Does NASA SMAP Improve the Accuracy of Power Outage Models?

NASA Astrophysics Data System (ADS)

Quiring, S. M.; McRoberts, D. B.; Toy, B.; Alvarado, B.

2016-12-01

Electric power utilities make critical decisions in the days prior to hurricane landfall that are primarily based on the estimated impact to their service area. For example, utilities must determine how many repair crews to request from other utilities, the amount of material and equipment they will need to make repairs, and where in their geographically expansive service area to station crews and materials. Accurate forecasts of the impact of an approaching hurricane within their service area are critical for utilities in balancing the costs and benefits of different levels of resources. The Hurricane Outage Prediction Model (HOPM) are a family of statistical models that utilize predictions of tropical cyclone windspeed and duration of strong winds, along with power system and environmental variables (e.g., soil moisture, long-term precipitation), to forecast the number and location of power outages. This project assesses whether using NASA SMAP soil moisture improves the accuracy of power outage forecasts as compared to using model-derived soil moisture from NLDAS-2. A sensitivity analysis is employed since there have been very few tropical cyclones making landfall in the United States since SMAP was launched. The HOPM is used to predict power outages for 13 historical tropical cyclones and the model is run using twice, once with NLDAS soil moisture and once with SMAP soil moisture. Our results demonstrate that using SMAP soil moisture can have a significant impact on power outage predictions. SMAP has the potential to enhance the accuracy of power outage forecasts. Improved outage forecasts reduce the duration of power outages which reduces economic losses and accelerates recovery.

Fractionating power and outlet stream polydispersity in asymmetrical flow field-flow fractionation. Part I: isocratic operation.

PubMed

Williams, P Stephen

2016-05-01

Asymmetrical flow field-flow fractionation (As-FlFFF) has become the most commonly used of the field-flow fractionation techniques. However, because of the interdependence of the channel flow and the cross flow through the accumulation wall, it is the most difficult of the techniques to optimize, particularly for programmed cross flow operation. For the analysis of polydisperse samples, the optimization should ideally be guided by the predicted fractionating power. Many experimentalists, however, neglect fractionating power and rely on light scattering detection simply to confirm apparent selectivity across the breadth of the eluted peak. The size information returned by the light scattering software is assumed to dispense with any reliance on theory to predict retention, and any departure of theoretical predictions from experimental observations is therefore considered of no importance. Separation depends on efficiency as well as selectivity, however, and efficiency can be a strong function of retention. The fractionation of a polydisperse sample by field-flow fractionation never provides a perfectly separated series of monodisperse fractions at the channel outlet. The outlet stream has some residual polydispersity, and it will be shown in this manuscript that the residual polydispersity is inversely related to the fractionating power. Due to the strong dependence of light scattering intensity and its angular distribution on the size of the scattering species, the outlet polydispersity must be minimized if reliable size data are to be obtained from the light scattering detector signal. It is shown that light scattering detection should be used with careful control of fractionating power to obtain optimized analysis of polydisperse samples. Part I is concerned with isocratic operation of As-FlFFF, and part II with programmed operation.

Mode-independent attenuation in evanescent-field sensors

NASA Astrophysics Data System (ADS)

Gnewuch, Harald; Renner, Hagen

1995-03-01

Generally, the total power attenuation in multimode evanescent-field sensor waveguides is nonproportional to the bulk absorbance because the modal attenuation constants differ. Hence a direct measurement is difficult and is additionally aggravated because the waveguide absorbance is highly sensitive to the specific launching conditions at the waveguide input. A general asymptotic formula for the modal power attenuation in strongly asymmetric inhomogeneous planar waveguides with arbitrarily distributed weak absorption in the low-index superstrate is derived. Explicit expressions for typical refractive-index profiles are given. Except when very close to the cutoff, the predicted asymptotic attenuation behavior agrees well with exact calculations. The ratio of TM versus TE absorption has been derived to be (2 - n0 2/nf2 ) for arbitrary profiles. Waveguides with a linear refractive-index profile show mode-independent attenuation coefficients within each polarization. Further, the asymptotic sensitivity is independent of the wavelength, so that it should be possible to directly measure the spectral variation of the bulk absorption. The mode independence of the attenuation has been verified experimentally for a second-order polynomial profile, which is close to a linear refractive-index distribution. In contrast, the attenuation in the step-profile waveguide has been found to depend strongly on the mode number, as predicted by theory. A strong spread of the modal attenuation coefficients is also predicted for the parabolic-profile waveguide sensor.

The need for an intermediate mass scale in GUTs

NASA Technical Reports Server (NTRS)

Shafi, Q.

1983-01-01

The minimal SU(5) grand unified field theory (GUT) model fails to resolve the strong charge parity (CP) problem, suffers from the cosmological monopole problem, sheds no light on the nature of the 'dark' mass in the universe, and predicts an unacceptably low value for the baryon asymmetry. All these problems can be overcome in suitable grand unified axion models with an intermediate mass scale of about 10 to the 11th power to 10 to the 12th power GeV. An example based on the gauge group SO(10) is presented. Among other things, it predicts that the axions comprise the 'dark' mass in the universe, and that there exists a galactic monopole flux of 10 to the -8th power to 10 to the -7th power/sq cm/yr. Other topics that are briefly discussed include proton decay, family symmetry, neutrino masses and the gauge hierarchy problem.

Time irreversibility and multifractality of power along single particle trajectories in turbulence

NASA Astrophysics Data System (ADS)

Cencini, Massimo; Biferale, Luca; Boffetta, Guido; De Pietro, Massimo

2017-10-01

The irreversible turbulent energy cascade epitomizes strongly nonequilibrium systems. At the level of single fluid particles, time irreversibility is revealed by the asymmetry of the rate of kinetic energy change, the Lagrangian power, whose moments display a power-law dependence on the Reynolds number, as recently shown by Xu et al. [H. Xu et al., Proc. Natl. Acad. Sci. USA 111, 7558 (2014), 10.1073/pnas.1321682111]. Here Lagrangian power statistics are rationalized within the multifractal model of turbulence, whose predictions are shown to agree with numerical and empirical data. Multifractal predictions are also tested, for very large Reynolds numbers, in dynamical models of the turbulent cascade, obtaining remarkably good agreement for statistical quantities insensitive to the asymmetry and, remarkably, deviations for those probing the asymmetry. These findings raise fundamental questions concerning time irreversibility in the infinite-Reynolds-number limit of the Navier-Stokes equations.

Sex-specific predictive power of 6-minute walk test in chronic heart failure is not enhanced using percent achieved of published reference equations.

PubMed

Frankenstein, Lutz; Zugck, Christian; Nelles, Manfred; Schellberg, Dieter; Katus, Hugo; Remppis, Andrew

2008-04-01

The 6-minute walk test (6MWT) is an established prognostic tool in chronic heart failure. The strong influence of height, weight, age, and sex on 6MWT distance may be accounted for by using percentage achieved of predicted value rather than uncorrected 6MWT values. The study included 1069 patients (862 men) with a mean age 55.2 +/- 11.7 years and mean left ventricular ejection fraction of 29% +/- 10%, attending the heart failure clinic of the University of Heidelberg between 1995 and 2005. The predictive power and accuracy of 6MWT and achieved percentage values according to all available published equations for mortality and mortality or transplant combined were tested separately for each sex. The percentage values varied largely between equations. For all equations, women in New York Heart Association (NYHA) functional class I had higher values than men. Although the 6MWT significantly discriminated all NYHA classes for both sexes, only 1 equation discriminated all NYHA classes. No significant differences in the area under the receiver operating-characteristic curve were noted between achieved percentage values and 6MWT. Despite strong univariate significance, achieved percentage values did not retain multivariate significance. The 6MWT was independent from N-terminal brain natriuretic propeptide, NYHA, left ventricular ejection fraction, and peak oxygen uptake. We confirmed 6MWT to be a strong and independent risk predictor for both sexes. Because the prognostic power of 6MWT is not enhanced using percentage achieved of published reference equations, we suggest recalibration of these reference values rather than discarding this approach.

Offshore Wind Power Integration in severely fluctuating Wind Conditions

NASA Astrophysics Data System (ADS)

von Bremen, L.

2010-09-01

Strong power fluctuations from offshore wind farms that are induced by wind speed fluctuations pose a severe problem to the save integration of offshore wind power into the power supply system. Experience at the first large-scale offshore wind farm Horns Rev showed that spatial smoothing of power fluctuations within a single wind farm is significantly smaller than onshore results suggest when distributed wind farms of 160 MW altogether are connected to a single point of common-coupling. Wind power gradients larger than 10% of the rated capacity within 5 minutes require large amount of regulation power that is very expensive for the grid operator. It must be noted that a wind speed change of only 0.5m/s result in a wind power change of 10% (within the range of 9-11 m/s where the wind power curve is steepest). Hence, it is very important for the grid operator to know if strong fluctuations are likely or not. Observed weather conditions at the German wind energy research platform FINO1 in the German bight are used to quantify wind fluctuations. With a standard power curve these wind fluctuations are transfered to wind power. The aim is to predict the probability of exceedence of certain wind power gradients that occur in a time interval of e.g. 12 hours. During 2006 and 2009 the distribution of wind power fluctuations looks very similar giving hope that distinct atmospheric processes can be determined that act as a trigger. Most often high wind power fluctuations occur in a range of wind speeds between 9-12 m/s as can be expected from the shape of the wind power curve. A cluster analysis of the 500 hPa geopotential height to detect predominant weather regimes shows that high fluctuations are more likely in north-western flow. It is shown that most often high fluctuations occur in non-stable atmospheric stratification. The description of stratification by means of the vertical gradient of the virtual potential temperature is chosen to be indicative for convection, i.e. it can be assumed that a negative gradient indicates convection which leads to strong wind fluctuations in the updraft and downdraft of the cloud. Neural Networks are used to determine the probability of exceedence of wind power gradients from a set of atmospheric parameters that are taken from Numerical Weather Prediction Models. Parameters describing atmospheric stability, that are related to convection (e.g. rain rate) and that forecast wind gusts tend to carry most information to estimate expected wind power fluctuations.

The effect of the oxygen uptake-power output relationship on the prediction of supramaximal oxygen demands.

PubMed

Muniz-Pumares, Daniel; Pedlar, Charles; Godfrey, Richard; Glaister, Mark

2017-01-01

The aim of this study was to investigate the relationship between oxygen uptake (V̇O2) and power output at intensities below and above the lactate threshold (LT) in cyclists; and to determine the reliability of supramaximal power outputs linearly projected from these relationships. Nine male cyclists (mean±standard deviation age: 41±8 years; mass: 77±6 kg, height: 1.79±0.05 m and V̇O2max: 54±7 mL∙kg-1∙min-1) completed two cycling trials each consisting of a step test (10×3 min stages at submaximal incremental intensities) followed by a maximal test to exhaustion. The lines of best fit for V̇O2 and power output were determined for: the entire step test; stages below and above the LT, and from rolling clusters of five consecutive stages. Lines were projected to determine a power output predicted to elicit 110% peak V̇O2. There were strong linear correlations (r≥0.953; P<0.01) between V̇O2 and power output using the three approaches; with the slope, intercept, and projected values of these lines unaffected (P≥0.05) by intensity. The coefficient of variation of the predicted power output at 110% V̇O2max was 6.7% when using all ten submaximal stages. Cyclists exhibit a linear V̇O2 and power output relationship when determined using 3 min stages, which allows for prediction of a supramaximal intensity with acceptable reliability.

Ensemble Data Assimilation of Photovoltaic Power Information in the Convection-permitting High-Resolution Model COSMO-DE

NASA Astrophysics Data System (ADS)

Declair, Stefan; Saint-Drenan, Yves-Marie; Potthast, Roland

2017-04-01

Determining the amount of weather dependent renewable energy is a demanding task for transmission system operators (TSOs) and wind and photovoltaic (PV) prediction errors require the use of reserve power, which generate costs and can - in extreme cases - endanger the security of supply. In the project EWeLiNE funded by the German government, the German Weather Service and the Fraunhofer Institute on Wind Energy and Energy System Technology develop innovative weather- and power forecasting models and tools for grid integration of weather dependent renewable energy. The key part in energy prediction process chains is the numerical weather prediction (NWP) system. Irradiation forecasts from NWP systems are however subject to several sources of error. For PV power prediction, weaknesses of the NWP model to correctly forecast i.e. low stratus, absorption of condensed water or aerosol optical depths are the main sources of errors. Inaccurate radiation schemes (i.e. the two-stream parametrization) are also known as a deficit of NWP systems with regard to irradiation forecast. To mitigate errors like these, latest observations can be used in a pre-processing technique called data assimilation (DA). In DA, not only the initial fields are provided, but the model is also synchronized with reality - the observations - and hence forecast errors are reduced. Besides conventional observation networks like radiosondes, synoptic observations or air reports of wind, pressure and humidity, the number of observations measuring meteorological information indirectly by means of remote sensing such as satellite radiances, radar reflectivities or GPS slant delays strongly increases. Numerous PV plants installed in Germany potentially represent a dense meteorological network assessing irradiation through their power measurements. Forecast accuracy may thus be enhanced by extending the observations in the assimilation by this new source of information. PV power plants can provide information on clouds, aerosol optical depth or low stratus in terms of remote sensing: the power output is strongly dependent on perturbations along the slant between sun position and PV panel. Since these data are not limited to the vertical column above or below the detector, it may thus complement satellite data and compensate weaknesses in the radiation scheme. In this contribution, the used DA technique (Local Ensemble Transform Kalman Filter, LETKF) is shortly sketched. Furthermore, the computation of the model power equivalents is described and first results are presented and discussed.

Qualitative modeling of silica plasma etching using neural network

NASA Astrophysics Data System (ADS)

Kim, Byungwhan; Kwon, Kwang Ho

2003-01-01

An etching of silica thin film is qualitatively modeled by using a neural network. The process was characterized by a 23 full factorial experiment plus one center point, in which the experimental factors and ranges include 100-800 W radio-frequency source power, 100-400 W bias power and gas flow rate ratio CHF3/CF4. The gas flow rate ratio varied from 0.2 to 5.0. The backpropagation neural network (BPNN) was trained on nine experiments and tested on six experiments, not pertaining to the original training data. The prediction ability of the BPNN was optimized as a function of the training parameters. Prediction errors are 180 Å/min and 1.33, for the etch rate and anisotropy models, respectively. Physical etch mechanisms were estimated from the three-dimensional plots generated from the optimized models. Predicted response surfaces were consistent with experimentally measured etch data. The dc bias was correlated to the etch responses to evaluate its contribution. Both the source power (plasma density) and bias power (ion directionality) strongly affected the etch rate. The source power was the most influential factor for the etch rate. A conflicting effect between the source and bias powers was noticed with respect to the anisotropy. The dc bias played an important role in understanding or separating physical etch mechanisms.

Power in everyday life.

PubMed

Smith, Pamela K; Hofmann, Wilhelm

2016-09-06

How does power manifest itself in everyday life? Using experience-sampling methodology, we investigated the prevalence, sources, and correlates of power in people's natural environments. Participants experienced power-relevant situations regularly, though not frequently. High power was not restricted to a limited few: almost half of the sample reported experiencing high-power positions. Positional power and subjective feelings of power were strongly related but had unique relations with several individual difference measures and independent effects on participants' affect, cognition, and interpersonal relations. Subjective feelings of power resulted more from within-participant situational fluctuation, such as the social roles participants held at different times, than from stable differences between people. Our data supported some theoretical predictions about power's effects on affect, cognition, and interpersonal relations, but qualified others, particularly highlighting the role of responsibility in power's effects. Although the power literature has focused on high power, we found stronger effects of low power than high power.

Revisiting Grodzins systematics of B(E2) values

DOE PAGES

Pritychenko, B.; Birch, M.; Singh, B.

2017-04-03

Using Grodzins formalism, we analyze systematics of our latest evaluated B(E2) data for all the even–even nuclei in Z=2–104. The analysis indicates a low predictive power of systematics for a large number of cases, and a strong correlation between B(E2) fit values and nuclear structure effects. These findings provide a strong rationale for introduction of individual or elemental (grouped by Z) fit parameters. The current estimates of quadrupole collectivities for systematics of even–even nuclei yield complementary values for comparison with experimental results and theoretical calculations. Furthermore, the lists of fit parameters and predicted B(E2) values are given and possible implicationsmore » are discussed.« less

Predictive power of food web models based on body size decreases with trophic complexity.

PubMed

Jonsson, Tomas; Kaartinen, Riikka; Jonsson, Mattias; Bommarco, Riccardo

2018-05-01

Food web models parameterised using body size show promise to predict trophic interaction strengths (IS) and abundance dynamics. However, this remains to be rigorously tested in food webs beyond simple trophic modules, where indirect and intraguild interactions could be important and driven by traits other than body size. We systematically varied predator body size, guild composition and richness in microcosm insect webs and compared experimental outcomes with predictions of IS from models with allometrically scaled parameters. Body size was a strong predictor of IS in simple modules (r 2  = 0.92), but with increasing complexity the predictive power decreased, with model IS being consistently overestimated. We quantify the strength of observed trophic interaction modifications, partition this into density-mediated vs. behaviour-mediated indirect effects and show that model shortcomings in predicting IS is related to the size of behaviour-mediated effects. Our findings encourage development of dynamical food web models explicitly including and exploring indirect mechanisms. © 2018 John Wiley & Sons Ltd/CNRS.

Reproducing tailing in breakthrough curves: Are statistical models equally representative and predictive?

NASA Astrophysics Data System (ADS)

Pedretti, Daniele; Bianchi, Marco

2018-03-01

Breakthrough curves (BTCs) observed during tracer tests in highly heterogeneous aquifers display strong tailing. Power laws are popular models for both the empirical fitting of these curves, and the prediction of transport using upscaling models based on best-fitted estimated parameters (e.g. the power law slope or exponent). The predictive capacity of power law based upscaling models can be however questioned due to the difficulties to link model parameters with the aquifers' physical properties. This work analyzes two aspects that can limit the use of power laws as effective predictive tools: (a) the implication of statistical subsampling, which often renders power laws undistinguishable from other heavily tailed distributions, such as the logarithmic (LOG); (b) the difficulties to reconcile fitting parameters obtained from models with different formulations, such as the presence of a late-time cutoff in the power law model. Two rigorous and systematic stochastic analyses, one based on benchmark distributions and the other on BTCs obtained from transport simulations, are considered. It is found that a power law model without cutoff (PL) results in best-fitted exponents (αPL) falling in the range of typical experimental values reported in the literature (1.5 < αPL < 4). The PL exponent tends to lower values as the tailing becomes heavier. Strong fluctuations occur when the number of samples is limited, due to the effects of subsampling. On the other hand, when the power law model embeds a cutoff (PLCO), the best-fitted exponent (αCO) is insensitive to the degree of tailing and to the effects of subsampling and tends to a constant αCO ≈ 1. In the PLCO model, the cutoff rate (λ) is the parameter that fully reproduces the persistence of the tailing and is shown to be inversely correlated to the LOG scale parameter (i.e. with the skewness of the distribution). The theoretical results are consistent with the fitting analysis of a tracer test performed during the MADE-5 experiment. It is shown that a simple mechanistic upscaling model based on the PLCO formulation is able to predict the ensemble of BTCs from the stochastic transport simulations without the need of any fitted parameters. The model embeds the constant αCO = 1 and relies on a stratified description of the transport mechanisms to estimate λ. The PL fails to reproduce the ensemble of BTCs at late time, while the LOG model provides consistent results as the PLCO model, however without a clear mechanistic link between physical properties and model parameters. It is concluded that, while all parametric models may work equally well (or equally wrong) for the empirical fitting of the experimental BTCs tails due to the effects of subsampling, for predictive purposes this is not true. A careful selection of the proper heavily tailed models and corresponding parameters is required to ensure physically-based transport predictions.

Power in everyday life

PubMed Central

Hofmann, Wilhelm

2016-01-01

How does power manifest itself in everyday life? Using experience-sampling methodology, we investigated the prevalence, sources, and correlates of power in people’s natural environments. Participants experienced power-relevant situations regularly, though not frequently. High power was not restricted to a limited few: almost half of the sample reported experiencing high-power positions. Positional power and subjective feelings of power were strongly related but had unique relations with several individual difference measures and independent effects on participants’ affect, cognition, and interpersonal relations. Subjective feelings of power resulted more from within-participant situational fluctuation, such as the social roles participants held at different times, than from stable differences between people. Our data supported some theoretical predictions about power’s effects on affect, cognition, and interpersonal relations, but qualified others, particularly highlighting the role of responsibility in power’s effects. Although the power literature has focused on high power, we found stronger effects of low power than high power. PMID:27551069

Correlating Structural Order with Structural Rearrangement in Dusty Plasma Liquids: Can Structural Rearrangement be Predicted by Static Structural Information?

NASA Astrophysics Data System (ADS)

Su, Yen-Shuo; Liu, Yu-Hsuan; I, Lin

2012-11-01

Whether the static microstructural order information is strongly correlated with the subsequent structural rearrangement (SR) and their predicting power for SR are investigated experimentally in the quenched dusty plasma liquid with microheterogeneities. The poor local structural order is found to be a good alarm to identify the soft spot and predict the short term SR. For the site with good structural order, the persistent time for sustaining the structural memory until SR has a large mean value but a broad distribution. The deviation of the local structural order from that averaged over nearest neighbors serves as a good second alarm to further sort out the short time SR sites. It has the similar sorting power to that using the temporal fluctuation of the local structural order over a small time interval.

Cognitive Styles in Admission Procedures for Assessing Candidates of Architecture

ERIC Educational Resources Information Center

Casakin, Hernan; Gigi, Ariela

2016-01-01

Cognitive style has a strong predictive power in academic and professional success. This study investigated the cognitive profile of candidates studying architecture. Specifically, it explored the relation between visual and verbal cognitive styles, and the performance of candidates in admission procedures. The cognitive styles of candidates who…

Direct solar-pumped iodine laser amplifier

NASA Technical Reports Server (NTRS)

Han, Kwang S.; Kim, K. H.; Stock, L. V.

1987-01-01

The improvement on the collection system of the Tarmarack Solar Simulator beam was attemped. The basic study of evaluating the solid state laser materials for the solar pumping and also the work to construct a kinetic model algorithm for the flashlamp pumped iodine lasers were carried out. It was observed that the collector cone worked better than the lens assembly in order to collect the solar simulator beam and to focus it down to a strong power density. The study on the various laser materials and their lasing characteristics shows that the neodymium and chromium co-doped gadolinium scandium gallium garnet (Nr:Cr:GSGG) may be a strong candidate for the high power solar pumped solid state laser crystal. On the other hand the improved kinetic modeling for the flashlamp pumped iodine laser provides a good agreement between the theoretical model and the experimental data on the laser power output, and predicts the output parameters of a solar pumped iodine laser.

Model of Energy Spectrum Parameters of Ground Level Enhancement Events in Solar Cycle 23

NASA Astrophysics Data System (ADS)

Wu, S.-S.; Qin, G.

2018-01-01

Mewaldt et al. (2012) fitted the observations of the ground level enhancement (GLE) events during solar cycle 23 to the double power law equation to obtain the four spectral parameters, the normalization constant C, low-energy power law slope γ1, high-energy power law slope γ2, and break energy E0. There are 16 GLEs from which we select 13 for study by excluding some events with complicated situation. We analyze the four parameters with conditions of the corresponding solar events. According to solar event conditions, we divide the GLEs into two groups, one with strong acceleration by interplanetary shocks and another one without strong acceleration. By fitting the four parameters with solar event conditions we obtain models of the parameters for the two groups of GLEs separately. Therefore, we establish a model of energy spectrum of solar cycle 23 GLEs, which may be used in prediction in the future.

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

Pulsar Polar Cap and Slot Gap Models: Confronting Fermi Data

NASA Technical Reports Server (NTRS)

Harding, Alice K.

2012-01-01

Rotation-powered pulsars are excellent laboratories for studying particle acceleration as well as fundamental physics of strong gravity, strong magnetic fields and relativity. I will review acceleration and gamma-ray emission from the pulsar polar cap and slot gap. Predictions of these models can be tested with the data set on pulsars collected by the Large Area Telescope on the Fermi Gamma-Ray Telescope over the last four years, using both detailed light curve fitting and population synthesis.

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.

An extended fatty liver index to predict non-alcoholic fatty liver disease.

PubMed

Kantartzis, K; Rettig, I; Staiger, H; Machann, J; Schick, F; Scheja, L; Gastaldelli, A; Bugianesi, E; Peter, A; Schulze, M B; Fritsche, A; Häring, H-U; Stefan, N

2017-06-01

In clinical practice, there is a strong interest in non-invasive markers of non-alcoholic fatty liver disease (NAFLD). Our hypothesis was that the fold-change in plasma triglycerides (TG) during a 2-h oral glucose tolerance test (fold-change TG OGTT ) in concert with blood glucose and lipid parameters, and the rs738409 C>G single nucleotide polymorphism (SNP) in PNPLA3 might improve the power of the widely used fatty liver index (FLI) to predict NAFLD. The liver fat content of 330 subjects was quantified by 1 H-magnetic resonance spectroscopy. Blood parameters were measured during fasting and after a 2-h OGTT. A subgroup of 213 subjects underwent these measurements before and after 9 months of a lifestyle intervention. The fold-change TG OGTT was closely associated with liver fat content (r=0.51, P<0.0001), but had less power to predict NAFLD (AUROC=0.75) than the FLI (AUROC=0.79). Not only was the fold-change TG OGTT independently associated with liver fat content and NAFLD, but so also were the 2-h blood glucose level and rs738409 C>G SNP in PNPLA3. In fact, a novel index (extended FLI) generated from these and the usual FLI parameters considerably increased its power to predict NAFLD (AUROC=0.79-0.86). The extended FLI also increased the power to predict changes in liver fat content with a lifestyle intervention (n=213; standardized beta coefficient: 0.23-0.29). This study has provided novel data confirming that the OGTT-derived fold-change TG OGTT and 2-h glucose level, together with the rs738409 C>G SNP in PNPLA3, allow calculation of an extended FLI that considerably improves its power to predict NAFLD. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Thermal Management Research for Power Generation. Delivery Order 0002 - Volume 2: Closed-Loop Spray Cooling of High-Power Semiconductor Lasers

DTIC Science & Technology

2002-12-01

surface temperature for a given heat flux [2]. Mudawar and Valentine conducted an experimental study of spray cooling to determine local quenching... Mudawar presented a CHF correlation with suitable dimensionless parameters that accurately predicted data for FC-72, FC-87 and water [5]. The 2...correlation by Estes and Mudawar had a strong dependence of CHF on volumetric flux and Sauter mean diameter. Sehmbey et al. developed a semiempirical

Trait psychopathy, emotional intelligence, and criminal thinking: Predicting illegal behavior among college students.

PubMed

Fix, Rebecca L; Fix, Spencer T

2015-01-01

Research focusing on individuals high on trait psychopathy remains limited. Higher trait psychopathy is associated with lower levels of emotional intelligence and increased participation in illegal behavior. Additionally, research has confirmed significantly higher levels of criminal thinking and lower levels of empathy in the incarcerated psychopathic population. However, the relationships between trait psychopathy and criminal thinking have not been researched in the community or college population. To test for such differences, questionnaires containing relevant measures were administered to 111 college students. Results indicated that higher levels of trait psychopathy were significantly related to less caring for others, intrapersonal understanding, and general mood, and greater interpersonal functioning and stress management. Furthermore, trait psychopathy was a strong predictor of violent, property, drug, and status offenses. Power-oriented criminal thinking was also predictive of violent behaviors, and entitlement predicted property offending. Results suggest emotional intelligence is important for predicting psychopathy, and trait psychopathy is a strong predictor of all types of illegal behaviors among the non-incarcerated population. Published by Elsevier Ltd.

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.

DEM modeling of ball mills with experimental validation: influence of contact parameters on charge motion and power draw

NASA Astrophysics Data System (ADS)

Boemer, Dominik; Ponthot, Jean-Philippe

2017-01-01

Discrete element method simulations of a 1:5-scale laboratory ball mill are presented in this paper to study the influence of the contact parameters on the charge motion and the power draw. The position density limit is introduced as an efficient mathematical tool to describe and to compare the macroscopic charge motion in different scenarios, i.a. with different values of the contact parameters. While the charge motion and the power draw are relatively insensitive to the stiffness and the damping coefficient of the linear spring-slider-damper contact law, the coefficient of friction has a strong influence since it controls the sliding propensity of the charge. Based on the experimental calibration and validation by charge motion photographs and power draw measurements, the descriptive and predictive capabilities of the position density limit and the discrete element method are demonstrated, i.e. the real position of the charge is precisely delimited by the respective position density limit and the power draw can be predicted with an accuracy of about 5 %.

Non-inductive current drive and transport in high βN plasmas in JET

NASA Astrophysics Data System (ADS)

Voitsekhovitch, I.; Alper, B.; Brix, M.; Budny, R. V.; Buratti, P.; Challis, C. D.; Ferron, J.; Giroud, C.; Joffrin, E.; Laborde, L.; Luce, T. C.; McCune, D.; Menard, J.; Murakami, M.; Park, J. M.; JET-EFDA contributors

2009-05-01

A route to stationary MHD stable operation at high βN has been explored at the Joint European Torus (JET) by optimizing the current ramp-up, heating start time and the waveform of neutral beam injection (NBI) power. In these scenarios the current ramp-up has been accompanied by plasma pre-heat (or the NBI has been started before the current flat-top) and NBI power up to 22 MW has been applied during the current flat-top. In the discharges considered transient total βN ≈ 3.3 and stationary (during high power phase) βN ≈ 3 have been achieved by applying the feedback control of βN with the NBI power in configurations with monotonic or flat core safety factor profile and without an internal transport barrier (ITB). The transport and current drive in this scenario is analysed here by using the TRANSP and ASTRA codes. The interpretative analysis performed with TRANSP shows that 50-70% of current is driven non-inductively; half of this current is due to the bootstrap current which has a broad profile since an ITB was deliberately avoided. The GLF23 transport model predicts the temperature profiles within a ±22% discrepancy with the measurements over the explored parameter space. Predictive simulations with this model show that the E × B rotational shear plays an important role for thermal ion transport in this scenario, producing up to a 40% increase of the ion temperature. By applying transport and current drive models validated in self-consistent simulations of given reference scenarios in a wider parameter space, the requirements for fully non-inductive stationary operation at JET are estimated. It is shown that the strong stiffness of the temperature profiles predicted by the GLF23 model restricts the bootstrap current at larger heating power. In this situation full non-inductive operation without an ITB can be rather expensive strongly relying on the external non-inductive current drive sources.

Titration Curves: Fact and Fiction.

ERIC Educational Resources Information Center

Chamberlain, John

1997-01-01

Discusses ways in which datalogging equipment can enable titration curves to be measured accurately and how computing power can be used to predict the shape of curves. Highlights include sources of error, use of spreadsheets to generate titration curves, titration of a weak acid with a strong alkali, dibasic acids, weak acid and weak base, and…

Optimizing Wind Power Generation while Minimizing Wildlife Impacts in an Urban Area

PubMed Central

Bohrer, Gil; Zhu, Kunpeng; Jones, Robert L.; Curtis, Peter S.

2013-01-01

The location of a wind turbine is critical to its power output, which is strongly affected by the local wind field. Turbine operators typically seek locations with the best wind at the lowest level above ground since turbine height affects installation costs. In many urban applications, such as small-scale turbines owned by local communities or organizations, turbine placement is challenging because of limited available space and because the turbine often must be added without removing existing infrastructure, including buildings and trees. The need to minimize turbine hazard to wildlife compounds the challenge. We used an exclusion zone approach for turbine-placement optimization that incorporates spatially detailed maps of wind distribution and wildlife densities with power output predictions for the Ohio State University campus. We processed public GIS records and airborne lidar point-cloud data to develop a 3D map of all campus buildings and trees. High resolution large-eddy simulations and long-term wind climatology were combined to provide land-surface-affected 3D wind fields and the corresponding wind-power generation potential. This power prediction map was then combined with bird survey data. Our assessment predicts that exclusion of areas where bird numbers are highest will have modest effects on the availability of locations for power generation. The exclusion zone approach allows the incorporation of wildlife hazard in wind turbine siting and power output considerations in complex urban environments even when the quantitative interaction between wildlife behavior and turbine activity is unknown. PMID:23409117

Optimizing wind power generation while minimizing wildlife impacts in an urban area.

PubMed

Bohrer, Gil; Zhu, Kunpeng; Jones, Robert L; Curtis, Peter S

2013-01-01

The location of a wind turbine is critical to its power output, which is strongly affected by the local wind field. Turbine operators typically seek locations with the best wind at the lowest level above ground since turbine height affects installation costs. In many urban applications, such as small-scale turbines owned by local communities or organizations, turbine placement is challenging because of limited available space and because the turbine often must be added without removing existing infrastructure, including buildings and trees. The need to minimize turbine hazard to wildlife compounds the challenge. We used an exclusion zone approach for turbine-placement optimization that incorporates spatially detailed maps of wind distribution and wildlife densities with power output predictions for the Ohio State University campus. We processed public GIS records and airborne lidar point-cloud data to develop a 3D map of all campus buildings and trees. High resolution large-eddy simulations and long-term wind climatology were combined to provide land-surface-affected 3D wind fields and the corresponding wind-power generation potential. This power prediction map was then combined with bird survey data. Our assessment predicts that exclusion of areas where bird numbers are highest will have modest effects on the availability of locations for power generation. The exclusion zone approach allows the incorporation of wildlife hazard in wind turbine siting and power output considerations in complex urban environments even when the quantitative interaction between wildlife behavior and turbine activity is unknown.

Analysis of significant factors for dengue fever incidence prediction.

PubMed

Siriyasatien, Padet; Phumee, Atchara; Ongruk, Phatsavee; Jampachaisri, Katechan; Kesorn, Kraisak

2016-04-16

Many popular dengue forecasting techniques have been used by several researchers to extrapolate dengue incidence rates, including the K-H model, support vector machines (SVM), and artificial neural networks (ANN). The time series analysis methodology, particularly ARIMA and SARIMA, has been increasingly applied to the field of epidemiological research for dengue fever, dengue hemorrhagic fever, and other infectious diseases. The main drawback of these methods is that they do not consider other variables that are associated with the dependent variable. Additionally, new factors correlated to the disease are needed to enhance the prediction accuracy of the model when it is applied to areas of similar climates, where weather factors such as temperature, total rainfall, and humidity are not substantially different. Such drawbacks may consequently lower the predictive power for the outbreak. The predictive power of the forecasting model-assessed by Akaike's information criterion (AIC), Bayesian information criterion (BIC), and the mean absolute percentage error (MAPE)-is improved by including the new parameters for dengue outbreak prediction. This study's selected model outperforms all three other competing models with the lowest AIC, the lowest BIC, and a small MAPE value. The exclusive use of climate factors from similar locations decreases a model's prediction power. The multivariate Poisson regression, however, effectively forecasts even when climate variables are slightly different. Female mosquitoes and seasons were strongly correlated with dengue cases. Therefore, the dengue incidence trends provided by this model will assist the optimization of dengue prevention. The present work demonstrates the important roles of female mosquito infection rates from the previous season and climate factors (represented as seasons) in dengue outbreaks. Incorporating these two factors in the model significantly improves the predictive power of dengue hemorrhagic fever forecasting models, as confirmed by AIC, BIC, and MAPE.

Sprinting performance on the Woodway Curve 3.0 is related to muscle architecture.

PubMed

Mangine, Gerald T; Fukuda, David H; Townsend, Jeremy R; Wells, Adam J; Gonzalez, Adam M; Jajtner, Adam R; Bohner, Jonathan D; LaMonica, Michael; Hoffman, Jay R; Fragala, Maren S; Stout, Jeffrey R

2015-01-01

To determine if unilateral measures of muscle architecture in the rectus femoris (RF) and vastus lateralis (VL) were related to (and predictive of) sprinting speed and unilateral (and bilateral) force (FRC) and power (POW) during a 30 s maximal sprint on the Woodway Curve 3.0 non-motorized treadmill. Twenty-eight healthy, physically active men (n = 14) and women (n = 14) (age = 22.9 ± 2.4 years; body mass = 77.1 ± 16.2 kg; height = 171.6 ± 11.2 cm; body-fa t = 19.4 ± 8.1%) completed one familiarization and one 30-s maximal sprint on the TM to obtain maximal sprinting speed, POW and FRC. Muscle thickness (MT), cross-sectional area (CSA) and echo intensity (ECHO) of the RF and VL in the dominant (DOM; determined by unilateral sprinting power) and non-dominant (ND) legs were measured via ultrasound. Pearson correlations indicated several significant (p < 0.05) relationships between sprinting performance [POW (peak, DOM and ND), FRC (peak, DOM, ND) and sprinting time] and muscle architecture. Stepwise regression indicated that POW(DOM) was predictive of ipsilateral RF (MT and CSA) and VL (CSA and ECHO), while POW(ND) was predictive of ipsilateral RF (MT and CSA) and VL (CSA); sprinting power/force asymmetry was not predictive of architecture asymmetry. Sprinting time was best predicted by peak power and peak force, though muscle quality (ECHO) and the bilateral percent difference in VL (CSA) were strong architectural predictors. Muscle architecture is related to (and predictive of) TM sprinting performance, while unilateral POW is predictive of ipsilateral architecture. However, the extent to which architecture and other factors (i.e. neuromuscular control and sprinting technique) affect TM performance remains unknown.

AEDT: A new concept for ecological dynamics in the ever-changing world.

PubMed

Chesson, Peter

2017-05-01

The important concept of equilibrium has always been controversial in ecology, but a new, more general concept, an asymptotic environmentally determined trajectory (AEDT), overcomes many concerns with equilibrium by realistically incorporating long-term climate change while retaining much of the predictive power of a stable equilibrium. A population or ecological community is predicted to approach its AEDT, which is a function of time reflecting environmental history and biology. The AEDT invokes familiar questions and predictions but in a more realistic context in which consideration of past environments and a future changing profoundly due to human influence becomes possible. Strong applications are also predicted in population genetics, evolution, earth sciences, and economics.

One-electron reduced density matrices of strongly correlated harmonium atoms.

PubMed

Cioslowski, Jerzy

2015-03-21

Explicit asymptotic expressions are derived for the reduced one-electron density matrices (the 1-matrices) of strongly correlated two- and three-electron harmonium atoms in the ground and first excited states. These expressions, which are valid at the limit of small confinement strength ω, yield electron densities and kinetic energies in agreement with the published values. In addition, they reveal the ω(5/6) asymptotic scaling of the exchange components of the electron-electron repulsion energies that differs from the ω(2/3) scaling of their Coulomb and correlation counterparts. The natural orbitals of the totally symmetric ground state of the two-electron harmonium atom are found to possess collective occupancies that follow a mixed power/Gaussian dependence on the angular momentum in variance with the simple power-law prediction of Hill's asymptotics. Providing rigorous constraints on energies as functionals of 1-matrices, these results are expected to facilitate development of approximate implementations of the density matrix functional theory and ensure their proper description of strongly correlated systems.

Correlations of Power-law Spectral and QPO Features In Black Hole Candidate Sources

NASA Technical Reports Server (NTRS)

Fiorito, Ralph; Titarchuk, Lev

2004-01-01

Recent studies have shown that strong correlations are observed between low frequency QPO s and the spectral power law index for a number of black hole candidate sources (BHCs), when these sources exhibit quasi-steady hard x-ray emission states. The dominant long standing interpretation of QPO's is that they are produced in and are the signature of the thermal accretion disk. Paradoxically, strong QPO's are present even in the cases where the thermal component is negligible. We present a model which identifies the origin of the QPO's and relates them directly to the properties of a compact coronal region which is bounded by the adjustment from Kepleriaa to sub-Kelperian inflow into the BH, and is primarily responsible for the observed power law spectrum. The model also predicts the relationship between high and low frequency QPO's and shows how BH's can be unique identified from observations of the soft states of NS's and BHC's.

Cycling Power Outputs Predict Functional Threshold Power And Maximum Oxygen Uptake.

PubMed

Denham, Joshua; Scott-Hamilton, John; Hagstrom, Amanda D; Gray, Adrian J

2017-09-11

Functional threshold power (FTP) has emerged as a correlate of lactate threshold and is commonly assessed by recreational and professional cyclists for tailored exercise programing. To identify whether results from traditional aerobic and anaerobic cycling tests could predict FTP and V˙ O2max, we analysed the association between estimated FTP, maximum oxygen uptake (V˙ O2max [mlkgmin]) and power outputs obtained from a maximal cycle ergometry cardiopulmonary exercise test (CPET) and a 30-s Wingate test in a heterogeneous cohort of cycle-trained and untrained individuals (N=40, mean±SD; age: 32.6±10.6 y; relative V˙ O2max: 46.8±9.1 mlkgmin). The accuracy and sensitivity of the prediction equations was also assessed in young men (N=11) before and after a 6-wk sprint interval training intervention.Moderate to strong positive correlations were observed between FTP, relative V˙ O2max and power outputs achieved during incremental and 30-s Wingate cycling tests (r=.39-.965, all P<.05). While maximum power achieved during incremental cycle testing (Pmax) and relative V˙ O2max were predictors of FTP (r =.93), age and FTP (Wkg) estimated relative V˙ O2max (r=.80). Our findings confirm that FTP predominantly relies on aerobic metabolism and indicate both prediction models are sensitive enough to detect meaningful exercise-induced changes in FTP and V˙ O2max. Thus, coaches should consider limiting the time and load demands placed on athletes by conducting a maximal cycle ergometry CPET to estimate FTP. Additionally, a 20-min FTP test is a convenient method to assess V˙ O2max and is particularly relevant for exercise professionals without access to expensive CPET equipment.

Enhanced outage prediction modeling for strong extratropical storms and hurricanes in the Northeastern United States

NASA Astrophysics Data System (ADS)

Cerrai, D.; Anagnostou, E. N.; Wanik, D. W.; Bhuiyan, M. A. E.; Zhang, X.; Yang, J.; Astitha, M.; Frediani, M. E.; Schwartz, C. S.; Pardakhti, M.

2016-12-01

The overwhelming majority of human activities need reliable electric power. Severe weather events can cause power outages, resulting in substantial economic losses and a temporary worsening of living conditions. Accurate prediction of these events and the communication of forecasted impacts to the affected utilities is necessary for efficient emergency preparedness and mitigation. The University of Connecticut Outage Prediction Model (OPM) uses regression tree models, high-resolution weather reanalysis and real-time weather forecasts (WRF and NCAR ensemble), airport station data, vegetation and electric grid characteristics and historical outage data to forecast the number and spatial distribution of outages in the power distribution grid located within dense vegetation. Recent OPM improvements consist of improved storm classification and addition of new predictive weather-related variables and are demonstrated using a leave-one-storm-out cross-validation based on 130 severe extratropical storms and two hurricanes (Sandy and Irene) in the Northeast US. We show that it is possible to predict the number of trouble spots causing outages in the electric grid with a median absolute percentage error as low as 27% for some storm types, and at most around 40%, in a scale that varies between four orders of magnitude, from few outages to tens of thousands. This outage information can be communicated to the electric utility to manage allocation of crews and equipment and minimize the recovery time for an upcoming storm hazard.

Increased prognostic accuracy of TBI when a brain electrical activity biomarker is added to loss of consciousness (LOC).

PubMed

Hack, Dallas; Huff, J Stephen; Curley, Kenneth; Naunheim, Roseanne; Ghosh Dastidar, Samanwoy; Prichep, Leslie S

2017-07-01

Extremely high accuracy for predicting CT+ traumatic brain injury (TBI) using a quantitative EEG (QEEG) based multivariate classification algorithm was demonstrated in an independent validation trial, in Emergency Department (ED) patients, using an easy to use handheld device. This study compares the predictive power using that algorithm (which includes LOC and amnesia), to the predictive power of LOC alone or LOC plus traumatic amnesia. ED patients 18-85years presenting within 72h of closed head injury, with GSC 12-15, were study candidates. 680 patients with known absence or presence of LOC were enrolled (145 CT+ and 535 CT- patients). 5-10min of eyes closed EEG was acquired using the Ahead 300 handheld device, from frontal and frontotemporal regions. The same classification algorithm methodology was used for both the EEG based and the LOC based algorithms. Predictive power was evaluated using area under the ROC curve (AUC) and odds ratios. The QEEG based classification algorithm demonstrated significant improvement in predictive power compared with LOC alone, both in improved AUC (83% improvement) and odds ratio (increase from 4.65 to 16.22). Adding RGA and/or PTA to LOC was not improved over LOC alone. Rapid triage of TBI relies on strong initial predictors. Addition of an electrophysiological based marker was shown to outperform report of LOC alone or LOC plus amnesia, in determining risk of an intracranial bleed. In addition, ease of use at point-of-care, non-invasive, and rapid result using such technology suggests significant value added to standard clinical prediction. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

Prestimulus alpha-band power biases visual discrimination confidence, but not accuracy.

PubMed

Samaha, Jason; Iemi, Luca; Postle, Bradley R

2017-09-01

The magnitude of power in the alpha-band (8-13Hz) of the electroencephalogram (EEG) prior to the onset of a near threshold visual stimulus predicts performance. Together with other findings, this has been interpreted as evidence that alpha-band dynamics reflect cortical excitability. We reasoned, however, that non-specific changes in excitability would be expected to influence signal and noise in the same way, leaving actual discriminability unchanged. Indeed, using a two-choice orientation discrimination task, we found that discrimination accuracy was unaffected by fluctuations in prestimulus alpha power. Decision confidence, on the other hand, was strongly negatively correlated with prestimulus alpha power. This finding constitutes a clear dissociation between objective and subjective measures of visual perception as a function of prestimulus cortical excitability. This dissociation is predicted by a model where the balance of evidence supporting each choice drives objective performance but only the magnitude of evidence supporting the selected choice drives subjective reports, suggesting that human perceptual confidence can be suboptimal with respect to tracking objective accuracy. Copyright © 2017 Elsevier Inc. All rights reserved.

Ensemble Data Assimilation of Wind and Photovoltaic Power Information in the Convection-permitting High-Resolution Model COSMO-DE

NASA Astrophysics Data System (ADS)

Declair, Stefan; Saint-Drenan, Yves-Marie; Potthast, Roland

2016-04-01

Determining the amount of weather dependent renewable energy is a demanding task for transmission system operators (TSOs) and wind and photovoltaic (PV) prediction errors require the use of reserve power, which generate costs and can - in extreme cases - endanger the security of supply. In the project EWeLiNE funded by the German government, the German Weather Service and the Fraunhofer Institute on Wind Energy and Energy System Technology develop innovative weather- and power forecasting models and tools for grid integration of weather dependent renewable energy. The key part in energy prediction process chains is the numerical weather prediction (NWP) system. Wind speed and irradiation forecast from NWP system are however subject to several sources of error. The quality of the wind power prediction is mainly penalized by forecast error of the NWP model in the planetary boundary layer (PBL), which is characterized by high spatial and temporal fluctuations of the wind speed. For PV power prediction, weaknesses of the NWP model to correctly forecast i.e. low stratus, the absorption of condensed water or aerosol optical depth are the main sources of errors. Inaccurate radiation schemes (i.e. the two-stream parametrization) are also known as a deficit of NWP systems with regard to irradiation forecast. To mitigate errors like these, NWP model data can be corrected by post-processing techniques such as model output statistics and calibration using historical observational data. Additionally, latest observations can be used in a pre-processing technique called data assimilation (DA). In DA, not only the initial fields are provided, but the model is also synchronized with reality - the observations - and hence the model error is reduced in the forecast. Besides conventional observation networks like radiosondes, synoptic observations or air reports of wind, pressure and humidity, the number of observations measuring meteorological information indirectly such as satellite radiances, radar reflectivities or GPS slant delays strongly increases. The numerous wind farm and PV plants installed in Germany potentially represent a dense meteorological network assessing irradiation and wind speed through their power measurements. The accuracy of the NWP data may thus be enhanced by extending the observations in the assimilation by this new source of information. Wind power data can serve as indirect measurements of wind speed at hub height. The impact on the NWP model is potentially interesting since conventional observation network lacks measurements in this part of the PBL. Photovoltaic power plants can provide information on clouds, aerosol optical depth or low stratus in terms of remote sensing: the power output is strongly dependent on perturbations along the slant between sun position and PV panel. Additionally, since the latter kind of data is not limited to the vertical column above or below the detector. It may thus complement satellite data and compensate weaknesses in the radiation scheme. In this contribution, the DA method (Local Ensemble Transform Kalman Filter, LETKF) is shortly sketched. Furthermore, the computation of the model power equivalents is described and first assimilation results are presented and discussed.

Proactive monitoring of a wind turbine array with lidar measurements, SCADA data and a data-driven RANS solver

NASA Astrophysics Data System (ADS)

Iungo, G.; Said, E. A.; Santhanagopalan, V.; Zhan, L.

2016-12-01

Power production of a wind farm and durability of wind turbines are strongly dependent on non-linear wake interactions occurring within a turbine array. Wake dynamics are highly affected by the specific site conditions, such as topography and local atmospheric conditions. Furthermore, contingencies through the life of a wind farm, such as turbine ageing and off-design operations, make prediction of wake interactions and power performance a great challenge in wind energy. In this work, operations of an onshore wind turbine array were monitored through lidar measurements, SCADA and met-tower data. The atmospheric wind field investing the wind farm was estimated by using synergistically the available data through five different methods, which are characterized by different confidence levels. By combining SCADA data and the lidar measurements, it was possible to estimate power losses connected with wake interactions. For this specific array, power losses were estimated to be 4% and 2% of the total power production for stable and convective atmospheric regimes, respectively. The entire dataset was then leveraged for the calibration of a data-driven RANS (DDRANS) solver for prediction of wind turbine wakes and power production. The DDRANS is based on a parabolic formulation of the Navier-Stokes equations with axisymmetry and boundary layer approximations, which allow achieving very low computational costs. Accuracy in prediction of wind turbine wakes and power production is achieved through an optimal tuning of the turbulence closure model. The latter is based on a mixing length model, which was developed based on previous wind turbine wake studies carried out through large eddy simulations and wind tunnel experiments. Several operative conditions of the wind farm under examination were reproduced through DDRANS for different stability regimes, wind directions and wind velocity. The results show that DDRANS is capable of achieving a good level of accuracy in prediction of power production and wake velocity field associated with the turbine array.

Compensation of strong thermal lensing in high-optical-power cavities.

PubMed

Zhao, C; Degallaix, J; Ju, L; Fan, Y; Blair, D G; Slagmolen, B J J; Gray, M B; Lowry, C M Mow; McClelland, D E; Hosken, D J; Mudge, D; Brooks, A; Munch, J; Veitch, P J; Barton, M A; Billingsley, G

2006-06-16

In an experiment to simulate the conditions in high optical power advanced gravitational wave detectors, we show for the first time that the time evolution of strong thermal lenses follows the predicted infinite sum of exponentials (approximated by a double exponential), and that such lenses can be compensated using an intracavity compensation plate heated on its cylindrical surface. We show that high finesse approximately 1400 can be achieved in cavities with internal compensation plates, and that mode matching can be maintained. The experiment achieves a wave front distortion similar to that expected for the input test mass substrate in the Advanced Laser Interferometer Gravitational Wave Observatory, and shows that thermal compensation schemes are viable. It is also shown that the measurements allow a direct measurement of substrate optical absorption in the test mass and the compensation plate.

Stable clustering and the resolution of dissipationless cosmological N-body simulations

NASA Astrophysics Data System (ADS)

Benhaiem, David; Joyce, Michael; Sylos Labini, Francesco

2017-10-01

The determination of the resolution of cosmological N-body simulations, I.e. the range of scales in which quantities measured in them represent accurately the continuum limit, is an important open question. We address it here using scale-free models, for which self-similarity provides a powerful tool to control resolution. Such models also provide a robust testing ground for the so-called stable clustering approximation, which gives simple predictions for them. Studying large N-body simulations of such models with different force smoothing, we find that these two issues are in fact very closely related: our conclusion is that the accuracy of two-point statistics in the non-linear regime starts to degrade strongly around the scale at which their behaviour deviates from that predicted by the stable clustering hypothesis. Physically the association of the two scales is in fact simple to understand: stable clustering fails to be a good approximation when there are strong interactions of structures (in particular merging) and it is precisely such non-linear processes which are sensitive to fluctuations at the smaller scales affected by discretization. Resolution may be further degraded if the short distance gravitational smoothing scale is larger than the scale to which stable clustering can propagate. We examine in detail the very different conclusions of studies by Smith et al. and Widrow et al. and find that the strong deviations from stable clustering reported by these works are the results of over-optimistic assumptions about scales resolved accurately by the measured power spectra, and the reliance on Fourier space analysis. We emphasize the much poorer resolution obtained with the power spectrum compared to the two-point correlation function.

[The Significance of Work Motivation for Rehabilitation Success].

PubMed

Kessemeier, Franziska; Stöckler, Christiane; Petermann, Franz; Bassler, Markus; Pfeiffer, Wolfgang; Kobelt, Axel

2017-11-28

Aim of this study Apart from the reduction of symptoms and the restoration of working ability, return to work is a long-term goal of medical rehabilitation. The aim of this study is to analyze the influence of work motivation on the outcome of rehabilitation. Methods The data basis consists of N=998 patients at the psychosomatic department of the Oberharz Rehabilitation Center as well as data from insurance accounts. Using multiple linear regression analysis the predictive power of work motivation on rehabilitation outcome as well as different facets of work motivation in their function as predictors are analyzed. Results Only minor statistical relations could be found between work motivation and rehabilitation success when also taking employment status of the previous year and subjective vocational disability into account. A small predictive power can be attributed to work motivation as a factor in rehabilitation success in the sense of a reduction of symptoms. Particular facets of work motivation are suitable to predict rehabilitation success. Patients with a work motivation risk profile differ from patients with a normal work motivation profile as regards their capacity to work in the year following rehabilitation treatment. Conclusion Work motivation represents a relevant construct in rehabilitation success but is strongly influenced by individual factors. During rehabilitation, individual problems which influence work motivation should be taken into account more strongly. © Georg Thieme Verlag KG Stuttgart · New York.

The factor structure of complex posttraumatic stress disorder in traumatized refugees.

PubMed

Nickerson, Angela; Cloitre, Marylene; Bryant, Richard A; Schnyder, Ulrich; Morina, Naser; Schick, Matthis

2016-01-01

The construct of complex posttraumatic stress disorder (CPTSD) has attracted much research attention in previous years, however it has not been systematically evaluated in individuals exposed to persecution and displacement. Given that CPTSD has been proposed as a diagnostic category in the ICD-11, it is important that it be examined in refugee groups. In the current study, we proposed to test, for the first time, the factor structure of CPTSD proposed for the ICD-11 in a sample of resettled treatment-seeking refugees. The study sample consisted of 134 traumatized refugees from a variety of countries of origin, with approximately 93% of the sample having been exposed to torture. We used confirmatory factor analysis to examine the factor structure of CPTSD in this sample and examined the sensitivity, specificity, positive predictive power and negative predictive power of individual items in relation to the CPTSD diagnosis. Findings revealed that a two-factor higher-order model of CPTSD comprising PTSD and Difficulties in Self-Organization (χ 2 (47)=57.322, p =0.144, RMSEA=0.041, CFI=0.981, TLI=0.974) evidenced superior fit compared to a one-factor higher-order model of CPTSD (χ 2 (48)=65.745, p =0.045, RMSEA=0.053, CFI=0.968, TLI=0.956). Overall, items evidenced strong sensitivity and negative predictive power, moderate positive predictive power, and poor specificity. Findings provide preliminary evidence for the validity of the CPTSD construct with highly traumatized treatment-seeking refugees.

European shags optimize their flight behavior according to wind conditions.

PubMed

Kogure, Yukihisa; Sato, Katsufumi; Watanuki, Yutaka; Wanless, Sarah; Daunt, Francis

2016-02-01

Aerodynamics results in two characteristic speeds of flying birds: the minimum power speed and the maximum range speed. The minimum power speed requires the lowest rate of energy expenditure per unit time to stay airborne and the maximum range speed maximizes air distance traveled per unit of energy consumed. Therefore, if birds aim to minimize the cost of transport under a range of wind conditions, they are predicted to fly at the maximum range speed. Furthermore, take-off is predicted to be strongly affected by wind speed and direction. To investigate the effect of wind conditions on take-off and cruising flight behavior, we equipped 14 European shags Phalacrocorax aristotelis with a back-mounted GPS logger to measure position and hence ground speed, and a neck-mounted accelerometer to record wing beat frequency and strength. Local wind conditions were recorded during the deployment period. Shags always took off into the wind regardless of their intended destination and take-off duration was correlated negatively with wind speed. We combined ground speed and direction during the cruising phase with wind speed and direction to estimate air speed and direction. Whilst ground speed was highly variable, air speed was comparatively stable, although it increased significantly during strong head winds, because of stronger wing beats. The increased air speeds in head winds suggest that birds fly at the maximum range speed, not at the minimum power speed. Our study demonstrates that European shags actively adjust their flight behavior to utilize wind power to minimize the costs of take-off and cruising flight. © 2016. Published by The Company of Biologists Ltd.

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.

Energy in a Planetary Context

NASA Technical Reports Server (NTRS)

Hoehler, Tori M.

2017-01-01

The potential present day habitability of solar system bodies beyond Earth is limited to subsurface environments, where the availability of energy in biologically useful form is a paramount consideration. Energy availability is commonly quantified in terms of molar Gibbs energy changes for metabolisms of interest, but this can provide an incomplete and even misleading picture. A second aspect of life's requirement for energy - the rate of delivery, or power - strongly influences habitability, biomass abundance, growth rates, and, ultimately, rates of evolution. We are developing an approach to quantify metabolic power, using a cell-scale reactive transport model in which physical and chemical environmental parameters are varied. Simultaneously, we evaluate cell-specific energy flux requirements and their dependence on environmental "extremes". Comparison of metabolic power supply and demand provides a constraint on how biomass abundance varies across a range of environmental parameters, and thereby a prediction of the relative habitability of different environments. We are evaluating the predictive capability of this approach through comparison to observed distributions of microbial abundance in a range of subsurface (predominantly serpentinizing) systems.

The Power of the Pygmalion Effect: Teachers' Expectations Strongly Predict College Completion

ERIC Educational Resources Information Center

Boser, Ulrich; Wilhelm, Megan; Hanna, Robert

2014-01-01

People do better when more is expected of them. In education circles, this is called the Pygmalion Effect. It has been demonstrated in study after study, and the results can sometimes be quite significant. In one research project, for instance, teacher expectations of a pre-schooler's ability was a robust predictor of the child's high school GPA.…

New 21 cm Power Spectrum Upper Limits From PAPER II: Constraints on IGM Properties at z = 7.7

NASA Astrophysics Data System (ADS)

Pober, Jonathan; Ali, Zaki; Parsons, Aaron; Paper Team

2015-01-01

Using a simulation-based framework, we interpret the power spectrum measurements from PAPER of Ali et al. in the context of IGM physics at z = 7.7. A cold IGM will result in strong 21 cm absorption relative to the CMB and leads to a 21 cm fluctuation power spectrum that can exceed 3000 mK^2. The new PAPER measurements allow us to rule out extreme cold IGM models, placing a lower limit on the physical temperature of the IGM. We also compare this limit with a calculation for the predicted heating from the currently observed galaxy population at z = 8.

Stability analysis of electrical powered wheelchair-mounted robotic-assisted transfer device.

PubMed

Wang, Hongwu; Tsai, Chung-Ying; Jeannis, Hervens; Chung, Cheng-Shiu; Kelleher, Annmarie; Grindle, Garrett G; Cooper, Rory A

2014-01-01

The ability of people with disabilities to live in their homes and communities with maximal independence often hinges, at least in part, on their ability to transfer or be transferred by an assistant. Because of limited resources and the expense of personal care, robotic transfer assistance devices will likely be in great demand. An easy-to-use system for assisting with transfers, attachable to electrical powered wheelchairs (EPWs) and readily transportable, could have a significant positive effect on the quality of life of people with disabilities. We investigated the stability of our newly developed Strong Arm, which is attached and integrated with an EPW to assist with transfers. The stability of the system was analyzed and verified by experiments applying different loads and using different system configurations. The model predicted the distributions of the system's center of mass very well compared with the experimental results. When real transfers were conducted with 50 and 75 kg loads and an 83.25 kg dummy, the current Strong Arm could transfer all weights safely without tip-over. Our modeling accurately predicts the stability of the system and is suitable for developing better control algorithms to enhance the safety of the device.

Analysis of LH Launcher Arrays (Like the ITER One) Using the TOPLHA Code

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

Maggiora, R.; Milanesio, D.; Vecchi, G.

2009-11-26

TOPLHA (Torino Polytechnic Lower Hybrid Antenna) code is an innovative tool for the 3D/1D simulation of Lower Hybrid (LH) antennas, i.e. accounting for realistic 3D waveguides geometry and for accurate 1D plasma models, and without restrictions on waveguide shape, including curvature. This tool provides a detailed performances prediction of any LH launcher, by computing the antenna scattering parameters, the current distribution, electric field maps and power spectra for any user-specified waveguide excitation. In addition, a fully parallelized and multi-cavity version of TOPLHA permits the analysis of large and complex waveguide arrays in a reasonable simulation time. A detailed analysis ofmore » the performances of the proposed ITER LH antenna geometry has been carried out, underlining the strong dependence of the antenna input parameters with respect to plasma conditions. A preliminary optimization of the antenna dimensions has also been accomplished. Electric current distribution on conductors, electric field distribution at the interface with plasma, and power spectra have been calculated as well. The analysis shows the strong capabilities of the TOPLHA code as a predictive tool and its usefulness to LH launcher arrays detailed design.« less

Association between routine and standardized blood pressure measurements and left ventricular hypertrophy among patients on hemodialysis.

PubMed

Khangura, Jaspreet; Culleton, Bruce F; Manns, Braden J; Zhang, Jianguo; Barnieh, Lianne; Walsh, Michael; Klarenbach, Scott W; Tonelli, Marcello; Sarna, Magdalena; Hemmelgarn, Brenda R

2010-06-24

Left ventricular (LV) hypertrophy is common among patients on hemodialysis. While a relationship between blood pressure (BP) and LV hypertrophy has been established, it is unclear which BP measurement method is the strongest correlate of LV hypertrophy. We sought to determine agreement between various blood pressure measurement methods, as well as identify which method was the strongest correlate of LV hypertrophy among patients on hemodialysis. This was a post-hoc analysis of data from a randomized controlled trial. We evaluated the agreement between seven BP measurement methods: standardized measurement at baseline; single pre- and post-dialysis, as well as mean intra-dialytic measurement at baseline; and cumulative pre-, intra- and post-dialysis readings (an average of 12 monthly readings based on a single day per month). Agreement was assessed using Lin's concordance correlation coefficient (CCC) and the Bland Altman method. Association between BP measurement method and LV hypertrophy on baseline cardiac MRI was determined using receiver operating characteristic curves and area under the curve (AUC). Agreement between BP measurement methods in the 39 patients on hemodialysis varied considerably, from a CCC of 0.35 to 0.94, with overlapping 95% confidence intervals. Pre-dialysis measurements were the weakest predictors of LV hypertrophy while standardized, post- and inter-dialytic measurements had similar and strong (AUC 0.79 to 0.80) predictive power for LV hypertrophy. A single standardized BP has strong predictive power for LV hypertrophy and performs just as well as more resource intensive cumulative measurements, whereas pre-dialysis blood pressure measurements have the weakest predictive power for LV hypertrophy. Current guidelines, which recommend using pre-dialysis measurements, should be revisited to confirm these results.

Relapse Risk Assessment for Schizophrenia Patients (RASP): A New Self-Report Screening Tool.

PubMed

Velligan, Dawn; Carpenter, William; Waters, Heidi C; Gerlanc, Nicole M; Legacy, Susan N; Ruetsch, Charles

2018-01-01

The Relapse Assessment for Schizophrenia Patients (RASP) was developed as a six-question self-report screener that measures indicators of Increased Anxiety and Social Isolation to assess patient stability and predict imminent relapse. This paper describes the development and psychometric characteristics of the RASP. The RASP and Positive and Negative Syndrome Scale (PANSS) were administered to patients with schizophrenia (n=166) three separate times. Chart data were collected on a subsample of patients (n=81). Psychometric analyses of RASP included tests of reliability, construct validity, and concurrent validity of items. Factors from RASP were correlated with subscales from PANSS (sensitivity to change and criterion validity [agreement between RASP and evidence of relapse]). Test-retest reliability returned modest to strong agreement at the item level and strong agreement at the questionnaire level. RASP showed good item response curves and internal consistency for the total instrument and within each of the two subscales (Increased Anxiety and Social Isolation). RASP Total Score and subscales showed good concurrent validity when correlated with PANSS Total Score, Positive, Excitement, and Anxiety subscales. RASP correctly predicted relapse in 67% of cases, with good specificity and negative predictive power and acceptable positive predictive power and sensitivity. The reliability and validity data presented support the use of RASP in settings where addition of a brief self-report assessment of relapse risk among patients with schizophrenia may be of benefit. Ease of use and scoring, and the ability to administer without clinical supervision allows for routine administration and assessment of relapse risk.

Improved pump turbine transient behaviour prediction using a Thoma number-dependent hillchart model

NASA Astrophysics Data System (ADS)

Manderla, M.; Kiniger, K.; Koutnik, J.

2014-03-01

Water hammer phenomena are important issues for high head hydro power plants. Especially, if several reversible pump-turbines are connected to the same waterways there may be strong interactions between the hydraulic machines. The prediction and coverage of all relevant load cases is challenging and difficult using classical simulation models. On the basis of a recent pump-storage project, dynamic measurements motivate an improved modeling approach making use of the Thoma number dependency of the actual turbine behaviour. The proposed approach is validated for several transient scenarios and turns out to increase correlation between measurement and simulation results significantly. By applying a fully automated simulation procedure broad operating ranges can be covered which provides a consistent insight into critical load case scenarios. This finally allows the optimization of the closing strategy and hence the overall power plant performance.

Strong pinning regimes explored with large-scale Ginzburg-Landau simulations

NASA Astrophysics Data System (ADS)

Willa, Roland; Koshelev, Alexei E.

Improving the current-carrying capability of superconductors requires a deep understanding of vortex pinning. Within the theory of (3D) strong pinning an ideal vortex lattice is weakly deformed by a low density np of strong defects. In this limit the critical current jc is expected to grow linearly with np and to decrease with the field B according to B-α with α 0 . 5 . In the small-field limit the (1D) strong pinning theory of isolated vortices predicts jc np0 . 5 , independent of B. We explore strong pinning by low defect densities using time-dependent Ginzburg-Landau simulations. Our numerical results suggest the existence of a wide regime, where the lattice order is destroyed and yet interactions between vortices are important. In particular, for large defects we found an extended range of power-law decay of jc (B) with α 0 . 3 , smaller than predicted. This regime requires the development of new analytical models. Exploring the behavior of jc for various defect densities and sizes, we will establish pinning regimes and applicability limits of the conventional theory. This work is supported by the U.S. Department of Energy, Office of Science, Materials Sciences and Engineering Division. R. W. acknowledges support from the Swiss National Science Foundation through the SNSF Early Postdoc Mobility Fellowship.

Identification of Hemoglobin Levels Based on Anthropometric Indices in Elderly Koreans

PubMed Central

Kim, Jong Yeol

2016-01-01

Objectives Anemia is independently and strongly associated with an increased risk of mortality in older people and is also strongly associated with obesity. The objectives of the present study were to examine the associations between the hemoglobin level and various anthropometric indices, to predict low and normal hemoglobin levels using combined anthropometric indices, and to assess differences in the hemoglobin level and anthropometric indices between Korean men and women. Methods A total of 7,156 individuals ranging in age from 53–90 years participated in this retrospective cross-sectional study. Binary logistic regression (LR) and naïve Bayes (NB) models were used to identify significant differences in the anthropometric indices between subjects with low and normal hemoglobin levels and to assess the predictive power of these indices for the hemoglobin level. Results Among all of the variables, age displayed the strongest association with the hemoglobin level in both men (p < 0.0001, odds ratio [OR] = 0.487, area under the receiver operating characteristic curve based on the LR [LR-AUC] = 0.702, NB-AUC = 0.701) and women (p < 0.0001, OR = 0.636, LR-AUC = 0.625, NB-AUC = 0.624). Among the anthropometric indices, weight and body mass index (BMI) were the best predictors of the hemoglobin level. The predictive powers of all of the variables were higher in men than in women. The AUC values for the NB-Wrapper and LR-Wrapper predictive models generated using combined anthropometric indices were 0.734 and 0.723, respectively, for men and 0.649 and 0.652, respectively, for women. The use of combined anthropometric indices may improve the predictive power for the hemoglobin level. Discussion Among the various anthropometric indices, with the exception of age, we did not identify any indices that were better predictors than weight and BMI for low and normal hemoglobin levels. In addition, none of the ratios between pairs of indices were good indicators of the hemoglobin level. Finally, the Korean men tended to have higher associations between the anthropometric indices and anemia than the women. PMID:27812118

On Geomagnetism and Paleomagnetism

NASA Technical Reports Server (NTRS)

Voorhies, Coerte V.

1998-01-01

A statistical description of Earth's broad scale, core-source magnetic field has been developed and tested. The description features an expected, or mean, spatial magnetic power spectrum that is neither "flat" nor "while" at any depth, but is akin to spectra advanced by Stevenson and McLeod. This multipole spectrum describes the magnetic energy range; it is not steep enough for Gubbins' magnetic dissipation range. Natural variations of core multipole powers about their mean values are to be expected over geologic time and are described via trial probability distribution functions that neither require nor prohibit magnetic isotropy. The description is thus applicable to core-source dipole and low degree non-dipole fields despite axial dipole anisotropy. The description is combined with main field models of modem satellite and surface geomagnetic measurements to make testable predictions of: (1) the radius of Earth's core, (2) mean paleomagnetic field intensity, and (3) the mean rates and durations of both dipole power excursions and durable axial dipole reversals. The predicted core radius is 0.7% above the 3480 km seismologic value. The predicted root mean square paleointensity (35.6 mu T) and mean Virtual Axial Dipole Moment (about 6.2 lx 1022 Am(exp 2)) are within the range of various mean paleointensity estimates. The predicted mean rate of dipole power excursions, as defined by an absolute dipole moment <20% of the 1980 value, is 9.04/Myr and 14% less than obtained by analysis of a 4 Myr paleointensity record. The predicted mean rate of durable axial dipole reversals (2.26/Myr) is 2.3% more than established by the polarity time-scale for the past 84 Myr. The predicted mean duration of axial dipole reversals (5533 yr) is indistinguishable from an observational value. The accuracy of these predictions demonstrates the power and utility of the description, which is thought to merit further development and testing. It is suggested that strong stable stratification of Earth's uppermost outer core leads to a geologically long interval of no dipole reversals and a very nearly axisymmetric field outside the core. Statistical descriptions of other planetary magnetic fields are outlined.

α-Oscillations in the monkey sensorimotor network influence discrimination performance by rhythmical inhibition of neuronal spiking.

PubMed

Haegens, Saskia; Nácher, Verónica; Luna, Rogelio; Romo, Ranulfo; Jensen, Ole

2011-11-29

Extensive work in humans using magneto- and electroencephalography strongly suggests that decreased oscillatory α-activity (8-14 Hz) facilitates processing in a given region, whereas increased α-activity serves to actively suppress irrelevant or interfering processing. However, little work has been done to understand how α-activity is linked to neuronal firing. Here, we simultaneously recorded local field potentials and spikes from somatosensory, premotor, and motor regions while a trained monkey performed a vibrotactile discrimination task. In the local field potentials we observed strong activity in the α-band, which decreased in the sensorimotor regions during the discrimination task. This α-power decrease predicted better discrimination performance. Furthermore, the α-oscillations demonstrated a rhythmic relation with the spiking, such that firing was highest at the trough of the α-cycle. Firing rates increased with a decrease in α-power. These findings suggest that α-oscillations exercise a strong inhibitory influence on both spike timing and firing rate. Thus, the pulsed inhibition by α-oscillations plays an important functional role in the extended sensorimotor system.

Geometric morphometric evaluation of cervical vertebrae shape and its relationship to skeletal maturation.

