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Sample records for additional predictive power

  1. Wind power prediction models

    NASA Technical Reports Server (NTRS)

    Levy, R.; Mcginness, H.

    1976-01-01

    Investigations were performed to predict the power available from the wind at the Goldstone, California, antenna site complex. The background for power prediction was derived from a statistical evaluation of available wind speed data records at this location and at nearby locations similarly situated within the Mojave desert. In addition to a model for power prediction over relatively long periods of time, an interim simulation model that produces sample wind speeds is described. The interim model furnishes uncorrelated sample speeds at hourly intervals that reproduce the statistical wind distribution at Goldstone. A stochastic simulation model to provide speed samples representative of both the statistical speed distributions and correlations is also discussed.

  2. Monotonic Weighted Power Transformations to Additivity

    ERIC Educational Resources Information Center

    Ramsay, J. O.

    1977-01-01

    A class of monotonic transformations which generalize the power transformation is fit to the independent and dependent variables in multiple regression so that the resulting additive relationship is optimized. Examples of analysis of real and artificial data are presented. (Author/JKS)

  3. Does finger sense predict addition performance?

    PubMed

    Newman, Sharlene D

    2016-05-01

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

  4. Criteria for deviation from predictions by the concentration addition model.

    PubMed

    Takeshita, Jun-Ichi; Seki, Masanori; Kamo, Masashi

    2016-07-01

    Loewe's additivity (concentration addition) is a well-known model for predicting the toxic effects of chemical mixtures under the additivity assumption of toxicity. However, from the perspective of chemical risk assessment and/or management, it is important to identify chemicals whose toxicities are additive when present concurrently, that is, it should be established whether there are chemical mixtures to which the concentration addition predictive model can be applied. The objective of the present study was to develop criteria for judging test results that deviated from the predictions by the concentration addition chemical mixture model. These criteria were based on the confidence interval of the concentration addition model's prediction and on estimation of errors of the predicted concentration-effect curves by toxicity tests after exposure to single chemicals. A log-logit model with 2 parameters was assumed for the concentration-effect curve of each individual chemical. These parameters were determined by the maximum-likelihood method, and the criteria were defined using the variances and the covariance of the parameters. In addition, the criteria were applied to a toxicity test of a binary mixture of p-n-nonylphenol and p-n-octylphenol using the Japanese killifish, medaka (Oryzias latipes). Consequently, the concentration addition model using confidence interval was capable of predicting the test results at any level, and no reason for rejecting the concentration addition was found. Environ Toxicol Chem 2016;35:1806-1814. © 2015 SETAC. PMID:26660330

  5. Power consumption monitoring using additional monitoring device

    SciTech Connect

    Truşcă, M. R. C. Albert, Ş. Tudoran, C. Soran, M. L. Fărcaş, F.; Abrudean, M.

    2013-11-13

    Today, emphasis is placed on reducing power consumption. Computers are large consumers; therefore it is important to know the total consumption of computing systems. Since their optimal functioning requires quite strict environmental conditions, without much variation in temperature and humidity, reducing energy consumption cannot be made without monitoring environmental parameters. Thus, the present work uses a multifunctional electric meter UPT 210 for power consumption monitoring. Two applications were developed: software which carries meter readings provided by electronic and programming facilitates remote device and a device for temperature monitoring and control. Following temperature variations that occur both in the cooling system, as well as the ambient, can reduce energy consumption. For this purpose, some air conditioning units or some computers are stopped in different time slots. These intervals were set so that the economy is high, but the work's Datacenter is not disturbed.

  6. 50 CFR 453.06 - Additional Committee powers.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... ADMINISTRATION, DEPARTMENT OF COMMERCE); ENDANGERED SPECIES COMMITTEE REGULATIONS ENDANGERED SPECIES EXEMPTION PROCESS ENDANGERED SPECIES COMMITTEE § 453.06 Additional Committee powers. (a) Secure information....

  7. 50 CFR 453.06 - Additional Committee powers.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... ADMINISTRATION, DEPARTMENT OF COMMERCE); ENDANGERED SPECIES COMMITTEE REGULATIONS ENDANGERED SPECIES EXEMPTION PROCESS ENDANGERED SPECIES COMMITTEE § 453.06 Additional Committee powers. (a) Secure information....

  8. 50 CFR 453.06 - Additional Committee powers.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... ADMINISTRATION, DEPARTMENT OF COMMERCE); ENDANGERED SPECIES COMMITTEE REGULATIONS ENDANGERED SPECIES EXEMPTION PROCESS ENDANGERED SPECIES COMMITTEE § 453.06 Additional Committee powers. (a) Secure information....

  9. 50 CFR 453.06 - Additional Committee powers.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... ADMINISTRATION, DEPARTMENT OF COMMERCE); ENDANGERED SPECIES COMMITTEE REGULATIONS ENDANGERED SPECIES EXEMPTION PROCESS ENDANGERED SPECIES COMMITTEE § 453.06 Additional Committee powers. (a) Secure information....

  10. Predicting the impact of biochar additions on soil hydraulic properties

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Different physical and chemical properties of biochar, which is made out of a variety of biomass materials, can impact water movement through amended soil. The objective of this research was to develop a decision support tool predicting the impact of biochar additions on soil saturated hydraulic con...

  11. Thermodynamically consistent microstructure prediction of additively manufactured materials

    NASA Astrophysics Data System (ADS)

    Smith, Jacob; Xiong, Wei; Cao, Jian; Liu, Wing Kam

    2016-03-01

    Additive manufacturing has risen to the top of research interest in advanced manufacturing in recent years due to process flexibility, achievability of geometric complexity, and the ability to locally modify and optimize materials. The present work is focused on providing an approach for incorporating thermodynamically consistent properties and microstructure evolution for non-equilibrium supercooling, as observed in additive manufacturing processes, into finite element analysis. There are two primary benefits of this work: (1) the resulting prediction is based on the material composition and (2) the nonlinear behavior caused by the thermodynamic properties of the material during the non-equilibrium solution is accounted for with extremely high resolution. The predicted temperature response and microstructure evolution for additively manufactured stainless steel 316L using standard handbook-obtained thermodynamic properties are compared with the thermodynamic properties calculated using the CALculation of PHAse Diagrams (CALPHAD) approach. Data transfer from the CALPHAD approach to finite element analysis is discussed.

  12. Maximum predictive power and the superposition principle

    NASA Technical Reports Server (NTRS)

    Summhammer, Johann

    1994-01-01

    In quantum physics the direct observables are probabilities of events. We ask how observed probabilities must be combined to achieve what we call maximum predictive power. According to this concept the accuracy of a prediction must only depend on the number of runs whose data serve as input for the prediction. We transform each probability to an associated variable whose uncertainty interval depends only on the amount of data and strictly decreases with it. We find that for a probability which is a function of two other probabilities maximum predictive power is achieved when linearly summing their associated variables and transforming back to a probability. This recovers the quantum mechanical superposition principle.

  13. PERSPECTIVE VIEW OF EAST ELEVATION OF POWER BUILDING WITH ADDITION. ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    PERSPECTIVE VIEW OF EAST ELEVATION OF POWER BUILDING WITH ADDITION. NOTE WINDOW OPENINGS, WHICH ARE MERELY OPENINGS IN THE BOARD AND BATTEN SIDING AND REVEAL THE CONCRETE BLOCK CONSTRUCTION OF THE BUILDING. - Radar Station B-71, Power Building, Coastal Drive, Klamath, Del Norte County, CA

  14. 50 CFR 453.06 - Additional Committee powers.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 50 Wildlife and Fisheries 9 2011-10-01 2011-10-01 false Additional Committee powers. 453.06 Section 453.06 Wildlife and Fisheries JOINT REGULATIONS (UNITED STATES FISH AND WILDLIFE SERVICE, DEPARTMENT OF THE INTERIOR AND NATIONAL MARINE FISHERIES SERVICE, NATIONAL OCEANIC AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE); ENDANGERED...

  15. Uncertainties in predicting solar panel power output

    NASA Technical Reports Server (NTRS)

    Anspaugh, B.

    1974-01-01

    The problem of calculating solar panel power output at launch and during a space mission is considered. The major sources of uncertainty and error in predicting the post launch electrical performance of the panel are considered. A general discussion of error analysis is given. Examples of uncertainty calculations are included. A general method of calculating the effect on the panel of various degrading environments is presented, with references supplied for specific methods. A technique for sizing a solar panel for a required mission power profile is developed.

  16. 4. FLOOR PLAN AND SECTIONS, ADDITION TO POWER HOUSE. United ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    4. FLOOR PLAN AND SECTIONS, ADDITION TO POWER HOUSE. United Engineering Company Ltd., Alameda Shipyard. Also includes plot plan at 1 inch to 100 feet. John Hudspeth, architect, foot of Main Street, Alameda, California. Sheet 3. Plan no. 10,548. Scale 1/4 inch and h inch to the foot. April 30, 1945, last revised 6/22/45. pencil on vellum - United Engineering Company Shipyard, Boiler House, 2900 Main Street, Alameda, Alameda County, CA

  17. 3. ELEVATIONS, ADDITION TO POWER HOUSE. United Engineering Company Ltd., ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    3. ELEVATIONS, ADDITION TO POWER HOUSE. United Engineering Company Ltd., Alameda Shipyard. John Hudspeth, architect, foot of Main Street, Alameda, California. Sheet 4. Plan no. 10,548. Scale 1/4 inch to the foot, elevations, and one inch to the foot, sections and details. April 30, 1945, last revised 6/19/45. pencil on vellum - United Engineering Company Shipyard, Boiler House, 2900 Main Street, Alameda, Alameda County, CA

  18. Using Predictive Analytics to Predict Power Outages from Severe Weather

    NASA Astrophysics Data System (ADS)

    Wanik, D. W.; Anagnostou, E. N.; Hartman, B.; Frediani, M. E.; Astitha, M.

    2015-12-01

    The distribution of reliable power is essential to businesses, public services, and our daily lives. With the growing abundance of data being collected and created by industry (i.e. outage data), government agencies (i.e. land cover), and academia (i.e. weather forecasts), we can begin to tackle problems that previously seemed too complex to solve. In this session, we will present newly developed tools to aid decision-support challenges at electric distribution utilities that must mitigate, prepare for, respond to and recover from severe weather. We will show a performance evaluation of outage predictive models built for Eversource Energy (formerly Connecticut Light & Power) for storms of all types (i.e. blizzards, thunderstorms and hurricanes) and magnitudes (from 20 to >15,000 outages). High resolution weather simulations (simulated with the Weather and Research Forecast Model) were joined with utility outage data to calibrate four types of models: a decision tree (DT), random forest (RF), boosted gradient tree (BT) and an ensemble (ENS) decision tree regression that combined predictions from DT, RF and BT. The study shows that the ENS model forced with weather, infrastructure and land cover data was superior to the other models we evaluated, especially in terms of predicting the spatial distribution of outages. This research has the potential to be used for other critical infrastructure systems (such as telecommunications, drinking water and gas distribution networks), and can be readily expanded to the entire New England region to facilitate better planning and coordination among decision-makers when severe weather strikes.

  19. Lithium Dinitramide as an Additive in Lithium Power Cells

    NASA Technical Reports Server (NTRS)

    Gorkovenko, Alexander A.

    2007-01-01

    Lithium dinitramide, LiN(NO2)2 has shown promise as an additive to nonaqueous electrolytes in rechargeable and non-rechargeable lithium-ion-based electrochemical power cells. Such non-aqueous electrolytes consist of lithium salts dissolved in mixtures of organic ethers, esters, carbonates, or acetals. The benefits of adding lithium dinitramide (which is also a lithium salt) include lower irreversible loss of capacity on the first charge/discharge cycle, higher cycle life, lower self-discharge, greater flexibility in selection of electrolyte solvents, and greater charge capacity. The need for a suitable electrolyte additive arises as follows: The metallic lithium in the anode of a lithium-ion-based power cell is so highly reactive that in addition to the desired main electrochemical reaction, it engages in side reactions that cause formation of resistive films and dendrites, which degrade performance as quantified in terms of charge capacity, cycle life, shelf life, first-cycle irreversible capacity loss, specific power, and specific energy. The incidence of side reactions can be reduced through the formation of a solid-electrolyte interface (SEI) a thin film that prevents direct contact between the lithium anode material and the electrolyte. Ideally, an SEI should chemically protect the anode and the electrolyte from each other while exhibiting high conductivity for lithium ions and little or no conductivity for electrons. A suitable additive can act as an SEI promoter. Heretofore, most SEI promotion was thought to derive from organic molecules in electrolyte solutions. In contrast, lithium dinitramide is inorganic. Dinitramide compounds are known as oxidizers in rocket-fuel chemistry and until now, were not known as SEI promoters in battery chemistry. Although the exact reason for the improvement afforded by the addition of lithium dinitramide is not clear, it has been hypothesized that lithium dinitramide competes with other electrolyte constituents to react with

  20. Prediction of crystal densities of organic explosives by group additivity

    SciTech Connect

    Stine, J R

    1981-08-01

    The molar volume of crystalline organic compound is assumed to be a linear combination of its constituent volumes. Compounds consisting only of the elements hydrogen, carbon, nitrogen, oxygen, and fluorine are considered. The constituent volumes are taken to be the volumes of atoms in particular bonding environments and are evaluated from a large set of crystallographic data. The predicted density has an expected error of about 3%. These results are applied to a large number of explosives compounds.

  1. When power shapes interpersonal behavior: Low relationship power predicts men's aggressive responses to low situational power.

    PubMed

    Overall, Nickola C; Hammond, Matthew D; McNulty, James K; Finkel, Eli J

    2016-08-01

    When does power in intimate relationships shape important interpersonal behaviors, such as psychological aggression? Five studies tested whether possessing low relationship power was associated with aggressive responses, but (a) only within power-relevant relationship interactions when situational power was low, and (b) only by men because masculinity (but not femininity) involves the possession and demonstration of power. In Studies 1 and 2, men lower in relationship power exhibited greater aggressive communication during couples' observed conflict discussions, but only when they experienced low situational power because they were unable to influence their partner. In Study 3, men lower in relationship power reported greater daily aggressive responses toward their partner, but only on days when they experienced low situational power because they were either (a) unable to influence their partner or (b) dependent on their partner for support. In Study 4, men who possessed lower relationship power exhibited greater aggressive responses during couples' support-relevant discussions, but only when they had low situational power because they needed high levels of support. Study 5 provided evidence for the theoretical mechanism underlying men's aggressive responses to low relationship power. Men who possessed lower relationship power felt less manly on days they faced low situational power because their partner was unwilling to change to resolve relationship problems, which in turn predicted greater aggressive behavior toward their partner. These results demonstrate that fully understanding when and why power is associated with interpersonal behavior requires differentiating between relationship and situational power. (PsycINFO Database Record PMID:27442766

  2. Overview of Heat Addition and Efficiency Predictions for an Advanced Stirling Convertor

    NASA Technical Reports Server (NTRS)

    Wilson, Scott D.; Reid, Terry V.; Schifer, Nicholas A.; Briggs, Maxwell H.

    2012-01-01

    The U.S. Department of Energy (DOE) and Lockheed Martin Space Systems Company (LMSSC) have been developing the Advanced Stirling Radioisotope Generator (ASRG) for use as a power system for space science missions. This generator would use two high-efficiency Advanced Stirling Convertors (ASCs), developed by Sunpower Inc. and NASA Glenn Research Center (GRC). The ASCs convert thermal energy from a radioisotope heat source into electricity. As part of ground testing of these ASCs, different operating conditions are used to simulate expected mission conditions. These conditions require achieving a particular operating frequency, hot end and cold end temperatures, and specified electrical power output for a given net heat input. Microporous bulk insulation is used in the ground support test hardware to minimize the loss of thermal energy from the electric heat source to the environment. The insulation package is characterized before operation to predict how much heat will be absorbed by the convertor and how much will be lost to the environment during operation. In an effort to validate these predictions, numerous tasks have been performed, which provided a more accurate value for net heat input into the ASCs. This test and modeling effort included: (a) making thermophysical property measurements of test setup materials to provide inputs to the numerical models, (b) acquiring additional test data that was collected during convertor tests to provide numerical models with temperature profiles of the test setup via thermocouple and infrared measurements, (c) using multidimensional numerical models (computational fluid dynamics code) to predict net heat input of an operating convertor, and (d) using validation test hardware to provide direct comparison of numerical results and validate the multidimensional numerical models used to predict convertor net heat input. This effort produced high fidelity ASC net heat input predictions, which were successfully validated using

  3. Cosmic Emulation: Fast Predictions for the Galaxy Power Spectrum

    NASA Astrophysics Data System (ADS)

    Kwan, Juliana; Heitmann, Katrin; Habib, Salman; Padmanabhan, Nikhil; Lawrence, Earl; Finkel, Hal; Frontiere, Nicholas; Pope, Adrian

    2015-09-01

    The halo occupation distribution (HOD) approach has proven to be an effective method for modeling galaxy clustering and bias. In this approach, galaxies of a given type are probabilistically assigned to individual halos in N-body simulations. In this paper, we present a fast emulator for predicting the fully nonlinear galaxy-galaxy auto and galaxy-dark matter cross power spectrum and correlation function over a range of freely specifiable HOD modeling parameters. The emulator is constructed using results from 100 HOD models run on a large ΛCDM N-body simulation, with Gaussian Process interpolation applied to a PCA-based representation of the galaxy power spectrum. The total error is currently ˜1% in the auto correlations and ˜2% in the cross correlations from z = 1 to z = 0, over the considered parameter range. We use the emulator to investigate the accuracy of various analytic prescriptions for the galaxy power spectrum, parametric dependencies in the HOD model, and the behavior of galaxy bias as a function of HOD parameters. Additionally, we obtain fully nonlinear predictions for tangential shear correlations induced by galaxy-galaxy lensing from our galaxy-dark matter cross power spectrum emulator. All emulation products are publicly available at http://www.hep.anl.gov/cosmology/CosmicEmu/emu.html.

  4. Concentration Addition, Independent Action and Generalized Concentration Addition Models for Mixture Effect Prediction of Sex Hormone Synthesis In Vitro

    PubMed Central

    Hadrup, Niels; Taxvig, Camilla; Pedersen, Mikael; Nellemann, Christine; Hass, Ulla; Vinggaard, Anne Marie

    2013-01-01

    Humans are concomitantly exposed to numerous chemicals. An infinite number of combinations and doses thereof can be imagined. For toxicological risk assessment the mathematical prediction of mixture effects, using knowledge on single chemicals, is therefore desirable. We investigated pros and cons of the concentration addition (CA), independent action (IA) and generalized concentration addition (GCA) models. First we measured effects of single chemicals and mixtures thereof on steroid synthesis in H295R cells. Then single chemical data were applied to the models; predictions of mixture effects were calculated and compared to the experimental mixture data. Mixture 1 contained environmental chemicals adjusted in ratio according to human exposure levels. Mixture 2 was a potency adjusted mixture containing five pesticides. Prediction of testosterone effects coincided with the experimental Mixture 1 data. In contrast, antagonism was observed for effects of Mixture 2 on this hormone. The mixtures contained chemicals exerting only limited maximal effects. This hampered prediction by the CA and IA models, whereas the GCA model could be used to predict a full dose response curve. Regarding effects on progesterone and estradiol, some chemicals were having stimulatory effects whereas others had inhibitory effects. The three models were not applicable in this situation and no predictions could be performed. Finally, the expected contributions of single chemicals to the mixture effects were calculated. Prochloraz was the predominant but not sole driver of the mixtures, suggesting that one chemical alone was not responsible for the mixture effects. In conclusion, the GCA model seemed to be superior to the CA and IA models for the prediction of testosterone effects. A situation with chemicals exerting opposing effects, for which the models could not be applied, was identified. In addition, the data indicate that in non-potency adjusted mixtures the effects cannot always be

  5. Additives

    NASA Technical Reports Server (NTRS)

    Smalheer, C. V.

    1973-01-01

    The chemistry of lubricant additives is discussed to show what the additives are chemically and what functions they perform in the lubrication of various kinds of equipment. Current theories regarding the mode of action of lubricant additives are presented. The additive groups discussed include the following: (1) detergents and dispersants, (2) corrosion inhibitors, (3) antioxidants, (4) viscosity index improvers, (5) pour point depressants, and (6) antifouling agents.

  6. Predicting the Survival Time for Bladder Cancer Using an Additive Hazards Model in Microarray Data

    PubMed Central

    TAPAK, Leili; MAHJUB, Hossein; SADEGHIFAR, Majid; SAIDIJAM, Massoud; POOROLAJAL, Jalal

    2016-01-01

    Background: One substantial part of microarray studies is to predict patients’ survival based on their gene expression profile. Variable selection techniques are powerful tools to handle high dimensionality in analysis of microarray data. However, these techniques have not been investigated in competing risks setting. This study aimed to investigate the performance of four sparse variable selection methods in estimating the survival time. Methods: The data included 1381 gene expression measurements and clinical information from 301 patients with bladder cancer operated in the years 1987 to 2000 in hospitals in Denmark, Sweden, Spain, France, and England. Four methods of the least absolute shrinkage and selection operator, smoothly clipped absolute deviation, the smooth integration of counting and absolute deviation and elastic net were utilized for simultaneous variable selection and estimation under an additive hazards model. The criteria of area under ROC curve, Brier score and c-index were used to compare the methods. Results: The median follow-up time for all patients was 47 months. The elastic net approach was indicated to outperform other methods. The elastic net had the lowest integrated Brier score (0.137±0.07) and the greatest median of the over-time AUC and C-index (0.803±0.06 and 0.779±0.13, respectively). Five out of 19 selected genes by the elastic net were significant (P<0.05) under an additive hazards model. It was indicated that the expression of RTN4, SON, IGF1R and CDC20 decrease the survival time, while the expression of SMARCAD1 increase it. Conclusion: The elastic net had higher capability than the other methods for the prediction of survival time in patients with bladder cancer in the presence of competing risks base on additive hazards model. PMID:27114989

  7. FLUKA: Predictive power for cosmogenic backgrounds

    SciTech Connect

    Empl, A. Hungerford, E. V.; Ferrari, A.; Smirnov, G. I.

    2015-08-17

    The next generation of experiments searching for rare physics events with increased sensitivity will require precise predictions of cosmogenic backgrounds. Recent high quality deep underground measurements for cosmogenic neutrons in large liquid scintillator targets were used to study the FLUKA simulation package for this purpose. The results and conclusions drawn from a detailed benchmark comparison with data from the Borexino experiment were reported recently. In general, good agreement between data and simulation results were found with some identified discrepancies. Improved physics models already implemented in the current version of the FLUKA code, which will be publicly available with the upcoming code release, address the more important identified issues. A careful evaluation of the improved predictions is ongoing. However, the agreement between preliminary FLUKA simulation results and the Borexino experimental data are excellent. The preliminary findings will be discussed.

  8. FLUKA: Predictive power for cosmogenic backgrounds

    NASA Astrophysics Data System (ADS)

    Empl, A.; Ferrari, A.; Hungerford, E. V.; Smirnov, G. I.

    2015-08-01

    The next generation of experiments searching for rare physics events with increased sensitivity will require precise predictions of cosmogenic backgrounds. Recent high quality deep underground measurements for cosmogenic neutrons in large liquid scintillator targets were used to study the FLUKA simulation package for this purpose. The results and conclusions drawn from a detailed benchmark comparison with data from the Borexino experiment were reported recently. In general, good agreement between data and simulation results were found with some identified discrepancies. Improved physics models already implemented in the current version of the FLUKA code, which will be publicly available with the upcoming code release, address the more important identified issues. A careful evaluation of the improved predictions is ongoing. However, the agreement between preliminary FLUKA simulation results and the Borexino experimental data are excellent. The preliminary findings will be discussed.

  9. System and method for high power diode based additive manufacturing

    DOEpatents

    El-Dasher, Bassem S.; Bayramian, Andrew; Demuth, James A.; Farmer, Joseph C.; Torres, Sharon G.

    2016-04-12

    A system is disclosed for performing an Additive Manufacturing (AM) fabrication process on a powdered material forming a substrate. The system may make use of a diode array for generating an optical signal sufficient to melt a powdered material of the substrate. A mask may be used for preventing a first predetermined portion of the optical signal from reaching the substrate, while allowing a second predetermined portion to reach the substrate. At least one processor may be used for controlling an output of the diode array.

  10. Prediction of Maximum Aerobic Power in Untrained Females

    ERIC Educational Resources Information Center

    Dolgener, Forrest A.

    1978-01-01

    The author presents an equation for predicting maximum aerobic power in untrained females from values of percent body fat, weight, and submaximal values of heart rate, respiratory quotient, and expired gas. (MJB)

  11. Genomic prediction of growth in pigs based on a model including additive and dominance effects.

    PubMed

    Lopes, M S; Bastiaansen, J W M; Janss, L; Knol, E F; Bovenhuis, H

    2016-06-01

    Independent of whether prediction is based on pedigree or genomic information, the focus of animal breeders has been on additive genetic effects or 'breeding values'. However, when predicting phenotypes rather than breeding values of an animal, models that account for both additive and dominance effects might be more accurate. Our aim with this study was to compare the accuracy of predicting phenotypes using a model that accounts for only additive effects (MA) and a model that accounts for both additive and dominance effects simultaneously (MAD). Lifetime daily gain (DG) was evaluated in three pig populations (1424 Pietrain, 2023 Landrace, and 2157 Large White). Animals were genotyped using the Illumina SNP60K Beadchip and assigned to either a training data set to estimate the genetic parameters and SNP effects, or to a validation data set to assess the prediction accuracy. Models MA and MAD applied random regression on SNP genotypes and were implemented in the program Bayz. The additive heritability of DG across the three populations and the two models was very similar at approximately 0.26. The proportion of phenotypic variance explained by dominance effects ranged from 0.04 (Large White) to 0.11 (Pietrain), indicating that importance of dominance might be breed-specific. Prediction accuracies were higher when predicting phenotypes using total genetic values (sum of breeding values and dominance deviations) from the MAD model compared to using breeding values from both MA and MAD models. The highest increase in accuracy (from 0.195 to 0.222) was observed in the Pietrain, and the lowest in Large White (from 0.354 to 0.359). Predicting phenotypes using total genetic values instead of breeding values in purebred data improved prediction accuracy and reduced the bias of genomic predictions. Additional benefit of the method is expected when applied to predict crossbred phenotypes, where dominance levels are expected to be higher. PMID:26676611

  12. Prediction of Technological Failures in Nuclear Power Plant Operation

    SciTech Connect

    Salnykov, A. A.

    2015-01-15

    A method for predicting operating technological failures in nuclear power plants which makes it possible to reduce the unloading of the generator unit during the onset and development of an anomalous engineering state of the equipment by detecting a change in state earlier and taking suitable measures. With the circulating water supply loop of a nuclear power plant as an example, scenarios and algorithms for predicting technological failures in the operation of equipment long before their actual occurrence are discussed.

  13. Wind Power Plant Prediction by Using Neural Networks: Preprint

    SciTech Connect

    Liu, Z.; Gao, W.; Wan, Y. H.; Muljadi, E.

    2012-08-01

    This paper introduces a method of short-term wind power prediction for a wind power plant by training neural networks based on historical data of wind speed and wind direction. The model proposed is shown to achieve a high accuracy with respect to the measured data.

  14. Genomic-scale comparison of sequence- and structure-based methods of function prediction: Does structure provide additional insight?

    PubMed Central

    Fetrow, Jacquelyn S.; Siew, Naomi; Di Gennaro, Jeannine A.; Martinez-Yamout, Maria; Dyson, H. Jane; Skolnick, Jeffrey

    2001-01-01

    A function annotation method using the sequence-to-structure-to-function paradigm is applied to the identification of all disulfide oxidoreductases in the Saccharomyces cerevisiae genome. The method identifies 27 sequences as potential disulfide oxidoreductases. All previously known thioredoxins, glutaredoxins, and disulfide isomerases are correctly identified. Three of the 27 predictions are probable false-positives. Three novel predictions, which subsequently have been experimentally validated, are presented. Two additional novel predictions suggest a disulfide oxidoreductase regulatory mechanism for two subunits (OST3 and OST6) of the yeast oligosaccharyltransferase complex. Based on homology, this prediction can be extended to a potential tumor suppressor gene, N33, in humans, whose biochemical function was not previously known. Attempts to obtain a folded, active N33 construct to test the prediction were unsuccessful. The results show that structure prediction coupled with biochemically relevant structural motifs is a powerful method for the function annotation of genome sequences and can provide more detailed, robust predictions than function prediction methods that rely on sequence comparison alone. PMID:11316881

  15. Hybrid robust predictive optimization method of power system dispatch

    DOEpatents

    Chandra, Ramu Sharat; Liu, Yan; Bose, Sumit; de Bedout, Juan Manuel

    2011-08-02

    A method of power system dispatch control solves power system dispatch problems by integrating a larger variety of generation, load and storage assets, including without limitation, combined heat and power (CHP) units, renewable generation with forecasting, controllable loads, electric, thermal and water energy storage. The method employs a predictive algorithm to dynamically schedule different assets in order to achieve global optimization and maintain the system normal operation.

  16. Does Biot's Theory Have Predictive Power?

    NASA Astrophysics Data System (ADS)

    Beresnev, I. A.

    2013-12-01

    Biot's theory of elastic waves in fluid-saturated porous solids has two free parameters: the tortuosity α, characterizing the dynamic coupling between the solid and the fluid, and the structural factor δ, representing the geometric properties of the porous space. The meaning and significance of these parameters have not been sufficiently understood. Tortuosity has the physical meaning of the normalized mean square of the velocity of the pore fluid relative to the solid wall; it has no low- and high-frequency limits. The analytical calculation of the tortuosity for Biot's slit-like pore provides its range of variability from approximately 1 to 100 in the frequency range of practical interest. The tortuosity has a significant effect on the properties of the Biot waves of the second kind in the high-frequency range. On the other hand, in realistically complex pore geometries, the values of the tortuosity are virtually unpredictable. This limits the usefulness of the Biot theory in predicting the wave propagation at high frequencies. At all frequencies, the effect of the structural factor is insignificant relative to the effect of the tortuosity. The conventional compressional wave (the wave of the first kind) is insensitive to both parameters at all frequencies. The frequencies of interest to seismic exploration are also free of the uncertainty imposed by the lack of constraints on the tortuosity as the only free parameter in Biot's theory.

  17. Does Biot's theory have predictive power?

    NASA Astrophysics Data System (ADS)

    Beresnev, Igor A.

    2016-08-01

    Biot's theory of elastic waves in fluid-saturated porous solids has two free parameters: the tortuosity α, characterizing the dynamic coupling between the solid and the fluid, and the structural factor δ, representing the geometric properties of the porous space. The meaning and significance of these parameters have not been sufficiently understood. The tortuosity has the physical meaning of the normalized mean square of the velocity of the pore fluid relative to the solid wall; it has a low-frequency but no high-frequency limits. The analytical calculation of the tortuosity for Biot's slit-like pore provides its range of variability from approximately 1-100 in the frequency range of practical interest. The tortuosity has a significant effect on the properties of the Biot waves of the second kind in the high-frequency range. On the other hand, in realistically complex pore geometries, the values of the tortuosity are virtually unpredictable. This limits the usefulness of the Biot theory in predicting the wave propagation at high frequencies. At all frequencies, the effect of the structural factor is insignificant relative to the effect of the tortuosity. The conventional compressional wave (the wave of the first kind) is insensitive to both parameters at all frequencies. The frequencies of interest to seismic exploration are also free of the uncertainty imposed by the lack of constraints on the tortuosity as the only free parameter in Biot's theory.

  18. New Dynamical-Statistical Techniques for Wind Power Prediction

    NASA Astrophysics Data System (ADS)

    Stathopoulos, C.; Kaperoni, A.; Galanis, G.; Kallos, G.

    2012-04-01

    The increased use of renewable energy sources, and especially of wind power, has revealed the significance of accurate environmental and wind power predictions over wind farms that critically affect the integration of the produced power in the general grid. This issue is studied in the present paper by means of high resolution physical and statistical models. Two numerical weather prediction (NWP) systems namely SKIRON and RAMS are used to simulate the flow characteristics in selected wind farms in Greece. The NWP model output is post-processed by utilizing Kalman and Kolmogorov statistics in order to remove systematic errors. Modeled wind predictions in combination with available on-site observations are used for estimation of the wind power potential by utilizing a variety of statistical power prediction models based on non-linear and hyperbolic functions. The obtained results reveal the strong dependence of the forecasts uncertainty on the wind variation, the limited influence of previously recorded power values and the advantages that nonlinear - non polynomial functions could have in the successful control of power curve characteristics. This methodology is developed at the framework of the FP7 projects WAUDIT and MARINA PLATFORM.

  19. Local Geomagnetic Indices and the Prediction of Auroral Power

    NASA Astrophysics Data System (ADS)

    Newell, P. T.; Gjerloev, J. W.

    2014-12-01

    As the number of magnetometer stations and data processing power increases, just how auroral power relates to geomagnetic observations becomes a quantitatively more tractable question. This paper compares Polar UVI auroral power observations during 1997 with a variety of geomagnetic indices. Local time (LT) versions of the SuperMAG auroral electojet (SME) are introduced and examined, along with the corresponding upper and lower envelopes (SMU and SML). Also, the East-West component, BE, is investigated. We also consider whether using any of the local indices is actually better at predicting local auroral power than a single global index. Each index is separated into 24 LT indices based on a sliding 3-h MLT window. The ability to predict - or better reconstruct - auroral power varies greatly with LT, peaking at 1900 MLT, where about 75% of the variance (r2) can be predicted at 1-min cadence. The aurora is fairly predictable from 1700 MLT - 0400 MLT, roughly the region in which substorms occur. Auroral power is poorly predicted from auroral electrojet indices from 0500 MLT - 1500 MLT, with the minima at 1000-1300 MLT. In the region of high predictability, the local variable which works best is BE, in contrast to long-standing expectations. However using global SME is better than any local variable. Auroral power is best predicted by combining global SME with a local index: BE from 1500-0200 MLT, and either SMU or SML from 0300-1400 MLT. In the region of the diffuse aurora, it is better to use a 30 min average than the cotemporaneous 1-min SME value, while from 1500-0200 MLT the cotemporaneous 1-min SME works best, suggesting a more direct physical relationship with the auroral circuit. These results suggest a significant role for discrete auroral currents closing locally with Pedersen currents.

  20. Benchmarking the Predictive Power of Ligand Efficiency Indices in QSAR.

    PubMed

    Cortes-Ciriano, Isidro

    2016-08-22

    Compound physicochemical properties favoring in vitro potency are not always correlated to desirable pharmacokinetic profiles. Therefore, using potency (i.e., IC50) as the main criterion to prioritize candidate drugs at early stage drug discovery campaigns has been questioned. Yet, the vast majority of the virtual screening models reported in the medicinal chemistry literature predict the biological activity of compounds by regressing in vitro potency on topological or physicochemical descriptors. Two studies published in this journal showed that higher predictive power on external molecules can be achieved by using ligand efficiency indices as the dependent variable instead of a metric of potency (IC50) or binding affinity (Ki). The present study aims at filling the shortage of a thorough assessment of the predictive power of ligand efficiency indices in QSAR. To this aim, the predictive power of 11 ligand efficiency indices has been benchmarked across four algorithms (Gradient Boosting Machines, Partial Least Squares, Random Forest, and Support Vector Machines), two descriptor types (Morgan fingerprints, and physicochemical descriptors), and 29 data sets collected from the literature and ChEMBL database. Ligand efficiency metrics led to the highest predictive power on external molecules irrespective of the descriptor type or algorithm used, with an R(2)test difference of ∼0.3 units and a this difference ∼0.4 units when modeling small data sets and a normalized RMSE decrease of >0.1 units in some cases. Polarity indices, such as SEI and NSEI, led to higher predictive power than metrics based on molecular size, i.e., BEI, NBEI, and LE. LELP, which comprises a polarity factor (cLogP) and a size parameter (LE) constantly led to the most predictive models, suggesting that these two properties convey a complementary predictive signal. Overall, this study suggests that using ligand efficiency indices as the dependent variable might be an efficient strategy to model

  1. Predicting power-optimal kinematics of avian wings.

    PubMed

    Parslew, Ben

    2015-01-01

    A theoretical model of avian flight is developed which simulates wing motion through a class of methods known as predictive simulation. This approach uses numerical optimization to predict power-optimal kinematics of avian wings in hover, cruise, climb and descent. The wing dynamics capture both aerodynamic and inertial loads. The model is used to simulate the flight of the pigeon, Columba livia, and the results are compared with previous experimental measurements. In cruise, the model unearths a vast range of kinematic modes that are capable of generating the required forces for flight. The most efficient mode uses a near-vertical stroke-plane and a flexed-wing upstroke, similar to kinematics recorded experimentally. In hover, the model predicts that the power-optimal mode uses an extended-wing upstroke, similar to hummingbirds. In flexing their wings, pigeons are predicted to consume 20% more power than if they kept their wings full extended, implying that the typical kinematics used by pigeons in hover are suboptimal. Predictions of climbing flight suggest that the most energy-efficient way to reach a given altitude is to climb as steeply as possible, subjected to the availability of power. PMID:25392398

  2. Predicting power-optimal kinematics of avian wings

    PubMed Central

    Parslew, Ben

    2015-01-01

    A theoretical model of avian flight is developed which simulates wing motion through a class of methods known as predictive simulation. This approach uses numerical optimization to predict power-optimal kinematics of avian wings in hover, cruise, climb and descent. The wing dynamics capture both aerodynamic and inertial loads. The model is used to simulate the flight of the pigeon, Columba livia, and the results are compared with previous experimental measurements. In cruise, the model unearths a vast range of kinematic modes that are capable of generating the required forces for flight. The most efficient mode uses a near-vertical stroke–plane and a flexed-wing upstroke, similar to kinematics recorded experimentally. In hover, the model predicts that the power-optimal mode uses an extended-wing upstroke, similar to hummingbirds. In flexing their wings, pigeons are predicted to consume 20% more power than if they kept their wings full extended, implying that the typical kinematics used by pigeons in hover are suboptimal. Predictions of climbing flight suggest that the most energy-efficient way to reach a given altitude is to climb as steeply as possible, subjected to the availability of power. PMID:25392398

  3. Using machine learning to predict wind turbine power output

    NASA Astrophysics Data System (ADS)

    Clifton, A.; Kilcher, L.; Lundquist, J. K.; Fleming, P.

    2013-06-01

    Wind turbine power output is known to be a strong function of wind speed, but is also affected by turbulence and shear. In this work, new aerostructural simulations of a generic 1.5 MW turbine are used to rank atmospheric influences on power output. Most significant is the hub height wind speed, followed by hub height turbulence intensity and then wind speed shear across the rotor disk. These simulation data are used to train regression trees that predict the turbine response for any combination of wind speed, turbulence intensity, and wind shear that might be expected at a turbine site. For a randomly selected atmospheric condition, the accuracy of the regression tree power predictions is three times higher than that from the traditional power curve methodology. The regression tree method can also be applied to turbine test data and used to predict turbine performance at a new site. No new data are required in comparison to the data that are usually collected for a wind resource assessment. Implementing the method requires turbine manufacturers to create a turbine regression tree model from test site data. Such an approach could significantly reduce bias in power predictions that arise because of the different turbulence and shear at the new site, compared to the test site.

  4. Analytical predictions of RTG power degradation. [Radioisotope Thermoelectric Generator

    NASA Technical Reports Server (NTRS)

    Noon, E. L.; Raag, V.

    1979-01-01

    The DEGRA computer code that is based on a mathematical model which predicts performance and time-temperature dependent degradation of a radioisotope thermoelectric generator is discussed. The computer code has been used to predict performance and generator degradation for the selenide Ground Demonstration Unit (GDS-1) and the generator used in the Galileo Project. Results of parametric studies of load voltage vs generator output are examined as well as the I-V curve and the resulting predicted power vs voltage. The paper also discusses the increased capability features contained in DEGRA2 and future plans for expanding the computer code performance.

  5. A model to predict the power output from wind farms

    SciTech Connect

    Landberg, L.

    1997-12-31

    This paper will describe a model that can predict the power output from wind farms. To give examples of input the model is applied to a wind farm in Texas. The predictions are generated from forecasts from the NGM model of NCEP. These predictions are made valid at individual sites (wind farms) by applying a matrix calculated by the sub-models of WASP (Wind Atlas Application and Analysis Program). The actual wind farm production is calculated using the Riso PARK model. Because of the preliminary nature of the results, they will not be given. However, similar results from Europe will be given.

  6. For Tests That Are Predictively Powerful and without Social Prejudice

    ERIC Educational Resources Information Center

    Soares, Joseph A.

    2012-01-01

    In Philip Pullman's dark matter sci-fi trilogy, there is a golden compass that in the hands of the right person is predictively powerful; the same was supposed to be true of the SAT/ACT--the statistically indistinguishable standardized tests for college admissions. They were intended to be reliable mechanisms for identifying future trajectories,…

  7. A new analytical model for wind farm power prediction

    NASA Astrophysics Data System (ADS)

    Niayifar, Amin; Porte-Agel, Fernando

    2015-04-01

    In this study, a new analytical approach is presented and validated to predict wind farm power production. The new model assumes a Gaussian distribution for the velocity deficit in the wake which has been recently proposed by Bastankhah and Porté-Agel (2014). To estimate the velocity deficit in the wake, this model needs the local wake growth rate parameter which is calculated based on the local turbulence intensity in the wind farm. The interaction of the wakes is modeled by use of the velocity deficit superposition principle. Finally, the power curve is used to estimate the power production from the wind turbines. The wind farm model is compared to large-eddy simulation (LES) data of Horns Rev wind farm for a wide range of wind directions. Reasonable agreement between the proposed analytical model and LES data is obtained. This prediction is substantially better than the one obtained with common wind farm softwares such as WAsP.

  8. ESB-based Sensor Web integration for the prediction of electric power supply system vulnerability.

    PubMed

    Stoimenov, Leonid; Bogdanovic, Milos; Bogdanovic-Dinic, Sanja

    2013-01-01

    Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application. PMID:23955435

  9. ESB-Based Sensor Web Integration for the Prediction of Electric Power Supply System Vulnerability

    PubMed Central

    Stoimenov, Leonid; Bogdanovic, Milos; Bogdanovic-Dinic, Sanja

    2013-01-01

    Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application. PMID:23955435

  10. Thermodynamic network model for predicting effects of substrate addition and other perturbations on subsurface microbial communities

    SciTech Connect

    Jack Istok; Melora Park; James McKinley; Chongxuan Liu; Lee Krumholz; Anne Spain; Aaron Peacock; Brett Baldwin

    2007-04-19

    The overall goal of this project is to develop and test a thermodynamic network model for predicting the effects of substrate additions and environmental perturbations on microbial growth, community composition and system geochemistry. The hypothesis is that a thermodynamic analysis of the energy-yielding growth reactions performed by defined groups of microorganisms can be used to make quantitative and testable predictions of the change in microbial community composition that will occur when a substrate is added to the subsurface or when environmental conditions change.

  11. Model Predictive Control of Integrated Gasification Combined Cycle Power Plants

    SciTech Connect

    B. Wayne Bequette; Priyadarshi Mahapatra

    2010-08-31

    The primary project objectives were to understand how the process design of an integrated gasification combined cycle (IGCC) power plant affects the dynamic operability and controllability of the process. Steady-state and dynamic simulation models were developed to predict the process behavior during typical transients that occur in plant operation. Advanced control strategies were developed to improve the ability of the process to follow changes in the power load demand, and to improve performance during transitions between power levels. Another objective of the proposed work was to educate graduate and undergraduate students in the application of process systems and control to coal technology. Educational materials were developed for use in engineering courses to further broaden this exposure to many students. ASPENTECH software was used to perform steady-state and dynamic simulations of an IGCC power plant. Linear systems analysis techniques were used to assess the steady-state and dynamic operability of the power plant under various plant operating conditions. Model predictive control (MPC) strategies were developed to improve the dynamic operation of the power plants. MATLAB and SIMULINK software were used for systems analysis and control system design, and the SIMULINK functionality in ASPEN DYNAMICS was used to test the control strategies on the simulated process. Project funds were used to support a Ph.D. student to receive education and training in coal technology and the application of modeling and simulation techniques.

  12. Using individual interest and conscientiousness to predict academic effort: Additive, synergistic, or compensatory effects?

    PubMed

    Trautwein, Ulrich; Lüdtke, Oliver; Nagy, Nicole; Lenski, Anna; Niggli, Alois; Schnyder, Inge

    2015-07-01

    Although both conscientiousness and domain-specific interest are believed to be major determinants of academic effort, they have rarely been brought together in empirical studies. In the present research, it was hypothesized that both interest and conscientiousness uniquely predict academic effort and statistically interact with each other to predict academic effort. In 4 studies with 2,557, 415, 1,025, and 1,531 students, respectively, conscientiousness and interest meaningfully and uniquely predicted academic effort. In addition, conscientiousness interacted with interest in a compensatory pattern, indicating that conscientiousness is especially important when a student finds a school subject uninteresting and that domain-specific interest plays a particularly important role for students low in conscientiousness. PMID:25915134

  13. Effect of accuracy of wind power prediction on power system operator

    NASA Technical Reports Server (NTRS)

    Schlueter, R. A.; Sigari, G.; Costi, T.

    1985-01-01

    This research project proposed a modified unit commitment that schedules connection and disconnection of generating units in response to load. A modified generation control is also proposed that controls steam units under automatic generation control, fast responding diesels, gas turbines and hydro units under a feedforward control, and wind turbine array output under a closed loop array control. This modified generation control and unit commitment require prediction of trend wind power variation one hour ahead and the prediction of error in this trend wind power prediction one half hour ahead. An improved meter for predicting trend wind speed variation is developed. Methods for accurately simulating the wind array power from a limited number of wind speed prediction records was developed. Finally, two methods for predicting the error in the trend wind power prediction were developed. This research provides a foundation for testing and evaluating the modified unit commitment and generation control that was developed to maintain operating reliability at a greatly reduced overall production cost for utilities with wind generation capacity.

  14. Predicting the effects of nanoscale cerium additives in diesel fuel on regional-scale air quality.

    PubMed

    Erdakos, Garnet B; Bhave, Prakash V; Pouliot, George A; Simon, Heather; Mathur, Rohit

    2014-11-01

    Diesel vehicles are a major source of air pollutant emissions. Fuel additives containing nanoparticulate cerium (nCe) are currently being used in some diesel vehicles to improve fuel efficiency. These fuel additives also reduce fine particulate matter (PM2.5) emissions and alter the emissions of carbon monoxide (CO), nitrogen oxides (NOx), and hydrocarbon (HC) species, including several hazardous air pollutants (HAPs). To predict their net effect on regional air quality, we review the emissions literature and develop a multipollutant inventory for a hypothetical scenario in which nCe additives are used in all on-road and nonroad diesel vehicles. We apply the Community Multiscale Air Quality (CMAQ) model to a domain covering the eastern U.S. for a summer and a winter period. Model calculations suggest modest decreases of average PM2.5 concentrations and relatively larger decreases in particulate elemental carbon. The nCe additives also have an effect on 8 h maximum ozone in summer. Variable effects on HAPs are predicted. The total U.S. emissions of fine-particulate cerium are estimated to increase 25-fold and result in elevated levels of airborne cerium (up to 22 ng/m3), which might adversely impact human health and the environment. PMID:25271762

  15. Pre-stimulus thalamic theta power predicts human memory formation.

    PubMed

    Sweeney-Reed, Catherine M; Zaehle, Tino; Voges, Jürgen; Schmitt, Friedhelm C; Buentjen, Lars; Kopitzki, Klaus; Richardson-Klavehn, Alan; Hinrichs, Hermann; Heinze, Hans-Jochen; Knight, Robert T; Rugg, Michael D

    2016-09-01

    Pre-stimulus theta (4-8Hz) power in the hippocampus and neocortex predicts whether a memory for a subsequent event will be formed. Anatomical studies reveal thalamus-hippocampal connectivity, and lesion, neuroimaging, and electrophysiological studies show that memory processing involves the dorsomedial (DMTN) and anterior thalamic nuclei (ATN). The small size and deep location of these nuclei have limited real-time study of their activity, however, and it is unknown whether pre-stimulus theta power predictive of successful memory formation is also found in these subcortical structures. We recorded human electrophysiological data from the DMTN and ATN of 7 patients receiving deep brain stimulation for refractory epilepsy. We found that greater pre-stimulus theta power in the right DMTN was associated with successful memory encoding, predicting both behavioral outcome and post-stimulus correlates of successful memory formation. In particular, significant correlations were observed between right DMTN theta power and both frontal theta and right ATN gamma (32-50Hz) phase alignment, and frontal-ATN theta-gamma cross-frequency coupling. We draw the following primary conclusions. Our results provide direct electrophysiological evidence in humans of a role for the DMTN as well as the ATN in memory formation. Furthermore, prediction of subsequent memory performance by pre-stimulus thalamic oscillations provides evidence that post-stimulus differences in thalamic activity that index successful and unsuccessful encoding reflect brain processes specifically underpinning memory formation. Finally, the findings broaden the understanding of brain states that facilitate memory encoding to include subcortical as well as cortical structures. PMID:27208861

  16. Predicted weakening of the spin-orbit interaction with the addition of neutrons

    SciTech Connect

    Hemalatha, M.; Gambhir, Y. K.; Haider, W.; Kailas, S.

    2009-05-15

    The fully microscopic p-nucleus optical potential has been calculated in the framework of the first order Brueckner theory employing Urbana V14, soft-core internucleon interaction along with the relativistic mean field densities both for protons and neutrons. It is observed that the volume integral per nucleon, of the real part of the spin-orbit interaction calculated for Zr (A=76-110) and Sn (A=96-136) isotopes, decreases with the increase in neutron number. The present optical model calculation satisfactorily reproduces the experimental (where available) cross sections and analyzing power. Further the magnitude of the first maximum (minimum) in the calculated analyzing power decreases (increases) with the addition of neutrons both for Zr and Sn isotopes reflecting the weakening of the spin-orbit interaction.

  17. Peak power prediction of a vanadium redox flow battery

    NASA Astrophysics Data System (ADS)

    Yu, V. K.; Chen, D.

    2014-12-01

    The vanadium redox flow battery (VRFB) is a promising grid-scale energy storage technology, but future widespread commercialization requires a considerable reduction in capital costs. Determining the appropriate battery size for the intended power range can help minimize the amount of materials needed, thereby reducing capital costs. A physics-based model is an essential tool for predicting the power range of large scale VRFB systems to aid in the design optimization process. This paper presents a modeling framework that accounts for the effects of flow rate on the pumping losses, local mass transfer rate, and nonuniform vanadium concentration in the cell. The resulting low-order model captures battery performance accurately even at high power densities and remains computationally practical for stack-level optimization and control purposes. We first use the model to devise an optimal control strategy that maximizes battery life during discharge. Assuming optimal control is implemented, we then determine the upper efficiency limits of a given VRFB system and compare the net power and associated overpotential and pumping losses at different operating points. We also investigate the effects of varying the electrode porosity, stack temperature, and total vanadium concentration on the peak power.

  18. A new analytical model for wind farm power prediction

    NASA Astrophysics Data System (ADS)

    Niayifar, Amin; Porté-Agel, Fernando

    2015-06-01

    In this study, a new analytical approach is presented and validated to predict wind farm power production. The new model is an extension of the recently proposed by Bastankhah and Porté-Agel for a single wake. It assumes a self-similar Gaussian shape of the velocity deficit and satisfies conservation of mass and momentum. To estimate the velocity deficit in the wake, this model needs the local wake growth rate parameter which is calculated based on the local turbulence intensity in the wind farm. The interaction of the wakes is modeled by use of the velocity deficit superposition principle. Finally, the power curve is used to estimate the power production from the wind turbines. The wind farm model is compared to large-eddy simulation (LES) data and measurments of Horns Rev wind farm for a wide range of wind directions. Reasonable agreement between the proposed analytical model, LES data and measurments is obtained. This prediction is also found to be substantially better than the one obtained with a commonly used wind farm wake model.

  19. Improving coeliac disease risk prediction by testing non-HLA variants additional to HLA variants

    PubMed Central

    Romanos, Jihane; Rosén, Anna; Kumar, Vinod; Trynka, Gosia; Franke, Lude; Szperl, Agata; Gutierrez-Achury, Javier; van Diemen, Cleo C; Kanninga, Roan; Jankipersadsing, Soesma A; Steck, Andrea; Eisenbarth, Georges; van Heel, David A; Cukrowska, Bozena; Bruno, Valentina; Mazzilli, Maria Cristina; Núñez, Concepcion; Bilbao, Jose Ramon; Mearin, M Luisa; Barisani, Donatella; Rewers, Marian; Norris, Jill M; Ivarsson, Anneli; Boezen, H Marieke; Liu, Edwin; Wijmenga, Cisca

    2014-01-01

    Background The majority of coeliac disease (CD) patients are not being properly diagnosed and therefore remain untreated, leading to a greater risk of developing CD-associated complications. The major genetic risk heterodimer, HLA-DQ2 and DQ8, is already used clinically to help exclude disease. However, approximately 40% of the population carry these alleles and the majority never develop CD. Objective We explored whether CD risk prediction can be improved by adding non-HLA-susceptible variants to common HLA testing. Design We developed an average weighted genetic risk score with 10, 26 and 57 single nucleotide polymorphisms (SNP) in 2675 cases and 2815 controls and assessed the improvement in risk prediction provided by the non-HLA SNP. Moreover, we assessed the transferability of the genetic risk model with 26 non-HLA variants to a nested case–control population (n=1709) and a prospective cohort (n=1245) and then tested how well this model predicted CD outcome for 985 independent individuals. Results Adding 57 non-HLA variants to HLA testing showed a statistically significant improvement compared to scores from models based on HLA only, HLA plus 10 SNP and HLA plus 26 SNP. With 57 non-HLA variants, the area under the receiver operator characteristic curve reached 0.854 compared to 0.823 for HLA only, and 11.1% of individuals were reclassified to a more accurate risk group. We show that the risk model with HLA plus 26 SNP is useful in independent populations. Conclusions Predicting risk with 57 additional non-HLA variants improved the identification of potential CD patients. This demonstrates a possible role for combined HLA and non-HLA genetic testing in diagnostic work for CD. PMID:23704318

  20. A mathematical look at a physical power prediction model

    SciTech Connect

    Landberg, L.

    1997-12-31

    This paper takes a mathematical look at a physical model used to predict the power produced from wind farms. The reason is to see whether simple mathematical expressions can replace the original equations, and to give guidelines as to where the simplifications can be made and where they can not. This paper shows that there is a linear dependence between the geostrophic wind and the wind at the surface, but also that great care must be taken in the selection of the models since physical dependencies play a very important role, e.g. through the dependence of the turning of the wind on the wind speed.

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

    NASA Technical Reports Server (NTRS)

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

    1993-01-01

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

  2. Support vector machine to predict diesel engine performance and emission parameters fueled with nano-particles additive to diesel fuel

    NASA Astrophysics Data System (ADS)

    Ghanbari, M.; Najafi, G.; Ghobadian, B.; Mamat, R.; Noor, M. M.; Moosavian, A.

    2015-12-01

    This paper studies the use of adaptive Support Vector Machine (SVM) to predict the performance parameters and exhaust emissions of a diesel engine operating on nanodiesel blended fuels. In order to predict the engine parameters, the whole experimental data were randomly divided into training and testing data. For SVM modelling, different values for radial basis function (RBF) kernel width and penalty parameters (C) were considered and the optimum values were then found. The results demonstrate that SVM is capable of predicting the diesel engine performance and emissions. In the experimental step, Carbon nano tubes (CNT) (40, 80 and 120 ppm) and nano silver particles (40, 80 and 120 ppm) with nanostructure were prepared and added as additive to the diesel fuel. Six cylinders, four-stroke diesel engine was fuelled with these new blended fuels and operated at different engine speeds. Experimental test results indicated the fact that adding nano particles to diesel fuel, increased diesel engine power and torque output. For nano-diesel it was found that the brake specific fuel consumption (bsfc) was decreased compared to the net diesel fuel. The results proved that with increase of nano particles concentrations (from 40 ppm to 120 ppm) in diesel fuel, CO2 emission increased. CO emission in diesel fuel with nano-particles was lower significantly compared to pure diesel fuel. UHC emission with silver nano-diesel blended fuel decreased while with fuels that contains CNT nano particles increased. The trend of NOx emission was inverse compared to the UHC emission. With adding nano particles to the blended fuels, NOx increased compared to the net diesel fuel. The tests revealed that silver & CNT nano particles can be used as additive in diesel fuel to improve complete combustion of the fuel and reduce the exhaust emissions significantly.

  3. Additive genetic risk from five serotonin system polymorphisms interacts with interpersonal stress to predict depression.

    PubMed

    Vrshek-Schallhorn, Suzanne; Stroud, Catherine B; Mineka, Susan; Zinbarg, Richard E; Adam, Emma K; Redei, Eva E; Hammen, Constance; Craske, Michelle G

    2015-11-01

    Behavioral genetic research supports polygenic models of depression in which many genetic variations each contribute a small amount of risk, and prevailing diathesis-stress models suggest gene-environment interactions (G×E). Multilocus profile scores of additive risk offer an approach that is consistent with polygenic models of depression risk. In a first demonstration of this approach in a G×E predicting depression, we created an additive multilocus profile score from 5 serotonin system polymorphisms (1 each in the genes HTR1A, HTR2A, HTR2C, and 2 in TPH2). Analyses focused on 2 forms of interpersonal stress as environmental risk factors. Using 5 years of longitudinal diagnostic and life stress interviews from 387 emerging young adults in the Youth Emotion Project, survival analyses show that this multilocus profile score interacts with major interpersonal stressful life events to predict major depressive episode onsets (hazard ratio [HR] = 1.815, p = .007). Simultaneously, there was a significant protective effect of the profile score without a recent event (HR = 0.83, p = .030). The G×E effect with interpersonal chronic stress was not significant (HR = 1.15, p = .165). Finally, effect sizes for genetic factors examined ignoring stress suggested such an approach could lead to overlooking or misinterpreting genetic effects. Both the G×E effect and the protective simple main effect were replicated in a sample of early adolescent girls (N = 105). We discuss potential benefits of the multilocus genetic profile score approach and caveats for future research. PMID:26595467

  4. Effective soil hydraulic conductivity predicted with the maximum power principle

    NASA Astrophysics Data System (ADS)

    Westhoff, Martijn; Erpicum, Sébastien; Archambeau, Pierre; Pirotton, Michel; Zehe, Erwin; Dewals, Benjamin

    2016-04-01

    Drainage of water in soils happens for a large extent through preferential flowpaths, but these subsurface flowpaths are extremely difficult to observe or parameterize in hydrological models. To potentially overcome this problem, thermodynamic optimality principles have been suggested to predict effective parametrization of these (sub-grid) structures, such as the maximum entropy production principle or the equivalent maximum power principle. These principles have been successfully applied to predict heat transfer from the Equator to the Poles, or turbulent heat fluxes between the surface and the atmosphere. In these examples, the effective flux adapts itself to its boundary condition by adapting its effective conductance through the creation of e.g. convection cells. However, flow through porous media, such as soils, can only quickly adapt its effective flow conductance by creation of preferential flowpaths, but it is unknown if this is guided by the aim to create maximum power. Here we show experimentally that this is indeed the case: In the lab, we created a hydrological analogue to the atmospheric model dealing with heat transport between Equator and poles. The experimental setup consists of two freely draining reservoirs connected with each other by a confined aquifer. By adding water to only one reservoir, a potential difference will build up until a steady state is reached. From the steady state potential difference and the observed flow through the aquifer, and effective hydraulic conductance can be determined. This observed conductance does correspond to the one maximizing power of the flux through the confined aquifer. Although this experiment is done in an idealized setting, it opens doors for better parameterizing hydrological models. Furthermore, it shows that hydraulic properties of soils are not static, but they change with changing boundary conditions. A potential limitation to the principle is that it only applies to steady state conditions

  5. Power system very short-term load prediction

    SciTech Connect

    Trudnowski, D.J.; Johnson, J.M.; Whitney, P.

    1997-02-01

    A fundamental objective of a power-system operating and control scheme is to maintain a match between the system`s overall real-power load and generation. To accurately maintain this match, modern energy management systems require estimates of the future total system load. Several strategies and tools are available for estimating system load. Nearly all of these estimate the future load in 1-hour steps over several hours (or time frames very close to this). While hourly load estimates are very useful for many operation and control decisions, more accurate estimates at closer intervals would also be valuable. This is especially true for emerging Area Generation Control (AGC) strategies such as look-ahead AGC. For these short-term estimation applications, future load estimates out to several minutes at intervals of 1 to 5 minutes are required. The currently emerging operation and control strategies being developed by the BPA are dependent on accurate very short-term load estimates. To meet this need, the BPA commissioned the Pacific Northwest National Laboratory (PNNL) and Montana Tech (an affiliate of the University of Montana) to develop an accurate load prediction algorithm and computer codes that automatically update and can reliably perform in a closed-loop controller for the BPA system. The requirements include accurate load estimation in 5-minute steps out to 2 hours. This report presents the results of this effort and includes: a methodology and algorithms for short-term load prediction that incorporates information from a general hourly forecaster; specific algorithm parameters for implementing the predictor in the BPA system; performance and sensitivity studies of the algorithms on BPA-supplied data; an algorithm for filtering power system load samples as a precursor to inputting into the predictor; and FORTRAN 77 subroutines for implementing the algorithms.

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

    PubMed

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

    2012-07-13

    The question of whether the probabilistic nature of quantum mechanical predictions can be alleviated by supplementing the wave function with additional information has received a lot of attention during the past century. A few specific models have been suggested and subsequently falsified. Here we give a more general answer to this question: We provide experimental data that, as well as falsifying these models, cannot be explained within any alternative theory that could predict the outcomes of measurements on maximally entangled particles with significantly higher probability than quantum theory. Our conclusion is based on the assumptions that all measurement settings have been chosen freely (within a causal structure compatible with relativity theory), and that the presence of the detection loophole did not affect the measurement outcomes. PMID:23030132

  7. Use of generalised additive models to categorise continuous variables in clinical prediction

    PubMed Central

    2013-01-01

    Background In medical practice many, essentially continuous, clinical parameters tend to be categorised by physicians for ease of decision-making. Indeed, categorisation is a common practice both in medical research and in the development of clinical prediction rules, particularly where the ensuing models are to be applied in daily clinical practice to support clinicians in the decision-making process. Since the number of categories into which a continuous predictor must be categorised depends partly on the relationship between the predictor and the outcome, the need for more than two categories must be borne in mind. Methods We propose a categorisation methodology for clinical-prediction models, using Generalised Additive Models (GAMs) with P-spline smoothers to determine the relationship between the continuous predictor and the outcome. The proposed method consists of creating at least one average-risk category along with high- and low-risk categories based on the GAM smooth function. We applied this methodology to a prospective cohort of patients with exacerbated chronic obstructive pulmonary disease. The predictors selected were respiratory rate and partial pressure of carbon dioxide in the blood (PCO2), and the response variable was poor evolution. An additive logistic regression model was used to show the relationship between the covariates and the dichotomous response variable. The proposed categorisation was compared to the continuous predictor as the best option, using the AIC and AUC evaluation parameters. The sample was divided into a derivation (60%) and validation (40%) samples. The first was used to obtain the cut points while the second was used to validate the proposed methodology. Results The three-category proposal for the respiratory rate was ≤ 20;(20,24];> 24, for which the following values were obtained: AIC=314.5 and AUC=0.638. The respective values for the continuous predictor were AIC=317.1 and AUC=0.634, with no statistically

  8. Power Prediction in Smart Grids with Evolutionary Local Kernel Regression

    NASA Astrophysics Data System (ADS)

    Kramer, Oliver; Satzger, Benjamin; Lässig, Jörg

    Electric grids are moving from a centralized single supply chain towards a decentralized bidirectional grid of suppliers and consumers in an uncertain and dynamic scenario. Soon, the growing smart meter infrastructure will allow the collection of terabytes of detailed data about the grid condition, e.g., the state of renewable electric energy producers or the power consumption of millions of private customers, in very short time steps. For reliable prediction strong and fast regression methods are necessary that are able to cope with these challenges. In this paper we introduce a novel regression technique, i.e., evolutionary local kernel regression, a kernel regression variant based on local Nadaraya-Watson estimators with independent bandwidths distributed in data space. The model is regularized with the CMA-ES, a stochastic non-convex optimization method. We experimentally analyze the load forecast behavior on real power consumption data. The proposed method is easily parallelizable, and therefore well appropriate for large-scale scenarios in smart grids.

  9. Predicting ice accretion and alleviating galloping on overhead power lines

    NASA Astrophysics Data System (ADS)

    Lu, Mingliang

    2002-04-01

    Both the static and dynamic effects of an ice storm on an overhead power line are investigated fairly comprehensively in this thesis. To determine the static, extreme ice load as well as the combined ice and wind load, a systematic procedure is established based on extensive freezing rain experiments and a Monte Carlo simulation. On the other hand, a dynamic effect---galloping---is examined quite extensively with the objective of better understanding its behavior. A novel add-on device---the hybrid nutation damper (HND)---is proposed to control galloping. Its effectiveness is assessed numerically by using a modified, 3DOF based, galloping software. The present investigations lead to the following findings. (i) Goodwin's simple theoretical model surprisingly predicts, quite accurately, the temporally changing weight of not only a dry ice growth but also a wet ice growth for a fixed, unheated conductor sample. (ii) The maximum ice loading may vary significantly over a power line's planned lifetime because of the randomness of an ice storm and its characteristics as well as the uncertainty involved in identifying the extreme probability distribution of the ice loading. Consequently, backup protection is presently essential for a power line in an ice prone area. (iii) A conductor's torsional flexibility does not appear to affect the growth of the accreted ice weight but it modifies the ice shape significantly. (iv) Three representative ice shapes (a crescent, D-like and icicle pendant) can initiate galloping so that galloping may occur in any icing condition. (v) A noticeable swingback or twist appears to develop only when their respective natural frequencies coincide with the plunge's natural frequency. (vi) A hydraulic jump is the major source of energy dissipation in a nutation damper. A properly induced rotation can significantly enhance a nutation damper's performance. (vii) A hybrid nutation damper has been demonstrated to be a promising means of alleviating

  10. General requirements on matter power spectrum predictions for cosmology with weak lensing tomography

    SciTech Connect

    Hearin, Andrew P.; Zentner, Andrew R.; Ma, Zhaoming E-mail: zentner@pitt.edu

    2012-04-01

    Forthcoming projects such as DES, LSST, WFIRST, and Euclid aim to measure weak lensing shear correlations with unprecedented precision, constraining the dark energy equation of state at the percent level. Reliance on photometrically-determined redshifts constitutes a major source of uncertainty for these surveys. Additionally, interpreting the weak lensing signal requires a detailed understanding of the nonlinear physics of gravitational collapse. We present a new analysis of the stringent calibration requirements for weak lensing analyses of future imaging surveys that addresses both photo-z uncertainty and errors in the calibration of the matter power spectrum. We find that when photo-z uncertainty is taken into account the requirements on the level of precision in the prediction for the matter power spectrum are more stringent than previously thought. Including degree-scale galaxy clustering statistics in a joint analysis with weak lensing not only strengthens the survey's constraining power by ∼ 20%, but can also have a profound impact on the calibration demands, decreasing the degradation in dark energy constraints with matter power spectrum uncertainty by a factor of 2-5. Similarly, using galaxy clustering information significantly relaxes the demands on photo-z calibration. We compare these calibration requirements to the contemporary state-of-the-art in photometric redshift estimation and predictions of the power spectrum and suggest strategies to utilize forthcoming data optimally.

  11. Failure location prediction by finite element analysis for an additive manufactured mandible implant.

    PubMed

    Huo, Jinxing; Dérand, Per; Rännar, Lars-Erik; Hirsch, Jan-Michaél; Gamstedt, E Kristofer

    2015-09-01

    In order to reconstruct a patient with a bone defect in the mandible, a porous scaffold attached to a plate, both in a titanium alloy, was designed and manufactured using additive manufacturing. Regrettably, the implant fractured in vivo several months after surgery. The aim of this study was to investigate the failure of the implant and show a way of predicting the mechanical properties of the implant before surgery. All computed tomography data of the patient were preprocessed to remove metallic artefacts with metal deletion technique before mandible geometry reconstruction. The three-dimensional geometry of the patient's mandible was also reconstructed, and the implant was fixed to the bone model with screws in Mimics medical imaging software. A finite element model was established from the assembly of the mandible and the implant to study stresses developed during mastication. The stress distribution in the load-bearing plate was computed, and the location of main stress concentration in the plate was determined. Comparison between the fracture region and the location of the stress concentration shows that finite element analysis could serve as a tool for optimizing the design of mandible implants. PMID:26227805

  12. Adaptive neuro-fuzzy and expert systems for power quality analysis and prediction of abnormal operation

    NASA Astrophysics Data System (ADS)

    Ibrahim, Wael Refaat Anis

    The present research involves the development of several fuzzy expert systems for power quality analysis and diagnosis. Intelligent systems for the prediction of abnormal system operation were also developed. The performance of all intelligent modules developed was either enhanced or completely produced through adaptive fuzzy learning techniques. Neuro-fuzzy learning is the main adaptive technique utilized. The work presents a novel approach to the interpretation of power quality from the perspective of the continuous operation of a single system. The research includes an extensive literature review pertaining to the applications of intelligent systems to power quality analysis. Basic definitions and signature events related to power quality are introduced. In addition, detailed discussions of various artificial intelligence paradigms as well as wavelet theory are included. A fuzzy-based intelligent system capable of identifying normal from abnormal operation for a given system was developed. Adaptive neuro-fuzzy learning was applied to enhance its performance. A group of fuzzy expert systems that could perform full operational diagnosis were also developed successfully. The developed systems were applied to the operational diagnosis of 3-phase induction motors and rectifier bridges. A novel approach for learning power quality waveforms and trends was developed. The technique, which is adaptive neuro fuzzy-based, learned, compressed, and stored the waveform data. The new technique was successfully tested using a wide variety of power quality signature waveforms, and using real site data. The trend-learning technique was incorporated into a fuzzy expert system that was designed to predict abnormal operation of a monitored system. The intelligent system learns and stores, in compressed format, trends leading to abnormal operation. The system then compares incoming data to the retained trends continuously. If the incoming data matches any of the learned trends, an

  13. Predictive model of avian electrocution risk on overhead power lines.

    PubMed

    Dwyer, J F; Harness, R E; Donohue, K

    2014-02-01

    Electrocution on overhead power structures negatively affects avian populations in diverse ecosystems worldwide, contributes to the endangerment of raptor populations in Europe and Africa, and is a major driver of legal action against electric utilities in North America. We investigated factors associated with avian electrocutions so poles that are likely to electrocute a bird can be identified and retrofitted prior to causing avian mortality. We used historical data from southern California to identify patterns of avian electrocution by voltage, month, and year to identify species most often killed by electrocution in our study area and to develop a predictive model that compared poles where an avian electrocution was known to have occurred (electrocution poles) with poles where no known electrocution occurred (comparison poles). We chose variables that could be quantified by personnel with little training in ornithology or electric systems. Electrocutions were more common at distribution voltages (≤ 33 kV) and during breeding seasons and were more commonly reported after a retrofitting program began. Red-tailed Hawks (Buteo jamaicensis) (n = 265) and American Crows (Corvus brachyrhynchos) (n = 258) were the most commonly electrocuted species. In the predictive model, 4 of 14 candidate variables were required to distinguish electrocution poles from comparison poles: number of jumpers (short wires connecting energized equipment), number of primary conductors, presence of grounding, and presence of unforested unpaved areas as the dominant nearby land cover. When tested against a sample of poles not used to build the model, our model distributed poles relatively normally across electrocution-risk values and identified the average risk as higher for electrocution poles relative to comparison poles. Our model can be used to reduce avian electrocutions through proactive identification and targeting of high-risk poles for retrofitting. PMID:24033371

  14. Overview of Heat Addition and Efficiency Predictions for an Advanced Stirling Convertor

    NASA Technical Reports Server (NTRS)

    Wilson, Scott D.; Reid, Terry; Schifer, Nicholas; Briggs, Maxwell

    2011-01-01

    Past methods of predicting net heat input needed to be validated. Validation effort pursued with several paths including improving model inputs, using test hardware to provide validation data, and validating high fidelity models. Validation test hardware provided direct measurement of net heat input for comparison to predicted values. Predicted value of net heat input was 1.7 percent less than measured value and initial calculations of measurement uncertainty were 2.1 percent (under review). Lessons learned during validation effort were incorporated into convertor modeling approach which improved predictions of convertor efficiency.

