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. 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.

  4. 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....

  5. 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....

  6. 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....

  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, 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....

  9. 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.

  10. 12. POWER PLANT PART OF BUILDING SHOWING RELATION TO ADDITION ...

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

    12. POWER PLANT PART OF BUILDING SHOWING RELATION TO ADDITION AND EQUIPMENT PART OF BUILDING - Boswell Bay White Alice Site, Radio Relay Building, Chugach National Forest, Cordova, Valdez-Cordova Census Area, AK

  11. Predictability of Brayton electric power system performance

    NASA Technical Reports Server (NTRS)

    Klann, J. L.; Hettel, H. J.

    1972-01-01

    Data from the first tests of the 2- to 15-kilowatt space power system in a vacuum chamber were compared with predictions of both a pretest analysis and a modified version of that analysis. The pretest analysis predicted test results with differences of no more than 9 percent of the largest measured value for each quantity. The modified analysis correlated measurements. Differences in conversion efficiency and power output were no greater than plus or minus 2.5 percent. This modified analysis was used to project space performance maps for the current test system.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  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. Precision prediction of the log power spectrum

    NASA Astrophysics Data System (ADS)

    Repp, A.; Szapudi, I.

    2017-01-01

    At translinear scales, the log power spectrum captures significantly more cosmological information than the standard power spectrum. At high wavenumbers k, the Fisher information in the standard power spectrum P(k) fails to increase in proportion to k, in part due to correlations between large- and small-scale modes. As a result, P(k) suffers from an information plateau on these translinear scales, so that analysis with the standard power spectrum cannot access the information contained in these small-scale modes. The log power spectrum PA(k), on the other hand, captures the majority of this otherwise lost information. Until now there has been no means of predicting the amplitude of the log power spectrum apart from cataloging the results of simulations. We here present a cosmology-independent prescription for the log power spectrum; this prescription displays accuracy comparable to that of Smith et al., over a range of redshifts and smoothing scales, and for wavenumbers up to 1.5 h Mpc-1.

  15. Uncertainties in predicting solar panel power output

    NASA Technical Reports Server (NTRS)

    Anspaugh, B.

    1974-01-01

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

  16. 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.

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

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

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

  18. 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. Can cycle power predict sprint running performance?

    PubMed

    van Ingen Schenau, G J; Jacobs, R; de Koning, J J

    1991-01-01

    A major criticism of present models of the energetics and mechanics of sprint running concerns the application of estimates of parameters which seem to be adapted from measurements of running during actual competitions. This study presents a model which does not perpetuate this solecism. Using data obtained during supra-maximal cycle ergometer tests of highly trained athletes, the kinetics of the anaerobic and aerobic pathways were modelled. Internal power wasted in the acceleration and deceleration of body limbs and the power necessary to overcome air friction was calculated from data in the literature. Assuming a mechanical efficiency as found during submaximal cycling, a power equation was constructed which also included the power necessary to accelerate the body at the start of movement. The differential equation thus obtained was solved through simulation. The model appeared to predict realistic times at 100 m (10.47 s), 200 m (19.63 s) and 400 m (42.99 s) distances. By comparison with other methods it is argued that power equations of locomotion should include the concept of mechanical efficiency.

  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. Power-law distributions from additive preferential redistributions

    NASA Astrophysics Data System (ADS)

    Ree, Suhan

    2006-02-01

    We introduce a nongrowth model that generates the power-law distribution with the Zipf exponent. There are N elements, each of which is characterized by a quantity, and at each time step these quantities are redistributed through binary random interactions with a simple additive preferential rule, while the sum of quantities is conserved. The situation described by this model is similar to those of closed N -particle systems when conservative two-body collisions are only allowed. We obtain stationary distributions of these quantities both analytically and numerically while varying parameters of the model, and find that the model exhibits the scaling behavior for some parameter ranges. Unlike well-known growth models, this alternative mechanism generates the power-law distribution when the growth is not expected and the dynamics of the system is based on interactions between elements. This model can be applied to some examples such as personal wealths, city sizes, and the generation of scale-free networks when only rewiring is allowed.

  5. COSMIC EMULATION: FAST PREDICTIONS FOR THE GALAXY POWER SPECTRUM

    SciTech Connect

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

    2015-09-01

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

  6. Predicting the performance of batteries having paste additives

    SciTech Connect

    Edwards, D.B.; Cantrell, R.L.; Dayton, T.C.

    1997-12-01

    This paper discusses how models previously developed at the University of Idaho can be used to design high performance batteries containing paste additives. One model characterizes the conductivity of the active material. With this model, the influence of different additives, both conductive and nonconductive, on the capacity of paste containing these additives can be evaluated. The results of this analysis is then used in a second model to characterize the performance of cells. The models are used in the paper to help design and evaluate a battery for a hybrid electric vehicle. This design example illustrates how the models can be used to investigate unique designs for electric and hybrid electric vehicles.

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

    SciTech Connect

    Stine, J R

    1981-08-01

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

  8. 18 CFR 385.705 - Additional powers of presiding officer with respect to briefs (Rule 705).

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 18 Conservation of Power and Water Resources 1 2011-04-01 2011-04-01 false Additional powers of presiding officer with respect to briefs (Rule 705). 385.705 Section 385.705 Conservation of Power and Water... PROCEDURE Decisions § 385.705 Additional powers of presiding officer with respect to briefs (Rule 705)....

  9. 18 CFR 385.705 - Additional powers of presiding officer with respect to briefs (Rule 705).

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Additional powers of presiding officer with respect to briefs (Rule 705). 385.705 Section 385.705 Conservation of Power and Water... PROCEDURE Decisions § 385.705 Additional powers of presiding officer with respect to briefs (Rule 705)....

  10. 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

  11. 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.

  12. 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)

  13. The predictive power of local properties of financial networks

    NASA Astrophysics Data System (ADS)

    Caraiani, Petre

    2017-01-01

    The literature on analyzing the dynamics of financial networks has focused so far on the predictive power of global measures of networks like entropy or index cohesive force. In this paper, I show that the local network properties have similar predictive power. I focus on key network measures like average path length, average degree or cluster coefficient, and also consider the diameter and the s-metric. Using Granger causality tests, I show that some of these measures have statistically significant prediction power with respect to the dynamics of aggregate stock market. Average path length is most robust relative to the frequency of data used or specification (index or growth rate). Most measures are found to have predictive power only for monthly frequency. Further evidences that support this view are provided through a simple regression model.

  14. 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.

  15. 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.

  16. 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.

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

    PubMed Central

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

    2013-01-01

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

  18. Predicting Rediated Noise With Power Flow Finite Element Analysis

    DTIC Science & Technology

    2007-02-01

    Defence R&D Canada – Atlantic DEFENCE DÉFENSE & Predicting Rediated Noise With Power Flow Finite Element Analysis D. Brennan T.S. Koko L. Jiang J...PREDICTING RADIATED NOISE WITH POWER FLOW FINITE ELEMENT ANALYSIS D.P. Brennan T.S. Koko L. Jiang J.C. Wallace Martec Limited Martec Limited...model- or full-scale data before it is available for general use. Brennan, D.P., Koko , T.S., Jiang, L., Wallace, J.C. 2007. Predicting Radiated

  19. 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.

  20. 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

  1. Predicting power-optimal kinematics of avian wings.

    PubMed

    Parslew, Ben

    2015-01-06

    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.

  2. Predicting power-optimal kinematics of avian wings

    PubMed Central

    Parslew, Ben

    2015-01-01

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

  3. Time series prediction using artificial neural network for power stabilization

    SciTech Connect

    Puranik, G.; Philip, T.; Nail, B.

    1996-12-31

    Time series prediction has been applied to many business and scientific applications. Prominent among them are stock market prediction, weather forecasting, etc. Here, this technique has been applied to forecast plasma torch voltages to stabilize power using a backpropagation, a model of artificial neural network. The Extended-Delta-Bar-Delta algorithm is used to improve the convergence rate of the network and also to avoid local minima. Results from off-line data was quite promising to use in on-line.

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

    NASA Technical Reports Server (NTRS)

    Noon, E. L.; Raag, V.

    1979-01-01

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

  5. 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.

  6. 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.

  7. 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,…

  8. 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.

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

    PubMed Central

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

    2013-01-01

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

  10. 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.

  11. 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.

  12. Model predictive control power management strategies for HEVs: A review

    NASA Astrophysics Data System (ADS)

    Huang, Yanjun; Wang, Hong; Khajepour, Amir; He, Hongwen; Ji, Jie

    2017-02-01

    This paper presents a comprehensive review of power management strategy (PMS) utilized in hybrid electric vehicles (HEVs) with an emphasis on model predictive control (MPC) based strategies for the first time. Research on MPC-based power management systems for HEVs has intensified recently due to its many inherent merits. The categories of the existing PMSs are identified from the latest literature, and a brief study of each type is conducted. Then, the MPC approach is introduced and its advantages are discussed. Based on the acquisition method of driver behavior used for state prediction and the dynamic model used, the MPC is classified and elaborated. Factors that affect the performance of the MPC are put forward, including prediction accuracy, design parameters, and solvers. Finally, several important issues in the application of MPC-based power management strategies and latest developing trends are discussed. This paper not only provides a comprehensive analysis of MPC-based power management strategies for HEVs but also puts forward the future and emphasis of future study, which will promote the development of energy management controller with high performance and low cost for HEVs.

  13. 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.

  14. PREDICTIVE MODELING OF ACOUSTIC SIGNALS FROM THERMOACOUSTIC POWER SENSORS (TAPS)

    SciTech Connect

    Dumm, Christopher M.; Vipperman, Jeffrey S.

    2016-06-30

    Thermoacoustic Power Sensor (TAPS) technology offers the potential for self-powered, wireless measurement of nuclear reactor core operating conditions. TAPS are based on thermoacoustic engines, which harness thermal energy from fission reactions to generate acoustic waves by virtue of gas motion through a porous stack of thermally nonconductive material. TAPS can be placed in the core, where they generate acoustic waves whose frequency and amplitude are proportional to the local temperature and radiation flux, respectively. TAPS acoustic signals are not measured directly at the TAPS; rather, they propagate wirelessly from an individual TAPS through the reactor, and ultimately to a low-power receiver network on the vessel’s exterior. In order to rely on TAPS as primary instrumentation, reactor-specific models which account for geometric/acoustic complexities in the signal propagation environment must be used to predict the amplitude and frequency of TAPS signals at receiver locations. The reactor state may then be derived by comparing receiver signals to the reference levels established by predictive modeling. In this paper, we develop and experimentally benchmark a methodology for predictive modeling of the signals generated by a TAPS system, with the intent of subsequently extending these efforts to modeling of TAPS in a liquid sodium environmen

  15. 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.

  16. Controlled test for predictive power of Lyapunov exponents: Their inability to predict epileptic seizures

    NASA Astrophysics Data System (ADS)

    Lai, Ying-Cheng; Harrison, Mary Ann F.; Frei, Mark G.; Osorio, Ivan

    2004-09-01

    Lyapunov exponents are a set of fundamental dynamical invariants characterizing a system's sensitive dependence on initial conditions. For more than a decade, it has been claimed that the exponents computed from electroencephalogram (EEG) or electrocorticogram (ECoG) signals can be used for prediction of epileptic seizures minutes or even tens of minutes in advance. The purpose of this paper is to examine the predictive power of Lyapunov exponents. Three approaches are employed. (1) We present qualitative arguments suggesting that the Lyapunov exponents generally are not useful for seizure prediction. (2) We construct a two-dimensional, nonstationary chaotic map with a parameter slowly varying in a range containing a crisis, and test whether this critical event can be predicted by monitoring the evolution of finite-time Lyapunov exponents. This can thus be regarded as a "control test" for the claimed predictive power of the exponents for seizure. We find that two major obstacles arise in this application: statistical fluctuations of the Lyapunov exponents due to finite time computation and noise from the time series. We show that increasing the amount of data in a moving window will not improve the exponents' detective power for characteristic system changes, and that the presence of small noise can ruin completely the predictive power of the exponents. (3) We report negative results obtained from ECoG signals recorded from patients with epilepsy. All these indicate firmly that, the use of Lyapunov exponents for seizure prediction is practically impossible as the brain dynamical system generating the ECoG signals is more complicated than low-dimensional chaotic systems, and is noisy.

  17. Peak power prediction of a vanadium redox flow battery

    NASA Astrophysics Data System (ADS)

    Yu, V. K.; Chen, D.

    2014-12-01

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

  18. Influence of edge additions on the synchronizability of oscillatory power networks

    NASA Astrophysics Data System (ADS)

    Yang, Li-xin; Jiang, Jun; Liu, Xiao-jun

    2016-12-01

    The influence of edge-adding number and edge-adding distance on synchronization of oscillatory power network is investigated. Here we study how the addition of new links impacts the emergence of synchrony in oscillatory power network, focusing on ring, and tree-like topologies. Numerical simulations show that the impact of distance of adding edges whether homogeneous (generators to generators or consumers to consumers) or heterogeneous (generators to consumer nodes and vice versa) edges is not obvious on the synchronizability of oscillatory power network. However, for the edge-adding number, it is observed that the bigger heterogeneous edge-adding number, the stronger synchronizability of power network will be. Furthermore, the homogeneous edge-adding number does not affect the synchronizability of oscillatory power network.

  19. 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.

  20. Power flow prediction in vibrating systems via model reduction

    NASA Astrophysics Data System (ADS)

    Li, Xianhui

    This dissertation focuses on power flow prediction in vibrating systems. Reduced order models (ROMs) are built based on rational Krylov model reduction which preserve power flow information in the original systems over a specified frequency band. Stiffness and mass matrices of the ROMs are obtained by projecting the original system matrices onto the subspaces spanned by forced responses. A matrix-free algorithm is designed to construct ROMs directly from the power quantities at selected interpolation frequencies. Strategies for parallel implementation of the algorithm via message passing interface are proposed. The quality of ROMs is iteratively refined according to the error estimate based on residual norms. Band capacity is proposed to provide a priori estimate of the sizes of good quality ROMs. Frequency averaging is recast as ensemble averaging and Cauchy distribution is used to simplify the computation. Besides model reduction for deterministic systems, details of constructing ROMs for parametric and nonparametric random systems are also presented. Case studies have been conducted on testbeds from Harwell-Boeing collections. Input and coupling power flow are computed for the original systems and the ROMs. Good agreement is observed in all cases.

  1. 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.

  2. Bundle critical power predictions under normal and abnormal conditions in pressurized water reactors

    SciTech Connect

    Lin, W.S.; Pei, B.S. ); Lee, C.H. )

    1992-06-01

    In this paper a new approach to bundle critical power predictions is presented. In addition to a very accurate critical heat flux (CHF) model, correction factors that account for the effects of grid spacers, heat flux non-uniformities, and cold walls, which are needed for critical power predictions for practical fuel bundles, are developed. By using the subchannel analysis code COBRA IIIC/MIT-1, local flow conditions needed as input to CHF correlations are obtained. Critical power is therefore obtained iteratively to ensure that the bundle power value from the subchannel analysis will cause CHF at only one point in the bundle. Good agreement with the experimental data is obtained. The accuracy is higher than that of the W-3 and EPRI-1 correlations for the limited data base used in this study. The effects of three types of fuel abnormalities, namely, local heat flux spikes, local flow blockages, and rod bowing, on bundle critical power are also analyzed. The local heat flux spikes and flow blockages have no significant influence on critical power. However, rod bowing phenomena have some effect, the severity of which depends on system pressure, the gap closure between adjacent rods, and the presence or absence of thimble tubes (cold walls). A correlation for the influence of various rod bowing phenomena on bundle critical power is developed. Good agreement with experimental data is shown.

  3. Spectral prediction model for color prints on paper with fluorescent additives.

    PubMed

    Hersch, Roger David

    2008-12-20

    I propose a model for predicting the total reflectance of color halftones printed on paper incorporating fluorescent brighteners. The total reflectance is modeled as the additive superposition of the relative fluorescent emission and the pure reflectance of the color print. The fluorescent emission prediction model accounts for both the attenuation of light by the halftone within the excitation wavelength range and for the attenuation of the fluorescent emission by the same halftone within the emission wavelength range. The model's calibration relies on reflectance measurements of the optically brightened paper and of the solid colorant patches with two illuminants, one including and one excluding the UV components. The part of the model predicting the pure reflectance relies on an ink-spreading extended Clapper-Yule model. On uniformly distributed surface coverages of cyan, magenta, and yellow halftone patches, the proposed model predicts the relative fluorescent emission with a high accuracy (mean DeltaE(94)=0.42 under a D65 standard illuminant). For optically brightened paper exhibiting a moderate fluorescence, the total reflectance prediction improves the spectral reflectance prediction mainly for highlight color halftones, comprising a proportion of paper white above 12%. Applications include the creation of improved printer characterization tables for color management purposes and the prediction of color gamuts for new combinations of optically brightened papers and inks.

  4. Graphene as conductive additives in binderless activated carbon electrodes for power enhancement of supercapacitor

    NASA Astrophysics Data System (ADS)

    Nor, N. S. M.; Deraman, M.; Suleman, M.; Norizam, M. D. M.; Basri, N. H.; Sazali, N. E. S.; Hamdan, E.; Hanappi, M. F. Y. M.; Tajuddin, N. S. M.; Othman, M. A. R.; Shamsudin, S. A.; Omar, R.

    2016-11-01

    Carbon based supercapacitor electrodes from composite of binderless activated carbon and graphene as a conductive additive were fabricated with various amount of graphene (0, 2, 4, 6, 8 and 10 wt%). Graphene was mixed in self-adhesive carbon grains produced from pre-carbonized powder derived from fibers of oil palm empty fruit bunches and converted into green monoliths (GMs). The GMs were carbonized (N2) and activated (CO2) to produce activated carbon monoliths (ACMs) electrodes. Porosity characterizations by nitrogen adsorption-desorption isotherm method shows that the pore characteristics of the ACMs are influenced by the graphene additive. The results of galvanostatic charge-discharge tests carried out on the supercapacitor cells fabricated using these electrodes shows that the addition of graphene additive (even in small amount) decreases the equivalent series resistance and enhances the specific power of the cells but significantly lowers the specific capacitance. The supercapacitor cell constructed with the electrode containing 4 wt % of graphene offers the maximum power (175 W kg-1) which corresponds to an improvement of 55%. These results demonstrate that the addition of graphene as conductive additive in activated carbon electrodes can enhance the specific power of the supercapacitor.

  5. 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

  6. 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.

  7. 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.

  8. Testcross additive and dominance effects in best linear unbiased prediction of maize single-cross performance.

    PubMed

    Bernardo, R

    1996-11-01

    Best linear unbiased prediction (BLUP) has been found to be useful in maize (Zea mays L.) breeding. The advantage of including both testcross additive and dominance effects (Intralocus Model) in BLUP, rather than only testcross additive effects (Additive Model), has not been clearly demonstrated. The objective of this study was to compare the usefulness of Intralocus and Additive Models for BLUP of maize single-cross performance. Multilocation data from 1990 to 1995 were obtained from the hybrid testing program of Limagrain Genetics. Grain yield, moisture, stalk lodging, and root lodging of untested single crosses were predicted from (1) the performance of tested single crosses and (2) known genetic relationships among the parental inbreds. Correlations between predicted and observed performance were obtained with a delete-one cross-validation procedure. For the Intralocus Model, the correlations ranged from 0.50 to 0.66 for yield, 0.88 to 0.94 for moisture, 0.47 to 0.69 for stalk lodging, and 0.31 to 0.45 for root lodging. The BLUP procedure was consistently more effective with the Intralocus Model than with the Additive Model. When the Additive Model was used instead of the Intralocus Model, the reductions in the correlation were largest for root lodging (0.06-0.35), smallest for moisture (0.00-0.02), and intermediate for yield (0.02-0.06) and stalk lodging (0.02-0.08). The ratio of dominance variance (v D) to total genetic variance (v G) was highest for root lodging (0.47) and lowest for moisture (0.10). The Additive Model may be used if prior information indicates that VD for a given trait has little contribution to VG. Otherwise, the continued use of the Intralocus Model for BLUP of single-cross performance is recommended.

  9. 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

  10. 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.

  11. Additivity property and emergence of power laws in nonequilibrium steady states.

    PubMed

    Das, Arghya; Chatterjee, Sayani; Pradhan, Punyabrata; Mohanty, P K

    2015-11-01

    We show that an equilibriumlike additivity property can remarkably lead to power-law distributions observed frequently in a wide class of out-of-equilibrium systems. The additivity property can determine the full scaling form of the distribution functions and the associated exponents. The asymptotic behavior of these distributions is solely governed by branch-cut singularity in the variance of subsystem mass. To substantiate these claims, we explicitly calculate, using the additivity property, subsystem mass distributions in a wide class of previously studied mass aggregation models as well as in their variants. These results could help in the thermodynamic characterization of nonequilibrium critical phenomena.

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

    PubMed

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

    2015-07-01

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

  13. Improving Hurricane Power Outage Prediction Models Through the Inclusion of Local Environmental Factors.

    PubMed

    McRoberts, D Brent; Quiring, Steven M; Guikema, Seth D

    2016-10-25

    Tropical cyclones can significantly damage the electrical power system, so an accurate spatiotemporal forecast of outages prior to landfall can help utilities to optimize the power restoration process. The purpose of this article is to enhance the predictive accuracy of the Spatially Generalized Hurricane Outage Prediction Model (SGHOPM) developed by Guikema et al. (2014). In this version of the SGHOPM, we introduce a new two-step prediction procedure and increase the number of predictor variables. The first model step predicts whether or not outages will occur in each location and the second step predicts the number of outages. The SGHOPM environmental variables of Guikema et al. (2014) were limited to the wind characteristics (speed and duration of strong winds) of the tropical cyclones. This version of the model adds elevation, land cover, soil, precipitation, and vegetation characteristics in each location. Our results demonstrate that the use of a new two-step outage prediction model and the inclusion of these additional environmental variables increase the overall accuracy of the SGHOPM by approximately 17%.

  14. Predicted Performances of Power Line Communication in Aircraft

    NASA Astrophysics Data System (ADS)

    Degardin, V.; Junqua, I.; Lienard, M.; Degauque, P.; Bertuol, S.; Genoulaz, J.; Dunand, M.

    2012-05-01

    The possibility of using power line communication to transmit information in a large aircraft is studied. The communication link, which has been identified and chosen in the frame of the TAUPE European project, is the cabin lighting system since its tree shape and large structure allows covering most of the other possible applications. A statistical theoretical analysis, based on the multiconductor transmission line theory, has been carried out to determine the properties of the channel transfer function. This has been done in two steps: First a simplified network was considered to outline the parameters of the network geometry playing an important role on the path loss, and then by modelling a test bench which will be used as a demonstrator. The PLC link has been modelled for predicting data rate and bit error rate, taking the EMC constraints into account.

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

    PubMed

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

    2014-11-04

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

  16. 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.

  17. 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.

  18. [Differences between experts and novices in estimations of cue predictive power in crime].

    PubMed

    García-Retamero, Rocío; Dhami, Mandeep K

    2009-08-01

    In this study, we compared experts' and novices' estimates of the power of several cues to predict residential burglary. Participants were experienced police officers and burglars, and graduates with no experience in this domain. They all estimated the weight of each cue in predicting the likelihood of a property being burgled. In addition, they ranked the cues according to how useful they would be in predicting the likelihood of burglary. Results showed that the two expert groups differed substantially in their cue weights and rankings, and the police officers were actually more similar to novices in this regard. Beyond this, the two expert groups were more consistent in their responses than novices, that is, they showed less variability in their estimates when using different response method and were more consistent with other participants from their own group. Our results extend the literature on expert-novice differences, and have implications for criminal justice policy and decision making.

  19. Short-term prediction of wind power using EMD and chaotic theory

    NASA Astrophysics Data System (ADS)

    An, Xueli; Jiang, Dongxiang; Zhao, Minghao; Liu, Chao

    2012-02-01

    Due to the strong non-linear, complexity and non-stationary characteristics of wind farm power, a hybrid prediction model with empirical mode decomposition (EMD), chaotic theory, and grey theory is constructed. The EMD is used to decompose the wind farm power into several intrinsic mode function (IMF) components and one residual component. The grey forecasting model is used to predict the residual component. For the IMF components, identify their characteristics, if it is chaotic time series use largest Lyapunov exponent prediction method to predict. If not, use grey forecasting model to predict. Prediction results of residual component and all IMF components are aggregated to produce the ultimate predicted result for wind farm power. The ultimate predicted result shows that the proposed method has good prediction accuracy, can be used for short-term prediction of wind farm power.

  20. Wind turbine power curve prediction with consideration of rotational augmentation effects

    NASA Astrophysics Data System (ADS)

    Tang, X.; Huang, X.; Sun, S.; Peng, R.

    2016-11-01

    Wind turbine power curve expresses the relationship between the rotor power and the hub wind speed. Wind turbine power curve prediction is of vital importance for power control and wind energy management. To predict power curve, the Blade Element Moment (BEM) method is used in both academic and industrial communities. Due to the limited range of angles of attack measured in wind tunnel testing and the three-dimensional (3D) rotational augmentation effects in rotating turbines, wind turbine power curve prediction remains a challenge especially at high wind speeds. This paper presents an investigation of considering the rotational augmentation effects using characterized lift and drag coefficients from 3D computational fluid dynamics (CFD) simulations coupled in the BEM method. A Matlab code was developed to implement the numerical calculation. The predicted power outputs were compared with the NREL Phase VI wind turbine measurements. The results demonstrate that the coupled method improves the wind turbine power curve prediction.

  1. 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.

  2. Predicting the occurrence of wildfires with binary structured additive regression models.

    PubMed

    Ríos-Pena, Laura; Kneib, Thomas; Cadarso-Suárez, Carmen; Marey-Pérez, Manuel

    2017-02-01

    Wildfires are one of the main environmental problems facing societies today, and in the case of Galicia (north-west Spain), they are the main cause of forest destruction. This paper used binary structured additive regression (STAR) for modelling the occurrence of wildfires in Galicia. Binary STAR models are a recent contribution to the classical logistic regression and binary generalized additive models. Their main advantage lies in their flexibility for modelling non-linear effects, while simultaneously incorporating spatial and temporal variables directly, thereby making it possible to reveal possible relationships among the variables considered. The results showed that the occurrence of wildfires depends on many covariates which display variable behaviour across space and time, and which largely determine the likelihood of ignition of a fire. The joint possibility of working on spatial scales with a resolution of 1 × 1 km cells and mapping predictions in a colour range makes STAR models a useful tool for plotting and predicting wildfire occurrence. Lastly, it will facilitate the development of fire behaviour models, which can be invaluable when it comes to drawing up fire-prevention and firefighting plans.

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

    PubMed

    Chapman, Benjamin P; Goldberg, Lewis R

    2011-09-01

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

  4. Prediction of reserves using multivariate power-normal mixture distribution

    NASA Astrophysics Data System (ADS)

    Ling, Ang Siew; Hin, Pooi Ah

    2016-10-01

    Recently, in the area on stochastic loss reserving, there are a number of papers which analyze the individual claims data using the Position Dependent Marked Poisson Process. The present paper instead uses a different type of individual data. For the i-th (1≤i≤n) customer, these individual data include the sum insured si together with the amount paid yi j and the amount ai j reported but not yet paid in the j-th (1 ≤ j ≤ 6) development year. A technique based on multivariate power-normal mixture distribution is already available for predicting the future value (yi j + 1, ai j + 1) using the present year value (yi j, ai j) and the sum insured si. Presently the above technique is improved by the transformation of distribution which is defined on the whole real line to one which is non-negative and having approximately the same first four moments as the original distribution. It is found that, for the dataset considered in this paper, the improved method gives a better estimate for the reserve when compared with the chain ladder reserve estimate. Furthermore, the method is expected to provide a fairly reliable value for the Provision of Risk Margin for Adverse Deviation (PRAD).