PubMed

Chatzigianni, Athina; Halazonetis, Demetrios J

2009-10-01

Cervical vertebrae shape has been proposed as a diagnostic factor for assessing skeletal maturation in orthodontic patients. However, evaluation of vertebral shape is mainly based on qualitative criteria. Comprehensive quantitative measurements of shape and assessments of its predictive power have not been reported. Our aims were to measure vertebral shape by using the tools of geometric morphometrics and to evaluate the correlation and predictive power of vertebral shape on skeletal maturation. Pretreatment lateral cephalograms and corresponding hand-wrist radiographs of 98 patients (40 boys, 58 girls; ages, 8.1-17.7 years) were used. Skeletal age was estimated from the hand-wrist radiographs. The first 4 vertebrae were traced, and 187 landmarks (34 fixed and 153 sliding semilandmarks) were used. Sliding semilandmarks were adjusted to minimize bending energy against the average of the sample. Principal components analysis in shape and form spaces was used for evaluating shape patterns. Shape measures, alone and combined with centroid size and age, were assessed as predictors of skeletal maturation. Shape alone could not predict skeletal maturation better than chronologic age. The best prediction was achieved with the combination of form space principal components and age, giving 90% prediction intervals of approximately 200 maturation units in the girls and 300 units in the boys. Similar predictive power could be obtained by using centroid size and age. Vertebrae C2, C3, and C4 gave similar results when examined individually or combined. C1 showed lower correlations, signifying lower integration with hand-wrist maturation. Vertebral shape is strongly correlated to skeletal age but does not offer better predictive value than chronologic age.

Transient Plasma Photonic Crystals for High-Power Lasers.

PubMed

Lehmann, G; Spatschek, K H

2016-06-03

A new type of transient photonic crystals for high-power lasers is presented. The crystal is produced by counterpropagating laser beams in plasma. Trapped electrons and electrically forced ions generate a strong density grating. The lifetime of the transient photonic crystal is determined by the ballistic motion of ions. The robustness of the photonic crystal allows one to manipulate high-intensity laser pulses. The scheme of the crystal is analyzed here by 1D Vlasov simulations. Reflection or transmission of high-power laser pulses are predicted by particle-in-cell simulations. It is shown that a transient plasma photonic crystal may act as a tunable mirror for intense laser pulses. Generalizations to 2D and 3D configurations are possible.

Efficiency at maximum power of a laser quantum heat engine enhanced by noise-induced coherence

NASA Astrophysics Data System (ADS)

Dorfman, Konstantin E.; Xu, Dazhi; Cao, Jianshu

2018-04-01

Quantum coherence has been demonstrated in various systems including organic solar cells and solid state devices. In this article, we report the lower and upper bounds for the performance of quantum heat engines determined by the efficiency at maximum power. Our prediction based on the canonical three-level Scovil and Schulz-Dubois maser model strongly depends on the ratio of system-bath couplings for the hot and cold baths and recovers the theoretical bounds established previously for the Carnot engine. Further, introducing a fourth level to the maser model can enhance the maximal power and its efficiency, thus demonstrating the importance of quantum coherence in the thermodynamics and operation of the heat engines beyond the classical limit.

The relation between statistical power and inference in fMRI

PubMed Central

Wager, Tor D.; Yarkoni, Tal

2017-01-01

Statistically underpowered studies can result in experimental failure even when all other experimental considerations have been addressed impeccably. In fMRI the combination of a large number of dependent variables, a relatively small number of observations (subjects), and a need to correct for multiple comparisons can decrease statistical power dramatically. This problem has been clearly addressed yet remains controversial—especially in regards to the expected effect sizes in fMRI, and especially for between-subjects effects such as group comparisons and brain-behavior correlations. We aimed to clarify the power problem by considering and contrasting two simulated scenarios of such possible brain-behavior correlations: weak diffuse effects and strong localized effects. Sampling from these scenarios shows that, particularly in the weak diffuse scenario, common sample sizes (n = 20–30) display extremely low statistical power, poorly represent the actual effects in the full sample, and show large variation on subsequent replications. Empirical data from the Human Connectome Project resembles the weak diffuse scenario much more than the localized strong scenario, which underscores the extent of the power problem for many studies. Possible solutions to the power problem include increasing the sample size, using less stringent thresholds, or focusing on a region-of-interest. However, these approaches are not always feasible and some have major drawbacks. The most prominent solutions that may help address the power problem include model-based (multivariate) prediction methods and meta-analyses with related synthesis-oriented approaches. PMID:29155843

Identification of the Best Anthropometric Predictors of Serum High- and Low-Density Lipoproteins Using Machine Learning.

PubMed

Lee, Bum Ju; Kim, Jong Yeol

2015-09-01

Serum high-density lipoprotein (HDL) and low-density lipoprotein (LDL) cholesterol levels are associated with risk factors for various diseases and are related to anthropometric measures. However, controversy remains regarding the best anthropometric indicators of the HDL and LDL cholesterol levels. The objectives of this study were to identify the best predictors of HDL and LDL cholesterol using statistical analyses and two machine learning algorithms and to compare the predictive power of combined anthropometric measures in Korean adults. A total of 13,014 subjects participated in this study. The anthropometric measures were assessed with binary logistic regression (LR) to evaluate statistically significant differences between the subjects with normal and high LDL cholesterol levels and between the subjects with normal and low HDL cholesterol levels. LR and the naive Bayes algorithm (NB), which provides more reasonable and reliable results, were used in the analyses of the predictive power of individual and combined measures. The best predictor of HDL was the rib to hip ratio (p =< 0.0001; odds ratio (OR) = 1.895; area under curve (AUC) = 0.681) in women and the waist to hip ratio (WHR) (p =< 0.0001; OR = 1.624; AUC = 0.633) in men. In women, the strongest indicator of LDL was age (p =< 0.0001; OR = 1.662; AUC by NB = 0.653 ; AUC by LR = 0.636). Among the anthropometric measures, the body mass index (BMI), WHR, forehead to waist ratio, forehead to rib ratio, and forehead to chest ratio were the strongest predictors of LDL; these measures had similar predictive powers. The strongest predictor in men was BMI (p =< 0.0001; OR = 1.369; AUC by NB = 0.594; AUC by LR = 0.595 ). The predictive power of almost all individual anthropometric measures was higher for HDL than for LDL, and the predictive power for both HDL and LDL in women was higher than for men. A combination of anthropometric measures slightly improved the predictive power for both HDL and LDL cholesterol. The best indicator for HDL and LDL might differ according to the type of cholesterol and the gender. In women, but not men, age was the variable that strongly predicted HDL and LDL cholesterol levels. Our findings provide new information for the development of better initial screening tools for HDL and LDL cholesterol.

A High Resolution Tropical Cyclone Power Outage Forecasting Model for the Continental United States

NASA Astrophysics Data System (ADS)

Pino, J. V.; Quiring, S. M.; Guikema, S.; Shashaani, S.; Linger, S.; Backhaus, S.

2017-12-01

Tropical cyclones cause extensive damage to the power infrastructure system throughout the United States. This damage can leave millions without power for extended periods of time, as most recently seen with Hurricane Matthew (2016). Accurate and timely prediction of power outages are essential for utility companies, emergency management agencies, and governmental organizations. Here we present a high-resolution (250 m x 250 m) hurricane power outage model for the United States. The model uses only publicly-available data to make predictions. It uses forecasts of storm variables such as maximum 3-second wind gust, duration of strong winds > 20 m s-2, soil moisture, and precipitation. It also incorporates static environmental variables such as elevation characteristics, land cover type, population density, tree species data, and root zone depth. A web tool was established for use by the Department of Energy (DOE) so that the model can be used for real-time outage forecasting or for synthetic tropical cyclones as an exercise in emergency management. This web tool provides DOE decision-makers with high impact analytic results and products that can be disseminated to federal, local, and state agencies. The results then aid utility companies in their pre- and post-storm activities, thus decreasing restoration times and lowering costs.

A new phenomenological /τ-/α interaction

NASA Astrophysics Data System (ADS)

Heiberg-Andersen, H.; Mackintosh, R. S.; Vaagen, J. S.

2003-01-01

We present a potential model, with distinctive features, reproducing angular distributions and analyzing power data for τ- α scattering from 20 to 30 MeV τ energy with regular variation of the parameters. The distinctive features are: (1) a spin-orbit term which incorporates the influence of central depression in the α nucleus, and, (2) central terms which are strongly parity dependent. The parity dependence of the real central term is such that the odd-parity component has both a greater rms radius and greater volume integral than the even-parity component. These parity dependence characteristics had been predicted by the inversion of the RGM S-matrix. Our result supports a considerable contribution from three-nucleon exchange processes. The predicted 1/2 - level of 7Be is shifted 3 MeV relative to a previous one-level R-matrix formula fit, and depends strongly on the geometry of the spin-orbit potential.

Multi-scale gyrokinetic simulation of Alcator C-Mod tokamak discharges

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

Howard, N. T., E-mail: nthoward@psfc.mit.edu; White, A. E.; Greenwald, M.

2014-03-15

Alcator C-Mod tokamak discharges have been studied with nonlinear gyrokinetic simulation simultaneously spanning both ion and electron spatiotemporal scales. These multi-scale simulations utilized the gyrokinetic model implemented by GYRO code [J. Candy and R. E. Waltz, J. Comput. Phys. 186, 545 (2003)] and the approximation of reduced electron mass (μ = (m{sub D}/m{sub e}){sup .5} = 20.0) to qualitatively study a pair of Alcator C-Mod discharges: a low-power discharge, previously demonstrated (using realistic mass, ion-scale simulation) to display an under-prediction of the electron heat flux and a high-power discharge displaying agreement with both ion and electron heat flux channels [N. T. Howard et al.,more » Nucl. Fusion 53, 123011 (2013)]. These multi-scale simulations demonstrate the importance of electron-scale turbulence in the core of conventional tokamak discharges and suggest it is a viable candidate for explaining the observed under-prediction of electron heat flux. In this paper, we investigate the coupling of turbulence at the ion (k{sub θ}ρ{sub s}∼O(1.0)) and electron (k{sub θ}ρ{sub e}∼O(1.0)) scales for experimental plasma conditions both exhibiting strong (high-power) and marginally stable (low-power) low-k (k{sub θ}ρ{sub s} < 1.0) turbulence. It is found that reduced mass simulation of the plasma exhibiting marginally stable low-k turbulence fails to provide even qualitative insight into the turbulence present in the realistic plasma conditions. In contrast, multi-scale simulation of the plasma condition exhibiting strong turbulence provides valuable insight into the coupling of the ion and electron scales.« less

SINGLE NEURON ACTIVITY AND THETA MODULATION IN POSTRHINAL CORTEX DURING VISUAL OBJECT DISCRIMINATION

PubMed Central

Furtak, Sharon C.; Ahmed, Omar J.; Burwell, Rebecca D.

2012-01-01

Postrhinal cortex, the rodent homolog of the primate parahippocampal cortex, processes spatial and contextual information. Our hypothesis of postrhinal function is that it serves to encode context, in part, by forming representations that link objects to places. We recorded postrhinal neuronal activity and local field potentials (LFPs) in rats trained on a two-choice, visual discrimination task. As predicted, a large proportion of postrhinal neurons signaled object-location conjunctions. In addition, postrhinal LFPs exhibited strong oscillatory rhythms in the theta band, and many postrhinal neurons were phase locked to theta. Although correlated with running speed, theta power was lower than predicted by speed alone immediately before and after choice. However, theta power was significantly increased following incorrect decisions, suggesting a role in signaling error. These findings provide evidence that postrhinal cortex encodes representations that link objects to places and suggest that postrhinal theta modulation extends to cognitive as well as spatial functions. PMID:23217745

Oblique H.F. radiowave propagation in the main trough region of the ionosphere

NASA Astrophysics Data System (ADS)

Lockwood, M.; Mitchell, V. B.

1980-12-01

The propagation of 7.335 MHz, CW signals over a 5212 km subauroral, west-east path is studied. Measurements and semiempirical predictions are made of the amplitude distributions and Doppler shifts of the received signals. The observed amplitude distribution is fitted with a numerical fading model, yielding the power losses suffered by the signals during propagation via the predominating modes. The mid-latitude trough in the F2 peak ionization density is predicted by a statistical model to be at the latitudes of this path at these times and at low K sub p values; a sharp cut-off in low-power losses at a mean K sub p of 2.75 strongly implicates the trough in the propagation of these signals. It is shown that a simple extension of this model to allow for the trough can reproduce the form of the observed diurnal variation.

Forecasting Financial Extremes: A Network Degree Measure of Super-Exponential Growth.

PubMed

Yan, Wanfeng; van Tuyll van Serooskerken, Edgar

2015-01-01

Investors in stock market are usually greedy during bull markets and scared during bear markets. The greed or fear spreads across investors quickly. This is known as the herding effect, and often leads to a fast movement of stock prices. During such market regimes, stock prices change at a super-exponential rate and are normally followed by a trend reversal that corrects the previous overreaction. In this paper, we construct an indicator to measure the magnitude of the super-exponential growth of stock prices, by measuring the degree of the price network, generated from the price time series. Twelve major international stock indices have been investigated. Error diagram tests show that this new indicator has strong predictive power for financial extremes, both peaks and troughs. By varying the parameters used to construct the error diagram, we show the predictive power is very robust. The new indicator has a better performance than the LPPL pattern recognition indicator.

Spin Dependence of η Meson Production in Proton-Proton Collisions Close to Threshold.

PubMed

Adlarson, P; Augustyniak, W; Bardan, W; Bashkanov, M; Bass, S D; Bergmann, F S; Berłowski, M; Bondar, A; Büscher, M; Calén, H; Ciepał, I; Clement, H; Czerwiński, E; Demmich, K; Engels, R; Erven, A; Erven, W; Eyrich, W; Fedorets, P; Föhl, K; Fransson, K; Goldenbaum, F; Goswami, A; Grigoryev, K; Gullström, C-O; Heijkenskjöld, L; Hejny, V; Hüsken, N; Jarczyk, L; Johansson, T; Kamys, B; Kemmerling, G; Khatri, G; Khoukaz, A; Khreptak, O; Kirillov, D A; Kistryn, S; Kleines, H; Kłos, B; Krzemień, W; Kulessa, P; Kupść, A; Kuzmin, A; Lalwani, K; Lersch, D; Lorentz, B; Magiera, A; Maier, R; Marciniewski, P; Mariański, B; Morsch, H-P; Moskal, P; Ohm, H; Parol, W; Perez Del Rio, E; Piskunov, N M; Prasuhn, D; Pszczel, D; Pysz, K; Pyszniak, A; Ritman, J; Roy, A; Rudy, Z; Rundel, O; Sawant, S; Schadmand, S; Schätti-Ozerianska, I; Sefzick, T; Serdyuk, V; Shwartz, B; Sitterberg, K; Skorodko, T; Skurzok, M; Smyrski, J; Sopov, V; Stassen, R; Stepaniak, J; Stephan, E; Sterzenbach, G; Stockhorst, H; Ströher, H; Szczurek, A; Trzciński, A; Wolke, M; Wrońska, A; Wüstner, P; Yamamoto, A; Zabierowski, J; Zieliński, M J; Złomańczuk, J; Żuprański, P; Żurek, M

2018-01-12

Taking advantage of the high acceptance and axial symmetry of the WASA-at-COSY detector, and the high polarization degree of the proton beam of COSY, the reaction p[over →]p→ppη has been measured close to threshold to explore the analyzing power A_{y}. The angular distribution of A_{y} is determined with the precision improved by more than 1 order of magnitude with respect to previous results, allowing a first accurate comparison with theoretical predictions. The determined analyzing power is consistent with zero for an excess energy of Q=15  MeV, signaling s-wave production with no evidence for higher partial waves. At Q=72  MeV the data reveal strong interference of Ps and Pp partial waves and cancellation of (Pp)^{2} and Ss^{*}Sd contributions. These results rule out the presently available theoretical predictions for the production mechanism of the η meson.

Hydrodynamic effects of kinetic power extraction by in-stream tidal turbines

NASA Astrophysics Data System (ADS)

Polagye, Brian L.

The hydrodynamic effects of extracting kinetic power from tidal streams presents unique challenges to the development of in-stream tidal power. In-stream tidal turbines superficially resemble wind turbines and extract kinetic power from the ebb and flood of strong tidal currents. Extraction increases the resistance to flow, leading to changes in tidal range, transport, mixing, and the kinetic resource itself. These far-field changes have environmental, social, and economic implications that must be understood to develop the in-stream resource. This dissertation describes the development of a one-dimensional numerical channel model and its application to the study of these effects. The model is applied to determine the roles played by site geometry, network topology, tidal regime, and device dynamics. A comparison is also made between theoretical and modeled predictions for the maximum amount of power which could be extracted from a tidal energy site. The model is extended to a simulation of kinetic power extraction from Puget Sound, Washington. In general, extracting tidal energy will have a number of far-field effects, in proportion to the level of power extraction. At the theoretical limit, these effects can be very significant (e.g., 50% reduction in transport), but are predicted to be immeasurably small for pilot-scale projects. Depending on the specifics of the site, far-field effects may either augment or reduce the existing tidal regime. Changes to the tide, in particular, have significant spatial variability. Since tidal streams are generally subcritical, effects are felt throughout the estuary, not just at the site of extraction. The one dimensional numerical modeling is supported by a robust theory for predicting the performance characteristics of in-stream devices. The far-field effects of tidal power depend on the total power dissipated by turbines, rather than the power extracted. When the low-speed wake downstream of a turbine mixes with the free-stream, power is lost, such that the total power dissipated by the turbine is significantly greater than the power extracted. This dissertation concludes with a framework for three-dimensional numerical modeling of near-field extraction effects.

ULF Wave Activity in the Magnetosphere: Resolving Solar Wind Interdependencies to Identify Driving Mechanisms

NASA Astrophysics Data System (ADS)

Bentley, S. N.; Watt, C. E. J.; Owens, M. J.; Rae, I. J.

2018-04-01

Ultralow frequency (ULF) waves in the magnetosphere are involved in the energization and transport of radiation belt particles and are strongly driven by the external solar wind. However, the interdependency of solar wind parameters and the variety of solar wind-magnetosphere coupling processes make it difficult to distinguish the effect of individual processes and to predict magnetospheric wave power using solar wind properties. We examine 15 years of dayside ground-based measurements at a single representative frequency (2.5 mHz) and a single magnetic latitude (corresponding to L ˜ 6.6RE). We determine the relative contribution to ULF wave power from instantaneous nonderived solar wind parameters, accounting for their interdependencies. The most influential parameters for ground-based ULF wave power are solar wind speed vsw, southward interplanetary magnetic field component Bz<0, and summed power in number density perturbations δNp. Together, the subordinate parameters Bz and δNp still account for significant amounts of power. We suggest that these three parameters correspond to driving by the Kelvin-Helmholtz instability, formation, and/or propagation of flux transfer events and density perturbations from solar wind structures sweeping past the Earth. We anticipate that this new parameter reduction will aid comparisons of ULF generation mechanisms between magnetospheric sectors and will enable more sophisticated empirical models predicting magnetospheric ULF power using external solar wind driving parameters.

Rainfall prediction using fuzzy inference system for preliminary micro-hydro power plant planning

NASA Astrophysics Data System (ADS)

Suprapty, B.; Malani, R.; Minardi, J.

2018-04-01

East Kalimantan is a very rich area with water sources, in the form of river streams that branch to the remote areas. The conditions of natural potency like this become alternative solution for area that has not been reached by the availability of electric energy from State Electricity Company. The river water in selected location (catchment area) which is channelled to the canal, pipeline or penstock can be used to drive the waterwheel or turbine. The amount of power obtained depends on the volume/water discharge and headwater (the effective height between the reservoir and the turbine). The water discharge is strongly influenced by the amount of rainfall. Rainfall is the amount of water falling on the flat surface for a certain period measured, in units of mm3, above the horizontal surface in the absence of evaporation, run-off and infiltration. In this study, the prediction of rainfall is done in the area of East Kalimantan which has 13 watersheds which, in principle, have the potential for the construction of Micro Hydro Power Plant. Rainfall time series data is modelled by using AR (Auto Regressive) Model based on FIS (Fuzzy Inference System). The FIS structure of the training results is then used to predict the next two years rainfall.

Simulation of medical Q-switch flash-pumped Er:YAG laser

NASA Astrophysics Data System (ADS)

-Yan-lin, Wang; Huang-Chuyun; Yao-Yucheng; Xiaolin, Zou

2011-01-01

Er: YAG laser, the wavelength is 2940nm, can be absorbed strongly by water. The absorption coefficient is as high as 13000 cm-1. As the water strong absorption, Erbium laser can bring shallow penetration depth and smaller surrounding tissue injury in most soft tissue and hard tissue. At the same time, the interaction between 2940nm radiation and biological tissue saturated with water is equivalent to instantaneous heating within limited volume, thus resulting in the phenomenon of micro-explosion to removal organization. Different parameters can be set up to cut enamel, dentin, caries and soft tissue. For the development and optimization of laser system, it is a practical choice to use laser modeling to predict the influence of various parameters for laser performance. Aim at the status of low Erbium laser output power, flash-pumped Er: YAG laser performance was simulated to obtain optical output in theory. the rate equation model was obtained and used to predict the change of population densities in various manifolds and use the technology of Q-switch the simulate laser output for different design parameters and results showed that Er: YAG laser output energy can achieve the maximum average output power of 9.8W under the given parameters. The model can be used to find the potential laser systems that meet application requirements.

Remnants of semiclassical bistability in the few-photon regime of cavity QED.

PubMed

Kerckhoff, Joseph; Armen, Michael A; Mabuchi, Hideo

2011-11-21

Broadband homodyne detection of the light transmitted by a Fabry-Perot cavity containing a strongly-coupled (133)Cs atom is used to probe the dynamic optical response in a regime where semiclassical theory predicts bistability but strong quantum corrections should apply. While quantum fluctuations destabilize true equilibrium bistability, our observations confirm the existence of metastable states with finite lifetimes and a hysteretic response is apparent when the optical drive is modulated on comparable timescales. Our experiment elucidates remnant semiclassical behavior in the attojoule (~10 photon) regime of single-atom cavity QED, of potential significance for ultra-low power photonic signal processing. © 2011 Optical Society of America

The potential distribution of Phlebotomus papatasi (Diptera: Psychodidae) in Libya based on ecological niche model.

PubMed

Abdel-Dayem, M S; Annajar, B B; Hanafi, H A; Obenauer, P J

2012-05-01

The increased cases of cutaneous leishmaniasis vectored by Phlebotomus papatasi (Scopoli) in Libya have driven considerable effort to develop a predictive model for the potential geographical distribution of this disease. We collected adult P. papatasi from 17 sites in Musrata and Yefern regions of Libya using four different attraction traps. Our trap results and literature records describing the distribution of P. papatasi were incorporated into a MaxEnt algorithm prediction model that used 22 environmental variables. The model showed a high performance (AUC = 0.992 and 0.990 for training and test data, respectively). High suitability for P. papatasi was predicted to be largely confined to the coast at altitudes <600 m. Regions south of 300 degrees N latitude were calculated as unsuitable for this species. Jackknife analysis identified precipitation as having the most significant predictive power, while temperature and elevation variables were less influential. The National Leishmaniasis Control Program in Libya may find this information useful in their efforts to control zoonotic cutaneous leishmaniasis. Existing records are strongly biased toward a few geographical regions, and therefore, further sand fly collections are warranted that should include documentation of such factors as soil texture and humidity, land cover, and normalized difference vegetation index (NDVI) data to increase the model's predictive power.

A model relating radiated power and impurity concentrations during Ne, N and Ar injection in Tore Supra

NASA Astrophysics Data System (ADS)

Hogan, J.; Demichelis, C.; Monier-Garbet, P.; Guirlet, R.; Hess, W.; Schunke, B.

2000-10-01

A model combining the MIST (core symmetric) and BBQ (SOL asymmetric) codes is used to study the relation between impurity density and radiated power for representative cases from Tore Supra experiments on strong radiation regimes using the ergodic divertor. Transport predictions of external radiation are compared with observation to estimate the absolute impurity density. BBQ provides the incoming distribution of recycling impurity charge states for the radial transport calculation. The shots studied use the ergodic divertor and high ICRH power. Power is first applied and then the extrinsic impurity (Ne, N or Ar) is injected. Separate time dependent intrinsic (C and O) impurity transport calculations match radiation levels before and during the high power and impurity injection phases. Empirical diffusivities are sought to reproduce the UV (CV R, I lines), CVI Lya, OVIII Lya, Zeff, and horizontal bolometer data. The model has been used to calculate the relative radiative efficiency (radiated power / extrinsically contributed electron) for the sample database.

Stick or Switch: A Selection Heuristic Predicts when People Take the Perspective of Others or Communicate Egocentrically.

PubMed

Rogers, Shane L; Fay, Nicolas

2016-01-01

This paper examines a cognitive mechanism that drives perspective-taking and egocentrism in interpersonal communication. Using a conceptual referential communication task, in which participants describe a range of abstract geometric shapes, Experiment 1 shows that perspective-taking and egocentric communication are frequent communication strategies. Experiment 2 tests a selection heuristic account of perspective-taking and egocentric communication. It uses participants' shape description ratings to predict their communication strategy. Participants' communication strategy was predicted by how informative they perceived the different shape descriptions to be. When participants' personal shape description was perceived to be more informative than their addressee's shape description, there was a strong bias to communicate egocentrically. By contrast, when their addressee's shape description was perceived to be more informative, there was a strong bias to take their addressee's perspective. When the shape descriptions were perceived to be equally informative, there was a moderate bias to communicate egocentrically. This simple, but powerful, selection heuristic may be critical to the cumulative cultural evolution of human communication systems, and cumulative cultural evolution more generally.

The implications of Big Five standing for the distribution of trait manifestation in behavior: fifteen experience-sampling studies and a meta-analysis.

PubMed

Fleeson, William; Gallagher, Patrick

2009-12-01

One of the fundamental questions in personality psychology is whether and how strongly trait standing relates to the traits that people actually manifest in their behavior when faced with real pressures and real consequences of their actions. One reason this question is fundamental is the common belief that traits do not predict how individuals behave, which leads to the reasonable conclusion that traits are not important to study. However, this conclusion is surprising given that there is almost no data on the ability of traits to predict distributions of naturally occurring, representative behaviors of individuals (and that there are many studies showing that traits do indeed predict specific behaviors). The authors describe a meta-analysis of 15 experience-sampling studies, conducted over the course of 8 years, amassing over 20,000 reports of trait manifestation in behavior. Participants reported traits on typical self-report questionnaires, then described their current behavior multiple times per day for several days as the behavior was occurring. Results show that traits, contrary to expectations, were strongly predictive of individual differences in trait manifestation in behavior, predicting average levels with correlations between .42 and .56 (approaching .60 for stringently restricted studies). Several other ways of summarizing trait manifestation in behavior were also predicted from traits. These studies provide evidence that traits are powerful predictors of actual manifestation of traits in behavior.

A summary of wind power prediction methods

NASA Astrophysics Data System (ADS)

Wang, Yuqi

2018-06-01

The deterministic prediction of wind power, the probability prediction and the prediction of wind power ramp events are introduced in this paper. Deterministic prediction includes the prediction of statistical learning based on histor ical data and the prediction of physical models based on NWP data. Due to the great impact of wind power ramp events on the power system, this paper also introduces the prediction of wind power ramp events. At last, the evaluation indicators of all kinds of prediction are given. The prediction of wind power can be a good solution to the adverse effects of wind power on the power system due to the abrupt, intermittent and undulation of wind power.

Predictive markers of honey bee colony collapse.

PubMed

Dainat, Benjamin; Evans, Jay D; Chen, Yan Ping; Gauthier, Laurent; Neumann, Peter

2012-01-01

Across the Northern hemisphere, managed honey bee colonies, Apis mellifera, are currently affected by abrupt depopulation during winter and many factors are suspected to be involved, either alone or in combination. Parasites and pathogens are considered as principal actors, in particular the ectoparasitic mite Varroa destructor, associated viruses and the microsporidian Nosema ceranae. Here we used long term monitoring of colonies and screening for eleven disease agents and genes involved in bee immunity and physiology to identify predictive markers of honeybee colony losses during winter. The data show that DWV, Nosema ceranae, Varroa destructor and Vitellogenin can be predictive markers for winter colony losses, but their predictive power strongly depends on the season. In particular, the data support that V. destructor is a key player for losses, arguably in line with its specific impact on the health of individual bees and colonies.

Predictive Markers of Honey Bee Colony Collapse

PubMed Central

Dainat, Benjamin; Evans, Jay D.; Chen, Yan Ping; Gauthier, Laurent; Neumann, Peter

2012-01-01

Across the Northern hemisphere, managed honey bee colonies, Apis mellifera, are currently affected by abrupt depopulation during winter and many factors are suspected to be involved, either alone or in combination. Parasites and pathogens are considered as principal actors, in particular the ectoparasitic mite Varroa destructor, associated viruses and the microsporidian Nosema ceranae. Here we used long term monitoring of colonies and screening for eleven disease agents and genes involved in bee immunity and physiology to identify predictive markers of honeybee colony losses during winter. The data show that DWV, Nosema ceranae, Varroa destructor and Vitellogenin can be predictive markers for winter colony losses, but their predictive power strongly depends on the season. In particular, the data support that V. destructor is a key player for losses, arguably in line with its specific impact on the health of individual bees and colonies. PMID:22384162

Ion cyclotron resonance heating for tungsten control in various JET H-mode scenarios

NASA Astrophysics Data System (ADS)

Goniche, M.; Dumont, R. J.; Bobkov, V.; Buratti, P.; Brezinsek, S.; Challis, C.; Colas, L.; Czarnecka, A.; Drewelow, P.; Fedorczak, N.; Garcia, J.; Giroud, C.; Graham, M.; Graves, J. P.; Hobirk, J.; Jacquet, P.; Lerche, E.; Mantica, P.; Monakhov, I.; Monier-Garbet, P.; Nave, M. F. F.; Noble, C.; Nunes, I.; Pütterich, T.; Rimini, F.; Sertoli, M.; Valisa, M.; Van Eester, D.; Contributors, JET

2017-05-01

Ion cyclotron resonance heating (ICRH) in the hydrogen minority scheme provides central ion heating and acts favorably on the core tungsten transport. Full wave modeling shows that, at medium power level (4 MW), after collisional redistribution, the ratio of power transferred to the ions and the electrons vary little with the minority (hydrogen) concentration n H/n e but the high-Z impurity screening provided by the fast ions temperature increases with the concentration. The power radiated by tungsten in the core of the JET discharges has been analyzed on a large database covering the 2013-2014 campaign. In the baseline scenario with moderate plasma current (I p = 2.5 MA) ICRH modifies efficiently tungsten transport to avoid its accumulation in the plasma centre and, when the ICRH power is increased, the tungsten radiation peaking evolves as predicted by the neo-classical theory. At higher current (3-4 MA), tungsten accumulation can be only avoided with 5 MW of ICRH power with high gas injection rate. For discharges in the hybrid scenario, the strong initial peaking of the density leads to strong tungsten accumulation. When this initial density peaking is slightly reduced, with an ICRH power in excess of 4 MW,very low tungsten concentration in the core (˜10-5) is maintained for 3 s. MHD activity plays a key role in tungsten transport and modulation of the tungsten radiation during a sawtooth cycle is correlated to the fishbone activity triggered by the fast ion pressure gradient.

A fully dynamic model of a multi-layer piezoelectric actuator incorporating the power amplifier

NASA Astrophysics Data System (ADS)

Zhu, Wei; Yang, Fufeng; Rui, Xiaoting

2017-12-01

The dynamic input-output characteristics of the multi-layer piezoelectric actuator (PA) are intrinsically rate-dependent and hysteresis. Meanwhile, aiming at the strong capacitive impedance of multi-layer PA, the power amplifier of the actuator can greatly affect the dynamic performances of the actuator. In this paper, a novel dynamic model that includes a model of the electric circuit providing voltage to the actuator, an inverse piezoelectric effect model describing the hysteresis and creep behavior of the actuator, and a mechanical model, in which the vibration characteristics of the multi-layer PA is described, is put forward. Validation experimental tests are conducted. Experimental results show that the proposed dynamic model can accurately predict the fully dynamic behavior of the multi-layer PA with different driving power.

Current drive at plasma densities required for thermonuclear reactors.

PubMed

Cesario, R; Amicucci, L; Cardinali, A; Castaldo, C; Marinucci, M; Panaccione, L; Santini, F; Tudisco, O; Apicella, M L; Calabrò, G; Cianfarani, C; Frigione, D; Galli, A; Mazzitelli, G; Mazzotta, C; Pericoli, V; Schettini, G; Tuccillo, A A

2010-08-10

Progress in thermonuclear fusion energy research based on deuterium plasmas magnetically confined in toroidal tokamak devices requires the development of efficient current drive methods. Previous experiments have shown that plasma current can be driven effectively by externally launched radio frequency power coupled to lower hybrid plasma waves. However, at the high plasma densities required for fusion power plants, the coupled radio frequency power does not penetrate into the plasma core, possibly because of strong wave interactions with the plasma edge. Here we show experiments performed on FTU (Frascati Tokamak Upgrade) based on theoretical predictions that nonlinear interactions diminish when the peripheral plasma electron temperature is high, allowing significant wave penetration at high density. The results show that the coupled radio frequency power can penetrate into high-density plasmas due to weaker plasma edge effects, thus extending the effective range of lower hybrid current drive towards the domain relevant for fusion reactors.

On the predictive potential of Pc5 ULF waves to forecast relativistic electrons based on their relationships over two solar cycles

NASA Astrophysics Data System (ADS)

Lam, Hing-Lan

2017-01-01

A statistical study of relativistic electron (>2 MeV) fluence derived from geosynchronous satellites and Pc5 ultralow frequency (ULF) wave power computed from a ground magnetic observatory data located in Canada's auroral zone has been carried out. The ground observations were made near the foot points of field lines passing through the GOESs from 1987 to 2009 (cycles 22 and 23). We determine statistical relationships between the two quantities for different phases of a solar cycle and validate these relationships in two different cycles. There is a positive linear relationship between log fluence and log Pc5 power for all solar phases; however, the power law indices vary for different phases of the cycle. High index values existed during the descending phase. The Pearson's cross correlation between electron fluence and Pc5 power indicates fluence enhancement 2-3 days after strong Pc5 wave activity for all solar phases. The lag between the two quantities is shorter for extremely high fluence (due to high Pc5 power), which tends to occur during the declining phases of both cycles. Most occurrences of extremely low fluence were observed during the extended solar minimum of cycle 23. The precursory attribute of Pc5 power with respect to fluence and the enhancement of fluence due to rising Pc5 power both support the notion of an electron acceleration mechanism by Pc5 ULF waves. This precursor behavior establishes the potential of using Pc5 power to predict relativistic electron fluence.

Impacts of past and future climate change on wind energy resources in the United States

NASA Astrophysics Data System (ADS)

McCaa, J. R.; Wood, A.; Eichelberger, S.; Westrick, K.

2009-12-01

The links between climate change and trends in wind energy resources have important potential implications for the wind energy industry, and have received significant attention in recent studies. We have conducted two studies that provide insights into the potential for climate change to affect future wind power production. In one experiment, we projected changes in power capacity for a hypothetical wind farm located near Kennewick, Washington, due to greenhouse gas-induced climate change, estimated using a set of regional climate model simulations. Our results show that the annual wind farm power capacity is projected to decrease 1.3% by 2050. In a wider study focusing on wind speed instead of power, we analyzed projected changes in wind speed from 14 different climate simulations that were performed in support of the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4). Our results show that the predicted ensemble mean changes in annual mean wind speeds are expected to be modest. However, seasonal changes and changes predicted by individual models are large enough to affect the profitability of existing and future wind projects. The majority of the model simulations reveal that near-surface wind speed values are expected to shift poleward in response to the IPCC A2 emission scenario, particularly during the winter season. In the United States, most models agree that the mean annual wind speed values will increase in a region extending from the Great Lakes southward across the Midwest and into Texas. Decreased values, though, are predicted across most of the western United States. However, these predicted changes have a strong seasonal dependence, with wind speed increases over most of the United States during the winter and decreases over the northern United States during the summer.

Optimal cycling time trial position models: aerodynamics versus power output and metabolic energy.

PubMed

Fintelman, D M; Sterling, M; Hemida, H; Li, F-X

2014-06-03

The aerodynamic drag of a cyclist in time trial (TT) position is strongly influenced by the torso angle. While decreasing the torso angle reduces the drag, it limits the physiological functioning of the cyclist. Therefore the aims of this study were to predict the optimal TT cycling position as function of the cycling speed and to determine at which speed the aerodynamic power losses start to dominate. Two models were developed to determine the optimal torso angle: a 'Metabolic Energy Model' and a 'Power Output Model'. The Metabolic Energy Model minimised the required cycling energy expenditure, while the Power Output Model maximised the cyclists׳ power output. The input parameters were experimentally collected from 19 TT cyclists at different torso angle positions (0-24°). The results showed that for both models, the optimal torso angle depends strongly on the cycling speed, with decreasing torso angles at increasing speeds. The aerodynamic losses outweigh the power losses at cycling speeds above 46km/h. However, a fully horizontal torso is not optimal. For speeds below 30km/h, it is beneficial to ride in a more upright TT position. The two model outputs were not completely similar, due to the different model approaches. The Metabolic Energy Model could be applied for endurance events, while the Power Output Model is more suitable in sprinting or in variable conditions (wind, undulating course, etc.). It is suggested that despite some limitations, the models give valuable information about improving the cycling performance by optimising the TT cycling position. Copyright © 2014 Elsevier Ltd. All rights reserved.

Modeling of static and flowing-gas diode pumped alkali lasers

NASA Astrophysics Data System (ADS)

Barmashenko, Boris D.; Auslender, Ilya; Yacoby, Eyal; Waichman, Karol; Sadot, Oren; Rosenwaks, Salman

2016-03-01

Modeling of static and flowing-gas subsonic, transonic and supersonic Cs and K Ti:Sapphire and diode pumped alkali lasers (DPALs) is reported. A simple optical model applied to the static K and Cs lasers shows good agreement between the calculated and measured dependence of the laser power on the incident pump power. The model reproduces the observed threshold pump power in K DPAL which is much higher than that predicted by standard models of the DPAL. Scaling up flowing-gas DPALs to megawatt class power is studied using accurate three-dimensional computational fluid dynamics model, taking into account the effects of temperature rise and losses of alkali atoms due to ionization. Both the maximum achievable power and laser beam quality are estimated for Cs and K lasers. The performance of subsonic and, in particular, supersonic DPALs is compared with that of transonic, where supersonic nozzle and diffuser are spared and high power mechanical pump (needed for recovery of the gas total pressure which strongly drops in the diffuser), is not required for continuous closed cycle operation. For pumping by beams of the same rectangular cross section, comparison between end-pumping and transverse-pumping shows that the output power is not affected by the pump geometry, however, the intensity of the output laser beam in the case of transverse-pumped DPALs is strongly non-uniform in the laser beam cross section resulting in higher brightness and better beam quality in the far field for the end-pumping geometry where the intensity of the output beam is uniform.

Endocrine and aggressive responses to competition are moderated by contest outcome, gender, individual versus team competition, and implicit motives

PubMed Central

Oxford, Jon K.; Tiedtke, Johanna M.; Ossmann, Anna; Özbe, Dominik

2017-01-01

This study examined hormonal responses to competition in relation to gender, social context, and implicit motives. Participants (N = 326) were randomly assigned to win or lose in a 10-round, virtual face-to-face competition, in same-sex individual- and team-competition contexts. Saliva samples, taken before and twice after the competition, were assayed for testosterone (T), estradiol (E), progesterone (P), and cortisol (C). Implicit needs for power (nPower) and affiliation (nAffiliation) were assessed with a picture-story exercise before the competition. Aggression was measured via the volume at which participants set noise blasts for their opponents. Men competing individually and women competing as teams showed similar T increases after winning. C was differentially associated with outcome in the team matches, with higher post-match cortisol for winning women, and an opposite effect for male teams. Analyses including implicit motives indicated that situational variables interacted with motivational needs in shaping hormonal responses to competition: in naturally cycling women, nPower predicted T increases after winning and T and E decreases after losing. In men, nPower predicted T increases after losing and decreases after winning. In male teams, nPower predicted C increases after losing, but not after winning, whereas in individual competitions, nPower was a general negative predictor of C changes in women. nAffiliation predicted P increases for women competing as teams, and P decreases for women competing individually. Aggression was higher in men, losers, and teams than in women, winners, and individuals. High aggression was associated with high baseline C in women competing individually and with low baseline C and C decreases in women competing as teams and in men generally. Our findings suggest that while situational and gender factors play a role in hormonal responses to competition, they also depend on their interplay with motivational factors. They also suggest that while aggression is strongly affected by situational factors in the context of a competition, it has no direct association with motivational and hormonal correlates of dominance (nPower, T, E) and instead is associated with (mostly) low levels of C. PMID:28750061

A prototype of the procedure of strong ground motion prediction for intraslab earthquake based on characterized source model

NASA Astrophysics Data System (ADS)

Iwata, T.; Asano, K.; Sekiguchi, H.

2011-12-01

We propose a prototype of the procedure to construct source models for strong motion prediction during intraslab earthquakes based on the characterized source model (Irikura and Miyake, 2011). The key is the characterized source model which is based on the empirical scaling relationships for intraslab earthquakes and involve the correspondence between the SMGA (strong motion generation area, Miyake et al., 2003) and the asperity (large slip area). Iwata and Asano (2011) obtained the empirical relationships of the rupture area (S) and the total asperity area (Sa) to the seismic moment (Mo) as follows, with assuming power of 2/3 dependency of S and Sa on M0, S (km**2) = 6.57×10**(-11)×Mo**(2/3) (Nm) (1) Sa (km**2) = 1.04 ×10**(-11)×Mo**(2/3) (Nm) (2). Iwata and Asano (2011) also pointed out that the position and the size of SMGA approximately corresponds to the asperity area for several intraslab events. Based on the empirical relationships, we gave a procedure for constructing source models of intraslab earthquakes for strong motion prediction. [1] Give the seismic moment, Mo. [2] Obtain the total rupture area and the total asperity area according to the empirical scaling relationships between S, Sa, and Mo given by Iwata and Asano (2011). [3] Square rupture area and asperities are assumed. [4] The source mechanism is assumed to be the same as that of small events in the source region. [5] Plural scenarios including variety of the number of asperities and rupture starting points are prepared. We apply this procedure by simulating strong ground motions for several observed events for confirming the methodology.

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

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

Cipcigan, Flaviu S., E-mail: flaviu.cipcigan@ed.ac.uk; National Physical Laboratory, Hampton Road, Teddington, Middlesex TW11 0LW; Sokhan, Vlad P.

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 inmore » 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 modeler 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. - Highlights: • Electronic coarse graining unites many-body dispersion and polarisation beyond the dipole limit. • It consists of replacing the electrons of a molecule using a quantum harmonic oscillator, called a Quantum Drude Oscillator. • We present the first general implementation of Quantum Drude Oscillators in the molecular dynamics package QDO-MD. • We highlight the successful construction of a new, transferable molecular model of water: QDO-water. - Graphical abstract:.« less

Proactive monitoring of an onshore wind farm through lidar measurements, SCADA data and a data-driven RANS solver

NASA Astrophysics Data System (ADS)

Iungo, Giacomo Valerio; Camarri, Simone; Ciri, Umberto; El-Asha, Said; Leonardi, Stefano; Rotea, Mario A.; Santhanagopalan, Vignesh; Viola, Francesco; Zhan, Lu

2016-11-01

Site conditions, such as topography and local climate, as well as wind farm layout strongly affect performance of a wind power plant. Therefore, predictions of wake interactions and their effects on power production still remain a great challenge in wind energy. For this study, an onshore wind turbine array was monitored through lidar measurements, SCADA and met-tower data. Power losses due to wake interactions were estimated to be approximately 4% and 2% of the total power production under stable and convective conditions, respectively. This dataset was then leveraged for the calibration of a data driven RANS (DDRANS) solver, which is a compelling tool for prediction of wind turbine wakes and power production. DDRANS is characterized by a computational cost as low as that for engineering wake models, and adequate accuracy achieved through data-driven tuning of the turbulence closure model. DDRANS is based on a parabolic formulation, axisymmetry and boundary layer approximations, which allow achieving low computational costs. The turbulence closure model consists in a mixing length model, which is optimally calibrated with the experimental dataset. Assessment of DDRANS is then performed through lidar and SCADA data for different atmospheric conditions. This material is based upon work supported by the National Science Foundation under the I/UCRC WindSTAR, NSF Award IIP 1362033.

Phytoplankton growth rate modelling: can spectroscopic cell chemotyping be superior to physiological predictors?

PubMed

Fanesi, Andrea; Wagner, Heiko; Wilhelm, Christian

2017-02-08

Climate change has a strong impact on phytoplankton communities and water quality. However, the development of robust techniques to assess phytoplankton growth is still in progress. In this study, the growth rate of phytoplankton cells grown at different temperatures was modelled based on conventional physiological traits (e.g. chlorophyll, carbon and photosynthetic parameters) using the partial least square regression (PLSR) algorithm and compared with a new approach combining Fourier transform infrared-spectroscopy and PLSR. In this second model, it is assumed that the macromolecular composition of phytoplankton cells represents an intracellular marker for growth. The models have comparable high predictive power (R 2 > 0.8) and low error in predicting new observations. Interestingly, not all of the predictors present the same weight in the modelling of growth rate. A set of specific parameters, such as non-photochemical fluorescence quenching (NPQ) and the quantum yield of carbon production in the first model, and lipid, protein and carbohydrate contents for the second one, strongly covary with cell growth rate regardless of the taxonomic position of the phytoplankton species investigated. This reflects a set of specific physiological adjustments covarying with growth rate, conserved among taxonomically distant algal species that might be used as guidelines for the improvement of modern primary production models. The high predictive power of both sets of cellular traits for growth rate is of great importance for applied phycological studies. Our approach may find application as a quality control tool for the monitoring of phytoplankton populations in natural communities or in photobioreactors. © 2017 The Author(s).

Utility of metabolic profiling of serum in the diagnosis of pregnancy complications.

PubMed

Powell, Katie L; Carrozzi, Anthony; Stephens, Alexandre S; Tasevski, Vitomir; Morris, Jonathan M; Ashton, Anthony W; Dona, Anthony C

2018-06-01

Currently there are no clinical screening tests available to identify pregnancies at risk of developing preeclampsia (PET) and/or intrauterine growth restriction (IUGR), both of which are associated with abnormal placentation. Metabolic profiling is now a stable analytical platform used in many laboratories and has successfully been used to identify biomarkers associated with various pathological states. We used nuclear magnetic resonance spectroscopy (NMR) to metabolically profile serum samples collected from 143 pregnant women at 26-41 weeks gestation with pregnancy outcomes of PET, IUGR, PET IUGR or small for gestational age (SGA) that were age-matched to normal pre/term pregnancies. Spectral analysis found no difference in the measured metabolites from normal term, pre-term and SGA samples, and of 25 identified metabolites, only glutamate was marginally different between groups. Of the identified metabolites, 3-methylhistidine, creatinine, acetyl groups and acetate, were determined to be independent predictors of PET and produced area under the curves (AUC) = 0.938 and 0.936 for the discovery and validation sets. Only 3-hydroxybutyrate was determined to be an independent predictor of IUGR, however the model had low predictive power (AUC = 0.623 and 0.581 for the discovery and validation sets). A sub-panel of metabolites had strong predictive power for identifying PET samples in a validation dataset, however prediction of IUGR was more difficult using the identified metabolites. NMR based metabolomics can identify metabolites strongly associated with disease and has the potential to be useful in developing early clinical screening tests for at risk pregnancies. Copyright © 2018 Elsevier Ltd. All rights reserved.

Spatial Distribution of Large Cloud Drops

NASA Technical Reports Server (NTRS)

Marshak, A.; Knyazikhin, Y.; Larsen, M.; Wiscombe, W.

2004-01-01

By analyzing aircraft measurements of individual drop sizes in clouds, we have shown in a companion paper (Knyazikhin et al., 2004) that the probability of finding a drop of radius r at a linear scale l decreases as l(sup D(r)) where 0 less than or equal to D(r) less than or equal to 1. This paper shows striking examples of the spatial distribution of large cloud drops using models that simulate the observed power laws. In contrast to currently used models that assume homogeneity and therefore a Poisson distribution of cloud drops, these models show strong drop clustering, the more so the larger the drops. The degree of clustering is determined by the observed exponents D(r). The strong clustering of large drops arises naturally from the observed power-law statistics. This clustering has vital consequences for rain physics explaining how rain can form so fast. It also helps explain why remotely sensed cloud drop size is generally biased and why clouds absorb more sunlight than conventional radiative transfer models predict.

Caring Cooperators and Powerful Punishers: Differential Effects of Induced Care and Power Motivation on Different Types of Economic Decision Making.

PubMed

Chierchia, G; Lesemann, F H Parianen; Snower, D; Vogel, M; Singer, T

2017-09-11

Standard economic theory postulates that decisions are driven by stable context-insensitive preferences, while motivation psychology suggests they are driven by distinct context-sensitive motives with distinct evolutionary goals and characteristic psycho-physiological and behavioral patterns. To link these fields and test how distinct motives could differentially predict different types of economic decisions, we experimentally induced participants with either a Care or a Power motive, before having them take part in a suite of classic game theoretical paradigms involving monetary exchange. We show that the Care induction alone raised scores on a latent factor of cooperation-related behaviors, relative to a control condition, while, relative to Care, Power raised scores on a punishment-related factor. These findings argue against context-insensitive stable preferences and theories of strong reciprocity and in favor of a motive-based approach to economic decision making: Care and Power motivation have a dissociable fingerprint in shaping either cooperative or punishment behaviors.

What is happening under the surface? Power, conflict and the performance of medical teams.

PubMed

Janss, Rozemarijn; Rispens, Sonja; Segers, Mien; Jehn, Karen A

2012-09-01

The effect of teamwork on team performance is broadly recognised in the medical field. This recognition is manifested in educational programmes in which attention to interpersonal behaviours during teamwork is growing. Conflict and power differences influence interpersonal behaviours and are marked topics in studies of group functioning in the social and organisational psychology literature. Insights from the domain of social sciences put the ongoing improvement of teamwork into broader perspective. This paper shows how knowledge from the domain of social and organisational psychology contributes to the understanding of teamwork in the medical environment. More specifically, this paper suggests that unfolding the underlying issues of power and conflict within medical teams can be of extra help in the development of educational interventions aimed at improving team performance. We review the key social psychology and organisational behaviour literature concerning power and conflict, and relate the insights derived from this to the team process of ad hoc medical action teams. We present a theoretical framework in which insights into power and conflict are used to explain and predict team dynamics in ad hoc medical action teams. Power and conflict strongly influence interpersonal behaviour. Characteristics of medical action teams give rise to all kinds of issues of disagreement and are accompanied by complex issues of intra-team power distribution. We argue that how team members coordinate, cooperate and communicate is steered by members' personal motivations, which, in turn, strongly depend on their perceptions of power and conflict. Given the importance of the performance of these teams, we suggest future directions for the development of training interventions building on knowledge and theories derived from social and organisational psychology. © Blackwell Publishing Ltd 2012.

Understanding GPU Power. A Survey of Profiling, Modeling, and Simulation Methods

DOE PAGES

Bridges, Robert A.; Imam, Neena; Mintz, Tiffany M.

2016-09-01

Modern graphics processing units (GPUs) have complex architectures that admit exceptional performance and energy efficiency for high throughput applications.Though GPUs consume large amounts of power, their use for high throughput applications facilitate state-of-the-art energy efficiency and performance. Consequently, continued development relies on understanding their power consumption. Our work is a survey of GPU power modeling and profiling methods with increased detail on noteworthy efforts. Moreover, as direct measurement of GPU power is necessary for model evaluation and parameter initiation, internal and external power sensors are discussed. Hardware counters, which are low-level tallies of hardware events, share strong correlation to powermore » use and performance. Statistical correlation between power and performance counters has yielded worthwhile GPU power models, yet the complexity inherent to GPU architectures presents new hurdles for power modeling. Developments and challenges of counter-based GPU power modeling is discussed. Often building on the counter-based models, research efforts for GPU power simulation, which make power predictions from input code and hardware knowledge, provide opportunities for optimization in programming or architectural design. Noteworthy strides in power simulations for GPUs are included along with their performance or functional simulator counterparts when appropriate. Lastly, possible directions for future research are discussed.« less

Understanding GPU Power. A Survey of Profiling, Modeling, and Simulation Methods

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

Bridges, Robert A.; Imam, Neena; Mintz, Tiffany M.

Modern graphics processing units (GPUs) have complex architectures that admit exceptional performance and energy efficiency for high throughput applications.Though GPUs consume large amounts of power, their use for high throughput applications facilitate state-of-the-art energy efficiency and performance. Consequently, continued development relies on understanding their power consumption. Our work is a survey of GPU power modeling and profiling methods with increased detail on noteworthy efforts. Moreover, as direct measurement of GPU power is necessary for model evaluation and parameter initiation, internal and external power sensors are discussed. Hardware counters, which are low-level tallies of hardware events, share strong correlation to powermore » use and performance. Statistical correlation between power and performance counters has yielded worthwhile GPU power models, yet the complexity inherent to GPU architectures presents new hurdles for power modeling. Developments and challenges of counter-based GPU power modeling is discussed. Often building on the counter-based models, research efforts for GPU power simulation, which make power predictions from input code and hardware knowledge, provide opportunities for optimization in programming or architectural design. Noteworthy strides in power simulations for GPUs are included along with their performance or functional simulator counterparts when appropriate. Lastly, possible directions for future research are discussed.« less

Plant reproductive allocation predicts herbivore dynamics across spatial and temporal scales.

PubMed

Miller, Tom E X; Tyre, Andrew J; Louda, Svata M

2006-11-01

Life-history theory suggests that iteroparous plants should be flexible in their allocation of resources toward growth and reproduction. Such plasticity could have consequences for herbivores that prefer or specialize on vegetative versus reproductive structures. To test this prediction, we studied the response of the cactus bug (Narnia pallidicornis) to meristem allocation by tree cholla cactus (Opuntia imbricata). We evaluated the explanatory power of demographic models that incorporated variation in cactus relative reproductive effort (RRE; the proportion of meristems allocated toward reproduction). Field data provided strong support for a single model that defined herbivore fecundity as a time-varying, increasing function of host RRE. High-RRE plants were predicted to support larger insect populations, and this effect was strongest late in the season. Independent field data provided strong support for these qualitative predictions and suggested that plant allocation effects extend across temporal and spatial scales. Specifically, late-season insect abundance was positively associated with interannual changes in cactus RRE over 3 years. Spatial variation in insect abundance was correlated with variation in RRE among five cactus populations across New Mexico. We conclude that plant allocation can be a critical component of resource quality for insect herbivores and, thus, an important mechanism underlying variation in herbivore abundance across time and space.

Small Fermi surfaces and strong correlation effects in Dirac materials with holography

NASA Astrophysics Data System (ADS)

Seo, Yunseok; Song, Geunho; Park, Chanyong; Sin, Sang-Jin

2017-10-01

Recent discovery of transport anomaly in graphene demonstrated that a system known to be weakly interacting may become strongly correlated if system parameter (s) can be tuned such that fermi surface is sufficiently small. We study the strong correlation effects in the transport coefficients of Dirac materials doped with magnetic impurity under the magnetic field using holographic method. The experimental data of magneto-conductivity are well fit by our theory, however, not much data are available for other transports of Dirac material in such regime. Therefore, our results on heat transport, thermo-electric power and Nernst coefficients are left as predictions of holographic theory for generic Dirac materials in the vicinity of charge neutral point with possible surface gap. We give detailed look over each magneto-transport observable and 3Dplots to guide future experiments.

Interpretable Deep Models for ICU Outcome Prediction

PubMed Central

Che, Zhengping; Purushotham, Sanjay; Khemani, Robinder; Liu, Yan

2016-01-01

Exponential surge in health care data, such as longitudinal data from electronic health records (EHR), sensor data from intensive care unit (ICU), etc., is providing new opportunities to discover meaningful data-driven characteristics and patterns ofdiseases. Recently, deep learning models have been employedfor many computational phenotyping and healthcare prediction tasks to achieve state-of-the-art performance. However, deep models lack interpretability which is crucial for wide adoption in medical research and clinical decision-making. In this paper, we introduce a simple yet powerful knowledge-distillation approach called interpretable mimic learning, which uses gradient boosting trees to learn interpretable models and at the same time achieves strong prediction performance as deep learning models. Experiment results on Pediatric ICU dataset for acute lung injury (ALI) show that our proposed method not only outperforms state-of-the-art approaches for morality and ventilator free days prediction tasks but can also provide interpretable models to clinicians. PMID:28269832

Resting-state qEEG predicts rate of second language learning in adults.

PubMed

Prat, Chantel S; Yamasaki, Brianna L; Kluender, Reina A; Stocco, Andrea

2016-01-01

Understanding the neurobiological basis of individual differences in second language acquisition (SLA) is important for research on bilingualism, learning, and neural plasticity. The current study used quantitative electroencephalography (qEEG) to predict SLA in college-aged individuals. Baseline, eyes-closed resting-state qEEG was used to predict language learning rate during eight weeks of French exposure using an immersive, virtual scenario software. Individual qEEG indices predicted up to 60% of the variability in SLA, whereas behavioral indices of fluid intelligence, executive functioning, and working-memory capacity were not correlated with learning rate. Specifically, power in beta and low-gamma frequency ranges over right temporoparietal regions were strongly positively correlated with SLA. These results highlight the utility of resting-state EEG for studying the neurobiological basis of SLA in a relatively construct-free, paradigm-independent manner. Published by Elsevier Inc.

Cultural variation in seasonal depression: cross-national differences in winter versus summer patterns of seasonal affective disorder.

PubMed

Kasof, Joseph

2009-05-01

Research suggests that two dimensions of national culture, individualism-collectivism and power distance, predict affective responses to the seasonally varying levels of ambient sunlight that may underlie regular cycles of mood and behavior in Seasonal Affective Disorder (SAD). Specifically, negative affect is predicted by the diminished sunlight of fall-winter in countries higher in individualism and lower in power distance, and by the increased sunlight of spring-summer in countries lower in individualism and higher in power distance. This study tests whether individualism correlates positively, and power distance negatively, with the frequency of winter-SAD relative to that of summer-SAD. A search for studies reporting frequencies of both winter-SAD and summer-SAD identified 55 samples encompassing 18 countries and 38,408 participants, including 1931 with SAD. The frequency of winter-SAD, relative to that of summer-SAD, correlated positively with individualism (r=.67, p=.001) and negatively with power distance (r=-.72, p=.0001). Countries in which winter-SAD was more common than summer-SAD were significantly more individualistic and less power-distant than countries in which summer-SAD was more common than winter-SAD. Results survived various tests of threats to validity. The study is limited by the quantity, quality, diversity, and representativeness of the research under review and by its correlational design. Individualism and power distance are strongly related to the relative prevalence of winter-SAD and summer-SAD. Culture may play an important but previously overlooked role in the etiology of SAD.

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.

Tidal current and tidal energy changes imposed by a dynamic tidal power system in the Taiwan Strait, China

NASA Astrophysics Data System (ADS)

Dai, Peng; Zhang, Jisheng; Zheng, Jinhai

2017-12-01

The Taiwan Strait has recently been proposed as a promising site for dynamic tidal power systems because of its shallow depth and strong tides. Dynamic tidal power is a new concept for extracting tidal potential energy in which a coast-perpendicular dike is used to create water head and generate electricity via turbines inserted in the dike. Before starting such a project, the potential power output and hydrodynamic impacts of the dike must be assessed. In this study, a two-dimensional numerical model based on the Delft3D-FLOW module is established to simulate tides in China. A dike module is developed to account for turbine processes and estimate power output by integrating a special algorithm into the model. The domain decomposition technique is used to divide the computational zone into two subdomains with grid refinement near the dike. The hydrodynamic processes predicted by the model, both with and without the proposed construction, are examined in detail, including tidal currents and tidal energy flux. The predicted time-averaged power yields with various opening ratios are presented. The results show that time-averaged power yield peaks at an 8% opening ratio. For semidiurnal tides, the flow velocity increases in front of the head of the dike and decreases on either side. For diurnal tides, these changes are complicated by the oblique incidence of tidal currents with respect to the dike as well as by bathymetric features. The dike itself blocks the propagation of tidal energy flux.

Three-dimensional effects for radio frequency antenna modeling

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

Carter, M.D.; Batchelor, D.B.; Stallings, D.C.

1994-10-15

Electromagnetic field calculations for radio frequency (rf) antennas in two dimensions (2-D) neglect finite antenna length effects as well as the feeders leading to the main current strap. The 2-D calculations predict that the return currents in the sidewalls of the antenna structure depend strongly on the plasma parameters, but this prediction is suspect because of experimental evidence. To study the validity of the 2-D approximation, the Multiple Antenna Implementation System (MAntIS) has been used to perform three-dimensional (3-D) modeling of the power spectrum, plasma loading, and inductance for a relevant loop antenna design. Effects on antenna performance caused bymore » feeders to the main current strap and conducting sidewalls are considered. The modeling shows that the feeders affect the launched power spectrum in an indirect way by forcing the driven rf current to return in the antenna structure rather than the plasma, as in the 2-D model. It has also been found that poloidal dependencies in the plasma impedance matrix can reduce the loading predicted from that predicted in the 2-D model. For some plasma parameters, the combined 3-D effects can lead to a reduction in the predicted loading by as much as a factor of 2 from that given by the 2-D model, even with end-effect corrections for the 2-D model.« less

Three-dimensional effects for radio frequency antenna modeling

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

Carter, M.D.; Batchelor, D.B.; Stallings, D.C.

1993-12-31

Electromagnetic field calculations for radio frequency (rf) antennas in two dimensions (2-D) neglect finite antenna length effects as well as the feeders leading to the main current strap. The 2-D calculations predict that the return currents in the sidewalls of the antenna structure depend strongly on the plasma parameters, but this prediction is suspect because of experimental evidence. To study the validity of the 2-D approximation, the Multiple Antenna Implementation System (MAntIS) has been used to perform three-dimensional (3-D) modeling of the power spectrum, plasma loading, and inductance for a relevant loop antenna design. Effects on antenna performance caused bymore » feeders to the main current strap and conducting sidewalls are considered. The modeling shows that the feeders affect the launched power spectrum in an indirect way by forcing the driven rf current to return in the antenna structure rather than the plasma, as in the 2-D model. It has also been found that poloidal dependencies in the plasma impedance matrix can reduce the loading predicted from that predicted in the 2-D model. For some plasma parameters, the combined 3-D effects can lead to a reduction in the predicted loading by as much as a factor of 2 from that given by the 2-D model, even with end-effect corrections for the 2-D model.« less

A Large-scale Cross-sectional Study of ALK Rearrangements and EGFR Mutations in Non-small-cell Lung Cancer in Chinese Han Population

PubMed Central

Hong, Shaodong; Fang, Wenfeng; Hu, Zhihuang; Zhou, Ting; Yan, Yue; Qin, Tao; Tang, Yanna; Ma, Yuxiang; Zhao, Yuanyuan; Xue, Cong; Huang, Yan; Zhao, Hongyun; Zhang, Li

2014-01-01

The predictive power of age at diagnosis and smoking history for ALK rearrangements and EGFR mutations in non-small-cell lung cancer (NSCLC) remains not fully understood. In this cross-sectional study, 1160 NSCLC patients were prospectively enrolled and genotyped for EML4-ALK rearrangements and EGFR mutations. Multivariate logistic regression analysis was performed to explore the association between clinicopathological features and these two genetic aberrations. Receiver operating characteristic (ROC) curves methodology was applied to evaluate the predictive value. We showed that younger age at diagnosis was the only independent variable associated with EML4-ALK rearrangements (odds ratio (OR) per 5 years' increment, 0.68; p < 0.001), while lower tobacco exposure (OR per 5 pack-years' increment, 0.88; p < 0.001), adenocarcinoma (OR, 6.61; p < 0.001), and moderate to high differentiation (OR, 2.05; p < 0.001) were independently associated with EGFR mutations. Age at diagnosis was a very strong predictor of ALK rearrangements but poorly predicted EGFR mutations, while smoking pack-years may predict the presence of EGFR mutations and ALK rearrangements but with rather limited power. These findings should assist clinicians in assessing the likelihood of EML4-ALK rearrangements and EGFR mutations and understanding their biological implications in NSCLC. PMID:25434695

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.

The Implications of Big-Five Standing for the Distribution of Trait Manifestation in Behavior: Fifteen Experience-Sampling Studies and a Meta-Analysis

PubMed Central

Fleeson, William; Gallagher, M. Patrick

2009-01-01

One of the fundamental questions in personality psychology is whether and how strongly trait standing relates to the traits that people actually manifest in their behavior, when faced with real pressures and real consequences of their actions. One reason this question is fundamental is the common belief that traits do not predict how individuals behave, which leads to the reasonable conclusion that traits are not important to study. However, this conclusion is surprising given that there is almost no data on the ability of traits to predict distributions of naturally occurring, representative behaviors of individuals (and that there are many studies showing that traits do indeed predict specific behaviors). This paper describes a meta-analysis of 15 experience-sampling studies, conducted over the course of eight years, amassing over 20,000 reports of trait manifestation in behavior. Participants reported traits on typical self-report questionnaires, then described their current behavior multiple times per day for several days, as the behavior was occurring. Results showed that traits, contrary to expectations, were strongly predictive of individual differences in trait manifestation in behavior, predicting average levels with correlations between .42 and .56 (approaching .60 for stringently restricted studies). Several other ways of summarizing trait manifestation in behavior were also predicted from traits. These studies provide evidence that traits are powerful predictors of actual manifestation of traits in behavior. PMID:19968421

The wind power prediction research based on mind evolutionary algorithm

NASA Astrophysics Data System (ADS)

Zhuang, Ling; Zhao, Xinjian; Ji, Tianming; Miao, Jingwen; Cui, Haina

2018-04-01

When the wind power is connected to the power grid, its characteristics of fluctuation, intermittent and randomness will affect the stability of the power system. The wind power prediction can guarantee the power quality and reduce the operating cost of power system. There were some limitations in several traditional wind power prediction methods. On the basis, the wind power prediction method based on Mind Evolutionary Algorithm (MEA) is put forward and a prediction model is provided. The experimental results demonstrate that MEA performs efficiently in term of the wind power prediction. The MEA method has broad prospect of engineering application.

The effect of bedding system selected by manual muscle testing on sleep-related cardiovascular functions.

PubMed

Kuo, Terry B J; Li, Jia-Yi; Lai, Chun-Ting; Huang, Yu-Chun; Hsu, Ya-Chuan; Yang, Cheryl C H

2013-01-01

Different types of mattresses affect sleep quality and waking muscle power. Whether manual muscle testing (MMT) predicts the cardiovascular effects of the bedding system was explored using ten healthy young men. For each participant, two bedding systems, one inducing the strongest limb muscle force (strong bedding system) and the other inducing the weakest limb force (weak bedding system), were identified using MMT. Each bedding system, in total five mattresses and eight pillows of different firmness, was used for two continuous weeks at the participant's home in a random and double-blind sequence. A sleep log, a questionnaire, and a polysomnography were used to differentiate the two bedding systems. Heart rate variability and arterial pressure variability analyses showed that the strong bedding system resulted in decreased cardiovascular sympathetic modulation, increased cardiac vagal activity, and increased baroreceptor reflex sensitivity during sleep as compared to the weak bedding system. Different bedding systems have distinct cardiovascular effects during sleep that can be predicted by MMT.

The Effect of Bedding System Selected by Manual Muscle Testing on Sleep-Related Cardiovascular Functions

PubMed Central

Kuo, Terry B. J.; Li, Jia-Yi; Lai, Chun-Ting; Huang, Yu-Chun; Hsu, Ya-Chuan; Yang, Cheryl C. H.

2013-01-01

Background. Different types of mattresses affect sleep quality and waking muscle power. Whether manual muscle testing (MMT) predicts the cardiovascular effects of the bedding system was explored using ten healthy young men. Methods. For each participant, two bedding systems, one inducing the strongest limb muscle force (strong bedding system) and the other inducing the weakest limb force (weak bedding system), were identified using MMT. Each bedding system, in total five mattresses and eight pillows of different firmness, was used for two continuous weeks at the participant's home in a random and double-blind sequence. A sleep log, a questionnaire, and a polysomnography were used to differentiate the two bedding systems. Results and Conclusion. Heart rate variability and arterial pressure variability analyses showed that the strong bedding system resulted in decreased cardiovascular sympathetic modulation, increased cardiac vagal activity, and increased baroreceptor reflex sensitivity during sleep as compared to the weak bedding system. Different bedding systems have distinct cardiovascular effects during sleep that can be predicted by MMT. PMID:24371836

Entanglement of purification through holographic duality

NASA Astrophysics Data System (ADS)

Umemoto, Koji; Takayanagi, Tadashi

2018-06-01

The gauge/gravity correspondence discovered two decades ago has had a profound influence on how the basic laws in physics should be formulated. In spite of the predictive power of holographic approaches (for example, when they are applied to strongly coupled condensed-matter physics problems), the fundamental reasons behind their success remain unclear. Recently, the role of quantum entanglement has come to the fore. Here we explore a quantity that connects gravity and quantum information in the light of the gauge/gravity correspondence. This is given by the minimal cross-section of the entanglement wedge that connects two disjoint subsystems in a gravity dual. In particular, we focus on various inequalities that are satisfied by this quantity. They suggest that it is a holographic counterpart of the quantity called entanglement of purification, which measures a bipartite correlation in a given mixed state. We give a heuristic argument that supports this identification based on a tensor network interpretation of holography. This predicts that the entanglement of purification satisfies the strong superadditivity for holographic conformal field theories.

Identifying and modeling the structural discontinuities of human interactions

NASA Astrophysics Data System (ADS)

Grauwin, Sebastian; Szell, Michael; Sobolevsky, Stanislav; Hövel, Philipp; Simini, Filippo; Vanhoof, Maarten; Smoreda, Zbigniew; Barabási, Albert-László; Ratti, Carlo

2017-04-01

The idea of a hierarchical spatial organization of society lies at the core of seminal theories in human geography that have strongly influenced our understanding of social organization. Along the same line, the recent availability of large-scale human mobility and communication data has offered novel quantitative insights hinting at a strong geographical confinement of human interactions within neighboring regions, extending to local levels within countries. However, models of human interaction largely ignore this effect. Here, we analyze several country-wide networks of telephone calls - both, mobile and landline - and in either case uncover a systematic decrease of communication induced by borders which we identify as the missing variable in state-of-the-art models. Using this empirical evidence, we propose an alternative modeling framework that naturally stylizes the damping effect of borders. We show that this new notion substantially improves the predictive power of widely used interaction models. This increases our ability to understand, model and predict social activities and to plan the development of infrastructures across multiple scales.

Identifying and modeling the structural discontinuities of human interactions

PubMed Central

Grauwin, Sebastian; Szell, Michael; Sobolevsky, Stanislav; Hövel, Philipp; Simini, Filippo; Vanhoof, Maarten; Smoreda, Zbigniew; Barabási, Albert-László; Ratti, Carlo

2017-01-01

The idea of a hierarchical spatial organization of society lies at the core of seminal theories in human geography that have strongly influenced our understanding of social organization. Along the same line, the recent availability of large-scale human mobility and communication data has offered novel quantitative insights hinting at a strong geographical confinement of human interactions within neighboring regions, extending to local levels within countries. However, models of human interaction largely ignore this effect. Here, we analyze several country-wide networks of telephone calls - both, mobile and landline - and in either case uncover a systematic decrease of communication induced by borders which we identify as the missing variable in state-of-the-art models. Using this empirical evidence, we propose an alternative modeling framework that naturally stylizes the damping effect of borders. We show that this new notion substantially improves the predictive power of widely used interaction models. This increases our ability to understand, model and predict social activities and to plan the development of infrastructures across multiple scales. PMID:28443647

Identifying and modeling the structural discontinuities of human interactions.

PubMed

Grauwin, Sebastian; Szell, Michael; Sobolevsky, Stanislav; Hövel, Philipp; Simini, Filippo; Vanhoof, Maarten; Smoreda, Zbigniew; Barabási, Albert-László; Ratti, Carlo

2017-04-26

The idea of a hierarchical spatial organization of society lies at the core of seminal theories in human geography that have strongly influenced our understanding of social organization. Along the same line, the recent availability of large-scale human mobility and communication data has offered novel quantitative insights hinting at a strong geographical confinement of human interactions within neighboring regions, extending to local levels within countries. However, models of human interaction largely ignore this effect. Here, we analyze several country-wide networks of telephone calls - both, mobile and landline - and in either case uncover a systematic decrease of communication induced by borders which we identify as the missing variable in state-of-the-art models. Using this empirical evidence, we propose an alternative modeling framework that naturally stylizes the damping effect of borders. We show that this new notion substantially improves the predictive power of widely used interaction models. This increases our ability to understand, model and predict social activities and to plan the development of infrastructures across multiple scales.

