Science.gov

Sample records for additional predictive power

  1. Improving the predictive accuracy of hurricane power outage forecasts using generalized additive models.

    PubMed

    Han, Seung-Ryong; Guikema, Seth D; Quiring, Steven M

    2009-10-01

    Electric power is a critical infrastructure service after hurricanes, and rapid restoration of electric power is important in order to minimize losses in the impacted areas. However, rapid restoration of electric power after a hurricane depends on obtaining the necessary resources, primarily repair crews and materials, before the hurricane makes landfall and then appropriately deploying these resources as soon as possible after the hurricane. This, in turn, depends on having sound estimates of both the overall severity of the storm and the relative risk of power outages in different areas. Past studies have developed statistical, regression-based approaches for estimating the number of power outages in advance of an approaching hurricane. However, these approaches have either not been applicable for future events or have had lower predictive accuracy than desired. This article shows that a different type of regression model, a generalized additive model (GAM), can outperform the types of models used previously. This is done by developing and validating a GAM based on power outage data during past hurricanes in the Gulf Coast region and comparing the results from this model to the previously used generalized linear models.

  2. 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.

  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. 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.

  5. 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

  6. 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....

  7. 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....

  8. 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....

  9. 50 CFR 453.06 - Additional Committee powers.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

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

  10. 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....

  11. 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.

  12. THE PREDICTIVE POWER OF OHL'S PRECURSOR METHOD

    SciTech Connect

    Du, Z. L.; Wang, H. N.; Li, R.

    2009-12-15

    Using linear regression techniques and correlation analysis, the predictive power of Ohl's method is shown to satisfy one of the following relationships. Either a successful prediction of cycle amplitude can be obtained if the correlation between the minimum aa geomagnetic index in the declining phase of a solar cycle and the sunspot maximum of the succeeding cycle becomes stronger, or the prediction error exceeds the expected prediction error if the correlation becomes weaker. The correlation coefficient has a declining secular variation, which leads to a weakening trend in predictive power, as well as a 44 year periodicity that may explain why the prediction method did not work well for solar cycle 23. As this finding only emerged twice in the {approx}100 year period studied, this 44 year periodicity may occur with a degree of uncertainty and may therefore need to be checked in the future. Two quantities, namely a prediction parameter and the prediction index, are proposed to analyze predictive power. Using the above properties, the success probability of a prediction result can be analyzed in advance.

  13. 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.

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

    PubMed

    Lim, T J; Spokas, K A; Feyereisen, G; Novak, J M

    2016-01-01

    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 conductivity (Ksat). Four different kinds of biochar were added to four different textured soils (coarse sand, fine sand, loam, and clay texture) to assess these effects at the rates of 0%, 1%, 2%, and 5% (w/w). The Ksat of the biochar amended soils were significantly influenced by the rate and type of biochar, as well as the original particle size of soil. The Ksat decreased when biochar was added to coarse and fine sands. Biochar with larger particles sizes (60%; >1 mm) decreased Ksat to a larger degree than the smaller particle size biochar (60%; <1 mm) in the two sandy textured soils. Increasing tortuosity in the biochar amended sandy soil could explain this behavior. On the other hand, for the clay loam 1% and 2% biochar additions universally increased the Ksat with higher biochar amounts providing no further alterations. The developed model utilizes soil texture pedotransfer functions for predicting agricultural soil Ksat as a function of soil texture. The model accurately predicted the direction of the Ksat influence, even though the exact magnitude still requires further refinement. This represents the first step to a unified theory behind the impact of biochar additions on soil saturated conductivity. PMID:26145507

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

    PubMed

    Lim, T J; Spokas, K A; Feyereisen, G; Novak, J M

    2016-01-01

    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 conductivity (Ksat). Four different kinds of biochar were added to four different textured soils (coarse sand, fine sand, loam, and clay texture) to assess these effects at the rates of 0%, 1%, 2%, and 5% (w/w). The Ksat of the biochar amended soils were significantly influenced by the rate and type of biochar, as well as the original particle size of soil. The Ksat decreased when biochar was added to coarse and fine sands. Biochar with larger particles sizes (60%; >1 mm) decreased Ksat to a larger degree than the smaller particle size biochar (60%; <1 mm) in the two sandy textured soils. Increasing tortuosity in the biochar amended sandy soil could explain this behavior. On the other hand, for the clay loam 1% and 2% biochar additions universally increased the Ksat with higher biochar amounts providing no further alterations. The developed model utilizes soil texture pedotransfer functions for predicting agricultural soil Ksat as a function of soil texture. The model accurately predicted the direction of the Ksat influence, even though the exact magnitude still requires further refinement. This represents the first step to a unified theory behind the impact of biochar additions on soil saturated conductivity.

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

    NASA Astrophysics Data System (ADS)

    Spokas, Kurt; Lim, Tae Jun; Feyereisen, Gary; Novak, Jeff

    2015-04-01

    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 conductivity (Ksat). Four different kinds of biochar were added to four different textured soils (coarse sand, fine sand, loam, and clay texture) to assess these effects at the rates of 0, 1, 2, and 5 % (w/w). The Ksat of the biochar amended soils were significantly influenced by the rate and type of biochar, as well as the original particle size of soil. The Ksat decreased when biochar was added to coarse and fine sands. Biochar with larger particles sizes (60%; >1 mm) decreased Ksat to a larger degree than the smaller particle size biochar (60%; <1 mm) in the two sandy textured soils. Increasing tortuosity in the amended sandy soil could explain this behavior. On the other hand, for the clay loam 1% and 2% biochar additions universally increased the Ksat with higher biochar amounts providing no further alterations. The developed model utilizes soil texture pedotransfer functions for predicting agricultural soil Ksat as a function of soil texture. The model accurately predicted the direction of the Ksat influence, even though the exact magnitude still requires further refinement.

  17. 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.

  18. 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

  19. 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

  20. 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.

  1. Predictive aging results for cable materials in nuclear power plants

    SciTech Connect

    Gillen, K.T.; Clough, R.L.

    1990-11-01

    In this report, we provide a detailed discussion of methodology of predicting cable degradation versus dose rate, temperature, and exposure time and its application to data obtained on a number of additional nuclear power plant cable insulation (a hypalon, a silicon rubber and two ethylenetetrafluoroethylenes) and jacket (a hypalon) materials. We then show that the predicted, low-dose-rate results for our materials are in excellent agreement with long-term (7 to 9 years), low dose-rate results recently obtained for the same material types actually aged under nuclear power plant conditions. Based on a combination of the modelling and long-term results, we find indications of reasonably similar degradation responses among several different commercial formulations for each of the following generic'' materials: hypalon, ethylenetetrafluoroethylene, silicone rubber and PVC. If such generic'' behavior can be further substantiated through modelling and long-term results on additional formulations, predictions of cable life for other commercial materials of the same generic types would be greatly facilitated. Finally, to aid utilities in their cable life extension decisions, we utilize our modelling results to generate lifetime prediction curves for the materials modelled to data. These curves plot expected material lifetime versus dose rate and temperature down to the levels of interest to nuclear power plant aging. 18 refs., 30 figs., 3 tabs.

  2. 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

  3. 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

  4. 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

  5. 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

  6. Evaluation of peak power prediction equations in male basketball players.

    PubMed

    Duncan, Michael J; Lyons, Mark; Nevill, Alan M

    2008-07-01

    This study compared peak power estimated using 4 commonly used regression equations with actual peak power derived from force platform data in a group of adolescent basketball players. Twenty-five elite junior male basketball players (age, 16.5 +/- 0.5 years; mass, 74.2 +/- 11.8 kg; height, 181.8 +/- 8.1 cm) volunteered to participate in the study. Actual peak power was determined using a countermovement vertical jump on a force platform. Estimated peak power was determined using countermovement jump height and body mass. All 4 prediction equations were significantly related to actual peak power (all p < 0.01). Repeated-measures analysis of variance indicated significant differences between actual peak power and estimate peak power from all 4 prediction equations (p < 0.001). Bonferroni post hoc tests indicated that estimated peak power was significantly lower than actual peak power for all 4 prediction equations. Ratio limits of agreement for actual peak power and estimated peak power were 8% for the Harman et al. and Sayers squat jump prediction equations, 12% for the Canavan and Vescovi equation, and 6% for the Sayers countermovement jump equation. In all cases peak power was underestimated.

  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. 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

  10. 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.

  11. 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)

  12. 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.

  13. 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.

  14. 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.

  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, 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.

  17. 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.

  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. Predicting Ash Behavior in Conventional Power Systems

    NASA Astrophysics Data System (ADS)

    Zygarlicke, Christopher J.

    In summary, the use of thermoequilibrium modeling and advanced fouling indices has proven to be beneficial in helping a minemouth utility to improve performance. In this case, the mine used advanced indices to derive a fouling index contour map to plan blending schemes that would provide the plant with a more consistent blend of lignite that minimizes fouling potential. The plant also benefitted from this scheme by being able to correlate operation parameters such as quantified boiler ash deposition monitoring, sootblower control, gas attemperation, flue gas recirculation, and fuel/oxygen ratios to help extend the operation of the boiler between cleaning outages. This case is more extreme than most plants encounter, since the coal is very high in sodium and ash deposition and frequent boiler cleaning is inevitable. However, by gaining even just 2-3 extra weeks between cleaning shutdowns, the plant saves in costs. The plant also gains an indirect means of forewarning by analyzing the coal at the mine level in order to plan for lower FEGTs or additional sootblowing when a known high-fouling stream of coal is coming into the boiler.

  1. 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

  2. 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

  3. Additive Effects of Repetition and Predictability during Comprehension: Evidence from Event-Related Potentials

    PubMed Central

    Barrios, Shannon; Parker, Dan; Morini, Giovanna; Lau, Ellen

    2014-01-01

    Previous research has shown that neural responses to words during sentence comprehension are sensitive to both lexical repetition and a word’s predictability in context. While previous research has often contrasted the effects of these variables (e.g. by looking at cases in which word repetition violates sentence-level constraints), little is known about how they work in tandem. In the current study we examine how recent exposure to a word and its predictability in context combine to impact lexical semantic processing. We devise a novel paradigm that combines reading comprehension with a recognition memory task, allowing for an orthogonal manipulation of a word’s predictability and its repetition status. Using event-related brain potentials (ERPs), we show that word repetition and predictability have qualitatively similar and additive effects on the N400 amplitude. We propose that prior exposure to a word and predictability impact lexical semantic processing in an additive and independent fashion. PMID:24905459

  4. 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.

  5. 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

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. Takeoff predictions for powered-lift aircraft. Thesis

    NASA Technical Reports Server (NTRS)

    Wardwell, Douglas A.; Sandlin, Doral R.

    1988-01-01

    Takeoff predictions for powered-lift short takeoff (STO) and conventional takeoff (CTO) aircraft have been added to NASA Ames Research Center's Aircraft Synthesis (ACSYNT) code. The new computer code predicts the aircraft engine and nozzle settings required to achieve the minimum takeoff roll. As a test case, the code predicted takeoff ground rolls and nozzle settings for the YAV-8B Harrier that compared well with measured values. Brief analysis of takeoff performance for an Ejector, Remote Augmented Lift, Hybrid-Tandem Fan, and Vectored Thrust STO aircraft using the new routine will be presented.

  11. Skill forecasting from different wind power ensemble prediction methods

    NASA Astrophysics Data System (ADS)

    Pinson, Pierre; Nielsen, Henrik Aa; Madsen, Henrik; Kariniotakis, George

    2007-07-01

    This paper presents an investigation on alternative approaches to the providing of uncertainty estimates associated to point predictions of wind generation. Focus is given to skill forecasts in the form of prediction risk indices, aiming at giving a comprehensive signal on the expected level of forecast uncertainty. Ensemble predictions of wind generation are used as input. A proposal for the definition of prediction risk indices is given. Such skill forecasts are based on the dispersion of ensemble members for a single prediction horizon, or over a set of successive look-ahead times. It is shown on the test case of a Danish offshore wind farm how prediction risk indices may be related to several levels of forecast uncertainty (and energy imbalances). Wind power ensemble predictions are derived from the transformation of ECMWF and NCEP ensembles of meteorological variables to power, as well as by a lagged average approach alternative. The ability of risk indices calculated from the various types of ensembles forecasts to resolve among situations with different levels of uncertainty is discussed.

  12. 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,…

  13. 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.

  14. 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

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

    PubMed

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

    2013-08-15

    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.

  16. 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.

  17. Peak power prediction in junior basketballers: comparing linear and allometric models.

    PubMed

    Duncan, Michael J; Hankey, Joanne; Lyons, Mark; James, Rob S; Nevill, Alan M

    2013-03-01

    Equations, commonly used to predict peak power from jump height, have relied on linear additive models that are biologically unsound beyond the range of observations because of high negative intercept values. This study explored the utility of allometric multiplicative modeling to better predict peak power in adolescent basketball players. Seventy-seven elite junior basketball players (62 adolescent boys, 15 adolescent girls, age = 16.8 ± 0.8 years) performed 3 counter movement jumps (CMJs) on a force platform. Both linear and multiplicative models were then used to determine their efficacy. Four previously published linear equations were significantly associated with actual peak power (all p < 0.01), although here were significant differences between actual and estimated peak power using the SJ and CMJ equations by Sayers (both p < 0.001). Allometric modeling was used to determine an alternative biologically sound equation which was more strongly associated with (r = 0.886, p < 0.001), and not significantly different to (p > 0.05), actual peak power and predicted 77.9% of the variance in actual peak power (adjusted R = 0.779, p < 0.001). Exponents close to 1 for body mass and CMJ height indicated that peak power could also be determined from the product of body mass and CMJ height. This equation was significantly associated (r = 0.871, p < 0.001) with, and not significantly different to, actual peak power (adjusted R = 0.756, p > 0.05) and offered a more accurate estimation of peak power than previously validated linear additive models examined in this study. The allometric model determined from this study or the multiplicative model (body mass × CMJ height) provides biologically sound models to accurately estimate peak power in elite adolescent basketballers that are more accurate than equations based on linear additive models.

  18. Generalized Concentration Addition Modeling Predicts Mixture Effects of Environmental PPARγ Agonists.

    PubMed

    Watt, James; Webster, Thomas F; Schlezinger, Jennifer J

    2016-09-01

    The vast array of potential environmental toxicant combinations necessitates the development of efficient strategies for predicting toxic effects of mixtures. Current practices emphasize the use of concentration addition to predict joint effects of endocrine disrupting chemicals in coexposures. Generalized concentration addition (GCA) is one such method for predicting joint effects of coexposures to chemicals and has the advantage of allowing for mixture components to have differences in efficacy (ie, dose-response curve maxima). Peroxisome proliferator-activated receptor gamma (PPARγ) is a nuclear receptor that plays a central role in regulating lipid homeostasis, insulin sensitivity, and bone quality and is the target of an increasing number of environmental toxicants. Here, we tested the applicability of GCA in predicting mixture effects of therapeutic (rosiglitazone and nonthiazolidinedione partial agonist) and environmental PPARγ ligands (phthalate compounds identified using EPA's ToxCast database). Transcriptional activation of human PPARγ1 by individual compounds and mixtures was assessed using a peroxisome proliferator response element-driven luciferase reporter. Using individual dose-response parameters and GCA, we generated predictions of PPARγ activation by the mixtures, and we compared these predictions with the empirical data. At high concentrations, GCA provided a better estimation of the experimental response compared with 3 alternative models: toxic equivalency factor, effect summation and independent action. These alternatives provided reasonable fits to the data at low concentrations in this system. These experiments support the implementation of GCA in mixtures analysis with endocrine disrupting compounds and establish PPARγ as an important target for further studies of chemical mixtures.

  19. 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.

  20. Comparison and validation of statistical methods for predicting power outage durations in the event of hurricanes.

    PubMed

    Nateghi, Roshanak; Guikema, Seth D; Quiring, Steven M

    2011-12-01

    This article compares statistical methods for modeling power outage durations during hurricanes and examines the predictive accuracy of these methods. Being able to make accurate predictions of power outage durations is valuable because the information can be used by utility companies to plan their restoration efforts more efficiently. This information can also help inform customers and public agencies of the expected outage times, enabling better collective response planning, and coordination of restoration efforts for other critical infrastructures that depend on electricity. In the long run, outage duration estimates for future storm scenarios may help utilities and public agencies better allocate risk management resources to balance the disruption from hurricanes with the cost of hardening power systems. We compare the out-of-sample predictive accuracy of five distinct statistical models for estimating power outage duration times caused by Hurricane Ivan in 2004. The methods compared include both regression models (accelerated failure time (AFT) and Cox proportional hazard models (Cox PH)) and data mining techniques (regression trees, Bayesian additive regression trees (BART), and multivariate additive regression splines). We then validate our models against two other hurricanes. Our results indicate that BART yields the best prediction accuracy and that it is possible to predict outage durations with reasonable accuracy.

  1. Can metabolomics in addition to genomics add to prognostic and predictive information in breast cancer?

    PubMed

    Howell, Anthony

    2010-11-16

    Genomic data from breast cancers provide additional prognostic and predictive information that is beginning to be used for patient management. The question arises whether additional information derived from other 'omic' approaches such as metabolomics can provide additional information. In an article published this month in BMC Cancer, Borgan et al. add metabolomic information to genomic measures in breast tumours and demonstrate, for the first time, that it may be possible to further define subgroups of patients which could be of value clinically. See research article: http://www.biomedcentral.com/1471-2407/10/628.

  2. Additional disulfide bonds in insulin: Prediction, recombinant expression, receptor binding affinity, and stability

    PubMed Central

    Vinther, Tine N; Pettersson, Ingrid; Huus, Kasper; Schlein, Morten; Steensgaard, Dorte B; Sørensen, Anders; Jensen, Knud J; Kjeldsen, Thomas; Hubalek, František

    2015-01-01

    The structure of insulin, a glucose homeostasis-controlling hormone, is highly conserved in all vertebrates and stabilized by three disulfide bonds. Recently, we designed a novel insulin analogue containing a fourth disulfide bond located between positions A10-B4. The N-terminus of insulin's B-chain is flexible and can adapt multiple conformations. We examined how well disulfide bond predictions algorithms could identify disulfide bonds in this region of insulin. In order to identify stable insulin analogues with additional disulfide bonds, which could be expressed, the Cβ cut-off distance had to be increased in many instances and single X-ray structures as well as structures from MD simulations had to be used. The analogues that were identified by the algorithm without extensive adjustments of the prediction parameters were more thermally stable as assessed by DSC and CD and expressed in higher yields in comparison to analogues with additional disulfide bonds that were more difficult to predict. In contrast, addition of the fourth disulfide bond rendered all analogues resistant to fibrillation under stress conditions and all stable analogues bound to the insulin receptor with picomolar affinities. Thus activity and fibrillation propensity did not correlate with the results from the prediction algorithm. PMID:25627966

  3. 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

  4. 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.

  5. Ice Accretion Prediction on Wind Turbines and Consequent Power Losses

    NASA Astrophysics Data System (ADS)

    Yirtici, Ozcan; Tuncer, Ismail H.; Ozgen, Serkan

    2016-09-01

    Ice accretion on wind turbine blades modifies the sectional profiles and causes alteration in the aerodynamic characteristic of the blades. The objective of this study is to determine performance losses on wind turbines due to the formation of ice in cold climate regions and mountainous areas where wind energy resources are found. In this study, the Blade Element Momentum method is employed together with an ice accretion prediction tool in order to estimate the ice build-up on wind turbine blades and the energy production for iced and clean blades. The predicted ice shapes of the various airfoil profiles are validated with the experimental data and it is shown that the tool developed is promising to be used in the prediction of power production losses of wind turbines.

  6. 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

  7. Generalized Concentration Addition Modeling Predicts Mixture Effects of Environmental PPARγ Agonists.

    PubMed

    Watt, James; Webster, Thomas F; Schlezinger, Jennifer J

    2016-09-01

    The vast array of potential environmental toxicant combinations necessitates the development of efficient strategies for predicting toxic effects of mixtures. Current practices emphasize the use of concentration addition to predict joint effects of endocrine disrupting chemicals in coexposures. Generalized concentration addition (GCA) is one such method for predicting joint effects of coexposures to chemicals and has the advantage of allowing for mixture components to have differences in efficacy (ie, dose-response curve maxima). Peroxisome proliferator-activated receptor gamma (PPARγ) is a nuclear receptor that plays a central role in regulating lipid homeostasis, insulin sensitivity, and bone quality and is the target of an increasing number of environmental toxicants. Here, we tested the applicability of GCA in predicting mixture effects of therapeutic (rosiglitazone and nonthiazolidinedione partial agonist) and environmental PPARγ ligands (phthalate compounds identified using EPA's ToxCast database). Transcriptional activation of human PPARγ1 by individual compounds and mixtures was assessed using a peroxisome proliferator response element-driven luciferase reporter. Using individual dose-response parameters and GCA, we generated predictions of PPARγ activation by the mixtures, and we compared these predictions with the empirical data. At high concentrations, GCA provided a better estimation of the experimental response compared with 3 alternative models: toxic equivalency factor, effect summation and independent action. These alternatives provided reasonable fits to the data at low concentrations in this system. These experiments support the implementation of GCA in mixtures analysis with endocrine disrupting compounds and establish PPARγ as an important target for further studies of chemical mixtures. PMID:27255385

  8. 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.

  9. Estimating Additive and Non-Additive Genetic Variances and Predicting Genetic Merits Using Genome-Wide Dense Single Nucleotide Polymorphism Markers

    PubMed Central

    Su, Guosheng; Christensen, Ole F.; Ostersen, Tage; Henryon, Mark; Lund, Mogens S.

