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Sample records for conditional prediction intervals

  1. Predictive intervals for age-specific fertility.

    PubMed

    Keilman, N; Pham, D Q

    2000-03-01

    A multivariate ARIMA model is combined with a Gamma curve to predict confidence intervals for age-specific birth rates by 1-year age groups. The method is applied to observed age-specific births in Norway between 1900 and 1995, and predictive intervals are computed for each year up to 2050. The predicted two-thirds confidence intervals for Total Fertility (TF) around 2010 agree well with TF errors in old population forecasts made by Statistics Norway. The method gives useful predictions for age-specific fertility up to the years 2020-30. For later years, the intervals become too wide. Methods that do not take into account estimation errors in the ARIMA model coefficients underestimate the uncertainty for future TF values. The findings suggest that the margin between high and low fertility variants in official population forecasts for many Western countries are too narrow. PMID:12158991

  2. Interval prediction in structural dynamic analysis

    NASA Technical Reports Server (NTRS)

    Hasselman, Timothy K.; Chrostowski, Jon D.; Ross, Timothy J.

    1992-01-01

    Methods for assessing the predictive accuracy of structural dynamic models are examined with attention given to the effects of modal mass, stiffness, and damping uncertainties. The methods are based on a nondeterministic analysis called 'interval prediction' in which interval variables are used to describe parameters and responses that are unknown. Statistical databases for generic modeling uncertainties are derived from experimental data and incorporated analytically to evaluate responses. Covariance matrices of modal mass, stiffness, and damping parameters are propagated numerically in models of large space structures by means of three methods. The test data tend to fall within the predicted intervals of uncertainty determined by the statistical databases. The present findings demonstrate the suitability of using data from previously analyzed and tested space structures for assessing the predictive accuracy of an analytical model.

  3. Bootstrap Prediction Intervals in Non-Parametric Regression with Applications to Anomaly Detection

    NASA Technical Reports Server (NTRS)

    Kumar, Sricharan; Srivistava, Ashok N.

    2012-01-01

    Prediction intervals provide a measure of the probable interval in which the outputs of a regression model can be expected to occur. Subsequently, these prediction intervals can be used to determine if the observed output is anomalous or not, conditioned on the input. In this paper, a procedure for determining prediction intervals for outputs of nonparametric regression models using bootstrap methods is proposed. Bootstrap methods allow for a non-parametric approach to computing prediction intervals with no specific assumptions about the sampling distribution of the noise or the data. The asymptotic fidelity of the proposed prediction intervals is theoretically proved. Subsequently, the validity of the bootstrap based prediction intervals is illustrated via simulations. Finally, the bootstrap prediction intervals are applied to the problem of anomaly detection on aviation data.

  4. New delay-interval stability condition

    NASA Astrophysics Data System (ADS)

    Souza, Fernando O.; Palhares, Reinaldo M.

    2014-03-01

    The delay-dependent stability problem for systems with time-delay varying in an interval is addressed in this article. The new idea in this article is to connect two very efficient approaches: the discretised Lyapunov functional for systems with pointwise delay and the convex analysis for systems with time-varying delay. The proposed method is able to check the stability interval when the time-varying delay d(t) belongs to an interval [r, τ]. The case of unstable delayed systems for r = 0 is also treatable. The resulting criterion, expressed in terms of a convex optimisation problem, outperforms the existing ones in the literature, as illustrated by the numerical examples.

  5. Inflation of Conditional Predictions

    ERIC Educational Resources Information Center

    Koriat, Asher; Fiedler, Klaus; Bjork, Robert A.

    2006-01-01

    The authors report 7 experiments indicating that conditional predictions--the assessed probability that a certain outcome will occur given a certain condition--tend to be markedly inflated. The results suggest that this inflation derives in part from backward activation in which the target outcome highlights aspects of the condition that are…

  6. Plea for routinely presenting prediction intervals in meta-analysis

    PubMed Central

    IntHout, Joanna; Ioannidis, John P A; Rovers, Maroeska M; Goeman, Jelle J

    2016-01-01

    Objectives Evaluating the variation in the strength of the effect across studies is a key feature of meta-analyses. This variability is reflected by measures like τ2 or I2, but their clinical interpretation is not straightforward. A prediction interval is less complicated: it presents the expected range of true effects in similar studies. We aimed to show the advantages of having the prediction interval routinely reported in meta-analyses. Design We show how the prediction interval can help understand the uncertainty about whether an intervention works or not. To evaluate the implications of using this interval to interpret the results, we selected the first meta-analysis per intervention review of the Cochrane Database of Systematic Reviews Issues 2009–2013 with a dichotomous (n=2009) or continuous (n=1254) outcome, and generated 95% prediction intervals for them. Results In 72.4% of 479 statistically significant (random-effects p<0.05) meta-analyses in the Cochrane Database 2009–2013 with heterogeneity (I2>0), the 95% prediction interval suggested that the intervention effect could be null or even be in the opposite direction. In 20.3% of those 479 meta-analyses, the prediction interval showed that the effect could be completely opposite to the point estimate of the meta-analysis. We demonstrate also how the prediction interval can be used to calculate the probability that a new trial will show a negative effect and to improve the calculations of the power of a new trial. Conclusions The prediction interval reflects the variation in treatment effects over different settings, including what effect is to be expected in future patients, such as the patients that a clinician is interested to treat. Prediction intervals should be routinely reported to allow more informative inferences in meta-analyses. PMID:27406637

  7. Statistics of return intervals between long heartbeat intervals and their usability for online prediction of disorders

    NASA Astrophysics Data System (ADS)

    Bogachev, Mikhail I.; Kireenkov, Igor S.; Nifontov, Eugene M.; Bunde, Armin

    2009-06-01

    We study the statistics of return intervals between large heartbeat intervals (above a certain threshold Q) in 24 h records obtained from healthy subjects. We find that both the linear and the nonlinear long-term memory inherent in the heartbeat intervals lead to power-laws in the probability density function PQ(r) of the return intervals. As a consequence, the probability WQ(t; Δt) that at least one large heartbeat interval will occur within the next Δt heartbeat intervals, with an increasing elapsed number of intervals t after the last large heartbeat interval, follows a power-law. Based on these results, we suggest a method of obtaining a priori information about the occurrence of the next large heartbeat interval, and thus to predict it. We show explicitly that the proposed method, which exploits long-term memory, is superior to the conventional precursory pattern recognition technique, which focuses solely on short-term memory. We believe that our results can be straightforwardly extended to obtain more reliable predictions in other physiological signals like blood pressure, as well as in other complex records exhibiting multifractal behaviour, e.g. turbulent flow, precipitation, river flows and network traffic.

  8. PREDICTION INTERVALS FOR INTEGRALS OF GAUSSIAN RANDOM FIELDS

    PubMed Central

    De Oliveira, Victor; Kone, Bazoumana

    2014-01-01

    Methodology is proposed for the construction of prediction intervals for integrals of Gaussian random fields over bounded regions (called block averages in the geostatistical literature) based on observations at a finite set of sampling locations. Two bootstrap calibration algorithms are proposed, termed indirect and direct, aimed at improving upon plug-in prediction intervals in terms of coverage probability. A simulation study is carried out that illustrates the effectiveness of both procedures, and these procedures are applied to estimate block averages of chromium traces in a potentially contaminated region in Switzerland. PMID:25431507

  9. Hourly Wind Speed Interval Prediction in Arid Regions

    NASA Astrophysics Data System (ADS)

    Chaouch, M.; Ouarda, T.

    2013-12-01

    context, probabilistic forecasts might be more relevant than point forecasts for the planner to build scenarios In this paper, we are interested in estimating predictive intervals of the hourly wind speed measures in few cities in United Arab emirates (UAE). More precisely, given a wind speed time series, our target is to forecast the wind speed at any specific hour during the day and provide in addition an interval with the coverage probability 0interval we need to estimate the lower band (resp. upper band) which corresponds to the (1-p)/2-th (resp. (1+p)/2-th) conditional quantile. In this paper, a kernel-smoothed estimator of the conditional quantiles is introduced. The proposed non-parametric approach has many advantages since it is flexible because it does not need a specification of the model to work with (such as normal distribution or a linear relation). Here, we use a covariable that is correlated to the wind speed. In practice, many possible choices of the covariate are available. In fact, in addition to its historical data, the wind speed is highly correlated to temperature, humidity and wind direction. In this paper a comparison, in terms of Mean Absolute Prediction Errors and Interquartile Range, between those choices will be provided to show which covariates are more suitable to forecast wind speed.

  10. Measurement of Phonated Intervals during Four Fluency-Inducing Conditions

    ERIC Educational Resources Information Center

    Davidow, Jason H.; Bothe, Anne K.; Andreatta, Richard D.; Ye, Jun

    2009-01-01

    Purpose: Previous investigations of persons who stutter have demonstrated changes in vocalization variables during fluency-inducing conditions (FICs). A series of studies has also shown that a reduction in short intervals of phonation, those from 30 to 200 ms, is associated with decreased stuttering. The purpose of this study, therefore, was to…

  11. Interval Prediction of Molecular Properties in Parametrized Quantum Chemistry

    NASA Astrophysics Data System (ADS)

    Edwards, David E.; Zubarev, Dmitry Yu.; Packard, Andrew; Lester, William A.; Frenklach, Michael

    2014-06-01

    The accurate evaluation of molecular properties lies at the core of predictive physical models. Most reliable quantum-chemical calculations are limited to smaller molecular systems while purely empirical approaches are limited in accuracy and reliability. A promising approach is to employ a quantum-mechanical formalism with simplifications and to compensate for the latter with parametrization. We propose a strategy of directly predicting the uncertainty interval for a property of interest, based on training-data uncertainties, which sidesteps the need for an optimum set of parameters.

  12. Bridging the interval: theory and neurobiology of trace conditioning.

    PubMed

    Raybuck, Jonathan D; Lattal, K Matthew

    2014-01-01

    An early finding in the behavioral analysis of learning was that conditioned responding weakens as the conditioned stimulus (CS) and unconditioned stimulus (US) are separated in time. This "trace" conditioning effect has been the focus of years of research in associative learning. Theoretical accounts of trace conditioning have focused on mechanisms that allow associative learning to occur across long intervals between the CS and US. These accounts have emphasized degraded contingency effects, timing mechanisms, and inhibitory learning. More recently, study of the neurobiology of trace conditioning has shown that even a short interval between the CS and US alters the circuitry recruited for learning. Here, we review some of the theoretical and neurobiological mechanisms underlying trace conditioning with an emphasis on recent studies of trace fear conditioning. Findings across many studies have implications not just for how we think about time and conditioning, but also for how we conceptualize fear conditioning in general, suggesting that circuitry beyond the usual suspects needs to be incorporated into current thinking about fear, learning, and anxiety. PMID:24036411

  13. Mapping of Estimations and Prediction Intervals Using Extreme Learning Machines

    NASA Astrophysics Data System (ADS)

    Leuenberger, Michael; Kanevski, Mikhail

    2015-04-01

    Due to the large amount and complexity of data available nowadays in environmental sciences, we face the need to apply more robust methodology allowing analyses and understanding of the phenomena under study. One particular but very important aspect of this understanding is the reliability of generated prediction models. From the data collection to the prediction map, several sources of error can occur and affect the final result. Theses sources are mainly identified as uncertainty in data (data noise), and uncertainty in the model. Their combination leads to the so-called prediction interval. Quantifying these two categories of uncertainty allows a finer understanding of phenomena under study and a better assessment of the prediction accuracy. The present research deals with a methodology combining a machine learning algorithm (ELM - Extreme Learning Machine) with a bootstrap-based procedure. Developed by G.-B. Huang et al. (2006), ELM is an artificial neural network following the structure of a multilayer perceptron (MLP) with one single hidden layer. Compared to classical MLP, ELM has the ability to learn faster without loss of accuracy, and need only one hyper-parameter to be fitted (that is the number of nodes in the hidden layer). The key steps of the proposed method are as following: sample from the original data a variety of subsets using bootstrapping; from these subsets, train and validate ELM models; and compute residuals. Then, the same procedure is performed a second time with only the squared training residuals. Finally, taking into account the two modeling levels allows developing the mean prediction map, the model uncertainty variance, and the data noise variance. The proposed approach is illustrated using geospatial data. References Efron B., and Tibshirani R. 1986, Bootstrap Methods for Standard Errors, Confidence Intervals, and Other Measures of Statistical accuracy, Statistical Science, vol. 1: 54-75. Huang G.-B., Zhu Q.-Y., and Siew C.-K. 2006

  14. Evaluation of prediction intervals for expressing uncertainties in groundwater flow model predictions

    USGS Publications Warehouse

    Christensen, S.; Cooley, R.L.

    1999-01-01

    We tested the accuracy of 95% individual prediction intervals for hydraulic heads, streamflow gains, and effective transmissivities computed by groundwater models of two Danish aquifers. To compute the intervals, we assumed that each predicted value can be written as the sum of a computed dependent variable and a random error. Testing was accomplished by using a cross-validation method and by using new field measurements of hydraulic heads and transmissivities that were not used to develop or calibrate the models. The tested null hypotheses are that the coverage probability of the prediction intervals is not significantly smaller than the assumed probability (95%) and that each tail probability is not significantly different from the assumed probability (2.5%). In all cases tested, these hypotheses were accepted at the 5% level of significance. We therefore conclude that for the groundwater models of two real aquifers the individual prediction intervals appear to be accurate.We tested the accuracy of 95% individual prediction intervals for hydraulic heads, streamflow gains, and effective transmissivities computed by groundwater models of two Danish aquifers. To compute the intervals, we assumed that each predicted value can be written as the sum of a computed dependent variable and a random error. Testing was accomplished by using a cross-validation method and by using new field measurements of hydraulic heads and transmissivities that were not used to develop or calibrate the models. The tested null hypotheses are that the coverage probability of the prediction intervals is not significantly smaller than the assumed probability (95%) and that each tail probability is not significantly different from the assumed probability (2.5%). In all cases tested, these hypotheses were accepted at the 5% level of significance. We therefore conclude that for the groundwater models of two real aquifers the individual prediction intervals appear to be accurate.

  15. Trial order and retention interval in human predictive judgment.

    PubMed

    Stout, Steven C; Amundson, Jeffrey C; Miller, Ralph R

    2005-12-01

    The influences of order of trial type and retention interval on human predictive judgments were assessed for a cue that was reinforced on half of its training presentations. Subjects observed 10 cue-outcome presentations (i.e., reinforced trials) and 10 cue-alone presentations (i.e., nonreinforced trials) in one of three different orders: all nonreinforced trials followed by all reinforced trials(latent inhibition), reinforced and nonreinforced trials interspersed (partial reinforcement), or al lreinforced trials followed by all nonreinforced trials (extinction). Ratings were based mainly on the most recent event type (i.e., a recency effect) when the test occurred immediately after training but were based mainly on initial event types (i.e., a primacy effect) when the test occurred after a 48-h delay. The subjects tested both immediately and with a long retention interval did not exhibit this shift to primacy (i.e., the recency effect persisted). These results demonstrate noncatastrophic forgetting and the flexible use of trial order information in predictive judgments.

  16. Eyelid response topography in differential interstimulus interval conditioning.

    PubMed

    Kadlac, J A; Grant, D A

    1977-05-01

    The problem of conditioned eyelid discrimination was investigated with a differential interstimulus interval (ISI) conditioning procedure. In two groups, conditioned stimulus (CS) lights presented in the left or right visual fields signaled ISIs of 800 or 1,200 msec before delivery of an airpuff unconditioned stimulus. Two additional groups received one or the other ISI with both CSs. Somewhat unexpectedly, none of the response-frequency or topography measures showed evidence of conditioned discrimination in the differential ISI groups. Instead, the latencies and puff-attenuating topographies of responses were much more appropriate to the ISI given on the preceding trial, n--1, than to the ISI cued on trial n. Neither the absence of conditioned discrimination nor the presence of ISI sequential effects was related to subjects' reported awareness of the CS-ISI contingencies, suggesting that the overriding process was a relatively "automatic" shaping and reshaping of responses in accord with recent ISI experience. These results are discussed in terms of the complex stimulus- and response-processing requirements of the task. Across all four groups there was some evidence of a relative excitatory response bias to CSs presented in the right visual field, and it was found that voluntary-form responders (but not conditioned-form responders) initially gave more alpha responses to the right-field CS than to the left-field CS. These results were examined for possible hemispheric processing implications. PMID:870612

  17. Two Efficient Twin ELM Methods With Prediction Interval.

    PubMed

    Ning, Kefeng; Liu, Min; Dong, Mingyu; Wu, Cheng; Wu, ZhanSong

    2015-09-01

    In the operational optimization and scheduling problems of actual industrial processes, such as iron and steel, and microelectronics, the operational indices and process parameters usually need to be predicted. However, for some input and output variables of these prediction models, there may exist a lot of uncertainties coming from themselves, the measurement error, the rough representation, and so on. In such cases, constructing a prediction interval (PI) for the output of the corresponding prediction model is very necessary. In this paper, two twin extreme learning machine (TELM) models for constructing PIs are proposed. First, we propose a regularized asymmetric least squares extreme learning machine (RALS-ELM) method, in which different weights of its squared error loss function are set according to whether the error of the model output is positive or negative in order that the above error can be differentiated in the parameter learning process, and Tikhonov regularization is introduced to reduce overfitting. Then, we propose an asymmetric Bayesian extreme learning machine (AB-ELM) method based on the Bayesian framework with the asymmetric Gaussian distribution (AB-ELM), in which the weights of its likelihood function are determined as the same method in RALS-ELM, and the type II maximum likelihood algorithm is derived to learn the parameters of AB-ELM. Based on RALS-ELM and AB-ELM, we use a pair of weights following the reciprocal relationship to obtain two nonparallel regressors, including a lower-bound regressor and an upper-bound regressor, respectively, which can be used for calculating the PIs. Finally, some discussions are given, about how to adjust the weights adaptively to meet the desired PI, how to use the proposed TELMs for nonlinear quantile regression, and so on. Results of numerical comparison on data from one synthetic regression problem, three University of California Irvine benchmark regression problems, and two actual industrial regression

  18. Fixed-interval behavior maintained by conditioned reinforcement.

    PubMed

    De Lorge, J

    1967-05-01

    The key-pecking of a pigeon was reinforced with grain on an 18-min second-order schedule. During the 18 min, a key peck which completed a 3-min fixed interval produced a stimulus of 0.5-sec duration. The first 3-min fixed interval completed after 18 min resulted in primary reinforcement. Behavior characteristic of fixed-interval schedules was produced on both the 3-min components and the 18-min schedule. This performance was shown to be enhanced whenever the 0.5-sec stimulus was also presented before the presentation of grain.

  19. One-Year Real-Time Operational Prediction Intervals for Direct Normal Irradiance

    NASA Astrophysics Data System (ADS)

    Chu, Y.; Carreira Pedro, H. T.; Coimbra, C. F.

    2015-12-01

    This work describes an algorithm to generate intra-hour prediction intervals (PIs) for the highly-variable direct normal irradiance, which is the energy source for the concentrated solar power technologies. The prediction intervals are generated using a Multi-layer Stochastic-Learning Model (MSLM), which is developed based on methods such as: sky imaging techniques, support vector machine and artificial neural network. The MSLM is trained using one year of co-located, high-quality irradiance and sky image recording in Folsom, California. In addition to being validated with historical data, the algorithm has been generating operational PI forecasts in real-time for that observatory since July 1st 2014. In the real-time scenario, without re-training or significant maintenance, the hybrid model consistently provides valid PI (PICP > 92%) and outperforms the reference persistence model (PICP ~ 85%) regardless of weather condition. This work has great impact in the field of solar energy to potentially facilitate the level of solar penetration in the grid with significantly reduced integration costs.

  20. Constructing prediction interval for artificial neural network rainfall runoff models based on ensemble simulations

    NASA Astrophysics Data System (ADS)

    Kasiviswanathan, K. S.; Cibin, R.; Sudheer, K. P.; Chaubey, I.

    2013-08-01

    This paper presents a method of constructing prediction interval for artificial neural network (ANN) rainfall runoff models during calibration with a consideration of generating ensemble predictions. A two stage optimization procedure is envisaged in this study for construction of prediction interval for the ANN output. In Stage 1, ANN model is trained with genetic algorithm (GA) to obtain optimal set of weights and biases vector. In Stage 2, possible variability of ANN parameters (obtained in Stage 1) is optimized so as to create an ensemble of models with the consideration of minimum residual variance for the ensemble mean, while ensuring a maximum of the measured data to fall within the estimated prediction interval. The width of the prediction interval is also minimized simultaneously. The method is demonstrated using a real world case study of rainfall runoff data for an Indian basin. The method was able to produce ensembles with a prediction interval (average width) of 26.49 m3/s with 97.17% of the total observed data points lying within the interval in validation. One specific advantage of the method is that when ensemble mean value is considered as a forecast, the peak flows are predicted with improved accuracy by this method compared to traditional single point forecasted ANNs.

  1. CALCULATION OF NONLINEAR CONFIDENCE AND PREDICTION INTERVALS FOR GROUND-WATER FLOW MODELS.

    USGS Publications Warehouse

    Cooley, Richard L.; Vecchia, Aldo V.

    1987-01-01

    A method is derived to efficiently compute nonlinear confidence and prediction intervals on any function of parameters derived as output from a mathematical model of a physical system. The method is applied to the problem of obtaining confidence and prediction intervals for manually-calibrated ground-water flow models. To obtain confidence and prediction intervals resulting from uncertainties in parameters, the calibrated model and information on extreme ranges and ordering of the model parameters within one or more independent groups are required. If random errors in the dependent variable are present in addition to uncertainties in parameters, then calculation of prediction intervals also requires information on the extreme range of error expected. A simple Monte Carlo method is used to compute the quantiles necessary to establish probability levels for the confidence and prediction intervals. Application of the method to a hypothetical example showed that inclusion of random errors in the dependent variable in addition to uncertainties in parameters can considerably widen the prediction intervals.

  2. Intertrial intervals and contextual conditioning in appetitive pavlovian learning: effects over the ABA renewal paradigm.

    PubMed

    Carranza-Jasso, Rodrigo; Urcelay, Gonzalo P; Nieto, Javier; Sánchez-Carrasco, Livia

    2014-09-01

    Three experiments using rats in an appetitive conditioning procedure analyzed the effect of short and long (50s vs. 1440s) intertrial intervals (ITI) over the acquisition of conditioned stimulus (CS), context (Ctxt), and unconditioned stimulus (US) associations, as well as the effect on the extinction and renewal of the conditioned response to the CS. Experiment 1 revealed more contextual conditioned responses in groups trained with the short ITIs, however the renewal effect was not observed during test phase with either ITI condition. When subjects were pre-exposed to the contexts before the acquisition phase (Experiment 2) renewal of the conditioned response (CR) was only observed in long ITI group. However, when the acquisition context was extinguished (Experiment 3) the renewal effect observed in the Experiment 2 was weakened. In all three experiments subjects showed a similar number of responses to the tone predicting food, however they showed a clear contextual conditioning effect only for the groups trained with short ITIs. It is noteworthy that the acquisition context showed high levels of the CR in the renewal test only for groups trained with short ITIs (Experiment 2) but these responses were absent if additional contextual extinction was imposed before such test (Experiment 3). In general, all groups showed similar acquisition curves for the CS but only Short groups had an increase in the CR during the pre-CS. Also, context conditioning does not interfere with the conditioning of the CS and context pre-exposure prior to acquisition is essential in order to observe the renewal effect when long ITIs are used.

  3. Prediction Interval Development for Wind-Tunnel Balance Check-Loading

    NASA Technical Reports Server (NTRS)

    Landman, Drew; Toro, Kenneth G.; Commo, Sean A.; Lynn, Keith C.

    2014-01-01

    Results from the Facility Analysis Verification and Operational Reliability project revealed a critical gap in capability in ground-based aeronautics research applications. Without a standardized process for check-loading the wind-tunnel balance or the model system, the quality of the aerodynamic force data collected varied significantly between facilities. A prediction interval is required in order to confirm a check-loading. The prediction interval provides an expected upper and lower bound on balance load prediction at a given confidence level. A method has been developed which accounts for sources of variability due to calibration and check-load application. The prediction interval method of calculation and a case study demonstrating its use is provided. Validation of the methods is demonstrated for the case study based on the probability of capture of confirmation points.

  4. Statistical prediction intervals for the evaluation of ground-water quality

    SciTech Connect

    Gibbons, R.D.

    1987-07-01

    Factors for a normal distribution are given such that one may be 99% confident that the two-sided prediction interval chi-bar +- rs or the one-sided prediction several chi-bar + rs will contain all of the kappa future values, where chi-bar and s are the sample means and standard deviation obtained from n previous values. In the context of ground-water monitoring, the future samples may represent new monitoring values at each of kappa downgradient wells, and the n previous values might be the historical monitoring results for one or more upgradient wells. The Tables provided in this paper allow the computation of one-sided and two-sided 99% prediction intervals for previous sample sizes of n = 4 to 100 and future samples of kappa = 1 to 100. Modification of these intervals for log-normally distributed data is also presented.

  5. Prediction intervals for a noisy nonlinear time series based on a bootstrapping reservoir computing network ensemble.

    PubMed

    Sheng, Chunyang; Zhao, Jun; Wang, Wei; Leung, Henry

    2013-07-01

    Prediction intervals that provide estimated values as well as the corresponding reliability are applied to nonlinear time series forecast. However, constructing reliable prediction intervals for noisy time series is still a challenge. In this paper, a bootstrapping reservoir computing network ensemble (BRCNE) is proposed and a simultaneous training method based on Bayesian linear regression is developed. In addition, the structural parameters of the BRCNE, that is, the number of reservoir computing networks and the reservoir dimension, are determined off-line by the 0.632 bootstrap cross-validation. To verify the effectiveness of the proposed method, two kinds of time series data, including the multisuperimposed oscillator problem with additive noises and a practical gas flow in steel industry are employed here. The experimental results indicate that the proposed approach has a satisfactory performance on prediction intervals for practical applications.

  6. Predicted Interval Plots (PIPS): A Graphical Tool for Data Monitoring of Clinical Trials

    PubMed Central

    Li, Lingling; Evans, Scott R.; Uno, Hajime; Wei, L.J.

    2011-01-01

    Group sequential designs are often used in clinical trials to evaluate efficacy and/or futility. Many methods have been developed for different types of endpoints and scenarios. However, few of these methods convey information regarding effect sizes (e.g., treatment differences) and none uses prediction to convey information regarding potential effect size estimates and associated precision, with trial continuation. To address these limitations, Evans et al. (2007) proposed to use prediction and predicted intervals as a flexible and practical tool for quantitative monitoring of clinical trials. In this article, we reaffirm the importance and usefulness of this innovative approach and introduce a graphical summary, predicted interval plots (PIPS), to display the information obtained in the prediction process in a straightforward yet comprehensive manner. We outline the construction of PIPS and apply this method in two examples. The results and the interpretations of the PIPS are discussed. PMID:21423789

  7. On the Effective Construction of Compactly Supported Wavelets Satisfying Homogenous Boundary Conditions on the Interval

    NASA Technical Reports Server (NTRS)

    Chiavassa, G.; Liandrat, J.

    1996-01-01

    We construct compactly supported wavelet bases satisfying homogeneous boundary conditions on the interval (0,1). The maximum features of multiresolution analysis on the line are retained, including polynomial approximation and tree algorithms. The case of H(sub 0)(sup 1)(0, 1)is detailed, and numerical values, required for the implementation, are provided for the Neumann and Dirichlet boundary conditions.

  8. Classical Conditioning and Retention of the Infant's Eyelid Response: Effects of Age and Interstimulus Interval.

    ERIC Educational Resources Information Center

    Little, Arlene H.; And Others

    1984-01-01

    Reports that lengthy interstimulus interval facilitates classical conditioning in very young infants. Infants trained in a single session at 20 days of age exhibited reliable retention of the conditioned eyelid reflex 10 days later, but infants 10 days of age did not. (Author)

  9. The effect of US signalling and the US–CS interval on backward conditioning in mice

    PubMed Central

    Sanderson, David J.; Cuell, Steven F.; Bannerman, David M.

    2014-01-01

    The effect of US signalling and the US–CS interval in backward conditioning was assessed in mice. For one group of mice the presentation of food was signalled by a tone and for another group, food was unsignalled. For half of the mice, within each group, the presentation of food preceded a visual cue by 10 s. For the other half, food was presented at the start of the visual cue (0-s US–CS interval), resulting in simultaneous pairings of these events. A summation test and a subsequent retardation test were used to assess the inhibitory effects of backward conditioning in comparison to training with a non-reinforced visual cue that controlled for the possible effects of latent inhibition and conditioned inhibition caused as a consequence of differential conditioning. In the summation test unsignalled presentations of the US resulted in inhibition when the US–CS interval was 10 s, but not 0 s. Signalled presentations of the US resulted in inhibition, independent of the US–CS interval. In the retardation test, independent of US signalling, a US–CS interval of 10 s failed to result in inhibition, but an interval of 0 s resulted in greater conditioned responding to the backward CS than the control CS. A generalisation decrement account of the effect of signalling the US with a 0-s US–CS interval, which resulted in reduced responding in the summation test and faster acquisition in the retardation test, is discussed. PMID:25512678

  10. Prediction Interval: What to Expect When You're Expecting … A Replication.

    PubMed

    Spence, Jeffrey R; Stanley, David J

    2016-01-01

    A challenge when interpreting replications is determining whether the results of a replication "successfully" replicate the original study. Looking for consistency between two studies is challenging because individual studies are susceptible to many sources of error that can cause study results to deviate from each other and the population effect in unpredictable directions and magnitudes. In the current paper, we derive methods to compute a prediction interval, a range of results that can be expected in a replication due to chance (i.e., sampling error), for means and commonly used indexes of effect size: correlations and d-values. The prediction interval is calculable based on objective study characteristics (i.e., effect size of the original study and sample sizes of the original study and planned replication) even when sample sizes across studies are unequal. The prediction interval provides an a priori method for assessing if the difference between an original and replication result is consistent with what can be expected due to sample error alone. We provide open-source software tools that allow researchers, reviewers, replicators, and editors to easily calculate prediction intervals.

  11. Prediction Interval: What to Expect When You’re Expecting … A Replication

    PubMed Central

    2016-01-01

    A challenge when interpreting replications is determining whether the results of a replication “successfully” replicate the original study. Looking for consistency between two studies is challenging because individual studies are susceptible to many sources of error that can cause study results to deviate from each other and the population effect in unpredictable directions and magnitudes. In the current paper, we derive methods to compute a prediction interval, a range of results that can be expected in a replication due to chance (i.e., sampling error), for means and commonly used indexes of effect size: correlations and d-values. The prediction interval is calculable based on objective study characteristics (i.e., effect size of the original study and sample sizes of the original study and planned replication) even when sample sizes across studies are unequal. The prediction interval provides an a priori method for assessing if the difference between an original and replication result is consistent with what can be expected due to sample error alone. We provide open-source software tools that allow researchers, reviewers, replicators, and editors to easily calculate prediction intervals. PMID:27644090

  12. Prediction Interval: What to Expect When You're Expecting … A Replication.

    PubMed

    Spence, Jeffrey R; Stanley, David J

    2016-01-01

    A challenge when interpreting replications is determining whether the results of a replication "successfully" replicate the original study. Looking for consistency between two studies is challenging because individual studies are susceptible to many sources of error that can cause study results to deviate from each other and the population effect in unpredictable directions and magnitudes. In the current paper, we derive methods to compute a prediction interval, a range of results that can be expected in a replication due to chance (i.e., sampling error), for means and commonly used indexes of effect size: correlations and d-values. The prediction interval is calculable based on objective study characteristics (i.e., effect size of the original study and sample sizes of the original study and planned replication) even when sample sizes across studies are unequal. The prediction interval provides an a priori method for assessing if the difference between an original and replication result is consistent with what can be expected due to sample error alone. We provide open-source software tools that allow researchers, reviewers, replicators, and editors to easily calculate prediction intervals. PMID:27644090

  13. Prediction interval evaluation in modelling of soil texture for regional mapping: methodology and a case study

    NASA Astrophysics Data System (ADS)

    Ciampalini, Rossano; Martin, Manuel; Saby, Nicolas P. A.; Richer de Forges, Anne C.; Nehlig, Pierre; Martelet, Guillaume; Arrouays, Dominique

    2015-04-01

    Model uncertainty mapping represents a practical way to describe efficiency and limits of models prediction and can be calculated using different techniques. The object of this study is to determine and apply a procedure for the prediction interval (PI) evaluation for extended maps of soil granulometric fractions (i.e. clay, silt, sand) in the region "Centre" of France. Among the various methodologies for PI determination, a recent approach is the use of a non-parametric procedure evaluating the prediction interval. The PI is defined as a conventional bound of the predicted values (i.e. 95th percentile) and can be calculated as follows. Assuming a relationship between the inputs of the model and the resulting prediction error (Shrestha et al., 2006, Malone et al., 2011), the input variables-space is classified into different clusters having similar errors with a fuzzy c-means clustering technique. Then, a prediction interval (PI) is calculated for each cluster on the basis of the associated empirical distributions of the errors and considering the degree of membership belonging to each cluster. A relationship between the input variables and the computed prediction intervals is founded using a modelling procedure (calibration), then; the relationship is applied to estimate the prediction interval for the out-of-sample data (validation) (e.g. Solomatine et al., 2008, 2009, Malone et al., 2011). This approach requires the assumption of a relationships between the input variables and the errors, and, obviously the relevancy and accuracy of such approach depends on the validity of the assumption. These assumptions have been accepted in all the studies quoted above. In this work we adopted a similar procedure to the third approach. Our hypothesis is, if a correspondence is supposed and identified between confidence interval and predictors (i.e., 2.5-97.5% values, respectively), a model between predictors and PI may be used to extrapolate it to the whole map. This

  14. Human serotonin transporter availability predicts fear conditioning.

    PubMed

    Åhs, Fredrik; Frick, Andreas; Furmark, Tomas; Fredrikson, Mats

    2015-12-01

    Serotonin facilitates fear learning in animals. We therefore predicted that individual differences in the capacity to regulate serotonergic transmission in the human neural fear circuit would be inversely related to fear conditioning. The capacity to regulate serotonergic transmission was indexed by serotonin transporter availability measured with [(11)C]-DASB positron emission tomography. Results indicate that lower serotonin transporter availability in the amygdala, insula and dorsal anterior cingulate cortex predicts enhanced conditioned autonomic fear responses. Our finding supports serotonergic modulation of fear conditioning in humans and may aid in understanding susceptibility for developing anxiety conditions such as post-traumatic stress disorder. PMID:25498766

  15. Human serotonin transporter availability predicts fear conditioning.

    PubMed

    Åhs, Fredrik; Frick, Andreas; Furmark, Tomas; Fredrikson, Mats

    2015-12-01

    Serotonin facilitates fear learning in animals. We therefore predicted that individual differences in the capacity to regulate serotonergic transmission in the human neural fear circuit would be inversely related to fear conditioning. The capacity to regulate serotonergic transmission was indexed by serotonin transporter availability measured with [(11)C]-DASB positron emission tomography. Results indicate that lower serotonin transporter availability in the amygdala, insula and dorsal anterior cingulate cortex predicts enhanced conditioned autonomic fear responses. Our finding supports serotonergic modulation of fear conditioning in humans and may aid in understanding susceptibility for developing anxiety conditions such as post-traumatic stress disorder.

  16. Multilevel, discrete, point-interval data can predict bioattenuation`s potential

    SciTech Connect

    Kabis, T.W.

    1996-05-01

    Closely spaced, discrete-interval groundwater sampling is critical for monitoring aqueous-phase contaminants at hazardous waste sites. Data obtained from discrete-interval sampling devices accurately represent horizontal and vertical extants of contaminant plumes. Discrete point-interval groundwater sampling has been tested in various applications, including natural- and forced-gradient tracer tests plume delineation, and in identifying discrete zones of microbial activity and vertical chemical gradients within an aquifer. An increasingly popular strategy is to avoid active remediation in favor of natural, in-situ attenuation processes. Evaluation of natural attenuation, particularly in-situ bioremediation resulting from multiple terminal electron acceptors, requires site-specific data. Here, multilevel, discrete, point-interval groundwater sampling data is critical. Because groundwater samples from standard monitoring wells often are derived from large vertical sampling zones, the resulting data presents a smeared picture of chemical-microbial conditions; moreover, the potential for natural in-situ bioattenuation can be under- or overestimated without multilevel, discrete, point-interval data. Discrete, point-interval samplers provide a sound basis for evaluating remediation options. One potential obstacle has been the lack of a multipurpose, cost-effective sampler that is operational under a variety of field conditions.

  17. Can different conditioning activities and rest intervals affect the acute performance of taekwondo turning kick?

    PubMed

    Santos, Jonatas F da Silva; Valenzuela, Tomás H; Franchini, Emerson

    2015-06-01

    This study compared the acute effect of strength, plyometric, and complex exercises (combined strength and plyometric exercise) in the countermovement jump (CMJ) and frequency speed of kick test (FSKT) and attempted to establish the best rest interval to maximize performance in the CMJ, number of kicks, and impact generated during FSKT. Eleven taekwondo athletes (mean ± SD; age: 20.3 ± 5.2 years; body mass: 71.8 ± 15.3 kg; height: 177 ± 7.2 cm) participated. One control and 9 experimental conditions were randomly applied. Each condition was composed of warm-up, conditioning activity (half-squat: 3 × 1 at 95% 1RM; jumps: 3 × 10 vertical jumps above 40-cm barrier; or complex exercise: half-squat 3 × 2 at 95% 1RM + 4 vertical jumps above 40-cm barrier), followed by different rest intervals (5-, 10-minute, and self-selected) before CMJ and FSKT. The conditions were compared using an analysis of variance with repeated measures, followed by Bonferroni's post hoc test. The alpha level was set at 5%. Significant difference was found in the number of kicks (F9,90 = 1.32; p = 0.239; and η2 = 0.116 [small]). The complex method with a 10-minute rest interval (23 ± 5 repetitions) was superior (p = 0.026) to the control (19 ± 3 repetitions), maximum strength with a self-selected rest interval (328 ± 139 seconds; 18 ± 2 repetitions) (p = 0.015), and plyometric with a 5-minute rest interval (18 ± 3 repetitions) (p < 0.001). Our results indicate that taekwondo athletes increased the number of kicks in a specific test by using the complex method when 10-minute rest interval was used.

  18. Can different conditioning activities and rest intervals affect the acute performance of taekwondo turning kick?

    PubMed

    Santos, Jonatas F da Silva; Valenzuela, Tomás H; Franchini, Emerson

    2015-06-01

    This study compared the acute effect of strength, plyometric, and complex exercises (combined strength and plyometric exercise) in the countermovement jump (CMJ) and frequency speed of kick test (FSKT) and attempted to establish the best rest interval to maximize performance in the CMJ, number of kicks, and impact generated during FSKT. Eleven taekwondo athletes (mean ± SD; age: 20.3 ± 5.2 years; body mass: 71.8 ± 15.3 kg; height: 177 ± 7.2 cm) participated. One control and 9 experimental conditions were randomly applied. Each condition was composed of warm-up, conditioning activity (half-squat: 3 × 1 at 95% 1RM; jumps: 3 × 10 vertical jumps above 40-cm barrier; or complex exercise: half-squat 3 × 2 at 95% 1RM + 4 vertical jumps above 40-cm barrier), followed by different rest intervals (5-, 10-minute, and self-selected) before CMJ and FSKT. The conditions were compared using an analysis of variance with repeated measures, followed by Bonferroni's post hoc test. The alpha level was set at 5%. Significant difference was found in the number of kicks (F9,90 = 1.32; p = 0.239; and η2 = 0.116 [small]). The complex method with a 10-minute rest interval (23 ± 5 repetitions) was superior (p = 0.026) to the control (19 ± 3 repetitions), maximum strength with a self-selected rest interval (328 ± 139 seconds; 18 ± 2 repetitions) (p = 0.015), and plyometric with a 5-minute rest interval (18 ± 3 repetitions) (p < 0.001). Our results indicate that taekwondo athletes increased the number of kicks in a specific test by using the complex method when 10-minute rest interval was used. PMID:26010798

  19. Prediction of genetic contributions and generation intervals in populations with overlapping generations under selection.

    PubMed Central

    Bijma, P; Woolliams, J A

    1999-01-01

    A method to predict long-term genetic contributions of ancestors to future generations is studied in detail for a population with overlapping generations under mass or sib index selection. An existing method provides insight into the mechanisms determining the flow of genes through selected populations, and takes account of selection by modeling the long-term genetic contribution as a linear regression on breeding value. Total genetic contributions of age classes are modeled using a modified gene flow approach and long-term predictions are obtained assuming equilibrium genetic parameters. Generation interval was defined as the time in which genetic contributions sum to unity, which is equal to the turnover time of genes. Accurate predictions of long-term genetic contributions of individual animals, as well as total contributions of age classes were obtained. Due to selection, offspring of young parents had an above-average breeding value. Long-term genetic contributions of youngest age classes were therefore higher than expected from the age class distribution of parents, and generation interval was shorter than the average age of parents at birth of their offspring. Due to an increased selective advantage of offspring of young parents, generation interval decreased with increasing heritability and selection intensity. The method was compared to conventional gene flow and showed more accurate predictions of long-term genetic contributions. PMID:10049935

  20. Fast time-series prediction using high-dimensional data: Evaluating confidence interval credibility

    NASA Astrophysics Data System (ADS)

    Hirata, Yoshito

    2014-05-01

    I propose an index for evaluating the credibility of confidence intervals for future observables predicted from high-dimensional time-series data. The index evaluates the distance from the current state to the data manifold. I demonstrate the index with artificial datasets generated from the Lorenz'96 II model [Lorenz, in Proceedings of the Seminar on Predictability, Vol. 1 (ECMWF, Reading, UK, 1996), p. 1], the Lorenz'96 I model [Hansen and Smith, J. Atmos. Sci. 57, 2859 (2000), 10.1175/1520-0469(2000)057<2859:TROOCI>2.0.CO;2], and the coupled map lattice, and a real dataset for the solar irradiation around Japan.

  1. Conditional sampling schemes based on the Variable Interval Time Averaging (VITA) algorithm

    NASA Astrophysics Data System (ADS)

    Morrison, J. F.; Tsai, H. M.; Bradshaw, P.

    1986-08-01

    The variable interval time averaging (VITA) algorithm was tested in a variety of boundary layers for its ability to detect motions principally involved in the production of shear stress. A VITA+LEVEL scheme (which uses a variance and level criterion) was devised and is shown to produce length scale statistics that are independent of the conditioning criteria, where those from the VITA scheme are not.

  2. Pavlovian conditioning of morphine hyperthermia: assessment of interstimulus interval and CS-US overlap.

    PubMed

    Broadbent, J; Cunningham, C L

    1996-07-01

    The present study examined the effect of interstimulus interval on acquisition of conditioned thermal responses produced by trials in which a light/noise stimulus (CS) was repeatedly paired with infusion of morphine sulphate (US). Rats were implanted with a chronic intravenous catheter for drug delivery and a biotelemetry device for remote monitoring of core body temperature. In experiment 1, different groups received morphine either 0.5 (group P0.5) or 15 min (group P15) after onset of the 15-min CS. A third group was exposed to an identical number of CS and US presentations but in an explicitly unpaired manner (group UP). After repeated exposure to morphine, all groups showed a more rapid rise in body temperature in response to drug infusion. Test presentations of CS alone revealed conditioned hyperthermic responses to CS in groups P0.5 and P15. However, the response of the P15 group was smaller than that of the P0.5 group, suggesting weaker conditioning at the longer interstimulus interval. The contribution of CS-US overlap to the diminished associative strength observed in the P15 group was assessed in experiment 2. Groups P0.5/15 and P0.5/30 received infusions of morphine 0.5 min after onset of a 15- or 30-min CS, respectively. Group P15/30 received morphine 15 min after onset of a 30 min CS, whereas group UP/30 received explicitly unpaired presentations of the US and a 30-min CS. Enhancement of the hyperthermic effect of morphine was observed in all groups after ten conditioning trials. Test presentations of the CS without drug revealed that all paired groups had acquired conditioned hyperthermic responses. These results support the conclusion that drug-induced conditioning can occur at relatively long interstimulus intervals when there is sufficient temporal overlap between the CS and unconditioned response evoked by the drug US.

  3. Heart Rate-Corrected QT Interval Helps Predict Mortality after Intentional Organophosphate Poisoning

    PubMed Central

    Liu, Shou-Hsuan; Lin, Ja-Liang; Weng, Cheng-Hao; Yang, Huang-Yu; Hsu, Ching-Wei; Chen, Kuan-Hsing; Huang, Wen-Hung; Yen, Tzung-Hai

    2012-01-01

    with prolonged QTc intervals than among those with normal QTc intervals (Log-rank test, Chi-square test = 20.36, P<0.001). Conclusions QTc interval helps predict mortality after intentional organophosphate poisoning. PMID:22574184

  4. Competition between novelty and cocaine conditioned reward is sensitive to drug dose and retention interval

    PubMed Central

    Reichel, Carmela M.; Bevins, Rick A.

    2010-01-01

    The following manuscript is the final accepted manuscript. It has not been subjected to the final copyediting, fact-checking, and proofreading required for formal publication. It is not the definitive, publisher-authenticated version. The American Psychological Association and its Council of Editors disclaim any responsibility or liabilities for errors or omissions of this manuscript version, any version derived from this manuscript by NIH, or other third parties. The published version is available at www.apa.org/pubs/journals/bne The conditioned rewarding effects of novelty compete with those of cocaine for control over choice behavior using a place-conditioning task. The purpose of the present study was to use multiple doses of cocaine to determine the extent of this competition and to determine whether novelty's impact on cocaine reward was maintained over an abstinence period. In Experiment 1, rats were conditioned with cocaine (7.5, 20, or 30 mg/kg, IP) to prefer one side of an unbiased place conditioning apparatus relative to the other. In a subsequent phase, all rats received alternating daily confinements to the previously cocaine-paired and unpaired sides of the apparatus. During this phase, half the rats had access to a novel object on their initially unpaired side; the remaining rats did not receive objects. The ability of novelty to compete with cocaine in a drug-free and cocaine-challenge test was sensitive to cocaine dose. In Experiment 2, a place preference was established with 10 mg/kg cocaine and testing occurred after 1, 14, or 28 day retention intervals. Findings indicate that choice behaviors mediated by cocaine conditioning are reduced with the passing of time. Taken together, competition between cocaine and novelty conditioned rewards are sensitive to drug dose and retention interval. PMID:20141289

  5. Estimation of confidence intervals of global horizontal irradiance obtained from a weather prediction model

    NASA Astrophysics Data System (ADS)

    Ohtake, Hideaki; Gari da Silva Fonseca, Joao, Jr.; Takashima, Takumi; Oozeki, Takashi; Yamada, Yoshinori

    2014-05-01

    Many photovoltaic (PV) systems have been installed in Japan after the introduction of the Feed-in-Tariff. For an energy management of electric power systems included many PV systems, the forecast of the PV power production are useful technology. Recently numerical weather predictions have been applied to forecast the PV power production while the forecasted values invariably have forecast errors for each modeling system. So, we must use the forecast data considering its error. In this study, we attempted to estimate confidence intervals for hourly forecasts of global horizontal irradiance (GHI) values obtained from a mesoscale model (MSM) de-veloped by the Japan Meteorological Agency. In the recent study, we found that the forecasted values of the GHI of the MSM have two systematical forecast errors; the first is that forecast values of the GHI are depended on the clearness indices, which are defined as the GHI values divided by the extraterrestrial solar irradiance. The second is that forecast errors have the seasonal variations; the overestimation of the GHI forecasts is found in winter while the underestimation of those is found in summer. The information of the errors of the hourly GHI forecasts, that is, confidence intervals of the forecasts, is of great significance for planning the energy management included a lot of PV systems by an electric company. On the PV systems, confidence intervals of the GHI forecasts are required for a pinpoint area or for a relatively large area control-ling the power system. For the relatively large area, a spatial-smoothing method of the GHI values is performed for both the observations and forecasts. The spatial-smoothing method caused the decline of confidence intervals of the hourly GHI forecasts on an extreme event of the GHI forecast (a case of large forecast error) over the relatively large area of the Tokyo electric company (approximately 68 % than for a pinpoint forecast). For more credible estimation of the confidence

  6. Prediction of temperature conditions at great depths

    SciTech Connect

    Lyubimova, Y.A.

    1981-02-01

    The effects of temperature and pressure on the heat conductivity of dry, and water- and oil-saturated rocks, which form the upper part of the Earth's crust were examined: carbonates, sulfates, clastic rocks (siltstones), and also granites and andesite-basalts. Using the data on the intensity of heat flow and changes in the heat-conductivity of rocks, as exemplified by the Front Ranges of Eastern Ciscaucasia, the predicted temperatures through the sequence of oil fields were calculated and a sketch map of the distribution of temperatures along the top of the Jurassic subsalt deposits was constructed. It has been established that neglect of the temperature and pressure effects on the heat-conductivity of rocks will lead to distortion of the heat-flow assessment, and for the conditions under discussion, its over-estimate is 20 to 25%. When determining the intensity of heat flow, distortion factors, such as surface, hydrogeologic, and sedimentation conditions, were accounted for. (JMT)

  7. Functional plasticity in the interposito-thalamo-cortical pathway during conditioning. Role of the interstimulus interval.

    PubMed

    Pananceau, M; Rispal-Padel, L

    2000-06-01

    In classic conditioning, the interstimulus interval (ISI) between the conditioned (CS) and unconditioned (US) stimulus is a critical parameter. The aim of the present experiment was to assess whether, during conditioning, modification of the CS-US interval could reliably produce changes in the functional properties of the interposito-thalamo-cortical pathways (INTCps). Five cats were prepared for chronic stimulation and recording from several brain regions along this pathway in awake animals. The CS was a weak electric shock applied on the interposed nucleus of the cerebellum in sites that initially elicited forelimb flexion (i.e., alpha motor responses) in three cats, and equal proportions of flexor and extensor responses in two cats. The US was an electric shock applied on the skin that elicited forelimb flexions. The motor and neurobiological effects of synchronous CS-US were compared with pairings in which the CS was applied 100 ms before US. Simultaneous and sequential application of CS and US produced different behavioral outcomes and resulted in different neural processes in the interposito-thalamo-cortical pathways (INTCps). The simultaneous presentation of stimuli only produced a small increase in excitability spreading to all the body representational zones of the primary motor cortex and a weak increase in the amplitude of the alpha motor response. In contrast, the sequential application led to a profound modification of the interposed output to neurons in the forelimb representation of the motor cortex. These robust neuronal correlates of conditioning were accompanied by a large facilitation of the alpha motor response (alpha-MR). There were also changes in the direction of misdirected alpha responses and an emergence of functionally appropriate, long-latency withdrawal forelimb flexion. These data revealed that, during conditioning, plastic changes within the thalamocortical connections are selectively induced by sequential information from central and

  8. Predicting biological condition in southern California streams

    USGS Publications Warehouse

    Brown, Larry R.; May, Jason T.; Rehn, Andrew C.; Ode, Peter R.; Waite, Ian R.; Kennen, Jonathan G.

    2012-01-01

    As understanding of the complex relations among environmental stressors and biological responses improves, a logical next step is predictive modeling of biological condition at unsampled sites. We developed a boosted regression tree (BRT) model of biological condition, as measured by a benthic macroinvertebrate index of biotic integrity (BIBI), for streams in urbanized Southern Coastal California. We also developed a multiple linear regression (MLR) model as a benchmark for comparison with the BRT model. The BRT model explained 66% of the variance in B-IBI, identifying watershed population density and combined percentage agricultural and urban land cover in the riparian buffer as the most important predictors of B-IBI, but with watershed mean precipitation and watershed density of manmade channels also important. The MLR model explained 48% of the variance in B-IBI and included watershed population density and combined percentage agricultural and urban land cover in the riparian buffer. For a verification data set, the BRT model correctly classified 75% of impaired sites (B-IBI < 40) and 78% of unimpaired sites (B-IBI = 40). For the same verification data set, the MLR model correctly classified 69% of impaired sites and 87% of unimpaired sites. The BRT model should not be used to predict B-IBI for specific sites; however, the model can be useful for general applications such as identifying and prioritizing regions for monitoring, remediation or preservation, stratifying new bioassessments according to anticipated biological condition, or assessing the potential for change in stream biological condition based on anticipated changes in population density and development in stream buffers.

  9. Predicting watershed acidification under alternate rainfall conditions

    USGS Publications Warehouse

    Huntington, T.G.

    1996-01-01

    The effect of alternate rainfall scenarios on acidification of a forested watershed subjected to chronic acidic deposition was assessed using the model of acidification of groundwater in catchments (MAGIC). The model was calibrated at the Panola Mountain Research Watershed, near Atlanta, Georgia, U.S.A. using measured soil properties, wet and dry deposition, and modeled hydrologic routing. Model forecast simulations were evaluated to compare alternate temporal averaging of rainfall inputs and variations in rainfall amount and seasonal distribution. Soil water alkalinity was predicted to decrease to substantially lower concentrations under lower rainfall compared with current or higher rainfall conditions. Soil water alkalinity was also predicted to decrease to lower levels when the majority of rainfall occurred during the growing season compared with other rainfall distributions. Changes in rainfall distribution that result in decreases in net soil water flux will temporarily delay acidification. Ultimately, however, decreased soil water flux will result in larger increases in soil- adsorbed sulfur and soil-water sulfate concentrations and decreases in alkalinity when compared to higher water flux conditions. Potential climate change resulting in significant changes in rainfall amounts, seasonal distribution of rainfall, or evapotranspiration will change net soil water flux and, consequently, will affect the dynamics of the acidification response to continued sulfate loading.

  10. Prolonged QT interval at onset of acute myocardial infarction in predicting early phase ventricular tachycardia

    SciTech Connect

    Taylor, G.J.; Crampton, R.S.; Gibson, R.S.; Stebbins, P.T.; Waldman, M.T.; Beller, G.A.

    1981-07-01

    The prospectively assessed time course of changes in ventricular repolarization during acute myocardial infarction (AMI) is reported in 32 patients admitted 2.0 +/- 1.8 (SD) hours after AMI onset. The initial corrected QT interval (QTc) upon hospitalization was longer in the 14 patients developing ventricular tachycardia (VT) within the first 48 hours as compared to QTc in the eight patients with frequent ventricular premature beats (VPBs) and to QTc in the 10 patients with infrequent VPBs. By the fifth day after AMI onset, the QTc shortened significantly only in the VT group, suggesting a greater initial abnormality of repolarization in these patients. All 32 patients had coronary angiography, radionuclide ventriculography, and myocardial perfusion scintigraphy before hospital discharge. Significant discriminating factors related to early phase VT in AMI included initially longer QT and QTc intervals, faster heart rate, higher peak serum levels of creatine kinase, acute anterior infarction, angiographically documented proximal stenosis of the left anterior descending coronary artery, and scintigraphic evidence of hypoperfusion of the interventricular septum. Prior infarction, angina pectoris, hypertension, multivessel coronary artery disease, and depressed left ventricular ejection fraction did not provide discrimination among the three different ventricular arrhythmia AMI groups. Researchers conclude that (1) the QT interval is frequently prolonged early in AMI, (2) the initial transiently prolonged ventricular repolarization facilitates and predicts complex ventricular tachyarrhythmias within the first 48 hours of AMI, (3) jeopardized blood supply to the interventricular septum frequently coexists, and (4) therapeutic enhancement of rapid recovery of the ventricular repolarization process merits investigation for prevention of VT in AMI.

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

    PubMed

    Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

    2015-09-01

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

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

    PubMed

    Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

    2015-09-01

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

  13. Constructing Optimal Prediction Intervals by Using Neural Networks and Bootstrap Method.

    PubMed

    Khosravi, Abbas; Nahavandi, Saeid; Srinivasan, Dipti; Khosravi, Rihanna

    2015-08-01

    This brief proposes an efficient technique for the construction of optimized prediction intervals (PIs) by using the bootstrap technique. The method employs an innovative PI-based cost function in the training of neural networks (NNs) used for estimation of the target variance in the bootstrap method. An optimization algorithm is developed for minimization of the cost function and adjustment of NN parameters. The performance of the optimized bootstrap method is examined for seven synthetic and real-world case studies. It is shown that application of the proposed method improves the quality of constructed PIs by more than 28% over the existing technique, leading to narrower PIs with a coverage probability greater than the nominal confidence level.

  14. Classical Conditioning Components of the Orienting Reflex to Words Using Innocuous and Noxious Unconditioned Stimuli Under Different Conditioned Stimulus-Unconditioned Stimulus Intervals

    ERIC Educational Resources Information Center

    Maltzman, Irving; And Others

    1977-01-01

    Concerns the examination of conditioned stimulus--unconditioned stimulus (CS--UCS) intervals of different lengths. Demonstrates the feasibility of using a forewarned reaction time procedure with an innocuous imperative stimulus for the investigation of classical conditioning. (Editor/RK)

  15. Uncertainty analysis of neural network based flood forecasting models: An ensemble based approach for constructing prediction interval

    NASA Astrophysics Data System (ADS)

    Kasiviswanathan, K.; Sudheer, K.

    2013-05-01

    Artificial neural network (ANN) based hydrologic models have gained lot of attention among water resources engineers and scientists, owing to their potential for accurate prediction of flood flows as compared to conceptual or physics based hydrologic models. The ANN approximates the non-linear functional relationship between the complex hydrologic variables in arriving at the river flow forecast values. Despite a large number of applications, there is still some criticism that ANN's point prediction lacks in reliability since the uncertainty of predictions are not quantified, and it limits its use in practical applications. A major concern in application of traditional uncertainty analysis techniques on neural network framework is its parallel computing architecture with large degrees of freedom, which makes the uncertainty assessment a challenging task. Very limited studies have considered assessment of predictive uncertainty of ANN based hydrologic models. In this study, a novel method is proposed that help construct the prediction interval of ANN flood forecasting model during calibration itself. The method is designed to have two stages of optimization during calibration: at stage 1, the ANN model is trained with genetic algorithm (GA) to obtain optimal set of weights and biases vector, and during stage 2, the optimal variability of ANN parameters (obtained in stage 1) is identified so as to create an ensemble of predictions. During the 2nd stage, the optimization is performed with multiple objectives, (i) minimum residual variance for the ensemble mean, (ii) maximum measured data points to fall within the estimated prediction interval and (iii) minimum width of prediction interval. The method is illustrated using a real world case study of an Indian basin. The method was able to produce an ensemble that has an average prediction interval width of 23.03 m3/s, with 97.17% of the total validation data points (measured) lying within the interval. The derived

  16. Inhibitory effect of intensity and interstimulus interval of conditioning stimuli on somatosensory evoked magnetic fields.

    PubMed

    Onishi, Hideaki; Sugawara, Kazuhiro; Yamashiro, Koya; Sato, Daisuke; Kirimoto, Hikari; Tamaki, Hiroyuki; Shirozu, Hiroshi; Kameyama, Shigeki

    2016-08-01

    Magnetoencephalography (MEG) recordings were performed to investigate the inhibitory effects of conditioning stimuli with various types of interstimulus intervals (ISIs) or intensities on somatosensory evoked magnetic fields (SEFs) using a 306-ch whole-head MEG system. Twenty-three healthy volunteers participated in this study. Electrical stimuli were applied to the right median nerve at the wrist. Six pulse trains with ISIs of 500 ms were presented in Experiment 1. A paired-pulse paradigm with three kinds of conditioning stimulus (CON) intensities, 500 ms before the test stimulus (TS), was applied in Experiment 2. Finally, three CONs 500 or 1000 ms before TS were presented in Experiment 3. Three main SEF deflections (N20m, P35m, and P60m) were observed, and the source activities of P35m and P60m significantly decreased after the 2nd pulse of a six pulse trains. These source activities also significantly decreased with increasing intensity of CON. In addition, these attenuations of source activities were affected by CON-CON or CON-TS intervals. These results indicated that the source activities were modulated by the intensity and ISIs of CONs. Furthermore, P35m after the stimulation were very sensitive to CONs; however, the attenuation of P60m after the stimulation lasted for a longer period than that of P35m. Our findings suggest that the conditioning stimulation had inhibitory effects on subsequent evoked cortical responses for more than 500 ms. Our results also provide important clues about the nature of short-latency somatosensory responses in human studies. PMID:27319980

  17. Study on short term prediction using observed water quality from 8-day intervals in Nakdong river

    NASA Astrophysics Data System (ADS)

    Kim, M.; Shon, T.; Joo, J.; Kim, J.; Shin, H.

    2012-12-01

    There are lots of accidents on water quality, like green algal blooms, occurring in Nakdong river which is one of the largest river in Korea. This is because of climate change around the world. It is essential to develop scientific and quantitative assessment methods. In this study, artificial neural network based on back propagation algorithm, which is simple and flexible method, was used for forecasting the water quality on the purpose of water resources management. Especially, as used observed water quality data from 8-day intervals in Nakdong river, it makes to increase the accuracy of water quality forecast over short term. This was established for predicting the water quality factors 1, 3, and 7 days ahead. The best model, as evaluated by its performance functions with RMSE and R2, was selected and applied to established models of BOD, DO, COD, and Chl-a using artificial neural network. The results showed that the models were suitable for 1 and 3 days forecasts in particular. This method is strong and convenient to predict water quality factors over the short term easily based on observed data. It is possible to overcome and manage problems related to the water resources. In the future, this will be a powerful method because it is basically based on observed water quality data.

  18. Ambulatory blood pressure reduction following high-intensity interval exercise performed in water or dryland condition.

    PubMed

    Sosner, Philippe; Gayda, Mathieu; Dupuy, Olivier; Garzon, Mauricio; Lemasson, Christopher; Gremeaux, Vincent; Lalongé, Julie; Gonzales, Mariel; Hayami, Douglas; Juneau, Martin; Nigam, Anil; Bosquet, Laurent

    2016-05-01

    We aimed to compare blood pressure (BP) responses following moderate-intensity continuous exercise (MICE), high-intensity interval exercise (HIIE) in dry land or HIIE in immersed condition, using 24-hour ambulatory BP monitoring. Forty-two individuals (65 ± 7 years, 52% men) with a baseline BP ≥ 130/85 mm Hg (systolic/diastolic blood pressures [SBP/DBP]) were randomly assigned to perform one of the three following exercises on a stationary cycle: MICE (24 minutes at 50% peak power output) or HIIE in dry land (two sets of 10 minutes with phases of 15 seconds 100% peak power output interspersed by 15 seconds of passive recovery) or HIIE in up-to-the-chest immersed condition. While MICE modified none of the 24-hour average hemodynamic variables, dryland HIIE induced a 24-hour BP decrease (SBP: -3.6 ± 5.7/DBP: -2.8 ± 3.0 mm Hg, P < .05) and, to a much greater extent, immersed HIIE (SBP: -6.8 ± 9.5/DBP: -3.0 ± 4.5 mm Hg, P < .05). The one condition that modified 24-hour pulse-wave velocity was immersed HIIE (-0.21 ± 0.30 m/s, P < .05).

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

    PubMed

    Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

    2014-02-01

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

  20. Personalized Metabolomics for Predicting Glucose Tolerance Changes in Sedentary Women After High-Intensity Interval Training

    PubMed Central

    Kuehnbaum, Naomi L.; Gillen, Jenna B.; Gibala, Martin J.; Britz-McKibbin, Philip

    2014-01-01

    High-intensity interval training (HIIT) offers a practical approach for enhancing cardiorespiratory fitness, however its role in improving glucose regulation among sedentary yet normoglycemic women remains unclear. Herein, multi-segment injection capillary electrophoresis-mass spectrometry is used as a high-throughput platform in metabolomics to assess dynamic responses of overweight/obese women (BMI > 25, n = 11) to standardized oral glucose tolerance tests (OGTTs) performed before and after a 6-week HIIT intervention. Various statistical methods were used to classify plasma metabolic signatures associated with post-prandial glucose and/or training status when using a repeated measures/cross-over study design. Branched-chain/aromatic amino acids and other intermediates of urea cycle and carnitine metabolism decreased over time in plasma after oral glucose loading. Adaptive exercise-induced changes to plasma thiol redox and orthinine status were measured for trained subjects while at rest in a fasting state. A multi-linear regression model was developed to predict changes in glucose tolerance based on a panel of plasma metabolites measured for naïve subjects in their untrained state. Since treatment outcomes to physical activity are variable between-subjects, prognostic markers offer a novel approach to screen for potential negative responders while designing lifestyle modifications that maximize the salutary benefits of exercise for diabetes prevention on an individual level. PMID:25164777

  1. Personalized metabolomics for predicting glucose tolerance changes in sedentary women after high-intensity interval training.

    PubMed

    Kuehnbaum, Naomi L; Gillen, Jenna B; Gibala, Martin J; Britz-McKibbin, Philip

    2014-01-01

    High-intensity interval training (HIIT) offers a practical approach for enhancing cardiorespiratory fitness, however its role in improving glucose regulation among sedentary yet normoglycemic women remains unclear. Herein, multi-segment injection capillary electrophoresis-mass spectrometry is used as a high-throughput platform in metabolomics to assess dynamic responses of overweight/obese women (BMI > 25, n = 11) to standardized oral glucose tolerance tests (OGTTs) performed before and after a 6-week HIIT intervention. Various statistical methods were used to classify plasma metabolic signatures associated with post-prandial glucose and/or training status when using a repeated measures/cross-over study design. Branched-chain/aromatic amino acids and other intermediates of urea cycle and carnitine metabolism decreased over time in plasma after oral glucose loading. Adaptive exercise-induced changes to plasma thiol redox and orthinine status were measured for trained subjects while at rest in a fasting state. A multi-linear regression model was developed to predict changes in glucose tolerance based on a panel of plasma metabolites measured for naïve subjects in their untrained state. Since treatment outcomes to physical activity are variable between-subjects, prognostic markers offer a novel approach to screen for potential negative responders while designing lifestyle modifications that maximize the salutary benefits of exercise for diabetes prevention on an individual level.

  2. An Interval-Valued Neural Network Approach for Uncertainty Quantification in Short-Term Wind Speed Prediction.

    PubMed

    Ak, Ronay; Vitelli, Valeria; Zio, Enrico

    2015-11-01

    We consider the task of performing prediction with neural networks (NNs) on the basis of uncertain input data expressed in the form of intervals. We aim at quantifying the uncertainty in the prediction arising from both the input data and the prediction model. A multilayer perceptron NN is trained to map interval-valued input data onto interval outputs, representing the prediction intervals (PIs) of the real target values. The NN training is performed by nondominated sorting genetic algorithm-II, so that the PIs are optimized both in terms of accuracy (coverage probability) and dimension (width). Demonstration of the proposed method is given in two case studies: 1) a synthetic case study, in which the data have been generated with a 5-min time frequency from an autoregressive moving average model with either Gaussian or Chi-squared innovation distribution and 2) a real case study, in which experimental data consist of wind speed measurements with a time step of 1 h. Comparisons are given with a crisp (single-valued) approach. The results show that the crisp approach is less reliable than the interval-valued input approach in terms of capturing the variability in input.

  3. Exertional responses to sprint interval training: a comparison of 30-sec. and 60-sec. conditions.

    PubMed

    Kilpatrick, Marcus W; Greeley, Samuel J

    2014-06-01

    The purpose of this study was to assess the effect of sprint interval training on rating of perceived exertion. 20 healthy participants (11 men, 9 women; M age = 23 yr.) completed a maximal cycle ergometer test and two high-intensity interval training cycling sessions. Each session utilized the same work-to-rest ratio (1:1), work intensity (90% max), recovery intensity (10% work intensity), and session duration (16 min.). Trials differed on duration of the interval segment, with a 30-sec. trial and a 60-sec. trial. Sessions required the same amount of total work over the duration of the trial. Rating of perceived exertion assessed before, during, and after exercise were higher for the 60-sec. trial than the 30-sec. trial despite no difference in total work. High intensity interval training trials utilizing the same total external work but differing in interval length produced different ratings of perceived exertion. Perceived exertion is significantly higher for sessions of exercise that utilize longer work intervals. These findings suggest that shorter intervals may produce more favorable exertional responses that could positively affect future behavior.

  4. Prediction bands and intervals for the scapulo-humeral coordination based on the Bootstrap and two Gaussian methods.

    PubMed

    Cutti, A G; Parel, I; Raggi, M; Petracci, E; Pellegrini, A; Accardo, A P; Sacchetti, R; Porcellini, G

    2014-03-21

    Quantitative motion analysis protocols have been developed to assess the coordination between scapula and humerus. However, the application of these protocols to test whether a subject's scapula resting position or pattern of coordination is "normal", is precluded by the unavailability of reference prediction intervals and bands, respectively. The aim of this study was to present such references for the "ISEO" protocol, by using the non-parametric Bootstrap approach and two parametric Gaussian methods (based on Student's T and Normal distributions). One hundred and eleven asymptomatic subjects were divided into three groups based on their age (18-30, 31-50, and 51-70). For each group, "monolateral" prediction bands and intervals were computed for the scapulo-humeral patterns and the scapula resting orientation, respectively. A fourth group included the 36 subjects (42 ± 13 year-old) for whom the scapulo-humeral coordination was measured bilaterally, and "differential" prediction bands and intervals were computed, which describe right-to-left side differences. Bootstrap and Gaussian methods were compared using cross-validation analyses, by evaluating the coverage probability in comparison to a 90% target. Results showed a mean coverage for Bootstrap from 86% to 90%, compared to 67-70% for parametric bands and 87-88% for parametric intervals. Bootstrap prediction bands showed a distinctive change in amplitude and mean pattern related to age, with an increase toward scapula retraction, lateral rotation and posterior tilt. In conclusion, Bootstrap ensures an optimal coverage and should be preferred over parametric methods. Moreover, the stratification of "monolateral" prediction bands and intervals by age appears relevant for the correct classification of patients.