  15. Replicability and 40-Year Predictive Power of Childhood ARC Types

    PubMed Central

    Chapman, Benjamin P.; Goldberg, Lewis R.

    2011-01-01

    We examined three questions surrounding the Undercontrolled, Overcontrolled, and Resilient--or Asendorpf-Robins-Caspi (ARC)--personality types originally identified by Block (1971). In analyses of the teacher personality assessments of over 2,000 children in 1st through 6th grade in 1959-1967, and follow-up data on general and cardiovascular health outcomes in over 1,100 adults recontacted 40 years later, we found: (1) Bootstrapped internal replication clustering suggested that Big Five scores were best characterized by a tripartite cluster structure corresponding to the ARC types; (2) this cluster structure was fuzzy, rather than discrete, indicating that ARC constructs are best represented as gradients of similarity to three prototype Big Five profiles; and (3) ARC types and degrees of ARC prototypicality showed associations with multiple health outcomes 40 years later. ARC constructs were more parsimonious, but neither better nor more consistent predictors than the dimensional Big Five traits. Forty-year incident cases of heart disease could be correctly identified with 68% accuracy by personality information alone, a figure approaching the 12-year accuracy of a leading medical cardiovascular risk model. Findings support the theoretical validity of ARC constructs, their treatment as continua of prototypicality rather than discrete categories, and the need for further understanding the robust predictive power of childhood personality traits for mid-life health. PMID:21744975

  16. Replicability and 40-year predictive power of childhood ARC types.

    PubMed

    Chapman, Benjamin P; Goldberg, Lewis R

    2011-09-01

    We examined 3 questions surrounding the undercontrolled, overcontrolled, and resilient-or Asendorpf-Robins-Caspi (ARC)-personality types originally identified by Block (1971). In analyses of the teacher personality assessments of over 2,000 children in 1st through 6th grade in 1959-1967 and follow-up data on general and cardiovascular health outcomes in over 1,100 adults recontacted 40 years later, we found bootstrapped internal replication clustering suggesting that Big Five scores were best characterized by a tripartite cluster structure corresponding to the ARC types. This cluster structure was fuzzy rather than discrete, indicating that ARC constructs are best represented as gradients of similarity to 3 prototype Big Five profiles; ARC types and degrees of ARC prototypicality showed associations with multiple health outcomes 40 years later. ARC constructs were more parsimonious but, depending on the outcome, comparable or slightly worse classifiers than the dimensional Big Five traits. Forty-year incident cases of heart disease could be correctly identified with 67% accuracy by childhood personality information alone and stroke incidence with over 70% accuracy. Findings support the theoretical validity of ARC constructs, their treatment as continua of prototypicality rather than discrete categories, and the need for further understanding the robust predictive power of childhood personality for midlife health. PMID:21744975

  17. Numerical Predictions of Wind Turbine Power and Aerodynamic Loads for the NREL Phase II and IV Combined Experiment Rotor

    NASA Technical Reports Server (NTRS)

    Duque, Earl P. N.; Johnson, Wayne; vanDam, C. P.; Chao, David D.; Cortes, Regina; Yee, Karen

    1999-01-01

    Accurate, reliable and robust numerical predictions of wind turbine rotor power remain a challenge to the wind energy industry. The literature reports various methods that compare predictions to experiments. The methods vary from Blade Element Momentum Theory (BEM), Vortex Lattice (VL), to variants of Reynolds-averaged Navier-Stokes (RaNS). The BEM and VL methods consistently show discrepancies in predicting rotor power at higher wind speeds mainly due to inadequacies with inboard stall and stall delay models. The RaNS methodologies show promise in predicting blade stall. However, inaccurate rotor vortex wake convection, boundary layer turbulence modeling and grid resolution has limited their accuracy. In addition, the inherently unsteady stalled flow conditions become computationally expensive for even the best endowed research labs. Although numerical power predictions have been compared to experiment. The availability of good wind turbine data sufficient for code validation experimental data that has been extracted from the IEA Annex XIV download site for the NREL Combined Experiment phase II and phase IV rotor. In addition, the comparisons will show data that has been further reduced into steady wind and zero yaw conditions suitable for comparisons to "steady wind" rotor power predictions. In summary, the paper will present and discuss the capabilities and limitations of the three numerical methods and make available a database of experimental data suitable to help other numerical methods practitioners validate their own work.

  18. Thermoelectric Power Generation from Lanthanum Strontium Titanium Oxide at Room Temperature through the Addition of Graphene.

    PubMed

    Lin, Yue; Norman, Colin; Srivastava, Deepanshu; Azough, Feridoon; Wang, Li; Robbins, Mark; Simpson, Kevin; Freer, Robert; Kinloch, Ian A

    2015-07-29

    The applications of strontium titanium oxide based thermoelectric materials are currently limited by their high operating temperatures of >700 °C. Herein, we show that the thermal operating window of lanthanum strontium titanium oxide (LSTO) can be reduced to room temperature by the addition of a small amount of graphene. This increase in operating performance will enable future applications such as generators in vehicles and other sectors. The LSTO composites incorporated one percent or less of graphene and were sintered under an argon/hydrogen atmosphere. The resultant materials were reduced and possessed a multiphase structure with nanosized grains. The thermal conductivity of the nanocomposites decreased upon the addition of graphene, whereas the electrical conductivity and power factor both increased significantly. These factors, together with a moderate Seebeck coefficient, meant that a high power factor of ∼2500 μWm(-1)K(-2) was reached at room temperature at a loading of 0.6 wt % graphene. The highest thermoelectric figure of merit (ZT) was achieved when 0.6 wt % graphene was added (ZT = 0.42 at room temperature and 0.36 at 750 °C), with >280% enhancement compared to that of pure LSTO. A preliminary 7-couple device was produced using bismuth strontium cobalt oxide/graphene-LSTO pucks. This device had a Seebeck coefficient of ∼1500 μV/K and an open voltage of 600 mV at a mean temperature of 219 °C. PMID:26095083

  19. Dynamic effect of sodium-water reaction in fast flux test facility power addition sodium pipes

    SciTech Connect

    Huang, S.N.; Anderson, M.J.

    1990-03-01

    The Fast Flux Facility (FFTF) is a demonstration and test facility of the sodium-cooled fast breeder reactor. A power addition'' to the facility is being considered to convert some of the dumped, unused heat into electricity generation. Components and piping systems to be added are sodium-water steam generators, sodium loop extensions from existing dump heat exchangers to sodium-water steam generators, and conventional water/steam loops. The sodium loops can be subjected to the dynamic loadings of pressure pulses that are caused by postulated sodium leaks and subsequent sodium-water reaction in the steam generator. The existing FFTF secondary pipes and the new power addition sodium loops were evaluated for exposure to the dynamic effect of the sodium-water reaction. Elastic and simplified inelastic dynamic analyses were used in this feasibility study. The results indicate that both the maximum strain and strain range are within the allowable limits. Several cycles of the sodium-water reaction can be sustained by the sodium pipes that are supported by ordinary pipe supports and seismic restraints. Expensive axial pipe restraints to withstand the sodium-water reaction loads are not needed, because the pressure-pulse-induced alternating bending stresses act as secondary stresses and the pressure pulse dynamic effect is a deformation-controlled quantity and is self-limiting. 14 refs., 7 figs., 3 tabs.

  20. Conceptual Software Reliability Prediction Models for Nuclear Power Plant Safety Systems

    SciTech Connect

    Johnson, G.; Lawrence, D.; Yu, H.

    2000-04-03

    of the individual hardware/software components. Existing modeling techniques--such as fault tree analyses or reliability block diagrams--can probably be adapted to bridge the gaps between the reliability of the hardware components, the individual software elements, and the overall digital system. This project builds upon previous work to survey and rank potential measurement methods which could be used to measure software product reliability 3. This survey and ranking identified candidate measures for use in predicting the reliability of digital computer-based control and protection systems for nuclear power plants. Additionally, information gleaned from the study can be used to supplement existing review methods during an assessment of software-based digital systems.

  1. Nuclear power plant maintenance personnel reliability prediction (NPP/MPRP) effort at Oak Ridge National Laboratory

    SciTech Connect

    Knee, H.E.; Haas, P.M.; Siegel, A.I.

    1981-01-01

    Human errors committed during maintenance activities are potentially a major contribution to the overall risk associated with the operation of a nuclear power plant (NPP). An NRC-sponsored program at Oak Ridge National Laboratory is attempting to develop a quantitative predictive technique to evaluate the contribution of maintenance errors to the overall NPP risk. The current work includes a survey of the requirements of potential users to ascertain the need for and content of the proposed quantitative model, plus an initial job/task analysis to determine the scope and applicability of various maintenance tasks. In addition, existing human reliability prediction models are being reviewed and assessed with respect to their applicability to NPP maintenance tasks. This paper discusses the status of the program and summarizes the results to date.

  2. Complex additive systems for Mn-Zn ferrites with low power loss

    SciTech Connect

    Töpfer, J. Angermann, A.

    2015-05-07

    Mn-Zn ferrites were prepared via an oxalate-based wet-chemical synthesis process. Nanocrystalline ferrite powders with particle size of 50 nm were sintered at 1150 °C with 500 ppm CaO and 100 ppm SiO{sub 2} as standard additives. A fine-grained, dense microstructure with grain size of 4–5 μm was obtained. Simultaneous addition of Nb{sub 2}O{sub 5}, ZrO{sub 2}, V{sub 2}O{sub 5}, and SnO{sub 2} results low power losses, e.g., 65 mW/cm{sup 3} (500 kHz, 50 mT, 80 °C) and 55 mW/cm{sup 3} (1 MHz, 25 mT, 80 °C). Loss analysis shows that eddy current and residual losses were minimized through formation of insulating grain boundary phases, which is confirmed by transmission electron microscopy. Addition of SnO{sub 2} increases the ferrous ion concentration and affects anisotropy as reflected in permeability measurements μ(T)

  3. Complex additive systems for Mn-Zn ferrites with low power loss

    NASA Astrophysics Data System (ADS)

    Töpfer, J.; Angermann, A.

    2015-05-01

    Mn-Zn ferrites were prepared via an oxalate-based wet-chemical synthesis process. Nanocrystalline ferrite powders with particle size of 50 nm were sintered at 1150 °C with 500 ppm CaO and 100 ppm SiO2 as standard additives. A fine-grained, dense microstructure with grain size of 4-5 μm was obtained. Simultaneous addition of Nb2O5, ZrO2, V2O5, and SnO2 results low power losses, e.g., 65 mW/cm3 (500 kHz, 50 mT, 80 °C) and 55 mW/cm3 (1 MHz, 25 mT, 80 °C). Loss analysis shows that eddy current and residual losses were minimized through formation of insulating grain boundary phases, which is confirmed by transmission electron microscopy. Addition of SnO2 increases the ferrous ion concentration and affects anisotropy as reflected in permeability measurements μ(T).

  4. Kicking Back Cognitive Ageing: Leg Power Predicts Cognitive Ageing after Ten Years in Older Female Twins

    PubMed Central

    Steves, Claire J.; Mehta, Mitul M.; Jackson, Stephen H.D.; Spector, Tim D.

    2016-01-01

    Background Many observational studies have shown a protective effect of physical activity on cognitive ageing, but interventional studies have been less convincing. This may be due to short time scales of interventions, suboptimal interventional regimes or lack of lasting effect. Confounding through common genetic and developmental causes is also possible. Objectives We aimed to test whether muscle fitness (measured by leg power) could predict cognitive change in a healthy older population over a 10-year time interval, how this performed alongside other predictors of cognitive ageing, and whether this effect was confounded by factors shared by twins. In addition, we investigated whether differences in leg power were predictive of differences in brain structure and function after 12 years of follow-up in identical twin pairs. Methods A total of 324 healthy female twins (average age at baseline 55, range 43-73) performed the Cambridge Neuropsychological Test Automated Battery (CANTAB) at two time points 10 years apart. Linear regression modelling was used to assess the relationships between baseline leg power, physical activity and subsequent cognitive change, adjusting comprehensively for baseline covariates (including heart disease, diabetes, blood pressure, fasting blood glucose, lipids, diet, body habitus, smoking and alcohol habits, reading IQ, socioeconomic status and birthweight). A discordant twin approach was used to adjust for factors shared by twins. A subset of monozygotic pairs then underwent magnetic resonance imaging. The relationship between muscle fitness and brain structure and function was assessed using linear regression modelling and paired t tests. Results A striking protective relationship was found between muscle fitness (leg power) and both 10-year cognitive change [fully adjusted model standardised β-coefficient (Stdβ) = 0.174, p = 0.002] and subsequent total grey matter (Stdβ = 0.362, p = 0.005). These effects were robust in discordant

  5. Students' Predictions about the Sensory Properties of Chemical Compounds: Additive versus Emergent Frameworks

    ERIC Educational Resources Information Center

    Talanquer, Vicente

    2008-01-01

    We investigated general chemistry students' intuitive ideas about the expected properties of the products of a chemical reaction. In particular, we analyzed college chemistry students' predictions about the color, smell, and taste of the products of chemical reactions represented at the molecular level. The study was designed to explore the extent…

  6. A MIXTURE OF SEVEN ANTIANDROGENIC COMPOUNDS ELICITS ADDITIVE EFFECTS ON THE MALE RAT REPRODUCTIVE TRACT THAT CORRESPOND TO MODELED PREDICTIONS

    EPA Science Inventory

    The main objectives of this study were to: (1) determine whether dissimilar antiandrogenic compounds display additive effects when present in combination and (2) to assess the ability of modelling approaches to accurately predict these mixture effects based on data from single ch...

  7. NUCLEOPHILIC ADDITION TO ACTIVATED DOUBLE BONDS: PREDICTION OF REACTIVITY FROM THE LAPLACIAN OF CHARGE DENSITY

    EPA Science Inventory

    The reactivities of a series of molecules in a Michael addition reaction are analyzed on the basis of properties expressed in the Laplacian of the charge density distribution. he charge densities of structurally optimized acrylic acid (AA), methacrylic acid (MAA), acrylonitrile (...

  8. Additive method for the prediction of protein-peptide binding affinity. Application to the MHC class I molecule HLA-A*0201.

    PubMed

    Doytchinova, Irini A; Blythe, Martin J; Flower, Darren R

    2002-01-01

    A method has been developed for prediction of binding affinities between proteins and peptides. We exemplify the method through its application to binding predictions of peptides with affinity to major histocompatibility complex class I molecule HLA-A*0201. The method is named "additive" because it is based on the assumption that the binding affinity of a peptide could be presented as a sum of the contributions of the amino acids at each position and the interactions between them. The amino acid contributions and the contributions of the interactions between adjacent side chains and every second side chain were derived using a partial least squares (PLS) statistical methodology using a training set of 420 experimental IC50 values. The predictive power of the method was assessed using rigorous cross-validation and using an independent test set of 89 peptides. The mean value of the residuals between the experimental and predicted pIC50 values was 0.508 for this test set. The additive method was implemented in a program for rapid T-cell epitope search. It is universal and can be applied to any peptide-protein interaction where binding data is known. PMID:12645903

  9. Genome-Enabled Estimates of Additive and Nonadditive Genetic Variances and Prediction of Apple Phenotypes Across Environments

    PubMed Central

    Kumar, Satish; Molloy, Claire; Muñoz, Patricio; Daetwyler, Hans; Chagné, David; Volz, Richard

    2015-01-01

    The nonadditive genetic effects may have an important contribution to total genetic variation of phenotypes, so estimates of both the additive and nonadditive effects are desirable for breeding and selection purposes. Our main objectives were to: estimate additive, dominance and epistatic variances of apple (Malus × domestica Borkh.) phenotypes using relationship matrices constructed from genome-wide dense single nucleotide polymorphism (SNP) markers; and compare the accuracy of genomic predictions using genomic best linear unbiased prediction models with or without including nonadditive genetic effects. A set of 247 clonally replicated individuals was assessed for six fruit quality traits at two sites, and also genotyped using an Illumina 8K SNP array. Across several fruit quality traits, the additive, dominance, and epistatic effects contributed about 30%, 16%, and 19%, respectively, to the total phenotypic variance. Models ignoring nonadditive components yielded upwardly biased estimates of additive variance (heritability) for all traits in this study. The accuracy of genomic predicted genetic values (GEGV) varied from about 0.15 to 0.35 for various traits, and these were almost identical for models with or without including nonadditive effects. However, models including nonadditive genetic effects further reduced the bias of GEGV. Between-site genotypic correlations were high (>0.85) for all traits, and genotype-site interaction accounted for <10% of the phenotypic variability. The accuracy of prediction, when the validation set was present only at one site, was generally similar for both sites, and varied from about 0.50 to 0.85. The prediction accuracies were strongly influenced by trait heritability, and genetic relatedness between the training and validation families. PMID:26497141

  10. Can arousing feedback rectify lapses in driving? Prediction from EEG power spectra

    NASA Astrophysics Data System (ADS)

    Lin, Chin-Teng; Huang, Kuan-Chih; Chuang, Chun-Hsiang; Ko, Li-Wei; Jung, Tzyy-Ping

    2013-10-01

    Objective. This study explores the neurophysiological changes, measured using an electroencephalogram (EEG), in response to an arousing warning signal delivered to drowsy drivers, and predicts the efficacy of the feedback based on changes in the EEG. Approach. Eleven healthy subjects participated in sustained-attention driving experiments. The driving task required participants to maintain their cruising position and compensate for randomly induced lane deviations using the steering wheel, while their EEG and driving performance were continuously monitored. The arousing warning signal was delivered to participants who experienced momentary behavioral lapses, failing to respond rapidly to lane-departure events (specifically the reaction time exceeded three times the alert reaction time). Main results. The results of our previous studies revealed that arousing feedback immediately reversed deteriorating driving performance, which was accompanied by concurrent EEG theta- and alpha-power suppression in the bilateral occipital areas. This study further proposes a feedback efficacy assessment system to accurately estimate the efficacy of arousing warning signals delivered to drowsy participants by monitoring the changes in their EEG power spectra immediately thereafter. The classification accuracy was up 77.8% for determining the need for triggering additional warning signals. Significance. The findings of this study, in conjunction with previous studies on EEG correlates of behavioral lapses, might lead to a practical closed-loop system to predict, monitor and rectify behavioral lapses of human operators in attention-critical settings.

  11. Additive SMILES-Based Carcinogenicity Models: Probabilistic Principles in the Search for Robust Predictions

    PubMed Central

    Toropov, Andrey A.; Toropova, Alla P.; Benfenati, Emilio

    2009-01-01

    Optimal descriptors calculated with the simplified molecular input line entry system (SMILES) have been utilized in modeling of carcinogenicity as continuous values (logTD50). These descriptors can be calculated using correlation weights of SMILES attributes calculated by the Monte Carlo method. A considerable subset of these attributes includes rare attributes. The use of these rare attributes can lead to overtraining. One can avoid the influence of the rare attributes if their correlation weights are fixed to zero. A function, limS, has been defined to identify rare attributes. The limS defines the minimum number of occurrences in the set of structures of the training (subtraining) set, to accept attributes as usable. If an attribute is present less than limS, it is considered “rare”, and thus not used. Two systems of building up models were examined: 1. classic training-test system; 2. balance of correlations for the subtraining and calibration sets (together, they are the original training set: the function of the calibration set is imitation of a preliminary test set). Three random splits into subtraining, calibration, and test sets were analysed. Comparison of abovementioned systems has shown that balance of correlations gives more robust prediction of the carcinogenicity for all three splits (split 1: rtest2=0.7514, stest=0.684; split 2: rtest2=0.7998, stest=0.600; split 3: rtest2=0.7192, stest=0.728). PMID:19742127

  12. The Development of Mathematical Prediction Model to Predict Resilient Modulus for Natural Soil Stabilized by Pofa-Opc Additive for the Use in Unpaved Road Design

    NASA Astrophysics Data System (ADS)

    Gamil, Y. M. R.; Bakar, I. H.

    2016-07-01

    Resilient Modulus (Mr) is considered one of the most important parameters in the design of road structure. This paper describes the development of the mathematical model to predict resilient modulus of organic soil stabilized by the mix of Palm Oil Fuel Ash - Ordinary Portland Cement (POFA-OPC) soil stabilization additives. It aims to optimize the use of the use of POFA in soil stabilization. The optimization models enable to eliminate the arbitrary selection and its associated disadvantages in determination of the optimum additive proportion. The model was developed based on Scheffe regression theory. The mix proportions of the samples in the experiment were adopted from similar studies reported in the literature Twenty five samples were designed, prepared and then characterized for each mix proportion based on the MR in 28 days curing. The results are used to develop the mathematical prediction model. The model was statistically analyzed and verified for its adequacy and validity using F-test.

  13. Global and Limited-Area Ensemble Prediction Systems deployed for Wind Power Forecasting

    NASA Astrophysics Data System (ADS)

    Petroliagis, T. I.; Jacques, M.; Montani, A.; Bremen, L. V.; Heinemann, D.

    2010-09-01

    Small-scale MOdeling (COSMO), formed in October 1998. As designed and developed, COSMO-LEPS platform aims at improving upon the early and medium-range predictability of extreme and localized weather events, especially when orographic and mesoscale related processes play a crucial role. The present status of COSMO-LEPS, based on 16 integrations of the COSMO-model (7 km of horizontal resolution, 40 vertical levels, 132 hours of forecast range) is running operationally as a 'time-critical application' at ECMWF. Verification results for ECMWF EPS are valid for two periods, before and after 26 January 2010, when the latest upgrade of EPS (and IFS) took place. Same wise verification results for COSMO-LEPS are also referred to two periods: before and after 1 December 2009 (latest upgrade for COSMO-LEPS). Emphasis is given on the performance of ECMWF EPS & COSMO-LEPS investigating cases of particular interest over Europe, such as extreme events. The additional information coming from COSMO-LEPS, complementing the coarser resolution ECMWF EPS is validated. Verification has been performed in both the wind and wind power mode.

  14. Experimental verification of ion stopping power prediction from dual energy CT data in tissue surrogates.

    PubMed

    Hünemohr, Nora; Krauss, Bernhard; Tremmel, Christoph; Ackermann, Benjamin; Jäkel, Oliver; Greilich, Steffen

    2014-01-01

    We present an experimental verification of stopping-power-ratio (SPR) prediction from dual energy CT (DECT) with potential use for dose planning in proton and ion therapy. The approach is based on DECT images converted to electron density relative to water ϱe/ϱe, w and effective atomic number Zeff. To establish a parameterization of the I-value by Zeff, 71 tabulated tissue compositions were used. For the experimental assessment of the method we scanned 20 materials (tissue surrogates, polymers, aluminum, titanium) at 80/140Sn kVp and 100/140Sn kVp (Sn: additional tin filtration) and computed the ϱe/ϱe, w and Zeff with a purely image based algorithm. Thereby, we found that ϱe/ϱe, w (Zeff) could be determined with an accuracy of 0.4% (1.7%) for the tissue surrogates with known elemental compositions. SPRs were predicted from DECT images for all 20 materials using the presented approach and were compared to measured water-equivalent path lengths (closely related to SPR). For the tissue surrogates the presented DECT approach was found to predict the experimental values within 0.6%, for aluminum and titanium within an accuracy of 1.7% and 9.4% (from 16-bit reconstructed DECT images). PMID:24334601

  15. A method for predicting DCT-based denoising efficiency for grayscale images corrupted by AWGN and additive spatially correlated noise

    NASA Astrophysics Data System (ADS)

    Rubel, Aleksey S.; Lukin, Vladimir V.; Egiazarian, Karen O.

    2015-03-01

    Results of denoising based on discrete cosine transform for a wide class of images corrupted by additive noise are obtained. Three types of noise are analyzed: additive white Gaussian noise and additive spatially correlated Gaussian noise with middle and high correlation levels. TID2013 image database and some additional images are taken as test images. Conventional DCT filter and BM3D are used as denoising techniques. Denoising efficiency is described by PSNR and PSNR-HVS-M metrics. Within hard-thresholding denoising mechanism, DCT-spectrum coefficient statistics are used to characterize images and, subsequently, denoising efficiency for them. Results of denoising efficiency are fitted for such statistics and efficient approximations are obtained. It is shown that the obtained approximations provide high accuracy of prediction of denoising efficiency.

  16. You know when: event-related potentials and theta/beta power indicate boundary prediction in music.

    PubMed

    Silva, Susana; Barbosa, Fernando; Marques-Teixeira, João; Petersson, Karl Magnus; Castro, São Luís

    2014-03-01

    Neuroscientific and musicological approaches to music cognition indicate that listeners familiarized in the Western tonal tradition expect a musical phrase boundary at predictable time intervals. However, phrase boundary prediction processes in music remain untested. We analyzed event-related potentials (ERPs) and event-related induced power changes at the onset and offset of a boundary pause. We made comparisons with modified melodies, where the pause was omitted and filled by tones. The offset of the pause elicited a closure positive shift (CPS), indexing phrase boundary detection. The onset of the filling tones elicited significant increases in theta and beta powers. In addition, the P2 component was larger when the filling tones started than when they ended. The responses to boundary omission suggest that listeners expected to hear a boundary pause. Therefore, boundary prediction seems to coexist with boundary detection in music segmentation. PMID:24738537

  17. How to interpret a small increase in AUC with an additional risk prediction marker: Decision analysis comes through

    PubMed Central

    Baker, Stuart G.; Schuit, Ewoud; Steyerberg, Ewout W.; Pencina, Michael J.; Vickers, Andew; Moons, Karel G. M.; Mol, Ben W.J.; Lindeman, Karen S.

    2014-01-01

    An important question in the evaluation of an additional risk prediction marker is how to interpret a small increase in the area under the receiver operating characteristic curve (AUC). Many researchers believe that a change in AUC is a poor metric because it increases only slightly with the addition of a marker with a large odds ratio. Because it is not possible on purely statistical grounds to choose between the odds ratio and AUC, we invoke decision analysis, which incorporates costs and benefits. For example a timely estimate of the risk of later non-elective operative delivery can help a woman in labor decide if she wants an early elective cesarean section to avoid greater complications from possible later non-elective operative delivery. A basic risk prediction model for later non-elective operative delivery involves only antepartum markers. Because adding intrapartum markers to this risk prediction model increases AUC by 0.02, we questioned whether this small improvement is worthwhile. A key decision-analytic quantity is the risk threshold, here the risk of later non-elective operative delivery at which a patient would be indifferent between an early elective cesarean section and usual care. For a range of risk thresholds, we found that an increase in the net benefit of risk prediction requires collecting intrapartum marker data on 68 to 124 women for every correct prediction of later non-elective operative delivery. Because data collection is non-invasive, this test tradeoff of 68 to 124 is clinically acceptable, indicating the value of adding intrapartum markers to the risk prediction model. PMID:24825728

  18. Model-based prediction of suitable operating range of a SOFC for an Auxiliary Power Unit

    NASA Astrophysics Data System (ADS)

    Pfafferodt, Matthias; Heidebrecht, Peter; Stelter, Michael; Sundmacher, Kai

    This paper presents a one-dimensional steady state model of a solid oxide fuel cell (SOFC) to be used in an Auxiliary Power Unit (APU). The fuel cell is fed a prereformed gas from an external autothermic reformer. In addition to the three electrochemical reactions (reduction of oxygen at the cathode, oxidation of hydrogen and carbon monoxide at the anode) the water-gas shift reaction and the methane steam reforming reaction are taken into account in the anode channel. The model predicts concentrations and temperatures and uses an equivalent circuit approach to describe the current-voltage characteristics of the cell. The model equations are presented and their implementation into the commercial mathematical software FEMLAB is discussed. An application of this model is used to determine suitable operating parameters with respect to optimum performance and allowable temperature.

  19. Characteristics of concentration-inhibition curves of individual chemicals and applicability of the concentration addition model for mixture toxicity prediction.

    PubMed

    Wang, Na; Wang, Xiaochang C; Ma, Xiaoyan

    2015-03-01

    The concentration addition (CA) model has been widely applied to predict mixture toxicity. However, its applicability is difficult to evaluate due to the complexity of interactions among substances. Considering that the concentration-response curve (CRC) of each component of the mixture is closely related to the prediction of mixture toxicity, mathematical treatments were used to derive a characteristic index kECx (k was the slope of the tangent line of a CRC at concentration ECx). The implication is that the CA model would be applicable for predicting the mixture toxicity only when chemical components have similar kECx in the whole or part of the concentration range. For five selected chemicals whose toxicity was detected using luminescent bacteria, sodium dodecyl benzene sulfonate (SDBS) showed much higher kECx values than the others and its existence in the binary mixtures brought about overestimation of the mixture toxicity with the CA model. The higher the mass ratio of SDBS in a multi-mixture was, the more the toxicity prediction deviated from measurements. By applying the method proposed in this study to analyze some published data, it is confirmed that some components having significantly different kECx values from the other components could explain the large deviation of the mixture toxicity predicted by the CA model. PMID:25499050

  20. The Power of Renal Function Estimation Equations for Predicting Long-Term Kidney Graft Survival

    PubMed Central

    Choi, Hoon Young; Joo, Dong Jin; Song, Mi Kyung; Kim, Myoung Soo; Park, Hyeong Cheon; Kim, Yu Seun; Kim, Beom Seok

    2016-01-01

    Abstract Evaluation of renal function using an accurate estimation equation is important for predicting long-term graft survival. We designed this retrospective cohort study to evaluate the predictive power of renal function estimation by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and the Modification of Diet in Renal Disease (MDRD) study equations for graft survival. We reviewed data of 3290 adult kidney transplant recipients who underwent transplantation at a single center between April 1979 and September 2012. The reliability and agreement of chronic kidney disease (CKD) stages based on the estimated glomerular filtration rate (eGFR) as calculated by the CKD-EPI and MDRD equations were evaluated using Bland–Altman plots and Cohen weighted kappa analyses. The predictive power of CKD stages as classified by each equation for graft survival was investigated using Cox regression models. Additionally, Pearson and Spearman correlation coefficients were used to reveal the relationship between graft survival and eGFR equations. Of 3290 kidney transplant recipients, 3040 were included in the analysis. The mean follow-up duration was 128.08 ± 83.54 months, and 29.8% of participants were reclassified to higher eGFR categories by the CKD-EPI equation compared to the category classification by the MDRD equation. eGFR calculated using the MDRD equation was underestimated compared to that calculated using the CKD-EPI equation, based on the Bland–Altman plot. In Cohen weighted kappa analysis, agreement across CKD stages classified using the 2 equations was reliable, but all CKD stages classified using the MDRD equation appeared to be in lower eGFR categories than those classified using the CKD-EPI equation. Pearson and Spearman correlation analyses indicated that the CKD stage as classified by the CKD-EPI equation, but not the MDRD equation, was significantly correlated with the risk of graft failure. In multivariable Cox regression analysis for

  1. Predicting the Effects of Short-Term Photovoltaic Variability on Power System Frequency for Systems with Integrated Energy Storage

    NASA Astrophysics Data System (ADS)

    Traube, Joshua White

    The percentage of electricity supplied by photovoltaic (PV) generators is steadily rising in power systems worldwide. This rise in PV penetration may lead to larger fluctuations in power system frequency due to variability in PV generator output at time scales that fall between the inertial damping and automatic generation control (AGC) responses of power systems. To reduce PV generator variability, active power controls can be implemented in the power electronic inverters that interface PV generators to the power system. Although various types of active power controls have been developed, no standard methodology exists for evaluating the effectiveness of these controls at improving power system frequency regulation. This dissertation presents a method for predicting the effects of short-term PV variability on power system frequency for a PV generator with active power control provided by integrated energy storage. A custom model of a PV generator with integrated energy storage is implemented in a power system dynamic simulator and validated through experiments with a grid emulator. The model is used to predict the effects of short-term PV variability on the frequency of the IEEE 9-bus test power system modified to include a PV generator with integrated energy storage. In addition, this dissertation utilizes linear analysis of power system frequency control to predict worst-case frequency deviations as a function of the amount of energy storage integrated into PV generators. Through simulation and emulation on a scaled experimental prototype, the maximum frequency deviation caused by the PV generator with a small amount of integrated energy storage is found to be approximately 33% lower than the maximum frequency deviation caused by the PV generator alone. Through linear analysis it is shown that by adding only 36.7 kWh of integrated energy storage to a 1.2 MW PV system, the worst-case frequency deviation on the IEEE 9-bus test system can be reduced 65% from 0

  2. Human Hippocampal Increases in Low-Frequency Power during Associative Prediction Violations

    PubMed Central

    Chen, Janice; Dastjerdi, Mohammad; Foster, Brett L.; LaRocque, Karen F.; Rauschecker, Andreas M.; Parvizi, Josef; Wagner, Anthony D.

    2013-01-01

    Environmental cues often trigger memories of past events (associative retrieval), and these memories are a form of prediction about imminent experience. Learning is driven by the detection of prediction violations, when the past and present diverge. Using intracranial electroencephalography (iEEG), we show that associative prediction violations elicit increased low-frequency power (in the slow-theta range) in human hippocampus, that this low-frequency power increase is modulated by whether conditions allow predictions to be generated, that the increase rapidly onsets after the moment of violation, and that changes in low-frequency power are not present in adjacent perirhinal cortex. These data suggest that associative mismatch is computed within hippocampus when cues trigger predictions that are violated by imminent experience. PMID:23571081

  3. The predictive power of Japanese candlestick charting in Chinese stock market

    NASA Astrophysics Data System (ADS)

    Chen, Shi; Bao, Si; Zhou, Yu

    2016-09-01

    This paper studies the predictive power of 4 popular pairs of two-day bullish and bearish Japanese candlestick patterns in Chinese stock market. Based on Morris' study, we give the quantitative details of definition of long candlestick, which is important in two-day candlestick pattern recognition but ignored by several previous researches, and we further give the quantitative definitions of these four pairs of two-day candlestick patterns. To test the predictive power of candlestick patterns on short-term price movement, we propose the definition of daily average return to alleviate the impact of correlation among stocks' overlap-time returns in statistical tests. To show the robustness of our result, two methods of trend definition are used for both the medium-market-value and large-market-value sample sets. We use Step-SPA test to correct for data snooping bias. Statistical results show that the predictive power differs from pattern to pattern, three of the eight patterns provide both short-term and relatively long-term prediction, another one pair only provide significant forecasting power within very short-term period, while the rest three patterns present contradictory results for different market value groups. For all the four pairs, the predictive power drops as predicting time increases, and forecasting power is stronger for stocks with medium market value than those with large market value.

  4. Critical assessment of indoor noise propagation and prediction in power plants

    NASA Astrophysics Data System (ADS)

    Brittain, Frank H.

    2005-09-01

    Accurate prediction of indoor noise propagation in power plants is important to help estimate occupational noise exposures, and to help predict community noise radiated by plant walls-from levels predicted just inside of each wall. Unfortunately, the basic theories of room acoustics are not applicable. Most power plant rooms are both too large, and too odd shaped for basic room theory, including the Sabine and Norris-Erying theories, to be applicable. Even more important, basic room theory requires empty rooms, and power plant spaces are densely packed with equipment, piping, cable trays, etc. (called fittings). This paper reviews basic room theory, and outlines deficiencies for use in predicting noise propagation inside power plant buildings. Examples are given of walk-away measurements showing that there is no reverberant field, and that reverberation measurements do not correlate well with walk-away test data. Using measurements as an alternative to levels predicted just inside of plant walls to help predict community noise radiated by each wall are discussed. Software for predicting noise in industrial spaces is identified, and their suitability for power plants, which have unusually high fitting densities, is also discussed.

  5. No extension of quantum theory can have improved predictive power.

    PubMed

    Colbeck, Roger; Renner, Renato

    2011-01-01

    According to quantum theory, measurements generate random outcomes, in stark contrast with classical mechanics. This raises the question of whether there could exist an extension of the theory that removes this indeterminism, as suspected by Einstein, Podolsky and Rosen. Although this has been shown to be impossible, existing results do not imply that the current theory is maximally informative. Here we ask the more general question of whether any improved predictions can be achieved by any extension of quantum theory. Under the assumption that measurements can be chosen freely, we answer this question in the negative: no extension of quantum theory can give more information about the outcomes of future measurements than quantum theory itself. Our result has significance for the foundations of quantum mechanics, as well as applications to tasks that exploit the inherent randomness in quantum theory, such as quantum cryptography. PMID:21811240

  6. Predicting, examining, and evaluating FAC in US power plants

    SciTech Connect

    Cohn, M.J.; Garud, Y.S.; Raad, J. de

    1999-11-01

    There have been many pipe failures in fossil and nuclear power plant piping systems caused by flow-accelerated corrosion (FAC). In some piping systems, this failure mechanism maybe the most important type of damage to mitigate because FAC damage has led to catastrophic failures and fatalities. Detecting the damage and mitigating the problem can significantly reduce future forced outages and increase personnel safety. This article discusses the implementation of recent developments to select FAC inspection locations, perform cost-effective examinations, evaluate results, and mitigate FAC failures. These advances include implementing the combination of software to assist in selecting examination locations and an improved pulsed eddy current technique to scan for wall thinning without removing insulation. The use of statistical evaluation methodology and possible mitigation strategies also are discussed.

  7. Nest of Origin Predicts Adult Neuron Addition Rates in the Vocal Control System of the Zebra Finch

    PubMed Central

    Hurley, Patrick; Pytte, Carolyn; Kirn, John R.

    2008-01-01

    Neurogenesis and neuronal replacement in adulthood represent dramatic forms of plasticity that might serve as a substrate for behavioral flexibility. In songbirds, neurons are continually replaced in HVC (used as a proper name), a pre-motor region necessary for the production of learned vocalizations. There are large individual differences in HVC neuron addition. Some of this variation is probably due to individual differences in adult experience; however, it is also possible that heritability or experience early in development constrains the levels of adult neuron addition. As a step toward addressing the latter two possibilities, we explored the extent to which nest of origin predicts rates of HVC neuron addition in adult male zebra finches. One month after injections of [3H]-thymidine to mark dividing cells, neuron addition in HVC was found to co-vary among birds that had been nest mates, even when they were housed in different cages as adults. We also tested whether nest mate co-variation might be due to shared adult auditory experience by measuring neuron addition in nest mate pairs after one member was deafened. There were significant differences in neuron addition between hearing and deaf birds but nest mate relationships persisted. These results suggest that variation in genotype and/or early pre- or postnatal experience can account for a large fraction of adult variation in rates of neuron addition. These results also suggest that a major constraint on neurogenesis and the capacity to adjust rates of neuron addition in response to adult auditory experience is established early in development. PMID:18431053

  8. Mentoring Support and Power: A Three Year Predictive Field Study on Protege Networking and Career Success

    ERIC Educational Resources Information Center

    Blickle, Gerhard; Witzki, Alexander H.; Schneider, Paula B.

    2009-01-01

    Career success of early employees was analyzed from a power perspective and a developmental network perspective. In a predictive field study with 112 employees mentoring support and mentors' power were assessed in the first wave, employees' networking was assessed after two years, and career success (i.e. income and hierarchical position) and…

  9. Robust predictions for the large-scale cosmological power deficit from primordial quantum nonequilibrium

    NASA Astrophysics Data System (ADS)

    Colin, Samuel; Valentini, Antony

    2016-04-01

    The de Broglie-Bohm pilot-wave formulation of quantum theory allows the existence of physical states that violate the Born probability rule. Recent work has shown that in pilot-wave field theory on expanding space relaxation to the Born rule is suppressed for long-wavelength field modes, resulting in a large-scale power deficit ξ(k) which for a radiation-dominated expansion is found to have an approximate inverse-tangent dependence on k (assuming that the width of the initial distribution is smaller than the width of the initial Born-rule distribution and that the initial quantum states are evenly-weighted superpositions of energy states). In this paper, we show that the functional form of ξ(k) is robust under changes in the initial nonequilibrium distribution — subject to the limitation of a subquantum width — as well as under the addition of an inflationary era at the end of the radiation-dominated phase. In both cases, the predicted deficit ξ(k) remains an inverse-tangent function of k. Furthermore, with the inflationary phase the dependence of the fitting parameters on the number of superposed pre-inflationary energy states is comparable to that found previously. Our results indicate that, for the assumed broad class of initial conditions, an inverse-tangent power deficit is likely to be a fairly general and robust signature of quantum relaxation in the early universe.

  10. Factors Predictive of Type of Powered Mobility Received by Veterans with Disability

    PubMed Central

    Rabadi, Meheroz H.; Vincent, Andrea S.

    2015-01-01

    Background The goal of this observational study was to determine factors predictive of the type of powered mobility prescribed to veterans with disability. Material/Methods A retrospective chart review was conducted for all veterans (n=170) who received powered mobility from a designated power mobility clinic. Logistic regression analysis was used to determined factors predictive of the type of powered mobility provided. Results Sixty-four (38%) veterans were provided powered wheelchairs and 106 (62%) were provided powered scooters. Of the variables examined, only primary medical conditions for referral and disability severity (as measured by the 2-minute timed walk test; 2-MWT) were predictive of the types of powered mobility prescribed. Veterans who were able to walk longer distances were more likely to be prescribed powered scooters. Age, gender, race, level of education, marital and employment status, number of chronic medical conditions, and upper and lower limb muscle strength were not significant predictors. Conclusions This study suggests that the primary medical conditions for referral and 2-MWT can assist clinicians in the determination of the type of powered mobility to prescribe to veterans with disability. PMID:25955214

  11. Stack and dump: Peak-power scaling by coherent pulse addition in passive cavities

    NASA Astrophysics Data System (ADS)

    Breitkopf, S.; Eidam, T.; Klenke, A.; Carstens, H.; Holzberger, S.; Fill, E.; Schreiber, T.; Krausz, F.; Tünnermann, A.; Pupeza, I.; Limpert, J.

    2015-10-01

    During the last decades femtosecond lasers have proven their vast benefit in both scientific and technological tasks. Nevertheless, one laser feature bearing the tremendous potential for high-field applications, delivering extremely high peak and average powers simultaneously, is still not accessible. This is the performance regime several upcoming applications such as laser particle acceleration require, and therefore, challenge laser technology to the fullest. On the one hand, some state-of-the-art canonical bulk amplifier systems provide pulse peak powers in the range of multi-terawatt to petawatt. On the other hand, concepts for advanced solid-state-lasers, specifically thin disk, slab or fiber systems have shown their capability of emitting high average powers in the kilowatt range with a high wall-plug-efficiency while maintaining an excellent spatial and temporal quality of the output beam. In this article, a brief introduction to a concept for a compact laser system capable of simultaneously providing high peak and average powers all along with a high wall-plug efficiency will be given. The concept relies on the stacking of a pulse train emitted from a high-repetitive femtosecond laser system in a passive enhancement cavity, also referred to as temporal coherent combining. In this manner, the repetition rate is decreased in favor of a pulse energy enhancement by the same factor while the average power is almost preserved. The key challenge of this concept is a fast, purely reflective switching element that allows for the dumping of the enhanced pulse out of the cavity. Addressing this challenge could, for the first time, allow for the highly efficient extraction of joule-class pulses at megawatt average power levels and thus lead to a whole new area of applications for ultra-fast laser systems.

  12. Low back pain predict sickness absence among power plant workers

    PubMed Central

    Murtezani, Ardiana; Hundozi, Hajrije; Orovcanec, Nikola; Berisha, Merita; Meka, Vjollca

    2010-01-01

    Background: Low back pain (LBP) remains the predominant occupational health problem in most industrialized countries and low-income countries. Both work characteristics and individual factors have been identified as risk factors. More knowledge about the predictors of sickness absence from LBP in the industry will be valuable in determining strategies for prevention. Objectives: The aim of this longitudinal study was to investigate whether individual, work-related physical risk factors were involved in the occurrence of LBP sickness absence. Methods: A follow-up study was conducted among 489 workers, aged 18–65 years, at Kosovo Energetic Corporation in Kosovo. This cross-sectional study used a self-administered questionnaire to collect data on individual and work-related risk factors and the occurrence of LBP sickness absence. Logistic regression models were used to determine associations between risk factors and the occurrence of sickness absence due to LBP. Results: Individual factors did not influence sickness absence, whereas work-related physical factors showed strong associations with sickness absence. The main risk factors for sickness absence due to LBP among production workers were extreme trunk flexion (OR = 1.71, 95% CI = 1.05–2.78) as well as very extreme trunk flexion (OR = 6.04, 95% CI = 1.12–32.49) and exposure to whole-body vibration (OR = 1.75, 95% CI = 1.04–2.95). Conclusion: Reducing sickness absence from LBP among power plant workers requires focusing on the working conditions of blue-collar workers and risk factors for LBP. Increasing social support in the work environment may have effects in reducing sickness absence from LBP. PMID:21120081

  13. PowerPoint Presentations: A Creative Addition to the Research Process.

    ERIC Educational Resources Information Center

    Perry, Alan E.

    2003-01-01

    Contends that the requirement of a PowerPoint presentation as part of the research process would benefit students in the following ways: learning how to conduct research; starting their research project sooner; honing presentation and public speaking skills; improving cooperative and social skills; and enhancing technology skills. Outlines the…

  14. Nonlinear Recurrent Neural Network Predictive Control for Energy Distribution of a Fuel Cell Powered Robot

    PubMed Central

    Chen, Qihong; Long, Rong; Quan, Shuhai

    2014-01-01

    This paper presents a neural network predictive control strategy to optimize power distribution for a fuel cell/ultracapacitor hybrid power system of a robot. We model the nonlinear power system by employing time variant auto-regressive moving average with exogenous (ARMAX), and using recurrent neural network to represent the complicated coefficients of the ARMAX model. Because the dynamic of the system is viewed as operating- state- dependent time varying local linear behavior in this frame, a linear constrained model predictive control algorithm is developed to optimize the power splitting between the fuel cell and ultracapacitor. The proposed algorithm significantly simplifies implementation of the controller and can handle multiple constraints, such as limiting substantial fluctuation of fuel cell current. Experiment and simulation results demonstrate that the control strategy can optimally split power between the fuel cell and ultracapacitor, limit the change rate of the fuel cell current, and so as to extend the lifetime of the fuel cell. PMID:24707206

  15. Wind Power predictability a risk factor in the design, construction and operation of Wind Generation Turbines

    NASA Astrophysics Data System (ADS)

    Thiesen, J.; Gulstad, L.; Ristic, I.; Maric, T.

    2010-09-01

    Summit: The wind power predictability is often a forgotten decision and planning factor for most major wind parks, both onshore and offshore. The results of the predictability are presented after having examined a number of European offshore and offshore parks power predictability by using three(3) mesoscale model IRIE_GFS and IRIE_EC and WRF. Full description: It is well known that the potential wind production is changing with latitude and complexity in terrain, but how big are the changes in the predictability and the economic impacts on a project? The concept of meteorological predictability has hitherto to some degree been neglected as a risk factor in the design, construction and operation of wind power plants. Wind power plants are generally built in places where the wind resources are high, but these are often also sites where the predictability of the wind and other weather parameters is comparatively low. This presentation addresses the question of whether higher predictability can outweigh lower average wind speeds with regard to the overall economy of a wind power project. Low predictability also tends to reduce the value of the energy produced. If it is difficult to forecast the wind on a site, it will also be difficult to predict the power production. This, in turn, leads to increased balance costs and a less reduced carbon emission from the renewable source. By investigating the output from three(3) mesoscale models IRIE and WRF, using ECMWF and GFS as boundary data over a forecasting period of 3 months for 25 offshore and onshore wind parks in Europe, the predictability are mapped. Three operational mesoscale models with two different boundary data have been chosen in order to eliminate the uncertainty with one mesoscale model. All mesoscale models are running in a 10 km horizontal resolution. The model output are converted into "day a head" wind turbine generation forecasts by using a well proven advanced physical wind power model. The power models

  16. Predicting future wind power generation and power demand in France using statistical downscaling methods developed for hydropower applications

    NASA Astrophysics Data System (ADS)

    Najac, Julien

    2014-05-01

    For many applications in the energy sector, it is crucial to dispose of downscaling methods that enable to conserve space-time dependences at very fine spatial and temporal scales between variables affecting electricity production and consumption. For climate change impact studies, this is an extremely difficult task, particularly as reliable climate information is usually found at regional and monthly scales at best, although many industry oriented applications need further refined information (hydropower production model, wind energy production model, power demand model, power balance model…). Here we thus propose to investigate the question of how to predict and quantify the influence of climate change on climate-related energies and the energy demand. To do so, statistical downscaling methods originally developed for studying climate change impacts on hydrological cycles in France (and which have been used to compute hydropower production in France), have been applied for predicting wind power generation in France and an air temperature indicator commonly used for predicting power demand in France. We show that those methods provide satisfactory results over the recent past and apply this methodology to several climate model runs from the ENSEMBLES project.

  17. Rational molecular dynamics scheme for predicting optimum concentration loading of nano-additive in phase change materials

    NASA Astrophysics Data System (ADS)

    Rastogi, Monisha; Vaish, Rahul; Madhar, Niyaz Ahamad; Shaikh, Hamid; Al-Zahrani, S. M.

    2015-10-01

    The present study deals with the diffusion and phase transition behaviour of paraffin reinforced with carbon nano-additives namely graphene oxide (GO) and surface functionalized single walled carbon nanotubes (SWCNT). Bulk disordered systems of paraffin hydrocarbons impregnated with carbon nano-additives have been generated in realistic equilibrium conformations for potential application as latent heat storage systems. Ab initio molecular dynamics(MD) in conjugation with COMPASS forcefield has been implemented using periodic boundary conditions. The proposed scheme allows determination of optimum nano-additive loading for improving thermo-physical properties through analysis of mass, thermal and transport properties; and assists in determination of composite behaviour and related performance from microscopic point of view. It was observed that nanocomposites containing 7.8 % surface functionalised SWCNT and 55% GO loading corresponds to best latent heat storage system. The propounded methodology could serve as a by-pass route for economically taxing and iterative experimental procedures required to attain the optimum composition for best performance. The results also hint at the large unexplored potential of ab-initio classical MD techniques for predicting performance of new nanocomposites for potential phase change material applications.

  18. Evaluation of Different Power of Near Addition in Two Different Multifocal Intraocular Lenses

    PubMed Central

    Unsal, Ugur; Baser, Gonen

    2016-01-01

    Purpose. To compare near, intermediate, and distance vision and quality of vision, when refractive rotational multifocal intraocular lenses with 3.0 diopters or diffractive multifocal intraocular lenses with 2.5 diopters near addition are implanted. Methods. 41 eyes of 41 patients in whom rotational +3.0 diopters near addition IOLs were implanted and 30 eyes of 30 patients in whom diffractive +2.5 diopters near addition IOLs were implanted after cataract surgery were reviewed. Uncorrected and corrected distance visual acuity, intermediate visual acuity, near visual acuity, and patient satisfaction were evaluated 6 months later. Results. The corrected and uncorrected distance visual acuity were the same between both groups (p = 0.50 and p = 0.509, resp.). The uncorrected intermediate and corrected intermediate and near vision acuities were better in the +2.5 near vision added intraocular lens implanted group (p = 0.049, p = 0.005, and p = 0.001, resp.) and the uncorrected near vision acuity was better in the +3.0 near vision added intraocular lens implanted group (p = 0.001). The patient satisfactions of both groups were similar. Conclusion. The +2.5 diopters near addition could be a better choice in younger patients with more distance and intermediate visual requirements (driving, outdoor activities), whereas the + 3.0 diopters should be considered for patients with more near vision correction (reading). PMID:27340560

  19. Quantifying the Effect of Lidar Turbulence Error on Wind Power Prediction

    SciTech Connect

    Newman, Jennifer F.; Clifton, Andrew

    2016-01-01

    Currently, cup anemometers on meteorological towers are used to measure wind speeds and turbulence intensity to make decisions about wind turbine class and site suitability; however, as modern turbine hub heights increase and wind energy expands to complex and remote sites, it becomes more difficult and costly to install meteorological towers at potential sites. As a result, remote-sensing devices (e.g., lidars) are now commonly used by wind farm managers and researchers to estimate the flow field at heights spanned by a turbine. Although lidars can accurately estimate mean wind speeds and wind directions, there is still a large amount of uncertainty surrounding the measurement of turbulence using these devices. Errors in lidar turbulence estimates are caused by a variety of factors, including instrument noise, volume averaging, and variance contamination, in which the magnitude of these factors is highly dependent on measurement height and atmospheric stability. As turbulence has a large impact on wind power production, errors in turbulence measurements will translate into errors in wind power prediction. The impact of using lidars rather than cup anemometers for wind power prediction must be understood if lidars are to be considered a viable alternative to cup anemometers.In this poster, the sensitivity of power prediction error to typical lidar turbulence measurement errors is assessed. Turbulence estimates from a vertically profiling WINDCUBE v2 lidar are compared to high-resolution sonic anemometer measurements at field sites in Oklahoma and Colorado to determine the degree of lidar turbulence error that can be expected under different atmospheric conditions. These errors are then incorporated into a power prediction model to estimate the sensitivity of power prediction error to turbulence measurement error. Power prediction models, including the standard binning method and a random forest method, were developed using data from the aeroelastic simulator FAST

  20. Adaptive neuro-fuzzy inference system (ANFIS) to predict CI engine parameters fueled with nano-particles additive to diesel fuel

    NASA Astrophysics Data System (ADS)

    Ghanbari, M.; Najafi, G.; Ghobadian, B.; Mamat, R.; Noor, M. M.; Moosavian, A.

    2015-12-01

    This paper studies the use of adaptive neuro-fuzzy inference system (ANFIS) to predict the performance parameters and exhaust emissions of a diesel engine operating on nanodiesel blended fuels. In order to predict the engine parameters, the whole experimental data were randomly divided into training and testing data. For ANFIS modelling, Gaussian curve membership function (gaussmf) and 200 training epochs (iteration) were found to be optimum choices for training process. The results demonstrate that ANFIS is capable of predicting the diesel engine performance and emissions. In the experimental step, Carbon nano tubes (CNT) (40, 80 and 120 ppm) and nano silver particles (40, 80 and 120 ppm) with nanostructure were prepared and added as additive to the diesel fuel. Six cylinders, four-stroke diesel engine was fuelled with these new blended fuels and operated at different engine speeds. Experimental test results indicated the fact that adding nano particles to diesel fuel, increased diesel engine power and torque output. For nano-diesel it was found that the brake specific fuel consumption (bsfc) was decreased compared to the net diesel fuel. The results proved that with increase of nano particles concentrations (from 40 ppm to 120 ppm) in diesel fuel, CO2 emission increased. CO emission in diesel fuel with nano-particles was lower significantly compared to pure diesel fuel. UHC emission with silver nano-diesel blended fuel decreased while with fuels that contains CNT nano particles increased. The trend of NOx emission was inverse compared to the UHC emission. With adding nano particles to the blended fuels, NOx increased compared to the net diesel fuel. The tests revealed that silver & CNT nano particles can be used as additive in diesel fuel to improve combustion of the fuel and reduce the exhaust emissions significantly.

  1. The effectiveness of power-generating complexes constructed on the basis of nuclear power plants combined with additional sources of energy determined taking risk factors into account

    NASA Astrophysics Data System (ADS)

    Aminov, R. Z.; Khrustalev, V. A.; Portyankin, A. V.

    2015-02-01

    The effectiveness of combining nuclear power plants equipped with water-cooled water-moderated power-generating reactors (VVER) with other sources of energy within unified power-generating complexes is analyzed. The use of such power-generating complexes makes it possible to achieve the necessary load pickup capability and flexibility in performing the mandatory selective primary and emergency control of load, as well as participation in passing the night minimums of electric load curves while retaining high values of the capacity utilization factor of the entire power-generating complex at higher levels of the steam-turbine part efficiency. Versions involving combined use of nuclear power plants with hydrogen toppings and gas turbine units for generating electricity are considered. In view of the fact that hydrogen is an unsafe energy carrier, the use of which introduces additional elements of risk, a procedure for evaluating these risks under different conditions of implementing the fuel-and-hydrogen cycle at nuclear power plants is proposed. Risk accounting technique with the use of statistical data is considered, including the characteristics of hydrogen and gas pipelines, and the process pipelines equipment tightness loss occurrence rate. The expected intensities of fires and explosions at nuclear power plants fitted with hydrogen toppings and gas turbine units are calculated. In estimating the damage inflicted by events (fires and explosions) occurred in nuclear power plant turbine buildings, the US statistical data were used. Conservative scenarios of fires and explosions of hydrogen-air mixtures in nuclear power plant turbine buildings are presented. Results from calculations of the introduced annual risk to the attained net annual profit ratio in commensurable versions are given. This ratio can be used in selecting projects characterized by the most technically attainable and socially acceptable safety.

  2. The effects of material property assumptions on predicted meltpool shape for laser powder bed fusion based additive manufacturing

    NASA Astrophysics Data System (ADS)

    Teng, Chong; Ashby, Kathryn; Phan, Nam; Pal, Deepankar; Stucker, Brent

    2016-08-01

    The objective of this study was to provide guidance on material specifications for powders used in laser powder bed fusion based additive manufacturing (AM) processes. The methodology was to investigate how different material property assumptions in a simulation affect meltpool prediction and by corrolary how different material properties affect meltpool formation in AM processes. The sensitvity of meltpool variations to each material property can be used as a guide to help drive future research and to help prioritize material specifications in requirements documents. By identifying which material properties have the greatest affect on outcomes, metrology can be tailored to focus on those properties which matter most; thus reducing costs by eliminating unnecessary testing and property charaterizations. Futhermore, this sensitivity study provides insight into which properties require more accurate measurements, thus motivating development of new metrology methods to measure those properties accurately.

  3. The additive and interactive effects of parenting and temperament in predicting adjustment problems of children of divorce.

    PubMed

    Lengua, L J; Wolchik, S A; Sandler, I N; West, S G

    2000-06-01

    Investigated the interaction between parenting and temperament in predicting adjustment problems in children of divorce. The study utilized a sample of 231 mothers and children, 9 to 12 years old, who had experienced divorce within the previous 2 years. Both mothers' and children's reports on parenting, temperament, and adjustment variables were obtained and combined to create cross-reporter measures of the variables. Parenting and temperament were directly and independently related to outcomes consistent with an additive model of their effects. Significant interactions indicated that parental rejection was more strongly related to adjustment problems for children low in positive emotionality, and inconsistent discipline was more strongly related to adjustment problems for children high in impulsivity. These findings suggest that children who are high in impulsivity may be at greater risk for developing problems, whereas positive emotionality may operate as a protective factor, decreasing the risk of adjustment problems in response to negative parenting. PMID:10802832

  4. Wide-area Power System Oscillation Damping using Model Predictive Control Technique

    NASA Astrophysics Data System (ADS)

    Mohamed, Tarek Hassan; Abdel-Rahim, Abdel-Moamen Mohammed; Hassan, Ahmed Abd-Eltawwab; Hiyama, Takashi

    This paper presents a new approach to deal with the problem of robust tuning of power system stabilizer (PSS) and automatic voltage regulator (AVR) in multi-machine power systems. The proposed method is based on a model predictive control (MPC) technique, for improvement stability of the wide-area power system with multiple generators and distribution systems including dispersed generations. The proposed method provides better damping of power system oscillations under small and large disturbances even with the inclusion of local PSSs. The effectiveness of the proposed approach is demonstrated through a two areas, four machines power system. A performance comparison between the proposed controller and some of other controllers is carried out confirming the superiority of the proposed technique. It has also been observed that the proposed algorithm can be successfully applied to larger multiarea power systems and do not suffer with computational difficulties. The proposed algorithm carried out using MATLAB/SIMULINK software package.

  5. Generalized additive models used to predict species abundance in the Gulf of Mexico: an ecosystem modeling tool.

    PubMed

    Drexler, Michael; Ainsworth, Cameron H

    2013-01-01

    Spatially explicit ecosystem models of all types require an initial allocation of biomass, often in areas where fisheries independent abundance estimates do not exist. A generalized additive modelling (GAM) approach is used to describe the abundance of 40 species groups (i.e. functional groups) across the Gulf of Mexico (GoM) using a large fisheries independent data set (SEAMAP) and climate scale oceanographic conditions. Predictor variables included in the model are chlorophyll a, sediment type, dissolved oxygen, temperature, and depth. Despite the presence of a large number of zeros in the data, a single GAM using a negative binomial distribution was suitable to make predictions of abundance for multiple functional groups. We present an example case study using pink shrimp (Farfantepenaeus duroarum) and compare the results to known distributions. The model successfully predicts the known areas of high abundance in the GoM, including those areas where no data was inputted into the model fitting. Overall, the model reliably captures areas of high and low abundance for the large majority of functional groups observed in SEAMAP. The result of this method allows for the objective setting of spatial distributions for numerous functional groups across a modeling domain, even where abundance data may not exist. PMID:23691223

  6. Generalized Additive Models Used to Predict Species Abundance in the Gulf of Mexico: An Ecosystem Modeling Tool

    PubMed Central

    Drexler, Michael; Ainsworth, Cameron H.

    2013-01-01

    Spatially explicit ecosystem models of all types require an initial allocation of biomass, often in areas where fisheries independent abundance estimates do not exist. A generalized additive modelling (GAM) approach is used to describe the abundance of 40 species groups (i.e. functional groups) across the Gulf of Mexico (GoM) using a large fisheries independent data set (SEAMAP) and climate scale oceanographic conditions. Predictor variables included in the model are chlorophyll a, sediment type, dissolved oxygen, temperature, and depth. Despite the presence of a large number of zeros in the data, a single GAM using a negative binomial distribution was suitable to make predictions of abundance for multiple functional groups. We present an example case study using pink shrimp (Farfantepenaeus duroarum) and compare the results to known distributions. The model successfully predicts the known areas of high abundance in the GoM, including those areas where no data was inputted into the model fitting. Overall, the model reliably captures areas of high and low abundance for the large majority of functional groups observed in SEAMAP. The result of this method allows for the objective setting of spatial distributions for numerous functional groups across a modeling domain, even where abundance data may not exist. PMID:23691223

  7. Detection of gene pathways with predictive power for breast cancer prognosis

    PubMed Central

    2010-01-01

    Background Prognosis is of critical interest in breast cancer research. Biomedical studies suggest that genomic measurements may have independent predictive power for prognosis. Gene profiling studies have been conducted to search for predictive genomic measurements. Genes have the inherent pathway structure, where pathways are composed of multiple genes with coordinated functions. The goal of this study is to identify gene pathways with predictive power for breast cancer prognosis. Since our goal is fundamentally different from that of existing studies, a new pathway analysis method is proposed. Results The new method advances beyond existing alternatives along the following aspects. First, it can assess the predictive power of gene pathways, whereas existing methods tend to focus on model fitting accuracy only. Second, it can account for the joint effects of multiple genes in a pathway, whereas existing methods tend to focus on the marginal effects of genes. Third, it can accommodate multiple heterogeneous datasets, whereas existing methods analyze a single dataset only. We analyze four breast cancer prognosis studies and identify 97 pathways with significant predictive power for prognosis. Important pathways missed by alternative methods are identified. Conclusions The proposed method provides a useful alternative to existing pathway analysis methods. Identified pathways can provide further insights into breast cancer prognosis. PMID:20043860

  8. Carbon monoxide exposures from propane-powered floor burnishers following addition of emissions controls

    SciTech Connect

    Demer, F.R.

    1998-11-01

    Previous published work by this author suggests that propane-powered floor burnisher use represents a potentially serious health hazard from carbon monoxide exposures, particularly for susceptible individuals. This earlier study was repeated using burnishers retrofitted with emission controls consisting of self-aspirating catalytic mufflers and computerized air/fuel monitors and alarms. Real-time carbon monoxide detectors with data-logging capabilities were placed on the burnishers in the breathing zones of operators during burnisher use. Carbon monoxide levels were recorded every 30 seconds. Ventilation and physical characteristics of the spaces of burnisher use were characterized, as were burnisher maintenance practices. Thirteen burnishing events were monitored under conditions comparable to previously published monitoring. All carbon monoxide exposures were well below even the most conservative recommended limits from the American Conference of Governmental Industrial Hygienists. Potential failures of the emission controls were also identified and included air filter blockage, spark plug malfunction, and faulty alarm function design.

  9. A Global Perspective: NASA's Prediction of Worldwide Energy Resources (POWER) Project

    NASA Technical Reports Server (NTRS)

    Zhang, Taiping; Stackhouse, Paul W., Jr.; Chandler, William S.; Hoell, James M.; Westberg, David; Whitlock, Charles H.

    2007-01-01

    The Prediction of the Worldwide Energy Resources (POWER) Project, initiated under the NASA Science Mission Directorate Applied Science Energy Management Program, synthesizes and analyzes data on a global scale that are invaluable to the renewable energy industries, especially to the solar and wind energy sectors. The POWER project derives its data primarily from NASA's World Climate Research Programme (WCRP)/Global Energy and Water cycle Experiment (GEWEX) Surface Radiation Budget (SRB) project (Version 2.9) and the Global Modeling and Assimilation Office (GMAO) Goddard Earth Observing System (GEOS) assimilation model (Version 4). The latest development of the NASA POWER Project and its plans for the future are presented in this paper.

  10. [Predictive power on therapy engagement in personality disorders: SWAP- 200 versus SCID-II].

    PubMed

    Löffler-Stastka, Henriette; Blüml, Victor; Jandl-Jager, Elisabeth

    2010-01-01

    The study compares the predictive power of the Shedler-Westen-Assessment Procedure-200 with the Structured Clinical Interview for DSM-IV on engagement in (psychoanalytic) psychotherapy within 297 patients with personality disorders in a 4-year-follow-up. Multinomial logistic regression showed small differences between the prediction rates in the cross-validated data. Both instruments showed clinically useful prediction rates for treatment rejecters: SWAP scales led to correct predictions with dysphoric traits as semi-stable predictors for rejecters, while SCID scales led to correct predictions with Negativistic, Depressive and Schizotypal PD as stable predictors. Results are discussed under the aspect of advantages and disadvantages of the SWAP-200 diagnostic procedure, which includes the assessment of affect-experience, defence-organisation, and object-relation-style. PMID:19790028

  11. Effect of ferrite addition above the base ferrite on the coupling factor of wireless power transfer for vehicle applications

    NASA Astrophysics Data System (ADS)

    Batra, T.; Schaltz, E.; Ahn, S.

    2015-05-01

    Power transfer capability of wireless power transfer systems is highly dependent on the magnetic design of the primary and secondary inductors and is measured quantitatively by the coupling factor. The inductors are designed by placing the coil over a ferrite base to increase the coupling factor and reduce magnetic emissions to the surroundings. Effect of adding extra ferrite above the base ferrite at different physical locations on the self-inductance, mutual inductance, and coupling factor is under investigation in this paper. The addition can increase or decrease the mutual inductance depending on the placement of ferrite. Also, the addition of ferrite increases the self-inductance of the coils, and there is a probability for an overall decrease in the coupling factor. Correct placement of ferrite, on the other hand, can increase the coupling factor relatively higher than the base ferrite as it is closer to the other inductor. Ferrite being a heavy compound of iron increases the inductor weight significantly and needs to be added judiciously. Four zones have been identified in the paper, which shows different sensitivity to addition of ferrite in terms of the two inductances and coupling factor. Simulation and measurement results are presented for different air gaps between the coils and at different gap distances between the ferrite base and added ferrite. This paper is beneficial in improving the coupling factor while adding minimum weight to wireless power transfer system.

  12. The Prediction Power of Servant and Ethical Leadership Behaviours of Administrators on Teachers' Job Satisfaction

    ERIC Educational Resources Information Center

    Güngör, Semra Kiranli

    2016-01-01

    The purpose of this study is to identify servant leadership and ethical leadership behaviors of administrators and the prediction power of these behaviors on teachers' job satisfaction according to the views of schoolteachers. This research, figured in accordance with the quantitative research processes. The target population of the research has…

  13. Predictive-model-based dynamic coordination control strategy for power-split hybrid electric bus

    NASA Astrophysics Data System (ADS)

    Zeng, Xiaohua; Yang, Nannan; Wang, Junnian; Song, Dafeng; Zhang, Nong; Shang, Mingli; Liu, Jianxin

    2015-08-01

    Parameter-matching methods and optimal control strategies of the top-selling hybrid electric vehicle (HEV), namely, power-split HEV, are widely studied. In particular, extant research on control strategy focuses on the steady-state energy management strategy to obtain better fuel economy. However, given that multi-power sources are highly coupled in power-split HEVs and influence one another during mode shifting, conducting research on dynamic coordination control strategy (DCCS) to achieve riding comfort is also important. This paper proposes a predictive-model-based DCCS. First, the dynamic model of the objective power-split HEV is built and the mode shifting process is analyzed based on the developed model to determine the reason for the system shock generated. Engine torque estimation algorithm is then designed according to the principle of the nonlinear observer, and the prediction model of the degree of shock is established based on the theory of model predictive control. Finally, the DCCS with adaptation for a complex driving cycle is realized by combining the feedback control and the predictive model. The presented DCCS is validated on the co-simulation platform of AMESim and Simulink. Results show that the shock during mode shifting is well controlled, thereby improving riding comfort.

