional form, have already been shown to outperform a broad range of state-of-the-art scoring functions in a widely used benchmark. Here, we investigate the impact of the chemical description of the complex on the predictive power of the resulting scoring function using a systematic battery of numerical experiments. The latter resulted in the most accurate scoring function to date on the benchmark. Strikingly, we also found that a more precise chemical description of the protein–ligand complex does not generally lead to a more accurate prediction of binding affinity. We discuss four factors that may contribute to this result: modeling assumptions, codependence of representation and regression, data restricted to the bound state, and conformational heterogeneity in data. PMID:24528282

  8. Accurate Ab Initio and Template-Based Prediction of Short Intrinsically-Disordered Regions by Bidirectional Recurrent Neural Networks Trained on Large-Scale Datasets

    PubMed Central

    Volpato, Viola; Alshomrani, Badr; Pollastri, Gianluca

    2015-01-01

    Intrinsically-disordered regions lack a well-defined 3D structure, but play key roles in determining the function of many proteins. Although predictors of disorder have been shown to achieve relatively high rates of correct classification of these segments, improvements over the the years have been slow, and accurate methods are needed that are capable of accommodating the ever-increasing amount of structurally-determined protein sequences to try to boost predictive performances. In this paper, we propose a predictor for short disordered regions based on bidirectional recurrent neural networks and tested by rigorous five-fold cross-validation on a large, non-redundant dataset collected from MobiDB, a new comprehensive source of protein disorder annotations. The system exploits sequence and structural information in the forms of frequency profiles, predicted secondary structure and solvent accessibility and direct disorder annotations from homologous protein structures (templates) deposited in the Protein Data Bank. The contributions of sequence, structure and homology information result in large improvements in predictive accuracy. Additionally, the large scale of the training set leads to low false positive rates, making our systems a robust and efficient way to address high-throughput disorder prediction. PMID:26307973

  9. A hyperspectral imaging system for an accurate prediction of the above-ground biomass of individual rice plants.

    PubMed

    Feng, Hui; Jiang, Ni; Huang, Chenglong; Fang, Wei; Yang, Wanneng; Chen, Guoxing; Xiong, Lizhong; Liu, Qian

    2013-09-01

    Biomass is an important component of the plant phenomics, and the existing methods for biomass estimation for individual plants are either destructive or lack accuracy. In this study, a hyperspectral imaging system was developed for the accurate prediction of the above-ground biomass of individual rice plants in the visible and near-infrared spectral region. First, the structure of the system and the influence of various parameters on the camera acquisition speed were established. Then the system was used to image 152 rice plants, which selected from the rice mini-core collection, in two stages, the tillering to elongation (T-E) stage and the booting to heading (B-H) stage. Several variables were extracted from the images. Following, linear stepwise regression analysis and 5-fold cross-validation were used to select effective variables for model construction and test the stability of the model, respectively. For the T-E stage, the R(2) value was 0.940 for the fresh weight (FW) and 0.935 for the dry weight (DW). For the B-H stage, the R(2) value was 0.891 for the FW and 0.783 for the DW. Moreover, estimations of the biomass using visible light images were also calculated. These comparisons showed that hyperspectral imaging performed better than the visible light imaging. Therefore, this study provides not only a stable hyperspectral imaging platform but also an accurate and nondestructive method for the prediction of biomass for individual rice plants. PMID:24089866

  10. 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

  11. The Validity of the "Boehm Test of Basic Concepts" in Predicting Achievement.

    ERIC Educational Resources Information Center

    Olinger, Clarice K.

    To determine the validity of the Boehm Test of Basic Concepts in predicting reading achievement as measured by the reading scores of the Iowa Test of Basic Skills, the Boehm test was given to 55 kindergarten children and the Iowa test was given to 42 of the same children in second grade. The results indiciated that the Boehm test appeared to be of…

  12. Predicting Early School Achievement with the EDI: A Longitudinal Population-Based Study

    ERIC Educational Resources Information Center

    Forget-Dubois, Nadine; Lemelin, Jean-Pascal; Boivin, Michel; Dionne, Ginette; Seguin, Jean R.; Vitaro, Frank; Tremblay, Richard E.

    2007-01-01

    School readiness tests are significant predictors of early school achievement. Measuring school readiness on a large scale would be necessary for the implementation of intervention programs at the community level. However, assessment of school readiness is costly and time consuming. This study assesses the predictive value of a school readiness…

  13. Implicit Theories of Intelligence Predict Achievement across an Adolescent Transition: A Longitudinal Study and an Intervention

    ERIC Educational Resources Information Center

    Blackwell, Lisa S.; Trzesniewski, Kali H.; Dweck, Carol Sorich

    2007-01-01

    Two studies explored the role of implicit theories of intelligence in adolescents' mathematics achievement. In Study 1 with 373 7th graders, the belief that intelligence is malleable (incremental theory) predicted an upward trajectory in grades over the two years of junior high school, while a belief that intelligence is fixed (entity theory)…

  14. Achievement Motivation Revisited: New Longitudinal Data to Demonstrate Its Predictive Power

    ERIC Educational Resources Information Center

    Hustinx, Paul W. J.; Kuyper, Hans; van der Werf, Margaretha P. C.; Dijkstra, Pieternel

    2009-01-01

    During recent decades, the classical one-dimensional concept of achievement motivation has become less popular among motivation researchers. This study aims to revive the concept by demonstrating its predictive power using longitudinal data from two cohort samples, each with 20,000 Dutch secondary school students. Two measures of achievement…

  15. Intelligence Predicts Scholastic Achievement Irrespective of SES Factors: Evidence from Brazil

    ERIC Educational Resources Information Center

    Colom, Roberto; Flores-Mendoza, Carmen E.

    2007-01-01

    This study explores whether or not intelligence tests' scores predict individual differences in scholastic achievement irrespective of SES factors such parents' income and education. The variables of interest are analyzed considering three independent samples of participants comprising a total of 641 children. The participants belonged to a…

  16. Predicting Mathematical Achievement and Mathematical Learning Disability with a Simple Screening Tool: The Number Sets Test

    ERIC Educational Resources Information Center

    Geary, David C.; Bailey, Drew H.; Hoard, Mary K.

    2009-01-01

    The Number Sets Test was developed to assess the speed and accuracy with which children can identify and process quantities represented by Arabic numerals and object sets. The utility of this test for predicting mathematics achievement and risk for mathematical learning disability (MLD) was assessed for a sample of 223 children. A signal detection…

  17. Ten Years on: Does Graduate Student Promise Predict Later Scientific Achievement?

    ERIC Educational Resources Information Center

    Haslam, Nick; Laham, Simon M.

    2009-01-01

    We examined publication records of 60 social psychologists to determine whether publication record at the time of the PhD (t0) predicted scientific achievement (publication quantity, quality, and impact) ten years later (t10). Publication quantity and quality each correlated moderately across this time-span. Productivity and impact at t10 were…

  18. Predicting End-of-Year Achievement Test Performance: A Comparison of Assessment Methods

    ERIC Educational Resources Information Center

    Kettler, Ryan J.; Elliott, Stephen N.; Kurz, Alexander; Zigmond, Naomi; Lemons, Christopher J.; Kloo, Amanda; Shrago, Jacqueline; Beddow, Peter A.; Williams, Leila; Bruen, Charles; Lupp, Lynda; Farmer, Jeanie; Mosiman, Melanie

    2014-01-01

    Motivated by the multiple-measures clause of recent federal policy regarding student eligibility for alternate assessments based on modified academic achievement standards (AA-MASs), this study examined how scores or combinations of scores from a diverse set of assessments predicted students' end-of-year proficiency status on statewide…

  19. Which Variables Associated with Data-Driven Instruction Are Believed to Best Predict Urban Student Achievement?

    ERIC Educational Resources Information Center

    Greer, Wil

    2013-01-01

    This study identified the variables associated with data-driven instruction (DDI) that are perceived to best predict student achievement. Of the DDI variables discussed in the literature, 51 of them had a sufficient enough research base to warrant statistical analysis. Of them, 26 were statistically significant. Multiple regression and an…

  20. Examining the Validity of Behavioral Self-Regulation Tools in Predicting Preschoolers' Academic Achievement

    ERIC Educational Resources Information Center

    Schmitt, Sara A.; Pratt, Megan E.; McClelland, Megan M.

    2014-01-01

    The current study investigated the predictive utility among teacher-rated, observed, and directly assessed behavioral self-regulation skills to academic achievement in preschoolers. Specifically, this study compared how a teacher report, the Child Behavior Rating Scale, an observer report, the Observed Child Engagement Scale, and a direct…

  1. Examining the Validity of Behavioral Self-Regulation Tools in Predicting Preschoolers' Academic Achievement

    ERIC Educational Resources Information Center

    Schmitt, Sara A.; Pratt, Megan E.; McClelland, Megan M.

    2014-01-01

    Research Findings: The current study investigated the predictive utility of teacher-rated, observed, and directly assessed behavioral self-regulation skills to academic achievement in preschoolers. Specifically, this study compared how a teacher report (the Child Behavior Rating Scale), an observer report (the Observed Child Engagement Scale), and…

  2. Factors Predicting Turkish and Korean Students' Science and Mathematics Achievement in TIMSS 2011

    ERIC Educational Resources Information Center

    Topçu, Mustafa Sami; Erbilgin, Evrim; Arikan, Serkan

    2016-01-01

    This study makes an important contribution to an expanding body of international comparative studies by exploring factors predicting differences in science and mathematics achievement by students in Turkey and the Republic of Korea on the 2011 TIMSS assessment. While these countries are similar with regards to population size, cultural beliefs…

  3. Differential Prediction of Academic Achievement in Elementary and Junior High School by Sex.

    ERIC Educational Resources Information Center

    Lewis, J. C.

    This study examined differences in predicting achievement by sex on the Iowa Tests of Basic Skills (ITBS) from the verbal, quantitative, and nonverbal scores on the Cognitive Abilities Test (CogAT). The sample (n=10,000) consisted of all students in Grades 2, 5, and 8 who completed both tests in fall 1984. Examinations of means and standard…

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

    NASA Astrophysics Data System (ADS)

    Bozinoski, Radoslav

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

  5. Preschool Interpersonal Relationships Predict Kindergarten Achievement: Mediated by Gains in Emotion Knowledge

    PubMed Central

    Torres, Marcela M.; Domitrovich, Celene E.; Bierman, Karen L.

    2016-01-01

    Using longitudinal data, this study tested a model in which preschool interpersonal relationships promoted kindergarten achievement in a pathway mediated by growth in emotion knowledge. The sample included 164 children attending Head Start (14% Hispanic-American, 30% African-American, 56% Caucasian; 56% girls). Preschool interpersonal relationships were indexed by student-teacher relationship closeness and positive peer interactions. Two measures of emotion knowledge (identifying emotions in photographs, recognizing emotions in stories) were assessed at the start and end of the preschool year. Structural equation models revealed that positive interpersonal relationships (with teachers and peers) predicted gains in emotion knowledge (identification, recognition) during the preschool year. Positive interpersonal relationships in preschool also predicted kindergarten achievement (controlling for initial preschool achievement); however, this association was mediated by gains in emotion knowledge during the preschool year. Implications are discussed for school readiness programs serving economically-disadvantaged children.

  6. Predicting the academic achievement of gifted students with autism spectrum disorder.

    PubMed

    Assouline, Susan G; Foley Nicpon, Megan; Dockery, Lori

    2012-09-01

    We are not well informed regarding the ability-achievement relationship for twice-exceptional individuals (very high cognitive ability and a diagnosed disability, e.g., autism spectrum disorder [ASD]). The research question for this investigation (N = 59) focused on the predictability of achievement among variables related to ability and education in a twice-exceptional sample of students (cognitive ability of 120 [91st percentile], or above, and diagnosed with ASD). We determined that WISC-IV Working Memory and Processing Speed Indices were both significantly positively correlated with achievement in math, reading, and written language. WISC Perceptual Reasoning Index was uniquely predictive of Oral Language test scores. Unexpected findings were that ASD diagnosis, Verbal Comprehension Index, and forms of academic acceleration were not related to the dependent variables. PMID:22105142

  7. Boasts are a boost: achievement prime self-reactivity predicts subsequent academic performance.

    PubMed

    Gramzow, Richard H; Johnson, Camille S; Willard, Greg

    2014-03-01

    The present research tests the hypothesis that self-reactivity following an achievement prime reflects the strength of achievement goals and is a predictor of future goal-relevant performance. In Studies 1-3, undergraduates reported their grade-point averages (GPAs) following either an achievement goal prime or a control prime. Academic exaggeration (higher self-reported than official GPA) was the indicator of self-reactivity to the prime. Study 1 involved a direct achievement goal prime, whereas Studies 2 and 3 involved indirect priming techniques. In all 3 experiments, greater academic exaggeration following the achievement goal prime (but not the control prime) predicted better academic performance a semester later (based on official records). Study 4 demonstrated that the magnitude of students' GPA goals mediated the association between academic exaggeration and subsequent performance (1 year later). The fact that self-reactivity to a single achievement goal prime in the lab predicted later performance in "real life" suggests that individual differences in reactivity to a specific prime can signal much broader motivational orientations related to the primed goal. PMID:24588092

  8. Accurate prediction of protein structural classes by incorporating predicted secondary structure information into the general form of Chou's pseudo amino acid composition.

    PubMed

    Kong, Liang; Zhang, Lichao; Lv, Jinfeng

    2014-03-01

    Extracting good representation from protein sequence is fundamental for protein structural classes prediction tasks. In this paper, we propose a novel and powerful method to predict protein structural classes based on the predicted secondary structure information. At the feature extraction stage, a 13-dimensional feature vector is extracted to characterize general contents and spatial arrangements of the secondary structural elements of a given protein sequence. Specially, four segment-level features are designed to elevate discriminative ability for proteins from the α/β and α+β classes. After the features are extracted, a multi-class non-linear support vector machine classifier is used to implement protein structural classes prediction. We report extensive experiments comparing the proposed method to the state-of-the-art in protein structural classes prediction on three widely used low-similarity benchmark datasets: FC699, 1189 and 640. Our method achieves competitive performance on prediction accuracies, especially for the overall prediction accuracies which have exceeded the best reported results on all of the three datasets. PMID:24316044

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

    PubMed

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

    2015-02-01

    As intermolecular interactions such as the hydrogen bond are electrostatic in origin, rigorous treatment of this term within force field methodologies should be mandatory. We present a method able of accurately reproducing such interactions for seven van der Waals complexes. It uses atomic multipole moments up to hexadecupole moment mapped to the positions of the nuclear coordinates by the machine learning method kriging. Models were built at three levels of theory: HF/6-31G(**), B3LYP/aug-cc-pVDZ and M06-2X/aug-cc-pVDZ. The quality of the kriging models was measured by their ability to predict the electrostatic interaction energy between atoms in external test examples for which the true energies are known. At all levels of theory, >90% of test cases for small van der Waals complexes were predicted within 1 kJ mol(-1), decreasing to 60-70% of test cases for larger base pair complexes. Models built on moments obtained at B3LYP and M06-2X level generally outperformed those at HF level. For all systems the individual interactions were predicted with a mean unsigned error of less than 1 kJ mol(-1). PMID:24274986

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

    PubMed

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

    2016-01-01

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

  11. Accurate 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

  12. The Predictive Relationship between Achievement and Participation in Music and Achievement in Core Grade 12 Academic Subjects

    ERIC Educational Resources Information Center

    Gouzouasis, Peter; Guhn, Martin; Kishor, Nand

    2007-01-01

    The relationship between musical training and general intellectual capacity as well as academic achievement has been discussed in numerous contexts. In our study, we examined the relationship between participation and achievement in music and achievement in academic courses, based on data from three consecutive British Columbia student cohorts.…

  13. 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

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

    PubMed Central

    Steele, Mark A.; Forrester, Graham E.

    2005-01-01

    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. PMID:16150721

  15. 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. PMID:16150721

  16. 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.

  17. The general AMBER force field (GAFF) can accurately predict thermodynamic and transport properties of many ionic liquids.

    PubMed

    Sprenger, K G; Jaeger, Vance W; Pfaendtner, Jim

    2015-05-01

    We have applied molecular dynamics to calculate thermodynamic and transport properties of a set of 19 room-temperature ionic liquids. Since accurately simulating the thermophysical properties of solvents strongly depends upon the force field of choice, we tested the accuracy of the general AMBER force field, without refinement, for the case of ionic liquids. Electrostatic point charges were developed using ab initio calculations and a charge scaling factor of 0.8 to more accurately predict dynamic properties. The density, heat capacity, molar enthalpy of vaporization, self-diffusivity, and shear viscosity of the ionic liquids were computed and compared to experimentally available data, and good agreement across a wide range of cation and anion types was observed. Results show that, for a wide range of ionic liquids, the general AMBER force field, with no tuning of parameters, can reproduce a variety of thermodynamic and transport properties with similar accuracy to that of other published, often IL-specific, force fields. PMID:25853313

  18. Perceived parenting and social support: can they predict academic achievement in Argentinean college students?

    PubMed

    de la Iglesia, Guadalupe; Freiberg Hoffmann, Agustin; Fernández Liporace, Mercedes

    2014-01-01

    The aim of this study was to test the ability to predict academic achievement through the perception of parenting and social support in a sample of 354 Argentinean college students. Their mean age was 23.50 years (standard deviation =2.62 years) and most of them (83.3%) were females. As a prerequisite for admission to college, students are required to pass a series of mandatory core classes and are expected to complete them in two semesters. Delay in completing the curriculum is considered low academic achievement. Parenting was assessed taking into account the mother and the father and considering two dimensions: responsiveness and demandingness. Perceived social support was analyzed considering four sources: parents, teachers, classmates, and best friend or boyfriend/girlfriend. Path analysis showed that, as hypothesized, responsiveness had a positive indirect effect on the perception of social support and enhanced achievement. Demandingness had a different effect in the case of the mother as compared to the father. In the mother model, demandingness had a positive direct effect on achievement. In the case of the father, however, the effect of demandingness had a negative and indirect impact on the perception of social support. Teachers were the only source of perceived social support that significantly predicted achievement. The pathway that belongs to teachers as a source of support was positive and direct. Implications for possible interventions are discussed. PMID:25258563

  19. 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

  20. The Role of Self-Regulated Strategies and Goal Orientation in Predicting Achievement of Elementary School Children

    ERIC Educational Resources Information Center

    Kitsantas, Anastasia; Steen, Sam; Huie, Faye

    2009-01-01

    The present study examined the predictiveness of self-regulated learning strategies and goal orientation of elementary students' academic achievement. Eighty one (n = 81) fifth graders were asked to respond to two scales. It was hypothesized that student achievement would be predicted by prior achievement, use of self-regulation strategies,…

  1. Accurate prediction for atomic-level protein design and its application in diversifying the near-optimal sequence space.

    PubMed

    Fromer, Menachem; Yanover, Chen

    2009-05-15

    precisely. Examination of the predicted ensembles indicates that, for each structure, the amino acid identity at a majority of positions must be chosen extremely selectively so as to not incur significant energetic penalties. We investigate this high degree of similarity and demonstrate how more diverse near-optimal sequences can be predicted in order to systematically overcome this bottleneck for computational design. Finally, we exploit this in-depth analysis of a collection of the lowest energy sequences to suggest an explanation for previously observed experimental design results. The novel methodologies introduced here accurately portray the sequence space compatible with a protein structure and further supply a scheme to yield heterogeneous low-energy sequences, thus providing a powerful instrument for future work on protein design. PMID:19003998

  2. Prediction of intrinsic motivation and sports performance using 2 x 2 achievement goal framework.

    PubMed

    Li, Chiung-Huang; Chi, Likang; Yeh, Suh-Ruu; Guo, Kwei-Bin; Ou, Cheng-Tsung; Kao, Chun-Chieh

    2011-04-01

    The purpose of this study was to examine the influence of 2 x 2 achievement goals on intrinsic motivation and performance in handball. Participants were 164 high school athletes. All completed the 2 x 2 Achievement Goals Questionnaire for Sport and the Intrinsic Motivation subscale of the Sport Motivation Scale; the coach for each team rated his athletes' overall sports performance. Using simultaneous-regression analyses, mastery-approach goals positively predicted both intrinsic motivation and performance in sports, whereas performance-avoidance goals negatively predicted sports performance. These results suggest that athletes who pursue task mastery and improvement of their competence perform well and enjoy their participation. In contrast, those who focus on avoiding normative incompetence perform poorly. PMID:21675576

  3. Predicting suitable optoelectronic properties of monoclinic VON semiconductor crystals for photovoltaics using accurate first-principles computations.

    PubMed

    Harb, Moussab

    2015-10-14

    Using accurate first-principles quantum calculations based on DFT (including the DFPT) with the range-separated hybrid HSE06 exchange-correlation functional, we can predict the essential fundamental properties (such as bandgap, optical absorption co-efficient, dielectric constant, charge carrier effective masses and exciton binding energy) of two stable monoclinic vanadium oxynitride (VON) semiconductor crystals for solar energy conversion applications. In addition to the predicted band gaps in the optimal range for making single-junction solar cells, both polymorphs exhibit a relatively high absorption efficiency in the visible range, high dielectric constant, high charge carrier mobility and much lower exciton binding energy than the thermal energy at room temperature. Moreover, their optical absorption, dielectric and exciton dissociation properties were found to be better than those obtained for semiconductors frequently utilized in photovoltaic devices such as Si, CdTe and GaAs. These novel results offer a great opportunity for this stoichiometric VON material to be properly synthesized and considered as a new good candidate for photovoltaic applications. PMID:26351755

  4. [Prediction of mathematics achievement: effect of personal, socioeducational and contextual variables].

    PubMed

    Rosário, Pedro; Lourenço, Abílio; Paiva, Olímpia; Rodrigues, Adriana; Valle, Antonio; Tuero-Herrero, Ellián

    2012-05-01

    Based upon the self-regulated learning theoretical framework this study examined to what extent students' Math school achievement (fifth to ninth graders from compulsory education) can be explained by different cognitive-motivational, social, educational, and contextual variables. A sample of 571 students (10 to 15 year old) enrolled in the study. Findings suggest that Math achievement can be predicted by self-efficacy in Math, school success and self-regulated learning and that these same variables can be explained by other motivational (ej., achievement goals) and contextual variables (school disruption) stressing this way the main importance of self-regulated learning processes and the role context can play in the promotion of school success. The educational implications of the results to the school levels taken are also discussed in the present paper. PMID:22420359

  5. Creative motivation: creative achievement predicts cardiac autonomic markers of effort during divergent thinking.

    PubMed

    Silvia, Paul J; Beaty, Roger E; Nusbaum, Emily C; Eddington, Kari M; Kwapil, Thomas R

    2014-10-01

    Executive approaches to creativity emphasize that generating creative ideas can be hard and requires mental effort. Few studies, however, have examined effort-related physiological activity during creativity tasks. Using motivational intensity theory as a framework, we examined predictors of effort-related cardiac activity during a creative challenge. A sample of 111 adults completed a divergent thinking task. Sympathetic (PEP and RZ) and parasympathetic (RSA and RMSSD) outcomes were assessed using impedance cardiography. As predicted, people with high creative achievement (measured with the Creative Achievement Questionnaire) showed significantly greater increases in sympathetic activity from baseline to task, reflecting higher effort. People with more creative achievements generated ideas that were significantly more creative, and creative performance correlated marginally with PEP and RZ. The results support the view that creative thought can be a mental challenge. PMID:25063471

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

    NASA Astrophysics Data System (ADS)

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

    2009-03-01

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

  7. 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. PMID:26460680

  8. Comparative study of exchange-correlation functionals for accurate predictions of structural and magnetic properties of multiferroic oxides

    NASA Astrophysics Data System (ADS)

    Chen, Hanghui; Millis, Andrew J.

    2016-05-01

    We systematically compare predictions of various exchange correlation functionals for the structural and magnetic properties of perovskite Sr1 -xBaxMnO3 (0 ≤x ≤1 )—a representative class of multiferroic oxides. The local spin density approximation (LSDA) and spin-dependent generalized gradient approximation with Perdew-Burke-Ernzerhof parametrization (sPBE) make substantial different predictions for ferroelectric atomic distortions, tetragonality, and ground state magnetic ordering. Neither approximation quantitatively reproduces all the measured structural and magnetic properties of perovskite Sr0.5Ba0.5MnO3 . The spin-dependent generalized gradient approximation with Perdew-Burke-Ernzerhof revised for solids parametrization (sPBEsol) and the charge-only Perdew-Burke-Ernzerhof parametrized generalized gradient approximation with Hubbard U and Hund's J extensions both provide overall better agreement with measured structural and magnetic properties of Sr0.5Ba0.5MnO3 , compared to LSDA and sPBE. Using these two methods, we find that different from previous predictions, perovskite BaMnO3 has large Mn off-center displacements and is close to a ferromagnetic-to-antiferromagnetic phase boundary, making it a promising candidate to induce effective giant magnetoelectric effects and to achieve cross-field control of polarization and magnetism.

