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  1. Using Monte Carlo transport to accurately predict isotope production and activation analysis rates at the University of Missouri research reactor

    A detailed Monte Carlo N-Particle Transport Code (MCNP5) model of the University of Missouri research reactor (MURR) has been developed. The ability of the model to accurately predict isotope production rates was verified by comparing measured and calculated neutron- capture reaction rates for numerous isotopes. In addition to thermal (1/v) monitors, the benchmarking included a number of isotopes whose (n, γ) reaction rates are very sensitive to the epithermal portion of the neutron spectrum. Using the most recent neutron libraries (ENDF/ B-VII.0), the model was able to accurately predict the measured reaction rates in all cases. The model was then combined with ORIGEN 2.2, via MONTEBURNS 2.0, to calculate production of 99Mo from fission of low-enriched uranium foils. The model was used to investigate both annular and plate LEU foil targets in a variety of arrangements in a graphite irradiation wedge to optimize the production of 99Mo. (author)

  2. Accurate hydrocarbon estimates attained with radioactive isotope

    To make accurate economic evaluations of new discoveries, an oil company needs to know how much gas and oil a reservoir contains. The porous rocks of these reservoirs are not completely filled with gas or oil, but contain a mixture of gas, oil and water. It is extremely important to know what volume percentage of this water--called connate water--is contained in the reservoir rock. The percentage of connate water can be calculated from electrical resistivity measurements made downhole. The accuracy of this method can be improved if a pure sample of connate water can be analyzed or if the chemistry of the water can be determined by conventional logging methods. Because of the similarity of the mud filtrate--the water in a water-based drilling fluid--and the connate water, this is not always possible. If the oil company cannot distinguish between connate water and mud filtrate, its oil-in-place calculations could be incorrect by ten percent or more. It is clear that unless an oil company can be sure that a sample of connate water is pure, or at the very least knows exactly how much mud filtrate it contains, its assessment of the reservoir's water content--and consequently its oil or gas content--will be distorted. The oil companies have opted for the Repeat Formation Tester (RFT) method. Label the drilling fluid with small doses of tritium--a radioactive isotope of hydrogen--and it will be easy to detect and quantify in the sample

  3. You Can Accurately Predict Land Acquisition Costs.

    Garrigan, Richard

    1967-01-01

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

  4. How accurate can genetic predictions be?

    Dreyfuss Jonathan M

    2012-07-01

    Full Text Available Abstract Background Pre-symptomatic prediction of disease and drug response based on genetic testing is a critical component of personalized medicine. Previous work has demonstrated that the predictive capacity of genetic testing is constrained by the heritability and prevalence of the tested trait, although these constraints have only been approximated under the assumption of a normally distributed genetic risk distribution. Results Here, we mathematically derive the absolute limits that these factors impose on test accuracy in the absence of any distributional assumptions on risk. We present these limits in terms of the best-case receiver-operating characteristic (ROC curve, consisting of the best-case test sensitivities and specificities, and the AUC (area under the curve measure of accuracy. We apply our method to genetic prediction of type 2 diabetes and breast cancer, and we additionally show the best possible accuracy that can be obtained from integrated predictors, which can incorporate non-genetic features. Conclusion Knowledge of such limits is valuable in understanding the implications of genetic testing even before additional associations are identified.

  5. A new, accurate predictive model for incident hypertension

    Völzke, Henry; Fung, Glenn; Ittermann, Till; Yu, Shipeng; Baumeister, Sebastian E; Dörr, Marcus; Lieb, Wolfgang; Völker, Uwe; Linneberg, Allan; Jørgensen, Torben; Felix, Stephan B; Rettig, Rainer; Rao, Bharat; Kroemer, Heyo K

    2013-01-01

    Data mining represents an alternative approach to identify new predictors of multifactorial diseases. This work aimed at building an accurate predictive model for incident hypertension using data mining procedures.......Data mining represents an alternative approach to identify new predictors of multifactorial diseases. This work aimed at building an accurate predictive model for incident hypertension using data mining procedures....

  6. DOMAC: an accurate, hybrid protein domain prediction server

    Cheng, Jianlin

    2007-01-01

    Protein domain prediction is important for protein structure prediction, structure determination, function annotation, mutagenesis analysis and protein engineering. Here we describe an accurate protein domain prediction server (DOMAC) combining both template-based and ab initio methods. The preliminary version of the server was ranked among the top domain prediction servers in the seventh edition of Critical Assessment of Techniques for Protein Structure Prediction (CASP7), 2006. DOMAC server...

  7. Do foraminifera accurately record seawater neodymium isotope composition?

    Scrivner, Adam; Skinner, Luke; Vance, Derek

    2010-05-01

    Palaeoclimate studies involving the reconstruction of past Atlantic meridional overturning circulation increasingly employ isotopes of neodymium (Nd), measured on a variety of sample media (Frank, 2002). In the open ocean, Nd isotopes are a conservative tracer of water mass mixing and are unaffected by biological and low-temperature fractionation processes (Piepgras and Wasserburg, 1987; Lacan and Jeandel, 2005). For decades, benthic foraminifera have been widely utilised in stable isotope and geochemical studies, but have only recently begun to be exploited as a widely distributed, high-resolution Nd isotope archive (Klevenz et al., 2008), potentially circumventing the difficulties associated with other methods used to recover past deep-water Nd isotopes (Klevenz et al., 2008; Rutberg et al., 2000; Tachikawa et al., 2004). Thus far, a single pilot study (Klevenz et al., 2008) has indicated that core-top sedimentary benthic foraminifera record a Nd isotope composition in agreement with the nearest available bottom seawater data, and has suggested that this archive is potentially useful on both millennial and million-year timescales. Here we present seawater and proximal core-top foraminifer Nd isotope data for samples recovered during the 2008 "RETRO" cruise of the Marion Dufresne. The foraminifer samples comprise a depth-transect spanning 3000m of the water column in the Angola Basin and permit a direct comparison between high-resolution water column and core-top foraminiferal Nd isotope data. We use these data to assess the reliability of both planktonic and benthic foraminifera as recorders of water column neodymium isotope composition. Frank, M., 2002. Radiogenic isotopes: Tracers of past ocean circulation and erosional input, Rev. Geophys., 40 (1), 1001, doi:10.1029/2000RG000094. Klevenz, V., Vance, D., Schmidt, D.N., and Mezger, K., 2008. Neodymium isotopes in benthic foraminifera: Core-top systematics and a down-core record from the Neogene south Atlantic

  8. Accurate Multisteps Traffic Flow Prediction Based on SVM

    Zhang Mingheng; Zhen Yaobao; Hui Ganglong; Chen Gang

    2013-01-01

    Accurate traffic flow prediction is prerequisite and important for realizing intelligent traffic control and guidance, and it is also the objective requirement for intelligent traffic management. Due to the strong nonlinear, stochastic, time-varying characteristics of urban transport system, artificial intelligence methods such as support vector machine (SVM) are now receiving more and more attentions in this research field. Compared with the traditional single-step prediction method, the mul...

  9. Accurate Identification of Fear Facial Expressions Predicts Prosocial Behavior

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

    2007-01-01

    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 beha...

  10. Accurate Multisteps Traffic Flow Prediction Based on SVM

    Zhang Mingheng

    2013-01-01

    Full Text Available Accurate traffic flow prediction is prerequisite and important for realizing intelligent traffic control and guidance, and it is also the objective requirement for intelligent traffic management. Due to the strong nonlinear, stochastic, time-varying characteristics of urban transport system, artificial intelligence methods such as support vector machine (SVM are now receiving more and more attentions in this research field. Compared with the traditional single-step prediction method, the multisteps prediction has the ability that can predict the traffic state trends over a certain period in the future. From the perspective of dynamic decision, it is far important than the current traffic condition obtained. Thus, in this paper, an accurate multi-steps traffic flow prediction model based on SVM was proposed. In which, the input vectors were comprised of actual traffic volume and four different types of input vectors were compared to verify their prediction performance with each other. Finally, the model was verified with actual data in the empirical analysis phase and the test results showed that the proposed SVM model had a good ability for traffic flow prediction and the SVM-HPT model outperformed the other three models for prediction.

  11. The isotope effect: Prediction, discussion, and discovery

    Kragh, Helge

    2011-01-01

    The precise position of a spectral line emitted by an atomic system depends on the mass of the atomic nucleus and is therefore different for isotopes belonging to the same element. The possible presence of an isotope effect followed from Bohr's atomic theory of 1913, but it took several years before it was confirmed experimentally. Its early history involves the childhood not only of the quantum atom, but also of the concept of isotopy. Bohr's prediction of the isotope effect was apparently at odds with early attempts to distinguish between isotopes by means of their optical spectra. However, in 1920 the effect was discovered in HCl molecules, which gave rise to a fruitful development in molecular spectroscopy. The first detection of an atomic isotope effect was no less important, as it was by this means that the heavy hydrogen isotope deuterium was discovered in 1932. The early development of isotope spectroscopy illustrates the complex relationship between theory and experiment, and is also instructive with...

  12. Bayesian calibration of power plant models for accurate performance prediction

    Highlights: • Bayesian calibration is applied to power plant performance prediction. • Measurements from a plant in operation are used for model calibration. • A gas turbine performance model and steam cycle model are calibrated. • An integrated plant model is derived. • Part load efficiency is accurately predicted as a function of ambient conditions. - Abstract: Gas turbine combined cycles are expected to play an increasingly important role in the balancing of supply and demand in future energy markets. Thermodynamic modeling of these energy systems is frequently applied to assist in decision making processes related to the management of plant operation and maintenance. In most cases, model inputs, parameters and outputs are treated as deterministic quantities and plant operators make decisions with limited or no regard of uncertainties. As the steady integration of wind and solar energy into the energy market induces extra uncertainties, part load operation and reliability are becoming increasingly important. In the current study, methods are proposed to not only quantify various types of uncertainties in measurements and plant model parameters using measured data, but to also assess their effect on various aspects of performance prediction. The authors aim to account for model parameter and measurement uncertainty, and for systematic discrepancy of models with respect to reality. For this purpose, the Bayesian calibration framework of Kennedy and O’Hagan is used, which is especially suitable for high-dimensional industrial problems. The article derives a calibrated model of the plant efficiency as a function of ambient conditions and operational parameters, which is also accurate in part load. The article shows that complete statistical modeling of power plants not only enhances process models, but can also increases confidence in operational decisions

  13. Passive samplers accurately predict PAH levels in resident crayfish.

    Paulik, L Blair; Smith, Brian W; Bergmann, Alan J; Sower, Greg J; Forsberg, Norman D; Teeguarden, Justin G; Anderson, Kim A

    2016-02-15

    Contamination of resident aquatic organisms is a major concern for environmental risk assessors. However, collecting organisms to estimate risk is often prohibitively time and resource-intensive. Passive sampling accurately estimates resident organism contamination, and it saves time and resources. This study used low density polyethylene (LDPE) passive water samplers to predict polycyclic aromatic hydrocarbon (PAH) levels in signal crayfish, Pacifastacus leniusculus. Resident crayfish were collected at 5 sites within and outside of the Portland Harbor Superfund Megasite (PHSM) in the Willamette River in Portland, Oregon. LDPE deployment was spatially and temporally paired with crayfish collection. Crayfish visceral and tail tissue, as well as water-deployed LDPE, were extracted and analyzed for 62 PAHs using GC-MS/MS. Freely-dissolved concentrations (Cfree) of PAHs in water were calculated from concentrations in LDPE. Carcinogenic risks were estimated for all crayfish tissues, using benzo[a]pyrene equivalent concentrations (BaPeq). ∑PAH were 5-20 times higher in viscera than in tails, and ∑BaPeq were 6-70 times higher in viscera than in tails. Eating only tail tissue of crayfish would therefore significantly reduce carcinogenic risk compared to also eating viscera. Additionally, PAH levels in crayfish were compared to levels in crayfish collected 10years earlier. PAH levels in crayfish were higher upriver of the PHSM and unchanged within the PHSM after the 10-year period. Finally, a linear regression model predicted levels of 34 PAHs in crayfish viscera with an associated R-squared value of 0.52 (and a correlation coefficient of 0.72), using only the Cfree PAHs in water. On average, the model predicted PAH concentrations in crayfish tissue within a factor of 2.4±1.8 of measured concentrations. This affirms that passive water sampling accurately estimates PAH contamination in crayfish. Furthermore, the strong predictive ability of this simple model suggests

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

    Cecilia Noecker

    2015-03-01

    Full Text Available 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

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

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

    2016-05-01

    We assess the predictive accuracy of perturbation theory based estimates of changes in covalent bonding due to linear alchemical interpolations among molecules. We have investigated σ bonding to hydrogen, as well as σ and π bonding between main-group elements, occurring in small sets of iso-valence-electronic molecules with elements drawn from second to fourth rows in the p-block of the periodic table. Numerical evidence suggests that first order Taylor expansions of covalent bonding potentials can achieve high accuracy if (i) the alchemical interpolation is vertical (fixed geometry), (ii) it involves elements from the third and fourth rows of the periodic table, and (iii) an optimal reference geometry is used. This leads to near linear changes in the bonding potential, resulting in analytical predictions with chemical accuracy (˜1 kcal/mol). Second order estimates deteriorate the prediction. If initial and final molecules differ not only in composition but also in geometry, all estimates become substantially worse, with second order being slightly more accurate than first order. The independent particle approximation based second order perturbation theory performs poorly when compared to the coupled perturbed or finite difference approach. Taylor series expansions up to fourth order of the potential energy curve of highly symmetric systems indicate a finite radius of convergence, as illustrated for the alchemical stretching of H 2+ . Results are presented for (i) covalent bonds to hydrogen in 12 molecules with 8 valence electrons (CH4, NH3, H2O, HF, SiH4, PH3, H2S, HCl, GeH4, AsH3, H2Se, HBr); (ii) main-group single bonds in 9 molecules with 14 valence electrons (CH3F, CH3Cl, CH3Br, SiH3F, SiH3Cl, SiH3Br, GeH3F, GeH3Cl, GeH3Br); (iii) main-group double bonds in 9 molecules with 12 valence electrons (CH2O, CH2S, CH2Se, SiH2O, SiH2S, SiH2Se, GeH2O, GeH2S, GeH2Se); (iv) main-group triple bonds in 9 molecules with 10 valence electrons (HCN, HCP, HCAs, HSiN, HSi

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

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

    2016-05-01

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

  17. Newtonian Kinetic Isotope Effects. Observation, Prediction, and Origin of Heavy-Atom Dynamic Isotope Effects

    Kelly, Kelmara K.; Hirschi, Jennifer S.; Singleton, Daniel A.

    2009-01-01

    Intramolecular 13C kinetic isotope effects were determined for the dimerization of cyclopentadiene. Substantial isotope effects were observed in three positions, despite the C2 symmetry of the cycloaddition transition state and the absence of dynamical bottlenecks after this transition state. The observed isotope effects were predicted well from trajectory studies by extrapolating the outcomes of trajectories incorporating superheavy isotopes of carbon, ranging from 20C to 140C. Trajectory st...

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

    Xin Deng

    2015-07-01

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

  19. Accurate determination of the 235U isotope abundance by gamma spectrometry

    The purpose of this manual is to serve as guide in applications of the Certified Reference Material EC-NRM-171/NBS-SRM-969 for accurate U-235 isotope abundance measurements on bulk uranium samples by means of gamma spectrometry. The manual provides a thorough description of this non-destructive assay technique. Crucial measurement parameters affecting the accuracy of the gamma-spectrometric U-235 isotope abundance determination are discussed in detail and, whereever possible, evaluated quantitatively. The correction terms and tolerance limits given refer both to physical and chemical properties of the samples under assay and to relevant parameters of typical measurement systems such as counting geometry, signal processing, data evaluation and calibration. (orig.)

  20. Accurate contact predictions using covariation techniques and machine learning.

    Kosciolek, T.; Jones, D T

    2015-01-01

    Here we present the results of residue-residue contact predictions achieved in CASP11 by the CONSIP2 server, which is based around our MetaPSICOV contact prediction method. On a set of 40 target domains with a median family size of around 40 effective sequences, our server achieved an average top-L/5 long-range contact precision of 27%. MetaPSICOV method bases on a combination of classical contact prediction features, enhanced with three distinct covariation methods embedded in a two-stage ne...

  1. Mouse models of human AML accurately predict chemotherapy response

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

    2009-01-01

    The genetic heterogeneity of cancer influences the trajectory of tumor progression and may underlie clinical variation in therapy response. To model such heterogeneity, we produced genetically and pathologically accurate mouse models of common forms of human acute myeloid leukemia (AML) and developed methods to mimic standard induction chemotherapy and efficiently monitor therapy response. We see that murine AMLs harboring two common human AML genotypes show remarkably diverse responses to co...

  2. Final Progress Report: Isotope Identification Algorithm for Rapid and Accurate Determination of Radioisotopes Feasibility Study

    Rawool-Sullivan, Mohini [Los Alamos National Laboratory; Bounds, John Alan [Los Alamos National Laboratory; Brumby, Steven P. [Los Alamos National Laboratory; Prasad, Lakshman [Los Alamos National Laboratory; Sullivan, John P. [Los Alamos National Laboratory

    2012-04-30

    This is the final report of the project titled, 'Isotope Identification Algorithm for Rapid and Accurate Determination of Radioisotopes,' PMIS project number LA10-HUMANID-PD03. The goal of the work was to demonstrate principles of emulating a human analysis approach towards the data collected using radiation isotope identification devices (RIIDs). It summarizes work performed over the FY10 time period. The goal of the work was to demonstrate principles of emulating a human analysis approach towards the data collected using radiation isotope identification devices (RIIDs). Human analysts begin analyzing a spectrum based on features in the spectrum - lines and shapes that are present in a given spectrum. The proposed work was to carry out a feasibility study that will pick out all gamma ray peaks and other features such as Compton edges, bremsstrahlung, presence/absence of shielding and presence of neutrons and escape peaks. Ultimately success of this feasibility study will allow us to collectively explain identified features and form a realistic scenario that produced a given spectrum in the future. We wanted to develop and demonstrate machine learning algorithms that will qualitatively enhance the automated identification capabilities of portable radiological sensors that are currently being used in the field.

  3. Towards more accurate and reliable predictions for nuclear applications

    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. In the present contribution, the reliability and accuracy of recent nuclear theories are discussed for most of the relevant quantities needed to estimate reaction cross sections and beta-decay rates, namely nuclear masses, nuclear level densities, gamma-ray strength, fission properties and beta-strength functions. It is shown that 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 phenomenogical inputs in the prediction of nuclear data. While fundamental nuclear physicists keep on improving state-of-the-art models, e.g. within the shell model or ab initio models, nuclear applications could make use of their most recent results as quantitative constraints or guides to improve the predictions in energy or mass domain that will remain inaccessible experimentally. (orig.)

  4. Accurate determination and certification of bromine in plastic by isotope dilution inductively coupled plasma mass spectrometry

    Highlights: • Accurate analytical method of Br in plastic was studied by isotope dilution ICPMS. • A microwave acid digestion using quartz vessel was suitable for Br analysis. • Sample dilution by NH3 solution could remove memory effect for ICPMS measurement. • The analytical result of the ID-ICPMS showed consistency with that of INAA. • The ID-ICPMS developed could apply to certification of Br in candidate plastic CRM. - Abstract: The accurate analytical method of bromine (Br) in plastic was developed by an isotope dilution inductively coupled plasma mass spectrometry (ID-ICPMS). The figures of merit of microwave acid digestion procedures using polytetrafluoroethylene (PTFE) or quartz vessels were studied and the latter one was suitable for Br analysis since its material was free from Br contamination. The sample dilution procedures using Milli-Q water or ammonium (NH3) solution were also studied to remove memory effect for ICPMS measurement. Although severe memory effect was observed on Milli-Q water dilution, NH3 solution could remove it successfully. The accuracy of the ID-ICPMS was validated by a certified reference material (CRM) as well as the comparison with the analytical result obtained by an instrumental neutron activation analysis (INAA) as different analytical method. From these results, the ID-ICPMS developed in the present study could be evaluated as accurate analytical method of Br in plastic materials and it could apply to certification of Br in candidate plastic CRM with respect to such regulations related to RoHS (restriction of the use of hazardous substances in electrical and electronics equipment) directive

  5. Accurate determination and certification of bromine in plastic by isotope dilution inductively coupled plasma mass spectrometry

    Ohata, Masaki, E-mail: m-oohata@aist.go.jp; Miura, Tsutomu

    2014-07-21

    Highlights: • Accurate analytical method of Br in plastic was studied by isotope dilution ICPMS. • A microwave acid digestion using quartz vessel was suitable for Br analysis. • Sample dilution by NH{sub 3} solution could remove memory effect for ICPMS measurement. • The analytical result of the ID-ICPMS showed consistency with that of INAA. • The ID-ICPMS developed could apply to certification of Br in candidate plastic CRM. - Abstract: The accurate analytical method of bromine (Br) in plastic was developed by an isotope dilution inductively coupled plasma mass spectrometry (ID-ICPMS). The figures of merit of microwave acid digestion procedures using polytetrafluoroethylene (PTFE) or quartz vessels were studied and the latter one was suitable for Br analysis since its material was free from Br contamination. The sample dilution procedures using Milli-Q water or ammonium (NH{sub 3}) solution were also studied to remove memory effect for ICPMS measurement. Although severe memory effect was observed on Milli-Q water dilution, NH{sub 3} solution could remove it successfully. The accuracy of the ID-ICPMS was validated by a certified reference material (CRM) as well as the comparison with the analytical result obtained by an instrumental neutron activation analysis (INAA) as different analytical method. From these results, the ID-ICPMS developed in the present study could be evaluated as accurate analytical method of Br in plastic materials and it could apply to certification of Br in candidate plastic CRM with respect to such regulations related to RoHS (restriction of the use of hazardous substances in electrical and electronics equipment) directive.

  6. Standardized EEG interpretation accurately predicts prognosis after cardiac arrest

    Rossetti, Andrea O.; van Rootselaar, Anne-Fleur; Wesenberg Kjaer, Troels; Horn, Janneke; Ullén, Susann; Friberg, Hans; Nielsen, Niklas; Rosén, Ingmar; Åneman, Anders; Erlinge, David; Gasche, Yvan; Hassager, Christian; Hovdenes, Jan; Kjaergaard, Jesper; Kuiper, Michael; Pellis, Tommaso; Stammet, Pascal; Wanscher, Michael; Wetterslev, Jørn; Wise, Matt P.; Cronberg, Tobias

    2016-01-01

    Objective: To identify reliable predictors of outcome in comatose patients after cardiac arrest using a single routine EEG and standardized interpretation according to the terminology proposed by the American Clinical Neurophysiology Society. Methods: In this cohort study, 4 EEG specialists, blinded to outcome, evaluated prospectively recorded EEGs in the Target Temperature Management trial (TTM trial) that randomized patients to 33°C vs 36°C. Routine EEG was performed in patients still comatose after rewarming. EEGs were classified into highly malignant (suppression, suppression with periodic discharges, burst-suppression), malignant (periodic or rhythmic patterns, pathological or nonreactive background), and benign EEG (absence of malignant features). Poor outcome was defined as best Cerebral Performance Category score 3–5 until 180 days. Results: Eight TTM sites randomized 202 patients. EEGs were recorded in 103 patients at a median 77 hours after cardiac arrest; 37% had a highly malignant EEG and all had a poor outcome (specificity 100%, sensitivity 50%). Any malignant EEG feature had a low specificity to predict poor prognosis (48%) but if 2 malignant EEG features were present specificity increased to 96% (p < 0.001). Specificity and sensitivity were not significantly affected by targeted temperature or sedation. A benign EEG was found in 1% of the patients with a poor outcome. Conclusions: Highly malignant EEG after rewarming reliably predicted poor outcome in half of patients without false predictions. An isolated finding of a single malignant feature did not predict poor outcome whereas a benign EEG was highly predictive of a good outcome. PMID:26865516

  7. Analytical method to accurately predict LMFBR core flow distribution

    An accurate and detailed representation of the flow distribution in LMFBR cores is very important as the starting point and basis of the thermal and structural core design. Previous experience indicated that the steady state and transient core design is as good as the core orificing; thus, a new orificing philosophy satisfying a priori all design constraints was developd. However, optimized orificing is a necessary, but not sufficient condition for achieving the optimum core flow distribution, which is affected by the hydraulic characteristics of the remainder of the primary system. Consequently, an analytical model of the overall primary system was developed, resulting in the CATFISH computer code, which, even though specifically written for LMFBRs, can be used for any reactor employing ducted assemblies

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

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

    2015-01-01

    We assess the predictive accuracy of perturbation theory based estimates of changes in covalent bonding due to linear alchemical interpolations among molecules. We have investigated $\\sigma$ bonding to hydrogen, as well as $\\sigma$ and $\\pi$ bonding between main-group elements, occurring in small sets of iso-valence-electronic molecular species with elements drawn from second to fourth rows in the $p$-block of the periodic table. Numerical evidence suggests that first order estimates of coval...

  9. Copeptin does not accurately predict disease severity in imported malaria

    van Wolfswinkel Marlies E

    2012-01-01

    Full Text Available Abstract Background Copeptin has recently been identified to be a stable surrogate marker for the unstable hormone arginine vasopressin (AVP. Copeptin has been shown to correlate with disease severity in leptospirosis and bacterial sepsis. Hyponatraemia is common in severe imported malaria and dysregulation of AVP release has been hypothesized as an underlying pathophysiological mechanism. The aim of the present study was to evaluate the performance of copeptin as a predictor of disease severity in imported malaria. Methods Copeptin was measured in stored serum samples of 204 patients with imported malaria that were admitted to our Institute for Tropical Diseases in Rotterdam in the period 1999-2010. The occurrence of WHO defined severe malaria was the primary end-point. The diagnostic performance of copeptin was compared to that of previously evaluated biomarkers C-reactive protein, procalcitonin, lactate and sodium. Results Of the 204 patients (141 Plasmodium falciparum, 63 non-falciparum infection, 25 had severe malaria. The Area Under the ROC curve of copeptin for severe disease (0.66 [95% confidence interval 0.59-0.72] was comparable to that of lactate, sodium and procalcitonin. C-reactive protein (0.84 [95% CI 0.79-0.89] had a significantly better performance as a biomarker for severe malaria than the other biomarkers. Conclusions C-reactive protein but not copeptin was found to be an accurate predictor for disease severity in imported malaria. The applicability of copeptin as a marker for severe malaria in clinical practice is limited to exclusion of severe malaria.