  5. Predicting subjective perceptions of powered tool torque reactions.

    PubMed

    Lin, Jia-Hua; McGorry, Raymond W

    2009-01-01

    Powered hand tools have the potential to produce reaction forces that may be associated with upper extremity musculoskeletal disorders. In this study, subjective ratings of discomfort and acceptability of reaction forces were collected in an attempt to identify their associations with factors such as work location, and response covariates such as grip force and tool handle displacement. Three work configurations using pistol grip and right angle pneumatic nutrunners on horizontal and vertical surfaces were set up in the laboratory. Twenty healthy right-handed male participants operated four tools at nine locations and the corresponding subjective responses were collected. The results indicate that normalized grip force during the torque buildup period was a significant factor for both subjective ratings. For the unacceptable torque reactions across the three tool configurations, the ratio of hand moment impulse over tool torque impulse was significantly greater than for the acceptable reactions. For pistol grip tools used on the vertical surface, as the working height increased 30 cm, the odds of an unacceptable rating over an acceptable rating increased 1.6 times. Prediction models for subjective ratings of discomfort and acceptability provide insight regarding either workstation design or exposure control. These models can further be used to establish exposure limits based on handle displacement and grip force.

  6. 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

  7. 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.

  8. Model predictive direct power control for active power decoupled single-phase quasi-Z -source inverter

    SciTech Connect

    Liu, Yushan; Ge, Baoming; Abu-Rub, Haitham; Sun, Hexu; Peng, Fang Zheng; Xue, Yaosuo

    2016-06-14

    In this study, the active power filter (APF) that consists of a half-bridge leg and an ac capacitor is integrated in the single-phase quasi-Z-source inverter (qZSI) in this paper to avoid the second harmonic power flowing into the dc side. The capacitor of APF buffers the second harmonic power of the load, and the ac capacitor allows highly pulsating ac voltage, so that the capacitances of both dc and ac sides can be small. A model predictive direct power control (DPC) is further proposed to achieve the purpose of this newtopology through predicting the capacitor voltage of APF at each sampling period and ensuring the APF power to track the second harmonic power of single-phase qZSI. Simulation and experimental results verify the model predictive DPC for the APF-integrated single-phase qZSI.

  9. Model predictive direct power control for active power decoupled single-phase quasi-Z -source inverter

    DOE PAGES

    Liu, Yushan; Ge, Baoming; Abu-Rub, Haitham; ...

    2016-06-14

    In this study, the active power filter (APF) that consists of a half-bridge leg and an ac capacitor is integrated in the single-phase quasi-Z-source inverter (qZSI) in this paper to avoid the second harmonic power flowing into the dc side. The capacitor of APF buffers the second harmonic power of the load, and the ac capacitor allows highly pulsating ac voltage, so that the capacitances of both dc and ac sides can be small. A model predictive direct power control (DPC) is further proposed to achieve the purpose of this newtopology through predicting the capacitor voltage of APF at eachmore » sampling period and ensuring the APF power to track the second harmonic power of single-phase qZSI. Simulation and experimental results verify the model predictive DPC for the APF-integrated single-phase qZSI.« less

  10. Bragg's rule of stopping power additivity: a compilation and summary of results

    SciTech Connect

    Thwaites, D.I.

    1983-09-01

    Stopping power additivity, as expressed by Bragg's rule, is an important concept in many practical situations involving charged particles. Its validity has been investigated in a large number of studies and the wide range of data is confusing and at times conflicting. No previous comprehensive survey of the data has been undertaken. Thus a compilation is attempted here of a hundred or so papers which have included tests of Bragg's rule. Their main results are indicated and a summary is given of the effects of chemical binding and phase on the stopping power of heavy charged particles. Such effects are confirmed on the evidence available. Chemical binding effects become more significant for materials containing low-Z constituents and as energy falls into and through the transition region. Deviations of up to 50% have been observed in atomic stopping cross sections extracted from measurements on hydrocarbons. There is still some conflicting evidence appearing on phase effects. However, in general a broad consensus is emerging indicating significant differences in H/sub 2/O and organic and similar materials. Stopping cross sections in the vapor phase are greater by up to approx. 5 or 10% at energies around those of the stopping power maximum for protons and He ions. The effects decrease as energy increases.

  11. 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.

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

    PubMed

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

    2015-07-29

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

  13. Lifetime prediction modeling of airfoils for advanced power generation

    NASA Astrophysics Data System (ADS)

    Karaivanov, Ventzislav Gueorguiev

    The use of gases produced from coal as a turbine fuel offers an attractive means for efficiently generating electric power from our Nation's most abundant fossil fuel resource. The oxy-fuel and hydrogen-fired turbine concepts promise increased efficiency and low emissions on the expense of increased turbine inlet temperature (TIT) and different working fluid. Developing the turbine technology and materials is critical to the creation of these near-zero emission power generation technologies. A computational methodology, based on three-dimensional finite element analysis (FEA) and damage mechanics is presented for predicting the evolution of creep and fatigue in airfoils. We took a first look at airfoil thermal distributions in these advanced turbine systems based on CFD analysis. The damage mechanics-based creep and fatigue models were implemented as user modified routine in commercial package ANSYS. This routine was used to visualize the creep and fatigue damage evolution over airfoils for hydrogen-fired and oxy-fuel turbines concepts, and regions most susceptible to failure were indentified. Model allows for interaction between creep and fatigue damage thus damage due to fatigue and creep processes acting separately in one cycle will affect both the fatigue and creep damage rates in the next cycle. Simulation results were presented for various thermal conductivity of the top coat. Surface maps were created on the airfoil showing the development of the TGO scale and the Al depletion of the bond coat. In conjunction with model development, laboratory-scale experimental validation was executed to evaluate the influence of operational compressive stress levels on the performance of the TBC system. TBC coated single crystal coupons were exposed isothermally in air at 900, 1000, 1100oC with and without compressive load. Exposed samples were cross-sectioned and evaluated with scanning electron microscope (SEM). Performance data was collected based on image analysis

  14. Analytical relationships for prediction of the mechanical properties of additively manufactured porous biomaterials

    PubMed Central

    Hedayati, Reza

    2016-01-01

    Abstract Recent developments in additive manufacturing techniques have motivated an increasing number of researchers to study regular porous biomaterials that are based on repeating unit cells. The physical and mechanical properties of such porous biomaterials have therefore received increasing attention during recent years. One of the areas that have revived is analytical study of the mechanical behavior of regular porous biomaterials with the aim of deriving analytical relationships that could predict the relative density and mechanical properties of porous biomaterials, given the design and dimensions of their repeating unit cells. In this article, we review the analytical relationships that have been presented in the literature for predicting the relative density, elastic modulus, Poisson's ratio, yield stress, and buckling limit of regular porous structures based on various types of unit cells. The reviewed analytical relationships are used to compare the mechanical properties of porous biomaterials based on different types of unit cells. The major areas where the analytical relationships have improved during the recent years are discussed and suggestions are made for future research directions. © 2016 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 104A: 3164–3174, 2016. PMID:27502358

  15. 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.

  16. 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

  17. 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.

  18. 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)

  19. On Application of Model Predictive Control to Power Converter with Switching

    NASA Astrophysics Data System (ADS)

    Zanma, Tadanao; Fukuta, Junichi; Doki, Shinji; Ishida, Muneaki; Okuma, Shigeru; Matsumoto, Takashi; Nishimori, Eiji

    This paper concerns a DC-DC converter control. In DC-DC converters, there exist both continuous components such as inductance, conductance and resistance and discrete ones, IGBT and MOSFET as semiconductor switching elements. Such a system can be regarded as a hybrid dynamical system. Thus, this paper presents a dc-dc control technique based on the model predictive control. Specifically, a case in which the load of the dc-dc converter changes from active to sleep is considered. In the case, a control method which makes the output voltage follow to the reference quickly in transition, and the switching frequency be constant in steady state. In addition, in applying the model predictive control to power electronics circuits, the switching characteristic of the device and the restriction condition for protection are also considered. The effectiveness of the proposed method is illustrated by comparing a conventional method through some simulation results.

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

    SciTech Connect

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

    1981-01-01

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

  1. Estimation and prediction of noise power based on variational Bayesian and adaptive ARMA time series

    NASA Astrophysics Data System (ADS)

    Zhang, Jingyi; Li, Yonggui; Zhu, Yonggang; Li, Binwu

    2014-04-01

    Estimation and prediction of noise power are very important for communication anti-jamming and efficient allocation of spectrum resources in adaptive wireless communication and cognitive radio. In order to estimate and predict the time-varying noise power caused by natural factors and jamming in the high frequency channel, Variational Bayesian algorithm and adaptive ARMA time series are proposed. Through establishing the time-varying noise power model, which controlled by the noise variance rate, the noise power can be estimated with Variational Bayesian algorithm, and the results show that the estimation error is related to observation interval. What's more, through the analysis of the correlation characteristics of the estimation power, noise power can be predicted based on adaptive ARMA time series, and the results show that it will be available to predict the noise power in next 5 intervals with the proportional error less than 0.2.

  2. 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

  3. 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.

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

    PubMed

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

    2015-09-01

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

  5. Second by second prediction of solar power generation based on cloud shadow behavior estimation near a power station

    NASA Astrophysics Data System (ADS)

    Nomura, Ryohei; Harigai, Toru; Suda, Yoshiyuki; Takikawa, Hirofumi

    2017-01-01

    Photovoltaic (PV) power generation has a particular problem for grid cooperation in that output can fluctuate due to the shadows created by clouds. If we can grasp the behavior of cloud shadows beforehand, then it may be possible to forecast output fluctuations. In this study, we want to prove if it is possible to calculate power output variation from the accumulated cloud shadow data. Cloud shadow behavior was measured from the ground by photodiodes (PDs) and the cloud shadow vector was calculated from the position and time difference. The time from the calculated cloud shadow vector to the arrival of the cloud shadow and the power generation output was calculated and compared with the actual solar power generation output. Thus, we confirmed that we can predict power generation output from a high correlation of two outputs. We found that prediction is possible, with high precision, at a short distance.

  6. 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.

  7. 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.

  8. Photovoltaic power generation for air-conditioning system based on predictive control

    SciTech Connect

    Kim, S.; Choi, J.; Park, G.; Yoo Jiyoon

    1995-12-31

    In this paper an auxiliary power supply scheme using photovoltaic power generation for air-conditioning system and its novel control strategy are proposed. The proposed auxiliary power supply system employs a boost converter, a bidirectional power converter and photovoltaic arrays. The boost converter controlled by a predictive control strategy provides maximum power track (MPT) state on the photovoltaic (PV) arrays as well as power generation facility function on the ac utility grid. Furthermore the bidirectional power converter controls the power flow balance between the loads and two different power sources according to the condition of the load power and the supplied power from photovoltaic arrays. It is shown that the maximum power tracking of the PV arrays, the unit power factor of ac utility grid and the descent input dc voltage regulation of the air-conditioning system are achieved by the proposed predictive control strategy. The proposed switching strategy for the boost converter and the bidirectional power converter are based on the predictive control with ac line current and output voltage of the PV arrays. The bidirectional power converter is suitably modulation controlled to rectify the ac source during the power shortage under the poor power generation of PV arrays or over load conditions of air conditioner. During the opposite state, the bidirectional power converter is gated to function as a regeneration inverter. Controller design procedure for the proposed approach to achieve near sinusoidal input currents under the inverter mode and the rectifier mode is detailed. Simulation results on a laboratory prototype system are discussed. Experimental results from the laboratory prototype system will be presented in the near future.

  9. 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.

  10. Fluctuations of Prestimulus Oscillatory Power Predict Subjective Perception of Tactile Simultaneity

    PubMed Central

    Halacz, Johanna; van Dijk, Hanneke; Kahlbrock, Nina; Schnitzler, Alfons

    2012-01-01

    Oscillatory activity is modulated by sensory stimulation but can also fluctuate in the absence of sensory input. Recent studies have demonstrated that such fluctuations of oscillatory activity can have substantial influence on the perception of subsequent stimuli. In the present study, we employed a simultaneity task in the somatosensory domain to study the role of prestimulus oscillatory activity on the temporal perception of 2 events. Subjects received electrical stimulations of the left and right index finger with varying stimulus onset asynchronies (SOAs) and reported their subjective perception of simultaneity, while brain activity was recorded with magnetoencephalography. With intermediate SOAs (30 and 45 ms), subjects frequently misperceived the stimulation as simultaneously. We compared neuronal oscillatory power in these conditions and found that power in the high beta band (∼20 to 40 Hz) in primary and secondary somatosensory cortex prior to the electrical stimulation predicted subjects' reports of simultaneity. Additionally, prestimulus alpha-band power influenced perception in the condition SOA 45 ms. Our results indicate that fluctuations of ongoing oscillatory activity in the beta and alpha bands shape subjective perception of physically identical stimulation. PMID:22114082

  11. Fluctuations of prestimulus oscillatory power predict subjective perception of tactile simultaneity.

    PubMed

    Lange, Joachim; Halacz, Johanna; van Dijk, Hanneke; Kahlbrock, Nina; Schnitzler, Alfons

    2012-11-01

    Oscillatory activity is modulated by sensory stimulation but can also fluctuate in the absence of sensory input. Recent studies have demonstrated that such fluctuations of oscillatory activity can have substantial influence on the perception of subsequent stimuli. In the present study, we employed a simultaneity task in the somatosensory domain to study the role of prestimulus oscillatory activity on the temporal perception of 2 events. Subjects received electrical stimulations of the left and right index finger with varying stimulus onset asynchronies (SOAs) and reported their subjective perception of simultaneity, while brain activity was recorded with magnetoencephalography. With intermediate SOAs (30 and 45 ms), subjects frequently misperceived the stimulation as simultaneously. We compared neuronal oscillatory power in these conditions and found that power in the high beta band (∼20 to 40 Hz) in primary and secondary somatosensory cortex prior to the electrical stimulation predicted subjects' reports of simultaneity. Additionally, prestimulus alpha-band power influenced perception in the condition SOA 45 ms. Our results indicate that fluctuations of ongoing oscillatory activity in the beta and alpha bands shape subjective perception of physically identical stimulation.

  12. Power Relative to Body Mass Best Predicts Change in Core Temperature During Exercise-Heat Stress.

    PubMed

    Gibson, Oliver R; Willmott, Ashley G B; James, Carl A; Hayes, Mark; Maxwell, Neil S

    2017-02-01

    Gibson, OR, Willmott, AGB, James, CA, Hayes, M, and Maxwell, NS. Power relative to body mass best predicts change in core temperature during exercise-heat stress. J Strength Cond Res 31(2): 403-414, 2017-Controlling internal temperature is crucial when prescribing exercise-heat stress, particularly during interventions designed to induce thermoregulatory adaptations. This study aimed to determine the relationship between the rate of rectal temperature (Trec) increase, and various methods for prescribing exercise-heat stress, to identify the most efficient method of prescribing isothermic heat acclimation (HA) training. Thirty-five men cycled in hot conditions (40° C, 39% R.H.) for 29 ± 2 minutes. Subjects exercised at 60 ± 9% V[Combining Dot Above]O2peak, with methods for prescribing exercise retrospectively observed for each participant. Pearson product moment correlations were calculated for each prescriptive variable against the rate of change in Trec (° C·h), with stepwise multiple regressions performed on statistically significant variables (p ≤ 0.05). Linear regression identified the predicted intensity required to increase Trec by 1.0-2.0° C between 20- and 45-minute periods and the duration taken to increase Trec by 1.5° C in response to incremental intensities to guide prescription. Significant (p ≤ 0.05) relationships with the rate of change in Trec were observed for prescriptions based on relative power (W·kg; r = 0.764), power (%Powermax; r = 0.679), rating of perceived exertion (RPE) (r = 0.577), V[Combining Dot Above]O2 (%V[Combining Dot Above]O2peak; r = 0.562), heart rate (HR) (%HRmax; r = 0.534), and thermal sensation (r = 0.311). Stepwise multiple regressions observed relative power and RPE as variables to improve the model (r = 0.791), with no improvement after inclusion of any anthropometric variable. Prescription of exercise under heat stress using power (W·kg or %Powermax) has the strongest relationship with the rate of change in

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

    PubMed

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

    2014-01-06

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

  14. Do temporal changes in vegetation structure additional to time since fire predict changes in bird occurrence?

    PubMed

    Lindenmayer, David B; Candy, Steven G; MacGregor, Christopher I; Banks, Sam C; Westgate, Martin; Ikin, Karen; Pierson, Jennifer; Tulloch, Ayesha; Barton, Philip

    2016-10-01

    Fire is a major ecological process in ecosystems globally. Its impacts on fauna can be both direct (e.g., mortality) and indirect (e.g., altered habitat), resulting in population recovery being driven by several possible mechanisms. Separating direct from indirect impacts of fire on faunal population recovery can be valuable in guiding management of biodiversity in fire-prone environments. However, resolving the influence of direct and indirect processes remains a key challenge because many processes affecting fauna can change concomitantly with time since fire. We explore the mechanisms influencing bird response to fire by posing the question, can temporal changes in vegetation structure predict changes in bird occurrence on sites, and can these be separated from other temporal changes using the surrogate of time since fire? We conducted a 12-yr study of bird and vegetation responses to fire at 124 sites across six vegetation classes in Booderee National Park, Australia. Approximately half of these sites, established in 2002, were burned by a large (>3000 ha) wildfire in 2003. To disentangle collinear effects of temporal changes in vegetation and direct demographic effects on population recovery that are subsumed by time since fire, we incorporated both longitudinal and cross-sectional vegetation effects in addition to time since fire within logistic structural equation models. We identified temporal changes in vegetation structure and richness of plant and bird species that characterized burned and unburned sites in all vegetation classes. For nine bird species, a significant component of the year trend was driven by temporal trends in one of three vegetation variables (number of understory or midstory plant species, or midstory cover). By contrast, we could not separate temporal effects between time since fire and vegetation attributes for bird species richness, reporting rate, and the occurrence of 11 other bird species. Our findings help identify species for

  15. Non-invasive prediction of blood lactate response to constant power outputs from incremental exercise tests.

    PubMed

    Sullivan, C S; Casaburi, R; Storer, T W; Wasserman, K

    1995-01-01

    We determined the ability of gas exchange analyses during incremental exercise tests (IXT) to predict blood lactate levels associated with a range of constant power output cycle ergometer tests. Twenty-seven healthy young men performed duplicate IXT and four 15-min constant power output tests at intensities ranging from moderate to very severe, before and after a training program. End-exercise blood lactate levels were approximated from superficial venous samples obtained 60 s after each constant power output test. From IXT, the power outputs corresponding to peak oxygen uptake (Wmax) and lactic acidosis threshold (WLAT), were determined. We examined the ability of four measures of exercise intensity to predict blood lactate levels for power outputs above the LAT: (1) power output (W), (2) power difference (W-WLAT), (3) power fraction (W/Wmax) and (4) power difference to delta ratio [(W-WLAT)/(Wmax-WLAT)]. Correlation coefficients were r = 0.38, 0.69, 0.75, and 0.81, respectively. The best linear regression prediction equation was: lactate (mmol.l-1) = 12.2[(W-WLAT)/(Wmax-WLAT)] + 0.7 mmol.l-1. This relationship was not significantly affected by training, despite increased values of LAT and peak oxygen uptake. Normalizing exercise intensity to the range of power outputs between WLAT and Wmax provided an estimate of blood lactate response to constant power outputs with a standard error of the estimate of 1.66 mmol.l-1.

  16. V3 net charge: additional tool in HIV-1 tropism prediction.

    PubMed

    Montagna, Claudia; De Crignis, Elisa; Bon, Isabella; Re, Maria Carla; Mezzaroma, Ivano; Turriziani, Ombretta; Graziosi, Cecilia; Antonelli, Guido

    2014-12-01

    Genotype-based algorithms are valuable tools for the identification of patients eligible for CCR5 inhibitors administration in clinical practice. Among the available methods, geno2pheno[coreceptor] (G2P) is the most used online tool for tropism prediction. This study was conceived to assess if the combination of G2P prediction with V3 peptide net charge (NC) value could improve the accuracy of tropism prediction. A total of 172 V3 bulk sequences from 143 patients were analyzed by G2P and NC values. A phenotypic assay was performed by cloning the complete env gene and tropism determination was assessed on U87_CCR5(+)/CXCR4(+) cells. Sequences were stratified according to the agreement between NC values and G2P results. Of sequences predicted as X4 by G2P, 61% showed NC values higher than 5; similarly, 76% of sequences predicted as R5 by G2P had NC values below 4. Sequences with NC values between 4 and 5 were associated with different G2P predictions: 65% of samples were predicted as R5-tropic and 35% of sequences as X4-tropic. Sequences identified as X4 by NC value had at least one positive residue at positions known to be involved in tropism prediction and positive residues in position 32. These data supported the hypothesis that NC values between 4 and 5 could be associated with the presence of dual/mixed-tropic (DM) variants. The phenotypic assay performed on a subset of sequences confirmed the tropism prediction for concordant sequences and showed that NC values between 4 and 5 are associated with DM tropism. These results suggest that the combination of G2P and NC could increase the accuracy of tropism prediction. A more reliable identification of X4 variants would be useful for better selecting candidates for Maraviroc (MVC) administration, but also as a predictive marker in coreceptor switching, strongly associated with the phase of infection.

  17. 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.

  18. 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

  19. A transdiagnostic approach to examining the incremental predictive power of emotion regulation and basic personality dimensions.

    PubMed

    Stanton, Kasey; Rozek, David C; Stasik-O'Brien, Sara M; Ellickson-Larew, Stephanie; Watson, David

    2016-10-01

    Although personality and emotion regulation abilities appear to overlap considerably, few studies have adopted an integrative approach by examining personality and emotion regulation together. Therefore, it is unclear how much incremental power emotion regulation demonstrates in predicting psychopathology beyond personality traits, and vice versa. Results from a community sample characterized by high levels of psychopathology (N = 299) indicated that personality and emotion regulation represent strongly related but distinguishable constructs, with both showing incremental power beyond the other in many cases in predicting self-reported and interview-rated psychopathology. More specifically, difficulties in responding adaptively to negative emotional experiences displayed predictive power beyond neuroticism and other personality traits in predicting internalizing psychopathology and psychoticism. Conversely, neuroticism displayed substantial incremental predictive power beyond emotion regulation and other five-factor model traits, especially for anxiety and other internalizing psychopathology. Other five-factor model traits also showed incremental predictive power in specific cases (e.g., agreeableness and conscientiousness showed specificity in predicting antagonism and disinhibition, respectively). These data provide a starting point for developing a finer-grained understanding of how emotion dysregulation and personality traits are implicated in a range of psychopathology, highlighting the value of adopting an integrative approach of examining emotion regulation and personality traits concurrently. (PsycINFO Database Record

  20. 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…

  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. 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.

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

    PubMed Central

    Rabadi, Meheroz H.; Vincent, Andrea S.

    2015-01-01

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

  4. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

  6. Smoothing of wind farm output power using prediction based flywheel energy storage system

    NASA Astrophysics Data System (ADS)

    Islam, Farzana

    Being socially beneficial, economically competitive and environment friendly, wind energy is now considered to be the world's fastest growing renewable energy source. However, the stochastic nature of wind imposes a considerable challenge in the optimal management and operation of wind power system. Wind speed prediction is critical for wind energy conversion system since it greatly influences the issues related to effective energy management, dynamic control of wind turbine, and improvement of the overall efficiency of the power generation system. This thesis focuses on integration of energy storage system with wind farm, considering wind speed prediction in the control scheme to overcome the problems associated with wind power fluctuations. In this thesis, flywheel energy storage system (FESS) with adjustable speed rotary machine has been considered for smoothing of output power in a wind farm composed of a fixed speed wind turbine generator (FSWTG). Since FESS has both active and reactive power compensation ability, it enhances the stability of the system effectively. An efficient energy management system combined with supervisory control unit (SCU) for FESS and wind speed prediction has been developed to improve the smoothing of the wind farm output effectively. Wind speed prediction model is developed by artificial neural network (ANN) which has advantages over the conventional prediction scheme including data error tolerance and ease in adaptability. The model for prediction with ANN is developed in MATLAB/Simulink and interfaced with PSCAD/EMTDC. Effectiveness of the proposed control system is illustrated using real wind speed data in various operating conditions.

  7. 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.

  8. An Operating Method Using Prediction of Photovoltaic Power for a Photovoltaic-Diesel Hybrid Power Generation System

    NASA Astrophysics Data System (ADS)

    Yamamoto, Shigehiro; Sumi, Kazuyoshi; Nishikawa, Eiichi; Hashimoto, Takeshi

    This paper describes a novel operating method using prediction of photovoltaic (PV) power for a photovoltaic-diesel hybrid power generation system. The system is composed of a PV array, a storage battery, a bi-directional inverter and a diesel engine generator (DG). The proposed method enables the system to save fuel consumption by using PV energy effectively, reducing charge and discharge energy of the storage battery, and avoiding low-load operation of the DG. The PV power is simply predicted from a theoretical equation of solar radiation and the observed PV energy for a constant time before the prediction. The amount of fuel consumption of the proposed method is compared with that of other methods by a simulation based on measurement data of the PV power at an actual PV generation system for one year. The simulation results indicate that the amount of fuel consumption of the proposed method is smaller than that of any other methods, and is close to that of the ideal operation of the DG.

  9. 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.

  10. 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…

  11. 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.

  12. 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.

  13. 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

  14. The cut-off value for interleukin 34 as an additional potential inflammatory biomarker for the prediction of the risk of diabetic complications.

    PubMed

    Zorena, Katarzyna; Jachimowicz-Duda, Olga; Wąż, Piotr

    2016-01-01

    In the present study, we have decided to evaluate whether serum interleukin 34 (IL-34) levels may have diagnostic value in predicting the risk of vascular diabetic complications. The study included 49 patients with type 2 diabetes mellitus (T2DM) and 23 high-risk group. The receiver operating characteristic (ROC) curve analysis has shown that IL-34 has more discriminatory power than C-reactive protein (CRP) for the risk of diabetic complications. The cut-off value for IL-34 was established as 91.2 pg/mL. The gist of our research was identification of IL-34 as an additional potential inflammatory biomarker for the prediction of the risk of vascular diabetic complications.

  15. 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.

  16. Improving Performance of Power Systems with Large-scale Variable Generation Additions

    SciTech Connect

    Makarov, Yuri V.; Etingov, Pavel V.; Samaan, Nader A.; Lu, Ning; Ma, Jian; Subbarao, Krishnappa; Du, Pengwei; Kannberg, Landis D.

    2012-07-22

    A power system with large-scale renewable resources, like wind and solar generation, creates significant challenges to system control performance and reliability characteristics because of intermittency and uncertainties associated with variable generation. It is important to quantify these uncertainties, and then incorporate this information into decision-making processes and power system operations. This paper presents three approaches to evaluate the flexibility needed from conventional generators and other resources in the presence of variable generation as well as provide this flexibility from a non-traditional resource – wide area energy storage system. These approaches provide operators with much-needed information on the likelihood and magnitude of ramping and capacity problems, and the ability to dispatch available resources in response to such problems.

  17. Coherent addition of high power laser diode array with a V-shape external Talbot cavity.

    PubMed

    Liu, B; Liu, Y; Braiman, Y

    2008-12-08

    We designed a V-shape external Talbot cavity for a broad-area laser diode array and demonstrated coherent laser beam combining at high power with narrow spectral linewidth. The V-shape external Talbot cavity provides good mode-discrimination and does not require a spatial filter. A multi-lobe far-field profile generated by a low filling-factor phase-locked array is confirmed by our numerical simulation.

  18. 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.

  19. 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

  20. 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.

  1. 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

  2. Contributions of the stochastic shape wake model to predictions of aerodynamic loads and power under single wake conditions

    DOE PAGES

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

    2016-10-03

    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. Furthermore, these results indicate that the stochasticmore » shape wake simulator is a valuable addition to simplified wake models when seeking to obtain higher-fidelity computationally inexpensive predictions of loads and power.« less

  3. Contributions of the stochastic shape wake model to predictions of aerodynamic loads and power under single wake conditions

    SciTech Connect

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

    2016-10-03

    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. Furthermore, 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.