  14. Loneliness among University Students: Predictive Power of Sex Roles and Attachment Styles on Loneliness

    ERIC Educational Resources Information Center

    Ilhan, Tahsin

    2012-01-01

    This study examined the predictive power of sex roles and attachment styles on loneliness. A total of 188 undergraduate students (114 female, and 74 male) from Gazi University completed the Bem Sex Role Inventory, UCLA Loneliness Scale, and Relationship Scales Questionnaire. Hierarchic Multiple Regression analysis and t-test were used to test…

  15. Predictive Power of the Success Tendency and Ego Identity Status of the University Students

    ERIC Educational Resources Information Center

    Osman, Pepe

    2015-01-01

    The aim of this research is to assess the predictive power of the success tendency and ego identity status of the students of Physical Education and Sports Teaching Department. 581 students of Physical Education and Sports Teaching Department in Kayseri, Nigde, Burdur, Bolu and Diyarbakir participated in this research. The acquired results were…

  16. The Predictive Power of Socialization Variables for Thinking Styles among Adults in the Workplace

    ERIC Educational Resources Information Center

    Zhang, Li-fang; Higgins, Paul

    2008-01-01

    The present study examines the predictive power of socialization variables for thinking styles among adults in the workplace. One hundred and seventeen managerial personnel (aged between 18 and 55 years) in England responded to the Thinking Styles Inventory-Revised based on Sternberg's theory of mental self-government and to questions concerning…

  17. Aggression in Primary Schools: The Predictive Power of the School and Home Environment

    ERIC Educational Resources Information Center

    Kozina, Ana

    2015-01-01

    In this study, we analyse the predictive power of home and school environment-related factors for determining pupils' aggression. The multiple regression analyses are performed for fourth- and eighth-grade pupils based on the Trends in Mathematics and Science Study (TIMSS) 2007 (N = 8394) and TIMSS 2011 (N = 9415) databases for Slovenia. At…

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

    ERIC Educational Resources Information Center

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

    2009-01-01

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

  19. Research Design and the Predictive Power of Measures of Self-Efficacy

    ERIC Educational Resources Information Center

    Moriarty, Beverley

    2014-01-01

    The purpose of this enquiry was to examine how research design impacts on the predictive power of measures of self-efficacy. Three cautions for designing research into self-efficacy drawn from the seminal work of Albert Bandura (1986) and a further caution proposed by the current author together form the analytical framework for this enquiry. For…

  20. The Influence of Differential "Power" and "Solidarity" upon the Predictability of Behavior: A Peruvian Example

    ERIC Educational Resources Information Center

    Moles, Jerry A.

    1978-01-01

    The usage of Spanish address terms is investigated to explore the predictability and variability in the behavior of non-Indians and Quechua Indians in Peru. The behavior variations are related to differential "power" and "solidarity" between the two ethnic groups and differential "solidarity" within the Quecha group. (Author/SW)

  1. Enhancing Specific Energy and Power in Asymmetric Supercapacitors - A Synergetic Strategy based on the Use of Redox Additive Electrolytes.

    PubMed

    Singh, Arvinder; Chandra, Amreesh

    2016-01-01

    The strategy of using redox additive electrolyte in combination with multiwall carbon nanotubes/metal oxide composites leads to a substantial improvements in the specific energy and power of asymmetric supercapacitors (ASCs). When the pure electrolyte is optimally modified with a redox additive viz., KI, ~105% increase in the specific energy is obtained with good cyclic stability over 3,000 charge-discharge cycles and ~14.7% capacitance fade. This increase is a direct consequence of the iodine/iodide redox pairs that strongly modifies the faradaic and non-faradaic type reactions occurring on the surface of the electrodes. Contrary to what is shown in few earlier reports, it is established that indiscriminate increase in the concentration of redox additives will leads to performance loss. Suitable explanations are given based on theoretical laws. The specific energy or power values being reported in the fabricated ASCs are comparable or higher than those reported in ASCs based on toxic acetonitrile or expensive ionic liquids. The paper shows that the use of redox additive is economically favorable strategy for obtaining cost effective and environmentally friendly ASCs. PMID:27184260

  2. Enhancing Specific Energy and Power in Asymmetric Supercapacitors - A Synergetic Strategy based on the Use of Redox Additive Electrolytes

    NASA Astrophysics Data System (ADS)

    Singh, Arvinder; Chandra, Amreesh

    2016-05-01

    The strategy of using redox additive electrolyte in combination with multiwall carbon nanotubes/metal oxide composites leads to a substantial improvements in the specific energy and power of asymmetric supercapacitors (ASCs). When the pure electrolyte is optimally modified with a redox additive viz., KI, ~105% increase in the specific energy is obtained with good cyclic stability over 3,000 charge-discharge cycles and ~14.7% capacitance fade. This increase is a direct consequence of the iodine/iodide redox pairs that strongly modifies the faradaic and non-faradaic type reactions occurring on the surface of the electrodes. Contrary to what is shown in few earlier reports, it is established that indiscriminate increase in the concentration of redox additives will leads to performance loss. Suitable explanations are given based on theoretical laws. The specific energy or power values being reported in the fabricated ASCs are comparable or higher than those reported in ASCs based on toxic acetonitrile or expensive ionic liquids. The paper shows that the use of redox additive is economically favorable strategy for obtaining cost effective and environmentally friendly ASCs.

  3. Enhancing Specific Energy and Power in Asymmetric Supercapacitors - A Synergetic Strategy based on the Use of Redox Additive Electrolytes

    PubMed Central

    Singh, Arvinder; Chandra, Amreesh

    2016-01-01

    The strategy of using redox additive electrolyte in combination with multiwall carbon nanotubes/metal oxide composites leads to a substantial improvements in the specific energy and power of asymmetric supercapacitors (ASCs). When the pure electrolyte is optimally modified with a redox additive viz., KI, ~105% increase in the specific energy is obtained with good cyclic stability over 3,000 charge-discharge cycles and ~14.7% capacitance fade. This increase is a direct consequence of the iodine/iodide redox pairs that strongly modifies the faradaic and non-faradaic type reactions occurring on the surface of the electrodes. Contrary to what is shown in few earlier reports, it is established that indiscriminate increase in the concentration of redox additives will leads to performance loss. Suitable explanations are given based on theoretical laws. The specific energy or power values being reported in the fabricated ASCs are comparable or higher than those reported in ASCs based on toxic acetonitrile or expensive ionic liquids. The paper shows that the use of redox additive is economically favorable strategy for obtaining cost effective and environmentally friendly ASCs. PMID:27184260

  4. Is It Really Self-Control? Examining the Predictive Power of the Delay of Gratification Task

    PubMed Central

    Duckworth, Angela L.; Tsukayama, Eli; Kirby, Teri A.

    2013-01-01

    This investigation tests whether the predictive power of the delay of gratification task (colloquially known as the “marshmallow test”) derives from its assessment of self-control or of theoretically unrelated traits. Among 56 school-age children in Study 1, delay time was associated with concurrent teacher ratings of self-control and Big Five conscientiousness—but not with other personality traits, intelligence, or reward-related impulses. Likewise, among 966 preschool children in Study 2, delay time was consistently associated with concurrent parent and caregiver ratings of self-control but not with reward-related impulses. While delay time in Study 2 was also related to concurrently measured intelligence, predictive relations with academic, health, and social outcomes in adolescence were more consistently explained by ratings of effortful control. Collectively, these findings suggest that delay task performance may be influenced by extraneous traits, but its predictive power derives primarily from its assessment of self-control. PMID:23813422

  5. A Machine Learning Method for Power Prediction on the Mobile Devices.

    PubMed

    Chen, Da-Ren; Chen, You-Shyang; Chen, Lin-Chih; Hsu, Ming-Yang; Chiang, Kai-Feng

    2015-10-01

    Energy profiling and estimation have been popular areas of research in multicore mobile architectures. While short sequences of system calls have been recognized by machine learning as pattern descriptions for anomalous detection, power consumption of running processes with respect to system-call patterns are not well studied. In this paper, we propose a fuzzy neural network (FNN) for training and analyzing process execution behaviour with respect to series of system calls, parameters and their power consumptions. On the basis of the patterns of a series of system calls, we develop a power estimation daemon (PED) to analyze and predict the energy consumption of the running process. In the initial stage, PED categorizes sequences of system calls as functional groups and predicts their energy consumptions by FNN. In the operational stage, PED is applied to identify the predefined sequences of system calls invoked by running processes and estimates their energy consumption. PMID:26306877

  6. Charge generation by heavy ions in power MOSFETs, burnout space predictions, and dynamic SEB sensitivity

    NASA Astrophysics Data System (ADS)

    Stassinopoulos, E. G.; Brucker, G. J.; Calvel, P.; Baiget, A.; Peyrotte, C.; Gaillard, R.

    1992-12-01

    The transport, energy loss, and charge production of heavy ions in the sensitive regions of IRF 150 power MOSFETs are described. The dependence and variation of transport parameters with ion type and energy relative to the requirements for single event burnout in this part type are discussed. Test data taken with this power MOSFET are used together with analyses by means of a computer code of the ion energy loss and charge production in the device to establish criteria for burnout and parameters for space predictions. These parameters are then used in an application to predict burnout rates in a geostationary orbit for power converters operating in a dynamic mode. Comparisons of rates for different geometries in simulating SEU (single event upset) sensitive volumes are presented.

  7. Charge generation by heavy ions in power MOSFETs, burnout space predictions, and dynamic SEB sensitivity

    NASA Technical Reports Server (NTRS)

    Stassinopoulos, E. G.; Brucker, G. J.; Calvel, P.; Baiget, A.; Peyrotte, C.; Gaillard, R.

    1992-01-01

    The transport, energy loss, and charge production of heavy ions in the sensitive regions of IRF 150 power MOSFETs are described. The dependence and variation of transport parameters with ion type and energy relative to the requirements for single event burnout in this part type are discussed. Test data taken with this power MOSFET are used together with analyses by means of a computer code of the ion energy loss and charge production in the device to establish criteria for burnout and parameters for space predictions. These parameters are then used in an application to predict burnout rates in a geostationary orbit for power converters operating in a dynamic mode. Comparisons of rates for different geometries in simulating SEU (single event upset) sensitive volumes are presented.

  8. Attracted to power: challenge/threat and promotion/prevention focus differentially predict the attractiveness of group power

    PubMed Central

    Scholl, Annika; Sassenrath, Claudia; Sassenberg, Kai

    2015-01-01

    Depending on their motivation, individuals prefer different group contexts for social interactions. The present research sought to provide more insight into this relationship. More specifically, we tested how challenge/threat and a promotion/prevention focus predict attraction to groups with high- or low-power. As such, we examined differential outcomes of threat and prevention focus as well as challenge and promotion focus that have often been regarded as closely related. According to regulatory focus, individuals should prefer groups that they expect to “feel right” for them to join: Low-power groups should be more attractive in a prevention (than a promotion) focus, as these groups suggest security-oriented strategies, which fit a prevention focus. High-power groups should be more attractive in a promotion (rather than a prevention) focus, as these groups are associated with promotion strategies fitting a promotion focus (Sassenberg et al., 2007). In contrast, under threat (vs. challenge), groups that allow individuals to restore their (perceived) lack of control should be preferred: Low-power groups should be less attractive under threat (than challenge) because they provide low resources which threatened individuals already perceive as insufficient and high-power groups might be more attractive under threat (than under challenge), because their high resources allow individuals to restore control. Two experiments (N = 140) supported these predictions. The attractiveness of a group often depends on the motivation to engage in what fits (i.e., prefer a group that feels right in the light of one’s regulatory focus). However, under threat the striving to restore control (i.e., prefer a group allowing them to change the status quo under threat vs. challenge) overrides the fit effect, which may in turn guide individuals’ behavior in social interactions. PMID:25904887

  9. Characterization of Steel-Ta Dissimilar Metal Builds Made Using Very High Power Ultrasonic Additive Manufacturing (VHP-UAM)

    NASA Astrophysics Data System (ADS)

    Sridharan, Niyanth; Norfolk, Mark; Babu, Sudarsanam Suresh

    2016-05-01

    Ultrasonic additive manufacturing is a solid-state additive manufacturing technique that utilizes ultrasonic vibrations to bond metal tapes into near net-shaped components. The major advantage of this process is the ability to manufacture layered structures with dissimilar materials without any intermetallic formation. Majority of the published literature had focused only on the bond formation mechanism in Aluminum alloys. The current work pertains to explain the microstructure evolution during dissimilar joining of iron and tantalum using very high power ultrasonic additive manufacturing and characterization of the interfaces using electron back-scattered diffraction and Nano-indentation measurement. The results showed extensive grain refinement at the bonded interfaces of these metals. This phenomenon was attributed to continuous dynamic recrystallization process driven by the high strain rate plastic deformation and associated adiabatic heating that is well below 50 pct of melting point of both iron and Ta.

  10. Neck Circumference, along with Other Anthropometric Indices, Has an Independent and Additional Contribution in Predicting Fatty Liver Disease

    PubMed Central

    Huang, Bi-xia; Zhu, Ming-fan; Wu, Ting; Zhou, Jing-ya; Liu, Yan; Chen, Xiao-lin; Zhou, Rui-fen; Wang, Li-jun; Chen, Yu-ming; Zhu, Hui-lian

    2015-01-01

    Background and Aim Previous studies have indicated that neck circumference is a valuable predictor for obesity and metabolic syndrome, but little evidence is available for fatty liver disease. We examined the association of neck circumference with fatty liver disease and evaluated its predictive value in Chinese adults. Methods This cross-sectional study comprised 4053 participants (1617 women and 2436 men, aged 20-88) recruited from the Health Examination Center in Guangzhou, China between May 2009 and April 2010. Anthropometric measurements were taken, abdominal ultrasonography was conducted and blood biochemical parameters were measured. Covariance, logistic regression and receiver operating characteristic curve analyses were employed. Results The mean neck circumference was greater in subjects with fatty liver disease than those without the disease in both women and men after adjusting for age (P<0.001). Logistic regression analysis showed that the age-adjusted ORs (95% CI) of fatty liver disease for quartile 4 (vs. quartile 1) of neck circumference were 7.70 (4.95-11.99) for women and 12.42 (9.22-16.74) for men. After further adjusting for other anthropometric indices, both individually and combined, the corresponding ORs remained significant (all P-trends<0.05) but were attenuated to 1.94-2.53 for women and 1.45-2.08 for men. An additive interaction existed between neck circumference and the other anthropometric measures (all P<0.05). A high neck circumference value was associated with a much greater prevalence of fatty liver disease in participants with both high and normal BMI, waist circumference and waist-to-hip ratio values. Conclusions Neck circumference was an independent predictor for fatty liver disease and provided an additional contribution when applied with other anthropometric measures. PMID:25679378

  11. Multivariable time series prediction for the icing process on overhead power transmission line.

    PubMed

    Li, Peng; Zhao, Na; Zhou, Donghua; Cao, Min; Li, Jingjie; Shi, Xinling

    2014-01-01

    The design of monitoring and predictive alarm systems is necessary for successful overhead power transmission line icing. Given the characteristics of complexity, nonlinearity, and fitfulness in the line icing process, a model based on a multivariable time series is presented here to predict the icing load of a transmission line. In this model, the time effects of micrometeorology parameters for the icing process have been analyzed. The phase-space reconstruction theory and machine learning method were then applied to establish the prediction model, which fully utilized the history of multivariable time series data in local monitoring systems to represent the mapping relationship between icing load and micrometeorology factors. Relevant to the characteristic of fitfulness in line icing, the simulations were carried out during the same icing process or different process to test the model's prediction precision and robustness. According to the simulation results for the Tao-Luo-Xiong Transmission Line, this model demonstrates a good accuracy of prediction in different process, if the prediction length is less than two hours, and would be helpful for power grid departments when deciding to take action in advance to address potential icing disasters. PMID:25136653

  12. Multivariable Time Series Prediction for the Icing Process on Overhead Power Transmission Line

    PubMed Central

    Li, Peng; Zhao, Na; Zhou, Donghua; Cao, Min; Li, Jingjie; Shi, Xinling

    2014-01-01

    The design of monitoring and predictive alarm systems is necessary for successful overhead power transmission line icing. Given the characteristics of complexity, nonlinearity, and fitfulness in the line icing process, a model based on a multivariable time series is presented here to predict the icing load of a transmission line. In this model, the time effects of micrometeorology parameters for the icing process have been analyzed. The phase-space reconstruction theory and machine learning method were then applied to establish the prediction model, which fully utilized the history of multivariable time series data in local monitoring systems to represent the mapping relationship between icing load and micrometeorology factors. Relevant to the characteristic of fitfulness in line icing, the simulations were carried out during the same icing process or different process to test the model's prediction precision and robustness. According to the simulation results for the Tao-Luo-Xiong Transmission Line, this model demonstrates a good accuracy of prediction in different process, if the prediction length is less than two hours, and would be helpful for power grid departments when deciding to take action in advance to address potential icing disasters. PMID:25136653

  13. Sensitivity of power and RMS delay spread predictions of a 3D indoor ray tracing model.

    PubMed

    Liu, Zhong-Yu; Guo, Li-Xin; Li, Chang-Long; Wang, Qiang; Zhao, Zhen-Wei

    2016-06-13

    This study investigates the sensitivity of a three-dimensional (3D) indoor ray tracing (RT) model for the use of the uniform theory of diffraction and geometrical optics in radio channel characterizations of indoor environments. Under complex indoor environments, RT-based predictions require detailed and accurate databases of indoor object layouts and the electrical characteristics of such environments. The aim of this study is to assist in selecting the appropriate level of accuracy required in indoor databases to achieve good trade-offs between database costs and prediction accuracy. This study focuses on the effects of errors in indoor environments on prediction results. In studying the effects of inaccuracies in geometry information (indoor object layout) on power coverage prediction, two types of artificial erroneous indoor maps are used. Moreover, a systematic analysis is performed by comparing the predictions with erroneous indoor maps and those with the original indoor map. Subsequently, the influence of random errors on RMS delay spread results is investigated. Given the effect of electrical parameters on the accuracy of the predicted results of the 3D RT model, the relative permittivity and conductivity of different fractions of an indoor environment are set with different values. Five types of computer simulations are considered, and for each type, the received power and RMS delay spread under the same circumstances are simulated with the RT model. PMID:27410335

  14. Predictive Bioinformatic Assignment of Methyl-Bearing Stereocenters, Total Synthesis, and an Additional Molecular Target of Ajudazol B.

    PubMed

    Essig, Sebastian; Schmalzbauer, Björn; Bretzke, Sebastian; Scherer, Olga; Koeberle, Andreas; Werz, Oliver; Müller, Rolf; Menche, Dirk

    2016-02-19

    Full details on the evaluation and application of an easily feasible and generally useful method for configurational assignments of isolated methyl-bearing stereocenters are reported. The analytical tool relies on a bioinformatic gene cluster analysis and utilizes a predictive enoylreductase alignment, and its feasibility was demonstrated by the full stereochemical determination of the ajudazols, highly potent inhibitors of the mitochondrial respiratory chain. Furthermore, a full account of our strategies and tactics that culminated in the total synthesis of ajudazol B, the most potent and least abundant of these structurally unique class of myxobacterial natural products, is presented. Key features include an application of an asymmetric ortholithiation strategy for synthesis of the characteristic anti-configured hydroxyisochromanone core bearing three contiguous stereocenters, a modular oxazole formation, a flexible cross-metathesis approach for terminal allyl amide synthesis, and a late-stage Z,Z-selective Suzuki coupling. This total synthesis unambiguously proves the correct stereochemistry, which was further corroborated by comparison with reisolated natural material. Finally, 5-lipoxygenase was discovered as an additional molecular target of ajudazol B. Activities against this clinically validated key enzyme of the biosynthesis of proinflammatory leukotrienes were in the range of the approved drug zileuton, which further underlines the biological importance of this unique natural product. PMID:26796481

  15. A Model to Predict Total Chlorine Residue in the Cooling Seawater of a Power Plant Using Iodine Colorimetric Method

    PubMed Central

    Wang, Jih-Terng; Chen, Ming-Hui; Lee, Hung-Jen; Chang, Wen-Been; Chen, Chung-Chi; Pai, Su-Cheng; Meng, Pei-Jie

    2008-01-01

    A model experiment monitoring the fate of total residue oxidant (TRO) in water at a constant temperature and salinity indicated that it decayed exponentially with time, and with TRO decaying faster in seawater than in distilled water. The reduction of TRO by temperature (°K) was found to fit a curvilinear relationship in distilled water (r2 = 0.997) and a linear relationship in seawater (r2 = 0.996). Based on the decay rate, flow rate, and the length of cooling water flowing through at a given temperature, the TRO level in the cooling water of a power plant could be estimated using the equation developed in this study. This predictive model would provide a benchmark for power plant operators to adjust the addition of chlorine to levels necessary to control bio-fouling of cooling water intake pipelines, but without irritating ambient marine organisms. PMID:19325768

  16. Power and Performance Management in Nonlinear Virtualized Computing Systems via Predictive Control.

    PubMed

    Wen, Chengjian; Mu, Yifen

    2015-01-01

    The problem of power and performance management captures growing research interest in both academic and industrial field. Virtulization, as an advanced technology to conserve energy, has become basic architecture for most data centers. Accordingly, more sophisticated and finer control are desired in virtualized computing systems, where multiple types of control actions exist as well as time delay effect, which make it complicated to formulate and solve the problem. Furthermore, because of improvement on chips and reduction of idle power, power consumption in modern machines shows significant nonlinearity, making linear power models(which is commonly adopted in previous work) no longer suitable. To deal with this, we build a discrete system state model, in which all control actions and time delay effect are included by state transition and performance and power can be defined on each state. Then, we design the predictive controller, via which the quadratic cost function integrating performance and power can be dynamically optimized. Experiment results show the effectiveness of the controller. By choosing a moderate weight, a good balance can be achieved between performance and power: 99.76% requirements can be dealt with and power consumption can be saved by 33% comparing to the case with open loop controller. PMID:26225769

  17. Power and Performance Management in Nonlinear Virtualized Computing Systems via Predictive Control

    PubMed Central

    Wen, Chengjian; Mu, Yifen

    2015-01-01

    The problem of power and performance management captures growing research interest in both academic and industrial field. Virtulization, as an advanced technology to conserve energy, has become basic architecture for most data centers. Accordingly, more sophisticated and finer control are desired in virtualized computing systems, where multiple types of control actions exist as well as time delay effect, which make it complicated to formulate and solve the problem. Furthermore, because of improvement on chips and reduction of idle power, power consumption in modern machines shows significant nonlinearity, making linear power models(which is commonly adopted in previous work) no longer suitable. To deal with this, we build a discrete system state model, in which all control actions and time delay effect are included by state transition and performance and power can be defined on each state. Then, we design the predictive controller, via which the quadratic cost function integrating performance and power can be dynamically optimized. Experiment results show the effectiveness of the controller. By choosing a moderate weight, a good balance can be achieved between performance and power: 99.76% requirements can be dealt with and power consumption can be saved by 33% comparing to the case with open loop controller. PMID:26225769

  18. Off-Ice Anaerobic Power Does Not Predict On-Ice Repeated Shift Performance in Hockey.

    PubMed

    Peterson, Ben J; Fitzgerald, John S; Dietz, Calvin C; Ziegler, Kevin S; Baker, Sarah E; Snyder, Eric M

    2016-09-01

    Peterson, BJ, Fitzgerald, JS, Dietz, CC, Ziegler, KS, Baker, SE, and Snyder, EM. Off-ice anaerobic power does not predict on-ice repeated shift performance in hockey. J Strength Cond Res 30(9): 2375-2381, 2016-Anaerobic power is a significant predictor of acceleration and top speed in team sport athletes. Historically, these findings have been applied to ice hockey although recent research has brought their validity for this sport into question. As ice hockey emphasizes the ability to repeatedly produce power, single bout anaerobic power tests should be examined to determine their ability to predict on-ice performance. We tested whether conventional off-ice anaerobic power tests could predict on-ice acceleration, top speed, and repeated shift performance. Forty-five hockey players, aged 18-24 years, completed anthropometric, off-ice, and on-ice tests. Anthropometric and off-ice testing included height, weight, body composition, vertical jump, and Wingate tests. On-ice testing consisted of acceleration, top speed, and repeated shift fatigue tests. Vertical jump (VJ) (r = -0.42; r = -0.58), Wingate relative peak power (WRPP) (r = -0.32; r = -0.43), and relative mean power (WRMP) (r = -0.34; r = -0.48) were significantly correlated (p ≤ 0.05) to on-ice acceleration and top speed, respectively. Conversely, none of the off-ice tests correlated with on-ice repeated shift performance, as measured by first gate, second gate, or total course fatigue; VJ (r = 0.06; r = 0.13; r = 0.09), WRPP (r = 0.06; r = 0.14; r = 0.10), or WRMP (r = -0.10; r = -0.01; r = -0.01). Although conventional off-ice anaerobic power tests predict single bout on-ice acceleration and top speed, they neither predict the repeated shift ability of the player, nor are good markers for performance in ice hockey. PMID:26808844

  19. Using Reanalysis Data for the Prediction of Seasonal Wind Turbine Power Losses Due to Icing

    NASA Astrophysics Data System (ADS)

    Burtch, D.; Mullendore, G. L.; Delene, D. J.; Storm, B.

    2013-12-01

    The Northern Plains region of the United States is home to a significant amount of potential wind energy. However, in winter months capturing this potential power is severely impacted by the meteorological conditions, in the form of icing. Predicting the expected loss in power production due to icing is a valuable parameter that can be used in wind turbine operations, determination of wind turbine site locations and long-term energy estimates which are used for financing purposes. Currently, losses due to icing must be estimated when developing predictions for turbine feasibility and financing studies, while icing maps, a tool commonly used in Europe, are lacking in the United States. This study uses the Modern-Era Retrospective Analysis for Research and Applications (MERRA) dataset in conjunction with turbine production data to investigate various methods of predicting seasonal losses (October-March) due to icing at two wind turbine sites located 121 km apart in North Dakota. The prediction of icing losses is based on temperature and relative humidity thresholds and is accomplished using three methods. For each of the three methods, the required atmospheric variables are determined in one of two ways: using industry-specific software to correlate anemometer data in conjunction with the MERRA dataset and using only the MERRA dataset for all variables. For each season, a percentage of the total expected generated power lost due to icing is determined and compared to observed losses from the production data. An optimization is performed in order to determine the relative humidity threshold that minimizes the difference between the predicted and observed values. Eight seasons of data are used to determine an optimal relative humidity threshold, and a further three seasons of data are used to test this threshold. Preliminary results have shown that the optimized relative humidity threshold for the northern turbine is higher than the southern turbine for all methods

  20. Predicting Power Output of Upper Body using the OMNI-RES Scale

    PubMed Central

    Bautista, Iker J.; Chirosa, Ignacio J.; Tamayo, Ignacio Martín; González, Andrés; Robinson, Joseph E.; Chirosa, Luis J.; Robertson, Robert J.

    2014-01-01

    The main aim of this study was to determine the optimal training zone for maximum power output. This was to be achieved through estimating mean bar velocity of the concentric phase of a bench press using a prediction equation. The values for the prediction equation would be obtained using OMNI–RES scale values of different loads of the bench press exercise. Sixty males (age 23.61 2.81 year; body height 176.29 6.73 cm; body mass 73.28 4.75 kg) voluntarily participated in the study and were tested using an incremental protocol on a Smith machine to determine one repetition maximum (1RM) in the bench press exercise. A linear regression analysis produced a strong correlation (r = −0.94) between rating of perceived exertion (RPE) and mean bar velocity (Velmean). The Pearson correlation analysis between real power output (PotReal) and estimated power (PotEst) showed a strong correlation coefficient of r = 0.77, significant at a level of p = 0.01. Therefore, the OMNI–RES scale can be used to predict Velmean in the bench press exercise to control the intensity of the exercise. The positive relationship between PotReal and PotEst allowed for the identification of a maximum power-training zone. PMID:25713677

  1. Low-Complexity Seizure Prediction From iEEG/sEEG Using Spectral Power and Ratios of Spectral Power.

    PubMed

    Zhang, Zisheng; Parhi, Keshab K

    2016-06-01

    Prediction of seizures is a difficult problem as the EEG patterns are not wide-sense stationary and change from seizure to seizure, electrode to electrode, and from patient to patient. This paper presents a novel patient-specific algorithm for prediction of seizures in epileptic patients from either one or two single-channel or bipolar channel intra-cranial or scalp electroencephalogram (EEG) recordings with low hardware complexity. Spectral power features are extracted and their ratios are computed. For each channel, a total of 44 features including 8 absolute spectral powers, 8 relative spectral powers and 28 spectral power ratios are extracted every two seconds using a 4-second window with a 50% overlap. These features are then ranked and selected in a patient-specific manner using a two-step feature selection. Selected features are further processed by a second-order Kalman filter and then input to a linear support vector machine (SVM) classifier. The algorithm is tested on the intra-cranial EEG (iEEG) from the Freiburg database and scalp EEG (sEEG) from the MIT Physionet database. The Freiburg database contains 80 seizures among 18 patients in 427 hours of recordings. The MIT EEG database contains 78 seizures from 17 children in 647 hours of recordings. It is shown that the proposed algorithm can achieve a sensitivity of 100% and an average false positive rate (FPR) of 0.0324 per hour for the iEEG (Freiburg) database and a sensitivity of 98.68% and an average FPR of 0.0465 per hour for the sEEG (MIT) database. These results are obtained with leave-one-out cross-validation where the seizure being tested is always left out from the training set. The proposed algorithm also has a low complexity as the spectral powers can be computed using FFT. The area and power consumption of the proposed linear SVM are 2 to 3 orders of magnitude less than a radial basis function kernel SVM (RBF-SVM) classifier. Furthermore, the total energy consumption of a system using linear

  2. Incorporating Wind Power Forecast Uncertainties Into Stochastic Unit Commitment Using Neural Network-Based Prediction Intervals.

    PubMed

    Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

    2015-09-01

    Penetration of renewable energy resources, such as wind and solar power, into power systems significantly increases the uncertainties on system operation, stability, and reliability in smart grids. In this paper, the nonparametric neural network-based prediction intervals (PIs) are implemented for forecast uncertainty quantification. Instead of a single level PI, wind power forecast uncertainties are represented in a list of PIs. These PIs are then decomposed into quantiles of wind power. A new scenario generation method is proposed to handle wind power forecast uncertainties. For each hour, an empirical cumulative distribution function (ECDF) is fitted to these quantile points. The Monte Carlo simulation method is used to generate scenarios from the ECDF. Then the wind power scenarios are incorporated into a stochastic security-constrained unit commitment (SCUC) model. The heuristic genetic algorithm is utilized to solve the stochastic SCUC problem. Five deterministic and four stochastic case studies incorporated with interval forecasts of wind power are implemented. The results of these cases are presented and discussed together. Generation costs, and the scheduled and real-time economic dispatch reserves of different unit commitment strategies are compared. The experimental results show that the stochastic model is more robust than deterministic ones and, thus, decreases the risk in system operations of smart grids. PMID:25532191

  3. Personality cannot be predicted from the power of resting state EEG

    PubMed Central

    Korjus, Kristjan; Uusberg, Andero; Uusberg, Helen; Kuldkepp, Nele; Kreegipuu, Kairi; Allik, Jüri; Vicente, Raul; Aru, Jaan

    2015-01-01

    In the present study we asked whether it is possible to decode personality traits from resting state EEG data. EEG was recorded from a large sample of subjects (n = 289) who had answered questionnaires measuring personality trait scores of the five dimensions as well as the 10 subordinate aspects of the Big Five. Machine learning algorithms were used to build a classifier to predict each personality trait from power spectra of the resting state EEG data. The results indicate that the five dimensions as well as their subordinate aspects could not be predicted from the resting state EEG data. Finally, to demonstrate that this result is not due to systematic algorithmic or implementation mistakes the same methods were used to successfully classify whether the subject had eyes open or closed. These results indicate that the extraction of personality traits from the power spectra of resting state EEG is extremely noisy, if possible at all. PMID:25762912

  4. Predicts the Long Term Performance and Economic Feasibility of Hybrid Power Sys

    1996-12-01

    HYBRID2 is a combined probalistic/time series model designed to study a wide variety of hybrid power systems. Hybrid power systems combine a number of sources of power generation and, usually, a form of energy storage to supply an electrical load. Hybrid power systems are mainly used in areas such as islands or remote communities that are removed from a power distribution network. These power systems can range from large, multi-megawatt systems to those supplying singlemore » family dwellings. HYBRID2 simulates systems that include diesel generators, wind turbines, battery storage, different power conversion devices and a photovoltaic array. Systems can be modeled with components on the AC, DC or multiple buses. A variety of different operating strategies have been allowed as well as an economic analysis tool. The HYBRID2 code has a user-friendly Graphical User Interface (GUI) as well as a glossary of terms commonly associated with hybrid power systems. HYBRID2 is also packaged with an extensive library of equipment to assist the user in designing hybrid power systems. Each piece of equipment is commercially available and uses manufacturer''s specifications. In addition the library includes resource data and some sample power systems and projects that can be used as templates. Two levels of output are provided, a summary as well as a detailed time step by time step description of power flows. A Graphical Results Interface (GRI) allows for easy and in-depth review of the detailed simulation results.« less

  5. Life prediction of 808nm high power semiconductor laser by accelerated life test of constant current stress

    NASA Astrophysics Data System (ADS)

    Yao, Nan; Li, Wei; Zhao, Yihao; Zhong, Li; Liu, Suping; Ma, Xiaoyu

    2015-10-01

    High power semiconductor laser is widely used because of its high transformation efficiency, good working stability, compact volume and simple driving requirements. Laser's lifetime is very long, but tests at high levels of stress can speed up the failure process and shorten the times to failure significantly. So accelerated life test is used here for forecasting the lifetime of 808nm CW GaAs/AlGaAs high power semiconductor laser that has an output power of 1W under 1.04A. Accelerated life test of constant current stress based on the Inverse Power Law Relationship was designed. Tests were conducted under 1.3A, 1.6A and 1.9A at room temperature. It is the first time that this method is used in the domestic research of laser's lifetime prediction. Applying Weibull Distribution to describe the lifetime distribution and analyzing the data of times to failure, characteristics lifetime's functional relationship model with current is achieved. Then the characteristics lifetime under normal current is extrapolated, which is 9473h. Besides, to confirm the validity of the functional relationship model, we conduct an additional accelerated life test under 1.75A. Based on this experimental data we calculated the characteristics lifetime corresponding to 1.75A that is 171h, while the extrapolated characteristics lifetime from the former functional relationship model is 162h. The two results shows 5% deviation that is very low and acceptable, which indicates that the test design is reasonable and authentic.

  6. Predicted and Measured Modal Sound Power Levels for a Fan Ingesting Distorted Inflow

    NASA Technical Reports Server (NTRS)

    Koch, L. Danielle

    2010-01-01

    Refinements have been made to a method for estimating the modal sound power levels of a ducted fan ingesting distorted inflow. By assuming that each propagating circumferential mode consists only of a single radial mode (the one with the highest cut-off ratio), circumferential mode sound power levels can be computed for a variety of inflow distortion patterns and operating speeds. Predictions from the refined theory have been compared to data from an experiment conducted in the Advanced Noise Control Fan at NASA Glenn Research Center. The inflow to the fan was distorted by inserting cylindrical rods radially into the inlet duct. The rods were placed at an axial location one rotor chord length upstream of the fan and arranged in both regular and irregular circumferential patterns. The fan was operated at 2000, 1800, and 1400 rpm. Acoustic pressure levels were measured in the fan inlet and exhaust ducts using the Rotating Rake fan mode measurement system. Far field sound pressure levels were also measured. It is shown that predicted trends in circumferential mode sound power levels closely match the experimental data for all operating speeds and distortion configurations tested. Insight gained through this work is being used to develop more advanced tools for predicting fan inflow distortion tone noise levels.

  7. Measuring the benefits of climate forecasts in predicting PV power production

    NASA Astrophysics Data System (ADS)

    De Felice, Matteo; Alessandri, Andrea; Pollino, Maurizio

    2016-04-01

    Surface solar radiation is an important variable to model and predict solar power output. Having accurate forecast may be of potential use for planning and operational tasks, both at short- and long-time scales. This study examines the predictability of seasonal surface solar radiation comparing ECMWF System4 Seasonal operational forecasts the SARAH Satellite Dataset on the period 1984-2007. This work tries to answer the following question: how useful are climate forecasts in predicting seasonal PV production? The "information layer" provided by climate information is overlapped with 1) the information about the land cover (CLC2006) to consider the potential amount of land available for PV panels and 2) the information about the solar power installed capacity for European region in order to define the areas where an improved forecast could have a bigger impact. All the information layers are summarised by using a simple scalar index (Index of Opportunity) computed for all the European regions for the four seasons. The results are very interesting, in fact the potential benefits of climate forecasts are not (only) related to their statistical skills (e.g. probabilistic scores) but also to the actual and potential installed capacity of solar power. Here, we show that to assess the usefulness of climate forecasts in the energy sector we should use all the relevant information layers, combining them according to the "needs" of the potential users.

  8. Comparison of Comet Enflow and VA One Acoustic-to-Structure Power Flow Predictions

    NASA Technical Reports Server (NTRS)

    Grosveld, Ferdinand W.; Schiller, Noah H.; Cabell, Randolph H.

    2010-01-01

    Comet Enflow is a commercially available, high frequency vibroacoustic analysis software based on the Energy Finite Element Analysis (EFEA). In this method the same finite element mesh used for structural and acoustic analysis can be employed for the high frequency solutions. Comet Enflow is being validated for a floor-equipped composite cylinder by comparing the EFEA vibroacoustic response predictions with Statistical Energy Analysis (SEA) results from the commercial software program VA One from ESI Group. Early in this program a number of discrepancies became apparent in the Enflow predicted response for the power flow from an acoustic space to a structural subsystem. The power flow anomalies were studied for a simple cubic, a rectangular and a cylindrical structural model connected to an acoustic cavity. The current investigation focuses on three specific discrepancies between the Comet Enflow and the VA One predictions: the Enflow power transmission coefficient relative to the VA One coupling loss factor; the importance of the accuracy of the acoustic modal density formulation used within Enflow; and the recommended use of fast solvers in Comet Enflow. The frequency region of interest for this study covers the one-third octave bands with center frequencies from 16 Hz to 4000 Hz.

  9. A modified Hill muscle model that predicts muscle power output and efficiency during sinusoidal length changes.

    PubMed

    Lichtwark, G A; Wilson, A M

    2005-08-01

    The power output of a muscle and its efficiency vary widely under different activation conditions. This is partially due to the complex interaction between the contractile component of a muscle and the serial elasticity. We investigated the relationship between power output and efficiency of muscle by developing a model to predict the power output and efficiency of muscles under varying activation conditions during cyclical length changes. A comparison to experimental data from two different muscle types suggests that the model can effectively predict the time course of force and mechanical energetic output of muscle for a wide range of contraction conditions, particularly during activation of the muscle. With fixed activation properties, discrepancies in the work output between the model and the experimental results were greatest at the faster and slower cycle frequencies than that for which the model was optimised. Further optimisation of the activation properties across each individual cycle frequency examined demonstrated that a change in the relationship between the concentration of the activator (Ca2+) and the activation level could account for these discrepancies. The variation in activation properties with speed provides evidence for the phenomenon of shortening deactivation, whereby at higher speeds of contraction the muscle deactivates at a faster rate. The results of this study demonstrate that predictions about the mechanics and energetics of muscle are possible when sufficient information is known about the specific muscle. PMID:16043588

  10. Using reanalysis data for the prediction of seasonal wind turbine power losses due to icing

    NASA Astrophysics Data System (ADS)

    Burtch, Daniel G.

    The Northern Plains region of the United States is home to a significant amount of potential wind energy. However, in winter months capturing this potential power is severely impacted by the meteorological conditions, in the form of icing. Predicting the expected loss in power production due to icing is a valuable parameter that can be used in wind turbine operations, determination of wind turbine site locations and long-term energy estimates which are used for financing purposes. Currently, losses due to icing must be estimated when developing predictions for turbine feasibility and financing studies, while icing maps, a tool commonly used in Europe, are lacking in the United States. This study uses the Modern-Era Retrospective Analysis for Research and Applications (MERRA) dataset in conjunction with turbine production data and in-situ wind measurements to investigate six methods of predicting seasonal losses (October-March) due to icing at two sites located in Petersburg, ND and Valley City, ND. The prediction of icing losses is based on temperature and relative humidity thresholds and is accomplished using six methods. Three methods use a Measure-Correlate-Predict (MCP) and flow model (WAsP) analysis for the determination of wind speeds and MERRA for temperature and relative humidity, while three methods use MERRA for all three variables. For each season from 2002 to 2010, the predicted losses due to icing are determined for a range of relative humidity thresholds and compared with observed icing losses. An optimal relative humidity is then determined and tested on all seasons from 2002 to 2013. The prediction methods are then compared to a common practice used in the wind energy industry of assuming a constant percentage loss for icing over the same time period. The three methods using MERRA data alone show severe deficiencies in the accurate determination of wind speeds which leads to a large underprediction in accurate power output. Of the three MCP

  11. Polarization predictions for cosmological models with large-scale power modulation

    NASA Astrophysics Data System (ADS)

    Bunn, Emory F.; Xue, Qingyang

    2016-01-01

    Several "anomalies" have been noted on large angular scales in maps of the cosmic microwave background (CMB) radiation, although the statistical significance of these anomalies is hotly debated. Of particular interest is the evidence for large-scale power modulation: the variance in one half of the sky is larger than the other half. Either this variation is a mere fluke, or it requires a major revision of the standard cosmological paradigm. The way to determine which is the case is to make predictions for future data sets, based on the hypothesis that the anomaly is meaningful and on the hypothesis that it is a fluke. We make predictions for the CMB polarization anisotropy based on a cosmological model in which statistical isotropy is broken via coupling with a dipolar modulation field. Our predictions are constrained to match the observed Planck temperature variations. We identify the modes in CMB polarization data that most strongly distinguish between the modulation and no-modulation hypotheses.

  12. Short-term load and wind power forecasting using neural network-based prediction intervals.

    PubMed

    Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

    2014-02-01

    Electrical power systems are evolving from today's centralized bulk systems to more decentralized systems. Penetrations of renewable energies, such as wind and solar power, significantly increase the level of uncertainty in power systems. Accurate load forecasting becomes more complex, yet more important for management of power systems. Traditional methods for generating point forecasts of load demands cannot properly handle uncertainties in system operations. To quantify potential uncertainties associated with forecasts, this paper implements a neural network (NN)-based method for the construction of prediction intervals (PIs). A newly introduced method, called lower upper bound estimation (LUBE), is applied and extended to develop PIs using NN models. A new problem formulation is proposed, which translates the primary multiobjective problem into a constrained single-objective problem. Compared with the cost function, this new formulation is closer to the primary problem and has fewer parameters. Particle swarm optimization (PSO) integrated with the mutation operator is used to solve the problem. Electrical demands from Singapore and New South Wales (Australia), as well as wind power generation from Capital Wind Farm, are used to validate the PSO-based LUBE method. Comparative results show that the proposed method can construct higher quality PIs for load and wind power generation forecasts in a short time. PMID:24807030

  13. Performance Prediction of Active Piezo Fiber Rackets in Terms of Tennis Power

    NASA Astrophysics Data System (ADS)

    Kawazoe, Yoshihiko; Takeda, Yukihiro; Nakagawa, Masamichi

    Several former top players sent a letter to the International Tennis Federation (ITF) encouraging the governing body to revisit the question of rackets. In the letter, the players wrote that racket technology has led to major changes in how the game is played at the top level. This paper investigated the physical properties of a new type of racket with active piezoelectric fibers appeared recently in the market, and predicted the various factors associated with the frontal impact, such as impact force, contact time, deformation of ball and strings, and also estimated the racket performance such as the coefficient of restitution, the rebound power coefficient, the post-impact ball velocity and the sweet areas relevant to the power in tennis. It is based on the experimental identification of the dynamics of the ball-racket-arm system and the approximate nonlinear impact analysis with a simple swing model. The predicted results with forehand stroke model can explain the difference in mechanism of performance between the new type racket with active piezoelectric fibers and the conventional passive representative rackets. It showed that this new type racket provides higher coefficient of restitution on the whole area of string face and also gives larger rebound power coefficients particularly at the topside and bigger powers on the whole area of string face but the difference was not so large. It seems that the racket-related improvements in play are relatively small and the players themselves continue to improve, accordingly there is a gap between a perception and reality.

  14. A Mechanistic Approach for the Prediction of Critical Power in BWR Fuel Bundles

    NASA Astrophysics Data System (ADS)

    Chandraker, Dinesh Kumar; Vijayan, Pallipattu Krishnan; Sinha, Ratan Kumar; Aritomi, Masanori

    The critical power corresponding to the Critical Heat Flux (CHF) or dryout condition is an important design parameter for the evaluation of safety margins in a nuclear fuel bundle. The empirical approaches for the prediction of CHF in a rod bundle are highly geometric specific and proprietary in nature. The critical power experiments are very expensive and technically challenging owing to the stringent simulation requirements for the rod bundle tests involving radial and axial power profiles. In view of this, the mechanistic approach has gained momentum in the thermal hydraulic community. The Liquid Film Dryout (LFD) in an annular flow is the mechanism of CHF under BWR conditions and the dryout modeling has been found to predict the CHF quite accurately for a tubular geometry. The successful extension of the mechanistic model of dryout to the rod bundle application is vital for the evaluation of critical power in the rod bundle. The present work proposes the uniform film flow approach around the rod by analyzing individual film of the subchannel bounded by rods with different heat fluxes resulting in different film flow rates around a rod and subsequently distributing the varying film flow rates of a rod to arrive at the uniform film flow rate as it has been found that the liquid film has a strong tendency to be uniform around the rod. The FIDOM-Rod code developed for the dryout prediction in BWR assemblies provides detailed solution of the multiple liquid films in a subchannel. The approach of uniform film flow rate around the rod simplifies the liquid film cross flow modeling and was found to provide dryout prediction with a good accuracy when compared with the experimental data of 16, 19 and 37 rod bundles under BWR conditions. The critical power has been predicted for a newly designed 54 rod bundle of the Advanced Heavy Water Reactor (AHWR). The selected constitutive models for the droplet entrainment and deposition rates validated for the dryout in tube were

  15. Three dimensional numerical prediction of icing related power and energy losses on a wind turbine

    NASA Astrophysics Data System (ADS)

    Sagol, Ece

    Regions of Canada experience harsh winter conditions that may persist for several months. Consequently, wind turbines located in these regions are exposed to ice accretion and its adverse effects, from loss of power to ceasing to function altogether. Since the weather-related annual energy production loss of a turbine may be as high as 16% of the nominal production for Canada, estimating these losses before the construction of a wind farm is essential for investors. A literature survey shows that most icing prediction methods and codes are developed for aircraft, and, as this information is mostly considered corporate intellectual property, it is not accessible to researchers in other domains. Moreover, aircraft icing is quite different from wind turbine icing. Wind turbines are exposed to icing conditions for much longer periods than aircraft, perhaps for several days in a harsh climate, whereas the maximum length of exposure of an aircraft is about 3-4 hours. In addition, wind turbine blades operate at subsonic speeds, at lower Reynolds numbers than aircraft, and their physical characteristics are different. A few icing codes have been developed for wind turbine icing nevertheless. However, they are either in 2D, which does not consider the 3D characteristics of the flow field, or they focus on simulating each rotation in a time-dependent manner, which is not practical for computing long hours of ice accretion. Our objective in this thesis is to develop a 3D numerical methodology to predict rime ice shape and the power loss of a wind turbine as a function of wind farm icing conditions. In addition, we compute the Annual Energy Production of a sample turbine under both clean and icing conditions. The sample turbine we have selected is the NREL Phase VI experimental wind turbine installed on a wind farm in Sweden, the icing events at which have been recorded and published. The proposed method is based on computing and validating the clean performance of the turbine

  16. A Comparison of Synoptic Classification Methods for Application to Wind Power Prediction

    NASA Astrophysics Data System (ADS)

    Fowler, P.; Basu, S.

    2008-12-01

    Wind energy is a highly variable resource. To make it competitive with other sources of energy for integration on the power grid, at the very least, a day-ahead forecast of power output must be available. In many grid operations worldwide, next-day power output is scheduled in 30 minute intervals and grid management routinely occurs at real time. Maintenance and repairs require costly time to complete and must be scheduled along with normal operations. Revenue is dependent on the reliability of the entire system. In other words, there is financial and managerial benefit to short-term prediction of wind power. One approach to short-term forecasting is to combine a data centric method such as an artificial neural network with a physically based approach like numerical weather prediction (NWP). The key is in associating high-dimensional NWP model output with the most appropriately trained neural network. Because neural networks perform the best in the situations they are designed for, one can hypothesize that if one can identify similar recurring states in historical weather data, this data can be used to train multiple custom designed neural networks to be used when called upon by numerical prediction. Identifying similar recurring states may offer insight to how a neural network forecast can be improved, but amassing the knowledge and utilizing it efficiently in the time required for power prediction would be difficult for a human to master, thus showing the advantage of classification. Classification methods are important tools for short-term forecasting because they can be unsupervised, objective, and computationally quick. They primarily involve categorizing data sets in to dominant weather classes, but there are numerous ways to define a class and a great variety in interpretation of the results. In the present study a collection of classification methods are used on a sampling of atmospheric variables from the North American Regional Reanalysis data set. The

  17. CMB power spectra from cosmic strings: Predictions for the Planck satellite and beyond

    SciTech Connect

    Bevis, Neil; Hindmarsh, Mark; Kunz, Martin; Urrestilla, Jon

    2010-09-15

    We present a significant improvement over our previous calculations of the cosmic string contribution to cosmic microwave background (CMB) power spectra, with particular focus on sub-WMAP angular scales. These smaller scales are relevant for the now-operational Planck satellite and additional suborbital CMB projects that have even finer resolutions. We employ larger Abelian Higgs string simulations than before and we additionally model and extrapolate the statistical measures from our simulations to smaller length scales. We then use an efficient means of including the extrapolations into our Einstein-Boltzmann calculations in order to yield accurate results over the multipole range 2{<=}l{<=}4000. Our results suggest that power-law behavior cuts in for l > or approx. 3000 in the case of the temperature power spectrum, which then allows cautious extrapolation to even smaller scales. We find that a string contribution to the temperature power spectrum making up 10% of power at l=10 would be larger than the Silk-damped primary adiabatic contribution for l > or approx. 3500. Astrophysical contributions such as the Sunyaev-Zeldovich effect also become important at these scales and will reduce the sensitivity to strings, but these are potentially distinguishable by their frequency-dependence.

  18. The Predictive Power of SIMION/SDS Simulation Software for Modeling Ion Mobility Spectrometry Instruments

    SciTech Connect

    Hanh Lai; Timothy R. McJunkin; Carla J. Miller; Jill R. Scott; Jose R. Almirall

    2008-09-01

    The combined use of SIMION 7.0 and the statistical diffusion simulation (SDS) user program in conjunction with SolidWorks® with COSMSOFloWorks® fluid dynamics software to model a complete, commercial ion mobility spectrometer (IMS) was demonstrated for the first time and compared to experimental results for tests using compounds of immediate interest in the security industry (e.g., 2,4,6-trinitrotoluene and cocaine). The effort of this research was to evaluate the predictive power of SIMION/SDS for application to IMS instruments. The simulation was evaluated against experimental results in three studies: 1) a drift:carrier gas flow rates study assesses the ability of SIMION/SDS to correctly predict the ion drift times; 2) a drift gas composition study evaluates the accuracy in predicting the resolution; and 3) a gate width study compares the simulated peak shape and peak intensity with the experimental values. SIMION/SDS successfully predicted the correct drift time, intensity, and resolution trends for the operating parameters studied. Despite the need for estimations and assumptions in the construction of the simulated instrument, SIMION/SDS was able to predict the resolution between two ion species in air within 3% accuracy. The preliminary success of IMS simulations using SIMION/SDS software holds great promise for the design of future instruments with enhanced performance.

  19. The predictive power of SIMION/SDS simulation software for modeling ion mobility spectrometry instruments

    NASA Astrophysics Data System (ADS)

    Lai, Hanh; McJunkin, Timothy R.; Miller, Carla J.; Scott, Jill R.; Almirall, José R.

    2008-09-01

    The combined use of SIMION 7.0 and the statistical diffusion simulation (SDS) user program in conjunction with SolidWorks® with COSMSOSFloWorks® fluid dynamics software to model a complete, commercial ion mobility spectrometer (IMS) was demonstrated for the first time and compared to experimental results for tests using compounds of immediate interest in the security industry (e.g., 2,4,6-trinitrotoluene, 2,7-dinitrofluorene, and cocaine). The effort of this research was to evaluate the predictive power of SIMION/SDS for application to IMS instruments. The simulation was evaluated against experimental results in three studies: (1) a drift:carrier gas flow rates study assesses the ability of SIMION/SDS to correctly predict the ion drift times; (2) a drift gas composition study evaluates the accuracy in predicting the resolution; (3) a gate width study compares the simulated peak shape and peak intensity with the experimental values. SIMION/SDS successfully predicted the correct drift time, intensity, and resolution trends for the operating parameters studied. Despite the need for estimations and assumptions in the construction of the simulated instrument, SIMION/SDS was able to predict the resolution between two ion species in air within 3% accuracy. The preliminary success of IMS simulations using SIMION/SDS software holds great promise for the design of future instruments with enhanced performance.

  20. Predicting the long tail of book sales: Unearthing the power-law exponent

    NASA Astrophysics Data System (ADS)

    Fenner, Trevor; Levene, Mark; Loizou, George

    2010-06-01

    The concept of the long tail has recently been used to explain the phenomenon in e-commerce where the total volume of sales of the items in the tail is comparable to that of the most popular items. In the case of online book sales, the proportion of tail sales has been estimated using regression techniques on the assumption that the data obeys a power-law distribution. Here we propose a different technique for estimation based on a generative model of book sales that results in an asymptotic power-law distribution of sales, but which does not suffer from the problems related to power-law regression techniques. We show that the proportion of tail sales predicted is very sensitive to the estimated power-law exponent. In particular, if we assume that the power-law exponent of the cumulative distribution is closer to 1.1 rather than to 1.2 (estimates published in 2003, calculated using regression by two groups of researchers), then our computations suggest that the tail sales of Amazon.com, rather than being 40% as estimated by Brynjolfsson, Hu and Smith in 2003, are actually closer to 20%, the proportion estimated by its CEO.

  1. Building ceramics with an addition of pulverized combustion fly ash from the thermal power plant Nováky

    NASA Astrophysics Data System (ADS)

    Húlan, Tomáš; Trník, Anton; Medved, Igor; Štubňa, Igor; Kaljuvee, Tiit

    2016-07-01

    Pulverized combustion fly ash (PFA) from the Power plant Nováky (Slovakia) is analyzed for its potential use in the production of building ceramics. Three materials are used to prepare the mixtures: illite-rich clay (IRC), PFA and IRC fired at 1000 °C (called grog). The mixtures contain 60 % of IRC and 40 % of a non-plastic compound (grog or PFA). A various amount of the grog is replaced by PFA and the effect of this substitution is studied. Thermal analyses (TGA, DTA, thermodilatometry, and dynamical thermomechanical analysis) are used to analyze the processes occurring during firing. The flexural strength and thermal conductivity are determined at room temperature after firing in the temperature interval from 800 to 1100 °C. The results show that an addition of PFA slightly decreases the flexural strength. The thermal conductivity and porosity are practically unaffected by the presence of PFA. Thus, PFA from the Power plant Nováky is a convenient non-plastic component for manufacturing building ceramics.

  2. Optimal welding parameters for very high power ultrasonic additive manufacturing of smart structures with aluminum 6061 matrix

    NASA Astrophysics Data System (ADS)

    Wolcott, Paul J.; Hehr, Adam; Dapino, Marcelo J.

    2014-03-01

    Ultrasonic additive manufacturing (UAM) is a recent solid state manufacturing process that combines ad- ditive joining of thin metal tapes with subtractive milling operations to generate near net shape metallic parts. Due to the minimal heating during the process, UAM is a proven method of embedding Ni-Ti, Fe-Ga, and PVDF to create active metal matrix composites. Recently, advances in the UAM process utilizing 9 kW very high power (VHP) welding has improved bonding properties, enabling joining of high strength materials previously unweldable with 1 kW low power UAM. Consequently, a design of experiments study was conducted to optimize welding conditions for aluminum 6061 components. This understanding is critical in the design of UAM parts containing smart materials. Build parameters, including weld force, weld speed, amplitude, and temperature were varied based on a Taguchi experimental design matrix and tested for me- chanical strength. Optimal weld parameters were identi ed with statistical methods including a generalized linear model for analysis of variance (ANOVA), mean e ects plots, and interaction e ects plots.

  3. Predictions for the 21 cm-galaxy cross-power spectrum observable with LOFAR and Subaru

    NASA Astrophysics Data System (ADS)

    Vrbanec, Dijana; Ciardi, Benedetta; Jelić, Vibor; Jensen, Hannes; Zaroubi, Saleem; Fernandez, Elizabeth R.; Ghosh, Abhik; Iliev, Ilian T.; Kakiichi, Koki; Koopmans, Léon V. E.; Mellema, Garrelt

    2016-03-01

    The 21 cm-galaxy cross-power spectrum is expected to be one of the promising probes of the Epoch of Reionization (EoR), as it could offer information about the progress of reionization and the typical scale of ionized regions at different redshifts. With upcoming observations of 21 cm emission from the EoR with the Low Frequency Array (LOFAR), and of high-redshift Ly α emitters with Subaru's Hyper Suprime-Cam (HSC), we investigate the observability of such cross-power spectrum with these two instruments, which are both planning to observe the ELAIS-N1 field at z = 6.6. In this paper, we use N-body + radiative transfer (both for continuum and Ly α photons) simulations at redshift 6.68, 7.06 and 7.3 to compute the 3D theoretical 21 cm-galaxy cross-power spectrum and cross-correlation function, as well as to predict the 2D 21 cm-galaxy cross-power spectrum and cross-correlation function expected to be observed by LOFAR and HSC. Once noise and projection effects are accounted for, our predictions of the 21 cm-galaxy cross-power spectrum show clear anti-correlation on scales larger than ˜60 h-1 Mpc (corresponding to k ˜ 0.1 h Mpc-1), with levels of significance p = 0.003 at z = 6.6 and p = 0.08 at z = 7.3. On smaller scales, instead, the signal is completely contaminated. On the other hand, our 21 cm-galaxy cross-correlation function is strongly contaminated by noise on all scales, since the noise is no longer being separated by its k modes.

  4. Enhancing prediction power of chemometric models through manipulation of the fed spectrophotometric data: A comparative study.

    PubMed

    Saad, Ahmed S; Hamdy, Abdallah M; Salama, Fathy M; Abdelkawy, Mohamed

    2016-10-01

    Effect of data manipulation in preprocessing step proceeding construction of chemometric models was assessed. The same set of UV spectral data was used for construction of PLS and PCR models directly and after mathematically manipulation as per well known first and second derivatives of the absorption spectra, ratio spectra and first and second derivatives of the ratio spectra spectrophotometric methods, meanwhile the optimal working wavelength ranges were carefully selected for each model and the models were constructed. Unexpectedly, number of latent variables used for models' construction varied among the different methods. The prediction power of the different models was compared using a validation set of 8 mixtures prepared as per the multilevel multifactor design and results were statistically compared using two-way ANOVA test. Root mean squares error of prediction (RMSEP) was used for further comparison of the predictability among different constructed models. Although no significant difference was found between results obtained using Partial Least Squares (PLS) and Principal Component Regression (PCR) models, however, discrepancies among results was found to be attributed to the variation in the discrimination power of adopted spectrophotometric methods on spectral data. PMID:27235828

  5. Predicting the Effects of Nano-Scale Cerium Additives in Diesel Fuel on Regional-Scale Air Quality

    EPA Science Inventory

    Diesel vehicles are a major source of air pollutant emissions. Fuel additives containing nanoparticulate cerium (nCe) are currently being used in some diesel vehicles to improve fuel efficiency. These fuel additives also reduce fine particulate matter (PM2.5) emissio...

  6. Predicting transmission of structure-borne sound power from machines by including terminal cross-coupling

    NASA Astrophysics Data System (ADS)

    Ohlrich, Mogens

    2011-10-01

    Structure-borne sound generated by audible vibration of machines in vehicles, equipment and house-hold appliances is often a major cause of noise. Such vibration of complex machines is mostly determined and quantified by measurements. It has been found that characterization of the vibratory source strength and the prediction of power transmission to a supporting structure or the machine casing itself can be greatly simplified if all mobility cross-terms and spatial cross-coupling of source velocities can be neglected in the analysis. In many cases this gives an acceptable engineering accuracy, especially at mid- and high-frequencies. For structurally compact machines, however, the influence of cross-coupling cannot always be ignored. The present paper addresses this problem and examines the transmission of structure-borne sound power by including spatial cross-coupling between pairs of translational terminals in a global plane. This paired or bi-coupled power transmission represents the simplest case of cross-coupling. The procedure and quality of the predicted transmission using this improved technique is demonstrated experimentally for an electrical motor unit with an integrated radial fan that was mounted resiliently in a vacuum cleaner casing. It is found that cross-coupling plays a significant role, but only at frequencies below 100 Hz for the examined system.

  7. Analysis of contingency tables based on generalised median polish with power transformations and non-additive models.

    PubMed

    Klawonn, Frank; Jayaram, Balasubramaniam; Crull, Katja; Kukita, Akiko; Pessler, Frank

    2013-01-01

    Contingency tables are a very common basis for the investigation of effects of different treatments or influences on a disease or the health state of patients. Many journals put a strong emphasis on p-values to support the validity of results. Therefore, even small contingency tables are analysed by techniques like t-test or ANOVA. Both these concepts are based on normality assumptions for the underlying data. For larger data sets, this assumption is not so critical, since the underlying statistics are based on sums of (independent) random variables which can be assumed to follow approximately a normal distribution, at least for a larger number of summands. But for smaller data sets, the normality assumption can often not be justified. Robust methods like the Wilcoxon-Mann-Whitney-U test or the Kruskal-Wallis test do not lead to statistically significant p-values for small samples. Median polish is a robust alternative to analyse contingency tables providing much more insight than just a p-value. Median polish is a technique that provides more information than just a p-value. It explains the contingency table in terms of an overall effect, row and columns effects and residuals. The underlying model for median polish is an additive model which is sometimes too restrictive. In this paper, we propose two related approach to generalise median polish. A power transformation can be applied to the values in the table, so that better results for median polish can be achieved. We propose a graphical method how to find a suitable power transformation. If the original data should be preserved, one can apply other transformations - based on so-called additive generators - that have an inverse transformation. In this way, median polish can be applied to the original data, but based on a non-additive model. The non-linearity of such a model can also be visualised to better understand the joint effects of rows and columns in a contingency table. PMID:25825662

  8. Within-socket myoelectric prediction of continuous ankle kinematics for control of a powered transtibial prosthesis

    NASA Astrophysics Data System (ADS)

    Farmer, Samuel; Silver-Thorn, Barbara; Voglewede, Philip; Beardsley, Scott A.

    2014-10-01

    Objective. Powered robotic prostheses create a need for natural-feeling user interfaces and robust control schemes. Here, we examined the ability of a nonlinear autoregressive model to continuously map the kinematics of a transtibial prosthesis and electromyographic (EMG) activity recorded within socket to the future estimates of the prosthetic ankle angle in three transtibial amputees. Approach. Model performance was examined across subjects during level treadmill ambulation as a function of the size of the EMG sampling window and the temporal ‘prediction’ interval between the EMG/kinematic input and the model’s estimate of future ankle angle to characterize the trade-off between model error, sampling window and prediction interval. Main results. Across subjects, deviations in the estimated ankle angle from the actual movement were robust to variations in the EMG sampling window and increased systematically with prediction interval. For prediction intervals up to 150 ms, the average error in the model estimate of ankle angle across the gait cycle was less than 6°. EMG contributions to the model prediction varied across subjects but were consistently localized to the transitions to/from single to double limb support and captured variations from the typical ankle kinematics during level walking. Significance. The use of an autoregressive modeling approach to continuously predict joint kinematics using natural residual muscle activity provides opportunities for direct (transparent) control of a prosthetic joint by the user. The model’s predictive capability could prove particularly useful for overcoming delays in signal processing and actuation of the prosthesis, providing a more biomimetic ankle response.

  9. Impact of Statistical Learning Methods on the Predictive Power of Multivariate Normal Tissue Complication Probability Models

    SciTech Connect

    Xu Chengjian; Schaaf, Arjen van der; Schilstra, Cornelis; Langendijk, Johannes A.; Veld, Aart A. van't

    2012-03-15

    Purpose: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. Methods and Materials: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. Results: It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. Conclusions: The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended.

  10. A 10-kW SiC Inverter with A Novel Printed Metal Power Module With Integrated Cooling Using Additive Manufacturing

    SciTech Connect

    Chinthavali, Madhu Sudhan; Ayers, Curtis William; Campbell, Steven L; Wiles, Randy H; Ozpineci, Burak

    2014-01-01

    With efforts to reduce the cost, size, and thermal management systems for the power electronics drivetrain in hybrid electric vehicles (HEVs) and plug-in hybrid electric vehicles (PHEVs), wide band gap semiconductors including silicon carbide (SiC) have been identified as possibly being a partial solution. This paper focuses on the development of a 10-kW all SiC inverter using a high power density, integrated printed metal power module with integrated cooling using additive manufacturing techniques. This is the first ever heat sink printed for a power electronics application. About 50% of the inverter was built using additive manufacturing techniques.

  11. Prediction of Giant Thermoelectric Power Factor in Type-VIII Clathrate Si46

    NASA Astrophysics Data System (ADS)

    Norouzzadeh, Payam; Myles, Charles W.; Vashaee, Daryoosh

    2014-11-01

    Clathrate materials have been the subject of intense interest and research for thermoelectric application. Nevertheless, from the very large number of conceivable clathrate structures, only a small fraction of them have been examined. Since the thermal conductivity of clathrates is inherently small due to their large unit cell size and open-framework structure, the current research on clathrates is focused on finding the ones with large thermoelectric power factor. Here we predict an extraordinarily large power factor for type-VIII clathrate Si46. We show the existence of a large density of closely packed elongated ellipsoidal carrier pockets near the band edges of this so far hypothetical material structure, which is higher than that of the best thermoelectric materials known today. The high crystallographic symmetry near the energy band edges for Si46-VIII clathrates is responsible for the formation of such a large number of carrier pockets.

  12. Prediction of giant thermoelectric power factor in type-VIII clathrate Si46.

    PubMed

    Norouzzadeh, Payam; Myles, Charles W; Vashaee, Daryoosh

    2014-01-01

    Clathrate materials have been the subject of intense interest and research for thermoelectric application. Nevertheless, from the very large number of conceivable clathrate structures, only a small fraction of them have been examined. Since the thermal conductivity of clathrates is inherently small due to their large unit cell size and open-framework structure, the current research on clathrates is focused on finding the ones with large thermoelectric power factor. Here we predict an extraordinarily large power factor for type-VIII clathrate Si(46). We show the existence of a large density of closely packed elongated ellipsoidal carrier pockets near the band edges of this so far hypothetical material structure, which is higher than that of the best thermoelectric materials known today. The high crystallographic symmetry near the energy band edges for Si(46)-VIII clathrates is responsible for the formation of such a large number of carrier pockets. PMID:25391971

  13. Prediction of radio frequency power generation of Neptune's magnetosphere from generalized radiometric Bode's law

    NASA Technical Reports Server (NTRS)

    Million, M. A.; Goertz, C. K.

    1988-01-01

    Magnetospheric radio frequency emission power has been shown to vary as a function of both solar wind and planetary values such as magnetic field by Kaiser and Desch (1984). Planetary magnetic fields have been shown to scale with planetary variables such as density and angular momentum by numerous researchers. This paper combines two magnetic scaling laws with the radiometric law to yield 'Bode's'-type laws governing planetary radio emissions. Further analysis allows the reduction of variables to planetary mass and orbital distance. These generalized laws are then used to predict the power otuput of Neptune to be about 1.6 x 10 to the 7th W; with the intensity peaking at about 3 MHz.

  14. Prediction of radio frequency power generation of Neptune's magnetosphere from generalized radiometric Bode's law

    NASA Astrophysics Data System (ADS)

    Millon, M. A.; Goertz, C. K.

    1988-01-01

    Magnetospheric radio frequency emission power has been shown to vary as a function of both solar wind and planetary values such as magnetic field by Kaiser and Desch. Planetary magnetic fields have been shown to scale with planetary variables such as density and angular momentum by numerous researchers. This paper combines two magnetic scaling laws (Busse's and Curtis Ness') with the radiometric law to yield "Bode's"-type laws governing planetary radio emission. Further analysis allows the reduction of variables to planetary mass and orbital distance. These generalized laws are then used to predict the power output of Neptune to be about 1.6×107W; with the intensity peaking at about 3 MHz.

  15. Fuzzy modeling and predictive control of superheater steam temperature for power plant.

    PubMed

    Wu, Xiao; Shen, Jiong; Li, Yiguo; Lee, Kwang Y

    2015-05-01

    This paper develops a stable fuzzy model predictive controller (SFMPC) to solve the superheater steam temperature (SST) control problem in a power plant. First, a data-driven Takagi-Sugeno (TS) fuzzy model is developed to approximate the behavior of the SST control system using the subspace identification (SID) method. Then, an SFMPC for output regulation is designed based on the TS-fuzzy model to regulate the SST while guaranteeing the input-to-state stability under the input constraints. The effect of modeling mismatches and unknown plant behavior variations are overcome by the use of a disturbance term and steady-state target calculator (SSTC). Simulation results for a 600 MW power plant show that an offset-free tracking of SST can be achieved over a wide range of load variation. PMID:25530258

  16. Power and energy dissipation in subsequent return strokes as predicted by a new return stroke model

    NASA Technical Reports Server (NTRS)

    Cooray, Vernon

    1991-01-01

    Recently, Cooray introduced a new return stroke model which is capable of predicting the temporal behavior of the return stroke current and the return stroke velocity as a function of the height along the return stroke channel. The authors employed this model to calculate the power and energy dissipation in subsequent return strokes. The results of these calculations are presented here. It was concluded that a large fraction of the total energy available for the dart leader-subsequent stroke process is dissipated in the dart leader stage. The peak power per unit length dissipated in a subsequent stroke channel element decreases with increasing height of that channel element from ground level. For a given channel element, the peak power dissipation increases with increasing current in that channel element. The peak electrical power dissipation in a typical subsequent return stroke is about 1.5 times 10(exp 11) W. The energy dissipation in a subsequent stroke increases with increasing current in the return stroke channel, and for a typical subsequent stroke, the energy dissipation per unit length is about 5.0 times 10(exp 3) J/m.

