Sample records for accurate theoretical predictions

  1. Molecular acidity: An accurate description with information-theoretic approach in density functional reactivity theory.

    PubMed

    Cao, Xiaofang; Rong, Chunying; Zhong, Aiguo; Lu, Tian; Liu, Shubin

    2018-01-15

    Molecular acidity is one of the important physiochemical properties of a molecular system, yet its accurate calculation and prediction are still an unresolved problem in the literature. In this work, we propose to make use of the quantities from the information-theoretic (IT) approach in density functional reactivity theory and provide an accurate description of molecular acidity from a completely new perspective. To illustrate our point, five different categories of acidic series, singly and doubly substituted benzoic acids, singly substituted benzenesulfinic acids, benzeneseleninic acids, phenols, and alkyl carboxylic acids, have been thoroughly examined. We show that using IT quantities such as Shannon entropy, Fisher information, Ghosh-Berkowitz-Parr entropy, information gain, Onicescu information energy, and relative Rényi entropy, one is able to simultaneously predict experimental pKa values of these different categories of compounds. Because of the universality of the quantities employed in this work, which are all density dependent, our approach should be general and be applicable to other systems as well. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  2. Accurate Theoretical Predictions of the Properties of Energetic Materials

    DTIC Science & Technology

    2008-09-18

    decomposition, Monte Carlo, molecular dynamics, supercritical fluids, solvation and separation, quantum Monte Carlo, potential energy surfaces, RDX , TNAZ...labs, who are contributing to the theoretical efforts, providing data for testing of the models, or aiding in the transition of the methods, models...and results to DoD applications. The major goals of the project are: • Models that describe phase transitions and chemical reactions in

  3. Mental models accurately predict emotion transitions.

    PubMed

    Thornton, Mark A; Tamir, Diana I

    2017-06-06

    Successful social interactions depend on people's ability to predict others' future actions and emotions. People possess many mechanisms for perceiving others' current emotional states, but how might they use this information to predict others' future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others' emotional dynamics. People could then use these mental models of emotion transitions to predict others' future emotions from currently observable emotions. To test this hypothesis, studies 1-3 used data from three extant experience-sampling datasets to establish the actual rates of emotional transitions. We then collected three parallel datasets in which participants rated the transition likelihoods between the same set of emotions. Participants' ratings of emotion transitions predicted others' experienced transitional likelihoods with high accuracy. Study 4 demonstrated that four conceptual dimensions of mental state representation-valence, social impact, rationality, and human mind-inform participants' mental models. Study 5 used 2 million emotion reports on the Experience Project to replicate both of these findings: again people reported accurate models of emotion transitions, and these models were informed by the same four conceptual dimensions. Importantly, neither these conceptual dimensions nor holistic similarity could fully explain participants' accuracy, suggesting that their mental models contain accurate information about emotion dynamics above and beyond what might be predicted by static emotion knowledge alone.

  4. Mental models accurately predict emotion transitions

    PubMed Central

    Thornton, Mark A.; Tamir, Diana I.

    2017-01-01

    Successful social interactions depend on people’s ability to predict others’ future actions and emotions. People possess many mechanisms for perceiving others’ current emotional states, but how might they use this information to predict others’ future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others’ emotional dynamics. People could then use these mental models of emotion transitions to predict others’ future emotions from currently observable emotions. To test this hypothesis, studies 1–3 used data from three extant experience-sampling datasets to establish the actual rates of emotional transitions. We then collected three parallel datasets in which participants rated the transition likelihoods between the same set of emotions. Participants’ ratings of emotion transitions predicted others’ experienced transitional likelihoods with high accuracy. Study 4 demonstrated that four conceptual dimensions of mental state representation—valence, social impact, rationality, and human mind—inform participants’ mental models. Study 5 used 2 million emotion reports on the Experience Project to replicate both of these findings: again people reported accurate models of emotion transitions, and these models were informed by the same four conceptual dimensions. Importantly, neither these conceptual dimensions nor holistic similarity could fully explain participants’ accuracy, suggesting that their mental models contain accurate information about emotion dynamics above and beyond what might be predicted by static emotion knowledge alone. PMID:28533373

  5. Searching for an Accurate Marker-Based Prediction of an Individual Quantitative Trait in Molecular Plant Breeding

    PubMed Central

    Fu, Yong-Bi; Yang, Mo-Hua; Zeng, Fangqin; Biligetu, Bill

    2017-01-01

    Molecular plant breeding with the aid of molecular markers has played an important role in modern plant breeding over the last two decades. Many marker-based predictions for quantitative traits have been made to enhance parental selection, but the trait prediction accuracy remains generally low, even with the aid of dense, genome-wide SNP markers. To search for more accurate trait-specific prediction with informative SNP markers, we conducted a literature review on the prediction issues in molecular plant breeding and on the applicability of an RNA-Seq technique for developing function-associated specific trait (FAST) SNP markers. To understand whether and how FAST SNP markers could enhance trait prediction, we also performed a theoretical reasoning on the effectiveness of these markers in a trait-specific prediction, and verified the reasoning through computer simulation. To the end, the search yielded an alternative to regular genomic selection with FAST SNP markers that could be explored to achieve more accurate trait-specific prediction. Continuous search for better alternatives is encouraged to enhance marker-based predictions for an individual quantitative trait in molecular plant breeding. PMID:28729875

  6. Accurate experimental and theoretical comparisons between superconductor-insulator-superconductor mixers showing weak and strong quantum effects

    NASA Technical Reports Server (NTRS)

    Mcgrath, W. R.; Richards, P. L.; Face, D. W.; Prober, D. E.; Lloyd, F. L.

    1988-01-01

    A systematic study of the gain and noise in superconductor-insulator-superconductor mixers employing Ta based, Nb based, and Pb-alloy based tunnel junctions was made. These junctions displayed both weak and strong quantum effects at a signal frequency of 33 GHz. The effects of energy gap sharpness and subgap current were investigated and are quantitatively related to mixer performance. Detailed comparisons are made of the mixing results with the predictions of a three-port model approximation to the Tucker theory. Mixer performance was measured with a novel test apparatus which is accurate enough to allow for the first quantitative tests of theoretical noise predictions. It is found that the three-port model of the Tucker theory underestimates the mixer noise temperature by a factor of about 2 for all of the mixers. In addition, predicted values of available mixer gain are in reasonable agreement with experiment when quantum effects are weak. However, as quantum effects become strong, the predicted available gain diverges to infinity, which is in sharp contrast to the experimental results. Predictions of coupled gain do not always show such divergences.

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

    NASA Astrophysics Data System (ADS)

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

    2014-06-01

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

  8. Kinetic approach to degradation mechanisms in polymer solar cells and their accurate lifetime predictions

    NASA Astrophysics Data System (ADS)

    Arshad, Muhammad Azeem; Maaroufi, AbdelKrim

    2018-07-01

    A beginning has been made in the present study regarding the accurate lifetime predictions of polymer solar cells. Certain reservations about the conventionally employed temperature accelerated lifetime measurements test for its unworthiness of predicting reliable lifetimes of polymer solar cells are brought into light. Critical issues concerning the accelerated lifetime testing include, assuming reaction mechanism instead of determining it, and relying solely on the temperature acceleration of a single property of material. An advanced approach comprising a set of theoretical models to estimate the accurate lifetimes of polymer solar cells is therefore suggested in order to suitably alternate the accelerated lifetime testing. This approach takes into account systematic kinetic modeling of various possible polymer degradation mechanisms under natural weathering conditions. The proposed kinetic approach is substantiated by its applications on experimental aging data-sets of polymer solar materials/solar cells including, P3HT polymer film, bulk heterojunction (MDMO-PPV:PCBM) and dye-sensitized solar cells. Based on the suggested approach, an efficacious lifetime determination formula for polymer solar cells is derived and tested on dye-sensitized solar cells. Some important merits of the proposed method are also pointed out and its prospective applications are discussed.

  9. Biomarker Surrogates Do Not Accurately Predict Sputum Eosinophils and Neutrophils in Asthma

    PubMed Central

    Hastie, Annette T.; Moore, Wendy C.; Li, Huashi; Rector, Brian M.; Ortega, Victor E.; Pascual, Rodolfo M.; Peters, Stephen P.; Meyers, Deborah A.; Bleecker, Eugene R.

    2013-01-01

    Background Sputum eosinophils (Eos) are a strong predictor of airway inflammation, exacerbations, and aid asthma management, whereas sputum neutrophils (Neu) indicate a different severe asthma phenotype, potentially less responsive to TH2-targeted therapy. Variables such as blood Eos, total IgE, fractional exhaled nitric oxide (FeNO) or FEV1% predicted, may predict airway Eos, while age, FEV1%predicted, or blood Neu may predict sputum Neu. Availability and ease of measurement are useful characteristics, but accuracy in predicting airway Eos and Neu, individually or combined, is not established. Objectives To determine whether blood Eos, FeNO, and IgE accurately predict sputum eosinophils, and age, FEV1% predicted, and blood Neu accurately predict sputum neutrophils (Neu). Methods Subjects in the Wake Forest Severe Asthma Research Program (N=328) were characterized by blood and sputum cells, healthcare utilization, lung function, FeNO, and IgE. Multiple analytical techniques were utilized. Results Despite significant association with sputum Eos, blood Eos, FeNO and total IgE did not accurately predict sputum Eos, and combinations of these variables failed to improve prediction. Age, FEV1%predicted and blood Neu were similarly unsatisfactory for prediction of sputum Neu. Factor analysis and stepwise selection found FeNO, IgE and FEV1% predicted, but not blood Eos, correctly predicted 69% of sputum Eospredicted 64% of sputum Neupredict both sputum Eos and Neu accurately assigned only 41% of samples. Conclusion Despite statistically significant associations FeNO, IgE, blood Eos and Neu, FEV1%predicted, and age are poor surrogates, separately and combined, for accurately predicting sputum eosinophils and neutrophils. PMID:23706399

  10. Experimental and theoretical oscillator strengths of Mg I for accurate abundance analysis

    NASA Astrophysics Data System (ADS)

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

    2017-02-01

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

  11. Accurate Identification of Fear Facial Expressions Predicts Prosocial Behavior

    PubMed Central

    Marsh, Abigail A.; Kozak, Megan N.; Ambady, Nalini

    2009-01-01

    The fear facial expression is a distress cue that is associated with the provision of help and prosocial behavior. Prior psychiatric studies have found deficits in the recognition of this expression by individuals with antisocial tendencies. However, no prior study has shown accuracy for recognition of fear to predict actual prosocial or antisocial behavior in an experimental setting. In 3 studies, the authors tested the prediction that individuals who recognize fear more accurately will behave more prosocially. In Study 1, participants who identified fear more accurately also donated more money and time to a victim in a classic altruism paradigm. In Studies 2 and 3, participants’ ability to identify the fear expression predicted prosocial behavior in a novel task designed to control for confounding variables. In Study 3, accuracy for recognizing fear proved a better predictor of prosocial behavior than gender, mood, or scores on an empathy scale. PMID:17516803

  12. Accurate identification of fear facial expressions predicts prosocial behavior.

    PubMed

    Marsh, Abigail A; Kozak, Megan N; Ambady, Nalini

    2007-05-01

    The fear facial expression is a distress cue that is associated with the provision of help and prosocial behavior. Prior psychiatric studies have found deficits in the recognition of this expression by individuals with antisocial tendencies. However, no prior study has shown accuracy for recognition of fear to predict actual prosocial or antisocial behavior in an experimental setting. In 3 studies, the authors tested the prediction that individuals who recognize fear more accurately will behave more prosocially. In Study 1, participants who identified fear more accurately also donated more money and time to a victim in a classic altruism paradigm. In Studies 2 and 3, participants' ability to identify the fear expression predicted prosocial behavior in a novel task designed to control for confounding variables. In Study 3, accuracy for recognizing fear proved a better predictor of prosocial behavior than gender, mood, or scores on an empathy scale.

  13. Accurate Binding Free Energy Predictions in Fragment Optimization.

    PubMed

    Steinbrecher, Thomas B; Dahlgren, Markus; Cappel, Daniel; Lin, Teng; Wang, Lingle; Krilov, Goran; Abel, Robert; Friesner, Richard; Sherman, Woody

    2015-11-23

    Predicting protein-ligand binding free energies is a central aim of computational structure-based drug design (SBDD)--improved accuracy in binding free energy predictions could significantly reduce costs and accelerate project timelines in lead discovery and optimization. The recent development and validation of advanced free energy calculation methods represents a major step toward this goal. Accurately predicting the relative binding free energy changes of modifications to ligands is especially valuable in the field of fragment-based drug design, since fragment screens tend to deliver initial hits of low binding affinity that require multiple rounds of synthesis to gain the requisite potency for a project. In this study, we show that a free energy perturbation protocol, FEP+, which was previously validated on drug-like lead compounds, is suitable for the calculation of relative binding strengths of fragment-sized compounds as well. We study several pharmaceutically relevant targets with a total of more than 90 fragments and find that the FEP+ methodology, which uses explicit solvent molecular dynamics and physics-based scoring with no parameters adjusted, can accurately predict relative fragment binding affinities. The calculations afford R(2)-values on average greater than 0.5 compared to experimental data and RMS errors of ca. 1.1 kcal/mol overall, demonstrating significant improvements over the docking and MM-GBSA methods tested in this work and indicating that FEP+ has the requisite predictive power to impact fragment-based affinity optimization projects.

  14. Aircraft noise prediction program theoretical manual, part 1

    NASA Technical Reports Server (NTRS)

    Zorumski, W. E.

    1982-01-01

    Aircraft noise prediction theoretical methods are given. The prediction of data which affect noise generation and propagation is addressed. These data include the aircraft flight dynamics, the source noise parameters, and the propagation effects.

  15. Theoretical model predictions and experimental results for a wavelength switchable Tm:YAG laser.

    PubMed

    Niu, Yanxiong; Wang, Caili; Liu, Wenwen; Niu, Haisha; Xu, Bing; Man, Da

    2014-07-01

    We present a theoretical model study of a quasi-three-level laser with particular attention given to the Tm:YAG laser. The oscillating conditions of this laser were theoretically analyzed from the point of the pump threshold while taking into account reabsorption loss. The laser oscillation at 2.02 μm with large stimulated emission sections was suppressed by selecting the appropriate coating for the cavity mirrors, then an efficient laser-diode side-pumped continuous-wave Tm:YAG crystal laser operating at 2.07 μm was realized. Experiments with the Tm:YAG laser confirmed the accuracy of the model, and the model was able to accurately predict that the high Stark sub-level within the H36 ground state manifold has a low laser threshold and long laser wavelength, which was achieved by decreasing the transmission of the output coupler.

  16. 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

  17. ASTRAL, DRAGON and SEDAN scores predict stroke outcome more accurately than physicians.

    PubMed

    Ntaios, G; Gioulekas, F; Papavasileiou, V; Strbian, D; Michel, P

    2016-11-01

    ASTRAL, SEDAN and DRAGON scores are three well-validated scores for stroke outcome prediction. Whether these scores predict stroke outcome more accurately compared with physicians interested in stroke was investigated. Physicians interested in stroke were invited to an online anonymous survey to provide outcome estimates in randomly allocated structured scenarios of recent real-life stroke patients. Their estimates were compared to scores' predictions in the same scenarios. An estimate was considered accurate if it was within 95% confidence intervals of actual outcome. In all, 244 participants from 32 different countries responded assessing 720 real scenarios and 2636 outcomes. The majority of physicians' estimates were inaccurate (1422/2636, 53.9%). 400 (56.8%) of physicians' estimates about the percentage probability of 3-month modified Rankin score (mRS) > 2 were accurate compared with 609 (86.5%) of ASTRAL score estimates (P < 0.0001). 394 (61.2%) of physicians' estimates about the percentage probability of post-thrombolysis symptomatic intracranial haemorrhage were accurate compared with 583 (90.5%) of SEDAN score estimates (P < 0.0001). 160 (24.8%) of physicians' estimates about post-thrombolysis 3-month percentage probability of mRS 0-2 were accurate compared with 240 (37.3%) DRAGON score estimates (P < 0.0001). 260 (40.4%) of physicians' estimates about the percentage probability of post-thrombolysis mRS 5-6 were accurate compared with 518 (80.4%) DRAGON score estimates (P < 0.0001). ASTRAL, DRAGON and SEDAN scores predict outcome of acute ischaemic stroke patients with higher accuracy compared to physicians interested in stroke. © 2016 EAN.

  18. Accurate Theoretical Methane Line Lists in the Infrared up to 3000 K and Quasi-continuum Absorption/Emission Modeling for Astrophysical Applications

    NASA Astrophysics Data System (ADS)

    Rey, Michael; Nikitin, Andrei V.; Tyuterev, Vladimir G.

    2017-10-01

    Modeling atmospheres of hot exoplanets and brown dwarfs requires high-T databases that include methane as the major hydrocarbon. We report a complete theoretical line list of 12CH4 in the infrared range 0-13,400 cm-1 up to T max = 3000 K computed via a full quantum-mechanical method from ab initio potential energy and dipole moment surfaces. Over 150 billion transitions were generated with the lower rovibrational energy cutoff 33,000 cm-1 and intensity cutoff down to 10-33 cm/molecule to ensure convergent opacity predictions. Empirical corrections for 3.7 million of the strongest transitions permitted line position accuracies of 0.001-0.01 cm-1. Full data are partitioned into two sets. “Light lists” contain strong and medium transitions necessary for an accurate description of sharp features in absorption/emission spectra. For a fast and efficient modeling of quasi-continuum cross sections, billions of tiny lines are compressed in “super-line” libraries according to Rey et al. These combined data will be freely accessible via the TheoReTS information system (http://theorets.univ-reims.fr, http://theorets.tsu.ru), which provides a user-friendly interface for simulations of absorption coefficients, cross-sectional transmittance, and radiance. Comparisons with cold, room, and high-T experimental data show that the data reported here represent the first global theoretical methane lists suitable for high-resolution astrophysical applications.

  19. Accurate Theoretical Methane Line Lists in the Infrared up to 3000 K and Quasi-continuum Absorption/Emission Modeling for Astrophysical Applications

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Rey, Michael; Tyuterev, Vladimir G.; Nikitin, Andrei V., E-mail: michael.rey@univ-reims.fr

    Modeling atmospheres of hot exoplanets and brown dwarfs requires high- T databases that include methane as the major hydrocarbon. We report a complete theoretical line list of {sup 12}CH{sub 4} in the infrared range 0–13,400 cm{sup −1} up to T {sub max} = 3000 K computed via a full quantum-mechanical method from ab initio potential energy and dipole moment surfaces. Over 150 billion transitions were generated with the lower rovibrational energy cutoff 33,000 cm{sup −1} and intensity cutoff down to 10{sup −33} cm/molecule to ensure convergent opacity predictions. Empirical corrections for 3.7 million of the strongest transitions permitted line positionmore » accuracies of 0.001–0.01 cm{sup −1}. Full data are partitioned into two sets. “Light lists” contain strong and medium transitions necessary for an accurate description of sharp features in absorption/emission spectra. For a fast and efficient modeling of quasi-continuum cross sections, billions of tiny lines are compressed in “super-line” libraries according to Rey et al. These combined data will be freely accessible via the TheoReTS information system (http://theorets.univ-reims.fr, http://theorets.tsu.ru), which provides a user-friendly interface for simulations of absorption coefficients, cross-sectional transmittance, and radiance. Comparisons with cold, room, and high- T experimental data show that the data reported here represent the first global theoretical methane lists suitable for high-resolution astrophysical applications.« less

  20. Accurate Prediction of Motor Failures by Application of Multi CBM Tools: A Case Study

    NASA Astrophysics Data System (ADS)

    Dutta, Rana; Singh, Veerendra Pratap; Dwivedi, Jai Prakash

    2018-02-01

    Motor failures are very difficult to predict accurately with a single condition-monitoring tool as both electrical and the mechanical systems are closely related. Electrical problem, like phase unbalance, stator winding insulation failures can, at times, lead to vibration problem and at the same time mechanical failures like bearing failure, leads to rotor eccentricity. In this case study of a 550 kW blower motor it has been shown that a rotor bar crack was detected by current signature analysis and vibration monitoring confirmed the same. In later months in a similar motor vibration monitoring predicted bearing failure and current signature analysis confirmed the same. In both the cases, after dismantling the motor, the predictions were found to be accurate. In this paper we will be discussing the accurate predictions of motor failures through use of multi condition monitoring tools with two case studies.

  1. Radiomics biomarkers for accurate tumor progression prediction of oropharyngeal cancer

    NASA Astrophysics Data System (ADS)

    Hadjiiski, Lubomir; Chan, Heang-Ping; Cha, Kenny H.; Srinivasan, Ashok; Wei, Jun; Zhou, Chuan; Prince, Mark; Papagerakis, Silvana

    2017-03-01

    Accurate tumor progression prediction for oropharyngeal cancers is crucial for identifying patients who would best be treated with optimized treatment and therefore minimize the risk of under- or over-treatment. An objective decision support system that can merge the available radiomics, histopathologic and molecular biomarkers in a predictive model based on statistical outcomes of previous cases and machine learning may assist clinicians in making more accurate assessment of oropharyngeal tumor progression. In this study, we evaluated the feasibility of developing individual and combined predictive models based on quantitative image analysis from radiomics, histopathology and molecular biomarkers for oropharyngeal tumor progression prediction. With IRB approval, 31, 84, and 127 patients with head and neck CT (CT-HN), tumor tissue microarrays (TMAs) and molecular biomarker expressions, respectively, were collected. For 8 of the patients all 3 types of biomarkers were available and they were sequestered in a test set. The CT-HN lesions were automatically segmented using our level sets based method. Morphological, texture and molecular based features were extracted from CT-HN and TMA images, and selected features were merged by a neural network. The classification accuracy was quantified using the area under the ROC curve (AUC). Test AUCs of 0.87, 0.74, and 0.71 were obtained with the individual predictive models based on radiomics, histopathologic, and molecular features, respectively. Combining the radiomics and molecular models increased the test AUC to 0.90. Combining all 3 models increased the test AUC further to 0.94. This preliminary study demonstrates that the individual domains of biomarkers are useful and the integrated multi-domain approach is most promising for tumor progression prediction.

  2. SCPRED: accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences.

    PubMed

    Kurgan, Lukasz; Cios, Krzysztof; Chen, Ke

    2008-05-01

    Protein structure prediction methods provide accurate results when a homologous protein is predicted, while poorer predictions are obtained in the absence of homologous templates. However, some protein chains that share twilight-zone pairwise identity can form similar folds and thus determining structural similarity without the sequence similarity would be desirable for the structure prediction. The folding type of a protein or its domain is defined as the structural class. Current structural class prediction methods that predict the four structural classes defined in SCOP provide up to 63% accuracy for the datasets in which sequence identity of any pair of sequences belongs to the twilight-zone. We propose SCPRED method that improves prediction accuracy for sequences that share twilight-zone pairwise similarity with sequences used for the prediction. SCPRED uses a support vector machine classifier that takes several custom-designed features as its input to predict the structural classes. Based on extensive design that considers over 2300 index-, composition- and physicochemical properties-based features along with features based on the predicted secondary structure and content, the classifier's input includes 8 features based on information extracted from the secondary structure predicted with PSI-PRED and one feature computed from the sequence. Tests performed with datasets of 1673 protein chains, in which any pair of sequences shares twilight-zone similarity, show that SCPRED obtains 80.3% accuracy when predicting the four SCOP-defined structural classes, which is superior when compared with over a dozen recent competing methods that are based on support vector machine, logistic regression, and ensemble of classifiers predictors. The SCPRED can accurately find similar structures for sequences that share low identity with sequence used for the prediction. The high predictive accuracy achieved by SCPRED is attributed to the design of the features, which are

  3. SCPRED: Accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences

    PubMed Central

    Kurgan, Lukasz; Cios, Krzysztof; Chen, Ke

    2008-01-01

    Background Protein structure prediction methods provide accurate results when a homologous protein is predicted, while poorer predictions are obtained in the absence of homologous templates. However, some protein chains that share twilight-zone pairwise identity can form similar folds and thus determining structural similarity without the sequence similarity would be desirable for the structure prediction. The folding type of a protein or its domain is defined as the structural class. Current structural class prediction methods that predict the four structural classes defined in SCOP provide up to 63% accuracy for the datasets in which sequence identity of any pair of sequences belongs to the twilight-zone. We propose SCPRED method that improves prediction accuracy for sequences that share twilight-zone pairwise similarity with sequences used for the prediction. Results SCPRED uses a support vector machine classifier that takes several custom-designed features as its input to predict the structural classes. Based on extensive design that considers over 2300 index-, composition- and physicochemical properties-based features along with features based on the predicted secondary structure and content, the classifier's input includes 8 features based on information extracted from the secondary structure predicted with PSI-PRED and one feature computed from the sequence. Tests performed with datasets of 1673 protein chains, in which any pair of sequences shares twilight-zone similarity, show that SCPRED obtains 80.3% accuracy when predicting the four SCOP-defined structural classes, which is superior when compared with over a dozen recent competing methods that are based on support vector machine, logistic regression, and ensemble of classifiers predictors. Conclusion The SCPRED can accurately find similar structures for sequences that share low identity with sequence used for the prediction. The high predictive accuracy achieved by SCPRED is attributed to the design of

  4. Accurate prediction of bacterial type IV secreted effectors using amino acid composition and PSSM profiles.

    PubMed

    Zou, Lingyun; Nan, Chonghan; Hu, Fuquan

    2013-12-15

    Various human pathogens secret effector proteins into hosts cells via the type IV secretion system (T4SS). These proteins play important roles in the interaction between bacteria and hosts. Computational methods for T4SS effector prediction have been developed for screening experimental targets in several isolated bacterial species; however, widely applicable prediction approaches are still unavailable In this work, four types of distinctive features, namely, amino acid composition, dipeptide composition, .position-specific scoring matrix composition and auto covariance transformation of position-specific scoring matrix, were calculated from primary sequences. A classifier, T4EffPred, was developed using the support vector machine with these features and their different combinations for effector prediction. Various theoretical tests were performed in a newly established dataset, and the results were measured with four indexes. We demonstrated that T4EffPred can discriminate IVA and IVB effectors in benchmark datasets with positive rates of 76.7% and 89.7%, respectively. The overall accuracy of 95.9% shows that the present method is accurate for distinguishing the T4SS effector in unidentified sequences. A classifier ensemble was designed to synthesize all single classifiers. Notable performance improvement was observed using this ensemble system in benchmark tests. To demonstrate the model's application, a genome-scale prediction of effectors was performed in Bartonella henselae, an important zoonotic pathogen. A number of putative candidates were distinguished. A web server implementing the prediction method and the source code are both available at http://bioinfo.tmmu.edu.cn/T4EffPred.

  5. Theoretical prediction of nuclear magnetic shieldings and indirect spin-spin coupling constants in 1,1-, cis-, and trans-1,2-difluoroethylenes

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Nozirov, Farhod, E-mail: teobaldk@gmail.com, E-mail: farhod.nozirov@gmail.com; Stachów, Michał, E-mail: michal.stachow@gmail.com; Kupka, Teobald, E-mail: teobaldk@gmail.com, E-mail: farhod.nozirov@gmail.com

    2014-04-14

    A theoretical prediction of nuclear magnetic shieldings and indirect spin-spin coupling constants in 1,1-, cis- and trans-1,2-difluoroethylenes is reported. The results obtained using density functional theory (DFT) combined with large basis sets and gauge-independent atomic orbital calculations were critically compared with experiment and conventional, higher level correlated electronic structure methods. Accurate structural, vibrational, and NMR parameters of difluoroethylenes were obtained using several density functionals combined with dedicated basis sets. B3LYP/6-311++G(3df,2pd) optimized structures of difluoroethylenes closely reproduced experimental geometries and earlier reported benchmark coupled cluster results, while BLYP/6-311++G(3df,2pd) produced accurate harmonic vibrational frequencies. The most accurate vibrations were obtained using B3LYP/6-311++G(3df,2pd)more » with correction for anharmonicity. Becke half and half (BHandH) density functional predicted more accurate {sup 19}F isotropic shieldings and van Voorhis and Scuseria's τ-dependent gradient-corrected correlation functional yielded better carbon shieldings than B3LYP. A surprisingly good performance of Hartree-Fock (HF) method in predicting nuclear shieldings in these molecules was observed. Inclusion of zero-point vibrational correction markedly improved agreement with experiment for nuclear shieldings calculated by HF, MP2, CCSD, and CCSD(T) methods but worsened the DFT results. The threefold improvement in accuracy when predicting {sup 2}J(FF) in 1,1-difluoroethylene for BHandH density functional compared to B3LYP was observed (the deviations from experiment were −46 vs. −115 Hz)« less

  6. New analytical model for the ozone electronic ground state potential surface and accurate ab initio vibrational predictions at high energy range.

    PubMed

    Tyuterev, Vladimir G; Kochanov, Roman V; Tashkun, Sergey A; Holka, Filip; Szalay, Péter G

    2013-10-07

    An accurate description of the complicated shape of the potential energy surface (PES) and that of the highly excited vibration states is of crucial importance for various unsolved issues in the spectroscopy and dynamics of ozone and remains a challenge for the theory. In this work a new analytical representation is proposed for the PES of the ground electronic state of the ozone molecule in the range covering the main potential well and the transition state towards the dissociation. This model accounts for particular features specific to the ozone PES for large variations of nuclear displacements along the minimum energy path. The impact of the shape of the PES near the transition state (existence of the "reef structure") on vibration energy levels was studied for the first time. The major purpose of this work was to provide accurate theoretical predictions for ozone vibrational band centres at the energy range near the dissociation threshold, which would be helpful for understanding the very complicated high-resolution spectra and its analyses currently in progress. Extended ab initio electronic structure calculations were carried out enabling the determination of the parameters of a minimum energy path PES model resulting in a new set of theoretical vibrational levels of ozone. A comparison with recent high-resolution spectroscopic data on the vibrational levels gives the root-mean-square deviations below 1 cm(-1) for ozone band centres up to 90% of the dissociation energy. New ab initio vibrational predictions represent a significant improvement with respect to all previously available calculations.

  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. Confirmation of theoretical colour predictions for layering dental composite materials.

    PubMed

    Mikhail, Sarah S; Johnston, William M

    2014-04-01

    The aim of this study is to confirm the theoretical colour predictions for single and double layers of dental composite materials on an opaque backing. Single and double layers of composite resins were fabricated, placed in optical contact with a grey backing and measured for spectral radiance. The spectral reflectance and colour were directly determined. Absorption and scattering coefficients as previously reported, the measured thickness of the single layers and the effective reflectance of the grey backing were utilized to theoretically predict the reflectance of the single layer using corrected Kubelka-Munk reflectance theory. For double layers the predicted effective reflectance of the single layer was used as the reflectance of the backing of the second layer and the thickness of the second layer was used to predict the reflectance of the double layer. Colour differences, using both the CIELAB and CIEDE2000 formulae, measured the discrepancy between each directly determined colour and its corresponding theoretical colour. The colour difference discrepancies generally ranged around the perceptibility threshold but were consistently below the respective acceptability threshold. This theory can predict the colour of layers of composite resin within acceptability limits and generally also within perceptibility limits. This theory could therefore be incorporated into computer-based optical measuring instruments that can automate the shade selections for layers of a more opaque first layer under a more translucent second layer for those clinical situations where an underlying background colour and a desirable final colour can be measured. Copyright © 2014 Elsevier Ltd. All rights reserved.

  9. Heart rate during basketball game play and volleyball drills accurately predicts oxygen uptake and energy expenditure.

    PubMed

    Scribbans, T D; Berg, K; Narazaki, K; Janssen, I; Gurd, B J

    2015-09-01

    There is currently little information regarding the ability of metabolic prediction equations to accurately predict oxygen uptake and exercise intensity from heart rate (HR) during intermittent sport. The purpose of the present study was to develop and, cross-validate equations appropriate for accurately predicting oxygen cost (VO2) and energy expenditure from HR during intermittent sport participation. Eleven healthy adult males (19.9±1.1yrs) were recruited to establish the relationship between %VO2peak and %HRmax during low-intensity steady state endurance (END), moderate-intensity interval (MOD) and high intensity-interval exercise (HI), as performed on a cycle ergometer. Three equations (END, MOD, and HI) for predicting %VO2peak based on %HRmax were developed. HR and VO2 were directly measured during basketball games (6 male, 20.8±1.0 yrs; 6 female, 20.0±1.3yrs) and volleyball drills (12 female; 20.8±1.0yrs). Comparisons were made between measured and predicted VO2 and energy expenditure using the 3 equations developed and 2 previously published equations. The END and MOD equations accurately predicted VO2 and energy expenditure, while the HI equation underestimated, and the previously published equations systematically overestimated VO2 and energy expenditure. Intermittent sport VO2 and energy expenditure can be accurately predicted from heart rate data using either the END (%VO2peak=%HRmax x 1.008-17.17) or MOD (%VO2peak=%HRmax x 1.2-32) equations. These 2 simple equations provide an accessible and cost-effective method for accurate estimation of exercise intensity and energy expenditure during intermittent sport.

  10. Aircraft noise prediction program theoretical manual: Rotorcraft System Noise Prediction System (ROTONET), part 4

    NASA Technical Reports Server (NTRS)

    Weir, Donald S.; Jumper, Stephen J.; Burley, Casey L.; Golub, Robert A.

    1995-01-01

    This document describes the theoretical methods used in the rotorcraft noise prediction system (ROTONET), which is a part of the NASA Aircraft Noise Prediction Program (ANOPP). The ANOPP code consists of an executive, database manager, and prediction modules for jet engine, propeller, and rotor noise. The ROTONET subsystem contains modules for the prediction of rotor airloads and performance with momentum theory and prescribed wake aerodynamics, rotor tone noise with compact chordwise and full-surface solutions to the Ffowcs-Williams-Hawkings equations, semiempirical airfoil broadband noise, and turbulence ingestion broadband noise. Flight dynamics, atmosphere propagation, and noise metric calculations are covered in NASA TM-83199, Parts 1, 2, and 3.

  11. 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

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

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

    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, andmore » 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.« less

  13. Accurate prediction of energy expenditure using a shoe-based activity monitor.

    PubMed

    Sazonova, Nadezhda; Browning, Raymond C; Sazonov, Edward

    2011-07-01

    The aim of this study was to develop and validate a method for predicting energy expenditure (EE) using a footwear-based system with integrated accelerometer and pressure sensors. We developed a footwear-based device with an embedded accelerometer and insole pressure sensors for the prediction of EE. The data from the device can be used to perform accurate recognition of major postures and activities and to estimate EE using the acceleration, pressure, and posture/activity classification information in a branched algorithm without the need for individual calibration. We measured EE via indirect calorimetry as 16 adults (body mass index=19-39 kg·m) performed various low- to moderate-intensity activities and compared measured versus predicted EE using several models based on the acceleration and pressure signals. Inclusion of pressure data resulted in better accuracy of EE prediction during static postures such as sitting and standing. The activity-based branched model that included predictors from accelerometer and pressure sensors (BACC-PS) achieved the lowest error (e.g., root mean squared error (RMSE)=0.69 METs) compared with the accelerometer-only-based branched model BACC (RMSE=0.77 METs) and nonbranched model (RMSE=0.94-0.99 METs). Comparison of EE prediction models using data from both legs versus models using data from a single leg indicates that only one shoe needs to be equipped with sensors. These results suggest that foot acceleration combined with insole pressure measurement, when used in an activity-specific branched model, can accurately estimate the EE associated with common daily postures and activities. The accuracy and unobtrusiveness of a footwear-based device may make it an effective physical activity monitoring tool.

  14. Are EMS call volume predictions based on demand pattern analysis accurate?

    PubMed

    Brown, Lawrence H; Lerner, E Brooke; Larmon, Baxter; LeGassick, Todd; Taigman, Michael

    2007-01-01

    Most EMS systems determine the number of crews they will deploy in their communities and when those crews will be scheduled based on anticipated call volumes. Many systems use historical data to calculate their anticipated call volumes, a method of prediction known as demand pattern analysis. To evaluate the accuracy of call volume predictions calculated using demand pattern analysis. Seven EMS systems provided 73 consecutive weeks of hourly call volume data. The first 20 weeks of data were used to calculate three common demand pattern analysis constructs for call volume prediction: average peak demand (AP), smoothed average peak demand (SAP), and 90th percentile rank (90%R). The 21st week served as a buffer. Actual call volumes in the last 52 weeks were then compared to the predicted call volumes by using descriptive statistics. There were 61,152 hourly observations in the test period. All three constructs accurately predicted peaks and troughs in call volume but not exact call volume. Predictions were accurate (+/-1 call) 13% of the time using AP, 10% using SAP, and 19% using 90%R. Call volumes were overestimated 83% of the time using AP, 86% using SAP, and 74% using 90%R. When call volumes were overestimated, predictions exceeded actual call volume by a median (Interquartile range) of 4 (2-6) calls for AP, 4 (2-6) for SAP, and 3 (2-5) for 90%R. Call volumes were underestimated 4% of time using AP, 4% using SAP, and 7% using 90%R predictions. When call volumes were underestimated, call volumes exceeded predictions by a median (Interquartile range; maximum under estimation) of 1 (1-2; 18) call for AP, 1 (1-2; 18) for SAP, and 2 (1-3; 20) for 90%R. Results did not vary between systems. Generally, demand pattern analysis estimated or overestimated call volume, making it a reasonable predictor for ambulance staffing patterns. However, it did underestimate call volume between 4% and 7% of the time. Communities need to determine if these rates of over

  15. Rapid and accurate prediction and scoring of water molecules in protein binding sites.

    PubMed

    Ross, Gregory A; Morris, Garrett M; Biggin, Philip C

    2012-01-01

    Water plays a critical role in ligand-protein interactions. However, it is still challenging to predict accurately not only where water molecules prefer to bind, but also which of those water molecules might be displaceable. The latter is often seen as a route to optimizing affinity of potential drug candidates. Using a protocol we call WaterDock, we show that the freely available AutoDock Vina tool can be used to predict accurately the binding sites of water molecules. WaterDock was validated using data from X-ray crystallography, neutron diffraction and molecular dynamics simulations and correctly predicted 97% of the water molecules in the test set. In addition, we combined data-mining, heuristic and machine learning techniques to develop probabilistic water molecule classifiers. When applied to WaterDock predictions in the Astex Diverse Set of protein ligand complexes, we could identify whether a water molecule was conserved or displaced to an accuracy of 75%. A second model predicted whether water molecules were displaced by polar groups or by non-polar groups to an accuracy of 80%. These results should prove useful for anyone wishing to undertake rational design of new compounds where the displacement of water molecules is being considered as a route to improved affinity.

  16. Accurate thermoelastic tensor and acoustic velocities of NaCl

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Marcondes, Michel L., E-mail: michel@if.usp.br; Chemical Engineering and Material Science, University of Minnesota, Minneapolis, 55455; Shukla, Gaurav, E-mail: shukla@physics.umn.edu

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

  17. Prediction and theoretical characterization of p-type organic semiconductor crystals for field-effect transistor applications.

    PubMed

    Atahan-Evrenk, Sule; Aspuru-Guzik, Alán

    2014-01-01

    The theoretical prediction and characterization of the solid-state structure of organic semiconductors has tremendous potential for the discovery of new high performance materials. To date, the theoretical analysis mostly relied on the availability of crystal structures obtained through X-ray diffraction. However, the theoretical prediction of the crystal structures of organic semiconductor molecules remains a challenge. This review highlights some of the recent advances in the determination of structure-property relationships of the known organic semiconductor single-crystals and summarizes a few available studies on the prediction of the crystal structures of p-type organic semiconductors for transistor applications.

  18. Multi-fidelity machine learning models for accurate bandgap predictions of solids

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Pilania, Ghanshyam; Gubernatis, James E.; Lookman, Turab

    Here, we present a multi-fidelity co-kriging statistical learning framework that combines variable-fidelity quantum mechanical calculations of bandgaps to generate a machine-learned model that enables low-cost accurate predictions of the bandgaps at the highest fidelity level. Additionally, the adopted Gaussian process regression formulation allows us to predict the underlying uncertainties as a measure of our confidence in the predictions. In using a set of 600 elpasolite compounds as an example dataset and using semi-local and hybrid exchange correlation functionals within density functional theory as two levels of fidelities, we demonstrate the excellent learning performance of the method against actual high fidelitymore » quantum mechanical calculations of the bandgaps. The presented statistical learning method is not restricted to bandgaps or electronic structure methods and extends the utility of high throughput property predictions in a significant way.« less

  19. Multi-fidelity machine learning models for accurate bandgap predictions of solids

    DOE PAGES

    Pilania, Ghanshyam; Gubernatis, James E.; Lookman, Turab

    2016-12-28

    Here, we present a multi-fidelity co-kriging statistical learning framework that combines variable-fidelity quantum mechanical calculations of bandgaps to generate a machine-learned model that enables low-cost accurate predictions of the bandgaps at the highest fidelity level. Additionally, the adopted Gaussian process regression formulation allows us to predict the underlying uncertainties as a measure of our confidence in the predictions. In using a set of 600 elpasolite compounds as an example dataset and using semi-local and hybrid exchange correlation functionals within density functional theory as two levels of fidelities, we demonstrate the excellent learning performance of the method against actual high fidelitymore » quantum mechanical calculations of the bandgaps. The presented statistical learning method is not restricted to bandgaps or electronic structure methods and extends the utility of high throughput property predictions in a significant way.« less

  20. Measuring the value of accurate link prediction for network seeding.

    PubMed

    Wei, Yijin; Spencer, Gwen

    2017-01-01

    The influence-maximization literature seeks small sets of individuals whose structural placement in the social network can drive large cascades of behavior. Optimization efforts to find the best seed set often assume perfect knowledge of the network topology. Unfortunately, social network links are rarely known in an exact way. When do seeding strategies based on less-than-accurate link prediction provide valuable insight? We introduce optimized-against-a-sample ([Formula: see text]) performance to measure the value of optimizing seeding based on a noisy observation of a network. Our computational study investigates [Formula: see text] under several threshold-spread models in synthetic and real-world networks. Our focus is on measuring the value of imprecise link information. The level of investment in link prediction that is strategic appears to depend closely on spread model: in some parameter ranges investments in improving link prediction can pay substantial premiums in cascade size. For other ranges, such investments would be wasted. Several trends were remarkably consistent across topologies.

  1. Accurate prediction of secondary metabolite gene clusters in filamentous fungi.

    PubMed

    Andersen, Mikael R; Nielsen, Jakob B; Klitgaard, Andreas; Petersen, Lene M; Zachariasen, Mia; Hansen, Tilde J; Blicher, Lene H; Gotfredsen, Charlotte H; Larsen, Thomas O; Nielsen, Kristian F; Mortensen, Uffe H

    2013-01-02

    Biosynthetic pathways of secondary metabolites from fungi are currently subject to an intense effort to elucidate the genetic basis for these compounds due to their large potential within pharmaceutics and synthetic biochemistry. The preferred method is methodical gene deletions to identify supporting enzymes for key synthases one cluster at a time. In this study, we design and apply a DNA expression array for Aspergillus nidulans in combination with legacy data to form a comprehensive gene expression compendium. We apply a guilt-by-association-based analysis to predict the extent of the biosynthetic clusters for the 58 synthases active in our set of experimental conditions. A comparison with legacy data shows the method to be accurate in 13 of 16 known clusters and nearly accurate for the remaining 3 clusters. Furthermore, we apply a data clustering approach, which identifies cross-chemistry between physically separate gene clusters (superclusters), and validate this both with legacy data and experimentally by prediction and verification of a supercluster consisting of the synthase AN1242 and the prenyltransferase AN11080, as well as identification of the product compound nidulanin A. We have used A. nidulans for our method development and validation due to the wealth of available biochemical data, but the method can be applied to any fungus with a sequenced and assembled genome, thus supporting further secondary metabolite pathway elucidation in the fungal kingdom.

  2. Simple prediction scores predict good and devastating outcomes after stroke more accurately than physicians.

    PubMed

    Reid, John Michael; Dai, Dingwei; Delmonte, Susanna; Counsell, Carl; Phillips, Stephen J; MacLeod, Mary Joan

    2017-05-01

    physicians are often asked to prognosticate soon after a patient presents with stroke. This study aimed to compare two outcome prediction scores (Five Simple Variables [FSV] score and the PLAN [Preadmission comorbidities, Level of consciousness, Age, and focal Neurologic deficit]) with informal prediction by physicians. demographic and clinical variables were prospectively collected from consecutive patients hospitalised with acute ischaemic or haemorrhagic stroke (2012-13). In-person or telephone follow-up at 6 months established vital and functional status (modified Rankin score [mRS]). Area under the receiver operating curves (AUC) was used to establish prediction score performance. five hundred and seventy-five patients were included; 46% female, median age 76 years, 88% ischaemic stroke. Six months after stroke, 47% of patients had a good outcome (alive and independent, mRS 0-2) and 26% a devastating outcome (dead or severely dependent, mRS 5-6). The FSV and PLAN scores were superior to physician prediction (AUCs of 0.823-0.863 versus 0.773-0.805, P < 0.0001) for good and devastating outcomes. The FSV score was superior to the PLAN score for predicting good outcomes and vice versa for devastating outcomes (P < 0.001). Outcome prediction was more accurate for those with later presentations (>24 hours from onset). the FSV and PLAN scores are validated in this population for outcome prediction after both ischaemic and haemorrhagic stroke. The FSV score is the least complex of all developed scores and can assist outcome prediction by physicians. © The Author 2016. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For permissions, please email: journals.permissions@oup.com

  3. Accurate Prediction of Contact Numbers for Multi-Spanning Helical Membrane Proteins

    PubMed Central

    Li, Bian; Mendenhall, Jeffrey; Nguyen, Elizabeth Dong; Weiner, Brian E.; Fischer, Axel W.; Meiler, Jens

    2017-01-01

    Prediction of the three-dimensional (3D) structures of proteins by computational methods is acknowledged as an unsolved problem. Accurate prediction of important structural characteristics such as contact number is expected to accelerate the otherwise slow progress being made in the prediction of 3D structure of proteins. Here, we present a dropout neural network-based method, TMH-Expo, for predicting the contact number of transmembrane helix (TMH) residues from sequence. Neuronal dropout is a strategy where certain neurons of the network are excluded from back-propagation to prevent co-adaptation of hidden-layer neurons. By using neuronal dropout, overfitting was significantly reduced and performance was noticeably improved. For multi-spanning helical membrane proteins, TMH-Expo achieved a remarkable Pearson correlation coefficient of 0.69 between predicted and experimental values and a mean absolute error of only 1.68. In addition, among those membrane protein–membrane protein interface residues, 76.8% were correctly predicted. Mapping of predicted contact numbers onto structures indicates that contact numbers predicted by TMH-Expo reflect the exposure patterns of TMHs and reveal membrane protein–membrane protein interfaces, reinforcing the potential of predicted contact numbers to be used as restraints for 3D structure prediction and protein–protein docking. TMH-Expo can be accessed via a Web server at www.meilerlab.org. PMID:26804342

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

    DOE PAGES

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

    2013-03-07

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

  5. Accurate line intensities of methane from first-principles calculations

    NASA Astrophysics Data System (ADS)

    Nikitin, Andrei V.; Rey, Michael; Tyuterev, Vladimir G.

    2017-10-01

    In this work, we report first-principle theoretical predictions of methane spectral line intensities that are competitive with (and complementary to) the best laboratory measurements. A detailed comparison with the most accurate data shows that discrepancies in integrated polyad intensities are in the range of 0.4%-2.3%. This corresponds to estimations of the best available accuracy in laboratory Fourier Transform spectra measurements for this quantity. For relatively isolated strong lines the individual intensity deviations are in the same range. A comparison with the most precise laser measurements of the multiplet intensities in the 2ν3 band gives an agreement within the experimental error margins (about 1%). This is achieved for the first time for five-atomic molecules. In the Supplementary Material we provide the lists of theoretical intensities at 269 K for over 5000 strongest transitions in the range below 6166 cm-1. The advantage of the described method is that this offers a possibility to generate fully assigned exhaustive line lists at various temperature conditions. Extensive calculations up to 12,000 cm-1 including high-T predictions will be made freely available through the TheoReTS information system (http://theorets.univ-reims.fr, http://theorets.tsu.ru) that contains ab initio born line lists and provides a user-friendly graphical interface for a fast simulation of the absorption cross-sections and radiance.

  6. Sediment sorting along tidal sand waves: A comparison between field observations and theoretical predictions

    NASA Astrophysics Data System (ADS)

    Van Oyen, Tomas; Blondeaux, Paolo; Van den Eynde, Dries

    2013-07-01

    A site-by-site comparison between field observations and theoretical predictions of sediment sorting patterns along tidal sand waves is performed for ten locations in the North Sea. At each site, the observed grain size distribution along the bottom topography and the geometry of the bed forms is described in detail and the procedure used to obtain the model parameters is summarized. The model appears to accurately describe the wavelength of the observed sand waves for the majority of the locations; still providing a reliable estimate for the other sites. In addition, it is found that for seven out of the ten locations, the qualitative sorting process provided by the model agrees with the observed grain size distribution. A discussion of the site-by-site comparison is provided which, taking into account uncertainties in the field data, indicates that the model grasps the major part of the key processes controlling the phenomenon.

  7. An accurate model for predicting high frequency noise of nanoscale NMOS SOI transistors

    NASA Astrophysics Data System (ADS)

    Shen, Yanfei; Cui, Jie; Mohammadi, Saeed

    2017-05-01

    A nonlinear and scalable model suitable for predicting high frequency noise of N-type Metal Oxide Semiconductor (NMOS) transistors is presented. The model is developed for a commercial 45 nm CMOS SOI technology and its accuracy is validated through comparison with measured performance of a microwave low noise amplifier. The model employs the virtual source nonlinear core and adds parasitic elements to accurately simulate the RF behavior of multi-finger NMOS transistors up to 40 GHz. For the first time, the traditional long-channel thermal noise model is supplemented with an injection noise model to accurately represent the noise behavior of these short-channel transistors up to 26 GHz. The developed model is simple and easy to extract, yet very accurate.

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

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

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

  9. The prediction of candidate genes for cervix related cancer through gene ontology and graph theoretical approach.

    PubMed

    Hindumathi, V; Kranthi, T; Rao, S B; Manimaran, P

    2014-06-01

    With rapidly changing technology, prediction of candidate genes has become an indispensable task in recent years mainly in the field of biological research. The empirical methods for candidate gene prioritization that succors to explore the potential pathway between genetic determinants and complex diseases are highly cumbersome and labor intensive. In such a scenario predicting potential targets for a disease state through in silico approaches are of researcher's interest. The prodigious availability of protein interaction data coupled with gene annotation renders an ease in the accurate determination of disease specific candidate genes. In our work we have prioritized the cervix related cancer candidate genes by employing Csaba Ortutay and his co-workers approach of identifying the candidate genes through graph theoretical centrality measures and gene ontology. With the advantage of the human protein interaction data, cervical cancer gene sets and the ontological terms, we were able to predict 15 novel candidates for cervical carcinogenesis. The disease relevance of the anticipated candidate genes was corroborated through a literature survey. Also the presence of the drugs for these candidates was detected through Therapeutic Target Database (TTD) and DrugMap Central (DMC) which affirms that they may be endowed as potential drug targets for cervical cancer.

  10. Competitive Abilities in Experimental Microcosms Are Accurately Predicted by a Demographic Index for R*

    PubMed Central

    Murrell, Ebony G.; Juliano, Steven A.

    2012-01-01

    Resource competition theory predicts that R*, the equilibrium resource amount yielding zero growth of a consumer population, should predict species' competitive abilities for that resource. This concept has been supported for unicellular organisms, but has not been well-tested for metazoans, probably due to the difficulty of raising experimental populations to equilibrium and measuring population growth rates for species with long or complex life cycles. We developed an index (Rindex) of R* based on demography of one insect cohort, growing from egg to adult in a non-equilibrium setting, and tested whether Rindex yielded accurate predictions of competitive abilities using mosquitoes as a model system. We estimated finite rate of increase (λ′) from demographic data for cohorts of three mosquito species raised with different detritus amounts, and estimated each species' Rindex using nonlinear regressions of λ′ vs. initial detritus amount. All three species' Rindex differed significantly, and accurately predicted competitive hierarchy of the species determined in simultaneous pairwise competition experiments. Our Rindex could provide estimates and rigorous statistical comparisons of competitive ability for organisms for which typical chemostat methods and equilibrium population conditions are impractical. PMID:22970128

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

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

    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

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

    DOE PAGES

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

    2015-05-15

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

  13. XenoSite: accurately predicting CYP-mediated sites of metabolism with neural networks.

    PubMed

    Zaretzki, Jed; Matlock, Matthew; Swamidass, S Joshua

    2013-12-23

    Understanding how xenobiotic molecules are metabolized is important because it influences the safety, efficacy, and dose of medicines and how they can be modified to improve these properties. The cytochrome P450s (CYPs) are proteins responsible for metabolizing 90% of drugs on the market, and many computational methods can predict which atomic sites of a molecule--sites of metabolism (SOMs)--are modified during CYP-mediated metabolism. This study improves on prior methods of predicting CYP-mediated SOMs by using new descriptors and machine learning based on neural networks. The new method, XenoSite, is faster to train and more accurate by as much as 4% or 5% for some isozymes. Furthermore, some "incorrect" predictions made by XenoSite were subsequently validated as correct predictions by revaluation of the source literature. Moreover, XenoSite output is interpretable as a probability, which reflects both the confidence of the model that a particular atom is metabolized and the statistical likelihood that its prediction for that atom is correct.

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

    NASA Technical Reports Server (NTRS)

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

    1986-01-01

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

  15. A Theoretical Model to Predict Both Horizontal Displacement and Vertical Displacement for Electromagnetic Induction-Based Deep Displacement Sensors

    PubMed Central

    Shentu, Nanying; Zhang, Hongjian; Li, Qing; Zhou, Hongliang; Tong, Renyuan; Li, Xiong

    2012-01-01

    Deep displacement observation is one basic means of landslide dynamic study and early warning monitoring and a key part of engineering geological investigation. In our previous work, we proposed a novel electromagnetic induction-based deep displacement sensor (I-type) to predict deep horizontal displacement and a theoretical model called equation-based equivalent loop approach (EELA) to describe its sensing characters. However in many landslide and related geological engineering cases, both horizontal displacement and vertical displacement vary apparently and dynamically so both may require monitoring. In this study, a II-type deep displacement sensor is designed by revising our I-type sensor to simultaneously monitor the deep horizontal displacement and vertical displacement variations at different depths within a sliding mass. Meanwhile, a new theoretical modeling called the numerical integration-based equivalent loop approach (NIELA) has been proposed to quantitatively depict II-type sensors’ mutual inductance properties with respect to predicted horizontal displacements and vertical displacements. After detailed examinations and comparative studies between measured mutual inductance voltage, NIELA-based mutual inductance and EELA-based mutual inductance, NIELA has verified to be an effective and quite accurate analytic model for characterization of II-type sensors. The NIELA model is widely applicable for II-type sensors’ monitoring on all kinds of landslides and other related geohazards with satisfactory estimation accuracy and calculation efficiency. PMID:22368467

  16. A theoretical model to predict both horizontal displacement and vertical displacement for electromagnetic induction-based deep displacement sensors.

    PubMed

    Shentu, Nanying; Zhang, Hongjian; Li, Qing; Zhou, Hongliang; Tong, Renyuan; Li, Xiong

    2012-01-01

    Deep displacement observation is one basic means of landslide dynamic study and early warning monitoring and a key part of engineering geological investigation. In our previous work, we proposed a novel electromagnetic induction-based deep displacement sensor (I-type) to predict deep horizontal displacement and a theoretical model called equation-based equivalent loop approach (EELA) to describe its sensing characters. However in many landslide and related geological engineering cases, both horizontal displacement and vertical displacement vary apparently and dynamically so both may require monitoring. In this study, a II-type deep displacement sensor is designed by revising our I-type sensor to simultaneously monitor the deep horizontal displacement and vertical displacement variations at different depths within a sliding mass. Meanwhile, a new theoretical modeling called the numerical integration-based equivalent loop approach (NIELA) has been proposed to quantitatively depict II-type sensors' mutual inductance properties with respect to predicted horizontal displacements and vertical displacements. After detailed examinations and comparative studies between measured mutual inductance voltage, NIELA-based mutual inductance and EELA-based mutual inductance, NIELA has verified to be an effective and quite accurate analytic model for characterization of II-type sensors. The NIELA model is widely applicable for II-type sensors' monitoring on all kinds of landslides and other related geohazards with satisfactory estimation accuracy and calculation efficiency.

  17. Accurate prediction of personalized olfactory perception from large-scale chemoinformatic features.

    PubMed

    Li, Hongyang; Panwar, Bharat; Omenn, Gilbert S; Guan, Yuanfang

    2018-02-01

    The olfactory stimulus-percept problem has been studied for more than a century, yet it is still hard to precisely predict the odor given the large-scale chemoinformatic features of an odorant molecule. A major challenge is that the perceived qualities vary greatly among individuals due to different genetic and cultural backgrounds. Moreover, the combinatorial interactions between multiple odorant receptors and diverse molecules significantly complicate the olfaction prediction. Many attempts have been made to establish structure-odor relationships for intensity and pleasantness, but no models are available to predict the personalized multi-odor attributes of molecules. In this study, we describe our winning algorithm for predicting individual and population perceptual responses to various odorants in the DREAM Olfaction Prediction Challenge. We find that random forest model consisting of multiple decision trees is well suited to this prediction problem, given the large feature spaces and high variability of perceptual ratings among individuals. Integrating both population and individual perceptions into our model effectively reduces the influence of noise and outliers. By analyzing the importance of each chemical feature, we find that a small set of low- and nondegenerative features is sufficient for accurate prediction. Our random forest model successfully predicts personalized odor attributes of structurally diverse molecules. This model together with the top discriminative features has the potential to extend our understanding of olfactory perception mechanisms and provide an alternative for rational odorant design.

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

    PubMed

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

    2017-04-01

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

  19. Ensemble predictive model for more accurate soil organic carbon spectroscopic estimation

    NASA Astrophysics Data System (ADS)

    Vašát, Radim; Kodešová, Radka; Borůvka, Luboš

    2017-07-01

    A myriad of signal pre-processing strategies and multivariate calibration techniques has been explored in attempt to improve the spectroscopic prediction of soil organic carbon (SOC) over the last few decades. Therefore, to come up with a novel, more powerful, and accurate predictive approach to beat the rank becomes a challenging task. However, there may be a way, so that combine several individual predictions into a single final one (according to ensemble learning theory). As this approach performs best when combining in nature different predictive algorithms that are calibrated with structurally different predictor variables, we tested predictors of two different kinds: 1) reflectance values (or transforms) at each wavelength and 2) absorption feature parameters. Consequently we applied four different calibration techniques, two per each type of predictors: a) partial least squares regression and support vector machines for type 1, and b) multiple linear regression and random forest for type 2. The weights to be assigned to individual predictions within the ensemble model (constructed as a weighted average) were determined by an automated procedure that ensured the best solution among all possible was selected. The approach was tested at soil samples taken from surface horizon of four sites differing in the prevailing soil units. By employing the ensemble predictive model the prediction accuracy of SOC improved at all four sites. The coefficient of determination in cross-validation (R2cv) increased from 0.849, 0.611, 0.811 and 0.644 (the best individual predictions) to 0.864, 0.650, 0.824 and 0.698 for Site 1, 2, 3 and 4, respectively. Generally, the ensemble model affected the final prediction so that the maximal deviations of predicted vs. observed values of the individual predictions were reduced, and thus the correlation cloud became thinner as desired.

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

    NASA Astrophysics Data System (ADS)

    Blacknell, David

    2003-09-01

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

  1. Towards First Principles-Based Prediction of Highly Accurate Electrochemical Pourbaix Diagrams

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Zeng, Zhenhua; Chan, Maria K. Y.; Zhao, Zhi-Jian

    2015-08-13

    Electrochemical potential/pH (Pourbaix) diagrams underpin many 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 diagrams, inherent errors in the description of transition metal (hydroxy)oxides, together with neglect of van der Waals interactions, have limited the reliability of such predictions for even the simplest pure metal bulk compounds, and corresponding predictions for more complex alloy or surface structures are even more challenging. In the present work, through synergistic use of a Hubbard U correction,more » a state-of-the-art dispersion correction, and a water-based bulk reference state for the calculations, these errors are systematically corrected. The approach describes the weak binding that occurs between hydroxyl-containing functional groups in certain compounds in Pourbaix diagrams, corrects for self-interaction errors in transition metal compounds, and reduces residual errors on oxygen atoms by preserving a consistent oxidation state between the reference state, water, and the relevant bulk phases. The strong performance is illustrated on a series of bulk transition metal (Mn, Fe, Co and Ni) hydroxides, oxyhydroxides, binary, and ternary oxides, where the corresponding thermodynamics of redox and (de)hydration are described with standard errors of 0.04 eV per (reaction) formula unit. The approach further preserves accurate descriptions of the overall thermodynamics of electrochemically-relevant bulk reactions, such as water formation, which is an essential condition for facilitating accurate analysis of reaction energies for electrochemical processes on surfaces. The overall generality and transferability of the scheme suggests that it may find useful application in the construction of a broad array of electrochemical phase diagrams, including

  2. 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 (c) 2016 APA, all rights reserved).

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

    PubMed Central

    Doré, B.P.; Meksin, R.; Mather, M.; Hirst, W.; Ochsner, K.N

    2016-01-01

    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 1) the overall intensity of their future negative emotion, and 2) 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. PMID:27100309

  4. 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.

  5. Uncertainties of predictions from parton distributions II: theoretical errors

    NASA Astrophysics Data System (ADS)

    Martin, A. D.; Roberts, R. G.; Stirling, W. J.; Thorne, R. S.