  4. 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

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

    NASA Astrophysics Data System (ADS)

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

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

  6. 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.

  7. 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.

  8. Integrated fuzzy concentration addition-independent action (IFCA-IA) model outperforms two-stage prediction (TSP) for predicting mixture toxicity.

    PubMed

    Wang, Zhuang; Chen, Jingwen; Huang, Liping; Wang, Ying; Cai, Xiyun; Qiao, Xianliang; Dong, Yuying

    2009-02-01

    Mixture toxicities were determined for 12 industrial organic chemicals bearing four different modes of toxic action (MOAs) to Vibrio fischeri, to compare the predictability of the integrated fuzzy concentration addition-independent action (IFCA-IA) model and the two-stage prediction (TSP) model. Three mixtures were designed: The first and second mixtures were based on the ratios of each component at the 1% and 50% effect concentrations (EC(1) and EC(50)), respectively; and the third mixture contained an equimolar ratio of individual components. For the EC(1), EC(50) and equimolar ratio, prediction errors from the IFCA-IA model at the 50% experimental mixture effects were 0.3%, 6% and 0.6%, respectively; while for the TSP model, the corresponding errors were 2.8%, 19% and 24%, respectively. Thus, the IFCA-IA model performed better than the TSP model. The IFCA-IA model calculated two weight coefficients from the molecular structural descriptors, which weigh the relation between concentration addition (CA) and independent action (IA) through the fuzzy membership functions. Thus, MOAs are not pre-requisites for mixture toxicity prediction by the IFCA-IA approach, implying the practicability of this method in toxicity assessment of mixtures.

  9. 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

  10. 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.

  11. Impact of fitting dominance and additive effects on accuracy of genomic prediction of breeding values in layers.

    PubMed

    Heidaritabar, M; Wolc, A; Arango, J; Zeng, J; Settar, P; Fulton, J E; O'Sullivan, N P; Bastiaansen, J W M; Fernando, R L; Garrick, D J; Dekkers, J C M

    2016-10-01

    Most genomic prediction studies fit only additive effects in models to estimate genomic breeding values (GEBV). However, if dominance genetic effects are an important source of variation for complex traits, accounting for them may improve the accuracy of GEBV. We investigated the effect of fitting dominance and additive effects on the accuracy of GEBV for eight egg production and quality traits in a purebred line of brown layers using pedigree or genomic information (42K single-nucleotide polymorphism (SNP) panel). Phenotypes were corrected for the effect of hatch date. Additive and dominance genetic variances were estimated using genomic-based [genomic best linear unbiased prediction (GBLUP)-REML and BayesC] and pedigree-based (PBLUP-REML) methods. Breeding values were predicted using a model that included both additive and dominance effects and a model that included only additive effects. The reference population consisted of approximately 1800 animals hatched between 2004 and 2009, while approximately 300 young animals hatched in 2010 were used for validation. Accuracy of prediction was computed as the correlation between phenotypes and estimated breeding values of the validation animals divided by the square root of the estimate of heritability in the whole population. The proportion of dominance variance to total phenotypic variance ranged from 0.03 to 0.22 with PBLUP-REML across traits, from 0 to 0.03 with GBLUP-REML and from 0.01 to 0.05 with BayesC. Accuracies of GEBV ranged from 0.28 to 0.60 across traits. Inclusion of dominance effects did not improve the accuracy of GEBV, and differences in their accuracies between genomic-based methods were small (0.01-0.05), with GBLUP-REML yielding higher prediction accuracies than BayesC for egg production, egg colour and yolk weight, while BayesC yielded higher accuracies than GBLUP-REML for the other traits. In conclusion, fitting dominance effects did not impact accuracy of genomic prediction of breeding values in

  12. Predicting lower body power from vertical jump prediction equations for loaded jump squats at different intensities in men and women.

    PubMed

    Wright, Glenn A; Pustina, Andrew A; Mikat, Richard P; Kernozek, Thomas W

    2012-03-01

    The purpose of this study was to determine the efficacy of estimating peak lower body power from a maximal jump squat using 3 different vertical jump prediction equations. Sixty physically active college students (30 men, 30 women) performed jump squats with a weighted bar's applied load of 20, 40, and 60% of body mass across the shoulders. Each jump squat was simultaneously monitored using a force plate and a contact mat. Peak power (PP) was calculated using vertical ground reaction force from the force plate data. Commonly used equations requiring body mass and vertical jump height to estimate PP were applied such that the system mass (mass of body + applied load) was substituted for body mass. Jump height was determined from flight time as measured with a contact mat during a maximal jump squat. Estimations of PP (PP(est)) for each load and for each prediction equation were compared with criterion PP values from a force plate (PP(FP)). The PP(est) values had high test-retest reliability and were strongly correlated to PP(FP) in both men and women at all relative loads. However, only the Harman equation accurately predicted PP(FP) at all relative loads. It can therefore be concluded that the Harman equation may be used to estimate PP of a loaded jump squat knowing the system mass and peak jump height when more precise (and expensive) measurement equipment is unavailable. Further, high reliability and correlation with criterion values suggest that serial assessment of power production across training periods could be used for relative assessment of change by either of the prediction equations used in this study.

  13. Assessment of technologies for predicting insertion loss and directivity of power plant exhaust systems

    NASA Astrophysics Data System (ADS)

    Cummins, Jim R.; Loewenstein, Marshall

    2005-09-01

    Much technology exists for predicting the insertion loss, directivity and radiation of various components in a power plant. For example, the ASHRAE noise guide gives the IL and/or directivity for many duct configurations. Unfortunately, there are also many components or geometries for which there is currently no practical prediction methodology. The state of the technology for predicting insertion loss, directivity and sound radiation by power plant components, especially ducted sources, such as intake and exhaust, is reviewed with emphasis on modeling techniques and verification. Several cases where the normal prediction methods are both adequate and inadequate are presented. Suggestions are given as to methods and/or future development that could provide more accurate, reliable, or useable results.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. Lack of predictive power of trait fear and anxiety for conditioned pain modulation (CPM).

    PubMed

    Horn-Hofmann, Claudia; Priebe, Janosch A; Schaller, Jörg; Görlitz, Rüdiger; Lautenbacher, Stefan

    2016-12-01

    In recent years the association of conditioned pain modulation (CPM) with trait fear and anxiety has become a hot topic in pain research due to the assumption that such variables may explain the low CPM efficiency in some individuals. However, empirical evidence concerning this association is still equivocal. Our study is the first to investigate the predictive power of fear and anxiety for CPM by using a well-established psycho-physiological measure of trait fear, i.e. startle potentiation, in addition to two self-report measures of pain-related trait anxiety. Forty healthy, pain-free participants (female: N = 20; age: M = 23.62 years) underwent two experimental blocks in counter-balanced order: (1) a startle paradigm with affective picture presentation and (2) a CPM procedure with hot water as conditioning stimulus (CS) and contact heat as test stimulus (TS). At the end of the experimental session, pain catastrophizing (PCS) and pain anxiety (PASS) were assessed. PCS score, PASS score and startle potentiation to threatening pictures were entered as predictors in a linear regression model with CPM magnitude as criterion. We were able to show an inhibitory CPM effect in our sample: pain ratings of the heat stimuli were significantly reduced during hot water immersion. However, CPM was neither predicted by self-report of pain-related anxiety nor by startle potentiation as psycho-physiological measure of trait fear. These results corroborate previous negative findings concerning the association between trait fear/anxiety and CPM efficiency and suggest that shifting the focus from trait to state measures might be promising.

  19. Model based predictive control of a high temperature gas cooled power plant coupled to a hydrogen production facility

    NASA Astrophysics Data System (ADS)

    Rhoads, Lloyd A.

    This thesis builds upon recent studies focusing on modeling, operation, and control of high temperature gas cooled reactors. A computer model was developed, based on mass, energy, and momentum balances of control volumes throughout the plant. Several simulations of the plant behavior were conducted and their results were compared with those from the literature. Proportional control was combined with optimal control to form a time varying, adjustable gain predictive controller which adjusts the proportional gains during transients. The controller was designed to utilize control rod motions and bypass control valves to maintain desired plant conditions. An optimization scheme was introduced to efficiently solve the optimization problem formulated as part of the predictive controller operation. Several additional transients were run to examine the full plant controller performance. Multiple predictive controllers were designed and their performance was compared with a proportional controller throughout each transient. The predictive controller results confirmed the importance of proper selection of the optimal controller parameters, in particular the controller time step size and the horizon time. The well-designed proportional controllers clearly demonstrated improvements in plant performance during short time scale transients, namely a loss of secondary heat transfer transient and a step change in desired power transient. Results from long time scale transients demonstrated the capabilities of the proposed bypass control system to control electrical power production without the need for storage vessels.

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

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

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

  1. 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.

  2. Multiple-Swarm Ensembles: Improving the Predictive Power and Robustness of Predictive Models and Its Use in Computational Biology.

    PubMed

    Alves, Pedro; Liu, Shuang; Wang, Daifeng; Gerstein, Mark

    2017-04-05

    Machine learning is an integral part of computational biology, and has already shown its use in various applications, such as prognostic tests. In the last few years in the non-biological machine learning community, ensembling techniques have shown their power in data mining competitions such as the Netflix challenge; however, such methods have not found wide use in computational biology. In this work we endeavor to show how ensembling techniques can be applied to practical problems, including problems in the field of bioinformatics, and how they often outperform other machine learning techniques in both predictive power and robustness. Furthermore, we develop a methodology of ensembling, Multi-Swarm Ensemble (MSWE) by using multiple particle swarm optimizations and demonstrate its ability to further enhance the performance of ensembles.

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

    ERIC Educational Resources Information Center

    Yuksel, Ismail; Toker, Yalcin

    2013-01-01

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

  4. 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…

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

    ERIC Educational Resources Information Center

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

    2009-01-01

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

  6. 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…

  7. 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.

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

    ERIC Educational Resources Information Center

    Zhang, Li-fang; Higgins, Paul

    2008-01-01

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

  9. 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 the…

  10. The Predictive Power of Leadership to the Perception of School Trust

    ERIC Educational Resources Information Center

    Babaoglan, Emine

    2016-01-01

    The leadership of school principal and trust to school is important organizational variable for pleasure of school stakeholders and effectiveness of them. In this research these two variables are inquired according to school principal and vice principal perception. The purpose of this research is to determine predictive power of leadership to the…

  11. 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…

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

    ERIC Educational Resources Information Center

    Güngör, Semra Kiranli

    2016-01-01

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

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

    PubMed

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

    2015-10-01

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

  14. 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.

  15. 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.

  16. 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

  17. Low predictive power of peritraumatic dissociation for PTSD symptoms in accident survivors.

    PubMed

    Wittmann, Lutz; Moergeli, Hanspeter; Schnyder, Ulrich

    2006-10-01

    To test the predictive power of peritraumatic dissociation for the development of psychopathology, the authors assessed symptoms of peritraumatic dissociation (Peritraumatic Dissociative Experiences Questionnaire; PDEQ), posttraumatic stress disorder (Clinician-Administered PTSD Scale; CAPS), anxiety and depression (Hospital Anxiety and Depression Scale; HADS) in a sample of 214 accident victims 5 days postaccident (T1). Six months later (T2), CAPS and HADS were administered again. Acute stress disorder (ASD) and PTSD symptom levels were surprisingly low. In sequential regression analyses, initial reexperiencing and hyperarousal significantly predicted PTSD symptom level (T2) over several possibly confounding variables controlled for. Peritraumatic dissociation explained less than 3% of variance. For PTSD scores, 38% overall variance explanation was obtained; the variance for HADS scores was low. Possible explanations for the low-predictive power of peritraumatic dissociation for posttraumatic psychopathology in the sample are discussed.

  18. 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.

  19. 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

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

    PubMed

    Singh, Arvinder; Chandra, Amreesh

    2016-05-17

    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.

  1. 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.

  2. Validation of the FAST skating protocol to predict aerobic power in ice hockey players.

    PubMed

    Petrella, Nicholas J; Montelpare, William J; Nystrom, Murray; Plyley, Michael; Faught, Brent E

    2007-08-01

    Few studies have reported a sport-specific protocol to measure the aerobic power of ice hockey players using a predictive process. The purpose of our study was to validate an ice hockey aerobic field test on players of varying ages, abilities, and levels. The Faught Aerobic Skating Test (FAST) uses an on-ice continuous skating protocol on a course measuring 160 feet (48.8 m) using a CD to pace the skater with a beep signal to cross the starting line at each end of the course. The FAST incorporates the principle of increasing workload at measured time intervals during a continuous skating exercise. Step-wise multiple regression modelling was used to determine the estimate of aerobic power. Participants completed a maximal aerobic power test using a modified Bruce incremental treadmill protocol, as well as the on-ice FAST. Normative data were collected on 406 ice hockey players (291 males, 115 females) ranging in age from 9 to 25 y. A regression to predict maximum aerobic power was developed using body mass (kg), height (m), age (y), and maximum completed lengths of the FAST as the significant predictors of skating aerobic power (adjusted R2 = 0.387, SEE = 7.25 mL.kg-1.min-1, p < 0.0001). These results support the application of the FAST in estimating aerobic power among male and female competitive ice hockey players between the ages of 9 and 25 years.

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

    PubMed

    Wen, Chengjian; Mu, Yifen

    2015-01-01

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

  4. 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

  5. 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.

  6. 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.

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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.

  13. 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.

  14. The critical power function is dependent on the duration of the predictive exercise tests chosen.

    PubMed

    Bishop, D; Jenkins, D G; Howard, A

    1998-02-01

    The linear relationship between work accomplished (W(lim)) and time to exhaustion (t(lim)) can be described by the equation: W(lim) = a + CP x t(lim). Critical power (CP) is the slope of this line and is thought to represent a maximum rate of ATP synthesis without exhaustion, presumably an inherent characteristic of the aerobic energy system. The present investigation determined whether the choice of predictive tests would elicit significant differences in the estimated CP. Ten female physical education students completed, in random order and on consecutive days, five all-out predictive tests at preselected constant-power outputs. Predictive tests were performed on an electrically-braked cycle ergometer and power loadings were individually chosen so as to induce fatigue within approximately 1-10 mins. CP was derived by fitting the linear W(lim)-t(lim) regression and calculated three ways: 1) using the first, third and fifth W(lim)-t(lim) coordinates (I135), 2) using coordinates from the three highest power outputs (I123; mean t(lim) = 68-193 s) and 3) using coordinates from the lowest power outputs (I345; mean t(lim) = 193-485 s). Repeated measures ANOVA revealed that CPI123 (201.0+/-37.9W) > CPI135 (176.1+/-27.6W) > CPI345 (164.0+/-22.8W) (P<0.05). When the three sets of data were used to fit the hyperbolic Power-t(lim) regression, statistically significant differences between each CP were also found (P<0.05). The shorter the predictive trials, the greater the slope of the W(lim)-t(lim) regression; possibly because of the greater influence of 'aerobic inertia' on these trials. This may explain why CP has failed to represent a maximal, sustainable work rate. The present findings suggest that if CP is to represent the highest power output that an individual can maintain "for a very long time without fatigue" then CP should be calculated over a range of predictive tests in which the influence of aerobic inertia is minimised.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. Development and evaluation of an optimization-based model for power-grip posture prediction.

    PubMed

    Lee, Sang-Wook; Zhang, Xudong

    2005-08-01

    An optimization-based model for power-grip posture prediction was proposed. The model was based on the premise that the hand prehensile configuration in a power grip best conforms to the object shape. This premise was embodied by an optimization procedure that minimized the sum of distances from the finger joints to the object surface. The model was evaluated against data from an experiment that measured the grasp postures of 28 subjects having diverse anthropometry. The intra- and inter-person variabilities in grip postures were empirically assessed and used as benchmark values for model evaluation. The evaluation showed that the root-mean-square (RMS) values of angle differences between the predicted and measured postures had a 13.7 degrees grand mean (across all joints, subjects, and two cylindrical handles grasped), whereas the RMS values of the inter- and intra-person variabilities in measured postures had grand means of 13.0 degrees and 4.4 degrees , respectively. The model can be readily generalized to the prediction of postures in power-grasping objects of different shapes, and adapted for testing alternative prehensile strategies or performance criteria.

  20. 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.

  1. 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.

  2. Power prediction in mobile communication systems using an optimal neural-network structure.

    PubMed

    Gao, X M; Gao, X Z; Tanskanen, J A; Ovaska, S J

    1997-01-01

    Presents a novel neural-network-based predictor for received power level prediction in direct sequence code division multiple access (DS/CDMA) systems. The predictor consists of an adaptive linear element (Adaline) followed by a multilayer perceptron (MLP). An important but difficult problem in designing such a cascade predictor is to determine the complexity of the networks. We solve this problem by using the predictive minimum description length (PMDL) principle to select the optimal numbers of input and hidden nodes. This approach results in a predictor with both good noise attenuation and excellent generalization capability. The optimized neural networks are used for predictive filtering of very noisy Rayleigh fading signals with 1.8 GHz carrier frequency. Our results show that the optimal neural predictor can provide smoothed in-phase and quadrature signals with signal-to-noise ratio (SNR) gains of about 12 and 7 dB at the urban mobile speeds of 5 and 50 km/h, respectively. The corresponding power signal SNR gains are about 11 and 5 dB. Therefore, the neural predictor is well suitable for power control applications where ldquodelaylessrdquo noise attenuation and efficient reduction of fast fading are required.

  3. 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.

  4. 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.

  5. 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

  6. Model predictive control of a combined heat and power plant using local linear models

    SciTech Connect

    Kikstra, J.F.; Roffel, B.; Schoen, P.

    1998-10-01

    Model predictive control has been applied to control of a combined heat and power plant. One of the main features of this plant is that it exhibits nonlinear process behavior due to large throughput swings. In this application, the operating window of the plant has been divided into a number of smaller windows in which the nonlinear process behavior has been approximated by linear behavior. For each operating window, linear step weight models were developed from a detailed nonlinear first principles model, and the model prediction is calculated based on interpolation between these linear models. The model output at each operating point can then be calculated from four basic linear models, and the required control action can subsequently be calculated with the standard model predictive control approach using quadratic programming.

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

    PubMed

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

    2000-06-01

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

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

    PubMed

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

    2013-01-01

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

  9. 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

  10. 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

  11. 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

  12. Specific predictive power of automatic spider-related affective associations for controllable and uncontrollable fear responses toward spiders.

    PubMed

    Huijding, Jorg; de Jong, Peter J

    2006-02-01

    This study examined the predictive power of automatically activated spider-related affective associations for automatic and controllable fear responses. The Extrinsic Affective Simon Task (EAST; De Houwer, 2003) was used to indirectly assess automatic spider fear-related associations. The EAST and the Fear of Spiders Questionnaire (FSQ) were used to predict fear responses in 48 female students from Maastricht University with varying levels of spider fear. Results showed that: (i) the EAST best predicted automatic fear responses, whereas (ii) the FSQ best predicted strategic avoidance behavior. These results suggest that indirect measures of automatic associations may have specific predictive power for automatic fear responses.

  13. 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.

  14. 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.

  15. 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.

  16. [Failure Prediction of Power-Shift Steering Transmission Based on Oil Spectral Analysis with Wiener Process].

    PubMed

    Liu, Yong; Ma, Biao; Zheng, Chang-song; Xie, Shang-yu

    2015-09-01

    The most common methodology used in element concentration measurement and analyzing of wear particles is Atomic emission (AE) spectroscopy. As an indirect measuring method, the oil spectral data is introduced to indicate the performance degradation and the residual life prediction in the reliability evaluation of Power shift steering transmission (PSST). Stochastic methods especially the Wiener process is convenient in solving and analyzing the unitary degradation failure indicated by the oil spectral data. The oil data have been sampled in the real operating condition, and the data set has more than 50 samples taken from PSST. The mean values and time-dependent characteristics of three indicating elements are statistically obtained by the linear regression analysis. The model of the degradation and failure prediction has been proposed based on the Wiener process with the positive drift. For modeling and simulation the software R was used. Therefore, the trend curves of diffusion process with their First Hitting Time have been predicted. Through comparison, the time intervals of condition-based maintenance have been extended as 27 Mh (15.9%). This will save the cost of maintenances by eliminate the preventive maintained cycles. The advantage and novelty of the outcomes presented in the article are that the stochastic process might be applied for predicting the degradation failure occurrence and also for optimizing the maintenance intervals and the cost-benefit. As might be expected, the method can be extended to other cases of wear prediction and evaluation in complex mechanical system.

  17. 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.

  18. 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

    2016-10-05

    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.

  19. 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.

  20. 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.

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

    PubMed Central

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

    2014-01-01

    Clathrate materials have been the subject of intense interest and research for thermoelectric application. Nevertheless, from the very large number of conceivable clathrate structures, only a small fraction of them have been examined. Since the thermal conductivity of clathrates is inherently small due to their large unit cell size and open-framework structure, the current research on clathrates is focused on finding the ones with large thermoelectric power factor. Here we predict an extraordinarily large power factor for type-VIII clathrate Si46. We show the existence of a large density of closely packed elongated ellipsoidal carrier pockets near the band edges of this so far hypothetical material structure, which is higher than that of the best thermoelectric materials known today. The high crystallographic symmetry near the energy band edges for Si46-VIII clathrates is responsible for the formation of such a large number of carrier pockets. PMID:25391971

  2. 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.

  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. 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.

  5. 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.

  6. 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.

  7. Aging predictions in nuclear power plants: Crosslinked polyolefin and EPR cable insulation materials

    SciTech Connect

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

    1991-06-01

    In two earlier reports, we derived a time-temperature-dose rate superposition methodology, which, when applicable, can be used to predict cable degradation versus dose rate, temperature and exposure time. This methodology results in long-term predictive capabilities at the low dose rates appropriate to ambient nuclear power plant aging environments. The methodology was successfully applied to numerous important cable materials used in nuclear applications and the extrapolated predictions were verified by comparisons with long-term (7 to 12 year) results for similar or identical materials aged in nuclear environments. In this report, we test the methodology on three crosslinked polyolefin (CLPO) and two ethylene propylene rubber (EPR) cable insulation materials. The methodology applies to one of the CLPO materials and one of the EPR materials, allowing predictions to be made for these materials under low dose-rate, low temperature conditions. For the other materials, it is determined that, at low temperatures, a decrease in temperature at a constant radiation dose rate leads to an increase in the degradation rate for the mechanical properties. Since these results contradict the fundamental assumption underlying time-temperature-dose rate superposition, this methodology cannot be applied to such data. As indicated in the earlier reports, such anomalous results might be expected when attempting to model data taken across the crystalline melting region of semicrystalline materials. Nonetheless, the existing experimental evidence suggests that these CLPO and EPR materials have substantial aging endurance for typical reactor conditions. 28 refs., 26 figs., 3 tabs.

  8. 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.

  9. 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

  10. A power comparison of generalized additive models and the spatial scan statistic in a case-control setting

    PubMed Central

    2010-01-01

    Background A common, important problem in spatial epidemiology is measuring and identifying variation in disease risk across a study region. In application of statistical methods, the problem has two parts. First, spatial variation in risk must be detected across the study region and, second, areas of increased or decreased risk must be correctly identified. The location of such areas may give clues to environmental sources of exposure and disease etiology. One statistical method applicable in spatial epidemiologic settings is a generalized additive model (GAM) which can be applied with a bivariate LOESS smoother to account for geographic location as a possible predictor of disease status. A natural hypothesis when applying this method is whether residential location of subjects is associated with the outcome, i.e. is the smoothing term necessary? Permutation tests are a reasonable hypothesis testing method and provide adequate power under a simple alternative hypothesis. These tests have yet to be compared to other spatial statistics. Results This research uses simulated point data generated under three alternative hypotheses to evaluate the properties of the permutation methods and compare them to the popular spatial scan statistic in a case-control setting. Case 1 was a single circular cluster centered in a circular study region. The spatial scan statistic had the highest power though the GAM method estimates did not fall far behind. Case 2 was a single point source located at the center of a circular cluster and Case 3 was a line source at the center of the horizontal axis of a square study region. Each had linearly decreasing logodds with distance from the point. The GAM methods outperformed the scan statistic in Cases 2 and 3. Comparing sensitivity, measured as the proportion of the exposure source correctly identified as high or low risk, the GAM methods outperformed the scan statistic in all three Cases. Conclusions The GAM permutation testing methods

  11. 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)

  12. 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.

  13. 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.

  14. 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

  15. Unraveling the fundamental mechanisms of solvent-additive-induced optimization of power conversion efficiencies in organic photovoltaic devices

    SciTech Connect

    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

    2016-07-12

    The realization of controllable morphologies of bulk heterojunction (BHJ) in organic photovoltics (OPVs) is one of the key factors in obtaining high-efficiency devices. Here via simultaneous monitoring of the three-dimensional nanostructural modifications in BHJ correlated with the optical analysis and theoretical modeling of charge transport, we provide new insights into the fundamental mechanisms essential for the optimization of (power conversion efficiency) PCEs with additive processing. Our results demonstrate how a trace amount of diiodooctane (DIO) remarkably changes the vertical phase morphology of the active layers resulting in formation of a well-mixed donor-acceptor compact film, augments charge transfer and PCEs. In contrast, excess amount of DIO promotes a massive reordering and results loosely packed mixed phase vertical phase morphology with large clusters leading to deterioration in PCEs. 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 results show the significant of phase separation and carrier transport pathways to achieve optimal device performances.

  16. Unraveling the fundamental mechanisms of solvent-additive-induced optimization of power conversion efficiencies in organic photovoltaic devices

    DOE PAGES

    Herath, Nuradhika; Das, Sanjib; Zhu, Jiahua; ...

    2016-07-12

    The realization of controllable morphologies of bulk heterojunction (BHJ) in organic photovoltics (OPVs) is one of the key factors in obtaining high-efficiency devices. Here via simultaneous monitoring of the three-dimensional nanostructural modifications in BHJ correlated with the optical analysis and theoretical modeling of charge transport, we provide new insights into the fundamental mechanisms essential for the optimization of (power conversion efficiency) PCEs with additive processing. Our results demonstrate how a trace amount of diiodooctane (DIO) remarkably changes the vertical phase morphology of the active layers resulting in formation of a well-mixed donor-acceptor compact film, augments charge transfer and PCEs. Inmore » contrast, excess amount of DIO promotes a massive reordering and results loosely packed mixed phase vertical phase morphology with large clusters leading to deterioration in PCEs. 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 results show the significant of phase separation and carrier transport pathways to achieve optimal device performances.« less

  17. A predictive controller based on transient simulations for controlling a power plant

    NASA Astrophysics Data System (ADS)

    Svingen, B.

    2016-11-01

    A predictive governor based on an embedded, online transient simulation was commissioned at Tonstad power plant in Norway in December 2014. This governor controls each individual turbine governor by feeding them modified setpoints. Tonstad power plant consists of 4 × 160 MW + 1 × 320 MW high head Francis turbines. With a yearly production of 3888 GWh, it is the largest in Norway. The plant is a typical high head Norwegian plant with very long tunnels and correspondingly active dynamic behaviour. This new governor system continuously simulates the entire plant, and appropriate actions are taken automatically by special algorithms. The simulations are based on the method of characteristics (MOC). The governing system has been in full operational mode since December 19 2014. The testing period also included special acceptance tests to be able to deliver FRR, both on the Nordic grid and on DC cable to Denmark. Although in full operational mode, this system is still a prototype under constant development. It shows a new way of using transient analysis that may become increasingly important in the future with added power from un-regulated sources such as wind, solar and bio.

  18. 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.

  19. 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.

  20. 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.

  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. Power of screening tests for colorectal cancer enhanced by high levels of M2-PK in addition to FOBT.