  5. Effects of changes in frequency on guinea pig ventricular action potential duration and on QT interval under different experimental conditions.

    PubMed

    von Savigny, L; Hohnloser, S; Antoni, H

    1981-01-01

    Isolated perfused guinea pig hearts (Langendorff preparation) were arrested by carbachol (0.1-0.2 mg/l) and electrically stimulated in the region of the av-conducting system. The QT interval was determined by means of extracellular electrodes at different driving frequencies. Separate experiments were performed on papillary muscles from the right ventricle to measure the duration of the transmembrane action potential under comparable conditions. At 35 degrees C (Ke+ 5.4 mmol/l) increasing the frequency of stimulation (range 12-120/min) caused the action potential duration (APD) to decrease to a greater extent than the QT interval. Stepwise rising of the external K+ concentration up to 16.2 mmol/l produced a nearly parallel shift to the APD-frequency relation to lower values. Again, the QT interval was less affected by increasing the external K+ concentration than the APD. Stepwise reduction of the temperature down to 20 degrees C prolonged the APD as well as the QT interval, the effects being more pronounced at lower than at higher stimulation frequencies. Under all examined experimental conditions, the APD proved to be markedly shorter than the QT interval even when the latter is diminished by the duration of QRS. The results suggest that no close relation exists between the APD and the QT interval. The observed divergencies may be due to functional differences among various parts of the ventricles.

  6. Cues Produced by Reward and Nonreward and Temporal Cues Influence Responding in the Intertrial Interval and to the Conditioned Stimulus

    ERIC Educational Resources Information Center

    Capaldi, E. J.; Martins, Ana; Miller, Ronald M.

    2007-01-01

    Rats in a Pavlovian situation were trained under three different reward schedules, at either a 30 s or a 90 s intertrial interval (ITI): Consistent reward (C), 50% irregular reward (I), and single alternation of reward and nonrewarded trials (SA). Activity was recorded to the conditioned stimulus (CS) and in all 10 s bins in each ITI except the…

  7. Effects of Paradigm and Inter-Stimulus Interval on Age Differences in Eyeblink Classical Conditioning in Rabbits

    ERIC Educational Resources Information Center

    Woodruff-Pak, Diana S.; Seta, Susan E.; Roker, LaToya A.; Lehr, Melissa A.

    2007-01-01

    The aim of this study was to examine parameters affecting age differences in eyeblink classical conditioning in a large sample of young and middle-aged rabbits. A total of 122 rabbits of mean ages of 4 or 26 mo were tested at inter-stimulus intervals (ISIs) of 600 or 750 msec in the delay or trace paradigms. Paradigm affected both age groups…

  8. Logistic regression analysis to predict weaning-to-estrous interval in first-litter gilts

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Delayed return to estrus after weaning is a significant problem for swine producers. In this study, we investigated the relationships between weaning-to-estrous interval (WEI) and body weight (BW), back fat (BF), plasma leptin (L), glucose (G), albumin (A), urea nitrogen (PUN) concentrations and lit...

  9. Predicting Road Conditions with Internet Search

    PubMed Central

    2016-01-01

    Traffic congestion is an important problem both on an individual and on a societal level and much research has been done to explain and prevent their emergence. There are currently many systems which provide a reasonably good picture of actual road traffic by employing either fixed measurement points on highways or so called “floating car data” i.e. by using velocity and location data from roaming, networked, GPS enabled members of traffic. Some of these systems also offer forecasting of road conditions based on such historical data. To my knowledge there is as yet no system which offers advance notice on road conditions based on a signal which is guaranteed to occur in advance of these conditions and this is the novelty of this paper. Google Search intensity for the German word stau (i.e. traffic jam) peaks 2 hours ahead of the number of traffic jam reports as reported by the ADAC, a well known German automobile club and the largest of its kind in Europe. This is true both in the morning (7 am to 9 am) and in the evening (4 pm to 6 pm). The main result of this paper is then that after controlling for time-of-day and day-of-week effects we can still explain a significant additional portion of the variation of the number of traffic jam reports with Google Trends and we can thus explain well over 80% of the variation of road conditions using Google search activity. A one percent increase in Google stau searches implies a .4 percent increase of traffic jams. Our paper is a proof of concept that aggregate, timely delivered behavioural data can help fine tune modern societies and prompts for more research with better, more disaggregated data in order to also achieve practical solutions. PMID:27571518

  10. Predicting Road Conditions with Internet Search.

    PubMed

    Askitas, Nikolaos

    2016-01-01

    Traffic congestion is an important problem both on an individual and on a societal level and much research has been done to explain and prevent their emergence. There are currently many systems which provide a reasonably good picture of actual road traffic by employing either fixed measurement points on highways or so called "floating car data" i.e. by using velocity and location data from roaming, networked, GPS enabled members of traffic. Some of these systems also offer forecasting of road conditions based on such historical data. To my knowledge there is as yet no system which offers advance notice on road conditions based on a signal which is guaranteed to occur in advance of these conditions and this is the novelty of this paper. Google Search intensity for the German word stau (i.e. traffic jam) peaks 2 hours ahead of the number of traffic jam reports as reported by the ADAC, a well known German automobile club and the largest of its kind in Europe. This is true both in the morning (7 am to 9 am) and in the evening (4 pm to 6 pm). The main result of this paper is then that after controlling for time-of-day and day-of-week effects we can still explain a significant additional portion of the variation of the number of traffic jam reports with Google Trends and we can thus explain well over 80% of the variation of road conditions using Google search activity. A one percent increase in Google stau searches implies a .4 percent increase of traffic jams. Our paper is a proof of concept that aggregate, timely delivered behavioural data can help fine tune modern societies and prompts for more research with better, more disaggregated data in order to also achieve practical solutions.

  11. Predicting Road Conditions with Internet Search.

    PubMed

    Askitas, Nikolaos

    2016-01-01

    Traffic congestion is an important problem both on an individual and on a societal level and much research has been done to explain and prevent their emergence. There are currently many systems which provide a reasonably good picture of actual road traffic by employing either fixed measurement points on highways or so called "floating car data" i.e. by using velocity and location data from roaming, networked, GPS enabled members of traffic. Some of these systems also offer forecasting of road conditions based on such historical data. To my knowledge there is as yet no system which offers advance notice on road conditions based on a signal which is guaranteed to occur in advance of these conditions and this is the novelty of this paper. Google Search intensity for the German word stau (i.e. traffic jam) peaks 2 hours ahead of the number of traffic jam reports as reported by the ADAC, a well known German automobile club and the largest of its kind in Europe. This is true both in the morning (7 am to 9 am) and in the evening (4 pm to 6 pm). The main result of this paper is then that after controlling for time-of-day and day-of-week effects we can still explain a significant additional portion of the variation of the number of traffic jam reports with Google Trends and we can thus explain well over 80% of the variation of road conditions using Google search activity. A one percent increase in Google stau searches implies a .4 percent increase of traffic jams. Our paper is a proof of concept that aggregate, timely delivered behavioural data can help fine tune modern societies and prompts for more research with better, more disaggregated data in order to also achieve practical solutions. PMID:27571518

  12. Prediction of Machine Tool Condition Using Support Vector Machine

    NASA Astrophysics Data System (ADS)

    Wang, Peigong; Meng, Qingfeng; Zhao, Jian; Li, Junjie; Wang, Xiufeng

    2011-07-01

    Condition monitoring and predicting of CNC machine tools are investigated in this paper. Considering the CNC machine tools are often small numbers of samples, a condition predicting method for CNC machine tools based on support vector machines (SVMs) is proposed, then one-step and multi-step condition prediction models are constructed. The support vector machines prediction models are used to predict the trends of working condition of a certain type of CNC worm wheel and gear grinding machine by applying sequence data of vibration signal, which is collected during machine processing. And the relationship between different eigenvalue in CNC vibration signal and machining quality is discussed. The test result shows that the trend of vibration signal Peak-to-peak value in surface normal direction is most relevant to the trend of surface roughness value. In trends prediction of working condition, support vector machine has higher prediction accuracy both in the short term ('One-step') and long term (multi-step) prediction compared to autoregressive (AR) model and the RBF neural network. Experimental results show that it is feasible to apply support vector machine to CNC machine tool condition prediction.

  13. Autonomic Function Predicts Fitness Response to Short-Term High-Intensity Interval Training.

    PubMed

    Kiviniemi, A M; Tulppo, M P; Eskelinen, J J; Savolainen, A M; Kapanen, J; Heinonen, I H A; Hautala, A J; Hannukainen, J C; Kalliokoski, K K

    2015-11-01

    We tested the hypothesis that baseline cardiac autonomic function and its acute response to all-out interval exercise explains individual fitness responses to high-intensity interval training (HIT). Healthy middle-aged sedentary men performed HIT (n=12, 4-6×30 s of all-out cycling efforts with 4-min recovery) or aerobic training (AET, n=9, 40-60 min at 60% of peak workload in exercise test [Loadpeak]), comprising 6 sessions within 2 weeks. Low (LF) and high frequency (HF) power of R-R interval oscillation were analyzed from data recorded at supine and standing position (5+5 min) every morning during the intervention. A significant training effect (p< 0.001), without a training*group interaction, was observed in Loadpeak and peak oxygen consumption (VO2peak). Pre-training supine LF/HF ratio, an estimate of sympathovagal balance, correlated with training outcome in Loadpeak (Spearman's rho [rs]=-0.74, p=0.006) and VO2peak (rs=- 0.59, p=0.042) in the HIT but not the AET group. Also, the mean change in the standing LF/HF ratio in the morning after an acute HIT exercise during the 1(st) week of intervention correlated with training response in Loadpeak (rs=- 0.68, p=0.014) and VO2peak (rs=-0.60, p=0.039) with HIT but not with AET. In conclusion, pre-training cardiac sympathovagal balance and its initial alterations in response to acute HIT exercise were related to fitness responses to short-term HIT.

  14. How Children Use Examples to Make Conditional Predictions

    ERIC Educational Resources Information Center

    Kalish, Charles W.

    2010-01-01

    Two experiments explored children's and adults' use of examples to make conditional predictions. In Experiment 1 adults (N = 20) but not 4-year-olds (N = 21) or 8-year-olds (N =1 8) distinguished predictable from unpredictable features when features were partially correlated (e.g., necessary but not sufficient). Children did make reliable…

  15. Interstimulus Interval and Delivery Cues Influence Timed Conditioned Responding in Rats

    ERIC Educational Resources Information Center

    Williams, Douglas A.; Chubala, Chrissy M.; Mather, Amber A.; Johns, Kenneth W.

    2009-01-01

    Appetitive contextual excitation supported by intertrial unconditioned stimuli was more easily overcome by timed conditioned responding in rats using quiet (Experiment 1) rather than noisy (Experiment 2) food pellet deliveries. Head-entry responding in acquisition peaked above the contextual baseline when pellet delivery occurred 10, 30, 60, or 90…

  16. Phonation Interval Modification and Speech Performance Quality during Fluency-Inducing Conditions by Adults Who Stutter

    ERIC Educational Resources Information Center

    Ingham, Roger J.; Bothe, Anne K.; Wang, Yuedong; Purkhiser, Krystal; New, Anneliese

    2012-01-01

    Purpose: To relate changes in four variables previously defined as characteristic of normally fluent speech to changes in phonatory behavior during oral reading by persons who stutter (PWS) and normally fluent controls under multiple fluency-inducing (FI) conditions. Method: Twelve PWS and 12 controls each completed 4 ABA experiments. During A…

  17. Super-Latent Inhibition of Conditioned Taste Preference with a Long Retention Interval

    ERIC Educational Resources Information Center

    De la Casa, L. G.; Marquez, R.; Lubow, R. E.

    2009-01-01

    A long delay inserted between conditioning and test phases of a 3-stage Latent Inhibition (LI) procedure produces differential effects on LI depending on the delay context. Thus, enhanced LI has been obtained when the delay is spent in a context that is different from the remaining experimental contexts, but not when it is the same. The present…

  18. Observing response acquisition: preference for unpredictable appetitive rewards obtained under conditions predicted by DMOD.

    PubMed

    Daly, H B

    1985-04-01

    In five E-maze experiments, rats were given a choice between receiving reward and nonreward in a situation where stimuli were correlated with reward outcome (predictable situation) versus one where the stimuli were uncorrelated with reward outcome (unpredictable situation). Preference for the unpredictable situation occurred under the following conditions: (a) small (one 37-mg pellet), immediate rewards; (b) small, delayed (15 s) rewards, if the cues correlated with reward outcome were absent during the delay interval; (c) large (15 pellets), immediate rewards if a difficult discrimination was required; and (d) if the stimulus predicting nonreward was present at the choice point. Preference for the predictable situation was strongest if reinforcement was delayed and large or the stimulus predicting reward was present at the choice point. A weaker preference for the predictable situation occurred if reinforcement was immediate and large and a simple discrimination was required or if reinforcement was large and delayed and the cues that correlated with reward outcome were absent during the delay interval. The results support the predictions of DMOD (Daly modification of the Rescorla-Wagner model), a mathematical model of appetitive learning (Daly & Daly, 1982).

  19. The Influence of Prior Handling on the Effective CS-US Interval in Long-Trace Taste-Aversion Conditioning in Rats

    ERIC Educational Resources Information Center

    Hinderliter, Charles F.; Andrews, Amy; Misanin, James R.

    2012-01-01

    In conditioned taste aversion (CTA), a taste, the conditioned stimulus (CS), is paired with an illness-inducing stimulus, the unconditioned stimulus (US), to produce CS-US associations at very long (hours) intervals, a result that appears to violate the law of contiguity. The specific length of the maximum effective trace interval that has been…

  20. Low-latitude Pi2 pulsations during intervals of quiet geomagnetic conditions (Kp≤1)

    NASA Astrophysics Data System (ADS)

    Kwon, H.-J.; Kim, K.-H.; Jun, C.-W.; Takahashi, K.; Lee, D.-H.; Lee, E.; Jin, H.; Seon, J.; Park, Y.-D.; Hwang, J.

    2013-10-01

    It has been reported that Pi2 pulsations can be excited under extremely quiet geomagnetic conditions (Kp=0). However, there have been few comprehensive reports of Pi2 pulsations in such a near ground state magnetosphere. To understand the characteristics of quiet-time Pi2 pulsations, we statistically examined Pi2 events observed on the nightside between 1800 and 0600 local time at the low-latitude Bohyun (BOH, L = 1.35) station in South Korea. We chose year 2008 for analysis because geomagnetic activity was unusually low in that year. A total of 982 Pi2 events were identified when Kp≤1. About 80% of the Pi2 pulsations had a period between 110 and 300 s, which significantly differs from the conventional Pi2 period from 40 to 150 s. Comparing Pi2 periods and solar wind conditions, we found that Pi2 periods decrease with increasing solar wind speed, consistent with the result of Troitskaya (1967). The observed wave properties are discussed in terms of plasmaspheric resonance, which has been proposed for Pi2 pulsations in the inner magnetosphere. We also found that Pi2 pulsations occur quasi-periodically with a repetition period of ˜23-38 min. We will discuss what determines such a recurrence time of Pi2 pulsations under quiet geomagnetic conditions.

  1. Conditional-sampling schemes for turbulent flow, based on the variable-interval time averaging (VITA) algorithm

    NASA Astrophysics Data System (ADS)

    Morrison, J. F.; Tsai, H. M.; Bradshaw, P.

    1988-12-01

    The variable-interval time-averaging (“VITA”) algorithm has been tested in a variety of turbulent boundary layers for its ability to detect shear-stress-producing motions from hot-wire signals. A “VITA + LEVEL” scheme (which uses criteria for both short-time variance and short-time average, i.e.“level”) has been devised, and used in several different boundary layers. This scheme yields length-scale statistics that are acceptably independent of the conditioning criteria, which the VITA scheme does not.

  2. Conditional-sampling schemes for turbulent flow, based on the variable-interval time averaging (VITA) algorithm

    NASA Astrophysics Data System (ADS)

    Morrison, J. F.; Tsai, H. M.; Bradshaw, P.

    The variable-interval time-averaging ('VITA') algorithm has been tested in a variety of turbulent boundary layers for its ability to detect shear-stress-producing motions from hot-wire signals. A 'VITA+LEVEL' scheme (which uses criteria for both short-time variance and short-time average, i.e., 'level') has been devised, and used in several different boundary layers. This scheme yields length-scale statistics that are acceptably independent of the conditioning criteria, which the VITA scheme does not.

  3. Prediction of left ventricular peak ejection velocity by preceding and prepreceding RR intervals in atrial fibrillation: a new method to adjust the influence between two intervals.

    PubMed Central

    Ko, Hong Sook; Lee, Kwang Je; Kim, Sang Wook; Kim, Tae Ho; Kim, Chee Jeong; Ryu, Wang Seong

    2002-01-01

    In atrial fibrillation, cardiac performance is dependent on both preceding RR (RR-1) and prepreceding RR (RR-2) intervals. However, relative contributions were not well defined. Left ventricular outflow peak ejection velocity (Vpe) was measured by echocardiography from 21 patients. The relation between RR-1 and Vpe could be divided into two zones; steep slope in short RR-1 intervals (< or =0.5 sec) and plateau in long RR-1 intervals (> 0.5 sec). RR-2 had a weak negative association with Vpe. The mean squared correlation coefficient (r2) between RR-2 and Vpe was 0.15 +/-0.13 and improved to 0.29+/-0.21 (p<0.001), when coordinates with RR-1 < or =0.5 sec were excluded. The RR-1 was positively associated with Vpe. The mean r2 between RR-1 and Vpe was 0.52+/-0.17 and improved to 0.72+/-0.11 (p<0.001), when adjusted by RR-2. Simple linear regression analysis showed that mean RR interval, age, fractional shortening (FS), and mean peak velocity were negatively correlated with modified r2 between RR-2 and Vpe. Multiple stepwise regression analysis revealed that mean RR interval (r2=0.32) and FS (r2=0.16) were significant. In summary, simple modification could improve the relationship of both RR-1 and RR-2 with cardiac performance. RR-2 might play a more role in cardiac performance than previously expected, and when cardiac function was impaired. PMID:12482995

  4. An Evaluation of Conditioning Data for Solute Transport Prediction

    SciTech Connect

    Scheibe, Timothy D.; Chien, Yi-Ju

    2003-03-01

    The large and diverse body of subsurface characterization data generated at a field research site near Oyster, Virginia provides a unique opportunity to test the impact of conditioning data of various types on predictions of flow and transport. Bromide breakthrough curves (BTCs) were measured during a forced-gradient local-scale injection experiment conducted in 1999. Observed BTCs are available at 140 sampling points in a three dimensional array within the transport domain. A detailed three-dimensional numerical model is used to simulate breakthrough curves at the same locations as the observed BTCs under varying assumptions regarding the character of hydraulic conductivity spatial distributions, and variable amounts and types of conditioning data. We present comparative results of six different cases ranging from simple (deterministic homogeneous models) to complex (stochastic indicator simulation conditioned to cross-borehole geophysical observations). Quantitative measures of model goodness-of-fit are presented. The results show that conditioning to a large number of small-scale measurements does not significantly improve model predictions, and may lead to biased or overly confident predictions. However, conditioning to geophysical interpretations with larger spatial support significantly improves the accuracy and precision of model predictions. In all cases, the effects of model error appear to be significant in relation to parameter uncertainty.

  5. Conditions for predicting quasistationary states by rearrangement formula

    NASA Astrophysics Data System (ADS)

    Yamaguchi, Yoshiyuki Y.; Ogawa, Shun

    2015-10-01

    Predicting the long-lasting quasistationary state for a given initial state is one of central issues in Hamiltonian systems having long-range interaction. A recently proposed method is based on the Vlasov description and uniformly redistributes the initial distribution along contours of the asymptotic effective Hamiltonian, which is defined by the obtained quasistationary state and is determined self-consistently. The method, to which we refer as the rearrangement formula, was suggested to give precise prediction under limited situations. Restricting initial states consisting of a spatially homogeneous part and small perturbation, we numerically reveal two conditions that the rearrangement formula prefers: One is a no Landau damping condition for the unperturbed homogeneous part, and the other comes from the Casimir invariants. Mechanisms of these conditions are discussed. Clarifying these conditions, we validate to use the rearrangement formula as the response theory for an external field, and we shed light on improving the theory as a nonequilibrium statistical mechanics.

  6. Effects of paradigm and inter-stimulus interval on age differences in eyeblink classical conditioning in rabbits.

    PubMed

    Woodruff-Pak, Diana S; Seta, Susan E; Roker, LaToya A; Lehr, Melissa A

    2007-04-01

    The aim of this study was to examine parameters affecting age differences in eyeblink classical conditioning in a large sample of young and middle-aged rabbits. A total of 122 rabbits of mean ages of 4 or 26 mo were tested at inter-stimulus intervals (ISIs) of 600 or 750 msec in the delay or trace paradigms. Paradigm affected both age groups dramatically, with superior performance in the delay paradigm. ISI was salient as middle-aged rabbits were significantly impaired in 750-msec compared with 600-msec delays, and young rabbits were significantly less impaired in 600-msec than in 750-msec trace. Young rabbits performed equally well at both delay ISIs, and consequently, there were significant age differences in 750-msec but not in 600-msec delays. Middle-aged rabbits performed poorly at both 600- and 750-msec trace, resulting in significant age differences in 600-msec but not in 750-msec trace. Timing of the conditioned response has been associated with cerebellar cortical function. Normal aging of the cerebellar cortex likely contributed to the magnitude of the effect of ISI in delay conditioning in middle-aged rabbits. Results demonstrate that the magnitude of age differences in eyeblink conditioning can be enlarged or eliminated by ISI and paradigm.

  7. Effects of paradigm and inter-stimulus interval on age differences in eyeblink classical conditioning in rabbits

    PubMed Central

    Woodruff-Pak, Diana S.; Seta, Susan E.; Roker, LaToya A.; Lehr, Melissa A.

    2007-01-01

    The aim of this study was to examine parameters affecting age differences in eyeblink classical conditioning in a large sample of young and middle-aged rabbits. A total of 122 rabbits of mean ages of 4 or 26 mo were tested at inter-stimulus intervals (ISIs) of 600 or 750 msec in the delay or trace paradigms. Paradigm affected both age groups dramatically, with superior performance in the delay paradigm. ISI was salient as middle-aged rabbits were significantly impaired in 750-msec compared with 600-msec delays, and young rabbits were significantly less impaired in 600-msec than in 750-msec trace. Young rabbits performed equally well at both delay ISIs, and consequently, there were significant age differences in 750-msec but not in 600-msec delays. Middle-aged rabbits performed poorly at both 600- and 750-msec trace, resulting in significant age differences in 600-msec but not in 750-msec trace. Timing of the conditioned response has been associated with cerebellar cortical function. Normal aging of the cerebellar cortex likely contributed to the magnitude of the effect of ISI in delay conditioning in middle-aged rabbits. Results demonstrate that the magnitude of age differences in eyeblink conditioning can be enlarged or eliminated by ISI and paradigm. PMID:17522017

  8. Evaluation of techniques for estimating the power spectral density of RR-intervals under paced respiration conditions.

    PubMed

    Schaffer, Thorsten; Hensel, Bernhard; Weigand, Christian; Schüttler, Jürgen; Jeleazcov, Christian

    2014-10-01

    Heart rate variability (HRV) analysis is increasingly used in anaesthesia and intensive care monitoring of spontaneous breathing and mechanical ventilated patients. In the frequency domain, different estimation methods of the power spectral density (PSD) of RR-intervals lead to different results. Therefore, we investigated the PSD estimates of fast Fourier transform (FFT), autoregressive modeling (AR) and Lomb-Scargle periodogram (LSP) for 25 young healthy subjects subjected to metronomic breathing. The optimum method for determination of HRV spectral parameters under paced respiration was identified by evaluating the relative error (RE) and the root mean square relative error (RMSRE) for each breathing frequency (BF) and spectral estimation method. Additionally, the sympathovagal balance was investigated by calculating the low frequency/high frequency (LF/HF) ratio. Above 7 breaths per minute, all methods showed a significant increase in LF/HF ratio with increasing BF. On average, the RMSRE of FFT was lower than for LSP and AR. Therefore, under paced respiration conditions, estimating RR-interval PSD using FFT is recommend. PMID:23508826

  9. How to regress and predict in a Bland-Altman plot? Review and contribution based on tolerance intervals and correlated-errors-in-variables models.

    PubMed

    Francq, Bernard G; Govaerts, Bernadette

    2016-06-30

    Two main methodologies for assessing equivalence in method-comparison studies are presented separately in the literature. The first one is the well-known and widely applied Bland-Altman approach with its agreement intervals, where two methods are considered interchangeable if their differences are not clinically significant. The second approach is based on errors-in-variables regression in a classical (X,Y) plot and focuses on confidence intervals, whereby two methods are considered equivalent when providing similar measures notwithstanding the random measurement errors. This paper reconciles these two methodologies and shows their similarities and differences using both real data and simulations. A new consistent correlated-errors-in-variables regression is introduced as the errors are shown to be correlated in the Bland-Altman plot. Indeed, the coverage probabilities collapse and the biases soar when this correlation is ignored. Novel tolerance intervals are compared with agreement intervals with or without replicated data, and novel predictive intervals are introduced to predict a single measure in an (X,Y) plot or in a Bland-Atman plot with excellent coverage probabilities. We conclude that the (correlated)-errors-in-variables regressions should not be avoided in method comparison studies, although the Bland-Altman approach is usually applied to avert their complexity. We argue that tolerance or predictive intervals are better alternatives than agreement intervals, and we provide guidelines for practitioners regarding method comparison studies. Copyright © 2016 John Wiley & Sons, Ltd.

  10. [Primary Study on Predicting the Termination of Paroxysmal Atrial Fibrillation Based on a Novel RdR RR Intervals Scatter Plot].

    PubMed

    Lu, Hongwei; Zhang, Chenxi; Sun, Ying; Hao, Zhidong; Wang, Chunfang; Tian, Jiajia

    2015-08-01

    Predicting the termination of paroxysmal atrial fibrillation (AF) may provide a signal to decide whether there is a need to intervene the AF timely. We proposed a novel RdR RR intervals scatter plot in our study. The abscissa of the RdR scatter plot was set to RR intervals and the ordinate was set as the difference between successive RR intervals. The RdR scatter plot includes information of RR intervals and difference between successive RR intervals, which captures more heart rate variability (HRV) information. By RdR scatter plot analysis of one minute RR intervals for 50 segments with non-terminating AF and immediately terminating AF, it was found that the points in RdR scatter plot of non-terminating AF were more decentralized than the ones of immediately terminating AF. By dividing the RdR scatter plot into uniform grids and counting the number of non-empty grids, non-terminating AF and immediately terminating AF segments were differentiated. By utilizing 49 RR intervals, for 20 segments of learning set, 17 segments were correctly detected, and for 30 segments of test set, 20 segments were detected. While utilizing 66 RR intervals, for 18 segments of learning set, 16 segments were correctly detected, and for 28 segments of test set, 20 segments were detected. The results demonstrated that during the last one minute before the termination of paroxysmal AF, the variance of the RR intervals and the difference of the neighboring two RR intervals became smaller. The termination of paroxysmal AF could be successfully predicted by utilizing the RdR scatter plot, while the predicting accuracy should be further improved.

  11. Sensitivity to masked conditioned stimuli predicts conditioned response magnitude under masked conditions

    PubMed Central

    Cornwell, Brian R.; Echiverri, Aileen M.; Grillon, Christian

    2009-01-01

    Expression of conditioned fear has been reported to be independent of perceptual awareness of conditioned stimuli (CSs). Previous studies have been criticized, however, for not adequately assessing perceptual awareness. We fear-conditioned participants to one of two symbols and measured skin conductance responses to dichoptically masked and unmasked CSs. Participants also performed a target detection task and sensitivity (d′) to the masked conditioned stimuli (CS+, CS−) was measured. Results showed that sensitivity under masking conditions was related to conditioned responses to masked CSs but not unmasked CSs. Thus, a strong relationship between expression of conditioned fear and awareness of the CS+ emerges when the latter is assessed by signal detection methods. Without consensus on how awareness should be defined, these findings bring balance to previous studies that have typically used less sensitive assessments of awareness. PMID:17433097

  12. Time-interval for integration of stabilizing haptic and visual information in subjects balancing under static and dynamic conditions

    PubMed Central

    Honeine, Jean-Louis; Schieppati, Marco

    2014-01-01

    Maintaining equilibrium is basically a sensorimotor integration task. The central nervous system (CNS) continually and selectively weights and rapidly integrates sensory inputs from multiple sources, and coordinates multiple outputs. The weighting process is based on the availability and accuracy of afferent signals at a given instant, on the time-period required to process each input, and possibly on the plasticity of the relevant pathways. The likelihood that sensory inflow changes while balancing under static or dynamic conditions is high, because subjects can pass from a dark to a well-lit environment or from a tactile-guided stabilization to loss of haptic inflow. This review article presents recent data on the temporal events accompanying sensory transition, on which basic information is fragmentary. The processing time from sensory shift to reaching a new steady state includes the time to (a) subtract or integrate sensory inputs; (b) move from allocentric to egocentric reference or vice versa; and (c) adjust the calibration of motor activity in time and amplitude to the new sensory set. We present examples of processes of integration of posture-stabilizing information, and of the respective sensorimotor time-intervals while allowing or occluding vision or adding or subtracting tactile information. These intervals are short, in the order of 1–2 s for different postural conditions, modalities and deliberate or passive shift. They are just longer for haptic than visual shift, just shorter on withdrawal than on addition of stabilizing input, and on deliberate than unexpected mode. The delays are the shortest (for haptic shift) in blind subjects. Since automatic balance stabilization may be vulnerable to sensory-integration delays and to interference from concurrent cognitive tasks in patients with sensorimotor problems, insight into the processing time for balance control represents a critical step in the design of new balance- and locomotion training devices

  13. Predicted Turbine Heat Transfer for a Range of Test Conditions

    NASA Technical Reports Server (NTRS)

    Boyle, R. J.; Lucci, B. L.

    1996-01-01

    Comparisons are shown between predictions and experimental data for blade and endwall heat transfer. The comparisons of computational domain parisons are given for both vane and rotor geometries over an extensive range of Reynolds and Mach numbers. Comparisons are made with experimental data from a variety of sources. A number of turbulence models are available for predicting blade surface heat transfer, as well as aerodynamic performance. The results of an investigation to determine the turbulence model which gives the best agreement with experimental data over a wide range of test conditions are presented.

  14. Time series and recurrence interval models to predict the vulnerability of streams to episodic acidification in Shenandoah National Park, Virginia

    USGS Publications Warehouse

    Deviney, F.A.; Rice, K.C.; Hornberger, G.M.

    2006-01-01

    Acid rain affects headwater streams by temporarily reducing the acid-neutralizing capacity (ANC) of the water, a process termed episodic acidification. The increase in acidic components in stream water can have deleterious effects on the aquatic biota. Although acidic deposition is uniform across Shenandoah National Park (SNP) in north central Virginia, the stream water quality response during rain events varies substantially. This response is a function of the catchment's underlying geology and topography. Geologic and topographic data for SNP's 231 catchments are readily available; however, long-term measurements (tens of years) of ANC and accompanying discharge are not and would be prohibitively expensive to collect. Transfer function time series models were developed to predict hourly ANC from discharge for five SNP catchments with long-term water-quality and discharge records. Hourly ANC predictions over short time periods (??? 1 week) were averaged, and distributions of the recurrence intervals of annual water-year minimum ANC values were model-simulated for periods of 6, 24, 72, and 168 hours. The distributions were extrapolated to the rest of the SNP catchments on the basis of catchment geology and topography. On the basis of the models, large numbers of SNP streams have 6- to 168-hour periods of low-ANC values, which may stress resident fish populations. Smaller catchments are more vulnerable to episodic acidification than larger catchments underlain by the same bedrock. Catchments with similar topography and size are more vulnerable if underlain by less basaltic/carbonate bedrock. Many catchments are predicted to have successive years of low-ANC values potentially sufficient to extirpate some species. Copyright 2006 by the American Geophysical Union.

  15. Time Series and Recurrence Interval Models to Predict the Vulnerability of Streams to Episodic Acidification in Shenandoah National Park, Virginia

    NASA Astrophysics Data System (ADS)

    Deviney, F. A.; Rice, K. C.; Hornberger, G. M.

    2006-05-01

    Acid rain affects headwater streams by temporarily reducing the acid-neutralizing capacity (ANC) of the water, a process termed episodic acidification. The increase in acidic components in streamwater can have deleterious effects on the aquatic biota. Although acidic deposition is uniform across Shenandoah National Park (SNP) in north-central Virginia, the streamwater quality response during rain events varies substantially. This response is a function of the catchment's underlying geology and topography. Geologic and topographic data for SNP's 231 catchments are readily available, however, long-term measurements (tens of years) of ANC and accompanying discharge are not and would be prohibitively expensive to collect. Transfer function time series models were developed to predict hourly ANC from discharge for five SNP catchments with long-term water-quality and discharge records. Hourly ANC predictions over short time periods were averaged and distributions of the recurrence intervals of annual water-year minimum ANC values were model-simulated for periods of 6, 24, 72, and 168 hours. The distributions were extrapolated to the rest of the SNP catchments on the basis of catchment geology and topography. On the basis of the models, large numbers of SNP streams have 6- to 168-hour periods of low-ANC values, which may stress resident fish populations. Smaller catchments are more vulnerable to episodic acidification than larger catchments underlain by the same bedrock. Catchments with similar topography and size are more vulnerable if underlain by less basaltic/carbonate bedrock. Many catchments are predicted to have successive years of low-ANC values potentially sufficient to extirpate some species.

  16. Time series and recurrence interval models to predict the vulnerability of streams to episodic acidification in Shenandoah National Park, Virginia

    NASA Astrophysics Data System (ADS)

    Deviney, Frank A.; Rice, Karen C.; Hornberger, George M.

    2006-09-01

    Acid rain affects headwater streams by temporarily reducing the acid-neutralizing capacity (ANC) of the water, a process termed episodic acidification. The increase in acidic components in stream water can have deleterious effects on the aquatic biota. Although acidic deposition is uniform across Shenandoah National Park (SNP) in north central Virginia, the stream water quality response during rain events varies substantially. This response is a function of the catchment's underlying geology and topography. Geologic and topographic data for SNP's 231 catchments are readily available; however, long-term measurements (tens of years) of ANC and accompanying discharge are not and would be prohibitively expensive to collect. Transfer function time series models were developed to predict hourly ANC from discharge for five SNP catchments with long-term water-quality and discharge records. Hourly ANC predictions over short time periods (≤1 week) were averaged, and distributions of the recurrence intervals of annual water-year minimum ANC values were model-simulated for periods of 6, 24, 72, and 168 hours. The distributions were extrapolated to the rest of the SNP catchments on the basis of catchment geology and topography. On the basis of the models, large numbers of SNP streams have 6- to 168-hour periods of low-ANC values, which may stress resident fish populations. Smaller catchments are more vulnerable to episodic acidification than larger catchments underlain by the same bedrock. Catchments with similar topography and size are more vulnerable if underlain by less basaltic/carbonate bedrock. Many catchments are predicted to have successive years of low-ANC values potentially sufficient to extirpate some species.

  17. The conditions that promote fear learning: prediction error and Pavlovian fear conditioning.

    PubMed

    Li, Susan Shi Yuan; McNally, Gavan P

    2014-02-01

    A key insight of associative learning theory is that learning depends on the actions of prediction error: a discrepancy between the actual and expected outcomes of a conditioning trial. When positive, such error causes increments in associative strength and, when negative, such error causes decrements in associative strength. Prediction error can act directly on fear learning by determining the effectiveness of the aversive unconditioned stimulus or indirectly by determining the effectiveness, or associability, of the conditioned stimulus. Evidence from a variety of experimental preparations in human and non-human animals suggest that discrete neural circuits code for these actions of prediction error during fear learning. Here we review the circuits and brain regions contributing to the neural coding of prediction error during fear learning and highlight areas of research (safety learning, extinction, and reconsolidation) that may profit from this approach to understanding learning.

  18. Effect of suckling restriction with nose plates and premature weaning on postpartum anestrous interval in primiparous cows under range conditions.

    PubMed

    Quintans, G; Vázquez, A I; Weigel, K A

    2009-11-01

    Suckling and nutrition are generally recognized as two major factors controlling the duration of the postpartum anovulatory period. In the present study, the effect of premature weaning and suckling restriction with nose plates (NPs) on cow and calf performance was evaluated. The study was conducted over 2 years; primiparous Hereford cows, weighing (mean+/-S.E.M.) 344+/-3.5kg and with 4.1+/-0.05 units of body condition score (BCS) (scale 1-8 [Vizcarra, J.A., Ibañez, W., Orcasberro, R., 1986. Repetibilidad y reproductibilidad de dos escalas para estimar la condición corporal de vacas Hereford. Investigaciones Agronómicas 7 (1), 45-47]) at calving, remained with their calves until 72.5+/-1.2 days postpartum (day 0). They were then assigned to one of three treatments: (i) calves with free access to their dams and ad libitum suckling (S, n=29); (ii) calves fitted with NPs for 14 days, but remained with their dams (NP, n=29), and (iii) calves that were weaned from their dams (W, n=28). All cows were anestrus at the time treatments commenced (day 0). All cows were blood sampled twice weekly from 1 week before the beginning of the experiment until the end of the mating period (day 74) for progesterone analysis. The mating period began on day 14. Cows in W treatment had ovulations earlier (P<0.05) than those in NP and S groups. Cows in the NP group had longer (P<0.05) intervals between the first progesterone increase and normal luteal phase than cows in the other two treatments groups (23.3+/-3.2 vs. 6.5+/-3.2 and 5.2+/-3.3 days for NP, S and W cows, respectively). Fifty per cent of the cows with NP had a short cycle (7 days) but there was a group of cows that had longer (P<0.05) intervals (66 days) between first progesterone increase and normal estrous activity. In the NP group, 8 of 29 cows had a short luteal phase and then a normal one; for 9 of these 29 cows progesterone concentrations remained low for 6 weeks from the beginning of the treatment; and for 12 of these

  19. Prediction of intake in growing dairy heifers under tropical conditions.

    PubMed

    Oliveira, A S; Ferreira, V B

    2016-02-01

    A meta-analysis was conducted to develop models of the prediction of dry matter intake (DMI) in growing dairy heifers [postweaning to 390 kg of body weight (BW)] under tropical conditions. The adequacy of the models was assessed in a comparison with the 4 US models currently used to predict DMI [Quigley; National Research Council; and 2 Hoffman models]. The data set was created using 95 treatment means from 28 studies published in journals. The data set (studies) was randomly divided into 2 data subsets for the statistical analyses. The first data subset was used to develop the prediction equations for DMI (17 studies; 58 treatment means), and the second data subset was used to assess the adequacy of the predictive models (11 studies; 37 treatment means). The models were developed using nonlinear and linear mixed analyses. Breed (Bos taurus vs. Bos taurus × Bos indicus), BW (240.2±62.2 kg), and average daily gain (ADG, 0.83±0.28 kg/d) were the independent variables. No significant effects of the breed or the interactions between the breed and metabolic BW (BW(0.75)) or breed and ADG were detected. Thus, nonlinear [DMI=0.1175 × BW(0.75) - 3.4984 × e((-2.4690 × ADG))] and linear models [DMI=8.7147 - 0.2402 × BW(0.75) + 0.0027 × (BW(0.75))(2) + 3.6050 × ADG - 1.4168 × ADG(2)] were proposed for both breeds. The nonlinear model explained 81% of the variation in the DMI, over-predicted the DMI by 0.21 kg/d and predicted the DMI with a higher accuracy and precision than the linear model [root mean square error of prediction (RMSEP)=8.82 vs. 10.71% of the observed DMI, respectively]. The Quigley model explained only 54% of the variation in the DMI and was the fourth most accurate and precise model (RMSEP=11.21% of the observed DMI). The National Research Council model explained 69% of the variation in the DMI but under-predicted the DMI by 0.53 kg/d, with an RMSEP of 12.72% of the observed DMI and presence of systematic constant bias. The Hoffman exponential

  20. Use of early lactation milk recording data to predict the calving to conception interval in dairy herds.

    PubMed

    Cook, J G; Green, M J

    2016-06-01

    Economic success in dairy herds is heavily reliant on obtaining pregnancies at an early stage of lactation. Our objective in this study was to attempt to predict the likelihood of conception occurring by d 100 and 150 of lactation (days in milk, DIM) by Markov chain Monte Carlo analysis using test day milk recording data and reproductive records gathered retrospectively from 8,750 cows from 33 dairy herds located in the United Kingdom. Overall, 65% of cows recalved with 30, 46, and 65% of cows conceiving by 100 DIM, 150 DIM, and beyond 150 DIM, respectively. Overall conception rate (total cows pregnant/total number of inseminations) was 27.47%. Median and mean calving to conception intervals were 123 and 105 d, respectively. The probability of conception by both 100 DIM and 150 DIM was positively associated with the average daily milk weight produced during the fourth week of lactation (W4MK) and protein percentage for test day samples collected between 0 to 30 and 31 to 60 DIM. Butterfat percentage at 0 to 30 DIM was negatively associated with the probability of conception by 100 DIM but not at 150 DIM. High somatic cell count (SCC) at both 0 to 30 and 31 to 60 DIM was negatively associated with the probability of conception by 100 DIM, whereas high SCC at 31 to 60 DIM was associated with a reduced probability of conception by 150 DIM. Increasing parity was associated with a reduced odds of pregnancy. Posterior predictions of the likelihood of conception for cows categorized as having "good" (W4MK >30kg and protein percentage at 0 to 30 and 31 to 60 DIM >3.2%) or "poor" (W4MK <25kg and protein percentage at 0 to 30 and 31 to 60 DIM <3.0%) early lactation attributes with actual observed values indicated model fit was good. The predicted likelihood of a "good" cow conceiving by 100 and 150 DIM was 0.39 and 0.57, respectively (actual observed values 0.40 and 0.59). The corresponding values for a "poor" cow were 0.28 and 0.42 (actual observed values 0.26 and 0

  1. Expert system for predicting reaction conditions: the Michael reaction case.

    PubMed

    Marcou, G; Aires de Sousa, J; Latino, D A R S; de Luca, A; Horvath, D; Rietsch, V; Varnek, A

    2015-02-23

    A generic chemical transformation may often be achieved under various synthetic conditions. However, for any specific reagents, only one or a few among the reported synthetic protocols may be successful. For example, Michael β-addition reactions may proceed under different choices of solvent (e.g., hydrophobic, aprotic polar, protic) and catalyst (e.g., Brønsted acid, Lewis acid, Lewis base, etc.). Chemoinformatics methods could be efficiently used to establish a relationship between the reagent structures and the required reaction conditions, which would allow synthetic chemists to waste less time and resources in trying out various protocols in search for the appropriate one. In order to address this problem, a number of 2-classes classification models have been built on a set of 198 Michael reactions retrieved from literature. Trained models discriminate between processes that are compatible and respectively processes not feasible under a specific reaction condition option (feasible or not with a Lewis acid catalyst, feasible or not in hydrophobic solvent, etc.). Eight distinct models were built to decide the compatibility of a Michael addition process with each considered reaction condition option, while a ninth model was aimed to predict whether the assumed Michael addition is feasible at all. Different machine-learning methods (Support Vector Machine, Naive Bayes, and Random Forest) in combination with different types of descriptors (ISIDA fragments issued from Condensed Graphs of Reactions, MOLMAP, Electronic Effect Descriptors, and Chemistry Development Kit computed descriptors) have been used. Models have good predictive performance in 3-fold cross-validation done three times: balanced accuracy varies from 0.7 to 1. Developed models are available for the users at http://infochim.u-strasbg.fr/webserv/VSEngine.html . Eventually, these were challenged to predict feasibility conditions for ∼50 novel Michael reactions from the eNovalys database (originally

  2. Expert system for predicting reaction conditions: the Michael reaction case.

    PubMed

    Marcou, G; Aires de Sousa, J; Latino, D A R S; de Luca, A; Horvath, D; Rietsch, V; Varnek, A

    2015-02-23

    A generic chemical transformation may often be achieved under various synthetic conditions. However, for any specific reagents, only one or a few among the reported synthetic protocols may be successful. For example, Michael β-addition reactions may proceed under different choices of solvent (e.g., hydrophobic, aprotic polar, protic) and catalyst (e.g., Brønsted acid, Lewis acid, Lewis base, etc.). Chemoinformatics methods could be efficiently used to establish a relationship between the reagent structures and the required reaction conditions, which would allow synthetic chemists to waste less time and resources in trying out various protocols in search for the appropriate one. In order to address this problem, a number of 2-classes classification models have been built on a set of 198 Michael reactions retrieved from literature. Trained models discriminate between processes that are compatible and respectively processes not feasible under a specific reaction condition option (feasible or not with a Lewis acid catalyst, feasible or not in hydrophobic solvent, etc.). Eight distinct models were built to decide the compatibility of a Michael addition process with each considered reaction condition option, while a ninth model was aimed to predict whether the assumed Michael addition is feasible at all. Different machine-learning methods (Support Vector Machine, Naive Bayes, and Random Forest) in combination with different types of descriptors (ISIDA fragments issued from Condensed Graphs of Reactions, MOLMAP, Electronic Effect Descriptors, and Chemistry Development Kit computed descriptors) have been used. Models have good predictive performance in 3-fold cross-validation done three times: balanced accuracy varies from 0.7 to 1. Developed models are available for the users at http://infochim.u-strasbg.fr/webserv/VSEngine.html . Eventually, these were challenged to predict feasibility conditions for ∼50 novel Michael reactions from the eNovalys database (originally

  3. Video compression using conditional replenishment and motion prediction

    NASA Technical Reports Server (NTRS)

    Hein, D. N.; Ahmed, N.

    1984-01-01

    A study of a low-rate monochrome video compression system is presentd in this paper. This system is a conditional-replenishment coder that uses two-dimensional Walsh-transform coding within each video frame. The conditional-replenishment algorithm works by transmitting only the portions of an image that are changing in time. This system is augmented with a motn-prediction algorithm that measures spatial dispalcement parameters from frame to frame, and codes the data using these parameters. A comparison is made between the conditional-replenishment system with, and without, the motion-predictinalgorthm. Subsampling in time is ued to maintain the data rate rate at a fixed value. Average bit rates of 1 bit/picture element (pel) to 1/16 bit/pel are considered. The resultant performance of the compression simulations is presented in terms of the average frame rates produced.

  4. USING CONDITION MONITORING TO PREDICT REMAINING LIFE OF ELECTRIC CABLES.

    SciTech Connect

    LOFARO,R.; SOO,P.; VILLARAN,M.; GROVE,E.

    2001-03-29

    Electric cables are passive components used extensively throughout nuclear power stations to perform numerous safety and non-safety functions. It is known that the polymers commonly used to insulate the conductors on these cables can degrade with time; the rate of degradation being dependent on the severity of the conditions in which the cables operate. Cables do not receive routine maintenance and, since it can be very costly, they are not replaced on a regular basis. Therefore, to ensure their continued functional performance, it would be beneficial if condition monitoring techniques could be used to estimate the remaining useful life of these components. A great deal of research has been performed on various condition monitoring techniques for use on electric cables. In a research program sponsored by the U.S. Nuclear Regulatory Commission, several promising techniques were evaluated and found to provide trendable information on the condition of low-voltage electric cables. These techniques may be useful for predicting remaining life if well defined limiting values for the aging properties being measured can be determined. However, each technique has advantages and limitations that must be addressed in order to use it effectively, and the necessary limiting values are not always easy to obtain. This paper discusses how condition monitoring measurements can be used to predict the remaining useful life of electric cables. The attributes of an appropriate condition monitoring technique are presented, and the process to be used in estimating the remaining useful life of a cable is discussed along with the difficulties that must be addressed.

  5. Prolonged corrected QT interval is predictive of future stroke events even in subjects without ECG-diagnosed left ventricular hypertrophy.

    PubMed

    Ishikawa, Joji; Ishikawa, Shizukiyo; Kario, Kazuomi

    2015-03-01

    We attempted to evaluate whether subjects who exhibit prolonged corrected QT (QTc) interval (≥440 ms in men and ≥460 ms in women) on ECG, with and without ECG-diagnosed left ventricular hypertrophy (ECG-LVH; Cornell product, ≥244 mV×ms), are at increased risk of stroke. Among the 10 643 subjects, there were a total of 375 stroke events during the follow-up period (128.7±28.1 months; 114 142 person-years). The subjects with prolonged QTc interval (hazard ratio, 2.13; 95% confidence interval, 1.22-3.73) had an increased risk of stroke even after adjustment for ECG-LVH (hazard ratio, 1.71; 95% confidence interval, 1.22-2.40). When we stratified the subjects into those with neither a prolonged QTc interval nor ECG-LVH, those with a prolonged QTc interval but without ECG-LVH, and those with ECG-LVH, multivariate-adjusted Cox proportional hazards analysis demonstrated that the subjects with prolonged QTc intervals but not ECG-LVH (1.2% of all subjects; incidence, 10.7%; hazard ratio, 2.70, 95% confidence interval, 1.48-4.94) and those with ECG-LVH (incidence, 7.9%; hazard ratio, 1.83; 95% confidence interval, 1.31-2.57) had an increased risk of stroke events, compared with those with neither a prolonged QTc interval nor ECG-LVH. In conclusion, prolonged QTc interval was associated with stroke risk even among patients without ECG-LVH in the general population.

  6. Electrocardiogram PR Interval Is a Surrogate Marker to Predict New Occurrence of Atrial Fibrillation in Patients with Frequent Premature Atrial Contractions

    PubMed Central

    Hwang, Jin Kyung; Choi, So Ra; Park, Seung-Jung; Kim, June Soo

    2016-01-01

    The clinical significance of prolonged PR interval has not been evaluated in patients with frequent premature atrial contractions (PACs). We investigated whether prolonged PR interval could predict new occurrence of atrial fibrillation (AF) in patients with frequent PACs. We retrospectively analyzed 684 patients with frequent PACs (> 100 PACs/day) who performed repeated 24-hour Holter monitoring. Prolonged PR interval was defined as longer than 200 msec. Among 684 patients, 626 patients had normal PR intervals (group A) and 58 patients had prolonged PR intervals (group B). After a mean follow-up of 59.3 months, 14 patients (24.1%) in group B developed AF compared to 50 patients (8.0%) in group A (P < 0.001). Cox regression analysis showed that prolonged PR interval (hazard ratio [HR], 1.950; 95% CI, 1.029–3.698; P = 0.041), age (HR, 1.033; 95% CI, 1.006–1.060; P = 0.015), and left atrial (LA) dimension (HR, 1.061; 95% CI, 1.012–1.112; P = 0.015) were associated with AF occurrence. Prolonged PR interval, advanced age, and enlarged LA dimension are independent risk factors of AF occurrence in patients with frequent PACs. PMID:27051234

  7. Visual Bias Predicts Gait Adaptability in Novel Sensory Discordant Conditions

    NASA Technical Reports Server (NTRS)

    Brady, Rachel A.; Batson, Crystal D.; Peters, Brian T.; Mulavara, Ajitkumar P.; Bloomberg, Jacob J.

    2010-01-01

    We designed a gait training study that presented combinations of visual flow and support-surface manipulations to investigate the response of healthy adults to novel discordant sensorimotor conditions. We aimed to determine whether a relationship existed between subjects visual dependence and their postural stability and cognitive performance in a new discordant environment presented at the conclusion of training (Transfer Test). Our training system comprised a treadmill placed on a motion base facing a virtual visual scene that provided a variety of sensory challenges. Ten healthy adults completed 3 training sessions during which they walked on a treadmill at 1.1 m/s while receiving discordant support-surface and visual manipulations. At the first visit, in an analysis of normalized torso translation measured in a scene-movement-only condition, 3 of 10 subjects were classified as visually dependent. During the Transfer Test, all participants received a 2-minute novel exposure. In a combined measure of stride frequency and reaction time, the non-visually dependent subjects showed improved adaptation on the Transfer Test compared to their visually dependent counterparts. This finding suggests that individual differences in the ability to adapt to new sensorimotor conditions may be explained by individuals innate sensory biases. An accurate preflight assessment of crewmembers biases for visual dependence could be used to predict their propensities to adapt to novel sensory conditions. It may also facilitate the development of customized training regimens that could expedite adaptation to alternate gravitational environments.

  8. Arc Jet Facility Test Condition Predictions Using the ADSI Code

    NASA Technical Reports Server (NTRS)

    Palmer, Grant; Prabhu, Dinesh; Terrazas-Salinas, Imelda

    2015-01-01

    The Aerothermal Design Space Interpolation (ADSI) tool is used to interpolate databases of previously computed computational fluid dynamic solutions for test articles in a NASA Ames arc jet facility. The arc jet databases are generated using an Navier-Stokes flow solver using previously determined best practices. The arc jet mass flow rates and arc currents used to discretize the database are chosen to span the operating conditions possible in the arc jet, and are based on previous arc jet experimental conditions where possible. The ADSI code is a database interpolation, manipulation, and examination tool that can be used to estimate the stagnation point pressure and heating rate for user-specified values of arc jet mass flow rate and arc current. The interpolation is performed in the other direction (predicting mass flow and current to achieve a desired stagnation point pressure and heating rate). ADSI is also used to generate 2-D response surfaces of stagnation point pressure and heating rate as a function of mass flow rate and arc current (or vice versa). Arc jet test data is used to assess the predictive capability of the ADSI code.

  9. Electrical PR Interval Variation Predicts New Occurrence of Atrial Fibrillation in Patients With Frequent Premature Atrial Contractions

    PubMed Central

    Chun, Kwang Jin; Hwang, Jin Kyung; Park, Seung-Jung; On, Young Keun; Kim, June Soo; Park, Kyoung-Min

    2016-01-01

    Abstract Atrial fibrillation (AF) is associated with the autonomic nervous system (ANS), and fluctuation of autonomic tone is more prominent in patients with AF. As autonomic tone affects the heart rate (HR), and there is an inverse relationship between HR and PR interval, PR interval variation could be greater in patients with AF than in those without AF. The purpose of this study was to investigate the correlation between PR interval variation and new-onset AF in patients with frequent PACs. We retrospectively enrolled 207 patients with frequent PACs who underwent electrocardiographs at least 4 times during the follow-up period. The PR variation was calculated by subtracting the minimum PR interval from the maximum PR interval. The outcomes were new occurrence of AF and all-cause mortality during the follow-up period. During a median follow-up of 8.3 years, 24 patients (11.6%) developed new-onset AF. Univariate analysis showed that prolonged PR interval (PR interval > 200 ms, P = 0.021), long PR variation (PR variation > 36.5 ms, P = 0.018), and PR variation (P = 0.004) as a continuous variable were associated with an increased risk of AF. Cox regression analysis showed that prolonged PR interval (hazard ratio = 3.321, 95% CI 1.064–10.362, P = 0.039) and PR variation (hazard ratio = 1.013, 95% CI 1.002–1.024, P = 0.022) were independent predictors for new-onset AF. However, PR variation and prolonged PR interval were not associated with all-cause mortality (P = 0.465 and 0.774, respectively). PR interval variation and prolonged PR interval are independent risk factors for new-onset AF in patients with frequent PACs. However we were unable to determine a cut-off value of PR interval variation for new-onset AF. PMID:27057868

  10. Predicting Redox Conditions in Groundwater Using Statistical Techniques: Implications for Nitrate Transport in Groundwater and Streams

    NASA Astrophysics Data System (ADS)

    Tesoriero, A. J.; Terziotti, S.

    2014-12-01

    Nitrate trends in streams often do not match expectations based on recent nitrogen source loadings to the land surface. Groundwater discharge with long travel times has been suggested as the likely cause for these observations. The fate of nitrate in groundwater depends to a large extent on the occurrence of denitrification along flow paths. Because denitrification in groundwater is inhibited when dissolved oxygen (DO) concentrations are high, defining the oxic-suboxic interface has been critical in determining pathways for nitrate transport in groundwater and to streams at the local scale. Predicting redox conditions on a regional scale is complicated by the spatial variability of reaction rates. In this study, logistic regression and boosted classification tree analysis were used to predict the probability of oxic water in groundwater in the Chesapeake Bay watershed. The probability of oxic water (DO > 2 mg/L) was predicted by relating DO concentrations in over 3,000 groundwater samples to indicators of residence time and/or electron donor availability. Variables that describe position in the flow system (e.g., depth to top of the open interval), soil drainage and surficial geology were the most important predictors of oxic water. Logistic regression and boosted classification tree analysis correctly predicted the presence or absence of oxic conditions in over 75 % of the samples in both training and validation data sets. Predictions of the percentages of oxic wells in deciles of risk were very accurate (r2>0.9) in both the training and validation data sets. Depth to the bottom of the oxic layer was predicted and is being used to estimate the effect that groundwater denitrification has on stream nitrate concentrations and the time lag between the application of nitrogen at the land surface and its effect on streams.

  11. Susceptibility and predictability of conditions for preferential flow

    NASA Astrophysics Data System (ADS)

    Wang, Zhi; Feyen, Jan; Ritsema, Coen J.

    1998-09-01

    Preferential flow in the field might be caused by various factors and is difficult to observe in situ. This experimental study was designed to identify the combined effects of air entrapment, surface desaturation (suction head), soil layering, and water repellency (hydrophobicity) of the porous media on unstable preferential flow (or fingering) in the vadose zone. The predictability of unstable flow was studied on the basis of two existing criteria for gravity fingering: (1) a velocity criterion proposed by Hill and Parlange [1972] and (2) a pressure head criterion by Raats [1973] and Philip [1975]. Two-dimensional transparent chambers (60 cm high, 41.5 cm wide, and 2.8 cm thick and 90 cm deep, 74.5 cm wide, and 1.8 cm thick) were used to visualize water infiltration into a water-wettable sand, a water-wettable loam, differently layered sand and loam, and a water-repellent sand. The results suggested that infiltration into the homogeneous sand and a sand-over-loam system, without the effects of air entrapment and surface desaturation, was unconditionally stable. Infiltration into the loam was also stable as observed in the limited chambers. The flow was unconditionally unstable in a fine-over-coarse stratified sublayer and conditionally unstable in the homogeneous sand under the effects of air entrapment and surface desaturation. In multiple-layered systems, infiltration flow was semiunstable; fingers developed in the sand layer and were stabilized in the loam. In the repellent sand the wetting front was unstable under low ponding conditions; however, it was stabilized when the ponding depth exceeded the water-bubbling (entry) value of the hydrophobic medium. Both the velocity and pressure head criteria predicted fingering in the sand (layers) with the effects of gravity. However, the criteria failed to predict stable flow in the loam, indicating that the capillary (stabilizing) effects on the flow need to be included in theoretical developments. Finally, the

  12. Rubber yield prediction by meteorological conditions using mixed models and multi-model inference techniques

    NASA Astrophysics Data System (ADS)

    Golbon, Reza; Ogutu, Joseph Ochieng; Cotter, Marc; Sauerborn, Joachim

    2015-12-01

    Linear mixed models were developed and used to predict rubber ( Hevea brasiliensis) yield based on meteorological conditions to which rubber trees had been exposed for periods ranging from 1 day to 2 months prior to tapping events. Predictors included a range of moving averages of meteorological covariates spanning different windows of time before the date of the tapping events. Serial autocorrelation in the latex yield measurements was accounted for using random effects and a spatial generalization of the autoregressive error covariance structure suited to data sampled at irregular time intervals. Information theoretics, specifically the Akaike information criterion (AIC), AIC corrected for small sample size (AICc), and Akaike weights, was used to select models with the greatest strength of support in the data from a set of competing candidate models. The predictive performance of the selected best model was evaluated using both leave-one-out cross-validation (LOOCV) and an independent test set. Moving averages of precipitation, minimum and maximum temperature, and maximum relative humidity with a 30-day lead period were identified as the best yield predictors. Prediction accuracy expressed in terms of the percentage of predictions within a measurement error of 5 g for cross-validation and also for the test dataset was above 99 %.

  13. Operational seasonal and interannual predictions of ocean conditions

    NASA Technical Reports Server (NTRS)

    Leetmaa, Ants

    1992-01-01

    Dr. Leetmaa described current work at the U.S. National Meteorological Center (NMC) on coupled systems leading to a seasonal prediction system. He described the way in which ocean thermal data is quality controlled and used in a four dimensional data assimilation system. This consists of a statistical interpolation scheme, a primitive equation ocean general circulation model, and the atmospheric fluxes that are required to force this. This whole process generated dynamically consist thermohaline and velocity fields for the ocean. Currently routine weekly analyses are performed for the Atlantic and Pacific oceans. These analyses are used for ocean climate diagnostics and as initial conditions for coupled forecast models. Specific examples of output products were shown both in the Pacific and the Atlantic Ocean.

  14. Backward conditioning of tumor necrosis factor-α in a single trial: changing intervals between exposures to lipopolysaccharide and saccharin taste.

    PubMed

    Washio, Yukiko; Hayes, Linda J; Hunter, Kenneth W; Pritchard, Josh K

    2011-02-01

    The current study examined the effect of backward conditioning with three different time intervals between exposures to lipopolysaccharide (LPS) as the unconditioned stimulus (US) and saccharin taste in water as the potential conditioned stimulus (CS). Forty-eight naïve female BALB/c mice at three months of age served as subjects, divided into six groups. Four groups were assigned to Experiment 1 for the tumor necrosis factor alpha (TNF-α) measure, and the remaining two groups were used in Experiment 2 to measure taste aversion behavior. Both experiments employed a single trial. The timing of introduction to the saccharin taste varied between 3 min, 7 h, and 24 h following an LPS injection in Experiment 1. Experiment 2 employed the three-minute interval only. These intervals correspond to distinct immunological, physiological, and behavioral events induced by LPS. On the day after re-exposure to the saccharin taste, the TNF-α groups were challenged with LPS to test the LPS tolerance response. While backward conditioning of taste aversion behavior was not observed, some evidence of conditioned TNF-α response and subsequent development of LPS tolerance was observed with backward conditioning in a single trial. This exploratory study demonstrated that the effect of backward conditioning on conditioned TNF-α response and LPS tolerance response in a single trial depended on the timing of when a CS is presented after LPS exposure.

  15. Prediction of glass durability as a function of environmental conditions

    SciTech Connect

    Jantzen, C M

    1988-01-01

    A thermodynamic model of glass durability is applied to natural, ancient, and nuclear waste glasses. The durabilities of over 150 different natural and man-made glasses, including actual ancient Roman and Islamic glasses (Jalame ca. 350 AD, Nishapur 10-11th century AD and Gorgon 9-11th century AD), are compared. Glass durability is a function of the thermodynamic hydration free energy, ..delta..G/sub hyd/, which can be calculated from glass composition and solution pH. The durability of the most durable nuclear waste glasses examined was /approximately/10/sup 6/ years. The least durable waste glass formulations were comparable in durability to the most durable simulated medieval window glasses of /approximately/10/sup 3/ years. In this manner, the durability of nuclear waste glasses has been interpolated to be /approximately/10/sup 6/ years and no less than 10/sup 3/ years. Hydration thermodynamics have been shown to be applicable to the dissolution of glass in various natural environments. Groundwater-glass interactions relative to geologic disposal of nuclear waste, hydration rind dating of obsidians, andor other archeological studies can be modeled, e.g., the relative durabilities of six simulated medieval window glasses have been correctly predicted for both laboratory (one month) and burial (5 years) experiments. Effects of solution pH on glass dissolution has been determined experimentally for the 150 different glasses and can be predicted theoretically by hydration thermodynamics. The effects of solution redox on dissolution of glass matrix elements such as SI and B have shown to be minimal. The combined effects of solution pH and Eh have been described and unified by construction of thermodynamically calculated Pourbaix (pH-Eh) diagrams for glass dissolution. The Pourbaix diagrams have been quantified to describe glass dissolution as a function of environmental conditions by use of the data derived from hydration thermodynamics. 56 refs., 7 figs.

  16. Conditional Weather Resampling Method for Seasonal Ensemble Streamflow Prediction

    NASA Astrophysics Data System (ADS)

    Beckers, Joost; Weerts, Albrecht; Welles, Edwin

    2014-05-01

    Ensemble Streamflow Prediction (ESP) is a commonly used method for water resources planning on the seasonal time scale. The starting point for the ESP is the current state of the hydrological system, which is generated form a short historical simulation up to the time of forecast. Starting from this initial state, a hydrologic model is run to produce an ensemble of possible realizations of future streamflows, taking meteorological time series from historical years as input. It is assumed that these historical weather time series represent climatology. One disadvantage of the original ESP method is that an expected deviation from average climatology is not accounted for. Here, we propose a variation to the ESP, in which shorter periods from historical time years are resampled and assembled to generate additional possible realizations of future weather. The resampling is done in such a way as to incorporate statistical deviations from the average climate that are linked to climate modes, such as El Niño Southern Oscillation (ENSO) or Pacific Decadal Oscillation (PDO). These climate modes are known to affect the local weather in many regions around the world. The resampling of historical weather periods is conditioned on the climate mode indices, starting with the current climate index value and searching for historical years with similar climate indices. The resampled weather time series are used as input for the hydrological model, similar to the original ESP procedure. The method was implemented in the operational forecasting environment of Bonneville Power Administration (BPA), which based on Delft-FEWS. The method was run for 55 non-operational years of hindcasts (forecasts in retrospect) for the Columbia River in the North-West of the U.S. An increase in forecast skill up to 5% was found relative to the standard ESP for streamflow predictions at three test-locations.

  17. Predictive hydrogeochemical modelling of bauxite residue sand in field conditions.

    PubMed

    Wissmeier, Laurin; Barry, David A; Phillips, Ian R

    2011-07-15

    The suitability of residue sand (the coarse fraction remaining from Bayer's process of bauxite refining) for constructing the surface cover of closed bauxite residue storage areas was investigated. Specifically, its properties as a medium for plant growth are of interest to ensure residue sand can support a sustainable ecosystem following site closure. The geochemical evolution of the residue sand under field conditions, its plant nutrient status and soil moisture retention were studied by integrated modelling of geochemical and hydrological processes. For the parameterization of mineral reactions, amounts and reaction kinetics of the mineral phases natron, calcite, tricalcium aluminate, sodalite, muscovite and analcime were derived from measured acid neutralization curves. The effective exchange capacity for ion adsorption was measured using three independent exchange methods. The geochemical model, which accounts for mineral reactions, cation exchange and activity corrected solution speciation, was formulated in the geochemical modelling framework PHREEQC, and partially validated in a saturated-flow column experiment. For the integration of variably saturated flow with multi-component solute transport in heterogeneous 2D domains, a coupling of PHREEQC with the multi-purpose finite-element solver COMSOL was established. The integrated hydrogeochemical model was applied to predict water availability and quality in a vertical flow lysimeter and a cover design for a storage facility using measured time series of rainfall and evaporation from southwest Western Australia. In both scenarios the sand was fertigated and gypsum-amended. Results show poor long-term retention of fertilizer ions and buffering of the pH around 10 for more than 5 y of leaching. It was concluded that fertigation, gypsum amendment and rainfall leaching alone were insufficient to render the geochemical conditions of residue sand suitable for optimal plant growth within the given timeframe. The

  18. Conditioning rainfall-runoff model parameter space to reduce prediction uncertainty in ungauged basins

    NASA Astrophysics Data System (ADS)

    Visessri, S.; Mcintyre, N.

    2012-04-01

    Prediction of streamflow for ungauged basins is associated with large uncertainty arising from input data, model structure, and parameter values. This paper investigates how conditioning the prior parameter space using regionalised indices of streamflow affects the prediction uncertainty for ungauged basins. The main concept used is filtering out the rainfall-runoff model parameter sets that do not give estimates of streamflow indices close to the regionalised values. These values are calculated based on regression equations, and associated Gaussian error distributions, constructed from the relationship between physical catchment properties and streamflow indices at gauged sites. The performance of the model is measured by 1-NSE and 1-log(NSE) for high and low flow fitting accordingly, calculated on daily and on monthly intervals. Ability to capture streamflow and reduction in prediction uncertainty is judged by reliability and sharpness. The case study is the upper Ping River in Thailand and the spatially lumped IHACRES model is used. Using the range defined by the regression at 95% confidence level of rainfall-runoff elasticity and base flow index to condition the prior parameter space is useful for reducing streamflow prediction uncertainty. The reliability obtained from conditioned parameter space is high, 73-99%, but the sharpness is low, 7-31%. It is suggested in this study that concurrently reaching the high sharpness and reliability is difficult, maybe due to poor data quality and high spatial variability of daily rainfall in this tropical region. The model usually overestimates peak flow throughout the period of simulation. The prior range of parameter values also contributes to the performance of the model but in this case rather wide prior parameter ranges are needed to accommodate all possible parameter values for all subcatchments which have various physical characteristics. The use of runoff coefficient to reduce uncertainty in streamflow prediction

  19. Interval Between Hysterectomy and Start of Radiation Treatment Is Predictive of Recurrence in Patients With Endometrial Carcinoma

    SciTech Connect

    Cattaneo, Richard; Hanna, Rabbie K.; Jacobsen, Gordon; Elshaikh, Mohamed A.