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

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

Martin, Luis; Marchante, Ruth; Cony, Marco

2010-10-15

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

Implications of Atmospheric Test Fallout Data for Nuclear Winter.

NASA Astrophysics Data System (ADS)

Baker, George Harold, III

1987-09-01

Atmospheric test fallout data have been used to determine admissable dust particle size distributions for nuclear winter studies. The research was originally motivated by extreme differences noted in the magnitude and longevity of dust effects predicted by particle size distributions routinely used in fallout predictions versus those used for nuclear winter studies. Three different sets of historical data have been analyzed: (1) Stratospheric burden of Strontium -90 and Tungsten-185, 1954-1967 (92 contributing events); (2) Continental U.S. Strontium-90 fallout through 1958 (75 contributing events); (3) Local Fallout from selected Nevada tests (16 events). The contribution of dust to possible long term climate effects following a nuclear exchange depends strongly on the particle size distribution. The distribution affects both the atmospheric residence time and optical depth. One dimensional models of stratospheric/tropospheric fallout removal were developed and used to identify optimum particle distributions. Results indicate that particle distributions which properly predict bulk stratospheric activity transfer tend to be somewhat smaller than number size distributions used in initial nuclear winter studies. In addition, both ^{90}Sr and ^ {185}W fallout behavior is better predicted by the lognormal distribution function than the prevalent power law hybrid function. It is shown that the power law behavior of particle samples may well be an aberration of gravitational cloud stratification. Results support the possible existence of two independent particle size distributions in clouds generated by surface or near surface bursts. One distribution governs late time stratospheric fallout, the other governs early time fallout. A bimodal lognormal distribution is proposed to describe the cloud particle population. The distribution predicts higher initial sunlight attenuation and lower late time attenuation than the power law hybrid function used in initial nuclear winter studies.

Testing the Predictive Power of Coulomb Stress on Aftershock Sequences

NASA Astrophysics Data System (ADS)

Woessner, J.; Lombardi, A.; Werner, M. J.; Marzocchi, W.

2009-12-01

Empirical and statistical models of clustered seismicity are usually strongly stochastic and perceived to be uninformative in their forecasts, since only marginal distributions are used, such as the Omori-Utsu and Gutenberg-Richter laws. In contrast, so-called physics-based aftershock models, based on seismic rate changes calculated from Coulomb stress changes and rate-and-state friction, make more specific predictions: anisotropic stress shadows and multiplicative rate changes. We test the predictive power of models based on Coulomb stress changes against statistical models, including the popular Short Term Earthquake Probabilities and Epidemic-Type Aftershock Sequences models: We score and compare retrospective forecasts on the aftershock sequences of the 1992 Landers, USA, the 1997 Colfiorito, Italy, and the 2008 Selfoss, Iceland, earthquakes. To quantify predictability, we use likelihood-based metrics that test the consistency of the forecasts with the data, including modified and existing tests used in prospective forecast experiments within the Collaboratory for the Study of Earthquake Predictability (CSEP). Our results indicate that a statistical model performs best. Moreover, two Coulomb model classes seem unable to compete: Models based on deterministic Coulomb stress changes calculated from a given fault-slip model, and those based on fixed receiver faults. One model of Coulomb stress changes does perform well and sometimes outperforms the statistical models, but its predictive information is diluted, because of uncertainties included in the fault-slip model. Our results suggest that models based on Coulomb stress changes need to incorporate stochastic features that represent model and data uncertainty.

Efficient Power-Transfer Capability Analysis of the TET System Using the Equivalent Small Parameter Method.

PubMed

Yanzhen Wu; Hu, A P; Budgett, D; Malpas, S C; Dissanayake, T

2011-06-01

Transcutaneous energy transfer (TET) enables the transfer of power across the skin without direct electrical connection. It is a mechanism for powering implantable devices for the lifetime of a patient. For maximum power transfer, it is essential that TET systems be resonant on both the primary and secondary sides, which requires considerable design effort. Consequently, a strong need exists for an efficient method to aid the design process. This paper presents an analytical technique appropriate to analyze complex TET systems. The system's steady-state solution in closed form with sufficient accuracy is obtained by employing the proposed equivalent small parameter method. It is shown that power-transfer capability can be correctly predicted without tedious iterative simulations or practical measurements. Furthermore, for TET systems utilizing a current-fed push-pull soft switching resonant converter, it is found that the maximum energy transfer does not occur when the primary and secondary resonant tanks are "tuned" to the nominal resonant frequency. An optimal turning point exists, corresponding to the system's maximum power-transfer capability when optimal tuning capacitors are applied.

Mir Cooperative Solar Array Flight Performance Data and Computational Analysis

NASA Technical Reports Server (NTRS)

Kerslake, Thomas W.; Hoffman, David J.

1997-01-01

The Mir Cooperative Solar Array (MCSA) was developed jointly by the United States (US) and Russia to provide approximately 6 kW of photovoltaic power to the Russian space station Mir. The MCSA was launched to Mir in November 1995 and installed on the Kvant-1 module in May 1996. Since the MCSA photovoltaic panel modules (PPMs) are nearly identical to those of the International Space Station (ISS) photovoltaic arrays, MCSA operation offered an opportunity to gather multi-year performance data on this technology prior to its implementation on ISS. Two specially designed test sequences were executed in June and December 1996 to measure MCSA performance. Each test period encompassed 3 orbital revolutions whereby the current produced by the MCSA channels was measured. The temperature of MCSA PPMs was also measured. To better interpret the MCSA flight data, a dedicated FORTRAN computer code was developed to predict the detailed thermal-electrical performance of the MCSA. Flight data compared very favorably with computational performance predictions. This indicated that the MCSA electrical performance was fully meeting pre-flight expectations. There were no measurable indications of unexpected or precipitous MCSA performance degradation due to contamination or other causes after 7 months of operation on orbit. Power delivered to the Mir bus was lower than desired as a consequence of the retrofitted power distribution cabling. The strong correlation of experimental and computational results further bolsters the confidence level of performance codes used in critical ISS electric power forecasting. In this paper, MCSA flight performance tests are described as well as the computational modeling behind the performance predictions.

The phase of prestimulus alpha oscillations affects tactile perception.

PubMed

Ai, Lei; Ro, Tony

2014-03-01

Previous studies have shown that neural oscillations in the 8- to 12-Hz range influence sensory perception. In the current study, we examined whether both the power and phase of these mu/alpha oscillations predict successful conscious tactile perception. Near-threshold tactile stimuli were applied to the left hand while electroencephalographic (EEG) activity was recorded over the contralateral right somatosensory cortex. We found a significant inverted U-shaped relationship between prestimulus mu/alpha power and detection rate, suggesting that there is an intermediate level of alpha power that is optimal for tactile perception. We also found a significant difference in phase angle concentration at stimulus onset that predicted whether the upcoming tactile stimulus was perceived or missed. As has been shown in the visual system, these findings suggest that these mu/alpha oscillations measured over somatosensory areas exert a strong inhibitory control on tactile perception and that pulsed inhibition by these oscillations shapes the state of brain activity necessary for conscious perception. They further suggest that these common phasic processing mechanisms across different sensory modalities and brain regions may reflect a common underlying encoding principle in perceptual processing that leads to momentary windows of perceptual awareness.

The Usability of Noise Level from Rock Cutting for the Prediction of Physico-Mechanical Properties of Rocks

NASA Astrophysics Data System (ADS)

Delibalta, M. S.; Kahraman, S.; Comakli, R.

2015-11-01

Because the indirect tests are easier and cheaper than the direct tests, the prediction of rock properties from the indirect testing methods is important especially for the preliminary investigations. In this study, the predictability of the physico-mechanical rock properties from the noise level measured during cutting rock with diamond saw was investigated. Noise measurement test, uniaxial compressive strength (UCS) test, Brazilian tensile strength (BTS) test, point load strength (Is) test, density test, and porosity test were carried out on 54 different rock types in the laboratory. The results were statistically analyzed to derive estimation equations. Strong correlations between the noise level and the mechanical rock properties were found. The relations follow power functions. Increasing rock strength increases the noise level. Density and porosity also correlated strongly with the noise level. The relations follow linear functions. Increasing density increases the noise level while increasing porosity decreases the noise level. The developed equations are valid for the rocks with a compressive strength below 150 MPa. Concluding remark is that the physico-mechanical rock properties can reliably be estimated from the noise level measured during cutting the rock with diamond saw.

Comparison of RNA-seq and microarray-based models for clinical endpoint prediction.

PubMed

Zhang, Wenqian; Yu, Ying; Hertwig, Falk; Thierry-Mieg, Jean; Zhang, Wenwei; Thierry-Mieg, Danielle; Wang, Jian; Furlanello, Cesare; Devanarayan, Viswanath; Cheng, Jie; Deng, Youping; Hero, Barbara; Hong, Huixiao; Jia, Meiwen; Li, Li; Lin, Simon M; Nikolsky, Yuri; Oberthuer, André; Qing, Tao; Su, Zhenqiang; Volland, Ruth; Wang, Charles; Wang, May D; Ai, Junmei; Albanese, Davide; Asgharzadeh, Shahab; Avigad, Smadar; Bao, Wenjun; Bessarabova, Marina; Brilliant, Murray H; Brors, Benedikt; Chierici, Marco; Chu, Tzu-Ming; Zhang, Jibin; Grundy, Richard G; He, Min Max; Hebbring, Scott; Kaufman, Howard L; Lababidi, Samir; Lancashire, Lee J; Li, Yan; Lu, Xin X; Luo, Heng; Ma, Xiwen; Ning, Baitang; Noguera, Rosa; Peifer, Martin; Phan, John H; Roels, Frederik; Rosswog, Carolina; Shao, Susan; Shen, Jie; Theissen, Jessica; Tonini, Gian Paolo; Vandesompele, Jo; Wu, Po-Yen; Xiao, Wenzhong; Xu, Joshua; Xu, Weihong; Xuan, Jiekun; Yang, Yong; Ye, Zhan; Dong, Zirui; Zhang, Ke K; Yin, Ye; Zhao, Chen; Zheng, Yuanting; Wolfinger, Russell D; Shi, Tieliu; Malkas, Linda H; Berthold, Frank; Wang, Jun; Tong, Weida; Shi, Leming; Peng, Zhiyu; Fischer, Matthias

2015-06-25

Gene expression profiling is being widely applied in cancer research to identify biomarkers for clinical endpoint prediction. Since RNA-seq provides a powerful tool for transcriptome-based applications beyond the limitations of microarrays, we sought to systematically evaluate the performance of RNA-seq-based and microarray-based classifiers in this MAQC-III/SEQC study for clinical endpoint prediction using neuroblastoma as a model. We generate gene expression profiles from 498 primary neuroblastomas using both RNA-seq and 44 k microarrays. Characterization of the neuroblastoma transcriptome by RNA-seq reveals that more than 48,000 genes and 200,000 transcripts are being expressed in this malignancy. We also find that RNA-seq provides much more detailed information on specific transcript expression patterns in clinico-genetic neuroblastoma subgroups than microarrays. To systematically compare the power of RNA-seq and microarray-based models in predicting clinical endpoints, we divide the cohort randomly into training and validation sets and develop 360 predictive models on six clinical endpoints of varying predictability. Evaluation of factors potentially affecting model performances reveals that prediction accuracies are most strongly influenced by the nature of the clinical endpoint, whereas technological platforms (RNA-seq vs. microarrays), RNA-seq data analysis pipelines, and feature levels (gene vs. transcript vs. exon-junction level) do not significantly affect performances of the models. We demonstrate that RNA-seq outperforms microarrays in determining the transcriptomic characteristics of cancer, while RNA-seq and microarray-based models perform similarly in clinical endpoint prediction. Our findings may be valuable to guide future studies on the development of gene expression-based predictive models and their implementation in clinical practice.

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.

Innate and genetic nature of circadian rhythms

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

Ehret, C.F.

1979-01-01

The field of Circadian Cybernetics is presented as a major new integrating discipline that deals with biological time constants in the temporal range from minutes to days. The essential generalizations that give the field strong predictive power are presented in the form of 3 sets of rules: (1) The Mode Rules; (2) The Period Rules; and (3) The Phase Rules. Within this context the innate and phylogenetically ubiquitous nature of circadian oscillations is comprehended, along with their responses to a wide variety environmental stimuli.

Preventing the spread of genital warts: using fear appeals to promote self-protective behaviors.

PubMed

Witte, K; Berkowitz, J M; Cameron, K A; McKeon, J K

1998-10-01

A fear appeal campaign to decrease the spread of genital warts was conducted and evaluated. Theoretically guided by the Extended Parallel Process Model, this field study illustrated why fear appeal campaigns often appear to fail in public health arenas. Five hypotheses, which predicted when and under what conditions fear appeal campaigns would fail or succeed, were tested and supported. The results demonstrated that fear appeals can be powerful persuasive devices if they induce strong perceptions of threat and fear (which motivate action) and if they induce strong perceptions of efficacy with regard to a recommended response (which channels the action in a health protective direction). Recommendations to researchers and public health practitioners are offered.

Modeling of flowing gas diode pumped alkali lasers: dependence of the operation on the gas velocity and on the nature of the buffer gas.

PubMed

Barmashenko, B D; Rosenwaks, S

2012-09-01

A simple, semi-analytical model of flowing gas diode pumped alkali lasers (DPALs) is presented. The model takes into account the rise of temperature in the lasing medium with increasing pump power, resulting in decreasing pump absorption and slope efficiency. The model predicts the dependence of power on the flow velocity in flowing gas DPALs and checks the effect of using a buffer gas with high molar heat capacity and large relaxation rate constant between the 2P3/2 and 2P1/2 fine-structure levels of the alkali atom. It is found that the power strongly increases with flow velocity and that by replacing, e.g., ethane by propane as a buffer gas the power may be further increased by up to 30%. Eight kilowatt is achievable for 20 kW pump at flow velocity of 20  m/s.

High power narrow-band fiber-based ASE source.

PubMed

Schmidt, O; Rekas, M; Wirth, C; Rothhardt, J; Rhein, S; Kliner, A; Strecker, M; Schreiber, T; Limpert, J; Eberhardt, R; Tünnermann, A

2011-02-28

In this paper we describe a high power narrow-band amplified spontaneous emission (ASE) light source at 1030 nm center wavelength generated in an Yb-doped fiber-based experimental setup. By cutting a small region out of a broadband ASE spectrum using two fiber Bragg gratings a strongly constrained bandwidth of 12±2 pm (3.5±0.6 GHz) is formed. A two-stage high power fiber amplifier system is used to boost the output power up to 697 W with a measured beam quality of M2≤1.34. In an additional experiment we demonstrate a stimulated Brillouin scattering (SBS) suppression of at least 17 dB (theoretically predicted ~20 dB), which is only limited by the dynamic range of the measurement and not by the onset of SBS when using the described light source. The presented narrow-band ASE source could be of great interest for brightness scaling applications by beam combination, where SBS is known as a limiting factor.

Comparative analysis of magnetic resonance in the polaron pair recombination and the triplet exciton-polaron quenching models

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

Mkhitaryan, V. V.; Danilovic, D.; Hippola, C.

We present a comparative theoretical study of magnetic resonance within the polaron pair recombination (PPR) and the triplet exciton-polaron quenching (TPQ) models. Both models have been invoked to interpret the photoluminescence detected magnetic resonance (PLDMR) results in π-conjugated materials and devices. We show that resonance line shapes calculated within the two models differ dramatically in several regards. First, in the PPR model, the line shape exhibits unusual behavior upon increasing the microwave power: it evolves from fully positive at weak power to fully negative at strong power. In contrast, in the TPQ model, the PLDMR is completely positive, showing amore » monotonic saturation. Second, the two models predict different dependencies of the resonance signal on the photoexcitation power, PL. At low PL, the resonance amplitude Δ I/I is ∝ PL within the PPR model, while it is ∝ P2L crossing over to P3L within the TPQ model. On the physical level, the differences stem from different underlying spin dynamics. Most prominently, a negative resonance within the PPR model has its origin in the microwave-induced spin-Dicke effect, leading to the resonant quenching of photoluminescence. The spin-Dicke effect results from the spin-selective recombination, leading to a highly correlated precession of the on-resonance pair partners under the strong microwave power. This effect is not relevant for TPQ mechanism, where the strong zero-field splitting renders the majority of triplets off resonance. On the technical level, the analytical evaluation of the line shapes for the two models is enabled by the fact that these shapes can be expressed via the eigenvalues of a complex Hamiltonian. This bypasses the necessity of solving the much larger complex linear system of the stochastic Liouville equations. Lastly, our findings pave the way towards a reliable discrimination between the two mechanisms via cw PLDMR.« less

Comparative analysis of magnetic resonance in the polaron pair recombination and the triplet exciton-polaron quenching models

DOE PAGES

Mkhitaryan, V. V.; Danilovic, D.; Hippola, C.; ...

2018-01-03

We present a comparative theoretical study of magnetic resonance within the polaron pair recombination (PPR) and the triplet exciton-polaron quenching (TPQ) models. Both models have been invoked to interpret the photoluminescence detected magnetic resonance (PLDMR) results in π-conjugated materials and devices. We show that resonance line shapes calculated within the two models differ dramatically in several regards. First, in the PPR model, the line shape exhibits unusual behavior upon increasing the microwave power: it evolves from fully positive at weak power to fully negative at strong power. In contrast, in the TPQ model, the PLDMR is completely positive, showing amore » monotonic saturation. Second, the two models predict different dependencies of the resonance signal on the photoexcitation power, PL. At low PL, the resonance amplitude Δ I/I is ∝ PL within the PPR model, while it is ∝ P2L crossing over to P3L within the TPQ model. On the physical level, the differences stem from different underlying spin dynamics. Most prominently, a negative resonance within the PPR model has its origin in the microwave-induced spin-Dicke effect, leading to the resonant quenching of photoluminescence. The spin-Dicke effect results from the spin-selective recombination, leading to a highly correlated precession of the on-resonance pair partners under the strong microwave power. This effect is not relevant for TPQ mechanism, where the strong zero-field splitting renders the majority of triplets off resonance. On the technical level, the analytical evaluation of the line shapes for the two models is enabled by the fact that these shapes can be expressed via the eigenvalues of a complex Hamiltonian. This bypasses the necessity of solving the much larger complex linear system of the stochastic Liouville equations. Lastly, our findings pave the way towards a reliable discrimination between the two mechanisms via cw PLDMR.« less

Comparative analysis of magnetic resonance in the polaron pair recombination and the triplet exciton-polaron quenching models

NASA Astrophysics Data System (ADS)

Mkhitaryan, V. V.; Danilović, D.; Hippola, C.; Raikh, M. E.; Shinar, J.

2018-01-01

We present a comparative theoretical study of magnetic resonance within the polaron pair recombination (PPR) and the triplet exciton-polaron quenching (TPQ) models. Both models have been invoked to interpret the photoluminescence detected magnetic resonance (PLDMR) results in π -conjugated materials and devices. We show that resonance line shapes calculated within the two models differ dramatically in several regards. First, in the PPR model, the line shape exhibits unusual behavior upon increasing the microwave power: it evolves from fully positive at weak power to fully negative at strong power. In contrast, in the TPQ model, the PLDMR is completely positive, showing a monotonic saturation. Second, the two models predict different dependencies of the resonance signal on the photoexcitation power, PL. At low PL, the resonance amplitude Δ I /I is ∝PL within the PPR model, while it is ∝PL2 crossing over to PL3 within the TPQ model. On the physical level, the differences stem from different underlying spin dynamics. Most prominently, a negative resonance within the PPR model has its origin in the microwave-induced spin-Dicke effect, leading to the resonant quenching of photoluminescence. The spin-Dicke effect results from the spin-selective recombination, leading to a highly correlated precession of the on-resonance pair partners under the strong microwave power. This effect is not relevant for TPQ mechanism, where the strong zero-field splitting renders the majority of triplets off resonance. On the technical level, the analytical evaluation of the line shapes for the two models is enabled by the fact that these shapes can be expressed via the eigenvalues of a complex Hamiltonian. This bypasses the necessity of solving the much larger complex linear system of the stochastic Liouville equations. Our findings pave the way towards a reliable discrimination between the two mechanisms via cw PLDMR.

Gyrokinetic predictions of multiscale transport in a DIII-D ITER baseline discharge

DOE PAGES

Holland, C.; Howard, N. T.; Grierson, B. A.

2017-05-08

New multiscale gyrokinetic simulations predict that electron energy transport in a DIII-D ITER baseline discharge with dominant electron heating and low input torque is multiscale in nature, with roughly equal amounts of the electron energy flux Q e coming from long wavelength ion-scale (k yρ s < 1) and short wavelength electron-scale (k yρ s > 1) fluctuations when the gyrokinetic results match independent power balance calculations. Corresponding conventional ion-scale simulations are able to match the power balance ion energy flux Q i, but systematically underpredict Q e when doing so. We observe significant nonlinear cross-scale couplings in the multiscalemore » simulations, but the exact simulation predictions are found to be extremely sensitive to variations of model input parameters within experimental uncertainties. Most notably, depending upon the exact value of the equilibrium E x B shearing rate γ E x B used, either enhancement or suppression of the long-wavelength turbulence and transport levels in the multiscale simulations is observed relative to what is predicted by ion-scale simulations. And while the enhancement of the long wavelength fluctuations by inclusion of the short wavelength turbulence was previously observed in similar multiscale simulations of an Alcator C-Mod L-mode discharge, these new results show for the first time a complete suppression of long-wavelength turbulence in a multiscale simulation, for parameters at which conventional ion-scale simulation predicts small but finite levels of low-k turbulence and transport consistent with the power balance Q i. Though computational resource limitations prevent a fully rigorous validation assessment of these new results, they provide significant new evidence that electron energy transport in burning plasmas is likely to have a strong multiscale character, with significant nonlinear cross-scale couplings that must be fully understood to predict the performance of those plasmas with confidence.« less

Gyrokinetic predictions of multiscale transport in a DIII-D ITER baseline discharge

NASA Astrophysics Data System (ADS)

Holland, C.; Howard, N. T.; Grierson, B. A.

2017-06-01

New multiscale gyrokinetic simulations predict that electron energy transport in a DIII-D ITER baseline discharge with dominant electron heating and low input torque is multiscale in nature, with roughly equal amounts of the electron energy flux Q e coming from long wavelength ion-scale (k y ρ s  <  1) and short wavelength electron-scale (k y ρ s  >  1) fluctuations when the gyrokinetic results match independent power balance calculations. Corresponding conventional ion-scale simulations are able to match the power balance ion energy flux Q i, but systematically underpredict Q e when doing so. Significant nonlinear cross-scale couplings are observed in the multiscale simulations, but the exact simulation predictions are found to be extremely sensitive to variations of model input parameters within experimental uncertainties. Most notably, depending upon the exact value of the equilibrium E  ×  B shearing rate γ E×B used, either enhancement or suppression of the long-wavelength turbulence and transport levels in the multiscale simulations is observed relative to what is predicted by ion-scale simulations. While the enhancement of the long wavelength fluctuations by inclusion of the short wavelength turbulence was previously observed in similar multiscale simulations of an Alcator C-Mod L-mode discharge, these new results show for the first time a complete suppression of long-wavelength turbulence in a multiscale simulation, for parameters at which conventional ion-scale simulation predicts small but finite levels of low-k turbulence and transport consistent with the power balance Q i. Although computational resource limitations prevent a fully rigorous validation assessment of these new results, they provide significant new evidence that electron energy transport in burning plasmas is likely to have a strong multiscale character, with significant nonlinear cross-scale couplings that must be fully understood to predict the performance of those plasmas with confidence.

High frequency sound propagation in a network of interconnecting streets

NASA Astrophysics Data System (ADS)

Hewett, D. P.

2012-12-01

We propose a new model for the propagation of acoustic energy from a time-harmonic point source through a network of interconnecting streets in the high frequency regime, in which the wavelength is small compared to typical macro-lengthscales such as street widths/lengths and building heights. Our model, which is based on geometrical acoustics (ray theory), represents the acoustic power flow from the source along any pathway through the network as the integral of a power density over the launch angle of a ray emanating from the source, and takes into account the key phenomena involved in the propagation, namely energy loss by wall absorption, energy redistribution at junctions, and, in 3D, energy loss to the atmosphere. The model predicts strongly anisotropic decay away from the source, with the power flow decaying exponentially in the number of junctions from the source, except along the axial directions of the network, where the decay is algebraic.

Influences of Atmospheric Stability State on Wind Turbine Aerodynamic Loadings

NASA Astrophysics Data System (ADS)

Vijayakumar, Ganesh; Lavely, Adam; Brasseur, James; Paterson, Eric; Kinzel, Michael

2011-11-01

Wind turbine power and loadings are influenced by the structure of atmospheric turbulence and thus on the stability state of the atmosphere. Statistical differences in loadings with atmospheric stability could impact controls, blade design, etc. Large-eddy simulation (LES) of the neutral and moderately convective atmospheric boundary layer (NBL, MCBL) are used as inflow to the NREL FAST advanced blade-element momentum theory code to predict wind turbine rotor power, sectional lift and drag, blade bending moments and shaft torque. Using horizontal homogeneity, we combine time and ensemble averages to obtain converged statistics equivalent to ``infinite'' time averages over a single turbine. The MCBL required longer effective time periods to obtain converged statistics than the NBL. Variances and correlation coefficients among wind velocities, turbine power and blade loadings were higher in the MCBL than the NBL. We conclude that the stability state of the ABL strongly influences wind turbine performance. Supported by NSF and DOE.

Individual Differences In The Executive Control Of Attention, Memory, And Thought, And Their Associations With Schizotypy

PubMed Central

Kane, Michael J.; Meier, Matt E.; Smeekens, Bridget A.; Gross, Georgina M.; Chun, Charlotte A.; Silvia, Paul J.; Kwapil, Thomas R.

2016-01-01

A large correlational study took a latent-variable approach to the generality of executive control by testing the individual-differences structure of executive-attention capabilities and assessing their prediction of schizotypy, a multidimensional construct (with negative, positive, disorganized, and paranoid factors) conveying risk for schizophrenia. Although schizophrenia is convincingly linked to executive deficits, the schizotypy literature is equivocal. Subjects completed tasks of working memory capacity (WMC), attention restraint (inhibiting prepotent responses), and attention constraint (focusing visual attention amid distractors), the latter two in an effort to fractionate the “inhibition” construct. We also assessed mind-wandering propensity (via in-task thought probes) and coefficient of variation in response times (RT CoV) from several tasks as more novel indices of executive attention. WMC, attention restraint, attention constraint, mind wandering, and RT CoV were correlated but separable constructs, indicating some distinctions among “attention control” abilities; WMC correlated more strongly with attentional restraint than constraint, and mind wandering correlated more strongly with attentional restraint, attentional constraint, and RT CoV than with WMC. Across structural models, no executive construct predicted negative schizotypy and only mind wandering and RT CoV consistently (but modestly) predicted positive, disorganized, and paranoid schizotypy; stalwart executive constructs in the schizophrenia literature — WMC and attention restraint — showed little to no predictive power, beyond restraint’s prediction of paranoia. Either executive deficits are consequences rather than risk factors for schizophrenia, or executive failures barely precede or precipitate diagnosable schizophrenia symptoms. PMID:27454042

Pretest thermal analysis of the Tuff Water Migration/In-Situ Heater Experiment

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

Bulmer, B.M.

This report describes the pretest thermal analysis for the Tuff Water Migration/In-Situ Heater Experiment to be conducted in welded tuff in G-tunnel, Nevada Test Site. The parametric thermal modeling considers variable boiling temperature, tuff thermal conductivity, tuff emissivity, and heater operating power. For nominal tuff properties, some near field boiling is predicted for realistic operating power. However, the extent of boiling will be strongly determined by the ambient (100% water saturated) rock thermal conductivity. In addition, the thermal response of the heater and of the tuff within the dry-out zone (i.e., bounded by boiling isotherm) is dependent on the temperaturemore » variation of rock conductivity as well as the extent of induced boiling.« less

Development of 3D pseudo pin-by-pin calculation methodology in ANC

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

Zhang, B.; Mayhue, L.; Huria, H.

2012-07-01

Advanced cores and fuel assembly designs have been developed to improve operational flexibility, economic performance and further enhance safety features of nuclear power plants. The simulation of these new designs, along with strong heterogeneous fuel loading, have brought new challenges to the reactor physics methodologies currently employed in the industrial codes for core analyses. Control rod insertion during normal operation is one operational feature in the AP1000{sup R} plant of Westinghouse next generation Pressurized Water Reactor (PWR) design. This design improves its operational flexibility and efficiency but significantly challenges the conventional reactor physics methods, especially in pin power calculations. Themore » mixture loading of fuel assemblies with significant neutron spectrums causes a strong interaction between different fuel assembly types that is not fully captured with the current core design codes. To overcome the weaknesses of the conventional methods, Westinghouse has developed a state-of-the-art 3D Pin-by-Pin Calculation Methodology (P3C) and successfully implemented in the Westinghouse core design code ANC. The new methodology has been qualified and licensed for pin power prediction. The 3D P3C methodology along with its application and validation will be discussed in the paper. (authors)« less

Prediction of brain tissue temperature using near-infrared spectroscopy.

PubMed

Holper, Lisa; Mitra, Subhabrata; Bale, Gemma; Robertson, Nicola; Tachtsidis, Ilias

2017-04-01

Broadband near-infrared spectroscopy (NIRS) can provide an endogenous indicator of tissue temperature based on the temperature dependence of the water absorption spectrum. We describe a first evaluation of the calibration and prediction of brain tissue temperature obtained during hypothermia in newborn piglets (animal dataset) and rewarming in newborn infants (human dataset) based on measured body (rectal) temperature. The calibration using partial least squares regression proved to be a reliable method to predict brain tissue temperature with respect to core body temperature in the wavelength interval of 720 to 880 nm with a strong mean predictive power of [Formula: see text] (animal dataset) and [Formula: see text] (human dataset). In addition, we applied regression receiver operating characteristic curves for the first time to evaluate the temperature prediction, which provided an overall mean error bias between NIRS predicted brain temperature and body temperature of [Formula: see text] (animal dataset) and [Formula: see text] (human dataset). We discuss main methodological aspects, particularly the well-known aspect of over- versus underestimation between brain and body temperature, which is relevant for potential clinical applications.

Peer Deviance, Parental Divorce, and Genetic Risk in the Prediction of Drug Abuse in a Nationwide Swedish Sample

PubMed Central

Kendler, Kenneth S.; Ohlsson, Henrik; Sundquist, Kristina; Sundquist, Jan

2014-01-01

IMPORTANCE Peer deviance (PD) strongly predicts externalizing psychopathologic conditions but has not been previously assessable in population cohorts. We sought to develop such an index of PD and to clarify its effects on risk of drug abuse (DA). OBJECTIVES To examine how strongly PD increases the risk of DA and whether this community-level liability indicator interacts with key DA risk factors at the individual and family levels. DESIGN, SETTING, AND PARTICIPANTS Studies of future DA registration in 1 401 698 Swedish probands born from January 1, 1970, through December 31, 1985, and their adolescent peers in approximately 9200 small community areas. Peer deviance was defined as the proportion of individuals born within 5 years of the proband living in the same small community when the proband was 15 years old who eventually were registered for DA. MAIN OUTCOMES AND MEASURES Drug abuse recorded in medical, legal, or pharmacy registry records. RESULTS Peer deviance was associated with future DA in the proband, with rates of DA in older and male peers more strongly predictive than in younger or female peers. The predictive power of PD was only slightly attenuated by adding measures of community deprivation, collective efficacy, or family socioeconomic status. Probands whose parents were divorced were more sensitive to the pathogenic effects of high PD environments. A robust positive interaction was also seen between genetic risk of DA (indexed by rates of DA in first-, second-, and third-degree relatives) and PD exposure. CONCLUSIONS AND RELEVANCE With sufficient data, PD can be measured in populations and strongly predicts DA. In a nationwide sample, risk factors at the level of the individual (genetic vulnerability), family (parental loss), and community (PD) contribute substantially to risk of DA. Individuals at elevated DA risk because of parental divorce or high genetic liability are more sensitive to the pathogenic effects of PD. Although the effect of our PD measure on DA liability cannot be explained by standard measures of community or family risk, we cannot, with available data, discriminate definitively between the effect of true peer effects and other unmeasured risk factors. PMID:24576925

Peer deviance, parental divorce, and genetic risk in the prediction of drug abuse in a nationwide Swedish sample: evidence of environment-environment and gene-environment interaction.

PubMed

Kendler, Kenneth S; Ohlsson, Henrik; Sundquist, Kristina; Sundquist, Jan

2014-04-01

Peer deviance (PD) strongly predicts externalizing psychopathologic conditions but has not been previously assessable in population cohorts. We sought to develop such an index of PD and to clarify its effects on risk of drug abuse (DA). To examine how strongly PD increases the risk of DA and whether this community-level liability indicator interacts with key DA risk factors at the individual and family levels. Studies of future DA registration in 1,401,698 Swedish probands born from January 1, 1970, through December 31, 1985, and their adolescent peers in approximately 9200 small community areas. Peer deviance was defined as the proportion of individuals born within 5 years of the proband living in the same small community when the proband was 15 years old who eventually were registered for DA. Drug abuse recorded in medical, legal, or pharmacy registry records. Peer deviance was associated with future DA in the proband, with rates of DA in older and male peers more strongly predictive than in younger or female peers. The predictive power of PD was only slightly attenuated by adding measures of community deprivation, collective efficacy, or family socioeconomic status. Probands whose parents were divorced were more sensitive to the pathogenic effects of high PD environments. A robust positive interaction was also seen between genetic risk of DA (indexed by rates of DA in first-, second-, and third-degree relatives) and PD exposure. With sufficient data, PD can be measured in populations and strongly predicts DA. In a nationwide sample, risk factors at the level of the individual (genetic vulnerability), family (parental loss), and community (PD) contribute substantially to risk of DA. Individuals at elevated DA risk because of parental divorce or high genetic liability are more sensitive to the pathogenic effects of PD. Although the effect of our PD measure on DA liability cannot be explained by standard measures of community or family risk, we cannot, with available data, discriminate definitively between the effect of true peer effects and other unmeasured risk factors.

Decision forests for learning prostate cancer probability maps from multiparametric MRI

NASA Astrophysics Data System (ADS)

Ehrenberg, Henry R.; Cornfeld, Daniel; Nawaf, Cayce B.; Sprenkle, Preston C.; Duncan, James S.

2016-03-01

Objectives: Advances in multiparametric magnetic resonance imaging (mpMRI) and ultrasound/MRI fusion imaging offer a powerful alternative to the typical undirected approach to diagnosing prostate cancer. However, these methods require the time and expertise needed to interpret mpMRI image scenes. In this paper, a machine learning framework for automatically detecting and localizing cancerous lesions within the prostate is developed and evaluated. Methods: Two studies were performed to gather MRI and pathology data. The 12 patients in the first study underwent an MRI session to obtain structural, diffusion-weighted, and dynamic contrast enhanced image vol- umes of the prostate, and regions suspected of being cancerous from the MRI data were manually contoured by radiologists. Whole-mount slices of the prostate were obtained for the patients in the second study, in addition to structural and diffusion-weighted MRI data, for pathology verification. A 3-D feature set for voxel-wise appear- ance description combining intensity data, textural operators, and zonal approximations was generated. Voxels in a test set were classified as normal or cancer using a decision forest-based model initialized using Gaussian discriminant analysis. A leave-one-patient-out cross-validation scheme was used to assess the predictions against the expert manual segmentations confirmed as cancer by biopsy. Results: We achieved an area under the average receiver-operator characteristic curve of 0.923 for the first study, and visual assessment of the probability maps showed 21 out of 22 tumors were identified while a high level of specificity was maintained. In addition to evaluating the model against related approaches, the effects of the individual MRI parameter types were explored, and pathological verification using whole-mount slices from the second study was performed. Conclusions: The results of this paper show that the combination of mpMRI and machine learning is a powerful tool for quantitatively diagnosing prostate cancer.

Testing the consistency of three-point halo clustering in Fourier and configuration space

NASA Astrophysics Data System (ADS)

Hoffmann, K.; Gaztañaga, E.; Scoccimarro, R.; Crocce, M.

2018-05-01

We compare reduced three-point correlations Q of matter, haloes (as proxies for galaxies) and their cross-correlations, measured in a total simulated volume of ˜100 (h-1 Gpc)3, to predictions from leading order perturbation theory on a large range of scales in configuration space. Predictions for haloes are based on the non-local bias model, employing linear (b1) and non-linear (c2, g2) bias parameters, which have been constrained previously from the bispectrum in Fourier space. We also study predictions from two other bias models, one local (g2 = 0) and one in which c2 and g2 are determined by b1 via approximately universal relations. Overall, measurements and predictions agree when Q is derived for triangles with (r1r2r3)1/3 ≳60 h-1 Mpc, where r1 - 3 are the sizes of the triangle legs. Predictions for Qmatter, based on the linear power spectrum, show significant deviations from the measurements at the BAO scale (given our small measurement errors), which strongly decrease when adding a damping term or using the non-linear power spectrum, as expected. Predictions for Qhalo agree best with measurements at large scales when considering non-local contributions. The universal bias model works well for haloes and might therefore be also useful for tightening constraints on b1 from Q in galaxy surveys. Such constraints are independent of the amplitude of matter density fluctuation (σ8) and hence break the degeneracy between b1 and σ8, present in galaxy two-point correlations.

The prognostic value of the strong ion gap in acute pancreatitis.

PubMed

Shen, Xiao; Ke, Lu; Yang, Dongliang; Sun, Jing; Tong, Zhihui; Li, Baiqiang; Li, Gang; Li, Weiqin; Li, Jieshou; Bellomo, Rinaldo

2016-12-01

In this study, we aimed to evaluate the predictive value of Stewart-derived parameters for the development of severe type of acute pancreatitis (AP) and for AP-related mortality. We studied 186 patients admitted to the hospital with AP. We performed blood gas and biochemical analysis for each patient on admission. We calculated multiple metrics according to the Stewart's acid-base theory and assessed their accuracy as predictors of AP severity and mortality. Of the 186 patients presenting with AP, 85 (45.7%) developed severe AP and 33 (17.7%) died during hospitalization. Patients with severe AP had significantly higher median strong ion gap (SIG) than did patients with mild or moderate AP (7.88 vs 2.11 mEq/L, P< .001). In multivariate logistic regression analysis, SIG had an odds ratio (OR) of 1.56 (P< .001). In addition, SIG had good predictive power for mortality (OR, 1.26; P= .014) as well as acute kidney injury (OR, 1.34; P< .001). In a cohort of patients with AP, SIG was a strong independent predictor of severity and mortality. Besides, SIG might also be an early marker for acute kidney injury in AP patients. Additional research is needed to identify the nature of the unmeasured anions responsible for such findings. Copyright © 2016 Elsevier Inc. All rights reserved.

The Interrelationships of Mathematical Precursors in Kindergarten

PubMed Central

Cirino, Paul T.

2011-01-01

This study evaluated the interrelations among cognitive precursors across quantitative, linguistic, and spatial attention domains that have been implicated for math achievement in young children. The dimensionality of the quantity precursors was evaluated in 286 Kindergarteners via latent variable techniques, and the contribution of precursors from each domain was established for small sums addition. Results showed a five factor structure for the quantity precursors with the major distinction between nonsymbolic and symbolic tasks. The overall model demonstrated good fit, and strong predictive power (R2 = 55%) for addition number combinations. Linguistic and spatial attention domains showed indirect relationships with outcomes, with their effects mediated by symbolic quantity measures. These results have implications for the measurement of mathematical precursors, and yield promise for predicting future math performance. PMID:21194711

A predictive model for the tokamak density limit

DOE PAGES

Teng, Q.; Brennan, D. P.; Delgado-Aparicio, L.; ...

2016-07-28

We reproduce the Greenwald density limit, in all tokamak experiments by using a phenomenologically correct model with parameters in the range of experiments. A simple model of equilibrium evolution and local power balance inside the island has been implemented to calculate the radiation-driven thermo-resistive tearing mode growth and explain the density limit. Strong destabilization of the tearing mode due to an imbalance of local Ohmic heating and radiative cooling in the island predicts the density limit within a few percent. Furthermore, we found the density limit and it is a local edge limit and weakly dependent on impurity densities. Ourmore » results are robust to a substantial variation in model parameters within the range of experiments.« less

The relationship between blood pressure and the structures of Pender's health promotion model in rural hypertensive patients.

PubMed

Kamran, Aziz; Azadbakht, Leila; Sharifirad, Gholamreza; Mahaki, Behzad; Mohebi, Siamak

2015-01-01

Perception is the most important predictor of behavior and there is a strong relation and correlation between behavior and believes. Thus, to improve self-care behaviors of patients, it is required to fully understand their perceptions about behavior. This paper aimed to assess the prediction power of health promotion model of systolic blood pressure (SBP) as the result of self-care behavior in rural hypertensive. This cross-sectional study has been carried out through random multistage sampling on 671 rural patients under the coverage of health center of Ardebil city in 2013. Data were collected through reliable and valid questionnaire based on the health promotion model in eight sectors. For data analysis, Pearson correlation statistical tests, multivariate linear regression, ANOVA and independent t-test were used and for confirmatory factor analysis, SPSS 18 and AMOS 18 (SPSS Inc., Chicago, IL, USA) were used. The results showed significant negative correlation between self-efficacy, perceived benefits, situational influences, affects related to behavior and commitment to action structures with SBP and showed a positive significant correlation between perceived barriers and SBP. Furthermore, age and body mass had direct significant relation with SBP. The age of patients showed inverse significant correlation with self-efficacy, perceived benefits, affects related to behavior, interpersonal influences and commitment and showed a direct significant correlation with perceived barriers, means that by increase of age, the perceived barriers also increased. The structures of health promotion model have in overall the prediction power of 71.4% of SBP changes. The diet perceptions of patients, the same as health promotion model, has good predictive power of SBP, especially the structures of perceived benefits and self-efficacy have inverse meaningful relation with systole blood pressure and predicted a higher percentage of this variable.

Phonon-tunnelling dissipation in mechanical resonators

PubMed Central

Cole, Garrett D.; Wilson-Rae, Ignacio; Werbach, Katharina; Vanner, Michael R.; Aspelmeyer, Markus

2011-01-01

Microscale and nanoscale mechanical resonators have recently emerged as ubiquitous devices for use in advanced technological applications, for example, in mobile communications and inertial sensors, and as novel tools for fundamental scientific endeavours. Their performance is in many cases limited by the deleterious effects of mechanical damping. In this study, we report a significant advancement towards understanding and controlling support-induced losses in generic mechanical resonators. We begin by introducing an efficient numerical solver, based on the 'phonon-tunnelling' approach, capable of predicting the design-limited damping of high-quality mechanical resonators. Further, through careful device engineering, we isolate support-induced losses and perform a rigorous experimental test of the strong geometric dependence of this loss mechanism. Our results are in excellent agreement with the theory, demonstrating the predictive power of our approach. In combination with recent progress on complementary dissipation mechanisms, our phonon-tunnelling solver represents a major step towards accurate prediction of the mechanical quality factor. PMID:21407197

Predicting phonetic transcription agreement: Insights from research in infant vocalizations

PubMed Central

RAMSDELL, HEATHER L.; OLLER, D. KIMBROUGH; ETHINGTON, CORINNA A.

2010-01-01

The purpose of this study is to provide new perspectives on correlates of phonetic transcription agreement. Our research focuses on phonetic transcription and coding of infant vocalizations. The findings are presumed to be broadly applicable to other difficult cases of transcription, such as found in severe disorders of speech, which similarly result in low reliability for a variety of reasons. We evaluated the predictiveness of two factors not previously documented in the literature as influencing transcription agreement: canonicity and coder confidence. Transcribers coded samples of infant vocalizations, judging both canonicity and confidence. Correlation results showed that canonicity and confidence were strongly related to agreement levels, and regression results showed that canonicity and confidence both contributed significantly to explanation of variance. Specifically, the results suggest that canonicity plays a major role in transcription agreement when utterances involve supraglottal articulation, with coder confidence offering additional power in predicting transcription agreement. PMID:17882695

Very-short-term wind power prediction by a hybrid model with single- and multi-step approaches

NASA Astrophysics Data System (ADS)

Mohammed, E.; Wang, S.; Yu, J.

2017-05-01

Very-short-term wind power prediction (VSTWPP) has played an essential role for the operation of electric power systems. This paper aims at improving and applying a hybrid method of VSTWPP based on historical data. The hybrid method is combined by multiple linear regressions and least square (MLR&LS), which is intended for reducing prediction errors. The predicted values are obtained through two sub-processes:1) transform the time-series data of actual wind power into the power ratio, and then predict the power ratio;2) use the predicted power ratio to predict the wind power. Besides, the proposed method can include two prediction approaches: single-step prediction (SSP) and multi-step prediction (MSP). WPP is tested comparatively by auto-regressive moving average (ARMA) model from the predicted values and errors. The validity of the proposed hybrid method is confirmed in terms of error analysis by using probability density function (PDF), mean absolute percent error (MAPE) and means square error (MSE). Meanwhile, comparison of the correlation coefficients between the actual values and the predicted values for different prediction times and window has confirmed that MSP approach by using the hybrid model is the most accurate while comparing to SSP approach and ARMA. The MLR&LS is accurate and promising for solving problems in WPP.

Multiphysics Computational Analysis of a Solid-Core Nuclear Thermal Engine Thrust Chamber

NASA Technical Reports Server (NTRS)

Wang, Ten-See; Canabal, Francisco; Cheng, Gary; Chen, Yen-Sen

2007-01-01

The objective of this effort is to develop an efficient and accurate computational heat transfer methodology to predict thermal, fluid, and hydrogen environments for a hypothetical solid-core, nuclear thermal engine - the Small Engine. In addition, the effects of power profile and hydrogen conversion on heat transfer efficiency and thrust performance were also investigated. The computational methodology is based on an unstructured-grid, pressure-based, all speeds, chemically reacting, computational fluid dynamics platform, while formulations of conjugate heat transfer were implemented to describe the heat transfer from solid to hydrogen inside the solid-core reactor. The computational domain covers the entire thrust chamber so that the afore-mentioned heat transfer effects impact the thrust performance directly. The result shows that the computed core-exit gas temperature, specific impulse, and core pressure drop agree well with those of design data for the Small Engine. Finite-rate chemistry is very important in predicting the proper energy balance as naturally occurring hydrogen decomposition is endothermic. Locally strong hydrogen conversion associated with centralized power profile gives poor heat transfer efficiency and lower thrust performance. On the other hand, uniform hydrogen conversion associated with a more uniform radial power profile achieves higher heat transfer efficiency, and higher thrust performance.

Symbolic racism and Whites' attitudes towards punitive and preventive crime policies.

PubMed

Green, Eva G T; Staerklé, Christian; Sears, David O

2006-08-01

This study analyzes the determinants of Whites' support for punitive and preventive crime policies. It focuses on the predictive power of beliefs about race as described by symbolic racism theory. A dataset with 849 White respondents from three waves of the Los Angeles County Social Survey was used. In order to assess the weight of racial factors in crime policy attitudes, the effects of a range of race-neutral attitude determinants were controlled for, namely individual and structural crime attributions, perceived seriousness of crime, crime victimization, conservatism and news exposure. Results show a strong effect of symbolic racism on both types of crime policies, and in particular on punitive policies. High levels of symbolic racism are associated with support for tough, punitive crime policies and with opposition to preventive policies. Sub-dimensions of symbolic racism qualified these relationships, by showing that internal symbolic racism (assessing perceived individual deficiencies of Blacks) was most strongly predictive of punitiveness, whereas external symbolic racism (denial of institutional discrimination) predicted opposition to structural remedies. On the whole, despite the effects of race-neutral factors, the impact of symbolic racism on policy attitudes was substantial. Thus, White public opinion on both punitive and preventive crime policies is at least partially driven by racial prejudice.

Agility performance in high-level junior basketball players: the predictive value of anthropometrics and power qualities.

PubMed

Sisic, Nedim; Jelicic, Mario; Pehar, Miran; Spasic, Miodrag; Sekulic, Damir

2016-01-01

In basketball, anthropometric status is an important factor when identifying and selecting talents, while agility is one of the most vital motor performances. The aim of this investigation was to evaluate the influence of anthropometric variables and power capacities on different preplanned agility performances. The participants were 92 high-level, junior-age basketball players (16-17 years of age; 187.6±8.72 cm in body height, 78.40±12.26 kg in body mass), randomly divided into a validation and cross-validation subsample. The predictors set consisted of 16 anthropometric variables, three tests of power-capacities (Sargent-jump, broad-jump and medicine-ball-throw) as predictors. The criteria were three tests of agility: a T-Shape-Test; a Zig-Zag-Test, and a test of running with a 180-degree turn (T180). Forward stepwise multiple regressions were calculated for validation subsamples and then cross-validated. Cross validation included correlations between observed and predicted scores, dependent samples t-test between predicted and observed scores; and Bland Altman graphics. Analysis of the variance identified centres being advanced in most of the anthropometric indices, and medicine-ball-throw (all at P<0.05); with no significant between-position-differences for other studied motor performances. Multiple regression models originally calculated for the validation subsample were then cross-validated, and confirmed for Zig-zag-Test (R of 0.71 and 0.72 for the validation and cross-validation subsample, respectively). Anthropometrics were not strongly related to agility performance, but leg length is found to be negatively associated with performance in basketball-specific agility. Power capacities are confirmed to be an important factor in agility. The results highlighted the importance of sport-specific tests when studying pre-planned agility performance in basketball. The improvement in power capacities will probably result in an improvement in agility in basketball athletes, while anthropometric indices should be used in order to identify those athletes who can achieve superior agility performance.

Do scale-invariant fluctuations imply the breaking of de Sitter invariance?

NASA Astrophysics Data System (ADS)

Youssef, A.

2013-01-01

The quantization of the massless minimally coupled (mmc) scalar field in de Sitter spacetime is known to be a non-trivial problem due to the appearance of strong infrared (IR) effects. In particular, the scale-invariance of the CMB power-spectrum - certainly one of the most successful predictions of modern cosmology - is widely believed to be inconsistent with a de Sitter invariant mmc two-point function. Using a Cesaro-summability technique to properly define an otherwise divergent Fourier transform, we show in this Letter that de Sitter symmetry breaking is not a necessary consequence of the scale-invariant fluctuation spectrum. We also generalize our result to the tachyonic scalar fields, i.e. the discrete series of representations of the de Sitter group, that suffer from similar strong IR effects.

Nuclear Fission: from more phenomenology and adjusted parameters to more fundamental theory and increased predictive power

NASA Astrophysics Data System (ADS)

Bulgac, Aurel; Jin, Shi; Magierski, Piotr; Roche, Kenneth; Schunck, Nicolas; Stetcu, Ionel

2017-11-01

Two major recent developments in theory and computational resources created the favorable conditions for achieving a microscopic description of fission dynamics in classically allowed regions of the collective potential energy surface, almost eighty years after its discovery in 1939 by Hahn and Strassmann [1]. The first major development was in theory, the extension of the Time-Dependent Density Functional Theory (TDDFT) [2-5] to superfluid fermion systems [6]. The second development was in computing, the emergence of powerful enough supercomputers capable of solving the complex systems of equations describing the time evolution in three dimensions without any restrictions of hundreds of strongly interacting nucleons. Thus the conditions have been created to renounce phenomenological models and incomplete microscopic treatments with uncontrollable approximations and/or assumptions in the description of the complex dynamics of fission. Even though the available nuclear energy density functionals (NEDFs) are phenomenological still, their accuracy is improving steadily and the prospects of being able to perform calculations of the nuclear fission dynamics and to predict many properties of the fission fragments, otherwise not possible to extract from experiments.

Fourier analysis of blazar variability

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

Finke, Justin D.; Becker, Peter A., E-mail: justin.finke@nrl.navy.mil

Blazars display strong variability on multiple timescales and in multiple radiation bands. Their variability is often characterized by power spectral densities (PSDs) and time lags plotted as functions of the Fourier frequency. We develop a new theoretical model based on the analysis of the electron transport (continuity) equation, carried out in the Fourier domain. The continuity equation includes electron cooling and escape, and a derivation of the emission properties includes light travel time effects associated with a radiating blob in a relativistic jet. The model successfully reproduces the general shapes of the observed PSDs and predicts specific PSD and timemore » lag behaviors associated with variability in the synchrotron, synchrotron self-Compton, and external Compton emission components, from submillimeter to γ-rays. We discuss applications to BL Lacertae objects and to flat-spectrum radio quasars (FSRQs), where there are hints that some of the predicted features have already been observed. We also find that FSRQs should have steeper γ-ray PSD power-law indices than BL Lac objects at Fourier frequencies ≲ 10{sup –4} Hz, in qualitative agreement with previously reported observations by the Fermi Large Area Telescope.« less

Artificial neural network optimization of Althaea rosea seeds polysaccharides and its antioxidant activity.

PubMed

Liu, Feng; Liu, Wenhui; Tian, Shuge

2014-09-01

A combination of an orthogonal L16(4)4 test design and a three-layer artificial neural network (ANN) model was applied to optimize polysaccharides from Althaea rosea seeds extracted by hot water method. The highest optimal experimental yield of A. rosea seed polysaccharides (ARSPs) of 59.85 mg/g was obtained using three extraction numbers, 113 min extraction time, 60.0% ethanol concentration, and 1:41 solid-liquid ratio. Under these optimized conditions, the ARSP experimental yield was very close to the predicted yield of 60.07 mg/g and was higher than the orthogonal test results (40.86 mg/g). Structural characterizations were conducted using physicochemical property and FTIR analysis. In addition, the study of ARSP antioxidant activity demonstrated that polysaccharides exhibited high superoxide dismutase activity, strong reducing power, and positive scavenging activity on superoxide anion, hydroxyl radical, 2,2-diphenyl-1-picrylhydrazyl, and reducing power. Our results indicated that ANNs were efficient quantitative tools for predicting the total ARSP content. Copyright © 2014 Elsevier B.V. All rights reserved.

Quantitative analysis of scale of aeromagnetic data raises questions about geologic-map scale

USGS Publications Warehouse

Nykanen, V.; Raines, G.L.

2006-01-01

A recently published study has shown that small-scale geologic map data can reproduce mineral assessments made with considerably larger scale data. This result contradicts conventional wisdom about the importance of scale in mineral exploration, at least for regional studies. In order to formally investigate aspects of scale, a weights-of-evidence analysis using known gold occurrences and deposits in the Central Lapland Greenstone Belt of Finland as training sites provided a test of the predictive power of the aeromagnetic data. These orogenic-mesothermal-type gold occurrences and deposits have strong lithologic and structural controls associated with long (up to several kilometers), narrow (up to hundreds of meters) hydrothermal alteration zones with associated magnetic lows. The aeromagnetic data were processed using conventional geophysical methods of successive upward continuation simulating terrane clearance or 'flight height' from the original 30 m to an artificial 2000 m. The analyses show, as expected, that the predictive power of aeromagnetic data, as measured by the weights-of-evidence contrast, decreases with increasing flight height. Interestingly, the Moran autocorrelation of aeromagnetic data representing differing flight height, that is spatial scales, decreases with decreasing resolution of source data. The Moran autocorrelation coefficient scems to be another measure of the quality of the aeromagnetic data for predicting exploration targets. ?? Springer Science+Business Media, LLC 2007.

A new model of cavern diameter based on a validated CFD study on stirring of a highly shear-thinning fluid.

PubMed

Story, Anna; Jaworski, Zdzisław

2017-01-01

Results of numerical simulations of momentum transfer for a highly shear-thinning fluid (0.2% Carbopol) in a stirred tank equipped with a Prochem Maxflo T type impeller are presented. The simulation results were validated using LDA data and both tangential and axial force measurements in the laminar and early transitional flow range. A good agreement between the predicted and experimental results of the local fluid velocity components was found. From the predicted and experimental values of both tangential and axial forces, the power number, Po , and thrust number, Th , were also calculated. Values of the absolute relative deviations were below 4.0 and 10.5%, respectively, for Po and Th , which confirms a satisfactory agreement with experiments. An intensive mixing zone, known as cavern, was observed near the impeller. In this zone, the local values of fluid velocity, strain rate, Metzner-Otto coefficient, shear stress and intensity of energy dissipation were all characterized by strong variability. Based on the results of experimental study a new model using non-dimensional impeller force number was proposed to predict the cavern diameter. Comparative numerical simulations were also carried out for a Newtonian fluid (water) and their results were similarly well verified using LDA measurements, as well as experimental power number values.

Using timing of ice retreat to predict timing of fall freeze-up in the Arctic

NASA Astrophysics Data System (ADS)

Stroeve, Julienne C.; Crawford, Alex D.; Stammerjohn, Sharon

2016-06-01

Reliable forecasts of the timing of sea ice advance are needed in order to reduce risks associated with operating in the Arctic as well as planning of human and environmental emergencies. This study investigates the use of a simple statistical model relating the timing of ice retreat to the timing of ice advance, taking advantage of the inherent predictive power supplied by the seasonal ice-albedo feedback and ocean heat uptake. Results show that using the last retreat date to predict the first advance date is applicable in some regions, such as Baffin Bay and the Laptev and East Siberian seas, where a predictive skill is found even after accounting for the long-term trend in both variables. Elsewhere, in the Arctic, there is some predictive skills depending on the year (e.g., Kara and Beaufort seas), but none in regions such as the Barents and Bering seas or the Sea of Okhotsk. While there is some suggestion that the relationship is strengthening over time, this may reflect that higher correlations are expected during periods when the underlying trend is strong.

Variation in aerosol nucleation and growth in coal-fired power plant plumes due to background aerosol, meteorology and emissions: sensitivity analysis and parameterization.

NASA Astrophysics Data System (ADS)

Stevens, R. G.; Lonsdale, C. L.; Brock, C. A.; Reed, M. K.; Crawford, J. H.; Holloway, J. S.; Ryerson, T. B.; Huey, L. G.; Nowak, J. B.; Pierce, J. R.

2012-04-01

New-particle formation in the plumes of coal-fired power plants and other anthropogenic sulphur sources may be an important source of particles in the atmosphere. It remains unclear, however, how best to reproduce this formation in global and regional aerosol models with grid-box lengths that are 10s of kilometres and larger. The predictive power of these models is thus limited by the resultant uncertainties in aerosol size distributions. In this presentation, we focus on sub-grid sulphate aerosol processes within coal-fired power plant plumes: the sub-grid oxidation of SO2 with condensation of H2SO4 onto newly-formed and pre-existing particles. Based on the results of the System for Atmospheric Modelling (SAM), a Large-Eddy Simulation/Cloud-Resolving Model (LES/CRM) with online TwO Moment Aerosol Sectional (TOMAS) microphysics, we develop a computationally efficient, but physically based, parameterization that predicts the characteristics of aerosol formed within coal-fired power plant plumes based on parameters commonly available in global and regional-scale models. Given large-scale mean meteorological parameters, emissions from the power plant, mean background condensation sink, and the desired distance from the source, the parameterization will predict the fraction of the emitted SO2 that is oxidized to H2SO4, the fraction of that H2SO4 that forms new particles instead of condensing onto preexisting particles, the median diameter of the newly-formed particles, and the number of newly-formed particles per kilogram SO2 emitted. We perform a sensitivity analysis of these characteristics of the aerosol size distribution to the meteorological parameters, the condensation sink, and the emissions. In general, new-particle formation and growth is greatly reduced during polluted conditions due to the large preexisting aerosol surface area for H2SO4 condensation and particle coagulation. The new-particle formation and growth rates are also a strong function of the amount of sunlight and NOx since both control OH concentrations. Decreases in NOx emissions without simultaneous decreases in SO2 emissions increase new-particle formation and growth due to increased oxidation of SO2. The parameterization we describe here should allow for more accurate predictions of aerosol size distributions and a greater confidence in the effects of aerosols in climate and health studies.

Finite coupling corrections to holographic predictions for hot QCD

DOE PAGES

Waeber, Sebastian; Schafer, Andreas; Vuorinen, Aleksi; ...

2015-11-13

Finite ’t Hooft coupling corrections to multiple physical observables in strongly coupled N=4 supersymmetric Yang-Mills plasma are examined, in an attempt to assess the stability of the expansion in inverse powers of the ’t Hooft coupling λ. Observables considered include thermodynamic quantities, transport coefficients, and quasinormal mode frequencies. Furthermore large λ expansions for quasinormal mode frequencies are notably less well behaved than the expansions of other quantities, we find that a partial resummation of higher order corrections can significantly reduce the sensitivity of the results to the value of λ.

Measurement of Solar pp-neutrino flux with Borexino: results and implications

NASA Astrophysics Data System (ADS)

Smirnov, O. Yu; Agostini, M.; Appel, S.; Bellini, G.; Benziger, J.; Bick, D.; Bonfini, G.; Bravo, D.; Caccianiga, B.; Calaprice, F.; Caminata, A.; Cavalcante, P.; Chepurnov, A.; D'Angelo, D.; Davini, S.; Derbin, A.; Di Noto, L.; Drachnev, I.; Etenko, A.; Fomenko, K.; Franco, D.; Gabriele, F.; Galbiati, C.; Ghiano, C.; Giammarchi, M.; Goeger-Neff, M.; Goretti, A.; Gromov, M.; Hagner, C.; Hungerford, E.; Ianni, Aldo; Ianni, Andrea; Jedrzejczak, K.; Kaiser, M.; Kobychev, V.; Korablev, D.; Korga, G.; Kryn, D.; Laubenstein, M.; Lehnert, B.; Litvinovich, E.; Lombardi, F.; Lombardi, P.; Ludhova, L.; Lukyanchenko, G.; Machulin, O.; Manecki, S.; Maneschg, W.; Marcocci, S.; Meroni, E.; Meyer, M.; Miramonti, L.; Misiaszek, M.; Montuschi, M.; Mosteiro, P.; Muratova, V.; Neumair, B.; Oberauer, L.; Obolensky, M.; Ortica, F.; Pallavicini, M.; Papp, L.; Perasso, L.; Pocar, A.; Ranucci, G.; Razeto, A.; Re, A.; Romani, A.; Roncin, R.; Rossi, N.; Schönert, S.; Semenov, D.; Simgen, H.; Skorokhvatov, M.; Sotnikov, A.; Sukhotin, S.; Suvorov, Y.; Tartaglia, R.; Testera, G.; Thurn, J.; Toropova, M.; Unzhakov, E.; Vishneva, A.; Vogelaar, R. B.; von Feilitzsch, F.; Wang, H.; Weinz, S.; Winter, J.; Wojcik, M.; Wurm, M.; Yokley, Z.; Zaimidoroga, O.; Zavatarelli, S.; Zuber, K.; Zuzel, G.

2016-02-01

Measurement of the Solar pp-neutrino flux completed the measurement of Solar neutrino fluxes from the pp-chain of reactions in Borexino experiment. The result is in agreement with the prediction of the Standard Solar Model and the MSW/LMA oscillation scenario. A comparison of the total neutrino flux from the Sun with Solar luminosity in photons provides a test of the stability of the Sun on the 105 years time scale, and sets a strong limit on the power production by the unknown energy sources in the Sun.

Shadow image on the retina of a defocused eye

NASA Astrophysics Data System (ADS)

Lenskii, A. V.

1994-04-01

Some visual conditions for transparent objects positioned within and beyond the accommodation limits on the path of the light traveling from a remote source of a small angular size are theoretically considered for the naked eye with a strong ametropia. The resolving power and admissible angular size of the light source are evaluated. The predicted possibility of seeing sufficiently extended transparent gratings at such distances has found that the density of ruling of the grating-object is higher than the ultimate angular resolution of the normal eye.

Individual differences in the executive control of attention, memory, and thought, and their associations with schizotypy.

PubMed

Kane, Michael J; Meier, Matt E; Smeekens, Bridget A; Gross, Georgina M; Chun, Charlotte A; Silvia, Paul J; Kwapil, Thomas R

2016-08-01

A large correlational study took a latent-variable approach to the generality of executive control by testing the individual-differences structure of executive-attention capabilities and assessing their prediction of schizotypy, a multidimensional construct (with negative, positive, disorganized, and paranoid factors) conveying risk for schizophrenia. Although schizophrenia is convincingly linked to executive deficits, the schizotypy literature is equivocal. Subjects completed tasks of working memory capacity (WMC), attention restraint (inhibiting prepotent responses), and attention constraint (focusing visual attention amid distractors), the latter 2 in an effort to fractionate the "inhibition" construct. We also assessed mind-wandering propensity (via in-task thought probes) and coefficient of variation in response times (RT CoV) from several tasks as more novel indices of executive attention. WMC, attention restraint, attention constraint, mind wandering, and RT CoV were correlated but separable constructs, indicating some distinctions among "attention control" abilities; WMC correlated more strongly with attentional restraint than constraint, and mind wandering correlated more strongly with attentional restraint, attentional constraint, and RT CoV than with WMC. Across structural models, no executive construct predicted negative schizotypy and only mind wandering and RT CoV consistently (but modestly) predicted positive, disorganized, and paranoid schizotypy; stalwart executive constructs in the schizophrenia literature-WMC and attention restraint-showed little to no predictive power, beyond restraint's prediction of paranoia. Either executive deficits are consequences rather than risk factors for schizophrenia, or executive failures barely precede or precipitate diagnosable schizophrenia symptoms. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Polycystic ovary syndrome

PubMed Central

Pedersen, Sue D.; Brar, Sony; Faris, Peter; Corenblum, Bernard

2007-01-01

OBJECTIVE To construct and validate a questionnaire for use in diagnosis of polycystic ovary syndrome (PCOS). DESIGN All participants completed a questionnaire, which asked clinical questions designed to assist in the diagnosis of PCOS, before their appointments with an endocrinologist. Following completion of the questionnaire, the endocrinologist (blinded to the answers) made or excluded a diagnosis of PCOS using clinical criteria and biochemical data as indicated. Questions were then evaluated for their power to predict PCOS, and a model was constructed using the most reliable items to establish a system to predict a diagnosis of PCOS. SETTING An outpatient reproductive endocrinology clinic in Calgary, Alta. PARTICIPANTS Adult women patients who had been referred to the clinic. Fifty patients with PCOS and 50 patients without PCOS were included in the study. MAIN OUTCOME MEASURES Demographic information, medical history, related diagnoses, menstrual history, and fertility history. RESULTS A history of infrequent menses, hirsutism, obesity, and acne were strongly predictive of a diagnosis of PCOS, whereas a history of failed pregnancy attempts was not useful. A history of nipple discharge outside of pregnancy strongly predicted no diagnosis of PCOS. We constructed a 4-item questionnaire for use in diagnosis of PCOS; the questionnaire yielded a sensitivity of 85% and a specificity of 85% on multivariate logistic regression and a sensitivity of 77% and a specificity of 94% using the 4-item questionnaire. Predictive accuracy was validated using a second sample of 117 patients, in addition to internal validation using bootstrap analysis. CONCLUSION We have constructed a simple clinical tool to help diagnose PCOS. This questionnaire can be easily incorporated into family physicians’ busy practices. PMID:17872783

The Topology of Large-Scale Structure in the 1.2 Jy IRAS Redshift Survey

NASA Astrophysics Data System (ADS)

Protogeros, Zacharias A. M.; Weinberg, David H.

1997-11-01

We measure the topology (genus) of isodensity contour surfaces in volume-limited subsets of the 1.2 Jy IRAS redshift survey, for smoothing scales λ = 4, 7, and 12 h-1 Mpc. At 12 h-1 Mpc, the observed genus curve has a symmetric form similar to that predicted for a Gaussian random field. At the shorter smoothing lengths, the observed genus curve shows a modest shift in the direction of an isolated cluster or ``meatball'' topology. We use mock catalogs drawn from cosmological N-body simulations to investigate the systematic biases that affect topology measurements in samples of this size and to determine the full covariance matrix of the expected random errors. We incorporate the error correlations into our evaluations of theoretical models, obtaining both frequentist assessments of absolute goodness of fit and Bayesian assessments of models' relative likelihoods. We compare the observed topology of the 1.2 Jy survey to the predictions of dynamically evolved, unbiased, gravitational instability models that have Gaussian initial conditions. The model with an n = -1 power-law initial power spectrum achieves the best overall agreement with the data, though models with a low-density cold dark matter power spectrum and an n = 0 power-law spectrum are also consistent. The observed topology is inconsistent with an initially Gaussian model that has n = -2, and it is strongly inconsistent with a Voronoi foam model, which has a non-Gaussian, bubble topology.

Validation of finite element and boundary element methods for predicting structural vibration and radiated noise

NASA Technical Reports Server (NTRS)

Seybert, A. F.; Wu, X. F.; Oswald, Fred B.

1992-01-01

Analytical and experimental validation of methods to predict structural vibration and radiated noise are presented. A rectangular box excited by a mechanical shaker was used as a vibrating structure. Combined finite element method (FEM) and boundary element method (BEM) models of the apparatus were used to predict the noise radiated from the box. The FEM was used to predict the vibration, and the surface vibration was used as input to the BEM to predict the sound intensity and sound power. Vibration predicted by the FEM model was validated by experimental modal analysis. Noise predicted by the BEM was validated by sound intensity measurements. Three types of results are presented for the total radiated sound power: (1) sound power predicted by the BEM modeling using vibration data measured on the surface of the box; (2) sound power predicted by the FEM/BEM model; and (3) sound power measured by a sound intensity scan. The sound power predicted from the BEM model using measured vibration data yields an excellent prediction of radiated noise. The sound power predicted by the combined FEM/BEM model also gives a good prediction of radiated noise except for a shift of the natural frequencies that are due to limitations in the FEM model.

Univariate Time Series Prediction of Solar Power Using a Hybrid Wavelet-ARMA-NARX Prediction Method

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

Nazaripouya, Hamidreza; Wang, Yubo; Chu, Chi-Cheng

This paper proposes a new hybrid method for super short-term solar power prediction. Solar output power usually has a complex, nonstationary, and nonlinear characteristic due to intermittent and time varying behavior of solar radiance. In addition, solar power dynamics is fast and is inertia less. An accurate super short-time prediction is required to compensate for the fluctuations and reduce the impact of solar power penetration on the power system. The objective is to predict one step-ahead solar power generation based only on historical solar power time series data. The proposed method incorporates discrete wavelet transform (DWT), Auto-Regressive Moving Average (ARMA)more » models, and Recurrent Neural Networks (RNN), while the RNN architecture is based on Nonlinear Auto-Regressive models with eXogenous inputs (NARX). The wavelet transform is utilized to decompose the solar power time series into a set of richer-behaved forming series for prediction. ARMA model is employed as a linear predictor while NARX is used as a nonlinear pattern recognition tool to estimate and compensate the error of wavelet-ARMA prediction. The proposed method is applied to the data captured from UCLA solar PV panels and the results are compared with some of the common and most recent solar power prediction methods. The results validate the effectiveness of the proposed approach and show a considerable improvement in the prediction precision.« less

Tests of Transport Theory and Reduced Impurity Influx with Highly Radiative Plasmas in TFTR

NASA Astrophysics Data System (ADS)

Hill, K. W.

1997-11-01

The electron and ion temperature profiles in beam-heated plasmas were observed to be remarkably invariant when radiative losses were increased significantly through gas puffing of high-Z impurities (argon, krypton, xenon) in the Tokamak Fusion Test Reactor. Without impurity puffing, radiative losses accounted for typically only ~ 25\\char'45 of the input power and the radiation profile was strongly peaked at the plasma edge, where the dominant carbon impurity was not fully stripped. At central electron temperatures, T_eo, of ~ 6 keV, trace concentrations of krypton and xenon (n_z/ne ~ 10-3) generated flat and centrally peaked radiation profiles respectively, and a significant fraction of the input power (45-100\\char'45 ) was lost through radiation. This loss provided a nearly ideal technique for studying local heat transport in tokamaks because it perturbed the net heating profile strongly and in a measureable way, with little effect on the density and the beam deposition profiles. In supershot plasmas, Ti >> T_e, the ion temperature profile remained constant, or even increased modestly, as the radiated power fraction was increased to 75-90\\char'45 with krypton and xenon. This observation is surprising because ion-electron coupling is the dominant power loss term for the ions in the core of supershot plasmas, and the central Ti would have decreased a factor of two if the local ion thermal diffusivity had remained constant at its value without impurity puffing. In L-mode plasmas where ion-electron power coupling is a smaller term in the power balance, the electron temperature during impurity puffing also changed only ~ 10-15\\char'45 even as the net power flow through the electrons was decreased by a factor of ~ 3. The ``stiffness" of the temperature profiles to net input power is supportive of transport mechanisms which have a marginal-stability character. Preliminary comparisons of the temperature changes with predictions of the IFS/PPPL transport model,(M. Kotschenreuther, W. Dorland, M. A. Beer, and G. W. Hammett, Phys. Plasmas 2, 2381 (1995)) which has strong marginal-stability behavior, are reasonable; more detailed comparisons are in progress. Use of high-Z radiators did not impair fusion performance, confirming they can be used to reduce the heat flux to the plasma facing components with minimal ion dilution. At input power level s of 30-33 MW, enhanced radiation through krypton and xenon puffing eliminated serious carbon influx (carbon ``blooms") which occurred in comparable plasmas without impurity puffing.