  9. Accurate Prediction of Advanced Liver Fibrosis Using the Decision Tree Learning Algorithm in Chronic Hepatitis C Egyptian Patients

    PubMed Central

    Hashem, Somaya; Esmat, Gamal; Elakel, Wafaa; Habashy, Shahira; Abdel Raouf, Safaa; Darweesh, Samar; Soliman, Mohamad; Elhefnawi, Mohamed; El-Adawy, Mohamed; ElHefnawi, Mahmoud

    2016-01-01

    Background/Aim. Respectively with the prevalence of chronic hepatitis C in the world, using noninvasive methods as an alternative method in staging chronic liver diseases for avoiding the drawbacks of biopsy is significantly increasing. The aim of this study is to combine the serum biomarkers and clinical information to develop a classification model that can predict advanced liver fibrosis. Methods. 39,567 patients with chronic hepatitis C were included and randomly divided into two separate sets. Liver fibrosis was assessed via METAVIR score; patients were categorized as mild to moderate (F0–F2) or advanced (F3-F4) fibrosis stages. Two models were developed using alternating decision tree algorithm. Model 1 uses six parameters, while model 2 uses four, which are similar to FIB-4 features except alpha-fetoprotein instead of alanine aminotransferase. Sensitivity and receiver operating characteristic curve were performed to evaluate the performance of the proposed models. Results. The best model achieved 86.2% negative predictive value and 0.78 ROC with 84.8% accuracy which is better than FIB-4. Conclusions. The risk of advanced liver fibrosis, due to chronic hepatitis C, could be predicted with high accuracy using decision tree learning algorithm that could be used to reduce the need to assess the liver biopsy. PMID:26880886

  10. Accurate Prediction of Advanced Liver Fibrosis Using the Decision Tree Learning Algorithm in Chronic Hepatitis C Egyptian Patients.

    PubMed

    Hashem, Somaya; Esmat, Gamal; Elakel, Wafaa; Habashy, Shahira; Abdel Raouf, Safaa; Darweesh, Samar; Soliman, Mohamad; Elhefnawi, Mohamed; El-Adawy, Mohamed; ElHefnawi, Mahmoud

    2016-01-01

    Background/Aim. Respectively with the prevalence of chronic hepatitis C in the world, using noninvasive methods as an alternative method in staging chronic liver diseases for avoiding the drawbacks of biopsy is significantly increasing. The aim of this study is to combine the serum biomarkers and clinical information to develop a classification model that can predict advanced liver fibrosis. Methods. 39,567 patients with chronic hepatitis C were included and randomly divided into two separate sets. Liver fibrosis was assessed via METAVIR score; patients were categorized as mild to moderate (F0-F2) or advanced (F3-F4) fibrosis stages. Two models were developed using alternating decision tree algorithm. Model 1 uses six parameters, while model 2 uses four, which are similar to FIB-4 features except alpha-fetoprotein instead of alanine aminotransferase. Sensitivity and receiver operating characteristic curve were performed to evaluate the performance of the proposed models. Results. The best model achieved 86.2% negative predictive value and 0.78 ROC with 84.8% accuracy which is better than FIB-4. Conclusions. The risk of advanced liver fibrosis, due to chronic hepatitis C, could be predicted with high accuracy using decision tree learning algorithm that could be used to reduce the need to assess the liver biopsy. PMID:26880886

  11. Advancing Achievement Goal Theory: Using Goal Structures and Goal Orientations to Predict Students' Motivation, Cognition, and Achievement

    ERIC Educational Resources Information Center

    Wolters, Christopher A.

    2004-01-01

    The objective of this study was to investigate how different components of achievement goal theory were related to each other and to students' motivation, cognitive engagement, and achievement in mathematics. Junior high school students (N=525) completed a self-report survey that assessed their perceived classroom goal structures; personal goal…

  12. 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

  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. Mathematical models for accurate prediction of atmospheric visibility with particular reference to the seasonal and environmental patterns in Hong Kong.

    PubMed

    Mui, K W; Wong, L T; Chung, L Y

    2009-11-01

    Atmospheric visibility impairment has gained increasing concern as it is associated with the existence of a number of aerosols as well as common air pollutants and produces unfavorable conditions for observation, dispersion, and transportation. This study analyzed the atmospheric visibility data measured in urban and suburban Hong Kong (two selected stations) with respect to time-matched mass concentrations of common air pollutants including nitrogen dioxide (NO(2)), nitrogen monoxide (NO), respirable suspended particulates (PM(10)), sulfur dioxide (SO(2)), carbon monoxide (CO), and meteorological parameters including air temperature, relative humidity, and wind speed. No significant difference in atmospheric visibility was reported between the two measurement locations (p > or = 0.6, t test); and good atmospheric visibility was observed more frequently in summer and autumn than in winter and spring (p < 0.01, t test). It was also found that atmospheric visibility increased with temperature but decreased with the concentrations of SO(2), CO, PM(10), NO, and NO(2). The results showed that atmospheric visibility was season dependent and would have significant correlations with temperature, the mass concentrations of PM(10) and NO(2), and the air pollution index API (correlation coefficients mid R: R mid R: > or = 0.7, p < or = 0.0001, t test). Mathematical expressions catering to the seasonal variations of atmospheric visibility were thus proposed. By comparison, the proposed visibility prediction models were more accurate than some existing regional models. In addition to improving visibility prediction accuracy, this study would be useful for understanding the context of low atmospheric visibility, exploring possible remedial measures, and evaluating the impact of air pollution and atmospheric visibility impairment in this region. PMID:18951139

  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. The honeymoon effect in job performance - Temporal increases in the predictive power of achievement motivation

    NASA Technical Reports Server (NTRS)

    Helmreich, Robert L.; Sawin, Linda L.; Carsrud, Alan L.

    1986-01-01

    Correlations between a job performance criterion and personality measures reflecting achievement motivation and an interpersonal orientation were examined at three points in time after completion of job training for a sample of airline reservations agents. Although correlations between the personality predictors and performance were small and nonsignificant for the 3-month period after beginning the job, by the end of six and eight months a number of significant relationships had emerged. Implications for the utility of personality measures in selection and performance prediction are discussed.

  17. Mental health matters in elementary school: first-grade screening predicts fourth grade achievement test scores.

    PubMed

    Guzman, Maria Paz; Jellinek, Michael; George, Myriam; Hartley, Marcela; Squicciarini, Ana Maria; Canenguez, Katia M; Kuhlthau, Karen A; Yucel, Recai; White, Gwyne W; Guzman, Javier; Murphy, J Michael

    2011-08-01

    The objective of the study was to evaluate whether mental health problems identified through screens administered in first grade are related to poorer academic achievement test scores in the fourth grade. The government of Chile uses brief teacher- and parent-completed measures [Teacher Observation of Classroom Adaptation-Revised (TOCA-RR) and Pediatric Symptom Checklist (PSC-Cl)] to screen for mental health problems in about one-fifth of the country's elementary schools. In fourth grade, students take the national achievement tests (SIMCE) of language, mathematics and science. This study examined whether mental health problems identified through either or both screens predicted achievement test scores after controlling for student and family risk factors. A total of 17,252 students had complete first grade teacher forms and these were matched with fourth grade SIMCE data for 11,185 students, 7,903 of whom also had complete parent form data from the first grade. Students at risk on either the TOCA-RR or the PSC-Cl or both performed significantly worse on all SIMCE subtests. Even after controlling for covariates and adjusting for missing data, students with mental health problems on one screen in first grade had fourth grade achievement scores that were 14-18 points (~1/3 SD) lower than students screened as not at risk. Students at risk on both screens had scores that were on average 33 points lower than students at risk on either screen. Mental health problems in first grade were one of the strongest predictors of lower achievement test scores 3 years later, supporting the premise that for children mental health matters in the real world. PMID:21647553

  18. 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

  19. 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

  20. Emotions in the classroom: the role of teachers' emotional intelligence ability in predicting students' achievement.

    PubMed

    Curci, Antonietta; Lanciano, Tiziana; Soleti, Emanuela

    2014-01-01

    School days can be a difficult time, especially when students are faced with subjects that require motivational investment along with cognitive effort, such as mathematics and sciences. In the present study, we investigated the effects of teachers' emotional intelligence (El) ability, self-efficacy, and emotional states and students' self-esteem, perceptions of ability, and metacognitive beliefs in predicting school achievement. We hypothesized that the level of teacher EI ability would moderate the impact of students' self-perceptions and beliefs about their achievements in mathematics and sciences. Students from Italian junior high schools (N = 338) and their math teachers (N = 12) were involved in the study, and a multilevel approach was used. Findings showed that teachers' EI has a positive role in promoting students' achievement, by enhancing the effects of students' self-perceptions of ability and self-esteem.These results have implications for the implementation of intervention programs on the emotional, motivational, and metacognitive correlates of studying and learning behavior. PMID:25603580

  1. Early identification of young children at risk for poor academic achievement: preliminary development of a parent-report prediction tool

    PubMed Central

    2011-01-01

    Background Early school success is clearly related to later health. A prediction index that uses parent report to assess children's risk for poor academic achievement could potentially direct targeted service delivery to improve child outcomes. Methods We obtained risk factors through literature review and used the National Longitudinal Survey of Youth 1979 Child Files to examine the predictive associations of these factors with academic achievement scores. Results Twenty predictors were identified including four strong predictors (maternal education, child gender, family income, and low birth weight). Significantly, 12 predictors explained 17-24% of score variance. Conclusions Parent-reported factors provide predictive accuracy for academic achievement. PMID:21851586

  2. Prosthetic Breast Reconstruction With Acellular Dermal Matrices: Achieving Predictability and Reproducibility.

    PubMed

    Nahabedian, Maurice Y

    2016-05-01

    The use of acellular dermal matrices in the setting of prosthetic breast reconstruction has captured the attention of many plastic surgeons. The regenerative capacity of these materials has provided additional tissue support to the mastectomy skin flaps with the ultimate result of improving surgical and aesthetic outcomes. Despite the benefits, there remains a significant diversity with regard to outcomes with some surgeons reporting increased morbidity. The reasons for this are varied but ultimately related to differences in patient selection and surgical techniques. The purpose of this article is to provide strategies for using acellular dermal matrix to achieve success in a manner that is usually associated with outcomes that are predictable and reproducible. PMID:27579223

  3. Prosthetic Breast Reconstruction With Acellular Dermal Matrices: Achieving Predictability and Reproducibility

    PubMed Central

    2016-01-01

    Summary: The use of acellular dermal matrices in the setting of prosthetic breast reconstruction has captured the attention of many plastic surgeons. The regenerative capacity of these materials has provided additional tissue support to the mastectomy skin flaps with the ultimate result of improving surgical and aesthetic outcomes. Despite the benefits, there remains a significant diversity with regard to outcomes with some surgeons reporting increased morbidity. The reasons for this are varied but ultimately related to differences in patient selection and surgical techniques. The purpose of this article is to provide strategies for using acellular dermal matrix to achieve success in a manner that is usually associated with outcomes that are predictable and reproducible. PMID:27579223

  4. Models of social evolution: can we do better to predict 'who helps whom to achieve what'?

    PubMed

    Rodrigues, António M M; Kokko, Hanna

    2016-02-01

    Models of social evolution and the evolution of helping have been classified in numerous ways. Two categorical differences have, however, escaped attention in the field. Models tend not to justify why they use a particular assumption structure about who helps whom: a large number of authors model peer-to-peer cooperation of essentially identical individuals, probably for reasons of mathematical convenience; others are inspired by particular cooperatively breeding species, and tend to assume unidirectional help where subordinates help a dominant breed more efficiently. Choices regarding what the help achieves (i.e. which life-history trait of the helped individual is improved) are similarly made without much comment: fecundity benefits are much more commonly modelled than survival enhancements, despite evidence that these may interact when the helped individual can perform life-history reallocations (load-lightening and related phenomena). We review our current theoretical understanding of effects revealed when explicitly asking 'who helps whom to achieve what', from models of mutual aid in partnerships to the very few models that explicitly contrast the strength of selection to help enhance another individual's fecundity or survival. As a result of idiosyncratic modelling choices in contemporary literature, including the varying degree to which demographic consequences are made explicit, there is surprisingly little agreement on what types of help are predicted to evolve most easily. We outline promising future directions to fill this gap. PMID:26729928

  5. Establishing Causality Using Longitudinal Hierarchical Linear Modeling: An Illustration Predicting Achievement From Self-Control

    PubMed Central

    Duckworth, Angela Lee; Tsukayama, Eli; May, Henry

    2010-01-01

    The predictive validity of personality for important life outcomes is well established, but conventional longitudinal analyses cannot rule out the possibility that unmeasured third-variable confounds fully account for the observed relationships. Longitudinal hierarchical linear models (HLM) with time-varying covariates allow each subject to serve as his or her own control, thus eliminating between-individual confounds. HLM also allows the directionality of the causal relationship to be tested by reversing time-lagged predictor and outcome variables. We illustrate these techniques through a series of models that demonstrate that within-individual changes in self-control over time predict subsequent changes in GPA but not vice-versa. The evidence supporting a causal role for self-control was not moderated by IQ, gender, ethnicity, or income. Further analyses rule out one time-varying confound: self-esteem. The analytic approach taken in this study provides the strongest evidence to date for the causal role of self-control in determining achievement. PMID:20976121

  6. The Achievement Flow Motive as an Element of the Autotelic Personality: Predicting Educational Attainment in Three Cultures

    ERIC Educational Resources Information Center

    Busch, Holger; Hofer, Jan; Chasiotis, Athanasios; Campos, Domingo

    2013-01-01

    Human behavior is directed by an implicit and an explicit motivational system. The intrinsic form of the implicit achievement motive has been demonstrated to predict the experience of flow. Thus, this achievement flow motive can be considered an integral component of the autotelic personality, posited in Flow Theory as dispositional difference in…

  7. Leveraging Improvements in Precipitation Measuring from GPM Mission to Achieve Prediction Improvements in Climate, Weather and Hydrometeorology

    NASA Technical Reports Server (NTRS)

    Smith, Eric A.

    2002-01-01

    the way for what ultimately is expected to become an internationally-organized operational global precipitation observing system. Notably, the broad societal applications of GPM are reflected in the United Nation s identification of this mission as a foremost candidate for its Peaceful Uses of Space Program. In this presentation, an overview of the GPM mission design will be presented, followed by an explanation of its scientific agenda as an outgrowth of making improvements in rain retrieval accuracy, microphysics dexterity, sampling frequency, and global coverage. All of these improvements offer new means to observe variability in precipitation and water cycle fluxes and to achieve improved predictability of weather, climate, and hydrometeorology. Specifically, the scientific agenda of GPM has been designed to leverage the measurement improvements to improve prognostic model performance, particularly quantitative precipitation forecasting and its linked phenomena at short, intermediate, and extended time scales. The talk will address how GPM measurements will enable better detection of accelerations and decelerations in regional and global water cycle processes and their relationship to climate variability, better impacts of precipitation data assimilation on numerical weather prediction and global climate reanalysis, and better performance from basin scale hydrometeorological models for short and long term flood-drought forecasting and seasonal fresh water resource assessment. Improved hydrometeorological forecasting will be possible by using continuous global precipitation observations to obtain better closure in water budgets and to generate more realistic forcing of the models themselves to achieve more accurate estimates of interception, infiltration, evaporation/transpiration fluxes, storage, and runoff.

  8. Prediction of Delinquency, Adjustment, and Academic Achievement Over a Five Year Period with the Kvaraceus Delinquency Proneness Scale.

    ERIC Educational Resources Information Center

    Benning, James J.; And Others

    The Kvaraceus Delinquency Proneness Scale (KD Scale) was developed as an instrument designed to aid in prediction of future juvenile delinquents. The purpose of this research was to evaluate the predictive validity of the instrument over a 5-year period. Indexes of delinquency adjustment and academic achievement served as the validational…

  9. Distraction by a monotube fixator to achieve limb lengthening: predictive factors for tibia trauma

    PubMed Central

    2013-01-01

    outcome in post traumatic tibia distraction. Conclusion Distraction by a monotube fixator appears effective in achieving correction >38.0% original tibia lengthening following traumatic bone gap. Predictive factors for poor outcome were useful for prognostication. PMID:23672599

  10. Extreme masking: achieving predictable outcomes in challenging situations with lithium disilicate bonded restorations.

    PubMed

    Hatai, Yugo

    2014-01-01

    In contemporary dentistry, we have a vast range of materials to choose from, and metal free restorations have become the premier materials for achieving the ultimate in both esthetics and durability. Metal-free restorations are utilized with more conservative preparations to preserve the vital natural dentition, and have proven to be superior alternatives to traditional porcelain-fused-to-metal (PFM) restorations in many cases. There are always "pros and cons" when selecting materials, and to make the best choice it is essential for dental professionals to plan precisely and understand their options in any clinical situation. Selecting suitable materials and techniques involves consideration of the following factors: - Esthetic zone. - Required strength based on the patient's occlusion/dental habits. - Preparation reduction. - Position of the margin. - Type of restoration/preparation. - The treating clinician's philosophy. - Stump shade. Final shade. One of the most significant challenges in the metal-free dentistry is the reproduction of natural dentition without the influence of a "negative stump" - a very dark or metal core showing through the final restorations. There are many factors to be considered when working on such a case, and controlling the opacity of the coping and crown is the key to success. This article presents a unique "outside of the box" technique that provides consistent, predictable and durable restorations, which provide the best possible esthetic outcome. PMID:24765627

  11. Accurate prediction of protein secondary structure and solvent accessibility by consensus combiners of sequence and structure information

    PubMed Central

    Pollastri, Gianluca; Martin, Alberto JM; Mooney, Catherine; Vullo, Alessandro

    2007-01-01

    Background Structural properties of proteins such as secondary structure and solvent accessibility contribute to three-dimensional structure prediction, not only in the ab initio case but also when homology information to known structures is available. Structural properties are also routinely used in protein analysis even when homology is available, largely because homology modelling is lower throughput than, say, secondary structure prediction. Nonetheless, predictors of secondary structure and solvent accessibility are virtually always ab initio. Results Here we develop high-throughput machine learning systems for the prediction of protein secondary structure and solvent accessibility that exploit homology to proteins of known structure, where available, in the form of simple structural frequency profiles extracted from sets of PDB templates. We compare these systems to their state-of-the-art ab initio counterparts, and with a number of baselines in which secondary structures and solvent accessibilities are extracted directly from the templates. We show that structural information from templates greatly improves secondary structure and solvent accessibility prediction quality, and that, on average, the systems significantly enrich the information contained in the templates. For sequence similarity exceeding 30%, secondary structure prediction quality is approximately 90%, close to its theoretical maximum, and 2-class solvent accessibility roughly 85%. Gains are robust with respect to template selection noise, and significant for marginal sequence similarity and for short alignments, supporting the claim that these improved predictions may prove beneficial beyond the case in which clear homology is available. Conclusion The predictive system are publicly available at the address . PMID:17570843

  12. Predictive Validity of the Boehm Test of Basic Concepts for Achievement in First Grade

    ERIC Educational Resources Information Center

    Estes, Gary D.; And Others

    1976-01-01

    The relation between performance on the Boehm Test of Basic Concepts (BTBC) and achievement in first grade was examined. The correlation between the BTBC and the Stanford Achievement Test was significant. The findings support Boehm's assertation that mastery of the concepts is related to achievement in the primary grades. (Author/JKS)

  13. Predicting Elementary and Secondary School Achievement with School-Related and Demographic Factors.

    ERIC Educational Resources Information Center

    Sutton, Alice; Soderstrom, Irina

    1999-01-01

    Investigated relationships between school and social factors, reported on the Illinois School Report Card, and student achievement, indicated on the Illinois Goal Assessment Program (IGAP). All of the independent variables except high school per-pupil expenditures significantly related to achievement scores. A school's IGAP achievement score was…

  14. 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.

  15. 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

  16. RepurposeVS: A Drug Repurposing-Focused Computational Method for Accurate Drug-Target Signature Predictions.

    PubMed

    Issa, Naiem T; Peters, Oakland J; Byers, Stephen W; Dakshanamurthy, Sivanesan

    2015-01-01

    We describe here RepurposeVS for the reliable prediction of drug-target signatures using X-ray protein crystal structures. RepurposeVS is a virtual screening method that incorporates docking, drug-centric and protein-centric 2D/3D fingerprints with a rigorous mathematical normalization procedure to account for the variability in units and provide high-resolution contextual information for drug-target binding. Validity was confirmed by the following: (1) providing the greatest enrichment of known drug binders for multiple protein targets in virtual screening experiments, (2) determining that similarly shaped protein target pockets are predicted to bind drugs of similar 3D shapes when RepurposeVS is applied to 2,335 human protein targets, and (3) determining true biological associations in vitro for mebendazole (MBZ) across many predicted kinase targets for potential cancer repurposing. Since RepurposeVS is a drug repurposing-focused method, benchmarking was conducted on a set of 3,671 FDA approved and experimental drugs rather than the Database of Useful Decoys (DUDE) so as to streamline downstream repurposing experiments. We further apply RepurposeVS to explore the overall potential drug repurposing space for currently approved drugs. RepurposeVS is not computationally intensive and increases performance accuracy, thus serving as an efficient and powerful in silico tool to predict drug-target associations in drug repurposing. PMID:26234515

  17. 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. PMID:25938675

  18. 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…

  19. 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.

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

    PubMed Central

    2014-01-01

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

  1. Classroom Factors and Student Characteristics Predicting Students' Use of Achievement Standards during Ability Self-Assessment.

    ERIC Educational Resources Information Center

    Mac Iver, Douglas

    1987-01-01

    Examines whether task structures, grading practices, and grouping patterns influence the achievement standards that upper-elementary students use in reaching a positive evaluation of their ability. (PCB)

  2. Calibrating the High Density Magnetic Port within Tissue Expanders to Achieve more Accurate Dose Calculations for Postmastectomy Patients with Immediate Breast Reconstruction

    NASA Astrophysics Data System (ADS)

    Jones, Jasmine; Zhang, Rui; Heins, David; Castle, Katherine

    In postmastectomy radiotherapy, an increasing number of patients have tissue expanders inserted subpectorally when receiving immediate breast reconstruction. These tissue expanders are composed of silicone and are inflated with saline through an internal metallic port; this serves the purpose of stretching the muscle and skin tissue over time, in order to house a permanent implant. The issue with administering radiation therapy in the presence of a tissue expander is that the port's magnetic core can potentially perturb the dose delivered to the Planning Target Volume, causing significant artifacts in CT images. Several studies have explored this problem, and suggest that density corrections must be accounted for in treatment planning. However, very few studies accurately calibrated commercial TP systems for the high density material used in the port, and no studies employed fusion imaging to yield a more accurate contour of the port in treatment planning. We compared depth dose values in the water phantom between measurement and TPS calculations, and we were able to overcome some of the inhomogeneities presented by the image artifact by fusing the KVCT and MVCT images of the tissue expander together, resulting in a more precise comparison of dose calculations at discrete locations. We expect this method to be pivotal in the quantification of dose distribution in the PTV. Research funded by the LS-AMP Award.

  3. Can the Gibbs free energy of adsorption be predicted efficiently and accurately: an M05-2X DFT study.

    PubMed

    Michalkova, A; Gorb, L; Hill, F; Leszczynski, J

    2011-03-24

    This study presents new insight into the prediction of partitioning of organic compounds between a carbon surface (soot) and water, and it also sheds light on the sluggish desorption of interacting molecules from activated and nonactivated carbon surfaces. This paper provides details about the structure and interactions of benzene, polycyclic aromatic hydrocarbons, and aromatic nitrocompounds with a carbon surface modeled by coronene using a density functional theory approach along with the M05-2X functional. The adsorption was studied in vacuum and from water solution. The molecules studied are physisorbed on the carbon surface. While the intermolecular interactions of benzene and hydrocarbons are governed by dispersion forces, nitrocompounds are adsorbed also due to quite strong electrostatic interactions with all types of carbon surfaces. On the basis of these results, we conclude that the method of prediction presented in this study allows one to approach the experimental level of accuracy in predicting thermodynamic parameters of adsorption on a carbon surface from the gas phase. The empirical modification of the polarized continuum model leads also to a quantitative agreement with the experimental data for the Gibbs free energy values of the adsorption from water solution. PMID:21361266

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

    PubMed Central

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

    2016-01-01

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

  5. 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

  6. Predicting Early Academic Failure in High School from Prior Academic Achievement, Psychosocial Characteristics, and Behavior

    ERIC Educational Resources Information Center

    Casillas, Alex; Robbins, Steve; Allen, Jeff; Kuo, Yi-Lung; Hanson, Mary Ann; Schmeiser, Cynthia

    2012-01-01

    The authors examined the differential effects of prior academic achievement, psychosocial, behavioral, demographic, and school context factors on early high school grade point average (GPA) using a prospective study of 4,660 middle-school students from 24 schools. The findings suggest that (a) prior grades and standardized achievement are the…

  7. The Role of Family Orientation in Predicting Korean Boys' and Girls' Achievement Motivation to Learn Mathematics

    ERIC Educational Resources Information Center

    Kim, Jung-In; Chung, Hyewon

    2012-01-01

    Informed by achievement goal orientation and self-determination theories, we explored the role of cultural/contextual factors on Korean students' achievement motivation. Specifically, we examined the role of the Korean middle school students' family orientation as a mediator between their perceptions of parent goals or motivating styles and their…

  8. Parental Warmth, Control, and Involvement in Schooling: Predicting Academic Achievement among Korean American Adolescents.