    2014-03-15

    Purpose: Adjuvant radiation therapy (RT) has been shown to improve local control in patients with endometrial carcinoma. We analyzed the impact of the time interval between hysterectomy and RT initiation in patients with endometrial carcinoma. Methods and Materials: In this institutional review board-approved study, we identified 308 patients with endometrial carcinoma who received adjuvant RT after hysterectomy. All patients had undergone hysterectomy, oophorectomy, and pelvic and para-aortic lymph node evaluation from 1988 to 2010. Patients' demographics, pathologic features, and treatments were compared. The time interval between hysterectomy and the start of RT was calculated. The effects of time interval on recurrence-free (RFS), disease-specific (DSS), and overall survival (OS) were calculated. Following univariate analysis, multivariate modeling was performed. Results: The median age and follow-up for the study cohort was 65 years and 72 months, respectively. Eighty-five percent of the patients had endometrioid carcinoma. RT was delivered with high-dose-rate brachytherapy alone (29%), pelvic RT alone (20%), or both (51%). Median time interval to start RT was 42 days (range, 21-130 days). A total of 269 patients (74%) started their RT <9 weeks after undergoing hysterectomy (group 1) and 26% started ≥9 weeks after surgery (group 2). There were a total of 43 recurrences. Tumor recurrence was significantly associated with treatment delay of ≥9 weeks, with 5-year RFS of 90% for group 1 compared to only 39% for group 2 (P<.001). On multivariate analysis, RT delay of ≥9 weeks (P<.001), presence of lymphovascular space involvement (P=.001), and higher International Federation of Gynecology and Obstetrics grade (P=.012) were independent predictors of recurrence. In addition, RT delay of ≥9 weeks was an independent significant predictor for worse DSS and OS (P=.001 and P=.01, respectively). Conclusions: Delay in administering adjuvant RT after hysterectomy was

  20. Predictive nature of prefrontal theta oscillation on the performance of trace conditioned eyeblink responses in guinea pigs.

    PubMed

    Chen, Hao; Wang, Yi-jie; Yang, Li; Hu, Chen; Ke, Xian-feng; Fan, Zheng-li; Sui, Jian-feng; Hu, Bo

    2014-05-15

    Stimulus-evoked theta oscillations are observed in the medial prefrontal cortex (mPFC) when executing a variety of learning tasks. Here, we aimed to further determine whether spontaneous theta-band (5.0-10.0 Hz) oscillations in the mPFC predicted the subsequent behavioral performance in trace eyeblink conditioning (TEBC), in which the conditioned stimulus (CS) was separated from the unconditioned stimulus (US) by 500 ms trace interval. By recording local field potentials (LFP) signals in the guinea pigs performing the TEBC task, we found that, a higher mPFC relative theta ratio [theta/(delta+beta)] during the baseline (850-ms period prior to the onset of the CS) was predictive of higher magnitude and more adaptive timing rather than faster acquisition of trace conditioned eyeblink responses (CR). However, the prediction of baseline mPFC theta activity was time-limited to the well-learning stage. Additionally, the relative power of mPFC theta activity did not correlate with the CR performance if the trace interval between the CS and the US was shortened to 100 ms. These results suggest that the brain state in which the baseline mPFC theta activity is present or absent is detrimental for the subsequent performance of trace CRs especially when the asymptotic learning state is achieved.

  1. Ensemble Prediction of Flood Maps Under Uncertain Conditions

    NASA Astrophysics Data System (ADS)

    Pedrozo-Acuña, A.; Rodríguez-Rincón, J. P.; Brena-Naranjo, J. A. A.

    2014-12-01

    Hydro-meteorological hazards can have cascading effects and far-reaching implications on water security, with socio-economic and environmental consequences. Worldwide the magnitude of recent floods highlight the necessity to generate a better understanding on their causes and associated risk. An improved flood risk strategy should incorporate the communication of uncertain research results to decision-makers. Therefore, it is of paramount importance to generate a robust framework that enables its quantification. The purpose of this study is to investigate the propagation of meteorological uncertainty within a cascade modelling approach to flood mapping. The methodology is comprised of a Numerical Weather Prediction Model (NWP), a distributed rainfall-runoff model and a standard 2D hydrodynamic model. The cascade of models is used to reproduce an extreme flood event that took place in Southern Mexico, during September 2013. The event is selected as high quality field data (e.g. LiDAR; rain gauges) and satellite imagery are available. Uncertainty in the meteorological model (Weather Research and Forecasting model) is evaluated through the use of a multi-physics ensemble technique, which considers twelve parameterisation schemes to determine a given precipitation. The resulting precipitation fields are used as input in a distributed hydrological model, enabling the determination of different hydrographs associated to this event. Lastly, by means of a standard 2D hydrodynamic model, resulting hydrographs are used as forcing conditions to study the propagation of the meteorological uncertainty to an estimated flooded area. Results show the utility of the selected modelling approach to investigate error propagation within a cascade of models. Moreover, the error associated to the determination of the runoff, is showed to be lower than that obtained in the precipitation estimation suggesting that uncertainty do not necessarily increase within a model cascade.

  2. Coastal dispersion conditions near the southwestern tip of Africa: a system for evaluation and prediction.

    PubMed

    Jury, M R; Mulholland, M

    1988-04-01

    A system is presented to monitor the local meteorology and to predict the dispersion of effluents from a nuclear power station situated on the coast near the southwestern tip of Africa. A computerized weather station forms the basis of the system and provides spatial definition of wind profiles and dispersion indices near the coastal interface by interpolation between a sensor array. The meteorological system measures winds, temperature structure and turbulence indices at the 10-m level at five remote points and in the 10- to 80-m layer at the main coastal station. To provide a system for evaluation and prediction of effluent trajectories, a real-time three-dimensional puff dispersion model was developed. The meteorology input to the model is automatically verified and updated at 15-min intervals. Model results are presented under complex weather conditions to show how time and space changes in the local wind field are handled. To assist weather forecasters supporting the nuclear emergency plan, a simple tabular display enables a view of the dispersion climatology over 24-h (coastal) and 7-d (synoptic) cycles. These results are presented to contrast the different scales of circulation and for comparison within the nuclear industry to assist health physicists in deciding appropriate levels of meteorological support for emergency plans.

  3. Coastal dispersion conditions near the southwestern tip of Africa: a system for evaluation and prediction.

    PubMed

    Jury, M R; Mulholland, M

    1988-04-01

    A system is presented to monitor the local meteorology and to predict the dispersion of effluents from a nuclear power station situated on the coast near the southwestern tip of Africa. A computerized weather station forms the basis of the system and provides spatial definition of wind profiles and dispersion indices near the coastal interface by interpolation between a sensor array. The meteorological system measures winds, temperature structure and turbulence indices at the 10-m level at five remote points and in the 10- to 80-m layer at the main coastal station. To provide a system for evaluation and prediction of effluent trajectories, a real-time three-dimensional puff dispersion model was developed. The meteorology input to the model is automatically verified and updated at 15-min intervals. Model results are presented under complex weather conditions to show how time and space changes in the local wind field are handled. To assist weather forecasters supporting the nuclear emergency plan, a simple tabular display enables a view of the dispersion climatology over 24-h (coastal) and 7-d (synoptic) cycles. These results are presented to contrast the different scales of circulation and for comparison within the nuclear industry to assist health physicists in deciding appropriate levels of meteorological support for emergency plans. PMID:3350663

  4. Interval Training.

    ERIC Educational Resources Information Center

    President's Council on Physical Fitness and Sports, Washington, DC.

    Regardless of the type of physical activity used, interval training is simply repeated periods of physical stress interspersed with recovery periods during which activity of a reduced intensity is performed. During the recovery periods, the individual usually keeps moving and does not completely recover before the next exercise interval (e.g.,…

  5. Body condition predicts energy stores in apex predatory sharks

    PubMed Central

    Gallagher, Austin J.; Wagner, Dominique N.; Irschick, Duncan J.; Hammerschlag, Neil

    2014-01-01

    Animal condition typically reflects the accumulation of energy stores (e.g. fatty acids), which can influence an individual's decision to undertake challenging life-history events, such as migration and reproduction. Accordingly, researchers often use measures of animal body size and/or weight as an index of condition. However, values of condition, such as fatty acid levels, may not always reflect the physiological state of animals accurately. While the relationships between condition indices and energy stores have been explored in some species (e.g. birds), they have yet to be examined in top predatory fishes, which often undertake extensive and energetically expensive migrations. We used an apex predatory shark (Galeocerdo cuvier, the tiger shark) as a model species to evaluate the relationship between triglycerides (energy metabolite) and a metric of overall body condition. We captured, blood sampled, measured and released 28 sharks (size range 125–303 cm pre-caudal length). In the laboratory, we assayed each plasma sample for triglyceride values. We detected a positive and significant relationship between condition and triglyceride values (P < 0.02). This result may have conservation implications if the largest and highest-condition sharks are exploited in fisheries, because these individuals are likely to have the highest potential for successful reproduction. Our results suggest that researchers may use either plasma triglyceride values or an appropriate measure of body condition for assessing health in large sharks. PMID:27293643

  6. User guide to the UNC process and three utility programs for computation of nonlinear confidence and prediction intervals using MODFLOW-2000

    USGS Publications Warehouse

    Christensen, Steen; Cooley, Richard L.

    2006-01-01

    This report introduces and documents the Uncertainty (UNC) Process, a new Process in MODFLOW-2000 that calculates uncertainty measures for model parameters and for predictions produced by the model. Uncertainty measures can be computed by various methods, but when regression is applied to calibrate a model (for example when using the Parameter-Estimation Process of MODFLOW-2000) it is advantageous to also use regression-based methods to quantify uncertainty. For this reason the UNC Process computes (1) confidence intervals for parameters of the Parameter-Estimation Process and (2) confidence and prediction intervals for most types of functions that can be computed by a MODFLOW-2000 model calibrated by the Parameter-Estimation Process. The types of functions for which the Process works include hydraulic heads, hydraulic head differences, head-dependent flows computed by the head-dependent flow packages for drains (DRN6), rivers (RIV6), general-head boundaries (GHB6), streams (STR6), drain-return cells (DRT1), and constant-head boundaries (CHD), and for differences between flows computed by any of the mentioned flow packages. The UNC Process does not allow computation of intervals for the difference between flows computed by two different flow packages. The report also documents three programs, RESAN2-2k, BEALE2-2k, and CORFAC-2k, which are valuable for the evaluation of results from the Parameter-Estimation Process and for the preparation of input values for the UNC Process. RESAN2-2k and BEALE2-2k are significant updates of the residual analysis and modified Beale's measure programs first published by Cooley and Naff (1990) and later modified for use with MODFLOWP (Hill, 1994) and MODFLOW-2000 (Hill and others, 2000). CORFAC-2k is a new program that computes correction factors to be used by UNC.

  7. Predicted favorable visibility conditions for anomalous tails of comets

    NASA Technical Reports Server (NTRS)

    Sekanina, Z.

    1976-01-01

    Visibility conditions are used to list the comets that have displayed a sunward dust tail during the time of earth's passage through the orbital plane of the comet. A computer program describing the conditions for this type of antitail observability was applied to the Catalogue of Cometary Orbits (Marsden, 1975), starting with the comets of 1737. It is shown that only about 20-30% of the nearly parabolic comets that should have displayed an antitail at the node were actually observed to do so. There appears to be a general absence of antitails among the short period comets.

  8. Cut off values of laser fluorescence for different storage methods at different time intervals in comparison to frozen condition: A 1 year in vitro study

    PubMed Central

    Kaul, Rudra; Kaul, Vibhuti; Farooq, Riyaz; Wazir, Nikhil Dev; Khateeb, Shafayat Ullah; Malik, Altaf H; Masoodi, Ajaz Amin

    2014-01-01

    Aims: The aim of the following study is to evaluate the change in laser fluorescence (LF) values for extracted teeth stored in different solutions over 1 year period, to give cut-off values for different storage media at different time intervals to get them at par with the in vivo conditions and to see which medium gives best results with the least change in LF values and while enhancing the validity of DIAGNOdent in research. Materials and Methods: Ninety extracted teeth selected, from a pool of frozen teeth, were divided into nine groups of 10 each. Specimens in Groups 1-8 were stored in 1% chloramine, 10% formalin, 10% buffered formalin, 0.02% thymol, 0.12% chlorhexidine, 3% sodium hypochlorite, a commercially available saliva substitute-Wet Mouth (ICPA Pharmaceuticals) and normal saline respectively at 4°C. The last group was stored under frozen condition at −20°C without contact with any storage solution. DIAGNOdent was used to measure the change the LF values at day 30, 45, 60, 160 and 365. Statistical Analysis Used: The mean change in LF values in different storage mediums at different time intervals were compared using two-way ANOVA. Results: At the end of 1 year, significant decrease in fluorescence (P < 0.05) was observed in Groups 1-8. Maximum drop in LF values occurred between day 1 and 30. Group 9 (frozen specimens) did not significantly change their fluorescence response. Conclusions: An inevitable change in LF takes place due to various storage media commonly used in dental research at different time intervals. The values obtained from our study can remove the bias caused by the storage media and the values of LF thus obtained can hence be conveniently extrapolated to the in vivo condition. PMID:24778506

  9. Developing Landscape Level Indicators for Predicting Watershed Condition

    EPA Science Inventory

    Drainage basins (watersheds) exert a strong influence on the condition of water bodies such as streams and lakes. Watersheds and associated aquatic systems respond differently to stressors (e.g., land use change) or restoration activities depending on the climatic setting, bedroc...

  10. Predicting redox conditions in groundwater at a regional scale

    USGS Publications Warehouse

    Tesoriero, Anthony J.; Terziotti, Silvia; Abrams, Daniel B.

    2015-01-01

    Defining the oxic-suboxic interface is often critical for determining pathways for nitrate transport in groundwater and to streams at the local scale. Defining this interface on a regional scale is complicated by the spatial variability of reaction rates. The probability of oxic groundwater in the Chesapeake Bay watershed was predicted by relating dissolved O2 concentrations in groundwater samples to indicators of residence time and/or electron donor availability using logistic regression. Variables that describe surficial geology, position in the flow system, and soil drainage were important predictors of oxic water. The probability of encountering oxic groundwater at a 30 m depth and the depth to the bottom of the oxic layer were predicted for the Chesapeake Bay watershed. The influence of depth to the bottom of the oxic layer on stream nitrate concentrations and time lags (i.e., time period between land application of nitrogen and its effect on streams) are illustrated using model simulations for hypothetical basins. Regional maps of the probability of oxic groundwater should prove useful as indicators of groundwater susceptibility and stream susceptibility to contaminant sources derived from groundwater.

  11. Predicting Redox Conditions in Groundwater at a Regional Scale.

    PubMed

    Tesoriero, Anthony J; Terziotti, Silvia; Abrams, Daniel B

    2015-08-18

    Defining the oxic-suboxic interface is often critical for determining pathways for nitrate transport in groundwater and to streams at the local scale. Defining this interface on a regional scale is complicated by the spatial variability of reaction rates. The probability of oxic groundwater in the Chesapeake Bay watershed was predicted by relating dissolved O2 concentrations in groundwater samples to indicators of residence time and/or electron donor availability using logistic regression. Variables that describe surficial geology, position in the flow system, and soil drainage were important predictors of oxic water. The probability of encountering oxic groundwater at a 30 m depth and the depth to the bottom of the oxic layer were predicted for the Chesapeake Bay watershed. The influence of depth to the bottom of the oxic layer on stream nitrate concentrations and time lags (i.e., time period between land application of nitrogen and its effect on streams) are illustrated using model simulations for hypothetical basins. Regional maps of the probability of oxic groundwater should prove useful as indicators of groundwater susceptibility and stream susceptibility to contaminant sources derived from groundwater. PMID:26230618

  12. Analytical ice shape predictions for flight in natural icing conditions

    NASA Technical Reports Server (NTRS)

    Berkowitz, Brian M.; Riley, James T.

    1988-01-01

    LEWICE is an analytical ice prediction code that has been evaluated against icing tunnel data, but on a more limited basis against flight data. Ice shapes predicted by LEWICE is compared with experimental ice shapes accreted on the NASA Lewis Icing Research Aircraft. The flight data selected for comparison includes liquid water content recorded using a hot wire device and droplet distribution data from a laser spectrometer; the ice shape is recorded using stereo photography. The main findings are as follows: (1) An equivalent sand grain roughness correlation different from that used for LEWICE tunnel comparisons must be employed to obtain satisfactory results for flight; (2) Using this correlation and making no other changes in the code, the comparisons to ice shapes accreted in flight are in general as good as the comparisons to ice shapes accreted in the tunnel (as in the case of tunnel ice shapes, agreement is least reliable for large glaze ice shapes at high angles of attack); (3) In some cases comparisons can be somewhat improved by utilizing the code so as to take account of the variation of parameters such as liquid water content, which may vary significantly in flight.

  13. Predicting Redox Conditions in Groundwater at a Regional Scale.

    PubMed

    Tesoriero, Anthony J; Terziotti, Silvia; Abrams, Daniel B

    2015-08-18

    Defining the oxic-suboxic interface is often critical for determining pathways for nitrate transport in groundwater and to streams at the local scale. Defining this interface on a regional scale is complicated by the spatial variability of reaction rates. The probability of oxic groundwater in the Chesapeake Bay watershed was predicted by relating dissolved O2 concentrations in groundwater samples to indicators of residence time and/or electron donor availability using logistic regression. Variables that describe surficial geology, position in the flow system, and soil drainage were important predictors of oxic water. The probability of encountering oxic groundwater at a 30 m depth and the depth to the bottom of the oxic layer were predicted for the Chesapeake Bay watershed. The influence of depth to the bottom of the oxic layer on stream nitrate concentrations and time lags (i.e., time period between land application of nitrogen and its effect on streams) are illustrated using model simulations for hypothetical basins. Regional maps of the probability of oxic groundwater should prove useful as indicators of groundwater susceptibility and stream susceptibility to contaminant sources derived from groundwater.

  14. Paleostriatal lesions in the pigeon (Columba livia) potentiate classical conditioning: evidence from fixed-interval responding, free operant go-no-go discrimination, and alternation.

    PubMed

    Mitchell, J A

    1983-04-01

    The paleostriatum augmentatum was the major site of interest for four experiments in which pigeons were given bilateral electrolytic lesions. Experiment 1 investigated the effects of lesions on key pecking for reinforcement on a 1-min fixed-interval schedule. The lesions were found to increase total response rates, but response timing was not disrupted in paleostriatal pigeons. In Experiment 2, naive subjects were given variable-interval baseline training and, in contrast to the results of Experiment 1, paleostriatal lesions did not increase responding. Go-no-go discrimination, which followed baseline training, revealed enhanced positive behavioral contrast in paleostriatal subjects, which was explained in terms of additivity theory, and together, the results of Experiments 1 and 2 suggested potentiated classical conditioning and paleostriatal pigeons. In Experiment 3, naive subjects were given spatial alternation training, and performance was temporarily impaired following paleostriatal lesions. The same paleostriatal subjects showed superior differentiation performance in Experiment 4 with a classical go-no-go alternation procedure (which also suggested potentiated classical conditioning), and it is argued that disruption of (irrelevant) response-produced information may account for paleostriatal superiority.

  15. Prediction and modeling of effects on the QTc interval for clinical safety margin assessment, based on single-ascending-dose study data with AZD3839.

    PubMed

    Sparve, Erik; Quartino, Angelica L; Lüttgen, Maria; Tunblad, Karin; Gårdlund, Anna Teiling; Fälting, Johanna; Alexander, Robert; Kågström, Jens; Sjödin, Linnea; Bulgak, Alexander; Al-Saffar, Ahmad; Bridgland-Taylor, Matthew; Pollard, Chris; Swedberg, Michael D B; Vik, Torbjörn; Paulsson, Björn

    2014-08-01

    Corrected QT interval (QTc) prolongation in humans is usually predictable based on results from preclinical findings. This study confirms the signal from preclinical cardiac repolarization models (human ether-a-go-go-related gene, guinea pig monophasic action potential, and dog telemetry) on the clinical effects on the QTc interval. A thorough QT/QTc study is generally required for bioavailable pharmaceutical compounds to determine whether or not a drug shows a QTc effect above a threshold of regulatory interest. However, as demonstrated in this AZD3839 [(S)-1-(2-(difluoromethyl)pyridin-4-yl)-4-fluoro-1-(3-(pyrimidin-5-yl)phenyl)-1H-isoindol-3-amine hemifumarate] single-ascending-dose (SAD) study, high-resolution digital electrocardiogram data, in combination with adequate efficacy biomarker and pharmacokinetic data and nonlinear mixed effects modeling, can provide the basis to safely explore the margins to allow for robust modeling of clinical effect versus the electrophysiological risk marker. We also conclude that a carefully conducted SAD study may provide reliable data for effective early strategic decision making ahead of the thorough QT/QTc study.

  16. Coding of predicted reward omission by dopamine neurons in a conditioned inhibition paradigm.

    PubMed

    Tobler, Philippe N; Dickinson, Anthony; Schultz, Wolfram

    2003-11-12

    Animals learn not only about stimuli that predict reward but also about those that signal the omission of an expected reward. We used a conditioned inhibition paradigm derived from animal learning theory to train a discrimination between a visual stimulus that predicted reward (conditioned excitor) and a second stimulus that predicted the omission of reward (conditioned inhibitor). Performing the discrimination required attention to both the conditioned excitor and the inhibitor; however, dopamine neurons showed very different responses to the two classes of stimuli. Conditioned inhibitors elicited considerable depressions in 48 of 69 neurons (median of 35% below baseline) and minor activations in 29 of 69 neurons (69% above baseline), whereas reward-predicting excitors induced pure activations in all 69 neurons tested (242% above baseline), thereby demonstrating that the neurons discriminated between conditioned stimuli predicting reward versus nonreward. The discriminative responses to stimuli with differential reward-predicting but common attentional functions indicate differential neural coding of reward prediction and attention. The neuronal responses appear to reflect reward prediction errors, thus suggesting an extension of the correspondence between learning theory and activity of single dopamine neurons to the prediction of nonreward.

  17. Predictions of Daily Milk and Fat Yields, Major Groups of Fatty Acids, and C18:1 cis-9 from Single Milking Data without a Milking Interval

    PubMed Central

    Arnould, Valérie M. R.; Reding, Romain; Bormann, Jeanne; Gengler, Nicolas; Soyeurt, Hélène

    2015-01-01

    Simple Summary Reducing the frequency of milk recording decreases the costs of official milk recording. However, this approach can negatively affect the accuracy of predicting daily yields. Equations to predict daily yield from morning or evening data were developed in this study for fatty milk components from traits recorded easily by milk recording organizations. The correlation values ranged from 96.4% to 97.6% (96.9% to 98.3%) when the daily yields were estimated from the morning (evening) milkings. The simplicity of the proposed models which do not include the milking interval should facilitate their use by breeding and milk recording organizations. Abstract Reducing the frequency of milk recording would help reduce the costs of official milk recording. However, this approach could also negatively affect the accuracy of predicting daily yields. This problem has been investigated in numerous studies. In addition, published equations take into account milking intervals (MI), and these are often not available and/or are unreliable in practice. The first objective of this study was to propose models in which the MI was replaced by a combination of data easily recorded by dairy farmers. The second objective was to further investigate the fatty acids (FA) present in milk. Equations to predict daily yield from AM or PM data were based on a calibration database containing 79,971 records related to 51 traits [milk yield (expected AM, expected PM, and expected daily); fat content (expected AM, expected PM, and expected daily); fat yield (expected AM, expected PM, and expected daily; g/day); levels of seven different FAs or FA groups (expected AM, expected PM, and expected daily; g/dL milk), and the corresponding FA yields for these seven FA types/groups (expected AM, expected PM, and expected daily; g/day)]. These equations were validated using two distinct external datasets. The results obtained from the proposed models were compared to previously published results for

  18. Neural networks for probabilistic environmental prediction: Conditional Density Estimation Network Creation and Evaluation (CaDENCE) in R

    NASA Astrophysics Data System (ADS)

    Cannon, Alex J.

    2012-04-01

    A conditional density estimation network (CDEN) is a probabilistic extension of the standard multilayer perceptron neural network (MLP). A CDEN model allows users to estimate parameters of a specified probability density function conditioned upon values of a set of predictors using the MLP architecture. The result is a flexible model for the mean, the variance, exceedance probabilities, prediction intervals, etc. from the specified conditional distribution. Because the CDEN is based on the MLP, nonlinear relationships, including those involving complicated interactions between predictors, can be described by the modeling framework. CDEN models have been applied to a wide range of environmental prediction tasks, such as precipitation downscaling, extreme value analysis in hydrology, wind retrievals from satellites, and air quality forecasting. This paper describes the CaDENCE (Conditional Density Estimation Network Creation and Evaluation) package, which provides routines for creating and evaluating CDEN models in the R programming language. CaDENCE routines are demonstrated on a dataset consisting of suspended sediment concentrations and discharge measurements from the Fraser River at Hope, British Columbia, Canada.

  19. Interoceptive fear conditioning and panic disorder: the role of conditioned stimulus-unconditioned stimulus predictability.

    PubMed

    Acheson, Dean T; Forsyth, John P; Moses, Erica

    2012-03-01

    Interoceptive fear conditioning is at the core of contemporary behavioral accounts of panic disorder. Yet, to date only one study has attempted to evaluate interoceptive fear conditioning in humans (see Acheson, Forsyth, Prenoveau, & Bouton, 2007). That study used brief (physiologically inert) and longer-duration (panicogenic) inhalations of 20% CO(2)-enriched air as an interoceptive conditioned (CS) and unconditioned (US) stimulus and evaluated fear learning in three conditions: CS only, CS-US paired, and CS-US unpaired. Results showed fear conditioning in the paired condition, and fearful responding and resistance to extinction in an unpaired condition. The authors speculated that such effects may be due to difficulty discriminating between the CS and the US. The aims of the present study are to (a) replicate and expand this line of work using an improved methodology, and (b) clarify the role of CS-US discrimination difficulties in either potentiating or depotentiating fear learning. Healthy participants (N=104) were randomly assigned to one of four conditions: (a) CS only, (b) contingent CS-US pairings, (c) unpaired CS and US presentations, or (d) an unpaired "discrimination" contingency, which included an exteroceptive discrimination cue concurrently with CS onset. Electrodermal and self-report ratings served as indices of conditioned responding. Consistent with expectation, the paired contingency and unpaired contingencies yielded elevated fearful responding to the CS alone. Moreover, adding a discrimination cue to the unpaired contingency effectively attenuated fearful responding. Overall, findings are consistent with modern learning theory accounts of panic and highlight the role of interoceptive conditioning and unpredictability in the etiology of panic disorder.

  20. Interoceptive fear conditioning and panic disorder: the role of conditioned stimulus-unconditioned stimulus predictability.

    PubMed

    Acheson, Dean T; Forsyth, John P; Moses, Erica

    2012-03-01

    Interoceptive fear conditioning is at the core of contemporary behavioral accounts of panic disorder. Yet, to date only one study has attempted to evaluate interoceptive fear conditioning in humans (see Acheson, Forsyth, Prenoveau, & Bouton, 2007). That study used brief (physiologically inert) and longer-duration (panicogenic) inhalations of 20% CO(2)-enriched air as an interoceptive conditioned (CS) and unconditioned (US) stimulus and evaluated fear learning in three conditions: CS only, CS-US paired, and CS-US unpaired. Results showed fear conditioning in the paired condition, and fearful responding and resistance to extinction in an unpaired condition. The authors speculated that such effects may be due to difficulty discriminating between the CS and the US. The aims of the present study are to (a) replicate and expand this line of work using an improved methodology, and (b) clarify the role of CS-US discrimination difficulties in either potentiating or depotentiating fear learning. Healthy participants (N=104) were randomly assigned to one of four conditions: (a) CS only, (b) contingent CS-US pairings, (c) unpaired CS and US presentations, or (d) an unpaired "discrimination" contingency, which included an exteroceptive discrimination cue concurrently with CS onset. Electrodermal and self-report ratings served as indices of conditioned responding. Consistent with expectation, the paired contingency and unpaired contingencies yielded elevated fearful responding to the CS alone. Moreover, adding a discrimination cue to the unpaired contingency effectively attenuated fearful responding. Overall, findings are consistent with modern learning theory accounts of panic and highlight the role of interoceptive conditioning and unpredictability in the etiology of panic disorder. PMID:22304889

  1. Interval-valued random functions and the kriging of intervals

    SciTech Connect

    Diamond, P.

    1988-04-01

    Estimation procedures using data that include some values known to lie within certain intervals are usually regarded as problems of constrained optimization. A different approach is used here. Intervals are treated as elements of a positive cone, obeying the arithmetic of interval analysis, and positive interval-valued random functions are discussed. A kriging formalism for interval-valued data is developed. It provides estimates that are themselves intervals. In this context, the condition that kriging weights be positive is seen to arise in a natural way. A numerical example is given, and the extension to universal kriging is sketched.

  2. Short-term climate prediction for South-Western Siberia, based on comparison of reconstructed annual temperature variability between recent 430 yrs interval and Roman era warming

    NASA Astrophysics Data System (ADS)

    Kalugin, I.; Daryin, A.; Babich, V.; Myglan, V.; Ovchinikov, D.

    2009-04-01

    instrumental temperature and precipitation data for 1840-1991, with lake level measurements in Yailu station for 1930-2006, with local dendrochronologies and other time series. Before calibration linear scale was transformed to time scale using XRD values as a portion of water content for correction on each step. Both time series of proxies and environmental data were preliminary smoothed by the same run average according to desired time scale. Variability of annual temperature and of generalized climate index (Dev. T - Dev. P) [1] was considered to search analogues between recent and past time intervals. The best coincidence was obtained for intervals 310BC - 120AD and 1560-1990AD, where correlation coefficient amounted to 0, 44 for 2000 points. The more smoothing of source data was applied - the correlation was higher. Also, sum of single periodicities after spectral Fourier analysis of primary time series showed the same results. Taking into account this good coincidence, the prolongation of the past temperature profile (moved forward on 1870 years) is possible to consider as predicted time interval after AD1990. The authentic duration of prediction may be accepted not less than 10% of compared time intervals i.e. 40 years. Certainly, it concerns only to natural component of climate variability. Real excess of temperature ~2oC in AD1990-2005 is explained by human impact. [1] I. Kalugin et al. The 800 year long annual records of air temperature and precipitation over Southern Siberia inferred from high-resolution time-series of Teletskoye Lake sediments. Quaternary Research. 67 (2007) 400-410.

  3. Interval ridge regression (iRR) as a fast and robust method for quantitative prediction and variable selection applied to edible oil adulteration.

    PubMed

    Jović, Ozren; Smrečki, Neven; Popović, Zora

    2016-04-01

    A novel quantitative prediction and variable selection method called interval ridge regression (iRR) is studied in this work. The method is performed on six data sets of FTIR, two data sets of UV-vis and one data set of DSC. The obtained results show that models built with ridge regression on optimal variables selected with iRR significantly outperfom models built with ridge regression on all variables in both calibration (6 out of 9 cases) and validation (2 out of 9 cases). In this study, iRR is also compared with interval partial least squares regression (iPLS). iRR outperfomed iPLS in validation (insignificantly in 6 out of 9 cases and significantly in one out of 9 cases for p<0.05). Also, iRR can be a fast alternative to iPLS, especially in case of unknown degree of complexity of analyzed system, i.e. if upper limit of number of latent variables is not easily estimated for iPLS. Adulteration of hempseed (H) oil, a well known health beneficial nutrient, is studied in this work by mixing it with cheap and widely used oils such as soybean (So) oil, rapeseed (R) oil and sunflower (Su) oil. Binary mixture sets of hempseed oil with these three oils (HSo, HR and HSu) and a ternary mixture set of H oil, R oil and Su oil (HRSu) were considered. The obtained accuracy indicates that using iRR on FTIR and UV-vis data, each particular oil can be very successfully quantified (in all 8 cases RMSEP<1.2%). This means that FTIR-ATR coupled with iRR can very rapidly and effectively determine the level of adulteration in the adulterated hempseed oil (R(2)>0.99).

  4. Interval to Biochemical Failure Predicts Clinical Outcomes in Patients With High-Risk Prostate Cancer Treated by Combined-Modality Radiation Therapy

    SciTech Connect

    Shilkrut, Mark; McLaughlin, P. William; Merrick, Gregory S.; Vainshtein, Jeffrey M.; Feng, Felix Y.; Hamstra, Daniel A.

    2013-07-15

    Purpose: To validate the prognostic value of interval to biochemical failure (IBF) in patients with high-risk prostate cancer (HiRPCa) treated with combined-modality radiation therapy (CMRT) with or without androgen deprivation therapy (ADT). Methods and Materials: We conducted a retrospective review of HiRPCa (prostate-specific antigen >20 ng/mL, Gleason score [GS] 8-10, or clinical T stage T3-T4) treated with either dose-escalated external beam radiation therapy (EBRT) or CMRT. Interval to biochemical failure was classified as ≤18 or >18 months from the end of all therapy to the date of biochemical failure (BF). Kaplan-Meier methods and Cox proportional hazards regression were used to evaluate the prognostic value of IBF ≤18 months for distant metastasis (DM) and prostate cancer-specific mortality (PCSM). Results: Of 958 patients with a median follow-up of 63.2 months, 175 patients experienced BF. In those with BF, there were no differences in pretreatment clinical characteristics between the EBRT and CMRT groups, except for a higher proportion of patients with GS 8-10 in the CMRT group (70% vs 52%, P=.02). Median IBF after all therapy was 24.0 months (interquartile range 9.6-46.0) in the EBRT group and 18.9 months (interquartile range 9.2-34.5) in the CMRT group (P=.055). On univariate analysis, IBF ≤18 months was associated with increased risk of DM and PCSM in the entire cohort and the individual EBRT and CMRT groups. On multivariate analysis, only GS 9-10 and IBF ≤18 months, but not the radiation therapy regimen or ADT use, predicted DM (hazard ratio [HR] 3.7, P<.01, 95% confidence interval [CI] 1.4-10.3 for GS 9-10; HR 3.9, P<.0001, 95% CI 2.4-6.5 for IBF ≤18 months) and PCSM (HR 14.8, P<.009, 95% CI 2.0-110 for GS 9-10; HR 4.4, P<.0001, 95% CI 2.4-8.1 for IBF ≤18 months). Conclusions: Short IBF was highly prognostic for higher DM and PCSM in patients with HiRPCa. The prognostic value of IBF for DM and PCSM was not affected by the radiation

  5. Donor chimerism early after reduced-intensity conditioning hematopoietic stem cell transplantation predicts relapse and survival.

    PubMed

    Koreth, John; Kim, Haesook T; Nikiforow, Sarah; Milford, Edgar L; Armand, Philippe; Cutler, Corey; Glotzbecker, Brett; Ho, Vincent T; Antin, Joseph H; Soiffer, Robert J; Ritz, Jerome; Alyea, Edwin P

    2014-10-01

    The impact of early donor cell chimerism on outcomes of T cell-replete reduced-intensity conditioning (RIC) hematopoietic stem cell transplantation (HSCT) is ill defined. We evaluated day 30 (D30) and 100 (D100) total donor cell chimerism after RIC HSCT undertaken between 2002 and 2010 at our institution, excluding patients who died or relapsed before D30. When available, donor T cell chimerism was also assessed. The primary outcome was overall survival (OS). Secondary outcomes included progression-free survival (PFS), relapse, and nonrelapse mortality (NRM). We evaluated 688 patients with hematologic malignancies (48% myeloid and 52% lymphoid) and a median age of 57 years (range, 18 to 74) undergoing RIC HSCT with T cell-replete donor grafts (97% peripheral blood; 92% HLA-matched), with a median follow-up of 58.2 months (range, 12.6 to 120.7). In multivariable analysis, total donor cell and T cell chimerism at D30 and D100 each predicted RIC HSCT outcomes, with D100 total donor cell chimerism most predictive. D100 total donor cell chimerism <90% was associated with increased relapse (hazard ratio [HR], 2.54; 95% confidence interval [CI], 1.83 to 3.51; P < .0001), impaired PFS (HR, 2.01; 95% CI, 1.53 to 2.65; P < .0001), and worse OS (HR, 1.50; 95% CI, 1.11 to 2.04, P = .009), but not with NRM (HR, .76; 95% CI, .44 to 2.27; P = .33). There was no additional utility of incorporating sustained D30 to D100 total donor cell chimerism or T cell chimerism. Low donor chimerism early after RIC HSCT is an independent risk factor for relapse and impaired survival. Donor chimerism assessment early after RIC HSCT can prognosticate for long-term outcomes and help identify high-risk patient cohorts who may benefit from additional therapeutic interventions.

  6. Body Condition Indices Predict Reproductive Success but Not Survival in a Sedentary, Tropical Bird

    PubMed Central

    Milenkaya, Olga; Catlin, Daniel H.; Legge, Sarah; Walters, Jeffrey R.

    2015-01-01

    Body condition may predict individual fitness because those in better condition have more resources to allocate towards improving their fitness. However, the hypothesis that condition indices are meaningful proxies for fitness has been questioned. Here, we ask if intraspecific variation in condition indices predicts annual reproductive success and survival. We monitored a population of Neochmia phaeton (crimson finch), a sedentary, tropical passerine, for reproductive success and survival over four breeding seasons, and sampled them for commonly used condition indices: mass adjusted for body size, muscle and fat scores, packed cell volume, hemoglobin concentration, total plasma protein, and heterophil to lymphocyte ratio. Our study population is well suited for this research because individuals forage in common areas and do not hold territories such that variation in condition between individuals is not confounded by differences in habitat quality. Furthermore, we controlled for factors that are known to impact condition indices in our study population (e.g., breeding stage) such that we assessed individual condition relative to others in the same context. Condition indices that reflect energy reserves predicted both the probability of an individual fledging young and the number of young produced that survived to independence, but only during some years. Those that were relatively heavy for their body size produced about three times more independent young compared to light individuals. That energy reserves are a meaningful predictor of reproductive success in a sedentary passerine supports the idea that energy reserves are at least sometimes predictors of fitness. However, hematological indices failed to predict reproductive success and none of the indices predicted survival. Therefore, some but not all condition indices may be informative, but because we found that most indices did not predict any component of fitness, we question the ubiquitous interpretation of

  7. Body Condition Indices Predict Reproductive Success but Not Survival in a Sedentary, Tropical Bird.

    PubMed

    Milenkaya, Olga; Catlin, Daniel H; Legge, Sarah; Walters, Jeffrey R

    2015-01-01

    Body condition may predict individual fitness because those in better condition have more resources to allocate towards improving their fitness. However, the hypothesis that condition indices are meaningful proxies for fitness has been questioned. Here, we ask if intraspecific variation in condition indices predicts annual reproductive success and survival. We monitored a population of Neochmia phaeton (crimson finch), a sedentary, tropical passerine, for reproductive success and survival over four breeding seasons, and sampled them for commonly used condition indices: mass adjusted for body size, muscle and fat scores, packed cell volume, hemoglobin concentration, total plasma protein, and heterophil to lymphocyte ratio. Our study population is well suited for this research because individuals forage in common areas and do not hold territories such that variation in condition between individuals is not confounded by differences in habitat quality. Furthermore, we controlled for factors that are known to impact condition indices in our study population (e.g., breeding stage) such that we assessed individual condition relative to others in the same context. Condition indices that reflect energy reserves predicted both the probability of an individual fledging young and the number of young produced that survived to independence, but only during some years. Those that were relatively heavy for their body size produced about three times more independent young compared to light individuals. That energy reserves are a meaningful predictor of reproductive success in a sedentary passerine supports the idea that energy reserves are at least sometimes predictors of fitness. However, hematological indices failed to predict reproductive success and none of the indices predicted survival. Therefore, some but not all condition indices may be informative, but because we found that most indices did not predict any component of fitness, we question the ubiquitous interpretation of

  8. Age related vascular endothelial function following lifelong sedentariness: positive impact of cardiovascular conditioning without further improvement following low frequency high intensity interval training

    PubMed Central

    Grace, Fergal M.; Herbert, Peter; Ratcliffe, John W.; New, Karl J.; Baker, Julien S.; Sculthorpe, Nicholas F.

    2015-01-01

    Abstract Aging is associated with diffuse impairments in vascular endothelial function and traditional aerobic exercise is known to ameliorate these changes. High intensity interval training (HIIT) is effective at improving vascular function in aging men with existing disease, but its effectiveness remains to be demonstrated in otherwise healthy sedentary aging. However, the frequency of commonly used HIIT protocols may be poorly tolerated in older cohorts. Therefore, the present study investigated the effectiveness of lower frequency HIIT (LfHIIT) on vascular function in a cohort of lifelong sedentary (SED; n =22, age 62.7 ± 5.2 years) men compared with a positive control group of lifelong exercisers (LEX; n = 17, age 61.1 ± 5.4 years). The study consisted of three assessment phases; enrolment to the study (Phase A), following 6 weeks of conditioning exercise in SED (Phase B) and following 6 weeks of low frequency HIIT in both SED and LEX (LfHIIT; Phase C). Conditioning exercise improved FMD in SED (3.4 ± 1.5% to 4.9 ± 1.1%; P <0.01) such that the difference between groups on enrolment (3.4 ± 1.5% vs. 5.3 ± 1.4%; P <0.01) was abrogated. This was maintained but not further improved following LfHIIT in SED whilst FMD remained unaffected by LfHIIT in LEX. In conclusion, LfHIIT is effective at maintaining improvements in vascular function achieved during conditioning exercise in SED. LfHIIT is a well‐tolerated and effective exercise mode for reducing cardiovascular risk and maintaining but does not improve vascular function beyond that achieved by conditioning exercise in aging men, irrespective of fitness level. PMID:25626864

  9. High intensity interval training vs. high-volume running training during pre-season conditioning in high-level youth football: a cross-over trial.

    PubMed

    Faude, Oliver; Schnittker, Reinhard; Schulte-Zurhausen, Roman; Müller, Florian; Meyer, Tim

    2013-01-01

    We aimed at comparing the endurance effects of high-intensity interval training (HIIT) with high-volume running training (HVT) during pre-season conditioning in 20 high-level youth football players (15.9 (s 0.8) years). Players either conducted HVT or HIIT during the summer preparation period. During winter preparation they performed the other training programme. Before and after each training period several fitness tests were conducted: multi-stage running test (to assess the individual anaerobic threshold (IAT) and maximal running velocity (Vmax)), vertical jumping height, and straight sprinting. A significant increase from pre- to post-test was observed in IAT velocity (P < 0.001) with a greater increase after HVT (+0.8 km · h(-1) vs. +0.5 km · h(-1) after HIIT, P = 0.04). Maximal velocity during the incremental exercise test also slightly increased with time (P = 0.09). Forty per cent (HIIT) and 15% (HVT) of all players did not improve IAT beyond baseline variability. The players who did not respond to HIIT were significantly slower during 30 m sprinting than responders (P = 0.02). No further significant differences between responders and non-responders were observed. Jump heights deteriorated significantly after both training periods (P < 0.003). Both training programmes seem to be promising means to improve endurance capacity in high-level youth football players during pre-season conditioning.

  10. Predictions of Daily Milk and Fat Yields, Major Groups of Fatty Acids, and C18:1 cis-9 from Single Milking Data without a Milking Interval.

    PubMed

    Arnould, Valérie M R; Reding, Romain; Bormann, Jeanne; Gengler, Nicolas; Soyeurt, Hélène

    2015-07-31

    Reducing the frequency of milk recording would help reduce the costs of official milk recording. However, this approach could also negatively affect the accuracy of predicting daily yields. This problem has been investigated in numerous studies. In addition, published equations take into account milking intervals (MI), and these are often not available and/or are unreliable in practice. The first objective of this study was to propose models in which the MI was replaced by a combination of data easily recorded by dairy farmers. The second objective was to further investigate the fatty acids (FA) present in milk. Equations to predict daily yield from AM or PM data were based on a calibration database containing 79,971 records related to 51 traits [milk yield (expected AM, expected PM, and expected daily); fat content (expected AM, expected PM, and expected daily); fat yield (expected AM, expected PM, and expected daily; g/day); levels of seven different FAs or FA groups (expected AM, expected PM, and expected daily; g/dL milk), and the corresponding FA yields for these seven FA types/groups (expected AM, expected PM, and expected daily; g/day)]. These equations were validated using two distinct external datasets. The results obtained from the proposed models were compared to previously published results for models which included a MI effect. The corresponding correlation values ranged from 96.4% to 97.6% when the daily yields were estimated from the AM milkings and ranged from 96.9% to 98.3% when the daily yields were estimated from the PM milkings. The simplicity of these proposed models should facilitate their use by breeding and milk recording organizations.

  11. The importance of spring atmospheric conditions for predictions of the Arctic summer sea ice extent

    NASA Astrophysics Data System (ADS)

    Kapsch, Marie-Luise; Graversen, Rune G.; Economou, Theodoros; Tjernström, Michael

    2014-07-01

    Recent studies have shown that atmospheric processes in spring play an important role for the initiation of the summer ice melt and therefore may strongly influence the September sea ice concentration (SSIC). Here a simple statistical regression model based on only atmospheric spring parameters is applied in order to predict the SSIC over the major part of the Arctic Ocean. By using spring anomalies of downwelling longwave radiation or atmospheric water vapor as predictor variables, correlation coefficients between observed and predicted SSIC of up to 0.5 are found. These skills of seasonal SSIC predictions are similar to those obtained using more complex dynamical forecast systems, despite the fact that the simple model applied here takes neither information of the sea ice state, oceanic conditions nor feedback mechanisms during summer into account. The results indicate that a realistic representation of spring atmospheric conditions in the prediction system plays an important role for the predictive skills of a model system.

  12. Pharmacological aversion treatment of alcohol dependence. I. Production and prediction of conditioned alcohol aversion.

    PubMed

    Howard, M O

    2001-08-01

    Eighty-two hospitalized alcoholics receiving pharmacological aversion therapy (PAT) over a 10-day treatment interval completed cognitive, behavioral, and psychophysiological measures evaluating conditioned aversion to alcohol. Pre-post assessments provided convergent support for the efficacy of PAT vis-à-vis production of conditioned aversion to alcohol. Positive alcohol-related outcome expectancies were significantly reduced, whereas confidence that drinking could be avoided in various high-risk situations for consumption was increased following PAT. Behavioral and cardiac rate assessments revealed significant changes following PAT that were specific to alcoholic beverages and potentially reflective of conditioned alcohol aversion. Patients with more extensive pretreatment experiences with alcohol-associated nausea and greater involvement in antisocial conduct appeared to be less susceptible to the PAT conditioning protocol.

  13. Do morphological condition indices predict locomotor performance in the lizard Podarcis sicula?

    NASA Astrophysics Data System (ADS)

    Vervust, Bart; Lailvaux, Simon P.; Grbac, Irena; Van Damme, Raoul

    2008-09-01

    Biologists have developed a number of simple metrics to assess the health and energetic status of individual organisms and populations. While these condition indices have been widely used to address questions in evolutionary ecology and conservation biology, the ability of such indices to predict ecologically relevant locomotor performance abilities remains unknown. We show here that the functional links between six commonly used morphological condition indices and locomotor performance in two populations of Adriatic lizards ( Podarcis sicula) are weak at best. Indeed, no indices consistently predict either maximum sprint speed or maximum exertion across sexes, seasons or populations. These results cast doubt on the ecological relevance of morphological condition indices in terms of locomotor performance, measured in laboratory conditions, at least in this species. We urge caution in using condition indices as proxies for individual physiological or phenotypic quality in ecological and evolutionary studies.

  14. Condition Assessment and End-of-Life Prediction System for Electric Machines and Their Loads

    NASA Technical Reports Server (NTRS)

    Parlos, Alexander G.; Toliyat, Hamid A.

    2005-01-01

    An end-of-life prediction system developed for electric machines and their loads could be used in integrated vehicle health monitoring at NASA and in other government agencies. This system will provide on-line, real-time condition assessment and end-of-life prediction of electric machines (e.g., motors, generators) and/or their loads of mechanically coupled machinery (e.g., pumps, fans, compressors, turbines, conveyor belts, magnetic levitation trains, and others). In long-duration space flight, the ability to predict the lifetime of machinery could spell the difference between mission success or failure. Therefore, the system described here may be of inestimable value to the U.S. space program. The system will provide continuous monitoring for on-line condition assessment and end-of-life prediction as opposed to the current off-line diagnoses.

  15. Studies on effects of boundary conditions in confined turbulent flow predictions

    NASA Astrophysics Data System (ADS)

    Nallasamy, M.; Chen, C. P.

    1985-09-01

    The differences in k epsilon model predictions of plane and axisymmetric expansion flows is investigated. The prediction of the coaxial jet for different velocity ratios of the annular to central jet is presented. The effects of inlet kinetic energy and the energy dissipation rate profiles are investigated for swirling and nonswirling flows. The effects of expansion ration and Reynolds number on the reattachment length are also presented. The results show that the inlet k and epsilon profiles have the most significant effect on the reattachment length and flow redevelopment for the case of coaxial jet of high velocity ratio. A comparison of k epsilon model predictions for the pipe expansion flow by the PHOENICS and TEACH codes reveals some discrepancies in the predicted results. TEACH prediction seems to produce unrealistic kinetic energy profiles in some regions of the flow. PHOENICS code produces a long tail in the recirculation region under certain conditions.

  16. ACCEPT: Introduction of the Adverse Condition and Critical Event Prediction Toolbox

    NASA Technical Reports Server (NTRS)

    Martin, Rodney A.; Santanu, Das; Janakiraman, Vijay Manikandan; Hosein, Stefan

    2015-01-01

    The prediction of anomalies or adverse events is a challenging task, and there are a variety of methods which can be used to address the problem. In this paper, we introduce a generic framework developed in MATLAB (sup registered mark) called ACCEPT (Adverse Condition and Critical Event Prediction Toolbox). ACCEPT is an architectural framework designed to compare and contrast the performance of a variety of machine learning and early warning algorithms, and tests the capability of these algorithms to robustly predict the onset of adverse events in any time-series data generating systems or processes.

  17. Linear Superposition and Prediction of Bacterial Promoter Activity Dynamics in Complex Conditions

    PubMed Central

    Rothschild, Daphna; Dekel, Erez; Hausser, Jean; Bren, Anat; Aidelberg, Guy; Szekely, Pablo; Alon, Uri

    2014-01-01

    Bacteria often face complex environments. We asked how gene expression in complex conditions relates to expression in simpler conditions. To address this, we obtained accurate promoter activity dynamical measurements on 94 genes in E. coli in environments made up of all possible combinations of four nutrients and stresses. We find that the dynamics across conditions is well described by two principal component curves specific to each promoter. As a result, the promoter activity dynamics in a combination of conditions is a weighted average of the dynamics in each condition alone. The weights tend to sum up to approximately one. This weighted-average property, called linear superposition, allows predicting the promoter activity dynamics in a combination of conditions based on measurements of pairs of conditions. If these findings apply more generally, they can vastly reduce the number of experiments needed to understand how E. coli responds to the combinatorially huge space of possible environments. PMID:24809350

  18. Piglet birth weight and litter uniformity: effects of weaning-to-pregnancy interval and body condition changes in sows of different parities and crossbred lines.

    PubMed

    Wientjes, J G M; Soede, N M; Knol, E F; van den Brand, H; Kemp, B

    2013-05-01

    Piglet birth weight and litter uniformity were studied in sows of different parities and crossbred lines in relation to: 1) weaning-to-pregnancy interval (WPI) and 2) sow body condition changes (in BW and backfat thickness) during lactation and gestation in sows with a short WPI (≤7d). At the Institute for Pig Genetics (IPG) research farm, individual piglet birth weights and sow body condition (BW and backfat thickness at farrowing and weaning) were measured for 949 TOPIGS20 and 889 TOPIGS40 sows with >4 total born piglets, inseminated between 2003 and 2011. In all analyses, mean piglet birth weight and birth weight SD and CV were corrected for total number born. Total number born was greater in sows with a WPI of 8 to 21 d (+1.2 piglets; n = 72) and >21 d (+0.7 piglets; n = 182), compared with sows with a WPI ≤7 d (P < 0.01; n = 1,584). Mean piglet birth weight was not affected by WPI. Birth weight SD (-23 g) and CV (-1.7%) were lower in sows with a WPI >21 d, compared with sows with a WPI ≤7 d (P < 0.01). Effects of WPI were independent of sow parity. Effects of body condition changes in sows with a WPI ≤7 d were studied separately in TOPIGS20 sows inseminated between 2006 and 2011 (n = 808), and in TOPIGS40 sows inseminated between 2003 and 2008 (n = 747). Sow body condition loss during lactation was not related with subsequent total number born or mean piglet birth weight. Only in TOPIGS20 sows, more BW loss during lactation was related with greater subsequent birth weight SD (β = 0.83 g/kg, P < 0.01; β = 1.62 g/%, P < 0.01). Additionally, more backfat loss during lactation was related with greater subsequent birth weight SD (β = 5.11 g/mm, P < 0.01) and CV (β = 0.36%/mm, P < 0.01), independent of sow parity. Sow BW increase during gestation was negatively related with total number born [TOPIGS20: β = -0.06 and -0.05 piglet/kg BW increase for parity 2 (P < 0.01), and 3 and 4 (P < 0.01), respectively; TOPIGS40: β = -0.04 piglet/kg BW increase (P

  19. Do sexual ornaments demonstrate heightened condition-dependent expression as predicted by the handicap hypothesis?

    PubMed Central

    Cotton, Samuel; Fowler, Kevin; Pomiankowski, Andrew

    2004-01-01

    The handicap hypothesis of sexual selection predicts that sexual ornaments have evolved heightened condition-dependent expression. The prediction has only recently been subject to experimental investigation. Many of the experiments are of limited value as they: (i) fail to compare condition dependence in sexual ornaments with suitable non-sexual trait controls; (ii) do not adequately account for body size variation; and (iii) typically consider no stress and extreme stress manipulations rather than a range of stresses similar to those experienced in nature. There is also a dearth of experimental studies investigating the genetic basis of condition dependence. Despite the common claim that sexual ornaments are condition-dependent, the unexpected conclusion from our literature review is that there is little support from well-designed experiments. PMID:15255094

  20. Appetite and gut hormone responses to moderate-intensity continuous exercise versus high-intensity interval exercise, in normoxic and hypoxic conditions.

    PubMed

    Bailey, Daniel P; Smith, Lindsey R; Chrismas, Bryna C; Taylor, Lee; Stensel, David J; Deighton, Kevin; Douglas, Jessica A; Kerr, Catherine J

    2015-06-01

    This study investigated the effects of continuous moderate-intensity exercise (MIE) and high-intensity interval exercise (HIIE) in combination with short exposure to hypoxia on appetite and plasma concentrations of acylated ghrelin, peptide YY (PYY), and glucagon-like peptide-1 (GLP-1). Twelve healthy males completed four, 2.6 h trials in a random order: (1) MIE-normoxia, (2) MIE-hypoxia, (3) HIIE-normoxia, and (4) HIIE-hypoxia. Exercise took place in an environmental chamber. During MIE, participants ran for 50 min at 70% of altitude-specific maximal oxygen uptake (V˙O2max) and during HIIE performed 6 × 3 min running at 90% V˙O2max interspersed with 6 × 3 min active recovery at 50% V˙O2max with a 7 min warm-up and cool-down at 70% V˙O2max (50 min total). In hypoxic trials, exercise was performed at a simulated altitude of 2980 m (14.5% O2). Exercise was completed after a standardised breakfast. A second meal standardised to 30% of participants' daily energy requirements was provided 45 min after exercise. Appetite was suppressed more in hypoxia than normoxia during exercise, post-exercise, and for the full 2.6 h trial period (linear mixed modelling, p <0.05). Plasma acylated ghrelin concentrations were lower in hypoxia than normoxia post-exercise and for the full 2.6 h trial period (p <0.05). PYY concentrations were higher in HIIE than MIE under hypoxic conditions during exercise (p = 0.042). No differences in GLP-1 were observed between conditions (p > 0.05). These findings demonstrate that short exposure to hypoxia causes suppressions in appetite and plasma acylated ghrelin concentrations. Furthermore, appetite responses to exercise do not appear to be influenced by exercise modality.

  1. A multivariate conditional model for streamflow prediction and spatial precipitation refinement

    NASA Astrophysics Data System (ADS)

    Liu, Zhiyong; Zhou, Ping; Chen, Xiuzhi; Guan, Yinghui

    2015-10-01

    The effective prediction and estimation of hydrometeorological variables are important for water resources planning and management. In this study, we propose a multivariate conditional model for streamflow prediction and the refinement of spatial precipitation estimates. This model consists of high dimensional vine copulas, conditional bivariate copula simulations, and a quantile-copula function. The vine copula is employed because of its flexibility in modeling the high dimensional joint distribution of multivariate data by building a hierarchy of conditional bivariate copulas. We investigate two cases to evaluate the performance and applicability of the proposed approach. In the first case, we generate one month ahead streamflow forecasts that incorporate multiple predictors including antecedent precipitation and streamflow records in a basin located in South China. The prediction accuracy of the vine-based model is compared with that of traditional data-driven models such as the support vector regression (SVR) and the adaptive neuro-fuzzy inference system (ANFIS). The results indicate that the proposed model produces more skillful forecasts than SVR and ANFIS. Moreover, this probabilistic model yields additional information concerning the predictive uncertainty. The second case involves refining spatial precipitation estimates derived from the tropical rainfall measuring mission precipitationproduct for the Yangtze River basin by incorporating remotely sensed soil moisture data and the observed precipitation from meteorological gauges over the basin. The validation results indicate that the proposed model successfully refines the spatial precipitation estimates. Although this model is tested for specific cases, it can be extended to other hydrometeorological variables for predictions and spatial estimations.

  2. Predicting failure using conditioning on damage history: Demonstration on percolation and hierarchical fiber bundles

    SciTech Connect

    Andersen, J.V.; Sornette, D.

    2005-11-01

    We formulate the problem of probabilistic predictions of global failure in the simplest possible model based on site percolation and on one of the simplest models of time-dependent rupture, a hierarchical fiber bundle model. We show that conditioning the predictions on the knowledge of the current degree of damage (occupancy density p or number and size of cracks) and on some information on the largest cluster improves significantly the prediction accuracy, in particular by allowing one to identify those realizations which have anomalously low or large clusters (cracks). We quantify the prediction gains using two measures, the relative specific information gain (which is the variation of entropy obtained by adding new information) and the root mean square of the prediction errors over a large ensemble of realizations. The bulk of our simulations have been obtained with the two-dimensional site percolation model on a lattice of size LxL=20x20 and hold true for other lattice sizes. For the hierarchical fiber bundle model, conditioning the measures of damage on the information of the location and size of the largest crack extends significantly the critical region and the prediction skills. These examples illustrate how ongoing damage can be used as a revelation of both the realization-dependent preexisting heterogeneity and the damage scenario undertaken by each specific sample.

  3. Posterior Predictive Checks for Conditional Independence between Response Time and Accuracy

    ERIC Educational Resources Information Center

    Bolsinova, Maria; Tijmstra, Jesper

    2016-01-01

    Conditional independence (CI) between response time and response accuracy is a fundamental assumption of many joint models for time and accuracy used in educational measurement. In this study, posterior predictive checks (PPCs) are proposed for testing this assumption. These PPCs are based on three discrepancy measures reflecting different…

  4. Impact of in-consistency between the climate model and its initial conditions on climate prediction

    NASA Astrophysics Data System (ADS)

    Liu, Xueyuan; Köhl, Armin; Stammer, Detlef; Masuda, Shuhei; Ishikawa, Yoichi; Mochizuki, Takashi

    2016-05-01

    We investigated the influence of dynamical in-consistency of initial conditions on the predictive skill of decadal climate predictions. The investigation builds on the fully coupled global model "Coupled GCM for Earth Simulator" (CFES). In two separate experiments, the ocean component of the coupled model is full-field initialized with two different initial fields from either the same coupled model CFES or the GECCO2 Ocean Synthesis while the atmosphere is initialized from CFES in both cases. Differences between both experiments show that higher SST forecast skill is obtained when initializing with coupled data assimilation initial conditions (CIH) instead of those from GECCO2 (GIH), with the most significant difference in skill obtained over the tropical Pacific at lead year one. High predictive skill of SST over the tropical Pacific seen in CIH reflects the good reproduction of El Niño events at lead year one. In contrast, GIH produces additional erroneous El Niño events. The tropical Pacific skill differences between both runs can be rationalized in terms of the zonal momentum balance between the wind stress and pressure gradient force, which characterizes the upper equatorial Pacific. In GIH, the differences between the oceanic and atmospheric state at initial time leads to imbalance between the zonal wind stress and pressure gradient force over the equatorial Pacific, which leads to the additional pseudo El Niño events and explains reduced predictive skill. The balance can be reestablished if anomaly initialization strategy is applied with GECCO2 initial conditions and improved predictive skill in the tropical Pacific is observed at lead year one. However, initializing the coupled model with self-consistent initial conditions leads to the highest skill of climate prediction in the tropical Pacific by preserving the momentum balance between zonal wind stress and pressure gradient force along the equatorial Pacific.

  5. Corrosion fatigue behavior and life prediction method under changing temperature condition

    SciTech Connect

    Kanasaki, Hiroshi; Hirano, Akihiko; Iida, Kunihiro; Asada, Yasuhide

    1997-12-01

    Axially strain controlled low cycle fatigue tests of a carbon steel in oxygenated high temperature water were carried out under changing temperature conditions. Two patterns of triangular wave were selected for temperature cycling. One was in-phase pattern synchronizing with strain cycling and the other was an out-of-phase pattern in which temperature was changed in anti-phase to the strain cycling. The fatigue life under changing temperature condition was in the range of the fatigue life under various constant temperature within the range of the changing temperature. The fatigue life of in-phase pattern was equivalent to that of out-of-phase pattern. The corrosion fatigue life prediction method was proposed for changing temperature condition, and was based on the assumption that the fatigue damage increased in linear proportion to increment of strain during cycling. The fatigue life predicted by this method was in good agreement with the test results.

  6. Aerosol speciation and mass prediction from toluene oxidation under high NO x conditions

    NASA Astrophysics Data System (ADS)

    Kelly, Janya L.; Michelangeli, Diane V.; Makar, Paul A.; Hastie, Donald R.; Mozurkewich, Michael; Auld, Janeen

    2010-01-01

    A kinetically based gas-particle partitioning box model is used to highlight the importance of parameter representation in the prediction of secondary organic aerosol (SOA) formation following the photo-oxidation of toluene. The model is initialized using experimental data from York University's indoor smog chamber and provides a prediction of the total aerosol yield and speciation. A series of model sensitivity experiments were performed to study the aerosol speciation and mass prediction under high NO x conditions (VOC/NO x = 0.2). Sensitivity experiments indicate vapour pressure estimation to be a large area of weakness in predicting aerosol mass, creating an average total error range of 70 μg m -3 (range of 5-145 μg m -3), using two different estimation methods. Aerosol speciation proved relatively insensitive to changes in vapour pressure. One species, 3-methyl-6-nitro-catechol, dominated the aerosol phase regardless of the vapour pressure parameterization used and comprised 73-88% of the aerosol by mass. The dominance is associated with the large concentration of 3-methyl-6-nitro-catechol in the gas-phase. The high NO x initial conditions of this study suggests that the predominance of 3-methyl-6-nitro-catechol likely results from the cresol-forming branch in the Master Chemical Mechanism taking a significant role in secondary organic aerosol formation under high NO x conditions. Further research into the yields and speciation leading to this reaction product is recommended.

  7. Bio-predictive tablet disintegration: effect of water diffusivity, fluid flow, food composition and test conditions.

    PubMed

    Radwan, Asma; Wagner, Manfred; Amidon, Gordon L; Langguth, Peter

    2014-06-16

    Food intake may delay tablet disintegration. Current in vitro methods have little predictive potential to account for such effects. The effect of a variety of factors on the disintegration of immediate release tablets in the gastrointestinal tract has been identified. They include viscosity of the media, precipitation of food constituents on the surface of the tablet and reduction of water diffusivity in the media as well as changes in the hydrodynamics in the surrounding media of the solid dosage form. In order to improve the predictability of food affecting the disintegration of a dosage form, tablet disintegration in various types of a liquefied meal has been studied under static vs. dynamic (agitative) conditions. Viscosity, water diffusivity, osmolality and Reynolds numbers for the different media were characterized. A quantitative model is introduced which predicts the influence of the Reynolds number in the tablet disintegration apparatus on the disintegration time. Viscosity, water diffusivity and media flow velocity are shown to be important factors affecting dosage form disintegration. The results suggest the necessity of considering these parameters when designing a predictive model for simulating the in vivo conditions. Based on these experiments and knowledge on in vivo hydrodynamics in the GI tract, it is concluded that the disintegration tester under current pharmacopoeial conditions is operated in an unphysiological mode and no bioprediction may be derived. Recommendations regarding alternative mode of operation are made.

  8. Objective measures for predicting speech intelligibility in noisy conditions based on new band-importance functions

    PubMed Central

    Ma, Jianfen; Hu, Yi; Loizou, Philipos C.

    2009-01-01

    The articulation index (AI), speech-transmission index (STI), and coherence-based intelligibility metrics have been evaluated primarily in steady-state noisy conditions and have not been tested extensively in fluctuating noise conditions. The aim of the present work is to evaluate the performance of new speech-based STI measures, modified coherence-based measures, and AI-based measures operating on short-term (30 ms) intervals in realistic noisy conditions. Much emphasis is placed on the design of new band-importance weighting functions which can be used in situations wherein speech is corrupted by fluctuating maskers. The proposed measures were evaluated with intelligibility scores obtained by normal-hearing listeners in 72 noisy conditions involving noise-suppressed speech (consonants and sentences) corrupted by four different maskers (car, babble, train, and street interferences). Of all the measures considered, the modified coherence-based measures and speech-based STI measures incorporating signal-specific band-importance functions yielded the highest correlations (r=0.89–0.94). The modified coherence measure, in particular, that only included vowel∕consonant transitions and weak consonant information yielded the highest correlation (r=0.94) with sentence recognition scores. The results from this study clearly suggest that the traditional AI and STI indices could benefit from the use of the proposed signal- and segment-dependent band-importance functions. PMID:19425678

  9. Defining boundary conditions for RANS predictions of urban flows using mesoscale simulations

    NASA Astrophysics Data System (ADS)

    Garcia Sanchez, Clara; Gorle, Catherine; van Beeck, Jeroen

    2015-11-01

    Pollutant dispersion and wind flows in urban canopies are major concerns for human health and energy, and the complex nature of the flow and transport processes remains a challenge when using Computational Fluid Dynamics (CFD) to predict wind flows. The definition of the inflow boundary condition in Reynolds-Averaged Navier-Stokes simulations (RANS) is one of the uncertainties that will strongly influence the prediction of the flow field, and thus, the dispersion pattern. The goal of the work presented is to define a methodology that improves the level of realism in the inflow condition for RANS simulations by accounting for larger mesoscale effects. The Weather Research and Forecasting model (WRF) is used to forecast mesoscale flow patterns, and two different approaches are used to define inflow conditions for the RANS simulations performed with OpenFOAM: 1) WRF variables such as local velocity magnitude, ABL height and friction velocity are directly interpolated onto the boundaries of the CFD domain; 2) WRF predictions for the geostrophic wind and friction velocity are applied as a forcing boundary condition. Simulations of the Joint Urban 2003 experimental campaign in Oklahoma City have been performed using both approaches and a comparison of the results will be presented.

  10. Assessing predictive capacity and conditional independence of landslide predisposing factors for shallow landslides susceptibility models

    NASA Astrophysics Data System (ADS)

    Pereira, S.; Zêzere, J. L.; Bateira, C.

    2012-04-01

    The aim of this study is to identify the landslide predisposing factors combination, using a bivariate statistical model that best predict landslide susceptibility. The best predictive model should have a good performance in terms of suitability and predictive power, and should be based on landslide predisposing factors that are conditionally independent. The study area is the Santa Marta de Penaguião council (70 km2) located in the Northern Portugal. Several destructive landslides occurred in this area in the last decades promoting landscape degradation and other negative human and economic impacts. A landslide inventory was built in 2005-2009 using aerial photo-interpretation (1/5.000 scale) and field work validation. This inventory contains 767 shallow translational slides. The landslide density is 11 events/square kilometre, and each landslide has, on average, 136 m2 and the depth of the slip surface typically ranges from 1 to 1.5 m. The landslide layer was crossed individually with seven landslide predisposing factors (Aspect; Curvature; Slope Angle; Geomorphological Units; Land Use; Inverse Wetness Index; Lithology) and each class within each predisposing theme was weighted using the Information Value Method. In order to identify the best combination of landslide predisposing factors, all possible combinations were tested which resulted in 120 predictive models. The goodness of fit of each landslide susceptibility model was evaluated by constructing the Success Rate Curves and by computing the Area Under the Curve (AUC). The best landslide susceptibility model was selected according to the model degree of fitness and on the basis of a conditional independence criterion. Two tests were performed to the entire dataset to assess conditional independence: the Overall Conditional Independence (OCI) and the Agterberg & Cheng Conditional Independence Test (ACCIT) (Agterberg and Cheng, 2002). The best landslide susceptibility model was constructed with only three

  11. Prediction suppression in monkey inferotemporal cortex depends on the conditional probability between images.

    PubMed

    Ramachandran, Suchitra; Meyer, Travis; Olson, Carl R

    2016-01-01

    When monkeys view two images in fixed sequence repeatedly over days and weeks, neurons in area TE of the inferotemporal cortex come to exhibit prediction suppression. The trailing image elicits only a weak response when presented following the leading image that preceded it during training. Induction of prediction suppression might depend either on the contiguity of the images, as determined by their co-occurrence and captured in the measure of joint probability P(A,B), or on their contingency, as determined by their correlation and as captured in the measures of conditional probability P(A|B) and P(B|A). To distinguish between these possibilities, we measured prediction suppression after imposing training regimens that held P(A,B) constant but varied P(A|B) and P(B|A). We found that reducing either P(A|B) or P(B|A) during training attenuated prediction suppression as measured during subsequent testing. We conclude that prediction suppression depends on contingency, as embodied in the predictive relations between the images, and not just on contiguity, as embodied in their co-occurrence.