    2004-06-01

    We study the uncertainties in parton distributions, determined in global fits to deep inelastic and related hard scattering data, due to so-called theoretical errors. Amongst these, we include potential errors due to the change of perturbative order (NLO to NNLO), ln(1/x) and ln(1-x) effects, absorptive corrections and higher-twist contributions. We investigate these uncertainties both by including explicit corrections to our standard global analysis and by examining the sensitivity to changes of the x, Q 2, W 2 cuts on the data that are fitted. In this way we expose those kinematic regions where the conventional DGLAP description is inadequate. As a consequence we obtain a set of NLO, and of NNLO, conservative partons where the data are fully consistent with DGLAP evolution, but over a restricted kinematic domain. We also examine the potential effects of such issues as the choice of input parametrisation, heavy target corrections, assumptions about the strange quark sea and isospin violation. Hence we are able to compare the theoretical errors with those uncertainties due to errors on the experimental measurements, which we studied previously. We use W and Higgs boson production at the Tevatron and the LHC as explicit examples of the uncertainties arising from parton distributions. For many observables the theoretical error is dominant, but for the cross section for W production at the Tevatron both the theoretical and experimental uncertainties are small, and hence the NNLO prediction may serve as a valuable luminosity monitor.

  6. Accurate high-throughput structure mapping and prediction with transition metal ion FRET

    PubMed Central

    Yu, Xiaozhen; Wu, Xiongwu; Bermejo, Guillermo A.; Brooks, Bernard R.; Taraska, Justin W.

    2013-01-01

    Mapping the landscape of a protein’s conformational space is essential to understanding its functions and regulation. The limitations of many structural methods have made this process challenging for most proteins. Here, we report that transition metal ion FRET (tmFRET) can be used in a rapid, highly parallel screen, to determine distances from multiple locations within a protein at extremely low concentrations. The distances generated through this screen for the protein Maltose Binding Protein (MBP) match distances from the crystal structure to within a few angstroms. Furthermore, energy transfer accurately detects structural changes during ligand binding. Finally, fluorescence-derived distances can be used to guide molecular simulations to find low energy states. Our results open the door to rapid, accurate mapping and prediction of protein structures at low concentrations, in large complex systems, and in living cells. PMID:23273426

  7. Accurate approximation method for prediction of class I MHC affinities for peptides of length 8, 10 and 11 using prediction tools trained on 9mers.

    PubMed

    Lundegaard, Claus; Lund, Ole; Nielsen, Morten

    2008-06-01

    Several accurate prediction systems have been developed for prediction of class I major histocompatibility complex (MHC):peptide binding. Most of these are trained on binding affinity data of primarily 9mer peptides. Here, we show how prediction methods trained on 9mer data can be used for accurate binding affinity prediction of peptides of length 8, 10 and 11. The method gives the opportunity to predict peptides with a different length than nine for MHC alleles where no such peptides have been measured. As validation, the performance of this approach is compared to predictors trained on peptides of the peptide length in question. In this validation, the approximation method has an accuracy that is comparable to or better than methods trained on a peptide length identical to the predicted peptides. The algorithm has been implemented in the web-accessible servers NetMHC-3.0: http://www.cbs.dtu.dk/services/NetMHC-3.0, and NetMHCpan-1.1: http://www.cbs.dtu.dk/services/NetMHCpan-1.1

  8. Predicting Child Abuse Potential: An Empirical Investigation of Two Theoretical Frameworks

    ERIC Educational Resources Information Center

    Begle, Angela Moreland; Dumas, Jean E.; Hanson, Rochelle F.

    2010-01-01

    This study investigated two theoretical risk models predicting child maltreatment potential: (a) Belsky's (1993) developmental-ecological model and (b) the cumulative risk model in a sample of 610 caregivers (49% African American, 46% European American; 53% single) with a child between 3 and 6 years old. Results extend the literature by using a…

  9. 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. © 2016 John Wiley & Sons Ltd.

  10. How accurate is our clinical prediction of "minimal prostate cancer"?

    PubMed

    Leibovici, Dan; Shikanov, Sergey; Gofrit, Ofer N; Zagaja, Gregory P; Shilo, Yaniv; Shalhav, Arieh L

    2013-07-01

    Recommendations for active surveillance versus immediate treatment for low risk prostate cancer are based on biopsy and clinical data, assuming that a low volume of well-differentiated carcinoma will be associated with a low progression risk. However, the accuracy of clinical prediction of minimal prostate cancer (MPC) is unclear. To define preoperative predictors for MPC in prostatectomy specimens and to examine the accuracy of such prediction. Data collected on 1526 consecutive radical prostatectomy patients operated in a single center between 2003 and 2008 included: age, body mass index, preoperative prostate-specific antigen level, biopsy Gleason score, clinical stage, percentage of positive biopsy cores, and maximal core length (MCL) involvement. MPC was defined as < 5% of prostate volume involvement with organ-confined Gleason score < or = 6. Univariate and multivariate logistic regression analyses were used to define independent predictors of minimal disease. Classification and Regression Tree (CART) analysis was used to define cutoff values for the predictors and measure the accuracy of prediction. MPC was found in 241 patients (15.8%). Clinical stage, biopsy Gleason's score, percent of positive biopsy cores, and maximal involved core length were associated with minimal disease (OR 0.42, 0.1, 0.92, and 0.9, respectively). Independent predictors of MPC included: biopsy Gleason score, percent of positive cores and MCL (OR 0.21, 095 and 0.95, respectively). CART showed that when the MCL exceeded 11.5%, the likelihood of MPC was 3.8%. Conversely, when applying the most favorable preoperative conditions (Gleason < or = 6, < 20% positive cores, MCL < or = 11.5%) the chance of minimal disease was 41%. Biopsy Gleason score, the percent of positive cores and MCL are independently associated with MPC. While preoperative prediction of significant prostate cancer was accurate, clinical prediction of MPC was incorrect 59% of the time. Caution is necessary when

  11. 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

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

    DOE PAGES

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

    2015-06-04

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

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

    PubMed Central

    2015-01-01

    Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and apply a systematic hierarchy of efficient empirical methods to estimate atomization and total energies of molecules. These methods range from a simple sum over atoms, to addition of bond energies, to pairwise interatomic force fields, reaching to the more sophisticated machine learning approaches that are capable of describing collective interactions between many atoms or bonds. In the case of equilibrium molecular geometries, even simple pairwise force fields demonstrate prediction accuracy comparable to benchmark energies calculated using density functional theory with hybrid exchange-correlation functionals; however, accounting for the collective many-body interactions proves to be essential for approaching the “holy grail” of chemical accuracy of 1 kcal/mol for both equilibrium and out-of-equilibrium geometries. This remarkable accuracy is achieved by a vectorized representation of molecules (so-called Bag of Bonds model) that exhibits strong nonlocality in chemical space. In addition, the same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies. PMID:26113956

  14. Distinguishing prognostic and predictive biomarkers: An information theoretic approach.

    PubMed

    Sechidis, Konstantinos; Papangelou, Konstantinos; Metcalfe, Paul D; Svensson, David; Weatherall, James; Brown, Gavin

    2018-05-02

    The identification of biomarkers to support decision-making is central to personalised medicine, in both clinical and research scenarios. The challenge can be seen in two halves: identifying predictive markers, which guide the development/use of tailored therapies; and identifying prognostic markers, which guide other aspects of care and clinical trial planning, i.e. prognostic markers can be considered as covariates for stratification. Mistakenly assuming a biomarker to be predictive, when it is in fact largely prognostic (and vice-versa) is highly undesirable, and can result in financial, ethical and personal consequences. We present a framework for data-driven ranking of biomarkers on their prognostic/predictive strength, using a novel information theoretic method. This approach provides a natural algebra to discuss and quantify the individual predictive and prognostic strength, in a self-consistent mathematical framework. Our contribution is a novel procedure, INFO+, which naturally distinguishes the prognostic vs predictive role of each biomarker and handles higher order interactions. In a comprehensive empirical evaluation INFO+ outperforms more complex methods, most notably when noise factors dominate, and biomarkers are likely to be falsely identified as predictive, when in fact they are just strongly prognostic. Furthermore, we show that our methods can be 1-3 orders of magnitude faster than competitors, making it useful for biomarker discovery in 'big data' scenarios. Finally, we apply our methods to identify predictive biomarkers on two real clinical trials, and introduce a new graphical representation that provides greater insight into the prognostic and predictive strength of each biomarker. R implementations of the suggested methods are available at https://github.com/sechidis. konstantinos.sechidis@manchester.ac.uk. Supplementary data are available at Bioinformatics online.

  15. Physics of mind: Experimental confirmations of theoretical predictions.

    PubMed

    Schoeller, Félix; Perlovsky, Leonid; Arseniev, Dmitry

    2018-02-02

    What is common among Newtonian mechanics, statistical physics, thermodynamics, quantum physics, the theory of relativity, astrophysics and the theory of superstrings? All these areas of physics have in common a methodology, which is discussed in the first few lines of the review. Is a physics of the mind possible? Is it possible to describe how a mind adapts in real time to changes in the physical world through a theory based on a few basic laws? From perception and elementary cognition to emotions and abstract ideas allowing high-level cognition and executive functioning, at nearly all levels of study, the mind shows variability and uncertainties. Is it possible to turn psychology and neuroscience into so-called "hard" sciences? This review discusses several established first principles for the description of mind and their mathematical formulations. A mathematical model of mind is derived from these principles. This model includes mechanisms of instincts, emotions, behavior, cognition, concepts, language, intuitions, and imagination. We clarify fundamental notions such as the opposition between the conscious and the unconscious, the knowledge instinct and aesthetic emotions, as well as humans' universal abilities for symbols and meaning. In particular, the review discusses in length evolutionary and cognitive functions of aesthetic emotions and musical emotions. Several theoretical predictions are derived from the model, some of which have been experimentally confirmed. These empirical results are summarized and we introduce new theoretical developments. Several unsolved theoretical problems are proposed, as well as new experimental challenges for future research. Copyright © 2017. Published by Elsevier B.V.

  16. Theoretical prediction of airplane stability derivatives at subcritical speeds

    NASA Technical Reports Server (NTRS)

    Tulinius, J.; Clever, W.; Nieman, A.; Dunn, K.; Gaither, B.

    1973-01-01

    The theoretical development and application is described of an analysis for predicting the major static and rotary stability derivatives for a complete airplane. The analysis utilizes potential flow theory to compute the surface flow fields and pressures on any configuration that can be synthesized from arbitrary lifting bodies and nonplanar thick lifting panels. The pressures are integrated to obtain section and total configuration loads and moments due side slip, angle of attack, pitching motion, rolling motion, yawing motion, and control surface deflection. Subcritical compressibility is accounted for by means of the Gothert similarity rule.

  17. How accurate are resting energy expenditure prediction equations in obese trauma and burn patients?

    PubMed

    Stucky, Chee-Chee H; Moncure, Michael; Hise, Mary; Gossage, Clint M; Northrop, David

    2008-01-01

    While the prevalence of obesity continues to increase in our society, outdated resting energy expenditure (REE) prediction equations may overpredict energy requirements in obese patients. Accurate feeding is essential since overfeeding has been demonstrated to adversely affect outcomes. The first objective was to compare REE calculated by prediction equations to the measured REE in obese trauma and burn patients. Our hypothesis was that an equation using fat-free mass would give a more accurate prediction. The second objective was to consider the effect of a commonly used injury factor on the predicted REE. A retrospective chart review was performed on 28 patients. REE was measured using indirect calorimetry and compared with the Harris-Benedict and Cunningham equations, and an equation using type II diabetes as a factor. Statistical analyses used were paired t test, +/-95% confidence interval, and the Bland-Altman method. Measured average REE in trauma and burn patients was 21.37 +/- 5.26 and 21.81 +/- 3.35 kcal/kg/d, respectively. Harris-Benedict underpredicted REE in trauma and burn patients to the least extent, while the Cunningham equation underpredicted REE in both populations to the greatest extent. Using an injury factor of 1.2, Cunningham continued to underestimate REE in both populations, while the Harris-Benedict and Diabetic equations overpredicted REE in both populations. The measured average REE is significantly less than current guidelines. This finding suggests that a hypocaloric regimen is worth considering for ICU patients. Also, if an injury factor of 1.2 is incorporated in certain equations, patients may be given too many calories.

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Visel, Axel; Blow, Matthew J.; Li, Zirong

    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. Wemore » 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.« less

  19. A comparison of naïve and sophisticated subject behavior with game theoretic predictions

    PubMed Central

    McCabe, Kevin A.; Smith, Vernon L.

    2000-01-01

    We use an extensive form two-person game as the basis for two experiments designed to compare the behavior of two groups of subjects with each other and with the subgame perfect theoretical prediction in an anonymous interaction protocol. The two subject groups are undergraduates and advanced graduate students, the latter having studied economics and game theory. There is no difference in their choice behavior, and both groups depart substantially from game theoretic predictions. We also compare a subsample of the same graduate students with a typical undergraduate sample in an asset trading environment in which inexperienced undergraduates invariably produce substantial departures from the rational expectations prediction. In this way, we examine how robust are the results across two distinct anonymous interactive environments. In the constant sum trading game, the graduate students closely track the predictions of rational theory. Our interpretation is that the graduate student subjects' departure from subgame perfection to achieve cooperative outcomes in the two-person bargaining game is a consequence of a deliberate strategy and is not the result of error or inadequate learning. PMID:10725349

  20. Information-theoretic model selection for optimal prediction of stochastic dynamical systems from data

    NASA Astrophysics Data System (ADS)

    Darmon, David

    2018-03-01

    In the absence of mechanistic or phenomenological models of real-world systems, data-driven models become necessary. The discovery of various embedding theorems in the 1980s and 1990s motivated a powerful set of tools for analyzing deterministic dynamical systems via delay-coordinate embeddings of observations of their component states. However, in many branches of science, the condition of operational determinism is not satisfied, and stochastic models must be brought to bear. For such stochastic models, the tool set developed for delay-coordinate embedding is no longer appropriate, and a new toolkit must be developed. We present an information-theoretic criterion, the negative log-predictive likelihood, for selecting the embedding dimension for a predictively optimal data-driven model of a stochastic dynamical system. We develop a nonparametric estimator for the negative log-predictive likelihood and compare its performance to a recently proposed criterion based on active information storage. Finally, we show how the output of the model selection procedure can be used to compare candidate predictors for a stochastic system to an information-theoretic lower bound.

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

    PubMed Central

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

    2015-01-01

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

  2. Vortex shedding from obstacles: theoretical frequency prediction

    NASA Astrophysics Data System (ADS)

    Pier, Benoît

    2001-11-01

    The existence of self-sustained oscillations in spatially developing systems is closely related to the presence of a locally absolutely unstable region. A recent investigation of a ``synthetic wake'' (a wake with no solid obstacle and no reverse flow region) has proved [Pier and Huerre, J. Fluid Mech. 435, 145 (2001)] that the observed Kármán vortex street is a nonlinear elephant global mode. The same criterion is now shown to hold for real obstacles. Local properties are derived from the unperturbed basic flow computed by enforcing a symmetry condition on the central line. Application of the theoretical criterion then yields the expected Strouhal vortex shedding frequency. The thus predicted frequency is in excellent agreement with direct numerical simulations of the complete flow. The use of the frequency selection mechanism to control the vortex shedding will also be discussed.

  3. Theoretical study of the diatomic alkali and alkaline-earth oxides

    NASA Technical Reports Server (NTRS)

    Langhoff, S. R.; Bauschlicher, C. W., Jr.; Partridge, H.

    1986-01-01

    Theoretical dissociation energies for the ground states of the alkali and alkaline earth oxides are presented that are believed to be accurate to 0.1 eV. The 2 Pi - 2 Sigma + separations for the alkali oxides are found to be more sensitive to basis set than to electron correlation. Predicted 2 Pi ground states for LiO and NaO and 2 Sigma + ground states for RbO and CsO are found to be in agreement with previous theoretical and experimental work. For KO, a 2 Sigma + state is found at both the numerical Hartree-Fock (NHF) level and at the singles plus doubles configuration interaction level using a Slater basis set that is within 0.02 eV of the NHF limit. It is found that an accurate balanced treatment of the two states requires correlating the electrons on both the metal and oxide ion.

  4. Improving medical decisions for incapacitated persons: does focusing on "accurate predictions" lead to an inaccurate picture?

    PubMed

    Kim, Scott Y H

    2014-04-01

    The Patient Preference Predictor (PPP) proposal places a high priority on the accuracy of predicting patients' preferences and finds the performance of surrogates inadequate. However, the quest to develop a highly accurate, individualized statistical model has significant obstacles. First, it will be impossible to validate the PPP beyond the limit imposed by 60%-80% reliability of people's preferences for future medical decisions--a figure no better than the known average accuracy of surrogates. Second, evidence supports the view that a sizable minority of persons may not even have preferences to predict. Third, many, perhaps most, people express their autonomy just as much by entrusting their loved ones to exercise their judgment than by desiring to specifically control future decisions. Surrogate decision making faces none of these issues and, in fact, it may be more efficient, accurate, and authoritative than is commonly assumed.

  5. Rapid and accurate prediction of degradant formation rates in pharmaceutical formulations using high-performance liquid chromatography-mass spectrometry.

    PubMed

    Darrington, Richard T; Jiao, Jim

    2004-04-01

    Rapid and accurate stability prediction is essential to pharmaceutical formulation development. Commonly used stability prediction methods include monitoring parent drug loss at intended storage conditions or initial rate determination of degradants under accelerated conditions. Monitoring parent drug loss at the intended storage condition does not provide a rapid and accurate stability assessment because often <0.5% drug loss is all that can be observed in a realistic time frame, while the accelerated initial rate method in conjunction with extrapolation of rate constants using the Arrhenius or Eyring equations often introduces large errors in shelf-life prediction. In this study, the shelf life prediction of a model pharmaceutical preparation utilizing sensitive high-performance liquid chromatography-mass spectrometry (LC/MS) to directly quantitate degradant formation rates at the intended storage condition is proposed. This method was compared to traditional shelf life prediction approaches in terms of time required to predict shelf life and associated error in shelf life estimation. Results demonstrated that the proposed LC/MS method using initial rates analysis provided significantly improved confidence intervals for the predicted shelf life and required less overall time and effort to obtain the stability estimation compared to the other methods evaluated. Copyright 2004 Wiley-Liss, Inc. and the American Pharmacists Association.

  6. Future missions studies: Combining Schatten's solar activity prediction model with a chaotic prediction model

    NASA Technical Reports Server (NTRS)

    Ashrafi, S.

    1991-01-01

    K. Schatten (1991) recently developed a method for combining his prediction model with our chaotic model. The philosophy behind this combined model and his method of combination is explained. Because the Schatten solar prediction model (KS) uses a dynamo to mimic solar dynamics, accurate prediction is limited to long-term solar behavior (10 to 20 years). The Chaotic prediction model (SA) uses the recently developed techniques of nonlinear dynamics to predict solar activity. It can be used to predict activity only up to the horizon. In theory, the chaotic prediction should be several orders of magnitude better than statistical predictions up to that horizon; beyond the horizon, chaotic predictions would theoretically be just as good as statistical predictions. Therefore, chaos theory puts a fundamental limit on predictability.

  7. 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. Copyright © 2016 Elsevier Inc. All rights reserved.

  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. © 2013 Wiley Periodicals, Inc.

  9. A comparison of measured and theoretical predictions for STS ascent and entry sonic booms

    NASA Technical Reports Server (NTRS)

    Garcia, F., Jr.; Jones, J. H.; Henderson, H. R.

    1983-01-01

    Sonic boom measurements have been obtained during the flights of STS-1 through 5. During STS-1, 2, and 4, entry sonic boom measurements were obtained and ascent measurements were made on STS-5. The objectives of this measurement program were (1) to define the sonic boom characteristics of the Space Transportation System (STS), (2) provide a realistic assessment of the validity of xisting theoretical prediction techniques, and (3) establish a level of confidence for predicting future STS configuration sonic boom environments. Detail evaluation and reporting of the results of this program are in progress. This paper will address only the significant results, mainly those data obtained during the entry of STS-1 at Edwards Air Force Base (EAFB), and the ascent of STS-5 from Kennedy Space Center (KSC). The theoretical prediction technique employed in this analysis is the so called Thomas Program. This prediction technique is a semi-empirical method that required definition of the near field signatures, detailed trajectory characteristics, and the prevailing meteorological characteristics as an input. This analytical procedure then extrapolates the near field signatures from the flight altitude to an altitude consistent with each measurement location.

  10. Do dual-route models accurately predict reading and spelling performance in individuals with acquired alexia and agraphia?

    PubMed

    Rapcsak, Steven Z; Henry, Maya L; Teague, Sommer L; Carnahan, Susan D; Beeson, Pélagie M

    2007-06-18

    Coltheart and co-workers [Castles, A., Bates, T. C., & Coltheart, M. (2006). John Marshall and the developmental dyslexias. Aphasiology, 20, 871-892; Coltheart, M., Rastle, K., Perry, C., Langdon, R., & Ziegler, J. (2001). DRC: A dual route cascaded model of visual word recognition and reading aloud. Psychological Review, 108, 204-256] have demonstrated that an equation derived from dual-route theory accurately predicts reading performance in young normal readers and in children with reading impairment due to developmental dyslexia or stroke. In this paper, we present evidence that the dual-route equation and a related multiple regression model also accurately predict both reading and spelling performance in adult neurological patients with acquired alexia and agraphia. These findings provide empirical support for dual-route theories of written language processing.

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Shvab, I.; Sadus, Richard J., E-mail: rsadus@swin.edu.au

    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.more » 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.« less

  12. Coarse-Graining Polymer Field Theory for Fast and Accurate Simulations of Directed Self-Assembly

    NASA Astrophysics Data System (ADS)

    Liu, Jimmy; Delaney, Kris; Fredrickson, Glenn

    To design effective manufacturing processes using polymer directed self-assembly (DSA), the semiconductor industry benefits greatly from having a complete picture of stable and defective polymer configurations. Field-theoretic simulations are an effective way to study these configurations and predict defect populations. Self-consistent field theory (SCFT) is a particularly successful theory for studies of DSA. Although other models exist that are faster to simulate, these models are phenomenological or derived through asymptotic approximations, often leading to a loss of accuracy relative to SCFT. In this study, we employ our recently-developed method to produce an accurate coarse-grained field theory for diblock copolymers. The method uses a force- and stress-matching strategy to map output from SCFT simulations into parameters for an optimized phase field model. This optimized phase field model is just as fast as existing phenomenological phase field models, but makes more accurate predictions of polymer self-assembly, both in bulk and in confined systems. We study the performance of this model under various conditions, including its predictions of domain spacing, morphology and defect formation energies. Samsung Electronics.

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

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

    PubMed

    Wang, Sheng; Sun, Siqi; Li, Zhen; Zhang, Renyu; Xu, Jinbo

    2017-01-01

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

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

    PubMed Central

    Li, Zhen; Zhang, Renyu

    2017-01-01

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

  16. Obtaining Accurate Probabilities Using Classifier Calibration

    ERIC Educational Resources Information Center

    Pakdaman Naeini, Mahdi

    2016-01-01

    Learning probabilistic classification and prediction models that generate accurate probabilities is essential in many prediction and decision-making tasks in machine learning and data mining. One way to achieve this goal is to post-process the output of classification models to obtain more accurate probabilities. These post-processing methods are…

  17. A Multiscale Red Blood Cell Model with Accurate Mechanics, Rheology, and Dynamics

    PubMed Central

    Fedosov, Dmitry A.; Caswell, Bruce; Karniadakis, George Em

    2010-01-01

    Abstract Red blood cells (RBCs) have highly deformable viscoelastic membranes exhibiting complex rheological response and rich hydrodynamic behavior governed by special elastic and bending properties and by the external/internal fluid and membrane viscosities. We present a multiscale RBC model that is able to predict RBC mechanics, rheology, and dynamics in agreement with experiments. Based on an analytic theory, the modeled membrane properties can be uniquely related to the experimentally established RBC macroscopic properties without any adjustment of parameters. The RBC linear and nonlinear elastic deformations match those obtained in optical-tweezers experiments. The rheological properties of the membrane are compared with those obtained in optical magnetic twisting cytometry, membrane thermal fluctuations, and creep followed by cell recovery. The dynamics of RBCs in shear and Poiseuille flows is tested against experiments and theoretical predictions, and the applicability of the latter is discussed. Our findings clearly indicate that a purely elastic model for the membrane cannot accurately represent the RBC's rheological properties and its dynamics, and therefore accurate modeling of a viscoelastic membrane is necessary. PMID:20483330

  18. Limb-Enhancer Genie: An accessible resource of accurate enhancer predictions in the developing limb

    DOE PAGES

    Monti, Remo; Barozzi, Iros; Osterwalder, Marco; ...

    2017-08-21

    Epigenomic mapping of enhancer-associated chromatin modifications facilitates the genome-wide discovery of tissue-specific enhancers in vivo. However, reliance on single chromatin marks leads to high rates of false-positive predictions. More sophisticated, integrative methods have been described, but commonly suffer from limited accessibility to the resulting predictions and reduced biological interpretability. Here we present the Limb-Enhancer Genie (LEG), a collection of highly accurate, genome-wide predictions of enhancers in the developing limb, available through a user-friendly online interface. We predict limb enhancers using a combination of > 50 published limb-specific datasets and clusters of evolutionarily conserved transcription factor binding sites, taking advantage ofmore » the patterns observed at previously in vivo validated elements. By combining different statistical models, our approach outperforms current state-of-the-art methods and provides interpretable measures of feature importance. Our results indicate that including a previously unappreciated score that quantifies tissue-specific nuclease accessibility significantly improves prediction performance. We demonstrate the utility of our approach through in vivo validation of newly predicted elements. Moreover, we describe general features that can guide the type of datasets to include when predicting tissue-specific enhancers genome-wide, while providing an accessible resource to the general biological community and facilitating the functional interpretation of genetic studies of limb malformations.« less

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

    PubMed Central

    Garcia Lopez, Sebastian; Kim, Philip M.

    2014-01-01

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

  20. Theoretical predictions of latitude dependencies in the solar wind

    NASA Technical Reports Server (NTRS)

    Winge, C. R., Jr.; Coleman, P. J., Jr.

    1974-01-01

    Results are presented which were obtained with the Winge-Coleman model for theoretical predictions of latitudinal dependencies in the solar wind. A first-order expansion is described which allows analysis of first-order latitudinal variations in the coronal boundary conditions and results in a second-order partial differential equation for the perturbation stream function. Latitudinal dependencies are analytically separated out in the form of Legendre polynomials and their derivative, and are reduced to the solution of radial differential equations. This analysis is shown to supply an estimate of how large the coronal variation in latitude must be to produce an 11 km/sec/deg gradient in the radial velocity of the solar wind, assuming steady-state processes.

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

    PubMed

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

    2011-12-01

    Proton uptake or release controls many important biological processes, such as energy transduction, virus replication, and catalysis. Accurate pK(a) prediction informs about proton pathways, thereby revealing detailed acid-base mechanisms. Physics-based methods in the framework of molecular dynamics simulations not only offer pK(a) predictions but also inform about the physical origins of pK(a) shifts and provide details of ionization-induced conformational relaxation and large-scale transitions. One such method is the recently developed continuous constant pH molecular dynamics (CPHMD) method, which has been shown to be an accurate and robust pK(a) prediction tool for naturally occurring titratable residues. To further examine the accuracy and limitations of CPHMD, we blindly predicted the pK(a) values for 87 titratable residues introduced in various hydrophobic regions of staphylococcal nuclease and variants. The predictions gave a root-mean-square deviation of 1.69 pK units from experiment, and there were only two pK(a)'s with errors greater than 3.5 pK units. Analysis of the conformational fluctuation of titrating side-chains in the context of the errors of calculated pK(a) values indicate that explicit treatment of conformational flexibility and the associated dielectric relaxation gives CPHMD a distinct advantage. Analysis of the sources of errors suggests that more accurate pK(a) predictions can be obtained for the most deeply buried residues by improving the accuracy in calculating desolvation energies. Furthermore, it is found that the generalized Born implicit-solvent model underlying the current CPHMD implementation slightly distorts the local conformational environment such that the inclusion of an explicit-solvent representation may offer improvement of accuracy. Copyright © 2011 Wiley-Liss, Inc.

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Martin, Katherine J.; Patrick, Denis R.; Bissell, Mina J.

    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 datasetsmore » 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

  3. Theoretical Predictions of Cross-Sections of the Super-Heavy Elements

    NASA Astrophysics Data System (ADS)

    Bouriquet, B.; Kosenko, G.; Abe, Y.

    The evaluation of the residue cross-sections of reactionssynthesising superheavy elements has been achieved by the combination of the two-step model for fusion and the evaporation code (KEWPIE) for survival probability. The theoretical scheme of those calculations is presented, and some encouraging results are given, together with some difficulties. With this approach, the measured excitation functions of the 1n reactions producing elements with Z=108, 110, 111 and 112 are well reproduced. Thus, the model has been used to predict the cross-sections of the reactions leading to the formation of the elements with Z=113 and Z=114.

  4. MetaPSICOV: combining coevolution methods for accurate prediction of contacts and long range hydrogen bonding in proteins.

    PubMed

    Jones, David T; Singh, Tanya; Kosciolek, Tomasz; Tetchner, Stuart

    2015-04-01

    Recent developments of statistical techniques to infer direct evolutionary couplings between residue pairs have rendered covariation-based contact prediction a viable means for accurate 3D modelling of proteins, with no information other than the sequence required. To extend the usefulness of contact prediction, we have designed a new meta-predictor (MetaPSICOV) which combines three distinct approaches for inferring covariation signals from multiple sequence alignments, considers a broad range of other sequence-derived features and, uniquely, a range of metrics which describe both the local and global quality of the input multiple sequence alignment. Finally, we use a two-stage predictor, where the second stage filters the output of the first stage. This two-stage predictor is additionally evaluated on its ability to accurately predict the long range network of hydrogen bonds, including correctly assigning the donor and acceptor residues. Using the original PSICOV benchmark set of 150 protein families, MetaPSICOV achieves a mean precision of 0.54 for top-L predicted long range contacts-around 60% higher than PSICOV, and around 40% better than CCMpred. In de novo protein structure prediction using FRAGFOLD, MetaPSICOV is able to improve the TM-scores of models by a median of 0.05 compared with PSICOV. Lastly, for predicting long range hydrogen bonding, MetaPSICOV-HB achieves a precision of 0.69 for the top-L/10 hydrogen bonds compared with just 0.26 for the baseline MetaPSICOV. MetaPSICOV is available as a freely available web server at http://bioinf.cs.ucl.ac.uk/MetaPSICOV. Raw data (predicted contact lists and 3D models) and source code can be downloaded from http://bioinf.cs.ucl.ac.uk/downloads/MetaPSICOV. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

  5. Quasi-closed phase forward-backward linear prediction analysis of speech for accurate formant detection and estimation.

    PubMed

    Gowda, Dhananjaya; Airaksinen, Manu; Alku, Paavo

    2017-09-01

    Recently, a quasi-closed phase (QCP) analysis of speech signals for accurate glottal inverse filtering was proposed. However, the QCP analysis which belongs to the family of temporally weighted linear prediction (WLP) methods uses the conventional forward type of sample prediction. This may not be the best choice especially in computing WLP models with a hard-limiting weighting function. A sample selective minimization of the prediction error in WLP reduces the effective number of samples available within a given window frame. To counter this problem, a modified quasi-closed phase forward-backward (QCP-FB) analysis is proposed, wherein each sample is predicted based on its past as well as future samples thereby utilizing the available number of samples more effectively. Formant detection and estimation experiments on synthetic vowels generated using a physical modeling approach as well as natural speech utterances show that the proposed QCP-FB method yields statistically significant improvements over the conventional linear prediction and QCP methods.

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

    PubMed

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

    2013-03-15

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

  7. WegoLoc: accurate prediction of protein subcellular localization using weighted Gene Ontology terms.

    PubMed

    Chi, Sang-Mun; Nam, Dougu

    2012-04-01

    We present an accurate and fast web server, WegoLoc for predicting subcellular localization of proteins based on sequence similarity and weighted Gene Ontology (GO) information. A term weighting method in the text categorization process is applied to GO terms for a support vector machine classifier. As a result, WegoLoc surpasses the state-of-the-art methods for previously used test datasets. WegoLoc supports three eukaryotic kingdoms (animals, fungi and plants) and provides human-specific analysis, and covers several sets of cellular locations. In addition, WegoLoc provides (i) multiple possible localizations of input protein(s) as well as their corresponding probability scores, (ii) weights of GO terms representing the contribution of each GO term in the prediction, and (iii) a BLAST E-value for the best hit with GO terms. If the similarity score does not meet a given threshold, an amino acid composition-based prediction is applied as a backup method. WegoLoc and User's guide are freely available at the website http://www.btool.org/WegoLoc smchiks@ks.ac.kr; dougnam@unist.ac.kr Supplementary data is available at http://www.btool.org/WegoLoc.

  8. Sex-specific lean body mass predictive equations are accurate in the obese paediatric population

    PubMed Central

    Jackson, Lanier B.; Henshaw, Melissa H.; Carter, Janet; Chowdhury, Shahryar M.

    2015-01-01

    Background The clinical assessment of lean body mass (LBM) is challenging in obese children. A sex-specific predictive equation for LBM derived from anthropometric data was recently validated in children. Aim The purpose of this study was to independently validate these predictive equations in the obese paediatric population. Subjects and methods Obese subjects aged 4–21 were analysed retrospectively. Predicted LBM (LBMp) was calculated using equations previously developed in children. Measured LBM (LBMm) was derived from dual-energy x-ray absorptiometry. Agreement was expressed as [(LBMm-LBMp)/LBMm] with 95% limits of agreement. Results Of 310 enrolled patients, 195 (63%) were females. The mean age was 11.8 ± 3.4 years and mean BMI Z-score was 2.3 ± 0.4. The average difference between LBMm and LBMp was −0.6% (−17.0%, 15.8%). Pearson’s correlation revealed a strong linear relationship between LBMm and LBMp (r=0.97, p<0.01). Conclusion This study validates the use of these clinically-derived sex-specific LBM predictive equations in the obese paediatric population. Future studies should use these equations to improve the ability to accurately classify LBM in obese children. PMID:26287383

  9. Predicting excitonic gaps of semiconducting single-walled carbon nanotubes from a field theoretic analysis

    DOE PAGES

    Konik, Robert M.; Sfeir, Matthew Y.; Misewich, James A.

    2015-02-17

    We demonstrate that a non-perturbative framework for the treatment of the excitations of single walled carbon nanotubes based upon a field theoretic reduction is able to accurately describe experiment observations of the absolute values of excitonic energies. This theoretical framework yields a simple scaling function from which the excitonic energies can be read off. This scaling function is primarily determined by a single parameter, the charge Luttinger parameter of the tube, which is in turn a function of the tube chirality, dielectric environment, and the tube's dimensions, thus expressing disparate influences on the excitonic energies in a unified fashion. Asmore » a result, we test this theory explicitly on the data reported in [NanoLetters 5, 2314 (2005)] and [Phys. Rev. B 82, 195424 (2010)] and so demonstrate the method works over a wide range of reported excitonic spectra.« less

  10. Accurate prediction of cation-π interaction energy using substituent effects.

    PubMed

    Sayyed, Fareed Bhasha; Suresh, Cherumuttathu H

    2012-06-14

    (M(+))' and ΔV(min). All the Φ-X···M(+) systems showed good agreement between the calculated and predicted E(M(+))() values, suggesting that the ΔV(min) approach to substituent effect is accurate and useful for predicting the interactive behavior of substituted π-systems with cations.

  11. Accurate predictions of iron redox state in silicate glasses: A multivariate approach using X-ray absorption spectroscopy

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Dyar, M. Darby; McCanta, Molly; Breves, Elly

    2016-03-01

    Pre-edge features in the K absorption edge of X-ray absorption spectra are commonly used to predict Fe3+ valence state in silicate glasses. However, this study shows that using the entire spectral region from the pre-edge into the extended X-ray absorption fine-structure region provides more accurate results when combined with multivariate analysis techniques. The least absolute shrinkage and selection operator (lasso) regression technique yields %Fe3+ values that are accurate to ±3.6% absolute when the full spectral region is employed. This method can be used across a broad range of glass compositions, is easily automated, and is demonstrated to yield accurate resultsmore » from different synchrotrons. It will enable future studies involving X-ray mapping of redox gradients on standard thin sections at 1 × 1 μm pixel sizes.« less

  12. Accurate predictions of iron redox state in silicate glasses: A multivariate approach using X-ray absorption spectroscopy

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Dyar, M. Darby; McCanta, Molly; Breves, Elly

    2016-03-01

    Pre-edge features in the K absorption edge of X-ray absorption spectra are commonly used to predict Fe 3+ valence state in silicate glasses. However, this study shows that using the entire spectral region from the pre-edge into the extended X-ray absorption fine-structure region provides more accurate results when combined with multivariate analysis techniques. The least absolute shrinkage and selection operator (lasso) regression technique yields %Fe 3+ values that are accurate to ±3.6% absolute when the full spectral region is employed. This method can be used across a broad range of glass compositions, is easily automated, and is demonstrated to yieldmore » accurate results from different synchrotrons. It will enable future studies involving X-ray mapping of redox gradients on standard thin sections at 1 × 1 μm pixel sizes.« less

  13. Theoretical prediction of crystallization kinetics of a supercooled Lennard-Jones fluid

    NASA Astrophysics Data System (ADS)

    Gunawardana, K. G. S. H.; Song, Xueyu

    2018-05-01

    The first order curvature correction to the crystal-liquid interfacial free energy is calculated using a theoretical model based on the interfacial excess thermodynamic properties. The correction parameter (δ), which is analogous to the Tolman length at a liquid-vapor interface, is found to be 0.48 ± 0.05 for a Lennard-Jones (LJ) fluid. We show that this curvature correction is crucial in predicting the nucleation barrier when the size of the crystal nucleus is small. The thermodynamic driving force (Δμ) corresponding to available simulated nucleation conditions is also calculated by combining the simulated data with a classical density functional theory. In this paper, we show that the classical nucleation theory is capable of predicting the nucleation barrier with excellent agreement to the simulated results when the curvature correction to the interfacial free energy is accounted for.

  14. Predictive power of theoretical modelling of the nuclear mean field: examples of improving predictive capacities

    NASA Astrophysics Data System (ADS)

    Dedes, I.; Dudek, J.

    2018-03-01

    We examine the effects of the parametric correlations on the predictive capacities of the theoretical modelling keeping in mind the nuclear structure applications. The main purpose of this work is to illustrate the method of establishing the presence and determining the form of parametric correlations within a model as well as an algorithm of elimination by substitution (see text) of parametric correlations. We examine the effects of the elimination of the parametric correlations on the stabilisation of the model predictions further and further away from the fitting zone. It follows that the choice of the physics case and the selection of the associated model are of secondary importance in this case. Under these circumstances we give priority to the relative simplicity of the underlying mathematical algorithm, provided the model is realistic. Following such criteria, we focus specifically on an important but relatively simple case of doubly magic spherical nuclei. To profit from the algorithmic simplicity we chose working with the phenomenological spherically symmetric Woods–Saxon mean-field. We employ two variants of the underlying Hamiltonian, the traditional one involving both the central and the spin orbit potential in the Woods–Saxon form and the more advanced version with the self-consistent density-dependent spin–orbit interaction. We compare the effects of eliminating of various types of correlations and discuss the improvement of the quality of predictions (‘predictive power’) under realistic parameter adjustment conditions.

  15. A multiscale red blood cell model with accurate mechanics, rheology, and dynamics.

    PubMed

    Fedosov, Dmitry A; Caswell, Bruce; Karniadakis, George Em

    2010-05-19

    Red blood cells (RBCs) have highly deformable viscoelastic membranes exhibiting complex rheological response and rich hydrodynamic behavior governed by special elastic and bending properties and by the external/internal fluid and membrane viscosities. We present a multiscale RBC model that is able to predict RBC mechanics, rheology, and dynamics in agreement with experiments. Based on an analytic theory, the modeled membrane properties can be uniquely related to the experimentally established RBC macroscopic properties without any adjustment of parameters. The RBC linear and nonlinear elastic deformations match those obtained in optical-tweezers experiments. The rheological properties of the membrane are compared with those obtained in optical magnetic twisting cytometry, membrane thermal fluctuations, and creep followed by cell recovery. The dynamics of RBCs in shear and Poiseuille flows is tested against experiments and theoretical predictions, and the applicability of the latter is discussed. Our findings clearly indicate that a purely elastic model for the membrane cannot accurately represent the RBC's rheological properties and its dynamics, and therefore accurate modeling of a viscoelastic membrane is necessary. Copyright 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  16. 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

  17. Prediction of the amount of urban waste solids by applying a gray theoretical model.

    PubMed

    Li, Xiao-Ming; Zeng, Guang-Ming; Wang, Ming; Liu, Jin-Jin

    2003-01-01

    Urban waste solids are now becoming one of the most crucial environmental problems. There are several different kinds of technologies normally used for waste solids disposal, among which landfill is more favorable in China than others, especially for urban waste solids. Most of the design works up to now are based on a roughly estimation of the amount of urban waste solids without any theoretical support, which lead to a series problems. To meet the basic information requirements for the design work, the amount of the urban waste solids was predicted in this research by applying the gray theoretical model GM (1,1) through non-linear differential equation simulation. The model parameters were estimated with the least square method (LSM) by running a certain MATALAB program, and the hypothesis test results show that the residual between the prediction value and the actual value approximately comply with the normal distribution N (0, 0.21(2)), and the probability of the residual within the range ( -0.17, 0.19) is more than 95%, which indicate obviously that the model can be well used for the prediction of the amount of waste solids and those had been already testified by the latest two years data about the urban waste solids from Loudi City of China. With this model, the predicted amount of the waste solids produced in Loudi City in the next 30 years is 8049000 ton in total.

  18. Predicting vapor-liquid phase equilibria with augmented ab initio interatomic potentials

    NASA Astrophysics Data System (ADS)

    Vlasiuk, Maryna; Sadus, Richard J.

    2017-06-01

    The ability of ab initio interatomic potentials to accurately predict vapor-liquid phase equilibria is investigated. Monte Carlo simulations are reported for the vapor-liquid equilibria of argon and krypton using recently developed accurate ab initio interatomic potentials. Seventeen interatomic potentials are studied, formulated from different combinations of two-body plus three-body terms. The simulation results are compared to either experimental or reference data for conditions ranging from the triple point to the critical point. It is demonstrated that the use of ab initio potentials enables systematic improvements to the accuracy of predictions via the addition of theoretically based terms. The contribution of three-body interactions is accounted for using the Axilrod-Teller-Muto plus other multipole contributions and the effective Marcelli-Wang-Sadus potentials. The results indicate that the predictive ability of recent interatomic potentials, obtained from quantum chemical calculations, is comparable to that of accurate empirical models. It is demonstrated that the Marcelli-Wang-Sadus potential can be used in combination with accurate two-body ab initio models for the computationally inexpensive and accurate estimation of vapor-liquid phase equilibria.

  19. Predicting vapor-liquid phase equilibria with augmented ab initio interatomic potentials.

    PubMed

    Vlasiuk, Maryna; Sadus, Richard J

    2017-06-28

    The ability of ab initio interatomic potentials to accurately predict vapor-liquid phase equilibria is investigated. Monte Carlo simulations are reported for the vapor-liquid equilibria of argon and krypton using recently developed accurate ab initio interatomic potentials. Seventeen interatomic potentials are studied, formulated from different combinations of two-body plus three-body terms. The simulation results are compared to either experimental or reference data for conditions ranging from the triple point to the critical point. It is demonstrated that the use of ab initio potentials enables systematic improvements to the accuracy of predictions via the addition of theoretically based terms. The contribution of three-body interactions is accounted for using the Axilrod-Teller-Muto plus other multipole contributions and the effective Marcelli-Wang-Sadus potentials. The results indicate that the predictive ability of recent interatomic potentials, obtained from quantum chemical calculations, is comparable to that of accurate empirical models. It is demonstrated that the Marcelli-Wang-Sadus potential can be used in combination with accurate two-body ab initio models for the computationally inexpensive and accurate estimation of vapor-liquid phase equilibria.

  20. TheoReTS - An information system for theoretical spectra based on variational predictions from molecular potential energy and dipole moment surfaces

    NASA Astrophysics Data System (ADS)

    Rey, Michaël; Nikitin, Andrei V.; Babikov, Yurii L.; Tyuterev, Vladimir G.

    2016-09-01

    Knowledge of intensities of rovibrational transitions of various molecules and theirs isotopic species in wide spectral and temperature ranges is essential for the modeling of optical properties of planetary atmospheres, brown dwarfs and for other astrophysical applications. TheoReTS ("Theoretical Reims-Tomsk Spectral data") is an Internet accessible information system devoted to ab initio based rotationally resolved spectra predictions for some relevant molecular species. All data were generated from potential energy and dipole moment surfaces computed via high-level electronic structure calculations using variational methods for vibration-rotation energy levels and transitions. When available, empirical corrections to band centers were applied, all line intensities remaining purely ab initio. The current TheoReTS implementation contains information on four-to-six atomic molecules, including phosphine, methane, ethylene, silane, methyl-fluoride, and their isotopic species 13CH4 , 12CH3D , 12CH2D2 , 12CD4 , 13C2H4, … . Predicted hot methane line lists up to T = 2000 K are included. The information system provides the associated software for spectra simulation including absorption coefficient, absorption and emission cross-sections, transmittance and radiance. The simulations allow Lorentz, Gauss and Voight line shapes. Rectangular, triangular, Lorentzian, Gaussian, sinc and sinc squared apparatus function can be used with user-defined specifications for broadening parameters and spectral resolution. All information is organized as a relational database with the user-friendly graphical interface according to Model-View-Controller architectural tools. The full-featured web application is written on PHP using Yii framework and C++ software modules. In case of very large high-temperature line lists, a data compression is implemented for fast interactive spectra simulations of a quasi-continual absorption due to big line density. Applications for the TheoReTS may

  1. Accurate and robust genomic prediction of celiac disease using statistical learning.

    PubMed

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

    2014-02-01

    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.

  2. Pseudoracemic amino acid complexes: blind predictions for flexible two-component crystals.

    PubMed

    Görbitz, Carl Henrik; Dalhus, Bjørn; Day, Graeme M

    2010-08-14

    Ab initio prediction of the crystal packing in complexes between two flexible molecules is a particularly challenging computational chemistry problem. In this work we present results of single crystal structure determinations as well as theoretical predictions for three 1 ratio 1 complexes between hydrophobic l- and d-amino acids (pseudoracemates), known from previous crystallographic work to form structures with one of two alternative hydrogen bonding arrangements. These are accurately reproduced in the theoretical predictions together with a series of patterns that have never been observed experimentally. In this bewildering forest of potential polymorphs, hydrogen bonding arrangements and molecular conformations, the theoretical predictions succeeded, for all three complexes, in finding the correct hydrogen bonding pattern. For two of the complexes, the calculations also reproduce the exact space group and side chain orientations in the best ranked predicted structure. This includes one complex for which the observed crystal packing clearly contradicted previous experience based on experimental data for a substantial number of related amino acid complexes. The results highlight the significant recent advances that have been made in computational methods for crystal structure prediction.

  3. An empirical/theoretical model with dimensionless numbers to predict the performance of electrodialysis systems on the basis of operating conditions.

    PubMed

    Karimi, Leila; Ghassemi, Abbas

    2016-07-01

    Among the different technologies developed for desalination, the electrodialysis/electrodialysis reversal (ED/EDR) process is one of the most promising for treating brackish water with low salinity when there is high risk of scaling. Multiple researchers have investigated ED/EDR to optimize the process, determine the effects of operating parameters, and develop theoretical/empirical models. Previously published empirical/theoretical models have evaluated the effect of the hydraulic conditions of the ED/EDR on the limiting current density using dimensionless numbers. The reason for previous studies' emphasis on limiting current density is twofold: 1) to maximize ion removal, most ED/EDR systems are operated close to limiting current conditions if there is not a scaling potential in the concentrate chamber due to a high concentration of less-soluble salts; and 2) for modeling the ED/EDR system with dimensionless numbers, it is more accurate and convenient to use limiting current density, where the boundary layer's characteristics are known at constant electrical conditions. To improve knowledge of ED/EDR systems, ED/EDR models should be also developed for the Ohmic region, where operation reduces energy consumption, facilitates targeted ion removal, and prolongs membrane life compared to limiting current conditions. In this paper, theoretical/empirical models were developed for ED/EDR performance in a wide range of operating conditions. The presented ion removal and selectivity models were developed for the removal of monovalent ions and divalent ions utilizing the dominant dimensionless numbers obtained from laboratory scale electrodialysis experiments. At any system scale, these models can predict ED/EDR performance in terms of monovalent and divalent ion removal. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. Toward an Accurate Theoretical Framework for Describing Ensembles for Proteins under Strongly Denaturing Conditions

    PubMed Central

    Tran, Hoang T.; Pappu, Rohit V.

    2006-01-01

    Our focus is on an appropriate theoretical framework for describing highly denatured proteins. In high concentrations of denaturants, proteins behave like polymers in a good solvent and ensembles for denatured proteins can be modeled by ignoring all interactions except excluded volume (EV) effects. To assay conformational preferences of highly denatured proteins, we quantify a variety of properties for EV-limit ensembles of 23 two-state proteins. We find that modeled denatured proteins can be best described as follows. Average shapes are consistent with prolate ellipsoids. Ensembles are characterized by large correlated fluctuations. Sequence-specific conformational preferences are restricted to local length scales that span five to nine residues. Beyond local length scales, chain properties follow well-defined power laws that are expected for generic polymers in the EV limit. The average available volume is filled inefficiently, and cavities of all sizes are found within the interiors of denatured proteins. All properties characterized from simulated ensembles match predictions from rigorous field theories. We use our results to resolve between conflicting proposals for structure in ensembles for highly denatured states. PMID:16766618

  5. 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…

  6. An Interpretable Machine Learning Model for Accurate Prediction of Sepsis in the ICU.

    PubMed

    Nemati, Shamim; Holder, Andre; Razmi, Fereshteh; Stanley, Matthew D; Clifford, Gari D; Buchman, Timothy G

    2018-04-01

    Sepsis is among the leading causes of morbidity, mortality, and cost overruns in critically ill patients. Early intervention with antibiotics improves survival in septic patients. However, no clinically validated system exists for real-time prediction of sepsis onset. We aimed to develop and validate an Artificial Intelligence Sepsis Expert algorithm for early prediction of sepsis. Observational cohort study. Academic medical center from January 2013 to December 2015. Over 31,000 admissions to the ICUs at two Emory University hospitals (development cohort), in addition to over 52,000 ICU patients from the publicly available Medical Information Mart for Intensive Care-III ICU database (validation cohort). Patients who met the Third International Consensus Definitions for Sepsis (Sepsis-3) prior to or within 4 hours of their ICU admission were excluded, resulting in roughly 27,000 and 42,000 patients within our development and validation cohorts, respectively. None. High-resolution vital signs time series and electronic medical record data were extracted. A set of 65 features (variables) were calculated on hourly basis and passed to the Artificial Intelligence Sepsis Expert algorithm to predict onset of sepsis in the proceeding T hours (where T = 12, 8, 6, or 4). Artificial Intelligence Sepsis Expert was used to predict onset of sepsis in the proceeding T hours and to produce a list of the most significant contributing factors. For the 12-, 8-, 6-, and 4-hour ahead prediction of sepsis, Artificial Intelligence Sepsis Expert achieved area under the receiver operating characteristic in the range of 0.83-0.85. Performance of the Artificial Intelligence Sepsis Expert on the development and validation cohorts was indistinguishable. Using data available in the ICU in real-time, Artificial Intelligence Sepsis Expert can accurately predict the onset of sepsis in an ICU patient 4-12 hours prior to clinical recognition. A prospective study is necessary to determine the

  7. Associated t t ¯ production at the LHC: Theoretical predictions at NLO +NNLL accuracy

    NASA Astrophysics Data System (ADS)

    Kulesza, Anna; Motyka, Leszek; Stebel, Tomasz; Theeuwes, Vincent

    2018-06-01

    We perform threshold resummation of soft gluon corrections to the total cross section and the invariant mass distribution for the process p p →t t ¯H . The resummation is carried out at next-to-next-to-leading-logarithmic (NNLL) accuracy using the direct QCD Mellin space technique in the three-particle invariant mass kinematics. After presenting analytical expressions we discuss the impact of resummation on the numerical predictions for the associated Higgs boson production with top quarks at the LHC. We find that next-to-leading-order (NLO)+NNLL resummation leads to predictions for which the central values are remarkably stable with respect to scale variation and for which theoretical uncertainties are reduced in comparison to NLO predictions.

  8. 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.

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

    PubMed Central

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

    2017-01-01

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

  10. Accurate prediction of vaccine stability under real storage conditions and during temperature excursions.

    PubMed

    Clénet, Didier

    2018-04-01

    Due to their thermosensitivity, most vaccines must be kept refrigerated from production to use. To successfully carry out global immunization programs, ensuring the stability of vaccines is crucial. In this context, two important issues are critical, namely: (i) predicting vaccine stability and (ii) preventing product damage due to excessive temperature excursions outside of the recommended storage conditions (cold chain break). We applied a combination of advanced kinetics and statistical analyses on vaccine forced degradation data to accurately describe the loss of antigenicity for a multivalent freeze-dried inactivated virus vaccine containing three variants. The screening of large amounts of kinetic models combined with a statistical model selection approach resulted in the identification of two-step kinetic models. Predictions based on kinetic analysis and experimental stability data were in agreement, with approximately five percentage points difference from real values for long-term stability storage conditions, after excursions of temperature and during experimental shipments of freeze-dried products. Results showed that modeling a few months of forced degradation can be used to predict various time and temperature profiles endured by vaccines, i.e. long-term stability, short time excursions outside the labeled storage conditions or shipments at ambient temperature, with high accuracy. Pharmaceutical applications of the presented kinetics-based approach are discussed. Copyright © 2018 The Author. Published by Elsevier B.V. All rights reserved.

  11. Accurate prediction of X-ray pulse properties from a free-electron laser using machine learning

    DOE PAGES

    Sanchez-Gonzalez, A.; Micaelli, P.; Olivier, C.; ...

    2017-06-05

    Free-electron lasers providing ultra-short high-brightness pulses of X-ray radiation have great potential for a wide impact on science, and are a critical element for unravelling the structural dynamics of matter. To fully harness this potential, we must accurately know the X-ray properties: intensity, spectrum and temporal profile. Owing to the inherent fluctuations in free-electron lasers, this mandates a full characterization of the properties for each and every pulse. While diagnostics of these properties exist, they are often invasive and many cannot operate at a high-repetition rate. Here, we present a technique for circumventing this limitation. Employing a machine learning strategy,more » we can accurately predict X-ray properties for every shot using only parameters that are easily recorded at high-repetition rate, by training a model on a small set of fully diagnosed pulses. Lastly, this opens the door to fully realizing the promise of next-generation high-repetition rate X-ray lasers.« less

  12. Accurate prediction of X-ray pulse properties from a free-electron laser using machine learning

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Sanchez-Gonzalez, A.; Micaelli, P.; Olivier, C.

    Free-electron lasers providing ultra-short high-brightness pulses of X-ray radiation have great potential for a wide impact on science, and are a critical element for unravelling the structural dynamics of matter. To fully harness this potential, we must accurately know the X-ray properties: intensity, spectrum and temporal profile. Owing to the inherent fluctuations in free-electron lasers, this mandates a full characterization of the properties for each and every pulse. While diagnostics of these properties exist, they are often invasive and many cannot operate at a high-repetition rate. Here, we present a technique for circumventing this limitation. Employing a machine learning strategy,more » we can accurately predict X-ray properties for every shot using only parameters that are easily recorded at high-repetition rate, by training a model on a small set of fully diagnosed pulses. Lastly, this opens the door to fully realizing the promise of next-generation high-repetition rate X-ray lasers.« less

  13. Predicting phenolic acid absorption in Caco-2 cells: a theoretical permeability model and mechanistic study.

    PubMed

    Farrell, Tracy L; Poquet, Laure; Dew, Tristan P; Barber, Stuart; Williamson, Gary

    2012-02-01

    There is a considerable need to rationalize the membrane permeability and mechanism of transport for potential nutraceuticals. The aim of this investigation was to develop a theoretical permeability equation, based on a reported descriptive absorption model, enabling calculation of the transcellular component of absorption across Caco-2 monolayers. Published data for Caco-2 permeability of 30 drugs transported by the transcellular route were correlated with the descriptors 1-octanol/water distribution coefficient (log D, pH 7.4) and size, based on molecular mass. Nonlinear regression analysis was used to derive a set of model parameters a', β', and b' with an integrated molecular mass function. The new theoretical transcellular permeability (TTP) model obtained a good fit of the published data (R² = 0.93) and predicted reasonably well (R² = 0.86) the experimental apparent permeability coefficient (P(app)) for nine non-training set compounds reportedly transported by the transcellular route. For the first time, the TTP model was used to predict the absorption characteristics of six phenolic acids, and this original investigation was supported by in vitro Caco-2 cell mechanistic studies, which suggested that deviation of the P(app) value from the predicted transcellular permeability (P(app)(trans)) may be attributed to involvement of active uptake, efflux transporters, or paracellular flux.

  14. Comparison of Theoretically Predicted Electromagnetic Heavy Ion Cross Sections with CERN SPS and RHIC Data

    NASA Astrophysics Data System (ADS)

    Baltz, Anthony J.

    2002-10-01

    Theoretical predictions for a number of electromagnetically induced reactions have been compared with available ultrarelativistic heavy ion data. Calculations for three atomic process have been confronted with CERN SPS data. Theoretically predicted rates are in good agreement with data[1] for bound-electron positron pairs and ionization of single electron heavy ions. Furthermore, the exact solution of the semi-classical Dirac equation in the ultrarelativistic limit reproduces the perturbative scaling result seen in data[2] for continuum pairs (i.e. cross sections go as Z_1^2 Z_2^2). In the area of electromagnetically induced nuclear and hadronic physics, mutual Coulomb dissociation predictions are in good agreement with RHIC Zero Degree Calorimeter measurements[3], and calculations of coherent vector meson production accompanied by mutual Coulomb dissociation[4] are in good agreement with RHIC STAR data[5]. [1] H. F. Krause et al., Phys. Rev. Lett., 80, 1190 (1998). [2] C. R. Vane et al., Phys. Rev. A 56, 3682 (1997). [3] Mickey Chiu et al., Phys. Rev. Lett. 89, 012302 (2002). [4] Anthony J. Baltz, Spencer R. Klein, and Joakim Nystrand, Phys. Rev. Lett. 89, 012301 (2002). [5] C. Adler et al., STAR Collaboration, arXiv:nucl-ex/206004.

  15. Accurate and dynamic predictive model for better prediction in medicine and healthcare.

    PubMed

    Alanazi, H O; Abdullah, A H; Qureshi, K N; Ismail, A S

    2018-05-01

    Information and communication technologies (ICTs) have changed the trend into new integrated operations and methods in all fields of life. The health sector has also adopted new technologies to improve the systems and provide better services to customers. Predictive models in health care are also influenced from new technologies to predict the different disease outcomes. However, still, existing predictive models have suffered from some limitations in terms of predictive outcomes performance. In order to improve predictive model performance, this paper proposed a predictive model by classifying the disease predictions into different categories. To achieve this model performance, this paper uses traumatic brain injury (TBI) datasets. TBI is one of the serious diseases worldwide and needs more attention due to its seriousness and serious impacts on human life. The proposed predictive model improves the predictive performance of TBI. The TBI data set is developed and approved by neurologists to set its features. The experiment results show that the proposed model has achieved significant results including accuracy, sensitivity, and specificity.

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

    PubMed

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

    2015-01-01

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

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

    PubMed Central

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

    2015-01-01

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

  18. A Machine Learned Classifier That Uses Gene Expression Data to Accurately Predict Estrogen Receptor Status

    PubMed Central

    Bastani, Meysam; Vos, Larissa; Asgarian, Nasimeh; Deschenes, Jean; Graham, Kathryn; Mackey, John; Greiner, Russell

    2013-01-01

    Background Selecting the appropriate treatment for breast cancer requires accurately determining the estrogen receptor (ER) status of the tumor. However, the standard for determining this status, immunohistochemical analysis of formalin-fixed paraffin embedded samples, suffers from numerous technical and reproducibility issues. Assessment of ER-status based on RNA expression can provide more objective, quantitative and reproducible test results. Methods To learn a parsimonious RNA-based classifier of hormone receptor status, we applied a machine learning tool to a training dataset of gene expression microarray data obtained from 176 frozen breast tumors, whose ER-status was determined by applying ASCO-CAP guidelines to standardized immunohistochemical testing of formalin fixed tumor. Results This produced a three-gene classifier that can predict the ER-status of a novel tumor, with a cross-validation accuracy of 93.17±2.44%. When applied to an independent validation set and to four other public databases, some on different platforms, this classifier obtained over 90% accuracy in each. In addition, we found that this prediction rule separated the patients' recurrence-free survival curves with a hazard ratio lower than the one based on the IHC analysis of ER-status. Conclusions Our efficient and parsimonious classifier lends itself to high throughput, highly accurate and low-cost RNA-based assessments of ER-status, suitable for routine high-throughput clinical use. This analytic method provides a proof-of-principle that may be applicable to developing effective RNA-based tests for other biomarkers and conditions. PMID:24312637

  19. Quokka: a comprehensive tool for rapid and accurate prediction of kinase family-specific phosphorylation sites in the human proteome.