    ERIC Educational Resources Information Center

    Kim, Kyoungho; Rohner, Ronald P.

    2002-01-01

    Explored the relationship between parenting style and academic achievement of Korean American adolescents, investigating the influence of perceived parental warmth and control and improvement in schooling. Survey data indicated that authoritative paternal parenting related to optimal academic achievement. Differences in maternal parenting styles…

  9. School Readiness Factors for Predicting High and Low Achieving Students in First Grade

    ERIC Educational Resources Information Center

    Davion, Edward, Jr.

    2011-01-01

    When analyzed according to race and ethnicity, poverty level, parental education level, as well as other related factors in schools in America, academic achievement disparities negatively impact educational outcomes for poor children and children of color on a consistent basis. At all educational levels, academic achievement and attainments of…

  10. Stratified neutrophil-to-lymphocyte ratio accurately predict mortality risk in hepatocellular carcinoma patients following curative liver resection

    PubMed Central

    Huang, Gui-Qian; Zhu, Gui-Qi; Liu, Yan-Long; Wang, Li-Ren; Braddock, Martin; Zheng, Ming-Hua; Zhou, Meng-Tao

    2016-01-01

    Objectives Neutrophil lymphocyte ratio (NLR) has been shown to predict prognosis of cancers in several studies. This study was designed to evaluate the impact of stratified NLR in patients who have received curative liver resection (CLR) for hepatocellular carcinoma (HCC). Methods A total of 1659 patients who underwent CLR for suspected HCC between 2007 and 2014 were reviewed. The preoperative NLR was categorized into quartiles based on the quantity of the study population and the distribution of NLR. Hazard ratios (HRs) and 95% confidence intervals (CIs) were significantly associated with overall survival (OS) and derived by Cox proportional hazard regression analyses. Univariate and multivariate Cox proportional hazard regression analyses were evaluated for association of all independent parameters with disease prognosis. Results Multivariable Cox proportional hazards models showed that the level of NLR (HR = 1.031, 95%CI: 1.002-1.060, P = 0.033), number of nodules (HR = 1.679, 95%CI: 1.285-2.194, P<0.001), portal vein thrombosis (HR = 4.329, 95%CI: 1.968-9.521, P<0.001), microvascular invasion (HR = 2.527, 95%CI: 1.726-3.700, P<0.001) and CTP score (HR = 1.675, 95%CI: 1.153-2.433, P = 0.007) were significant predictors of mortality. From the Kaplan-Meier analysis of overall survival (OS), each NLR quartile showed a progressively worse OS and apparent separation (log-rank P=0.008). The highest 5-year OS rate following CLR (60%) in HCC patients was observed in quartile 1. In contrast, the lowest 5-year OS rate (27%) was obtained in quartile 4. Conclusions Stratified NLR may predict significantly improved outcomes and strengthen the predictive power for patient responses to therapeutic intervention. PMID:26716411

  11. The Utility of the Dynamic Indicators of Basic Early Literacy Skills (DIBELS) in Predicting Reading Achievement

    ERIC Educational Resources Information Center

    Echols, Julie M. Young

    2010-01-01

    Reading proficiency is the goal of many local and national reading initiatives. A key component of these initiatives is accurate and reliable reading assessment. In this high-stakes testing arena, the Dynamic Indicators of Basic Early Literacy Skills (DIBELS) has emerged as a preferred measure for identification of students at risk for reading…

  12. Predicting Classroom Achievement from Active Responding on a Computer-Based Groupware System.

    ERIC Educational Resources Information Center

    Shin, Jongho; Deno, Stanley L.; Robinson, Steven L.; Marston, Douglas

    2000-01-01

    The predictive validity of active responding on a computer-based groupware system was examined with 48 second graders. Results showed that active responding correlated highly with initial and final performance measures and that active responding contributed significantly to predicting final performance when initial performance was controlled.…

  13. Multivariate Screening Model for Later Word Reading Achievement: Predictive Utility of Prereading Skills and Cognitive Ability

    ERIC Educational Resources Information Center

    MacDonald, Heidi H.; Sullivan, Amanda L.; Watkins, Marley W.

    2013-01-01

    The present study used multiple regression to determine the predictive value of Kindergarten phonemic awareness, rapid serial naming, letter knowledge, and cognitive ability for predicting first-grade word reading and fluency. Participants were 131 first-grade students from a mid-Atlantic school system. A combination of predictor variables was…

  14. 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

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

    NASA Astrophysics Data System (ADS)

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

    1994-01-01

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

  16. 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

  17. An Empirical Approach toward the Prediction of Students' Science Achievement in the United States and the Peoples' Republic of China.

    ERIC Educational Resources Information Center

    Wang, Jianjun; Staver, John R.

    An empirical approach is adopted in this paper to explore a possible model for prediction of students' science achievement in China and the United States. Construction of the model is based on the ninth-grade data base from Phase 2 of the Second International Education Association Science Study (SISS) in the United States and the SISS Extension…

  18. The Career Path of the Assistant Principalship as It Pertains to the Prediction of School Achievement in South Texas

    ERIC Educational Resources Information Center

    Castillo, Criselda I.

    2009-01-01

    The purpose of the study was to collect data to determine if assistant principal experience predicts student achievement as measured by the outcome measures of (1) school overall accountability rating, (2) Texas Assessment of Knowledge and Skills (TAKS) reading/English language arts score, (3) TAKS mathematics score, and (4) campus attendance rate…

  19. Predictive Power of School Based Assessment Scores on Students' Achievement in Junior Secondary Certificate Examination (JSCE) in English and Mathematics

    ERIC Educational Resources Information Center

    Opara, Ijeoma M.; Onyekuru, Bruno U.; Njoku, Joyce U.

    2015-01-01

    The study investigated the predictive power of school based assessment scores on students' achievement in Junior Secondary Certificate Examination (JSCE) in English and Mathematics. Two hypotheses tested at 0.05 level of significance guided the study. The study adopted an ex-post facto research design. A sample of 250 students were randomly drawn…

  20. Predicting School Achievement from Cognitive and Non-Cognitive Variables in a Chinese Sample of Elementary School Children

    ERIC Educational Resources Information Center

    Lu, Liping; Weber, Heike S.; Spinath, Frank M.; Shi, Jiannong

    2011-01-01

    The present study had two aims: First, to investigate the joint and specific roles of working memory (WM) and intelligence as predictors of school achievement. And second, to replicate and extend earlier findings (Spinath, Spinath, Harlaar, & Plomin, 2006) on the incremental validity of non-cognitive over cognitive abilities in the prediction of…

  1. Broad and Narrow Personality Traits Predicting Academic Achievement over Compulsory Schooling: A Cross-Sectional Study in Two Countries

    ERIC Educational Resources Information Center

    Zupancic, Maja; Kavcic, Tina; Slobodskaya, Helena R.; Akhmetova, Olga A.

    2016-01-01

    Incremental predictive value of 5 broad and 13 narrow personality traits for academic achievement over and beyond age, gender, parental education, and country was examined in Russian and Slovene 8- to 15-year-olds. Personality data were collected from mothers (Russia: N = 994, Slovenia: N = 624) and adolescents (Russia: N = 481, Slovenia: N = 310)…

  2. Middle School Characteristics That Predict Student Achievement, as Measured by the School-Wide California API Score

    ERIC Educational Resources Information Center

    Paredes, Josie Abaroa

    2013-01-01

    The purpose of this study was to investigate, through quantitative research, effective middle school characteristics that predict student achievement, as measured by the school-wide California API score. Characteristics were determined using an instrument developed by the Office of Superintendent of Public Instruction (OSPI), which asked middle…

  3. Predicting First Grade Reading Achievement for Spanish-Speaking Kindergartners: Is Early Literacy Screening in English Valid?

    ERIC Educational Resources Information Center

    Ford, Karen L.; Invernizzi, Marcia A.; Huang, Francis

    2014-01-01

    This study explored the viability of using kindergarten measures of phonological awareness, alphabet knowledge, and orthographic knowledge, administered in English, to predict first grade reading achievement of Spanish-speaking English language learners. The primary research question was: Do kindergarten measures of early literacy skills in…

  4. What Is the Predict Level of Which Computer Using Skills Measured in PISA for Achievement in Mathematics

    ERIC Educational Resources Information Center

    Ziya, Engin; Dogan, Nuri; Kelecioglu, Hulya

    2010-01-01

    This study aims at determining the extent to which computer using skills specified in Project for International Students Evaluation (PISA) 2006 predict Turkish students' achievement in mathematics. Apart from questions on mathematics, science and reading competencies, a student questionnaire, a school questionnaire and a parent questionnaire were…

  5. Predicting Teachers' Achievement Goals for Teaching: The Role of Perceived School Goal Structure and Teachers' Sense of Efficacy

    ERIC Educational Resources Information Center

    Cho, YoonJung; Shim, Sungok Serena

    2013-01-01

    The present study investigated contextual and personal factors associated with teachers' achievement goals for teaching. A total of 211 teachers completed an online survey. Hierarchical multiple regression analyses revealed that perceived school mastery goal structure and performance goal structure predicted teachers' mastery goals and…

  6. How preschool executive functioning predicts several aspects of math achievement in Grades 1 and 3: A longitudinal study.

    PubMed

    Viterbori, Paola; Usai, M Carmen; Traverso, Laura; De Franchis, Valentina

    2015-12-01

    This longitudinal study analyzes whether selected components of executive function (EF) measured during the preschool period predict several indices of math achievement in primary school. Six EF measures were assessed in a sample of 5-year-old children (N = 175). The math achievement of the same children was then tested in Grades 1 and 3 using both a composite math score and three single indices of written calculation, arithmetical facts, and problem solving. Using previous results obtained from the same sample of children, a confirmatory factor analysis examining the latent EF structure in kindergarten indicated that a two-factor model provided the best fit for the data. In this model, inhibition and working memory (WM)-flexibility were separate dimensions. A full structural equation model was then used to test the hypothesis that math achievement (the composite math score and single math scores) in Grades 1 and 3 could be explained by the two EF components comprising the kindergarten model. The results indicate that the WM-flexibility component measured during the preschool period substantially predicts mathematical achievement, especially in Grade 3. The math composite scores were predicted by the WM-flexibility factor at both grade levels. In Grade 3, both problem solving and arithmetical facts were predicted by the WM-flexibility component. The results empirically support interventions that target EF as an important component of early childhood mathematics education. PMID:26218333

  7. A Study of the Semantic Differential Based on Motivational Concepts as a Technique for Predicting Student Achievement.

    ERIC Educational Resources Information Center

    Sizemore, Oral Glen

    The purpose of this study was to develop a semantic differential scale based on achievement motivation concepts by which grade point averages could be predicted. A scale was constructed and administered to 944 freshmen at Northeastern State College in Fall 1967. Two approaches were used. One was to combine semantic differential scale scores…

  8. Predicting Long-Term Growth in Students' Mathematics Achievement: The Unique Contributions of Motivation and Cognitive Strategies

    ERIC Educational Resources Information Center

    Murayama, Kou; Pekrun, Reinhard; Lichtenfeld, Stephanie; vom Hofe, Rudolf

    2013-01-01

    This research examined how motivation (perceived control, intrinsic motivation, and extrinsic motivation), cognitive learning strategies (deep and surface strategies), and intelligence jointly predict long-term growth in students' mathematics achievement over 5 years. Using longitudinal data from six annual waves (Grades 5 through 10;…

  9. Examining the Predictive Power of Autonomy and Self-Evaluation on High School Students' Language Achievement

    ERIC Educational Resources Information Center

    Yuksel, Ismail; Toker, Yalcin

    2013-01-01

    This study aims to determine language learners' autonomy, self-evaluation levels and to examine the predictive power of these two variables on language achievement. The study was designed as mixed method design and was conducted with 108 high school students. Data were collected through an autonomy scale, a self-evaluation scale, schools…

  10. Accurate prediction of the toxicity of benzoic acid compounds in mice via oral without using any computer codes.

    PubMed

    Keshavarz, Mohammad Hossein; Gharagheizi, Farhad; Shokrolahi, Arash; Zakinejad, Sajjad

    2012-10-30

    Most of benzoic acid derivatives are toxic, which may cause serious public health and environmental problems. Two novel simple and reliable models are introduced for desk calculations of the toxicity of benzoic acid compounds in mice via oral LD(50) with more reliance on their answers as one could attach to the more complex outputs. They require only elemental composition and molecular fragments without using any computer codes. The first model is based on only the number of carbon and hydrogen atoms, which can be improved by several molecular fragments in the second model. For 57 benzoic compounds, where the computed results of quantitative structure-toxicity relationship (QSTR) were recently reported, the predicted results of two simple models of present method are more reliable than QSTR computations. The present simple method is also tested with further 324 benzoic acid compounds including complex molecular structures, which confirm good forecasting ability of the second model. PMID:22959133

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

    SciTech Connect

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

    2009-04-24

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

  12. Breadth of knowledge vs. grades: What best predicts achievement in the first year of health sciences programmes?

    PubMed Central

    Li, Meisong; McKimm, Judy; Smith, Melinda

    2012-01-01

    This study aimed to identify those features within secondary school curricula and assessment, particularly science subjects that best predict academic achievement in the first year of three different three-year undergraduate health professional programmes (nursing, pharmacy, and health sciences) at a large New Zealand university. In particular, this study compared the contribution of breadth of knowledge (number of credits acquired) versus grade level (grade point average) and explored the impact of demographic variables on achievement. The findings indicated that grades are the most important factor predicting student success in the first year of university. Although taking biology and physics at secondary school has some impact on university first year achievement, the effect is relatively minor. PMID:22639706

  13. 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

  14. 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

  15. 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

  16. 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.

  17. Understanding motivational structures that differentially predict engagement and achievement in middle school science

    NASA Astrophysics Data System (ADS)

    Lee, Christine S.; Hayes, Kathryn N.; Seitz, Jeffery; DiStefano, Rachelle; O'Connor, Dawn

    2016-01-01

    Middle school has been documented as the period in which a drop in students' science interest and achievement occurs. This trend indicates a lack of motivation for learning science; however, little is known about how different aspects of motivation interact with student engagement and science learning outcomes. This study examines the relationships among motivational factors, engagement, and achievement in middle school science (grades 6-8). Data were obtained from middle school students in the United States (N = 2094). The theoretical relationships among motivational constructs, including self-efficacy, and three types of goal orientations (mastery, performance approach, and performance avoid) were tested. The results showed that motivation is best modeled as distinct intrinsic and extrinsic factors; lending evidence that external, performance based goal orientations factor separately from self-efficacy and an internal, mastery based goal orientation. Second, a model was tested to examine how engagement mediated the relationships between intrinsic and extrinsic motivational factors and science achievement. Engagement mediated the relationship between intrinsic motivation and science achievement, whereas extrinsic motivation had no relationship with engagement and science achievement. Implications for how classroom practice and educational policy emphasize different student motivations, and in turn, can support or hinder students' science learning are discussed.

  18. Achieving the prediction results by visualized treatment objective following anterior maxillary segmental osteotomy. A retrospective study.

    PubMed

    Venkatesh, V; Kumar, K A Jeevan; Mohan, A P; Kumar, B Pavan; Kunusoth, Ramesh; Kumar, M Pavan

    2013-06-01

    This study used the manual visualized treatment objectives (VTO) as a tool to evaluate the predictive value of the computer-assisted VTO. Presurgical cephalometric tracing predictions generated by oral and maxillofacial surgeons and computer-assisted VTOs were compared with the postsurgical outcome as seen on lateral cephalometric tracings. Ten measurements of the predicted and actual postsurgical hard tissue landmarks were compared statistically. A paired Student's t test showed that in nine of ten measurements, there were no statistically significant differences in the mean values of manual VTO (MVTO). Statistically significant differences were found in one of the four linear measurements (cant of upper lip P - 0.0001). For computer assisted (CAVTO) Student's t test showed that in nine of ten measurements, there were no statistically significant differences in the mean values. Statistically significant differences were found in one of the four linear measurements (nasolabial angle, P  - 0.0001). From these data, it appears that both VTOs demonstrated good predictive comparative outcome, and are equally predictive, but CAVTO is precise. PMID:24431838

  19. Examining Organizational Practices That Predict Persistence among High-Achieving Black Males in High School

    ERIC Educational Resources Information Center

    Anderson, Kenneth Alonzo

    2016-01-01

    Background/Context: This article summarizes an increasing trend of antideficit Black male research in mathematics and highlights opportunities to add to the research. A review of the literature shows that antideficit researchers often examine relationships between individual traits and persistence of high-achieving Black males in mathematics.…

  20. Using the LASSI to Predict First Year College Achievement: Is a Gender-Specific Approach Necessary?

    ERIC Educational Resources Information Center

    Bender, David S.; Garner, Joanna K.

    2010-01-01

    LASSI responses were combined with SAT and GPA information from 342 first year college students to examine relationships between study habits, motivation, gender and achievement. Gender pervasively influenced the results. Despite lower SAT scores, females attained higher first year college GPAs. LASSI [Learning and Study Skills Inventory]…

  1. Regression Analyses of Self-Regulatory Concepts to Predict Community College Math Achievement and Persistence

    ERIC Educational Resources Information Center

    Gramlich, Stephen Peter

    2010-01-01

    Open door admissions at community colleges bring returning adults, first timers, low achievers, disabled persons, and immigrants. Passing and retention rates for remedial and non-developmental math courses can be comparatively inadequate (LAVC, 2005; CCPRDC, 2000; SBCC, 2004; Seybert & Soltz, 1992; Waycaster, 2002). Mathematics achievement…

  2. A Model for Predicting Learning Flow and Achievement in Corporate e-Learning

    ERIC Educational Resources Information Center

    Joo, Young Ju; Lim, Kyu Yon; Kim, Su Mi

    2012-01-01

    The primary objective of this study was to investigate the determinants of learning flow and achievement in corporate online training. Self-efficacy, intrinsic value, and test anxiety were selected as learners' motivational factors, while perceived usefulness and ease of use were also selected as learning environmental factors. Learning flow was…

  3. Arts Involvement Predicts Academic Achievement Only When the Child Has a Musical Instrument

    ERIC Educational Resources Information Center

    Young, Laura N.; Cordes, Sara; Winner, Ellen

    2014-01-01

    We examined the associations between academic achievement and arts involvement (access to a musical instrument for the child at home, participation in unspecified after-school arts activities) in a sample of 2339 11-12-year-olds surveyed in the USA between 1998 and 2008. We compared the contributions of these variables to other kinds of cognitive…

  4. Variables predicting students' first semester achievement in a graduate-entry dental school in Korea.

    PubMed

    Kim, Minkang; Lee, Jae Il

    2007-04-01

    The purpose of this study was to explore factors that influence academic achievement for dental students during their first semester of graduate-entry programs. Nine variables were considered, including students' age, gender, undergraduate grade point averages (UGPAs), Dental Education Eligibility Test (DEET) scores, oral exam, and interview selection scores. DEET is a standardized aptitude test developed for graduate-entry dental programs in Korea. The test consists of four separate sections: reading comprehension, scientific reasoning parts I and II, and perceptual ability. GPA scores were obtained as a measure of academic achievement from ninety students at the graduate-entry dental program at Seoul National University, Korea. Path analysis was used to test the hypothetical model of causal influence. The most significant predictors with direct influence on achievement were scores from both scientific reasoning parts I and II, undergraduate GPAs, and gender. Age, scores from the other subjects in DEET (reading comprehension and perceptual ability), and oral exam scores were found to bear no relation to the students' achievement. PMID:17468318

  5. Factors Predictive of Mathematics Achievement in Kindergarten, First and Third Grades: An Opportunity-Propensity Analysis

    ERIC Educational Resources Information Center

    Byrnes, James P.; Wasik, Barbara A.

    2009-01-01

    A secondary analysis of the Early Childhood Longitudinal Study-Kindergarten Sample (N = 17,401) was conducted to determine the factors that are most strongly associated with math achievement during kindergarten, first grade, and third grade. Factors from the following three categories were considered: antecedent factors (e.g., family…

  6. Achievement Strategies during University Studies Predict Early Career Burnout and Engagement

    ERIC Educational Resources Information Center

    Salmela-Aro, Katariina; Tolvanen, Asko; Nurmi, Jari-Erik

    2009-01-01

    To examine whether individuals' achievement strategies measured during university studies would have an impact on work burnout and work engagement measured 10, 14 and 17 years later, 292 university students completed the SAQ strategy questionnaire three times while at university, and the work burnout inventory three times and work engagement…

  7. Gender, Ethnicity, and Social Cognitive Factors Predicting the Academic Achievement of Students in Engineering.

    ERIC Educational Resources Information Center

    Hackett, Gail; And Others

    1992-01-01

    Examined relationships of measures of occupational and academic self-efficacy; vocational interests; outcome expectations; academic ability; and perceived stress, support, and coping to academic achievement of engineering/science majors (n=197). Self-efficacy for academic milestones, in combination with other academic and support variables, was…

  8. Social Adjustment and Academic Achievement: A Predictive Model for Students with Diverse Academic and Behavior Competencies

    ERIC Educational Resources Information Center

    Ray, Corey E.; Elliott, Stephen N.

    2006-01-01

    This study examined the hypothesized relationship between social adjustment, as measured by perceived social support, self-concept, and social skills, and performance on academic achievement tests. Participants included 27 teachers and 77 fourth- and eighth-grade students with diverse academic and behavior competencies. Teachers were asked to…

  9. Graduate-Entry Medical Student Variables that Predict Academic and Clinical Achievement

    ERIC Educational Resources Information Center

    Blackman, Ian; Darmawan, I Gusti Ngurah

    2004-01-01

    A hypothetical model was formulated to explore factors that influenced academic and clinical achievement for graduate-entry medical students completing their third year of university studies. Nine latent variables were considered including the students' background, previous successes with their undergraduate and postgraduate studies and their…

  10. Understanding Student Goal Orientation Tendencies to Predict Student Performance: A 2x2 Achievement Goal Orientation

    ERIC Educational Resources Information Center

    Miller, Mark Alan

    2013-01-01

    The study tested the 2X2 model of the Achievement Goal Orientation (AGO) theory in a military technical training environment while using the Air Force Officers Qualifying Test's academic aptitude score to control for the differences in the students' academic aptitude. The study method was quantitative and the design was correlational.…

  11. Understanding Motivational Structures That Differentially Predict Engagement and Achievement in Middle School Science

    ERIC Educational Resources Information Center

    Lee, Christine S.; Hayes, Kathryn N.; Seitz, Jeffery; DiStefano, Rachelle; O'Connor, Dawn

    2016-01-01

    Middle school has been documented as the period in which a drop in students' science interest and achievement occurs. This trend indicates a lack of motivation for learning science; however, little is known about how different aspects of motivation interact with student engagement and science learning outcomes. This study examines the…

  12. How Curriculum and Classroom Achievement Predict Teacher Time on Lecture- and Inquiry-Based Mathematics Activities

    ERIC Educational Resources Information Center

    Kaufman, Julia H.; Rita Karam; Pane, John F.; Junker, Brian W.

    2012-01-01

    This study drew on data from a large, randomized trial of Cognitive Tutor Algebra (CTA) in high-poverty settings to investigate how mathematics curricula and classroom achievement related to teacher reports of time spent on inquiry-based and lecture-based mathematics activities. We found that teachers using the CTA curriculum reported more time on…

  13. Undergraduate Nurse Variables that Predict Academic Achievement and Clinical Competence in Nursing

    ERIC Educational Resources Information Center

    Blackman, Ian; Hall, Margaret; Darmawan, I Gusti Ngurah.

    2007-01-01

    A hypothetical model was formulated to explore factors that influenced academic and clinical achievement for undergraduate nursing students. Sixteen latent variables were considered including the students' background, gender, type of first language, age, their previous successes with their undergraduate nursing studies and status given for…

  14. Implicit Social Cognitions Predict Sex Differences in Math Engagement and Achievement

    ERIC Educational Resources Information Center

    Nosek, Brian A.; Smyth, Frederick L.

    2011-01-01

    Gender stereotypes about math and science do not need to be endorsed, or even available to conscious introspection, to contribute to the sex gap in engagement and achievement in science, technology, engineering, and mathematics (STEM). The authors examined implicit math attitudes and stereotypes among a heterogeneous sample of 5,139 participants.…

  15. Predictive Relations between Peer Victimization and Academic Achievement in Chinese Children

    ERIC Educational Resources Information Center

    Liu, Junsheng; Bullock, Amanda; Coplan, Robert J.