  10. Accurate theoretical prediction on positron lifetime of bulk materials

    Zhang, Wenshuai; Liu, Jiandang; Ye, Bangjiao

    2015-01-01

    Based on the first-principles calculations, we perform an initiatory statistical assessment on the reliability level of theoretical positron lifetime of bulk material. We found the original generalized gradient approximation (GGA) form of the enhancement factor and correlation potentials overestimates the effect of the gradient factor. Furthermore, an excellent agreement between model and data with the difference being the noise level of the data is found in this work. In addition, we suggest a new GGA form of the correlation scheme which gives the best performance. This work demonstrates that a brand-new reliability level is achieved for the theoretical prediction on positron lifetime of bulk material and the accuracy of the best theoretical scheme can be independent on the type of materials.

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

    Rahman O Oloritun

    Full Text Available Research has mostly focused on obesity and not on processes of BMI change more generally, although these may be key factors that lead to obesity. Studies have suggested that obesity is affected by social ties. However these studies used survey based data collection techniques that may be biased toward select only close friends and relatives. In this study, mobile phone sensing techniques were used to routinely capture social interaction data in an undergraduate dorm. By automating the capture of social interaction data, the limitations of self-reported social exposure data are avoided. This study attempts to understand and develop a model that best describes the change in BMI using social interaction data. We evaluated a cohort of 42 college students in a co-located university dorm, automatically captured via mobile phones and survey based health-related information. We determined the most predictive variables for change in BMI using the least absolute shrinkage and selection operator (LASSO method. The selected variables, with gender, healthy diet category, and ability to manage stress, were used to build multiple linear regression models that estimate the effect of exposure and individual factors on change in BMI. We identified the best model using Akaike Information Criterion (AIC and R(2. This study found a model that explains 68% (p<0.0001 of the variation in change in BMI. The model combined social interaction data, especially from acquaintances, and personal health-related information to explain change in BMI. This is the first study taking into account both interactions with different levels of social interaction and personal health-related information. Social interactions with acquaintances accounted for more than half the variation in change in BMI. This suggests the importance of not only individual health information but also the significance of social interactions with people we are exposed to, even people we may not consider as

  12. Predicting accurate line shape parameters for CO2 transitions

    The vibrational dependence of CO2 half-widths and line shifts are given by a modification of the model proposed by Gamache and Hartmann [Gamache R, Hartmann J-M. J Quant Spectrosc Radiat Transfer 2004;83:119]. This model allows the half-widths and line shifts for a ro-vibrational transition to be expressed in terms of the number of vibrational quanta exchanged in the transition raised to a power and a reference ro-vibrational transition. Calculations were made for 24 bands for lower rotational quantum numbers from 0 to 160 for N2-, O2-, air-, and self-collisions with CO2. These data were extrapolated to J″=200 to accommodate several databases. Comparison of the CRB calculations with measurement gives very high confidence in the data. In the model a Quantum Coordinate is defined by (c1 |Δν1|+c2 |Δν2|+c3|Δν3|)p. The power p is adjusted and a linear least-squares fit to the data by the model expression is made. The procedure is iterated on the correlation coefficient, R, until [|R|−1] is less than a threshold. The results demonstrate the appropriateness of the model. The model allows the determination of the slope and intercept as a function of rotational transition, broadening gas, and temperature. From the data of the fits, the half-width, line shift, and the temperature dependence of the half-width can be estimated for any ro-vibrational transition, allowing spectroscopic CO2 databases to have complete information for the line shape parameters. -- Highlights: • Development of a quantum coordinate model for the half-width and line shift. • Calculations of γ and δ for N2-, O2-, air-, and CO2–CO2 systems for 24 bands. • J″=0–160, bands up to Δν1=3, Δν2=5, Δν3=9, 9 temperatures from 200–2000 K. • γ, n, δ, prediction routines for all ro-vibrational transitions up to J″=200

  13. Fast and accurate dating of nuclear events using La-140/Ba-140 isotopic activity ratio.

    Yamba, Kassoum; Sanogo, Oumar; Kalinowski, Martin B; Nikkinen, Mika; Koulidiati, Jean

    2016-06-01

    This study reports on a fast and accurate assessment of zero time of certain nuclear events using La-140/Ba-140 isotopic activity ratio. For a non-steady nuclear fission reaction, the dating is not possible. For the hypothesis of a nuclear explosion and for a release from a steady state nuclear fission reaction the zero-times will differ. This assessment is fast, because we propose some constants that can be used directly for the calculation of zero time and its upper and lower age limits. The assessment is accurate because of the calculation of zero time using a mathematical method, namely the weighted least-squares method, to evaluate an average value of the age of a nuclear event. This was done using two databases that exhibit differences between the values of some nuclear parameters. As an example, the calculation method is applied for the detection of radionuclides La-140 and Ba-140 in May 2010 at the radionuclides station JPP37 (Okinawa Island, Japan). PMID:27058322

  14. Predicting the isotopic ratio of western European Precipitation using an isotope trajectory model

    Full text: Spatial and seasonal variations of isotopic ratios in precipitation across Western Europe are well documented. Locations of moisture uptake, transport pathways, condensation temperatures, and surface temperatures at source region and precipitation location all influence the water isotope cycle. Isotope cycle modelling has been included in Global Circulation Models (GCMs) in order to model all of the controlling factors. However, the relative importance of each of these processes remains unclear due to the difficulties in decoupling these processes in GCMs. A combination of a Lagrangian Particle Dispersion Model and an extended Rayleigh distillation theory model allows the effects of different atmospheric processes on isotopic fractionation to be investigated. This method has previously been used to model precipitation in Antarctica and Greenland with excellent results. However, there are added complications involved when modelling rainfall rather than snowfall, such as isotopic re-equilibration between falling raindrops and the surrounding water vapour. Lower latitude locations also experience more evaporation and re-evaporation along the path of a moist air parcel, increasing opportunities for fractionation. These models have been used to predict the hydrogen and oxygen isotope ratios of rainfall in the U.K and Ireland. The model results have been compared with measured isotopic data from daily rainfall samples in order to test how the modelled processes interact. A case study is presented which incorporates observed data collected throughout November 2005 at stations in Norwich, Birmingham and Dublin, together with the corresponding temporal model predictions at these localities. (author)

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

    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

  16. Improve accuracy and sensibility in glycan structure prediction by matching glycan isotope abundance

    Highlights: ► A glycan isotope pattern recognition strategy for glycomics. ► A new data preprocessing procedure to detect ion peaks in a giving MS spectrum. ► A linear soft margin SVM classification for isotope pattern recognition. - Abstract: Mass Spectrometry (MS) is a powerful technique for the determination of glycan structures and is capable of providing qualitative and quantitative information. Recent development in computational method offers an opportunity to use glycan structure databases and de novo algorithms for extracting valuable information from MS or MS/MS data. However, detecting low-intensity peaks that are buried in noisy data sets is still a challenge and an algorithm for accurate prediction and annotation of glycan structures from MS data is highly desirable. The present study describes a novel algorithm for glycan structure prediction by matching glycan isotope abundance (mGIA), which takes isotope masses, abundances, and spacing into account. We constructed a comprehensive database containing 808 glycan compositions and their corresponding isotope abundance. Unlike most previously reported methods, not only did we take into count the m/z values of the peaks but also their corresponding logarithmic Euclidean distance of the calculated and detected isotope vectors. Evaluation against a linear classifier, obtained by training mGIA algorithm with datasets of three different human tissue samples from Consortium for Functional Glycomics (CFG) in association with Support Vector Machine (SVM), was proposed to improve the accuracy of automatic glycan structure annotation. In addition, an effective data preprocessing procedure, including baseline subtraction, smoothing, peak centroiding and composition matching for extracting correct isotope profiles from MS data was incorporated. The algorithm was validated by analyzing the mouse kidney MS data from CFG, resulting in the identification of 6 more glycan compositions than the previous annotation

  17. Improve accuracy and sensibility in glycan structure prediction by matching glycan isotope abundance

    Xu Guang [College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan (China); National Research Council Canada, Ottawa, Ont., K1A 0R6 (Canada); Liu Xin [College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan (China); Liu Qingyan [National Research Council Canada, Ottawa, Ont., Canada K1A 0R6 (Canada); Zhou Yanhong, E-mail: yhzhou@mail.hust.edu.cn [College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan (China); Li Jianjun, E-mail: Jianjun.Li@nrc-cnrc.gc.ca [National Research Council Canada, Ottawa, Ont., Canada K1A 0R6 (Canada)

    2012-09-19

    Highlights: Black-Right-Pointing-Pointer A glycan isotope pattern recognition strategy for glycomics. Black-Right-Pointing-Pointer A new data preprocessing procedure to detect ion peaks in a giving MS spectrum. Black-Right-Pointing-Pointer A linear soft margin SVM classification for isotope pattern recognition. - Abstract: Mass Spectrometry (MS) is a powerful technique for the determination of glycan structures and is capable of providing qualitative and quantitative information. Recent development in computational method offers an opportunity to use glycan structure databases and de novo algorithms for extracting valuable information from MS or MS/MS data. However, detecting low-intensity peaks that are buried in noisy data sets is still a challenge and an algorithm for accurate prediction and annotation of glycan structures from MS data is highly desirable. The present study describes a novel algorithm for glycan structure prediction by matching glycan isotope abundance (mGIA), which takes isotope masses, abundances, and spacing into account. We constructed a comprehensive database containing 808 glycan compositions and their corresponding isotope abundance. Unlike most previously reported methods, not only did we take into count the m/z values of the peaks but also their corresponding logarithmic Euclidean distance of the calculated and detected isotope vectors. Evaluation against a linear classifier, obtained by training mGIA algorithm with datasets of three different human tissue samples from Consortium for Functional Glycomics (CFG) in association with Support Vector Machine (SVM), was proposed to improve the accuracy of automatic glycan structure annotation. In addition, an effective data preprocessing procedure, including baseline subtraction, smoothing, peak centroiding and composition matching for extracting correct isotope profiles from MS data was incorporated. The algorithm was validated by analyzing the mouse kidney MS data from CFG, resulting in the

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

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

    2016-08-01

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

  19. A highly accurate predictive-adaptive method for lithium-ion battery remaining discharge energy prediction in electric vehicle applications

    Highlights: • An energy prediction (EP) method is introduced for battery ERDE determination. • EP determines ERDE through coupled prediction of future states, parameters, and output. • The PAEP combines parameter adaptation and prediction to update model parameters. • The PAEP provides improved ERDE accuracy compared with DC and other EP methods. - Abstract: In order to estimate the remaining driving range (RDR) in electric vehicles, the remaining discharge energy (ERDE) of the applied battery system needs to be precisely predicted. Strongly affected by the load profiles, the available ERDE varies largely in real-world applications and requires specific determination. However, the commonly-used direct calculation (DC) method might result in certain energy prediction errors by relating the ERDE directly to the current state of charge (SOC). To enhance the ERDE accuracy, this paper presents a battery energy prediction (EP) method based on the predictive control theory, in which a coupled prediction of future battery state variation, battery model parameter change, and voltage response, is implemented on the ERDE prediction horizon, and the ERDE is subsequently accumulated and real-timely optimized. Three EP approaches with different model parameter updating routes are introduced, and the predictive-adaptive energy prediction (PAEP) method combining the real-time parameter identification and the future parameter prediction offers the best potential. Based on a large-format lithium-ion battery, the performance of different ERDE calculation methods is compared under various dynamic profiles. Results imply that the EP methods provide much better accuracy than the traditional DC method, and the PAEP could reduce the ERDE error by more than 90% and guarantee the relative energy prediction error under 2%, proving as a proper choice in online ERDE prediction. The correlation of SOC estimation and ERDE calculation is then discussed to illustrate the importance of an

  20. Accurate measurement of neodymium isotopic composition using Neptune MC-ICP-MS

    Yueheng YANG; Hongfu ZHANG; Liewen XIE; Fuyuan WU

    2008-01-01

    This paper reports the measurement of the Neodymium isotopic composition by Neptune Multiple Collector Inductively Coupled Plasma Mass Spectrometry (MC-ICP-MS) over the last two years. Although there is concomitant Cerium in the chemical separation process, this has no significant influence on the Neodymium analysis. As for the sample containing small amounts of Samarium (Sm/Nd<0.04), direct calibration for isobaric interference and mass discrimina-tion by the exponential law can be obtained by assuming that Samarium mass discrimination is the same as that of Neodymium. Geological samples after traditional chemi-cal separation were measured by Neptune MC-ICP-MS and Thermal Ionization Mass Spectrometry (TIMS) respectively. The results show that Neptune MC-ICP-MS can measure Neodymium isotopic composition as precisely the TIMS does and is even more effective and less time-consuming than the TIMS Method.

  1. Hash: a program to accurately predict protein H{sup {alpha}} shifts from neighboring backbone shifts

    Zeng Jianyang, E-mail: zengjy@gmail.com [Tsinghua University, Institute for Interdisciplinary Information Sciences (China); Zhou Pei [Duke University Medical Center, Department of Biochemistry (United States); Donald, Bruce Randall [Duke University, Department of Computer Science (United States)

    2013-01-15

    Chemical shifts provide not only peak identities for analyzing nuclear magnetic resonance (NMR) data, but also an important source of conformational information for studying protein structures. Current structural studies requiring H{sup {alpha}} chemical shifts suffer from the following limitations. (1) For large proteins, the H{sup {alpha}} chemical shifts can be difficult to assign using conventional NMR triple-resonance experiments, mainly due to the fast transverse relaxation rate of C{sup {alpha}} that restricts the signal sensitivity. (2) Previous chemical shift prediction approaches either require homologous models with high sequence similarity or rely heavily on accurate backbone and side-chain structural coordinates. When neither sequence homologues nor structural coordinates are available, we must resort to other information to predict H{sup {alpha}} chemical shifts. Predicting accurate H{sup {alpha}} chemical shifts using other obtainable information, such as the chemical shifts of nearby backbone atoms (i.e., adjacent atoms in the sequence), can remedy the above dilemmas, and hence advance NMR-based structural studies of proteins. By specifically exploiting the dependencies on chemical shifts of nearby backbone atoms, we propose a novel machine learning algorithm, called Hash, to predict H{sup {alpha}} chemical shifts. Hash combines a new fragment-based chemical shift search approach with a non-parametric regression model, called the generalized additive model, to effectively solve the prediction problem. We demonstrate that the chemical shifts of nearby backbone atoms provide a reliable source of information for predicting accurate H{sup {alpha}} chemical shifts. Our testing results on different possible combinations of input data indicate that Hash has a wide rage of potential NMR applications in structural and biological studies of proteins.

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

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

    2016-02-18

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

  3. Rapid yet accurate first principle based predictions of alkali halide crystal phases using alchemical perturbation

    Solovyeva, Alisa

    2016-01-01

    We assess the predictive power of alchemical perturbations for estimating fundamental properties in ionic crystals. Using density functional theory we have calculated formation energies, lattice constants, and bulk moduli for all sixteen iso-valence-electronic combinations of pure pristine alkali halides involving elements $A \\in \\{$Na, K, Rb, Cs$\\}$ and $X \\in \\{$F, Cl, Br, I$\\}$. For rock salt, zincblende and cesium chloride symmetry, alchemical Hellmann-Feynman derivatives, evaluated along lattice scans of sixteen reference crystals, have been obtained for all respective 16$\\times$15 combinations of reference and predicted target crystals. Mean absolute errors (MAE) are on par with density functional theory level of accuracy for energies and bulk modulus. Predicted lattice constants are less accurate. NaCl is the best reference salt for alchemical estimates of relative energies (MAE $<$ 40 meV/atom) while alkali fluorides are the worst. By contrast, lattice constants are predicted best using NaF as a re...

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

    Gregory A Ross

    Full Text Available 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.

  5. Accurate mass measurements of short-lived isotopes with the MISTRAL rf spectrometer

    Toader, C F; Borcea, C; Doubre, H; Duma, M; Jacotin, M; Henry, S; Képinski, J F; Lebée, G; Le Scornet, G; Lunney, M D; Monsanglant, C; De Saint-Simon, M; Thibault, C

    1999-01-01

    The MISTRAL experiment has measured its first masses at ISOLDE. Installed in May 1997, this radiofrequency transmission spectrometer is to concentrate on nuclides with particularly short half-lives. MISTRAL received its first stable beam in October and first radioactive beam in November 1997. These first tests, with a plasma ion source, resulted in excellent isobaric separation and reasonable transmission. Further testing and development enabled first data taking in July 1998 on neutron-rich Na isotopes having half-lives as short as 31 ms.

  6. Can serum isotope levels accurately measure intestinal calcium absorption compared to gold-standard methods?

    Vreede, Andrew P; Jones, Andrea N; Hansen, Karen E

    2015-01-01

    Background Low fractional calcium absorption (FCA) contributes to osteoporosis but is not measured clinically, as the gold-standard method requires administration of two calcium tracers and a subsequent 24-h urine collection. We evaluated alternate methods to measure FCA, compared to the gold standard method. Methods We administered two stable calcium isotope tracers (~8 mg oral 44Ca and ~3 mg intravenous 42Ca) with breakfast to 20 fasting post-menopausal women (Cohort 1) 59 ± 7 years old wit...

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

    Chris A Kieslich

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

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

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

    2016-01-01

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

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

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

    2016-06-01

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

  10. An accurate model for numerical prediction of piezoelectric energy harvesting from fluid structure interaction problems

    Piezoelectric energy harvesting (PEH) from ambient energy sources, particularly vibrations, has attracted considerable interest throughout the last decade. Since fluid flow has a high energy density, it is one of the best candidates for PEH. Indeed, a piezoelectric energy harvesting process from the fluid flow takes the form of natural three-way coupling of the turbulent fluid flow, the electromechanical effect of the piezoelectric material and the electrical circuit. There are some experimental and numerical studies about piezoelectric energy harvesting from fluid flow in literatures. Nevertheless, accurate modeling for predicting characteristics of this three-way coupling has not yet been developed. In the present study, accurate modeling for this triple coupling is developed and validated by experimental results. A new code based on this modeling in an openFOAM platform is developed. (paper)

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

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

    2004-12-01

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

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

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

  13. Development and Validation of a Multidisciplinary Tool for Accurate and Efficient Rotorcraft Noise Prediction (MUTE)

    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.

  14. LogGPO: An accurate communication model for performance prediction of MPI programs

    CHEN WenGuang; ZHAI JiDong; ZHANG Jin; ZHENG WeiMin

    2009-01-01

    Message passing interface (MPI) is the de facto standard in writing parallel scientific applications on distributed memory systems. Performance prediction of MPI programs on current or future parallel sys-terns can help to find system bottleneck or optimize programs. To effectively analyze and predict per-formance of a large and complex MPI program, an efficient and accurate communication model is highly needed. A series of communication models have been proposed, such as the LogP model family, which assume that the sending overhead, message transmission, and receiving overhead of a communication is not overlapped and there is a maximum overlap degree between computation and communication. However, this assumption does not always hold for MPI programs because either sending or receiving overhead introduced by MPI implementations can decrease potential overlap for large messages. In this paper, we present a new communication model, named LogGPO, which captures the potential overlap between computation with communication of MPI programs. We design and implement a trace-driven simulator to verify the LogGPO model by predicting performance of point-to-point communication and two real applications CG and Sweep3D. The average prediction errors of LogGPO model are 2.4% and 2.0% for these two applications respectively, while the average prediction errors of LogGP model are 38.3% and 9.1% respectively.

  15. Microstructure-Dependent Gas Adsorption: Accurate Predictions of Methane Uptake in Nanoporous Carbons

    Ihm, Yungok [University of Tennessee (UTK) and Oak Ridge National Laboratory (ORNL); Cooper, Valentino R [ORNL; Gallego, Nidia C [ORNL; Contescu, Cristian I [ORNL; Morris, James R [ORNL

    2014-01-01

    We demonstrate a successful, efficient framework for predicting gas adsorption properties in real materials based on first-principles calculations, with a specific comparison of experiment and theory for methane adsorption in activated carbons. These carbon materials have different pore size distributions, leading to a variety of uptake characteristics. Utilizing these distributions, we accurately predict experimental uptakes and heats of adsorption without empirical potentials or lengthy simulations. We demonstrate that materials with smaller pores have higher heats of adsorption, leading to a higher gas density in these pores. This pore-size dependence must be accounted for, in order to predict and understand the adsorption behavior. The theoretical approach combines: (1) ab initio calculations with a van der Waals density functional to determine adsorbent-adsorbate interactions, and (2) a thermodynamic method that predicts equilibrium adsorption densities by directly incorporating the calculated potential energy surface in a slit pore model. The predicted uptake at P=20 bar and T=298 K is in excellent agreement for all five activated carbon materials used. This approach uses only the pore-size distribution as an input, with no fitting parameters or empirical adsorbent-adsorbate interactions, and thus can be easily applied to other adsorbent-adsorbate combinations.

  16. The MIDAS touch for Accurately Predicting the Stress-Strain Behavior of Tantalum

    Jorgensen, S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2016-03-02

    Testing the behavior of metals in extreme environments is not always feasible, so material scientists use models to try and predict the behavior. To achieve accurate results it is necessary to use the appropriate model and material-specific parameters. This research evaluated the performance of six material models available in the MIDAS database [1] to determine at which temperatures and strain-rates they perform best, and to determine to which experimental data their parameters were optimized. Additionally, parameters were optimized for the Johnson-Cook model using experimental data from Lassila et al [2].

  17. An accurate and efficient numerical framework for adaptive numerical weather prediction

    Tumolo, G

    2014-01-01

    We present an accurate and efficient discretization approach for the adaptive discretization of typical model equations employed in numerical weather prediction. A semi-Lagrangian approach is combined with the TR-BDF2 semi-implicit time discretization method and with a spatial discretization based on adaptive discontinuous finite elements. The resulting method has full second order accuracy in time and can employ polynomial bases of arbitrarily high degree in space, is unconditionally stable and can effectively adapt the number of degrees of freedom employed in each element, in order to balance accuracy and computational cost. The p-adaptivity approach employed does not require remeshing, therefore it is especially suitable for applications, such as numerical weather prediction, in which a large number of physical quantities are associated with a given mesh. Furthermore, although the proposed method can be implemented on arbitrary unstructured and nonconforming meshes, even its application on simple Cartesian...

  18. Accurate measurements of 129I concentration by isotope dilution using MC-ICPMS for half-life determination

    Determining the 129I concentration, a long-lived radionuclide present in spent nuclear fuel, is a major issue for nuclear waste disposal purpose. 129I also has to be measured in numerous environmental, nuclear and biological samples. To be able to accurately determine the 129I concentration, an analytical method based on the use of a multicollector-inductively coupled plasma mass spectrometer (MC-ICPMS) combined with an isotope dilution technique using an 127I spike, was developed. First, the influence of different media (HNO3, NaOH and TMAH) on natural 127I signal intensity and stability and on memory effects was studied. Then an analytical procedure was developed by taking into account the correction of blanks and interferences. Tellurium was chosen for instrumental mass bias correction, as no certified standards with suitable 127I/129I ratio are available. Finally, the results, reproducibility and uncertainties obtained for the 129I concentration determined by isotope dilution with a 127I spike are presented and discussed. The final expanded relative uncertainty obtained for the iodine-129 concentration was lower than 0.7% (k = 1). This precise 129I determination in association with further activity measurements of this nuclide on the same sample will render it possible to determine a new value of the 129I half-life with a reduced uncertainty (0.76%, k = 1).

  19. Accurate measurements of {sup 129}I concentration by isotope dilution using MC-ICPMS for half-life determination

    Isnard, Helene; Nonell, Anthony; Marie, Mylene [Commissariat a l' Energie Atomique et aux Energies alternatives (CEA), Gif Sur Yvette (France). DEN, DPC, SEARS, LANIE; Chartier, Frederic [Commissariat a l' Energie Atomique et aux Energies alternatives (CEA), Gif Sur Yvette (France). DEN, DPC

    2016-05-01

    Determining the {sup 129}I concentration, a long-lived radionuclide present in spent nuclear fuel, is a major issue for nuclear waste disposal purpose. {sup 129}I also has to be measured in numerous environmental, nuclear and biological samples. To be able to accurately determine the {sup 129}I concentration, an analytical method based on the use of a multicollector-inductively coupled plasma mass spectrometer (MC-ICPMS) combined with an isotope dilution technique using an {sup 127}I spike, was developed. First, the influence of different media (HNO{sub 3}, NaOH and TMAH) on natural {sup 127}I signal intensity and stability and on memory effects was studied. Then an analytical procedure was developed by taking into account the correction of blanks and interferences. Tellurium was chosen for instrumental mass bias correction, as no certified standards with suitable {sup 127}I/{sup 129}I ratio are available. Finally, the results, reproducibility and uncertainties obtained for the {sup 129}I concentration determined by isotope dilution with a {sup 127}I spike are presented and discussed. The final expanded relative uncertainty obtained for the iodine-129 concentration was lower than 0.7% (k = 1). This precise {sup 129}I determination in association with further activity measurements of this nuclide on the same sample will render it possible to determine a new value of the {sup 129}I half-life with a reduced uncertainty (0.76%, k = 1).

  20. Accurate Prediction of Radiation Exposures of Workers Involved in the Transport of NORM

    A study of the radiation exposures encountered by workers involved in the transport of minerals and mineral concentrates containing radionuclides of natural origin was undertaken during 2008–2012. Hundreds of measurements were made during road, rail and marine transport of NORM between mining and processing sites in Australia and within and between ports in Australia, China and Japan. The investigation was focused on minerals and mineral concentrates containing thorium and uranium (including ilmenite, rutile, zircon and monazite). It was found that the use of the ‘exclusion’ factor of 10 for the concentrations of radionuclides in natural materials in the IAEA Transport Regulations is appropriate and is to be maintained. The dose rates from all potential pathways of exposure of workers could be accurately predicted, based on the concentrations of thorium and uranium in the transported material. These dose rates remain the same, irrespective of whether the transport is by road, rail or sea. The information presented in the paper allows, by the use of simple charts, the accurate prediction of doses to workers involved in the transport of NORM. It is suggested that it can be used in any assessments of exposures of workers that may be required prior to the start of the NORM transport process, by both regulatory bodies and by the mining and mineral processing industry. (author)

  1. Physical modeling of real-world slingshots for accurate speed predictions

    Yeats, Bob

    2016-01-01

    We discuss the physics and modeling of latex-rubber slingshots. The goal is to get accurate speed predictions inspite of the significant real world difficulties of force drift, force hysteresis, rubber ageing, and the very non- linear, non-ideal, force vs. pull distance curves of slingshot rubber bands. Slingshots are known to shoot faster under some circumstances when the bands are tapered rather than having constant width and stiffness. We give both qualitative understanding and numerical predictions of this effect. We consider two models. The first is based on conservation of energy and is easier to implement, but cannot determine the speeds along the rubber bands without making assumptions. The second, treats the bands as a series of mass points subject to being pulled by immediately adjacent mass points according to how much the rubber has been stretched on the two adjacent sides. This is a classic many-body F=ma problem but convergence requires using a particular numerical technique. It gives accurate p...