    PubMed

    Li, Fuyi; Li, Chen; Marquez-Lago, Tatiana T; Leier, André; Akutsu, Tatsuya; Purcell, Anthony W; Smith, A Ian; Lithgow, Trevor; Daly, Roger J; Song, Jiangning; Chou, Kuo-Chen

    2018-06-27

    Kinase-regulated phosphorylation is a ubiquitous type of post-translational modification (PTM) in both eukaryotic and prokaryotic cells. Phosphorylation plays fundamental roles in many signalling pathways and biological processes, such as protein degradation and protein-protein interactions. Experimental studies have revealed that signalling defects caused by aberrant phosphorylation are highly associated with a variety of human diseases, especially cancers. In light of this, a number of computational methods aiming to accurately predict protein kinase family-specific or kinase-specific phosphorylation sites have been established, thereby facilitating phosphoproteomic data analysis. In this work, we present Quokka, a novel bioinformatics tool that allows users to rapidly and accurately identify human kinase family-regulated phosphorylation sites. Quokka was developed by using a variety of sequence scoring functions combined with an optimized logistic regression algorithm. We evaluated Quokka based on well-prepared up-to-date benchmark and independent test datasets, curated from the Phospho.ELM and UniProt databases, respectively. The independent test demonstrates that Quokka improves the prediction performance compared with state-of-the-art computational tools for phosphorylation prediction. In summary, our tool provides users with high-quality predicted human phosphorylation sites for hypothesis generation and biological validation. The Quokka webserver and datasets are freely available at http://quokka.erc.monash.edu/. Supplementary data are available at Bioinformatics online.

  20. Using the load-velocity relationship for 1RM prediction.

    PubMed

    Jidovtseff, Boris; Harris, Nigel K; Crielaard, Jean-Michel; Cronin, John B

    2011-01-01

    The purpose of this study was to investigate the ability of the load-velocity relationship to accurately predict a bench press 1 repetition maximum (1RM). Data from 3 different bench press studies (n = 112) that incorporated both 1RM assessment and submaximal load-velocity profiling were analyzed. Individual regression analysis was performed to determine the theoretical load at zero velocity (LD0). Data from each of the 3 studies were analyzed separately and also presented as overall group mean. Thereafter, correlation analysis provided quantification of the relationships between 1RM and LD0. Practically perfect correlations (r = ∼0.95) were observed in our samples, confirming the ability of the load-velocity profile to accurately predict bench press 1RM.

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

    PubMed

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

    2017-01-09

    The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid costly TF ChIP-seq assays. Thus, it is important to develop computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices. TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq. Additionally, Histone-Marks (HMs) can be used to identify candidate TF binding sites. TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength. Using machine learning, we find low affinity binding sites to improve our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites. Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance. In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq data sets. Finally, these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

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

    PubMed

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

    2017-02-14

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

  3. What predicts depression in cardiac patients: sociodemographic factors, disease severity or theoretical vulnerabilities?

    PubMed

    Doyle, F; McGee, H M; Conroy, R M; Delaney, M

    2011-05-01

    Depression is associated with increased cardiovascular risk in acute coronary syndrome (ACS) patients, but some argue that elevated depression is actually a marker of cardiovascular disease severity. Therefore, disease indices should better predict depression than established theoretical causes of depression (interpersonal life events, reinforcing events, cognitive distortions, type D personality). However, little theory-based research has been conducted in this area. In a cross-sectional design, ACS patients (n = 336) completed questionnaires assessing depression and psychosocial vulnerabilities. Nested logistic regression assessed the relative contribution of demographic or vulnerability factors, or disease indices or vulnerabilities to depression. In multivariate analysis, all vulnerabilities were independent significant predictors of depression (scoring above threshold on any scale, 48%). Demographic variables accounted for <1% of the variance of depression status, with vulnerabilities accounting for significantly more (pseudo R² = 0.16, χ²(change) = 150.9, df = 4, p < 0.001). Disease indices accounted for 7% of the variance in depression (pseudo R² = 0.07, χ² = 137.9, p < 0.001). However, adding the vulnerabilities increased the overall variance explained to 22% (pseudo R² = 0.22, χ² = 58.6, df = 4, p < 0.001). Theoretical vulnerabilities predicted depression status better than did either demographic or disease indices. The presence of these proximal causes of depression suggests that depression in ACS patients is not simply a result of cardiovascular disease severity.

  4. An Extrapolation of a Radical Equation More Accurately Predicts Shelf Life of Frozen Biological Matrices.

    PubMed

    De Vore, Karl W; Fatahi, Nadia M; Sass, John E

    2016-08-01

    Arrhenius modeling of analyte recovery at increased temperatures to predict long-term colder storage stability of biological raw materials, reagents, calibrators, and controls is standard practice in the diagnostics industry. Predicting subzero temperature stability using the same practice is frequently criticized but nevertheless heavily relied upon. We compared the ability to predict analyte recovery during frozen storage using 3 separate strategies: traditional accelerated studies with Arrhenius modeling, and extrapolation of recovery at 20% of shelf life using either ordinary least squares or a radical equation y = B1x(0.5) + B0. Computer simulations were performed to establish equivalence of statistical power to discern the expected changes during frozen storage or accelerated stress. This was followed by actual predictive and follow-up confirmatory testing of 12 chemistry and immunoassay analytes. Linear extrapolations tended to be the most conservative in the predicted percent recovery, reducing customer and patient risk. However, the majority of analytes followed a rate of change that slowed over time, which was fit best to a radical equation of the form y = B1x(0.5) + B0. Other evidence strongly suggested that the slowing of the rate was not due to higher-order kinetics, but to changes in the matrix during storage. Predicting shelf life of frozen products through extrapolation of early initial real-time storage analyte recovery should be considered the most accurate method. Although in this study the time required for a prediction was longer than a typical accelerated testing protocol, there are less potential sources of error, reduced costs, and a lower expenditure of resources. © 2016 American Association for Clinical Chemistry.

  5. Comparisons Between Experimental and Semi-theoretical Cutting Forces of CCS Disc Cutters

    NASA Astrophysics Data System (ADS)

    Xia, Yimin; Guo, Ben; Tan, Qing; Zhang, Xuhui; Lan, Hao; Ji, Zhiyong

    2018-05-01

    This paper focuses on comparisons between the experimental and semi-theoretical forces of CCS disc cutters acting on different rocks. The experimental forces obtained from LCM tests were used to evaluate the prediction accuracy of a semi-theoretical CSM model. The results show that the CSM model reliably predicts the normal forces acting on red sandstone and granite, but underestimates the normal forces acting on marble. Some additional LCM test data from the literature were collected to further explore the ability of the CSM model to predict the normal forces acting on rocks of different strengths. The CSM model underestimates the normal forces acting on soft rocks, semi-hard rocks and hard rocks by approximately 38, 38 and 10%, respectively, but very accurately predicts those acting on very hard and extremely hard rocks. A calibration factor is introduced to modify the normal forces estimated by the CSM model. The overall trend of the calibration factor is characterized by an exponential decrease with increasing rock uniaxial compressive strength. The mean fitting ratios between the normal forces estimated by the modified CSM model and the experimental normal forces acting on soft rocks, semi-hard rocks and hard rocks are 1.076, 0.879 and 1.013, respectively. The results indicate that the prediction accuracy and the reliability of the CSM model have been improved.

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

    PubMed Central

    2014-01-01

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

  7. Does the emergency surgery score accurately predict outcomes in emergent laparotomies?

    PubMed

    Peponis, Thomas; Bohnen, Jordan D; Sangji, Naveen F; Nandan, Anirudh R; Han, Kelsey; Lee, Jarone; Yeh, D Dante; de Moya, Marc A; Velmahos, George C; Chang, David C; Kaafarani, Haytham M A

    2017-08-01

    The emergency surgery score is a mortality-risk calculator for emergency general operation patients. We sought to examine whether the emergency surgery score predicts 30-day morbidity and mortality in a high-risk group of patients undergoing emergent laparotomy. Using the 2011-2012 American College of Surgeons National Surgical Quality Improvement Program database, we identified all patients who underwent emergent laparotomy using (1) the American College of Surgeons National Surgical Quality Improvement Program definition of "emergent," and (2) all Current Procedural Terminology codes denoting a laparotomy, excluding aortic aneurysm rupture. Multivariable logistic regression analyses were performed to measure the correlation (c-statistic) between the emergency surgery score and (1) 30-day mortality, and (2) 30-day morbidity after emergent laparotomy. As sensitivity analyses, the correlation between the emergency surgery score and 30-day mortality was also evaluated in prespecified subgroups based on Current Procedural Terminology codes. A total of 26,410 emergent laparotomy patients were included. Thirty-day mortality and morbidity were 10.2% and 43.8%, respectively. The emergency surgery score correlated well with mortality (c-statistic = 0.84); scores of 1, 11, and 22 correlated with mortalities of 0.4%, 39%, and 100%, respectively. Similarly, the emergency surgery score correlated well with morbidity (c-statistic = 0.74); scores of 0, 7, and 11 correlated with complication rates of 13%, 58%, and 79%, respectively. The morbidity rates plateaued for scores higher than 11. Sensitivity analyses demonstrated that the emergency surgery score effectively predicts mortality in patients undergoing emergent (1) splenic, (2) gastroduodenal, (3) intestinal, (4) hepatobiliary, or (5) incarcerated ventral hernia operation. The emergency surgery score accurately predicts outcomes in all types of emergent laparotomy patients and may prove valuable as a bedside decision

  8. MnNiO3 revisited with modern theoretical and experimental methods

    NASA Astrophysics Data System (ADS)

    Dzubak, Allison L.; Mitra, Chandrima; Chance, Michael; Kuhn, Stephen; Jellison, Gerald E.; Sefat, Athena S.; Krogel, Jaron T.; Reboredo, Fernando A.

    2017-11-01

    MnNiO3 is a strongly correlated transition metal oxide that has recently been investigated theoretically for its potential application as an oxygen-evolution photocatalyst. However, there is no experimental report on critical quantities such as the band gap or bulk modulus. Recent theoretical predictions with standard functionals such as LDA+U and HSE show large discrepancies in the band gaps (about 1.23 eV), depending on the nature of the functional used. Hence there is clearly a need for an accurate quantitative prediction of the band gap to gauge its utility as a photocatalyst. In this work, we present a diffusion quantum Monte Carlo study of the bulk properties of MnNiO3 and revisit the synthesis and experimental properties of the compound. We predict quasiparticle band gaps of 2.0(5) eV and 3.8(6) eV for the majority and minority spin channels, respectively, and an equilibrium volume of 92.8 Å3, which compares well to the experimental value of 94.4 Å3. A bulk modulus of 217 GPa is predicted for MnNiO3. We rationalize the difficulty for the formation of ordered ilmenite-type structure with specific sites for Ni and Mn to be potentially due to the formation of antisite defects that form during synthesis, which ultimately affects the physical properties of MnNiO3.

  9. 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. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  10. Theoretical prediction of gold vein location in deposits originated by a wall magma intrusion

    NASA Astrophysics Data System (ADS)

    Martin, Pablo; Maass-Artigas, Fernando; Cortés-Vega, Luis

    2016-05-01

    The isotherm time-evolution resulting from the intrusion of a hot dike in a cold rock is analized considering the general case of nonvertical walls. This is applied to the theoretical prediction of the gold veins location due to isothermal evolution. As in previous treatments earth surface effects are considered and the gold veins are determined by the envelope of the isotherms. The locations of the gold veins in the Callao mines of Venezuela are now well predicted. The new treatment is now more elaborated and complex that in the case of vertical walls, performed in previous papers, but it is more adequated to the real cases as the one in El Callao, where the wall is not vertical.

  11. 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.

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

    PubMed

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

    2016-05-07

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

  13. Accuracy of color prediction of anthraquinone dyes in methanol solution estimated from first principle quantum chemistry computations.

    PubMed

    Cysewski, Piotr; Jeliński, Tomasz

    2013-10-01

    The electronic spectrum of four different anthraquinones (1,2-dihydroxyanthraquinone, 1-aminoanthraquinone, 2-aminoanthraquinone and 1-amino-2-methylanthraquinone) in methanol solution was measured and used as reference data for theoretical color prediction. The visible part of the spectrum was modeled according to TD-DFT framework with a broad range of DFT functionals. The convoluted theoretical spectra were validated against experimental data by a direct color comparison in terms of CIE XYZ and CIE Lab tristimulus model color. It was found, that the 6-31G** basis set provides the most accurate color prediction and there is no need to extend the basis set since it does not improve the prediction of color. Although different functionals were found to give the most accurate color prediction for different anthraquinones, it is possible to apply the same DFT approach for the whole set of analyzed dyes. Especially three functionals seem to be valuable, namely mPW1LYP, B1LYP and PBE0 due to very similar spectra predictions. The major source of discrepancies between theoretical and experimental spectra comes from L values, representing the lightness, and the a parameter, depicting the position on green→magenta axis. Fortunately, the agreement between computed and observed blue→yellow axis (parameter b) is very precise in the case of studied anthraquinone dyes in methanol solution. Despite discussed shortcomings, color prediction from first principle quantum chemistry computations can lead to quite satisfactory results, expressed in terms of color space parameters.

  14. Can a numerically stable subgrid-scale model for turbulent flow computation be ideally accurate?: a preliminary theoretical study for the Gaussian filtered Navier-Stokes equations.

    PubMed

    Ida, Masato; Taniguchi, Nobuyuki

    2003-09-01

    This paper introduces a candidate for the origin of the numerical instabilities in large eddy simulation repeatedly observed in academic and practical industrial flow computations. Without resorting to any subgrid-scale modeling, but based on a simple assumption regarding the streamwise component of flow velocity, it is shown theoretically that in a channel-flow computation, the application of the Gaussian filtering to the incompressible Navier-Stokes equations yields a numerically unstable term, a cross-derivative term, which is similar to one appearing in the Gaussian filtered Vlasov equation derived by Klimas [J. Comput. Phys. 68, 202 (1987)] and also to one derived recently by Kobayashi and Shimomura [Phys. Fluids 15, L29 (2003)] from the tensor-diffusivity subgrid-scale term in a dynamic mixed model. The present result predicts that not only the numerical methods and the subgrid-scale models employed but also only the applied filtering process can be a seed of this numerical instability. An investigation concerning the relationship between the turbulent energy scattering and the unstable term shows that the instability of the term does not necessarily represent the backscatter of kinetic energy which has been considered a possible origin of numerical instabilities in large eddy simulation. The present findings raise the question whether a numerically stable subgrid-scale model can be ideally accurate.

  15. Does mesenteric venous imaging assessment accurately predict pathologic invasion in localized pancreatic ductal adenocarcinoma?

    PubMed

    Clanton, Jesse; Oh, Stephen; Kaplan, Stephen J; Johnson, Emily; Ross, Andrew; Kozarek, Richard; Alseidi, Adnan; Biehl, Thomas; Picozzi, Vincent J; Helton, William S; Coy, David; Dorer, Russell; Rocha, Flavio G

    2018-05-09

    Accurate prediction of mesenteric venous involvement in pancreatic ductal adenocarcinoma (PDAC) is necessary for adequate staging and treatment. A retrospective cohort study was conducted in PDAC patients at a single institution. All patients with resected PDAC and staging CT and EUS between 2003 and 2014 were included and sub-divided into "upfront resected" and "neoadjuvant chemotherapy (NAC)" groups. Independent imaging re-review was correlated to venous resection and venous invasion. Sensitivity, specificity, positive and negative predictive values were then calculated. A total of 109 patients underwent analysis, 60 received upfront resection, and 49 NAC. Venous resection (30%) and vein invasion (13%) was less common in patients resected upfront than those who received NAC (53% and 16%, respectively). Both CT and EUS had poor sensitivity (14-44%) but high specificity (75-95%) for detecting venous resection and vein invasion in patients resected upfront, whereas sensitivity was high (84-100%) and specificity was low (27-44%) after NAC. Preoperative CT and EUS in PDAC have similar efficacy but different predictive capacity in assessing mesenteric venous involvement depending on whether patients are resected upfront or received NAC. Both modalities appear to significantly overestimate true vascular involvement and should be interpreted in the appropriate clinical context. Copyright © 2018 International Hepato-Pancreato-Biliary Association Inc. Published by Elsevier Ltd. All rights reserved.

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

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

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

  17. Accurate secondary structure prediction and fold recognition for circular dichroism spectroscopy

    PubMed Central

    Micsonai, András; Wien, Frank; Kernya, Linda; Lee, Young-Ho; Goto, Yuji; Réfrégiers, Matthieu; Kardos, József

    2015-01-01

    Circular dichroism (CD) spectroscopy is a widely used technique for the study of protein structure. Numerous algorithms have been developed for the estimation of the secondary structure composition from the CD spectra. These methods often fail to provide acceptable results on α/β-mixed or β-structure–rich proteins. The problem arises from the spectral diversity of β-structures, which has hitherto been considered as an intrinsic limitation of the technique. The predictions are less reliable for proteins of unusual β-structures such as membrane proteins, protein aggregates, and amyloid fibrils. Here, we show that the parallel/antiparallel orientation and the twisting of the β-sheets account for the observed spectral diversity. We have developed a method called β-structure selection (BeStSel) for the secondary structure estimation that takes into account the twist of β-structures. This method can reliably distinguish parallel and antiparallel β-sheets and accurately estimates the secondary structure for a broad range of proteins. Moreover, the secondary structure components applied by the method are characteristic to the protein fold, and thus the fold can be predicted to the level of topology in the CATH classification from a single CD spectrum. By constructing a web server, we offer a general tool for a quick and reliable structure analysis using conventional CD or synchrotron radiation CD (SRCD) spectroscopy for the protein science research community. The method is especially useful when X-ray or NMR techniques fail. Using BeStSel on data collected by SRCD spectroscopy, we investigated the structure of amyloid fibrils of various disease-related proteins and peptides. PMID:26038575

  18. Theoretical prediction and atomic kinetic Monte Carlo simulations of void superlattice self-organization under irradiation.

    PubMed

    Gao, Yipeng; Zhang, Yongfeng; Schwen, Daniel; Jiang, Chao; Sun, Cheng; Gan, Jian; Bai, Xian-Ming

    2018-04-26

    Nano-structured superlattices may have novel physical properties and irradiation is a powerful mean to drive their self-organization. However, the formation mechanism of superlattice under irradiation is still open for debate. Here we use atomic kinetic Monte Carlo simulations in conjunction with a theoretical analysis to understand and predict the self-organization of nano-void superlattices under irradiation, which have been observed in various types of materials for more than 40 years but yet to be well understood. The superlattice is found to be a result of spontaneous precipitation of voids from the matrix, a process similar to phase separation in regular solid solution, with the symmetry dictated by anisotropic materials properties such as one-dimensional interstitial atom diffusion. This discovery challenges the widely accepted empirical rule of the coherency between the superlattice and host matrix crystal lattice. The atomic scale perspective has enabled a new theoretical analysis to successfully predict the superlattice parameters, which are in good agreement with independent experiments. The theory developed in this work can provide guidelines for designing target experiments to tailor desired microstructure under irradiation. It may also be generalized for situations beyond irradiation, such as spontaneous phase separation with reaction.

  19. Towards accurate cosmological predictions for rapidly oscillating scalar fields as dark matter

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Ureña-López, L. Arturo; Gonzalez-Morales, Alma X., E-mail: lurena@ugto.mx, E-mail: alma.gonzalez@fisica.ugto.mx

    2016-07-01

    As we are entering the era of precision cosmology, it is necessary to count on accurate cosmological predictions from any proposed model of dark matter. In this paper we present a novel approach to the cosmological evolution of scalar fields that eases their analytic and numerical analysis at the background and at the linear order of perturbations. The new method makes use of appropriate angular variables that simplify the writing of the equations of motion, and which also show that the usual field variables play a secondary role in the cosmological dynamics. We apply the method to a scalar fieldmore » endowed with a quadratic potential and revisit its properties as dark matter. Some of the results known in the literature are recovered, and a better understanding of the physical properties of the model is provided. It is confirmed that there exists a Jeans wavenumber k {sub J} , directly related to the suppression of linear perturbations at wavenumbers k > k {sub J} , and which is verified to be k {sub J} = a √ mH . We also discuss some semi-analytical results that are well satisfied by the full numerical solutions obtained from an amended version of the CMB code CLASS. Finally we draw some of the implications that this new treatment of the equations of motion may have in the prediction of cosmological observables from scalar field dark matter models.« less

  20. 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

  1. Theoretical prediction of the energy stability of graphene nanoblisters

    NASA Astrophysics Data System (ADS)

    Glukhova, O. E.; Slepchenkov, M. M.; Barkov, P. V.

    2018-04-01

    The paper presents the results of a theoretical prediction of the energy stability of graphene nanoblisters with various geometrical parameters. As a criterion for the evaluation of the stability of investigated carbon objects we propose to consider the value of local stress of the nanoblister atomic grid. Numerical evaluation of stresses experienced by atoms of the graphene blister framework was carried out by means of an original method for calculation of local stresses that is based on energy approach. Atomistic models of graphene nanoblisters corresponding to the natural experiment data were built for the first time in this work. New physical regularities of the influence of topology on the thermodynamic stability of nanoblisters were established as a result of the analysis of the numerical experiment data. We built the distribution of local stresses for graphene blister structures, whose atomic grid contains a variety of structural defects. We have shown how the concentration and location of defects affect the picture of the distribution of the maximum stresses experienced by the atoms of the nanoblisters.

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

    EPA Pesticide Factsheets

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

  3. PredSTP: a highly accurate SVM based model to predict sequential cystine stabilized peptides.

    PubMed

    Islam, S M Ashiqul; Sajed, Tanvir; Kearney, Christopher Michel; Baker, Erich J

    2015-07-05

    Numerous organisms have evolved a wide range of toxic peptides for self-defense and predation. Their effective interstitial and macro-environmental use requires energetic and structural stability. One successful group of these peptides includes a tri-disulfide domain arrangement that offers toxicity and high stability. Sequential tri-disulfide connectivity variants create highly compact disulfide folds capable of withstanding a variety of environmental stresses. Their combination of toxicity and stability make these peptides remarkably valuable for their potential as bio-insecticides, antimicrobial peptides and peptide drug candidates. However, the wide sequence variation, sources and modalities of group members impose serious limitations on our ability to rapidly identify potential members. As a result, there is a need for automated high-throughput member classification approaches that leverage their demonstrated tertiary and functional homology. We developed an SVM-based model to predict sequential tri-disulfide peptide (STP) toxins from peptide sequences. One optimized model, called PredSTP, predicted STPs from training set with sensitivity, specificity, precision, accuracy and a Matthews correlation coefficient of 94.86%, 94.11%, 84.31%, 94.30% and 0.86, respectively, using 200 fold cross validation. The same model outperforms existing prediction approaches in three independent out of sample testsets derived from PDB. PredSTP can accurately identify a wide range of cystine stabilized peptide toxins directly from sequences in a species-agnostic fashion. The ability to rapidly filter sequences for potential bioactive peptides can greatly compress the time between peptide identification and testing structural and functional properties for possible antimicrobial and insecticidal candidates. A web interface is freely available to predict STP toxins from http://crick.ecs.baylor.edu/.

  4. 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.

  5. MnNiO 3 revisited with modern theoretical and experimental methods

    DOE PAGES

    Dzubak, Allison L.; Mitra, Chandrima; Chance, Michael; ...

    2017-11-03

    MnNiO 3 is a strongly correlated transition metal oxide that has recently been investigated theoretically for its potential application as an oxygen-evolution photocatalyst. However, there is no experimental report on critical quantities such as the band gap or bulk modulus. Recent theoretical predictions with standard functionals such as LDA+U and HSE show large discrepancies in the band gaps (about 1.23 eV), depending on the nature of the functional used. Hence there is clearly a need for an accurate quantitative prediction of the band gap to gauge its utility as a photocatalyst. In this work, we present a diffusion quantum Montemore » Carlo study of the bulk properties of MnNiO 3 and revisit the synthesis and experimental properties of the compound. We predict quasiparticle band gaps of 2.0(5) eV and 3.8(6) eV for the majority and minority spin channels, respectively, and an equilibrium volume of 92.8 Å 3, which compares well to the experimental value of 94.4 Å 3. A bulk modulus of 217 GPa is predicted for MnNiO 3. As a result, we rationalize the difficulty for the formation of ordered ilmenite-type structure with specific sites for Ni and Mn to be potentially due to the formation of antisite defects that form during synthesis, which ultimately affects the physical properties of MnNiO 3.« less

  6. MnNiO 3 revisited with modern theoretical and experimental methods

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Dzubak, Allison L.; Mitra, Chandrima; Chance, Michael

    MnNiO 3 is a strongly correlated transition metal oxide that has recently been investigated theoretically for its potential application as an oxygen-evolution photocatalyst. However, there is no experimental report on critical quantities such as the band gap or bulk modulus. Recent theoretical predictions with standard functionals such as LDA+U and HSE show large discrepancies in the band gaps (about 1.23 eV), depending on the nature of the functional used. Hence there is clearly a need for an accurate quantitative prediction of the band gap to gauge its utility as a photocatalyst. In this work, we present a diffusion quantum Montemore » Carlo study of the bulk properties of MnNiO 3 and revisit the synthesis and experimental properties of the compound. We predict quasiparticle band gaps of 2.0(5) eV and 3.8(6) eV for the majority and minority spin channels, respectively, and an equilibrium volume of 92.8 Å 3, which compares well to the experimental value of 94.4 Å 3. A bulk modulus of 217 GPa is predicted for MnNiO 3. As a result, we rationalize the difficulty for the formation of ordered ilmenite-type structure with specific sites for Ni and Mn to be potentially due to the formation of antisite defects that form during synthesis, which ultimately affects the physical properties of MnNiO 3.« less

  7. Human Emotion Experiences Can Be Predicted on Theoretical Grounds: Evidence from Verbal Labeling

    PubMed Central

    Scherer, Klaus R.; Meuleman, Ben

    2013-01-01

    In an effort to demonstrate that the verbal labeling of emotional experiences obeys lawful principles, we tested the feasibility of using an expert system called the Geneva Emotion Analyst (GEA), which generates predictions based on an appraisal theory of emotion. Several thousand respondents participated in an Internet survey that applied GEA to self-reported emotion experiences. Users recalled appraisals of emotion-eliciting events and labeled the experienced emotion with one or two words, generating a massive data set on realistic, intense emotions in everyday life. For a final sample of 5969 respondents we show that GEA achieves a high degree of predictive accuracy by matching a user’s appraisal input to one of 13 theoretically predefined emotion prototypes. The first prediction was correct in 51% of the cases and the overall diagnosis was considered as at least partially correct or appropriate in more than 90% of all cases. These results support a component process model that encourages focused, hypothesis-guided research on elicitation and differentiation, memory storage and retrieval, and categorization and labeling of emotion episodes. We discuss the implications of these results for the study of emotion terms in natural language semantics. PMID:23483988

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

    PubMed

    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. Uniting Cheminformatics and Chemical Theory To Predict the Intrinsic Aqueous Solubility of Crystalline Druglike Molecules

    PubMed Central

    2014-01-01

    We present four models of solution free-energy prediction for druglike molecules utilizing cheminformatics descriptors and theoretically calculated thermodynamic values. We make predictions of solution free energy using physics-based theory alone and using machine learning/quantitative structure–property relationship (QSPR) models. We also develop machine learning models where the theoretical energies and cheminformatics descriptors are used as combined input. These models are used to predict solvation free energy. While direct theoretical calculation does not give accurate results in this approach, machine learning is able to give predictions with a root mean squared error (RMSE) of ∼1.1 log S units in a 10-fold cross-validation for our Drug-Like-Solubility-100 (DLS-100) dataset of 100 druglike molecules. We find that a model built using energy terms from our theoretical methodology as descriptors is marginally less predictive than one built on Chemistry Development Kit (CDK) descriptors. Combining both sets of descriptors allows a further but very modest improvement in the predictions. However, in some cases, this is a statistically significant enhancement. These results suggest that there is little complementarity between the chemical information provided by these two sets of descriptors, despite their different sources and methods of calculation. Our machine learning models are also able to predict the well-known Solubility Challenge dataset with an RMSE value of 0.9–1.0 log S units. PMID:24564264

  10. Theoretical predictions for hot-carrier generation from surface plasmon decay

    PubMed Central

    Sundararaman, Ravishankar; Narang, Prineha; Jermyn, Adam S.; Goddard III, William A.; Atwater, Harry A.

    2014-01-01

    Decay of surface plasmons to hot carriers finds a wide variety of applications in energy conversion, photocatalysis and photodetection. However, a detailed theoretical description of plasmonic hot-carrier generation in real materials has remained incomplete. Here we report predictions for the prompt distributions of excited ‘hot’ electrons and holes generated by plasmon decay, before inelastic relaxation, using a quantized plasmon model with detailed electronic structure. We find that carrier energy distributions are sensitive to the electronic band structure of the metal: gold and copper produce holes hotter than electrons by 1–2 eV, while silver and aluminium distribute energies more equitably between electrons and holes. Momentum-direction distributions for hot carriers are anisotropic, dominated by the plasmon polarization for aluminium and by the crystal orientation for noble metals. We show that in thin metallic films intraband transitions can alter the carrier distributions, producing hotter electrons in gold, but interband transitions remain dominant. PMID:25511713

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

    PubMed

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

    2014-01-01

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

  12. Theoretical study for aerial image intensity in resist in high numerical aperture projection optics and experimental verification with one-dimensional patterns

    NASA Astrophysics Data System (ADS)

    Shibuya, Masato; Takada, Akira; Nakashima, Toshiharu

    2016-04-01

    In optical lithography, high-performance exposure tools are indispensable to obtain not only fine patterns but also preciseness in pattern width. Since an accurate theoretical method is necessary to predict these values, some pioneer and valuable studies have been proposed. However, there might be some ambiguity or lack of consensus regarding the treatment of diffraction by object, incoming inclination factor onto image plane in scalar imaging theory, and paradoxical phenomenon of the inclined entrance plane wave onto image in vector imaging theory. We have reconsidered imaging theory in detail and also phenomenologically resolved the paradox. By comparing theoretical aerial image intensity with experimental pattern width for one-dimensional pattern, we have validated our theoretical consideration.

  13. Towards more accurate vegetation mortality predictions

    DOE PAGES

    Sevanto, Sanna Annika; Xu, Chonggang

    2016-09-26

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

  14. Theoretical predictions of a bucky-diamond SiC cluster.

    PubMed

    Yu, Ming; Jayanthi, C S; Wu, S Y

    2012-06-15

    A study of structural relaxations of Si(n)C(m) clusters corresponding to different compositions, different relative arrangements of Si/C atoms, and different types of initial structure, reveals that the Si(n)C(m) bucky-diamond structure can be obtained for an initial network structure constructed from a truncated bulk 3C-SiC for a magic composition corresponding to n = 68 and m = 79. This study was performed using a semi-empirical Hamiltonian (SCED-LCAO) since it allowed an extensive search of different types of initial structures. However, the bucky-diamond structure predicted by this method was also confirmed by a more accurate density functional theory (DFT) based method. The bucky-diamond structure exhibited by a SiC-based system represents an interesting paradigm where a Si atom can form three-coordinated as well as four-coordinated networks with carbon atoms and vice versa and with both types of network co-existing in the same structure. Specifically, the bucky-diamond structure of the Si(68)C(79) cluster consists of a 35-atom diamond-like inner core (four-atom coordinations) suspended inside a 112-atom fullerene-like shell (three-atom coordinations).

  15. Theoretical prediction of pullout strengths for dental and orthopaedic screws with conical profile and buttress threads.

    PubMed

    Shih, Kao-Shang; Hou, Sheng-Mou; Lin, Shang-Chih

    2017-12-01

    The pullout strength of a screw is an indicator of how secure bone fragments are being held in place. Such bone-purchasing ability is sensitive to bone quality, thread design, and the pilot hole, and is often evaluated by experimental and numerical methods. Historically, there are some mathematical formulae to simulate the screw withdrawal from the synthetic bone. There are great variations in screw specifications. However, extensive investigation of the correlation between experimental and analytical results has not been reported in literature. Referring to the literature formulae, this study aims to evaluate the differences in the calculated pullout strengths. The pullout tests of the surgical screws are measured and the sawbone is used as the testing block. The absolute errors and correlation coefficients of the experimental and analytical results are calculated as the comparison baselines of the formulae. The absolute error of the dental, traumatic, and spinal groups are 21.7%, 95.5%, and 37.0%, respectively. For the screws with a conical profile and/or tiny threads, the calculated and measured results are not well correlated. The formulae are not accurate indicators of the pullout strengths of the screws where the design parameters are slightly varied. However, the experimental and numerical results are highly correlated for the cylindrical screws. The pullout strength of a conical screw is higher than that of its counterpart, but all formulae consistently predict the opposite results. In general, the bony purchase of the buttress threads is securer than that of the symmetric thread. An absolute error of up to 51.4% indicates the theoretical results cannot predict the actual value of the pullout strength. Only thread diameter, pitch, and depth are considered in the investigated formulae. The thread profile and shape should be formulated to modify the slippage mechanism at the bone-screw interfaces and simulate the strength change in the squeezed bones

  16. Reference dosimetry at the Australian Synchrotron's imaging and medical beamline using free-air ionization chamber measurements and theoretical predictions of air kerma rate and half value layer

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Crosbie, Jeffrey C.; Rogers, Peter A. W.; Stevenson, Andrew W.

    2013-06-15

    Purpose: Novel, preclinical radiotherapy modalities are being developed at synchrotrons around the world, most notably stereotactic synchrotron radiation therapy and microbeam radiotherapy at the European Synchrotron Radiation Facility in Grenoble, France. The imaging and medical beamline (IMBL) at the Australian Synchrotron has recently become available for preclinical radiotherapy and imaging research with clinical trials, a distinct possibility in the coming years. The aim of this present study was to accurately characterize the synchrotron-generated x-ray beam for the purposes of air kerma-based absolute dosimetry. Methods: The authors used a theoretical model of the energy spectrum from the wiggler source and validatedmore » this model by comparing the transmission through copper absorbers (0.1-3.0 mm) against real measurements conducted at the beamline. The authors used a low energy free air ionization chamber (LEFAC) from the Australian Radiation Protection and Nuclear Safety Agency and a commercially available free air chamber (ADC-105) for the measurements. The dimensions of these two chambers are different from one another requiring careful consideration of correction factors. Results: Measured and calculated half value layer (HVL) and air kerma rates differed by less than 3% for the LEFAC when the ion chamber readings were corrected for electron energy loss and ion recombination. The agreement between measured and predicted air kerma rates was less satisfactory for the ADC-105 chamber, however. The LEFAC and ADC measurements produced a first half value layer of 0.405 {+-} 0.015 and 0.412 {+-} 0.016 mm Cu, respectively, compared to the theoretical prediction of 0.427 {+-} 0.012 mm Cu. The theoretical model based upon a spectrum calculator derived a mean beam energy of 61.4 keV with a first half value layer of approximately 30 mm in water. Conclusions: The authors showed in this study their ability to verify the predicted air kerma rate and x

  17. 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.

  18. Reliable and accurate point-based prediction of cumulative infiltration using soil readily available characteristics: A comparison between GMDH, ANN, and MLR

    NASA Astrophysics Data System (ADS)

    Rahmati, Mehdi

    2017-08-01

    Developing accurate and reliable pedo-transfer functions (PTFs) to predict soil non-readily available characteristics is one of the most concerned topic in soil science and selecting more appropriate predictors is a crucial factor in PTFs' development. Group method of data handling (GMDH), which finds an approximate relationship between a set of input and output variables, not only provide an explicit procedure to select the most essential PTF input variables, but also results in more accurate and reliable estimates than other mostly applied methodologies. Therefore, the current research was aimed to apply GMDH in comparison with multivariate linear regression (MLR) and artificial neural network (ANN) to develop several PTFs to predict soil cumulative infiltration point-basely at specific time intervals (0.5-45 min) using soil readily available characteristics (RACs). In this regard, soil infiltration curves as well as several soil RACs including soil primary particles (clay (CC), silt (Si), and sand (Sa)), saturated hydraulic conductivity (Ks), bulk (Db) and particle (Dp) densities, organic carbon (OC), wet-aggregate stability (WAS), electrical conductivity (EC), and soil antecedent (θi) and field saturated (θfs) water contents were measured at 134 different points in Lighvan watershed, northwest of Iran. Then, applying GMDH, MLR, and ANN methodologies, several PTFs have been developed to predict cumulative infiltrations using two sets of selected soil RACs including and excluding Ks. According to the test data, results showed that developed PTFs by GMDH and MLR procedures using all soil RACs including Ks resulted in more accurate (with E values of 0.673-0.963) and reliable (with CV values lower than 11 percent) predictions of cumulative infiltrations at different specific time steps. In contrast, ANN procedure had lower accuracy (with E values of 0.356-0.890) and reliability (with CV values up to 50 percent) compared to GMDH and MLR. The results also revealed

  19. Perceived Physician-informed Weight Status Predicts Accurate Weight Self-Perception and Weight Self-Regulation in Low-income, African American Women.

    PubMed

    Harris, Charlie L; Strayhorn, Gregory; Moore, Sandra; Goldman, Brian; Martin, Michelle Y

    2016-01-01

    Obese African American women under-appraise their body mass index (BMI) classification and report fewer weight loss attempts than women who accurately appraise their weight status. This cross-sectional study examined whether physician-informed weight status could predict weight self-perception and weight self-regulation strategies in obese women. A convenience sample of 118 low-income women completed a survey assessing demographic characteristics, comorbidities, weight self-perception, and weight self-regulation strategies. BMI was calculated during nurse triage. Binary logistic regression models were performed to test hypotheses. The odds of obese accurate appraisers having been informed about their weight status were six times greater than those of under-appraisers. The odds of those using an "approach" self-regulation strategy having been physician-informed were four times greater compared with those using an "avoidance" strategy. Physicians are uniquely positioned to influence accurate weight self-perception and adaptive weight self-regulation strategies in underserved women, reducing their risk for obesity-related morbidity.

  20. Predicted osteotomy planes are accurate when using patient-specific instrumentation for total knee arthroplasty in cadavers: a descriptive analysis.

    PubMed

    Kievit, A J; Dobbe, J G G; Streekstra, G J; Blankevoort, L; Schafroth, M U

    2018-06-01

    Malalignment of implants is a major source of failure during total knee arthroplasty. To achieve more accurate 3D planning and execution of the osteotomy cuts during surgery, the Signature (Biomet, Warsaw) patient-specific instrumentation (PSI) was used to produce pin guides for the positioning of the osteotomy blocks by means of computer-aided manufacture based on CT scan images. The research question of this study is: what is the transfer accuracy of osteotomy planes predicted by the Signature PSI system for preoperative 3D planning and intraoperative block-guided pin placement to perform total knee arthroplasty procedures? The transfer accuracy achieved by using the Signature PSI system was evaluated by comparing the osteotomy planes predicted preoperatively with the osteotomy planes seen intraoperatively in human cadaveric legs. Outcomes were measured in terms of translational and rotational errors (varus, valgus, flexion, extension and axial rotation) for both tibia and femur osteotomies. Average translational errors between the osteotomy planes predicted using the Signature system and the actual osteotomy planes achieved was 0.8 mm (± 0.5 mm) for the tibia and 0.7 mm (± 4.0 mm) for the femur. Average rotational errors in relation to predicted and achieved osteotomy planes were 0.1° (± 1.2°) of varus and 0.4° (± 1.7°) of anterior slope (extension) for the tibia, and 2.8° (± 2.0°) of varus and 0.9° (± 2.7°) of flexion and 1.4° (± 2.2°) of external rotation for the femur. The similarity between osteotomy planes predicted using the Signature system and osteotomy planes actually achieved was excellent for the tibia although some discrepancies were seen for the femur. The use of 3D system techniques in TKA surgery can provide accurate intraoperative guidance, especially for patients with deformed bone, tailored to individual patients and ensure better placement of the implant.

  1. A Theoretical Model for Predicting Fracture Strength and Critical Flaw Size of the ZrB2-ZrC Composites at High Temperatures

    NASA Astrophysics Data System (ADS)

    Wang, Ruzhuan; Li, Xiaobo; Wang, Jing; Jia, Bi; Li, Weiguo

    2018-06-01

    This work shows a new rational theoretical model for quantitatively predicting fracture strength and critical flaw size of the ZrB2-ZrC composites at different temperatures, which is based on a new proposed temperature dependent fracture surface energy model and the Griffith criterion. The fracture model takes into account the combined effects of temperature and damage terms (surface flaws and internal flaws) with no any fitting parameters. The predictions of fracture strength and critical flaw size of the ZrB2-ZrC composites at high temperatures agree well with experimental data. Then using the theoretical method, the improvement and design of materials are proposed. The proposed model can be used to predict the fracture strength, find the critical flaw and study the effects of microstructures on the fracture mechanism of the ZrB2-ZrC composites at high temperatures, which thus could become a potential convenient, practical and economical technical means for predicting fracture properties and material design.

  2. CodingQuarry: highly accurate hidden Markov model gene prediction in fungal genomes using RNA-seq transcripts.

    PubMed

    Testa, Alison C; Hane, James K; Ellwood, Simon R; Oliver, Richard P

    2015-03-11

    The impact of gene annotation quality on functional and comparative genomics makes gene prediction an important process, particularly in non-model species, including many fungi. Sets of homologous protein sequences are rarely complete with respect to the fungal species of interest and are often small or unreliable, especially when closely related species have not been sequenced or annotated in detail. In these cases, protein homology-based evidence fails to correctly annotate many genes, or significantly improve ab initio predictions. Generalised hidden Markov models (GHMM) have proven to be invaluable tools in gene annotation and, recently, RNA-seq has emerged as a cost-effective means to significantly improve the quality of automated gene annotation. As these methods do not require sets of homologous proteins, improving gene prediction from these resources is of benefit to fungal researchers. While many pipelines now incorporate RNA-seq data in training GHMMs, there has been relatively little investigation into additionally combining RNA-seq data at the point of prediction, and room for improvement in this area motivates this study. CodingQuarry is a highly accurate, self-training GHMM fungal gene predictor designed to work with assembled, aligned RNA-seq transcripts. RNA-seq data informs annotations both during gene-model training and in prediction. Our approach capitalises on the high quality of fungal transcript assemblies by incorporating predictions made directly from transcript sequences. Correct predictions are made despite transcript assembly problems, including those caused by overlap between the transcripts of adjacent gene loci. Stringent benchmarking against high-confidence annotation subsets showed CodingQuarry predicted 91.3% of Schizosaccharomyces pombe genes and 90.4% of Saccharomyces cerevisiae genes perfectly. These results are 4-5% better than those of AUGUSTUS, the next best performing RNA-seq driven gene predictor tested. Comparisons against

  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. pDeep: Predicting MS/MS Spectra of Peptides with Deep Learning.

    PubMed

    Zhou, Xie-Xuan; Zeng, Wen-Feng; Chi, Hao; Luo, Chunjie; Liu, Chao; Zhan, Jianfeng; He, Si-Min; Zhang, Zhifei

    2017-12-05

    In tandem mass spectrometry (MS/MS)-based proteomics, search engines rely on comparison between an experimental MS/MS spectrum and the theoretical spectra of the candidate peptides. Hence, accurate prediction of the theoretical spectra of peptides appears to be particularly important. Here, we present pDeep, a deep neural network-based model for the spectrum prediction of peptides. Using the bidirectional long short-term memory (BiLSTM), pDeep can predict higher-energy collisional dissociation, electron-transfer dissociation, and electron-transfer and higher-energy collision dissociation MS/MS spectra of peptides with >0.9 median Pearson correlation coefficients. Further, we showed that intermediate layer of the neural network could reveal physicochemical properties of amino acids, for example the similarities of fragmentation behaviors between amino acids. We also showed the potential of pDeep to distinguish extremely similar peptides (peptides that contain isobaric amino acids, for example, GG = N, AG = Q, or even I = L), which were very difficult to distinguish using traditional search engines.

  5. Accurate prediction of cardiorespiratory fitness using cycle ergometry in minimally disabled persons with relapsing-remitting multiple sclerosis.

    PubMed

    Motl, Robert W; Fernhall, Bo

    2012-03-01

    To examine the accuracy of predicting peak oxygen consumption (VO(2peak)) primarily from peak work rate (WR(peak)) recorded during a maximal, incremental exercise test on a cycle ergometer among persons with relapsing-remitting multiple sclerosis (RRMS) who had minimal disability. Cross-sectional study. Clinical research laboratory. Women with RRMS (n=32) and sex-, age-, height-, and weight-matched healthy controls (n=16) completed an incremental exercise test on a cycle ergometer to volitional termination. Not applicable. Measured and predicted VO(2peak) and WR(peak). There were strong, statistically significant associations between measured and predicted VO(2peak) in the overall sample (R(2)=.89, standard error of the estimate=127.4 mL/min) and subsamples with (R(2)=.89, standard error of the estimate=131.3 mL/min) and without (R(2)=.85, standard error of the estimate=126.8 mL/min) multiple sclerosis (MS) based on the linear regression analyses. Based on the 95% confidence limits for worst-case errors, the equation predicted VO(2peak) within 10% of its true value in 95 of every 100 subjects with MS. Peak VO(2) can be accurately predicted in persons with RRMS who have minimal disability as it is in controls by using established equations and WR(peak) recorded from a maximal, incremental exercise test on a cycle ergometer. Copyright © 2012 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

  6. Predicting human olfactory perception from chemical features of odor molecules.

    PubMed

    Keller, Andreas; Gerkin, Richard C; Guan, Yuanfang; Dhurandhar, Amit; Turu, Gabor; Szalai, Bence; Mainland, Joel D; Ihara, Yusuke; Yu, Chung Wen; Wolfinger, Russ; Vens, Celine; Schietgat, Leander; De Grave, Kurt; Norel, Raquel; Stolovitzky, Gustavo; Cecchi, Guillermo A; Vosshall, Leslie B; Meyer, Pablo

    2017-02-24

    It is still not possible to predict whether a given molecule will have a perceived odor or what olfactory percept it will produce. We therefore organized the crowd-sourced DREAM Olfaction Prediction Challenge. Using a large olfactory psychophysical data set, teams developed machine-learning algorithms to predict sensory attributes of molecules based on their chemoinformatic features. The resulting models accurately predicted odor intensity and pleasantness and also successfully predicted 8 among 19 rated semantic descriptors ("garlic," "fish," "sweet," "fruit," "burnt," "spices," "flower," and "sour"). Regularized linear models performed nearly as well as random forest-based ones, with a predictive accuracy that closely approaches a key theoretical limit. These models help to predict the perceptual qualities of virtually any molecule with high accuracy and also reverse-engineer the smell of a molecule. Copyright © 2017, American Association for the Advancement of Science.

  7. a Protocol for High-Accuracy Theoretical Thermochemistry

    NASA Astrophysics Data System (ADS)

    Welch, Bradley; Dawes, Richard

    2017-06-01

    Theoretical studies of spectroscopy and reaction dynamics including the necessary development of potential energy surfaces rely on accurate thermochemical information. The Active Thermochemical Tables (ATcT) approach by Ruscic^{1} incorporates data for a large number of chemical species from a variety of sources (both experimental and theoretical) and derives a self-consistent network capable of making extremely accurate estimates of quantities such as temperature dependent enthalpies of formation. The network provides rigorous uncertainties, and since the values don't rely on a single measurement or calculation, the provenance of each quantity is also obtained. To expand and improve the network it is desirable to have a reliable protocol such as the HEAT approach^{2} for calculating accurate theoretical data. Here we present and benchmark an approach based on explicitly-correlated coupled-cluster theory and vibrational perturbation theory (VPT2). Methyldioxy and Methyl Hydroperoxide are important and well-characterized species in combustion processes and begin the family of (ethyl-, propyl-based, etc) similar compounds (much less is known about the larger members). Accurate anharmonic frequencies are essential to accurately describe even the 0 K enthalpies of formation, but are especially important for finite temperature studies. Here we benchmark the spectroscopic and thermochemical accuracy of the approach, comparing with available data for the smallest systems, and comment on the outlook for larger systems that are less well-known and characterized. ^{1}B. Ruscic, Active Thermochemical Tables (ATcT) values based on ver. 1.118 of the Thermochemical Network (2015); available at ATcT.anl.gov ^{2}A. Tajti, P. G. Szalay, A. G. Császár, M. Kállay, J. Gauss, E. F. Valeev, B. A. Flowers, J. Vázquez, and J. F. Stanton. JCP 121, (2004): 11599.

  8. Sound transmission through lightweight double-leaf partitions: theoretical modelling

    NASA Astrophysics Data System (ADS)

    Wang, J.; Lu, T. J.; Woodhouse, J.; Langley, R. S.; Evans, J.

    2005-09-01

    This paper presents theoretical modelling of the sound transmission loss through double-leaf lightweight partitions stiffened with periodically placed studs. First, by assuming that the effect of the studs can be replaced with elastic springs uniformly distributed between the sheathing panels, a simple smeared model is established. Second, periodic structure theory is used to develop a more accurate model taking account of the discrete placing of the studs. Both models treat incident sound waves in the horizontal plane only, for simplicity. The predictions of the two models are compared, to reveal the physical mechanisms determining sound transmission. The smeared model predicts relatively simple behaviour, in which the only conspicuous features are associated with coincidence effects with the two types of structural wave allowed by the partition model, and internal resonances of the air between the panels. In the periodic model, many more features are evident, associated with the structure of pass- and stop-bands for structural waves in the partition. The models are used to explain the effects of incidence angle and of the various system parameters. The predictions are compared with existing test data for steel plates with wooden stiffeners, and good agreement is obtained.

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

    ERIC Educational Resources Information Center

    Lin, Jing-Wen

    2016-01-01

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

  10. Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties

    NASA Astrophysics Data System (ADS)

    Xie, Tian; Grossman, Jeffrey C.

    2018-04-01

    The use of machine learning methods for accelerating the design of crystalline materials usually requires manually constructed feature vectors or complex transformation of atom coordinates to input the crystal structure, which either constrains the model to certain crystal types or makes it difficult to provide chemical insights. Here, we develop a crystal graph convolutional neural networks framework to directly learn material properties from the connection of atoms in the crystal, providing a universal and interpretable representation of crystalline materials. Our method provides a highly accurate prediction of density functional theory calculated properties for eight different properties of crystals with various structure types and compositions after being trained with 1 04 data points. Further, our framework is interpretable because one can extract the contributions from local chemical environments to global properties. Using an example of perovskites, we show how this information can be utilized to discover empirical rules for materials design.

  11. Effect of foam on temperature prediction and heat recovery potential from biological wastewater treatment.

    PubMed

    Corbala-Robles, L; Volcke, E I P; Samijn, A; Ronsse, F; Pieters, J G

    2016-05-15

    Heat is an important resource in wastewater treatment plants (WWTPs) which can be recovered. A prerequisite to determine the theoretical heat recovery potential is an accurate heat balance model for temperature prediction. The insulating effect of foam present on the basin surface and its influence on temperature prediction were assessed in this study. Experiments were carried out to characterize the foam layer and its insulating properties. A refined dynamic temperature prediction model, taking into account the effect of foam, was set up. Simulation studies for a WWTP treating highly concentrated (manure) wastewater revealed that the foam layer had a significant effect on temperature prediction (3.8 ± 0.7 K over the year) and thus on the theoretical heat recovery potential (30% reduction when foam is not considered). Seasonal effects on the individual heat losses and heat gains were assessed. Additionally, the effects of the critical basin temperature above which heat is recovered, foam thickness, surface evaporation rate reduction and the non-absorbed solar radiation on the theoretical heat recovery potential were evaluated. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. Predicting Electrostatic Forces in RNA Folding

    PubMed Central

    Tan, Zhi-Jie; Chen, Shi-Jie

    2016-01-01

    Metal ion-mediated electrostatic interactions are critical to RNA folding. Although considerable progress has been made in mechanistic studies, the problem of accurate predictions for the ion effects in RNA folding remains unsolved, mainly due to the complexity of several potentially important issues such as ion correlation and dehydration effects. In this chapter, after giving a brief overview of the experimental findings and theoretical approaches, we focus on a recently developed new model, the tightly bound ion (TBI) model, for ion electrostatics in RNA folding. The model is unique because it can treat ion correlation and fluctuation effects for realistic RNA 3D structures. For monovalent ion (such as Na+) solutions, where ion correlation is weak, TBI and the Poisson–Boltzmann (PB) theory give the same results and the results agree with the experimental data. For multivalent ion (such as Mg2+) solutions, where ion correlation can be strong, however, TBI gives much improved predictions than the PB. Moreover, the model suggests an ion correlation- induced mechanism for the unusual efficiency of Mg2+ ions in the stabilization of RNA tertiary folds. In this chapter, after introducing the theoretical framework of the TBI model, we will describe how to apply the model to predict ion-binding properties and ion-dependent folding stabilities. PMID:20946803

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Liang, Yufeng; Vinson, John; Pemmaraju, Sri

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

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

    DOE PAGES

    Liang, Yufeng; Vinson, John; Pemmaraju, Sri; ...

    2017-03-03

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

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

    PubMed

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

    2017-03-03

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

  16. Super H-mode: theoretical prediction and initial observations of a new high performance regime for tokamak operation

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Snyder, Philip B.; Solomon, Wayne M.; Burrell, Keith H.

    2015-07-21

    A new “Super H-mode” regime is predicted, which enables pedestal height and predicted fusion performance substantially higher than for H-mode operation. This new regime is predicted to exist by the EPED pedestal model, which calculates criticality constraints for peeling-ballooning and kinetic ballooning modes, and combines them to predict the pedestal height and width. EPED usually predicts a single (“H-mode”) pedestal solution for each set of input parameters, however, in strongly shaped plasmas above a critical density, multiple pedestal solutions are found, including the standard “Hmode” solution, and a “Super H-Mode” solution at substantially larger pedestal height and width. The Supermore » H-mode regime is predicted to be accessible by controlling the trajectory of the density, and to increase fusion performance for ITER, as well as for DEMO designs with strong shaping. A set of experiments on DIII-D has identified the predicted Super H-mode regime, and finds pedestal height and width, and their variation with density, in good agreement with theoretical predictions from the EPED model. Finally, the very high pedestal enables operation at high global beta and high confinement, including the highest normalized beta achieved on DIII-D with a quiescent edge.« less

  17. Accurate prediction of acute fish toxicity of fragrance chemicals with the RTgill-W1 cell assay.

    PubMed

    Natsch, Andreas; Laue, Heike; Haupt, Tina; von Niederhäusern, Valentin; Sanders, Gordon

    2018-03-01

    Testing for acute fish toxicity is an integral part of the environmental safety assessment of chemicals. A true replacement of primary fish tissue was recently proposed using cell viability in a fish gill cell line (RTgill-W1) as a means of predicting acute toxicity, showing good predictivity on 35 chemicals. To promote regulatory acceptance, the predictivity and applicability domain of novel tests need to be carefully evaluated on chemicals with existing high-quality in vivo data. We applied the RTgill-W1 cell assay to 38 fragrance chemicals with a wide range of both physicochemical properties and median lethal concentration (LC50) values and representing a diverse range of chemistries. A strong correlation (R 2  = 0.90-0.94) between the logarithmic in vivo LC50 values, based on fish mortality, and the logarithmic in vitro median effect concentration (EC50) values based on cell viability was observed. A leave-one-out analysis illustrates a median under-/overprediction from in vitro EC50 values to in vivo LC50 values by a factor of 1.5. This assay offers a simple, accurate, and reliable alternative to in vivo acute fish toxicity testing for chemicals, presumably acting mainly by a narcotic mode of action. Furthermore, the present study provides validation of the predictivity of the RTgill-W1 assay on a completely independent set of chemicals that had not been previously tested and indicates that fragrance chemicals are clearly within the applicability domain. Environ Toxicol Chem 2018;37:931-941. © 2017 SETAC. © 2017 SETAC.

  18. Accurate deuterium spectroscopy for fundamental studies

    NASA Astrophysics Data System (ADS)

    Wcisło, P.; Thibault, F.; Zaborowski, M.; Wójtewicz, S.; Cygan, A.; Kowzan, G.; Masłowski, P.; Komasa, J.; Puchalski, M.; Pachucki, K.; Ciuryło, R.; Lisak, D.

    2018-07-01

    We present an accurate measurement of the weak quadrupole S(2) 2-0 line in self-perturbed D2 and theoretical ab initio calculations of both collisional line-shape effects and energy of this rovibrational transition. The spectra were collected at the 247-984 Torr pressure range with a frequency-stabilized cavity ring-down spectrometer linked to an optical frequency comb (OFC) referenced to a primary time standard. Our line-shape modeling employed quantum calculations of molecular scattering (the pressure broadening and shift and their speed dependencies were calculated, while the complex frequency of optical velocity-changing collisions was fitted to experimental spectra). The velocity-changing collisions are handled with the hard-sphere collisional kernel. The experimental and theoretical pressure broadening and shift are consistent within 5% and 27%, respectively (the discrepancy for shift is 8% when referred not to the speed averaged value, which is close to zero, but to the range of variability of the speed-dependent shift). We use our high pressure measurement to determine the energy, ν0, of the S(2) 2-0 transition. The ab initio line-shape calculations allowed us to mitigate the expected collisional systematics reaching the 410 kHz accuracy of ν0. We report theoretical determination of ν0 taking into account relativistic and QED corrections up to α5. Our estimation of the accuracy of the theoretical ν0 is 1.3 MHz. We observe 3.4σ discrepancy between experimental and theoretical ν0.

  19. Theoretical predicting of permeability evolution in damaged rock under compressive stress

    NASA Astrophysics Data System (ADS)

    Vu, M. N.; Nguyen, S. T.; To, Q. D.; Dao, N. H.

    2017-05-01

    This paper outlines an analytical model of crack growth induced permeability changes. A theoretical solution of effective permeability of cracked porous media is derived. The fluid flow obeys Poisseuille's law along the crack and Darcy's law in the porous matrix. This solution exhibits a percolation threshold for any type of crack distribution apart from a parallel crack distribution. The physical behaviour of fluid flow through a cracked porous material is well reproduced by the proposed model. The presence of this effective permeability coupling to analytical expression of crack growth under compression enables the modelling of the permeability variation due to stress-induced cracking in a porous rock. This incorporation allows the prediction of the permeability change of a porous rock embedding an anisotropic crack distribution from any initial crack density, that is, lower, around or upper to percolation threshold. The interaction between cracks is not explicitly taken into account. The model is well applicable both to micro- and macrocracks.

  20. Experimental and Theoretical Study of Heat Conduction for Air up to 5000 K

    NASA Technical Reports Server (NTRS)

    Peng, Tzy-Cheng; Ahtye, Warren F.

    1961-01-01

    The theoretical value of the integral of thermal conductivity is compared with the experimental values from shock-tube measurements. The particular case considered is the one-dimensional nonsteady flow of heat through air at constant pressure. This approach has been previously described in NASA TR R-27. experiment was uncertain because of the large scatter in the experimental data. In this paper, an attempt is made to improve the correlation by use of a more refined calculation of the integral of thermal conductivity, and by use of improved experimental techniques and instrumentation. As a result of these changes, a much closer correlation is shown between the experimental and theoretical heat-flux potentials. This indicates that the predicted values of the coefficient of thermal conductivity for high-temperature air may be suitably accurate for many engineering needs, up to the limits of the test (4600 K).

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

    PubMed Central

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

    2012-01-01

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

  2. Accurate RNA 5-methylcytosine site prediction based on heuristic physical-chemical properties reduction and classifier ensemble.

    PubMed

    Zhang, Ming; Xu, Yan; Li, Lei; Liu, Zi; Yang, Xibei; Yu, Dong-Jun

    2018-06-01

    RNA 5-methylcytosine (m 5 C) is an important post-transcriptional modification that plays an indispensable role in biological processes. The accurate identification of m 5 C sites from primary RNA sequences is especially useful for deeply understanding the mechanisms and functions of m 5 C. Due to the difficulty and expensive costs of identifying m 5 C sites with wet-lab techniques, developing fast and accurate machine-learning-based prediction methods is urgently needed. In this study, we proposed a new m 5 C site predictor, called M5C-HPCR, by introducing a novel heuristic nucleotide physicochemical property reduction (HPCR) algorithm and classifier ensemble. HPCR extracts multiple reducts of physical-chemical properties for encoding discriminative features, while the classifier ensemble is applied to integrate multiple base predictors, each of which is trained based on a separate reduct of the physical-chemical properties obtained from HPCR. Rigorous jackknife tests on two benchmark datasets demonstrate that M5C-HPCR outperforms state-of-the-art m 5 C site predictors, with the highest values of MCC (0.859) and AUC (0.962). We also implemented the webserver of M5C-HPCR, which is freely available at http://cslab.just.edu.cn:8080/M5C-HPCR/. Copyright © 2018 Elsevier Inc. All rights reserved.