    2012-01-01

    Non-additive genetic variation is usually ignored when genome-wide markers are used to study the genetic architecture and genomic prediction of complex traits in human, wild life, model organisms or farm animals. However, non-additive genetic effects may have an important contribution to total genetic variation of complex traits. This study presented a genomic BLUP model including additive and non-additive genetic effects, in which additive and non-additive genetic relation matrices were constructed from information of genome-wide dense single nucleotide polymorphism (SNP) markers. In addition, this study for the first time proposed a method to construct dominance relationship matrix using SNP markers and demonstrated it in detail. The proposed model was implemented to investigate the amounts of additive genetic, dominance and epistatic variations, and assessed the accuracy and unbiasedness of genomic predictions for daily gain in pigs. In the analysis of daily gain, four linear models were used: 1) a simple additive genetic model (MA), 2) a model including both additive and additive by additive epistatic genetic effects (MAE), 3) a model including both additive and dominance genetic effects (MAD), and 4) a full model including all three genetic components (MAED). Estimates of narrow-sense heritability were 0.397, 0.373, 0.379 and 0.357 for models MA, MAE, MAD and MAED, respectively. Estimated dominance variance and additive by additive epistatic variance accounted for 5.6% and 9.5% of the total phenotypic variance, respectively. Based on model MAED, the estimate of broad-sense heritability was 0.506. Reliabilities of genomic predicted breeding values for the animals without performance records were 28.5%, 28.8%, 29.2% and 29.5% for models MA, MAE, MAD and MAED, respectively. In addition, models including non-additive genetic effects improved unbiasedness of genomic predictions. PMID:23028912

  10. 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.

  11. 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.

  12. 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.

  13. Prediction of heater power distribution in radiative cylindrical furnaces

    SciTech Connect

    Ravichandran, M.; Dilber, I.; Torok, D.

    1999-07-01

    In the design of long radiative cylindrical furnaces, it is important to control the temperature variation along the furnace walls and consequently the temperature distribution in the processed material by selectively adjusting the power input to heater rods located circumferentially around the furnace walls. The heaters are grouped in zones located at different axial locations. By adjusting the power to each zone a specified temperature distribution along the furnace can be attained. The radiative interchange between different axial zones of the furnace affects the temperature distribution; this interchange is also impacted by the shadowing caused by the presence of the load, i.e. the processed material. A desired temperature distribution can only be achieved by selectively changing the power input to the heaters. For an a priori assessment of the commercial viability of using process friendly temperature distributions, it is necessary to determine: (a) the maximum power demand from each zone; (b) if active cooling is inevitable and (c) the bounds on temperature distribution that can be achieved without active cooling. It is therefore extremely useful to be able to predict the input power distribution for achieving desired furnace temperature profiles. For a given power input, the temperature distribution inside the furnace could be obtained by using a general purpose Computational Fluid Dynamics (CFD) software, such as FIDAP. A new methodology is developed within the framework of FIDAP software to eliminate the manual trial and error method. The method is based on obtaining the sensitivity of the temperature at the desired locations of the furnace as a function of the power input to the heating elements. Using these sensitivity coefficients, an iterative scheme is designed to adjust the boundary conditions (power to the heating elements in this case) based on the discrepancy of the solution temperatures from the desired temperature distribution. For each of these

  14. 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.

  15. Muscle Power Predicts Adolescent Bone Strength: Iowa Bone Development Study

    PubMed Central

    Janz, Kathleen F.; Letuchy, Elena M.; Burns, Trudy L.; Francis, Shelby L.; Levy, Steven M.

    2015-01-01

    Purpose To assess association between lower body muscle power and bone strength, as well as the mediating effect of muscle cross-sectional area (MCSA) on that association. Methods Participants (N=141 males; 162 females) were approximately 17 years. Muscle power was predicted using vertical jump and the Sayers equation. Using peripheral quantitative computed tomography (pQCT), bone strength indices were obtained at two locations of the tibia, corresponding to primary stressors acting upon each site: bone strength index for compression (BSI) at the distal 4% site; density-weighted polar section modulus strength-strain index [SSIp] and cortical bone area (CoA) at the 66% mid-shaft site for torsion. Muscle cross-sectional area (MCSA) was measured at the 66% site. Pearson bivariate and partial correlation coefficients were estimated to quantify the strength of the associations among variables. Direct and indirect mediation model effects were estimated and 95% bootstrap confidence intervals were constructed to test the causal hypothesis. Height and maturity were examined as covariates. Results Pearson correlation coefficients among muscle power, MCSA, and bone strength were statistically significant (p<0.01) and ranged from r=0.54 to 0.78. After adjustment for covariates, associations were reduced (r=0.37 to 0.69) (p<0.01). Mediation models for males for BSI, SSIp, and CoA accounted for 38%, 66%, and 54% of the variance in bone strength, respectively. Models for females for BSI, SSIp, and CoA accounted for 46%, 77%, and 66% of the variance, respectively. Conclusions We found strong and consistent associations, as well as direct and indirect pathways, among muscle power, MCSA, and tibia strength. These results support the use of muscle power as a component of health-related fitness in bone health interventions for older adolescents. PMID:25751769

  16. A feasibility study on the predictive emission monitoring system applied to the Hsinta power plant of Taiwan Power Company.

    PubMed

    Chien, T W; Chu, H; Hsu, W C; Tseng, T K; Hsu, C H; Chen, K Y

    2003-08-01

    The continuous emission monitoring system (CEMS) can monitor flue gas emissions continuously and instantaneously. However, it has the disadvantages of enormous cost, easily producing errors in sampling periods of bad weather, lagging response in variable ambient environments, and missing data in daily zero and span tests and maintenance. The concept of a predictive emission monitoring system (PEMS) is to use the operating parameters of combustion equipment through thermodynamic or statistical methods to construct a mathematic model that can predict emissions by a computer program. The goal of this study is to set up a PEMS in a gas-fired combined cycle power generation unit at the Hsinta station of Taiwan Power Co. The emissions to be monitored include nitrogen oxides (NOx) and oxygen (O2) in flue gas. The major variables of the predictive model were determined based on the combustion theory. The data of these variables then were analyzed to establish a regression model. From the regression results, the influences of these variables are discussed and the predicted values are compared with the CEMS data for accuracy. In addition, according to the cost information, the capital and operation and maintenance costs for a PEMS can be much lower than those for a CEMS.

  17. 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.

  18. 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

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. Additive Genetic Risk from Five Serotonin System Polymorphisms Interacts with Interpersonal Stress to Predict Depression

    PubMed Central

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

    2016-01-01

    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 (GxE). 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 GxE predicting depression, we created an additive multilocus profile score from five serotonin system polymorphisms (one each in the genes HTR1A, HTR2A, HTR2C, and two in TPH2). Analyses focused on two forms of interpersonal stress as environmental risk factors. Using five 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 (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 GxE 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 GxE 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. 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

  5. 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.

  6. 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

  7. Prediction of additional lymph node involvement in breast cancer patients with positive sentinel lymph nodes.

    PubMed

    Pohlodek, K; Bozikova, S; Meciarova, I; Mucha, V; Bartova, M; Ondrias, F

    2016-01-01

    Axillary lymph node dissection (ALND) has traditionally been the principal method for evaluating axillary lymph node status in breast cancer patients. In the past decades sentinel lymph nodes biopsy after lymphatic mapping has been used to stage the disease. The majority of sentinel lymph nodes (SLN) positive patients do not have additional metastases in non-sentinel nodes (non-SLN) after additional ALND. These patients are exposed to the morbidity of ALND without any benefit from additional axillary clearence. In the present study we would like to asses the criteria for selecting those patients, who have high risk for non-SLN metastases in the axilla in cases of positive SLN. In this retrospective analysis, clinical and pathologic data from 163 patients who underwent SLN biopsy followed by ALND were collected. Following clinical and pathological characteristics were analyzed to predict the likehood of non-SLN metastases: age, staging, histologic type and grading of the tumors, hormonal receptor status, HER-2 receptor status and Ki-67 protein, angioinvasion, metastases in SLN and non-SLN. Relative frequencies of individual characteristics between sample groups were statistically tested by Chi-square test at significance level p=0.5, when sample sizes in groups were small (≤5) by Fisher´s exact test. Metastasis in SLN were present in 67 (41%) of patients, 48 patients (29,4%) had metastasis also in non-SLN. The ratio between non-SLN positive / non-SLN negative lymph nodes in patients with positive SLN increases with the stage of the disease, the difference between values for the pT1c and pT2 stadium was statistically significant (p = 0.0296). The same applies to grading, but the differences were not significant (p>0.05). We could not find significant differences for angioinvasion of the tumor, probably for small number of patients with angioinvasion (p>0.05).Only the stage of the tumor was shown to be significant in predicting the metastasis in non-SLN in our

  8. 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

  9. 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

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. Unity power factor converter based on a fuzzy controller and predictive input current.

    PubMed

    Bouafassa, Amar; Rahmani, Lazhar; Kessal, Abdelhalim; Babes, Badreddine

    2014-11-01

    This paper proposes analysis and control of a single-phase power factor corrector (PFC). The proposed control is capable of achieving a unity power factor for each DC link voltage or load fluctuation. The method under study is composed of two intelligent approaches, a fuzzy logic controller to ensure an output voltage at a suitable value and predictive current control. The fuzzy controller is used with minimum rules to attain a low cost. The method is verified and discussed through simulation on the MATLAB/Simulink platform. It presents high dynamic performance under various parameter changes. Moreover, in order to examine and evaluate the method in real-time, a test bench is built using dSPACE 1104. The implantation of the proposed method is very easy and flexible and allows for operation under parameter variations. Additionally, the obtained results are very significant.

  17. 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

  18. How to produce personality neuroscience research with high statistical power and low additional cost.

    PubMed

    Mar, Raymond A; Spreng, R Nathan; Deyoung, Colin G

    2013-09-01

    Personality neuroscience involves examining relations between cognitive or behavioral variability and neural variables like brain structure and function. Such studies have uncovered a number of fascinating associations but require large samples, which are expensive to collect. Here, we propose a system that capitalizes on neuroimaging data commonly collected for separate purposes and combines it with new behavioral data to test novel hypotheses. Specifically, we suggest that groups of researchers compile a database of structural (i.e., anatomical) and resting-state functional scans produced for other task-based investigations and pair these data with contact information for the participants who contributed the data. This contact information can then be used to collect additional cognitive, behavioral, or individual-difference data that are then reassociated with the neuroimaging data for analysis. This would allow for novel hypotheses regarding brain-behavior relations to be tested on the basis of large sample sizes (with adequate statistical power) for low additional cost. This idea can be implemented at small scales at single institutions, among a group of collaborating researchers, or perhaps even within a single lab. It can also be implemented at a large scale across institutions, although doing so would entail a number of additional complications.

  19. 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)

  20. Power conversion efficiency enhancement in OPV devices using spin 1/2 molecular additives

    NASA Astrophysics Data System (ADS)

    Basel, Tek; Vardeny, Valy; Yu, Luping

    2014-03-01

    We investigated the power conversion efficiency of bulk heterojunction OPV cells based on the low bandgap polymer PTB7, blend with C61-PCBM. We also employed the technique of photo-induced absorption, PA; electrical and magneto-PA (MPA) techniques to understand the details of the photocurrent generation process in this blend. We found that spin 1/2 molecular additives, such as Galvinoxyl (Gxl) radicals dramatically enhance the cell efficiency; we obtained 20% increase in photocurrent upon Gxl doping with 2% weight. We explain our finding by the ability of the spin 1/2 radicals to interfere with the known major loss mechanism in the cell due to recombination of charge transfer exciton at the D-A interface via triplet excitons in the polymer donors. Supported by National Science Foundation-Material Science & Engineering Center (NSF-MRSEC), University of Utah.

  1. 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…

  2. Mixed model methods for genomic prediction and variance component estimation of additive and dominance effects using SNP markers.

    PubMed

    Da, Yang; Wang, Chunkao; Wang, Shengwen; Hu, Guo

    2014-01-01

    We established a genomic model of quantitative trait with genomic additive and dominance relationships that parallels the traditional quantitative genetics model, which partitions a genotypic value as breeding value plus dominance deviation and calculates additive and dominance relationships using pedigree information. Based on this genomic model, two sets of computationally complementary but mathematically identical mixed model methods were developed for genomic best linear unbiased prediction (GBLUP) and genomic restricted maximum likelihood estimation (GREML) of additive and dominance effects using SNP markers. These two sets are referred to as the CE and QM sets, where the CE set was designed for large numbers of markers and the QM set was designed for large numbers of individuals. GBLUP and associated accuracy formulations for individuals in training and validation data sets were derived for breeding values, dominance deviations and genotypic values. Simulation study showed that GREML and GBLUP generally were able to capture small additive and dominance effects that each accounted for 0.00005-0.0003 of the phenotypic variance and GREML was able to differentiate true additive and dominance heritability levels. GBLUP of the total genetic value as the summation of additive and dominance effects had higher prediction accuracy than either additive or dominance GBLUP, causal variants had the highest accuracy of GREML and GBLUP, and predicted accuracies were in agreement with observed accuracies. Genomic additive and dominance relationship matrices using SNP markers were consistent with theoretical expectations. The GREML and GBLUP methods can be an effective tool for assessing the type and magnitude of genetic effects affecting a phenotype and for predicting the total genetic value at the whole genome level.

  3. 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.

  4. Prediction of transient electromagnetic environment in power networks

    SciTech Connect

    Nekhoul, B.; Feuillet, R.; Sabonnadiere, J.C.; Quinchon, L.; Morillon, F.

    1994-09-01

    In this paper the authors suggest exact analytic formulations which allow numerical characterization of the transient electromagnetic environment, during operation of circuit breakers or disconnectors, of an electric power transmission network. In this work, an exact method for calculating the transient field radiated by an air insulation substation (AIS) together with the strictest formalism which enables the same calculation to be made for a power transmission line are paid particular attention. Results of simulations for different examples together with results of measurements complete the study.

  5. 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...

  6. 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.

  7. Initial Study on the Predictability of Real Power on the Grid based on PMU Data

    SciTech Connect

    Ferryman, Thomas A.; Tuffner, Francis K.; Zhou, Ning; Lin, Guang

    2011-03-23

    Operations on the electric power grid provide highly reliable power to the end users. These operations involve hundreds of human operators and automated control schemes. However, the operations process can often take several minutes to complete. During these several minutes, the operations are often evaluated on a past state of the power system. Proper prediction methods could change this to make the operations evaluate the state of the power grid minutes in advance. Such information allows proactive, rather than reactive, actions on the power system and aids in improving the efficiency and reliability of the power grid as a whole. A successful demonstration of this prediction framework is necessary to evaluate the feasibility of utilizing such predicted states in grid operations.

  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. 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

  10. 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.

  11. 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.

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

    PubMed

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

    2015-12-01

    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.

  13. 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

  14. 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

  15. 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

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. BDDCS Predictions, Self-Correcting Aspects of BDDCS Assignments, BDDCS Assignment Corrections, and Classification for more than 175 Additional Drugs.

    PubMed

    Hosey, Chelsea M; Chan, Rosa; Benet, Leslie Z

    2016-01-01

    The biopharmaceutics drug disposition classification system was developed in 2005 by Wu and Benet as a tool to predict metabolizing enzyme and drug transporter effects on drug disposition. The system was modified from the biopharmaceutics classification system and classifies drugs according to their extent of metabolism and their water solubility. By 2010, Benet et al. had classified over 900 drugs. In this paper, we incorporate more than 175 drugs into the system and amend the classification of 13 drugs. We discuss current and additional applications of BDDCS, which include predicting drug-drug and endogenous substrate interactions, pharmacogenomic effects, food effects, elimination routes, central nervous system exposure, toxicity, and environmental impacts of drugs. When predictions and classes are not aligned, the system detects an error and is able to self-correct, generally indicating a problem with initial class assignment and/or measurements determining such assignments.

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

    PubMed

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

    2014-09-28

    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.

  2. 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

  3. 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

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

    PubMed

    Colbeck, Roger; Renner, Renato

    2011-08-02

    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.

  5. Additive Methods for Prediction of Thermochemical Properties. The Laidler Method Revisited. 1. Hydrocarbons

    NASA Astrophysics Data System (ADS)

    Leal, Joa˜O. Paulo

    2006-03-01

    A new parameterization of the Laidler method for estimation of atomization enthalpies and standard enthalpies of formation at 298.15 K for several families of hydrocarbons (alkanes, alkenes, alkynes, polyenes, poly-ynes, alkyl radicals, cycloalkanes, cycloalkenes, benzene derivatives, and polyaromatics) is presented. A total of 200 compounds (164 for liquid phase) are used for the calculation of the parameters. Comparison between the experimental values and those calculated using the group additive scheme led to an average difference of 1.28 kJṡmol-1 for the gas phase enthalpy of formation (excluding the polyaromatic compounds) and of 1.38 kJṡmol-1 for the liquid phase enthalpy of formation. The data base used appears to be essentially error free, but for some compounds (e.g., 2,2,4-trimethyl-pentane, with the highest deviation among all compounds except the polyaromatic ones) the experimental values might need a reevaluation. An Excel worksheet is provided to simplify the calculation of enthalpies of formation and atomization enthalpies based on the Laidler terms defined in this paper.

  6. Harmonic Resonance in Power Transmission Systems due to the Addition of Shunt Capacitors

    NASA Astrophysics Data System (ADS)

    Patil, Hardik U.

    Shunt capacitors are often added in transmission networks at suitable locations to improve the voltage profile. In this thesis, the transmission system in Arizona is considered as a test bed. Many shunt capacitors already exist in the Arizona transmission system and more are planned to be added. Addition of these shunt capacitors may create resonance conditions in response to harmonic voltages and currents. Such resonance, if it occurs, may create problematic issues in the system. It is main objective of this thesis to identify potential problematic effects that could occur after placing new shunt capacitors at selected buses in the Arizona network. Part of the objective is to create a systematic plan for avoidance of resonance issues. For this study, a method of capacitance scan is proposed. The bus admittance matrix is used as a model of the networked transmission system. The calculations on the admittance matrix were done using Matlab. The test bed is the actual transmission system in Arizona; however, for proprietary reasons, bus names are masked in the thesis copy intended for the public domain. The admittance matrix was obtained from data using the PowerWorld Simulator after equivalencing the 2016 summer peak load (planning case). The full Western Electricity Coordinating Council (WECC) system data were used. The equivalencing procedure retains only the Arizona portion of the WECC. The capacitor scan results for single capacitor placement and multiple capacitor placement cases are presented. Problematic cases are identified in the form of 'forbidden response. The harmonic voltage impact of known sources of harmonics, mainly large scale HVDC sources, is also presented. Specific key results for the study indicated include: (1) The forbidden zones obtained as per the IEEE 519 standard indicates the bus 10 to be the most problematic bus. (2) The forbidden zones also indicate that switching values for the switched shunt capacitor (if used) at bus 3 should be

  7. 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…

  8. Episodic Memory Does Not Add Up: Verbatim-Gist Superposition Predicts Violations of the Additive Law of Probability

    PubMed Central

    Brainerd, C. J.; Wang, Zheng; Reyna, Valerie. F.; Nakamura, K.

    2015-01-01

    Fuzzy-trace theory’s assumptions about memory representation are cognitive examples of the familiar superposition property of physical quantum systems. When those assumptions are implemented in a formal quantum model (QEMc), they predict that episodic memory will violate the additive law of probability: If memory is tested for a partition of an item’s possible episodic states, the individual probabilities of remembering the item as belonging to each state must sum to more than 1. We detected this phenomenon using two standard designs, item false memory and source false memory. The quantum implementation of fuzzy-trace theory also predicts that violations of the additive law will vary in strength as a function of reliance on gist memory. That prediction, too, was confirmed via a series of manipulations (e.g., semantic relatedness, testing delay) that are thought to increase gist reliance. Surprisingly, an analysis of the underlying structure of violations of the additive law revealed that as a general rule, increases in remembering correct episodic states do not produce commensurate reductions in remembering incorrect states. PMID:26236091

  9. Predicting contamination by the fuel additive cerium oxide engineered nanoparticles within the United Kingdom and the associated risks.

    PubMed

    Johnson, Andrew C; Park, Barry

    2012-11-01

    As a fuel additive, cerium oxide nanoparticles may become widely dispersed throughout the environment. Commercial information from the United Kingdom (UK) on the use of cerium oxide nanoparticles was used to perform a modeling and risk assessment exercise. Discharge from exhausts took into account the likely removal by filters fitted to these vehicles. For predicting current soil exposure, scenarios were examined, ranging from dispersion occurring across the entire UK landmass to only within the urban area to only 20 m on either side of road networks. For soils, the highest predicted contamination level was 0.016 mg/kg within 20 m of a road following seven years of continuous deposition. This value would represent 0.027% of reported natural background cerium. If usage were to double for five more years, levels would not be expected to exceed 0.04 mg/kg. River water contamination considered direct aerial deposition and indirect contamination via runoff in the water and entrained soil sediment, with the highest level of 0.02 ng/L predicted. The highest predicted water concentration of 300 ng/L was associated with water draining from a road surface, assuming a restricted deposition spread. These predictions are well below most toxicological levels of concern.

  10. 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

  11. 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.

  12. Synchrophasor-Assisted Prediction of Stability/Instability of a Power System

    NASA Astrophysics Data System (ADS)

    Saha Roy, Biman Kumar; Sinha, Avinash Kumar; Pradhan, Ashok Kumar

    2013-05-01

    This paper presents a technique for real-time prediction of stability/instability of a power system based on synchrophasor measurements obtained from phasor measurement units (PMUs) at generator buses. For stability assessment the technique makes use of system severity indices developed using bus voltage magnitude obtained from PMUs and generator electrical power. Generator power is computed using system information and PMU information like voltage and current phasors obtained from PMU. System stability/instability is predicted when the indices exceeds a threshold value. A case study is carried out on New England 10-generator, 39-bus system to validate the performance of the technique.

  13. 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

  14. Nonlinear recurrent neural network predictive control for energy distribution of a fuel cell powered robot.

    PubMed

    Chen, Qihong; Long, Rong; Quan, Shuhai; Zhang, Liyan

    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.

  15. 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

  16. Emotional intimacy power predicts different sexual experiences for men and women.

    PubMed

    Edwards, Gaynor L; Barber, Bonnie L; Dziurawiec, Suzanne

    2014-01-01

    Those who are more emotionally invested in relationships have less power than their partners. Furthermore, less powerful individuals may attempt to equalize power imbalances by offering rewards to their partner and using sex and condom use as exchange resources. Australian young adults reported their condom use and pressured sex experiences in both romantic (n = 708) and casual (n = 118) relationships. Results showed that greater power (lower relative emotional investment) predicted more condom use among those wanting to use condoms. In casual relationships, an interaction with gender showed that women in particular used condoms more when they had more power. Power also interacted with gender for pressured sex and, unexpectedly, men who had more power experienced more pressured sex. The possibility that condom use and pressured sex have different meanings for men and women is explored.