  17. Application of explicit model predictive control to a hybrid battery-ultracapacitor power source

    NASA Astrophysics Data System (ADS)

    Hredzak, Branislav; Agelidis, Vassilios G.; Demetriades, Georgios

    2015-03-01

    An explicit model predictive control (EMPC) system for a hybrid battery-ultracapacitor power source is proposed and experimentally verified in this paper. The main advantage of using the EMPC system is that the control law computation is reduced to evaluation of an explicitly defined piecewise linear function of the states. Separate EMPC systems for the total output current loop, the battery loop and the ultracapacitor loop are designed. This modular design approach allows evaluation of the performance of each individual EMPC system separately and also improves the convergence of the EMPC system design algorithm as the models used to design each loop are smaller. In order to protect the hybrid power source, the designed EMPC systems maintain operation of the hybrid power source within specified constraints, namely, battery and ultracapacitor current constraints, battery state of charge constraints and ultracapacitor voltage constraints. At the same time, the total output current EMPC system allocates high frequency current changes to the ultracapacitor and the low frequency current changes to the battery thus extending the battery lifetime. Presented experimental results verify that the hybrid power source operates within the specified constraints while allocating high and low frequency current changes to the ultracapacitor and battery respectively.

  18. How Many Model Evaluations Are Required To Predict The AEP Of A Wind Power Plant?

    NASA Astrophysics Data System (ADS)

    Murcia, J. P.; Réthoré, P. E.; Natarajan, A.; Sørensen, J. D.

    2015-06-01

    Wind farm flow models have advanced considerably with the use of large eddy simulations (LES) and Reynolds averaged Navier-Stokes (RANS) computations. The main limitation of these techniques is their high computational time requirements; which makes their use for wind farm annual energy production (AEP) predictions expensive. The objective of the present paper is to minimize the number of model evaluations required to capture the wind power plant's AEP using stationary wind farm flow models. Polynomial chaos techniques are proposed based on arbitrary Weibull distributed wind speed and Von Misses distributed wind direction. The correlation between wind direction and wind speed are captured by defining Weibull-parameters as functions of wind direction. In order to evaluate the accuracy of these methods the expectation and variance of the wind farm power distributions are compared against the traditional binning method with trapezoidal and Simpson's integration rules. The wind farm flow model used in this study is the semi-empirical wake model developed by Larsen [1]. Three test cases are studied: a single turbine, a simple and a real offshore wind power plant. A reduced number of model evaluations for a general wind power plant is proposed based on the convergence of the present method for each case.

  19. Development of uncertainty methodology for COBRA-TF void distribution and critical power predictions

    NASA Astrophysics Data System (ADS)

    Aydogan, Fatih

    Thermal hydraulic codes are commonly used tools in licensing processes for the evaluation of various thermal hydraulic scenarios. The uncertainty of a thermal hydraulic code prediction is calculated with uncertainty analyses. The objective of all the uncertainty analysis is to determine how well a code predicts with corresponding uncertainties. If a code has a big output uncertainty, this code needs further development and/or model improvements. If a code has a small uncertainty, this code needs maintenance program in order to keep this small output uncertainty. Uncertainty analysis also indicates the more validation data is needed. Uncertainty analyses for the BWR nominal steady state and transient scenarios are necessary in order to develop and improve the two phase flow models in the thermal hydraulic codes. Because void distribution is the key factor in order to determine the flow regime and heat transfer regime of the flow and critical power is an important factor for the safety margin, both steady state void distribution and critical power predictions are important features of a code. An uncertainty analysis for these two phenomena/cases provides valuable results. These results can be used for the development of the thermal hydraulic codes that are used for designing a BWR bundle or for licensing procedures. This dissertation includes the development of a particular uncertainty methodology for the steady state void distribution and critical power predictions. In this methodology, the PIRT element of CSAU was used to eliminate the low ranked uncertainty parameters. The SPDF element of GRS was utilized to make the uncertainty methodology flexible for the assignment of PDFs to the uncertainty parameters. The developed methodology includes the uncertainty comparison methods to assess the code precision with the sample-averaged bias, to assess the code spreading with the sample-averaged standard deviation and to assess the code reliability with the proportion of

  20. A Comparison of the Predictive Power of Anthropometric Indices for Hypertension and Hypotension Risk

    PubMed Central

    Lee, Bum Ju; Kim, Jong Yeol

    2014-01-01

    Background and Aims It is commonly accepted that body fat distribution is associated with hypertension, but the strongest anthropometric indicator of the risk of hypertension is still controversial. Furthermore, no studies on the association of hypotension with anthropometric indices have been reported. The objectives of the present study were to determine the best predictors of hypertension and hypotension among various anthropometric indices and to assess the use of combined indices as a method of improving the predictive power in adult Korean women and men. Methods For 12789 subjects 21–85 years of age, we assessed 41 anthropometric indices using statistical analyses and data mining techniques to determine their ability to discriminate between hypertension and normotension as well as between hypotension and normotension. We evaluated the predictive power of combined indices using two machine learning algorithms and two variable subset selection techniques. Results The best indicator for predicting hypertension was rib circumference in both women (p = <0.0001; OR = 1.813; AUC = 0.669) and men (p = <0.0001; OR = 1.601; AUC = 0.627); for hypotension, the strongest predictor was chest circumference in women (p = <0.0001; OR = 0.541; AUC = 0.657) and neck circumference in men (p = <0.0001; OR = 0.522; AUC = 0.672). In experiments using combined indices, the areas under the receiver operating characteristic curves (AUC) for the prediction of hypertension risk in women and men were 0.721 and 0.652, respectively, according to the logistic regression with wrapper-based variable selection; for hypotension, the corresponding values were 0.675 in women and 0.737 in men, according to the naïve Bayes with wrapper-based variable selection. Conclusions The best indicators of the risk of hypertension and the risk of hypotension may differ. The use of combined indices seems to slightly improve the predictive power for both

  1. The Predictive Power of Evolutionary Biology and the Discovery of Eusociality in the Naked Mole-Rat.

    ERIC Educational Resources Information Center

    Braude, Stanton

    1997-01-01

    Discusses how biologists use evolutionary theory and provides examples of how evolutionary biologists test hypotheses on specific modes of selection and evolution. Presents an example of the successful predictive power of one evolutionary hypothesis. Contains 38 references. (DDR)

  2. Validation and comparison of three power prediction models for CPV modules

    NASA Astrophysics Data System (ADS)

    Mundel, Hannah; Treiber, Lara; Dufour, Pascal; Coish, Nicholas; Fischer, Anton; Myrskog, Stefan

    2015-09-01

    Accurate predictive energy modelling of a solar farm requires a thorough understanding of solar spectral variations, along with the spectral response and optical properties of the photovoltaic system. This paper investigates the minimum data required to accurately predict power output from CPV modules, comparing modelled output to both measured data and the existing method used by Sandia PV Array Performance Model (SAPM). Three models were derived based on various weather inputs. A Detailed Spectral Model (DS) uses SMARTS, inputting measured air mass, aerosols, ozone and water content, and incorporating measured DNI to account for cloudy days. The Sub-System Algebraic Model (SSA) removes the need for instantaneous spectrum calculations by creating equations for each sub-cell and DNI, based on the same inputs as the DS. These two models rely heavily on aerosol, which is not readily available. Alternatively, an Empirical model (EMP) may be used to determine the relationship between measured output power and easily measureable weather data (ambient temperature, air mass, direct normal irradiance and water content). These non-linear DS, SSA and EMP models have a bias error of 3.09 %, 4.24 % and -0.67 %, respectively. It was also found that the SSA model can be used in lieu of the SAPM.

  3. An outdoor noise propagation study to predict the effect of a power plant expansion

    NASA Astrophysics Data System (ADS)

    Brasovan, Philip J.; Carney, Melinda J.; Cheenne, Dominique J.

    2005-04-01

    The results of an outdoor noise propagation model using CadnaA were compared to test data obtained on-site. The subject property is the central utility plant of a hospital located in Milwaukee, scheduled to be expanded with the addition of cooling towers. The modeled area was 400 m squared with a resolution grid of 2 m squared. The model was used to validate the observed test data as well as to predict the anticipated noise levels at completion of the expansion. A total of 11 points were investigated and the predicted data were found to match the test values within 2 dB at many locations. The data from the model show that the anticipated noise levels at the East property line will exceed those mandated by local ordinances by 3 dB. The model also predicts that the addition of a three meter absorbing barrier and the use of reduced noise fans for the six cell cooling system will bring the overall noise level from the system into compliance.

  4. A GLOBAL ASSESSMENT OF SOLAR ENERGY RESOURCES: NASA's Prediction of Worldwide Energy Resources (POWER) Project

    NASA Astrophysics Data System (ADS)

    Zhang, T.; Stackhouse, P. W., Jr.; Chandler, W.; Hoell, J. M.; Westberg, D.; Whitlock, C. H.

    2010-12-01

    NASA's POWER project, or the Prediction of the Worldwide Energy Resources project, synthesizes and analyzes data on a global scale. The products of the project find valuable applications in the solar and wind energy sectors of the renewable energy industries. The primary source data for the POWER project are NASA's World Climate Research Project (WCRP)/Global Energy and Water cycle Experiment (GEWEX) Surface Radiation Budget (SRB) project (Release 3.0) and the Global Modeling and Assimilation Office (GMAO) Goddard Earth Observing System (GEOS) assimilation model (V 4.0.3). Users of the POWER products access the data through NASA's Surface meteorology and Solar Energy (SSE, Version 6.0) website (http://power.larc.nasa.gov). Over 200 parameters are available to the users. The spatial resolution is 1 degree by 1 degree now and will be finer later. The data covers from July 1983 to December 2007, a time-span of 24.5 years, and are provided as 3-hourly, daily and monthly means. As of now, there have been over 18 million web hits and over 4 million data file downloads. The POWER products have been systematically validated against ground-based measurements, and in particular, data from the Baseline Surface Radiation Network (BSRN) archive, and also against the National Solar Radiation Data Base (NSRDB). Parameters such as minimum, maximum, daily mean temperature and dew points, relative humidity and surface pressure are validated against the National Climate Data Center (NCDC) data. SSE feeds data directly into Decision Support Systems including RETScreen International clean energy project analysis software that is written in 36 languages and has greater than 260,000 users worldwide.

  5. HEPS4Power - Extended-range Hydrometeorological Ensemble Predictions for Improved Hydropower Operations and Revenues

    NASA Astrophysics Data System (ADS)

    Bogner, Konrad; Monhart, Samuel; Liniger, Mark; Spririg, Christoph; Jordan, Fred; Zappa, Massimiliano

    2015-04-01

    In recent years large progresses have been achieved in the operational prediction of floods and hydrological drought with up to ten days lead time. Both the public and the private sectors are currently using probabilistic runoff forecast in order to monitoring water resources and take actions when critical conditions are to be expected. The use of extended-range predictions with lead times exceeding 10 days is not yet established. The hydropower sector in particular might have large benefits from using hydro meteorological forecasts for the next 15 to 60 days in order to optimize the operations and the revenues from their watersheds, dams, captions, turbines and pumps. The new Swiss Competence Centers in Energy Research (SCCER) targets at boosting research related to energy issues in Switzerland. The objective of HEPS4POWER is to demonstrate that operational extended-range hydro meteorological forecasts have the potential to become very valuable tools for fine tuning the production of energy from hydropower systems. The project team covers a specific system-oriented value chain starting from the collection and forecast of meteorological data (MeteoSwiss), leading to the operational application of state-of-the-art hydrological models (WSL) and terminating with the experience in data presentation and power production forecasts for end-users (e-dric.ch). The first task of the HEPS4POWER will be the downscaling and post-processing of ensemble extended-range meteorological forecasts (EPS). The goal is to provide well-tailored forecasts of probabilistic nature that should be reliable in statistical and localized at catchment or even station level. The hydrology related task will consist in feeding the post-processed meteorological forecasts into a HEPS using a multi-model approach by implementing models with different complexity. Also in the case of the hydrological ensemble predictions, post-processing techniques need to be tested in order to improve the quality of the

  6. A Non-Additive Interaction of a Functional MAO-A VNTR and Testosterone Predicts Antisocial Behavior

    PubMed Central

    Sjöberg, Rickard L; Ducci, Francesca; Barr, Christina S; Newman, Timothy K; Dell'Osso, Liliana; Virkkunen, Matti; Goldman, David

    2008-01-01

    A functional VNTR polymorphism in the promoter of the monoamine oxidase A gene (MAOA-LPR) has previously been shown to be an important predictor of antisocial behavior in men. Testosterone analogues are known to interact with the MAOA promoter in vitro to influence gene transcription as well as in vivo to influence CSF levels of the MAO metabolite 3-methoxy-4-hydroxyphenylglycol (MHPG) in human males. We examined the possible joint effects of testosterone (measured in CSF) and MAOA-LPR genotype on antisocial personality disorder and scores on the Brown–Goodwin Aggression scale in 95 unrelated male criminal alcoholics and 45 controls. The results confirm that MAOA genotype and CSF testosterone interact to predict antisocial behaviors. The MAOA/testosterone interaction also predicted low levels of CSF MHPG, which tentatively suggests the possibility that the interaction may be mediated by a direct effect on gene transcription. If replicated these findings offer plausible explanations for previous inconsistencies in studies of the relationship between testosterone and male human aggression, as well as for how MAOA genotype may influence aggressive behavior in human males. PMID:17429405

  7. A non-additive interaction of a functional MAO-A VNTR and testosterone predicts antisocial behavior.

    PubMed

    Sjöberg, Rickard L; Ducci, Francesca; Barr, Christina S; Newman, Timothy K; Dell'osso, Liliana; Virkkunen, Matti; Goldman, David

    2008-01-01

    A functional VNTR polymorphism in the promoter of the monoamine oxidase A gene (MAOA-LPR) has previously been shown to be an important predictor of antisocial behavior in men. Testosterone analogues are known to interact with the MAOA promoter in vitro to influence gene transcription as well as in vivo to influence CSF levels of the MAO metabolite 3-methoxy-4-hydroxyphenylglycol (MHPG) in human males. We examined the possible joint effects of testosterone (measured in CSF) and MAOA-LPR genotype on antisocial personality disorder and scores on the Brown-Goodwin Aggression scale in 95 unrelated male criminal alcoholics and 45 controls. The results confirm that MAOA genotype and CSF testosterone interact to predict antisocial behaviors. The MAOA/testosterone interaction also predicted low levels of CSF MHPG, which tentatively suggests the possibility that the interaction may be mediated by a direct effect on gene transcription. If replicated these findings offer plausible explanations for previous inconsistencies in studies of the relationship between testosterone and male human aggression, as well as for how MAOA genotype may influence aggressive behavior in human males. PMID:17429405

  8. Unraveling the Fundamental Mechanisms of Solvent-Additive-Induced Optimization of Power Conversion Efficiencies in Organic Photovoltaic Devices.

    PubMed

    Herath, Nuradhika; Das, Sanjib; Zhu, Jiahua; Kumar, Rajeev; Chen, Jihua; Xiao, Kai; Gu, Gong; Browning, James F; Sumpter, Bobby G; Ivanov, Ilia N; Lauter, Valeria

    2016-08-10

    The realization of controllable morphologies of bulk heterojunctions (BHJ) in organic photovoltaics (OPVs) is one of the key factors enabling high-efficiency devices. We provide new insights into the fundamental mechanisms essential for the optimization of power conversion efficiencies (PCEs) with additive processing to PBDTTT-CF:PC71BM system. We have studied the underlying mechanisms by monitoring the 3D nanostructural modifications in BHJs and correlated the modifications with the optical analysis and theoretical modeling of charge transport. Our results demonstrate profound effects of diiodooctane (DIO) on morphology and charge transport in the active layers. For small amounts of DIO (<3 vol %), DIO promotes the formation of a well-mixed donor-acceptor compact film and augments charge transfer and PCE. In contrast, for large amounts of DIO (>3 vol %), DIO facilitates a loosely packed mixed morphology with large clusters of PC71BM, leading to deterioration in PCE. Theoretical modeling of charge transport reveals that DIO increases the mobility of electrons and holes (the charge carriers) by affecting the energetic disorder and electric field dependence of the mobility. Our findings show the implications of phase separation and carrier transport pathways to achieve optimal device performances. PMID:27403964

  9. Influences of Bi 2O 3 additive on the microstructure, permeability, and power loss characteristics of Ni-Zn ferrites

    NASA Astrophysics Data System (ADS)

    Su, Hua; Tang, Xiaoli; Zhang, Huaiwu; Jia, Lijun; Zhong, Zhiyong

    2009-10-01

    Nickel-zinc ferrite materials containing different Bi 2O 3 concentrations have been prepared by the conventional ceramic technique. Micrographs have clearly revealed that the Bi 2O 3 additive promoted grain growth. When the Bi 2O 3 content reached 0.15 wt%, a dual microstructure with both small grains (<5 μm) and some extremely large grains (>50 μm) appeared. With higher Bi 2O 3 content, the samples exhibited a very large average grain size of more than 30 μm. The initial permeability gradually decreased with increasing Bi 2O 3 content. When the Bi 2O 3 content exceeded 0.15 wt%, the permeability gradually decreased with frequency due to the low-frequency resonance induced by the large grain size. Neither the sintering density nor the saturation magnetization was obviously influenced by the Bi 2O 3 content or microstructure of the samples. However, power loss (Pcv) characteristics were evidently influenced. At low flux density, the sample with 0.10 wt% Bi 2O 3, which was characterized by an average grain size of 3-4 μm and few closed pores, displayed the lowest Pcv, irrespective of frequency. When the flux density was equal to or greater than the critical value of 40 mT, the sample with 0.20 wt% Bi 2O 3, which had the largest average grain size, displayed the lowest Pcv.

  10. Nitrogen oxides emissions from thermal power plants in china: current status and future predictions.

    PubMed

    Tian, Hezhong; Liu, Kaiyun; Hao, Jiming; Wang, Yan; Gao, Jiajia; Qiu, Peipei; Zhu, Chuanyong

    2013-10-01

    Increasing emissions of nitrogen oxides (NOx) over the Chinese mainland have been of great concern due to their adverse impacts on regional air quality and public health. To explore and obtain the temporal and spatial characteristics of NOx emissions from thermal power plants in China, a unit-based method is developed. The method assesses NOx emissions based on detailed information on unit capacity, boiler and burner patterns, feed fuel types, emission control technologies, and geographical locations. The national total NOx emissions in 2010 are estimated at 7801.6 kt, of which 5495.8 kt is released from coal-fired power plant units of considerable size between 300 and 1000 MW. The top provincial emitter is Shandong where plants are densely concentrated. The average NOx-intensity is estimated at 2.28 g/kWh, markedly higher than that of developed countries, mainly owing to the inadequate application of high-efficiency denitrification devices such as selective catalytic reduction (SCR). Future NOx emissions are predicted by applying scenario analysis, indicating that a reduction of about 40% by the year 2020 can be achieved compared with emissions in 2010. These results suggest that NOx emissions from Chinese thermal power plants could be substantially mitigated within 10 years if reasonable control measures were implemented effectively. PMID:24010996

  11. Does the singular value decomposition entropy have predictive power for stock market? - Evidence from the Shenzhen stock market

    NASA Astrophysics Data System (ADS)

    Gu, Rongbao; Xiong, Wei; Li, Xinjie

    2015-12-01

    This paper analyzes the predictive ability of the singular value decomposition entropy for the Shenzhen Component Index based on different scales. It is found that, the predictive ability of the entropy for the index is affected by the width of moving time windows and the structural break in stock market. By moving time windows with one year, the predictive power of singular value decomposition entropy of Shenzhen stock market for its component index is found after the reform of non-tradable shares.

  12. Precision predictions for the primordial power spectra of scalar potential models of inflation

    NASA Astrophysics Data System (ADS)

    Brooker, D. J.; Tsamis, N. C.; Woodard, R. P.

    2016-02-01

    We exploit a new numerical technique for evaluating the tree order contributions to the primordial scalar and tensor power spectra for scalar potential models of inflation. Among other things we use the formalism to develop a good analytic approximation which goes beyond generalized slow roll expansions in that (1) it is not contaminated by the physically irrelevant phase, (2) its 0th order term is exact for the constant first slow roll parameter, and (3) the correction is multiplicative rather than additive. These features allow our formalism to capture at first order effects which are higher order in other expansions. Although this accuracy is not necessary to compare current data with any specific model, our method has a number of applications owing to the simpler representation it provides for the connection between the power spectra and the expansion history of a general model.

  13. Critically Assessing the Predictive Power of QSAR Models for Human Liver Microsomal Stability.

    PubMed

    Liu, Ruifeng; Schyman, Patric; Wallqvist, Anders

    2015-08-24

    To lower the possibility of late-stage failures in the drug development process, an up-front assessment of absorption, distribution, metabolism, elimination, and toxicity is commonly implemented through a battery of in silico and in vitro assays. As in vitro data is accumulated, in silico quantitative structure-activity relationship (QSAR) models can be trained and used to assess compounds even before they are synthesized. Even though it is generally recognized that QSAR model performance deteriorates over time, rigorous independent studies of model performance deterioration is typically hindered by the lack of publicly available large data sets of structurally diverse compounds. Here, we investigated predictive properties of QSAR models derived from an assembly of publicly available human liver microsomal (HLM) stability data using variable nearest neighbor (v-NN) and random forest (RF) methods. In particular, we evaluated the degree of time-dependent model performance deterioration. Our results show that when evaluated by 10-fold cross-validation with all available HLM data randomly distributed among 10 equal-sized validation groups, we achieved high-quality model performance from both machine-learning methods. However, when we developed HLM models based on when the data appeared and tried to predict data published later, we found that neither method produced predictive models and that their applicability was dramatically reduced. On the other hand, when a small percentage of randomly selected compounds from data published later were included in the training set, performance of both machine-learning methods improved significantly. The implication is that 1) QSAR model quality should be analyzed in a time-dependent manner to assess their true predictive power and 2) it is imperative to retrain models with any up-to-date experimental data to ensure maximum applicability. PMID:26170251

  14. Towards prediction of redistribution of fallout radiocesium on forested area discharged from Fukushima Nuclear Power Plant

    NASA Astrophysics Data System (ADS)

    Miura, Satoru; Aoyama, Michio; Ito, Eriko; Shichi, Koji; Takata, Daisuke; Masaya, Masumori; Sekiya, Nobuhito; Kobayashi, Natsuko; Takano, Naoto; Kaneko, Shinji; Tanoi, Keitaro; Nakanishi, Tomoko

    2015-04-01

    Redistribution of fallout 137Cs on forested area discharged from Fukushima Nuclear Power Plant (FNPP) is an issue of major concern for the people in Fukushima and its surrounding areas. To approach this question we investigated global fallout 137Cs (137Cs-GFO) from nuclear weapon tests in the atmosphere in the 1950s and 60s, and 137Cs distribution derived from FNPP (137Cs-FK) within the whole trees contaminated directly. We examined concentrations and amounts of 137Cs-GFO in surface soils (0-5, 5-15 and 15-30 cm in depth) of 3470 samples at 316 sites all over Japan, which were collected just before the accident of FNPP. We determined 137Cs-GFO activities by NaI well-type scintillation counter with its accuracy verified using measurements by a germanium detector. We divided 316 sampling sites into 10 groups separated by one longitudinal line and four transversal lines on the terrain of Japan islands, then analyzed rainfall and geomorphological effects on 137Cs-GFO inventories. In addition to this dataset, we collected three whole tree samples of 26 year-old Quercus serrata at a contaminated area by FNPP accident in April, 2014 and examined concentrations of 137Cs-FK of above- and belowground tree parts by a germanium detector. We estimated an average of 137Cs-GFO inventories of forest soils in Japan to be 1.7 ± 1.4 kBq m-2 as of 2008. 137Cs-GFO inventories varied largely from 0-7.9 kBq m-2 among the country and accumulated greater in the north-western part along the Sea of Japan side. We detected rainfall effect on 137Cs-GFO inventories, which were greater where winter rainfall was large. As for vertical distribution of 137Cs-GFO, 44% of 137Cs-GFO remained within the uppermost 5 cm of soil profiles whereas the rest of 56% existed in 5-30 cm in depth. This indicated that considerable downward migration of 137Cs-GFO has happened during these fifty years in forest soils in Japan. However, multiple linear regression analysis by geomorphological factors related to soil

  15. Sonochemical degradation of Coomassie Brilliant Blue: effect of frequency, power density, pH and various additives.

    PubMed

    Rayaroth, Manoj P; Aravind, Usha K; Aravindakumar, Charuvila T

    2015-01-01

    Coomassie Brilliant Blue (CBB), discharged mainly from textile industries, is an identified water pollutant. Ultrasound initiated degradation of organic pollutants is one among the promising techniques and forms part of the Advanced Oxidation Processes (AOPs). Ultrasonic degradation of CBB under different experimental conditions has been investigated in the present work. The effect of frequency (200 kHz, 350 kHz, 620 kHz and 1 MHz) and power density (3.5 W mL(-1), 9.8 W mL(-1) and 19.6 W mL(-1)) on the degradation profile was evaluated. The optimum performance was obtained at 350 kHz and 19.6 W mL(-1). Similar to other sonolytic degradation of organic pollutants, maximum degradation of CBB was observed under acidic pH. The degradation profile indicated a pseudo-first order kinetics. The addition of ferrous ion (1×10(-4) M), hydrogen peroxide (1×10(-4) M), and peroxodisulphate (1×10(-4) M) had a positive effect on the degradation efficiency. The influence of certain important NOM like SDS and humic acid on the sonolytic degradation of CBB was also investigated. Both the compounds suppress the degradation efficiency. LC-Q-TOF-MS was used to identify the stable intermediate products. Nearly 13 transformed products were identified during 10min of sonication using the optimized operational parameters. This product profile demonstrated that most of the products are formed mainly by the OH radical attack. On the basis of these results, a degradation mechanism is proposed. PMID:25222624

  16. Worldwide impact of aerosol's time scale on the predicted long-term concentrating solar power potential.

    PubMed

    Ruiz-Arias, Jose A; Gueymard, Christian A; Santos-Alamillos, Francisco J; Pozo-Vázquez, David

    2016-01-01

    Concentrating solar technologies, which are fuelled by the direct normal component of solar irradiance (DNI), are among the most promising solar technologies. Currently, the state-of the-art methods for DNI evaluation use datasets of aerosol optical depth (AOD) with only coarse (typically monthly) temporal resolution. Using daily AOD data from both site-specific observations at ground stations as well as gridded model estimates, a methodology is developed to evaluate how the calculated long-term DNI resource is affected by using AOD data averaged over periods from 1 to 30 days. It is demonstrated here that the use of monthly representations of AOD leads to systematic underestimations of the predicted long-term DNI up to 10% in some areas with high solar resource, which may result in detrimental consequences for the bankability of concentrating solar power projects. Recommendations for the use of either daily or monthly AOD data are provided on a geographical basis. PMID:27507711

  17. Intelligent Prediction of Fan Rotation Stall in Power Plants Based on Pressure Sensor Data Measured In-Situ

    PubMed Central

    Xu, Xiaogang; Wang, Songling; Liu, Jinlian; Liu, Xinyu

    2014-01-01

    Blower and exhaust fans consume over 30% of electricity in a thermal power plant, and faults of these fans due to rotation stalls are one of the most frequent reasons for power plant outage failures. To accurately predict the occurrence of fan rotation stalls, we propose a support vector regression machine (SVRM) model that predicts the fan internal pressures during operation, leaving ample time for rotation stall detection. We train the SVRM model using experimental data samples, and perform pressure data prediction using the trained SVRM model. To prove the feasibility of using the SVRM model for rotation stall prediction, we further process the predicted pressure data via wavelet-transform-based stall detection. By comparison of the detection results from the predicted and measured pressure data, we demonstrate that the SVRM model can accurately predict the fan pressure and guarantee reliable stall detection with a time advance of up to 0.0625 s. This superior pressure data prediction capability leaves significant time for effective control and prevention of fan rotation stall faults. This model has great potential for use in intelligent fan systems with stall prevention capability, which will ensure safe operation and improve the energy efficiency of power plants. PMID:24854057

  18. Predictive Power of Air Travel and Socio-Economic Data for Early Pandemic Spread

    PubMed Central

    Hosseini, Parviez; Sokolow, Susanne H.; Vandegrift, Kurt J.; Kilpatrick, A. Marm; Daszak, Peter

    2010-01-01

    Background Controlling the pandemic spread of newly emerging diseases requires rapid, targeted allocation of limited resources among nations. Critical, early control steps would be greatly enhanced if the key risk factors can be identified that accurately predict early disease spread immediately after emergence. Methodology/Principal Findings Here, we examine the role of travel, trade, and national healthcare resources in predicting the emergence and initial spread of 2009 A/H1N1 influenza. We find that incorporating national healthcare resource data into our analyses allowed a much greater capacity to predict the international spread of this virus. In countries with lower healthcare resources, the reporting of 2009 A/H1N1 cases was significantly delayed, likely reflecting a lower capacity for testing and reporting, as well as other socio-political issues. We also report substantial international trade in live swine and poultry in the decade preceding the pandemic which may have contributed to the emergence and mixed genotype of this pandemic strain. However, the lack of knowledge of recent evolution of each H1N1 viral gene segment precludes the use of this approach to determine viral origins. Conclusions/Significance We conclude that strategies to prevent pandemic influenza virus emergence and spread in the future should include: 1) enhanced surveillance for strains resulting from reassortment in traded livestock; 2) rapid deployment of control measures in the initial spreading phase to countries where travel data predict the pathogen will reach and to countries where lower healthcare resources will likely cause delays in reporting. Our results highlight the benefits, for all parties, when higher income countries provide additional healthcare resources for lower income countries, particularly those that have high air traffic volumes. In particular, international authorities should prioritize aid to those poorest countries where both the risk of emerging infectious

  19. The Power of Implicit Social Relation in Rating Prediction of Social Recommender Systems

    PubMed Central

    Reafee, Waleed; Salim, Naomie; Khan, Atif

    2016-01-01

    The explosive growth of social networks in recent times has presented a powerful source of information to be utilized as an extra source for assisting in the social recommendation problems. The social recommendation methods that are based on probabilistic matrix factorization improved the recommendation accuracy and partly solved the cold-start and data sparsity problems. However, these methods only exploited the explicit social relations and almost completely ignored the implicit social relations. In this article, we firstly propose an algorithm to extract the implicit relation in the undirected graphs of social networks by exploiting the link prediction techniques. Furthermore, we propose a new probabilistic matrix factorization method to alleviate the data sparsity problem through incorporating explicit friendship and implicit friendship. We evaluate our proposed approach on two real datasets, Last.Fm and Douban. The experimental results show that our method performs much better than the state-of-the-art approaches, which indicates the importance of incorporating implicit social relations in the recommendation process to address the poor prediction accuracy. PMID:27152663

  20. LVP modeling and dynamic characteristics prediction of a hydraulic power unit in deep-sea

    NASA Astrophysics Data System (ADS)

    Cao, Xue-peng; Ye, Min; Deng, Bin; Zhang, Cui-hong; Yu, Zu-ying

    2013-03-01

    A hydraulic power unit (HPU) is the driving "heart" of deep-sea working equipment. It is critical to predict its dynamic performances in deep-water before being immerged in the seawater, while the experimental tests by simulating deep-sea environment have many disadvantages, such as expensive cost, long test cycles, and difficult to achieve low-temperature simulation, which is only used as a supplementary means for confirmatory experiment. This paper proposes a novel theoretical approach based on the linear varying parameters (LVP) modeling to foresee the dynamic performances of the driving unit. Firstly, based on the varying environment features, dynamic expressions of the compressibility and viscosity of hydraulic oil are derived to reveal the fluid performances changing. Secondly, models of hydraulic system and electrical system are accomplished respectively through studying the control process and energy transfer, and then LVP models of the pressure and flow rate control is obtained through the electro-hydraulic models integration. Thirdly, dynamic characteristics of HPU are obtained by the model simulating within bounded closed sets of varying parameters. Finally, the developed HPU is tested in a deep-sea imitating hull, and the experimental results are well consistent with the theoretical analysis outcomes, which clearly declare that the LVP modeling is a rational way to foresee dynamic performances of HPU. The research approach and model analysis results can be applied to the predictions of working properties and product designs for other deep-sea hydraulic pump.

  1. Heat Transfer Measurements and Predictions on a Power Generation Gas Turbine Blade

    NASA Technical Reports Server (NTRS)

    Giel, Paul W.; Bunker, Ronald S.; VanFossen, G. James; Boyle, Robert J.

    2000-01-01

    Detailed heat transfer measurements and predictions are given for a power generation turbine rotor with 129 deg of nominal turning and an axial chord of 137 mm. Data were obtained for a set of four exit Reynolds numbers comprised of the design point of 628,000, -20%, +20%, and +40%. Three ideal exit pressure ratios were examined including the design point of 1.378, -10%, and +10%. Inlet incidence angles of 0 deg and +/-2 deg were also examined. Measurements were made in a linear cascade with highly three-dimensional blade passage flows that resulted from the high flow turning and thick inlet boundary layers. Inlet turbulence was generated with a blown square bar grid. The purpose of the work is the extension of three-dimensional predictive modeling capability for airfoil external heat transfer to engine specific conditions including blade shape, Reynolds numbers, and Mach numbers. Data were obtained by a steady-state technique using a thin-foil heater wrapped around a low thermal conductivity blade. Surface temperatures were measured using calibrated liquid crystals. The results show the effects of strong secondary vortical flows, laminar-to-turbulent transition, and also show good detail in the stagnation region.

  2. The Power of Implicit Social Relation in Rating Prediction of Social Recommender Systems.

    PubMed

    Reafee, Waleed; Salim, Naomie; Khan, Atif

    2016-01-01

    The explosive growth of social networks in recent times has presented a powerful source of information to be utilized as an extra source for assisting in the social recommendation problems. The social recommendation methods that are based on probabilistic matrix factorization improved the recommendation accuracy and partly solved the cold-start and data sparsity problems. However, these methods only exploited the explicit social relations and almost completely ignored the implicit social relations. In this article, we firstly propose an algorithm to extract the implicit relation in the undirected graphs of social networks by exploiting the link prediction techniques. Furthermore, we propose a new probabilistic matrix factorization method to alleviate the data sparsity problem through incorporating explicit friendship and implicit friendship. We evaluate our proposed approach on two real datasets, Last.Fm and Douban. The experimental results show that our method performs much better than the state-of-the-art approaches, which indicates the importance of incorporating implicit social relations in the recommendation process to address the poor prediction accuracy. PMID:27152663

  3. Past as Prediction: Newcomb, Huxley, The Eclipse of Thales, and The Power of Science

    NASA Astrophysics Data System (ADS)

    Stanley, Matthew

    2009-12-01

    The ancient eclipse of Thales was an important, if peculiar, focus of scientific attention in the 19th century. Victorian-era astronomers first used it as data with which to calibrate their lunar theories, but its status became strangely malleable as the century progressed. The American astronomer Simon Newcomb re-examined the eclipse and rejected it as the basis for lunar theory. But strangely, it was the unprecedented accuracy of Newcomb's calculations that led the British biologist T.H. Huxley to declare the eclipse to be the quintessential example of the power of science. Huxley argued that astronomy's ability to create "retrospective prophecy” showed how scientific reasoning was superior to religion (and incidentally, helped support Darwin's theories). Both Newcomb and Huxley declared that prediction (of past and future) was what gave science its persuasive power. The eclipse of Thales's strange journey through Victorian astronomy reveals how these two influential scientists made the case for the social and cultural authority of science.

  4. Pre-stimulus beta and gamma oscillatory power predicts perceived audiovisual simultaneity.

    PubMed

    Yuan, Xiangyong; Li, Haijiang; Liu, Peiduo; Yuan, Hong; Huang, Xiting

    2016-09-01

    Pre-stimulus oscillation activity in the brain continuously fluctuates, but it is correlated with subsequent behavioral and perceptual performance. Here, using fast Fourier transformation of pre-stimulus electroencephalograms, we explored how oscillatory power modulates the subsequent discrimination of perceived simultaneity from non-simultaneity in the audiovisual domain. We found that the over-scalp high beta (20-28Hz), parieto-occipital low beta (14-20Hz), and high gamma oscillations (55-80Hz) were significantly stronger before audition-then-vision sequence when they were judged as simultaneous rather than non-simultaneous. In contrast, a broad range of oscillations, mainly the beta and gamma bands over a great part of the scalp were significantly weaker before vision-then-audition sequences when they were judged as simultaneous versus non-simultaneous. Moreover, for auditory-leading sequence, pre-stimulus beta and gamma oscillatory power successfully predicted subjects' reports of simultaneity on a trial-by-trial basis, with stronger activity resulting in more simultaneous judgments. These results indicate that ongoing fluctuations of beta and gamma oscillations can modulate subsequent perceived audiovisual simultaneity, but with an opposing pattern for auditory- and visual-leading sequences. PMID:27393081

  5. Noise Certification Predictions for FJX-2-Powered Aircraft Using Analytic Methods

    NASA Technical Reports Server (NTRS)

    Berton, Jeffrey J.

    1999-01-01

    Williams International Co. is currently developing the 700-pound thrust class FJX-2 turbofan engine for the general Aviation Propulsion Program's Turbine Engine Element. As part of the 1996 NASA-Williams cooperative working agreement, NASA agreed to analytically calculate the noise certification levels of the FJX-2-powered V-Jet II test bed aircraft. Although the V-Jet II is a demonstration aircraft that is unlikely to be produced and certified, the noise results presented here may be considered to be representative of the noise levels of small, general aviation jet aircraft that the FJX-2 would power. A single engine variant of the V-Jet II, the V-Jet I concept airplane, is also considered. Reported in this paper are the analytically predicted FJX-2/V-Jet noise levels appropriate for Federal Aviation Regulation certification. Also reported are FJX-2/V-Jet noise levels using noise metrics appropriate for the propeller-driven aircraft that will be its major market competition, as well as a sensitivity analysis of the certification noise levels to major system uncertainties.

  6. Predictability of Intraocular Lens Power Calculation After Simultaneous Pterygium Excision and Cataract Surgery.

    PubMed

    Kamiya, Kazutaka; Shimizu, Kimiya; Iijima, Kei; Shoji, Nobuyuki; Kobashi, Hidenaga

    2015-12-01

    This study was aimed to assess the predictability of intraocular lens (IOL) power calculation after simultaneous pterygium excision and phacoemulsification with IOL implantation. We retrospectively reviewed the clinical charts of 60 eyes of 60 consecutive patients (mean age ± standard deviation, 73.5 ± 7.0 years) who developed pterygium and cataract. We determined visual acuity (logMAR), manifest spherical equivalent, manifest astigmatism, corneal astigmatism, and mean keratometry, preoperatively and 3 months postoperatively. Corrected visual acuity was significantly improved from 0.19 ± 0.20 preoperatively to -0.06 ± 0.07 postoperatively (P < 0.001, Wilcoxon signed-rank test). Uncorrected visual acuity was also significantly improved from 0.62 ± 0.33 preoperatively to 0.31 ± 0.32 postoperatively (P < 0.001). At 3 months, 48% and 82% of the eyes were within ± 0.5 and ± 1.0 D, respectively, of the targeted correction. We found significant correlations of the prediction errors with the changes in the mean keratometry (Spearman signed-rank test, r = -0.535, P < 0.001) and with the pterygium size (r = -0.378, P = 0.033). Simultaneous pterygium and cataract surgery was safe and effective, and the accuracy was moderately predictable. However, it should be noted that a significant myopic shift occurred postoperatively, possibly resulting from the steepening of the cornea after pterygium removal, especially when the size of pterygium was large. PMID:26717362

  7. Contribution of Upper-Body Strength, Body Composition, and Maximal Oxygen Uptake to Predict Double Poling Power and Overall Performance in Female Cross-Country Skiers.

    PubMed

    Østerås, Sindre; Welde, Boye; Danielsen, Jørgen; van den Tillaar, Roland; Ettema, Gertjan; Sandbakk, Øyvind

    2016-09-01

    Østerås, S, Welde, B, Danielsen, J, van den Tillaar, R, Ettema, G, and Sandbakk, Ø. Contribution of upper-body strength, body composition, and maximal oxygen uptake to predict double poling power and overall performance in female cross-country skiers. J Strength Cond Res 30(9): 2557-2564, 2016-Maximal oxygen uptake (V[Combining Dot Above]O2max) is regarded as the most performance-differentiating physiological measure in cross-country (XC) skiing. In addition, upper-body strength and lean mass have been associated with double poling (DP) power in XC skiers. In this study, we tested upper-body maximal strength, lean mass, and V[Combining Dot Above]O2max's contributions to predict DP power production of different durations and the overall XC skiing performance level of elite female XC skiers. Thirteen skiers (V[Combining Dot Above]O2max: 64.9 ± 4.2 ml·kg·min) performed one 30-second and one 3-minute DP performance test using a ski ergometer. The International Ski Federation's (FIS) ranking points determined their overall XC skiing performance. The skiers performed three 1-repetition maximal strength tests in poling-specific exercises that isolated the elbow extension, shoulder extension, and trunk flexion movements. Body composition was determined by a DXA scan, and V[Combining Dot Above]O2max was tested in an incremental running test. Multiple regressions were used to predict power production in the 30-second and 3-minute tests and FIS points. The 2 best predictions of 30-second DP power were lean upper-body mass and maximal upper-body strength (with the 3 strength tests normalized and pooled together as one variable) (R = 0.84 and 0.81, p < 0.001). Along with V[Combining Dot Above]O2max, the same 2 variables were the best predictions of both 3-minute DP power (R = 0.60 and 0.44, p ≤ 0.05) and overall XC skiing performance (R = 0.43 and 0.40, p ≤ 0.05). Although the importance of upper-body strength and lean mass to predict DP power production and the

  8. Anti-androgens act jointly in suppressing spiggin concentrations in androgen-primed female three-spined sticklebacks - prediction of combined effects by concentration addition.

    PubMed

    Pottinger, T G; Katsiadaki, I; Jolly, C; Sanders, M; Mayer, I; Scott, A P; Morris, S; Kortenkamp, A; Scholze, M

    2013-09-15

    Increasing attention is being directed at the role played by anti-androgenic chemicals in endocrine disruption of wildlife within the aquatic environment. The co-occurrence of multiple contaminants with anti-androgenic activity highlights a need for the predictive assessment of combined effects, but information about anti-androgen mixture effects on wildlife is lacking. This study evaluated the suitability of the androgenised female stickleback screen (AFSS), in which inhibition of androgen-induced spiggin production provides a quantitative assessment of anti-androgenic activity, for predicting the effect of a four component mixture of anti-androgens. The anti-androgenic activity of four known anti-androgens (vinclozolin, fenitrothion, flutamide, linuron) was evaluated from individual concentration-response data and used to design a mixture containing each chemical at equipotent concentrations. Across a 100-fold concentration range, a concentration addition approach was used to predict the response of fish to the mixture. Two studies were conducted independently at each of two laboratories. By using a novel method to adjust for differences between nominal and measured concentrations, good agreement was obtained between the actual outcome of the mixture exposure and the predicted outcome. This demonstrated for the first time that androgen receptor antagonists act in concert in an additive fashion in fish and that existing mixture methodology is effective in predicting the outcome, based on concentration-response data for individual chemicals. The sensitivity range of the AFSS assay lies within the range of anti-androgenicity reported in rivers across many locations internationally. The approach taken in our study lays the foundations for understanding how androgen receptor antagonists work together in fish and is essential in informing risk assessment methods for complex anti-androgenic mixtures in the aquatic environment. PMID:23792627

  9. Energy Supply Characteristics of a Combined Solar Cell and Diesel Engine System with a Prediction Algorithm for Solar Power Generation

    NASA Astrophysics Data System (ADS)

    El-Sayed, Abeer Galal; Obara, Shin'ya

    The production of electricity from the solar cells continues to attract interest as a power source for distributed energy generation. It is important to be able to estimate solar cell power to optimize system energy management. This paper proposes a prediction algorithm based on a neural network (NN) to predict the electricity production from a solar cell. The operation plan for a combined solar cell and diesel engine generator system is examined using the NN prediction algorithm. Two systems are examined in this paper: one with and one without a power storage facility. Comparisons are presented of the results from the two systems with respect to the actual calculations of output power and the predicted electricity production from the solar cell. The exhaust heat from the engine is used to supply the heat demand. A back-up boiler is operated when the engine exhaust heat is insufficient to meet the heat demand. Electricity and heat are supplied to the demand side from the proposed systems, and no external sources are used. When the NN production-of-electricity prediction was introduced, the engine generator operating time was reduced by 12.5% in December and 16.7% for March and September. Moreover, an operation plan for the combined system exhaust heat is proposed, and the heat output characteristics of the back-up boiler are characterized.

  10. Cognitive training with and without additional physical activity in healthy older adults: cognitive effects, neurobiological mechanisms, and prediction of training success

    PubMed Central

    Rahe, Julia; Becker, Jutta; Fink, Gereon R.; Kessler, Josef; Kukolja, Juraj; Rahn, Andreas; Rosen, Jan B.; Szabados, Florian; Wirth, Brunhilde; Kalbe, Elke

    2015-01-01

    Data is inconsistent concerning the question whether cognitive-physical training (CPT) yields stronger cognitive gains than cognitive training (CT). Effects of additional counseling, neurobiological mechanisms, and predictors have scarcely been studied. Healthy older adults were trained with CT (n = 20), CPT (n = 25), or CPT with counseling (CPT+C; n = 23). Cognition, physical fitness, BDNF, IGF-1, and VEGF were assessed at pre- and post-test. No interaction effects were found except for one effect showing that CPT+C led to stronger gains in verbal fluency than CPT (p = 0.03). However, this superiority could not be assigned to additional physical training gains. Low baseline cognitive performance and BDNF, not carrying apoE4, gains in physical fitness and the moderation of gains in physical fitness × gains in BDNF predicted training success. Although all types of interventions seem successful to enhance cognition, our data do not support the hypotheses that CPT shows superior CT gains compared to CT or that CPT+C adds merit to CPT. However, as CPT leads to additional gains in physical fitness which in turn is known to have positive impact on cognition in the long-term, CPT seems more beneficial. Training success can partly be predicted by neuropsychological, neurobiological, and genetic parameters. Unique Identifier: WHO ICTRP (http://www.who.int/ictrp); ID: DRKS00005194. PMID:26528177

  11. RESIDUAL OXIDANTS REMOVAL FROM COASTAL POWER PLANT COOLING SYSTEM DISCHARGES: FIELD EVALUATION OF SO2 ADDITION SYSTEM

    EPA Science Inventory

    The report gives results of an evaluation of the performance of a dechlorination system that uses SO2 to remove residual oxidants from chlorinated sea water in a power plant cooling system. Samples of unchlorinated, chlorinated, and dechlorinated cooling water were obtained at Pa...

  12. Predicting tree species presence and basal area in Utah: A comparison of stochastic gradient boosting, generalized additive models, and tree-based methods

    USGS Publications Warehouse

    Moisen, G.G.; Freeman, E.A.; Blackard, J.A.; Frescino, T.S.; Zimmermann, N.E.; Edwards, T.C., Jr.

    2006-01-01

    Many efforts are underway to produce broad-scale forest attribute maps by modelling forest class and structure variables collected in forest inventories as functions of satellite-based and biophysical information. Typically, variants of classification and regression trees implemented in Rulequest's?? See5 and Cubist (for binary and continuous responses, respectively) are the tools of choice in many of these applications. These tools are widely used in large remote sensing applications, but are not easily interpretable, do not have ties with survey estimation methods, and use proprietary unpublished algorithms. Consequently, three alternative modelling techniques were compared for mapping presence and basal area of 13 species located in the mountain ranges of Utah, USA. The modelling techniques compared included the widely used See5/Cubist, generalized additive models (GAMs), and stochastic gradient boosting (SGB). Model performance was evaluated using independent test data sets. Evaluation criteria for mapping species presence included specificity, sensitivity, Kappa, and area under the curve (AUC). Evaluation criteria for the continuous basal area variables included correlation and relative mean squared error. For predicting species presence (setting thresholds to maximize Kappa), SGB had higher values for the majority of the species for specificity and Kappa, while GAMs had higher values for the majority of the species for sensitivity. In evaluating resultant AUC values, GAM and/or SGB models had significantly better results than the See5 models where significant differences could be detected between models. For nine out of 13 species, basal area prediction results for all modelling techniques were poor (correlations less than 0.5 and relative mean squared errors greater than 0.8), but SGB provided the most stable predictions in these instances. SGB and Cubist performed equally well for modelling basal area for three species with moderate prediction success

  13. A Risk Score with Additional Four Independent Factors to Predict the Incidence and Recovery from Metabolic Syndrome: Development and Validation in Large Japanese Cohorts

    PubMed Central

    Obokata, Masaru; Negishi, Kazuaki; Ohyama, Yoshiaki; Okada, Haruka; Imai, Kunihiko; Kurabayashi, Masahiko

    2015-01-01

    Background Although many risk factors for Metabolic syndrome (MetS) have been reported, there is no clinical score that predicts its incidence. The purposes of this study were to create and validate a risk score for predicting both incidence and recovery from MetS in a large cohort. Methods Subjects without MetS at enrollment (n = 13,634) were randomly divided into 2 groups and followed to record incidence of MetS. We also examined recovery from it in rest 2,743 individuals with prevalent MetS. Results During median follow-up of 3.0 years, 878 subjects in the derivation and 757 in validation cohorts developed MetS. Multiple logistic regression analysis identified 12 independent variables from the derivation cohort and initial score for subsequent MetS was created, which showed good discrimination both in the derivation (c-statistics 0.82) and validation cohorts (0.83). The predictability of the initial score for recovery from MetS was tested in the 2,743 MetS population (906 subjects recovered from MetS), where nine variables (including age, sex, γ-glutamyl transpeptidase, uric acid and five MetS diagnostic criteria constituents.) remained significant. Then, the final score was created using the nine variables. This score significantly predicted both the recovery from MetS (c-statistics 0.70, p<0.001, 78% sensitivity and 54% specificity) and incident MetS (c-statistics 0.80) with an incremental discriminative ability over the model derived from five factors used in the diagnosis of MetS (continuous net reclassification improvement: 0.35, p < 0.001 and integrated discrimination improvement: 0.01, p<0.001). Conclusions We identified four additional independent risk factors associated with subsequent MetS, developed and validated a risk score to predict both incident and recovery from MetS. PMID:26230621

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  15. Reinforcement learning versus model predictive control: a comparison on a power system problem.

    PubMed

    Ernst, Damien; Glavic, Mevludin; Capitanescu, Florin; Wehenkel, Louis

    2009-04-01

    This paper compares reinforcement learning (RL) with model predictive control (MPC) in a unified framework and reports experimental results of their application to the synthesis of a controller for a nonlinear and deterministic electrical power oscillations damping problem. Both families of methods are based on the formulation of the control problem as a discrete-time optimal control problem. The considered MPC approach exploits an analytical model of the system dynamics and cost function and computes open-loop policies by applying an interior-point solver to a minimization problem in which the system dynamics are represented by equality constraints. The considered RL approach infers in a model-free way closed-loop policies from a set of system trajectories and instantaneous cost values by solving a sequence of batch-mode supervised learning problems. The results obtained provide insight into the pros and cons of the two approaches and show that RL may certainly be competitive with MPC even in contexts where a good deterministic system model is available. PMID:19095542

  16. Genetic variation and prediction of additive and nonadditive genetic effects for six carcass traits in an Angus-Brahman multibreed herd.

    PubMed

    Elzo, M A; West, R L; Johnson, D D; Wakeman, D L

    1998-07-01

    Estimates of covariances and sire expected progeny differences of additive and nonadditive genetic effects for six carcass traits were obtained using records from 486 straightbred and crossbred steers from 121 sires born between 1989 and 1995 in the Angus-Brahman multibreed herd of the University of Florida. Steers were slaughtered at a similar carcass composition end point. Covariances were estimated by REML procedures, using a generalized expectation-maximization algorithm applied to multibreed populations. Straightbred and crossbred estimates of heritabilities and additive genetic correlations were within ranges found in the literature for steers slaughtered on an age- or weight-constant basis for hot carcass weight, longissimus muscle area, and shear force but equal to or less than the lower bound of these ranges for fat-related traits. Maximum values of interactibilities (i.e., ratios of nonadditive variances to phenotypic variances in the F1) and nonadditive genetic correlations were smaller than heritabilities and additive genetic correlations in straightbreds and crossbred groups. Sire additive and total direct genetic predictions for longissimus muscle area, marbling, and shear force tended to decrease with the fraction of Brahman alleles, whereas those for hot carcass weight and fat thickness over the longissimus were higher, and those for kidney fat were lower in straightbreds and F1 than in other crossbred groups. Nonadditive genetic predictions were similar across sire groups of all Angus and Brahman fractions. These results suggest that slaughtering steers on a similar carcass composition basis reduces variability of fat-related traits while retaining variability for non-fat-related traits comparable to slaughtering steers on a similar age or weight basis. Selection for carcass traits within desirable (narrow) ranges and slaughter of steers at similar compositional end point seems to be a good combination to help produce meat products of consistent

  17. Additive Manufacturing/Diagnostics via the High Frequency Induction Heating of Metal Powders: The Determination of the Power Transfer Factor for Fine Metallic Spheres

    SciTech Connect

    Rios, Orlando; Radhakrishnan, Balasubramaniam; Caravias, George; Holcomb, Matthew

    2015-03-11

    Grid Logic Inc. is developing a method for sintering and melting fine metallic powders for additive manufacturing using spatially-compact, high-frequency magnetic fields called Micro-Induction Sintering (MIS). One of the challenges in advancing MIS technology for additive manufacturing is in understanding the power transfer to the particles in a powder bed. This knowledge is important to achieving efficient power transfer, control, and selective particle heating during the MIS process needed for commercialization of the technology. The project s work provided a rigorous physics-based model for induction heating of fine spherical particles as a function of frequency and particle size. This simulation improved upon Grid Logic s earlier models and provides guidance that will make the MIS technology more effective. The project model will be incorporated into Grid Logic s power control circuit of the MIS 3D printer product and its diagnostics technology to optimize the sintering process for part quality and energy efficiency.

  18. Optimization of Acetylene Black Conductive Additive andPolyvinylidene Difluoride Composition for High Power RechargeableLithium-Ion Cells

    SciTech Connect

    Liu, G.; Zheng, H.; Battaglia, V.S.; Simens, A.S.; Minor, A.M.; Song, X.

    2007-07-01

    Fundamental electrochemical methods were applied to study the effect of the acetylene black (AB) and the polyvinylidene difluoride (PVDF) polymer binder on the performance of high-power designed rechargeable lithium ion cells. A systematic study of the AB/PVDF long-range electronic conductivity at different weight ratios is performed using four-probe direct current tests and the results reported. There is a wide range of AB/PVDF ratios that satisfy the long-range electronic conductivity requirement of the lithium-ion cathode electrode; however, a significant cell power performance improvement is observed at small AB/PVDF composition ratios that are far from the long-range conductivity optimum of 1 to 1.25. Electrochemical impedance spectroscopy (EIS) tests indicate that the interfacial impedance decreases significantly with increase in binder content. The hybrid power pulse characterization results agree with the EIS tests and also show improvement for cells with a high PVDF content. The AB to PVDF composition plays a significant role in the interfacial resistance. We believe the higher binder contents lead to a more cohesive conductive carbon particle network that results in better overall all local electronic conductivity on the active material surface and hence reduced charge transfer impedance.

  19. Predictive Power of Prospective Physical Education Teachers' Attitudes towards Educational Technologies for Their Technological Pedagogical Content Knowledge

    ERIC Educational Resources Information Center

    Varol, Yaprak Kalemoglu

    2015-01-01

    The aim of the research is to determine the predictive power of prospective physical education teachers' attitudes towards educational technologies for their technological pedagogical content knowledge. In this study, a relational research model was used on a study group that consisted of 529 (M[subscript age]=21.49, SD=1.44) prospective physical…

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

    ERIC Educational Resources Information Center

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

    2015-01-01

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

  1. Analysis of Academic Self-Efficacy, Self-Esteem and Coping with Stress Skills Predictive Power on Academic Procrastination

    ERIC Educational Resources Information Center

    Kandemir, Mehmet; Ilhan, Tahsin; Ozpolat, Ahmed Ragip; Palanci, Mehmet

    2014-01-01

    The goal of this research is to analyze the predictive power level of academic self-efficacy, self-esteem and coping with stress on academic procrastination behavior. Relational screening model is used in the research whose research group is made of 374 students in Kirikkale University, Education Faculty in Turkey. Students in the research group…

  2. Prediction-based optimal power management in a fuel cell/battery plug-in hybrid vehicle

    NASA Astrophysics Data System (ADS)

    Bubna, Piyush; Brunner, Doug; Advani, Suresh G.; Prasad, Ajay K.

    A prediction-based power management strategy is proposed for fuel cell/battery plug-in hybrid vehicles with the goal of improving overall system operating efficiency. The main feature of the proposed strategy is that, if the total amount of energy required to complete a particular drive cycle can be reliably predicted, then the energy stored in the onboard electrical storage system can be depleted in an optimal manner that permits the fuel cell to operate in its most efficient regime. The strategy has been implemented in a vehicle power-train simulator called LFM which was developed in MATLAB/SIMULINK software and its effectiveness was evaluated by comparing it with a conventional control strategy. The proposed strategy is shown to provide significant improvement in average fuel cell system efficiency while reducing hydrogen consumption. It has been demonstrated with the LFM simulation that the prediction-based power management strategy can maintain a stable power request to the fuel cell thereby improving fuel cell durability, and that the battery is depleted to the desired state-of-charge at the end of the drive cycle. A sensitivity analysis has also been conducted to study the effects of inaccurate predictions of the remaining portion of the drive cycle on hydrogen consumption and the final battery state-of-charge. Finally, the advantages of the proposed control strategy over the conventional strategy have been validated through implementation in the University of Delaware's fuel cell hybrid bus with operational data acquired from onboard sensors.

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

    ERIC Educational Resources Information Center

    Yuksel, Ismail; Toker, Yalcin

    2013-01-01

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

  4. Predicting the diffusion coefficient of water vapor through glassy HPMC films at different environmental conditions using the free volume additivity approach.

    PubMed

    Laksmana, Fesia Lestari; Hartman Kok, Paul Jean Antoine; Vromans, Herman; Van der Voort Maarschalk, Kees

    2009-07-12

    Prediction of diffusion coefficient of polymer materials is important in the pharmaceutical research and becomes the aim of this paper. This paper bases the prediction method on the estimation of the polymer fractional free volume at different environmental conditions. Focussing on glassy polymers, the free volumes of polymer films were estimated using the model of Vrentas et al. [J.S. Vrentas, J.L. Duda, H.-C. Ling, Antiplasticization and volumetric behavior in glassy polymers, Macromolecules 21 (1988) 1470-1475]. The required data are the moisture sorption and glass transition temperature data, which were measured on various hydroxypropyl methylcellulose (used as a model material) free films at different water activities. The temperature and molecular weight particularly determine the free volume of the polymer, while the sorbed water can either decrease or increase the specific free volume of the polymer. At high water activity, the amount of water sorbed in the film increases to such level that the direct free volume addition by water becomes proportional to the contribution of the polymer itself. This confirms the importance of considering the environmental effect on the diffusivity of polymer during coating material selection. The presented approach enables the prediction of the diffusivity at any given relevant material variable and therefore has the potency to be used as a formulation development tool. PMID:19409985

  5. Microstructure and properties of the low-power-laser clad coatings on magnesium alloy with different amount of rare earth addition

    NASA Astrophysics Data System (ADS)

    Zhu, Rundong; Li, Zhiyong; Li, Xiaoxi; Sun, Qi

    2015-10-01

    Due to the low-melting-point and high evaporation rate of magnesium at elevated temperature, high power laser clad coating on magnesium always causes subsidence and deterioration in the surface. Low power laser can reduce the evaporation effect while brings problems such as decreased thickness, incomplete fusion and unsatisfied performance. Therefore, low power laser with selected parameters was used in our research work to obtain Al-Cu coatings with Y2O3 addition on AZ91D magnesium alloy. The addition of Y2O3 obviously increases thickness of the coating and improves the melting efficiency. Furthermore, the effect of Y2O3 addition on the microstructure of laser clad Al-Cu coatings was investigated by scanning electron microscopy. The energy-dispersive spectrometer (EDS) and X-ray diffractometer (XRD) were used to examine the elemental and phase compositions of the coatings. The properties were investigated by micro-hardness test, dry wear test and electrochemical corrosion. It was found that the addition of Y2O3 refined the microstructure. The micro-hardness, abrasion resistance and corrosion resistance of the coatings was greatly improved compared with the magnesium matrix, especially for the Al-Cu coating with Y2O3 addition.

  6. Computation and Experiment: A Powerful Combination to Understand and Predict Reactivities.

    PubMed

    Sperger, Theresa; Sanhueza, Italo A; Schoenebeck, Franziska

    2016-06-21

    Computational chemistry has become an established tool for the study of the origins of chemical phenomena and examination of molecular properties. Because of major advances in theory, hardware and software, calculations of molecular processes can nowadays be done with reasonable accuracy on a time-scale that is competitive or even faster than experiments. This overview will highlight broad applications of computational chemistry in the study of organic and organometallic reactivities, including catalytic (NHC-, Cu-, Pd-, Ni-catalyzed) and noncatalytic examples of relevance to organic synthesis. The selected examples showcase the ability of computational chemistry to rationalize and also predict reactivities of broad significance. A particular emphasis is placed on the synergistic interplay of computations and experiments. It is discussed how this approach allows one to (i) gain greater insight than the isolated techniques, (ii) inspire novel chemistry avenues, and (iii) assist in reaction development. Examples of successful rationalizations of reactivities are discussed, including the elucidation of mechanistic features (radical versus polar) and origins of stereoselectivity in NHC-catalyzed reactions as well as the rationalization of ligand effects on ligation states and selectivity in Pd- and Ni-catalyzed transformations. Beyond explaining, the synergistic interplay of computation and experiments is then discussed, showcasing the identification of the likely catalytically active species as a function of ligand, additive, and solvent in Pd-catalyzed cross-coupling reactions. These may vary between mono- or bisphosphine-bound or even anionic Pd complexes in polar media in the presence of coordinating additives. These fundamental studies also inspired avenues in catalysis via dinuclear Pd(I) cycles. Detailed mechanistic studies supporting the direct reactivity of Pd(I)-Pd(I) with aryl halides as well as applications of air-stable dinuclear Pd(I) catalysts are

  7. Using Rényi parameter to improve the predictive power of singular value decomposition entropy on stock market

    NASA Astrophysics Data System (ADS)

    Jiang, Jiaqi; Gu, Rongbao

    2016-04-01

    This paper generalizes the method of traditional singular value decomposition entropy by incorporating orders q of Rényi entropy. We analyze the predictive power of the entropy based on trajectory matrix using Shanghai Composite Index and Dow Jones Index data in both static test and dynamic test. In the static test on SCI, results of global granger causality tests all turn out to be significant regardless of orders selected. But this entropy fails to show much predictability in American stock market. In the dynamic test, we find that the predictive power can be significantly improved in SCI by our generalized method but not in DJI. This suggests that noises and errors affect SCI more frequently than DJI. In the end, results obtained using different length of sliding window also corroborate this finding.

  8. Optimal power-to-mass ratios when predicting flat and hill-climbing time-trial cycling.

    PubMed

    Nevill, A M; Jobson, S A; Davison, R C R; Jeukendrup, A E

    2006-07-01

    The purpose of this article was to establish whether previously reported oxygen-to-mass ratios, used to predict flat and hill-climbing cycling performance, extend to similar power-to-mass ratios incorporating other, often quick and convenient measures of power output recorded in the laboratory [maximum aerobic power (W(MAP)), power output at ventilatory threshold (W(VT)) and average power output (W(AVG)) maintained during a 1 h performance test]. A proportional allometric model was used to predict the optimal power-to-mass ratios associated with cycling speeds during flat and hill-climbing cycling. The optimal models predicting flat time-trial cycling speeds were found to be (W(MAP)m(-0.48))(0.54), (W(VT)m(-0.48))(0.46) and (W(AVG)m(-0.34))(0.58) that explained 69.3, 59.1 and 96.3% of the variance in cycling speeds, respectively. Cross-validation results suggest that, in conjunction with body mass, W(MAP) can provide an accurate and independent prediction of time-trial cycling, explaining 94.6% of the variance in cycling speeds with the standard deviation about the regression line, s=0.686 km h(-1). Based on these models, there is evidence to support that previously reported VO2-to-mass ratios associated with flat cycling speed extend to other laboratory-recorded measures of power output (i.e. Wm(-0.32)). However, the power-function exponents (0.54, 0.46 and 0.58) would appear to conflict with the assumption that the cyclists' speeds should be proportional to the cube root (0.33) of power demand/expended, a finding that could be explained by other confounding variables such as bicycle geometry, tractional resistance and/or the presence of a tailwind. The models predicting 6 and 12% hill-climbing cycling speeds were found to be proportional to (W(MAP)m(-0.91))(0.66), revealing a mass exponent, 0.91, that also supports previous research. PMID:16685550

  9. Comparison of the predictive power of beef surface wavelet texture features at high and low magnification.

    PubMed

    Jackman, Patrick; Sun, Da-Wen; Allen, Paul

    2009-07-01

    Beef longissimus dorsi surface texture is an indicator used in predicting beef palatability by expert graders. Computer vision systems have previously used imaging at normal view to develop surface texture features with some success. Good models of beef overall acceptability using imaging at high magnification have been recently developed. As a comparison the same surface texture features were computed from the corresponding images at normal view and used to model overall acceptability. Both sets of texture features were also combined with muscle colour and marbling features and used to model overall acceptability. Models using texture features alone were more successful at normal modality. However colour and marbling features combined much better with texture features at high modality to yield the most accurate model of overall acceptability (r(2)=0.93). Accurate Partial Least Squares Regression (PLSR) models were computed at both modalities with and without inclusion of colour and marbling features. Addition of squared terms to the models failed to improve accuracy. PMID:20416713

  10. A method for predicting full scale buffet response with rigid wind tunnel model fluctuating pressure data. Volume 2: Power spectral densities for method assessment

    NASA Technical Reports Server (NTRS)

    Cunningham, A. M., Jr.; Benepe, D. B.; Watts, D.; Waner, P. G.

    1978-01-01

    The predicted upper and lower bounds power spectra for all of the cases and response items given in Volume 1 are plotted. The flight test power spectra are shown on each prediction plot for the nominal value of angle of attack that most closely agrees with the flexible angle for the prediction. The flight test and prediction conditions are given in tabular form for all cases considered.

  11. The predictive power of depression screening procedures for veterans with coronary artery disease

    PubMed Central

    Shankman, Stewart A; Nadelson, Jeffrey; McGowan, Sarah Kate; Sovari, Ali A; Vidovich, Mladen I

    2012-01-01

    Depression leads to a worse outcome for patients with coronary artery disease (CAD). Thus, accurately identifying depression in CAD patients is imperative. In many veterans affairs (VA) hospitals, patients are screened for depression once a year using the patient health questionnaire (PHQ-9). Although the PHQ-9 is generally considered a specific and sensitive measure of depression, there is reason to believe that these screening procedures may miss a large number of cases of depression within CAD patients and cardiology patients more generally. The goal of this study was to provide data as to the predictive power of this depression screening procedure by (a) comparing the prevalence rate of depression identified by the PHQ-9 to known prevalence rates and (b) examining whether patients identified as “depressed” also had conditions that consistently co-occur with depression (eg, post-traumatic stress disorder [PTSD], other medical issues). Participants were 813 consecutive patients who received an angiogram in the cardiac catheterization laboratory at a large VA Medical Center. Prevalence of depression was 6.9% in the overall sample and less than 6% when the sample was restricted to CAD patients with significant stenosis. Depression was significantly associated with PTSD, smoking, and alcohol problems. However, depression was not associated with other medical problems such as diabetes, renal failure, peripheral vascular disease, or anemia. In conclusion, the low prevalence rate of depression and lack of associations with comorbid medical problems may suggest that the VA’s depression screening procedures have low sensitivity for identifying depression in CAD patients. It is recommended that clinicians treating CAD regularly screen for depression and do not rely on archival depression screens. PMID:22566744

  12. Spontaneous Alpha Power Lateralization Predicts Detection Performance in an Un-Cued Signal Detection Task.

    PubMed

    Boncompte, Gonzalo; Villena-González, Mario; Cosmelli, Diego; López, Vladimir

    2016-01-01

    Focusing one's attention by external guiding stimuli towards a specific area of the visual field produces systematical neural signatures. One of the most robust is the change in topological distribution of oscillatory alpha band activity across parieto-occipital cortices. In particular, decreases in alpha activity over contralateral and/or increases over ipsilateral scalp sites, respect to the side of the visual field where attention was focused. This evidence comes mainly from experiments where an explicit cue informs subjects where to focus their attention, thus facilitating detection of an upcoming target stimulus. However, recent theoretical models of attention have highlighted a stochastic or non-deterministic component related to visuospatial attentional allocation. In an attempt to evidence this component, here we analyzed alpha activity in a signal detection paradigm in the lack of informative cues; in the absence of preceding information about the location (and time) of appearance of target stimuli. We believe that the unpredictability of this situation could be beneficial for unveiling this component. Interestingly, although total alpha power did not differ between Seen and Unseen conditions, we found a significant lateralization of alpha activity over parieto-occipital electrodes, which predicted behavioral performance. This effect had a smaller magnitude compared to paradigms in which attention is externally guided (cued). However we believe that further characterization of this spontaneous component of attention is of great importance in the study of visuospatial attentional dynamics. These results support the presence of a spontaneous component of visuospatial attentional allocation and they advance pre-stimulus alpha-band lateralization as one of its neural signatures. PMID:27504824

  13. Spontaneous Alpha Power Lateralization Predicts Detection Performance in an Un-Cued Signal Detection Task

    PubMed Central

    Villena-González, Mario; Cosmelli, Diego; López, Vladimir

    2016-01-01

    Focusing one’s attention by external guiding stimuli towards a specific area of the visual field produces systematical neural signatures. One of the most robust is the change in topological distribution of oscillatory alpha band activity across parieto-occipital cortices. In particular, decreases in alpha activity over contralateral and/or increases over ipsilateral scalp sites, respect to the side of the visual field where attention was focused. This evidence comes mainly from experiments where an explicit cue informs subjects where to focus their attention, thus facilitating detection of an upcoming target stimulus. However, recent theoretical models of attention have highlighted a stochastic or non-deterministic component related to visuospatial attentional allocation. In an attempt to evidence this component, here we analyzed alpha activity in a signal detection paradigm in the lack of informative cues; in the absence of preceding information about the location (and time) of appearance of target stimuli. We believe that the unpredictability of this situation could be beneficial for unveiling this component. Interestingly, although total alpha power did not differ between Seen and Unseen conditions, we found a significant lateralization of alpha activity over parieto-occipital electrodes, which predicted behavioral performance. This effect had a smaller magnitude compared to paradigms in which attention is externally guided (cued). However we believe that further characterization of this spontaneous component of attention is of great importance in the study of visuospatial attentional dynamics. These results support the presence of a spontaneous component of visuospatial attentional allocation and they advance pre-stimulus alpha-band lateralization as one of its neural signatures. PMID:27504824

  14. Predictability of Sirius dual-scanning corneal tomography in the measurement of corneal power after photorefractive surgery.