A Matter of Classes: Stratifying Health Care Populations to Produce Better Estimates of Inpatient Costs

PubMed Central

Rein, David B

2005-01-01

Objective To stratify traditional risk-adjustment models by health severity classes in a way that is empirically based, is accessible to policy makers, and improves predictions of inpatient costs. Data Sources Secondary data created from the administrative claims from all 829,356 children aged 21 years and under enrolled in Georgia Medicaid in 1999. Study Design A finite mixture model was used to assign child Medicaid patients to health severity classes. These class assignments were then used to stratify both portions of a traditional two-part risk-adjustment model predicting inpatient Medicaid expenditures. Traditional model results were compared with the stratified model using actuarial statistics. Principal Findings The finite mixture model identified four classes of children: a majority healthy class and three illness classes with increasing levels of severity. Stratifying the traditional two-part risk-adjustment model by health severity classes improved its R2 from 0.17 to 0.25. The majority of additional predictive power resulted from stratifying the second part of the two-part model. Further, the preference for the stratified model was unaffected by months of patient enrollment time. Conclusions Stratifying health care populations based on measures of health severity is a powerful method to achieve more accurate cost predictions. Insurers who ignore the predictive advances of sample stratification in setting risk-adjusted premiums may create strong financial incentives for adverse selection. Finite mixture models provide an empirically based, replicable methodology for stratification that should be accessible to most health care financial managers. PMID:16033501

A Predictive Model of Intein Insertion Site for Use in the Engineering of Molecular Switches

PubMed Central

Apgar, James; Ross, Mary; Zuo, Xiao; Dohle, Sarah; Sturtevant, Derek; Shen, Binzhang; de la Vega, Humberto; Lessard, Philip; Lazar, Gabor; Raab, R. Michael

2012-01-01

Inteins are intervening protein domains with self-splicing ability that can be used as molecular switches to control activity of their host protein. Successfully engineering an intein into a host protein requires identifying an insertion site that permits intein insertion and splicing while allowing for proper folding of the mature protein post-splicing. By analyzing sequence and structure based properties of native intein insertion sites we have identified four features that showed significant correlation with the location of the intein insertion sites, and therefore may be useful in predicting insertion sites in other proteins that provide native-like intein function. Three of these properties, the distance to the active site and dimer interface site, the SVM score of the splice site cassette, and the sequence conservation of the site showed statistically significant correlation and strong predictive power, with area under the curve (AUC) values of 0.79, 0.76, and 0.73 respectively, while the distance to secondary structure/loop junction showed significance but with less predictive power (AUC of 0.54). In a case study of 20 insertion sites in the XynB xylanase, two features of native insertion sites showed correlation with the splice sites and demonstrated predictive value in selecting non-native splice sites. Structural modeling of intein insertions at two sites highlighted the role that the insertion site location could play on the ability of the intein to modulate activity of the host protein. These findings can be used to enrich the selection of insertion sites capable of supporting intein splicing and hosting an intein switch. PMID:22649521

Precision cosmology with baryons: non-radiative hydrodynamics of galaxy groups

NASA Astrophysics Data System (ADS)

Rabold, Manuel; Teyssier, Romain

2017-05-01

The effect of baryons on the matter power spectrum is likely to have an observable effect for future galaxy surveys, like Euclid or Large Synoptic Survey Telescope (LSST). As a first step towards a fully predictive theory, we investigate the effect of non-radiative hydrodynamics on the structure of galaxy groups sized haloes, which contribute the most to the weak-lensing power spectrum. We perform high-resolution (more than one million particles per halo and one kilo-parsec resolution) non-radiative hydrodynamical zoom-in simulations of a sample of 16 haloes, comparing the profiles to popular analytical models. We find that the total mass profile is well fitted by a Navarro, Frenk & White model, with parameters slightly modified from the dark matter only simulation. We also find that the Komatsu & Seljak hydrostatic solution provides a good fit to the gas profiles, with however significant deviations, arising from strong turbulent mixing in the core and from non-thermal, turbulent pressure support in the outskirts. The turbulent energy follows a shallow, rising linear profile with radius, and correlates with the halo formation time. Using only three main structural halo parameters as variables (total mass, concentration parameter and central gas density), we can predict, with an accuracy better than 20 per cent, the individual gas density and temperature profiles. For the average total mass profile, which is relevant for power spectrum calculations, we even reach an accuracy of 1 per cent. The robustness of these predictions has been tested against resolution effects, different types of initial conditions and hydrodynamical schemes.

Impacts of Extreme Space Weather Events on Power Grid Infrastructure: Physics-Based Modelling of Geomagnetically-Induced Currents (GICs) During Carrington-Class Geomagnetic Storms

NASA Astrophysics Data System (ADS)

Henderson, M. G.; Bent, R.; Chen, Y.; Delzanno, G. L.; Jeffery, C. A.; Jordanova, V. K.; Morley, S.; Rivera, M. K.; Toth, G.; Welling, D. T.; Woodroffe, J. R.; Engel, M.

2017-12-01

Large geomagnetic storms can have devastating effects on power grids. The largest geomagnetic storm ever recorded - called the Carrington Event - occurred in 1859 and produced Geomagnetically Induced Currents (GICs) strong enough to set fires in telegraph offices. It has been estimated that if such a storm occurred today, it would have devastating, long-lasting effects on the North American power transmission infrastructure. Acutely aware of this imminent threat, the North American Electric Reliability Corporation (NERC) was recently instructed to establish requirements for transmission system performance during geomagnetic disturbance (GMD) events and, although the benchmarks adopted were based on the best available data at the time, they suffer from a severely limited physical understanding of the behavior of GMDs and the resulting GICs for strong events. To rectify these deficiencies, we are developing a first-of-its-kind data-informed modelling capability that will provide transformational understanding of the underlying physical mechanisms responsible for the most harmful intense localized GMDs and their impacts on real power transmission networks. This work is being conducted in two separate modes of operation: (1) using historical, well-observed large storm intervals for which robust data-assimilation can be performed, and (2) extending the modelling into a predictive realm in order to assess impacts of poorly and/or never-before observed Carrington-class events. Results of this work are expected to include a potential replacement for the current NERC benchmarking methodology and the development of mitigation strategies in real power grid networks. We report on progress to date and show some preliminary results of modeling large (but not yet extreme) events.

North Anna Nuclear Power Plant Strong Motion Records of the Mineral, Virginia Earthquake of August 23, 2011

NASA Astrophysics Data System (ADS)

Graizer, V.

2012-12-01

The MW 5.8 Mineral, Virginia earthquake was recorded at a relatively short epicentral distance of about 18 km at the North Anna Nuclear Power Plant (NPP) by the SMA-3 magnetic tape digital accelerographs installed inside the plant's containment at the foundation and deck levels. The North Anna NPP is operated by the Virginia Electric and Power Company (VEPCO) and has two pressurized water reactors (PWR) units that began operation in 1978 and 1980, respectively. Following the earthquake, both units were safely shutdown. The strong-motion records were processed to get velocity, displacement, Fourier and 5% damped response spectra. The basemat record demonstrated relatively high amplitudes of acceleration of 0.26 g and velocity of 13.8 cm/sec with a relatively short duration of strong motion of 2-3 sec. Recorded 5% damped Response Spectra exceed Design Basis Earthquake for the existing Units 1 and 2, while comprehensive plant inspections performed by VEPCO and U.S. Nuclear Regulatory Commission have concluded that the damage to the plant was minimal not affecting any structures and equipment significant to plant operation. This can be explained in part by short duration of the earthquake ground motion at the plant. The North Anna NPP did not have free-field strong motion instrumentation at the time of the earthquake. Since the containment is founded on rock there is a tendency to consider basemat record as an approximation of the free-field recording. However, comparisons of deck and basemat records demonstrate that the basemat recording is also affected by structural resonance frequencies higher than 3 Hz. Structural resonances in the frequency range of 3-4 Hz can at least partially explain significant exceedance of observed motions relative to ground motion calculated using ground motion prediction equations.cceleration, velocity and displacement at the North Anna NPP basemat level. Amplitudes of acceleration, velocity and displacement at basemat and deck levels

Optimal Parameter Selection for Support Vector Machine Based on Artificial Bee Colony Algorithm: A Case Study of Grid-Connected PV System Power Prediction.

PubMed

Gao, Xiang-Ming; Yang, Shi-Feng; Pan, San-Bo

2017-01-01

Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD) and support vector machine (SVM) optimized with an artificial bee colony (ABC) algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization.

Optimal Parameter Selection for Support Vector Machine Based on Artificial Bee Colony Algorithm: A Case Study of Grid-Connected PV System Power Prediction

PubMed Central

2017-01-01

Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD) and support vector machine (SVM) optimized with an artificial bee colony (ABC) algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization. PMID:28912803

Caviton dynamics in strong Langmuir turbulence

NASA Astrophysics Data System (ADS)

Dubois, Don; Rose, Harvey A.; Russell, David

Recent studies based on long time computer simulations of Langmuir turbulence as described by Zakharov's model will be reviewed. These show that for strong to moderate ion sound samping the turbulent energy is dominantly in nonlinear caviton excitations which are localized in space and time. A local caviton model will be presented which accounts for the nucleation collapse burnout cycles of individual cavitons as well as their space-time correlations. This model is in detailed agreement with many features of the electron density fluctuation spectra in the ionosphere modified by powerful HF waves as measured by incoherent scatter radar. Recently such observations have verified a prediction of the theory that free Langmuir waves are emitted in the caviton collapse process. These observations and theoretical considerations also strongly imply that cavitons in the heated ionosphere, under certain conditions, evolve to states in which they are ordered in space and time. The sensitivity of the high frequency Langmuir field dynamics to the low frequency ion density fluctuations and the related caviton nucleation process will be discussed.

Caviton dynamics in strong Langmuir turbulence

NASA Astrophysics Data System (ADS)

DuBois, Don; Rose, Harvey A.; Russell, David

1990-01-01

Recent studies based on long time computer simulations of Langmuir turbulence as described by Zakharov's model will be reviewed. These show that for strong to moderate ion sound damping the turbulent energy is dominantly in non-linear "caviton" excitations which are localized in space and time. A local caviton model will be presented which accounts for the nucleation-collapse-burnout cycles of individual cavitons as well as their space-time correlations. This model is in detailed agreement with many features of the electron density fluctuation spectra in the ionosphere modified by powerful HF waves as measured by incoherent scatter radar. Recently such observations have verified a prediction of the theory that "free" Langmuir waves are emitted in the caviton collapse process. These observations and theoretical considerations also strongly imply that cavitons in the heated ionosphere, under certain conditions, evolve to states in which they are ordered in space and time. The sensitivity of the high frequency Langmuir field dynamics to the low frequency ion density fluctuations and the related caviton nucleation process will be discussed.

Universal far-from-equilibrium dynamics of a holographic superconductor.

PubMed

Sonner, Julian; Del Campo, Adolfo; Zurek, Wojciech H

2015-06-23

Symmetry-breaking phase transitions are an example of non-equilibrium processes that require real-time treatment, a major challenge in strongly coupled systems without long-lived quasiparticles. Holographic duality provides such an approach by mapping strongly coupled field theories in D dimensions into weakly coupled quantum gravity in D+1 anti-de Sitter spacetime. Here we use holographic duality to study the formation of topological defects-winding numbers-in the course of a superconducting transition in a strongly coupled theory in a 1D ring. When the system undergoes the transition on a given quench time, the condensate builds up with a delay that can be deduced using the Kibble-Zurek mechanism from the quench time and the universality class of the theory, as determined from the quasinormal mode spectrum of the dual model. Typical winding numbers deposited in the ring exhibit a universal fractional power law dependence on the quench time, also predicted by the Kibble-Zurek Mechanism.

An electromagnetic induced transparency-like scheme for wireless power transfer using dielectric resonators

NASA Astrophysics Data System (ADS)

Elnaggar, Sameh Y.

2017-02-01

Similar to the hybridization of three atoms, three coupled resonators interact to form bonding, anti-bonding, and non-bonding modes. The non-bonding mode enables an electromagnetic induced transparency like transfer of energy. Here, the non-bonding mode, resulting from the strong electric coupling of two dielectric resonators and an enclosure, is exploited to show that it is feasible to transfer power over a distance comparable to the operating wavelength. In this scheme, the enclosure acts as a mediator. The strong coupling permits the excitation of the non-bonding mode with high purity. This approach is different from resonant inductive coupling, which works in the sub-wavelength regime. Optimal loads and the corresponding maximum efficiency are determined using two independent methods: Coupled Mode Theory and Circuit modelling. It is shown that, unlike resonant inductive coupling, the figure of merit depends on the enclosure quality and not on the load, which emphasizes the role of the enclosure as a mediator. Briefly after the input excitation is turned on, the energy in the receiver builds up via all coupled and spurious modes. As time elapses, all modes except the non-bonding cease to sustain. Due to the strong coupling between the dielectrics and the enclosure, such systems have unique properties such as high and uniform efficiency over large distances and minimal fringing fields. These properties suggest that electromagnetic induced transparency like schemes that rely on the use of dielectric resonators can be used to power autonomous systems inside an enclosure or find applications when exposure to the fields needs to be minimal. Finite Element computations are used to verify the theoretical predictions by determining the transfer efficiency, field profile, and coupling coefficients for two different systems. It is shown that the three resonators must be present for efficient power transfer; if one or more are removed, the transfer efficiency reduces significantly.

Predicting writing development in dual language instructional contexts: exploring cross-linguistic relationships.

PubMed

Savage, Robert; Kozakewich, Meagan; Genesee, Fred; Erdos, Caroline; Haigh, Corinne

2017-01-01

This study examined whether decoding and linguistic comprehension abilities, broadly defined by the Simple View of Reading, in grade 1 each uniquely predicted the grade 6 writing performance of English-speaking children (n = 76) who were educated bilingually in both English their first language and French, a second language. Prediction was made from (1) English to English; (2) French to French; and (3) English to French. Results showed that both decoding and linguistic comprehension scores predicted writing accuracy but rarely predicted persuasive writing. Within the linguistic comprehension cluster of tests, Formulating Sentences was a strong consistent within- and between-language predictor of writing accuracy. In practical terms, the present results indicate that early screening for later writing ability using measures of sentence formulation early in students' schooling, in their L1 or L2, can provide greatest predictive power and allow teachers to differentiate instruction in the primary grades. Theoretically, the present results argue that there are correlations between reading-related abilities and writing abilities not only within the same language but also across languages, adding to the growing body of evidence for facilitative cross-linguistic relationships between bilinguals' developing languages. © 2016 John Wiley & Sons Ltd.

Prediction of brain tissue temperature using near-infrared spectroscopy

PubMed Central

Holper, Lisa; Mitra, Subhabrata; Bale, Gemma; Robertson, Nicola; Tachtsidis, Ilias

2017-01-01

Abstract. Broadband near-infrared spectroscopy (NIRS) can provide an endogenous indicator of tissue temperature based on the temperature dependence of the water absorption spectrum. We describe a first evaluation of the calibration and prediction of brain tissue temperature obtained during hypothermia in newborn piglets (animal dataset) and rewarming in newborn infants (human dataset) based on measured body (rectal) temperature. The calibration using partial least squares regression proved to be a reliable method to predict brain tissue temperature with respect to core body temperature in the wavelength interval of 720 to 880 nm with a strong mean predictive power of R2=0.713±0.157 (animal dataset) and R2=0.798±0.087 (human dataset). In addition, we applied regression receiver operating characteristic curves for the first time to evaluate the temperature prediction, which provided an overall mean error bias between NIRS predicted brain temperature and body temperature of 0.436±0.283°C (animal dataset) and 0.162±0.149°C (human dataset). We discuss main methodological aspects, particularly the well-known aspect of over- versus underestimation between brain and body temperature, which is relevant for potential clinical applications. PMID:28630878

Stormtime and Interplanetary Magnetic Field Drivers of Wave and Particle Acceleration Processes in the Magnetosphere-Ionosphere Transition Region

NASA Astrophysics Data System (ADS)

Hatch, Spencer Mark

The magnetosphere-ionosphere (M-I) transition region is the several thousand-kilometer stretch between the cold, dense and variably resistive region of ionized atmospheric gases beginning tens of kilometers above the terrestrial surface, and the hot, tenuous, and conductive plasmas that interface with the solar wind at higher altitudes. The M-I transition region is therefore the site through which magnetospheric conditions, which are strongly susceptible to solar wind dynamics, are communicated to ionospheric plasmas, and vice versa. We systematically study the influence of geomagnetic storms on energy input, electron precipitation, and ion outflow in the M-I transition region, emphasizing the role of inertial Alfven waves both as a preferred mechanism for dynamic (instead of static) energy transfer and particle acceleration, and as a low-altitude manifestation of high-altitude interaction between the solar wind and the magnetosphere, as observed by the FAST satellite. Via superposed epoch analysis and high-latitude distributions derived as a function of storm phase, we show that storm main and recovery phase correspond to strong modulations of measures of Alfvenic activity in the vicinity of the cusp as well as premidnight. We demonstrate that storm main and recovery phases occur during 30% of the four-year period studied, but together account for more than 65% of global Alfvenic energy deposition and electron precipitation, and more than 70% of the coincident ion outflow. We compare observed interplanetary magnetic field (IMF) control of inertial Alfven wave activity with Lyon-Fedder-Mobarry global MHD simulations predicting that southward IMF conditions lead to generation of Alfvenic power in the magnetotail, and that duskward IMF conditions lead to enhanced prenoon Alfvenic power in the Northern Hemisphere. Observed and predicted prenoon Alfvenic power enhancements contrast with direct-entry precipitation, which is instead enhanced postnoon. This situation reverses under dawnward IMF. Despite clear observational and simulated signatures of dayside Alfvenic power, the generation mechanism remains unclear. Last, we present premidnight FAST observations of accelerated precipitation that is best described by a kappa distribution, signaling a nonthermal source population. We examine the implications for the commonly used Knight Relation.

Motivational Incongruence and Well-Being at the Workplace: Person-Job Fit, Job Burnout, and Physical Symptoms.

PubMed

Brandstätter, Veronika; Job, Veronika; Schulze, Beate

2016-01-01

Person-environment fit has been identified as a key prerequisite for employee well-being. We investigated to what extent a misfit between motivational needs and supplies at the workplace affects two key health outcomes: burnout and physical symptoms. Individual needs (implicit affiliation and power motives) and environment supplies (motive specific job characteristics) were assessed in an online survey of full time employees (n = 97), using a picture story exercise measuring implicit motives and a scale listing affiliation and power related job characteristics. Outcomes were assessed using the Maslach Burnout Inventory and a checklist of physical symptoms. We conducted polynomial regressions with response surface analysis. Results reveal that motivational incongruence with respect to the affiliation motive was related to high job burnout, while motivational incongruence concerning the power motive predicted increased physical symptoms. This was true for both those with a strong affiliation or power motive and low corresponding job characteristics and those with a weak affiliation or power motive and job characteristics demanding the respective motive. Results hint at potential interventions toward preventing or remedying a lack of needs-supply fit and reducing the risk of impairments of well-being.

Motivational Incongruence and Well-Being at the Workplace: Person-Job Fit, Job Burnout, and Physical Symptoms

PubMed Central

Brandstätter, Veronika; Job, Veronika; Schulze, Beate

2016-01-01

Person–environment fit has been identified as a key prerequisite for employee well-being. We investigated to what extent a misfit between motivational needs and supplies at the workplace affects two key health outcomes: burnout and physical symptoms. Individual needs (implicit affiliation and power motives) and environment supplies (motive specific job characteristics) were assessed in an online survey of full time employees (n = 97), using a picture story exercise measuring implicit motives and a scale listing affiliation and power related job characteristics. Outcomes were assessed using the Maslach Burnout Inventory and a checklist of physical symptoms. We conducted polynomial regressions with response surface analysis. Results reveal that motivational incongruence with respect to the affiliation motive was related to high job burnout, while motivational incongruence concerning the power motive predicted increased physical symptoms. This was true for both those with a strong affiliation or power motive and low corresponding job characteristics and those with a weak affiliation or power motive and job characteristics demanding the respective motive. Results hint at potential interventions toward preventing or remedying a lack of needs-supply fit and reducing the risk of impairments of well-being. PMID:27570513

Selenide isotope generator for the Galileo mission. SIG/Galileo contract compliance power prediction technique

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

Hammel, T.E.; Srinivas, V.

1978-11-01

This initial definition of the power degradation prediction technique outlines a model for predicting SIG/Galileo mean EOM power using component test data and data from a module power degradation demonstration test program. (LCL)

Quantitative variability of renewable energy resources in Norway

NASA Astrophysics Data System (ADS)

Christakos, Konstantinos; Varlas, George; Cheliotis, Ioannis; Aalstad, Kristoffer; Papadopoulos, Anastasios; Katsafados, Petros; Steeneveld, Gert-Jan

2017-04-01

Based on European Union (EU) targets for 2030, the share of renewable energy (RE) consumption should be increased at 27%. RE resources such as hydropower, wind, wave power and solar power are strongly depending on the chaotic behavior of the weather conditions and climate. Due to this dependency, the prediction of the spatiotemporal variability of the RE resources is more crucial factor than in other energy resources (i.e. carbon based energy). The fluctuation of the RE resources can affect the development of the RE technologies, the energy grid, supply and prices. This study investigates the variability of the potential RE resources in Norway. More specifically, hydropower, wind, wave, and solar power are quantitatively analyzed and correlated with respect to various spatial and temporal scales. In order to analyze the diversities and their interrelationships, reanalysis and observational data of wind, precipitation, wave, and solar radiation are used for a quantitative assessment. The results indicate a high variability of marine RE resources in the North Sea and the Norwegian Sea.

Effect of global warming on willingness to pay for uninterrupted electricity supply in European nations

NASA Astrophysics Data System (ADS)

Cohen, Jed; Moeltner, Klaus; Reichl, Johannes; Schmidthaler, Michael

2018-01-01

Predicted changes in temperature and other weather events may damage the electricity grid and cause power outages. Understanding the costs of power outages and how these costs change over time with global warming can inform outage-mitigation-investment decisions. Here we show that across 19 EU nations the value of uninterrupted electricity supply is strongly related to local temperatures, and will increase as the climate warms. Bayesian hierarchical modelling of data from a choice experiment and respondent-specific temperature measures reveals estimates of willingness to pay (WTP) to avoid an hour of power outage between €0.32 and €1.86 per household. WTP varies on the basis of season and is heterogeneous between European nations. Winter outages currently cause larger per household welfare losses than summer outages per hour of outage. However, this dynamic will begin to shift under plausible future climates, with summer outages becoming substantially more costly and winter outages becoming slightly less costly on a per-household, per-hour basis.

Initial Flight Test Evaluation of the F-15 ACTIVE Axisymmetric Vectoring Nozzle Performance

NASA Technical Reports Server (NTRS)

Orme, John S.; Hathaway, Ross; Ferguson, Michael D.

1998-01-01

A full envelope database of a thrust-vectoring axisymmetric nozzle performance for the Pratt & Whitney Pitch/Yaw Balance Beam Nozzle (P/YBBN) is being developed using the F-15 Advanced Control Technology for Integrated Vehicles (ACTIVE) aircraft. At this time, flight research has been completed for steady-state pitch vector angles up to 20' at an altitude of 30,000 ft from low power settings to maximum afterburner power. The nozzle performance database includes vector forces, internal nozzle pressures, and temperatures all of which can be used for regression analysis modeling. The database was used to substantiate a set of nozzle performance data from wind tunnel testing and computational fluid dynamic analyses. Findings from initial flight research at Mach 0.9 and 1.2 are presented in this paper. The results show that vector efficiency is strongly influenced by power setting. A significant discrepancy in nozzle performance has been discovered between predicted and measured results during vectoring.

The CANDELLE experiment for characterization of neutron sensitivity of LiF TLDs

NASA Astrophysics Data System (ADS)

Guillou, M. Le; Billebaud, A.; Gruel, A.; Kessedjian, G.; Méplan, O.; Destouches, C.; Blaise, P.

2018-01-01

As part of the design studies conducted at CEA for future power and research nuclear reactors, the validation of neutron and photon calculation schemes related to nuclear heating prediction are strongly dependent on the implementation of nuclear heating measurements. Such measurements are usually performed in low-power reactors, whose core dimensions are accurately known and where irradiation conditions (power, flux and temperature) are entirely controlled. Due to the very low operating power of such reactors (of the order of 100 W), nuclear heating is assessed by using dosimetry techniques such as thermoluminescent dosimeters (TLDs). However, although they are highly sensitive to gamma radiation, such dosimeters are also, to a lesser extent, sensitive to neutrons. The neutron dose depends strongly on the TLD composition, typically contributing to 10-30% of the total measured dose in a mixed neutron/gamma field. The experimental determination of the neutron correction appears therefore to be crucial to a better interpretation of doses measured in reactor with reduced uncertainties. A promising approach based on the use of two types of LiF TLDs respectively enriched with lithium-6 and lithium-7, precalibrated both in photon and neutron fields, has been recently developed at INFN (Milan, Italy) for medical purposes. The CANDELLE experiment is dedicated to the implementation of a pure neutron field "calibration" of TLDs by using the GENEPI-2 neutron source of LPSC (Grenoble, France). Those irradiation conditions allowed providing an early assessment of the neutron components of doses measured in EOLE reactor at CEA Cadarache with 10% uncertainty at 1σ.

Suprathermal electrons associated with a plasma discharge on an active sounding rocket experiment

NASA Astrophysics Data System (ADS)

Bale, S. D.; Kellogg, P. J.; Monson, S. J.; Anderson, H. R.; Potter, D. W.

1995-12-01

Electrons with energies up to 600 eV are observed with the retarding potential analyzer (RPA) instrument aboard the Several Compatible Experiments (SCEX) III sounding rocket. The electrons are concomitant with high-energy (2-6 keV) electron gun injections and also evidence themselves by luminosity observed with 3805 Å and 3914 Å photometers. Both the collected electron flux and luminosity measurements are strongly nonlinear with gun injection current. For a typical event, the electron distribution is similar to laboratory beam-plasma discharge (BPD) distributions reported by Sharp (1982) and when backed by HF electric field observations (Goerke et al., 1992; Llobet et al., 1985), the BPD mechanism becomes a most likely explanation. Strong turbulence theories of BPD predict a power law tail in the electron distribution, and we compare our spectral index with some previous observations.

Strong collective attraction in colloidal clusters on a liquid-air interface.

PubMed

Pergamenshchik, V M

2009-01-01

It is shown that in a cluster of many colloids, trapped at a liquid-air interface, the well-known vertical-force-induced pairwise logarithmic attraction changes to a strongly enhanced power-law attraction. In large two-dimensional clusters, the attraction energy scales as the inverse square of the distance between colloids. The enhancement is given by the ratio eta = (square of the capillary length) / (interface surface area per colloid) and can be as large as 10;{5} . This explains why a very small vertical force on colloids, which is too weak to bring two of them together, can stabilize many-body structures on a liquid-air interface. The profile of a cluster is shown to consist of a large slow collective envelope modulated by a fast low-amplitude perturbation due to individual colloids. A closed equation for the slow envelope, which incorporates an arbitrary power-law repulsion between colloids, is derived. For example, this equation is solved for a large circular cluster with the hard-core colloid repulsion. It is suggested that the predicted effect is responsible for mysterious stabilization of colloidal structures observed in experiments on a surface of isotropic liquid and nematic liquid crystal.

Simple, empirical approach to predict neutron capture cross sections from nuclear masses

NASA Astrophysics Data System (ADS)

Couture, A.; Casten, R. F.; Cakirli, R. B.

2017-12-01

Background: Neutron capture cross sections are essential to understanding the astrophysical s and r processes, the modeling of nuclear reactor design and performance, and for a wide variety of nuclear forensics applications. Often, cross sections are needed for nuclei where experimental measurements are difficult. Enormous effort, over many decades, has gone into attempting to develop sophisticated statistical reaction models to predict these cross sections. Such work has met with some success but is often unable to reproduce measured cross sections to better than 40 % , and has limited predictive power, with predictions from different models rapidly differing by an order of magnitude a few nucleons from the last measurement. Purpose: To develop a new approach to predicting neutron capture cross sections over broad ranges of nuclei that accounts for their values where known and which has reliable predictive power with small uncertainties for many nuclei where they are unknown. Methods: Experimental neutron capture cross sections were compared to empirical mass observables in regions of similar structure. Results: We present an extremely simple method, based solely on empirical mass observables, that correlates neutron capture cross sections in the critical energy range from a few keV to a couple hundred keV. We show that regional cross sections are compactly correlated in medium and heavy mass nuclei with the two-neutron separation energy. These correlations are easily amenable to predict unknown cross sections, often converting the usual extrapolations to more reliable interpolations. It almost always reproduces existing data to within 25 % and estimated uncertainties are below about 40 % up to 10 nucleons beyond known data. Conclusions: Neutron capture cross sections display a surprisingly strong connection to the two-neutron separation energy, a nuclear structure property. The simple, empirical correlations uncovered provide model-independent predictions of neutron capture cross sections, extending far from stability, including for nuclei of the highest sensitivity to r -process nucleosynthesis.

Power load prediction based on GM (1,1)

NASA Astrophysics Data System (ADS)

Wu, Di

2017-05-01

Currently, Chinese power load prediction is highly focused; the paper deeply studies grey prediction and applies it to Chinese electricity consumption during the recent 14 years; through after-test test, it obtains grey prediction which has good adaptability to medium and long-term power load.

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.

Dark matter statistics for large galaxy catalogs: power spectra and covariance matrices

NASA Astrophysics Data System (ADS)

Klypin, Anatoly; Prada, Francisco

2018-06-01

Large-scale surveys of galaxies require accurate theoretical predictions of the dark matter clustering for thousands of mock galaxy catalogs. We demonstrate that this goal can be achieve with the new Parallel Particle-Mesh (PM) N-body code GLAM at a very low computational cost. We run ˜22, 000 simulations with ˜2 billion particles that provide ˜1% accuracy of the dark matter power spectra P(k) for wave-numbers up to k ˜ 1hMpc-1. Using this large data-set we study the power spectrum covariance matrix. In contrast to many previous analytical and numerical results, we find that the covariance matrix normalised to the power spectrum C(k, k΄)/P(k)P(k΄) has a complex structure of non-diagonal components: an upturn at small k, followed by a minimum at k ≈ 0.1 - 0.2 hMpc-1, and a maximum at k ≈ 0.5 - 0.6 hMpc-1. The normalised covariance matrix strongly evolves with redshift: C(k, k΄)∝δα(t)P(k)P(k΄), where δ is the linear growth factor and α ≈ 1 - 1.25, which indicates that the covariance matrix depends on cosmological parameters. We also show that waves longer than 1h-1Gpc have very little impact on the power spectrum and covariance matrix. This significantly reduces the computational costs and complexity of theoretical predictions: relatively small volume ˜(1h-1Gpc)3 simulations capture the necessary properties of dark matter clustering statistics. As our results also indicate, achieving ˜1% errors in the covariance matrix for k < 0.50 hMpc-1 requires a resolution better than ɛ ˜ 0.5h-1Mpc.

Interacting dark sector and precision cosmology

NASA Astrophysics Data System (ADS)

Buen-Abad, Manuel A.; Schmaltz, Martin; Lesgourgues, Julien; Brinckmann, Thejs

2018-01-01

We consider a recently proposed model in which dark matter interacts with a thermal background of dark radiation. Dark radiation consists of relativistic degrees of freedom which allow larger values of the expansion rate of the universe today to be consistent with CMB data (H0-problem). Scattering between dark matter and radiation suppresses the matter power spectrum at small scales and can explain the apparent discrepancies between ΛCDM predictions of the matter power spectrum and direct measurements of Large Scale Structure LSS (σ8-problem). We go beyond previous work in two ways: 1. we enlarge the parameter space of our previous model and allow for an arbitrary fraction of the dark matter to be interacting and 2. we update the data sets used in our fits, most importantly we include LSS data with full k-dependence to explore the sensitivity of current data to the shape of the matter power spectrum. We find that LSS data prefer models with overall suppressed matter clustering due to dark matter - dark radiation interactions over ΛCDM at 3–4 σ. However recent weak lensing measurements of the power spectrum are not yet precise enough to clearly distinguish two limits of the model with different predicted shapes for the linear matter power spectrum. In two appendices we give a derivation of the coupled dark matter and dark radiation perturbation equations from the Boltzmann equation in order to clarify a confusion in the recent literature, and we derive analytic approximations to the solutions of the perturbation equations in the two physically interesting limits of all dark matter weakly interacting or a small fraction of dark matter strongly interacting.

Flow visualization studies of VTOL aircraft models during Hover in ground effect

NASA Technical Reports Server (NTRS)

Mourtos, Nikos J.; Couillaud, Stephane; Carter, Dale; Hange, Craig; Wardwell, Doug; Margason, Richard J.

1995-01-01

A flow visualization study of several configurations of a jet-powered vertical takeoff and landing (VTOL) aircraft model during hover in ground effect was conducted. A surface oil flow technique was used to observe the flow patterns on the lower surfaces of the model. There were significant configuration effects. Wing height with respect to fuselage, the presence of an engine inlet duct beside the fuselage, and nozzle pressure ratio are seen to have strong effects on the surface flow angles on the lower surface of the wing. This test was part of a program to improve the methods for predicting the hot gas ingestion (HGI) for jet-powered vertical/short takeoff and landing (V/STOL) aircraft. The tests were performed at the Jet Calibration and Hover Test (JCAHT) Facility at Ames Research Center.

Analysis of general power counting rules in effective field theory

DOE PAGES

Gavela, Belen; Jenkins, Elizabeth E.; Manohar, Aneesh V.; ...

2016-09-02

We derive the general counting rules for a quantum effective field theory (EFT) in d dimensions. The rules are valid for strongly and weakly coupled theories, and they predict that all kinetic energy terms are canonically normalized. They determine the energy dependence of scattering cross sections in the range of validity of the EFT expansion. We show that the size of the cross sections is controlled by the Λ power counting of EFT, not by chiral counting, even for chiral perturbation theory (χPT). The relation between Λ and f is generalized to d dimensions. We show that the naive dimensionalmore » analysis 4π counting is related to ℏ counting. The EFT counting rules are applied to χPT, low-energy weak interactions, Standard Model EFT and the non-trivial case of Higgs EFT.« less

Understanding the prevalence of lifetime abstinence from alcohol: An ecological study.

PubMed

Probst, Charlotte; Manthey, Jakob; Rehm, Jürgen

2017-09-01

The level of alcohol consumption and related burden in a country are strongly impacted by the prevalence of abstinence from alcohol use. The objective of this study was to characterize the association of lifetime abstinence from alcohol use with economic wealth (as measured in the gross domestic product [GDP]) and Muslim religion on a country level. An ecological study was performed using aggregate data of 183 countries for the year 2010. Lifetime abstinence among men and women was predicted using fractional response regression models with the natural logarithm of GDP-PPP (purchasing power parity) and the proportion of Muslim population as predictors. The models were further adjusted by the country's median age and World Health Organization region. Precision of prediction was investigated. Descriptive analyses showed a strong negative association between GDP-PPP and lifetime abstinence in countries without a Muslim majority and a GDP-PPP up to 20,000 international dollars. Regression models confirmed the negative association with GDP-PPP and showed a strong positive association between lifetime abstinence and the proportion of Muslim population. Stratified sensitivity analyses showed that in countries without a Muslim majority only GDP-PPP showed a statistically significant association whereas in Muslim majority countries only the proportion of Muslims was associated with the prevalence of lifetime abstinence. Particularly in countries with a lower GDP and without Muslim majority the prevalence of lifetime abstinence from alcohol use is strongly negatively associated with GDP-PPP. Future research should analyze the accordance in trends of GDP and lifetime abstinence over time. Copyright © 2017 Elsevier B.V. All rights reserved.

Predicting High-Power Performance in Professional Cyclists.

PubMed

Sanders, Dajo; Heijboer, Mathieu; Akubat, Ibrahim; Meijer, Kenneth; Hesselink, Matthijs K

2017-03-01

To assess if short-duration (5 to ~300 s) high-power performance can accurately be predicted using the anaerobic power reserve (APR) model in professional cyclists. Data from 4 professional cyclists from a World Tour cycling team were used. Using the maximal aerobic power, sprint peak power output, and an exponential constant describing the decrement in power over time, a power-duration relationship was established for each participant. To test the predictive accuracy of the model, several all-out field trials of different durations were performed by each cyclist. The power output achieved during the all-out trials was compared with the predicted power output by the APR model. The power output predicted by the model showed very large to nearly perfect correlations to the actual power output obtained during the all-out trials for each cyclist (r = .88 ± .21, .92 ± .17, .95 ± .13, and .97 ± .09). Power output during the all-out trials remained within an average of 6.6% (53 W) of the predicted power output by the model. This preliminary pilot study presents 4 case studies on the applicability of the APR model in professional cyclists using a field-based approach. The decrement in all-out performance during high-intensity exercise seems to conform to a general relationship with a single exponential-decay model describing the decrement in power vs increasing duration. These results are in line with previous studies using the APR model to predict performance during brief all-out trials. Future research should evaluate the APR model with a larger sample size of elite cyclists.

The Evolution of Energetic Scaling across the Vertebrate Tree of Life.

PubMed

Uyeda, Josef C; Pennell, Matthew W; Miller, Eliot T; Maia, Rafael; McClain, Craig R

2017-08-01

Metabolism is the link between ecology and physiology-it dictates the flow of energy through individuals and across trophic levels. Much of the predictive power of metabolic theories of ecology derives from the scaling relationship between organismal size and metabolic rate. There is growing evidence that this scaling relationship is not universal, but we have little knowledge of how it has evolved over macroevolutionary time. Here we develop a novel phylogenetic comparative method to investigate how often and in which clades the macroevolutionary dynamics of the metabolic scaling have changed. We find strong evidence that the metabolic scaling relationship has shifted multiple times across the vertebrate phylogeny. However, shifts are rare and otherwise strongly constrained. Importantly, both the estimated slope and intercept values vary widely across regimes, with slopes that spanned across theoretically predicted values such as 2/3 or 3/4. We further tested whether traits such as ecto-/endothermy, genome size, and quadratic curvature with body mass (i.e., energetic constraints at extreme body sizes) could explain the observed pattern of shifts. Though these factors help explain some of the variation in scaling parameters, much of the remaining variation remains elusive. Our results lay the groundwork for further exploration of the evolutionary and ecological drivers of major transitions in metabolic strategy and for harnessing this information to improve macroecological predictions.

Integration of biological data by kernels on graph nodes allows prediction of new genes involved in mitotic chromosome condensation

PubMed Central

Hériché, Jean-Karim; Lees, Jon G.; Morilla, Ian; Walter, Thomas; Petrova, Boryana; Roberti, M. Julia; Hossain, M. Julius; Adler, Priit; Fernández, José M.; Krallinger, Martin; Haering, Christian H.; Vilo, Jaak; Valencia, Alfonso; Ranea, Juan A.; Orengo, Christine; Ellenberg, Jan

2014-01-01

The advent of genome-wide RNA interference (RNAi)–based screens puts us in the position to identify genes for all functions human cells carry out. However, for many functions, assay complexity and cost make genome-scale knockdown experiments impossible. Methods to predict genes required for cell functions are therefore needed to focus RNAi screens from the whole genome on the most likely candidates. Although different bioinformatics tools for gene function prediction exist, they lack experimental validation and are therefore rarely used by experimentalists. To address this, we developed an effective computational gene selection strategy that represents public data about genes as graphs and then analyzes these graphs using kernels on graph nodes to predict functional relationships. To demonstrate its performance, we predicted human genes required for a poorly understood cellular function—mitotic chromosome condensation—and experimentally validated the top 100 candidates with a focused RNAi screen by automated microscopy. Quantitative analysis of the images demonstrated that the candidates were indeed strongly enriched in condensation genes, including the discovery of several new factors. By combining bioinformatics prediction with experimental validation, our study shows that kernels on graph nodes are powerful tools to integrate public biological data and predict genes involved in cellular functions of interest. PMID:24943848

Length of stay of stroke rehabilitation inpatients: prediction through the functional independence measure.

PubMed

Franchignoni, F; Tesio, L; Martino, M T; Benevolo, E; Castagna, M

1998-01-01

A model for prediction of length of stay (LOS, in days) of stroke rehabilitation inpatients was developed, based on patients' age (years) and function at admission (scored on the Functional Independence Measure, FIMSM). One hundred and twenty-nine cases, consecutively admitted to three free-standing rehabilitation centres in Italy, were analyzed. A multiple linear regression using forward stepwise selection procedure was adopted. Median admission and discharge scores were: 57 and 75 for the total FIM score, 29 and 48 for the 13-item motor FIM subscore, 29 and 30 for the 5-item cognitive FIM subscore (potential range: 18-126, 13-91, 5-35, respectively). Median LOS was 44 days (interquartile range 30-62). The logLOS predictive model included three FIM items ("toilet transfer", TTr; "social interaction"; "expression") and patient's age (R2 = 0.48). TTr alone explained 31.3% of the variance of logLOS. These results are consistent with previous American studies, showing that FIM scores at admission are strong predictors of patients' LOS, with the transfer items having the greatest predictive power.

FTIR-PAS: a powerful tool for characterising the chemical composition and predicting the labile C fraction of various organic waste products.

PubMed

Bekiaris, Georgios; Bruun, Sander; Peltre, Clément; Houot, Sabine; Jensen, Lars S

2015-05-01

Fourier transform infrared (FT-IR) spectroscopy has been used for several years as a fast, low-cost, reliable technique for characterising a large variety of materials. However, the strong influence of sample particle size and the inability to measure the absorption of very dark and opaque samples have made FTIR unsuitable for many waste materials. FTIR-photoacoustic spectroscopy (FTIR-PAS) can eliminate some of the shortcomings of traditional FTIR caused by scattering effects and reflection issues, and recent advances in PAS technology have made commercial instruments available. In this study, FTIR-PAS was used to characterise a wide range of organic waste products and predict their labile carbon fraction, which is normally determined from time-consuming assays. FTIR-PAS was found to be capable of predicting the labile fraction of carbon as efficiently as near infrared spectroscopy (NIR) and furthermore of identifying the compounds that are correlated with the predicted parameter, thus facilitating a more mechanistic interpretation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Conformations of organophosphine oxides

DOE PAGES

De Silva, Nuwan; Zahariev, Federico; Hay, Benjamin P.; ...

2015-07-17

The conformations of a series of organophosphine oxides, OP(CH 3) 2R, where R = methyl, ethyl, isopropyl, tert-butyl, vinyl, and phenyl, are predicted using the MP2/cc-pVTZ level of theory. Comparison of potential energy surfaces for rotation about P–C bonds with crystal structure data reveals a strong correlation between predicted location and energetics of minima and histograms of dihedral angle distributions observed in the solid state. In addition, the most stable conformers are those that minimize the extent of steric repulsion between adjacent rotor substituents, and the torsional barriers tend to increase with the steric bulk of the rotating alkyl group.more » MM3 force field parameters were adjusted to fit the MP2 results, providing a fast and accurate model for predicting organophosphine oxides shapes—an essential part of understanding the chemistry of these compounds. As a result, the predictive power of the modified MM3 model was tested against MP2/cc-pVTZ conformations for triethylphosphine oxide, OP(CH 2CH 3) 3, and triphenylphosphine oxide, OP(Ph) 3.« less

Psychopathy and criminal violence: the moderating effect of ethnicity.

PubMed

Walsh, Zach

2013-10-01

This study aimed to determine the cross-ethnic stability of the predictive relationship of psychopathy for violence. Participants were 424 adult male jail inmates. Psychopathy was assessed using the Psychopathy Checklist-Revised and criminal violence was assessed using a comprehensive database of arrests for violent crimes. Ethnic categories included the groups that make up the vast majority of U.S. inmates: European American (EA, n = 166), African American (AA, n = 174), and Latino American (LA, n = 84). Ethnically aggregated Cox regression survival analyses identified predictive effects for psychopathy. Disaggregated analyses identified ethnic differences: Psychopathy was more strongly predictive of violence among EA (R² = .13, 95% CI [.04, .22], p < .01) relative to AA inmates (R² = .05, 95% CI [.00, .11], p < .01) and was not related to violence among LA participants (R² = .02, 95% CI [.00, .08], p = .22). Receiver operating characteristic curve analyses yielded an equivalent pattern of results. These findings add to a growing literature suggesting cross-ethnic variability in the predictive power of psychopathy for violence. PsycINFO Database Record (c) 2013 APA, all rights reserved

Examination of the Mild Brain Injury Atypical Symptom Scale and the Validity-10 Scale to detect symptom exaggeration in US military service members.

PubMed

Lange, Rael T; Brickell, Tracey A; French, Louis M

2015-01-01

The purpose of this study was to examine the clinical utility of two validity scales designed for use with the Neurobehavioral Symptom Inventory (NSI) and the PTSD Checklist-Civilian Version (PCL-C); the Mild Brain Injury Atypical Symptoms Scale (mBIAS) and Validity-10 scale. Participants were 63 U.S. military service members (age: M = 31.9 years, SD = 12.5; 90.5% male) who sustained a mild traumatic brain injury (MTBI) and were prospectively enrolled from Walter Reed National Military Medical Center. Participants were divided into two groups based on the validity scales of the Minnesota Multiphasic Personality Inventory-2 Restructured Form (MMPI-2-RF): (a) symptom validity test (SVT)-Fail (n = 24) and (b) SVT-Pass (n = 39). Participants were evaluated on average 19.4 months postinjury (SD = 27.6). Participants in the SVT-Fail group had significantly higher scores (p < .05) on the mBIAS (d = 0.85), Validity-10 (d = 1.89), NSI (d = 2.23), and PCL-C (d = 2.47), and the vast majority of the MMPI-2-RF scales (d = 0.69 to d = 2.47). Sensitivity, specificity, and predictive power values were calculated across the range of mBIAS and Validity-10 scores to determine the optimal cutoff to detect symptom exaggeration. For the mBIAS, a cutoff score of ≥8 was considered optimal, which resulted in low sensitivity (.17), high specificity (1.0), high positive predictive power (1.0), and moderate negative predictive power (.69). For the Validity-10 scale, a cutoff score of ≥13 was considered optimal, which resulted in moderate-high sensitivity (.63), high specificity (.97), and high positive (.93) and negative predictive power (.83). These findings provide strong support for the use of the Validity-10 as a tool to screen for symptom exaggeration when administering the NSI and PCL-C. The mBIAS, however, was not a reliable tool for this purpose and failed to identify the vast majority of people who exaggerated symptoms.

Stochastic Short-term High-resolution Prediction of Solar Irradiance and Photovoltaic Power Output

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

Melin, Alexander M.; Olama, Mohammed M.; Dong, Jin

The increased penetration of solar photovoltaic (PV) energy sources into electric grids has increased the need for accurate modeling and prediction of solar irradiance and power production. Existing modeling and prediction techniques focus on long-term low-resolution prediction over minutes to years. This paper examines the stochastic modeling and short-term high-resolution prediction of solar irradiance and PV power output. We propose a stochastic state-space model to characterize the behaviors of solar irradiance and PV power output. This prediction model is suitable for the development of optimal power controllers for PV sources. A filter-based expectation-maximization and Kalman filtering mechanism is employed tomore » estimate the parameters and states in the state-space model. The mechanism results in a finite dimensional filter which only uses the first and second order statistics. The structure of the scheme contributes to a direct prediction of the solar irradiance and PV power output without any linearization process or simplifying assumptions of the signal’s model. This enables the system to accurately predict small as well as large fluctuations of the solar signals. The mechanism is recursive allowing the solar irradiance and PV power to be predicted online from measurements. The mechanism is tested using solar irradiance and PV power measurement data collected locally in our lab.« less

Two Years and Five Images of Supernova Refsdal

NASA Astrophysics Data System (ADS)

Kelly, Patrick

2017-01-01

In 1964, Sjur Refsdal hypothesized that a supernova (SN) whose light takes multiple paths to reach us around a strong gravitational lens could be used as a highly powerful probe. For such a system, the time delays between the images of the SN should depend sensitively on the cosmic expansion rate and the distribution of matter within the lens. I will present observations of the first strongly lensed SN resolved into multiple images, which was found in near-infrared imaging taken in early November 2014 with the Hubble Space Telescope (HST). SN `Refsdal' appeared in an Einstein cross configuration around an early-type galaxy in the MACS J1149.6+2223 cluster (z=0.54), and its light curve and spectrum are broadly similar to those of the peculiar and well-studied SN 1987A. Models of the cluster potential predicted that the SN would reappear within two years in a different image of its spiral host galaxy (z=1.49) closer to the cluster's center. In early December 2015, we detected the new image of the SN with the HST, and we anticipate being able to measure its relative time delay with a 1-2% precision, providing a rare test of blind model predictions.

Connections between the tropical Pacific Ocean, Arctic sea ice, and anomalous northeastern Pacific ridging

NASA Astrophysics Data System (ADS)

Swain, D. L.; Singh, D.; Horton, D. E.; Mankin, J. S.; Ballard, T.; Thomas, L. N.; Diffenbaugh, N. S.

2016-12-01

The ongoing and severe drought in California is linked to the multi-year persistence of anomalously strong ridging along the west coast of North America, which has deflected the Pacific storm track north of its climatological mean position. Recent work has shown that that highly amplified and strongly meridional atmospheric flow patterns in this region similar to the "Ridiculously Resilient Ridge" have become more common in recent decades. Previous investigations have suggested multiple possible contributors to this conspicuous atmospheric anomaly—including remote teleconnections to unusual tropical Pacific Ocean warmth and/or reduced Arctic sea ice, internal (natural) atmospheric variability, and anthropogenic forcing due to greenhouse gas emissions. Here, we explore observed relationships between mid-tropospheric atmospheric structure in this region and five hypothesized surface forcings: sea ice extent in the (1) Barents/Kara and (2) Beaufort/Chukchi regions, and sea surface temperatures in the (3) extratropical northeastern Pacific Ocean, (4) western tropical Pacific Ocean, and (5) eastern tropical Pacific Ocean. Using a predictive model based upon these observed relationships, we also investigate whether the failure of the powerful 2015-2016 El Niño event to bring above-average precipitation to California could have been predicted based upon these teleconnections.

Thermal Infrared Anomalies of Several Strong Earthquakes

PubMed Central

Wei, Congxin; Guo, Xiao; Qin, Manzhong

2013-01-01

In the history of earthquake thermal infrared research, it is undeniable that before and after strong earthquakes there are significant thermal infrared anomalies which have been interpreted as preseismic precursor in earthquake prediction and forecasting. In this paper, we studied the characteristics of thermal radiation observed before and after the 8 great earthquakes with magnitude up to Ms7.0 by using the satellite infrared remote sensing information. We used new types of data and method to extract the useful anomaly information. Based on the analyses of 8 earthquakes, we got the results as follows. (1) There are significant thermal radiation anomalies before and after earthquakes for all cases. The overall performance of anomalies includes two main stages: expanding first and narrowing later. We easily extracted and identified such seismic anomalies by method of “time-frequency relative power spectrum.” (2) There exist evident and different characteristic periods and magnitudes of thermal abnormal radiation for each case. (3) Thermal radiation anomalies are closely related to the geological structure. (4) Thermal radiation has obvious characteristics in abnormal duration, range, and morphology. In summary, we should be sure that earthquake thermal infrared anomalies as useful earthquake precursor can be used in earthquake prediction and forecasting. PMID:24222728

Thermal infrared anomalies of several strong earthquakes.

PubMed

Wei, Congxin; Zhang, Yuansheng; Guo, Xiao; Hui, Shaoxing; Qin, Manzhong; Zhang, Ying

2013-01-01

In the history of earthquake thermal infrared research, it is undeniable that before and after strong earthquakes there are significant thermal infrared anomalies which have been interpreted as preseismic precursor in earthquake prediction and forecasting. In this paper, we studied the characteristics of thermal radiation observed before and after the 8 great earthquakes with magnitude up to Ms7.0 by using the satellite infrared remote sensing information. We used new types of data and method to extract the useful anomaly information. Based on the analyses of 8 earthquakes, we got the results as follows. (1) There are significant thermal radiation anomalies before and after earthquakes for all cases. The overall performance of anomalies includes two main stages: expanding first and narrowing later. We easily extracted and identified such seismic anomalies by method of "time-frequency relative power spectrum." (2) There exist evident and different characteristic periods and magnitudes of thermal abnormal radiation for each case. (3) Thermal radiation anomalies are closely related to the geological structure. (4) Thermal radiation has obvious characteristics in abnormal duration, range, and morphology. In summary, we should be sure that earthquake thermal infrared anomalies as useful earthquake precursor can be used in earthquake prediction and forecasting.

In situ genetic association for serotiny, a fire-related trait, in Mediterranean maritime pine (Pinus pinaster).

PubMed

Budde, Katharina B; Heuertz, Myriam; Hernández-Serrano, Ana; Pausas, Juli G; Vendramin, Giovanni G; Verdú, Miguel; González-Martínez, Santiago C

2014-01-01

Wildfire is a major ecological driver of plant evolution. Understanding the genetic basis of plant adaptation to wildfire is crucial, because impending climate change will involve fire regime changes worldwide. We studied the molecular genetic basis of serotiny, a fire-related trait, in Mediterranean maritime pine using association genetics. A single nucleotide polymorphism (SNP) set was used to identify genotype : phenotype associations in situ in an unstructured natural population of maritime pine (eastern Iberian Peninsula) under a mixed-effects model framework. RR-BLUP was used to build predictive models for serotiny in this region. Model prediction power outside the focal region was tested using independent range-wide serotiny data. Seventeen SNPs were potentially associated with serotiny, explaining approximately 29% of the trait phenotypic variation in the eastern Iberian Peninsula. Similar prediction power was found for nearby geographical regions from the same maternal lineage, but not for other genetic lineages. Association genetics for ecologically relevant traits evaluated in situ is an attractive approach for forest trees provided that traits are under strong genetic control and populations are unstructured, with large phenotypic variability. This will help to extend the research focus to ecological keystone non-model species in their natural environments, where polymorphisms acquired their adaptive value. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

Role of maternal health and infant inflammation in nutritional and neurodevelopmental outcomes of two-year-old Bangladeshi children.

PubMed

Donowitz, Jeffrey R; Cook, Heather; Alam, Masud; Tofail, Fahmida; Kabir, Mamun; Colgate, E Ross; Carmolli, Marya P; Kirkpatrick, Beth D; Nelson, Charles A; Ma, Jennie Z; Haque, Rashidul; Petri, William A

2018-05-01

Previous studies have shown maternal, inflammatory, and socioeconomic variables to be associated with growth and neurodevelopment in children from low-income countries. However, these outcomes are multifactorial and work describing which predictors most strongly influence them is lacking. We conducted a longitudinal study of Bangladeshi children from birth to two years to assess oral vaccine efficacy. Variables pertaining to maternal and perinatal health, socioeconomic status, early childhood enteric and systemic inflammation, and anthropometry were collected. Bayley-III neurodevelopmental assessment was conducted at two years. As a secondary analysis, we employed hierarchical cluster and random forests techniques to identify and rank which variables predicted growth and neurodevelopment. Cluster analysis demonstrated three distinct groups of predictors. Mother's weight and length-for-age Z score (LAZ) at enrollment were the strongest predictors of LAZ at two years. Cognitive score on Bayley-III was strongly predicted by weight-for-age (WAZ) at enrollment, income, and LAZ at enrollment. Top predictors of language included Rotavirus vaccination, plasma IL 5, sCD14, TNFα, mother's weight, and male gender. Motor function was best predicted by fecal calprotectin, WAZ at enrollment, fecal neopterin, and plasma CRP index. The strongest predictors for social-emotional score included plasma sCD14, income, WAZ at enrollment, and LAZ at enrollment. Based on the random forests' predictions, the estimated percentage of variation explained was 35.4% for LAZ at two years, 34.3% for ΔLAZ, 42.7% for cognitive score, 28.1% for language, 40.8% for motor, and 37.9% for social-emotional score. Birth anthropometry and maternal weight were strong predictors of growth while enteric and systemic inflammation had stronger associations with neurodevelopment. Birth anthropometry was a powerful predictor for all outcomes. These data suggest that further study of stunting in low-income settings should include variables relating to maternal and prenatal health, while investigations focusing on neurodevelopmental outcomes should additionally target causes of systemic and enteric inflammation.

Hierarchical Status Predicts Behavioral Vulnerability and Nucleus Accumbens Metabolic Profile Following Chronic Social Defeat Stress.

PubMed

Larrieu, Thomas; Cherix, Antoine; Duque, Aranzazu; Rodrigues, João; Lei, Hongxia; Gruetter, Rolf; Sandi, Carmen

2017-07-24

Extensive data highlight the existence of major differences in individuals' susceptibility to stress [1-4]. While genetic factors [5, 6] and exposure to early life stress [7, 8] are key components for such neurobehavioral diversity, intriguing observations revealed individual differences in response to stress in inbred mice [9-12]. This raised the possibility that other factors might be critical in stress vulnerability. A key challenge in the field is to identify non-invasively risk factors for vulnerability to stress. Here, we investigated whether behavioral factors, emerging from preexisting dominance hierarchies, could predict vulnerability to chronic stress [9, 13-16]. We applied a chronic social defeat stress (CSDS) model of depression in C57BL/6J mice to investigate the predictive power of hierarchical status to pinpoint which individuals will exhibit susceptibility to CSDS. Given that the high social status of dominant mice would be the one particularly challenged by CSDS, we predicted and found that dominant individuals were the ones showing a strong susceptibility profile as indicated by strong social avoidance following CSDS, while subordinate mice were not affected. Data from 1 H-NMR spectroscopy revealed that the metabolic profile in the nucleus accumbens (NAc) relates to social status and vulnerability to stress. Under basal conditions, subordinates show lower levels of energy-related metabolites compared to dominants. In subordinates, but not dominants, levels of these metabolites were increased after exposure to CSDS. To the best of our knowledge, this is the first study that identifies non-invasively the origin of behavioral risk factors predictive of stress-induced depression-like behaviors associated with metabolic changes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Compton-Scattering Cross Section on the Proton at High Momentum Transfer

NASA Astrophysics Data System (ADS)

Danagoulian, A.; Mamyan, V. H.; Roedelbronn, M.; Aniol, K. A.; Annand, J. R. M.; Bertin, P. Y.; Bimbot, L.; Bosted, P.; Calarco, J. R.; Camsonne, A.; Chang, C. C.; Chang, T.-H.; Chen, J.-P.; Choi, Seonho; Chudakov, E.; Degtyarenko, P.; de Jager, C. W.; Deur, A.; Dutta, D.; Egiyan, K.; Gao, H.; Garibaldi, F.; Gayou, O.; Gilman, R.; Glamazdin, A.; Glashausser, C.; Gomez, J.; Hamilton, D. J.; Hansen, J.-O.; Hayes, D.; Higinbotham, D. W.; Hinton, W.; Horn, T.; Howell, C.; Hunyady, T.; Hyde, C. E.; Jiang, X.; Jones, M. K.; Khandaker, M.; Ketikyan, A.; Kubarovsky, V.; Kramer, K.; Kumbartzki, G.; Laveissière, G.; Lerose, J.; Lindgren, R. A.; Margaziotis, D. J.; Markowitz, P.; McCormick, K.; Meekins, D. G.; Meziani, Z.-E.; Michaels, R.; Moussiegt, P.; Nanda, S.; Nathan, A. M.; Nikolenko, D. M.; Nelyubin, V.; Norum, B. E.; Paschke, K.; Pentchev, L.; Perdrisat, C. F.; Piasetzky, E.; Pomatsalyuk, R.; Punjabi, V. A.; Rachek, I.; Radyushkin, A.; Reitz, B.; Roche, R.; Ron, G.; Sabatié, F.; Saha, A.; Savvinov, N.; Shahinyan, A.; Shestakov, Y.; Širca, S.; Slifer, K.; Solvignon, P.; Stoler, P.; Tajima, S.; Sulkosky, V.; Todor, L.; Vlahovic, B.; Weinstein, L. B.; Wang, K.; Wojtsekhowski, B.; Voskanyan, H.; Xiang, H.; Zheng, X.; Zhu, L.

2007-04-01

Cross-section values for Compton scattering on the proton were measured at 25 kinematic settings over the range s=5 11 and -t=2 7GeV2 with a statistical accuracy of a few percent. The scaling power for the s dependence of the cross section at fixed center-of-mass angle was found to be 8.0±0.2, strongly inconsistent with the prediction of perturbative QCD. The observed cross-section values are in fair agreement with the calculations using the handbag mechanism, in which the external photons couple to a single quark.

Innovation network

PubMed Central

Acemoglu, Daron; Akcigit, Ufuk; Kerr, William R.

2016-01-01

Technological progress builds upon itself, with the expansion of invention in one domain propelling future work in linked fields. Our analysis uses 1.8 million US patents and their citation properties to map the innovation network and its strength. Past innovation network structures are calculated using citation patterns across technology classes during 1975–1994. The interaction of this preexisting network structure with patent growth in upstream technology fields has strong predictive power on future innovation after 1995. This pattern is consistent with the idea that when there is more past upstream innovation for a particular technology class to build on, then that technology class innovates more. PMID:27681628

Mobile impurities in ferromagnetic liquids

NASA Astrophysics Data System (ADS)

Kantian, Adrian; Schollwoeck, Ulrich; Giamarchi, Thierry

2011-03-01

Recent work has shown that mobile impurities in one dimensional interacting systems may exhibit behaviour that differs strongly from that predicted by standard Tomonaga-Luttinger liquid theory, with the appearance of power-law divergences in the spectral function signifying sublinear diffusion of the impurity. Using time-dependent matrix product states, we investigate a range of cases of mobile impurities in systems beyond the analytically accessible examples to assess the existence of a new universality class of low-energy physics in one-dimensional systems. Correspondence: Adrian.Kantian@unige.ch This work was supported in part by the Swiss SNF under MaNEP and division II.

When Black Holes Collide

NASA Technical Reports Server (NTRS)

Baker, John

2010-01-01

Among the fascinating phenomena predicted by General Relativity, Einstein's theory of gravity, black holes and gravitational waves, are particularly important in astronomy. Though once viewed as a mathematical oddity, black holes are now recognized as the central engines of many of astronomy's most energetic cataclysms. Gravitational waves, though weakly interacting with ordinary matter, may be observed with new gravitational wave telescopes, opening a new window to the universe. These observations promise a direct view of the strong gravitational dynamics involving dense, often dark objects, such as black holes. The most powerful of these events may be merger of two colliding black holes. Though dark, these mergers may briefly release more energy that all the stars in the visible universe, in gravitational waves. General relativity makes precise predictions for the gravitational-wave signatures of these events, predictions which we can now calculate with the aid of supercomputer simulations. These results provide a foundation for interpreting expect observations in the emerging field of gravitational wave astronomy.

Measurement and Modeling of Acoustic Fields in a Gel Phantom at High Intensities

NASA Astrophysics Data System (ADS)

Canney, Michael S.; Bailey, Michael R.; Khokhlova, Vera A.; Crum, Lawrence A.

2006-05-01

The goal of this work was to compare measured and numerically predicted HIFU pressure waveforms in water and a tissue-mimicking phantom. Waveforms were measured at the focus of a 2-MHz HIFU transducer with a fiber optic hydrophone. The transducer was operated with acoustic powers ranging from 2W to 300W. A KZK-type equation was used for modeling the experimental conditions. Strongly asymmetric nonlinear waves with peak positive pressure up to 80 MPa and peak negative pressure up to 20 MPa were measured in water, while waves up to 50 MPa peak positive pressure and 15 MPa peak negative pressure were measured in tissue phantoms. The values of peak negative pressure corresponded well with numerical simulations and were significantly smaller than predicted by linear extrapolation from low-level measurements. The values of peak positive pressures differed only at high levels of excitation where bandwidth limitations of the hydrophone failed to fully capture the predicted sharp shock fronts.

Genome-Wide Association Analysis of Adaptation Using Environmentally Predicted Traits.

PubMed

van Heerwaarden, Joost; van Zanten, Martijn; Kruijer, Willem

2015-10-01

Current methods for studying the genetic basis of adaptation evaluate genetic associations with ecologically relevant traits or single environmental variables, under the implicit assumption that natural selection imposes correlations between phenotypes, environments and genotypes. In practice, observed trait and environmental data are manifestations of unknown selective forces and are only indirectly associated with adaptive genetic variation. In theory, improved estimation of these forces could enable more powerful detection of loci under selection. Here we present an approach in which we approximate adaptive variation by modeling phenotypes as a function of the environment and using the predicted trait in multivariate and univariate genome-wide association analysis (GWAS). Based on computer simulations and published flowering time data from the model plant Arabidopsis thaliana, we find that environmentally predicted traits lead to higher recovery of functional loci in multivariate GWAS and are more strongly correlated to allele frequencies at adaptive loci than individual environmental variables. Our results provide an example of the use of environmental data to obtain independent and meaningful information on adaptive genetic variation.

Evaluation of icing drag coefficient correlations applied to iced propeller performance prediction

NASA Technical Reports Server (NTRS)

Miller, Thomas L.; Shaw, R. J.; Korkan, K. D.

1987-01-01

Evaluation of three empirical icing drag coefficient correlations is accomplished through application to a set of propeller icing data. The various correlations represent the best means currently available for relating drag rise to various flight and atmospheric conditions for both fixed-wing and rotating airfoils, and the work presented here ilustrates and evaluates one such application of the latter case. The origins of each of the correlations are discussed, and their apparent capabilities and limitations are summarized. These correlations have been made to be an integral part of a computer code, ICEPERF, which has been designed to calculate iced propeller performance. Comparison with experimental propeller icing data shows generally good agreement, with the quality of the predicted results seen to be directly related to the radial icing extent of each case. The code's capability to properly predict thrust coefficient, power coefficient, and propeller efficiency is shown to be strongly dependent on the choice of correlation selected, as well as upon proper specificatioon of radial icing extent.

Behavior and dynamics of bubble breakup in gas pipeline leaks and accidental subsea oil well blowouts.

PubMed

Wang, Binbin; Socolofsky, Scott A; Lai, Chris C K; Adams, E Eric; Boufadel, Michel C

2018-06-01

Subsea oil well blowouts and pipeline leaks release oil and gas to the environment through vigorous jets. Predicting the breakup of the released fluids in oil droplets and gas bubbles is critical to predict the fate of petroleum compounds in the marine water column. To predict the gas bubble size in oil well blowouts and pipeline leaks, we observed and quantified the flow behavior and breakup process of gas for a wide range of orifice diameters and flow rates. Flow behavior at the orifice transitions from pulsing flow to continuous discharge as the jet crosses the sonic point. Breakup dynamics transition from laminar to turbulent at a critical value of the Weber number. Very strong pure gas jets and most gas/liquid co-flowing jets exhibit atomization breakup. Bubble sizes in the atomization regime scale with the jet-to-plume transition length scale and follow -3/5 power-law scaling for a mixture Weber number. Copyright © 2018 Elsevier Ltd. All rights reserved.

On the origin of X-ray spectra in luminous blazars

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

Sikora, Marek; Janiak, Mateusz; Nalewajko, Krzysztof

2013-11-26

Gamma-ray luminosities of some quasar-associated blazars imply jet powers reaching values comparable to the accretion power even if assuming very strong Doppler boosting and very high efficiency of gamma-ray production. With much lower radiative efficiencies of protons than of electrons, and the recent reports of very strong coupling of electrons with shock-heated protons indicated by particle-in-cell simulations, the leptonic models seem to be strongly favored over the hadronic ones. However, the electron-proton coupling combined with the external-radiation-Compton (ERC) models of gamma-ray production in leptonic models predict extremely hard X-ray spectra, with energy indices α x ~ 0. This is inconsistentmore » with the observed 2-10 keV slopes of blazars, which cluster around α x ~ 0.6. This problem can be resolved by assuming that electrons can be efficiently cooled down radiatively to non-relativistic energies, or that blazar spectra are entirely dominated by the synchrotron self-Compton (SSC) component up to at least 10 keV. Here, we show that the required cooling can be sufficiently efficient only at distances r < 0.03 pc. SSC spectra, on the other hand, can be produced roughly co-spatially with the observed synchrotron and ERC components, which are most likely located roughly at a parsec scale. We show that the dominant SSC component can also be produced much further than the dominant synchrotron and ERC components, at distances of gsim 10 pc. Hence, depending on the spatial distribution of the energy dissipation along the jet, one may expect to see γ-ray/optical events with either correlated or uncorrelated X-rays. In all cases the number of e +e – pairs per proton is predicted to be very low. The direct verification of the proposed SSC scenario, and particularly the question of the co-spatiality of the SSC component with other spectral components, requires sensitive observations in the hard X-ray band. Lastly, this is now possible with the deployment of the NuSTAR satellite, providing the required sensitivity to monitor the details of the hard X-ray spectra of blazars in the range where the ERC component is predicted to start dominating over the SSC component.« less

Spontaneous mentalizing predicts the fundamental attribution error.

PubMed

Moran, Joseph M; Jolly, Eshin; Mitchell, Jason P

2014-03-01

When explaining the reasons for others' behavior, perceivers often overemphasize underlying dispositions and personality traits over the power of the situation, a tendency known as the fundamental attribution error. One possibility is that this bias results from the spontaneous processing of others' mental states, such as their momentary feelings or more enduring personality characteristics. Here, we use fMRI to test this hypothesis. Participants read a series of stories that described a target's ambiguous behavior in response to a specific social situation and later judged whether that act was attributable to the target's internal dispositions or to external situational factors. Neural regions consistently associated with mental state inference-especially, the medial pFC-strongly predicted whether participants later made dispositional attributions. These results suggest that the spontaneous engagement of mentalizing may underlie the biased tendency to attribute behavior to dispositional over situational forces.

Child and Adolescent Clinical Features Preceding Adult Suicide Attempts.

PubMed

Serra, Giulia; Koukopoulos, Athanasios; De Chiara, Lavinia; Napoletano, Flavia; Koukopoulos, Alexia; Sani, Gabriele; Faedda, Gianni L; Girardi, Paolo; Reginaldi, Daniela; Baldessarini, Ross J

2017-07-03

The objective of this study was to identify the predictive value of juvenile factors for adult suicidal behavior. We reviewed clinical records to compare factors identified in childhood and adolescence between adult suicidal versus nonsuicidal major affective disorder subjects. Suicide attempts occurred in 23.1% of subjects. Age-at-first-symptom was 14.2 vs. 20.2 years among suicidal versus nonsuicidal subjects (p < 0.0001). More prevalent in suicidal versus non-suicidal subjects by multivariate analysis were: depressive symptoms, hyper-emotionality, younger-at-first-affective-episode, family suicide history, childhood mood-swings, and adolescence low self-esteem. Presence of one factor yielded a Bayesian sensitivity of 64%, specificity of 50%, and negative predictive power of 86%. Several juvenile factors were associated with adult suicidal behavior; their absence was strongly associated with a lack of adult suicidal behavior.

The variability puzzle in human memory.

PubMed

Kahana, Michael J; Aggarwal, Eash V; Phan, Tung D

2018-04-26

Memory performance exhibits a high level of variability from moment to moment. Much of this variability may reflect inadequately controlled experimental variables, such as word memorability, past practice and subject fatigue. Alternatively, stochastic variability in performance may largely reflect the efficiency of endogenous neural processes that govern memory function. To help adjudicate between these competing views, the authors conducted a multisession study in which subjects completed 552 trials of a delayed free-recall task. Applying a statistical model to predict variability in each subject's recall performance uncovered modest effects of word memorability, proactive interference, and other variables. In contrast to the limited explanatory power of these experimental variables, performance on the prior list strongly predicted current list recall. These findings suggest that endogenous factors underlying successful encoding and retrieval drive variability in performance. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Predicting the vibroacoustic response of satellite equipment panels.