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

    Hönigschmid, Peter; Frishman, Dmitrij

    2016-04-01

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

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

    Shvab, I.; Sadus, Richard J., E-mail: rsadus@swin.edu.au [Centre for Molecular Simulation, Swinburne University of Technology, PO Box 218, Hawthorn, Victoria 3122 (Australia)

    2013-11-21

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

  4. Fast and accurate prediction of numerical relativity waveforms from binary black hole mergers using surrogate models

    Blackman, Jonathan; Galley, Chad R; Szilagyi, Bela; Scheel, Mark A; Tiglio, Manuel; Hemberger, Daniel A

    2015-01-01

    Simulating a binary black hole coalescence by solving Einstein's equations is computationally expensive, requiring days to months of supercomputing time. In this paper, we construct an accurate and fast-to-evaluate surrogate model for numerical relativity (NR) waveforms from non-spinning binary black hole coalescences with mass ratios from $1$ to $10$ and durations corresponding to about $15$ orbits before merger. Our surrogate, which is built using reduced order modeling techniques, is distinct from traditional modeling efforts. We find that the full multi-mode surrogate model agrees with waveforms generated by NR to within the numerical error of the NR code. In particular, we show that our modeling strategy produces surrogates which can correctly predict NR waveforms that were {\\em not} used for the surrogate's training. For all practical purposes, then, the surrogate waveform model is equivalent to the high-accuracy, large-scale simulation waveform but can be evaluated in a millisecond to a second dependin...

  5. Improvement of a land surface model for accurate prediction of surface energy and water balances

    In order to predict energy and water balances between the biosphere and atmosphere accurately, sophisticated schemes to calculate evaporation and adsorption processes in the soil and cloud (fog) water deposition on vegetation were implemented in the one-dimensional atmosphere-soil-vegetation model including CO2 exchange process (SOLVEG2). Performance tests in arid areas showed that the above schemes have a significant effect on surface energy and water balances. The framework of the above schemes incorporated in the SOLVEG2 and instruction for running the model are documented. With further modifications of the model to implement the carbon exchanges between the vegetation and soil, deposition processes of materials on the land surface, vegetation stress-growth-dynamics etc., the model is suited to evaluate an effect of environmental loads to ecosystems by atmospheric pollutants and radioactive substances under climate changes such as global warming and drought. (author)

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

    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).

  7. A fast and accurate method to predict 2D and 3D aerodynamic boundary layer flows

    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

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

    Matthew Almond Sochor

    2014-07-01

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

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

    Levinson, Ronnen; Akbari, Hashem; Berdahl, Paul

    2010-05-14

    Solar reflectance can vary with the spectral and angular distributions of incident sunlight, which in turn depend on surface orientation, solar position and atmospheric conditions. A widely used solar reflectance metric based on the ASTM Standard E891 beam-normal solar spectral irradiance underestimates the solar heat gain of a spectrally selective 'cool colored' surface because this irradiance contains a greater fraction of near-infrared light than typically found in ordinary (unconcentrated) global sunlight. At mainland U.S. latitudes, this metric RE891BN can underestimate the annual peak solar heat gain of a typical roof or pavement (slope {le} 5:12 [23{sup o}]) by as much as 89 W m{sup -2}, and underestimate its peak surface temperature by up to 5 K. Using R{sub E891BN} to characterize roofs in a building energy simulation can exaggerate the economic value N of annual cool-roof net energy savings by as much as 23%. We define clear-sky air mass one global horizontal ('AM1GH') solar reflectance R{sub g,0}, a simple and easily measured property that more accurately predicts solar heat gain. R{sub g,0} predicts the annual peak solar heat gain of a roof or pavement to within 2 W m{sup -2}, and overestimates N by no more than 3%. R{sub g,0} is well suited to rating the solar reflectances of roofs, pavements and walls. We show in Part II that R{sub g,0} can be easily and accurately measured with a pyranometer, a solar spectrophotometer or version 6 of the Solar Spectrum Reflectometer.

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

    Li, Zheng-Wei; You, Zhu-Hong; Chen, Xing; Gui, Jie; Nie, Ru

    2016-01-01

    Protein-protein interactions (PPIs) occur at almost all levels of cell functions and play crucial roles in various cellular processes. Thus, identification of PPIs is critical for deciphering the molecular mechanisms and further providing insight into biological processes. Although a variety of high-throughput experimental techniques have been developed to identify PPIs, existing PPI pairs by experimental approaches only cover a small fraction of the whole PPI networks, and further, those approaches hold inherent disadvantages, such as being time-consuming, expensive, and having high false positive rate. Therefore, it is urgent and imperative to develop automatic in silico approaches to predict PPIs efficiently and accurately. In this article, we propose a novel mixture of physicochemical and evolutionary-based feature extraction method for predicting PPIs using our newly developed discriminative vector machine (DVM) classifier. The improvements of the proposed method mainly consist in introducing an effective feature extraction method that can capture discriminative features from the evolutionary-based information and physicochemical characteristics, and then a powerful and robust DVM classifier is employed. To the best of our knowledge, it is the first time that DVM model is applied to the field of bioinformatics. When applying the proposed method to the Yeast and Helicobacter pylori (H. pylori) datasets, we obtain excellent prediction accuracies of 94.35% and 90.61%, respectively. The computational results indicate that our method is effective and robust for predicting PPIs, and can be taken as a useful supplementary tool to the traditional experimental methods for future proteomics research. PMID:27571061

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

    Visel, Axel; Blow, Matthew J.; Li, Zirong; Zhang, Tao; Akiyama, Jennifer A.; Holt, Amy; Plajzer-Frick, Ingrid; Shoukry, Malak; Wright, Crystal; Chen, Feng; Afzal, Veena; Ren, Bing; Rubin, Edward M.; Pennacchio, Len A.

    2009-02-01

    A major yet unresolved quest in decoding the human genome is the identification of the regulatory sequences that control the spatial and temporal expression of genes. Distant-acting transcriptional enhancers are particularly challenging to uncover since they are scattered amongst the vast non-coding portion of the genome. Evolutionary sequence constraint can facilitate the discovery of enhancers, but fails to predict when and where they are active in vivo. Here, we performed chromatin immunoprecipitation with the enhancer-associated protein p300, followed by massively-parallel sequencing, to map several thousand in vivo binding sites of p300 in mouse embryonic forebrain, midbrain, and limb tissue. We tested 86 of these sequences in a transgenic mouse assay, which in nearly all cases revealed reproducible enhancer activity in those tissues predicted by p300 binding. Our results indicate that in vivo mapping of p300 binding is a highly accurate means for identifying enhancers and their associated activities and suggest that such datasets will be useful to study the role of tissue-specific enhancers in human biology and disease on a genome-wide scale.

  12. An Accurate Calculation of the Big-Bang Prediction for the Abundance of Primordial Helium

    López, R E; Lopez, Robert E.; Turner, Michael S.

    1999-01-01

    Within the standard model of particle physics and cosmology we have calculated the big-bang prediction for the primordial abundance of Helium to a theoretical uncertainty of $0.1 \\pct$ $(\\delta Y_P = \\pm 0.0002)$. At this accuracy the uncertainty in the abundance is dominated by the experimental uncertainty in the neutron mean lifetime, $\\tau_n = 885.3 \\pm 2.0 \\rm{sec}$. The following physical effects were included in the calculation: the zero and finite-temperature radiative, Coulomb and finite-nucleon mass corrections to the weak rates; order-$\\alpha$ quantum-electrodynamic correction to the plasma density, electron mass, and neutrino temperature; and incomplete neutrino decoupling. New results for the finite-temperature radiative correction and the QED plasma correction were used. In addition, we wrote a new and independent nucleosynthesis code to control numerical errors to less than 0.1\\pct. Our predictions for the \\EL[4]{He} abundance are summarized with an accurate fitting formula. Summarizing our work...

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

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

    2016-04-01

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

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

    Matias I Maturana

    2016-04-01

    Full Text Available 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.

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

    Edwards, G E; Baker, N R

    1993-08-01

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

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

    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

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

    Ludlow, Lindsay W; Weyand, Peter G

    2016-03-01

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

  18. A hydrogen gas-water equilibration method produces accurate and precise stable hydrogen isotope ratio measurements in nutrition studies

    Stable hydrogen isotope methodology is used in nutrition studies to measure growth, breast milk intake, and energy requirement. Isotope ratio MS is the best instrumentation to measure the stable hydrogen isotope ratios in physiological fluids. Conventional methods to convert physiological fluids to ...

  19. A sensitive and accurate method for determination of radium isotopes in environmental samples by alpha-spectrometry

    A sensitive and accurate method for determination of radium isotopes in water and soil samples by alpha-spectrometry has been developed. Ra-225, which is in equilibrium with its mother 229Th, was used as a yield tracer. Radium in water samples was preconcentrated by coprecipitation with BaSO4 and iron (III) hydroxide at pH 8-9 using ammonia solution, isolated from uranium, thorium and iron using a Microthene-TOPO chromatography column at 8 M HCl, separated from barium in a cation-exchange resin column using 0.05 M 1,2-cyclo hexylene- dinitrilo-tetraacetic acid monohydrate at pH 8.5 as an eluant, electrodeposited on a stainless steel disc in a medium of 0.17 M (NH4)2C2O4 at pH 2.6 and current density of 400 mA cm-2, and counted by α-spectrometry. Radium in soil samples was fused with Na2CO3 and Na2O2 at 600 degree C, leached with HNO3, HCl and HF, and. preconcentrated by coprecipitation with BaSO4 at pH 3. The procedure for further separation, purification electrodeposition and measurement of radium in soil samples was same as that for water samples.

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

    Ureña-López, L Arturo

    2015-01-01

    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. We apply the method to a scalar field 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 shown that the Jeans wavenumber defined as $k_J = a \\sqrt{mH}$ is directly related to the suppression of linear perturbations at wavenumbers $k>k_J$. 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 t...

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

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

    2015-09-18

    Simulating a binary black hole coalescence by solving Einstein's equations is computationally expensive, requiring days to months of supercomputing time. Using reduced order modeling techniques, we construct an accurate surrogate model, which is evaluated in a millisecond to a second, for numerical relativity (NR) waveforms from nonspinning binary black hole coalescences with mass ratios in [1, 10] and durations corresponding to about 15 orbits before merger. We assess the model's uncertainty and show that our modeling strategy predicts NR waveforms not used for the surrogate's training with errors nearly as small as the numerical error of the NR code. Our model includes all spherical-harmonic _{-2}Y_{ℓm} waveform modes resolved by the NR code up to ℓ=8. We compare our surrogate model to effective one body waveforms from 50M_{⊙} to 300M_{⊙} for advanced LIGO detectors and find that the surrogate is always more faithful (by at least an order of magnitude in most cases). PMID:26430979

  2. Cluster abundance in chameleon $f(R)$ gravity I: toward an accurate halo mass function prediction

    Cataneo, Matteo; Lombriser, Lucas; Li, Baojiu

    2016-01-01

    We refine the mass and environment dependent spherical collapse model of chameleon $f(R)$ gravity by calibrating a phenomenological correction inspired by the parameterized post-Friedmann framework against high-resolution $N$-body simulations. We employ our method to predict the corresponding modified halo mass function, and provide fitting formulas to calculate the fractional enhancement of the $f(R)$ halo abundance with respect to that of General Relativity (GR) within a precision of $\\lesssim 5\\%$ from the results obtained in the simulations. Similar accuracy can be achieved for the full $f(R)$ mass function on the condition that the modeling of the reference GR abundance of halos is accurate at the percent level. We use our fits to forecast constraints on the additional scalar degree of freedom of the theory, finding that upper bounds competitive with current Solar System tests are within reach of cluster number count analyses from ongoing and upcoming surveys at much larger scales. Importantly, the flexi...

  3. Accurate and Simplified Prediction of AVF for Delay and Energy Efficient Cache Design

    An-Guo Ma; Yu Cheng; Zuo-Cheng Xing

    2011-01-01

    With continuous technology scaling, on-chip structures are becoming more and more susceptible to soft errors. Architectural vulnerability factor (AVF) has been introduced to quantify the architectural vulnerability of on-chip structures to soft errors. Recent studies have found that designing soft error protection techniques with the awareness of AVF is greatly helpful to achieve a tradeoff between performance and reliability for several structures (i.e., issue queue, reorder buffer). Cache is one of the most susceptible components to soft errors and is commonly protected with error correcting codes (ECC). However, protecting caches closer to the processor (i.e., L1 data cache (L1D)) using ECC could result in high overhead. Protecting caches without accurate knowledge of the vulnerability characteristics may lead to over-protection. Therefore, designing AVF-aware ECC is attractive for designers to balance among performance, power and reliability for cache, especially at early design stage. In this paper, we improve the methodology of cache AVF computation and develop a new AVF estimation framework, soft error reliability analysis based on SimpleScalar. Then we characterize dynamic vulnerability behavior of L1D and detect the correlations between LID AVF and various performance metrics. We propose to employ Bayesian additive regression trees to accurately model the variation of L1D AVF and to quantitatively explain the important effects of several key performance metrics on L1D AVF. Then, we employ bump hunting technique to reduce the complexity of L1D AVF prediction and extract some simple selecting rules based on several key performance metrics, thus enabling a simplified and fast estimation of L1D AVF. Based on the simplified and fast estimation of L1D AVF, intervals of high L1D AVF can be identified online, enabling us to develop the AVF-aware ECC technique to reduce the overhead of ECC. Experimental results show that compared with traditional ECC technique

  4. RCWIM - an improved global water isotope pattern prediction model using fuzzy climatic clustering regionalization

    Terzer, Stefan; Araguás-Araguás, Luis; Wassenaar, Leonard I.; Aggarwal, Pradeep K.

    2013-04-01

    Prediction of geospatial H and O isotopic patterns in precipitation has become increasingly important to diverse disciplines beyond hydrology, such as climatology, ecology, food authenticity, and criminal forensics, because these two isotopes of rainwater often control the terrestrial isotopic spatial patterns that facilitate the linkage of products (food, wildlife, water) to origin or movement (food, criminalistics). Currently, spatial water isotopic pattern prediction relies on combined regression and interpolation techniques to create gridded datasets by using data obtained from the Global Network of Isotopes In Precipitation (GNIP). However, current models suffer from two shortcomings: (a) models may have limited covariates and/or parameterization fitted to a global domain, which results in poor predictive outcomes at regional scales, or (b) the spatial domain is intentionally restricted to regional settings, and thereby of little use in providing information at global geospatial scales. Here we present a new global climatically regionalized isotope prediction model which overcomes these limitations through the use of fuzzy clustering of climatic data subsets, allowing us to better identify and customize appropriate covariates and their multiple regression coefficients instead of aiming for a one-size-fits-all global fit (RCWIM - Regionalized Climate Cluster Water Isotope Model). The new model significantly reduces the point-based regression residuals and results in much lower overall isotopic prediction uncertainty, since residuals are interpolated onto the regression surface. The new precipitation δ2H and δ18O isoscape model is available on a global scale at 10 arc-minutes spatial and at monthly, seasonal and annual temporal resolution, and will provide improved predicted stable isotope values used for a growing number of applications. The model further provides a flexible framework for future improvements using regional climatic clustering.

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

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

  6. Predictive isotopic biogeochemistry: hydrocarbons from anoxic marine basins

    Freeman, K. H.; Wakeham, S. G.; Hayes, J. M.

    1994-01-01

    Carbon isotopic compositions were determined for individual hydrocarbons in water column and sediment samples from the Cariaco Trench and Black Sea. In order to identify hydrocarbons derived from phytoplankton, the isotopic compositions expected for biomass of autotrophic organisms living in surface waters of both localities were calculated based on the concentrations of CO2(aq) and the isotopic compositions of dissolved inorganic carbon. These calculated values are compared to measured delta values for particulate organic carbon and for individual hydrocarbon compounds. Specifically, we find that lycopane is probably derived from phytoplankton and that diploptene is derived from the lipids of chemoautotrophs living above the oxic/anoxic boundary. Three acyclic isoprenoids that have been considered markers for methanogens, pentamethyleicosane and two hydrogenated squalenes, have different delta values and apparently do not derive from a common source. Based on the concentration profiles and isotopic compositions, the C31 and C33 n-alkanes and n-alkenes have a similar source, and both may have a planktonic origin. If so, previously assigned terrestrial origins of organic matter in some Black Sea sediments may be erroneous.

  7. Polymorph stability prediction: On the importance of accurate structures: A case study of pyrazinamide

    Wahlberg, N.; Ciochon, P.; Petříček, Václav; Madsen, A. O.

    2014-01-01

    Roč. 14, č. 1 (2014), s. 381-388. ISSN 1528-7483 Institutional support: RVO:68378271 Keywords : accurate structures * disorder * twinning Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 4.891, year: 2014

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

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

    2015-12-01

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

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

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

    2014-05-01

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

  10. Accurate wavelength prediction of photonic crystal resonant reflection and applications in refractive index measurement

    Hermannsson, Pétur Gordon; Vannahme, Christoph; Smith, Cameron L. C.;

    2014-01-01

    superstrate materials. The importance of accounting for material dispersion in order to obtain accurate simulation results is highlighted, and a method for doing so using an iterative approach is demonstrated. Furthermore, an application for the model is demonstrated, in which the material dispersion of a...

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

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

    2016-03-01

    Discrepancies between planned and delivered movements of multi-leaf collimators (MLCs) are an important source of errors in dose distributions during radiotherapy. In this work we used machine learning techniques to train models to predict these discrepancies, assessed the accuracy of the model predictions, and examined the impact these errors have on quality assurance (QA) procedures and dosimetry. Predictive leaf motion parameters for the models were calculated from the plan files, such as leaf position and velocity, whether the leaf was moving towards or away from the isocenter of the MLC, and many others. Differences in positions between synchronized DICOM-RT planning files and DynaLog files reported during QA delivery were used as a target response for training of the models. The final model is capable of predicting MLC positions during delivery to a high degree of accuracy. For moving MLC leaves, predicted positions were shown to be significantly closer to delivered positions than were planned positions. By incorporating predicted positions into dose calculations in the TPS, increases were shown in gamma passing rates against measured dose distributions recorded during QA delivery. For instance, head and neck plans with 1%/2 mm gamma criteria had an average increase in passing rate of 4.17% (SD  =  1.54%). This indicates that the inclusion of predictions during dose calculation leads to a more realistic representation of plan delivery. To assess impact on the patient, dose volumetric histograms (DVH) using delivered positions were calculated for comparison with planned and predicted DVHs. In all cases, predicted dose volumetric parameters were in closer agreement to the delivered parameters than were the planned parameters, particularly for organs at risk on the periphery of the treatment area. By incorporating the predicted positions into the TPS, the treatment planner is given a more realistic view of the dose distribution as it will truly be

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

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

    2016-03-21

    Discrepancies between planned and delivered movements of multi-leaf collimators (MLCs) are an important source of errors in dose distributions during radiotherapy. In this work we used machine learning techniques to train models to predict these discrepancies, assessed the accuracy of the model predictions, and examined the impact these errors have on quality assurance (QA) procedures and dosimetry. Predictive leaf motion parameters for the models were calculated from the plan files, such as leaf position and velocity, whether the leaf was moving towards or away from the isocenter of the MLC, and many others. Differences in positions between synchronized DICOM-RT planning files and DynaLog files reported during QA delivery were used as a target response for training of the models. The final model is capable of predicting MLC positions during delivery to a high degree of accuracy. For moving MLC leaves, predicted positions were shown to be significantly closer to delivered positions than were planned positions. By incorporating predicted positions into dose calculations in the TPS, increases were shown in gamma passing rates against measured dose distributions recorded during QA delivery. For instance, head and neck plans with 1%/2 mm gamma criteria had an average increase in passing rate of 4.17% (SD  =  1.54%). This indicates that the inclusion of predictions during dose calculation leads to a more realistic representation of plan delivery. To assess impact on the patient, dose volumetric histograms (DVH) using delivered positions were calculated for comparison with planned and predicted DVHs. In all cases, predicted dose volumetric parameters were in closer agreement to the delivered parameters than were the planned parameters, particularly for organs at risk on the periphery of the treatment area. By incorporating the predicted positions into the TPS, the treatment planner is given a more realistic view of the dose distribution as it will truly be

  13. Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics

    Ong, S.E.; Blagoev, B.; Kratchmarova, I.;

    2002-01-01

    . Here we describe a method, termed SILAC, for stable isotope labeling by amino acids in cell culture, for the in vivo incorporation of specific amino acids into all mammalian proteins. Mammalian cell lines are grown in media lacking a standard essential amino acid but supplemented with a non......Quantitative proteomics has traditionally been performed by two-dimensional gel electrophoresis, but recently, mass spectrometric methods based on stable isotope quantitation have shown great promise for the simultaneous and automated identification and quantitation of complex protein mixtures......-radioactive, isotopically labeled form of that amino acid, in this case deuterated leucine (Leu-d3). We find that growth of cells maintained in these media is no different from growth in normal media as evidenced by cell morphology, doubling time, and ability to differentiate. Complete incorporation of Leu-d3 occurred...

  14. Rapid, accurate and precise measurement of the isotopic composition of atmospheric gases: A generalized GC-IRMS solution

    The measurement of the isotopic composition of individual gas species in air is an analytical challenge faced by researchers in many disciplines. The existence of many different types of air (atmospheric air, dissolved air, air bubbles in ice, soil air, growth chamber atmospheres) and the enormous dynamic range of concentrations makes the problem difficult. The recent combination of gas chromatography with isotope ratio mass spectrometry (GC-IRMS) has allowed the solution of many previously difficult or intractable problems of this sort. Interest is divided between analysis of trace gases (CO2, CH4, N2O and CH3Cl) and the major species (N2, O2 and Ar). Recent instrumental developments have allowed us to assemble a generalized GC-IRMS approach capable of high precision isotopic analysis of both trace and major species at natural and enriched abundances, while permitting high throughput automated analysis using sample containers compatible with field collection

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

    Zimmermann, Olav; Hansmann, Ulrich H E

    2008-09-01

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

  16. Accurate Prediction of the Ammonia Probes of a Variable Proton-to-Electron Mass Ratio

    Owens, Alec; Thiel, Walter; Špirko, Vladimir

    2015-01-01

    A comprehensive study of the mass sensitivity of the vibration-rotation-inversion transitions of $^{14}$NH$_3$, $^{15}$NH$_3$, $^{14}$ND$_3$, and $^{15}$ND$_3$ is carried out variationally using the TROVE approach. Variational calculations are robust and accurate, offering a new way to compute sensitivity coefficients. Particular attention is paid to the $\\Delta k=\\pm 3$ transitions between the accidentally coinciding rotation-inversion energy levels of the $\

  17. PconsD: ultra rapid, accurate model quality assessment for protein structure prediction

    Skwark, M. J.; Elofsson, A.

    2013-01-01

    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 very 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 very fast, stream-computing method for distance-driven model qua...

  18. How accurate do markets predict the outcome of an event? The Euro 2000 soccer championships experiment

    Schmidt, Carsten; Werwatz, Axel

    2002-01-01

    For the Euro 2000 Soccer Championships an experimental asset market was condueted, with traders buying and selling contracts on the winners of individual matches. Market-generated probabilities are compared to professional bet quotas, and factors that are responsible for the quality of the market prognosis are identified. The comparison shows, that the market is more accurate than the random predictor and slightly better than professional bet quotas, in the sense of mean square error. Moreove...

  19. Accurate microRNA target prediction correlates with protein repression levels

    Simossis Victor A

    2009-09-01

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

  20. Selective, accurate, and timely self-invalidation using last-touch prediction

    Lai, An-Chow; Falsafi, Babak

    2000-01-01

    Communication in cache-coherent distributed shared memory (DSM) often requires invalidating (or writing back) cached copies of a memory block, incurring high overheads. This paper proposes Last-Touch Predictors (LTPs) that learn and predict the “last touch” to a memory block by one processor before the block is accessed and subsequently invalidated by another. By predicting a last-touch and (self-)invalidating the block in advance, an LTP hides the invalidation time, significantly reduc...

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

    Jesse S. Jin

    2010-10-01

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

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

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

    2013-12-01

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

  3. Accurate determination of Curium and Californium isotopic ratios by inductively coupled plasma quadrupole mass spectrometry (ICP-QMS) in 248Cm samples for transmutation studies

    The French Atomic Energy Commission has carried out several experiments including the mini-INCA (INcineration of Actinides) project for the study of minor-actinide transmutation processes in high intensity thermal neutron fluxes, in view of proposing solutions to reduce the radiotoxicity of long-lived nuclear wastes. In this context, a Cm sample enriched in 248Cm (∼97 %) was irradiated in thermal neutron flux at the High Flux Reactor (HFR) of the Laue-Langevin Institute (ILL). This work describes a quadrupole ICP-MS (ICP-QMS) analytical procedure for precise and accurate isotopic composition determination of Cm before sample irradiation and of Cm and Cf after sample irradiation. The factors that affect the accuracy and reproducibility of isotopic ratio measurements by ICP-QMS, such as peak centre correction, detector dead time, mass bias, abundance sensitivity and hydrides formation, instrumental background, and memory blank were carefully evaluated and corrected. Uncertainties of the isotopic ratios, taking into account internal precision of isotope ratio measurements, peak tailing, and hydrides formations ranged from 0.3% to 1.3%. This uncertainties range is quite acceptable for the nuclear data to be used in transmutation studies.

  4. Accurate determination of Curium and Californium isotopic ratios by inductively coupled plasma quadrupole mass spectrometry (ICP-QMS) in Cm-248 samples for transmutation studies

    The French Atomic Energy Commission has carried out several experiments including the mini-INCA (Incineration of Actinides) project for the study of minor-actinide transmutation processes in high intensity thermal neutron fluxes, in view of proposing solutions to reduce the radiotoxicity of long-lived nuclear wastes. In this context, a Cm sample enriched in 248Cm (similar to 97%) was irradiated in thermal neutron flux at the High Flux Reactor (HFR) of the Laue-Langevin Institute (ILL). This work describes a quadrupole ICP-MS (ICP-QMS) analytical procedure for precise and accurate isotopic composition determination of Cm before sample irradiation and of Cm and Cf after sample irradiation. The factors that affect the accuracy and reproducibility of isotopic ratio measurements by ICP-QMS, such as peak centre correction, detector dead time, mass bias, abundance sensitivity and hydrides formation, instrumental background, and memory blank were carefully evaluated and corrected. Uncertainties of the isotopic ratios, taking into account internal precision of isotope ratio measurements, peak tailing, and hydrides' formations ranged from 0. 3% to 1. 3%. This uncertainties' range is quite acceptable for the nuclear data to be used in transmutation studies. (authors)

  5. Empirical approaches to more accurately predict benthic-pelagic coupling in biogeochemical ocean models

    Dale, Andy; Stolpovsky, Konstantin; Wallmann, Klaus

    2016-04-01

    The recycling and burial of biogenic material in the sea floor plays a key role in the regulation of ocean chemistry. Proper consideration of these processes in ocean biogeochemical models is becoming increasingly recognized as an important step in model validation and prediction. However, the rate of organic matter remineralization in sediments and the benthic flux of redox-sensitive elements are difficult to predict a priori. In this communication, examples of empirical benthic flux models that can be coupled to earth system models to predict sediment-water exchange in the open ocean are presented. Large uncertainties hindering further progress in this field include knowledge of the reactivity of organic carbon reaching the sediment, the importance of episodic variability in bottom water chemistry and particle rain rates (for both the deep-sea and margins) and the role of benthic fauna. How do we meet the challenge?