  3. Comparison of experimentally and theoretically determined radiation characteristics of photosynthetic microorganisms

    NASA Astrophysics Data System (ADS)

    Kandilian, Razmig; Pruvost, Jérémy; Artu, Arnaud; Lemasson, Camille; Legrand, Jack; Pilon, Laurent

    2016-05-01

    This paper aims to experimentally and directly validate a recent theoretical method for predicting the radiation characteristics of photosynthetic microorganisms. Such predictions would facilitate light transfer analysis in photobioreactors (PBRs) to control their operation and to maximize their production of biofuel and other high-value products. The state of the art experimental method can be applied to microorganisms of any shape and inherently accounts for their non-spherical and heterogeneous nature. On the other hand, the theoretical method treats the microorganisms as polydisperse homogeneous spheres with some effective optical properties. The absorption index is expressed as the weighted sum of the pigment mass absorption cross-sections and the refractive index is estimated based on the subtractive Kramers-Kronig relationship given an anchor refractive index and wavelength. Here, particular attention was paid to green microalgae Chlamydomonas reinhardtii grown under nitrogen-replete and nitrogen-limited conditions and to Chlorella vulgaris grown under nitrogen-replete conditions. First, relatively good agreement was found between the two methods for determining the mass absorption and scattering cross-sections and the asymmetry factor of both nitrogen-replete and nitrogen-limited C. reinhardtii with the proper anchor point. However, the homogeneous sphere approximation significantly overestimated the absorption cross-section of C. vulgaris cells. The latter were instead modeled as polydisperse coated spheres consisting of an absorbing core containing pigments and a non-absorbing but strongly refracting wall made of sporopollenin. The coated sphere approximation gave good predictions of the experimentally measured integral radiation characteristics of C. vulgaris. In both cases, the homogeneous and coated sphere approximations predicted resonance in the scattering phase function that were not observed experimentally. However, these approximations were

  4. The NAFLD Index: A Simple and Accurate Screening Tool for the Prediction of Non-Alcoholic Fatty Liver Disease.

    PubMed

    Ichino, Naohiro; Osakabe, Keisuke; Sugimoto, Keiko; Suzuki, Koji; Yamada, Hiroya; Takai, Hiroji; Sugiyama, Hiroko; Yukitake, Jun; Inoue, Takashi; Ohashi, Koji; Hata, Tadayoshi; Hamajima, Nobuyuki; Nishikawa, Toru; Hashimoto, Senju; Kawabe, Naoto; Yoshioka, Kentaro

    2015-01-01

    Non-alcoholic fatty liver disease (NAFLD) is a common debilitating condition in many industrialized countries that increases the risk of cardiovascular disease. The aim of this study was to derive a simple and accurate screening tool for the prediction of NAFLD in the Japanese population. A total of 945 participants, 279 men and 666 women living in Hokkaido, Japan, were enrolled among residents who attended a health check-up program from 2010 to 2014. Participants with an alcohol consumption > 20 g/day and/or a chronic liver disease, such as chronic hepatitis B, chronic hepatitis C or autoimmune hepatitis, were excluded from this study. Clinical and laboratory data were examined to identify predictive markers of NAFLD. A new predictive index for NAFLD, the NAFLD index, was constructed for men and for women. The NAFLD index for men = -15.5693+0.3264 [BMI] +0.0134 [triglycerides (mg/dl)], and for women = -31.4686+0.3683 [BMI] +2.5699 [albumin (g/dl)] +4.6740[ALT/AST] -0.0379 [HDL cholesterol (mg/dl)]. The AUROC of the NAFLD index for men and for women was 0.87(95% CI 0.88-1.60) and 0.90 (95% CI 0.66-1.02), respectively. The cut-off point of -5.28 for men predicted NAFLD with an accuracy of 82.8%. For women, the cut-off point of -7.65 predicted NAFLD with an accuracy of 87.7%. A new index for the non-invasive prediction of NAFLD, the NAFLD index, was constructed using available clinical and laboratory data. This index is a simple screening tool to predict the presence of NAFLD.

  5. Mechanical Behaviour of 3D Multi-layer Braided Composites: Experimental, Numerical and Theoretical Study

    NASA Astrophysics Data System (ADS)

    Deng, Jian; Zhou, Guangming; Ji, Le; Wang, Xiaopei

    2017-12-01

    Mechanical properties and failure mechanisms of a newly designed 3D multi-layer braided composites are evaluated by experimental, numerical and theoretical studies. The microstructure of the composites is introduced. The unit cell technique is employed to address the periodic arrangement of the structure. The volume averaging method is used in theoretical solutions while FEM with reasonable periodic boundary conditions and meshing technique in numerical simulations. Experimental studies are also conducted to verify the feasibility of the proposed models. Predicted elastic properties agree well with the experimental data, indicating the feasibility of the proposed models. Numerical evaluation is more accurate than theoretical assessment. Deformations and stress distributions of the unit cell under tension shows displacement and traction continuity, guaranteeing the rationality of the applied periodic boundary conditions. Although compression and tension modulus are close, the compressive strength only reaches 70% of the tension strength. This indicates that the composites can be weakened in compressive loading. Additionally, by analysing the micrograph of fracture faces and strain-stress curves, a brittle failure mechanism is observed both in composites under tension and compression.

  6. Prediction of enzyme classes from 3D structure: a general model and examples of experimental-theoretic scoring of peptide mass fingerprints of Leishmania proteins.

    PubMed

    Concu, Riccardo; Dea-Ayuela, Maria A; Perez-Montoto, Lazaro G; Bolas-Fernández, Francisco; Prado-Prado, Francisco J; Podda, Gianni; Uriarte, Eugenio; Ubeira, Florencio M; González-Díaz, Humberto

    2009-09-01

    The number of protein and peptide structures included in Protein Data Bank (PDB) and Gen Bank without functional annotation has increased. Consequently, there is a high demand for theoretical models to predict these functions. Here, we trained and validated, with an external set, a Markov Chain Model (MCM) that classifies proteins by their possible mechanism of action according to Enzyme Classification (EC) number. The methodology proposed is essentially new, and enables prediction of all EC classes with a single equation without the need for an equation for each class or nonlinear models with multiple outputs. In addition, the model may be used to predict whether one peptide presents a positive or negative contribution of the activity of the same EC class. The model predicts the first EC number for 106 out of 151 (70.2%) oxidoreductases, 178/178 (100%) transferases, 223/223 (100%) hydrolases, 64/85 (75.3%) lyases, 74/74 (100%) isomerases, and 100/100 (100%) ligases, as well as 745/811 (91.9%) nonenzymes. It is important to underline that this method may help us predict new enzyme proteins or select peptide candidates that improve enzyme activity, which may be of interest for the prediction of new drugs or drug targets. To illustrate the model's application, we report the 2D-Electrophoresis (2DE) isolation from Leishmania infantum as well as MADLI TOF Mass Spectra characterization and theoretical study of the Peptide Mass Fingerprints (PMFs) of a new protein sequence. The theoretical study focused on MASCOT, BLAST alignment, and alignment-free QSAR prediction of the contribution of 29 peptides found in the PMF of the new protein to specific enzyme action. This combined strategy may be used to identify and predict peptides of prokaryote and eukaryote parasites and their hosts as well as other superior organisms, which may be of interest in drug development or target identification.

  7. A Deep Learning Framework for Robust and Accurate Prediction of ncRNA-Protein Interactions Using Evolutionary Information.

    PubMed

    Yi, Hai-Cheng; You, Zhu-Hong; Huang, De-Shuang; Li, Xiao; Jiang, Tong-Hai; Li, Li-Ping

    2018-06-01

    The interactions between non-coding RNAs (ncRNAs) and proteins play an important role in many biological processes, and their biological functions are primarily achieved by binding with a variety of proteins. High-throughput biological techniques are used to identify protein molecules bound with specific ncRNA, but they are usually expensive and time consuming. Deep learning provides a powerful solution to computationally predict RNA-protein interactions. In this work, we propose the RPI-SAN model by using the deep-learning stacked auto-encoder network to mine the hidden high-level features from RNA and protein sequences and feed them into a random forest (RF) model to predict ncRNA binding proteins. Stacked assembling is further used to improve the accuracy of the proposed method. Four benchmark datasets, including RPI2241, RPI488, RPI1807, and NPInter v2.0, were employed for the unbiased evaluation of five established prediction tools: RPI-Pred, IPMiner, RPISeq-RF, lncPro, and RPI-SAN. The experimental results show that our RPI-SAN model achieves much better performance than other methods, with accuracies of 90.77%, 89.7%, 96.1%, and 99.33%, respectively. It is anticipated that RPI-SAN can be used as an effective computational tool for future biomedical researches and can accurately predict the potential ncRNA-protein interacted pairs, which provides reliable guidance for biological research. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

  8. The costs and benefits of occasional sex: theoretical predictions and a case study.

    PubMed

    D'Souza, Thomas G; Michiels, Nico K

    2010-01-01

    Theory predicts that occasional sexual reproduction in predominantly parthenogenetic organisms offers all the advantages of obligate sexuality without paying its full costs. However, empirical examples identifying and evaluating the costs and benefits of rare sex are scarce. After reviewing the theoretical perspective on rare sex, we present our findings of potential costs and benefits of occasional sex in polyploid, sperm-dependent parthenogens of the planarian flatworm Schmidtea polychroa. Despite costs associated with the production of less fertile tetraploids as sexual intermediates, the benefits of rare sex prevail in S. polychroa and may be sufficiently strong to prevent extinction of parthenogenetic populations. This offers an explanation for the dominance of parthenogenesis in S. polychroa. We discuss the enigmatic question why not all organisms show a mixed reproduction mode.

  9. Accurate and Reliable Prediction of the Binding Affinities of Macrocycles to Their Protein Targets.

    PubMed

    Yu, Haoyu S; Deng, Yuqing; Wu, Yujie; Sindhikara, Dan; Rask, Amy R; Kimura, Takayuki; Abel, Robert; Wang, Lingle

    2017-12-12

    Macrocycles have been emerging as a very important drug class in the past few decades largely due to their expanded chemical diversity benefiting from advances in synthetic methods. Macrocyclization has been recognized as an effective way to restrict the conformational space of acyclic small molecule inhibitors with the hope of improving potency, selectivity, and metabolic stability. Because of their relatively larger size as compared to typical small molecule drugs and the complexity of the structures, efficient sampling of the accessible macrocycle conformational space and accurate prediction of their binding affinities to their target protein receptors poses a great challenge of central importance in computational macrocycle drug design. In this article, we present a novel method for relative binding free energy calculations between macrocycles with different ring sizes and between the macrocycles and their corresponding acyclic counterparts. We have applied the method to seven pharmaceutically interesting data sets taken from recent drug discovery projects including 33 macrocyclic ligands covering a diverse chemical space. The predicted binding free energies are in good agreement with experimental data with an overall root-mean-square error (RMSE) of 0.94 kcal/mol. This is to our knowledge the first time where the free energy of the macrocyclization of linear molecules has been directly calculated with rigorous physics-based free energy calculation methods, and we anticipate the outstanding accuracy demonstrated here across a broad range of target classes may have significant implications for macrocycle drug discovery.

  10. Flight-Test Evaluation of Flutter-Prediction Methods

    NASA Technical Reports Server (NTRS)

    Lind, RIck; Brenner, Marty

    2003-01-01

    The flight-test community routinely spends considerable time and money to determine a range of flight conditions, called a flight envelope, within which an aircraft is safe to fly. The cost of determining a flight envelope could be greatly reduced if there were a method of safely and accurately predicting the speed associated with the onset of an instability called flutter. Several methods have been developed with the goal of predicting flutter speeds to improve the efficiency of flight testing. These methods include (1) data-based methods, in which one relies entirely on information obtained from the flight tests and (2) model-based approaches, in which one relies on a combination of flight data and theoretical models. The data-driven methods include one based on extrapolation of damping trends, one that involves an envelope function, one that involves the Zimmerman-Weissenburger flutter margin, and one that involves a discrete-time auto-regressive model. An example of a model-based approach is that of the flutterometer. These methods have all been shown to be theoretically valid and have been demonstrated on simple test cases; however, until now, they have not been thoroughly evaluated in flight tests. An experimental apparatus called the Aerostructures Test Wing (ATW) was developed to test these prediction methods.

  11. Limited Sampling Strategy for Accurate Prediction of Pharmacokinetics of Saroglitazar: A 3-point Linear Regression Model Development and Successful Prediction of Human Exposure.

    PubMed

    Joshi, Shuchi N; Srinivas, Nuggehally R; Parmar, Deven V

    2018-03-01

    Our aim was to develop and validate the extrapolative performance of a regression model using a limited sampling strategy for accurate estimation of the area under the plasma concentration versus time curve for saroglitazar. Healthy subject pharmacokinetic data from a well-powered food-effect study (fasted vs fed treatments; n = 50) was used in this work. The first 25 subjects' serial plasma concentration data up to 72 hours and corresponding AUC 0-t (ie, 72 hours) from the fasting group comprised a training dataset to develop the limited sampling model. The internal datasets for prediction included the remaining 25 subjects from the fasting group and all 50 subjects from the fed condition of the same study. The external datasets included pharmacokinetic data for saroglitazar from previous single-dose clinical studies. Limited sampling models were composed of 1-, 2-, and 3-concentration-time points' correlation with AUC 0-t of saroglitazar. Only models with regression coefficients (R 2 ) >0.90 were screened for further evaluation. The best R 2 model was validated for its utility based on mean prediction error, mean absolute prediction error, and root mean square error. Both correlations between predicted and observed AUC 0-t of saroglitazar and verification of precision and bias using Bland-Altman plot were carried out. None of the evaluated 1- and 2-concentration-time points models achieved R 2 > 0.90. Among the various 3-concentration-time points models, only 4 equations passed the predefined criterion of R 2 > 0.90. Limited sampling models with time points 0.5, 2, and 8 hours (R 2 = 0.9323) and 0.75, 2, and 8 hours (R 2 = 0.9375) were validated. Mean prediction error, mean absolute prediction error, and root mean square error were <30% (predefined criterion) and correlation (r) was at least 0.7950 for the consolidated internal and external datasets of 102 healthy subjects for the AUC 0-t prediction of saroglitazar. The same models, when applied to the AUC 0-t

  12. Towards more accurate and reliable predictions for nuclear applications

    NASA Astrophysics Data System (ADS)

    Goriely, Stephane; Hilaire, Stephane; Dubray, Noel; Lemaître, Jean-François

    2017-09-01

    The need for nuclear data far from the valley of stability, for applications such as nuclear astrophysics or future nuclear facilities, challenges the robustness as well as the predictive power of present nuclear models. Most of the nuclear data evaluation and prediction are still performed on the basis of phenomenological nuclear models. For the last decades, important progress has been achieved in fundamental nuclear physics, making it now feasible to use more reliable, but also more complex microscopic or semi-microscopic models in the evaluation and prediction of nuclear data for practical applications. Nowadays mean-field models can be tuned at the same level of accuracy as the phenomenological models, renormalized on experimental data if needed, and therefore can replace the phenomenological inputs in the evaluation of nuclear data. The latest achievements to determine nuclear masses within the non-relativistic HFB approach, including the related uncertainties in the model predictions, are discussed. Similarly, recent efforts to determine fission observables within the mean-field approach are described and compared with more traditional existing models.

  13. Precise predictions for V+jets dark matter backgrounds

    NASA Astrophysics Data System (ADS)

    Lindert, J. M.; Pozzorini, S.; Boughezal, R.; Campbell, J. M.; Denner, A.; Dittmaier, S.; Gehrmann-De Ridder, A.; Gehrmann, T.; Glover, N.; Huss, A.; Kallweit, S.; Maierhöfer, P.; Mangano, M. L.; Morgan, T. A.; Mück, A.; Petriello, F.; Salam, G. P.; Schönherr, M.; Williams, C.

    2017-12-01

    High-energy jets recoiling against missing transverse energy (MET) are powerful probes of dark matter at the LHC. Searches based on large MET signatures require a precise control of the Z(ν {\\bar{ν }})+ jet background in the signal region. This can be achieved by taking accurate data in control regions dominated by Z(ℓ ^+ℓ ^-)+ jet, W(ℓ ν )+ jet and γ + jet production, and extrapolating to the Z(ν {\\bar{ν }})+ jet background by means of precise theoretical predictions. In this context, recent advances in perturbative calculations open the door to significant sensitivity improvements in dark matter searches. In this spirit, we present a combination of state-of-the-art calculations for all relevant V+ jets processes, including throughout NNLO QCD corrections and NLO electroweak corrections supplemented by Sudakov logarithms at two loops. Predictions at parton level are provided together with detailed recommendations for their usage in experimental analyses based on the reweighting of Monte Carlo samples. Particular attention is devoted to the estimate of theoretical uncertainties in the framework of dark matter searches, where subtle aspects such as correlations across different V+ jet processes play a key role. The anticipated theoretical uncertainty in the Z(ν {\\bar{ν }})+ jet background is at the few percent level up to the TeV range.

  14. Theoretical Prediction of Am(III)/Eu(III) Selectivity to Aid the Design of Actinide-Lanthanide Separation Agents

    DOE PAGES

    Bryantsev, Vyacheslav S.; Hay, Benjamin P.

    2015-03-20

    Selective extraction of minor actinides from lanthanides is a critical step in the reduction of radiotoxicity of spent nuclear fuels. However, the design of suitable ligands for separating chemically similar 4f- and 5f-block trivalent metal ions poses a significant challenge. Furthermore, first-principles calculations should play an important role in the design of new separation agents, but their ability to predict metal ion selectivity has not been systematically evaluated. We examine the ability of several density functional theory methods to predict selectivity of Am(III) and Eu(III) with oxygen, mixed oxygen–nitrogen, and sulfur donor ligands. The results establish a computational method capablemore » of predicting the correct order of selectivities obtained from liquid–liquid extraction and aqueous phase complexation studies. To allow reasonably accurate predictions, it was critical to employ sufficiently flexible basis sets and provide proper account of solvation effects. The approach is utilized to estimate the selectivity of novel amide-functionalized diazine and 1,2,3-triazole ligands.« less

  15. New accurate theoretical line lists of 12CH4 and 13CH4 in the 0-13400 cm-1 range: Application to the modeling of methane absorption in Titan's atmosphere

    NASA Astrophysics Data System (ADS)

    Rey, Michaël; Nikitin, Andrei V.; Bézard, Bruno; Rannou, Pascal; Coustenis, Athena; Tyuterev, Vladimir G.

    2018-03-01

    The spectrum of methane is very important for the analysis and modeling of Titan's atmosphere but its insufficient knowledge in the near infrared, with the absence of reliable absorption coefficients, is an important limitation. In order to help the astronomer community for analyzing high-quality spectra, we report in the present work the first accurate theoretical methane line lists (T = 50-350 K) of 12CH4 and 13CH4 up to 13400 cm-1 ( > 0.75 μm). These lists are built from extensive variational calculations using our recent ab initio potential and dipole moment surfaces and will be freely accessible via the TheoReTS information system (http://theorets.univ-reims.fr, http://theorets.tsu.ru). Validation of these lists is presented throughout the present paper. For the sample of lines where upper energies were available from published analyses of experimental laboratory 12CH4 spectra, small empirical corrections in positions were introduced that could be useful for future high-resolution applications. We finally apply the TheoRetS line list to model Titan spectra as observed by VIMS and by DISR, respectively onboard Cassini and Huygens. These data are used to check that the TheoReTS line lists are able to model observations. We also make comparisons with other experimental or theoretical line lists. It appears that TheoRetS gives very reliable results better than ExoMol and even than HITRAN2012, except around 1.6 μm where it gives very similar results. We conclude that TheoReTS is suitable to be used for the modeling of planetary radiative transfer and photometry. A re-analysis of spectra recorded by the DISR instrument during the descent of the Huygens probe suggests that the CH4 mixing ratio decreases with altitude in Titan's stratosphere, reaching a value of ∼10-2 above the 110 km altitude.

  16. Predictive Model and Software for Inbreeding-Purging Analysis of Pedigreed Populations

    PubMed Central

    García-Dorado, Aurora; Wang, Jinliang; López-Cortegano, Eugenio

    2016-01-01

    The inbreeding depression of fitness traits can be a major threat to the survival of populations experiencing inbreeding. However, its accurate prediction requires taking into account the genetic purging induced by inbreeding, which can be achieved using a “purged inbreeding coefficient”. We have developed a method to compute purged inbreeding at the individual level in pedigreed populations with overlapping generations. Furthermore, we derive the inbreeding depression slope for individual logarithmic fitness, which is larger than that for the logarithm of the population fitness average. In addition, we provide a new software, PURGd, based on these theoretical results that allows analyzing pedigree data to detect purging, and to estimate the purging coefficient, which is the parameter necessary to predict the joint consequences of inbreeding and purging. The software also calculates the purged inbreeding coefficient for each individual, as well as standard and ancestral inbreeding. Analysis of simulation data show that this software produces reasonably accurate estimates for the inbreeding depression rate and for the purging coefficient that are useful for predictive purposes. PMID:27605515

  17. 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.

  18. Chaotic advection at large Péclet number: Electromagnetically driven experiments, numerical simulations, and theoretical predictions

    NASA Astrophysics Data System (ADS)

    Figueroa, Aldo; Meunier, Patrice; Cuevas, Sergio; Villermaux, Emmanuel; Ramos, Eduardo

    2014-01-01

    We present a combination of experiment, theory, and modelling on laminar mixing at large Péclet number. The flow is produced by oscillating electromagnetic forces in a thin electrolytic fluid layer, leading to oscillating dipoles, quadrupoles, octopoles, and disordered flows. The numerical simulations are based on the Diffusive Strip Method (DSM) which was recently introduced (P. Meunier and E. Villermaux, "The diffusive strip method for scalar mixing in two-dimensions," J. Fluid Mech. 662, 134-172 (2010)) to solve the advection-diffusion problem by combining Lagrangian techniques and theoretical modelling of the diffusion. Numerical simulations obtained with the DSM are in reasonable agreement with quantitative dye visualization experiments of the scalar fields. A theoretical model based on log-normal Probability Density Functions (PDFs) of stretching factors, characteristic of homogeneous turbulence in the Batchelor regime, allows to predict the PDFs of scalar in agreement with numerical and experimental results. This model also indicates that the PDFs of scalar are asymptotically close to log-normal at late stages, except for the large concentration levels which correspond to low stretching factors.

  19. Estimating energy expenditure in vascular surgery patients: Are predictive equations accurate enough?

    PubMed

    Suen, J; Thomas, J M; Delaney, C L; Spark, J I; Miller, M D

    2016-12-01

    Malnutrition is prevalent in vascular surgical patients who commonly seek tertiary care at advanced stages of disease. Adjunct nutrition support is therefore pertinent to optimise patient outcomes. To negate consequences related to excessive or suboptimal dietary energy intake, it is essential to accurately determine energy expenditure and subsequent requirements. This study aims to compare resting energy expenditure (REE) measured by indirect calorimetry, a commonly used comparator, to REE estimated by predictive equations (Schofield, Harris-Benedict equations and Miller equation) to determine the most suitable equation for vascular surgery patients. Data were collected from four studies that measured REE in 77 vascular surgery patients. Bland-Altman analyses were conducted to explore agreement. Presence of fixed or proportional bias was assessed by linear regression analyses. In comparison to measured REE, on average REE was overestimated when Schofield (+857 kJ/day), Harris-Benedict (+801 kJ/day) and Miller (+71 kJ/day) equations were used. Wide limits of agreement led to an over or underestimation from 1552 to 1755 kJ. Proportional bias was absent in Schofield (R 2  = 0.005, p = 0.54) and Harris-Benedict equations (R 2  = 0.045, p = 0.06) but was present in the Miller equation (R 2  = 0.210, p < 0.01) even after logarithmic transformation (R 2  = 0.213, p < 0.01). Whilst the Miller equation tended to overestimate resting energy expenditure and was affected by proportional bias, the limits of agreement and mean bias were smaller compared to Schofield and Harris-Benedict equations. This suggested that it is the preferred predictive equation for vascular surgery patients. Future research to refine the Miller equation to improve its overall accuracy will better inform the provision of nutritional support for vascular surgery patients and subsequently improve outcomes. Alternatively, an equation might be developed specifically for use with

  20. An experimental, theoretical and event-driven computational study of narrow vibrofluidised granular materials

    NASA Astrophysics Data System (ADS)

    Thornton, Anthony; Windows-Yule, Kit; Parker, David; Luding, Stefan

    2017-06-01

    We review simulations, experiments and a theoretical treatment of vertically vibrated granular media. The systems considered are confined in narrow quasi-two-dimensional and quasi-one-dimensional (column) geometries, where the vertical extension of the container is much larger than one or both horizontal lengths. The additional geometric constraint present in the column setup frustrates the convection state that is normally observed in wider geometries. We start by showing that the Event Driven (ED) simulation method is able to accurately reproduce the previously experimentally determined phase-diagram for vibrofludised granular materials. We then review two papers that used ED simulations to study narrow quasi-one-dimensional systems revealing a new phenomenon: collective oscillations of the grains with a characteristic frequency that is much lower than the frequency of energy injection. Theoretical work was then undertaken that is able to accurately predict the frequency of such an oscillation and Positron Emission Particle Tracking (PEPT) experiments were undertaken to provide the first experimental evidence of this new phenomenon. Finally, we briefly discuss ongoing work to create an open-source version of this ED via its integration in the existing open-source package MercuryDPM (http://MercuryDPM.org); which has many advanced features that are not found in other codes.

  1. 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.

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

    PubMed

    Magozzi, Sarah; Calosi, Piero

    2015-01-01

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

  3. Ensemble MD simulations restrained via crystallographic data: Accurate structure leads to accurate dynamics

    PubMed Central

    Xue, Yi; Skrynnikov, Nikolai R

    2014-01-01

    Currently, the best existing molecular dynamics (MD) force fields cannot accurately reproduce the global free-energy minimum which realizes the experimental protein structure. As a result, long MD trajectories tend to drift away from the starting coordinates (e.g., crystallographic structures). To address this problem, we have devised a new simulation strategy aimed at protein crystals. An MD simulation of protein crystal is essentially an ensemble simulation involving multiple protein molecules in a crystal unit cell (or a block of unit cells). To ensure that average protein coordinates remain correct during the simulation, we introduced crystallography-based restraints into the MD protocol. Because these restraints are aimed at the ensemble-average structure, they have only minimal impact on conformational dynamics of the individual protein molecules. So long as the average structure remains reasonable, the proteins move in a native-like fashion as dictated by the original force field. To validate this approach, we have used the data from solid-state NMR spectroscopy, which is the orthogonal experimental technique uniquely sensitive to protein local dynamics. The new method has been tested on the well-established model protein, ubiquitin. The ensemble-restrained MD simulations produced lower crystallographic R factors than conventional simulations; they also led to more accurate predictions for crystallographic temperature factors, solid-state chemical shifts, and backbone order parameters. The predictions for 15N R1 relaxation rates are at least as accurate as those obtained from conventional simulations. Taken together, these results suggest that the presented trajectories may be among the most realistic protein MD simulations ever reported. In this context, the ensemble restraints based on high-resolution crystallographic data can be viewed as protein-specific empirical corrections to the standard force fields. PMID:24452989

  4. Accurate disulfide-bonding network predictions improve ab initio structure prediction of cysteine-rich proteins

    PubMed Central

    Yang, Jing; He, Bao-Ji; Jang, Richard; Zhang, Yang; Shen, Hong-Bin

    2015-01-01

    Abstract Motivation: Cysteine-rich proteins cover many important families in nature but there are currently no methods specifically designed for modeling the structure of these proteins. The accuracy of disulfide connectivity pattern prediction, particularly for the proteins of higher-order connections, e.g. >3 bonds, is too low to effectively assist structure assembly simulations. Results: We propose a new hierarchical order reduction protocol called Cyscon for disulfide-bonding prediction. The most confident disulfide bonds are first identified and bonding prediction is then focused on the remaining cysteine residues based on SVR training. Compared with purely machine learning-based approaches, Cyscon improved the average accuracy of connectivity pattern prediction by 21.9%. For proteins with more than 5 disulfide bonds, Cyscon improved the accuracy by 585% on the benchmark set of PDBCYS. When applied to 158 non-redundant cysteine-rich proteins, Cyscon predictions helped increase (or decrease) the TM-score (or RMSD) of the ab initio QUARK modeling by 12.1% (or 14.4%). This result demonstrates a new avenue to improve the ab initio structure modeling for cysteine-rich proteins. Availability and implementation: http://www.csbio.sjtu.edu.cn/bioinf/Cyscon/ Contact: zhng@umich.edu or hbshen@sjtu.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26254435

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

    NASA Astrophysics Data System (ADS)

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

    2006-12-01

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

  6. Theoretical Prediction of Microgravity Ignition Delay of Polymeric Fuels in Low Velocity Flows

    NASA Technical Reports Server (NTRS)

    Fernandez-Pello, A. C.; Torero, J. L.; Zhou, Y. Y.; Walther, D.; Ross, H. D.

    2001-01-01

    A new flammability apparatus and protocol, FIST (Forced Flow Ignition and Flame Spread Test), is under development. Based on the LIFT (Lateral Ignition and Flame Spread Test) protocol, FIST better reflects the environments expected in spacebased facilities. The final objective of the FIST research is to provide NASA with a test methodology that complements the existing protocol and provides a more comprehensive assessment of material flammability of practical materials for space applications. Theoretical modeling, an extensive normal gravity data bank and a few validation space experiments will support the testing methodology. The objective of the work presented here is to predict the ignition delay and critical heat flux for ignition of solid fuels in microgravity at airflow velocities below those induced in normal gravity. This is achieved through the application of a numerical model previously developed of piloted ignition of solid polymeric materials exposed to an external radiant heat flux. The model predictions will provide quantitative results about ignition of practical materials in the limiting conditions expected in space facilities. Experimental data of surface temperature histories and ignition delay obtained in the KC-135 aircraft are used to determine the critical pyrolysate mass flux for ignition and this value is subsequently used to predict the ignition delay and the critical heat flux for ignition of the material. Surface temperature and piloted ignition delay calculations for Polymethylmethacrylate (PMMA) and a Polypropylene/Fiberglass (PP/GL) composite were conducted under both reduced and normal gravity conditions. It was found that ignition delay times are significantly shorter at velocities below those induced by natural convection.

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

    PubMed

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

    2015-02-05

    As intermolecular interactions such as the hydrogen bond are electrostatic in origin, rigorous treatment of this term within force field methodologies should be mandatory. We present a method able of accurately reproducing such interactions for seven van der Waals complexes. It uses atomic multipole moments up to hexadecupole moment mapped to the positions of the nuclear coordinates by the machine learning method kriging. Models were built at three levels of theory: HF/6-31G(**), B3LYP/aug-cc-pVDZ and M06-2X/aug-cc-pVDZ. The quality of the kriging models was measured by their ability to predict the electrostatic interaction energy between atoms in external test examples for which the true energies are known. At all levels of theory, >90% of test cases for small van der Waals complexes were predicted within 1 kJ mol(-1), decreasing to 60-70% of test cases for larger base pair complexes. Models built on moments obtained at B3LYP and M06-2X level generally outperformed those at HF level. For all systems the individual interactions were predicted with a mean unsigned error of less than 1 kJ mol(-1). Copyright © 2013 Elsevier B.V. All rights reserved.

  8. Accurate prediction of pregnancy viability by means of a simple scoring system.

    PubMed

    Bottomley, Cecilia; Van Belle, Vanya; Kirk, Emma; Van Huffel, Sabine; Timmerman, Dirk; Bourne, Tom

    2013-01-01

    What is the performance of a simple scoring system to predict whether women will have an ongoing viable intrauterine pregnancy beyond the first trimester? A simple scoring system using demographic and initial ultrasound variables accurately predicts pregnancy viability beyond the first trimester with an area under the curve (AUC) in a receiver operating characteristic curve of 0.924 [95% confidence interval (CI) 0.900-0.947] on an independent test set. Individual demographic and ultrasound factors, such as maternal age, vaginal bleeding and gestational sac size, are strong predictors of miscarriage. Previous mathematical models have combined individual risk factors with reasonable performance. A simple scoring system derived from a mathematical model that can be easily implemented in clinical practice has not previously been described for the prediction of ongoing viability. This was a prospective observational study in a single early pregnancy assessment centre during a 9-month period. A cohort of 1881 consecutive women undergoing transvaginal ultrasound scan at a gestational age <84 days were included. Women were excluded if the first trimester outcome was not known. Demographic features, symptoms and ultrasound variables were tested for their influence on ongoing viability. Logistic regression was used to determine the influence on first trimester viability from demographics and symptoms alone, ultrasound findings alone and then from all the variables combined. Each model was developed on a training data set, and a simple scoring system was derived from this. This scoring system was tested on an independent test data set. The final outcome based on a total of 1435 participants was an ongoing viable pregnancy in 885 (61.7%) and early pregnancy loss in 550 (38.3%) women. The scoring system using significant demographic variables alone (maternal age and amount of bleeding) to predict ongoing viability gave an AUC of 0.724 (95% CI = 0.692-0.756) in the training set

  9. Robust and accurate decoding of motoneuron behavior and prediction of the resulting force output.

    PubMed

    Thompson, Christopher K; Negro, Francesco; Johnson, Michael D; Holmes, Matthew R; McPherson, Laura Miller; Powers, Randall K; Farina, Dario; Heckman, Charles J

    2018-05-03

    The spinal alpha motoneuron is the only cell in the human CNS whose discharge can be routinely recorded in humans. We have reengineered motor unit collection and decomposition approaches, originally developed in humans, to measure the neural drive to muscle and estimate muscle force generation in the decerebrate cat model. Experimental, computational, and predictive approaches are used to demonstrate the validity of this approach across a wide range of modes to activate the motor pool. The utility of this approach is shown through the ability to track individual motor units across trials, allowing for better predictions of muscle force than the electromyography signal, and providing insights in to the stereotypical discharge characteristics in response to synaptic activation of the motor pool. This approach now allows for a direct link between the intracellular data of single motoneurons, the discharge properties of motoneuron populations, and muscle force generation in the same preparation. The discharge of a spinal alpha motoneuron and the resulting contraction of its muscle fibers represents the functional quantum of the motor system. Recent advances in the recording and decomposition of the electromyographic signal allows for the identification of several tens of concurrently active motor units. These detailed population data provide the potential to achieve deep insights into the synaptic organization of motor commands. Yet most of our understanding of the synaptic input to motoneurons is derived from intracellular recordings in animal preparations. Thus, it is necessary to extend the new electrode and decomposition methods to recording of motor unit populations in these same preparations. To achieve this goal, we use high-density electrode arrays and decomposition techniques, analogous to those developed for humans, to record and decompose the activity of tens of concurrently active motor units in a hindlimb muscle in the decerebrate cat. Our results showed

  10. An Accurate Temperature Correction Model for Thermocouple Hygrometers 1

    PubMed Central

    Savage, Michael J.; Cass, Alfred; de Jager, James M.

    1982-01-01

    Numerous water relation studies have used thermocouple hygrometers routinely. However, the accurate temperature correction of hygrometer calibration curve slopes seems to have been largely neglected in both psychrometric and dewpoint techniques. In the case of thermocouple psychrometers, two temperature correction models are proposed, each based on measurement of the thermojunction radius and calculation of the theoretical voltage sensitivity to changes in water potential. The first model relies on calibration at a single temperature and the second at two temperatures. Both these models were more accurate than the temperature correction models currently in use for four psychrometers calibrated over a range of temperatures (15-38°C). The model based on calibration at two temperatures is superior to that based on only one calibration. The model proposed for dewpoint hygrometers is similar to that for psychrometers. It is based on the theoretical voltage sensitivity to changes in water potential. Comparison with empirical data from three dewpoint hygrometers calibrated at four different temperatures indicates that these instruments need only be calibrated at, e.g. 25°C, if the calibration slopes are corrected for temperature. PMID:16662241

  11. 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. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  12. Accurate prediction of collapse temperature using optical coherence tomography-based freeze-drying microscopy.

    PubMed

    Greco, Kristyn; Mujat, Mircea; Galbally-Kinney, Kristin L; Hammer, Daniel X; Ferguson, R Daniel; Iftimia, Nicusor; Mulhall, Phillip; Sharma, Puneet; Kessler, William J; Pikal, Michael J

    2013-06-01

    The objective of this study was to assess the feasibility of developing and applying a laboratory tool that can provide three-dimensional product structural information during freeze-drying and which can accurately characterize the collapse temperature (Tc ) of pharmaceutical formulations designed for freeze-drying. A single-vial freeze dryer coupled with optical coherence tomography freeze-drying microscopy (OCT-FDM) was developed to investigate the structure and Tc of formulations in pharmaceutically relevant products containers (i.e., freeze-drying in vials). OCT-FDM was used to measure the Tc and eutectic melt of three formulations in freeze-drying vials. The Tc as measured by OCT-FDM was found to be predictive of freeze-drying with a batch of vials in a conventional laboratory freeze dryer. The freeze-drying cycles developed using OCT-FDM data, as compared with traditional light transmission freeze-drying microscopy (LT-FDM), resulted in a significant reduction in primary drying time, which could result in a substantial reduction of manufacturing costs while maintaining product quality. OCT-FDM provides quantitative data to justify freeze-drying at temperatures higher than the Tc measured by LT-FDM and provides a reliable upper limit to setting a product temperature in primary drying. Copyright © 2013 Wiley Periodicals, Inc.

  13. Hindered rotor models with variable kinetic functions for accurate thermodynamic and kinetic predictions

    NASA Astrophysics Data System (ADS)

    Reinisch, Guillaume; Leyssale, Jean-Marc; Vignoles, Gérard L.

    2010-10-01

    We present an extension of some popular hindered rotor (HR) models, namely, the one-dimensional HR (1DHR) and the degenerated two-dimensional HR (d2DHR) models, allowing for a simple and accurate treatment of internal rotations. This extension, based on the use of a variable kinetic function in the Hamiltonian instead of a constant reduced moment of inertia, is extremely suitable in the case of rocking/wagging motions involved in dissociation or atom transfer reactions. The variable kinetic function is first introduced in the framework of a classical 1DHR model. Then, an effective temperature and potential dependent constant is proposed in the cases of quantum 1DHR and classical d2DHR models. These methods are finally applied to the atom transfer reaction SiCl3+BCl3→SiCl4+BCl2. We show, for this particular case, that a proper accounting of internal rotations greatly improves the accuracy of thermodynamic and kinetic predictions. Moreover, our results confirm (i) that using a suitably defined kinetic function appears to be very adapted to such problems; (ii) that the separability assumption of independent rotations seems justified; and (iii) that a quantum mechanical treatment is not a substantial improvement with respect to a classical one.

  14. Highly accurate nephelometric titrimetry.

    PubMed

    Zhan, Xiancheng; Li, Chengrong; Li, Zhiyi; Yang, Xiucen; Zhong, Shuguang; Yi, Tao

    2004-02-01

    A method that accurately indicates the end-point of precipitation reactions by the measurement of the relative intensity of the scattered light in the titrate is presented. A new nephelometric titrator with an internal nephelometric sensor has been devised. The work of the titrator including the sensor and change in the turbidity of the titrate and intensity of the scattered light are described. The accuracy of the nephelometric titrimetry is discussed theoretically. The titration of NaCl with AgNO(3) serves as a model. A relative error as well as deviation is within 0.2% under the experimental conditions. The applicability of the titrimetry in pharmaceutical analyses, for example, phenytoin sodium and procaine hydrochloride, is generally illustrated. Copyright 2004 Wiley-Liss, Inc. and the American Pharmacists Association

  15. Ab Initio Potential Energy Surfaces and the Calculation of Accurate Vibrational Frequencies

    NASA Technical Reports Server (NTRS)

    Lee, Timothy J.; Dateo, Christopher E.; Martin, Jan M. L.; Taylor, Peter R.; Langhoff, Stephen R. (Technical Monitor)

    1995-01-01

    Due to advances in quantum mechanical methods over the last few years, it is now possible to determine ab initio potential energy surfaces in which fundamental vibrational frequencies are accurate to within plus or minus 8 cm(exp -1) on average, and molecular bond distances are accurate to within plus or minus 0.001-0.003 Angstroms, depending on the nature of the bond. That is, the potential energy surfaces have not been scaled or empirically adjusted in any way, showing that theoretical methods have progressed to the point of being useful in analyzing spectra that are not from a tightly controlled laboratory environment, such as vibrational spectra from the interstellar medium. Some recent examples demonstrating this accuracy will be presented and discussed. These include the HNO, CH4, C2H4, and ClCN molecules. The HNO molecule is interesting due to the very large H-N anharmonicity, while ClCN has a very large Fermi resonance. The ab initio studies for the CH4 and C2H4 molecules present the first accurate full quartic force fields of any kind (i.e., whether theoretical or empirical) for a five-atom and six-atom system, respectively.

  16. Chaotic advection at large Péclet number: Electromagnetically driven experiments, numerical simulations, and theoretical predictions

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Figueroa, Aldo; Meunier, Patrice; Villermaux, Emmanuel

    2014-01-15

    We present a combination of experiment, theory, and modelling on laminar mixing at large Péclet number. The flow is produced by oscillating electromagnetic forces in a thin electrolytic fluid layer, leading to oscillating dipoles, quadrupoles, octopoles, and disordered flows. The numerical simulations are based on the Diffusive Strip Method (DSM) which was recently introduced (P. Meunier and E. Villermaux, “The diffusive strip method for scalar mixing in two-dimensions,” J. Fluid Mech. 662, 134–172 (2010)) to solve the advection-diffusion problem by combining Lagrangian techniques and theoretical modelling of the diffusion. Numerical simulations obtained with the DSM are in reasonable agreement withmore » quantitative dye visualization experiments of the scalar fields. A theoretical model based on log-normal Probability Density Functions (PDFs) of stretching factors, characteristic of homogeneous turbulence in the Batchelor regime, allows to predict the PDFs of scalar in agreement with numerical and experimental results. This model also indicates that the PDFs of scalar are asymptotically close to log-normal at late stages, except for the large concentration levels which correspond to low stretching factors.« less

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

    PubMed Central

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

    2016-01-01

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

  18. Theoretical predictions for α -decay chains of 118 290 -298Og isotopes using a finite-range nucleon-nucleon interaction

    NASA Astrophysics Data System (ADS)

    Ismail, M.; Adel, A.

    2018-04-01

    The α -decay half-lives of the recently synthesized superheavy nuclei (SHN) are investigated by employing the density dependent cluster model. A realistic nucleon-nucleon (NN ) interaction with a finite-range exchange part is used to calculate the microscopic α -nucleus potential in the well-established double-folding model. The calculated potential is then implemented to find both the assault frequency and the penetration probability of the α particle by means of the Wentzel-Kramers-Brillouin (WKB) approximation in combination with the Bohr-Sommerfeld quantization condition. The calculated values of α -decay half-lives of the recently synthesized Og isotopes and its decay products are in good agreement with the experimental data. Moreover, the calculated values of α -decay half-lives have been compared with those values evaluated using other theoretical models, and it was found that our theoretical values match well with their counterparts. The competition between α decay and spontaneous fission is investigated and predictions for possible decay modes for the unknown nuclei 118 290 -298Og are presented. We studied the behavior of the α -decay half-lives of Og isotopes and their decay products as a function of the mass number of the parent nuclei. We found that the behavior of the curves is governed by proton and neutron magic numbers found from previous studies. The proton numbers Z =114 , 116, 108, 106 and the neutron numbers N =172 , 164, 162, 158 show some magic character. We hope that the theoretical prediction of α -decay chains provides a new perspective to experimentalists.

  19. Spectral and structural studies of the anti-cancer drug Flutamide by density functional theoretical method

    NASA Astrophysics Data System (ADS)

    Mariappan, G.; Sundaraganesan, N.

    2014-01-01

    A comprehensive screening of the more recent DFT theoretical approach to structural analysis is presented in this section of theoretical structural analysis. The chemical name of 2-methyl-N-[4-nitro-3-(trifluoromethyl)phenyl]-propanamide is usually called as Flutamide (In the present study it is abbreviated as FLT) and is an important and efficacious drug in the treatment of anti-cancer resistant. The molecular geometry, vibrational spectra, electronic and NMR spectral interpretation of Flutamide have been studied with the aid of density functional theory method (DFT). The vibrational assignments of the normal modes were performed on the basis of the PED calculations using the VEDA 4 program. Comparison of computational results with X-ray diffraction results of Flutamide allowed the evaluation of structure predictions and confirmed B3LYP/6-31G(d,p) as accurate for structure determination. Application of scaling factors for IR and Raman frequency predictions showed good agreement with experimental values. This is supported the assignment of the major contributors of the vibration modes of the title compound. Stability of the molecule arising from hyperconjugative interactions leading to its bioactivity, charge delocalization have been analyzed using natural bond orbital (NBO) analysis. NMR chemical shifts of the molecule were calculated using the gauge independent atomic orbital (GIAO) method. The comparison of measured FTIR, FT-Raman, and UV-Visible data to calculated values allowed assignment of major spectral features of the title molecule. Besides, Frontier molecular orbital analyze was also investigated using theoretical calculations.

  20. Combining Mean and Standard Deviation of Hounsfield Unit Measurements from Preoperative CT Allows More Accurate Prediction of Urinary Stone Composition Than Mean Hounsfield Units Alone.

    PubMed

    Tailly, Thomas; Larish, Yaniv; Nadeau, Brandon; Violette, Philippe; Glickman, Leonard; Olvera-Posada, Daniel; Alenezi, Husain; Amann, Justin; Denstedt, John; Razvi, Hassan

    2016-04-01

    The mineral composition of a urinary stone may influence its surgical and medical treatment. Previous attempts at identifying stone composition based on mean Hounsfield Units (HUm) have had varied success. We aimed to evaluate the additional use of standard deviation of HU (HUsd) to more accurately predict stone composition. We identified patients from two centers who had undergone urinary stone treatment between 2006 and 2013 and had mineral stone analysis and a computed tomography (CT) available. HUm and HUsd of the stones were compared with ANOVA. Receiver operative characteristic analysis with area under the curve (AUC), Youden index, and likelihood ratio calculations were performed. Data were available for 466 patients. The major components were calcium oxalate monohydrate (COM), uric acid, hydroxyapatite, struvite, brushite, cystine, and CO dihydrate (COD) in 41.4%, 19.3%, 12.4%, 7.5%, 5.8%, 5.4%, and 4.7% of patients, respectively. The HUm of UA and Br was significantly lower and higher than the HUm of any other stone type, respectively. HUm and HUsd were most accurate in predicting uric acid with an AUC of 0.969 and 0.851, respectively. The combined use of HUm and HUsd resulted in increased positive predictive value and higher likelihood ratios for identifying a stone's mineral composition for all stone types but COM. To the best of our knowledge, this is the first report of CT data aiding in the prediction of brushite stone composition. Both HUm and HUsd can help predict stone composition and their combined use results in higher likelihood ratios influencing probability.

  1. 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

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

    PubMed

    Wang, Shiyao; Deng, Zhidong; Yin, Gang

    2016-02-24

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

  3. Frequency, probability, and prediction: easy solutions to cognitive illusions?

    PubMed

    Griffin, D; Buehler, R

    1999-02-01

    Many errors in probabilistic judgment have been attributed to people's inability to think in statistical terms when faced with information about a single case. Prior theoretical analyses and empirical results imply that the errors associated with case-specific reasoning may be reduced when people make frequentistic predictions about a set of cases. In studies of three previously identified cognitive biases, we find that frequency-based predictions are different from-but no better than-case-specific judgments of probability. First, in studies of the "planning fallacy, " we compare the accuracy of aggregate frequency and case-specific probability judgments in predictions of students' real-life projects. When aggregate and single-case predictions are collected from different respondents, there is little difference between the two: Both are overly optimistic and show little predictive validity. However, in within-subject comparisons, the aggregate judgments are significantly more conservative than the single-case predictions, though still optimistically biased. Results from studies of overconfidence in general knowledge and base rate neglect in categorical prediction underline a general conclusion. Frequentistic predictions made for sets of events are no more statistically sophisticated, nor more accurate, than predictions made for individual events using subjective probability. Copyright 1999 Academic Press.

  4. A Novel Information-Theoretic Approach for Variable Clustering and Predictive Modeling Using Dirichlet Process Mixtures

    PubMed Central

    Chen, Yun; Yang, Hui

    2016-01-01

    In the era of big data, there are increasing interests on clustering variables for the minimization of data redundancy and the maximization of variable relevancy. Existing clustering methods, however, depend on nontrivial assumptions about the data structure. Note that nonlinear interdependence among variables poses significant challenges on the traditional framework of predictive modeling. In the present work, we reformulate the problem of variable clustering from an information theoretic perspective that does not require the assumption of data structure for the identification of nonlinear interdependence among variables. Specifically, we propose the use of mutual information to characterize and measure nonlinear correlation structures among variables. Further, we develop Dirichlet process (DP) models to cluster variables based on the mutual-information measures among variables. Finally, orthonormalized variables in each cluster are integrated with group elastic-net model to improve the performance of predictive modeling. Both simulation and real-world case studies showed that the proposed methodology not only effectively reveals the nonlinear interdependence structures among variables but also outperforms traditional variable clustering algorithms such as hierarchical clustering. PMID:27966581

  5. A Novel Information-Theoretic Approach for Variable Clustering and Predictive Modeling Using Dirichlet Process Mixtures.

    PubMed

    Chen, Yun; Yang, Hui

    2016-12-14

    In the era of big data, there are increasing interests on clustering variables for the minimization of data redundancy and the maximization of variable relevancy. Existing clustering methods, however, depend on nontrivial assumptions about the data structure. Note that nonlinear interdependence among variables poses significant challenges on the traditional framework of predictive modeling. In the present work, we reformulate the problem of variable clustering from an information theoretic perspective that does not require the assumption of data structure for the identification of nonlinear interdependence among variables. Specifically, we propose the use of mutual information to characterize and measure nonlinear correlation structures among variables. Further, we develop Dirichlet process (DP) models to cluster variables based on the mutual-information measures among variables. Finally, orthonormalized variables in each cluster are integrated with group elastic-net model to improve the performance of predictive modeling. Both simulation and real-world case studies showed that the proposed methodology not only effectively reveals the nonlinear interdependence structures among variables but also outperforms traditional variable clustering algorithms such as hierarchical clustering.

  6. Referential Choice: Predictability and Its Limits

    PubMed Central

    Kibrik, Andrej A.; Khudyakova, Mariya V.; Dobrov, Grigory B.; Linnik, Anastasia; Zalmanov, Dmitrij A.

    2016-01-01

    We report a study of referential choice in discourse production, understood as the choice between various types of referential devices, such as pronouns and full noun phrases. Our goal is to predict referential choice, and to explore to what extent such prediction is possible. Our approach to referential choice includes a cognitively informed theoretical component, corpus analysis, machine learning methods and experimentation with human participants. Machine learning algorithms make use of 25 factors, including referent’s properties (such as animacy and protagonism), the distance between a referential expression and its antecedent, the antecedent’s syntactic role, and so on. Having found the predictions of our algorithm to coincide with the original almost 90% of the time, we hypothesized that fully accurate prediction is not possible because, in many situations, more than one referential option is available. This hypothesis was supported by an experimental study, in which participants answered questions about either the original text in the corpus, or about a text modified in accordance with the algorithm’s prediction. Proportions of correct answers to these questions, as well as participants’ rating of the questions’ difficulty, suggested that divergences between the algorithm’s prediction and the original referential device in the corpus occur overwhelmingly in situations where the referential choice is not categorical. PMID:27721800

  7. A comparison of experimental and theoretical results for labyrinth gas seals with honeycomb stators. M.S. Thesis

    NASA Technical Reports Server (NTRS)

    Hawkins, Lawrence Allen

    1988-01-01

    Experimental results for the rotordynamic stiffness and damping coefficients of a labyrinth -rotor honeycomb-stator seal are presented. The coefficients are compared to the coefficients of a labyrinth-rotor smooth-stator seal having the same geometry. The coefficients are compared to analytical results from a two-control-volume compressible flow model. The experimental results show that the honeycomb stator configuration is more stable than the smooth stator configuration at low rotor speeds. At high rotor speeds and low clearance, the smooth stator seal is more stable. The theoretical model predicts the cross-coupled stiffness of the honeycomb stator seal correctly within 25 percent of measured values. The model provides accurate predictions of direct damping for large clearance seals. Overall, the model does not perform as well for low clearance seals as for high clearance seals.

  8. Accurate quasiparticle calculation of x-ray photoelectron spectra of solids

    NASA Astrophysics Data System (ADS)

    Aoki, Tsubasa; Ohno, Kaoru

    2018-05-01

    It has been highly desired to provide an accurate and reliable method to calculate core electron binding energies (CEBEs) of crystals and to understand the final state screening effect on a core hole in high resolution x-ray photoelectron spectroscopy (XPS), because the ΔSCF method cannot be simply used for bulk systems. We propose to use the quasiparticle calculation based on many-body perturbation theory for this problem. In this study, CEBEs of band-gapped crystals, silicon, diamond, β-SiC, BN, and AlP, are investigated by means of the GW approximation (GWA) using the full ω integration and compared with the preexisting XPS data. The screening effect on a deep core hole is also investigated in detail by evaluating the relaxation energy (RE) from the core and valence contributions separately. Calculated results show that not only the valence electrons but also the core electrons have an important contribution to the RE, and the GWA have a tendency to underestimate CEBEs due to the excess RE. This underestimation can be improved by introducing the self-screening correction to the GWA. The resulting C1s, B1s, N1s, Si2p, and Al2p CEBEs are in excellent agreement with the experiments within 1 eV absolute error range. The present self-screening corrected GW approach has the capability to achieve the highly accurate prediction of CEBEs without any empirical parameter for band-gapped crystals, and provide a more reliable theoretical approach than the conventional ΔSCF-DFT method.

  9. Accurate quasiparticle calculation of x-ray photoelectron spectra of solids.

    PubMed

    Aoki, Tsubasa; Ohno, Kaoru

    2018-05-31

    It has been highly desired to provide an accurate and reliable method to calculate core electron binding energies (CEBEs) of crystals and to understand the final state screening effect on a core hole in high resolution x-ray photoelectron spectroscopy (XPS), because the ΔSCF method cannot be simply used for bulk systems. We propose to use the quasiparticle calculation based on many-body perturbation theory for this problem. In this study, CEBEs of band-gapped crystals, silicon, diamond, β-SiC, BN, and AlP, are investigated by means of the GW approximation (GWA) using the full ω integration and compared with the preexisting XPS data. The screening effect on a deep core hole is also investigated in detail by evaluating the relaxation energy (RE) from the core and valence contributions separately. Calculated results show that not only the valence electrons but also the core electrons have an important contribution to the RE, and the GWA have a tendency to underestimate CEBEs due to the excess RE. This underestimation can be improved by introducing the self-screening correction to the GWA. The resulting C1s, B1s, N1s, Si2p, and Al2p CEBEs are in excellent agreement with the experiments within 1 eV absolute error range. The present self-screening corrected GW approach has the capability to achieve the highly accurate prediction of CEBEs without any empirical parameter for band-gapped crystals, and provide a more reliable theoretical approach than the conventional ΔSCF-DFT method.

  10. Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification.

    PubMed

    Andreatta, Massimo; Karosiene, Edita; Rasmussen, Michael; Stryhn, Anette; Buus, Søren; Nielsen, Morten

    2015-11-01

    A key event in the generation of a cellular response against malicious organisms through the endocytic pathway is binding of peptidic antigens by major histocompatibility complex class II (MHC class II) molecules. The bound peptide is then presented on the cell surface where it can be recognized by T helper lymphocytes. NetMHCIIpan is a state-of-the-art method for the quantitative prediction of peptide binding to any human or mouse MHC class II molecule of known sequence. In this paper, we describe an updated version of the method with improved peptide binding register identification. Binding register prediction is concerned with determining the minimal core region of nine residues directly in contact with the MHC binding cleft, a crucial piece of information both for the identification and design of CD4(+) T cell antigens. When applied to a set of 51 crystal structures of peptide-MHC complexes with known binding registers, the new method NetMHCIIpan-3.1 significantly outperformed the earlier 3.0 version. We illustrate the impact of accurate binding core identification for the interpretation of T cell cross-reactivity using tetramer double staining with a CMV epitope and its variants mapped to the epitope binding core. NetMHCIIpan is publicly available at http://www.cbs.dtu.dk/services/NetMHCIIpan-3.1 .

  11. 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 Central

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

    2016-01-01

    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

  12. Theoretical study of solvent effects on the coil-globule transition

    NASA Astrophysics Data System (ADS)

    Polson, James M.; Opps, Sheldon B.; Abou Risk, Nicholas

    2009-06-01

    The coil-globule transition of a polymer in a solvent has been studied using Monte Carlo simulations of a single chain subject to intramolecular interactions as well as a solvent-mediated effective potential. This solvation potential was calculated using several different theoretical approaches for two simple polymer/solvent models, each employing hard-sphere chains and hard-sphere solvent particles as well as attractive square-well potentials between some interaction sites. For each model, collapse is driven by variation in a parameter which changes the energy mismatch between monomers and solvent particles. The solvation potentials were calculated using two fundamentally different methodologies, each designed to predict the conformational behavior of polymers in solution: (1) the polymer reference interaction site model (PRISM) theory and (2) a many-body solvation potential (MBSP) based on scaled particle theory introduced by Grayce [J. Chem. Phys. 106, 5171 (1997)]. For the PRISM calculations, two well-studied solvation monomer-monomer pair potentials were employed, each distinguished by the closure relation used in its derivation: (i) a hypernetted-chain (HNC)-type potential and (ii) a Percus-Yevick (PY)-type potential. The theoretical predictions were each compared to results obtained from explicit-solvent discontinuous molecular dynamics simulations on the same polymer/solvent model systems [J. Chem. Phys. 125, 194904 (2006)]. In each case, the variation in the coil-globule transition properties with solvent density is mostly qualitatively correct, though the quantitative agreement between the theory and prediction is typically poor. The HNC-type potential yields results that are more qualitatively consistent with simulation. The conformational behavior of the polymer upon collapse predicted by the MBSP approach is quantitatively correct for low and moderate solvent densities but is increasingly less accurate for higher densities. At high solvent densities

  13. Theoretical predictions of vibration-rotation-tunneling dynamics of the weakly bound trimer (H 2O) 2HCl

    NASA Astrophysics Data System (ADS)

    Struniewicz, Cezary; Korona, Tatiana; Moszynski, Robert; Milet, Anne

    2001-08-01

    In this Letter we report a theoretical study of the vibration-rotation-tunneling (VRT) states of the (H 2O) 2HCl trimer. Five degrees of freedom are considered: two angles corresponding to the torsional (flipping) motions of the free, non-hydrogen-bonded, hydrogen atoms in the complex, and three angles describing the overall rotation of the trimer in the space. A two-dimensional potential energy surface is generated ab initio by symmetry-adapted perturbation theory (SAPT). Tunneling splittings, frequencies of the intermolecular vibrations, and vibrational line strengths of spectroscopic transitions are predicted.

  14. Learning a weighted sequence model of the nucleosome core and linker yields more accurate predictions in Saccharomyces cerevisiae and Homo sapiens.

    PubMed

    Reynolds, Sheila M; Bilmes, Jeff A; Noble, William Stafford

    2010-07-08

    DNA in eukaryotes is packaged into a chromatin complex, the most basic element of which is the nucleosome. The precise positioning of the nucleosome cores allows for selective access to the DNA, and the mechanisms that control this positioning are important pieces of the gene expression puzzle. We describe a large-scale nucleosome pattern that jointly characterizes the nucleosome core and the adjacent linkers and is predominantly characterized by long-range oscillations in the mono, di- and tri-nucleotide content of the DNA sequence, and we show that this pattern can be used to predict nucleosome positions in both Homo sapiens and Saccharomyces cerevisiae more accurately than previously published methods. Surprisingly, in both H. sapiens and S. cerevisiae, the most informative individual features are the mono-nucleotide patterns, although the inclusion of di- and tri-nucleotide features results in improved performance. Our approach combines a much longer pattern than has been previously used to predict nucleosome positioning from sequence-301 base pairs, centered at the position to be scored-with a novel discriminative classification approach that selectively weights the contributions from each of the input features. The resulting scores are relatively insensitive to local AT-content and can be used to accurately discriminate putative dyad positions from adjacent linker regions without requiring an additional dynamic programming step and without the attendant edge effects and assumptions about linker length modeling and overall nucleosome density. Our approach produces the best dyad-linker classification results published to date in H. sapiens, and outperforms two recently published models on a large set of S. cerevisiae nucleosome positions. Our results suggest that in both genomes, a comparable and relatively small fraction of nucleosomes are well-positioned and that these positions are predictable based on sequence alone. We believe that the bulk of the

  15. Learning a Weighted Sequence Model of the Nucleosome Core and Linker Yields More Accurate Predictions in Saccharomyces cerevisiae and Homo sapiens

    PubMed Central

    Reynolds, Sheila M.; Bilmes, Jeff A.; Noble, William Stafford

    2010-01-01

    DNA in eukaryotes is packaged into a chromatin complex, the most basic element of which is the nucleosome. The precise positioning of the nucleosome cores allows for selective access to the DNA, and the mechanisms that control this positioning are important pieces of the gene expression puzzle. We describe a large-scale nucleosome pattern that jointly characterizes the nucleosome core and the adjacent linkers and is predominantly characterized by long-range oscillations in the mono, di- and tri-nucleotide content of the DNA sequence, and we show that this pattern can be used to predict nucleosome positions in both Homo sapiens and Saccharomyces cerevisiae more accurately than previously published methods. Surprisingly, in both H. sapiens and S. cerevisiae, the most informative individual features are the mono-nucleotide patterns, although the inclusion of di- and tri-nucleotide features results in improved performance. Our approach combines a much longer pattern than has been previously used to predict nucleosome positioning from sequence—301 base pairs, centered at the position to be scored—with a novel discriminative classification approach that selectively weights the contributions from each of the input features. The resulting scores are relatively insensitive to local AT-content and can be used to accurately discriminate putative dyad positions from adjacent linker regions without requiring an additional dynamic programming step and without the attendant edge effects and assumptions about linker length modeling and overall nucleosome density. Our approach produces the best dyad-linker classification results published to date in H. sapiens, and outperforms two recently published models on a large set of S. cerevisiae nucleosome positions. Our results suggest that in both genomes, a comparable and relatively small fraction of nucleosomes are well-positioned and that these positions are predictable based on sequence alone. We believe that the bulk of the

  16. Accurate predictions of population-level changes in sequence and structural properties of HIV-1 Env using a volatility-controlled diffusion model

    PubMed Central

    DeLeon, Orlando; Hodis, Hagit; O’Malley, Yunxia; Johnson, Jacklyn; Salimi, Hamid; Zhai, Yinjie; Winter, Elizabeth; Remec, Claire; Eichelberger, Noah; Van Cleave, Brandon; Puliadi, Ramya; Harrington, Robert D.; Stapleton, Jack T.; Haim, Hillel

    2017-01-01

    The envelope glycoproteins (Envs) of HIV-1 continuously evolve in the host by random mutations and recombination events. The resulting diversity of Env variants circulating in the population and their continuing diversification process limit the efficacy of AIDS vaccines. We examined the historic changes in Env sequence and structural features (measured by integrity of epitopes on the Env trimer) in a geographically defined population in the United States. As expected, many Env features were relatively conserved during the 1980s. From this state, some features diversified whereas others remained conserved across the years. We sought to identify “clues” to predict the observed historic diversification patterns. Comparison of viruses that cocirculate in patients at any given time revealed that each feature of Env (sequence or structural) exists at a defined level of variance. The in-host variance of each feature is highly conserved among individuals but can vary between different HIV-1 clades. We designate this property “volatility” and apply it to model evolution of features as a linear diffusion process that progresses with increasing genetic distance. Volatilities of different features are highly correlated with their divergence in longitudinally monitored patients. Volatilities of features also correlate highly with their population-level diversification. Using volatility indices measured from a small number of patient samples, we accurately predict the population diversity that developed for each feature over the course of 30 years. Amino acid variants that evolved at key antigenic sites are also predicted well. Therefore, small “fluctuations” in feature values measured in isolated patient samples accurately describe their potential for population-level diversification. These tools will likely contribute to the design of population-targeted AIDS vaccines by effectively capturing the diversity of currently circulating strains and addressing properties

  17. Analytical prediction of sub-surface thermal history in translucent tissue phantoms during plasmonic photo-thermotherapy (PPTT).