PubMed

Conlon, S C; Hambric, S A

2003-03-01

Modern satellites are constructed of large, lightweight equipment panels that are strongly excited by acoustic pressures during launch. During design, performing vibroacoustic analyses to evaluate and ensure the integrity of the complex electronics mounted on the panels is critical. In this study the attached equipment is explicitly addressed and how its properties affect the panel responses is characterized. FEA and BEA methods are used to derive realistic parameters to input to a SEA hybrid model of a panel with multiple attachments. Specifically, conductance/modal density and radiation efficiency for nonhomogeneous panel structures with and without mass loading are computed. The validity of using the spatially averaged conductance of panels with irregular features for deriving the structure modal density is demonstrated. Maidanik's proposed method of modifying the traditional SEA input power is implemented, illustrating the importance of accounting for system internal couplings when calculating the external input power. The predictions using the SEA hybrid model agree with the measured data trends, and are found to be most sensitive to the assumed dynamic mass ratio (attachments/structure) and the attachment internal loss factor. Additional experimental and analytical investigations are recommended to better characterize dynamic masses, modal densities and loss factors.

Spectrotemporal dynamics of the EEG during working memory encoding and maintenance predicts individual behavioral capacity.

PubMed

Bashivan, Pouya; Bidelman, Gavin M; Yeasin, Mohammed

2014-12-01

We investigated the effect of memory load on encoding and maintenance of information in working memory. Electroencephalography (EEG) signals were recorded while participants performed a modified Sternberg visual memory task. Independent component analysis (ICA) was used to factorise the EEG signals into distinct temporal activations to perform spectrotemporal analysis and localisation of source activities. We found 'encoding' and 'maintenance' operations were correlated with negative and positive changes in α-band power, respectively. Transient activities were observed during encoding of information in the bilateral cuneus, precuneus, inferior parietal gyrus and fusiform gyrus, and a sustained activity in the inferior frontal gyrus. Strong correlations were also observed between changes in α-power and behavioral performance during both encoding and maintenance. Furthermore, it was also found that individuals with higher working memory capacity experienced stronger neural oscillatory responses during the encoding of visual objects into working memory. Our results suggest an interplay between two distinct neural pathways and different spatiotemporal operations during the encoding and maintenance of information which predict individual differences in working memory capacity observed at the behavioral level. © 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Estimation of CO2 reduction by parallel hard-type power hybridization for gasoline and diesel vehicles.

PubMed

Oh, Yunjung; Park, Junhong; Lee, Jong Tae; Seo, Jigu; Park, Sungwook

2017-10-01

The purpose of this study is to investigate possible improvements in ICEVs by implementing fuzzy logic-based parallel hard-type power hybrid systems. Two types of conventional ICEVs (gasoline and diesel) and two types of HEVs (gasoline-electric, diesel electric) were generated using vehicle and powertrain simulation tools and a Matlab-Simulink application programming interface. For gasoline and gasoline-electric HEV vehicles, the prediction accuracy for four types of LDV models was validated by conducting comparative analysis with the chassis dynamometer and OBD test data. The predicted results show strong correlation with the test data. The operating points of internal combustion engines and electric motors are well controlled in the high efficiency region and battery SOC was well controlled within ±1.6%. However, for diesel vehicles, we generated virtual diesel-electric HEV vehicle because there is no available vehicles with similar engine and vehicle specifications with ICE vehicle. Using a fuzzy logic-based parallel hybrid system in conventional ICEVs demonstrated that HEVs showed superior performance in terms of fuel consumption and CO 2 emission in most driving modes. Copyright © 2017 Elsevier B.V. All rights reserved.

Efficiency of autonomous soft nanomachines at maximum power.

PubMed

Seifert, Udo

2011-01-14

We consider nanosized artificial or biological machines working in steady state enforced by imposing nonequilibrium concentrations of solutes or by applying external forces, torques, or electric fields. For unicyclic and strongly coupled multicyclic machines, efficiency at maximum power is not bounded by the linear response value 1/2. For strong driving, it can even approach the thermodynamic limit 1. Quite generally, such machines fall into three different classes characterized, respectively, as "strong and efficient," "strong and inefficient," and "balanced." For weakly coupled multicyclic machines, efficiency at maximum power has lost any universality even in the linear response regime.

Earthquake Intensity and Strong Motion Analysis Within SEISCOMP3

NASA Astrophysics Data System (ADS)

Becker, J.; Weber, B.; Ghasemi, H.; Cummins, P. R.; Murjaya, J.; Rudyanto, A.; Rößler, D.

2017-12-01

Measuring and predicting ground motion parameters including seismic intensities for earthquakes is crucial and subject to recent research in engineering seismology.gempa has developed the new SIGMA module for Seismic Intensity and Ground Motion Analysis. The module is based on the SeisComP3 framework extending it in the field of seismic hazard assessment and engineering seismology. SIGMA may work with or independently of SeisComP3 by supporting FDSN Web services for importing earthquake or station information and waveforms. It provides a user-friendly and modern graphical interface for semi-automatic and interactive strong motion data processing. SIGMA provides intensity and (P)SA maps based on GMPE's or recorded data. It calculates the most common strong motion parameters, e.g. PGA/PGV/PGD, Arias intensity and duration, Tp, Tm, CAV, SED and Fourier-, power- and response spectra. GMPE's are configurable. Supporting C++ and Python plug-ins, standard and customized GMPE's including the OpenQuake Hazard Library can be easily integrated and compared. Originally tailored to specifications by Geoscience Australia and BMKG (Indonesia) SIGMA has become a popular tool among SeisComP3 users concerned with seismic hazard and strong motion seismology.

Extending the ACEs Framework: Examining the Relations Between Childhood Abuse and Later Victimization and Perpetration With College Men.

PubMed

Voith, Laura A; Anderson, RaeAnn E; Cahill, Shawn P

2017-05-01

Research has revealed that forms of violence are interconnected, but less work focuses on the interconnection of victimization and perpetration, particularly with men. Subsequently, our understanding of the complexities of violence exposure in men's lives and related policies and treatments remains limited. The present study utilizes a sample of at-risk for violence involvement, college men, to examine the relationships between childhood victimization, adulthood victimization, and adulthood perpetration. Participants are 423 college men receiving course credit who completed a battery of standardized questionnaires via an anonymous web survey. Logistic regression is used. Results indicate that 27% of the men report polyperpetration (two or more types of perpetration), 43.5% report polyvictimization (two or more types of victimization), and 60% report experiencing both forms of victimization and perpetration in the past year. Childhood physical abuse has predictive power for perpetration (psychological aggression and polyperpetration) and victimization (sexual violence, psychological aggression, and polyvictimization) for the men in the past year. Childhood sexual abuse has strong predictive power for perpetration (physical violence, sexual violence, and polyperpetration) and victimization (physical violence and sexual violence) with the men in the past year. Finally, emotional abuse has predictive power for victimization (physical violence and psychological aggression), but not perpetration, for the men in the past year. Developmental psychopathology and the adverse childhood experiences frameworks are used to posit potential pathways explaining the relation between childhood abuse and the overlap between victimization and perpetration in adulthood for men. Implications of this study include the use of trauma-informed models of care with men and expanding the scope of study to examine experiences of both victimization and perpetration, and various types of violence, among men.

Height extrapolation of wind data

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

Mikhail, A.S.

1982-11-01

Hourly average data for a period of 1 year from three tall meteorological towers - the Erie tower in Colorado, the Goodnoe Hills tower in Washington and the WKY-TV tower in Oklahoma - were used to analyze the wind shear exponent variabiilty with various parameters such as thermal stability, anemometer level wind speed, projection height and surface roughness. Different proposed models for prediction of height variability of short-term average wind speeds were discussed. Other models that predict the height dependence of Weilbull distribution parameters were tested. The observed power law exponent for all three towers showed strong dependence on themore » anemometer level wind speed and stability (nighttime and daytime). It also exhibited a high degree of dependence on extrapolation height with respect to anemometer height. These dependences became less severe as the anemometer level wind speeds were increased due to the turbulent mixing of the atmospheric boundary layer. The three models used for Weibull distribution parameter extrapolation were he velocity-dependent power law model (Justus), the velocity, surface roughness, and height-dependent model (Mikhail) and the velocity and surface roughness-dependent model (NASA). The models projected the scale parameter C fairly accurately for the Goodnoe Hills and WKY-TV towers and were less accurate for the Erie tower. However, all models overestimated the C value. The maximum error for the Mikhail model was less than 2% for Goodnoe Hills, 6% for WKY-TV and 28% for Erie. The error associated with the prediction of the shape factor (K) was similar for the NASA, Mikhail and Justus models. It ranged from 20 to 25%. The effect of the misestimation of hub-height distribution parameters (C and K) on average power output is briefly discussed.« less

Flow of variably fluidized granular masses across three-dimensional terrain 2. Numerical predictions and experimental tests

USGS Publications Warehouse

Denlinger, R.P.; Iverson, R.M.

2001-01-01

Numerical solutions of the equations describing flow of variably fluidized Coulomb mixtures predict key features of dry granular avalanches and water-saturated debris flows measured in physical experiments. These features include time-dependent speeds, depths, and widths of flows as well as the geometry of resulting deposits. Threedimensional (3-D) boundary surfaces strongly influence flow dynamics because transverse shearing and cross-stream momentum transport occur where topography obstructs or redirects motion. Consequent energy dissipation can cause local deceleration and deposition, even on steep slopes. Velocities of surge fronts and other discontinuities that develop as flows cross 3-D terrain are predicted accurately by using a Riemann solution algorithm. The algorithm employs a gravity wave speed that accounts for different intensities of lateral stress transfer in regions of extending and compressing flow and in regions with different degrees of fluidization. Field observations and experiments indicate that flows in which fluid plays a significant role typically have high-friction margins with weaker interiors partly fluidized by pore pressure. Interaction of the strong perimeter and weak interior produces relatively steep-sided, flat-topped deposits. To simulate these effects, we compute pore pressure distributions using an advection-diffusion model with enhanced diffusivity near flow margins. Although challenges remain in evaluating pore pressure distributions in diverse geophysical flows, Riemann solutions of the depthaveraged 3-D Coulomb mixture equations provide a powerful tool for interpreting and predicting flow behavior. They provide a means of modeling debris flows, rock avalanches, pyroclastic flows, and related phenomena without invoking and calibrating Theological parameters that have questionable physical significance.

Variability of stratification according to operation of the tidal power plant in Lake Sihwa, South Korea.

NASA Astrophysics Data System (ADS)

Woo, S. B.; Song, J. I.; Jang, T. H.; Park, C. J.; Kwon, H. K.

2017-12-01

Artificial forcing according to operation of the tidal power plant (TPP) affects the physical environmental changes near the power plant. Strong turbulence by generation is expected to change the stratification structure of the Lake Sihwa inside. In order to examine the stratification changes by the power plant operation, ship bottom mounted observation were performed for 13 hours using an acoustic Doppler current profiler (ADCP) and Conductivity-Temperature-Depth (CTD) in Lake Sihwa at near TPP. The strong stratification in Sihwa Lake is maintained before TPP operation. The absence of external forces and freshwater inflow from the land forms the stratification in the Lake. Strong winds in a stratification statement lead to two-layer circulation. After wind event, multi-layer velocity structure is formed which lasted for approximately 4 h. After TPP operation, the jet flow was observed in entire water column at the beginning of the power generation. Vortex is formed by strong jet flow and maintained throughout during power generation period. Strong turbulence flow is generated by the turbine blades, enhancing vertical mixing. External forces, which dominantly affect Lake Sihwa, have changed from the wind to the turbulent flow. The stratification was extinguished by strong turbulent flow and becomes fully-mixed state. Changes in stratification structure are expected to affect material transport and ecological environment change continuously.

Image Feature Types and Their Predictions of Aesthetic Preference and Naturalness

PubMed Central

Ibarra, Frank F.; Kardan, Omid; Hunter, MaryCarol R.; Kotabe, Hiroki P.; Meyer, Francisco A. C.; Berman, Marc G.

2017-01-01

Previous research has investigated ways to quantify visual information of a scene in terms of a visual processing hierarchy, i.e., making sense of visual environment by segmentation and integration of elementary sensory input. Guided by this research, studies have developed categories for low-level visual features (e.g., edges, colors), high-level visual features (scene-level entities that convey semantic information such as objects), and how models of those features predict aesthetic preference and naturalness. For example, in Kardan et al. (2015a), 52 participants provided aesthetic preference and naturalness ratings, which are used in the current study, for 307 images of mixed natural and urban content. Kardan et al. (2015a) then developed a model using low-level features to predict aesthetic preference and naturalness and could do so with high accuracy. What has yet to be explored is the ability of higher-level visual features (e.g., horizon line position relative to viewer, geometry of building distribution relative to visual access) to predict aesthetic preference and naturalness of scenes, and whether higher-level features mediate some of the association between the low-level features and aesthetic preference or naturalness. In this study we investigated these relationships and found that low- and high- level features explain 68.4% of the variance in aesthetic preference ratings and 88.7% of the variance in naturalness ratings. Additionally, several high-level features mediated the relationship between the low-level visual features and aaesthetic preference. In a multiple mediation analysis, the high-level feature mediators accounted for over 50% of the variance in predicting aesthetic preference. These results show that high-level visual features play a prominent role predicting aesthetic preference, but do not completely eliminate the predictive power of the low-level visual features. These strong predictors provide powerful insights for future research relating to landscape and urban design with the aim of maximizing subjective well-being, which could lead to improved health outcomes on a larger scale. PMID:28503158

Prediction of Wind Energy Resources (PoWER) Users Guide

DTIC Science & Technology

2016-01-01

ARL-TR-7573● JAN 2016 US Army Research Laboratory Prediction of Wind Energy Resources (PoWER) User’s Guide by David P Sauter...not return it to the originator. ARL-TR-7573 ● JAN 2016 US Army Research Laboratory Prediction of Wind Energy Resources (PoWER...2016 2. REPORT TYPE Final 3. DATES COVERED (From - To) 09/2015–11/2015 4. TITLE AND SUBTITLE Prediction of Wind Energy Resources (PoWER) User’s

Design of experiment for optimization of plasma-polymerized octafluorocyclobutane coating on very high aspect ratio silicon molds.

PubMed

Yeo, L P; Yan, Y H; Lam, Y C; Chan-Park, Mary B

2006-11-21

As-fabricated deep reactive ion etched (DRIE) silicon mold with very high aspect ratio (>10) feature patterns is unsuitable for poly(dimethylsiloxane) (PDMS) replication because of the strong interaction between the Si surface and the replica and the corrugated mold sidewalls. The silicon mold can be conveniently passivated via plasma polymerization of octafluorocyclobutane (C4F8), which is also employed in the DRIE process itself, to enable the mold to be used repeatedly. To optimize the passivation conditions, we have undertaken a Box-Behnken experimental design on the basis of three passivation process parameters (plasma power, C4F8 flow rate, and deposition time). The measured responses were fluorinated film thickness, demolding status/success, demolding force, and fluorine/carbon ratio on the fifth replica surface. The optimal passivation process conditions were predicted to be an input power of 195 W, a C4F8 flow rate of 57 sccm, and a deposition time of 364 s; these were verified experimentally to have high accuracy. Demolding success requires medium-deposited film thickness (66-91 nm), and the thickness of the deposited films correlated strongly with deposition time. At moderate to high ranges, increased plasma power or gas flow rate promoted polymerization over reactive etching of the film. It was also found that small quantities of the fluorinated surface were transferred from the Si mold to the PDMS at each replication, entailing progressive wear of the fluorinated layer.

Analysis and experimental evaluation of shunt active power filter for power quality improvement based on predictive direct power control.

PubMed

Aissa, Oualid; Moulahoum, Samir; Colak, Ilhami; Babes, Badreddine; Kabache, Nadir

2017-10-12

This paper discusses the use of the concept of classical and predictive direct power control for shunt active power filter function. These strategies are used to improve the active power filter performance by compensation of the reactive power and the elimination of the harmonic currents drawn by non-linear loads. A theoretical analysis followed by a simulation using MATLAB/Simulink software for the studied techniques has been established. Moreover, two test benches have been carried out using the dSPACE card 1104 for the classic and predictive DPC control to evaluate the studied methods in real time. Obtained results are presented and compared in this paper to confirm the superiority of the predictive technique. To overcome the pollution problems caused by the consumption of fossil fuels, renewable energies are the alternatives recommended to ensure green energy. In the same context, the tested predictive filter can easily be supplied by a renewable energy source that will give its impact to enhance the power quality.

Electroencephalographic identifiers of motor adaptation learning

NASA Astrophysics Data System (ADS)

Özdenizci, Ozan; Yalçın, Mustafa; Erdoğan, Ahmetcan; Patoğlu, Volkan; Grosse-Wentrup, Moritz; Çetin, Müjdat

2017-08-01

Objective. Recent brain-computer interface (BCI) assisted stroke rehabilitation protocols tend to focus on sensorimotor activity of the brain. Relying on evidence claiming that a variety of brain rhythms beyond sensorimotor areas are related to the extent of motor deficits, we propose to identify neural correlates of motor learning beyond sensorimotor areas spatially and spectrally for further use in novel BCI-assisted neurorehabilitation settings. Approach. Electroencephalographic (EEG) data were recorded from healthy subjects participating in a physical force-field adaptation task involving reaching movements through a robotic handle. EEG activity recorded during rest prior to the experiment and during pre-trial movement preparation was used as features to predict motor adaptation learning performance across subjects. Main results. Subjects learned to perform straight movements under the force-field at different adaptation rates. Both resting-state and pre-trial EEG features were predictive of individual adaptation rates with relevance of a broad network of beta activity. Beyond sensorimotor regions, a parieto-occipital cortical component observed across subjects was involved strongly in predictions and a fronto-parietal cortical component showed significant decrease in pre-trial beta-powers for users with higher adaptation rates and increase in pre-trial beta-powers for users with lower adaptation rates. Significance. Including sensorimotor areas, a large-scale network of beta activity is presented as predictive of motor learning. Strength of resting-state parieto-occipital beta activity or pre-trial fronto-parietal beta activity can be considered in BCI-assisted stroke rehabilitation protocols with neurofeedback training or volitional control of neural activity for brain-robot interfaces to induce plasticity.

Rolling Bearing Life Prediction, Theory, and Application

NASA Technical Reports Server (NTRS)

Zaretsky, Erwin V.

2013-01-01

A tutorial is presented outlining the evolution, theory, and application of rolling-element bearing life prediction from that of A. Palmgren, 1924; W. Weibull, 1939; G. Lundberg and A. Palmgren, 1947 and 1952; E. Ioannides and T. Harris, 1985; and E. Zaretsky, 1987. Comparisons are made between these life models. The Ioannides-Harris model without a fatigue limit is identical to the Lundberg-Palmgren model. The Weibull model is similar to that of Zaretsky if the exponents are chosen to be identical. Both the load-life and Hertz stress-life relations of Weibull, Lundberg and Palmgren, and Ioannides and Harris reflect a strong dependence on the Weibull slope. The Zaretsky model decouples the dependence of the critical shear stress-life relation from the Weibull slope. This results in a nominal variation of the Hertz stress-life exponent. For 9th- and 8th-power Hertz stress-life exponents for ball and roller bearings, respectively, the Lundberg- Palmgren model best predicts life. However, for 12th- and 10th-power relations reflected by modern bearing steels, the Zaretsky model based on the Weibull equation is superior. Under the range of stresses examined, the use of a fatigue limit would suggest that (for most operating conditions under which a rolling-element bearing will operate) the bearing will not fail from classical rolling-element fatigue. Realistically, this is not the case. The use of a fatigue limit will significantly overpredict life over a range of normal operating Hertz stresses. Since the predicted lives of rolling-element bearings are high, the problem can become one of undersizing a bearing for a particular application.

Quantitative Determination of Technological Improvement from Patent Data

PubMed Central

2015-01-01

The results in this paper establish that information contained in patents in a technological domain is strongly correlated with the rate of technological progress in that domain. The importance of patents in a domain, the recency of patents in a domain and the immediacy of patents in a domain are all strongly correlated with increases in the rate of performance improvement in the domain of interest. A patent metric that combines both importance and immediacy is not only highly correlated (r = 0.76, p = 2.6*10-6) with the performance improvement rate but the correlation is also very robust to domain selection and appears to have good predictive power for more than ten years into the future. Linear regressions with all three causal concepts indicate realistic value in practical use to estimate the important performance improvement rate of a technological domain. PMID:25874447

Computational Approaches to the Chemical Equilibrium Constant in Protein-ligand Binding.

PubMed

Montalvo-Acosta, Joel José; Cecchini, Marco

2016-12-01

The physiological role played by protein-ligand recognition has motivated the development of several computational approaches to the ligand binding affinity. Some of them, termed rigorous, have a strong theoretical foundation but involve too much computation to be generally useful. Some others alleviate the computational burden by introducing strong approximations and/or empirical calibrations, which also limit their general use. Most importantly, there is no straightforward correlation between the predictive power and the level of approximation introduced. Here, we present a general framework for the quantitative interpretation of protein-ligand binding based on statistical mechanics. Within this framework, we re-derive self-consistently the fundamental equations of some popular approaches to the binding constant and pinpoint the inherent approximations. Our analysis represents a first step towards the development of variants with optimum accuracy/efficiency ratio for each stage of the drug discovery pipeline. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Pulsars and Acceleration Sites

NASA Technical Reports Server (NTRS)

Harding, Alice

2008-01-01

Rotation-powered pulsars are excellent laboratories for the studying particle acceleration as well as fundamental physics of strong gravity, strong magnetic fields and relativity. But even forty years after their discovery, we still do not understand their pulsed emission at any wavelength. I will review both the basic physics of pulsars as well as the latest developments in understanding their high-energy emission. Special and general relativistic effects play important roles in pulsar emission, from inertial frame-dragging near the stellar surface to aberration, time-of-flight and retardation of the magnetic field near the light cylinder. Understanding how these effects determine what we observe at different wavelengths is critical to unraveling the emission physics. Fortunately the Gamma-Ray Large Area Space Telescope (GLAST), with launch in May 2008 will detect many new gamma-ray pulsars and test the predictions of these models with unprecedented sensitivity and energy resolution for gamma-rays in the range of 30 MeV to 300 GeV.

Three-dimensional simulations of rapidly rotating core-collapse supernovae: finding a neutrino-powered explosion aided by non-axisymmetric flows

NASA Astrophysics Data System (ADS)

Takiwaki, Tomoya; Kotake, Kei; Suwa, Yudai

2016-09-01

We report results from a series of three-dimensional (3D) rotational core-collapse simulations for 11.2 and 27 M⊙ stars employing neutrino transport scheme by the isotropic diffusion source approximation. By changing the initial strength of rotation systematically, we find a rotation-assisted explosion for the 27 M⊙ progenitor , which fails in the absence of rotation. The unique feature was not captured in previous two-dimensional (2D) self-consistent rotating models because the growing non-axisymmetric instabilities play a key role. In the rapidly rotating case, strong spiral flows generated by the so-called low T/|W| instability enhance the energy transport from the proto-neutron star (PNS) to the gain region, which makes the shock expansion more energetic. The explosion occurs more strongly in the direction perpendicular to the rotational axis, which is different from previous 2D predictions.

The aerodynamic cost of flight in the short-tailed fruit bat (Carollia perspicillata): comparing theory with measurement

PubMed Central

von Busse, Rhea; Waldman, Rye M.; Swartz, Sharon M.; Voigt, Christian C.; Breuer, Kenneth S.

2014-01-01

Aerodynamic theory has long been used to predict the power required for animal flight, but widely used models contain many simplifications. It has been difficult to ascertain how closely biological reality matches model predictions, largely because of the technical challenges of accurately measuring the power expended when an animal flies. We designed a study to measure flight speed-dependent aerodynamic power directly from the kinetic energy contained in the wake of bats flying in a wind tunnel. We compared these measurements with two theoretical predictions that have been used for several decades in diverse fields of vertebrate biology and to metabolic measurements from a previous study using the same individuals. A high-accuracy displaced laser sheet stereo particle image velocimetry experimental design measured the wake velocities in the Trefftz plane behind four bats flying over a range of speeds (3–7 m s−1). We computed the aerodynamic power contained in the wake using a novel interpolation method and compared these results with the power predicted by Pennycuick's and Rayner's models. The measured aerodynamic power falls between the two theoretical predictions, demonstrating that the models effectively predict the appropriate range of flight power, but the models do not accurately predict minimum power or maximum range speeds. Mechanical efficiency—the ratio of aerodynamic power output to metabolic power input—varied from 5.9% to 9.8% for the same individuals, changing with flight speed. PMID:24718450

An index predictive of cognitive outcome in retired professional American Football players with a history of sports concussion.

PubMed

Wright, Mathew J; Woo, Ellen; Birath, J Brandon; Siders, Craig A; Kelly, Daniel F; Wang, Christina; Swerdloff, Ronald; Romero, Elizabeth; Kernan, Claudia; Cantu, Robert C; Guskiewicz, Kevin

2016-01-01

Various concussion characteristics and personal factors are associated with cognitive recovery in athletes. We developed an index based on concussion frequency, severity, and timeframe, as well as cognitive reserve (CR), and we assessed its predictive power regarding cognitive ability in retired professional football players. Data from 40 retired professional American football players were used in the current study. On average, participants had been retired from football for 20 years. Current neuropsychological performances, indicators of CR, concussion history, and play data were used to create an index for predicting cognitive outcome. The sample displayed a range of concussions, concussion severities, seasons played, CR, and cognitive ability. Many of the participants demonstrated cognitive deficits. The index strongly predicted global cognitive ability (R(2) = .31). The index also predicted the number of areas of neuropsychological deficit, which varied as a function of the deficit classification system used (Heaton: R(2) = .15; Wechsler: R(2) = .28). The current study demonstrated that a unique combination of CR, sports concussion, and game-related data can predict cognitive outcomes in participants who had been retired from professional American football for an average of 20 years. Such indices may prove to be useful for clinical decision making and research.

Functional brain imaging predicts public health campaign success

PubMed Central

O’Donnell, Matthew Brook; Tompson, Steven; Gonzalez, Richard; Dal Cin, Sonya; Strecher, Victor; Cummings, Kenneth Michael; An, Lawrence

2016-01-01

Mass media can powerfully affect health decision-making. Pre-testing through focus groups or surveys is a standard, though inconsistent, predictor of effectiveness. Converging evidence demonstrates that activity within brain systems associated with self-related processing can predict individual behavior in response to health messages. Preliminary evidence also suggests that neural activity in small groups can forecast population-level campaign outcomes. Less is known about the psychological processes that link neural activity and population-level outcomes, or how these predictions are affected by message content. We exposed 50 smokers to antismoking messages and used their aggregated neural activity within a ‘self-localizer’ defined region of medial prefrontal cortex to predict the success of the same campaign messages at the population level (n = 400 000 emails). Results demonstrate that: (i) independently localized neural activity during health message exposure complements existing self-report data in predicting population-level campaign responses (model combined R2 up to 0.65) and (ii) this relationship depends on message content—self-related neural processing predicts outcomes in response to strong negative arguments against smoking and not in response to compositionally similar neutral images. These data advance understanding of the psychological link between brain and large-scale behavior and may aid the construction of more effective media health campaigns. PMID:26400858

Prediction of anaerobic power values from an abbreviated WAnT protocol.

PubMed

Stickley, Christopher D; Hetzler, Ronald K; Kimura, Iris F

2008-05-01

The traditional 30-second Wingate anaerobic test (WAnT) is a widely used anaerobic power assessment protocol. An abbreviated protocol has been shown to decrease the mild to severe physical discomfort often associated with the WAnT. Therefore, the purpose of this study was to determine whether a 20-second WAnT protocol could be used to accurately predict power values of a standard 30-second WAnT. In 96 college females, anaerobic power variables were assessed using a standard 30-second WAnT protocol. Maximum power values as well as instantaneous power at 10, 15, and 20 seconds were recorded. Based on these results, stepwise regression analysis was performed to determine the accuracy with which mean power, minimum power, 30-second power, and percentage of fatigue for a standard 30-second WAnT could be predicted from values obtained during the first 20 seconds of testing. Mean power values showed the highest level of predictability (R2 = 0.99) from the 20-second values. Minimum power, 30-second power, and percentage of fatigue also showed high levels of predictability (R2 = 0.91, 0.84, and 0.84, respectively) using only values obtained during the first 20 seconds of the protocol. An abbreviated (20-second) WAnT protocol appears to effectively predict results of a standard 30-second WAnT in college-age females, allowing for comparison of data to published norms. A shortened test may allow for a decrease in unwanted side effects associated with the traditional WAnT protocol.

Sensitivity analysis of numerical weather prediction radiative schemes to forecast direct solar radiation over Australia

NASA Astrophysics Data System (ADS)

Mukkavilli, S. K.; Kay, M. J.; Taylor, R.; Prasad, A. A.; Troccoli, A.

2014-12-01

The Australian Solar Energy Forecasting System (ASEFS) project requires forecasting timeframes which range from nowcasting to long-term forecasts (minutes to two years). As concentrating solar power (CSP) plant operators are one of the key stakeholders in the national energy market, research and development enhancements for direct normal irradiance (DNI) forecasts is a major subtask. This project involves comparing different radiative scheme codes to improve day ahead DNI forecasts on the national supercomputing infrastructure running mesoscale simulations on NOAA's Weather Research & Forecast (WRF) model. ASEFS also requires aerosol data fusion for improving accurate representation of spatio-temporally variable atmospheric aerosols to reduce DNI bias error in clear sky conditions over southern Queensland & New South Wales where solar power is vulnerable to uncertainities from frequent aerosol radiative events such as bush fires and desert dust. Initial results from thirteen years of Bureau of Meteorology's (BOM) deseasonalised DNI and MODIS NASA-Terra aerosol optical depth (AOD) anomalies demonstrated strong negative correlations in north and southeast Australia along with strong variability in AOD (~0.03-0.05). Radiative transfer schemes, DNI and AOD anomaly correlations will be discussed for the population and transmission grid centric regions where current and planned CSP plants dispatch electricity to capture peak prices in the market. Aerosol and solar irradiance datasets include satellite and ground based assimilations from the national BOM, regional aerosol researchers and agencies. The presentation will provide an overview of this ASEFS project task on WRF and results to date. The overall goal of this ASEFS subtask is to develop a hybrid numerical weather prediction (NWP) and statistical/machine learning multi-model ensemble strategy that meets future operational requirements of CSP plant operators.

Acoustic receptivity and transition modeling of Tollmien-Schlichting disturbances induced by distributed surface roughness

NASA Astrophysics Data System (ADS)

Raposo, Henrique; Mughal, Shahid; Ashworth, Richard

2018-04-01

Acoustic receptivity to Tollmien-Schlichting waves in the presence of surface roughness is investigated for a flat plate boundary layer using the time-harmonic incompressible linearized Navier-Stokes equations. It is shown to be an accurate and efficient means of predicting receptivity amplitudes and, therefore, to be more suitable for parametric investigations than other approaches with direct-numerical-simulation-like accuracy. Comparison with the literature provides strong evidence of the correctness of the approach, including the ability to quantify non-parallel flow effects. These effects are found to be small for the efficiency function over a wide range of frequencies and local Reynolds numbers. In the presence of a two-dimensional wavy-wall, non-parallel flow effects are quite significant, producing both wavenumber detuning and an increase in maximum amplitude. However, a smaller influence is observed when considering an oblique Tollmien-Schlichting wave. This is explained by considering the non-parallel effects on receptivity and on linear growth which may, under certain conditions, cancel each other out. Ultimately, we undertake a Monte Carlo type uncertainty quantification analysis with two-dimensional distributed random roughness. Its power spectral density (PSD) is assumed to follow a power law with an associated uncertainty following a probabilistic Gaussian distribution. The effects of the acoustic frequency over the mean amplitude of the generated two-dimensional Tollmien-Schlichting waves are studied. A strong dependence on the mean PSD shape is observed and discussed according to the basic resonance mechanisms leading to receptivity. The growth of Tollmien-Schlichting waves is predicted with non-linear parabolized stability equations computations to assess the effects of stochasticity in transition location.

Tribological characteristic enhancement effects by polymer thickened oil in lubricated sliding contacts

NASA Astrophysics Data System (ADS)

Pratomo, Ariawan Wahyu; Muchammad, Tauviqirrahman, Mohammad; Jamari, Bayuseno, Athanasius P.

2016-04-01

Polymer thickened oils are the most preferred materials for modern lubrication applications due to their high shear. The present paper explores a lubrication mechanism in sliding contact lubricated with polymer thickened oil considering cavitation. Investigations are carried out by using a numerical method based on commercial CFD (computational fluid dynamic) software ANSYS for fluid flow phenomenon (Fluent) to assess the tribological characteristic (i.e. hydrodynamic pressure distribution) of lubricated sliding contact. The Zwart-Gerber-Belamri model for cavitation is adopted in this simulation to predict the extent of the full film region. The polymer thickened oil is characterized as non-Newtonian power-law fluid. The simulation results show that the cavitation lead lower pressure profile compared to that without cavitation. In addition, it is concluded that the characteristic of the lubrication performance with polymer thickened oil is strongly dependent on the Power-law index of lubricant.

Respiratory function of children in homes insulated with urea formaldehyde foam insulation.

PubMed Central

Norman, G R; Pengelly, L D; Kerigan, A T; Goldsmith, C H

1986-01-01

A study was carried out to assess the respiratory function of children living in homes insulated with urea formaldehyde foam insulation (UFFI). A large data base on the effect of environmental variables on the respiratory function of 3500 children in the Hamilton, Ont., area had been collected from 1978 to 1980. From this data base 29 children who lived in UFFI-insulated homes were identified, and each was matched with 2 controls according to nine variables that had been shown to be strongly predictive of respiratory function. Reported respiratory symptoms and results of pulmonary function testing in the year immediately following installation of UFFI were examined. No significant differences in any variable were found between the subjects and controls. A power calculation indicated that the study had adequate power to detect clinically important changes. The authors conclude that there was no evidence of respiratory problems resulting from UFFI in the sample studied. PMID:3697859

Intermodulation in nonlinear SQUID metamaterials: Experiment and theory

NASA Astrophysics Data System (ADS)

Zhang, Daimeng; Trepanier, Melissa; Antonsen, Thomas; Ott, Edward; Anlage, Steven M.

2016-11-01

The response of nonlinear metamaterials and superconducting electronics to two-tone excitation is critical for understanding their use as low-noise amplifiers and tunable filters. A new setting for such studies is that of metamaterials made of radio frequency superconducting quantum interference devices (rf-SQUIDs). The two-tone response of self-resonant rf-SQUID meta-atoms and metamaterials is studied here via intermodulation (IM) measurement over a broad range of tone frequencies and tone powers. A sharp onset followed by a surprising strongly suppressed IM region near the resonance is observed. Using a two time scale analysis technique, we present an analytical theory that successfully explains our experimental observations. The theory predicts that the IM can be manipulated with tone power, center frequency, frequency difference between the two tones, and temperature. This quantitative understanding potentially allows for the design of rf-SQUID metamaterials with either very low or very high IM response.

Microwave Ablation With a Triaxial Antenna: Results in ex vivo Bovine Liver

PubMed Central

Brace, Christopher L.; Laeseke, Paul F.; van der Weide, Daniel W.; Lee, Fred T.

2007-01-01

We apply a new triaxial antenna for microwave ablation procedures to an ex vivo bovine liver. The antenna consists of a coaxial monopole inserted through a biopsy needle positioned one quarter-wavelength from the antenna base. The insertion needle creates a triaxial structure, which enhances return loss more than 10 dB, maximizing energy transfer to the tissue while minimizing feed cable heating and invasiveness. Numerical electromagnetic and thermal simulations are used to optimize the antenna design and predict heating patterns. Numerical and ex vivo experimental results show that the lesion size depends strongly on ablation time and average input power, but not on peak power. Pulsing algorithms are also explored. We were able to measure a 3.8-cm lesion using 50 W for 7 min, which we believe to be the largest lesion reported thus far using a 17-gauge insertion needle. PMID:18079981

Hydrodynamics of a cold one-dimensional fluid: the problem of strong shock waves

NASA Astrophysics Data System (ADS)

Hurtado, Pablo I.

2005-03-01

We study a shock wave induced by an infinitely massive piston propagating into a one-dimensional cold gas. The cold gas is modelled as a collection of hard rods which are initially at rest, so the temperature is zero. Most of our results are based on simulations of a gas of rods with binary mass distribution, and we partcularly focus on the case of spatially alternating masses. We find that the properties of the resulting shock wave are in striking contrast with those predicted by hydrodynamic and kinetic approaches, e.g., the flow-field profiles relax algebraically toward their equilibrium values. In addition, most relevant observables characterizing local thermodynamic equilibrium and equipartition decay as a power law of the distance to the shock layer. The exponents of these power laws depend non-monotonously on the mass ratio. Similar interesting dependences on the mass ratio also characterize the shock width, density and temperature overshoots, etc.

Effect of low level laser therapy and high intensity laser therapy on endothelial cell proliferation in vitro: preliminary communication

NASA Astrophysics Data System (ADS)

Lukowicz, Malgorzata; Szymanska, Justyna; Goralczyk, Krzysztof; Zajac, Andrzej; Rość, Danuta

2013-01-01

Background: The main purpose of this study was to analyze the influence of power intensity and wavelength of Low Level Laser Therapy (LLLT) and HILT (High Intensity Laser Therapy) on endothelial cell proliferation. Material and methods: The tests were done on human umbilical vein endothelial cells (HUVEC). Cultures were exposed to laser irradiation of 660 nm and 670 nm at different dosages, power output was 10 - 40 mW as well as 820 nm with power 100 mW and 808 nm with power 1500 mW. Energy density was from 0.28 to 11,43 J/cm2. Cell proliferation of a control and tested culture was evaluated with a colorimetric device to detect live cells. The tests were repeated 8 times. Results: We observed good effects of LLLT on live isolated ECs and no effects in experiments on previous deep-frozen cultures. Also HILT stimulated the proliferation of HUVEC. Conclusion: Endothelial cells play a key role in vascular homeostasis in humans. We observed the stimulatory effect of LLLT and HILT on proliferation of HUVEC. Many factors influence the proliferation of EC, so is it necessary to continue the experiment with different doses, intensity and cell concentration.

Constraints on parton distribution functions and extraction of the strong coupling constant from the inclusive jet cross section in pp collisions at [Formula: see text][Formula: see text].

PubMed

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The inclusive jet cross section for proton-proton collisions at a centre-of-mass energy of 7[Formula: see text] was measured by the CMS Collaboration at the LHC with data corresponding to an integrated luminosity of 5.0[Formula: see text]. The measurement covers a phase space up to 2[Formula: see text] in jet transverse momentum and 2.5 in absolute jet rapidity. The statistical precision of these data leads to stringent constraints on the parton distribution functions of the proton. The data provide important input for the gluon density at high fractions of the proton momentum and for the strong coupling constant at large energy scales. Using predictions from perturbative quantum chromodynamics at next-to-leading order, complemented with electroweak corrections, the constraining power of these data is investigated and the strong coupling constant at the Z boson mass [Formula: see text] is determined to be [Formula: see text], which is in agreement with the world average.

Exploring the Effects of Low Power Schemas in Mothers.

ERIC Educational Resources Information Center

Mills, Rosemary S. L.

1999-01-01

Assessed whether low perceived maternal power and temperamentally fearful preschool-aged daughters predicted subsequent maternal overcontrol and internalizing symptoms in daughters 2 years later. Found that low perceived maternal power predicted subsequent maternal overcontrol with initially fearful daughters but did not predict subsequent…

Highly Efficient Wireless Powering for Autonomous Structural Health Monitoring and Test/Evaluation Systems

DTIC Science & Technology

2016-07-27

ADDRESS (ES) U.S. Army Research Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 Wireless Power Transfer , Structural Health Monitoring...efficient strongly coupled magnetic resonant systems, Wireless Power Transfer , (03 2014): 0. doi: 10.1017/wpt.2014.3 TOTAL: 1 Received Paper TOTAL...2016 Received Paper . Miniaturized Strongly Coupled Magnetic Resonant Systems for Wireless Power Transfer , 2016 IEEE Antennas Propagat. Society

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

Potentiality Prediction of Electric Power Replacement Based on Power Market Development Strategy

NASA Astrophysics Data System (ADS)

Miao, Bo; Yang, Shuo; Liu, Qiang; Lin, Jingyi; Zhao, Le; Liu, Chang; Li, Bin

2017-05-01

The application of electric power replacement plays an important role in promoting the development of energy conservation and emission reduction in our country. To exploit the potentiality of regional electric power replacement, the regional GDP (gross domestic product) and energy consumption are taken as potentiality evaluation indicators. The principal component factors are extracted with PCA (principal component analysis), and the integral potentiality analysis is made to the potentiality of electric power replacement in the national various regions; a region is taken as a research object, and the potentiality of electric power replacement is defined and quantified. The analytical model for the potentiality of multi-scenario electric power replacement is developed, and prediction is made to the energy consumption with the grey prediction model. The relevant theoretical research is utilized to realize prediction analysis on the potentiality amount of multi-scenario electric power replacement.

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

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

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

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

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. Copyright © 2016 John Wiley & Sons, Ltd.

Error-growth dynamics and predictability of surface thermally induced atmospheric flow

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

Zeng, X.; Pielke, R.A.

1993-09-01

Using the CSU Regional Atmospheric Modeling System (RAMS) in its nonhydrostatic and compressible configuration, over 200 two-dimensional simulations with [Delta]x = 2 km and [Delta]x = 100 m are performed to study in detail the initial adjustment process and the error-growth dynamics of surface thermally induced circulation including the sensitivity to initial conditions, boundary conditions, and model parameters, and to study the predictability as a function of the size of surface heat patches under a calm mean wind. It is found that the error growth is not sensitive to the characterisitics of the initial perturbations. The numerical smoothing has amore » strong impact on the initial adjustment process and on the error-growth dynamics. The predictability and flow structures, it is found that the vertical velocity field is strongly affected by the mean wind, and the flow structures are quite sensitive to the initial soil water content. The transition from organized flow to the situation in which fluxes are dominated by noncoherent turbulent eddies under a calm mean wind is quantitatively evaluated and this transition is different for different variables. The relationship between the predictability of a realization and of an ensemble average is discussed. The predictability and the coherent circulations modulated by the surface inhomogeneities are also studied by computing the autocorrelations and the power spectra. The three-dimensional mesoscale and large-eddy simulations are performed to verify the above results. It is found that the two-dimensional mesoscale (or fine resolution) simulation yields very close or similar results regarding the predictability as those from the three-dimensional mesoscale (or large eddy) simulation. The horizontally averaged quantities based on two-dimensional fine-resolution simulations are insensitive to initial perturbations and agree with those based on three-dimensional large-eddy simulations. 87 refs., 25 figs.« less

Non-Gaussianity of the cosmic infrared background anisotropies - II. Predictions of the bispectrum and constraints forecast

NASA Astrophysics Data System (ADS)

Pénin, A.; Lacasa, F.; Aghanim, N.

2014-03-01

Using a full analytical computation of the bispectrum based on the halo model together with the halo occupation number, we derive the bispectrum of the cosmic infrared background (CIB) anisotropies that trace the clustering of dusty-star-forming galaxies. We focus our analysis on wavelengths in the far-infrared and the sub-millimeter typical of the Planck/HFI and Herschel/SPIRE instruments, 350, 550, 850 and 1380 μm. We explore the bispectrum behaviour as a function of several models of evolution of galaxies and show that it is strongly sensitive to that ingredient. Contrary to the power spectrum, the bispectrum, at the four wavelengths, seems dominated by low-redshift galaxies. Such a contribution can be hardly limited by applying low flux cuts. We also discuss the contributions of halo mass as a function of the redshift and the wavelength, recovering that each term is sensitive to a different mass range. Furthermore, we show that the CIB bispectrum is a strong contaminant of the cosmic microwave background bispectrum at 850 μm and higher. Finally, a Fisher analysis of the power spectrum, bispectrum alone and of the combination of both shows that degeneracies on the halo occupation distribution parameters are broken by including the bispectrum information, leading to tight constraints even when including foreground residuals.

Fluid-Plasma-Combustion Coupling Effects on the Ignition of a Fuel Jet

NASA Astrophysics Data System (ADS)

Massa, Luca; Freund, Jonathan

2016-11-01

We analyze the effect of plasma-combustion coupling on the ignition and flame supported by a DBD interacting with a jet of H2 in a air cross-flow. We propose that plasma-combustion coupling is due to the strong temperature-dependence of specific collisional energy loss as predicted by the Boltzmann equation, and that e- transport can be modeled by assuming a form for the E-field pulse in microstreamers. We introduce a two-way coupling based on the Boltzmann equation and the charged species conservation. The addition of this mechanism to a hydrogen combustion scheme leads to an improvement of the ignition prediction and of the understanding of the effect of the plasma on the flow. The key points of the analysis are 1) explanation of the mechanism for the two-stage ignition and quenching observed experimentally, 2) explanation of the existence of a power threshold above which the plasma is beneficial to the ignition probability, 3) understanding of the increase in power absorbed by the plasma in burning conditions and the reduction in power absorbed with an increase in the cross velocity, 4) explanation of the non-symmetric emissions and the increase in luminescence at the rotovibrational H2O band. The model is validated in part against air-H2 flow experiments. This material is based in part upon work supported by the Department of Energy, National Nuclear Security Administration, under Award Number DE-NA0002374.

The neoclassical ``Electron Root'' feature in the Wendelstein-7-AS stellarator

NASA Astrophysics Data System (ADS)

Maaßberg, H.; Beidler, C. D.; Gasparino, U.; Romé, M.; Dyabilin, K. S.; Marushchenko, N. B.; Murakami, S.

2000-01-01

The neoclassical prediction of the "electron root," i.e., a strongly positive radial electric field, Er (being the solution of the ambipolarity condition of the particle fluxes), is analyzed for low-density discharges in Wendelstein-7-AS [G. Grieger, W. Lotz, P. Merkel, et al., Phys. Fluids B 4, 2081 (1992)]. In these electron cyclotron resonance heated (ECRH) discharges with highly localized central power deposition, peaked Te profiles [with Te(0) up to 6 keV and with Ti≪Te] and strongly positive Er in the central region are measured. It is shown that this "electron root" feature at W7-AS is driven by ripple-trapped suprathermal electrons generated by the ECRH. The fraction of ripple-trapped particles in the ECRH launching plane, which can be varied at W7-AS, is found to be the most important. After switching off the heating the "electron root" feature disappears nearly immediately, i.e., two different time scales for the electron temperature decay in the central region are observed. Monte Carlo simulations in five-dimensional phase space are presented, clearly indicating that the additional "convective" electron fluxes driven by the ECRH are of the same order as the ambipolar neoclassical prediction for the "ion root" at much lower Er. For the predicted "electron root," the ion fluxes calculated based on the traditional neoclassical ordering are much too small; shortcomings of the usual approach are indentified and a new ordering scheme is proposed.

Low Power Magnetic Bearing Design for High Speed Rotating Machinery

NASA Technical Reports Server (NTRS)

Allaire, P. E.; Maslen, E. H.; Humphris, R. R.; Sortore, C. K.; Studer, P. A.

1992-01-01

Magnetic suspension technology has advanced to the point of being able to offer a number of advantages to a variety of applications in the rotating machinery and aerospace fields. One strong advantage is the decrease in power consumption. The design and construction of a set of permanent magnet biased, actively controlled magnetic bearing for a flexible rotor are presented. Both permanent magnets and electromagnets are used in a configuration which effectively provides the necessary fluxes in the appropriate air gaps, while simultaneously keeping the undesirable destabilizing forces to a minimum. The design includes two radial bearings and a thrust bearing. The theoretical development behind the design is briefly discussed. Experimental performance results for a set of operating prototype bearings is presented. The results include measurements of load capacity, bearing stiffness and damping, and the dynamic response of the rotor. With few exceptions, the experimental results matched very well with the predicted performance. The power consumption of these bearings was found to be significantly reduced from that for a comparable set of all electromagnetic bearings.

Ground state energies from converging and diverging power series expansions

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

Lisowski, C.; Norris, S.; Pelphrey, R.

2016-10-15

It is often assumed that bound states of quantum mechanical systems are intrinsically non-perturbative in nature and therefore any power series expansion methods should be inapplicable to predict the energies for attractive potentials. However, if the spatial domain of the Schrödinger Hamiltonian for attractive one-dimensional potentials is confined to a finite length L, the usual Rayleigh–Schrödinger perturbation theory can converge rapidly and is perfectly accurate in the weak-binding region where the ground state’s spatial extension is comparable to L. Once the binding strength is so strong that the ground state’s extension is less than L, the power expansion becomes divergent,more » consistent with the expectation that bound states are non-perturbative. However, we propose a new truncated Borel-like summation technique that can recover the bound state energy from the diverging sum. We also show that perturbation theory becomes divergent in the vicinity of an avoided-level crossing. Here the same numerical summation technique can be applied to reproduce the energies from the diverging perturbative sums.« less

Uncertain future, non-numeric preferences, and the fertility transition: A case study of rural Mozambique

PubMed Central

Hayford, Sarah R.; Agadjanian, Victor

2012-01-01

In many high-fertility countries, and especially in sub-Saharan Africa, substantial proportions of women give non-numeric responses when asked about desired family size. Demographic transition theory has interpreted responses of “don’t know” or “up to God” as evidence of fatalistic attitudes toward childbearing. Alternatively, these responses can be understood as meaningful reactions to uncertainty about the future. Following this latter approach, we use data from rural Mozambique to test the hypothesis that non-numeric responses are more common when uncertainty about the future is greater. We expand on previous research linking child mortality and non-numeric fertility preferences by testing the predictive power of economic conditions, marital instability, and adult mortality. Results show that uncertainty related to adult and child mortality and to economic conditions predicts non-numeric responses, while marital stability is less strongly related. PMID:26430294

Popularity versus similarity in growing networks

NASA Astrophysics Data System (ADS)

Krioukov, Dmitri; Papadopoulos, Fragkiskos; Kitsak, Maksim; Serrano, Mariangeles; Boguna, Marian

2012-02-01

Preferential attachment is a powerful mechanism explaining the emergence of scaling in growing networks. If new connections are established preferentially to more popular nodes in a network, then the network is scale-free. Here we show that not only popularity but also similarity is a strong force shaping the network structure and dynamics. We develop a framework where new connections, instead of preferring popular nodes, optimize certain trade-offs between popularity and similarity. The framework admits a geometric interpretation, in which preferential attachment emerges from local optimization processes. As opposed to preferential attachment, the optimization framework accurately describes large-scale evolution of technological (Internet), social (web of trust), and biological (E.coli metabolic) networks, predicting the probability of new links in them with a remarkable precision. The developed framework can thus be used for predicting new links in evolving networks, and provides a different perspective on preferential attachment as an emergent phenomenon.

Uncertain future, non-numeric preferences, and the fertility transition: A case study of rural Mozambique.

PubMed

Hayford, Sarah R; Agadjanian, Victor

In many high-fertility countries, and especially in sub-Saharan Africa, substantial proportions of women give non-numeric responses when asked about desired family size. Demographic transition theory has interpreted responses of "don't know" or "up to God" as evidence of fatalistic attitudes toward childbearing. Alternatively, these responses can be understood as meaningful reactions to uncertainty about the future. Following this latter approach, we use data from rural Mozambique to test the hypothesis that non-numeric responses are more common when uncertainty about the future is greater. We expand on previous research linking child mortality and non-numeric fertility preferences by testing the predictive power of economic conditions, marital instability, and adult mortality. Results show that uncertainty related to adult and child mortality and to economic conditions predicts non-numeric responses, while marital stability is less strongly related.

Intrinsic two-dimensional features as textons

NASA Technical Reports Server (NTRS)

Barth, E.; Zetzsche, C.; Rentschler, I.

1998-01-01

We suggest that intrinsic two-dimensional (i2D) features, computationally defined as the outputs of nonlinear operators that model the activity of end-stopped neurons, play a role in preattentive texture discrimination. We first show that for discriminable textures with identical power spectra the predictions of traditional models depend on the type of nonlinearity and fail for energy measures. We then argue that the concept of intrinsic dimensionality, and the existence of end-stopped neurons, can help us to understand the role of the nonlinearities. Furthermore, we show examples in which models without strong i2D selectivity fail to predict the correct ranking order of perceptual segregation. Our arguments regarding the importance of i2D features resemble the arguments of Julesz and co-workers regarding textons such as terminators and crossings. However, we provide a computational framework that identifies textons with the outputs of nonlinear operators that are selective to i2D features.

Analytical modeling of eddy-current losses caused by pulse-width-modulation switching in permanent-magnet brushless direct-current motors

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

Deng, F.; Nehl, T.W.

1998-09-01

Because of their high efficiency and power density the PM brushless dc motor is a strong candidate for electric and hybrid vehicle propulsion systems. An analytical approach is developed to predict the inverter high frequency pulse width modulation (PWM) switching caused eddy-current losses in a permanent magnet brushless dc motor. The model uses polar coordinates to take curvature effects into account, and is also capable of including the space harmonic effect of the stator magnetic field and the stator lamination effect on the losses. The model was applied to an existing motor design and was verified with the finite elementmore » method. Good agreement was achieved between the two approaches. Hence, the model is expected to be very helpful in predicting PWM switching losses in permanent magnet machine design.« less

Power maximization of a point absorber wave energy converter using improved model predictive control

NASA Astrophysics Data System (ADS)

Milani, Farideh; Moghaddam, Reihaneh Kardehi

2017-08-01

This paper considers controlling and maximizing the absorbed power of wave energy converters for irregular waves. With respect to physical constraints of the system, a model predictive control is applied. Irregular waves' behavior is predicted by Kalman filter method. Owing to the great influence of controller parameters on the absorbed power, these parameters are optimized by imperialist competitive algorithm. The results illustrate the method's efficiency in maximizing the extracted power in the presence of unknown excitation force which should be predicted by Kalman filter.

Contribution of strong discontinuities to the power spectrum of the solar wind.

PubMed

Borovsky, Joseph E

2010-09-10

Eight and a half years of magnetic field measurements (2(22) samples) from the ACE spacecraft in the solar wind at 1 A.U. are analyzed. Strong (large-rotation-angle) discontinuities in the solar wind are collected and measured. An artificial time series is created that preserves the timing and amplitudes of the discontinuities. The power spectral density of the discontinuity series is calculated and compared with the power spectral density of the solar-wind magnetic field. The strong discontinuities produce a power-law spectrum in the "inertial subrange" with a spectral index near the Kolmogorov -5/3 index. The discontinuity spectrum contains about half of the power of the full solar-wind magnetic field over this "inertial subrange." Warnings are issued about the significant contribution of discontinuities to the spectrum of the solar wind, complicating interpretation of spectral power and spectral indices.

Search for an X-ray identification of a strong gamma-ray source. [sas-3 observations

NASA Technical Reports Server (NTRS)

Lamb, R. C.

1979-01-01

X-rays from Cygnus X-3 were observed during early 1978 with the detectors of the SAS-3 satellite. These observations in conjunction with earlier UHURU and ANS data indicate that the 4.8 hr period of Cygnus X-3 is increasing at the rate of P/P = (5/1 plus or minus 1.3) x 10 to the minus 6 power/1 yr. The sign and magnitude for this change are incompatible with a rotation model for the period and are in reasonable agreement with model predictions for orbital changes associated with mass loss and transfer in a binary system.

Impact of ionization equilibrium on electrokinetic flow of weak electrolytes in nanochannels

NASA Astrophysics Data System (ADS)

Ji, Ziwei; Huang, Zhuo; Chen, Bowei; He, Yuhui; Tsutsui, Makusu; Miao, Xiangshui

2018-07-01

Weak electrolyte transport in nanochannels or nanopores has been actively explored in recent experiments. In this paper, we establish a new electrokinetic model where the ionization balance effect of weak electrolytes is outlined, and performed numerical calculations for H3PO4 concentration-biased nanochannel systems. By considering the roles of local chemical equilibrium in phosphorous acid ionization, the simulation results show quantitative agreement with experimental observations. Based on the model, we predict that enhanced energy harvesting capacity could be accomplished by utilizing weak electrolytes compared to the conventional strong electrolyte approaches in a concentration gradient-based power-generating system.

The Exciton-Polariton Dispersion Law under the Action of Strong Pumping in the Region of the M-Band of Luminescence

NASA Astrophysics Data System (ADS)

Khadzhi, P. I.; Nad'kin, L. Yu.; Markov, D. A.

2018-04-01

The double-pulse interaction with excitons and biexcitons in semiconductors is studied theoretically. It is shown that the dispersion law of carrier wave has three branches under the action of a powerful pumping in the region of the M-band of luminescence. Values of parameters at which the dispersion law branches can intersect due to the degeneration of the exciton level energy have been found. The effect of a significant change in the force of coupling between the exciton and photon of a weak pulse with a change in the pumping intensity is predicted.

First results from the IllustrisTNG simulations: matter and galaxy clustering

NASA Astrophysics Data System (ADS)

Springel, Volker; Pakmor, Rüdiger; Pillepich, Annalisa; Weinberger, Rainer; Nelson, Dylan; Hernquist, Lars; Vogelsberger, Mark; Genel, Shy; Torrey, Paul; Marinacci, Federico; Naiman, Jill

2018-03-01

Hydrodynamical simulations of galaxy formation have now reached sufficient volume to make precision predictions for clustering on cosmologically relevant scales. Here, we use our new IllustrisTNG simulations to study the non-linear correlation functions and power spectra of baryons, dark matter, galaxies, and haloes over an exceptionally large range of scales. We find that baryonic effects increase the clustering of dark matter on small scales and damp the total matter power spectrum on scales up to k ˜ 10 h Mpc-1 by 20 per cent. The non-linear two-point correlation function of the stellar mass is close to a power-law over a wide range of scales and approximately invariant in time from very high redshift to the present. The two-point correlation function of the simulated galaxies agrees well with Sloan Digital Sky Survey at its mean redshift z ≃ 0.1, both as a function of stellar mass and when split according to galaxy colour, apart from a mild excess in the clustering of red galaxies in the stellar mass range of109-1010 h-2 M⊙. Given this agreement, the TNG simulations can make valuable theoretical predictions for the clustering bias of different galaxy samples. We find that the clustering length of the galaxy autocorrelation function depends strongly on stellar mass and redshift. Its power-law slope γ is nearly invariant with stellar mass, but declines from γ ˜ 1.8 at redshift z = 0 to γ ˜ 1.6 at redshift z ˜ 1, beyond which the slope steepens again. We detect significant scale dependences in the bias of different observational tracers of large-scale structure, extending well into the range of the baryonic acoustic oscillations and causing nominal (yet fortunately correctable) shifts of the acoustic peaks of around ˜ 5 per cent.

A study of the vibrational energies of two coupled beams by finite element and green function (receptance) methods

NASA Astrophysics Data System (ADS)

Shankar, K.; Keane, A. J.

1995-04-01

The behaviour of two hinged-hinged beams, point coupled by springs (translational, rotary and a combination of both) with weak to strong coupling is studied from the point of view of vibrational energies, input power and power transferred through the coupling. Two configurations are studied: in the first case the beams are placed parallel to each other and only the transverse, Euler-Bernoulli modes are considered; the second configuration is more complicated with the beams placed perpendicular to each other, executing axial as well as transverse vibrations. These models are studied by using a finite element analysis (FEA) package and, alternatively, via the modally derived Green functions of the uncoupled subsystems. In both cases the beams are given proportional damping and one of the beams is driven by a point harmonic force. The effects of coupling stiffness and modal summation bandwidth are studied. It is shown that there is good agreement between the FEA and the Green function approach over a range of coupling strengths, but that at higher strengths the number of uncoupled modes used significantly affects the accuracy of the Green function method used here. The beams in the second configuration are then further studied from the point of view of SEA coupling loss factors. The frequency averaged coupling loss factors are calculated for weak and strong coupling, first by using a power injection method, where the power balance equations are formed on the assumption of only direct coupling loss factors. Then, the entire matrix of direct and indirect coupling loss factors is derived by using a deterministic modal approach. These are compared and the indirect coupling loss factors are found to be significant in magnitude in respect to the direct coupling loss factors. Several cases are studied in which the coupling powers and energy levels are predicted by using only the direct coupling loss factors and compared with the exact results obtained by using both direct and indirect factors. These agree only under certain conditions for weak coupling and show rather poorer agreement in the case of strong coupling. This behaviour demonstrates the importance of taking into account indirect coupling loss factors in SEA models having several subsystems.

Statistical aspects of radiogenomics: can radiogenomics models be used to aid prediction of outcomes in cancer patients?

NASA Astrophysics Data System (ADS)

Ren, Boya; Mazurowski, Maciej A.

2017-03-01

Radiogenomics is a new direction in cancer research that aims at identifying the relationship between tumor genomics and its appearance in imaging (i.e. its radiophenotype). Recent years brought multiple radiogenomic discoveries in brain, breast, lung, and other cancers. With development of this new field we believe that it important to investigate in which setting radiogenomics could be useful to better direct research effort. One of the general applications of radiogenomics is to generate imaging-based models for prediction of outcomes and doing so through modeling the relationship between imaging and genomics and the relationship between genomics and outcomes. We believe that this is an important potential application of radiogenomic as it could advance imaging-based precision medicine. We show a preliminary simulation study evaluation whether such approach results in improved models. We investigate different setting in terms of the strengths of the radiogenomic relationship, prognostic power of the imaging and genomic descriptors, and availability and quality of data. Our experiments indicated that the following parameters have impact on usefulness of the radiogenomic approach: predictive power of genomic features and imaging features, strength of the radiogenomic relationship as well as number and follow up time for the genomic data. Overall, we found that there are some situations in which radiogenomics approach is beneficial but only when the radiogenomic relationship is strong and low number of imaging cases with outcomes data are available.

Evidence for large inversion polymorphisms in the human genome from HapMap data

PubMed Central

Bansal, Vikas; Bashir, Ali; Bafna, Vineet

2007-01-01

Knowledge about structural variation in the human genome has grown tremendously in the past few years. However, inversions represent a class of structural variation that remains difficult to detect. We present a statistical method to identify large inversion polymorphisms using unusual Linkage Disequilibrium (LD) patterns from high-density SNP data. The method is designed to detect chromosomal segments that are inverted (in a majority of the chromosomes) in a population with respect to the reference human genome sequence. We demonstrate the power of this method to detect such inversion polymorphisms through simulations done using the HapMap data. Application of this method to the data from the first phase of the International HapMap project resulted in 176 candidate inversions ranging from 200 kb to several megabases in length. Our predicted inversions include an 800-kb polymorphic inversion at 7p22, a 1.1-Mb inversion at 16p12, and a novel 1.2-Mb inversion on chromosome 10 that is supported by the presence of two discordant fosmids. Analysis of the genomic sequence around inversion breakpoints showed that 11 predicted inversions are flanked by pairs of highly homologous repeats in the inverted orientation. In addition, for three candidate inversions, the inverted orientation is represented in the Celera genome assembly. Although the power of our method to detect inversions is restricted because of inherently noisy LD patterns in population data, inversions predicted by our method represent strong candidates for experimental validation and analysis. PMID:17185644

Development and design of photovoltaic power prediction system

NASA Astrophysics Data System (ADS)

Wang, Zhijia; Zhou, Hai; Cheng, Xu

2018-02-01

In order to reduce the impact of power grid safety caused by volatility and randomness of the energy produced in photovoltaic power plants, this paper puts forward a construction scheme on photovoltaic power generation prediction system, introducing the technical requirements, system configuration and function of each module, and discussing the main technical features of the platform software development. The scheme has been applied in many PV power plants in the northwest of China. It shows that the system can produce reasonable prediction results, providing a right guidance for dispatching and efficient running for PV power plant.

Beating the news using social media: the case study of American Idol

NASA Astrophysics Data System (ADS)

Ciulla, Fabio; Mocanu, Delia; Baronchelli, Andrea; Goncalves, Bruno; Perra, Nicola; Vespignani, Alessandro

2013-03-01

We present a contribution to the debate on the predictability of social events using big data analytics. We focus on the elimination of contestants in the American Idol TV shows as an example of a well defined electoral phenomenon to assess the predictive power of twitter signals. We provide evidence that Twitter activity during the time span defined by the TV show airing and the voting period following it allows the anticipation of the voting outcome. Twitter data have been analyzed to attempt the winner prediction ahead of the airing of the official result. We also show that the fraction of Tweets that contain geolocation information allows us to map the fanbase of each contestant, both within the US and abroad, showing that strong regional polarizations occur. The geolocalized data are crucial for the correct prediction of the final outcome of the show, pointing out the importance of considering information beyond the aggregated twitter signal. Although American Idol voting is just a minimal and simplified version of complex societal phenomena, this work shows that the volume of information available in online systems permits the real time gathering of quantitative indicators that may be able to anticipate the future unfolding of opinion formation events.

Systems-based biological concordance and predictive reproducibility of gene set discovery methods in cardiovascular disease.

PubMed

Azuaje, Francisco; Zheng, Huiru; Camargo, Anyela; Wang, Haiying

2011-08-01

The discovery of novel disease biomarkers is a crucial challenge for translational bioinformatics. Demonstration of both their classification power and reproducibility across independent datasets are essential requirements to assess their potential clinical relevance. Small datasets and multiplicity of putative biomarker sets may explain lack of predictive reproducibility. Studies based on pathway-driven discovery approaches have suggested that, despite such discrepancies, the resulting putative biomarkers tend to be implicated in common biological processes. Investigations of this problem have been mainly focused on datasets derived from cancer research. We investigated the predictive and functional concordance of five methods for discovering putative biomarkers in four independently-generated datasets from the cardiovascular disease domain. A diversity of biosignatures was identified by the different methods. However, we found strong biological process concordance between them, especially in the case of methods based on gene set analysis. With a few exceptions, we observed lack of classification reproducibility using independent datasets. Partial overlaps between our putative sets of biomarkers and the primary studies exist. Despite the observed limitations, pathway-driven or gene set analysis can predict potentially novel biomarkers and can jointly point to biomedically-relevant underlying molecular mechanisms. Copyright © 2011 Elsevier Inc. All rights reserved.

Unified force-level theory of multiscale transient localization and emergent elasticity in polymer solutions and melts

NASA Astrophysics Data System (ADS)

Dell, Zachary E.; Schweizer, Kenneth S.

A unified, microscopic, theoretical understanding of polymer dynamics in concentrated liquids from segmental to macromolecular scales remains an open problem. We have formulated a statistical mechanical theory for this problem that explicitly accounts for intra- and inter-molecular forces at the Kuhn segment level. The theory is self-consistently closed at the level of a matrix of dynamical second moments of a tagged chain. Two distinct regimes of isotropic transient localization are predicted. In semidilute solutions, weak localization is predicted on a mesoscopic length scale between segment and chain scales which is a power law function of the invariant packing length. This is consistent with the breakdown of Rouse dynamics and the emergence of entanglements. The chain structural correlations in the dynamically arrested state are also computed. In dense melts, strong localization is predicted on a scale much smaller than the segment size which is weakly dependent on chain connectivity and signals the onset of glassy dynamics. Predictions of the dynamic plateau shear modulus are consistent with the known features of emergent rubbery and glassy elasticity. Generalizations to treat the effects of chemical crosslinking and physical bond formation in polymer gels are possible.

Managing PV Power on Mars - MER Rovers

NASA Technical Reports Server (NTRS)

Stella, Paul M.; Chin, Keith; Wood, Eric; Herman, Jennifer; Ewell, Richard

2009-01-01

The MER Rovers have recently completed over 5 years of operation! This is a remarkable demonstration of the capabilities of PV power on the Martian surface. The extended mission required the development of an efficient process to predict the power available to the rovers on a day-to-day basis. The performance of the MER solar arrays is quite unlike that of any other Space array and perhaps more akin to Terrestrial PV operation, although even severe by that comparison. The impact of unpredictable factors, such as atmospheric conditions and dust accumulation (and removal) on the panels limits the accurate prediction of array power to short time spans. Based on the above, it is clear that long term power predictions are not sufficiently accurate to allow for detailed long term planning. Instead, the power assessment is essentially a daily activity, effectively resetting the boundary points for the overall predictive power model. A typical analysis begins with the importing of the telemetry from each rover's previous day's power subsystem activities. This includes the array power generated, battery state-of-charge, rover power loads, and rover orientation, all as functions of time. The predicted performance for that day is compared to the actual performance to identify the extent of any differences. The model is then corrected for these changes. Details of JPL's MER power analysis procedure are presented, including the description of steps needed to provide the final prediction for the mission planners. A dust cleaning event of the solar array is also highlighted to illustrate the impact of Martian weather on solar array performance

NASA's Prediction Of Worldwide Energy Resource (POWER) Project Unveils a New Geospatial Data Portal

Atmospheric Science Data Center

2018-03-16

NASA's Prediction Of Worldwide Energy Resource (POWER) Project Unveils a New Geospatial Data Portal ... current POWER home page. The new POWER will include improved solar and meteorological data with all parameters available on a 0.5-degree ...

Swift, XMM-Newton, and NuSTAR Observations of PSR J2032+4127/MT91 213

NASA Astrophysics Data System (ADS)

Li, K. L.; Kong, A. K. H.; Tam, P. H. T.; Hou, X.; Takata, J.; Hui, C. Y.

2017-07-01

We report our recent Swift, NuSTAR, and XMM-Newton X-ray and Lijiang optical observations on PSR J2032+4127/MT91 213, the γ-ray binary candidate with a period of 45-50 years. The coming periastron of the system was predicted to be in 2017 November, around which high-energy flares from keV to TeV are expected. Recent studies with Chandra and Swift X-ray observations taken in 2015/2016 showed that its X-ray emission has been brighter by a factors of ˜10 than that before 2013, probably revealing some ongoing activities between the pulsar wind and the stellar wind. Our new Swift/XRT lightcurve shows no strong evidence of a single vigorous brightening trend, but rather several strong X-ray flares on weekly to monthly timescales with a slowly brightening baseline, namely the low state. The NuSTAR and XMM-Newton observations taken during the flaring and the low states, respectively, show a denser environment and a softer power-law index during the flaring state, implying that the pulsar wind interacted with the stronger stellar winds of the companion to produce the flares. These precursors would be crucial in studying the predicted giant outburst from this extreme γ-ray binary during the periastron passage in late 2017.

Communal and Agentic Interpersonal and Intergroup Motives Predict Preferences for Status Versus Power.

PubMed

Locke, Kenneth D; Heller, Sonja

2017-01-01

Seven studies involving 1,343 participants showed how circumplex models of social motives can help explain individual differences in preferences for status (having others' admiration) versus power (controlling valuable resources). Studies 1 to 3 and 7 concerned interpersonal motives in workplace contexts, and found that stronger communal motives (to have mutual trust, support, and cooperation) predicted being more attracted to status (but not power) and achieving more workplace status, while stronger agentic motives (to be firm, decisive, and influential) predicted being more attracted to and achieving more workplace power, and experiencing a stronger connection between workplace power and job satisfaction. Studies 4 to 6 found similar effects for intergroup motives: Stronger communal motives predicted wanting one's ingroup (e.g., country) to have status-but not power-relative to other groups. Finally, most people preferred status over power, and this was especially true for women, which was partially explained by women having stronger communal motives.

El-Niño/Southern Oscillation (ENSO) influences on monthly NO 3 load and concentration, stream flow and precipitation in the Little River Watershed, Tifton, Georgia (GA)

NASA Astrophysics Data System (ADS)

Keener, V. W.; Feyereisen, G. W.; Lall, U.; Jones, J. W.; Bosch, D. D.; Lowrance, R.

2010-02-01

SummaryAs climate variability increases, it is becoming increasingly critical to find predictable patterns that can still be identified despite overall uncertainty. The El-Niño/Southern Oscillation is the best known pattern. Its global effects on weather, hydrology, ecology and human health have been well documented. Climate variability manifested through ENSO has strong effects in the southeast United States, seen in precipitation and stream flow data. However, climate variability may also affect water quality in nutrient concentrations and loads, and have impacts on ecosystems, health, and food availability in the southeast. In this research, we establish a teleconnection between ENSO and the Little River Watershed (LRW), GA., as seen in a shared 3-7 year mode of variability for precipitation, stream flow, and nutrient load time series. Univariate wavelet analysis of the NINO 3.4 index of sea surface temperature (SST) and of precipitation, stream flow, NO 3 concentration and load time series from the watershed was used to identify common signals. Shared 3-7 year modes of variability were seen in all variables, most strongly in precipitation, stream flow and nutrient load in strong El Niño years. The significance of shared 3-7 year periodicity over red noise with 95% confidence in SST and precipitation, stream flow, and NO 3 load time series was confirmed through cross-wavelet and wavelet-coherence transforms, in which common high power and co-variance were computed for each set of data. The strongest 3-7 year shared power was seen in SST and stream flow data, while the strongest co-variance was seen in SST and NO 3 load data. The strongest cross-correlation was seen as a positive value between the NINO 3.4 and NO 3 load with a three-month lag. The teleconnection seen in the LRW between the NINO 3.4 index and precipitation, stream flow, and NO 3 load can be utilized in a model to predict monthly nutrient loads based on short-term climate variability, facilitating management in high risk seasons.