  12. Testing of the hydromechanical prediction model of soil erosion under the conditions of Georgia

    NASA Astrophysics Data System (ADS)

    Gogichaishvili, G. P.; Kirvalidze, D. R.; Gorjomeladze, O. L.

    2014-09-01

    A hydromechanical model for predicting water (rain-induced) soil erosion was tested on the experimental plots of the Research Institute of Tea and Subtropical Crops in Zendidi village (the Ajara Autonomous Republic) and the Sabashvili Institute of Soil Science, Agrochemistry, and Melioration in Khevi and Kitskhi villages (Upper Imeretia, Western Georgia). A comparison of factual and predicted values of rain-induced erosion for the plots with permanent black fallow showed that the model overestimated the average annual soil loss for the yellow-brown strongly eroded soil in Zendidi village by 23.22 t/ha (133%). This value ranged in different years from 18 to 1052%. For the plots with corn, the predicted value of annual erosion was by 16.94 t/ha higher than the factual value (overestimation of 488%). A comparison of factual and predicted values of rainfall erosion for the plots under sprinkling irrigation also showed that the predicted soil loss was higher than the factual one by 4.14-30.40 t/ha for corn, 6.76-11.14 t/ha for winter wheat, and 15.75-24.12 t/ha for the plots with stubble of winter wheat and barley. Thus, the hydromechanical model for predicting water erosion inadequately describes it under the conditions of Western Georgia and has to be refined.

  13. Predictions of structural integrity of steam generator tubes under normal operating, accident, and severe accident conditions

    SciTech Connect

    Majumdar, S.

    1996-09-01

    Available models for predicting failure of flawed and unflawed steam generator tubes under normal operating, accident, and severe accident conditions are reviewed. Tests conducted in the past, though limited, tended to show that the earlier flow-stress model for part-through-wall axial cracks overestimated the damaging influence of deep cracks. This observation is confirmed by further tests at high temperatures as well as by finite element analysis. A modified correlation for deep cracks can correct this shortcoming of the model. Recent tests have shown that lateral restraint can significantly increase the failure pressure of tubes with unsymmetrical circumferential cracks. This observation is confirmed by finite element analysis. The rate-independent flow stress models that are successful at low temperatures cannot predict the rate sensitive failure behavior of steam generator tubes at high temperatures. Therefore, a creep rupture model for predicting failure is developed and validated by tests under varying temperature and pressure loading expected during severe accidents.

  14. Prediction of "fear" acquisition in healthy control participants in a de novo fear-conditioning paradigm.

    PubMed

    Otto, Michael W; Leyro, Teresa M; Christian, Kelly; Deveney, Christen M; Reese, Hannah; Pollack, Mark H; Orr, Scott P

    2007-01-01

    Studies using fear-conditioning paradigms have found that anxiety patients are more conditionable than individuals without these disorders, but these effects have been demonstrated inconsistently. It is unclear whether these findings have etiological significance or whether enhanced conditionability is linked only to certain anxiety characteristics. To further examine these issues, the authors assessed the predictive significance of relevant subsyndromal characteristics in 72 healthy adults, including measures of worry, avoidance, anxious mood, depressed mood, and fears of anxiety symptoms (anxiety sensitivity), as well as the dimensions of Neuroticism and Extraversion. Of these variables, the authors found that the combination of higher levels of subsyndromal worry and lower levels of behavioral avoidance predicted heightened conditionability, raising questions about the etiological significance of these variables in the acquisition or maintenance of anxiety disorders. In contrast, the authors found that anxiety sensitivity was more linked to individual differences in orienting response than differences in conditioning per se. PMID:17179530

  15. Correlate Life Predictions and Condition Indicators in Helicopter Tail Gearbox Bearings

    NASA Technical Reports Server (NTRS)

    Dempsey, Paula J.; Bolander, Nathan; Haynes, Chris; Branning, Jeremy; Wade, Daniel R.

    2010-01-01

    Research to correlate bearing remaining useful life (RUL) predictions with Helicopter Health Usage Monitoring Systems (HUMS) condition indicators (CI) to indicate the damage state of a transmission component has been developed. Condition indicators were monitored and recorded on UH-60M (Black Hawk) tail gearbox output shaft thrust bearings, which had been removed from helicopters and installed in a bearing spall propagation test rig. Condition indicators monitoring the tail gearbox output shaft thrust bearings in UH-60M helicopters were also recorded from an on-board HUMS. The spal-lpropagation data collected in the test rig was used to generate condition indicators for bearing fault detection. A damage progression model was also developed from this data. Determining the RUL of this component in a helicopter requires the CI response to be mapped to the damage state. The data from helicopters and a test rig were analyzed to determine if bearing remaining useful life predictions could be correlated with HUMS condition indicators (CI). Results indicate data fusion analysis techniques can be used to map the CI response to the damage levels.

  16. Computational ecotoxicology: simultaneous prediction of ecotoxic effects of nanoparticles under different experimental conditions.

    PubMed

    Kleandrova, Valeria V; Luan, Feng; González-Díaz, Humberto; Ruso, Juan M; Melo, André; Speck-Planche, Alejandro; Cordeiro, M Natália D S

    2014-12-01

    Nanotechnology has brought great advances to many fields of modern science. A manifold of applications of nanoparticles have been found due to their interesting optical, electrical, and biological/chemical properties. However, the potential toxic effects of nanoparticles to different ecosystems are of special concern nowadays. Despite the efforts of the scientific community, the mechanisms of toxicity of nanoparticles are still poorly understood. Quantitative-structure activity/toxicity relationships (QSAR/QSTR) models have just started being useful computational tools for the assessment of toxic effects of nanomaterials. But most QSAR/QSTR models have been applied so far to predict ecotoxicity against only one organism/bio-indicator such as Daphnia magna. This prevents having a deeper knowledge about the real ecotoxic effects of nanoparticles, and consequently, there is no possibility to establish an efficient risk assessment of nanomaterials in the environment. In this work, a perturbation model for nano-QSAR problems is introduced with the aim of simultaneously predicting the ecotoxicity of different nanoparticles against several assay organisms (bio-indicators), by considering also multiple measures of ecotoxicity, as well as the chemical compositions, sizes, conditions under which the sizes were measured, shapes, and the time during which the diverse assay organisms were exposed to nanoparticles. The QSAR-perturbation model was derived from a database containing 5520 cases (nanoparticle-nanoparticle pairs), and it was shown to exhibit accuracies of ca. 99% in both training and prediction sets. In order to demonstrate the practical applicability of our model, three different nickel-based nanoparticles (Ni) with experimental values reported in the literature were predicted. The predictions were found to be in very good agreement with the experimental evidences, confirming that Ni-nanoparticles are not ecotoxic when compared with other nanoparticles. The results

  17. Impact of soil moisture initial conditions on multi model summer predictions over mid-latitudes

    NASA Astrophysics Data System (ADS)

    Ardilouze, Constantin; Prodhomme, Chloé; Batté, Lauriane; Déqué, Michel

    2016-04-01

    Land surface initial conditions have been recognized as a potential source of predictability at seasonal time scales. As an example, results from GLACE-2 (phase 2 of the Global Land-Atmosphere Coupling Experiment) highlighted the impact of spring soil moisture in summer near-surface air temperature prediction over Europe and Northern America with global long-range forecast systems (Koster et al., 2011, van den Hurk et al.,2012). Yet, few studies have explored such an influence over a sufficient hindcast period to produce a robust quantitative assessment. In the framework of the FP7-SPECS project, dedicated experiments have been carried out with June-August hindcasts from 5 distinct Atmosphere Ocean Global Climate Models initialized either by realistic or climatological soil moisture conditions on May 1st. Realistic initialization leads to an improved 2-meter temperature prediction skill over parts of Europe in the multi model, particularly the Balkans peninsula which had been identified as a hot spot of soil moisture-atmosphere coupling (Seneviratne et al. 2006) However no improvement was found over North-American Great Plains in spite of the high potential of this region. Further analyses suggest that this lack of skill stems from a common shortcoming of the models. All of them tend to overestimate the positive feedback between soil moisture, temperature and precipitation with respect to the observations. Hence, tackling model systematic biases over the US Southern Great Plains appears as a necessary prerequisite for summer predictability enhancement.

  18. Predictive statistical models linking antecedent meteorological conditions and waterway bacterial contamination in urban waterways.

    PubMed

    Farnham, David J; Lall, Upmanu

    2015-06-01

    Although the relationships between meteorological conditions and waterway bacterial contamination are being better understood, statistical models capable of fully leveraging these links have not been developed for highly urbanized settings. We present a hierarchical Bayesian regression model for predicting transient fecal indicator bacteria contamination episodes in urban waterways. Canals, creeks, and rivers of the New York City harbor system are used to examine the model. The model configuration facilitates the hierarchical structure of the underlying system with weekly observations nested within sampling sites, which in turn were nested inside of the harbor network. Models are compared using cross-validation and a variety of Bayesian and classical model fit statistics. The uncertainty of predicted enterococci concentration values is reflected by sampling from the posterior predictive distribution. Issuing predictions with the uncertainty reasonably reflected allows a water manager or a monitoring agency to issue warnings that better reflect the underlying risk of exposure. A model using only antecedent meteorological conditions is shown to correctly classify safe and unsafe levels of enterococci with good accuracy. The hierarchical Bayesian regression approach is most valuable where transient fecal indicator bacteria contamination is problematic and drainage network data are scarce. PMID:25813489

  19. Prediction of peptide retention at different HPLC conditions from multiple linear regression models.

    PubMed

    Baczek, Tomasz; Wiczling, Paweł; Marszałł, Michał; Heyden, Yvan Vander; Kaliszan, Roman

    2005-01-01

    To quantitatively characterize the structure of a peptide and to predict its gradient retention time at given HPLC conditions three structural descriptors are used: (i) logarithm of the sum of retention times of the amino acids composing the peptide, log SumAA, (ii) logarithm of the van der Waals volume of the peptide, log VDW(Vol), (iii) and the logarithm of the peptide's calculated n-octanol-water partition coefficient, clog P. The log SumAA descriptor is obtained from empirical data for 20 natural amino acids, determined in a given HPLC system. The two other descriptors are calculated from the peptides' structural formulas using molecular modeling methods. The quantitative structure-retention relationships (QSRR), build by multiple linear regression, describe HPLC retention of peptide on a given chromatographic system on which the retention of the 20 amino acids was predetermined. A structurally diversified series of 98 peptides was employed. The predicted gradient retention times on several chromatographic systems were in good agreement with the experimental data. The QSRR equations, derived for a given system operated at variable gradient times and temperatures allowed for the prediction of peptide retention in that system. Matching the experimental HPLC retention to the theoretically predicted for a presumed peptide could facilitate original protein identification in proteomics. In conjunction with MS data, prediction of the retention time for a given peptide might be used to improve the confidence of peptide identifications and to increase the number of correctly identified peptides.

  20. Importance of initial conditions in seasonal predictions of Arctic sea ice extent

    NASA Astrophysics Data System (ADS)

    Msadek, R.; Vecchi, G. A.; Winton, M.; Gudgel, R. G.

    2014-07-01

    We present seasonal predictions of Arctic sea ice extent (SIE) over the 1982-2013 period using two suites of retrospective forecasts initialized from a fully coupled ocean-atmosphere-sea ice assimilation system. High skill scores are found in predicting year-to-year fluctuations of Arctic SIE, with significant correlations up to 7 month ahead for September detrended anomalies. Predictions over the recent era, which coincides with an improved observational coverage, outperform the earlier period for most target months. We find, however, a degradation of skill in September during the last decade, a period of sea ice thinning in observations. The two prediction models, Climate Model version 2.1 (CM2.1) and Forecast-oriented Low Ocean Resolution (FLOR), share very similar ocean and ice component and initialization but differ by their atmospheric component. FLOR has improved climatological atmospheric circulation and sea ice mean state, but its skill is overall similar to CM2.1 for most seasons, which suggests a key role for initial conditions in predicting seasonal SIE fluctuations.

  1. Uncertainties in Predicting Rice Yield by Current Crop Models Under a Wide Range of Climatic Conditions

    NASA Technical Reports Server (NTRS)

    Li, Tao; Hasegawa, Toshihiro; Yin, Xinyou; Zhu, Yan; Boote, Kenneth; Adam, Myriam; Bregaglio, Simone; Buis, Samuel; Confalonieri, Roberto; Fumoto, Tamon; Gaydon, Donald; Marcaida, Manuel, III; Nakagawa, Hiroshi; Oriol, Philippe; Ruane, Alex C.; Ruget, Francoise; Singh, Balwinder; Singh, Upendra; Tang, Liang; Tao, Fulu; Wilkens, Paul; Yoshida, Hiroe; Zhang, Zhao; Bouman, Bas

    2014-01-01

    Predicting rice (Oryza sativa) productivity under future climates is important for global food security. Ecophysiological crop models in combination with climate model outputs are commonly used in yield prediction, but uncertainties associated with crop models remain largely unquantified. We evaluated 13 rice models against multi-year experimental yield data at four sites with diverse climatic conditions in Asia and examined whether different modeling approaches on major physiological processes attribute to the uncertainties of prediction to field measured yields and to the uncertainties of sensitivity to changes in temperature and CO2 concentration [CO2]. We also examined whether a use of an ensemble of crop models can reduce the uncertainties. Individual models did not consistently reproduce both experimental and regional yields well, and uncertainty was larger at the warmest and coolest sites. The variation in yield projections was larger among crop models than variation resulting from 16 global climate model-based scenarios. However, the mean of predictions of all crop models reproduced experimental data, with an uncertainty of less than 10 percent of measured yields. Using an ensemble of eight models calibrated only for phenology or five models calibrated in detail resulted in the uncertainty equivalent to that of the measured yield in well-controlled agronomic field experiments. Sensitivity analysis indicates the necessity to improve the accuracy in predicting both biomass and harvest index in response to increasing [CO2] and temperature.

  2. Uncertainties in predicting rice yield by current crop models under a wide range of climatic conditions.

    PubMed

    Li, Tao; Hasegawa, Toshihiro; Yin, Xinyou; Zhu, Yan; Boote, Kenneth; Adam, Myriam; Bregaglio, Simone; Buis, Samuel; Confalonieri, Roberto; Fumoto, Tamon; Gaydon, Donald; Marcaida, Manuel; Nakagawa, Hiroshi; Oriol, Philippe; Ruane, Alex C; Ruget, Françoise; Singh, Balwinder-; Singh, Upendra; Tang, Liang; Tao, Fulu; Wilkens, Paul; Yoshida, Hiroe; Zhang, Zhao; Bouman, Bas

    2015-03-01

    Predicting rice (Oryza sativa) productivity under future climates is important for global food security. Ecophysiological crop models in combination with climate model outputs are commonly used in yield prediction, but uncertainties associated with crop models remain largely unquantified. We evaluated 13 rice models against multi-year experimental yield data at four sites with diverse climatic conditions in Asia and examined whether different modeling approaches on major physiological processes attribute to the uncertainties of prediction to field measured yields and to the uncertainties of sensitivity to changes in temperature and CO2 concentration [CO2 ]. We also examined whether a use of an ensemble of crop models can reduce the uncertainties. Individual models did not consistently reproduce both experimental and regional yields well, and uncertainty was larger at the warmest and coolest sites. The variation in yield projections was larger among crop models than variation resulting from 16 global climate model-based scenarios. However, the mean of predictions of all crop models reproduced experimental data, with an uncertainty of less than 10% of measured yields. Using an ensemble of eight models calibrated only for phenology or five models calibrated in detail resulted in the uncertainty equivalent to that of the measured yield in well-controlled agronomic field experiments. Sensitivity analysis indicates the necessity to improve the accuracy in predicting both biomass and harvest index in response to increasing [CO2 ] and temperature.

  3. Conditioning rainfall-runoff model parameters to reduce prediction uncertainty in ungauged basins

    NASA Astrophysics Data System (ADS)

    Visessri, S.; McIntyre, N.; Maksimovic, C.

    2012-12-01

    Conditioning rainfall-runoff model parameters in ungauged catchments in Thailand presents problems common to ungauged basins involving data availability, data quality, and rainfall-runoff model suitability, which all contribute to prediction uncertainty. This paper attempts to improve the estimation of streamflow in ungauged basins and reduce associated uncertainties using the approaches of conditioning the prior parameter space. 35 catchments from the upper Ping River basin, Thailand are selected as a case study. The catchments have a range of attributes e.g. catchment sizes 20-6350 km2, elevations 632-1529 m above sea level. and annual rainfall 846-1447 mm/year. For each catchment, three indices - rainfall-runoff elasticity, base flow index and runoff coefficient - are calculated using the observed rainfall-runoff data and regression equations relating these indices to the catchment attributes are identified. Uncertainty in expected indices is defined by the regression error distribution, approximated by a Gaussian model. The IHACRES model is applied for simulating streamflow. The IHACRES parameters are randomly sampled from their presumed prior parameter space. For each sampled parameter set, the streamflow and hence the three indices are modelled. The parameter sets are conditioned on the probability distributions of the regionalised indices, allowing ensemble predictions to be made. The objective function, NSE, calculated for daily and weekly time steps from the water years 1995-2000, is used to assess model performance. Ability to capture observed streamflow and the precision of the estimate is evaluated using reliability and sharpness measures. Similarity in modelled and expected indices contributes to good objective function values. Using only the regionalised runoff coefficient to condition the model yields better NSE values compared to using either only the rainfall-runoff elasticity or only the base flow index. Conditioning on the runoff coefficient

  4. Neonatal body condition, immune responsiveness, and hematocrit predict longevity in a wild bird population

    PubMed Central

    Hodges, Christine J.; Forsman, Anna M.; Vogel, Laura A.; Masters, Brian S.; Johnson, Bonnie G. P.; Johnson, L. Scott; Thompson, Charles F.; Sakaluk, Scott K.

    2014-01-01

    Measures of body condition, immune function, and hematological health are widely used in ecological studies of vertebrate populations, predicated on the assumption that these traits are linked to fitness. However, compelling evidence that these traits actually predict long-term survival and reproductive success among individuals in the wild is lacking. Here, we show that body condition (i.e., size-adjusted body mass) and cutaneous immune responsiveness to phytohaemagglutinin (PHA) injection among neonates positively predict recruitment and subsequent longevity in a wild, migratory population of house wrens (Troglodytes aedon). However, neonates with intermediate hematocrit had the highest recruitment and longevity. Neonates with the highest PHA responsiveness and intermediate hematocrit prior to independence eventually produced the most offspring during their lifetime breeding on the study site. Importantly, the effects of PHA responsiveness and hematocrit were revealed while controlling for variation in body condition, sex, and environmental variation. Thus, our data demonstrate that body condition, cutaneous immune responsiveness, and hematocrit as a neonate are associated with individual fitness. Although hematocrit's effect is more complex than traditionally thought, our results suggest a previously underappreciated role for this trait in influencing survival in the wild. PMID:25505800

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

    NASA Astrophysics Data System (ADS)

    Saito, Sumio; Sato, Kenichi; Sekizuka, Satoshi

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

  6. Short communication: Prediction of intake in dairy cows under tropical conditions.

    PubMed

    Souza, M C; Oliveira, A S; Araújo, C V; Brito, A F; Teixeira, R M A; Moares, E H B K; Moura, D C

    2014-01-01

    A meta-analysis was conducted to develop a model for predicting dry matter intake (DMI) in dairy cows under the tropical conditions of Brazil and to assess its adequacy compared with 5 currently available DMI prediction models: Agricultural and Food Research Council (AFRC); National Research Council (NRC); Cornell Net Carbohydrate and Protein System (CNCPS; version 6); and 2 other Brazilian models. The data set was created using 457 observations (n=1,655 cows) from 100 studies, and it was randomly divided into 2 subsets for statistical analysis. The first subset was used to develop a DMI prediction equation (60 studies; 309 treatment means) and the second subset was used to assess the adequacy of DMI predictive models (40 studies; 148 treatment means). The DMI prediction model proposed in the current study was developed using a nonlinear mixed model analysis after reparameterizing the NRC equation but including study as a random effect in the model. Body weight (mean = 540 ± 57.6 kg), 4% fat-corrected milk (mean = 21.3 ± 7.7 kg/d), and days in milk (mean = 110 ± 62 d) were used as independent variables in the model. The adequacy of the DMI prediction models was evaluated based on coefficient of determination, mean square prediction error (MSPE), root MSPE (RMSPE), and concordance correlation coefficient (CCC). The observed DMI obtained from the data set used to evaluate the prediction models averaged 17.6 ± 3.2 kg/d. The following model was proposed: DMI (kg/d) = [0.4762 (± 0.0358) × 4% fat-corrected milk + 0.07219 (± 0.00605) × body weight(0.75)] × (1 - e(-0.03202 (± 0.00615) × [days in milk + 24.9576 (± 5.909)])). This model explained 93.0% of the variation in DMI, predicting it with the lowest mean bias (0.11 kg/d) and RMSPE (4.9% of the observed DMI) and the highest precision [correlation coefficient estimate (ρ) = 0.97] and accuracy [bias correction factor (Cb)=0.99]. The NRC model prediction equation explained 92.0% of the variation in DMI and

  7. The salt marsh vegetation spread dynamics simulation and prediction based on conditions optimized CA

    NASA Astrophysics Data System (ADS)

    Guan, Yujuan; Zhang, Liquan

    2006-10-01

    The biodiversity conservation and management of the salt marsh vegetation relies on processing their spatial information. Nowadays, more attentions are focused on their classification surveying and describing qualitatively dynamics based on RS images interpreted, rather than on simulating and predicting their dynamics quantitatively, which is of greater importance for managing and planning the salt marsh vegetation. In this paper, our notion is to make a dynamic model on large-scale and to provide a virtual laboratory in which researchers can run it according requirements. Firstly, the characteristic of the cellular automata was analyzed and a conclusion indicated that it was necessary for a CA model to be extended geographically under varying conditions of space-time circumstance in order to make results matched the facts accurately. Based on the conventional cellular automata model, the author introduced several new conditions to optimize it for simulating the vegetation objectively, such as elevation, growth speed, invading ability, variation and inheriting and so on. Hence the CA cells and remote sensing image pixels, cell neighbors and pixel neighbors, cell rules and nature of the plants were unified respectively. Taking JiuDuanSha as the test site, where holds mainly Phragmites australis (P.australis) community, Scirpus mariqueter (S.mariqueter) community and Spartina alterniflora (S.alterniflora) community. The paper explored the process of making simulation and predictions about these salt marsh vegetable changing with the conditions optimized CA (COCA) model, and examined the links among data, statistical models, and ecological predictions. This study exploited the potential of applying Conditioned Optimized CA model technique to solve this problem.

  8. Subsecond dopamine release in the nucleus accumbens predicts conditioned punishment and its successful avoidance.

    PubMed

    Oleson, Erik B; Gentry, Ronny N; Chioma, Vivian C; Cheer, Joseph F

    2012-10-17

    The mesolimbic dopamine system is believed to be a pathway that processes rewarding information. While previous studies have also implicated a general role for dopamine in punishment and its avoidance, the precise nature of subsecond dopamine release during these phenomena remains unknown. Here, we used fast-scan cyclic voltammetry to investigate whether subsecond dopamine release events in the nucleus accumbens encode cues predicting the avoidance of punishment during behavior maintained in a signaled footshock avoidance procedure. In this task, rats could initiate an avoidance response by pressing a lever within a warning period, preventing footshock. Alternatively, once footshocks commenced, animals could initiate an escape response by pressing the lever, terminating footshock. This design allowed us to assess subsecond dopamine release events during the presentation of a warning signal, safety periods, and two distinct behavioral responses. We found that release consistently increased upon presentation of the warning signal in a manner that reliably predicted successful punishment avoidance. We also observed subsecond dopamine release during the safety period, as occurs following the receipt of reward. Conversely, we observed a decrease in release at the warning signal during escape responses. Because of this finding, we next assessed dopamine release in a conditioned fear model. As seen during escape responses, we observed a time-locked decrease in dopamine release upon presentation of a cue conditioned to inescapable footshock. Together, these data show that subsecond fluctuations in mesolimbic dopamine release predict when rats will successfully avoid punishment and differentially encode cues related to aversive outcomes.

  9. Adapting SOYGRO V5.42 for prediction under climate change conditions

    SciTech Connect

    Pickering, N.B.; Jones, J.W.; Boote, K.J.

    1995-12-31

    In some studies of the impacts of climate change on global crop production, crop growth models were empirically adapted to improve their response to increased CO{sub 2} concentration and air temperature. This chapter evaluates the empirical adaptations of the photosynthesis and evapotranspiration (ET) algorithms used in the soybean [Glycine max (L.) Merr.] model, SOYGRO V5.42, by comparing it with a new model that includes mechanistic approaches for these two processes. The new evapotranspiration-photosynthesis sub-model (ETPHOT) uses a hedgerow light interception algorithm, a C{sub 3}-leaf biochemical photosynthesis submodel, and predicts canopy ET and temperatures using a three-zone energy balance. ETPHOT uses daily weather data, has an internal hourly time step, and sums hourly predictions to obtain daily gross photosynthesis and ET. The empirical ET and photosynthesis curves included in SOYGRO V5.42 for climate change prediction were similar to those predicted by the ETPHOT model. Under extreme conditions that promote high leaf temperatures, like in the humid tropics. SOYGRO V5.42 overestimated daily gross photosynthesis response to CO{sub 2} compared with the ETPHOT model. SOYGRO V5.42 also slightly overestimated daily gross photosynthesis at intermediate air temperatures and ambient CO{sub 2} concentrations. 80 refs., 12 figs.

  10. Prediction of air temperature in the aircraft cabin under different operational conditions

    NASA Astrophysics Data System (ADS)

    Volavý, F.; Fišer, J.; Nöske, I.

    2013-04-01

    This paper deals with the prediction of the air temperature in the aircraft cabin by means of Computational Fluid Dynamics. The simulations are performed on the CFD model which is based on geometry and cabin interior arrangement of the Flight Test Facility (FTF) located at Fraunhofer IBP, Germany. The experimental test flights under three different cabin temperatures were done in FTF and the various data were gathered during these flights. Air temperature in the cabin was measured on probes located near feet, torso and head of each passenger and also surface temperature and air temperature distributed from inlets were measured. The data were firstly analysed in order to obtain boundary conditions for cabin surfaces and inlets. Then the results of air temperature from the simulations were compared with measured data. The suitability and accuracy of the CFD approach for temperature prediction is discussed.

  11. Prediction of water intake and excretion flows in Holstein dairy cows under thermoneutral conditions.

    PubMed

    Khelil-Arfa, H; Boudon, A; Maxin, G; Faverdin, P

    2012-10-01

    The increase in the worldwide demand for dairy products, associated with global warming, will emphasize the issue of water use efficiency in dairy systems. The evaluation of environmental issues related to the management of animal dejections will also require precise biotechnical models that can predict effluent management in farms. In this study, equations were developed and evaluated for predicting the main water flows at the dairy cow level, based on parameters related to cow productive performance and diet under thermoneutral conditions. Two datasets were gathered. The first one comprised 342 individual measurements of water balance in dairy cows obtained during 18 trials at the experimental farm of Méjussaume (INRA, France). Predictive equations of water intake, urine and fecal water excretion were developed by multiple regression using a stepwise selection of regressors from a list of seven candidate parameters, which were milk yield, dry matter intake (DMI), body weight, diet dry matter content (DM), proportion of concentrate (CONC) and content of crude protein (CP) ingested with forage and concentrate (CPf and CPc, g/kg DM). The second dataset was used for external validation of the developed equations and comprised 196 water flow measurements on experimental lots obtained from 43 published papers related to water balance or digestibility measurements in dairy cows. Although DMI was the first predictor of the total water intake (TWI), with a partial r(2) of 0.51, DM was the first predictive parameter of free water intake (FWI), with a partial r(2) of 0.57, likely due to the large variability of DM in the first dataset (from 11.5 to 91.4 g/100 g). This confirmed the compensation between water drunk and ingested with diet when DM changes. The variability of urine volume was explained mainly by the CPf associated with DMI (r.s.d. 5.4 kg/day for an average flow of 24.0 kg/day) and that of fecal water was explained by the proportion of CONC in the diet and DMI

  12. Predicting changes in alluvial channel patterns in North-European Russia under conditions of global warming

    NASA Astrophysics Data System (ADS)

    Anisimov, Oleg; Vandenberghe, Jef; Lobanov, Vladimir; Kondratiev, Alexander

    2008-06-01

    Global climate change may have a noticeable impact on the northern environment, leading to changes in permafrost, vegetation and fluvial morphology. In this paper we compare the results from three geomorphological models and study the potential effects of changing climatic factors on the river channel types in North-European Russia. Two of the selected models by Romashin [Romashin, V.V., 1968. Variations of the river channel types under governing factors, Annals of the Hydrological Institute, vol. 155. Hydrometeoizdat, Leningrad, pp. 56-63.] and Leopold and Wolman [Leopold, L.B., Wolman, M.G., 1957. River channel pattern: braided, meandering and straight, Physiographic and hydraulic studies of rivers. USA Geological Survey Professional Paper 252, pp. 85-98.] are conventional QS-type models, which predict the existence of either multi-thread or single-tread channel types using data on discharge and channel slope. The more advanced model by Van den Berg [Van den Berg, J.H., 1995. Prediction of alluvial channel pattern of perennial rivers. Geomorphology 12, 259-270.] takes into account the size of the sediment material. We used data from 16 runoff gauges to validate the models and predict the channel types at selected locations under modern and predicted for the future climatic conditions. Two of the three models successfully replicated the currently existing channel types in all but one of the studied sites. Predictive calculations under the hypothetical scenarios of 10%, 15%, 20% and 35% runoff increase gave different results. Van den Berg's model predicted potential transformation of the channel types, from single- to multi-thread, at 4 of 16 selected locations in the next few decades, and at 5 locations by the middle of the 21st century. Each of the QS-type models predicted such transformation at one site only. Results of the study indicate that climatic warming in combination with other environmental changes may lead to transformation of the river channel types

  13. On the Impact of Uncertainty in Initial Conditions of Hydrologic Models on Prediction

    NASA Astrophysics Data System (ADS)

    Razavi, S.; Sheikholeslami, R.

    2015-12-01

    Determining the initial conditions for predictive models remains a challenge due to the uncertainty in measurement/identification of the state variables at the scale of interest. However, the characterization of uncertainty in initial conditions has arguably attracted less attention compared with other sources of uncertainty in hydrologic modelling (e.g, parameter, data, and structural uncertainty). This is perhaps because it is commonly believed that: (1) hydrologic systems (relatively rapidly) forget their initial conditions over time, and (2) other sources of uncertainty (e.g., in data) are dominant. This presentation revisits the basic principles of the theory of nonlinear dynamical systems in the context of hydrologic systems. Through simple example case studies, we demonstrate how and under what circumstances different hydrologic processes represent a range of attracting limit sets in their evolution trajectory in state space over time, including fixed points, limit cycles (periodic behaviour), torus (quasi-periodic behaviour), and strange attractors (chaotic behaviour). Furthermore, the propagation (or dissipation) of uncertainty in initial conditions of several hydrologic models through time, under any of the possible attracting limit sets, is investigated. This study highlights that there are definite situations in hydrology where uncertainty in initial conditions remains of significance. The results and insights gained have important implications for hydrologic modelling under non-stationarity in climate and environment.

  14. Conditioned cortical reactivity to cues predicting cigarette-related or pleasant images.

    PubMed

    Deweese, Menton M; Robinson, Jason D; Cinciripini, Paul M; Versace, Francesco

    2016-03-01

    Through Pavlovian conditioning, reward-associated neutral stimuli can acquire incentive salience and motivate complex behaviors. In smokers, cigarette-associated cues may induce cravings and trigger smoking. Understanding the brain mechanisms underlying conditioned responses to cigarette-associated relative to other inherently pleasant stimuli might contribute to the development of more effective smoking cessation treatments that emphasize the rehabilitation of reward circuitry. Here we measured brain responses to geometric patterns (the conditioned stimuli, CSs) predicting cigarette-related, intrinsically pleasant and neutral images (the unconditioned stimuli, USs) using event-related potentials (ERPs) in 29 never-smokers, 20 nicotine-deprived smokers, and 19 non-deprived smokers. Results showed that during US presentation, cigarette-related and pleasant images prompted higher cortical positivity than neutral images over centro-parietal sensors between 400 and 800ms post-US onset (late positive potential, LPP). The LPP evoked by pleasant images was significantly larger than the LPP evoked by cigarette images. During CS presentation, ERPs evoked by geometric patterns predicting pleasant and cigarette-related images had significantly larger amplitude than ERPs evoked by CSs predicting neutral images. These effects were maximal over right parietal sites between 220 and 240ms post-CS onset and over occipital and frontal sites between 308 and 344ms post-CS onset. Smoking status did not modulate these effects. Our results show that stimuli with no intrinsic reward value (e.g., geometric patterns) may acquire rewarding properties through repeated pairings with established reward cues (i.e., cigarette-related, intrinsically pleasant).

  15. Assessing Long-Term Wind Conditions by Combining Different Measure-Correlate-Predict Algorithms: Preprint

    SciTech Connect

    Zhang, J.; Chowdhury, S.; Messac, A.; Hodge, B. M.

    2013-08-01

    This paper significantly advances the hybrid measure-correlate-predict (MCP) methodology, enabling it to account for variations of both wind speed and direction. The advanced hybrid MCP method uses the recorded data of multiple reference stations to estimate the long-term wind condition at a target wind plant site. The results show that the accuracy of the hybrid MCP method is highly sensitive to the combination of the individual MCP algorithms and reference stations. It was also found that the best combination of MCP algorithms varies based on the length of the correlation period.

  16. Do Early-Life Conditions Predict Functional Health Status in Adulthood? The Case of Mexico

    PubMed Central

    Huang, Cheng; Soldo, Beth J; Elo, Irma T

    2010-01-01

    Relatively few researchers have investigated early antecedents of adult functional limitations in developing countries. In this study, we assessed associations between childhood conditions and adult lower-body functional limitations (LBFL) as well as the potential mediating role of adult socioeconomic status, smoking, body mass index, and chronic diseases or symptoms. Based on data from the Mexican Health and Aging Study (MHAS) of individuals born prior to 1951 and contacted in 2001 and 2003, we found that childhood nutritional deprivation, serious health problems, and family background predict adult LBFL in Mexico. Adjustment for the potential mediators in adulthood attenuates these associations only to a modest degree. PMID:21074924

  17. Vortical gust boundary condition for realistic rotor wake/stator interaction noise prediction using computational aeroacoustics

    NASA Astrophysics Data System (ADS)

    Hixon, Ray; Sescu, Adrian; Sawyer, Scott

    2011-08-01

    In this work, the NASA Glenn Research Center Broadband Aeroacoustic Stator Simulation (BASS) code is extended for use in the prediction of noise produced by realistic three-dimensional rotor wakes impinging on a downstream stator row. In order to accurately simulate such a flow using a nonlinear time-accurate solver, the inflow and outflow boundary conditions must simultaneously maintain the desired mean flow, allow outgoing vortical, entropic, and acoustic waves to cleanly exit the domain, and accurately impose the desired incoming flow disturbances. This work validates a new method for the acoustics-free imposition of three-dimensional vortical disturbances using benchmark test cases.

  18. Sensitivity of soil moisture initialization for decadal predictions under different regional climatic conditions in Europe

    NASA Astrophysics Data System (ADS)

    Khodayar, S.; Sehlinger, A.; Feldmann, H.; Kottmeier, C.

    2015-12-01

    The impact of soil initialization is investigated through perturbation simulations with the regional climate model COSMO-CLM. The focus of the investigation is to assess the sensitivity of simulated extreme periods, dry and wet, to soil moisture initialization in different climatic regions over Europe and to establish the necessary spin up time within the framework of decadal predictions for these regions. Sensitivity experiments consisted of a reference simulation from 1968 to 1999 and 5 simulations from 1972 to 1983. The Effective Drought Index (EDI) is used to select and quantify drought status in the reference run to establish the simulation time period for the sensitivity experiments. Different soil initialization procedures are investigated. The sensitivity of the decadal predictions to soil moisture initial conditions is investigated through the analysis of water cycle components' (WCC) variability. In an episodic time scale the local effects of soil moisture on the boundary-layer and the propagated effects on the large-scale dynamics are analysed. The results show: (a) COSMO-CLM reproduces the observed features of the drought index. (b) Soil moisture initialization exerts a relevant impact on WCC, e.g., precipitation distribution and intensity. (c) Regional characteristics strongly impact the response of the WCC. Precipitation and evapotranspiration deviations are larger for humid regions. (d) The initial soil conditions (wet/dry), the regional characteristics (humid/dry) and the annual period (wet/dry) play a key role in the time that soil needs to restore quasi-equilibrium and the impact on the atmospheric conditions. Humid areas, and for all regions, a humid initialization, exhibit shorter spin up times, also soil reacts more sensitive when initialised during dry periods. (e) The initial soil perturbation may markedly modify atmospheric pressure field, wind circulation systems and atmospheric water vapour distribution affecting atmospheric stability

  19. Can phenological models predict tree phenology accurately under climate change conditions?

    NASA Astrophysics Data System (ADS)

    Chuine, Isabelle; Bonhomme, Marc; Legave, Jean Michel; García de Cortázar-Atauri, Inaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry

    2014-05-01

    The onset of the growing season of trees has been globally earlier by 2.3 days/decade during the last 50 years because of global warming and this trend is predicted to continue according to climate forecast. The effect of temperature on plant phenology is however not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud dormancy, and on the other hand higher temperatures are necessary to promote bud cells growth afterwards. Increasing phenological changes in temperate woody species have strong impacts on forest trees distribution and productivity, as well as crops cultivation areas. Accurate predictions of trees phenology are therefore a prerequisite to understand and foresee the impacts of climate change on forests and agrosystems. Different process-based models have been developed in the last two decades to predict the date of budburst or flowering of woody species. They are two main families: (1) one-phase models which consider only the ecodormancy phase and make the assumption that endodormancy is always broken before adequate climatic conditions for cell growth occur; and (2) two-phase models which consider both the endodormancy and ecodormancy phases and predict a date of dormancy break which varies from year to year. So far, one-phase models have been able to predict accurately tree bud break and flowering under historical climate. However, because they do not consider what happens prior to ecodormancy, and especially the possible negative effect of winter temperature warming on dormancy break, it seems unlikely that they can provide accurate predictions in future climate conditions. It is indeed well known that a lack of low temperature results in abnormal pattern of bud break and development in temperate fruit trees. An accurate modelling of the dormancy break date has thus become a major issue in phenology modelling. Two-phases phenological models predict that global warming should delay

  20. Predicting a contact's sensitivity to initial conditions using metrics of frictional coupling

    DOE PAGESBeta

    Flicek, Robert C.; Hills, David A.; Brake, Matthew Robert W.

    2016-09-29

    This paper presents a method for predicting how sensitive a frictional contact’s steady-state behavior is to its initial conditions. Previous research has proven that if a contact is uncoupled, i.e. if slip displacements do not influence the contact pressure distribution, then its steady-state response is independent of initial conditions, but if the contact is coupled, the steady-state response depends on initial conditions. In this paper, two metrics for quantifying coupling in discrete frictional systems are examined. These metrics suggest that coupling is dominated by material dissimilarity due to Dundurs’ composite material parameter β when β ≥ 0.2, but geometric mismatchmore » becomes the dominant source of coupling for smaller values of β. Based on a large set of numerical simulations with different contact geometries, material combinations, and friction coefficients, a contact’s sensitivity to initial conditions is found to be correlated with the product of the coupling metric and the friction coefficient. For cyclic shear loading, this correlation is maintained for simulations with different contact geometries, material combinations, and friction coefficients. Furthermore, for cyclic bulk loading, the correlation is only maintained when the contact edge angle is held constant.« less

  1. Predictions of structural integrity of steam generator tubes under normal operating, accident, an severe accident conditions

    SciTech Connect

    Majumdar, S.

    1997-02-01

    Available models for predicting failure of flawed and unflawed steam generator tubes under normal operating, accident, and severe accident conditions are reviewed. Tests conducted in the past, though limited, tended to show that the earlier flow-stress model for part-through-wall axial cracks overestimated the damaging influence of deep cracks. This observation was confirmed by further tests at high temperatures, as well as by finite-element analysis. A modified correlation for deep cracks can correct this shortcoming of the model. Recent tests have shown that lateral restraint can significantly increase the failure pressure of tubes with unsymmetrical circumferential cracks. This observation was confirmed by finite-element analysis. The rate-independent flow stress models that are successful at low temperatures cannot predict the rate-sensitive failure behavior of steam generator tubes at high temperatures. Therefore, a creep rupture model for predicting failure was developed and validated by tests under various temperature and pressure loadings that can occur during postulated severe accidents.

  2. Influence of thermal buoyancy on vertical tube bundle thermal density head predictions under transient conditions. [LMFBR

    SciTech Connect

    Lin, H.C.; Kasza, K.E.

    1984-01-01

    The thermal-hydraulic behavior of an LMFBR system under various types of plant transients is usually studied using one-dimensional (1-D) flow and energy transport models of the system components. Many of the transient events involve the change from a high to a low flow with an accompanying change in temperature of the fluid passing through the components which can be conductive to significant thermal bouyancy forces. Thermal bouyancy can exert its influence on system dynamic energy transport predictions through alterations of flow and thermal distributions which in turn can influence decay heat removal, system-response time constants, heat transport between primary and secondary systems, and thermal energy rejection at the reactor heat sink, i.e., the steam generator. In this paper the results from a comparison of a 1-D model prediction and experimental data for vertical tube bundle overall thermal density head and outlet temperature under transient conditions causing varying degrees of thermal bouyancy are presented. These comparisons are being used to generate insight into how, when, and to what degree thermal buoyancy can cause departures from 1-D model predictions.

  3. Predicting long-term risk for relationship dissolution using nonparametric conditional survival trees.

    PubMed

    Kliem, Sören; Weusthoff, Sarah; Hahlweg, Kurt; Baucom, Katherine J W; Baucom, Brian R

    2015-12-01

    Identifying risk factors for divorce or separation is an important step in the prevention of negative individual outcomes and societal costs associated with relationship dissolution. Programs that aim to prevent relationship distress and dissolution typically focus on changing processes that occur during couple conflict, although the predictive ability of conflict-specific variables has not been examined in the context of other factors related to relationship dissolution. The authors examine whether emotional responding and communication during couple conflict predict relationship dissolution after controlling for overall relationship quality and individual well-being. Using nonparametric conditional survival trees, the study at hand simultaneously examined the predictive abilities of physiological (systolic and diastolic blood pressure, heart rate, cortisol) and behavioral (fundamental frequency; f0) indices of emotional responding, as well as observationally coded positive and negative communication behavior, on long-term relationship stability after controlling for relationship satisfaction and symptoms of depression. One hundred thirty-six spouses were assessed after participating in a randomized clinical trial of a relationship distress prevention program as well as 11 years thereafter; 32.5% of the couples' relationships had dissolved by follow up. For men, the only significant predictor of relationship dissolution was cortisol change score (p = .012). For women, only f0 range was a significant predictor of relationship dissolution (p = .034). These findings highlight the importance of emotional responding during couple conflict for long-term relationship stability. PMID:26192131

  4. Impacts of the surface conditions uncertainties in the Canadian Regional Ensemble Prediction System

    NASA Astrophysics Data System (ADS)

    Lavaysse, C.; Carrera, M. L.; Belair, S.; Charron, M.; Yau, P. M.; Frenette, R.; Gagnon, N.

    2010-12-01

    The aim of this study is to quantify the impacts of surface condition uncertainties and the various surface parameters on the atmosphere of the Canadian Regional Ensemble Prediction System (REPS). In this study, the Canadian version of the ISBA land-surface scheme has been coupled to Environment Canada's Numerical Weather Prediction model (GEM) within the REPS. For twenty summer days in 2009, stochastic perturbations have been generated in 18 experiments. Each experiment corresponds to twenty simulations differing by the perturbations at the initial time of one or several surface parameters (e.g., vegetation fraction, leaf area index, sea-ice fraction) or prognostic variables (e.g., soil moisture, soil temperature at different layers). To better isolate these impacts, atmospheric perturbations are not added and all members of the REPS are driven by the same initial atmospheric conditions and large-scale forcing. The impact of these perturbations has been quantified especially for 2-m temperature, 10-m wind speed, and precipitation up to 48-h lead time. Spatial variability and diurnal evolution of these sensitivities over the North American continent will be discussed.

  5. Predicting success on conditional release for insanity acquittees: regionalized versus nonregionalized hospital patients.

    PubMed

    Tellefsen, C; Cohen, M I; Silver, S B; Dougherty, C

    1992-01-01

    This research compared the outcomes of two cohorts of insanity acquittees: one group was treated solely in the maximum security state forensic hospital before their release to the community (nonregionalized) and the other group was treated at the state forensic hospital and transferred for further treatment at less secure state regional hospitals (regionalized). This research describes the outcome of a group of insanity acquittees (regionalized patients) never previously studied. The applicability of a prediction model based on earlier research of insanity acquittees was tested on the patients. Findings on four outcome indicators are reported: rearrests within five years after release, overall functioning in the community five years after release, rehospitalizations for mental illness, and successful completion of the terms of the five-year conditional release (nonrevocation). Discriminant analysis was performed on the four outcome variables. The model was found to accurately predict the four types of outcome from 69 percent to 94 percent accurately for the nonregionalized insanity acquittees and from 87.5 percent to 95.8 percent for the regionalized patients. This model is currently being adapted to classify patients into potential high- and low-risk groups at the time of conditional release for the purpose of determining the intensity of outpatient supervision.

  6. Probing Pluto's Underworld : Predicted Ice Temperatures from Microwave Radiometry Decoupled from Surface Conditions

    NASA Astrophysics Data System (ADS)

    Le Gall, Alice; Lorenz, Ralph; Leyrat, Cedric

    2015-11-01

    The Pluto dwarf planet has been successfully observed in July 2015 by the New Horizons spacecraft (NASA) during a close-targeted flyby which reavealed surprising and fascinating landscapes. While data are still being downlinked on the ground, we propose to present a prediction of the observation of the Radio Science Experiment experiment (REX) that occured on July 14, 2015 and aimed at measuring the microwave brightness temperature of Pluto’s night side.Present models admit a wide range of 2015 surface conditions at Pluto and Charon, where the atmospheric pressure may undergo dramatic seasonal variation and for which measurements have been performed by the New Horizons mission. One anticipated observation is the microwave brightness temperature, heretofore anticipated as indicating surface conditions relevant to surface-atmosphere equilibrium. However, drawing on recent experience with Cassini observations at Iapetus and Titan, we call attention to the large electrical skin depth of outer solar system materials such as methane, nitrogen or water ice, such that this observation may indicate temperatures averaged over depths of several or tens of meters beneath the surface.Using a seasonally-forced thermal model to determine microwave emission we predict that the southern hemisphere observations (in the polar night in July 2015) of New Horizons should display relatively warm effective temperatures of about 40 K. This would reflect the deep heat buried over the last century of summer, even if the atmospheric pressure suggests that the surface nitrogen frost point may be much lower. We will present our predictions and discuss their impact for the interpretation of the REX measurements.

  7. Elevated neutrophil to lymphocyte ratio predicts mortality in medical inpatients with multiple chronic conditions

    PubMed Central

    Isaac, Vivian; Wu, Chia-Yi; Huang, Chun-Ta; Baune, Bernhard T.; Tseng, Chia-Lin; McLachlan, Craig S.

    2016-01-01

    Abstract Neutrophil to lymphocyte ratio (NLR) is an easy measurable laboratory marker used to evaluate systemic inflammation. Elevated NLR is associated with poor survival and increased morbidity in cancer and cardiovascular disease. However, the usefulness of NLR to predict morbidity and mortality in a hospital setting for patients with multiple chronic conditions has not been previously examined. In this study, we investigate the association between NLR and mortality in multimorbid medical inpatients. Two hundred thirty medical in-patients with chronic conditions were selected from a single academic medical center in Taiwan. Retrospective NLRs were calculated from routine full blood counts previously obtained during the initial hospital admission and at the time of discharge. Self-rated health (using a single-item question), medical disorders, depressive symptoms, and medical service utilization over a 1-year period were included in the analyses. Mortality outcomes were ascertained by reviewing electronic medical records and follow-up. The mortality rate at 2-year follow-up was 23%. Depression (odds ratio [OR] 1.9 [95% CI 1.0–3.7]), poor self-rated health (OR 2.1 [95% CI 1.1–3.9]), being hospitalized 2 or more times in the previous year (OR 2.3 [95% CI 1.2–4.6]), metastatic cancer (OR 4.7 [95% CI 2.3–9.7]), and chronic liver disease (OR 4.3 [95% CI 1.5–12.1]) were associated with 2-year mortality. The median (interquartile range) NLR at admission and discharge were 4.47 (2.4–8.7) and 3.65 (2.1–6.5), respectively. Two-year mortality rates were higher in patients with an elevated NLR at admission (NLR <3 = 15.5%, NLR >3 = 27.6%) and discharge (NLR < 3 = 14.7%, NLR >3 = 29.1%). Multivariate logistic regression demonstrated that an elevated NLR >3.0 at admission (OR 2.3 [95% CI 1.0–5.2]) and discharge (OR 2.3 [95% CI 1.1–5.0]) were associated with mortality independent of baseline age, sex, education, metastatic cancer, liver disease

  8. Elevated neutrophil to lymphocyte ratio predicts mortality in medical inpatients with multiple chronic conditions.

    PubMed

    Isaac, Vivian; Wu, Chia-Yi; Huang, Chun-Ta; Baune, Bernhard T; Tseng, Chia-Lin; McLachlan, Craig S

    2016-06-01

    Neutrophil to lymphocyte ratio (NLR) is an easy measurable laboratory marker used to evaluate systemic inflammation. Elevated NLR is associated with poor survival and increased morbidity in cancer and cardiovascular disease. However, the usefulness of NLR to predict morbidity and mortality in a hospital setting for patients with multiple chronic conditions has not been previously examined. In this study, we investigate the association between NLR and mortality in multimorbid medical inpatients. Two hundred thirty medical in-patients with chronic conditions were selected from a single academic medical center in Taiwan. Retrospective NLRs were calculated from routine full blood counts previously obtained during the initial hospital admission and at the time of discharge. Self-rated health (using a single-item question), medical disorders, depressive symptoms, and medical service utilization over a 1-year period were included in the analyses. Mortality outcomes were ascertained by reviewing electronic medical records and follow-up. The mortality rate at 2-year follow-up was 23%. Depression (odds ratio [OR] 1.9 [95% CI 1.0-3.7]), poor self-rated health (OR 2.1 [95% CI 1.1-3.9]), being hospitalized 2 or more times in the previous year (OR 2.3 [95% CI 1.2-4.6]), metastatic cancer (OR 4.7 [95% CI 2.3-9.7]), and chronic liver disease (OR 4.3 [95% CI 1.5-12.1]) were associated with 2-year mortality. The median (interquartile range) NLR at admission and discharge were 4.47 (2.4-8.7) and 3.65 (2.1-6.5), respectively. Two-year mortality rates were higher in patients with an elevated NLR at admission (NLR <3 = 15.5%, NLR >3 = 27.6%) and discharge (NLR < 3 = 14.7%, NLR >3 = 29.1%). Multivariate logistic regression demonstrated that an elevated NLR >3.0 at admission (OR 2.3 [95% CI 1.0-5.2]) and discharge (OR 2.3 [95% CI 1.1-5.0]) were associated with mortality independent of baseline age, sex, education, metastatic cancer, liver disease, depression, and previous

  9. Developing A New Predictive Dispersion Equation Based on Tidal Average (TA) Condition in Alluvial Estuaries

    NASA Astrophysics Data System (ADS)

    Anak Gisen, Jacqueline Isabella; Nijzink, Remko C.; Savenije, Hubert H. G.

    2014-05-01

    Dispersion mathematical representation of tidal mixing between sea water and fresh water in The definition of dispersion somehow remains unclear as it is not directly measurable. The role of dispersion is only meaningful if it is related to the appropriate temporal and spatial scale of mixing, which are identified as the tidal period, tidal excursion (longitudinal), width of estuary (lateral) and mixing depth (vertical). Moreover, the mixing pattern determines the salt intrusion length in an estuary. If a physically based description of the dispersion is defined, this would allow the analytical solution of the salt intrusion problem. The objective of this study is to develop a predictive equation for estimating the dispersion coefficient at tidal average (TA) condition, which can be applied in the salt intrusion model to predict the salinity profile for any estuary during different events. Utilizing available data of 72 measurements in 27 estuaries (including 6 recently studied estuaries in Malaysia), regressions analysis has been performed with various combinations of dimensionless parameters . The predictive dispersion equations have been developed for two different locations, at the mouth D0TA and at the inflection point D1TA (where the convergence length changes). Regressions have been carried out with two separated datasets: 1) more reliable data for calibration; and 2) less reliable data for validation. The combination of dimensionless ratios that give the best performance is selected as the final outcome which indicates that the dispersion coefficient is depending on the tidal excursion, tidal range, tidal velocity amplitude, friction and the Richardson Number. A limitation of the newly developed equation is that the friction is generally unknown. In order to compensate this problem, further analysis has been performed adopting the hydraulic model of Cai et. al. (2012) to estimate the friction and depth. Keywords: dispersion, alluvial estuaries, mixing, salt

  10. Building spatially-explicit model predictions for ecological condition of streams in the Pacific Northwest: An assessment of landscape variables, models, endpoints and prediction scale

    EPA Science Inventory

    While large-scale, randomized surveys estimate the percentage of a region’s streams in poor ecological condition, identifying particular stream reaches or watersheds in poor condition is an equally important goal for monitoring and management. We built predictive models of strea...

  11. Microbial Forensics: Predicting Phenotypic Characteristics and Environmental Conditions from Large-Scale Gene Expression Profiles

    PubMed Central

    Kim, Minseung; Zorraquino, Violeta; Tagkopoulos, Ilias

    2015-01-01

    A tantalizing question in cellular physiology is whether the cellular state and environmental conditions can be inferred by the expression signature of an organism. To investigate this relationship, we created an extensive normalized gene expression compendium for the bacterium Escherichia coli that was further enriched with meta-information through an iterative learning procedure. We then constructed an ensemble method to predict environmental and cellular state, including strain, growth phase, medium, oxygen level, antibiotic and carbon source presence. Results show that gene expression is an excellent predictor of environmental structure, with multi-class ensemble models achieving balanced accuracy between 70.0% (±3.5%) to 98.3% (±2.3%) for the various characteristics. Interestingly, this performance can be significantly boosted when environmental and strain characteristics are simultaneously considered, as a composite classifier that captures the inter-dependencies of three characteristics (medium, phase and strain) achieved 10.6% (±1.0%) higher performance than any individual models. Contrary to expectations, only 59% of the top informative genes were also identified as differentially expressed under the respective conditions. Functional analysis of the respective genetic signatures implicates a wide spectrum of Gene Ontology terms and KEGG pathways with condition-specific information content, including iron transport, transferases, and enterobactin synthesis. Further experimental phenotypic-to-genotypic mapping that we conducted for knock-out mutants argues for the information content of top-ranked genes. This work demonstrates the degree at which genome-scale transcriptional information can be predictive of latent, heterogeneous and seemingly disparate phenotypic and environmental characteristics, with far-reaching applications. PMID:25774498

  12. Microbial forensics: predicting phenotypic characteristics and environmental conditions from large-scale gene expression profiles.

    PubMed

    Kim, Minseung; Zorraquino, Violeta; Tagkopoulos, Ilias

    2015-03-01

    A tantalizing question in cellular physiology is whether the cellular state and environmental conditions can be inferred by the expression signature of an organism. To investigate this relationship, we created an extensive normalized gene expression compendium for the bacterium Escherichia coli that was further enriched with meta-information through an iterative learning procedure. We then constructed an ensemble method to predict environmental and cellular state, including strain, growth phase, medium, oxygen level, antibiotic and carbon source presence. Results show that gene expression is an excellent predictor of environmental structure, with multi-class ensemble models achieving balanced accuracy between 70.0% (±3.5%) to 98.3% (±2.3%) for the various characteristics. Interestingly, this performance can be significantly boosted when environmental and strain characteristics are simultaneously considered, as a composite classifier that captures the inter-dependencies of three characteristics (medium, phase and strain) achieved 10.6% (±1.0%) higher performance than any individual models. Contrary to expectations, only 59% of the top informative genes were also identified as differentially expressed under the respective conditions. Functional analysis of the respective genetic signatures implicates a wide spectrum of Gene Ontology terms and KEGG pathways with condition-specific information content, including iron transport, transferases, and enterobactin synthesis. Further experimental phenotypic-to-genotypic mapping that we conducted for knock-out mutants argues for the information content of top-ranked genes. This work demonstrates the degree at which genome-scale transcriptional information can be predictive of latent, heterogeneous and seemingly disparate phenotypic and environmental characteristics, with far-reaching applications.

  13. A uniqueness theorem of a boundary inverse problem of a differential operator on an interval with integro-differential boundary conditions

    NASA Astrophysics Data System (ADS)

    Kanguzhin, Baltabek; Tokmagambetov, Niyaz

    2016-08-01

    In this work, we research a boundary inverse problem of spectral analysis of a differential operator with integral boundary conditions in the functional space L2(0, b) where b < ∞. A uniqueness theorem of the inverse boundary problem in L2(0, b) is proved. Note that a boundary inverse problem of spectral analysis is the problem of recovering boundary conditions of the operator by its spectrum and some additional data.

  14. Predicting Ductility and Failure Modes of TRIP Steels under Different Loading Conditions

    SciTech Connect

    Choi, Kyoo Sil; Liu, Wenning N.; Sun, Xin; Khaleel, Mohammad A.

    2010-06-12

    We study the ultimate ductility and failure modes of a TRIP (TRansformation-Induced Plasticity) 800 steel under different loading conditions with an advanced micromechanics-based finite element analysis. The representative volume element (RVE) for the TRIP800 under examination is developed based on an actual microstructure obtained from scanning electron microscopy (SEM). The evolution of retained austenite during deformation process and the mechanical properties of the constituent phases of the TRIP800 steel are obtained from the synchrotron-based in-situ high-energy X-ray diffraction (HEXRD) experiments and a self-consistent (SC) model. The ductile failure of the TRIP800 under different loading conditions is predicted in the form of plastic strain localization without any prescribed failure criteria for the individual phases. Comparisons of the computational results with experimental measurements suggest that the microstructure-based finite element analysis can well capture the overall macroscopic behavior of the TRIP800 steel under different loading conditions. The methodology described in this study may be extended for studying the ultimate ductile failure mechanisms of TRIP steels as well as the effects of the various processing parameters on the macroscopic behaviors of TRIP steels.

  15. ENSO-conditioned weather resampling method for seasonal ensemble streamflow prediction

    NASA Astrophysics Data System (ADS)

    Beckers, Joost V. L.; Weerts, Albrecht H.; Tijdeman, Erik; Welles, Edwin

    2016-08-01

    Oceanic-atmospheric climate modes, such as El Niño-Southern Oscillation (ENSO), are known to affect the local streamflow regime in many rivers around the world. A new method is proposed to incorporate climate mode information into the well-known ensemble streamflow prediction (ESP) method for seasonal forecasting. The ESP is conditioned on an ENSO index in two steps. First, a number of original historical ESP traces are selected based on similarity between the index value in the historical year and the index value at the time of forecast. In the second step, additional ensemble traces are generated by a stochastic ENSO-conditioned weather resampler. These resampled traces compensate for the reduction of ensemble size in the first step and prevent degradation of skill at forecasting stations that are less affected by ENSO. The skill of the ENSO-conditioned ESP is evaluated over 50 years of seasonal hindcasts of streamflows at three test stations in the Columbia River basin in the US Pacific Northwest. An improvement in forecast skill of 5 to 10 % is found for two test stations. The streamflows at the third station are less affected by ENSO and no change in forecast skill is found here.

  16. Influence of uncertain boundary conditions and model structure on flood inundation predictions

    NASA Astrophysics Data System (ADS)

    Pappenberger, Florian; Matgen, Patrick; Beven, Keith J.; Henry, Jean-Baptiste; Pfister, Laurent; Fraipont, Paul

    2006-10-01

    In this study, the GLUE methodology is applied to establish the sensitivity of flood inundation predictions to uncertainty of the upstream boundary condition and bridges within the modelled region. An understanding of such uncertainties is essential to improve flood forecasting and floodplain mapping. The model has been evaluated on a large data set. This paper shows uncertainty of the upstream boundary can have significant impact on the model results, exceeding the importance of model parameter uncertainty in some areas. However, this depends on the hydraulic conditions in the reach e.g. internal boundary conditions and, for example, the amount of backwater within the modelled region. The type of bridge implementation can have local effects, which is strongly influenced by the bridge geometry (in this case the area of the culvert). However, the type of bridge will not merely influence the model performance within the region of the structure, but also other evaluation criteria such as the travel time. This also highlights the difficulties in establishing which parameters have to be more closely examined in order to achieve better fits. In this study no parameter set or model implementation that fulfils all evaluation criteria could be established. We propose four different approaches to this problem: closer investigation of anomalies; introduction of local parameters; increasing the size of acceptable error bounds; and resorting to local model evaluation. Moreover, we show that it can be advantageous to decouple the classification into behavioural and non-behavioural model data/parameter sets from the calculation of uncertainty bounds.

  17. Conditional spectrum computation incorporating multiple causal earthquakes and ground-motion prediction models

    USGS Publications Warehouse

    Lin, Ting; Harmsen, Stephen C.; Baker, Jack W.; Luco, Nicolas

    2013-01-01

    The conditional spectrum (CS) is a target spectrum (with conditional mean and conditional standard deviation) that links seismic hazard information with ground-motion selection for nonlinear dynamic analysis. Probabilistic seismic hazard analysis (PSHA) estimates the ground-motion hazard by incorporating the aleatory uncertainties in all earthquake scenarios and resulting ground motions, as well as the epistemic uncertainties in ground-motion prediction models (GMPMs) and seismic source models. Typical CS calculations to date are produced for a single earthquake scenario using a single GMPM, but more precise use requires consideration of at least multiple causal earthquakes and multiple GMPMs that are often considered in a PSHA computation. This paper presents the mathematics underlying these more precise CS calculations. Despite requiring more effort to compute than approximate calculations using a single causal earthquake and GMPM, the proposed approach produces an exact output that has a theoretical basis. To demonstrate the results of this approach and compare the exact and approximate calculations, several example calculations are performed for real sites in the western United States. The results also provide some insights regarding the circumstances under which approximate results are likely to closely match more exact results. To facilitate these more precise calculations for real applications, the exact CS calculations can now be performed for real sites in the United States using new deaggregation features in the U.S. Geological Survey hazard mapping tools. Details regarding this implementation are discussed in this paper.

  18. Modelling volatility recurrence intervals in the Chinese commodity futures market

    NASA Astrophysics Data System (ADS)

    Zhou, Weijie; Wang, Zhengxin; Guo, Haiming

    2016-09-01

    The law of extreme event occurrence attracts much research. The volatility recurrence intervals of Chinese commodity futures market prices are studied: the results show that the probability distributions of the scaled volatility recurrence intervals have a uniform scaling curve for different thresholds q. So we can deduce the probability distribution of extreme events from normal events. The tail of a scaling curve can be well fitted by a Weibull form, which is significance-tested by KS measures. Both short-term and long-term memories are present in the recurrence intervals with different thresholds q, which denotes that the recurrence intervals can be predicted. In addition, similar to volatility, volatility recurrence intervals also have clustering features. Through Monte Carlo simulation, we artificially synthesise ARMA, GARCH-class sequences similar to the original data, and find out the reason behind the clustering. The larger the parameter d of the FIGARCH model, the stronger the clustering effect is. Finally, we use the Fractionally Integrated Autoregressive Conditional Duration model (FIACD) to analyse the recurrence interval characteristics. The results indicated that the FIACD model may provide a method to analyse volatility recurrence intervals.

  19. Effect of pour-on alphacypermethrin on feed intake, body condition score, milk yield, pregnancy rates, and calving-to-conception interval in buffaloes.

    PubMed

    Bifulco, G; Veneziano, V; Cimmino, R; Esposito, L; Auletta, L; Varricchio, E; Balestrieri, A; Claps, S; Campanile, G; Neglia, G

    2015-04-01

    The aims of this study were to assess the efficacy of alphacypermethrin (ACYP) on pediculosis due to Haematopinus tuberculatus and to evaluate the influence of the treatment on productive and reproductive performance in buffaloes (Bubalus bubalis) reared in an intensive system. The trial was performed on 56 pluriparous buffaloes at 86.8 ± 8.1 d in milk. The animals underwent individual louse count and were divided into 2 homogenous groups according to louse count, age, number of lactations, days in milk, live BW, BCS, pregnancy status, and milk yield. Group A (n = 28) was treated by a pour-on formulation of ACYP, and Group S (n = 28) was treated by pour-on saline solution. Individual louse counts were performed weekly on 10 buffaloes in each group. Feed intake was recorded daily and the total mixed ration, individual ingredients, and orts were analyzed to calculate DM ingestion. Individual milk yield was recorded daily and milk samples were analyzed at the beginning of the trial, after 4 wk, and at the end of the trial to assess milk composition. Individual BCS was also evaluated simultaneously. Finally, the animals underwent synchronization of ovulation starting 4 wk after treatment and the pregnancy rate and the calving-conception interval were evaluated. Data were analyzed by the Mann-Whitney test and ANOVA for repeated measures. The infestation was constant in Group S, whereas no lice were present in Group A throughout the study. Daily DMI was similar in the 2 groups (16.7 ± 0.4 vs. 16.3 ± 0.3 kg/d in Group A vs. Group S, respectively), although buffaloes in Group A showed higher (P < 0.05) BCS score at the end of the trial (7.39 ± 0.1 vs. 7.14 ± 0.1 in Group A vs. Group S, respectively). The average milk yield/buffalo was higher (P < 0.05) in Group A compared to Group S (10.58 ± 0.1 vs. 10.39 ± 0.1 kg in Group A vs. Group S, respectively) and this was mainly due to the higher milk production recorded in buffaloes at less than 75 d in milk (11.81 ± 0

  20. Effect of pour-on alphacypermethrin on feed intake, body condition score, milk yield, pregnancy rates, and calving-to-conception interval in buffaloes.

    PubMed

    Bifulco, G; Veneziano, V; Cimmino, R; Esposito, L; Auletta, L; Varricchio, E; Balestrieri, A; Claps, S; Campanile, G; Neglia, G

    2015-04-01

    The aims of this study were to assess the efficacy of alphacypermethrin (ACYP) on pediculosis due to Haematopinus tuberculatus and to evaluate the influence of the treatment on productive and reproductive performance in buffaloes (Bubalus bubalis) reared in an intensive system. The trial was performed on 56 pluriparous buffaloes at 86.8 ± 8.1 d in milk. The animals underwent individual louse count and were divided into 2 homogenous groups according to louse count, age, number of lactations, days in milk, live BW, BCS, pregnancy status, and milk yield. Group A (n = 28) was treated by a pour-on formulation of ACYP, and Group S (n = 28) was treated by pour-on saline solution. Individual louse counts were performed weekly on 10 buffaloes in each group. Feed intake was recorded daily and the total mixed ration, individual ingredients, and orts were analyzed to calculate DM ingestion. Individual milk yield was recorded daily and milk samples were analyzed at the beginning of the trial, after 4 wk, and at the end of the trial to assess milk composition. Individual BCS was also evaluated simultaneously. Finally, the animals underwent synchronization of ovulation starting 4 wk after treatment and the pregnancy rate and the calving-conception interval were evaluated. Data were analyzed by the Mann-Whitney test and ANOVA for repeated measures. The infestation was constant in Group S, whereas no lice were present in Group A throughout the study. Daily DMI was similar in the 2 groups (16.7 ± 0.4 vs. 16.3 ± 0.3 kg/d in Group A vs. Group S, respectively), although buffaloes in Group A showed higher (P < 0.05) BCS score at the end of the trial (7.39 ± 0.1 vs. 7.14 ± 0.1 in Group A vs. Group S, respectively). The average milk yield/buffalo was higher (P < 0.05) in Group A compared to Group S (10.58 ± 0.1 vs. 10.39 ± 0.1 kg in Group A vs. Group S, respectively) and this was mainly due to the higher milk production recorded in buffaloes at less than 75 d in milk (11.81 ± 0

  1. Improved Prediction of Quasi-Global Vegetation Conditions Using Remotely-Sensed Surface Soil Moisture

    NASA Technical Reports Server (NTRS)

    Bolten, John; Crow, Wade

    2012-01-01

    The added value of satellite-based surface soil moisture retrievals for agricultural drought monitoring is assessed by calculating the lagged rank correlation between remotely-sensed vegetation indices (VI) and soil moisture estimates obtained both before and after the assimilation of surface soil moisture retrievals derived from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) into a soil water balance model. Higher soil moisture/VI lag correlations imply an enhanced ability to predict future vegetation conditions using estimates of current soil moisture. Results demonstrate that the assimilation of AMSR-E surface soil moisture retrievals substantially improve the performance of a global drought monitoring system - particularly in sparsely-instrumented areas of the world where high-quality rainfall observations are unavailable.