  17. 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…

  18. 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.

  19. Outsmarting cancer: the power of hybrid genomic/proteomic biomarkers to predict drug response.

    PubMed

    Rexer, Brent N; Arteaga, Carlos L

    2014-01-01

    A recent study by Niepel and colleagues describes a novel approach to predicting response to targeted anti-cancer therapies. The authors used biochemical profiling of signaling activity in basal and ligand-stimulated states for a panel of receptor and intracellular kinases to develop predictive models of drug sensitivity. In some cases, the response to ligand stimulation predicted drug response better than did target abundance or genomic alterations in the targeted pathway. Furthermore, combining biochemical profiles with genomic information was better at predicting drug response. This work suggests that incorporating biochemical signaling profiles with genomic alterations should provide powerful predictors of response to molecularly targeted therapies.

  20. 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

  1. 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.

  2. Contributions of the Stochastic Shape Wake Model to Predictions of Aerodynamic Loads and Power under Single Wake Conditions

    NASA Astrophysics Data System (ADS)

    Doubrawa, P.; Barthelmie, R. J.; Wang, H.; Churchfield, M. J.

    2016-09-01

    The contribution of wake meandering and shape asymmetry to load and power estimates is quantified by comparing aeroelastic simulations initialized with different inflow conditions: an axisymmetric base wake, an unsteady stochastic shape wake, and a large-eddy simulation with rotating actuator-line turbine representation. Time series of blade-root and tower base bending moments are analyzed. We find that meandering has a large contribution to the fluctuation of the loads. Moreover, considering the wake edge intermittence via the stochastic shape model improves the simulation of load and power fluctuations and of the fatigue damage equivalent loads. These results indicate that the stochastic shape wake simulator is a valuable addition to simplified wake models when seeking to obtain higher-fidelity computationally inexpensive predictions of loads and power.

  3. 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

  4. Hurricane destructive power predictions based on historical storm and sea surface temperature data.

    PubMed

    Bogen, Kenneth T; Jones, Edwin D; Fischer, Larry E

    2007-12-01

    additional model was developed that predicts PDI statistics conditional on APDI. These PDI and APDI models can be used to estimate upper bounds on indices of hurricane power likely to be realized over the next century, under divergent assumptions regarding SST influence.

  5. Making oxidation potentials predictable: coordination of additives applied to the electronic fine tuning of an iron(II) complex.

    PubMed

    Haslinger, Stefan; Kück, Jens W; Hahn, Eva M; Cokoja, Mirza; Pöthig, Alexander; Basset, Jean-Marie; Kühn, Fritz E

    2014-11-01

    This work examines the impact of axially coordinating additives on the electronic structure of a bioinspired octahedral low-spin iron(II) N-heterocyclic carbene (Fe-NHC) complex. Bearing two labile trans-acetonitrile ligands, the Fe-NHC complex, which is also an excellent oxidation catalyst, is prone to axial ligand exchange. Phosphine- and pyridine-based additives are used for substitution of the acetonitrile ligands. On the basis of the resulting defined complexes, predictability of the oxidation potentials is demonstrated, based on a correlation between cyclic voltammetry experiments and density functional theory calculated molecular orbital energies. Fundamental insights into changes of the electronic properties upon axial ligand exchange and the impact on related attributes will finally lead to target-oriented manipulation of the electronic properties and consequently to the effective tuning of the reactivity of bioinspired systems.

  6. 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.

  7. 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

  8. EXAMINING PLANNED U.S. POWER PLANT CAPACITY ADDITIONS IN THE CONTEXT OF CLIMATE CHANGE

    SciTech Connect

    Dooley, James J.; Dahowski, Robert T.; Gale, J.; Kaya, Y.

    2003-01-01

    This paper seeks to assess the degree to which the 471 planned fossil fired power plants announced to be built within the next decade in the continental U.S. are amenable to significant carbon dioxide emissions mitigation via carbon dioxide capture and disposal in geologic reservoirs. The combined generating capacity of these 471 planned plants is 320 GW. In particular, we seek to assess the looming ''carbon liability'' (i.e., the nearly 1 billion tons of CO2 these plants are likely to emit annually) that these power plants represent for their owners and for the nation as the U.S. begins to address climate change. Significant emission reductions will likely be brought about through the use of advanced technologies such as carbon capture and disposal. We find that less than half of these plants are located in the immediate vicinity of potentially suitable geologic carbon dioxide disposal reservoirs. The authors discuss the implications of this potential carbon liability that these plants may come to represent.

  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. 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.

  11. 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.

  12. Prediction of Period-Doubling Bifurcation Based on Dynamic Recognition and Its Application to Power Systems

    NASA Astrophysics Data System (ADS)

    Chen, Danfeng; Wang, Cong

    In this paper, a bifurcation prediction approach is proposed based on dynamic recognition and further applied to predict the period-doubling bifurcation (PDB) of power systems. Firstly, modeling of the internal dynamics of nonlinear systems is obtained through deterministic learning (DL), and the modeling results are applied for constructing the dynamic training pattern database. Specifically, training patterns are chosen according to the hierarchical structured knowledge representation based on the qualitative property of dynamical systems, which is capable of arranging the dynamical models into a specific order in the pattern database. Then, a dynamic recognition-based bifurcation prediction approach is suggested. As a result, perturbations implying PDB on the testing patterns can be predicted through the minimum dynamic error between the training patterns and testing patterns by recalling the knowledge restored in the pattern database. Finally, the second-order single-machine to infinite bus power system model is introduced to check the effectiveness of this prediction approach, which implies PDB under small periodic parameter perturbations. The key point that determines the prediction effect mainly lies in two methods: (1) accurate approximation of the unknown system dynamics through DL guarantees the feasibility of the prediction process; (2) the qualitative property of PDB and the generalization ability of DL algorithm ensure the validity of the selected training patterns. Simulations are included to illustrate the effectiveness of the proposed approach.

  13. [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

  14. 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…

  15. 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…

  16. 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.

  17. 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)

  18. 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…

  19. 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…

  20. 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…

  1. Fourier, Gegenbauer and Jacobi Expansions for a Power-Law Fundamental Solution of the Polyharmonic Equation and Polyspherical Addition Theorems

    NASA Astrophysics Data System (ADS)

    Cohl, Howard S.

    2013-06-01

    We develop complex Jacobi, Gegenbauer and Chebyshev polynomial expansions for the kernels associated with power-law fundamental solutions of the polyharmonic equation on d-dimensional Euclidean space. From these series representations we derive Fourier expansions in certain rotationally-invariant coordinate systems and Gegenbauer polynomial expansions in Vilenkin's polyspherical coordinates. We compare both of these expansions to generate addition theorems for the azimuthal Fourier coefficients.

  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. 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

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

    PubMed

    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.

  5. 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

  6. 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

  7. Is it really self-control? Examining the predictive power of the delay of gratification task.

    PubMed

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

    2013-07-01

    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.

  8. 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.

  9. 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.

  10. Ride-Through Capability Predictions for Wind Power Plants in the ERCOT Network: Preprint

    SciTech Connect

    Muljadi, E.; Butterfield, C. P.; Conto, J.; Donohoo, K.

    2005-01-01

    Utility system operators and engineers now want a better understanding of the impacts of large wind farms on grid stability before the farms are interconnected to the grid. Utilities need wind farm electrical models and methods of analysis that will help them analyze potential problems of grid stability. Without the necessary tools and knowledge of the behavior of large wind power plants, utilities are reluctant to integrate more wind power into the grid. The dynamic models used in this paper were developed by Power Technologies Inc. (PTI), under subcontract from ERCOT. A three-phase fault on important buses will be tested, and the potential impact on wind farms will be investigated. Two methods, dynamic analysis and steady state analysis (Zbus prediction), will be used to predict the low voltage ride through capability of the wind farms. Comparison between the two methods will be presented.

  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. 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.

  13. 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

  14. 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

  15. 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.

  16. 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

  17. 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

  18. 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

  19. 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.

  20. 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

  1. Can the Maximum Power Principle predict Effective Conductivities of a Confined Aquifer? A Lab Experiment

    NASA Astrophysics Data System (ADS)

    Westhoff, M.; Erpicum, S.; Archambeau, P.; Pirotton, M.; Zehe, E.; Dewals, B.

    2015-12-01

    Power can be performed by a system driven by a potential difference. From a given potential difference, the power that can be subtracted is constraint by the Carnot limit, which follows from the first and second laws of thermodynamics. If the system is such that the flux producing power (with power being the flux times its driving potential difference) also influences the potential difference, a maximum in power can be obtained as a result of the trade-off between the flux and the potential difference. This is referred to as the maximum power principle. It has already been shown that the atmosphere operates close to this maximum power limit when it comes to heat transport from the Equator to the poles, or vertically, from the surface to the atmospheric boundary layer. To reach this state of maximum power, the effective thermal conductivity of the atmosphere is adapted by the creation of convection cells. The aim of this study is to test if the soil's effective hydraulic conductivity also adapts in such a way that it produces maximum power. However, the soil's hydraulic conductivity adapts differently; for example by the creation of preferential flow paths. Here, this process is simulated in a lab experiment, which focuses on preferential flow paths created by piping. In the lab, we created a hydrological analogue to the atmospheric model dealing with heat transport between Equator and poles, with the aim to test if the effective hydraulic conductivity of the sand bed can be predicted with the maximum power principle. The experimental setup consists of two freely draining reservoir 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. The results will indicate whether the maximum power principle does apply for groundwater flow and how it should be applied. Because of the different way of adaptation of flow conductivity, the results differ from that of the

  2. 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

  3. 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

  4. A Bayesian Prediction Framework of Weather Based Power Line Damages in the Northeast

    NASA Astrophysics Data System (ADS)

    frediani, M.; Anagnostou, E. N.; Wanik, D.; Scerbo, D.

    2012-12-01

    This study aims to evaluate the predictability of damages to overhead power distribution lines from severe weather events in the New England area. During storms, trees and branches can come down and interact with power lines that results in significant interruptions to electricity distribution, causing major interruptions to residents and monetary losses to the utility company. In Connecticut, a densely forested state, severe winds and precipitation (in the form of rain and snow) from storms are key weather factors that challenge the power grid infrastructure vulnerability. Evaluating the local predictability of these impacts may aid local power utilities with crew allocation and preparedness during an event. A probabilistic approach to damage prediction caused by trees subjected to severe weather is being investigated in the region. This study specifically, explores the feasibility of applying Bayesian inversion technique to weather parameters by developing a damage decision tree composed of various meteorological and static parameters, like wind gust, precipitation (rain and snow accumulation and rates), high canopy forest density and tree trimming history for the power distribution lines. The resulting decision tree can be used as a Bayesian inversion database to predict the probability distribution of damages given a storm forecast. The Bayesian database is based on a historical data source provided by The Connecticut Light & Power Company (Connecticut's primary power utility) containing geographical information of trouble spots caused by thunderstorm and winter/snow-storm events; power line specifications and trimming history; and high-resolution model analysis of those storms. The analysis is based on a 2-sqkm model grid cropped over the state of Connecticut comprising a database of 3,307 pixels per storm. Each storm pixel is flagged to contain power line damages or no-damages. A total of 50 storm simulations is used to build the database. Pairs of

  5. Numerical predictions versus experimental findings on the power-harvesting output of a NiMnGa alloy

    NASA Astrophysics Data System (ADS)

    Nelson, Isaac; Dikes, Jason; Feigenbaum, Heidi; Ciocanel, Constantin

    2014-03-01

    Magnetic shape memory alloys (MSMAs) can display up to 10% recoverable strain in response to the application of a magnetic field or compressive mechanical stress. The amount of recoverable strain depends on the amount and direction of the applied stress and magnetic field as well as manufacturing, chemical composition, and training of the material. Due to their relatively large strains and fast response, MSMAs are suitable for a wide range of applications, including power harvesting, sensing, and actuation. The response of MSMAs is primarily driven by the reorientation of martensite variants. Power harvesting is possible due to this reorientation process and the accompanying change in material's magnetization, which can be changed into an electric potential/voltage using a pick-up coil placed around (or on the side of) the specimen. The magnitude of the output voltage depends on the number of turns of the pick-up coil, the amplitude of the reorientation strain, the magnitude and direction of the biased magnetic field, and the frequency at which the reorientation occurs. This paper focuses on the ability of a two dimensional constitutive model, developed by the group to capture the magnetomechanical response of MSMAs under general two dimensional loading conditions, to predict the power harvesting output of a Ni2MnGa specimen. Comparison between model predictions of voltage output and experimental measurements of the same indicate that, while the model is able to replicate the stress-strain response of the material during power harvesting, it is unable to accurately predict the magnitude of the experimentally measured voltage output. This indicates that additional features still need to be included in the model to better capture the change in magnetization that occurs during variant reorientation.

  6. 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

  7. 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

  8. 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.

  9. 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

  10. 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.

  11. 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

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. Battery available power prediction of hybrid electric vehicle based on improved Dynamic Matrix Control algorithms

    NASA Astrophysics Data System (ADS)

    Wang, Limei; Cheng, Yong; Zou, Ju

    2014-09-01

    The core technology to any hybrid engine vehicle (HEV) is the design of energy management strategy (EMS). To develop a reasonable EMS, it is necessary to monitor the state of capacity, state of health and instantaneous available power of battery packs. A new method that linearizes RC equivalent circuit model and predicts battery available power according to original Dynamic Matrix Control algorithm is proposed. To verify the validity of the new algorithm, a bench test with lithium-ion battery cell and a HEV test with lithium-ion battery packs are carried out. The bench test results indicate that a single RC block equivalent circuit model could be used to describe the dynamic and the steady state characteristics of a battery under testing conditions. However, lacking of long time constant of RC modules, there is a sample deviation in the open-circuit voltage identified and that measured. The HEV testing results show that the battery voltage predicted is in good agreement with that measured, the maximum difference is within 3.7%. Fixing the time constant to a numeric value, satisfactory results can still be achieved. After setting a battery discharge cut-off voltage, the instantaneous available power of the battery can be predicted.

  18. 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.

  19. Bayesian predictive power: choice of prior and some recommendations for its use as probability of success in drug development.

    PubMed

    Rufibach, Kaspar; Burger, Hans Ulrich; Abt, Markus

    2016-09-01

    Bayesian predictive power, the expectation of the power function with respect to a prior distribution for the true underlying effect size, is routinely used in drug development to quantify the probability of success of a clinical trial. Choosing the prior is crucial for the properties and interpretability of Bayesian predictive power. We review recommendations on the choice of prior for Bayesian predictive power and explore its features as a function of the prior. The density of power values induced by a given prior is derived analytically and its shape characterized. We find that for a typical clinical trial scenario, this density has a u-shape very similar, but not equal, to a β-distribution. Alternative priors are discussed, and practical recommendations to assess the sensitivity of Bayesian predictive power to its input parameters are provided. Copyright © 2016 John Wiley & Sons, Ltd.

  20. 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

  1. Additional Value of Transluminal Attenuation Gradient in CT Angiography to Predict Hemodynamic Significance of Coronary Artery Stenosis

    PubMed Central

    Stuijfzand, Wynand J.; Danad, Ibrahim; Raijmakers, Pieter G.; Marcu, C. Bogdan; Heymans, Martijn W.; van Kuijk, Cornelis C.; van Rossum, Albert C.; Nieman, Koen; Min, James K.; Leipsic, Jonathon; van Royen, Niels; Knaapen, Paul

    2015-01-01

    OBJECTIVES The current study evaluates the incremental value of transluminal attenuation gradient (TAG), TAG with corrected contrast opacification (CCO), and TAG with exclusion of calcified coronary segments (ExC) over coronary computed tomography angiogram (CTA) alone using fractional flow reserve (FFR) as the gold standard. BACKGROUND TAG is defined as the contrast opacification gradient along the length of a coronary artery on a coronary CTA. Preliminary data suggest that TAG provides additional functional information. Interpretation of TAG is hampered by multiple heartbeat acquisition algorithms and coronary calcifications. Two correction models have been proposed based on either dephasing of contrast delivery by relating coronary density to corresponding descending aortic opacification (TAG-CCO) or excluding calcified coronary segments (TAG-ExC). METHODS Eighty-five patients with intermediate probability of coronary artery disease were prospectively included. All patients underwent step-and-shoot 256-slice coronary CTA. TAG, TAG-CCO, and TAG-ExC analyses were performed followed by invasive coronary angiography in conjunction with FFR measurements of all major coronary branches. RESULTS Thirty-four patients (40%) were diagnosed with hemodynamically-significant coronary artery disease (i.e., FFR ≤0.80). On a per-vessel basis (n = 253), 59 lesions (23%) were graded as hemodynamically significant, and the diagnostic accuracy of coronary CTA (diameter stenosis ≥50%) was 95%, 75%, 98%, and 54% for sensitivity, specificity, negative predictive value, and positive predictive value, respectively. TAG and TAG-ExC did not discriminate between vessels with or without hemodynamically significant lesions (−13.5 ± 17.1 HU [Hounsfield units] × 10 mm−1 vs. −11.6 ± 13.3 HU × 10 mm−1, p = 0.36; and 13.1 ± 15.9 HU × 10 mm−1 vs. −11.4 ± 11.7 HU × 10 mm−1, p = 0.77, respectively). TAG-CCO was lower in vessels with a hemodynamically-significant lesion (−0

  2. 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.

  3. A Discussion on Prediction of Wind Conditions and Power Generation with the Weibull Distribution

    NASA Astrophysics Data System (ADS)

    Saito, Sumio; Sato, Kenichi; Sekizuka, Satoshi

    Assessment of profitability, based on the accurate measurement of the frequency distribution of wind speed over a certain period and the prediction of power generation under measured conditions, is normally a centrally important consideration for the installation of wind turbines. The frequency distribution of wind speed is evaluated, in general, using the Weibull distribution. In order to predict the frequency distribution from the average wind speed, a formula based on the Rayleigh distribution is often used, in which a shape parameter equal to 2 is assumed. The shape parameter is also used with the Weibull distribution; however, its effect on calculation of wind conditions and wind power has not been sufficiently clarified. This study reports on the evaluation of wind conditions and wind power generation as they are affected by the change of the shape parameter in the Weibull distribution with regard to two wind turbine generator systems that have the same nominal rated power, but different control methods. It further discusses the effect of the shape parameter of prototype wind turbines at a site with the measured wind condition data.

  4. 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

  5. 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

  6. 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.

  7. Power and metabolic scope of bird flight: a phylogenetic analysis of biomechanical predictions.

    PubMed

    Hedenström, Anders

    2008-07-01

    For flying animals aerodynamic theory predicts that mechanical power required to fly scales as P proportional, variant m (7/6) in a series of isometric birds, and that the flight metabolic scope (P/BMR; BMR is basal metabolic rate) scales as P (scope) proportional, variant m (5/12). I tested these predictions by using phylogenetic independent contrasts from a set of 20 bird species, where flight metabolic rate was measured during laboratory conditions (mainly in wind tunnels). The body mass scaling exponent for P was 0.90, significantly lower than the predicted 7/6. This is partially due to the fact that real birds show an allometric scaling of wing span, which reduces flight cost. P (scope) was estimated using direct measurements of BMR in combination with allometric equations. The body mass scaling of P (scope) ranged between 0.31 and 0.51 for three data sets, respectively, and none differed significantly from the prediction of 5/12. Body mass scaling exponents of P (scope) differed significantly from 0 in all cases, and so P (scope) showed a positive body mass scaling in birds in accordance with the prediction.

  8. 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.

  9. 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.

  10. 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.

  11. 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

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

    NASA Astrophysics Data System (ADS)

    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.

  13. An improved BEM model for the power curve prediction of stall-regulated wind turbines

    NASA Astrophysics Data System (ADS)

    Martínez, Jaime; Bernabini, Luca; Probst, Oliver; Rodríguez, Ciro

    2005-10-01

    Blade element momentum (BEM) theory is the standard computational technique for the prediction of power curves of wind turbines; it is based on the two-dimensional aerodynamic properties of aerofoil blade elements and some corrections accounting for three-dimensional wing aerodynamics. Although most BEM models yield acceptable results for low-wind and pitch-controlled regimes where the local angles of attack are small, no generally accepted model exists up to date that consistently predicts the power curve in the stall regime for a variety of blade properties and operating conditions. In this article we present a modified BEM model which satisfactorily reproduces the power curves of four experimental wind turbines reported in the literature, using no free fit parameters. Since these four experimental cases comprehend a great variety of conditions (wind tunnel vs field experiments, different air densities) and blade parameters (no twist and no taper, no taper but twist, both twist and taper, different aerofoil families), it is believed that our model represents a useful working tool for the aerodynamic design of stall-regulated wind turbines. Copyright

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. Method for predicting junction temperature distribution in a high-power laser diode bar.

    PubMed

    Kim, Dae-Suk; Holloway, Caleb; Han, Bongtae; Bar-Cohen, Avram

    2016-09-20

    A hybrid experimental/numerical method is proposed for predicting the junction temperature distribution in a high-power laser diode (LD) bar with multiple emitters. A commercial water-cooled LD bar with multiple emitters is used to illustrate and validate the proposed method. A unique experimental setup is developed and implemented first to measure the average junction temperatures of the LD bar emitters. After measuring the heat dissipation of the LD bar, the effective heat transfer coefficient of the cooling system is determined inversely from the numerical simulation using the measured average junction temperature and the heat dissipation. The characterized heat dissipation and effective heat transfer coefficient are used to predict the junction temperature distribution over the LD bar numerically under high operating currents. The results are presented in conjunction with the wall-plug efficiency and the center wavelength shift. PMID:27661573

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. Robust regression and posterior predictive simulation increase power to detect early bursts of trait evolution.