  6. LocARNA-P: Accurate boundary prediction and improved detection of structural RNAs

    Will, Sebastian; Joshi, Tejal; Hofacker, Ivo L.;

    2012-01-01

    from AUC 0.71 to AUC 0.87, significantly reduces the cost of successive analysis steps. The ready-to-use software tool LocARNA-P produces structure-based multiple RNA alignments with associated columnwise STARs and predicts ncRNA boundaries. We provide additional results, a web server for Loc...... on sequence and structure similarity; we refer to these structure-based alignment reliabilities as STARs. The columnwise STARs of alignments, or STAR profiles, provide a versatile tool for the manual and automatic analysis of ncRNAs. In particular, we improve the boundary prediction of the widely...

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

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

    2016-01-01

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

  8. Precise and accurate isotopic analysis of microscopic uranium-oxide grains using LA-MC-ICP-MS

    Lloyd, Nicholas S.; Parrish, Randall R.; Horstwood, Matthew S.A.; Chenery, Simon R.N.

    2009-01-01

    Uranium isotope (235U, 236U, 238U) ratios were determined for microscopic uranium-oxide grains using laser-ablation multi-collector inductively-coupled-plasma mass-spectrometry (LA-MC-ICP-MS). The grains were retrieved from contaminated soil and dust samples. The analytical technique utilised is rapid, requires minimal sample preparation, and is well suited for nuclear forensic applications. Precision and accuracy were assessed by replicate analyses of natural uraninite grains: relative uncer...

  9. Safe surgery: how accurate are we at predicting intra-operative blood loss?

    2012-02-01

    Introduction Preoperative estimation of intra-operative blood loss by both anaesthetist and operating surgeon is a criterion of the World Health Organization\\'s surgical safety checklist. The checklist requires specific preoperative planning when anticipated blood loss is greater than 500 mL. The aim of this study was to assess the accuracy of surgeons and anaesthetists at predicting intra-operative blood loss. Methods A 6-week prospective study of intermediate and major operations in an academic medical centre was performed. An independent observer interviewed surgical and anaesthetic consultants and registrars, preoperatively asking each to predict expected blood loss in millilitre. Intra-operative blood loss was measured and compared with these predictions. Parameters including the use of anticoagulation and anti-platelet therapy as well as intra-operative hypothermia and hypotension were recorded. Results One hundred sixty-eight operations were included in the study, including 142 elective and 26 emergency operations. Blood loss was predicted to within 500 mL of measured blood loss in 89% of cases. Consultant surgeons tended to underestimate blood loss, doing so in 43% of all cases, while consultant anaesthetists were more likely to overestimate (60% of all operations). Twelve patients (7%) had underestimation of blood loss of more than 500 mL by both surgeon and anaesthetist. Thirty per cent (n = 6\\/20) of patients requiring transfusion of a blood product within 24 hours of surgery had blood loss underestimated by more than 500 mL by both surgeon and anaesthetist. There was no significant difference in prediction between patients on anti-platelet or anticoagulation therapy preoperatively and those not on the said therapies. Conclusion Predicted intra-operative blood loss was within 500 mL of measured blood loss in 89% of operations. In 30% of patients who ultimately receive a blood transfusion, both the surgeon and anaesthetist significantly underestimate

  10. nuMap: A Web Platform for Accurate Prediction of Nucleosome Positioning

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

    2014-01-01

    Nucleosome positioning is critical for gene expression and of major biological interest. The high cost of experimentally mapping nucleosomal arrangement signifies the need for computational approaches to predict nucleosome positions at high resolution. Here, we present a web-based application to fulfill this need by implementing two models, YR and W/S schemes, for the translational and rotational positioning of nucleosomes, respectively. Our methods are based on sequence-dependent anisotropic...

  11. Accurate and efficient target prediction using a potency-sensitive influence-relevance voter

    Lusci, Alessandro; Browning, Michael; Fooshee, David; Swamidass, Joshua; Baldi, Pierre

    2015-01-01

    Background A number of algorithms have been proposed to predict the biological targets of diverse molecules. Some are structure-based, but the most common are ligand-based and use chemical fingerprints and the notion of chemical similarity. These methods tend to be computationally faster than others, making them particularly attractive tools as the amount of available data grows. Results Using a ChEMBL-derived database covering 490,760 molecule-protein interactions and 3236 protein targets, w...

  12. Bedside tracer gas technique accurately predicts outcome in aspiration of spontaneous pneumothorax

    Kiely, D; Ansari, S.; Davey, W.; Mahadevan, V.; Taylor, G.; Seaton, D

    2001-01-01

    BACKGROUND—There is no technique in general use that reliably predicts the outcome of manual aspiration of spontaneous pneumothorax. We have hypothesised that the absence of a pleural leak at the time of aspiration will identify a group of patients in whom immediate discharge is unlikely to be complicated by early lung re-collapse and have tested this hypothesis by using a simple bedside tracer gas technique.
METHODS—Eighty four episodes of primary spontaneous pneumothora...

  13. Revisiting the blind tests in crystal structure prediction: accurate energy ranking of molecular crystals.

    Asmadi, Aldi; Neumann, Marcus A; Kendrick, John; Girard, Pascale; Perrin, Marc-Antoine; Leusen, Frank J J

    2009-12-24

    In the 2007 blind test of crystal structure prediction hosted by the Cambridge Crystallographic Data Centre (CCDC), a hybrid DFT/MM method correctly ranked each of the four experimental structures as having the lowest lattice energy of all the crystal structures predicted for each molecule. The work presented here further validates this hybrid method by optimizing the crystal structures (experimental and submitted) of the first three CCDC blind tests held in 1999, 2001, and 2004. Except for the crystal structures of compound IX, all structures were reminimized and ranked according to their lattice energies. The hybrid method computes the lattice energy of a crystal structure as the sum of the DFT total energy and a van der Waals (dispersion) energy correction. Considering all four blind tests, the crystal structure with the lowest lattice energy corresponds to the experimentally observed structure for 12 out of 14 molecules. Moreover, good geometrical agreement is observed between the structures determined by the hybrid method and those measured experimentally. In comparison with the correct submissions made by the blind test participants, all hybrid optimized crystal structures (apart from compound II) have the smallest calculated root mean squared deviations from the experimentally observed structures. It is predicted that a new polymorph of compound V exists under pressure. PMID:19950907

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

    Faraggi, Eshel; Zhou, Yaoqi; Kloczkowski, Andrzej

    2014-11-01

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

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

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

    2013-11-01

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

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

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

    2014-07-01

    With the preponderance of multidomain proteins in eukaryotic genomes, it is essential to recognize the constituent domains and their functions. Often function involves communications across the domain interfaces, and the knowledge of the interacting sites is essential to our understanding of the structure-function relationship. Using evolutionary information extracted from homologous domains in at least two diverse domain architectures (single and multidomain), we predict the interface residues corresponding to domains from the two-domain proteins. We also use information from the three-dimensional structures of individual domains of two-domain proteins to train naïve Bayes classifier model to predict the interfacial residues. Our predictions are highly accurate (∼85%) and specific (∼95%) to the domain-domain interfaces. This method is specific to multidomain proteins which contain domains in at least more than one protein architectural context. Using predicted residues to constrain domain-domain interaction, rigid-body docking was able to provide us with accurate full-length protein structures with correct orientation of domains. We believe that these results can be of considerable interest toward rational protein and interaction design, apart from providing us with valuable information on the nature of interactions. PMID:24375512

  17. Accurate experimental determination of the isotope effects on the triple point temperature of water. II. Combined dependence on the 18O and 17O abundances

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

    2015-12-01

    This paper is the second of two articles on the quantification of isotope effects on the triple point temperature of water. In this second article, we address the combined effects of 18O and 17O isotopes. We manufactured five triple point cells with waters with 18O and 17O abundances exceeding widely the natural abundance range while maintaining their natural 18O/17O relationship. The 2H isotopic abundance was kept close to that of VSMOW (Vienna Standard Mean Ocean Water). These cells realized triple point temperatures ranging between  -220 μK to 1420 μK with respect to the temperature realized by a triple point cell filled with VSMOW. Our experiment allowed us to determine an accurate and reliable value for the newly defined combined 18, 17O correction parameter of AO  =  630 μK with a combined uncertainty of 10 μK. To apply this correction, only the 18O abundance of the TPW needs to be known (and the water needs to be of natural origin). Using the results of our two articles, we recommend a correction equation along with the coefficient values for isotopic compositions differing from that of VSMOW and compare the effect of this new equation on a number of triple point cells from the literature and from our own institute. Using our correction equation, the uncertainty in the isotope correction for triple point cell waters used around the world will be  <1 μK.

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

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

    2016-02-01

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

  19. Can magnetic resonance imaging accurately predict concordant pain provocation during provocative disc injection?

    Kang, Chang Ho; Kim, Yun Hwan; Kim, Jung Hyuk; Chung, Kyoo Byung; Sung, Deuk Jae [Korea University Anam Hospital, Korea University College of Medicine, Department of Radiology, Seoul (Korea); Lee, Sang-Heon [Korea University Anam Hospital, Korea University College of Medicine, Department of Physical Medicine and Rehabilitation, Seoul (Korea); Derby, Richard [Spinal Diagnostics and Treatment Center, Daly City, CA (United States); Stanford University Medical Center, Division of Physical Medicine and Rehabilitation, Stanford, CA (United States)

    2009-09-15

    To correlate magnetic resonance (MR) image findings with pain response by provocation discography in patients with discogenic low back pain, with an emphasis on the combination analysis of a high intensity zone (HIZ) and disc contour abnormalities. Sixty-two patients (aged 17-68 years) with axial low back pain that was likely to be disc related underwent lumbar discography (178 discs tested). The MR images were evaluated for disc degeneration, disc contour abnormalities, HIZ, and endplate abnormalities. Based on the combination of an HIZ and disc contour abnormalities, four classes were determined: (1) normal or bulging disc without HIZ; (2) normal or bulging disc with HIZ; (3) disc protrusion without HIZ; (4) disc protrusion with HIZ. These MR image findings and a new combined MR classification were analyzed in the base of concordant pain determined by discography. Disc protrusion with HIZ [sensitivity 45.5%; specificity 97.8%; positive predictive value (PPV), 87.0%] correlated significantly with concordant pain provocation (P < 0.01). A normal or bulging disc with HIZ was not associated with reproduction of pain. Disc degeneration (sensitivity 95.4%; specificity 38.8%; PPV 33.9%), disc protrusion (sensitivity 68.2%; specificity 80.6%; PPV 53.6%), and HIZ (sensitivity 56.8%; specificity 83.6%; PPV 53.2%) were not helpful in the identification of a disc with concordant pain. The proposed MR classification is useful to predict a disc with concordant pain. Disc protrusion with HIZ on MR imaging predicted positive discography in patients with discogenic low back pain. (orig.)

  20. Can magnetic resonance imaging accurately predict concordant pain provocation during provocative disc injection?

    To correlate magnetic resonance (MR) image findings with pain response by provocation discography in patients with discogenic low back pain, with an emphasis on the combination analysis of a high intensity zone (HIZ) and disc contour abnormalities. Sixty-two patients (aged 17-68 years) with axial low back pain that was likely to be disc related underwent lumbar discography (178 discs tested). The MR images were evaluated for disc degeneration, disc contour abnormalities, HIZ, and endplate abnormalities. Based on the combination of an HIZ and disc contour abnormalities, four classes were determined: (1) normal or bulging disc without HIZ; (2) normal or bulging disc with HIZ; (3) disc protrusion without HIZ; (4) disc protrusion with HIZ. These MR image findings and a new combined MR classification were analyzed in the base of concordant pain determined by discography. Disc protrusion with HIZ [sensitivity 45.5%; specificity 97.8%; positive predictive value (PPV), 87.0%] correlated significantly with concordant pain provocation (P < 0.01). A normal or bulging disc with HIZ was not associated with reproduction of pain. Disc degeneration (sensitivity 95.4%; specificity 38.8%; PPV 33.9%), disc protrusion (sensitivity 68.2%; specificity 80.6%; PPV 53.6%), and HIZ (sensitivity 56.8%; specificity 83.6%; PPV 53.2%) were not helpful in the identification of a disc with concordant pain. The proposed MR classification is useful to predict a disc with concordant pain. Disc protrusion with HIZ on MR imaging predicted positive discography in patients with discogenic low back pain. (orig.)

  1. Can tritiated water-dilution space accurately predict total body water in chukar partridges

    Total body water (TBW) volumes determined from the dilution space of injected tritiated water have consistently overestimated actual water volumes (determined by desiccation to constant mass) in reptiles and mammals, but results for birds are controversial. We investigated potential errors in both the dilution method and the desiccation method in an attempt to resolve this controversy. Tritiated water dilution yielded an accurate measurement of water mass in vitro. However, in vivo, this method yielded a 4.6% overestimate of the amount of water (3.1% of live body mass) in chukar partridges, apparently largely because of loss of tritium from body water to sites of dissociable hydrogens on body solids. An additional source of overestimation (approximately 2% of body mass) was loss of tritium to the solids in blood samples during distillation of blood to obtain pure water for tritium analysis. Measuring tritium activity in plasma samples avoided this problem but required measurement of, and correction for, the dry matter content in plasma. Desiccation to constant mass by lyophilization or oven-drying also overestimated the amount of water actually in the bodies of chukar partridges by 1.4% of body mass, because these values included water adsorbed onto the outside of feathers. When desiccating defeathered carcasses, oven-drying at 70 degrees C yielded TBW values identical to those obtained from lyophilization, but TBW was overestimated (0.5% of body mass) by drying at 100 degrees C due to loss of organic substances as well as water

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

    Oyeyemi, Victor B; Krisiloff, David B; Keith, John A; Libisch, Florian; Pavone, Michele; Carter, Emily A

    2014-01-28

    Oxygenated hydrocarbons play important roles in combustion science as renewable fuels and additives, but many details about their combustion chemistry remain poorly understood. Although many methods exist for computing accurate electronic energies of molecules at equilibrium geometries, a consistent description of entire combustion reaction potential energy surfaces (PESs) requires multireference correlated wavefunction theories. Here we use bond dissociation energies (BDEs) as a foundational metric to benchmark methods based on multireference configuration interaction (MRCI) for several classes of oxygenated compounds (alcohols, aldehydes, carboxylic acids, and methyl esters). We compare results from multireference singles and doubles configuration interaction to those utilizing a posteriori and a priori size-extensivity corrections, benchmarked against experiment and coupled cluster theory. We demonstrate that size-extensivity corrections are necessary for chemically accurate BDE predictions even in relatively small molecules and furnish examples of unphysical BDE predictions resulting from using too-small orbital active spaces. We also outline the specific challenges in using MRCI methods for carbonyl-containing compounds. The resulting complete basis set extrapolated, size-extensivity-corrected MRCI scheme produces BDEs generally accurate to within 1 kcal/mol, laying the foundation for this scheme's use on larger molecules and for more complex regions of combustion PESs. PMID:25669533

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

    Liu, Qianlong; Reifsnider, Kenneth

    2012-11-01

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

  4. Accurate prediction of hot spot residues through physicochemical characteristics of amino acid sequences

    Chen, Peng

    2013-07-23

    Hot spot residues of proteins are fundamental interface residues that help proteins perform their functions. Detecting hot spots by experimental methods is costly and time-consuming. Sequential and structural information has been widely used in the computational prediction of hot spots. However, structural information is not always available. In this article, we investigated the problem of identifying hot spots using only physicochemical characteristics extracted from amino acid sequences. We first extracted 132 relatively independent physicochemical features from a set of the 544 properties in AAindex1, an amino acid index database. Each feature was utilized to train a classification model with a novel encoding schema for hot spot prediction by the IBk algorithm, an extension of the K-nearest neighbor algorithm. The combinations of the individual classifiers were explored and the classifiers that appeared frequently in the top performing combinations were selected. The hot spot predictor was built based on an ensemble of these classifiers and to work in a voting manner. Experimental results demonstrated that our method effectively exploited the feature space and allowed flexible weights of features for different queries. On the commonly used hot spot benchmark sets, our method significantly outperformed other machine learning algorithms and state-of-the-art hot spot predictors. The program is available at http://sfb.kaust.edu.sa/pages/software.aspx. © 2013 Wiley Periodicals, Inc.

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

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

    2016-06-01

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

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

    Martin, Katherine J.; Patrick, Denis R.; Bissell, Mina J.; Fournier, Marcia V.

    2008-10-20

    One of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasets having 295, 286, and 118 samples, respectively. Our results show that the 3D-signature accurately predicts prognosis in three unrelated patient datasets. At 10 years, the probability of positive outcome was 52, 51, and 47 percent in the group with a poor-prognosis signature and 91, 75, and 71 percent in the group with a good-prognosis signature for the three datasets, respectively (Kaplan-Meier survival analysis, p<0.05). Hazard ratios for poor outcome were 5.5 (95% CI 3.0 to 12.2, p<0.0001), 2.4 (95% CI 1.6 to 3.6, p<0.0001) and 1.9 (95% CI 1.1 to 3.2, p = 0.016) and remained significant for the two larger datasets when corrected for estrogen receptor (ER) status. Hence the 3D-signature accurately predicts breast cancer outcome in both ER-positive and ER-negative tumors, though individual genes differed in their prognostic ability in the two subtypes. Genes that were prognostic in ER+ patients are AURKA, CEP55, RRM2, EPHA2, FGFBP1, and VRK1, while genes prognostic in ER patients include ACTB, FOXM1 and SERPINE2 (Kaplan-Meier p<0.05). Multivariable Cox regression analysis in the largest dataset showed that the 3D-signature was a strong independent factor in predicting breast cancer outcome. The 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds prognostic

  7. Combining multiple regression and principal component analysis for accurate predictions for column ozone in Peninsular Malaysia

    Rajab, Jasim M.; MatJafri, M. Z.; Lim, H. S.

    2013-06-01

    This study encompasses columnar ozone modelling in the peninsular Malaysia. Data of eight atmospheric parameters [air surface temperature (AST), carbon monoxide (CO), methane (CH4), water vapour (H2Ovapour), skin surface temperature (SSKT), atmosphere temperature (AT), relative humidity (RH), and mean surface pressure (MSP)] data set, retrieved from NASA's Atmospheric Infrared Sounder (AIRS), for the entire period (2003-2008) was employed to develop models to predict the value of columnar ozone (O3) in study area. The combined method, which is based on using both multiple regressions combined with principal component analysis (PCA) modelling, was used to predict columnar ozone. This combined approach was utilized to improve the prediction accuracy of columnar ozone. Separate analysis was carried out for north east monsoon (NEM) and south west monsoon (SWM) seasons. The O3 was negatively correlated with CH4, H2Ovapour, RH, and MSP, whereas it was positively correlated with CO, AST, SSKT, and AT during both the NEM and SWM season periods. Multiple regression analysis was used to fit the columnar ozone data using the atmospheric parameter's variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to acquire subsets of the predictor variables to be comprised in the linear regression model of the atmospheric parameter's variables. It was found that the increase in columnar O3 value is associated with an increase in the values of AST, SSKT, AT, and CO and with a drop in the levels of CH4, H2Ovapour, RH, and MSP. The result of fitting the best models for the columnar O3 value using eight of the independent variables gave about the same values of the R (≈0.93) and R2 (≈0.86) for both the NEM and SWM seasons. The common variables that appeared in both regression equations were SSKT, CH4 and RH, and the principal precursor of the columnar O3 value in both the NEM and SWM seasons was SSKT.

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

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

    2014-10-01

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

  9. nuMap:A Web Platform for Accurate Prediction of Nucleosome Positioning

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

    2014-01-01

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

  10. The admixed population structure in Danish Jersey dairy cattle challenges accurate genomic predictions

    Thomasen, Jørn Rind; Sørensen, Anders Christian; Su, Guosheng; Madsen, Per; Lund, Mogens Sandø; Guldbrandtsen, Bernt

    2013-01-01

    The main purpose of this study is to evaluate whether the population structure in Danish Jersey known from the history of the breed also is reflected in the markers. This is done by comparing the linkage disequilibrium and persistence of phase for subgroups of Jersey animals with high proportions...... structure incorporated 1,730 genotyped Jersey animals. In total 39,542 SNP markers were included in the analysis. The 1,079 genotyped bulls with de-regressed proof for udder health were used in the analysis for the predictions of the genomic breeding values. A range of random regressions models that...... included the breed origin were analyzed and compared to a basic genomic model that assumes a homogeneous breed structure. The main finding in this study is that the importation of germ plasma from the US Jersey population is readily reflected in the genomes of modern Danish Jersey animals. Firstly, linkage...

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

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

    2009-04-01

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

  12. A Comparison of Digital Elevation Models to Accurately Predict Stream Locations

    Trowbridge, Spencer

    Three separate digital elevation models (DEMs) were compared in their ability to predict stream locations. The first DEM from the Shuttle Radar Topography Mission had a resolution of 90 meters, the second DEM from the National Elevation Dataset had a resolution of 30 meters, and the third DEM was created from Light Detection and Ranging (LiDAR) data and had a resolution of 4.34 meters. Ultimately, stream locations were created from these DEMs and compared to the National Hydrography Dataset (NHD) and stream channels traced from aerial photographs. Each bank of the named streams of the Papillion Creek Watershed were traced and samples were obtained that represent error in the placement of the derived stream locations. Measurements were taken from the centerline of the traced stream channels to where orthogonal transects intersected with the derived stream channel of the DEMs and the streams of the NHD. This study found that DEMs with differing resolutions will delineate stream channels differently and that without human assistance in processing elevation data, the finest resolution DEM was not the best at reproducing stream locations.

  13. Development of isotope dilution-liquid chromatography/mass spectrometry combined with standard addition techniques for the accurate determination of tocopherols in infant formula

    Graphical abstract: -- Highlights: •ID-LC/MS method showed biased results for tocopherols analysis in infant formula. •H/D exchange of deuterated tocopherols in sample preparation was the source of bias. •Standard addition (SA)-ID-LC/MS was developed as an alternative to ID-LC/MS. •Details of calculation and uncertainty evaluation of the SA-IDMS were described. •SA-ID-LC/MS showed a higher-order metrological quality as a reference method. -- Abstract: During the development of isotope dilution-liquid chromatography/mass spectrometry (ID-LC/MS) for tocopherol analysis in infant formula, biased measurement results were observed when deuterium-labeled tocopherols were used as internal standards. It turned out that the biases came from intermolecular H/D exchange and intramolecular H/D scrambling of internal standards in sample preparation processes. Degrees of H/D exchange and scrambling showed considerable dependence on sample matrix. Standard addition-isotope dilution mass spectrometry (SA-IDMS) based on LC/MS was developed in this study to overcome the shortcomings of using deuterium-labeled internal standards while the inherent advantage of isotope dilution techniques is utilized for the accurate recovery correction in sample preparation processes. Details of experimental scheme, calculation equation, and uncertainty evaluation scheme are described in this article. The proposed SA-IDMS method was applied to several infant formula samples to test its validity. The method was proven to have a higher-order metrological quality with providing very accurate and precise measurement results

  14. Mini-Mental Status Examination: a short form of MMSE was as accurate as the original MMSE in predicting dementia

    Schultz-Larsen, Kirsten; Lomholt, Rikke Kirstine; Kreiner, Svend

    2006-01-01

    OBJECTIVES: This study assesses the properties of the Mini-Mental State Examination (MMSE) with the purpose of improving the efficiencies of the methods of screening for cognitive impairment and dementia. A specific purpose was to determine whether an abbreviated version would be as accurate as the.......4%), and positive predictive value (71.0%) but equal area under the receiver operating characteristic curve. Cross-validation on follow-up data confirmed the results. CONCLUSION: A short, valid MMSE, which is as sensitive and specific as the original MMSE for the screening of cognitive impairments and...

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

    Yu, Victoria Y.; Tran, Angelia; Nguyen, Dan; Cao, Minsong; Ruan, Dan; Low, Daniel A.; Sheng, Ke, E-mail: ksheng@mednet.ucla.edu [Department of Radiation Oncology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California 90024 (United States)

    2015-11-15

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

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

    Margot Gerritsen

    2008-10-31

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

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

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

    2014-12-01

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

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

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

    2016-03-01

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

  19. Accurate predictions for charged Higgs production: closing the $m_{H^{\\pm}}\\sim m_t$ window

    Degrande, Celine; Hirschi, Valentin; Ubiali, Maria; Wiesemann, Marius; Zaro, Marco

    2016-01-01

    We present predictions for the total cross section for the production of a charged Higgs boson in a generic type-II two-Higgs-doublet model in the intermediate-mass range ($m_{H^{\\pm}}\\sim m_t$) at the LHC. Results are obtained at next-to-leading order (NLO) accuracy in QCD perturbation theory, by studying the full process $pp\\to H^\\pm W^\\mp b \\bar b$ in the complex-(top)-mass scheme with massive bottom quarks. Compared to lowest-order predictions, NLO corrections have a sizable impact: they increase the cross section by roughly 50% and reduce uncertainties due to scale variations by more than a factor of two. Our computation reliably interpolates between the low- and high-mass regime. Our results provide the first NLO prediction for charged Higgs production in the intermediate-mass range and therefore allow to have NLO accurate predictions in the full $m_{H^{\\pm}}$ range.

  20. Accurate prediction of sour gas hydrate equilibrium dissociation conditions by using an adaptive neuro fuzzy inference system

    Highlights: ► An ANFIS model is developed for predicting sour gas hydrate dissociation conditions. ► It can be used over wide ranges of operating conditions. ► At all H2S concentrations, the developed model outperforms the thermodynamic models. ► The presented model is useful for design of industrial sour gas handling systems. - Abstract: An adaptive neuro fuzzy inference system (ANFIS) has been proposed for predicting the sour gas hydrate equilibrium dissociation conditions. The proposed model predictions have been compared with those of the available thermodynamic models at different operating conditions. It is found that at all H2S concentrations especially at the concentrations higher than 10 mol%, the developed ANFIS model outperforms the existing thermodynamic models with the average absolute deviation of 2.18%. The proposed ANFIS model can be used for accurate and reliable predictions of sour gas hydrate equilibrium conditions over wide ranges of temperatures and acid gas concentrations and is a useful tool for proper design of sour natural gas flow assurance systems and gas hydrate energy storage processes in oil and gas industries.