    PubMed

    Dhar, Purbarun; Paul, Anup; Narasimhan, Arunn; Das, Sarit K

    2016-12-01

    Knowledge of thermal history and/or distribution in biological tissues during laser based hyperthermia is essential to achieve necrosis of tumour/carcinoma cells. A semi-analytical model to predict sub-surface thermal distribution in translucent, soft, tissue mimics has been proposed. The model can accurately predict the spatio-temporal temperature variations along depth and the anomalous thermal behaviour in such media, viz. occurrence of sub-surface temperature peaks. Based on optical and thermal properties, the augmented temperature and shift of the peak positions in case of gold nanostructure mediated tissue phantom hyperthermia can be predicted. Employing inverse approach, the absorption coefficient of nano-graphene infused tissue mimics is determined from the peak temperature and found to provide appreciably accurate predictions along depth. Furthermore, a simplistic, dimensionally consistent correlation to theoretically determine the position of the peak in such media is proposed and found to be consistent with experiments and computations. The model shows promise in predicting thermal distribution induced by lasers in tissues and deduction of therapeutic hyperthermia parameters, thereby assisting clinical procedures by providing a priori estimates. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Hierarchical representations of the five-factor model of personality in predicting job performance: integrating three organizing frameworks with two theoretical perspectives.

    PubMed

    Judge, Timothy A; Rodell, Jessica B; Klinger, Ryan L; Simon, Lauren S; Crawford, Eean R

    2013-11-01

    Integrating 2 theoretical perspectives on predictor-criterion relationships, the present study developed and tested a hierarchical framework in which each five-factor model (FFM) personality trait comprises 2 DeYoung, Quilty, and Peterson (2007) facets, which in turn comprise 6 Costa and McCrae (1992) NEO facets. Both theoretical perspectives-the bandwidth-fidelity dilemma and construct correspondence-suggest that lower order traits would better predict facets of job performance (task performance and contextual performance). They differ, however, as to the relative merits of broad and narrow traits in predicting a broad criterion (overall job performance). We first meta-analyzed the relationship of the 30 NEO facets to overall job performance and its facets. Overall, 1,176 correlations from 410 independent samples (combined N = 406,029) were coded and meta-analyzed. We then formed the 10 DeYoung et al. facets from the NEO facets, and 5 broad traits from those facets. Overall, results provided support for the 6-2-1 framework in general and the importance of the NEO facets in particular. (c) 2013 APA, all rights reserved.

  19. A Novel Quasi-One-Dimensional Topological Insulator in Bismuth Iodide β-Bi4I4: Theoretical Prediction and Experimental Confirmation

    NASA Astrophysics Data System (ADS)

    Yazyev, Oleg V.; Autès, Gabriel; Isaeva, Anna; Moreschini, Luca; Johannsen, Jens C.; Pisoni, Andrea; Filatova, Taisia G.; Kuznetsov, Alexey N.; Forró, László; van den Broek, Wouter; Kim, Yeongkwan; Denlinger, Jonathan D.; Rotenberg, Eli; Bostwick, Aaron; Grioni, Marco

    2015-03-01

    A new strong Z2 topological insulator is theoretically predicted and experimentally confirmed in the β-phase of quasi-one-dimensional bismuth iodide Bi4I4. According to our first-principles calculations the material is characterized by Z2 invariants (1;110) making it the first representative of this topological class. Importantly, the electronic structure of β-Bi4I4 is in proximity with both the weak topological insulator phase (0;001) and the trivial phase (0;000), suggesting that a high degree of control over the topological electronic properties of this material can be achieved. Experimentally produced samples of this material appears to be practically defect-free, which results in a low concentration of intrinsic charge carriers. By using angle-resolved photoemission spectroscopy (ARPES) on the (001) surface we confirm the theoretical predictions of a highly anisotropic band structure with a small band gap hosting topological surface states centered at the M point, at the boundary of the surface Brillouin zone. We acknowledge support from Swiss NSF, ERC project ``TopoMat'', NCCR-MARVEL, DFG and US DoE. G.A., A.I., L.M. and J.C.J. contributed equally to this work.

  20. 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).

  1. 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).

  2. Quicksilver: Fast predictive image registration - A deep learning approach.

    PubMed

    Yang, Xiao; Kwitt, Roland; Styner, Martin; Niethammer, Marc

    2017-09-01

    This paper introduces Quicksilver, a fast deformable image registration method. Quicksilver registration for image-pairs works by patch-wise prediction of a deformation model based directly on image appearance. A deep encoder-decoder network is used as the prediction model. While the prediction strategy is general, we focus on predictions for the Large Deformation Diffeomorphic Metric Mapping (LDDMM) model. Specifically, we predict the momentum-parameterization of LDDMM, which facilitates a patch-wise prediction strategy while maintaining the theoretical properties of LDDMM, such as guaranteed diffeomorphic mappings for sufficiently strong regularization. We also provide a probabilistic version of our prediction network which can be sampled during the testing time to calculate uncertainties in the predicted deformations. Finally, we introduce a new correction network which greatly increases the prediction accuracy of an already existing prediction network. We show experimental results for uni-modal atlas-to-image as well as uni-/multi-modal image-to-image registrations. These experiments demonstrate that our method accurately predicts registrations obtained by numerical optimization, is very fast, achieves state-of-the-art registration results on four standard validation datasets, and can jointly learn an image similarity measure. Quicksilver is freely available as an open-source software. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. A NEW CLINICAL PREDICTION CRITERION ACCURATELY DETERMINES A SUBSET OF PATIENTS WITH BILATERAL PRIMARY ALDOSTERONISM BEFORE ADRENAL VENOUS SAMPLING.

    PubMed

    Kocjan, Tomaz; Janez, Andrej; Stankovic, Milenko; Vidmar, Gaj; Jensterle, Mojca

    2016-05-01

    Adrenal venous sampling (AVS) is the only available method to distinguish bilateral from unilateral primary aldosteronism (PA). AVS has several drawbacks, so it is reasonable to avoid this procedure when the results would not affect clinical management. Our objective was to identify a clinical criterion that can reliably predict nonlateralized AVS as a surrogate for bilateral PA that is not treated surgically. A retrospective diagnostic cross-sectional study conducted at Slovenian national endocrine referral center included 69 consecutive patients (mean age 56 ± 8 years, 21 females) with PA who underwent AVS. PA was confirmed with the saline infusion test (SIT). AVS was performed sequentially during continuous adrenocorticotrophic hormone (ACTH) infusion. The main outcome measures were variables associated with nonlateralized AVS to derive a clinical prediction rule. Sixty-seven (97%) patients had a successful AVS and were included in the statistical analysis. A total of 39 (58%) patients had nonlateralized AVS. The combined criterion of serum potassium ≥3.5 mmol/L, post-SIT aldosterone <18 ng/dL, and either no or bilateral tumor found on computed tomography (CT) imaging had perfect estimated specificity (and thus 100% positive predictive value) for bilateral PA, saving an estimated 16% of the patients (11/67) from unnecessary AVS. The best overall classification accuracy (50/67 = 75%) was achieved using the post-SIT aldosterone level <18 ng/dL alone, which yielded 74% sensitivity and 75% specificity for predicting nonlateralized AVS. Our clinical prediction criterion appears to accurately determine a subset of patients with bilateral PA who could avoid unnecessary AVS and immediately commence with medical treatment.

  4. Recent theoretical, neural, and clinical advances in sustained attention research.

    PubMed

    Fortenbaugh, Francesca C; DeGutis, Joseph; Esterman, Michael

    2017-05-01

    Models of attention often distinguish among attention subtypes, with classic models separating orienting, switching, and sustaining functions. Compared with other forms of attention, the neurophysiological basis of sustaining attention has received far less notice, yet it is known that momentary failures of sustained attention can have far-ranging negative effects in healthy individuals, and lasting sustained attention deficits are pervasive in clinical populations. In recent years, however, there has been increased interest in characterizing moment-to-moment fluctuations in sustained attention, in addition to the overall vigilance decrement, and understanding how these neurocognitive systems change over the life span and across various clinical populations. The use of novel neuroimaging paradigms and statistical approaches has allowed for better characterization of the neural networks supporting sustained attention and has highlighted dynamic interactions within and across multiple distributed networks that predict behavioral performance. These advances have also provided potential biomarkers to identify individuals with sustained attention deficits. These findings have led to new theoretical models explaining why sustaining focused attention is a challenge for individuals and form the basis for the next generation of sustained attention research, which seeks to accurately diagnose and develop theoretically driven treatments for sustained attention deficits that affect a variety of clinical populations. © 2017 New York Academy of Sciences.

  5. Recent theoretical, neural, and clinical advances in sustained attention research

    PubMed Central

    Fortenbaugh, Francesca C.; DeGutis, Joseph; Esterman, Michael

    2017-01-01

    Models of attention often distinguish between attention subtypes, with classic models separating orienting, switching, and sustaining functions. Compared to other forms of attention, the neurophysiological basis of sustaining attention has received far less attention yet it is known that momentary failures of sustained attention can have far ranging negative impacts in healthy individuals and lasting sustained attention deficits are pervasive in clinical populations. In recent years, however, there has been increased interest in characterizing moment-to-moment fluctuations in sustained attention in addition to the overall vigilance decrement and understanding how these neurocognitive systems change over the lifespan and across various clinical populations. The use of novel neuroimaging paradigms and statistical approaches has allowed for better characterization of the neural networks supporting sustained attention, and highlighted dynamic interactions within and across multiple distributed networks that predict behavioral performance. These advances have also provided potential biomarkers to identify individuals with sustained attention deficits. These findings have led to new theoretical models of why sustaining focused attention is a challenge for individuals and form the basis for the next generation of sustained attention research, which seeks to accurately diagnose and develop theoretically-driven treatments for sustained attention deficits that affect a variety of clinical populations. PMID:28260249

  6. The successful merger of theoretical thermochemistry with fragment-based methods in quantum chemistry.

    PubMed

    Ramabhadran, Raghunath O; Raghavachari, Krishnan

    2014-12-16

    CONSPECTUS: Quantum chemistry and electronic structure theory have proven to be essential tools to the experimental chemist, in terms of both a priori predictions that pave the way for designing new experiments and rationalizing experimental observations a posteriori. Translating the well-established success of electronic structure theory in obtaining the structures and energies of small chemical systems to increasingly larger molecules is an exciting and ongoing central theme of research in quantum chemistry. However, the prohibitive computational scaling of highly accurate ab initio electronic structure methods poses a fundamental challenge to this research endeavor. This scenario necessitates an indirect fragment-based approach wherein a large molecule is divided into small fragments and is subsequently reassembled to compute its energy accurately. In our quest to further reduce the computational expense associated with the fragment-based methods and overall enhance the applicability of electronic structure methods to large molecules, we realized that the broad ideas involved in a different area, theoretical thermochemistry, are transferable to the area of fragment-based methods. This Account focuses on the effective merger of these two disparate frontiers in quantum chemistry and how new concepts inspired by theoretical thermochemistry significantly reduce the total number of electronic structure calculations needed to be performed as part of a fragment-based method without any appreciable loss of accuracy. Throughout, the generalized connectivity based hierarchy (CBH), which we developed to solve a long-standing problem in theoretical thermochemistry, serves as the linchpin in this merger. The accuracy of our method is based on two strong foundations: (a) the apt utilization of systematic and sophisticated error-canceling schemes via CBH that result in an optimal cutting scheme at any given level of fragmentation and (b) the use of a less expensive second

  7. Theoretical dissociation energies for ionic molecules

    NASA Technical Reports Server (NTRS)

    Langhoff, S. R.; Bauschlicher, C. W., Jr.; Partridge, H.

    1986-01-01

    Ab initio calculations at the self-consistent-field and singles plus doubles configuration-interaction level are used to determine accurate spectroscopic parameters for most of the alkali and alkaline-earth fluorides, chlorides, oxides, sulfides, hydroxides, and isocyanides. Numerical Hartree-Fock (NHF) calculations are performed on selected systems to ensure that the extended Slater basis sets employed for the diatomic systems are near the Hartree-Fock limit. Extended Gaussian basis sets of at least triple-zeta plus double polarization equality are employed for the triatomic system. With this model, correlation effects are relatively small, but invariably increase the theoretical dissociation energies. The importance of correlating the electrons on both the anion and the metal is discussed. The theoretical dissociation energies are critically compared with the literature to rule out disparate experimental values. Theoretical (sup 2)Pi - (sup 2)Sigma (sup +) energy separations are presented for the alkali oxides and sulfides.

  8. Parallel kinetic Monte Carlo simulation framework incorporating accurate models of adsorbate lateral interactions

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Nielsen, Jens; D’Avezac, Mayeul; Hetherington, James

    2013-12-14

    Ab initio kinetic Monte Carlo (KMC) simulations have been successfully applied for over two decades to elucidate the underlying physico-chemical phenomena on the surfaces of heterogeneous catalysts. These simulations necessitate detailed knowledge of the kinetics of elementary reactions constituting the reaction mechanism, and the energetics of the species participating in the chemistry. The information about the energetics is encoded in the formation energies of gas and surface-bound species, and the lateral interactions between adsorbates on the catalytic surface, which can be modeled at different levels of detail. The majority of previous works accounted for only pairwise-additive first nearest-neighbor interactions. Moremore » recently, cluster-expansion Hamiltonians incorporating long-range interactions and many-body terms have been used for detailed estimations of catalytic rate [C. Wu, D. J. Schmidt, C. Wolverton, and W. F. Schneider, J. Catal. 286, 88 (2012)]. In view of the increasing interest in accurate predictions of catalytic performance, there is a need for general-purpose KMC approaches incorporating detailed cluster expansion models for the adlayer energetics. We have addressed this need by building on the previously introduced graph-theoretical KMC framework, and we have developed Zacros, a FORTRAN2003 KMC package for simulating catalytic chemistries. To tackle the high computational cost in the presence of long-range interactions we introduce parallelization with OpenMP. We further benchmark our framework by simulating a KMC analogue of the NO oxidation system established by Schneider and co-workers [J. Catal. 286, 88 (2012)]. We show that taking into account only first nearest-neighbor interactions may lead to large errors in the prediction of the catalytic rate, whereas for accurate estimates thereof, one needs to include long-range terms in the cluster expansion.« less

  9. Accurate prediction of complex free surface flow around a high speed craft using a single-phase level set method

    NASA Astrophysics Data System (ADS)

    Broglia, Riccardo; Durante, Danilo

    2017-11-01

    This paper focuses on the analysis of a challenging free surface flow problem involving a surface vessel moving at high speeds, or planing. The investigation is performed using a general purpose high Reynolds free surface solver developed at CNR-INSEAN. The methodology is based on a second order finite volume discretization of the unsteady Reynolds-averaged Navier-Stokes equations (Di Mascio et al. in A second order Godunov—type scheme for naval hydrodynamics, Kluwer Academic/Plenum Publishers, Dordrecht, pp 253-261, 2001; Proceedings of 16th international offshore and polar engineering conference, San Francisco, CA, USA, 2006; J Mar Sci Technol 14:19-29, 2009); air/water interface dynamics is accurately modeled by a non standard level set approach (Di Mascio et al. in Comput Fluids 36(5):868-886, 2007a), known as the single-phase level set method. In this algorithm the governing equations are solved only in the water phase, whereas the numerical domain in the air phase is used for a suitable extension of the fluid dynamic variables. The level set function is used to track the free surface evolution; dynamic boundary conditions are enforced directly on the interface. This approach allows to accurately predict the evolution of the free surface even in the presence of violent breaking waves phenomena, maintaining the interface sharp, without any need to smear out the fluid properties across the two phases. This paper is aimed at the prediction of the complex free-surface flow field generated by a deep-V planing boat at medium and high Froude numbers (from 0.6 up to 1.2). In the present work, the planing hull is treated as a two-degree-of-freedom rigid object. Flow field is characterized by the presence of thin water sheets, several energetic breaking waves and plungings. The computational results include convergence of the trim angle, sinkage and resistance under grid refinement; high-quality experimental data are used for the purposes of validation, allowing to

  10. Accurate prediction of protein-protein interactions by integrating potential evolutionary information embedded in PSSM profile and discriminative vector machine classifier.

    PubMed

    Li, Zheng-Wei; You, Zhu-Hong; Chen, Xing; Li, Li-Ping; Huang, De-Shuang; Yan, Gui-Ying; Nie, Ru; Huang, Yu-An

    2017-04-04

    Identification of protein-protein interactions (PPIs) is of critical importance for deciphering the underlying mechanisms of almost all biological processes of cell and providing great insight into the study of human disease. Although much effort has been devoted to identifying PPIs from various organisms, existing high-throughput biological techniques are time-consuming, expensive, and have high false positive and negative results. Thus it is highly urgent to develop in silico methods to predict PPIs efficiently and accurately in this post genomic era. In this article, we report a novel computational model combining our newly developed discriminative vector machine classifier (DVM) and an improved Weber local descriptor (IWLD) for the prediction of PPIs. Two components, differential excitation and orientation, are exploited to build evolutionary features for each protein sequence. The main characteristics of the proposed method lies in introducing an effective feature descriptor IWLD which can capture highly discriminative evolutionary information from position-specific scoring matrixes (PSSM) of protein data, and employing the powerful and robust DVM classifier. When applying the proposed method to Yeast and H. pylori data sets, we obtained excellent prediction accuracies as high as 96.52% and 91.80%, respectively, which are significantly better than the previous methods. Extensive experiments were then performed for predicting cross-species PPIs and the predictive results were also pretty promising. To further validate the performance of the proposed method, we compared it with the state-of-the-art support vector machine (SVM) classifier on Human data set. The experimental results obtained indicate that our method is highly effective for PPIs prediction and can be taken as a supplementary tool for future proteomics research.

  11. Spectral and structural studies of the anti-cancer drug Flutamide by density functional theoretical method.

    PubMed

    Mariappan, G; Sundaraganesan, N

    2014-01-03

    A comprehensive screening of the more recent DFT theoretical approach to structural analysis is presented in this section of theoretical structural analysis. The chemical name of 2-methyl-N-[4-nitro-3-(trifluoromethyl)phenyl]-propanamide is usually called as Flutamide (In the present study it is abbreviated as FLT) and is an important and efficacious drug in the treatment of anti-cancer resistant. The molecular geometry, vibrational spectra, electronic and NMR spectral interpretation of Flutamide have been studied with the aid of density functional theory method (DFT). The vibrational assignments of the normal modes were performed on the basis of the PED calculations using the VEDA 4 program. Comparison of computational results with X-ray diffraction results of Flutamide allowed the evaluation of structure predictions and confirmed B3LYP/6-31G(d,p) as accurate for structure determination. Application of scaling factors for IR and Raman frequency predictions showed good agreement with experimental values. This is supported the assignment of the major contributors of the vibration modes of the title compound. Stability of the molecule arising from hyperconjugative interactions leading to its bioactivity, charge delocalization have been analyzed using natural bond orbital (NBO) analysis. NMR chemical shifts of the molecule were calculated using the gauge independent atomic orbital (GIAO) method. The comparison of measured FTIR, FT-Raman, and UV-Visible data to calculated values allowed assignment of major spectral features of the title molecule. Besides, Frontier molecular orbital analyze was also investigated using theoretical calculations. Copyright © 2013 Elsevier B.V. All rights reserved.

  12. Testing the hierarchical assembly of massive galaxies using accurate merger rates out to z ˜ 1.5

    NASA Astrophysics Data System (ADS)

    Rodrigues, Myriam; Puech, M.; Flores, H.; Hammer, F.; Pirzkal, N.

    2018-04-01

    We established an accurate comparison between observationally and theoretically estimated major merger rates over a large range of mass (log Mbar/M⊙ =9.9-11.4) and redshift (z = 0.7-1.6). For this, we combined a new estimate of the merger rate from an exhaustive count of pairs within the virial radius of massive galaxies at z ˜ 1.265 and cross-validated with their morphology, with estimates from the morpho-kinematic analysis of two other samples. Theoretical predictions were estimated using semi-empirical models with inputs matching the properties of the observed samples, while specific visibility time-scales scaled to the observed samples were used. Both theory and observations are found to agree within 30 per cent of the observed value, which provides strong support to the hierarchical assembly of galaxies over the probed ranges of mass and redshift. Here, we find that ˜60 per cent of population of local massive (Mstellar =1010.3-11.6 M⊙) galaxies would have undergone a wet major merger since z = 1.5, consistently with previous studies. Such recent mergers are expected to result in the (re-)formation of a significant fraction of local disc galaxies.

  13. Predicting chemical degradation during storage from two successive concentration ratios: Theoretical investigation.

    PubMed

    Peleg, Micha; Normand, Mark D

    2015-09-01

    When a vitamin's, pigment's or other food component's chemical degradation follows a known fixed order kinetics, and its rate constant's temperature-dependence follows a two parameter model, then, at least theoretically, it is possible to extract these two parameters from two successive experimental concentration ratios determined during the food's non-isothermal storage. This requires numerical solution of two simultaneous equations, themselves the numerical solutions of two differential rate equations, with a program especially developed for the purpose. Once calculated, these parameters can be used to reconstruct the entire degradation curve for the particular temperature history and predict the degradation curves for other temperature histories. The concept and computation method were tested with simulated degradation under rising and/or falling oscillating temperature conditions, employing the exponential model to characterize the rate constant's temperature-dependence. In computer simulations, the method's predictions were robust against minor errors in the two concentration ratios. The program to do the calculations was posted as freeware on the Internet. The temperature profile can be entered as an algebraic expression that can include 'If' statements, or as an imported digitized time-temperature data file, to be converted into an Interpolating Function by the program. The numerical solution of the two simultaneous equations requires close initial guesses of the exponential model's parameters. Programs were devised to obtain these initial values by matching the two experimental concentration ratios with a generated degradation curve whose parameters can be varied manually with sliders on the screen. These programs too were made available as freeware on the Internet and were tested with published data on vitamin A. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. Accurate airway centerline extraction based on topological thinning using graph-theoretic analysis.

    PubMed

    Bian, Zijian; Tan, Wenjun; Yang, Jinzhu; Liu, Jiren; Zhao, Dazhe

    2014-01-01

    The quantitative analysis of the airway tree is of critical importance in the CT-based diagnosis and treatment of popular pulmonary diseases. The extraction of airway centerline is a precursor to identify airway hierarchical structure, measure geometrical parameters, and guide visualized detection. Traditional methods suffer from extra branches and circles due to incomplete segmentation results, which induce false analysis in applications. This paper proposed an automatic and robust centerline extraction method for airway tree. First, the centerline is located based on the topological thinning method; border voxels are deleted symmetrically to preserve topological and geometrical properties iteratively. Second, the structural information is generated using graph-theoretic analysis. Then inaccurate circles are removed with a distance weighting strategy, and extra branches are pruned according to clinical anatomic knowledge. The centerline region without false appendices is eventually determined after the described phases. Experimental results show that the proposed method identifies more than 96% branches and keep consistency across different cases and achieves superior circle-free structure and centrality.

  15. Theoretical predictions for spatially-focused heating of magnetic nanoparticles guided by magnetic particle imaging field gradients

    NASA Astrophysics Data System (ADS)

    Dhavalikar, Rohan; Rinaldi, Carlos

    2016-12-01

    Magnetic nanoparticles in alternating magnetic fields (AMFs) transfer some of the field's energy to their surroundings in the form of heat, a property that has attracted significant attention for use in cancer treatment through hyperthermia and in developing magnetic drug carriers that can be actuated to release their cargo externally using magnetic fields. To date, most work in this field has focused on the use of AMFs that actuate heat release by nanoparticles over large regions, without the ability to select specific nanoparticle-loaded regions for heating while leaving other nanoparticle-loaded regions unaffected. In parallel, magnetic particle imaging (MPI) has emerged as a promising approach to image the distribution of magnetic nanoparticle tracers in vivo, with sub-millimeter spatial resolution. The underlying principle in MPI is the application of a selection magnetic field gradient, which defines a small region of low bias field, superimposed with an AMF (of lower frequency and amplitude than those normally used to actuate heating by the nanoparticles) to obtain a signal which is proportional to the concentration of particles in the region of low bias field. Here we extend previous models for estimating the energy dissipation rates of magnetic nanoparticles in uniform AMFs to provide theoretical predictions of how the selection magnetic field gradient used in MPI can be used to selectively actuate heating by magnetic nanoparticles in the low bias field region of the selection magnetic field gradient. Theoretical predictions are given for the spatial decay in energy dissipation rate under magnetic field gradients representative of those that can be achieved with current MPI technology. These results underscore the potential of combining MPI and higher amplitude/frequency actuation AMFs to achieve selective magnetic fluid hyperthermia (MFH) guided by MPI.

  16. The turbulent recirculating flow field in a coreless induction furnace. A comparison of theoretical predictions with measurements

    NASA Technical Reports Server (NTRS)

    El-Kaddah, N.; Szekely, J.

    1982-01-01

    A mathematical representation for the electromagnetic force field and the fluid flow field in a coreless induction furnace is presented. The fluid flow field was represented by writing the axisymmetric turbulent Navier-Stokes equation, containing the electromagnetic body force term. The electromagnetic body force field was calculated by using a technique of mutual inductances. The kappa-epsilon model was employed for evaluating the turbulent viscosity and the resultant differential equations were solved numerically. Theoretically predicted velocity fields are in reasonably good agreement with the experimental measurements reported by Hunt and Moore; furthermore, the agreement regarding the turbulent intensities are essentially quantitative. These results indicate that the kappa-epsilon model provides a good engineering representation of the turbulent recirculating flows occurring in induction furnaces. At this stage it is not clear whether the discrepancies between measurements and the predictions, which were not very great in any case, are attributable either to the model or to the measurement techniques employed.

  17. Using radiance predicted by the P3 approximation in a spherical geometry to predict tissue optical properties

    NASA Astrophysics Data System (ADS)

    Dickey, Dwayne J.; Moore, Ronald B.; Tulip, John

    2001-01-01

    For photodynamic therapy of solid tumors, such as prostatic carcinoma, to be achieved, an accurate model to predict tissue parameters and light dose must be found. Presently, most analytical light dosimetry models are fluence based and are not clinically viable for tissue characterization. Other methods of predicting optical properties, such as Monet Carlo, are accurate but far too time consuming for clinical application. However, radiance predicted by the P3-Approximation, an anaylitical solution to the transport equation, may be a viable and accurate alternative. The P3-Approximation accurately predicts optical parameters in intralipid/methylene blue based phantoms in a spherical geometry. The optical parameters furnished by the radiance, when introduced into fluence predicted by both P3- Approximation and Grosjean Theory, correlate well with experimental data. The P3-Approximation also predicts the optical properties of prostate tissue, agreeing with documented optical parameters. The P3-Approximation could be the clinical tool necessary to facilitate PDT of solid tumors because of the limited number of invasive measurements required and the speed in which accurate calculations can be performed.

  18. Accurate density functional prediction of molecular electron affinity with the scaling corrected Kohn–Sham frontier orbital energies

    NASA Astrophysics Data System (ADS)

    Zhang, DaDi; Yang, Xiaolong; Zheng, Xiao; Yang, Weitao

    2018-04-01

    Electron affinity (EA) is the energy released when an additional electron is attached to an atom or a molecule. EA is a fundamental thermochemical property, and it is closely pertinent to other important properties such as electronegativity and hardness. However, accurate prediction of EA is difficult with density functional theory methods. The somewhat large error of the calculated EAs originates mainly from the intrinsic delocalisation error associated with the approximate exchange-correlation functional. In this work, we employ a previously developed non-empirical global scaling correction approach, which explicitly imposes the Perdew-Parr-Levy-Balduz condition to the approximate functional, and achieve a substantially improved accuracy for the calculated EAs. In our approach, the EA is given by the scaling corrected Kohn-Sham lowest unoccupied molecular orbital energy of the neutral molecule, without the need to carry out the self-consistent-field calculation for the anion.

  19. Theoretical geology

    NASA Astrophysics Data System (ADS)

    Mikeš, Daniel

    2010-05-01

    Theoretical geology Present day geology is mostly empirical of nature. I claim that geology is by nature complex and that the empirical approach is bound to fail. Let's consider the input to be the set of ambient conditions and the output to be the sedimentary rock record. I claim that the output can only be deduced from the input if the relation from input to output be known. The fundamental question is therefore the following: Can one predict the output from the input or can one predict the behaviour of a sedimentary system? If one can, than the empirical/deductive method has changes, if one can't than that method is bound to fail. The fundamental problem to solve is therefore the following: How to predict the behaviour of a sedimentary system? It is interesting to observe that this question is never asked and many a study is conducted by the empirical/deductive method; it seems that the empirical method has been accepted as being appropriate without question. It is, however, easy to argument that a sedimentary system is by nature complex and that several input parameters vary at the same time and that they can create similar output in the rock record. It follows trivially from these first principles that in such a case the deductive solution cannot be unique. At the same time several geological methods depart precisely from the assumption, that one particular variable is the dictator/driver and that the others are constant, even though the data do not support such an assumption. The method of "sequence stratigraphy" is a typical example of such a dogma. It can be easily argued that all the interpretation resulting from a method that is built on uncertain or wrong assumptions is erroneous. Still, this method has survived for many years, nonwithstanding all the critics it has received. This is just one example of the present day geological world and is not unique. Even the alternative methods criticising sequence stratigraphy actually depart from the same

  20. Combining first-principles and data modeling for the accurate prediction of the refractive index of organic polymers

    NASA Astrophysics Data System (ADS)

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

    2018-06-01

    Organic materials with a high index of refraction (RI) are attracting considerable interest due to their potential application in optic and optoelectronic devices. However, most of these applications require an RI value of 1.7 or larger, while typical carbon-based polymers only exhibit values in the range of 1.3-1.5. This paper introduces an efficient computational protocol for the accurate prediction of RI values in polymers to facilitate in silico studies that can guide the discovery and design of next-generation high-RI materials. Our protocol is based on the Lorentz-Lorenz equation and is parametrized by the polarizability and number density values of a given candidate compound. In the proposed scheme, we compute the former using first-principles electronic structure theory and the latter using an approximation based on van der Waals volumes. The critical parameter in the number density approximation is the packing fraction of the bulk polymer, for which we have devised a machine learning model. We demonstrate the performance of the proposed RI protocol by testing its predictions against the experimentally known RI values of 112 optical polymers. Our approach to combine first-principles and data modeling emerges as both a successful and a highly economical path to determining the RI values for a wide range of organic polymers.

  1. Lower NIH stroke scale scores are required to accurately predict a good prognosis in posterior circulation stroke.

    PubMed

    Inoa, Violiza; Aron, Abraham W; Staff, Ilene; Fortunato, Gilbert; Sansing, Lauren H

    2014-01-01

    The NIH stroke scale (NIHSS) is an indispensable tool that aids in the determination of acute stroke prognosis and decision making. Patients with posterior circulation (PC) strokes often present with lower NIHSS scores, which may result in the withholding of thrombolytic treatment from these patients. However, whether these lower initial NIHSS scores predict better long-term prognoses is uncertain. We aimed to assess the utility of the NIHSS at presentation for predicting the functional outcome at 3 months in anterior circulation (AC) versus PC strokes. This was a retrospective analysis of a large prospectively collected database of adults with acute ischemic stroke. Univariate and multivariate analyses were conducted to identify factors associated with outcome. Additional analyses were performed to determine the receiver operating characteristic (ROC) curves for NIHSS scores and outcomes in AC and PC infarctions. Both the optimal cutoffs for maximal diagnostic accuracy and the cutoffs to obtain >80% sensitivity for poor outcomes were determined in AC and PC strokes. The analysis included 1,197 patients with AC stroke and 372 with PC stroke. The median initial NIHSS score for patients with AC strokes was 7 and for PC strokes it was 2. The majority (71%) of PC stroke patients had baseline NIHSS scores ≤4, and 15% of these 'minor' stroke patients had a poor outcome at 3 months. ROC analysis identified that the optimal NIHSS cutoff for outcome prediction after infarction in the AC was 8 and for infarction in the PC it was 4. To achieve >80% sensitivity for detecting patients with a subsequent poor outcome, the NIHSS cutoff for infarctions in the AC was 4 and for infarctions in the PC it was 2. The NIHSS cutoff that most accurately predicts outcomes is 4 points higher in AC compared to PC infarctions. There is potential for poor outcomes in patients with PC strokes and low NIHSS scores, suggesting that thrombolytic treatment should not be withheld from these patients

  2. Theoretical and Empirical Descriptions of Thermospheric Density

    NASA Astrophysics Data System (ADS)

    Solomon, S. C.; Qian, L.

    2004-12-01

    The longest-term and most accurate overall description the density of the upper thermosphere is provided by analysis of change in the ephemeris of Earth-orbiting satellites. Empirical models of the thermosphere developed in part from these measurements can do a reasonable job of describing thermospheric properties on a climatological basis, but the promise of first-principles global general circulation models of the coupled thermosphere/ionosphere system is that a true high-resolution, predictive capability may ultimately be developed for thermospheric density. However, several issues are encountered when attempting to tune such models so that they accurately represent absolute densities as a function of altitude, and their changes on solar-rotational and solar-cycle time scales. Among these are the crucial ones of getting the heating rates (from both solar and auroral sources) right, getting the cooling rates right, and establishing the appropriate boundary conditions. However, there are several ancillary issues as well, such as the problem of registering a pressure-coordinate model onto an altitude scale, and dealing with possible departures from hydrostatic equilibrium in empirical models. Thus, tuning a theoretical model to match empirical climatology may be difficult, even in the absence of high temporal or spatial variation of the energy sources. We will discuss some of the challenges involved, and show comparisons of simulations using the NCAR Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIE-GCM) to empirical model estimates of neutral thermosphere density and temperature. We will also show some recent simulations using measured solar irradiance from the TIMED/SEE instrument as input to the TIE-GCM.

  3. Ab Initio Calculation of Accurate Vibrational Frequencies for Molecules of Interest in Atmospheric Chemistry

    NASA Technical Reports Server (NTRS)

    Lee, Timothy J.; Langhoff, Stephen R. (Technical Monitor)

    1996-01-01

    Due to advances in quantum mechanical methods over the last few years, it is now possible to determine ab initio potential energy surfaces in which fundamental vibrational frequencies are accurate to within +/- 8 cm(sup -1) on average, and molecular bond distances are accurate to within +/- 0.001-0.003 A, depending on the nature of the bond. That is, the potential energy surfaces have not been scaled or empirically adjusted in any way, showing that theoretical methods have progressed to the point of being useful in analyzing spectra that are not from a tightly controlled laboratory environment, such as rovibrational spectra from the interstellar medium. Some recent examples demonstrating this accuracy win be presented and discussed. These include the HNO, CH4, C2H4, and ClCN molecules. The HNO molecule is interesting due to the very large H-N anharmonicity, while ClCN has a very large Fermi resonance. The ab initio studies for the CH4 and C2H4 molecules present the first accurate full quartic force fields of any kind (i.e., whether theoretical or empirical) for a five-atom and six-atom system, respectively.

  4. Accurate expansion of cylindrical paraxial waves for its straightforward implementation in electromagnetic scattering

    NASA Astrophysics Data System (ADS)

    Naserpour, Mahin; Zapata-Rodríguez, Carlos J.

    2018-01-01

    The evaluation of vector wave fields can be accurately performed by means of diffraction integrals, differential equations and also series expansions. In this paper, a Bessel series expansion which basis relies on the exact solution of the Helmholtz equation in cylindrical coordinates is theoretically developed for the straightforward yet accurate description of low-numerical-aperture focal waves. The validity of this approach is confirmed by explicit application to Gaussian beams and apertured focused fields in the paraxial regime. Finally we discuss how our procedure can be favorably implemented in scattering problems.

  5. Theoretical and experimental prediction of the redox potentials of metallocene compounds

    NASA Astrophysics Data System (ADS)

    Li, Ya-Ping; Liu, Hai-Bo; Liu, Tao; Yu, Zhang-Yu

    2017-11-01

    The standard redox electrode potential ( E°) values of metallocene compounds are obtained theoretically with density functional theory (DFT) method at B3LYP/6-311++G( d, p) level and experimentally with cyclic voltammetry (CV). The theoretical E° values of metallocene compounds are in good agreement with experimental ones. We investigate the substituent effects on the redox properties of metallocene compounds. Among the four metallocene compounds, the E° values is largest for titanocene dichloride and smallest for ferrocene.

  6. 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. Published by Oxford University Press on behalf of the Society of Toxicology 2016. This work is written by US Government employees and is in the public domain in the US.

  7. Tautomerism in cytosine and uracil: an experimental and theoretical core level spectroscopic study.

    PubMed

    Feyer, Vitaliy; Plekan, Oksana; Richter, Robert; Coreno, Marcello; Vall-llosera, Gemma; Prince, Kevin C; Trofimov, Alexander B; Zaytseva, Irina L; Moskovskaya, Tatyana E; Gromov, Evgeniy V; Schirmer, Jochen

    2009-05-14

    The O, N, and C 1s core level photoemission spectra of the nucleobases cytosine and uracil have been measured in the vapor phase, and the results have been interpreted via theoretical calculations. Our calculations accurately predict the relative binding energies of the core level features observed in the experimental photoemission results and provide a full assignment. In agreement with previous work, a single tautomer of uracil is populated at 405 K, giving rise to relatively simple spectra. At 450 K, three tautomers of cytosine, one of which may consist of two rotamers, are identified, and their populations are determined. This resolves inconsistencies between recent laser studies of this molecule in which the rare imino-oxo tautomer was not observed and older microwave spectra in which it was reported.

  8. Accurate, precise, and efficient theoretical methods to calculate anion-π interaction energies in model structures.

    PubMed

    Mezei, Pál D; Csonka, Gábor I; Ruzsinszky, Adrienn; Sun, Jianwei

    2015-01-13

    A correct description of the anion-π interaction is essential for the design of selective anion receptors and channels and important for advances in the field of supramolecular chemistry. However, it is challenging to do accurate, precise, and efficient calculations of this interaction, which are lacking in the literature. In this article, by testing sets of 20 binary anion-π complexes of fluoride, chloride, bromide, nitrate, or carbonate ions with hexafluorobenzene, 1,3,5-trifluorobenzene, 2,4,6-trifluoro-1,3,5-triazine, or 1,3,5-triazine and 30 ternary π-anion-π' sandwich complexes composed from the same monomers, we suggest domain-based local-pair natural orbital coupled cluster energies extrapolated to the complete basis-set limit as reference values. We give a detailed explanation of the origin of anion-π interactions, using the permanent quadrupole moments, static dipole polarizabilities, and electrostatic potential maps. We use symmetry-adapted perturbation theory (SAPT) to calculate the components of the anion-π interaction energies. We examine the performance of the direct random phase approximation (dRPA), the second-order screened exchange (SOSEX), local-pair natural-orbital (LPNO) coupled electron pair approximation (CEPA), and several dispersion-corrected density functionals (including generalized gradient approximation (GGA), meta-GGA, and double hybrid density functional). The LPNO-CEPA/1 results show the best agreement with the reference results. The dRPA method is only slightly less accurate and precise than the LPNO-CEPA/1, but it is considerably more efficient (6-17 times faster) for the binary complexes studied in this paper. For 30 ternary π-anion-π' sandwich complexes, we give dRPA interaction energies as reference values. The double hybrid functionals are much more efficient but less accurate and precise than dRPA. The dispersion-corrected double hybrid PWPB95-D3(BJ) and B2PLYP-D3(BJ) functionals perform better than the GGA and meta

  9. A Simple Iterative Model Accurately Captures Complex Trapline Formation by Bumblebees Across Spatial Scales and Flower Arrangements

    PubMed Central

    Reynolds, Andrew M.; Lihoreau, Mathieu; Chittka, Lars

    2013-01-01

    Pollinating bees develop foraging circuits (traplines) to visit multiple flowers in a manner that minimizes overall travel distance, a task analogous to the travelling salesman problem. We report on an in-depth exploration of an iterative improvement heuristic model of bumblebee traplining previously found to accurately replicate the establishment of stable routes by bees between flowers distributed over several hectares. The critical test for a model is its predictive power for empirical data for which the model has not been specifically developed, and here the model is shown to be consistent with observations from different research groups made at several spatial scales and using multiple configurations of flowers. We refine the model to account for the spatial search strategy of bees exploring their environment, and test several previously unexplored predictions. We find that the model predicts accurately 1) the increasing propensity of bees to optimize their foraging routes with increasing spatial scale; 2) that bees cannot establish stable optimal traplines for all spatial configurations of rewarding flowers; 3) the observed trade-off between travel distance and prioritization of high-reward sites (with a slight modification of the model); 4) the temporal pattern with which bees acquire approximate solutions to travelling salesman-like problems over several dozen foraging bouts; 5) the instability of visitation schedules in some spatial configurations of flowers; 6) the observation that in some flower arrays, bees' visitation schedules are highly individually different; 7) the searching behaviour that leads to efficient location of flowers and routes between them. Our model constitutes a robust theoretical platform to generate novel hypotheses and refine our understanding about how small-brained insects develop a representation of space and use it to navigate in complex and dynamic environments. PMID:23505353

  10. A theoretical framework to predict the most likely ion path in particle imaging.

    PubMed

    Collins-Fekete, Charles-Antoine; Volz, Lennart; Portillo, Stephen K N; Beaulieu, Luc; Seco, Joao

    2017-03-07

    In this work, a generic rigorous Bayesian formalism is introduced to predict the most likely path of any ion crossing a medium between two detection points. The path is predicted based on a combination of the particle scattering in the material and measurements of its initial and final position, direction and energy. The path estimate's precision is compared to the Monte Carlo simulated path. Every ion from hydrogen to carbon is simulated in two scenarios, (1) where the range is fixed and (2) where the initial velocity is fixed. In the scenario where the range is kept constant, the maximal root-mean-square error between the estimated path and the Monte Carlo path drops significantly between the proton path estimate (0.50 mm) and the helium path estimate (0.18 mm), but less so up to the carbon path estimate (0.09 mm). However, this scenario is identified as the configuration that maximizes the dose while minimizing the path resolution. In the scenario where the initial velocity is fixed, the maximal root-mean-square error between the estimated path and the Monte Carlo path drops significantly between the proton path estimate (0.29 mm) and the helium path estimate (0.09 mm) but increases for heavier ions up to carbon (0.12 mm). As a result, helium is found to be the particle with the most accurate path estimate for the lowest dose, potentially leading to tomographic images of higher spatial resolution.

  11. Mach 6 experimental and theoretical stability and performance of a cruciform missile at angles of attack up to 65 degrees

    NASA Technical Reports Server (NTRS)

    Hartman, Edward R.; Johnston, Patrick J.

    1987-01-01

    An experimental and theoretical investigation of the longitudinal and lateral-directional stability and control of an axisymmetric cruciform-finned missile has been conducted at Mach 6. The angle-of-attack range extended from 20 to 65 deg to encompass maximum lift. Longitudinal stability, performance, and trim could be accurately predicted with the fins at a fin roll angle of 0 deg but not when the fins were at a fin roll angle of 45 deg. At this roll angle, windward fin choking occurred at angles of attack above 50 deg and reduced the effectiveness of the fins and caused pitch-up.

  12. Shedding light on the variability of optical skin properties: finding a path towards more accurate prediction of light propagation in human cutaneous compartments

    PubMed Central

    Mignon, C.; Tobin, D. J.; Zeitouny, M.; Uzunbajakava, N. E.

    2018-01-01

    Finding a path towards a more accurate prediction of light propagation in human skin remains an aspiration of biomedical scientists working on cutaneous applications both for diagnostic and therapeutic reasons. The objective of this study was to investigate variability of the optical properties of human skin compartments reported in literature, to explore the underlying rational of this variability and to propose a dataset of values, to better represent an in vivo case and recommend a solution towards a more accurate prediction of light propagation through cutaneous compartments. To achieve this, we undertook a novel, logical yet simple approach. We first reviewed scientific articles published between 1981 and 2013 that reported on skin optical properties, to reveal the spread in the reported quantitative values. We found variations of up to 100-fold. Then we extracted the most trust-worthy datasets guided by a rule that the spectral properties should reflect the specific biochemical composition of each of the skin layers. This resulted in the narrowing of the spread in the calculated photon densities to 6-fold. We conclude with a recommendation to use the identified most robust datasets when estimating light propagation in human skin using Monte Carlo simulations. Alternatively, otherwise follow our proposed strategy to screen any new datasets to determine their biological relevance. PMID:29552418

  13. Local lung deposition of ultrafine particles in healthy adults: experimental results and theoretical predictions.

    PubMed

    Sturm, Robert

    2016-11-01

    Ultrafine particles (UFP) of biogenic and anthropogenic origin occur in high numbers in the ambient atmosphere. In addition, aerosols containing ultrafine powders are used for the inhalation therapy of various diseases. All these facts make it necessary to obtain comprehensive knowledge regarding the exact behavior of UFP in the respiratory tract. Theoretical simulations of local UFP deposition are based on previously conducted inhalation experiments, where particles with various sizes (0.04, 0.06, 0.08, and 0.10 µm) were administered to the respiratory tract by application of the aerosol bolus technique. By the sequential change of the lung penetration depth of the inspired bolus, different volumetric lung regions could be generated and particle deposition in these regions could be evaluated. The model presented in this contribution adopted all parameters used in the experiments. Besides the obligatory comparison between practical and theoretical data, also advanced modeling predictions including the effect of varying functional residual capacity (FRC) and respiratory flow rate were conducted. Validation of the UFP deposition model shows that highest deposition fractions occur in those volumetric lung regions corresponding to the small and partly alveolated airways of the tracheobronchial tree. Particle deposition proximal to the trachea is increased in female probands with respect to male subjects. Decrease of both the FRC and the respiratory flow rate results in an enhancement of UFP deposition. The study comes to the conclusion that deposition of UFP taken up via bolus inhalation is influenced by a multitude of factors, among which lung morphometry and breathing conditions play a superior role.

  14. Local lung deposition of ultrafine particles in healthy adults: experimental results and theoretical predictions

    PubMed Central

    2016-01-01

    Background Ultrafine particles (UFP) of biogenic and anthropogenic origin occur in high numbers in the ambient atmosphere. In addition, aerosols containing ultrafine powders are used for the inhalation therapy of various diseases. All these facts make it necessary to obtain comprehensive knowledge regarding the exact behavior of UFP in the respiratory tract. Methods Theoretical simulations of local UFP deposition are based on previously conducted inhalation experiments, where particles with various sizes (0.04, 0.06, 0.08, and 0.10 µm) were administered to the respiratory tract by application of the aerosol bolus technique. By the sequential change of the lung penetration depth of the inspired bolus, different volumetric lung regions could be generated and particle deposition in these regions could be evaluated. The model presented in this contribution adopted all parameters used in the experiments. Besides the obligatory comparison between practical and theoretical data, also advanced modeling predictions including the effect of varying functional residual capacity (FRC) and respiratory flow rate were conducted. Results Validation of the UFP deposition model shows that highest deposition fractions occur in those volumetric lung regions corresponding to the small and partly alveolated airways of the tracheobronchial tree. Particle deposition proximal to the trachea is increased in female probands with respect to male subjects. Decrease of both the FRC and the respiratory flow rate results in an enhancement of UFP deposition. Conclusions The study comes to the conclusion that deposition of UFP taken up via bolus inhalation is influenced by a multitude of factors, among which lung morphometry and breathing conditions play a superior role. PMID:27942511

  15. Suitability of frequency modulated thermal wave imaging for skin cancer detection-A theoretical prediction.

    PubMed

    Bhowmik, Arka; Repaka, Ramjee; Mulaveesala, Ravibabu; Mishra, Subhash C

    2015-07-01

    A theoretical study on the quantification of surface thermal response of cancerous human skin using the frequency modulated thermal wave imaging (FMTWI) technique has been presented in this article. For the first time, the use of the FMTWI technique for the detection and the differentiation of skin cancer has been demonstrated in this article. A three dimensional multilayered skin has been considered with the counter-current blood vessels in individual skin layers along with different stages of cancerous lesions based on geometrical, thermal and physical parameters available in the literature. Transient surface thermal responses of melanoma during FMTWI of skin cancer have been obtained by integrating the heat transfer model for biological tissue along with the flow model for blood vessels. It has been observed from the numerical results that, flow of blood in the subsurface region leads to a substantial alteration on the surface thermal response of the human skin. The alteration due to blood flow further causes a reduction in the performance of the thermal imaging technique during the thermal evaluation of earliest melanoma stages (small volume) compared to relatively large volume. Based on theoretical study, it has been predicted that the method is suitable for detection and differentiation of melanoma with comparatively large volume than the earliest development stages (small volume). The study has also performed phase based image analysis of the raw thermograms to resolve the different stages of melanoma volume. The phase images have been found to be clearly individuate the different development stages of melanoma compared to raw thermograms. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. Robust and accurate vectorization of line drawings.

    PubMed

    Hilaire, Xavier; Tombre, Karl

    2006-06-01

    This paper presents a method for vectorizing the graphical parts of paper-based line drawings. The method consists of separating the input binary image into layers of homogeneous thickness, skeletonizing each layer, segmenting the skeleton by a method based on random sampling, and simplifying the result. The segmentation method is robust with a best bound of 50 percent noise reached for indefinitely long primitives. Accurate estimation of the recognized vector's parameters is enabled by explicitly computing their feasibility domains. Theoretical performance analysis and expression of the complexity of the segmentation method are derived. Experimental results and comparisons with other vectorization systems are also provided.

  17. Using leg muscles as shock absorbers: theoretical predictions and experimental results of drop landing performance.

    PubMed

    Minetti, A E; Ardigò, L P; Susta, D; Cotelli, F

    1998-12-01

    The use of muscles as power dissipators is investigated in this study, both from the modellistic and the experimental points of view. Theoretical predictions of the drop landing manoeuvre for a range of initial conditions have been obtained by accounting for the mechanical characteristics of knee extensor muscles, the limb geometry and assuming maximum neural activation. Resulting dynamics have been represented in the phase plane (vertical displacement versus speed) to better classify the damping performance. Predictions of safe landing in sedentary subjects were associated to dropping from a maximum (feet) height of 1.6-2.0 m (about 11 m on the moon). Athletes can extend up to 2.6-3.0 m, while for obese males (m = 100 kg, standard stature) the limit should reduce to 0.9-1.3 m. These results have been calculated by including in the model the estimated stiffness of the 'global elastic elements' acting below the squat position. Experimental landings from a height of 0.4, 0.7, 1.1 m (sedentary males (SM) and male (AM) and female (AF) athletes from the alpine ski national team) showed dynamics similar to the model predictions. While the peak power (for a drop height of about 0.7 m) was similar in SM and AF (AM shows a +40% increase, about 33 W/kg), AF stopped the downward movement after a time interval (0.219 +/- 0.030 s) from touch-down 20% significantly shorter than SM. Landing strategy and the effect of anatomical constraints are discussed in the paper.

  18. A rapid and accurate approach for prediction of interactomes from co-elution data (PrInCE).

    PubMed

    Stacey, R Greg; Skinnider, Michael A; Scott, Nichollas E; Foster, Leonard J

    2017-10-23

    An organism's protein interactome, or complete network of protein-protein interactions, defines the protein complexes that drive cellular processes. Techniques for studying protein complexes have traditionally applied targeted strategies such as yeast two-hybrid or affinity purification-mass spectrometry to assess protein interactions. However, given the vast number of protein complexes, more scalable methods are necessary to accelerate interaction discovery and to construct whole interactomes. We recently developed a complementary technique based on the use of protein correlation profiling (PCP) and stable isotope labeling in amino acids in cell culture (SILAC) to assess chromatographic co-elution as evidence of interacting proteins. Importantly, PCP-SILAC is also capable of measuring protein interactions simultaneously under multiple biological conditions, allowing the detection of treatment-specific changes to an interactome. Given the uniqueness and high dimensionality of co-elution data, new tools are needed to compare protein elution profiles, control false discovery rates, and construct an accurate interactome. Here we describe a freely available bioinformatics pipeline, PrInCE, for the analysis of co-elution data. PrInCE is a modular, open-source library that is computationally inexpensive, able to use label and label-free data, and capable of detecting tens of thousands of protein-protein interactions. Using a machine learning approach, PrInCE offers greatly reduced run time, more predicted interactions at the same stringency, prediction of protein complexes, and greater ease of use over previous bioinformatics tools for co-elution data. PrInCE is implemented in Matlab (version R2017a). Source code and standalone executable programs for Windows and Mac OSX are available at https://github.com/fosterlab/PrInCE , where usage instructions can be found. An example dataset and output are also provided for testing purposes. PrInCE is the first fast and easy

  19. Hounsfield unit density accurately predicts ESWL success.

    PubMed

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

    2005-01-01

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

  20. 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.

  1. Accurate genomic predictions for BCWD resistance in rainbow trout are achieved using low-density SNP panels: Evidence that long-range LD is a major contributing factor.

    PubMed

    Vallejo, Roger L; Silva, Rafael M O; Evenhuis, Jason P; Gao, Guangtu; Liu, Sixin; Parsons, James E; Martin, Kyle E; Wiens, Gregory D; Lourenco, Daniela A L; Leeds, Timothy D; Palti, Yniv

    2018-06-05

    Previously accurate genomic predictions for Bacterial cold water disease (BCWD) resistance in rainbow trout were obtained using a medium-density single nucleotide polymorphism (SNP) array. Here, the impact of lower-density SNP panels on the accuracy of genomic predictions was investigated in a commercial rainbow trout breeding population. Using progeny performance data, the accuracy of genomic breeding values (GEBV) using 35K, 10K, 3K, 1K, 500, 300 and 200 SNP panels as well as a panel with 70 quantitative trait loci (QTL)-flanking SNP was compared. The GEBVs were estimated using the Bayesian method BayesB, single-step GBLUP (ssGBLUP) and weighted ssGBLUP (wssGBLUP). The accuracy of GEBVs remained high despite the sharp reductions in SNP density, and even with 500 SNP accuracy was higher than the pedigree-based prediction (0.50-0.56 versus 0.36). Furthermore, the prediction accuracy with the 70 QTL-flanking SNP (0.65-0.72) was similar to the panel with 35K SNP (0.65-0.71). Genomewide linkage disequilibrium (LD) analysis revealed strong LD (r 2  ≥ 0.25) spanning on average over 1 Mb across the rainbow trout genome. This long-range LD likely contributed to the accurate genomic predictions with the low-density SNP panels. Population structure analysis supported the hypothesis that long-range LD in this population may be caused by admixture. Results suggest that lower-cost, low-density SNP panels can be used for implementing genomic selection for BCWD resistance in rainbow trout breeding programs. © 2018 The Authors. This article is a U.S. Government work and is in the public domain in the USA. Journal of Animal Breeding and Genetics published by Blackwell Verlag GmbH.

  2. Theoretical performance of foil journal bearings

    NASA Technical Reports Server (NTRS)

    Carpino, M.; Peng, J.-P.

    1991-01-01

    A modified forward iteration approach for the coupled solution of foil bearings is presented. The method is used to predict the steady state theoretical performance of a journal type gas bearing constructed from an inextensible shell supported by an elastic foundation. Bending effects are treated as negligible. Finite element methods are used to predict both the foil deflections and the pressure distribution in the gas film.

  3. Accurate Prediction of Inducible Transcription Factor Binding Intensities In Vivo

    PubMed Central

    Siepel, Adam; Lis, John T.

    2012-01-01

    DNA sequence and local chromatin landscape act jointly to determine transcription factor (TF) binding intensity profiles. To disentangle these influences, we developed an experimental approach, called protein/DNA binding followed by high-throughput sequencing (PB–seq), that allows the binding energy landscape to be characterized genome-wide in the absence of chromatin. We applied our methods to the Drosophila Heat Shock Factor (HSF), which inducibly binds a target DNA sequence element (HSE) following heat shock stress. PB–seq involves incubating sheared naked genomic DNA with recombinant HSF, partitioning the HSF–bound and HSF–free DNA, and then detecting HSF–bound DNA by high-throughput sequencing. We compared PB–seq binding profiles with ones observed in vivo by ChIP–seq and developed statistical models to predict the observed departures from idealized binding patterns based on covariates describing the local chromatin environment. We found that DNase I hypersensitivity and tetra-acetylation of H4 were the most influential covariates in predicting changes in HSF binding affinity. We also investigated the extent to which DNA accessibility, as measured by digital DNase I footprinting data, could be predicted from MNase–seq data and the ChIP–chip profiles for many histone modifications and TFs, and found GAGA element associated factor (GAF), tetra-acetylation of H4, and H4K16 acetylation to be the most predictive covariates. Lastly, we generated an unbiased model of HSF binding sequences, which revealed distinct biophysical properties of the HSF/HSE interaction and a previously unrecognized substructure within the HSE. These findings provide new insights into the interplay between the genomic sequence and the chromatin landscape in determining transcription factor binding intensity. PMID:22479205

  4. A link prediction approach to cancer drug sensitivity prediction.

    PubMed

    Turki, Turki; Wei, Zhi

    2017-10-03

    Predicting the response to a drug for cancer disease patients based on genomic information is an important problem in modern clinical oncology. This problem occurs in part because many available drug sensitivity prediction algorithms do not consider better quality cancer cell lines and the adoption of new feature representations; both lead to the accurate prediction of drug responses. By predicting accurate drug responses to cancer, oncologists gain a more complete understanding of the effective treatments for each patient, which is a core goal in precision medicine. In this paper, we model cancer drug sensitivity as a link prediction, which is shown to be an effective technique. We evaluate our proposed link prediction algorithms and compare them with an existing drug sensitivity prediction approach based on clinical trial data. The experimental results based on the clinical trial data show the stability of our link prediction algorithms, which yield the highest area under the ROC curve (AUC) and are statistically significant. We propose a link prediction approach to obtain new feature representation. Compared with an existing approach, the results show that incorporating the new feature representation to the link prediction algorithms has significantly improved the performance.

  5. FragBag, an accurate representation of protein structure, retrieves structural neighbors from the entire PDB quickly and accurately.

    PubMed

    Budowski-Tal, Inbal; Nov, Yuval; Kolodny, Rachel

    2010-02-23

    Fast identification of protein structures that are similar to a specified query structure in the entire Protein Data Bank (PDB) is fundamental in structure and function prediction. We present FragBag: An ultrafast and accurate method for comparing protein structures. We describe a protein structure by the collection of its overlapping short contiguous backbone segments, and discretize this set using a library of fragments. Then, we succinctly represent the protein as a "bags-of-fragments"-a vector that counts the number of occurrences of each fragment-and measure the similarity between two structures by the similarity between their vectors. Our representation has two additional benefits: (i) it can be used to construct an inverted index, for implementing a fast structural search engine of the entire PDB, and (ii) one can specify a structure as a collection of substructures, without combining them into a single structure; this is valuable for structure prediction, when there are reliable predictions only of parts of the protein. We use receiver operating characteristic curve analysis to quantify the success of FragBag in identifying neighbor candidate sets in a dataset of over 2,900 structures. The gold standard is the set of neighbors found by six state of the art structural aligners. Our best FragBag library finds more accurate candidate sets than the three other filter methods: The SGM, PRIDE, and a method by Zotenko et al. More interestingly, FragBag performs on a par with the computationally expensive, yet highly trusted structural aligners STRUCTAL and CE.

  6. Accurate interatomic force fields via machine learning with covariant kernels

    NASA Astrophysics Data System (ADS)

    Glielmo, Aldo; Sollich, Peter; De Vita, Alessandro

    2017-06-01

    We present a novel scheme to accurately predict atomic forces as vector quantities, rather than sets of scalar components, by Gaussian process (GP) regression. This is based on matrix-valued kernel functions, on which we impose the requirements that the predicted force rotates with the target configuration and is independent of any rotations applied to the configuration database entries. We show that such covariant GP kernels can be obtained by integration over the elements of the rotation group SO (d ) for the relevant dimensionality d . Remarkably, in specific cases the integration can be carried out analytically and yields a conservative force field that can be recast into a pair interaction form. Finally, we show that restricting the integration to a summation over the elements of a finite point group relevant to the target system is sufficient to recover an accurate GP. The accuracy of our kernels in predicting quantum-mechanical forces in real materials is investigated by tests on pure and defective Ni, Fe, and Si crystalline systems.