    PubMed

    Zaccaro, Cristina; Saracino, Ilaria Maria; Fiorini, Giulia; Figura, Natale; Holton, John; Castelli, Valentina; Pesci, Valeria; Gatta, Luigi; Vaira, Dino

    2017-02-02

    Colorectal cancer (CRC) is a multistep process that involves adenoma-carcinoma sequence. CRC can be prevented by routine screening, which can detect precancerous lesions. The aim of this study is to clarify whether faecal occult blood test (i-FOBT), tumor M2 pyruvate kinase (t-M2-PK), and endocannabinoid system molecules (cannabinoid receptors type 1-CB1, type 2-CB2, and fatty acid amide hydrolase-FAAH) might represent better diagnostic tools, alone or in combination, for an early diagnosis of CRC. An immunochemical FOB test (i-FOBT) and quantitative ELISA stool test for t-M2-PK were performed in 127 consecutive patients during a 12 month period. Endocannabinoid system molecules and t-M2-PK expression were detected by immunostaining in healthy tissues and normal mucosa surrounding adenomatous and cancerous colon lesions. i-FOBT and t-M2-PK combination leads to a better diagnostic accuracy for pre-neoplastic and neoplastic colon lesions. T-M2-PK quantification in stool samples and in biopsy samples (immunostaining) correlates with tumourigenesis stages. CB1 and CB2 are well expressed in healthy tissues, and their expression decreases in the presence of advanced stages of carcinogenesis and disappears in CRC. FAAH signal is well expressed in normal mucosa and low-risk adenoma, and increased in high-risk adenoma and carcinoma adjacent tissues. This study shows that high levels of t-M2-PK in addition to FOBT enhance the power of a CRC screening test. Endocannabinoid system molecule expression correlates with colon carcinogenesis stages. Developing future faecal tests for their quantification must be undertaken to obtain a more accurate early non-invasive diagnosis for CRC.

  3. 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

  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

    2016-08-10

    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.

  5. Addition of an Aerosol Transmission Model to the Aeronautical Systems Division Infra-Red Emission Prediction Program (ASDIR).

    DTIC Science & Technology

    1979-03-01

    Surface Emissions. ASDIR uses a subroutine, SIGNIR, to predict IR emissions from axisymmetric turbojet , turbofan, and turboshaft engine exhaust system...PREDICTION PROGRAM (ASDIR) THESIS Presented to the Faculty of the School of Engineering of the Air Force Institute of Technology Air Training Command in...Partial Fulfillment of the Requirements for the Degree of Master of Science by Allen C. McLellan, B.S.A.E. Captain USAF Graduate Aerospace Engineering March

  6. 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.

  7. 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.

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

    NASA Technical Reports Server (NTRS)

    Berton, Jeffrey J.

    1999-01-01

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

  9. 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.

  10. 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.

  11. Power-law decay exponents: A dynamical criterion for predicting thermalization

    NASA Astrophysics Data System (ADS)

    Távora, Marco; Torres-Herrera, E. J.; Santos, Lea F.

    2017-01-01

    From the analysis of the relaxation process of isolated lattice many-body quantum systems quenched far from equilibrium, we deduce a criterion for predicting when they are certain to thermalize. It is based on the algebraic behavior ∝t-γ of the survival probability at long times. We show that the value of the power-law exponent γ depends on the shape and filling of the weighted energy distribution of the initial state. Two scenarios are explored in detail: γ ≥2 and γ <1 . Exponents γ ≥2 imply that the energy distribution of the initial state is ergodically filled and the eigenstates are uncorrelated, so thermalization is guaranteed to happen. In this case, the power-law behavior is caused by bounds in the energy spectrum. Decays with γ <1 emerge when the energy eigenstates are correlated and signal lack of ergodicity. They are typical of systems undergoing localization due to strong onsite disorder and are found also in clean integrable systems.

  12. 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

  13. Intelligent prediction of fan rotation stall in power plants based on pressure sensor data measured in-situ.

    PubMed

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

    2014-05-19

    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.

  14. Prediction of Critical Power and W′ in Hypoxia: Application to Work-Balance Modelling

    PubMed Central

    Townsend, Nathan E.; Nichols, David S.; Skiba, Philip F.; Racinais, Sebastien; Périard, Julien D.

    2017-01-01

    Purpose: Develop a prediction equation for critical power (CP) and work above CP (W′) in hypoxia for use in the work-balance (WBAL′) model. Methods: Nine trained male cyclists completed cycling time trials (TT; 12, 7, and 3 min) to determine CP and W′ at five altitudes (250, 1,250, 2,250, 3,250, and 4,250 m). Least squares regression was used to predict CP and W′ at altitude. A high-intensity intermittent test (HIIT) was performed at 250 and 2,250 m. Actual and predicted CP and W′ were used to compute W′ during HIIT using differential (WBALdiff′) and integral (WBALint′) forms of the WBAL′ model. Results: CP decreased at altitude (P < 0.001) as described by 3rd order polynomial function (R2 = 0.99). W′ decreased at 4,250 m only (P < 0.001). A double-linear function characterized the effect of altitude on W′ (R2 = 0.99). There was no significant effect of parameter input (actual vs. predicted CP and W′) on modelled WBAL′ at 2,250 m (P = 0.24). WBALdiff′ returned higher values than WBALint′ throughout HIIT (P < 0.001). During HIIT, WBALdiff′ was not different to 0 kJ at completion, at 250 m (0.7 ± 2.0 kJ; P = 0.33) and 2,250 m (−1.3 ± 3.5 kJ; P = 0.30). However, WBALint′ was lower than 0 kJ at 250 m (−0.9 ± 1.3 kJ; P = 0.058) and 2,250 m (−2.8 ± 2.8 kJ; P = 0.02). Conclusion: The altitude prediction equations for CP and W′ developed in this study are suitable for use with the WBAL′ model in acute hypoxia. This enables the application of WBAL′ modelling to training prescription and competition analysis at altitude. PMID:28386237

  15. Prediction of Critical Power and W' in Hypoxia: Application to Work-Balance Modelling.

    PubMed

    Townsend, Nathan E; Nichols, David S; Skiba, Philip F; Racinais, Sebastien; Périard, Julien D

    2017-01-01

    Purpose: Develop a prediction equation for critical power (CP) and work above CP (W') in hypoxia for use in the work-balance ([Formula: see text]) model. Methods: Nine trained male cyclists completed cycling time trials (TT; 12, 7, and 3 min) to determine CP and W' at five altitudes (250, 1,250, 2,250, 3,250, and 4,250 m). Least squares regression was used to predict CP and W' at altitude. A high-intensity intermittent test (HIIT) was performed at 250 and 2,250 m. Actual and predicted CP and W' were used to compute W' during HIIT using differential ([Formula: see text]) and integral ([Formula: see text]) forms of the [Formula: see text] model. Results: CP decreased at altitude (P < 0.001) as described by 3rd order polynomial function (R(2) = 0.99). W' decreased at 4,250 m only (P < 0.001). A double-linear function characterized the effect of altitude on W' (R(2) = 0.99). There was no significant effect of parameter input (actual vs. predicted CP and W') on modelled [Formula: see text] at 2,250 m (P = 0.24). [Formula: see text] returned higher values than [Formula: see text] throughout HIIT (P < 0.001). During HIIT, [Formula: see text] was not different to 0 kJ at completion, at 250 m (0.7 ± 2.0 kJ; P = 0.33) and 2,250 m (-1.3 ± 3.5 kJ; P = 0.30). However, [Formula: see text] was lower than 0 kJ at 250 m (-0.9 ± 1.3 kJ; P = 0.058) and 2,250 m (-2.8 ± 2.8 kJ; P = 0.02). Conclusion: The altitude prediction equations for CP and W' developed in this study are suitable for use with the [Formula: see text] model in acute hypoxia. This enables the application of [Formula: see text] modelling to training prescription and competition analysis at altitude.

  16. 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

  17. 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.

  18. 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

  19. 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...

  20. Novel Genetic Analysis for Case-Control Genome-Wide Association Studies: Quantification of Power and Genomic Prediction Accuracy

    PubMed Central

    Lee, Sang Hong; Wray, Naomi R.

    2013-01-01

    Genome-wide association studies (GWAS) are routinely conducted for both quantitative and binary (disease) traits. We present two analytical tools for use in the experimental design of GWAS. Firstly, we present power calculations quantifying power in a unified framework for a range of scenarios. In this context we consider the utility of quantitative scores (e.g. endophenotypes) that may be available on cases only or both cases and controls. Secondly, we consider, the accuracy of prediction of genetic risk from genome-wide SNPs and derive an expression for genomic prediction accuracy using a liability threshold model for disease traits in a case-control design. The expected values based on our derived equations for both power and prediction accuracy agree well with observed estimates from simulations. PMID:23977056

  1. 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

  2. Mathematical explanation of the predictive power of the X-level approach reaction noise estimator method

    PubMed Central

    2012-01-01

    The X-level Approach Reaction Noise Estimator (XARNES) method has been developed previously to study reaction noise in well mixed reaction volumes. The method is a typical moment closure method and it works by closing the infinite hierarchy of equations that describe moments of the particle number distribution function. This is done by using correlation forms which describe correlation effects in a strict mathematical way. The variable X is used to specify which correlation effects (forms) are included in the description. Previously, it was argued, in a rather informal way, that the method should work well in situations where the particle number distribution function is Poisson-like. Numerical tests confirmed this. It was shown that the predictive power of the method increases, i.e. the agreement between the theory and simulations improves, if X is increased. In here, these features of the method are explained by using rigorous mathematical reasoning. Three derivative matching theoremsare proven which show that the observed numerical behavior is generic to the method. PMID:22500492

  3. 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.

  4. 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.

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

    NASA Astrophysics Data System (ADS)

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

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

  6. 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…

  7. 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…

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

    ERIC Educational Resources Information Center

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

    2015-01-01

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

  9. Effects of TiO2 and Co2O3 combination additions on the elemental distribution and electromagnetic properties of Mn-Zn power ferrites

    NASA Astrophysics Data System (ADS)

    Yang, W. D.; Wang, Y. G.

    2015-06-01

    The effects of TiO2 and Co2O3 combination additions on the elemental distribution and electromagnetic properties of Mn-Zn power ferrites are investigated. TiO2 addition can promote Co2O3 transfer from grain boundaries to the bulk of the grains. The temperature at which the highest initial permeability μi and the lowest power losses PL appear shifts to low temperature range with the increase of Co2O3 content. Compared with the reference sample without TiO2 and Co2O3 addition, the microstructure and electromagnetic properties of Mn-Zn power ferrites can be considerably improved with suitable amounts of TiO2 and Co2O3 combination additions. At the peak temperature, the sample with the 0.1 wt% TiO2 and 0.08 wt% Co2O3 additions has an increase of 15.8% in μi to 3951, and a decrease of 22.9% in PL to 286 kW/m3. The saturation magnetic induction Bs and electrical resistivity ρ at 25 °C reach the highest values of 532 mT and 8.12 Ω m, respectively.

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. Additive clinical value of serum brain-derived neurotrophic factor for prediction of chronic heart failure outcome.

    PubMed

    Kadowaki, Shinpei; Shishido, Tetsuro; Honda, Yuki; Narumi, Taro; Otaki, Yoichiro; Kinoshita, Daisuke; Nishiyama, Satoshi; Takahashi, Hiroki; Arimoto, Takanori; Miyamoto, Takuya; Watanabe, Tetsu; Kubota, Isao

    2016-04-01

    The importance of the central nervous system in cardiovascular events has been recognized. Recently, brain-derived neurotrophic factor (BDNF), a member of the neurotrophic factor family, is involved in depression mechanisms and also in stress and anxiety. Because BDNF is reported about cardioprotective role, we elucidated whether BDNF is associated with cardiovascular events in patients with chronic heart failure (CHF). We examined serum BDNF levels in 134 patients with CHF and 23 control subjects. The patients were followed to register cardiac events for a median of 426 days. BDNF was significantly lower in CHF patients than in control subjects (25.8 ± 8.4 vs 14.7 ± 8.4, P < 0.0001). Serum BDNF was also lower in patients with cardiac events than in event-free patients (16.1 ± 8.0 vs 12.5 ± 8.5, P < 0.0001). The cutoff value of BDNF was determined by performing receiver operating characteristic curve analysis. Kaplan-Meier analysis demonstrated that patients with low levels of BDNF experienced higher rates of cardiac events than those with high levels of BDNF. Multivariate Cox hazard analysis demonstrated that low BDNF levels (≤12.4 ng/mL) were an independent prognostic factor for cardiac events (hazard ratio 2.932, 95 % confidence interval 1.622-5.301; P = 0.0004). Adding levels of BDNF to the model with BNP levels, age, and eGFR for the prediction of cardiac events yielded significant net reclassification improvement of 0.429 (P < 0.001) and an integrated discrimination improvement of 0.101 (P < 0.001). Low serum BDNF levels were found in patients with CHF, and these levels were found to be independently associated with an increased risk of cardiac events.

  15. A method to predict cavitation and the extent of damage in power plant piping. Tier 1, Cavitation erosion model: Final report

    SciTech Connect

    Wilby, J.; Mahini, R.

    1993-12-01

    Cavitation erosion damage to power plant piping systems is a serious concern; it is often difficult to detect and can lead to unscheduled repairs and costly outages. The objective of this study was to develop a mathematical model and method to predict the onset of cavitation erosion and to estimate the extent of cavitation damage. Four severity levels of cavitation erosion have been defined in the literature: incipient cavitation, critical cavitation, incipient damage and choking cavitation. The prediction method, which for the most part is empirical, is based on a variety of data including flow characteristics, sound and vibration levels, and the pitting rates of material specimens exposed to cavitation. The method relates the four cavitation levels to the orifice or valve discharge coefficient for a baseline pressure and size. Scale factors make it possible to extrapolate to specific plant pressures and sizes. Currently, prediction coefficients are available for orifices, and butterfly, globe, cone, ball and gate valves. They are also available for bends and elbows. Other components are excluded due to the paucity of data. Because the accuracy of the method depends to a large extent on the amount of available test data, components are categorized according to three classes of reliability, with orifices having the highest rating of the components considered. In order to enhance the confidence in the prediction method and extend the range of application to include other components, it is recommended that predictions be validated where possible and that additional data be acquired.

  16. An effects addition model based on bioaccumulation of metals from exposure to mixtures of metals can predict chronic mortality in the aquatic invertebrate Hyalella azteca.

    PubMed

    Norwood, Warren P; Borgmann, Uwe; Dixon, D George

    2013-07-01

    Chronic toxicity tests of mixtures of 9 metals and 1 metalloid (As, Cd, Co, Cr, Cu, Mn, Ni, Pb, Tl, and Zn) at equitoxic concentrations over an increasing concentration range were conducted with the epibenthic, freshwater amphipod Hyalella azteca. The authors conducted 28-d, water-only tests. The bioaccumulation trends changed for 8 of the elements in exposures to mixtures of the metals compared with individual metal exposures. The bioaccumulation of Co and Tl were affected the most. These changes may be due to interactions between all the metals as well as interactions with waterborne ligands. A metal effects addition model (MEAM) is proposed as a more accurate method to assess the impact of mixtures of metals and to predict chronic mortality. The MEAM uses background-corrected body concentration to predict toxicity. This is important because the chemical characteristics of different waters can greatly alter the bioavailability and bioaccumulation of metals, and interactions among metals for binding at the site of action within the organism can affect body concentration. The MEAM accurately predicted toxicity in exposures to mixtures of metals, and predicted results were within a factor of 1.1 of the observed data, using 24-h depurated body concentrations. The traditional concentration addition model overestimated toxicity by a factor of 2.7.

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

    PubMed Central

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

    2015-01-01

    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

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

    PubMed

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

    2015-04-01

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

  19. Predicting speech intelligibility based on the signal-to-noise envelope power ratio after modulation-frequency selective processing.

    PubMed

    Jørgensen, Søren; Dau, Torsten

    2011-09-01

    A model for predicting the intelligibility of processed noisy speech is proposed. The speech-based envelope power spectrum model has a similar structure as the model of Ewert and Dau [(2000). J. Acoust. Soc. Am. 108, 1181-1196], developed to account for modulation detection and masking data. The model estimates the speech-to-noise envelope power ratio, SNR(env), at the output of a modulation filterbank and relates this metric to speech intelligibility using the concept of an ideal observer. Predictions were compared to data on the intelligibility of speech presented in stationary speech-shaped noise. The model was further tested in conditions with noisy speech subjected to reverberation and spectral subtraction. Good agreement between predictions and data was found in all cases. For spectral subtraction, an analysis of the model's internal representation of the stimuli revealed that the predicted decrease of intelligibility was caused by the estimated noise envelope power exceeding that of the speech. The classical concept of the speech transmission index fails in this condition. The results strongly suggest that the signal-to-noise ratio at the output of a modulation frequency selective process provides a key measure of speech intelligibility.

  20. 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.

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

    USGS Publications Warehouse

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

    2013-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

  3. 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.

  4. 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.

  5. 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.

  6. 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.

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

    PubMed

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

    2010-08-01

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

  8. 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.

  9. 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.

  10. 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

  11. Short-term prediction of Betula airborne pollen concentration in Vigo (NW Spain) using logistic additive models and partially linear models

    NASA Astrophysics Data System (ADS)

    Cotos-Yáñez, Tomas R.; Rodríguez-Rajo, F. J.; Jato, M. V.

    Betula pollen is a common cause of pollinosis in localities in NW Spain and between 13% and 60% of individuals who are immunosensitive to pollen grains respond positively to its allergens. It is important in the case of all such people to be able to predict pollen concentrations in advance. We therefore undertook an aerobiological study in the city of Vigo (Pontevedra, Spain) from 1995 to 2001, using a Hirst active-impact pollen trap (VPPS 2000) situated in the city centre. Vigo presents a temperate maritime climate with a mean annual temperature of 14.9 °C and 1,412 mm annual total precipitation. This paper analyses two ways of quantifying the prediction of pollen concentration: first by means of a generalized additive regression model with the object of predicting whether the series of interest exceeds a certain threshold; second using a partially linear model to obtain specific prediction values for pollen grains. Both models use a self-explicative part and another formed by exogenous meteorological factors. The models were tested with data from 2001 (year in which the total precipitation registered was almost twice the climatological average overall during the flowering period), which were not used in formulating the models. A highly satisfactory classification and good forecasting results were achieved with the first and second approaches respectively. The estimated line taking into account temperature and a calm S-SW wind, corresponds to the real line recorded during 2001, which gives us an idea of the proposed model's validity.

  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.

    2017-01-01

    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. Validity of the running anaerobic sprint test for assessing anaerobic power and predicting short-distance performances.

    PubMed

    Zagatto, Alessandro M; Beck, Wladimir R; Gobatto, Claudio A

    2009-09-01

    The purpose of this study was to investigate the reliability and validity of the running anaerobic sprint test (RAST) in anaerobic assessment and predicting short-distance performance. Forty members of the armed forces were recruited for this study (age 19.78 +/- 1.18 years; body mass 70.34 +/- 8.10 kg; height 1.76 +/- 0.53 m; body fat 15.30 +/- 5.65 %). The RAST test was applied to six 35-meter maximal running performances with a 10-second recovery between each run; the peak power, mean power, and the fatigue index were measured. The study was divided in two stages. The first stage investigated the reliability of the RAST using a test-retest method; the second stage aimed to evaluate the validity of the RAST comparing the results with the Wingate test and running performances of 35, 50, 100, 200, and 400 m. There were not significant differences between test-retest scores in the first stage of the study (p > 0.05) and were found significant correlations between these variables (intraclass correlation coefficient approximately = 0.88). The RAST had significant correlations with the Wingate test (peak power r = 0.46; mean power r = 0.53; fatigue index r = 0.63) and 35, 50, 100, 200, and 400 m performances scores (p < 0.05). The advantage of using the RAST for measuring anaerobic power is that it allows for the execution of movements more specific to sporting events that use running as the principal style of locomotion, is easily applied and low cost, and due to its simplicity can easily be incorporated into routine training. We concluded that this procedure is reliable and valid, and can be used to measure running anaerobic power and predict short-distance performances.

  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. 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.

  16. 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.

  17. A priori performance prediction in pharmaceutical wet granulation: testing the applicability of the nucleation regime map to a formulation with a broad size distribution and dry binder addition.

    PubMed

    Kayrak-Talay, Defne; Litster, James D

    2011-10-14

    In this study, Hapgood's nucleation regime map (Hapgood et al., 2003) was tested for a formulation that consists of an active pharmaceutical ingredient (API) of broad size distribution and a fine dry binder. Gabapentin was used as the API and hydroxypropyl cellulose (HPC) as the dry binder with deionized water as the liquid binder. The formulation was granulated in a 6l Diosna high shear granulator. The effect of liquid addition method (spray, dripping), liquid addition rate (29-245 g/min), total liquid content (2, 4 and 10%), and impeller speed (250 and 500 rpm) on the granule size distribution and lump formation were investigated. Standard methods were successfully used to characterize the process parameters (spray drop size, spray geometry and powder surface velocity) for calculating the dimensionless spray flux. However, the addition of dry binder had a very strong effect on drop penetration time that could not be predicted from simple capillary flow considerations. This is most likely due to preferential liquid penetration into the fine pores related to the dry binder particles and subsequent partial softening and dissolution of the binder. For systems containing a dry binder or other amorphous powders, it is recommended that drop penetration time be measured directly for the blended formulation and then scaled to the drop size during spraying. Using these approaches to characterize the key dimensionless groups (dimensionless spray flux and drop penetration time), Hapgood's nucleation regime map was successfully used to predict a priori the effect of process conditions on the quality of the granule size distribution as measured by lump formation and the span of the size distribution, both before and after wet massing for range of conditions studied. Wider granule size distributions and higher amount of lumps were obtained moving from intermediate to mechanical dispersion regime. Addition of the liquid in the dripping mode gave the broadest size distribution

  18. Selectivity Guidelines and a Reductive Elimination-Based Model for Predicting the Stereochemical Course of Conjugate Addition Reactions of Organocuprates to γ-Alkoxy-α,β-Enoates

    PubMed Central

    Kireev, Artem S.; Manpadi, Madhuri; Kornienko, Alexander

    2008-01-01

    Current models used to predict the stereochemical outcome of organocopper conjugate addition processes focus on the nucleophilic addition step as stereochemistry-determining. Recent kinetic, NMR, kinetic isotope effect and theoretical density functional studies strongly support the proposal that stereochemical preferences in these processes are dictated by the reductive elimination step, transforming CuIII to CuI intermediates. A new model that considers various steric and stereoelectronic factors involved in the transition state of the reductive elimination step is proposed and then used to interpret the results of systematic studies of arylcuprate conjugate addition reactions with cis and trans γ-alkoxy-α,β-enoates. The results give rise to the following selectivity guidelines for this process. To achieve high anti-addition diastereoselectivities the use of trans esters with a bulky non-alkoxy substituent at the γ-position is recommended. While stereoelectronics disfavor syn-addition, a judicious choice of properly sized γ-substituents may lead to the predominant formation of syn-products, especially with cis enoates. However, high syn-selelectivities may be achieved by using γ-amino-α,β-enoates. PMID:16555814

  19. Selectivity guidelines and a reductive elimination-based model for predicting the stereochemical course of conjugate addition reactions of organocuprates to gamma-alkoxy-alpha,beta-enoates.

    PubMed

    Kireev, Artem S; Manpadi, Madhuri; Kornienko, Alexander

    2006-03-31

    Current models used to predict the stereochemical outcome of organocopper conjugate addition processes focus on the nucleophilic addition step as stereochemistry-determining. Recent kinetic, NMR, kinetic isotope effect, and theoretical density functional studies strongly support the proposal that stereochemical preferences in these processes are dictated by the reductive elimination step, transforming Cu(III) to Cu(I) intermediates. A new model that considers various steric and stereoelectronic factors involved in the transition state of the reductive elimination step is proposed and then used to interpret the results of systematic studies of arylcuprate conjugate addition reactions with cis and trans gamma-alkoxy-alpha,beta-enoates. The results give rise to the following selectivity guidelines for this process. To achieve high anti-addition diastereoselectivities the use of trans esters with a bulky nonalkoxy substituent at the gamma-position is recommended. While stereoelectronics disfavor syn-addition, a judicious choice of properly sized gamma-substituents may lead to the predominant formation of syn-products, especially with cis enoates. However, high syn-selectivities may be achieved by using gamma-amino-alpha,beta-enoates.

  20. The Measurement of Reading Comprehension: How Not to Trade Construct Validity for Predictive Power.

    ERIC Educational Resources Information Center

    Daneman, Meredyth

    1982-01-01

    The effectiveness of a measure of the processing capacity of working memory, called the reading span test, is demonstrated in predicting performance and understanding individual differences in reading comprehension. (Author/PN)

  1. 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

  2. Powering and Motion Predictions of High Speed Sea Lift (HSSL) Ships

    DTIC Science & Technology

    2007-06-01

    and Motion Predictions of High Speed Sea Lift (HSSL) Ships Joseph Gorski and Ronald Miller Pablo Carrica, Mani Kandasamy , and Fred Stem US Naval...Carrica, P.M., R. Wilson, R. Noack, T. Xing, M. Kandasamy , J. Shao, N. Sakamoto, and F. Stem, "A Dynamic Overset, Single- Figure 5. Model 5594 centerhull...experience is limited. Miller, R., P. Carrica, M. Kandasamy , T. Xing, J. Gorski, and F. Consequently, computational tools are needed to predict Stem

  3. 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.

  4. Prestimulus alpha power predicts fidelity of sensory encoding in perceptual decision making.

    PubMed

    Lou, Bin; Li, Yun; Philiastides, Marios G; Sajda, Paul

    2014-02-15

    Pre-stimulus α power has been shown to correlate with the behavioral accuracy of perceptual decisions. In most cases, these correlations have been observed by comparing α power for different behavioral outcomes (e.g. correct vs incorrect trials). In this paper we investigate such covariation within the context of behaviorally-latent fluctuations in task-relevant post-stimulus neural activity. Specially we consider variations of pre-stimulus α power with post-stimulus EEG components in a two alternative forced choice visual discrimination task. EEG components, discriminative of stimulus class, are identified using a linear multivariate classifier and only the variability of the components for correct trials (regardless of stimulus class, and for nominally identical stimuli) are correlated with the corresponding pre-stimulus α power. We find a significant relationship between the mean and variance of the pre-stimulus α power and the variation of the trial-to-trial magnitude of an early post-stimulus EEG component. This relationship is not seen for a later EEG component that is also discriminative of stimulus class and which has been previously linked to the quality of evidence driving the decision process. Our results suggest that early perceptual representations, rather than temporally later neural correlates of the perceptual decision, are modulated by pre-stimulus state.

  5. 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.

  6. 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

  7. Online identification of lithium-ion battery parameters based on an improved equivalent-circuit model and its implementation on battery state-of-power prediction

    NASA Astrophysics Data System (ADS)

    Feng, Tianheng; Yang, Lin; Zhao, Xiaowei; Zhang, Huidong; Qiang, Jiaxi

    2015-05-01

    In battery management system (BMS), equivalent-circuit model (ECM) is commonly used to simulate battery dynamics. However, there always is a contradiction between model simplicity and accuracy. A simple model is usually unable to reflect all the dynamic effects of the battery, which may bring errors to parameter identification. A complex model, however, always has too many parameters to be identified and may have parameter divergence problem. This paper tries to solve this problem with a novel ECM by adding a moving average (MA) noise to the one resistor-capacity (RC) circuit model. It can accurately capture the battery dynamics and retain a simple topology. A recursive extended least squares (RELS) algorithm is applied to online identify the ECM parameters, which shows a high accuracy in the experiments. In addition, a battery state-of-power (SOP) prediction algorithm is derived based on the proposed ECM. It considers both the voltage and current limitations of the battery, and offers a two-level prediction of the battery peak power capabilities.

  8. 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

  9. 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.

  10. 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.