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

    Bozinoski, Radoslav

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

  2. Predictive isotopic biogeochemistry of lipids from the Black Sea and Cariaco Trench

    Carbon isotopic compositions of autotrophic organisms can be predicted based on recently established relationships between [CO2(aq)] and var-epsilon p, the isotopic fractionation accompanying carbon fixation. In both the Black Sea and the Cariaco Trench, where [CO2(aq)] values are known and δ values for hydrocarbons were recently determined, predicted biomass δ values can be compared to those of biomarkers extracted from POM and sediment samples. The agreement is good, although a 5 per-thousand range in δ values is observed for the lipids, which may be due to ecological factors or to contributions from organisms that assimilate HCO3-. Lycopane and pentamethyleicosane apparently derive from planktonic organisms. Diploptene in the Black Sea apparently is derived from chemoautotrophic bacteria living at the oxic/anoxic interface. Some odd-C, long-chain n-alkanes have planktonic δ values, and the authors suggest they are not strict terrestrial indicators

  3. International challenge to predict the impact of radioxenon releases from medical isotope production on a comprehensive nuclear test ban treaty sampling station.

    Eslinger, Paul W; Bowyer, Ted W; Achim, Pascal; Chai, Tianfeng; Deconninck, Benoit; Freeman, Katie; Generoso, Sylvia; Hayes, Philip; Heidmann, Verena; Hoffman, Ian; Kijima, Yuichi; Krysta, Monika; Malo, Alain; Maurer, Christian; Ngan, Fantine; Robins, Peter; Ross, J Ole; Saunier, Olivier; Schlosser, Clemens; Schöppner, Michael; Schrom, Brian T; Seibert, Petra; Stein, Ariel F; Ungar, Kurt; Yi, Jing

    2016-06-01

    The International Monitoring System (IMS) is part of the verification regime for the Comprehensive Nuclear-Test-Ban-Treaty Organization (CTBTO). At entry-into-force, half of the 80 radionuclide stations will be able to measure concentrations of several radioactive xenon isotopes produced in nuclear explosions, and then the full network may be populated with xenon monitoring afterward. An understanding of natural and man-made radionuclide backgrounds can be used in accordance with the provisions of the treaty (such as event screening criteria in Annex 2 to the Protocol of the Treaty) for the effective implementation of the verification regime. Fission-based production of (99)Mo for medical purposes also generates nuisance radioxenon isotopes that are usually vented to the atmosphere. One of the ways to account for the effect emissions from medical isotope production has on radionuclide samples from the IMS is to use stack monitoring data, if they are available, and atmospheric transport modeling. Recently, individuals from seven nations participated in a challenge exercise that used atmospheric transport modeling to predict the time-history of (133)Xe concentration measurements at the IMS radionuclide station in Germany using stack monitoring data from a medical isotope production facility in Belgium. Participants received only stack monitoring data and used the atmospheric transport model and meteorological data of their choice. Some of the models predicted the highest measured concentrations quite well. A model comparison rank and ensemble analysis suggests that combining multiple models may provide more accurate predicted concentrations than any single model. None of the submissions based only on the stack monitoring data predicted the small measured concentrations very well. Modeling of sources by other nuclear facilities with smaller releases than medical isotope production facilities may be important in understanding how to discriminate those releases from

  4. Kinetic isotope effect of the 16O + 36O2 and 18O + 32O2 isotope exchange reactions: Dominant role of reactive resonances revealed by an accurate time-dependent quantum wavepacket study

    The O + O2 isotope exchange reactions play an important role in determining the oxygen isotopic composition of a number of trace gases in the atmosphere, and their temperature dependence and kinetic isotope effects (KIEs) provide important constraints on our understanding of the origin and mechanism of these and other unusual oxygen KIEs important in the atmosphere. This work reports a quantum dynamics study of the title reactions on the newly constructed Dawes-Lolur-Li-Jiang-Guo (DLLJG) potential energy surface (PES). The thermal reaction rate coefficients of both the 18O + 32O2 and 16O + 36O2 reactions obtained using the DLLJG PES exhibit a clear negative temperature dependence, in sharp contrast with the positive temperature dependence obtained using the earlier modified Siebert-Schinke-Bittererova (mSSB) PES. In addition, the calculated KIE shows an improved agreement with the experiment. These results strongly support the absence of the “reef” structure in the entrance/exit channels of the DLLJG PES, which is present in the mSSB PES. The quantum dynamics results on both PESs attribute the marked KIE to strong near-threshold reactive resonances, presumably stemming from the mass differences and/or zero point energy difference between the diatomic reactant and product. The accurate characterization of the reactivity for these near-thermoneutral reactions immediately above the reaction threshold is important for correct characterization of the thermal reaction rate coefficients

  5. Isotopic Ratio Outlier Analysis of the S. cerevisiae Metabolome Using Accurate Mass Gas Chromatography/Time-of-Flight Mass Spectrometry: A New Method for Discovery.

    Qiu, Yunping; Moir, Robyn; Willis, Ian; Beecher, Chris; Tsai, Yu-Hsuan; Garrett, Timothy J; Yost, Richard A; Kurland, Irwin J

    2016-03-01

    Isotopic ratio outlier analysis (IROA) is a (13)C metabolomics profiling method that eliminates sample to sample variance, discriminates against noise and artifacts, and improves identification of compounds, previously done with accurate mass liquid chromatography/mass spectrometry (LC/MS). This is the first report using IROA technology in combination with accurate mass gas chromatography/time-of-flight mass spectrometry (GC/TOF-MS), here used to examine the S. cerevisiae metabolome. S. cerevisiae was grown in YNB media, containing randomized 95% (13)C, or 5%(13)C glucose as the single carbon source, in order that the isotopomer pattern of all metabolites would mirror the labeled glucose. When these IROA experiments are combined, the abundance of the heavy isotopologues in the 5%(13)C extracts, or light isotopologues in the 95%(13)C extracts, follows the binomial distribution, showing mirrored peak pairs for the molecular ion. The mass difference between the (12)C monoisotopic and the (13)C monoisotopic equals the number of carbons in the molecules. The IROA-GC/MS protocol developed, using both chemical and electron ionization, extends the information acquired from the isotopic peak patterns for formulas generation. The process that can be formulated as an algorithm, in which the number of carbons, as well as the number of methoximations and silylations are used as search constraints. In electron impact (EI/IROA) spectra, the artifactual peaks are identified and easily removed, which has the potential to generate "clean" EI libraries. The combination of chemical ionization (CI) IROA and EI/IROA affords a metabolite identification procedure that enables the identification of coeluting metabolites, and allowed us to characterize 126 metabolites in the current study. PMID:26820234

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

    Steele, Mark A; Forrester, Graham E

    2005-09-20

    Field experiments provide rigorous tests of ecological hypotheses but are usually limited to small spatial scales. It is thus unclear whether these findings extrapolate to larger scales relevant to conservation and management. We show that the results of experiments detecting density-dependent mortality of reef fish on small habitat patches scale up to have similar effects on much larger entire reefs that are the size of small marine reserves and approach the scale at which some reef fisheries operate. We suggest that accurate scaling is due to the type of species interaction causing local density dependence and the fact that localized events can be aggregated to describe larger-scale interactions with minimal distortion. Careful extrapolation from small-scale experiments identifying species interactions and their effects should improve our ability to predict the outcomes of alternative management strategies for coral reef fishes and their habitats. PMID:16150721

  7. An approach to estimating and extrapolating model error based on inverse problem methods: towards accurate numerical weather prediction

    Model error is one of the key factors restricting the accuracy of numerical weather prediction (NWP). Considering the continuous evolution of the atmosphere, the observed data (ignoring the measurement error) can be viewed as a series of solutions of an accurate model governing the actual atmosphere. Model error is represented as an unknown term in the accurate model, thus NWP can be considered as an inverse problem to uncover the unknown error term. The inverse problem models can absorb long periods of observed data to generate model error correction procedures. They thus resolve the deficiency and faultiness of the NWP schemes employing only the initial-time data. In this study we construct two inverse problem models to estimate and extrapolate the time-varying and spatial-varying model errors in both the historical and forecast periods by using recent observations and analogue phenomena of the atmosphere. Numerical experiment on Burgers' equation has illustrated the substantial forecast improvement using inverse problem algorithms. The proposed inverse problem methods of suppressing NWP errors will be useful in future high accuracy applications of NWP. (geophysics, astronomy, and astrophysics)

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

    Magdalena Ydreborg

    Full Text Available 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.

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

    Harb, Moussab

    2015-10-14

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

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

    Harb, Moussab

    2015-08-26

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

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

    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.

  12. Accurate determination of sulfur in gasoline and related fuel samples using isotope dilution ICP-MS with direct sample injection and microwave-assisted digestion

    Heilmann, Jens; Boulyga, Sergei F.; Heumann, Klaus G. [Johannes Gutenberg-University, Institute of Inorganic Chemistry and Analytical Chemistry, Mainz (Germany)

    2004-09-01

    Inductively coupled plasma isotope-dilution mass spectrometry (ICP-IDMS) with direct injection of isotope-diluted samples into the plasma, using a direct injection high-efficiency nebulizer (DIHEN), was applied for accurate sulfur determinations in sulfur-free premium gasoline, gas oil, diesel fuel, and heating oil. For direct injection a micro-emulsion consisting of the corresponding organic sample and an aqueous {sup 34}S-enriched spike solution with additions of tetrahydronaphthalene and Triton X-100, was prepared. The ICP-MS parameters were optimized with respect to high sulfur ion intensities, low mass-bias values, and high precision of {sup 32}S/{sup 34}S ratio measurements. For validation of the DIHEN-ICP-IDMS method two certified gas oil reference materials (BCR 107 and BCR 672) were analyzed. For comparison a wet-chemical ICP-IDMS method was applied with microwave-assisted digestion using decomposition of samples in a closed quartz vessel inserted into a normal microwave system. The results from both ICP-IDMS methods agree well with the certified values of the reference materials and also with each other for analyses of other samples. However, the standard deviation of DIHEN-ICP-IDMS was about a factor of two higher (5-6% RSD at concentration levels above 100 {mu}g g{sup -1}) compared with those of wet-chemical ICP-IDMS, mainly due to inhomogeneities of the micro-emulsion, which causes additional plasma instabilities. Detection limits of 4 and 18 {mu}g g{sup -1} were obtained for ICP-IDMS in connection with microwave-assisted digestion and DIHEN-ICP-IDMS, respectively, with a sulfur background of the used Milli-Q water as the main limiting factor for both methods. (orig.)

  13. Validation of SCALE (SAS2H) Isotopic Predictions for BWR Spent Fuel

    Hermann, O.W.

    1998-01-01

    Thirty spent fuel samples obtained from boiling-water-reactor (BWR) fuel pins have been modeled at Oak Ridge National Laboratory using the SAS2H sequence of the SCALE code system. The SAS2H sequence uses transport methods combined with the depletion and decay capabilities of the ORIGEN-S code to estimate the isotopic composition of fuel as a function of its burnup history. Results of these calculations are compared with chemical assay measurements of spent fuel inventories for each sample. Results show reasonable agreement between measured and predicted isotopic concentrations for important actinides; however, little data are available for most fission products considered to be important for spent fuel concerns (e.g., burnup credit, shielding, source-term calculations, etc.). This work is a follow-up to earlier works that studied the ability to predict spent fuel compositions in pressurized-water-reactor (PWR) fuel pins. Biases and uncertainties associated with BWR isotopic predictions are found to be larger than those of PWR calculations. Such behavior is expected, as the operation of a BWR is significantly more complex than that of a PWR plant, and in general the design of a BWR has a more heterogeneous configuration than that of a PWR. Nevertheless, this work shows that the simple models employed using SAS2H to represent such complexities result in agreement to within 5% (and often less than 1%) or less for most nuclides important for spent fuel applications. On the other hand, however, the set of fuel samples analyzed represent a small subset of the BWR fuel population, and results reported herein may not be representative of the full population of BWR spent fuel.

  14. High IFIT1 expression predicts improved clinical outcome, and IFIT1 along with MGMT more accurately predicts prognosis in newly diagnosed glioblastoma.

    Zhang, Jin-Feng; Chen, Yao; Lin, Guo-Shi; Zhang, Jian-Dong; Tang, Wen-Long; Huang, Jian-Huang; Chen, Jin-Shou; Wang, Xing-Fu; Lin, Zhi-Xiong

    2016-06-01

    Interferon-induced protein with tetratricopeptide repeat 1 (IFIT1) plays a key role in growth suppression and apoptosis promotion in cancer cells. Interferon was reported to induce the expression of IFIT1 and inhibit the expression of O-6-methylguanine-DNA methyltransferase (MGMT).This study aimed to investigate the expression of IFIT1, the correlation between IFIT1 and MGMT, and their impact on the clinical outcome in newly diagnosed glioblastoma. The expression of IFIT1 and MGMT and their correlation were investigated in the tumor tissues from 70 patients with newly diagnosed glioblastoma. The effects on progression-free survival and overall survival were evaluated. Of 70 cases, 57 (81.4%) tissue samples showed high expression of IFIT1 by immunostaining. The χ(2) test indicated that the expression of IFIT1 and MGMT was negatively correlated (r = -0.288, P = .016). Univariate and multivariate analyses confirmed high IFIT1 expression as a favorable prognostic indicator for progression-free survival (P = .005 and .017) and overall survival (P = .001 and .001), respectively. Patients with 2 favorable factors (high IFIT1 and low MGMT) had an improved prognosis as compared with others. The results demonstrated significantly increased expression of IFIT1 in newly diagnosed glioblastoma tissue. The negative correlation between IFIT1 and MGMT expression may be triggered by interferon. High IFIT1 can be a predictive biomarker of favorable clinical outcome, and IFIT1 along with MGMT more accurately predicts prognosis in newly diagnosed glioblastoma. PMID:26980050

  15. International Challenge to Predict the Impact of Radioxenon Releases from Medical Isotope Production on a Comprehensive Nuclear Test Ban Treaty Sampling Station

    Eslinger, Paul W.; Bowyer, Ted W.; Achim, Pascal; Chai, T.; Deconninck, Benoit; Freeman, Katie; Generoso, Sylvia; Hayes, Philip; Heidmann, Verena; Hoffman, Ian; Kijima, Yuichi; Krysta, Monika; Malo, Alain; Maurer, Christian; Ngan, Fantine; Robins, Peter; Ross, J. Ole; Saunier, Olivier; Schlosser, Clemens; Schoeppner, Michael; Schrom, Brian T.; Seibert, P.; Stein, Ariel; Ungar, Kurt; Yi, Jing

    2016-03-01

    Abstract The International Monitoring System (IMS) is part of the verification regime for the Comprehensive Nuclear-Test-Ban-Treaty Organization (CTBTO). At entry-into-force, half of the 80 radionuclide stations will be able to measure concentrations of several radioactive xenon isotopes produced in nuclear explosions, and then the full network may be populated with xenon monitoring afterward (Bowyer et al., 2013). Fission-based production of 99Mo for medical purposes also releases radioxenon isotopes to the atmosphere (Saey, 2009). One of the ways to mitigate the effect of emissions from medical isotope production is the use of stack monitoring data, if it were available, so that the effect of radioactive xenon emissions could be subtracted from the effect from a presumed nuclear explosion, when detected at an IMS station location. To date, no studies have addressed the impacts the time resolution or data accuracy of stack monitoring data have on predicted concentrations at an IMS station location. Recently, participants from seven nations used atmospheric transport modeling to predict the time-history of 133Xe concentration measurements at an IMS station in Germany using stack monitoring data from a medical isotope production facility in Belgium. Participants received only stack monitoring data and used the atmospheric transport model and meteorological data of their choice. Some of the models predicted the highest measured concentrations quite well (a high composite statistical model comparison rank or a small mean square error with the measured values). The results suggest release data on a 15 min time spacing is best. The model comparison rank and ensemble analysis suggests that combining multiple models may provide more accurate predicted concentrations than any single model. Further research is needed to identify optimal methods for selecting ensemble members and those methods may depend on the specific transport problem. None of the submissions based only

  16. Predicting the bioavailability of phosphorus in soil amended with phosphate rocks using isotopic exchange kinetics

    Investigations on plant responses to applications of various forms and rates of P fertilizers usually involve glasshouse and/or field experiments. This traditional procedure assumes that whatever the soil-fertilizer-plant system, increase in total P uptake by plant between no P treatment (control) and fertilizer treatment equals the plant P uptake from fertilizer. This study uses the isotopic exchange techniques in the laboratory to predict bioavailability of P fertilizers without the need to conduct glasshouse or field experiments. Serdang series soil (Typic Paleudult) was incubated with 7 sources of P fertilizers comprising of triple superhosphate (TSP) and phosphate rocks from North Carolina (NCPR), Algeria (APR), Tunisia (TPR), Jordan (JPR), Christmas Island (CIPR) and China (CPR) at the rates of 0, 2, 4, 6 and 8g Kg-' soil with 20% moisture content at room temperature in three replications. The soils were sampled at 1, 3, 6 and 9 months after incubation and isotopically exchangeable p determined by the method of Fardeau and Jappe (1976). Intensity, quantity and capacity factors of soil P were calculated and the residual availability of these fertilizers were predicted. Phosphorus in solution was highest in TSP treated soil for all treatments. Among the phosphate rocks, NCPR at rate 8g kg-' soil gave the highest value while, CPR at rate 2 gave the lowest value. Thus showing that these PRs have different reactivities in this soil, where NCPR, APR, TPR and JPR were the reactive PR, while CIPR and CPR were the unreactive ones. The isotopically exchangeable P at one minute (1) in the soil sampled 9 months after incubation was found to correlate very well with plant P uptake by oil palm seedlings grown under the same conditions. Calculations made on the percentage of P derived from these fertilizers up to a period of more than one year after application showed that the reactive PRs to have more residual P made available to plants than the unreactive PR

  17. Ab initio prediction of equilibrium boron isotope fractionation between minerals and aqueous fluids at high P and T

    Kowalski, Piotr M.; Wunder, Bernd; Jahn, Sandro

    2013-01-01

    Over the last decade experimental studies have shown a large B isotope fractionation between materials carrying boron incorporated in trigonally and tetrahedrally coordinated sites, but the mechanisms responsible for producing the observed isotopic signatures are poorly known. In order to understand the boron isotope fractionation processes and to obtain a better interpretation of the experimental data and isotopic signatures observed in natural samples, we use first principles calculations based on density functional theory in conjunction with ab initio molecular dynamics and a new pseudofrequency analysis method to investigate the B isotope fractionation between B-bearing minerals (such as tourmaline and micas) and aqueous fluids containing HBO and HBO4- species. We confirm the experimental finding that the isotope fractionation is mainly driven by the coordination of the fractionating boron atoms and have found in addition that the strength of the produced isotopic signature is strongly correlated with the Bsbnd O bond length. We also demonstrate the ability of our computational scheme to predict the isotopic signatures of fluids at extreme pressures by showing the consistency of computed pressure-dependent β factors with the measured pressure shifts of the Bsbnd O vibrational frequencies of HBO and HBO4- in aqueous fluid. The comparison of the predicted with measured fractionation factors between boromuscovite and neutral fluid confirms the existence of the admixture of tetrahedral boron species in neutral fluid at high P and T found experimentally, which also explains the inconsistency between the various measurements on the tourmaline-mica system reported in the literature. Our investigation shows that the calculated equilibrium isotope fractionation factors have an accuracy comparable to the experiments and give unique and valuable insight into the processes governing the isotope fractionation mechanisms on the atomic scale.

  18. Accurate Quantification of Selenoprotein P (SEPP1) in Plasma Using Isotopically Enriched Seleno-peptides and Species-Specific Isotope Dilution with HPLC Coupled to ICP-MS/MS.

    Deitrich, Christian L; Cuello-Nuñez, Susana; Kmiotek, Diana; Torma, Frank Attila; Del Castillo Busto, Maria Estela; Fisicaro, Paola; Goenaga-Infante, Heidi

    2016-06-21

    A novel strategy for the absolute quantification of selenium (Se) included in selenoprotein P (SEPP1), an important biomarker for human nutrition and disease, including diabetes and cancer, is presented here for the first time. It is based on the use of species-specific double isotope dilution mass spectrometry (SSIDA) in combination with HPLC-ICP-MS/MS for the determination of protein bound Se down to the peptide level in a complex plasma matrix with a total content of Se of 105.5 μg kg(-1). The method enabled the selective Se speciation analysis of human plasma samples without the need of extensive cleanup or preconcentration steps as required for traditional protein mass spectrometric approaches. To assess the method accuracy, two plasma reference materials, namely, BCR-637 and SRM1950, for which literature data and a reference value for SEPP1 have been reported, were analyzed using complementary hyphenated methods and the species-specific approach developed in this work. The Se mass fractions obtained via the isotopic ratios (78)Se/(76)Se and (82)Se/(76)Se for each of the Se-peptides, namely, ENLPSLCSUQGLR (ENL) and AEENITESCQUR (AEE) (where U is SeCys), were found to agree within 2.4%. A relative expanded combined uncertainty (k = 2) of 5.4% was achieved for a Se (as SEPP1) mass fraction of approximately 60 μg kg(-1). This work represents a systematic approach to the accurate quantitation of plasma SEPP1 at clinical levels using SSIDA quantification. Such methodology will be invaluable for the certification of reference materials and the provision of reference values to clinical measurements and clinical trials. PMID:27108743

  19. Elaboration of advanced predictive and interpretive models in hydrogeology: Isotope tracer movement description in the aeration zone and groundwater systems

    The authors described a cascade multicompartment model to predict migration on radioisotopes in multiplayer geological bodies on the base of the residence time and retardation factor concepts and isotope tracer techniques. The model developed needs a combination of isotope tracer techniques as a source of data on key parameters of the radionuclides transfer in geological media. The model to predict radionuclides migration takes into account a multiplayer lithological construction of the protective barrier. The Chernobyl radionuclides released into the environment should be actively used to verify mathematical models and different methodological approaches. (author)

  20. Isotopes as validation tools for predictions of the impact of Amazonian deforestation on climate and regional hydrology

    Isotopic analysis and modelling of the Amazon Basin have both been reported for about thirty years. Isotopic data have been used to explain important characteristics of Amazonian hydrologic cycling by means of simple models. To date there has been no attempt to use isotopic data to evaluate global climate models employed to predict the possible impacts of Amazonian deforestation. This paper reviews the history of isotopic analysis and simulations of deforestation in the Amazon and initiates isotopic evaluation of GCMs. It is shown that one widely reported simulation set gives seasonal transpiration and re-evaporated canopy interception budgets different from those derived from isotopic analysis. It is found that temporal changes (1965 to 1990) in wet season deuterium excess differences between Belem and Manaus are consistent with GCM results only if there has been a relative increase in evaporation from non-fractionating water sources over this period. We propose synergistic future interactions among the climate/hydrological modelling and isotopic analysis communities in order to improve confidence in simulations of Amazonian deforestation. (author)

  1. Isotopic Soret effect in ternary mixtures: Theoretical predictions and molecular simulations

    Artola, Pierre-Arnaud, E-mail: pierre-arnaud.artola@u-psud.fr [Laboratoire de Chimie-Physique, Université de Paris-Sud, Orsay (France); Rousseau, Bernard [Laboratoire de Chimie-Physique, CNRS Université de Paris-Sud, Orsay (France)

    2015-11-07

    In this paper, we study the Soret effect in ternary fluid mixtures of isotopic argon like atoms. Soret coefficients have been computed using non-equilibrium molecular dynamics and a theoretical approach based on our extended Prigogine model (with mass effect) and generalized to mixtures with any number of components. As is well known for binary mixture studies, the heaviest component always accumulates on the cold side whereas the lightest species accumulate on the hot side. An interesting behavior is observed for the species with the intermediate mass: it can accumulate on both sides, depending on composition and mass ratios. A simple picture can be given to understand this change of sign: the intermediate mass species can be seen as evolving in an equivalent fluid whose species mass varies with composition. An excellent prediction of all simulated data has been obtained using our model including the change of sign of the Soret coefficient for species with intermediate mass.

  2. Measurement of (alpha,n) reaction cross sections of erbium isotopes for testing astrophysical rate predictions

    Kiss, G G; Rauscher, T; Török, Zs; Csedreki, L; Fülöp, Zs; Gyürky, Gy; Halász, Z

    2015-01-01

    The $\\gamma$-process in core-collapse and/or type Ia supernova explosions is thought to explain the origin of the majority of the so-called $p$ nuclei (the 35 proton-rich isotopes between Se and Hg). Reaction rates for $\\gamma$-process reaction network studies have to be predicted using Hauser-Feshbach statistical model calculations. Recent investigations have shown problems in the prediction of $\\alpha$-widths at astrophysical energies which are an essential input for the statistical model. It has an impact on the reliability of abundance predictions in the upper mass range of the $p$ nuclei. With the measurement of the $^{164,166}$Er($\\alpha$,n)$^{167,169}$Yb reaction cross sections at energies close to the astrophysically relevant energy range we tested the recently suggested low energy modification of the $\\alpha$+nucleus optical potential in a mass region where $\\gamma$-process calculations exhibit an underproduction of the $p$ nuclei. Using the same optical potential for the $\\alpha$-width which was der...

  3. Isotopic uncertainty assessment due to nuclear data uncertainties in high-burnup samples.

    Cabellos de Francisco, Oscar Luis; Martínez, J. S.; Diez de la Obra, Carlos Javier

    2011-01-01

    The accurate prediction of the spent nuclear fuel content is essential for its safe and optimized transportation, storage and management. This isotopic evolution can be predicted using powerful codes and methodologies throughout irradiation as well as cooling time periods. However, in order to have a realistic confidence level in the prediction of spent fuel isotopic content, it is desirable to determine how uncertainties affect isotopic prediction calculations by quantifying their associ...

  4. How accurately can subject-specific finite element models predict strains and strength of human femora? Investigation using full-field measurements.