    2014-01-01

    The goal of this study was to explore longitudinal associations between peer victimization and academic achievement in Chinese children. Participants were N = 805 3rd-grade students (486 boys, 319 girls; M[subscript age] = 9.5 years, SD = 3 months) attending primary schools in Shanghai, People's Republic of China. At Time 1 and Time 2 (2 years…

  16. The Relationship between Vocational Interests, Self-Efficacy, and Achievement in the Prediction of Educational Pathways

    ERIC Educational Resources Information Center

    Patrick, Lyn; Care, Esther; Ainley, Mary

    2011-01-01

    The influence of vocational interest, self-efficacy beliefs, and academic achievement on choice of educational pathway is described for a cohort of Australian students. Participants were 189 students aged 14-15 years, who were considering either academic or applied learning pathways and subject choices for the final 3 years of secondary school.…

  17. Predicting Children's Achievement from Teacher Judgements: An Alternative to Standardized Testing.

    ERIC Educational Resources Information Center

    Quay, Lorene C.; Steele, Donald C.

    1998-01-01

    Constructed and tested for validity the Developmental Rating Scale (DRS), which uses teacher judgments about the academic development of children to evaluate student achievement. Teachers evaluated children at the pre-kindergarten, first-, and second-grade levels using the DRS and the Developmental Profile II (DPII). Found that the DRS, unlike the…

  18. Preschool Teaching Students' Prediction of Decision Making Strategies and Academic Achievement on Learning Motivations

    ERIC Educational Resources Information Center

    Acat, M. Bahaddin; Dereli, Esra

    2012-01-01

    The purpose of this study was to identify problems and motivation sources and strategies of decision-making of the students' attending preschool education teacher department, was to determine the relationship between learning motivation and strategies of decision-making, academic achievement of students, was to determine whether strategies of…

  19. Factors Predicting Science Achievement of Immigrant and Non-Immigrant Students: A Multilevel Analysis

    ERIC Educational Resources Information Center

    Areepattamannil, Shaljan; Kaur, Berinderjeet

    2013-01-01

    This study, employing hierarchical linear modeling (HLM), sought to investigate the student-level and school-level factors associated with the science achievement of immigrant and non-immigrant students among a national sample of 22,646 students from 896 schools in Canada. While student background characteristics such as home language, family…

  20. Moving Toward Integrating Gene Expression Profiling Into High-Throughput Testing: A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium.

    PubMed

    Ryan, Natalia; Chorley, Brian; Tice, Raymond R; Judson, Richard; Corton, J Christopher

    2016-05-01

    Microarray profiling of chemical-induced effects is being increasingly used in medium- and high-throughput formats. Computational methods are described here to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), often modulated by potential endocrine disrupting chemicals. ERα biomarker genes were identified by their consistent expression after exposure to 7 structurally diverse ERα agonists and 3 ERα antagonists in ERα-positive MCF-7 cells. Most of the biomarker genes were shown to be directly regulated by ERα as determined by ESR1 gene knockdown using siRNA as well as through chromatin immunoprecipitation coupled with DNA sequencing analysis of ERα-DNA interactions. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression datasets from experiments using MCF-7 cells, including those evaluating the transcriptional effects of hormones and chemicals. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% and 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) ER reference chemicals including "very weak" agonists. Importantly, the biomarker predictions accurately replicated predictions based on 18 in vitro high-throughput screening assays that queried different steps in ERα signaling. For 114 chemicals, the balanced accuracies were 95% and 98% for activation or suppression, respectively. These results demonstrate that the ERα gene expression biomarker can accurately identify ERα modulators in large collections of microarray data derived from MCF-7 cells. PMID:26865669

  1. Most Likely to Achieve: Predicting Early Success of the Practical Nurse Student

    ERIC Educational Resources Information Center

    Cline, April P.

    2013-01-01

    It is important that practical nurse (PN) educators be able to identify which students are likely to be successful in their programs. However, the majority of literature related to predicting success of nursing students has been done on baccalaureate nursing students in the university setting. This study sought to determine whether the same…

  2. Using Hierarchical Linear Modelling to Examine Factors Predicting English Language Students' Reading Achievement

    ERIC Educational Resources Information Center

    Fung, Karen; ElAtia, Samira

    2015-01-01

    Using Hierarchical Linear Modelling (HLM), this study aimed to identify factors such as ESL/ELL/EAL status that would predict students' reading performance in an English language arts exam taken across Canada. Using data from the 2007 administration of the Pan-Canadian Assessment Program (PCAP) along with the accompanying surveys for students and…

  3. Approaches to Learning and Age in Predicting College Students' Academic Achievement

    ERIC Educational Resources Information Center

    Cetin, Baris

    2016-01-01

    The aim of this study is to determine whether the approaches to learning and age are significantly correlated to grade point average (GPA) in early childhood education students. In addition, another purpose of this study is to determine whether approaches to learning and age predicted students' GPAs in the Early Childhood Education Department. The…

  4. Predicting Reading and Arithmetic Achievement by Using Bender Gestalt and Visual Memory Technique.

    ERIC Educational Resources Information Center

    Rust, James O.; And Others

    1982-01-01

    First grade students were administered a screening battery that included the Otis-Lennon Mental Ability Test, the Metropolitan Readiness Test, the Bender Gestalt Test, and the Visual Memory Technique. Stepwise regression equations revealed that the Bender Gestalt Test significantly increased the predictive power of the test battery. (FL)

  5. PREDICTING ACHIEVEMENT IN TECHNICAL PROGRAMS AT THE NORTH DAKOTA STATE SCHOOL OF SCIENCE.

    ERIC Educational Resources Information Center

    ANDERSON, ROGER C.

    DATA WERE COLLECTED FROM SCHOOL RECORDS FOR 876 STUDENTS ENROLLED IN SIX TECHNICAL PROGRAMS FROM 1961-63. THIS PROVIDES EIGHT BIOGRAPHICAL AND 17 ACADEMIC VARIABLES WHICH WERE EXAMINED FOR THEIR USEFULNESS IN PREDICTING STUDENT SUCCESS. THE STUDENT SAMPLE WAS DIVIDED INTO GRADUATES AND NONGRADUATES. NONGRADUATES WERE THOSE WHO ATTENDED FOUR OR…

  6. End of Course Grades and Standardized Test Scores: Are Grades Predictive of Student Achievement?

    ERIC Educational Resources Information Center

    Ricketts, Christine R.

    2010-01-01

    This study examined the extent to which end-of-course grades are predictive of Virginia Standards of Learning test scores in nine high school content areas. It also analyzed the impact of the variables school cluster attended, gender, ethnicity, disability status, Limited English Proficiency status, and socioeconomic status on the relationship…

  7. A Brief Screening Battery for Predicting School Achievement at Ages Seven and Nine Years.

    ERIC Educational Resources Information Center

    Friedman, Robert; And Others

    1980-01-01

    The Beery-Butkenica Developmental Test and the Caldwell Test were the best predictors. Combining the academic performance with visual-motor integration results at age seven years yielded 89 percent accuracy of prediction at age nine years. The false-positive rate represents the problem of mislabeling children as school failures. (Author)

  8. Predictive Validity of the Vane for the Stanford Early School Achievement Test. Report No. l25.

    ERIC Educational Resources Information Center

    Hersh, Leonard R.

    Evidence on the predictive validity of the Vane Kindergarten Test (VKT) as a part of the comprehensive screening and assessment battery administered by the Horseheads Central School District in New York is presented. Variable numbers of students at each of six elementary schools were administered the VKT. At the end of the kindergarten year, all…

  9. Academic Motivation and Self-Regulated Learning in Predicting Academic Achievement in College

    ERIC Educational Resources Information Center

    Çetin, Baris

    2015-01-01

    The purpose of this study was to determine whether academic motivation and academic self-regulated learning predicted students' GPAs in the Early Childhood Education Department. The study participants consisted of 166 early childhood education majors enrolled in the 2014 spring semester at Georgia Southern University, USA. Data were gathered using…

  10. Predicting subjective vitality and performance in sports: the role of passion and achievement goals.

    PubMed

    Li, Chiung-Huang

    2010-06-01

    The major purpose of this study was to test the hypothesized paths from dualistic passions through achievement goals to subjective vitality and performance in sports. 645 high school athletes participated. The proposed structural equation model, with relationships between dualistic passions and subjective vitality and sports performance mediated by achievement goals, fit the data well, especially for mastery-approach and performance-approach goals. Harmonious and obsessive passions may lead athletes to high performance via the adoption of mastery-approach goals. However, these passions seem to have two paths influencing personal functioning: direct effects make players feel energetic, and indirect effects on subjective vitality through adoption of mastery-approach and performance-approach goals. PMID:20865990

  11. Early noninvasive measurement of the indocyanine green plasma disappearance rate accurately predicts early graft dysfunction and mortality after deceased donor liver transplantation.

    PubMed

    Olmedilla, Luis; Pérez-Peña, José María; Ripoll, Cristina; Garutti, Ignacio; de Diego, Roberto; Salcedo, Magdalena; Jiménez, Consuelo; Bañares, Rafael

    2009-10-01

    Early diagnosis of graft dysfunction in liver transplantation is essential for taking appropriate action. Indocyanine green clearance is closely related to liver function and can be measured noninvasively by spectrophotometry. The objectives of this study were to prospectively analyze the relationship between the indocyanine green plasma disappearance rate (ICGPDR) and early graft function after liver transplantation and to evaluate the role of ICGPDR in the prediction of severe graft dysfunction (SGD). One hundred seventy-two liver transplants from deceased donors were analyzed. Ten patients had SGD: 6 were retransplanted, and 4 died while waiting for a new graft. The plasma disappearance rate was measured 1 hour (PDRr60) and within the first 24 hours (PDR1) after reperfusion, and it was significantly lower in the SGD group. PDRr60 and PDR1 were excellent predictors of SGD. A threshold PDRr60 value of 10.8%/minute and a PDR1 value of 10%/minute accurately predicted SGD with areas under the receiver operating curve of 0.94 (95% confidence interval, 0.89-0.97) and 0.96 (95% confidence interval, 0.92-0.98), respectively. In addition, survival was significantly lower in patients with PDRr60 values below 10.8%/minute (53%, 47%, and 47% versus 95%, 94%, and 90% at 3, 6, and 12 months, respectively) and with PDR1 values below 10%/minute (62%, 62%, and 62% versus 94%, 92%, and 88%). In conclusion, very early noninvasive measurement of ICGPDR can accurately predict early severe graft dysfunction and mortality after liver transplantation. PMID:19790138

  12. Recent Achievements of the Collaboratory for the Study of Earthquake Predictability

    NASA Astrophysics Data System (ADS)

    Jackson, D. D.; Liukis, M.; Werner, M. J.; Schorlemmer, D.; Yu, J.; Maechling, P. J.; Zechar, J. D.; Jordan, T. H.

    2015-12-01

    Maria Liukis, SCEC, USC; Maximilian Werner, University of Bristol; Danijel Schorlemmer, GFZ Potsdam; John Yu, SCEC, USC; Philip Maechling, SCEC, USC; Jeremy Zechar, Swiss Seismological Service, ETH; Thomas H. Jordan, SCEC, USC, and the CSEP Working Group The Collaboratory for the Study of Earthquake Predictability (CSEP) supports a global program to conduct prospective earthquake forecasting experiments. CSEP testing centers are now operational in California, New Zealand, Japan, China, and Europe with 435 models under evaluation. The California testing center, operated by SCEC, has been operational since Sept 1, 2007, and currently hosts 30-minute, 1-day, 3-month, 1-year and 5-year forecasts, both alarm-based and probabilistic, for California, the Western Pacific, and worldwide. We have reduced testing latency, implemented prototype evaluation of M8 forecasts, and are currently developing formats and procedures to evaluate externally-hosted forecasts and predictions. These efforts are related to CSEP support of the USGS program in operational earthquake forecasting and a DHS project to register and test external forecast procedures from experts outside seismology. A retrospective experiment for the 2010-2012 Canterbury earthquake sequence has been completed, and the results indicate that some physics-based and hybrid models outperform purely statistical (e.g., ETAS) models. The experiment also demonstrates the power of the CSEP cyberinfrastructure for retrospective testing. Our current development includes evaluation strategies that increase computational efficiency for high-resolution global experiments, such as the evaluation of the Global Earthquake Activity Rate (GEAR) model. We describe the open-source CSEP software that is available to researchers as they develop their forecast models (http://northridge.usc.edu/trac/csep/wiki/MiniCSEP). We also discuss applications of CSEP infrastructure to geodetic transient detection and how CSEP procedures are being

  13. Predicting elite Scottish athletes' attitudes towards doping: examining the contribution of achievement goals and motivational climate.

    PubMed

    Allen, Justine; Taylor, John; Dimeo, Paul; Dixon, Sarah; Robinson, Leigh

    2015-01-01

    Understanding athletes' attitudes to doping continues to be of interest for its potential to contribute to an international anti-doping system. However, little is known about the relationship between elite athletes' attitudes to drug use and potential explanatory factors, including achievement goals and the motivational climate. In addition, despite specific World Anti-Doping Agency Code relating to team sport athletes, little is known about whether sport type (team or individual) is a risk or protective factor in relation to doping. Elite athletes from Scotland (N = 177) completed a survey examining attitudes to performance-enhancing drug (PED) use, achievement goal orientations and perceived motivational climate. Athletes were generally against doping for performance enhancement. Hierarchical regression analysis revealed that task and ego goals and mastery motivational climate were predictors of attitudes to PED use (F (4, 171) = 15.81, P < .01). Compared with individual athletes, team athletes were significantly lower in attitude to PED use and ego orientation scores and significantly higher in perceptions of a mastery motivational climate (Wilks' lambda = .76, F = 10.89 (5, 170), P < .01). The study provides insight into how individual and situational factors may act as protective and risk factors in doping in sport. PMID:25537139

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

    PubMed

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

    2013-08-01

    This study evaluates the role of postterm age at assessment and the use of one or two video recordings for the detection of fidgety movements (FMs) and prediction of cerebral palsy (CP) using computer vision software. Recordings between 9 and 17 weeks postterm age from 52 preterm and term infants (24 boys, 28 girls; 26 born preterm) were used. Recordings were analyzed using computer vision software. Movement variables, derived from differences between subsequent video frames, were used for quantitative analysis. Sensitivities, specificities, and area under curve were estimated for the first and second recording, or a mean of both. FMs were classified based on the Prechtl approach of general movement assessment. CP status was reported at 2 years. Nine children developed CP of whom all recordings had absent FMs. The mean variability of the centroid of motion (CSD) from two recordings was more accurate than using only one recording, and identified all children who were diagnosed with CP at 2 years. Age at assessment did not influence the detection of FMs or prediction of CP. The accuracy of computer vision techniques in identifying FMs and predicting CP based on two recordings should be confirmed in future studies. PMID:23343036

  15. Prediction of chirality- and size-dependent elastic properties of single-walled boron nitride nanotubes based on an accurate molecular mechanics model

    NASA Astrophysics Data System (ADS)

    Ansari, R.; Mirnezhad, M.; Sahmani, S.

    2015-04-01

    Molecular mechanics theory has been widely used to investigate the mechanical properties of nanostructures analytically. However, there is a limited number of research in which molecular mechanics model is utilized to predict the elastic properties of boron nitride nanotubes (BNNTs). In the current study, the mechanical properties of chiral single-walled BNNTs are predicted analytically based on an accurate molecular mechanics model. For this purpose, based upon the density functional theory (DFT) within the framework of the generalized gradient approximation (GGA), the exchange correlation of Perdew-Burke-Ernzerhof is adopted to evaluate force constants used in the molecular mechanics model. Afterwards, based on the principle of molecular mechanics, explicit expressions are given to calculate surface Young's modulus and Poisson's ratio of the single-walled BNNTs for different values of tube diameter and types of chirality. Moreover, the values of surface Young's modulus, Poisson's ratio and bending stiffness of boron nitride sheets are obtained via the DFT as byproducts. The results predicted by the present model are in reasonable agreement with those reported by other models in the literature.

  16. Comparing Cattell-Horn-Carroll factor models: differences between bifactor and higher order factor models in predicting language achievement.

    PubMed

    Beaujean, A Alexander; Parkin, Jason; Parker, Sonia

    2014-09-01

    Previous research using the Cattell-Horn-Carroll (CHC) theory of cognitive abilities has shown a relationship between cognitive ability and academic achievement. Most of this research, however, has been done using the Woodcock-Johnson family of instruments with a higher order factor model. For CHC theory to grow, research should be done with other assessment instruments and tested with other factor models. This study examined the relationship between different factor models of CHC theory and the factors' relationships with language-based academic achievement (i.e., reading and writing). Using the co-norming sample for the Wechsler Intelligence Scale for Children--4th Edition and the Wechsler Individual Achievement Test--2nd Edition, we found that bifactor and higher order models of the subtests of the Wechsler Intelligence Scale for Children-4th Edition produced a different set of Stratum II factors, which, in turn, have very different relationships with the language achievement variables of the Wechsler Individual Achievement Test--2nd Edition. We conclude that the factor model used to represent CHC theory makes little difference when general intelligence is of major interest, but it makes a large difference when the Stratum II factors are of primary concern, especially when they are used to predict other variables. PMID:24840178

  17. Quality of Education Predicts Performance on the Wide Range Achievement Test-4th Edition Word Reading Subtest

    PubMed Central

    Sayegh, Philip; Arentoft, Alyssa; Thaler, Nicholas S.; Dean, Andy C.; Thames, April D.

    2014-01-01

    The current study examined whether self-rated education quality predicts Wide Range Achievement Test-4th Edition (WRAT-4) Word Reading subtest and neurocognitive performance, and aimed to establish this subtest's construct validity as an educational quality measure. In a community-based adult sample (N = 106), we tested whether education quality both increased the prediction of Word Reading scores beyond demographic variables and predicted global neurocognitive functioning after adjusting for WRAT-4. As expected, race/ethnicity and education predicted WRAT-4 reading performance. Hierarchical regression revealed that when including education quality, the amount of WRAT-4's explained variance increased significantly, with race/ethnicity and both education quality and years as significant predictors. Finally, WRAT-4 scores, but not education quality, predicted neurocognitive performance. Results support WRAT-4 Word Reading as a valid proxy measure for education quality and a key predictor of neurocognitive performance. Future research should examine these findings in larger, more diverse samples to determine their robust nature. PMID:25404004

  18. Quality of education predicts performance on the Wide Range Achievement Test-4th Edition Word Reading subtest.

    PubMed

    Sayegh, Philip; Arentoft, Alyssa; Thaler, Nicholas S; Dean, Andy C; Thames, April D

    2014-12-01

    The current study examined whether self-rated education quality predicts Wide Range Achievement Test-4th Edition (WRAT-4) Word Reading subtest and neurocognitive performance, and aimed to establish this subtest's construct validity as an educational quality measure. In a community-based adult sample (N = 106), we tested whether education quality both increased the prediction of Word Reading scores beyond demographic variables and predicted global neurocognitive functioning after adjusting for WRAT-4. As expected, race/ethnicity and education predicted WRAT-4 reading performance. Hierarchical regression revealed that when including education quality, the amount of WRAT-4's explained variance increased significantly, with race/ethnicity and both education quality and years as significant predictors. Finally, WRAT-4 scores, but not education quality, predicted neurocognitive performance. Results support WRAT-4 Word Reading as a valid proxy measure for education quality and a key predictor of neurocognitive performance. Future research should examine these findings in larger, more diverse samples to determine their robust nature. PMID:25404004

  19. Can single empirical algorithms accurately predict inland shallow water quality status from high resolution, multi-sensor, multi-temporal satellite data?

    NASA Astrophysics Data System (ADS)

    Theologou, I.; Patelaki, M.; Karantzalos, K.

    2015-04-01

    Assessing and monitoring water quality status through timely, cost effective and accurate manner is of fundamental importance for numerous environmental management and policy making purposes. Therefore, there is a current need for validated methodologies which can effectively exploit, in an unsupervised way, the enormous amount of earth observation imaging datasets from various high-resolution satellite multispectral sensors. To this end, many research efforts are based on building concrete relationships and empirical algorithms from concurrent satellite and in-situ data collection campaigns. We have experimented with Landsat 7 and Landsat 8 multi-temporal satellite data, coupled with hyperspectral data from a field spectroradiometer and in-situ ground truth data with several physico-chemical and other key monitoring indicators. All available datasets, covering a 4 years period, in our case study Lake Karla in Greece, were processed and fused under a quantitative evaluation framework. The performed comprehensive analysis posed certain questions regarding the applicability of single empirical models across multi-temporal, multi-sensor datasets towards the accurate prediction of key water quality indicators for shallow inland systems. Single linear regression models didn't establish concrete relations across multi-temporal, multi-sensor observations. Moreover, the shallower parts of the inland system followed, in accordance with the literature, different regression patterns. Landsat 7 and 8 resulted in quite promising results indicating that from the recreation of the lake and onward consistent per-sensor, per-depth prediction models can be successfully established. The highest rates were for chl-a (r2=89.80%), dissolved oxygen (r2=88.53%), conductivity (r2=88.18%), ammonium (r2=87.2%) and pH (r2=86.35%), while the total phosphorus (r2=70.55%) and nitrates (r2=55.50%) resulted in lower correlation rates.

  20. State-of-the-art in permeability determination from well log data: Part 2- verifiable, accurate permeability predictions, the touch-stone of all models

    SciTech Connect

    Mohaghegh, S.; Balan, B.; Ameri, S.

    1995-12-31

    The ultimate test for any technique that bears the claim of permeability prediction from well log data, is accurate and verifiable prediction of permeability for wells from which only the well log data is available. So far all the available models and techniques have been tried on data that includes both well logs and the corresponding permeability values. This approach at best is nothing more than linear or nonlinear curve fitting. The objective of this paper is to test the capability of the most promising of these techniques in independent (where corresponding permeability values are not available or have not been used in development of the model) prediction of permeability in a heterogeneous formation. These techniques are {open_quotes}Multiple Regression{close_quotes} and {open_quotes}Virtual Measurements using Artificial Neural Networks.{close_quotes} For the purposes of this study several wells from a heterogeneous formation in West Virginia were selected. Well log data and corresponding permeability values for these wells were available. The techniques were applied to the remaining data and a permeability model for the field was developed. The model was then applied to the well that was separated from the rest of the data earlier and the results were compared. This approach will test the generalization power of each technique. The result will show that although Multiple Regression provides acceptable results for wells that were used during model development, (good curve fitting,) it lacks a consistent generalization capability, meaning that it does not perform as well with data it has not been exposed to (the data from well that has been put aside). On the other hand, Virtual Measurement technique provides a steady generalization power. This technique is able to perform the permeability prediction task even for the entire wells with no prior exposure to their permeability profile.

  1. 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.

  2. The Role of Self-Efficacy, Task Value, and Achievement Goals in Predicting Learning Strategies, Task Disengagement, Peer Relationship, and Achievement Outcome

    ERIC Educational Resources Information Center

    Liem, Arief Darmanegara; Lau, Shun; Nie, Youyan

    2008-01-01

    Adopting a combination of expectancy-value and achievement goal theories, this study examined the role of self-efficacy, task value, and achievement goals in students' learning strategies, task disengagement, peer relationship, and English achievement outcome. A sample of 1475 Year-9 students participated in the study. A structural equation model…

  3. 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

  4. 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

  5. Improved predictive modeling of white LEDs with accurate luminescence simulation and practical inputs with TracePro opto-mechanical design software

    NASA Astrophysics Data System (ADS)

    Tsao, Chao-hsi; Freniere, Edward R.; Smith, Linda

    2009-02-01

    The use of white LEDs for solid-state lighting to address applications in the automotive, architectural and general illumination markets is just emerging. LEDs promise greater energy efficiency and lower maintenance costs. However, there is a significant amount of design and cost optimization to be done while companies continue to improve semiconductor manufacturing processes and begin to apply more efficient and better color rendering luminescent materials such as phosphor and quantum dot nanomaterials. In the last decade, accurate and predictive opto-mechanical software modeling has enabled adherence to performance, consistency, cost, and aesthetic criteria without the cost and time associated with iterative hardware prototyping. More sophisticated models that include simulation of optical phenomenon, such as luminescence, promise to yield designs that are more predictive - giving design engineers and materials scientists more control over the design process to quickly reach optimum performance, manufacturability, and cost criteria. A design case study is presented where first, a phosphor formulation and excitation source are optimized for a white light. The phosphor formulation, the excitation source and other LED components are optically and mechanically modeled and ray traced. Finally, its performance is analyzed. A blue LED source is characterized by its relative spectral power distribution and angular intensity distribution. YAG:Ce phosphor is characterized by relative absorption, excitation and emission spectra, quantum efficiency and bulk absorption coefficient. Bulk scatter properties are characterized by wavelength dependent scatter coefficients, anisotropy and bulk absorption coefficient.