  2. Predicting the drying properties of sludge based on hydrothermal treatment under subcritical conditions.

    PubMed

    Mäkelä, Mikko; Fraikin, Laurent; Léonard, Angélique; Benavente, Verónica; Fullana, Andrés

    2016-03-15

    The effects of hydrothermal treatment on the drying properties of sludge were determined. Sludge was hydrothermally treated at 180-260 °C for 0.5-5 h using NaOH and HCl as additives to influence reaction conditions. Untreated sludge and attained hydrochar samples were then dried under identical conditions with a laboratory microdryer and an X-ray microtomograph was used to follow changes in sample dimensions. The effective moisture diffusivities of sludge and hydrochar samples were determined and the effect of process conditions on respective mean diffusivities evaluated using multiple linear regression. Based on the results the drying time of untreated sludge decreased from approximately 80 min to 37-59 min for sludge hydrochar. Drying of untreated sludge was governed by the falling rate period where drying flux decreased continuously as a function of sludge moisture content due to heat and mass transfer limitations and sample shrinkage. Hydrothermal treatment increased the drying flux of sludge hydrochar and decreased the effect of internal heat and mass transfer limitations and sample shrinkage especially at higher treatment temperatures. The determined effective moisture diffusivities of sludge and hydrochar increased as a function of decreasing moisture content and the mean diffusivity of untreated sludge (8.56·10(-9) m(2) s(-1)) and sludge hydrochar (12.7-27.5·10(-9) m(2) s(-1)) were found statistically different. The attained regression model indicated that treatment temperature governed the mean diffusivity of hydrochar, as the effects of NaOH and HCl were statistically insignificant. The attained results enabled prediction of sludge drying properties through mean moisture diffusivity based on hydrothermal treatment conditions. PMID:26773481

  3. Transport of simazine in unsaturated sandy soil and predictions of its leaching under hypothetical field conditions.

    PubMed

    Suárez, Francisco; Bachmann, Jaime; Muñoz, José F; Ortiz, Cristian; Tyler, Scott W; Alister, Claudio; Kogan, Marcelo

    2007-12-01

    The potential contamination of groundwater by herbicides is often controlled by processes in the vadose zone, through which herbicides travel before entering groundwater. In the vadose zone, both physical and chemical processes affect the fate and transport of herbicides, therefore it is important to represent these processes by mathematical models to predict contaminant movement. To simulate the movement of simazine, a herbicide commonly used in Chilean vineyards, batch and miscible displacement column experiments were performed on a disturbed sandy soil to quantify the primary parameters and processes of simazine transport. Chloride (Cl(-)) was used as a non-reactive tracer, and simazine as the reactive tracer. The Hydrus-1D model was used to estimate the parameters by inversion from the breakthrough curves of the columns and to evaluate the potential groundwater contamination in a sandy soil from the Casablanca Valley, Chile. The two-site, chemical non-equilibrium model was observed to best represent the experimental results of the miscible displacement experiments in laboratory soil columns. Predictions of transport under hypothetical field conditions using the same soil from the column experiments were made for 40 years by applying herbicide during the first 20 years, and then halting the application and considering different rates of groundwater recharge. For recharge rates smaller than 84 mm year(-1), the predicted concentration of simazine at a depth of 1 m is below the U.S. EPA's maximum contaminant levels (4 microg L(-1)). After eight years of application at a groundwater recharge rate of 180 mm year(-1) (approximately 50% of the annual rainfall), simazine was found to reach the groundwater (located at 1 m depth) at a higher concentration (more than 40 microg L(-1)) than the existing guidelines in the USA and Europe.

  4. Ion exchange chromatography of proteins-predictions of elution curves and operating conditions. II. Experimental verification.

    PubMed

    Yamamoto, S; Nakanishi, K; Matsuno, R; Kamijubo, T

    1983-05-01

    The applicability and validity of the model developed in Part I were confirmed experimentally. In this article, various proteins were eluted both by stepwise and linear gradient elution on DEAE ion exchangers under a variety of experimental conditions. Adsorption isotherms were measured as a function of ionic strength in batch experiments. The moment method was employed for the determination of various parameters such as the gel-phase diffusion coefficient and the longitudinal dispersion coefficient. By use of these parameters and the experimentally measured ionic strength of the peak position, the number of plates was determined according to the method described in Part I. Theoretical elution curves were calculated with the experimentally measured adsorption equilibria and the number of plates. Good agreement was observed between theory an experiments. Various factors affecting the separation were investigated. It was found that the effect of the number of plates for salts, N'(p), was negligible except the case of stepwise elution of high ionic strength buffer. When elution curves were symmetrical, the widths of the elution curves were inversely proportional to the square root of the number of plates of proteins, N(p), as in other chromatographic techniques. A simple graphical method for prediction of the peak position in linear gradient elution described in Part I was found applicable when the elution curves were symmetrical. A useful correlation of prediction of the peak width in a linear gradient elution was proposed on the basis of the approximate solution derived in Part I of this study. This graphical method and correlation permit easy prediction of the peak position and peak width in linear gradient elution in the case of symmetrical elution curves.

  5. Experimental tests and predictive model of an adsorptive air conditioning unit

    SciTech Connect

    Poyelle, F.; Guilleminot, J.J.; Meunier, F.

    1999-01-01

    An adsorption air conditioning unit has been built operating with a heat nd mass recovery cycle and a zeolite-water pair. A new consolidated adsorbent composite with good heat transfer properties has been developed and implemented in the adsorber. At an evaporating temperature of 4 C, the experimental specific cooling power (SCP) of 97 W/kg achieved represents a real improvement in comparison with those measured with a packed bed technology. At this evaporating pressure, the mass transfer resistance controls the process. Therefore, at higher evaporating temperature a COP of 0.68 and a SCP of 135 W/kg were experimentally achieved. A new model has been developed to take into account the mass transfer limitations. The model has been validated and can predict the average pressure inside the adsorber and the components temperature of the unit. A new high conductive material with enhanced mass transfer properties has been developed. The predictive model shows that a SCP of 600 W/kg and a COP of 0.74 could be achieved with this new material.

  6. Variably-saturated flow in large weighing lysimeters under dry conditions: inverse and predictive modeling

    NASA Astrophysics Data System (ADS)

    Iden, Sascha; Reineke, Daniela; Koonce, Jeremy; Berli, Markus; Durner, Wolfgang

    2015-04-01

    A reliable quantification of the soil water balance in semi-arid regions requires an accurate determination of bare soil evaporation. Modeling of soil water movement in relatively dry soils and the quantitative prediction of evaporation rates and groundwater recharge pose considerable challenges in these regions. Actual evaporation from dry soil cannot be predicted without detailed knowledge of the complex interplay between liquid, vapor and heat flow and soil hydraulic properties exert a strong influence on evaporation rates during stage-two evaporation. We have analyzed data from the SEPHAS lysimeter facility in Boulder City (NV) which was installed to investigate the near-surface processes of water and energy exchange in desert environments. The scientific instrumentation consists of 152 sensors per Lysimeter which measured soil temperature, soil water content, and soil water potential. Data from three weighing lysimeters (3 m long, surface area 4 m2) were used to identifiy effective soil hydraulic properties of the disturbed soil monoliths by inverse modeling with the Richards equation assuming isothermal flow conditions. Results indicate that the observed soil water content in 8 different soil depths can be well matched for all three lysimeters and that the effective soil hydraulic properties of the three lysimeters agree well. These results could only be obtained with a flexible model of the soil hydraulic properties which guaranteed physical plausibility of water retention towards complete dryness and accounted for capillary, film and isothermal vapor flow. Conversely, flow models using traditional parameterizations of the soil hydraulic properties were not able to match the observed evaporation fluxes and water contents. After identifying the system properties by inverse modeling, we checked the possibility to forecast evaporation rates by running a fully coupled water, heat and vapor flow model which solved the energy balance of the soil surface. In these

  7. Aeroheating Testing and Predictions for Project Orion CEV at Turbulent Conditions

    NASA Technical Reports Server (NTRS)

    Hollis, Brian R.; Berger, Karen T.; Horvath, Thomas J.; Coblish, Joseph J.; Norris, Joseph D.; Lillard, Randolph P.; Kirk, Benjamin S.

    2009-01-01

    An investigation of the aeroheating environment of the Project Orion Crew Exploration Vehicle was performed in the Arnold Engineering Development Center Hypervelocity Wind Tunnel No. 9 Mach 8 and Mach 10 nozzles and in the NASA Langley Research Center 20 - Inch Mach 6 Air Tunnel. Heating data were obtained using a thermocouple-instrumented approx.0.035-scale model (0.1778-m/7-inch diameter) of the flight vehicle. Runs were performed in the Tunnel 9 Mach 10 nozzle at free stream unit Reynolds numbers of 1x10(exp 6)/ft to 20x10(exp 6)/ft, in the Tunnel 9 Mach 8 nozzle at free stream unit Reynolds numbers of 8 x 10(exp 6)/ft to 48x10(exp 6)/ft, and in the 20-Inch Mach 6 Air Tunnel at free stream unit Reynolds numbers of 1x10(exp 6)/ft to 7x10(exp 6)/ft. In both facilities, enthalpy levels were low and the test gas (N2 in Tunnel 9 and air in the 20-Inch Mach 6) behaved as a perfect-gas. These test conditions produced laminar, transitional and turbulent data in the Tunnel 9 Mach 10 nozzle, transitional and turbulent data in the Tunnel 9 Mach 8 nozzle, and laminar and transitional data in the 20- Inch Mach 6 Air Tunnel. Laminar and turbulent predictions were generated for all wind tunnel test conditions and comparisons were performed with the experimental data to help define the accuracy of computational method. In general, it was found that both laminar data and predictions, and turbulent data and predictions, agreed to within less than the estimated 12% experimental uncertainty estimate. Laminar heating distributions from all three data sets were shown to correlate well and demonstrated Reynolds numbers independence when expressed in terms of the Stanton number based on adiabatic wall-recovery enthalpy. Transition onset locations on the leeside centerline were determined from the data and correlated in terms of boundary-layer parameters. Finally turbulent heating augmentation ratios were determined for several body-point locations and correlated in terms of the

  8. Predicting the solubility of gases in Nitrile Butadiene Rubber in extreme conditions using molecular simulation

    NASA Astrophysics Data System (ADS)

    Khawaja, Musab; Molinari, Nicola; Sutton, Adrian; Mostofi, Arash

    In the oil and gas industry, elastomer seals play an important role in protecting sensitive monitoring equipment from contamination by gases - a problem that is exacerbated by the high pressures and temperatures found down-hole. The ability to predict and prevent such permeative failure has proved elusive to-date. Nitrile butadiene rubber (NBR) is a common choice of elastomer for seals due to its resistance to heat and fuels. In the conditions found in the well it readily absorbs small molecular weight gases. How this behaviour changes quantitatively for different gases as a function of temperature and pressure is not well-understood. In this work a series of fully atomistic simulations are performed to understand the effect of extreme conditions on gas solubility in NBR. Widom particle insertion is used to compute solubilities. The importance of sampling and allowing structural relaxation upon compression are highlighted, and qualitatively reasonable trends reproduced. Finally, while at STP it has previously been shown that the solubility of CO2 is higher than that of He in NBR, we observe that under the right circumstances it is possible to reverse this trend.

  9. Mercury's core fraction and ancient crustal composition: Predictions from planetary formation under extremely reducing conditions

    NASA Astrophysics Data System (ADS)

    Brown, S. M.; Elkins-Tanton, L.

    2007-12-01

    Several hypotheses have been suggested to explain the paradox of Mercury's large core, which is on the order of sixty percent of the mass of the planet and recently demonstrated to be at least partially molten. Here we suggest that extremely reducing conditions in the earliest stages of planetary accretion nearest to the Sun may have produced the unusual metallic iron fraction by reducing iron otherwise bound into silicates. We demonstrate the formation conditions necessary for various meteoritic bulk compositions to produce the core/mantle ratio of Mercury. During this hypothetical core formation, we assume the remaining silicate fraction of Mercury (now largely lacking iron) has been heated to produce a magma ocean. The resulting cumulate mantle composition is calculated in a Matlab simulation of magma ocean solidification using a CMAS system adapted for Mercury. Plagioclase flotation, frequently cited as the necessary signature of a magma ocean, is highly dependent upon initial bulk composition. We demonstrate the initial silicate iron content of the magma ocean necessary to make plagioclase buoyant and thus produce a plagioclase flotation crust as seen on the Moon. In addition, over a range of bulk compositions the solidified mantle cumulates are unstable to gravitational overturn. During overturn hot cumulates rise from depth and may cross their solidi and melt, producing an earliest planetary crust. This crust may still exist on Mercury. With the first flyby results of the MESSENGER mission coming this winter, predictions from these models can be compared with initial ground measurements.

  10. Prediction of the radiation situation during conditioned radioactive waste storage in hangar-type storage facilities

    NASA Astrophysics Data System (ADS)

    Rosnovskii, S. V.; Bulka, S. K.

    2014-02-01

    An original technology for the conditioning of solidified radioactive waste was developed by the Novovoronezh nuclear power plant (NPP) staff. The technology provides for waste placement inside NZK-150-1.5P containers with their further storage at light hangar-type storage facilities. A number of technical solutions were developed that allow for reducing the gamma-radiation dose rate from the package formed. A methodology for prediction of the radiation situation around hangars, depending on the radiation characteristics of irrecoverable shielding containers (ISCs) located in the peripheral row of a storage facility, was developed with the purpose of assuring safe storage. Based on empirical data, the field background gamma-radiation dose rate at an area as a function of the average dose rate at the hangar surface and the average dose rate close packages, placed in the peripheral row of the storage facility, was calculated. The application of the developed methodology made it possible to reduce by ten times the expenditures for the conditioning and holding of solidified radioactive waste (SRW) while unconditionally providing storage safety.

  11. Prediction of glass durability as a function of glass composition and test conditions: Thermodynamics and kinetics

    SciTech Connect

    Jantzen, C M

    1988-01-01

    The long-term durability of nuclear waste glasses can be predicted by comparing their performance to natural and ancient glasses. Glass durability is a function of the kinetic and thermodynamic stability of glass in solution. The relationship between the kinetic and thermodynamic aspects of glass durability can be understood when the relative contributions of glass composition and imposed test conditions are delineated. Glass durability has been shown to be a function of the thermodynamic hydration free energy which can be calculated from the glass composition. Hydration thermodynamics also furnishes a quantitative frame of reference to understand how various test parameters affect glass durability. Linear relationships have been determined between the logarithmic extent of hydration and the calculated hydration free energy for several different test geometries. Different test conditions result in different kinetic reactivity parameters such as the exposed glass surface area (SA), the leachant solution volume (V), and the length of time that the glass is in the leachant (t). Leachate concentrations are known to be a function of the kinetic test parameter (SAV)t. The relative durabilities of glasses, including pure silica, obsidians, nuclear waste glasses, medieval window glasses, and frit glasses define a plane in three dimensional ..delta..G/sub hyd/-concentration-(SAV)t space. At constant kinetic conditions, e.g., test geometry and test duration, the three dimensional plane is intersected at constant (SAV)t and the ..delta..G/sub hyd/-concentration plots have similar slopes. The slope represents the natural logarithm of the theoretical slope, (12.303 RT), for the rate of glass dissolution. 53 refs., 4 figs.

  12. Geochemical Predictions of Elemental Compositions using Remote LIBS under Mars Conditions

    NASA Astrophysics Data System (ADS)

    Dyar, M. D.; Tucker, J.; Humphries, S.; Clegg, S. M.; Wiens, R. C.; Carmosino, M. L.

    2010-12-01

    The ChemCam instrument on Mars Science Laboratory will be the first deployment of laser-induced breakdown spectroscopy (LIBS) for remote geochemical analysis. Successful quantitative analyses of those results will use in-situ calibration targets and laboratory calibrations, and employ sophisticated algorithms for data reduction in order to correct for variations in peak intensities and areas caused by interactions in the plasma that are a function of chemical composition. Such chemical matrix effects influence the ratio of each emission line to the abundance of the element that produces it, and are directly related to the elemental composition of the sample. Advances in statistical analysis of LIBS data that mitigate matrix effects and provide for accurate and precise bulk analysis of major, minor, and trace elements are reported here. Our in-house data set currently includes LIBS spectra of >140 rock powders (igneous, metamorphic, and sedimentary) with highly-varying compositions (as determined by XRF) that were acquired at 7-9 m standoff distance under Mars atmospheric conditions using a laboratory instrument [1]. LIBS spectra were modeled using partial least squares analysis (PLS) to predict elemental compositions. Within the igneous suite, 10 repeat measurements of a single sample demonstrates consistency and precision; calculated 1-σ errors were 1.6 wt.%SiO2, 1.5 wt.% Al2O3, 0.4 wt.% TiO2, 1.2 wt.% Fe2O3T, 1.6 wt.% MgO, 0.02 wt.% MnO, 1.1 wt.% CaO, 0.5 wt.% Na2O, 0.2 wt.% P2O5, and 0.4 wt.% K2O. In the overall suite, predictions of all elements, expressed as root mean square errors (RMSEP), are better than ±2.45 for SiO2, ±1.64 for Al2O3, ±0.38 for TiO2, ±1.50 for Fe2O3T, ±1.88 for MgO, ±0.03 for MnO, ±0.82 for CaO, ±0.55 for K2O, ±0.62 for Na2O, and ±0.24 for P2O5 in units of wt.% oxides. On-going work should reduce these values even further. For elements at low concentrations, multivariate analyses must be interpreted with care because their

  13. A Novel Remote Sensing Approach for Prediction of Maize Yield Under Different Conditions of Nitrogen Fertilization

    PubMed Central

    Vergara-Díaz, Omar; Zaman-Allah, Mainassara A.; Masuka, Benhildah; Hornero, Alberto; Zarco-Tejada, Pablo; Prasanna, Boddupalli M.; Cairns, Jill E.; Araus, José L.

    2016-01-01

    Maize crop production is constrained worldwide by nitrogen (N) availability and particularly in poor tropical and subtropical soils. The development of affordable high-throughput crop monitoring and phenotyping techniques is key to improving maize cultivation under low-N fertilization. In this study several vegetation indices (VIs) derived from Red-Green-Blue (RGB) digital images at the leaf and canopy levels are proposed as low-cost tools for plant breeding and fertilization management. They were compared with the performance of the normalized difference vegetation index (NDVI) measured at ground level and from an aerial platform, as well as with leaf chlorophyll content (LCC) and other leaf composition and structural parameters at flowering stage. A set of 10 hybrids grown under five different nitrogen regimes and adequate water conditions were tested at the CIMMYT station of Harare (Zimbabwe). Grain yield and leaf N concentration across N fertilization levels were strongly predicted by most of these RGB indices (with R2~ 0.7), outperforming the prediction power of the NDVI and LCC. RGB indices also outperformed the NDVI when assessing genotypic differences in grain yield and leaf N concentration within a given level of N fertilization. The best predictor of leaf N concentration across the five N regimes was LCC but its performance within N treatments was inefficient. The leaf traits evaluated also seemed inefficient as phenotyping parameters. It is concluded that the adoption of RGB-based phenotyping techniques may significantly contribute to the progress of plant breeding and the appropriate management of fertilization. PMID:27242867

  14. A Novel Remote Sensing Approach for Prediction of Maize Yield Under Different Conditions of Nitrogen Fertilization.

    PubMed

    Vergara-Díaz, Omar; Zaman-Allah, Mainassara A; Masuka, Benhildah; Hornero, Alberto; Zarco-Tejada, Pablo; Prasanna, Boddupalli M; Cairns, Jill E; Araus, José L

    2016-01-01

    Maize crop production is constrained worldwide by nitrogen (N) availability and particularly in poor tropical and subtropical soils. The development of affordable high-throughput crop monitoring and phenotyping techniques is key to improving maize cultivation under low-N fertilization. In this study several vegetation indices (VIs) derived from Red-Green-Blue (RGB) digital images at the leaf and canopy levels are proposed as low-cost tools for plant breeding and fertilization management. They were compared with the performance of the normalized difference vegetation index (NDVI) measured at ground level and from an aerial platform, as well as with leaf chlorophyll content (LCC) and other leaf composition and structural parameters at flowering stage. A set of 10 hybrids grown under five different nitrogen regimes and adequate water conditions were tested at the CIMMYT station of Harare (Zimbabwe). Grain yield and leaf N concentration across N fertilization levels were strongly predicted by most of these RGB indices (with R (2)~ 0.7), outperforming the prediction power of the NDVI and LCC. RGB indices also outperformed the NDVI when assessing genotypic differences in grain yield and leaf N concentration within a given level of N fertilization. The best predictor of leaf N concentration across the five N regimes was LCC but its performance within N treatments was inefficient. The leaf traits evaluated also seemed inefficient as phenotyping parameters. It is concluded that the adoption of RGB-based phenotyping techniques may significantly contribute to the progress of plant breeding and the appropriate management of fertilization. PMID:27242867

  15. In vitro simulation of pathological bone conditions to predict clinical outcome of bone tissue engineered materials

    NASA Astrophysics Data System (ADS)

    Nguyen, Duong Thuy Thi

    According to the Centers for Disease Control, the geriatric population of ≥65 years of age will increase to 51.5 million in 2020; 40% of white women and 13% of white men will be at risk for fragility fractures or fractures sustained under normal stress and loading conditions due to bone disease, leading to hospitalization and surgical treatment. Fracture management strategies can be divided into pharmaceutical therapy, surgical intervention, and tissue regeneration for fracture prevention, fracture stabilization, and fracture site regeneration, respectively. However, these strategies fail to accommodate the pathological nature of fragility fractures, leading to unwanted side effects, implant failures, and non-unions. Compromised innate bone healing reactions of patients with bone diseases are exacerbated with protective bone therapy. Once these patients sustain a fracture, bone healing is a challenge, especially when fracture stabilization is unsuccessful. Traditional stabilizing screw and plate systems were designed with emphasis on bone mechanics rather than biology. Bone grafts are often used with fixation devices to provide skeletal continuity at the fracture gap. Current bone grafts include autologous bone tissue and donor bone tissue; however, the quality and quantity demanded by fragility fractures sustained by high-risk geriatric patients and patients with bone diseases are not met. Consequently, bone tissue engineering strategies are advancing towards functionalized bone substitutes to provide fracture reconstruction while effectively mediating bone healing in normal and diseased fracture environments. In order to target fragility fractures, fracture management strategies should be tailored to allow bone regeneration and fracture stabilization with bioactive bone substitutes designed for the pathological environment. The clinical outcome of these materials must be predictable within various disease environments. Initial development of a targeted

  16. Donor Chimerism Early after Reduced-intensity Conditioning Hematopoietic Stem Cell Transplantation Predicts Relapse and Survival

    PubMed Central

    Koreth, John; Kim, Haesook T.; Nikiforow, Sarah; Milford, Edgar L.; Armand, Philippe; Cutler, Corey; Glotzbecker, Brett; Ho, Vincent T.; Antin, Joseph H.; Soiffer, Robert J.; Ritz, Jerome; Alyea, Edwin P.

    2015-01-01

    The impact of early donor cell chimerism on outcomes of T-replete reduced-intensity conditioning (RIC) hematopoietic stem cell transplantation (HSCT) is ill-defined. We evaluated day 30 (D30) and 100 (D100) total donor cell chimerism after RIC HSCT undertaken between 2002 and 2010 at our institution, excluding patients who died or relapsed before D30. When available, donor T-cell chimerism was also assessed. The primary outcome was overall survival (OS). Secondary outcomes included progression-free survival (PFS), relapse and non-relapse mortality (NRM). 688 patients with hematologic malignancies (48% myeloid; 52% lymphoid) and a median age of 57 years (range, 18-74) undergoing RIC HSCT with T-replete donor grafts (97% peripheral blood; 92% HLA-matched) and median follow-up of 58.2 months (range, 12.6-120.7) were evaluated. In multivariable analysis total donor cell and T-cell chimerism at D30 and D100 each predicted RIC HSCT outcomes, with D100 total donor cell chimerism most predictive. D100 total donor cell chimerism <90% was associated with increased relapse (HR 2.54, 95% CI 1.83-3.51, p<0.0001), impaired PFS (HR 2.01, 95% CI 1.53-2.65, p<0.0001) and worse OS (1.50, 95% CI 1.11-2.04, p=0.009), but not NRM (HR 0.76; 95% CI 0.44-2.27, p=0.33). There was no additional utility of incorporating sustained D30-D100 total donor cell chimerism, or T-cell chimerism. Low donor chimerism early after RIC HSCT is an independent risk factor for relapse and impaired survival. Donor chimerism assessment early after RIC HSCT can prognosticate for long-term outcomes and help identify high-risk patient cohorts that may benefit from additional therapeutic interventions. PMID:24907627

  17. Stagnation-point heat-transfer rate predictions at aeroassist flight conditions

    NASA Technical Reports Server (NTRS)

    Gupta, Roop N.; Jones, Jim J.; Rochelle, William C.

    1992-01-01

    The results are presented for the stagnation-point heat-transfer rates used in the design process of the Aeroassist Flight Experiment (AFE) vehicle over its entire aeropass trajectory. The prediction methods used in this investigation demonstrate the application of computational fluid dynamics (CFD) techniques to a wide range of flight conditions and their usefulness in a design process. The heating rates were computed by a viscous-shock-layer (VSL) code at the lower altitudes and by a Navier-Stokes (N-S) code for the higher altitude cases. For both methods, finite-rate chemically reacting gas was considered, and a temperature-dependent wall-catalysis model was used. The wall temperature for each case was assumed to be radiative equilibrium temperature, based on total heating. The radiative heating was estimated by using a correlation equation. Wall slip was included in the N-S calculation method, and this method implicitly accounts for shock slip. The N-S/VSL combination of projection methods was established by comparison with the published benchmark flow-field code LAURA results at lower altitudes, and the direct simulation Monte Carlo results at higher altitude cases. To obtain the design heating rate over the entire forward face of the vehicle, a boundary-layer method (BLIMP code) that employs reacting chemistry and surface catalysis was used. The ratio of the VSL or N-S method prediction to that obtained from the boundary-layer method code at the stagnation point is used to define an adjustment factor, which accounts for the errors involved in using the boundary-layer method.

  18. An ENSO prediction approach based on ocean conditions and ocean-atmosphere coupling

    NASA Astrophysics Data System (ADS)

    Tseng, Yu-heng; Hu, Zeng-Zhen; Ding, Ruiqiang; Chen, Han-ching

    2016-05-01

    A simple statistical model for the El Niño-Southern Oscillation (ENSO) prediction is derived based on the evolution of the ocean heat condition and the oceanic Kelvin wave propagation associated with westerly wind events (WWEs) and easterly wind surges (EWSs) in the tropical Pacific. The multivariate linear regression model solely relies on the pentad thermocline depth anomaly evolution in 25 days along with the zonal surface wind modulation. It successfully hindcasts all ENSOs except for the 2000/01 La Niña, using the pentad (or monthly) mean tropical atmosphere ocean array data since 1994 with an averaged skill (measured by anomaly correlation) of 0.62 (or 0.67) with a 6-month lead. The exception is mainly due to the long-lasting cold sea surface temperature anomalies in the subtropics resulting from the strong 1998/99 La Niña, even though the tropical warm water volume (WWV) had rebounded and turned phases after 2000. We also note that the hindcast skill is comparable using pentad or monthly mean NCEP global ocean data assimilation system data for the same time period. The hindcast skill of the proposed statistical model is better than that based on the WWV index in terms of the monthly correlation, normalized RMSEs and ENSO occurrences, which suggest that including the evolution of the subsurface ocean temperature anomaly and the WWEs/EWSs in the central tropical Pacific can enhance the ability to predict ENSO. The hindcast skill is also comparable to the predictions using other dynamical and statistical models, indicating that these processes are the keys to ENSO development. The dynamics behind the statistical model are consistent with the physical processes of ENSO development as follows: the tropical WWV resulting from the interannually-varying meridional subtropical cell transport provides a sufficient heat source. When the seasonal phase lock of ocean-atmosphere coupling triggers the positive (negative) zonal wind anomaly in boreal summer and fall, an

  19. Updating representations of temporal intervals.

    PubMed

    Danckert, James; Anderson, Britt

    2015-12-01

    Effectively engaging with the world depends on accurate representations of the regularities that make up that world-what we call mental models. The success of any mental model depends on the ability to adapt to changes-to 'update' the model. In prior work, we have shown that damage to the right hemisphere of the brain impairs the ability to update mental models across a range of tasks. Given the disparate nature of the tasks we have employed in this prior work (i.e. statistical learning, language acquisition, position priming, perceptual ambiguity, strategic game play), we propose that a cognitive module important for updating mental representations should be generic, in the sense that it is invoked across multiple cognitive and perceptual domains. To date, the majority of our tasks have been visual in nature. Given the ubiquity and import of temporal information in sensory experience, we examined the ability to build and update mental models of time. We had healthy individuals complete a temporal prediction task in which intervals were initially drawn from one temporal range before an unannounced switch to a different range of intervals. Separate groups had the second range of intervals switch to one that contained either longer or shorter intervals than the first range. Both groups showed significant positive correlations between perceptual and prediction accuracy. While each group updated mental models of temporal intervals, those exposed to shorter intervals did so more efficiently. Our results support the notion of generic capacity to update regularities in the environment-in this instance based on temporal information. The task developed here is well suited to investigations in neurological patients and in neuroimaging settings.

  20. Updating representations of temporal intervals.

    PubMed

    Danckert, James; Anderson, Britt

    2015-12-01

    Effectively engaging with the world depends on accurate representations of the regularities that make up that world-what we call mental models. The success of any mental model depends on the ability to adapt to changes-to 'update' the model. In prior work, we have shown that damage to the right hemisphere of the brain impairs the ability to update mental models across a range of tasks. Given the disparate nature of the tasks we have employed in this prior work (i.e. statistical learning, language acquisition, position priming, perceptual ambiguity, strategic game play), we propose that a cognitive module important for updating mental representations should be generic, in the sense that it is invoked across multiple cognitive and perceptual domains. To date, the majority of our tasks have been visual in nature. Given the ubiquity and import of temporal information in sensory experience, we examined the ability to build and update mental models of time. We had healthy individuals complete a temporal prediction task in which intervals were initially drawn from one temporal range before an unannounced switch to a different range of intervals. Separate groups had the second range of intervals switch to one that contained either longer or shorter intervals than the first range. Both groups showed significant positive correlations between perceptual and prediction accuracy. While each group updated mental models of temporal intervals, those exposed to shorter intervals did so more efficiently. Our results support the notion of generic capacity to update regularities in the environment-in this instance based on temporal information. The task developed here is well suited to investigations in neurological patients and in neuroimaging settings. PMID:26303026

  1. Jet fuel ignition delay times: Shock tube experiments over wide conditions and surrogate model predictions

    SciTech Connect

    Vasu, Subith S.; Davidson, David F.; Hanson, Ronald K.

    2008-01-15

    Ignition delay times were measured for gas-phase jet fuel (Jet-A and JP-8) in air behind reflected shock waves in a heated high-pressure shock tube. Initial reflected shock conditions were as follows: temperatures of 715-1229 K, pressures of 17-51 atm, equivalence ratios of 0.5 and 1, and oxygen concentrations of 10 and 21% in synthetic air. Ignition delay times were measured using sidewall pressure and OH* emission at 306 nm. Longer ignition delay times at low temperatures (715-850 K) were accessed by utilizing driver-gas tailoring methods. Also presented is a review of previous ignition delay time measurements of kerosene-based fuels and recent work on surrogate fuel and kinetic mechanism development. To our knowledge, we report the first gas-phase shock tube ignition delay time data for JP-8, and our measurements for Jet-A are for a broader range of conditions than previously available. Our results have very low scatter and are in excellent agreement with the limited previous shock tube data for Jet-A. Although JP-8 and Jet-A have slightly different compositions, their ignition delay times are very similar. A simple 1/P dependence was found for ignition delay times from 874 to 1220 K for the pressure range studied for both fuels. Ignition delay time variations with equivalence ratio and oxygen concentration were also investigated. The new experimental results were compared with predictions of several kinetic mechanisms, using different jet fuel surrogate mixtures. (author)

  2. Towards national mapping of aquatic condition (II): Predicting the probable biological condition of USA streams and rivers

    EPA Science Inventory

    The US EPA’s National River and Stream Assessment (NRSA) uses spatially balanced sampling to estimate the proportion of streams within the conterminous US (CONUS) that deviate from least-disturbed biological condition (BC). These assessments do not infer BC at un-sampled st...

  3. Computer prediction of human thermoregulatory and temperature responses to a wide range of environmental conditions

    NASA Astrophysics Data System (ADS)

    Fiala, D.; Lomas, K. J.; Stohrer, M.

    A mathematical model for predicting human thermal and regulatory responses in cold, cool, neutral, warm, and hot environments has been developed and validated. The multi-segmental passive system, which models the dynamic heat transport within the body and the heat exchange between body parts and the environment, is discussed elsewhere. This paper is concerned with the development of the active system, which simulates the regulatory responses of shivering, sweating, and peripheral vasomotion of unacclimatised subjects. Following a comprehensive literature review, 26 independent experiments were selected that were designed to provoke each of these responses in different circumstances. Regression analysis revealed that skin and head core temperature affect regulatory responses in a non-linear fashion. A further signal, i.e. the rate of change of the mean skin temperature weighted by the skin temperature error signal, was identified as governing the dynamics of thermoregulatory processes in the cold. Verification and validation work was carried out using experimental data obtained from 90 exposures covering a range of steady and transient ambient temperatures between 5°C and 50°C and exercise intensities between 46 W/m2 and 600 W/m2. Good general agreement with measured data was obtained for regulatory responses, internal temperatures, and the mean and local skin temperatures of unacclimatised humans for the whole spectrum of climatic conditions and for different activity levels.

  4. Predictive analysis of landslide susceptibility in the Kao-Ping watershed, Taiwan under climate change conditions

    NASA Astrophysics Data System (ADS)

    Shou, K. J.; Wu, C. C.; Lin, J. F.

    2015-01-01

    Among the most critical issues, climatic abnormalities caused by global warming also affect Taiwan significantly for the past decade. The increasing frequency of extreme rainfall events, in which concentrated and intensive rainfalls generally cause geohazards including landslides and debris flows. The extraordinary Typhoon Morakot hit Southern Taiwan on 8 August 2009 and induced serious flooding and landslides. In this study, the Kao-Ping River watershed was adopted as the study area, and the typical events 2007 Krosa Typhoon and 2009 Morakot Typhoon were adopted to train the susceptibility model. This study employs rainfall frequency analysis together with the atmospheric general circulation model (AGCM) downscaling estimation to understand the temporal rainfall trends, distributions, and intensities in the Kao-Ping River watershed. The rainfall estimates were introduced in the landslide susceptibility model to produce the predictive landslide susceptibility for various rainfall scenarios, including abnormal climate conditions. These results can be used for hazard remediation, mitigation, and prevention plans for the Kao-Ping River watershed.

  5. Predicting aversive events and terminating fear in the mouse anterior cingulate cortex during trace fear conditioning.

    PubMed

    Steenland, Hendrik W; Li, Xiang-Yao; Zhuo, Min

    2012-01-18

    A variety of studies have implicated the anterior cingulate cortex (ACC) in fear, including permanent storage of fear memory. Recent pharmacological and genetic studies indicate that early synaptic plasticity in the ACC may also contribute to certain forms of fear memory at early time points. However, no study has directly examined the possible changes in neuronal activity of ACC neurons in freely behaving mice during early learning. In the present study, we examined the neural responses of the ACC during trace fear conditioning. We found that ACC putative pyramidal and nonpyramidal neurons were involved in the termination of fear behavior ("un-freezing"), and the spike activity of these neurons was reduced during freezing. Some of the neurons were also found to acquire un-freezing locked activity and change their tuning. The results implicate the ACC neurons in fear learning and controlling the abolition of fear behavior. We also show that the ACC is important for making cue-related fear memory associations in the trace fear paradigm as measured with tone-evoked potentials and single-unit activity. Collectively, our findings indicate that the ACC is involved in predicting future aversive events and terminating fear during trace fear. PMID:22262906

  6. Antecedent Moisture Conditions and the Application to Runoff Prediction in a Low Relief Peatland

    NASA Astrophysics Data System (ADS)

    Gibson, J.; Vallarino, A.; Birks, S. J.

    2012-12-01

    Vertical water balances have been used in the past to determine areas that will experience potential runoff where little to no relief exists. In the boreal plains this becomes a useful tool to predict runoff based on indexed precipitation events. By coupling runoff with precipitation indices and hydrograph response in different vegetation ecosystems a better understanding can be gained as to the role antecedent moisture plays in fens and bogs. This will be useful information as to determining flow and runoff of nutrients specifically the deposition of atmospheric sulphur and nitrogen on a surficial level in peatlands. A peatland complex was examined comprised of a treed bog, and fen. The site was instrumented with meteorological stations, water table wells and water capacitance loggers in each of the vegetation ecosystems. In addition, surface water and rain event water was sampled for isotopic labelling of water (2H and 18O) and was used to aid in the tracing of the flow and runoff of the water. Results suggest the precipitation response in the treed bog is more muted than in the fen. As well, response changed based on antecedent moisture conditions.

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

    NASA Astrophysics Data System (ADS)

    Rey, M.; Nikitin, A. V.; Tyuterev, V.

    2014-06-01

    Knowledge of near infrared intensities of rovibrational transitions of polyatomic molecules is essential for the modeling of various planetary atmospheres, brown dwarfs and for other astrophysical applications 1,2,3. For example, to analyze exoplanets, atmospheric models have been developed, thus making the need to provide accurate spectroscopic data. Consequently, the spectral characterization of such planetary objects relies on the necessity of having adequate and reliable molecular data in extreme conditions (temperature, optical path length, pressure). On the other hand, in the modeling of astrophysical opacities, millions of lines are generally involved and the line-by-line extraction is clearly not feasible in laboratory measurements. It is thus suggested that this large amount of data could be interpreted only by reliable theoretical predictions. There exists essentially two theoretical approaches for the computation and prediction of spectra. The first one is based on empirically-fitted effective spectroscopic models. Another way for computing energies, line positions and intensities is based on global variational calculations using ab initio surfaces. They do not yet reach the spectroscopic accuracy stricto sensu but implicitly account for all intramolecular interactions including resonance couplings in a wide spectral range. The final aim of this work is to provide reliable predictions which could be quantitatively accurate with respect to the precision of available observations and as complete as possible. All this thus requires extensive first-principles quantum mechanical calculations essentially based on three necessary ingredients which are (i) accurate intramolecular potential energy surface and dipole moment surface components well-defined in a large range of vibrational displacements and (ii) efficient computational methods combined with suitable choices of coordinates to account for molecular symmetry properties and to achieve a good numerical

  8. Wave-current interaction in the bottom boundary layer during storm and non-storm conditions: observations and model predictions

    USGS Publications Warehouse

    Drake, D.E.; Cacchione, D.A.

    1992-01-01

    Bottom boundary layer measurements of current velocity profiles and bed response under combined wave and current conditions were obtained at a water depth of 145 m on the shelf off central California during December 1988. High quality logarithmic current profiles, excellent time-series bottom photographs, and a large variation in the relative strengths of the wave-induced oscillatory currents and the quasi-steady low frequency currents provided a dataset that is ideal for examining the effects of wave-current interaction near a rough boundary. During one period of 3 days that included a brief storm event, the wave-induced bottom currents (Ub 1 10) ranged from 2.3 to 22 cm s-1 and the steady currents (Ur) ranged from 1.8 to 28.1 cm s-1 at 0.18 m above the bottom; the ratio Ub U18 varied from below 0.2 to more than 7. Velocity profiles were highly logarithmic (R2 > 0.95) 60% of the time and 27 profiles collected at 2-h intervals had R2 {slanted equal to or greater-than} 0.994 which allowed reliable estimates of the current shear velocity (U*c) and roughness length (zoc). Mean U*c values had magnitudes of 0.3-2.4 cm s-1 and zoc, which ranged from 0.04 to 3.5 cm, was strongly correlated to the Ub U18 ratio. Drag coefficients (CD = ??c/??U1002) ranged from about 2.5 ?? 10-3-12 ?? 10-3 in direct response to the wave-current variation; the use of a constant CD of 3 ?? 10-3 for steady flow over a rough bed would have underpredicted the shear stress by up to four times during the storm event. The large zoc and U*c values cannot be explained by changes in the carefully-observed, small (<1 cm) physical bed roughness elements that covered the mud-rich study site. A side-scan sonar site survey also eliminated the possibility of flow disturbance by larger upstream topography. The observations clearly demonstrate the importance of wave-current interaction near a rough boundary. Comparison of the observations with results of the combined flow models of Grant and Madsen and Glenn

  9. Landslide occurrences and recurrence intervals of heavy rainfalls in Japan

    NASA Astrophysics Data System (ADS)

    Saito, H.; Uchida, T.; Matsuyama, H.; Korup, O.

    2015-12-01

    Dealing with predicted increases in extreme weather conditions due to climate change requires robust knowledge about controls on rainfall-triggered landslides. This study developed the probable rainfall database from weather radar data, and analyzed the potential correlation between the landslide magnitude-frequency and the recurrence interval of the heavy rainfall across Japan. We analyzed 4,744 rainfall-induced landslides (Saito et al., 2014, Geology), 1 to 72 h rainfalls, and soil water index (SWI). We then estimated recurrence intervals for these rainfall parameters using a Gumbel distribution with jackknife fitting. Results showed that the recurrence intervals of rainfall events which caused landslides (<10^3 m^3) were less than 10 yr across Japan. The recurrence intervals increased with increases in landslide volumes. With regard to the landslides larger than 10^5 m^3, recurrence intervals of the rainfall events were more than 100 yr. These results suggest that recurrence intervals of heavy rainfalls are important for assessing regional landslide hazard in Japan.

  10. Inactivation model equations and their associated parameter values obtained under static acid stress conditions cannot be used directly for predicting inactivation under dynamic conditions.

    PubMed

    Janssen, M; Verhulst, A; Valdramidis, V; Devlieghere, F; Van Impe, J F; Geeraerd, A H

    2008-11-30

    Organic acids (e.g., lactic acid, acetic acid and citric acid) are popular preservatives. In this study, the Listeria innocua inactivation is investigated under dynamic conditions of pH and undissociated lactic acid ([LaH]). A combined primary (Weibull-type) and secondary model developed for the L. innocua inactivation under static conditions [Janssen, M., Geeraerd, A.H., Cappuyns, A., Garcia-Gonzalez, L., Schockaert, G., Van Houteghem, N., Vereecken, K.M., Debevere, J., Devlieghere, F., Van Impe, J.F., 2007. Individual and combined effects of pH and lactic acid concentration on L. innocua inactivation: development of a predictive model and assessment of experimental variability. Applied and Environmental Microbiology 73(5), 1601-1611] was applied to predict the microbial inactivation under dynamic conditions. Because of its non-autonomous character, two approaches were proposed for the application of the Weibull-type model to dynamic conditions. The results quantitatively indicated that the L. innocua cell population was able to develop an induced acid stress resistance under dynamic conditions of pH and [LaH]. From a modeling point of view, it needs to be stressed that (i) inactivation model equations and associated parameter values, derived under static conditions, may not be suitable for use as such under dynamic conditions, and (ii) non-autonomous dynamic models reveal additional technical intricacies in comparison with autonomous models.

  11. Predicting the biological condition of streams: Use of geospatial indicators of natural and anthropogenic characteristics of watersheds

    USGS Publications Warehouse

    Carlisle, D.M.; Falcone, J.; Meador, M.R.

    2009-01-01

    We developed and evaluated empirical models to predict biological condition of wadeable streams in a large portion of the eastern USA, with the ultimate goal of prediction for unsampled basins. Previous work had classified (i.e., altered vs. unaltered) the biological condition of 920 streams based on a biological assessment of macroinvertebrate assemblages. Predictor variables were limited to widely available geospatial data, which included land cover, topography, climate, soils, societal infrastructure, and potential hydrologic modification. We compared the accuracy of predictions of biological condition class based on models with continuous and binary responses. We also evaluated the relative importance of specific groups and individual predictor variables, as well as the relationships between the most important predictors and biological condition. Prediction accuracy and the relative importance of predictor variables were different for two subregions for which models were created. Predictive accuracy in the highlands region improved by including predictors that represented both natural and human activities. Riparian land cover and road-stream intersections were the most important predictors. In contrast, predictive accuracy in the lowlands region was best for models limited to predictors representing natural factors, including basin topography and soil properties. Partial dependence plots revealed complex and nonlinear relationships between specific predictors and the probability of biological alteration. We demonstrate a potential application of the model by predicting biological condition in 552 unsampled basins across an ecoregion in southeastern Wisconsin (USA). Estimates of the likelihood of biological condition of unsampled streams could be a valuable tool for screening large numbers of basins to focus targeted monitoring of potentially unaltered or altered stream segments. ?? Springer Science+Business Media B.V. 2008.

  12. Predicting New Target Conditions for Drug Retesting Using Temporal Patterns in Clinical Trials: A Proof of Concept.

    PubMed

    He, Zhe; Weng, Chunhua

    2015-01-01

    Drug discovery is costly and time-consuming. Efficient drug repurposing promises to accelerate drug discovery with reduced cost. However, most successful repurposing cases so far have been achieved by serendipity. There is a need for more efficient computational methods for predicting new indications for existing drugs. This paper conducts a retrospective analysis of the temporal patterns of drug intervention trials for every drug in a pair of different conditions in ClinicalTrials.gov, including 550 drugs used for 451 conditions between 2003 and 2013. We found that drugs are often targeted towards conditions that are related by similar or identical eligibility criteria. We demonstrated the preliminary feasibility of predicting new target conditions for drug retesting among conditions with similar aggregated clinical trial eligibility criteria and confirmed this hypothesis using evidence from the literature. PMID:26306283

  13. Effects of lateral boundary condition resolution and update frequency on regional climate model predictions

    NASA Astrophysics Data System (ADS)

    Pankatz, Klaus; Kerkweg, Astrid

    2015-04-01

    The work presented is part of the joint project "DecReg" ("Regional decadal predictability") which is in turn part of the project "MiKlip" ("Decadal predictions"), an effort funded by the German Federal Ministry of Education and Research to improve decadal predictions on a global and regional scale. In MiKlip, one big question is if regional climate modeling shows "added value", i.e. to evaluate, if regional climate models (RCM) produce better results than the driving models. However, the scope of this study is to look more closely at the setup specific details of regional climate modeling. As regional models only simulate a small domain, they have to inherit information about the state of the atmosphere at their lateral boundaries from external data sets. There are many unresolved questions concerning the setup of lateral boundary conditions (LBC). External data sets come from global models or from global reanalysis data-sets. A temporal resolution of six hours is common for this kind of data. This is mainly due to the fact, that storage space is a limiting factor, especially for climate simulations. However, theoretically, the coupling frequency could be as high as the time step of the driving model. Meanwhile, it is unclear if a more frequent update of the LBCs has a significant effect on the climate in the domain of the RCM. The first study examines how the RCM reacts to a higher update frequency. The study is based on a 30 year time slice experiment for three update frequencies of the LBC, namely six hours, one hour and six minutes. The evaluation of means, standard deviations and statistics of the climate in the regional domain shows only small deviations, some statistically significant though, of 2m temperature, sea level pressure and precipitation. The second part of the first study assesses parameters linked to cyclone activity, which is affected by the LBC update frequency. Differences in track density and strength are found when comparing the simulations

  14. Boreal Winter Predictions with the GEOS-2 GCM: The Role of Boundary Forcing and Initial Conditions

    NASA Technical Reports Server (NTRS)

    Chang, Yehui; Schubert, Siegfried D.; Suarez, Max J.

    1998-01-01

    Ensembles of atmospheric General Circulation Model (GCM) seasonal forecasts and long-term simulations (1980-94) are analyzed to assess the controlling influences of boundary forcing and memory of the initial conditions. Both the forecasts and simulations are carried out with version 2 of the Goddard Earth Observing System (GEOS-2) GCM forced with observed sea surface temperatures (SSTs). While much of the focus is on the seasonal time scale (January- March) and the Pacific North American (PNA) region, we also present results for other regions, shorter time scales, and other known modes of variability in the northern hemisphere extratropics. Forecasts of indices of some of the key large-scale modes of variability show that there is considerable variability in skill between different regions of the Northern Hemisphere. The eastern North Atlantic region has the poorest long lead forecast skill showing no skill beyond about 10 days. Skillful seasonal forecasts are primarily confined to the wave-like ENSO response emanating from the tropical Pacific. In the Northern Hemisphere, this is associated with the well-known Pacific/North American (PNA) pattern. Memory of the initial conditions is the major factor leading to skillful extratropical forecasts of lead time less than one month, while SST forcing is the only factor at the seasonal time scale. SST forcing contributes to skillful forecasts at sub- seasonal time scales only over the PNA region. The GEOS-2 GCM produces average (1980-94) signal to noise ratios which are less than one everywhere in the extratropics, except for the subtropical Pacific where they approach 1.5. When confined to the ENSO years, the maximum signal to noise ratios occur in the PNA region where they exceed three. An assessment of the sampling distribution of the forecasts suggests the model's ENSO response is very likely too weak. These results show some sensitivity to the uncertainties in the estimates of the SST forcing fields. In the North

  15. Once is too much: Conditioned aversion develops immediately and predicts future cocaine self-administration behavior in rats

    PubMed Central

    Colechio, Elizabeth M.; Imperio, Caesar G.; Grigson, Patricia S.

    2014-01-01

    Rats emit aversive taste reactivity (TR) behavior (i.e., gapes) following intraoral delivery of a cocaine-paired taste cue and greater conditioned aversive TR at the end of training predicts greater drug-seeking and taking. Here, we examined the development of this conditioned aversive TR behavior on a trial by trial basis in an effort to determine when the change in behavior occurs and whether early changes in this behavior can be used to predict later drug-taking. The results show that conditioned aversive TR to a cocaine-paired cue occurs very early in training (i.e., following as few as 1 – 2 taste-drug pairings) and, importantly, that it can be used to predict later drug-seeking and drug-taking in rats. PMID:24773440

  16. A data-driven feature extraction framework for predicting the severity of condition of congestive heart failure patients.

    PubMed

    Sideris, Costas; Alshurafa, Nabil; Pourhomayoun, Mohammad; Shahmohammadi, Farhad; Samy, Lauren; Sarrafzadeh, Majid

    2015-01-01

    In this paper, we propose a novel methodology for utilizing disease diagnostic information to predict severity of condition for Congestive Heart Failure (CHF) patients. Our methodology relies on a novel, clustering-based, feature extraction framework using disease diagnostic information. To reduce the dimensionality we identify disease clusters using cooccurence frequencies. We then utilize these clusters as features to predict patient severity of condition. We build our clustering and feature extraction algorithm using the 2012 National Inpatient Sample (NIS), Healthcare Cost and Utilization Project (HCUP) which contains 7 million discharge records and ICD-9-CM codes. The proposed framework is tested on Ronald Reagan UCLA Medical Center Electronic Health Records (EHR) from 3041 patients. We compare our cluster-based feature set with another that incorporates the Charlson comorbidity score as a feature and demonstrate an accuracy improvement of up to 14% in the predictability of the severity of condition. PMID:26736808

  17. Analysis and Prediction of the Critical Regions of Antimicrobial Peptides Based on Conditional Random Fields

    PubMed Central

    Chang, Kuan Y.; Lin, Tung-pei; Shih, Ling-Yi; Wang, Chien-Kuo

    2015-01-01

    Antimicrobial peptides (AMPs) are potent drug candidates against microbes such as bacteria, fungi, parasites, and viruses. The size of AMPs ranges from less than ten to hundreds of amino acids. Often only a few amino acids or the critical regions of antimicrobial proteins matter the functionality. Accurately predicting the AMP critical regions could benefit the experimental designs. However, no extensive analyses have been done specifically on the AMP critical regions and computational modeling on them is either non-existent or settled to other problems. With a focus on the AMP critical regions, we thus develop a computational model AMPcore by introducing a state-of-the-art machine learning method, conditional random fields. We generate a comprehensive dataset of 798 AMPs cores and a low similarity dataset of 510 representative AMP cores. AMPcore could reach a maximal accuracy of 90% and 0.79 Matthew’s correlation coefficient on the comprehensive dataset and a maximal accuracy of 83% and 0.66 MCC on the low similarity dataset. Our analyses of AMP cores follow what we know about AMPs: High in glycine and lysine, but low in aspartic acid, glutamic acid, and methionine; the abundance of α-helical structures; the dominance of positive net charges; the peculiarity of amphipathicity. Two amphipathic sequence motifs within the AMP cores, an amphipathic α-helix and an amphipathic π-helix, are revealed. In addition, a short sequence motif at the N-terminal boundary of AMP cores is reported for the first time: arginine at the P(-1) coupling with glycine at the P1 of AMP cores occurs the most, which might link to microbial cell adhesion. PMID:25803302

  18. Full-field predictions of ice dynamic recrystallisation under simple shear conditions

    NASA Astrophysics Data System (ADS)

    Llorens, Maria-Gema; Griera, Albert; Bons, Paul D.; Lebensohn, Ricardo A.; Evans, Lynn A.; Jansen, Daniela; Weikusat, Ilka

    2016-09-01

    Understanding the flow of ice on the microstructural scale is essential for improving our knowledge of large-scale ice dynamics, and thus our ability to predict future changes of ice sheets. Polar ice behaves anisotropically during flow, which can lead to strain localisation. In order to study how dynamic recrystallisation affects to strain localisation in deep levels of polar ice sheets, we present a series of numerical simulations of ice polycrystals deformed under simple-shear conditions. The models explicitly simulate the evolution of microstructures using a full-field approach, based on the coupling of a viscoplastic deformation code (VPFFT) with dynamic recrystallisation codes. The simulations provide new insights into the distribution of stress, strain rate and lattice orientation fields with progressive strain, up to a shear strain of three. Our simulations show how the recrystallisation processes have a strong influence on the resulting microstructure (grain size and shape), while the development of lattice preferred orientations (LPO) appears to be less affected. Activation of non-basal slip systems is enhanced by recrystallisation and induces a strain hardening behaviour up to the onset of strain localisation and strain weakening behaviour. Simulations demonstrate that the strong intrinsic anisotropy of ice crystals is transferred to the polycrystalline scale and results in the development of strain localisation bands than can be masked by grain boundary migration. Therefore, the finite-strain history is non-directly reflected by the final microstructure. Masked strain localisation can be recognised in ice cores, such as the EDML, from the presence of stepped boundaries, microshear and grains with zig-zag geometries.

  19. Global atmospheric sulfur budget under volcanically quiescent conditions: Aerosol-chemistry-climate model predictions and validation

    NASA Astrophysics Data System (ADS)

    Sheng, Jian-Xiong; Weisenstein, Debra K.; Luo, Bei-Ping; Rozanov, Eugene; Stenke, Andrea; Anet, Julien; Bingemer, Heinz; Peter, Thomas

    2015-01-01

    The global atmospheric sulfur budget and its emission dependence have been investigated using the coupled aerosol-chemistry-climate model SOCOL-AER. The aerosol module comprises gaseous and aqueous sulfur chemistry and comprehensive microphysics. The particle distribution is resolved by 40 size bins spanning radii from 0.39 nm to 3.2 μm, including size-dependent particle composition. Aerosol radiative properties required by the climate model are calculated online from the aerosol module. The model successfully reproduces main features of stratospheric aerosols under nonvolcanic conditions, including aerosol extinctions compared to Stratospheric Aerosol and Gas Experiment II (SAGE II) and Halogen Occultation Experiment, and size distributions compared to in situ measurements. The calculated stratospheric aerosol burden is 109 Gg of sulfur, matching the SAGE II-based estimate (112 Gg). In terms of fluxes through the tropopause, the stratospheric aerosol layer is due to about 43% primary tropospheric aerosol, 28% SO2, 23% carbonyl sulfide (OCS), 4% H2S, and 2% dimethyl sulfide (DMS). Turning off emissions of the short-lived species SO2, H2S, and DMS shows that OCS alone still establishes about 56% of the original stratospheric aerosol burden. Further sensitivity simulations reveal that anticipated increases in anthropogenic SO2 emissions in China and India have a larger influence on stratospheric aerosols than the same increase in Western Europe or the U.S., due to deep convection in the western Pacific region. However, even a doubling of Chinese and Indian emissions is predicted to increase the stratospheric background aerosol burden only by 9%. In contrast, small to moderate volcanic eruptions, such as that of Nabro in 2011, may easily double the stratospheric aerosol loading.

  20. Predicting water quality at Santa Monica Beach: evaluation of five different models for public notification of unsafe swimming conditions.

    PubMed

    Thoe, W; Gold, M; Griesbach, A; Grimmer, M; Taggart, M L; Boehm, A B

    2014-12-15

    Bathing beaches are monitored for fecal indicator bacteria (FIB) to protect swimmers from unsafe conditions. However, FIB assays take ∼24 h and water quality conditions can change dramatically in that time, so unsafe conditions cannot presently be identified in a timely manner. Statistical, data-driven predictive models use information on environmental conditions (i.e., rainfall, turbidity) to provide nowcasts of FIB concentrations. Their ability to predict real time FIB concentrations can make them more accurate at identifying unsafe conditions than the current method of using day or older FIB measurements. Predictive models are used in the Great Lakes, Hong Kong, and Scotland for beach management, but they are presently not used in California - the location of some of the world's most popular beaches. California beaches are unique as point source pollution has generally been mitigated, the summer bathing season receives little to no rainfall, and in situ measurements of turbidity and salinity are not readily available. These characteristics may make modeling FIB difficult, as many current FIB models rely heavily on rainfall or salinity. The current study investigates the potential for FIB models to predict water quality at a quintessential California Beach: Santa Monica Beach. This study compares the performance of five predictive models, multiple linear regression model, binary logistic regression model, partial least square regression model, artificial neural network, and classification tree, to predict concentrations of summertime fecal coliform and enterococci concentrations. Past measurements of bacterial concentration, storm drain condition, and tide level are found to be critical factors in the predictive models. The models perform better than the current beach management method. The classification tree models perform the best; for example they correctly predict 42% of beach postings due to fecal coliform exceedances during model validation, as compared

  1. Predicting water quality at Santa Monica Beach: evaluation of five different models for public notification of unsafe swimming conditions.

    PubMed

    Thoe, W; Gold, M; Griesbach, A; Grimmer, M; Taggart, M L; Boehm, A B

    2014-12-15

    Bathing beaches are monitored for fecal indicator bacteria (FIB) to protect swimmers from unsafe conditions. However, FIB assays take ∼24 h and water quality conditions can change dramatically in that time, so unsafe conditions cannot presently be identified in a timely manner. Statistical, data-driven predictive models use information on environmental conditions (i.e., rainfall, turbidity) to provide nowcasts of FIB concentrations. Their ability to predict real time FIB concentrations can make them more accurate at identifying unsafe conditions than the current method of using day or older FIB measurements. Predictive models are used in the Great Lakes, Hong Kong, and Scotland for beach management, but they are presently not used in California - the location of some of the world's most popular beaches. California beaches are unique as point source pollution has generally been mitigated, the summer bathing season receives little to no rainfall, and in situ measurements of turbidity and salinity are not readily available. These characteristics may make modeling FIB difficult, as many current FIB models rely heavily on rainfall or salinity. The current study investigates the potential for FIB models to predict water quality at a quintessential California Beach: Santa Monica Beach. This study compares the performance of five predictive models, multiple linear regression model, binary logistic regression model, partial least square regression model, artificial neural network, and classification tree, to predict concentrations of summertime fecal coliform and enterococci concentrations. Past measurements of bacterial concentration, storm drain condition, and tide level are found to be critical factors in the predictive models. The models perform better than the current beach management method. The classification tree models perform the best; for example they correctly predict 42% of beach postings due to fecal coliform exceedances during model validation, as compared

  2. PREDICTING ESTUARINE SEDIMENT METAL CONCENTRATIONS AND INFERRED ECOLOGICAL CONDITIONS: AN INFORMATION THEORETIC APPROACH

    EPA Science Inventory

    Empirically derived values associating sediment metal concentrations with degraded ecological conditions provide important information to assess estuarine condition. However, resources limit the number, magnitude, and frequency of monitoring programs to gather these data. As su...

  3. Prediction of Air Conditioning Load Response for Providing Spinning Reserve - ORNL Report

    SciTech Connect

    Kueck, John D; Kirby, Brendan J; Ally, Moonis Raza; Rice, C Keith

    2009-02-01

    This report assesses the use of air conditioning load for providing spinning reserve and discusses the barriers and opportunities. Air conditioning load is well suited for this service because it often increases during heavy load periods and can be curtailed for short periods with little impact to the customer. The report also provides an appendix describing the ambient temperature effect on air conditioning load.

  4. Influence of Yield Condition on the Accuracy of Earing Prediction for Steel Sheets

    NASA Astrophysics Data System (ADS)

    Gösling, Marco

    2016-08-01

    This paper is dealing with the material modelling of steel sheets and is focused on the input parameters for a correct earing prediction. The cause of earing is the anisotropy of the rolled sheet which is usually modelled by a yield criterion. In a first study earing predictions with the Hill’48 yield criterion and with the Barlat’2000 yield criterion are conducted for different steel grades between 200 and 800 MPa yield strength. A comparison of the results shows that the Barlat’2000 yield criterion leads in almost all cases to a better earing prediction. In a second study the measurements for the Barlat’2000 law were analysed, to find the main parameter influencing the accuracy in earing prediction. The results of this study show that it is not affected by the biaxial measurements, but by the yield strength in 45° regarding to rolling direction.

  5. Chimerism status after unrelated donor bone marrow transplantation with fludarabine-melphalan conditioning is affected by the melphalan dose and is predictive of relapse.

    PubMed

    Imahashi, Nobuhiko; Ohashi, Haruhiko; Terakura, Seitaro; Miyao, Kotaro; Sakemura, Reona; Kato, Tomonori; Sawa, Masashi; Yokohata, Emi; Kurahashi, Shingo; Ozawa, Yukiyasu; Nishida, Tetsuya; Kiyoi, Hitoshi; Watamoto, Koichi; Kohno, Akio; Kasai, Masanobu; Kato, Chiaki; Iida, Hiroatsu; Naoe, Tomoki; Miyamura, Koichi; Murata, Makoto

    2015-07-01

    Little is known regarding the chimerism status after reduced-intensity conditioning transplantation when bone marrow is used as a stem cell source. We prospectively analyzed lineage-specific chimerism and retrospectively evaluated clinical outcomes in 80 adult patients who underwent unrelated donor bone marrow transplantation (URBMT) with fludarabine plus melphalan (FM) as the conditioning regimen. Mixed donor chimerism (MDC) was seen in 43 and 10 % of patients at days 14 and 28, respectively. Melphalan at ≤130 mg/m(2) was associated with an increased incidence of MDC at day 28 (P = 0.03). Patients with MDC at day 14 showed a marginally increased risk of primary graft failure and a marginally decreased risk of graft-versus-host disease. In multivariate analysis, MDC at day 14 was associated with higher overall mortality (hazard ratio (HR) = 2.1; 95 % confidence interval (CI), 1.1-4.2; P = 0.04) and relapse rate (HR = 3.0; 95 % CI, 1.2-7.5; P = 0.02), but not with non-relapse mortality (HR = 1.8; 95 % CI, 0.70-4.6; P = 0.23). Thus, the FM regimen yields prompt complete donor chimerism after URBMT, but the melphalan dose significantly impacts the kinetics of chimerism. Chimerism status evaluation at day 14 may be instrumental in predicting relapse after URBMT with the FM regimen. PMID:25680895

  6. Chimerism status after unrelated donor bone marrow transplantation with fludarabine-melphalan conditioning is affected by the melphalan dose and is predictive of relapse.

    PubMed

    Imahashi, Nobuhiko; Ohashi, Haruhiko; Terakura, Seitaro; Miyao, Kotaro; Sakemura, Reona; Kato, Tomonori; Sawa, Masashi; Yokohata, Emi; Kurahashi, Shingo; Ozawa, Yukiyasu; Nishida, Tetsuya; Kiyoi, Hitoshi; Watamoto, Koichi; Kohno, Akio; Kasai, Masanobu; Kato, Chiaki; Iida, Hiroatsu; Naoe, Tomoki; Miyamura, Koichi; Murata, Makoto

    2015-07-01

    Little is known regarding the chimerism status after reduced-intensity conditioning transplantation when bone marrow is used as a stem cell source. We prospectively analyzed lineage-specific chimerism and retrospectively evaluated clinical outcomes in 80 adult patients who underwent unrelated donor bone marrow transplantation (URBMT) with fludarabine plus melphalan (FM) as the conditioning regimen. Mixed donor chimerism (MDC) was seen in 43 and 10 % of patients at days 14 and 28, respectively. Melphalan at ≤130 mg/m(2) was associated with an increased incidence of MDC at day 28 (P = 0.03). Patients with MDC at day 14 showed a marginally increased risk of primary graft failure and a marginally decreased risk of graft-versus-host disease. In multivariate analysis, MDC at day 14 was associated with higher overall mortality (hazard ratio (HR) = 2.1; 95 % confidence interval (CI), 1.1-4.2; P = 0.04) and relapse rate (HR = 3.0; 95 % CI, 1.2-7.5; P = 0.02), but not with non-relapse mortality (HR = 1.8; 95 % CI, 0.70-4.6; P = 0.23). Thus, the FM regimen yields prompt complete donor chimerism after URBMT, but the melphalan dose significantly impacts the kinetics of chimerism. Chimerism status evaluation at day 14 may be instrumental in predicting relapse after URBMT with the FM regimen.

  7. Prediction of as-cast grain size of inoculated aluminum alloys melt solidified under non-isothermal conditions

    NASA Astrophysics Data System (ADS)

    Du, Qiang; Li, Yanjun

    2015-06-01

    In this paper, a multi-scale as-cast grain size prediction model is proposed to predict as-cast grain size of inoculated aluminum alloys melt solidified under non-isothermal condition, i.e., the existence of temperature gradient. Given melt composition, inoculation and heat extraction boundary conditions, the model is able to predict maximum nucleation undercooling, cooling curve, primary phase solidification path and final as-cast grain size of binary alloys. The proposed model has been applied to two Al-Mg alloys, and comparison with laboratory and industrial solidification experimental results have been carried out. The preliminary conclusion is that the proposed model is a promising suitable microscopic model used within the multi-scale casting simulation modelling framework.

  8. Vehicle dynamic prediction systems with on-line identification of vehicle parameters and road conditions.

    PubMed

    Hsu, Ling-Yuan; Chen, Tsung-Lin

    2012-01-01

    This paper presents a vehicle dynamics prediction system, which consists of a sensor fusion system and a vehicle parameter identification system. This sensor fusion system can obtain the six degree-of-freedom vehicle dynamics and two road angles without using a vehicle model. The vehicle parameter identification system uses the vehicle dynamics from the sensor fusion system to identify ten vehicle parameters in real time, including vehicle mass, moment of inertial, and road friction coefficients. With above two systems, the future vehicle dynamics is predicted by using a vehicle dynamics model, obtained from the parameter identification system, to propagate with time the current vehicle state values, obtained from the sensor fusion system. Comparing with most existing literatures in this field, the proposed approach improves the prediction accuracy both by incorporating more vehicle dynamics to the prediction system and by on-line identification to minimize the vehicle modeling errors. Simulation results show that the proposed method successfully predicts the vehicle dynamics in a left-hand turn event and a rollover event. The prediction inaccuracy is 0.51% in a left-hand turn event and 27.3% in a rollover event.