    PubMed

    Fouda, Sameh M; Al-Nashar, Haitham Y; Ibrahim, Basem M; Bor'i, Ashraf

    2016-02-01

    Determining an accurate central corneal power (K) measurement is crucial for calculating the intraocular lens power in patients who are undergoing cataract extraction. The ideal method for measuring K is to use a device that works independently of the refractive surgery information. The Scheimpflug camera system offers a promising means of measuring the true corneal power after keratorefractive surgery. In this study, we investigated the accuracy of this system in measuring central corneal power after photorefractive corneal surgery by comparing it to the theoretically derived central corneal power by history method. A total of 120 eyes of 65 (35 females and 30 males) patients were included in this study. The mean change of refraction at the spectacle plane was 3.75 D, whereas the mean change of refraction at the corneal plane was 3.37 D. Using the Sirius dual-scanning corneal tomography, the mean change in corneal power was 3.96 D. No significant differences were detected between the mean post-operative corneal power measured by the Sirius tomographer and the mean change in refraction at the corneal plane calculated clinically (P = 0.076) and the correlation was found to be high (0.913). This study suggests that Sirius dual-scanning corneal tomography offers high predictability when measuring the central 5 mm corneal power in patients who have had myopic corneal photorefractive surgery. PMID:25982158

  15. Background rhythm frequency and theta power of quantitative EEG analysis: predictive biomarkers for cognitive impairment post-cerebral infarcts.

    PubMed

    Song, Yang; Zang, Da-Wei; Jin, Yan-Yu; Wang, Zhi-Jun; Ni, Hong-Yan; Yin, Jian-Zhong; Ji, Dong-Xu

    2015-04-01

    In clinical settings, cerebral infarct is a common disease of older adults, which usually increases the risk of cognitive impairment. This study aims to assess the quantitative electroencephalography (qEEG) as a predictive biomarker for the development of cognitive impairment, post-cerebral infarcts, in subjects from the Department of Neurology. They underwent biennial EEG recording. Cerebral infarct subjects, with follow-up cognitive evaluation, were analyzed for qEEG measures of background rhythm frequency (BRF) and relative δ, θ, α, and β band power. The relationship between cognitive impairment and qEEG, and other possible predictors, was assessed by Cox regression. The results showed that the risk hazard of developing cognitive impairment was 14 times higher for those with low BRF than for those with high BRF (P < .001). Hazard ratio (HR) was also significant for more than median θ band power (HR = 5, P = .002) compared with less than median θ band power. The HRs for δ, α, and β bands were equal to the baseline demographic, and clinical characteristics were not significantly different. In conclusion, qEEG measures of BRF, and relative power in θ band, are potential predictive biomarkers for cognitive impairment in patients with cerebral infarcts. These biomarkers might be valuable in early prediction of cognitive impairment in patients with cerebral infarcts. PMID:24699438

  16. Development Report for Islanded System Automatic Synchronizer and Predictive Step Out Prevention Relay System using Power Flow Parameters

    NASA Astrophysics Data System (ADS)

    Yasuda, Tadaaki; Nishi, Tetsuya; Inukai, Michihiko; Miura, Shogo

    This is the development report for our new type relay systems, Islanded System Automatic Synchronizer (ISAS) and the predictive step out prevention relay system using power flow parameters. ISAS is a kind of device for self-healing. It performs emergency system re-synchronize operation automatically when the islanded system is separated from the main grid. TEPCO applied some ISAS devices in Tokyo metropolitan area and resulted that reliability in the area was much improved. The predictive step out prevention relay system mentioned above is a kind of special protection scheme, which predicts generator step out and calculates how much amount of generator should be tripped to stabilize the power system when the fault on the transmission lines is detected. A New predicteve step out calculation algorithm using power flow parameters was developped so that it can be applied for the complex power system. TEPCO applied the new relay system to the area where TEPCO's criteria was not satisfied due to transient instability problem and resulted that the stability was improved enough to meet TEPCO's criteria.

  17. Prediction error and accuracy of intraocular lens power calculation in pediatric patient comparing SRK II and Pediatric IOL Calculator

    PubMed Central

    2010-01-01

    Background Despite growing number of intraocular lens power calculation formulas, there is no evidence that these formulas have good predictive accuracy in pediatric, whose eyes are still undergoing rapid growth and refractive changes. This study is intended to compare the prediction error and the accuracy of predictability of intraocular lens power calculation in pediatric patients at 3 month post cataract surgery with primary implantation of an intraocular lens using SRK II versus Pediatric IOL Calculator for pediatric intraocular lens calculation. Pediatric IOL Calculator is a modification of SRK II using Holladay algorithm. This program attempts to predict the refraction of a pseudophakic child as he grows, using a Holladay algorithm model. This model is based on refraction measurements of pediatric aphakic eyes. Pediatric IOL Calculator uses computer software for intraocular lens calculation. Methods This comparative study consists of 31 eyes (24 patients) that successfully underwent cataract surgery and intraocular lens implantations. All patients were 12 years old and below (range: 4 months to 12 years old). Patients were randomized into 2 groups; SRK II group and Pediatric IOL Calculator group using envelope technique sampling procedure. Intraocular lens power calculations were made using either SRK II or Pediatric IOL Calculator for pediatric intraocular lens calculation based on the printed technique selected for every patient. Thirteen patients were assigned for SRK II group and another 11 patients for Pediatric IOL Calculator group. For SRK II group, the predicted postoperative refraction is based on the patient's axial length and is aimed for emmetropic at the time of surgery. However for Pediatric IOL Calculator group, the predicted postoperative refraction is aimed for emmetropic spherical equivalent at age 2 years old. The postoperative refractive outcome was taken as the spherical equivalent of the refraction at 3 month postoperative follow-up. The

  18. Higher TSH can be used as an additional risk factor in prediction of malignancy in euthyroid thyroid nodules evaluated by cytology based on Bethesda system.

    PubMed

    Baser, Husniye; Topaloglu, Oya; Tam, Abbas Ali; Evranos, Berna; Alkan, Afra; Sungu, Nuran; Dumlu, Ersin Gurkan; Ersoy, Reyhan; Cakir, Bekir

    2016-08-01

    Recently, it has been suggested that thyrotropin (TSH) concentration can be used as a marker for prediction of thyroid malignancy. In this study, we aimed to investigate the association between TSH levels and prediction of malignancy in euthyroid patients with different Bethesda categories. The data of 1433 euthyroid patients with 3206 thyroid nodules who underwent thyroidectomy were screened retrospectively. The preoperative cytology results, thyroid function tests, thyroid autoantibodies, and presence of histopathological Hashimoto's thyroiditis (HT) were recorded. Of the 1433 patients, 585 (40.8 %) had malignant and 848 (59.2 %) had benign histopathology. Malignant group had smaller nodule size, elevated TSH levels, and higher rate of presence of HT compared to benign group (p < 0.001, all). Cytology results of 3206 nodules were as follows: 832 nondiagnostic (ND), 1666 benign, 392 atypia of undetermined significance/follicular lesion of undetermined significance (AUS/FLUS), 68 follicular neoplasm/suspicious for follicular neoplasm (FN/SFN), 133 suspicious for malignancy (SM), and 115 malignant. Both SM and malignant cytology groups had higher TSH levels than other 4 Bethesda categories (p < 0.05, all). Benign cytology group had significantly lower TSH levels compared to other cytology groups (p < 0.05, all). Patients with malignant final histopathology in ND and AUS/FLUS cytology groups had significantly higher TSH levels compared to patients with benign final histopathology (p < 0.05, all). Moreover, TSH levels showed to increase from Bethesda categories II to VI. In addition to cytology, higher TSH levels can be used as a supplementary marker in prediction of malignancy in certain Bethesda categories. PMID:26972701

  19. Evaluating the predictive power of multivariate tensor-based morphometry in Alzheimer's disease progression via convex fused sparse group Lasso

    NASA Astrophysics Data System (ADS)

    Tsao, Sinchai; Gajawelli, Niharika; Zhou, Jiayu; Shi, Jie; Ye, Jieping; Wang, Yalin; Lepore, Natasha

    2014-03-01

    Prediction of Alzheimers disease (AD) progression based on baseline measures allows us to understand disease progression and has implications in decisions concerning treatment strategy. To this end we combine a predictive multi-task machine learning method1 with novel MR-based multivariate morphometric surface map of the hippocampus2 to predict future cognitive scores of patients. Previous work by Zhou et al.1 has shown that a multi-task learning framework that performs prediction of all future time points (or tasks) simultaneously can be used to encode both sparsity as well as temporal smoothness. They showed that this can be used in predicting cognitive outcomes of Alzheimers Disease Neuroimaging Initiative (ADNI) subjects based on FreeSurfer-based baseline MRI features, MMSE score demographic information and ApoE status. Whilst volumetric information may hold generalized information on brain status, we hypothesized that hippocampus specific information may be more useful in predictive modeling of AD. To this end, we applied Shi et al.2s recently developed multivariate tensor-based (mTBM) parametric surface analysis method to extract features from the hippocampal surface. We show that by combining the power of the multi-task framework with the sensitivity of mTBM features of the hippocampus surface, we are able to improve significantly improve predictive performance of ADAS cognitive scores 6, 12, 24, 36 and 48 months from baseline.

  20. TNF-α Promoter Polymorphisms Predict the Response to Etanercept More Powerfully than that to Infliximab/Adalimumab in Spondyloarthritis.

    PubMed

    Liu, Jing; Dong, Zheng; Zhu, Qi; He, Dongyi; Ma, Yanyun; Du, Aiping; He, Fan; Zhao, Dongbao; Xu, Xia; Zhang, Hui; Jin, Li; Wang, Jiucun

    2016-01-01

    While previous studies have researched in association analyses between TNFα promoter polymorphisms and responses to TNF blockers in spondyloarthritis patients, their results were conflicting. Therefore, we aimed to determine whether TNFα promoter polymorphisms could predict response to TNF blockers and find the source of heterogeneity. Data were extracted and analyzed from published articles and combined with our unpublished data. We found that the greatest potential sources of heterogeneity in the results were gender ratio, disease type, continents, and TNF blockers. Then Stratification analysis showed that the TNFα -308 G allele and the -238 G allele predicted a good response to TNF blockers (OR = 2.64 [1.48-4.73]; 2.52 [1.46-4.37]). However, G alleles of TNFα -308 and -238 could predict the response to etanercept (OR = 4.02 [2.24-7.23]; 5.17 [2.29-11.67]) much more powerfully than the response to infiliximab/adalimumab (OR = 1.68 [1.02-2.78]; 1.28 [0.57-2.86]). TNFα -857 could not predict the response in either subgroup. Cumulative meta-analysis performed in ankylosing spondylitis patients presented the odds ratio decreased with stricter response criteria. In conclusion, TNFα -308 A/G and -238 A/G are more powerful to predict the response to Etanercept and it is dependent on the criteria of response. PMID:27578555

  1. Improving predictive power of physically based rainfall-induced shallow landslide models: a probablistic approach

    USGS Publications Warehouse

    Raia, S.; Alvioli, M.; Rossi, M.; Baum, R.L.; Godt, J.W.; Guzzetti, F.

    2013-01-01

    are analyzed statistically, and compared to the original (deterministic) model output. The comparison suggests an improvement of the predictive power of the model of about 10% and 16% in two small test areas, i.e. the Frontignano (Italy) and the Mukilteo (USA) areas, respectively. We discuss the computational requirements of TRIGRS-P to determine the potential use of the numerical model to forecast the spatial and temporal occurrence of rainfall-induced shallow landslides in very large areas, extending for several hundreds or thousands of square kilometers. Parallel execution of the code using a simple process distribution and the Message Passing Interface (MPI) on multi-processor machines was successful, opening the possibly of testing the use of TRIGRS-P for the operational forecasting of rainfall-induced shallow landslides over large regions.

  2. Improving predictive power of physically based rainfall-induced shallow landslide models: a probabilistic approach

    NASA Astrophysics Data System (ADS)

    Raia, S.; Alvioli, M.; Rossi, M.; Baum, R. L.; Godt, J. W.; Guzzetti, F.

    2014-03-01

    runs obtained varying the input parameters are analyzed statistically, and compared to the original (deterministic) model output. The comparison suggests an improvement of the predictive power of the model of about 10% and 16% in two small test areas, that is, the Frontignano (Italy) and the Mukilteo (USA) areas. We discuss the computational requirements of TRIGRS-P to determine the potential use of the numerical model to forecast the spatial and temporal occurrence of rainfall-induced shallow landslides in very large areas, extending for several hundreds or thousands of square kilometers. Parallel execution of the code using a simple process distribution and the message passing interface (MPI) on multi-processor machines was successful, opening the possibly of testing the use of TRIGRS-P for the operational forecasting of rainfall-induced shallow landslides over large regions.

  3. Subjective Career Success and Emotional Well-Being: Longitudinal Predictive Power of Selection, Optimization, and Compensation.

    ERIC Educational Resources Information Center

    Wiese, Bettina S.; Freund, Alexandra M.; Baltes, Paul B.

    2002-01-01

    A 3-year study of 82 young professionals found that work-related well-being was predicted by selection (commitment to personal goals), optimization (application of goal-related skills), and compensation (maintaining goals in the face of loss). The degree of compensation predicted emotional well-being and job satisfaction 3 years later. (Contains…

  4. Model-Predictive Cascade Mitigation in Electric Power Systems With Storage and Renewables-Part I: Theory and Implementation

    SciTech Connect

    Almassalkhi, MR; Hiskens, IA

    2015-01-01

    A novel model predictive control (MPC) scheme is developed for mitigating the effects of severe line-overload disturbances in electrical power systems. A piece-wise linear convex approximation of line losses is employed to model the effect of transmission line power flow on conductor temperatures. Control is achieved through a receding-horizon model predictive control (MPC) strategy which alleviates line temperature overloads and thereby prevents the propagation of outages. The MPC strategy adjusts line flows by rescheduling generation, energy storage and controllable load, while taking into account ramp-rate limits and network limitations. In Part II of this paper, the MPC strategy is illustrated through simulation of the IEEE RTS-96 network, augmented to incorporate energy storage and renewable generation.

  5. Assessment of the Annual Additional Effective Doses amongst Minamisoma Children during the Second Year after the Fukushima Daiichi Nuclear Power Plant Disaster

    PubMed Central

    Tsubokura, Masaharu; Kato, Shigeaki; Morita, Tomohiro; Nomura, Shuhei; Kami, Masahiro; Sakaihara, Kikugoro; Hanai, Tatsuo; Oikawa, Tomoyoshi; Kanazawa, Yukio

    2015-01-01

    An assessment of the external and internal radiation exposure levels, which includes calculation of effective doses from chronic radiation exposure and assessment of long-term radiation-related health risks, has become mandatory for residents living near the nuclear power plant in Fukushima, Japan. Data for all primary and secondary children in Minamisoma who participated in both external and internal screening programs were employed to assess the annual additional effective dose acquired due to the Fukushima Daiichi nuclear power plant disaster. In total, 881 children took part in both internal and external radiation exposure screening programs between 1st April 2012 to 31st March 2013. The level of additional effective doses ranged from 0.025 to 3.49 mSv/year with the median of 0.70 mSv/year. While 99.7% of the children (n = 878) were not detected with internal contamination, 90.3% of the additional effective doses was the result of external radiation exposure. This finding is relatively consistent with the doses estimated by the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR). The present study showed that the level of annual additional effective doses among children in Minamisoma has been low, even after the inter-individual differences were taken into account. The dose from internal radiation exposure was negligible presumably due to the success of contaminated food control. PMID:26053271

  6. Assessment of the Annual Additional Effective Doses amongst Minamisoma Children during the Second Year after the Fukushima Daiichi Nuclear Power Plant Disaster.

    PubMed

    Tsubokura, Masaharu; Kato, Shigeaki; Morita, Tomohiro; Nomura, Shuhei; Kami, Masahiro; Sakaihara, Kikugoro; Hanai, Tatsuo; Oikawa, Tomoyoshi; Kanazawa, Yukio

    2015-01-01

    An assessment of the external and internal radiation exposure levels, which includes calculation of effective doses from chronic radiation exposure and assessment of long-term radiation-related health risks, has become mandatory for residents living near the nuclear power plant in Fukushima, Japan. Data for all primary and secondary children in Minamisoma who participated in both external and internal screening programs were employed to assess the annual additional effective dose acquired due to the Fukushima Daiichi nuclear power plant disaster. In total, 881 children took part in both internal and external radiation exposure screening programs between 1st April 2012 to 31st March 2013. The level of additional effective doses ranged from 0.025 to 3.49 mSv/year with the median of 0.70 mSv/year. While 99.7% of the children (n = 878) were not detected with internal contamination, 90.3% of the additional effective doses was the result of external radiation exposure. This finding is relatively consistent with the doses estimated by the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR). The present study showed that the level of annual additional effective doses among children in Minamisoma has been low, even after the inter-individual differences were taken into account. The dose from internal radiation exposure was negligible presumably due to the success of contaminated food control. PMID:26053271

  7. A feasibility study of a predictive emissions monitoring system applied to taipower's nanpu and hsinta power plants.

    PubMed

    Chien, Tsung-Wen; Hsueh, Hsin-Ta; Chu, Hsin; Hsu, Wei-Chieh; Tu, Yueh-Yuan; Tsai, Hsien-Shiou; Chen, Kuo-Yi

    2010-08-01

    The Hsinta and Nanpu Power Stations are located in southern Taiwan. The Hsinta Power Station consists of five combined-cycle gas turbines (CCGT), whereas the Nanpu Power Station consists of four. A project was undertaken to develop and deploy a predictive emissions monitoring system (PEMS) on CCGT unit 3 of Hsinta Power Station (HT-3) and CCGT unit 1 of Nanpu Power Station (NP-1) with the long-term goal of developing a universal model for this kind of power plant. After the first-year PEMS project at the Hsinta power plant, one goal of the second-year PEMS project was to set up a second PEMS at the Nanpu power plant and compare the PEM models applied the to two gas-fired combined cycle power generation units. Consequently, the second and third PEMS of Taiwan at CCGT HT-3 and NP-1 were finished. After comparing the differences among HT-1, HT-3, and NP-1 PEMS models, the pattern of model functionality indicated that this model could be applied to the other units of the same type and size. However, the PEMS function constant or parameter coefficients must be modified on a case-by-case basis. With regard to the PEMS model developed for HT-3, the relative accuracy (RA) of the 15-variable model with start-up mode is only 7.43% and met the criteria of draft PS-16. With regard to the PEMS model developed for NP-1, the RA of the 10-variable model with start-up mode was only 7.76% and also met the criteria of draft PS-16. PMID:20842930

  8. The Acoustic Analogy: A Powerful Tool in Aeroacoustics with Emphasis on Jet Noise Prediction

    NASA Technical Reports Server (NTRS)

    Farassat, F.; Doty, Michael J.; Hunter, Craig A.

    2004-01-01

    The acoustic analogy introduced by Lighthill to study jet noise is now over 50 years old. In the present paper, Lighthill s Acoustic Analogy is revisited together with a brief evaluation of the state-of-the-art of the subject and an exploration of the possibility of further improvements in jet noise prediction from analytical methods, computational fluid dynamics (CFD) predictions, and measurement techniques. Experimental Particle Image Velocimetry (PIV) data is used both to evaluate turbulent statistics from Reynolds-averaged Navier-Stokes (RANS) CFD and to propose correlation models for the Lighthill stress tensor. The NASA Langley Jet3D code is used to study the effect of these models on jet noise prediction. From the analytical investigation, a retarded time correction is shown that improves, by approximately 8 dB, the over-prediction of aft-arc jet noise by Jet3D. In experimental investigation, the PIV data agree well with the CFD mean flow predictions, with room for improvement in Reynolds stress predictions. Initial modifications, suggested by the PIV data, to the form of the Jet3D correlation model showed no noticeable improvements in jet noise prediction.

  9. Prediction of joint algal toxicity of nano-CeO2/nano-TiO2 and florfenicol: Independent action surpasses concentration addition.

    PubMed

    Wang, Zhuang; Wang, Se; Peijnenburg, Willie J G M

    2016-08-01

    Co-exposure of aquatic organisms to engineered nanoparticles (ENPs) and antibiotics is likely to take place in the environment. However, the impacts of co-exposure on aquatic organisms are virtually unknown and understanding the joint toxicity of ENPs and antibiotics is a topic of importance. The independent action (IA) model and the concentration addition (CA) model are two of the most common approaches to mixture toxicity assessment. In this study, the joint toxicity of two ENPs (nCeO2 and nTiO2) and one antibiotic (florfenicol, FLO) to Chlorella pyrenoidosa was determined to compare the applicability of the IA and the CA model. Concentration-response analyses were performed for single toxicants and for binary mixtures containing FLO and one of the ENPs at two suspended particle concentrations. The effect concentrations and the observed effects of the binary mixtures were compared to the predictions of the joint toxicity. The observed toxicity associated with the nCeO2 or nTiO2 exposure was enhanced by the concomitant FLO exposure. The joint toxicity of nCeO2 and FLO was significantly higher than that of nTiO2 and FLO. Predictions based on the IA and CA models tend to underestimate the overall toxicity (in terms of median effect concentration) of the binary mixtures, but IA performs better than CA, irrespective of the effect level under consideration and the types of mixtures studied. This result underpins the need to consider the effects of mixtures of ENPs and organic chemicals on aquatic organisms, and the practicability of the IA and CA methods in toxicity assessment of ENPs. PMID:27156210

  10. Impact of high microwave power on hydrogen impurity trapping in nanocrystalline diamond films grown with simultaneous nitrogen and oxygen addition into methane/hydrogen plasma

    NASA Astrophysics Data System (ADS)

    Tang, C. J.; Fernandes, A. J. S.; Jiang, X. F.; Pinto, J. L.; Ye, H.

    2016-01-01

    In this work, we study for the first time the influence of microwave power higher than 2.0 kW on bonded hydrogen impurity incorporation (form and content) in nanocrystalline diamond (NCD) films grown in a 5 kW MPCVD reactor. The NCD samples of different thickness ranging from 25 to 205 μm were obtained through a small amount of simultaneous nitrogen and oxygen addition into conventional about 4% methane in hydrogen reactants by keeping the other operating parameters in the same range as that typically used for the growth of large-grained polycrystalline diamond films. Specific hydrogen point defect in the NCD films is analyzed by using Fourier-transform infrared (FTIR) spectroscopy. When the other operating parameters are kept constant (mainly the input gases), with increasing of microwave power from 2.0 to 3.2 kW (the pressure was increased slightly in order to stabilize the plasma ball of the same size), which simultaneously resulting in the rise of substrate temperature more than 100 °C, the growth rate of the NCD films increases one order of magnitude from 0.3 to 3.0 μm/h, while the content of hydrogen impurity trapped in the NCD films during the growth process decreases with power. It has also been found that a new H related infrared absorption peak appears at 2834 cm-1 in the NCD films grown with a small amount of nitrogen and oxygen addition at power higher than 2.0 kW and increases with power higher than 3.0 kW. According to these new experimental results, the role of high microwave power on diamond growth and hydrogen impurity incorporation is discussed based on the standard growth mechanism of CVD diamonds using CH4/H2 gas mixtures. Our current experimental findings shed light into the incorporation mechanism of hydrogen impurity in NCD films grown with a small amount of nitrogen and oxygen addition into methane/hydrogen plasma.

  11. Impact of the flame retardant additive triphenyl phosphate (TPP) on the performance of graphite/LiFePO4 cells in high power applications

    NASA Astrophysics Data System (ADS)

    Ciosek Högström, Katarzyna; Lundgren, Henrik; Wilken, Susanne; Zavalis, Tommy G.; Behm, Mårten; Edström, Kristina; Jacobsson, Per; Johansson, Patrik; Lindbergh, Göran

    2014-06-01

    This study presents an extensive characterization of a standard Li-ion battery (LiB) electrolyte containing different concentrations of the flame retardant triphenyl phosphate (TPP) in the context of high power applications. Electrolyte characterization shows only a minor decrease in the electrolyte flammability for low TPP concentrations. The addition of TPP to the electrolyte leads to increased viscosity and decreased conductivity. The solvation of the lithium ion charge carriers seem to be directly affected by the TPP addition - as evidenced by Raman spectroscopy and increased mass-transport resistivity. Graphite/LiFePO4 full cell tests show the energy efficiency to decrease with the addition of TPP. Specifically, diffusion resistivity is observed to be the main source of increased losses. Furthermore, TPP influences the interface chemistry on both the positive and the negative electrode. Higher concentrations of TPP lead to thicker interface layers on LiFePO4. Even though TPP is not electrochemically reduced on graphite, it does participate in SEI formation. TPP cannot be considered a suitable flame retardant for high power applications as there is only a minor impact of TPP on the flammability of the electrolyte for low concentrations of TPP, and a significant increase in polarization is observed for higher concentrations of TPP.

  12. A predictive model of nuclear power plant crew decision-making and performance in a dynamic simulation environment

    NASA Astrophysics Data System (ADS)

    Coyne, Kevin Anthony

    The safe operation of complex systems such as nuclear power plants requires close coordination between the human operators and plant systems. In order to maintain an adequate level of safety following an accident or other off-normal event, the operators often are called upon to perform complex tasks during dynamic situations with incomplete information. The safety of such complex systems can be greatly improved if the conditions that could lead operators to make poor decisions and commit erroneous actions during these situations can be predicted and mitigated. The primary goal of this research project was the development and validation of a cognitive model capable of simulating nuclear plant operator decision-making during accident conditions. Dynamic probabilistic risk assessment methods can improve the prediction of human error events by providing rich contextual information and an explicit consideration of feedback arising from man-machine interactions. The Accident Dynamics Simulator paired with the Information, Decision, and Action in a Crew context cognitive model (ADS-IDAC) shows promise for predicting situational contexts that might lead to human error events, particularly knowledge driven errors of commission. ADS-IDAC generates a discrete dynamic event tree (DDET) by applying simple branching rules that reflect variations in crew responses to plant events and system status changes. Branches can be generated to simulate slow or fast procedure execution speed, skipping of procedure steps, reliance on memorized information, activation of mental beliefs, variations in control inputs, and equipment failures. Complex operator mental models of plant behavior that guide crew actions can be represented within the ADS-IDAC mental belief framework and used to identify situational contexts that may lead to human error events. This research increased the capabilities of ADS-IDAC in several key areas. The ADS-IDAC computer code was improved to support additional

  13. High SO{sub 2} removal efficiency testing: Results of DBA and sodium formate additive tests at Southwestern Electric Power company`s Pirkey Station

    SciTech Connect

    1996-05-30

    Tests were conducted at Southwestern Electric Power Company`s (SWEPCo) Henry W. Pirkey Station wet limestone flue gas desulfurization (FGD) system to evaluate options for achieving high sulfur dioxide removal efficiency. The Pirkey FGD system includes four absorber modules, each with dual slurry recirculation loops and with a perforated plate tray in the upper loop. The options tested involved the use of dibasic acid (DBA) or sodium formate as a performance additive. The effectiveness of other potential options was simulated with the Electric Power Research Institute`s (EPRI) FGD PRocess Integration and Simulation Model (FGDPRISM) after it was calibrated to the system. An economic analysis was done to determine the cost effectiveness of the high-efficiency options. Results are-summarized below.

  14. Testing the predictive power of cognitive atypicalities in autistic children: evidence from a 3-year follow-up study.

    PubMed

    Pellicano, Elizabeth

    2013-08-01

    This follow-up study investigated the predictive power of early cognitive atypicalities. Specifically, it examined whether early individual differences in specific cognitive skills, including theory of mind, executive function, and central coherence, could uniquely account for variation in autistic children's behaviors-social communication, repetitive behaviors, and interests and insistence on sameness-at follow-up. Thirty-seven cognitively able children with an autism spectrum condition were assessed on tests tapping verbal and nonverbal ability, theory of mind (false-belief prediction), executive function (planning ability, cognitive flexibility, and inhibitory control), and central coherence (local processing) at intake and their behavioral functioning (social communication, repetitive behaviors and interests, insistence on sameness) 3 years later. Individual differences in early executive but not theory of mind skills predicted variation in children's social communication. Individual differences in children's early executive function also predicted the degree of repetitive behaviors and interests at follow-up. There were no predictive relationships between early central coherence and children's insistence on sameness. These findings challenge the notion that distinct cognitive atypicalities map on to specific behavioral features of autism. Instead, early variation in executive function plays a key role in helping to shape autistic children's emerging behaviors, including their social communication and repetitive behaviors and interests. PMID:23495146

  15. Using micro saint to predict performance in a nuclear power plant control room

    SciTech Connect

    Lawless, M.T.; Laughery, K.R.; Persenky, J.J.

    1995-09-01

    The United States Nuclear Regulatory Commission (NRC) requires a technical basis for regulatory actions. In the area of human factors, one possible technical basis is human performance modeling technology including task network modeling. This study assessed the feasibility and validity of task network modeling to predict the performance of control room crews. Task network models were built that matched the experimental conditions of a study on computerized procedures that was conducted at North Carolina State University. The data from the {open_quotes}paper procedures{close_quotes} conditions were used to calibrate the task network models. Then, the models were manipulated to reflect expected changes when computerized procedures were used. These models` predictions were then compared to the experimental data from the {open_quotes}computerized conditions{close_quotes} of the North Carolina State University study. Analyses indicated that the models predicted some subsets of the data well, but not all. Implications for the use of task network modeling are discussed.

  16. TNF-α Promoter Polymorphisms Predict the Response to Etanercept More Powerfully than that to Infliximab/Adalimumab in Spondyloarthritis

    PubMed Central

    Liu, Jing; Dong, Zheng; Zhu, Qi; He, Dongyi; Ma, Yanyun; Du, Aiping; He, Fan; Zhao, Dongbao; Xu, Xia; Zhang, Hui; jin, Li; Wang, Jiucun

    2016-01-01

    While previous studies have researched in association analyses between TNFα promoter polymorphisms and responses to TNF blockers in spondyloarthritis patients, their results were conflicting. Therefore, we aimed to determine whether TNFα promoter polymorphisms could predict response to TNF blockers and find the source of heterogeneity. Data were extracted and analyzed from published articles and combined with our unpublished data. We found that the greatest potential sources of heterogeneity in the results were gender ratio, disease type, continents, and TNF blockers. Then Stratification analysis showed that the TNFα −308 G allele and the −238 G allele predicted a good response to TNF blockers (OR = 2.64 [1.48–4.73]; 2.52 [1.46–4.37]). However, G alleles of TNFα −308 and −238 could predict the response to etanercept (OR = 4.02 [2.24–7.23]; 5.17 [2.29–11.67]) much more powerfully than the response to infiliximab/adalimumab (OR = 1.68 [1.02–2.78]; 1.28 [0.57–2.86]). TNFα −857 could not predict the response in either subgroup. Cumulative meta-analysis performed in ankylosing spondylitis patients presented the odds ratio decreased with stricter response criteria. In conclusion, TNFα −308 A/G and −238 A/G are more powerful to predict the response to Etanercept and it is dependent on the criteria of response. PMID:27578555

  17. Rational Design of Lanthanoid Single-Ion Magnets: Predictive Power of the Theoretical Models.

    PubMed

    Baldoví, José J; Duan, Yan; Morales, Roser; Gaita-Ariño, Alejandro; Ruiz, Eliseo; Coronado, Eugenio

    2016-09-12

    We report two new single-ion magnets (SIMs) of a family of oxydiacetate lanthanide complexes with D3 symmetry to test the predictive capabilities of complete active space ab initio methods (CASSCF and CASPT2) and the semiempirical radial effective charge (REC) model. Comparison of the theoretical predictions of the energy levels, wave functions and magnetic properties with detailed spectroscopic and magnetic characterisation is used to critically discuss the limitations of these theoretical approaches. The need for spectroscopic information for a reliable description of the properties of lanthanide SIMs is emphasised. PMID:27465352

  18. Feasibility study on a perceived fatigue prediction dependent power control for an electrically assisted bicycle.

    PubMed

    Kiryu, T; Minagawa, H

    2013-01-01

    Several types of electric motor assists have been developed, as a result, it is important to control muscular fatigue on-site in terms of health promotion and motor rehabilitation. Predicting the perceived fatigue by several biosignal-related variables with the multiple regression model and polynomial approximation, we try to propose a self control design for the electrically assisted bicycle (EAB). We also determine the meaningful muscles during pedaling by muscle synergies in relation to the motion maturity. In field experiments, prediction of ongoing perceived physical fatigue could have the potential of suitable control of EAB. PMID:24110131

  19. Ideal MHD Stability Prediction and Required Power for EAST Advanced Scenario

    NASA Astrophysics Data System (ADS)

    Chen, Junjie; Li, Guoqiang; Qian, Jinping; Liu, Zixi

    2012-11-01

    The Experimental Advanced Superconducting Tokamak (EAST) is the first fully superconducting tokamak with a D-shaped cross-sectional plasma presently in operation. The ideal magnetohydrodynamic (MHD) stability and required power for the EAST advanced tokamak (AT) scenario with negative central shear and double transport barrier (DTB) are investigated. With the equilibrium code TOQ and stability code GATO, the ideal MHD stability is analyzed. It is shown that a moderate ratio of edge transport barriers' (ETB) height to internal transport barriers' (ITBs) height is beneficial to ideal MHD stability. The normalized beta βN limit is about 2.20 (without wall) and 3.70 (with ideal wall). With the scaling law of energy confinement time, the required heating power for EAST AT scenario is calculated. The total heating power Pt increases as the toroidal magnetic field BT or the normalized beta βN is increased.

  20. Performance Prediction of OWC Type Small Size Wave Power Device with Impulse Turbine

    NASA Astrophysics Data System (ADS)

    Suzuki, Masami; Takao, Manabu; Satoh, Eiji; Nagata, Shuichi; Toyota, Kazutaka; Setoguchi, Toshiaki

    This paper investigates a small size wave power device with an impulse turbine installed in the breakwater near Niigata Port, Japan. The device consists of an air chamber, a turbine, a generator and pressure-relief valves. This study reveals the characteristics of each component in this system with impulse turbine and a direct current dynamo the power of which is consumed by a constant resistor. In this paper special features of the impulse turbine are found, and the system characteristics are briefly represented. The overall plant performance was analyzed using mathematical model of an oscillating water column (OWC) based on linear water wave theory and the special features of the impulse turbine.

  1. Modelling for Understanding AND for Prediction/Classification--The Power of Neural Networks in Research

    ERIC Educational Resources Information Center

    Cascallar, Eduardo; Musso, Mariel; Kyndt, Eva; Dochy, Filip

    2014-01-01

    Two articles, Edelsbrunner and, Schneider (2013), and Nokelainen and Silander (2014) comment on Musso, Kyndt, Cascallar, and Dochy (2013). Several relevant issues are raised and some important clarifications are made in response to both commentaries. Predictive systems based on artificial neural networks continue to be the focus of current…

  2. Statistical Power for a Simultaneous Test of Factorial and Predictive Invariance

    ERIC Educational Resources Information Center

    Olivera-Aguilar, Margarita; Millsap, Roger E.

    2013-01-01

    A common finding in studies of differential prediction across groups is that although regression slopes are the same or similar across groups, group differences exist in regression intercepts. Building on earlier work by Birnbaum (1979), Millsap (1998) presented an invariant factor model that would explain such intercept differences as arising due…

  3. The Predictive Power of Phonemic Awareness and Naming Speed for Early Dutch Word Recognition

    ERIC Educational Resources Information Center

    Verhagen, Wim G. M.; Aarnoutse, Cor A. J.; van Leeuwe, Jan F. J.

    2009-01-01

    Effects of phonemic awareness and naming speed on the speed and accuracy of Dutch children's word recognition were investigated in a longitudinal study. Both the speed and accuracy of word recognition at the end of Grade 2 were predicted by naming speed from both kindergarten and Grade 1, after control for autoregressive relations, kindergarten…

  4. Fatigue life prediction of mooring chains for a floating tidal current power station

    NASA Astrophysics Data System (ADS)

    Jing, Fengmei; Zhang, Liang; Yang, Zhong

    2012-06-01

    As a kind of clean and renewable energy, tidal current energy is becoming increasingly popular all over the world with the shortage of energy and environmental problems becoming more and more severe. A floating tidal current power station is a typical type of tidal current power transformers which can sustain the loads of wind, waves, and current, and even the extreme situation of a typhoon. Therefore, the mooring system must be reliable enough to keep the station operating normally and to survive in extreme situations. The power station examined in this paper was installed at a depth of 40 m. A 44 mm-diameter R4-RQ4 chain was chosen, with a 2 147 kN minimum break strength and 50 kN pretension. Common studless link chain was used in this paper. Based on the Miner fatigue cumulative damage rule, S-N curves of chains, and MOSES software, a highly reliable mooring system was designed and analyzed. The calculation results show that the mooring system designed is reliable throughout a 10-year period. It can completely meet the design requirements of American Petroleum institution (API). Therefore, the presented research is significant for advancing the design of this kind of power station.

  5. The SURA Coastal Ocean Observing and Prediction (SCOOP) Program: Adapting Web 2.0 technologies to power next generation science

    NASA Astrophysics Data System (ADS)

    Bogden, P.; Partners, S.

    2008-12-01

    The Web 2.0 has helped globalize the economy and change social interactions, but the full impact on coastal sciences has yet to be realized. The SCOOP program (www.OpenIOOS.org/about/sura.html), an initiative of the Coastal Research Committee of the Southeastern Universities Research Association (SURA), has been using Web 2.0 technologies to create infrastructure for a multi-disciplinary Distributed Coastal Laboratory (DCL). In the spirit of the Web 2.0, SCOOP strives to provide an open-access virtual facility where "virtual visiting" scientists can log in, perform experiments (e.g., evaluate new wetting/drying algorithms in several different inundation models), potentially contribute to the assembly of resources (e.g., leave their algorithms for others), and then move on. The SCOOP prototype has focused on storm surge and waves (the initial science focus), and integrates a real-time data network to evaluate the predictions. The multi-purpose SCOOP components support a sensor-web initiative (www.OOSTethys.org) that is co-led by SURA. SCOOP also includes portals with real-time visualization, workflow configuration and decision-tool prototypes (www.OpenIOOS.org), powered by distributed computing resources from multiple universities across the nation (www.sura.org/SURAgrid). Based on our experience, we propose three key ingredients for initiatives to have the biggest impact on coastal science: (1) standards, (2) working prototypes and (3) communities of interest. We strongly endorse the Open Geospatial Consortium - a geospatial analog of the World Wide Web consortium - and other international consensus-standards bodies that engage government, private sector and academic involvement. But these standards are often highly complex, which can be an impediment to their use. We have overcome such hurdles with the second key ingredient: a focused working prototype. The prototype should include guides and resources that make it easy for others to apply, test, and revise the

  6. Assessment of Gasoline Prices and its Predictive Power on U.S. Consumers' Retail Spending and Savings

    NASA Astrophysics Data System (ADS)

    Alvarado-Bonilla, Joel

    The rising costs of fuels and specifically gasoline pose an economic challenge to U.S. consumers. Thus, the specific problem considered in this study was a rise in gasoline prices can reduce consumer spending, disposable income, food service traffic, and spending on healthy food, medicines, or visits to the doctor. Aligned with the problem, the purpose of this quantitative multiple correlation study was to examine the economic aspects for a rise in gasoline prices to reduce the six elements in the problem. This study consisted of a correlational design based on a retrospective longitudinal analysis (RLA) to examine gasoline prices versus the economic indexes of: (a) Retail Spending and (b) personal savings (PS). The RLA consisted on historic archival public data from 1978 to 2015. This RLA involved two separate linear multiple regression analyses to measure gasoline price's predictive power (PP) on two indexes while controlling for Unemployment Rate (UR). In summary, regression Formula 1 revealed Gasoline Price had a significant 61.1% PP on Retail Spending. In contrast, Formula 2 had Gasoline Price not having a significant PP on PS. Formula 2 yielded UR with 38.8% PP on PS. Results were significant at p<.01. Gasoline Price's PP on Retail Spending means a spending link to retail items such as: food service traffic, healthy food, medicines, and consumer spending. The UR predictive power on PS was unexpected, but logical from an economic view. Also unexpected was Gasoline Price's non-predictive power on PS, which suggests Americans may not save money when gasoline prices drop. These results shed light on the link of gasoline and UR on U.S. consumer's economy through savings and spending, which can be useful for policy design on gasoline and fuels taxing and pricing. The results serve as a basis for future study on gasoline and economics.

  7. Application of computational neural networks in predicting atmospheric pollutant concentrations due to fossil-fired electric power generation

    SciTech Connect

    El-Hawary, F.

    1995-12-31

    The ability to accurately predict the behavior of a dynamic system is of essential importance in monitoring and control of complex processes. In this regard recent advances in neural-net based system identification represent a significant step toward development and design of a new generation of control tools for increased system performance and reliability. The enabling functionality is the one of accurate representation of a model of a nonlinear and nonstationary dynamic system. This functionality provides valuable new opportunities including: (1) The ability to predict future system behavior on the basis of actual system observations, (2) On-line evaluation and display of system performance and design of early warning systems, and (3) Controller optimization for improved system performance. In this presentation, we discuss the issues involved in definition and design of learning control systems and their impact on power system control. Several numerical examples are provided for illustrative purpose.

  8. The choice of the mathematical method for prediction of electrochemical accumulator parameters value in power installations of space-rocket objects

    NASA Astrophysics Data System (ADS)

    Bezruchko, K. V.; Davidov, A. O.; Katorgina, J. G.; Logvin, V. M.; Kharchenko, A. A.

    2013-11-01

    The review and analysis of several mathematical methods for prediction of electrochemical accumulator parameters are provided in the article: according to the mathematical expectation, the latest entry, a statistical prediction, Box-Jenkins model, decomposition Volta, ARMA, ARIMA and Kalman filter. The results of these methods for prediction of the electrochemical battery 22НКГ-4CK characteristics which is a part of spacecraft power plant of the “Mikrosputnik” type are given. Possible usage of these methods for long prediction of electrochemical accumulator characteristics on space-rocket objects power plants is showed.

  9. A novel ZePoC encoder for sinusoidal signals with a predictable accuracy for an AC power standard

    NASA Astrophysics Data System (ADS)

    Vennemann, T.; Frye, T.; Liu, Z.; Kahmann, M.; Mathis, W.

    2015-11-01

    In this paper we present an analytical formulation of a Zero Position Coding (ZePoC) encoder for an AC power standard based on class-D topologies. For controlling a class-D power stage a binary signal with special spectral characteristics will be generated by this ZePoC encoder for sinusoidal signals. These spectral characteristics have a predictable accuracy within a separated baseband to keep the noise floor below a specified level. Simulation results will validate the accuracy of this novel ZePoC encoder. For a real-time implementation of the encoder on a DSP/FPGA hardware architecture a trade-off between accuracy and speed of the ZePoC algorithm has to be made. Therefore the numerical effects of different floating point formats will be analyzed.

  10. Predicting punching acceleration from selected strength and power variables in elite karate athletes: a multiple regression analysis.

    PubMed

    Loturco, Irineu; Artioli, Guilherme Giannini; Kobal, Ronaldo; Gil, Saulo; Franchini, Emerson

    2014-07-01

    This study investigated the relationship between punching acceleration and selected strength and power variables in 19 professional karate athletes from the Brazilian National Team (9 men and 10 women; age, 23 ± 3 years; height, 1.71 ± 0.09 m; and body mass [BM], 67.34 ± 13.44 kg). Punching acceleration was assessed under 4 different conditions in a randomized order: (a) fixed distance aiming to attain maximum speed (FS), (b) fixed distance aiming to attain maximum impact (FI), (c) self-selected distance aiming to attain maximum speed, and (d) self-selected distance aiming to attain maximum impact. The selected strength and power variables were as follows: maximal dynamic strength in bench press and squat-machine, squat and countermovement jump height, mean propulsive power in bench throw and jump squat, and mean propulsive velocity in jump squat with 40% of BM. Upper- and lower-body power and maximal dynamic strength variables were positively correlated to punch acceleration in all conditions. Multiple regression analysis also revealed predictive variables: relative mean propulsive power in squat jump (W·kg-1), and maximal dynamic strength 1 repetition maximum in both bench press and squat-machine exercises. An impact-oriented instruction and a self-selected distance to start the movement seem to be crucial to reach the highest acceleration during punching execution. This investigation, while demonstrating strong correlations between punching acceleration and strength-power variables, also provides important information for coaches, especially for designing better training strategies to improve punching speed. PMID:24276310

  11. Prediction of global solar irradiance based on time series analysis: Application to solar thermal power plants energy production planning

    SciTech Connect

    Martin, Luis; Marchante, Ruth; Cony, Marco; Zarzalejo, Luis F.; Polo, Jesus; Navarro, Ana

    2010-10-15

    Due to strong increase of solar power generation, the predictions of incoming solar energy are acquiring more importance. Photovoltaic and solar thermal are the main sources of electricity generation from solar energy. In the case of solar thermal energy plants with storage energy system, its management and operation need reliable predictions of solar irradiance with the same temporal resolution as the temporal capacity of the back-up system. These plants can work like a conventional power plant and compete in the energy stock market avoiding intermittence in electricity production. This work presents a comparisons of statistical models based on time series applied to predict half daily values of global solar irradiance with a temporal horizon of 3 days. Half daily values consist of accumulated hourly global solar irradiance from solar raise to solar noon and from noon until dawn for each day. The dataset of ground solar radiation used belongs to stations of Spanish National Weather Service (AEMet). The models tested are autoregressive, neural networks and fuzzy logic models. Due to the fact that half daily solar irradiance time series is non-stationary, it has been necessary to transform it to two new stationary variables (clearness index and lost component) which are used as input of the predictive models. Improvement in terms of RMSD of the models essayed is compared against the model based on persistence. The validation process shows that all models essayed improve persistence. The best approach to forecast half daily values of solar irradiance is neural network models with lost component as input, except Lerida station where models based on clearness index have less uncertainty because this magnitude has a linear behaviour and it is easier to simulate by models. (author)

  12. An analysis of the impact of tumor amount on the predictive power of a prostate biopsy prognostic assay

    NASA Astrophysics Data System (ADS)

    Khan, Faisal M.; Fogarasi, Stephen I.; Powell, Douglas; Fernandez, Gerardo; Mesa-Tejada, Ricardo; Donovan, Michael J.

    2011-03-01

    The Prostate Px prognostic assay offered by Aureon Biosciences is designed to predict progression post primary treatment for prostate cancer patients based on their diagnostic biopsy specimen. The assay is driven by the automated image analysis of a diagnostic prostate needle biopsy (PNB) and incorporates pathologist acquired and digitally masked images which reflect the morphometric (Hematoxylin and Eosin, H&E) and protein expression (immunofluorescence, IF) properties of the PNB. Up to 9 images (3 H&E and 6 IF) from each of 1027 patients, with varying amounts of tumor content were included in the study. We wanted to understand what was the minimal tumor volume required to maintain assay predictive robustness as a result of overall PNB tumor content and assess the impact of pathologist tumor masking variability. 232 patients were selected who had a minimum of 80% tumor volume in a 20x magnification image. In each of the three imaging domains (2 different multiplex (Mplex) IF images and one H&E), the tumor volume was artificially reduced in increments from 80% to 2.5% of the original image area. This simulated decreasing amounts of tumor as well as variations in digital tumor masking. The univariate predictive power of individual imaging domains remained robust down to the 10% tumor level, whereas the total assay was robust through the 20% to 10% tumor level. This work presents one of the first assessments of the variety in tumor amounts on the predictive power of a commercially available prognostic assay that is reliant on multiple bioimaging domains.

  13. Power Output Prediction From Jump Height and Body Mass Does Not Appropriately Categorize or Rank Athletes.

    PubMed

    Ache-Dias, Jonathan; Dal Pupo, Juliano; Gheller, Rodrigo G; Külkamp, Wladymir; Moro, Antônio R P

    2016-03-01

    The purposes of this study were (a) to verify the agreement of categorization and ranks based on the actual power output measured by a force plate (PPact) and the estimated power output (PPest) from jump height and body mass (BM), and (b) to verify whether the ratio standard is adequate to scale the PPact for BM. The countermovement jumps of 309 male athletes were analyzed. The athletes were first categorized into tertiles (superior, intermediate, and inferior) according to PPact and PPest. After that the athletes were ranked (highest to lowest power output) according to PPact and PPest. The PPest equation explained 81% of PPact variance (standard error of estimate = 277.4 W). The PPest (3,757.1 ± 579.8 W) displayed similar mean values compared with PPact (3,757.1 ± 642.3 W). However, the agreement between the categories generated by PPact and PPest was only moderate (k = 0.6; p < 0.01), and in the intermediate tertile, the categorization differs 38.8%. The agreement between the ranks analyzed from a Bland-Altman plot shows bias zero, but a wide limits of agreement (81 ranks; 26.2%). For the PPact scaling, the ratio standard may be considered as an adequate method for removing the BM effect, considering the lack of correlation between the scaled PPact (PPact/BM) and BM, and also the confirmation of Tanner's special circumstance. In conclusion, our findings indicate that the athlete's power output was not appropriately categorized or ranked when using PPest. Furthermore, the use of the scaled PPact is recommended to fairly compare athletes with different BMs. PMID:26332774

  14. EEG Beta Power but Not Background Music Predicts the Recall Scores in a Foreign-Vocabulary Learning Task.

    PubMed

    Küssner, Mats B; de Groot, Annette M B; Hofman, Winni F; Hillen, Marij A

    2016-01-01

    As tantalizing as the idea that background music beneficially affects foreign vocabulary learning may seem, there is-partly due to a lack of theory-driven research-no consistent evidence to support this notion. We investigated inter-individual differences in the effects of background music on foreign vocabulary learning. Based on Eysenck's theory of personality we predicted that individuals with a high level of cortical arousal should perform worse when learning with background music compared to silence, whereas individuals with a low level of cortical arousal should be unaffected by background music or benefit from it. Participants were tested in a paired-associate learning paradigm consisting of three immediate word recall tasks, as well as a delayed recall task one week later. Baseline cortical arousal assessed with spontaneous EEG measurement in silence prior to the learning rounds was used for the analyses. Results revealed no interaction between cortical arousal and the learning condition (background music vs. silence). Instead, we found an unexpected main effect of cortical arousal in the beta band on recall, indicating that individuals with high beta power learned more vocabulary than those with low beta power. To substantiate this finding we conducted an exact replication of the experiment. Whereas the main effect of cortical arousal was only present in a subsample of participants, a beneficial main effect of background music appeared. A combined analysis of both experiments suggests that beta power predicts the performance in the word recall task, but that there is no effect of background music on foreign vocabulary learning. In light of these findings, we discuss whether searching for effects of background music on foreign vocabulary learning, independent of factors such as inter-individual differences and task complexity, might be a red herring. Importantly, our findings emphasize the need for sufficiently powered research designs and exact replications

  15. EEG Beta Power but Not Background Music Predicts the Recall Scores in a Foreign-Vocabulary Learning Task

    PubMed Central

    de Groot, Annette M. B.; Hofman, Winni F.; Hillen, Marij A.

    2016-01-01

    As tantalizing as the idea that background music beneficially affects foreign vocabulary learning may seem, there is—partly due to a lack of theory-driven research—no consistent evidence to support this notion. We investigated inter-individual differences in the effects of background music on foreign vocabulary learning. Based on Eysenck’s theory of personality we predicted that individuals with a high level of cortical arousal should perform worse when learning with background music compared to silence, whereas individuals with a low level of cortical arousal should be unaffected by background music or benefit from it. Participants were tested in a paired-associate learning paradigm consisting of three immediate word recall tasks, as well as a delayed recall task one week later. Baseline cortical arousal assessed with spontaneous EEG measurement in silence prior to the learning rounds was used for the analyses. Results revealed no interaction between cortical arousal and the learning condition (background music vs. silence). Instead, we found an unexpected main effect of cortical arousal in the beta band on recall, indicating that individuals with high beta power learned more vocabulary than those with low beta power. To substantiate this finding we conducted an exact replication of the experiment. Whereas the main effect of cortical arousal was only present in a subsample of participants, a beneficial main effect of background music appeared. A combined analysis of both experiments suggests that beta power predicts the performance in the word recall task, but that there is no effect of background music on foreign vocabulary learning. In light of these findings, we discuss whether searching for effects of background music on foreign vocabulary learning, independent of factors such as inter-individual differences and task complexity, might be a red herring. Importantly, our findings emphasize the need for sufficiently powered research designs and exact

  16. Application of Hybrid Geo-Spatially Granular Fragility Curves to Improve Power Outage Predictions

    SciTech Connect

    Fernandez, Steven J; Allen, Melissa R; Omitaomu, Olufemi A; Walker, Kimberly A

    2014-01-01

    Fragility curves depict the relationship between a weather variable (wind speed, gust speed, ice accumulation, precipitation rate) and the observed outages for a targeted infrastructure network. This paper describes an empirical study of the county by county distribution of power outages and one minute weather variables during Hurricane Irene with the objective of comparing 1) as built fragility curves (statistical approach) to engineering as designed (bottom up) fragility curves for skill in forecasting outages during future hurricanes; 2) county specific fragility curves to find examples of significant deviation from average behavior; and 3) the engineering practices of outlier counties to suggest future engineering studies of robustness. Outages in more than 90% of the impacted counties could be anticipated through an average or generic fragility curve. The remaining counties could be identified and handled as exceptions through geographic data sets. The counties with increased or decreased robustness were characterized by terrain more or less susceptible to persistent flooding in areas where above ground poles located their foundations. Land use characteristics of the area served by the power distribution system can suggest trends in the as built power grid vulnerabilities to extreme weather events that would be subjects for site specific studies.

  17. Prediction of Cardiorespiratory Fitness by the Six-Minute Step Test and Its Association with Muscle Strength and Power in Sedentary Obese and Lean Young Women: A Cross-Sectional Study

    PubMed Central

    Bonjorno Junior, José Carlos; de Oliveira, Cláudio Ricardo; Luporini, Rafael Luís; Mendes, Renata Gonçalves; Zangrando, Katiany Thais Lopes; Trimer, Renata; Arena, Ross

    2015-01-01

    Impaired cardiorespiratory fitness (CRF) is a hallmark characteristic in obese and lean sedentary young women. Peak oxygen consumption (VO2peak) prediction from the six-minute step test (6MST) has not been established for sedentary females. It is recognized that lower-limb muscle strength and power play a key role during functional activities. The aim of this study was to investigate cardiorespiratory responses during the 6MST and CPX and to develop a predictive equation to estimate VO2peak in both lean and obese subjects. Additionally we aim to investigate how muscle function impacts functional performance. Lean (LN = 13) and obese (OB = 18) women, aged 20–45, underwent a CPX, two 6MSTs, and isokinetic and isometric knee extensor strength and power evaluations. Regression analysis assessed the ability to predict VO2peak from the 6MST, age and body mass index (BMI). CPX and 6MST main outcomes were compared between LN and OB and correlated with strength and power variables. CRF, functional capacity, and muscle strength and power were lower in the OB compared to LN (<0.05). During the 6MST, LN and OB reached ~90% of predicted maximal heart rate and ~80% of the VO2peak obtained during CPX. BMI, age and number of step cycles (NSC) explained 83% of the total variance in VO2peak. Moderate to strong correlations between VO2peak at CPX and VO2peak at 6MST (r = 0.86), VO2peak at CPX and NSC (r = 0.80), as well as between VO2peak, NSC and muscle strength and power variables were found (p<0.05). These findings indicate the 6MST, BMI and age accurately predict VO2peak in both lean and obese young sedentary women. Muscle strength and power were related to measures of aerobic and functional performance. PMID:26717568

  18. The predictive power of singular value decomposition entropy for stock market dynamics

    NASA Astrophysics Data System (ADS)

    Caraiani, Petre

    2014-01-01

    We use a correlation-based approach to analyze financial data from the US stock market, both daily and monthly observations from the Dow Jones. We compute the entropy based on the singular value decomposition of the correlation matrix for the components of the Dow Jones Industrial Index. Based on a moving window, we derive time varying measures of entropy for both daily and monthly data. We find that the entropy has a predictive ability with respect to stock market dynamics as indicated by the Granger causality tests.

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

    NASA Technical Reports Server (NTRS)

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

    1986-01-01

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

  20. Wind assessment and power prediction from a wind farm in southern Saskatchewan

    NASA Astrophysics Data System (ADS)

    Chakravarthy, Mukundhan

    Mesoscale and Microscale Modeling are two methods used to estimate wind energy resources. The main parameters of wind resource estimation are the mean wind speed and the mean wind power density. Mesoscale Modeling was applied to three different regions, Regina, Saskatoon, and Gull Lake, located in southern Saskatchewan, Canada. The areas were selected as centers of a domain for a grid with a horizontal resolution of 3 kilometers. Mesoscale Modeling was performed using the software tool, Anemoscope. Wind resources for the regions and the areas surrounding them have been generated for three elevations (30, 50, and 80 meters). As it is a site for a large wind turbine farm, the region in and around Swift Current in southern Saskatchewan (approximately 36 km x 36 km in area) was the site of choice for this study in Microscale Modeling. A widely popular software, WAsP, was chosen to perform the study. Statistical wind data was obtained from a Swift Current meteorological station over a period of ten years (2000-2009). A wind resource grid has been set up for the area at a horizontal resolution of 200 meters, and wind resource maps have been generated for heights of 50, 65, and 80 meters above ground level as the heights are the potential wind turbine hub heights. In order to simulate the SaskPower Centennial Wind Power Station, a wind farm was set up with 83 wind turbines in the Coulee Municipality region near Swift Current. The annual energy production for the entire farm, along with those of the individual turbines, has been calculated. Both total and individual wind turbine productions were accurately modeled.

  1. Kinetic modeling of plant metabolism and its predictive power: peppermint essential oil biosynthesis as an example.

    PubMed

    Lange, Bernd Markus; Rios-Estepa, Rigoberto

    2014-01-01

    The integration of mathematical modeling with analytical experimentation in an iterative fashion is a powerful approach to advance our understanding of the architecture and regulation of metabolic networks. Ultimately, such knowledge is highly valuable to support efforts aimed at modulating flux through target pathways by molecular breeding and/or metabolic engineering. In this article we describe a kinetic mathematical model of peppermint essential oil biosynthesis, a pathway that has been studied extensively for more than two decades. Modeling assumptions and approximations are described in detail. We provide step-by-step instructions on how to run simulations of dynamic changes in pathway metabolites concentrations. PMID:24218222

  2. Comparison of Analytical Predictions and Experimental Results for a Dual Brayton Power System

    NASA Technical Reports Server (NTRS)

    Johnson, Paul

    2007-01-01

    NASA Glenn Research Center (GRC) contracted Barber- Nichols, Arvada, CO to construct a dual Brayton power conversion system for use as a hardware proof of concept and to validate results from a computational code known as the Closed Cycle System Simulation (CCSS). Initial checkout tests were performed at Barber- Nichols to ready the system for delivery to GRC. This presentation describes the system hardware components and lists the types of checkout tests performed along with a couple issues encountered while conducting the tests. A description of the CCSS model is also presented. The checkout tests did not focus on generating data, therefore, no test data or model analyses are presented.

  3. Transfer of infrared thermography predictive maintenance technologies to Soviet-designed nuclear power plants: experience at Chernobyl

    NASA Astrophysics Data System (ADS)

    Pugh, Ray; Huff, Roy

    1999-03-01

    The importance of infrared (IR) technology and analysis in today's world of predictive maintenance and reliability- centered maintenance cannot be understated. The use of infrared is especially important in facilities that are required to maintain a high degree of equipment reliability because of plant or public safety concerns. As with all maintenance tools, particularly those used in predictive maintenance approaches, training plays a key role in their effectiveness and the benefit gained from their use. This paper details an effort to transfer IR technology to Soviet- designed nuclear power plants in Russia, Ukraine, and Lithuania. Delivery of this technology and post-delivery training activities have been completed recently at the Chornobyl nuclear power plant in Ukraine. Many interesting challenges were encountered during this effort. Hardware procurement and delivery of IR technology to a sensitive country were complicated by United States regulations. Freight and shipping infrastructure and host-country customs policies complicated hardware transport. Training activities were complicated by special hardware, software and training material translation needs, limited communication opportunities, and site logistical concerns. These challenges and others encountered while supplying the Chornobyl plant with state-of-the-art IR technology are described in this paper.

  4. Molecular Dynamics Approach for Predicting Helical Twisting Powers of Metal Complex Dopants in Nematic Solvents.

    PubMed

    Watanabe, Go; Yoshida, Jun

    2016-07-14

    Nematic liquid crystals of small molecules are known to transform into chiral nematic liquid crystals with supramolecular helical structures upon doping with enantiomeric compounds. Although this phenomenon is well established, the basic mechanism is still unclear. We have previously examined metal complexes with Δ and Λ chiralities as dopants in nematic liquid crystals and have found that slight differences in the molecular structure determine the handedness of the induced helical structure. In this study, we investigated the microscopic arrangement of liquid crystal molecules around metal complex dopants with the aid of molecular dynamics (MD) simulations. There are several restrictions to performing MD simulations of the chiral nematic system; for example, one pitch of the helix usually exceeds one side of an applicable periodic boundary box (∼10(2) nm). In view of these simulation problems, we therefore examined racemic systems in which a pair of Δ- and Λ-isomers of the chiral dopant is mixed with liquid crystal molecules. We selected two different octahedral ruthenium complexes as the chiral dopant molecules. As a result, we accurately calculated the ordering matrix that is essential parameter to estimate the helical twisting power of the chiral dopant based on the surface chirality model. Since the microscopic ordering is experimentally hard to be determined, our new approach with using MD simulations accurately deduced the ordering matrix and, with the aid of the surface chirality model, gave reasonable values for the helical twisting powers of each complex. PMID:27333445

  5. A training method for locomotion mode prediction using powered lower limb prostheses.

    PubMed

    Young, Aaron J; Simon, Ann M; Hargrove, Levi J

    2014-05-01

    Recently developed lower-limb prostheses are capable of actuating the knee and ankle joints, allowing amputees to perform advanced locomotion modes such as step-over-step stair ascent and walking on sloped surfaces. However, transitions between these locomotion modes and walking are neither automatic nor seamless. This study describes methods for construction and training of a high-level intent recognition system for a lower-limb prosthesis that provides natural transitions between walking, stair ascent, stair descent, ramp ascent, and ramp descent. Using mechanical sensors onboard a powered prosthesis, we collected steady-state and transition data from six transfemoral amputees while the five locomotion modes were performed. An intent recognition system built using only mechanical sensor data was 84.5% accurate using only steady-state training data. Including training data collected while amputees performed seamless transitions between locomotion modes improved the overall accuracy rate to 93.9%. Training using a single analysis window at heel contact and toe off provided higher recognition accuracy than training with multiple analysis windows. This study demonstrates the capability of an intent recognition system to provide automatic, natural, and seamless transitions between five locomotion modes for transfemoral amputees using powered lower limb prostheses. PMID:24184753

  6. Fuel Reduction Effect of the Solar Cell and Diesel Engine Hybrid System with a Prediction Algorithm of Solar Power Generation

    NASA Astrophysics Data System (ADS)

    Obara, Shin'ya; Tanno, Itaru

    Green energy utilization technology is an effective means of reducing greenhouse gas emissions. In this paper, the production-of-electricity prediction algorithm (PAS) of the solar cell was developed. In PAS, a layered neural network is made to learn based on past weather data and the operation plan of the hybrid system (proposed system) of a solar cell and a diesel engine generator was examined using this prediction algorithm. In addition, system operation without a electricity-storage facility, and the system with the engine generator operating at 25% or less of battery residual quantity was investigated, and the fuel consumption of each system was measured. Numerical simulation showed that the fuel consumption of the proposed system was modest compared with other operating methods. However, there was a significant difference in the prediction error of the electricity production of the solar cell and the actual value, and the proposed system was shown to be not always superior to others. Moreover, although there are errors in the predicted and actual values using PAS, there is no significant influence in the operation plan of the proposed system in almost all cases. In the operation plan of the system with PAS, there was a case where the fuel consumption decreased by 15% compared with other systems.

  7. Prediction of solar induced currents and effects on power transmission systems in central Canada

    NASA Technical Reports Server (NTRS)

    Goddard, W. R.; Boerner, W. M.

    1979-01-01

    The auroral-electrojet zone covers three quarters of Manitoba and consequently, solar storms strongly affect transmission lines. Harmonics are generated at transformers due to the saturation of their cores by induced currents, and the level of harmonics produced may cause malfunction of control relays, and yield unacceptable distortions in normal ac waveforms. The expected effects of long ac transmission systems were studied with emphasis on a 500 kv line to be built from Winnipeg to Minneapolis-St. Paul. Spectral analysis of induced current records from Manitoba Hydro's LaVerendrye station and magnetograms from IMS stations in Manitoba were used along with results of Campbell's work on the Alaskan pipeline induction problem (1978) in order to predict periodic and surge currents. It is concluded that the surge currents will produce significant levels of harmonics and corresponding operating problems during magnetic storms.

  8. Comparing Parameter Estimation Techniques for an Electrical Power Transformer Oil Temperature Prediction Model

    NASA Technical Reports Server (NTRS)

    Morris, A. Terry

    1999-01-01

    This paper examines various sources of error in MIT's improved top oil temperature rise over ambient temperature model and estimation process. The sources of error are the current parameter estimation technique, quantization noise, and post-processing of the transformer data. Results from this paper will show that an output error parameter estimation technique should be selected to replace the current least squares estimation technique. The output error technique obtained accurate predictions of transformer behavior, revealed the best error covariance, obtained consistent parameter estimates, and provided for valid and sensible parameters. This paper will also show that the output error technique should be used to minimize errors attributed to post-processing (decimation) of the transformer data. Models used in this paper are validated using data from a large transformer in service.

  9. Model predictive control system and method for integrated gasification combined cycle power generation

    DOEpatents

    Kumar, Aditya; Shi, Ruijie; Kumar, Rajeeva; Dokucu, Mustafa

    2013-04-09

    Control system and method for controlling an integrated gasification combined cycle (IGCC) plant are provided. The system may include a controller coupled to a dynamic model of the plant to process a prediction of plant performance and determine a control strategy for the IGCC plant over a time horizon subject to plant constraints. The control strategy may include control functionality to meet a tracking objective and control functionality to meet an optimization objective. The control strategy may be configured to prioritize the tracking objective over the optimization objective based on a coordinate transformation, such as an orthogonal or quasi-orthogonal projection. A plurality of plant control knobs may be set in accordance with the control strategy to generate a sequence of coordinated multivariable control inputs to meet the tracking objective and the optimization objective subject to the prioritization resulting from the coordinate transformation.

  10. Validation of the predictive power of a calibrated physical stochastic resist model

    NASA Astrophysics Data System (ADS)

    Robertson, Stewart A.; Biafore, John J.; Smith, Mark D.; Reilly, Michael T.; Wandell, Jerome

    2009-12-01

    A newly developed stochastic resist model, implemented in a prototype version of the PROLITH lithography simulation software is fitted to experimental data for a commercially available immersion ArF photoresist, EPIC 2013 (Dow Electronic Materials). Calibration is performed only considering the mean CD value through focus and dose for three line/space features of varying pitch (dense, semi-dense and isolated). An unweighted Root Mean Squared Error (RMSE) of approximately 2.0 nm is observed when the calibrated model is compared to the experimental data. Although the model is calibrated only to mean CD values, it is able to accurately predict LER through focus to better than 1.5 nm RMSE and highly accurate CDU distributions at fixed focus and dose conditions. It is also shown how a stochastic model can be used to the describe the bridging behavior often observed at marginal focus and exposure conditions.

  11. The future is in the numbers: the power of predictive analysis in the biomedical educational environment.

    PubMed

    Gullo, Charles A

    2016-01-01

    Biomedical programs have a potential treasure trove of data they can mine to assist admissions committees in identification of students who are likely to do well and help educational committees in the identification of students who are likely to do poorly on standardized national exams and who may need remediation. In this article, we provide a step-by-step approach that schools can utilize to generate data that are useful when predicting the future performance of current students in any given program. We discuss the use of linear regression analysis as the means of generating that data and highlight some of the limitations. Finally, we lament on how the combination of these institution-specific data sets are not being fully utilized at the national level where these data could greatly assist programs at large. PMID:27374246

  12. The future is in the numbers: the power of predictive analysis in the biomedical educational environment

    PubMed Central

    Gullo, Charles A.

    2016-01-01

    Biomedical programs have a potential treasure trove of data they can mine to assist admissions committees in identification of students who are likely to do well and help educational committees in the identification of students who are likely to do poorly on standardized national exams and who may need remediation. In this article, we provide a step-by-step approach that schools can utilize to generate data that are useful when predicting the future performance of current students in any given program. We discuss the use of linear regression analysis as the means of generating that data and highlight some of the limitations. Finally, we lament on how the combination of these institution-specific data sets are not being fully utilized at the national level where these data could greatly assist programs at large. PMID:27374246

  13. Using a Simple Binomial Model to Assess Improvement in Predictive Capability: Sequential Bayesian Inference, Hypothesis Testing, and Power Analysis

    SciTech Connect

    Sigeti, David E.; Pelak, Robert A.