  6. 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

  7. 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

  8. Change in ST segment elevation 60 minutes after thrombolytic initiation predicts clinical outcome as accurately as later electrocardiographic changes

    PubMed Central

    Purcell, I; Newall, N; Farrer, M

    1997-01-01

    Objective—To compare prospectively the prognostic accuracy of a 50% decrease in ST segment elevation on standard 12-lead electrocardiograms (ECGs) recorded at 60, 90, and 180 minutes after thrombolysis initiation in acute myocardial infarction.
Design—Consecutive sample prospective cohort study.
Setting—A single coronary care unit in the north of England.
Patients—190 consecutive patients receiving thrombolysis for first acute myocardial infarction.
Interventions—Thrombolysis at baseline.
Main outcome measures—Cardiac mortality and left ventricular size and function assessed 36 days later.
Results—Failure of ST segment elevation to resolve by 50% in the single lead of maximum ST elevation or the sum ST elevation of all infarct related ECG leads at each of the times studied was associated with a significantly higher mortality, larger left ventricular volume, and lower ejection fraction. There was some variation according to infarct site with only the 60 minute ECG predicting mortality after inferior myocardial infarction and only in anterior myocardial infarction was persistent ST elevation associated with worse left ventricular function. The analysis of the lead of maximum ST elevation at 60 minutes from thrombolysis performed as well as later ECGs in receiver operating characteristic curves for predicting clinical outcome.
Conclusion—The standard 12-lead ECG at 60 minutes predicts clinical outcome as accurately as later ECGs after thrombolysis for first acute myocardial infarction.

 Keywords: myocardial infarction;  thrombolysis;  ST segment elevation PMID:9415005

  9. Fecal Calprotectin is an Accurate Tool and Correlated to Seo Index in Prediction of Relapse in Iranian Patients With Ulcerative Colitis

    PubMed Central

    Hosseini, Seyed Vahid; Jafari, Peyman; Taghavi, Seyed Alireza; Safarpour, Ali Reza; Rezaianzadeh, Abbas; Moini, Maryam; Mehrabi, Manoosh

    2015-01-01

    . Besides, FC level of 341 μg/g was identified as the cut-off point with 11.2% and 79.7% relapse rate below and above this point, respectively. Additionally, Pearson correlation coefficient (r) between FC and the Seo index was significant in prediction of relapse (r = 0.63, P < 0.001). Conclusions: As a simple and noninvasive marker, FC is highly accurate and significantly correlated to the Seo activity index in prediction of relapse in the course of quiescent UC in Iranian patients. PMID:25793117

  10. Calibrating transition-metal energy levels and oxygen bands in first-principles calculations: Accurate prediction of redox potentials and charge transfer in lithium transition-metal oxides

    NASA Astrophysics Data System (ADS)

    Seo, Dong-Hwa; Urban, Alexander; Ceder, Gerbrand

    2015-09-01

    Transition-metal (TM) oxides play an increasingly important role in technology today, including applications such as catalysis, solar energy harvesting, and energy storage. In many of these applications, the details of their electronic structure near the Fermi level are critically important for their properties. We propose a first-principles-based computational methodology for the accurate prediction of oxygen charge transfer in TM oxides and lithium TM (Li-TM) oxides. To obtain accurate electronic structures, the Heyd-Scuseria-Ernzerhof (HSE06) hybrid functional is adopted, and the amount of exact Hartree-Fock exchange (mixing parameter) is adjusted to reproduce reference band gaps. We show that the HSE06 functional with optimal mixing parameter yields not only improved electronic densities of states, but also better energetics (Li-intercalation voltages) for LiCo O2 and LiNi O2 as compared to the generalized gradient approximation (GGA), Hubbard U corrected GGA (GGA +U ), and standard HSE06. We find that the optimal mixing parameters for TM oxides are system specific and correlate with the covalency (ionicity) of the TM species. The strong covalent (ionic) nature of TM-O bonding leads to lower (higher) optimal mixing parameters. We find that optimized HSE06 functionals predict stronger hybridization of the Co 3 d and O 2 p orbitals as compared to GGA, resulting in a greater contribution from oxygen states to charge compensation upon delithiation in LiCo O2 . We also find that the band gaps of Li-TM oxides increase linearly with the mixing parameter, enabling the straightforward determination of optimal mixing parameters based on GGA (α =0.0 ) and HSE06 (α =0.25 ) calculations. Our results also show that G0W0@GGA +U band gaps of TM oxides (M O ,M =Mn ,Co ,Ni ) and LiCo O2 agree well with experimental references, suggesting that G0W0 calculations can be used as a reference for the calibration of the mixing parameter in cases when no experimental band gap has been

  11. Determination of the structure of {gamma}-alumina from interatomic potential and first-principles calculations: The requirement of significant numbers of nonspinel positions to achieve an accurate structural model

    SciTech Connect

    Paglia, Gianluca; Rohl, Andrew L.; Gale, Julian D.; Buckley, Craig E.

    2005-06-01

    We have performed an extensive computational study of {gamma}-Al{sub 2}O{sub 3}, beginning with the geometric analysis of approximately 1.47 billion spinel-based structural candidates, followed by derivative method energy minimization calculations of approximately 122 000 structures. Optimization of the spinel-based structural models demonstrated that structures exhibiting nonspinel site occupancy after simulation were more energetically favorable, as suggested in other computational studies. More importantly, none of the spinel structures exhibited simulated diffraction patterns that were characteristic of {gamma}-Al{sub 2}O{sub 3}. This suggests that cations of {gamma}-Al{sub 2}O{sub 3} are not exclusively held in spinel positions, that the spinel model of {gamma}-Al{sub 2}O{sub 3} does not accurately reflect its structure, and that a representative structure cannot be achieved from molecular modeling when the spinel representation is used as the starting structure. The latter two of these three findings are extremely important when trying to accurately model the structure. A second set of starting models were generated with a large number of cations occupying c symmetry positions, based on the findings from recent experiments. Optimization of the new c symmetry-based structural models resulted in simulated diffraction patterns that were characteristic of {gamma}-Al{sub 2}O{sub 3}. The modeling, conducted using supercells, yields a more accurate and complete determination of the defect structure of {gamma}-Al{sub 2}O{sub 3} than can be achieved with current experimental techniques. The results show that on average over 40% of the cations in the structure occupy nonspinel positions, and approximately two-thirds of these occupy c symmetry positions. The structures exhibit variable occupancy in the site positions that follow local symmetry exclusion rules. This variation was predominantly represented by a migration of cations away from a symmetry positions to other

  12. Determination of the structure of γ -alumina from interatomic potential and first-principles calculations: The requirement of significant numbers of nonspinel positions to achieve an accurate structural model

    NASA Astrophysics Data System (ADS)

    Paglia, Gianluca; Rohl, Andrew L.; Buckley, Craig E.; Gale, Julian D.

    2005-06-01

    We have performed an extensive computational study of γ-Al2O3 , beginning with the geometric analysis of approximately 1.47 billion spinel-based structural candidates, followed by derivative method energy minimization calculations of approximately 122 000 structures. Optimization of the spinel-based structural models demonstrated that structures exhibiting nonspinel site occupancy after simulation were more energetically favorable, as suggested in other computational studies. More importantly, none of the spinel structures exhibited simulated diffraction patterns that were characteristic of γ-Al2O3 . This suggests that cations of γ-Al2O3 are not exclusively held in spinel positions, that the spinel model of γ-Al2O3 does not accurately reflect its structure, and that a representative structure cannot be achieved from molecular modeling when the spinel representation is used as the starting structure. The latter two of these three findings are extremely important when trying to accurately model the structure. A second set of starting models were generated with a large number of cations occupying c symmetry positions, based on the findings from recent experiments. Optimization of the new c symmetry-based structural models resulted in simulated diffraction patterns that were characteristic of γ-Al2O3 . The modeling, conducted using supercells, yields a more accurate and complete determination of the defect structure of γ-Al2O3 than can be achieved with current experimental techniques. The results show that on average over 40% of the cations in the structure occupy nonspinel positions, and approximately two-thirds of these occupy c symmetry positions. The structures exhibit variable occupancy in the site positions that follow local symmetry exclusion rules. This variation was predominantly represented by a migration of cations away from a symmetry positions to other tetrahedral site positions during optimization which were found not to affect the diffraction

  13. Accurate blackbodies

    NASA Astrophysics Data System (ADS)

    Latvakoski, Harri M.; Watson, Mike; Topham, Shane; Scott, Deron; Wojcik, Mike; Bingham, Gail

    2010-07-01

    Infrared radiometers and spectrometers generally use blackbodies for calibration, and with the high accuracy needs of upcoming missions, blackbodies capable of meeting strict accuracy requirements are needed. One such mission, the NASA climate science mission Climate Absolute Radiance and Refractivity Observatory (CLARREO), which will measure Earth's emitted spectral radiance from orbit, has an absolute accuracy requirement of 0.1 K (3σ) at 220 K over most of the thermal infrared. Space Dynamics Laboratory (SDL) has a blackbody design capable of meeting strict modern accuracy requirements. This design is relatively simple to build, was developed for use on the ground or onorbit, and is readily scalable for aperture size and required performance. These-high accuracy blackbodies are currently in use as a ground calibration unit and with a high-altitude balloon instrument. SDL is currently building a prototype blackbody to demonstrate the ability to achieve very high accuracy, and we expect it to have emissivity of ~0.9999 from 1.5 to 50 μm, temperature uncertainties of ~25 mK, and radiance uncertainties of ~10 mK due to temperature gradients. The high emissivity and low thermal gradient uncertainties are achieved through cavity design, while the low temperature uncertainty is attained by including phase change materials such as mercury, gallium, and water in the blackbody. Blackbody temperature sensors are calibrated at the melt points of these materials, which are determined by heating through their melt point. This allows absolute temperature calibration traceable to the SI temperature scale.

  14. 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

  15. 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

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

    PubMed

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

    2015-12-01

    Triple therapy using boceprevir or telaprevir remains the reference treatment for genotype 1 chronic hepatitis C in countries where new interferon-free regimens have not yet become available. Antiviral treatment is highly required in cirrhotic patients, but they represent a difficult-to-treat population. We aimed to develop a simple algorithm for the prediction of sustained viral response (SVR) in cirrhotic patients treated with triple therapy. A total of 484 cirrhotic patients from the ANRS CO20 CUPIC cohort treated with triple therapy were randomly distributed into derivation and validation sets. A total of 52.1% of patients achieved SVR. In the derivation set, a D0 score for the prediction of SVR before treatment initiation included the following independent predictors collected at day 0: prior treatment response, gamma-GT, platelets, telaprevir treatment, viral load. To refine the prediction at the early phase of the treatment, a W4 score included as additional parameter the viral load collected at week 4. The D0 and W4 scores were combined in the CUPIC algorithm defining three subgroups: 'no treatment initiation or early stop at week 4', 'undetermined' and 'SVR highly probable'. In the validation set, the rates of SVR in these three subgroups were, respectively, 11.1%, 50.0% and 82.2% (P < 0.001). By replacing the variable 'prior treatment response' with 'IL28B genotype', another algorithm was derived for treatment-naïve patients with similar results. The CUPIC algorithm is an easy-to-use tool that helps physicians weigh their decision between immediately treating cirrhotic patients using boceprevir/telaprevir triple therapy or waiting for new drugs to become available in their country. PMID:26216230

  17. Predicting Levels of Reading and Writing Achievement in Typically Developing, English-Speaking 2nd and 5th Graders

    PubMed Central

    Jones, Jasmin Niedo; Abbott, Robert D.; Berninger, Virginia W.

    2014-01-01

    Human traits tend to fall along normal distributions. The aim of this research was to evaluate an evidence-based conceptual framework for predicting expected individual differences in reading and writing achievement outcomes for typically developing readers and writers in early and middle childhood from Verbal Reasoning with or without Working Memory Components (phonological, orthographic, and morphological word storage and processing units, phonological and orthographic loops, and rapid switching attention for cross-code integration). Verbal Reasoning (reconceptualized as Bidirectional Cognitive-Linguistic Translation) plus the Working Memory Components (reconceptualized as a language learning system) accounted for more variance than Verbal Reasoning alone, except for handwriting for which Working Memory Components alone were better predictors. Which predictors explained unique variance varied within and across reading (oral real word and pseudoword accuracy and rate, reading comprehension) and writing (handwriting, spelling, composing) skills and grade levels (second and fifth) in this longitudinal study. Educational applications are illustrated and theoretical and practical significance discussed. PMID:24948868

  18. More than just IQ: school achievement is predicted by self-perceived abilities--but for genetic rather than environmental reasons.

    PubMed

    Greven, Corina U; Harlaar, Nicole; Kovas, Yulia; Chamorro-Premuzic, Tomas; Plomin, Robert

    2009-06-01

    Evidence suggests that children's self-perceptions of their abilities predict their school achievement even after one accounts for their tested cognitive ability (IQ). However, the roles of nature and nurture in the association between school achievement and self-perceived abilities (SPAs), independent of IQ, is unknown. Here we reveal that there are substantial genetic influences on SPAs and that there is genetic covariance between SPAs and achievement independent of IQ. Although it has been assumed that the origins of SPAs are environmental, this first genetic analysis of SPAs yielded a heritability of 51% in a sample of 3,785 pairs of twins, whereas shared environment accounted for only 2% of the variance in SPAs. Moreover, multivariate genetic analyses indicated that SPAs predict school achievement independently of IQ for genetic rather than environmental reasons. It should therefore be possible to identify "SPA genes" that predict school achievement independently of "IQ genes." PMID:19470122

  19. Using Achievement Tests/SAT® II: Subject Tests to Demonstrate Achievement and Predict College Grades: Sex, Language, Ethnic, and Parental Education Groups. Research Report No. 2001-5

    ERIC Educational Resources Information Center

    Ramist, Leonard; Lewis, Charles; McCamley-Jenkins, Laura

    2001-01-01

    There has been increased interest in emphasizing Achievement Tests, as SAT II: Subject Tests, for use in admission and placement. In this report, data was obtained from a comprehensive database of categorized course grades for a large number and great variety of colleges, with student groups identified. For each student group, the percentage of…

  20. The Predictability of Enrolment and First-Year University Results from Secondary School Performance: The New Zealand National Certificate of Educational Achievement

    ERIC Educational Resources Information Center

    Shulruf, Boaz; Hattie, John; Tumen, Sarah

    2008-01-01

    This study investigates the predictive correlations between results from the New Zealand National Certificate of Educational Achievement (NCEA), a standards-based qualification, and university grade point averages achieved by first-year students in one large New Zealand University (and, for comparison purposes, also presents correlations from the…

  1. Testing a Multi-Stage Screening System: Predicting Performance on Australia's National Achievement Test Using Teachers' Ratings of Academic and Social Behaviors

    ERIC Educational Resources Information Center

    Kettler, Ryan J.; Elliott, Stephen N.; Davies, Michael; Griffin, Patrick

    2012-01-01

    This study addresses the predictive validity of results from a screening system of academic enablers, with a sample of Australian elementary school students, when the criterion variable is end-of-year achievement. The investigation included (a) comparing the predictive validity of a brief criterion-referenced nomination system with more…

  2. Critical Combinations of Radiation Dose and Volume Predict IQ and Academic Achievement Scores after Craniospinal Irradiation in Children with Medulloblastoma

    PubMed Central

    Merchant, Thomas E.; Schreiber, Jane E.; Wu, Shengjie; Lukose, Renin; Xiong, Xiaoping; Gajjar, Amar

    2016-01-01

    Purpose To prospectively follow children treated with craniospinal irradiation to determine critical combinations of radiation dose and volume that would predict for cognitive effects. Methods and Materials Between 1996 and 2003, 58 patients (median age 8.14 years, range 3.99–20.11 years) with medulloblastoma received risk-adapted CSI followed by dose-intense chemotherapy and were followed longitudinally with multiple cognitive evaluations (through 5 years post-treatment) that included IQ (estimated-EIQ, full-scale, verbal and performance) and academic achievement (math, reading, spelling) tests. CSI consisted of 23.4Gy for average-risk patients (non-metastatic) and 36–39.6Gy for high-risk patients (metastatic or residual disease > 1.5cm2). The primary site was treated using conformal or intensity-modulated radiation therapy using a 2cm clinical target volume margin. The effect of clinical variables and radiation dose to different brain volumes were modeled to estimate cognitive scores after treatment. Results A decline with time for all test scores was observed for the entire cohort. Sex, race and CSF shunt status had a significant impact on baseline scores. Age and mean radiation dose to specific brain volumes, including the temporal lobes and hippocampi, had a significant impact on longitudinal scores. Dichotomized dose distributions at 25Gy, 35Gy, 45Gy and 55Gy were modeled to show the impact of the high-dose volume on longitudinal test scores. The 50% risk of a below-normal cognitive test score was calculated according to mean dose and dose intervals between 25Gy and 55Gy at 10Gy increments according to brain volume and age. Conclusions The ability to predict cognitive outcomes in children with medulloblastoma using dose-effects models for different brain sub-volumes will improve treatment planning, guide intervention, and help estimate the value of newer methods of irradiation. PMID:25160611

  3. Variables that predict academic achievement in the Spanish compulsory secondary educational system: a longitudinal, multi-level analysis.

    PubMed

    Martín, Elena; Martínez-Arias, Rosario; Marchesi, Alvaro; Pérez, Eva M

    2008-11-01

    This article presents a study whose objective was to identify certain personal and institutional variables that are associated with academic achievement among Spanish, secondary school students, and to analyze their influence on the progress of those students over the course of that stage of their education. In order to do this, a longitudinal, multi-level study was conducted in which a total of 965 students and 27 different schools were evaluated in Language, Math and Social Science at three different times (beginning, middle and end of the period). The results show progress in all the schools and in all areas. As for the personal, student variables, the longitudinal, HLM analyses confirmed the importance of sex and sociocultural background and, distinguishing it from other studies, also the predictive capacity of meta-cognitive abilities and learning strategies on success in school. On the institutional level, the school climate and teachers' expectations of their students were the most relevant of the variables studied. The size of the school, the percentage of students who repeat grades, and the leadership of the administration also explained a portion of the variance in some areas. PMID:18988427

  4. Predictive Indicators of High Performing Schools: A Study of Evaluative Inquiry and the Effective Use of Achievement Test Data

    ERIC Educational Resources Information Center

    Hill, Kathryn L.

    2010-01-01

    Existing research suggests a link between evaluative inquiry (EI) and student achievement, where EI is defined as the practice of analyzing student achievement data to identify ways to improve instruction. However, researchers lacked empirical evidence regarding the relationship between specific EI indicators and student achievement. The purpose…

  5. Calibration of DFT Functionals for the Prediction of 57Fe Mössbauer Spectral Parameters in Iron-Nitrosyl and Iron-Sulfur Complexes: Accurate Geometries Prove Essential

    PubMed Central

    Sandala, Gregory M.; Hopmann, Kathrin H.; Ghosh, Abhik

    2011-01-01

    Six popular density functionals in conjunction with the conductor-like screening (COSMO) solvation model have been used to obtain linear Mössbauer isomer shift (IS) and quadrupole splitting (QS) parameters for a test set of 20 complexes (with 24 sites) comprised of nonheme nitrosyls (Fe–NO) and non-nitrosyl (Fe–S) complexes. For the first time in an IS analysis, the Fe electron density was calculated both directly at the nucleus, ρ(0)N, which is the typical procedure, and on a small sphere surrounding the nucleus, ρ(0)S, which is the new standard algorithm implemented in the ADF software package. We find that both methods yield (near) identical slopes from each linear regression analysis but are shifted with respect to ρ(0) along the x-axis. Therefore, the calculation of the Fe electron density with either method gives calibration fits with equal predictive value. Calibration parameters obtained from the complete test set for OLYP, OPBE, PW91, and BP86 yield correlation coefficients (r2) of approximately 0.90, indicating that the calibration fit is of good quality. However, fits obtained from B3LYP and B3LYP* with both Slater-type and Gaussian-type orbitals are generally found to be of poorer quality. For several of the complexes examined in this study, we find that B3LYP and B3LYP* give geometries that possess significantly larger deviations from the experimental structures than OLYP, OPBE, PW91 or BP86. This phenomenon is particularly true for the di- and tetranuclear Fe complexes examined in this study. Previous Mössbauer calibration fit studies using these functionals have usually included mononuclear Fe complexes alone, where these discrepancies are less pronounced. An examination of spin expectation values reveals B3LYP and B3LYP* approach the weak-coupling limit more closely than the GGA exchange-correlation functionals. The high degree of variability in our calculated S2 values for the Fe–NO complexes highlights their challenging electronic

  6. 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.

  7. Fast and accurate predictions of heat of formation by G4MP2-SFM parameterization scheme: An application to imidazole derivatives

    NASA Astrophysics Data System (ADS)

    Shoaib, Mahbubul Alam; Cho, Soo Gyeong; Choi, Cheol Ho

    2014-04-01

    We proposed a new parameterization scheme, G4MP2-SFM, for the prediction of heat of formation by combining SFM (Systematic Fragmentation Method) and high accuracy G4MP2 theories. In an application to imidazole derivatives, we found that the overall MAD and RMSD of the particular G4MP2-SFM(opt) are 1.9 and 2.2 kcal/mol, respectively, demonstrating its high prediction accuracy. In addition, our parameterization scheme replaces the ab initio computations with a set of simple arithmetic, allowing fast predictions. Our new computational scheme can be of practical use in high throughput search for new high energy materials.

  8. Understanding the independent influence of duty and achievement striving when predicting the relationship between conscientiousness and organizational cultural profiles and helping behaviors.

    PubMed

    Moon, Henry; Livne, Ephrat; Marinova, Sophia

    2013-01-01

    The theory that 2 facets of the factor conscientiousness, duty and achievement striving, are related to self- or other-centered motives, is supported in 2 studies. In Study 1 (N = 204 undergraduates), the self-centered facet of achievement striving was found to be the most important predictor of attraction toward organizational cultures that were outcome-based, aggressive, and emphasized rewards. Achievement strivers were less attracted to supportive and decisive organizations. In Study 2 (N = 189 part-time MBA students) the other-centered facet of duty was found to be predictive of helping behaviors. Theoretical and practical implications are discussed. PMID:23171231

  9. Subjective Evaluations of Intelligence and Academic Self-Concept Predict Academic Achievement: Evidence from a Selective Student Population

    ERIC Educational Resources Information Center

    Kornilova, Tatiana V.; Kornilov, Sergey A.; Chumakova, Maria A.

    2009-01-01

    The study examined the relationship between implicit theories, goal orientations, subjective and test estimates of intelligence, academic self-concept, and achievement in a selective student population (N=300). There was no direct impact of implicit theories of intelligence and goal orientations on achievement. However, subjective evaluations of…

  10. The Predictive Relation of a High School Mathematic GPA to High-Stakes Assessment Achievement Scores in Mathematics

    ERIC Educational Resources Information Center

    West, Suzanne M.

    2013-01-01

    Course grades, which often include non-achievement factors such as effort and behavior and are subject to individual teacher grading philosophies, suffer from issues of unreliability. Yet, course grades continue to be utilized as a primary tool for reporting academic achievement to students and parents and are used by most colleges and…

  11. Can Curriculum-Embedded Measures Predict the Later Reading Achievement of Kindergarteners at Risk of Reading Disability?

    ERIC Educational Resources Information Center

    Oslund, Eric L.; Simmons, Deborah C.; Hagan-Burke, Shanna; Kwok, Oi-Man; Simmons, Leslie E.; Taylor, Aaron B.; Coyne, Michael D.

    2015-01-01

    This study examined the changing role and longitudinal predictive validity of curriculum-embedded progress-monitoring measures (CEMs ) for kindergarten students receiving Tier 2 intervention and identified as at risk of developing reading difficulties. Multiple measures were examined to determine whether they could predict comprehensive latent…

  12. District Support Systems for the Alignment of Curriculum, Instruction, and Assessment: Can We Predict Student Achievement in Reading and Writing for School Turnaround?

    ERIC Educational Resources Information Center

    Abbott, Laura Lynn Tanner

    2014-01-01

    The purpose of this quantitative non-experimental predictive study was to determine if CIA alignment factors and related district support systems are associated with student achievement to enable the turnaround of schools in crisis. This study aimed to utilize the District Snapshot Tool to determine if the district systems that support CIA…

  13. Life Satisfaction among Highly Achieving Students in Hong Kong: Do Gratitude and the "Good-Enough Mindset" Add to the Contribution of Perfectionism in Prediction?

    ERIC Educational Resources Information Center

    Chan, David W.

    2012-01-01

    This study investigated whether gratitude and the "good-enough mindset" added to the contribution of perfectionism in predicting life satisfaction in 245 Chinese highly achieving students in Hong Kong. Participants completed self-report questionnaires that included scales on life satisfaction, positive and negative perfectionism (perfectionistic…

  14. The Effectiveness of Predict-Observe-Explain Tasks in Diagnosing Students' Understanding of Science and in Identifying Their Levels of Achievement.

    ERIC Educational Resources Information Center

    Liew, Chong-Wah; Treagust, David F.

    This study involves action research to explore the effectiveness of the Predict-Observe-Explain (POE) technique in diagnosing students' understanding of science and identifying their levels of achievement. A multidimensional interpretive framework is used to interpret students' understanding of science. The research methodology incorporated…

  15. Assessing the Incremental Value of KABC-II Luria Model Scores in Predicting Achievement: What Do They Tell Us beyond the MPI?

    ERIC Educational Resources Information Center

    McGill, Ryan J.; Spurgin, Angelia R.