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.

Measured vs. Predicted Pedestal Pressure During RMP ELM Control in DIII-D

NASA Astrophysics Data System (ADS)

Zywicki, Bailey; Fenstermacher, Max; Groebner, Richard; Meneghini, Orso

2017-10-01

From database analysis of DIII-D plasmas with Resonant Magnetic Perturbations (RMPs) for ELM control, we will compare the experimental pedestal pressure (p_ped) to EPED code predictions and present the dependence of any p_ped differences from EPED on RMP parameters not included in the EPED model e.g. RMP field strength, toroidal and poloidal spectrum etc. The EPED code, based on Peeling-Ballooning and Kinetic Ballooning instability constraints, will also be used by ITER to predict the H-mode p_ped without RMPs. ITER plans to use RMPs as an effective ELM control method. The need to control ELMs in ITER is of the utmost priority, as it directly correlates to the lifetime of the plasma facing components. An accurate means of determining the impact of RMP ELM control on the p_ped is needed, because the device fusion power is strongly dependent on p_ped. With this new collection of data, we aim to provide guidance to predictions of the ITER pedestal during RMP ELM control that can be incorporated in a future predictive code. Work supported in part by US DoE under the Science Undergraduate Laboratory Internship (SULI) program and under DE-FC02-04ER54698, and DE-AC52-07NA27344.

Fatty Liver Index and Lipid Accumulation Product Can Predict Metabolic Syndrome in Subjects without Fatty Liver Disease

PubMed Central

Cheng, Yuan-Lung; Wang, Yuan-Jen; Lan, Keng-Hsin; Huo, Teh-Ia; Hsieh, Wei-Yao; Hou, Ming-Chih; Lee, Fa-Yauh; Wu, Jaw-Ching; Lee, Shou-Dong

2017-01-01

Background. Fatty liver index (FLI) and lipid accumulation product (LAP) are indexes originally designed to assess the risk of fatty liver and cardiovascular disease, respectively. Both indexes have been proven to be reliable markers of subsequent metabolic syndrome; however, their ability to predict metabolic syndrome in subjects without fatty liver disease has not been clarified. Methods. We enrolled consecutive subjects who received health check-up services at Taipei Veterans General Hospital from 2002 to 2009. Fatty liver disease was diagnosed by abdominal ultrasonography. The ability of the FLI and LAP to predict metabolic syndrome was assessed by analyzing the area under the receiver operating characteristic (AUROC) curve. Results. Male sex was strongly associated with metabolic syndrome, and the LAP and FLI were better than other variables to predict metabolic syndrome among the 29,797 subjects. Both indexes were also better than other variables to detect metabolic syndrome in subjects without fatty liver disease (AUROC: 0.871 and 0.879, resp.), and the predictive power was greater among women. Conclusion. Metabolic syndrome increases the cardiovascular disease risk. The FLI and LAP could be used to recognize the syndrome in both subjects with and without fatty liver disease who require lifestyle modifications and counseling. PMID:28194177

Predicting energy expenditure through hand rim propulsion power output in individuals who use wheelchairs.

PubMed

Conger, Scott A; Scott, Stacy N; Bassett, David R

2014-07-01

To examine the relationship between hand rim propulsion power and energy expenditure (EE) during wheelchair wheeling and to investigate whether adding other variables to the model could improve on the prediction of EE. Individuals who use manual wheelchairs (n=14) performed five different wheeling activities in a wheelchair with a PowerTap power meter hub built into the right rear wheel. Activities included wheeling on a smooth, level surface at three different speeds (4.5, 5.5 and 6.5 km/h), wheeling on a rubberised track at one speed (5.5 km/h) and wheeling on a sidewalk course that included uphill and downhill segments at a self-selected speed. EE was measured using a portable indirect calorimetry system. Stepwise linear regression was performed to predict EE from power output variables. A repeated-measures analysis of variance was used to compare the measured EE to the estimates from the power models. Bland-Altman plots were used to assess the agreement between the criterion values and the predicted values. EE and power were significantly correlated (r=0.694, p<0.001). Regression analysis yielded three significant prediction models utilising measured power; measured power and speed; and measured power, speed and heart rate. No significant differences were found between measured EE and any of the prediction models. EE can be accurately and precisely estimated based on hand rim propulsion power. These results indicate that power could be used as a method to assess EE in individuals who use wheelchairs. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Conditional power and predictive power based on right censored data with supplementary auxiliary information.

PubMed

Sun, Libo; Wan, Ying

2018-04-22

Conditional power and predictive power provide estimates of the probability of success at the end of the trial based on the information from the interim analysis. The observed value of the time to event endpoint at the interim analysis could be biased for the true treatment effect due to early censoring, leading to a biased estimate of conditional power and predictive power. In such cases, the estimates and inference for this right censored primary endpoint are enhanced by incorporating a fully observed auxiliary variable. We assume a bivariate normal distribution of the transformed primary variable and a correlated auxiliary variable. Simulation studies are conducted that not only shows enhanced conditional power and predictive power but also can provide the framework for a more efficient futility interim analysis in terms of an improved accuracy in estimator, a smaller inflation in type II error and an optimal timing for such analysis. We also illustrated the new approach by a real clinical trial example. Copyright © 2018 John Wiley & Sons, Ltd.

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.

Predictive ability of a comprehensive incremental test in mountain bike marathon.

PubMed

Ahrend, Marc-Daniel; Schneeweiss, Patrick; Martus, Peter; Niess, Andreas M; Krauss, Inga

2018-01-01

Traditional performance tests in mountain bike marathon (XCM) primarily quantify aerobic metabolism and may not describe the relevant capacities in XCM. We aimed to validate a comprehensive test protocol quantifying its intermittent demands. Forty-nine athletes (38.8±9.1 years; 38 male; 11 female) performed a laboratory performance test, including an incremental test, to determine individual anaerobic threshold (IAT), peak power output (PPO) and three maximal efforts (10 s all-out sprint, 1 min maximal effort and 5 min maximal effort). Within 2 weeks, the athletes participated in one of three XCM races (n=15, n=9 and n=25). Correlations between test variables and race times were calculated separately. In addition, multiple regression models of the predictive value of laboratory outcomes were calculated for race 3 and across all races (z-transformed data). All variables were correlated with race times 1, 2 and 3: 10 s all-out sprint (r=-0.72; r=-0.59; r=-0.61), 1 min maximal effort (r=-0.85; r=-0.84; r=-0.82), 5 min maximal effort (r=-0.57; r=-0.85; r=-0.76), PPO (r=-0.77; r=-0.73; r=-0.76) and IAT (r=-0.71; r=-0.67; r=-0.68). The best-fitting multiple regression models for race 3 (r 2 =0.868) and across all races (r 2 =0.757) comprised 1 min maximal effort, IAT and body weight. Aerobic and intermittent variables correlated least strongly with race times. Their use in a multiple regression model confirmed additional explanatory power to predict XCM performance. These findings underline the usefulness of the comprehensive incremental test to predict performance in that sport more precisely.

The prediction of the impact of climatic factors on short-term electric power load based on the big data of smart city

NASA Astrophysics Data System (ADS)

Qiu, Yunfei; Li, Xizhong; Zheng, Wei; Hu, Qinghe; Wei, Zhanmeng; Yue, Yaqin

2017-08-01

The climate changes have great impact on the residents’ electricity consumption, so the study on the impact of climatic factors on electric power load is of significance. In this paper, the effects of the data of temperature, rainfall and wind of smart city on short-term power load is studied to predict power load. The authors studied the relation between power load and daily temperature, rainfall and wind in the 31 days of January of one year. In the research, the authors used the Matlab neural network toolbox to establish the combinational forecasting model. The authors trained the original input data continuously to get the internal rules inside the data and used the rules to predict the daily power load in the next January. The prediction method relies on the accuracy of weather forecasting. If the weather forecasting is different from the actual weather, we need to correct the climatic factors to ensure accurate prediction.

A search for jet handedness in hadronic Z{sup 0} decays

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

Hasegawa, Yoji

1995-03-01

Transport of polarization through hadronization process is one of the fundamental interest in Quantum Chromodynamics which is a theory of strong interactions. In the low energy region where the hadronization occurs, QCD calculations are difficult, therefore at present the transport can be investigated experimentally. In this study the authors have searched for signatures of polarization of quarks and antiquarks in hadronic jets from Z{sup 0} {yields} q{bar q} decays. The polarization of quarks and antiquark produced by Z{sup 0} decays are predicted by the Standard Model of elementary particle physics. The authors defined several quantities depending on {open_quotes}jet handedness{close_quotes} methodsmore » and studied the correlation between the predicted polarization and the quantities. The signal was estimated by analyzing power which represents degree of the polarization transport through the hadronization process. The Z{sup 0} decays were measured by SLC Large Detector and the polarized electron beam provided by SLAC Linear Collider was useful for this study. The data from the 1993 run showed no signature of the transport of quark and antiquark polarization. Upper limits on magnitude of the analyzing power were set in the range 0.05-0.15 depending on the methods.« less

Parameter exploration for a Compact Advanced Tokamak DEMO

NASA Astrophysics Data System (ADS)

Weisberg, D. B.; Buttery, R. J.; Ferron, J. R.; Garofalo, A. M.; Snyder, P. B.; Turnbull, A. D.; Holcomb, C. T.; McClenaghan, J.; Canik, J.; Park, J.-M.

2017-10-01

A new parameter study has explored a range of design points to assess the physics feasibility for a compact 200MWe advanced tokamak DEMO that combines high beta (βN < 4) and high toroidal field (BT = 6 - 7 T). A unique aspect of this study is the use of a FASTRAN modeling suite that combines integrated transport, pedestal, stability, and heating & current drive calculations to predict steady-state solutions with neutral beam and helicon powered current drive. This study has identified a range of design solutions in a compact (R0 = 4 m), high-field (BT = 6 - 7 T), strongly-shaped (κ = 2 , δ = 0.6) device. Unlike previous proposals, C-AT DEMO takes advantage of high-beta operation as well as emerging advances in magnet technology to demonstrate net electric production in a moderately sized machine. We present results showing that the large bootstrap fraction and low recirculating power enabled by high normalized beta can achieve tolerable heat and neutron load with good H-mode access. The prediction of operating points with simultaneously achieved high-confinement (H98 < 1.3), high-density (fGW < 1.3), and high-beta warrants additional assessment of this approach towards a cost-attractive DEMO device. Work supported by the US DOE under DE-FC02-04ER54698.

Evaluating Upper-Body Strength and Power From a Single Test: The Ballistic Push-up.

PubMed

Wang, Ran; Hoffman, Jay R; Sadres, Eliahu; Bartolomei, Sandro; Muddle, Tyler W D; Fukuda, David H; Stout, Jeffrey R

2017-05-01

Wang, R, Hoffman, JR, Sadres, E, Bartolomei, S, Muddle, TWD, Fukuda, DH, and Stout, JR. Evaluating upper-body strength and power from a single test: the ballistic push-up. J Strength Cond Res 31(5): 1338-1345, 2017-The purpose of this study was to examine the reliability of the ballistic push-up (BPU) exercise and to develop a prediction model for both maximal strength (1 repetition maximum [1RM]) in the bench press exercise and upper-body power. Sixty recreationally active men completed a 1RM bench press and 2 BPU assessments in 3 separate testing sessions. Peak and mean force, peak and mean rate of force development, net impulse, peak velocity, flight time, and peak and mean power were determined. Intraclass correlation coefficients were used to examine the reliability of the BPU. Stepwise linear regression was used to develop 1RM bench press and power prediction equations. Intraclass correlation coefficient's ranged from 0.849 to 0.971 for the BPU measurements. Multiple regression analysis provided the following 1RM bench press prediction equation: 1RM = 0.31 × Mean Force - 1.64 × Body Mass + 0.70 (R = 0.837, standard error of the estimate [SEE] = 11 kg); time-based power prediction equation: Peak Power = 11.0 × Body Mass + 2012.3 × Flight Time - 338.0 (R = 0.658, SEE = 150 W), Mean Power = 6.7 × Body Mass + 1004.4 × Flight Time - 224.6 (R = 0.664, SEE = 82 W); and velocity-based power prediction equation: Peak Power = 8.1 × Body Mass + 818.6 × Peak Velocity - 762.0 (R = 0.797, SEE = 115 W); Mean Power = 5.2 × Body Mass + 435.9 × Peak Velocity - 467.7 (R = 0.838, SEE = 57 W). The BPU is a reliable test for both upper-body strength and power. Results indicate that the mean force generated from the BPU can be used to predict 1RM bench press, whereas peak velocity and flight time measured during the BPU can be used to predict upper-body power. These findings support the potential use of the BPU as a valid method to evaluate upper-body strength and power.

Toward a theory of persuasive hope: effects of cognitive appraisals, hope appeals, and hope in the context of climate change.

PubMed

Chadwick, Amy E

2015-01-01

Hope has the potential to be a powerful motivator for influencing behavior. However, hope and messages that evoke hope (hope appeals) have rarely been the focus of theoretical development or empirical research. As a step toward the effective development and use of hope appeals in persuasive communication, this study conceptualized and operationalized hope appeals in the context of climate change prevention. Then, the study manipulated components of the hope evocation part of a hope appeal. Specifically, the components were designed to address appraisals of the importance, goal congruence, future expectation, and possibility of climate protection, resulting in a 2 (strong/weak importance) × 2 (strong/weak goal congruence) × 2 (strong/weak future expectation) × 2 (strong/weak possibility) between-subjects pretest-posttest factorial design. Two hundred forty-five undergraduate students were randomly assigned to one of the 16 message conditions and completed the study online. The study tested whether the four appraisals predict feelings of hope. It determined whether message components that address importance, goal congruence, future expectation, and possibility affect appraisals, feelings of hope, and persuasion outcomes. Finally, this study tested the effects of feelings of hope on persuasion outcomes. This study takes an important step toward enabling the effective use of hope appeals in persuasive communication.

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 are using a number of weather parameters like wind speed in different heights, friction velocity and DTHV. The 25 wind sites are scattered around in Europe and contains 4 offshore parks and 21 onshore parks in various terrain complexity. The "day a head" forecasts are compared with production data and predictability for the period February 2010-April 2010 are given in Mean Absolute Errors (MAE) and Root Mean Squared Errors (RMSE). The power predictability results are mapped for each turbine giving a clear picture of the predictability in Europe. . Finally a economic analysis are shown for each wind parks in different regimes of predictability will be compared with regard to the balance costs that result from errors in the wind power prediction. Analysis shows that it may very well be profitable to place wind parks in regions of lower, but more predictable wind ressource. Authors: Ivan Ristic, CTO Weather2Umberlla D.O.O Tomislav Maric, Meteorologist at Global Flow Solutions Vestas Wind Technology R&D Line Gulstad, Manager Global Flow Solutions Vestas Wind Technology R&D Jesper Thiesen, CEO ConWx ApS

Polarization modeling and predictions for Daniel K. Inouye Solar Telescope part 1: telescope and example instrument configurations

NASA Astrophysics Data System (ADS)

Harrington, David M.; Sueoka, Stacey R.

2017-01-01

We outline polarization performance calculations and predictions for the Daniel K. Inouye Solar Telescope (DKIST) optics and show Mueller matrices for two of the first light instruments. Telescope polarization is due to polarization-dependent mirror reflectivity and rotations between groups of mirrors as the telescope moves in altitude and azimuth. The Zemax optical modeling software has polarization ray-trace capabilities and predicts system performance given a coating prescription. We develop a model coating formula that approximates measured witness sample polarization properties. Estimates show the DKIST telescope Mueller matrix as functions of wavelength, azimuth, elevation, and field angle for the cryogenic near infra-red spectro-polarimeter (CryoNIRSP) and visible spectro-polarimeter. Footprint variation is substantial and shows vignetted field points will have strong polarization effects. We estimate 2% variation of some Mueller matrix elements over the 5-arc min CryoNIRSP field. We validate the Zemax model by showing limiting cases for flat mirrors in collimated and powered designs that compare well with theoretical approximations and are testable with lab ellipsometers.

Summary of recent NASA propeller research

NASA Technical Reports Server (NTRS)

Mikkelson, D. C.; Mitchell, G. A.; Bober, L. J.

1984-01-01

Advanced high-speed propellers offer large performance improvements for aircraft that cruise in the Mach 0.7 to 0.8 speed regime. At these speeds, studies indicate that there is a 15 to near 40 percent block fuel savings and associated operating cost benefits for advanced turboprops compared to equivalent technology turbofan powered aircraft. Recent wind tunnel results for five eight to ten blade advanced models are compared with analytical predictions. Test results show that blade sweep was important in achieving net efficiencies near 80 percent at Mach 0.8 and reducing nearfield cruise noise by about 6 dB. Lifting line and lifting surface aerodynamic analysis codes are under development and some results are compared with propeller force and probe data. Also, analytical predictions are compared with some initial laser velocimeter measurements of the flow field velocities of an eightbladed 45 swept propeller. Experimental aeroelastic results indicate that cascade effects and blade sweep strongly affect propeller aeroelastic characteristics. Comparisons of propeller near-field noise data with linear acoustic theory indicate that the theory adequately predicts near-field noise for subsonic tip speeds but overpredicts the noise for supersonic tip speeds.

Beyond clay: Towards an improved set of variables for predicting soil organic matter content

USGS Publications Warehouse

Rasmussen, Craig; Heckman, Katherine; Wieder, William R.; Keiluweit, Marco; Lawrence, Corey R.; Berhe, Asmeret Asefaw; Blankinship, Joseph C.; Crow, Susan E.; Druhan, Jennifer; Hicks Pries, Caitlin E.; Marin-Spiotta, Erika; Plante, Alain F.; Schadel, Christina; Schmiel, Joshua P.; Sierra, Carlos A.; Thompson, Aaron; Wagai, Rota

2018-01-01

Improved quantification of the factors controlling soil organic matter (SOM) stabilization at continental to global scales is needed to inform projections of the largest actively cycling terrestrial carbon pool on Earth, and its response to environmental change. Biogeochemical models rely almost exclusively on clay content to modify rates of SOM turnover and fluxes of climate-active CO2 to the atmosphere. Emerging conceptual understanding, however, suggests other soil physicochemical properties may predict SOM stabilization better than clay content. We addressed this discrepancy by synthesizing data from over 5,500 soil profiles spanning continental scale environmental gradients. Here, we demonstrate that other physicochemical parameters are much stronger predictors of SOM content, with clay content having relatively little explanatory power. We show that exchangeable calcium strongly predicted SOM content in water-limited, alkaline soils, whereas with increasing moisture availability and acidity, iron- and aluminum-oxyhydroxides emerged as better predictors, demonstrating that the relative importance of SOM stabilization mechanisms scales with climate and acidity. These results highlight the urgent need to modify biogeochemical models to better reflect the role of soil physicochemical properties in SOM cycling.

The Influence of Pre-stimulus EEG Activity on Reaction Time During a Verbal Sternberg Task is Related to Musical Expertise.

PubMed

Klein, Carina; Diaz Hernandez, Laura; Koenig, Thomas; Kottlow, Mara; Elmer, Stefan; Jäncke, Lutz

2016-01-01

Previous work highlighted the possibility that musical training has an influence on cognitive functioning. The suggested reason for this influence is the strong recruitment of attention, planning, and working memory functions during playing a musical instrument. The purpose of the present work was twofold, namely to evaluate the general relationship between pre-stimulus electrophysiological activity and cognition, and more specifically the influence of musical expertise on working memory functions. With this purpose in mind, we used covariance mapping analyses to evaluate whether pre-stimulus electroencephalographic activity is predictive for reaction time during a visual working memory task (Sternberg paradigm) in musicians and non-musicians. In line with our hypothesis, we replicated previous findings pointing to a general predictive value of pre-stimulus activity for working memory performance. Most importantly, we also provide first evidence for an influence of musical expertise on working memory performance that could distinctively be predicted by pre-stimulus spectral power. Our results open novel perspectives for better comprehending the vast influences of musical expertise on cognition.

Summary of recent NASA propeller research

NASA Technical Reports Server (NTRS)

Mikkelson, D. C.; Mitchell, G. A.; Bober, L. J.

1985-01-01

Advanced high speed propellers offer large performance improvements for aircraft that cruise in the Mach 0.7 to 0.8 speed regime. At these speeds, studies indicate that there is a 15 to near 40 percent block fuel savings and associated operating cost benefits for advanced turboprops compared to equivalent technology turbofan powered aircraft. Recent wind tunnel results for five eight to ten blade advanced models are compared with analytical predictions. Test results show that blade sweep was important in achieving net efficiencies near 80 percent at Mach 0.8 and reducing nearfield cruise noise about 6 dB. Lifting line and lifting surface aerodynamic analysis codes are under development and some results are compared with propeller force and probe data. Also, analytical predictions are compared with some initial laser velocimeter measurements of the flow field velocities of an eight bladed 45 swept propeller. Experimental aeroelastic results indicate that cascade effects and blade sweep strongly affect propeller aeroelastic characteristics. Comparisons of propeller nearfield noise data with linear acoustic theory indicate that the theory adequately predicts nearfield noise for subsonic tip speeds, but overpredicts the noise for supersonic tip speeds.

Genome-Wide Association Analysis of Adaptation Using Environmentally Predicted Traits

PubMed Central

van Zanten, Martijn

2015-01-01

Current methods for studying the genetic basis of adaptation evaluate genetic associations with ecologically relevant traits or single environmental variables, under the implicit assumption that natural selection imposes correlations between phenotypes, environments and genotypes. In practice, observed trait and environmental data are manifestations of unknown selective forces and are only indirectly associated with adaptive genetic variation. In theory, improved estimation of these forces could enable more powerful detection of loci under selection. Here we present an approach in which we approximate adaptive variation by modeling phenotypes as a function of the environment and using the predicted trait in multivariate and univariate genome-wide association analysis (GWAS). Based on computer simulations and published flowering time data from the model plant Arabidopsis thaliana, we find that environmentally predicted traits lead to higher recovery of functional loci in multivariate GWAS and are more strongly correlated to allele frequencies at adaptive loci than individual environmental variables. Our results provide an example of the use of environmental data to obtain independent and meaningful information on adaptive genetic variation. PMID:26496492

Utilization of Model Predictive Control to Balance Power Absorption Against Load Accumulation

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

Abbas, Nikhar; Tom, Nathan M

2017-06-03

Wave energy converter (WEC) control strategies have been primarily focused on maximizing power absorption. The use of model predictive control strategies allows for a finite-horizon, multiterm objective function to be solved. This work utilizes a multiterm objective function to maximize power absorption while minimizing the structural loads on the WEC system. Furthermore, a Kalman filter and autoregressive model were used to estimate and forecast the wave exciting force and predict the future dynamics of the WEC. The WEC's power-take-off time-averaged power and structural loads under a perfect forecast assumption in irregular waves were compared against results obtained from the Kalmanmore » filter and autoregressive model to evaluate model predictive control performance.« less

Utilization of Model Predictive Control to Balance Power Absorption Against Load Accumulation: Preprint

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

Abbas, Nikhar; Tom, Nathan

Wave energy converter (WEC) control strategies have been primarily focused on maximizing power absorption. The use of model predictive control strategies allows for a finite-horizon, multiterm objective function to be solved. This work utilizes a multiterm objective function to maximize power absorption while minimizing the structural loads on the WEC system. Furthermore, a Kalman filter and autoregressive model were used to estimate and forecast the wave exciting force and predict the future dynamics of the WEC. The WEC's power-take-off time-averaged power and structural loads under a perfect forecast assumption in irregular waves were compared against results obtained from the Kalmanmore » filter and autoregressive model to evaluate model predictive control performance.« less

On climate prediction: how much can we expect from climate memory?

NASA Astrophysics Data System (ADS)

Yuan, Naiming; Huang, Yan; Duan, Jianping; Zhu, Congwen; Xoplaki, Elena; Luterbacher, Jürg

2018-03-01

Slowing variability in climate system is an important source of climate predictability. However, it is still challenging for current dynamical models to fully capture the variability as well as its impacts on future climate. In this study, instead of simulating the internal multi-scale oscillations in dynamical models, we discussed the effects of internal variability in terms of climate memory. By decomposing climate state x(t) at a certain time point t into memory part M(t) and non-memory part ɛ (t) , climate memory effects from the past 30 years on climate prediction are quantified. For variables with strong climate memory, high variance (over 20% ) in x(t) is explained by the memory part M(t), and the effects of climate memory are non-negligible for most climate variables, but the precipitation. Regarding of multi-steps climate prediction, a power law decay of the explained variance was found, indicating long-lasting climate memory effects. The explained variances by climate memory can remain to be higher than 10% for more than 10 time steps. Accordingly, past climate conditions can affect both short (monthly) and long-term (interannual, decadal, or even multidecadal) climate predictions. With the memory part M(t) precisely calculated from Fractional Integral Statistical Model, one only needs to focus on the non-memory part ɛ (t) , which is an important quantity that determines climate predictive skills.

Functional brain imaging predicts public health campaign success.

PubMed

Falk, Emily B; O'Donnell, Matthew Brook; Tompson, Steven; Gonzalez, Richard; Dal Cin, Sonya; Strecher, Victor; Cummings, Kenneth Michael; An, Lawrence

2016-02-01

Mass media can powerfully affect health decision-making. Pre-testing through focus groups or surveys is a standard, though inconsistent, predictor of effectiveness. Converging evidence demonstrates that activity within brain systems associated with self-related processing can predict individual behavior in response to health messages. Preliminary evidence also suggests that neural activity in small groups can forecast population-level campaign outcomes. Less is known about the psychological processes that link neural activity and population-level outcomes, or how these predictions are affected by message content. We exposed 50 smokers to antismoking messages and used their aggregated neural activity within a 'self-localizer' defined region of medial prefrontal cortex to predict the success of the same campaign messages at the population level (n = 400,000 emails). Results demonstrate that: (i) independently localized neural activity during health message exposure complements existing self-report data in predicting population-level campaign responses (model combined R(2) up to 0.65) and (ii) this relationship depends on message content-self-related neural processing predicts outcomes in response to strong negative arguments against smoking and not in response to compositionally similar neutral images. These data advance understanding of the psychological link between brain and large-scale behavior and may aid the construction of more effective media health campaigns. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Ultra-Short-Term Wind Power Prediction Using a Hybrid Model

NASA Astrophysics Data System (ADS)

Mohammed, E.; Wang, S.; Yu, J.

2017-05-01

This paper aims to develop and apply a hybrid model of two data analytical methods, multiple linear regressions and least square (MLR&LS), for ultra-short-term wind power prediction (WPP), for example taking, Northeast China electricity demand. The data was obtained from the historical records of wind power from an offshore region, and from a wind farm of the wind power plant in the areas. The WPP achieved in two stages: first, the ratios of wind power were forecasted using the proposed hybrid method, and then the transformation of these ratios of wind power to obtain forecasted values. The hybrid model combines the persistence methods, MLR and LS. The proposed method included two prediction types, multi-point prediction and single-point prediction. WPP is tested by applying different models such as autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA) and artificial neural network (ANN). By comparing results of the above models, the validity of the proposed hybrid model is confirmed in terms of error and correlation coefficient. Comparison of results confirmed that the proposed method works effectively. Additional, forecasting errors were also computed and compared, to improve understanding of how to depict highly variable WPP and the correlations between actual and predicted wind power.

Experimental validation of boundary element methods for noise prediction

NASA Technical Reports Server (NTRS)

Seybert, A. F.; Oswald, Fred B.

1992-01-01

Experimental validation of methods to predict radiated noise is presented. A combined finite element and boundary element model was used to predict the vibration and noise of a rectangular box excited by a mechanical shaker. The predicted noise was compared to sound power measured by the acoustic intensity method. Inaccuracies in the finite element model shifted the resonance frequencies by about 5 percent. The predicted and measured sound power levels agree within about 2.5 dB. In a second experiment, measured vibration data was used with a boundary element model to predict noise radiation from the top of an operating gearbox. The predicted and measured sound power for the gearbox agree within about 3 dB.

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

Dynamic Modeling and Very Short-term Prediction of Wind Power Output Using Box-Cox Transformation

NASA Astrophysics Data System (ADS)

Urata, Kengo; Inoue, Masaki; Murayama, Dai; Adachi, Shuichi

2016-09-01

We propose a statistical modeling method of wind power output for very short-term prediction. The modeling method with a nonlinear model has cascade structure composed of two parts. One is a linear dynamic part that is driven by a Gaussian white noise and described by an autoregressive model. The other is a nonlinear static part that is driven by the output of the linear part. This nonlinear part is designed for output distribution matching: we shape the distribution of the model output to match with that of the wind power output. The constructed model is utilized for one-step ahead prediction of the wind power output. Furthermore, we study the relation between the prediction accuracy and the prediction horizon.

Origin and Consequences of the Relationship between Protein Mean and Variance

PubMed Central

Vallania, Francesco Luigi Massimo; Sherman, Marc; Goodwin, Zane; Mogno, Ilaria; Cohen, Barak Alon; Mitra, Robi David

2014-01-01

Cell-to-cell variance in protein levels (noise) is a ubiquitous phenomenon that can increase fitness by generating phenotypic differences within clonal populations of cells. An important challenge is to identify the specific molecular events that control noise. This task is complicated by the strong dependence of a protein's cell-to-cell variance on its mean expression level through a power-law like relationship (σ2∝μ1.69). Here, we dissect the nature of this relationship using a stochastic model parameterized with experimentally measured values. This framework naturally recapitulates the power-law like relationship (σ2∝μ1.6) and accurately predicts protein variance across the yeast proteome (r2 = 0.935). Using this model we identified two distinct mechanisms by which protein variance can be increased. Variables that affect promoter activation, such as nucleosome positioning, increase protein variance by changing the exponent of the power-law relationship. In contrast, variables that affect processes downstream of promoter activation, such as mRNA and protein synthesis, increase protein variance in a mean-dependent manner following the power-law. We verified our findings experimentally using an inducible gene expression system in yeast. We conclude that the power-law-like relationship between noise and protein mean is due to the kinetics of promoter activation. Our results provide a framework for understanding how molecular processes shape stochastic variation across the genome. PMID:25062021

Analysis of impact of “strong DC and weak AC” on receiving-end power system

NASA Astrophysics Data System (ADS)

Wang, Qiang; Li, Tianran; Yang, Pengcheng

2018-02-01

The rapid development of UHVDC transmission project has brought abundant power supply to the receiving-end power system area, but also many security and stability problems. This paper summarizes four elements that affect the strength of AC system, and then simulates the most basic two-terminal single-pole UHV transmission system by MATLAB/Simulink. It analyses the impact of receiving-end AC power system strength on real-time power, frequency and voltage. Finally, in view of operation risk of “strong DC and weak AC”, this paper puts forward three countermeasures.

Pool Formation in Boulder-Bed Streams: Implications From 1-D and 2-D Numerical Modeling

NASA Astrophysics Data System (ADS)

Harrison, L. R.; Keller, E. A.

2003-12-01

In mountain rivers of Southern California, boulder-large roughness elements strongly influence flow hydraulics and pool formation and maintenance. In these systems, boulders appear to control the stream morphology by converging flow and producing deep pools during channel forming discharges. Our research goal is to develop quantitative relationships between boulder roughness elements, temporal patterns of scour and fill, and geomorphic processes that are important in producing pool habitat. The longitudinal distribution of shear stress, unit stream power and velocity were estimated along a 48 m reach on Rattlesnake Creek, using the HEC-RAS v 3.0 and River 2-D numerical models. The reach has an average slope of 0.02 and consists of a pool-riffle sequence with a large boulder constriction directly above the pool. Model runs were performed for a range of stream discharges to test if scour and fill thresholds for pool and riffle environments could be identified. Results from the HEC-RAS simulations identified that thresholds in shear stress, unit stream power and mean velocity occur above a discharge of 5.0 cms. Results from the one-dimensional analysis suggest that the reversal in competency is likely due to changes in cross-sectional width at varying flows. River 2-D predictions indicated that strong transverse velocity gradients were present through the pool at higher modeled discharges. At a flow of 0.5 cms (roughly 1/10th bankfull discharge), velocities are estimated at 0.6 m/s and 1.3 m/s for the pool and riffle, respectively. During discharges of 5.15 cms (approximate bankfull discharge), the maximum velocity in the pool center increased to nearly 3.0 m/s, while the maximum velocity over the riffle is estimated at approximately 2.5 cms. These results are consistent with those predicted by HEC-RAS, though the reversal appears to be limited to a narrow jet that occurs through the pool head and pool center. Model predictions suggest that the velocity reversal is produced by a boulder-bedrock constriction that rapidly decreases the channel width above the pool by roughly 25 percent. The width constriction creates highly turbulent flow capable of scouring bed material through the pool. The high velocity core that is produced through the pool center appears to be enhanced by the formation of a large eddy directly below the boulder. Values of unit stream power and shear stress indicate that the pool exit is an area of deposition of bed material due to a decrease in tractive force. The presence of a strong transverse velocity gradient suggests that only a portion of the flow is responsible for scouring bed material. After we eliminate the dead water zone, the lowest five percent of the velocity range, patterns of effective width between pools and riffles begin to emerge. The ratio of flow width between adjacent pools and riffles is one measure of flow convergence. At a discharge of 0.5 cms, the ratio of effective width between pools and riffles is roughly 1:1, implying that there is uniform flow with little flow convergence. At a discharge of 5.15 cms the width ratio between the pool and riffle is about 1:3, demonstrating the strong convergent flow patterns at the pool head. The observed effective width relationship suggests that when considering restoration designs, boulders should be placed in areas that replicate natural convergence and divergence patterns in order to maximize pool area and depth.

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

Newman, Jennifer F.; Clifton, Andrew

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 ofmore » 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 for a 1.5 MW turbine. The impact of lidar turbulence error on the predicted power from these different models is examined to determine the degree of turbulence measurement accuracy needed for accurate power prediction.« less

POWER Web Access Data

Atmospheric Science Data Center

2018-05-27

Description:  Obtain Prediction of Worldwide Energy Resource (POWER) data The Prediction of Worldwide Energy ... (POWER) project was initiated to improve upon the current renewable energy data set and to create new data sets from new satellite ...

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

Forecasting destructive hurricane potential is complicated by substantial, unexplained intraannual variation in storm-specific power dissipation index (PDI, or integrated third power of wind speed), and interannual variation in annual accumulated PDI (APDI). A growing controversy concerns the recent hypothesis that the clearly positive trend in North Atlantic Ocean (NAO) sea surface temperature (SST) since 1970 explains increased hurricane intensities over this period, and so implies ominous PDI and APDI growth as global warming continues. To test this "SST hypothesis" and examine its quantitative implications, a combination of statistical and probabilistic methods were applied to National Hurricane Center HURDAT best-track data on NAO hurricanes during 1880-2002, and corresponding National Oceanographic and Atmospheric Administration Extended Reconstruction SST estimates. Notably, hurricane behavior was compared to corresponding hurricane-specific (i.e., spatiotemporally linked) SST; previous similar comparisons considered only SST averaged over large NAO regions. Contrary to the SST hypothesis, SST was found to vary in a monthly pattern inconsistent with that of corresponding PDI, and to be at best weakly associated with PDI or APDI despite strong correlation with corresponding mean latitude (R(2)= 0.55) or with combined mean location and a approximately 90-year periodic trend (R(2)= 0.70). Over the last century, the lower 75% of APDIs appear randomly sampled from a nearly uniform distribution, and the upper 25% of APDIs from a nearly lognormal distribution. From the latter distribution, a baseline (SST-independent) stochastic model was derived predicting that over the next half century, APDI will not likely exceed its maximum value over the last half century by more than a factor of 1.5. This factor increased to 2 using a baseline model modified to assume SST-dependence conditioned on an upper bound of the increasing NAO SST trend observed since 1970. An 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.

Mapping the cortical representation of speech sounds in a syllable repetition task.

PubMed

Markiewicz, Christopher J; Bohland, Jason W

2016-11-01

Speech repetition relies on a series of distributed cortical representations and functional pathways. A speaker must map auditory representations of incoming sounds onto learned speech items, maintain an accurate representation of those items in short-term memory, interface that representation with the motor output system, and fluently articulate the target sequence. A "dorsal stream" consisting of posterior temporal, inferior parietal and premotor regions is thought to mediate auditory-motor representations and transformations, but the nature and activation of these representations for different portions of speech repetition tasks remains unclear. Here we mapped the correlates of phonetic and/or phonological information related to the specific phonemes and syllables that were heard, remembered, and produced using a series of cortical searchlight multi-voxel pattern analyses trained on estimates of BOLD responses from individual trials. Based on responses linked to input events (auditory syllable presentation), predictive vowel-level information was found in the left inferior frontal sulcus, while syllable prediction revealed significant clusters in the left ventral premotor cortex and central sulcus and the left mid superior temporal sulcus. Responses linked to output events (the GO signal cueing overt production) revealed strong clusters of vowel-related information bilaterally in the mid to posterior superior temporal sulcus. For the prediction of onset and coda consonants, input-linked responses yielded distributed clusters in the superior temporal cortices, which were further informative for classifiers trained on output-linked responses. Output-linked responses in the Rolandic cortex made strong predictions for the syllables and consonants produced, but their predictive power was reduced for vowels. The results of this study provide a systematic survey of how cortical response patterns covary with the identity of speech sounds, which will help to constrain and guide theoretical models of speech perception, speech production, and phonological working memory. Copyright © 2016 Elsevier Inc. All rights reserved.

Physics of the Tokamak Pedestal, and Implications for Magnetic Fusion Energy

NASA Astrophysics Data System (ADS)

Snyder, Philip

2017-10-01

High performance in tokamaks is achieved via the spontaneous formation of a transport barrier in the outer few percent of the confined plasma. This narrow insulating layer, referred to as a ``pedestal,'' typically results in a >30x increase in pressure across a 0.4-5cm layer. Predicted fusion power scales with the square of the pedestal top pressure (or ``pedestal height''), hence a fusion reactor strongly benefits from a high pedestal, provided this can be attained without large Edge Localized Modes (ELMs), which may erode plasma facing materials. The overlap of drift orbit, turbulence, and equilibrium scales across this narrow layer leads to rich and complex physics, and challenges traditional analytic and computational approaches. We review studies employing gyrokinetic, neoclassical, MHD, and other methods, which have explored how a range of instabilities, influenced by complex geometry, and strong ExB flows and bootstrap current, drive transport across the pedestal and guide its structure and dynamics. Development of high resolution diagnostics, and coordinated experiments on several tokamaks, have validated understanding of important aspects of the physics, while highlighting open issues. A predictive model (EPED) has proven capable of predicting the pedestal height and width to 20-25% accuracy in large statistical studies. This model was used to predict a new, high pedestal ``Super H-Mode'' regime, which was subsequently discovered on DIII-D, and motivated experiments on Alcator C-Mod which achieved world record, reactor relevant pedestal pressure. We review open issues including improved formalism, particle and momentum transport, the role of neutrals and impurities, ELM control, and pedestal formation. Finally we discuss coupling pedestal and core predictive models to enable more comprehensive optimization of the tokamak fusion concept. Supported by the US DOE under DE-FG02-95ER54309, FC02-06ER54873, DE-FC02-04ER54698, DE-FC02-99ER54512.

Influence of performance level on anaerobic power and body composition in elite male judoists.

PubMed

Kim, Jongkyu; Cho, Hyun-Chul; Jung, Han-Sang; Yoon, Jong-Dae

2011-05-01

This study examined the relationship between 30-second anaerobic power and body composition by performance level in elite Judoists. During a 3-month period, 10 male Korean Judo national team athletes (NT), 26 male university varsity team athletes (VT), and 28 male junior varsity team athletes (JT) were assessed for 30-second anaerobic power and body composition at the Youngin University. Anaerobic power was measured using a 30-second Wingate test. Body composition was assessed via bioelectric impedance analysis in standardized conditions using BioSpace (Korean)-specific prediction formulas. All testing occurred at the beginning of the winter nonseason period but excluded a brief weight-loss period before the competition phase. Anaerobic power measures were significantly greater (p < 0.05) in NT and VT than in JT. Fat-free mass (FFM), muscle mass (MM), and total body water in JT were also greater than in VT and JT (p < 0.05). Muscle mass in VT was significantly lower than in NT (p < 0.05). Fat-free mass in NT was strongly correlated to mean and peak anaerobic power (r = 0.77, p = 0.009; r = 0.87, p < 0.001, respectively). Varsity team athletes also indicated a moderate association between FFM and peak and mean anaerobic power (r = 0.63, p < 0.001; r = 0.48, p = 0.013, respectively). However, relationship between FFM and anaerobic power was not statistically significantly correlated in JT (r = 0.14, p = 0.470; r = 0.23, p = 0.232, separately). In conclusion, our data indicated that anaerobic power is closely correlated with increase in FFM and MM and was different dependent among performance levels. Further research in the field is warranted to elucidate the Judo-specific relationship between FFM and performance.

Spiral spectrum of Airy beams propagation through moderate-to-strong turbulence of maritime atmosphere.

PubMed

Zhu, Yun; Zhang, Yixin; Hu, Zhengda

2016-05-16

The spatial coherence radius in moderate-to-strong maritime turbulence is derived on the basis of the modified Rytov approximation. Models are developed to simulate the spiral spectrum of Airy beams propagating through moderate-to-strong maritime turbulence. In the moderate-to-strong irradiance fluctuation region, we analyze the effects of maritime turbulence on the spread of the spiral spectrum of Airy beams in a horizontal propagation path. Results indicate that the increment in the inner-scale significantly increases the received power. By contrast, the outer-scale elicits a negligible effect on the received power if the ratio of the inner-scale to the outer-scale is less than 0.01. The outer-scale affects the received power only if the ratio is greater than 0.01. The performance of a light source is essential for the received power of Airy beams carrying orbital angular momentum (OAM) through moderate-to-strong maritime turbulence. Airy beams with longer wavelengths, smaller OAM numbers, larger radii of the main ring, and smaller diameters of the circular aperture are less affected by maritime turbulence. Autofocusing of Airy beams is beneficial for the propagation of the spiral spectrum in a certain propagation distance. These results contribute to the design of optical communication systems with OAM encoding for moderate-to-strong maritime turbulence.

Core or Cusps: The Central Dark Matter Profile of a Strong Lensing Cluster with a Bright Central Image at Redshift 1 [Core or Cusps: The Central Dark Matter Profile of a Redshift One Strong Lensing Cluster with a Bright Central Image

DOE PAGES

Collett, Thomas E.; Buckley-Geer, Elizabeth; Lin, Huan; ...

2017-07-10

Here, we report on SPT-CLJ2011-5228, a giant system of arcs created by a cluster at z = 1.06. The arc system is notable for the presence of a bright central image. The source is a Lyman break galaxy at z s = 2.39 and the mass enclosed within the Einstein ring of radius 14 arcsec ismore » $$\\sim {10}^{14.2}\\ {M}_{\\odot }$$. We perform a full reconstruction of the light profile of the lensed images to precisely infer the parameters of the mass distribution. The brightness of the central image demands that the central total density profile of the lens be shallow. By fitting the dark matter as a generalized Navarro–Frenk–White profile—with a free parameter for the inner density slope—we find that the break radius is $${270}_{-76}^{+48}$$ kpc, and that the inner density falls with radius to the power –0.38 ± 0.04 at 68% confidence. Such a shallow profile is in strong tension with our understanding of relaxed cold dark matter halos; dark matter-only simulations predict that the inner density should fall as $${r}^{-1}$$. The tension can be alleviated if this cluster is in fact a merger; a two-halo model can also reconstruct the data, with both clumps (density varying as $${r}^{-0.8}$$ and $${r}^{-1.0}$$) much more consistent with predictions from dark matter-only simulations. At the resolution of our Dark Energy Survey imaging, we are unable to choose between these two models, but we make predictions for forthcoming Hubble Space Telescope imaging that will decisively distinguish between them.« less

Core or Cusps: The Central Dark Matter Profile of a Strong Lensing Cluster with a Bright Central Image at Redshift 1 [Core or Cusps: The Central Dark Matter Profile of a Redshift One Strong Lensing Cluster with a Bright Central Image

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

Collett, Thomas E.; Buckley-Geer, Elizabeth; Lin, Huan

Here, we report on SPT-CLJ2011-5228, a giant system of arcs created by a cluster at z = 1.06. The arc system is notable for the presence of a bright central image. The source is a Lyman break galaxy at z s = 2.39 and the mass enclosed within the Einstein ring of radius 14 arcsec ismore » $$\\sim {10}^{14.2}\\ {M}_{\\odot }$$. We perform a full reconstruction of the light profile of the lensed images to precisely infer the parameters of the mass distribution. The brightness of the central image demands that the central total density profile of the lens be shallow. By fitting the dark matter as a generalized Navarro–Frenk–White profile—with a free parameter for the inner density slope—we find that the break radius is $${270}_{-76}^{+48}$$ kpc, and that the inner density falls with radius to the power –0.38 ± 0.04 at 68% confidence. Such a shallow profile is in strong tension with our understanding of relaxed cold dark matter halos; dark matter-only simulations predict that the inner density should fall as $${r}^{-1}$$. The tension can be alleviated if this cluster is in fact a merger; a two-halo model can also reconstruct the data, with both clumps (density varying as $${r}^{-0.8}$$ and $${r}^{-1.0}$$) much more consistent with predictions from dark matter-only simulations. At the resolution of our Dark Energy Survey imaging, we are unable to choose between these two models, but we make predictions for forthcoming Hubble Space Telescope imaging that will decisively distinguish between them.« less

A proof-of-principle simulation for closed-loop control based on preexisting experimental thalamic DBS-enhanced instrumental learning.

PubMed

Wang, Ching-Fu; Yang, Shih-Hung; Lin, Sheng-Huang; Chen, Po-Chuan; Lo, Yu-Chun; Pan, Han-Chi; Lai, Hsin-Yi; Liao, Lun-De; Lin, Hui-Ching; Chen, Hsu-Yan; Huang, Wei-Chen; Huang, Wun-Jhu; Chen, You-Yin

Deep brain stimulation (DBS) has been applied as an effective therapy for treating Parkinson's disease or essential tremor. Several open-loop DBS control strategies have been developed for clinical experiments, but they are limited by short battery life and inefficient therapy. Therefore, many closed-loop DBS control systems have been designed to tackle these problems by automatically adjusting the stimulation parameters via feedback from neural signals, which has been reported to reduce the power consumption. However, when the association between the biomarkers of the model and stimulation is unclear, it is difficult to develop an optimal control scheme for other DBS applications, i.e., DBS-enhanced instrumental learning. Furthermore, few studies have investigated the effect of closed-loop DBS control for cognition function, such as instrumental skill learning, and have been implemented in simulation environments. In this paper, we proposed a proof-of-principle design for a closed-loop DBS system, cognitive-enhancing DBS (ceDBS), which enhanced skill learning based on in vivo experimental data. The ceDBS acquired local field potential (LFP) signal from the thalamic central lateral (CL) nuclei of animals through a neural signal processing system. A strong coupling of the theta oscillation (4-7 Hz) and the learning period was found in the water reward-related lever-pressing learning task. Therefore, the theta-band power ratio, which was the averaged theta band to averaged total band (1-55 Hz) power ratio, could be used as a physiological marker for enhancement of instrumental skill learning. The on-line extraction of the theta-band power ratio was implemented on a field-programmable gate array (FPGA). An autoregressive with exogenous inputs (ARX)-based predictor was designed to construct a CL-thalamic DBS model and forecast the future physiological marker according to the past physiological marker and applied DBS. The prediction could further assist the design of a closed-loop DBS controller. A DBS controller based on a fuzzy expert system was devised to automatically control DBS according to the predicted physiological marker via a set of rules. The simulated experimental results demonstrate that the ceDBS based on the closed-loop control architecture not only reduced power consumption using the predictive physiological marker, but also achieved a desired level of physiological marker through the DBS controller. Copyright © 2017 Elsevier Inc. All rights reserved.

Using an Alzheimer Disease Polygenic Risk Score to Predict Memory Decline in Black and White Americans Over 14 Years of Follow-up.

PubMed

Marden, Jessica R; Mayeda, Elizabeth R; Walter, Stefan; Vivot, Alexandre; Tchetgen Tchetgen, Eric J; Kawachi, Ichiro; Glymour, M Maria

2016-01-01

Evidence on whether genetic predictors of Alzheimer disease (AD) also predict memory decline is inconsistent, and limited data are available for African ancestry populations. For 8253 non-Hispanic white (NHW) and non-Hispanic black (NHB) Health and Retirement Study participants with memory scores measured 1 to 8 times between 1998 and 2012 (average baseline age=62), we calculated weighted polygenic risk scores [AD Genetic Risk Score (AD-GRS)] using the top 22 AD-associated loci, and an alternative score excluding apolipoprotein E (APOE) (AD-GRSexAPOE). We used generalized linear models with AD-GRS-by-age and AD-GRS-by-age interactions (age centered at 70) to predict memory decline. Average NHB decline was 26% faster than NHW decline (P<0.001). Among NHW, 10% higher AD-GRS predicted faster memory decline (linear β=-0.058 unit decrease over 10 y; 95% confidence interval,-0.074 to -0.043). AD-GRSexAPOE also predicted faster decline for NHW, although less strongly. Among NHB, AD-GRS predicted faster memory decline (linear β=-0.050; 95% confidence interval, -0.106 to 0.006), but AD-GRSexAPOE did not. Our nonsignificant estimate among NHB may reflect insufficient statistical power or a misspecified AD-GRS among NHB as an overwhelming majority of genome-wide association studies are conducted in NHW. A polygenic score based on previously identified AD loci predicts memory loss in US blacks and whites.

POWER/SSE Web Access Data

Atmospheric Science Data Center

2018-06-25

Description:  Obtain Prediction of Worldwide Energy Resource (POWER) data The Prediction of Worldwide Energy ... (POWER) project was initiated to improve upon the current renewable energy data set and to create new data sets from new satellite ...

Research on prediction of agricultural machinery total power based on grey model optimized by genetic algorithm

NASA Astrophysics Data System (ADS)

Xie, Yan; Li, Mu; Zhou, Jin; Zheng, Chang-zheng

2009-07-01

Agricultural machinery total power is an important index to reflex and evaluate the level of agricultural mechanization. It is the power source of agricultural production, and is the main factors to enhance the comprehensive agricultural production capacity expand production scale and increase the income of the farmers. Its demand is affected by natural, economic, technological and social and other "grey" factors. Therefore, grey system theory can be used to analyze the development of agricultural machinery total power. A method based on genetic algorithm optimizing grey modeling process is introduced in this paper. This method makes full use of the advantages of the grey prediction model and characteristics of genetic algorithm to find global optimization. So the prediction model is more accurate. According to data from a province, the GM (1, 1) model for predicting agricultural machinery total power was given based on the grey system theories and genetic algorithm. The result indicates that the model can be used as agricultural machinery total power an effective tool for prediction.

Toward a computational framework for cognitive biology: Unifying approaches from cognitive neuroscience and comparative cognition

NASA Astrophysics Data System (ADS)

Fitch, W. Tecumseh

2014-09-01

Progress in understanding cognition requires a quantitative, theoretical framework, grounded in the other natural sciences and able to bridge between implementational, algorithmic and computational levels of explanation. I review recent results in neuroscience and cognitive biology that, when combined, provide key components of such an improved conceptual framework for contemporary cognitive science. Starting at the neuronal level, I first discuss the contemporary realization that single neurons are powerful tree-shaped computers, which implies a reorientation of computational models of learning and plasticity to a lower, cellular, level. I then turn to predictive systems theory (predictive coding and prediction-based learning) which provides a powerful formal framework for understanding brain function at a more global level. Although most formal models concerning predictive coding are framed in associationist terms, I argue that modern data necessitate a reinterpretation of such models in cognitive terms: as model-based predictive systems. Finally, I review the role of the theory of computation and formal language theory in the recent explosion of comparative biological research attempting to isolate and explore how different species differ in their cognitive capacities. Experiments to date strongly suggest that there is an important difference between humans and most other species, best characterized cognitively as a propensity by our species to infer tree structures from sequential data. Computationally, this capacity entails generative capacities above the regular (finite-state) level; implementationally, it requires some neural equivalent of a push-down stack. I dub this unusual human propensity "dendrophilia", and make a number of concrete suggestions about how such a system may be implemented in the human brain, about how and why it evolved, and what this implies for models of language acquisition. I conclude that, although much remains to be done, a neurally-grounded framework for theoretical cognitive science is within reach that can move beyond polarized debates and provide a more adequate theoretical future for cognitive biology.

Toward a computational framework for cognitive biology: unifying approaches from cognitive neuroscience and comparative cognition.

PubMed

Fitch, W Tecumseh

2014-09-01

Progress in understanding cognition requires a quantitative, theoretical framework, grounded in the other natural sciences and able to bridge between implementational, algorithmic and computational levels of explanation. I review recent results in neuroscience and cognitive biology that, when combined, provide key components of such an improved conceptual framework for contemporary cognitive science. Starting at the neuronal level, I first discuss the contemporary realization that single neurons are powerful tree-shaped computers, which implies a reorientation of computational models of learning and plasticity to a lower, cellular, level. I then turn to predictive systems theory (predictive coding and prediction-based learning) which provides a powerful formal framework for understanding brain function at a more global level. Although most formal models concerning predictive coding are framed in associationist terms, I argue that modern data necessitate a reinterpretation of such models in cognitive terms: as model-based predictive systems. Finally, I review the role of the theory of computation and formal language theory in the recent explosion of comparative biological research attempting to isolate and explore how different species differ in their cognitive capacities. Experiments to date strongly suggest that there is an important difference between humans and most other species, best characterized cognitively as a propensity by our species to infer tree structures from sequential data. Computationally, this capacity entails generative capacities above the regular (finite-state) level; implementationally, it requires some neural equivalent of a push-down stack. I dub this unusual human propensity "dendrophilia", and make a number of concrete suggestions about how such a system may be implemented in the human brain, about how and why it evolved, and what this implies for models of language acquisition. I conclude that, although much remains to be done, a neurally-grounded framework for theoretical cognitive science is within reach that can move beyond polarized debates and provide a more adequate theoretical future for cognitive biology. Copyright © 2014. Published by Elsevier B.V.

Constraints on parton distribution functions and extraction of the strong coupling constant from the inclusive jet cross section in pp collisions at $$\\sqrt{s} = 7$$ $$\\,\\text {TeV}$$

DOE PAGES

Khachatryan, Vardan

2015-06-26

The inclusive jet cross section for proton–proton collisions at a centre-of-mass energy of 7TeVwas measured by the CMS Collaboration at the LHC with data corresponding to an integrated luminosity of 5.0fb -1. The measurement covers a phase space up to 2TeV in jet transverse momentum and 2.5 in absolute jet rapidity. The statistical precision of these data leads to stringent constraints on the parton distribution functions of the proton. The data provide important input for the gluon density at high fractions of the proton momentum and for the strong coupling constant at large energy scales. Using predictions from perturbative quantummore » chromodynamics at next-to-leading order, complemented with electroweak corrections, the constraining power of these data is investigated and the strong coupling constant at the Z boson mass M Z is determined to be α S(M Z)=0.1185±0.0019(exp) +0.0060 -0.0037(theo), which is in agreement with the world average.« less

Cognitive consistency and math-gender stereotypes in Singaporean children.

PubMed

Cvencek, Dario; Meltzoff, Andrew N; Kapur, Manu

2014-01-01

In social psychology, cognitive consistency is a powerful principle for organizing psychological concepts. There have been few tests of cognitive consistency in children and no research about cognitive consistency in children from Asian cultures, who pose an interesting developmental case. A sample of 172 Singaporean elementary school children completed implicit and explicit measures of math-gender stereotype (male=math), gender identity (me=male), and math self-concept (me=math). Results showed strong evidence for cognitive consistency; the strength of children's math-gender stereotypes, together with their gender identity, significantly predicted their math self-concepts. Cognitive consistency may be culturally universal and a key mechanism for developmental change in social cognition. We also discovered that Singaporean children's math-gender stereotypes increased as a function of age and that boys identified with math more strongly than did girls despite Singaporean girls' excelling in math. The results reveal both cultural universals and cultural variation in developing social cognition. Copyright © 2013 Elsevier Inc. All rights reserved.

Applicability of Quantum Thermal Baths to Complex Many-Body Systems with Various Degrees of Anharmonicity.

PubMed

Hernández-Rojas, Javier; Calvo, Florent; Noya, Eva Gonzalez

2015-03-10

The semiclassical method of quantum thermal baths by colored noise thermostats has been used to simulate various atomic systems in the molecular and bulk limits, at finite temperature and in moderately to strongly anharmonic regimes. In all cases, the method performs relatively well against alternative approaches in predicting correct energetic properties, including in the presence of phase changes, provided that vibrational delocalization is not too strong-neon appearing already as an upper limiting case. In contrast, the dynamical behavior inferred from global indicators such as the root-mean-square bond length fluctuation index or the vibrational spectrum reveals more marked differences caused by zero-point energy leakage, except in the case of isolated molecules with well separated vibrational modes. To correct for such deficiencies and reduce the undesired transfer among modes, empirical modifications of the noise power spectral density were attempted to better describe thermal equilibrium but still failed when used as semiclassical preparation for microcanonical trajectories.

Issues with Strong Compression of Plasma Target by Stabilized Imploding Liner

NASA Astrophysics Data System (ADS)

Turchi, Peter; Frese, Sherry; Frese, Michael

2017-10-01

Strong compression (10:1 in radius) of an FRC by imploding liquid metal liners, stabilized against Rayleigh-Taylor modes, using different scalings for loss based on Bohm vs 100X classical diffusion rates, predict useful compressions with implosion times half the initial energy lifetime. The elongation (length-to-diameter ratio) near peak compression needed to satisfy empirical stability criterion and also retain alpha-particles is about ten. The present paper extends these considerations to issues of the initial FRC, including stability conditions (S*/E) and allowable angular speeds. Furthermore, efficient recovery of the implosion energy and alpha-particle work, in order to reduce the necessary nuclear gain for an economical power reactor, is seen as an important element of the stabilized liner implosion concept for fusion. We describe recent progress in design and construction of the high energy-density prototype of a Stabilized Liner Compressor (SLC) leading to repetitive laboratory experiments to develop the plasma target. Supported by ARPA-E ALPHA Program.

Determination of enantiomeric composition of ibuprofen in pharmaceutical formulations by partial least-squares regression of strongly overlapped chromatographic profiles.

PubMed

Grisales, Jaiver Osorio; Arancibia, Juan A; Castells, Cecilia B; Olivieri, Alejandro C

2012-12-01

In this report, we demonstrate how chiral liquid chromatography combined with multivariate chemometric techniques, specifically unfolded-partial least-squares regression (U-PLS), provides a powerful analytical methodology. Using U-PLS, strongly overlapped enantiomer profiles in a sample could be successfully processed and enantiomeric purity could be accurately determined without requiring baseline enantioresolution between peaks. The samples were partially enantioseparated with a permethyl-β-cyclodextrin chiral column under reversed-phase conditions. Signals detected with a diode-array detector within a wavelength range from 198 to 241 nm were recorded, and the data were processed by a second-order multivariate algorithm to decrease detection limits. The R-(-)-enantiomer of ibuprofen in tablet formulation samples could be determined at the level of 0.5 mg L⁻¹ in the presence of 99.9% of the S-(+)-enantiomorph with relative prediction error within ±3%. Copyright © 2012 Elsevier B.V. All rights reserved.

Integrated Wind Power Planning Tool

NASA Astrophysics Data System (ADS)

Rosgaard, Martin; Giebel, Gregor; Skov Nielsen, Torben; Hahmann, Andrea; Sørensen, Poul; Madsen, Henrik

2013-04-01

This poster presents the current state of the public service obligation (PSO) funded project PSO 10464, with the title "Integrated Wind Power Planning Tool". The goal is to integrate a mesoscale 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. Using the state-of-the-art mesoscale NWP model Weather Research & Forecasting model (WRF) the forecast error is sought quantified in dependence of the time scale involved. This task constitutes a preparative study for later implementation of features accounting for NWP forecast errors in the DTU Wind Energy maintained Corwind code - a long term wind power planning tool. Within the framework of PSO 10464 research related to operational short term wind power prediction will be carried out, including a comparison of forecast quality at different mesoscale NWP model resolutions and development of a statistical wind power prediction tool taking input from WRF. The short term prediction part of the project is carried out in collaboration with ENFOR A/S; a Danish company that specialises in forecasting and optimisation for the energy sector. The 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 short term prediction tool constitutes scenario forecasts for the coming period, which can then be fed into any type of system model or decision making problem to be solved. The high resolution of the WRF results loaded into the integrated prediction model will ensure a high accuracy data basis is available for use in the decision making process of the Danish transmission system operator. The need for high accuracy predictions will only increase over the next decade as Denmark approaches the goal of 50% wind power based electricity in 2025 from the current 20%.

Method for predicting water demand for crop uses in New Jersey in 1990, 2000, 2010, and 2020, and for estimating water use for livestock and selected sectors of the food-processing industry in New Jersey in 1987

USGS Publications Warehouse

Clawges, R.M.; Titus, E.O.

1993-01-01

A method was developed to predict water demand for crop uses in New Jersey. A separate method was developed to estimate water use for livestock and selected sectors of the food-processing industry in 1987. Predictions of water demand for field- grown crops in New Jersey were made for 1990, 2000, 2010, and 2020 under three climatological scenarios: (1) wet year, (2) average year, and (3) drought year. These estimates ranged from 4.10 times 10 to the 9th power to 16.82 times 10 to the 9th power gal (gallons). Irrigation amounts calculated for the three climatological scenarios by using a daily water-balance model were multiplied by predicted numbers of irrigated acreage. Irrigated acreage was predicted from historical crop-irrigation data and from predictions of harvested acreage produced by using a statistical model relating population to harvested acreage. Predictions of water demand for cranberries and container-grown nursery crops also were made for 1990, 2000, 2010, and 2020. Predictions of water demand under the three climatological scenarios were made for container- grown nursery crops, but not for cranberries, because water demand for cranberries varies little in response to climatological factors. Water demand for cranberries was predicted to remain constant at 4.43 times 10 to the 9th power gal through the year 2020. Predictions of water demand for container-grown nursery crops ranged from 1.89 times 10 to the 9th power to 3.63 times 10 to the 9th power gal. Water-use for livestock in 1987 was estimated to be 0.78 times 10 to the 9th power gal, and water use for selected sectors of the food-processing industry was estimated to be 3.75 times 10 to the 9th power gal.

Generation of non-classical correlated photon pairs via a ladder-type atomic configuration: theory and experiment.

PubMed

Ding, Dong-Sheng; Zhou, Zhi-Yuan; Shi, Bao-Sen; Zou, Xu-Bo; Guo, Guang-Can

2012-05-07

We experimentally generate a non-classical correlated two-color photon pair at 780 and 1529.4 nm in a ladder-type configuration using a hot 85Rb atomic vapor with the production rate of ~10(7)/s. The non-classical correlation between these two photons is demonstrated by strong violation of Cauchy-Schwarz inequality by the factor R = 48 ± 12. Besides, we experimentally investigate the relations between the correlation and some important experimental parameters such as the single-photon detuning, the powers of pumps. We also make a theoretical analysis in detail and the theoretical predictions are in reasonable agreement with our experimental results.

Lorentz invariance violation in the neutrino sector: a joint analysis from big bang nucleosynthesis and the cosmic microwave background

NASA Astrophysics Data System (ADS)

Dai, Wei-Ming; Guo, Zong-Kuan; Cai, Rong-Gen; Zhang, Yuan-Zhong

2017-06-01

We investigate constraints on Lorentz invariance violation in the neutrino sector from a joint analysis of big bang nucleosynthesis and the cosmic microwave background. The effect of Lorentz invariance violation during the epoch of big bang nucleosynthesis changes the predicted helium-4 abundance, which influences the power spectrum of the cosmic microwave background at the recombination epoch. In combination with the latest measurement of the primordial helium-4 abundance, the Planck 2015 data of the cosmic microwave background anisotropies give a strong constraint on the deformation parameter since adding the primordial helium measurement breaks the degeneracy between the deformation parameter and the physical dark matter density.

The role of multifamily therapy in promoting retention in treatment of alcohol and cocaine dependence.

PubMed

Conner, K R; Shea, R R; McDermott, M P; Grolling, R; Tocco, R V; Baciewicz, G

1998-01-01

The authors present a model for incorporating multifamily therapy in the treatment of chemical dependency and investigate the association of family participation in multifamily therapy group with treatment retention in a sample of 164 alcohol- and/or cocaine-dependent outpatients. Results indicate that level of family attendance at a multifamily group strongly predicted completion of short-term and long-term out-patient treatment. Effects were greater for cocaine-dependent than for alcohol-dependent subjects in analyses of short-term treatment retention. Multifamily therapy may be a powerful method to engage patients families in treatment and promote treatment retention, especially in the early, intensive phases of treatment for cocaine dependency.

Propagation of flexural waves in inhomogeneous plates exhibiting hysteretic nonlinearity: Nonlinear acoustic black holes.

PubMed

Gusev, Vitalyi E; Ni, Chenyin; Lomonosov, Alexey; Shen, Zhonghua

2015-08-01

Theory accounting for the influence of hysteretic nonlinearity of micro-inhomogeneous material on flexural wave in the plates of continuously varying thickness is developed. For the wedges with thickness increasing as a power law of distance from its edge strong modifications of the wave dynamics with propagation distance are predicted. It is found that nonlinear absorption progressively disappearing with diminishing wave amplitude leads to complete attenuation of acoustic waves in most of the wedges exhibiting black hole phenomenon. It is also demonstrated that black holes exist beyond the geometrical acoustic approximation. Applications include nondestructive evaluation of micro-inhomogeneous materials and vibrations damping. Copyright © 2015 Elsevier B.V. All rights reserved.

Experimental Challenges to Stiffness as a Transport Paradigm

NASA Astrophysics Data System (ADS)

Luce, T. C.

2017-10-01

Transport in plasmas is treated experimentally as a relationship between gradients and fluxes in analogy to the random-walk problem. Gyrokinetic models often predict strong increases in local flux for small increases in local gradient when above a threshold, holding all other parameters fixed. This has been named `stiffness'. The radial scalelength is then expected to vary little with source strength as a result of high stiffness. To probe the role of ExB shearing on stiffness in the DIII-D tokamak, two neutral beam injection power scans in H-mode plasmas were specially crafted-one with constant, low torque and one with increasing torque. The ion heat, electron heat, and ion toroidal momentum transport do not show expected signatures of stiffness, while the ion particle transport does. The ion heat transport shows the clearest discrepancy; the normalized heat flux drops with increasing inverse ion temperature scalelength. ExB shearing affects the transport magnitude, but not the scalelength dependence. Linear gyrofluid (TGLF) and nonlinear gyrokinetic (GYRO) predictions show stiff ion heat transport around the experimental profiles. The ion temperature gradient required to match the ion heat flux with increasing auxiliary power is not correctly described by TGLF, even when parameters are varied within the experimental uncertainties. TGLF also underpredicts transport at smaller radii, but overpredicts transport at larger radii. Independent of the theory/experiment comparison, it is not clear that the theoretical definition of stiffness yields any prediction about parameter scans such as the power scans here, because the quantities that must be held fixed to quantify stiffness are varied. A survey of recent literature indicated that profile resilience is routinely attributed to stiffness, but simple model calculations show profile resilience does not imply stiffness. Taken together, these observations challenge the use of local stiffness as a paradigm for explaining global transport behavior. Work supported by US DOE under DE-FC02-04ER54698.

Design of a thermosyphon-based thermal valve for controlled high-temperature heat extraction

DOE PAGES

Oshman, Christopher; Hardin, Corey; Rea, Jonathan; ...

2017-01-16

Conventional concentrated solar power (CSP) is a reliable alternative energy source that uses the sun’s heat to drive a heat engine to produce electrical power. An advantage of CSP is its ability to store thermal energy for use during off-sun hours which is typically done by storing sensible heat in molten salts. Alternatively, thermal energy may be stored as latent heat in a phase-change material (PCM), which stores large quantities of thermal energy in an isothermal process. On-sun, the PCM melts, storing energy. Off-sun, the latent heat is extracted to produce dispatchable electrical power. Here, this paper presents the designmore » of a thermosyphon-based device with sodium working fluid that is able to extract heat from a source as demand requires. A prototype has been designed to transfer 37 kW of thermal energy from a 600°C molten PCM tank to an array of 9% efficient thermoelectric generators (TEGs) to produce 3 kW of usable electrical energy for 5 h. This “thermal valve” design incorporates a funnel to collect condensate and a central shut-off valve to control condensate gravity return to the evaporator. Three circumferential tubes allow vapour transport up to the condenser. Pressure and a thermal resistance models were developed to predict the performance of the thermal valve. The pressure model predicts that the thermal valve will function as designed. The thermal resistance model predicts a 5500× difference in total thermal resistance between “on” and “off” states. The evaporator and condenser walls comprise 96% of the “on” thermal resistance, while the small parasitic heat transfer in the “off” state is primarily (77%) due to radiation losses. Lastly, this simple and effective technology can have a strong impact on the feasibility, scalability, and dispatchability of CSP latent storage. In addition, other industrial and commercial applications can benefit from this thermal valve concept.« less

Design of a thermosyphon-based thermal valve for controlled high-temperature heat extraction

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

Oshman, Christopher; Hardin, Corey; Rea, Jonathan

Conventional concentrated solar power (CSP) is a reliable alternative energy source that uses the sun’s heat to drive a heat engine to produce electrical power. An advantage of CSP is its ability to store thermal energy for use during off-sun hours which is typically done by storing sensible heat in molten salts. Alternatively, thermal energy may be stored as latent heat in a phase-change material (PCM), which stores large quantities of thermal energy in an isothermal process. On-sun, the PCM melts, storing energy. Off-sun, the latent heat is extracted to produce dispatchable electrical power. Here, this paper presents the designmore » of a thermosyphon-based device with sodium working fluid that is able to extract heat from a source as demand requires. A prototype has been designed to transfer 37 kW of thermal energy from a 600°C molten PCM tank to an array of 9% efficient thermoelectric generators (TEGs) to produce 3 kW of usable electrical energy for 5 h. This “thermal valve” design incorporates a funnel to collect condensate and a central shut-off valve to control condensate gravity return to the evaporator. Three circumferential tubes allow vapour transport up to the condenser. Pressure and a thermal resistance models were developed to predict the performance of the thermal valve. The pressure model predicts that the thermal valve will function as designed. The thermal resistance model predicts a 5500× difference in total thermal resistance between “on” and “off” states. The evaporator and condenser walls comprise 96% of the “on” thermal resistance, while the small parasitic heat transfer in the “off” state is primarily (77%) due to radiation losses. Lastly, this simple and effective technology can have a strong impact on the feasibility, scalability, and dispatchability of CSP latent storage. In addition, other industrial and commercial applications can benefit from this thermal valve concept.« less

Prognostic value of cardiac power output to left ventricular mass in patients with left ventricular dysfunction and dobutamine stress echo negative by wall motion criteria.

PubMed

Cortigiani, Lauro; Sorbo, Simone; Miccoli, Mario; Scali, Maria Chiara; Simioniuc, Anca; Morrone, Doralisa; Bovenzi, Francesco; Marzilli, Mario; Dini, Frank Lloyd

2017-02-01

Cardiac power output to left ventricular mass (power/mass) is an index of myocardial efficiency reflecting the rate at which cardiac work is delivered with respect to the potential energy stored in the left ventricular mass. In the present study, we sought to investigate the capability of power/mass assessed at peak of dobutamine stress echocardiography to predict mortality in patients with ischaemic cardiomyopathy and no inducible ischaemia. One-hundred eleven patients (95 males; age 68 ± 10 years) with 35 ± 7% mean left ventricular ejection fraction and a dobutamine stress echocardiography (up to 40 µg/kg/min) negative by wall motion criteria formed the study population. Power/mass at peak stress was obtained as the product of a constant (K = 2.22 × 10 -1 ) with cardiac output and the mean arterial pressure divided by left ventricular mass to convert the units to W/100 g. Patients were followed up for a median of 29 months (inter-quartile range 16-72 months). All-cause mortality was the only accepted clinical end point. Mean peak-stress power/mass was 0.70 ± 0.31 W/100 g. During follow-up, 29 deaths (26%) were registered. With a receiver operating characteristic analysis, a peak-stress power/mass ≤0.50 W/100 g [area under curve 0.72 (95% CI 0.63; 0.80), sensitivity 59%, specificity 80%] was the best value for predicting mortality. Univariate prognostic indicators were age, male sex, peak-stress ejection fraction, peak-stress stroke volume, peak-stress cardiac output, peak-stress cardiac power output ≤1.48 W, and peak-stress power/mass ≤0.50 W/100 g. At multivariate analysis, age (HR 1.08, 95% CI 1.04; 1.14; P = 0.004) and peak-stress power/mass ≤0.50 W/100 g (HR 4.05, 95% CI 1.36; 12.00; P = 0.01) provided independent prognostic information. Three-year mortality was 14% in patients with peak-stress power/mass >0.50 W/100 g and 47% in those with peak-stress power/mass ≤0.50 W/100 g (log-rank 20.4; P < 0.0001). Power/mass assessed at peak of dobutamine stress echocardiography allows effective prognostication in patients with ischaemic cardiomyopathy and test result negative by wall motion criteria. In particular, a peak-stress power/mass ≤50 W/100 g is a strong and multivariable predictor of mortality. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2016. For permissions please email: journals.permissions@oup.com.