  9. Vehicle Dynamic Prediction Systems with On-Line Identification of Vehicle Parameters and Road Conditions

    PubMed Central

    Hsu, Ling-Yuan; Chen, Tsung-Lin

    2012-01-01

    This paper presents a vehicle dynamics prediction system, which consists of a sensor fusion system and a vehicle parameter identification system. This sensor fusion system can obtain the six degree-of-freedom vehicle dynamics and two road angles without using a vehicle model. The vehicle parameter identification system uses the vehicle dynamics from the sensor fusion system to identify ten vehicle parameters in real time, including vehicle mass, moment of inertial, and road friction coefficients. With above two systems, the future vehicle dynamics is predicted by using a vehicle dynamics model, obtained from the parameter identification system, to propagate with time the current vehicle state values, obtained from the sensor fusion system. Comparing with most existing literatures in this field, the proposed approach improves the prediction accuracy both by incorporating more vehicle dynamics to the prediction system and by on-line identification to minimize the vehicle modeling errors. Simulation results show that the proposed method successfully predicts the vehicle dynamics in a left-hand turn event and a rollover event. The prediction inaccuracy is 0.51% in a left-hand turn event and 27.3% in a rollover event. PMID:23202231

  10. Multi-omics integration accurately predicts cellular state in unexplored conditions for Escherichia coli

    PubMed Central

    Kim, Minseung; Rai, Navneet; Zorraquino, Violeta; Tagkopoulos, Ilias

    2016-01-01

    A significant obstacle in training predictive cell models is the lack of integrated data sources. We develop semi-supervised normalization pipelines and perform experimental characterization (growth, transcriptional, proteome) to create Ecomics, a consistent, quality-controlled multi-omics compendium for Escherichia coli with cohesive meta-data information. We then use this resource to train a multi-scale model that integrates four omics layers to predict genome-wide concentrations and growth dynamics. The genetic and environmental ontology reconstructed from the omics data is substantially different and complementary to the genetic and chemical ontologies. The integration of different layers confers an incremental increase in the prediction performance, as does the information about the known gene regulatory and protein-protein interactions. The predictive performance of the model ranges from 0.54 to 0.87 for the various omics layers, which far exceeds various baselines. This work provides an integrative framework of omics-driven predictive modelling that is broadly applicable to guide biological discovery. PMID:27713404

  11. Locally linear neurofuzzy modeling and prediction of geomagnetic disturbances based on solar wind conditions

    NASA Astrophysics Data System (ADS)

    Sharifie, Javad; Lucas, Caro; Araabi, Babak N.

    2006-06-01

    Disturbance storm time index (Dst) is nonlinearly related to solar wind data. In this paper, Dst past values, Dst derivative, past values of southward interplanetary magnetic field, and the square root of dynamic pressure are used as inputs for modeling and prediction of the Dst index, especially during extreme events. The geoeffective solar wind parameters are selected depending on the physical background of the geomagnetic storm procedure and physical models. A locally linear neurofuzzy model with a progressive tree construction learning algorithm is applied as a powerful tool for nonlinear modeling of Dst index on the basis of its past values and solar wind parameters. The result for modeling and prediction of several intense storms shows that the geomagnetic disturbance Dst index based on geoeffective parameters is a nonlinear model that could be considered as the nonlinear extension of empirical linear physical models. The method is applied for prediction of some geomagnetic storms. Obtained results show that using the proposed method, the predicted values of several extreme storms are highly correlated with observed values. In addition, prediction of the main phase of many storms shows a good match with observed data, which constitutes an appropriate approach for solar storm alerting to vulnerable industries.

  12. Condition, not eyespan, predicts contest outcome in female stalk-eyed flies, Teleopsis dalmanni

    PubMed Central

    Bath, Eleanor; Wigby, Stuart; Vincent, Claire; Tobias, Joseph A; Seddon, Nathalie

    2015-01-01

    In contests among males, body condition is often the key determinant of a successful outcome, with fighting ability signaled by so-called armaments, that is, exaggerated, condition-dependent traits. However, it is not known whether condition and exaggerated traits function in the same way in females. Here, we manipulated adult condition by varying larval nutrition in the stalk-eyed fly, Teleopsis dalmanni, a species in which eyespan is exaggerated in both sexes, and we measured the outcome of contests between females of similar or different body condition and relative eyespan. We found that females in higher condition, with both larger bodies and eyespan, won a higher proportion of encounters when competing against rivals of lower condition. However, when females were of equal condition, neither eyespan nor body length had an effect on the outcome of a contest. An analysis of previously published data revealed a similar pattern in males: individuals with large relative eyespan did not win significantly more encounters when competing with individuals of a similar body size. Contrary to expectations, and to previous findings in males, there was no clear effect of differences in body size or eyespan affecting contest duration in females. Taken together, our findings suggest that although eyespan can provide an honest indicator of condition, large eyespans provide no additional benefit to either sex in intrasexual aggressive encounters; body size is instead the most important factor. PMID:26140199

  13. Techniques for the Enhancement of Linear Predictive Speech Coding in Adverse Conditions

    NASA Astrophysics Data System (ADS)

    Wrench, Alan A.

    Available from UMI in association with The British Library. Requires signed TDF. The Linear Prediction model was first applied to speech two and a half decades ago. Since then it has been the subject of intense research and continues to be one of the principal tools in the analysis of speech. Its mathematical tractability makes it a suitable subject for study and its proven success in practical applications makes the study worthwhile. The model is known to be unsuited to speech corrupted by background noise. This has led many researchers to investigate ways of enhancing the speech signal prior to Linear Predictive analysis. In this thesis this body of work is extended. The chosen application is low bit-rate (2.4 kbits/sec) speech coding. For this task the performance of the Linear Prediction algorithm is crucial because there is insufficient bandwidth to encode the error between the modelled speech and the original input. A review of the fundamentals of Linear Prediction and an independent assessment of the relative performance of methods of Linear Prediction modelling are presented. A new method is proposed which is fast and facilitates stability checking, however, its stability is shown to be unacceptably poorer than existing methods. A novel supposition governing the positioning of the analysis frame relative to a voiced speech signal is proposed and supported by observation. The problem of coding noisy speech is examined. Four frequency domain speech processing techniques are developed and tested. These are: (i) Combined Order Linear Prediction Spectral Estimation; (ii) Frequency Scaling According to an Aural Model; (iii) Amplitude Weighting Based on Perceived Loudness; (iv) Power Spectrum Squaring. These methods are compared with the Recursive Linearised Maximum a Posteriori method. Following on from work done in the frequency domain, a time domain implementation of spectrum squaring is developed. In addition, a new method of power spectrum estimation is

  14. Prediction of hydrolysis pathways and kinetics for antibiotics under environmental pH conditions: a quantum chemical study on cephradine.

    PubMed

    Zhang, Haiqin; Xie, Hongbin; Chen, Jingwen; Zhang, Shushen

    2015-02-01

    Understanding hydrolysis pathways and kinetics of many antibiotics that have multiple hydrolyzable functional groups is important for their fate assessment. However, experimental determination of hydrolysis encounters difficulties due to time and cost restraint. We employed the density functional theory and transition state theory to predict the hydrolysis pathways and kinetics of cephradine, a model of cephalosporin with two hydrolyzable groups, two ionization states, two isomers and two nucleophilic attack directions. Results showed that the hydrolysis of cephradine at pH = 8.0 proceeds via opening of the β-lactam ring followed by intramolecular amidation. The predicted rate constants at different pH conditions are of the same order of magnitude as the experimental values, and the predicted products are confirmed by experiment. This study identified a catalytic role of the carboxyl group in the hydrolysis, and implies that the carboxyl group also plays a catalytic role in the hydrolysis of other cephalosporin and penicillin antibiotics. This is a first attempt to quantum chemically predict hydrolysis of an antibiotic with complex pathways, and indicates that to predict hydrolysis products under the environmental pH conditions, the variation of the rate constants for different pathways with pH should be evaluated.

  15. MERGER RATES OF DOUBLE NEUTRON STARS AND STELLAR ORIGIN BLACK HOLES: THE IMPACT OF INITIAL CONDITIONS ON BINARY EVOLUTION PREDICTIONS

    SciTech Connect

    Mink, S. E. de; Belczynski, K. E-mail: kbelczyn@astrouw.edu.pl

    2015-11-20

    The initial mass function (IMF), binary fraction, and distributions of binary parameters (mass ratios, separations, and eccentricities) are indispensable inputs for simulations of stellar populations. It is often claimed that these are poorly constrained, significantly affecting evolutionary predictions. Recently, dedicated observing campaigns have provided new constraints on the initial conditions for massive stars. Findings include a larger close binary fraction and a stronger preference for very tight systems. We investigate the impact on the predicted merger rates of neutron stars and black holes. Despite the changes with previous assumptions, we only find an increase of less than a factor of 2 (insignificant compared with evolutionary uncertainties of typically a factor of 10–100). We further show that the uncertainties in the new initial binary properties do not significantly affect (within a factor of 2) our predictions of double compact object merger rates. An exception is the uncertainty in IMF (variations by a factor of 6 up and down). No significant changes in the distributions of final component masses, mass ratios, chirp masses, and delay times are found. We conclude that the predictions are, for practical purposes, robust against uncertainties in the initial conditions concerning binary parameters, with the exception of the IMF. This eliminates an important layer of the many uncertain assumptions affecting the predictions of merger detection rates with the gravitational wave detectors aLIGO/aVirgo.

  16. Merger Rates of Double Neutron Stars and Stellar Origin Black Holes: The Impact of Initial Conditions on Binary Evolution Predictions

    NASA Astrophysics Data System (ADS)

    de Mink, S. E.; Belczynski, K.

    2015-11-01

    The initial mass function (IMF), binary fraction, and distributions of binary parameters (mass ratios, separations, and eccentricities) are indispensable inputs for simulations of stellar populations. It is often claimed that these are poorly constrained, significantly affecting evolutionary predictions. Recently, dedicated observing campaigns have provided new constraints on the initial conditions for massive stars. Findings include a larger close binary fraction and a stronger preference for very tight systems. We investigate the impact on the predicted merger rates of neutron stars and black holes. Despite the changes with previous assumptions, we only find an increase of less than a factor of 2 (insignificant compared with evolutionary uncertainties of typically a factor of 10–100). We further show that the uncertainties in the new initial binary properties do not significantly affect (within a factor of 2) our predictions of double compact object merger rates. An exception is the uncertainty in IMF (variations by a factor of 6 up and down). No significant changes in the distributions of final component masses, mass ratios, chirp masses, and delay times are found. We conclude that the predictions are, for practical purposes, robust against uncertainties in the initial conditions concerning binary parameters, with the exception of the IMF. This eliminates an important layer of the many uncertain assumptions affecting the predictions of merger detection rates with the gravitational wave detectors aLIGO/aVirgo.

  17. The Central Amygdala Projection to the Substantia Nigra Reflects Prediction Error Information in Appetitive Conditioning

    ERIC Educational Resources Information Center

    Lee, Hongjoo J.; Gallagher, Michela; Holland, Peter C.

    2010-01-01

    The central amygdala nucleus (CeA) plays a critical role in cognitive processes beyond fear conditioning. For example, intact CeA function is essential for enhancing attention to conditioned stimuli (CSs). Furthermore, this enhanced attention depends on the CeA's connections to the nigrostriatal system. In the current study, we examined the role…

  18. Predictions of Separated and Transitional Boundary Layers Under Low-Pressure Turbine Airfoil Conditions Using an Intermittency Transport Equation

    NASA Technical Reports Server (NTRS)

    Suzen, Y. B.; Huang, P. G.; Hultgren, Lennart S.; Ashpis, David E.

    2003-01-01

    A new transport equation for the intermittency factor was proposed to predict separated and transitional boundary layers under low-pressure turbine airfoil conditions. The intermittent behavior of the transitional flows is taken into account and incorporated into computations by modifying the eddy viscosity, t , with the intermittency factor, y. Turbulent quantities are predicted by using Menter s two-equation turbulence model (SST). The intermittency factor is obtained from a transport equation model, which not only can reproduce the experimentally observed streamwise variation of the intermittency in the transition zone, but also can provide a realistic cross-stream variation of the intermittency profile. In this paper, the intermittency model is used to predict a recent separated and transitional boundary layer experiment under low pressure turbine airfoil conditions. The experiment provides detailed measurements of velocity, turbulent kinetic energy and intermittency profiles for a number of Reynolds numbers and freestream turbulent intensity conditions and is suitable for validation purposes. Detailed comparisons of computational results with experimental data are presented and good agreements between the experiments and predictions are obtained.

  19. Stimulus properties of fixed-interval responses.

    PubMed

    Buchman, I B; Zeiler, M D

    1975-11-01

    Responses in the first component of a chained schedule produced a change to the terminal component according to a fixed-interval schedule. The number of responses emitted in the fixed interval determined whether a variable-interval schedule of food presentation or extinction prevailed in the terminal component. In one condition, the variable-interval schedule was in effect only if the number of responses during the fixed interval was less than that specified; in another condition, the number of responses had to exceed that specified. The number of responses emitted in the fixed interval did not shift markedly in the direction required for food presentation. Instead, responding often tended to change in the opposite direction. Such an effect indicated that differential food presentation did not modify the reference behavior in accord with the requirement, but it was consistent with other data on fixed-interval schedule performance. Behavior in the terminal component, however, did reveal sensitivity to the relation between total responses emitted in the fixed interval and the availability of food. Response rate in the terminal component was a function of the proximity of the response number emitted in the fixed interval to that required for food presentation. Thus, response number served as a discriminative stimulus controlling subsequent performance.

  20. Predicting Pilot Performance in Off-Nominal Conditions: A Meta-Analysis and Model Validation

    NASA Technical Reports Server (NTRS)

    Wickens, C.D.; Hooey, B.L.; Gore, B.F.; Sebok, A.; Koenecke, C.; Salud, E.

    2009-01-01

    Pilot response to off-nominal (very rare) events represents a critical component to understanding the safety of next generation airspace technology and procedures. We describe a meta-analysis designed to integrate the existing data regarding pilot accuracy of detecting rare, unexpected events such as runway incursions in realistic flight simulations. Thirty-five studies were identified and pilot responses were categorized by expectancy, event location, and whether the pilot was flying with a highway-in-the-sky display. All three dichotomies produced large, significant effects on event miss rate. A model of human attention and noticing, N-SEEV, was then used to predict event noticing performance as a function of event salience and expectancy, and retinal eccentricity. Eccentricity is predicted from steady state scanning by the SEEV model of attention allocation. The model was used to predict miss rates for the expectancy, location and highway-in-the-sky (HITS) effects identified in the meta-analysis. The correlation between model-predicted results and data from the meta-analysis was 0.72.

  1. Prediction of lung function response for populations exposed to a wide range of ozone conditions

    EPA Science Inventory

    Abstract Context: A human exposure-response (E-R) model that has previously been demonstrated to accurately predict population mean FEV1 response to ozone exposure has been proposed as the foundation for future risk assessments for ambient ozone. Objective: Fit the origi...

  2. Analytical Predictions of Thermal Stress in the Stardust PICA Heatshield Under Reentry Flight Conditions

    NASA Technical Reports Server (NTRS)

    Squire, Thomas; Milos, Frank; Agrawal, Parul

    2009-01-01

    We performed finite element analyses on a model of the Phenolic Impregnated Carbon Ablator (PICA) heatshield from the Stardust sample return capsule (SRC) to predict the thermal stresses in the PICA material during reentry. The heatshield on the Stardust SRC was a 0.83 m sphere cone, fabricated from a single piece of 5.82 cm-thick PICA. The heatshield performed successfully during Earth reentry of the SRC in January 2006. Material response analyses of the full, axisymmetric PICA heatshield were run using the Two-Dimensional Implicit Ablation, Pyrolysis, and Thermal Response Program (TITAN). Peak surface temperatures were predicted to be 3385K, while the temperature at the PICA backface remained at the estimated initial cold-soak temperature of 278K. Surface recession and temperature distribution results from TITAN, at several points in the reentry trajectory, were mapped onto an axisymmetric finite element model of the heatshield. We used the finite element model to predict the thermal stresses in the PICA from differential thermal expansion. The predicted peak compressive stress in the PICA heatshield was 1.38 MPa. Although this level of stress exceeded the chosen design limit for compressive stresses in PICA tiles for the design of the Orion crew exploration vehicle heatshield, the Stardust heatshield exhibited no obvious mechanical failures from thermal stress. The analyses of the Stardust heatshield were used to assess and adjust the level of conservatism in the finite element analyses in support of the Orion heatshield design.

  3. Conditions for Effective Application of Analysis of Symmetrically-Predicted Endogenous Subgroups

    ERIC Educational Resources Information Center

    Peck, Laura R.

    2015-01-01

    Several analytic strategies exist for opening up the "black box" to reveal more about what drives policy and program impacts. This article focuses on one of these strategies: the Analysis of Symmetrically-Predicted Endogenous Subgroups (ASPES). ASPES uses exogenous baseline data to identify endogenously-defined subgroups, keeping the…

  4. Elements of a pragmatic approach for dealing with bias and uncertainty in experiments through predictions : experiment design and data conditioning; %22real space%22 model validation and conditioning; hierarchical modeling and extrapolative prediction.

    SciTech Connect

    Romero, Vicente Jose

    2011-11-01

    This report explores some important considerations in devising a practical and consistent framework and methodology for utilizing experiments and experimental data to support modeling and prediction. A pragmatic and versatile 'Real Space' approach is outlined for confronting experimental and modeling bias and uncertainty to mitigate risk in modeling and prediction. The elements of experiment design and data analysis, data conditioning, model conditioning, model validation, hierarchical modeling, and extrapolative prediction under uncertainty are examined. An appreciation can be gained for the constraints and difficulties at play in devising a viable end-to-end methodology. Rationale is given for the various choices underlying the Real Space end-to-end approach. The approach adopts and refines some elements and constructs from the literature and adds pivotal new elements and constructs. Crucially, the approach reflects a pragmatism and versatility derived from working many industrial-scale problems involving complex physics and constitutive models, steady-state and time-varying nonlinear behavior and boundary conditions, and various types of uncertainty in experiments and models. The framework benefits from a broad exposure to integrated experimental and modeling activities in the areas of heat transfer, solid and structural mechanics, irradiated electronics, and combustion in fluids and solids.

  5. Importance of Watershed Land Use in Predicting Benthic Invertebrate Condition in the Virginian Biogeographic Province, USA.

    EPA Science Inventory

    Estuaries are dynamic transition zones linking freshwater and oceanic habitats. These productive ecosystems are threatened by a variety of stressors including human modification of coastal watersheds. In this study we examined potential linkages between estuarine condition and...

  6. Quantitative Prediction of Beef Quality Using Visible and NIR Spectroscopy with Large Data Samples Under Industry Conditions

    NASA Astrophysics Data System (ADS)

    Qiao, T.; Ren, J.; Craigie, C.; Zabalza, J.; Maltin, Ch.; Marshall, S.

    2015-03-01

    It is well known that the eating quality of beef has a significant influence on the repurchase behavior of consumers. There are several key factors that affect the perception of quality, including color, tenderness, juiciness, and flavor. To support consumer repurchase choices, there is a need for an objective measurement of quality that could be applied to meat prior to its sale. Objective approaches such as offered by spectral technologies may be useful, but the analytical algorithms used remain to be optimized. For visible and near infrared (VISNIR) spectroscopy, Partial Least Squares Regression (PLSR) is a widely used technique for meat related quality modeling and prediction. In this paper, a Support Vector Machine (SVM) based machine learning approach is presented to predict beef eating quality traits. Although SVM has been successfully used in various disciplines, it has not been applied extensively to the analysis of meat quality parameters. To this end, the performance of PLSR and SVM as tools for the analysis of meat tenderness is evaluated, using a large dataset acquired under industrial conditions. The spectral dataset was collected using VISNIR spectroscopy with the wavelength ranging from 350 to 1800 nm on 234 beef M. longissimus thoracis steaks from heifers, steers, and young bulls. As the dimensionality with the VISNIR data is very high (over 1600 spectral bands), the Principal Component Analysis (PCA) technique was applied for feature extraction and data reduction. The extracted principal components (less than 100) were then used for data modeling and prediction. The prediction results showed that SVM has a greater potential to predict beef eating quality than PLSR, especially for the prediction of tenderness. The infl uence of animal gender on beef quality prediction was also investigated, and it was found that beef quality traits were predicted most accurately in beef from young bulls.

  7. Interval neural networks

    SciTech Connect

    Patil, R.B.

    1995-05-01

    Traditional neural networks like multi-layered perceptrons (MLP) use example patterns, i.e., pairs of real-valued observation vectors, ({rvec x},{rvec y}), to approximate function {cflx f}({rvec x}) = {rvec y}. To determine the parameters of the approximation, a special version of the gradient descent method called back-propagation is widely used. In many situations, observations of the input and output variables are not precise; instead, we usually have intervals of possible values. The imprecision could be due to the limited accuracy of the measuring instrument or could reflect genuine uncertainty in the observed variables. In such situation input and output data consist of mixed data types; intervals and precise numbers. Function approximation in interval domains is considered in this paper. We discuss a modification of the classical backpropagation learning algorithm to interval domains. Results are presented with simple examples demonstrating few properties of nonlinear interval mapping as noise resistance and finding set of solutions to the function approximation problem.

  8. Prediction of velocities for a range of streamflow conditions in Pennsylvania

    USGS Publications Warehouse

    Reed, L.A.; Stuckey, M.H.

    2002-01-01

    A regression equation that is used nationwide to predict traveltime in streams during periods of low and moderate flow was developed by H.E. Jobson in 1996. Because none of the data used in the development of the equation were from streams in Pennsylvania, velocities for low and moderate flows predicted by the equation were compared to velocities measured during time-of-travel studies on the Susquehanna, Delaware, and Lehigh Rivers. Although these comparisons showed good agreement, a similar comparison using velocities for higher flows indicated an overestimate by this regression equation. Because of the need for a method of computing traveltimes for periods of high flows, a new regression equation was developed using data from three sources: (1) time-of-travel studies conducted at low and moderate flow, (2) slopearea measurements of flood flows, and (3) velocities of the 100-year floodway as reported in various flood-insurance studies. The new regression equation can be used for predicting velocities associated with flows up to the 100-year flood for Pennsylvania streams. It has standard errors of estimate of 0.18 feet per second, 0.37 feet per second; and 0.31 feet per second, for time-of-travel studies in the Susquehanna, Delaware, and Lehigh Rivers, respectively. The standard error of estimate is 1.71 feet per second for velocities determined from the slope-area measurements and 1.22 feet per second for velocities determined from the flood-insurance studies.

  9. High-speed propeller noise predictions: Effects of boundary conditions used in blade loading calculations

    NASA Technical Reports Server (NTRS)

    Nallasamy, M.; Clark, B. J.; Groeneweg, J. F.

    1987-01-01

    The acoustics of an advanced single rotation SR-3 propeller at cruise conditions are studied employing a time-domain approach. The study evaluates the acoustic significance of the differences in blade pressures computed using nonreflecting rather than hard wall boundary conditions in the three-dimensional Euler code solution. The directivities of the harmonics of the blade passing frequency tone and the effects of chordwise loading on tone directivity are examined. The results show that the maximum difference in the computed sound pressure levels due to the use of blade pressure distributions obtained with the nonreflecting rather than the hard wall boundary conditions is about 1.5 dB. The blade passing frequency tone directivity obtained in the present study shows good agreement with jetstar flight data.

  10. Predicting the onset of transformation under noncontinuous cooling conditions. Part 2: Application to the austenite pearlite transformation

    SciTech Connect

    Pham, T.T.; Hawbolt, E.B.; Brimacombe, J.K.

    1995-08-01

    A detailed review of the additivity principle with respect to the incubation of the austenite decomposition was summarized in Part 1 of this two-part series and led to the concept of an ideal time-temperature-transformation (TTT) diagram. This curve is characteristic of the chemistry and austenite grain size in the steel and allows nonisothermal behavior to be described assuming additivity holds. The derivation of mathematical relationships between the ideal and experimental cooling data was presented in the first article. In this second article, an ideal curve for the austenite-to-pearlite transformation was derived from cooling data. The applicability of the ideal TTT curve for predicting the start of transformation under continuous cooling conditions was assessed for a range of cooling rates. Experiments were conducted under both isothermal and varying temperature conditions, including an industrial cooling schedule, using a Gleeble Thermal Simulator. Reasonable agreement was found between the predictions and the observed transformation start temperatures; predictions were consistent and compared favorably against other methods which have been frequently used to estimate the transformation start temperature for nonisothermal conditions.

  11. Reliability of Degree-Day Models to Predict the Development Time of Plutella xylostella (L.) under Field Conditions.

    PubMed

    Marchioro, C A; Krechemer, F S; de Moraes, C P; Foerster, L A

    2015-12-01

    The diamondback moth, Plutella xylostella (L.), is a cosmopolitan pest of brassicaceous crops occurring in regions with highly distinct climate conditions. Several studies have investigated the relationship between temperature and P. xylostella development rate, providing degree-day models for populations from different geographical regions. However, there are no data available to date to demonstrate the suitability of such models to make reliable projections on the development time for this species in field conditions. In the present study, 19 models available in the literature were tested regarding their ability to accurately predict the development time of two cohorts of P. xylostella under field conditions. Only 11 out of the 19 models tested accurately predicted the development time for the first cohort of P. xylostella, but only seven for the second cohort. Five models correctly predicted the development time for both cohorts evaluated. Our data demonstrate that the accuracy of the models available for P. xylostella varies widely and therefore should be used with caution for pest management purposes.

  12. Predicting maize yield in Zimbabwe using dry dekads derived from remotely sensed Vegetation Condition Index

    NASA Astrophysics Data System (ADS)

    Kuri, Farai; Murwira, Amon; Murwira, Karin S.; Masocha, Mhosisi

    2014-12-01

    Maize is a key crop contributing to food security in Southern Africa yet accurate estimates of maize yield prior to harvesting are scarce. Timely and accurate estimates of maize production are essential for ensuring food security by enabling actionable mitigation strategies and policies for prevention of food shortages. In this study, we regressed the number of dry dekads derived from VCI against official ground-based maize yield estimates to generate simple linear regression models for predicting maize yield throughout Zimbabwe over four seasons (2009-10, 2010-11, 2011-12, and 2012-13). The VCI was computed using Normalized Difference Vegetation Index (NDVI) time series dataset from the SPOT VEGETATION sensor for the period 1998-2013. A significant negative linear relationship between number of dry dekads and maize yield was observed in each season. The variation in yield explained by the models ranged from 75% to 90%. The models were evaluated with official ground-based yield data that was not used to generate the models. There is a close match between the predicted yield and the official yield statistics with an error of 33%. The observed consistency in the negative relationship between number of dry dekads and ground-based estimates of maize yield as well as the high explanatory power of the regression models suggest that VCI-derived dry dekads could be used to predict maize yield before the end of the season thereby making it possible to plan strategies for dealing with food deficits or surpluses on time.

  13. Perceived Working Conditions and Personal Resources Predicting Mental Health Counselor Well-Being

    ERIC Educational Resources Information Center

    Thompson, Isabel A.

    2012-01-01

    This study examined the influence of counselor perceived working conditions, length of time in field, counselor gender, mindfulness attitudes, compassion satisfaction, emotion-focused coping, problem focused coping, and maladaptive coping on levels of burnout and compassion fatigue in a sample of 213 mental health counselors. Cross-sectional…

  14. Childhood Nocturnal Enuresis: The Prediction of Premature Withdrawal from Behavioral Conditioning.

    ERIC Educational Resources Information Center

    Wagner, William G.; Johnson, J. T.

    1988-01-01

    Predictors of premature withdrawal from a 12-week program of behavioral conditioning for childhood nocturnal enuresis were examined for 47 children (ages 5-14). The function containing number of previous techniques used, presence of child behavior problems, and parent tolerance of enuresis was a significant predictor of early termination of…

  15. Spatial prediction models for the probable biological condition of streams and rivers in the USA

    EPA Science Inventory

    The National Rivers and Streams Assessment (NRSA) is a probability-based survey conducted by the US Environmental Protection Agency and its state and tribal partners. It provides information on the ecological condition of the rivers and streams in the conterminous USA, and the ex...

  16. A Preliminary Evaluation of Season-ahead Flood Prediction Conditioned on Large-scale Climate Drivers

    NASA Astrophysics Data System (ADS)

    Lee, Donghoon; Ward, Philip; Block, Paul

    2016-04-01

    Globally, flood disasters lead all natural hazards in terms of impacts on society, causing billions of dollars of damages each year. Typically, short-term forecasts emphasize immediate emergency actions, longer-range forecasts, on the order of months to seasons, however, can compliment short-term forecasts by focusing on disaster preparedness. In this study, the inter-annual variability of large-scale climate drivers (e.g. ENSO) is investigated to understand the prospects for skillful season-ahead flood prediction globally using PCR-GLOBWB modeled simulations. For example, global gridded correlations between discharge and Nino 3.4 are calculated, with notably strong correlations in the northwestern (-0.4~-0.6) and the southeastern (0.4~0.6) United States, and the Amazon river basin (-0.6~-0.8). Coupled interactions from multiple, simultaneous climate drivers are also evaluated. Skillful prediction has the potential to estimate season-ahead flood probabilities, flood extent, damages, and eventually integrate into early warning systems. This global approach is especially attractive for areas with limited observations and/or little capacity to develop early warning flood systems.

  17. Internet-based monitoring and prediction system of coal stockpile behaviors under atmospheric conditions.

    PubMed

    Yilmaz, Nihat; Ozdeniz, A Hadi

    2010-03-01

    Spontaneous combustion on industrial-scale stockpiles causes environmental problems and economic losses for the companies consuming large amounts of coal. In this study, an effective monitoring and prediction system based on internet was developed and implemented to prevent losses and environmental problems. The system was performed in a coal stockpile with 5 m width, 10 m length, 3 m height, and having 120 t of weight. The inner temperature data of the stockpile was recorded by 17 temperature sensors placed inside the stockpile at certain points. Additionally, the data relating to the air temperature, air humidity, atmospheric pressure, wind velocity, and wind direction that are the parameters affecting the coal stockpile were also recorded. The recorded values were analyzed with artificial neural network and Statistical modeling methods for prediction of spontaneous combustion. Real-time measurement values and model outputs were published with a web page on internet. The internet-based system can also provide real-time monitoring (combustion alarms, system status) and tele-controlling (Parameter adjusting, system control) through internet exclusively with a standard web browser without the need of any additional software.

  18. Predicting electromyographic signals under realistic conditions using a multiscale chemo–electro–mechanical finite element model

    PubMed Central

    Mordhorst, Mylena; Heidlauf, Thomas; Röhrle, Oliver

    2015-01-01

    This paper presents a novel multiscale finite element-based framework for modelling electromyographic (EMG) signals. The framework combines (i) a biophysical description of the excitation–contraction coupling at the half-sarcomere level, (ii) a model of the action potential (AP) propagation along muscle fibres, (iii) a continuum-mechanical formulation of force generation and deformation of the muscle, and (iv) a model for predicting the intramuscular and surface EMG. Owing to the biophysical description of the half-sarcomere, the model inherently accounts for physiological properties of skeletal muscle. To demonstrate this, the influence of membrane fatigue on the EMG signal during sustained contractions is investigated. During a stimulation period of 500 ms at 100 Hz, the predicted EMG amplitude decreases by 40% and the AP propagation velocity decreases by 15%. Further, the model can take into account contraction-induced deformations of the muscle. This is demonstrated by simulating fixed-length contractions of an idealized geometry and a model of the human tibialis anterior muscle (TA). The model of the TA furthermore demonstrates that the proposed finite element model is capable of simulating realistic geometries, complex fibre architectures, and can include different types of heterogeneities. In addition, the TA model accounts for a distributed innervation zone, different fibre types and appeals to motor unit discharge times that are based on a biophysical description of the α motor neurons. PMID:25844148

  19. Environmental and mental conditions predicting the experience of involuntary musical imagery: An experience sampling method study.

    PubMed

    Floridou, Georgia A; Müllensiefen, Daniel

    2015-05-01

    An experience sampling method (ESM) study on 40 volunteers was conducted to explore the environmental factors and psychological conditions related to involuntary musical imagery (INMI) in everyday life. Participants reported 6 times per day for one week on their INMI experiences, relevant contextual information and associated environmental conditions. The resulting data was modeled with Bayesian networks and led to insights into the interplay of factors related to INMI experiences. The activity that a person is engaged was found to play an important role in the experience of mind wandering, which in turn enables the experience of INMI. INMI occurrence is independent of the time of the day while the INMI trigger affects the subjective evaluation of the INMI experience. The results are compared to findings from earlier studies based on retrospective surveys and questionnaires and highlight the advantage of ESM techniques in research on spontaneous experiences like INMI. PMID:25800098

  20. Metabarcoding of benthic eukaryote communities predicts the ecological condition of estuaries.

    PubMed

    Chariton, Anthony A; Stephenson, Sarah; Morgan, Matthew J; Steven, Andrew D L; Colloff, Matthew J; Court, Leon N; Hardy, Christopher M

    2015-08-01

    DNA-derived measurements of biological composition have the potential to produce data covering all of life, and provide a tantalizing proposition for researchers and managers. We used metabarcoding to compare benthic eukaryote composition from five estuaries of varying condition. In contrast to traditional studies, we found biotic richness was greatest in the most disturbed estuary, with this being due to the large volume of extraneous material (i.e. run-off from aquaculture, agriculture and other catchment activities) being deposited in the system. In addition, we found strong correlations between composition and a number of environmental variables, including nutrients, pH and turbidity. A wide range of taxa responded to these environmental gradients, providing new insights into their sensitivities to natural and anthropogenic stressors. Metabarcoding has the capacity to bolster current monitoring techniques, enabling the decisions regarding ecological condition to be based on a more holistic view of biodiversity.

  1. Voxel-based morphometry predicts shifts in dendritic spine density and morphology with auditory fear conditioning.

    PubMed

    Keifer, O P; Hurt, R C; Gutman, D A; Keilholz, S D; Gourley, S L; Ressler, K J

    2015-07-07

    Neuroimaging has provided compelling data about the brain. Yet the underlying mechanisms of many neuroimaging techniques have not been elucidated. Here we report a voxel-based morphometry (VBM) study of Thy1-YFP mice following auditory fear conditioning complemented by confocal microscopy analysis of cortical thickness, neuronal morphometric features and nuclei size/density. Significant VBM results included the nuclei of the amygdala, the insula and the auditory cortex. There were no significant VBM changes in a control brain area. Focusing on the auditory cortex, confocal analysis showed that fear conditioning led to a significantly increased density of shorter and wider dendritic spines, while there were no spine differences in the control area. Of all the morphology metrics studied, the spine density was the only one to show significant correlation with the VBM signal. These data demonstrate that learning-induced structural changes detected by VBM may be partially explained by increases in dendritic spine density.

  2. An Individual-Based Diploid Model Predicts Limited Conditions Under Which Stochastic Gene Expression Becomes Advantageous.

    PubMed

    Matsumoto, Tomotaka; Mineta, Katsuhiko; Osada, Naoki; Araki, Hitoshi

    2015-01-01

    Recent studies suggest the existence of a stochasticity in gene expression (SGE) in many organisms, and its non-negligible effect on their phenotype and fitness. To date, however, how SGE affects the key parameters of population genetics are not well understood. SGE can increase the phenotypic variation and act as a load for individuals, if they are at the adaptive optimum in a stable environment. On the other hand, part of the phenotypic variation caused by SGE might become advantageous if individuals at the adaptive optimum become genetically less-adaptive, for example due to an environmental change. Furthermore, SGE of unimportant genes might have little or no fitness consequences. Thus, SGE can be advantageous, disadvantageous, or selectively neutral depending on its context. In addition, there might be a genetic basis that regulates magnitude of SGE, which is often referred to as "modifier genes," but little is known about the conditions under which such an SGE-modifier gene evolves. In the present study, we conducted individual-based computer simulations to examine these conditions in a diploid model. In the simulations, we considered a single locus that determines organismal fitness for simplicity, and that SGE on the locus creates fitness variation in a stochastic manner. We also considered another locus that modifies the magnitude of SGE. Our results suggested that SGE was always deleterious in stable environments and increased the fixation probability of deleterious mutations in this model. Even under frequently changing environmental conditions, only very strong natural selection made SGE adaptive. These results suggest that the evolution of SGE-modifier genes requires strict balance among the strength of natural selection, magnitude of SGE, and frequency of environmental changes. However, the degree of dominance affected the condition under which SGE becomes advantageous, indicating a better opportunity for the evolution of SGE in different genetic

  3. Learning to predict and control harmful events: chronic pain and conditioning.

    PubMed

    Vlaeyen, Johan W S

    2015-04-01

    Pain is a biologically relevant signal and response to bodily threat, associated with the urge to restore the integrity of the body. Immediate protective responses include increased arousal, selective attention, escape, and facial expressions, followed by recuperative avoidance and safety-seeking behaviors. To facilitate early and effective protection against future bodily threat or injury, learning takes place rapidly. Learning is the observable change in behavior due to events in the internal and external environmental and includes nonassociative (habituation and sensitization) and associative learning (Pavlovian and operant conditioning). Once acquired, these knowledge representations remain stored in memory and may generalize to perceptually or functionally similar events. Moreover, these processes are not just a consequence of pain; they may directly influence pain perception. In contrast to the rapid acquisition of learned responses, their extinction is slow, fragile, context dependent and only occurs through inhibitory processes. Here, we review features of associative forms of learning in humans that contribute to pain, pain-related distress, and disability and discuss promising future directions. Although conditioning has a long and honorable history, a conditioning perspective still might open new windows on novel treatment modalities that facilitate the well-being of individuals with chronic pain.

  4. Bioenergetics of Nutrient Reserves and Metabolism in Spiny Lobster Juveniles Sagmariasus verreauxi: Predicting Nutritional Condition from Hemolymph Biochemistry.

    PubMed

    Simon, C J; Fitzgibbon, Q P; Battison, A; Carter, C G; Battaglene, S C

    2015-01-01

    The nutritional condition of cultured Sagmariasus verreauxi juveniles over the molt and during starvation was investigated by studying their metabolism, bioenergetics of nutrient reserves, and hemolymph biochemistry. Juveniles were shown to downregulate standard metabolic rate by as much as 52% within 14 d during starvation. Hepatopancreas (HP) lipid was prioritized as a source of energy, but this reserve represented only between 1% and 13% of the total measured energy reserve and was used quickly during starvation, especially in the immediate postmolt period when as much as 60% was depleted within 3 d. Abdominal muscle (AM) protein represented between 74% and 90% of the total measured energy reserve in juvenile lobsters, and as much as 40% of available AM protein energy was used over 28 d of starvation after the molt. Carbohydrate reserves represented less than 2% of the measured total energy reserve in fed intermolt lobsters and provided negligible energy during starvation. Eighteen hemolymph parameters were measured to identify a nondestructive biomarker of condition that would reflect accurately the state of energy reserves of the lobster. Among these, the hemolymph Brix index was the most accurate and practical method to predict HP lipid and the total energy content of both the HP and the AM in juvenile S. verreauxi. The Brix index was strongly correlated with hemolymph proteins, triglyceride, cholesterol, calcium, and phosphorus concentrations, as well as lipase activity; all were useful in predicting condition. Electrolytes such as chloride, magnesium, and potassium and metabolites such as glucose and lactate were poor indicators of nutritional condition. Uric acid and the "albumin"-to-"globulin" ratio provided complementary information to the Brix index, which may assist in determining nutritional condition of wild juvenile lobsters of unknown intermolt development. This study will greatly assist future ecological studies examining the nutritional condition

  5. Bioenergetics of Nutrient Reserves and Metabolism in Spiny Lobster Juveniles Sagmariasus verreauxi: Predicting Nutritional Condition from Hemolymph Biochemistry.

    PubMed

    Simon, C J; Fitzgibbon, Q P; Battison, A; Carter, C G; Battaglene, S C

    2015-01-01

    The nutritional condition of cultured Sagmariasus verreauxi juveniles over the molt and during starvation was investigated by studying their metabolism, bioenergetics of nutrient reserves, and hemolymph biochemistry. Juveniles were shown to downregulate standard metabolic rate by as much as 52% within 14 d during starvation. Hepatopancreas (HP) lipid was prioritized as a source of energy, but this reserve represented only between 1% and 13% of the total measured energy reserve and was used quickly during starvation, especially in the immediate postmolt period when as much as 60% was depleted within 3 d. Abdominal muscle (AM) protein represented between 74% and 90% of the total measured energy reserve in juvenile lobsters, and as much as 40% of available AM protein energy was used over 28 d of starvation after the molt. Carbohydrate reserves represented less than 2% of the measured total energy reserve in fed intermolt lobsters and provided negligible energy during starvation. Eighteen hemolymph parameters were measured to identify a nondestructive biomarker of condition that would reflect accurately the state of energy reserves of the lobster. Among these, the hemolymph Brix index was the most accurate and practical method to predict HP lipid and the total energy content of both the HP and the AM in juvenile S. verreauxi. The Brix index was strongly correlated with hemolymph proteins, triglyceride, cholesterol, calcium, and phosphorus concentrations, as well as lipase activity; all were useful in predicting condition. Electrolytes such as chloride, magnesium, and potassium and metabolites such as glucose and lactate were poor indicators of nutritional condition. Uric acid and the "albumin"-to-"globulin" ratio provided complementary information to the Brix index, which may assist in determining nutritional condition of wild juvenile lobsters of unknown intermolt development. This study will greatly assist future ecological studies examining the nutritional condition

  6. Predicting favorable conditions for early leaf spot of peanut using output from the Weather Research and Forecasting (WRF) model.

    PubMed

    Olatinwo, Rabiu O; Prabha, Thara V; Paz, Joel O; Hoogenboom, Gerrit

    2012-03-01

    Early leaf spot of peanut (Arachis hypogaea L.), a disease caused by Cercospora arachidicola S. Hori, is responsible for an annual crop loss of several million dollars in the southeastern United States alone. The development of early leaf spot on peanut and subsequent spread of the spores of C. arachidicola relies on favorable weather conditions. Accurate spatio-temporal weather information is crucial for monitoring the progression of favorable conditions and determining the potential threat of the disease. Therefore, the development of a prediction model for mitigating the risk of early leaf spot in peanut production is important. The specific objective of this study was to demonstrate the application of the high-resolution Weather Research and Forecasting (WRF) model for management of early leaf spot in peanut. We coupled high-resolution weather output of the WRF, i.e. relative humidity and temperature, with the Oklahoma peanut leaf spot advisory model in predicting favorable conditions for early leaf spot infection over Georgia in 2007. Results showed a more favorable infection condition in the southeastern coastline of Georgia where the infection threshold were met sooner compared to the southwestern and central part of Georgia where the disease risk was lower. A newly introduced infection threat index indicates that the leaf spot threat threshold was met sooner at Alma, GA, compared to Tifton and Cordele, GA. The short-term prediction of weather parameters and their use in the management of peanut diseases is a viable and promising technique, which could help growers make accurate management decisions, and lower disease impact through optimum timing of fungicide applications.

  7. Nondestructive prediction of point source pyroshock response spectra based on experimental conditioning of laser-induced shocks

    NASA Astrophysics Data System (ADS)

    Jang, Jae-Kyeong; Lee, Jung-Ryul

    2014-09-01

    Pyroshock can easily cause failures in electronic and optical components that are sensitive to high-frequency energy. Pyroshock is generated during explosive-based pyrotechnical events, such as the separation of boosters from a space shuttle and the separation of satellites from a space launcher. Therefore, the prediction of high-frequency structural response, particularly the shock response spectrum (SRS), is important for safe operation of pyrotechnical devices. In general, real explosive testing using distributed accelerometers is widely used. This paper proposes a technology to replace the expensive, dangerous, low-repeatability explosive test with a laser-induced shock test based on a laser beam and in-line filter conditioning. This method does not use any special numerical signal processing. Two different experiments based on explosive and laser excitation were performed with a 2-mm thick aluminum plate. The optimum laser-induced shock experimental conditions to predict real pyroshock were investigated while considering the size, energy, and fluence of the laser beam as parameters. The similarity of the SRS of the laser-induced shock to that of the real explosive pyroshock was evaluated based on the mean acceleration difference (MAD, %). The experimentally determined optimal conditions were also applied to four points on the path of a pyroshock propagation. To match the SRS at each point, the laser-induced shock was amplified, for which three different gain concepts are proposed: the initial gain, optimized gain, and constant gain. The proposed technology enables nondestructive pyro SRS prediction by conditioning the laser-induced shock to obtain an SRS with high similarity to the real pyroshock.

  8. Chemiluminescence as a condition monitoring method for thermal aging and lifetime prediction of an HTPB elastomer.

    SciTech Connect

    Gillen, Kenneth Todd; Minier, Leanna M. G.; Celina, Mathias Christopher; Trujillo, Ana B.

    2007-03-01

    Chemiluminescence (CL) has been applied as a condition monitoring technique to assess aging related changes in a hydroxyl-terminated-polybutadiene based polyurethane elastomer. Initial thermal aging of this polymer was conducted between 110 and 50 C. Two CL methods were applied to examine the degradative changes that had occurred in these aged samples: isothermal 'wear-out' experiments under oxygen yielding initial CL intensity and 'wear-out' time data, and temperature ramp experiments under inert conditions as a measure of previously accumulated hydroperoxides or other reactive species. The sensitivities of these CL features to prior aging exposure of the polymer were evaluated on the basis of qualifying this method as a quick screening technique for quantification of degradation levels. Both the techniques yielded data representing the aging trends in this material via correlation with mechanical property changes. Initial CL rates from the isothermal experiments are the most sensitive and suitable approach for documenting material changes during the early part of thermal aging.

  9. Predicting apparent slip at liquid-liquid interfaces without an interface slip condition

    NASA Astrophysics Data System (ADS)

    Poesio, Pietro; Damone, Angelo; Matar, Omar

    2015-11-01

    We show that if we include a density-dependent viscosity into the Navier-Stokes equations then we can describe, naturally, the velocity profile in the interfacial region, as we transition from one fluid to another. This requires knowledge of the density distribution (for instance, via Molecular Dynamics [MD] simulations, a diffuse-interface approach, or Density Functional Theory) everywhere in the fluids, even at liquid-liquid interfaces where regions of rapid density variations are possible due to molecular interactions. We therefore do not need an artificial interface condition that describes the apparent velocity slip. If the results are compared with the computations obtained from MD simulations, we find an almost perfect agreement. The main contribution of this work is to provide a simple way to account for the apparent slip at liquid-liquid interfaces without relying upon an additional boundary condition, which needs to be calculated separately using MD simulations. Examples are provided involving two immiscible fluids of varying average density ratios, undergoing simple Couette and Poisseuille flows. MIUR through PRIN2012-NANOBridge; Royal Society International Exchange Scheme (IE141486).

  10. Suitability of different comfort indices for the prediction of thermal conditions in tree-covered outdoor spaces in arid cities

    NASA Astrophysics Data System (ADS)

    Ruiz, María Angélica; Correa, Erica Norma

    2015-10-01

    Outdoor thermal comfort is one of the most influential factors in the habitability of a space. Thermal level is defined not only by climate variables but also by the adaptation of people to the environment. This study presents a comparison between inductive and deductive thermal comfort models, contrasted with subjective reports, in order to identify which of the models can be used to most correctly predict thermal comfort in tree-covered outdoor spaces of the Mendoza Metropolitan Area, an intensely forested and open city located in an arid zone. Interviews and microclimatic measurements were carried out in winter 2010 and in summer 2011. Six widely used indices were selected according to different levels of complexity: the Temperature-Humidity Index (THI), Vinje's Comfort Index (PE), Thermal Sensation Index (TS), the Predicted Mean Vote (PMV), the COMFA model's energy balance (S), and the Physiological Equivalent Temperature (PET). The results show that the predictive models evaluated show percentages of predictive ability lower than 25 %. Despite this low indicator, inductive methods are adequate for obtaining a diagnosis of the degree and frequency in which a space is comfortable or not whereas deductive methods are recommended to influence urban design strategies. In addition, it is necessary to develop local models to evaluate perceived thermal comfort more adequately. This type of tool is very useful in the design and evaluation of the thermal conditions in outdoor spaces, based not only to climatic criteria but also subjective sensations.

  11. Thermal conditions in freezing chambers and prediction of the thermophysiological responses of workers

    NASA Astrophysics Data System (ADS)

    Raimundo, A. M.; Oliveira, A. V. M.; Gaspar, A. R.; Quintela, D. A.

    2015-11-01

    The present work is dedicated to the assessment of the cold thermal strain of human beings working within freezing chambers. To obtain the present results, both field measurements and a numerical procedure based on a modified version of the Stolwijk thermoregulation model were used. Eighteen freezing chambers were considered. A wide range of physical parameters of the cold stores, the workers clothing insulation, and the working and recovering periods were observed. The combination of these environmental and individual parameters lead to different levels of thermal stress, which were grouped under three categories. Some good practices were observed in the field evaluations, namely situations with appropriate level of clothing protection and limited duration of exposure to cold avoiding unacceptable level of hypothermia. However, the clothing ensembles normally used by the workers do not provide the minimum required insulation, which suggests the possibility of the whole body cooling for levels higher than admissible. The numerical predictions corroborate the main conclusions of the field survey. The results obtained with both methodologies clearly show that, for the low temperature of the freezing chambers, the clothing insulation is insufficient, the exposure periods are too long, and the recovering periods are inadequate. Thus, high levels of physiological strain can indeed be reached by human beings under such working environments.

  12. Predicting field-scale dispersion under realistic conditions with the polar Markovian velocity process model

    NASA Astrophysics Data System (ADS)

    Dünser, Simon; Meyer, Daniel W.

    2016-06-01

    In most groundwater aquifers, dispersion of tracers is dominated by flow-field inhomogeneities resulting from the underlying heterogeneous conductivity or transmissivity field. This effect is referred to as macrodispersion. Since in practice, besides a few point measurements the complete conductivity field is virtually never available, a probabilistic treatment is needed. To quantify the uncertainty in tracer concentrations from a given geostatistical model for the conductivity, Monte Carlo (MC) simulation is typically used. To avoid the excessive computational costs of MC, the polar Markovian velocity process (PMVP) model was recently introduced delivering predictions at about three orders of magnitude smaller computing times. In artificial test cases, the PMVP model has provided good results in comparison with MC. In this study, we further validate the model in a more challenging and realistic setup. The setup considered is derived from the well-known benchmark macrodispersion experiment (MADE), which is highly heterogeneous and non-stationary with a large number of unevenly scattered conductivity measurements. Validations were done against reference MC and good overall agreement was found. Moreover, simulations of a simplified setup with a single measurement were conducted in order to reassess the model's most fundamental assumptions and to provide guidance for model improvements.

  13. The Value of Conditioning Data for Prediction of Conservative Solute Transport at the Oyster Site, Virginia

    SciTech Connect

    Scheibe, Timothy D.

    2001-12-01

    The large and diverse body of subsurface characterization data generated at a field research site near Oyster, VA provides a unique opportunity to test various approaches for characterizing field-scale heterogeneity in aquifer properties and modeling subsurface flow and transport. We are using observed bromide breakthrough curves (BTCs) from an injection experiment conducted in 1999 as a baseline for evaluating data worth and model effectiveness. BTCs are available at 24 multi-level samplers, eight ports each (192 total sampling points). Each BTC is a time series of measured concentrations, spaced two to twelve hours apart over the seven-day field experiment. A detailed model, implemented using the RAFT code, is used to simulate breakthrough curves at the sampler locations. This model requires the specification of spatial distributions of hydrologic parameters such as hydraulic conductivity. This in turn involves the integration of data of various types and amounts into a conceptual model framework. The number of possible conceptualizations and methods for data integration is nearly limitless, and each gives rise to a different prediction of bromide breakthrough at sampling points. To evaluate the relative appropriateness of each approach, and the value of the data utilized therein, we simulate BTCs at each sampler location and quantitatively compare them to the observed BTCs.

  14. Thermal conditions in freezing chambers and prediction of the thermophysiological responses of workers.

    PubMed

    Raimundo, A M; Oliveira, A V M; Gaspar, A R; Quintela, D A

    2015-11-01

    The present work is dedicated to the assessment of the cold thermal strain of human beings working within freezing chambers. To obtain the present results, both field measurements and a numerical procedure based on a modified version of the Stolwijk thermoregulation model were used. Eighteen freezing chambers were considered. A wide range of physical parameters of the cold stores, the workers clothing insulation, and the working and recovering periods were observed. The combination of these environmental and individual parameters lead to different levels of thermal stress, which were grouped under three categories. Some good practices were observed in the field evaluations, namely situations with appropriate level of clothing protection and limited duration of exposure to cold avoiding unacceptable level of hypothermia. However, the clothing ensembles normally used by the workers do not provide the minimum required insulation, which suggests the possibility of the whole body cooling for levels higher than admissible. The numerical predictions corroborate the main conclusions of the field survey. The results obtained with both methodologies clearly show that, for the low temperature of the freezing chambers, the clothing insulation is insufficient, the exposure periods are too long, and the recovering periods are inadequate. Thus, high levels of physiological strain can indeed be reached by human beings under such working environments.

  15. Evaluation of operational numerical weather predictions in relation to the prevailing synoptic conditions

    NASA Astrophysics Data System (ADS)

    Pytharoulis, Ioannis; Tegoulias, Ioannis; Karacostas, Theodore; Kotsopoulos, Stylianos; Kartsios, Stergios; Bampzelis, Dimitrios

    2015-04-01

    The Thessaly plain, which is located in central Greece, has a vital role in the financial life of the country, because of its significant agricultural production. The aim of DAPHNE project (http://www.daphne-meteo.gr) is to tackle the problem of drought in this area by means of Weather Modification in convective clouds. This problem is reinforced by the increase of population and the water demand for irrigation, especially during the warm period of the year. The nonhydrostatic Weather Research and Forecasting model (WRF), is utilized for research and operational purposes of DAPHNE project. The WRF output fields are employed by the partners in order to provide high-resolution meteorological guidance and plan the project's operations. The model domains cover: i) Europe, the Mediterranean sea and northern Africa, ii) Greece and iii) the wider region of Thessaly (at selected periods), at horizontal grid-spacings of 15km, 5km and 1km, respectively, using 2-way telescoping nesting. The aim of this research work is to investigate the model performance in relation to the prevailing upper-air synoptic circulation. The statistical evaluation of the high-resolution operational forecasts of near-surface and upper air fields is performed at a selected period of the operational phase of the project using surface observations, gridded fields and weather radar data. The verification is based on gridded, point and object oriented techniques. The 10 upper-air circulation types, which describe the prevailing conditions over Greece, are employed in the synoptic classification. This methodology allows the identification of model errors that occur and/or are maximized at specific synoptic conditions and may otherwise be obscured in aggregate statistics. Preliminary analysis indicates that the largest errors are associated with cyclonic conditions. Acknowledgments This research work of Daphne project (11SYN_8_1088) is co-funded by the European Union (European Regional Development Fund

  16. Modeling stream fish distributions using interval-censored detection times.

    PubMed

    Ferreira, Mário; Filipe, Ana Filipa; Bardos, David C; Magalhães, Maria Filomena; Beja, Pedro

    2016-08-01

    Controlling for imperfect detection is important for developing species distribution models (SDMs). Occupancy-detection models based on the time needed to detect a species can be used to address this problem, but this is hindered when times to detection are not known precisely. Here, we extend the time-to-detection model to deal with detections recorded in time intervals and illustrate the method using a case study on stream fish distribution modeling. We collected electrofishing samples of six fish species across a Mediterranean watershed in Northeast Portugal. Based on a Bayesian hierarchical framework, we modeled the probability of water presence in stream channels, and the probability of species occupancy conditional on water presence, in relation to environmental and spatial variables. We also modeled time-to-first detection conditional on occupancy in relation to local factors, using modified interval-censored exponential survival models. Posterior distributions of occupancy probabilities derived from the models were used to produce species distribution maps. Simulations indicated that the modified time-to-detection model provided unbiased parameter estimates despite interval-censoring. There was a tendency for spatial variation in detection rates to be primarily influenced by depth and, to a lesser extent, stream width. Species occupancies were consistently affected by stream order, elevation, and annual precipitation. Bayesian P-values and AUCs indicated that all models had adequate fit and high discrimination ability, respectively. Mapping of predicted occupancy probabilities showed widespread distribution by most species, but uncertainty was generally higher in tributaries and upper reaches. The interval-censored time-to-detection model provides a practical solution to model occupancy-detection when detections are recorded in time intervals. This modeling framework is useful for developing SDMs while controlling for variation in detection rates, as it

  17. Use of statistical modeling to predict the effect of formulation composition on conditioning shampoo performance.

    PubMed

    Lepilleur, Carole; Giovannitti-Jensen, Ann; Kyer, Carol

    2013-01-01

    Formulation composition has a dramatic influence on the performance of conditioning shampoos. The purpose of this study is to determine the factors affecting the performance of various cationic polymers in those systems. An experiment was conducted by varying the levels of three surfactants (sodium lauryl ether sulfate, sodium lauryl sulfate, and cocamidopropyl betaine) in formulations containing various cationic polymers such as cationic cassia derivatives of different cationic charge densities (1.9, 2.3, and 3.0 mEq/g), cationic guar (0.98 mEq/g), and cationic hydroxyethyl cellulose (1.03 mEq/g). The results show the formulation composition dramatically affects silicone and cationic polymer deposition. In particular, three parameters are of importance in determining deposition efficiency: ionic strength, surfactant (micelle) charge, and total amount of surfactant. The cationic polymer composition, molecular weight, and charge density are also important in determining which of the previous three parameters influence the performance most.

  18. Differences in Light Interception in Grass Monocultures Predict Short-Term Competitive Outcomes under Productive Conditions

    PubMed Central

    Vojtech, Eva; Turnbull, Lindsay A.; Hector, Andy

    2007-01-01

    Due to its inherent asymmetry, competition for light is thought to cause loss of diversity from eutrophied systems. However, most of the work on this topic in grasslands has been phenomenological and has not measured light directly. We present the results of one of the few mechanistic experiments investigating the outcome of short-term competition using measurements of light interception from monocultures of five perennial grass species grown under fertilized and irrigated conditions. We found that the level of incident light intercepted by each species in monoculture, a direct measure of resource-reduction ability, was an excellent predictor of the relative competitive effect in pairwise mixtures. Competition for light was asymmetric in relation to differences in light intercepting ability. Our results are consistent with the idea that when light is a limiting resource, competition between species for this resource can be asymmetric, contributing to high dominance and low diversity. PMID:17565366

  19. Bayesian conditioning of a rainfall-runoff model for predicting flows in ungauged catchments and under land use changes

    NASA Astrophysics Data System (ADS)

    Bulygina, Nataliya; McIntyre, Neil; Wheater, Howard

    2011-02-01

    A novel method is presented for conditioning rainfall-runoff models for ungauged catchment and land use impact applications. The method conditions the model on information from multiple regionalized response indices using a formal Bayesian approach. Two indices that hold information about soil type and land use effects are the base flow index from the Hydrology of Soil Type (HOST) classification and curve number from the U.S. Department of Agriculture's Soil Conservation Service soil and land use classification. These indices are used to constrain a five-parameter probability distributed moisture model for subcatchments of the Wye (grazed grassland) and Severn (mainly afforested) catchments in the United Kingdom. The base flow index and curve number constrain only two of the five model parameters, indicating that ideally, other sources of information would be sought. Nevertheless, the procedure significantly reduces the prior uncertainty in runoff prediction and gives predictions close to those of the calibrated models. For the case study, the introduction of the curve number in addition to the base flow index has only a small effect on model performance and uncertainty; however, it allows a distinction between the effects of soil type and land management for the purpose of scenario analysis. The principal assumptions used in the method are the applicability of the curve number classification system and its mapping to UK soil types and the likelihood function used for Bayesian conditioning.

  20. Prediction of methotrexate CNS distribution in different species - influence of disease conditions.

    PubMed

    Westerhout, Joost; van den Berg, Dirk-Jan; Hartman, Robin; Danhof, Meindert; de Lange, Elizabeth C M

    2014-06-16

    Children and adults with malignant diseases have a high risk of prevalence of the tumor in the central nervous system (CNS). As prophylaxis treatment methotrexate is often given. In order to monitor methotrexate exposure in the CNS, cerebrospinal fluid (CSF) concentrations are often measured. However, the question is in how far we can rely on CSF concentrations of methotrexate as appropriate surrogate for brain target site concentrations, especially under disease conditions. In this study, we have investigated the spatial distribution of unbound methotrexate in healthy rat brain by parallel microdialysis, with or without inhibition of Mrp/Oat/Oatp-mediated active transport processes by a co-administration of probenecid. Specifically, we have focused on the relationship between brain extracellular fluid (brainECF) and CSF concentrations. The data were used to develop a systems-based pharmacokinetic (SBPK) brain distribution model for methotrexate. This model was subsequently applied on literature data on methotrexate brain distribution in other healthy and diseased rats (brainECF), healthy dogs (CSF) and diseased children (CSF) and adults (brainECF and CSF). Important differences between brainECF and CSF kinetics were found, but we have found that inhibition of Mrp/Oat/Oatp-mediated active transport processes does not significantly influence the relationship between brainECF and CSF fluid methotrexate concentrations. It is concluded that in parallel obtained data on unbound brainECF, CSF and plasma concentrations, under dynamic conditions, combined with advanced mathematical modeling is a most valid approach to develop SBPK models that allow for revealing the mechanisms underlying the relationship between brainECF and CSF concentrations in health and disease.

  1. Chronic health conditions and depressive symptoms strongly predict persistent food insecurity among rural low-income families.

    PubMed

    Hanson, Karla L; Olson, Christine M

    2012-08-01

    Longitudinal studies of food insecurity have not considered the unique circumstances of rural families. This study identified factors predictive of discontinuous and persistent food insecurity over three years among low-income families with children in rural counties in 13 U.S. states. Respondents reported substantial knowledge of community resources, food and finance skills, and use of formal public food assistance, yet 24% had persistent food insecurity, and another 41% were food insecure for one or two years. Multivariate multinomial regression models tested relationships between human capital, social support, financial resources, expenses, and food insecurity. Enduring chronic health conditions increased the risk of both discontinuous and persistent food insecurity. Lasting risk for depression predicted only persistent food insecurity. Education beyond high school was the only factor found protective against persistent food insecurity. Access to quality physical and mental health care services are essential to ameliorate persistent food insecurity among rural, low-income families.

  2. Efficiency of neural network-based combinatorial model predicting optimal culture conditions for maximum biomass yields in hairy root cultures.

    PubMed

    Mehrotra, Shakti; Prakash, O; Khan, Feroz; Kukreja, A K

    2013-02-01

    KEY MESSAGE : ANN-based combinatorial model is proposed and its efficiency is assessed for the prediction of optimal culture conditions to achieve maximum productivity in a bioprocess in terms of high biomass. A neural network approach is utilized in combination with Hidden Markov concept to assess the optimal values of different environmental factors that result in maximum biomass productivity of cultured tissues after definite culture duration. Five hidden Markov models (HMMs) were derived for five test culture conditions, i.e. pH of liquid growth medium, volume of medium per culture vessel, sucrose concentration (%w/v) in growth medium, nitrate concentration (g/l) in the medium and finally the density of initial inoculum (g fresh weight) per culture vessel and their corresponding fresh weight biomass. The artificial neural network (ANN) model was represented as the function of these five Markov models, and the overall simulation of fresh weight biomass was done with this combinatorial ANN-HMM. The empirical results of Rauwolfia serpentina hairy roots were taken as model and compared with simulated results obtained from pure ANN and ANN-HMMs. The stochastic testing and Cronbach's α-value of pure and combinatorial model revealed more internal consistency and skewed character (0.4635) in histogram of ANN-HMM compared to pure ANN (0.3804). The simulated results for optimal conditions of maximum fresh weight production obtained from ANN-HMM and ANN model closely resemble the experimentally optimized culture conditions based on which highest fresh weight was obtained. However, only 2.99 % deviation from the experimental values could be observed in the values obtained from combinatorial model when compared to the pure ANN model (5.44 %). This comparison showed 45 % better potential of combinatorial model for the prediction of optimal culture conditions for the best growth of hairy root cultures.

  3. Brain natriuretic peptide predicts forced vital capacity of the lungs, oxygen pulse and peak oxygen consumption in physiological condition.

    PubMed

    Popovic, Dejana; Ostojic, Miodrag C; Popovic, Bojana; Petrovic, Milan; Vujisic-Tesic, Bosiljka; Kocijancic, Aleksandar; Banovic, Marko; Arandjelovic, Aleksandra; Stojiljkovic, Stanimir; Markovic, Vidan; Damjanovic, Svetozar S

    2013-05-01

    Brain natriuretic peptide (NT-pro-BNP) is used as marker of cardiac and pulmonary diseases. However, the predictive value of circulating NT-pro-BNP for cardiac and pulmonary performance is unclear in physiological conditions. Standard echocardiography, tissue Doppler and forced spirometry at rest were used to assess cardiac parameters and forced vital capacity (FVC) in two groups of athletes (16 elite male wrestlers (W), 21 water polo player (WP)), as different stress adaptation models, and 20 sedentary subjects (C) matched for age. Cardiopulmonary test on treadmill (CPET), as acute stress model, was used to measure peak oxygen consumption (peak VO2), maximal heart rate (HRmax) and peak oxygen pulse (peak VO2/HR). NT-pro-BNP was measured by immunoassey sandwich technique 10min before the test - at rest, at the beginning of the test, at maximal effort, at third minute of recovery. FVC was higher in athletes and the highest in W (WP 5.60±0.29 l; W 6.57±1.00 l; C 5.41±0.29 l; p<0.01). Peak VO2 and peak VO2/HR were higher in athletes and the highest in WP. HRmax was not different among groups. In all groups, NT-pro-BNP decreased from rest to the beginning phase, increased in maximal effort and stayed unchanged in recovery. NT-pro-BNP was higher in C than W in all phases; WP had similar values as W and C. On multiple regression analysis, in all three groups together, ΔNT-pro-BNP from rest to the beginning phase independently predicted both peak VO2 and peak VO2/HR (r=0.38, 0.35; B=37.40, 0.19; p=0.007, 0.000, respectively). NT-pro-BNP at rest predicted HRmax (r=-0.32, B=-0.22, p=0.02). Maximal NT-pro-BNP predicted FVC (r=-0.22, B=-0.07, p=0.02). These results show noticeable predictive value of NT-pro-BNP for both cardiac and pulmonary performance in physiological conditions suggesting that NT-pro-BNP could be a common regulatory factor coordinating adaptation of heart and lungs to stress condition.

  4. Acceleration-induced electrocardiographic interval changes.

    PubMed

    Whinnery, C C; Whinnery, J E

    1988-02-01

    The electrocardiographic intervals (PR, QRS, QT, and RR) before, during, and post +Gz stress were measured in 24 healthy male subjects undergoing +Gz centrifuge exposure. The PR and QRS intervals responded in a predictable manner, shortening during stress and returning to baseline resting values post-stress. The QT interval, however, was not observed to be dependent solely on heart rate. Bazett's formula, which was developed to correct for heart rate variability, did not adequately result in a homogeneous correction of the QT interval for each stress-related period. During +Gz stress, the QT was shortened, and the QTc prolonged. The QT interval remained shortened even though the heart rate returned to baseline (with the QTc undercorrected) in the post-stress period. The QT (QTc) interval variations probably reflect the effects of both heart rate and autonomic balance during and after +Gz stress, and may provide a measure of the prevailing autonomic (sympathetic or parasympathetic) tone existing at a given point associated with +Gz stress. These electrocardiographic interval changes define the normal response for healthy individuals. Individuals with exaggerated autonomic responses could be identified by comparing their responses to these normal responses resulting from +Gz stress. PMID:3345170

  5. Prediction of a new ground state of superhard compound B6O at ambient conditions.

    PubMed

    Dong, Huafeng; Oganov, Artem R; Wang, Qinggao; Wang, Sheng-Nan; Wang, Zhenhai; Zhang, Jin; Esfahani, M Mahdi Davari; Zhou, Xiang-Feng; Wu, Fugen; Zhu, Qiang

    2016-08-08

    Boron suboxide B6O, the hardest known oxide, has an Rm crystal structure (α-B6O) that can be described as an oxygen-stuffed structure of α-boron, or, equivalently, as a cubic close packing of B12 icosahedra with two oxygen atoms occupying all octahedral voids in it. Here we show a new ground state of this compound at ambient conditions, Cmcm-B6O (β-B6O), which in all quantum-mechanical treatments that we tested comes out to be slightly but consistently more stable. Increasing pressure and temperature further stabilizes it with respect to the known α-B6O structure. β-B6O also has a slightly higher hardness and may be synthesized using different experimental protocols. We suggest that β-B6O is present in mixture with α-B6O, and its presence accounts for previously unexplained bands in the experimental Raman spectrum.

  6. Prediction of a new ground state of superhard compound B6O at ambient conditions

    NASA Astrophysics Data System (ADS)

    Dong, Huafeng; Oganov, Artem R.; Wang, Qinggao; Wang, Sheng-Nan; Wang, Zhenhai; Zhang, Jin; Esfahani, M. Mahdi Davari; Zhou, Xiang-Feng; Wu, Fugen; Zhu, Qiang

    2016-08-01

    Boron suboxide B6O, the hardest known oxide, has an Rm crystal structure (α-B6O) that can be described as an oxygen-stuffed structure of α-boron, or, equivalently, as a cubic close packing of B12 icosahedra with two oxygen atoms occupying all octahedral voids in it. Here we show a new ground state of this compound at ambient conditions, Cmcm-B6O (β-B6O), which in all quantum-mechanical treatments that we tested comes out to be slightly but consistently more stable. Increasing pressure and temperature further stabilizes it with respect to the known α-B6O structure. β-B6O also has a slightly higher hardness and may be synthesized using different experimental protocols. We suggest that β-B6O is present in mixture with α-B6O, and its presence accounts for previously unexplained bands in the experimental Raman spectrum.