    PubMed

    Slater, Graham J; Pennell, Matthew W

    2014-05-01

    A central prediction of much theory on adaptive radiations is that traits should evolve rapidly during the early stages of a clade's history and subsequently slowdown in rate as niches become saturated--a so-called "Early Burst." Although a common pattern in the fossil record, evidence for early bursts of trait evolution in phylogenetic comparative data has been equivocal at best. We show here that this may not necessarily be due to the absence of this pattern in nature. Rather, commonly used methods to infer its presence perform poorly when when the strength of the burst--the rate at which phenotypic evolution declines--is small, and when some morphological convergence is present within the clade. We present two modifications to existing comparative methods that allow greater power to detect early bursts in simulated datasets. First, we develop posterior predictive simulation approaches and show that they outperform maximum likelihood approaches at identifying early bursts at moderate strength. Second, we use a robust regression procedure that allows for the identification and down-weighting of convergent taxa, leading to moderate increases in method performance. We demonstrate the utility and power of these approach by investigating the evolution of body size in cetaceans. Model fitting using maximum likelihood is equivocal with regards the mode of cetacean body size evolution. However, posterior predictive simulation combined with a robust node height test return low support for Brownian motion or rate shift models, but not the early burst model. While the jury is still out on whether early bursts are actually common in nature, our approach will hopefully facilitate more robust testing of this hypothesis. We advocate the adoption of similar posterior predictive approaches to improve the fit and to assess the adequacy of macroevolutionary models in general.

  5. 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

  6. 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.

  7. 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)

  8. 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...

  9. 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.

  10. 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.

  11. 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

  12. Comprehensive lipid analysis: a powerful metanomic tool for predictive and diagnostic medicine.

    PubMed

    Watkins, S M

    2000-09-01

    The power and accuracy of predictive diagnostics stand to improve dramatically as a result of lipid metanomics. The high definition of data obtained with this approach allows multiple rather than single metabolites to be used in markers for a group. Since as many as 40 fatty acids are quantified from each lipid class, and up to 15 lipid classes can be quantified easily, more than 600 individual lipid metabolites can be measured routinely for each sample. Because these analyses are comprehensive, only the most appropriate and unique metabolites are selected for their predictive value. Thus, comprehensive lipid analysis promises to greatly improve predictive diagnostics for phenotypes that directly or peripherally involve lipids. A broader and possibly more exciting aspect of this technology is the generation of metabolic profiles that are not simply markers for disease, but metabolic maps that can be used to identify specific genes or activities that cause or influence the disease state. Metanomics is, in essence, functional genomics from metabolite analysis. By defining the metabolic basis for phenotype, researchers and clinicians will have an extraordinary opportunity to understand and treat disease. Much in the same way that gene chips allow researchers to observe the complex expression response to a stimulus, metanomics will enable researchers to observe the complex metabolic interplay responsible for defining phenotype. By extending this approach beyond the observation of individual dysregulations, medicine will begin to profile not single diseases, but health. As health is the proper balance of all vital metabolic pathways, comprehensive or metanomic analysis lends itself very well to identifying the metabolite distributions necessary for optimum health. Comprehensive and quantitative analysis of lipids would provide this degree of diagnostic power to researchers and clinicians interested in mining metabolic profiles for biological meaning.

  13. Ambulatory wireless sensor network power management using constrained explicit generalised predictive control

    NASA Astrophysics Data System (ADS)

    Witheephanich, K.; Escaño, J. M.; Hayes, M. J.

    2011-08-01

    This work considers the problem of controlling transmit power within a wireless sensor network (WSN), where the practical constraints typically posed by an ambulatory healthcare setting are explicitly taken into account, as a constrained received signal strength indicator (RSSI) tracking control problem. The problem is formulated using an explicit generalised predictive control (GPC) strategy for dynamic transmission power control that ensures a balance between energy consumption and quality of service (QoS) through the creation of a stable floor on information throughput. Optimal power assignment is achieved by an explicit solution of the constrained GPC problem that is computed off-line using a multi-parametric quadratic program (mpQP). The solution is shown to be a piecewise-affine function. The new design is demonstrated to be practically feasible via a resource-constrained, fully IEEE 802.15.4 compliant, Moteiv's Tmote Sky sensor node platform. Design utility is benchmarked experimentally using a representative selection of scaled ambulatory scenarios.

  14. 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.

  15. sEMG wavelet-based indices predicts muscle power loss during dynamic contractions.

    PubMed

    González-Izal, M; Rodríguez-Carreño, I; Malanda, A; Mallor-Giménez, F; Navarro-Amézqueta, I; Gorostiaga, E M; Izquierdo, M

    2010-12-01

    The purpose of this study was to investigate the sensitivity of new surface electromyography (sEMG) indices based on the discrete wavelet transform to estimate acute exercise-induced changes on muscle power output during a dynamic fatiguing protocol. Fifteen trained subjects performed five sets consisting of 10 leg press, with 2 min rest between sets. sEMG was recorded from vastus medialis (VM) muscle. Several surface electromyographic parameters were computed. These were: mean rectified voltage (MRV), median spectral frequency (F(med)), Dimitrov spectral index of muscle fatigue (FI(nsm5)), as well as five other parameters obtained from the stationary wavelet transform (SWT) as ratios between different scales. The new wavelet indices showed better accuracy to map changes in muscle power output during the fatiguing protocol. Moreover, the new wavelet indices as a single parameter predictor accounted for 46.6% of the performance variance of changes in muscle power and the log-FI(nsm5) and MRV as a two-factor combination predictor accounted for 49.8%. On the other hand, the new wavelet indices proposed, showed the highest robustness in presence of additive white Gaussian noise for different signal to noise ratios (SNRs). The sEMG wavelet indices proposed may be a useful tool to map changes in muscle power output during dynamic high-loading fatiguing task.

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. 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

  3. 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

    2016-08-10

    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.

  4. 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

  5. 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

  6. 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.

  7. 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.

  8. 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

  9. 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

  10. 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.

  11. 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.

  12. Model Predictive Wind Turbine Control with Move-Blocking Strategy for Load Alleviation and Power Leveling

    NASA Astrophysics Data System (ADS)

    Jassmann, U.; Dickler, S.; Zierath, J.; Hakenberg, M.; Abel, D.

    2016-09-01

    This contribution presents a Model Predictive Controller (MPC) with moveblocking strategy for combined power leveling and load alleviation in wind turbine operation with a focus on extreme loads. The controller is designed for a 3 MW wind turbine developed by W2E Wind to Energy GmbH and compared to a baseline controller, using a classic control scheme, which currently operates the wind turbine. All simulations are carried out with a detailed multibody simulation turbine model implemented in alaska/Wind. The performance of the two different controllers is compared using a 50-year Extreme Operation Gust event, since it is one of the main design drivers for the wind turbine considered in this work. The implemented MPC is able to level electrical output power and reduce mechanical loads at the same time. Without de-rating the achieved control results, a move-blocking strategy is utilized and allowed to reduce the computational burden of the MPC by more than 50% compared to a baseline MPC implementation. This even allows to run the MPC on a state of the art Programmable Logic Controller.

  13. Nonlinear predictive control for durability enhancement and efficiency improvement in a fuel cell power system

    NASA Astrophysics Data System (ADS)

    Luna, Julio; Jemei, Samir; Yousfi-Steiner, Nadia; Husar, Attila; Serra, Maria; Hissel, Daniel

    2016-10-01

    In this work, a nonlinear model predictive control (NMPC) strategy is proposed to improve the efficiency and enhance the durability of a proton exchange membrane fuel cell (PEMFC) power system. The PEMFC controller is based on a distributed parameters model that describes the nonlinear dynamics of the system, considering spatial variations along the gas channels. Parasitic power from different system auxiliaries is considered, including the main parasitic losses which are those of the compressor. A nonlinear observer is implemented, based on the discretised model of the PEMFC, to estimate the internal states. This information is included in the cost function of the controller to enhance the durability of the system by means of avoiding local starvation and inappropriate water vapour concentrations. Simulation results are presented to show the performance of the proposed controller over a given case study in an automotive application (New European Driving Cycle). With the aim of representing the most relevant phenomena that affects the PEMFC voltage, the simulation model includes a two-phase water model and the effects of liquid water on the catalyst active area. The control model is a simplified version that does not consider two-phase water dynamics.

  14. Biochemical systems theory: increasing predictive power by using second-order derivatives measurements.

    PubMed

    Cascante, M; Sorribas, A; Franco, R; Canela, E I

    1991-04-21

    Models based on the power-law formalism provide a useful tool for analyzing metabolic systems. Within this methodology, the S-system variant furnishes the best strategy. In this paper we explore an extension of this formalism by considering second-order derivative terms of the Taylor series which the power-law is based upon. Results show that the S-system equations which include second-order Taylor coefficients give better accuracy in predicting the response of the system to a perturbation. Hence, models based on this new approach could provide a useful tool for quantitative purposes if one is able to measure the required derivatives experimentally. In particular we show the utility of this approach when it comes to discriminating between two mechanisms that are equivalent in the S-system a representation based on first-order coefficients. However, the loss of analytical tractability is a serious disadvantage for using this approach as a general tool for studying metabolic systems.

  15. Predictions of Taylor's power law, density dependence and pink noise from a neutrally modeled time series.

    PubMed

    Keil, Petr; Herben, Tomás; Rosindell, James; Storch, David

    2010-07-01

    There has recently been increasing interest in neutral models of biodiversity and their ability to reproduce the patterns observed in nature, such as species abundance distributions. Here we investigate the ability of a neutral model to predict phenomena observed in single-population time series, a study complementary to most existing work that concentrates on snapshots in time of the whole community. We consider tests for density dependence, the dominant frequencies of population fluctuation (spectral density) and a relationship between the mean and variance of a fluctuating population (Taylor's power law). We simulated an archipelago model of a set of interconnected local communities with variable mortality rate, migration rate, speciation rate, size of local community and number of local communities. Our spectral analysis showed 'pink noise': a departure from a standard random walk dynamics in favor of the higher frequency fluctuations which is partly consistent with empirical data. We detected density dependence in local community time series but not in metacommunity time series. The slope of the Taylor's power law in the model was similar to the slopes observed in natural populations, but the fit to the power law was worse. Our observations of pink noise and density dependence can be attributed to the presence of an upper limit to community sizes and to the effect of migration which distorts temporal autocorrelation in local time series. We conclude that some of the phenomena observed in natural time series can emerge from neutral processes, as a result of random zero-sum birth, death and migration. This suggests the neutral model would be a parsimonious null model for future studies of time series data.

  16. 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

  17. An Efficient Multi-Scale Simulation Architecture for the Prediction of Performance Metrics of Parts Fabricated Using Additive Manufacturing

    NASA Astrophysics Data System (ADS)

    Pal, Deepankar; Patil, Nachiket; Zeng, Kai; Teng, Chong; Stucker, Brent

    2015-09-01

    In this study, an overview of the computational tools developed in the area of metal-based additively manufactured (AM) to simulate the performance metrics along with their experimental validations will be presented. The performance metrics of the AM fabricated parts such as the inter- and intra-layer strengths could be characterized in terms of the melt pool dimensions, solidification times, cooling rates, granular microstructure, and phase morphologies along with defect distributions which are a function of the energy source, scan pattern(s), and the material(s). The four major areas of AM simulation included in this study are thermo-mechanical constitutive relationships during fabrication and in- service, the use of Euler angles for gaging static and dynamic strengths, the use of algorithms involving intelligent use of matrix algebra and homogenization extracting the spatiotemporal nature of these processes, a fast GPU architecture, and specific challenges targeted toward attaining a faster than real-time simulation efficiency and accuracy.

  18. Dose Addition Models Based on Biologically Relevant Reductions in Fetal Testosterone Accurately Predict Postnatal Reproductive Tract Alterations by a Phthalate Mixture in Rats.

    PubMed

    Howdeshell, Kembra L; Rider, Cynthia V; Wilson, Vickie S; Furr, Johnathan R; Lambright, Christy R; Gray, L Earl

    2015-12-01

    Challenges in cumulative risk assessment of anti-androgenic phthalate mixtures include a lack of data on all the individual phthalates and difficulty determining the biological relevance of reduction in fetal testosterone (T) on postnatal development. The objectives of the current study were 2-fold: (1) to test whether a mixture model of dose addition based on the fetal T production data of individual phthalates would predict the effects of a 5 phthalate mixture on androgen-sensitive postnatal male reproductive tract development, and (2) to determine the biological relevance of the reductions in fetal T to induce abnormal postnatal reproductive tract development using data from the mixture study. We administered a dose range of the mixture (60, 40, 20, 10, and 5% of the top dose used in the previous fetal T production study consisting of 300 mg/kg per chemical of benzyl butyl (BBP), di(n)butyl (DBP), diethyl hexyl phthalate (DEHP), di-isobutyl phthalate (DiBP), and 100 mg dipentyl (DPP) phthalate/kg; the individual phthalates were present in equipotent doses based on their ability to reduce fetal T production) via gavage to Sprague Dawley rat dams on GD8-postnatal day 3. We compared observed mixture responses to predictions of dose addition based on the previously published potencies of the individual phthalates to reduce fetal T production relative to a reference chemical and published postnatal data for the reference chemical (called DAref). In addition, we predicted DA (called DAall) and response addition (RA) based on logistic regression analysis of all 5 individual phthalates when complete data were available. DA ref and DA all accurately predicted the observed mixture effect for 11 of 14 endpoints. Furthermore, reproductive tract malformations were seen in 17-100% of F1 males when fetal T production was reduced by about 25-72%, respectively. PMID:26350170

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  20. Predictive Value of Class III D Cytological Diagnosis (Munich II, Low and Moderate Dysplasia) and Additional High-risk HPV Testing.

    PubMed

    Ziemke, P

    2012-07-01

    The validity of cytological diagnostic procedures for the detection of pre- and early cervical cancer stages is limited due to biological conditions, the uncertainty of cell sampling, and the subjective nature of microscopic assessment. Particularly in class III D cases (Munich II) this can lead to a stigmatization of patients and uncertainty with regard to further clinical follow-up and therapy. Prior to carrying out additional investigations such as high-risk HPV testing or the examination of biomarkers, the positive predictive values of patients with a class III D cytological diagnosis need to be assessed in routine practice. To this end, all relevant data from patients from our practice classed as class III D (pap smears) between 2002 and 2008 (n = 1190; 38.2 % histological diagnosis = therapeutic endpoint) and their current HPV status were recorded. Cytology, histology, persistence, age and follow-up were recorded. The database was used for comparative statistical analysis. Overall, the positive predictive value of conventional pap smear for CIN 2+ was calculated to be 32.3 % (mean follow-up: 39.7 months). The following values were calculated for high-risk HPV testing: sensitivity 94.8 %, specificity 39 %, positive predictive value 42.8 %, negative predictive value 94 %. The additional information obtained from high-risk HPV testing resulted in a significantly better positive predictive value only in patients older than 40 years. However, there was no evidence for an individual risk stratification approach which would reduce uncertainty in the management of III D patients.

  1. 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.

  2. 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…

  3. 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…

  4. 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…

  5. 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.

  6. 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.

  7. 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

  8. 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.

  9. 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.

  10. 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

  11. 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.

  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. 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.

  15. 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.

    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

  16. 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

  17. 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

  18. 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

  19. On-Board Prediction of Power Consumption in Automobile Active Suspension SYSTEMS—I: Predictor Design Issues

    NASA Astrophysics Data System (ADS)

    Ben Mrad, R.; Fassois, S. D.; Levitt, J. A.; Bachrach, B. I.

    1996-03-01

    On-board prediction of automobile active suspension power consumption is considered important in securing fast engine response and avoiding potential vehicle hesitation or surge. In this study the problem is considered within the context of a broad-bandwidth hydraulic active suspension design, with the following main objectives: (a) power consumption prediction feasibility assessment, (b) examination of predictor design options, and (c) achievable prediction accuracy assessment. In this part I the first two objectives are pursued based on a detailed, non-linear, mathematical system model. The power consumption signal is found to be non-stationary, but stationarily is shown to be possible to impose through a moving-average transformation. Predictor design options are then considered: first, the wheel vertical acceleration is shown to be ineffective as a prediction leading indicator; second, the relative merits of time/step-recursive and time-recursive predictor realizations are examined, and the latter are shown to be presently preferable from the point of view of computational complexity, error propagation, and predictor stability; third, indirect (standard) vs. direct predictor types are considered, and a direct predictor is developed based on a novel estimator characterised by features important for on-board implementation.

  20. Predicting acute and chronic effects of wood preservative products in Daphnia magna and Pseudokirchneriella subcapitata based on the concept of concentration addition.

    PubMed

    Coors, Anja; Weisbrod, Barbara; Schoknecht, Ute; Sacher, Frank; Kehrer, Anja

    2014-02-01

    The current European legislation requires that combined effects of the active substances and any substance of concern contained in biocidal products are taken into account in environmental risk assessment. The hypothesis whether the consideration of active substances together with all formulation additives that are labeled as presenting an environmental hazard is sufficient for a reliable environmental risk assessment was tested in the present study by investigating 3 wood preservative products. Relevant single substances in the products, some of their generic mixtures, the biocidal products themselves, and aqueous eluates prepared from the products (representing potential environmental mixtures) were tested for effects on algal growth and Daphnia acute immobilization as well as reproduction. Predictions for the products and the eluates were based on the concept of concentration addition and were mostly found to provide reliable or at least protective estimates for the observed acute and chronic toxicity of the mixtures. The mixture toxicity considerations also indicated that the toxicity of each product was dominated by just 1 of the components, and that assessments based only on the dominating substance would be similarly protective as a full-mixture risk assessment. Yet, there remained uncertainty in some cases that could be related to the toxicity of transformation products, the impact of unidentified formulation additives, or synergistic interaction between active substances and formulation additives.

  1. 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

  2. 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.

  3. Prediction of vertical PM2.5 concentrations alongside an elevated expressway by using the neural network hybrid model and generalized additive model

    NASA Astrophysics Data System (ADS)

    Gao, Ya; Wang, Zhanyong; Lu, Qing-Chang; Liu, Chao; Peng, Zhong-Ren; Yu, Yue

    2016-10-01

    A study on vertical variation of PM2.5 concentrations was carried out in this paper. Field measurements were conducted at eight different floor heights outside a building alongside a typical elevated expressway in downtown Shanghai, China. Results show that PM2.5 concentration decreases significantly with the increase of height from the 3rd to 7th floor or the 8th to 15th floor, and increases suddenly from the 7th to 8th floor which is the same height as the elevated expressway. A non-parametric test indicates that the data of PM2.5 concentration is statistically different under the 7th floor and above the 8th floor at the 5% significance level. To investigate the relationships between PM2.5 concentration and influencing factors, the Pearson correlation analysis was performed and the results indicate that both traffic and meteorological factors have crucial impacts on the variation of PM2.5 concentration, but there is a rather large variation in correlation coefficients under the 7th floor and above the 8th floor. Furthermore, the back propagation neural network based on principal component analysis (PCA-BPNN), as well as generalized additive model (GAM), was applied to predict the vertical PM2.5 concentration and examined with the field measurement dataset. Experimental results indicated that both models can obtain accurate predictions, while PCA-BPNN model provides more reliable and accurate predictions as it can reduce the complexity and eliminate data co-linearity. These findings reveal the vertical distribution of PM2.5 concentration and the potential of the proposed model to be applicable to predict the vertical trends of air pollution in similar situations.

  4. Computational prediction of tube erosion in coal fired power utility boilers

    SciTech Connect

    Lee, B.E.; Fletcher, C.A.J.; Behnia, M.

    1999-10-01

    Erosion of boiler tubes causes serious operational problems in many pulverized coal-fired utility boilers. A new erosion model has been developed in the present study for the prediction of boiler tube erosion. The Lagrangian approach is employed to predict the behavior of the particulate phase. The results of computational prediction of boiler tube erosion and the various parameters causing erosion are discussed in this paper. Comparison of the numerical predictions for a single tube erosion with experimental data shows very good agreement.

  5. Development of prediction models for radioactive caesium distribution within the 80-km radius of the Fukushima Daiichi nuclear power plant.

    PubMed

    Kinase, Sakae; Takahashi, Tomoyuki; Sato, Satoshi; Sakamoto, Ryuichi; Saito, Kimiaki

    2014-08-01

    Preliminary prediction models have been studied for the radioactive caesium distribution within the 80-km radius of the Fukushima Daiichi nuclear power plant. The models were represented by exponential functions using ecological half-life of radioactive caesium in the environment. The ecological half-lives were derived from the changes in ambient dose equivalent rates through vehicle-borne surveys. It was found that the ecological half-lives of radioactive caesium were not constant within the 80-km radius of the Fukushima Daiichi nuclear power plant. The ecological half-life of radioactive caesium in forest areas was found to be much larger than that in urban and water areas.

  6. 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.

  7. 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.

    2013-02-01

    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.

  8. First-order electroweak phase transition powered by additional F-term loop effects in an extended supersymmetric Higgs sector

    NASA Astrophysics Data System (ADS)

    Kanemura, Shinya; Senaha, Eibun; Shindou, Tetsuo

    2011-11-01

    We investigate the one-loop effect of new charged scalar bosons on the Higgs potential at finite temperatures in the supersymmetric standard model with four Higgs doublet chiral superfields as well as a pair of charged singlet chiral superfields. In this model, the mass of the lightest Higgs boson h is determined only by the D-term in the Higgs potential at the tree-level, while the triple Higgs boson coupling for hhh can receive a significant radiative correction due to nondecoupling one-loop contributions of the additional charged scalar bosons. We find that the same nondecoupling mechanism can also contribute to realize stronger first order electroweak phase transition than that in the minimal supersymmetric standard model, which is definitely required for a successful scenario of electroweak baryogenesis. Therefore, this model can be a new candidate for a model in which the baryon asymmetry of the Universe is explained at the electroweak scale.

  9. Body fat distribution in the Finnish population: environmental determinants and predictive power for cardiovascular risk factor levels.

    PubMed Central

    Marti, B; Tuomilehto, J; Salomaa, V; Kartovaara, L; Korhonen, H J; Pietinen, P

    1991-01-01

    STUDY OBJECTIVE--The aim was to examine (1) whether health habits are associated with body fat distribution, as measured by the waist/hip girth ratio, and (2) to what extent environmental factors, including anthropometric characteristics, explain the variability in levels of cardiovascular risk factors. DESIGN--The study was a population based cross sectional survey, conducted in the spring of 1987 as a part of an international research project on cardiovascular epidemiology. SETTING--The survey was conducted in three geographical areas of eastern and south western Finland. SUBJECTS--2526 men and 2756 women aged 25-64 years took part in the study, corresponding to a survey participation rate of 82%. MEASUREMENTS AND MAIN RESULTS--In men, waist/hip ratio showed stronger associations with exercise (Pearson's r = -0.24), resting heart rate (r = 0.10), alcohol consumption (r = 0.07), smoking (r = 0.05), and education (r = -0.23) than did body mass index. Jointly, exercise, resting heart rate, alcohol consumption, education, and age explained 18% of variance in male waist/hip ratio, but only 9% of variance in male body mass index. In women, environmental factors were more predictive for body mass index than for waist/hip ratio, with age and education being the strongest determinants. Waist/hip ratio and body mass index were approximately equally strong predictors of cardiovascular risk factor levels. The additional predictive power of waist/hip ratio over and above body mass index was tested in a hierarchical, stepwise regression. In this conservative type of analysis the increase in explained variance uniquely attributable to waist/hip ratio was 2-3% for female and 1-2% for male lipoprotein levels, and less than 0.5% for female and 0-2% for male blood pressure values. CONCLUSIONS--The distribution of abdominal obesity in Finland is significantly influenced by health habits and sociodemographic factors in both men and women. This in turn is obviously one reason for the

  10. 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…

  11. 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.