    2016-01-01

    The current study examined the incremental validity of the Luria interpretive scheme for the Kaufman Assessment Battery for Children-Second Edition (KABC-II) for predicting scores on the Kaufman Test of Educational Achievement-Second Edition (KTEA-II). All participants were children and adolescents (N = 2,025) drawn from the nationally…

  16. Predicting Student Achievement with the Education Production-Function and Per-Pupil Expenditure: Synthesizing Regression Models from 1968-1994

    ERIC Educational Resources Information Center

    Pigott, Therese D.; Williams, Ryan T.; Polanin, Joshua R.; Wu-Bohanon, Meng-Jia

    2012-01-01

    The purpose of this research to investigate the heterogeneity of per-pupil expenditure (PPE) slope estimates in predicting student achievement. The research question guiding this project is: how does the measured relationship between per-pupil expenditure vary across studies that use different models? In concert with SREE's 2012 conference mission…

  17. Examining the integrity of measurement of cognitive abilities in the prediction of achievement: Comparisons and contrasts across variables from higher-order and bifactor models.

    PubMed

    Benson, Nicholas F; Kranzler, John H; Floyd, Randy G

    2016-10-01

    Prior research examining cognitive ability and academic achievement relations have been based on different theoretical models, have employed both latent variables as well as observed variables, and have used a variety of analytic methods. Not surprisingly, results have been inconsistent across studies. The aims of this study were to (a) examine how relations between psychometric g, Cattell-Horn-Carroll (CHC) broad abilities, and academic achievement differ across higher-order and bifactor models; (b) examine how well various types of observed scores corresponded with latent variables; and (c) compare two types of observed scores (i.e., refined and non-refined factor scores) as predictors of academic achievement. Results suggest that cognitive-achievement relations vary across theoretical models and that both types of factor scores tend to correspond well with the models on which they are based. However, orthogonal refined factor scores (derived from a bifactor model) have the advantage of controlling for multicollinearity arising from the measurement of psychometric g across all measures of cognitive abilities. Results indicate that the refined factor scores provide more precise representations of their targeted constructs than non-refined factor scores and maintain close correspondence with the cognitive-achievement relations observed for latent variables. Thus, we argue that orthogonal refined factor scores provide more accurate representations of the relations between CHC broad abilities and achievement outcomes than non-refined scores do. Further, the use of refined factor scores addresses calls for the application of scores based on latent variable models. PMID:27586067

  18. Derivation and validation of a simple, accurate and robust prediction rule for risk of mortality in patients with Clostridium difficile infection

    PubMed Central

    2013-01-01

    Background Clostridium difficile infection poses a significant healthcare burden. However, the derivation of a simple, evidence based prediction rule to assist patient management has not yet been described. This study aimed to identify such a prediction rule to stratify hospital inpatients according to risk of all-cause mortality, at initial diagnosis of infection. Method Univariate, multivariate and decision tree procedures were used to deduce a prediction rule from over 186 variables; retrospectively collated from clinical data for 213 patients. The resulting prediction rule was validated on independent data from a cohort of 158 patients described by Bhangu et al. (Colorectal Disease, 12(3):241-246, 2010). Results Serum albumin levels (g/L) (P = 0.001), respiratory rate (resps /min) (P = 0.002), C-reactive protein (mg/L) (P = 0.034) and white cell count (mcL) (P = 0.049) were predictors of all-cause mortality. Threshold levels of serum albumin ≤ 24.5 g/L, C- reactive protein >228 mg/L, respiratory rate >17 resps/min and white cell count >12 × 103 mcL were associated with an increased risk of all-cause mortality. A simple four variable prediction rule was devised based on these threshold levels and when tested on the initial data, yield an area under the curve score of 0.754 (P < 0.001) using receiver operating characteristics. The prediction rule was then evaluated using independent data, and yield an area under the curve score of 0.653 (P = 0.001). Conclusions Four easily measurable clinical variables can be used to assess the risk of mortality of patients with Clostridium difficile infection and remains robust with respect to independent data. PMID:23849267

  19. Accurate modeling of parallel scientific computations

    NASA Technical Reports Server (NTRS)

    Nicol, David M.; Townsend, James C.

    1988-01-01

    Scientific codes are usually parallelized by partitioning a grid among processors. To achieve top performance it is necessary to partition the grid so as to balance workload and minimize communication/synchronization costs. This problem is particularly acute when the grid is irregular, changes over the course of the computation, and is not known until load time. Critical mapping and remapping decisions rest on the ability to accurately predict performance, given a description of a grid and its partition. This paper discusses one approach to this problem, and illustrates its use on a one-dimensional fluids code. The models constructed are shown to be accurate, and are used to find optimal remapping schedules.

  20. MREdictor: a two-step dynamic interaction model that accounts for mRNA accessibility and Pumilio binding accurately predicts microRNA targets

    PubMed Central

    Incarnato, Danny; Neri, Francesco; Diamanti, Daniela; Oliviero, Salvatore

    2013-01-01

    The prediction of pairing between microRNAs (miRNAs) and the miRNA recognition elements (MREs) on mRNAs is expected to be an important tool for understanding gene regulation. Here, we show that mRNAs that contain Pumilio recognition elements (PRE) in the proximity of predicted miRNA-binding sites are more likely to form stable secondary structures within their 3′-UTR, and we demonstrated using a PUM1 and PUM2 double knockdown that Pumilio proteins are general regulators of miRNA accessibility. On the basis of these findings, we developed a computational method for predicting miRNA targets that accounts for the presence of PRE in the proximity of seed-match sequences within poorly accessible structures. Moreover, we implement the miRNA-MRE duplex pairing as a two-step model, which better fits the available structural data. This algorithm, called MREdictor, allows for the identification of miRNA targets in poorly accessible regions and is not restricted to a perfect seed-match; these features are not present in other computational prediction methods. PMID:23863844

  1. Achievement goals and autonomy: how person--context interactions predict effective functioning and well-being during a career transition.

    PubMed

    Heidemeier, Heike; Wiese, Bettina S

    2014-01-01

    This study examined how achievement goals interact with autonomy to explain mastery of a challenging career transition. In a sample of women who were returning from maternity leave, we examined how autonomy interacted with achievement goals to explain two types of outcomes: effective functioning (i.e., self-rated work adjustment, coworker-rated work adjustment, and coworker-rated learning competence) and well-being at work (i.e., positive affect and life satisfaction). In a longitudinal design (249 employees), we found that achievement goals and autonomy had direct effects on successful return to work. Moreover, maladaptive motivational states hindered the effective use of workplace resources: Autonomy moderated the consequences associated with performance-prove and -avoidance goals. Among those who adopted performance-prove goals, autonomy improved work adjustment and learning. However, women who adopted performance-avoidance goals experienced a trade-off between effective functioning and well-being, when equipped with high autonomy. PMID:24447218

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

    NASA Astrophysics Data System (ADS)

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

    2009-09-01

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

  3. Extent of Resection of Glioblastoma Revisited: Personalized Survival Modeling Facilitates More Accurate Survival Prediction and Supports a Maximum-Safe-Resection Approach to Surgery

    PubMed Central

    Marko, Nicholas F.; Weil, Robert J.; Schroeder, Jason L.; Lang, Frederick F.; Suki, Dima; Sawaya, Raymond E.

    2014-01-01

    Purpose Approximately 12,000 glioblastomas are diagnosed annually in the United States. The median survival rate for this disease is 12 months, but individual survival rates can vary with patient-specific factors, including extent of surgical resection (EOR). The goal of our investigation is to develop a reliable strategy for personalized survival prediction and for quantifying the relationship between survival, EOR, and adjuvant chemoradiotherapy. Patients and Methods We used accelerated failure time (AFT) modeling using data from 721 newly diagnosed patients with glioblastoma (from 1993 to 2010) to model the factors affecting individualized survival after surgical resection, and we used the model to construct probabilistic, patient-specific tools for survival prediction. We validated this model with independent data from 109 patients from a second institution. Results AFT modeling using age, Karnofsky performance score, EOR, and adjuvant chemoradiotherapy produced a continuous, nonlinear, multivariable survival model for glioblastoma. The median personalized predictive error was 4.37 months, representing a more than 20% improvement over current methods. Subsequent model-based calculations yield patient-specific predictions of the incremental effects of EOR and adjuvant therapy on survival. Conclusion Nonlinear, multivariable AFT modeling outperforms current methods for estimating individual survival after glioblastoma resection. The model produces personalized survival curves and quantifies the relationship between variables modulating patient-specific survival. This approach provides comprehensive, personalized, probabilistic, and clinically relevant information regarding the anticipated course of disease, the overall prognosis, and the patient-specific influence of EOR and adjuvant chemoradiotherapy. The continuous, nonlinear relationship identified between expected median survival and EOR argues against a surgical management strategy based on rigid EOR

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

    PubMed

    Haney, J

    2015-02-01

    The mouse dose at the lowest water concentration used in the National Toxicology Program hexavalent chromium (CrVI) drinking water study (NTP, 2008) is about 74,500 times higher than the approximate human dose corresponding to the 35-city geometric mean reported in EWG (2010) and over 1000 times higher than that based on the highest reported tap water concentration. With experimental and environmental doses differing greatly, it is a regulatory challenge to extrapolate high-dose results to environmental doses orders of magnitude lower in a meaningful and toxicologically predictive manner. This seems particularly true for the low-dose extrapolation of results for oral CrVI-induced carcinogenesis since dose-dependent differences in the dose fraction absorbed by mouse target tissues are apparent (Kirman et al., 2012). These data can be used for a straightforward adjustment of the USEPA (2010) draft oral slope factor (SFo) to be more predictive of risk at environmentally-relevant doses. More specifically, the evaluation of observed and modeled differences in the fraction of dose absorbed by target tissues at the point-of-departure for the draft SFo calculation versus lower doses suggests that the draft SFo be divided by a dose-specific adjustment factor of at least an order of magnitude to be less over-predictive of risk at more environmentally-relevant doses. PMID:25445295

  5. Homework Works If Homework Quality Is High: Using Multilevel Modeling to Predict the Development of Achievement in Mathematics

    ERIC Educational Resources Information Center

    Dettmers, Swantje; Trautwein, Ulrich; Ludtke, Oliver; Kunter, Mareike; Baumert, Jurgen

    2010-01-01

    The present study examined the associations of 2 indicators of homework quality (homework selection and homework challenge) with homework motivation, homework behavior, and mathematics achievement. Multilevel modeling was used to analyze longitudinal data from a representative national sample of 3,483 students in Grades 9 and 10; homework effects…

  6. Personal Best (PB) and "Classic" Achievement Goals in the Chinese Context: Their Role in Predicting Academic Motivation, Engagement and Buoyancy

    ERIC Educational Resources Information Center

    Yu, Kai; Martin, Andrew J.

    2014-01-01

    Prior research has shown personal best (PB) goals to be significantly related to students' motivation, engagement and achievement. However, research thus far has investigated PB goals only among Western samples and it is unclear to what extent PB goals hold academic merit in the Asian context. It is also unclear whether PB goals explain…

  7. Predicting Undergraduates' Academic Achievement: The Role of the Curriculum, Time Investment and Self-Regulated Learning

    ERIC Educational Resources Information Center

    Torenbeek, Marjolein; Jansen, Ellen; Suhre, Cor

    2013-01-01

    The time students invest in their studies and their resulting achievement is partly dependent on curriculum characteristics. Degree programmes differ greatly with respect to how the curriculum is organized, for example in the type (e.g. lectures, practicals) and the number of classes. The focus of this study is on the relationships between…

  8. Predicting Achievement: Confidence vs Self-Efficacy, Anxiety, and Self-Concept in Confucian and European Countries

    ERIC Educational Resources Information Center

    Morony, Suzanne; Kleitman, Sabina; Lee, Yim Ping; Stankov, Lazar

    2013-01-01

    This study investigates the structure and cross-cultural (in)variance of mathematical self-beliefs in relation to mathematics achievement in two world regions: Confucian Asia (Singapore, South Korea, Hong Kong and Taiwan) and Europe (Denmark, The Netherlands, Finland, Serbia and Latvia). This is done both pan-culturally and at a multigroup-level,…

  9. Prediction of Kindergartners' Academic Achievement from Their Effortful Control and Emotionality: Evidence for Direct and Moderated Relations

    ERIC Educational Resources Information Center

    Valiente, Carlos; Lemery-Chalfant, Kathryn; Swanson, Jodi

    2010-01-01

    The relations between effortful control, emotionality (anger, sadness, and shyness), and academic achievement were examined in a short-term longitudinal study of 291 kindergartners. Teachers and parents reported on students' effortful control and emotionality. Students completed the Continuous Performance Task and the Letter-Word, Passage…

  10. Predicting High School Graduation for Latino Males Using Expectancy Value Theory of Motivation and Tenth Grade Reading Achievement Scores

    ERIC Educational Resources Information Center

    Knape, Erin Oakley

    2010-01-01

    National education data indicate that young men of color and students living in poverty are not experiencing the same academic success as their female, White, or higher socioeconomic status peers, as evidenced by low reading achievement levels and high dropout rates. Of particular concern is the underachievement of Latino males, who currently have…

  11. Mothers' Expressive Style and Emotional Responses to Children's Behavior Predict Children's Prosocial and Achievement-Related Self-Ratings

    ERIC Educational Resources Information Center

    Dunsmore, Julie C.; Bradburn, Isabel S.; Costanzo, Philip R.; Fredrickson, Barbara L.

    2009-01-01

    In this study we investigated whether mothers' typical expressive style and specific emotional responses to children's behaviors are linked to children's prosocial and competence self-ratings. Eight- to 12-year-old children and their mothers rated how mothers had felt when children behaved prosocially and antisocially, achieved and failed to…

  12. The Role of Moral and Performance Character Strengths in Predicting Achievement and Conduct among Urban Middle School Students

    ERIC Educational Resources Information Center

    Seider, Scott; Gilbert, Jennifer K.; Novick, Sarah; Gomez, Jessica

    2013-01-01

    Background/Context: Performance character consists of the qualities that allow individuals to regulate their thoughts and actions in ways that support achievement in a particular endeavor. Moral character consists of the qualities relevant to striving for ethical behavior in one's relationships with other individuals and communities. A…

  13. Predicting the Academic Achievement of Deaf and Hard-of-Hearing Students from Individual, Household, Communication, and Educational Factors

    ERIC Educational Resources Information Center

    Marschark, Marc; Shaver, Debra M.; Nagle, Katherine M.; Newman, Lynn A.

    2015-01-01

    Research suggests that the academic achievement of deaf and hard-of-hearing (DHH) students is the result of a complex interplay of many factors. These factors include characteristics of the students (e.g., hearing thresholds, language fluencies, mode of communication, and communication functioning), characteristics of their family environments…

  14. Predicting Academic Achievement from Cumulative Home Risk: The Mediating Roles of Effortful Control, Academic Relationships, and School Avoidance

    ERIC Educational Resources Information Center

    Swanson, Jodi; Valiente, Carlos; Lemery-Chalfant, Kathryn

    2012-01-01

    Components of the home environment are associated with children's academic functioning. The accumulation of risks in the home are expected to prove more detrimental to achievement than any one risk alone, but the processes accounting for this relation are unclear. Using an index of cumulative home risk (CHR) inclusive of protective factors, as…

  15. Unfair, Unsafe, and Unwelcome: Do High School Students' Perceptions of Unfairness, Hostility, and Victimization in School Predict Engagement and Achievement?

    ERIC Educational Resources Information Center

    Ripski, Michael B.; Gregory, Anne

    2009-01-01

    Using a national data set, Education Longitudinal Study of 2002 (ELS:2002), we examined three dimensions of 10th-grade school climate--unfairness, hostility, and victimization--as predictors of teacher-perceived student engagement and achievement in reading and mathematics in the same year. The dimensions of school climate that predicted…

  16. Investigating Predictive Role of 2x2 Achievement Goal Orientations on Learning Strategies with Structural Equation Modeling

    ERIC Educational Resources Information Center

    Soltaninejad, Mehraneh

    2015-01-01

    The purpose of this study is to examine the relationships between achievement goal orientations and Learning Strategies. The sample of study consists of 350 public high school students (135 males and 215 females, mean age: 17 ± 0.65) from two high schools in Kerman province of Iran selected by random multistage cluster sampling method. In this…

  17. Predicting Early Adolescents' Academic Achievement, Social Competence, and Physical Health from Parenting, Ego Resilience, and Engagement Coping

    ERIC Educational Resources Information Center

    Swanson, Jodi; Valiente, Carlos; Lemery-Chalfant, Kathryn; O'Brien, T. Caitlin

    2011-01-01

    This study examined ego resilience and engagement coping as mediators of the relationships between supportive and controlling parenting practices and early adolescents' academic achievement, social competence, and physical health. Participants were 240 predominantly Mexican American early adolescents, their parents, and their teachers. There were…

  18. Do L1 Reading Achievement and L1 Print Exposure Contribute to the Prediction of L2 Proficiency?

    ERIC Educational Resources Information Center

    Sparks, Richard L.; Patton, Jon; Ganschow, Leonore; Humbach, Nancy

    2012-01-01

    The study examined whether individual differences in high school first language (L1) reading achievement and print exposure would account for unique variance in second language (L2) written (word decoding, spelling, writing, reading comprehension) and oral (listening/speaking) proficiency after adjusting for the effects of early L1 literacy and…

  19. Predicting Performance on State Achievement Tests Using Curriculum-Based Measurement in Reading: A Multilevel Meta-Analysis

    ERIC Educational Resources Information Center

    Yeo, Seungsoo

    2010-01-01

    The purpose of this synthesis was to examine the relationship between Curriculum-Based Measurement (CBM) and statewide achievement tests in reading. A multilevel meta-analysis was used to calculate the correlation coefficient of the population for 27 studies that met the inclusion criteria. Results showed an overall large correlation coefficient…

  20. 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

  1. Predictive models of lameness in dairy cows achieve high sensitivity and specificity with force measurements in three dimensions.

    PubMed

    Dunthorn, Jason; Dyer, Robert M; Neerchal, Nagaraj K; McHenry, Jonathan S; Rajkondawar, Parimal G; Steingraber, Gary; Tasch, Uri

    2015-11-01

    Lameness remains a significant cause of production losses, a growing welfare concern and may be a greater economic burden than clinical mastitis . A growing need for accurate, continuous automated detection systems continues because US prevalence of lameness is 12.5% while individual herds may experience prevalence's of 27.8-50.8%. To that end the first force-plate system restricted to the vertical dimension identified lame cows with 85% specificity and 52% sensitivity. These results lead to the hypothesis that addition of transverse and longitudinal dimensions could improve sensitivity of lameness detection. To address the hypothesis we upgraded the original force plate system to measure ground reaction forces (GRFs) across three directions. GRFs and locomotion scores were generated from randomly selected cows and logistic regression was used to develop a model that characterised relationships of locomotion scores to the GRFs. This preliminary study showed 76 variables across 3 dimensions produced a model with greater than 90% sensitivity, specificity, and area under the receiver operating curve (AUC). The result was a marked improvement on the 52% sensitivity, and 85% specificity previously observed with the 1 dimensional model or the 45% sensitivities reported with visual observations. Validation of model accuracy continues with the goal to finalise accurate automated methods of lameness detection. PMID:26278403

  2. Predictive, Construct, and Convergent Validity of General and Domain-Specific Measures of Hope for College Student Academic Achievement

    ERIC Educational Resources Information Center

    Robinson, Cecil; Rose, Sage

    2010-01-01

    One leading version of hope theory posits hope to be a general disposition for goal-directed agency and pathways thinking. Domain-specific hope theory suggests that hope operates within context and measures of hope should reflect that context. This study examined three measures of hope to test the predictive, construct, and convergent validity…

  3. Academic Motivation and Approaches to Learning in Predicting College Students' Academic Achievement: Findings from Turkish and US Samples

    ERIC Educational Resources Information Center

    Çetin, Baris

    2015-01-01

    The aim of this study is to determine if approaches to learning and academic motivation together predict grade point averages (GPAs) of students who study at Primary School Education and Preschool Education in Turkey and of students who study at Early Childhood Education in the US. The first group of participants included 166 third- and…

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

    PubMed Central

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

    2012-01-01

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

  5. Race-specific genetic risk score is more accurate than nonrace-specific genetic risk score for predicting prostate cancer and high-grade diseases

    PubMed Central

    Na, Rong; Ye, Dingwei; Qi, Jun; Liu, Fang; Lin, Xiaoling; Helfand, Brian T; Brendler, Charles B; Conran, Carly; Gong, Jian; Wu, Yishuo; Gao, Xu; Chen, Yaqing; Zheng, S Lilly; Mo, Zengnan; Ding, Qiang; Sun, Yinghao; Xu, Jianfeng

    2016-01-01

    Genetic risk score (GRS) based on disease risk-associated single nucleotide polymorphisms (SNPs) is an informative tool that can be used to provide inherited information for specific diseases in addition to family history. However, it is still unknown whether only SNPs that are implicated in a specific racial group should be used when calculating GRSs. The objective of this study is to compare the performance of race-specific GRS and nonrace-specific GRS for predicting prostate cancer (PCa) among 1338 patients underwent prostate biopsy in Shanghai, China. A race-specific GRS was calculated with seven PCa risk-associated SNPs implicated in East Asians (GRS7), and a nonrace-specific GRS was calculated based on 76 PCa risk-associated SNPs implicated in at least one racial group (GRS76). The means of GRS7 and GRS76 were 1.19 and 1.85, respectively, in the study population. Higher GRS7 and GRS76 were independent predictors for PCa and high-grade PCa in univariate and multivariate analyses. GRS7 had a better area under the receiver-operating curve (AUC) than GRS76 for discriminating PCa (0.602 vs 0.573) and high-grade PCa (0.603 vs 0.575) but did not reach statistical significance. GRS7 had a better (up to 13% at different cutoffs) positive predictive value (PPV) than GRS76. In conclusion, a race-specific GRS is more robust and has a better performance when predicting PCa in East Asian men than a GRS calculated using SNPs that are not shown to be associated with East Asians. PMID:27140652

  6. Race-specific genetic risk score is more accurate than nonrace-specific genetic risk score for predicting prostate cancer and high-grade diseases.

    PubMed

    Na, Rong; Ye, Dingwei; Qi, Jun; Liu, Fang; Lin, Xiaoling; Helfand, Brian T; Brendler, Charles B; Conran, Carly; Gong, Jian; Wu, Yishuo; Gao, Xu; Chen, Yaqing; Zheng, S Lilly; Mo, Zengnan; Ding, Qiang; Sun, Yinghao; Xu, Jianfeng

    2016-01-01

    Genetic risk score (GRS) based on disease risk-associated single nucleotide polymorphisms (SNPs) is an informative tool that can be used to provide inherited information for specific diseases in addition to family history. However, it is still unknown whether only SNPs that are implicated in a specific racial group should be used when calculating GRSs. The objective of this study is to compare the performance of race-specific GRS and nonrace-specific GRS for predicting prostate cancer (PCa) among 1338 patients underwent prostate biopsy in Shanghai, China. A race-specific GRS was calculated with seven PCa risk-associated SNPs implicated in East Asians (GRS7), and a nonrace-specific GRS was calculated based on 76 PCa risk-associated SNPs implicated in at least one racial group (GRS76). The means of GRS7 and GRS76 were 1.19 and 1.85, respectively, in the study population. Higher GRS7 and GRS76 were independent predictors for PCa and high-grade PCa in univariate and multivariate analyses. GRS7 had a better area under the receiver-operating curve (AUC) than GRS76 for discriminating PCa (0.602 vs 0.573) and high-grade PCa (0.603 vs 0.575) but did not reach statistical significance. GRS7 had a better (up to 13% at different cutoffs) positive predictive value (PPV) than GRS76. In conclusion, a race-specific GRS is more robust and has a better performance when predicting PCa in East Asian men than a GRS calculated using SNPs that are not shown to be associated with East Asians. PMID:27140652

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

    PubMed

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

    2015-01-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Byun, Jaeseung; Bodony, Daniel; Pantano, Carlos

    2014-11-01

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

  10. Leukemia-induced phenotypic and functional defects in natural killer cells predict failure to achieve remission in acute myeloid leukemia.