    2012-09-11

    We present a Bayesian statistical methodology for identifying improvement in predictive simulations, including an analysis of the number of (presumably expensive) simulations that will need to be made in order to establish with a given level of confidence that an improvement has been observed. Our analysis assumes the ability to predict (or postdict) the same experiments with legacy and new simulation codes and uses a simple binomial model for the probability, {theta}, that, in an experiment chosen at random, the new code will provide a better prediction than the old. This model makes it possible to do statistical analysis with an absolute minimum of assumptions about the statistics of the quantities involved, at the price of discarding some potentially important information in the data. In particular, the analysis depends only on whether or not the new code predicts better than the old in any given experiment, and not on the magnitude of the improvement. We show how the posterior distribution for {theta} may be used, in a kind of Bayesian hypothesis testing, both to decide if an improvement has been observed and to quantify our confidence in that decision. We quantify the predictive probability that should be assigned, prior to taking any data, to the possibility of achieving a given level of confidence, as a function of sample size. We show how this predictive probability depends on the true value of {theta} and, in particular, how there will always be a region around {theta} = 1/2 where it is highly improbable that we will be able to identify an improvement in predictive capability, although the width of this region will shrink to zero as the sample size goes to infinity. We show how the posterior standard deviation may be used, as a kind of 'plan B metric' in the case that the analysis shows that {theta} is close to 1/2 and argue that such a plan B should generally be part of hypothesis testing. All the analysis presented in the paper is done with a general

  14. Space Weather Influence on Power Systems: Prediction, Risk Analysis, and Modeling

    NASA Astrophysics Data System (ADS)

    Yatsenko, Vitaliy

    2016-04-01

    This report concentrates on dynamic probabilistic risk analysis of optical elements for complex characterization of damages using physical model of solid state lasers and predictable level of ionizing radiation and space weather. The following main subjects will be covered by our report: (a) solid-state laser model; (b) mathematical models for dynamic probabilistic risk assessment; and (c) software for modeling and prediction of ionizing radiation. A probabilistic risk assessment method for solid-state lasers is presented with consideration of some deterministic and stochastic factors. Probabilistic risk assessment is a comprehensive, structured, and logical analysis method aimed at identifying and assessing risks in solid-state lasers for the purpose of cost-e®ectively improving their safety and performance. This method based on the Conditional Value-at-Risk measure (CVaR) and the expected loss exceeding Value-at-Risk (VaR). We propose to use a new dynamical-information approach for radiation damage risk assessment of laser elements by cosmic radiation. Our approach includes the following steps: laser modeling, modeling of ionizing radiation in°uences on laser elements, probabilistic risk assessment methods, and risk minimization. For computer simulation of damage processes at microscopic and macroscopic levels the following methods are used: () statistical; (b) dynamical; (c) optimization; (d) acceleration modeling, and (e) mathematical modeling of laser functioning. Mathematical models of space ionizing radiation in°uence on laser elements were developed for risk assessment in laser safety analysis. This is a so-called `black box' or `input-output' models, which seeks only to reproduce the behaviour of the system's output in response to changes in its inputs. The model inputs are radiation in°uences on laser systems and output parameters are dynamical characteristics of the solid laser. Algorithms and software for optimal structure and parameters of

  15. Predictive Power-balance Modeling of PEGASUS and NSTX-U Local Helicity Injection Discharges

    NASA Astrophysics Data System (ADS)

    Barr, J. L.; Bongard, M. W.; Burke, M. G.; Fonck, R. J.; Hinson, E. T.; Perry, J. M.; Redd, A. J.; Schlossberg, D. J.

    2013-10-01

    Local helicity injection (LHI) with outer poloidal-field (PF) induction for solenoid-free startup is being studied on PEGASUS, reaching Ip <= 0 . 175 MA with 6 kA of injected current. A lumped-parameter circuit model for predicting the performance of LHI initiated plasmas is under development. The model employs energy and helicity balance, and includes applied PF ramping and the inductive effects of shape evolution. Low- A formulations for both the plasma external inductance and a uniform equilibrium-field are used to estimate inductive voltages. PEGASUS LHI plasmas are created near the outboard injectors with aspect ratio (A) ~ 5-6.5 and grow inward to fill the confinement region at A <= 1 . 3 . Initial results match experimental Ip (t) trajectories within 15 kA with a prescribed geometry evolution. Helicity injection is the largest driving term in the initial phase, but in the later phase is reduced to 20-45% of the total drive as PF induction and decreasing plasma inductance become dominant. In contrast, attaining ~1 MA non-solenoidal startup via LHI on NSTX-U will require operation in the regime where helicity injection drive exceeds inductive and geometric changes at full size. A large-area multi-injector array will increase available helicity injection by 3-4 times and allow exploration of this helicity-dominated regime at Ip ~ 0 . 3 MA in PEGASUS. Comparison of model predictions with time-evolving magnetic equilibria is in progress for model validation. Work supported by US DOE Grant DE-FG02-96ER54375.

  16. Thermogravimetric analysis coupled with chemometrics as a powerful predictive tool for ß-thalassemia screening.

    PubMed

    Risoluti, Roberta; Materazzi, Stefano; Sorrentino, Francesco; Maffei, Laura; Caprari, Patrizia

    2016-10-01

    β-Thalassemia is a hemoglobin genetic disorder characterized by the absence or reduced β-globin chain synthesis, one of the constituents of the adult hemoglobin tetramer. In this study the possibility of using thermogravimetric analysis (TGA) followed by chemometrics as a new approach for β-thalassemia detection is proposed. Blood samples from patients with β-thalassemia were analyzed by the TG7 thermobalance and the resulting curves were compared to those typical of healthy individuals. Principal Component Analysis (PCA) was used to evaluate the correlation between the hematological parameters and the thermogravimetric results. The thermogravimetric profiles of blood samples from β-thalassemia patients were clearly distinct from those of healthy individuals as result of the different quantities of water content and corpuscular fraction. The hematological overview showed significant decreases in the values of red blood cell indices and an increase in red cell distribution width value in thalassemia subjects when compared with those of healthy subjects. The implementation of a predictive model based on Partial Least Square Discriminant Analysis (PLS-DA) for β-thalassemia diagnosis, was performed and validated. This model permitted the discrimination of anemic patients and healthy individuals and was able to detect thalassemia in clinically heterogeneous patients as in the presence of δβ-thalassemia and β-thalassemia combined with Hb Lepore. TGA and Chemometrics are capable of predicting ß-thalassemia syndromes using only a few microliters of blood without any pretreatment and with an hour of analysis time. A fast, rapid and cost-effective diagnostic tool for the β-thalassemia screening is proposed. PMID:27474327

  17. Feasibility of High-Power Diode Laser Array Surrogate to Support Development of Predictive Laser Lethality Model

    SciTech Connect

    Lowdermilk, W H; Rubenchik, A M; Springer, H K

    2011-01-13

    Predictive modeling and simulation of high power laser-target interactions is sufficiently undeveloped that full-scale, field testing is required to assess lethality of military directed-energy (DE) systems. The cost and complexity of such testing programs severely limit the ability to vary and optimize parameters of the interaction. Thus development of advanced simulation tools, validated by experiments under well-controlled and diagnosed laboratory conditions that are able to provide detailed physics insight into the laser-target interaction and reduce requirements for full-scale testing will accelerate development of DE weapon systems. The ultimate goal is a comprehensive end-to-end simulation capability, from targeting and firing the laser system through laser-target interaction and dispersal of target debris; a 'Stockpile Science' - like capability for DE weapon systems. To support development of advanced modeling and simulation tools requires laboratory experiments to generate laser-target interaction data. Until now, to make relevant measurements required construction and operation of very high power and complex lasers, which are themselves costly and often unique devices, operating in dedicated facilities that don't permit experiments on targets containing energetic materials. High power diode laser arrays, pioneered by LLNL, provide a way to circumvent this limitation, as such arrays capable of delivering irradiances characteristic of De weapon requires are self-contained, compact, light weight and thus easily transportable to facilities, such as the High Explosives Applications Facility (HEAF) at Lawrence Livermore National Laboratory (LLNL) where testing with energetic materials can be performed. The purpose of this study was to establish the feasibility of using such arrays to support future development of advanced laser lethality and vulnerability simulation codes through providing data for materials characterization and laser-material interaction

  18. Optimal launch power prediction of a 100G PM-DQPSK dispersion-managed link with the Gaussian noise model

    NASA Astrophysics Data System (ADS)

    Almeida, Telmo P.; Drummond, Miguel V.; Pavlović, Natasa B.; André, Paulo S.; Nogueira, Rogério N.

    2014-08-01

    Of all the non-linear fiber propagation models proposed over the years, the Gaussian Noise (GN) model is growing in popularity due to its simplicity and yet reliability when it comes to predict performance of uncompensated coherent transmission (UT) systems that rely on state-of-the art digital-signal processing (DSP) for dispersion compensation. However, many of the systems currently deployed rely on optical CD compensation. Overhauling or upgrading these systems with the most recent DSP is not always feasible. In this context, it is important to broad the range of the GNmodel to dispersion managed (DM) systems, so both scenarios can benefit from a low complexity, fast and reliable performance prediction tool. In this paper, we validate the first results comparing the performance in both accuracy and simulation time of the GN model simulating a realistic DM scenario that relies on periodical spans of non-dispersion shifted fiber (NDSF) to perform the dispersion compensation. The same realistic scenarios were modeled with commercial software and the GN model. The objective was to predict the optimal launch power for different link lengths, central wavelengths and channel spacing values. Preliminary results obtained with the GN model are in good agreement with the ones from the commercial software for several link distances tested up to 2400 Km.

  19. Cell-Line Selectivity Improves the Predictive Power of Pharmacogenomic Analyses and Helps Identify NADPH as Biomarker for Ferroptosis Sensitivity.

    PubMed

    Shimada, Kenichi; Hayano, Miki; Pagano, Nen C; Stockwell, Brent R

    2016-02-18

    Precision medicine in oncology requires not only identification of cancer-associated mutations but also effective drugs for each cancer genotype, which is still a largely unsolved problem. One approach for the latter challenge has been large-scale testing of small molecules in genetically characterized cell lines. We hypothesized that compounds with high cell-line-selective lethality exhibited consistent results across such pharmacogenomic studies. We analyzed the compound sensitivity data of 6,259 lethal compounds from the NCI-60 project. A total of 2,565 cell-line-selective lethal compounds were identified and grouped into 18 clusters based on their median growth inhibitory GI50 profiles across the 60 cell lines, which were shown to represent distinct mechanisms of action. Further transcriptome analysis revealed a biomarker, NADPH abundance, for predicting sensitivity to ferroptosis-inducing compounds, which we experimentally validated. In summary, incorporating cell-line-selectivity filters improves the predictive power of pharmacogenomic analyses and enables discovery of biomarkers that predict the sensitivity of cells to specific cell death inducers. PMID:26853626

  20. Experimental verification of ion stopping power prediction from dual energy CT data in tissue surrogates

    NASA Astrophysics Data System (ADS)

    Farace, Paolo

    2014-11-01

    A two-steps procedure is presented to convert dual-energy CT data to stopping power ratio (SPR), relative to water. In the first step the relative electron density (RED) is calculated from dual-energy CT-numbers by means of a bi-linear relationship: RED = a HUscH + b HUscL + c, where HUscH and HUscL are scaled units (HUsc = HU + 1000) acquired at high and low energy respectively, and the three parameters a, b and c has to be determined for each CT scanner. In the second step the RED values were converted into SPR by means of published poly-line functions, which are invariant as they do not depend on a specific CT scanner. The comparison with other methods provides encouraging results, with residual SPR error on human tissue within 1%. The distinctive features of the proposed method are its simplicity and the generality of the conversion functions.

  1. Prediction of Corrosion Fatigue Damages for Turbine Blades Subjecting to Randomly Distributed Power System Unbalance

    NASA Astrophysics Data System (ADS)

    Lin, Chi-Hshiung

    In this paper, a fatigue damage estimation procedure is implemented by integrating the results of an EPRI and a GE testing reports as well as a shareware developed by the Oslo University, which is incorporated with a verified transient simulation program developed by the Aberdeen University to study the effects of power system unbalance on turbine blade damaging. Based on the Weibull distribution in the negative sequence current (I2) and the operational environment containing 22% NaCl, the probability level of fatigue life as well as the reliability against fatigue failure for the long blades of low-pressure (LP) turbine are evaluated. It is shown that even though the blades could withstand the most serious impact arising from three-phase-to-ground fault, still it cannot guarantee adequate long-term reliability in the normal operational condition.

  2. On the impact of power corrections in the prediction of B → K *μ+μ- observables

    NASA Astrophysics Data System (ADS)

    Descotes-Genon, Sébastien; Hofer, Lars; Matias, Joaquim; Virto, Javier

    2014-12-01

    The recent LHCb angular analysis of the exclusive decay B → K * μ + μ - has indicated significant deviations from the Standard Model expectations. Accurate predictions can be achieved at large K *-meson recoil for an optimised set of observables designed to have no sensitivity to hadronic input in the heavy-quark limit at leading order in α s . However, hadronic uncertainties reappear through non-perturbative ΛQCD /m b power corrections, which must be assessed precisely. In the framework of QCD factorisation we present a systematic method to include factorisable power corrections and point out that their impact on angular observables depends on the scheme chosen to define the soft form factors. Associated uncertainties are found to be under control, contrary to earlier claims in the literature. We also discuss the impact of possible non-factorisable power corrections, including an estimate of charm-loop effects. We provide results for angular observables at large recoil for two different sets of inputs for the form factors, spelling out the different sources of theoretical uncertainties. Finally, we comment on a recent proposal to explain the anomaly in B → K * μ + μ - observables through charm-resonance effects, and we propose strategies to test this proposal identifying observables and kinematic regions where either the charm-loop model can be disentangled from New Physics effects or the two options leave different imprints.

  3. A new method to predict the evolution of the power spectral density for a finite-amplitude sound wave

    NASA Astrophysics Data System (ADS)

    Menounou, Penelope; Blackstock, David T.

    2004-02-01

    A method to predict the effect of nonlinearity on the power spectral density of a plane wave traveling in a thermoviscous fluid is presented. As opposed to time-domain methods, the method presented here is based directly on the power spectral density of the signal, not the signal itself. The Burgers equation is employed for the mathematical description of the combined effects of nonlinearity and dissipation. The Burgers equation is transformed into an infinite set of linear equations that describe the evolution of the joint moments of the signal. A method for solving this system of equations is presented. Only a finite number of equations is appropriately selected and solved by numerical means. For the method to be applied all appropriate joint moments must be known at the source. If the source condition has Gaussian characteristics (it is a Gaussian noise signal or a Gaussian stationary and ergodic stochastic process), then all the joint moments can be computed from the power spectral density of the signal at the source. Numerical results from the presented method are shown to be in good agreement with known analytical solutions in the preshock region for two benchmark cases: (i) sinusoidal source signal and (ii) a Gaussian stochastic process as the source condition.

  4. Broad climatological variation of surface energy balance partitioning across land and ocean predicted from the maximum power limit

    NASA Astrophysics Data System (ADS)

    Dhara, Chirag; Renner, Maik; Kleidon, Axel

    2016-07-01

    Longwave radiation and turbulent heat fluxes are the mechanisms by which the Earth's surface transfers heat into the atmosphere, thus affecting the surface temperature. However, the energy partitioning between the radiative and turbulent components is poorly constrained by energy and mass balances alone. We use a simple energy balance model with the thermodynamic limit of maximum power as an additional constraint to determine this partitioning. Despite discrepancies over tropical oceans, we find that the broad variation of heat fluxes and surface temperatures in the ERA-Interim reanalyzed observations can be recovered from this approach. The estimates depend considerably on the formulation of longwave radiative transfer, and a spatially uniform offset is related to the assumed cold temperature sink at which the heat engine operates. Our results suggest that the steady state surface energy partitioning may reflect the maximum power constraint.

  5. Testing projected wild bee distributions in agricultural habitats: predictive power depends on species traits and habitat type.

    PubMed

    Marshall, Leon; Carvalheiro, Luísa G; Aguirre-Gutiérrez, Jesús; Bos, Merijn; de Groot, G Arjen; Kleijn, David; Potts, Simon G; Reemer, Menno; Roberts, Stuart; Scheper, Jeroen; Biesmeijer, Jacobus C

    2015-10-01

    Species distribution models (SDM) are increasingly used to understand the factors that regulate variation in biodiversity patterns and to help plan conservation strategies. However, these models are rarely validated with independently collected data and it is unclear whether SDM performance is maintained across distinct habitats and for species with different functional traits. Highly mobile species, such as bees, can be particularly challenging to model. Here, we use independent sets of occurrence data collected systematically in several agricultural habitats to test how the predictive performance of SDMs for wild bee species depends on species traits, habitat type, and sampling technique. We used a species distribution modeling approach parametrized for the Netherlands, with presence records from 1990 to 2010 for 193 Dutch wild bees. For each species, we built a Maxent model based on 13 climate and landscape variables. We tested the predictive performance of the SDMs with independent datasets collected from orchards and arable fields across the Netherlands from 2010 to 2013, using transect surveys or pan traps. Model predictive performance depended on species traits and habitat type. Occurrence of bee species specialized in habitat and diet was better predicted than generalist bees. Predictions of habitat suitability were also more precise for habitats that are temporally more stable (orchards) than for habitats that suffer regular alterations (arable), particularly for small, solitary bees. As a conservation tool, SDMs are best suited to modeling rarer, specialist species than more generalist and will work best in long-term stable habitats. The variability of complex, short-term habitats is difficult to capture in such models and historical land use generally has low thematic resolution. To improve SDMs' usefulness, models require explanatory variables and collection data that include detailed landscape characteristics, for example, variability of crops and

  6. Bacterial Resistance Studies Using In Vitro Dynamic Models: the Predictive Power of the Mutant Prevention and Minimum Inhibitory Antibiotic Concentrations

    PubMed Central

    Strukova, Elena N.; Shlykova, Darya S.; Portnoy, Yury A.; Kozyreva, Varvara K.; Edelstein, Mikhail V.; Dovzhenko, Svetlana A.; Kobrin, Mikhail B.; Zinner, Stephen H.

    2013-01-01

    In light of the concept of the mutant selection window, i.e., the range between the MIC and the mutant prevention concentration (MPC), MPC-related pharmacokinetic indices should be more predictive of bacterial resistance than the respective MIC-related indices. However, experimental evidence of this hypothesis remains limited and contradictory. To examine the predictive power of the ratios of the area under the curve (AUC24) to the MPC and the MIC, the selection of ciprofloxacin-resistant mutants of four Escherichia coli strains with different MPC/MIC ratios was studied. Each organism was exposed to twice-daily ciprofloxacin for 3 days at AUC24/MIC ratios that provide peak antibiotic concentrations close to the MIC, between the MIC and the MPC, and above the MPC. Resistant E. coli was intensively enriched at AUC24/MPCs from 1 to 10 h (AUC24/MIC from 60 to 360 h) but not at the lower or higher AUC24/MPC and AUC24/MIC ratios. AUC24/MPC and AUC24/MIC relationships of the areas under the time courses of ciprofloxacin-resistant E. coli (AUBCM) were bell-shaped. A Gaussian-like function fits the AUBCM-AUC24/MPC and AUBCM-AUC24/MIC data combined for all organisms (r2 = 0.69 and 0.86, respectively). The predicted anti-mutant AUC24/MPC ratio was 58 ± 35 h, and the respective AUC24/MIC ratio was 1,080 ± 416 h. Although AUC24/MPC was less predictive of strain-independent E. coli resistance than AUC24/MIC, the established anti-mutant AUC24/MPC ratio was closer to values reported for Staphylococcus aureus (60 to 69 h) than the respective AUC24/MIC ratio (1,080 versus 200 to 240 h). This implies that AUC24/MPC might be a better interspecies predictor of bacterial resistance than AUC24/MIC. PMID:23896481

  7. Energy-Efficient Control with Harvesting Predictions for Solar-Powered Wireless Sensor Networks.

    PubMed

    Zou, Tengyue; Lin, Shouying; Feng, Qijie; Chen, Yanlian

    2016-01-01

    Wireless sensor networks equipped with rechargeable batteries are useful for outdoor environmental monitoring. However, the severe energy constraints of the sensor nodes present major challenges for long-term applications. To achieve sustainability, solar cells can be used to acquire energy from the environment. Unfortunately, the energy supplied by the harvesting system is generally intermittent and considerably influenced by the weather. To improve the energy efficiency and extend the lifetime of the networks, we propose algorithms for harvested energy prediction using environmental shadow detection. Thus, the sensor nodes can adjust their scheduling plans accordingly to best suit their energy production and residual battery levels. Furthermore, we introduce clustering and routing selection methods to optimize the data transmission, and a Bayesian network is used for warning notifications of bottlenecks along the path. The entire system is implemented on a real-time Texas Instruments CC2530 embedded platform, and the experimental results indicate that these mechanisms sustain the networks' activities in an uninterrupted and efficient manner. PMID:26742042

  8. Energy-Efficient Control with Harvesting Predictions for Solar-Powered Wireless Sensor Networks

    PubMed Central

    Zou, Tengyue; Lin, Shouying; Feng, Qijie; Chen, Yanlian

    2016-01-01

    Wireless sensor networks equipped with rechargeable batteries are useful for outdoor environmental monitoring. However, the severe energy constraints of the sensor nodes present major challenges for long-term applications. To achieve sustainability, solar cells can be used to acquire energy from the environment. Unfortunately, the energy supplied by the harvesting system is generally intermittent and considerably influenced by the weather. To improve the energy efficiency and extend the lifetime of the networks, we propose algorithms for harvested energy prediction using environmental shadow detection. Thus, the sensor nodes can adjust their scheduling plans accordingly to best suit their energy production and residual battery levels. Furthermore, we introduce clustering and routing selection methods to optimize the data transmission, and a Bayesian network is used for warning notifications of bottlenecks along the path. The entire system is implemented on a real-time Texas Instruments CC2530 embedded platform, and the experimental results indicate that these mechanisms sustain the networks’ activities in an uninterrupted and efficient manner. PMID:26742042

  9. Modeling PHA-producing microbial enrichment cultures--towards a generalized model with predictive power.

    PubMed

    Tamis, Jelmer; Marang, Leonie; Jiang, Yang; van Loosdrecht, Mark C M; Kleerebezem, Robbert

    2014-06-25

    Polyhydroxyalkanoate (PHA) production from waste streams using microbial enrichment cultures is a promising option for cost price reduction of this biopolymer. For proper understanding and successful optimization of the process, a consistent mechanistic model for PHA conversion by microbial enrichment cultures is needed. However, there is still a lack of mechanistic expressions describing the dynamics of the feast-famine process. The scope of this article is to provide an overview of the current models, investigate points of improvement, and contribute concepts for creation of a generalized model with more predictive value for the feast-famine process. Based on experimental data available in literature we have proposed model improvements for (i) modeling mixed substrates uptake, (ii) growth in the feast phase, (iii) switching between feast and famine phase, (iv) PHA degradation and (v) modeling the accumulation phase. Finally, we provide an example of a simple uniform model. Herewith we aim to give an impulse to the establishment of a generalized model. PMID:24333144

  10. Liquidity crisis detection: An application of log-periodic power law structures to default prediction

    NASA Astrophysics Data System (ADS)

    Wosnitza, Jan Henrik; Denz, Cornelia

    2013-09-01

    We employ the log-periodic power law (LPPL) to analyze the late-2000 financial crisis from the perspective of critical phenomena. The main purpose of this study is to examine whether LPPL structures in the development of credit default swap (CDS) spreads can be used for default classification. Based on the different triggers of Bear Stearns’ near bankruptcy during the late-2000 financial crisis and Ford’s insolvency in 2009, this study provides a quantitative description of the mechanism behind bank runs. We apply the Johansen-Ledoit-Sornette (JLS) positive feedback model to explain the rise of financial institutions’ CDS spreads during the global financial crisis 2007-2009. This investigation is based on CDS spreads of 40 major banks over the period from June 2007 to April 2009 which includes a significant CDS spread increase. The qualitative data analysis indicates that the CDS spread variations have followed LPPL patterns during the global financial crisis. Furthermore, the univariate classification performances of seven LPPL parameters as default indicators are measured by Mann-Whitney U tests. The present study supports the hypothesis that discrete scale-invariance governs the dynamics of financial markets and suggests the application of new and fast updateable default indicators to capture the buildup of long-range correlations between creditors.

  11. Experimental verification of ion stopping power prediction from dual energy CT data in tissue surrogates.

    PubMed

    Farace, Paolo

    2014-11-21

    A two-steps procedure is presented to convert dual-energy CT data to stopping power ratio (SPR), relative to water. In the first step the relative electron density (RED) is calculated from dual-energy CT-numbers by means of a bi-linear relationship: RED=a HUscH+b HUscL+c, where HUscH and HUscL are scaled units (HUsc=HU+1000) acquired at high and low energy respectively, and the three parameters a, b and c has to be determined for each CT scanner. In the second step the RED values were converted into SPR by means of published poly-line functions, which are invariant as they do not depend on a specific CT scanner. The comparison with other methods provides encouraging results, with residual SPR error on human tissue within 1%. The distinctive features of the proposed method are its simplicity and the generality of the conversion functions. PMID:25360874

  12. Market Powers Predict Reciprocal Grooming in Golden Snub-Nosed Monkeys (Rhinopithecus roxellana)

    PubMed Central

    Guo, Song-Tao; Zhao, Da-Peng; Zhang, Peng; Huang, Kang; Li, Bao-Guo

    2012-01-01

    Social grooming is a common form of affiliative behavior in primates. Biological market theory suggests that grooming can be traded either for grooming or other social commodities and services. When no other services are exchanged, grooming is predicted to be approximately reciprocated within a dyad. In contrast, the amount of reciprocal grooming should decrease as other offered services increase. We studied grooming patterns between polygamous male and female in golden snub-nosed monkeys (Rhinopithecus roxellana) from the Qinling Mountains of central China and found that about 29.7% of grooming bouts were reciprocated. However, the durations of grooming bouts offered and returned was asymmetrical within dyads. In bisexual dyads, more grooming was initiated by females than males, which became more pronounced as the number of females per one-male unit increased. The rate of copulation per day for each female was positively correlated with the total duration of grooming time females invested in males.. Females without an infant (non-mothers) directed more grooming towards females with an infant (mothers) and were significantly more likely to be non-reciprocated. There was a significant negative relationship between non-mother and mother grooming duration and the rate of infants per female in each one-male unit. High-ranking females also received more grooming from low-ranking females than vice versa. The rate of food-related aggressive interactions was per day for low-ranking females was negatively correlated with the duration of grooming that low-ranking females gave to high-ranking females. Our results showed that grooming reciprocation in R. roxellana was discrepancy. This investment-reciprocity rate could be explained by the exchange of other social services in lieu of grooming. PMID:22590611

  13. Worldwide impact of aerosol’s time scale on the predicted long-term concentrating solar power potential

    NASA Astrophysics Data System (ADS)

    Ruiz-Arias, Jose A.; Gueymard, Christian A.; Santos-Alamillos, Francisco J.; Pozo-Vázquez, David

    2016-08-01

    Concentrating solar technologies, which are fuelled by the direct normal component of solar irradiance (DNI), are among the most promising solar technologies. Currently, the state-of the-art methods for DNI evaluation use datasets of aerosol optical depth (AOD) with only coarse (typically monthly) temporal resolution. Using daily AOD data from both site-specific observations at ground stations as well as gridded model estimates, a methodology is developed to evaluate how the calculated long-term DNI resource is affected by using AOD data averaged over periods from 1 to 30 days. It is demonstrated here that the use of monthly representations of AOD leads to systematic underestimations of the predicted long-term DNI up to 10% in some areas with high solar resource, which may result in detrimental consequences for the bankability of concentrating solar power projects. Recommendations for the use of either daily or monthly AOD data are provided on a geographical basis.

  14. Worldwide impact of aerosol’s time scale on the predicted long-term concentrating solar power potential

    PubMed Central

    Ruiz-Arias, Jose A.; Gueymard, Christian A.; Santos-Alamillos, Francisco J.; Pozo-Vázquez, David

    2016-01-01

    Concentrating solar technologies, which are fuelled by the direct normal component of solar irradiance (DNI), are among the most promising solar technologies. Currently, the state-of the-art methods for DNI evaluation use datasets of aerosol optical depth (AOD) with only coarse (typically monthly) temporal resolution. Using daily AOD data from both site-specific observations at ground stations as well as gridded model estimates, a methodology is developed to evaluate how the calculated long-term DNI resource is affected by using AOD data averaged over periods from 1 to 30 days. It is demonstrated here that the use of monthly representations of AOD leads to systematic underestimations of the predicted long-term DNI up to 10% in some areas with high solar resource, which may result in detrimental consequences for the bankability of concentrating solar power projects. Recommendations for the use of either daily or monthly AOD data are provided on a geographical basis. PMID:27507711

  15. Efficacy of changing physics misconceptions held by ninth grade students at varying developmental levels through teacher addition of a prediction phase to the learning cycle

    NASA Astrophysics Data System (ADS)

    Oglesby, Michael L.

    This study examines the efficacy in correcting student misconceptions about science concepts by using the pedagogical method of asking students to make a prediction in science laboratory lessons for students within pre-formal, transitional, or formal stages of cognitive development. The subjects were students (n = 235) enrolled in ninth grade physical science classes (n=15) in one high school of an urban profile school district. The four freshmen physical science teachers who were part of the study routinely taught the concepts in the study as a part of the normal curriculum during the time of the school year in which the research was conducted. Classrooms representing approximately half of the students were presented with a prediction phase at the start of each of ten learning cycle lesson. The other classrooms were not presented with a prediction phase. Students were pre and post tested using a 40 question instrument based on the Force Concept Inventory augmented with questions on the concepts taught during the period of the study. Students were also tested using the Test of Scientific Reasoning to determine their cognitive developmental level. Results showed 182 of the students to be cognitively pre-formal, 50 to be transitional, and only 3 to be cognitively formal. There were significantly higher gains (p < .05) for the formal group over the transitional group and for the transitional group over the Pre-formal group. However, there were not significantly higher gains (p > .05) for the total students having a prediction phase compared to those not having a prediction phase. Neither were there significant gains (p > .05) within the pre-formal group or within the transitional group. There were too few students within the formal group for meaningful results.

  16. A cascaded QSAR model for efficient prediction of overall power conversion efficiency of all-organic dye-sensitized solar cells.

    PubMed

    Li, Hongzhi; Zhong, Ziyan; Li, Lin; Gao, Rui; Cui, Jingxia; Gao, Ting; Hu, Li Hong; Lu, Yinghua; Su, Zhong-Min; Li, Hui

    2015-05-30

    A cascaded model is proposed to establish the quantitative structure-activity relationship (QSAR) between the overall power conversion efficiency (PCE) and quantum chemical molecular descriptors of all-organic dye sensitizers. The cascaded model is a two-level network in which the outputs of the first level (JSC, VOC, and FF) are the inputs of the second level, and the ultimate end-point is the overall PCE of dye-sensitized solar cells (DSSCs). The model combines quantum chemical methods and machine learning methods, further including quantum chemical calculations, data division, feature selection, regression, and validation steps. To improve the efficiency of the model and reduce the redundancy and noise of the molecular descriptors, six feature selection methods (multiple linear regression, genetic algorithms, mean impact value, forward selection, backward elimination, and +n-m algorithm) are used with the support vector machine. The best established cascaded model predicts the PCE values of DSSCs with a MAE of 0.57 (%), which is about 10% of the mean value PCE (5.62%). The validation parameters according to the OECD principles are R(2) (0.75), Q(2) (0.77), and Qcv2 (0.76), which demonstrate the great goodness-of-fit, predictivity, and robustness of the model. Additionally, the applicability domain of the cascaded QSAR model is defined for further application. This study demonstrates that the established cascaded model is able to effectively predict the PCE for organic dye sensitizers with very low cost and relatively high accuracy, providing a useful tool for the design of dye sensitizers with high PCE. PMID:25773984

  17. Predicting the ultimate potential of natural gas SOFC power cycles with CO2 capture - Part A: Methodology and reference cases

    NASA Astrophysics Data System (ADS)

    Campanari, Stefano; Mastropasqua, Luca; Gazzani, Matteo; Chiesa, Paolo; Romano, Matteo C.

    2016-08-01

    Driven by the search for the highest theoretical efficiency, in the latest years several studies investigated the integration of high temperature fuel cells in natural gas fired power plants, where fuel cells are integrated with simple or modified Brayton cycles and/or with additional bottoming cycles, and CO2 can be separated via chemical or physical separation, oxy-combustion and cryogenic methods. Focusing on Solid Oxide Fuel Cells (SOFC) and following a comprehensive review and analysis of possible plant configurations, this work investigates their theoretical potential efficiency and proposes two ultra-high efficiency plant configurations based on advanced intermediate-temperature SOFCs integrated with a steam turbine or gas turbine cycle. The SOFC works at atmospheric or pressurized conditions and the resulting power plant exceeds 78% LHV efficiency without CO2 capture (as discussed in part A of the work) and 70% LHV efficiency with substantial CO2 capture (part B). The power plants are simulated at the 100 MW scale with a complete set of realistic assumptions about fuel cell (FC) performance, plant components and auxiliaries, presenting detailed energy and material balances together with a second law analysis.

  18. Predicting the ultimate potential of natural gas SOFC power cycles with CO2 capture - Part A: Methodology and reference cases

    NASA Astrophysics Data System (ADS)

    Campanari, Stefano; Mastropasqua, Luca; Gazzani, Matteo; Chiesa, Paolo; Romano, Matteo C.

    2016-08-01

    Driven by the search for the highest theoretical efficiency, in the latest years several studies investigated the integration of high temperature fuel cells in natural gas fired power plants, where fuel cells are integrated with simple or modified Brayton cycles and/or with additional bottoming cycles, and CO2 can be separated via chemical or physical separation, oxy-combustion and cryogenic methods. Focusing on Solid Oxide Fuel Cells (SOFC) and following a comprehensive review and analysis of possible plant configurations, this work investigates their theoretical potential efficiency and proposes two ultra-high efficiency plant configurations based on advanced intermediate-temperature SOFCs integrated with a steam turbine or gas turbine cycle. The SOFC works at atmospheric or pressurized conditions and the resulting power plant exceeds 78% LHV efficiency without CO2 capture (as discussed in part A of the work) and 70% LHV efficiency with substantial CO2 capture (part B). The power plants are simulated at the 100 MW scale with a complete set of realistic assumptions about fuel cell (FC) performance, plant components and auxiliaries, presenting detailed energy and material balances together with a second law analysis.

  19. Food additives

    MedlinePlus

    Food additives are substances that become part of a food product when they are added during the processing or making of that food. "Direct" food additives are often added during processing to: Add nutrients ...

  20. The Predictive Power of Serum α-Fetoprotein and Des-γ-Carboxy Prothrombin for Survival Varies by Tumor Size in Hepatocellular Carcinoma.

    PubMed

    Tsugawa, Daisuke; Fukumoto, Takumi; Kido, Masahiro; Takebe, Atsushi; Tanaka, Motofumi; Kuramitsu, Kaori; Matsumoto, Ippei; Ajiki, Tetsuo; Koyama, Tatsuki; Ku, Yonson

    2016-01-01

    Alpha-fetoprotein (AFP) and des-γ-carboxy prothrombin (DCP) are frequently used as tumor markers in hepatocellular carcinoma (HCC). The authors hypothesized different patient populations with varying tumor sizes would influence the predictive power of tumor markers for survival in HCC patients. The authors investigated the influence of tumor size on predictive powers of AFP and DCP. 181 patients underwent hepatectomy for HCC from 2003 to 2008 at Kobe University Hospital. Tumor markers were measured before and at 1 month post-hepatectomy. The Cox proportional-hazards model revealed that preoperative serum AFP was associated with survival; its effects depended on tumor size. Hazard ratios (HRs) for preoperative AFP were maximum for medium-sized HCC, and for DCP, HRs were maximum in small-sized tumors. Post-hepatectomy, both tumor markers were associated with survival, revealing significant interactions with tumor size. HRs for postoperative AFP were greater than 1 for relatively wide range tumors (3-11 cm). HRs for postoperative DCP increased with tumor size, with a strong prognostic predictive power for tumors >5 cm. The predictive power of serum tumor markers varied by tumor size in HCC patients. By selecting the appropriate tumor marker, its predictive power can be improved. PMID:27363395

  1. Food additives

    PubMed Central

    Spencer, Michael

    1974-01-01

    Food additives are discussed from the food technology point of view. The reasons for their use are summarized: (1) to protect food from chemical and microbiological attack; (2) to even out seasonal supplies; (3) to improve their eating quality; (4) to improve their nutritional value. The various types of food additives are considered, e.g. colours, flavours, emulsifiers, bread and flour additives, preservatives, and nutritional additives. The paper concludes with consideration of those circumstances in which the use of additives is (a) justified and (b) unjustified. PMID:4467857

  2. Crying without a cause and being easily upset in two-year-olds: heritability and predictive power of behavioral problems.

    PubMed

    Groen-Blokhuis, Maria M; Middeldorp, Christel M; M van Beijsterveldt, Catharina E; Boomsma, Dorret I

    2011-10-01

    In order to estimate the influence of genetic and environmental factors on 'crying without a cause' and 'being easily upset' in 2-year-old children, a large twin study was carried out. Prospective data were available for ~18,000 2-year-old twin pairs from the Netherlands Twin Register. A bivariate genetic analysis was performed using structural equation modeling in the Mx software package. The influence of maternal personality characteristics and demographic and lifestyle factors was tested to identify specific risk factors that may underlie the shared environment of twins. Furthermore, it was tested whether crying without a cause and being easily upset were predictive of later internalizing, externalizing and attention problems. Crying without a cause yielded a heritability estimate of 60% in boys and girls. For easily upset, the heritability was estimated at 43% in boys and 31% in girls. The variance explained by shared environment varied between 35% and 63%. The correlation between crying without a cause and easily upset (r = .36) was explained both by genetic and shared environmental factors. Birth cohort, gestational age, socioeconomic status, parental age, parental smoking behavior and alcohol use during pregnancy did not explain the shared environmental component. Neuroticism of the mother explained a small proportion of the additive genetic, but not of the shared environmental effects for easily upset. Crying without a cause and being easily upset at age 2 were predictive of internalizing, externalizing and attention problems at age 7, with effect sizes of .28-.42. A large influence of shared environmental factors on crying without a cause and easily upset was detected. Although these effects could be specific to these items, we could not explain them by personality characteristics of the mother or by demographic and lifestyle factors, and we recognize that these effects may reflect other maternal characteristics. A substantial influence of genetic factors

  3. Predicting the performance of system for the co-production of Fischer-Tropsch synthetic liquid and power from coal

    SciTech Connect

    Wang, X.; Xiao, Y.; Xu, S.; Guo, Z.

    2008-01-15

    A co-production system based on Fischer-Tropsch (FT) synthesis reactor and gas turbine was simulated and analyzed. Syngas from entrained bed coal gasification was used as feedstock of the low-temperature slurry phase Fischer-Tropsch reactor. Raw synthetic liquid produced was fractioned and upgraded to diesel, gasoline, and liquid petrol gas (LPG). Tail gas composed of unconverted syngas and FT light components was fed to the gas turbine. Supplemental fuel (NG, or refinery mine gas) might be necessary, which was dependent on gas turbine capacity expander through flow capacity, etc. FT yield information was important to the simulation of this co-production system. A correlation model based on Mobil's two step pilot plant was applied. User models that can predict product yields and cooperate with other units were embedded into Aspen plus simulation. Performance prediction of syngas fired gas turbine was the other key of this system. The increase in mass flow through the turbine affects the match between compressor and turbine operating conditions. The calculation was carried out by GS software developed by Politecnico Di Milano and Princeton University. Various cases were investigated to match the FT synthesis island, power island, and gasification island in co-production systems. Effects of CO{sub 2} removal/LPG recovery, co-firing, and CH{sub 4} content variation were studied. Simulation results indicated that more than 50% of input energy was converted to electricity and FT products. Total yield of gasoline, diesel, and LPG was 136-155 g/N m{sup 3} (CO+H{sub 2}). At coal feed of 21.9 kg/s, net electricity exported to the grid was higher than 100 MW. Total production of diesel and gasoline (and LPG) was 118,000 t (134,000 t)/year. Under the economic analysis conditions assumed in this paper the co-production system was economically feasible.

  4. Predicting binaural speech intelligibility using the signal-to-noise ratio in the envelope power spectrum domain.

    PubMed

    Chabot-Leclerc, Alexandre; MacDonald, Ewen N; Dau, Torsten

    2016-07-01

    This study proposes a binaural extension to the multi-resolution speech-based envelope power spectrum model (mr-sEPSM) [Jørgensen, Ewert, and Dau (2013). J. Acoust. Soc. Am. 134, 436-446]. It consists of a combination of better-ear (BE) and binaural unmasking processes, implemented as two monaural realizations of the mr-sEPSM combined with a short-term equalization-cancellation process, and uses the signal-to-noise ratio in the envelope domain (SNRenv) as the decision metric. The model requires only two parameters to be fitted per speech material and does not require an explicit frequency weighting. The model was validated against three data sets from the literature, which covered the following effects: the number of maskers, the masker types [speech-shaped noise (SSN), speech-modulated SSN, babble, and reversed speech], the masker(s) azimuths, reverberation on the target and masker, and the interaural time difference of the target and masker. The Pearson correlation coefficient between the simulated speech reception thresholds and the data across all experiments was 0.91. A model version that considered only BE processing performed similarly (correlation coefficient of 0.86) to the complete model, suggesting that BE processing could be considered sufficient to predict intelligibility in most realistic conditions. PMID:27475146

  5. Food additives.

    PubMed

    Berglund, F

    1978-01-01

    The use of additives to food fulfils many purposes, as shown by the index issued by the Codex Committee on Food Additives: Acids, bases and salts; Preservatives, Antioxidants and antioxidant synergists; Anticaking agents; Colours; Emulfifiers; Thickening agents; Flour-treatment agents; Extraction solvents; Carrier solvents; Flavours (synthetic); Flavour enhancers; Non-nutritive sweeteners; Processing aids; Enzyme preparations. Many additives occur naturally in foods, but this does not exclude toxicity at higher levels. Some food additives are nutrients, or even essential nutritents, e.g. NaCl. Examples are known of food additives causing toxicity in man even when used according to regulations, e.g. cobalt in beer. In other instances, poisoning has been due to carry-over, e.g. by nitrate in cheese whey - when used for artificial feed for infants. Poisonings also occur as the result of the permitted substance being added at too high levels, by accident or carelessness, e.g. nitrite in fish. Finally, there are examples of hypersensitivity to food additives, e.g. to tartrazine and other food colours. The toxicological evaluation, based on animal feeding studies, may be complicated by impurities, e.g. orthotoluene-sulfonamide in saccharin; by transformation or disappearance of the additive in food processing in storage, e.g. bisulfite in raisins; by reaction products with food constituents, e.g. formation of ethylurethane from diethyl pyrocarbonate; by metabolic transformation products, e.g. formation in the gut of cyclohexylamine from cyclamate. Metabolic end products may differ in experimental animals and in man: guanylic acid and inosinic acid are metabolized to allantoin in the rat but to uric acid in man. The magnitude of the safety margin in man of the Acceptable Daily Intake (ADI) is not identical to the "safety factor" used when calculating the ADI. The symptoms of Chinese Restaurant Syndrome, although not hazardous, furthermore illustrate that the whole ADI

  6. Spatial prediction of Soil Organic Carbon contents in croplands, grasslands and forests using environmental covariates and Generalized Additive Models (Southern Belgium)

    NASA Astrophysics Data System (ADS)

    Chartin, Caroline; Stevens, Antoine; van Wesemael, Bas

    2015-04-01

    Providing spatially continuous Soil Organic Carbon data (SOC) is needed to support decisions regarding soil management, and inform the political debate with quantified estimates of the status and change of the soil resource. Digital Soil Mapping techniques are based on relations existing between a soil parameter (measured at different locations in space at a defined period) and relevant covariates (spatially continuous data) that are factors controlling soil formation and explaining the spatial variability of the target variable. This study aimed at apply DSM techniques to recent SOC content measurements (2005-2013) in three different landuses, i.e. cropland, grassland, and forest, in the Walloon region (Southern Belgium). For this purpose, SOC databases of two regional Soil Monitoring Networks (CARBOSOL for croplands and grasslands, and IPRFW for forests) were first harmonized, totalising about 1,220 observations. Median values of SOC content for croplands, grasslands, and forests, are respectively of 12.8, 29.0, and 43.1 g C kg-1. Then, a set of spatial layers were prepared with a resolution of 40 meters and with the same grid topology, containing environmental covariates such as, landuses, Digital Elevation Model and its derivatives, soil texture, C factor, carbon inputs by manure, and climate. Here, in addition to the three classical texture classes (clays, silt, and sand), we tested the use of clays + fine silt content (particles < 20 µm and related to stable carbon fraction) as soil covariate explaining SOC variations. For each of the three land uses (cropland, grassland and forest), a Generalized Additive Model (GAM) was calibrated on two thirds of respective dataset. The remaining samples were assigned to a test set to assess model performance. A backward stepwise procedure was followed to select the relevant environmental covariates using their approximate p-values (the level of significance was set at p < 0.05). Standard errors were estimated for each of

  7. Density Functional Theory-Derived Group Additivity and Linear Scaling Methods for Prediction of Oxygenate Stability on Metal Catalysts. Adsorption of Open-Ring Alcohol and Polyol Dehydrogenation Intermediates on Pt-Based Metals

    SciTech Connect

    Salciccioli, Michael; Chen, Ying; Vlachos, Dion G.

    2010-11-09

    Semiempirical methods for prediction of thermochemical properties of adsorbed oxygenates are developed. Periodic density functional theory calculations are used to study the relative stability of ethanol, ethylene glycol, isopropyl alcohol, and glycerol dehydrogenation intermediates on Pt(111). For ethylene glycol dehydrogenation intermediates, it is found that the thermodynamically favored intermediates at each level of dehydrogenation are as follows: HOCH2CHOH, HOCHCHOH, HOCHCOH, HOCCOH ≈ HOCHCO, HOCCO, OCCO. Structural and energetic patterns emerge from these C2HxO2 adsorption calculations that lead to the formation of group additive properties for thermochemical property prediction of oxygenates on Pt(111). Finally, linear scaling relationships of atomic binding energy are used to predict the binding energy of the C2HxO2 species on the Ni(111) surface and Ni-Pt-Pt(111) bimetallic surface. It is shown that the linear scaling relationships can accurately predict the binding energy of larger oxygenates as well as of oxygenates on bimetallic catalysts. Corrections for ring strain and weak oxygen-metal and hydrogen-bonding interactions are added to increase the accuracy of group additivity and linear scaling relationships.

  8. Multigene phylogenetic reconstruction of the Tubulinea (Amoebozoa) corroborates four of the six major lineages, while additionally revealing that shell composition does not predict phylogeny in the Arcellinida.

    PubMed

    Lahr, Daniel J G; Grant, Jessica R; Katz, Laura A

    2013-05-01

    Tubulinea is a phylogenetically stable higher-level taxon within Amoebozoa, morphologically characterized by monoaxially streaming and cylindrical pseudopods. Contemporary phylogenetic reconstructions have largely relied on SSU rDNA, and to a lesser extent, on actin genes to reveal the relationships among these organisms. Additionally, the test (shell) forming Arcellinida, one of the most species-rich amoebozoan groups, is nested within Tubulinea and suffers from substantial under-sampling of taxa. Here, we increase taxonomic and gene sampling within the Tubulinea, characterizing molecular data for 22 taxa and six genes (SSU rDNA, actin, α- and β-tubulin, elongation factor 2 and the 14-3-3 regulatory protein). We perform concatenated phylogenetic analyses using these genes as well as approximately unbiased tests to assess evolutionary relationships within the Tubulinea. We confirm the monophyly of Tubulinea and four of the six included lineages (Echinamoeboidea, Leptomyxida, Amoebida and Poseidonida). Arcellinida and Hartmanellidae, the remaining lineages, are not monophyletic in our reconstructions, although statistical testing does not allow rejection of either group. We further investigate more fine-grained morphological evolution of previously defined groups, concluding that relationships within Arcellinida are more consistent with general test and aperture shape than with test composition. We also discuss the implications of this phylogeny for interpretations of the Precambrian fossil record of testate amoebae. PMID:23499265

  9. Predicting Unprotected Sex and Unplanned Pregnancy among Urban African-American Adolescent Girls Using the Theory of Gender and Power.

    PubMed

    Rosenbaum, Janet E; Zenilman, Jonathan; Rose, Eve; Wingood, Gina; DiClemente, Ralph

    2016-06-01

    Reproductive coercion has been hypothesized as a cause of unprotected sex and unplanned pregnancies, but research has focused on a narrow set of potential sources of reproductive coercion. We identified and evaluated eight potential sources of reproductive coercion from the Theory of Gender and Power including economic inequality between adolescent girls and their boyfriends, cohabitation, and age differences. The sample comprised sexually active African-American female adolescents, ages 15-21. At baseline (n = 715), 6 months (n = 607), and 12 months (n = 605), participants completed a 40-min interview and were tested for semen Y-chromosome with polymerase chain reaction from a self-administered vaginal swab. We predicted unprotected sex and pregnancy using multivariate regression controlling for demographics, economic factors, relationship attributes, and intervention status using a Poisson working model. Factors associated with unprotected sex included cohabitation (incidence risk ratio (IRR) 1.48, 95 % confidence interval (1.22, 1.81)), physical abuse (IRR 1.55 (1.21, 2.00)), emotional abuse (IRR 1.31 (1.06, 1.63)), and having a boyfriend as a primary source of spending money (IRR 1.18 (1.00, 1.39)). Factors associated with unplanned pregnancy 6 months later included being at least 4 years younger than the boyfriend (IRR 1.68 (1.14, 2.49)) and cohabitation (2.19 (1.35, 3.56)). Among minors, cohabitation predicted even larger risks of unprotected sex (IRR 1.93 (1.23, 3.03)) and unplanned pregnancy (3.84 (1.47, 10.0)). Adolescent cohabitation is a marker for unprotected sex and unplanned pregnancy, especially among minors. Cohabitation may have stemmed from greater commitment, but the shortage of affordable housing in urban areas could induce women to stay in relationships for housing. Pregnancy prevention interventions should attempt to delay cohabitation until adulthood and help cohabiting adolescents to find affordable housing. PMID:27188460

  10. Potlining Additives

    SciTech Connect

    Rudolf Keller

    2004-08-10

    In this project, a concept to improve the performance of aluminum production cells by introducing potlining additives was examined and tested. Boron oxide was added to cathode blocks, and titanium was dissolved in the metal pool; this resulted in the formation of titanium diboride and caused the molten aluminum to wet the carbonaceous cathode surface. Such wetting reportedly leads to operational improvements and extended cell life. In addition, boron oxide suppresses cyanide formation. This final report presents and discusses the results of this project. Substantial economic benefits for the practical implementation of the technology are projected, especially for modern cells with graphitized blocks. For example, with an energy savings of about 5% and an increase in pot life from 1500 to 2500 days, a cost savings of $ 0.023 per pound of aluminum produced is projected for a 200 kA pot.

  11. Phosphazene additives

    SciTech Connect

    Harrup, Mason K; Rollins, Harry W

    2013-11-26

    An additive comprising a phosphazene compound that has at least two reactive functional groups and at least one capping functional group bonded to phosphorus atoms of the phosphazene compound. One of the at least two reactive functional groups is configured to react with cellulose and the other of the at least two reactive functional groups is configured to react with a resin, such as an amine resin of a polycarboxylic acid resin. The at least one capping functional group is selected from the group consisting of a short chain ether group, an alkoxy group, or an aryloxy group. Also disclosed are an additive-resin admixture, a method of treating a wood product, and a wood product.

  12. An Evaluation of the Additional Acoustic Power Needed to Overcome the Effects of a Test-Articles Absorption During Reverberant Chamber Acoustic Testing of Spaceflight Hardware

    NASA Technical Reports Server (NTRS)

    Hozman, Aron D.; Hughes, William O.

    2014-01-01

    It is important to realize that some test-articles may have significant sound absorption that may challenge the acoustic power capabilities of a test facility. Therefore, to mitigate this risk of not being able to meet the customers target spectrum, it is prudent to demonstrate early-on an increased acoustic power capability which compensates for this test-article absorption. This paper describes a concise method to reduce this risk when testing aerospace test-articles which have significant absorption. This method was successfully applied during the SpaceX Falcon 9 Payload Fairing acoustic test program at the NASA Glenn Research Center Plum Brook Stations RATF.

  13. Validation of the Predicted Circumferential and Radial Mode Sound Power Levels in the Inlet and Exhaust Ducts of a Fan Ingesting Distorted Inflow

    NASA Technical Reports Server (NTRS)

    Koch, L. Danielle

    2012-01-01

    Fan inflow distortion tone noise has been studied computationally and experimentally. Data from two experiments in the NASA Glenn Advanced Noise Control Fan rig have been used to validate acoustic predictions. The inflow to the fan was distorted by cylindrical rods inserted radially into the inlet duct one rotor chord length upstream of the fan. The rods were arranged in both symmetric and asymmetric circumferential patterns. In-duct and farfield sound pressure level measurements were recorded. It was discovered that for positive circumferential modes, measured circumferential mode sound power levels in the exhaust duct were greater than those in the inlet duct and for negative circumferential modes, measured total circumferential mode sound power levels in the exhaust were less than those in the inlet. Predicted trends in overall sound power level were proven to be useful in identifying circumferentially asymmetric distortion patterns that reduce overall inlet distortion tone noise, as compared to symmetric arrangements of rods. Detailed comparisons between the measured and predicted radial mode sound power in the inlet and exhaust duct indicate limitations of the theory.

  14. A Hierarchical Examination of the Immigrant Achievement Gap: The Additional Explanatory Power of Nationality and Educational Selectivity over Traditional Explorations of Race and Socioeconomic Status

    ERIC Educational Resources Information Center

    Simms, Kathryn

    2012-01-01

    This study compared immigrant and nonimmigrant educational achievement (i.e., the immigrant gap) in math by reexamining the explanatory power of race and socioeconomic status (SES)--two variables, perhaps, most commonly considered in educational research. Four research questions were explored through growth curve modeling, factor analysis, and…

  15. Jet Power and Black Hole Spin: Testing an Empirical Relationship and Using it to Predict the Spins of Six Black Holes

    NASA Astrophysics Data System (ADS)

    Steiner, James F.; McClintock, Jeffrey E.; Narayan, Ramesh

    2013-01-01

    Using 5 GHz radio luminosity at light-curve maximum as a proxy for jet power and black hole spin measurements obtained via the continuum-fitting method, Narayan & McClintock presented the first direct evidence for a relationship between jet power and black hole spin for four transient black hole binaries. We test and confirm their empirical relationship using a fifth source, H1743-322, whose spin was recently measured. We show that this relationship is consistent with Fe-line spin measurements provided that the black hole spin axis is assumed to be aligned with the binary angular momentum axis. We also show that, during a major outburst of a black hole transient, the system reasonably approximates an X-ray standard candle. We further show, using the standard synchrotron bubble model, that the radio luminosity at light-curve maximum is a good proxy for jet kinetic energy. Thus, the observed tight correlation between radio power and black hole spin indicates a strong underlying link between mechanical jet power and black hole spin. Using the fitted correlation between radio power and spin for the above five calibration sources, we predict the spins of six other black holes in X-ray/radio transient systems with low-mass companions. Remarkably, these predicted spins are all relatively low, especially when compared to the high measured spins of black holes in persistent, wind-fed systems with massive companions.

  16. JET POWER AND BLACK HOLE SPIN: TESTING AN EMPIRICAL RELATIONSHIP AND USING IT TO PREDICT THE SPINS OF SIX BLACK HOLES

    SciTech Connect

    Steiner, James F.; McClintock, Jeffrey E.; Narayan, Ramesh

    2013-01-10

    Using 5 GHz radio luminosity at light-curve maximum as a proxy for jet power and black hole spin measurements obtained via the continuum-fitting method, Narayan and McClintock presented the first direct evidence for a relationship between jet power and black hole spin for four transient black hole binaries. We test and confirm their empirical relationship using a fifth source, H1743-322, whose spin was recently measured. We show that this relationship is consistent with Fe-line spin measurements provided that the black hole spin axis is assumed to be aligned with the binary angular momentum axis. We also show that, during a major outburst of a black hole transient, the system reasonably approximates an X-ray standard candle. We further show, using the standard synchrotron bubble model, that the radio luminosity at light-curve maximum is a good proxy for jet kinetic energy. Thus, the observed tight correlation between radio power and black hole spin indicates a strong underlying link between mechanical jet power and black hole spin. Using the fitted correlation between radio power and spin for the above five calibration sources, we predict the spins of six other black holes in X-ray/radio transient systems with low-mass companions. Remarkably, these predicted spins are all relatively low, especially when compared to the high measured spins of black holes in persistent, wind-fed systems with massive companions.

  17. An Evaluation of the Additional Acoustic Power Needed to Overcome the Effects of a Test-Article's Absorption During Reverberant Chamber Acoustic Testing of Spaceflight Hardware

    NASA Technical Reports Server (NTRS)

    Hozman, Aron D.; Hughes, William O.

    2014-01-01

    The exposure of a customer's aerospace test-article to a simulated acoustic launch environment is typically performed in a reverberant acoustic test chamber. The acoustic pre-test runs that will ensure that the sound pressure levels of this environment can indeed be met by a test facility are normally performed without a test-article dynamic simulator of representative acoustic absorption and size. If an acoustic test facility's available acoustic power capability becomes maximized with the test-article installed during the actual test then the customer's environment requirement may become compromised. In order to understand the risk of not achieving the customer's in-tolerance spectrum requirement with the test-article installed, an acoustic power margin evaluation as a function of frequency may be performed by the test facility. The method for this evaluation of acoustic power will be discussed in this paper. This method was recently applied at the NASA Glenn Research Center Plum Brook Station's Reverberant Acoustic Test Facility for the SpaceX Falcon 9 Payload Fairing acoustic test program.

  18. An Evaluation of the Additional Acoustic Power Needed to Overcome the Effects of a Test-Article's Absorption during Reverberant Chamber Acoustic Testing of Spaceflight Hardware

    NASA Technical Reports Server (NTRS)

    Hozman, Aron D.; Hughes, William O.

    2014-01-01

    The exposure of a customers aerospace test-article to a simulated acoustic launch environment is typically performed in a reverberant acoustic test chamber. The acoustic pre-test runs that will ensure that the sound pressure levels of this environment can indeed be met by a test facility are normally performed without a test-article dynamic simulator of representative acoustic absorption and size. If an acoustic test facilitys available acoustic power capability becomes maximized with the test-article installed during the actual test then the customers environment requirement may become compromised. In order to understand the risk of not achieving the customers in-tolerance spectrum requirement with the test-article installed, an acoustic power margin evaluation as a function of frequency may be performed by the test facility. The method for this evaluation of acoustic power will be discussed in this paper. This method was recently applied at the NASA Glenn Research Center Plum Brook Stations Reverberant Acoustic Test Facility for the SpaceX Falcon 9 Payload Fairing acoustic test program.

  19. Predicting contraceptive use from an egalitarian model of women's overall household power vis-à-vis conventional power models and third variables.

    PubMed

    León, Federico R

    2013-07-01

    Research on gender power in contraceptive use has focused on whether women have an active role in household decision-making (the participation model) or on the extent of their control of domestic decisions (the control model); it has also addressed the joint effects of power, age, education and work. Findings published in this journal (Woldemicael, 2009) suggest a third power model according to which wives make joint decisions with their husbands on important domestic areas and autonomous decisions on secondary matters (the egalitarian model). In analyses of Demographic and Health Survey data sets from 46 countries, the egalitarian model explained contraceptive use better than the control and participation models in 19 out of 20 countries outside sub-Saharan Africa; its superiority was less overwhelming in this sub-continent. Power effects on contraceptive use that depend on women's education, age and work for cash are larger in sub-Saharan Africa than in other world regions, whereas independent power effects differ little regionally, suggesting the action of a personality factor. Situational specification of decision importance and direct measurement of women's assertiveness are needed to improve the explanation of contraceptive behaviour. PMID:23137710

  20. The suitability of concentration addition for predicting the effects of multi-component mixtures of up to 17 anti-androgens with varied structural features in an in vitro AR antagonist assay

    SciTech Connect

    Ermler, Sibylle; Scholze, Martin; Kortenkamp, Andreas

    2011-12-15

    The risks associated with human exposures to chemicals capable of antagonising the effects of endogenous androgens have attracted considerable recent interest. Exposure is typically to large numbers of chemicals with androgen receptor (AR) antagonist activity, yet there is limited evidence of the combined effects of multi-component mixtures of these chemicals. A few in vitro studies with mixtures of up to six AR antagonists suggest that the concept of concentration addition (CA) provides good approximations of experimentally observed mixture effects, but studies with larger numbers of anti-androgens, and with more varied structural features, are missing. Here we show that the mixture effects of up to 17 AR antagonists, comprising compounds as diverse as UV-filter substances, parabens, perfluorinated compounds, bisphenol-A, benzo({alpha})pyrene, synthetic musks, antioxidants and polybrominated biphenyls, can be predicted well on the basis of the anti-androgenicity of the single components using the concept of CA. We tested these mixtures in an in vitro AR-dependent luciferase reporter gene assay, based on MDA-kb2 cells. The effects of further mixtures, composed of four and six anti-androgens, could be predicted accurately by CA. However, there was a shortfall from expected additivity with a ten-component mixture at two different mixture ratios, but attempts to attribute these deviations to differential expression of hormone-metabolising CYP isoforms did not produce conclusive results. CA provides good approximations of in vitro mixture effects of anti-androgens with varying structural features. -- Highlights: Black-Right-Pointing-Pointer Humans are exposed to a large number of androgen receptor antagonists. Black-Right-Pointing-Pointer There is limited evidence of the combined effects of anti-androgenic chemicals. Black-Right-Pointing-Pointer We modelled the predictability of combined effects of up to 17 anti-androgens. Black-Right-Pointing-Pointer We tested the

  1. Congruence and predictive power of mothers' and teachers' ratings of mastery motivation in children with mental retardation.

    PubMed

    Hauser-Cram, P; Krauss, M W; Warfield, M E; Steele, A

    1997-10-01

    The congruence between mothers' and teachers' ratings of mastery motivation among 3-year-old children with mental retardation was investigated. The extent to which maternal and teacher ratings of task persistence at entry to preschool are predictive of observed mastery behaviors at age 5 was tested. Results indicate that mothers rated their children's task persistence behaviors higher than did teachers. Further, once the child's cognitive level and teacher ratings were controlled for statistically, maternal ratings of the child's mastery behaviors were predictive of the child's task mastery performance 2 years subsequent. Implications for educational planning were discussed. PMID:9339064

  2. Drift and diffusion coefficients of Markov diffusional process in problems of predicting the life of atomic-power-plant equipment

    SciTech Connect

    Emel'yanov, V.S.; Klemin, A.I.; Rabchun, A.V.

    1987-06-01

    The authors construct a statistical model based on the Markov diffusion process and the Fokker-Planck-Kolmogorov equation for forecasting the remaining service life of reactor components. The model is one-dimensional and allows changes in the probabilistic characteristics of random aging processes of individual mechanical systems to be predicted with sufficient accuracy for engineering purposes.

  3. Predictive Power of ETRE Polymorphism and Katg463 Mutation to INH-Resistance of M.tuberculosis

    PubMed Central

    WEN, Yu-feng; JIANG, Chao; CHENG, Xian-feng; ZHANG, Zhi-ping; Chen, Bai-feng; ZHU, Yu

    2015-01-01

    Background: The MIRU-VNTR polymorphism and katG463 mutation are used to genotype the mycobacterium tuberculosis, but the correlation between them and INH-resistance were unknown. This study was aimed to explore whether ETRE polymorphism and katG463 mutation could predict the INH-resistance, and the relationship between ETRE polymorphism and katG463 mutation. Methods: The ETRE, katG463 mutation and drug resistance information of 109 M. tuberculosis strains were collected from online public database. We constructed the predictive diagnostic tool of ETRE polymorphism and katG463 mutation. Chi-square test was used to analyze the relationship between ETRE polymorphism, katG463 mutation and INH-resistance. ROC curve analysis and Z-test were used to evaluate the predictive ability of ETRE and katG463. The relationship between ETRE polymorphism and katG463 mutation was analyzed with Spearman correlation analysis. Results: The mutation rate of katG463 was 27.50%, and the h value of ETRE polymorphism was 0.67. KatG463 mutation was associated with INH resistance (OR=3.72). The INH drug resistance rate in VNTR≧5 group was 3.43 times higher than that in VNTR≦3 group (χ2=24.77, P<0.01), and there was no significant difference of INH resistance between the VNTR=4 group and VNTR≦3 group. The areas under the ROC curve of two loci prediction diagnostic tools were 0.64 and 0.70 respectively. The katG463 mutation was significantly related to the ETRE polymorphism (r=0.79, P<0.01). Conclusion: Both katG463 mutation and the ETRE polymorphism can predict the INH-resistance of tuberculosis. The katG463 mutation was associated with ETRE VNTR polymorphism. PMID:25905061

  4. Predicting the ultimate potential of natural gas SOFC power cycles with CO2 capture - Part B: Applications

    NASA Astrophysics Data System (ADS)

    Campanari, Stefano; Mastropasqua, Luca; Gazzani, Matteo; Chiesa, Paolo; Romano, Matteo C.

    2016-09-01

    An important advantage of solid oxide fuel cells (SOFC) as future systems for large scale power generation is the possibility of being efficiently integrated with processes for CO2 capture. Focusing on natural gas power generation, Part A of this work assessed the performances of advanced pressurised and atmospheric plant configurations (SOFC + GT and SOFC + ST, with fuel cell integration within a gas turbine or a steam turbine cycle) without CO2 separation. This Part B paper investigates such kind of power cycles when applied to CO2 capture, proposing two ultra-high efficiency plant configurations based on advanced intermediate-temperature SOFCs with internal reforming and low temperature CO2 separation process. The power plants are simulated at the 100 MW scale with a set of realistic assumptions about FC performances, main components and auxiliaries, and show the capability of exceeding 70% LHV efficiency with high CO2 capture (above 80%) and a low specific primary energy consumption for the CO2 avoided (1.1-2.4 MJ kg-1). Detailed results are presented in terms of energy and material balances, and a sensitivity analysis of plant performance is developed vs. FC voltage and fuel utilisation to investigate possible long-term improvements. Options for further improvement of the CO2 capture efficiency are also addressed.

  5. Predictive power of UKCAT and other pre-admission measures for performance in a medical school in Glasgow: a cohort study

    PubMed Central

    2014-01-01

    Background The UK Clinical Aptitude Test (UKCAT) and its four subtests are currently used by 24 Medical and Dental Schools in the UK for admissions. This longitudinal study examines the predictive validity of UKCAT for final performance in the undergraduate medical degree programme at one Medical School and compares this with the predictive validity of the selection measures available pre-UKCAT. Methods This was a retrospective observational study of one cohort of students, admitted to Glasgow Medical School in 2007. We examined the associations which UKCAT scores, school science grades and pre-admissions interview scores had with performance indicators, particularly final composite scores that determine students’ postgraduate training opportunities and overall ranking (Educational Performance Measure - EPM, and Honours and Commendation – H&C). Analyses were conducted both with and without adjustment for potential socio-demographic confounders (gender, age, ethnicity and area deprivation). Results Despite its predictive value declining as students progress through the course, UKCAT was associated with the final composite scores. In mutually adjusted analyses (also adjusted for socio-demographic confounders), only UKCAT total showed independent relationships with both EPM (p = 0.005) and H&C (p = 0.004), school science achievements predicted EPM (p = 0.009), and pre-admissions interview score predicted neither. UKCAT showed less socio-demographic variation than did TSS. Conclusion UKCAT has a modest predictive power for overall course performance at the University of Glasgow Medical School over and above that of school science achievements or pre-admission interview score and we conclude that UKCAT is the most useful predictor of final ranking. PMID:24919950

  6. Code System for Real-Time Prediction of Radiation Dose to the Public Due to an Accidental Release from a Nuclear Power Plant.

    1987-01-20

    Version 00 The suite of computer codes, SPEEDI, predicts the dose to the public from a plume released from a nuclear power plant. The main codes comprising SPEEDI are: WIND04, PRWDA, and CIDE. WIND04 calculates three-dimensional mass-conservative windfields. PRWDA calculates concentration distributions, and CIDE estimates the external and internal doses. These models can take into account the spatial and temporal variation of wind, variable topography, deposition and variable source intensity for use in real-time assessment.more » We recommend that you also review the emergency response supporting system CCC-661/ EXPRESS documentation.« less

  7. Current status and prediction of major atmospheric emissions from coal-fired power plants in Shandong Province, China

    NASA Astrophysics Data System (ADS)

    Xiong, Tianqi; Jiang, Wei; Gao, Weidong

    2016-01-01

    Shandong is considered to be the top provincial emitter of air pollutants in China due to its large consumption of coal in the power sector and its dense distribution of coal-fired plants. To explore the atmospheric emissions of the coal-fired power sector in Shandong, an updated emission inventory of coal-fired power plants for the year 2012 in Shandong was developed. The inventory is based on the following parameters: coal quality, unit capacity and unit starting year, plant location, boiler type and control technologies. The total SO2, NOx, fine particulate matter (PM2.5) and mercury (Hg) emissions are estimated at 705.93 kt, 754.30 kt, 63.99 kt and 10.19 kt, respectively. Larger units have cleaner emissions than smaller ones. The coal-fired units (≥300 MW) are estimated to account for 35.87% of SO2, 43.24% of NOx, 47.74% of PM2.5 and 49.83% of Hg emissions, which is attributed primarily to the improved penetration of desulfurization, LNBs, denitration and dust-removing devices in larger units. The major regional contributors are southwestern cities, such as Jining, Liaocheng, Zibo and Linyi, and eastern cities, such as Yantai and Qindao. Under the high-efficiency control technology (HECT) scenario analysis, emission reductions of approximately 58.61% SO2, 80.63% NOx, 34.20% PM2.5 and 50.08% Hg could be achieved by 2030 compared with a 2012 baseline. This inventory demonstrates why it is important for policymakers and researchers to assess control measure effectiveness and to supply necessary input for regional policymaking and the management of the coal-fired power sector in Shandong.