  12. Universal Inverse Power-Law Distribution for Fractal Fluctuations in Dynamical Systems: Applications for Predictability of Inter-Annual Variability of Indian and USA Region Rainfall

    NASA Astrophysics Data System (ADS)

    Selvam, A. M.

    2016-09-01

    Dynamical systems in nature exhibit self-similar fractal space-time fluctuations on all scales indicating long-range correlations and, therefore, the statistical normal distribution with implicit assumption of independence, fixed mean and standard deviation cannot be used for description and quantification of fractal data sets. The author has developed a general systems theory based on classical statistical physics for fractal fluctuations which predicts the following. (1) The fractal fluctuations signify an underlying eddy continuum, the larger eddies being the integrated mean of enclosed smaller-scale fluctuations. (2) The probability distribution of eddy amplitudes and the variance (square of eddy amplitude) spectrum of fractal fluctuations follow the universal Boltzmann inverse power law expressed as a function of the golden mean. (3) Fractal fluctuations are signatures of quantum-like chaos since the additive amplitudes of eddies when squared represent probability densities analogous to the sub-atomic dynamics of quantum systems such as the photon or electron. (4) The model predicted distribution is very close to statistical normal distribution for moderate events within two standard deviations from the mean but exhibits a fat long tail that are associated with hazardous extreme events. Continuous periodogram power spectral analyses of available GHCN annual total rainfall time series for the period 1900-2008 for Indian and USA stations show that the power spectra and the corresponding probability distributions follow model predicted universal inverse power law form signifying an eddy continuum structure underlying the observed inter-annual variability of rainfall. On a global scale, man-made greenhouse gas related atmospheric warming would result in intensification of natural climate variability, seen immediately in high frequency fluctuations such as QBO and ENSO and even shorter timescales. Model concepts and results of analyses are discussed with reference

  13. Harnessing the power of personality assessment: subjective assessment predicts behaviour in horses.

    PubMed

    Ijichi, Carrie; Collins, Lisa M; Creighton, Emma; Elwood, Robert W

    2013-06-01

    Objective assessment of animal personality is typically time consuming, requiring the repeated measure of behavioural responses. By contrast, subjective assessment of personality allows information to be collected quickly by experienced caregivers. However, subjective assessment must predict behaviour to be valid. Comparisons of subjective assessments and behaviour have been made but often with methodological weaknesses and thus, limited success. Here we test the validity of a subjective assessment against a battery of behaviour tests in 146 horses (Equus caballus). Our first aim was to determine if subjective personality assessment could predict behaviour during behaviour testing. We made specific a priori predictions for how subjectively measured personality should relate to behaviour testing. We found that Extroversion predicted time to complete a handling test and refusal behaviour during this test. It also predicted minimum distance to a novel object. Neuroticism predicted how reactive an individual was to a sudden visual stimulus but not how quickly it recovered from this. Agreeableness did not predict any behaviour during testing. There were several unpredicted correlations between subjective measures and behaviour tests which we explore further. Our second aim was to combine data from the subjective assessment and behaviour tests to gain a more comprehensive understanding of personality. We found that the combination of methods provides new insights into horse behaviour. Furthermore, our data are consistent with the idea of horses showing different coping styles, a novel finding for this species.

  14. 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.

  15. Enhanced computational prediction of polyethylene wear in hip joints by incorporating cross-shear and contact pressure in additional to load and sliding distance: effect of head diameter.

    PubMed

    Kang, Lu; Galvin, Alison L; Fisher, John; Jin, Zhongmin

    2009-05-11

    A new definition of the experimental wear factor was established and reported as a function of cross-shear motion and contact pressure using a multi-directional pin-on-plate wear testing machine for conventional polyethylene in the present study. An independent computational wear model was developed by incorporating the cross-shear motion and contact pressure-dependent wear factor into the Archard's law, in additional to load and sliding distance. The computational prediction of wear volume was directly compared with a simulator testing of a polyethylene hip joint with a 28 mm diameter. The effect of increasing the femoral head size was subsequently considered and was shown to increase wear, as a result of increased sliding distance and reduced contact pressure. PMID:19261286

  16. 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

  17. 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

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. 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

  6. Predictive power of the polygraph: can the "lie detector" really detect liars?

    PubMed

    Brett, A S; Phillips, M; Beary, J F

    1986-03-01

    Expanded use of the polygraph as a detector of lies has been proposed in the United States and the United Kingdom. The positive predictive value of the polygraph (ie, the proportion of positive test results that are true positives) was assessed, on the evidence of the best published data for the sensitivity and specificity of the device. In many screening or investigative situations, the predictive value would be poor; most of the positive results would be false positives. Consequently, truthful persons incriminated as liars by the polygraph would outnumber actual liars with a positive result on the test.

  7. 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.

  8. 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.

  9. 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

  10. On-Board Prediction of Power Consumption in Automobile Active Suspension SYSTEMS—II: Validation and Performance Evaluation

    NASA Astrophysics Data System (ADS)

    Ben Mrad, R.; Fassois, S. D.; Levitt, J. A.; Bachrach, B. I.

    1996-03-01

    The focus of this part of the paper is on validation and performance evaluation. The indirect (standard) and novel direct predictors or part I, which use time-recursive realisations and no leading indicators, are critically compared by using the non-linear active suspension system model. The results, constituting the first known comparison between indirect and direct schemes, show similar performance with a slight superiority of the former. Experimental validation is based on an especially developed active suspension vehicle. The power consumption non-stationarity is, in this case, shown to be of the homogeneous type, and completely "masking" the signal's second-order characteristics, which revealed only after the non-stationarity's effective removal. The analysis leads to two distinct types of indirect predictors: An explicit type, based on non-stationary integrated autoregressive moving average models, and an implicit type, based on stationary autoregressive moving average model. The explicit predictor is shown to be uniformly better than the implicit, although the difference is small for short prediction horizons. The experimental results indicate that accurate power consumption prediction is possible, with errors ranging from 2.22% for a prediction horizon of 0.156 s, to still less than 10% for horizons that are up to 0.470 s long, and about 25% for 1.563 s long horizons.

  11. 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.

  12. 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…

  13. 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…

  14. 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…

  15. Predicting First-Year Student Success in Learning Communities: The Power of Pre-College Variables

    ERIC Educational Resources Information Center

    Sperry, Rita A.

    2015-01-01

    The study used pre-college variables in the prediction of retention and probation status of first-year students in learning communities at a regional public university in South Texas. The correlational study employed multivariate analyses on data collected from the campus registrar about three consecutive cohorts (N = 4,215) of first-year…

  16. Prediction of Production Power for High-pressure Hydrogen by High-pressure Water Electrolysis

    NASA Astrophysics Data System (ADS)

    Kyakuno, Takahiro; Hattori, Kikuo; Ito, Kohei; Onda, Kazuo

    Recently the high attention for fuel cell electric vehicle (FCEV) is pushing to construct the hydrogen supplying station for FCEV in the world. The hydrogen pressure supplied at the current test station is intended to be high for increasing the FCEV’s driving distance. The water electrolysis can produce cleanly the hydrogen by utilizing the electricity from renewable energy without emitting CO2 to atmosphere, when it is compared to be the popular reforming process of fossil fuel in the industry. The power required for the high-pressure water electrolysis, where water is pumped up to high-pressure, may be smaller than the power for the atmospheric water electrolysis, where the produced atmospheric hydrogen is pumped up by compressor, since the compression power for water is much smaller than that for hydrogen gas. In this study the ideal water electrolysis voltage up to 70MPa and 523K is estimated referring to both the results by LeRoy et al up to 10MPa and 523K, and to the latest steam table. By using this high-pressure water electrolysis voltage, the power required for high-pressure hydrogen produced by the high-pressure water electrolysis method is estimated to be about 5% smaller than that by the atmospheric water electrolysis method, by assuming the compressor and pump efficiency of 50%.

  17. Prediction of production power for high-pressure hydrogen by high-pressure water electrolysis

    NASA Astrophysics Data System (ADS)

    Onda, Kazuo; Kyakuno, Takahiro; Hattori, Kikuo; Ito, Kohei

    Recent attention focused on fuel cell electric vehicles (FCEVs) has created demand for the construction of hydrogen supply stations for FCEVs throughout the world. The hydrogen pressure supplied at the supply stations is intentionally high to increase the FCEVs driving mileage. Water electrolysis can produce clean hydrogen by utilizing electricity from renewable energy without CO 2 emission to the atmosphere when compared with the industrial fossil fuel reforming process. The power required for high-pressure water electrolysis, wherein water is pumped up to a high-pressure, may be less than the power required for atmospheric water electrolysis, wherein the produced atmospheric hydrogen is pumped by a compressor, since the compression power for water is much less than that for hydrogen-gas. In this study, the ideal water electrolysis voltage of up to 70 MPa and 250 °C is estimated by referring to both the results of LeRoy et al. up to 10 MPa and 250 °C, and the latest steam tables. Using this high-pressure water electrolysis voltage, the power required to produce high-pressure hydrogen by high-pressure water electrolysis is estimated to be about 5% less than that required for atmospheric water electrolysis, assuming compressor and pump efficiencies of 50%.

  18. Prediction of Single-Peak Flow Stress Curves at High Temperatures Using a New Logarithmic-Power Function

    NASA Astrophysics Data System (ADS)

    Shafiei, Ehsan; Dehghani, Kamran

    2016-09-01

    In this study, using a nonlinear estimation of strain hardening rate versus strain, a new phenomenological constitutive equation is developed. Utilizing the presented model, three new equations were presented to determine the peak strain, critical strain for initiation of dynamic recrystallization (DRX), and transition strain associated with the maximum softening rate of DRX. Also, two temperature and strain rate-sensitive parameters were introduced to generate flow stress curve at any desired deformation conditions. The predicted results were found to be in a good agreement with the ones measured experimentally. Maximum errors in prediction of peak strain, critical strain, and transition strain were about 8, 11, and 4%, respectively. In addition, evaluation of maximum errors in prediction of flow stress indicates that the presented constitutive equation gives a more precise estimation of flow stress curves in comparison with the previous models pertaining modeling of single-peak flow stress curves.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. Precision predictions for the primordial power spectra from f(R) models of inflation

    NASA Astrophysics Data System (ADS)

    Brooker, D. J.; Odintsov, S. D.; Woodard, R. P.

    2016-10-01

    We study the power spectra of f (R) inflation using a new technique in which the norm-squared of the mode functions is evolved. Our technique results in excellent analytic approximations for how the spectra depend upon the function f (R). Although the spectra are numerically the same in the Jordan and Einstein frames for the same wave number k, they depend upon the geometries of these frames in quite different ways. For example, the power spectra in the two frames are different functions of the number of e-foldings until end of inflation. We discuss how future data on reheating can be used to distinguish f (R) inflation from scalar-driven inflation.

  4. High gamma-power predicts performance in sensorimotor-rhythm brain-computer interfaces

    NASA Astrophysics Data System (ADS)

    Grosse-Wentrup, Moritz; Schölkopf, Bernhard

    2012-08-01

    Subjects operating a brain-computer interface (BCI) based on sensorimotor rhythms exhibit large variations in performance over the course of an experimental session. Here, we show that high-frequency γ-oscillations, originating in fronto-parietal networks, predict such variations on a trial-to-trial basis. We interpret this finding as empirical support for an influence of attentional networks on BCI performance via modulation of the sensorimotor rhythm.

  5. High γ-power predicts performance in sensorimotor-rhythm brain-computer interfaces.

    PubMed

    Grosse-Wentrup, Moritz; Schölkopf, Bernhard

    2012-08-01

    Subjects operating a brain-computer interface (BCI) based on sensorimotor rhythms exhibit large variations in performance over the course of an experimental session. Here, we show that high-frequency γ-oscillations, originating in fronto-parietal networks, predict such variations on a trial-to-trial basis. We interpret this finding as empirical support for an influence of attentional networks on BCI performance via modulation of the sensorimotor rhythm.

  6. 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)

  7. 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

  8. 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

  9. 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

  10. 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.

  11. Comprehensive evaluation of ten docking programs on a diverse set of protein-ligand complexes: the prediction accuracy of sampling power and scoring power.

    PubMed

    Wang, Zhe; Sun, Huiyong; Yao, Xiaojun; Li, Dan; Xu, Lei; Li, Youyong; Tian, Sheng; Hou, Tingjun

    2016-05-14

    As one of the most popular computational approaches in modern structure-based drug design, molecular docking can be used not only to identify the correct conformation of a ligand within the target binding pocket but also to estimate the strength of the interaction between a target and a ligand. Nowadays, as a variety of docking programs are available for the scientific community, a comprehensive understanding of the advantages and limitations of each docking program is fundamentally important to conduct more reasonable docking studies and docking-based virtual screening. In the present study, based on an extensive dataset of 2002 protein-ligand complexes from the PDBbind database (version 2014), the performance of ten docking programs, including five commercial programs (LigandFit, Glide, GOLD, MOE Dock, and Surflex-Dock) and five academic programs (AutoDock, AutoDock Vina, LeDock, rDock, and UCSF DOCK), was systematically evaluated by examining the accuracies of binding pose prediction (sampling power) and binding affinity estimation (scoring power). Our results showed that GOLD and LeDock had the best sampling power (GOLD: 59.8% accuracy for the top scored poses; LeDock: 80.8% accuracy for the best poses) and AutoDock Vina had the best scoring power (rp/rs of 0.564/0.580 and 0.569/0.584 for the top scored poses and best poses), suggesting that the commercial programs did not show the expected better performance than the academic ones. Overall, the ligand binding poses could be identified in most cases by the evaluated docking programs but the ranks of the binding affinities for the entire dataset could not be well predicted by most docking programs. However, for some types of protein families, relatively high linear correlations between docking scores and experimental binding affinities could be achieved. To our knowledge, this study has been the most extensive evaluation of popular molecular docking programs in the last five years. It is expected that our work

  12. 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

  13. 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

    Carvalho, Lívia Pinheiro; Di Thommazo-Luporini, Luciana; Aubertin-Leheudre, Mylène; Bonjorno Junior, José Carlos; de Oliveira, Cláudio Ricardo; Luporini, Rafael Luís; Mendes, Renata Gonçalves; Zangrando, Katiany Thais Lopes; Trimer, Renata; Arena, Ross; Borghi-Silva, Audrey

    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.

  14. 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.

  15. 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.

  16. Integration of small run-of-river and solar power: The hydrological regime prediction/assessment accuracy

    NASA Astrophysics Data System (ADS)

    Francois, Baptiste; Creutin, Jean-Dominique; Hingray, Benoit; Zoccatelli, Davide

    2014-05-01

    The possibility to achieved a high integration of climate related energies (i.e. run-of-river-, wind- and solar- energies) depends on the possibility to balance the potentially large deviations between the related intermittent productions and the variable demand using storage facilities such as water storage in accumulation dams. These deviations depend obviously on how energy sources co-fluctuate in time among themselves and with the demand as well. Balancing hydropower system design as well as their operational planning requires the estimation of these co-fluctuations, resulting from both, space and time weather structures/patterns and watershed features (e.g. area, altitude range, geological basement …). The co-fluctuations between intermittent energy sources can be estimated from observed time series when available or from time series obtained from simulation models when not or when different contexts have to be considered (e.g. climate change and/or intermittent energy development). The simulation models were classically developed and evaluated for the prediction of each energy source individually. The ability of the models to simulate relevant levels of co-fluctuations is however to our knowledge not really considered. This issue is however critical and should also require thorough attention. This work focuses on run-of-river and solar- power interaction assessment. The study area is located in Italy where run-of-river power plants, mainly located on small river tributaries, represent almost 43 % of the hydropower production with only 27 % of the installed hydro-capacity (in 2011). Solar power generation is available from observed time series at different locations over the region but there is no systematic measurement of water discharges over the considered river tributaries and discharges have to be reconstituted from simulations. The absence of discharge measures makes also impossible to calibrate hydrological model at each power plant location. We thus

  17. Primary air pollutant emissions of coal-fired power plants in China: Current status and future prediction

    NASA Astrophysics Data System (ADS)

    Zhao, Yu; Wang, Shuxiao; Duan, Lei; Lei, Yu; Cao, Pengfei; Hao, Jiming

    To explore the atmospheric emissions of coal-fired power sector in China, a unit-based method was developed based on detailed information of unit type, fuel quality, emission control technology, and geographical location. During 2000-2005, the period when power sector developed fastest in the past 20 years, SO 2, NO x and PM emissions of coal-fired power plants increased by 1.5, 1.7 and 1.2 times, respectively. The SO 2, emission of coal-fired power sector was estimated to be 16 097 kt in 2005, and would decrease to 11 801 kt in 2010, attributed mainly to the wide application of the flue gas desulfurization (FGD) technology. The NO x emission, however, would increase from 6965 kt in 2005 to 9680 kt in 2010, since few NO x control measures would be taken during the five years. The TSP, PM 10, and PM 2.5 emissions in 2005 were estimated to be 2774, 1842 and 994 kt, and the values would be 2540, 1824 and 1090 kt in 2010 respectively. The wet FGD would play an important role on dust emission removal. Through faithful implementation of closing small units and emission control policies in the acid rain and sulfur dioxide control zones, approximately 33%, 6% and 25% of SO 2, NO x, and TSP emissions respectively could be further reduced in 2010. Emissions in 2015 and 2020 of coal-fired power plants were predicted applying scenario analysis. For SO 2 and TSP, optimistic situation can be achieved through reasonable control policies; in contrast, NO x would probably be a more serious issue in future.

  18. The power of exercise-induced T-wave alternans to predict ventricular arrhythmias in patients with implanted cardiac defibrillator.

    PubMed

    Burattini, Laura; Man, Sumche; Sweene, Cees A

    2013-01-01

    The power of exercise-induced T-wave alternans (TWA) to predict the occurrence of ventricular arrhythmias was evaluated in 67 patients with an implanted cardiac defibrillator (ICD). During the 4-year follow-up, electrocardiographic (ECG) tracings were recorded in a bicycle ergometer test with increasing workload ranging from zero (NoWL) to the patient's maximal capacity (MaxWL). After the follow-up, patients were classified as either ICD_Cases (n = 29), if developed ventricular tachycardia/fibrillation, or ICD_Controls (n = 38). TWA was quantified using our heart-rate adaptive match filter. Compared to NoWL, MaxWL was characterized by faster heart rates and higher TWA in both ICD_Cases (12-18 μ V vs. 20-39 μ V; P < 0.05) and ICD_Controls (9-15 μ V vs. 20-32 μ V; P < 0.05). Still, TWA was able to discriminate the two ICD groups during NoWL (sensitivity = 59-83%, specificity = 53-84%) but not MaxWL (sensitivity = 55-69%, specificity = 39-74%). Thus, this retrospective observational case-control study suggests that TWA's predictive power for the occurrence of ventricular arrhythmias could increase at low heart rates.

  19. 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

  20. 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.

  1. No Additional Prognostic Value of Genetic Information in the Prediction of Vascular Events after Cerebral Ischemia of Arterial Origin: The PROMISe Study

    PubMed Central

    Achterberg, Sefanja; Kappelle, L. Jaap; de Bakker, Paul I. W.; Traylor, Matthew; Algra, Ale

    2015-01-01

    Background Patients who have suffered from cerebral ischemia have a high risk of recurrent vascular events. Predictive models based on classical risk factors typically have limited prognostic value. Given that cerebral ischemia has a heritable component, genetic information might improve performance of these risk models. Our aim was to develop and compare two models: one containing traditional vascular risk factors, the other also including genetic information. Methods and Results We studied 1020 patients with cerebral ischemia and genotyped them with the Illumina Immunochip. Median follow-up time was 6.5 years; the annual incidence of new ischemic events (primary outcome, n=198) was 3.0%. The prognostic model based on classical vascular risk factors had an area under the receiver operating characteristics curve (AUC-ROC) of 0.65 (95% confidence interval 0.61-0.69). When we added a genetic risk score based on prioritized SNPs from a genome-wide association study of ischemic stroke (using summary statistics from the METASTROKE study which included 12389 cases and 62004 controls), the AUC-ROC remained the same. Similar results were found for the secondary outcome ischemic stroke. Conclusions We found no additional value of genetic information in a prognostic model for the risk of ischemic events in patients with cerebral ischemia of arterial origin. This is consistent with a complex, polygenic architecture, where many genes of weak effect likely act in concert to influence the heritable risk of an individual to develop (recurrent) vascular events. At present, genetic information cannot help clinicians to distinguish patients at high risk for recurrent vascular events. PMID:25906364

  2. FOREGROUND PREDICTIONS FOR THE COSMIC MICROWAVE BACKGROUND POWER SPECTRUM FROM MEASUREMENTS OF FAINT INVERTED RADIO SOURCES AT 5 GHz

    SciTech Connect

    Schneider, Michael D.; Becker, Robert H.; De Vries, Willem; White, Richard L.