Band structure and thermoelectric properties of half-Heusler semiconductors from many-body perturbation theory

NASA Astrophysics Data System (ADS)

Zahedifar, Maedeh; Kratzer, Peter

2018-01-01

Various ab initio approaches to the band structure of A NiSn and A CoSb half-Heusler compounds (A = Ti, Zr, Hf) are compared and their consequences for the prediction of thermoelectric properties are explored. Density functional theory with the generalized-gradient approximation (GGA), as well as the hybrid density functional HSE06 and ab initio many-body perturbation theory in the form of the G W0 approach, are employed. The G W0 calculations confirm the trend of a smaller band gap (0.75 to 1.05 eV) in A NiSn compared to the A CoSb compounds (1.13 to 1.44 eV) already expected from the GGA calculations. While in A NiSn materials the G W0 band gap is 20% to 50% larger than in HSE06, the fundamental gap of A CoSb materials is smaller in G W0 compared to HSE06. This is because G W0 , similar to PBE, locates the valence band maximum at the L point of the Brillouin zone, whereas it is at the Γ point in the HSE06 calculations. The differences are attributed to the observation that the relative positions of the d levels of the transition metal atoms vary among the different methods. Using the calculated band structures and scattering rates taking into account the band effective masses at the extrema, the Seebeck coefficients, thermoelectric power factors, and figures of merit Z T are predicted for all six half-Heusler compounds. Comparable performance is predicted for the n -type A NiSn materials, whereas clear differences are found for the p -type A CoSb materials. Using the most reliable G W0 electronic structure, ZrCoSb is predicted to be the most efficient material with a power factor of up to 0.07 W/(K2 m) at a temperature of 600 K. We find strong variations among the different ab initio methods not only in the prediction of the maximum power factor and Z T value of a given material, but also in comparing different materials to each other, in particular in the p -type thermoelectric materials. Thus we conclude that the most elaborate, but also most costly G W0 method is required to perform a reliable computational search for the optimum material.

Transient Simulation of the Multi-SERTTA Experiment with MAMMOTH

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

Ortensi, Javier; Baker, Benjamin; Wang, Yaqi

This work details the MAMMOTH reactor physics simulations of the Static Environment Rodlet Transient Test Apparatus (SERTTA) conducted at Idaho National Laboratory in FY-2017. TREAT static-environment experiment vehicles are being developed to enable transient testing of Pressurized Water Reactor (PWR) type fuel specimens, including fuel concepts with enhanced accident tolerance (Accident Tolerant Fuels, ATF). The MAMMOTH simulations include point reactor kinetics as well as spatial dynamics for a temperature-limited transient. The strongly coupled multi-physics solutions of the neutron flux and temperature fields are second order accurate both in the spatial and temporal domains. MAMMOTH produces pellet stack powers that are within 1.5% of the Monte Carlo reference solutions. Some discrepancies between the MCNP model used in the design of the flux collars and the Serpent/MAMMOTH models lead to higher power and energy deposition values in Multi-SERTTA unit 1. The TREAT core results compare well with the safety case computed with point reactor kinetics in RELAP5-3D. The reactor period is 44 msec, which corresponds to a reactivity insertion of 2.685% delta k/kmore » $. The peak core power in the spatial dynamics simulation is 431 MW, which the point kinetics model over-predicts by 12%. The pulse width at half the maximum power is 0.177 sec. Subtle transient effects are apparent at the beginning insertion in the experimental samples due to the control rod removal. Additional difference due to transient effects are observed in the sample powers and enthalpy. The time dependence of the power coupling factor (PCF) is calculated for the various fuel stacks of the Multi-SERTTA vehicle. Sample temperatures in excess of 3100 K, the melting point UO$$_2$$, are computed with the adiabatic heat transfer model. The planned shaped-transient might introduce additional effects that cannot be predicted with PRK models. Future modeling will be focused on the shaped-transient by improving the control rod models in MAMMOTH and adding the BISON thermo-elastic models and thermal-fluids heat transfer.« less

A deformation-processed Al-matrix/Ca-nanofilamentary composite with low density, high strength, and high conductivity

DOE PAGES

Tian, Liang

2017-03-06

Light, strong materials with high conductivity are desired for many applications such as power transmission conductors, fly-by-wire systems, and downhole power feeds. However, it is difficult to obtain both high strength and high conductivity simultaneously in a material. In this study, an Al/Ca (20 vol%) nanofilamentary metal-metal composite was produced by powder metallurgy and severe plastic deformation. Fine Ca metal powders (~200 µm) were produced by centrifugal atomization, mixed with pure Al powder, and deformed by warm extrusion, swaging, and wire drawing to a true strain of 12.9. The Ca powder particles became fine Ca nanofilaments that reinforce the compositemore » substantially by interface strengthening. The conductivity of the composite is slightly lower than the rule-of-mixtures prediction due to minor quantities of impurity inclusions. As a result, the elevated temperature performance of this composite was also evaluated by differential scanning calorimetry and resistivity measurements.« less

Near-self-imaging cavity for three-mode optoacoustic parametric amplifiers using silicon microresonators.

PubMed

Liu, Jian; Torres, F A; Ma, Yubo; Zhao, C; Ju, L; Blair, D G; Chao, S; Roch-Jeune, I; Flaminio, R; Michel, C; Liu, K-Y

2014-02-10

Three-mode optoacoustic parametric amplifiers (OAPAs), in which a pair of photon modes are strongly coupled to an acoustic mode, provide a general platform for investigating self-cooling, parametric instability and very sensitive transducers. Their realization requires an optical cavity with tunable transverse modes and a high quality-factor mirror resonator. This paper presents the design of a table-top OAPA based on a near-self-imaging cavity design, using a silicon torsional microresonator. The design achieves a tuning coefficient for the optical mode spacing of 2.46  MHz/mm. This allows tuning of the mode spacing between amplification and self-cooling regimes of the OAPA device. Based on demonstrated resonator parameters (frequencies ∼400  kHz and quality-factors ∼7.5×10(5) we predict that the OAPA can achieve parametric instability with 1.6 μW of input power and mode cooling by a factor of 1.9×10(4) with 30 mW of input power.

Water soluble polysaccharides from Spirulina platensis: extraction and in vitro anti-cancer activity.

PubMed

Kurd, Forouzan; Samavati, Vahid

2015-03-01

Polysaccharides from Spirulina platensis algae (SP) were extracted by ultrasound-assisted extraction procedure. The optimal conditions for ultrasonic extraction of SP were determined by response surface methodology. The four parameters were, extraction time (X1), extraction temperature (X2), ultrasonic power (X3) and the ratio of water to raw material (X4), respectively. The experimental data obtained were fitted to a second-order polynomial equation. The optimum conditions were extraction time of 25 min, extraction temperature 85°C, ultrasonic power 90 W and ratio of water to raw material 20 mL/g. Under these optimal conditions, the experimental yield was 13.583±0.51%, well matched with the predicted models with the coefficients of determination (R2) of 0.9971. Then, we demonstrated that SP polysaccharides had strong scavenging activities in vitro on DPPH and hydroxyl radicals. Overall, SP may have potential applications in the medical and food industries. Copyright © 2015 Elsevier B.V. All rights reserved.

Alcohol use, sexual relationship power, and unprotected sex among patrons in bars and taverns in rural areas of North West province, South Africa.

PubMed

Nkosi, Sebenzile; Rich, Eileen P; Morojele, Neo K

2014-11-01

We examined the relative importance of alcohol consumption and sexual relationship power (SRP) in predicting unprotected sex among 406 bar patrons in North West province, South Africa. We assessed participants' demographic characteristics, alcohol consumption, SRP, and number of unprotected sexual episodes in the past 6 months. In correlational analyses, alcohol consumption was significantly associated with frequency of unprotected sex for both males and females. SRP was significantly associated with frequency of unprotected sex for males and marginally associated for females. In multivariate regression analyses, alcohol consumption was significantly associated with frequency of unprotected sex for both males and females. SRP's association was marginally significant for females and not significant for males. Alcohol consumption is more strongly associated with unprotected sex than is SRP among bar patrons. Combination HIV prevention approaches to curb problem drinking and increase condom accessibility, and regular and effective use are needed in tavern settings. SRP needs further examination among tavern populations.

Capacitively coupled hydrogen plasmas sustained by tailored voltage waveforms: excitation dynamics and ion flux asymmetry

DOE PAGES

Bruneau, B.; Diomede, P.; Economou, D. J.; ...

2016-06-08

Parallel plate capacitively coupled plasmas in hydrogen at relatively high pressure (~1 Torr) are excited with tailored voltage waveforms containing up to five frequencies. Predictions of a hybrid model combining a particle-in-cell simulation with Monte Carlo collisions and a fluid model are compared to phase resolved optical emission spectroscopy measurements, yielding information on the dynamics of the excitation rate in these discharges. When the discharge is excited with amplitude asymmetric waveforms, the discharge becomes electrically asymmetric, with different ion energies at each of the two electrodes. Unexpectedly, large differences in themore » $$\\text{H}_{2}^{+}$$ fluxes to each of the two electrodes are caused by the different $$\\text{H}_{3}^{+}$$ energies. When the discharge is excited with slope asymmetric waveforms, only weak electrical asymmetry of the discharge is observed. In this case, electron power absorption due to fast sheath expansion at one electrode is balanced by electron power absorption at the opposite electrode due to a strong electric field reversal.« less

Optimisation of pressurised water extraction of polysaccharides from blackcurrant and its antioxidant activity.

PubMed

Xu, Yaqin; Cai, Fei; Yu, Zeyuan; Zhang, Ling; Li, Xingguo; Yang, Yu; Liu, Gaijie

2016-03-01

Pressurised water extraction (PWE) of polysaccharides from blackcurrant fruits was investigated using a response surface methodology (RSM). The optimal conditions for PWE were: time 51min, pressure 1.6MPa, and temperature 52°C. Under these conditions, the experimental yield of Ribes nigrum L. polysaccharides (RNLP) was 11.68±0.12%, which closely agreed with the predicted value (11.77%). After preliminary purification with D4006 macroporous resin, RNLP I was obtained and its chemical characterisation was undertaken by GC, HPLC, and IR spectroscopy. RNLP I was composed of rhamnose, arabinose, xylose, mannose, galactose, and glucose with a molar ratio of 2.89:14.82:1.02:1.00:2.53:6.39 and its molecular weight was 1.49×10(4)kDa. The antioxidant activity of RNLP I was evaluated by free radical scavenging assays and a reducing power assay in vitro. RNLP I showed strong DPPH and superoxide radical scavenging activities and reducing power. Copyright © 2015 Elsevier Ltd. All rights reserved.

A deformation-processed Al-matrix/Ca-nanofilamentary composite with low density, high strength, and high conductivity

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

Tian, Liang

Light, strong materials with high conductivity are desired for many applications such as power transmission conductors, fly-by-wire systems, and downhole power feeds. However, it is difficult to obtain both high strength and high conductivity simultaneously in a material. In this study, an Al/Ca (20 vol%) nanofilamentary metal-metal composite was produced by powder metallurgy and severe plastic deformation. Fine Ca metal powders (~200 µm) were produced by centrifugal atomization, mixed with pure Al powder, and deformed by warm extrusion, swaging, and wire drawing to a true strain of 12.9. The Ca powder particles became fine Ca nanofilaments that reinforce the compositemore » substantially by interface strengthening. The conductivity of the composite is slightly lower than the rule-of-mixtures prediction due to minor quantities of impurity inclusions. As a result, the elevated temperature performance of this composite was also evaluated by differential scanning calorimetry and resistivity measurements.« less

Dinucleotide Composition in Animal RNA Viruses Is Shaped More by Virus Family than by Host Species

PubMed Central

Di Giallonardo, Francesca; Schlub, Timothy E.; Shi, Mang

2017-01-01

ABSTRACT Viruses use the cellular machinery of their hosts for replication. It has therefore been proposed that the nucleotide and dinucleotide compositions of viruses should match those of their host species. If this is upheld, it may then be possible to use dinucleotide composition to predict the true host species of viruses sampled in metagenomic surveys. However, it is also clear that different taxonomic groups of viruses tend to have distinctive patterns of dinucleotide composition that may be independent of host species. To determine the relative strength of the effect of host versus virus family in shaping dinucleotide composition, we performed a comparative analysis of 20 RNA virus families from 15 host groupings, spanning two animal phyla and more than 900 virus species. In particular, we determined the odds ratios for the 16 possible dinucleotides and performed a discriminant analysis to evaluate the capability of virus dinucleotide composition to predict the correct virus family or host taxon from which it was isolated. Notably, while 81% of the data analyzed here were predicted to the correct virus family, only 62% of these data were predicted to their correct subphylum/class host and a mere 32% to their correct mammalian order. Similarly, dinucleotide composition has a weak predictive power for different hosts within individual virus families. We therefore conclude that dinucleotide composition is generally uniform within a virus family but less well reflects that of its host species. This has obvious implications for attempts to accurately predict host species from virus genome sequences alone. IMPORTANCE Determining the processes that shape virus genomes is central to understanding virus evolution and emergence. One question of particular importance is why nucleotide and dinucleotide frequencies differ so markedly between viruses. In particular, it is currently unclear whether host species or virus family has the biggest impact on dinucleotide frequencies and whether dinucleotide composition can be used to accurately predict host species. Using a comparative analysis, we show that dinucleotide composition has a strong phylogenetic association across different RNA virus families, such that dinucleotide composition can predict the family from which a virus sequence has been isolated. Conversely, dinucleotide composition has a poorer predictive power for the different host species within a virus family and across different virus families, indicating that the host has a relatively small impact on the dinucleotide composition of a virus genome. PMID:28148785

Application of clustering analysis in the prediction of photovoltaic power generation based on neural network

NASA Astrophysics Data System (ADS)

Cheng, K.; Guo, L. M.; Wang, Y. K.; Zafar, M. T.

2017-11-01

In order to select effective samples in the large number of data of PV power generation years and improve the accuracy of PV power generation forecasting model, this paper studies the application of clustering analysis in this field and establishes forecasting model based on neural network. Based on three different types of weather on sunny, cloudy and rainy days, this research screens samples of historical data by the clustering analysis method. After screening, it establishes BP neural network prediction models using screened data as training data. Then, compare the six types of photovoltaic power generation prediction models before and after the data screening. Results show that the prediction model combining with clustering analysis and BP neural networks is an effective method to improve the precision of photovoltaic power generation.

Electrophoresis in strong electric fields.

PubMed

Barany, Sandor

2009-01-01

Two kinds of non-linear electrophoresis (ef) that can be detected in strong electric fields (several hundred V/cm) are considered. The first ("classical" non-linear ef) is due to the interaction of the outer field with field-induced ionic charges in the electric double layer (EDL) under conditions, when field-induced variations of electrolyte concentration remain to be small comparatively to its equilibrium value. According to the Shilov theory, the non-linear component of the electrophoretic velocity for dielectric particles is proportional to the cubic power of the applied field strength (cubic electrophoresis) and to the second power of the particles radius; it is independent of the zeta-potential but is determined by the surface conductivity of particles. The second one, the so-called "superfast electrophoresis" is connected with the interaction of a strong outer field with a secondary diffuse layer of counterions (space charge) that is induced outside the primary (classical) diffuse EDL by the external field itself because of concentration polarization. The Dukhin-Mishchuk theory of "superfast electrophoresis" predicts quadratic dependence of the electrophoretic velocity of unipolar (ionically or electronically) conducting particles on the external field gradient and linear dependence on the particle's size in strong electric fields. These are in sharp contrast to the laws of classical electrophoresis (no dependence of V(ef) on the particle's size and linear dependence on the electric field gradient). A new method to measure the ef velocity of particles in strong electric fields is developed that is based on separation of the effects of sedimentation and electrophoresis using videoimaging and a new flowcell and use of short electric pulses. To test the "classical" non-linear electrophoresis, we have measured the ef velocity of non-conducting polystyrene, aluminium-oxide and (semiconductor) graphite particles as well as Saccharomice cerevisiae yeast cells as a function of the electric field strength, particle size, electrolyte concentration and the adsorbed polymer amount. It has been shown that the electrophoretic velocity of the particles/cells increases with field strength linearly up to about 100 and 200 V/cm (for cells) without and with adsorbed polymers both in pure water and in electrolyte solutions. In line with the theoretical predictions, in stronger fields substantial non-linear effects were recorded (V(ef)~E(3)). The ef velocity of unipolar ion-type conducting (ion-exchanger particles and fibres), electron-type conducting (magnesium and Mg/Al alloy) and semiconductor particles (graphite, activated carbon, pyrite, molybdenite) increases significantly with the electric field (V(ef)~E(2)) and the particle's size but is almost independent of the ionic strength. These trends are inconsistent with Smoluchowski's equation for dielectric particles, but are consistent with the Dukhin-Mishchuk theory of superfast electrophoresis.

Integrated modelling of H-mode pedestal and confinement in JET-ILW

NASA Astrophysics Data System (ADS)

Saarelma, S.; Challis, C. D.; Garzotti, L.; Frassinetti, L.; Maggi, C. F.; Romanelli, M.; Stokes, C.; Contributors, JET

2018-01-01

A pedestal prediction model Europed is built on the existing EPED1 model by coupling it with core transport simulation using a Bohm-gyroBohm transport model to self-consistently predict JET-ILW power scan for hybrid plasmas that display weaker power degradation than the IPB98(y, 2) scaling of the energy confinement time. The weak power degradation is reproduced in the coupled core-pedestal simulation. The coupled core-pedestal model is further tested for a 3.0 MA plasma with the highest stored energy achieved in JET-ILW so far, giving a prediction of the stored plasma energy within the error margins of the measured experimental value. A pedestal density prediction model based on the neutral penetration is tested on a JET-ILW database giving a prediction with an average error of 17% from the experimental data when a parameter taking into account the fuelling rate is added into the model. However the model fails to reproduce the power dependence of the pedestal density implying missing transport physics in the model. The future JET-ILW deuterium campaign with increased heating power is predicted to reach plasma energy of 11 MJ, which would correspond to 11-13 MW of fusion power in equivalent deuterium-tritium plasma but with isotope effects on pedestal stability and core transport ignored.

Powering prolonged hydrothermal activity inside Enceladus

NASA Astrophysics Data System (ADS)

Choblet, Gaël; Tobie, Gabriel; Sotin, Christophe; Běhounková, Marie; Čadek, Ondřej; Postberg, Frank; Souček, Ondřej

2017-12-01

Geophysical data from the Cassini spacecraft imply the presence of a global ocean underneath the ice shell of Enceladus1, only a few kilometres below the surface in the South Polar Terrain2-4. Chemical analyses indicate that the ocean is salty5 and is fed by ongoing hydrothermal activity6-8. In order to explain these observations, an abnormally high heat power (>20 billion watts) is required, as well as a mechanism to focus endogenic activity at the south pole9,10. Here, we show that more than 10 GW of heat can be generated by tidal friction inside the unconsolidated rocky core. Water transport in the tidally heated permeable core results in hot narrow upwellings with temperatures exceeding 363 K, characterized by powerful (1-5 GW) hotspots at the seafloor, particularly at the south pole. The release of heat in narrow regions favours intense interaction between water and rock, and the transport of hydrothermal products from the core to the plume sources. We are thus able to explain the main global characteristics of Enceladus: global ocean, strong dissipation, reduced ice-shell thickness at the south pole and seafloor activity. We predict that this endogenic activity can be sustained for tens of millions to billions of years.

Fresh and Dry Mass Estimates of Hermetia illucens (Linnaeus, 1758) (Diptera: Stratiomyidae) Larvae Associated with Swine Decomposition in Urban Area of Central Amazonia.

PubMed

Barros, L M; Martins, R T; Ferreira-Keppler, R L; Gutjahr, A L N

2017-08-04

Information on biomass is substantial for calculating growth rates and may be employed in the medicolegal and economic importance of Hermetia illucens (Linnaeus, 1758). Although biomass is essential to understanding many ecological processes, it is not easily measured. Biomass may be determined by directly weighing or indirectly through regression models of fresh/dry mass versus body dimensions. In this study, we evaluated the association between morphometry and fresh/dry mass of immature H. illucens using linear, exponential, and power regression models. We measured width and length of the cephalic capsule, overall body length, and width of the largest abdominal segment of 280 larvae. Overall body length and width of the largest abdominal segment were the best predictors for biomass. Exponential models best fitted body dimensions and biomass (both fresh and dry), followed by power and linear models. In all models, fresh and dry biomass were strongly correlated (>75%). Values estimated by the models did not differ from observed ones, and prediction power varied from 27 to 79%. Accordingly, the correspondence between biomass and body dimensions should facilitate and motivate the development of applied studies involving H. illucens in the Amazon region.

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.

LOCAL IMPACTS OF MERCURY EMISSIONS FROM COAL FIRED POWER PLANTS.

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

SULLIVAN, T.M.; BOWERMAN, B.; ADAMS, J.

2004-03-30

A thorough quantitative understanding of the processes of mercury emissions, deposition, and translocation through the food chain is currently not available. Complex atmospheric chemistry and dispersion models are required to predict concentration and deposition contributions, and aquatic process models are required to predict effects on fish. There are uncertainties in all of these predictions. Therefore, the most reliable method of understanding impacts of coal-fired power plants on Hg deposition is from empirical data. A review of the literature on mercury deposition around sources including coal-fired power plants found studies covering local mercury concentrations in soil, vegetation, and animals (fish andmore » cows (Lopez et al. 2003)). There is strong evidence of enhanced local deposition within 3 km of the chlor-alkali plants, with elevated soil concentrations and estimated deposition rates of 10 times background. For coal-fired power plants, the data show that atmospheric deposition of Hg may be slightly enhanced. On the scale of a few km, modeling suggests that wet deposition may be increased by a factor of two or three over background. The measured data suggest lower increases of 15% or less. The effects of coal-fired plants seem to be less than 10% of total deposition on a national scale, based on emissions and global modeling. The following summarizes our findings from published reports on the impacts of local deposition. In terms of excesses over background the following increments have been observed within a few km of the plant: (1) local soil concentration Hg increments of 30%-60%, (2) sediment increments of 18-30%, (3) wet deposition increments of 11-12%, and (4) fish Hg increments of about 5-6%, based on an empirical finding that fish concentrations are proportional to the square root of deposition. Important uncertainties include possible reductions of RGM to Hg(0) in power plant plumes and the role of water chemistry in the relationship between Hg deposition and fish content. Soil and vegetation sampling programs were performed around two mid-size coal fired power plants. The objectives were to determine if local mercury hot spots exist, to determine if they could be attributed to deposition of coal-fired power plant emissions, and to determine if they correlated with model predictions. These programs found the following: (1) At both sites, there was no correlation between modeled mercury deposition and either soil concentrations or vegetation concentrations. At the Kincaid plant, there was excess soil Hg along heavily traveled roads. The spatial pattern of soil mercury concentrations did not match the pattern of vegetation Hg concentrations at either plant. (2) At both sites, the subsurface (5-10 cm) samples the Hg concentration correlated strongly with the surface samples (0-5 cm). Average subsurface sample concentrations were slightly less than the surface samples, however, the difference was not statistically significant. (3) An unequivocal definition of background Hg was not possible at either site. Using various assumed background soil mercury concentrations, the percentage of mercury deposited within 10 km of the plant ranged between 1.4 and 8.5% of the RGM emissions. Based on computer modeling, Hg deposition was primarily RGM with much lower deposition from elemental mercury. Estimates of the percentage of total Hg deposition ranged between 0.3 and 1.7%. These small percentages of deposition are consistent with the empirical findings of only minor perturbations in environmental levels, as opposed to ''hot spots'', near the plants. The major objective of this study was to determine if there was evidence for ''hot spots'' of mercury deposition around coal-fired power plants. Although the term has been used extensively, it has never been defined. From a public health perspective, such a ''hot spot'' must be large enough to insure that it did not occur by chance, and it must affect water bodies large enough to support a population of subsistence fishers. The results of this study support the hypothesis that neither of these conditions have been met.« less

Strong ground motion prediction using virtual earthquakes.

PubMed

Denolle, M A; Dunham, E M; Prieto, G A; Beroza, G C

2014-01-24

Sedimentary basins increase the damaging effects of earthquakes by trapping and amplifying seismic waves. Simulations of seismic wave propagation in sedimentary basins capture this effect; however, there exists no method to validate these results for earthquakes that have not yet occurred. We present a new approach for ground motion prediction that uses the ambient seismic field. We apply our method to a suite of magnitude 7 scenario earthquakes on the southern San Andreas fault and compare our ground motion predictions with simulations. Both methods find strong amplification and coupling of source and structure effects, but they predict substantially different shaking patterns across the Los Angeles Basin. The virtual earthquake approach provides a new approach for predicting long-period strong ground motion.

Predictive modelling of grain-size distributions from marine electromagnetic profiling data using end-member analysis and a radial basis function network

NASA Astrophysics Data System (ADS)

Baasch, B.; Müller, H.; von Dobeneck, T.

2018-07-01

In this work, we present a new methodology to predict grain-size distributions from geophysical data. Specifically, electric conductivity and magnetic susceptibility of seafloor sediments recovered from electromagnetic profiling data are used to predict grain-size distributions along shelf-wide survey lines. Field data from the NW Iberian shelf are investigated and reveal a strong relation between the electromagnetic properties and grain-size distribution. The here presented workflow combines unsupervised and supervised machine-learning techniques. Non-negative matrix factorization is used to determine grain-size end-members from sediment surface samples. Four end-members were found, which well represent the variety of sediments in the study area. A radial basis function network modified for prediction of compositional data is then used to estimate the abundances of these end-members from the electromagnetic properties. The end-members together with their predicted abundances are finally back transformed to grain-size distributions. A minimum spatial variation constraint is implemented in the training of the network to avoid overfitting and to respect the spatial distribution of sediment patterns. The predicted models are tested via leave-one-out cross-validation revealing high prediction accuracy with coefficients of determination (R2) between 0.76 and 0.89. The predicted grain-size distributions represent the well-known sediment facies and patterns on the NW Iberian shelf and provide new insights into their distribution, transition and dynamics. This study suggests that electromagnetic benthic profiling in combination with machine learning techniques is a powerful tool to estimate grain-size distribution of marine sediments.

Predictive modelling of grain size distributions from marine electromagnetic profiling data using end-member analysis and a radial basis function network

NASA Astrophysics Data System (ADS)

Baasch, B.; M"uller, H.; von Dobeneck, T.

2018-04-01

In this work we present a new methodology to predict grain-size distributions from geophysical data. Specifically, electric conductivity and magnetic susceptibility of seafloor sediments recovered from electromagnetic profiling data are used to predict grain-size distributions along shelf-wide survey lines. Field data from the NW Iberian shelf are investigated and reveal a strong relation between the electromagnetic properties and grain-size distribution. The here presented workflow combines unsupervised and supervised machine learning techniques. Nonnegative matrix factorisation is used to determine grain-size end-members from sediment surface samples. Four end-members were found which well represent the variety of sediments in the study area. A radial-basis function network modified for prediction of compositional data is then used to estimate the abundances of these end-members from the electromagnetic properties. The end-members together with their predicted abundances are finally back transformed to grain-size distributions. A minimum spatial variation constraint is implemented in the training of the network to avoid overfitting and to respect the spatial distribution of sediment patterns. The predicted models are tested via leave-one-out cross-validation revealing high prediction accuracy with coefficients of determination (R2) between 0.76 and 0.89. The predicted grain-size distributions represent the well-known sediment facies and patterns on the NW Iberian shelf and provide new insights into their distribution, transition and dynamics. This study suggests that electromagnetic benthic profiling in combination with machine learning techniques is a powerful tool to estimate grain-size distribution of marine sediments.

Phase change alloy viscosities down to T{sub g} using Adam-Gibbs-equation fittings to excess entropy data: A fragile-to-strong transition

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

Wei, Shuai, E-mail: shuai.wei@asu.edu; Department of Materials Science and Engineering, University of Arizona, Tucson, Arizona 85712; Lucas, Pierre

2015-07-21

A striking anomaly in the viscosity of Te{sub 85}Ge{sub 15} alloys noted by Greer and coworkers from the work of Neumann et al. is reminiscent of the equally striking comparison of liquid tellurium and water anomalies documented long ago by Kanno et al. In view of the power laws that are used to fit the data on water, we analyze the data on Te{sub 85}Ge{sub 15} using the Speedy-Angell power-law form, and find a good account with a singularity T{sub s} only 25 K below the eutectic temperature. However, the heat capacity data in this case are not diverging, but insteadmore » exhibit a sharp maximum like that observed in fast cooling in the Molinero-Moore model of water. Applying the Adam-Gibbs viscosity equation to these calorimetric data, we find that there must be a fragile-to-strong liquid transition at the heat capacity peak temperature, and then predict the 'strong' liquid course of the viscosity down to T{sub g} at 406 K (403.6 K at 20 K min{sup −1} in this study). Since crystallization can be avoided by moderately fast cooling in this case, we can check the validity of the extrapolation by making a direct measurement of fragility at T{sub g}, using differential scanning calorimetric techniques, and then comparing with the value from the extrapolated viscosity at T{sub g}. The agreement is encouraging, and prompts discussion of relations between water and phase change alloy anomalies.« less

Epithelial–mesenchymal transition biomarkers and support vector machine guided model in preoperatively predicting regional lymph node metastasis for rectal cancer

PubMed Central

Fan, X-J; Wan, X-B; Huang, Y; Cai, H-M; Fu, X-H; Yang, Z-L; Chen, D-K; Song, S-X; Wu, P-H; Liu, Q; Wang, L; Wang, J-P

2012-01-01

Background: Current imaging modalities are inadequate in preoperatively predicting regional lymph node metastasis (RLNM) status in rectal cancer (RC). Here, we designed support vector machine (SVM) model to address this issue by integrating epithelial–mesenchymal-transition (EMT)-related biomarkers along with clinicopathological variables. Methods: Using tissue microarrays and immunohistochemistry, the EMT-related biomarkers expression was measured in 193 RC patients. Of which, 74 patients were assigned to the training set to select the robust variables for designing SVM model. The SVM model predictive value was validated in the testing set (119 patients). Results: In training set, eight variables, including six EMT-related biomarkers and two clinicopathological variables, were selected to devise SVM model. In testing set, we identified 63 patients with high risk to RLNM and 56 patients with low risk. The sensitivity, specificity and overall accuracy of SVM in predicting RLNM were 68.3%, 81.1% and 72.3%, respectively. Importantly, multivariate logistic regression analysis showed that SVM model was indeed an independent predictor of RLNM status (odds ratio, 11.536; 95% confidence interval, 4.113–32.361; P<0.0001). Conclusion: Our SVM-based model displayed moderately strong predictive power in defining the RLNM status in RC patients, providing an important approach to select RLNM high-risk subgroup for neoadjuvant chemoradiotherapy. PMID:22538975

Predicting the composition of red wine blends using an array of multicomponent Peptide-based sensors.

PubMed

Ghanem, Eman; Hopfer, Helene; Navarro, Andrea; Ritzer, Maxwell S; Mahmood, Lina; Fredell, Morgan; Cubley, Ashley; Bolen, Jessica; Fattah, Rabia; Teasdale, Katherine; Lieu, Linh; Chua, Tedmund; Marini, Federico; Heymann, Hildegarde; Anslyn, Eric V

2015-05-20

Differential sensing using synthetic receptors as mimics of the mammalian senses of taste and smell is a powerful approach for the analysis of complex mixtures. Herein, we report on the effectiveness of a cross-reactive, supramolecular, peptide-based sensing array in differentiating and predicting the composition of red wine blends. Fifteen blends of Cabernet Sauvignon, Merlot and Cabernet Franc, in addition to the mono varietals, were used in this investigation. Linear Discriminant Analysis (LDA) showed a clear differentiation of blends based on tannin concentration and composition where certain mono varietals like Cabernet Sauvignon seemed to contribute less to the overall characteristics of the blend. Partial Least Squares (PLS) Regression and cross validation were used to build a predictive model for the responses of the receptors to eleven binary blends and the three mono varietals. The optimized model was later used to predict the percentage of each mono varietal in an independent test set composted of four tri-blends with a 15% average error. A partial least square regression model using the mouth-feel and taste descriptive sensory attributes of the wine blends revealed a strong correlation of the receptors to perceived astringency, which is indicative of selective binding to polyphenols in wine.

Antibubble and prediction of China's stock market and real-estate

NASA Astrophysics Data System (ADS)

Zhou, Wei-Xing; Sornette, Didier

2004-06-01

We show that the Chinese stock markets are quite different and decoupled from Western markets (which include Tokyo). We document a well-developed log-periodic power-law antibubble in China's stock market, which started in August 2001. We argue that the current stock market antibubble is sustained by a contemporary active unsustainable real-estate bubble in China. The characteristic parameters of the antibubble have exhibited remarkable stability over one year (October 2002-October 2003). Many tests, including predictability over different horizons and time periods, confirm the high significance of the antibubble detection. Based on an analysis including data up to 2003/10/28, we have predicted that the Chinese stock market will stop its negative trend around the end of 2003 and start going up, appreciating by at least 25% in the following 6 months. We present a partial assessment of this prediction at the time of revision of this manuscript (early January 2004). Notwithstanding the immature nature of the Chinese equity market and the strong influence of government policy, we have found maybe even stronger imprints of herding than in other mature markets. This is maybe due indeed to the immaturity of the Chinese market which seems to attract short-term investors more interested in fast gains than in long-term investments, thus promoting speculative herding.

Plant interactions alter the predictions of metabolic scaling theory.

PubMed

Lin, Yue; Berger, Uta; Grimm, Volker; Huth, Franka; Weiner, Jacob

2013-01-01

Metabolic scaling theory (MST) is an attempt to link physiological processes of individual organisms with macroecology. It predicts a power law relationship with an exponent of -4/3 between mean individual biomass and density during density-dependent mortality (self-thinning). Empirical tests have produced variable results, and the validity of MST is intensely debated. MST focuses on organisms' internal physiological mechanisms but we hypothesize that ecological interactions can be more important in determining plant mass-density relationships induced by density. We employ an individual-based model of plant stand development that includes three elements: a model of individual plant growth based on MST, different modes of local competition (size-symmetric vs. -asymmetric), and different resource levels. Our model is consistent with the observed variation in the slopes of self-thinning trajectories. Slopes were significantly shallower than -4/3 if competition was size-symmetric. We conclude that when the size of survivors is influenced by strong ecological interactions, these can override predictions of MST, whereas when surviving plants are less affected by interactions, individual-level metabolic processes can scale up to the population level. MST, like thermodynamics or biomechanics, sets limits within which organisms can live and function, but there may be stronger limits determined by ecological interactions. In such cases MST will not be predictive.

The interference of flexible working times with the circadian temperature rhythm--a predictor of impairment to health and well-being?

PubMed

Giebel, Ole; Wirtz, Anna; Nachreiner, Friedhelm

2008-04-01

In order to analyze whether impairments to health and well-being under flexible working hours can be predicted from specific characteristics of the work schedules, periodic components in flexible working hours and their interference with the circadian temperature rhythm were analyzed applying univariate and bivariate spectrum analyses to both time series. The resulting indicators of spectral power and phase shift of these components were then related to reported health impairments using regression analysis. The results show that a suppression of both the 24 and the 168 h components in the work schedules (i.e., a lack of periodicity) can be used to predict reported health impairments, and that if there are relatively strong 24 and 168 h components left in the work schedules, their phase difference with the temperature rhythm (as an indicator of the interference between working time and the circadian rhythm) further predicts impairment. The results indicate that the periodicity of working hours and the amount of (circadian) desynchronization induced by flexible work schedules can be used for predicting the impairing effects of flexible work schedules on health and well-being. The results can thus be used for evaluating and designing flexible shift rosters.

Edge-localized mode avoidance and pedestal structure in I-mode plasmas

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

Walk, J. R., E-mail: jrwalk@psfc.mit.edu; Hughes, J. W.; Hubbard, A. E.

I-mode is a high-performance tokamak regime characterized by the formation of a temperature pedestal and enhanced energy confinement, without an accompanying density pedestal or drop in particle and impurity transport. I-mode operation appears to have naturally occurring suppression of large Edge-Localized Modes (ELMs) in addition to its highly favorable scalings of pedestal structure and overall performance. Extensive study of the ELMy H-mode has led to the development of the EPED model, which utilizes calculations of coupled peeling-ballooning MHD modes and kinetic-ballooning mode (KBM) stability limits to predict the pedestal structure preceding an ELM crash. We apply similar tools to themore » structure and ELM stability of I-mode pedestals. Analysis of I-mode discharges prepared with high-resolution pedestal data from the most recent C-Mod campaign reveals favorable pedestal scalings for extrapolation to large machines—pedestal temperature scales strongly with power per particle P{sub net}/n{sup ¯}{sub e}, and likewise pedestal pressure scales as the net heating power (consistent with weak degradation of confinement with heating power). Matched discharges in current, field, and shaping demonstrate the decoupling of energy and particle transport in I-mode, increasing fueling to span nearly a factor of two in density while maintaining matched temperature pedestals with consistent levels of P{sub net}/n{sup ¯}{sub e}. This is consistent with targets for increased performance in I-mode, elevating pedestal β{sub p} and global performance with matched increases in density and heating power. MHD calculations using the ELITE code indicate that I-mode pedestals are strongly stable to edge peeling-ballooning instabilities. Likewise, numerical modeling of the KBM turbulence onset, as well as scalings of the pedestal width with poloidal beta, indicates that I-mode pedestals are not limited by KBM turbulence—both features identified with the trigger for large ELMs, consistent with the observed suppression of large ELMs in I-mode.« less

Optimal and Miniaturized Strongly Coupled Magnetic Resonant Systems

NASA Astrophysics Data System (ADS)

Hu, Hao

Wireless power transfer (WPT) technologies for communication and recharging devices have recently attracted significant research attention. Conventional WPT systems based either on far-field or near-field coupling cannot provide simultaneously high efficiency and long transfer range. The Strongly Coupled Magnetic Resonance (SCMR) method was introduced recently, and it offers the possibility of transferring power with high efficiency over longer distances. Previous SCMR research has only focused on how to improve its efficiency and range through different methods. However, the study of optimal and miniaturized designs has been limited. In addition, no multiband and broadband SCMR WPT systems have been developed and traditional SCMR systems exhibit narrowband efficiency thereby imposing strict limitations on simultaneous wireless transmission of information and power, which is important for battery-less sensors. Therefore, new SCMR systems that are optimally designed and miniaturized in size will significantly enhance various technologies in many applications. The optimal and miniaturized SCMR systems are studied here. First, analytical models of the Conformal SCMR (CSCMR) system and thorough analysis and design methodology have been presented. This analysis specifically leads to the identification of the optimal design parameters, and predicts the performance of the designed CSCMR system. Second, optimal multiband and broadband CSCMR systems are designed. Two-band, three-band, and four-band CSCMR systems are designed and validated using simulations and measurements. Novel broadband CSCMR systems are also analyzed, designed, simulated and measured. The proposed broadband CSCMR system achieved more than 7 times larger bandwidth compared to the traditional SCMR system at the same frequency. Miniaturization methods of SCMR systems are also explored. Specifically, methods that use printable CSCMR with large capacitors, novel topologies including meandered, SRRs, and spiral topologies or 3-D structures, lower the operating frequency of SCMR systems, thereby reducing their size. Finally, SCMR systems are discussed and designed for various applications, such as biomedical devices and simultaneous powering of multiple devices.

Edge-localized mode avoidance and pedestal structure in I-mode plasmasa)

NASA Astrophysics Data System (ADS)

Walk, J. R.; Hughes, J. W.; Hubbard, A. E.; Terry, J. L.; Whyte, D. G.; White, A. E.; Baek, S. G.; Reinke, M. L.; Theiler, C.; Churchill, R. M.; Rice, J. E.; Snyder, P. B.; Osborne, T.; Dominguez, A.; Cziegler, I.

2014-05-01

I-mode is a high-performance tokamak regime characterized by the formation of a temperature pedestal and enhanced energy confinement, without an accompanying density pedestal or drop in particle and impurity transport. I-mode operation appears to have naturally occurring suppression of large Edge-Localized Modes (ELMs) in addition to its highly favorable scalings of pedestal structure and overall performance. Extensive study of the ELMy H-mode has led to the development of the EPED model, which utilizes calculations of coupled peeling-ballooning MHD modes and kinetic-ballooning mode (KBM) stability limits to predict the pedestal structure preceding an ELM crash. We apply similar tools to the structure and ELM stability of I-mode pedestals. Analysis of I-mode discharges prepared with high-resolution pedestal data from the most recent C-Mod campaign reveals favorable pedestal scalings for extrapolation to large machines—pedestal temperature scales strongly with power per particle Pnet/n ¯e, and likewise pedestal pressure scales as the net heating power (consistent with weak degradation of confinement with heating power). Matched discharges in current, field, and shaping demonstrate the decoupling of energy and particle transport in I-mode, increasing fueling to span nearly a factor of two in density while maintaining matched temperature pedestals with consistent levels of Pnet/n ¯e. This is consistent with targets for increased performance in I-mode, elevating pedestal βp and global performance with matched increases in density and heating power. MHD calculations using the ELITE code indicate that I-mode pedestals are strongly stable to edge peeling-ballooning instabilities. Likewise, numerical modeling of the KBM turbulence onset, as well as scalings of the pedestal width with poloidal beta, indicates that I-mode pedestals are not limited by KBM turbulence—both features identified with the trigger for large ELMs, consistent with the observed suppression of large ELMs in I-mode.

Does a Relationship Exist Between Lower Body Power and Balance Scores Among Older Adults?

PubMed

Shim, Andrew; Harr, Brady; Waller, Mike

2018-03-12

Falls are the second-leading cause of unintentional injury and death worldwide. To determine if a relationship exists between lower body power scores and center of pressure (CoP) and limits of stability (LoS) scores. A one-shot case study design (n = 13) was selected for the investigation. All participants were assessed stability scores via computerized posturography to determine CoP and LoS balance scores. Participants stood on a perturbed surface with their eyes open and closed. An experimental stair ramp with a switch mat timing device was used to determine lower body power scores in watts. There was a strong correlation (r = 0.725, p = 0.005) between the posterior (LoS) plane and relative peak power. An intraclass R revealed a strong correlation among the three trials (R = 0.831) performed on the stair ramp. Muscle power output and LoS scores have moderate to strong correlations with balance scores in older adults.

How important is getting the land surface energy exchange correct in WRF for wind energy forecasting?

NASA Astrophysics Data System (ADS)

Wharton, S.; Simpson, M.; Osuna, J. L.; Newman, J. F.; Biraud, S.

2013-12-01

Wind power forecasting is plagued with difficulties in accurately predicting the occurrence and intensity of atmospheric conditions at the heights spanned by industrial-scale turbines (~ 40 to 200 m above ground level). Better simulation of the relevant physics would enable operational practices such as integration of large fractions of wind power into power grids, scheduling maintenance on wind energy facilities, and deciding design criteria based on complex loads for next-generation turbines and siting. Accurately simulating the surface energy processes in numerical models may be critically important for wind energy forecasting as energy exchange at the surface strongly drives atmospheric mixing (i.e., stability) in the lower layers of the planetary boundary layer (PBL), which in turn largely determines wind shear and turbulence at heights found in the turbine rotor-disk. We hypothesize that simulating accurate a surface-atmosphere energy coupling should lead to more accurate predictions of wind speed and turbulence at heights within the turbine rotor-disk. Here, we tested 10 different land surface model configurations in the Weather Research and Forecasting (WRF) model including Noah, Noah-MP, SSiB, Pleim-Xiu, RUC, and others to evaluate (1) the accuracy of simulated surface energy fluxes to flux tower measurements, (2) the accuracy of forecasted wind speeds to observations at rotor-disk heights, and (3) the sensitivity of forecasting hub-height rotor disk wind speed to the choice of land surface model. WRF was run for four, two-week periods covering both summer and winter periods over the Southern Great Plains ARM site in Oklahoma. Continuous measurements of surface energy fluxes and lidar-based wind speed, direction and turbulence were also available. The SGP ARM site provided an ideal location for this evaluation as it centrally located in the wind-rich Great Plains and multi-MW wind farms are rapidly expanding in the area. We found significant differences in simulated wind speeds at rotor-disk heights from WRF which indicated, in part, the sensitivity of lower PBL winds to surface energy exchange. We also found significant differences in energy partitioning between sensible heat and latent energy depending on choice of land surface model. Overall, the most consistent, accurate model results were produced using Noah-MP. Noah-MP was most accurate at simulating energy fluxes and wind shear. Hub-height wind speed, however, was predicted with most accuracy with Pleim-Xiu. This suggests that simulating wind shear in the surface layer is consistent with accurately simulating surface energy exchange while the exact magnitudes of wind speed may be more strongly influenced by the PBL dynamics. As the nation is working towards a 20% wind energy goal by 2030, increasing the accuracy of wind forecasting at rotor-disk heights becomes more important considering that utilities require wind farms to estimate their power generation 24 to 36 hours ahead and face penalties for inaccuracies in those forecasts.

Does Spontaneous Favorability to Power (vs. Universalism) Values Predict Spontaneous Prejudice and Discrimination?

PubMed

Souchon, Nicolas; Maio, Gregory R; Hanel, Paul H P; Bardin, Brigitte

2017-10-01

We conducted five studies testing whether an implicit measure of favorability toward power over universalism values predicts spontaneous prejudice and discrimination. Studies 1 (N = 192) and 2 (N = 86) examined correlations between spontaneous favorability toward power (vs. universalism) values, achievement (vs. benevolence) values, and a spontaneous measure of prejudice toward ethnic minorities. Study 3 (N = 159) tested whether conditioning participants to associate power values with positive adjectives and universalism values with negative adjectives (or inversely) affects spontaneous prejudice. Study 4 (N = 95) tested whether decision bias toward female handball players could be predicted by spontaneous attitude toward power (vs. universalism) values. Study 5 (N = 123) examined correlations between spontaneous attitude toward power (vs. universalism) values, spontaneous importance toward power (vs. universalism) values, and spontaneous prejudice toward Black African people. Spontaneous positivity toward power (vs. universalism) values was associated with spontaneous negativity toward minorities and predicted gender bias in a decision task, whereas the explicit measures did not. These results indicate that the implicit assessment of evaluative responses attached to human values helps to model value-attitude-behavior relations. © 2016 The Authors. Journal of Personality Published by Wiley Periodicals, Inc.

Swift , XMM - Newton , and NuSTAR Observations of PSR J2032+4127/MT91 213

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

Li, K. L.; Kong, A. K. H.; Tam, P. H. T.

2017-07-10

We report our recent Swift , NuSTAR , and XMM - Newton X-ray and Lijiang optical observations on PSR J2032+4127/MT91 213, the γ -ray binary candidate with a period of 45–50 years. The coming periastron of the system was predicted to be in 2017 November, around which high-energy flares from keV to TeV are expected. Recent studies with Chandra and Swift X-ray observations taken in 2015/2016 showed that its X-ray emission has been brighter by a factors of ∼10 than that before 2013, probably revealing some ongoing activities between the pulsar wind and the stellar wind. Our new Swift /XRTmore » lightcurve shows no strong evidence of a single vigorous brightening trend, but rather several strong X-ray flares on weekly to monthly timescales with a slowly brightening baseline, namely the low state. The NuSTAR and XMM - Newton observations taken during the flaring and the low states, respectively, show a denser environment and a softer power-law index during the flaring state, implying that the pulsar wind interacted with the stronger stellar winds of the companion to produce the flares. These precursors would be crucial in studying the predicted giant outburst from this extreme γ -ray binary during the periastron passage in late 2017.« less

Inflammatory macrophage-associated 3-gene signature predicts subclinical allograft injury and graft survival.

PubMed

Azad, Tej D; Donato, Michele; Heylen, Line; Liu, Andrew B; Shen-Orr, Shai S; Sweeney, Timothy E; Maltzman, Jonathan Scott; Naesens, Maarten; Khatri, Purvesh

2018-01-25

Late allograft failure is characterized by cumulative subclinical insults manifesting over many years. Although immunomodulatory therapies targeting host T cells have improved short-term survival rates, rates of chronic allograft loss remain high. We hypothesized that other immune cell types may drive subclinical injury, ultimately leading to graft failure. We collected whole-genome transcriptome profiles from 15 independent cohorts composed of 1,697 biopsy samples to assess the association of an inflammatory macrophage polarization-specific gene signature with subclinical injury. We applied penalized regression to a subset of the data sets and identified a 3-gene inflammatory macrophage-derived signature. We validated discriminatory power of the 3-gene signature in 3 independent renal transplant data sets with mean AUC of 0.91. In a longitudinal cohort, the 3-gene signature strongly correlated with extent of injury and accurately predicted progression of subclinical injury 18 months before clinical manifestation. The 3-gene signature also stratified patients at high risk of graft failure as soon as 15 days after biopsy. We found that the 3-gene signature also distinguished acute rejection (AR) accurately in 3 heart transplant data sets but not in lung transplant. Overall, we identified a parsimonious signature capable of diagnosing AR, recognizing subclinical injury, and risk-stratifying renal transplant patients. Our results strongly suggest that inflammatory macrophages may be a viable therapeutic target to improve long-term outcomes for organ transplantation patients.

A new method to quantify the effects of baryons on the matter power spectrum

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

Schneider, Aurel; Teyssier, Romain, E-mail: aurel@physik.uzh.ch, E-mail: teyssier@physik.uzh.ch

2015-12-01

Future large-scale galaxy surveys have the potential to become leading probes for cosmology provided the influence of baryons on the total mass distribution is understood well enough. As hydrodynamical simulations strongly depend on details in the feedback implementations, no unique and robust predictions for baryonic effects currently exist. In this paper we propose a baryonic correction model that modifies the density field of dark-matter-only N-body simulations to mimic the effects of baryons from any underlying adopted feedback recipe. The model assumes haloes to consist of 4 components: 1- hot gas in hydrostatical equilibrium, 2- ejected gas from feedback processes, 3-more » central galaxy stars, and 4- adiabatically relaxed dark matter, which all modify the initial dark-matter-only density profiles. These altered profiles allow to define a displacement field for particles in N-body simulations and to modify the total density field accordingly. The main advantage of the baryonic correction model is to connect the total matter density field to the observable distribution of gas and stars in haloes, making it possible to parametrise baryonic effects on the matter power spectrum. We show that the most crucial quantities are the mass fraction of ejected gas and its corresponding ejection radius. The former controls how strongly baryons suppress the power spectrum, while the latter provides a measure of the scale where baryonic effects become important. A comparison with X-ray and Sunyaev-Zel'dovich cluster observations suggests that baryons suppress wave modes above k∼0.5 h/Mpc with a maximum suppression of 10-25 percent around k∼ 2 h/Mpc. More detailed observations of the gas in the outskirts of groups and clusters are required to decrease the large uncertainties of these numbers.« less

Electric Power Engineering Cost Predicting Model Based on the PCA-GA-BP

NASA Astrophysics Data System (ADS)

Wen, Lei; Yu, Jiake; Zhao, Xin

2017-10-01

In this paper a hybrid prediction algorithm: PCA-GA-BP model is proposed. PCA algorithm is established to reduce the correlation between indicators of original data and decrease difficulty of BP neural network in complex dimensional calculation. The BP neural network is established to estimate the cost of power transmission project. The results show that PCA-GA-BP algorithm can improve result of prediction of electric power engineering cost.

Assessment of a virtual functional prototyping process for the rapid manufacture of passive-dynamic ankle-foot orthoses.

PubMed

Schrank, Elisa S; Hitch, Lester; Wallace, Kevin; Moore, Richard; Stanhope, Steven J

2013-10-01

Passive-dynamic ankle-foot orthosis (PD-AFO) bending stiffness is a key functional characteristic for achieving enhanced gait function. However, current orthosis customization methods inhibit objective premanufacture tuning of the PD-AFO bending stiffness, making optimization of orthosis function challenging. We have developed a novel virtual functional prototyping (VFP) process, which harnesses the strengths of computer aided design (CAD) model parameterization and finite element analysis, to quantitatively tune and predict the functional characteristics of a PD-AFO, which is rapidly manufactured via fused deposition modeling (FDM). The purpose of this study was to assess the VFP process for PD-AFO bending stiffness. A PD-AFO CAD model was customized for a healthy subject and tuned to four bending stiffness values via VFP. Two sets of each tuned model were fabricated via FDM using medical-grade polycarbonate (PC-ISO). Dimensional accuracy of the fabricated orthoses was excellent (average 0.51 ± 0.39 mm). Manufacturing precision ranged from 0.0 to 0.74 Nm/deg (average 0.30 ± 0.36 Nm/deg). Bending stiffness prediction accuracy was within 1 Nm/deg using the manufacturer provided PC-ISO elastic modulus (average 0.48 ± 0.35 Nm/deg). Using an experimentally derived PC-ISO elastic modulus improved the optimized bending stiffness prediction accuracy (average 0.29 ± 0.57 Nm/deg). Robustness of the derived modulus was tested by carrying out the VFP process for a disparate subject, tuning the PD-AFO model to five bending stiffness values. For this disparate subject, bending stiffness prediction accuracy was strong (average 0.20 ± 0.14 Nm/deg). Overall, the VFP process had excellent dimensional accuracy, good manufacturing precision, and strong prediction accuracy with the derived modulus. Implementing VFP as part of our PD-AFO customization and manufacturing framework, which also includes fit customization, provides a novel and powerful method to predictably tune and precisely manufacture orthoses with objectively customized fit and functional characteristics.

The roles of climate, phylogenetic relatedness, introduction effort, and reproductive traits in the establishment of non-native reptiles and amphibians.

PubMed

van Wilgen, Nicola J; Richardson, David M

2012-04-01

We developed a method to predict the potential of non-native reptiles and amphibians (herpetofauna) to establish populations. This method may inform efforts to prevent the introduction of invasive non-native species. We used boosted regression trees to determine whether nine variables influence establishment success of introduced herpetofauna in California and Florida. We used an independent data set to assess model performance. Propagule pressure was the variable most strongly associated with establishment success. Species with short juvenile periods and species with phylogenetically more distant relatives in regional biotas were more likely to establish than species that start breeding later and those that have close relatives. Average climate match (the similarity of climate between native and non-native range) and life form were also important. Frogs and lizards were the taxonomic groups most likely to establish, whereas a much lower proportion of snakes and turtles established. We used results from our best model to compile a spreadsheet-based model for easy use and interpretation. Probability scores obtained from the spreadsheet model were strongly correlated with establishment success as were probabilities predicted for independent data by the boosted regression tree model. However, the error rate for predictions made with independent data was much higher than with cross validation using training data. This difference in predictive power does not preclude use of the model to assess the probability of establishment of herpetofauna because (1) the independent data had no information for two variables (meaning the full predictive capacity of the model could not be realized) and (2) the model structure is consistent with the recent literature on the primary determinants of establishment success for herpetofauna. It may still be difficult to predict the establishment probability of poorly studied taxa, but it is clear that non-native species (especially lizards and frogs) that mature early and come from environments similar to that of the introduction region have the highest probability of establishment. ©2012 Society for Conservation Biology.

Evaluation of Data-Driven Models for Predicting Solar Photovoltaics Power Output

DOE PAGES

Moslehi, Salim; Reddy, T. Agami; Katipamula, Srinivas

2017-09-10

This research was undertaken to evaluate different inverse models for predicting power output of solar photovoltaic (PV) systems under different practical scenarios. In particular, we have investigated whether PV power output prediction accuracy can be improved if module/cell temperature was measured in addition to climatic variables, and also the extent to which prediction accuracy degrades if solar irradiation is not measured on the plane of array but only on a horizontal surface. We have also investigated the significance of different independent or regressor variables, such as wind velocity and incident angle modifier in predicting PV power output and cell temperature.more » The inverse regression model forms have been evaluated both in terms of their goodness-of-fit, and their accuracy and robustness in terms of their predictive performance. Given the accuracy of the measurements, expected CV-RMSE of hourly power output prediction over the year varies between 3.2% and 8.6% when only climatic data are used. Depending on what type of measured climatic and PV performance data is available, different scenarios have been identified and the corresponding appropriate modeling pathways have been proposed. The corresponding models are to be implemented on a controller platform for optimum operational planning of microgrids and integrated energy systems.« less

Improved techniques for predicting spacecraft power

NASA Technical Reports Server (NTRS)

Chmielewski, A. B.

1987-01-01

Radioisotope Thermoelectric Generators (RTGs) are going to supply power for the NASA Galileo and Ulysses spacecraft now scheduled to be launched in 1989 and 1990. The duration of the Galileo mission is expected to be over 8 years. This brings the total RTG lifetime to 13 years. In 13 years, the RTG power drops more than 20 percent leaving a very small power margin over what is consumed by the spacecraft. Thus it is very important to accurately predict the RTG performance and be able to assess the magnitude of errors involved. The paper lists all the error sources involved in the RTG power predictions and describes a statistical method for calculating the tolerance.

Classification of Bitter Orange Essential Oils According to Fruit Ripening Stage by Untargeted Chemical Profiling and Machine Learning.

PubMed

Taghadomi-Saberi, Saeedeh; Mas Garcia, Sílvia; Allah Masoumi, Amin; Sadeghi, Morteza; Marco, Santiago

2018-06-13

The quality and composition of bitter orange essential oils (EOs) strongly depend on the ripening stage of the citrus fruit. The concentration of volatile compounds and consequently its organoleptic perception varies. While this can be detected by trained humans, we propose an objective approach for assessing the bitter orange from the volatile composition of their EO. The method is based on the combined use of headspace gas chromatography⁻mass spectrometry (HS-GC-MS) and artificial neural networks (ANN) for predictive modeling. Data obtained from the analysis of HS-GC-MS were preprocessed to select relevant peaks in the total ion chromatogram as input features for ANN. Results showed that key volatile compounds have enough predictive power to accurately classify the EO, according to their ripening stage for different applications. A sensitivity analysis detected the key compounds to identify the ripening stage. This study provides a novel strategy for the quality control of bitter orange EO without subjective methods.

Perceived Partner Responsiveness Predicts Diurnal Cortisol Profiles 10 Years Later.

PubMed

Slatcher, Richard B; Selcuk, Emre; Ong, Anthony D

2015-07-01

Several decades of research have demonstrated that marital relationships have a powerful influence on physical health. However, surprisingly little is known about how marriage affects health--both in terms of psychological processes and biological ones. Over a 10-year period, we investigated the associations between perceived partner responsiveness--the extent to which people feel understood, cared for, and appreciated by their romantic partners--and diurnal cortisol in a large sample of married and cohabitating couples in the United States. Partner responsiveness predicted higher cortisol values at awakening and steeper (i.e., healthier) cortisol slopes at the 10-year follow-up. These associations remained strong after we controlled for demographic factors, depressive symptoms, agreeableness, and other positive and negative relationship factors. Furthermore, declines in negative affect over the 10-year period mediated the prospective association between responsiveness and cortisol slope. These findings suggest that diurnal cortisol may be a key biological pathway through which social relationships affect long-term health. © The Author(s) 2015.

Sneutrinos as mixed inflaton and curvaton

NASA Astrophysics Data System (ADS)

Haba, Naoyuki; Takahashi, Tomo; Yamada, Toshifumi

2018-06-01

We investigate a scenario where the supersymmetric partners of two right-handed neutrinos (sneutrinos) work as mixed inflaton and curvaton, motivated by the fact that the curvaton contribution to scalar perturbations can reduce the tensor-to-scalar ratio r so that chaotic inflation models with a quadratic potential are made consistent with the experimental bound on r. After confirming that the scenario evades the current bounds on r and the scalar perturbation spectral index ns, we make a prediction on the local non-Gaussianity in bispectrum, fNL, and one in trispectrum, τNL. Remarkably, since the sneutrino decay widths are determined by the neutrino Dirac Yukawa coupling, which can be estimated from the measured active neutrino mass differences in the seesaw model, our scenario has a strong predictive power about local non-Gaussianities, as they heavily depend on the inflaton and curvaton decay rates. Using this fact, we can constrain the sneutrino mass from the experimental bounds on ns, r and fNL.

Coupling physically based and data-driven models for assessing freshwater inflow into the Small Aral Sea

NASA Astrophysics Data System (ADS)

Ayzel, Georgy; Izhitskiy, Alexander

2018-06-01

The Aral Sea desiccation and related changes in hydroclimatic conditions on a regional level is a hot topic for past decades. The key problem of scientific research projects devoted to an investigation of modern Aral Sea basin hydrological regime is its discontinuous nature - the only limited amount of papers takes into account the complex runoff formation system entirely. Addressing this challenge we have developed a continuous prediction system for assessing freshwater inflow into the Small Aral Sea based on coupling stack of hydrological and data-driven models. Results show a good prediction skill and approve the possibility to develop a valuable water assessment tool which utilizes the power of classical physically based and modern machine learning models both for territories with complex water management system and strong water-related data scarcity. The source code and data of the proposed system is available on a Github page (https://github.com/SMASHIproject/IWRM2018).

What do gas-rich galaxies actually tell us about modified Newtonian dynamics?

PubMed

Foreman, Simon; Scott, Douglas

2012-04-06

It has recently been claimed that measurements of the baryonic Tully-Fisher relation (BTFR), a power-law relationship between the observed baryonic masses and outer rotation velocities of galaxies, support the predictions of modified Newtonian dynamics for the slope and scatter in the relation, while challenging the cold dark matter (CDM) paradigm. We investigate these claims, and find that (1) the scatter in the data used to determine the BTFR is in conflict with observational uncertainties on the data, (2) these data do not make strong distinctions regarding the best-fit BTFR parameters, (3) the literature contains a wide variety of measurements of the BTFR, many of which are discrepant with the recent results, and (4) the claimed CDM "prediction" for the BTFR is a gross oversimplification of the complex galaxy-scale physics involved. We conclude that the BTFR is currently untrustworthy as a test of CDM. © 2012 American Physical Society

Effect of Load Rate on Ultimate Tensile Strength of Ceramic Matrix Composites at Elevated Temperatures

NASA Technical Reports Server (NTRS)

Choi, Sung R.; Gyekenyesi, John P.

2001-01-01

The strengths of three continuous fiber-reinforced ceramic composites, including SiC/CAS-II, SiC/MAS-5 and SiC/SiC, were determined as a function of test rate in air at 1100 to 1200 C. All three composite materials exhibited a strong dependency of strength on test rate, similar to the behavior observed in many advanced monolithic ceramics at elevated temperatures. The application of the preloading technique as well as the prediction of life from one loading configuration (constant stress-rate) to another (constant stress loading) suggested that the overall macroscopic failure mechanism of the composites would be the one governed by a power-law type of damage evolution/accumulation, analogous to slow crack growth commonly observed in advanced monolithic ceramics. It was further found that constant stress-rate testing could be used as an alternative to life prediction test methodology even for composite materials, at least for short range of lifetimes and when ultimate strength is used as the failure criterion.

On the use of colour reflectivity plots to monitor the structure of the troposphere and stratosphere

NASA Technical Reports Server (NTRS)

Rottger, J.; Fu, I. J.; Kuo, F. S.; Liu, C. H.; Chao, J. K.

1986-01-01

The radar reflectivity, defined as the range squared corrected power of VHF radar echoes, can be used to monitor and study the temporal development of inversion layer, frontal boundaries and convective turbulence. From typical featurs of upward or downward motion of reflectivity structures, the advection/convection of cold and warm air can be predicted. High resolution color plots appear to be useful to trace and to study the life history of these structures, particularly their persistency, descent and ascent. These displays allow an immediate determination of the tropopause height as well as the determination of the tropopause structure. The life history of warm fronts, cold fronts, and occlusions can be traced, and these reflectivity plots allow detection of even very weak events which cannot be seen in the traditional meteorological data sets. The life history of convective turbulence, particular evolving from the planetary boundary layer, can be tracked quite easily. Its development into strong convection reaching the middle troposphere can be followed and predicted.

Measurement of psychopathology in Huntington's disease: the critical role of caregivers.

PubMed

van Duijn, Erik; Giltay, Erik J; Zitman, Frans G; Roos, Raymund A C; van der Mast, Rose C

2010-05-01

Assessment of psychopathology in Huntington's disease (HD) using formal DSM-IV criteria is complex because of comorbid somatic and cognitive disturbances and diminished disease awareness. Using dimensional tests in 152 HD mutation carriers, both the total score of the Problem Behaviors Assessment (PBA) scale and the behavioral section of the Unified Huntington's Disease Rating Scale (UHDRS-b) corresponded with presence of DSM-IV diagnoses. Receiver operating characteristic curves showed an area under the curve of 0.87 for the PBA and 0.91 for the UHDRS-b, demonstrating moderate to strong discriminatory power. Using caregiver information, subjects who were too cognitively impaired for composite international diagnostic interview assessment showed similar high PBA and UHDRS-b scores, with both a negative predictive value of 96% and a positive predictive value of 40% and 44%, respectively, for the presence of formal psychiatric disorders, indicating that dimensional rating scales and caregiver information allow for the assessment of psychopathology in advanced-stage HD.

Drift from the Use of Hand-Held Knapsack Pesticide Sprayers in Boyacá (Colombian Andes).

PubMed

García-Santos, Glenda; Feola, Giuseppe; Nuyttens, David; Diaz, Jaime

2016-05-25

Offsite pesticide losses in tropical mountainous regions have been little studied. One example is measuring pesticide drift soil deposition, which can support pesticide risk assessment for surface water, soil, bystanders, and off-target plants and fauna. This is considered a serious gap, given the evidence of pesticide-related poisoning in those regions. Empirical data of drift deposition of a pesticide surrogate, Uranine tracer, within one of the highest potato-producing regions in Colombia, characterized by small plots and mountain orography, is presented. High drift values encountered in this study reflect the actual spray conditions using hand-held knapsack sprayers. Comparison between measured and predicted drift values using three existing empirical equations showed important underestimation. However, after their optimization based on measured drift information, the equations showed a strong predictive power for this study area and the study conditions. The most suitable curve to assess mean relative drift was the IMAG calculator after optimization.

Observations of the 51.8 micron (O III) emission line in Orion

NASA Technical Reports Server (NTRS)

Melnick, G.; Gull, G. E.; Harwit, M.; Ward, D. B.

1978-01-01

The 51.8 micron fine structure transition P2:3P2 3P1 for doubly ionized oxygen was observed in the Orion nebula. The observed line strength is of 5 plus or minus 3 times 10 to the minus 15th power watt/sq cm is in good agreement with theoretical predictions. Observations are consistent with the newly predicted 51.8 micron line position. The line lies close to an atmospheric water vapor feature at 51.7 micron, but is sufficiently distant so that corrections for this feature are straightforward. Observations of the 51.8 (O III) line are particularly important since the previously discovered 88 micron line from the same ion also is strong. This pair of lines should, therefore, yield new data about densities in observed H II regions; or else, if density data already are available from radio or other observations, the lines can be used to determine the differential dust absorption between 52 and 88 micron in front of heavily obscured regions.

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.

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

Power quality analysis based on spatial correlation

NASA Astrophysics Data System (ADS)

Li, Jiangtao; Zhao, Gang; Liu, Haibo; Li, Fenghou; Liu, Xiaoli

2018-03-01

With the industrialization and urbanization, the status of electricity in the production and life is getting higher and higher. So the prediction of power quality is the more potential significance. Traditional power quality analysis methods include: power quality data compression, disturbance event pattern classification, disturbance parameter calculation. Under certain conditions, these methods can predict power quality. This paper analyses the temporal variation of power quality of one provincial power grid in China from time angle. The distribution of power quality was analyzed based on spatial autocorrelation. This paper tries to prove that the research idea of geography is effective for mining the potential information of power quality.

Auditory Power-Law Activation Avalanches Exhibit a Fundamental Computational Ground State

NASA Astrophysics Data System (ADS)

Stoop, Ruedi; Gomez, Florian

2016-07-01

The cochlea provides a biological information-processing paradigm that we are only beginning to understand in its full complexity. Our work reveals an interacting network of strongly nonlinear dynamical nodes, on which even a simple sound input triggers subnetworks of activated elements that follow power-law size statistics ("avalanches"). From dynamical systems theory, power-law size distributions relate to a fundamental ground state of biological information processing. Learning destroys these power laws. These results strongly modify the models of mammalian sound processing and provide a novel methodological perspective for understanding how the brain processes information.

How does the Earth system generate and maintain thermodynamic disequilibrium and what does it imply for the future of the planet?

PubMed

Kleidon, Axel

2012-03-13

The Earth's chemical composition far from chemical equilibrium is unique in our Solar System, and this uniqueness has been attributed to the presence of widespread life on the planet. Here, I show how this notion can be quantified using non-equilibrium thermodynamics. Generating and maintaining disequilibrium in a thermodynamic variable requires the extraction of power from another thermodynamic gradient, and the second law of thermodynamics imposes fundamental limits on how much power can be extracted. With this approach and associated limits, I show that the ability of abiotic processes to generate geochemical free energy that can be used to transform the surface-atmosphere environment is strongly limited to less than 1 TW. Photosynthetic life generates more than 200 TW by performing photochemistry, thereby substantiating the notion that a geochemical composition far from equilibrium can be a sign for strong biotic activity. Present-day free energy consumption by human activity in the form of industrial activity and human appropriated net primary productivity is of the order of 50 TW and therefore constitutes a considerable term in the free energy budget of the planet. When aiming to predict the future of the planet, we first note that since global changes are closely related to this consumption of free energy, and the demands for free energy by human activity are anticipated to increase substantially in the future, the central question in the context of predicting future global change is then how human free energy demands can increase sustainably without negatively impacting the ability of the Earth system to generate free energy. This question could be evaluated with climate models, and the potential deficiencies in these models to adequately represent the thermodynamics of the Earth system are discussed. Then, I illustrate the implications of this thermodynamic perspective by discussing the forms of renewable energy and planetary engineering that would enhance the overall free energy generation and, thereby 'empower' the future of the planet.

The Crucial Role of Error Correlation for Uncertainty Modeling of CFD-Based Aerodynamics Increments

NASA Technical Reports Server (NTRS)

Hemsch, Michael J.; Walker, Eric L.

2011-01-01

The Ares I ascent aerodynamics database for Design Cycle 3 (DAC-3) was built from wind-tunnel test results and CFD solutions. The wind tunnel results were used to build the baseline response surfaces for wind-tunnel Reynolds numbers at power-off conditions. The CFD solutions were used to build increments to account for Reynolds number effects. We calculate the validation errors for the primary CFD code results at wind tunnel Reynolds number power-off conditions and would like to be able to use those errors to predict the validation errors for the CFD increments. However, the validation errors are large compared to the increments. We suggest a way forward that is consistent with common practice in wind tunnel testing which is to assume that systematic errors in the measurement process and/or the environment will subtract out when increments are calculated, thus making increments more reliable with smaller uncertainty than absolute values of the aerodynamic coefficients. A similar practice has arisen for the use of CFD to generate aerodynamic database increments. The basis of this practice is the assumption of strong correlation of the systematic errors inherent in each of the results used to generate an increment. The assumption of strong correlation is the inferential link between the observed validation uncertainties at wind-tunnel Reynolds numbers and the uncertainties to be predicted for flight. In this paper, we suggest a way to estimate the correlation coefficient and demonstrate the approach using code-to-code differences that were obtained for quality control purposes during the Ares I CFD campaign. Finally, since we can expect the increments to be relatively small compared to the baseline response surface and to be typically of the order of the baseline uncertainty, we find that it is necessary to be able to show that the correlation coefficients are close to unity to avoid overinflating the overall database uncertainty with the addition of the increments.

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

Performance of comorbidity, risk adjustment, and functional status measures in expenditure prediction for patients with diabetes.