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

    NASA Astrophysics Data System (ADS)

    Jing, Fengmei; Zhang, Liang; Yang, Zhong

    2012-06-01

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

  12. Use of Interplanetary Radio Scintillation Power Spectra in Predicting Geomagnetic Disturbances.

    DTIC Science & Technology

    1977-10-31

    COCOA -Cross array at 34.3 MHz located at Clark Lake Radio Observatory near Borrego Springs, California and synoptic data on 33 sources were reduced to...yield scintillation index (band-pass integrated IPS power) for each source. In 1976, COCOA -Cross observations at 34.3 MHz were supplemented by 38 MHz

  13. Midfrontal conflict-related theta-band power reflects neural oscillations that predict behavior.

    PubMed

    Cohen, Michael X; Donner, Tobias H

    2013-12-01

    Action monitoring and conflict resolution require the rapid and flexible coordination of activity in multiple brain regions. Oscillatory neural population activity may be a key physiological mechanism underlying such rapid and flexible network coordination. EEG power modulations of theta-band (4-8 Hz) activity over the human midfrontal cortex during response conflict have been proposed to reflect neural oscillations that support conflict detection and resolution processes. However, it has remained unclear whether this frequency-band-specific activity reflects neural oscillations or nonoscillatory responses (i.e., event-related potentials). Here, we show that removing the phase-locked component of the EEG did not reduce the strength of the conflict-related modulation of the residual (i.e., non-phase-locked) theta power over midfrontal cortex. Furthermore, within-subject regression analyses revealed that the non-phase-locked theta power was a significantly better predictor of the conflict condition than was the time-domain phase-locked EEG component. Finally, non-phase-locked theta power showed robust and condition-specific (high- vs. low-conflict) cross-trial correlations with reaction time, whereas the phase-locked component did not. Taken together, our results indicate that most of the conflict-related and behaviorally relevant midfrontal EEG signal reflects a modulation of ongoing theta-band oscillations that occurs during the decision process but is not phase-locked to the stimulus or to the response.

  14. 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.

  15. 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…

  16. 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…

  17. 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…

  18. 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…

  19. 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.

  20. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-11-01

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

  2. 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.

  3. 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.

  4. Prediction of a Newbuilding Proce of the Bulk Carriers based on Gross Tonnage GT and Main Engine Power

    NASA Astrophysics Data System (ADS)

    Cepowska, Żaneta; Cepowski, Tomasz

    2017-03-01

    The paper presents mathematical relationships that allow us to forecast the newbuilding price of new bulk carriers, based on data concerning vessels built in 2005-2015. The presented approximations allow us to estimate the price based on a gross tonnage capacity and a main engine power The approximations were developed using linear regression and the theory of artificial neural networks. The presented relations have practical application for estimation of bulk carrier newbuilding price needed in preliminary parametric design of the ship. It follows from the above that the use of artificial neural networks to predict the price of a bulk carrier brings more accurate solutions than linear regression.

  5. 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

  6. 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

  7. 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.

  8. Uncertainties in predicting structure-borne sound power input into buildings.

    PubMed

    Gibbs, B M

    2013-05-01

    There has been a steady development of methods of measurement and prediction of structure-borne noise in buildings, particularly over the last two decades. In proposing and evaluating these methods, a major consideration has been the likely trade-off between accuracy and simplicity. Structure-borne sound transmission is a more complicated process than airborne sound transmission, but practitioners seek methods of prediction for the former, which are as straightforward as for the latter. In this paper a description is given of a study of multi-contact sources in buildings. The study concentrates on measurement and calculation procedures for sources and calculation procedures for receiver structures, particularly lightweight building elements. Although the study is not exhaustive, the findings point to the limitations of simplified methods, specifically the uncertainties likely as a result of reducing the data sets and computational effort, and the discrepancies resulting from simplifying assumptions.

  9. Maintenance personnel performance simulation (MAPPS): a model for predicting maintenance performance reliability in nuclear power plants

    SciTech Connect

    Knee, H.E.; Krois, P.A.; Haas, P.M.; Siegel, A.I.; Ryan, T.G.

    1983-01-01

    The NRC has developed a structured, quantitative, predictive methodology in the form of a computerized simulation model for assessing maintainer task performance. Objective of the overall program is to develop, validate, and disseminate a practical, useful, and acceptable methodology for the quantitative assessment of NPP maintenance personnel reliability. The program was organized into four phases: (1) scoping study, (2) model development, (3) model evaluation, and (4) model dissemination. The program is currently nearing completion of Phase 2 - Model Development.

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

    PubMed

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

    2016-08-01

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

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

    NASA Technical Reports Server (NTRS)

    Johnson, Paul

    2007-01-01

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

  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. 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.

  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. 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.

  17. 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.

  18. Transient stability enhancement of modern power grid using predictive Wide-Area Monitoring and Control

    NASA Astrophysics Data System (ADS)

    Yousefian, Reza

    This dissertation presents a real-time Wide-Area Control (WAC) designed based on artificial intelligence for large scale modern power systems transient stability enhancement. The WAC using the measurements available from Phasor Measurement Units (PMUs) at generator buses, monitors the global oscillations in the system and optimally augments the local excitation system of the synchronous generators. The complexity of the power system stability problem along with uncertainties and nonlinearities makes the conventional modeling non-practical or inaccurate. In this work Reinforcement Learning (RL) algorithm on the benchmark of Neural Networks (NNs) is used to map the nonlinearities of the system in real-time. This method different from both the centralized and the decentralized control schemes, employs a number of semi-autonomous agents to collaborate with each other to perform optimal control theory well-suited for WAC applications. Also, to handle the delays in Wide-Area Monitoring (WAM) and adapt the RL toward the robust control design, Temporal Difference (TD) is proposed as a solver for RL problem or optimal cost function. However, the main drawback of such WAC design is that it is challenging to determine if an offline trained network is valid to assess the stability of the power system once the system is evolved to a different operating state or network topology. In order to address the generality issue of NNs, a value priority scheme is proposed in this work to design a hybrid linear and nonlinear controllers. The algorithm so-called supervised RL is based on mixture of experts, where it is initialized by linear controller and as the performance and identification of the RL controller improves in real-time switches to the other controller. This work also focuses on transient stability and develops Lyapunov energy functions for synchronous generators to monitor the stability stress of the system. Using such energies as a cost function guarantees the convergence

  19. The Power of Learning Goal Orientation in Predicting Student Mathematics Achievement

    ERIC Educational Resources Information Center

    Lin, Chuan-Ju; Hung, Pi-Hsia; Lin, Su-Wei; Lin, Bor-Hung; Lin, Fou-Lai

    2009-01-01

    The teaching and learning of mathematics in schools has drawn tremendous attention since the education reform in Taiwan. In addition to assessing cognitive abilities, Taiwan Assessment of Student Achievement in Mathematics (TASA-MAT) collects background information to help depict average student achievement in schools in an educational context.…

  20. EEG biomarkers in major depressive disorder: discriminative power and prediction of treatment response.

    PubMed

    Olbrich, Sebastian; Arns, Martijn

    2013-10-01

    Major depressive disorder (MDD) has high population prevalence and is associated with substantial impact on quality of life, not least due to an unsatisfactory time span of sometimes several weeks from initiation of treatment to clinical response. Therefore extensive research focused on the identification of cost-effective and widely available electroencephalogram (EEG)-based biomarkers that not only allow distinguishing between patients and healthy controls but also have predictive value for treatment response for a variety of treatments. In this comprehensive overview on EEG research on MDD, biomarkers that are either assessed at baseline or during the early course of treatment and are helpful in discriminating patients from healthy controls and assist in predicting treatment outcome are reviewed, covering recent decades up to now. Reviewed markers include quantitative EEG (QEEG) measures, connectivity measures, EEG vigilance-based measures, sleep-EEG-related measures and event-related potentials (ERPs). Further, the value and limitations of these different markers are discussed. Finally, the need for integrated models of brain function and the necessity for standardized procedures in EEG biomarker research are highlighted to enhance future research in this field.

  1. An Assessment of the Model of Concentration Addition for Predicting the Estrogenic Activity of Chemical Mixtures in Wastewater Treatment Works Effluents

    PubMed Central

    Thorpe, Karen L.; Gross-Sorokin, Melanie; Johnson, Ian; Brighty, Geoff; Tyler, Charles R.

    2006-01-01

    The effects of simple mixtures of chemicals, with similar mechanisms of action, can be predicted using the concentration addition model (CA). The ability of this model to predict the estrogenic effects of more complex mixtures such as effluent discharges, however, has yet to be established. Effluents from 43 U.K. wastewater treatment works were analyzed for the presence of the principal estrogenic chemical contaminants, estradiol, estrone, ethinylestradiol, and nonylphenol. The measured concentrations were used to predict the estrogenic activity of each effluent, employing the model of CA, based on the relative potencies of the individual chemicals in an in vitro recombinant yeast estrogen screen (rYES) and a short-term (14-day) in vivo rainbow trout vitellogenin induction assay. Based on the measured concentrations of the four chemicals in the effluents and their relative potencies in each assay, the calculated in vitro and in vivo responses compared well and ranged between 3.5 and 87 ng/L of estradiol equivalents (E2 EQ) for the different effluents. In the rYES, however, the measured E2 EQ concentrations in the effluents ranged between 0.65 and 43 ng E2 EQ/L, and they varied against those predicted by the CA model. Deviations in the estimation of the estrogenic potency of the effluents by the CA model, compared with the measured responses in the rYES, are likely to have resulted from inaccuracies associated with the measurement of the chemicals in the extracts derived from the complex effluents. Such deviations could also result as a consequence of interactions between chemicals present in the extracts that disrupted the activation of the estrogen response elements in the rYES. E2 EQ concentrations derived from the vitellogenic response in fathead minnows exposed to a series of effluent dilutions were highly comparable with the E2 EQ concentrations derived from assessments of the estrogenic potency of these dilutions in the rYES. Together these data support the

  2. An assessment of the model of concentration addition for predicting the estrogenic activity of chemical mixtures in wastewater treatment works effluents.

    PubMed

    Thorpe, Karen L; Gross-Sorokin, Melanie; Johnson, Ian; Brighty, Geoff; Tyler, Charles R

    2006-04-01

    The effects of simple mixtures of chemicals, with similar mechanisms of action, can be predicted using the concentration addition model (CA). The ability of this model to predict the estrogenic effects of more complex mixtures such as effluent discharges, however, has yet to be established. Effluents from 43 U.K. wastewater treatment works were analyzed for the presence of the principal estrogenic chemical contaminants, estradiol, estrone, ethinylestradiol, and nonylphenol. The measured concentrations were used to predict the estrogenic activity of each effluent, employing the model of CA, based on the relative potencies of the individual chemicals in an in vitro recombinant yeast estrogen screen (rYES) and a short-term (14-day) in vivo rainbow trout vitellogenin induction assay. Based on the measured concentrations of the four chemicals in the effluents and their relative potencies in each assay, the calculated in vitro and in vivo responses compared well and ranged between 3.5 and 87 ng/L of estradiol equivalents (E2 EQ) for the different effluents. In the rYES, however, the measured E2 EQ concentrations in the effluents ranged between 0.65 and 43 ng E2 EQ/L, and they varied against those predicted by the CA model. Deviations in the estimation of the estrogenic potency of the effluents by the CA model, compared with the measured responses in the rYES, are likely to have resulted from inaccuracies associated with the measurement of the chemicals in the extracts derived from the complex effluents. Such deviations could also result as a consequence of interactions between chemicals present in the extracts that disrupted the activation of the estrogen response elements in the rYES. E2 EQ concentrations derived from the vitellogenic response in fathead minnows exposed to a series of effluent dilutions were highly comparable with the E2 EQ concentrations derived from assessments of the estrogenic potency of these dilutions in the rYES. Together these data support the

  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. Predicting the sound power and impact of a wastewater treatment plant.

    PubMed

    De Heyder, B; Ockier, P; Jansen, R; Huiberts, R

    2001-01-01

    Several process units at a wastewater treatment plant (WWTP) can produce a significant level of sound and thus induce sound nuisance for nearby residents. The risk for sound nuisance should be considered by making a prognosis of sound impact in an early project phase (planning, design). A prognosis requires information with respect to the sound characteristics of the different process units. This paper reports the development of empirical models for the sound power of relevant process units in the water line at Aquafin WWTPs. The used methodology for model derivation and validation allowed us to minimize the required number of measurements. Besides the methodology, the paper describes in detail the derivation and validation of the empirical model for the splashing water of screw pumps. Also the use of all the derived empirical models to determine the sound impact of a wastewater treatment plant at close distance is illustrated with a case-study.

  5. On the impact of power corrections in the prediction of B → K *μ+μ- observables

    NASA Astrophysics Data System (ADS)

    Descotes-Genon, Sébastien; Hofer, Lars; Matias, Joaquim; Virto, Javier

    2014-12-01

    The recent LHCb angular analysis of the exclusive decay B → K * μ + μ - has indicated significant deviations from the Standard Model expectations. Accurate predictions can be achieved at large K *-meson recoil for an optimised set of observables designed to have no sensitivity to hadronic input in the heavy-quark limit at leading order in α s . However, hadronic uncertainties reappear through non-perturbative ΛQCD /m b power corrections, which must be assessed precisely. In the framework of QCD factorisation we present a systematic method to include factorisable power corrections and point out that their impact on angular observables depends on the scheme chosen to define the soft form factors. Associated uncertainties are found to be under control, contrary to earlier claims in the literature. We also discuss the impact of possible non-factorisable power corrections, including an estimate of charm-loop effects. We provide results for angular observables at large recoil for two different sets of inputs for the form factors, spelling out the different sources of theoretical uncertainties. Finally, we comment on a recent proposal to explain the anomaly in B → K * μ + μ - observables through charm-resonance effects, and we propose strategies to test this proposal identifying observables and kinematic regions where either the charm-loop model can be disentangled from New Physics effects or the two options leave different imprints.

  6. Electronic coarse graining enhances the predictive power of molecular simulation allowing challenges in water physics to be addressed

    NASA Astrophysics Data System (ADS)

    Cipcigan, Flaviu S.; Sokhan, Vlad P.; Crain, Jason; Martyna, Glenn J.

    2016-12-01

    One key factor that limits the predictive power of molecular dynamics simulations is the accuracy and transferability of the input force field. Force fields are challenged by heterogeneous environments, where electronic responses give rise to biologically important forces such as many-body polarisation and dispersion. The importance of polarisation in the condensed phase was recognised early on, as described by Cochran in 1959 [Philosophical Magazine 4 (1959) 1082-1086] [32]. Currently in molecular simulation, dispersion forces are treated at the two-body level and in the dipole limit, although the importance of three-body terms in the condensed phase was demonstrated by Barker in the 1980s [Phys. Rev. Lett. 57 (1986) 230-233] [72]. One approach for treating both polarisation and dispersion on an equal basis is to coarse grain the electrons surrounding a molecular moiety to a single quantum harmonic oscillator (cf. Hirschfelder, Curtiss and Bird 1954 [The Molecular Theory of Gases and Liquids (1954)] [37]). The approach, when solved in strong coupling beyond the dipole limit, gives a description of long-range forces that includes two- and many-body terms to all orders. In the last decade, the tools necessary to implement the strong coupling limit have been developed, culminating in a transferable model of water with excellent predictive power across the phase diagram. Transferability arises since the environment automatically identifies the important long range interactions, rather than the modeller through a limited set of expressions. Here, we discuss the role of electronic coarse-graining in predictive multiscale materials modelling and describe the first implementation of the method in a general purpose molecular dynamics software: QDO_MD.

  7. ADME evaluation in drug discovery. 2. Prediction of partition coefficient by atom-additive approach based on atom-weighted solvent accessible surface areas.

    PubMed

    Hou, T J; Xu, X J

    2003-01-01

    A novel method for the calculations of 1-octanol/water partition coefficient (log P) of organic molecules has been presented here. The method, SLOGP v1.0, estimates the log P values by summing the contribution of atom-weighted solvent accessible surface areas (SASA) and correction factors. Altogether 100 atom/group types were used to classify atoms with different chemical environments, and two correlation factors were used to consider the intermolecular hydrophobic interactions and intramolecular hydrogen bonds. Coefficient values for 100 atom/group and two correction factors have been derived from a training set of 1850 compounds. The parametrization procedure for different kinds of atoms was performed as follows: first, the atoms in a molecule were defined to different atom/group types based on SMARTS language, and the correction factors were determined by substructure searching; then, SASA for each atom/group type was calculated and added; finally, multivariate linear regression analysis was applied to optimize the hydrophobic parameters for different atom/group types and correction factors in order to reproduce the experimental log P. The correlation based on the training set gives a model with the correlation coefficient (r) of 0.988, the standard deviation (SD) of 0.368 log units, and the absolute unsigned mean error of 0.261. Comparison of various procedures of log P calculations for the external test set of 138 organic compounds demonstrates that our method bears very good accuracy and is comparable or even better than the fragment-based approaches. Moreover, the atom-additive approach based on SASA was compared with the simple atom-additive approach based on the number of atoms. The calculated results show that the atom-additive approach based on SASA gives better predictions than the simple atom-additive one. Due to the connection between the molecular conformation and the molecular surface areas, the atom-additive model based on SASA may be a more

  8. Protein function prediction and annotation in an integrated environment powered by web services (AFAWE).

    PubMed

    Jöcker, Anika; Hoffmann, Fabian; Groscurth, Andreas; Schoof, Heiko

    2008-10-15

    Many sequenced genes are mainly annotated through automatic transfer of annotation from similar sequences. Manual comparison of results or intermediate results from different tools can help avoid wrong annotations and give hints to the function of a gene even if none of the automated tools could return any result. AFAWE simplifies the task of manual functional annotation by running different tools and workflows for automatic function prediction and displaying the results in a way that facilitates comparison. Because all programs are executed as web services, AFAWE is easily extensible and can directly query primary databases, thereby always using the most up-to-date data sources. Visual filters help to distinguish trustworthy results from non-significant results. Furthermore, an interface to add detailed manual annotation to each gene is provided, which can be displayed to other users.

  9. 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.

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

    DOEpatents

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

    2013-04-09

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

  11. Cell-line selectivity improves the predictive power of pharmacogenomic analyses and helps identify NADPH as biomarker for ferroptosis sensitivity

    PubMed Central

    Shimada, Kenichi; Hayano, Miki; Pagano, Nen; Stockwell, Brent

    2016-01-01

    Precision medicine in oncology requires not only identification of cancer-associated mutations, but also effective drugs for each cancer genotype, which is still a largely unsolved problem. One approach for the latter challenge has been large-scale testing of small molecules in genetically characterized cell lines. We hypothesized that compounds with high cell-line-selective lethality exhibited consistent results across such pharmacogenomic studies. We analyzed the compound sensitivity data of 6,259 lethal compounds from the NCI-60 project. 2,565 cell-line-selective lethal compounds were identified and grouped into 18 clusters based on their GI50 profiles across the 60 cell lines, which were shown to represent distinct mechanisms of action. Further transcriptome analysis revealed a biomarker, NADPH abundance, for predicting sensitivity to ferroptosis-inducing compounds, which we experimentally validated. In summary, incorporating cell-line selectivity filters improves the predictive power of pharmacogenomic analyses and enables discovery of biomarkers that predict the sensitivity of cells to specific cell death inducers. PMID:26853626

  12. Cell-Line Selectivity Improves the Predictive Power of Pharmacogenomic Analyses and Helps Identify NADPH as Biomarker for Ferroptosis Sensitivity.

    PubMed

    Shimada, Kenichi; Hayano, Miki; Pagano, Nen C; Stockwell, Brent R

    2016-02-18

    Precision medicine in oncology requires not only identification of cancer-associated mutations but also effective drugs for each cancer genotype, which is still a largely unsolved problem. One approach for the latter challenge has been large-scale testing of small molecules in genetically characterized cell lines. We hypothesized that compounds with high cell-line-selective lethality exhibited consistent results across such pharmacogenomic studies. We analyzed the compound sensitivity data of 6,259 lethal compounds from the NCI-60 project. A total of 2,565 cell-line-selective lethal compounds were identified and grouped into 18 clusters based on their median growth inhibitory GI50 profiles across the 60 cell lines, which were shown to represent distinct mechanisms of action. Further transcriptome analysis revealed a biomarker, NADPH abundance, for predicting sensitivity to ferroptosis-inducing compounds, which we experimentally validated. In summary, incorporating cell-line-selectivity filters improves the predictive power of pharmacogenomic analyses and enables discovery of biomarkers that predict the sensitivity of cells to specific cell death inducers.

  13. 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.

  14. Determination of Aerobic Power Through a Specific Test for Taekwondo - A Predictive Equation Model

    PubMed Central

    Louro, Hugo; Matias, Ricardo; Brito, João; Costa, Aldo M.

    2016-01-01

    Abstract Our aim was to verify the concurrent validity of a maximal taekwondo specific test (TST) to predict VO2max through an explanatory model. Seventeen elite male taekwondo athletes (age: 17.59 ± 4.34 years; body height: 1.72 ± 6.5 m; body mass: 61.3 ± 8.7 kg) performed two graded maximal exercise tests on different days: a 20 m multistage shuttle run test (SRT) and an incremental TST. We recorded test time, VO2max, ventilation, a heart rate and time to exhaustion. Significant differences were found between observed and estimated VO2max values [F (2, 16) = 5.77, p < 0.01]; post-hoc subgroup analysis revealed the existence of significant differences (p = 0.04) between the estimated VO2max value in the SRT and the observed value recorded in the TST (58.4 ± 6.4 ml/kg/min and 52.6 ± 5.2 ml/kg/min, respectively). Our analysis also revealed a moderate correlation between both testing protocols regarding VO2max (r = 0.70; p = 0.005), test time (r = 0.77; p = 0.02) and ventilation (r = 0.69; p = 0.03). There was no proportional bias in the mean difference (t = -1.04; p = 0.313), and there was a level of agreement between both tests. An equation/model was used to estimate VO2max during the TST based on the mean heart rate, test time, body height and mass, which explained 74.3% of the observed VO2max variability. A moderate correlation was found between the observed and predicted VO2max values in the taekwondo TST (r = 0.74, p = 0.001). Our results suggest that an incremental specific test estimates VO2max of elite taekwondo athletes with acceptable concurrent validity. PMID:28149417

  15. 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

  16. Determination of Aerobic Power Through a Specific Test for Taekwondo - A Predictive Equation Model.

    PubMed

    Rocha, Fernando P S; Louro, Hugo; Matias, Ricardo; Brito, João; Costa, Aldo M

    2016-12-01

    Our aim was to verify the concurrent validity of a maximal taekwondo specific test (TST) to predict VO2max through an explanatory model. Seventeen elite male taekwondo athletes (age: 17.59 ± 4.34 years; body height: 1.72 ± 6.5 m; body mass: 61.3 ± 8.7 kg) performed two graded maximal exercise tests on different days: a 20 m multistage shuttle run test (SRT) and an incremental TST. We recorded test time, VO2max, ventilation, a heart rate and time to exhaustion. Significant differences were found between observed and estimated VO2max values [F (2, 16) = 5.77, p < 0.01]; post-hoc subgroup analysis revealed the existence of significant differences (p = 0.04) between the estimated VO2max value in the SRT and the observed value recorded in the TST (58.4 ± 6.4 ml/kg/min and 52.6 ± 5.2 ml/kg/min, respectively). Our analysis also revealed a moderate correlation between both testing protocols regarding VO2max (r = 0.70; p = 0.005), test time (r = 0.77; p = 0.02) and ventilation (r = 0.69; p = 0.03). There was no proportional bias in the mean difference (t = -1.04; p = 0.313), and there was a level of agreement between both tests. An equation/model was used to estimate VO2max during the TST based on the mean heart rate, test time, body height and mass, which explained 74.3% of the observed VO2max variability. A moderate correlation was found between the observed and predicted VO2max values in the taekwondo TST (r = 0.74, p = 0.001). Our results suggest that an incremental specific test estimates VO2max of elite taekwondo athletes with acceptable concurrent validity.

  17. 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

  18. Model measurement based identification of Francis turbine vortex rope parameters for prototype part load pressure and power pulsation prediction

    NASA Astrophysics Data System (ADS)

    Manderla, M.; Weber, W.; Koutnik, J.

    2016-11-01

    Pressure and power fluctuations of hydro-electric power plants in part-load operation are an important measure for the quality of the power which is delivered to the electrical grid. It is well known that the unsteadiness is driven by the flow patterns in the draft tube where a vortex rope is present. However, until today the equivalent vortex rope parameters for common numerical 1D-models are a major source of uncertainty. In this work, a new optimization-based grey box method for experimental vortex rope modelling and parameter identification is presented. The combination of analytical vortex rope and test rig modelling and the usage of dynamic measurements allow the identification of the unknown vortex rope parameters. Upscaling from model to prototype size is achieved via existing nondimensional parameters. In this work, a new experimental setup and system identification method is proposed which are suitable for the determination of the full set of part load vortex rope parameters in the lab. For the vortex rope, a symmetric model with cavity compliance, bulk viscosity and two pressure excitation sources is developed and implemented which shows the best correspondence with available measurement data. Due to the non-dimensional parameter definition, scaling is possible. This finally provides a complete method for the prediction of prototype part-load pressure and power oscillations. Since the proposed method is based on a simple limited control domain, limited modelling effort and also small modelling uncertainties are some major advantages. Due to the generality of the approach, a future application to other operating conditions such as full load will be straightforward.

  19. 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.

  20. Long-Latency Reductions in Gamma Power Predict Hemodynamic Changes That Underlie the Negative BOLD Signal

    PubMed Central

    Harris, Samuel; Bruyns-Haylett, Michael; Kennerley, Aneurin; Zheng, Ying; Martin, Chris; Jones, Myles; Redgrave, Peter; Berwick, Jason

    2015-01-01

    Studies that use prolonged periods of sensory stimulation report associations between regional reductions in neural activity and negative blood oxygenation level-dependent (BOLD) signaling. However, the neural generators of the negative BOLD response remain to be characterized. Here, we use single-impulse electrical stimulation of the whisker pad in the anesthetized rat to identify components of the neural response that are related to “negative” hemodynamic changes in the brain. Laminar multiunit activity and local field potential recordings of neural activity were performed concurrently with two-dimensional optical imaging spectroscopy measuring hemodynamic changes. Repeated measurements over multiple stimulation trials revealed significant variations in neural responses across session and animal datasets. Within this variation, we found robust long-latency decreases (300 and 2000 ms after stimulus presentation) in gamma-band power (30–80 Hz) in the middle-superficial cortical layers in regions surrounding the activated whisker barrel cortex. This reduction in gamma frequency activity was associated with corresponding decreases in the hemodynamic responses that drive the negative BOLD signal. These findings suggest a close relationship between BOLD responses and neural events that operate over time scales that outlast the initiating sensory stimulus, and provide important insights into the neurophysiological basis of negative neuroimaging signals. PMID:25788681

  1. Predicting compliance with command hallucinations: anger, impulsivity and appraisals of voices' power and intent.

    PubMed

    Bucci, Sandra; Birchwood, Max; Twist, Laura; Tarrier, Nicholas; Emsley, Richard; Haddock, Gillian

    2013-06-01

    Command hallucinations are experienced by 33-74% of people who experience voices, with varying levels of compliance reported. Compliance with command hallucinations can result in acts of aggression, violence, suicide and self-harm; the typical response however is non-compliance or appeasement. Two factors associated with such dangerous behaviours are anger and impulsivity, however few studies have examined their relationship with compliance to command hallucinations. The current study aimed to examine the roles of anger and impulsivity on compliance with command hallucinations in people diagnosed with a psychotic disorder. The study was a cross-sectional design and included individuals who reported auditory hallucinations in the past month. Subjects completed a variety of self-report questionnaire measures. Thirty-two people experiencing command hallucinations, from both in-patient and community settings, were included. The tendency to appraise the voice as powerful, to be impulsive, to experience anger and to regulate anger were significantly associated with compliance with command hallucinations to do harm. Two factors emerged as significant independent predictors of compliance with command hallucinations; omnipotence and impulsivity. An interaction between omnipotence and compliance with commands, via a link with impulsivity, is considered and important clinical factors in the assessment of risk when working with clients experiencing command hallucinations are recommended. The data is highly suggestive and warrants further investigation with a larger sample.