    Grassi, Lorenzo; Väänänen, Sami P; Ristinmaa, Matti; Jurvelin, Jukka S; Isaksson, Hanna

    2016-03-21

    Subject-specific finite element models have been proposed as a tool to improve fracture risk assessment in individuals. A thorough laboratory validation against experimental data is required before introducing such models in clinical practice. Results from digital image correlation can provide full-field strain distribution over the specimen surface during in vitro test, instead of at a few pre-defined locations as with strain gauges. The aim of this study was to validate finite element models of human femora against experimental data from three cadaver femora, both in terms of femoral strength and of the full-field strain distribution collected with digital image correlation. The results showed a high accuracy between predicted and measured principal strains (R(2)=0.93, RMSE=10%, 1600 validated data points per specimen). Femoral strength was predicted using a rate dependent material model with specific strain limit values for yield and failure. This provided an accurate prediction (strain accuracy was comparable to that obtained in state-of-the-art studies which validated their prediction accuracy against 10-16 strain gauge measurements. Fracture force was accurately predicted, with the predicted failure location being very close to the experimental fracture rim. Despite the low sample size and the single loading condition tested, the present combined numerical-experimental method showed that finite element models can predict femoral strength by providing a thorough description of the local bone mechanical response. PMID:26944687

  5. Kinetics of the Reaction of the Heaviest Hydrogen Atom with H2, the 4Heμ + H2 -> 4HeμΗ + H Reaction: Experiments, Accurate Quantal Calculations, and Variational Transition State Theory, including Kinetic Isotope Effects for a Factor of 36.1 in Isotopic Mass

    Fleming, Donald G.; Arseneau, Donald J.; Sukhorukov, Oleksandr; Brewer, Jess H.; Mielke, Steven L.; Truhlar, Donald G.; Schatz, George C.; Garrett, Bruce C.; Peterson, Kirk A.

    2011-11-14

    The neutral muonic helium atom {sup 4}He{mu}, in which one of the electrons of He is replaced by a negative muon, may be effectively regarded as the heaviest isotope of the hydrogen atom, with a mass of 4.115 amu. We report details of the first muon spin rotation ({mu}SR) measurements of the chemical reaction rate constant of {sup 4}He{mu} with molecular hydrogen, {sup 4}He{mu} + H{sub 2} {yields} {sup 4}He{mu}H + H, at temperatures of 295.5, 405, and 500 K, as well as a {mu}SR measurement of the hyperfine coupling constant of muonic He at high pressures. The experimental rate constants, k{sub He{mu}}, are compared with the predictions of accurate quantum mechanical (QM) dynamics calculations carried out on a well converged Born-Huang (BH) potential energy surface, based on complete configuration interaction calculations and including a Born-Oppenheimer diagonal correction. At the two highest measured temperatures the agreement between the quantum theory and experiment is good to excellent, well within experimental uncertainties that include an estimate of possible systematic error, but at 295.5 K the quantum calculations for k{sub He{mu}} are below the experimental value by 2.1 times the experimental uncertainty estimates. Possible reasons for this discrepancy are discussed. Variational transition state theory calculations with multidimensional tunneling have also been carried out for k{sub He{mu}} on the BH surface, and they agree with the accurate QM rate constants to within 30% over a wider temperature range of 200-1000 K. Comparisons between theory and experiment are also presented for the rate constants for both the D + H{sub 2} and Mu + H{sub 2} reactions in a novel study of kinetic isotope effects for the H + H{sub 2} reactions over a factor of 36.1 in isotopic mass of the atomic reactant.

  6. Accurately Predicting the Density and Hydrostatic Compression of Hexahydro-1,3,5-Trinitro-1,3,5-Triazine from First Principles

    SONG HuarJie; HUANG Feng-Lei

    2011-01-01

    @@ We predict the densities of crystalline hexahydro-1,3,5-trinitro-1,3,5-triazine(RDX)by introducing a factor of(1+1.5×10(-4)T)into the wavefunction-based potential of RDX constructed from first principles using the symmetry-adapted perturbation theory and the Williams-Stone-Misquitta method.The predicted values are within an accuracy of 1%of the density from O to 430K and closely reproduced the RDX densities under hydrostatic compression.This work heralds a promising approach to predicting accurately the densities of high explosives at temperatures and pressures to which they are often subjected,which is a long-standing issue in the field of energetic materials.%We predict the densities of crystalline hexahydro-l,3,5-trinitro-l,3,5-triazine (RDX) by introducing a factor of (1+1.5 x 10~* T) into the wavefunction-based potential of RDX constructed from first principles using the symmetry-adapted perturbation theory and the Williams-Stone-Misquitta method. The predicted values are within an accuracy of 1% of the density from 0 to 430 K and closely reproduced the RDX densities under hydrostatic compression. This work heralds a promising approach to predicting accurately the densities of high explosives at temperatures and pressures to which they are often subjected, which is a long-standing issue in the Beld of energetic materials.

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

    Liqi Li

    Full Text Available 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.

  8. Accurate and computationally efficient prediction of thermochemical properties of biomolecules using the generalized connectivity-based hierarchy.

    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. PMID:25068299

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

    Shiyao Wang; Zhidong Deng; Gang Yin

    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...

  10. Knowledge-guided docking: Accurate prospective prediction of bound configurations of novel ligands using Surflex-Dock

    Cleves, AE; Jain, AN

    2015-01-01

    © 2015 The Author(s). Prediction of the bound configuration of small-molecule ligands that differ substantially from the cognate ligand of a protein co-crystal structure is much more challenging than re-docking the cognate ligand. Success rates for cross-docking in the range of 20-30 % are common. We present an approach that uses structural information known prior to a particular cutoff-date to make predictions on ligands whose bounds structures were determined later. The knowledge-guided doc...

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

    Highlights: ► A novel method is introduced for desk calculation of toxicity of benzoic acid derivatives. ► There is no need to use QSAR and QSTR methods, which are based on computer codes. ► The predicted results of 58 compounds are more reliable than those predicted by QSTR method. ► The present method gives good predictions for further 324 benzoic acid compounds. - Abstract: Most of benzoic acid derivatives are toxic, which may cause serious public health and environmental problems. Two novel simple and reliable models are introduced for desk calculations of the toxicity of benzoic acid compounds in mice via oral LD50 with more reliance on their answers as one could attach to the more complex outputs. They require only elemental composition and molecular fragments without using any computer codes. The first model is based on only the number of carbon and hydrogen atoms, which can be improved by several molecular fragments in the second model. For 57 benzoic compounds, where the computed results of quantitative structure–toxicity relationship (QSTR) were recently reported, the predicted results of two simple models of present method are more reliable than QSTR computations. The present simple method is also tested with further 324 benzoic acid compounds including complex molecular structures, which confirm good forecasting ability of the second model.

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

    Keshavarz, Mohammad Hossein, E-mail: mhkeshavarz@mut-es.ac.ir [Department of Chemistry, Malek-ashtar University of Technology, Shahin-shahr P.O. Box 83145/115, Isfahan, Islamic Republic of Iran (Iran, Islamic Republic of); Gharagheizi, Farhad [Department of Chemical Engineering, Buinzahra Branch, Islamic Azad University, Buinzahra, Islamic Republic of Iran (Iran, Islamic Republic of); Shokrolahi, Arash; Zakinejad, Sajjad [Department of Chemistry, Malek-ashtar University of Technology, Shahin-shahr P.O. Box 83145/115, Isfahan, Islamic Republic of Iran (Iran, Islamic Republic of)

    2012-10-30

    Highlights: Black-Right-Pointing-Pointer A novel method is introduced for desk calculation of toxicity of benzoic acid derivatives. Black-Right-Pointing-Pointer There is no need to use QSAR and QSTR methods, which are based on computer codes. Black-Right-Pointing-Pointer The predicted results of 58 compounds are more reliable than those predicted by QSTR method. Black-Right-Pointing-Pointer The present method gives good predictions for further 324 benzoic acid compounds. - Abstract: Most of benzoic acid derivatives are toxic, which may cause serious public health and environmental problems. Two novel simple and reliable models are introduced for desk calculations of the toxicity of benzoic acid compounds in mice via oral LD{sub 50} with more reliance on their answers as one could attach to the more complex outputs. They require only elemental composition and molecular fragments without using any computer codes. The first model is based on only the number of carbon and hydrogen atoms, which can be improved by several molecular fragments in the second model. For 57 benzoic compounds, where the computed results of quantitative structure-toxicity relationship (QSTR) were recently reported, the predicted results of two simple models of present method are more reliable than QSTR computations. The present simple method is also tested with further 324 benzoic acid compounds including complex molecular structures, which confirm good forecasting ability of the second model.

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

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

    2016-09-01

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

  14. Externally validated HPV-based prognostic nomogram for oropharyngeal carcinoma patients yields more accurate predictions than TNM staging

    Purpose: Due to the established role of the human papillomavirus (HPV), the optimal treatment for oropharyngeal carcinoma is currently under debate. We evaluated the most important determinants of treatment outcome to develop a multifactorial predictive model that could provide individualized predictions of treatment outcome in oropharyngeal carcinoma patients. Methods: We analyzed the association between clinico-pathological factors and overall and progression-free survival in 168 OPSCC patients treated with curative radiotherapy or concurrent chemo-radiation. A multivariate model was validated in an external dataset of 189 patients and compared to the TNM staging system. This nomogram will be made publicly available at (www.predictcancer.org). Results: Predictors of unfavorable outcomes were negative HPV-status, moderate to severe comorbidity, T3–T4 classification, N2b–N3 stage, male gender, lower hemoglobin levels and smoking history of more than 30 pack years. Prediction of overall survival using the multi-parameter model yielded a C-index of 0.82 (95% CI, 0.76–0.88). Validation in an independent dataset yielded a C-index of 0.73 (95% CI, 0.66–0.79. For progression-free survival, the model’s C-index was 0.80 (95% CI, 0.76–0.88), with a validation C-index of 0.67, (95% CI, 0.59–0.74). Stratification of model estimated probabilities showed statistically different prognosis groups in both datasets (p < 0.001). Conclusion: This nomogram was superior to TNM classification or HPV status alone in an independent validation dataset for prediction of overall and progression-free survival in OPSCC patients, assigning patients to distinct prognosis groups. These individualized predictions could be used to stratify patients for treatment de-escalation trials

  15. Accurate and efficient prediction of fine-resolution hydrologic and carbon dynamic simulations from coarse-resolution models

    Pau, George Shu Heng; Shen, Chaopeng; Riley, William J.; Liu, Yaning

    2016-02-01

    The topography, and the biotic and abiotic parameters are typically upscaled to make watershed-scale hydrologic-biogeochemical models computationally tractable. However, upscaling procedure can produce biases when nonlinear interactions between different processes are not fully captured at coarse resolutions. Here we applied the Proper Orthogonal Decomposition Mapping Method (PODMM) to downscale the field solutions from a coarse (7 km) resolution grid to a fine (220 m) resolution grid. PODMM trains a reduced-order model (ROM) with coarse-resolution and fine-resolution solutions, here obtained using PAWS+CLM, a quasi-3-D watershed processes model that has been validated for many temperate watersheds. Subsequent fine-resolution solutions were approximated based only on coarse-resolution solutions and the ROM. The approximation errors were efficiently quantified using an error estimator. By jointly estimating correlated variables and temporally varying the ROM parameters, we further reduced the approximation errors by up to 20%. We also improved the method's robustness by constructing multiple ROMs using different set of variables, and selecting the best approximation based on the error estimator. The ROMs produced accurate downscaling of soil moisture, latent heat flux, and net primary production with O(1000) reduction in computational cost. The subgrid distributions were also nearly indistinguishable from the ones obtained using the fine-resolution model. Compared to coarse-resolution solutions, biases in upscaled ROM solutions were reduced by up to 80%. This method has the potential to help address the long-standing spatial scaling problem in hydrology and enable long-time integration, parameter estimation, and stochastic uncertainty analysis while accurately representing the heterogeneities.

  16. How accurate is our prediction of biopsy outcome? PCA3-based nomograms in personalized diagnosis of prostate cancer

    Salagierski, Maciej; Sosnowski, Marek; Schalken, Jack A.

    2012-01-01

    Purpose The sensitivity and specificity of prostate-specific antigen (PSA) alone to select men for prostate biopsy remain suboptimal. This review aims at presenting a review of current prostate cancer (PCa) nomograms that incorporate Prostate Cancer Gene 3 (PCA3), which was designed to outperform PSA at predicting biopsy outcome. Materials and methods The PubMed database and current literature search was conducted for reports on PCA3-based nomograms and tools for examining the risk of a posit...

  17. ADMET evaluation in drug discovery: 15. Accurate prediction of rat oral acute toxicity using relevance vector machine and consensus modeling

    Lei, Tailong; Li, Youyong; Song, Yunlong; Li, Dan; Sun, Huiyong; Hou, Tingjun

    2016-01-01

    Background Determination of acute toxicity, expressed as median lethal dose (LD50), is one of the most important steps in drug discovery pipeline. Because in vivo assays for oral acute toxicity in mammals are time-consuming and costly, there is thus an urgent need to develop in silico prediction models of oral acute toxicity. Results In this study, based on a comprehensive data set containing 7314 diverse chemicals with rat oral LD50 values, relevance vector machine (RVM) technique was employ...

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

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

    2016-01-01

    Background/Aim. Respectively with the prevalence of chronic hepatitis C in the world, using noninvasive methods as an alternative method in staging chronic liver diseases for avoiding the drawbacks of biopsy is significantly increasing. The aim of this study is to combine the serum biomarkers and clinical information to develop a classification model that can predict advanced liver fibrosis. Methods. 39,567 patients with chronic hepatitis C were included and randomly divided into two separate...

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

    Somaya Hashem

    2016-01-01

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

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

    Ting Wang

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

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

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

    2016-01-01

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

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

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

    2016-01-01

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

  3. Efficient Separation and Accurate Isotopic Determination of Lithium in Brine%盐湖卤水中锂的高效分离及其同位素比值的精确测定进展

    马茹莹; 韩凤清; 罗重光; 闫建平; 张燕霞

    2012-01-01

    The significant relative mass difference between the two stable isotopes of lithium makes a great lithium isotopic fractionation in nature materials. Lithium isotopes, as a tracer, have been used to indicate the material source and formation mechanism of lithium deposit. At present,the lithium isotope ratio was measured by thermal ionization mass spectrometry (TIMS) or the multiple collector inductively coupled plasma mass spectrometry ( MC-ICP-MS). Both methods require the lithium completely separated from other elements. The adsorption method, in all the lithium extractive technique,could produce higher recovery rate and minimize isotopic fractionation. This paper mainly introduced the progress of the separation and accurate isotopic determination of lithium in brine at home and abroad in recent years.%锂的两个稳定同位素相对质量差较大,导致了自然界中的锂同位素分馏强烈.卤水中锂同位素作为良好示踪剂,可用以指示盐湖锂矿床的物质来源和形成机理.现阶段一般用热电离质谱法(TIMS)或多接收器电感耦合等离子质谱法(MC-ICP-MS)测量锂同位素比值,这两种方法都需要将锂从样品中与其它元素完全分离.在现有的卤水提锂方法中,吸附法能够得到较高的锂回收率,减少了锂同位素在提取过程中的分馏效应.本文主要介绍国内外近年来在提取锂和准确测定锂同位素比值方面所取得的进展.

  4. Accurately Predicting the Density and Hydrostatic Compression of Hexahydro-1,3,5-Trinitro-1,3,5-Triazine from First Principles

    We predict the densities of crystalline hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) by introducing a factor of (1+1.5 × 10−4T) into the wavefunction-based potential of RDX constructed from first principles using the symmetry-adapted perturbation theory and the Williams—Stone—Misquitta method. The predicted values are within an accuracy of 1% of the density from 0 to 430 K and closely reproduced the RDX densities under hydrostatic compression. This work heralds a promising approach to predicting accurately the densities of high explosives at temperatures and pressures to which they are often subjected, which is a long-standing issue in the field of energetic materials. (condensed matter: structure, mechanical and thermal properties)

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

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

    2016-01-01

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

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

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

    2012-10-30

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

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

    Powell, Erica Dion

    2013-01-01

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

  8. Benchmark of SCALE (SAS2H) isotopic predictions of depletion analyses for San Onofre PWR MOX fuel

    Hermann, O.W.

    2000-02-01

    The isotopic composition of mixed-oxide (MOX) fuel, fabricated with both uranium and plutonium, after discharge from reactors is of significant interest to the Fissile Materials Disposition Program. The validation of the SCALE (SAS2H) depletion code for use in the prediction of isotopic compositions of MOX fuel, similar to previous validation studies on uranium-only fueled reactors, has corresponding significance. The EEI-Westinghouse Plutonium Recycle Demonstration Program examined the use of MOX fuel in the San Onofre PWR, Unit 1, during cycles 2 and 3. Isotopic analyses of the MOX spent fuel were conducted on 13 actinides and {sup 148}Nd by either mass or alpha spectrometry. Six fuel pellet samples were taken from four different fuel pins of an irradiated MOX assembly. The measured actinide inventories from those samples has been used to benchmark SAS2H for MOX fuel applications. The average percentage differences in the code results compared with the measurement were {minus}0.9% for {sup 235}U and 5.2% for {sup 239}Pu. The differences for most of the isotopes were significantly larger than in the cases for uranium-only fueled reactors. In general, comparisons of code results with alpha spectrometer data had extreme differences, although the differences in the calculations compared with mass spectrometer analyses were not extremely larger than that of uranium-only fueled reactors. This benchmark study should be useful in estimating uncertainties of inventory, criticality and dose calculations of MOX spent fuel.

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

    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

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

    Shiyao Wang

    2016-02-01

    Full Text Available 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.

  11. An Approach for Validating Actinide and Fission Product Burnup Credit Criticality Safety Analyses-Isotopic Composition Predictions

    The expanded use of burnup credit in the United States (U.S.) for storage and transport casks, particularly in the acceptance of credit for fission products, has been constrained by the availability of experimental fission product data to support code validation. The U.S. Nuclear Regulatory Commission (NRC) staff has noted that the rationale for restricting the Interim Staff Guidance on burnup credit for storage and transportation casks (ISG-8) to actinide-only is based largely on the lack of clear, definitive experiments that can be used to estimate the bias and uncertainty for computational analyses associated with using burnup credit. To address the issues of burnup credit criticality validation, the NRC initiated a project with the Oak Ridge National Laboratory to (1) develop and establish a technically sound validation approach for commercial spent nuclear fuel (SNF) criticality safety evaluations based on best-available data and methods and (2) apply the approach for representative SNF storage and transport configurations/conditions to demonstrate its usage and applicability, as well as to provide reference bias results. The purpose of this paper is to describe the isotopic composition (depletion) validation approach and resulting observations and recommendations. Validation of the criticality calculations is addressed in a companion paper at this conference. For isotopic composition validation, the approach is to determine burnup-dependent bias and uncertainty in the effective neutron multiplication factor (keff) due to bias and uncertainty in isotopic predictions, via comparisons of isotopic composition predictions (calculated) and measured isotopic compositions from destructive radiochemical assay utilizing as much assay data as is available, and a best-estimate Monte Carlo based method. This paper (1) provides a detailed description of the burnup credit isotopic validation approach and its technical bases, (2) describes the application of the approach for

  12. Comparisons of the predicted and measured isotopic composition for high burnup PWR spent fuels

    Comparisons between the calculated and measured isotopic composition for high burnup Korean PWR spent fuel samples were carried out. Spent fuel samples used in this study were obtained from commercial Korean PWRs, Ulchin unit 2 and Yonggwang unit 1. A radiochemical analysis of the spent fuel samples was performed to determine the isotopic compositions of U, Pu, and Nd. The depletion calculations which were carried out using the SAS2H control module in Version 5.1 of the SCALE code system were compared with the results of the radiochemical analyses. The results derived from the measured and calculated concentrations for each isotope of the corresponding samples were generally consistent with the earlier studies and the results were different within a few percent. The validity of the SAS2H control module in Version 5.1 of the SCALE code system could be confirmed in a high burnup spent fuel above 45 GWd/MTU

  13. Accurate measurement of stable isotopes 46Ca and 48Ca in human feces, plasma, and urine in relation to human nutrition of calcium

    A method based on Radiochemical Neutron Activation Analysis (RNAA) is described which allows simultaneous measurement of two stable isotopes of calcium, 46Ca and 48Ca, in human feces, plasma, and urine for the purpose of studying human nutrition and metabolism of calcium. It is shown that these measurements can be made with relative analytical precision of 1-5% depending on the particulars of a given experiment. The method has been applied in humans and data are given showing that kinetics of plasma appearance of 46Ca administered orally with food can be readily investigated. This method allows investigation of a number of important nutritional and metabolic issues in all human population groups without regard to radioisotope safety considerations, and should prove especially helpful in relation to studies of calcium bioavailability from different foods in a variety of population groups for whom use of radiocalcium is not warranted. (Auth.)

  14. Using isotopes to improve impact and hydrological predictions of land-surface schemes in global climate models

    Global climate model (GCM) predictions of the impact of large-scale land-use change date back to 1984 as do the earliest isotopic studies of large-basin hydrology. Despite this coincidence in interest and geography, with both papers focussed on the Amazon, there have been few studies that have tried to exploit isotopic information with the goal of improving climate model simulations of the land-surface. In this paper we analyze isotopic results from the IAEA global data base specifically with the goal of identifying signatures of potential value for improving global and regional climate model simulations of the land-surface. Evaluation of climate model predictions of the impacts of deforestation of the Amazon has been shown to be of significance by recent results which indicate impacts occurring distant from the Amazon i.e. tele-connections causing climate change elsewhere around the globe. It is suggested that these could be similar in magnitude and extent to the global impacts of ENSO events. Validation of GCM predictions associated with Amazonian deforestation are increasingly urgently required because of the additional effects of other aspects of climate change, particularly synergies occurring between forest removal and greenhouse gas increases, especially CO2. Here we examine three decades distributions of deuterium excess across the Amazon and use the results to evaluate the relative importance of the fractionating (partial evaporation) and non-fractionating (transpiration) processes. These results illuminate GCM scenarios of importance to the regional climate and hydrology: (i) the possible impact of increased stomatal resistance in the rainforest caused by higher levels of atmospheric CO2 [4]; and (ii) the consequences of the combined effects of deforestation and global warming on the regions climate and hydrology

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

    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

  16. Application of mass-predictions to isotope-abundances in breeder-reactor cores

    The decay-heat and isotope composition of breeder reactor-cores is calculated at normal shut-down, and a core disintegration event. Using the ORIGRN-code, the influence of the most neutron-rich fission-yield nuclei is studied. Their abundances depend on the assumption about the nuclear data (mass and half-lives). The total decay-heat is not changed from any technically view-point. (orig.)

  17. Application of mass-predictions to isotope-abundances in breeder-reactor cores

    Kirchner, G

    1981-01-01

    The decay-heat and isotope composition of breeder reactor-cores is calculated at normal shut-down, and a core disintegration event. Using the ORIGEN-code, the influence of the most neutron-rich fission-yield nuclei is studied. Their abundances depend on the assumption about the nuclear data (mass and half-lives). The total decay-heat is not changed from any technical viewpoint. (15 refs).

  18. Review of Technical Issues Related to Predicting Isotopic Compositions and Source Terms for High-Burnup LWR Fuel

    Gauld, I. C.; Parks, C. V.

    2000-12-11

    This report has been prepared to review the technical issues important to the prediction of isotopic compositions and source terms for high-burnup, light-water-reactor (LWR) fuel as utilized in the licensing of spent fuel transport and storage systems. The current trend towards higher initial 235U enrichments, more complex assembly designs, and more efficient fuel management schemes has resulted in higher spent fuel burnups than seen in the past. This trend has led to a situation where high-burnup assemblies from operating LWRs now extend beyond the area where available experimental data can be used to validate the computational methods employed to calculate spent fuel inventories and source terms. This report provides a brief review of currently available validation data, including isotopic assays, decay heat measurements, and shielded dose-rate measurements. Potential new sources of experimental data available in the near term are identified. A review of the background issues important to isotopic predictions and some of the perceived technical challenges that high-burnup fuel presents to the current computational methods are discussed. Based on the review, the phenomena that need to be investigated further and the technical issues that require resolution are presented. The methods and data development that may be required to address the possible shortcomings of physics and depletion methods in the high-burnup and high-enrichment regime are also discussed. Finally, a sensitivity analysis methodology is presented. This methodology is currently being investigated at the Oak Ridge National Laboratory as a computational tool to better understand the changing relative significance of the underlying nuclear data in the different enrichment and burnup regimes and to identify the processes that are dominant in the high-burnup regime. The potential application of the sensitivity analysis methodology to help establish a range of applicability for experimental

  19. Trajectory Calculations for Bergman Cyclization Predict H/D Kinetic Isotope Effects Due to Nonstatistical Dynamics in the Product.

    Doubleday, Charles; Boguslav, Mayla; Howell, Caronae; Korotkin, Scott D; Shaked, David

    2016-06-22

    An unusual H/D kinetic isotope effect (KIE) is described, in which isotopic selectivity arises primarily from nonstatistical dynamics in the product. In DFT-based quasiclassical trajectories of Bergman cyclization of (Z)-3-hexen-1,5-diyne (1) at 470 K, the new CC bond retains its energy, and 28% of nascent p-benzyne recrosses back to the enediyne on a vibrational time scale. The competing process of intramolecular vibrational redistribution (IVR) in p-benzyne is too slow to prevent this. Deuteration increases the rate of IVR, which decreases the fraction of recrossing and increases the yield of statistical (trapable) p-benzyne, 2. Trapable yields for three isotopomers of 2 range from 72% to 86%. The resulting KIEs for Bergman cyclization differ substantially from KIEs predicted by transition state theory, which suggests that IVR in this reaction can be studied by conventional KIEs. Leakage of vibrational zero point energy (ZPE) into the reaction coordinate was probed by trajectories in which initial ZPE in the CH/CD stretching modes was reduced by 25%. This did not change the predicted KIEs. PMID:27281683

  20. SCALE 5.1 Predictions of PWR Spent Nuclear Fuel Isotopic Compositions

    Radulescu, Georgeta [ORNL; Gauld, Ian C [ORNL; Ilas, Germina [ORNL

    2010-03-01

    The purpose of this calculation report is to document the comparison to measurement of the isotopic concentrations for pressurized water reactor (PWR) spent nuclear fuel determined with the Standardized Computer Analysis for Licensing Evaluation (SCALE) 5.1 (Ref. ) epletion calculation method. Specifically, the depletion computer code and the cross-section library being evaluated are the twodimensional (2-D) transport and depletion module, TRITON/NEWT,2, 3 and the 44GROUPNDF5 (Ref. 4) cross-section library, respectively, in the SCALE .1 code system.

  1. Prediction of isotope effects for anticipated intermediate structures in the course of bacterial denitrification

    Vibrational-analysis methods have been used to estimate the equilibrium 14N/15N isotope effects to be expected for conversion of nitrite anion to thirteen possible intermediate-state and product-state structures [HONO, NO+, NO, NO-, FeNO, ON*NO2, O*NNO2, O2NNO2, ONO*N, O*NON, ONNO, *NNO, N*NO] in the reduction of nitrite ion to nitrous oxide denitrifying bacteria. The results, taken in combination with previous experimental isotope-effect and tracer studies of the Pseudomonas stutzeri and related systems, are consistent with a suggestion that a second nitrite anion enters the enzyme-catalytic cycle at the stage of a nitrosyl-ion intermediate but re-emerges after entry of the reducing electrons; the product nitrous oxide is then formed by disproportionation of enzymically generated hyponitrous acid. The calculations are consistent with contributions, under different experimental conditions, of several different transition states to limiting the rate of the enzymic reaction. These transition states (and the corresponding experimental conditions) are the transition states for N-O fission in the generation of a mononitrogen electrophilic species from nitrite anion (high reductant, high nitrite concentrations), for attack of nitrite on this electrophile (high reductant, low nitrite concentrations) and for electron transfer to a dinitrogen-trioxide-like species (low reductant concentration). (orig.)