  7. Accurate simulation of geometry, singlet-singlet and triplet-singlet excitation of cyclometalated iridium(III) complex.

    PubMed

    Wang, Jian; Bai, Fu-Quan; Xia, Bao-Hui; Zhang, Hong-Xing; Cui, Tian

    2014-03-01

    In the current contribution, we present a critical study of the theoretical protocol used for the determination of the electronic spectra properties of luminescent cyclometalated iridium(III) complex, [Ir(III)(ppy)₂H₂dcbpy]⁺ (where, ppy = 2-phenylpyridine, H₂dcbpy = 2,2'-bipyridine-4,4'-dicarboxylic acid), considered as a representative example of the various problems related to the prediction of electronic spectra of transition metal complex. The choice of the exchange-correlation functional is crucial for the validity of the conclusions that would be drawn from the numerical results. The influence of the exchange-correlation on geometry parameter and absorption/emission band, the role of solvent effects on time-dependent density function theory (TD-DFT) calculations, as well as the importance of the chosen proper procedure to optimize triplet excited geometry, have been thus examined in detail. From the obtained results, some general conclusions and guidelines are presented: i) PBE0 functional is the most accurate in prediction of ground state geometry; ii) the well-established B3LYP, B3P86, PBE0, and X3LYP have similar accuracy in calculation of absorption spectrum; and iii) the hybrid approach TD-DFT//CIS gives out excellent agreement in the evaluation of triplet excitation energy.

  8. Aircraft Noise Prediction Program theoretical manual: Propeller aerodynamics and noise

    NASA Technical Reports Server (NTRS)

    Zorumski, W. E. (Editor); Weir, D. S. (Editor)

    1986-01-01

    The prediction sequence used in the aircraft noise prediction program (ANOPP) is described. The elements of the sequence are called program modules. The first group of modules analyzes the propeller geometry, the aerodynamics, including both potential and boundary-layer flow, the propeller performance, and the surface loading distribution. This group of modules is based entirely on aerodynamic strip theory. The next group of modules deals with the first group. Predictions of periodic thickness and loading noise are determined with time-domain methods. Broadband noise is predicted by a semiempirical method. Near-field predictions of fuselage surface pressrues include the effects of boundary layer refraction and scattering. Far-field predictions include atmospheric and ground effects.

  9. Knotty: Efficient and Accurate Prediction of Complex RNA Pseudoknot Structures.

    PubMed

    Jabbari, Hosna; Wark, Ian; Montemagno, Carlo; Will, Sebastian

    2018-06-01

    The computational prediction of RNA secondary structure by free energy minimization has become an important tool in RNA research. However in practice, energy minimization is mostly limited to pseudoknot-free structures or rather simple pseudoknots, not covering many biologically important structures such as kissing hairpins. Algorithms capable of predicting sufficiently complex pseudoknots (for sequences of length n) used to have extreme complexities, e.g. Pknots (Rivas and Eddy, 1999) has O(n6) time and O(n4) space complexity. The algorithm CCJ (Chen et al., 2009) dramatically improves the asymptotic run time for predicting complex pseudoknots (handling almost all relevant pseudoknots, while being slightly less general than Pknots), but this came at the cost of large constant factors in space and time, which strongly limited its practical application (∼200 bases already require 256GB space). We present a CCJ-type algorithm, Knotty, that handles the same comprehensive pseudoknot class of structures as CCJ with improved space complexity of Θ(n3 + Z)-due to the applied technique of sparsification, the number of "candidates", Z, appears to grow significantly slower than n4 on our benchmark set (which include pseudoknotted RNAs up to 400 nucleotides). In terms of run time over this benchmark, Knotty clearly outperforms Pknots and the original CCJ implementation, CCJ 1.0; Knotty's space consumption fundamentally improves over CCJ 1.0, being on a par with the space-economic Pknots. By comparing to CCJ 2.0, our unsparsified Knotty variant, we demonstrate the isolated effect of sparsification. Moreover, Knotty employs the state-of-the-art energy model of "HotKnots DP09", which results in superior prediction accuracy over Pknots. Our software is available at https://github.com/HosnaJabbari/Knotty. will@tbi.unvie.ac.at. Supplementary data are available at Bioinformatics online.

  10. Accurate Prediction of Protein Contact Maps by Coupling Residual Two-Dimensional Bidirectional Long Short-Term Memory with Convolutional Neural Networks.

    PubMed

    Hanson, Jack; Paliwal, Kuldip; Litfin, Thomas; Yang, Yuedong; Zhou, Yaoqi

    2018-06-19

    Accurate prediction of a protein contact map depends greatly on capturing as much contextual information as possible from surrounding residues for a target residue pair. Recently, ultra-deep residual convolutional networks were found to be state-of-the-art in the latest Critical Assessment of Structure Prediction techniques (CASP12, (Schaarschmidt et al., 2018)) for protein contact map prediction by attempting to provide a protein-wide context at each residue pair. Recurrent neural networks have seen great success in recent protein residue classification problems due to their ability to propagate information through long protein sequences, especially Long Short-Term Memory (LSTM) cells. Here we propose a novel protein contact map prediction method by stacking residual convolutional networks with two-dimensional residual bidirectional recurrent LSTM networks, and using both one-dimensional sequence-based and two-dimensional evolutionary coupling-based information. We show that the proposed method achieves a robust performance over validation and independent test sets with the Area Under the receiver operating characteristic Curve (AUC)>0.95 in all tests. When compared to several state-of-the-art methods for independent testing of 228 proteins, the method yields an AUC value of 0.958, whereas the next-best method obtains an AUC of 0.909. More importantly, the improvement is over contacts at all sequence-position separations. Specifically, a 8.95%, 5.65% and 2.84% increase in precision were observed for the top L∕10 predictions over the next best for short, medium and long-range contacts, respectively. This confirms the usefulness of ResNets to congregate the short-range relations and 2D-BRLSTM to propagate the long-range dependencies throughout the entire protein contact map 'image'. SPOT-Contact server url: http://sparks-lab.org/jack/server/SPOT-Contact/. Supplementary data is available at Bioinformatics online.

  11. Local Debonding and Fiber Breakage in Composite Materials Modeled Accurately

    NASA Technical Reports Server (NTRS)

    Bednarcyk, Brett A.; Arnold, Steven M.

    2001-01-01

    A prerequisite for full utilization of composite materials in aerospace components is accurate design and life prediction tools that enable the assessment of component performance and reliability. Such tools assist both structural analysts, who design and optimize structures composed of composite materials, and materials scientists who design and optimize the composite materials themselves. NASA Glenn Research Center's Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) software package (http://www.grc.nasa.gov/WWW/LPB/mac) addresses this need for composite design and life prediction tools by providing a widely applicable and accurate approach to modeling composite materials. Furthermore, MAC/GMC serves as a platform for incorporating new local models and capabilities that are under development at NASA, thus enabling these new capabilities to progress rapidly to a stage in which they can be employed by the code's end users.

  12. Urinary Squamous Epithelial Cells Do Not Accurately Predict Urine Culture Contamination, but May Predict Urinalysis Performance in Predicting Bacteriuria.

    PubMed

    Mohr, Nicholas M; Harland, Karisa K; Crabb, Victoria; Mutnick, Rachel; Baumgartner, David; Spinosi, Stephanie; Haarstad, Michael; Ahmed, Azeemuddin; Schweizer, Marin; Faine, Brett

    2016-03-01

    The presence of squamous epithelial cells (SECs) has been advocated to identify urinary contamination despite a paucity of evidence supporting this practice. We sought to determine the value of using quantitative SECs as a predictor of urinalysis contamination. Retrospective cross-sectional study of adults (≥18 years old) presenting to a tertiary academic medical center who had urinalysis with microscopy and urine culture performed. Patients with missing or implausible demographic data were excluded (2.5% of total sample). The primary analysis aimed to determine an SEC threshold that predicted urine culture contamination using receiver operating characteristics (ROC) curve analysis. The a priori secondary analysis explored how demographic variables (age, sex, body mass index) may modify the SEC test performance and whether SECs impacted traditional urinalysis indicators of bacteriuria. A total of 19,328 records were included. ROC curve analysis demonstrated that SEC count was a poor predictor of urine culture contamination (area under the ROC curve = 0.680, 95% confidence interval [CI] = 0.671 to 0.689). In secondary analysis, the positive likelihood ratio (LR+) of predicting bacteriuria via urinalysis among noncontaminated specimens was 4.98 (95% CI = 4.59 to 5.40) in the absence of SECs, but the LR+ fell to 2.35 (95% CI = 2.17 to 2.54) for samples with more than 8 SECs/low-powered field (lpf). In an independent validation cohort, urinalysis samples with fewer than 8 SECs/lpf predicted bacteriuria better (sensitivity = 75%, specificity = 84%) than samples with more than 8 SECs/lpf (sensitivity = 86%, specificity = 70%; diagnostic odds ratio = 17.5 [14.9 to 20.7] vs. 8.7 [7.3 to 10.5]). Squamous epithelial cells are a poor predictor of urine culture contamination, but may predict poor predictive performance of traditional urinalysis measures. © 2016 by the Society for Academic Emergency Medicine.

  13. Large-scale structure prediction by improved contact predictions and model quality assessment.

    PubMed

    Michel, Mirco; Menéndez Hurtado, David; Uziela, Karolis; Elofsson, Arne

    2017-07-15

    Accurate contact predictions can be used for predicting the structure of proteins. Until recently these methods were limited to very big protein families, decreasing their utility. However, recent progress by combining direct coupling analysis with machine learning methods has made it possible to predict accurate contact maps for smaller families. To what extent these predictions can be used to produce accurate models of the families is not known. We present the PconsFold2 pipeline that uses contact predictions from PconsC3, the CONFOLD folding algorithm and model quality estimations to predict the structure of a protein. We show that the model quality estimation significantly increases the number of models that reliably can be identified. Finally, we apply PconsFold2 to 6379 Pfam families of unknown structure and find that PconsFold2 can, with an estimated 90% specificity, predict the structure of up to 558 Pfam families of unknown structure. Out of these, 415 have not been reported before. Datasets as well as models of all the 558 Pfam families are available at http://c3.pcons.net/ . All programs used here are freely available. arne@bioinfo.se. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  14. An accurate empirical method to predict the adsorption strength for π-orbital contained molecules on two dimensional materials.

    PubMed

    Li, Hongping; Wang, Changwei; Xun, Suhang; He, Jing; Jiang, Wei; Zhang, Ming; Zhu, Wenshuai; Li, Huaming

    2018-06-01

    To obtain the adsorption strength is the key point for materials design and parameters optimization in chemical engineering. Here we report a simple but accuracy method to estimate the adsorptive energies by counting the number of π-orbital involved atoms based on theoretical computations for hexagonal boron nitride (h-BN) and graphene. Computational results by density function theory (DFT) as well as spin-component scaled second-order Møller-Plesset perturbation theory (SCS-MP2) both confirm that the adsorptive energies correlate well with the number of π-orbital involved atoms for π-orbital contained molecules. The selected molecules (adsorbates) are commonly used in chemical industry, which contains C, N, S, O atoms. The predicted results for the proposed formulas agree well with the current and previous DFT calculated values both on h-BN and graphene surfaces. Further, it can be also used to predict the adsorptive energies for small π-orbital contained molecules on BN and carbon nanotubes. The interaction type for these adsorptions is typical π-π interaction. Further investigations show that the physical origin of these interactions source from the polar interactions between the adsorbents and adsorbates. Hence, for separation or removal of aromatic molecules, how to modify the aromaticity and polarity of both adsorbents and adsorbates will be the key points for experiments. Copyright © 2018 Elsevier Inc. All rights reserved.

  15. Chemometric Methods and Theoretical Molecular Descriptors in Predictive QSAR Modeling of the Environmental Behavior of Organic Pollutants

    NASA Astrophysics Data System (ADS)

    Gramatica, Paola

    This chapter surveys the QSAR modeling approaches (developed by the author's research group) for the validated prediction of environmental properties of organic pollutants. Various chemometric methods, based on different theoretical molecular descriptors, have been applied: explorative techniques (such as PCA for ranking, SOM for similarity analysis), modeling approaches by multiple-linear regression (MLR, in particular OLS), and classification methods (mainly k-NN, CART, CP-ANN). The focus of this review is on the main topics of environmental chemistry and ecotoxicology, related to the physico-chemical properties, the reactivity, and biological activity of chemicals of high environmental concern. Thus, the review deals with atmospheric degradation reactions of VOCs by tropospheric oxidants, persistence and long-range transport of POPs, sorption behavior of pesticides (Koc and leaching), bioconcentration, toxicity (acute aquatic toxicity, mutagenicity of PAHs, estrogen binding activity for endocrine disruptors compounds (EDCs)), and finally persistent bioaccumulative and toxic (PBT) behavior for the screening and prioritization of organic pollutants. Common to all the proposed models is the attention paid to model validation for predictive ability (not only internal, but also external for chemicals not participating in the model development) and checking of the chemical domain of applicability. Adherence to such a policy, requested also by the OECD principles, ensures the production of reliable predicted data, useful also in the new European regulation of chemicals, REACH.

  16. Chaos in the sunspot cycle - Analysis and prediction

    NASA Technical Reports Server (NTRS)

    Mundt, Michael D.; Maguire, W. Bruce, II; Chase, Robert R. P.

    1991-01-01

    The variability of solar activity over long time scales, given semiquantitatively by measurements of sunspot numbers, is examined as a nonlinear dynamical system. First, a discussion of the data set used and the techniques utilized to reduce the noise and capture the long-term dynamics inherent in the data is presented. Subsequently, an attractor is reconstructed from the data set using the method of time delays. The reconstructed attractor is then used to determine both the dimension of the underlying system and also the largest Lyapunov exponent, which together indicate that the sunspot cycle is indeed chaotic and also low dimensional. In addition, recent techniques of exploiting chaotic dynamics to provide accurate, short-term predictions are utilized in order to improve upon current forecasting methods and also to place theoretical limits on predictability extent. The results are compared to chaotic solar-dynamo models as a possible physically motivated source of this chaotic behavior.

  17. Accurate and scalable social recommendation using mixed-membership stochastic block models.

    PubMed

    Godoy-Lorite, Antonia; Guimerà, Roger; Moore, Cristopher; Sales-Pardo, Marta

    2016-12-13

    With increasing amounts of information available, modeling and predicting user preferences-for books or articles, for example-are becoming more important. We present a collaborative filtering model, with an associated scalable algorithm, that makes accurate predictions of users' ratings. Like previous approaches, we assume that there are groups of users and of items and that the rating a user gives an item is determined by their respective group memberships. However, we allow each user and each item to belong simultaneously to mixtures of different groups and, unlike many popular approaches such as matrix factorization, we do not assume that users in each group prefer a single group of items. In particular, we do not assume that ratings depend linearly on a measure of similarity, but allow probability distributions of ratings to depend freely on the user's and item's groups. The resulting overlapping groups and predicted ratings can be inferred with an expectation-maximization algorithm whose running time scales linearly with the number of observed ratings. Our approach enables us to predict user preferences in large datasets and is considerably more accurate than the current algorithms for such large datasets.

  18. Accurate and scalable social recommendation using mixed-membership stochastic block models

    PubMed Central

    Godoy-Lorite, Antonia; Moore, Cristopher

    2016-01-01

    With increasing amounts of information available, modeling and predicting user preferences—for books or articles, for example—are becoming more important. We present a collaborative filtering model, with an associated scalable algorithm, that makes accurate predictions of users’ ratings. Like previous approaches, we assume that there are groups of users and of items and that the rating a user gives an item is determined by their respective group memberships. However, we allow each user and each item to belong simultaneously to mixtures of different groups and, unlike many popular approaches such as matrix factorization, we do not assume that users in each group prefer a single group of items. In particular, we do not assume that ratings depend linearly on a measure of similarity, but allow probability distributions of ratings to depend freely on the user’s and item’s groups. The resulting overlapping groups and predicted ratings can be inferred with an expectation-maximization algorithm whose running time scales linearly with the number of observed ratings. Our approach enables us to predict user preferences in large datasets and is considerably more accurate than the current algorithms for such large datasets. PMID:27911773

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

    PubMed

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

    2017-04-01

    The humidity surrounding a sample is an important variable in scientific experiments. Biological samples in particular require not just a humid atmosphere but often a relative humidity (RH) that is in equilibrium with a stabilizing solution required to maintain the sample in the same state during measurements. The controlled dehydration of macromolecular crystals can lead to significant increases in crystal order, leading to higher diffraction quality. Devices that can accurately control the humidity surrounding crystals while monitoring diffraction have led to this technique being increasingly adopted, as the experiments become easier and more reproducible. Matching the RH to the mother liquor is the first step in allowing the stable mounting of a crystal. In previous work [Wheeler, Russi, Bowler & Bowler (2012). Acta Cryst. F 68 , 111-114], the equilibrium RHs were measured for a range of concentrations of the most commonly used precipitants in macromolecular crystallography and it was shown how these related to Raoult's law for the equilibrium vapour pressure of water above a solution. However, a discrepancy between the measured values and those predicted by theory could not be explained. Here, a more precise humidity control device has been used to determine equilibrium RH points. The new results are in agreement with Raoult's law. A simple argument in statistical mechanics is also presented, demonstrating that the equilibrium vapour pressure of a solvent is proportional to its mole fraction in an ideal solution: Raoult's law. The same argument can be extended to the case where the solvent and solute molecules are of different sizes, as is the case with polymers. The results provide a framework for the correct maintenance of the RH surrounding a sample.

  20. Theoretical study in carrier mobility of two-dimensional materials

    NASA Astrophysics Data System (ADS)

    Huang, R.

    2017-09-01

    Recently, the theoretical prediction on carrier mobility of two-dimensional (2D) materials has aroused wild attention. At present, there is still a large gap between the theoretical prediction and the device performance of the semiconductor based on the 2D layer semiconductor materials such as graphene. It is particularly important to theoretically design and screen the high-performance 2D layered semiconductor materials with suitable band gap and high carrier mobility. This paper introduces some 2D materials with fine properties and deduces the formula for mobility of the isotropic materials on the basis of the deformation potential theory and Fermic golden rule under acoustic phonon scattering conditions, and then discusses the carrier mobility of anisotropic materials with Dirac cones. We point out the misconceptions in the existing literature and discuss the correct ones.

  1. 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?

  2. Theoretical prediction and impact of fundamental electric dipole moments

    DOE PAGES

    Ellis, Sebastian A. R.; Kane, Gordon L.

    2016-01-13

    The predicted Standard Model (SM) electric dipole moments (EDMs) of electrons and quarks are tiny, providing an important window to observe new physics. Theories beyond the SM typically allow relatively large EDMs. The EDMs depend on the relative phases of terms in the effective Lagrangian of the extended theory, which are generally unknown. Underlying theories, such as string/M-theories compactified to four dimensions, could predict the phases and thus EDMs in the resulting supersymmetric (SUSY) theory. Earlier one of us, with collaborators, made such a prediction and found, unexpectedly, that the phases were predicted to be zero at tree level inmore » the theory at the unification or string scale ~O(10 16 GeV). Electroweak (EW) scale EDMs still arise via running from the high scale, and depend only on the SM Yukawa couplings that also give the CKM phase. Here we extend the earlier work by studying the dependence of the low scale EDMs on the constrained but not fully known fundamental Yukawa couplings. The dominant contribution is from two loop diagrams and is not sensitive to the choice of Yukawa texture. The electron EDM should not be found to be larger than about 5 × 10 –30e cm, and the neutron EDM should not be larger than about 5 × 10 –29e cm. These values are quite a bit smaller than the reported predictions from Split SUSY and typical effective theories, but much larger than the Standard Model prediction. Also, since models with random phases typically give much larger EDMs, it is a significant testable prediction of compactified M-theory that the EDMs should not be above these upper limits. The actual EDMs can be below the limits, so once they are measured they could provide new insight into the fundamental Yukawa couplings of leptons and quarks. As a result, we comment also on the role of strong CP violation. EDMs probe fundamental physics near the Planck scale.« less

  3. Theoretical prediction and impact of fundamental electric dipole moments

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Ellis, Sebastian A. R.; Kane, Gordon L.

    The predicted Standard Model (SM) electric dipole moments (EDMs) of electrons and quarks are tiny, providing an important window to observe new physics. Theories beyond the SM typically allow relatively large EDMs. The EDMs depend on the relative phases of terms in the effective Lagrangian of the extended theory, which are generally unknown. Underlying theories, such as string/M-theories compactified to four dimensions, could predict the phases and thus EDMs in the resulting supersymmetric (SUSY) theory. Earlier one of us, with collaborators, made such a prediction and found, unexpectedly, that the phases were predicted to be zero at tree level inmore » the theory at the unification or string scale ~O(10 16 GeV). Electroweak (EW) scale EDMs still arise via running from the high scale, and depend only on the SM Yukawa couplings that also give the CKM phase. Here we extend the earlier work by studying the dependence of the low scale EDMs on the constrained but not fully known fundamental Yukawa couplings. The dominant contribution is from two loop diagrams and is not sensitive to the choice of Yukawa texture. The electron EDM should not be found to be larger than about 5 × 10 –30e cm, and the neutron EDM should not be larger than about 5 × 10 –29e cm. These values are quite a bit smaller than the reported predictions from Split SUSY and typical effective theories, but much larger than the Standard Model prediction. Also, since models with random phases typically give much larger EDMs, it is a significant testable prediction of compactified M-theory that the EDMs should not be above these upper limits. The actual EDMs can be below the limits, so once they are measured they could provide new insight into the fundamental Yukawa couplings of leptons and quarks. As a result, we comment also on the role of strong CP violation. EDMs probe fundamental physics near the Planck scale.« less

  4. Accurate prediction of RNA-binding protein residues with two discriminative structural descriptors.

    PubMed

    Sun, Meijian; Wang, Xia; Zou, Chuanxin; He, Zenghui; Liu, Wei; Li, Honglin

    2016-06-07

    RNA-binding proteins participate in many important biological processes concerning RNA-mediated gene regulation, and several computational methods have been recently developed to predict the protein-RNA interactions of RNA-binding proteins. Newly developed discriminative descriptors will help to improve the prediction accuracy of these prediction methods and provide further meaningful information for researchers. In this work, we designed two structural features (residue electrostatic surface potential and triplet interface propensity) and according to the statistical and structural analysis of protein-RNA complexes, the two features were powerful for identifying RNA-binding protein residues. Using these two features and other excellent structure- and sequence-based features, a random forest classifier was constructed to predict RNA-binding residues. The area under the receiver operating characteristic curve (AUC) of five-fold cross-validation for our method on training set RBP195 was 0.900, and when applied to the test set RBP68, the prediction accuracy (ACC) was 0.868, and the F-score was 0.631. The good prediction performance of our method revealed that the two newly designed descriptors could be discriminative for inferring protein residues interacting with RNAs. To facilitate the use of our method, a web-server called RNAProSite, which implements the proposed method, was constructed and is freely available at http://lilab.ecust.edu.cn/NABind .

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

    NASA Astrophysics Data System (ADS)

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

    2017-01-01

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

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

    ERIC Educational Resources Information Center

    Salley, Charles D.

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

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

    DTIC Science & Technology

    2011-09-30

    System via Accurate Light Calculations Curtis D. Mobley Sequoia Scientific, Inc. 2700 Richards Road, Suite 107 Bellevue, WA 98005 phone: 425...7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Sequoia Scientific, Inc,2700 Richards Road, Suite 107,Bellevue,WA,98005 8. PERFORMING...EcoLight-S 1.0 Users’ Guide and Technical Documentation. Sequoia Scientific, Inc., Bellevue, WA, 38 pages. Mobley, C. D., 2011. Fast light calculations

  8. Time-Accurate Numerical Prediction of Free Flight Aerodynamics of a Finned Projectile

    DTIC Science & Technology

    2005-09-01

    develop (with fewer dollars) more lethal and effective munitions. The munitions must stay abreast of the latest technology available to our...consuming. Computer simulations can and have provided an effective means of determining the unsteady aerodynamics and flight mechanics of guided projectile...Recently, the time-accurate technique was used to obtain improved results for Magnus moment and roll damping moment of a spinning projectile at transonic

  9. Accurate LC Peak Boundary Detection for 16 O/ 18 O Labeled LC-MS Data

    PubMed Central

    Cui, Jian; Petritis, Konstantinos; Tegeler, Tony; Petritis, Brianne; Ma, Xuepo; Jin, Yufang; Gao, Shou-Jiang (SJ); Zhang, Jianqiu (Michelle)

    2013-01-01

    In liquid chromatography-mass spectrometry (LC-MS), parts of LC peaks are often corrupted by their co-eluting peptides, which results in increased quantification variance. In this paper, we propose to apply accurate LC peak boundary detection to remove the corrupted part of LC peaks. Accurate LC peak boundary detection is achieved by checking the consistency of intensity patterns within peptide elution time ranges. In addition, we remove peptides with erroneous mass assignment through model fitness check, which compares observed intensity patterns to theoretically constructed ones. The proposed algorithm can significantly improve the accuracy and precision of peptide ratio measurements. PMID:24115998

  10. Theoretical prediction of the mechanistic pathways and kinetics of methylcyclohexane initiated by OH radicals

    NASA Astrophysics Data System (ADS)

    Begum, Saheen Shehnaz; Deka, Ramesh Chandra; Gour, Nand Kishor

    2018-06-01

    In this manuscript, we have systematically depicted the theoretical prediction of H-absorption from methylcyclohexane initiated by OH radical. For this we have performed dual-level of quantum chemical calculations on the gas-phase reactions between methylcyclohexane (MCH) and OH radical. Geometry optimisation and vibrational frequency calculations have been performed at BHandHLYP/6-311G(d,p) level of theory along with energetic calculations at coupled cluster CCSD(T) method using the same basis set. All the stationary points of titled reaction have been located on the potential energy surface. It has also been found that the H-abstraction takes place from -CH site of MCH, which is the minimum energy pathway than others. The rate constant was calculated using canonical transition state theory for MCH with OH radical and is found to be 3.27 × 10-12 cm3 molecule-1 s-1, which is in sound agreement with reported experimental data. The atmospheric lifetime of MCH and branching ratios of the reaction channels are also reported in the manuscript.

  11. Theoretical prediction of the electronic transport properties of the Al-Cu alloys based on the first-principle calculation and Boltzmann transport equation

    NASA Astrophysics Data System (ADS)

    Choi, Garam; Lee, Won Bo

    Metal alloys, especially Al-based, are commonly-used materials for various industrial applications. In this paper, the Al-Cu alloys with varying the Al-Cu ratio were investigated based on the first-principle calculation using density functional theory. And the electronic transport properties of the Al-Cu alloys were carried out using Boltzmann transport theory. From the results, the transport properties decrease with Cu-containing ratio at the temperature from moderate to high, but with non-linearity. It is inferred by various scattering effects from the calculation results with relaxation time approximation. For the Al-Cu alloy system, where it is hard to find the reliable experimental data for various alloys, it supports understanding and expectation for the thermal electrical properties from the theoretical prediction. Theoretical and computational soft matters laboratory.

  12. Enthalpy/entropy contributions to conformational KIEs: theoretical predictions and comparison with experiment.

    PubMed

    Fong, Aaron; Meyer, Matthew P; O'Leary, Daniel J

    2013-02-18

    Previous theoretical studies of Mislow's doubly-bridged biphenyl ketone 1 and dihydrodimethylphenanthrene 2 have determined significant entropic contributions to their normal (1) and inverse (2) conformational kinetic isotope effects (CKIEs). To broaden our investigation, we have used density functional methods to characterize the potential energy surfaces and vibrational frequencies for ground and transition structures of additional systems with measured CKIEs, including [2.2]-metaparacyclophane-d (3), 1,1'-binaphthyl (4), 2,2'-dibromo-[1,1'-biphenyl]-4,4'-dicarboxylic acid (5), and the 2-(N,N,N-trimethyl)-2'-(N,N-dimethyl)-diaminobiphenyl cation (6). We have also computed CKIEs in a number of systems whose experimental CKIEs are unknown. These include analogs of 1 in which the C=O groups have been replaced with CH₂ (7), O (8), and S (9) atoms and ring-expanded variants of 2 containing CH₂ (10), O (11), S (12), or C=O (13) groups. Vibrational entropy contributes to the CKIEs in all of these systems with the exception of cyclophane 3, whose isotope effect is predicted to be purely enthalpic in origin and whose Bigeleisen-Mayer ZPE term is equivalent to DDH‡. There is variable correspondence between these terms in the other molecules studied, thus identifying additional examples of systems in which the Bigeleisen-Mayer formalism does not correlate with DH/DS dissections.

  13. A theoretical perspective on road safety communication campaigns.

    PubMed

    Elvik, Rune

    2016-12-01

    This paper proposes a theoretical perspective on road safety communication campaigns, which may help in identifying the conditions under which such campaigns can be effective. The paper proposes that, from a theoretical point of view, it is reasonable to assume that road user behaviour is, by and large, subjectively rational. This means that road users are assumed to behave the way they think is best. If this assumption is accepted, the best theoretical prediction is that road safety campaigns consisting of persuasive messages only will have no effect on road user behaviour and accordingly no effect on accidents. This theoretical prediction is not supported by meta-analyses of studies that have evaluated the effects of road safety communication campaigns. These analyses conclude that, on the average, such campaigns are associated with an accident reduction. The paper discusses whether this finding can be explained theoretically. The discussion relies on the distinction made by many modern theorists between bounded and perfect rationality. Road user behaviour is characterised by bounded rationality. Hence, if road users can gain insight into the bounds of their rationality, so that they see advantages to themselves of changing behaviour, they are likely to do so. It is, however, largely unknown whether such a mechanism explains why some road safety communication campaigns have been found to be more effective than others. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. Accurate image-charge method by the use of the residue theorem for core-shell dielectric sphere

    NASA Astrophysics Data System (ADS)

    Fu, Jing; Xu, Zhenli

    2018-02-01

    An accurate image-charge method (ICM) is developed for ionic interactions outside a core-shell structured dielectric sphere. Core-shell particles have wide applications for which the theoretical investigation requires efficient methods for the Green's function used to calculate pairwise interactions of ions. The ICM is based on an inverse Mellin transform from the coefficients of spherical harmonic series of the Green's function such that the polarization charge due to dielectric boundaries is represented by a series of image point charges and an image line charge. The residue theorem is used to accurately calculate the density of the line charge. Numerical results show that the ICM is promising in fast evaluation of the Green's function, and thus it is useful for theoretical investigations of core-shell particles. This routine can also be applicable for solving other problems with spherical dielectric interfaces such as multilayered media and Debye-Hückel equations.

  15. A reduced theoretical model for estimating condensation effects in combustion-heated hypersonic tunnel

    NASA Astrophysics Data System (ADS)

    Lin, L.; Luo, X.; Qin, F.; Yang, J.

    2018-03-01

    As one of the combustion products of hydrocarbon fuels in a combustion-heated wind tunnel, water vapor may condense during the rapid expansion process, which will lead to a complex two-phase flow inside the wind tunnel and even change the design flow conditions at the nozzle exit. The coupling of the phase transition and the compressible flow makes the estimation of the condensation effects in such wind tunnels very difficult and time-consuming. In this work, a reduced theoretical model is developed to approximately compute the nozzle-exit conditions of a flow including real-gas and homogeneous condensation effects. Specifically, the conservation equations of the axisymmetric flow are first approximated in the quasi-one-dimensional way. Then, the complex process is split into two steps, i.e., a real-gas nozzle flow but excluding condensation, resulting in supersaturated nozzle-exit conditions, and a discontinuous jump at the end of the nozzle from the supersaturated state to a saturated state. Compared with two-dimensional numerical simulations implemented with a detailed condensation model, the reduced model predicts the flow parameters with good accuracy except for some deviations caused by the two-dimensional effect. Therefore, this reduced theoretical model can provide a fast, simple but also accurate estimation of the condensation effect in combustion-heated hypersonic tunnels.

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

    NASA Astrophysics Data System (ADS)

    Zhang, H. F.; Royer, G.

    2007-10-01

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

  17. Predicting the size of individual and group differences on speeded cognitive tasks.

    PubMed

    Chen, Jing; Hale, Sandra; Myerson, Joel

    2007-06-01

    An a priori test of the difference engine model (Myerson, Hale, Zheng, Jenkins, & Widaman, 2003) was conducted using a large, diverse sample of individuals who performed three speeded verbal tasks and three speeded visuospatial tasks. Results demonstrated that, as predicted by the model, the group standard deviation (SD) on any task was proportional to the amount of processing required by that task. Both individual performances as well as those of fast and slow subgroups could be accurately predicted by the model using no free parameters, just an individual or subgroup's mean z-score and the values of theoretical constructs estimated from fits to the group SDs. Taken together, these results are consistent with post hoc analyses reported by Myerson et al. and provide even stronger supporting evidence. In particular, the ability to make quantitative predictions without using any free parameters provides the clearest demonstration to date of the power of an analytic approach on the basis of the difference engine.

  18. Theoretical Characterizaiton of Visual Signatures

    NASA Astrophysics Data System (ADS)

    Kashinski, D. O.; Chase, G. M.; di Nallo, O. E.; Scales, A. N.; Vanderley, D. L.; Byrd, E. F. C.

    2015-05-01

    We are investigating the accuracy of theoretical models used to predict the visible, ultraviolet, and infrared spectra, as well as other properties, of product materials ejected from the muzzle of currently fielded systems. Recent advances in solid propellants has made the management of muzzle signature (flash) a principle issue in weapons development across the calibers. A priori prediction of the electromagnetic spectra of formulations will allow researchers to tailor blends that yield desired signatures and determine spectrographic detection ranges. Quantum chemistry methods at various levels of sophistication have been employed to optimize molecular geometries, compute unscaled vibrational frequencies, and determine the optical spectra of specific gas-phase species. Electronic excitations are being computed using Time Dependent Density Functional Theory (TD-DFT). A full statistical analysis and reliability assessment of computational results is currently underway. A comparison of theoretical results to experimental values found in the literature is used to assess any affects of functional choice and basis set on calculation accuracy. The status of this work will be presented at the conference. Work supported by the ARL, DoD HPCMP, and USMA.

  19. Predictive Computational Modeling of Chromatin Folding

    NASA Astrophysics Data System (ADS)

    di Pierro, Miichele; Zhang, Bin; Wolynes, Peter J.; Onuchic, Jose N.

    In vivo, the human genome folds into well-determined and conserved three-dimensional structures. The mechanism driving the folding process remains unknown. We report a theoretical model (MiChroM) for chromatin derived by using the maximum entropy principle. The proposed model allows Molecular Dynamics simulations of the genome using as input the classification of loci into chromatin types and the presence of binding sites of loop forming protein CTCF. The model was trained to reproduce the Hi-C map of chromosome 10 of human lymphoblastoid cells. With no additional tuning the model was able to predict accurately the Hi-C maps of chromosomes 1-22 for the same cell line. Simulations show unknotted chromosomes, phase separation of chromatin types and a preference of chromatin of type A to sit at the periphery of the chromosomes.

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-09-30

    database of images for evaluating object recognition performance. We used multielectrode arrays to characterize hundreds of neurons in the visual ventral stream of nonhuman primates and measured the object recognition performance of >100 human observers. Remarkably, we found that simple learned weighted sums of firing rates of neurons in monkey inferior temporal (IT) cortex accurately predicted human performance. Although previous work led us to expect that IT would outperform V4, we were surprised by the quantitative precision with which simple IT-based linking hypotheses accounted for human behavior. Copyright © 2015 the authors 0270-6474/15/3513402-17$15.00/0.

  2. Improvement of experimental testing and network training conditions with genome-wide microarrays for more accurate predictions of drug gene targets

    PubMed Central

    2014-01-01

    Background Genome-wide microarrays have been useful for predicting chemical-genetic interactions at the gene level. However, interpreting genome-wide microarray results can be overwhelming due to the vast output of gene expression data combined with off-target transcriptional responses many times induced by a drug treatment. This study demonstrates how experimental and computational methods can interact with each other, to arrive at more accurate predictions of drug-induced perturbations. We present a two-stage strategy that links microarray experimental testing and network training conditions to predict gene perturbations for a drug with a known mechanism of action in a well-studied organism. Results S. cerevisiae cells were treated with the antifungal, fluconazole, and expression profiling was conducted under different biological conditions using Affymetrix genome-wide microarrays. Transcripts were filtered with a formal network-based method, sparse simultaneous equation models and Lasso regression (SSEM-Lasso), under different network training conditions. Gene expression results were evaluated using both gene set and single gene target analyses, and the drug’s transcriptional effects were narrowed first by pathway and then by individual genes. Variables included: (i) Testing conditions – exposure time and concentration and (ii) Network training conditions – training compendium modifications. Two analyses of SSEM-Lasso output – gene set and single gene – were conducted to gain a better understanding of how SSEM-Lasso predicts perturbation targets. Conclusions This study demonstrates that genome-wide microarrays can be optimized using a two-stage strategy for a more in-depth understanding of how a cell manifests biological reactions to a drug treatment at the transcription level. Additionally, a more detailed understanding of how the statistical model, SSEM-Lasso, propagates perturbations through a network of gene regulatory interactions is achieved

  3. A theoretical and experimental study of wood planer noise and its control

    NASA Technical Reports Server (NTRS)

    Stewart, J. S.

    1972-01-01

    A combined analytical and experimental study of wood planer noise is made and the results applied to the development of practical noise control techniques. The dominant mechanisms of sound generation are identified and an analysis is presented which accurately predicts the governing levels of noise emission. Planing operations in which the length of the board is much greater than the width are considered. The dominant source of planer noise is identified as the board being surfaced, which is set into vibration by the impact of cutterhead knives. This is determined from studies made both in the laboratory and in the field concerning the effect of board width on the resulting noise, which indicate a six decibel increase in noise level for each doubling of board width. The theoretical development of a model for board vibration defines the vibrational field set up in the board and serves as a guide for cutterhead redesign.

  4. Breaking the theoretical scaling limit for predicting quasiparticle energies: the stochastic GW approach.

    PubMed

    Neuhauser, Daniel; Gao, Yi; Arntsen, Christopher; Karshenas, Cyrus; Rabani, Eran; Baer, Roi

    2014-08-15

    We develop a formalism to calculate the quasiparticle energy within the GW many-body perturbation correction to the density functional theory. The occupied and virtual orbitals of the Kohn-Sham Hamiltonian are replaced by stochastic orbitals used to evaluate the Green function G, the polarization potential W, and, thereby, the GW self-energy. The stochastic GW (sGW) formalism relies on novel theoretical concepts such as stochastic time-dependent Hartree propagation, stochastic matrix compression, and spatial or temporal stochastic decoupling techniques. Beyond the theoretical interest, the formalism enables linear scaling GW calculations breaking the theoretical scaling limit for GW as well as circumventing the need for energy cutoff approximations. We illustrate the method for silicon nanocrystals of varying sizes with N_{e}>3000 electrons.

  5. An experimental/theoretical method to measure the capacitive compactness of an aqueous electrolyte surrounding a spherical charged colloid

    NASA Astrophysics Data System (ADS)

    Moraila-Martínez, Carmen Lucía; Guerrero-García, Guillermo Iván; Chávez-Páez, Martín; González-Tovar, Enrique

    2018-04-01

    The capacitive compactness has been introduced very recently [G. I. Guerrero-García et al., Phys. Chem. Chem. Phys. 20, 262-275 (2018)] as a robust and accurate measure to quantify the thickness, or spatial extension, of the electrical double layer next to either an infinite charged electrode or a spherical macroion. We propose here an experimental/theoretical scheme to determine the capacitive compactness of a spherical electrical double layer that relies on the calculation of the electrokinetic charge and the associated mean electrostatic potential at the macroparticle's surface. This is achieved by numerically solving the non-linear Poisson-Boltzmann equation of point ions around a colloidal sphere and matching the corresponding theoretical mobility, predicted by the O'Brien and White theory [J. Chem. Soc., Faraday Trans. 2 74, 1607-1626 (1978)], with experimental measurements of the electrophoretic mobility under the same conditions. This novel method is used to calculate the capacitive compactness of NaCl and CaCl2 electrolytes surrounding a negatively charged polystyrene particle as a function of the salt concentration.

  6. High Speed Research Noise Prediction Code (HSRNOISE) User's and Theoretical Manual

    NASA Technical Reports Server (NTRS)

    Golub, Robert (Technical Monitor); Rawls, John W., Jr.; Yeager, Jessie C.

    2004-01-01

    This report describes a computer program, HSRNOISE, that predicts noise levels for a supersonic aircraft powered by mixed flow turbofan engines with rectangular mixer-ejector nozzles. It fully documents the noise prediction algorithms, provides instructions for executing the HSRNOISE code, and provides predicted noise levels for the High Speed Research (HSR) program Technology Concept (TC) aircraft. The component source noise prediction algorithms were developed jointly by Boeing, General Electric Aircraft Engines (GEAE), NASA and Pratt & Whitney during the course of the NASA HSR program. Modern Technologies Corporation developed an alternative mixer ejector jet noise prediction method under contract to GEAE that has also been incorporated into the HSRNOISE prediction code. Algorithms for determining propagation effects and calculating noise metrics were taken from the NASA Aircraft Noise Prediction Program.

  7. Using Data Assimilation Methods of Prediction of Solar Activity

    NASA Technical Reports Server (NTRS)

    Kitiashvili, Irina N.; Collins, Nancy S.

    2017-01-01

    The variable solar magnetic activity known as the 11-year solar cycle has the longest history of solar observations. These cycles dramatically affect conditions in the heliosphere and the Earth's space environment. Our current understanding of the physical processes that make up global solar dynamics and the dynamo that generates the magnetic fields is sketchy, resulting in unrealistic descriptions in theoretical and numerical models of the solar cycles. The absence of long-term observations of solar interior dynamics and photospheric magnetic fields hinders development of accurate dynamo models and their calibration. In such situations, mathematical data assimilation methods provide an optimal approach for combining the available observational data and their uncertainties with theoretical models in order to estimate the state of the solar dynamo and predict future cycles. In this presentation, we will discuss the implementation and performance of an Ensemble Kalman Filter data assimilation method based on the Parker migratory dynamo model, complemented by the equation of magnetic helicity conservation and long-term sunspot data series. This approach has allowed us to reproduce the general properties of solar cycles and has already demonstrated a good predictive capability for the current cycle, 24. We will discuss further development of this approach, which includes a more sophisticated dynamo model, synoptic magnetogram data, and employs the DART Data Assimilation Research Testbed.

  8. Accurate lithography simulation model based on convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Watanabe, Yuki; Kimura, Taiki; Matsunawa, Tetsuaki; Nojima, Shigeki

    2017-07-01

    Lithography simulation is an essential technique for today's semiconductor manufacturing process. In order to calculate an entire chip in realistic time, compact resist model is commonly used. The model is established for faster calculation. To have accurate compact resist model, it is necessary to fix a complicated non-linear model function. However, it is difficult to decide an appropriate function manually because there are many options. This paper proposes a new compact resist model using CNN (Convolutional Neural Networks) which is one of deep learning techniques. CNN model makes it possible to determine an appropriate model function and achieve accurate simulation. Experimental results show CNN model can reduce CD prediction errors by 70% compared with the conventional model.

  9. Theoretical Prediction of the Forming Limit Band

    NASA Astrophysics Data System (ADS)

    Banabic, D.; Vos, M.; Paraianu, L.; Jurco, P.

    2007-04-01

    Forming Limit Band (FLB) is a very useful tool to improve the sheet metal forming simulation robustness. Until now, the study of the FLB was only experimental. This paper presents the first attempt to model the FLB. The authors have established an original method for predicting the two margins of the limit band. The method was illustrated on the AA6111-T43 aluminum alloy. A good agreement with the experiments has been obtained.

  10. Metabolite signal identification in accurate mass metabolomics data with MZedDB, an interactive m/z annotation tool utilising predicted ionisation behaviour 'rules'

    PubMed Central

    Draper, John; Enot, David P; Parker, David; Beckmann, Manfred; Snowdon, Stuart; Lin, Wanchang; Zubair, Hassan

    2009-01-01

    Background Metabolomics experiments using Mass Spectrometry (MS) technology measure the mass to charge ratio (m/z) and intensity of ionised molecules in crude extracts of complex biological samples to generate high dimensional metabolite 'fingerprint' or metabolite 'profile' data. High resolution MS instruments perform routinely with a mass accuracy of < 5 ppm (parts per million) thus providing potentially a direct method for signal putative annotation using databases containing metabolite mass information. Most database interfaces support only simple queries with the default assumption that molecules either gain or lose a single proton when ionised. In reality the annotation process is confounded by the fact that many ionisation products will be not only molecular isotopes but also salt/solvent adducts and neutral loss fragments of original metabolites. This report describes an annotation strategy that will allow searching based on all potential ionisation products predicted to form during electrospray ionisation (ESI). Results Metabolite 'structures' harvested from publicly accessible databases were converted into a common format to generate a comprehensive archive in MZedDB. 'Rules' were derived from chemical information that allowed MZedDB to generate a list of adducts and neutral loss fragments putatively able to form for each structure and calculate, on the fly, the exact molecular weight of every potential ionisation product to provide targets for annotation searches based on accurate mass. We demonstrate that data matrices representing populations of ionisation products generated from different biological matrices contain a large proportion (sometimes > 50%) of molecular isotopes, salt adducts and neutral loss fragments. Correlation analysis of ESI-MS data features confirmed the predicted relationships of m/z signals. An integrated isotope enumerator in MZedDB allowed verification of exact isotopic pattern distributions to corroborate experimental data

  11. 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.

  12. Prediction using patient comparison vs. modeling: a case study for mortality prediction.

    PubMed

    Hoogendoorn, Mark; El Hassouni, Ali; Mok, Kwongyen; Ghassemi, Marzyeh; Szolovits, Peter

    2016-08-01

    Information in Electronic Medical Records (EMRs) can be used to generate accurate predictions for the occurrence of a variety of health states, which can contribute to more pro-active interventions. The very nature of EMRs does make the application of off-the-shelf machine learning techniques difficult. In this paper, we study two approaches to making predictions that have hardly been compared in the past: (1) extracting high-level (temporal) features from EMRs and building a predictive model, and (2) defining a patient similarity metric and predicting based on the outcome observed for similar patients. We analyze and compare both approaches on the MIMIC-II ICU dataset to predict patient mortality and find that the patient similarity approach does not scale well and results in a less accurate model (AUC of 0.68) compared to the modeling approach (0.84). We also show that mortality can be predicted within a median of 72 hours.

  13. The prediction of pressure distributions on an arrow-wing configuration including the effect of camber, twist, and a wing fin

    NASA Technical Reports Server (NTRS)

    Bobbitt, P. J.; Manro, M. E.; Kulfan, R. M.

    1980-01-01

    Wind tunnel tests of an arrow wing body configuration consisting of flat, twisted, and cambered twisted wings were conducted at Mach numbers from 0.40 to 2.50 to provide an experimental data base for comparison with theoretical methods. A variety of leading and trailing edge control surface deflections were included in these tests, and in addition, the cambered twisted wing was tested with an outboard vertical fin to determine its effect on wing and control surface loads. Theory experiment comparisons show that current state of the art linear and nonlinear attached flow methods were adequate at small angles of attack typical of cruise conditions. The incremental effects of outboard fin, wing twist, and wing camber are most accurately predicted by the advanced panel method PANAIR. Results of the advanced panel separated flow method, obtained with an early version of the program, show promise that accurate detailed pressure predictions may soon be possible for an aeroelasticity deformed wing at high angles of attack.

  14. Dynamic properties and damping predictions for laminated plates: High order theories - Timoshenko beam

    NASA Astrophysics Data System (ADS)

    Diveyev, Bohdan; Konyk, Solomija; Crocker, Malcolm J.

    2018-01-01

    The main aim of this study is to predict the elastic and damping properties of composite laminated plates. This problem has an exact elasticity solution for simple uniform bending and transverse loading conditions. This paper presents a new stress analysis method for the accurate determination of the detailed stress distributions in laminated plates subjected to cylindrical bending. Some approximate methods for the stress state predictions for laminated plates are presented here. The present method is adaptive and does not rely on strong assumptions about the model of the plate. The theoretical model described here incorporates deformations of each sheet of the lamina, which account for the effects of transverse shear deformation, transverse normal strain-stress and nonlinear variation of displacements with respect to the thickness coordinate. Predictions of the dynamic and damping values of laminated plates for various geometrical, mechanical and fastening properties are presented. Comparison with the Timoshenko beam theory is systematically made for analytical and approximation variants.

  15. New and Accurate Predictive Model for the Efficacy of Extracorporeal Shock Wave Therapy in Managing Patients With Chronic Plantar Fasciitis.

    PubMed

    Yin, Mengchen; Chen, Ni; Huang, Quan; Marla, Anastasia Sulindro; Ma, Junming; Ye, Jie; Mo, Wen

    2017-12-01

    Youden index was .4243, .3003, and .7189, respectively. The Hosmer-Lemeshow test showed a good fitting of the predictive model, with an overall accuracy of 89.6%. This study establishes a new and accurate predictive model for the efficacy of ESWT in managing patients with chronic plantar fasciitis. The use of these parameters, in the form of a predictive model for ESWT efficacy, has the potential to improve decision-making in the application of ESWT. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

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

    PubMed Central

    2016-01-01

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

  17. Vibrational spectroscopy and theoretical studies on 2,4-dinitrophenylhydrazine

    NASA Astrophysics Data System (ADS)

    Chiş, V.; Filip, S.; Miclăuş, V.; Pîrnău, A.; Tănăselia, C.; Almăşan, V.; Vasilescu, M.

    2005-06-01

    In this work, we will report a combined experimental and theoretical study on molecular and vibrational structure of 2,4-dinitrophenylhydrazine. FT-IR, FT-IR/ATR and Raman spectra of normal and deuterated DNPH have been recorded and analyzed in order to get new insights into molecular structure and properties of this molecule, with particular emphasize on its intra- and intermolecular hydrogen bonds (HB's). For computational purposes we used density functional theory (DFT) methods, with B3LYP and BLYP exchange-correlation functionals, in conjunction with 6-31G(d) basis set. All experimental vibrational bands have been discussed and assigned to normal modes on the basis of DFT calculations and isotopic shifts and by comparison to other dinitro- substituted compounds [V. Chiş, Chem. Phys., 300 (2004) 1]. To aid in mode assignments, we based on the direct comparison between experimental and calculated spectra by considering both the frequency sequence and the intensity pattern of the experimental and computed vibrational bands. It is also shown that semiempirical AM1 method predicts geometrical parameters and vibrational frequencies related to the HB in a pleasant agreement with experiment, being surprisingly accurate from this perspective.

  18. Theoretical integration and the psychology of sport injury prevention.

    PubMed

    Chan, Derwin King-Chung; Hagger, Martin S

    2012-09-01

    Integrating different theories of motivation to facilitate or predict behaviour change has received an increasing amount of attention within the health, sport and exercise science literature. A recent review article in Sports Medicine, by Keats, Emery and Finch presented an integrated model using two prominent theories in social psychology, self-determination theory (SDT) and the theory of planned behaviour (TPB), aimed at explaining and enhancing athletes' adherence to sport injury prevention. While echoing their optimistic views about the utility of these two theories to explain adherence in this area and the virtues of theoretical integration, we would like to seize this opportunity to clarify several conceptual principles arising from the authors' integration of the theories. Clarifying the theoretical assumptions and explaining precisely how theoretical integration works is crucial not only for improving the comprehensiveness of the integrated framework for predicting injury prevention behaviour, but also to aid the design of effective intervention strategies targeting behavioural adherence. In this article, we use the integration of SDT and TPB as an example to demonstrate how theoretical integration can advance the understanding of injury prevention behaviour in sport.

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

    NASA Astrophysics Data System (ADS)

    Shavalikul, Akamol

    accurate flow characteristics in the NGV domain and the rotor domain with less computational time and computer memory requirements. In contrast, the time accurate flow simulation can predict all unsteady flow characteristics occurring in the turbine stage, but with high computational resource requirements. (Abstract shortened by UMI.)

  20. An instrument for rapid, accurate, determination of fuel moisture content

    Treesearch

    Stephen S. Sackett

    1980-01-01

    Moisture contents of dead and living fuels are key variables in fire behavior. Accurate, real-time fuel moisture data are required for prescribed burning and wildfire behavior predictions. The convection oven method has become the standard for direct fuel moisture content determination. Efforts to quantify fuel moisture through indirect methods have not been...

  1. Theoretical calculations of physico-chemical and spectroscopic properties of bioinorganic systems: current limits and perspectives.

    PubMed

    Rokob, Tibor András; Srnec, Martin; Rulíšek, Lubomír

    2012-05-21

    In the last decade, we have witnessed substantial progress in the development of quantum chemical methodologies. Simultaneously, robust solvation models and various combined quantum and molecular mechanical (QM/MM) approaches have become an integral part of quantum chemical programs. Along with the steady growth of computer power and, more importantly, the dramatic increase of the computer performance to price ratio, this has led to a situation where computational chemistry, when exercised with the proper amount of diligence and expertise, reproduces, predicts, and complements the experimental data. In this perspective, we review some of the latest achievements in the field of theoretical (quantum) bioinorganic chemistry, concentrating mostly on accurate calculations of the spectroscopic and physico-chemical properties of open-shell bioinorganic systems by wave-function (ab initio) and DFT methods. In our opinion, the one-to-one mapping between the calculated properties and individual molecular structures represents a major advantage of quantum chemical modelling since this type of information is very difficult to obtain experimentally. Once (and only once) the physico-chemical, thermodynamic and spectroscopic properties of complex bioinorganic systems are quantitatively reproduced by theoretical calculations may we consider the outcome of theoretical modelling, such as reaction profiles and the various decompositions of the calculated parameters into individual spatial or physical contributions, to be reliable. In an ideal situation, agreement between theory and experiment may imply that the practical problem at hand, such as the reaction mechanism of the studied metalloprotein, can be considered as essentially solved.

  2. The CPA Equation of State and an Activity Coefficient Model for Accurate Molar Enthalpy Calculations of Mixtures with Carbon Dioxide and Water/Brine

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Myint, P. C.; Hao, Y.; Firoozabadi, A.

    2015-03-27

    Thermodynamic property calculations of mixtures containing carbon dioxide (CO 2) and water, including brines, are essential in theoretical models of many natural and industrial processes. The properties of greatest practical interest are density, solubility, and enthalpy. Many models for density and solubility calculations have been presented in the literature, but there exists only one study, by Spycher and Pruess, that has compared theoretical molar enthalpy predictions with experimental data [1]. In this report, we recommend two different models for enthalpy calculations: the CPA equation of state by Li and Firoozabadi [2], and the CO 2 activity coefficient model by Duanmore » and Sun [3]. We show that the CPA equation of state, which has been demonstrated to provide good agreement with density and solubility data, also accurately calculates molar enthalpies of pure CO 2, pure water, and both CO 2-rich and aqueous (H 2O-rich) mixtures of the two species. It is applicable to a wider range of conditions than the Spycher and Pruess model. In aqueous sodium chloride (NaCl) mixtures, we show that Duan and Sun’s model yields accurate results for the partial molar enthalpy of CO 2. It can be combined with another model for the brine enthalpy to calculate the molar enthalpy of H 2O-CO 2-NaCl mixtures. We conclude by explaining how the CPA equation of state may be modified to further improve agreement with experiments. This generalized CPA is the basis of our future work on this topic.« less

  3. Predicting Stability Constants for Uranyl Complexes Using Density Functional Theory

    DOE PAGES

    Vukovic, Sinisa; Hay, Benjamin P.; Bryantsev, Vyacheslav S.

    2015-04-02

    The ability to predict the equilibrium constants for the formation of 1:1 uranyl:ligand complexes (log K 1 values) provides the essential foundation for the rational design of ligands with enhanced uranyl affinity and selectivity. We also use density functional theory (B3LYP) and the IEFPCM continuum solvation model to compute aqueous stability constants for UO 2 2+ complexes with 18 donor ligands. Theoretical calculations permit reasonably good estimates of relative binding strengths, while the absolute log K 1 values are significantly overestimated. Accurate predictions of the absolute log K 1 values (root mean square deviation from experiment < 1.0 for logmore » K 1 values ranging from 0 to 16.8) can be obtained by fitting the experimental data for two groups of mono and divalent negative oxygen donor ligands. The utility of correlations is demonstrated for amidoxime and imide dioxime ligands, providing a useful means of screening for new ligands with strong chelate capability to uranyl.« less

  4. Accurate age determinations of several nearby open clusters containing magnetic Ap stars

    NASA Astrophysics Data System (ADS)

    Silaj, J.; Landstreet, J. D.

    2014-06-01

    Context. To study the time evolution of magnetic fields, chemical abundance peculiarities, and other characteristics of magnetic Ap and Bp stars during their main sequence lives, a sample of these stars in open clusters has been obtained, as such stars can be assumed to have the same ages as the clusters to which they belong. However, in exploring age determinations in the literature, we find a large dispersion among different age determinations, even for bright, nearby clusters. Aims: Our aim is to obtain ages that are as accurate as possible for the seven nearby open clusters α Per, Coma Ber, IC 2602, NGC 2232, NGC 2451A, NGC 2516, and NGC 6475, each of which contains at least one magnetic Ap or Bp star. Simultaneously, we test the current calibrations of Te and luminosity for the Ap/Bp star members, and identify clearly blue stragglers in the clusters studied. Methods: We explore the possibility that isochrone fitting in the theoretical Hertzsprung-Russell diagram (i.e. log (L/L⊙) vs. log Te), rather than in the conventional colour-magnitude diagram, can provide more precise and accurate cluster ages, with well-defined uncertainties. Results: Well-defined ages are found for all the clusters studied. For the nearby clusters studied, the derived ages are not very sensitive to the small uncertainties in distance, reddening, membership, metallicity, or choice of isochrones. Our age determinations are all within the range of previously determined values, but the associated uncertainties are considerably smaller than the spread in recent age determinations from the literature. Furthermore, examination of proper motions and HR diagrams confirms that the Ap stars identified in these clusters are members, and that the presently accepted temperature scale and bolometric corrections for Ap stars are approximately correct. We show that in these theoretical HR diagrams blue stragglers are particularly easy to identify. Conclusions: Constructing the theoretical HR diagram

  5. An Accurate ab initio Quartic Force Field and Vibrational Frequencies for CH4 and Isotopomers

    NASA Technical Reports Server (NTRS)

    Lee, Timothy J.; Martin, Jan M. L.; Taylor, Peter R.

    1995-01-01

    A very accurate ab initio quartic force field for CH4 and its isotopomers is presented. The quartic force field was determined with the singles and doubles coupled-cluster procedure that includes a quasiperturbative estimate of the effects of connected triple excitations, CCSD(T), using the correlation consistent polarized valence triple zeta, cc-pVTZ, basis set. Improved quadratic force constants were evaluated with the correlation consistent polarized valence quadruple zeta, cc-pVQZ, basis set. Fundamental vibrational frequencies are determined using second-order perturbation theory anharmonic analyses. All fundamentals of CH4 and isotopomers for which accurate experimental values exist and for which there is not a large Fermi resonance, are predicted to within +/- 6 cm(exp -1). It is thus concluded that our predictions for the harmonic frequencies and the anharmonic constants are the most accurate estimates available. It is also shown that using cubic and quartic force constants determined with the correlation consistent polarized double zeta, cc-pVDZ, basis set in conjunction with the cc-pVQZ quadratic force constants and equilibrium geometry leads to accurate predictions for the fundamental vibrational frequencies of methane, suggesting that this approach may be a viable alternative for larger molecules. Using CCSD(T), core correlation is found to reduce the CH4 r(e), by 0.0015 A. Our best estimate for r, is 1.0862 +/- 0.0005 A.

  6. Theoretical prediction of pKa in methanol: testing SM8 and SMD models for carboxylic acids, phenols, and amines.

    PubMed

    Miguel, Elizabeth L M; Silva, Poliana L; Pliego, Josefredo R

    2014-05-29

    Methanol is a widely used solvent for chemical reactions and has solvation properties similar to those of water. However, the performance of continuum solvation models in this solvent has not been tested yet. In this report, we have investigated the performance of the SM8 and SMD models for pKa prediction of 26 carboxylic acids, 24 phenols, and 23 amines in methanol. The gas phase contribution was included at the X3LYP/TZVPP+diff//X3LYP/DZV+P(d) level. Using the proton exchange reaction with acetic acid, phenol, and ammonia as reference species leads to RMS error in the range of 1.4 to 3.6 pKa units. This finding suggests that the performance of the continuum models for methanol is similar to that found for aqueous solvent. Application of simple empirical correction through a linear equation leads to accurate pKa prediction, with uncertainty less than 0.8 units with the SM8 method. Testing with the less expensive PBE1PBE/6-311+G** method results in a slight improvement in the results.