  2. 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.

  3. Bacterial Resistance Studies Using In Vitro Dynamic Models: the Predictive Power of the Mutant Prevention and Minimum Inhibitory Antibiotic Concentrations

    PubMed Central

    Strukova, Elena N.; Shlykova, Darya S.; Portnoy, Yury A.; Kozyreva, Varvara K.; Edelstein, Mikhail V.; Dovzhenko, Svetlana A.; Kobrin, Mikhail B.; Zinner, Stephen H.

    2013-01-01

    In light of the concept of the mutant selection window, i.e., the range between the MIC and the mutant prevention concentration (MPC), MPC-related pharmacokinetic indices should be more predictive of bacterial resistance than the respective MIC-related indices. However, experimental evidence of this hypothesis remains limited and contradictory. To examine the predictive power of the ratios of the area under the curve (AUC24) to the MPC and the MIC, the selection of ciprofloxacin-resistant mutants of four Escherichia coli strains with different MPC/MIC ratios was studied. Each organism was exposed to twice-daily ciprofloxacin for 3 days at AUC24/MIC ratios that provide peak antibiotic concentrations close to the MIC, between the MIC and the MPC, and above the MPC. Resistant E. coli was intensively enriched at AUC24/MPCs from 1 to 10 h (AUC24/MIC from 60 to 360 h) but not at the lower or higher AUC24/MPC and AUC24/MIC ratios. AUC24/MPC and AUC24/MIC relationships of the areas under the time courses of ciprofloxacin-resistant E. coli (AUBCM) were bell-shaped. A Gaussian-like function fits the AUBCM-AUC24/MPC and AUBCM-AUC24/MIC data combined for all organisms (r2 = 0.69 and 0.86, respectively). The predicted anti-mutant AUC24/MPC ratio was 58 ± 35 h, and the respective AUC24/MIC ratio was 1,080 ± 416 h. Although AUC24/MPC was less predictive of strain-independent E. coli resistance than AUC24/MIC, the established anti-mutant AUC24/MPC ratio was closer to values reported for Staphylococcus aureus (60 to 69 h) than the respective AUC24/MIC ratio (1,080 versus 200 to 240 h). This implies that AUC24/MPC might be a better interspecies predictor of bacterial resistance than AUC24/MIC. PMID:23896481

  4. 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.

  5. 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

  6. The power of DNA double-strand break (DSB) repair testing to predict breast cancer susceptibility.

    PubMed

    Keimling, Marlen; Deniz, Miriam; Varga, Dominic; Stahl, Andreea; Schrezenmeier, Hubert; Kreienberg, Rolf; Hoffmann, Isabell; König, Jochem; Wiesmüller, Lisa

    2012-05-01

    Most presently known breast cancer susceptibility genes have been linked to DSB repair. To identify novel markers that may serve as indicators for breast cancer risk, we performed DSB repair analyses using a case-control design. Thus, we examined 35 women with defined familial history of breast and/or ovarian cancer (first case group), 175 patients with breast cancer (second case group), and 245 healthy women without previous cancer or family history of breast cancer (control group). We analyzed DSB repair in peripheral blood lymphocytes (PBLs) by a GFP-based test system using 3 pathway-specific substrates. We found increases of microhomology-mediated nonhomologous end joining (mmNHEJ) and nonconservative single-strand annealing (SSA) in women with familial risk vs. controls (P=0.0001-0.0022) and patients with breast cancer vs. controls (P=0.0004-0.0042). Young age (<50) at initial diagnosis of breast cancer, which could be indicative of genetic predisposition, was associated with elevated SSA using two different substrates, amounting to similar odds ratios (ORs=2.54-4.46, P=0.0059-0.0095) as for familial risk (ORs=2.61-4.05, P=0.0007-0.0045). These findings and supporting validation data underscore the great potential of detecting distinct DSB repair activities in PBLs as method to estimate breast cancer susceptibility beyond limitations of genotyping and to predict responsiveness to therapeutics targeting DSB repair-dysfunctional tumors.

  7. 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.

  8. Market Powers Predict Reciprocal Grooming in Golden Snub-Nosed Monkeys (Rhinopithecus roxellana)

    PubMed Central

    Guo, Song-Tao; Zhao, Da-Peng; Zhang, Peng; Huang, Kang; Li, Bao-Guo

    2012-01-01

    Social grooming is a common form of affiliative behavior in primates. Biological market theory suggests that grooming can be traded either for grooming or other social commodities and services. When no other services are exchanged, grooming is predicted to be approximately reciprocated within a dyad. In contrast, the amount of reciprocal grooming should decrease as other offered services increase. We studied grooming patterns between polygamous male and female in golden snub-nosed monkeys (Rhinopithecus roxellana) from the Qinling Mountains of central China and found that about 29.7% of grooming bouts were reciprocated. However, the durations of grooming bouts offered and returned was asymmetrical within dyads. In bisexual dyads, more grooming was initiated by females than males, which became more pronounced as the number of females per one-male unit increased. The rate of copulation per day for each female was positively correlated with the total duration of grooming time females invested in males.. Females without an infant (non-mothers) directed more grooming towards females with an infant (mothers) and were significantly more likely to be non-reciprocated. There was a significant negative relationship between non-mother and mother grooming duration and the rate of infants per female in each one-male unit. High-ranking females also received more grooming from low-ranking females than vice versa. The rate of food-related aggressive interactions was per day for low-ranking females was negatively correlated with the duration of grooming that low-ranking females gave to high-ranking females. Our results showed that grooming reciprocation in R. roxellana was discrepancy. This investment-reciprocity rate could be explained by the exchange of other social services in lieu of grooming. PMID:22590611

  9. 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.

  10. 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

  11. 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.

  12. Addition and Subtraction Theory of TCM Using Xiao-Chaihu-Decoction and Naturopathy in Predicting Survival Outcomes of Primary Liver Cancer Patients: A Prospective Cohort Study

    PubMed Central

    Dai, Min; Yang, Yue-Wu; Guo, Wen-Hai; Wang, Feng-Lin; Xiao, Ge-Min; Li, Yang-Mei

    2016-01-01

    To investigate the therapeutic effect of combined Xiao-Chaihu-Decoction and naturopathic medicine therapy on survival outcomes of patients' PLC. In XCHD group (n = 76), patients were treated with Xiao-Chaihu-Decoction in accordance with the addition and subtraction theory of TCM; in NM group (n = 89), patients were managed by naturopathic medicine; in combined group (n = 70), the same volume of Xiao-Chaihu-Decoction combined with naturopathic medicine procedures was applied. There were no evident statistical differences of age, gender, KPS score, body weight, smoking status, AFP levels, HbsAg status, TBIL levels, tumor diameters, and numbers among different groups, showing comparability among groups. No significant difference was found regarding the total remission rate and stability rate of tumors in patients treated by Xiao-Chaihu-Decoction and naturopathic medicine, except the combined therapy. KPS scores were significantly improved after treatment among groups. After treatment, 52.8% cases maintained a stable or slight increase in weight, of which 42.1%, 48.3%, and 70.0% cases maintained weight stably in the XCHD group, NM group, and combined treatment group, respectively. Xiao-Chaihu-Decoction associated with naturopathy may predict improved prognostic outcomes in PLC patients, along with improved remission and stability rates, increased KPS scores, and stable weight maintenance. PMID:27843477

  13. Application of computational chemistry methods to the prediction of chirality and helical twisting power in liquid crystal systems

    NASA Astrophysics Data System (ADS)

    Noto, Anthony G.; Marshall, Kenneth L.

    2005-08-01

    Until recently, it has not been possible to determine, with any real certainty, a complete picture of "chirality" (absolute configuration, optical rotation direction, and helical twisting power) for new chiral compounds without first synthesizing, purifying, characterizing, and testing every new material. Recent advances in computational chemistry now allow the prediction of certain key chiral molecular properties prior to synthesis, which opens the possibility of predetermining the "chiroptical" properties of new liquid crystal dopants and mixtures for advanced optical and photonics applications. A key element to this activity was the development of both the chirality index (G0) by Osipov et al., and the scaled chirality index (G0S) by Solymosi et al., that can be used as a "figure of merit" for molecular chirality. Promising correlations between G0S and both circular dichroism (CD) and the helical twisting power (HTP) of a chiral dopant in a liquid crystal host have been shown by Neal et al., Osipov, and Kuball. Our work improves the predictive capabilities of G0S by taking into account the actual mass of each atom in the molecule in the calculations; in previous studies the mass of each atom was assumed to be equal. This "weighted" scaled chirality index (G0SW) was calculated and correlated to existing experimental HTP data for each member of a series of existing, well-known chiral compounds. The computed HTP using G0SW for these model systems correlated to the experimental data with remarkable accuracy. Weighted, scaled chiral indices were also calculated for the first time for a series of novel chiral transition metal dithiolene dyes for near-IR liquid crystal device applications.

  14. Ground-based remote sensing profiling and numerical weather prediction model to manage nuclear power plants meteorological surveillance in Switzerland

    NASA Astrophysics Data System (ADS)

    Calpini, B.; Ruffieux, D.; Bettems, J.-M.; Hug, C.; Huguenin, P.; Isaak, H.-P.; Kaufmann, P.; Maier, O.; Steiner, P.

    2011-08-01

    The meteorological surveillance of the four nuclear power plants in Switzerland is of first importance in a densely populated area such as the Swiss Plateau. The project "Centrales Nucléaires et Météorologie" CN-MET aimed at providing a new security tool based on one hand on the development of a high resolution numerical weather prediction (NWP) model. The latter is providing essential nowcasting information in case of a radioactive release from a nuclear power plant in Switzerland. On the other hand, the model input over the Swiss Plateau is generated by a dedicated network of surface and upper air observations including remote sensing instruments (wind profilers and temperature/humidity passive microwave radiometers). This network is built upon three main sites ideally located for measuring the inflow/outflow and central conditions of the main wind field in the planetary boundary layer over the Swiss Plateau, as well as a number of surface automatic weather stations (AWS). The network data are assimilated in real-time into the fine grid NWP model using a rapid update cycle of eight runs per day (one forecast every three hours). This high resolution NWP model has replaced the former security tool based on in situ observations (in particular one meteorological mast at each of the power plants) and a local dispersion model. It is used to forecast the dynamics of the atmosphere in the planetary boundary layer (typically the first 4 km above ground layer) and over a time scale of 24 h. This tool provides at any time (e.g. starting at the initial time of a nuclear power plant release) the best picture of the 24-h evolution of the air mass over the Swiss Plateau and furthermore generates the input data (in the form of simulated values substituting in situ observations) required for the local dispersion model used at each of the nuclear power plants locations. This paper is presenting the concept and two validation studies as well as the results of an emergency

  15. Ground-based remote sensing profiling and numerical weather prediction model to manage nuclear power plants meteorological surveillance in Switzerland

    NASA Astrophysics Data System (ADS)

    Calpini, B.; Ruffieux, D.; Bettems, J.-M.; Hug, C.; Huguenin, P.; Isaak, H.-P.; Kaufmann, P.; Maier, O.; Steiner, P.

    2011-01-01

    The meteorological surveillance of the four nuclear power plants in Switzerland is of first importance in a densely populated area such as the Swiss Plateau. The project "Centrales Nucléaires et Météorologie" CN-MET aimed at providing a new security tool based on one hand on the development of a high resolution numerical weather prediction (NWP) model. The latter is providing essential nowcasting information in case of a radioactive release from a nuclear power plant in Switzerland. On the other hand, the model input over the Swiss Plateau is generated by a dedicated network of surface and upper air observations including remote sensing instruments (wind profilers and temperature/humidity passive microwave radiometers). This network is built upon three main sites ideally located for measuring the inflow/outflow and central conditions of the main wind field in the planetary boundary layer over the Swiss Plateau, as well as a number of surface automatic weather stations (AWS). The network data are assimilated in real-time into the fine grid NWP model using a rapid update cycle of eight runs per day (one forecast every 3 h). This high resolution NWP model has replaced the former security tool based on in situ observations (in particular one meteorological mast at each of the power plant) and a local dispersion model. It is used to forecast the dynamics of the atmosphere in the planetary boundary layer (typically the first 4 km above ground layer) and over a time scale of 24 h. This tool provides at any time (e.g. starting at the initial time of a nuclear power plant release) the best picture of the 24-h evolution of air mass over the Swiss Plateau and furthermore generates the input data (in the form of simulated values substituting in situ observations) required for the local dispersion model used at each of the nuclear power plants locations. This paper is presenting the concept and two validation studies as well as the results of an emergency response exercise

  16. Characteristics of voxel prediction power in full-brain Granger causality analysis of fMRI data

    NASA Astrophysics Data System (ADS)

    Garg, Rahul; Cecchi, Guillermo A.; Rao, A. Ravishankar

    2011-03-01

    Functional neuroimaging research is moving from the study of "activations" to the study of "interactions" among brain regions. Granger causality analysis provides a powerful technique to model spatio-temporal interactions among brain regions. We apply this technique to full-brain fMRI data without aggregating any voxel data into regions of interest (ROIs). We circumvent the problem of dimensionality using sparse regression from machine learning. On a simple finger-tapping experiment we found that (1) a small number of voxels in the brain have very high prediction power, explaining the future time course of other voxels in the brain; (2) these voxels occur in small sized clusters (of size 1-4 voxels) distributed throughout the brain; (3) albeit small, these clusters overlap with most of the clusters identified with the non-temporal General Linear Model (GLM); and (4) the method identifies clusters which, while not determined by the task and not detectable by GLM, still influence brain activity.

  17. The Power of Personality: The Comparative Validity of Personality Traits, Socioeconomic Status, and Cognitive Ability for Predicting Important Life Outcomes.

    PubMed

    Roberts, Brent W; Kuncel, Nathan R; Shiner, Rebecca; Caspi, Avshalom; Goldberg, Lewis R

    2007-12-01

    The ability of personality traits to predict important life outcomes has traditionally been questioned because of the putative small effects of personality. In this article, we compare the predictive validity of personality traits with that of socioeconomic status (SES) and cognitive ability to test the relative contribution of personality traits to predictions of three critical outcomes: mortality, divorce, and occupational attainment. Only evidence from prospective longitudinal studies was considered. In addition, an attempt was made to limit the review to studies that controlled for important background factors. Results showed that the magnitude of the effects of personality traits on mortality, divorce, and occupational attainment was indistinguishable from the effects of SES and cognitive ability on these outcomes. These results demonstrate the influence of personality traits on important life outcomes, highlight the need to more routinely incorporate measures of personality into quality of life surveys, and encourage further research about the developmental origins of personality traits and the processes by which these traits influence diverse life outcomes.

  18. 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.

  19. 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.

  20. 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.

  1. 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. PMID:27818593

  2. A short fuse after alcohol: implicit power associations predict aggressiveness after alcohol consumption in young heavy drinkers with limited executive control.

    PubMed

    Wiers, Reinout W; Beckers, Leen; Houben, Katrijn; Hofmann, Wilhelm

    2009-09-01

    This study tested a hypothesis derived from recent dual-process models, which conceptualize behavior as the interplay of associative and Executive Control (EC) processes. This general logic was applied here to the phenomenon of aggressiveness after drinking alcohol. Specifically, we predicted that automatic associations between alcohol and power would predict aggressiveness after drinking in men with relatively weak EC. Participants were 57 heavy drinking male students, who completed two versions of the Implicit Association Test (IAT), one assessing alcohol-power associations (hypothesized critical associations) and one alcohol-arousal associations (control-test), a classical Stroop test (measure of EC) and a number of alcohol-related questionnaires, including four questions on aggressiveness after drinking (dependent variable). As predicted, automatic alcohol-power associations significantly predicted self-reported aggressiveness after drinking in low but not in high EC individuals. As expected, this interaction was specific for alcohol-power associations since it was not found with regard to alcohol-arousal associations. We argue that this finding, together with a recent related findings, indicates that specific instances of "impulsivity" can be conceptualized as the joint outcome of two processes: a general weak EC and an associative process that predicts the impulsive behavior under study when not inhibited by EC processes.

  3. Examination of The Predictive Power of Electromyography and Urodynamic Study in Patients with Cauda Equina Syndrome (Horse Tail Syndrome)

    PubMed Central

    Shahmohammadi, Mohammadreza; Khoshuod, Reza Jalil; Zali, Alireza; Seddeghi, Amir Saied; Kabir, Nima Mohseni

    2016-01-01

    Background: Cauda equina syndrome is a rare disorder that causes loss of Lumbar plexus function (nerve roots) lower than conus medullaris. No risk factor has been defined for this disease yet. Due to the high morbidity of Cauda equina syndrome and lack of sufficient information about the connection between the disease and urodynamic findings and EMG (Electromyography) findings, the need for this comprehensive study is felt. Objective: The aim is to determine the predictive power of findings resulted from urodynamics and electromyography of perineal region and around sphincter in the clinical cure rate of urination in patients with urinary retention followed by Cauda equina syndrome. Method: Patients referred to Shohadaye Tajrish Hospital during the years 2009 to 2013, in case of having Cauda equina syndrome symptoms (confirmed with Lumbar MRI), were undergone urodynamic examination and perineal electromyography after surgical decompression action. These both assessments (urodynamic study and electromyography) were repeated during the follow-up of 15 patients in the first and sixth months after surgery and findings were compared with each other. Results: Among the Urodynamic findings, Qmax (maximum urine flow) during three studies had a significant relationship with long-term recovery rate of patients (P <0.05). The relationship had been more valuable in follow-ups after one month (P = 0.0001). Also, BCI (Bladder Contractility Index) in all three studies had a significant relationship with clinical improvement in the ability to urinate (P <0.001). The residual urine (PVR) compared to two previous urodynamic findings showed a less significant relationship with clinical cure rate (P = 0.04). Among the findings of muscle-nerve (MUAP Fibrillation, Positive sharp way) none of them had a significant relationship with cure rate. Conclusion: Urodynamic finding, especially Qmax and bladder contractility index, can be considered as predictive indicators for patients

  4. Do main partner conflict, power dynamics, and control over use of male condoms predict subsequent use of the female condom?

    PubMed

    Cabral, Rebecca J; Posner, Samuel F; Macaluso, Maurizio; Artz, Lynn M; Johnson, Christopher; Pulley, LeaVonne

    2003-01-01

    This study assessed hypotheses that measures of power and control over male condom (MC) use would predict use of the female condom (FC) among women with main partners from two public STD clinics (n = 616). The women (mean age 24 years, 87% African American) were enrolled in an intervention study to promote barrier contraceptive use and were interviewed at baseline and at 6 monthly follow-up visits. Seven baseline predictor variables were assessed: her having requested MC use, his having objected, her having wanted a MC used but not asking, percentage of MC use, perceived control over MC use, anticipated consequences of refusing unprotected sex, and physical violence. In the first Poisson regression analysis, none of the hypothesized predictors was significantly associated with FC use during follow up. In the second regression analysis, which assessed the influence of the hypothesized set of predictors on follow-up FC use in situations when MCs were not used, we found two effects. Either no or inconsistent MC use before study entry was associated with less subsequent FC use; women who reported, at study entry, having more control over MC use were more likely to use FCs during follow up. We found no evidence of adoption of the FC by women in relationships marked by history of conflict over the MC, circumstances in which alternatives are most needed. On the contrary, we found that women with a history of control and consistent use of MCs were the most likely users of FCs when MCs were not used.

  5. Subjective Well-Being: The Constructionist Point of View. A Longitudinal Study to Verify the Predictive Power of Top-Down Effects and Bottom-Up Processes

    ERIC Educational Resources Information Center

    Leonardi, Fabio; Spazzafumo, Liana; Marcellini, Fiorella

    2005-01-01

    Based on the constructionist point of view applied to Subjective Well-Being (SWB), five hypotheses were advanced about the predictive power of the top-down effects and bottom-up processes over a five years period. The sample consisted of 297 respondents, which represent the Italian sample of a European longitudinal survey; the first phase was…

  6. 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.

  7. Identifying Essential Features of Juvenile Psychopathy in the Prediction of Later Antisocial Behavior: Is There an Additive, Synergistic, or Curvilinear Role for Fearless Dominance?

    PubMed

    Vize, Colin E; Lynam, Donald R; Lamkin, Joanna; Miller, Joshua D; Pardini, Dustin

    2016-05-01

    Despite years of research, and inclusion of psychopathy DSM-5, there remains debate over the fundamental components of psychopathy. Although there is agreement about traits related to Agreeableness and Conscientiousness, there is less agreement about traits related to Fearless Dominance (FD) or Boldness. The present paper uses proxies of FD and Self-centered Impulsivity (SCI) to examine the contribution of FD-related traits to the predictive utility of psychopathy in a large, longitudinal, sample of boys to test four possibilities: FD 1. assessed earlier is a risk factor, 2. interacts with other risk-related variables to predict later psychopathy, 3. interacts with SCI interact to predict outcomes, and 4. bears curvilinear relations to outcomes. SCI received excellent support as a measure of psychopathy in adolescence; however, FD was unrelated to criteria in all tests. It is suggested that FD be dropped from psychopathy and that future research focus on Agreeableness and Conscientiousness.

  8. Factors influencing the predictive power of models for predicting mortality and/or heart failure hospitalization in patients with heart failure.

    PubMed

    Ouwerkerk, Wouter; Voors, Adriaan A; Zwinderman, Aeilko H

    2014-10-01

    The present paper systematically reviews and compares existing prediction models in order to establish the strongest variables, models, and model characteristics in patients with heart failure predicting outcome. To improve decision making accurately predicting mortality and heart-failure hospitalization in patients with heart failure can be important for selecting patients with a poorer prognosis or nonresponders to current therapy, to improve decision making. MEDLINE/PubMed was searched for papers dealing with heart failure prediction models. To identify similar models on the basis of their variables hierarchical cluster analysis was performed. Meta-analysis was used to estimate the mean predictive value of the variables and models; meta-regression was used to find characteristics that explain variation in discriminating values between models. We identified 117 models in 55 papers. These models used 249 different variables. The strongest predictors were blood urea nitrogen and sodium. Four subgroups of models were identified. Mortality was most accurately predicted by prospective registry-type studies using a large number of clinical predictor variables. Mean C-statistic of all models was 0.66 ± 0.0005, with 0.71 ± 0.001, 0.68 ± 0.001 and 0.63 ± 0.001 for models predicting mortality, heart failure hospitalization, or both, respectively. There was no significant difference in discriminating value of models between patients with chronic and acute heart failure. Prediction of mortality and in particular heart failure hospitalization in patients with heart failure remains only moderately successful. The strongest predictors were blood urea nitrogen and sodium. The highest C-statistic values were achieved in a clinical setting, predicting short-term mortality with the use of models derived from prospective cohort/registry studies with a large number of predictor variables.

  9. A distributed model predictive control based load frequency control scheme for multi-area interconnected power system using discrete-time Laguerre functions.

    PubMed

    Zheng, Yang; Zhou, Jianzhong; Xu, Yanhe; Zhang, Yuncheng; Qian, Zhongdong

    2017-03-23

    This paper proposes a distributed model predictive control based load frequency control (MPC-LFC) scheme to improve control performances in the frequency regulation of power system. In order to reduce the computational burden in the rolling optimization with a sufficiently large prediction horizon, the orthonormal Laguerre functions are utilized to approximate the predicted control trajectory. The closed-loop stability of the proposed MPC scheme is achieved by adding a terminal equality constraint to the online quadratic optimization and taking the cost function as the Lyapunov function. Furthermore, the treatments of some typical constraints in load frequency control have been studied based on the specific Laguerre-based formulations. Simulations have been conducted in two different interconnected power systems to validate the effectiveness of the proposed distributed MPC-LFC as well as its superiority over the comparative methods.

  10. 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.

  11. Marker-Based Estimates Reveal Significant Non-additive Effects in Clonally Propagated Cassava (Manihot esculenta): Implications for the Prediction of Total Genetic Value and the Selection of Varieties.

    PubMed

    Wolfe, Marnin D; Kulakow, Peter; Rabbi, Ismail Y; Jannink, Jean-Luc

    2016-08-31

    In clonally propagated crops, non-additive genetic effects can be effectively exploited by the identification of superior genetic individuals as varieties. Cassava (Manihot esculenta Crantz) is a clonally propagated staple food crop that feeds hundreds of millions. We quantified the amount and nature of non-additive genetic variation for three key traits in a breeding population of cassava from sub-Saharan Africa using additive and non-additive genome-wide marker-based relationship matrices. We then assessed the accuracy of genomic prediction for total (additive plus non-additive) genetic value. We confirmed previous findings based on diallel populations, that non-additive genetic variation is significant for key cassava traits. Specifically, we found that dominance is particularly important for root yield and epistasis contributes strongly to variation in CMD resistance. Further, we showed that total genetic value predicted observed phenotypes more accurately than additive only models for root yield but not for dry matter content, which is mostly additive or for CMD resistance, which has high narrow-sense heritability. We address the implication of these results for cassava breeding and put our work in the context of previous results in cassava, and other plant and animal species.

  12. An Evaluation of the Additional Acoustic Power Needed to Overcome the Effects of a Test-Articles Absorption During Reverberant Chamber Acoustic Testing of Spaceflight Hardware

    NASA Technical Reports Server (NTRS)

    Hozman, Aron D.; Hughes, William O.

    2014-01-01

    It is important to realize that some test-articles may have significant sound absorption that may challenge the acoustic power capabilities of a test facility. Therefore, to mitigate this risk of not being able to meet the customers target spectrum, it is prudent to demonstrate early-on an increased acoustic power capability which compensates for this test-article absorption. This paper describes a concise method to reduce this risk when testing aerospace test-articles which have significant absorption. This method was successfully applied during the SpaceX Falcon 9 Payload Fairing acoustic test program at the NASA Glenn Research Center Plum Brook Stations RATF.

  13. 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

  14. 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.

  15. A framework for predicting the yield stress, Charpy toughness and one hundred-year activation level for irradiated fusion power plant alloys

    NASA Astrophysics Data System (ADS)

    Windsor, Colin; Cottrell, Geoff; Kemp, Richard

    2011-04-01

    Recent papers have demonstrated that the yield stress and the Charpy ductile to brittle transition temperature shift at the high irradiation levels of a fusion power plant may be predicted from measurements at lower irradiation levels using neural networks. It was demonstrated that the extrapolation inherent in such predictions could be validated provided that network complexity was appropriately low. Simultaneous predictions of these metallurgical properties at the 100 dpa irradiation level and 400 °C irradiation temperature of a possible fusion power plant have been made for a series of ferritic/martensitic steels, albeit based on mainly fission data. Together with the readily available one hundred-year activation level, benefit functions are defined which can be used to predict the most suitable alloys for a fusion power plant from within existing databases. Our model is sufficiently flexible to allow a variety of possible benefit functions to be defined. The F82H, Eurofer and LA12 alloy series all receive a favourable rating, although all results presented here must be tempered with caution until more data at relevant irradiation levels and with relevant energy spectra become available.

  16. 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.

  17. A Hierarchical Examination of the Immigrant Achievement Gap: The Additional Explanatory Power of Nationality and Educational Selectivity over Traditional Explorations of Race and Socioeconomic Status

    ERIC Educational Resources Information Center

    Simms, Kathryn

    2012-01-01

    This study compared immigrant and nonimmigrant educational achievement (i.e., the immigrant gap) in math by reexamining the explanatory power of race and socioeconomic status (SES)--two variables, perhaps, most commonly considered in educational research. Four research questions were explored through growth curve modeling, factor analysis, and…

  18. 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.