  7. Prediction of a new ground state of superhard compound B6O at ambient conditions

    PubMed Central

    Dong, Huafeng; Oganov, Artem R.; Wang, Qinggao; Wang, Sheng-Nan; Wang, Zhenhai; Zhang, Jin; Esfahani, M. Mahdi Davari; Zhou, Xiang-Feng; Wu, Fugen; Zhu, Qiang

    2016-01-01

    Boron suboxide B6O, the hardest known oxide, has an Rm crystal structure (α-B6O) that can be described as an oxygen-stuffed structure of α-boron, or, equivalently, as a cubic close packing of B12 icosahedra with two oxygen atoms occupying all octahedral voids in it. Here we show a new ground state of this compound at ambient conditions, Cmcm-B6O (β-B6O), which in all quantum-mechanical treatments that we tested comes out to be slightly but consistently more stable. Increasing pressure and temperature further stabilizes it with respect to the known α-B6O structure. β-B6O also has a slightly higher hardness and may be synthesized using different experimental protocols. We suggest that β-B6O is present in mixture with α-B6O, and its presence accounts for previously unexplained bands in the experimental Raman spectrum. PMID:27498718

  8. Using conditional inference trees and random forests to predict the bioaccumulation potential of organic chemicals.

    PubMed

    Strempel, Sebastian; Nendza, Monika; Scheringer, Martin; Hungerbühler, Konrad

    2013-04-01

    The present study presents a data-oriented, tiered approach to assessing the bioaccumulation potential of chemicals according to the European chemicals regulation on Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH). The authors compiled data for eight physicochemical descriptors (partition coefficients, degradation half-lives, polarity, and so forth) for a set of 713 organic chemicals for which experimental values of the bioconcentration factor (BCF) are available. The authors employed supervised machine learning methods (conditional inference trees and random forests) to derive relationships between the physicochemical descriptors and the BCF values. In a first tier, the authors established rules for classifying a chemical as bioaccumulative (B) or nonbioaccumulative (non-B). In a second tier, the authors developed a new tool for estimating numerical BCF values. For both cases the optimal set of relevant descriptors was determined; these are biotransformation half-life and octanol-water distribution coefficient (log D) for the classification rules and log D, biotransformation half-life, and topological polar surface area for the BCF estimation tool. The uncertainty of the BCF estimates obtained with the new estimation tool was quantified by comparing the estimated and experimental BCF values of the 713 chemicals. Comparison with existing BCF estimation methods indicates that the performance of this new BCF estimation tool is at least as high as that of existing methods. The authors recommend the present study's classification rules and BCF estimation tool for a consensus application in combination with existing BCF estimation methods.

  9. Prediction of a new ground state of superhard compound B6O at ambient conditions.

    PubMed

    Dong, Huafeng; Oganov, Artem R; Wang, Qinggao; Wang, Sheng-Nan; Wang, Zhenhai; Zhang, Jin; Esfahani, M Mahdi Davari; Zhou, Xiang-Feng; Wu, Fugen; Zhu, Qiang

    2016-01-01

    Boron suboxide B6O, the hardest known oxide, has an Rm crystal structure (α-B6O) that can be described as an oxygen-stuffed structure of α-boron, or, equivalently, as a cubic close packing of B12 icosahedra with two oxygen atoms occupying all octahedral voids in it. Here we show a new ground state of this compound at ambient conditions, Cmcm-B6O (β-B6O), which in all quantum-mechanical treatments that we tested comes out to be slightly but consistently more stable. Increasing pressure and temperature further stabilizes it with respect to the known α-B6O structure. β-B6O also has a slightly higher hardness and may be synthesized using different experimental protocols. We suggest that β-B6O is present in mixture with α-B6O, and its presence accounts for previously unexplained bands in the experimental Raman spectrum. PMID:27498718

  10. Predictions of Actinide Solubilities under Near-Field Conditions Expected in the WIPP

    NASA Astrophysics Data System (ADS)

    Brush, L. H.; Xiong, Y.

    2009-12-01

    The Waste Isolation Pilot Plant (WIPP) is a U.S. Department of Energy (DOE) repository in southeast New Mexico for defense-related transuranic (TRU) waste. The repository, which opened in March 1999, is located at a subsurface depth of 655 m (2150 ft) in the Salado Fm., a Permian bedded-salt formation. The repository will eventually contain the equivalent of 844,000 208 L (55 gal) drums of TRU waste. After filling the rooms and access drifts and installing panel closures, creep closure of the salt will crush the steel waste containers in most cases and encapsulate the waste. The WIPP actinide source term model used for long-term performance assessment (PA) of the repository comprises dissolved and suspended submodels (solubilities and colloids). This presentation will describe the solubilities. From the standpoint of long-term PA, the order of importance of the radioelements in the TRU waste to be emplaced in the WIPP is Pu ~ Am >> U > Th >> Np ~ Cm and fission products. The DOE has included all of these actinides, but not fission products, in the WIPP Actinide Source Term Program (ASTP). Anoxic corrosion of Fe- and Al-base metals and microbial consumption of cellulosic, plastic, and rubber materials will produce gas and create strongly reducing conditions in the WIPP after closure. The use of MgO as an engineered barrier to consume microbially produced CO2 will result in low fCO2 and basic pH. Under these conditions, Th, U, Np, Pu, and Am will speciate essentially entirely as Th(IV), U(IV), Np(IV), Pu(III), and Am(III); or Th(IV), U(VI), Np(V), Pu(IV), and Am(III). The DOE has developed thermodynamic speciation-and-solubility models for +III, +IV, and +V actinides in brines. Experimental data for Nd, Am, and Cm species were used to parameterize the +III Pitzer activity-coefficient model; data for Th species were used for the +IV model; and data for Np(V) species were used for the +V model. These models include the effects of the organic ligands acetate, citrate

  11. Prediction of modeled velopharyngeal orifice areas during steady flow conditions and during aerodynamic simulation of voiceless stop consonants.

    PubMed

    Smith, B E; Weinberg, B

    1982-07-01

    Results of a small number of studies (Warren and DuBois, 1964; Lubker, 1969; Smith and Weinberg, 1980; Horii and Lang, 1981) have led to expression of divergent views concerning the accuracy of modeled velopharyngeal orifice area estimates obtained on the basis of hydrokinetic principles. In this work, the hydrokinetic equation (Warren and DuBois, 1964) was subjected to experimentation: (1) in which flow rates through a vocal tract model were not varied and (2) in which flow rates were varied to simulate pressure/flow events found during voiceless, stop consonant production. With consideration given to instrumental and procedural factors, results indicated that accurate estimates of modeled velopharyngeal orifice areas can be obtained during steady flow conditions and during alternating flow conditions when measurements are made at airflow peaks. Results were interpreted to provide strong support for clinical and research use of the hydrokinetic equation to predict velopharyngeal orifice areas during stop consonant production.

  12. Prediction of modeled velopharyngeal orifice areas during steady flow conditions and during aerodynamic simulation of voiceless stop consonants.

    PubMed

    Smith, B E; Weinberg, B

    1982-07-01

    Results of a small number of studies (Warren and DuBois, 1964; Lubker, 1969; Smith and Weinberg, 1980; Horii and Lang, 1981) have led to expression of divergent views concerning the accuracy of modeled velopharyngeal orifice area estimates obtained on the basis of hydrokinetic principles. In this work, the hydrokinetic equation (Warren and DuBois, 1964) was subjected to experimentation: (1) in which flow rates through a vocal tract model were not varied and (2) in which flow rates were varied to simulate pressure/flow events found during voiceless, stop consonant production. With consideration given to instrumental and procedural factors, results indicated that accurate estimates of modeled velopharyngeal orifice areas can be obtained during steady flow conditions and during alternating flow conditions when measurements are made at airflow peaks. Results were interpreted to provide strong support for clinical and research use of the hydrokinetic equation to predict velopharyngeal orifice areas during stop consonant production. PMID:6956460

  13. Effects of the inlet conditions and blood models on accurate prediction of hemodynamics in the stented coronary arteries

    NASA Astrophysics Data System (ADS)

    Jiang, Yongfei; Zhang, Jun; Zhao, Wanhua

    2015-05-01

    Hemodynamics altered by stent implantation is well-known to be closely related to in-stent restenosis. Computational fluid dynamics (CFD) method has been used to investigate the hemodynamics in stented arteries in detail and help to analyze the performances of stents. In this study, blood models with Newtonian or non-Newtonian properties were numerically investigated for the hemodynamics at steady or pulsatile inlet conditions respectively employing CFD based on the finite volume method. The results showed that the blood model with non-Newtonian property decreased the area of low wall shear stress (WSS) compared with the blood model with Newtonian property and the magnitude of WSS varied with the magnitude and waveform of the inlet velocity. The study indicates that the inlet conditions and blood models are all important for accurately predicting the hemodynamics. This will be beneficial to estimate the performances of stents and also help clinicians to select the proper stents for the patients.

  14. A predictive model of muscle excitations based on muscle modularity for a large repertoire of human locomotion conditions

    PubMed Central

    Gonzalez-Vargas, Jose; Sartori, Massimo; Dosen, Strahinja; Torricelli, Diego; Pons, Jose L.; Farina, Dario

    2015-01-01

    Humans can efficiently walk across a large variety of terrains and locomotion conditions with little or no mental effort. It has been hypothesized that the nervous system simplifies neuromuscular control by using muscle synergies, thus organizing multi-muscle activity into a small number of coordinative co-activation modules. In the present study we investigated how muscle modularity is structured across a large repertoire of locomotion conditions including five different speeds and five different ground elevations. For this we have used the non-negative matrix factorization technique in order to explain EMG experimental data with a low-dimensional set of four motor components. In this context each motor components is composed of a non-negative factor and the associated muscle weightings. Furthermore, we have investigated if the proposed descriptive analysis of muscle modularity could be translated into a predictive model that could: (1) Estimate how motor components modulate across locomotion speeds and ground elevations. This implies not only estimating the non-negative factors temporal characteristics, but also the associated muscle weighting variations. (2) Estimate how the resulting muscle excitations modulate across novel locomotion conditions and subjects. The results showed three major distinctive features of muscle modularity: (1) the number of motor components was preserved across all locomotion conditions, (2) the non-negative factors were consistent in shape and timing across all locomotion conditions, and (3) the muscle weightings were modulated as distinctive functions of locomotion speed and ground elevation. Results also showed that the developed predictive model was able to reproduce well the muscle modularity of un-modeled data, i.e., novel subjects and conditions. Muscle weightings were reconstructed with a cross-correlation factor greater than 70% and a root mean square error less than 0.10. Furthermore, the generated muscle excitations matched

  15. Environmental conditions predict helminth prevalence in red foxes in Western Australia.

    PubMed

    Dybing, Narelle A; Fleming, Patricia A; Adams, Peter J

    2013-12-01

    Red foxes (Vulpes vulpes) are the most common and widely distributed wild carnivore worldwide. These predators harbour a wide range of parasites, many of which may have important conservation, agricultural and zoonotic repercussions. This project investigated the occurrence of helminth parasites from the intestines of 147 red foxes across 14 sampling localities of southwest Western Australia. Helminth parasites were detected in 58% of fox intestines: Dipylidium caninum (27.7% of foxes), Uncinaria stenocephala (18.2%), Toxocara canis (14.9%), Spirometra erinaceieuropaei (5.4%), Toxascaris leonina (4.7%), Taenia serialis (1.4%), Taenia hydatigena (0.7%), unidentified Taenia spp. (4.1%), Brachylaima cribbi (0.7%), Plagiorchis maculosus (0.7%) and an Acanthocephalan; family Centrorhynchidae (2.1%). Importantly, two cestodes of agricultural significance, Echinococcus granulosus and Taenia ovis, were not detected in red foxes in this study, despite the presence of suitable intermediate hosts in the diets of these animals. Parasite richness varied from 1-3 species per host, with average parasite number varying from 1-39 worms (across all helminth species). Regression analyses indicated that the presence of four helminth parasites was related to various environmental factors. The presence of S. erinaceieuropaei (p < 0.001), T. leonina (p < 0.01) and U. stenocephala (p < 0.01) was positively associated with average relative humidity which may affect the longevity of infective stages in the environment. The presence of S. erinaceieuropaei and U. stenocephala (p < 0.001) was positively associated with 5-y-average minimum temperature which could reflect poor survival of infective stages through cold winter conditions. The presence of T. canis and U. stenocephala (p < 0.001) was positively associated with the percentage cover of native vegetation at each sampling location, which is likely to reflect transmission from native prey species acting as paratenic hosts

  16. Environmental conditions predict helminth prevalence in red foxes in Western Australia☆

    PubMed Central

    Dybing, Narelle A.; Fleming, Patricia A.; Adams, Peter J.

    2013-01-01

    Red foxes (Vulpes vulpes) are the most common and widely distributed wild carnivore worldwide. These predators harbour a wide range of parasites, many of which may have important conservation, agricultural and zoonotic repercussions. This project investigated the occurrence of helminth parasites from the intestines of 147 red foxes across 14 sampling localities of southwest Western Australia. Helminth parasites were detected in 58% of fox intestines: Dipylidium caninum (27.7% of foxes), Uncinaria stenocephala (18.2%), Toxocara canis (14.9%), Spirometra erinaceieuropaei (5.4%), Toxascaris leonina (4.7%), Taenia serialis (1.4%), Taenia hydatigena (0.7%), unidentified Taenia spp. (4.1%), Brachylaima cribbi (0.7%), Plagiorchis maculosus (0.7%) and an Acanthocephalan; family Centrorhynchidae (2.1%). Importantly, two cestodes of agricultural significance, Echinococcus granulosus and Taenia ovis, were not detected in red foxes in this study, despite the presence of suitable intermediate hosts in the diets of these animals. Parasite richness varied from 1–3 species per host, with average parasite number varying from 1–39 worms (across all helminth species). Regression analyses indicated that the presence of four helminth parasites was related to various environmental factors. The presence of S. erinaceieuropaei (p < 0.001), T. leonina (p < 0.01) and U. stenocephala (p < 0.01) was positively associated with average relative humidity which may affect the longevity of infective stages in the environment. The presence of S. erinaceieuropaei and U. stenocephala (p < 0.001) was positively associated with 5-y-average minimum temperature which could reflect poor survival of infective stages through cold winter conditions. The presence of T. canis and U. stenocephala (p < 0.001) was positively associated with the percentage cover of native vegetation at each sampling location, which is likely to reflect transmission from native prey species acting as paratenic hosts

  17. Interval arithmetic operations for uncertainty analysis with correlated interval variables

    NASA Astrophysics Data System (ADS)

    Jiang, Chao; Fu, Chun-Ming; Ni, Bing-Yu; Han, Xu

    2016-08-01

    A new interval arithmetic method is proposed to solve interval functions with correlated intervals through which the overestimation problem existing in interval analysis could be significantly alleviated. The correlation between interval parameters is defined by the multidimensional parallelepiped model which is convenient to describe the correlative and independent interval variables in a unified framework. The original interval variables with correlation are transformed into the standard space without correlation, and then the relationship between the original variables and the standard interval variables is obtained. The expressions of four basic interval arithmetic operations, namely addition, subtraction, multiplication, and division, are given in the standard space. Finally, several numerical examples and a two-step bar are used to demonstrate the effectiveness of the proposed method.

  18. Sensory prediction or motor control? Application of marr-albus type models of cerebellar function to classical conditioning.

    PubMed

    Lepora, Nathan F; Porrill, John; Yeo, Christopher H; Dean, Paul

    2010-01-01

    Marr-Albus adaptive filter models of the cerebellum have been applied successfully to a range of sensory and motor control problems. Here we analyze their properties when applied to classical conditioning of the nictitating membrane response in rabbits. We consider a system-level model of eyeblink conditioning based on the anatomy of the eyeblink circuitry, comprising an adaptive filter model of the cerebellum, a comparator model of the inferior olive and a linear dynamic model of the nictitating membrane plant. To our knowledge, this is the first model that explicitly includes all these principal components, in particular the motor plant that is vital for shaping and timing the behavioral response. Model assumptions and parameters were systematically investigated to disambiguate basic computational capacities of the model from features requiring tuning of properties and parameter values. Without such tuning, the model robustly reproduced a range of behaviors related to sensory prediction, by displaying appropriate trial-level associative learning effects for both single and multiple stimuli, including blocking and conditioned inhibition. In contrast, successful reproduction of the real-time motor behavior depended on appropriate specification of the plant, cerebellum and comparator models. Although some of these properties appear consistent with the system biology, fundamental questions remain about how the biological parameters are chosen if the cerebellar microcircuit applies a common computation to many distinct behavioral tasks. It is possible that the response profiles in classical conditioning of the eyeblink depend upon operant contingencies that have previously prevailed, for example in naturally occurring avoidance movements.

  19. Multichannel interval timer (MINT)

    SciTech Connect

    Kimball, K.B.

    1982-06-01

    A prototype Multichannel INterval Timer (MINT) has been built for measuring signal Time of Arrival (TOA) from sensors placed in blast environments. The MINT is intended to reduce the space, equipment costs, and data reduction efforts associated with traditional analog TOA recording methods, making it more practical to field the large arrays of TOA sensors required to characterize blast environments. This document describes the MINT design features, provides the information required for installing and operating the system, and presents proposed improvements for the next generation system.

  20. Long Range River Discharge Forecasting Using the Gravity Recovery and Climate Experiment (GRACE) Satellite to Predict Conditions for Endemic Cholera

    NASA Astrophysics Data System (ADS)

    Jutla, A.; Akanda, A. S.; Colwell, R. R.

    2014-12-01

    Prediction of conditions of an impending disease outbreak remains a challenge but is achievable if the associated and appropriate large scale hydroclimatic process can be estimated in advance. Outbreaks of diarrheal diseases such as cholera, are related to episodic seasonal variability in river discharge in the regions where water and sanitation infrastructure are inadequate and insufficient. However, forecasting river discharge, few months in advance, remains elusive where cholera outbreaks are frequent, probably due to non-availability of geophysical data as well as transboundary water stresses. Here, we show that satellite derived water storage from Gravity Recovery and Climate Experiment Forecasting (GRACE) sensors can provide reliable estimates on river discharge atleast two months in advance over regional scales. Bayesian regression models predicted flooding and drought conditions, a prerequisite for cholera outbreaks, in Bengal Delta with an overall accuracy of 70% for upto 60 days in advance without using any other ancillary ground based data. Forecasting of river discharge will have significant impacts on planning and designing intervention strategies for potential cholera outbreaks in the coastal regions where the disease remain endemic and often fatal.

  1. Predicting Plant Performance Under Simultaneously Changing Environmental Conditions-The Interplay Between Temperature, Light, and Internode Growth.

    PubMed

    Kahlen, Katrin; Chen, Tsu-Wei

    2015-01-01

    Plant performance is significantly influenced by prevailing light and temperature conditions during plant growth and development. For plants exposed to natural fluctuations in abiotic environmental conditions it is however laborious and cumbersome to experimentally assign any contribution of individual environmental factors to plant responses. This study aimed at analyzing the interplay between light, temperature and internode growth based on model approaches. We extended the light-sensitive virtual plant model L-Cucumber by implementing a common Arrhenius function for appearance rates, growth rates, and growth durations. For two greenhouse experiments, the temperature-sensitive model approach resulted in a precise prediction of cucumber mean internode lengths and number of internodes, as well as in accurately predicted patterns of individual internode lengths along the main stem. In addition, a system's analysis revealed that environmental data averaged over the experimental period were not necessarily related to internode performance. Finally, the need for a species-specific parameterization of the temperature response function and related aspects in modeling temperature effects on plant development and growth is discussed.

  2. Work conditions and employees' self-set goals: goal processes enhance prediction of psychological distress and well-being.

    PubMed

    Pomaki, Georgia; Maes, Stan; Ter Doest, Laura

    2004-06-01

    Although previous theory and research suggest that employee well-being should be predicted by work conditions (viz., Karasek and colleagues' job demands-control-social support [J-DCS] model), other factors are also likely to be important. In this study, the authors consider correlates of employee psychological distress and well-being using a goal-focused approach grounded in Ford's (1992) motivational systems theory. Specifically, work conditions and midlevel work goal processes (WGP) were examined in a questionnaire study of health care employees. Regarding predictions derived from the J-DCS model, the authors found full support for the iso-strain, partial support for the nonlinearity, and no support for the buffer hypothesis. Of importance, however, WGP (i.e., cognitions and emotions involved in the pursuit of self-set work goals) explained variance in job satisfaction, burnout, depression, and somatic complaints, over and above that of the J-DCS model. This suggests that investigation of WGP can enhance our understanding of employee psychological distress and well-being.

  3. Time-domain inflow boundary condition for turbulence-airfoil interaction noise prediction using synthetic turbulence modeling

    NASA Astrophysics Data System (ADS)

    Kim, Daehwan; Heo, Seung; Cheong, Cheolung

    2015-03-01

    The present paper deals with development of the synthetic turbulence inflow boundary condition (STIBC) to predict inflow broadband noise generated by interaction between turbulence and an airfoil/a cascade of airfoils in the time-domain. The STIBC is derived by combining inflow boundary conditions that have been successfully applied in external and internal computational aeroacoustics (CAA) simulations with a synthetic turbulence model. The random particle mesh (RPM) method based on a digital filter is used as the synthetic turbulence model. Gaussian and Liepmann spectra are used to define the filters for turbulence energy spectra. The linearized Euler equations are used as governing equations to evaluate the suitability of the STIBC in time-domain CAA simulations. First, the velocity correlations and energy spectra of the synthesized turbulent velocities are compared with analytic ones. The comparison results reveal that the STIBC can reproduce a turbulent velocity field satisfying the required statistical characteristics of turbulence. Particularly, the Liepmann filter representing a non-Gaussian filter is shown to be effectively described by superposing the Gaussian filters. Each Gaussian filter has a different turbulent kinetic energy and integral length scale. Second, two inflow noise problems are numerically solved using the STIBC: the turbulence-airfoil interaction and the turbulence-a cascade of airfoils interaction problems. The power spectrum of noise due to an isolated flat plate airfoil interacting with incident turbulence is predicted, and its result is successfully validated against Amiet's analytic model (Amiet, 1975) [4]. The prediction results of the upstream and downstream acoustic power spectra from a cascade of flat plates are then compared with Cheong's analytic model (Cheong et al., 2006) [30]. These comparisons are also in excellent agreement. On the basis of these illustrative computation results, the STIBC is expected to be applied to

  4. Prediction of high spatio-temporal resolution land surface temperature under cloudy conditions using microwave vegetation index and ANN

    NASA Astrophysics Data System (ADS)

    Shwetha, H. R.; Kumar, D. Nagesh

    2016-07-01

    Land Surface Temperature (LST) with high spatio-temporal resolution is in demand for hydrology, climate change, ecology, urban climate and environmental studies, etc. Moderate Resolution Imaging Spectroradiometer (MODIS) is one of the most commonly used sensors owing to its high spatial and temporal availability over the globe, but is incapable of providing LST data under cloudy conditions, resulting in gaps in the data. In contrast, microwave measurements have a capability to penetrate under clouds. The current study proposes a methodology by exploring this property to predict high spatio-temporal resolution LST under cloudy conditions during daytime and nighttime without employing in-situ LST measurements. To achieve this, Artificial Neural Networks (ANNs) based models are employed for different land cover classes, utilizing Microwave Polarization Difference Index (MPDI) at finer resolution with ancillary data. MPDI was derived using resampled (from 0.25° to 1 km) brightness temperatures (Tb) at 36.5 GHz channel of dual polarization from Advance Microwave Scanning Radiometer (AMSR)-Earth Observing System and AMSR2 sensors. The proposed methodology is tested over Cauvery basin in India and the performance of the model is quantitatively evaluated through performance measures such as correlation coefficient (r), Nash Sutcliffe Efficiency (NSE) and Root Mean Square Error (RMSE). Results revealed that during daytime, AMSR-E(AMSR2) derived LST under clear sky conditions corresponds well with MODIS LST resulting in values of r ranging from 0.76(0.78) to 0.90(0.96), RMSE from 1.76(1.86) K to 4.34(4.00) K and NSE from 0.58(0.61) to 0.81(0.90) for different land cover classes. During nighttime, r values ranged from 0.76(0.56) to 0.87(0.90), RMSE from 1.71(1.70) K to 2.43(2.12) K and NSE from 0.43(0.28) to 0.80(0.81) for different land cover classes. RMSE values found between predicted LST and MODIS LST during daytime under clear sky conditions were within acceptable

  5. Sequential Processing and the Matching-Stimulus Interval Effect in ERP Components: An Exploration of the Mechanism Using Multiple Regression

    PubMed Central

    Steiner, Genevieve Z.; Barry, Robert J.; Gonsalvez, Craig J.

    2016-01-01

    In oddball tasks, increasing the time between stimuli within a particular condition (target-to-target interval, TTI; nontarget-to-nontarget interval, NNI) systematically enhances N1, P2, and P300 event-related potential (ERP) component amplitudes. This study examined the mechanism underpinning these effects in ERP components recorded from 28 adults who completed a conventional three-tone oddball task. Bivariate correlations, partial correlations and multiple regression explored component changes due to preceding ERP component amplitudes and intervals found within the stimulus series, rather than constraining the task with experimentally constructed intervals, which has been adequately explored in prior studies. Multiple regression showed that for targets, N1 and TTI predicted N2, TTI predicted P3a and P3b, and Processing Negativity (PN), P3b, and TTI predicted reaction time. For rare nontargets, P1 predicted N1, NNI predicted N2, and N1 predicted Slow Wave (SW). Findings show that the mechanism is operating on separate stages of stimulus-processing, suggestive of either increased activation within a number of stimulus-specific pathways, or very long component generator recovery cycles. These results demonstrate the extent to which matching-stimulus intervals influence ERP component amplitudes and behavior in a three-tone oddball task, and should be taken into account when designing similar studies. PMID:27445774

  6. Confidence intervals in Flow Forecasting by using artificial neural networks

    NASA Astrophysics Data System (ADS)

    Panagoulia, Dionysia; Tsekouras, George

    2014-05-01

    One of the major inadequacies in implementation of Artificial Neural Networks (ANNs) for flow forecasting is the development of confidence intervals, because the relevant estimation cannot be implemented directly, contrasted to the classical forecasting methods. The variation in the ANN output is a measure of uncertainty in the model predictions based on the training data set. Different methods for uncertainty analysis, such as bootstrap, Bayesian, Monte Carlo, have already proposed for hydrologic and geophysical models, while methods for confidence intervals, such as error output, re-sampling, multi-linear regression adapted to ANN have been used for power load forecasting [1-2]. The aim of this paper is to present the re-sampling method for ANN prediction models and to develop this for flow forecasting of the next day. The re-sampling method is based on the ascending sorting of the errors between real and predicted values for all input vectors. The cumulative sample distribution function of the prediction errors is calculated and the confidence intervals are estimated by keeping the intermediate value, rejecting the extreme values according to the desired confidence levels, and holding the intervals symmetrical in probability. For application of the confidence intervals issue, input vectors are used from the Mesochora catchment in western-central Greece. The ANN's training algorithm is the stochastic training back-propagation process with decreasing functions of learning rate and momentum term, for which an optimization process is conducted regarding the crucial parameters values, such as the number of neurons, the kind of activation functions, the initial values and time parameters of learning rate and momentum term etc. Input variables are historical data of previous days, such as flows, nonlinearly weather related temperatures and nonlinearly weather related rainfalls based on correlation analysis between the under prediction flow and each implicit input

  7. Computational prediction of the refinement of oxide agglomerates in a physical conditioning process for molten aluminium alloy

    NASA Astrophysics Data System (ADS)

    Tong, M.; Jagarlapudi, S. C.; Patel, J. B.; Stone, I. C.; Fan, Z.; Browne, D. J.

    2015-06-01

    Physically conditioning molten scrap aluminium alloys using high shear processing (HSP) was recently found to be a promising technology for purification of contaminated alloys. HSP refines the solid oxide agglomerates in molten alloys, so that they can act as sites for the nucleation of Fe-rich intermetallic phases which can subsequently be removed by the downstream de-drossing process. In this paper, a computational modelling for predicting the evolution of size of oxide clusters during HSP is presented. We used CFD to predict the macroscopic flow features of the melt, and the resultant field predictions of temperature and melt shear rate were transferred to a population balance model (PBM) as its key inputs. The PBM is a macroscopic model that formulates the microscopic agglomeration and breakage of a population of a dispersed phase. Although it has been widely used to study conventional deoxidation of liquid metal, this is the first time that PBM has been used to simulate the melt conditioning process within a rotor/stator HSP device. We employed a method which discretizes the continuous profile of size of the dispersed phase into a collection of discrete bins of size, to solve the governing population balance equation for the size of agglomerates. A finite volume method was used to solve the continuity equation, the energy equation and the momentum equation. The overall computation was implemented mainly using the FLUENT module of ANSYS. The simulations showed that there is a relatively high melt shear rate between the stator and sweeping tips of the rotor blades. This high shear rate leads directly to significant fragmentation of the initially large oxide aggregates. Because the process of agglomeration is significantly slower than the breakage processes at the beginning of HSP, the mean size of oxide clusters decreases very rapidly. As the process of agglomeration gradually balances the process of breakage, the mean size of oxide clusters converges to a

  8. Feedback precision and postfeedback interval duration

    NASA Technical Reports Server (NTRS)

    Rogers, C. A., Jr.

    1974-01-01

    Precision of feedback gain was manipulated in a simple positioning task. An optimum was found; an increase in precision past that optimum produced deleterious effects upon rate of acquisition. In a second study, increasing postfeedback interval removed that optimum. The feedback precision effects were then replicated in a timing task. The combined results of the 3 studies were interpreted as supportive of an information-processing approach to the study of postfeedback interval events for simple motor skills. The findings additionally supported specific predictions by Bilodeau and deductions from Adams' 1971 theory of motor learning.

  9. [Development of a computer program to simulate the predictions of the replaced elements model of Pavlovian conditioning].

    PubMed

    Vogel, Edgar H; Díaz, Claudia A; Ramírez, Jorge A; Jarur, Mary C; Pérez-Acosta, Andrés M; Wagner, Allan R

    2007-08-01

    Despite of the apparent simplicity of Pavlovian conditioning, research on its mechanisms has caused considerable debate, such as the dispute about whether the associated stimuli are coded in an "elementistic"(a compound stimuli is equivalent to the sum of its components) or a "configural" (a compound stimuli is a unique exemplar) fashion. This controversy is evident in the abundant research on the contrasting predictions of elementistic and the configural models. Recently, some mixed solutions have been proposed, which, although they have the advantages of both approaches, are difficult to evaluate due to their complexity. This paper presents a computer program to conduct simulations of a mixed model ( replaced elements model or REM). Instructions and examples are provided to use the simulator for research and educational purposes.

  10. Comparison of Damage Models for Predicting the Non-Linear Response of Laminates Under Matrix Dominated Loading Conditions

    NASA Technical Reports Server (NTRS)

    Schuecker, Clara; Davila, Carlos G.; Rose, Cheryl A.

    2010-01-01

    Five models for matrix damage in fiber reinforced laminates are evaluated for matrix-dominated loading conditions under plane stress and are compared both qualitatively and quantitatively. The emphasis of this study is on a comparison of the response of embedded plies subjected to a homogeneous stress state. Three of the models are specifically designed for modeling the non-linear response due to distributed matrix cracking under homogeneous loading, and also account for non-linear (shear) behavior prior to the onset of cracking. The remaining two models are localized damage models intended for predicting local failure at stress concentrations. The modeling approaches of distributed vs. localized cracking as well as the different formulations of damage initiation and damage progression are compared and discussed.

  11. Prediction of performance of two-phase flow nozzle and liquid metal magnetohydrodynamic (LMMHD) generator for no slip condition

    NASA Technical Reports Server (NTRS)

    Fabris, G.; Back, L.

    1992-01-01

    Two-phase LMMHD energy conversion systems have potentially significant advantages over conventional systems such as higher thermal efficiency and substantial simplicity with lower capital and maintenance costs. Maintenance of low velocity slip is of importance for achieving high generator efficiency. A bubbly flow pattern ensures very low velocity slip. The full governing equations have been written out, and a computer prediction code has been developed to analyze performance of a two-phase flow LMMHD generator and nozzle under conditions of no slip. Three different shapes of a LMMHD generator have been investigated. Electrical power outputs are in the 20 kW range. Generator efficiency exceeds 71 percent at an average void fraction of about 70 percent. This is an appreciable performance for a short generator without insulating vanes for minimizing electrical losses in the end regions.

  12. Ground-water conditions in Salt Lake Valley, Utah, 1969-83, and predicted effects of increased withdrawals from wells

    USGS Publications Warehouse

    Waddell, K.M.; Seiler, R.L.; Santini, Melissa; Solomon, D.K.

    1987-01-01

    This report was prepared in cooperation with several organizations in the Salt Lake Valley and with the Central Utah Water Conservancy District to present results of a study to determine changes in the ground-water conditions in Salt Lake Valley, Utah, from 1969 to 1983, and to predict the aquifer response to projected withdrawals. The average annual recharge and discharge from the ground-water reservoir in Salt Lake Valley, Utah, during 1969-82 were estimated to be about 352,000 and 353,000 acre-feet per year. Withdrawals from wells increased from 107,000 acre-feet per year during 1964-68 to 117,000 acre-feet per year during 1969-82. The greatest increase in use was for public supply and institutions which increased from 35,000 acre-feet per year during 1964-68 to 46,700 acre-feet per year during 1969-82.

  13. A testable prediction of the no-signalling condition using a variant of the EPR-Bohm example

    NASA Astrophysics Data System (ADS)

    Home, Dipankar; Rai, Ashutosh; Majumdar, A. S.

    2013-02-01

    Predictive power of the no-signalling condition (NSC) is demonstrated in a testable situation involving a non-ideal Stern-Gerlach (SG) device in one of the two wings of the EPR-Bohm entangled pairs. In this wing, for two types of measurement in the other wing, we consider the spin state of a selected set of particles that are confined to a particular half of the plane while emerging from the SG magnetic field region. Due to non-idealness of the SG setup, this spin state will have superposing components involving a relative phase for which a testable quantitative constraint is obtained by invoking NSC, thereby providing a means for precision testing of this fundamentally significant principle.

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

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

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

  15. Early donor chimerism levels predict relapse and survival after allogeneic stem-cell transplantation with reduced intensity conditioning

    PubMed Central

    Reshef, Ran; Hexner, Elizabeth O.; Loren, Alison W.; Frey, Noelle V.; Stadtmauer, Edward A.; Luger, Selina M.; Mangan, James K.; Gill, Saar I.; Vassilev, Pavel; Lafferty, Kathryn A.; Smith, Jacqueline; Van Deerlin, Vivianna M.; Mick, Rosemarie; Porter, David L.

    2014-01-01

    The success of hematopoietic stem-cell transplantation (HSCT) with reduced-intensity conditioning (RIC) is limited by a high rate of disease relapse. Early risk assessment could potentially improve outcomes by identifying appropriate patients for pre-emptive strategies that may ameliorate this high risk. Using a series of landmark analyses, we investigated the predictive value of early (day-30) donor chimerism measurements on disease relapse, graft-versus-host disease and survival in a cohort of 121 patients who were allografted with a uniform RIC regimen. Chimerism levels were analyzed as continuous variables. In multivariate analysis, day-30 whole blood chimerism levels were significantly associated with relapse (HR=0.90, p<0.001), relapse-free survival (HR=0.89, p<0.001) and overall survival (HR=0.94, p=0.01). Day-30 T-cell chimerism levels were also significantly associated with relapse (HR=0.97, p=0.002), relapse-free survival (HR=0.97, p<0.001) and overall survival (HR=0.99, p=0.05). Multivariate models that included T-cell chimerism provided a better prediction for these outcomes compared to whole blood chimerism. Day-30 chimerism levels were not associated with acute or chronic graft-versus-host disease. We found that high donor chimerism levels were significantly associated with a low lymphocyte count in the recipient prior to transplant, highlighting the impact of pre-transplant lymphopenia on the kinetics of engraftment after RIC HSCT. In summary, low donor chimerism levels are associated with relapse and mortality and can potentially be used as an early predictive and prognostic marker. These findings can be used to design novel approaches to prevent relapse and to improve survival after RIC HSCT. PMID:25016197

  16. Prediction of Low-Voltage Tetrafluoromethane Emissions Based on the Operating Conditions of an Aluminium Electrolysis Cell

    NASA Astrophysics Data System (ADS)

    Dion, Lukas; Kiss, László I.; Poncsák, Sándor; Lagacé, Charles-Luc

    2016-08-01

    Greenhouse gas (GHG) generation is inherent in the production of aluminium by a technology that uses carbon anodes. Most of those GHG are composed of CO2 produced by redox reaction that occurs in the cell. However, a significant fraction of the annual GHG production is composed of perfluorocarbons (PFC) resulting from anode effects (AE). Multiple investigations have shown that tetrafluoromethane (CF4) can be generated under low-voltage conditions in the electrolysis cells, without global anode effect. The aim of this paper is to find a quantitative relationship between monitored cell parameters and the emissions of CF4. To achieve this goal, a predictive algorithm has been developed using seven cell indicators. These indicators are based on the cell voltage, the noise level and other parameters calculated from individual anode current monitoring. The predictive algorithm is structured into three different steps. The first two steps give qualitative information while the third one quantitatively describes the expected CF4 concentration at the duct end of the electrolysis cells. Validations after each step are presented and discussed. Finally, a sensitivity analysis was performed to understand the effect of each indicator on the onset of low-voltage PFC emissions. The standard deviation of individual anode currents was found to be the dominant variable. Cell voltage, noise level, and maximum individual anode current also showed a significant correlation with the presence of CF4 in the output gas of an electrolysis cell.

  17. Prediction of matching condition for a microstrip subsystem using artificial neural network and adaptive neuro-fuzzy inference system

    NASA Astrophysics Data System (ADS)

    Salehi, Mohammad Reza; Noori, Leila; Abiri, Ebrahim

    2016-11-01

    In this paper, a subsystem consisting of a microstrip bandpass filter and a microstrip low noise amplifier (LNA) is designed for WLAN applications. The proposed filter has a small implementation area (49 mm2), small insertion loss (0.08 dB) and wide fractional bandwidth (FBW) (61%). To design the proposed LNA, the compact microstrip cells, an field effect transistor, and only a lumped capacitor are used. It has a low supply voltage and a low return loss (-40 dB) at the operation frequency. The matching condition of the proposed subsystem is predicted using subsystem analysis, artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS). To design the proposed filter, the transmission matrix of the proposed resonator is obtained and analysed. The performance of the proposed ANN and ANFIS models is tested using the numerical data by four performance measures, namely the correlation coefficient (CC), the mean absolute error (MAE), the average percentage error (APE) and the root mean square error (RMSE). The obtained results show that these models are in good agreement with the numerical data, and a small error between the predicted values and numerical solution is obtained.

  18. Prediction of Low-Voltage Tetrafluoromethane Emissions Based on the Operating Conditions of an Aluminium Electrolysis Cell

    NASA Astrophysics Data System (ADS)

    Dion, Lukas; Kiss, László I.; Poncsák, Sándor; Lagacé, Charles-Luc

    2016-09-01

    Greenhouse gas (GHG) generation is inherent in the production of aluminium by a technology that uses carbon anodes. Most of those GHG are composed of CO2 produced by redox reaction that occurs in the cell. However, a significant fraction of the annual GHG production is composed of perfluorocarbons (PFC) resulting from anode effects (AE). Multiple investigations have shown that tetrafluoromethane (CF4) can be generated under low-voltage conditions in the electrolysis cells, without global anode effect. The aim of this paper is to find a quantitative relationship between monitored cell parameters and the emissions of CF4. To achieve this goal, a predictive algorithm has been developed using seven cell indicators. These indicators are based on the cell voltage, the noise level and other parameters calculated from individual anode current monitoring. The predictive algorithm is structured into three different steps. The first two steps give qualitative information while the third one quantitatively describes the expected CF4 concentration at the duct end of the electrolysis cells. Validations after each step are presented and discussed. Finally, a sensitivity analysis was performed to understand the effect of each indicator on the onset of low-voltage PFC emissions. The standard deviation of individual anode currents was found to be the dominant variable. Cell voltage, noise level, and maximum individual anode current also showed a significant correlation with the presence of CF4 in the output gas of an electrolysis cell.

  19. Prediction of Bubble Diameter at Detachment from a Wall Orifice in Liquid Cross Flow Under Reduced and Normal Gravity Conditions

    NASA Technical Reports Server (NTRS)

    Nahra, Henry K.; Kamotani, Y.

    2003-01-01

    Bubble formation and detachment is an integral part of the two-phase flow science. The objective of the present work is to theoretically investigate the effects of liquid cross-flow velocity, gas flow rate embodied in the momentum flux force, and orifice diameter on bubble formation in a wall-bubble injection configuration. A two-dimensional one-stage theoretical model based on a global force balance on the bubble evolving from a wall orifice in a cross liquid flow is presented in this work. In this model, relevant forces acting on the evolving bubble are expressed in terms of the bubble center of mass coordinates and solved simultaneously. Relevant forces in low gravity included the momentum flux, shear-lift, surface tension, drag and inertia forces. Under normal gravity conditions, the buoyancy force, which is dominant under such conditions, can be added to the force balance. Two detachment criteria were applicable depending on the gas to liquid momentum force ratio. For low ratios, the time when the bubble acceleration in the direction of the detachment angle is greater or equal to zero is calculated from the bubble x and y coordinates. This time is taken as the time at which all the detaching forces that are acting on the bubble are greater or equal to the attaching forces. For high gas to liquid momentum force ratios, the time at which the y coordinate less the bubble radius equals zero is calculated. The bubble diameter is evaluated at this time as the diameter at detachment from the fact that the bubble volume is simply given by the product of the gas flow rate and time elapsed. Comparison of the model s predictions was also made with predictions from a two-dimensional normal gravity model based on Kumar-Kuloor formulation and such a comparison is presented in this work.

  20. Contracting, equal, and expanding learning schedules: the optimal distribution of learning sessions depends on retention interval.

    PubMed

    Küpper-Tetzel, Carolina E; Kapler, Irina V; Wiseheart, Melody

    2014-07-01

    In laboratory and applied learning experiments, researchers have extensively investigated the optimal distribution of two learning sessions (i.e., initial learning and one relearning session) for the learning of verbatim materials. However, research has not yet provided a satisfying and conclusive answer to the optimal scheduling of three learning sessions (i.e., initial learning and two relearning sessions) across educationally relevant time intervals. Should the to-be-learned material be repeated at decreasing intervals (contracting schedule), constant intervals (equal schedule), or increasing intervals (expanding schedule) between learning sessions? Different theories and memory models (e.g., study-phase retrieval theory, contextual variability theory, ACT-R, and the Multiscale Context Model) make distinct predictions about the optimal learning schedule. We discuss the extant theories and derive clear predictions from each of them. To test these predictions empirically, we conducted an experiment in which participants studied and restudied paired associates with a contracting, equal, or expanding learning schedule. Memory performance was assessed immediately, 1 day, 7 days, or 35 days later with free- and cued-recall tests. Our results revealed that the optimal learning schedule is conditional on the length of the retention interval: A contracting learning schedule was beneficial for retention intervals up to 7 days, but both equal and expanding learning schedules were better for a long retention interval of 35 days. Our findings can be accommodated best by the contextual variability theory and indicate that revisions are needed to existing memory models. Our results are practically relevant, and their implications for real-world learning are discussed. PMID:24500777

  1. Contracting, equal, and expanding learning schedules: the optimal distribution of learning sessions depends on retention interval.

    PubMed

    Küpper-Tetzel, Carolina E; Kapler, Irina V; Wiseheart, Melody

    2014-07-01

    In laboratory and applied learning experiments, researchers have extensively investigated the optimal distribution of two learning sessions (i.e., initial learning and one relearning session) for the learning of verbatim materials. However, research has not yet provided a satisfying and conclusive answer to the optimal scheduling of three learning sessions (i.e., initial learning and two relearning sessions) across educationally relevant time intervals. Should the to-be-learned material be repeated at decreasing intervals (contracting schedule), constant intervals (equal schedule), or increasing intervals (expanding schedule) between learning sessions? Different theories and memory models (e.g., study-phase retrieval theory, contextual variability theory, ACT-R, and the Multiscale Context Model) make distinct predictions about the optimal learning schedule. We discuss the extant theories and derive clear predictions from each of them. To test these predictions empirically, we conducted an experiment in which participants studied and restudied paired associates with a contracting, equal, or expanding learning schedule. Memory performance was assessed immediately, 1 day, 7 days, or 35 days later with free- and cued-recall tests. Our results revealed that the optimal learning schedule is conditional on the length of the retention interval: A contracting learning schedule was beneficial for retention intervals up to 7 days, but both equal and expanding learning schedules were better for a long retention interval of 35 days. Our findings can be accommodated best by the contextual variability theory and indicate that revisions are needed to existing memory models. Our results are practically relevant, and their implications for real-world learning are discussed.

  2. Applicability of DLVO Approach to Predict Trends in Iron Oxide Colloid Mobility Under Various Physical And Chemical Soil Conditions

    NASA Astrophysics Data System (ADS)

    Florian Carstens, Jannis; Bachmann, Jörg; Neuweiler, Insa

    2014-05-01

    In soil and groundwater, highly mobile iron oxide colloids can act as "shuttles" for transport of adsorbed contaminants such as heavy metals and radionuclides. Artificial iron oxide colloids are injected into polluted porous media to accelerate bacterial degradation of pollutants in the context of bioremediation purposes. The mobility of iron oxide colloids is strongly affected by the hydraulic, physical and chemical conditions of the pore space, the solid particle surface properties, the fluid phase, and the colloids themselves. Most pioneering studies focused on iron oxide colloid transport and retention in simplified model systems. The aim of this study is to investigate iron oxide colloid mobility under more complex, soil-typical conditions that have as yet only been applied for model microspheres, i.e. functionalized latex colloids. Among these conditions is the pivotal impact of organic matter, either dissolved or adsorbed onto solid particles, modifying wettability properties. Of particular importance was to determine if effective chemical surface parameters derived from contact angle and zeta potential measurements can be used as a tool to predict general tendencies for iron oxide colloid mobility in porous media. In column breakthrough experiments, goethite colloids (particle size: 200-900 nm) were percolated through quartz sand (grain size: 100-300 µm) at pH 5. The impact of a multitude of conditions on colloid mobility was determined: dissolved organic matter (DOM) concentration, ionic strength, flow velocity, flow interruption, partial saturation, and drying with subsequent re-wetting. The solid matrix consisted of either clean sand, organic matter-coated sand, goethite-coated sand, or sand hydrophobized with dichlorodimethylsilane. Additionally, contact angles and zeta potentials of the materials applied in the column experiments were measured. By means of these surface parameters, traditional DLVO interaction energies based on zeta potential as well

  3. Identification, Expression Analysis, and Target Prediction of Flax Genotroph MicroRNAs Under Normal and Nutrient Stress Conditions.

    PubMed

    Melnikova, Nataliya V; Dmitriev, Alexey A; Belenikin, Maxim S; Koroban, Nadezhda V; Speranskaya, Anna S; Krinitsina, Anastasia A; Krasnov, George S; Lakunina, Valentina A; Snezhkina, Anastasiya V; Sadritdinova, Asiya F; Kishlyan, Natalya V; Rozhmina, Tatiana A; Klimina, Kseniya M; Amosova, Alexandra V; Zelenin, Alexander V; Muravenko, Olga V; Bolsheva, Nadezhda L; Kudryavtseva, Anna V

    2016-01-01

    Cultivated flax (Linum usitatissimum L.) is an important plant valuable for industry. Some flax lines can undergo heritable phenotypic and genotypic changes (LIS-1 insertion being the most common) in response to nutrient stress and are called plastic lines. Offspring of plastic lines, which stably inherit the changes, are called genotrophs. MicroRNAs (miRNAs) are involved in a crucial regulatory mechanism of gene expression. They have previously been assumed to take part in nutrient stress response and can, therefore, participate in genotroph formation. In the present study, we performed high-throughput sequencing of small RNAs (sRNAs) extracted from flax plants grown under normal, phosphate deficient and nutrient excess conditions to identify miRNAs and evaluate their expression. Our analysis revealed expression of 96 conserved miRNAs from 21 families in flax. Moreover, 475 novel potential miRNAs were identified for the first time, and their targets were predicted. However, none of the identified miRNAs were transcribed from LIS-1. Expression of seven miRNAs (miR168, miR169, miR395, miR398, miR399, miR408, and lus-miR-N1) with up- or down-regulation under nutrient stress (on the basis of high-throughput sequencing data) was evaluated on extended sampling using qPCR. Reference gene search identified ETIF3H and ETIF3E genes as most suitable for this purpose. Down-regulation of novel potential lus-miR-N1 and up-regulation of conserved miR399 were revealed under the phosphate deficient conditions. In addition, the negative correlation of expression of lus-miR-N1 and its predicted target, ubiquitin-activating enzyme E1 gene, as well as, miR399 and its predicted target, ubiquitin-conjugating enzyme E2 gene, was observed. Thus, in our study, miRNAs expressed in flax plastic lines and genotrophs were identified and their expression and expression of their targets was evaluated using high-throughput sequencing and qPCR for the first time. These data provide new insights

  4. Identification, Expression Analysis, and Target Prediction of Flax Genotroph MicroRNAs Under Normal and Nutrient Stress Conditions.

    PubMed

    Melnikova, Nataliya V; Dmitriev, Alexey A; Belenikin, Maxim S; Koroban, Nadezhda V; Speranskaya, Anna S; Krinitsina, Anastasia A; Krasnov, George S; Lakunina, Valentina A; Snezhkina, Anastasiya V; Sadritdinova, Asiya F; Kishlyan, Natalya V; Rozhmina, Tatiana A; Klimina, Kseniya M; Amosova, Alexandra V; Zelenin, Alexander V; Muravenko, Olga V; Bolsheva, Nadezhda L; Kudryavtseva, Anna V

    2016-01-01

    Cultivated flax (Linum usitatissimum L.) is an important plant valuable for industry. Some flax lines can undergo heritable phenotypic and genotypic changes (LIS-1 insertion being the most common) in response to nutrient stress and are called plastic lines. Offspring of plastic lines, which stably inherit the changes, are called genotrophs. MicroRNAs (miRNAs) are involved in a crucial regulatory mechanism of gene expression. They have previously been assumed to take part in nutrient stress response and can, therefore, participate in genotroph formation. In the present study, we performed high-throughput sequencing of small RNAs (sRNAs) extracted from flax plants grown under normal, phosphate deficient and nutrient excess conditions to identify miRNAs and evaluate their expression. Our analysis revealed expression of 96 conserved miRNAs from 21 families in flax. Moreover, 475 novel potential miRNAs were identified for the first time, and their targets were predicted. However, none of the identified miRNAs were transcribed from LIS-1. Expression of seven miRNAs (miR168, miR169, miR395, miR398, miR399, miR408, and lus-miR-N1) with up- or down-regulation under nutrient stress (on the basis of high-throughput sequencing data) was evaluated on extended sampling using qPCR. Reference gene search identified ETIF3H and ETIF3E genes as most suitable for this purpose. Down-regulation of novel potential lus-miR-N1 and up-regulation of conserved miR399 were revealed under the phosphate deficient conditions. In addition, the negative correlation of expression of lus-miR-N1 and its predicted target, ubiquitin-activating enzyme E1 gene, as well as, miR399 and its predicted target, ubiquitin-conjugating enzyme E2 gene, was observed. Thus, in our study, miRNAs expressed in flax plastic lines and genotrophs were identified and their expression and expression of their targets was evaluated using high-throughput sequencing and qPCR for the first time. These data provide new insights

  5. Identification, Expression Analysis, and Target Prediction of Flax Genotroph MicroRNAs Under Normal and Nutrient Stress Conditions

    PubMed Central

    Melnikova, Nataliya V.; Dmitriev, Alexey A.; Belenikin, Maxim S.; Koroban, Nadezhda V.; Speranskaya, Anna S.; Krinitsina, Anastasia A.; Krasnov, George S.; Lakunina, Valentina A.; Snezhkina, Anastasiya V.; Sadritdinova, Asiya F.; Kishlyan, Natalya V.; Rozhmina, Tatiana A.; Klimina, Kseniya M.; Amosova, Alexandra V.; Zelenin, Alexander V.; Muravenko, Olga V.; Bolsheva, Nadezhda L.; Kudryavtseva, Anna V.

    2016-01-01

    Cultivated flax (Linum usitatissimum L.) is an important plant valuable for industry. Some flax lines can undergo heritable phenotypic and genotypic changes (LIS-1 insertion being the most common) in response to nutrient stress and are called plastic lines. Offspring of plastic lines, which stably inherit the changes, are called genotrophs. MicroRNAs (miRNAs) are involved in a crucial regulatory mechanism of gene expression. They have previously been assumed to take part in nutrient stress response and can, therefore, participate in genotroph formation. In the present study, we performed high-throughput sequencing of small RNAs (sRNAs) extracted from flax plants grown under normal, phosphate deficient and nutrient excess conditions to identify miRNAs and evaluate their expression. Our analysis revealed expression of 96 conserved miRNAs from 21 families in flax. Moreover, 475 novel potential miRNAs were identified for the first time, and their targets were predicted. However, none of the identified miRNAs were transcribed from LIS-1. Expression of seven miRNAs (miR168, miR169, miR395, miR398, miR399, miR408, and lus-miR-N1) with up- or down-regulation under nutrient stress (on the basis of high-throughput sequencing data) was evaluated on extended sampling using qPCR. Reference gene search identified ETIF3H and ETIF3E genes as most suitable for this purpose. Down-regulation of novel potential lus-miR-N1 and up-regulation of conserved miR399 were revealed under the phosphate deficient conditions. In addition, the negative correlation of expression of lus-miR-N1 and its predicted target, ubiquitin-activating enzyme E1 gene, as well as, miR399 and its predicted target, ubiquitin-conjugating enzyme E2 gene, was observed. Thus, in our study, miRNAs expressed in flax plastic lines and genotrophs were identified and their expression and expression of their targets was evaluated using high-throughput sequencing and qPCR for the first time. These data provide new insights

  6. Model predictions of realgar precipitation by reaction of As(III) with synthetic mackinawite under anoxic conditions

    USGS Publications Warehouse

    Gallegos, T.J.; Han, Y.-S.; Hayes, K.F.

    2008-01-01

    This study investigates the removal of As(III) from solution using mackinawite, a nanoparticulate reduced iron sulfide. Mackinawite suspensions (0.1-40 g/L) effectively lower initial concentrations of 1.3 ?? 10 -5 M As(III) from pH 5-10, with maximum removal occurring under acidic conditions. Based on Eh measurements, it was found that the redox state of the system depended on the mackinawite solids concentration and pH. Higher initial mackinawite concentrations and alkaline pH resulted in a more reducing redox condition. Given this, the pH edge data were modeled thermodynamically using pe (-log[e-]) as a fitting parameter and linear pe-pH relationships within the range of measured Eh values as a function of pH and mackinawite concentration. The model predicts removal of As(III) from solution by precipitation of realgar with the formation of secondary oxidation products, greigite or a mixed-valence iron oxide phase, depending on pH. This study demonstrates that mackinawite is an effective sequestration agent for As(III) and highlights the importance of incorporating redox into models describing the As-Fe-S-H2O system. ?? 2008 American Chemical Society.

  7. Postexercise Hypotension After Continuous, Aerobic Interval, and Sprint Interval Exercise.

    PubMed

    Angadi, Siddhartha S; Bhammar, Dharini M; Gaesser, Glenn A

    2015-10-01

    We examined the effects of 3 exercise bouts, differing markedly in intensity, on postexercise hypotension (PEH). Eleven young adults (age: 24.6 ± 3.7 years) completed 4 randomly assigned experimental conditions: (a) control, (b) 30-minute steady-state exercise (SSE) at 75-80% maximum heart rate (HRmax), (4) aerobic interval exercise (AIE): four 4-minute bouts at 90-95% HRmax, separated by 3 minutes of active recovery, and (d) sprint interval exercise (SIE): six 30-second Wingate sprints, separated by 4 minutes of active recovery. Exercise was performed on a cycle ergometer. Blood pressure (BP) was measured before exercise and every 15-minute postexercise for 3 hours. Linear mixed models were used to compare BP between trials. During the 3-hour postexercise, systolic BP (SBP) was lower (p < 0.001) after AIE (118 ± 10 mm Hg), SSE (121 ± 10 mm Hg), and SIE (121 ± 11 mm Hg) compared with control (124 ± 8 mm Hg). Diastolic BP (DBP) was also lower (p < 0.001) after AIE (66 ± 7 mm Hg), SSE (69 ± 6 mm Hg), and SIE (68 ± 8 mm Hg) compared with control (71 ± 7 mm Hg). Only AIE resulted in sustained (>2 hours) PEH, with SBP (120 ± 9 mm Hg) and DBP (68 ± 7 mm Hg) during the third-hour postexercise being lower (p ≤ 0.05) than control (124 ± 8 and 70 ± 7 mm Hg). Although all exercise bouts produced similar reductions in BP at 1-hour postexercise, the duration of PEH was greatest after AIE.

  8. Coefficient Omega Bootstrap Confidence Intervals: Nonnormal Distributions

    ERIC Educational Resources Information Center

    Padilla, Miguel A.; Divers, Jasmin

    2013-01-01

    The performance of the normal theory bootstrap (NTB), the percentile bootstrap (PB), and the bias-corrected and accelerated (BCa) bootstrap confidence intervals (CIs) for coefficient omega was assessed through a Monte Carlo simulation under conditions not previously investigated. Of particular interests were nonnormal Likert-type and binary items.…

  9. MEETING DATA QUALITY OBJECTIVES WITH INTERVAL INFORMATION

    EPA Science Inventory

    Immunoassay test kits are promising technologies for measuring analytes under field conditions. Frequently, these field-test kits report the analyte concentrations as falling in an interval between minimum and maximum values. Many project managers use field-test kits only for scr...

  10. Order and chaos in fixed-interval schedules of reinforcement

    PubMed Central

    Hoyert, Mark S.

    1992-01-01

    Fixed-interval schedule performance is characterized by high levels of variability. Responding is absent at the onset of the interval and gradually increases in frequency until reinforcer delivery. Measures of behavior also vary drastically and unpredictably between successive intervals. Recent advances in the study of nonlinear dynamics have allowed researchers to study irregular and unpredictable behavior in a number of fields. This paper reviews several concepts and techniques from nonlinear dynamics and examines their utility in predicting the behavior of pigeons responding to a fixed-interval schedule of reinforcement. The analysis provided fairly accurate a priori accounts of response rates, accounting for 92.8% of the variance when predicting response rate 1 second in the future and 64% of the variance when predicting response rates for each second over the entire next interreinforcer interval. The nonlinear dynamics account suggests that even the “noisiest” behavior might be the product of purely deterministic mechanisms. PMID:16812657

  11. Reduced intensity conditioning allogeneic stem cell transplantation for Hodgkin’s lymphoma: identification of prognostic factors predicting outcome

    PubMed Central

    Robinson, Stephen P.; Sureda, Anna; Canals, Carmen; Russell, Nigel; Caballero, Dolores; Bacigalupo, Andrea; Iriondo, Arturo; Cook, Gordon; Pettitt, Andrew; Socie, Gerard; Bonifazi, Francesca; Bosi, Alberto; Michallet, Mauricette; Liakopoulou, Effie; Maertens, Johan; Passweg, Jakob; Clarke, Fiona; Martino, Rodrigo; Schmitz, Norbert

    2009-01-01

    Background The role of reduced intensity conditioning allogeneic stem transplantation (RICalloSCT) in the management of patients with Hodgkin’s lymphoma remains controversial. Design and Methods To further define its role we have conducted a retrospective analysis of 285 patients with HL who underwent a RICalloSCT in order to identify prognostic factors that predict outcome. Eighty percent of patients had undergone a prior autologous stem cell transplantation and 25% had refractory disease at transplant. Results Non-relapse mortality was associated with chemorefractory disease, poor performance status, age >45 and transplantation before 2002. For patients with no risk factors the 3-year non-relapse mortality rate was 12.5% compared to 46.2% for patients with 2 or more risk factors. The use of an unrelated donor had no adverse effect on the non-relapse mortality. Acute graft versus host disease (aGVHD) grades II–IV developed in 30% and chronic GVHD in 42%. The development of cGVHD was associated with a lower relapse rate. The disease progression rate at one and five years was 41% and 58.7% respectively and was associated with chemorefractory disease and extent of prior therapy. Donor lymphocyte infusions were administered to 64 patients for active disease of whom 32% showed a clinical response. Eight out of 18 patients receiving donor lymphocyte infusions alone had clinical responses. Progression-free and overall survival were both associated with performance status and disease status at transplant. Patients with neither risk factor had a 3-year PFS and overall survival of 42% and 56% respectively compared to 8% and 25% for patients with one or more risk factors. Relapse within six months of a prior autologous transplant was associated with a higher relapse rate and a lower progression-free. Conclusions This analysis identifies important clinical parameters that may be useful in predicting the outcome of RICaIICalloSCT in Hodgkin’s lymphoma. PMID:19066328

  12. Integrating Genomics with Nutrition Models to Improve the Prediction of Cattle Performance and Carcass Composition under Feedlot Conditions.

    PubMed

    Tedeschi, Luis O

    2015-01-01

    Cattle body composition is difficult to model because several factors affect the composition of the average daily gain (ADG) of growing animals. The objective of this study was to identify commercial single nucleotide polymorphism (SNP) panels that could improve the predictability of days on feed (DOF) to reach a target United States Department of Agriculture (USDA) grade given animal, diet, and environmental information under feedyard conditions. The data for this study was comprised of crossbred heifers (n = 681) and steers (n = 836) from commercial feedyards. Eleven molecular breeding value (MBV) scores derived from SNP panels of candidate gene polymorphisms and two-leptin gene SNP (UASMS2 and E2FB) were evaluated. The empty body fat (EBF) and the shrunk body weight (SBW) at 28% EBF (AFSBW) were computed by the Cattle Value Discovery System (CVDS) model using hip height (EBFHH and AFSBWHH) or carcass traits (EBFCT and AFSBWCT) of the animals. The DOFHH was calculated when AFSBWHH and ADGHH were used and DOFCT was calculated when AFSBWCT and ADGCT were used. The CVDS estimates dry matter required (DMR) by individuals fed in groups when observed ADG and AFSBW are provided. The AFSBWCT was assumed more accurate than the AFSBWHH because it was computed using carcass traits. The difference between AFSBWCT and AFSBWHH, DOFCT and DOFHH, and DMR and dry matter intake (DMI) were regressed on the MBV scores and leptin gene SNP to explain the variation. Our results indicate quite a large range of correlations among MBV scores and model input and output variables, but MBV ribeye area was the most strongly correlated with the differences in DOF, AFSBW, and DMI by explaining 8, 13.2 and 6.5%, respectively, of the variation. This suggests that specific MBV scores might explain additional variation of input and output variables used by nutritional models in predicting individual animal performance. PMID:26599759

  13. CMAQ predictions of tropospheric ozone in the U.S. southwest: influence of lateral boundary and synoptic conditions.

    PubMed

    Shi, Chune; Fernando, H J S; Hyde, Peter

    2012-02-01

    Phoenix, Arizona, has been an ozone nonattainment area for the past several years and it remains so. Mitigation strategies call for improved modeling methodologies as well as understanding of ozone formation and destruction mechanisms during seasons of high ozone events. To this end, the efficacy of lateral boundary conditions (LBCs) based on satellite measurements (adjusted-LBCs) was investigated, vis-à-vis the default-LBCs, for improving the predictions of Models-3/CMAQ photochemical air quality modeling system. The model evaluations were conducted using hourly ground-level ozone and NO(2) concentrations as well as tropospheric NO(2) columns and ozone concentrations in the middle to upper troposphere, with the 'design' periods being June and July of 2006. Both included high ozone episodes, but the June (pre-monsoon) period was characterized by local thermal circulation whereas the July (monsoon) period by synoptic influence. Overall, improved simulations were noted for adjusted-LBC runs for ozone concentrations both at the ground-level and in the middle to upper troposphere, based on EPA-recommended model performance metrics. The probability of detection (POD) of ozone exceedances (>75ppb, 8-h averages) for the entire domain increased from 20.8% for the default-LBC run to 33.7% for the adjusted-LBC run. A process analysis of modeling results revealed that ozone within PBL during bulk of the pre-monsoon season is contributed by local photochemistry and vertical advection, while the contributions of horizontal and vertical advections are comparable in the monsoon season. The process analysis with adjusted-LBC runs confirms the contributions of vertical advection to episodic high ozone days, and hence elucidates the importance of improving predictability of upper levels with improved LBCs.

  14. Integrating Genomics with Nutrition Models to Improve the Prediction of Cattle Performance and Carcass Composition under Feedlot Conditions

    PubMed Central

    Tedeschi, Luis O.

    2015-01-01

    Cattle body composition is difficult to model because several factors affect the composition of the average daily gain (ADG) of growing animals. The objective of this study was to identify commercial single nucleotide polymorphism (SNP) panels that could improve the predictability of days on feed (DOF) to reach a target United States Department of Agriculture (USDA) grade given animal, diet, and environmental information under feedyard conditions. The data for this study was comprised of crossbred heifers (n = 681) and steers (n = 836) from commercial feedyards. Eleven molecular breeding value (MBV) scores derived from SNP panels of candidate gene polymorphisms and two-leptin gene SNP (UASMS2 and E2FB) were evaluated. The empty body fat (EBF) and the shrunk body weight (SBW) at 28% EBF (AFSBW) were computed by the Cattle Value Discovery System (CVDS) model using hip height (EBFHH and AFSBWHH) or carcass traits (EBFCT and AFSBWCT) of the animals. The DOFHH was calculated when AFSBWHH and ADGHH were used and DOFCT was calculated when AFSBWCT and ADGCT were used. The CVDS estimates dry matter required (DMR) by individuals fed in groups when observed ADG and AFSBW are provided. The AFSBWCT was assumed more accurate than the AFSBWHH because it was computed using carcass traits. The difference between AFSBWCT and AFSBWHH, DOFCT and DOFHH, and DMR and dry matter intake (DMI) were regressed on the MBV scores and leptin gene SNP to explain the variation. Our results indicate quite a large range of correlations among MBV scores and model input and output variables, but MBV ribeye area was the most strongly correlated with the differences in DOF, AFSBW, and DMI by explaining 8, 13.2 and 6.5%, respectively, of the variation. This suggests that specific MBV scores might explain additional variation of input and output variables used by nutritional models in predicting individual animal performance. PMID:26599759

  15. An interval model updating strategy using interval response surface models

    NASA Astrophysics Data System (ADS)

    Fang, Sheng-En; Zhang, Qiu-Hu; Ren, Wei-Xin

    2015-08-01

    Stochastic model updating provides an effective way of handling uncertainties existing in real-world structures. In general, probabilistic theories, fuzzy mathematics or interval analyses are involved in the solution of inverse problems. However in practice, probability distributions or membership functions of structural parameters are often unavailable due to insufficient information of a structure. At this moment an interval model updating procedure shows its superiority in the aspect of problem simplification since only the upper and lower bounds of parameters and responses are sought. To this end, this study develops a new concept of interval response surface models for the purpose of efficiently implementing the interval model updating procedure. The frequent interval overestimation due to the use of interval arithmetic can be maximally avoided leading to accurate estimation of parameter intervals. Meanwhile, the establishment of an interval inverse problem is highly simplified, accompanied by a saving of computational costs. By this means a relatively simple and cost-efficient interval updating process can be achieved. Lastly, the feasibility and reliability of the developed method have been verified against a numerical mass-spring system and also against a set of experimentally tested steel plates.

  16. Minimax confidence intervals in geomagnetism

    NASA Technical Reports Server (NTRS)

    Stark, Philip B.

    1992-01-01

    The present paper uses theory of Donoho (1989) to find lower bounds on the lengths of optimally short fixed-length confidence intervals (minimax confidence intervals) for Gauss coefficients of the field of degree 1-12 using the heat flow constraint. The bounds on optimal minimax intervals are about 40 percent shorter than Backus' intervals: no procedure for producing fixed-length confidence intervals, linear or nonlinear, can give intervals shorter than about 60 percent the length of Backus' in this problem. While both methods rigorously account for the fact that core field models are infinite-dimensional, the application of the techniques to the geomagnetic problem involves approximations and counterfactual assumptions about the data errors, and so these results are likely to be extremely optimistic estimates of the actual uncertainty in Gauss coefficients.

  17. Predicting conditions for the reception of one-hop signals from the Siple transmitter experiment using the Kp index

    NASA Astrophysics Data System (ADS)

    Li, J. D.; Spasojevic, M.; Inan, U. S.

    2015-10-01

    Wave injection experiments provide an opportunity to explore and quantify aspects of nonlinear wave-particle phenomena in a controlled manner. Waves are injected into space from ground-based ELF/VLF transmitters, and the modified waves are measured by radio receivers on the ground in the conjugate hemisphere. These experiments are expensive and challenging projects to build and to operate, and the transmitted waves are not always detected in the conjugate region. Even the powerful transmitter located at Siple Station, Antarctica in 1986, estimated to radiate over 1 kW, only reported a reception rate of ˜40%, indicating that a significant number of transmissions served no observable scientific purpose and reflecting the difficulty in determining suitable conditions for transmission and reception. Leveraging modern machine-learning classification techniques, we apply two statistical techniques, a Bayes and a support vector machine classifier, to predict the occurrence of detectable one-hop transmissions from Siple data with accuracies on the order of 80%-90%. Applying these classifiers to our 1986 Siple data set, we detect 406 receptions of Siple transmissions which we analyze to generate more robust statistics on nonlinear growth rates, 3 dB/s-270 dB/s, and nonlinear total amplification, 3 dB-41 dB.