    2012-05-10

    We present measurements of a population of matched radio sources at 1.4 and 5 GHz down to a flux limit of 1.5 mJy in 7 deg{sup 2} of the NOAO Deep Field South. We find a significant fraction of sources with inverted spectral indices that all have 1.4 GHz fluxes less than 10 mJy and are therefore too faint to have been detected and included in previous radio source count models that are matched at multiple frequencies. Combined with the matched source population at 1.4 and 5 GHz in 1 deg{sup -2} in the ATESP survey, we update models for the 5 GHz differential number counts and distributions of spectral indices in 5 GHz flux bins that can be used to estimate the unresolved point source contribution to the cosmic microwave background temperature anisotropies. We find a shallower logarithmic slope in the 5 GHz differential counts than in previously published models for fluxes {approx}< 100 mJy as well as larger fractions of inverted spectral indices at these fluxes. Because the Planck flux limit for resolved sources is larger than 100 mJy in all channels, our modified number counts yield at most a 10% change in the predicted Poisson contribution to the Planck temperature power spectrum. For a flux cut of 5 mJy with the South Pole Telescope and a flux cut of 20 mJy with the Atacama Cosmology Telescope, we predict a {approx}30% and {approx}10% increase, respectively, in the radio source Poisson power in the lowest frequency channels of each experiment relative to that predicted by previous models.

  3. 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

  4. 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.

  5. 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.

  6. 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

  7. 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.

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

    SciTech Connect

    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.

  9. 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

  10. 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

  11. 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

  12. 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.

  13. 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.

  14. Synthesis of superheavy elements: Uncertainty analysis to improve the predictive power of reaction models

    NASA Astrophysics Data System (ADS)

    Lü, Hongliang; Boilley, David; Abe, Yasuhisa; Shen, Caiwan

    2016-09-01

    Background: Synthesis of superheavy elements is performed by heavy-ion fusion-evaporation reactions. However, fusion is known to be hindered with respect to what can be observed with lighter ions. Thus some delicate ambiguities remain on the fusion mechanism that eventually lead to severe discrepancies in the calculated formation probabilities coming from different fusion models. Purpose: In the present work, we propose a general framework based upon uncertainty analysis in the hope of constraining fusion models. Method: To quantify uncertainty associated with the formation probability, we propose to propagate uncertainties in data and parameters using the Monte Carlo method in combination with a cascade code called kewpie2, with the aim of determining the associated uncertainty, namely the 95 % confidence interval. We also investigate the impact of different models or options, which cannot be modeled by continuous probability distributions, on the final results. An illustrative example is presented in detail and then a systematic study is carried out for a selected set of cold-fusion reactions. Results: It is rigorously shown that, at the 95 % confidence level, the total uncertainty of the empirical formation probability appears comparable to the discrepancy between calculated values. Conclusions: The results obtained from the present study provide direct evidence for predictive limitations of the existing fusion-evaporation models. It is thus necessary to find other ways to assess such models for the purpose of establishing a more reliable reaction theory, which is expected to guide future experiments on the production of superheavy elements.

  15. Energy-Efficient Control with Harvesting Predictions for Solar-Powered Wireless Sensor Networks.

    PubMed

    Zou, Tengyue; Lin, Shouying; Feng, Qijie; Chen, Yanlian

    2016-01-04

    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.

  16. 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

  17. Patient-derived xenograft models of breast cancer and their predictive power.

    PubMed

    Whittle, James R; Lewis, Michael T; Lindeman, Geoffrey J; Visvader, Jane E

    2015-02-10

    Despite advances in the treatment of patients with early and metastatic breast cancer, mortality remains high due to intrinsic or acquired resistance to therapy. Increased understanding of the genomic landscape through massively parallel sequencing has revealed somatic mutations common to specific subtypes of breast cancer, provided new prognostic and predictive markers, and highlighted potential therapeutic targets. Evaluating new targets using established cell lines is limited by the inexact correlation between responsiveness observed in cell lines versus that elicited in the patient. Patient-derived xenografts (PDXs) generated from fresh tumor specimens recapitulate the diversity of breast cancer and reflect histopathology, tumor behavior, and the metastatic properties of the original tumor. The high degree of genomic preservation evident across primary tumors and their matching PDXs over serial passaging validate them as important preclinical tools. Indeed, there is accumulating evidence that PDXs can recapitulate treatment responses of the parental tumor. The finding that tumor engraftment is an independent and poor prognostic indicator of patient outcome represents the first step towards personalized medicine. Here we review the utility of breast cancer PDX models to study the clonal evolution of tumors and to evaluate novel therapies and drug resistance.

  18. 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

  19. 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.

  20. Predicting the environmental risks of radioactive discharges from Belgian nuclear power plants.

    PubMed

    Vandenhove, H; Sweeck, L; Vives I Batlle, J; Wannijn, J; Van Hees, M; Camps, J; Olyslaegers, G; Miliche, C; Lance, B

    2013-12-01

    An environmental risk assessment (ERA) was performed to evaluate the impact on non-human biota from liquid and atmospheric radioactive discharges by the Belgian Nuclear Power Plants (NPP) of Doel and Tihange. For both sites, characterisation of the source term and wildlife population around the NPPs was provided, whereupon the selection of reference organisms and the general approach taken for the environmental risk assessment was established. A deterministic risk assessment for aquatic and terrestrial ecosystems was performed using the ERICA assessment tool and applying the ERICA screening value of 10 μGy h(-1). The study was performed for the radioactive discharge limits and for the actual releases (maxima and averages over the period 1999-2008 or 2000-2009). It is concluded that the current discharge limits for the Belgian NPPs considered do not result in significant risks to the aquatic and terrestrial environment and that the actual discharges, which are a fraction of the release limits, are unlikely to harm the environment.

  1. Lack of predictive power of plasma lipids or lipoproteins for gestational diabetes mellitus in Japanese women

    PubMed Central

    Iimura, Yuko; Matsuura, Masaaki; Yao, Zemin; Ito, Satoru; Fujiwara, Mutsunori; Yoshitsugu, Michiyasu; Miyauchi, Akito; Hiyoshi, Toru

    2015-01-01

    Aims/Introduction To determine the diagnostic potential of plasma lipids and apolipoproteins in gestational diabetes mellitus (GDM), we carried out a retrospective cohort study of 1,161 Japanese women at 20–28 weeks of gestation who underwent a glucose challenge test (GCT). Materials and Methods A total of 1,161 Japanese women at 20–28 weeks of gestation underwent a GCT. Participants with a positive test (GCT[+]) underwent a subsequent oral glucose tolerance test. Clinical and biochemical parameters were determined and quantification of apolipoproteins (Apo), including ApoB, ApoB48, ApoA-I and ApoC-III, was carried out. Results The prevalence of GCT(+; with a 130 mg/dL glucose cut-off) and GDM was 20% and 4%, respectively. There was a trend for increased triglycerides and ApoC-III in GDM(+) participants. However, the difference in plasma triglycerides, ApoC-III or ApoB48 did not reach statistical significance between GDM(+) and GDM(−) women. Values of 1-h glucose (P < 0.001) and fasting glucose (P = 0.002) were significant risk factors for GDM. Conclusions Prediction of GDM using only the ApoC-III value is not easy, although triglycerides and ApoC-III were higher in the GDM(+) group. The present findings show no significant difference in plasma lipid levels between women diagnosed with GDM and those with normal glucose tolerance. PMID:26543537

  2. Market powers predict reciprocal grooming in golden snub-nosed monkeys (Rhinopithecus roxellana).

    PubMed

    Wei, Wei; Qi, Xiao-Guang; 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.

  3. 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.

  4. Predicting the Impact of Climate Change on U.S. Power Grids and Its Wider Implications on National Security

    SciTech Connect

    Wong, Pak C.; Leung, Lai-Yung R.; Lu, Ning; Paget, Maria L.; Correia, James; Jiang, Wei; Mackey, Patrick S.; Taylor, Zachary T.; Xie, YuLong; Xu, Jianhua; Unwin, Stephen D.; Sanfilippo, Antonio P.

    2009-03-23

    We discuss our technosocial analytics research and devel-opment on predicting and assessing the impact of climate change on U.S. power-grids and the wider implications for national security. The ongoing efforts extend cutting-edge modeling theories derived from climate, energy, social sciences, and national security domains to form a unified system coupled with an interactive visual interface for technosocial analysis. The goal of the system is to create viable future scenarios that address both technical and social factors involved in the model domains. These scenarios enable policy makers to formulate a coherent, unified strategy towards building a safe and secure society. The paper gives an executive summary of our efforts in the past fiscal year and provides a glimpse of our work planned for the second year of the three-year project being conducted at the Pacific Northwest National Laboratory.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. What if the power-law model did not apply for the prediction of very large rockfall events?

    NASA Astrophysics Data System (ADS)

    Rohmer, J.; Dewez, T.

    2012-04-01

    Extreme events are of primary importance for risk management in a variety of natural phenomena, and more particularly for landslides and rockfalls, because they might be associated with huge losses. Numerous research works have addressed this problem based on the same paradigm: if events exhibit the same statistical properties across a broad range of sizes, the probability of extreme events can be evaluated by extrapolating the frequency-size distribution. Considering landslides' areas or rockfalls' volumes, the frequency distribution has been found to be heavy-tailed and the well-known power law distribution has been proposed to model it. Yet, the vision of very large extreme event (catastrophic) frequency being an extrapolation of the power laws fitted on small and intermediate events has been challenged in various contexts, in particular by Sornette and co-authors, who proposed viewing such catastrophic events as "outliers" from the power-law model, i.e. they deviate by an abnormal large distance from the extrapolated prediction. In this study, we address such an issue considering a rockfall inventory, containing >8500 events spanning 8 orders of magnitudes of volume and collated from 2.5 years of high-accuracy repeated terrestrial laser scanning (TLS) surveys on a coastal chalk cliff in Normandy (France). This inventory contains a particularly large event of 70,949 m3 which occurred some time between February 1 and 7 April 2008. It is the second largest cliff failure reported in Normandy, and is larger than those collated in historical cliff failure inventories across various geological and geomorphological coastal settings. Is this event an outlier of the power-law volume-frequency distribution ? And if so, why? This largest event recorded appears to stand out of the rest of the sample. We use it to revisit the techniques to fit power-law distribution with robust techniques (robust weighted maximum likelihood estimator), rarely used in rockfall studies, and

  10. 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

  11. Prediction and measurement of the electromagnetic environment of high-power medium-wave and short-wave broadcast antennas in far field.

    PubMed

    Tang, Zhanghong; Wang, Qun; Ji, Zhijiang; Shi, Meiwu; Hou, Guoyan; Tan, Danjun; Wang, Pengqi; Qiu, Xianbo

    2014-12-01

    With the increasing city size, high-power electromagnetic radiation devices such as high-power medium-wave (MW) and short-wave (SW) antennas have been inevitably getting closer and closer to buildings, which resulted in the pollution of indoor electromagnetic radiation becoming worsened. To avoid such radiation exceeding the exposure limits by national standards, it is necessary to predict and survey the electromagnetic radiation by MW and SW antennas before constructing the buildings. In this paper, a modified prediction method for the far-field electromagnetic radiation is proposed and successfully applied to predict the electromagnetic environment of an area close to a group of typical high-power MW and SW wave antennas. Different from currently used simplified prediction method defined in the Radiation Protection Management Guidelines (H J/T 10. 3-1996), the new method in this article makes use of more information such as antennas' patterns to predict the electromagnetic environment. Therefore, it improves the prediction accuracy significantly by the new feature of resolution at different directions. At the end of this article, a comparison between the prediction data and the measured results is given to demonstrate the effectiveness of the proposed new method.

  12. Critical power derived from a 3-min all-out test predicts 16.1-km road time-trial performance.

    PubMed

    Black, Matthew I; Durant, Jacob; Jones, Andrew M; Vanhatalo, Anni

    2014-01-01

    It has been shown that the critical power (CP) in cycling estimated using a novel 3-min all-out protocol is reliable and closely matches the CP derived from conventional procedures. The purpose of this study was to assess the predictive validity of the all-out test CP estimate. We hypothesised that the all-out test CP would be significantly correlated with 16.1-km road time-trial (TT) performance and more strongly correlated with performance than the gas exchange threshold (GET), respiratory compensation point (RCP) and VO2 max. Ten club-level male cyclists (mean±SD: age 33.8±8.2 y, body mass 73.8±4.3 kg, VO2 max 60±4 ml·kg(-1)·min(-1)) performed a 10-mile road TT, a ramp incremental test to exhaustion, and two 3-min all-out tests, the first of which served as familiarisation. The 16.1-km TT performance (27.1±1.2 min) was significantly correlated with the CP (309±34 W; r = -0.83, P<0.01) and total work done during the all-out test (70.9±6.5 kJ; r = -0.86, P<0.01), the ramp incremental test peak power (433±30 W; r = -0.75, P<0.05) and the RCP (315±29 W; r = -0.68, P<0.05), but not with GET (151±32 W; r = -0.21) or the VO2 max (4.41±0.25 L·min(-1); r = -0.60). These data provide evidence for the predictive validity and practical performance relevance of the 3-min all-out test. The 3-min all-out test CP may represent a useful addition to the battery of tests employed by applied sport physiologists or coaches to track fitness and predict performance in atheletes.

  13. 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.

  14. Macrophage colony-stimulating factor expressed in non-cancer tissues provides predictive powers for recurrence in hepatocellular carcinoma

    PubMed Central

    Kono, Hiroshi; Fujii, Hideki; Furuya, Shinji; Hara, Michio; Hirayama, Kazuyoshi; Akazawa, Yoshihiro; Nakata, Yuuki; Tsuchiya, Masato; Hosomura, Naohiro; Sun, Chao

    2016-01-01

    AIM To investigate the role of macrophage colony-stimulating factor (M-CSF) in patients with hepatocellular carcinoma (HCC) after surgery. METHODS Expression of M-CSF, distribution of M2 macrophages (MΦs), and angiogenesis were assessed in the liver, including tumors and peritumoral liver tissues. The prognostic power of these factors was assessed. Mouse isolated hepatic MΦs or monocytes were cultured with media containing M-CSF. The concentration of vascular endothelial growth factor (VEGF) in media was assessed. Furthermore, the role of the M-CSF-matured hepatic MΦs on proliferation of the vascular endothelial cell (VEC) was investigated. RESULTS A strong correlation between the expressions of M-CSF and CD163 was observed in the peritumoral area. Also, groups with high density of M-CSF, CD163 or CD31 showed a significantly shorter time to recurrence (TTR) than low density groups. Multivariate analysis revealed the expression of M-CSF or hepatic M2MΦs in the peritumoral area as the most crucial factor responsible for shorter TTR. Moreover, the expression of M-CSF and hepatic M2MΦs in the peritumoral area had better predictable power of overall survival. Values of VEGF in culture media were significantly greater in the hepatic MΦs compared with the monocytes. Proliferation of the VEC was greatest in the cells co-cultured with hepatic MΦs when M-CSF was present in media. CONCLUSION M-CSF increases hepatocarcinogenesis, most likely by enhancing an angiogenic factor derived from hepatic MΦ and could be a useful target for therapy against HCC.

  15. 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

  16. Enthalpy relaxation of polymers: comparing the predictive power of two configurational entropy models extending the AGV approach

    NASA Astrophysics Data System (ADS)

    Andreozzi, L.; Faetti, M.; Zulli, F.; Giordano, M.

    2004-10-01

    The Tool-Narayanaswamy-Moynihan (TNM) phenomenological model is widely accepted in order to describe the structural relaxation of glasses. However several quantitative discrepancies can be found in the literature that cannot be entirely ascribed to the experimental errors. In this work we compare the predictive power of two recently proposed configurational entropy approaches extending the TNM formalism. Both of them change the treatment of non linearity by adding a free parameter. We use Differential Scanning Calorimetry (DSC) experiments in order to test the models in two different polymers. One of them is a commercial PMMA sample, the other is a side chain liquid crystal azo-benzene polymer properly synthesized for optical nanorecording purposes. Different results were found for the two systems. In the PMMA sample only one of the new models was able to improve the agreement between DSC experiments and theory with respect to the TNM model, whereas in the second polymer both the approaches were able to describe the experiments better than TNM model.

  17. A comprehensive review of on-board State-of-Available-Power prediction techniques for lithium-ion batteries in electric vehicles

    NASA Astrophysics Data System (ADS)

    Farmann, Alexander; Sauer, Dirk Uwe

    2016-10-01

    This study provides an overview of available techniques for on-board State-of-Available-Power (SoAP) prediction of lithium-ion batteries (LIBs) in electric vehicles. Different approaches dealing with the on-board estimation of battery State-of-Charge (SoC) or State-of-Health (SoH) have been extensively discussed in various researches in the past. However, the topic of SoAP prediction has not been explored comprehensively yet. The prediction of the maximum power that can be applied to the battery by discharging or charging it during acceleration, regenerative braking and gradient climbing is definitely one of the most challenging tasks of battery management systems. In large lithium-ion battery packs because of many factors, such as temperature distribution, cell-to-cell deviations regarding the actual battery impedance or capacity either in initial or aged state, the use of efficient and reliable methods for battery state estimation is required. The available battery power is limited by the safe operating area (SOA), where SOA is defined by battery temperature, current, voltage and SoC. Accurate SoAP prediction allows the energy management system to regulate the power flow of the vehicle more precisely and optimize battery performance and improve its lifetime accordingly. To this end, scientific and technical literature sources are studied and available approaches are reviewed.

  18. 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

  19. 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.

  20. Plant-mPLoc: a top-down strategy to augment the power for predicting plant protein subcellular localization.

    PubMed

    Chou, Kuo-Chen; Shen, Hong-Bin

    2010-01-01

    One of the fundamental goals in proteomics and cell biology is to identify the functions of proteins in various cellular organelles and pathways. Information of subcellular locations of proteins can provide useful insights for revealing their functions and understanding how they interact with each other in cellular network systems. Most of the existing methods in predicting plant protein subcellular localization can only cover three or four location sites, and none of them can be used to deal with multiplex plant proteins that can simultaneously exist at two, or move between, two or more different location sits. Actually, such multiplex proteins might have special biological functions worthy of particular notice. The present study was devoted to improve the existing plant protein subcellular location predictors from the aforementioned two aspects. A new predictor called "Plant-mPLoc" is developed by integrating the gene ontology information, functional domain information, and sequential evolutionary information through three different modes of pseudo amino acid composition. It can be used to identify plant proteins among the following 12 location sites: (1) cell membrane, (2) cell wall, (3) chloroplast, (4) cytoplasm, (5) endoplasmic reticulum, (6) extracellular, (7) Golgi apparatus, (8) mitochondrion, (9) nucleus, (10) peroxisome, (11) plastid, and (12) vacuole. Compared with the existing methods for predicting plant protein subcellular localization, the new predictor is much more powerful and flexible. Particularly, it also has the capacity to deal with multiple-location proteins, which is beyond the reach of any existing predictors specialized for identifying plant protein subcellular localization. As a user-friendly web-server, Plant-mPLoc is freely accessible at http://www.csbio.sjtu.edu.cn/bioinf/plant-multi/. Moreover, for the convenience of the vast majority of experimental scientists, a step-by-step guide is provided on how to use the web-server to get the

  1. 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

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Phosphazene additives

    DOEpatents

    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.

  9. 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.

  10. 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.

  11. 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.

  12. Resting Frontal Gamma Power at 16, 24 and 36 months Predicts Individual Differences in Language and Cognition at 4 and 5 years

    PubMed Central

    Gou, Zhenkun; Choudhury, Naseem; Benasich, April A.

    2011-01-01

    Gamma activity has been linked to a variety of different cognitive processes and exists in both transient and persistent forms. Across studies, different brain regions have been suggested to contribute to gamma activity. Multiple studies have shown that the function of gamma oscillations may be related to temporal binding of early sensory information to relevant top-down processes. Given this hypothesis, we expected gamma oscillations to subserve general brain mechanisms that contribute to the development of cognitive and linguistic systems. The present study aims to examine the predictive relations between resting-state cortical gamma power density at a critical point in language and cognitive acquisition (i.e. 16, 24 and 36 months), and cognitive and language output at ages 4 and 5 years. Our findings show that both 24- and 36-month gamma power are significantly correlated with later language scores, notably Non-Word Repetition. Further, 16-, 24- and 36-month gamma were all significantly correlated with 4-year PLS-3 and CELF-P sentence structure scores. Although associations reported here do not reflect a direct cause and effect of early resting gamma power on later language outcomes, capacity to generate higher power in the gamma range at crucial developmental periods may index better modulation of attention and allow easier access to working memory, thus providing an advantage for overall development, particularly in the linguistic domain. Moreover, measuring abilities at times when these abilities are still emergent may allow better prediction of later outcomes. PMID:21295619

  13. Resting frontal gamma power at 16, 24 and 36 months predicts individual differences in language and cognition at 4 and 5 years.

    PubMed

    Gou, Zhenkun; Choudhury, Naseem; Benasich, April A

    2011-07-01

    Gamma activity has been linked to a variety of different cognitive processes and exists in both transient and persistent forms. Across studies, different brain regions have been suggested to contribute to gamma activity. Multiple studies have shown that the function of gamma oscillations may be related to temporal binding of early sensory information to relevant top-down processes. Given this hypothesis, we expected gamma oscillations to subserve general brain mechanisms that contribute to the development of cognitive and linguistic systems. The present study aims to examine the predictive relations between resting-state cortical gamma power density at a critical point in language and cognitive acquisition (i.e. 16, 24 and 36 months), and cognitive and language output at ages 4 and 5 years. Our findings show that both 24- and 36-month gamma power are significantly correlated with later language scores, notably Non-Word Repetition. Further, 16-, 24- and 36-month gamma were all significantly correlated with 4-year PLS-3 and CELF-P sentence structure scores. Although associations reported here do not reflect a direct cause and effect of early resting gamma power on later language outcomes, capacity to generate higher power in the gamma range at crucial developmental periods may index better modulation of attention and allow easier access to working memory, thus providing an advantage for overall development, particularly in the linguistic domain. Moreover, measuring abilities at times when these abilities are still emergent may allow better prediction of later outcomes.

  14. Statistical evaluation of the predictive power of fine needle aspiration (FNA) of salivary glands. Results and cytohistological correlation.

    PubMed

    Abad, M M; G-Macias, C; Alonso, M J; Muñoz, E; Paz, J I; Galindo, P; Herrero, A; Bullon, A

    1992-04-01

    Fine needle aspiration (FNA) of the salivary glands was carried out on 97 patients. Diagnosis was confirmed by histological findings in 93 patients. There were 75 benign lesions (including 52 benign tumours) and 18 malignant lesions. In our series "positive predictive value" of FNA was 0.900 and the negative predictive value was 0.963. Thus, the probability of a false positive is 0.100 and of a false negative 0.037.

  15. Variable versus constant power strategies during cycling time-trials: prediction of time savings using an up-to-date mathematical model.