  19. Jet Power and Black Hole Spin: Testing an Empirical Relationship and Using it to Predict the Spins of Six Black Holes

    NASA Astrophysics Data System (ADS)

    Steiner, James F.; McClintock, Jeffrey E.; Narayan, Ramesh

    2013-01-01

    Using 5 GHz radio luminosity at light-curve maximum as a proxy for jet power and black hole spin measurements obtained via the continuum-fitting method, Narayan & McClintock presented the first direct evidence for a relationship between jet power and black hole spin for four transient black hole binaries. We test and confirm their empirical relationship using a fifth source, H1743-322, whose spin was recently measured. We show that this relationship is consistent with Fe-line spin measurements provided that the black hole spin axis is assumed to be aligned with the binary angular momentum axis. We also show that, during a major outburst of a black hole transient, the system reasonably approximates an X-ray standard candle. We further show, using the standard synchrotron bubble model, that the radio luminosity at light-curve maximum is a good proxy for jet kinetic energy. Thus, the observed tight correlation between radio power and black hole spin indicates a strong underlying link between mechanical jet power and black hole spin. Using the fitted correlation between radio power and spin for the above five calibration sources, we predict the spins of six other black holes in X-ray/radio transient systems with low-mass companions. Remarkably, these predicted spins are all relatively low, especially when compared to the high measured spins of black holes in persistent, wind-fed systems with massive companions.

  20. A Comparative Study to Assess the Predictability of Different IOL Power Calculation Formulas in Eyes of Short and Long Axial Length

    PubMed Central

    Limdi, Purvi; Parekh, Nilesh; Gohil, Neepa

    2017-01-01

    Introduction Accurate Intraocular Lens (IOL) power calculation in cataract surgery is very important for providing postoperative precise vision. Selection of most appropriate formula is difficult in high myopic and hypermetropic patients. Aim To investigate the predictability of different IOL (Intra Ocular Lens) power calculation formulae in eyes with short and long Axial Length (AL) and to find out most accurate IOL power calculation formula in both groups. Materials and Methods A prospective study was conducted on 80 consecutive patients who underwent phacoemulsification with monofocal IOL implantation after obtaining an informed and written consent. Preoperative keratometry was done by IOL Master. Axial length and anterior chamber depth was measured using A-scan machine ECHORULE 2 (BIOMEDIX). Patients were divided into two groups based on AL. (40 in each group). Group A with AL<22 mm and Group B with AL>24.5 mm. The IOL power calculation in each group was done by Haigis, Hoffer Q, Holladay-I, SRK/T formulae using the software of ECHORULE 2. The actual postoperative Spherical Equivalent (SE), Estimation error (E) and Absolute Error (AE) were calculated at one and half months and were used in data analysis. The predictive accuracy of each formula in each group was analyzed by comparing the Absolute Error (AE). The Kruskal Wallis test was used to compare differences in the (AE) of the formulae. A statistically significant difference was defined as p-value<0.05. Results In Group A, Hoffer Q, Holladay 1 and SRK/T formulae were equally accurate in predicting the postoperative refraction after cataract surgery (IOL power calculation) in eyes with AL less than 22.0 mm and accuracy of these three formulae was significantly higher than Haigis formula. Whereas in Group B, Hoffer Q, Holladay 1, SRK/T and Haigis formulae were equally accurate in predicting the postoperative refraction after cataract surgery (IOL power calculation) in eyes with AL more than 24.5 mm

  1. Improvement in the prediction of the translation initiation site through balancing methods, inclusion of acquired knowledge and addition of features to sequences of mRNA

    PubMed Central

    2011-01-01

    Background The accurate prediction of the initiation of translation in sequences of mRNA is an important activity for genome annotation. However, obtaining an accurate prediction is not always a simple task and can be modeled as a problem of classification between positive sequences (protein codifiers) and negative sequences (non-codifiers). The problem is highly imbalanced because each molecule of mRNA has a unique translation initiation site and various others that are not initiators. Therefore, this study focuses on the problem from the perspective of balancing classes and we present an undersampling balancing method, M-clus, which is based on clustering. The method also adds features to sequences and improves the performance of the classifier through the inclusion of knowledge obtained by the model, called InAKnow. Results Through this methodology, the measures of performance used (accuracy, sensitivity, specificity and adjusted accuracy) are greater than 93% for the Mus musculus and Rattus norvegicus organisms, and varied between 72.97% and 97.43% for the other organisms evaluated: Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Homo sapiens, Nasonia vitripennis. The precision increases significantly by 39% and 22.9% for Mus musculus and Rattus norvegicus, respectively, when the knowledge obtained by the model is included. For the other organisms, the precision increases by between 37.10% and 59.49%. The inclusion of certain features during training, for example, the presence of ATG in the upstream region of the Translation Initiation Site, improves the rate of sensitivity by approximately 7%. Using the M-Clus balancing method generates a significant increase in the rate of sensitivity from 51.39% to 91.55% (Mus musculus) and from 47.45% to 88.09% (Rattus norvegicus). Conclusions In order to solve the problem of TIS prediction, the results indicate that the methodology proposed in this work is adequate, particularly when using the

  2. Predicting Sexual Harassment From Hostile Sexism and Short-Term Mating Orientation: Relative Strength of Predictors Depends on Situational Priming of Power Versus Sex.

    PubMed

    Diehl, Charlotte; Rees, Jonas; Bohner, Gerd

    2016-12-09

    Previous research has shown that short-term mating orientation (STMO) and hostile sexism (HS) selectively predict different types of sexual harassment. In a priming experiment, we studied the situational malleability of those effects. Male participants could repeatedly send sexist jokes (gender harassment), harassing remarks (unwanted sexual attention), or nonharassing messages to a (computer-simulated) female target. Before entering the laboratory, participants were unobtrusively primed with the concepts of either sexuality or power. As hypothesized, sexuality priming strengthened the link between STMO and unwanted sexual attention, whereas power priming strengthened the link between HS and gender harassment. Practical implications are discussed.

  3. 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.

  4. 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.

  5. Additive value of blood neutrophil gelatinase-associated lipocalin to clinical judgement in acute kidney injury diagnosis and mortality prediction in patients hospitalized from the emergency department

    PubMed Central

    2013-01-01

    Introduction Acute kidney injury (AKI) is a common complication among hospitalized patients. The aim of this study was to evaluate the utility of blood neutrophil gelatinase-associated lipocalin (NGAL) assessment as an aid in the early risk evaluation for AKI development in admitted patients. Methods This is a multicenter Italian prospective emergency department (ED) cohort study in which we enrolled 665 patients admitted to hospital from the ED. Results Blood NGAL and serum creatinine (sCr) were determined at ED presentation (T0), and at: 6 (T6), 12 (T12), 24 (T24) and 72 (T72) hours after hospitalization. A preliminary assessment of AKI by the treating ED physician occurred in 218 out of 665 patients (33%), while RIFLE AKI by expert nephrologists was confirmed in 49 out of 665 patients (7%). The ED physician's initial judgement lacked sensitivity and specificity, overpredicting the diagnosis of AKI in 27% of the cohort, while missing 20% of those with AKI as a final diagnosis. The area under the receiver operating characteristic curve (AUC), obtained at T0, for blood NGAL alone in the AKI group was 0.80. When NGAL at T0 was added to the ED physician's initial clinical judgment the AUC was increased to 0.90, significantly greater when compared to the AUC of the T0 estimated glomerular filtration rate (eGFR) obtained either by modification of diet in renal disease (MDRD) equation (0.78) or Cockroft-Gault formula (0.78) (P = 0.022 and P = 0.020 respectively). The model obtained by combining NGAL with the ED physician's initial clinical judgement compared to the model combining sCr with the ED physician's initial clinical judgement, resulted in a net reclassification index of 32.4 percentage points. Serial assessment of T0 and T6 hours NGAL provided a high negative predictive value (NPV) (98%) in ruling out the diagnosis of AKI within 6 hours of patients' ED arrival. NGAL (T0) showed the strongest predictive value for in-hospital patient's mortality at a cutoff of

  6. Additional considerations and recommendations for the quantification of hand-grip strength in the measurement of leg power during high-intensity cycle ergometry.

    PubMed

    Baker, Julien Steven; Davies, Bruce

    2009-01-01

    The purpose of this study was to further examine the influence of hand-grip strength on power profiles and blood lactate values during high-intensity cycle ergometry. Fifteen male subjects each completed a 20-second cycle ergometer test twice, in a random manner, using two protocols, with a hand grip (WG), and without hand grip (WOHG). Hand-grip strength was quantified prior to exercise using a hand-grip dynamometer. Capillary (earlobe) blood was collected at rest, immediately following exercise, and 5 minutes postexercise. In the WG protocol, mean (+/-SD) blood lactate concentrations were 1.11 +/- 0.7 mmol.l( -1), 3.68 +/- 1.2 mmol.l( -1), and 8.14 +/- 1.3 mmol.l( -1), respectively. During the WOHG protocol, blood lactate values recorded were 0.99 +/- 0.9 mmol.l( -1), 3.68 +/- 1.1 mmol.l( -1), and 6.62 +/- 0.9 mmol.l( -1), respectively. Differences in lactate concentrations were found (P < 0.05) from rest to 5 minutes postexercise for both groups. Differences in concentrations also were observed between groups at the 5-minutes postexercise stage. Peak power output and fatigue index values also were greater using the WG protocol (792 +/- 73 W vs. 624 +/- 66 W; 38 +/- 6 vs. 24 +/- 8 W respectively; P< 0.05). No differences were recorded for mean power output (MPO) or work done (WD) between experimental conditions. These findings suggest that the performance of traditional style leg cycle ergometry is influenced by a muscular contribution from the upper body and by upper body strength.

  7. Effect of organic additives on the mitigation of volatility of 1-nitro-3,3'-dinitroazetidine (TNAZ): next generation powerful melt cast able high energy material.

    PubMed

    Talawar, M B; Singh, Alok; Naik, N H; Polke, B G; Gore, G M; Asthana, S N; Gandhe, B R

    2006-06-30

    1-Nitro-3,3'-dinitroazetidine (TNAZ) was synthesized based on the lines of reported method. Thermolysis studies on synthesized and characterized TNAZ using differential scanning calorimetry (DSC) and hyphenated TG-FT-IR techniques were undertaken to generate data on decomposition pattern. FT-IR of decomposition products of TNAZ revealed the evolution of oxides of nitrogen and HCN containing species suggesting the cleavage of C/N-NO(2) bond accompanied with the collapse of ring structure. The effect of incorporation of 15% additives namely, 3-amino-1,2,4-triazole (AT), 3,5-diamino-1,2,4-triazole (DAT), carbohydrazide (CHZ), 5,7-dinitrobenzofuroxan (DNBF), bis (2,2-dinitropropyl) succinate (BNPS), triaminoguanidinium nitrate (TAGN), 2,4,6-trinitrobenzoic acid (TNBA) and nitroguanidine (NQ) on the volatility of TNAZ was investigated by undertaking thermogravimetric analysis. The TG pattern brings out the potential of BNPS and TAGN as additives to mitigate the volatility of TNAZ. The influence of additives on thermal decomposition of pattern of TNAZ was also investigated by DSC. The DSC results indicated that the additives did not have appreciable effect on the melting point of TNAZ. Scanning electron microscopic (SEM) studies were carried out to investigate the effect of additives on morphology of TNAZ. This paper also discusses the possible mechanism involved in between the TNAZ and TAGN and BNPS. It appears that the formation of charge transfer complex formation between the TNAZ and TAGN/BNPS. The effect of addition of high explosives such as CL-20, HMX and RDX on thermo-physical characteristics of TNAZ is also reported in this paper.

  8. Food additives

    MedlinePlus

    ... or natural. Natural food additives include: Herbs or spices to add flavor to foods Vinegar for pickling ... Certain colors improve the appearance of foods. Many spices, as well as natural and man-made flavors, ...

  9. A fast algorithm to predict spectral broadening in CW bidirectionally pumped high-power Yb-doped fiber lasers

    NASA Astrophysics Data System (ADS)

    Szabó, Áron; Várallyay, Zoltán; Rosales-Garcia, Andrea; Headley, Clifford

    2015-11-01

    A detailed, fast-converging iterative numerical method has been developed to model continuous-wave bidirectionally pumped Yb-doped fiber lasers with output powers of several hundred watts. The analysis shows nonlinearity-induced broadening of the lasing spectrum, which also modifies power efficiency. Cavity dynamics is described by combining the effects of Kerr nonlinearities with power evolution equations and rate equations. The fast method to find steady-state solutions for cavity setups is based on setting the temporal phase evolution as a stochastic process with proper spectral filtering. Spectral properties of bidirectionally pumped lasers are calculated within few minutes using a commercial desktop computer, and very good agreement with experimental measurements is obtained for up to 922 W total pump and 708 W output power.

  10. 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

  11. Female mate choice predicts paternity success in the absence of additive genetic variance for other female paternity bias mechanisms in Drosophila serrata.

    PubMed

    Collet, J M; Blows, M W

    2014-11-01

    After choosing a first mate, polyandrous females have access to a range of opportunities to bias paternity, such as repeating matings with the preferred male, facilitating fertilization from the best sperm or differentially investing in offspring according to their sire. Female ability to bias paternity after a first mating has been demonstrated in a few species, but unambiguous evidence remains limited by the access to complex behaviours, sperm storage organs and fertilization processes within females. Even when found at the phenotypic level, the potential evolution of any mechanism allowing females to bias paternity other than mate choice remains little explored. Using a large population of pedigreed females, we developed a simple test to determine whether there is additive genetic variation in female ability to bias paternity after a first, chosen, mating. We applied this method in the highly polyandrous Drosophila serrata, giving females the opportunity to successively mate with two males ad libitum. We found that despite high levels of polyandry (females mated more than once per day), the first mate choice was a significant predictor of male total reproductive success. Importantly, there was no detectable genetic variance in female ability to bias paternity beyond mate choice. Therefore, whether or not females can bias paternity before or after copulation, their role on the evolution of sexual male traits is likely to be limited to their first mate choice in D. serrata.

  12. Optimization and Annual Average Power Predictions of a Backward Bent Duct Buoy Oscillating Water Column Device Using the Wells Turbine.

    SciTech Connect

    Smith, Christopher S.; Bull, Diana L; Willits, Steven M.; Fontaine, Arnold A.

    2014-08-01

    This Technical Report presents work completed by The Applied Research Laboratory at The Pennsylvania State University, in conjunction with Sandia National Labs, on the optimization of the power conversion chain (PCC) design to maximize the Average Annual Electric Power (AAEP) output of an Oscillating Water Column (OWC) device. The design consists of two independent stages. First, the design of a floating OWC, a Backward Bent Duct Buoy (BBDB), and second the design of the PCC. The pneumatic power output of the BBDB in random waves is optimized through the use of a hydrodynamically coupled, linear, frequency-domain, performance model that links the oscillating structure to internal air-pressure fluctuations. The PCC optimization is centered on the selection and sizing of a Wells Turbine and electric power generation equipment. The optimization of the PCC involves the following variables: the type of Wells Turbine (fixed or variable pitched, with and without guide vanes), the radius of the turbine, the optimal vent pressure, the sizing of the power electronics, and number of turbines. Also included in this Technical Report are further details on how rotor thrust and torque are estimated, along with further details on the type of variable frequency drive selected.

  13. 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.

  14. 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.

  15. Results from expert tests of the TP-100A boiler at the Lugansk thermal power station during the combustion of lean coal and anthracite culm with addition of RA-GEN-F anaklarid

    NASA Astrophysics Data System (ADS)

    Mikhailov, V. E.; Tupitsyn, S. P.; Sokolov, V. V.; Chebakova, G. F.; Malygin, V. I.; Yazykov, Yu. V.; Kharchenko, A. V.; Chetverikov, A. N.

    2012-08-01

    Results from expert tests of separated combustion of Grade T and Grade ASh anthracite culm in the TP-100A boiler No. 15 at the Lugansk thermal power station carried out with and without addition of RA-GEN-F anaklarid are presented. The possibility of extending the boiler load adjustment range and excluding the use of natural gas for supporting the flame at minimal loads is considered.

  16. 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.

  17. Predictive power of quantitative and qualitative fecal immunochemical tests for hemoglobin in population screening for colorectal neoplasm.

    PubMed

    Huang, Yanqin; Li, Qilong; Ge, Weiting; Cai, Shanrong; Zhang, Suzhan; Zheng, Shu

    2014-01-01

    The aim of this study was to evaluate the performance of qualitative and quantitative fecal immunochemical tests (FITs) in population screening for colorectal neoplasm. A total of 9000 participants aged between 40 and 74 years were enrolled in this study. Each participant received two stool sampling tubes and was asked to simultaneously submit two stool samples from the same bowel movement. The stool samples of each participant were tested using an immunogold labeling FIT dipstick (qualitative FIT) and an automated fecal blood analyzer (quantitative FIT). Colonoscopy was performed for those who test positive in either FIT. The positive predictive values and population detection rates of the FITs for predicting colorectal neoplasm were compared. A total of 6494 (72.16%) participants simultaneously submitted two stool samples. The diagnostic consistency for a positive result between quantitative and qualitative FITs was poor (κ=0.278, 95% confidence interval=0.223-0.333). The positive predictive values of the quantitative FIT were significantly higher than those of the qualitative FIT for predicting large (≥1 cm) adenomas (23 cases, 14.29% and 16 cases, 6.72%, P=0.013) and colorectal cancer (10 cases, 6.21% and 5 cases, 2.10%, P=0.034); however, the population detection rate for advanced neoplasm of the quantitative FIT was not significantly different from that of the qualitative FIT. Quantitative FIT is superior to qualitative FIT in predicting advanced colorectal neoplasm during colorectal cancer screening. Further studies are needed to elucidate the causes of the predictive superiority.

  18. Relative power of clinical, exercise test, and angiographic variables in predicting clinical outcome after myocardial infarction: the Newham and Tower Hamlets study.

    PubMed Central

    de Belder, M A; Pumphrey, C W; Skehan, J D; Rimington, H; al Wakeel, B; Evans, S J; Rothman, M; Mills, P G

    1988-01-01

    The interrelations of clinical, exercise test, and angiographic variables and their relative values in predicting specific clinical outcomes after myocardial infarction have not been fully established. Of 302 consecutive stable survivors of infarction, 262 performed a predischarge submaximal exercise test. In the first year after infarction patients with a "positive" exercise test were 13 times more likely to die, 2.8 times more likely to have an ischaemic event, and 2.3 times more likely to develop left ventricular failure than patients with negative tests. Patients with positive exercise tests underwent cardiac catheterization. Features of the history, 12 lead electrocardiogram, in-hospital clinical course, exercise test, and left ventricular and coronary angiograms that predicted these clinical end points were identified by univariate analysis. Then multivariable analysis was used to assess the relative powers of all variables in predicting end points. Certain features of the exercise test remained independent predictors of future ischaemic events and the development of overt left ventricular failure, but clinical and angiographic variables were more powerful predictors of mortality. Because the exercise test is also used to select patients for angiography, however, the results of this study strongly support the use of early submaximal exercise testing after infarction. PMID:3203032

  19. 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.

  20. 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)

  1. Predictability of Intraocular Lens Power Calculation Formulae in Infantile Eyes With Unilateral Congenital Cataract: Results from the Infant Aphakia Treatment Study

    PubMed Central

    VANDERVEEN, DEBORAH K.; TRIVEDI, RUPAL H.; NIZAM, AZHAR; LYNN, MICHAEL J.; LAMBERT, SCOTT R.

    2014-01-01

    PURPOSE To compare accuracy of intraocular lens (IOL) power calculation formulae in infantile eyes with primary IOL implantation. DESIGN Comparative case series. METHODS The Hoffer Q, Holladay 1, Holladay 2, Sanders-Retzlaff-Kraff (SRK) II, and Sanders-Retzlaff-Kraff theoretic (SRK/T) formulae were used to calculate predicted postoperative refraction for eyes that received primary IOL implantation in the Infant Aphakia Treatment Study. The protocol targeted postoperative hyperopia of +6.0 or +8.0 diopters (D). Eyes were excluded for invalid biometry, lack of refractive data at the specified postoperative visit, diagnosis of glaucoma or suspected glaucoma, or sulcus IOL placement. Actual refraction 1 month after surgery was converted to spherical equivalent and prediction error (predicted refraction – actual refraction) was calculated. Baseline characteristics were analyzed for effect on prediction error for each formula. The main outcome measure was absolute prediction error. RESULTS Forty-three eyes were studied; mean axial length was 18.1 ± 1.1 mm (in 23 eyes, it was <18.0 mm). Average age at surgery was 2.5 ± 1.5 months. Holladay 1 showed the lowest median absolute prediction error (1.2 D); a paired comparison of medians showed clinically similar results using the Holladay 1 and SRK/T formulae (median difference, 0.3 D). Comparison of the mean absolute prediction error showed the lowest values using the SRK/T formula (1.4 ± 1.1 D), followed by the Holladay 1 formula (1.7 ± 1.3 D). Calculations with an optimized constant showed the lowest values and no significant difference between the Holladay 1 and SRK/T formulae (median difference, 0.3 D). Eyes with globe AL of less than 18 mm had the largest mean and median prediction error and absolute prediction error, regardless of the formula used. CONCLUSIONS The Holladay 1 and SRK/T formulae gave equally good results and had the best predictive value for infant eyes. PMID:24011524

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

    PubMed

    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 ([Formula: see text], [Formula: see text], [Formula: see text], Ca(2+), K(+), [Formula: see text], Mg(2+), 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 R(2) 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, [Formula: see text] and [Formula: see text] 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 [Formula: see text], 14 [Formula: see text], 5 Ca(2+), 25.9 K(+), 0.7 Mg(2+), 1.1 [Formula: see text], 4.7 [Formula: see text], 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

  3. 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

  4. 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.

  5. 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.

  6. Analytical and numerical prediction of harmonic sound power in the inlet of aero-engines with emphasis on transonic rotation speeds

    NASA Astrophysics Data System (ADS)

    Lewy, Serge; Polacsek, Cyril; Barrier, Raphael

    2014-12-01

    Tone noise radiated through the inlet of a turbofan is mainly due to rotor-stator interactions at subsonic regimes (approach flight), and to the shock waves attached to each blade at supersonic helical tip speeds (takeoff). The axial compressor of a helicopter turboshaft engine is transonic as well and can be studied like turbofans at takeoff. The objective of the paper is to predict the sound power at the inlet radiating into the free field, with a focus on transonic conditions because sound levels are much higher. Direct numerical computation of tone acoustic power is based on a RANS (Reynolds averaged Navier-Stokes) solver followed by an integration of acoustic intensity over specified inlet cross-sections, derived from Cantrell and Hart equations (valid in irrotational flows). In transonic regimes, sound power decreases along the intake because of nonlinear propagation, which must be discriminated from numerical dissipation. This is one of the reasons why an analytical approach is also suggested. It is based on three steps: (i) appraisal of the initial pressure jump of the shock waves; (ii) 2D nonlinear propagation model of Morfey and Fisher; (iii) calculation of the sound power of the 3D ducted acoustic field. In this model, all the blades are assumed to be identical such that only the blade passing frequency and its harmonics are predicted (like in the present numerical simulations). However, transfer from blade passing frequency to multiple pure tones can be evaluated in a fourth step through a statistical analysis of irregularities between blades. Interest of the analytical method is to provide a good estimate of nonlinear acoustic propagation in the upstream duct while being easy and fast to compute. The various methods are applied to two turbofan models, respectively in approach (subsonic) and takeoff (transonic) conditions, and to a Turbomeca turboshaft engine (transonic case). The analytical method in transonic appears to be quite reliable by comparison

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. Prediction and modeling of the two-dimensional separation characteristic of a steam generator at a nuclear power station with VVER-1000 reactors

    NASA Astrophysics Data System (ADS)

    Parchevsky, V. M.; Guryanova, V. V.

    2017-01-01

    A computational and experimental procedure for construction of the two-dimensional separation curve (TDSC) for a horizontal steam generator (SG) at a nuclear power station (NPS) with VVER-reactors. In contrast to the conventional one-dimensional curve describing the wetness of saturated steam generated in SG as a function of the boiler water level at one, usually rated, load, TDSC is a function of two variables, which are the level and the load of SGB that enables TDSC to be used for wetness control in a wide load range. The procedure is based on two types of experimental data obtained during rated load operation: the nonuniformity factor of the steam load at the outlet from the submerged perforated sheet (SPS) and the dependence of the mass water level in the vicinity of the "hot" header on the water level the "cold" end of SG. The TDSC prediction procedure is presented in the form of an algorithm using SG characteristics, such as steam load and water level as the input and giving the calculated steam wetness at the output. The zoneby-zone calculation method is used. The result is presented in an analytical form (as an empirical correlation) suitable for uploading into controllers or other controls. The predicted TDSC can be used during real-time operation for implementation of different wetness control scenarios (for example, if the effectiveness is a priority, then the minimum water level, minimum wetness, and maximum turbine efficiency should be maintained; if safety is a priority, then the maximum level at the allowable wetness and the maximum water inventory should be kept), for operation of NPS in controlling the frequency and power in a power system, at the design phase (as a part of the simulation complex for verification of design solutions), during construction and erection (in developing software for personnel training simulators), during commissioning tests (to reduce the duration and labor-intensity of experimental activities), and for training.

  12. 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.

  13. Fisher Matrix-based Predictions for Measuring the z = 3.35 Binned 21-cm Power Spectrum using the Ooty Wide Field Array (OWFA)

    NASA Astrophysics Data System (ADS)

    Sarkar, Anjan Kumar; Bharadwaj, Somnath; Ali, Sk. Saiyad

    2017-03-01

    We use the Fisher matrix formalism to predict the prospects of measuring the redshifted 21-cm power spectrum in different k-bins using observations with the upcoming Ooty Wide Field Array (OWFA) which will operate at 326.5 MHz. This corresponds to neutral hydrogen (HI) at z = 3.35, and a measurement of the 21-cm power spectrum provides a unique method to probe the large-scale structures at this redshift. Our analysis indicates that a 5 σ detection of the binned power spectrum is possible in the k range 0.05 ≤ k ≤ 0.3 Mpc-1 with 1000 hours of observation. We find that the signal- to-noise ratio (SNR) peaks in the k range 0.1-0.2 Mpc-1 where a 10 σ detection is possible with 2000 hours of observations. Our analysis also indicates that it is not very advantageous to observe beyond 1000 h in a single field-of-view as the SNR increases rather slowly beyond this in many of the small k-bins. The entire analysis reported here assumes that the foregrounds have been completely removed.

  14. The effect of non-Gaussianity on error predictions for the Epoch of Reionization (EoR) 21-cm power spectrum

    NASA Astrophysics Data System (ADS)

    Mondal, Rajesh; Bharadwaj, Somnath; Majumdar, Suman; Bera, Apurba; Acharyya, Ayan

    2015-04-01

    The Epoch of Reionization (EoR) 21-cm signal is expected to become increasingly non-Gaussian as reionization proceeds. We have used seminumerical simulations to study how this affects the error predictions for the EoR 21-cm power spectrum. We expect SNR=√{N_k} for a Gaussian random field where Nk is the number of Fourier modes in each k bin. We find that non-Gaussianity is important at high SNR where it imposes an upper limit [SNR]l. For a fixed volume V, it is not possible to achieve SNR > [SNR]l even if Nk is increased. The value of [SNR]l falls as reionization proceeds, dropping from ˜500 at bar{x}_{H I} = 0.8-0.9 to ˜10 at bar{x}_{H I} = 0.15 for a [150.08 Mpc]3 simulation. We show that it is possible to interpret [SNR]l in terms of the trispectrum, and we expect [SNR]_l ∝ √{V} if the volume is increased. For SNR ≪ [SNR]l we find SNR= √{N_k}/A with A ˜ 0.95-1.75, roughly consistent with the Gaussian prediction. We present a fitting formula for the SNR as a function of Nk, with two parameters A and [SNR]l that have to be determined using simulations. Our results are relevant for predicting the sensitivity of different instruments to measure the EoR 21-cm power spectrum, which till date have been largely based on the Gaussian assumption.

  15. Predictions of U.K. regulated power station contributions to regional air pollution and deposition: a model comparison exercise.