  8. Analytical and numerical prediction of harmonic sound power in the inlet of aero-engines with emphasis on transonic rotation speeds

    NASA Astrophysics Data System (ADS)

    Lewy, Serge; Polacsek, Cyril; Barrier, Raphael

    2014-12-01

    Tone noise radiated through the inlet of a turbofan is mainly due to rotor-stator interactions at subsonic regimes (approach flight), and to the shock waves attached to each blade at supersonic helical tip speeds (takeoff). The axial compressor of a helicopter turboshaft engine is transonic as well and can be studied like turbofans at takeoff. The objective of the paper is to predict the sound power at the inlet radiating into the free field, with a focus on transonic conditions because sound levels are much higher. Direct numerical computation of tone acoustic power is based on a RANS (Reynolds averaged Navier-Stokes) solver followed by an integration of acoustic intensity over specified inlet cross-sections, derived from Cantrell and Hart equations (valid in irrotational flows). In transonic regimes, sound power decreases along the intake because of nonlinear propagation, which must be discriminated from numerical dissipation. This is one of the reasons why an analytical approach is also suggested. It is based on three steps: (i) appraisal of the initial pressure jump of the shock waves; (ii) 2D nonlinear propagation model of Morfey and Fisher; (iii) calculation of the sound power of the 3D ducted acoustic field. In this model, all the blades are assumed to be identical such that only the blade passing frequency and its harmonics are predicted (like in the present numerical simulations). However, transfer from blade passing frequency to multiple pure tones can be evaluated in a fourth step through a statistical analysis of irregularities between blades. Interest of the analytical method is to provide a good estimate of nonlinear acoustic propagation in the upstream duct while being easy and fast to compute. The various methods are applied to two turbofan models, respectively in approach (subsonic) and takeoff (transonic) conditions, and to a Turbomeca turboshaft engine (transonic case). The analytical method in transonic appears to be quite reliable by comparison

  9. The Predictive Power of Family History Measures of Alcohol and Drug Problems and Internalizing Disorders In A College Population

    PubMed Central

    Kendler, Kenneth S; Edwards, Alexis; Myers, John; Cho, Seung Bin; Adkins, Amy; Dick, Danielle

    2015-01-01

    A family history (FH) of psychiatric and substance use problems is a potent risk factor for common internalizing and externalizing disorders. In a large web-based assessment of mental health in college students, we developed a brief set of screening questions for a FH of alcohol problems (AP), drug problems (DP) and depression-anxiety in four classes of relatives (father, mother, aunts/uncles/grandparents, and siblings) as reported by the student. Positive reports of a history of AP, DP, and depression-anxiety were substantially correlated within relatives. These FH measures predicted in the student, in an expected pattern, dimensions of personality and impulsivity, alcohol consumption and problems, smoking and nicotine dependence, use of illicit drugs, and symptoms of depression and anxiety. Using the mean score from the four classes of relatives was more predictive than using a familial/sporadic dichotomy. Interactions were seen between the FH of AP, DP, and depression-anxiety and peer deviance in predicting symptoms of alcohol and tobacco dependence. As the students aged, the FH of AP became a stronger predictor of alcohol problems. While we cannot directly assess the validity of these FH reports, the pattern of findings suggest that our brief screening items were able to assess, with some accuracy, the FH of substance misuse and internalizing psychiatric disorders in relatives. If correct, these measures can play an important role in the creation of developmental etiologic models for substance and internalizing psychiatric disorders which constitute one of the central goals of the overall project. PMID:25946510

  10. The predictive power of family history measures of alcohol and drug problems and internalizing disorders in a college population.

    PubMed

    Kendler, Kenneth S; Edwards, Alexis; Myers, John; Cho, Seung Bin; Adkins, Amy; Dick, Danielle

    2015-07-01

    A family history (FH) of psychiatric and substance use problems is a potent risk factor for common internalizing and externalizing disorders. In a large web-based assessment of mental health in college students, we developed a brief set of screening questions for a FH of alcohol problems (AP), drug problems (DP) and depression-anxiety in four classes of relatives (father, mother, aunts/uncles/grandparents, and siblings) as reported by the student. Positive reports of a history of AP, DP, and depression-anxiety were substantially correlated within relatives. These FH measures predicted in the student, in an expected pattern, dimensions of personality and impulsivity, alcohol consumption and problems, smoking and nicotine dependence, use of illicit drugs, and symptoms of depression and anxiety. Using the mean score from the four classes of relatives was more predictive than using a familial/sporadic dichotomy. Interactions were seen between the FH of AP, DP, and depression-anxiety and peer deviance in predicting symptoms of alcohol and tobacco dependence. As the students aged, the FH of AP became a stronger predictor of alcohol problems. While we cannot directly assess the validity of these FH reports, the pattern of findings suggest that our brief screening items were able to assess, with some accuracy, the FH of substance misuse and internalizing psychiatric disorders in relatives. If correct, these measures can play an important role in the creation of developmental etiologic models for substance and internalizing psychiatric disorders which constitute one of the central goals of the overall project. PMID:25946510

  11. Pole coordinates data prediction by combination of least squares extrapolation and double autoregressive prediction

    NASA Astrophysics Data System (ADS)

    Kosek, Wieslaw

    2016-04-01

    Future Earth Orientation Parameters data are needed to compute real time transformation between the celestial and terrestrial reference frames. This transformation is realized by predictions of x, y pole coordinates data, UT1-UTC data and precesion-nutation extrapolation model. This paper is focused on the pole coordinates data prediction by combination of the least-squares (LS) extrapolation and autoregressive (AR) prediction models (LS+AR). The AR prediction which is applied to the LS extrapolation residuals of pole coordinates data does not able to predict all frequency bands of them and it is mostly tuned to predict subseasonal oscillations. The absolute values of differences between pole coordinates data and their LS+AR predictions increase with prediction length and depend mostly on starting prediction epochs, thus time series of these differences for 2, 4 and 8 weeks in the future were analyzed. Time frequency spectra of these differences for different prediction lengths are very similar showing some power in the frequency band corresponding to the prograde Chandler and annual oscillations, which means that the increase of prediction errors is caused by mismodelling of these oscillations by the LS extrapolation model. Thus, the LS+AR prediction method can be modified by taking into additional AR prediction correction computed from time series of these prediction differences for different prediction lengths. This additional AR prediction is mostly tuned to the seasonal frequency band of pole coordinates data.

  12. Zinc Isotope Variability in Three Coal-Fired Power Plants: A Predictive Model for Determining Isotopic Fractionation during Combustion.

    PubMed

    Ochoa Gonzalez, R; Weiss, D

    2015-10-20

    The zinc (Zn) isotope compositions of feed materials and combustion byproducts were investigated in three different coal-fired power plants, and the results were used to develop a generalized model that can account for Zn isotopic fractionation during coal combustion. The isotope signatures in the coal (δ(66)ZnIRMM) ranged between +0.73 and +1.18‰, values that fall well within those previously determined for peat (+0.6 ±2.0‰). We therefore propose that the speciation of Zn in peat determines the isotope fingerprint in coal. All of the bottom ashes collected in these power plants were isotopically depleted in the heavy isotopes relative to the coals, with δ(66)ZnIRMM values ranging between +0.26‰ and +0.64‰. This suggests that the heavy isotopes, possibly associated with the organic matter of the coal, may be preferentially released into the vapor phase. The fly ash in all of these power plants was, in contrast, enriched in the heavy isotopes relative to coal. The signatures in the fly ash can be accounted for using a simple unidirectional fractionation model with isotope fractionation factors (αsolid-vapor) ranging between 1.0003 and 1.0007, and we suggest that condensation is the controlling process. The model proposed allows, once the isotope composition of the feed coal is known, the constraining of the Zn signatures in the byproducts. This will now enable the integration of Zn isotopes as a quantitative tool for the source apportionment of this metal from coal combustion in the atmosphere. PMID:26422061

  13. Prediction of functional recovery of hibernating myocardium using harmonic power Doppler imaging and dobutamine stress echocardiography in patients with coronary artery disease.

    PubMed

    Aggeli, Constadina; Stefanadis, Christodoulos; Bonou, Maria; Pitsavos, Christos; Theocharis, Constantinos; Roussakis, George; Chatzos, Constantinos; Brili, Stela; Toutouzas, Pavlos

    2003-06-15

    The aim of this study was to compare the accuracy of harmonic power Doppler imaging (HPDI) and dobutamine stress echocardiography (DSE) in predicting recovery of myocardial function after bypass surgery. HPDI using triggering imaging with the administration of Levovist (Shering AG, Berlin, Germany) and DSE were performed in 34 patients (mean age 64 +/- 5 years) with left ventricular dysfunction. A repeat echocardiogram at rest was performed 3 months after revascularization. Of the 408 revascularized dysfunctional segments, 188 (45%) improved on the repeat echocardiogram. HPDI exhibited overall similar sensitivity (88% vs 87%) and accuracy (74% vs 79%) but lower specificity (61% vs 72%, p<0.05) compared with DSE for predicting recovery of myocardial function. Only delayed opacification at the 1:8 triggering point, demonstrated in 62% of viable segments, exhibited higher sensitivity (63%) and positive (58%) and negative (66%) predictive values than early opacification at 1:4 (25%, p<0.001; 35%, p<0.001; and 49%, p<0.001, respectively) in predicting functional recovery. The presence of contrast enhancement within the revascularized area resulted in a significant improvement after revascularization in wall motion score index and ejection fraction compared with areas with residual contrast defect (1.9 +/- 0.3 vs 2.3 +/- 0.3, p<0.01; 36 +/- 6% vs 29 +/- 5%, p<0.01, respectively). Significant correlations were observed between the contrast score index and the follow-up wall motion score index (r = -0.67) and between the contrast score index and the follow-up ejection fraction change (r = 0.65). Triggered HPDI has high sensitivity in detecting hibernating myocardium and can accurately predict the potential for recovery of ischemic left ventricular dysfunction 3 months after revascularization. PMID:12804726

  14. Predictive power of the Braden scale for pressure sore risk in adult critical care patients: a comprehensive review.

    PubMed

    Cox, Jill

    2012-01-01

    Critical care is designed for managing the sickest patients within our healthcare system. Multiple factors associated with an increased likelihood of pressure ulcer development have been investigated in the critical care population. Nevertheless, there is a lack of consensus regarding which of these factors poses the greatest risk for pressure ulceration. While the Braden scale for pressure sore risk is the most commonly used tool for measuring pressure ulcer risk in the United States, research focusing on the cumulative Braden Scale score and subscale scores is lacking in the critical care population. This author conducted a literature review on pressure ulcer risk assessment in the critical care population, to include the predictive value of both the total score and the subscale scores. In this review, the subscales sensory perception, mobility, moisture, and friction/shear were found to be associated with an increased likelihood of pressure ulcer development; in contrast, the Activity and Nutrition subscales were not found to predict pressure ulcer development in this population. In order to more precisely quantify risk in the critically ill population, modification of the Braden scale or development of a critical care specific risk assessment tool may be indicated. PMID:22948495

  15. Model-Predictive Cascade Mitigation in Electric Power Systems With Storage and Renewables-Part II: Case-Study

    SciTech Connect

    Almassalkhi, MR; Hiskens, IA

    2015-01-01

    The novel cascade-mitigation scheme developed in Part I of this paper is implemented within a receding-horizon model predictive control (MPC) scheme with a linear controller model. This present paper illustrates the MPC strategy with a case-study that is based on the IEEE RTS-96 network, though with energy storage and renewable generation added. It is shown that the MPC strategy alleviates temperature overloads on transmission lines by rescheduling generation, energy storage, and other network elements, while taking into account ramp-rate limits and network limitations. Resilient performance is achieved despite the use of a simplified linear controller model. The MPC scheme is compared against a base-case that seeks to emulate human operator behavior.

  16. Use seismic colored inversion and power law committee machine based on imperial competitive algorithm for improving porosity prediction in a heterogeneous reservoir

    NASA Astrophysics Data System (ADS)

    Ansari, Hamid Reza

    2014-09-01

    In this paper we propose a new method for predicting rock porosity based on a combination of several artificial intelligence systems. The method focuses on one of the Iranian carbonate fields in the Persian Gulf. Because there is strong heterogeneity in carbonate formations, estimation of rock properties experiences more challenge than sandstone. For this purpose, seismic colored inversion (SCI) and a new approach of committee machine are used in order to improve porosity estimation. The study comprises three major steps. First, a series of sample-based attributes is calculated from 3D seismic volume. Acoustic impedance is an important attribute that is obtained by the SCI method in this study. Second, porosity log is predicted from seismic attributes using common intelligent computation systems including: probabilistic neural network (PNN), radial basis function network (RBFN), multi-layer feed forward network (MLFN), ε-support vector regression (ε-SVR) and adaptive neuro-fuzzy inference system (ANFIS). Finally, a power law committee machine (PLCM) is constructed based on imperial competitive algorithm (ICA) to combine the results of all previous predictions in a single solution. This technique is called PLCM-ICA in this paper. The results show that PLCM-ICA model improved the results of neural networks, support vector machine and neuro-fuzzy system.

  17. Prediction of corridor effect from the launching of the satellite power system. [air pollutant concentration into narrow band of latitude

    NASA Technical Reports Server (NTRS)

    Borucki, W. J.; Whitten, R. C.; Woodward, H. T.; Capone, L. A.; Riegel, C. A.

    1982-01-01

    A diagnostic model is developed to define the parameters which control the corridor effect of contaminants deposited in a narrow latitudinal band of the earth's atmosphere by numerous launches of the STS and heavy lift launch vehicles for construction of satellite solar power systems. Identified factors included the pollution injection rate, the ambient background levels of the pollutant species, and the transport properties related to the dilution rate of the chemicals. If the chemical life of the pollutant was shorter or the same length of time as the transport time, alterations in the chemical production and loss rates were found to be parameters necessarily added to the model. A comparison with NASA Ames Research Center two-dimensional model results indicate that the corridor effect was possile with operations above 60 km in the case of H2O, H2, and NO production.

  18. Predictions of U.K. regulated power station contributions to regional air pollution and deposition: a model comparison exercise.

    PubMed

    Chemel, Charles; Sokhi, Ranjeet S; Dore, Anthony J; Sutton, Paul; Vincent, Keith J; Griffiths, Stephen J; Hayman, Garry D; Wright, Raymond D; Baggaley, Matthew; Hallsworth, Stephen; Prain, H Douglas; Fisher, Bernard E A

    2011-11-01

    Contributions of the emissions from a U.K. regulated fossil-fuel power station to regional air pollution and deposition are estimated using four air quality modeling systems for the year 2003. The modeling systems vary in complexity and emphasis in the way they treat atmospheric and chemical processes, and include the Community Multiscale Air Quality (CMAQ) modeling system in its versions 4.6 and 4.7, a nested modeling system that combines long- and short-range impacts (referred to as TRACK-ADMS [Trajectory Model with Atmospheric Chemical Kinetics-Atmospheric Dispersion Modelling System]), and the Fine Resolution Atmospheric Multi-pollutant Exchange (FRAME) model. An evaluation of the baseline calculations against U.K. monitoring network data is performed. The CMAQ modeling system version 4.6 data set is selected as the reference data set for the model footprint comparison. The annual mean air concentration and total deposition footprints are summarized for each modeling system. The footprints of the power station emissions can account for a significant fraction of the local impacts for some species (e.g., more than 50% for SO2 air concentration and non-sea-salt sulfur deposition close to the source) for 2003. The spatial correlation and the coefficient of variation of the root mean square error (CVRMSE) are calculated between each model footprint and that calculated by the CMAQ modeling system version 4.6. The correlation coefficient quantifies model agreement in terms of spatial patterns, and the CVRMSE measures the magnitude of the difference between model footprints. Possible reasons for the differences between model results are discussed. Finally, implications and recommendations for the regulatory assessment of the impact of major industrial sources using regional air quality modeling systems are discussed in the light of results from this case study. PMID:22168107

  19. Individual Differences in Behavioural Despair Predict Brain GSK-3beta Expression in Mice: The Power of a Modified Swim Test

    PubMed Central

    Markova, Nataliia; Shevtsova, Elena; Bakhmet, Anastassia; Steinbusch, Harry M.

    2016-01-01

    While deficient brain plasticity is a well-established pathophysiologic feature of depression, little is known about disorder-associated enhanced cognitive processing. Here, we studied a novel mouse paradigm that potentially models augmented learning of adverse memories during development of a depressive-like state. We used a modification of the classic two-day protocol of a mouse Porsolt test with an additional session occurring on Day 5 following the initial exposure. Unexpectedly, floating behaviour and brain glycogen synthase kinase-3 beta (GSK-3beta) mRNA levels, a factor of synaptic plasticity as well as a marker of distress and depression, were increased during the additional swimming session that was prevented by imipramine. Observed increases of GSK-3beta mRNA in prefrontal cortex during delayed testing session correlated with individual parameters of behavioural despair that was not found in the classic Porsolt test. Repeated swim exposure was accompanied by a lower pGSK-3beta/GSK-3beta ratio. A replacement of the second or the final swim sessions with exposure to the context of testing resulted in increased GSK-3beta mRNA level similar to the effects of swimming, while exclusion of the second testing prevented these changes. Together, our findings implicate the activation of brain GSK-3beta expression in enhanced contextual conditioning of adverse memories, which is associated with an individual susceptibility to a depressive syndrome. PMID:27478647

  20. Individual Differences in Behavioural Despair Predict Brain GSK-3beta Expression in Mice: The Power of a Modified Swim Test.

    PubMed

    Strekalova, Tatyana; Markova, Nataliia; Shevtsova, Elena; Zubareva, Olga; Bakhmet, Anastassia; Steinbusch, Harry M; Bachurin, Sergey; Lesch, Klaus-Peter

    2016-01-01

    While deficient brain plasticity is a well-established pathophysiologic feature of depression, little is known about disorder-associated enhanced cognitive processing. Here, we studied a novel mouse paradigm that potentially models augmented learning of adverse memories during development of a depressive-like state. We used a modification of the classic two-day protocol of a mouse Porsolt test with an additional session occurring on Day 5 following the initial exposure. Unexpectedly, floating behaviour and brain glycogen synthase kinase-3 beta (GSK-3beta) mRNA levels, a factor of synaptic plasticity as well as a marker of distress and depression, were increased during the additional swimming session that was prevented by imipramine. Observed increases of GSK-3beta mRNA in prefrontal cortex during delayed testing session correlated with individual parameters of behavioural despair that was not found in the classic Porsolt test. Repeated swim exposure was accompanied by a lower pGSK-3beta/GSK-3beta ratio. A replacement of the second or the final swim sessions with exposure to the context of testing resulted in increased GSK-3beta mRNA level similar to the effects of swimming, while exclusion of the second testing prevented these changes. Together, our findings implicate the activation of brain GSK-3beta expression in enhanced contextual conditioning of adverse memories, which is associated with an individual susceptibility to a depressive syndrome. PMID:27478647

  1. The Predictive Power of Electronic Polarizability for Tailoring the Refractivity of High Index Glasses Optical Basicity Versus the Single Oscillator Model

    SciTech Connect

    McCloy, John S.; Riley, Brian J.; Johnson, Bradley R.; Schweiger, Michael J.; Qiao, Hong; Carlie, Nathan

    2010-06-01

    Four compositions of high density (~8 g/cm3) heavy metal oxide glasses composed of PbO, Bi2O3, and Ga2O3 were produced and refractivity parameters (refractive index and density) were computed and measured. Optical basicity was computed using three different models – average electronegativity, ionic-covalent parameter, and energy gap – and the basicity results were used to compute oxygen polarizability and subsequently refractive index. Refractive indices were measured in the visible and infrared at 0.633 μm, 1.55 μm, 3.39 μm, 5.35 μm, 9.29 μm, and 10.59 μm using a unique prism coupler setup, and data were fitted to the Sellmeier expression to obtain an equation of the dispersion of refractive index with wavelength. Using this dispersion relation, single oscillator energy, dispersion energy, and lattice energy were determined. Oscillator parameters were also calculated for the various glasses from their oxide values as an additional means of predicting index. Calculated dispersion parameters from oxides underestimate the index by 3 to 4%. Predicted glass index from optical basicity, based on component oxide energy gaps, underpredicts the index at 0.633 μm by only 2%, while other basicity scales are less accurate. The predicted energy gap of the glasses based on this optical basicity overpredicts the Tauc optical gap as determined by transmission measurements by 6 to 10%. These results show that for this system, density, refractive index in the visible, and energy gap can be reasonably predicted using only composition, optical basicity values for the constituent oxides, and partial molar volume coefficients. Calculations such as these are useful for a priori prediction of optical properties of glasses.

  2. Genome-wide prediction models that incorporate de novo GWAS are a powerful new tool for tropical rice improvement.

    PubMed

    Spindel, J E; Begum, H; Akdemir, D; Collard, B; Redoña, E; Jannink, J-L; McCouch, S

    2016-04-01

    To address the multiple challenges to food security posed by global climate change, population growth and rising incomes, plant breeders are developing new crop varieties that can enhance both agricultural productivity and environmental sustainability. Current breeding practices, however, are unable to keep pace with demand. Genomic selection (GS) is a new technique that helps accelerate the rate of genetic gain in breeding by using whole-genome data to predict the breeding value of offspring. Here, we describe a new GS model that combines RR-BLUP with markers fit as fixed effects selected from the results of a genome-wide-association study (GWAS) on the RR-BLUP training data. We term this model GS + de novo GWAS. In a breeding population of tropical rice, GS + de novo GWAS outperformed six other models for a variety of traits and in multiple environments. On the basis of these results, we propose an extended, two-part breeding design that can be used to efficiently integrate novel variation into elite breeding populations, thus expanding genetic diversity and enhancing the potential for sustainable productivity gains. PMID:26860200

  3. Genome-wide prediction models that incorporate de novo GWAS are a powerful new tool for tropical rice improvement

    PubMed Central

    Spindel, J E; Begum, H; Akdemir, D; Collard, B; Redoña, E; Jannink, J-L; McCouch, S

    2016-01-01

    To address the multiple challenges to food security posed by global climate change, population growth and rising incomes, plant breeders are developing new crop varieties that can enhance both agricultural productivity and environmental sustainability. Current breeding practices, however, are unable to keep pace with demand. Genomic selection (GS) is a new technique that helps accelerate the rate of genetic gain in breeding by using whole-genome data to predict the breeding value of offspring. Here, we describe a new GS model that combines RR-BLUP with markers fit as fixed effects selected from the results of a genome-wide-association study (GWAS) on the RR-BLUP training data. We term this model GS + de novo GWAS. In a breeding population of tropical rice, GS + de novo GWAS outperformed six other models for a variety of traits and in multiple environments. On the basis of these results, we propose an extended, two-part breeding design that can be used to efficiently integrate novel variation into elite breeding populations, thus expanding genetic diversity and enhancing the potential for sustainable productivity gains. PMID:26860200

  4. Health effects models for nuclear power plant accident consequence analysis. Modification of models resulting from addition of effects of exposure to alpha-emitting radionuclides: Revision 1, Part 2, Scientific bases for health effects models, Addendum 2

    SciTech Connect

    Abrahamson, S.; Bender, M.A.; Boecker, B.B.; Scott, B.R.; Gilbert, E.S.

    1993-05-01

    The Nuclear Regulatory Commission (NRC) has sponsored several studies to identify and quantify, through the use of models, the potential health effects of accidental releases of radionuclides from nuclear power plants. The Reactor Safety Study provided the basis for most of the earlier estimates related to these health effects. Subsequent efforts by NRC-supported groups resulted in improved health effects models that were published in the report entitled {open_quotes}Health Effects Models for Nuclear Power Plant Consequence Analysis{close_quotes}, NUREG/CR-4214, 1985 and revised further in the 1989 report NUREG/CR-4214, Rev. 1, Part 2. The health effects models presented in the 1989 NUREG/CR-4214 report were developed for exposure to low-linear energy transfer (LET) (beta and gamma) radiation based on the best scientific information available at that time. Since the 1989 report was published, two addenda to that report have been prepared to (1) incorporate other scientific information related to low-LET health effects models and (2) extend the models to consider the possible health consequences of the addition of alpha-emitting radionuclides to the exposure source term. The first addendum report, entitled {open_quotes}Health Effects Models for Nuclear Power Plant Accident Consequence Analysis, Modifications of Models Resulting from Recent Reports on Health Effects of Ionizing Radiation, Low LET Radiation, Part 2: Scientific Bases for Health Effects Models,{close_quotes} was published in 1991 as NUREG/CR-4214, Rev. 1, Part 2, Addendum 1. This second addendum addresses the possibility that some fraction of the accident source term from an operating nuclear power plant comprises alpha-emitting radionuclides. Consideration of chronic high-LET exposure from alpha radiation as well as acute and chronic exposure to low-LET beta and gamma radiations is a reasonable extension of the health effects model.

  5. Transition Metal Diborides as Electrode Material for MHD Direct Power Extraction: High-temperature Oxidation of ZrB2-HfB2 Solid Solution with LaB6 Addition

    NASA Astrophysics Data System (ADS)

    Sitler, Steven; Hill, Cody; Raja, Krishnan S.; Charit, Indrajit

    2016-04-01

    Transition metal borides are being considered for use as potential electrode coating materials in magnetohydrodynamic direct power extraction plants from coal-fired plasma. These electrode materials will be exposed to aggressive service conditions at high temperatures. Therefore, high-temperature oxidation resistance is an important property. Consolidated samples containing an equimolar solid solution of ZrB2-HfB2 with and without the addition of 1.8 mol pct LaB6 were prepared by ball milling of commercial boride material followed by spark plasma sintering. These samples were oxidized at 1773 K (1500 °C) in two different conditions: (1) as-sintered and (2) anodized (10 V in 0.1 M KOH electrolyte). Oxidation studies were carried out in 0.3 × 105 and 0.1 Pa oxygen partial pressures. The anodic oxide layers showed hafnium enrichment on the surface of the samples, whereas the high-temperature oxides showed zirconium enrichment. The anodized samples without LaB6 addition showed about 2.5 times higher oxidation resistance in high-oxygen partial pressures than the as-sintered samples. Addition of LaB6 improved the oxidation resistance in the as-sintered condition by about 30 pct in the high-oxygen partial pressure tests.

  6. Influence of the additional p+ doped layers on the properties of AlGaAs/InGaAs/AlGaAs heterostructures for high power SHF transistors

    NASA Astrophysics Data System (ADS)

    Gulyaev, D. V.; Zhuravlev, K. S.; Bakarov, A. K.; Toropov, A. I.; Protasov, D. Yu; Gutakovskii, A. K.; Ber, B. Ya; Kazantsev, D. Yu

    2016-03-01

    The peculiarities of a new type of pseudomorphic AlGaAs/InGaAs/AlGaAs heterostructures with the additional acceptor doping of barriers used for the creation of the power SHF pseudomorphic high electron mobility transistor (pHEMT) have been studied. A comparison of the transport characteristic of the new and typical pHEMT heterostructures was carried out. The influence of the doped acceptor impurities in the AlGaAs barriers of the new pHEMT heterostructure on the transport properties was studied. It was shown that the application of the additional p+ doped barrier layers allows the achievement of a double multiplex increase in the two-dimensional electron gas (2DEG) concentration in the InGaAs quantum well with no parasite parallel conductivity in the AlGaAs barrier layers. An estimation of the concentration of the doped donors and acceptors penetrating into the deliberately undoped InGaAs quantum well from the AlGaAs barriers was performed by second ion mass spectrometry and photoluminescence spectrometry methods. Taking into account the electron scattering by the ionized impurity atoms, calculation of the electron mobility in the InGaAs channel showed that some reduction of the electron mobility results from scattering by the ionized Si donor due to an increase in the Si concentration and, therefore, is not caused by the application of additional p+ doped layers in the construction of pHEMT heterostructures.

  7. Transition Metal Diborides as Electrode Material for MHD Direct Power Extraction: High-temperature Oxidation of ZrB2-HfB2 Solid Solution with LaB6 Addition

    NASA Astrophysics Data System (ADS)

    Sitler, Steven; Hill, Cody; Raja, Krishnan S.; Charit, Indrajit

    2016-06-01

    Transition metal borides are being considered for use as potential electrode coating materials in magnetohydrodynamic direct power extraction plants from coal-fired plasma. These electrode materials will be exposed to aggressive service conditions at high temperatures. Therefore, high-temperature oxidation resistance is an important property. Consolidated samples containing an equimolar solid solution of ZrB2-HfB2 with and without the addition of 1.8 mol pct LaB6 were prepared by ball milling of commercial boride material followed by spark plasma sintering. These samples were oxidized at 1773 K (1500 °C) in two different conditions: (1) as-sintered and (2) anodized (10 V in 0.1 M KOH electrolyte). Oxidation studies were carried out in 0.3 × 105 and 0.1 Pa oxygen partial pressures. The anodic oxide layers showed hafnium enrichment on the surface of the samples, whereas the high-temperature oxides showed zirconium enrichment. The anodized samples without LaB6 addition showed about 2.5 times higher oxidation resistance in high-oxygen partial pressures than the as-sintered samples. Addition of LaB6 improved the oxidation resistance in the as-sintered condition by about 30 pct in the high-oxygen partial pressure tests.

  8. Functional Generalized Additive Models.

    PubMed

    McLean, Mathew W; Hooker, Giles; Staicu, Ana-Maria; Scheipl, Fabian; Ruppert, David

    2014-01-01

    We introduce the functional generalized additive model (FGAM), a novel regression model for association studies between a scalar response and a functional predictor. We model the link-transformed mean response as the integral with respect to t of F{X(t), t} where F(·,·) is an unknown regression function and X(t) is a functional covariate. Rather than having an additive model in a finite number of principal components as in Müller and Yao (2008), our model incorporates the functional predictor directly and thus our model can be viewed as the natural functional extension of generalized additive models. We estimate F(·,·) using tensor-product B-splines with roughness penalties. A pointwise quantile transformation of the functional predictor is also considered to ensure each tensor-product B-spline has observed data on its support. The methods are evaluated using simulated data and their predictive performance is compared with other competing scalar-on-function regression alternatives. We illustrate the usefulness of our approach through an application to brain tractography, where X(t) is a signal from diffusion tensor imaging at position, t, along a tract in the brain. In one example, the response is disease-status (case or control) and in a second example, it is the score on a cognitive test. R code for performing the simulations and fitting the FGAM can be found in supplemental materials available online. PMID:24729671

  9. FERMI OBSERVATIONS OF GRB 090510: A SHORT-HARD GAMMA-RAY BURST WITH AN ADDITIONAL, HARD POWER-LAW COMPONENT FROM 10 keV TO GeV ENERGIES

    SciTech Connect

    Ackermann, M.; Bechtol, K.; Berenji, B.; Blandford, R. D.; Bloom, E. D.; Borgland, A. W.; Bouvier, A.; Asano, K.; Atwood, W. B.; Axelsson, M.; Baldini, L.; Bellazzini, R.; Bregeon, J.; Ballet, J.; Baring, M. G.; Bastieri, D.; Bhat, P. N.; Bissaldi, E.; Bonamente, E. E-mail: sylvain.guiriec@lpta.in2p3.f E-mail: ohno@astro.isas.jaxa.j

    2010-06-20

    We present detailed observations of the bright short-hard gamma-ray burst GRB 090510 made with the Gamma-ray Burst Monitor (GBM) and Large Area Telescope (LAT) on board the Fermi observatory. GRB 090510 is the first burst detected by the LAT that shows strong evidence for a deviation from a Band spectral fitting function during the prompt emission phase. The time-integrated spectrum is fit by the sum of a Band function with E{sub peak} = 3.9 {+-} 0.3 MeV, which is the highest yet measured, and a hard power-law component with photon index -1.62 {+-} 0.03 that dominates the emission below {approx}20 keV and above {approx}100 MeV. The onset of the high-energy spectral component appears to be delayed by {approx}0.1 s with respect to the onset of a component well fit with a single Band function. A faint GBM pulse and a LAT photon are detected 0.5 s before the main pulse. During the prompt phase, the LAT detected a photon with energy 30.5{sup +5.8}{sub -2.6} GeV, the highest ever measured from a short GRB. Observation of this photon sets a minimum bulk outflow Lorentz factor, {Gamma}{approx_gt} 1200, using simple {gamma}{gamma} opacity arguments for this GRB at redshift z = 0.903 and a variability timescale on the order of tens of ms for the {approx}100 keV-few MeV flux. Stricter high confidence estimates imply {Gamma} {approx_gt} 1000 and still require that the outflows powering short GRBs are at least as highly relativistic as those of long-duration GRBs. Implications of the temporal behavior and power-law shape of the additional component on synchrotron/synchrotron self-Compton, external-shock synchrotron, and hadronic models are considered.

  10. Fermi Observations of GRB 090510: A Short-Hard Gamma-ray Burst with an Additional, Hard Power-law Component from 10 keV TO GeV Energies

    NASA Astrophysics Data System (ADS)

    Ackermann, M.; Asano, K.; Atwood, W. B.; Axelsson, M.; Baldini, L.; Ballet, J.; Barbiellini, G.; Baring, M. G.; Bastieri, D.; Bechtol, K.; Bellazzini, R.; Berenji, B.; Bhat, P. N.; Bissaldi, E.; Blandford, R. D.; Bloom, E. D.; Bonamente, E.; Borgland, A. W.; Bouvier, A.; Bregeon, J.; Brez, A.; Briggs, M. S.; Brigida, M.; Bruel, P.; Buson, S.; Caliandro, G. A.; Cameron, R. A.; Caraveo, P. A.; Carrigan, S.; Casandjian, J. M.; Cecchi, C.; Çelik, Ö.; Charles, E.; Chiang, J.; Ciprini, S.; Claus, R.; Cohen-Tanugi, J.; Connaughton, V.; Conrad, J.; Dermer, C. D.; de Palma, F.; Dingus, B. L.; Silva, E. do Couto e.; Drell, P. S.; Dubois, R.; Dumora, D.; Farnier, C.; Favuzzi, C.; Fegan, S. J.; Finke, J.; Focke, W. B.; Frailis, M.; Fukazawa, Y.; Fusco, P.; Gargano, F.; Gasparrini, D.; Gehrels, N.; Germani, S.; Giglietto, N.; Giordano, F.; Glanzman, T.; Godfrey, G.; Granot, J.; Grenier, I. A.; Grondin, M.-H.; Grove, J. E.; Guiriec, S.; Hadasch, D.; Harding, A. K.; Hays, E.; Horan, D.; Hughes, R. E.; Jóhannesson, G.; Johnson, W. N.; Kamae, T.; Katagiri, H.; Kataoka, J.; Kawai, N.; Kippen, R. M.; Knödlseder, J.; Kocevski, D.; Kouveliotou, C.; Kuss, M.; Lande, J.; Latronico, L.; Lemoine-Goumard, M.; Llena Garde, M.; Longo, F.; Loparco, F.; Lott, B.; Lovellette, M. N.; Lubrano, P.; Makeev, A.; Mazziotta, M. N.; McEnery, J. E.; McGlynn, S.; Meegan, C.; Mészáros, P.; Michelson, P. F.; Mitthumsiri, W.; Mizuno, T.; Moiseev, A. A.; Monte, C.; Monzani, M. E.; Moretti, E.; Morselli, A.; Moskalenko, I. V.; Murgia, S.; Nakajima, H.; Nakamori, T.; Nolan, P. L.; Norris, J. P.; Nuss, E.; Ohno, M.; Ohsugi, T.; Omodei, N.; Orlando, E.; Ormes, J. F.; Ozaki, M.; Paciesas, W. S.; Paneque, D.; Panetta, J. H.; Parent, D.; Pelassa, V.; Pepe, M.; Pesce-Rollins, M.; Piron, F.; Preece, R.; Rainò, S.; Rando, R.; Razzano, M.; Razzaque, S.; Reimer, A.; Ritz, S.; Rodriguez, A. Y.; Roth, M.; Ryde, F.; Sadrozinski, H. F.-W.; Sander, A.; Scargle, J. D.; Schalk, T. L.; Sgrò, C.; Siskind, E. J.; Smith, P. D.; Spandre, G.; Spinelli, P.; Stamatikos, M.; Stecker, F. W.; Strickman, M. S.; Suson, D. J.; Tajima, H.; Takahashi, H.; Takahashi, T.; Tanaka, T.; Thayer, J. B.; Thayer, J. G.; Thompson, D. J.; Tibaldo, L.; Toma, K.; Torres, D. F.; Tosti, G.; Tramacere, A.; Uchiyama, Y.; Uehara, T.; Usher, T. L.; van der Horst, A. J.; Vasileiou, V.; Vilchez, N.; Vitale, V.; von Kienlin, A.; Waite, A. P.; Wang, P.; Wilson-Hodge, C.; Winer, B. L.; Wu, X. F.; Yamazaki, R.; Yang, Z.; Ylinen, T.; Ziegler, M.

    2010-06-01

    We present detailed observations of the bright short-hard gamma-ray burst GRB 090510 made with the Gamma-ray Burst Monitor (GBM) and Large Area Telescope (LAT) on board the Fermi observatory. GRB 090510 is the first burst detected by the LAT that shows strong evidence for a deviation from a Band spectral fitting function during the prompt emission phase. The time-integrated spectrum is fit by the sum of a Band function with E peak = 3.9 ± 0.3 MeV, which is the highest yet measured, and a hard power-law component with photon index -1.62 ± 0.03 that dominates the emission below ≈20 keV and above ≈100 MeV. The onset of the high-energy spectral component appears to be delayed by ~0.1 s with respect to the onset of a component well fit with a single Band function. A faint GBM pulse and a LAT photon are detected 0.5 s before the main pulse. During the prompt phase, the LAT detected a photon with energy 30.5+5.8 -2.6 GeV, the highest ever measured from a short GRB. Observation of this photon sets a minimum bulk outflow Lorentz factor, Γgsim 1200, using simple γγ opacity arguments for this GRB at redshift z = 0.903 and a variability timescale on the order of tens of ms for the ≈100 keV-few MeV flux. Stricter high confidence estimates imply Γ >~ 1000 and still require that the outflows powering short GRBs are at least as highly relativistic as those of long-duration GRBs. Implications of the temporal behavior and power-law shape of the additional component on synchrotron/synchrotron self-Compton, external-shock synchrotron, and hadronic models are considered.

  11. Improvement of Transient Voltage Responses using an Additional PID-loop on ANFIS-based Composite Controller-SVC (CC-SVC) to Control Chaos and Voltage Collapse in Power Systems

    NASA Astrophysics Data System (ADS)

    Ginarsa, I. Made; Soeprijanto, Adi; Purnomo, Mauridhi Hery; Syafaruddin, Mauridhi Hery; Hiyama, Takashi

    Chaos and voltage collapse are qualitative behaviors in power systems that exist due to lack of reactive power in critical loading. These phenomena are deeply explored using both detailed and approximate models in this paper. The ANFIS-based CC-SVC with an additional PID-loop was proposed to control these problems and to improve transient response of the detailed model. The main function of the PID-loop was to increase the minimum voltage and to decrease the settling time at transient response. The ANFIS-based method was chosen because its computational complexity was more efficient than Mamdani fuzzy logic controller. Therefore the convergence of training processes was more rapidly achieved by the ANFIS-based method. The load voltage was held to the setting value by adjusting the SVC susceptance properly. From the experimental results, the PID-loop was an effective controller which achieved good simulation result for the reactive load, the minimum voltage increased and the settling time decreased at the values of j0.12pu, 0.9435pu and 7.01s, respectively.

  12. A single-degree-of-freedom dynamic model predicts the range of human responses to impulsive forces produced by power hand tools.

    PubMed

    Lin, Jia-Hua; Radwin, Robert G; Richard, Terry G

    2003-12-01

    The human operator is modelled as a single-degree-of-freedom dynamic mechanical system for predicting the response to impulsive torque reaction forces produced by rotating spindle power hand tools such as nutrunners or screwdrivers. The model uses mass, spring and damping elements to represent the standing operator supporting the tool in the hand. It was hypothesized that these mechanical elements are affected by work location and vary among individuals. These elements were ascertained by measuring the resulting frequency and amplitude of a freely oscillating defined mechanical system when externally loaded using maximal effort to oppose its motion. Twenty-five subjects (13 female, 12 male) participated in the full factorial experiment that measured the effects of gender, vertical and horizontal work location for various tool shapes (in-line, pistol, right angle), and orientations (horizontal and vertical). The mean operator stiffness decreased from 1721 to 1195 N/m when the horizontal work location increased from 30 to 90 cm in front of the ankles for a pistol-grip handle used on a vertical surface. Males had greater mass moment of inertia of (0.0099 kg m2) than females (0.0072 kg m2) for an in-line handle used on a horizontal surface. Internal validation by independently measuring apparatus torque found that the model satisfactorily explained the measured operator dynamics with an average error of 2.86%. Group variance reflects the range of operator capacities to react against power hand tool generated forces for the sample group and therefore it may also be useful for understanding the range of capacities among a group of operators performing similar tasks. PMID:14614938

  13. Two-gene signature improves the discriminatory power of IASLC/ATS/ERS classification to predict the survival of patients with early-stage lung adenocarcinoma

    PubMed Central

    Sun, Yifeng; Hou, Likun; Yang, Yu; Xie, Huikang; Yang, Yang; Li, Zhigang; Zhao, Heng; Gao, Wen; Su, Bo

    2016-01-01

    risk factor of the IASLC/ATS/ERS classification, which can be used to improve the discriminatory power of prognosis prediction of the IASLC/ATS/ERS classification in early-stage lung adenocarcinoma. The two-gene signature combination with the IASLC/ATS/ERS classification might contribute to better patient stratification for adjuvant chemoradiotherapy or targeted therapy after the surgery. PMID:27524912

  14. ADDITIVITY ASSESSMENT OF TRIHALOMETHANE MIXTURES BY PROPORTIONAL RESPONSE ADDITION

    EPA Science Inventory

    If additivity is known or assumed, the toxicity of a chemical mixture may be predicted from the dose response curves of the individual chemicals comprising the mixture. As single chemical data are abundant and mixture data sparse, mixture risk methods that utilize single chemical...

  15. Smoking-related thoughts and microbehaviours and their predictive power for quitting: Findings from the International Tobacco Control (ITC) China Survey

    PubMed Central

    Li, Lin; Borland, Ron; Fong, Geoffrey T.; Jiang, Yuan; Yang, Yan; Wang, Lili; Partos, Timea R.; Thrasher, James F.

    2015-01-01

    Background Negative attitudes to smoking are well-established predictors of intentions to quit and quit behaviours, but less attention has been given to whether quitting is influenced by smoking-related thoughts and microbehaviours that reflect a concern about smoking. Objectives This paper aimed to describe the occurrence of smoking-related thoughts and microbehaviours among Chinese smokers and to examine their predictive power for making quit attempts and sustained abstinence. Methods The data came from the first three waves of the International Tobacco Control China Survey. Four measures of recent thoughts about smoking and two microbehaviour measures (collectively referred to as micro indicators) were examined. Results Most smokers (around three quarters) reported thinking about harms of smoking to themselves or to others at least occasionally, and an increasing minority reported the two microbehaviours of prematurely butting out cigarettes and forgoing them. All micro indicators were positively related to subsequent quit attempts in individual predictor analyses, but only serious thoughts about quitting and -butting out cigarettes had independent relationships. Overall, there was no clear relationship between these micro indicators and sustained abstinence. Conclusions There was a moderately high level of occurrence of recent smoking-related thoughts and microbehaviours among the Chinese adult smokers in the six cities studied. Like in the west, micro indicators of concern about smoking were positively associated with subsequent quit attempts, but unlike in the west, they were largely unrelated to sustained abstinence. PMID:24570098

  16. Latinas and Postpartum Depression: Role of Partner Relationship, Additional Children, and Breastfeeding

    ERIC Educational Resources Information Center

    Hassert, Silva; Kurpius, Sharon E. Robinson

    2011-01-01

    Breastfeeding, additional children, and partner relationship predicted postpartum depression among 59 Latinas who had an infant who was 6 months old or younger. The most powerful predictor was conflict with partner. Counselors working with Latinas experiencing postpartum depression should explore the partner relationship, particularly relationship…

  17. Power management system

    DOEpatents

    Algrain, Marcelo C.; Johnson, Kris W.; Akasam, Sivaprasad; Hoff, Brian D.

    2007-10-02

    A method of managing power resources for an electrical system of a vehicle may include identifying enabled power sources from among a plurality of power sources in electrical communication with the electrical system and calculating a threshold power value for the enabled power sources. A total power load placed on the electrical system by one or more power consumers may be measured. If the total power load exceeds the threshold power value, then a determination may be made as to whether one or more additional power sources is available from among the plurality of power sources. At least one of the one or more additional power sources may be enabled, if available.

  18. Assessment of potential for small hydro/solar power integration in a mountainous, data sparse region: the role of hydrological prediction accuracy

    NASA Astrophysics Data System (ADS)

    Borga, Marco; Francois, Baptiste; Creutin, Jean-Dominique; Hingray, Benoit; Zoccatelli, Davide; Tardivo, Gianmarco

    2015-04-01

    In many parts of the world, integration of small hydropower and solar/wind energy sources along river systems is examined as a way to meet pressing renewable energy targets. Depending on the space and time scales considered, hydrometeorological variability may synchronize or desynchronize solar/wind, runoff and the demand opening the possibility to use their complementarity to smooth the intermittency of each individual energy source. Rivers also provide important ecosystem services, including the provision of high quality downstream water supply and the maintenance of in-stream habitats. With future supply and demand of water resources both impacted by environmental change, a good understanding of the potential for the integration among hydropower and solar/wind energy sources in often sparsely gauged catchments is important. In such cases, where complex data-demanding models may be inappropriate, there is a need for simple conceptual modelling approaches that can still capture the main features of runoff generation and artificial regulation processes. In this work we focus on run-of-the-river and solar-power interaction assessment. In order to catch the three key cycles of the load fluctuation - daily, weekly and seasonal, the time step used in the study is the hourly resolution. We examine the performance of a conceptual hydrological model which includes facilities to model dam regulation and diversions and hydrological modules to account for the effect of glaciarised catchments. The model is applied to catchments of the heavily regulated Upper Adige river system (6900 km2), Eastern Italian Alps, which has a long history of hydropower generation. The model is used to characterize and predict the natural flow regime, assess the regulation impacts, and simulate co-fluctuations between run-of- the-river and solar power. The results demonstrates that the simple, conceptual modelling approach developed here can capture the main hydrological and regulation processes

  19. Model prediction for ranking lead-acid batteries according to expected lifetime in renewable energy systems and autonomous power-supply systems

    NASA Astrophysics Data System (ADS)

    Schiffer, Julia; Sauer, Dirk Uwe; Bindner, Henrik; Cronin, Tom; Lundsager, Per; Kaiser, Rudi

    Predicting the lifetime of lead-acid batteries in applications with irregular operating conditions such as partial state-of-charge cycling, varying depth-of-discharge and different times between full charging is known as a difficult task. Experimental investigations in the laboratory are difficult because each application has its own specific operation profile. Therefore, an experimental investigation is necessary for each application and, moreover, for each operation strategy. This paper presents a lifetime model that allows comparison of the impact of different operating conditions, different system sizing and different battery technologies on battery lifetime. It is a tool for system designers and system operators to select appropriate batteries, to do a proper system design (sizing of the battery, power generators and loads), and to implement an optimized operation strategy (end-of-charge voltage, frequency of full charging, gassing periods, maximum depth-of-discharge). The model is a weighted Ah throughput approach based on the assumption that operating conditions are typically more severe than those used in standard tests of cycling and float lifetime. The wear depends on the depth-of-discharge, the current rate, the existing acid stratification, and the time since the last full charging. The actual Ah throughput is continuously multiplied by a weight factor that represents the actual operating conditions. Even though the modelling approach is mainly heuristic, all of the effects that are taken into account are based on a detailed analysis and understanding of ageing processes in lead-acid batteries. The 'normal' user can adapt the model to different battery types simply from the data sheet information on cycle lifetime and float lifetime.

  20. Predicting the long-term (137)Cs distribution in Fukushima after the Fukushima Dai-ichi nuclear power plant accident: a parameter sensitivity analysis.

    PubMed

    Yamaguchi, Masaaki; Kitamura, Akihiro; Oda, Yoshihiro; Onishi, Yasuo

    2014-09-01

    Radioactive materials deposited on the land surface of Fukushima Prefecture from the Fukushima Dai-ichi Nuclear Power Plant explosion is a crucial issue for a number of reasons, including external and internal radiation exposure and impacts on agricultural environments and aquatic biota. Predicting the future distribution of radioactive materials and their fates is therefore indispensable for evaluation and comparison of the effectiveness of remediation options regarding human health and the environment. Cesium-137, the main radionuclide to be focused on, is well known to adsorb to clay-rich soils; therefore its primary transportation mechanism is in the form of soil erosion on the land surface and transport of sediment-sorbed contaminants in the water system. In this study, we applied the Soil and Cesium Transport model, which we have developed, to predict a long-term cesium distribution in the Fukushima area, based on the Universal Soil Loss Equation and simple sediment discharge formulas. The model consists of calculation schemes of soil erosion, transportation and deposition, as well as cesium transport and its future distribution. Since not all the actual data on parameters is available, a number of sensitivity analyses were conducted here to find the range of the output results due to the uncertainties of parameters. The preliminary calculation indicated that a large amount of total soil loss remained in slope, and the residual sediment was transported to rivers, deposited in rivers and lakes, or transported farther downstream to the river mouths. Most of the sediment deposited in rivers and lakes consists of sand. On the other hand, most of the silt and clay portions transported to river were transported downstream to the river mouths. The rate of sediment deposition in the Abukuma River basin was three times as high as those of the other 13 river basins. This may be due to the larger catchment area and more moderate channel slope of the Abukuma River basin

  1. 18 CFR 33.10 - Additional information.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    .... 33.10 Section 33.10 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY REGULATIONS UNDER THE FEDERAL POWER ACT APPLICATIONS UNDER FEDERAL POWER ACT SECTION 203 § 33.10 Additional information. The Director of the Office of Energy Market Regulation, or his...

  2. Additional short-term plutonium urinary excretion data from the 1945-1947 plutonium injection studies

    SciTech Connect

    Moss, W.D.; Gautier, M.A.

    1986-01-01

    The amount of plutonium excreted per day following intravenous injection was shown to be significantly higher than predicted by the Langham power function model. Each of the Los Alamos National Laboratory notebooks used to record the original analytical data was studied for details that could influence the findings. It was discovered there were additional urine excretion data for case HP-3. This report presents the additional data, as well as data on case HP-6. (ACR)

  3. EFFECT OF VITAMIN C ADDITION TO GROUND BEEF FROM GRASS-FED OR GRAIN-FED SOURCES ON COLOR AND LIPID STABILITY, AND PREDICTION OF FATTY ACID COMPOSITION BY NEAR INFRARED REFLECTANCE ANALYSIS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Research was conducted to determine the effect of postmortem vitamin C addition (VITC) versus no VITC (CONTROL) to ground beef from grass-fed (GRASS) or grain-fed (GRAIN) sources on color and lipid stability during 8 d of illuminated display at 4°C. The use of near infrared reflectance (NIR) spectro...

  4. Effectiveness of evaluating tumor vascularization using 3D power Doppler ultrasound with high-definition flow technology in the prediction of the response to neoadjuvant chemotherapy for T2 breast cancer: a preliminary report

    NASA Astrophysics Data System (ADS)

    Shia, Wei-Chung; Chen, Dar-Ren; Huang, Yu-Len; Wu, Hwa-Koon; Kuo, Shou-Jen

    2015-10-01

    The aim of this study was to evaluate the effectiveness of advanced ultrasound (US) imaging of vascular flow and morphological features in the prediction of a pathologic complete response (pCR) and a partial response (PR) to neoadjuvant chemotherapy for T2 breast cancer. Twenty-nine consecutive patients with T2 breast cancer treated with six courses of anthracycline-based neoadjuvant chemotherapy were enrolled. Three-dimensional (3D) power Doppler US with high-definition flow (HDF) technology was used to investigate the blood flow in and morphological features of the tumors. Six vascularity quantization features, three morphological features, and two vascular direction features were selected and extracted from the US images. A support vector machine was used to evaluate the changes in vascularity after neoadjuvant chemotherapy, and pCR and PR were predicted on the basis of these changes. The most accurate prediction of pCR was achieved after the first chemotherapy cycle, with an accuracy of 93.1% and a specificity of 85.5%, while that of a PR was achieved after the second cycle, with an accuracy of 79.31% and a specificity of 72.22%. Vascularity data can be useful to predict the effects of neoadjuvant chemotherapy. Determination of changes in vascularity after neoadjuvant chemotherapy using 3D power Doppler US with HDF can generate accurate predictions of the patient response, facilitating early decision-making.

  5. Effectiveness of evaluating tumor vascularization using 3D power Doppler ultrasound with high-definition flow technology in the prediction of the response to neoadjuvant chemotherapy for T2 breast cancer: a preliminary report.

    PubMed

    Shia, Wei-Chung; Chen, Dar-Ren; Huang, Yu-Len; Wu, Hwa-Koon; Kuo, Shou-Jen

    2015-10-01

    The aim of this study was to evaluate the effectiveness of advanced ultrasound (US) imaging of vascular flow and morphological features in the prediction of a pathologic complete response (pCR) and a partial response (PR) to neoadjuvant chemotherapy for T2 breast cancer.Twenty-nine consecutive patients with T2 breast cancer treated with six courses of anthracycline-based neoadjuvant chemotherapy were enrolled. Three-dimensional (3D) power Doppler US with high-definition flow (HDF) technology was used to investigate the blood flow in and morphological features of the tumors. Six vascularity quantization features, three morphological features, and two vascular direction features were selected and extracted from the US images. A support vector machine was used to evaluate the changes in vascularity after neoadjuvant chemotherapy, and pCR and PR were predicted on the basis of these changes.The most accurate prediction of pCR was achieved after the first chemotherapy cycle, with an accuracy of 93.1% and a specificity of 85.5%, while that of a PR was achieved after the second cycle, with an accuracy of 79.31% and a specificity of 72.22%.Vascularity data can be useful to predict the effects of neoadjuvant chemotherapy. Determination of changes in vascularity after neoadjuvant chemotherapy using 3D power Doppler US with HDF can generate accurate predictions of the patient response, facilitating early decision-making. PMID:26393306

  6. Predictive complexation models of the impact of natural organic matter and cations on scaling in cooling water pipes: A case study of power generation plants in South Africa

    NASA Astrophysics Data System (ADS)

    Bosire, G. O.; Ngila, J. C.; Mbugua, J. M.

    This work discusses simulative models of Ca and Mg complexation with natural organic matter (NOM), in order to control the incidence of scaling in pipes carrying cooling water at the Eskom power generating stations in South Africa. In particular, the paper reports how parameters such as pH and trace element levels influence the distribution of scaling species and their interactions, over and above mineral phase saturation indices. In order to generate modelling inputs, two experimental scenarios were created in the model solutions: Firstly, the trace metals Cu, Pb and Zn were used as markers for Ca and Mg complexation to humic acid and secondly the effect of natural organic matter in cooling water was determined by spiking model solutions. Labile metal ions and total elements in model solutions and water samples were analysed by square wave anodic stripping voltammetry and inductively coupled plasma optical emission spectrometry (ICP-OES), respectively. ICP-OES results revealed high levels of K, Na, S, Mg and Ca and low levels of trace elements (Cd, Se, Pb, Cu, Mn, Mo, Ni, Al and Zn) in the cooling water samples. Using the Tipping and Hurley's database WHAM in PHREEQC format (T_H.DAT), the total elemental concentrations were run as inputs on a PHREEQC code, at pH 6.8 and defined charge as alkalinity (as HCO3-) For model solutions, PHREEQC inputs were based on (i) free metal differences attributed to competitive effect of Ca and the effect of Ca + Mg, respectively; (ii) total Ca and Mg used in the model solutions and (iii) alkalinity described as hydrogen carbonate. Anodic stripping peak heights were used to calculate the concentration of the free/uncomplexed/labile metal ions (used as tracers) in the model solutions. The objective of modelling was to describe scaling in terms of saturation indices of mineral phases. Accordingly, the minerals most likely to generate scale were further simulated (over a range of pH (3-10) to yield results that mimicked changing p

  7. Child Abuse Screening: Implications of the Limited Predictive Power of Abuse Discriminants from a Controlled Family Study of Pediatric Social Illness.

    ERIC Educational Resources Information Center

    Daniel, Jessica H.; And Others

    The predictive value of a child abuse screening instrument on unselected populations is illustrated for varying hypothesized levels of child abuse prevalence to demonstrate outcome of a hypothetical national screening program. At any level of application, the prediction of false positives (nonabusing families labeled as abusing or potentially…

  8. Successful Predictions

    NASA Astrophysics Data System (ADS)

    Pierrehumbert, R.

    2012-12-01

    In an observational science, it is not possible to test hypotheses through controlled laboratory experiments. One can test parts of the system in the lab (as is done routinely with infrared spectroscopy of greenhouse gases), but the collective behavior cannot be tested experimentally because a star or planet cannot be brought into the lab; it must, instead, itself be the lab. In the case of anthropogenic global warming, this is all too literally true, and the experiment would be quite exciting if it weren't for the unsettling fact that we and all our descendents for the forseeable future will have to continue making our home in the lab. There are nonetheless many routes though which the validity of a theory of the collective behavior can be determined. A convincing explanation must not be a"just-so" story, but must make additional predictions that can be verified against observations that were not originally used in formulating the theory. The field of Earth and planetary climate has racked up an impressive number of such predictions. I will also admit as "predictions" statements about things that happened in the past, provided that observations or proxies pinning down the past climate state were not available at the time the prediction was made. The basic prediction that burning of fossil fuels would lead to an increase of atmospheric CO2, and that this would in turn alter the Earth's energy balance so as to cause tropospheric warming, is one of the great successes of climate science. It began in the lineage of Fourier, Tyndall and Arrhenius, and was largely complete with the the radiative-convective modeling work of Manabe in the 1960's -- all well before the expected warming had progressed far enough to be observable. Similarly, long before the increase in atmospheric CO2 could be detected, Bolin formulated a carbon cycle model and used it to predict atmospheric CO2 out to the year 2000; the actual values come in at the high end of his predicted range, for

  9. Predicting Aircraft Noise Levels

    NASA Technical Reports Server (NTRS)

    Clark, B. J.

    1983-01-01

    Computer program developed for predicting aircraft noise levels either in flight or in ground tests. Noise sources include fan inlet and exhaust jet flap (for powered lift), core (combustor), turbine and airframe. Program written in FORTRAN IV.

  10. Program Predicts Nonlinear Inverter Performance

    NASA Technical Reports Server (NTRS)

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

    1985-01-01

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

  11. [Food additives and healthiness].

    PubMed

    Heinonen, Marina

    2014-01-01

    Additives are used for improving food structure or preventing its spoilage, for example. Many substances used as additives are also naturally present in food. The safety of additives is evaluated according to commonly agreed principles. If high concentrations of an additive cause adverse health effects for humans, a limit of acceptable daily intake (ADI) is set for it. An additive is a risk only when ADI is exceeded. The healthiness of food is measured on the basis of nutrient density and scientifically proven effects. PMID:24772784

  12. Polyimide processing additives

    NASA Technical Reports Server (NTRS)

    Pratt, J. R.; St. Clair, T. L.; Burks, H. D.; Stoakley, D. M.

    1987-01-01

    A method has been found for enhancing the melt flow of thermoplastic polyimides during processing. A high molecular weight 422 copoly(amic acid) or copolyimide was fused with approximately 0.05 to 5 pct by weight of a low molecular weight amic acid or imide additive, and this melt was studied by capillary rheometry. Excellent flow and improved composite properties on graphite resulted from the addition of a PMDA-aniline additive to LARC-TPI. Solution viscosity studies imply that amic acid additives temporarily lower molecular weight and, hence, enlarge the processing window. Thus, compositions containing the additive have a lower melt viscosity for a longer time than those unmodified.

  13. Power system

    DOEpatents

    Hickam, Christopher Dale

    2008-03-18

    A power system includes a prime mover, a transmission, and a fluid coupler having a selectively engageable lockup clutch. The fluid coupler may be drivingly connected between the prime mover and the transmission. Additionally, the power system may include a motor/generator drivingly connected to at least one of the prime mover and the transmission. The power-system may also include power-system controls configured to execute a control method. The control method may include selecting one of a plurality of modes of operation of the power system. Additionally, the control method may include controlling the operating state of the lockup clutch dependent upon the mode of operation selected. The control method may also include controlling the operating state of the motor/generator dependent upon the mode of operation selected.

  14. Atomistic Simulations of Ti Additions to NiAl

    NASA Technical Reports Server (NTRS)

    Bozzolo, Guillermo; Noebe, Ronald D.; Garg, Anita; Ferrante, John; Amador, Carlos

    1997-01-01

    The development of more efficient engines and power plants for future supersonic transports depends on the advancement of new high-temperature materials with temperature capabilities exceeding those of Ni-based superalloys. Having theoretical modelling techniques to aid in the design of these alloys would greatly facilitate this development. The present paper discusses a successful attempt to correlate theoretical predictions of alloy properties with experimental confirmation for ternary NiAl-Ti alloys. The B.F.S. (Bozzolo-Ferrante-Smith) method for alloys is used to predict the solubility limit and site preference energies for Ti additions of 1 to 25 at.% to NiAl. The results show the solubility limit to be around 5% Ti, above which the formation of Heusler precipitates is favored. These results were confirmed by transmission electron microscopy performed on a series of NiAl-Ti alloys.

  15. Atomistic simulations of Ti additions to NiAl

    SciTech Connect

    Bozzolo, G.; Noebe, R.D.; Garg, A.; Ferrante, J.; Amador, C.

    1997-12-31

    The development of more efficient engines and power plants for future supersonic transports depend on the advancement of new high-temperature materials with temperature capabilities exceeding those of Ni-based superalloys. Having theoretical modelling techniques to aid in the design of these alloys would greatly facilitate this development. The present paper discusses a successful attempt to correlate theoretical predictions of alloy properties with experimental confirmation for ternary NiAl-Ti alloys. The B.F.S. (Bozzolo- Ferrante-Smith) method for alloys is used to predict the solubility limit and site preference energies for Ti additions of 1 to 25 at. % to NiAl. The results show the solubility limit to be around 5% Ti, above which the formation of Heusler precipitates is favored. These results were confirmed by transmission electron microscopy performed on a series of NiAl-Ti alloys.

  16. Using ensemble NWP wind power forecasts to improve national power system management

    NASA Astrophysics Data System (ADS)

    Cannon, D.; Brayshaw, D.; Methven, J.; Coker, P.; Lenaghan, D.

    2014-12-01

    National power systems are becoming increasingly sensitive to atmospheric variability as generation from wind (and other renewables) increases. As such, the days-ahead predictability of wind power has significant implications for power system management. At this time horizon, power system operators plan transmission line outages for maintenance. In addition, forecast users begin to form backup strategies to account for the uncertainty in wind power predictions. Under-estimating this uncertainty could result in a failure to meet system security standards, or in the worst instance, a shortfall in total electricity supply. On the other hand, overly conservative assumptions about the forecast uncertainty incur costs associated with the unnecessary holding of reserve power. Using the power system of Great Britain (GB) as an example, we construct time series of GB-total wind power output using wind speeds from either reanalyses or global weather forecasts. To validate the accuracy of these data sets, wind power reconstructions using reanalyses and forecast analyses over a recent period are compared to measured GB-total power output. The results are found to be highly correlated on time scales greater than around 6 hours. Results are presented using ensemble wind power forecasts from several national and international forecast centres (obtained through TIGGE). Firstly, the skill with which global ensemble forecasts can represent the uncertainty in the GB-total power output at up to 10 days ahead is quantified. Following this, novel ensemble forecast metrics are developed to improve estimates of forecast uncertainty within the context of power system operations, thus enabling the development of more cost effective strategies. Finally, the predictability of extreme events such as prolonged low wind periods or rapid changes in wind power output are examined in detail. These events, if poorly forecast, induce high stress scenarios that could threaten the security of the power

  17. Power Curve Modeling in Complex Terrain Using Statistical Models

    NASA Astrophysics Data System (ADS)

    Bulaevskaya, V.; Wharton, S.; Clifton, A.; Qualley, G.; Miller, W.

    2014-12-01

    Traditional power output curves typically model power only as a function of the wind speed at the turbine hub height. While the latter is an essential predictor of power output, wind speed information in other parts of the vertical profile, as well as additional atmospheric variables, are also important determinants of power. The goal of this work was to determine the gain in predictive ability afforded by adding wind speed information at other heights, as well as other atmospheric variables, to the power prediction model. Using data from a wind farm with a moderately complex terrain in the Altamont Pass region in California, we trained three statistical models, a neural network, a random forest and a Gaussian process model, to predict power output from various sets of aforementioned predictors. The comparison of these predictions to the observed power data revealed that considerable improvements in prediction accuracy can be achieved both through the addition of predictors other than the hub-height wind speed and the use of statistical models. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344 and was funded by Wind Uncertainty Quantification Laboratory Directed Research and Development Project at LLNL under project tracking code 12-ERD-069.

  18. Additive usage levels.

    PubMed

    Langlais, R

    1996-01-01

    With the adoption of the European Parliament and Council Directives on sweeteners, colours and miscellaneous additives the Commission is now embarking on the project of coordinating the activities of the European Union Member States in the collection of the data that are to make up the report on food additive intake requested by the European Parliament. This presentation looks at the inventory of available sources on additive use levels and concludes that for the time being national legislation is still the best source of information considering that the directives have yet to be transposed into national legislation. Furthermore, this presentation covers the correlation of the food categories as found in the additives directives with those used by national consumption surveys and finds that in a number of instances this correlation still leaves a lot to be desired. The intake of additives via food ingestion and the intake of substances which are chemically identical to additives but which occur naturally in fruits and vegetables is found in a number of cases to be higher than the intake of additives added during the manufacture of foodstuffs. While the difficulties are recognized in contributing to the compilation of food additive intake data, industry as a whole, i.e. the food manufacturing and food additive manufacturing industries, are confident that in a concerted effort, use data on food additives by industry can be made available. Lastly, the paper points out that with the transportation of the additives directives into national legislation and the time by which the food industry will be able to make use of the new food legislative environment several years will still go by; food additives use data by the food industry will thus have to be reviewed at the beginning of the next century. PMID:8792135

  19. An additional middle cuneiform?

    PubMed Central

    Brookes-Fazakerley, S.D.; Jackson, G.E.; Platt, S.R.

    2015-01-01

    Additional cuneiform bones of the foot have been described in reference to the medial bipartite cuneiform or as small accessory ossicles. An additional middle cuneiform has not been previously documented. We present the case of a patient with an additional ossicle that has the appearance and location of an additional middle cuneiform. Recognizing such an anatomical anomaly is essential for ruling out second metatarsal base or middle cuneiform fractures and for the preoperative planning of arthrodesis or open reduction and internal fixation procedures in this anatomical location. PMID:26224890

  20. [INVITED] Lasers in additive manufacturing

    NASA Astrophysics Data System (ADS)

    Pinkerton, Andrew J.

    2016-04-01

    Additive manufacturing is a topic of considerable ongoing interest, with forecasts predicting it to have major impact on industry in the future. This paper focusses on the current status and potential future development of the technology, with particular reference to the role of lasers within it. It begins by making clear the types and roles of lasers in the different categories of additive manufacturing. This is followed by concise reviews of the economic benefits and disadvantages of the technology, current state of the market and use of additive manufacturing in different industries. Details of these fields are referenced rather than expanded in detail. The paper continues, focusing on current indicators to the future of additive manufacturing. Barriers to its development, trends and opportunities in major industrial sectors, and wider opportunities for its development are covered. Evidence indicates that additive manufacturing may not become the dominant manufacturing technology in all industries, but represents an excellent opportunity for lasers to increase their influence in manufacturing as a whole.

  1. Does Preoperative Measurement of Cerebral Blood Flow with Acetazolamide Challenge in Addition to Preoperative Measurement of Cerebral Blood Flow at the Resting State Increase the Predictive Accuracy of Development of Cerebral Hyperperfusion after Carotid Endarterectomy? Results from 500 Cases with Brain Perfusion Single-photon Emission Computed Tomography Study

    PubMed Central

    OSHIDA, Sotaro; OGASAWARA, Kuniaki; SAURA, Hiroaki; YOSHIDA, Koji; FUJIWARA, Shunro; KOJIMA, Daigo; KOBAYASHI, Masakazu; YOSHIDA, Kenji; KUBO, Yoshitaka; OGAWA, Akira

    2015-01-01

    The purpose of the present study was to determine whether preoperative measurement of cerebral blood flow (CBF) with acetazolamide in addition to preoperative measurement of CBF at the resting state increases the predictive accuracy of development of cerebral hyperperfusion after carotid endarterectomy (CEA). CBF at the resting state and cerebrovascular reactivity (CVR) to acetazolamide were quantitatively assessed using N-isopropyl-p-[123I]-iodoamphetamine (IMP)-autoradiography method with single-photon emission computed tomography (SPECT) before CEA in 500 patients with ipsilateral internal carotid artery stenosis (≥ 70%). CBF measurement using 123I-IMP SPECT was also performed immediately and 3 days after CEA. A region of interest (ROI) was automatically placed in the middle cerebral artery territory in the affected cerebral hemisphere using a three-dimensional stereotactic ROI template. Preoperative decreases in CBF at the resting state [95% confidence intervals (CIs), 0.855 to 0.967; P = 0.0023] and preoperative decreases in CVR to acetazolamide (95% CIs, 0.844 to 0.912; P < 0.0001) were significant independent predictors of post-CEA hyperperfusion. The area under the receiver operating characteristic curve for prediction of the development of post-CEA hyperperfusion was significantly greater for CVR to acetazolamide than for CBF at the resting state (difference between areas, 0.173; P < 0.0001). Sensitivity, specificity, and positive- and negative-predictive values for the prediction of the development of post-CEA hyperperfusion were significantly greater for CVR to acetazolamide than for CBF at the resting state (P < 0.05, respectively). The present study demonstrated that preoperative measurement of CBF with acetazolamide in addition to preoperative measurement of CBF at the resting state increases the predictive accuracy of the development of post-CEA hyperperfusion. PMID:25746308

  2. Carbamate deposit control additives

    SciTech Connect

    Honnen, L.R.; Lewis, R.A.

    1980-11-25

    Deposit control additives for internal combustion engines are provided which maintain cleanliness of intake systems without contributing to combustion chamber deposits. The additives are poly(oxyalkylene) carbamates comprising a hydrocarbyloxyterminated poly(Oxyalkylene) chain of 2-5 carbon oxyalkylene units bonded through an oxycarbonyl group to a nitrogen atom of ethylenediamine.

  3. Potential of laser for SPS power transmission

    NASA Technical Reports Server (NTRS)

    Bain, C. N.

    1978-01-01

    Research on the feasibility of using a laser subsystem as an additional option for the transmission of the satellite power system (STS) power is presented. Current laser work and predictions for future laser performance provide a level of confidence that the development of a laser power transmission system is technologically feasible in the time frame required to develop the SBS. There are significant economic advantages in lower ground distribution costs and a reduction of more than two orders of magnitude in real estate requirements for ground based receiving/conversion sites.