PubMed

Maciejewski, Matthew L; Liu, Chuan-Fen; Fihn, Stephan D

2009-01-01

To compare the ability of generic comorbidity and risk adjustment measures, a diabetes-specific measure, and a self-reported functional status measure to explain variation in health care expenditures for individuals with diabetes. This study included a retrospective cohort of 3,092 diabetic veterans participating in a multisite trial. Two comorbidity measures, four risk adjusters, a functional status measure, a diabetes complication count, and baseline expenditures were constructed from administrative and survey data. Outpatient, inpatient, and total expenditure models were estimated using ordinary least squares regression. Adjusted R(2) statistics and predictive ratios were compared across measures to assess overall explanatory power and explanatory power of low- and high-cost subgroups. Administrative data-based risk adjusters performed better than the comorbidity, functional status, and diabetes-specific measures in all expenditure models. The diagnostic cost groups (DCGs) measure had the greatest predictive power overall and for the low- and high-cost subgroups, while the diabetes-specific measure had the lowest predictive power. A model with DCGs and the diabetes-specific measure modestly improved predictive power. Existing generic measures can be useful for diabetes-specific research and policy applications, but more predictive diabetes-specific measures are needed.

Prediction of light aircraft interior sound pressure level using the room equation

NASA Technical Reports Server (NTRS)

Atwal, M.; Bernhard, R.

1984-01-01

The room equation is investigated for predicting interior sound level. The method makes use of an acoustic power balance, by equating net power flow into the cabin volume to power dissipated within the cabin using the room equation. The sound power level transmitted through the panels was calculated by multiplying the measured space averaged transmitted intensity for each panel by its surface area. The sound pressure level was obtained by summing the mean square sound pressures radiated from each panel. The data obtained supported the room equation model in predicting the cabin interior sound pressure level.

Late Holocene climate variability from Lake Pupuke maar, Auckland, New Zealand

NASA Astrophysics Data System (ADS)

Striewski, B.; Shulmeister, J.; Augustinus, P. C.; Soderholm, J.

2013-10-01

Spectral analyses of quasi-annual organo-diatomaceous laminae couplets in an Auckland maar lake indicate brief (sub-decadal scale) episodes with strong spectral power and long periods of weak to no spectral power between c. 1700 to c. 550 cal. yr BP. Laminae couplet thickness appears to be a function of changes in wind flow over the basin, with enhanced wind flow deepening the mixing zone and providing additional nutrients for laminae formation. Aeolian dust from Australia amplifies the wind signal. Spectral signals in the high power episodes are focused in <4 years and 6-8 years windows. These are consistent with El Niño-Southern Oscillation (ENSO) periodicity. This climate system is known to play a major role in the modern Auckland climate whereby strongly negative (positive) ENSO are associated with enhanced (diminished) SW airflow over Auckland. ENSO events interact in the modern climate and the spectral results indicate that this is the case when spectral power is strong in the laminae. These results highlight strong but intermittent ENSO activity between 600 and 1400 cal. yr BP.

Multi-Temporal Decomposed Wind and Load Power Models for Electric Energy Systems

NASA Astrophysics Data System (ADS)

Abdel-Karim, Noha

This thesis is motivated by the recognition that sources of uncertainties in electric power systems are multifold and may have potentially far-reaching effects. In the past, only system load forecast was considered to be the main challenge. More recently, however, the uncertain price of electricity and hard-to-predict power produced by renewable resources, such as wind and solar, are making the operating and planning environment much more challenging. The near-real-time power imbalances are compensated by means of frequency regulation and generally require fast-responding costly resources. Because of this, a more accurate forecast and look-ahead scheduling would result in a reduced need for expensive power balancing. Similarly, long-term planning and seasonal maintenance need to take into account long-term demand forecast as well as how the short-term generation scheduling is done. The better the demand forecast, the more efficient planning will be as well. Moreover, computer algorithms for scheduling and planning are essential in helping the system operators decide what to schedule and planners what to build. This is needed given the overall complexity created by different abilities to adjust the power output of generation technologies, demand uncertainties and by the network delivery constraints. Given the growing presence of major uncertainties, it is likely that the main control applications will use more probabilistic approaches. Today's predominantly deterministic methods will be replaced by methods which account for key uncertainties as decisions are made. It is well-understood that although demand and wind power cannot be predicted at very high accuracy, taking into consideration predictions and scheduling in a look-ahead way over several time horizons generally results in more efficient and reliable utilization, than when decisions are made assuming deterministic, often worst-case scenarios. This change is in approach is going to ultimately require new electricity market rules capable of providing the right incentives to manage uncertainties and of differentiating various technologies according to the rate at which they can respond to ever changing conditions. Given the overall need for modeling uncertainties in electric energy systems, we consider in this thesis the problem of multi-temporal modeling of wind and demand power, in particular. Historic data is used to derive prediction models for several future time horizons. Short-term prediction models derived can be used for look-ahead economic dispatch and unit commitment, while the long-term annual predictive models can be used for investment planning. As expected, the accuracy of such predictive models depends on the time horizons over which the predictions are made, as well as on the nature of uncertain signals. It is shown that predictive models obtained using the same general modeling approaches result in different accuracy for wind than for demand power. In what follows, we introduce several models which have qualitatively different patterns, ranging from hourly to annual. We first transform historic time-stamped data into the Fourier Transform (Fr) representation. The frequency domain data representation is used to decompose the wind and load power signals and to derive predictive models relevant for short-term and long-term predictions using extracted spectral techniques. The short-term results are interpreted next as a Linear Prediction Coding Model (LPC) and its accuracy is analyzed. Next, a new Markov-Based Sensitivity Model (MBSM) for short term prediction has been proposed and the dispatched costs of uncertainties for different predictive models with comparisons have been developed. Moreover, the Discrete Markov Process (DMP) representation is applied to help assess probabilities of most likely short-, medium- and long-term states and the related multi-temporal risks. In addition, this thesis discusses operational impacts of wind power integration in different scenario levels by performing more than 9,000 AC Optimal Power Flow runs. The effects of both wind and load variations on system constraints and costs are presented. The limitations of DC Optimal Power Flow (DCOPF) vs. ACOPF are emphasized by means of system convergence problems due to the effect of wind power on changing line flows and net power injections. By studying the effect of having wind power on line flows, we found that the divergence problem applies in areas with high wind and hydro generation capacity share (cheap generations). (Abstract shortened by UMI.).

The effects of load on system and lower-body joint kinetics during jump squats.

PubMed

Moir, Gavin L; Gollie, Jared M; Davis, Shala E; Guers, John J; Witmer, Chad A

2012-11-01

To investigate the effects of different loads on system and lower-body kinetics during jump squats, 12 resistance-trained men performed jumps under different loading conditions: 0%, 12%, 27%, 42%, 56%, 71%, and 85% of 1-repetition maximum (1-RM). System power output was calculated as the product of the vertical component of the ground reaction force and the vertical velocity of the bar during its ascent. Joint power output was calculated during bar ascent for the hip, knee, and ankle joints, and was also summed across the joints. System power output and joint power at knee and ankle joints were maximized at 0% 1-RM (p < 0.001) and followed the linear trends (p < 0.001) caused by power output decreasing as the load increased. Power output at the hip was maximized at 42% 1-RM (p = 0.016) and followed a quadratic trend (p = 0.030). Summed joint power could be predicted from system power (p < 0.05), while system power could predict power at the knee and ankle joints under some of the loading conditions. Power at the hip could not be predicted from system power. System power during loaded jumps reflects the power at the knee and ankle, while power at the hip does not correspond to system power.

The effects of psammophilous plants on sand dune dynamics

NASA Astrophysics Data System (ADS)

Bel, Golan; Ashkenazy, Yosef

2014-07-01

Mathematical models of sand dune dynamics have considered different types of sand dune cover. However, despite the important role of psammophilous plants (plants that flourish in moving-sand environments) in dune dynamics, the incorporation of their effects into mathematical models of sand dunes remains a challenging task. Here we propose a nonlinear physical model for the role of psammophilous plants in the stabilization and destabilization of sand dunes. There are two main mechanisms by which the wind affects these plants: (i) sand drift results in the burial and exposure of plants, a process that is known to result in an enhanced growth rate, and (ii) strong winds remove shoots and rhizomes and seed them in nearby locations, enhancing their growth rate. Our model describes the temporal evolution of the fractions of surface cover of regular vegetation, biogenic soil crust, and psammophilous plants. The latter reach their optimal growth under either (i) specific sand drift or (ii) specific wind power. The model exhibits complex bifurcation diagrams and dynamics, which explain observed phenomena, and it predicts new dune stabilization scenarios. Depending on the climatological conditions, it is possible to obtain one, two, or, predicted here for the first time, three stable dune states. Our model shows that the development of the different cover types depends on the precipitation rate and the wind power and that the psammophilous plants are not always the first to grow and stabilize the dunes.

Recombination in diverse maize is stable, predictable, and associated with genetic load.

PubMed

Rodgers-Melnick, Eli; Bradbury, Peter J; Elshire, Robert J; Glaubitz, Jeffrey C; Acharya, Charlotte B; Mitchell, Sharon E; Li, Chunhui; Li, Yongxiang; Buckler, Edward S

2015-03-24

Among the fundamental evolutionary forces, recombination arguably has the largest impact on the practical work of plant breeders. Varying over 1,000-fold across the maize genome, the local meiotic recombination rate limits the resolving power of quantitative trait mapping and the precision of favorable allele introgression. The consequences of low recombination also theoretically extend to the species-wide scale by decreasing the power of selection relative to genetic drift, and thereby hindering the purging of deleterious mutations. In this study, we used genotyping-by-sequencing (GBS) to identify 136,000 recombination breakpoints at high resolution within US and Chinese maize nested association mapping populations. We find that the pattern of cross-overs is highly predictable on the broad scale, following the distribution of gene density and CpG methylation. Several large inversions also suppress recombination in distinct regions of several families. We also identify recombination hotspots ranging in size from 1 kb to 30 kb. We find these hotspots to be historically stable and, compared with similar regions with low recombination, to have strongly differentiated patterns of DNA methylation and GC content. We also provide evidence for the historical action of GC-biased gene conversion in recombination hotspots. Finally, using genomic evolutionary rate profiling (GERP) to identify putative deleterious polymorphisms, we find evidence for reduced genetic load in hotspot regions, a phenomenon that may have considerable practical importance for breeding programs worldwide.

Self-tuning wireless power transmission scheme based on on-line scattering parameters measurement and two-side power matching.

PubMed

Luo, Yanting; Yang, Yongmin; Chen, Zhongsheng

2014-04-10

Sub-resonances often happen in wireless power transmission (WPT) systems using coupled magnetic resonances (CMR) due to environmental changes, coil movements or component degradations, which is a serious challenge for high efficiency power transmission. Thus self-tuning is very significant to keep WPT systems following strongly magnetic resonant conditions in practice. Traditional coupled-mode ways is difficult to solve this problem. In this paper a two-port power wave model is presented, where power matching and the overall systemic power transmission efficiency are firstly defined by scattering (S) parameters. Then we propose a novel self-tuning scheme based on on-line S parameters measurements and two-side power matching. Experimental results testify the feasibility of the proposed method. These findings suggest that the proposed method is much potential to develop strongly self-adaptive WPT systems with CMR.

Wind farms production: Control and prediction

NASA Astrophysics Data System (ADS)

El-Fouly, Tarek Hussein Mostafa

Wind energy resources, unlike dispatchable central station generation, produce power dependable on external irregular source and that is the incident wind speed which does not always blow when electricity is needed. This results in the variability, unpredictability, and uncertainty of wind resources. Therefore, the integration of wind facilities to utility electrical grid presents a major challenge to power system operator. Such integration has significant impact on the optimum power flow, transmission congestion, power quality issues, system stability, load dispatch, and economic analysis. Due to the irregular nature of wind power production, accurate prediction represents the major challenge to power system operators. Therefore, in this thesis two novel models are proposed for wind speed and wind power prediction. One proposed model is dedicated to short-term prediction (one-hour ahead) and the other involves medium term prediction (one-day ahead). The accuracy of the proposed models is revealed by comparing their results with the corresponding values of a reference prediction model referred to as the persistent model. Utility grid operation is not only impacted by the uncertainty of the future production of wind farms, but also by the variability of their current production and how the active and reactive power exchange with the grid is controlled. To address this particular task, a control technique for wind turbines, driven by doubly-fed induction generators (DFIGs), is developed to regulate the terminal voltage by equally sharing the generated/absorbed reactive power between the rotor-side and the gridside converters. To highlight the impact of the new developed technique in reducing the power loss in the generator set, an economic analysis is carried out. Moreover, a new aggregated model for wind farms is proposed that accounts for the irregularity of the incident wind distribution throughout the farm layout. Specifically, this model includes the wake effect and the time delay of the incident wind speed of the different turbines on the farm, and to simulate the fluctuation in the generated power more accurately and more closer to real-time operation. Recently, wind farms with considerable output power ratings have been installed. Their integrating into the utility grid will substantially affect the electricity markets. This thesis investigates the possible impact of wind power variability, wind farm control strategy, wind energy penetration level, wind farm location, and wind power prediction accuracy on the total generation costs and close to real time electricity market prices. These issues are addressed by developing a single auction market model for determining the real-time electricity market prices.

Large-scale climate variation modifies the winter grouping behavior of endangered Indiana bats

USGS Publications Warehouse

Thogmartin, Wayne E.; McKann, Patrick C.

2014-01-01

Power laws describe the functional relationship between 2 quantities, such as the frequency of a group as the multiplicative power of group size. We examined whether the annual size of well-surveyed wintering populations of endangered Indiana bats (Myotis sodalis) followed a power law, and then leveraged this relationship to predict whether the aggregation of Indiana bats in winter was influenced by global climate processes. We determined that Indiana bat wintering populations were distributed according to a power law (mean scaling coefficient α = −0.44 [95% confidence interval {95% CI} = −0.61, −0.28). The antilog of these annual scaling coefficients ranged between 0.67 and 0.81, coincident with the three-fourths power found in many other biological phenomena. We associated temporal patterns in the annual (1983–2011) scaling coefficient with the North Atlantic Oscillation (NAO) index in August (βNAOAugust = −0.017 [90% CI = −0.032, −0.002]), when Indiana bats are deciding when and where to hibernate. After accounting for the strong effect of philopatry to habitual wintering locations, Indiana bats aggregated in larger wintering populations during periods of severe winter and in smaller populations in milder winters. The association with August values of the NAO indicates that bats anticipate future winter weather conditions when deciding where to roost, a heretofore unrecognized role for prehibernation swarming behavior. Future research is needed to understand whether the three-fourths–scaling patterns we observed are related to scaling in metabolism.

Analytical and experimental comparisons of electromechanical vibration response of a piezoelectric bimorph beam for power harvesting

NASA Astrophysics Data System (ADS)

Lumentut, M. F.; Howard, I. M.

2013-03-01

Power harvesters that extract energy from vibrating systems via piezoelectric transduction show strong potential for powering smart wireless sensor devices in applications of health condition monitoring of rotating machinery and structures. This paper presents an analytical method for modelling an electromechanical piezoelectric bimorph beam with tip mass under two input base transverse and longitudinal excitations. The Euler-Bernoulli beam equations were used to model the piezoelectric bimorph beam. The polarity-electric field of the piezoelectric element is excited by the strain field caused by base input excitation, resulting in electrical charge. The governing electromechanical dynamic equations were derived analytically using the weak form of the Hamiltonian principle to obtain the constitutive equations. Three constitutive electromechanical dynamic equations based on independent coefficients of virtual displacement vectors were formulated and then further modelled using the normalised Ritz eigenfunction series. The electromechanical formulations include both the series and parallel connections of the piezoelectric bimorph. The multi-mode frequency response functions (FRFs) under varying electrical load resistance were formulated using Laplace transformation for the multi-input mechanical vibrations to provide the multi-output dynamic displacement, velocity, voltage, current and power. The experimental and theoretical validations reduced for the single mode system were shown to provide reasonable predictions. The model results from polar base excitation for off-axis input motions were validated with experimental results showing the change to the electrical power frequency response amplitude as a function of excitation angle, with relevance for practical implementation.

Replacement of SSE (Release 6) with NASA's Prediction of Worldwide Energy Resource (POWER) Project GIS-enabled Web Data Portal:

Atmospheric Science Data Center

2018-03-15

... effort has been developed under the Prediction Of Worldwide Energy Resource (POWER) Project funded largely by NASA Earth Applied Sciences ... to NASA's satellite and modeling analysis for Renewable Energy, Sustainable Buildings and Agroclimatology applications.  A new POWER ...

POWER/SSE

Atmospheric Science Data Center

2018-06-15

... The Prediction of Worldwide Energy Resource (POWER) project was initiated to improve upon the current SSE ... continue to be focussed on the solar and wind Renewable Energy industry. New data sets will target Sustainable Buildings ... The Prediction of Worldwide Energy Resource (POWER) project was initiated to improve upon the current SSE ...

Non-Gaussian effects, space-time decoupling, and mobility bifurcation in glassy hard-sphere fluids and suspensions.

PubMed

Saltzman, Erica J; Schweizer, Kenneth S

2006-12-01

Brownian trajectory simulation methods are employed to fully establish the non-Gaussian fluctuation effects predicted by our nonlinear Langevin equation theory of single particle activated dynamics in glassy hard-sphere fluids. The consequences of stochastic mobility fluctuations associated with the space-time complexities of the transient localization and barrier hopping processes have been determined. The incoherent dynamic structure factor was computed for a range of wave vectors and becomes of an increasingly non-Gaussian form for volume fractions beyond the (naive) ideal mode coupling theory (MCT) transition. The non-Gaussian parameter (NGP) amplitude increases markedly with volume fraction and is well described by a power law in the maximum restoring force of the nonequilibrium free energy profile. The time scale associated with the NGP peak becomes much smaller than the alpha relaxation time for systems characterized by significant entropic barriers. An alternate non-Gaussian parameter that probes the long time alpha relaxation process displays a different shape, peak intensity, and time scale of its maximum. However, a strong correspondence between the classic and alternate NGP amplitudes is predicted which suggests a deep connection between the early and final stages of cage escape. Strong space-time decoupling emerges at high volume fractions as indicated by a nondiffusive wave vector dependence of the relaxation time and growth of the translation-relaxation decoupling parameter. Displacement distributions exhibit non-Gaussian behavior at intermediate times, evolving into a strongly bimodal form with slow and fast subpopulations at high volume fractions. Qualitative and semiquantitative comparisons of the theoretical results with colloid experiments, ideal MCT, and multiple simulation studies are presented.

Alpha and theta band dynamics related to sentential constraint and word expectancy.

PubMed

Rommers, Joost; Dickson, Danielle S; Norton, James J S; Wlotko, Edward W; Federmeier, Kara D

2017-01-01

Despite strong evidence for prediction during language comprehension, the underlying mechanisms, and the extent to which they are specific to language, remain unclear. Re-analyzing an ERP study, we examined responses in the time-frequency domain to expected and unexpected (but plausible) words in strongly and weakly constraining sentences, and found results similar to those reported in nonverbal domains. Relative to expected words, unexpected words elicited an increase in the theta band (4-7 Hz) in strongly constraining contexts, suggesting the involvement of control processes to deal with the consequences of having a prediction disconfirmed. Prior to critical word onset, strongly constraining sentences exhibited a decrease in the alpha band (8-12 Hz) relative to weakly constraining sentences, suggesting that comprehenders can take advantage of predictive sentence contexts to prepare for the input. The results suggest that the brain recruits domain-general preparation and control mechanisms when making and assessing predictions during sentence comprehension.

CRISP: Catheterization RISk score for Pediatrics: A Report from the Congenital Cardiac Interventional Study Consortium (CCISC).

PubMed

Nykanen, David G; Forbes, Thomas J; Du, Wei; Divekar, Abhay A; Reeves, Jaxk H; Hagler, Donald J; Fagan, Thomas E; Pedra, Carlos A C; Fleming, Gregory A; Khan, Danyal M; Javois, Alexander J; Gruenstein, Daniel H; Qureshi, Shakeel A; Moore, Phillip M; Wax, David H

2016-02-01

We sought to develop a scoring system that predicts the risk of serious adverse events (SAE's) for individual pediatric patients undergoing cardiac catheterization procedures. Systematic assessment of risk of SAE in pediatric catheterization can be challenging in view of a wide variation in procedure and patient complexity as well as rapidly evolving technology. A 10 component scoring system was originally developed based on expert consensus and review of the existing literature. Data from an international multi-institutional catheterization registry (CCISC) between 2008 and 2013 were used to validate this scoring system. In addition we used multivariate methods to further refine the original risk score to improve its predictive power of SAE's. Univariate analysis confirmed the strong correlation of each of the 10 components of the original risk score with SAE attributed to a pediatric cardiac catheterization (P < 0.001 for all variables). Multivariate analysis resulted in a modified risk score (CRISP) that corresponds to an increase in value of area under a receiver operating characteristic curve (AUC) from 0.715 to 0.741. The CRISP score predicts risk of occurrence of an SAE for individual patients undergoing pediatric cardiac catheterization procedures. © 2015 Wiley Periodicals, Inc.

The effect of iconicity of visual displays on statistical reasoning: evidence in favor of the null hypothesis.

PubMed

Sirota, Miroslav; Kostovičová, Lenka; Juanchich, Marie

2014-08-01

Knowing which properties of visual displays facilitate statistical reasoning bears practical and theoretical implications. Therefore, we studied the effect of one property of visual diplays - iconicity (i.e., the resemblance of a visual sign to its referent) - on Bayesian reasoning. Two main accounts of statistical reasoning predict different effect of iconicity on Bayesian reasoning. The ecological-rationality account predicts a positive iconicity effect, because more highly iconic signs resemble more individuated objects, which tap better into an evolutionary-designed frequency-coding mechanism that, in turn, facilitates Bayesian reasoning. The nested-sets account predicts a null iconicity effect, because iconicity does not affect the salience of a nested-sets structure-the factor facilitating Bayesian reasoning processed by a general reasoning mechanism. In two well-powered experiments (N = 577), we found no support for a positive iconicity effect across different iconicity levels that were manipulated in different visual displays (meta-analytical overall effect: log OR = -0.13, 95% CI [-0.53, 0.28]). A Bayes factor analysis provided strong evidence in favor of the null hypothesis-the null iconicity effect. Thus, these findings corroborate the nested-sets rather than the ecological-rationality account of statistical reasoning.

Genetic influence on athletic performance.

PubMed

Guth, Lisa M; Roth, Stephen M

2013-12-01

To summarize the existing literature on the genetics of athletic performance, with particular consideration for the relevance to young athletes. Two gene variants, ACE I/D and ACTN3 R577X, have been consistently associated with endurance (ACE I/I) and power-related (ACTN3 R/R) performance, though neither can be considered predictive. The role of genetic variation in injury risk and outcomes is more sparsely studied, but genetic testing for injury susceptibility could be beneficial in protecting young athletes from serious injury. Little information on the association of genetic variation with athletic performance in young athletes is available; however, genetic testing is becoming more popular as a means of talent identification. Despite this increase in the use of such testing, evidence is lacking for the usefulness of genetic testing over traditional talent selection techniques in predicting athletic ability, and careful consideration should be given to the ethical issues surrounding such testing in children. A favorable genetic profile, when combined with an optimal training environment, is important for elite athletic performance; however, few genes are consistently associated with elite athletic performance, and none are linked strongly enough to warrant their use in predicting athletic success.

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

Effect of the equivalent refractive index on intraocular lens power prediction with ray tracing after myopic laser in situ keratomileusis.

PubMed

Canovas, Carmen; van der Mooren, Marrie; Rosén, Robert; Piers, Patricia A; Wang, Li; Koch, Douglas D; Artal, Pablo

2015-05-01

To determine the impact of the equivalent refractive index (ERI) on intraocular lens (IOL) power prediction for eyes with previous myopic laser in situ keratomileusis (LASIK) using custom ray tracing. AMO B.V., Groningen, the Netherlands, and the Department of Ophthalmology, Baylor College of Medicine, Houston, Texas, USA. Retrospective data analysis. The ERI was calculated individually from the post-LASIK total corneal power. Two methods to account for the posterior corneal surface were tested; that is, calculation from pre-LASIK data or from post-LASIK data only. Four IOL power predictions were generated using a computer-based ray-tracing technique, including individual ERI results from both calculation methods, a mean ERI over the whole population, and the ERI for normal patients. For each patient, IOL power results calculated from the four predictions as well as those obtained with the Haigis-L were compared with the optimum IOL power calculated after cataract surgery. The study evaluated 25 patients. The mean and range of ERI values determined using post-LASIK data were similar to those determined from pre-LASIK data. Introducing individual or an average ERI in the ray-tracing IOL power calculation procedure resulted in mean IOL power errors that were not significantly different from zero. The ray-tracing procedure that includes an average ERI gave a greater percentage of eyes with an IOL power prediction error within ±0.5 diopter than the Haigis-L (84% versus 52%). For IOL power determination in post-LASIK patients, custom ray tracing including a modified ERI was an accurate procedure that exceeded the current standards for normal eyes. Copyright © 2015 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

Efficient differentially private learning improves drug sensitivity prediction.

PubMed

Honkela, Antti; Das, Mrinal; Nieminen, Arttu; Dikmen, Onur; Kaski, Samuel

2018-02-06

Users of a personalised recommendation system face a dilemma: recommendations can be improved by learning from data, but only if other users are willing to share their private information. Good personalised predictions are vitally important in precision medicine, but genomic information on which the predictions are based is also particularly sensitive, as it directly identifies the patients and hence cannot easily be anonymised. Differential privacy has emerged as a potentially promising solution: privacy is considered sufficient if presence of individual patients cannot be distinguished. However, differentially private learning with current methods does not improve predictions with feasible data sizes and dimensionalities. We show that useful predictors can be learned under powerful differential privacy guarantees, and even from moderately-sized data sets, by demonstrating significant improvements in the accuracy of private drug sensitivity prediction with a new robust private regression method. Our method matches the predictive accuracy of the state-of-the-art non-private lasso regression using only 4x more samples under relatively strong differential privacy guarantees. Good performance with limited data is achieved by limiting the sharing of private information by decreasing the dimensionality and by projecting outliers to fit tighter bounds, therefore needing to add less noise for equal privacy. The proposed differentially private regression method combines theoretical appeal and asymptotic efficiency with good prediction accuracy even with moderate-sized data. As already the simple-to-implement method shows promise on the challenging genomic data, we anticipate rapid progress towards practical applications in many fields. This article was reviewed by Zoltan Gaspari and David Kreil.

NEXT Ion Thruster Thermal Model

NASA Technical Reports Server (NTRS)

VanNoord, Jonathan L.

2010-01-01

As the NEXT ion thruster progresses towards higher technology readiness, it is necessary to develop the tools that will support its implementation into flight programs. An ion thruster thermal model has been developed for the latest prototype model design to aid in predicting thruster temperatures for various missions. This model is comprised of two parts. The first part predicts the heating from the discharge plasma for various throttling points based on a discharge chamber plasma model. This model shows, as expected, that the internal heating is strongly correlated with the discharge power. Typically, the internal plasma heating increases with beam current and decreases slightly with beam voltage. The second is a model based on a finite difference thermal code used to predict the thruster temperatures. Both parts of the model will be described in this paper. This model has been correlated with a thermal development test on the NEXT Prototype Model 1 thruster with most predicted component temperatures within 5 to 10 C of test temperatures. The model indicates that heating, and hence current collection, is not based purely on the footprint of the magnet rings, but follows a 0.1:1:2:1 ratio for the cathode-to-conical-to-cylindrical-to-front magnet rings. This thermal model has also been used to predict the temperatures during the worst case mission profile that is anticipated for the thruster. The model predicts ample thermal margin for all of its components except the external cable harness under the hottest anticipated mission scenario. The external cable harness will be re-rated or replaced to meet the predicted environment.

Data integration of structured and unstructured sources for assigning clinical codes to patient stays

PubMed Central

Luyckx, Kim; Luyten, Léon; Daelemans, Walter; Van den Bulcke, Tim

2016-01-01

Objective Enormous amounts of healthcare data are becoming increasingly accessible through the large-scale adoption of electronic health records. In this work, structured and unstructured (textual) data are combined to assign clinical diagnostic and procedural codes (specifically ICD-9-CM) to patient stays. We investigate whether integrating these heterogeneous data types improves prediction strength compared to using the data types in isolation. Methods Two separate data integration approaches were evaluated. Early data integration combines features of several sources within a single model, and late data integration learns a separate model per data source and combines these predictions with a meta-learner. This is evaluated on data sources and clinical codes from a broad set of medical specialties. Results When compared with the best individual prediction source, late data integration leads to improvements in predictive power (eg, overall F-measure increased from 30.6% to 38.3% for International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnostic codes), while early data integration is less consistent. The predictive strength strongly differs between medical specialties, both for ICD-9-CM diagnostic and procedural codes. Discussion Structured data provides complementary information to unstructured data (and vice versa) for predicting ICD-9-CM codes. This can be captured most effectively by the proposed late data integration approach. Conclusions We demonstrated that models using multiple electronic health record data sources systematically outperform models using data sources in isolation in the task of predicting ICD-9-CM codes over a broad range of medical specialties. PMID:26316458

Optimization of Contrast Detection Power with Probabilistic Behavioral Information

PubMed Central

Cordes, Dietmar; Herzmann, Grit; Nandy, Rajesh; Curran, Tim

2012-01-01

Recent progress in the experimental design for event-related fMRI experiments made it possible to find the optimal stimulus sequence for maximum contrast detection power using a genetic algorithm. In this study, a novel algorithm is proposed for optimization of contrast detection power by including probabilistic behavioral information, based on pilot data, in the genetic algorithm. As a particular application, a recognition memory task is studied and the design matrix optimized for contrasts involving the familiarity of individual items (pictures of objects) and the recollection of qualitative information associated with the items (left/right orientation). Optimization of contrast efficiency is a complicated issue whenever subjects’ responses are not deterministic but probabilistic. Contrast efficiencies are not predictable unless behavioral responses are included in the design optimization. However, available software for design optimization does not include options for probabilistic behavioral constraints. If the anticipated behavioral responses are included in the optimization algorithm, the design is optimal for the assumed behavioral responses, and the resulting contrast efficiency is greater than what either a block design or a random design can achieve. Furthermore, improvements of contrast detection power depend strongly on the behavioral probabilities, the perceived randomness, and the contrast of interest. The present genetic algorithm can be applied to any case in which fMRI contrasts are dependent on probabilistic responses that can be estimated from pilot data. PMID:22326984

Numerical analyses of baseline JT-60SA design concepts with the COREDIV code

NASA Astrophysics Data System (ADS)

Zagórski, R.; Gałązka, K.; Ivanova-Stanik, I.; Stępniewski, W.; Garzotti, L.; Giruzzi, G.; Neu, R.; Romanelli, M.

2017-06-01

JT-60SA reference design scenarios at high (#3) and low (#2) density have been analyzed with the help of the self-consistent COREDIV code. Simulations results for a standard C wall and full W wall have been compared in terms of the influence of impurities, both intrinsic (C, W) and seeded (N, Ar, Ne, Kr), on the radiation losses and plasma parameters. For scenario #3 in a C environment, the regime of detachment on divertor plates can be achieved with N or Ne seeding, whereas for the low density and high power scenario (#2), the C and seeding impurity radiation does not effectively reduce power to the targets. In this case, only an increase of either average density or edge density together with Kr seeding might help to develop conditions with strong radiation losses and semi-detached conditions in the divertor. The calculations show that, in the case of a W divertor, the power load to the plate is mitigated by seeding and the central plasma dilution is smaller compared to the C divertor. For the high density case (#3) with Ne seeding, operation in full detachment mode is predicted. Ar seems to be an optimal choice for the low-density high-power scenario #2, showing a wide operating window, whereas Ne leads to high plasma dilution at high seeding levels albeit not achieving semi-detached conditions in the divertor.

Forecasting Electric Power Generation of Photovoltaic Power System for Energy Network

NASA Astrophysics Data System (ADS)

Kudo, Mitsuru; Takeuchi, Akira; Nozaki, Yousuke; Endo, Hisahito; Sumita, Jiro

Recently, there has been an increase in concern about the global environment. Interest is growing in developing an energy network by which new energy systems such as photovoltaic and fuel cells generate power locally and electric power and heat are controlled with a communications network. We developed the power generation forecast method for photovoltaic power systems in an energy network. The method makes use of weather information and regression analysis. We carried out forecasting power output of the photovoltaic power system installed in Expo 2005, Aichi Japan. As a result of comparing measurements with a prediction values, the average prediction error per day was about 26% of the measured power.

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. For the three test seasons, the optimized thresholds tend to under-predict the icing losses. However, the threshold determined using boundary layer similarity theory most closely predicts the power losses due to icing versus the other methods. For the northern turbine, the average predicted power loss over the three seasons is 4.65 % while the observed power loss is 6.22 % (average difference of 1.57 %). For the southern turbine, the average predicted power loss and observed power loss over the same time period are 4.43 % and 6.16 %, respectively (average difference of 1.73 %). The three-year average, however, does not clearly capture the variability that exists season-to-season. On examination of each of the test seasons individually, the optimized relative humidity threshold methodology performs better than fixed power loss estimates commonly used in the wind energy industry.

Prediction of seasonal runoff in ungauged basins

USDA-ARS?s Scientific Manuscript database

Many regions of the world experience strong seasonality in climate (i.e. precipitation and temperature), and strong seasonal runoff variability. Predictable patterns in seasonal water availability are of significant benefit to society because they allow reliable planning and infrastructure developme...

Improved accuracy of intraocular lens power calculation with the Zeiss IOLMaster.

PubMed

Olsen, Thomas

2007-02-01

This study aimed to demonstrate how the level of accuracy in intraocular lens (IOL) power calculation can be improved with optical biometry using partial optical coherence interferometry (PCI) (Zeiss IOLMaster) and current anterior chamber depth (ACD) prediction algorithms. Intraocular lens power in 461 consecutive cataract operations was calculated using both PCI and ultrasound and the accuracy of the results of each technique were compared. To illustrate the importance of ACD prediction per se, predictions were calculated using both a recently published 5-variable method and the Haigis 2-variable method and the results compared. All calculations were optimized in retrospect to account for systematic errors, including IOL constants and other off-set errors. The average absolute IOL prediction error (observed minus expected refraction) was 0.65 dioptres with ultrasound and 0.43 D with PCI using the 5-variable ACD prediction method (p < 0.00001). The number of predictions within +/- 0.5 D, +/- 1.0 D and +/- 2.0 D of the expected outcome was 62.5%, 92.4% and 99.9% with PCI, compared with 45.5%, 77.3% and 98.4% with ultrasound, respectively (p < 0.00001). The 2-variable ACD method resulted in an average error in PCI predictions of 0.46 D, which was significantly higher than the error in the 5-variable method (p < 0.001). The accuracy of IOL power calculation can be significantly improved using calibrated axial length readings obtained with PCI and modern IOL power calculation formulas incorporating the latest generation ACD prediction algorithms.

Hybrid robust predictive optimization method of power system dispatch

DOEpatents

Chandra, Ramu Sharat [Niskayuna, NY; Liu, Yan [Ballston Lake, NY; Bose, Sumit [Niskayuna, NY; de Bedout, Juan Manuel [West Glenville, NY

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.

Power capability evaluation for lithium iron phosphate batteries based on multi-parameter constraints estimation

NASA Astrophysics Data System (ADS)

Wang, Yujie; Pan, Rui; Liu, Chang; Chen, Zonghai; Ling, Qiang

2018-01-01

The battery power capability is intimately correlated with the climbing, braking and accelerating performance of the electric vehicles. Accurate power capability prediction can not only guarantee the safety but also regulate driving behavior and optimize battery energy usage. However, the nonlinearity of the battery model is very complex especially for the lithium iron phosphate batteries. Besides, the hysteresis loop in the open-circuit voltage curve is easy to cause large error in model prediction. In this work, a multi-parameter constraints dynamic estimation method is proposed to predict the battery continuous period power capability. A high-fidelity battery model which considers the battery polarization and hysteresis phenomenon is presented to approximate the high nonlinearity of the lithium iron phosphate battery. Explicit analyses of power capability with multiple constraints are elaborated, specifically the state-of-energy is considered in power capability assessment. Furthermore, to solve the problem of nonlinear system state estimation, and suppress noise interference, the UKF based state observer is employed for power capability prediction. The performance of the proposed methodology is demonstrated by experiments under different dynamic characterization schedules. The charge and discharge power capabilities of the lithium iron phosphate batteries are quantitatively assessed under different time scales and temperatures.

Galaxy-galaxy weak gravitational lensing in f(R) gravity

NASA Astrophysics Data System (ADS)

Li, Baojiu; Shirasaki, Masato

2018-03-01

We present an analysis of galaxy-galaxy weak gravitational lensing (GGL) in chameleon f(R) gravity - a leading candidate of non-standard gravity models. For the analysis, we have created mock galaxy catalogues based on dark matter haloes from two sets of numerical simulations, using a halo occupation distribution (HOD) prescription which allows a redshift dependence of galaxy number density. To make a fairer comparison between the f(R) and Λ cold dark matter (ΛCDM) models, their HOD parameters are tuned so that the galaxy two-point correlation functions in real space (and therefore the projected two-point correlation functions) match. While the f(R) model predicts an enhancement of the convergence power spectrum by up to ˜ 30 per cent compared to the standard ΛCDM model with the same parameters, the maximum enhancement of GGL is only half as large and less than 5 per cent on separations above ˜1-2 h-1 Mpc, because the latter is a cross-correlation of shear (or matter, which is more strongly affected by modified gravity) and galaxy (which is weakly affected given the good match between galaxy autocorrelations in the two models) fields. We also study the possibility of reconstructing the matter power spectrum by combination of GGL and galaxy clustering in f(R) gravity. We find that the galaxy-matter cross-correlation coefficient remains at unity down to ˜2-3 h-1 Mpc at relevant redshifts even in f(R) gravity, indicating joint analysis of GGL and galaxy clustering can be a powerful probe of matter density fluctuations in chameleon gravity. The scale dependence of the model differences in their predictions of GGL can potentially allows us to break the degeneracy between f(R) gravity and other cosmological parameters such as Ωm and σ8.

Bayesian Analysis of Hot-Jupiter Radius Anomalies: Evidence for Ohmic Dissipation?

NASA Astrophysics Data System (ADS)

Thorngren, Daniel P.; Fortney, Jonathan J.

2018-05-01

The cause of hot-Jupiter radius inflation, where giant planets with {T}eq} > 1000 K are significantly larger than expected, is an open question and the subject of many proposed explanations. Many of these hypotheses postulate an additional anomalous power that heats planets’ convective interiors, leading to larger radii. Rather than examine these proposed models individually, we determine what anomalous powers are needed to explain the observed population’s radii, and consider which models are most consistent with this. We examine 281 giant planets with well-determined masses and radii and apply thermal evolution and Bayesian statistical models to infer the anomalous power as a fraction of (and varying with) incident flux ɛ(F) that best reproduces the observed radii. First, we observe that the inflation of planets below about M = 0.5 M J appears very different than their higher-mass counterparts, perhaps as the result of mass loss or an inefficient heating mechanism. As such, we exclude planets below this threshold. Next, we show with strong significance that ɛ(F) increases with {T}eq} toward a maximum of ∼2.5% at T eq ≈ 1500 K, and then decreases as temperatures increase further, falling to ∼0.2% at T eff = 2500 K. This high-flux decrease in inflation efficiency was predicted by the Ohmic dissipation model of giant planet inflation but not other models. We also show that the thermal tides model predicts far more variance in radii than is observed. Thus, our results provide evidence for the Ohmic dissipation model and a functional form for ɛ(F) that any future theories of hot-Jupiter radii can be tested against.

The variable heart: High frequency and very low frequency correlates of depressive symptoms in children and adolescents

PubMed Central

Blood, Julia D.; Wu, Jia; Chaplin, Tara M.; Hommer, Rebecca; Vazquez, Lauren; Rutherford, Helena J.V.; Mayes, Linda C.; Crowley, Michael J.

2015-01-01

Background Work examining the link between lower heart rate variability (HRV) and depression in children and adolescents is lacking, especially in light of the physiological changes that occur during pubertal development. Method We investigated the association between spectral measures of resting HRV and depressive symptoms among 127 children and adolescents, ages 10–17. Using spectral analysis, we evaluated (1) the association between relative high frequency (HF) HRV and depressive symptoms; (2) the predictive power of relative HF HRV for depressive symptoms in the context of relative low frequency (LF) and relative very low frequency (VLF) HRV; and (3) the relationship between relative HF, LF, and VLF band activity, age and pubertal maturation. Results Consistent with previous work, results revealed that relative HF HRV was negatively associated with self-reported depressive symptoms. As well, relative VLF HRV was positively associated with depressive symptoms. Regression analyses revealed that relative HF HRV and relative VLF HRV significantly predicted self-report depressive symptoms while controlling for age, sex and pubertal maturation, with relative VLF HRV emerging as the strongest indicator of depressive symptoms. Developmental findings also emerged. Age and pubertal maturation were negatively associated with relative HF HRV and positively correlated with relative VLF HRV. Conclusions Results provide support for the relationship between HRV and depression and suggest that both HF and VLF HRV are relevant to depression symptom severity. Findings also reinforce the importance of considering pubertal development when investigating HRV-depression associations in children and adolescents. Limitations Influences on cardiac control including physical activity levels and exercise patterns could be controlled in future work. Our data speak to a depressive symptom dimension and relative spectral power HRV. Thus, we cannot make strong claims about relative spectral power HRV and clinical depression. PMID:26233322

Balancing computation and communication power in power constrained clusters

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

Piga, Leonardo; Paul, Indrani; Huang, Wei

Systems, apparatuses, and methods for balancing computation and communication power in power constrained environments. A data processing cluster with a plurality of compute nodes may perform parallel processing of a workload in a power constrained environment. Nodes that finish tasks early may be power-gated based on one or more conditions. In some scenarios, a node may predict a wait duration and go into a reduced power consumption state if the wait duration is predicted to be greater than a threshold. The power saved by power-gating one or more nodes may be reassigned for use by other nodes. A cluster agentmore » may be configured to reassign the unused power to the active nodes to expedite workload processing.« less

Modeling of a resonant heat engine

NASA Astrophysics Data System (ADS)

Preetham, B. S.; Anderson, M.; Richards, C.

2012-12-01

A resonant heat engine in which the piston assembly is replaced by a sealed elastic cavity is modeled and analyzed. A nondimensional lumped-parameter model is derived and used to investigate the factors that control the performance of the engine. The thermal efficiency predicted by the model agrees with that predicted from the relation for the Otto cycle based on compression ratio. The predictions show that for a fixed mechanical load, increasing the heat input results in increased efficiency. The output power and power density are shown to depend on the loading for a given heat input. The loading condition for maximum output power is different from that required for maximum power density.

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.

Prediction of the effects of propeller operation on the static longitudinal stability of single-engine tractor monoplanes with flaps retracted

NASA Technical Reports Server (NTRS)

Weil, Joseph; Sleeman, William C , Jr

1949-01-01

The effects of propeller operation on the static longitudinal stability of single-engine tractor monoplanes are analyzed, and a simple method is presented for computing power-on pitching-moment curves for flap-retracted flight conditions. The methods evolved are based on the results of powered-model wind-tunnel investigations of 28 model configurations. Correlation curves are presented from which the effects of power on the downwash over the tail and the stabilizer effectiveness can be rapidly predicted. The procedures developed enable prediction of power-on longitudinal stability characteristics that are generally in very good agreement with experiment.

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.

Strong ground motion in the Kathmandu Valley during the 2015 Gorkha, Nepal, earthquake

NASA Astrophysics Data System (ADS)

Takai, Nobuo; Shigefuji, Michiko; Rajaure, Sudhir; Bijukchhen, Subeg; Ichiyanagi, Masayoshi; Dhital, Megh Raj; Sasatani, Tsutomu

2016-01-01

On 25 April 2015, a large earthquake of Mw 7.8 occurred along the Main Himalayan Thrust fault in central Nepal. It was caused by a collision of the Indian Plate beneath the Eurasian Plate. The epicenter was near the Gorkha region, 80 km northwest of Kathmandu, and the rupture propagated toward east from the epicentral region passing through the sediment-filled Kathmandu Valley. This event resulted in over 8000 fatalities, mostly in Kathmandu and the adjacent districts. We succeeded in observing strong ground motions at our four observation sites (one rock site and three sedimentary sites) in the Kathmandu Valley during this devastating earthquake. While the observed peak ground acceleration values were smaller than the predicted ones that were derived from the use of a ground motion prediction equation, the observed peak ground velocity values were slightly larger than the predicted ones. The ground velocities observed at the rock site (KTP) showed a simple velocity pulse, resulting in monotonic-step displacements associated with the permanent tectonic offset. The vertical ground velocities observed at the sedimentary sites had the same pulse motions that were observed at the rock site. In contrast, the horizontal ground velocities as well as accelerations observed at three sedimentary sites showed long duration with conspicuous long-period oscillations, due to the valley response. The horizontal valley response was characterized by large amplification (about 10) and prolonged oscillations. However, the predominant period and envelope shape of their oscillations differed from site to site, indicating a complicated basin structure. Finally, on the basis of the velocity response spectra, we show that the horizontal long-period oscillations on the sedimentary sites had enough destructive power to damage high-rise buildings with natural periods of 3 to 5 s.

Toward a theory of the general-anesthetic-induced phase transition of the cerebral cortex. I. A thermodynamics analogy

NASA Astrophysics Data System (ADS)

Steyn-Ross, Moira L.; Steyn-Ross, D. A.; Sleigh, J. W.; Wilcocks, Lara C.

2001-07-01

In a recent paper the authors developed a stochastic model for the response of the cerebral cortex to a general anesthetic agent. The model predicted that there would be an anesthetic-induced phase change at the point of transition into unconsciousness, manifested as a divergence in the electroencephalogram spectral power, and a change in spectral energy distribution from being relatively broadband in the conscious state to being strongly biased towards much lower frequencies in the unconscious state. Both predictions have been verified in recent clinical measurements. In the present paper we extend the model by calculating the equilibrium distribution function for the cortex, allowing us to establish a correspondence between the cortical phase transition and the more familiar thermodynamic phase transitions. This correspondence is achieved by first identifying a cortical free energy function, then by postulating that there exists an inverse relationship between an anesthetic effect and a quantity we define as cortical excitability, which plays a role analogous to temperature in thermodynamic phase transitions. We follow standard thermodynamic theory to compute a cortical entropy and a cortical ``heat capacity,'' and we investigate how these will vary with anesthetic concentration. The significant result is the prediction that the entropy will decrease discontinuously at the moment of induction into unconsciousness, concomitant with a release of ``latent heat'' which should manifest as a divergence in the analogous heat capacity. There is clear clinical evidence of heat capacity divergence in historical anesthetic-effect measurements performed in 1977 by Stullken et al. [Anesthesiology 46, 28 (1977)]. The discontinuous step change in cortical entropy suggests that the cortical phase transition is analogous to a first-order thermodynamic transition in which the comatose-quiescent state is strongly ordered, while the active cortical state is relatively disordered.

Core or Cusps: The Central Dark Matter Profile of a Strong Lensing Cluster with a Bright Central Image at Redshift 1

NASA Astrophysics Data System (ADS)

Collett, Thomas E.; Buckley-Geer, Elizabeth; Lin, Huan; Bacon, David; Nichol, Robert C.; Nord, Brian; Morice-Atkinson, Xan; Amara, Adam; Birrer, Simon; Kuropatkin, Nikolay; More, Anupreeta; Papovich, Casey; Romer, Kathy K.; Tessore, Nicolas; Abbott, Tim M. C.; Allam, Sahar; Annis, James; Benoit-Lévy, Aurlien; Brooks, David; Burke, David L.; Carrasco Kind, Matias; Castander, Francisco Javier J.; D'Andrea, Chris B.; da Costa, Luiz N.; Desai, Shantanu; Diehl, H. Thomas; Doel, Peter; Eifler, Tim F.; Flaugher, Brenna; Frieman, Josh; Gerdes, David W.; Goldstein, Daniel A.; Gruen, Daniel; Gschwend, Julia; Gutierrez, Gaston; James, David J.; Kuehn, Kyler; Kuhlmann, Steve; Lahav, Ofer; Li, Ting S.; Lima, Marcos; Maia, Marcio A. G.; March, Marisa; Marshall, Jennifer L.; Martini, Paul; Melchior, Peter; Miquel, Ramon; Plazas, Andrs A.; Rykoff, Eli S.; Sanchez, Eusebio; Scarpine, Vic; Schindler, Rafe; Schubnell, Michael; Sevilla-Noarbe, Ignacio; Smith, Mathew; Sobreira, Flavia; Suchyta, Eric; Swanson, Molly E. C.; Tarle, Gregory; Tucker, Douglas L.; Walker, Alistair R.

2017-07-01

We report on SPT-CLJ2011-5228, a giant system of arcs created by a cluster at z = 1.06. The arc system is notable for the presence of a bright central image. The source is a Lyman break galaxy at z s = 2.39 and the mass enclosed within the Einstein ring of radius 14 arcsec is ˜ {10}14.2 {M}⊙ . We perform a full reconstruction of the light profile of the lensed images to precisely infer the parameters of the mass distribution. The brightness of the central image demands that the central total density profile of the lens be shallow. By fitting the dark matter as a generalized Navarro-Frenk-White profile—with a free parameter for the inner density slope—we find that the break radius is {270}-76+48 kpc, and that the inner density falls with radius to the power -0.38 ± 0.04 at 68% confidence. Such a shallow profile is in strong tension with our understanding of relaxed cold dark matter halos; dark matter-only simulations predict that the inner density should fall as {r}-1. The tension can be alleviated if this cluster is in fact a merger; a two-halo model can also reconstruct the data, with both clumps (density varying as {r}-0.8 and {r}-1.0) much more consistent with predictions from dark matter-only simulations. At the resolution of our Dark Energy Survey imaging, we are unable to choose between these two models, but we make predictions for forthcoming Hubble Space Telescope imaging that will decisively distinguish between them.

Combination of MUC1 and MUC4 expression predicts clinical outcome in patients with oral squamous cell carcinoma.

PubMed

Kamikawa, Yoshiaki; Kanmura, Yuji; Hamada, Tomofumi; Yamada, Norishige; Macha, Muzafar A; Batra, Surinder K; Higashi, Michiyo; Yonezawa, Suguru; Sugihara, Kazumasa

2015-04-01

Both MUC1 and MUC4 are high molecular weight glycoproteins and are independent indicators of worse prognosis in many human epithelial cancers including oral squamous cell carcinoma (OSCC). However, there has been no investigation of the clinical importance of the co-expression of MUC1 and MUC4 in OSCC. The aim of this study was to evaluate the co-expression profile of MUC1/MUC4 and analyze the prognostic significance in OSCC. We examined the expression profile of MUC1 and MUC4 in OSCC tissues from 206 patients using immunohistochemistry. The co-expression profile of MUC1/MUC4 and its prognostic significance in OSCC was statistically analyzed. MUC1 and MUC4 overexpression were strongly correlated with each other (p < 0.0001) and a combination of both MUC1 and MUC4 expression was a powerful indicator for tumor aggressiveness such as tumor size (p = 0.014), lymph node metastasis (0.0001), tumor stage (p = 0.006), diffuse invasion (p = 0.028), and vascular invasion (p = 0.014). The MUC1/MUC4 double-positive patients showed the poorest overall and disease-free survival. Multivariate analysis revealed that MUC1/MUC4 double-positivity was the strong independent prognostic factor for overall and disease-free survival (p = 0.007 and (p = 0.0019), in addition to regional recurrence (p = 0.0025). Taken together, these observations indicate that the use of a combination of MUC1/MUC4 can predict outcomes for patients with OSCC. This combination is also a useful marker for predicting regional recurrence. MUC1 and MUC4 may be attractive targets for the selection of treatment methods in OSCC.

Core or Cusps: The Central Dark Matter Profile of a Strong Lensing Cluster with a Bright Central Image at Redshift 1

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

Collett, Thomas E.; Buckley-Geer, Elizabeth; Lin, Huan

We report on SPT-CLJ2011-5228, a giant system of arcs created by a cluster atmore » $z=1.06$. The arc system is notable for the presence of a bright central image. The source is a Lyman Break galaxy at $$z_s=2.39$$ and the mass enclosed within the 14 arc second radius Einstein ring is $$10^{14.2}$$ solar masses. We perform a full light profile reconstruction of the lensed images to precisely infer the parameters of the mass distribution. The brightness of the central image demands that the central total density profile of the lens be shallow. By fitting the dark matter as a generalized Navarro-Frenk-White profile---with a free parameter for the inner density slope---we find that the break radius is $$270^{+48}_{-76}$$ kpc, and that the inner density falls with radius to the power $$-0.38\\pm0.04$$ at 68 percent confidence. Such a shallow profile is in strong tension with our understanding of relaxed cold dark matter halos; dark matter only simulations predict the inner density should fall as $$r^{-1}$$. The tension can be alleviated if this cluster is in fact a merger; a two halo model can also reconstruct the data, with both clumps (density going as $$r^{-0.8}$$ and $$r^{-1.0}$$) much more consistent with predictions from dark matter only simulations. At the resolution of our Dark Energy Survey imaging, we are unable to choose between these two models, but we make predictions for forthcoming Hubble Space Telescope imaging that will decisively distinguish between them.« less

A Comparison between Bench Press Throw and Ballistic Push-Up tests to assess upper-body power in trained individuals.

PubMed

Bartolomei, Sandro; Nigro, Federico; Ruggeri, Sandro; Lanzoni, Ivan Malagoli; Ciacci, Simone; Merni, Franco; Sadres, Eliahu; Hoffman, Jay R; Semprini, Gabriele

2018-03-06

The purpose of the present study was to validate the ballistic push-up test performed with hands on a force plate (BPU) as a method to measure upper-body power. Twenty-eight experienced resistance trained men (age = 25.4 ± 5.2 y; body mass = 78.5 ± 9.0 kg; body height = 179.6 ± 7.8 cm) performed, two days apart, a bench press 1RM test and upper-body power tests. Mean power and peak power were assessed using the bench press throw test (BT) and the BPU test performed in randomized order. The area under the force/power curve (AUC) obtained at BT was also calculated. Power expressed at BPU was estimated using a time-based prediction equation. Mean force and the participant's body weight were used to predict the bench press 1RM. Pearson product moment correlations were used to examine relationships between the power assessment methods and between the predicted 1RM bench and the actual value. Large correlations (0.79; p < 0.001) were found between AUC and mean power expressed at BPU. Large correlations were also detected between mean power and peak power expressed at BT and BPU (0.75; p < 0.001 and 0.74; p < 0.001, respectively). Very large correlations (0.87; p < 0.001) were found between the 1RM bench and the 1RM predicted by the BPU. Results of the present study indicate that BPU represents a valid and reliable method to estimate the upper-body power in resistance-trained individuals.

CMB temperature trispectrum of cosmic strings

NASA Astrophysics Data System (ADS)

Hindmarsh, Mark; Ringeval, Christophe; Suyama, Teruaki

2010-03-01

We provide an analytical expression for the trispectrum of the cosmic microwave background (CMB) temperature anisotropies induced by cosmic strings. Our result is derived for the small angular scales under the assumption that the temperature anisotropy is induced by the Gott-Kaiser-Stebbins effect. The trispectrum is predicted to decay with a noninteger power-law exponent ℓ-ρ with 6<ρ<7, depending on the string microstructure, and thus on the string model. For Nambu-Goto strings, this exponent is related to the string mean square velocity and the loop distribution function. We then explore two classes of wave number configuration in Fourier space, the kite and trapezium quadrilaterals. The trispectrum can be of any sign and appears to be strongly enhanced for all squeezed quadrilaterals.

SPLICEFINDER – A Fast and Easy Screening Method for Active Protein Trans-Splicing Positions

PubMed Central

Eppmann, Simone; Busche, Alena; Dikovskaya, Dina; Dötsch, Volker; Mootz, Henning D.

2013-01-01

Split intein enabled protein trans-splicing (PTS) is a powerful method for the ligation of two protein fragments, thereby paving the way for various protein modification or protein function control applications. PTS activity is strongly influenced by the amino acids directly flanking the splice junctions. However, to date no reliable prediction can be made whether or not a split intein is active in a particular foreign extein context. Here we describe SPLICEFINDER, a PCR-based method, allowing fast and easy screening for active split intein insertions in any target protein. Furthermore we demonstrate the applicability of SPLICEFINDER for segmental isotopic labeling as well as for the generation of multi-domain and enzymatically active proteins. PMID:24023792

Predictors of elderly mortality: health status, socioeconomic characteristics and social determinants of health.

PubMed

Mete, Cem

2005-02-01

This paper uses longitudinal survey data from Taiwan to investigate the predictors of elderly mortality. The empirical analysis confirms a relationship between socioeconomic characteristics and mortality, but this relationship weakens considerably when estimates are conditional on the health status at the time of the first wave survey. In terms of predictive power, the models with an activities of daily living index fare better (as opposed to models with self-evaluated health or self-reported illnesses). Having said that there is a payoff to the consideration of self-evaluated health jointly with other 'objective' health indicators. Other findings include a strong association between life satisfaction and survival, which prevails even after controlling for other explanatory variables. Copyright (c) 2004 John Wiley & Sons, Ltd.

Finite-Size Effects on the Behavior of the Susceptibility in van der Waals Films Bounded by Strongly Absorbing Substrates

NASA Technical Reports Server (NTRS)

Dantchev, Daniel; Rudnick, Joseph; Barmatz, M.

2007-01-01

We study critical point finite-size effects in the case of the susceptibility of a film in which interactions are characterized by a van der Waals-type power law tail. The geometry is appropriate to a slab-like system with two bounding surfaces. Boundary conditions are consistent with surfaces that both prefer the same phase in the low temperature, or broken symmetry, state. We take into account both interactions within the system and interactions between the constituents of the system and the material surrounding it. Specific predictions are made with respect to the behavior of 3He and 4He films in the vicinity of their respective liquid-vapor critical points.

Impact of Various Charge States of Hydrogen on Passivation of Dislocation in Silicon

NASA Astrophysics Data System (ADS)

Song, Lihui; Lou, Jingjing; Fu, Jiayi; Ji, Zhenguo

2018-03-01

Dislocation, one of typical crystallographic defects in silicon, is detrimental to the minority carrier lifetime of silicon wafer. Hydrogen passivation is able to reduce the recombination activity of dislocation, however, the passivation efficacy is strongly dependent on the experimental conditions. In this paper, a model based on the theory of hydrogen charge state control is proposed to explain the passivation efficacy of dislocation correlated to the peak temperature of thermal annealing and illumination intensity. Experimental results support the prediction of the model that a mix of positively charged hydrogen and negatively charged hydrogen at certain ratio can maximise the passivation efficacy of dislocation, leading to a better power conversion efficiency of silicon solar cell with dislocation in it.

Rapid nitrous oxide cycling in the suboxic ocean

NASA Astrophysics Data System (ADS)

Babbin, Andrew R.; Bianchi, Daniele; Jayakumar, Amal; Ward, Bess B.

2015-06-01

Nitrous oxide (N2O) is a powerful greenhouse gas and a major cause of stratospheric ozone depletion, yet its sources and sinks remain poorly quantified in the oceans. We used isotope tracers to directly measure N2O reduction rates in the eastern tropical North Pacific. Because of incomplete denitrification, N2O cycling rates are an order of magnitude higher than predicted by current models in suboxic regions, and the spatial distribution suggests strong dependence on both organic carbon and dissolved oxygen concentrations. Furthermore, N2O turnover is 20 times higher than the net atmospheric efflux. The rapid rate of this cycling coupled to an expected expansion of suboxic ocean waters implies future increases in N2O emissions.

Diagnostic studies of ensemble forecast "jumps"

NASA Astrophysics Data System (ADS)

Magnusson, Linus; Hewson, Tim; Ferranti, Laura; Rodwell, Mark

2016-04-01

During 2015 we saw exceptional consistency in successive seasonal forecasts produced at ECMWF, for the winter period 2015/16, right across the globe. This winter was characterised by a well-predicted and unusually strong El Nino, and some have ascribed the consistency to that. For most of December this consistency was mirrored in the (separate) ECMWF monthly forecast system, which correctly predicted anomalously strong (mild) zonal flow, over the North Atlantic and western Eurasia, even in forecasts for weeks 3 and 4. In monthly forecasts in general these weeks are often devoid of strong signals. However in late December and early January strong signals, even in week 2, proved to be incorrect, most notably over the North Atlantic and Eurasian sectors. Indeed on at least two occasions the outcome was beyond the ensemble forecast range over Scandinavia. In one of these conditions flipped from extreme mild to extreme cold as a high latitude block developed. Temperature prediction is very important to many customers, notably those dealing with renewable energy, because cold weather causes increased demand but also tends to coincide with reduced wind power production. So understandably jumps can cause consternation amongst some customer groups, and are very difficult to handle operationally. This presentation will discuss the results of initial diagnostic investigations into what caused the "ensemble jumps", particularly at the week two lead, though reference will also be made to a related shorter range (day 3) jump that was important for flooding over the UK. Initial results suggest that an inability of the ECMWF model to correctly represent convective outbreaks over North America (that for winter-time were quite extreme) played an important role. Significantly, during this period, an unusually large amount of upper air data over North America was rejected or ascribed low weight. These results bear similarities to previous diagnostic studies at ECMWF, wherein major convective outbreaks in spring and early summer over North America were shown to have a detrimental impact on forecast quality. The possible contributions of other factors will also be discussed; for example we know that the ECMWF model exhibits different skill levels for different regime transitions. It will also be shown that the new higher resolution ECMWF forecast system, then running in trial mode, performed somewhat better, at least for some of these cases.

Studying the Power of the Integrative Weaning Index in Predicting the Success Rate of the Spontaneous Breathing Trial in Patients under Mechanical Ventilation.

PubMed

Ebrahimabadi, Sahar; Moghadam, Ahmad Bagheri; Vakili, Mohammadali; Modanloo, Mahnaz; Khoddam, Homeira

2017-08-01

The use of weaning predictive indicators can avoid early extubation and wrongful prolonged mechanical ventilation. This study aimed to determine the power of the integrative weaning index (IWI) in predicting the success rate of the spontaneous breathing trial (SBT) in patients under mechanical ventilation. In this prospective study, 105 patients undergoing mechanical ventilation for over 48 h were enrolled. Before weaning initiation, the IWI was calculated and based on the defined cutoff point (≥25), the success rate of the SBT was predicted. In case of weaning from the device, 2-h SBT was performed and the physiologic and respiratory indices were continuously studied while being intubated. If they were in the normal range besides the patient's tolerance, the test was considered as a success. The result was then compared with the IWI and further analyzed. The SBT was successful in 90 (85.7%) and unsuccessful in 15 (14.3%) cases. The difference between the true patient outcome after SBT, and the IWI prediction was 0.143 according to the Kappa agreement coefficient ( P < 0.001). Moreover, regarding the predictive power, IWI had high sensitivity (95.6%), specificity (40%), positive and negative predictive values (90.5% and 60), positive and negative likelihood ratios (1.59 and 0.11), and accuracy (86.7%). The IWI as a more objective indicator has acceptable accuracy and power for predicting the 2-h SBT result. Therefore, in addition to the reliable prediction of the final weaning outcome, it has favorable power to predict if the patient is ready to breathe spontaneously as the first step to weaning.

Studying the Power of the Integrative Weaning Index in Predicting the Success Rate of the Spontaneous Breathing Trial in Patients under Mechanical Ventilation

PubMed Central

Ebrahimabadi, Sahar; Moghadam, Ahmad Bagheri; Vakili, Mohammadali; Modanloo, Mahnaz; Khoddam, Homeira

2017-01-01

Background and Aims: The use of weaning predictive indicators can avoid early extubation and wrongful prolonged mechanical ventilation. This study aimed to determine the power of the integrative weaning index (IWI) in predicting the success rate of the spontaneous breathing trial (SBT) in patients under mechanical ventilation. Materials and Methods: In this prospective study, 105 patients undergoing mechanical ventilation for over 48 h were enrolled. Before weaning initiation, the IWI was calculated and based on the defined cutoff point (≥25), the success rate of the SBT was predicted. In case of weaning from the device, 2-h SBT was performed and the physiologic and respiratory indices were continuously studied while being intubated. If they were in the normal range besides the patient's tolerance, the test was considered as a success. The result was then compared with the IWI and further analyzed. Results: The SBT was successful in 90 (85.7%) and unsuccessful in 15 (14.3%) cases. The difference between the true patient outcome after SBT, and the IWI prediction was 0.143 according to the Kappa agreement coefficient (P < 0.001). Moreover, regarding the predictive power, IWI had high sensitivity (95.6%), specificity (40%), positive and negative predictive values (90.5% and 60), positive and negative likelihood ratios (1.59 and 0.11), and accuracy (86.7%). Conclusion: The IWI as a more objective indicator has acceptable accuracy and power for predicting the 2-h SBT result. Therefore, in addition to the reliable prediction of the final weaning outcome, it has favorable power to predict if the patient is ready to breathe spontaneously as the first step to weaning. PMID:28904477

Good Health: The Power of Power

ERIC Educational Resources Information Center

Corbin, Charles B.; Janz, Kathleen F.; Baptista, Fátima

2017-01-01

Power has long been considered to be a skill-related fitness component. However, based on recent evidence, a strong case can be made for the classification of power as a health-related fitness component. Additionally, the evidence indicates that performing physical activities that build power is associated with the healthy development of bones…

Rolling Bearing Life Prediction, Theory, and Application

NASA Technical Reports Server (NTRS)

Zaretsky, Erwin V.

2016-01-01

A tutorial is presented outlining the evolution, theory, and application of rolling-element bearing life prediction from that of A. Palmgren, 1924; W. Weibull, 1939; G. Lundberg and A. Palmgren, 1947 and 1952; E. Ioannides and T. Harris, 1985; and E. Zaretsky, 1987. Comparisons are made between these life models. The Ioannides-Harris model without a fatigue limit is identical to the Lundberg-Palmgren model. The Weibull model is similar to that of Zaretsky if the exponents are chosen to be identical. Both the load-life and Hertz stress-life relations of Weibull, Lundberg and Palmgren, and Ioannides and Harris reflect a strong dependence on the Weibull slope. The Zaretsky model decouples the dependence of the critical shear stress-life relation from the Weibull slope. This results in a nominal variation of the Hertz stress-life exponent. For 9th- and 8th-power Hertz stress-life exponents for ball and roller bearings, respectively, the Lundberg-Palmgren model best predicts life. However, for 12th- and 10th-power relations reflected by modern bearing steels, the Zaretsky model based on the Weibull equation is superior. Under the range of stresses examined, the use of a fatigue limit would suggest that (for most operating conditions under which a rolling-element bearing will operate) the bearing will not fail from classical rolling-element fatigue. Realistically, this is not the case. The use of a fatigue limit will significantly overpredict life over a range of normal operating Hertz stresses. (The use of ISO 281:2007 with a fatigue limit in these calculations would result in a bearing life approaching infinity.) Since the predicted lives of rolling-element bearings are high, the problem can become one of undersizing a bearing for a particular application. Rules had been developed to distinguish and compare predicted lives with those actually obtained. Based upon field and test results of 51 ball and roller bearing sets, 98 percent of these bearing sets had acceptable life results using the Lundberg- Palmgren equations with life adjustment factors to predict bearing life. That is, they had lives equal to or greater than that predicted. The Lundberg-Palmgren model was used to predict the life of a commercial turboprop gearbox. The life prediction was compared with the field lives of 64 gearboxes. From these results, the roller bearing lives exhibited a load-life exponent of 5.2, which correlated with the Zaretsky model. The use of the ANSI/ABMA and ISO standards load-life exponent of 10/3 to predict roller bearing life is not reflective of modern roller bearings and will underpredict bearing lives.

Electronic stopping powers for heavy ions in SiC and SiO{sub 2}

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

Jin, K.; Xue, H.; Zhang, Y., E-mail: Zhangy1@ornl.gov

2014-01-28

Accurate information on electronic stopping power is fundamental for broad advances in materials science, electronic industry, space exploration, and sustainable energy technologies. In the case of slow heavy ions in light targets, current codes and models provide significantly inconsistent predictions, among which the Stopping and Range of Ions in Matter (SRIM) code is the most commonly used one. Experimental evidence, however, has demonstrated considerable errors in the predicted ion and damage profiles based on SRIM stopping powers. In this work, electronic stopping powers for Cl, Br, I, and Au ions are experimentally determined in two important functional materials, SiC andmore » SiO{sub 2}, based on a single ion technique, and new electronic stopping power values are derived over the energy regime from 0 to 15 MeV, where large deviations from the SRIM predictions are observed. As an experimental validation, Rutherford backscattering spectrometry (RBS) and secondary ion mass spectrometry (SIMS) are utilized to measure the depth profiles of implanted Au ions in SiC for energies from 700 keV to 15 MeV. The measured ion distributions by both RBS and SIMS are considerably deeper than the SRIM predictions, but agree well with predictions based on our derived stopping powers.« less

Electronic Stopping Powers For Heavy Ions In SiC And SiO2

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

Jin, Ke; Zhang, Y.; Zhu, Zihua

2014-01-24

Accurate information on electronic stopping power is fundamental for broad advances in materials science, electronic industry, space exploration, and sustainable energy technologies. In the case of slow heavy ions in light targets, current codes and models provide significantly inconsistent predictions, among which the Stopping and Range of Ions in Matter (SRIM) code is the most commonly used one. Experimental evidence, however, has demonstrated considerable errors in the predicted ion and damage profiles based on SRIM stopping powers. In this work, electronic stopping powers for Cl, Br, I, and Au ions are experimentally determined in two important functional materials, SiC andmore » SiO2, based on a single ion technique, and new electronic stopping power values are derived over the energy regime from 0 to 15 MeV, where large deviations from the SRIM predictions are observed. As an experimental validation, Rutherford backscattering spectrometry (RBS) and secondary ion mass spectrometry (SIMS) are utilized to measure the depth profiles of implanted Au ions in SiC for energies from 700 keV to 15MeV. The measured ion distributions by both RBS and SIMS are considerably deeper than the SRIM predictions, but agree well with predictions based on our derived stopping powers.« less

Attributing spatial and temporal changes in soil C in the UK to environmental drivers

NASA Astrophysics Data System (ADS)

Thomas, Amy; Cosby, Bernard; Quin, Sam; Henrys, Pete; Robinson, David; Emmett, Bridget

2015-04-01

The largest terrestrial pool of carbon is found in soils. Understanding how soil C responds to drivers of change (land use and management, atmospheric deposition, climate change) and how these responses are modified by inherent soil properties is crucial if we are to manage soils more sustainably in the future. Here we attempt to attribute spatial and temporal changes in UK soil C to environmental drivers using data from the UK Countryside Survey (CS), a national soil survey across England, Scotland and Wales repeated in 1978, 1998 and 2007. A mixed model approach was used to model soil C concentration (g C kg-1) and density (t C ha-1) and their absolute changes for the time periods 1978-1998, 1998-2007 and 1978-2007 across the CS sites using a variety of explanatory variables: soil (parent material, pH, moisture, Olsen-P, Shannon Diversity Index); atmospheric deposition (nitrogen and sulphur); climate (growing degree days and rain); and land use (aggregate vegetation class). Spatially, prediction of soil C concentration was good; soil moisture, pH, vegetation class and dominant grain size were all significant predictors. Field capacity also appeared to be important; however this data was only collected for a fraction of sites. N% was also strongly related to soil C concentration and density, as would be expected due to coupling of C and N in soil OM pools. Although N may drive soil C through impact on plant productivity, this cannot be separated from correlated C and N losses with OM decomposition, and hence N was not included as a driver for modelling. Predictive power for C density is not as strong as for concentration, which may reflect nonlinear relationships not represented by the modelling approach. Temporally, change in soil C is more difficult to explain, and model predictive power was lower. Change in soil pH was important in explaining change in C concentration and density, along with change in atmospheric deposition; decrease in deposition and associated soil acidity (increase in pH) was associated with a decrease in soil C concentration and density. Change in soil moisture or rainfall was also important. Inherent soil and site properties such as soil texture, vegetation class and parent material appeared to contribute most to the prediction of soil C change through modulation of the relationship between change in soil C and change in pH. Including anthropogenic and natural drivers in models of soil C stocks and changes in the UK enables assessment of the relative importance of each across the UK CS sites, however interactions among the drivers are more difficult to disentangle. Given the statistical significance of a number of drivers and soil variables in predicting soil C stocks and changes in the UK, it is important that these continue to be measured to allow better model development and more reliable predictions of future soil C conditions.

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. © 2011 Society for Risk Analysis.