    PubMed

    Chemel, Charles; Sokhi, Ranjeet S; Dore, Anthony J; Sutton, Paul; Vincent, Keith J; Griffiths, Stephen J; Hayman, Garry D; Wright, Raymond D; Baggaley, Matthew; Hallsworth, Stephen; Prain, H Douglas; Fisher, Bernard E A

    2011-11-01

    Contributions of the emissions from a U.K. regulated fossil-fuel power station to regional air pollution and deposition are estimated using four air quality modeling systems for the year 2003. The modeling systems vary in complexity and emphasis in the way they treat atmospheric and chemical processes, and include the Community Multiscale Air Quality (CMAQ) modeling system in its versions 4.6 and 4.7, a nested modeling system that combines long- and short-range impacts (referred to as TRACK-ADMS [Trajectory Model with Atmospheric Chemical Kinetics-Atmospheric Dispersion Modelling System]), and the Fine Resolution Atmospheric Multi-pollutant Exchange (FRAME) model. An evaluation of the baseline calculations against U.K. monitoring network data is performed. The CMAQ modeling system version 4.6 data set is selected as the reference data set for the model footprint comparison. The annual mean air concentration and total deposition footprints are summarized for each modeling system. The footprints of the power station emissions can account for a significant fraction of the local impacts for some species (e.g., more than 50% for SO2 air concentration and non-sea-salt sulfur deposition close to the source) for 2003. The spatial correlation and the coefficient of variation of the root mean square error (CVRMSE) are calculated between each model footprint and that calculated by the CMAQ modeling system version 4.6. The correlation coefficient quantifies model agreement in terms of spatial patterns, and the CVRMSE measures the magnitude of the difference between model footprints. Possible reasons for the differences between model results are discussed. Finally, implications and recommendations for the regulatory assessment of the impact of major industrial sources using regional air quality modeling systems are discussed in the light of results from this case study.

  16. 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.

  17. Covariant Spectator Theory of heavy-light and heavy mesons and the predictive power of covariant interaction kernels

    NASA Astrophysics Data System (ADS)

    Leitão, Sofia; Stadler, Alfred; Peña, M. T.; Biernat, Elmar P.

    2017-01-01

    The Covariant Spectator Theory (CST) is used to calculate the mass spectrum and vertex functions of heavy-light and heavy mesons in Minkowski space. The covariant kernel contains Lorentz scalar, pseudoscalar, and vector contributions. The numerical calculations are performed in momentum space, where special care is taken to treat the strong singularities present in the confining kernel. The observed meson spectrum is very well reproduced after fitting a small number of model parameters. Remarkably, a fit to a few pseudoscalar meson states only, which are insensitive to spin-orbit and tensor forces and do not allow to separate the spin-spin from the central interaction, leads to essentially the same model parameters as a more general fit. This demonstrates that the covariance of the chosen interaction kernel is responsible for the very accurate prediction of the spin-dependent quark-antiquark interactions.

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. Predicting the predictive power of IDP ensembles.

    PubMed

    Tompa, Peter; Varadi, Mihaly

    2014-02-04

    The function of intrinsically disordered proteins may be interpreted in terms of their structural ensembles. The article by Schwalbe and colleagues in this issue of Structure combines NMR and SAXS constraints to generate structural ensembles that unveil important functional and pathological features.

  3. 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

  4. 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

  5. Predictive power of long-range corrected functionals on the spectroscopic properties of tetrapyrrole derivatives for photodynamic therapy.

    PubMed

    Eriksson, Emma S E; Eriksson, Leif A

    2011-04-21

    Porphyrin and chlorin based compounds possess promising properties to be utilized as photosensitizers in photodynamic therapy (PDT). However, the photosensitizers available on the market today are not ideal for use in PDT, which has emphasized the need for new photosensitizers with improved photodynamic properties to be developed. Computational drug-design can be utilized in the search for improved pharmaceutical compounds, provided that the methods used are able to reproduce experimental data. In the present study we investigated, by the use of time-dependent density functional theory (TD-DFT), the performance of the long-range corrected functionals ωB97, ωB97X and ωB97XD on their ability to predict low-lying singlet excitations (>600 nm) of a set of well-known photosensitizing compounds. It was found that ωB97X reproduced the experimental red-most absorption band most satisfactorily. The use of either B3LYP, ωB97XD or M06 in geometry optimizations has a minor effect on the spectra in most cases. Calculated energy differences between the optimized singlet ground states and optimized first excited triplet states show consistent and overall higher triplet state energies for B3LYP, M06, and PBE0 compared with ωB97, ωB97X, and ωB97XD. The calculated triplet state energies are, however, sufficient to generate singlet oxygen in most cases.

  6. Predictive Power of Incidents Reporting Rate and Its Dimensions by Job Stress among Workers’ Isfahan Steel Company

    PubMed Central

    Kiani, F; Samavatyan, H; Pourabdian, S; Jafari, E

    2011-01-01

    Background: There is long-term interest in the effects of stress on health, due to the strain that it places on individuals which can lead to an increased risk of disease. The present study examined degree of perceived job stress related to incidents reporting rate and its dimensions among workers’ Isfahan Steel Company. Methods: A self-administered anonymous was distributed to 189 workers. The survey included demographic factors, incidents reporting rate and its components (physical symptoms, psychological symptoms and accidents) and the Job Stress Questionnaire. The data were analyzed by multivariate (MANOVA) and correlation techniques. Results: 1) there was internal significant correlation between perceived job stress with incident reporting rate as well as with its two components namely physical symptoms and psychological symptoms; 2) there was not a significant relationship between perceived job stress and accident; 2) In multivariate analysis, perceived job stress respectively about 12%, 18% and 19% of the variance of variables of incidents reporting rate, physical and psychological symptoms significantly predicted (P< 0.05). Conclusion: Perceived job stress influences to physical and psychological symptoms. Therefore, decreasing job stress can be important to prevent the development of stress-related diseases and to promote workers health. PMID:23113092

  7. 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.

  8. The Predictive Power of Electronic Polarizability for Tailoring the Refractivity of High Index Glasses Optical Basicity Versus the Single Oscillator Model

    SciTech Connect

    McCloy, John S.; Riley, Brian J.; Johnson, Bradley R.; Schweiger, Michael J.; Qiao, Hong; Carlie, Nathan

    2010-06-01

    Four compositions of high density (~8 g/cm3) heavy metal oxide glasses composed of PbO, Bi2O3, and Ga2O3 were produced and refractivity parameters (refractive index and density) were computed and measured. Optical basicity was computed using three different models – average electronegativity, ionic-covalent parameter, and energy gap – and the basicity results were used to compute oxygen polarizability and subsequently refractive index. Refractive indices were measured in the visible and infrared at 0.633 μm, 1.55 μm, 3.39 μm, 5.35 μm, 9.29 μm, and 10.59 μm using a unique prism coupler setup, and data were fitted to the Sellmeier expression to obtain an equation of the dispersion of refractive index with wavelength. Using this dispersion relation, single oscillator energy, dispersion energy, and lattice energy were determined. Oscillator parameters were also calculated for the various glasses from their oxide values as an additional means of predicting index. Calculated dispersion parameters from oxides underestimate the index by 3 to 4%. Predicted glass index from optical basicity, based on component oxide energy gaps, underpredicts the index at 0.633 μm by only 2%, while other basicity scales are less accurate. The predicted energy gap of the glasses based on this optical basicity overpredicts the Tauc optical gap as determined by transmission measurements by 6 to 10%. These results show that for this system, density, refractive index in the visible, and energy gap can be reasonably predicted using only composition, optical basicity values for the constituent oxides, and partial molar volume coefficients. Calculations such as these are useful for a priori prediction of optical properties of glasses.

  9. 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.

  10. Improvement of the Prediction Power of the CoMFA and CoMSIA Models on Histamine H3 Antagonists by Different Variable Selection Methods

    PubMed Central

    Ghasemi, Jahan B.; Tavakoli, Hossein

    2012-01-01

    The aim of this study is to enhance the predictivity power of CoMFA and CoMSIA models by means of different variable selection algorithms. The genetic algorithm (GA), successive projection algorithm (SPA), stepwise multiple linear regression (SW-MLR), and the enhanced replacement method (ERM) were used and tested as variable selection algorithms. Then, the selected variables were used to generate a simple and predictive model by the multilinear regression algorithm. A set of 74 histamine H3 antagonists were split into 40 compounds as a training set, and 17 compounds as a test set, by the Kennard-Stone algorithm. Before splitting the data, 17 compounds were randomly selected from the pool of the whole data set as an evaluation set without any supervision, pretreatment, or visual inspection. Among applied variable selection algorithms, ERM had noticeable improvement on the statistical parameters. The r2 values of training, test, and evaluation sets for the ERM-MLR model using CoMFA fields were 0.9560, 0.8630, and 0.8460 and using the CoMSIA fields were 0.9800, 0.8521, and 0.9080, respectively. In this study, the principles of organization for economic cooperation and development (OECD) for regulatory acceptability of QSARs are considered. PMID:23008805

  11. 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.

  12. Pole coordinates data prediction by combination of least squares extrapolation and double autoregressive prediction

    NASA Astrophysics Data System (ADS)

    Kosek, Wieslaw

    2016-04-01

    Future Earth Orientation Parameters data are needed to compute real time transformation between the celestial and terrestrial reference frames. This transformation is realized by predictions of x, y pole coordinates data, UT1-UTC data and precesion-nutation extrapolation model. This paper is focused on the pole coordinates data prediction by combination of the least-squares (LS) extrapolation and autoregressive (AR) prediction models (LS+AR). The AR prediction which is applied to the LS extrapolation residuals of pole coordinates data does not able to predict all frequency bands of them and it is mostly tuned to predict subseasonal oscillations. The absolute values of differences between pole coordinates data and their LS+AR predictions increase with prediction length and depend mostly on starting prediction epochs, thus time series of these differences for 2, 4 and 8 weeks in the future were analyzed. Time frequency spectra of these differences for different prediction lengths are very similar showing some power in the frequency band corresponding to the prograde Chandler and annual oscillations, which means that the increase of prediction errors is caused by mismodelling of these oscillations by the LS extrapolation model. Thus, the LS+AR prediction method can be modified by taking into additional AR prediction correction computed from time series of these prediction differences for different prediction lengths. This additional AR prediction is mostly tuned to the seasonal frequency band of pole coordinates data.

  13. 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.

  14. 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.

  15. Fused Lasso Additive Model

    PubMed Central

    Petersen, Ashley; Witten, Daniela; Simon, Noah

    2016-01-01

    We consider the problem of predicting an outcome variable using p covariates that are measured on n independent observations, in a setting in which additive, flexible, and interpretable fits are desired. We propose the fused lasso additive model (FLAM), in which each additive function is estimated to be piecewise constant with a small number of adaptively-chosen knots. FLAM is the solution to a convex optimization problem, for which a simple algorithm with guaranteed convergence to a global optimum is provided. FLAM is shown to be consistent in high dimensions, and an unbiased estimator of its degrees of freedom is proposed. We evaluate the performance of FLAM in a simulation study and on two data sets. Supplemental materials are available online, and the R package flam is available on CRAN. PMID:28239246

  16. Correlation between computerised findings and Newman's scaling on vascularity using power Doppler ultrasonography imaging and its predictive value in patients with plantar fasciitis

    PubMed Central

    Chen, H; Ho, H M; Ying, M; Fu, S N

    2012-01-01

    Objectives The purpose of this study was to correlate findings on small vessel vascularity between computerised findings and Newman's scaling using power Doppler ultrasonography (PDU) imaging and its predictive value in patients with plantar fasciitis. Methods PDU was performed on 44 patients (age range 30–66 years; mean age 48 years) with plantar fasciitis and 46 healthy subjects (age range 18–61 years; mean age 36 years). The vascularity was quantified using ultrasound images by a customised software program and graded by Newman's grading scale. Vascular index (VI) was calculated from the software program as the ratio of the number of colour pixels to the total number of pixels within a standardised selected area of proximal plantar fascia. The 46 healthy subjects were examined on 2 occasions 7–10 days apart, and 18 of them were assessed by 2 examiners. Statistical analyses were performed using intraclass correlation coefficient and linear regression analysis. Results Good correlation was found between the averaged VI ratios and Newman's qualitative scale (ρ = 0.70; p<0.001). Intratester and intertester reliability were 0.89 and 0.61, respectively. Furthermore, higher VI was correlated with less reduction in pain after physiotherapeutic intervention. Conclusions The computerised VI not only has a high level of concordance with the Newman grading scale but is also reliable in reflecting the vascularity of proximal plantar fascia, and can predict pain reduction after intervention. This index can be used to characterise the changes in vascularity of patients with plantar fasciitis, and it may also be helpful for evaluating treatment and monitoring the progress after intervention in future studies. PMID:22167513

  17. Group Sparse Additive Models

    PubMed Central

    Yin, Junming; Chen, Xi; Xing, Eric P.

    2016-01-01

    We consider the problem of sparse variable selection in nonparametric additive models, with the prior knowledge of the structure among the covariates to encourage those variables within a group to be selected jointly. Previous works either study the group sparsity in the parametric setting (e.g., group lasso), or address the problem in the nonparametric setting without exploiting the structural information (e.g., sparse additive models). In this paper, we present a new method, called group sparse additive models (GroupSpAM), which can handle group sparsity in additive models. We generalize the ℓ1/ℓ2 norm to Hilbert spaces as the sparsity-inducing penalty in GroupSpAM. Moreover, we derive a novel thresholding condition for identifying the functional sparsity at the group level, and propose an efficient block coordinate descent algorithm for constructing the estimate. We demonstrate by simulation that GroupSpAM substantially outperforms the competing methods in terms of support recovery and prediction accuracy in additive models, and also conduct a comparative experiment on a real breast cancer dataset.

  18. Smoking-related thoughts and microbehaviours and their predictive power for quitting: Findings from the International Tobacco Control (ITC) China Survey

    PubMed Central

    Li, Lin; Borland, Ron; Fong, Geoffrey T.; Jiang, Yuan; Yang, Yan; Wang, Lili; Partos, Timea R.; Thrasher, James F.

    2015-01-01

    Background Negative attitudes to smoking are well-established predictors of intentions to quit and quit behaviours, but less attention has been given to whether quitting is influenced by smoking-related thoughts and microbehaviours that reflect a concern about smoking. Objectives This paper aimed to describe the occurrence of smoking-related thoughts and microbehaviours among Chinese smokers and to examine their predictive power for making quit attempts and sustained abstinence. Methods The data came from the first three waves of the International Tobacco Control China Survey. Four measures of recent thoughts about smoking and two microbehaviour measures (collectively referred to as micro indicators) were examined. Results Most smokers (around three quarters) reported thinking about harms of smoking to themselves or to others at least occasionally, and an increasing minority reported the two microbehaviours of prematurely butting out cigarettes and forgoing them. All micro indicators were positively related to subsequent quit attempts in individual predictor analyses, but only serious thoughts about quitting and -butting out cigarettes had independent relationships. Overall, there was no clear relationship between these micro indicators and sustained abstinence. Conclusions There was a moderately high level of occurrence of recent smoking-related thoughts and microbehaviours among the Chinese adult smokers in the six cities studied. Like in the west, micro indicators of concern about smoking were positively associated with subsequent quit attempts, but unlike in the west, they were largely unrelated to sustained abstinence. PMID:24570098

  19. The Next Big Five Inventory (BFI-2): Developing and Assessing a Hierarchical Model With 15 Facets to Enhance Bandwidth, Fidelity, and Predictive Power.

    PubMed

    Soto, Christopher J; John, Oliver P

    2016-04-07

    Three studies were conducted to develop and validate the Big Five Inventory-2 (BFI-2), a major revision of the Big Five Inventory (BFI). Study 1 specified a hierarchical model of personality structure with 15 facet traits nested within the Big Five domains, and developed a preliminary item pool to measure this structure. Study 2 used conceptual and empirical criteria to construct the BFI-2 domain and facet scales from the preliminary item pool. Study 3 used data from 2 validation samples to evaluate the BFI-2's measurement properties and substantive relations with self-reported and peer-reported criteria. The results of these studies indicate that the BFI-2 is a reliable and valid personality measure, and an important advance over the original BFI. Specifically, the BFI-2 introduces a robust hierarchical structure, controls for individual differences in acquiescent responding, and provides greater bandwidth, fidelity, and predictive power than the original BFI, while still retaining the original measure's conceptual focus, brevity, and ease of understanding. The BFI-2 therefore offers valuable new opportunities for research examining the structure, assessment, development, and life outcomes of personality traits. (PsycINFO Database Record

  20. 18 CFR 33.10 - Additional information.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Additional information. 33.10 Section 33.10 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY REGULATIONS UNDER THE FEDERAL POWER ACT APPLICATIONS UNDER FEDERAL POWER ACT SECTION...

  1. Synchrotron-Based X-ray Microtomography Characterization of the Effect of Processing Variables on Porosity Formation in Laser Power-Bed Additive Manufacturing of Ti-6Al-4V

    NASA Astrophysics Data System (ADS)

    Cunningham, Ross; Narra, Sneha P.; Montgomery, Colt; Beuth, Jack; Rollett, A. D.

    2017-01-01

    The porosity observed in additively manufactured (AM) parts is a potential concern for components intended to undergo high-cycle fatigue without post-processing to remove such defects. The morphology of pores can help identify their cause: irregularly shaped lack of fusion or key-holing pores can usually be linked to incorrect processing parameters, while spherical pores suggest trapped gas. Synchrotron-based x-ray microtomography was performed on laser powder-bed AM Ti-6Al-4V samples over a range of processing conditions to investigate the effects of processing parameters on porosity. The process mapping technique was used to control melt pool size. Tomography was also performed on the powder to measure porosity within the powder that may transfer to the parts. As observed previously in experiments with electron beam powder-bed fabrication, significant variations in porosity were found as a function of the processing parameters. A clear connection between processing parameters and resulting porosity formation mechanism was observed in that inadequate melt pool overlap resulted in lack-of-fusion pores whereas excess power density produced keyhole pores.

  2. Synchrotron-Based X-ray Microtomography Characterization of the Effect of Processing Variables on Porosity Formation in Laser Power-Bed Additive Manufacturing of Ti-6Al-4V

    NASA Astrophysics Data System (ADS)

    Cunningham, Ross; Narra, Sneha P.; Montgomery, Colt; Beuth, Jack; Rollett, A. D.

    2017-03-01

    The porosity observed in additively manufactured (AM) parts is a potential concern for components intended to undergo high-cycle fatigue without post-processing to remove such defects. The morphology of pores can help identify their cause: irregularly shaped lack of fusion or key-holing pores can usually be linked to incorrect processing parameters, while spherical pores suggest trapped gas. Synchrotron-based x-ray microtomography was performed on laser powder-bed AM Ti-6Al-4V samples over a range of processing conditions to investigate the effects of processing parameters on porosity. The process mapping technique was used to control melt pool size. Tomography was also performed on the powder to measure porosity within the powder that may transfer to the parts. As observed previously in experiments with electron beam powder-bed fabrication, significant variations in porosity were found as a function of the processing parameters. A clear connection between processing parameters and resulting porosity formation mechanism was observed in that inadequate melt pool overlap resulted in lack-of-fusion pores whereas excess power density produced keyhole pores.

  3. 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.

  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. 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.

  6. 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

  7. Prostate Specific Antigen (PSA) as Predicting Marker for Clinical Outcome and Evaluation of Early Toxicity Rate after High-Dose Rate Brachytherapy (HDR-BT) in Combination with Additional External Beam Radiation Therapy (EBRT) for High Risk Prostate Cancer.

    PubMed

    Ecke, Thorsten H; Huang-Tiel, Hui-Juan; Golka, Klaus; Selinski, Silvia; Geis, Berit Christine; Koswig, Stephan; Bathe, Katrin; Hallmann, Steffen; Gerullis, Holger

    2016-11-10

    High-dose-rate brachytherapy (HDR-BT) with external beam radiation therapy (EBRT) is a common treatment option for locally advanced prostate cancer (PCa). Seventy-nine male patients (median age 71 years, range 50 to 79) with high-risk PCa underwent HDR-BT following EBRT between December 2009 and January 2016 with a median follow-up of 21 months. HDR-BT was administered in two treatment sessions (one week interval) with 9 Gy per fraction using a planning system and the Ir192 treatment unit GammaMed Plus iX. EBRT was performed with CT-based 3D-conformal treatment planning with a total dose administration of 50.4 Gy with 1.8 Gy per fraction and five fractions per week. Follow-up for all patients was organized one, three, and five years after radiation therapy to evaluate early and late toxicity side effects, metastases, local recurrence, and prostate-specific antigen (PSA) value measured in ng/mL. The evaluated data included age, PSA at time of diagnosis, PSA density, BMI (body mass index), Gleason score, D'Amico risk classification for PCa, digital rectal examination (DRE), PSA value after one/three/five year(s) follow-up (FU), time of follow-up, TNM classification, prostate volume, and early toxicity rates. Early toxicity rates were 8.86% for gastrointestinal, and 6.33% for genitourinary side effects. Of all treated patients, 84.81% had no side effects. All reported complications in early toxicity were grade 1. PSA density at time of diagnosis (p = 0.009), PSA on date of first HDR-BT (p = 0.033), and PSA on date of first follow-up after one year (p = 0.025) have statistical significance on a higher risk to get a local recurrence during follow-up. HDR-BT in combination with additional EBRT in the presented design for high-risk PCa results in high biochemical control rates with minimal side-effects. PSA is a negative predictive biomarker for local recurrence during follow-up. A longer follow-up is needed to assess long-term outcome and toxicities.

  8. Prostate Specific Antigen (PSA) as Predicting Marker for Clinical Outcome and Evaluation of Early Toxicity Rate after High-Dose Rate Brachytherapy (HDR-BT) in Combination with Additional External Beam Radiation Therapy (EBRT) for High Risk Prostate Cancer

    PubMed Central

    Ecke, Thorsten H.; Huang-Tiel, Hui-Juan; Golka, Klaus; Selinski, Silvia; Geis, Berit Christine; Koswig, Stephan; Bathe, Katrin; Hallmann, Steffen; Gerullis, Holger

    2016-01-01

    High-dose-rate brachytherapy (HDR-BT) with external beam radiation therapy (EBRT) is a common treatment option for locally advanced prostate cancer (PCa). Seventy-nine male patients (median age 71 years, range 50 to 79) with high-risk PCa underwent HDR-BT following EBRT between December 2009 and January 2016 with a median follow-up of 21 months. HDR-BT was administered in two treatment sessions (one week interval) with 9 Gy per fraction using a planning system and the Ir192 treatment unit GammaMed Plus iX. EBRT was performed with CT-based 3D-conformal treatment planning with a total dose administration of 50.4 Gy with 1.8 Gy per fraction and five fractions per week. Follow-up for all patients was organized one, three, and five years after radiation therapy to evaluate early and late toxicity side effects, metastases, local recurrence, and prostate-specific antigen (PSA) value measured in ng/mL. The evaluated data included age, PSA at time of diagnosis, PSA density, BMI (body mass index), Gleason score, D’Amico risk classification for PCa, digital rectal examination (DRE), PSA value after one/three/five year(s) follow-up (FU), time of follow-up, TNM classification, prostate volume, and early toxicity rates. Early toxicity rates were 8.86% for gastrointestinal, and 6.33% for genitourinary side effects. Of all treated patients, 84.81% had no side effects. All reported complications in early toxicity were grade 1. PSA density at time of diagnosis (p = 0.009), PSA on date of first HDR-BT (p = 0.033), and PSA on date of first follow-up after one year (p = 0.025) have statistical significance on a higher risk to get a local recurrence during follow-up. HDR-BT in combination with additional EBRT in the presented design for high-risk PCa results in high biochemical control rates with minimal side-effects. PSA is a negative predictive biomarker for local recurrence during follow-up. A longer follow-up is needed to assess long-term outcome and toxicities. PMID:27834929

  9. 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

  10. Dynamic power flow controllers

    DOEpatents

    Divan, Deepakraj M.; Prasai, Anish

    2017-03-07

    Dynamic power flow controllers are provided. A dynamic power flow controller may comprise a transformer and a power converter. The power converter is subject to low voltage stresses and not floated at line voltage. In addition, the power converter is rated at a fraction of the total power controlled. A dynamic power flow controller controls both the real and the reactive power flow between two AC sources having the same frequency. A dynamic power flow controller inserts a voltage with controllable magnitude and phase between two AC sources; thereby effecting control of active and reactive power flows between two AC sources.

  11. 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…

  12. 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.

  13. 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

  14. Autoantibody Signature Enhances the Positive Predictive Power of Computed Tomography and Nodule-Based Risk Models for Detection of Lung Cancer

    PubMed Central

    Massion, Pierre P.; Healey, Graham F.; Peek, Laura J.; Fredericks, Lynn; Sewell, Herb F.; Murray, Andrea; Robertson, John F. R.

    2017-01-01

    Introduction The incidence of pulmonary nodules is increasing with the movement toward screening for lung cancer by low-dose computed tomography. Given the large number of benign nodules detected by computed tomography, an adjunctive test capable of distinguishing malignant from benign nodules would benefit practitioners. The ability of the EarlyCDT-Lung blood test (Oncimmune Ltd., Nottingham, United Kingdom) to make this distinction by measuring autoantibodies to seven tumor-associated antigens was evaluated in a prospective registry. Methods Of the members of a cohort of 1987 individuals with Health Insurance Portability and Accountability Act authorization, those with pulmonary nodules detected, imaging, and pathology reports were reviewed. All patients for whom a nodule was identified within 6 months of testing by EarlyCDT-Lung were included. The additivity of the test to nodule size and nodule-based risk models was explored. Results A total of 451 patients (32%) had at least one nodule, leading to 296 eligible patients after exclusions, with a lung cancer prevalence of 25%. In 4- to 20-mm nodules, a positive test result represented a greater than twofold increased relative risk for development of lung cancer as compared with a negative test result. Also, when the “both-positive rule” for combining binary tests was used, adding EarlyCDT-Lung to risk models improved diagnostic performance with high specificity (>92%) and positive predictive value (>70%). Conclusions A positive autoantibody test result reflects a significant increased risk for malignancy in lung nodules 4 to 20 mm in largest diameter. These data confirm that EarlyCDT-Lung may add value to the armamentarium of the practitioner in assessing the risk for malignancy in indeterminate pulmonary nodules. PMID:27615397

  15. 18 CFR 5.21 - Additional information.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 18 Conservation of Power and Water Resources 1 2012-04-01 2012-04-01 false Additional information. 5.21 Section 5.21 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY REGULATIONS UNDER THE FEDERAL POWER ACT INTEGRATED LICENSE APPLICATION PROCESS §...

  16. 18 CFR 5.21 - Additional information.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Additional information. 5.21 Section 5.21 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY REGULATIONS UNDER THE FEDERAL POWER ACT INTEGRATED LICENSE APPLICATION PROCESS §...

  17. 18 CFR 5.21 - Additional information.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 18 Conservation of Power and Water Resources 1 2013-04-01 2013-04-01 false Additional information. 5.21 Section 5.21 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY REGULATIONS UNDER THE FEDERAL POWER ACT INTEGRATED LICENSE APPLICATION PROCESS §...

  18. 18 CFR 5.21 - Additional information.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 18 Conservation of Power and Water Resources 1 2011-04-01 2011-04-01 false Additional information. 5.21 Section 5.21 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY REGULATIONS UNDER THE FEDERAL POWER ACT INTEGRATED LICENSE APPLICATION PROCESS §...

  19. 18 CFR 5.21 - Additional information.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 18 Conservation of Power and Water Resources 1 2014-04-01 2014-04-01 false Additional information. 5.21 Section 5.21 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY COMMISSION, DEPARTMENT OF ENERGY REGULATIONS UNDER THE FEDERAL POWER ACT INTEGRATED LICENSE APPLICATION PROCESS §...

  20. 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.

  1. 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.

  2. 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