  7. Calibration Techniques for Accurate Measurements by Underwater Camera Systems

    PubMed Central

    Shortis, Mark

    2015-01-01

    Calibration of a camera system is essential to ensure that image measurements result in accurate estimates of locations and dimensions within the object space. In the underwater environment, the calibration must implicitly or explicitly model and compensate for the refractive effects of waterproof housings and the water medium. This paper reviews the different approaches to the calibration of underwater camera systems in theoretical and practical terms. The accuracy, reliability, validation and stability of underwater camera system calibration are also discussed. Samples of results from published reports are provided to demonstrate the range of possible accuracies for the measurements produced by underwater camera systems. PMID:26690172

  8. Accurate virial coefficients of gaseous krypton from state-of-the-art ab initio potential and polarizability of the krypton dimer

    NASA Astrophysics Data System (ADS)

    Song, Bo; Waldrop, Jonathan M.; Wang, Xiaopo; Patkowski, Konrad

    2018-01-01

    We have developed a new krypton-krypton interaction-induced isotropic dipole polarizability curve based on high-level ab initio methods. The determination was carried out using the coupled-cluster singles and doubles plus perturbative triples method with very large basis sets up to augmented correlation-consistent sextuple zeta as well as the corrections for core-core and core-valence correlation and relativistic effects. The analytical function of polarizability and our recently constructed reference interatomic potential [J. M. Waldrop et al., J. Chem. Phys. 142, 204307 (2015)] were used to predict the thermophysical and electromagnetic properties of krypton gas. The second pressure, acoustic, and dielectric virial coefficients were computed for the temperature range of 116 K-5000 K using classical statistical mechanics supplemented with high-order quantum corrections. The virial coefficients calculated were compared with the generally less precise available experimental data as well as with values computed from other potentials in the literature {in particular, the recent highly accurate potential of Jäger et al. [J. Chem. Phys. 144, 114304 (2016)]}. The detailed examination in this work suggests that the present theoretical prediction can be applied as reference values in disciplines involving thermophysical and electromagnetic properties of krypton gas.

  9. Theoretical status of the lifetime predictions:. (ΔΓ/Γ)Bs, τB+/τBd and τΛbBd

    NASA Astrophysics Data System (ADS)

    Lenz, Alexander

    2002-04-01

    We give a review of the theoretical status of the lifetime predictions in the standard model. In case of (ΔΓ/Γ)Bs we are already in a rather advanced stage. We obtain (Δ Γ /Γ )Bs = (9.3+3.4-4.6)%. It seems to be difficult to improve these errors substantially. In addition now some experimental results are available. For τB+/τBd and τΛbBd the theoretical status is much less advanced and the discrepancy between experiment and theory still remains. We conclude with a what-to-do-list for theorists.

  10. A quantum theoretical study of polyimides

    NASA Technical Reports Server (NTRS)

    Burke, Luke A.

    1987-01-01

    One of the most important contributions of theoretical chemistry is the correct prediction of properties of materials before any costly experimental work begins. This is especially true in the field of electrically conducting polymers. Development of the Valence Effective Hamiltonian (VEH) technique for the calculation of the band structure of polymers was initiated. The necessary VEH potentials were developed for the sulfur and oxygen atoms within the particular molecular environments and the explanation explored for the success of this approximate method in predicting the optical properties of conducting polymers.

  11. Predicted and experimental aerodynamic forces on the Darrieus rotor

    NASA Astrophysics Data System (ADS)

    Paraschivoiu, I.

    1983-12-01

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

  12. An Experimental and Theoretical Study on Cavitating Propellers.

    DTIC Science & Technology

    1982-10-01

    34 And Identfyp eV &to" nMeeJ cascade flow theoretical supercavitating flow performance prediction method partially cavitating flow supercavitating ...the present work was to develop an analytical tool for predicting the off-design performance of supercavitating propellers over a wide range of...operating conditions. Due to the complex nature of the flow phenomena, a lifting line theory sirply combined with the two-dimensional supercavitating

  13. Array Simulations Platform (ASP) predicts NASA Data Link Module (NDLM) performance

    NASA Technical Reports Server (NTRS)

    Snook, Allen David

    1993-01-01

    Through a variety of imbedded theoretical and actual antenna patterns, the array simulation platform (ASP) enhanced analysis of the array antenna pattern effects for the KTx (Ku-Band Transmit) service of the NDLM (NASA Data Link Module). The ASP utilizes internally stored models of the NDLM antennas and can develop the overall pattern of antenna arrays through common array calculation techniques. ASP expertly assisted in the diagnosing of element phase shifter errors during KTx testing and was able to accurately predict the overall array pattern from combinations of the four internally held element patterns. This paper provides an overview of the use of the ASP software in the solving of array mis-phasing problems.

  14. A combined theoretical and in vitro modeling approach for predicting the magnetic capture and retention of magnetic nanoparticles in vivo

    PubMed Central

    David, Allan E.; Cole, Adam J.; Chertok, Beata; Park, Yoon Shin; Yang, Victor C.

    2011-01-01

    Magnetic nanoparticles (MNP) continue to draw considerable attention as potential diagnostic and therapeutic tools in the fight against cancer. Although many interacting forces present themselves during magnetic targeting of MNP to tumors, most theoretical considerations of this process ignore all except for the magnetic and drag forces. Our validation of a simple in vitro model against in vivo data, and subsequent reproduction of the in vitro results with a theoretical model indicated that these two forces do indeed dominate the magnetic capture of MNP. However, because nanoparticles can be subject to aggregation, and large MNP experience an increased magnetic force, the effects of surface forces on MNP stability cannot be ignored. We accounted for the aggregating surface forces simply by measuring the size of MNP retained from flow by magnetic fields, and utilized this size in the mathematical model. This presumably accounted for all particle-particle interactions, including those between magnetic dipoles. Thus, our “corrected” mathematical model provided a reasonable estimate of not only fractional MNP retention, but also predicted the regions of accumulation in a simulated capillary. Furthermore, the model was also utilized to calculate the effects of MNP size and spatial location, relative to the magnet, on targeting of MNPs to tumors. This combination of an in vitro model with a theoretical model could potentially assist with parametric evaluations of magnetic targeting, and enable rapid enhancement and optimization of magnetic targeting methodologies. PMID:21295085

  15. Do measures of surgical effectiveness at 1 year after lumbar spine surgery accurately predict 2-year outcomes?

    PubMed

    Adogwa, Owoicho; Elsamadicy, Aladine A; Han, Jing L; Cheng, Joseph; Karikari, Isaac; Bagley, Carlos A

    2016-12-01

    OBJECTIVE With the recent passage of the Patient Protection and Affordable Care Act, there has been a dramatic shift toward critical analyses of quality and longitudinal assessment of subjective and objective outcomes after lumbar spine surgery. Accordingly, the emergence and routine use of real-world institutional registries have been vital to the longitudinal assessment of quality. However, prospectively obtaining longitudinal outcomes for patients at 24 months after spine surgery remains a challenge. The aim of this study was to assess if 12-month measures of treatment effectiveness accurately predict long-term outcomes (24 months). METHODS A nationwide, multiinstitutional, prospective spine outcomes registry was used for this study. Enrollment criteria included available demographic, surgical, and clinical outcomes data. All patients had prospectively collected outcomes measures and a minimum 2-year follow-up. Patient-reported outcomes instruments (Oswestry Disability Index [ODI], SF-36, and visual analog scale [VAS]-back pain/leg pain) were completed before surgery and then at 3, 6, 12, and 24 months after surgery. The Health Transition Index of the SF-36 was used to determine the 1- and 2-year minimum clinically important difference (MCID), and logistic regression modeling was performed to determine if achieving MCID at 1 year adequately predicted improvement and achievement of MCID at 24 months. RESULTS The study group included 969 patients: 300 patients underwent anterior lumbar interbody fusion (ALIF), 606 patients underwent transforaminal lumbar interbody fusion (TLIF), and 63 patients underwent lateral interbody fusion (LLIF). There was a significant correlation between the 12- and 24-month ODI (r = 0.82; p < 0.0001), SF-36 Physical Component Summary score (r = 0.89; p < 0.0001), VAS-back pain (r = 0.90; p < 0.0001), and VAS-leg pain (r = 0.85; p < 0.0001). For the ALIF cohort, patients achieving MCID thresholds for ODI at 12 months were 13-fold (p < 0

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Zhang, H. F.; Royer, G.

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

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

    PubMed

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

    2016-10-01

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

  18. Theoretical NMR and conformational analysis of solvated oximes for organophosphates-inhibited acetylcholinesterase reactivation

    NASA Astrophysics Data System (ADS)

    da Silva, Jorge Alberto Valle; Modesto-Costa, Lucas; de Koning, Martijn C.; Borges, Itamar; França, Tanos Celmar Costa

    2018-01-01

    In this work, quaternary and non-quaternary oximes designed to bind at the peripheral site of acetylcholinesterase previously inhibited by organophosphates were investigated theoretically. Some of those oximes have a large number of degrees of freedom, thus requiring an accurate method to obtain molecular geometries. For this reason, the density functional theory (DFT) was employed to refine their molecular geometries after conformational analysis and to compare their 1H and 13C nuclear magnetic resonance (NMR) theoretical signals in gas-phase and in solvent. A good agreement with experimental data was achieved and the same theoretical approach was employed to obtain the geometries in water environment for further studies.

  19. Mergers in ΛCDM: Uncertainties in Theoretical Predictions and Interpretations of the Merger Rate

    NASA Astrophysics Data System (ADS)

    Hopkins, Philip F.; Croton, Darren; Bundy, Kevin; Khochfar, Sadegh; van den Bosch, Frank; Somerville, Rachel S.; Wetzel, Andrew; Keres, Dusan; Hernquist, Lars; Stewart, Kyle; Younger, Joshua D.; Genel, Shy; Ma, Chung-Pei

    2010-12-01

    Different theoretical methodologies lead to order-of-magnitude variations in predicted galaxy-galaxy merger rates. We examine how this arises and quantify the dominant uncertainties. Modeling of dark matter and galaxy inspiral/merger times contribute factor of ~2 uncertainties. Different estimates of the halo-halo merger rate, the subhalo "destruction" rate, and the halo merger rate with some dynamical friction time delay for galaxy-galaxy mergers, agree to within this factor of ~2, provided proper care is taken to define mergers consistently. There are some caveats: if halo/subhalo masses are not appropriately defined the major-merger rate can be dramatically suppressed, and in models with "orphan" galaxies and under-resolved subhalos the merger timescale can be severely over-estimated. The dominant differences in galaxy-galaxy merger rates between models owe to the treatment of the baryonic physics. Cosmological hydrodynamic simulations without strong feedback and some older semi-analytic models (SAMs), with known discrepancies in mass functions, can be biased by large factors (~5) in predicted merger rates. However, provided that models yield a reasonable match to the total galaxy mass function, the differences in properties of central galaxies are sufficiently small to alone contribute small (factor of ~1.5) additional systematics to merger rate predictions. But variations in the baryonic physics of satellite galaxies in models can also have a dramatic effect on merger rates. The well-known problem of satellite "over-quenching" in most current SAMs—whereby SAM satellite populations are too efficiently stripped of their gas—could lead to order-of-magnitude under-estimates of merger rates for low-mass, gas-rich galaxies. Models in which the masses of satellites are fixed by observations (or SAMs adjusted to resolve this "over-quenching") tend to predict higher merger rates, but with factor of ~2 uncertainties stemming from the uncertainty in those

  20. ROCK I Has More Accurate Prognostic Value than MET in Predicting Patient Survival in Colorectal Cancer.

    PubMed

    Li, Jian; Bharadwaj, Shruthi S; Guzman, Grace; Vishnubhotla, Ramana; Glover, Sarah C

    2015-06-01

    Colorectal cancer remains the second leading cause of death in the United States despite improvements in incidence rates and advancements in screening. The present study evaluated the prognostic value of two tumor markers, MET and ROCK I, which have been noted in other cancers to provide more accurate prognoses of patient outcomes than tumor staging alone. We constructed a tissue microarray from surgical specimens of adenocarcinomas from 108 colorectal cancer patients. Using immunohistochemistry, we examined the expression levels of tumor markers MET and ROCK I, with a pathologist blinded to patient identities and clinical outcomes providing the scoring of MET and ROCK I expression. We then used retrospective analysis of patients' survival data to provide correlations with expression levels of MET and ROCK I. Both MET and ROCK I were significantly over-expressed in colorectal cancer tissues, relative to the unaffected adjacent mucosa. Kaplan-Meier survival analysis revealed that patients' 5-year survival was inversely correlated with levels of expression of ROCK I. In contrast, MET was less strongly correlated with five-year survival. ROCK I provides better efficacy in predicting patient outcomes, compared to either tumor staging or MET expression. As a result, ROCK I may provide a less invasive method of assessing patient prognoses and directing therapeutic interventions. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

  1. A composite score combining waist circumference and body mass index more accurately predicts body fat percentage in 6- to 13-year-old children.

    PubMed

    Aeberli, I; Gut-Knabenhans, M; Kusche-Ammann, R S; Molinari, L; Zimmermann, M B

    2013-02-01

    Body mass index (BMI) and waist circumference (WC) are widely used to predict % body fat (BF) and classify degrees of pediatric adiposity. However, both measures have limitations. The aim of this study was to evaluate whether a combination of WC and BMI would more accurately predict %BF than either alone. In a nationally representative sample of 2,303 6- to 13-year-old Swiss children, weight, height, and WC were measured, and %BF was determined from multiple skinfold thicknesses. Regression and receiver operating characteristic (ROC) curves were used to evaluate the combination of WC and BMI in predicting %BF against WC or BMI alone. An optimized composite score (CS) was generated. A quadratic polynomial combination of WC and BMI led to a better prediction of %BF (r (2) = 0.68) compared with the two measures alone (r (2) = 0.58-0.62). The areas under the ROC curve for the CS [0.6 * WC-SDS + 0.4 * BMI-SDS] ranged from 0.962 ± 0.0053 (overweight girls) to 0.982 ± 0.0046 (obese boys) and were somewhat greater than the AUCs for either BMI or WC alone. At a given specificity, the sensitivity of the prediction of overweight and obesity based on the CS was higher than that based on either WC or BMI alone, although the improvement was small. Both BMI and WC are good predictors of %BF in primary school children. However, a composite score incorporating both measures increased sensitivity at a constant specificity as compared to the individual measures. It may therefore be a useful tool for clinical and epidemiological studies of pediatric adiposity.

  2. Can computerized tomography accurately stage childhood renal tumors?

    PubMed

    Abdelhalim, Ahmed; Helmy, Tamer E; Harraz, Ahmed M; Abou-El-Ghar, Mohamed E; Dawaba, Mohamed E; Hafez, Ashraf T

    2014-07-01

    Staging of childhood renal tumors is crucial for treatment planning and outcome prediction. We sought to identify whether computerized tomography could accurately predict the local stage of childhood renal tumors. We retrospectively reviewed our database for patients diagnosed with childhood renal tumors and treated surgically between 1990 and 2013. Inability to retrieve preoperative computerized tomography, intraoperative tumor spillage and nonWilms childhood renal tumors were exclusion criteria. Local computerized tomography stage was assigned by a single experienced pediatric radiologist blinded to the pathological stage, using a consensus similar to the Children's Oncology Group Wilms tumor staging system. Tumors were stratified into up-front surgery and preoperative chemotherapy groups. The radiological stage of each tumor was compared to the pathological stage. A total of 189 tumors in 179 patients met inclusion criteria. Computerized tomography staging matched pathological staging in 68% of up-front surgery (70 of 103), 31.8% of pre-chemotherapy (21 of 66) and 48.8% of post-chemotherapy scans (42 of 86). Computerized tomography over staged 21.4%, 65.2% and 46.5% of tumors in the up-front surgery, pre-chemotherapy and post-chemotherapy scans, respectively, and under staged 10.7%, 3% and 4.7%. Computerized tomography staging was more accurate in tumors managed by up-front surgery (p <0.001) and those without extracapsular extension (p <0.001). The validity of computerized tomography staging of childhood renal tumors remains doubtful. This staging is more accurate for tumors treated with up-front surgery and those without extracapsular extension. Preoperative computerized tomography can help to exclude capsular breach. Treatment strategy should be based on surgical and pathological staging to avoid the hazards of inaccurate staging. Copyright © 2014 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

  3. New developments in theoretical thermochemistry and electronic structure applications in supramolecular chemistry and cluster science

    NASA Astrophysics Data System (ADS)

    Ramabhadran, Raghunath Ozhapakkam

    In a concise display of the power and diversity of electronic structure theory (EST), the work presented herein involves the development of new computational methods to advance the practical utility of quantum chemistry, as well as solving different types of challenging chemical problems by applying existing EST tools. The research presented is highly interdisciplinary in nature and features synergistic collaborations to solve real-life problems such as regulating toxic chemicals and generating alternative sources of energy. In the first chapter of this dissertation, the solution to a long-standing problem in theoretical thermochemistry is accomplished by the development of the automated, chemically intuitive and generalized thermochemical hierarchy, Connectivity-Based Hierarchy (CBH) to accurately predict the thermochemical properties of organic molecules. The extension of the hierarchy to predict the enthalpies of formations of biomonomers such as amino acids is also presented. The development of a computationally efficient protocol to accurately extrapolate to high CCSD(T) energies based on MP2 and DFT energies using CBH is presented in the second chapter, thus merging theoretical thermochemistry with fragment-based methods in quantum chemistry. This merger drastically reduces the computational cost involved in a CCSD(T) calculation, while retaining the impeccable accuracy it offers. The practical utility of the CH hydrogen bond, commonly thought as being too weak to be used in supramolecular applications has been demonstrated by DFT calculations (along with experimental results from the Flood group) in the third chapter. This is accomplished by systematically studying the binding of monoatomic chloride, diatomic and toxic cyanide and the polyatomic bi-fluoride anions for the first time using only CH hydrogen bonds within a triazolophane macrocycle. The fourth chapter contains the introduction of the concept of fluxionality in the chemical reactions of

  4. 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

  5. Accurate LC peak boundary detection for ¹⁶O/¹⁸O labeled LC-MS data.

    PubMed

    Cui, Jian; Petritis, Konstantinos; Tegeler, Tony; Petritis, Brianne; Ma, Xuepo; Jin, Yufang; Gao, Shou-Jiang S J; Zhang, Jianqiu Michelle

    2013-01-01

    In liquid chromatography-mass spectrometry (LC-MS), parts of LC peaks are often corrupted by their co-eluting peptides, which results in increased quantification variance. In this paper, we propose to apply accurate LC peak boundary detection to remove the corrupted part of LC peaks. Accurate LC peak boundary detection is achieved by checking the consistency of intensity patterns within peptide elution time ranges. In addition, we remove peptides with erroneous mass assignment through model fitness check, which compares observed intensity patterns to theoretically constructed ones. The proposed algorithm can significantly improve the accuracy and precision of peptide ratio measurements.

  6. A statistical rain attenuation prediction model with application to the advanced communication technology satellite project. 1: Theoretical development and application to yearly predictions for selected cities in the United States

    NASA Technical Reports Server (NTRS)

    Manning, Robert M.

    1986-01-01

    A rain attenuation prediction model is described for use in calculating satellite communication link availability for any specific location in the world that is characterized by an extended record of rainfall. Such a formalism is necessary for the accurate assessment of such availability predictions in the case of the small user-terminal concept of the Advanced Communication Technology Satellite (ACTS) Project. The model employs the theory of extreme value statistics to generate the necessary statistical rainrate parameters from rain data in the form compiled by the National Weather Service. These location dependent rain statistics are then applied to a rain attenuation model to obtain a yearly prediction of the occurrence of attenuation on any satellite link at that location. The predictions of this model are compared to those of the Crane Two-Component Rain Model and some empirical data and found to be very good. The model is then used to calculate rain attenuation statistics at 59 locations in the United States (including Alaska and Hawaii) for the 20 GHz downlinks and 30 GHz uplinks of the proposed ACTS system. The flexibility of this modeling formalism is such that it allows a complete and unified treatment of the temporal aspects of rain attenuation that leads to the design of an optimum stochastic power control algorithm, the purpose of which is to efficiently counter such rain fades on a satellite link.

  7. Theoretical survey on positronium formation and ionisation in positron atom scattering

    NASA Technical Reports Server (NTRS)

    Basu, Madhumita; Ghosh, A. S.

    1990-01-01

    The recent theoretical studies are surveyed and reported on the formation of exotic atoms in positron-hydrogen, positron-helium and positron-lithium scattering specially at intermediate energy region. The ionizations of these targets by positron impact was also considered. Theoretical predictions for both the processes are compared with existing measured values.

  8. Experimental and Theoretical Investigation of Sodiated Multimers of Steroid Epimers with Ion Mobility-Mass Spectrometry

    NASA Astrophysics Data System (ADS)

    Chouinard, Christopher D.; Cruzeiro, Vinícius Wilian D.; Roitberg, Adrian E.; Yost, Richard A.

    2017-02-01

    Ion mobility-mass spectrometry (IM-MS) has recently seen increased use in the analysis of small molecules, especially in the field of metabolomics, for increased breadth of information and improved separation of isomers. In this study, steroid epimers androsterone and trans-androsterone were analyzed with IM-MS to investigate differences in their relative mobilities. Although sodiated monomers exhibited very similar collision cross-sections (CCS), baseline separation was observed for the sodiated dimer species (RS = 1.81), with measured CCS of 242.6 and 256.3 Å2, respectively. Theoretical modeling was performed to determine the most energetically stable structures of solution-phase and gas-phase monomer and dimer structures. It was revealed that these epimers differ in their preferred dimer binding mode in solution phase: androsterone adopts a R=O - Na+ - OH—R' configuration, whereas trans-androsterone adopts a R=O - Na+ - O=R' configuration. This difference contributes to a significant structural variation, and subsequent CCS calculations based on these structures relaxed in the gas phase were in agreement with experimentally measured values (ΔCCS 5%). Additionally, these calculations accurately predicted the relative difference in mobility between the epimers. This study illustrates the power of combining experimental and theoretical results to better elucidate gas-phase structures.

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

    DOE PAGES

    An, Zhe; Rey, Daniel; Ye, Jingxin; ...

    2017-01-16

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

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    An, Zhe; Rey, Daniel; Ye, Jingxin

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

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

    PubMed

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

    2017-04-24

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

  12. Advanced turboprop noise prediction based on recent theoretical results

    NASA Technical Reports Server (NTRS)

    Farassat, F.; Padula, S. L.; Dunn, M. H.

    1987-01-01

    The development of a high speed propeller noise prediction code at Langley Research Center is described. The code utilizes two recent acoustic formulations in the time domain for subsonic and supersonic sources. The structure and capabilities of the code are discussed. Grid size study for accuracy and speed of execution on a computer is also presented. The code is tested against an earlier Langley code. Considerable increase in accuracy and speed of execution are observed. Some examples of noise prediction of a high speed propeller for which acoustic test data are available are given. A brisk derivation of formulations used is given in an appendix.

  13. Aluminum/hydrocarbon gel propellants: An experimental and theoretical investigation of secondary atomization and predicted rocket engine performance

    NASA Astrophysics Data System (ADS)

    Mueller, Donn Christopher

    1997-12-01

    Experimental and theoretical investigations of aluminum/hydrocarbon gel propellant secondary atomization and its potential effects on rocket engine performance were conducted. In the experimental efforts, a dilute, polydisperse, gel droplet spray was injected into the postflame region of a burner and droplet size distributions was measured as a function of position above the burner using a laser-based sizing/velocimetry technique. The sizing/velocimetry technique was developed to measure droplets in the 10-125 mum size range and avoids size-biased detection through the use of a uniformly illuminated probe volume. The technique was used to determine particle size distributions and velocities at various axial locations above the burner for JP-10, and 50 and 60 wt% aluminum gels. Droplet shell formation models were applied to aluminum/hydrocarbon gels to examine particle size and mass loading effects on the minimum droplet diameter that will permit secondary atomization. This diameter was predicted to be 38.1 and 34.7 mum for the 50 and 60 wt% gels, which is somewhat greater than the experimentally measured 30 and 25 mum diameters. In the theoretical efforts, three models were developed and an existing rocket code was exercised to gain insights into secondary atomization. The first model was designed to predict gel droplet properties and shell stresses after rigid shell formation, while the second, a one-dimensional gel spray combustion model was created to quantify the secondary atomization process. Experimental and numerical comparisons verify that secondary atomization occurs in 10-125 mum diameter particles although an exact model could not be derived. The third model, a one-dimensional gel-fueled rocket combustion chamber, was developed to evaluate secondary atomization effects on various engine performance parameters. Results show that only modest secondary atomization may be required to reduce propellant burnout distance and radiation losses. A solid propellant

  14. Theoretical study of strain-dependent optical absorption in a doped self-assembled InAs/InGaAs/GaAs/AlGaAs quantum dot

    PubMed Central

    Tankasala, Archana; Hsueh, Yuling; Charles, James; Fonseca, Jim; Povolotskyi, Michael; Kim, Jun Oh; Krishna, Sanjay; Allen, Monica S; Allen, Jeffery W; Rahman, Rajib; Klimeck, Gerhard

    2018-01-01

    A detailed theoretical study of the optical absorption in doped self-assembled quantum dots is presented. A rigorous atomistic strain model as well as a sophisticated 20-band tight-binding model are used to ensure accurate prediction of the single particle states in these devices. We also show that for doped quantum dots, many-particle configuration interaction is also critical to accurately capture the optical transitions of the system. The sophisticated models presented in this work reproduce the experimental results for both undoped and doped quantum dot systems. The effects of alloy mole fraction of the strain controlling layer and quantum dot dimensions are discussed. Increasing the mole fraction of the strain controlling layer leads to a lower energy gap and a larger absorption wavelength. Surprisingly, the absorption wavelength is highly sensitive to the changes in the diameter, but almost insensitive to the changes in dot height. This behavior is explained by a detailed sensitivity analysis of different factors affecting the optical transition energy. PMID:29719758

  15. Accurate quantum chemical calculations

    NASA Technical Reports Server (NTRS)

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

    1989-01-01

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

  16. 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.

  17. Wettability of graphitic-carbon and silicon surfaces: MD modeling and theoretical analysis

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Ramos-Alvarado, Bladimir; Kumar, Satish; Peterson, G. P.

    2015-07-28

    The wettability of graphitic carbon and silicon surfaces was numerically and theoretically investigated. A multi-response method has been developed for the analysis of conventional molecular dynamics (MD) simulations of droplets wettability. The contact angle and indicators of the quality of the computations are tracked as a function of the data sets analyzed over time. This method of analysis allows accurate calculations of the contact angle obtained from the MD simulations. Analytical models were also developed for the calculation of the work of adhesion using the mean-field theory, accounting for the interfacial entropy changes. A calibration method is proposed to providemore » better predictions of the respective contact angles under different solid-liquid interaction potentials. Estimations of the binding energy between a water monomer and graphite match those previously reported. In addition, a breakdown in the relationship between the binding energy and the contact angle was observed. The macroscopic contact angles obtained from the MD simulations were found to match those predicted by the mean-field model for graphite under different wettability conditions, as well as the contact angles of Si(100) and Si(111) surfaces. Finally, an assessment of the effect of the Lennard-Jones cutoff radius was conducted to provide guidelines for future comparisons between numerical simulations and analytical models of wettability.« less

  18. Accurate and fiducial-marker-free correction for three-dimensional chromatic shift in biological fluorescence microscopy.

    PubMed

    Matsuda, Atsushi; Schermelleh, Lothar; Hirano, Yasuhiro; Haraguchi, Tokuko; Hiraoka, Yasushi

    2018-05-15

    Correction of chromatic shift is necessary for precise registration of multicolor fluorescence images of biological specimens. New emerging technologies in fluorescence microscopy with increasing spatial resolution and penetration depth have prompted the need for more accurate methods to correct chromatic aberration. However, the amount of chromatic shift of the region of interest in biological samples often deviates from the theoretical prediction because of unknown dispersion in the biological samples. To measure and correct chromatic shift in biological samples, we developed a quadrisection phase correlation approach to computationally calculate translation, rotation, and magnification from reference images. Furthermore, to account for local chromatic shifts, images are split into smaller elements, for which the phase correlation between channels is measured individually and corrected accordingly. We implemented this method in an easy-to-use open-source software package, called Chromagnon, that is able to correct shifts with a 3D accuracy of approximately 15 nm. Applying this software, we quantified the level of uncertainty in chromatic shift correction, depending on the imaging modality used, and for different existing calibration methods, along with the proposed one. Finally, we provide guidelines to choose the optimal chromatic shift registration method for any given situation.

  19. Substituent effects on the relaxation dynamics of furan, furfural and β-furfural: a combined theoretical and experimental approach.

    PubMed

    Oesterling, Sven; Schalk, Oliver; Geng, Ting; Thomas, Richard D; Hansson, Tony; de Vivie-Riedle, Regina

    2017-01-18

    For the series furan, furfural and β-furfural we investigated the effect of substituents and their positioning on the photoinduced relaxation dynamics in a combined theoretical and experimental approach. Using time resolved photoelectron spectroscopy with a high intensity probe pulse, we can, for the first time, follow the whole deactivation process of furan through a two photon probe signal. Using the extended 2-electron 2-orbital model [Nenov et al., J. Chem. Phys., 2011, 135, 034304] we explain the formation of one central conical intersection and predict the influence of the aldehyde group of the derivatives on its geometry. This, as well as the relaxation mechanisms from photoexcitation to the final outcome was investigated using a variety of theoretical methods. Complete active space self consistent field was used for on-the-fly calculations while complete active space perturbation theory and coupled cluster theory were used to accurately describe critical configurations. Experiment and theory show the relaxation dynamics of furfural and β-furfural to be slowed down, and together they disclose an additional deactivation pathway, which is attributed to the n O lonepair state introduced with the aldehyde group.

  20. Parsimonious description for predicting high-dimensional dynamics

    PubMed Central

    Hirata, Yoshito; Takeuchi, Tomoya; Horai, Shunsuke; Suzuki, Hideyuki; Aihara, Kazuyuki

    2015-01-01

    When we observe a system, we often cannot observe all its variables and may have some of its limited measurements. Under such a circumstance, delay coordinates, vectors made of successive measurements, are useful to reconstruct the states of the whole system. Although the method of delay coordinates is theoretically supported for high-dimensional dynamical systems, practically there is a limitation because the calculation for higher-dimensional delay coordinates becomes more expensive. Here, we propose a parsimonious description of virtually infinite-dimensional delay coordinates by evaluating their distances with exponentially decaying weights. This description enables us to predict the future values of the measurements faster because we can reuse the calculated distances, and more accurately because the description naturally reduces the bias of the classical delay coordinates toward the stable directions. We demonstrate the proposed method with toy models of the atmosphere and real datasets related to renewable energy. PMID:26510518

  1. Accurate Bit Error Rate Calculation for Asynchronous Chaos-Based DS-CDMA over Multipath Channel

    NASA Astrophysics Data System (ADS)

    Kaddoum, Georges; Roviras, Daniel; Chargé, Pascal; Fournier-Prunaret, Daniele

    2009-12-01

    An accurate approach to compute the bit error rate expression for multiuser chaosbased DS-CDMA system is presented in this paper. For more realistic communication system a slow fading multipath channel is considered. A simple RAKE receiver structure is considered. Based on the bit energy distribution, this approach compared to others computation methods existing in literature gives accurate results with low computation charge. Perfect estimation of the channel coefficients with the associated delays and chaos synchronization is assumed. The bit error rate is derived in terms of the bit energy distribution, the number of paths, the noise variance, and the number of users. Results are illustrated by theoretical calculations and numerical simulations which point out the accuracy of our approach.

  2. Theoretical kinetics of O + C 2H 4

    DOE PAGES

    Li, Xiaohu; Jasper, Ahren W.; Zádor, Judit; ...

    2016-06-01

    The reaction of atomic oxygen with ethylene is a fundamental oxidation step in combustion and is prototypical of reactions in which oxygen adds to double bonds. For 3O+C 2H 4 and for this class of reactions generally, decomposition of the initial adduct via spin-allowed reaction channels on the triplet surface competes with intersystem crossing (ISC) and a set of spin-forbidden reaction channels on the ground-state singlet surface. The two surfaces share some bimolecular products but feature different intermediates, pathways, and transition states. In addition, the overall product branching is therefore a sensitive function of the ISC rate. The 3O+C 2Hmore » 4 reaction has been extensively studied, but previous experimental work has not provided detailed branching information at elevated temperatures, while previous theoretical studies have employed empirical treatments of ISC. Here we predict the kinetics of 3O+C 2H 4 using an ab initio transition state theory based master equation (AITSTME) approach that includes an a priori description of ISC. Specifically, the ISC rate is calculated using Landau–Zener statistical theory, consideration of the four lowest-energy electronic states, and a direct classical trajectory study of the product branching immediately after ISC. The present theoretical results are largely in good agreement with existing low-temperature experimental kinetics and molecular beam studies. Good agreement is also found with past theoretical work, with the notable exception of the predicted product branching at elevated temperatures. Above ~1000 K, we predict CH 2CHO+H and CH 2+CH 2O as the major products, which differs from the room temperature preference for CH 3+HCO (which is assumed to remain at higher temperatures in some models) and from the prediction of a previous detailed master equation study.« less

  3. Traditional and non-traditional approaches to the prediction of natural disasters

    NASA Astrophysics Data System (ADS)

    Sapunov, Valentin; Glazyrina, Tatiana

    2016-04-01

    Since the beginning of the 21st century the number of disasters in the world increased approximately two times. Damage from disasters cost an average of 230 billion dollars per year. Recently, the death toll in the disaster has reached 230,000 - 1 000,000 per year. Along with earthquakes, tsunamis, floods, increased the number of forest and steppe fires. These processes are not fully known global, geophysical and space reasons. Of great importance are perennial not until the end of the study of natural cycles. There is evidence that the state of the planet's surface affect processes in the Earth's core. Understanding the causes and prediction of the tragic events require an integrated effort based on the synthesis of various sciences as well as history which has knowledge about the disasters of the past. Factor that reduces the risk is constant monitoring, including both distant and contact methods. However, its possibility is limited. Firstly, due to the high cost of global, especially space monitoring. Secondly, due to the unpredictability of some processes. In December 2004, the countries of Southeast Asia hit by the tsunami. The death gotten 250 000 people. Animals in this cataclysm appeared to stay safety and advance left the danger zone. Animals are able to predict hazards having no materials predecessors. Participants nuclear tests show - a day before the explosion of the animals escape dangerous zone. This means that animals have the ability to predict the catastrophic events. The most important abiotic factor, the physical nature of which is still not clear is time. One of the scientists, who achieved some success in the study of time, was N.Kozyrev (1908-1983). He devoted his life to the study of the phenomenon of time and attempt to systematize the knowledge of him as a physical substance. Kozyrev in his theoretical calculations and experiments found the new field - the field of time (chrono-information). Through it can instantly and accurately transmit

  4. Accurate simulations of helium pick-up experiments using a rejection-free Monte Carlo method

    NASA Astrophysics Data System (ADS)

    Dutra, Matthew; Hinde, Robert

    2018-04-01

    In this paper, we present Monte Carlo simulations of helium droplet pick-up experiments with the intention of developing a robust and accurate theoretical approach for interpreting experimental helium droplet calorimetry data. Our approach is capable of capturing the evaporative behavior of helium droplets following dopant acquisition, allowing for a more realistic description of the pick-up process. Furthermore, we circumvent the traditional assumption of bulk helium behavior by utilizing density functional calculations of the size-dependent helium droplet chemical potential. The results of this new Monte Carlo technique are compared to commonly used Poisson pick-up statistics for simulations that reflect a broad range of experimental parameters. We conclude by offering an assessment of both of these theoretical approaches in the context of our observed results.

  5. TAD- THEORETICAL AERODYNAMICS PROGRAM

    NASA Technical Reports Server (NTRS)

    Barrowman, J.

    1994-01-01

    This theoretical aerodynamics program, TAD, was developed to predict the aerodynamic characteristics of vehicles with sounding rocket configurations. These slender, axisymmetric finned vehicle configurations have a wide range of aeronautical applications from rockets to high speed armament. Over a given range of Mach numbers, TAD will compute the normal force coefficient derivative, the center-of-pressure, the roll forcing moment coefficient derivative, the roll damping moment coefficient derivative, and the pitch damping moment coefficient derivative of a sounding rocket configured vehicle. The vehicle may consist of a sharp pointed nose of cone or tangent ogive shape, up to nine other body divisions of conical shoulder, conical boattail, or circular cylinder shape, and fins of trapezoid planform shape with constant cross section and either three or four fins per fin set. The characteristics computed by TAD have been shown to be accurate to within ten percent of experimental data in the supersonic region. The TAD program calculates the characteristics of separate portions of the vehicle, calculates the interference between separate portions of the vehicle, and then combines the results to form a total vehicle solution. Also, TAD can be used to calculate the characteristics of the body or fins separately as an aid in the design process. Input to the TAD program consists of simple descriptions of the body and fin geometries and the Mach range of interest. Output includes the aerodynamic characteristics of the total vehicle, or user-selected portions, at specified points over the mach range. The TAD program is written in FORTRAN IV for batch execution and has been implemented on an IBM 360 computer with a central memory requirement of approximately 123K of 8 bit bytes. The TAD program was originally developed in 1967 and last updated in 1972.

  6. 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

  7. 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.

  8. A hybrid method for accurate star tracking using star sensor and gyros.

    PubMed

    Lu, Jiazhen; Yang, Lie; Zhang, Hao

    2017-10-01

    Star tracking is the primary operating mode of star sensors. To improve tracking accuracy and efficiency, a hybrid method using a star sensor and gyroscopes is proposed in this study. In this method, the dynamic conditions of an aircraft are determined first by the estimated angular acceleration. Under low dynamic conditions, the star sensor is used to measure the star vector and the vector difference method is adopted to estimate the current angular velocity. Under high dynamic conditions, the angular velocity is obtained by the calibrated gyros. The star position is predicted based on the estimated angular velocity and calibrated gyros using the star vector measurements. The results of the semi-physical experiment show that this hybrid method is accurate and feasible. In contrast with the star vector difference and gyro-assisted methods, the star position prediction result of the hybrid method is verified to be more accurate in two different cases under the given random noise of the star centroid.

  9. Computer-based personality judgments are more accurate than those made by humans.

    PubMed

    Youyou, Wu; Kosinski, Michal; Stillwell, David

    2015-01-27

    Judging others' personalities is an essential skill in successful social living, as personality is a key driver behind people's interactions, behaviors, and emotions. Although accurate personality judgments stem from social-cognitive skills, developments in machine learning show that computer models can also make valid judgments. This study compares the accuracy of human and computer-based personality judgments, using a sample of 86,220 volunteers who completed a 100-item personality questionnaire. We show that (i) computer predictions based on a generic digital footprint (Facebook Likes) are more accurate (r = 0.56) than those made by the participants' Facebook friends using a personality questionnaire (r = 0.49); (ii) computer models show higher interjudge agreement; and (iii) computer personality judgments have higher external validity when predicting life outcomes such as substance use, political attitudes, and physical health; for some outcomes, they even outperform the self-rated personality scores. Computers outpacing humans in personality judgment presents significant opportunities and challenges in the areas of psychological assessment, marketing, and privacy.

  10. Neural and hybrid modeling: an alternative route to efficiently predict the behavior of biotechnological processes aimed at biofuels obtainment.

    PubMed

    Curcio, Stefano; Saraceno, Alessandra; Calabrò, Vincenza; Iorio, Gabriele

    2014-01-01

    The present paper was aimed at showing that advanced modeling techniques, based either on artificial neural networks or on hybrid systems, might efficiently predict the behavior of two biotechnological processes designed for the obtainment of second-generation biofuels from waste biomasses. In particular, the enzymatic transesterification of waste-oil glycerides, the key step for the obtainment of biodiesel, and the anaerobic digestion of agroindustry wastes to produce biogas were modeled. It was proved that the proposed modeling approaches provided very accurate predictions of systems behavior. Both neural network and hybrid modeling definitely represented a valid alternative to traditional theoretical models, especially when comprehensive knowledge of the metabolic pathways, of the true kinetic mechanisms, and of the transport phenomena involved in biotechnological processes was difficult to be achieved.

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

    NASA Technical Reports Server (NTRS)

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

    1975-01-01

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

  12. Motor system contribution to action prediction: Temporal accuracy depends on motor experience.

    PubMed

    Stapel, Janny C; Hunnius, Sabine; Meyer, Marlene; Bekkering, Harold

    2016-03-01

    Predicting others' actions is essential for well-coordinated social interactions. In two experiments including an infant population, this study addresses to what extent motor experience of an observer determines prediction accuracy for others' actions. Results show that infants who were proficient crawlers but inexperienced walkers predicted crawling more accurately than walking, whereas age groups mastering both skills (i.e. toddlers and adults) were equally accurate in predicting walking and crawling. Regardless of experience, human movements were predicted more accurately by all age groups than non-human movement control stimuli. This suggests that for predictions to be accurate, the observed act needs to be established in the motor repertoire of the observer. Through the acquisition of new motor skills, we also become better at predicting others' actions. The findings thus stress the relevance of motor experience for social-cognitive development. Copyright © 2015 Elsevier B.V. All rights reserved.

  13. Towards accurate ab initio predictions of the vibrational spectrum of methane

    NASA Technical Reports Server (NTRS)

    Schwenke, David W.

    2002-01-01

    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.

  14. Fraction of organic carbon predicts labile desorption rates of chlorinated organic pollutants in laboratory-spiked geosorbents.

    PubMed

    Ginsbach, Jake W; Killops, Kato L; Olsen, Robert M; Peterson, Brittney; Dunnivant, Frank M

    2010-05-01

    The resuspension of large volumes of sediments that are contaminated with chlorinated pollutants continues to threaten environmental quality and human health. Whereas kinetic models are more accurate for estimating the environmental impact of these events, their widespread use is substantially hampered by the need for costly, time-consuming, site-specific kinetics experiments. The present study investigated the development of a predictive model for desorption rates from easily measurable sorbent and pollutant properties by examining the relationship between the fraction of organic carbon (fOC) and labile release rates. Duplicate desorption measurements were performed on 46 unique combinations of pollutants and sorbents with fOC values ranging from 0.001 to 0.150. Labile desorption rate constants indicate that release rates predominantly depend upon the fOC in the geosorbent. Previous theoretical models, such as the macro-mesopore and organic matter (MOM) diffusion model, have predicted such a relationship but could not accurately predict the experimental rate constants collected in the present study. An empirical model was successfully developed to correlate the labile desorption rate constant (krap) to the fraction of organic material where log(krap)=0.291-0.785 . log(fOC). These results provide the first experimental evidence that kinetic pollution releases during resuspension events are governed by the fOC content in natural geosorbents. Copyright (c) 2010 SETAC.

  15. Inverse and Predictive Modeling

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Syracuse, Ellen Marie

    The LANL Seismo-Acoustic team has a strong capability in developing data-driven models that accurately predict a variety of observations. These models range from the simple – one-dimensional models that are constrained by a single dataset and can be used for quick and efficient predictions – to the complex – multidimensional models that are constrained by several types of data and result in more accurate predictions. Team members typically build models of geophysical characteristics of Earth and source distributions at scales of 1 to 1000s of km, the techniques used are applicable for other types of physical characteristics at an evenmore » greater range of scales. The following cases provide a snapshot of some of the modeling work done by the Seismo- Acoustic team at LANL.« less

  16. 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

  17. Exploring the knowledge behind predictions in everyday cognition: an iterated learning study.

    PubMed

    Stephens, Rachel G; Dunn, John C; Rao, Li-Lin; Li, Shu

    2015-10-01

    Making accurate predictions about events is an important but difficult task. Recent work suggests that people are adept at this task, making predictions that reflect surprisingly accurate knowledge of the distributions of real quantities. Across three experiments, we used an iterated learning procedure to explore the basis of this knowledge: to what extent is domain experience critical to accurate predictions and how accurate are people when faced with unfamiliar domains? In Experiment 1, two groups of participants, one resident in Australia, the other in China, predicted the values of quantities familiar to both (movie run-times), unfamiliar to both (the lengths of Pharaoh reigns), and familiar to one but unfamiliar to the other (cake baking durations and the lengths of Beijing bus routes). While predictions from both groups were reasonably accurate overall, predictions were inaccurate in the selectively unfamiliar domains and, surprisingly, predictions by the China-resident group were also inaccurate for a highly familiar domain: local bus route lengths. Focusing on bus routes, two follow-up experiments with Australia-resident groups clarified the knowledge and strategies that people draw upon, plus important determinants of accurate predictions. For unfamiliar domains, people appear to rely on extrapolating from (not simply directly applying) related knowledge. However, we show that people's predictions are subject to two sources of error: in the estimation of quantities in a familiar domain and extension to plausible values in an unfamiliar domain. We propose that the key to successful predictions is not simply domain experience itself, but explicit experience of relevant quantities.

  18. Theoretical Dipole Moment for the X211 State of NO

    NASA Technical Reports Server (NTRS)

    Langhoff, Stephen R.; Bauschlicher, Charles W., Jr.; Partridge, Harry; Arnold, James O. (Technical Monitor)

    1994-01-01

    The dipole moment function for the X(sup 2)II state of NO is studied as a function of the completeness in both the one- and n-particle spaces. Einstein coefficients are presented that are significantly more accurate than previous tabulations for the higher vibrational levels. The theoretical values give considerable insight into the limitations of recently published ratios of Einstein coefficients measured by spectrally resolved infrared chemiluminescence.

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  20. Review of Nearshore Morphologic Prediction

    NASA Astrophysics Data System (ADS)

    Plant, N. G.; Dalyander, S.; Long, J.

    2014-12-01

    The evolution of the world's erodible coastlines will determine the balance between the benefits and costs associated with human and ecological utilization of shores, beaches, dunes, barrier islands, wetlands, and estuaries. So, we would like to predict coastal evolution to guide management and planning of human and ecological response to coastal changes. After decades of research investment in data collection, theoretical and statistical analysis, and model development we have a number of empirical, statistical, and deterministic models that can predict the evolution of the shoreline, beaches, dunes, and wetlands over time scales of hours to decades, and even predict the evolution of geologic strata over the course of millennia. Comparisons of predictions to data have demonstrated that these models can have meaningful predictive skill. But these comparisons also highlight the deficiencies in fundamental understanding, formulations, or data that are responsible for prediction errors and uncertainty. Here, we review a subset of predictive models of the nearshore to illustrate tradeoffs in complexity, predictive skill, and sensitivity to input data and parameterization errors. We identify where future improvement in prediction skill will result from improved theoretical understanding, and data collection, and model-data assimilation.

  1. Predicting beta-turns and their types using predicted backbone dihedral angles and secondary structures.

    PubMed

    Kountouris, Petros; Hirst, Jonathan D

    2010-07-31

    Beta-turns are secondary structure elements usually classified as coil. Their prediction is important, because of their role in protein folding and their frequent occurrence in protein chains. We have developed a novel method that predicts beta-turns and their types using information from multiple sequence alignments, predicted secondary structures and, for the first time, predicted dihedral angles. Our method uses support vector machines, a supervised classification technique, and is trained and tested on three established datasets of 426, 547 and 823 protein chains. We achieve a Matthews correlation coefficient of up to 0.49, when predicting the location of beta-turns, the highest reported value to date. Moreover, the additional dihedral information improves the prediction of beta-turn types I, II, IV, VIII and "non-specific", achieving correlation coefficients up to 0.39, 0.33, 0.27, 0.14 and 0.38, respectively. Our results are more accurate than other methods. We have created an accurate predictor of beta-turns and their types. Our method, called DEBT, is available online at http://comp.chem.nottingham.ac.uk/debt/.

  2. Theoretical prediction of welding distortion in large and complex structures

    NASA Astrophysics Data System (ADS)

    Deng, De-An

    2010-06-01

    Welding technology is widely used to assemble large thin plate structures such as ships, automobiles, and passenger trains because of its high productivity. However, it is impossible to avoid welding-induced distortion during the assembly process. Welding distortion not only reduces the fabrication accuracy of a weldment, but also decreases the productivity due to correction work. If welding distortion can be predicted using a practical method beforehand, the prediction will be useful for taking appropriate measures to control the dimensional accuracy to an acceptable limit. In this study, a two-step computational approach, which is a combination of a thermoelastic-plastic finite element method (FEM) and an elastic finite element with consideration for large deformation, is developed to estimate welding distortion for large and complex welded structures. Welding distortions in several representative large complex structures, which are often used in shipbuilding, are simulated using the proposed method. By comparing the predictions and the measurements, the effectiveness of the two-step computational approach is verified.

  3. Rapid and Accurate Evaluation of the Quality of Commercial Organic Fertilizers Using Near Infrared Spectroscopy

    PubMed Central

    Wang, Chang; Huang, Chichao; Qian, Jian; Xiao, Jian; Li, Huan; Wen, Yongli; He, Xinhua; Ran, Wei; Shen, Qirong; Yu, Guanghui

    2014-01-01

    The composting industry has been growing rapidly in China because of a boom in the animal industry. Therefore, a rapid and accurate assessment of the quality of commercial organic fertilizers is of the utmost importance. In this study, a novel technique that combines near infrared (NIR) spectroscopy with partial least squares (PLS) analysis is developed for rapidly and accurately assessing commercial organic fertilizers quality. A total of 104 commercial organic fertilizers were collected from full-scale compost factories in Jiangsu Province, east China. In general, the NIR-PLS technique showed accurate predictions of the total organic matter, water soluble organic nitrogen, pH, and germination index; less accurate results of the moisture, total nitrogen, and electrical conductivity; and the least accurate results for water soluble organic carbon. Our results suggested the combined NIR-PLS technique could be applied as a valuable tool to rapidly and accurately assess the quality of commercial organic fertilizers. PMID:24586313

  4. Rapid and accurate evaluation of the quality of commercial organic fertilizers using near infrared spectroscopy.

    PubMed

    Wang, Chang; Huang, Chichao; Qian, Jian; Xiao, Jian; Li, Huan; Wen, Yongli; He, Xinhua; Ran, Wei; Shen, Qirong; Yu, Guanghui

    2014-01-01

    The composting industry has been growing rapidly in China because of a boom in the animal industry. Therefore, a rapid and accurate assessment of the quality of commercial organic fertilizers is of the utmost importance. In this study, a novel technique that combines near infrared (NIR) spectroscopy with partial least squares (PLS) analysis is developed for rapidly and accurately assessing commercial organic fertilizers quality. A total of 104 commercial organic fertilizers were collected from full-scale compost factories in Jiangsu Province, east China. In general, the NIR-PLS technique showed accurate predictions of the total organic matter, water soluble organic nitrogen, pH, and germination index; less accurate results of the moisture, total nitrogen, and electrical conductivity; and the least accurate results for water soluble organic carbon. Our results suggested the combined NIR-PLS technique could be applied as a valuable tool to rapidly and accurately assess the quality of commercial organic fertilizers.

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Park, Min-Sun; Park, Sung Yong; Miller, Keith R.

    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 conformationalmore » 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.« less

  6. Theoretical models of helicopter rotor noise

    NASA Technical Reports Server (NTRS)

    Hawkings, D. L.

    1978-01-01

    For low speed rotors, it is shown that unsteady load models are only partially successful in predicting experimental levels. A theoretical model is presented which leads to the concept of unsteady thickness noise. This gives better agreement with test results. For high speed rotors, it is argued that present models are incomplete and that other mechanisms are at work. Some possibilities are briefly discussed.

  7. 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

  8. 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.

  9. Theoretical hot methane line lists up to T = 2000 K for astrophysical applications

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Rey, M.; Tyuterev, Vl. G.; Nikitin, A. V., E-mail: michael.rey@univ-reims.fr

    2014-07-01

    The paper describes the construction of complete sets of hot methane lines based on accurate ab initio potential and dipole moment surfaces and extensive first-principle calculations. Four line lists spanning the [0-5000] cm{sup –1} infrared region were built at T = 500, 1000, 1500, and 2000 K. For each of these four temperatures, we have constructed two versions of line lists: a version for high-resolution applications containing strong and medium lines and a full version appropriate for low-resolution opacity calculations. A comparison with available empirical databases is discussed in detail for both cold and hot bands giving a very goodmore » agreement for line positions, typically <0.1-0.5 cm{sup –1} and ∼5% for intensities of strong lines. Together with numerical tests using various basis sets, this confirms the computational convergence of our results for the most important lines, which is the major issue for theoretical spectra predictions. We showed that transitions with lower state energies up to 14,000 cm{sup –1} could give significant contributions to the methane opacity and have to be systematically taken into account. Our list at 2000 K calculated up to J = 50 contains 11.5 billion transitions for I > 10{sup –29} cm mol{sup –1}. These new lists are expected to be quantitatively accurate with respect to the precision of available and currently planned observations of astrophysical objects with improved spectral resolution.« less

  10. Predicting fiber refractive index from a measured preform index profile

    NASA Astrophysics Data System (ADS)

    Kiiveri, P.; Koponen, J.; Harra, J.; Novotny, S.; Husu, H.; Ihalainen, H.; Kokki, T.; Aallos, V.; Kimmelma, O.; Paul, J.

    2018-02-01

    When producing fiber lasers and amplifiers, silica glass compositions consisting of three to six different materials are needed. Due to the varying needs of different applications, substantial number of different glass compositions are used in the active fiber structures. Often it is not possible to find material parameters for theoretical models to estimate thermal and mechanical properties of those glass compositions. This makes it challenging to predict accurately fiber core refractive index values, even if the preform index profile is measured. Usually the desired fiber refractive index value is achieved experimentally, which is expensive. To overcome this problem, we analyzed statistically the changes between the measured preform and fiber index values. We searched for correlations that would help to predict the Δn-value change from preform to fiber in a situation where we don't know the values of the glass material parameters that define the change. Our index change models were built using the data collected from preforms and fibers made by the Direct Nanoparticle Deposition (DND) technology.

  11. Accurate Cross Sections for Microanalysis.

    PubMed

    Rez, Peter

    2002-01-01

    To calculate the intensity of x-ray emission in electron beam microanalysis requires a knowledge of the energy distribution of the electrons in the solid, the energy variation of the ionization cross section of the relevant subshell, the fraction of ionizations events producing x rays of interest and the absorption coefficient of the x rays on the path to the detector. The theoretical predictions and experimental data available for ionization cross sections are limited mainly to K shells of a few elements. Results of systematic plane wave Born approximation calculations with exchange for K, L, and M shell ionization cross sections over the range of electron energies used in microanalysis are presented. Comparisons are made with experimental measurement for selected K shells and it is shown that the plane wave theory is not appropriate for overvoltages less than 2.5 V.

  12. Experimental and theoretical characterization of the voltage distribution generated by deep brain stimulation.

    PubMed

    Miocinovic, Svjetlana; Lempka, Scott F; Russo, Gary S; Maks, Christopher B; Butson, Christopher R; Sakaie, Ken E; Vitek, Jerrold L; McIntyre, Cameron C

    2009-03-01

    Deep brain stimulation (DBS) is an established therapy for the treatment of Parkinson's disease and shows great promise for numerous other disorders. While the fundamental purpose of DBS is to modulate neural activity with electric fields, little is known about the actual voltage distribution generated in the brain by DBS electrodes and as a result it is difficult to accurately predict which brain areas are directly affected by the stimulation. The goal of this study was to characterize the spatial and temporal characteristics of the voltage distribution generated by DBS electrodes. We experimentally recorded voltages around active DBS electrodes in either a saline bath or implanted in the brain of a non-human primate. Recordings were made during voltage-controlled and current-controlled stimulation. The experimental findings were compared to volume conductor electric field models of DBS parameterized to match the different experiments. Three factors directly affected the experimental and theoretical voltage measurements: 1) DBS electrode impedance, primarily dictated by a voltage drop at the electrode-electrolyte interface and the conductivity of the tissue medium, 2) capacitive modulation of the stimulus waveform, and 3) inhomogeneity and anisotropy of the tissue medium. While the voltage distribution does not directly predict the neural response to DBS, the results of this study do provide foundational building blocks for understanding the electrical parameters of DBS and characterizing its effects on the nervous system.

  13. Internal performance predictions for Langley scramjet engine module

    NASA Technical Reports Server (NTRS)

    Pinckney, S. Z.

    1978-01-01

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

  14. Theoretical relationship between elastic wave velocity and electrical resistivity

    NASA Astrophysics Data System (ADS)

    Lee, Jong-Sub; Yoon, Hyung-Koo

    2015-05-01

    Elastic wave velocity and electrical resistivity have been commonly applied to estimate stratum structures and obtain subsurface soil design parameters. Both elastic wave velocity and electrical resistivity are related to the void ratio; the objective of this study is therefore to suggest a theoretical relationship between the two physical parameters. Gassmann theory and Archie's equation are applied to propose a new theoretical equation, which relates the compressional wave velocity to shear wave velocity and electrical resistivity. The piezo disk element (PDE) and bender element (BE) are used to measure the compressional and shear wave velocities, respectively. In addition, the electrical resistivity is obtained by using the electrical resistivity probe (ERP). The elastic wave velocity and electrical resistivity are recorded in several types of soils including sand, silty sand, silty clay, silt, and clay-sand mixture. The appropriate input parameters are determined based on the error norm in order to increase the reliability of the proposed relationship. The predicted compressional wave velocities from the shear wave velocity and electrical resistivity are similar to the measured compressional velocities. This study demonstrates that the new theoretical relationship may be effectively used to predict the unknown geophysical property from the measured values.

  15. Optimal prediction of the number of unseen species

    PubMed Central

    Orlitsky, Alon; Suresh, Ananda Theertha; Wu, Yihong

    2016-01-01

    Estimating the number of unseen species is an important problem in many scientific endeavors. Its most popular formulation, introduced by Fisher et al. [Fisher RA, Corbet AS, Williams CB (1943) J Animal Ecol 12(1):42−58], uses n samples to predict the number U of hitherto unseen species that would be observed if t⋅n new samples were collected. Of considerable interest is the largest ratio t between the number of new and existing samples for which U can be accurately predicted. In seminal works, Good and Toulmin [Good I, Toulmin G (1956) Biometrika 43(102):45−63] constructed an intriguing estimator that predicts U for all t≤1. Subsequently, Efron and Thisted [Efron B, Thisted R (1976) Biometrika 63(3):435−447] proposed a modification that empirically predicts U even for some t>1, but without provable guarantees. We derive a class of estimators that provably predict U all of the way up to t∝log⁡n. We also show that this range is the best possible and that the estimator’s mean-square error is near optimal for any t. Our approach yields a provable guarantee for the Efron−Thisted estimator and, in addition, a variant with stronger theoretical and experimental performance than existing methodologies on a variety of synthetic and real datasets. The estimators are simple, linear, computationally efficient, and scalable to massive datasets. Their performance guarantees hold uniformly for all distributions, and apply to all four standard sampling models commonly used across various scientific disciplines: multinomial, Poisson, hypergeometric, and Bernoulli product. PMID:27830649

  16. Optimal prediction of the number of unseen species.

    PubMed

    Orlitsky, Alon; Suresh, Ananda Theertha; Wu, Yihong

    2016-11-22

    Estimating the number of unseen species is an important problem in many scientific endeavors. Its most popular formulation, introduced by Fisher et al. [Fisher RA, Corbet AS, Williams CB (1943) J Animal Ecol 12(1):42-58], uses n samples to predict the number U of hitherto unseen species that would be observed if [Formula: see text] new samples were collected. Of considerable interest is the largest ratio t between the number of new and existing samples for which U can be accurately predicted. In seminal works, Good and Toulmin [Good I, Toulmin G (1956) Biometrika 43(102):45-63] constructed an intriguing estimator that predicts U for all [Formula: see text] Subsequently, Efron and Thisted [Efron B, Thisted R (1976) Biometrika 63(3):435-447] proposed a modification that empirically predicts U even for some [Formula: see text], but without provable guarantees. We derive a class of estimators that provably predict U all of the way up to [Formula: see text] We also show that this range is the best possible and that the estimator's mean-square error is near optimal for any t Our approach yields a provable guarantee for the Efron-Thisted estimator and, in addition, a variant with stronger theoretical and experimental performance than existing methodologies on a variety of synthetic and real datasets. The estimators are simple, linear, computationally efficient, and scalable to massive datasets. Their performance guarantees hold uniformly for all distributions, and apply to all four standard sampling models commonly used across various scientific disciplines: multinomial, Poisson, hypergeometric, and Bernoulli product.

  17. Comparison of two computer programs by predicting turbulent mixing of helium in a ducted supersonic airstream

    NASA Technical Reports Server (NTRS)

    Pan, Y. S.; Drummond, J. P.; Mcclinton, C. R.

    1978-01-01

    Two parabolic flow computer programs, SHIP (a finite-difference program) and COMOC (a finite-element program), are used for predicting three-dimensional turbulent reacting flow fields in supersonic combustors. The theoretical foundation of the two computer programs are described, and then the programs are applied to a three-dimensional turbulent mixing experiment. The cold (nonreacting) flow experiment was performed to study the mixing of helium jets with a supersonic airstream in a rectangular duct. Surveys of the flow field at an upstream were used as the initial data by programs; surveys at a downstream station provided comparison to assess program accuracy. Both computer programs predicted the experimental results and data trends reasonably well. However, the comparison between the computations from the two programs indicated that SHIP was more accurate in computation and more efficient in both computer storage and computing time than COMOC.

  18. Intrasubject Predictions of Vocational Preference: Convergent Validation via the Decision Theoretic Paradigm.

    ERIC Educational Resources Information Center

    Monahan, Carlyn J.; Muchinsky, Paul M.

    1985-01-01

    The degree of convergent validity among four methods of identifying vocational preferences is assessed via the decision theoretic paradigm. Vocational preferences identified by Holland's Vocational Preference Inventory (VPI), a rating procedure, and ranking were compared with preferences identified from a policy-capturing model developed from an…

  19. PconsD: ultra rapid, accurate model quality assessment for protein structure prediction.

    PubMed

    Skwark, Marcin J; Elofsson, Arne

    2013-07-15

    Clustering methods are often needed for accurately assessing the quality of modeled protein structures. Recent blind evaluation of quality assessment methods in CASP10 showed that there is little difference between many different methods as far as ranking models and selecting best model are concerned. When comparing many models, the computational cost of the model comparison can become significant. Here, we present PconsD, a fast, stream-computing method for distance-driven model quality assessment that runs on consumer hardware. PconsD is at least one order of magnitude faster than other methods of comparable accuracy. The source code for PconsD is freely available at http://d.pcons.net/. Supplementary benchmarking data are also available there. arne@bioinfo.se Supplementary data are available at Bioinformatics online.