  2. Validation of spent-fuel isotopics predicted by the SCALE-4 depletion sequence

    The Standardized Computer Analyses for Licensing Evaluation (SCALE) code system is used extensively to perform away-from-reactor safety analyses (particularly criticality safety, shielding, and heat transfer analyses) for spent light water reactor fuel. Spent-fuel characteristics, such as radiation sources, heat generation sources, and isotopic concentrations, can be computed within SCALE using the SAS2 control module. At user-defined time steps, the SAS2 sequence performs a radiation transport analysis (via XSDRNPM-S) to obtain appropriate cross sections and spectral parameters for an ORIGEN-S point-depletion analysis. Each ORIGEN-S case produces the burnup-dependent fuel composition to be used in the next spectral calculation. Thus, the burnup-dependent cross sections and spectral parameters generated for ORIGEN-S are dependent on the initial enrichment, specified power history, and assembly model input to SAS2. A final ORIGEN-S case is used to perform the complete depletion/decay analysis using the burnup-dependent cross sections developed by the iterative scheme. The latest version of the SAS2 control module as released with SCALE-4 is denoted SAS2H. The purpose of this paper is to report recent SAS2H/ORIGEN-S calculations that were performed to compare pressurized water reactor (PWR) spent-fuel isotopic concentrations with measured data determined by radiochemical analyses

  3. Defining the Most Accurate Measurable Dimension(s of the Liver in Predicting Liver Volume Based on CT Volumetery and Reconstruction

    Reza Saadat Mostafavi

    2010-05-01

    Full Text Available Background/Objective: The presence of liver volume has a great effect on diagnosis and management of different diseases such as lymphoproliferative conditions. "nPatients and Methods: Abdominal CT scan of 100 patients without any findings for liver disease (in history and imaging was subjected to volumetry and reconstruction. Along with the liver volume, in axial series, the AP diameter of the left lobe (in midline and right lobe (mid-clavicular and lateral maximum diameter of the liver in the mid-axiliary line and maximum diameter to IVC were calculated. In the coronal mid-axillary and sagittal mid-clavicular plane, maximum superior-inferior dimensions were calculated with their various combinations (multiplying. Regression analysis between dimensions and volume were performed. "nResults: The most accurate combination was the superior inferior sagittal dimension multiplied by AP diameter of the right lobe (R squared 0.78, P-value<0.001 and the most solitary dimension was the lateral dimension to IVC in the axial plane (R squared 0.57, P-value<0.001 with an interval of 9-11cm for 68% of normal. "nConclusion: We recommend the lateral maximum diameter of liver from surface to IVC in the axial plane in ultrasound for liver volume prediction with an interval of 9-11cm for 68% of normal. Out of this range is regarded as abnormal.

  4. Accurate Prediction of Essential Fundamental Properties for Semiconductors Used in Solar-Energy Conversion Devices from Range-Separated Hybrid Density Functional Theory

    Harb, Moussab

    2016-01-05

    An essential issue in developing new semiconductors for photovoltaics devices is to design materials with appropriate fundamental parameters related to the light absorption, photogenerated exciton dissociation and charge carrier diffusion. These phenomena are governed by intrinsic properties of the semiconductor like the bandgap, the dielectric constant, the charge carrier effective masses, and the exciton binding energy. We present here the results of a systematic theoretical study on the fundamental properties of a series of selected semiconductors widely used in inorganic photovoltaic and dye-sensitized solar cells such as Si, Ge, CdS, CdSe, CdTe, and GaAs. These intrinsic properties were computed in the framework of the density functional theory (DFT) along with the standard PBE and the range-separated hybrid (HSE06) exchange-correlation functionals. Our calculations clearly show that the computed values using HSE06 reproduce with high accuracy the experimental data. The evaluation and accurate prediction of these key properties using HSE06 open nice perspectives for in silico design of new suitable candidate materials for solar energy conversion applications.

  5. Isotope and Patient Age Predict for PSA Spikes After Permanent Prostate Brachytherapy

    Purpose: To evaluate prostate-specific antigen (PSA) spikes after permanent prostate brachytherapy in low-risk patients. Methods and Materials: The study population consisted of 164 prostate cancer patients who were part of a prospective randomized trial comparing 103Pd and 125I for low-risk disease. Of the 164 patients, 61 (37.2%) received short-course androgen deprivation therapy. The median follow-up was 5.4 years. On average, 11.1 post-treatment PSA measurements were obtained per patient. Biochemical disease-free survival was defined as a PSA level of ≤0.40 ng/mL after nadir. A PSA spike was defined as an increase of ≥0.2 ng/mL, followed by a durable decline to prespike levels. Multiple parameters were evaluated as predictors for a PSA spike. Results: Of the 164 patients, 44 (26.9%) developed a PSA spike. Of the 46 hormone-naive 125I patients and 57 hormone-naive 103Pd patients, 21 (45.7%) and 8 (14.0%) developed a PSA spike. In the hormone-naive patients, the mean time between implantation and the spike was 22.6 months and 18.7 months for 125I and 103Pd, respectively. In patients receiving neoadjuvant androgen deprivation therapy, the incidence of spikes was comparable between isotopes (125I 28.1% and 103Pd 20.7%). The incidence of spikes was substantially different in patients 125I and/or <65 years of age. Differences in isotope-related spikes are most pronounced in hormone-naive patients

  6. New Approaches to Assessing and Predicting the Hydrologic Impacts of Urban Disturbance Using Isotopes and Transit Time Analysis

    Soulsby, C.; Geris, J.; Birkel, C.; Tetzlaff, D.

    2015-12-01

    Urbanization is an abrupt hydrological disturbance that affects large parts of the world. For ameliorative management, an understanding of how flow partitioning and storage dynamics are affected is crucial, yet this remains limited. This reflects the lack of integrated monitoring and modelling frameworks for characterizing these hydrological response dynamics to incremental urban development. Here we use a coupled flow-isotope model to assess the impacts of urbanisation (~20%) on stream water age distributions in an 8 km2 catchment. A conceptual runoff model was used with flux tracking to estimate the time-varying age of stream water at the outlet and both urban and non-urban sub-catchments over a 3 year period. Combined objective functions of both flow and isotope metric constrained model structures, improved calibration and aided model evaluation. Specifically, we explored (1) the age distribution of stream water draining urban and non-urban areas, (2) the integrated effect of these different land uses at larger catchment scales, and (3) how the modelling can predict the impacts on the stream water age of future urbanization proposals. The results showed that stream water draining the most urbanized tributary was youngest with a mean transit time (MTT) of < 6 months compared with ~18 months in the non-urban tributary. For the catchment outlet, the MTT was around 9 months. Here, the response of urban areas dominated smaller and moderate events, but rural contributions dominated during the wettest periods, giving a bi-modal distribution of water ages. Predictions for planned developments in the area indicated that just a 5% increase in urban area would give dramatic reductions in MTTs that can propagate to the larger catchment scale. This novel approach offers a framework for understanding the cumulative impacts of disturbances on streams. It can also contribute to the design of more sustainable urban water design in terms of targeted restriction of rapid water

  7. Kinetic isotope effect of the {sup 16}O + {sup 36}O{sub 2} and {sup 18}O + {sup 32}O{sub 2} isotope exchange reactions: Dominant role of reactive resonances revealed by an accurate time-dependent quantum wavepacket study

    Sun, Zhigang, E-mail: zsun@dicp.ac.cn; Yu, Dequan; Xie, Wenbo; Hou, Jiayi [State Key Laboratory of Molecular Reaction Dynamics and Center for Theoretical and Computational Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China and Center for Advanced Chemical Physics and 2011 Frontier Center for Quantum Science and Technology, University of Science and Technology of China, 96 Jinzhai Road, Hefei 230026 (China); Dawes, Richard [Department of Chemistry, Missouri University of Science and Technology, Rolla, Missouri 65409 (United States); Guo, Hua [Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, New Mexico 87131 (United States)

    2015-05-07

    The O + O{sub 2} isotope exchange reactions play an important role in determining the oxygen isotopic composition of a number of trace gases in the atmosphere, and their temperature dependence and kinetic isotope effects (KIEs) provide important constraints on our understanding of the origin and mechanism of these and other unusual oxygen KIEs important in the atmosphere. This work reports a quantum dynamics study of the title reactions on the newly constructed Dawes-Lolur-Li-Jiang-Guo (DLLJG) potential energy surface (PES). The thermal reaction rate coefficients of both the {sup 18}O + {sup 32}O{sub 2} and {sup 16}O + {sup 36}O{sub 2} reactions obtained using the DLLJG PES exhibit a clear negative temperature dependence, in sharp contrast with the positive temperature dependence obtained using the earlier modified Siebert-Schinke-Bittererova (mSSB) PES. In addition, the calculated KIE shows an improved agreement with the experiment. These results strongly support the absence of the “reef” structure in the entrance/exit channels of the DLLJG PES, which is present in the mSSB PES. The quantum dynamics results on both PESs attribute the marked KIE to strong near-threshold reactive resonances, presumably stemming from the mass differences and/or zero point energy difference between the diatomic reactant and product. The accurate characterization of the reactivity for these near-thermoneutral reactions immediately above the reaction threshold is important for correct characterization of the thermal reaction rate coefficients.

  8. Calculation of partial widths and isotope effects for reactive resonances by a reaction-path Hamiltonian model: Test against accurate quantal results for a twin-saddle point system

    We calculate the partial widths of three collisional resonances in a collinear system with mass combinations HFH and DFD on a low-barrier model potential energy surface. We compare accurate quantal results to results obtained with a reaction-path Hamiltonian model in which the resonances are interpreted as quasibound states trapped in wells of adiabatic potential curves and their decay probabilities are calculated by semiclassical tunneling calculations and a Feshbach golden-rule formula with the decay mediated by an internal centrifugal interaction proportional to the curvature of the reaction path. The model successfully predicts when vibrationally nonadiabatic decay dominates over the adiabatic mechanism for decomposition of the resonances and it predicts the nonadiabatic partial widths with an average error of 25%

  9. Ab initio prediction of equilibrium boron isotope fractionation between minerals and aqueous fluids at high P and T

    Kowalski, Piotr M; Jahn, Sandro

    2012-01-01

    Over the last decade experimental studies have shown a large B isotope fractionation between materials carrying boron incorporated in trigonally and tetrahedrally coordinated sites, but the mechanisms responsible for producing the observed isotopic signatures are poorly known. In order to understand the boron isotope fractionation processes and to obtain a better interpretation of the experimental data and isotopic signatures observed in natural samples, we use first principles calculations based on density functional theory in conjunction with ab initio molecular dynamics and a new pseudofrequency analysis method to investigate the B isotope fractionation between B-bearing minerals (such as tourmaline and micas) and aqueous fluids containing H_3BO_3 and H_4BO_4- species. We confirm the experimental finding that the isotope fractionation is mainly driven by the coordination of the fractionating boron atoms and have found in addition that the strength of the produced isotopic signature is strongly correlated w...

  10. Predicting outcomes of steady-state 13C isotope tracing experiments using Monte Carlo sampling

    Schellenberger Jan

    2012-01-01

    Full Text Available Abstract Background Carbon-13 (13C analysis is a commonly used method for estimating reaction rates in biochemical networks. The choice of carbon labeling pattern is an important consideration when designing these experiments. We present a novel Monte Carlo algorithm for finding the optimal substrate input label for a particular experimental objective (flux or flux ratio. Unlike previous work, this method does not require assumption of the flux distribution beforehand. Results Using a large E. coli isotopomer model, different commercially available substrate labeling patterns were tested computationally for their ability to determine reaction fluxes. The choice of optimal labeled substrate was found to be dependent upon the desired experimental objective. Many commercially available labels are predicted to be outperformed by complex labeling patterns. Based on Monte Carlo Sampling, the dimensionality of experimental data was found to be considerably less than anticipated, suggesting that effectiveness of 13C experiments for determining reaction fluxes across a large-scale metabolic network is less than previously believed. Conclusions While 13C analysis is a useful tool in systems biology, high redundancy in measurements limits the information that can be obtained from each experiment. It is however possible to compute potential limitations before an experiment is run and predict whether, and to what degree, the rate of each reaction can be resolved.

  11. In vivo prediction of goat kids body composition from the deuterium oxide dilution space determined by isotope-ratio mass spectrometry.

    Lerch, S; Lastel, M L; Grandclaudon, C; Brechet, C; Rychen, G; Feidt, C

    2015-09-01

    Deuterium oxide dilution space (DOS) determination is one of the most accurate methods for in vivo estimation of ruminant body composition. However, the time-consuming vacuum sublimation of blood preceding infrared spectroscopy analysis, which is traditionally used to determine deuterium oxide (DO) concentration, limits its current use. The use of isotope-ratio mass spectrometry (IRMS) to determine the deuterium enrichment and thus quantify DO in plasma could counteract this limitation by reducing the sample preparation for plasma deproteinisation through centrifugal filters. The aim of this study was to validate the DOS technique using IRMS in growing goat kids to establish in vivo prediction equations of body composition. Seventeen weaned male Alpine goat kids (8.6 wk old) received a hay-based diet supplemented with 2 types of concentrates providing medium ( = 9) or high ( = 8) energy levels. Kids were slaughtered at 14.0 ( = 1, medium-energy diet), 17.2 ( = 4, medium-energy diet, and = 4, high-energy diet), or 21.2 wk of age ( = 4, medium-energy diet, and = 4, high-energy diet). Two days before slaughter, DOS was determined after an intravenous injection of 0.2 g DO/kg body mass (BM) and the resulting study of DO dilution kinetics from 4 plasma samples (+5, +7, +29, and +31 h after injection). The deuterium enrichment was analyzed by IRMS. After slaughter, the gut contents were discarded, the empty body (EB) was minced, and EB water, lipid, protein, ash, and energy contents were measured by chemical analyses. Prediction equations for body components measured postmortem were computed from in vivo BM and DOS. The lack of postmortem variation of fat-free EB composition was confirmed (mean of 75.3% [SD 0.6] of water), and the proportion of lipids in the EB tended ( = 0.06) to be greater for the high-energy diet (13.1%) than for the medium-energy diet (11.1%). There was a close negative relationship (residual CV [rCV] = 3.9%, = 0.957) between EB water and lipid

  12. Equilibrium isotopic fractionation in the kaolinite, quartz, water system : Prediction from first-principles density-functional theory

    Meheut, M.; Lazzeri, M.; Balan, Etienne; Mauri, F.

    2007-01-01

    Isotopic fractionation factors for oxygen, hydrogen and silicon have been calculated using first-principles methods for the kaolinite, quartz, water (ice and gas water) system. Good agreement between theory and experiment is obtained for mineral-water oxygen isotope fractionation. This approach gives reliable results on isotopic fractionation factors as a function of temperature, within a relative precision of typically 5%. These calculations provide independent quantitative constraints on th...

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

    Lundegaard, Claus; Lamberth, K; Harndahl, M;

    2008-01-01

    NetMHC-3.0 is trained on a large number of quantitative peptide data using both affinity data from the Immune Epitope Database and Analysis Resource (IEDB) and elution data from SYFPEITHI. The method generates high-accuracy predictions of major histocompatibility complex (MHC): peptide binding. The...... predictions are based on artificial neural networks trained on data from 55 MHC alleles (43 Human and 12 non-human), and position-specific scoring matrices (PSSMs) for additional 67 HLA alleles. As only the MHC class I prediction server is available, predictions are possible for peptides of length 8–11 for...... all 122 alleles. artificial neural network predictions are given as actual IC50 values whereas PSSM predictions are given as a log-odds likelihood scores. The output is optionally available as download for easy post-processing. The training method underlying the server is the best available, and has...

  14. Development of an accurate, sensitive, and robust isotope dilution laser ablation ICP-MS method for simultaneous multi-element analysis (chlorine, sulfur, and heavy metals) in coal samples

    A method for the direct multi-element determination of Cl, S, Hg, Pb, Cd, U, Br, Cr, Cu, Fe, and Zn in powdered coal samples has been developed by applying inductively coupled plasma isotope dilution mass spectrometry (ICP-IDMS) with laser-assisted introduction into the plasma. A sector-field ICP-MS with a mass resolution of 4,000 and a high-ablation rate laser ablation system provided significantly better sensitivity, detection limits, and accuracy compared to a conventional laser ablation system coupled with a quadrupole ICP-MS. The sensitivity ranges from about 590 cps for 35Cl+ to more than 6 x 105 cps for 238U+ for 1 μg of trace element per gram of coal sample. Detection limits vary from 450 ng g-1 for chlorine and 18 ng g-1 for sulfur to 9.5 pg g-1 for mercury and 0.3 pg g-1 for uranium. Analyses of minor and trace elements in four certified reference materials (BCR-180 Gas Coal, BCR-331 Steam Coal, SRM 1632c Trace Elements in Coal, SRM 1635 Trace Elements in Coal) yielded good agreement of usually not more than 5% deviation from the certified values and precisions of less than 10% relative standard deviation for most elements. Higher relative standard deviations were found for particular elements such as Hg and Cd caused by inhomogeneities due to associations of these elements within micro-inclusions in coal which was demonstrated for Hg in SRM 1635, SRM 1632c, and another standard reference material (SRM 2682b, Sulfur and Mercury in Coal). The developed LA-ICP-IDMS method with its simple sample pretreatment opens the possibility for accurate, fast, and highly sensitive determinations of environmentally critical contaminants in coal as well as of trace impurities in similar sample materials like graphite powder and activated charcoal on a routine basis. (orig.)

  15. Nuclear-Analytical and Mineralogical Principles and Techniques for Prediction and Investigation of the Native-Pure Rare Isotope Occurrence

    Combining nuclear microanalytical, mineralogical, crystallochemical and geochemical approaches, the authors analyze a possibility of natural occurrence of enriched or even pure and super pure rare isotopes that can be extracted from ores. Methods of and results from the investigations of these isotope anomalies are presented

  16. Is scoring system of computed tomography based metric parameters can accurately predicts shock wave lithotripsy stone-free rates and aid in the development of treatment strategies?

    Yasser ALI Badran

    2016-01-01

    Conclusion: Stone size, stone density (HU, and SSD is simple to calculate and can be reported by radiologists to applying combined score help to augment predictive power of SWL, reduce cost, and improving of treatment strategies.

  17. The predicted production cross sections using HIVAP code for the synthesis of unknown isotopes of element Fm

    Super heavy element (SHE) research has reached a high degree of sophistication and elements up to Z=118 have been produced. However a gap remains in the upper end of the nuclear chart between the isotopes produced in cold- and hot-fusion reactions. It is a challenging task to synthesise the missing isotopes experimentally for which suitable projectile target combinations may not be available. Theoretical energy dependent evaporation residue cross-section (σER) calculations are useful in assisting experimentalists to plan future experiments. As an illustration we present the calculated production cross-sections using the HIVAP code to synthesise presently unknown Fermium isotopes

  18. Development of an accurate, sensitive, and robust isotope dilution laser ablation ICP-MS method for simultaneous multi-element analysis (chlorine, sulfur, and heavy metals) in coal samples

    Boulyga, Sergei F. [University of Natural Resources and Applied Life Sciences, Department of Chemistry, Division of Analytical Chemistry-VIRIS Laboratory, Vienna (Austria); Johannes Gutenberg-University, Institute of Inorganic Chemistry and Analytical Chemistry, Mainz (Germany); Heilmann, Jens; Heumann, Klaus G. [Johannes Gutenberg-University, Institute of Inorganic Chemistry and Analytical Chemistry, Mainz (Germany); Prohaska, Thomas [University of Natural Resources and Applied Life Sciences, Department of Chemistry, Division of Analytical Chemistry-VIRIS Laboratory, Vienna (Austria)

    2007-10-15

    A method for the direct multi-element determination of Cl, S, Hg, Pb, Cd, U, Br, Cr, Cu, Fe, and Zn in powdered coal samples has been developed by applying inductively coupled plasma isotope dilution mass spectrometry (ICP-IDMS) with laser-assisted introduction into the plasma. A sector-field ICP-MS with a mass resolution of 4,000 and a high-ablation rate laser ablation system provided significantly better sensitivity, detection limits, and accuracy compared to a conventional laser ablation system coupled with a quadrupole ICP-MS. The sensitivity ranges from about 590 cps for {sup 35}Cl{sup +} to more than 6 x 10{sup 5} cps for {sup 238}U{sup +} for 1 {mu}g of trace element per gram of coal sample. Detection limits vary from 450 ng g{sup -1} for chlorine and 18 ng g{sup -1} for sulfur to 9.5 pg g{sup -1} for mercury and 0.3 pg g{sup -1} for uranium. Analyses of minor and trace elements in four certified reference materials (BCR-180 Gas Coal, BCR-331 Steam Coal, SRM 1632c Trace Elements in Coal, SRM 1635 Trace Elements in Coal) yielded good agreement of usually not more than 5% deviation from the certified values and precisions of less than 10% relative standard deviation for most elements. Higher relative standard deviations were found for particular elements such as Hg and Cd caused by inhomogeneities due to associations of these elements within micro-inclusions in coal which was demonstrated for Hg in SRM 1635, SRM 1632c, and another standard reference material (SRM 2682b, Sulfur and Mercury in Coal). The developed LA-ICP-IDMS method with its simple sample pretreatment opens the possibility for accurate, fast, and highly sensitive determinations of environmentally critical contaminants in coal as well as of trace impurities in similar sample materials like graphite powder and activated charcoal on a routine basis. (orig.)

  19. c-myc, not her-2/neu, can predict the prognosis of breast cancer patients: how novel, how accurate, and how significant?

    The predictive and prognostic implication of oncogene amplification in breast cancer has received great attention in the past two decades. her-2/neu and c-myc are two oncogenes that are frequently amplified and overexpressed in breast carcinomas. Despite the extensive data on these oncogenes, their prognostic and predictive impact on breast cancer patients remains controversial. Schlotter and colleagues have recently suggested that c-myc, and not her-2/neu, could predict the recurrence and mortality of patients with node-negative breast carcinomas. Regardless of the promising results, caution should be exercised in the interpretation of data from studies assessing gene amplification without in situ analysis. We address the novelty, accuracy and clinical significance of the study by Schlotter and colleagues

  20. The accurate definition of metabolic volumes on 18F-FDG-PET before treatment allows the response to chemoradiotherapy to be predicted in the case of oesophagus cancers

    This study aims at assessing the possibility of prediction of the response of locally advanced oesophagus cancers, even before the beginning of treatment, by using metabolic volume measurements performed on 18F-FDG PET images made before the treatment. Medical files of 50 patients have been analyzed. According to the observed responses, and to metabolic volume and Total Lesion Glycosis (TLG) values, it appears that the images allow the extraction of parameters, such as the TLG, which are criteria for the prediction of the therapeutic response. Short communication

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

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

    2013-10-01

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

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

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

    2015-01-01

    Background: The natural clinical course of Ulcerative Colitis (UC) is characterized by episodes of relapse and remission. Fecal Calprotectin (FC) is a relatively new marker of intestinal inflammation and is an available, non-expensive tool for predicting relapse of quiescent UC. The Seo colitis activity index is a clinical index for assessment of the severity of UC. Objectives: The present study aimed to evaluate the accuracy of FC and the Seo colitis activity index and their correlation in p...

  3. Predicting equilibrium vapour pressure isotope effects by using artificial neural networks or multi-linear regression - A quantitative structure property relationship approach.

    Parinet, Julien; Julien, Maxime; Nun, Pierrick; Robins, Richard J; Remaud, Gerald; Höhener, Patrick

    2015-09-01

    We aim at predicting the effect of structure and isotopic substitutions on the equilibrium vapour pressure isotope effect of various organic compounds (alcohols, acids, alkanes, alkenes and aromatics) at intermediate temperatures. We attempt to explore quantitative structure property relationships by using artificial neural networks (ANN); the multi-layer perceptron (MLP) and compare the performances of it with multi-linear regression (MLR). These approaches are based on the relationship between the molecular structure (organic chain, polar functions, type of functions, type of isotope involved) of the organic compounds, and their equilibrium vapour pressure. A data set of 130 equilibrium vapour pressure isotope effects was used: 112 were used in the training set and the remaining 18 were used for the test/validation dataset. Two sets of descriptors were tested, a set with all the descriptors: number of(12)C, (13)C, (16)O, (18)O, (1)H, (2)H, OH functions, OD functions, CO functions, Connolly Solvent Accessible Surface Area (CSA) and temperature and a reduced set of descriptors. The dependent variable (the output) is the natural logarithm of the ratios of vapour pressures (ln R), expressed as light/heavy as in classical literature. Since the database is rather small, the leave-one-out procedure was used to validate both models. Considering higher determination coefficients and lower error values, it is concluded that the multi-layer perceptron provided better results compared to multi-linear regression. The stepwise regression procedure is a useful tool to reduce the number of descriptors. To our knowledge, a Quantitative Structure Property Relationship (QSPR) approach for isotopic studies is novel. PMID:25559176

  4. Normal Tissue Complication Probability Estimation by the Lyman-Kutcher-Burman Method Does Not Accurately Predict Spinal Cord Tolerance to Stereotactic Radiosurgery

    Purpose: To determine whether normal tissue complication probability (NTCP) analyses of the human spinal cord by use of the Lyman-Kutcher-Burman (LKB) model, supplemented by linear–quadratic modeling to account for the effect of fractionation, predict the risk of myelopathy from stereotactic radiosurgery (SRS). Methods and Materials: From November 2001 to July 2008, 24 spinal hemangioblastomas in 17 patients were treated with SRS. Of the tumors, 17 received 1 fraction with a median dose of 20 Gy (range, 18–30 Gy) and 7 received 20 to 25 Gy in 2 or 3 sessions, with cord maximum doses of 22.7 Gy (range, 17.8–30.9 Gy) and 22.0 Gy (range, 20.2–26.6 Gy), respectively. By use of conventional values for α/β, volume parameter n, 50% complication probability dose TD50, and inverse slope parameter m, a computationally simplified implementation of the LKB model was used to calculate the biologically equivalent uniform dose and NTCP for each treatment. Exploratory calculations were performed with alternate values of α/β and n. Results: In this study 1 case (4%) of myelopathy occurred. The LKB model using radiobiological parameters from Emami and the logistic model with parameters from Schultheiss overestimated complication rates, predicting 13 complications (54%) and 18 complications (75%), respectively. An increase in the volume parameter (n), to assume greater parallel organization, improved the predictive value of the models. Maximum-likelihood LKB fitting of α/β and n yielded better predictions (0.7 complications), with n = 0.023 and α/β = 17.8 Gy. Conclusions: The spinal cord tolerance to the dosimetry of SRS is higher than predicted by the LKB model using any set of accepted parameters. Only a high α/β value in the LKB model and only a large volume effect in the logistic model with Schultheiss data could explain the low number of complications observed. This finding emphasizes that radiobiological models traditionally used to estimate spinal cord NTCP

  5. PredPPCrys: accurate prediction of sequence cloning, protein production, purification and crystallization propensity from protein sequences using multi-step heterogeneous feature fusion and selection.