    PubMed

    Atkinson, G; Peacock, O; Passfield, L

    2007-07-01

    Swain (1997) employed the mathematical model of Di Prampero et al. (1979) to predict that, for cycling time-trials, the optimal pacing strategy is to vary power in parallel with the changes experienced in gradient and wind speed. We used a more up-to-date mathematical model with validated coefficients (Martin et al., 1998) to quantify the time savings that would result from such optimization of pacing strategy. A hypothetical cyclist (mass = 70 kg) and bicycle (mass = 10 kg) were studied under varying hypothetical wind velocities (-10 to 10 m x s(-1)), gradients (-10 to 10%), and pacing strategies. Mean rider power outputs of 164, 289, and 394 W were chosen to mirror baseline performances studied previously. The three race scenarios were: (i) a 10-km time-trial with alternating 1-km sections of 10% and -10% gradient; (ii) a 40-km time-trial with alternating 5-km sections of 4.4 and -4.4 m x s(-1) wind (Swain, 1997); and (iii) the 40-km time-trial delimited by Jeukendrup and Martin (2001). Varying a mean power of 289 W by +/- 10% during Swain's (1997) hilly and windy courses resulted in time savings of 126 and 51 s, respectively. Time savings for most race scenarios were greater than those suggested by Swain (1997). For a mean power of 289 W over the "standard" 40-km time-trial, a time saving of 26 s was observed with a power variability of 10%. The largest time savings were found for the hypothetical riders with the lowest mean power output who could vary power to the greatest extent. Our findings confirm that time savings are possible in cycling time-trials if the rider varies power in parallel with hill gradient and wind direction. With a more recent mathematical model, we found slightly greater time savings than those reported by Swain (1997). These time savings compared favourably with the predicted benefits of interventions such as altitude training or ingestion of carbohydrate-electrolyte drinks. Nevertheless, the extent to which such power output variations

  16. Simple equations to predict concentric lower-body muscle power in older adults using the 30-second chair-rise test: a pilot study

    PubMed Central

    Smith, Wesley N; Rossi, Gianluca Del; Adams, Jessica B; Abderlarahman, KZ; Asfour, Shihab A; Roos, Bernard A; Signorile, Joseph F

    2010-01-01

    Although muscle power is an important factor affecting independence in older adults, there is no inexpensive or convenient test to quantify power in this population. Therefore, this pilot study examined whether regression equations for evaluating muscle power in older adults could be derived from a simple chair-rise test. We collected data from a 30-second chair-rise test performed by fourteen older adults (76 ± 7.19 years). Average (AP) and peak (PP) power values were computed using data from force-platform and high-speed motion analyses. Using each participant’s body mass and the number of chair rises performed during the first 20 seconds of the 30-second trial, we developed multivariate linear regression equations to predict AP and PP. The values computed using these equations showed a significant linear correlation with the values derived from our force-platform and high-speed motion analyses (AP: R = 0.89; PP: R = 0.90; P < 0.01). Our results indicate that lower-body muscle power in fit older adults can be accurately evaluated using the data from the initial 20 seconds of a simple 30-second chair-rise test, which requires no special equipment, preparation, or setting. PMID:20711436

  17. Clinically insignificant improvement of prostate cancer prediction by addition of sex steroid hormones and SHBG serum levels to serum PSA, fPSA%, and age in a screening setting.

    PubMed

    Heidegger, Isabel; Popovscaia, Marina; Ramoner, Reinhold; Schäfer, Georg; Stenzel, Birgit; Bektic, Jasmin; Horninger, Wolfgang; Klocker, Helmut

    2012-10-01

    Abstract Various findings implicate sex hormones in prostate growth and development and also in prostate carcinogenesis. We investigated if addition of sex steroid hormone and sex hormone binding globulin (SHBG) serum levels to standard risk assessment parameters [prostate-specific antigen (PSA), free PSA percentage (fPSA%), and age] improves prostate cancer prediction in a PSA screening setting. Steroid hormones testosterone (T), free testosterone (fT), and estradiol (E2), and binding protein SHBG levels were measured in 762 men undergoing prostate biopsy due to suspect PSA serum levels. Prostate cancer was diagnosed in 286 (37.5%) of these men. Our data confirmed that PSA (mean BE=5.09; mean CA=6.05; p=1.24×10-5), fPSA% (mean BE=22.08; mean CA=18.67; p=1.97×10-7), and age (mean BE=60.64; mean CA=64.5; p=7.05×10-10) differentiate men with cancer (CA) and men with benign disease (BE), such as benign prostate hyperplasia. In addition, SHBG (mean BE=50.3; mean CA=54.9; p=0.008) also differed statistically significantly between these two groups. All hormones except E2 and tumor markers correlated significantly with age (T: ρ=-0.09; fT: ρ=-0.27; SHBG: ρ=0.21; PSA: ρ=0.32; and fPSA%: ρ=0.22). Furthermore, we found that PSA correlates with E2 (ρ=0.08), and fPSA% with SHBG (ρ=0.1) and fT (ρ=-0.09). Addition of hormones and SHBG to a baseline marker model including PSA, fPSA%, and age improved cancer prediction in three multivariate classification methods; however, the improvement was minimal. The best improvement by 0.8% was obtained in the logistic regression model with the addition of T and SHBG or of E2 and SHBG, or in the support vector machine model with the addition of SHBG and all steroid hormones to the combination of standard markers PSA, fPSA%, and age; however, this additional gain of accuracy is too small to justify the additional efforts and costs.

  18. Verification of CFD analysis methods for predicting the drag force and thrust power of an underwater disk robot

    NASA Astrophysics Data System (ADS)

    Joung, Tae-Hwan; Choi, Hyeung-Sik; Jung, Sang-Ki; Sammut, Karl; He, Fangpo

    2014-06-01

    This paper examines the suitability of using the Computational Fluid Dynamics (CFD) tools, ANSYSCFX, as an initial analysis tool for predicting the drag and propulsion performance (thrust and torque) of a concept underwater vehicle design. In order to select an appropriate thruster that will achieve the required speed of the Underwater Disk Robot (UDR), the ANSYS-CFX tools were used to predict the drag force of the UDR. Vertical Planar Motion Mechanism (VPMM) test simulations (i.e. pure heaving and pure pitching motion) by CFD motion analysis were carried out with the CFD software. The CFD results reveal the distribution of hydrodynamic values (velocity, pressure, etc.) of the UDR for these motion studies. Finally, CFD bollard pull test simulations were performed and compared with the experimental bollard pull test results conducted in a model basin. The experimental results confirm the suitability of using the ANSYS-CFX tools for predicting the behavior of concept vehicles early on in their design process.

  19. Ti-direct, powerful, stereoselective aldol-type additions of esters and thioesters to carbonyl compounds: application to the synthesis and evaluation of lactone analogs of jasmone perfumes.

    PubMed

    Nagase, Ryohei; Matsumoto, Noriaki; Hosomi, Kohei; Higashi, Takahiro; Funakoshi, Syunsuke; Misaki, Tomonori; Tanabe, Yoo

    2007-01-01

    An efficient TiCl(4)-Et(3)N or Bu(3)N-promoted aldol-type addition of phenyl and thiophenyl esters or thioaryl esters with aldehydes and ketones was performed (total 46 examples). The present method is advantageous from atom-economical and cost-effective viewpoints; good to excellent yields, moderate to good syn-selectivity, substrate variations, reagent availability, and simple procedures. Utilizing the present reaction as the key step, an efficient short synthesis of three lactone [2(5H)-furanone] analogs of jasmine perfumes was performed. Among them, the lactone analog of cis-jasmone had a unique perfume property (tabac).

  20. Prediction of light aircraft interior sound pressure level from the measured sound power flowing in to the cabin

    NASA Technical Reports Server (NTRS)

    Atwal, Mahabir S.; Heitman, Karen E.; Crocker, Malcolm J.

    1986-01-01

    The validity of the room equation of Crocker and Price (1982) for predicting the cabin interior sound pressure level was experimentally tested using a specially constructed setup for simultaneous measurements of transmitted sound intensity and interior sound pressure levels. Using measured values of the reverberation time and transmitted intensities, the equation was used to predict the space-averaged interior sound pressure level for three different fuselage conditions. The general agreement between the room equation and experimental test data is considered good enough for this equation to be used for preliminary design studies.

  1. A top-down approach to enhance the power of predicting human protein subcellular localization: Hum-mPLoc 2.0.

    PubMed

    Shen, Hong-Bin; Chou, Kuo-Chen

    2009-11-15

    Predicting subcellular localization of human proteins is a challenging problem, particularly when query proteins may have a multiplex character, i.e., simultaneously exist at, or move between, two or more different subcellular location sites. In a previous study, we developed a predictor called "Hum-mPLoc" to deal with the multiplex problem for the human protein system. However, Hum-mPLoc has the following shortcomings. (1) The input of accession number for a query protein is required in order to obtain a higher expected success rate by selecting to use the higher-level prediction pathway; but many proteins, such as synthetic and hypothetical proteins as well as those newly discovered proteins without being deposited into databanks yet, do not have accession numbers. (2) Neither functional domain nor sequential evolution information were taken into account in Hum-mPLoc, and hence its power may be reduced accordingly. In view of this, a top-down strategy to address these shortcomings has been implemented. The new predictor thus obtained is called Hum-mPLoc 2.0, where the accession number for input is no longer needed whatsoever. Moreover, both the functional domain information and the sequential evolution information have been fused into the predictor by an ensemble classifier. As a consequence, the prediction power has been significantly enhanced. The web server of Hum-mPLoc2.0 is freely accessible at http://www.csbio.sjtu.edu.cn/bioinf/hum-multi-2/.

  2. 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

  3. The Power of Perception: Children's Appearance as a Factor in Adults' Predictions of Gender-Typical Behavior.

    ERIC Educational Resources Information Center

    Rogers, Cindy M.; Ritter, Jean M.

    2002-01-01

    Examined the influence of 3-year-olds' facial characteristics on adults' predictions of children's gender- typical behaviors. Found that adults' expectations for children's gender-typical behaviors are influenced by the masculinity/femininity of children's facial appearance, regardless of the gender information provided. Explored implications on…

  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. Ratings of Perceived Exertion, Heart Rate, and Power Output in Predicting Maximal Oxygen Uptake During Submaximal Cycle Ergometry.

    ERIC Educational Resources Information Center

    Wilmore, Jack H.; And Others

    1986-01-01

    Sixty-two subjects completed a four-stage submaximal cycle ergometer test to determine if estimates of maximal oxygen uptake could be improved by using ratings of perceived exertion singly or in combination with easily obtainable physiological measures. These procedures could be used to estimate the aerobic power of patients and athletes. (MT)

  6. 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

  7. A novel material detection algorithm based on 2D GMM-based power density function and image detail addition scheme in dual energy X-ray images.

    PubMed

    Pourghassem, Hossein

    2012-01-01

    Material detection is a vital need in dual energy X-ray luggage inspection systems at security of airport and strategic places. In this paper, a novel material detection algorithm based on statistical trainable models using 2-Dimensional power density function (PDF) of three material categories in dual energy X-ray images is proposed. In this algorithm, the PDF of each material category as a statistical model is estimated from transmission measurement values of low and high energy X-ray images by Gaussian Mixture Models (GMM). Material label of each pixel of object is determined based on dependency probability of its transmission measurement values in the low and high energy to PDF of three material categories (metallic, organic and mixed materials). The performance of material detection algorithm is improved by a maximum voting scheme in a neighborhood of image as a post-processing stage. Using two background removing and denoising stages, high and low energy X-ray images are enhanced as a pre-processing procedure. For improving the discrimination capability of the proposed material detection algorithm, the details of the low and high energy X-ray images are added to constructed color image which includes three colors (orange, blue and green) for representing the organic, metallic and mixed materials. The proposed algorithm is evaluated on real images that had been captured from a commercial dual energy X-ray luggage inspection system. The obtained results show that the proposed algorithm is effective and operative in detection of the metallic, organic and mixed materials with acceptable accuracy.

  8. Artificial Neural Network Genetic Algorithm As Powerful Tool to Predict and Optimize In vitro Proliferation Mineral Medium for G × N15 Rootstock

    PubMed Central

    Arab, Mohammad M.; Yadollahi, Abbas; Shojaeiyan, Abdolali; Ahmadi, Hamed

    2016-01-01

    One of the major obstacles to the micropropagation of Prunus rootstocks has, up until now, been the lack of a suitable tissue culture medium. Therefore, reformulation of culture media or modification of the mineral content might be a breakthrough to improve in vitro multiplication of G × N15 (garnem). We found artificial neural network in combination of genetic algorithm (ANN-GA) as a very precise and powerful modeling system for optimizing the culture medium, So that modeling the effects of MS mineral salts (NH4+, NO3-, PO42-, Ca2+, K+, SO42-, Mg2+, and Cl−) on in vitro multiplication parameters (the number of microshoots per explant, average length of microshoots, weight of calluses derived from the base of stem explants, and quality index of plantlets) of G × N15. Showed high R2 correlation values of 87, 91, 87, and 74 between observed and predicted values were found for these four growth parameters, respectively. According to the ANN-GA results, among the input variables, NH4+ and NO3- had the highest values of VSR in data set for the parameters studied. The ANN-GA showed that the best proliferation rate was obtained from medium containing (mM) 27.5 NO3-, 14 NH4+, 5 Ca2+, 25.9 K+, 0.7 Mg2+, 1.1 PO42-, 4.7 SO42-, and 0.96 Cl−. The performance of the medium optimized by ANN-GA, denoted as YAS (Yadollahi, Arab and Shojaeiyan), was compared to that of standard growth media for all Prunus rootstock, including the Murashige and Skoog (MS) medium, (specific media) EM, Quoirin and Lepoivre (QL) medium, and woody plant medium (WPM) Prunus. With respect to shoot length, shoot number per cultured explant and productivity (number of microshoots × length of microshoots), YAS was found to be superior to other media for in vitro multiplication of G × N15 rootstocks. In addition, our results indicated that by using ANN-GA, we were able to determine a suitable culture medium formulation to achieve the best in vitro productivity. PMID:27807436

  9. Predictive Power and Implication of EuroSCORE, EuroSCORE II and STS Score for Isolated Repeated Aortic Valve Replacement

    PubMed Central

    Jessen, Sören; Neumann, Konrad; Konertz, Wolfgang

    2015-01-01

    Objective: We evaluated the predictive power of the EuroSCORE, EuroSCORE II and Society of Thoracic Surgeons (STS) score for isolated redo aortic valve replacement. Materials and Methods: 78 consecutive patients underwent the aforementioned procedure mainly with a stentless valve prosthesis at our institution. Observed mortality was compared to the predicted mortality, Receiver Operating Characteristics (ROC) curves were calculated and the area under the curve (AUC) analyzed. Result: Observed mortality was 11.5%. EuroSCORE and EuroScore II predicted a mortality of 28.2 ± 21.6% (p <0.001) and 10.2 ± 11.8% (p = 0.75), respectively. AUC of the EuroSCORE was 0.74 (95% CI: 0.62–0.83), p = 0.009 and of the EuroSCORE II 0.86 (95% CI: 0.76–0.93), p <0.0001. Optimal Youden index of the EuroSCORE II was 0.59 refering to a predicted mortality of 9.9% (sensitivity: 77.8% and specificity: 81.2%). Predicted mortality of STS score was 17.8 ± 10.6% (p = 0.08) and AUC was 0.64 (95% CI: 0.53–0.75), p = 0.06. Conclusion: EuroSCORE II calculation was not only superior to EuroSCORE and STS score but led to a very realistic mortality prediction for this special procedure at our institution. A EuroSCORE II greater 10 should encourage to consider an alternative treatment. PMID:25740446

  10. Different slopes for different folks: alpha and delta EEG power predict subsequent video game learning rate and improvements in cognitive control tasks.

    PubMed

    Mathewson, Kyle E; Basak, Chandramallika; Maclin, Edward L; Low, Kathy A; Boot, Walter R; Kramer, Arthur F; Fabiani, Monica; Gratton, Gabriele

    2012-12-01

    We hypothesized that control processes, as measured using electrophysiological (EEG) variables, influence the rate of learning of complex tasks. Specifically, we measured alpha power, event-related spectral perturbations (ERSPs), and event-related brain potentials during early training of the Space Fortress task, and correlated these measures with subsequent learning rate and performance in transfer tasks. Once initial score was partialled out, the best predictors were frontal alpha power and alpha and delta ERSPs, but not P300. By combining these predictors, we could explain about 50% of the learning rate variance and 10%-20% of the variance in transfer to other tasks using only pretraining EEG measures. Thus, control processes, as indexed by alpha and delta EEG oscillations, can predict learning and skill improvements. The results are of potential use to optimize training regimes.

  11. Time-series model for predicting ambient TSP concentrations at monitors located near coal-fired power plants

    SciTech Connect

    Warren-Hicks, W.; Siple, G.

    1984-01-01

    The scope of this paper is to develop a time-series model applicable to a number of data sets containing total suspended particulate (TSP) data. The authors wanted the mathematical form of the model to be as simple as possible while maintaining a good fit to all the TSP data sets involved. To this end, data from three TSP monitoring sites, which are located near coal-fired power plants operated by Carolina Power and Light Company in North Carolina, were chosen for analysis. The data consisted of every-sixth-day, 24-hour TSP concentrations collected using a high-volume sampler and measured gravimetrically. An autoregressive integrated moving average (ARIMA) time-series, model was fit to each data set. The model was then used to fill in missing concentrations and forecast future values. Forecasted values were compared against measured maximum and averaged values.

  12. 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

  13. 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.

  14. 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.

  15. Looking down secondary pore throats in Mississippian siliciclastic sandstones of eastern Nevada: Predicting porosity by low-power microscopy

    SciTech Connect

    McLean, H. )

    1993-04-01

    Mississippian sandstones in eastern Nevada consist of quartz, chert, and lithic detritus shed from erosion of the Roberts Mountain allochthon. Deposited in a marine flysch-trough and a variety of peripheral nonmarine environments, the sandstones reflect a complex history of compaction and cementation. The utility of studying sandstone pores in color impregnated thin sections and in images created with the scanning electron microscope (SEM) is well documented in geologic literature. However, low-power binocular microscopic examination of hand specimens cut with a petrographic diamond saw is a simple and inexpensive alternative for observing the number and type of pore throats, fractures, and presence or absence of quartz overgrowths. The low-power microscope technique is especially useful for observing pores formed by dissolution of rock fragments. Facets of quartz overgrowths and pitted quartz facets are also clearly visible using the low-power technique. Petrographic microscopy of non-calcareous, color-impregnated thin sections indicates porosity in the Mississippian sandstones of eastern Nevada was first reduced by mechanical compaction and (or) precipitation of authigenic cements such as quartz, calcite and dolomite. In rocks of moderate thermal maturity, secondary porosity results from dissolution of argillaceous and carbonaceous sedimentary rock fragments, and in some cases, by dissolution of earlier formed calcareous cement.

  16. 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

  17. 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

  18. 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

  19. 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.

  20. Real-time Coupled Ensemble Kalman Filter Forecasting & Nonlinear Model Predictive Control Approach for Optimal Power Take-off of a Wave Energy Converter

    NASA Astrophysics Data System (ADS)

    Cavaglieri, Daniele; Bewley, Thomas; Previsic, Mirko

    2014-11-01

    In recent years, there has been a growing interest in renewable energy. Among all the available possibilities, wave energy conversion, due to the huge availability of energy that the ocean could provide, represents nowadays one of the most promising solutions. However, the efficiency of a wave energy converter for ocean wave energy harvesting is still far from making it competitive with more mature fields of renewable energy, such as solar and wind energy. One of the main problems is related to the difficulty to increase the power take-off through the implementation of an active controller without a precise knowledge of the oncoming wavefield. This work represents the first attempt at defining a realistic control framework for optimal power take-off of a wave energy converter where the ocean wavefield is predicted through a nonlinear Ensemble Kalman filter which assimilates data from a wave measurement device, such as a Doppler radar or a measurement buoy. Knowledge of the future wave profile is then leveraged in a nonlinear direct multiple shooting model predictive control framework allowing the online optimization of the energy absorption under motion and machinery constraints of the device.

  1. 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.

  2. GABA concentration in superior temporal sulcus predicts gamma power and perception in the sound-induced flash illusion.

    PubMed

    Balz, Johanna; Keil, Julian; Roa Romero, Yadira; Mekle, Ralf; Schubert, Florian; Aydin, Semiha; Ittermann, Bernd; Gallinat, Jürgen; Senkowski, Daniel

    2016-01-15

    In everyday life we are confronted with inputs of multisensory stimuli that need to be integrated across our senses. Individuals vary considerably in how they integrate multisensory information, yet the neurochemical foundations underlying this variability are not well understood. Neural oscillations, especially in the gamma band (>30Hz) play an important role in multisensory processing. Furthermore, gamma-aminobutyric acid (GABA) neurotransmission contributes to the generation of gamma band oscillations (GBO), which can be sustained by activation of metabotropic glutamate receptors. Hence, differences in the GABA and glutamate systems might contribute to individual differences in multisensory processing. In this combined magnetic resonance spectroscopy and electroencephalography study, we examined the relationships between GABA and glutamate concentrations in the superior temporal sulcus (STS), source localized GBO, and illusion rate in the sound-induced flash illusion (SIFI). In 39 human volunteers we found robust relationships between GABA concentration, GBO power, and the SIFI perception rate (r-values=0.44 to 0.53). The correlation between GBO power and SIFI perception rate was about twofold higher when the modulating influence of the GABA level was included in the analysis as compared to when it was excluded. No significant effects were obtained for glutamate concentration. Our study suggests that the GABA level shapes individual differences in audiovisual perception through its modulating influence on GBO. GABA neurotransmission could be a promising target for treatment interventions of multisensory processing deficits in clinical populations, such as schizophrenia or autism.

  3. 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.

  4. A GIS-based prediction and assessment system of off-site accident consequence for Guangdong nuclear power plant.

    PubMed

    Wang, X Y; Qu, J Y; Shi, Z Q; Ling, Y S

    2003-01-01

    GNARD (Guangdong Nuclear Accident Real-time Decision support system) is a decision support system for off-site emergency management in the event of an accidental release from the nuclear power plants located in Guangdong province, China. The system is capable of calculating wind field, concentrations of radionuclide in environmental media and radiation doses. It can also estimate the size of the area where protective actions should be taken and provide other information about population distribution and emergency facilities available in the area. Furthermore, the system can simulate and evaluate the effectiveness of countermeasures assumed and calculate averted doses by protective actions. All of the results can be shown and analysed on the platform of a geographical information system (GIS).