  4. French and English Together: An "Additive" Experience

    ERIC Educational Resources Information Center

    Wiltshire, Jessica; Harbon, Lesley

    2010-01-01

    This paper examines the nature of the "additive" experience of a bilingual French-English curriculum at Killarney Heights Public School in New South Wales. Predictably, the well-supported "additive" nature of the languages program model elicited positive reactions regarding educational success. The paper also explores issues for administration,…

  5. Is there evidence for additional neutrino species from cosmology?

    SciTech Connect

    Feeney, Stephen M.; Peiris, Hiranya V.; Verde, Licia E-mail: h.peiris@ucl.ac.uk

    2013-04-01

    It has been suggested that recent cosmological and flavor-oscillation data favor the existence of additional neutrino species beyond the three predicted by the Standard Model of particle physics. We apply Bayesian model selection to determine whether there is indeed any evidence from current cosmological datasets for the standard cosmological model to be extended to include additional neutrino flavors. The datasets employed include cosmic microwave background temperature, polarization and lensing power spectra, and measurements of the baryon acoustic oscillation scale and the Hubble constant. We also consider other extensions to the standard neutrino model, such as massive neutrinos, and possible degeneracies with other cosmological parameters. The Bayesian evidence indicates that current cosmological data do not require any non-standard neutrino properties.

  6. Polyimide processing additives

    NASA Technical Reports Server (NTRS)

    Fletcher, James C. (Inventor); Pratt, J. Richard (Inventor); St.clair, Terry L. (Inventor); Stoakley, Diane M. (Inventor); Burks, Harold D. (Inventor)

    1992-01-01

    A process for preparing polyimides having enhanced melt flow properties is described. The process consists of heating a mixture of a high molecular weight poly-(amic acid) or polyimide with a low molecular weight amic acid or imide additive in the range of 0.05 to 15 percent by weight of additive. The polyimide powders so obtained show improved processability, as evidenced by lower melt viscosity by capillary rheometry. Likewise, films prepared from mixtures of polymers with additives show improved processability with earlier onset of stretching by TMA.

  7. Polyimide processing additives

    NASA Technical Reports Server (NTRS)

    Pratt, J. Richard (Inventor); St.clair, Terry L. (Inventor); Stoakley, Diane M. (Inventor); Burks, Harold D. (Inventor)

    1993-01-01

    A process for preparing polyimides having enhanced melt flow properties is described. The process consists of heating a mixture of a high molecular weight poly-(amic acid) or polyimide with a low molecular weight amic acid or imide additive in the range of 0.05 to 15 percent by weight of the additive. The polyimide powders so obtained show improved processability, as evidenced by lower melt viscosity by capillary rheometry. Likewise, films prepared from mixtures of polymers with additives show improved processability with earlier onset of stretching by TMA.

  8. Regiodivergent Addition of Phenols to Allylic Oxides

    PubMed Central

    Vaccarello, David N.; Moschitto, Matthew J.; Lewis, Chad A.

    2015-01-01

    The regiodivergent addition of substituted phenols to allylic-oxides has been demonstrated using C2-symmetric palladium complexes. Complex phenol donors tyrosine, estradiol, and griseofulvin follow the predictive model. The Tsuji-Trost reaction is a powerful method to append both O- and C-donors to η3-allyl systems.1 The η3-allyl progenitor structures include allylic esters, carbonates, halides, and oxides. Internal allylic oxides2 remain one of the few systems that retain a marker of stereochemical induction with the newly liberated carbinol. The origin of the products can be traced to the diastereomeric η3-allyl intermediate and stereoisomer of oxide employed. We have recently identified3 a system capable of the conversion of racemic allylic oxides to distinct enantioenriched regioisomers using achiral phenol donors (Scheme 1). The allylic oxide regio-resolution (AORR) allowed the preparation of enantioenriched carbasugar natural products. We have now expanded this study to include a diverse array of achiral and chiral phenol donors. PMID:25933102

  9. Smog control fuel additives

    SciTech Connect

    Lundby, W.

    1993-06-29

    A method is described of controlling, reducing or eliminating, ozone and related smog resulting from photochemical reactions between ozone and automotive or industrial gases comprising the addition of iodine or compounds of iodine to hydrocarbon-base fuels prior to or during combustion in an amount of about 1 part iodine per 240 to 10,000,000 parts fuel, by weight, to be accomplished by: (a) the addition of these inhibitors during or after the refining or manufacturing process of liquid fuels; (b) the production of these inhibitors for addition into fuel tanks, such as automotive or industrial tanks; or (c) the addition of these inhibitors into combustion chambers of equipment utilizing solid fuels for the purpose of reducing ozone.

  10. Food Additives and Hyperkinesis

    ERIC Educational Resources Information Center

    Wender, Ester H.

    1977-01-01

    The hypothesis that food additives are causally associated with hyperkinesis and learning disabilities in children is reviewed, and available data are summarized. Available from: American Medical Association 535 North Dearborn Street Chicago, Illinois 60610. (JG)

  11. Additional Types of Neuropathy

    MedlinePlus

    ... A A Listen En Español Additional Types of Neuropathy Charcot's Joint Charcot's Joint, also called neuropathic arthropathy, ... can stop bone destruction and aid healing. Cranial Neuropathy Cranial neuropathy affects the 12 pairs of nerves ...

  12. Constraints on the power spectrum of the primordial density field from large-scale data - Microwave background and predictions of inflation

    NASA Technical Reports Server (NTRS)

    Kashlinsky, A.

    1992-01-01

    It is shown here that, by using galaxy catalog correlation data as input, measurements of microwave background radiation (MBR) anisotropies should soon be able to test two of the inflationary scenario's most basic predictions: (1) that the primordial density fluctuations produced were scale-invariant and (2) that the universe is flat. They should also be able to detect anisotropies of large-scale structure formed by gravitational evolution of density fluctuations present at the last scattering epoch. Computations of MBR anisotropies corresponding to the minimum of the large-scale variance of the MBR anisotropy are presented which favor an open universe with P(k) significantly different from the Harrison-Zeldovich spectrum predicted by most inflationary models.

  13. Multi-heat addition turbine engine

    NASA Technical Reports Server (NTRS)

    Franciscus, Leo C. (Inventor); Brabbs, Theodore A. (Inventor)

    1993-01-01

    A multi-heat addition turbine engine (MHATE) incorporates a plurality of heat addition devices to transfer energy to air and a plurality of turbines to extract energy from the air while converting it to work. The MHATE provides dry power and lower fuel consumption or lower combustor exit temperatures.

  14. Predictive Power of the Sources of Primary School Students' Self-Efficacy Beliefs on Their Self-Efficacy Beliefs for Learning and Performance

    ERIC Educational Resources Information Center

    Arslan, Ali

    2012-01-01

    The purpose of this study is to reveal the extent to which the sources of 6th- 8th grade students' self-efficacy beliefs predict their self-efficacy beliefs for learning and performance. The study is correlational and was conducted on a total of 1049 students during the fall term of the educational year 2010-2011. The data of the study were…

  15. An assessment of discriminatory power of office blood pressure measurements in predicting optimal ambulatory blood pressure control in people with type 2 diabetes

    PubMed Central

    Kengne, Andre Pascal; Libend, Christelle Nong; Dzudie, Anastase; Menanga, Alain; Dehayem, Mesmin Yefou; Kingue, Samuel; Sobngwi, Eugene

    2014-01-01

    Introduction Ambulatory blood pressure (BP) measurements (ABPM) predict health outcomes better than office BP, and are recommended for assessing BP control, particularly in high-risk patients. We assessed the performance of office BP in predicting optimal ambulatory BP control in sub-Saharan Africans with type 2 diabetes (T2DM). Methods Participants were a random sample of 51 T2DM patients (25 men) drug-treated for hypertension, receiving care in a referral diabetes clinic in Yaounde, Cameroon. A quality control group included 46 non-diabetic individuals with hypertension. Targets for BP control were systolic (and diastolic) BP. Results Mean age of diabetic participants was 60 years (standard deviation: 10) and median duration of diabetes was 6 years (min-max: 0-29). Correlation coefficients between each office-based variable and the 24-h ABPM equivalent (diabetic vs. non-diabetic participants) were 0.571 and 0.601 for systolic (SBP), 0.520 and 0.539 for diastolic (DBP), 0.631 and 0.549 for pulse pressure (PP), and 0.522 and 0.583 for mean arterial pressure (MAP). The c-statistic for the prediction of optimal ambulatory control from office-BP in diabetic participants was 0.717 for SBP, 0.494 for DBP, 0.712 for PP, 0.582 for MAP, and 0.721 for either SBP + DBP or PP + MAP. Equivalents in diabetes-free participants were 0.805, 0.763, 0.695, 0.801 and 0.813. Conclusion Office DBP was ineffective in discriminating optimal ambulatory BP control in diabetic patients, and did not improve predictions based on office SBP alone. Targeting ABPM to those T2DM patients who are already at optimal office-based SBP would likely be more cost effective in this setting. PMID:25838859

  16. NOAA OTEC CWP (National Oceanic and Atmospheric Administration Ocean Thermal Energy Conversion Cold Water Pipe) at-sea test. Volume 3: Additional tabulation of the power spectra, part 2

    NASA Astrophysics Data System (ADS)

    1983-12-01

    Data collected during the Ocean Thermal Energy Conversion (OTEC) Cold Water Pipe At Sea Test are analyzed. Also included are the following ittems: (1) sensor factors and offsets, and the data processing algorithms used to convert the recorded sensor measurements from electrical to engineering units; (2) plots of the power spectra estimates obtained from a fast fourier transform (FFT) analysis of selected channels; (3) plots of selected sensor measurements as a function of time; and (4) plots of bending strain along the pipe using statistics and values presented.

  17. Assessment, validation and intercomparison of operational models for predicting tritium migration from routine discharges of nuclear power plants: the case of Loire River.

    PubMed

    Goutal, Nicole; Luck, Marilyne; Boyer, Patrick; Monte, Luigi; Siclet, Françoise; Angeli, Giacomo

    2008-02-01

    During last decades, a number of projects have been launched to validate models for predicting the behaviour of radioactive substances in the environment. The project of the "Aquatic" working group of the project EMRAS (Environmental Modelling for Radiation Safety) organised by the International Atomic Energy Agency (IAEA) was based on the validation and assessment of models for predicting the behaviour of radionuclides in the aquatic ecosystems. The present paper describes a blind test of models aimed at assessing the dispersion of tritium releases in the Loire River (France), on a large domain ( approximately 350km) and on a period of six months, by comparing the results obtained by operational-to-experimental values of tritium concentration at Angers, a city along the Loire River. The common conclusion is that the models used by the different participants namely 1D models and models based on a schematic hydraulic (box models) are reliable tools for tritium transport modelling. Nevertheless, the importance of proper and detailed hydrological data for the appropriate prediction of pollutant migration in water is demonstrated by the example provided during this study. PMID:18068278

  18. Multimodal imaging measures predict rearrest

    PubMed Central

    Steele, Vaughn R.; Claus, Eric D.; Aharoni, Eyal; Vincent, Gina M.; Calhoun, Vince D.; Kiehl, Kent A.

    2015-01-01

    Rearrest has been predicted by hemodynamic activity in the anterior cingulate cortex (ACC) during error-processing (Aharoni et al., 2013). Here, we evaluate the predictive power after adding an additional imaging modality in a subsample of 45 incarcerated males from Aharoni et al. (2013). Event-related potentials (ERPs) and hemodynamic activity were collected during a Go/NoGo response inhibition task. Neural measures of error-processing were obtained from the ACC and two ERP components, the error-related negativity (ERN/Ne) and the error positivity (Pe). Measures from the Pe and ACC differentiated individuals who were and were not subsequently rearrested. Cox regression, logistic regression, and support vector machine (SVM) neuroprediction models were calculated. Each of these models proved successful in predicting rearrest and SVM provided the strongest results. Multimodal neuroprediction SVM models with out of sample cross-validating accurately predicted rearrest (83.33%). Offenders with increased Pe amplitude and decreased ACC activation, suggesting abnormal error-processing, were at greatest risk of rearrest. PMID:26283947

  19. Additive Manufacturing Infrared Inspection

    NASA Technical Reports Server (NTRS)

    Gaddy, Darrell

    2014-01-01

    Additive manufacturing is a rapid prototyping technology that allows parts to be built in a series of thin layers from plastic, ceramics, and metallics. Metallic additive manufacturing is an emerging form of rapid prototyping that allows complex structures to be built using various metallic powders. Significant time and cost savings have also been observed using the metallic additive manufacturing compared with traditional techniques. Development of the metallic additive manufacturing technology has advanced significantly over the last decade, although many of the techniques to inspect parts made from these processes have not advanced significantly or have limitations. Several external geometry inspection techniques exist such as Coordinate Measurement Machines (CMM), Laser Scanners, Structured Light Scanning Systems, or even traditional calipers and gages. All of the aforementioned techniques are limited to external geometry and contours or must use a contact probe to inspect limited internal dimensions. This presentation will document the development of a process for real-time dimensional inspection technique and digital quality record of the additive manufacturing process using Infrared camera imaging and processing techniques.

  20. Phenylethynyl Containing Reactive Additives

    NASA Technical Reports Server (NTRS)

    Connell, John W. (Inventor); Smith, Joseph G., Jr. (Inventor); Hergenrother, Paul M. (Inventor)

    2002-01-01

    Phenylethynyl containing reactive additives were prepared from aromatic diamine, containing phenylethvnvl groups and various ratios of phthalic anhydride and 4-phenylethynviphthalic anhydride in glacial acetic acid to form the imide in one step or in N-methyl-2-pvrrolidinone to form the amide acid intermediate. The reactive additives were mixed in various amounts (10% to 90%) with oligomers containing either terminal or pendent phenylethynyl groups (or both) to reduce the melt viscosity and thereby enhance processability. Upon thermal cure, the additives react and become chemically incorporated into the matrix and effect an increase in crosslink density relative to that of the host resin. This resultant increase in crosslink density has advantageous consequences on the cured resin properties such as higher glass transition temperature and higher modulus as compared to that of the host resin.

  1. Additives in plastics.

    PubMed Central

    Deanin, R D

    1975-01-01

    The polymers used in plastics are generally harmless. However, they are rarely used in pure form. In almost all commercial plastics, they are "compounded" with monomeric ingredients to improve their processing and end-use performance. In order of total volume used, these monomeric additives may be classified as follows: reinforcing fibers, fillers, and coupling agents; plasticizers; colorants; stabilizers (halogen stabilizers, antioxidants, ultraviolet absorbers, and biological preservatives); processing aids (lubricants, others, and flow controls); flame retardants, peroxides; and antistats. Some information is already available, and much more is needed, on potential toxicity and safe handling of these additives during processing and manufacture of plastics products. PMID:1175566

  2. Measurement of carotid artery intima-media thickness in dyslipidemic patients increases the power of traditional risk factors to predict cardiovascular events.

    PubMed

    Baldassarre, Damiano; Amato, Mauro; Pustina, Linda; Castelnuovo, Samuela; Sanvito, Silvia; Gerosa, Lorenzo; Veglia, Fabrizio; Keidar, Shlomo; Tremoli, Elena; Sirtori, Cesare R

    2007-04-01

    A longitudinal observational study investigated whether the measurement, in clinical practice, of carotid maximum intima-media thickness (Max-IMT) could be combined with the Framingham risk score (FRS) to improve the predictability of cardiovascular events in dyslipidemic patients who are at low or intermediate risk. Max-IMT was measured by ultrasound in 1969 patients attending a lipid clinic. The "best threshold values" (BTVs) above which we considered the Max-IMT to be abnormally high were calculated for our dyslipdemic population for each 10-year age interval in men and women. Two hundred and forty-two patients (age 54+/-10 years; 43.8% women) with an FRS <20%, i.e. at low or intermediate risk, were monitored for more than 5 years. Twenty-four of these patients suffered a cardiovascular event within 5.1+/-2.3 years. Both FRS and Max-IMT proved to be independent outcome predictors (p<0.04, both), with a hazard ratio (HR) of 6.7 (95% CI 1.43, 31.04; p=0.015) in patients in whom FRS was 10-20% and Max-IMT was above the BTV (60th percentile of Max-IMT distribution for men or 80th for women). In Kaplan-Meier analysis, the Max-IMT significantly improved the predictive value of the FRS (chi(2)=8.13, p=0.04). Patients with FRS 10-20% (currently considered intermediate-risk) and also elevated Max-IMT values came into the same high-risk category as patients with FRS 20-30%. The combination of FRS with Max-IMT measurement can be used in routine clinical practice to greatly enhance the predictability of cardiovascular events in the large number of patients who fall into the intermediate-risk category, which currently does not call for aggressive preventive measures. PMID:16682042

  3. The Role of Atmospheric Measurements in Wind Power Statistical Models

    NASA Astrophysics Data System (ADS)

    Wharton, S.; Bulaevskaya, V.; Irons, Z.; Newman, J. F.; Clifton, A.

    2015-12-01

    The simplest wind power generation curves model power only as a function of the wind speed at turbine hub-height. While the latter is an essential predictor of power output, it is widely accepted that wind speed information in other parts of the vertical profile, as well as additional atmospheric variables including atmospheric stability, wind veer, and hub-height turbulence are also important factors. The goal of this work is to determine the gain in predictive ability afforded by adding additional atmospheric measurements to the power prediction model. In particular, we are interested in quantifying any gain in predictive ability afforded by measurements taken from a laser detection and ranging (lidar) instrument, as lidar provides high spatial and temporal resolution measurements of wind speed and direction at 10 or more levels throughout the rotor-disk and at heights well above. Co-located lidar and meteorological tower data as well as SCADA power data from a wind farm in Northern Oklahoma will be used to train a set of statistical models. In practice, most wind farms continue to rely on atmospheric measurements taken from less expensive, in situ instruments mounted on meteorological towers to assess turbine power response to a changing atmospheric environment. Here, we compare a large suite of atmospheric variables derived from tower measurements to those taken from lidar to determine if remote sensing devices add any competitive advantage over tower measurements alone to predict turbine power response.

  4. Prediction of the effects of nutrient loadings from a power plant at Perryman on the water quality of the Bush River estuary. Final report

    SciTech Connect

    Rose, K.A.; Dwyer, R.L.; Turner, M.A.

    1986-10-01

    A water-quality model consisting of a one-dimensional Hydraulic Module coupled with a Water Quality Module was used to assess the effects of increased nutrient loadings from the proposed Perryman Power Plant on the dissolved oxygen and chlorophyll-a concentrations in the Bush River estuary. The Hydraulic Module represented the longitudinal water movement (and physical transport of associated constituents) among 12 spatial segments. The Water Quality Module represented the biological processes affecting nitrogen, phosphorus, chlorophyll-a, and dissolved oxygen in each segment (e.g., photosynthesis, nutrient uptake, decomposition).

  5. Comparison of Analytical Predictions and Experimental Results for a Dual Brayton Power System (Discussion on Test Hardware and Computer Model for a Dual Brayton System)

    NASA Technical Reports Server (NTRS)

    Johnson, Paul K.

    2007-01-01

    NASA Glenn Research Center (GRC) contracted Barber-Nichols, Arvada, CO to construct a dual Brayton power conversion system for use as a hardware proof of concept and to validate results from a computational code known as the Closed Cycle System Simulation (CCSS). Initial checkout tests were performed at Barber- Nichols to ready the system for delivery to GRC. This presentation describes the system hardware components and lists the types of checkout tests performed along with a couple issues encountered while conducting the tests. A description of the CCSS model is also presented. The checkout tests did not focus on generating data, therefore, no test data or model analyses are presented.

  6. Prediction of Ungauged River Basin for Hydro Power Potential and Flood Risk Mitigation; a Case Study at Gin River, Sri Lanka

    NASA Astrophysics Data System (ADS)

    Ratnayake, A. S.

    2011-12-01

    The most of the primary civilizations of the world emerged in or near river valleys or floodplains. The river channels and floodplains are single hydrologic and geomorphic system. The failure to appreciate the integral connection between floodplains and channel underlies many socioeconomic and environmental problems in river management today. However it is a difficult task of collecting reliable field hydrological data. Under such situations either synthetic or statistically generated data were used for hydraulic engineering designing and flood modeling. The fundamentals of precipitation-runoff relationship through synthetic unit hydrograph for Gin River basin were prepared using the method of the Flood Studies Report of the National Environmental Research Council, United Kingdom (1975). The Triangular Irregular Network model was constructed using Geographic Information System (GIS) to determine hazard prone zones. The 1:10,000 and 1:50,000 topography maps and field excursions were also used for initial site selection of mini-hydro power units and determine flooding area. The turbines output power generations were calculated using the parameters of net head and efficiency of turbine. The peak discharge achieves within 4.74 hours from the onset of the rainstorm and 11.95 hours time takes to reach its normal discharge conditions of Gin River basin. Stream frequency of Gin River is 4.56 (Junctions/ km2) while the channel slope is 7.90 (m/km). The regional coefficient on the catchment is 0.00296. Higher stream frequency and gentle channel slope were recognized as the flood triggering factors of Gin River basin and other parameters such as basins catchment area, main stream length, standard average annual rainfall and soil do not show any significant variations with other catchments of Sri Lanka. The flood management process, including control of flood disaster, prepared for a flood, and minimize it impacts are complicated in human population encroached and modified

  7. Biobased lubricant additives

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Fully biobased lubricants are those formulated using all biobased ingredients, i.e. biobased base oils and biobased additives. Such formulations provide the maximum environmental, safety, and economic benefits expected from a biobased product. Currently, there are a number of biobased base oils that...

  8. Multifunctional fuel additives

    SciTech Connect

    Baillargeon, D.J.; Cardis, A.B.; Heck, D.B.

    1991-03-26

    This paper discusses a composition comprising a major amount of a liquid hydrocarbyl fuel and a minor low-temperature flow properties improving amount of an additive product of the reaction of a suitable diol and product of a benzophenone tetracarboxylic dianhydride and a long-chain hydrocarbyl aminoalcohol.

  9. Bioconcentration of metals in the moss Scleropodium purum in the area surrounding a power plant. A geotopographical predictive model for mercury.

    PubMed

    Carballeira, A; Fernández, J A

    2002-06-01

    Samples of the moss Scleropodium purum collected in 1995 and 1997 were used to biomonitor the deposition of metals in the area surrounding a thermal power plant. Significantly higher levels of Cu (p < 0.05), Fe (p < 0.01), As and Hg (p < 0.001) were found in the 1997 samples than in the 1995 samples, due to changes in atmospheric conditions. The influence on bioconcentration of the orientation of the sampling sites relative to the source of emission was studied. It was found that the increase recorded in 1997 generally occurred in the sampling sites in the south east of the study area. Analysis of the effect of distance from the source of emission revealed that the increase in metal levels in 1997 took place close to the power station (10-30 km). Finally, multiple regression analysis was used to construct a model that related different topographical variables to the concentrations of Hg in moss. The model, constructed using the data collected in both sampling periods, included the orientation of the sampling sites relative to the source of emission as well as the height of sampling sites in 1995 and the distance from the emission point in 1997. The model allowed us to determine the extent of the area affected by deposition and to establish the magnitude of deposition. PMID:12137036

  10. Can TRUS Power Doppler Predict the Preservation of Erectile Function in HIFU Treatment of Localised Prostate Cancer? — A Preliminary Study

    NASA Astrophysics Data System (ADS)

    Hoh, I. M.; Calleary, J. G.; Moore, C.; Emberton, M.; Allen, C.

    2006-05-01

    Perhaps the single most significant unifying feature in men diagnosed with organ confined prostate cancer is the hope of erectile preservation in the treatment that offers cure. Although it is not 100% certain that the preservation of neurovascular bundle (NVB) can actually lead to intact sexual function, there is evidence that non-sparing nerve radical prostatectomy has a much higher incidence of impotence compared to nerve-sparing ones. The idea to monitor NVB flow can be realized using a simple power Doppler technique that was done before and after HIFU. The NVB flow was found intact in all patients (n=14). Tumescence returned in 93% of patients with a mean time of 6 weeks for this to occur. The erectile function score, IIEF-15 decreased by a third but shows a trend towards recovery. This preliminary study demonstrates the feasibility of transrectal power Doppler as a monitoring tool to provide immediate feedback on the NVB flow which was found intact in all patients. Although early reports of the tumescence proved encouraging, its full impact on erectile function will require longer follow-up.

  11. Post-response βγ power predicts the degree of choice-based learning in internally guided decision-making

    PubMed Central

    Nakao, Takashi; Kanayama, Noriaki; Katahira, Kentaro; Odani, Misaki; Ito, Yosuke; Hirata, Yuki; Nasuno, Reika; Ozaki, Hanako; Hiramoto, Ryosuke; Miyatani, Makoto; Northoff, Georg

    2016-01-01

    Choosing an option increases a person’s preference for that option. This phenomenon, called choice-based learning (CBL), has been investigated separately in the contexts of internally guided decision-making (IDM, e.g., preference judgment), for which no objectively correct answer exists, and externally guided decision making (EDM, e.g., perceptual decision making), for which one objectively correct answer exists. For the present study, we compared decision making of these two types to examine differences of underlying neural processes of CBL. As IDM and EDM tasks, occupation preference judgment and salary judgment were used, respectively. To compare CBL for the two types of decision making, we developed a novel measurement of CBL: decision consistency. When CBL occurs, decision consistency is higher in the last-half trials than in first-half trials. Electroencephalography (EEG) data have demonstrated that the change of decision consistency is positively correlated with the fronto-central beta–gamma power after response in the first-half trials for IDM, but not for EDM. Those results demonstrate for the first time the difference of CBL between IDM and EDM. The fronto-central beta–gamma power is expected to reflect a key process of CBL, specifically for IDM. PMID:27576670

  12. A test program for predicting and monitoring the emergency diesel generator heat exchangers at Limerick Generating Station and Peach Bottom Atomic Power Station

    SciTech Connect

    Elder, J.J.; Fusegni, L.J.; McFarland, W.J.; Andreone, C.F.

    1995-12-31

    The USNRC issued Generic Letter 89-13, ``Service Water Problems Affecting Safety-Related Equipment`` to all nuclear power plant licensees which requires the implementation of a program to ensure that nuclear safety-related heat exchangers are capable of performing their intended functions. The heat exchangers on the standby emergency diesel generator (EDG) skids are covered by this requirement. PECo and SWEC have developed a program of testing and analysis to monitor the level of fouling in the EDG`s at the Limerick and Peach Bottom nuclear power plants in response to the Generic Letter. The development of an EDG heat exchanger test program is significantly more complex than for most other heat exchangers. This is because the process fluid flows are controlled by self-modulating thermostatic valves to maintain proper process temperature setpoints. As a result, under some test conditions the process flows may be reduced to as little as 20% of their design values. Flow changes of this magnitude significantly affect the performance of the coolers and obscure observation of the effects of fouling if not properly addressed. This paper describes the methods developed by PECo and SWEC to address this problem.

  13. Post-response βγ power predicts the degree of choice-based learning in internally guided decision-making.

    PubMed

    Nakao, Takashi; Kanayama, Noriaki; Katahira, Kentaro; Odani, Misaki; Ito, Yosuke; Hirata, Yuki; Nasuno, Reika; Ozaki, Hanako; Hiramoto, Ryosuke; Miyatani, Makoto; Northoff, Georg

    2016-01-01

    Choosing an option increases a person's preference for that option. This phenomenon, called choice-based learning (CBL), has been investigated separately in the contexts of internally guided decision-making (IDM, e.g., preference judgment), for which no objectively correct answer exists, and externally guided decision making (EDM, e.g., perceptual decision making), for which one objectively correct answer exists. For the present study, we compared decision making of these two types to examine differences of underlying neural processes of CBL. As IDM and EDM tasks, occupation preference judgment and salary judgment were used, respectively. To compare CBL for the two types of decision making, we developed a novel measurement of CBL: decision consistency. When CBL occurs, decision consistency is higher in the last-half trials than in first-half trials. Electroencephalography (EEG) data have demonstrated that the change of decision consistency is positively correlated with the fronto-central beta-gamma power after response in the first-half trials for IDM, but not for EDM. Those results demonstrate for the first time the difference of CBL between IDM and EDM. The fronto-central beta-gamma power is expected to reflect a key process of CBL, specifically for IDM. PMID:27576670

  14. Liquid chromatography coupled to different atmospheric pressure ionization sources-quadrupole-time-of-flight mass spectrometry and post-column addition of metal salt solutions as a powerful tool for the metabolic profiling of Fusarium oxysporum.

    PubMed

    Cirigliano, Adriana M; Rodriguez, M Alejandra; Gagliano, M Laura; Bertinetti, Brenda V; Godeas, Alicia M; Cabrera, Gabriela M

    2016-03-25

    Fusarium oxysporum L11 is a non-pathogenic soil-borne fungal strain that yielded an extract that showed antifungal activity against phytopathogens. In this study, reversed-phase high-performance liquid chromatography (RP-HPLC) coupled to different atmospheric pressure ionization sources-quadrupole-time-of-flight mass spectrometry (API-QTOF-MS) was applied for the comprehensive profiling of the metabolites from the extract. The employed sources were electrospray (ESI), atmospheric pressure chemical ionization (APCI) and atmospheric pressure photoionization (APPI). Post-column addition of metal solutions of Ca, Cu and Zn(II) was also tested using ESI. A total of 137 compounds were identified or tentatively identified by matching their accurate mass signals, suggested molecular formulae and MS/MS analysis with previously reported data. Some compounds were isolated and identified by NMR. The extract was rich in cyclic peptides like cyclosporins, diketopiperazines and sansalvamides, most of which were new, and are reported here for the first time. The use of post-column addition of metals resulted in a useful strategy for the discrimination of compound classes since specific adducts were observed for the different compound families. This technique also allowed the screening for compounds with metal binding properties. Thus, the applied methodology is a useful choice for the metabolic profiling of extracts and also for the selection of metabolites with potential biological activities related to interactions with metal ions. PMID:26655791

  15. Boron addition to alloys

    SciTech Connect

    Coad, B. C.

    1985-08-20

    A process for addition of boron to an alloy which involves forming a melt of the alloy and a reactive metal, selected from the group consisting of aluminum, titanium, zirconium and mixtures thereof to the melt, maintaining the resulting reactive mixture in the molten state and reacting the boric oxide with the reactive metal to convert at least a portion of the boric oxide to boron which dissolves in the resulting melt, and to convert at least portion of the reactive metal to the reactive metal oxide, which oxide remains with the resulting melt, and pouring the resulting melt into a gas stream to form a first atomized powder which is subsequently remelted with further addition of boric oxide, re-atomized, and thus reprocessed to convert essentially all the reactive metal to metal oxide to produce a powdered alloy containing specified amounts of boron.

  16. Tackifier for addition polyimides

    NASA Technical Reports Server (NTRS)

    Butler, J. M.; St.clair, T. L.

    1980-01-01

    A modification to the addition polyimide, LaRC-160, was prepared to improve tack and drape and increase prepeg out-time. The essentially solventless, high viscosity laminating resin is synthesized from low cost liquid monomers. The modified version takes advantage of a reactive, liquid plasticizer which is used in place of solvent and helps solve a major problem of maintaining good prepeg tack and drape, or the ability of the prepeg to adhere to adjacent plies and conform to a desired shape during the lay up process. This alternate solventless approach allows both longer life of the polymer prepeg and the processing of low void laminates. This approach appears to be applicable to all addition polyimide systems.

  17. Vinyl capped addition polyimides

    NASA Technical Reports Server (NTRS)

    Vannucci, Raymond D. (Inventor); Malarik, Diane C. (Inventor); Delvigs, Peter (Inventor)

    1991-01-01

    Polyimide resins (PMR) are generally useful where high strength and temperature capabilities are required (at temperatures up to about 700 F). Polyimide resins are particularly useful in applications such as jet engine compressor components, for example, blades, vanes, air seals, air splitters, and engine casing parts. Aromatic vinyl capped addition polyimides are obtained by reacting a diamine, an ester of tetracarboxylic acid, and an aromatic vinyl compound. Low void materials with improved oxidative stability when exposed to 700 F air may be fabricated as fiber reinforced high molecular weight capped polyimide composites. The aromatic vinyl capped polyimides are provided with a more aromatic nature and are more thermally stable than highly aliphatic, norbornenyl-type end-capped polyimides employed in PMR resins. The substitution of aromatic vinyl end-caps for norbornenyl end-caps in addition polyimides results in polymers with improved oxidative stability.

  18. [Biologically active food additives].

    PubMed

    Velichko, M A; Shevchenko, V P

    1998-07-01

    More than half out of 40 projects for the medical science development by the year of 2000 have been connected with the bio-active edible additives that are called "the food of XXI century", non-pharmacological means for many diseases. Most of these additives--nutricevtics and parapharmacevtics--are intended for the enrichment of food rations for the sick or healthy people. The ecologicaly safest and most effective are combined domestic adaptogens with immuno-modulating and antioxidating action that give anabolic and stimulating effect,--"leveton", "phytoton" and "adapton". The MKTs-229 tablets are residue discharge means. For atherosclerosis and general adiposis they recommend "tsar tablets" and "aiconol (ikhtien)"--on the base of cod-liver oil or "splat" made out of seaweed (algae). All these preparations have been clinically tested and received hygiene certificates from the Institute of Dietology of the Russian Academy of Medical Science. PMID:9752776

  19. Piezoelectric Power Requirements for Active Vibration Control

    NASA Technical Reports Server (NTRS)

    Brennan, Matthew C.; McGowan, Anna-Maria Rivas

    1997-01-01

    This paper presents a method for predicting the power consumption of piezoelectric actuators utilized for active vibration control. Analytical developments and experimental tests show that the maximum power required to control a structure using surface-bonded piezoelectric actuators is independent of the dynamics between the piezoelectric actuator and the host structure. The results demonstrate that for a perfectly-controlled system, the power consumption is a function of the quantity and type of piezoelectric actuators and the voltage and frequency of the control law output signal. Furthermore, as control effectiveness decreases, the power consumption of the piezoelectric actuators decreases. In addition, experimental results revealed a non-linear behavior in the material properties of piezoelectric actuators. The material non- linearity displayed a significant increase in capacitance with an increase in excitation voltage. Tests show that if the non-linearity of the capacitance was accounted for, a conservative estimate of the power can easily be determined.

  20. Electrophilic addition of astatine

    SciTech Connect

    Norseev, Yu.V.; Vasaros, L.; Nhan, D.D.; Huan, N.K.

    1988-03-01

    It has been shown for the first time that astatine is capable of undergoing addition reactions to unsaturated hydrocarbons. A new compound of astatine, viz., ethylene astatohydrin, has been obtained, and its retention numbers of squalane, Apiezon, and tricresyl phosphate have been found. The influence of various factors on the formation of ethylene astatohydrin has been studied. It has been concluded on the basis of the results obtained that the univalent cations of astatine in an acidic medium is protonated hypoastatous acid.

  1. Hydrocarbon fuel additive

    SciTech Connect

    Ambrogio, S.

    1989-02-28

    This patent describes the method of fuel storage or combustion, wherein the fuel supply contains small amounts of water, the step of adding to the fuel supply an additive comprising a blend of a hydrophilic agent chosen from the group of ethylene glycol, n-butyl alcohol, and cellosolve in the range of 22-37% by weight; ethoxylated nonylphenol in the range of 26-35% by weight; nonylphenol polyethylene glycol ether in the range of 32-43% by weight.

  2. Climate prediction and predictability

    NASA Astrophysics Data System (ADS)

    Allen, Myles

    2010-05-01

    Climate prediction is generally accepted to be one of the grand challenges of the Geophysical Sciences. What is less widely acknowledged is that fundamental issues have yet to be resolved concerning the nature of the challenge, even after decades of research in this area. How do we verify or falsify a probabilistic forecast of a singular event such as anthropogenic warming over the 21st century? How do we determine the information content of a climate forecast? What does it mean for a modelling system to be "good enough" to forecast a particular variable? How will we know when models and forecasting systems are "good enough" to provide detailed forecasts of weather at specific locations or, for example, the risks associated with global geo-engineering schemes. This talk will provide an overview of these questions in the light of recent developments in multi-decade climate forecasting, drawing on concepts from information theory, machine learning and statistics. I will draw extensively but not exclusively from the experience of the climateprediction.net project, running multiple versions of climate models on personal computers.

  3. Computer-aided modeling and prediction of performance of the modified Lundell class of alternators in space station solar dynamic power systems

    NASA Technical Reports Server (NTRS)

    Demerdash, Nabeel A. O.; Wang, Ren-Hong

    1988-01-01

    The main purpose of this project is the development of computer-aided models for purposes of studying the effects of various design changes on the parameters and performance characteristics of the modified Lundell class of alternators (MLA) as components of a solar dynamic power system supplying electric energy needs in the forthcoming space station. Key to this modeling effort is the computation of magnetic field distribution in MLAs. Since the nature of the magnetic field is three-dimensional, the first step in the investigation was to apply the finite element method to discretize volume, using the tetrahedron as the basic 3-D element. Details of the stator 3-D finite element grid are given. A preliminary look at the early stage of a 3-D rotor grid is presented.

  4. Performance of the Carrisa 6-MW photovoltaic power plant

    SciTech Connect

    Shushnar, G.J.; Caldwell, J.H.; Hoff, T.E.

    1986-01-01

    Photovoltaic (PV) power generation for the electric utility industry will soon become a commercial reality in the United States. Arco Solar's Carrisa 6.4-MWp (dc at standard test conditions (STC)) PV Power Plant is the world's largest. As such, the lessons to be learned from its performance are significant. The energy output of the plant for 1 yr has been analyzed and compared to plant performance predictions. This comparison required a prediction of insolation, ambient temperature, and wind speed. The results of the study indicate the performance of a PV power plant is highly predictable. In addition, this power plant has been highly reliable with a high capacity factor. Pacific Gas and Electric (PG and E), the utility that purchases Carrisa's energy, has reported capacity factors exceeding 65% when PG and E's hourly load is 85% or greater than their system peak load.

  5. Optics of progressive addition lenses.

    PubMed

    Sheedy, J E; Buri, M; Bailey, I L; Azus, J; Borish, I M

    1987-02-01

    The optical characteristics of the major progressive addition lenses were measured using an automated lensometer with a specially designed lens holder to simulate eye rotation. Measurements were made every 3 degrees (about 1.5 mm) and graphs of isospherical equivalent lines and isocylinder lines were developed. Generally the near zone of these lenses is narrower and lower than in bifocal or trifocal lenses. Distinct differences exist between the various progressive lenses. The width of the near zone, rate of power progression, amount of unwanted cylinder (level with the distance center), and clarity of the distance zone are compared for the various lenses. The optical measurements demonstrate an apparent trade-off between the size of the cylinder-free area of the lens and the amount of the cylinder. PMID:3826294

  6. Secondary power systems

    SciTech Connect

    Not Available

    1985-01-01

    In aeronautical engineering secondary power systems have long played second fiddle to the airframe, the engine, and indeed, the avionics. This collection of papers is thus timely, and its publication by the Institution of Mechanical Engineers appropriate, as secondary power systems in modern aircraft present challenging mechanical engineering problems. In military aircraft demands for electrical and hydraulic power and high pressure air have grown over the past two decades. To these basic needs are added requirements for emergency power, ground power, and independent engine starting. Additionally increased reliability and maintainability is demanded from all secondary power systems. Complete contents: What is a secondary power system. Modern technology secondary power systems for next generation military aircraft; Integrated power units; Secondary power system gearbox; Starting the system - air turbine starters; Auxiliary and emergency power system; Secondary hydraulic power generation; Advanced technology electrical power generation equipment.

  7. Development of embrittlement prediction models for U.S. power reactors and the impact of the heat-affected zone to thermal annealing

    SciTech Connect

    Wang, J.A.

    1998-05-01

    The NRC Regulatory Guide 1.99 Revision 2 was based on 177 surveillance data points and the EPRI data base, where 76% of 177 data points and 60% of EPRI data base were from Westinghouse`s data. Therefore, other vendors` radiation environment may not be properly characterized by R.G. 1.99`s prediction. To minimize scatter from the influences of the irradiation temperature, neutron energy spectrum, displacement rate, and plant operation procedures on embrittlement models, improved embrittlement models based on group data that have similar radiation environments and reactor design and operation criteria are examined. A total of 653 shift data points from the current FR-EDB, including 397 Westinghouse data, 93 B and W data, 37 CE data, and 106 GE data, are used. A nonlinear least squares fitting FORTRAN program, incorporating a Monte Carlo procedure with 35% and 10% uncertainty assigned to the fluence and shift data, respectively, was written for this study. In order to have the same adjusted fluence value for the weld and plate material in the same capsule, the Monte Carlo least squares fitting procedure has the ability to adjust the fluence values while running the weld and plate formula simultaneously. Six chemical components, namely, copper, nickel, phosphorus, sulfur, manganese, and molybdenum, were considered in the development of the new embrittlement models. The overall percentage of reduction of the 2-sigma margins per delta RTNDT predicted by the new embrittlement models, compared to that of R.G. 1.99, for weld and base materials are 42% and 36%, respectively. Currently, the need for thermal annealing is seriously being considered for several A302B type RPVs. From the macroscopic view point, even if base and weld materials were verified from mechanical tests to be fully recovered, the linking heat affected zone (HAZ) material has not been properly characterized. Thus the final overall recovery will still be unknown. The great data scatter of the HAZ metals may

  8. Siloxane containing addition polyimides

    NASA Technical Reports Server (NTRS)

    Maudgal, S.; St. Clair, T. L.

    1984-01-01

    Addition polyimide oligomers have been synthesized from bis(gamma-aminopropyl) tetramethyldisiloxane and 3, 3', 4, 4'-benzophenonetetracarboxylic dianhydride using a variety of latent crosslinking groups as endcappers. The prepolymers were isolated and characterized for solubility (in amide, chlorinated and ether solvents), melt flow and cure properties. The most promising systems, maleimide and acetylene terminated prepolymers, were selected for detailed study. Graphite cloth reinforced composites were prepared and properties compared with those of graphite/Kerimid 601, a commercially available bismaleimide. Mixtures of the maleimide terminated system with Kerimid 601, in varying proportions, were also studied.

  9. Oil additive process

    SciTech Connect

    Bishop, H.

    1988-10-18

    This patent describes a method of making an additive comprising: (a) adding 2 parts by volume of 3% sodium hypochlorite to 45 parts by volume of diesel oil fuel to form a sulphur free fuel, (b) removing all water and foreign matter formed by the sodium hypochlorite, (c) blending 30 parts by volume of 24% lead naphthanate with 15 parts by volume of the sulphur free fuel, 15 parts by volume of light-weight material oil to form a blended mixture, and (d) heating the blended mixture slowly and uniformly to 152F.

  10. Enhancing the Predictive Power of Mutations in the C-Terminus of the KCNQ1-Encoded Kv7.1 Voltage-Gated Potassium Channel

    PubMed Central

    Kapplinger, Jamie D.; Tseng, Andrew S.; Salisbury, Benjamin A.; Tester, David J.; Callis, Thomas E.; Alders, Marielle; Wilde, Arthur A.M.; Ackerman, Michael J.

    2016-01-01

    Despite the overrepresentation of Kv7.1 mutations among patients with a robust diagnosis of LQTS, a background rate of innocuous Kv7.1 missense variants observed in healthy controls creates ambiguity in the interpretation of LQTS genetic test results. A recent study showed the probability of pathogenicity for rare missense mutations depends in part on the topological location of the variant in Kv7.1’s various structure-function domains. Since the Kv7.1 C-terminus accounts for nearly 50% of the overall protein and nearly 50% of the overall background rate of rare variants falls within the C-terminus, further enhancement in mutation calling may provide guidance in distinguishing pathogenic LQT1-causing mutations from non-disease causing rare variants in Kv7.1’s C-terminus. Therefore, we have used conservation analysis and a large case/control study to generate topology-based estimative predictive values to aid in interpretation; identifying three regions of high conservation within the Kv7.1 C-terminus which have a high probability of LQT1 pathogenicity. PMID:25854863

  11. Prediction During Natural Language Comprehension.

    PubMed

    Willems, Roel M; Frank, Stefan L; Nijhof, Annabel D; Hagoort, Peter; van den Bosch, Antal

    2016-06-01

    The notion of prediction is studied in cognitive neuroscience with increasing intensity. We investigated the neural basis of 2 distinct aspects of word prediction, derived from information theory, during story comprehension. We assessed the effect of entropy of next-word probability distributions as well as surprisal A computational model determined entropy and surprisal for each word in 3 literary stories. Twenty-four healthy participants listened to the same 3 stories while their brain activation was measured using fMRI. Reversed speech fragments were presented as a control condition. Brain areas sensitive to entropy were left ventral premotor cortex, left middle frontal gyrus, right inferior frontal gyrus, left inferior parietal lobule, and left supplementary motor area. Areas sensitive to surprisal were left inferior temporal sulcus ("visual word form area"), bilateral superior temporal gyrus, right amygdala, bilateral anterior temporal poles, and right inferior frontal sulcus. We conclude that prediction during language comprehension can occur at several levels of processing, including at the level of word form. Our study exemplifies the power of combining computational linguistics with cognitive neuroscience, and additionally underlines the feasibility of studying continuous spoken language materials with fMRI. PMID:25903464

  12. Performance Boosting Additive

    NASA Technical Reports Server (NTRS)

    1999-01-01

    Mainstream Engineering Corporation was awarded Phase I and Phase II contracts from Goddard Space Flight Center's Small Business Innovation Research (SBIR) program in early 1990. With support from the SBIR program, Mainstream Engineering Corporation has developed a unique low cost additive, QwikBoost (TM), that increases the performance of air conditioners, heat pumps, refrigerators, and freezers. Because of the energy and environmental benefits of QwikBoost, Mainstream received the Tibbetts Award at a White House Ceremony on October 16, 1997. QwikBoost was introduced at the 1998 International Air Conditioning, Heating, and Refrigeration Exposition. QwikBoost is packaged in a handy 3-ounce can (pressurized with R-134a) and will be available for automotive air conditioning systems in summer 1998.

  13. Sewage sludge additive

    NASA Technical Reports Server (NTRS)

    Kalvinskas, J. J.; Mueller, W. A.; Ingham, J. D. (Inventor)

    1980-01-01

    The additive is for a raw sewage treatment process of the type where settling tanks are used for the purpose of permitting the suspended matter in the raw sewage to be settled as well as to permit adsorption of the dissolved contaminants in the water of the sewage. The sludge, which settles down to the bottom of the settling tank is extracted, pyrolyzed and activated to form activated carbon and ash which is mixed with the sewage prior to its introduction into the settling tank. The sludge does not provide all of the activated carbon and ash required for adequate treatment of the raw sewage. It is necessary to add carbon to the process and instead of expensive commercial carbon, coal is used to provide the carbon supplement.

  14. Perspectives on Additive Manufacturing

    NASA Astrophysics Data System (ADS)

    Bourell, David L.

    2016-07-01

    Additive manufacturing (AM) has skyrocketed in visibility commercially and in the public sector. This article describes the development of this field from early layered manufacturing approaches of photosculpture, topography, and material deposition. Certain precursors to modern AM processes are also briefly described. The growth of the field over the last 30 years is presented. Included is the standard delineation of AM technologies into seven broad categories. The economics of AM part generation is considered, and the impacts of the economics on application sectors are described. On the basis of current trends, the future outlook will include a convergence of AM fabricators, mass-produced AM fabricators, enabling of topology optimization designs, and specialization in the AM legal arena. Long-term developments with huge impact are organ printing and volume-based printing.

  15. New addition curing polyimides

    NASA Technical Reports Server (NTRS)

    Frimer, Aryeh A.; Cavano, Paul

    1991-01-01

    In an attempt to improve the thermal-oxidative stability (TOS) of PMR-type polymers, the use of 1,4-phenylenebis (phenylmaleic anhydride) PPMA, was evaluated. Two series of nadic end-capped addition curing polyimides were prepared by imidizing PPMA with either 4,4'-methylene dianiline or p-phenylenediamine. The first resulted in improved solubility and increased resin flow while the latter yielded a compression molded neat resin sample with a T(sub g) of 408 C, close to 70 C higher than PME-15. The performance of these materials in long term weight loss studies was below that of PMR-15, independent of post-cure conditions. These results can be rationalized in terms of the thermal lability of the pendant phenyl groups and the incomplete imidization of the sterically congested PPMA. The preparation of model compounds as well as future research directions are discussed.

  16. Error mode prediction.

    PubMed

    Hollnagel, E; Kaarstad, M; Lee, H C

    1999-11-01

    The study of accidents ('human errors') has been dominated by efforts to develop 'error' taxonomies and 'error' models that enable the retrospective identification of likely causes. In the field of Human Reliability Analysis (HRA) there is, however, a significant practical need for methods that can predict the occurrence of erroneous actions--qualitatively and quantitatively. The present experiment tested an approach for qualitative performance prediction based on the Cognitive Reliability and Error Analysis Method (CREAM). Predictions of possible erroneous actions were made for operators using different types of alarm systems. The data were collected as part of a large-scale experiment using professional nuclear power plant operators in a full scope simulator. The analysis showed that the predictions were correct in more than 70% of the cases, and also that the coverage of the predictions depended critically on the comprehensiveness of the preceding task analysis. PMID:10582035

  17. Earthquake prediction

    NASA Technical Reports Server (NTRS)

    Turcotte, Donald L.

    1991-01-01

    The state of the art in earthquake prediction is discussed. Short-term prediction based on seismic precursors, changes in the ratio of compressional velocity to shear velocity, tilt and strain precursors, electromagnetic precursors, hydrologic phenomena, chemical monitors, and animal behavior is examined. Seismic hazard assessment is addressed, and the applications of dynamical systems to earthquake prediction are discussed.

  18. The Predictive Power of the Annellation Theory: The Case of the C26H16 Cata-Condensed Benzenoid Polycyclic Aromatic Hydrocarbons.

    PubMed

    Oña-Ruales, Jorge O; Ruiz-Morales, Yosadara

    2015-10-22

    The Annellation Theory was applied to establish the locations of maximum absorbance for the p and β bands in the UV-vis spectra of eight benzenoid cata-condensed polycyclic aromatic hydrocarbons (PAHs) with molecular formula C26H16 and no available syntheses procedures. In this group of eight isomers, there are seven compounds with potential carcinogenic properties due to geometrical constraints. In addition, crude oil and asphaltene absorption spectra exhibit similar properties, and the PAHs in heavier crude oils and asphaltenes are known to be the source of the color of heavy oils. Therefore, understanding the electronic bands of PAHs is becoming increasingly important. The methodology was validated using information for the remaining 29 isomers with available UV-vis spectra. The results satisfactorily agree with the results from semiempirical calculations made using the ZINDO/S approach. The locations of maximum absorbance for the p and β bands in the UV-vis spectra of the eight C26H16 cata-condensed isomers dibenzo[c,m]tetraphene, naphtho[1,2-c]chrysene, dibenzo[c,f]tetraphene, benzo[f]picene, naphtho[2,1-a]tetraphene, naphtho[2,1-c]tetraphene, dibenzo[c,l]chrysene, and naphtho[1,2-a]tetraphene were established for the first time. PMID:26419919

  19. The use of real-time off-site observations as a methodology for increasing forecast skill in prediction of large wind power ramps one or more hours ahead of their impact on a wind plant.

    SciTech Connect

    Martin Wilde, Principal Investigator

    2012-12-31

    ABSTRACT Application of Real-Time Offsite Measurements in Improved Short-Term Wind Ramp Prediction Skill Improved forecasting performance immediately preceding wind ramp events is of preeminent concern to most wind energy companies, system operators, and balancing authorities. The value of near real-time hub height-level wind data and more general meteorological measurements to short-term wind power forecasting is well understood. For some sites, access to onsite measured wind data - even historical - can reduce forecast error in the short-range to medium-range horizons by as much as 50%. Unfortunately, valuable free-stream wind measurements at tall tower are not typically available at most wind plants, thereby forcing wind forecasters to rely upon wind measurements below hub height and/or turbine nacelle anemometry. Free-stream measurements can be appropriately scaled to hub-height levels, using existing empirically-derived relationships that account for surface roughness and turbulence. But there is large uncertainty in these relationships for a given time of day and state of the boundary layer. Alternatively, forecasts can rely entirely on turbine anemometry measurements, though such measurements are themselves subject to wake effects that are not stationary. The void in free-stream hub-height level measurements of wind can be filled by remote sensing (e.g., sodar, lidar, and radar). However, the expense of such equipment may not be sustainable. There is a growing market for traditional anemometry on tall tower networks, maintained by third parties to the forecasting process (i.e., independent of forecasters and the forecast users). This study examines the value of offsite tall-tower data from the WINDataNOW Technology network for short-horizon wind power predictions at a wind farm in northern Montana. The presentation shall describe successful physical and statistical techniques for its application and the practicality of its application in an operational

  20. Computational Process Modeling for Additive Manufacturing

    NASA Technical Reports Server (NTRS)

    Bagg, Stacey; Zhang, Wei

    2014-01-01

    Computational Process and Material Modeling of Powder Bed additive manufacturing of IN 718. Optimize material build parameters with reduced time and cost through modeling. Increase understanding of build properties. Increase reliability of builds. Decrease time to adoption of process for critical hardware. Potential to decrease post-build heat treatments. Conduct single-track and coupon builds at various build parameters. Record build parameter information and QM Meltpool data. Refine Applied Optimization powder bed AM process model using data. Report thermal modeling results. Conduct metallography of build samples. Calibrate STK models using metallography findings. Run STK models using AO thermal profiles and report STK modeling results. Validate modeling with additional build. Photodiode Intensity measurements highly linear with power input. Melt Pool Intensity highly correlated to Melt Pool Size. Melt Pool size and intensity increase with power. Applied Optimization will use data to develop powder bed additive manufacturing process model.

  1. Prediction of future asset prices

    NASA Astrophysics Data System (ADS)

    Seong, Ng Yew; Hin, Pooi Ah; Ching, Soo Huei

    2014-12-01

    This paper attempts to incorporate trading volumes as an additional predictor for predicting asset prices. Denoting r(t) as the vector consisting of the time-t values of the trading volume and price of a given asset, we model the time-(t+1) asset price to be dependent on the present and l-1 past values r(t), r(t-1), ....., r(t-1+1) via a conditional distribution which is derived from a (2l+1)-dimensional power-normal distribution. A prediction interval based on the 100(α/2)% and 100(1-α/2)% points of the conditional distribution is then obtained. By examining the average lengths of the prediction intervals found by using the composite indices of the Malaysia stock market for the period 2008 to 2013, we found that the value 2 appears to be a good choice for l. With the omission of the trading volume in the vector r(t), the corresponding prediction interval exhibits a slightly longer average length, showing that it might be desirable to keep trading volume as a predictor. From the above conditional distribution, the probability that the time-(t+1) asset price will be larger than the time-t asset price is next computed. When the probability differs from 0 (or 1) by less than 0.03, the observed time-(t+1) increase in price tends to be negative (or positive). Thus the above probability has a good potential of being used as a market indicator in technical analysis.

  2. Power quality load management for large spacecraft electrical power systems

    NASA Technical Reports Server (NTRS)

    Lollar, Louis F.

    1988-01-01

    In December, 1986, a Center Director's Discretionary Fund (CDDF) proposal was granted to study power system control techniques in large space electrical power systems. Presented are the accomplishments in the area of power system control by power quality load management. In addition, information concerning the distortion problems in a 20 kHz ac power system is presented.

  3. "Old" tail lobes provide significant additional substorm power

    NASA Astrophysics Data System (ADS)

    Mishin, V.; Mishin, V. V.; Karavaev, Y.

    2012-12-01

    In each polar cap (PC) we mark out "old PC" observed during quiet time before the event under consideration, and "new PC" that emerges during rounding the old one and expanding the PC total area. Old and new PCs correspond in the magnetosphere to the old and new tail lobes, respectively. The new lobe variable magnetic flux Ψ1 is usually assumed to be active, i.e. it provides transport of the electromagnetic energy flux (Poynting flux) ɛ' from solar wind into the magnetosphere. The old lobe magnetic flux Ψ2 is usually supposed to be passive, i.e. it remains constant during the disturbance and does not participate in the transporting process which would mean the old PC electric field absolute screening from the convection electric field created by the magnetopause reconnection. In fact, screening is observed, but it is far from absolute. We suggest a model of screening and determine its quantitative characteristics in the selected superstorm. The coefficient of a screening is the β = Ψ2/Ψ02, where Ψ02 = const is open magnetic flux through the old PC measured prior to the substorm, and Ψ2 is variable magnetic flux during the substorm. We consider three various regimes of disturbance. In each, the coefficient β decreased during the loading phase and increased at the unloading phase, but the rates and amplitudes of variations exhibited a strong dependence on the regime. We interpreted decrease in β as a result of involving the old PC magnetic flux Ψ2, which was considered to be constant earlier, to the ' transport process of the Poynting flux from the solar wind into the magnetosphere. A weakening of the transport process at the subsequent unloading phase creates increase in β. Estimates showed that coefficient β during each regime and the computed Poynting flux varied manifolds. In general, unlike the existing substorm conception, the new scenario describes an unknown earlier tail lobe activation process during a substorm growth phase that effectively increases the accumulated tail energy for the expansion and recovery phases.

  4. 18 CFR 367.59 - Additions and retirements of property.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Additions and retirements of property. 367.59 Section 367.59 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY REGULATIONS UNDER THE PUBLIC UTILITY HOLDING COMPANY ACT OF 2005, FEDERAL POWER ACT AND NATURAL GAS ACT...

  5. 18 CFR 367.59 - Additions and retirements of property.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 18 Conservation of Power and Water Resources 1 2012-04-01 2012-04-01 false Additions and retirements of property. 367.59 Section 367.59 Conservation of Power and Water Resources FEDERAL ENERGY... GAS ACT Service Company Property Instructions § 367.59 Additions and retirements of property. (a)...

  6. 18 CFR 367.59 - Additions and retirements of property.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 18 Conservation of Power and Water Resources 1 2013-04-01 2013-04-01 false Additions and retirements of property. 367.59 Section 367.59 Conservation of Power and Water Resources FEDERAL ENERGY... GAS ACT Service Company Property Instructions § 367.59 Additions and retirements of property. (a)...

  7. 18 CFR 367.59 - Additions and retirements of property.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 18 Conservation of Power and Water Resources 1 2014-04-01 2014-04-01 false Additions and retirements of property. 367.59 Section 367.59 Conservation of Power and Water Resources FEDERAL ENERGY... GAS ACT Service Company Property Instructions § 367.59 Additions and retirements of property. (a)...

  8. 18 CFR 367.59 - Additions and retirements of property.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 18 Conservation of Power and Water Resources 1 2011-04-01 2011-04-01 false Additions and retirements of property. 367.59 Section 367.59 Conservation of Power and Water Resources FEDERAL ENERGY... GAS ACT Service Company Property Instructions § 367.59 Additions and retirements of property. (a)...

  9. Additive attacks on speaker recognition

    NASA Astrophysics Data System (ADS)

    Farrokh Baroughi, Alireza; Craver, Scott

    2014-02-01

    Speaker recognition is used to identify a speaker's voice from among a group of known speakers. A common method of speaker recognition is a classification based on cepstral coefficients of the speaker's voice, using a Gaussian mixture model (GMM) to model each speaker. In this paper we try to fool a speaker recognition system using additive noise such that an intruder is recognized as a target user. Our attack uses a mixture selected from a target user's GMM model, inverting the cepstral transformation to produce noise samples. In our 5 speaker data base, we achieve an attack success rate of 50% with a noise signal at 10dB SNR, and 95% by increasing noise power to 0dB SNR. The importance of this attack is its simplicity and flexibility: it can be employed in real time with no processing of an attacker's voice, and little computation is needed at the moment of detection, allowing the attack to be performed by a small portable device. For any target user, knowing that user's model or voice sample is sufficient to compute the attack signal, and it is enough that the intruder plays it while he/she is uttering to be classiffed as the victim.

  10. Predictability of Conversation Partners

    NASA Astrophysics Data System (ADS)

    Takaguchi, Taro; Nakamura, Mitsuhiro; Sato, Nobuo; Yano, Kazuo; Masuda, Naoki

    2011-08-01

    Recent developments in sensing technologies have enabled us to examine the nature of human social behavior in greater detail. By applying an information-theoretic method to the spatiotemporal data of cell-phone locations, [C. Song , ScienceSCIEAS0036-8075 327, 1018 (2010)] found that human mobility patterns are remarkably predictable. Inspired by their work, we address a similar predictability question in a different kind of human social activity: conversation events. The predictability in the sequence of one’s conversation partners is defined as the degree to which one’s next conversation partner can be predicted given the current partner. We quantify this predictability by using the mutual information. We examine the predictability of conversation events for each individual using the longitudinal data of face-to-face interactions collected from two company offices in Japan. Each subject wears a name tag equipped with an infrared sensor node, and conversation events are marked when signals are exchanged between sensor nodes in close proximity. We find that the conversation events are predictable to a certain extent; knowing the current partner decreases the uncertainty about the next partner by 28.4% on average. Much of the predictability is explained by long-tailed distributions of interevent intervals. However, a predictability also exists in the data, apart from the contribution of their long-tailed nature. In addition, an individual’s predictability is correlated with the position of the individual in the static social network derived from the data. Individuals confined in a community—in the sense of an abundance of surrounding triangles—tend to have low predictability, and those bridging different communities tend to have high predictability.

  11. Predictive Value of Morphological Features in Patients with Autism versus Normal Controls

    ERIC Educational Resources Information Center

    Ozgen, H.; Hellemann, G. S.; de Jonge, M. V.; Beemer, F. A.; van Engeland, H.

    2013-01-01

    We investigated the predictive power of morphological features in 224 autistic patients and 224 matched-pairs controls. To assess the relationship between the morphological features and autism, we used the receiver operator curves (ROC). In addition, we used recursive partitioning (RP) to determine a specific pattern of abnormalities that is…

  12. Prediction of PARP Inhibition with Proteochemometric Modelling and Conformal Prediction.

    PubMed

    Cortés-Ciriano, Isidro; Bender, Andreas; Malliavin, Thérèse

    2015-06-01

    Poly(ADP-ribose) polymerases (PARPs) play a key role in DNA damage repair. PARP inhibitors act as chemo- and radio- sensitizers and thus potentiate the cytotoxicity of DNA damaging agents. Although PARP inhibitors are currently investigated as chemotherapeutic agents, their cross-reactivity with other members of the PARP family remains unclear. Here, we apply Proteochemometric Modelling (PCM) to model the activity of 181 compounds on 12 human PARPs. We demonstrate that PCM (R0 (2) test =0.65-0.69; RMSEtest =0.95-1.01 °C) displays higher performance on the test set (interpolation) than Family QSAR and Family QSAM (Tukey's HSD, α 0.05), and outperforms Inductive Transfer knowledge among targets (Tukey's HSD, α 0.05). We benchmark the predictive signal of 8 amino acid and 11 full-protein sequence descriptors, obtaining that all of them (except for SOCN) perform at the same level of statistical significance (Tukey's HSD, α 0.05). The extrapolation power of PCM to new compounds (RMSE=1.02±0.80 °C) and targets (RMSE=1.03±0.50 °C) is comparable to interpolation, although the extrapolation ability is not uniform across the chemical and the target space. For this reason, we also provide confidence intervals calculated with conformal prediction. In addition, we present the R package conformal, which permits the calculation of confidence intervals for regression and classification caret models. PMID:27490382

  13. Graphing Predictions

    ERIC Educational Resources Information Center

    Connery, Keely Flynn

    2007-01-01

    Graphing predictions is especially important in classes where relationships between variables need to be explored and derived. In this article, the author describes how his students sketch the graphs of their predictions before they begin their investigations on two laboratory activities: Distance Versus Time Cart Race Lab and Resistance; and…

  14. Predictive Evaluation

    ERIC Educational Resources Information Center

    Scriven, Michael

    2007-01-01

    Noting that there has been extensive discussion of the relation of evaluation to: (1) research; (2) explanations (a.k.a. theory-driven, logic model, or realistic evaluation); and (3) recommendations, the author introduces: (4) prediction. He advocates that unlike the first three concepts, prediction is necessarily part of most kinds of evaluation,…

  15. Multikernel linear mixed models for complex phenotype prediction.

    PubMed

    Weissbrod, Omer; Geiger, Dan; Rosset, Saharon

    2016-07-01

    Linear mixed models (LMMs) and their extensions have recently become the method of choice in phenotype prediction for complex traits. However, LMM use to date has typically been limited by assuming simple genetic architectures. Here, we present multikernel linear mixed model (MKLMM), a predictive modeling framework that extends the standard LMM using multiple-kernel machine learning approaches. MKLMM can model genetic interactions and is particularly suitable for modeling complex local interactions between nearby variants. We additionally present MKLMM-Adapt, which automatically infers interaction types across multiple genomic regions. In an analysis of eight case-control data sets from the Wellcome Trust Case Control Consortium and more than a hundred mouse phenotypes, MKLMM-Adapt consistently outperforms competing methods in phenotype prediction. MKLMM is as computationally efficient as standard LMMs and does not require storage of genotypes, thus achieving state-of-the-art predictive power without compromising computational feasibility or genomic privacy. PMID:27302636

  16. Prediction of windage power loss in alternators

    NASA Technical Reports Server (NTRS)

    Vrancik, J. E.

    1971-01-01

    Simplified equations and constants, based on laminar and turbulent flow theory between parallel plates, estimate windage loss in rotating electrical machinery. Comparison of calculated results and experimental data for smooth cylindrical rotor and slotted alternator yields 7 percent maximum variation between calculated and experimental data.

  17. Airframe noise prediction

    NASA Astrophysics Data System (ADS)

    1990-11-01

    This Data Item 90023, an addition to the Noise Sub-series, provides the FORTRAN listing of a computer program for a semi-empirical method that calculates the far-field airframe aerodynamic noise generated by turbo-fan powered transport aircraft or gliders in one-third octave bands over a frequency range specified by the user. The overall sound pressure level is also output. The results apply for a still, lossless atmosphere; other ESDU methods may be used to correct for atmospheric attenuation, ground reflection, lateral attenuation, and wind and temperature gradients. The position of the aircraft relative to the observer is input in terms of the height at minimum range, and the elevation and azimuthal angles to the aircraft; if desired the user may obtain results over a range of those angles in 10 degree intervals. The method sums the contributions made by various components, results for which can also be output individually. The components are: the wind (conventional or delta), tailplane, fin, flaps (single/double slotted or triple slotted), leading-edge slats, and undercarriage legs and wheels (one/two wheel or four wheel units). The program requires only geometric data for each component (area and span in the case of lifting elements, flap deflection angle, and leg length and wheel diameter for the undercarriage). The program was validated for aircraft with take-off masses from 42,000 to 390,000 kg (92,000 to 860,000 lb) at airspeeds from 70 to 145 m/s (135 to 280 kn). Comparisons with available experimental data suggest a prediction rms accuracy of 1 dB at minimum range, rising to between 2 and 3 dB at 60 degrees to either side.

  18. A Complete Procedure for Predicting and Improving the Performance of HAWT's

    NASA Astrophysics Data System (ADS)

    Al-Abadi, Ali; Ertunç, Özgür; Sittig, Florian; Delgado, Antonio

    2014-06-01

    A complete procedure for predicting and improving the performance of the horizontal axis wind turbine (HAWT) has been developed. The first process is predicting the power extracted by the turbine and the derived rotor torque, which should be identical to that of the drive unit. The BEM method and a developed post-stall treatment for resolving stall-regulated HAWT is incorporated in the prediction. For that, a modified stall-regulated prediction model, which can predict the HAWT performance over the operating range of oncoming wind velocity, is derived from existing models. The model involves radius and chord, which has made it more general in applications for predicting the performance of different scales and rotor shapes of HAWTs. The second process is modifying the rotor shape by an optimization process, which can be applied to any existing HAWT, to improve its performance. A gradient- based optimization is used for adjusting the chord and twist angle distribution of the rotor blade to increase the extraction of the power while keeping the drive torque constant, thus the same drive unit can be kept. The final process is testing the modified turbine to predict its enhanced performance. The procedure is applied to NREL phase-VI 10kW as a baseline turbine. The study has proven the applicability of the developed model in predicting the performance of the baseline as well as the optimized turbine. In addition, the optimization method has shown that the power coefficient can be increased while keeping same design rotational speed.

  19. Bubble formation in additive manufacturing of glass

    NASA Astrophysics Data System (ADS)

    Luo, Junjie; Gilbert, Luke J.; Peters, Daniel C.; Bristow, Douglas A.; Landers, Robert G.; Goldstein, Jonathan T.; Urbas, Augustine M.; Kinzel, Edward C.

    2016-05-01

    Bubble formation is a common problem in glass manufacturing. The spatial density of bubbles in a piece of glass is a key limiting factor to the optical quality of the glass. Bubble formation is also a common problem in additive manufacturing, leading to anisotropic material properties. In glass Additive Manufacturing (AM) two separate types of bubbles have been observed: a foam layer caused by the reboil of the glass melt and a periodic pattern of bubbles which appears to be unique to glass additive manufacturing. This paper presents a series of studies to relate the periodicity of bubble formation to part scan speed, laser power, and filament feed rate. These experiments suggest that bubbles are formed by the reboil phenomena why periodic bubbles result from air being trapped between the glass filament and the substrate. Reboil can be detected using spectroscopy and avoided by minimizing the laser power while periodic bubbles can be avoided by a two-step laser melting process to first establish good contact between the filament and substrate before reflowing the track with higher laser power.

  20. An experiment on prediction markets in science.

    PubMed

    Almenberg, Johan; Kittlitz, Ken; Pfeiffer, Thomas

    2009-01-01

    Prediction markets are powerful forecasting tools. They have the potential to aggregate private information, to generate and disseminate a consensus among the market participants, and to provide incentives for information acquisition. These market functionalities can be very valuable for scientific research. Here, we report an experiment that examines the compatibility of prediction markets with the current practice of scientific publication. We investigated three settings. In the first setting, different pieces of information were disclosed to the public during the experiment. In the second setting, participants received private information. In the third setting, each piece of information was private at first, but was subsequently disclosed to the public. An automated, subsidizing market maker provided additional incentives for trading and mitigated liquidity problems. We find that the third setting combines the advantages of the first and second settings. Market performance was as good as in the setting with public information, and better than in the setting with private information. In contrast to the first setting, participants could benefit from information advantages. Thus the publication of information does not detract from the functionality of prediction markets. We conclude that for integrating prediction markets into the practice of scientific research it is of advantage to use subsidizing market makers, and to keep markets aligned with current publication practice. PMID:20041139