    Huilin Wang

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

  6. Race-specific genetic risk score is more accurate than nonrace-specific genetic risk score for predicting prostate cancer and high-grade diseases

    Na, Rong; Ye, Dingwei; Qi, Jun; Liu, Fang; Lin, Xiaoling; Helfand, Brian T; Brendler, Charles B; Conran, Carly; Gong, Jian; Wu, Yishuo; Gao, Xu; Chen, Yaqing; Zheng, S Lilly; Mo, Zengnan; Ding, Qiang; Sun, Yinghao; Xu, Jianfeng

    2016-01-01

    Genetic risk score (GRS) based on disease risk-associated single nucleotide polymorphisms (SNPs) is an informative tool that can be used to provide inherited information for specific diseases in addition to family history. However, it is still unknown whether only SNPs that are implicated in a specific racial group should be used when calculating GRSs. The objective of this study is to compare the performance of race-specific GRS and nonrace-specific GRS for predicting prostate cancer (PCa) among 1338 patients underwent prostate biopsy in Shanghai, China. A race-specific GRS was calculated with seven PCa risk-associated SNPs implicated in East Asians (GRS7), and a nonrace-specific GRS was calculated based on 76 PCa risk-associated SNPs implicated in at least one racial group (GRS76). The means of GRS7 and GRS76 were 1.19 and 1.85, respectively, in the study population. Higher GRS7 and GRS76 were independent predictors for PCa and high-grade PCa in univariate and multivariate analyses. GRS7 had a better area under the receiver-operating curve (AUC) than GRS76 for discriminating PCa (0.602 vs 0.573) and high-grade PCa (0.603 vs 0.575) but did not reach statistical significance. GRS7 had a better (up to 13% at different cutoffs) positive predictive value (PPV) than GRS76. In conclusion, a race-specific GRS is more robust and has a better performance when predicting PCa in East Asian men than a GRS calculated using SNPs that are not shown to be associated with East Asians. PMID:27140652

  7. A random forest based risk model for reliable and accurate prediction of receipt of transfusion in patients undergoing percutaneous coronary intervention.

    Hitinder S Gurm

    Full Text Available BACKGROUND: Transfusion is a common complication of Percutaneous Coronary Intervention (PCI and is associated with adverse short and long term outcomes. There is no risk model for identifying patients most likely to receive transfusion after PCI. The objective of our study was to develop and validate a tool for predicting receipt of blood transfusion in patients undergoing contemporary PCI. METHODS: Random forest models were developed utilizing 45 pre-procedural clinical and laboratory variables to estimate the receipt of transfusion in patients undergoing PCI. The most influential variables were selected for inclusion in an abbreviated model. Model performance estimating transfusion was evaluated in an independent validation dataset using area under the ROC curve (AUC, with net reclassification improvement (NRI used to compare full and reduced model prediction after grouping in low, intermediate, and high risk categories. The impact of procedural anticoagulation on observed versus predicted transfusion rates were assessed for the different risk categories. RESULTS: Our study cohort was comprised of 103,294 PCI procedures performed at 46 hospitals between July 2009 through December 2012 in Michigan of which 72,328 (70% were randomly selected for training the models, and 30,966 (30% for validation. The models demonstrated excellent calibration and discrimination (AUC: full model  = 0.888 (95% CI 0.877-0.899, reduced model AUC = 0.880 (95% CI, 0.868-0.892, p for difference 0.003, NRI = 2.77%, p = 0.007. Procedural anticoagulation and radial access significantly influenced transfusion rates in the intermediate and high risk patients but no clinically relevant impact was noted in low risk patients, who made up 70% of the total cohort. CONCLUSIONS: The risk of transfusion among patients undergoing PCI can be reliably calculated using a novel easy to use computational tool (https://bmc2.org/calculators/transfusion. This risk prediction

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

    Byun, Jaeseung; Bodony, Daniel; Pantano, Carlos

    2014-11-01

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

  9. A New Strategy for Accurately Predicting I-V Electrical Characteristics of PV Modules Using a Nonlinear Five-Point Model

    Sakaros Bogning Dongue

    2013-01-01

    Full Text Available This paper presents the modelling of electrical I-V response of illuminated photovoltaic crystalline modules. As an alternative method to the linear five-parameter model, our strategy uses advantages of a nonlinear analytical five-point model to take into account the effects of nonlinear variations of current with respect to solar irradiance and of voltage with respect to cells temperature. We succeeded in this work to predict with great accuracy the I-V characteristics of monocrystalline shell SP75 and polycrystalline GESOLAR GE-P70 photovoltaic modules. The good comparison of our calculated results to experimental data provided by the modules manufacturers makes it possible to appreciate the contribution of taking into account the nonlinear effect of operating conditions data on I-V characteristics of photovoltaic modules.

  10. Is the predicted postoperative FEV1 estimated by planar lung perfusion scintigraphy accurate in patients undergoing pulmonary resection? Comparison of two processing methods

    Estimation of postoperative forced expiratory volume in 1 s (FEV1) with radionuclide lung scintigraphy is frequently used to define functional operability in patients undergoing lung resection. We conducted a study to outline the reliability of planar quantitative lung perfusion scintigraphy (QLPS) with two different processing methods to estimate the postoperative lung function in patients with resectable lung disease. Forty-one patients with a mean age of 57±12 years who underwent either a pneumonectomy (n=14) or a lobectomy (n=27) were included in the study. QLPS with Tc-99m macroaggregated albumin was performed. Both three equal zones were generated for each lung [zone method (ZM)] and more precise regions of interest were drawn according to their anatomical shape in the anterior and posterior projections [lobe mapping method (LMM)] for each patient. The predicted postoperative (ppo) FEV1 values were compared with actual FEV1 values measured on postoperative day 1 (pod1 FEV1) and day 7 (pod7 FEV1). The mean of preoperative FEV 1 and ppoFEV1 values was 2.10±0.57 and 1.57±0.44 L, respectively. The mean of Pod1FEV1 (1.04±0.30 L) was lower than ppoFEV1 (p0.05). PpoFEV1 values predicted by both the zone and LMMs overestimated the actual measured lung volumes in patients undergoing pulmonary resection in the early postoperative period. LMM is not superior to ZM. (author)

  11. Accurate prediction of the binding free energy and analysis of the mechanism of the interaction of replication protein A (RPA) with ssDNA.

    Carra, Claudio; Cucinotta, Francis A

    2012-06-01

    The eukaryotic replication protein A (RPA) has several pivotal functions in the cell metabolism, such as chromosomal replication, prevention of hairpin formation, DNA repair and recombination, and signaling after DNA damage. Moreover, RPA seems to have a crucial role in organizing the sequential assembly of DNA processing proteins along single stranded DNA (ssDNA). The strong RPA affinity for ssDNA, K(A) between 10(-9)-10(-10) M, is characterized by a low cooperativity with minor variation for changes on the nucleotide sequence. Recently, new data on RPA interactions was reported, including the binding free energy of the complex RPA70AB with dC(8) and dC(5), which has been estimated to be -10 ± 0.4 kcal mol(-1) and -7 ± 1 kcal mol(-1), respectively. In view of these results we performed a study based on molecular dynamics aimed to reproduce the absolute binding free energy of RPA70AB with the dC(5) and dC(8) oligonucleotides. We used several tools to analyze the binding free energy, rigidity, and time evolution of the complex. The results obtained by MM-PBSA method, with the use of ligand free geometry as a reference for the receptor in the separate trajectory approach, are in excellent agreement with the experimental data, with ±4 kcal mol(-1) error. This result shows that the MM-PB(GB)SA methods can provide accurate quantitative estimates of the binding free energy for interacting complexes when appropriate geometries are used for the receptor, ligand and complex. The decomposition of the MM-GBSA energy for each residue in the receptor allowed us to correlate the change of the affinity of the mutated protein with the ΔG(gas+sol) contribution of the residue considered in the mutation. The agreement with experiment is optimal and a strong change in the binding free energy can be considered as the dominant factor in the loss for the binding affinity resulting from mutation. PMID:22116609

  12. Carbon Isotope Composition of Carbohydrates and Polyols in Leaf and Phloem Sap of Phaseolus vulgaris L. Influences Predictions of Plant Water Use Efficiency.

    Smith, Millicent; Wild, Birgit; Richter, Andreas; Simonin, Kevin; Merchant, Andrew

    2016-08-01

    The use of carbon isotope abundance (δ(13)C) to assess plant carbon acquisition and water use has significant potential for use in crop management and plant improvement programs. Utilizing Phaseolus vulgaris L. as a model system, this study demonstrates the occurrence and sensitivity of carbon isotope fractionation during the onset of abiotic stresses between leaf and phloem carbon pools. In addition to gas exchange data, compound-specific measures of carbon isotope abundance and concentrations of soluble components of phloem sap were compared with major carbohydrate and sugar alcohol pools in leaf tissue. Differences in both δ(13)C and concentration of metabolites were found in leaf and phloem tissues, the magnitude of which responded to changing environmental conditions. These changes have inplications for the modeling of leaf-level gas exchange based upon δ(13)C natural abundance. Estimates of δ(13)C of low molecular weight carbohydrates and polyols increased the precision of predictions of water use efficiency compared with those based on bulk soluble carbon. The use of this technique requires consideration of the dynamics of the δ(13)C pool under investigation. Understanding the dynamics of changes in δ(13)C during movement and incorporation into heterotrophic tissues is vital for the continued development of tools that provide information on plant physiological performance relating to water use. PMID:27335348

  13. Accurate prediction of hard-sphere virial coefficients B6 to B12 from a compressibility-based equation of state

    Hansen-Goos, Hendrik

    2016-04-01

    We derive an analytical equation of state for the hard-sphere fluid that is within 0.01% of computer simulations for the whole range of the stable fluid phase. In contrast, the commonly used Carnahan-Starling equation of state deviates by up to 0.3% from simulations. The derivation uses the functional form of the isothermal compressibility from the Percus-Yevick closure of the Ornstein-Zernike relation as a starting point. Two additional degrees of freedom are introduced, which are constrained by requiring the equation of state to (i) recover the exact fourth virial coefficient B4 and (ii) involve only integer coefficients on the level of the ideal gas, while providing best possible agreement with the numerical result for B5. Virial coefficients B6 to B10 obtained from the equation of state are within 0.5% of numerical computations, and coefficients B11 and B12 are within the error of numerical results. We conjecture that even higher virial coefficients are reliably predicted.

  14. Quantitative Assessment of Protein Structural Models by Comparison of H/D Exchange MS Data with Exchange Behavior Accurately Predicted by DXCOREX

    Liu, Tong; Pantazatos, Dennis; Li, Sheng; Hamuro, Yoshitomo; Hilser, Vincent J.; Woods, Virgil L.

    2012-01-01

    Peptide amide hydrogen/deuterium exchange mass spectrometry (DXMS) data are often used to qualitatively support models for protein structure. We have developed and validated a method (DXCOREX) by which exchange data can be used to quantitatively assess the accuracy of three-dimensional (3-D) models of protein structure. The method utilizes the COREX algorithm to predict a protein's amide hydrogen exchange rates by reference to a hypothesized structure, and these values are used to generate a virtual data set (deuteron incorporation per peptide) that can be quantitatively compared with the deuteration level of the peptide probes measured by hydrogen exchange experimentation. The accuracy of DXCOREX was established in studies performed with 13 proteins for which both high-resolution structures and experimental data were available. The DXCOREX-calculated and experimental data for each protein was highly correlated. We then employed correlation analysis of DXCOREX-calculated versus DXMS experimental data to assess the accuracy of a recently proposed structural model for the catalytic domain of a Ca2+-independent phospholipase A2. The model's calculated exchange behavior was highly correlated with the experimental exchange results available for the protein, supporting the accuracy of the proposed model. This method of analysis will substantially increase the precision with which experimental hydrogen exchange data can help decipher challenging questions regarding protein structure and dynamics.

  15. The M. D. Anderson Symptom Inventory-Head and Neck Module, a Patient-Reported Outcome Instrument, Accurately Predicts the Severity of Radiation-Induced Mucositis

    Purpose: To compare the M. D. Anderson Symptom Inventory-Head and Neck (MDASI-HN) module, a symptom burden instrument, with the Functional Assessment of Cancer Therapy-Head and Neck (FACT-HN) module, a quality-of-life instrument, for the assessment of mucositis in patients with head-and-neck cancer treated with radiotherapy and to identify the most distressing symptoms from the patient's perspective. Methods and Materials: Consecutive patients with head-and-neck cancer (n = 134) completed the MDASI-HN and FACT-HN before radiotherapy (time 1) and after 6 weeks of radiotherapy or chemoradiotherapy (time 2). The mean global and subscale scores for each instrument were compared with the objective mucositis scores determined from the National Cancer Institute Common Terminology Criteria for Adverse Events, version 3.0. Results: The global and subscale scores for each instrument showed highly significant changes from time 1 to time 2 and a significant correlation with the objective mucositis scores at time 2. Only the MDASI scores, however, were significant predictors of objective Common Terminology Criteria for Adverse Events mucositis scores on multivariate regression analysis (standardized regression coefficient, 0.355 for the global score and 0.310 for the head-and-neck cancer-specific score). Most of the moderate and severe symptoms associated with mucositis as identified on the MDASI-HN are not present on the FACT-HN. Conclusion: Both the MDASI-HN and FACT-HN modules can predict the mucositis scores. However, the MDASI-HN, a symptom burden instrument, was more closely associated with the severity of radiation-induced mucositis than the FACT-HN on multivariate regression analysis. This greater association was most likely related to the inclusion of a greater number of face-valid mucositis-related items in the MDASI-HN compared with the FACT-HN

  16. ID-TIMS 准确测定国际关键比对大米粉中痕量镉%Accurate Determination of Trace Amount of Cadmium in Rice for International Key Comparison by Isotope Dilution Thermal Ionization Mass Spectrometry

    王军; 赵墨田; 逯海

    2005-01-01

    The method of isotope dilution thermal ionization mass spectrometry able to trace to SI was developed to accurately measure trace amount of cadmium in the rice powder sample from CCQM-K24 international key comparison organized by CCQM(Comité Consultatif pour la Quantité de Matière, Paris). By comparison with our previous work, there was much improvement in aspects of digestion of the rice powder sample, separation of cadmium from the sample and dry-mass correction. As a result, the blank of this procedure was reduced and the measurement precisions of isotopic ratios of cadmium were increased. In addition, the uncertainty evaluation of the entire process of measurement was profoundly studied. The analytical result of this work (14.53±0.15) nmol/g was in agreement with the certified value.

  17. Implementing the Effects of Changing Landscape by the Recent Bark Beetle Infestation on Snow Accumulation and Ablation to More Accurately Predict Stream Flow in the Upper Little Laramie River, Wyoming watershed.

    Heward, J.; Ohara, N.

    2014-12-01

    In many alpine regions, especially in the western United States, the snow pack is the cause of the peak discharge and most of the annual flow. A distributed snow melt model with a point-scale snow melt theory is used to estimate the timing and intensity of both snow accumulation and ablation. The type and distribution of vegetation across a watershed influences timing and intensity of snow melt processes. Efforts are being made to understand how a changing landscape will ultimately affect stream flow in a mountainous environment. This study includes an analysis of the effects of the recent bark beetle infestation, using leaf area index (LAI) data acquired from MODIS data sets. These changes were incorporated into the snow model to more accurately predict snow melt timing and intensity. It was observed through the primary model implementation that snowmelt was intensified by the LAI reduction. The radiation change and turbulent flux effects were separately quantified by the vegetation parameterization in the snow model. This distributed snow model will be used to more accurately predict stream flow in the Upper Little Laramie River, Wyoming watershed.

  18. Methodologies for an improved prediction of the isotopic content in high burnup samples. Application to Vandellós-II reactor core

    Highlights: ► The isotopic prediction of high burnup samples has been addressed through the use of MONTEBURNS 2.0 and SCALE 6.0. ► It is implemented a power normalization capability in MONTEBURNS 2.0 so the user can specify precise experimental powers. ► MONTEBURNS 2.0 has been modified to handle the complete list of isotopes managed by ORIGEN 2.1. ► An external capability is developed to follow irradiations involving geometrical and positional changes automatically. - Abstract: Fuel cycles are designed with the aim of obtaining the highest amount of energy possible. Since higher burnup values are reached, it is necessary to improve our disposal designs, traditionally based on the conservative assumption that they contain fresh fuel. The criticality calculations involved must consider burnup by making the most of the experimental and computational capabilities developed, respectively, to measure and predict the isotopic content of the spent nuclear fuel. These high burnup scenarios encourage a review of the computational tools to find out possible weaknesses in the nuclear data libraries, in the methodologies applied and their applicability range. Experimental measurements of the spent nuclear fuel provide the perfect framework to benchmark the most well-known and established codes, both in the industry and academic research activity. For the present paper, SCALE 6.0/TRITON and MONTEBURNS 2.0 have been chosen to follow the isotopic content of four samples irradiated in the Spanish Vandellós-II pressurized water reactor up to burnup values ranging from 40 GWd/MTU to 75 GWd/MTU. By comparison with the experimental data reported for these samples, we can probe the applicability of these codes to deal with high burnup problems. We have developed new computational tools within MONTENBURNS 2.0. They make possible to handle an irradiation history that includes geometrical and positional changes of the samples within the reactor core. This paper describes the

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

    Arockia Bazil Raj, A.; Padmavathi, S.

    2016-07-01

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

  20. Unraveling quantum mechanical effects in water using isotopic fractionation

    Markland, Thomas E

    2013-01-01

    When two phases of water are at equilibrium, the ratio of hydrogen isotopes in each is slightly altered due to their different phase affinities. This isotopic fractionation process can be utilized to analyze water's movement in the world's climate. Here we show that equilibrium fractionation ratios, an entirely quantum mechanical property, also provide a sensitive probe to assess the magnitude of nuclear quantum fluctuations in water. By comparing the predictions of a series of water models, we show that those describing the OH chemical bond as rigid or harmonic greatly over-predict the magnitude of isotope fractionation. Models that account for anharmonicity in this coordinate are shown to provide much more accurate results due to their ability to give partial cancellation between inter and intra-molecular quantum effects. These results give evidence of the existence of competing quantum effects in water and allow us to identify how this cancellation varies across a wide range of temperatures. In addition, t...

  1. Kinetic Isotope Effects for the Reactions of Muonic Helium and Muonium with H2

    Fleming, Donald G.; Arseneau, Donald J.; Sukhorukov, Oleksandr; Brewer, Jess H.; Mielke, Steven L.; Schatz, George C.; Garrett, Bruce C.; Peterson, Kirk A.; Truhlar, Donald G.

    2011-01-28

    The neutral muonic helium atom may be regarded as the heaviest isotope of the hydrogen atom, with a mass of ~4.1 amu (4.1H), because the negative muon screens one proton charge. We report the reaction rate of 4.1H with 1H2 to produce 4.1H1H + 1H at 295 to 500 K. The experimental rate constants are compared with the predictions of accurate quantum mechanical dynamics calculations carried out on an accurate Born-Huang potential energy surface and with previously measured rate constants of 0.11H (where 0.11H is shorthand for muonium). Kinetic isotope effects can be compared for the unprecedentedly large mass ratio of 36. The agreement with accurate quantum dynamics is quantitative at 500 K, and variational transition state theory is used to interpret the extremely low (large inverse) kinetic isotope effects in the 10-4 to 10-2 range.

  2. Prediction

    Woollard, W.J.

    2006-01-01

    In this chapter we will look at the ways in which you can use ICT in the classroom to support hypothesis and prediction and how modern technology is enabling: pattern seeking, extrapolation and interpolation to meet the challenges of the information explosion of the 21st century.

  3. Accurate long-range coefficients for two excited like isotope He atoms: He(2 1P)-He(2 1P), He(2 1P)-He(2 3P), and He(2 3P)-He(2 3P)

    A general formalism is used to express the long-range potential energies in inverse powers of the separation distance between two like atomic or molecular systems with P symmetries. The long-range molecular interaction coefficients are calculated for the molecular symmetries Δ, Π, and Σ, arising from the following interactions: He(2 1P)-He(2 1P), He(2 1P)-He(2 3P), and He(2 3P)-He(2 3P). The electric quadrupole-quadrupole term C5, the van der Waals (dispersion) term C6, and higher-order terms C8 and C10 are calculated ab initio using accurate variational wave functions in Hylleraas coordinates with finite nuclear mass effects. A comparison is made with previously published results where available

  4. Isotopic Biogeochemistry

    Hayes, J. M.

    1985-01-01

    An overview is provided of the biogeochemical research. The funding, productivity, personnel and facilities are reviewed. Some of the technical areas covered are: carbon isotopic records; isotopic studies of banded iron formations; isotope effects in microbial systems; studies of organic compounds in ancient sediments; and development in isotopic geochemistry and analysis.

  5. Prediction

    Sornette, Didier

    2010-01-01

    This chapter first presents a rather personal view of some different aspects of predictability, going in crescendo from simple linear systems to high-dimensional nonlinear systems with stochastic forcing, which exhibit emergent properties such as phase transitions and regime shifts. Then, a detailed correspondence between the phenomenology of earthquakes, financial crashes and epileptic seizures is offered. The presented statistical evidence provides the substance of a general phase diagram for understanding the many facets of the spatio-temporal organization of these systems. A key insight is to organize the evidence and mechanisms in terms of two summarizing measures: (i) amplitude of disorder or heterogeneity in the system and (ii) level of coupling or interaction strength among the system's components. On the basis of the recently identified remarkable correspondence between earthquakes and seizures, we present detailed information on a class of stochastic point processes that has been found to be particu...

  6. Tritium isotopic exchange in air detritiation dryers

    Isotopic exchange between tritiated and non-tritiated water species in a molecular sieve bed has been demonstrated. At high humidities (+6 degrees Celsius dew point) the rate of tritium isotopic exchange in a 2.4 L molecular sieve bed has been demonstrated to be at least 50% of published exchange rates. In an industrial-sized air detritiation dryer, utilizing the pretreatment technique of H2O steam washing to elute the residual tritium, a DF of 12 600 has been demonstrated when operating at an inlet vapor tritium concentration of 14 Ci/kg and at inlet and outlet dew points of 4.8 and -54 degrees Celsius, respectively. In the NPD dryer bed studied, which was not optimally designed for full benefit from isotopic exchange, at least one order of magnitude in additional detritiation is attributed to isotopic exchange in the unsaturated zone. The technique of eluting the residual tritium from an industrial sized bed by H2O washing at high temperature, high humidity and low bed loading has been demonstrated to be a fast and effective way of removing tritium from a molecular sieve bed during regeneration. The isotopic exchange model accurately predicted the exchange between tritiated and non-tritiated water species in a molecular sieve bed where there is no net adsorption or desorption. The model's prediction of the tritium breakthrough trend observed in the NPD tests was poor; however, a forced fit can be achieved if the exchange rates in the MTZ and the unsaturated zone are manipulated. More experiments are needed to determine the relative rates of tritium exchange in the saturated, mass transfer, and unsaturated zones of a dryer bed

  7. Prediction of plant vulnerability to salinity increase in a coastal ecosystem by stable isotopic composition (δ18O) of plant stem water: a model study

    Zhai, Lu; Jiang, Jiang; DeAngelis, Don; Sternberg, Leonel d.S.L

    2016-01-01

    Sea level rise and the subsequent intrusion of saline seawater can result in an increase in soil salinity, and potentially cause coastal salinity-intolerant vegetation (for example, hardwood hammocks or pines) to be replaced by salinity-tolerant vegetation (for example, mangroves or salt marshes). Although the vegetation shifts can be easily monitored by satellite imagery, it is hard to predict a particular area or even a particular tree that is vulnerable to such a shift. To find an appropriate indicator for the potential vegetation shift, we incorporated stable isotope 18O abundance as a tracer in various hydrologic components (for example, vadose zone, water table) in a previously published model describing ecosystem shifts between hammock and mangrove communities in southern Florida. Our simulations showed that (1) there was a linear relationship between salinity and the δ18O value in the water table, whereas this relationship was curvilinear in the vadose zone; (2) hammock trees with higher probability of being replaced by mangroves had higher δ18O values of plant stem water, and this difference could be detected 2 years before the trees reached a tipping point, beyond which future replacement became certain; and (3) individuals that were eventually replaced by mangroves from the hammock tree population with a 50% replacement probability had higher stem water δ18O values 3 years before their replacement became certain compared to those from the same population which were not replaced. Overall, these simulation results suggest that it is promising to track the yearly δ18O values of plant stem water in hammock forests to predict impending salinity stress and mortality.

  8. Accurate Finite Difference Algorithms

    Goodrich, John W.

    1996-01-01

    Two families of finite difference algorithms for computational aeroacoustics are presented and compared. All of the algorithms are single step explicit methods, they have the same order of accuracy in both space and time, with examples up to eleventh order, and they have multidimensional extensions. One of the algorithm families has spectral like high resolution. Propagation with high order and high resolution algorithms can produce accurate results after O(10(exp 6)) periods of propagation with eight grid points per wavelength.

  9. Isotopic clusters

    Spectra of isotopically mixed clusters (dimers of SF6) are calculated as well as transition frequencies. The result leads to speculations about the suitability of the laser-cluster fragmentation process for isotope separation. (Auth.)

  10. Isotopic geology

    Born from the application to geology of nuclear physics techniques, the isotopic geology has revolutionized the Earth's sciences. Beyond the dating of rocks, the tracer techniques have permitted to reconstruct the Earth's dynamics, to measure the temperatures of the past (giving birth to paleoclimatology) and to understand the history of chemical elements thanks to the analysis of meteorites. Today, all domains of Earth sciences appeal more or less to the methods of isotopic geology. In this book, the author explains the principles, methods and recent advances of this science: 1 - isotopes and radioactivity; 2 - principles of isotope dating; 3 - radio-chronological methods; 4 - cosmogenic isotope chronologies; 5 - uncertainties and radio-chronological results; 6 - geochemistry of radiogenic isotopes; 7 - geochemistry of stable isotopes; 8 - isotopic geology and dynamical analysis of reservoirs. (J.S.)