  5. 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.

  6. Mollusc communities in Bulgarian fens: predictive power of the environment, vegetation, and spatial structure in an isolated habitat

    NASA Astrophysics Data System (ADS)

    Horsák, Michal; Hájek, Michal; Hájková, Petra; Cameron, Robert; Cernohorsky, Nicole; Apostolova, Iva

    2011-08-01

    Mollusc communities of previously unexplored Bulgarian fens were studied in order to determine and generalise the patterns of species richness and composition along the mineral richness gradient. The aim was also to compare predictive values of the environment, vegetation and spatial structure. Altogether, 44 mollusc species were recorded at 40 treeless fen sites. Species richness varied from 0 to 18 species per site, and it was positively associated with the mineral gradient and negatively with altitude. However, the best predictor was obtained using plant species composition. All explanatory variables had higher effect on land snails than on the entire mollusc assemblage (including aquatic species). Species richness and abundance were significantly and positively correlated with the species composition turnover; the communities were highly nested, with poor sites having subsets of the fauna found in the richest. The main direction of mollusc species turnover was highly associated with that observed for vegetation, and the main gradient of plant species composition was able to explain nearly 20% of total variation in mollusc data. We found that spatial structure explained by far the highest proportion of independent variation, which reflected the high level of geographical isolation of Bulgarian fens and regional differences independent of any environmental variation. Our results demonstrate (1) the general role of mineral richness gradient for structuring mollusc communities in fens, (2) the pivotal indicator role of plant species composition in predicting species composition of mollusc communities, despite being trophically independent and (3) the effect of isolation and origins of the habitat on species composition: most species have wide geographical distributions within the habitat type, and geographical patterns within Bulgaria may have a stochastic element.

  7. Mollusc communities in Bulgarian fens: predictive power of the environment, vegetation, and spatial structure in an isolated habitat.

    PubMed

    Horsák, Michal; Hájek, Michal; Hájková, Petra; Cameron, Robert; Cernohorsky, Nicole; Apostolova, Iva

    2011-08-01

    Mollusc communities of previously unexplored Bulgarian fens were studied in order to determine and generalise the patterns of species richness and composition along the mineral richness gradient. The aim was also to compare predictive values of the environment, vegetation and spatial structure. Altogether, 44 mollusc species were recorded at 40 treeless fen sites. Species richness varied from 0 to 18 species per site, and it was positively associated with the mineral gradient and negatively with altitude. However, the best predictor was obtained using plant species composition. All explanatory variables had higher effect on land snails than on the entire mollusc assemblage (including aquatic species). Species richness and abundance were significantly and positively correlated with the species composition turnover; the communities were highly nested, with poor sites having subsets of the fauna found in the richest. The main direction of mollusc species turnover was highly associated with that observed for vegetation, and the main gradient of plant species composition was able to explain nearly 20% of total variation in mollusc data. We found that spatial structure explained by far the highest proportion of independent variation, which reflected the high level of geographical isolation of Bulgarian fens and regional differences independent of any environmental variation. Our results demonstrate (1) the general role of mineral richness gradient for structuring mollusc communities in fens, (2) the pivotal indicator role of plant species composition in predicting species composition of mollusc communities, despite being trophically independent and (3) the effect of isolation and origins of the habitat on species composition: most species have wide geographical distributions within the habitat type, and geographical patterns within Bulgaria may have a stochastic element.

  8. 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.

  9. A multiscale technique for the validation of a numerical code for predicting the pressure field induced by a high-power spark

    NASA Astrophysics Data System (ADS)

    Villa, A.; Malgesini, R.; Barbieri, L.

    2011-04-01

    A more precise knowledge of the pressure field induced by a high-power spark is essential to estimate the mechanical damage that a lightning strike can induce near the impact point. In this work we propose a multiscale approach to validate a numerical magnetohydro-dynamic model that can predict the pressure field when a very high-power discharge is considered. Two simplified models for the arc resistance are considered and their respective results are compared. A brief analysis regarding the numerical issues involved in the solution of a very high temperature gas is included. The numerical code has been validated against the experimental data of a short-arc discharge using a current waveform prescribed by the aeronautical standards. Our study shows that a strong shock wave is generated in the first power peak and this travels away from the arc column maintaining a relatively high strength a few tens of centimetres away. The pressure in the arc region remains high for the whole discharge period.

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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.

  15. Empowerment and continuous improvement in the United States, Mexico, Poland, and India: predicting fit on the basis of the dimensions of power distance and individualism.

    PubMed

    Robert, C; Probst, T M; Martocchio, J J; Drasgow, F; Lawler, J J

    2000-10-01

    Although variations in national cultures predominate as explanation for the belief that universal approaches to management do not exist, there have been few reports of systematic studies. Data from employees of a single firm with operations in the United States, Mexico, Poland, and India were used to test the fit of empowerment and continuous improvement practices with national culture. Using the theoretical constructs of individualism-collectivism and power distance, the authors predicted that the practices would be more congruent in some cultures than in others and that value congruence would result in job satisfaction. Using structural equations modeling, the authors found that empowerment was negatively associated with satisfaction in India but positively associated in the other 3 samples. Continuous improvement was positively associated with satisfaction in all samples. Substantive, theoretical, and methodological implications are discussed.

  16. 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.

  17. 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.

  18. CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Simulation of SET Operation in Phase-Change Random Access Memories with Heater Addition and Ring-Type Contactor for Low-Power Consumption by Finite Element Modeling

    NASA Astrophysics Data System (ADS)

    Gong, Yue-Feng; Song, Zhi-Tang; Ling, Yun; Liu, Yan; Feng, Song-Lin

    2009-11-01

    A three-dimensional finite element model for phase change random access memory (PCRAM) is established for comprehensive electrical and thermal analysis during SET operation. The SET behaviours of the heater addition structure (HS) and the ring-type contact in bottom electrode (RIB) structure are compared with each other. There are two ways to reduce the RESET current, applying a high resistivity interfacial layer and building a new device structure. The simulation results indicate that the variation of SET current with different power reduction ways is little. This study takes the RESET and SET operation current into consideration, showing that the RIB structure PCRAM cell is suitable for future devices with high heat efficiency and high-density, due to its high heat efficiency in RESET operation.

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. On the predictive power of the minimum energy condition. 2: Fractional calorimeter behaviour in the diffuse high energy gamma emission of spiral galaxies

    NASA Astrophysics Data System (ADS)

    Pohl, M.

    1994-07-01

    In this paper we investigate the high energy gamma ray emission from spiral galaxies. The calculations are based on equilibrium spectra for cosmic ray protons and electrons, respectively, which have been derived in an earlier paper (Pohl 1993a). There, the cosmic ray particles are assumed to undergo simultaneously transport by diffusion, escape, and energy losses by ionization, inelastic scattering, bremsstrahlung, adiabatic cooling and radiative losses. In the thick target case a fractional calorimeter behavior occurs both for leptonic and for hadronic gamma ray emission: the resultant gamma ray flux depends solely on the injection rate of cosmic rays and on a fraction factor. This fraction factor is in fact a combination of two: the first is the fraction of cosmic rays which meet the interaction targets like protons or thermal gas. The second is the fraction of the gamma ray producing loss mechanism to the total losses in the gas disk. Once reliable gamma ray and radio spectra of spiral galaxies are obtained these calorimeter fractions may help to gain information about the physical state of the interstellar medium in these objects, especially on the proton-to-electron ratio in cosmic rays. The integrated radio spectra of spiral galaxies tell us whether these systems form a thick target for cosmic rays or not. With the minimum energy consumption for the magnetic field strength we are then able to predict explicitely the gamma ray flux from these objects in a broad energy range. The hitherto promising candidates M 31 and M 82 will not be detected by EGRET, since their integrated flux is les than 2 x 10-8ph./sq cm/sec. It appears that our Galaxy is the only object apart from Large Magellanic Cloud (LMC) which we observe with sufficient accuracy to base clues on the gamma ray emission. Since via the calorimeter effects spiral galaxies can regulate themselves, the minimum energy condition has a predictive power which is much more precise than earlier estimated

  4. 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

  5. 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...

  6. 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.

  7. 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…

  8. 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

  9. 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

  10. 18 CFR 1314.10 - Additional provisions.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 18 Conservation of Power and Water Resources 2 2010-04-01 2010-04-01 false Additional provisions. 1314.10 Section 1314.10 Conservation of Power and Water Resources TENNESSEE VALLEY AUTHORITY BOOK-ENTRY... attachment for TVA Power Securities in Book-entry System. The interest of a debtor in a Security...

  11. 18 CFR 1314.10 - Additional provisions.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 18 Conservation of Power and Water Resources 2 2011-04-01 2011-04-01 false Additional provisions. 1314.10 Section 1314.10 Conservation of Power and Water Resources TENNESSEE VALLEY AUTHORITY BOOK-ENTRY... attachment for TVA Power Securities in Book-entry System. The interest of a debtor in a Security...

  12. 18 CFR 1314.10 - Additional provisions.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 18 Conservation of Power and Water Resources 2 2014-04-01 2014-04-01 false Additional provisions. 1314.10 Section 1314.10 Conservation of Power and Water Resources TENNESSEE VALLEY AUTHORITY BOOK-ENTRY... attachment for TVA Power Securities in Book-entry System. The interest of a debtor in a Security...

  13. 18 CFR 1314.10 - Additional provisions.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 18 Conservation of Power and Water Resources 2 2012-04-01 2012-04-01 false Additional provisions. 1314.10 Section 1314.10 Conservation of Power and Water Resources TENNESSEE VALLEY AUTHORITY BOOK-ENTRY... attachment for TVA Power Securities in Book-entry System. The interest of a debtor in a Security...

  14. 18 CFR 1314.10 - Additional provisions.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 18 Conservation of Power and Water Resources 2 2013-04-01 2012-04-01 true Additional provisions. 1314.10 Section 1314.10 Conservation of Power and Water Resources TENNESSEE VALLEY AUTHORITY BOOK-ENTRY... attachment for TVA Power Securities in Book-entry System. The interest of a debtor in a Security...

  15. 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.

  16. Predictive aging results in radiation environments

    NASA Astrophysics Data System (ADS)

    Gillen, Kenneth T.; Clough, Roger L.

    1993-06-01

    We have previously derived a time-temperature-dose rate superposition methodology, which, when applicable, can be used to predict polymer degradation versus dose rate, temperature and exposure time. This methodology results in predictive capabilities at the low dose rates and long time periods appropriate, for instance, to ambient nuclear power plant environments. The methodology was successfully applied to several polymeric cable materials and then verified for two of the materials by comparisons of the model predictions with 12 year, low-dose-rate aging data on these materials from a nuclear environment. In this paper, we provide a more detailed discussion of the methodology and apply it to data obtained on a number of additional nuclear power plant cable insulation (a hypalon, a silicone rubber and two ethylene-tetrafluoroethylenes) and jacket (a hypalon) materials. We then show that the predicted, low-dose-rate results for our materials are in excellent agreement with long-term (7-9 year) low-dose-rate results recently obtained for the same material types actually aged under bnuclear power plant conditions. Based on a combination of the modelling and long-term results, we find indications of reasonably similar degradation responses among several different commercial formulations for each of the following "generic" materials: hypalon, ethylene-tetrafluoroethylene, silicone rubber and PVC. If such "generic" behavior can be further substantiated through modelling and long-term results on additional formulations, predictions of cable life for other commercial materials of the same generic types would be greatly facilitated.

  17. 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

  18. PREDICTIVE MODELS

    SciTech Connect

    Ray, R.M. )

    1986-12-01

    PREDICTIVE MODELS is a collection of five models - CFPM, CO2PM, ICPM, PFPM, and SFPM - used in the 1982-1984 National Petroleum Council study of enhanced oil recovery (EOR) potential. Each pertains to a specific EOR process designed to squeeze additional oil from aging or spent oil fields. The processes are: 1) chemical flooding, where soap-like surfactants are injected into the reservoir to wash out the oil; 2) carbon dioxide miscible flooding, where carbon dioxide mixes with the lighter hydrocarbons making the oil easier to displace; 3) in-situ combustion, which uses the heat from burning some of the underground oil to thin the product; 4) polymer flooding, where thick, cohesive material is pumped into a reservoir to push the oil through the underground rock; and 5) steamflood, where pressurized steam is injected underground to thin the oil. CFPM, the Chemical Flood Predictive Model, models micellar (surfactant)-polymer floods in reservoirs, which have been previously waterflooded to residual oil saturation. Thus, only true tertiary floods are considered. An option allows a rough estimate of oil recovery by caustic or caustic-polymer processes. CO2PM, the Carbon Dioxide miscible flooding Predictive Model, is applicable to both secondary (mobile oil) and tertiary (residual oil) floods, and to either continuous CO2 injection or water-alternating gas processes. ICPM, the In-situ Combustion Predictive Model, computes the recovery and profitability of an in-situ combustion project from generalized performance predictive algorithms. PFPM, the Polymer Flood Predictive Model, is switch-selectable for either polymer or waterflooding, and an option allows the calculation of the incremental oil recovery and economics of polymer relative to waterflooding. SFPM, the Steamflood Predictive Model, is applicable to the steam drive process, but not to cyclic steam injection (steam soak) processes.

  19. 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.

  20. 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

  1. Further finite element analyses of fully developed laminar flow of power-law non-Newtonian fluid in rectangular ducts: Heat transfer predictions

    SciTech Connect

    Syrjaelae, S.

    1996-10-01

    Forced convection heat transfer to hydrodynamically and thermally fully developed laminar flow of power-law non-Newtonian fluid in rectangular ducts has been studied for the H1 and T thermal boundary conditions. The solutions for the velocity and temperature fields were obtained numerically using the finite element method with quartic triangular elements. From these solutions, very accurate Nusselt number values were determined. Computations were performed over a range of power-law indices and duct aspect ratios.

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. Postmarketing surveillance of food additives.

    PubMed

    Butchko, H H; Tschanz, C; Kotsonis, F N

    1994-08-01

    Postmarketing surveillance of consumption and of anecdotal reports of adverse health effects has been recognized by a number of regulatory authorities as a potentially useful method to provide further assurance of the safety of new food additives. Surveillance of consumption is used to estimate more reliably actual consumption levels relative to the acceptable daily intake of a food additive. Surveillance of anecdotal reports of adverse health effects is used to determine the presence of infrequent idiosyncratic responses that may not be predictable from premarket evaluations. The high-intensity sweetner, aspartame, is a food additive that has been the subject of extensive evaluation during the postmarketing period and is thus used as an example to discuss postmarketing surveillance.

  7. [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.

  8. 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.

  9. 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.

  10. The 3D-QSAR study of 110 diverse, dual binding, acetylcholinesterase inhibitors based on alignment independent descriptors (GRIND-2). The effects of conformation on predictive power and interpretability of the models.

    PubMed

    Vitorović-Todorović, Maja D; Cvijetić, Ilija N; Juranić, Ivan O; Drakulić, Branko J

    2012-09-01

    The 3D-QSAR analysis based on alignment independent descriptors (GRIND-2) was performed on the set of 110 structurally diverse, dual binding AChE reversible inhibitors. Three separate models were built, based on different conformations, generated following next criteria: (i) minimum energy conformations, (ii) conformation most similar to the co-crystalized ligand conformation, and (iii) docked conformation. We found that regardless on conformation used, all the three models had good statistic and predictivity. The models revealed the importance of protonated pyridine nitrogen of tacrine moiety for anti AChE activity, and recognized HBA and HBD interactions as highly important for the potency. This was revealed by the variables associated with protonated pyridinium nitrogen, and the two amino groups of the linker. MIFs calculated with the N1 (pyridinium nitrogen) and the DRY GRID probes in the AChE active site enabled us to establish the relationship between amino acid residues within AChE active site and the variables having high impact on models. External predictive power of the models was tested on the set of 40 AChE reversible inhibitors, most of them structurally different from the training set. Some of those compounds were tested on the different enzyme source. We found that external predictivity was highly sensitive on conformations used. Model based on docked conformations had superior predictive ability, emphasizing the need for the employment of conformations built by taking into account geometrical restrictions of AChE active site gorge.

  11. 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…

  12. 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

  13. Toxicokinetic-toxicodynamic modelling of survival of Gammarus pulex in multiple pulse exposures to propiconazole: model assumptions, calibration data requirements and predictive power.

    PubMed

    Nyman, Anna-Maija; Schirmer, Kristin; Ashauer, Roman

    2012-10-01

    Toxicokinetic-toxicodynamic (TKTD) models quantify the time-course of internal concentration, which is defined by uptake, elimination and biotransformation (TK), and the processes which lead to the toxic effects (TD). TKTD models show potential in predicting pesticide effects in fluctuating concentrations, but the data requirements and validity of underlying model assumptions are not known. We calibrated TKTD models to predict survival of Gammarus pulex in propiconazole exposure and investigated the data requirements. In order to assess the need of TK in survival models, we included or excluded simulated internal concentrations based on pre-calibrated TK. Adding TK did not improve goodness of fits. Moreover, different types of calibration data could be used to model survival, which might affect model parameterization. We used two types of data for calibration: acute toxicity (standard LC50, 4 d) or pulsed toxicity data (total length 10 d). The calibration data set influenced how well the survival in the other exposure scenario was predicted (acute to pulsed scenario or vice versa). We also tested two contrasting assumptions in ecotoxicology: stochastic death and individual tolerance distribution. Neither assumption fitted to data better than the other. We observed in 10-d toxicity experiments that pulsed treatments killed more organisms than treatments with constant concentration. All treatments received the same dose, i.e. the time-weighted average concentration was equal. We studied mode of toxic action of propiconazole and it likely acts as a baseline toxicant in G. pulex during 10-days of exposure for the endpoint survival.

  14. [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.

  15. Integrated Wind Power Planning Tool

    NASA Astrophysics Data System (ADS)

    Rosgaard, M. H.; Giebel, G.; Nielsen, T. S.; Hahmann, A.; Sørensen, P.; Madsen, H.

    2012-04-01

    This poster presents the current state of the public service obligation (PSO) funded project PSO 10464, with the working title "Integrated Wind Power Planning Tool". The project commenced October 1, 2011, and the goal is to integrate a numerical weather prediction (NWP) model with purely statistical tools in order to assess wind power fluctuations, with focus on long term power system planning for future wind farms as well as short term forecasting for existing wind farms. Currently, wind power fluctuation models are either purely statistical or integrated with NWP models of limited resolution. With regard to the latter, one such simulation tool has been developed at the Wind Energy Division, Risø DTU, intended for long term power system planning. As part of the PSO project the inferior NWP model used at present will be replaced by the state-of-the-art Weather Research & Forecasting (WRF) model. Furthermore, the integrated simulation tool will be improved so it can handle simultaneously 10-50 times more turbines than the present ~ 300, as well as additional atmospheric parameters will be included in the model. The WRF data will also be input for a statistical short term prediction model to be developed in collaboration with ENFOR A/S; a danish company that specialises in forecasting and optimisation for the energy sector. This integrated prediction model will allow for the description of the expected variability in wind power production in the coming hours to days, accounting for its spatio-temporal dependencies, and depending on the prevailing weather conditions defined by the WRF output. The output from the integrated prediction tool constitute scenario forecasts for the coming period, which can then be fed into any type of system model or decision making problem to be solved. The high resolution of the WRF results loaded into the integrated prediction model will ensure a high accuracy data basis is available for use in the decision making process of the Danish

  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. Resonant packaged piezoelectric power harvester for machinery health monitoring

    NASA Astrophysics Data System (ADS)

    du Plessis, Andries J.; Huigsloot, Marcel J.; Discenzo, Fred D.

    2005-05-01

    Packaged piezoelectric bi-morph actuators offer an alternative power source for health monitoring using localized vibrational power harvesting. Packaging piezoelectric wafers simplify the integration of piezoelectric ceramic wafers into products and improve the durability of the brittle piezoelectric ceramic material. This paper describes a model for predicting the power harvested from a resonant cantilevered beam piezoelectric power harvester across a resistive load. The model results are correlated with experimental power harvesting measurements made using a commercially available piezoelectric bi-morph actuator. Additionally, experimental power harvesting levels were determined under high root strain conditions and varying command frequencies. Finally, the power production capability of the packaged piezoelectric bi-morph generator was evaluated over millions of cycles at very high root strains levels, representative of the loads expected in an industrial application. Results from the testing indicate that packaged piezoelectric wafer products used in power harvesting devices are very reliable and well suited for harsh industrial application environments.

  18. 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.

  19. MultiUse solar thermal power generators

    NASA Astrophysics Data System (ADS)

    Abbott, Russell

    2001-02-01

    This paper describes Ontario Engineering International, Inc. (OEI) approach to a solar thermal power generation system using a number of thermal power generation technologies for possible applications to Mars exploration, material processing and for power generation on Earth. The latest power stage and generator design presented here were the culmination of studies covering a wide variety of generator configurations and operating parameters. The many steps and rationale leading to OEI's design evolution and materials selection will not be repeated here except for a description of OEI's latest design, including a heat source support scheme and power stage configuration. OEI's performance predictions were based on its techniques for the thermal analyses of thermal power generators. The analytical results indicate that the OEI power system design, operating within the stipulated solar input and temperature limits and well within its mass goals, can yield power outputs and system efficiencies that substantially exceed existing solar power generation technologies. The calculated efficiency for a cascaded power generation system is estimated to be 42% for a DC output or 37% for an AC power output. With the addition of a thermal storage medium power can be provided on a continuous basis during any shadow period. Recent advances in thermal power generation technologies have now progressed to the point where a solar thermal power generation system can be fabricated. This system can provide terrestrial power generation capacity in remote areas and provide a means for load leveling in the commercial power grid. This system is also adaptable for material processing and/or life-support on Mars. .

  20. 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

  1. 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.

  2. 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

  3. 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,…

  4. Multimodal imaging measures predict rearrest.

    PubMed

    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

  5. 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

  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. 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.

  9. 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

    2016-08-31

    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.

  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. 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

  13. 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.

  14. 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