    PubMed

    Stringaris, Kate; Sekine, Takuya; Khoder, Ahmad; Alsuliman, Abdullah; Razzaghi, Bonnie; Sargeant, Ruhena; Pavlu, Jiri; Brisley, Gill; de Lavallade, Hugues; Sarvaria, Anushruthi; Marin, David; Mielke, Stephan; Apperley, Jane F; Shpall, Elizabeth J; Barrett, A John; Rezvani, Katayoun

    2014-05-01

    The majority of patients with acute myeloid leukemia will relapse, and older patients often fail to achieve remission with induction chemotherapy. We explored the possibility that leukemic suppression of innate immunity might contribute to treatment failure. Natural killer cell phenotype and function was measured in 32 consecutive acute myeloid leukemia patients at presentation, including 12 achieving complete remission. Compared to 15 healthy age-matched controls, natural killer cells from acute myeloid leukemia patients were abnormal at presentation, with downregulation of the activating receptor NKp46 (P=0.007) and upregulation of the inhibitory receptor NKG2A (P=0.04). Natural killer cells from acute myeloid leukemia patients had impaired effector function against autologous blasts and K562 targets, with significantly reduced CD107a degranulation, TNF-α and IFN-γ production. Failure to achieve remission was associated with NKG2A overexpression and reduced TNF-α production. These phenotypic and functional abnormalities were partially restored in the 12 patients achieving remission. In vitro co-incubation of acute myeloid leukemia blasts with natural killer cells from healthy donors induced significant impairment in natural killer cell TNF-α and IFN-γ production (P=0.02 and P=0.01, respectively) against K562 targets and a trend to reduced CD107a degranulation (P=0.07). Under transwell conditions, the inhibitory effect of AML blasts on NK cytotoxicity and effector function was still present, and this inhibitory effect was primarily mediated by IL-10. These results suggest that acute myeloid leukemia blasts induce long-lasting changes in natural killer cells, impairing their effector function and reducing the competence of the innate immune system, favoring leukemia survival. PMID:24488563

  11. Leukemia-induced phenotypic and functional defects in natural killer cells predict failure to achieve remission in acute myeloid leukemia

    PubMed Central

    Stringaris, Kate; Sekine, Takuya; Khoder, Ahmad; Alsuliman, Abdullah; Razzaghi, Bonnie; Sargeant, Ruhena; Pavlu, Jiri; Brisley, Gill; de Lavallade, Hugues; Sarvaria, Anushruthi; Marin, David; Mielke, Stephan; Apperley, Jane F.; Shpall, Elizabeth J.; Barrett, A. John; Rezvani, Katayoun

    2014-01-01

    The majority of patients with acute myeloid leukemia will relapse, and older patients often fail to achieve remission with induction chemotherapy. We explored the possibility that leukemic suppression of innate immunity might contribute to treatment failure. Natural killer cell phenotype and function was measured in 32 consecutive acute myeloid leukemia patients at presentation, including 12 achieving complete remission. Compared to 15 healthy age-matched controls, natural killer cells from acute myeloid leukemia patients were abnormal at presentation, with downregulation of the activating receptor NKp46 (P=0.007) and upregulation of the inhibitory receptor NKG2A (P=0.04). Natural killer cells from acute myeloid leukemia patients had impaired effector function against autologous blasts and K562 targets, with significantly reduced CD107a degranulation, TNF-α and IFN-γ production. Failure to achieve remission was associated with NKG2A overexpression and reduced TNF-α production. These phenotypic and functional abnormalities were partially restored in the 12 patients achieving remission. In vitro co-incubation of acute myeloid leukemia blasts with natural killer cells from healthy donors induced significant impairment in natural killer cell TNF-α and IFN-γ production (P=0.02 and P=0.01, respectively) against K562 targets and a trend to reduced CD107a degranulation (P=0.07). Under transwell conditions, the inhibitory effect of AML blasts on NK cytotoxicity and effector function was still present, and this inhibitory effect was primarily mediated by IL-10. These results suggest that acute myeloid leukemia blasts induce long-lasting changes in natural killer cells, impairing their effector function and reducing the competence of the innate immune system, favoring leukemia survival. PMID:24488563

  12. Accurate prediction of diradical chemistry from a single-reference density-matrix method: Model application to the bicyclobutane to gauche-1,3-butadiene isomerization

    SciTech Connect

    Bertels, Luke W.; Mazziotti, David A.

    2014-07-28

    Multireference correlation in diradical molecules can be captured by a single-reference 2-electron reduced-density-matrix (2-RDM) calculation with only single and double excitations in the 2-RDM parametrization. The 2-RDM parametrization is determined by N-representability conditions that are non-perturbative in their treatment of the electron correlation. Conventional single-reference wave function methods cannot describe the entanglement within diradical molecules without employing triple- and potentially even higher-order excitations of the mean-field determinant. In the isomerization of bicyclobutane to gauche-1,3-butadiene the parametric 2-RDM (p2-RDM) method predicts that the diradical disrotatory transition state is 58.9 kcal/mol above bicyclobutane. This barrier is in agreement with previous multireference calculations as well as recent Monte Carlo and higher-order coupled cluster calculations. The p2-RDM method predicts the Nth natural-orbital occupation number of the transition state to be 0.635, revealing its diradical character. The optimized geometry from the p2-RDM method differs in important details from the complete-active-space self-consistent-field geometry used in many previous studies including the Monte Carlo calculation.

  13. Predicting the Academic Achievement of Deaf and Hard-of-Hearing Students From Individual, Household, Communication, and Educational Factors

    PubMed Central

    Marschark, Marc; Shaver, Debra M.; Nagle, Katherine M.; Newman, Lynn A.

    2015-01-01

    Research suggests that the academic achievement of deaf and hard-of-hearing (DHH) students is the result of a complex interplay of many factors. These factors include characteristics of the students (e.g., hearing thresholds, language fluencies, mode of communication, and communication functioning), characteristics of their family environments (e.g., parent education level, socioeconomic status), and experiences inside and outside school (e.g., school placement, having been retained at grade level). This paper examines the relative importance of such characteristics to U.S. DHH secondary students’ academic achievement as indicated by the Woodcock-Johnson III subtests in passage comprehension, mathematics calculation, science, and social studies. Data were obtained for approximately 500 DHH secondary students who had attended regular secondary schools or state-sponsored special schools designed for DHH students. Across all subject areas, having attended regular secondary schools and having better spoken language were associated with higher test scores. Significant negative predictors of achievement varied by type of subtest but included having an additional diagnosis of a learning disability, having a mild hearing loss, and being African American or Hispanic. The findings have important implications for policy and practice in educating DHH students as well for interpreting previous research. PMID:26549890

  14. Peer assessments of normative and individual teacher–student support predict social acceptance and engagement among low-achieving children

    PubMed Central

    Hughes, Jan N.; Zhang, Duan; Hill, Crystal R.

    2010-01-01

    This study used hierarchical linear modeling to predict first grade students' peer acceptance, classroom engagement, and sense of school belonging from measures of normative classroom teacher–student support and individual teacher–student support. Participants were 509 (54.4% male) ethnically diverse, first grade children attending one of three Texas School districts (1 urban, 2 small city) who scored below their school district median on a measure of literacy administered at the beginning of first grade. Peer nominations from 5147 classmates were used to assess both normative and individual levels of teacher support. Normative classroom teacher–student support predicted children's peer acceptance and classroom engagement, above the effects of child gender, ethnic minority status, and individual teacher–student support. Results are discussed in terms of implications for teacher preparation and professional development. PMID:20411044

  15. Patient-specific coronary stenoses can be modeled using a combination of OCT and flow velocities to accurately predict hyperemic pressure gradients.

    PubMed

    Kousera, C A; Nijjer, S; Torii, R; Petraco, R; Sen, S; Foin, N; Hughes, A D; Francis, D P P; Xu, X Y; Davies, J E

    2014-06-01

    Computational fluid dynamics (CFD) is increasingly being developed for the diagnostics of arterial diseases. Imaging methods such as computed tomography (CT) and angiography are commonly used. However, these have limited spatial resolution and are subject to movement artifact. This study developed a new approach to generate CFD models by combining high-fidelity, patient-specific coronary anatomy models derived from optical coherence tomography (OCT) imaging with patient-specific pressure and velocity phasic data. Additionally, we used a new technique which does not require the catheter to be used to determine the centerline of the vessel. The CFD data were then compared with invasively measured pressure and velocity. Angiography imaging data of 21 vessels collected from 19 patients were fused with OCT visualizations of the same vessels using an algorithm that produces reconstructions inheriting the in-plane (10 μm) and longitudinal (0.2 mm) resolution of OCT. Proximal pressure and distal velocity waveforms ensemble averaged from invasively measured data were used as inlet and outlet boundary conditions, respectively, in CFD simulations. The resulting distal pressure waveform was compared against the measured waveform to test the model. The results followed the shape of the measured waveforms closely (cross-correlation coefficient = 0.898 ± 0.005, ), indicating realistic modeling of flow resistance, the mean of differences between measured and simulated results was -3. 5 mmHg, standard deviation of differences (SDD) = 8.2 mmHg over the cycle and -9.8 mmHg, SDD = 16.4 mmHg at peak flow. Models incorporating phasic velocity in patient-specific models of coronary anatomy derived from high-resolution OCT images show a good correlation with the measured pressure waveforms in all cases, indicating that the model results may be an accurate representation of the measured flow conditions. PMID:24845301

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

    PubMed Central

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

    2016-01-01

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

  17. What No Child Left Behind Leaves Behind: The Roles of IQ and Self-Control in Predicting Standardized Achievement Test Scores and Report Card Grades

    PubMed Central

    Duckworth, Angela L.; Quinn, Patrick D.; Tsukayama, Eli

    2013-01-01

    The increasing prominence of standardized testing to assess student learning motivated the current investigation. We propose that standardized achievement test scores assess competencies determined more by intelligence than by self-control, whereas report card grades assess competencies determined more by self-control than by intelligence. In particular, we suggest that intelligence helps students learn and solve problems independent of formal instruction, whereas self-control helps students study, complete homework, and behave positively in the classroom. Two longitudinal, prospective studies of middle school students support predictions from this model. In both samples, IQ predicted changes in standardized achievement test scores over time better than did self-control, whereas self-control predicted changes in report card grades over time better than did IQ. As expected, the effect of self-control on changes in report card grades was mediated in Study 2 by teacher ratings of homework completion and classroom conduct. In a third study, ratings of middle school teachers about the content and purpose of standardized achievement tests and report card grades were consistent with the proposed model. Implications for pedagogy and public policy are discussed. PMID:24072936

  18. What No Child Left Behind Leaves Behind: The Roles of IQ and Self-Control in Predicting Standardized Achievement Test Scores and Report Card Grades.

    PubMed

    Duckworth, Angela L; Quinn, Patrick D; Tsukayama, Eli

    2012-05-01

    The increasing prominence of standardized testing to assess student learning motivated the current investigation. We propose that standardized achievement test scores assess competencies determined more by intelligence than by self-control, whereas report card grades assess competencies determined more by self-control than by intelligence. In particular, we suggest that intelligence helps students learn and solve problems independent of formal instruction, whereas self-control helps students study, complete homework, and behave positively in the classroom. Two longitudinal, prospective studies of middle school students support predictions from this model. In both samples, IQ predicted changes in standardized achievement test scores over time better than did self-control, whereas self-control predicted changes in report card grades over time better than did IQ. As expected, the effect of self-control on changes in report card grades was mediated in Study 2 by teacher ratings of homework completion and classroom conduct. In a third study, ratings of middle school teachers about the content and purpose of standardized achievement tests and report card grades were consistent with the proposed model. Implications for pedagogy and public policy are discussed. PMID:24072936

  19. Predicting first-grade mathematics achievement: the contributions of domain-general cognitive abilities, nonverbal number sense, and early number competence

    PubMed Central

    Hornung, Caroline; Schiltz, Christine; Brunner, Martin; Martin, Romain

    2014-01-01

    Early number competence, grounded in number-specific and domain-general cognitive abilities, is theorized to lay the foundation for later math achievement. Few longitudinal studies have tested a comprehensive model for early math development. Using structural equation modeling and mediation analyses, the present work examined the influence of kindergarteners' nonverbal number sense and domain-general abilities (i.e., working memory, fluid intelligence, and receptive vocabulary) and their early number competence (i.e., symbolic number skills) on first grade math achievement (i.e., arithmetic, shape and space skills, and number line estimation) assessed 1 year later. Latent regression models revealed that nonverbal number sense and working memory are central building blocks for developing early number competence in kindergarten and that early number competence is key for first grade math achievement. After controlling for early number competence, fluid intelligence significantly predicted arithmetic and number line estimation while receptive vocabulary significantly predicted shape and space skills. In sum we suggest that early math achievement draws on different constellations of number-specific and domain-general mechanisms. PMID:24772098

  20. Predicting first-grade mathematics achievement: the contributions of domain-general cognitive abilities, nonverbal number sense, and early number competence.

    PubMed

    Hornung, Caroline; Schiltz, Christine; Brunner, Martin; Martin, Romain

    2014-01-01

    Early number competence, grounded in number-specific and domain-general cognitive abilities, is theorized to lay the foundation for later math achievement. Few longitudinal studies have tested a comprehensive model for early math development. Using structural equation modeling and mediation analyses, the present work examined the influence of kindergarteners' nonverbal number sense and domain-general abilities (i.e., working memory, fluid intelligence, and receptive vocabulary) and their early number competence (i.e., symbolic number skills) on first grade math achievement (i.e., arithmetic, shape and space skills, and number line estimation) assessed 1 year later. Latent regression models revealed that nonverbal number sense and working memory are central building blocks for developing early number competence in kindergarten and that early number competence is key for first grade math achievement. After controlling for early number competence, fluid intelligence significantly predicted arithmetic and number line estimation while receptive vocabulary significantly predicted shape and space skills. In sum we suggest that early math achievement draws on different constellations of number-specific and domain-general mechanisms. PMID:24772098

  1. Accurate prediction of the binding free energy and analysis of the mechanism of the interaction of replication protein A (RPA) with ssDNA.

    PubMed

    Carra, Claudio; Cucinotta, Francis A

    2012-06-01

    The eukaryotic replication protein A (RPA) has several pivotal functions in the cell metabolism, such as chromosomal replication, prevention of hairpin formation, DNA repair and recombination, and signaling after DNA damage. Moreover, RPA seems to have a crucial role in organizing the sequential assembly of DNA processing proteins along single stranded DNA (ssDNA). The strong RPA affinity for ssDNA, K(A) between 10(-9)-10(-10) M, is characterized by a low cooperativity with minor variation for changes on the nucleotide sequence. Recently, new data on RPA interactions was reported, including the binding free energy of the complex RPA70AB with dC(8) and dC(5), which has been estimated to be -10 ± 0.4 kcal mol(-1) and -7 ± 1 kcal mol(-1), respectively. In view of these results we performed a study based on molecular dynamics aimed to reproduce the absolute binding free energy of RPA70AB with the dC(5) and dC(8) oligonucleotides. We used several tools to analyze the binding free energy, rigidity, and time evolution of the complex. The results obtained by MM-PBSA method, with the use of ligand free geometry as a reference for the receptor in the separate trajectory approach, are in excellent agreement with the experimental data, with ±4 kcal mol(-1) error. This result shows that the MM-PB(GB)SA methods can provide accurate quantitative estimates of the binding free energy for interacting complexes when appropriate geometries are used for the receptor, ligand and complex. The decomposition of the MM-GBSA energy for each residue in the receptor allowed us to correlate the change of the affinity of the mutated protein with the ΔG(gas+sol) contribution of the residue considered in the mutation. The agreement with experiment is optimal and a strong change in the binding free energy can be considered as the dominant factor in the loss for the binding affinity resulting from mutation. PMID:22116609

  2. Do attitudes toward societal structure predict beliefs about free will and achievement? Evidence from the Indian caste system.

    PubMed

    Srinivasan, Mahesh; Dunham, Yarrow; Hicks, Catherine M; Barner, David

    2016-01-01

    Intuitive theories about the malleability of intellectual ability affect our motivation and achievement in life. But how are such theories shaped by the culture in which an individual is raised? We addressed this question by exploring how Indian children's and adults' attitudes toward the Hindu caste system--and its deterministic worldview--are related to differences in their intuitive theories. Strikingly, we found that, beginning at least in middle school and continuing into adulthood, individuals who placed more importance on caste were more likely to adopt deterministic intuitive theories. We also found a developmental change in the scope of this relationship, such that in children, caste attitudes were linked only to abstract beliefs about personal freedom, but that by adulthood, caste attitudes were also linked to beliefs about the potential achievement of members of different castes, personal intellectual ability, and personality attributes. These results are the first to directly relate the societal structure in which a person is raised to the specific intuitive theories they adopt. PMID:25754516

  3. Quantitative Assessment of Protein Structural Models by Comparison of H/D Exchange MS Data with Exchange Behavior Accurately Predicted by DXCOREX

    NASA Astrophysics Data System (ADS)

    Liu, Tong; Pantazatos, Dennis; Li, Sheng; Hamuro, Yoshitomo; Hilser, Vincent J.; Woods, Virgil L.

    2012-01-01

    Peptide amide hydrogen/deuterium exchange mass spectrometry (DXMS) data are often used to qualitatively support models for protein structure. We have developed and validated a method (DXCOREX) by which exchange data can be used to quantitatively assess the accuracy of three-dimensional (3-D) models of protein structure. The method utilizes the COREX algorithm to predict a protein's amide hydrogen exchange rates by reference to a hypothesized structure, and these values are used to generate a virtual data set (deuteron incorporation per peptide) that can be quantitatively compared with the deuteration level of the peptide probes measured by hydrogen exchange experimentation. The accuracy of DXCOREX was established in studies performed with 13 proteins for which both high-resolution structures and experimental data were available. The DXCOREX-calculated and experimental data for each protein was highly correlated. We then employed correlation analysis of DXCOREX-calculated versus DXMS experimental data to assess the accuracy of a recently proposed structural model for the catalytic domain of a Ca2+-independent phospholipase A2. The model's calculated exchange behavior was highly correlated with the experimental exchange results available for the protein, supporting the accuracy of the proposed model. This method of analysis will substantially increase the precision with which experimental hydrogen exchange data can help decipher challenging questions regarding protein structure and dynamics.

  4. Accurate prediction of hard-sphere virial coefficients B6 to B12 from a compressibility-based equation of state

    NASA Astrophysics Data System (ADS)

    Hansen-Goos, Hendrik

    2016-04-01

    We derive an analytical equation of state for the hard-sphere fluid that is within 0.01% of computer simulations for the whole range of the stable fluid phase. In contrast, the commonly used Carnahan-Starling equation of state deviates by up to 0.3% from simulations. The derivation uses the functional form of the isothermal compressibility from the Percus-Yevick closure of the Ornstein-Zernike relation as a starting point. Two additional degrees of freedom are introduced, which are constrained by requiring the equation of state to (i) recover the exact fourth virial coefficient B4 and (ii) involve only integer coefficients on the level of the ideal gas, while providing best possible agreement with the numerical result for B5. Virial coefficients B6 to B10 obtained from the equation of state are within 0.5% of numerical computations, and coefficients B11 and B12 are within the error of numerical results. We conjecture that even higher virial coefficients are reliably predicted.

  5. Accurate predictions of spectroscopic and molecular properties of 27 Λ-S and 73 Ω states of AsS radical

    NASA Astrophysics Data System (ADS)

    Shi, Deheng; Song, Ziyue; Niu, Xianghong; Sun, Jinfeng; Zhu, Zunlue

    2016-01-01

    The PECs are calculated for the 27 Λ-S states and their corresponding 73 Ω states of AsS radical. Of these Λ-S states, only the 22Δ and 54Π states are replulsive. The 12Σ+, 22Σ+, 42Π, 34Δ, 34Σ+, and 44Π states possess double wells. The 32Σ+ state possesses three wells. The A2Π, 32Π, 12Φ, 24Π, 34Π, 24Δ, 34Δ, 16Σ+, and 16Π states are inverted with the SO coupling effect included. The 14Σ+, 24Σ+, 24Σ-, 24Δ, 14Φ, 16Σ+, and 16Π states, the second wells of 12Σ+, 34Σ+, 42Π, 44Π, and 34Δ states, and the third well of 32Σ+ state are very weakly-bound states. The PECs are extrapolated to the CBS limit. The effect of SO coupling on the PECs is discussed. The spectroscopic parameters are evaluated, and compared with available measurements and other theoretical ones. The vibrational properties of several weakly-bound states are determined. The spectroscopic properties reported here can be expected to be reliably predicted ones.

  6. Accurate prediction of hard-sphere virial coefficients B6 to B12 from a compressibility-based equation of state.

    PubMed

    Hansen-Goos, Hendrik

    2016-04-28

    We derive an analytical equation of state for the hard-sphere fluid that is within 0.01% of computer simulations for the whole range of the stable fluid phase. In contrast, the commonly used Carnahan-Starling equation of state deviates by up to 0.3% from simulations. The derivation uses the functional form of the isothermal compressibility from the Percus-Yevick closure of the Ornstein-Zernike relation as a starting point. Two additional degrees of freedom are introduced, which are constrained by requiring the equation of state to (i) recover the exact fourth virial coefficient B4 and (ii) involve only integer coefficients on the level of the ideal gas, while providing best possible agreement with the numerical result for B5. Virial coefficients B6 to B10 obtained from the equation of state are within 0.5% of numerical computations, and coefficients B11 and B12 are within the error of numerical results. We conjecture that even higher virial coefficients are reliably predicted. PMID:27131556

  7. The M. D. Anderson Symptom Inventory-Head and Neck Module, a Patient-Reported Outcome Instrument, Accurately Predicts the Severity of Radiation-Induced Mucositis

    SciTech Connect

    Rosenthal, David I. Mendoza, Tito R.; Chambers, Mark; Burkett, V. Shannon; Garden, Adam S.; Hessell, Amy C.; Lewin, Jan S.; Ang, K. Kian; Kies, Merrill S.

    2008-12-01

    Purpose: To compare the M. D. Anderson Symptom Inventory-Head and Neck (MDASI-HN) module, a symptom burden instrument, with the Functional Assessment of Cancer Therapy-Head and Neck (FACT-HN) module, a quality-of-life instrument, for the assessment of mucositis in patients with head-and-neck cancer treated with radiotherapy and to identify the most distressing symptoms from the patient's perspective. Methods and Materials: Consecutive patients with head-and-neck cancer (n = 134) completed the MDASI-HN and FACT-HN before radiotherapy (time 1) and after 6 weeks of radiotherapy or chemoradiotherapy (time 2). The mean global and subscale scores for each instrument were compared with the objective mucositis scores determined from the National Cancer Institute Common Terminology Criteria for Adverse Events, version 3.0. Results: The global and subscale scores for each instrument showed highly significant changes from time 1 to time 2 and a significant correlation with the objective mucositis scores at time 2. Only the MDASI scores, however, were significant predictors of objective Common Terminology Criteria for Adverse Events mucositis scores on multivariate regression analysis (standardized regression coefficient, 0.355 for the global score and 0.310 for the head-and-neck cancer-specific score). Most of the moderate and severe symptoms associated with mucositis as identified on the MDASI-HN are not present on the FACT-HN. Conclusion: Both the MDASI-HN and FACT-HN modules can predict the mucositis scores. However, the MDASI-HN, a symptom burden instrument, was more closely associated with the severity of radiation-induced mucositis than the FACT-HN on multivariate regression analysis. This greater association was most likely related to the inclusion of a greater number of face-valid mucositis-related items in the MDASI-HN compared with the FACT-HN.

  8. Accurate predictions of spectroscopic and molecular properties of 27 Λ-S and 73 Ω states of AsS radical.

    PubMed

    Shi, Deheng; Song, Ziyue; Niu, Xianghong; Sun, Jinfeng; Zhu, Zunlue

    2016-01-15

    The PECs are calculated for the 27 Λ-S states and their corresponding 73 Ω states of AsS radical. Of these Λ-S states, only the 2(2)Δ and 5(4)Π states are replulsive. The 1(2)Σ(+), 2(2)Σ(+), 4(2)Π, 3(4)Δ, 3(4)Σ(+), and 4(4)Π states possess double wells. The 3(2)Σ(+) state possesses three wells. The A(2)Π, 3(2)Π, 1(2)Φ, 2(4)Π, 3(4)Π, 2(4)Δ, 3(4)Δ, 1(6)Σ(+), and 1(6)Π states are inverted with the SO coupling effect included. The 1(4)Σ(+), 2(4)Σ(+), 2(4)Σ(-), 2(4)Δ, 1(4)Φ, 1(6)Σ(+), and 1(6)Π states, the second wells of 1(2)Σ(+), 3(4)Σ(+), 4(2)Π, 4(4)Π, and 3(4)Δ states, and the third well of 3(2)Σ(+) state are very weakly-bound states. The PECs are extrapolated to the CBS limit. The effect of SO coupling on the PECs is discussed. The spectroscopic parameters are evaluated, and compared with available measurements and other theoretical ones. The vibrational properties of several weakly-bound states are determined. The spectroscopic properties reported here can be expected to be reliably predicted ones. PMID:26282321

  9. "I Can Read Accurately but Can't Understand the Text Read": The Effects of Using a Reading Intervention on Fifth-Grade Students' "Word Callers" Reading Comprehension Achievement

    ERIC Educational Resources Information Center

    Grant, Christina E.

    2013-01-01

    The purpose of this study was to determine the effects of an intervention of five researched reading strategies on fifth-grade students' "word callers" reading achievement. Twenty-one fifth-grade students attending elementary schools in midwestern United States participated in this study. Students were randomly assigned to either the…

  10. Implementing the Effects of Changing Landscape by the Recent Bark Beetle Infestation on Snow Accumulation and Ablation to More Accurately Predict Stream Flow in the Upper Little Laramie River, Wyoming watershed.

    NASA Astrophysics Data System (ADS)

    Heward, J.; Ohara, N.