  20. Large arterial occlusive strokes as a medical emergency: need to accurately predict clot location.

    PubMed

    Vanacker, Peter; Faouzi, Mohamed; Eskandari, Ashraf; Maeder, Philippe; Meuli, Reto; Michel, Patrik

    2017-10-01

    Endovascular treatment for acute ischemic stroke with a large intracranial occlusion was recently shown to be effective. Timely knowledge of the presence, site, and extent of arterial occlusions in the ischemic territory has the potential to influence patient selection for endovascular treatment. We aimed to find predictors of large vessel occlusive strokes, on the basis of available demographic, clinical, radiological, and laboratory data in the emergency setting. Patients enrolled in ASTRAL registry with acute ischemic stroke and computed tomography (CT)-angiography within 12 h of stroke onset were selected and categorized according to occlusion site. Easily accessible variables were used in a multivariate analysis. Of 1645 patients enrolled, a significant proportion (46.2%) had a large vessel occlusion in the ischemic territory. The main clinical predictors of any arterial occlusion were in-hospital stroke [odd ratios (OR) 2.1, 95% confidence interval 1.4-3.1], higher initial National Institute of Health Stroke Scale (OR 1.1, 1.1-1.2), presence of visual field defects (OR 1.9, 1.3-2.6), dysarthria (OR 1.4, 1.0-1.9), or hemineglect (OR 2.0, 1.4-2.8) at admission and atrial fibrillation (OR 1.7, 1.2-2.3). Further, the following radiological predictors were identified: time-to-imaging (OR 0.9, 0.9-1.0), early ischemic changes (OR 2.3, 1.7-3.2), and silent lesions on CT (OR 0.7, 0.5-1.0). The area under curve for this analysis was 0.85. Looking at different occlusion sites, National Institute of Health Stroke Scale and early ischemic changes on CT were independent predictors in all subgroups. Neurological deficits, stroke risk factors, and CT findings accurately identify acute ischemic stroke patients at risk of symptomatic vessel occlusion. Predicting the presence of these occlusions may impact emergency stroke care in regions with limited access to noninvasive vascular imaging.

  1. Remaining dischargeable time prediction for lithium-ion batteries using unscented Kalman filter

    NASA Astrophysics Data System (ADS)

    Dong, Guangzhong; Wei, Jingwen; Chen, Zonghai; Sun, Han; Yu, Xiaowei

    2017-10-01

    To overcome the range anxiety, one of the important strategies is to accurately predict the range or dischargeable time of the battery system. To accurately predict the remaining dischargeable time (RDT) of a battery, a RDT prediction framework based on accurate battery modeling and state estimation is presented in this paper. Firstly, a simplified linearized equivalent-circuit-model is developed to simulate the dynamic characteristics of a battery. Then, an online recursive least-square-algorithm method and unscented-Kalman-filter are employed to estimate the system matrices and SOC at every prediction point. Besides, a discrete wavelet transform technique is employed to capture the statistical information of past dynamics of input currents, which are utilized to predict the future battery currents. Finally, the RDT can be predicted based on the battery model, SOC estimation results and predicted future battery currents. The performance of the proposed methodology has been verified by a lithium-ion battery cell. Experimental results indicate that the proposed method can provide an accurate SOC and parameter estimation and the predicted RDT can solve the range anxiety issues.

  2. Geodetic analysis of disputed accurate qibla direction

    NASA Astrophysics Data System (ADS)

    Saksono, Tono; Fulazzaky, Mohamad Ali; Sari, Zamah

    2018-04-01

    Muslims perform the prayers facing towards the correct qibla direction would be the only one of the practical issues in linking theoretical studies with practice. The concept of facing towards the Kaaba in Mecca during the prayers has long been the source of controversy among the muslim communities to not only in poor and developing countries but also in developed countries. The aims of this study were to analyse the geodetic azimuths of qibla calculated using three different models of the Earth. The use of ellipsoidal model of the Earth could be the best method for determining the accurate direction of Kaaba from anywhere on the Earth's surface. A muslim cannot direct himself towards the qibla correctly if he cannot see the Kaaba due to setting out process and certain motions during the prayer this can significantly shift the qibla direction from the actual position of the Kaaba. The requirement of muslim prayed facing towards the Kaaba is more as spiritual prerequisite rather than physical evidence.

  3. Predicting conversion from MCI to AD using resting-state fMRI, graph theoretical approach and SVM.

    PubMed

    Hojjati, Seyed Hani; Ebrahimzadeh, Ata; Khazaee, Ali; Babajani-Feremi, Abbas

    2017-04-15

    We investigated identifying patients with mild cognitive impairment (MCI) who progress to Alzheimer's disease (AD), MCI converter (MCI-C), from those with MCI who do not progress to AD, MCI non-converter (MCI-NC), based on resting-state fMRI (rs-fMRI). Graph theory and machine learning approach were utilized to predict progress of patients with MCI to AD using rs-fMRI. Eighteen MCI converts (average age 73.6 years; 11 male) and 62 age-matched MCI non-converters (average age 73.0 years, 28 male) were included in this study. We trained and tested a support vector machine (SVM) to classify MCI-C from MCI-NC using features constructed based on the local and global graph measures. A novel feature selection algorithm was developed and utilized to select an optimal subset of features. Using subset of optimal features in SVM, we classified MCI-C from MCI-NC with an accuracy, sensitivity, specificity, and the area under the receiver operating characteristic (ROC) curve of 91.4%, 83.24%, 90.1%, and 0.95, respectively. Furthermore, results of our statistical analyses were used to identify the affected brain regions in AD. To the best of our knowledge, this is the first study that combines the graph measures (constructed based on rs-fMRI) with machine learning approach and accurately classify MCI-C from MCI-NC. Results of this study demonstrate potential of the proposed approach for early AD diagnosis and demonstrate capability of rs-fMRI to predict conversion from MCI to AD by identifying affected brain regions underlying this conversion. Copyright © 2017 Elsevier B.V. All rights reserved.

  4. Variational transition state theory: theoretical framework and recent developments.

    PubMed

    Bao, Junwei Lucas; Truhlar, Donald G

    2017-12-11

    This article reviews the fundamentals of variational transition state theory (VTST), its recent theoretical development, and some modern applications. The theoretical methods reviewed here include multidimensional quantum mechanical tunneling, multistructural VTST (MS-VTST), multi-path VTST (MP-VTST), both reaction-path VTST (RP-VTST) and variable reaction coordinate VTST (VRC-VTST), system-specific quantum Rice-Ramsperger-Kassel theory (SS-QRRK) for predicting pressure-dependent rate constants, and VTST in the solid phase, liquid phase, and enzymes. We also provide some perspectives regarding the general applicability of VTST.

  5. Control surface hinge moment prediction using computational fluid dynamics

    NASA Astrophysics Data System (ADS)

    Simpson, Christopher David

    The following research determines the feasibility of predicting control surface hinge moments using various computational methods. A detailed analysis is conducted using a 2D GA(W)-1 airfoil with a 20% plain flap. Simple hinge moment prediction methods are tested, including empirical Datcom relations and XFOIL. Steady-state and time-accurate turbulent, viscous, Navier-Stokes solutions are computed using Fun3D. Hinge moment coefficients are computed. Mesh construction techniques are discussed. An adjoint-based mesh adaptation case is also evaluated. An NACA 0012 45-degree swept horizontal stabilizer with a 25% elevator is also evaluated using Fun3D. Results are compared with experimental wind-tunnel data obtained from references. Finally, the costs of various solution methods are estimated. Results indicate that while a steady-state Navier-Stokes solution can accurately predict control surface hinge moments for small angles of attack and deflection angles, a time-accurate solution is necessary to accurately predict hinge moments in the presence of flow separation. The ability to capture the unsteady vortex shedding behavior present in moderate to large control surface deflections is found to be critical to hinge moment prediction accuracy. Adjoint-based mesh adaptation is shown to give hinge moment predictions similar to a globally-refined mesh for a steady-state 2D simulation.

  6. Droplet size in flow: Theoretical model and application to polymer blends

    NASA Astrophysics Data System (ADS)

    Fortelný, Ivan; Jůza, Josef

    2017-05-01

    The paper is focused on prediction of the average droplet radius, R, in flowing polymer blends where the droplet size is determined by dynamic equilibrium between the droplet breakup and coalescence. Expressions for the droplet breakup frequency in systems with low and high contents of the dispersed phase are derived using available theoretical and experimental results for model blends. Dependences of the coalescence probability, Pc, on system parameters, following from recent theories, is considered and approximate equation for Pc in a system with a low polydispersity in the droplet size is proposed. Equations for R in systems with low and high contents of the dispersed phase are derived. Combination of these equations predicts realistic dependence of R on the volume fraction of dispersed droplets, φ. Theoretical prediction of the ratio of R to the critical droplet radius at breakup agrees fairly well with experimental values for steadily mixed polymer blends.

  7. Accurately controlled sequential self-folding structures by polystyrene film

    NASA Astrophysics Data System (ADS)

    Deng, Dongping; Yang, Yang; Chen, Yong; Lan, Xing; Tice, Jesse

    2017-08-01

    Four-dimensional (4D) printing overcomes the traditional fabrication limitations by designing heterogeneous materials to enable the printed structures evolve over time (the fourth dimension) under external stimuli. Here, we present a simple 4D printing of self-folding structures that can be sequentially and accurately folded. When heated above their glass transition temperature pre-strained polystyrene films shrink along the XY plane. In our process silver ink traces printed on the film are used to provide heat stimuli by conducting current to trigger the self-folding behavior. The parameters affecting the folding process are studied and discussed. Sequential folding and accurately controlled folding angles are achieved by using printed ink traces and angle lock design. Theoretical analyses are done to guide the design of the folding processes. Programmable structures such as a lock and a three-dimensional antenna are achieved to test the feasibility and potential applications of this method. These self-folding structures change their shapes after fabrication under controlled stimuli (electric current) and have potential applications in the fields of electronics, consumer devices, and robotics. Our design and fabrication method provides an easy way by using silver ink printed on polystyrene films to 4D print self-folding structures for electrically induced sequential folding with angular control.

  8. 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

  9. Accurate SHAPE-directed RNA secondary structure modeling, including pseudoknots.

    PubMed

    Hajdin, Christine E; Bellaousov, Stanislav; Huggins, Wayne; Leonard, Christopher W; Mathews, David H; Weeks, Kevin M

    2013-04-02

    A pseudoknot forms in an RNA when nucleotides in a loop pair with a region outside the helices that close the loop. Pseudoknots occur relatively rarely in RNA but are highly overrepresented in functionally critical motifs in large catalytic RNAs, in riboswitches, and in regulatory elements of viruses. Pseudoknots are usually excluded from RNA structure prediction algorithms. When included, these pairings are difficult to model accurately, especially in large RNAs, because allowing this structure dramatically increases the number of possible incorrect folds and because it is difficult to search the fold space for an optimal structure. We have developed a concise secondary structure modeling approach that combines SHAPE (selective 2'-hydroxyl acylation analyzed by primer extension) experimental chemical probing information and a simple, but robust, energy model for the entropic cost of single pseudoknot formation. Structures are predicted with iterative refinement, using a dynamic programming algorithm. This melded experimental and thermodynamic energy function predicted the secondary structures and the pseudoknots for a set of 21 challenging RNAs of known structure ranging in size from 34 to 530 nt. On average, 93% of known base pairs were predicted, and all pseudoknots in well-folded RNAs were identified.

  10. Accurate Induction Energies for Small Organic Molecules. 2. Development and Testing of Distributed Polarizability Models against SAPT(DFT) Energies.

    PubMed

    Misquitta, Alston J; Stone, Anthony J; Price, Sarah L

    2008-01-01

    In part 1 of this two-part investigation we set out the theoretical basis for constructing accurate models of the induction energy of clusters of moderately sized organic molecules. In this paper we use these techniques to develop a variety of accurate distributed polarizability models for a set of representative molecules that include formamide, N-methyl propanamide, benzene, and 3-azabicyclo[3.3.1]nonane-2,4-dione. We have also explored damping, penetration, and basis set effects. In particular, we have provided a way to treat the damping of the induction expansion. Different approximations to the induction energy are evaluated against accurate SAPT(DFT) energies, and we demonstrate the accuracy of our induction models on the formamide-water dimer.

  11. 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.

  12. Field theoretical prediction of a property of the tropical cyclone

    NASA Astrophysics Data System (ADS)

    Spineanu, F.; Vlad, M.

    2014-01-01

    The large scale atmospheric vortices (tropical cyclones, tornadoes) are complex physical systems combining thermodynamics and fluid-mechanical processes. The late phase of the evolution towards stationarity consists of the vorticity concentration, a well known tendency to self-organization , an universal property of the two-dimensional fluids. It may then be expected that the stationary state of the tropical cyclone has the same nature as the vortices of many other systems in nature: ideal (Euler) fluids, superconductors, Bose-Einsetin condensate, cosmic strings, etc. Indeed it was found that there is a description of the atmospheric vortex in terms of a classical field theory. It is compatible with the more conventional treatment based on conservation laws, but the field theoretical model reveals properties that are almost inaccessible to the conventional formulation: it identifies the stationary states as being close to self-duality. This is of highest importance: the self-duality is known to be the origin of all coherent structures known in natural systems. Therefore the field theoretical (FT) formulation finds that the cuasi-coherent form of the atmospheric vortex (tropical cyclone) at stationarity is an expression of this particular property. In the present work we examine a strong property of the tropical cyclone, which arises in the FT formulation in a natural way: the equality of the masses of the particles associated to the matter field and respectively to the gauge field in the FT model is translated into the equality between the maximum radial extension of the tropical cyclone and the Rossby radius. For the cases where the FT model is a good approximation we calculate characteristic quantities of the tropical cyclone and find good comparison with observational data.

  13. Short communication: Genetic lag represents commercial herd genetic merit more accurately than the 4-path selection model.

    PubMed

    Dechow, C D; Rogers, G W

    2018-05-01

    Expectation of genetic merit in commercial dairy herds is routinely estimated using a 4-path genetic selection model that was derived for a closed population, but commercial herds using artificial insemination sires are not closed. The 4-path model also predicts a higher rate of genetic progress in elite herds that provide artificial insemination sires than in commercial herds that use such sires, which counters other theoretical assumptions and observations of realized genetic responses. The aim of this work is to clarify whether genetic merit in commercial herds is more accurately reflected under the assumptions of the 4-path genetic response formula or by a genetic lag formula. We demonstrate by tracing the transmission of genetic merit from parents to offspring that the rate of genetic progress in commercial dairy farms is expected to be the same as that in the genetic nucleus. The lag in genetic merit between the nucleus and commercial farms is a function of sire and dam generation interval, the rate of genetic progress in elite artificial insemination herds, and genetic merit of sires and dams. To predict how strategies such as the use of young versus daughter-proven sires, culling heifers following genomic testing, or selective use of sexed semen will alter genetic merit in commercial herds, genetic merit expectations for commercial herds should be modeled using genetic lag expectations. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  14. Accurate band-to-band registration of AOTF imaging spectrometer using motion detection technology

    NASA Astrophysics Data System (ADS)

    Zhou, Pengwei; Zhao, Huijie; Jin, Shangzhong; Li, Ningchuan

    2016-05-01

    This paper concerns the problem of platform vibration induced band-to-band misregistration with acousto-optic imaging spectrometer in spaceborne application. Registrating images of different bands formed at different time or different position is difficult, especially for hyperspectral images form acousto-optic tunable filter (AOTF) imaging spectrometer. In this study, a motion detection method is presented using the polychromatic undiffracted beam of AOTF. The factors affecting motion detect accuracy are analyzed theoretically, and calculations show that optical distortion is an easily overlooked factor to achieve accurate band-to-band registration. Hence, a reflective dual-path optical system has been proposed for the first time, with reduction of distortion and chromatic aberration, indicating the potential of higher registration accuracy. Consequently, a spectra restoration experiment using additional motion detect channel is presented for the first time, which shows the accurate spectral image registration capability of this technique.

  15. Prediction of DHF disease spreading patterns using inverse distances weighted (IDW), ordinary and universal kriging

    NASA Astrophysics Data System (ADS)

    Prasetiyowati, S. S.; Sibaroni, Y.

    2018-03-01

    Dengue hemorrhagic disease, is a disease caused by the Dengue virus of the Flavivirus genus Flaviviridae family. Indonesia is the country with the highest case of dengue in Southeast Asia. In addition to mosquitoes as vectors and humans as hosts, other environmental and social factors are also the cause of widespread dengue fever. To prevent the occurrence of the epidemic of the disease, fast and accurate action is required. Rapid and accurate action can be taken, if there is appropriate information support on the occurrence of the epidemic. Therefore, a complete and accurate information on the spread pattern of endemic areas is necessary, so that precautions can be done as early as possible. The information on dispersal patterns can be obtained by various methods, which are based on empirical and theoretical considerations. One of the methods used is based on the estimated number of infected patients in a region based on spatial and time. The first step of this research is conducted by predicting the number of DHF patients in 2016 until 2018 based on 2010 to 2015 data using GSTAR (1, 1). In the second phase, the distribution pattern prediction of dengue disease area is conducted. Furthermore, based on the characteristics of DHF epidemic trends, i.e. down, stable or rising, the analysis of distribution patterns of dengue fever distribution areas with IDW and Kriging (ordinary and universal Kriging) were conducted in this study. The difference between IDW and Kriging, is the initial process that underlies the prediction process. Based on the experimental results, it is known that the dispersion pattern of epidemic areas of dengue disease with IDW and Ordinary Kriging is similar in the period of time.

  16. Practical guidance on representing the heteroscedasticity of residual errors of hydrological predictions

    NASA Astrophysics Data System (ADS)

    McInerney, David; Thyer, Mark; Kavetski, Dmitri; Kuczera, George

    2016-04-01

    Appropriate representation of residual errors in hydrological modelling is essential for accurate and reliable probabilistic streamflow predictions. In particular, residual errors of hydrological predictions are often heteroscedastic, with large errors associated with high runoff events. Although multiple approaches exist for representing this heteroscedasticity, few if any studies have undertaken a comprehensive evaluation and comparison of these approaches. This study fills this research gap by evaluating a range of approaches for representing heteroscedasticity in residual errors. These approaches include the 'direct' weighted least squares approach and 'transformational' approaches, such as logarithmic, Box-Cox (with and without fitting the transformation parameter), logsinh and the inverse transformation. The study reports (1) theoretical comparison of heteroscedasticity approaches, (2) empirical evaluation of heteroscedasticity approaches using a range of multiple catchments / hydrological models / performance metrics and (3) interpretation of empirical results using theory to provide practical guidance on the selection of heteroscedasticity approaches. Importantly, for hydrological practitioners, the results will simplify the choice of approaches to represent heteroscedasticity. This will enhance their ability to provide hydrological probabilistic predictions with the best reliability and precision for different catchment types (e.g. high/low degree of ephemerality).

  17. A new approach to compute accurate velocity of meteors

    NASA Astrophysics Data System (ADS)

    Egal, Auriane; Gural, Peter; Vaubaillon, Jeremie; Colas, Francois; Thuillot, William

    2016-10-01

    The CABERNET project was designed to push the limits of meteoroid orbit measurements by improving the determination of the meteors' velocities. Indeed, despite of the development of the cameras networks dedicated to the observation of meteors, there is still an important discrepancy between the measured orbits of meteoroids computed and the theoretical results. The gap between the observed and theoretic semi-major axis of the orbits is especially significant; an accurate determination of the orbits of meteoroids therefore largely depends on the computation of the pre-atmospheric velocities. It is then imperative to dig out how to increase the precision of the measurements of the velocity.In this work, we perform an analysis of different methods currently used to compute the velocities and trajectories of the meteors. They are based on the intersecting planes method developed by Ceplecha (1987), the least squares method of Borovicka (1990), and the multi-parameter fitting (MPF) method published by Gural (2012).In order to objectively compare the performances of these techniques, we have simulated realistic meteors ('fakeors') reproducing the different error measurements of many cameras networks. Some fakeors are built following the propagation models studied by Gural (2012), and others created by numerical integrations using the Borovicka et al. 2007 model. Different optimization techniques have also been investigated in order to pick the most suitable one to solve the MPF, and the influence of the geometry of the trajectory on the result is also presented.We will present here the results of an improved implementation of the multi-parameter fitting that allow an accurate orbit computation of meteors with CABERNET. The comparison of different velocities computation seems to show that if the MPF is by far the best method to solve the trajectory and the velocity of a meteor, the ill-conditioning of the costs functions used can lead to large estimate errors for noisy

  18. Theoretical prediction of a rotating magnon wave packet in ferromagnets.

    PubMed

    Matsumoto, Ryo; Murakami, Shuichi

    2011-05-13

    We theoretically show that the magnon wave packet has a rotational motion in two ways: a self-rotation and a motion along the boundary of the sample (edge current). They are similar to the cyclotron motion of electrons, but unlike electrons the magnons have no charge and the rotation is not due to the Lorentz force. These rotational motions are caused by the Berry phase in momentum space from the magnon band structure. Furthermore, the rotational motion of the magnon gives an additional correction term to the magnon Hall effect. We also discuss the Berry curvature effect in the classical limit of long-wavelength magnetostatic spin waves having macroscopic coherence length.

  19. Experimental and theoretical rotordynamic stiffness coefficients for a three-stage brush seal

    NASA Astrophysics Data System (ADS)

    Pugachev, A. O.; Deckner, M.

    2012-08-01

    Experimental and theoretical results are presented for a multistage brush seal. Experimental stiffness is obtained from integrating circumferential pressure distribution measured in seal cavities. A CFD analysis is used to predict seal performance. Bristle packs are modeled by the porous medium approach. Leakage is predicted well by the CFD method. Theoretical stiffness coefficients are in reasonable agreement with the measurements. Experimental results are also compared with a three-teeth-on-stator labyrinth seal. The multistage brush seal gives about 60% leakage reduction over the labyrinth seal. Rotordynamic stiffness coefficients are also improved: the brush seal has positive direct stiffness and smaller cross-coupled stiffness.

  20. Neural and Hybrid Modeling: An Alternative Route to Efficiently Predict the Behavior of Biotechnological Processes Aimed at Biofuels Obtainment

    PubMed Central

    Saraceno, Alessandra; Calabrò, Vincenza; Iorio, Gabriele

    2014-01-01

    The present paper was aimed at showing that advanced modeling techniques, based either on artificial neural networks or on hybrid systems, might efficiently predict the behavior of two biotechnological processes designed for the obtainment of second-generation biofuels from waste biomasses. In particular, the enzymatic transesterification of waste-oil glycerides, the key step for the obtainment of biodiesel, and the anaerobic digestion of agroindustry wastes to produce biogas were modeled. It was proved that the proposed modeling approaches provided very accurate predictions of systems behavior. Both neural network and hybrid modeling definitely represented a valid alternative to traditional theoretical models, especially when comprehensive knowledge of the metabolic pathways, of the true kinetic mechanisms, and of the transport phenomena involved in biotechnological processes was difficult to be achieved. PMID:24516363

  1. Predictive modeling of complications.

    PubMed

    Osorio, Joseph A; Scheer, Justin K; Ames, Christopher P

    2016-09-01

    Predictive analytic algorithms are designed to identify patterns in the data that allow for accurate predictions without the need for a hypothesis. Therefore, predictive modeling can provide detailed and patient-specific information that can be readily applied when discussing the risks of surgery with a patient. There are few studies using predictive modeling techniques in the adult spine surgery literature. These types of studies represent the beginning of the use of predictive analytics in spine surgery outcomes. We will discuss the advancements in the field of spine surgery with respect to predictive analytics, the controversies surrounding the technique, and the future directions.

  2. Computer-based personality judgments are more accurate than those made by humans

    PubMed Central

    Youyou, Wu; Kosinski, Michal; Stillwell, David

    2015-01-01

    Judging others’ personalities is an essential skill in successful social living, as personality is a key driver behind people’s interactions, behaviors, and emotions. Although accurate personality judgments stem from social-cognitive skills, developments in machine learning show that computer models can also make valid judgments. This study compares the accuracy of human and computer-based personality judgments, using a sample of 86,220 volunteers who completed a 100-item personality questionnaire. We show that (i) computer predictions based on a generic digital footprint (Facebook Likes) are more accurate (r = 0.56) than those made by the participants’ Facebook friends using a personality questionnaire (r = 0.49); (ii) computer models show higher interjudge agreement; and (iii) computer personality judgments have higher external validity when predicting life outcomes such as substance use, political attitudes, and physical health; for some outcomes, they even outperform the self-rated personality scores. Computers outpacing humans in personality judgment presents significant opportunities and challenges in the areas of psychological assessment, marketing, and privacy. PMID:25583507

  3. Accurate van der Waals force field for gas adsorption in porous materials.

    PubMed

    Sun, Lei; Yang, Li; Zhang, Ya-Dong; Shi, Qi; Lu, Rui-Feng; Deng, Wei-Qiao

    2017-09-05

    An accurate van der Waals force field (VDW FF) was derived from highly precise quantum mechanical (QM) calculations. Small molecular clusters were used to explore van der Waals interactions between gas molecules and porous materials. The parameters of the accurate van der Waals force field were determined by QM calculations. To validate the force field, the prediction results from the VDW FF were compared with standard FFs, such as UFF, Dreiding, Pcff, and Compass. The results from the VDW FF were in excellent agreement with the experimental measurements. This force field can be applied to the prediction of the gas density (H 2 , CO 2 , C 2 H 4 , CH 4 , N 2 , O 2 ) and adsorption performance inside porous materials, such as covalent organic frameworks (COFs), zeolites and metal organic frameworks (MOFs), consisting of H, B, N, C, O, S, Si, Al, Zn, Mg, Ni, and Co. This work provides a solid basis for studying gas adsorption in porous materials. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  4. Predictive value of diminutive colonic adenoma trial: the PREDICT trial.

    PubMed

    Schoenfeld, Philip; Shad, Javaid; Ormseth, Eric; Coyle, Walter; Cash, Brooks; Butler, James; Schindler, William; Kikendall, Walter J; Furlong, Christopher; Sobin, Leslie H; Hobbs, Christine M; Cruess, David; Rex, Douglas

    2003-05-01

    Diminutive adenomas (1-9 mm in diameter) are frequently found during colon cancer screening with flexible sigmoidoscopy (FS). This trial assessed the predictive value of these diminutive adenomas for advanced adenomas in the proximal colon. In a multicenter, prospective cohort trial, we matched 200 patients with normal FS and 200 patients with diminutive adenomas on FS for age and gender. All patients underwent colonoscopy. The presence of advanced adenomas (adenoma >or= 10 mm in diameter, villous adenoma, adenoma with high grade dysplasia, and colon cancer) and adenomas (any size) was recorded. Before colonoscopy, patients completed questionnaires about risk factors for adenomas. The prevalence of advanced adenomas in the proximal colon was similar in patients with diminutive adenomas and patients with normal FS (6% vs. 5.5%, respectively) (relative risk, 1.1; 95% confidence interval [CI], 0.5-2.6). Diminutive adenomas on FS did not accurately predict advanced adenomas in the proximal colon: sensitivity, 52% (95% CI, 32%-72%); specificity, 50% (95% CI, 49%-51%); positive predictive value, 6% (95% CI, 4%-8%); and negative predictive value, 95% (95% CI, 92%-97%). Male gender (odds ratio, 1.63; 95% CI, 1.01-2.61) was associated with an increased risk of proximal colon adenomas. Diminutive adenomas on sigmoidoscopy may not accurately predict advanced adenomas in the proximal colon.

  5. Energy prediction equations are inadequate for obese Hispanic youth.

    PubMed

    Klein, Catherine J; Villavicencio, Stephan A; Schweitzer, Amy; Bethepu, Joel S; Hoffman, Heather J; Mirza, Nazrat M

    2011-08-01

    Assessing energy requirements is a fundamental activity in clinical dietetics practice. A study was designed to determine whether published linear regression equations were accurate for predicting resting energy expenditure (REE) in fasted Hispanic children with obesity (aged 7 to 15 years). REE was measured using indirect calorimetry; body composition was estimated with whole-body air displacement plethysmography. REE was predicted using four equations: Institute of Medicine for healthy-weight children (IOM-HW), IOM for overweight and obese children (IOM-OS), Harris-Benedict, and Schofield. Accuracy of the prediction was calculated as the absolute value of the difference between the measured and predicted REE divided by the measured REE, expressed as a percentage. Predicted values within 85% to 115% of measured were defined as accurate. Participants (n=58; 53% boys) were mean age 11.8±2.1 years, had 43.5%±5.1% body fat, and had a body mass index of 31.5±5.8 (98.6±1.1 body mass index percentile). Measured REE was 2,339±680 kcal/day; predicted REE was 1,815±401 kcal/day (IOM-HW), 1,794±311 kcal/day (IOM-OS), 1,151±300 kcal/day (Harris-Benedict), and, 1,771±316 kcal/day (Schofield). Measured REE adjusted for body weight averaged 32.0±8.4 kcal/kg/day (95% confidence interval 29.8 to 34.2). Published equations predicted REE within 15% accuracy for only 36% to 40% of 58 participants, except for Harris-Benedict, which did not achieve accuracy for any participant. The most frequently accurate values were obtained using IOM-HW, which predicted REE within 15% accuracy for 55% (17/31) of boys. Published equations did not accurately predict REE for youth in the study sample. Further studies are warranted to formulate accurate energy prediction equations for this population. Copyright © 2011 American Dietetic Association. Published by Elsevier Inc. All rights reserved.

  6. Laser-Induced Translative Hydrodynamic Mass Snapshots: Noninvasive Characterization and Predictive Modeling via Mapping at Nanoscale

    NASA Astrophysics Data System (ADS)

    Wang, X. W.; Kuchmizhak, A. A.; Li, X.; Juodkazis, S.; Vitrik, O. B.; Kulchin, Yu. N.; Zhakhovsky, V. V.; Danilov, P. A.; Ionin, A. A.; Kudryashov, S. I.; Rudenko, A. A.; Inogamov, N. A.

    2017-10-01

    Subwavelength structures (meta-atoms) with artificially engineered permittivity and permeability have shown promising applications for guiding and controlling the flow of electromagnetic energy on the nanoscale. Ultrafast laser nanoprinting emerges as a promising single-step, green and flexible technology in fabricating large-area arrays of meta-atoms through the translative or ablative modification of noble-metal thin films. Ultrafast laser energy deposition in noble-metal films produces irreversible, intricate nanoscale translative mass redistributions after resolidification of the transient thermally assisted hydrodynamic melt perturbations. Such mass redistribution results in the formation of a radially symmetric frozen surface with modified hidden nanofeatures, which strongly affect the optical response harnessed in plasmonic sensing and nonlinear optical applications. Here, we demonstrate that side-view electron microscopy and ion-beam cross sections together with low-energy electron x-ray dispersion microscopy provide exact information about such three-dimensional patterns, enabling an accurate acquisition of their cross-sectional mass distributions. Such nanoscale solidified structures are theoretically modeled, considering the underlying physical processes associated with laser-induced energy absorption, electron-ion energy exchange, acoustic relaxation, and hydrodynamic flows. A theoretical approach, separating slow and fast physical processes and combining hybrid analytical two-temperature calculations, scalable molecular-dynamics simulations, and a semianalytical thin-shell model is synergistically applied. These advanced characterization approaches are required for a detailed modeling of near-field electromagnetic response and pave the way to a fully automated noninvasive in-line control of a high-throughput and large-scale laser fabrication. This theoretical modeling provides an accurate prediction of scales and topographies of the laser

  7. ACCURATE CHEMICAL MASTER EQUATION SOLUTION USING MULTI-FINITE BUFFERS

    PubMed Central

    Cao, Youfang; Terebus, Anna; Liang, Jie

    2016-01-01

    The discrete chemical master equation (dCME) provides a fundamental framework for studying stochasticity in mesoscopic networks. Because of the multi-scale nature of many networks where reaction rates have large disparity, directly solving dCMEs is intractable due to the exploding size of the state space. It is important to truncate the state space effectively with quantified errors, so accurate solutions can be computed. It is also important to know if all major probabilistic peaks have been computed. Here we introduce the Accurate CME (ACME) algorithm for obtaining direct solutions to dCMEs. With multi-finite buffers for reducing the state space by O(n!), exact steady-state and time-evolving network probability landscapes can be computed. We further describe a theoretical framework of aggregating microstates into a smaller number of macrostates by decomposing a network into independent aggregated birth and death processes, and give an a priori method for rapidly determining steady-state truncation errors. The maximal sizes of the finite buffers for a given error tolerance can also be pre-computed without costly trial solutions of dCMEs. We show exactly computed probability landscapes of three multi-scale networks, namely, a 6-node toggle switch, 11-node phage-lambda epigenetic circuit, and 16-node MAPK cascade network, the latter two with no known solutions. We also show how probabilities of rare events can be computed from first-passage times, another class of unsolved problems challenging for simulation-based techniques due to large separations in time scales. Overall, the ACME method enables accurate and efficient solutions of the dCME for a large class of networks. PMID:27761104

  8. Accurate chemical master equation solution using multi-finite buffers

    DOE PAGES

    Cao, Youfang; Terebus, Anna; Liang, Jie

    2016-06-29

    Here, the discrete chemical master equation (dCME) provides a fundamental framework for studying stochasticity in mesoscopic networks. Because of the multiscale nature of many networks where reaction rates have a large disparity, directly solving dCMEs is intractable due to the exploding size of the state space. It is important to truncate the state space effectively with quantified errors, so accurate solutions can be computed. It is also important to know if all major probabilistic peaks have been computed. Here we introduce the accurate CME (ACME) algorithm for obtaining direct solutions to dCMEs. With multifinite buffers for reducing the state spacemore » by $O(n!)$, exact steady-state and time-evolving network probability landscapes can be computed. We further describe a theoretical framework of aggregating microstates into a smaller number of macrostates by decomposing a network into independent aggregated birth and death processes and give an a priori method for rapidly determining steady-state truncation errors. The maximal sizes of the finite buffers for a given error tolerance can also be precomputed without costly trial solutions of dCMEs. We show exactly computed probability landscapes of three multiscale networks, namely, a 6-node toggle switch, 11-node phage-lambda epigenetic circuit, and 16-node MAPK cascade network, the latter two with no known solutions. We also show how probabilities of rare events can be computed from first-passage times, another class of unsolved problems challenging for simulation-based techniques due to large separations in time scales. Overall, the ACME method enables accurate and efficient solutions of the dCME for a large class of networks.« less

  9. Accurate chemical master equation solution using multi-finite buffers

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Cao, Youfang; Terebus, Anna; Liang, Jie

    Here, the discrete chemical master equation (dCME) provides a fundamental framework for studying stochasticity in mesoscopic networks. Because of the multiscale nature of many networks where reaction rates have a large disparity, directly solving dCMEs is intractable due to the exploding size of the state space. It is important to truncate the state space effectively with quantified errors, so accurate solutions can be computed. It is also important to know if all major probabilistic peaks have been computed. Here we introduce the accurate CME (ACME) algorithm for obtaining direct solutions to dCMEs. With multifinite buffers for reducing the state spacemore » by $O(n!)$, exact steady-state and time-evolving network probability landscapes can be computed. We further describe a theoretical framework of aggregating microstates into a smaller number of macrostates by decomposing a network into independent aggregated birth and death processes and give an a priori method for rapidly determining steady-state truncation errors. The maximal sizes of the finite buffers for a given error tolerance can also be precomputed without costly trial solutions of dCMEs. We show exactly computed probability landscapes of three multiscale networks, namely, a 6-node toggle switch, 11-node phage-lambda epigenetic circuit, and 16-node MAPK cascade network, the latter two with no known solutions. We also show how probabilities of rare events can be computed from first-passage times, another class of unsolved problems challenging for simulation-based techniques due to large separations in time scales. Overall, the ACME method enables accurate and efficient solutions of the dCME for a large class of networks.« less

  10. Predicting β-turns and their types using predicted backbone dihedral angles and secondary structures

    PubMed Central

    2010-01-01

    Background β-turns are secondary structure elements usually classified as coil. Their prediction is important, because of their role in protein folding and their frequent occurrence in protein chains. Results We have developed a novel method that predicts β-turns and their types using information from multiple sequence alignments, predicted secondary structures and, for the first time, predicted dihedral angles. Our method uses support vector machines, a supervised classification technique, and is trained and tested on three established datasets of 426, 547 and 823 protein chains. We achieve a Matthews correlation coefficient of up to 0.49, when predicting the location of β-turns, the highest reported value to date. Moreover, the additional dihedral information improves the prediction of β-turn types I, II, IV, VIII and "non-specific", achieving correlation coefficients up to 0.39, 0.33, 0.27, 0.14 and 0.38, respectively. Our results are more accurate than other methods. Conclusions We have created an accurate predictor of β-turns and their types. Our method, called DEBT, is available online at http://comp.chem.nottingham.ac.uk/debt/. PMID:20673368

  11. Predicting differences in the perceived relevance of crime's costs and benefits in a test of rational choice theory.

    PubMed

    Bouffard, Jeffrey A

    2007-08-01

    Previous hypothetical scenario tests of rational choice theory have presented all participants with the same set of consequences, implicitly assuming that these consequences would be relevant for each individual. Recent research demonstrates that those researcher-presented consequences do not accurately reflect those considered by study participants and that there is individual variation in the relevance of various consequences. Despite this and some theoretical propositions that such differences should exist, little empirical research has explored the possibility of predicting such variation. This study allows participants to develop their own set of relevant consequences for three hypothetical offenses and examines how several demographic and theoretical variables impact those consequences' relevance. Exploratory results suggest individual factors impact the perceived relevance of several cost and benefit types, even among a relatively homogenous sample of college students. Implications for future tests of rational choice theory, as well as policy implications are discussed.

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Zuniga, Cristal; Li, Chien -Ting; Huelsman, Tyler

    The green microalgae 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 organismmore » 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. Moreover, 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.« less

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

    DOE PAGES

    Zuniga, Cristal; Li, Chien -Ting; Huelsman, Tyler; ...

    2016-07-02

    The green microalgae 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 organismmore » 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. Moreover, 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.« less

  14. 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. © 2016 American Society of Plant Biologists. All rights reserved.

  15. Improving the theoretical prediction for the Bs - B̅s width difference: matrix elements of next-to-leading order ΔB = 2 operators

    NASA Astrophysics Data System (ADS)

    Davies, Christine; Harrison, Judd; Lepage, G. Peter; Monahan, Christopher; Shigemitsu, Junko; Wingate, Matthew

    2018-03-01

    We present lattice QCD results for the matrix elements of R2 and other dimension-7, ΔB = 2 operators relevant for calculations of Δs, the Bs - B̅s width difference. We have computed correlation functions using 5 ensembles of the MILC Collaboration's 2+1 + 1-flavour gauge field configurations, spanning 3 lattice spacings and light sea quarks masses down to the physical point. The HISQ action is used for the valence strange quarks, and the NRQCD action is used for the bottom quarks. Once our analysis is complete, the theoretical uncertainty in the Standard Model prediction for ΔΓs will be substantially reduced.

  16. Accurate prediction of retention in hydrophilic interaction chromatography by back calculation of high pressure liquid chromatography gradient profiles.

    PubMed

    Wang, Nu; Boswell, Paul G

    2017-10-20

    Gradient retention times are difficult to project from the underlying retention factor (k) vs. solvent composition (φ) relationships. A major reason for this difficulty is that gradients produced by HPLC pumps are imperfect - gradient delay, gradient dispersion, and solvent mis-proportioning are all difficult to account for in calculations. However, we recently showed that a gradient "back-calculation" methodology can measure these imperfections and take them into account. In RPLC, when the back-calculation methodology was used, error in projected gradient retention times is as low as could be expected based on repeatability in the k vs. φ relationships. HILIC, however, presents a new challenge: the selectivity of HILIC columns drift strongly over time. Retention is repeatable in short time, but selectivity frequently drifts over the course of weeks. In this study, we set out to understand if the issue of selectivity drift can be avoid by doing our experiments quickly, and if there any other factors that make it difficult to predict gradient retention times from isocratic k vs. φ relationships when gradient imperfections are taken into account with the back-calculation methodology. While in past reports, the accuracy of retention projections was >5%, the back-calculation methodology brought our error down to ∼1%. This result was 6-43 times more accurate than projections made using ideal gradients and 3-5 times more accurate than the same retention projections made using offset gradients (i.e., gradients that only took gradient delay into account). Still, the error remained higher in our HILIC projections than in RPLC. Based on the shape of the back-calculated gradients, we suspect the higher error is a result of prominent gradient distortion caused by strong, preferential water uptake from the mobile phase into the stationary phase during the gradient - a factor our model did not properly take into account. It appears that, at least with the stationary phase

  17. 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

  18. 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

  19. Dynamic sensing model for accurate delectability of environmental phenomena using event wireless sensor network

    NASA Astrophysics Data System (ADS)

    Missif, Lial Raja; Kadhum, Mohammad M.

    2017-09-01

    Wireless Sensor Network (WSN) has been widely used for monitoring where sensors are deployed to operate independently to sense abnormal phenomena. Most of the proposed environmental monitoring systems are designed based on a predetermined sensing range which does not reflect the sensor reliability, event characteristics, and the environment conditions. Measuring of the capability of a sensor node to accurately detect an event within a sensing field is of great important for monitoring applications. This paper presents an efficient mechanism for even detection based on probabilistic sensing model. Different models have been presented theoretically in this paper to examine their adaptability and applicability to the real environment applications. The numerical results of the experimental evaluation have showed that the probabilistic sensing model provides accurate observation and delectability of an event, and it can be utilized for different environment scenarios.

  20. Predicting Clear-Sky Reflectance Over Snow/Ice in Polar Regions

    NASA Technical Reports Server (NTRS)

    Chen, Yan; Sun-Mack, Sunny; Arduini, Robert F.; Hong, Gang; Minnis, Patrick

    2015-01-01

    Satellite remote sensing of clouds requires an accurate estimate of the clear-sky radiances for a given scene to detect clouds and aerosols and to retrieve their microphysical properties. Knowing the spatial and angular variability of clear-sky albedo is essential for predicting clear-sky radiance at solar wavelengths. The Clouds and the Earth's Radiant Energy System (CERES) Project uses the nearinfrared (NIR; 1.24, 1.6 or 2.13 micrometers), visible (VIS; 0.63 micrometers) and vegetation (VEG; 0.86 micrometers) channels available on the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) to help identify clouds and retrieve their properties in both snow-free and snow-covered conditions. Thus, it is critical to have reliable distributions of clear-sky albedo for all of these channels. In CERES Edition 4 (Ed4), the 1.24-micrometer channel is used to retrieve cloud optical depth over snow/ice-covered surfaces. Thus, it is especially critical to accurately predict the 1.24-micrometer clear-sky albedo alpha and reflectance rho for a given location and time. Snow albedo and reflectance patterns are very complex due to surface texture, particle shapes and sizes, melt water, and vegetation protrusions from the snow surface. To minimize those effects, this study focuses on the permanent snow cover of Antarctica where vegetation is absent and melt water is minimal. Clear-sky albedos are determined as a function of solar zenith angle (SZA) from observations over all scenes determined to be cloud-free to produce a normalized directional albedo model (DRM). The DRM is used to develop alpha(SZA=0 degrees) on 10 foot grid for each season. These values provide the basis for predicting r at any location and set of viewing & illumination conditions. This paper examines the accuracy of this approach for two theoretical snow surface reflectance models.

  1. Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions1

    PubMed Central

    Zuñiga, Cristal; Li, Chien-Ting; Zielinski, Daniel C.; Guarnieri, Michael T.; Antoniewicz, Maciek R.; Zengler, Karsten

    2016-01-01

    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

  2. Accurate van der Waals coefficients from density functional theory

    PubMed Central

    Tao, Jianmin; Perdew, John P.; Ruzsinszky, Adrienn

    2012-01-01

    The van der Waals interaction is a weak, long-range correlation, arising from quantum electronic charge fluctuations. This interaction affects many properties of materials. A simple and yet accurate estimate of this effect will facilitate computer simulation of complex molecular materials and drug design. Here we develop a fast approach for accurate evaluation of dynamic multipole polarizabilities and van der Waals (vdW) coefficients of all orders from the electron density and static multipole polarizabilities of each atom or other spherical object, without empirical fitting. Our dynamic polarizabilities (dipole, quadrupole, octupole, etc.) are exact in the zero- and high-frequency limits, and exact at all frequencies for a metallic sphere of uniform density. Our theory predicts dynamic multipole polarizabilities in excellent agreement with more expensive many-body methods, and yields therefrom vdW coefficients C6, C8, C10 for atom pairs with a mean absolute relative error of only 3%. PMID:22205765

  3. Method for Accurately Calibrating a Spectrometer Using Broadband Light

    NASA Technical Reports Server (NTRS)

    Simmons, Stephen; Youngquist, Robert

    2011-01-01

    A novel method has been developed for performing very fine calibration of a spectrometer. This process is particularly useful for modern miniature charge-coupled device (CCD) spectrometers where a typical factory wavelength calibration has been performed and a finer, more accurate calibration is desired. Typically, the factory calibration is done with a spectral line source that generates light at known wavelengths, allowing specific pixels in the CCD array to be assigned wavelength values. This method is good to about 1 nm across the spectrometer s wavelength range. This new method appears to be accurate to about 0.1 nm, a factor of ten improvement. White light is passed through an unbalanced Michelson interferometer, producing an optical signal with significant spectral variation. A simple theory can be developed to describe this spectral pattern, so by comparing the actual spectrometer output against this predicted pattern, errors in the wavelength assignment made by the spectrometer can be determined.

  4. An evidential link prediction method and link predictability based on Shannon entropy

    NASA Astrophysics Data System (ADS)

    Yin, Likang; Zheng, Haoyang; Bian, Tian; Deng, Yong

    2017-09-01

    Predicting missing links is of both theoretical value and practical interest in network science. In this paper, we empirically investigate a new link prediction method base on similarity and compare nine well-known local similarity measures on nine real networks. Most of the previous studies focus on the accuracy, however, it is crucial to consider the link predictability as an initial property of networks itself. Hence, this paper has proposed a new link prediction approach called evidential measure (EM) based on Dempster-Shafer theory. Moreover, this paper proposed a new method to measure link predictability via local information and Shannon entropy.

  5. Taxi-Out Time Prediction for Departures at Charlotte Airport Using Machine Learning Techniques

    NASA Technical Reports Server (NTRS)

    Lee, Hanbong; Malik, Waqar; Jung, Yoon C.

    2016-01-01

    Predicting the taxi-out times of departures accurately is important for improving airport efficiency and takeoff time predictability. In this paper, we attempt to apply machine learning techniques to actual traffic data at Charlotte Douglas International Airport for taxi-out time prediction. To find the key factors affecting aircraft taxi times, surface surveillance data is first analyzed. From this data analysis, several variables, including terminal concourse, spot, runway, departure fix and weight class, are selected for taxi time prediction. Then, various machine learning methods such as linear regression, support vector machines, k-nearest neighbors, random forest, and neural networks model are applied to actual flight data. Different traffic flow and weather conditions at Charlotte airport are also taken into account for more accurate prediction. The taxi-out time prediction results show that linear regression and random forest techniques can provide the most accurate prediction in terms of root-mean-square errors. We also discuss the operational complexity and uncertainties that make it difficult to predict the taxi times accurately.

  6. Predictability of the 2012 Great Arctic Cyclone on medium-range timescales

    NASA Astrophysics Data System (ADS)

    Yamagami, Akio; Matsueda, Mio; Tanaka, Hiroshi L.

    2018-03-01

    Arctic Cyclones (ACs) can have a significant impact on the Arctic region. Therefore, the accurate prediction of ACs is important in anticipating their associated environmental and societal costs. This study investigates the predictability of the 2012 Great Arctic Cyclone (AC12) that exhibited a minimum central pressure of 964 hPa on 6 August 2012, using five medium-range ensemble forecasts. We show that the development and position of AC12 were better predicted in forecasts initialized on and after 4 August 2012. In addition, the position of AC12 was more predictable than its development. A comparison of ensemble members, classified by the error in predictability of the development and position of AC12, revealed that an accurate prediction of upper-level fields, particularly temperature, was important for the prediction of this event. The predicted position of AC12 was influenced mainly by the prediction of the polar vortex, whereas the predicted development of AC12 was dependent primarily on the prediction of the merging of upper-level warm cores. Consequently, an accurate prediction of the polar vortex position and the development of the warm core through merging resulted in better prediction of AC12.

  7. Theoretical development and first-principles analysis of strongly correlated systems

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Liu, Chen

    A variety of quantum many-body methods have been developed for studying the strongly correlated electron systems. We have also proposed a computationally efficient and accurate approach, named the correlation matrix renormalization (CMR) method, to address the challenges. The initial implementation of the CMR method is designed for molecules which have theoretical advantages, including small size of system, manifest mechanism and strongly correlation effect such as bond breaking process. The theoretic development and benchmark tests of the CMR method are included in this thesis. Meanwhile, ground state total energy is the most important property of electronic calculations. We also investigated anmore » alternative approach to calculate the total energy, and extended this method for magnetic anisotropy energy (MAE) of ferromagnetic materials. In addition, another theoretical tool, dynamical mean- field theory (DMFT) on top of the DFT , has also been used in electronic structure calculations for an Iridium oxide to study the phase transition, which results from an interplay of the d electrons' internal degrees of freedom.« less

  8. Microvascular remodelling in preeclampsia: quantifying capillary rarefaction accurately and independently predicts preeclampsia.

    PubMed

    Antonios, Tarek F T; Nama, Vivek; Wang, Duolao; Manyonda, Isaac T

    2013-09-01

    Preeclampsia is a major cause of maternal and neonatal mortality and morbidity. The incidence of preeclampsia seems to be rising because of increased prevalence of predisposing disorders, such as essential hypertension, diabetes, and obesity, and there is increasing evidence to suggest widespread microcirculatory abnormalities before the onset of preeclampsia. We hypothesized that quantifying capillary rarefaction could be helpful in the clinical prediction of preeclampsia. We measured skin capillary density according to a well-validated protocol at 5 consecutive predetermined visits in 322 consecutive white women, of whom 16 subjects developed preeclampsia. We found that structural capillary rarefaction at 20-24 weeks of gestation yielded a sensitivity of 0.87 with a specificity of 0.50 at the cutoff of 2 capillaries/field with the area under the curve of the receiver operating characteristic value of 0.70, whereas capillary rarefaction at 27-32 weeks of gestation yielded a sensitivity of 0.75 and a higher specificity of 0.77 at the cutoff of 8 capillaries/field with area under the curve of the receiver operating characteristic value of 0.82. Combining capillary rarefaction with uterine artery Doppler pulsatility index increased the sensitivity and specificity of the prediction. Multivariable analysis shows that the odds of preeclampsia are increased in women with previous history of preeclampsia or chronic hypertension and in those with increased uterine artery Doppler pulsatility index, but the most powerful and independent predictor of preeclampsia was capillary rarefaction at 27-32 weeks. Quantifying structural rarefaction of skin capillaries in pregnancy is a potentially useful clinical marker for the prediction of preeclampsia.

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

    PubMed Central

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

    2011-01-01

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

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

    PubMed

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

    2014-08-14

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

  11. Theoretical Prediction of Magnetism in C-doped TlBr

    NASA Astrophysics Data System (ADS)

    Zhou, Yuzhi; Haller, E. E.; Chrzan, D. C.

    2014-05-01

    We predict that C, N, and O dopants in TlBr can display large, localized magnetic moments. Density functional theory based electronic structure calculations show that the moments arise from partial filling of the crystal-field-split localized p states of the dopant atoms. A simple model is introduced to explain the magnitude of the moments.

  12. A transcriptomics data-driven gene space accurately predicts liver cytopathology and drug-induced liver injury

    PubMed Central

    Kohonen, Pekka; Parkkinen, Juuso A.; Willighagen, Egon L.; Ceder, Rebecca; Wennerberg, Krister; Kaski, Samuel; Grafström, Roland C.

    2017-01-01

    Predicting unanticipated harmful effects of chemicals and drug molecules is a difficult and costly task. Here we utilize a ‘big data compacting and data fusion’—concept to capture diverse adverse outcomes on cellular and organismal levels. The approach generates from transcriptomics data set a ‘predictive toxicogenomics space’ (PTGS) tool composed of 1,331 genes distributed over 14 overlapping cytotoxicity-related gene space components. Involving ∼2.5 × 108 data points and 1,300 compounds to construct and validate the PTGS, the tool serves to: explain dose-dependent cytotoxicity effects, provide a virtual cytotoxicity probability estimate intrinsic to omics data, predict chemically-induced pathological states in liver resulting from repeated dosing of rats, and furthermore, predict human drug-induced liver injury (DILI) from hepatocyte experiments. Analysing 68 DILI-annotated drugs, the PTGS tool outperforms and complements existing tests, leading to a hereto-unseen level of DILI prediction accuracy. PMID:28671182

  13. Accurate in silico prediction of species-specific methylation sites based on information gain feature optimization.

    PubMed

    Wen, Ping-Ping; Shi, Shao-Ping; Xu, Hao-Dong; Wang, Li-Na; Qiu, Jian-Ding

    2016-10-15

    As one of the most important reversible types of post-translational modification, protein methylation catalyzed by methyltransferases carries many pivotal biological functions as well as many essential biological processes. Identification of methylation sites is prerequisite for decoding methylation regulatory networks in living cells and understanding their physiological roles. Experimental methods are limitations of labor-intensive and time-consuming. While in silicon approaches are cost-effective and high-throughput manner to predict potential methylation sites, but those previous predictors only have a mixed model and their prediction performances are not fully satisfactory now. Recently, with increasing availability of quantitative methylation datasets in diverse species (especially in eukaryotes), there is a growing need to develop a species-specific predictor. Here, we designed a tool named PSSMe based on information gain (IG) feature optimization method for species-specific methylation site prediction. The IG method was adopted to analyze the importance and contribution of each feature, then select the valuable dimension feature vectors to reconstitute a new orderly feature, which was applied to build the finally prediction model. Finally, our method improves prediction performance of accuracy about 15% comparing with single features. Furthermore, our species-specific model significantly improves the predictive performance compare with other general methylation prediction tools. Hence, our prediction results serve as useful resources to elucidate the mechanism of arginine or lysine methylation and facilitate hypothesis-driven experimental design and validation. The tool online service is implemented by C# language and freely available at http://bioinfo.ncu.edu.cn/PSSMe.aspx CONTACT: jdqiu@ncu.edu.cnSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights

  14. Accurate collision-induced line-coupling parameters for the fundamental band of CO in He - Close coupling and coupled states scattering calculations

    NASA Technical Reports Server (NTRS)

    Green, Sheldon; Boissoles, J.; Boulet, C.

    1988-01-01

    The first accurate theoretical values for off-diagonal (i.e., line-coupling) pressure-broadening cross sections are presented. Calculations were done for CO perturbed by He at thermal collision energies using an accurate ab initio potential energy surface. Converged close coupling, i.e., numerically exact values, were obtained for coupling to the R(0) and R(2) lines. These were used to test the coupled states (CS) and infinite order sudden (IOS) approximate scattering methods. CS was found to be of quantitative accuracy (a few percent) and has been used to obtain coupling values for lines to R(10). IOS values are less accurate, but, owing to their simplicity, may nonetheless prove useful as has been recently demonstrated.

  15. Adaptive learning compressive tracking based on Markov location prediction

    NASA Astrophysics Data System (ADS)

    Zhou, Xingyu; Fu, Dongmei; Yang, Tao; Shi, Yanan

    2017-03-01

    Object tracking is an interdisciplinary research topic in image processing, pattern recognition, and computer vision which has theoretical and practical application value in video surveillance, virtual reality, and automatic navigation. Compressive tracking (CT) has many advantages, such as efficiency and accuracy. However, when there are object occlusion, abrupt motion and blur, similar objects, and scale changing, the CT has the problem of tracking drift. We propose the Markov object location prediction to get the initial position of the object. Then CT is used to locate the object accurately, and the classifier parameter adaptive updating strategy is given based on the confidence map. At the same time according to the object location, extract the scale features, which is able to deal with object scale variations effectively. Experimental results show that the proposed algorithm has better tracking accuracy and robustness than current advanced algorithms and achieves real-time performance.

  16. Propagation studies using a theoretical ionosphere model

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Lee, M.K.

    1973-03-01

    The mid-latitude ionospheric and neutral atmospheric models are coupled with an advanced three dimensional ray-tracing pron predicting the wave propagation conditions and to study to what extent the use of theoretical ionospheric models is practical. The Penn State MK 1 ionospheric model, the Mitra--Rowe D-region model, and the Groves' neutral atmospheric model are used throughout ihis work to represent the real electron densities and collision frequencies. The Faraday rotation and differential Doppler velocities from satellites, the propagation modes for long-distance high-frequency propagation, the group delays for each mode, the ionospheric absorption, and the spatial loss are all predicted. (auth) (STAR)

  17. An Accurate Potential Energy Surface for H2O

    NASA Technical Reports Server (NTRS)

    Schwenke, David W.; Partridge, Harry; Langhoff, Stephen R. (Technical Monitor)

    1997-01-01

    We have carried out extensive high quality ab initio electronic structure calculations of the ground state potential energy surface (PES) and dipole moment function (DMF) for H2O. A small adjustment is made to the PES to improve the agreement of line positions from theory and experiment. The theoretical line positions are obtained from variational ro-vibrational calculations using the exact kinetic energy operator. For the lines being fitted, the root-mean-square error was reduced from 6.9 to 0.08 /cm. We were then able to match 30,092 of the 30,117 lines from the HITRAN 96 data base to theoretical lines, and 80% of the line positions differed less than 0.1 /cm. About 3% of the line positions in the experimental data base appear to be incorrect. Theory predicts the existence of many additional weak lines with intensities above the cutoff used in the data base. To obtain results of similar accuracy for HDO, a mass dependent correction to the PH is introduced and is parameterized by simultaneously fitting line positions for HDO and D2O. The mass dependent PH has good predictive value for T2O and HTO. Nonadiabatic effects are not explicitly included. Line strengths for vibrational bands summed over rotational levels usually agree well between theory and experiment, but individual line strengths can differ greatly. A high temperature line list containing about 380 million lines has been generated using the present PES and DMF

  18. Methods for Efficiently and Accurately Computing Quantum Mechanical Free Energies for Enzyme Catalysis.

    PubMed

    Kearns, F L; Hudson, P S; Boresch, S; Woodcock, H L

    2016-01-01

    Enzyme activity is inherently linked to free energies of transition states, ligand binding, protonation/deprotonation, etc.; these free energies, and thus enzyme function, can be affected by residue mutations, allosterically induced conformational changes, and much more. Therefore, being able to predict free energies associated with enzymatic processes is critical to understanding and predicting their function. Free energy simulation (FES) has historically been a computational challenge as it requires both the accurate description of inter- and intramolecular interactions and adequate sampling of all relevant conformational degrees of freedom. The hybrid quantum mechanical molecular mechanical (QM/MM) framework is the current tool of choice when accurate computations of macromolecular systems are essential. Unfortunately, robust and efficient approaches that employ the high levels of computational theory needed to accurately describe many reactive processes (ie, ab initio, DFT), while also including explicit solvation effects and accounting for extensive conformational sampling are essentially nonexistent. In this chapter, we will give a brief overview of two recently developed methods that mitigate several major challenges associated with QM/MM FES: the QM non-Boltzmann Bennett's acceptance ratio method and the QM nonequilibrium work method. We will also describe usage of these methods to calculate free energies associated with (1) relative properties and (2) along reaction paths, using simple test cases with relevance to enzymes examples. © 2016 Elsevier Inc. All rights reserved.

  19. T-cell epitope prediction and immune complex simulation using molecular dynamics: state of the art and persisting challenges

    PubMed Central

    2010-01-01

    Atomistic Molecular Dynamics provides powerful and flexible tools for the prediction and analysis of molecular and macromolecular systems. Specifically, it provides a means by which we can measure theoretically that which cannot be measured experimentally: the dynamic time-evolution of complex systems comprising atoms and molecules. It is particularly suitable for the simulation and analysis of the otherwise inaccessible details of MHC-peptide interaction and, on a larger scale, the simulation of the immune synapse. Progress has been relatively tentative yet the emergence of truly high-performance computing and the development of coarse-grained simulation now offers us the hope of accurately predicting thermodynamic parameters and of simulating not merely a handful of proteins but larger, longer simulations comprising thousands of protein molecules and the cellular scale structures they form. We exemplify this within the context of immunoinformatics. PMID:21067546

  20. Predicting DNA hybridization kinetics from sequence

    NASA Astrophysics Data System (ADS)

    Zhang, Jinny X.; Fang, John Z.; Duan, Wei; Wu, Lucia R.; Zhang, Angela W.; Dalchau, Neil; Yordanov, Boyan; Petersen, Rasmus; Phillips, Andrew; Zhang, David Yu

    2018-01-01

    Hybridization is a key molecular process in biology and biotechnology, but so far there is no predictive model for accurately determining hybridization rate constants based on sequence information. Here, we report a weighted neighbour voting (WNV) prediction algorithm, in which the hybridization rate constant of an unknown sequence is predicted based on similarity reactions with known rate constants. To construct this algorithm we first performed 210 fluorescence kinetics experiments to observe the hybridization kinetics of 100 different DNA target and probe pairs (36 nt sub-sequences of the CYCS and VEGF genes) at temperatures ranging from 28 to 55 °C. Automated feature selection and weighting optimization resulted in a final six-feature WNV model, which can predict hybridization rate constants of new sequences to within a factor of 3 with ∼91% accuracy, based on leave-one-out cross-validation. Accurate prediction of hybridization kinetics allows the design of efficient probe sequences for genomics research.