    2014-12-01

    In many alpine regions, especially in the western United States, the snow pack is the cause of the peak discharge and most of the annual flow. A distributed snow melt model with a point-scale snow melt theory is used to estimate the timing and intensity of both snow accumulation and ablation. The type and distribution of vegetation across a watershed influences timing and intensity of snow melt processes. Efforts are being made to understand how a changing landscape will ultimately affect stream flow in a mountainous environment. This study includes an analysis of the effects of the recent bark beetle infestation, using leaf area index (LAI) data acquired from MODIS data sets. These changes were incorporated into the snow model to more accurately predict snow melt timing and intensity. It was observed through the primary model implementation that snowmelt was intensified by the LAI reduction. The radiation change and turbulent flux effects were separately quantified by the vegetation parameterization in the snow model. This distributed snow model will be used to more accurately predict stream flow in the Upper Little Laramie River, Wyoming watershed.

  11. A Survey Study of Significent Achievements Accomplished By Snon-mainstreamt Seismologists In ¸ Earthquake Monitoring and Prediction Science In China Since 1970

    NASA Astrophysics Data System (ADS)

    Chen, I. W.

    Since 1990, the author, a British U Chinese consultant, has studied and followed the significant achievements accomplished by Snon-mainstreamT seismologists in ¸ earthquake prediction in China since 1970. The scientific systems used include: (1) Astronomy-seismology: The relativity between special positions of certain planets (es- pecially the moon and another planet) relative to the seismic active areas on the earth and the occurrence time of major damaging earthquakes in these areas on the earth, the relativity between the dates of magnetic storms on the earth and the occurrence dates of major damaging earthquakes on the earth, as well as certain cycle relativity be- tween the occurrence dates of major historical earthquakes occurring in relative areas on the earth. (2) Precursor analysis: With own-developed sensors and instruments, nu- merous precursors were recorded. In most cases, these precursors can not be detected by conventional seismological sensors/instruments. Through exploratory practice and theoretical studies, various relativity between different characteristics of the precur- sors, and the occurrence time, epicenter location and magnitude of the developing earthquake were identified and can be calculated. Through approaches quite differ- ent to conventional methods, successful predictions of quite a large number of earth- quakes have been achieved, including earthquakes that occurred in mainland China, Taiwan and Japan. (3) Earthquake imminent affirmative confirmation: With a special instrument, the background of imminent state of earthquakes can be identified, and a universal earthquake imminent signal is further identified. It can be used to confirm if an earlier predicted earthquake is entering its imminent state, if it will definitely occur, or if an earlier prediction can be released. (4) 5km, 7km and 10km depth com- parative terrestrial stress survey measurement to identify earthquake focus zones in surveyed areas. Then, with an eight

  12. Once we know all the radiobiology we need to know, how can we use it to predict space radiation risks and achieve fame and fortune?

    NASA Technical Reports Server (NTRS)

    Cucinotta, F. A.

    2001-01-01

    It has been over 40 years since occupational radiation exposures to NASA's astronauts began and more than 300 individuals have been exposed to low and intermediate doses of trapped protons and galactic cosmic rays (GCR). The International Space Station (ISS) will add substantially to this number and significantly increase average lifetime doses. We review these exposures in this report. After many years of investigation, the method used to assess risk have not changed significantly. However, molecular biology and genetics have made enormous progress in establishing the mechanisms of cancer formation, damage to the central nervous system, and individual variation in sensitivity to radiation. We discuss critical questions and possible new approaches to the prediction of risk from space radiation exposures. Experimental models can lead to testable theories that along with extensive biophysical and informatics approaches, will lead to fame and fortune by allowing for accurate projections of astronaut risks and for the development of biological countermeasures.

  13. Can Selforganizing Maps Accurately Predict Photometric Redshifts?

    NASA Technical Reports Server (NTRS)

    Way, Michael J.; Klose, Christian

    2012-01-01

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

  14. 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.

  15. Prediction of the curing time to achieve maturity of the nano-cement based concrete using the Weibull distribution model: A complementary data set

    PubMed Central

    Jo, Byung Wan; Chakraborty, Sumit; Kim, Heon

    2015-01-01

    This data article provides a comparison data for nano-cement based concrete (NCC) and ordinary Portland cement based concrete (OPCC). Concrete samples (OPCC) were fabricated using ten different mix design and their characterization data is provided here. Optimization of curing time using the Weibull distribution model was done by analyzing the rate of change of compressive strength of the OPCC. Initially, the compressive strength of the OPCC samples was measured after completion of four desired curing times. Thereafter, the required curing time to achieve a particular rate of change of the compressive strength has been predicted utilizing the equation derived from the variation of the rate of change of compressive strength with the curing time, prior to the optimization of the curing time (at the 99.99% confidence level) using the Weibull distribution model. This data article complements the research article entitled “Prediction of the curing time to achieve maturity of the nano-cement based concrete using the Weibull distribution model” [1]. PMID:26217804

  16. Prediction of the curing time to achieve maturity of the nano-cement based concrete using the Weibull distribution model: A complementary data set.

    PubMed

    Jo, Byung Wan; Chakraborty, Sumit; Kim, Heon

    2015-09-01

    This data article provides a comparison data for nano-cement based concrete (NCC) and ordinary Portland cement based concrete (OPCC). Concrete samples (OPCC) were fabricated using ten different mix design and their characterization data is provided here. Optimization of curing time using the Weibull distribution model was done by analyzing the rate of change of compressive strength of the OPCC. Initially, the compressive strength of the OPCC samples was measured after completion of four desired curing times. Thereafter, the required curing time to achieve a particular rate of change of the compressive strength has been predicted utilizing the equation derived from the variation of the rate of change of compressive strength with the curing time, prior to the optimization of the curing time (at the 99.99% confidence level) using the Weibull distribution model. This data article complements the research article entitled "Prediction of the curing time to achieve maturity of the nano-cement based concrete using the Weibull distribution model" [1]. PMID:26217804

  17. ABC goal achievement predicts microvascular but not macrovascular complications over 6-years in adults with type 1 diabetes: the Coronary Artery Calcification in Type 1 Diabetes Study

    PubMed Central

    Bjornstad, Petter; Maahs, David M.; Rewers, Marian; Johnson, Richard J.; Snell-Bergeon, Janet K.

    2014-01-01

    Hypothesis Vascular complications of type 1 diabetes are thought to cluster. We examined the prevalence and incidence of vascular complications and American Diabetes Association’s ABC goal achievements in a prospective cohort of adults with type 1 diabetes. We hypothesized that ABC achievement at baseline would predict both micro- and macrovascular complications over 6-years. Methods Participants (N=652) were 19–56 year old at baseline and re-examined 6-years later. Microvascular complications included diabetic nephropathy (DN), defined as incident albuminuria (AER≥20μg/min) or rapid GFR decline (>3.3%/year) by CKD-EPI cystatin C and proliferative diabetic retinopathy (PDR), defined as laser eye-therapy. Macrovascular complications were defined as coronary artery calcium progression (CACp), measured by electron-beam computed-tomography. ABC goals were defined as HbA1c<7.0%, BP<130/80 mmHg, LDL-C<100mg/dL. Results ABC control was suboptimal with only 6% meeting all goals. Meeting no ABC goals at baseline compared to meeting all goals was associated with increased odds of developing microvascular complications (OR: 8.5, 2.3–31.5, p=0.001), but did not reach significance for CACp (OR: 1.7, 0.8–3.9, p=0.19). Conclusion ABC achievement at baseline strongly predicted microvascular but not macrovascular complications over 6-years in adults with type 1 diabetes, suggesting a need for novel therapeutic targets to complement conventional risk factors in treating macrovascular complications. PMID:25270733

  18. A Survey Study of Significent Achievements Accomplished By Snon-mainstreamt Seismologists In ¸ Earthquake Monitoring and Prediction Science In China Since 1970

    NASA Astrophysics Data System (ADS)

    Chen, I. W.

    Since 1990, the author, a British U Chinese consultant, has studied and followed the significant achievements accomplished by Snon-mainstreamT seismologists in & cedil;earthquake prediction in China since 1970. The scientific systems used include: (1) Astronomy-seismology: The relativity between special positions of certain planets (es- pecially the moon and another planet) relative to the seismic active areas on the earth and the occurrence time of major damaging earthquakes in these areas on the earth, the relativity between the dates of magnetic storms on the earth and the occurrence dates of major damaging earthquakes on the earth, as well as certain cycle relativity be- tween the occurrence dates of major historical earthquakes occurring in relative areas on the earth. (2) Precursor analysis: With own-developed sensors and instruments, nu- merous precursors were recorded. In most cases, these precursors can not be detected by conventional seismological sensors/instruments. Through exploratory practice and theoretical studies, various relativity between different characteristics of the precur- sors, and the occurrence time, epicenter location and magnitude of the developing earthquake were identified and can be calculated. Through approaches quite differ- ent to conventional methods, successful predictions of quite a large number of earth- quakes have been achieved, including earthquakes that occurred in mainland China, Taiwan and Japan. (3) Earthquake imminent affirmative confirmation: With a special instrument, the background of imminent state of earthquakes can be identified, and a universal earthquake imminent signal is further identified. It can be used to confirm if an earlier predicted earthquake is entering its imminent state, if it will definitely occur, or if an earlier prediction can be released. (4) 5km, 7km and 10km depth com- parative terrestrial stress survey measurement to identify earthquake focus zones in surveyed areas. Then, with an eight

  19. How Many Letters Should Preschoolers in Public Programs Know? The Diagnostic Efficiency of Various Preschool Letter-Naming Benchmarks for Predicting First-Grade Literacy Achievement

    PubMed Central

    Piasta, Shayne B.; Petscher, Yaacov; Justice, Laura M.

    2015-01-01

    Review of current federal and state standards indicates little consensus or empirical justification regarding appropriate goals, often referred to as benchmarks, for preschool letter-name learning. The present study investigated the diagnostic efficiency of various letter-naming benchmarks using a longitudinal database of 371 children who attended publicly funded preschools. Children’s uppercase and lowercase letter-naming abilities were assessed at the end of preschool, and their literacy achievement on 3 standardized measures was assessed at the end of 1st grade. Diagnostic indices (sensitivity, specificity, and negative and positive predictive power) were generated to examine the extent to which attainment of various preschool letter-naming benchmarks was associated with later risk for literacy difficulties. Results indicated generally high negative predictive power for benchmarks requiring children to know 10 or more letter names by the end of preschool. Balancing across all diagnostic indices, optimal benchmarks of 18 uppercase and 15 lowercase letter names were identified. These findings are discussed in terms of educational implications, limitations, and future directions. PMID:26346643

  20. Varieties of Achievement Motivation.

    ERIC Educational Resources Information Center

    Kukla, Andre; Scher, Hal

    1986-01-01

    A recent article by Nicholls on achievement motivation is criticized on three points: (1) definitions of achievement motives are ambiguous; (2) behavioral consequences predicted do not follow from explicit theoretical assumptions; and (3) Nicholls's account of the relation between his theory and other achievement theories is factually incorrect.…

  1. PASS and Reading Achievement.

    ERIC Educational Resources Information Center

    Kirby, John R.

    Two studies examined the effectiveness of the PASS (Planning, Attention, Simultaneous, and Successive cognitive processes) theory of intelligence in predicting reading achievement scores of normally achieving children and distinguishing children with reading disabilities from normally achieving children. The first study dealt with predicting…

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

    PubMed Central

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

    2016-01-01

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

  3. Grading More Accurately

    ERIC Educational Resources Information Center

    Rom, Mark Carl

    2011-01-01

    Grades matter. College grading systems, however, are often ad hoc and prone to mistakes. This essay focuses on one factor that contributes to high-quality grading systems: grading accuracy (or "efficiency"). I proceed in several steps. First, I discuss the elements of "efficient" (i.e., accurate) grading. Next, I present analytical results…

  4. Critical Combinations of Radiation Dose and Volume Predict Intelligence Quotient and Academic Achievement Scores After Craniospinal Irradiation in Children With Medulloblastoma

    SciTech Connect

    Merchant, Thomas E.; Schreiber, Jane E.; Wu, Shengjie; Lukose, Renin; Xiong, Xiaoping; Gajjar, Amar

    2014-11-01

    Purpose: To prospectively follow children treated with craniospinal irradiation to determine critical combinations of radiation dose and volume that would predict for cognitive effects. Methods and Materials: Between 1996 and 2003, 58 patients (median age 8.14 years, range 3.99-20.11 years) with medulloblastoma received risk-adapted craniospinal irradiation followed by dose-intense chemotherapy and were followed longitudinally with multiple cognitive evaluations (through 5 years after treatment) that included intelligence quotient (estimated intelligence quotient, full-scale, verbal, and performance) and academic achievement (math, reading, spelling) tests. Craniospinal irradiation consisted of 23.4 Gy for average-risk patients (nonmetastatic) and 36-39.6 Gy for high-risk patients (metastatic or residual disease >1.5 cm{sup 2}). The primary site was treated using conformal or intensity modulated radiation therapy using a 2-cm clinical target volume margin. The effect of clinical variables and radiation dose to different brain volumes were modeled to estimate cognitive scores after treatment. Results: A decline with time for all test scores was observed for the entire cohort. Sex, race, and cerebrospinal fluid shunt status had a significant impact on baseline scores. Age and mean radiation dose to specific brain volumes, including the temporal lobes and hippocampi, had a significant impact on longitudinal scores. Dichotomized dose distributions at 25 Gy, 35 Gy, 45 Gy, and 55 Gy were modeled to show the impact of the high-dose volume on longitudinal test scores. The 50% risk of a below-normal cognitive test score was calculated according to mean dose and dose intervals between 25 Gy and 55 Gy at 10-Gy increments according to brain volume and age. Conclusions: The ability to predict cognitive outcomes in children with medulloblastoma using dose-effects models for different brain subvolumes will improve treatment planning, guide intervention, and help

  5. Accurate monotone cubic interpolation

    NASA Technical Reports Server (NTRS)

    Huynh, Hung T.

    1991-01-01

    Monotone piecewise cubic interpolants are simple and effective. They are generally third-order accurate, except near strict local extrema where accuracy degenerates to second-order due to the monotonicity constraint. Algorithms for piecewise cubic interpolants, which preserve monotonicity as well as uniform third and fourth-order accuracy are presented. The gain of accuracy is obtained by relaxing the monotonicity constraint in a geometric framework in which the median function plays a crucial role.

  6. Accurate Finite Difference Algorithms

    NASA Technical Reports Server (NTRS)

    Goodrich, John W.

    1996-01-01

    Two families of finite difference algorithms for computational aeroacoustics are presented and compared. All of the algorithms are single step explicit methods, they have the same order of accuracy in both space and time, with examples up to eleventh order, and they have multidimensional extensions. One of the algorithm families has spectral like high resolution. Propagation with high order and high resolution algorithms can produce accurate results after O(10(exp 6)) periods of propagation with eight grid points per wavelength.

  7. 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…

  8. Efficient and accurate sound propagation using adaptive rectangular decomposition.

    PubMed

    Raghuvanshi, Nikunj; Narain, Rahul; Lin, Ming C

    2009-01-01

    Accurate sound rendering can add significant realism to complement visual display in interactive applications, as well as facilitate acoustic predictions for many engineering applications, like accurate acoustic analysis for architectural design. Numerical simulation can provide this realism most naturally by modeling the underlying physics of wave propagation. However, wave simulation has traditionally posed a tough computational challenge. In this paper, we present a technique which relies on an adaptive rectangular decomposition of 3D scenes to enable efficient and accurate simulation of sound propagation in complex virtual environments. It exploits the known analytical solution of the Wave Equation in rectangular domains, and utilizes an efficient implementation of the Discrete Cosine Transform on Graphics Processors (GPU) to achieve at least a 100-fold performance gain compared to a standard Finite-Difference Time-Domain (FDTD) implementation with comparable accuracy, while also being 10-fold more memory efficient. Consequently, we are able to perform accurate numerical acoustic simulation on large, complex scenes in the kilohertz range. To the best of our knowledge, it was not previously possible to perform such simulations on a desktop computer. Our work thus enables acoustic analysis on large scenes and auditory display for complex virtual environments on commodity hardware. PMID:19590105

  9. Radio interferometric measurements for accurate planetary orbiter navigation

    NASA Technical Reports Server (NTRS)

    Poole, S. R.; Ananda, M.; Hildebrand, C. E.

    1979-01-01

    The use of narrowband delta-VLBI to achieve accurate orbit determination is presented by viewing a spacecraft from widely separated stations followed by viewing a nearby quasar from the same stations. Current analysis is examined that establishes the orbit determination accuracy achieved with data arcs spanning up to 3.5 d. Strategies for improving prediction accuracy are given, and the performance of delta-VLBI is compared with conventional radiometric tracking data. It is found that accuracy 'within the fit' is on the order of 0.5 km for data arcs having delta-VLBI on the ends of the arcs and for arc lengths varying from one baseline to 3.5 d. The technique is discussed with reference to the proposed Venus Orbiting Imaging Radar mission.

  10. Accurate adiabatic correction in the hydrogen molecule

    SciTech Connect

    Pachucki, Krzysztof; Komasa, Jacek

    2014-12-14

    A new formalism for the accurate treatment of adiabatic effects in the hydrogen molecule is presented, in which the electronic wave function is expanded in the James-Coolidge basis functions. Systematic increase in the size of the basis set permits estimation of the accuracy. Numerical results for the adiabatic correction to the Born-Oppenheimer interaction energy reveal a relative precision of 10{sup −12} at an arbitrary internuclear distance. Such calculations have been performed for 88 internuclear distances in the range of 0 < R ⩽ 12 bohrs to construct the adiabatic correction potential and to solve the nuclear Schrödinger equation. Finally, the adiabatic correction to the dissociation energies of all rovibrational levels in H{sub 2}, HD, HT, D{sub 2}, DT, and T{sub 2} has been determined. For the ground state of H{sub 2} the estimated precision is 3 × 10{sup −7} cm{sup −1}, which is almost three orders of magnitude higher than that of the best previous result. The achieved accuracy removes the adiabatic contribution from the overall error budget of the present day theoretical predictions for the rovibrational levels.

  11. Accurate adiabatic correction in the hydrogen molecule

    NASA Astrophysics Data System (ADS)

    Pachucki, Krzysztof; Komasa, Jacek

    2014-12-01

    A new formalism for the accurate treatment of adiabatic effects in the hydrogen molecule is presented, in which the electronic wave function is expanded in the James-Coolidge basis functions. Systematic increase in the size of the basis set permits estimation of the accuracy. Numerical results for the adiabatic correction to the Born-Oppenheimer interaction energy reveal a relative precision of 10-12 at an arbitrary internuclear distance. Such calculations have been performed for 88 internuclear distances in the range of 0 < R ⩽ 12 bohrs to construct the adiabatic correction potential and to solve the nuclear Schrödinger equation. Finally, the adiabatic correction to the dissociation energies of all rovibrational levels in H2, HD, HT, D2, DT, and T2 has been determined. For the ground state of H2 the estimated precision is 3 × 10-7 cm-1, which is almost three orders of magnitude higher than that of the best previous result. The achieved accuracy removes the adiabatic contribution from the overall error budget of the present day theoretical predictions for the rovibrational levels.

  12. Accurate, reliable prototype earth horizon sensor head

    NASA Technical Reports Server (NTRS)

    Schwarz, F.; Cohen, H.

    1973-01-01

    The design and performance is described of an accurate and reliable prototype earth sensor head (ARPESH). The ARPESH employs a detection logic 'locator' concept and horizon sensor mechanization which should lead to high accuracy horizon sensing that is minimally degraded by spatial or temporal variations in sensing attitude from a satellite in orbit around the earth at altitudes in the 500 km environ 1,2. An accuracy of horizon location to within 0.7 km has been predicted, independent of meteorological conditions. This corresponds to an error of 0.015 deg-at 500 km altitude. Laboratory evaluation of the sensor indicates that this accuracy is achieved. First, the basic operating principles of ARPESH are described; next, detailed design and construction data is presented and then performance of the sensor under laboratory conditions in which the sensor is installed in a simulator that permits it to scan over a blackbody source against background representing the earth space interface for various equivalent plant temperatures.

  13. Downstream prediction using a nonlinear prediction method

    NASA Astrophysics Data System (ADS)

    Adenan, N. H.; Noorani, M. S. M.

    2013-11-01

    The estimation of river flow is significantly related to the impact of urban hydrology, as this could provide information to solve important problems, such as flooding downstream. The nonlinear prediction method has been employed for analysis of four years of daily river flow data for the Langat River at Kajang, Malaysia, which is located in a downstream area. The nonlinear prediction method involves two steps; namely, the reconstruction of phase space and prediction. The reconstruction of phase space involves reconstruction from a single variable to the m-dimensional phase space in which the dimension m is based on optimal values from two methods: the correlation dimension method (Model I) and false nearest neighbour(s) (Model II). The selection of an appropriate method for selecting a combination of preliminary parameters, such as m, is important to provide an accurate prediction. From our investigation, we gather that via manipulation of the appropriate parameters for the reconstruction of the phase space, Model II provides better prediction results. In particular, we have used Model II together with the local linear prediction method to achieve the prediction results for the downstream area with a high correlation coefficient. In summary, the results show that Langat River in Kajang is chaotic, and, therefore, predictable using the nonlinear prediction method. Thus, the analysis and prediction of river flow in this area can provide river flow information to the proper authorities for the construction of flood control, particularly for the downstream area.

  14. Accurate measurement of time

    NASA Astrophysics Data System (ADS)

    Itano, Wayne M.; Ramsey, Norman F.

    1993-07-01

    The paper discusses current methods for accurate measurements of time by conventional atomic clocks, with particular attention given to the principles of operation of atomic-beam frequency standards, atomic hydrogen masers, and atomic fountain and to the potential use of strings of trapped mercury ions as a time device more stable than conventional atomic clocks. The areas of application of the ultraprecise and ultrastable time-measuring devices that tax the capacity of modern atomic clocks include radio astronomy and tests of relativity. The paper also discusses practical applications of ultraprecise clocks, such as navigation of space vehicles and pinpointing the exact position of ships and other objects on earth using the GPS.

  15. A method of predicting flow rates required to achieve anti-icing performance with a porous leading edge ice protection system

    NASA Technical Reports Server (NTRS)

    Kohlman, D. L.; Albright, A. E.

    1983-01-01

    An analytical method was developed for predicting minimum flow rates required to provide anti-ice protection with a porous leading edge fluid ice protection system. The predicted flow rates compare with an average error of less than 10 percent to six experimentally determined flow rates from tests in the NASA Icing Research Tunnel on a general aviation wing section.

  16. What "No Child Left Behind" Leaves behind: The Roles of IQ and Self-Control in Predicting Standardized Achievement Test Scores and Report Card Grades

    ERIC Educational Resources Information Center

    Duckworth, Angela L.; Quinn, Patrick D.; Tsukayama, Eli

    2012-01-01

    The increasing prominence of standardized testing to assess student learning motivated the current investigation. We propose that standardized achievement test scores assess competencies determined more by intelligence than by self-control, whereas report card grades assess competencies determined more by self-control than by intelligence. In…

  17. Humor and College Adjustment: The Predictive Nature of Humor, Academic Achievement, Authoritative Parenting Styles on the Initial Adjustment of Male and Female First-Year College Students

    ERIC Educational Resources Information Center

    Hickman, Gregory P.; Andrews, David W.

    2003-01-01

    A self-report questionnaire on academic achievement, birth order, and family structure; the Student Adaptation to College Questionnaire; the Parental Authority Questionnaire; and the Coping Humor Scale were administered to 257 first-year college students. Researchers examined the relationships among (a) authoritative parenting style, (b) family…

  18. The Predictive Nature of Humor, Authoritative Parenting Style, and Academic Achievement on Indices of Initial Adjustment and Commitment to College among College Freshmen

    ERIC Educational Resources Information Center

    Hickman, Gregory P.; Crossland, Garnet L.

    2004-01-01

    Through the administration of self-report surveys, this study examined the relationships among a) parenting styles, b) family structure, c) academic achievement, d) birth order, e) gender, and f) humor on the initial personal-emotional, social, academic, and commitment to college adjustment among 257 first-quarter college freshmen. Multiple…

  19. The Extended Theory of Planned Behaviour and College Grades: The Role of Cognition and Past Behaviour in the Prediction of Students' Academic Intentions and Achievements

    ERIC Educational Resources Information Center

    Kovac, Velibor Bobo; Cameron, David Lansing; Høigaard, Rune

    2016-01-01

    Understanding the underlying processes influencing college students' academic achievement represents an important goal of educational research. The aim of the present study was to examine the utility of the extended Theory of Planned Behaviour (TPB) and the relative influence of cognitive processes and measures of past behaviour in the prediction…

  20. Predicting Academic Outcomes for Third Grade Students: Examining the Reading Achievement of Diverse Students Using the Diagnostic Lens of the Dynamic Indicators of Basic Early Literacy Skills

    ERIC Educational Resources Information Center

    Adderley, Zhivago Trevino

    2013-01-01

    Despite the billions of dollars spent in the last forty years, America's efforts toward closing the achievement gaps among diverse learners and their receptive counterparts have not been realized. Limitations noted in previous research discussed the need to examine the unique contributions of diverse learner variables as a way of determining their…