  18. Effect Sizes, Confidence Intervals, and Confidence Intervals for Effect Sizes

    ERIC Educational Resources Information Center

    Thompson, Bruce

    2007-01-01

    The present article provides a primer on (a) effect sizes, (b) confidence intervals, and (c) confidence intervals for effect sizes. Additionally, various admonitions for reformed statistical practice are presented. For example, a very important implication of the realization that there are dozens of effect size statistics is that "authors must…

  19. Prediction of Malaysian monthly GDP

    NASA Astrophysics Data System (ADS)

    Hin, Pooi Ah; Ching, Soo Huei; Yeing, Pan Wei

    2015-12-01

    The paper attempts to use a method based on multivariate power-normal distribution to predict the Malaysian Gross Domestic Product next month. Letting r(t) be the vector consisting of the month-t values on m selected macroeconomic variables, and GDP, we model the month-(t+1) GDP to be dependent on the present and l-1 past values r(t), r(t-1),…,r(t-l+1) via a conditional distribution which is derived from a [(m+1)l+1]-dimensional power-normal distribution. The 100(α/2)% and 100(1-α/2)% points of the conditional distribution may be used to form an out-of sample prediction interval. This interval together with the mean of the conditional distribution may be used to predict the month-(t+1) GDP. The mean absolute percentage error (MAPE), estimated coverage probability and average length of the prediction interval are used as the criterions for selecting the suitable lag value l-1 and the subset from a pool of 17 macroeconomic variables. It is found that the relatively better models would be those of which 2 ≤ l ≤ 3, and involving one or two of the macroeconomic variables given by Market Indicative Yield, Oil Prices, Exchange Rate and Import Trade.

  20. Volatility return intervals analysis of the Japanese market

    NASA Astrophysics Data System (ADS)

    Jung, W.-S.; Wang, F. Z.; Havlin, S.; Kaizoji, T.; Moon, H.-T.; Stanley, H. E.

    2008-03-01

    We investigate scaling and memory effects in return intervals between price volatilities above a certain threshold q for the Japanese stock market using daily and intraday data sets. We find that the distribution of return intervals can be approximated by a scaling function that depends only on the ratio between the return interval τ and its mean <τ>. We also find memory effects such that a large (or small) return interval follows a large (or small) interval by investigating the conditional distribution and mean return interval. The results are similar to previous studies of other markets and indicate that similar statistical features appear in different financial markets. We also compare our results between the period before and after the big crash at the end of 1989. We find that scaling and memory effects of the return intervals show similar features although the statistical properties of the returns are different.

  1. Interval approach to braneworld gravity

    NASA Astrophysics Data System (ADS)

    Carena, Marcela; Lykken, Joseph; Park, Minjoon

    2005-10-01

    Gravity in five-dimensional braneworld backgrounds may exhibit extra scalar degrees of freedom with problematic features, including kinetic ghosts and strong coupling behavior. Analysis of such effects is hampered by the standard heuristic approaches to braneworld gravity, which use the equations of motion as the starting point, supplemented by orbifold projections and junction conditions. Here we develop the interval approach to braneworld gravity, which begins with an action principle. This shows how to implement general covariance, despite allowing metric fluctuations that do not vanish on the boundaries. We reproduce simple Z2 orbifolds of gravity, even though in this approach we never perform a Z2 projection. We introduce a family of “straight gauges”, which are bulk coordinate systems in which both branes appear as straight slices in a single coordinate patch. Straight gauges are extremely useful for analyzing metric fluctuations in braneworld models. By explicit gauge-fixing, we show that a general AdS5/AdS4 setup with two branes has at most a radion, but no physical “brane-bending” modes.

  2. Explorations in Statistics: Confidence Intervals

    ERIC Educational Resources Information Center

    Curran-Everett, Douglas

    2009-01-01

    Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This third installment of "Explorations in Statistics" investigates confidence intervals. A confidence interval is a range that we expect, with some level of confidence, to include the true value of a population parameter…

  3. Teaching Confidence Intervals Using Simulation

    ERIC Educational Resources Information Center

    Hagtvedt, Reidar; Jones, Gregory Todd; Jones, Kari

    2008-01-01

    Confidence intervals are difficult to teach, in part because most students appear to believe they understand how to interpret them intuitively. They rarely do. To help them abandon their misconception and achieve understanding, we have developed a simulation tool that encourages experimentation with multiple confidence intervals derived from the…

  4. Automatic Error Analysis Using Intervals

    ERIC Educational Resources Information Center

    Rothwell, E. J.; Cloud, M. J.

    2012-01-01

    A technique for automatic error analysis using interval mathematics is introduced. A comparison to standard error propagation methods shows that in cases involving complicated formulas, the interval approach gives comparable error estimates with much less effort. Several examples are considered, and numerical errors are computed using the INTLAB…

  5. Remote detection of water stress conditions via a diurnal photochemical reflectance index (PRI) improves yield prediction in rainfed wheat

    NASA Astrophysics Data System (ADS)

    Magney, T. S.; Vierling, L. A.; Eitel, J.

    2014-12-01

    Employing remotely sensed techniques to quantify the existence and magnitude of midday photosynthetic downregulation using the photochemical reflectance index (PRI) may reveal new information about plant responses to abiotic stressors in space and time. However, the interpretation and application of the PRI can be confounded because of its sensitivity to several variables changing at the diurnal (e.g., irradiation, shadow fraction) and seasonal (e.g., leaf area, chlorophyll and carotene pigment concentrations, irradiation) time scales. We explored different techniques to correct the PRI for variations in canopy structure and relative chlorophyll content (ChlR) using highly temporally resolved (frequency = five minutes) in-situ radiometric measurements of PRI and the Normalized Difference Vegetation Index (NDVI) over eight soft white spring wheat (Triticum aestivum L.)field plots under varying nitrogen and soil water conditions over two seasons. Our results suggest that the influence of seasonal variation in canopy ChlR and LAI on the diurnally measured PRI (PRIdiurnal) can be minimized using simple correction techniques, therefore improving the strength of PRI as a tool to quantify abiotic stressors such as daily changes in soil volumetric water content (SVWC), and vapor pressure deficit (VPD). PRIdiurnal responded strongly to available nitrogen, and linearly tracked seasonal changes in SVWC, VPD, and stomatal conductance (gc). Utilizing the PRI as an indicator of stress, yield predictions significantly over greenness indices such as the NDVI. This study provides insight towards the future interpretation and scaling of PRI to quantify rapid changes in photosynthesis, and as an indicator of plant stress.

  6. VARIABLE TIME-INTERVAL GENERATOR

    DOEpatents

    Gross, J.E.

    1959-10-31

    This patent relates to a pulse generator and more particularly to a time interval generator wherein the time interval between pulses is precisely determined. The variable time generator comprises two oscillators with one having a variable frequency output and the other a fixed frequency output. A frequency divider is connected to the variable oscillator for dividing its frequency by a selected factor and a counter is used for counting the periods of the fixed oscillator occurring during a cycle of the divided frequency of the variable oscillator. This defines the period of the variable oscillator in terms of that of the fixed oscillator. A circuit is provided for selecting as a time interval a predetermined number of periods of the variable oscillator. The output of the generator consists of a first pulse produced by a trigger circuit at the start of the time interval and a second pulse marking the end of the time interval produced by the same trigger circuit.

  7. Prediction of rectal temperature using non-invasive physiologic variable measurements in hair pregnant ewes subjected to natural conditions of heat stress.

    PubMed

    Vicente-Pérez, Ricardo; Avendaño-Reyes, Leonel; Mejía-Vázquez, Ángel; Álvarez-Valenzuela, F Daniel; Correa-Calderón, Abelardo; Mellado, Miguel; Meza-Herrera, Cesar A; Guerra-Liera, Juan E; Robinson, P H; Macías-Cruz, Ulises

    2016-01-01

    Rectal temperature (RT) is the foremost physiological variable indicating if an animal is suffering hyperthermia. However, this variable is traditionally measured by invasive methods, which may compromise animal welfare. Models to predict RT have been developed for growing pigs and lactating dairy cows, but not for pregnant heat-stressed ewes. Our aim was to develop a prediction equation for RT using non-invasive physiological variables in pregnant ewes under heat stress. A total of 192 records of respiratory frequency (RF) and hair coat temperature in various body regions (i.e., head, rump, flank, shoulder, and belly) obtained from 24 Katahdin × Pelibuey pregnant multiparous ewes were collected during the last third of gestation (i.e., d 100 to lambing) with a 15 d sampling interval. Hair coat temperatures were taken using infrared thermal imaging technology. Initially, a Pearson correlation analysis examined the relationship among variables, and then multiple linear regression analysis was used to develop the prediction equations. All predictor variables were positively correlated (P<0.01; r=0.59-0.67) with RT. The adjusted equation which best predicted RT (P<0.01; Radj(2)=56.15%; CV=0.65%) included as predictors RF and head and belly temperatures. Comparison of predicted and observed values for RT indicates a suitable agreement (P<0.01) between them with moderate accuracy (Radj(2)=56.15%) when RT was calculated with the adjusted equation. In general, the final equation does not violate any assumption of multiple regression analysis. The RT in heat-stressed pregnant ewes can be predicted with an adequate accuracy using non-invasive physiologic variables, and the final equation was: RT=35.57+0.004 (RF)+0.067 (heat temperature)+0.028 (belly temperature).

  8. Subjective probability intervals: how to reduce overconfidence by interval evaluation.

    PubMed

    Winman, Anders; Hansson, Patrik; Juslin, Peter

    2004-11-01

    Format dependence implies that assessment of the same subjective probability distribution produces different conclusions about over- or underconfidence depending on the assessment format. In 2 experiments, the authors demonstrate that the overconfidence bias that occurs when participants produce intervals for an uncertain quantity is almost abolished when they evaluate the probability that the same intervals include the quantity. The authors successfully apply a method for adaptive adjustment of probability intervals as a debiasing tool and discuss a tentative explanation in terms of a naive sampling model. According to this view, people report their experiences accurately, but they are naive in that they treat both sample proportion and sample dispersion as unbiased estimators, yielding small bias in probability evaluation but strong bias in interval production. PMID:15521796

  9. Unpacking a time interval lengthens its perceived temporal distance

    PubMed Central

    Liu, Yang; Li, Shu; Sun, Yan

    2014-01-01

    In quantity estimation, people often perceive that the whole is less than the sum of its parts. The current study investigated such an unpacking effect in temporal distance judgment. Our results showed that participants in the unpacked condition judged a given time interval longer than those in the packed condition, even the time interval was kept constant between the two conditions. Furthermore, this unpacking effect persists regardless of the unpacking ways we employed. Results suggest that unpacking a time interval may be a good strategy for lengthening its perceived temporal distance. PMID:25477854

  10. Unpacking a time interval lengthens its perceived temporal distance.

    PubMed

    Liu, Yang; Li, Shu; Sun, Yan

    2014-01-01

    In quantity estimation, people often perceive that the whole is less than the sum of its parts. The current study investigated such an unpacking effect in temporal distance judgment. Our results showed that participants in the unpacked condition judged a given time interval longer than those in the packed condition, even the time interval was kept constant between the two conditions. Furthermore, this unpacking effect persists regardless of the unpacking ways we employed. Results suggest that unpacking a time interval may be a good strategy for lengthening its perceived temporal distance. PMID:25477854

  11. Quantifying chaotic dynamics from interspike intervals

    NASA Astrophysics Data System (ADS)

    Pavlov, A. N.; Pavlova, O. N.; Mohammad, Y. K.; Shihalov, G. M.

    2015-03-01

    We address the problem of characterization of chaotic dynamics at the input of a threshold device described by an integrate-and-fire (IF) or a threshold crossing (TC) model from the output sequences of interspike intervals (ISIs). We consider the conditions under which quite short sequences of spiking events provide correct identification of the dynamical regime characterized by the single positive Lyapunov exponent (LE). We discuss features of detecting the second LE for both types of the considered models of events generation.

  12. Comparison of spring measures of length, weight, and condition factor for predicting metamorphosis in two populations of sea lampreys (Petromyzon marinus) larvae

    USGS Publications Warehouse

    Henson, Mary P.; Bergstedt, Roger A.; Adams, Jean V.

    2003-01-01

    The ability to predict when sea lampreys (Petromyzon marinus) will metamorphose from the larval phase to the parasitic phase is essential to the operation of the sea lamprey control program. During the spring of 1994, two populations of sea lamprey larvae from two rivers were captured, measured, weighed, implanted with coded wire tags, and returned to the same sites in the streams from which they were taken. Sea lampreys were recovered in the fall, after metamorphosis would have occurred, and checked for the presence of a tag. When the spring data were compared to the fall data it was found that the minimum requirements (length ≥ 120 mm, weight ≥ 3 g, and condition factor ≥ 1.50) suggested for metamorphosis did define a pool of larvae capable of metamorphosing. However, logistic regressions that relate the probability of metamorphosis to size are necessary to predict metamorphosis in a population. The data indicated, based on cross-validation, that weight measurements alone predicted metamorphosis with greater precision than length or condition factor in both the Marengo and Amnicon rivers. Based on the Akaike Information Criterion, weight alone was a better predictor in the Amnicon River, but length and condition factor combined predicted metamorphosis better in the Marengo River. There would be no additional cost if weight alone were used instead of length. However, if length and weight were measured the gain in predictive power would not be enough to justify the additional cost.

  13. TIME-INTERVAL MEASURING DEVICE

    DOEpatents

    Gross, J.E.

    1958-04-15

    An electronic device for measuring the time interval between two control pulses is presented. The device incorporates part of a previous approach for time measurement, in that pulses from a constant-frequency oscillator are counted during the interval between the control pulses. To reduce the possible error in counting caused by the operation of the counter gating circuit at various points in the pulse cycle, the described device provides means for successively delaying the pulses for a fraction of the pulse period so that a final delay of one period is obtained and means for counting the pulses before and after each stage of delay during the time interval whereby a plurality of totals is obtained which may be averaged and multplied by the pulse period to obtain an accurate time- Interval measurement.

  14. Simple Interval Timers for Microcomputers.

    ERIC Educational Resources Information Center

    McInerney, M.; Burgess, G.

    1985-01-01

    Discusses simple interval timers for microcomputers, including (1) the Jiffy clock; (2) CPU count timers; (3) screen count timers; (4) light pen timers; and (5) chip timers. Also examines some of the general characteristics of all types of timers. (JN)

  15. Packet theory of conditioning and timing.

    PubMed

    Kirkpatrick, Kimberly

    2002-04-28

    Packet theory is based on the assumption that the momentary probability of producing a bout or packet of responding is controlled by the conditional expected time function. Bouts of head entry responses of rats into a food cup appear to have the same characteristics across a range of conditions. The conditional expected time function is the mean expected time remaining until the next food delivery as a function of time since an event such as food or stimulus onset. The conditional expected time function encodes mean interval duration as well as the distribution form so that both the mean response rate and form of responding in time can be predicted. Simulations of Packet theory produced accurate quantitative predictions of: (1) the effect of reinforcement density (mean food-food interval) and distribution form on responding; (2) scalar variance in fixed interval responding; (3) CS-US and intertrial interval effects on the strength of conditioning; and (4) the effect of the ratio of cycle:trial time on the strength of conditioning.

  16. Verification of an ENSO-Based Long-Range Prediction of Anomalous Weather Conditions During the Vancouver 2010 Olympics and Paralympics

    NASA Astrophysics Data System (ADS)

    Mo, Ruping; Joe, Paul I.; Doyle, Chris; Whitfield, Paul H.

    2014-01-01

    A brief review of the anomalous weather conditions during the Vancouver 2010 Winter Olympic and Paralympic Games and the efforts to predict these anomalies based on some preceding El Niño-Southern Oscillation (ENSO) signals are presented. It is shown that the Olympic Games were held under extraordinarily warm conditions in February 2010, with monthly mean temperature anomalies of +2.2 °C in Vancouver and +2.8 °C in Whistler, ranking respectively as the highest and the second highest in the past 30 years (1981-2010). The warm conditions continued, but became less anomalous, in March 2010 for the Paralympic Games. While the precipitation amounts in the area remained near normal through this winter, the lack of snow due to warm conditions created numerous media headlines and practical problems for the alpine competitions. A statistical model was developed on the premise that February and March temperatures in the Vancouver area could be predicted using an ENSO signal with considerable lead time. This model successfully predicted the warmer-than-normal, lower-snowfall conditions for the Vancouver 2010 Winter Olympics and Paralympics.

  17. A QSPR model for prediction of diffusion coefficient of non-electrolyte organic compounds in air at ambient condition.

    PubMed

    Mirkhani, Seyyed Alireza; Gharagheizi, Farhad; Sattari, Mehdi

    2012-03-01

    Evaluation of diffusion coefficients of pure compounds in air is of great interest for many diverse industrial and air quality control applications. In this communication, a QSPR method is applied to predict the molecular diffusivity of chemical compounds in air at 298.15K and atmospheric pressure. Four thousand five hundred and seventy nine organic compounds from broad spectrum of chemical families have been investigated to propose a comprehensive and predictive model. The final model is derived by Genetic Function Approximation (GFA) and contains five descriptors. Using this dedicated model, we obtain satisfactory results quantified by the following statistical results: Squared Correlation Coefficient=0.9723, Standard Deviation Error=0.003 and Average Absolute Relative Deviation=0.3% for the predicted properties from existing experimental values. PMID:22189378

  18. ASSESSING THE PREDICTIVE CAPABILITY OF LANDSCAPE SAMPLING UNITS OF VARYING SCALE IN THE ANALYSIS OF ESTUARINE CONDITION

    EPA Science Inventory

    Landscape structure metrics are often used to predict water and sediment quality of lakes, streams, and estuaries; however, the sampling units used to generate the landscape metrics are often at an irrelevant spatial scale. They are either too large (i.e., an entire watershed) or...

  19. Constraint-based Attribute and Interval Planning

    NASA Technical Reports Server (NTRS)

    Jonsson, Ari; Frank, Jeremy

    2013-01-01

    In this paper we describe Constraint-based Attribute and Interval Planning (CAIP), a paradigm for representing and reasoning about plans. The paradigm enables the description of planning domains with time, resources, concurrent activities, mutual exclusions among sets of activities, disjunctive preconditions and conditional effects. We provide a theoretical foundation for the paradigm, based on temporal intervals and attributes. We then show how the plans are naturally expressed by networks of constraints, and show that the process of planning maps directly to dynamic constraint reasoning. In addition, we de ne compatibilities, a compact mechanism for describing planning domains. We describe how this framework can incorporate the use of constraint reasoning technology to improve planning. Finally, we describe EUROPA, an implementation of the CAIP framework.

  20. Temporal control in fixed-interval schedules.

    PubMed

    Zeiler, M D; Powell, D G

    1994-01-01

    The peak procedure was used to study temporal control in pigeons exposed to seven fixed-interval schedules ranging from 7.5 to 480 s. The focus was on behavior in individual intervals. Quantitative properties of temporal control depended on whether the aspect of behavior considered was initial pause duration, the point of maximum acceleration in responding, the point of maximum deceleration, the point at which responding stopped, or several different statistical derivations of a point of maximum responding. Each aspect produced different conclusions about the nature of temporal control, and none conformed to what was known previously about the way ongoing responding was controlled by time under conditions of differential reinforcement. Existing theory does not explain why Weber's law so rarely fit the results or why each type of behavior seemed unique. These data fit with others suggesting that principles of temporal control may depend on the role played by the particular aspect of behavior in particular situations.

  1. Subjective Probability Intervals: How to Reduce Overconfidence by Interval Evaluation

    ERIC Educational Resources Information Center

    Winman, Anders; Hansson, Patrik; Juslin, Peter

    2004-01-01

    Format dependence implies that assessment of the same subjective probability distribution produces different conclusions about over- or underconfidence depending on the assessment format. In 2 experiments, the authors demonstrate that the overconfidence bias that occurs when participants produce intervals for an uncertain quantity is almost…

  2. Generalized Confidence Intervals and Fiducial Intervals for Some Epidemiological Measures

    PubMed Central

    Bebu, Ionut; Luta, George; Mathew, Thomas; Agan, Brian K.

    2016-01-01

    For binary outcome data from epidemiological studies, this article investigates the interval estimation of several measures of interest in the absence or presence of categorical covariates. When covariates are present, the logistic regression model as well as the log-binomial model are investigated. The measures considered include the common odds ratio (OR) from several studies, the number needed to treat (NNT), and the prevalence ratio. For each parameter, confidence intervals are constructed using the concepts of generalized pivotal quantities and fiducial quantities. Numerical results show that the confidence intervals so obtained exhibit satisfactory performance in terms of maintaining the coverage probabilities even when the sample sizes are not large. An appealing feature of the proposed solutions is that they are not based on maximization of the likelihood, and hence are free from convergence issues associated with the numerical calculation of the maximum likelihood estimators, especially in the context of the log-binomial model. The results are illustrated with a number of examples. The overall conclusion is that the proposed methodologies based on generalized pivotal quantities and fiducial quantities provide an accurate and unified approach for the interval estimation of the various epidemiological measures in the context of binary outcome data with or without covariates. PMID:27322305

  3. High resolution time interval meter

    DOEpatents

    Martin, A.D.

    1986-05-09

    Method and apparatus are provided for measuring the time interval between two events to a higher resolution than reliability available from conventional circuits and component. An internal clock pulse is provided at a frequency compatible with conventional component operating frequencies for reliable operation. Lumped constant delay circuits are provided for generating outputs at delay intervals corresponding to the desired high resolution. An initiation START pulse is input to generate first high resolution data. A termination STOP pulse is input to generate second high resolution data. Internal counters count at the low frequency internal clock pulse rate between the START and STOP pulses. The first and second high resolution data are logically combined to directly provide high resolution data to one counter and correct the count in the low resolution counter to obtain a high resolution time interval measurement.

  4. Optimal descriptor as a translator of eclectic data into prediction of cytotoxicity for metal oxide nanoparticles under different conditions.

    PubMed

    Toropova, Alla P; Toropov, Andrey A; Rallo, Robert; Leszczynska, Danuta; Leszczynski, Jerzy

    2015-02-01

    The Monte Carlo technique has been used to build up quantitative structure-activity relationships (QSARs) for prediction of dark cytotoxicity and photo-induced cytotoxicity of metal oxide nanoparticles to bacteria Escherichia coli (minus logarithm of lethal concentration for 50% bacteria pLC50, LC50 in mol/L). The representation of nanoparticles include (i) in the case of the dark cytotoxicity a simplified molecular input-line entry system (SMILES), and (ii) in the case of photo-induced cytotoxicity a SMILES plus symbol '^'. The predictability of the approach is checked up with six random distributions of available data into the visible training and calibration sets, and invisible validation set. The statistical characteristics of these models are correlation coefficient 0.90-0.94 (training set) and 0.73-0.98 (validation set). PMID:25463851

  5. Comparison of two methods of predicting characteristics of an organism which develops under the condition of free fall

    NASA Technical Reports Server (NTRS)

    Brown, A. H.; Dahl, A. O.; Chapman, D. K.; Loercher, L.

    1975-01-01

    Five morphological characteristics of Arabidopsis thaliana were measured on plant populations grown under continuous centrifugation. In separate tests different g-levels were used. For each character studied a linear g-function was calculated and extrapolated to zero-g. In other tests Arabidopsis plants were grown on horizontal clinostats after which the same set of characters was measured. Growth on a clinostat might simulate growth at zero-g; but the zero-g predictions by the two methods did not agree consistently. The results were significantly different for three of the five characters for which comparisons were made. Either the extrapolation method or the clinostat method are considered unreliable as a means of predicting plant growth characteristics in the weightless environment of an earth satellite laboratory.

  6. Predicting crystal structures and properties of matter under extreme conditions via quantum mechanics: the pressure is on.

    PubMed

    Zurek, Eva; Grochala, Wojciech

    2015-02-01

    Experimental studies of compressed matter are now routinely conducted at pressures exceeding 1 mln atm (100 GPa) and occasionally at pressures greater than 10 mln atm (1 TPa). The structure and properties of solids that have been so significantly squeezed differ considerably from those of solids at ambient pressure (1 atm), often leading to new and unexpected physics. Chemical reactivity is also substantially altered in the extreme pressure regime. In this feature paper we describe how synergy between theory and experiment can pave the road towards new experimental discoveries. Because chemical rules-of-thumb established at 1 atm often fail to predict the structures of solids under high pressure, automated crystal structure prediction (CSP) methods are increasingly employed. After outlining the most important CSP techniques, we showcase a few examples from the recent literature that exemplify just how useful theory can be as an aid in the interpretation of experimental data, describe exciting theoretical predictions that are guiding experiment, and discuss when the computational methods that are currently routinely employed fail. Finally, we forecast important problems that will be targeted by theory as theoretical methods undergo rapid development, along with the simultaneous increase of computational power.

  7. Mathematical forecasting methods for predicting lead contents in animal organs on the basis of the environmental conditions.

    PubMed

    Czech, Tomasz; Gambuś, Florian; Wieczorek, Jerzy

    2014-12-01

    The main objective of this study was to determine and describe the lead transfer in the soil-plant-animal system in areas polluted with this metal at varying degrees, with the use of mathematical forecasting methods and data mining tools contained in the Statistica 9.0 software programme. The starting point for the forecasting models comprised results derived from an analysis of different features of soil and plants, collected from 139 locations in an area covering 100km(2) around a lead-zinc ore mining and processing plant ('Boleslaw'), at Bukowno in southern Poland. In addition, the lead content was determined in the tissues and organs of 110 small rodents (mainly mice) caught in the same area. The prediction models, elaborated with the use of classification algorithms, forecasted with high probability the class (range) of pollution in animal tissues and organs with lead, based on various soil and plant properties of the study area. However, prediction models which use multilayer neural networks made it possible to calculate the content of lead (predicted versus measured) in animal tissues and organs with an excellent correlation coefficient.

  8. A conditional predictive p-value to compare a multinomial with an overdispersed multinomial in the analysis of T-cell populations.

    PubMed

    Pei, Qinglin; Zuleger, Cindy L; Macklin, Michael D; Albertini, Mark R; Newton, Michael A

    2014-01-01

    Immunological experiments that record primary molecular sequences of T-cell receptors produce moderate to high-dimensional categorical data, some of which may be subject to extra-multinomial variation caused by technical constraints of cell-based assays. Motivated by such experiments in melanoma research, we develop a statistical procedure for testing the equality of two discrete populations, where one population delivers multinomial data and the other is subject to a specific form of overdispersion. The procedure computes a conditional-predictive p-value by splitting the data set into two, obtaining a predictive distribution for one piece given the other, and using the observed predictive ordinate to generate a p-value. The procedure has a simple interpretation, requires fewer modeling assumptions than would be required of a fully Bayesian analysis, and has reasonable operating characteristics as evidenced empirically and by asymptotic analysis. PMID:24096387

  9. Interval, blocking, and marking effects during the development of schedule-induced drinking in rats.

    PubMed

    Patterson, Angela E; Boakes, Robert A

    2012-07-01

    Schedule-induced drinking (SID) can occur when food-deprived rats are given access to water while receiving pellets on an intermittent reinforcement schedule. These conditions can increase water intake excessively. The possible role of adventitious reinforcement of postpellet drinking was assessed by testing whether response-reinforcer contiguity, the relative predictiveness of a response, and whether it is marked are important in the development of SID. Rats exposed to a short interpellet interval acquired SID most rapidly, with this acquired drinking response maintained when animals were transferred to a longer interpellet interval, thus indicating an easy-to-hard effect (Experiment 1). Further experiments demonstrated that a stimulus (a brief-flashing house light) occurring prior to pellet delivery could block the acquisition of SID (Experiment 2), while a lick-contingent tone, intended to increase the associability of this response, produced more rapid acquisition of SID (Experiment 3). Analysis of lick distributions revealed that licking became concentrated in the first half of an interpellet interval only after several sessions. Overall, the results indicated that similar factors affect the acquisition of both SID and instrumental conditioning with delayed reinforcement, as is consistent with a superstitious conditioning account of SID development.

  10. Sensory Bias Predicts Postural Stability, Anxiety, and Cognitive Performance in Healthy Adults Walking in Novel Discordant Conditions

    NASA Technical Reports Server (NTRS)

    Brady, Rachel A.; Batson, Crystal D.; Peters, Brian T.; Mulavara, Ajitkumar P.; Bloomberg, Jacob J.

    2010-01-01

    We designed a gait training study that presented combinations of visual flow and support surface manipulations to investigate the response of healthy adults to novel discordant sensorimotor conditions. We aimed to determine whether a relationship existed between subjects visual dependence and their scores on a collective measure of anxiety, cognition, and postural stability in a new discordant environment presented at the conclusion of training (Transfer Test). A treadmill was mounted to a motion base platform positioned 2 m behind a large visual screen. Training consisted of three walking sessions, each within a week of the previous visit, that presented four 5-minute exposures to various combinations of support surface and visual scene manipulations, all lateral sinusoids. The conditions were scene translation only, support surface translation only, simultaneous scene and support surface translations in-phase, and simultaneous scene and support surface translations 180 out-of-phase. During the Transfer Test, the trained participants received a 2-minute novel exposure. A visual sinusoidal roll perturbation, with twice the original flow rate, was superimposed on a sinusoidal support surface roll perturbation that was 90 out of phase with the scene. A high correlation existed between normalized torso translation, measured in the scene-only condition at the first visit, and a combined measure of normalized heart rate, stride frequency, and reaction time at the transfer test. Results suggest that visually dependent participants experience decreased postural stability, increased anxiety, and increased reaction times compared to their less visually dependent counterparts when negotiating novel discordant conditions.

  11. Computing confidence intervals for standardized regression coefficients.

    PubMed

    Jones, Jeff A; Waller, Niels G

    2013-12-01

    With fixed predictors, the standard method (Cohen, Cohen, West, & Aiken, 2003, p. 86; Harris, 2001, p. 80; Hays, 1994, p. 709) for computing confidence intervals (CIs) for standardized regression coefficients fails to account for the sampling variability of the criterion standard deviation. With random predictors, this method also fails to account for the sampling variability of the predictor standard deviations. Nevertheless, under some conditions the standard method will produce CIs with accurate coverage rates. To delineate these conditions, we used a Monte Carlo simulation to compute empirical CI coverage rates in samples drawn from 36 populations with a wide range of data characteristics. We also computed the empirical CI coverage rates for 4 alternative methods that have been discussed in the literature: noncentrality interval estimation, the delta method, the percentile bootstrap, and the bias-corrected and accelerated bootstrap. Our results showed that for many data-parameter configurations--for example, sample size, predictor correlations, coefficient of determination (R²), orientation of β with respect to the eigenvectors of the predictor correlation matrix, RX--the standard method produced coverage rates that were close to their expected values. However, when population R² was large and when β approached the last eigenvector of RX, then the standard method coverage rates were frequently below the nominal rate (sometimes by a considerable amount). In these conditions, the delta method and the 2 bootstrap procedures were consistently accurate. Results using noncentrality interval estimation were inconsistent. In light of these findings, we recommend that researchers use the delta method to evaluate the sampling variability of standardized regression coefficients.

  12. Prediction models of silage fermentation products on crop composition under strict anaerobic conditions: a meta-analysis.

    PubMed

    Mogodiniyai Kasmaei, K; Rustas, B-O; Spörndly, R; Udén, P

    2013-10-01

    A meta-analysis was conducted to establish linkages between crop and fermentation variables. Data from well-controlled mini silage studies were used in which no additives had been used and no ingress of air had occurred. The silage set consisted of data on crop chemical composition and epiphytic lactic acid bacteria count, and fermentation products (organic acids, alcohols, and ammonia-N) from 118 silages made from 30 grass, 7 legume, 15 grass and legume mixtures, and 66 whole-crop maize samples. The prediction models for fermentation products on crop variables were obtained by stepwise multiple regression analysis. Perennial forage and maize silages were analyzed separately. The best models were obtained for acetic acid in perennial forage silages, with a coefficient of determination of 0.63, and for lactic acid and ethanol in whole-crop maize silages, with coefficients of determination of 0.84 and 0.61, respectively. Fermentation products of perennial forage and maize silages were best related to dry matter and crude protein contents, respectively. Overall, the prediction equations were weak.

  13. Increase in frailty of older workers and retirees predicted by negative psychosocial working conditions on the job.

    PubMed

    Kalousova, Lucie; Mendes de Leon, Carlos

    2015-01-01

    Well-established evidence has shown that negative psychosocial working conditions adversely affect the health and well-being of prime-age workers, yet little is known about the consequences on the health of older workers. Our article examines the associations between declines in health in later life, measured as frailty, and negative psychosocial working conditions, and considers the role of retirement. We use longitudinal cross-national data collected by SHARE I and SHARE IV and focus on the respondents who were working at baseline. We find that low reward, high effort, effort to reward ratio, and effort to control ratio were all predictors of increasing frailty. The association between low reward and change in frailty was modified by retirement status at follow-up, with nonretired respondents in low-reward jobs experiencing the largest increases in frailty at follow-up. These results suggest that the effect of psychosocial working conditions on physical health may extend well past the prime working age, and retirement may have a protective effect on the health of older workers in low reward jobs. PMID:25489851

  14. Developing a large-scale model to predict the effects of land use and climatic variation on the biological condition of USA streams and rivers

    NASA Astrophysics Data System (ADS)

    Hill, R. A.; Weber, M.; Leibowitz, S. G.; Olsen, A. R.

    2014-12-01

    The US EPA's National Rivers and Streams Assessment (NRSA) uses spatially balanced sampling to estimate the proportion of streams within the continental US (CONUS) that fail to support healthy biological communities. However, to manage these systems, we also must understand how human land use alters stream communities from their natural condition and how natural factors, such as climate, interact with these effects. We used random forest modeling and data from 1353 streams that NRSA determined to be in "good" or "poor" biological condition (BC) to predict the probable BC of nearly 5.4 million km of stream (National Hydrography Dataset) within the CONUS. BC was best predicted by 5 natural factors (mean discharge, mean annual air temperature [AT], soil water content, topography, major ecoregion) and 2 riparian factors that are easily altered by humans (% riparian urbanization [%Urb], % riparian forest [%Fst] cover). The model correctly predicted BC for 74% of sites, but predicted poor BC slightly more accurately (76%) than good BC (71%). Initial results showed that probability of good BC declined rapidly with increasing %Urb, but this effect leveled off in streams with >7 %Urb. Likewise, probability of good BC increased in streams with >45 %Fst. This model can be used to generate hypotheses to guide future research and test restoration scenarios. For example, BC had a U-shaped relationship with AT, with poorest BCs predicted between 10-15°C. Plots suggested a strong AT-%Fst interaction, where higher %Fst values mitigated this U-shaped response of BC to AT. These ATs correspond to latitudes that receive the greatest combination of solar radiation intensity and duration in July, and we hypothesize that thermal alteration due to riparian disturbance may be negatively affecting BC in these streams. Finally, simulations suggested that restoring riparian forests could increase the number of streams achieving good BC by 60%, and may represent a critical management tool.

  15. A predictive model for the influence of food components on survival of Listeria monocytogenes LM 54004 under high hydrostatic pressure and mild heat conditions.

    PubMed

    Gao, Yu-Long; Ju, Xing-Rong; Wu-Ding

    2007-07-15

    The combination of high hydrostatic pressure with mild temperature was explored to achieve a predictive model of microbial inactivation in food matrix processing. The pressure processing conditions were fixed at 448 MPa for 11 min at the treatment temperature of 41 degrees C, which have been determined as the optimum processing conditions considering six log-cycle reductions of Listeria monocytogenes. Based on the results, response surface methodology (RSM) was performed in the present work, the influence of food components like soybean protein (0-5.00%), sucrose (0.25-13.25%), bean oil (0-10.00%), and pH (4-10) of the food matrix on survival of L. monocytogenes by high pressure and mild heat was studied, and a quadratic predictive model for the influence of food components and pH of food matrix on L. monocytogenes reduction by high pressure and mild heat was built with RSM accurately. The experimental results showed that the efficiency of L. monocytogenes reduction in milk buffer and food matrix designed in the present work, under the HPP treatment process parameters described above, were different. The soybean protein (P=0.0086), sucrose (P<0.0001), and pH (P=0.0136) significantly affected reduction of L. monocytogenes, but the effect of bean oil on reduction of L. monocytogenes was not significant (P=0.1028). The predictive model is significant since the level of significance was P<0.0001 and the calculated F value (11.53) is much greater than the tabulated F value (F(0.01 (14, 5))=9.77). Moreover, the adequacy of the predictive model equation for predicting the level of L. monocytogenes reduction was verified effectively by the validation data.

  16. Improving prediction of conditions that modulate dengue fever risks in Yucatán, México.

    NASA Astrophysics Data System (ADS)

    Laureano-Rosario, A. E.; Garcia-Rejon, J. E.; Gomez-Carro, S.; Farfan-Ale, J.; Muller-Karger, F. E.

    2015-12-01

    Accurately predicting vector-borne diseases is essential for communities everywhere around the world. Yet this is a difficult task, even in areas where annual epidemics occur. The primary vector for dengue virus disease (DENV) is Aedes aegypti. This is a tropical-subtropical mosquito that proliferates in urban areas. Precipitation and increased temperatures are known to promote growth, reproduction and transmission of DENV. This study assesses potential health risks on coastal communities in the northwest Yucatan Peninsula, Mexico. We studied the relation between DENV incidences and environmental data. We hypothesized that environmental parameters such as rainfall, sea surface temperature (SST), air temperature, humidity, and past DENV cases are the primary drivers of DENV incidences. We collected DENV data from the National Health Information System and demographic data from the National Institute of Statistics and Geography. Precipitation and air temperature were obtained from the National Water Commission. SST was derived from the NOAA Advanced Very High Resolution Radiometer (AVHRR) satellite sensor. In addition, incidence of DENV cases per year was calculated. Multiple regression analyses show that previous DENV cases, minimum air temperature, humidity, and precipitation are positively related to DENV cases and explain 82% of the variation, with 77% explained by previous DENV cases (cases that took place 2-weeks before the target). A second regression model without the previous DENV cases showed 30% of the variation explained by humidity and precipitation (p<0.05). Satellite-derived SST was also included to test whether the percent variation of DENV explained increased. These results imply that if these environmental variables continue to increase with time, the trend of DENV cases will also increase. This study suggests that it is possible to significantly improve DENV prevention and prediction of potential outcomes in Yucatan using remote sensing data.

  17. Mathematical prediction of imidacloprid persistence in two Croatian soils with different texture, organic matter content and acidity under laboratory conditions.

    PubMed

    Broznić, Dalibor; Milin, Čedomila

    2013-01-01

    In the present laboratory study, persistence of imidacloprid (IMI) as a function of initial insecticide concentration and soil properties in two Croatian soils (Krk sandy clay and Istria clay soils) was studied and described mathematically. Upon fitting the obtained experimental data for the higher concentration level (5 mg/kg) to mathematical models, statistical parameters (R (2), scaled root mean squared error and χ (2) error) indicated that the single first-order kinetics model provided the best prediction of IMI degradation in the Krk sandy clay soil, while in the Istria clay soil biphasic degradation was observed. At the lower concentration level (0.5 mg/kg), the biphasic models Gustafson and Holden models as well as the first-order double exponential model fitted the best experimental data in both soils. The disappearance time (DT50) values estimated by the single first-order double exponential model (from 50 to 132 days) proved that IMI can be categorized as a moderately persistent pesticide. In the Krk sandy clay soil, resulting DT50 values tended to increase with an increase of initial IMI concentration, while in the Istria clay soil, IMI persistence did not depend on the concentration. Organic matter of both experimental soils provided an accelerating effect on the degradation rate. The logistic model demonstrated that the effect of microbial activity was not the most important parameter for the biodegradation of IMI in the Istria clay soil, where IMI degradation could be dominated by chemical processes, such as chemical hydrolysis. The results pointed that mathematical modeling could be considered as the most convenient tool for predicting IMI persistence and contributes to the establishment of adequate monitoring of IMI residues in contaminated soil. Furthermore, IMI usage should be strictly controlled, especially in soils with low organic matter content where the risk of soil and groundwater contamination is much higher due to its longer

  18. Predicting laser-induced bulk damage and conditioning for deuterated potassium di-hydrogen phosphate crystals using ADM (absorption distribution model)

    SciTech Connect

    Liao, Z M; Spaeth, M L; Manes, K; Adams, J J; Carr, C W

    2010-02-26

    We present an empirical model that describes the experimentally observed laser-induced bulk damage and conditioning behavior in deuterated Potassium dihydrogen Phosphate (DKDP) crystals in a self-consistent way. The model expands on an existing nanoabsorber precursor model and the multi-step absorption mechanism to include two populations of absorbing defects, one with linear absorption and another with nonlinear absorption. We show that this model connects previously uncorrelated small-beam damage initiation probability data to large-beam damage density measurements over a range of ns pulse widths relevant to ICF lasers such as the National Ignition Facility (NIF). In addition, this work predicts the damage behavior of laser-conditioned DKDP and explains the upper limit to the laser conditioning effect. The ADM model has been successfully used during the commissioning and early operation of the NIF.

  19. Improved central confidence intervals for the ratio of Poisson means

    NASA Astrophysics Data System (ADS)

    Cousins, R. D.

    The problem of confidence intervals for the ratio of two unknown Poisson means was "solved" decades ago, but a closer examination reveals that the standard solution is far from optimal from the frequentist point of view. We construct a more powerful set of central confidence intervals, each of which is a (typically proper) subinterval of the corresponding standard interval. They also provide upper and lower confidence limits which are more restrictive than the standard limits. The construction follows Neyman's original prescription, though discreteness of the Poisson distribution and the presence of a nuisance parameter (one of the unknown means) lead to slightly conservative intervals. Philosophically, the issue of the appropriateness of the construction method is similar to the issue of conditioning on the margins in 2×2 contingency tables. From a frequentist point of view, the new set maintains (over) coverage of the unknown true value of the ratio of means at each stated confidence level, even though the new intervals are shorter than the old intervals by any measure (except for two cases where they are identical). As an example, when the number 2 is drawn from each Poisson population, the 90% CL central confidence interval on the ratio of means is (0.169, 5.196), rather than (0.108, 9.245). In the cited literature, such confidence intervals have applications in numerous branches of pure and applied science, including agriculture, wildlife studies, manufacturing, medicine, reliability theory, and elementary particle physics.

  20. Seasonal Prediction of Hydro-Climatic Extremes in the Greater Horn of Africa Under Evolving Climate Conditions to Support Adaptation Strategies

    NASA Astrophysics Data System (ADS)

    Tadesse, T.; Zaitchik, B. F.; Habib, S.; Funk, C. C.; Senay, G. B.; Dinku, T.; Policelli, F. S.; Block, P.; Baigorria, G. A.; Beyene, S.; Wardlow, B.; Hayes, M. J.

    2014-12-01

    The development of effective strategies to adapt to changes in the character of droughts and floods in Africa will rely on improved seasonal prediction systems that are robust to an evolving climate baseline and can be integrated into disaster preparedness and response. Many efforts have been made to build models to improve seasonal forecasts in the Greater Horn of Africa region (GHA) using satellite and climate data, but these efforts and models must be improved and translated into future conditions under evolving climate conditions. This has considerable social significance, but is challenged by the nature of climate predictability and the adaptability of coupled natural and human systems facing exposure to climate extremes. To address these issues, work is in progress under a project funded by NASA. The objectives of the project include: 1) Characterize and explain large-scale drivers in the ocean-atmosphere-land system associated with years of extreme flood or drought in the GHA. 2) Evaluate the performance of state-of-the-art seasonal forecast methods for prediction of decision-relevant metrics of hydrologic extremes. 3) Apply seasonal forecast systems to prediction of socially relevant impacts on crops, flood risk, and economic outcomes, and assess the value of these predictions to decision makers. 4) Evaluate the robustness of seasonal prediction systems to evolving climate conditions. The National Drought Mitigation Center (University of Nebraska-Lincoln, USA) is leading this project in collaboration with the USGS, Johns Hopkins University, University of Wisconsin-Madison, the International Research Institute for Climate and Society, NASA, and GHA local experts. The project is also designed to have active engagement of end users in various sectors, university researchers, and extension agents in GHA through workshops and/or webinars. This project is expected improve and implement new and existing climate- and remote sensing-based agricultural

  1. A method for accounting for maintenance costs in flux balance analysis improves the prediction of plant cell metabolic phenotypes under stress conditions.

    PubMed

    Cheung, C Y Maurice; Williams, Thomas C R; Poolman, Mark G; Fell, David A; Ratcliffe, R George; Sweetlove, Lee J

    2013-09-01

    Flux balance models of metabolism generally utilize synthesis of biomass as the main determinant of intracellular fluxes. However, the biomass constraint alone is not sufficient to predict realistic fluxes in central heterotrophic metabolism of plant cells because of the major demand on the energy budget due to transport costs and cell maintenance. This major limitation can be addressed by incorporating transport steps into the metabolic model and by implementing a procedure that uses Pareto optimality analysis to explore the trade-off between ATP and NADPH production for maintenance. This leads to a method for predicting cell maintenance costs on the basis of the measured flux ratio between the oxidative steps of the oxidative pentose phosphate pathway and glycolysis. We show that accounting for transport and maintenance costs substantially improves the accuracy of fluxes predicted from a flux balance model of heterotrophic Arabidopsis cells in culture, irrespective of the objective function used in the analysis. Moreover, when the new method was applied to cells under control, elevated temperature and hyper-osmotic conditions, only elevated temperature led to a substantial increase in cell maintenance costs. It is concluded that the hyper-osmotic conditions tested did not impose a metabolic stress, in as much as the metabolic network is not forced to devote more resources to cell maintenance.

  2. Mathematical prediction of imidacloprid persistence in two Croatian soils with different texture, organic matter content and acidity under laboratory conditions.

    PubMed

    Broznić, Dalibor; Milin, Čedomila

    2013-01-01

    In the present laboratory study, persistence of imidacloprid (IMI) as a function of initial insecticide concentration and soil properties in two Croatian soils (Krk sandy clay and Istria clay soils) was studied and described mathematically. Upon fitting the obtained experimental data for the higher concentration level (5 mg/kg) to mathematical models, statistical parameters (R (2), scaled root mean squared error and χ (2) error) indicated that the single first-order kinetics model provided the best prediction of IMI degradation in the Krk sandy clay soil, while in the Istria clay soil biphasic degradation was observed. At the lower concentration level (0.5 mg/kg), the biphasic models Gustafson and Holden models as well as the first-order double exponential model fitted the best experimental data in both soils. The disappearance time (DT50) values estimated by the single first-order double exponential model (from 50 to 132 days) proved that IMI can be categorized as a moderately persistent pesticide. In the Krk sandy clay soil, resulting DT50 values tended to increase with an increase of initial IMI concentration, while in the Istria clay soil, IMI persistence did not depend on the concentration. Organic matter of both experimental soils provided an accelerating effect on the degradation rate. The logistic model demonstrated that the effect of microbial activity was not the most important parameter for the biodegradation of IMI in the Istria clay soil, where IMI degradation could be dominated by chemical processes, such as chemical hydrolysis. The results pointed that mathematical modeling could be considered as the most convenient tool for predicting IMI persistence and contributes to the establishment of adequate monitoring of IMI residues in contaminated soil. Furthermore, IMI usage should be strictly controlled, especially in soils with low organic matter content where the risk of soil and groundwater contamination is much higher due to its longer

  3. Predictive adaptive responses: Condition-dependent impact of adult nutrition and flight in the tropical butterfly Bicyclus anynana.

    PubMed

    Saastamoinen, Marjo; van der Sterren, Dominique; Vastenhout, Nienke; Zwaan, Bas J; Brakefield, Paul M

    2010-12-01

    The experience of environmental stress during development can substantially affect an organism's life history. These effects are often mainly negative, but a growing number of studies suggest that under certain environmental conditions early experience of such stress may yield individuals that are less sensitive to environmental stress later on in life. We used the butterfly Bicyclus anynana to study the effects of limited larval and adult food and forced flight on individual performance measured as reproduction and adult life span. Larvae exposed to food stress showed longer development and produced smaller adults. Thus, they were not able to fully compensate for the food deprivation during development. Females that experienced food stress during development did not increase tolerance for adult food limitation. However, females exposed to food stress during development coped better with forced flight compared with the control group. The apparent absence of costs of flight in poor-quality females may be a by-product of an altered body allocation, as females experiencing both food stress treatments had increased thorax ratios, compared with controls, and increased flight performances. The results reveal an important plasticity component to variation in flight performance and suggest that the cost of flight depends on an individual's internal condition.

  4. Application of Interval Predictor Models to Space Radiation Shielding

    NASA Technical Reports Server (NTRS)

    Crespo, Luis G.; Kenny, Sean P.; Giesy,Daniel P.; Norman, Ryan B.; Blattnig, Steve R.

    2016-01-01

    This paper develops techniques for predicting the uncertainty range of an output variable given input-output data. These models are called Interval Predictor Models (IPM) because they yield an interval valued function of the input. This paper develops IPMs having a radial basis structure. This structure enables the formal description of (i) the uncertainty in the models parameters, (ii) the predicted output interval, and (iii) the probability that a future observation would fall in such an interval. In contrast to other metamodeling techniques, this probabilistic certi cate of correctness does not require making any assumptions on the structure of the mechanism from which data are drawn. Optimization-based strategies for calculating IPMs having minimal spread while containing all the data are developed. Constraints for bounding the minimum interval spread over the continuum of inputs, regulating the IPMs variation/oscillation, and centering its spread about a target point, are used to prevent data over tting. Furthermore, we develop an approach for using expert opinion during extrapolation. This metamodeling technique is illustrated using a radiation shielding application for space exploration. In this application, we use IPMs to describe the error incurred in predicting the ux of particles resulting from the interaction between a high-energy incident beam and a target.

  5. Simulation of Interval Censored Data in Medical and Biological Studies

    NASA Astrophysics Data System (ADS)

    Kiani, Kaveh; Arasan, Jayanthi

    This research looks at the simulation of interval censored data when the survivor function of the survival time is known and attendance probability of the subjects for follow-ups can take any number between 0 to 1. Interval censored data often arise in the medical and biological follow-up studies where the event of interest occurs somewhere between two known times. Regardless of the methods used to analyze these types of data, simulation of interval censored data is an important and challenging step toward model building and prediction of survival time. The simulation itself is rather tedious and very computer intensive due to the interval monitoring of subjects at prescheduled times and subject's incomplete attendance to follow-ups. In this paper the simulated data by the proposed method were assessed using the bias, standard error and root mean square error (RMSE) of the parameter estimates where the survival time T is assumed to follow the Gompertz distribution function.

  6. Predictive variables for the occurrence of early clinical mastitis in primiparous Holstein cows under field conditions in France.

    PubMed Central

    Barnouin, J; Chassagne, M

    2001-01-01

    Holstein heifers from 47 dairy herds in France were enrolled in a field study to determine predictors for clinical mastitis within the first month of lactation. Precalving and calving variables (biochemical, hematological, hygienic, and disease indicators) were collected. Early clinical mastitis (ECM) predictive variables were analyzed by using a multiple logistic regression model (99 cows with ECM vs. 571 without clinical mastitis throughout the first lactation). Two variables were associated with a higher risk of ECM: a) difficult calving and b) medium and high white blood cell (WBC) counts in late gestation. Two prepartum indicators were associated with a lower ECM risk: a) medium and high serum concentrations of immunoglobulin G1 (IgG1) and b) high percentage of eosinophils among white blood cells. Calving difficulty and certain biological blood parameters (IgG1, eosinophils) could represent predictors that would merit further experimental studies, with the aim of designing programs for reducing the risk of clinical mastitis in the first lactation. PMID:11195522

  7. Prediction of future asset prices

    NASA Astrophysics Data System (ADS)

    Seong, Ng Yew; Hin, Pooi Ah; Ching, Soo Huei

    2014-12-01

    This paper attempts to incorporate trading volumes as an additional predictor for predicting asset prices. Denoting r(t) as the vector consisting of the time-t values of the trading volume and price of a given asset, we model the time-(t+1) asset price to be dependent on the present and l-1 past values r(t), r(t-1), ....., r(t-1+1) via a conditional distribution which is derived from a (2l+1)-dimensional power-normal distribution. A prediction interval based on the 100(α/2)% and 100(1-α/2)% points of the conditional distribution is then obtained. By examining the average lengths of the prediction intervals found by using the composite indices of the Malaysia stock market for the period 2008 to 2013, we found that the value 2 appears to be a good choice for l. With the omission of the trading volume in the vector r(t), the corresponding prediction interval exhibits a slightly longer average length, showing that it might be desirable to keep trading volume as a predictor. From the above conditional distribution, the probability that the time-(t+1) asset price will be larger than the time-t asset price is next computed. When the probability differs from 0 (or 1) by less than 0.03, the observed time-(t+1) increase in price tends to be negative (or positive). Thus the above probability has a good potential of being used as a market indicator in technical analysis.

  8. An Event Restriction Interval Theory of Tense

    ERIC Educational Resources Information Center

    Beamer, Brandon Robert

    2012-01-01

    This dissertation presents a novel theory of tense and tense-like constructions. It is named after a key theoretical component of the theory, the event restriction interval. In Event Restriction Interval (ERI) Theory, sentences are semantically evaluated relative to an index which contains two key intervals, the evaluation interval and the event…

  9. Costs, effects and implementation of routine data emergency admission risk prediction models in primary care for patients with, or at risk of, chronic conditions: a systematic review protocol

    PubMed Central

    Kingston, Mark Rhys; Evans, Bridie Angela; Nelson, Kayleigh; Hutchings, Hayley; Russell, Ian

    2016-01-01

    Introduction Emergency admission risk prediction models are increasingly used to identify patients, typically with one or more chronic conditions, for proactive management in primary care to avoid admissions, save costs and improve patient experience. Aim To identify and review the published evidence on the costs, effects and implementation of emergency admission risk prediction models in primary care for patients with, or at risk of, chronic conditions. Methods We shall search for studies of healthcare interventions using routine data-generated emergency admission risk models. We shall report: the effects on emergency admissions and health costs; clinician and patient views; and implementation findings. We shall search ASSIA, CINAHL, the Cochrane Library, HMIC, ISI Web of Science, MEDLINE and Scopus from 2005, review references in and citations of included articles, search key journals and contact experts. Study selection, data extraction and quality assessment will be performed by two independent reviewers. Ethics and dissemination No ethical permissions are required for this study using published data. Findings will be disseminated widely, including publication in a peer-reviewed journal and through conferences in primary and emergency care and chronic conditions. We judge our results will help a wide audience including primary care practitioners and commissioners, and policymakers. Trial registration number CRD42015016874; Pre-results. PMID:26932140

  10. Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions.

    PubMed

    Zuñiga, Cristal; Li, Chien-Ting; Huelsman, Tyler; Levering, Jennifer; Zielinski, Daniel C; McConnell, Brian O; Long, Christopher P; Knoshaug, Eric P; Guarnieri, Michael T; Antoniewicz, Maciek R; Betenbaugh, Michael J; Zengler, Karsten

    2016-09-01

    The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. PMID:27372244

  11. Fouling resistance prediction using artificial neural network nonlinear auto-regressive with exogenous input model based on operating conditions and fluid properties correlations

    NASA Astrophysics Data System (ADS)

    Biyanto, Totok R.

    2016-06-01

    Fouling in a heat exchanger in Crude Preheat Train (CPT) refinery is an unsolved problem that reduces the plant efficiency, increases fuel consumption and CO2 emission. The fouling resistance behavior is very complex. It is difficult to develop a model using first principle equation to predict the fouling resistance due to different operating conditions and different crude blends. In this paper, Artificial Neural Networks (ANN) MultiLayer Perceptron (MLP) with input structure using Nonlinear Auto-Regressive with eXogenous (NARX) is utilized to build the fouling resistance model in shell and tube heat exchanger (STHX). The input data of the model are flow rates and temperatures of the streams of the heat exchanger, physical properties of product and crude blend data. This model serves as a predicting tool to optimize operating conditions and preventive maintenance of STHX. The results show that the model can capture the complexity of fouling characteristics in heat exchanger due to thermodynamic conditions and variations in crude oil properties (blends). It was found that the Root Mean Square Error (RMSE) are suitable to capture the nonlinearity and complexity of the STHX fouling resistance during phases of training and validation.

  12. ATM gene single nucleotide polymorphisms predict regimen-related gastrointestinal toxicity in patients allografted after reduced conditioning.

    PubMed

    Kuba, Adam; Raida, Ludek; Mrazek, Frantisek; Schneiderova, Petra; Kriegova, Eva; Furst, Tomas; Furstova, Jana; Faber, Edgar; Ambruzova, Zuzana; Papajik, Tomas

    2015-06-01

    Polymorphisms of genes involved in innate and adaptive immunity have become an object of major interest in regard to hematopoietic stem cell transplantation (HSCT) complications. Regimen-related gastrointestinal toxicity (RR-GIT) is the dominant complication during the pre-engraftment period and has been linked to increased risk of graft-versus-host disease (GVHD) development. According to our hypothesis, functional variants of genes participating in DNA damage response (DDR) may have an impact on the extent of tissue damage caused by the conditioning regimen. In our single-center study, we analyzed 62 patients who underwent HSCT from HLA-identical donors after reduced conditioning. The patients were genotyped for 5 single nucleotide polymorphisms (SNPs, rs4585 T/G, rs189037 A/G, rs227092 T/G, rs228590 C/T, and rs664677 T/C) of the ATM gene-the essential member of the DDR pathways, using allele-specific matrix-assisted laser desorption/ionization, time-of-flight (MALDI-TOF) mass spectrometry assay. Because of almost absolute linkage disequilibrium observed among all 5 SNPs, association of 2 major ATM haplotypes (ATM1/ATM2) with RR-GIT and acute GVHD (aGVHD) was analyzed. Importantly, the univariate and multivariate analysis showed that patients homozygous for ATM2 haplotype (rs4585*T, rs189037*A, rs227092*T, rs228590*C, and rs664677*T) are more likely to suffer from high-grade RR-GIT than ATM1 homozygous patients. The association with aGVHD was not significant. To our knowledge, this is the first report showing the ATM gene variability in relation to RR-GIT in the allogeneic HSCT setting.

  13. Usefulness of a large field of view sensor for physicochemical, textural, and yield predictions under industrial goat cheese (Murcia al Vino) manufacturing conditions.

    PubMed

    Rovira, S; García, V; Ferrandini, E; Carrión, J; Castillo, M; López, M B

    2012-11-01

    The applicability of a light backscatter sensor with a large field of view was tested for on-line monitoring of coagulation and syneresis in a goat cheese (Murcia al Vino) manufactured under industrial conditions. Cheesemaking was carried out concurrently in a 12-L pilot vat and a 10,000-L industrial vat following the normal cheesemaking protocol. Cheese moisture, whey fat content, hardness, springiness, and adhesiveness were measured during syneresis. The results obtained show that cutting time is best predicted by considering the coagulation ratio at the inflection point and the percentage increase in the ratio during coagulation, with no need for the first derivative. The large field of view reflectance ratio provided good results for the prediction of moisture content, yield, hardness, springiness, and adhesiveness of the final cheese.

  14. The use of laboratory scale reactors to predict sensitivity to changes in operating conditions for full-scale anaerobic digestion treating municipal sewage sludge.

    PubMed

    McLeod, James D; Othman, Maazuza Z; Beale, David J; Joshi, Deepak

    2015-01-01

    Anaerobic digestion of sewage sludge is highly complex and prone to inhibition, which can cause major issues for digester operators. The result is that there have been numerous investigations into changes in operational conditions, however to date all have focused on the qualitative sensitivities, neglecting the quantitative. This study therefore aimed to determine the quantitative sensitivities by using factorial design of experiments and small semi continuous reactors. Analysis showed total and volatile solids removals are chiefly influenced by retention time, with 79% and 59% of the observed results being attributed to retention time respectively, whereas biogas was mainly influenced by loading rate, 38%, and temperature, 22%. Notably the regression model fitted to the experimental data predicted full-scale performance with a high level of precision, indicating that small reactors are subject to the same sensitivity of full-scale digesters and thus can be used to predict changes loading, retention time, and temperature.

  15. Benthic invertebrates and periphyton in the Elwha river basin: Current conditions and predicted response to dam removal

    USGS Publications Warehouse

    Morley, S.A.; Duda, J.J.; Coe, H.J.; Kloehn, K.K.; McHenry, M.L.

    2008-01-01

    The impending removal of two dams on the Elwha River in Washington State offers a unique opportunity to study ecosystem restoration at a watershed scale. We examine how periphyton and benthic invertebrate assemblages vary across regulated and unregulated sections of the Elwha River and across different habitat types, and establish baseline data for tracking future changes following dam removal. We collected multiple years of data on physical habitat, water chemistry, periphyton, and benthic invertebrates from 52 sites on the Elwha River and a reference section on the Quinault River, a neighboring basin. We found that substrate in regulated river sections was coarser and less heterogeneous in size than in unregulated sections, and summer water temperature and specific conductivity higher. Periphyton biomass was also consistently higher in regulated than unregulated sections. Benthic invertebrate assemblage structure at sites above both dams was distinct from sites between and below the dams, due in large part to dominance of mayfly taxa compared to higher relative abundance of midges and non-insect taxa at downstream sites. Following dam removal, we anticipate that both periphyton and benthic invertebrate abundance and diversity will temporarily decrease between and below dams as a result of sediment released from behind the reservoirs. Over the long-term, increased floodplain heterogeneity and recolonization by anadromous fish will alter benthic invertebrate and periphyton assemblages via increases in niche diversity and inputs of marine-derived nutrients. The extended timeline predicted for Elwha River recovery and the complexities of forecasting ecological response highlights the need for more long-term assessments of dam removal and river restoration practices.

  16. Computational tool for risk assessment of nanomaterials: novel QSTR-perturbation model for simultaneous prediction of ecotoxicity and cytotoxicity of uncoated and coated nanoparticles under multiple experimental conditions.

    PubMed

    Kleandrova, Valeria V; Luan, Feng; González-Díaz, Humberto; Ruso, Juan M; Speck-Planche, Alejandro; Cordeiro, M Natália D S

    2014-12-16

    Nanomaterials have revolutionized modern science and technology due to their multiple applications in engineering, physics, chemistry, and biomedicine. Nevertheless, the use and manipulation of nanoparticles (NPs) can bring serious damages to living organisms and their ecosystems. For this reason, ecotoxicity and cytotoxicity assays are of special interest in order to determine the potential harmful effects of NPs. Processes based on ecotoxicity and cytotoxicity tests can significantly consume time and financial resources. In this sense, alternative approaches such as quantitative structure-activity/toxicity relationships (QSAR/QSTR) modeling have provided important insights for the better understanding of the biological behavior of NPs that may be responsible for causing toxicity. Until now, QSAR/QSTR models have predicted ecotoxicity or cytotoxicity separately against only one organism (bioindicator species or cell line) and have not reported information regarding the quantitative influence of characteristics other than composition or size. In this work, we developed a unified QSTR-perturbation model to simultaneously probe ecotoxicity and cytotoxicity of NPs under different experimental conditions, including diverse measures of toxicities, multiple biological targets, compositions, sizes and conditions to measure those sizes, shapes, times during which the biological targets were exposed to NPs, and coating agents. The model was created from 36488 cases (NP-NP pairs) and exhibited accuracies higher than 98% in both training and prediction sets. The model was used to predict toxicities of several NPs that were not included in the original data set. The results of the predictions suggest that the present QSTR-perturbation model can be employed as a highly promising tool for the fast and efficient assessment of ecotoxicity and cytotoxicity of NPs.

  17. The predictive value of ICD-10 diagnostic coding used to assess Charlson comorbidity index conditions in the population-based Danish National Registry of Patients

    PubMed Central

    2011-01-01

    Background The Charlson comorbidity index is often used to control for confounding in research based on medical databases. There are few studies of the accuracy of the codes obtained from these databases. We examined the positive predictive value (PPV) of the ICD-10 diagnostic coding in the Danish National Registry of Patients (NRP) for the 19 Charlson conditions. Methods Among all hospitalizations in Northern Denmark between 1 January 1998 and 31 December 2007 with a first-listed diagnosis of a Charlson condition in the NRP, we selected 50 hospital contacts for each condition. We reviewed discharge summaries and medical records to verify the NRP diagnoses, and computed the PPV as the proportion of confirmed diagnoses. Results A total of 950 records were reviewed. The overall PPV for the 19 Charlson conditions was 98.0% (95% CI; 96.9, 98.8). The PPVs ranged from 82.0% (95% CI; 68.6%, 91.4%) for diabetes with diabetic complications to 100% (one-sided 97.5% CI; 92.9%, 100%) for congestive heart failure, peripheral vascular disease, chronic pulmonary disease, mild and severe liver disease, hemiplegia, renal disease, leukaemia, lymphoma, metastatic tumour, and AIDS. Conclusion The PPV of NRP coding of the Charlson conditions was consistently high. PMID:21619668

  18. A new method for wavelength interval selection that intelligently optimizes the locations, widths and combinations of the intervals.

    PubMed

    Deng, Bai-Chuan; Yun, Yong-Huan; Ma, Pan; Lin, Chen-Chen; Ren, Da-Bing; Liang, Yi-Zeng

    2015-03-21

    In this study, a new algorithm for wavelength interval selection, known as interval variable iterative space shrinkage approach (iVISSA), is proposed based on the VISSA algorithm. It combines global and local searches to iteratively and intelligently optimize the locations, widths and combinations of the spectral intervals. In the global search procedure, it inherits the merit of soft shrinkage from VISSA to search the locations and combinations of informative wavelengths, whereas in the local search procedure, it utilizes the information of continuity in spectroscopic data to determine the widths of wavelength intervals. The global and local search procedures are carried out alternatively to realize wavelength interval selection. This method was tested using three near infrared (NIR) datasets. Some high-performing wavelength selection methods, such as synergy interval partial least squares (siPLS), moving window partial least squares (MW-PLS), competitive adaptive reweighted sampling (CARS), genetic algorithm PLS (GA-PLS) and interval random frog (iRF), were used for comparison. The results show that the proposed method is very promising with good results both on prediction capability and stability. The MATLAB codes for implementing iVISSA are freely available on the website: .

  19. Weather conditions and visits to the medical wing of emergency rooms in a metropolitan area during the warm season in Israel: a predictive model

    NASA Astrophysics Data System (ADS)

    Novikov, Ilya; Kalter-Leibovici, Ofra; Chetrit, Angela; Stav, Nir; Epstein, Yoram

    2012-01-01

    Global climate changes affect health and present new challenges to healthcare systems. The aim of the present study was to analyze the pattern of visits to the medical wing of emergency rooms (ERs) in public hospitals during warm seasons, and to develop a predictive model that will forecast the number of visits to ERs 2 days ahead. Data on daily visits to the ERs of the four largest medical centers in the Tel-Aviv metropolitan area during the warm months of the year (April-October, 2001-2004), the corresponding daily meteorological data, daily electrical power consumption (a surrogate marker for air-conditioning), air-pollution parameters, and calendar information were obtained and used in the analyses. The predictive model employed a time series analysis with transitional Poisson regression. The concise multivariable model was highly accurate ( r 2 = 0.819). The contribution of mean daily temperature was small but significant: an increase of 1°C in ambient temperature was associated with a 1.47% increase in the number of ER visits ( P < 0.001). An increase in electrical power consumption significantly attenuated the effect of weather conditions on ER visits by 4% per 1,000 MWh ( P < 0.001). Higher daily mean SO2 concentrations were associated with a greater number of ER visits (1% per 1 ppb increment; P = 0.017). Calendar data were the main predictors of ER visits ( r 2 = 0.794). The predictive model was highly accurate in forecasting the number of visits to ERs 2 days ahead. The marginal effect of temperature on the number of ER visits can be attributed to behavioral adaptations, including the use of air-conditioning.

  20. Sport-Specific Conditioning Variables Predict Offensive and Defensive Performance in High-Level Youth Water Polo Athletes.

    PubMed

    Sekulic, Damir; Kontic, Dean; Esco, Michael R; Zenic, Natasa; Milanovic, Zoran; Zvan, Milan

    2016-05-01

    Specific-conditioning capacities (SCC) are known to be generally important in water polo (WP), yet the independent associations to offensive and defensive performance is unknown. This study aimed to determine whether offense and defense abilities in WP were independently associated with SCC and anthropometrics. The participants were 82 high-level male youth WP players (all 17-19 years of age; body height, 186.3 ± 6.07 cm; body mass, 84.8 ± 9.6 kg). The independent variables were body height and body mass, and 5 sport-specific fitness tests: sprint swimming over 15 meters; 4 × 50-meter anaerobic-endurance test; vertical in-water-jump; maximum intensity isometric force in upright swimming using an eggbeater kick; and test of throwing velocity. The 6 dependent variables comprised parameters of defensive and offensive performance, such as polyvalence, i.e., ability to play on different positions in defensive tasks (PD) and offensive tasks (PO), efficacy in primary playing position in defensive (ED) and offensive (EO) tasks, and agility in defensive (AD) and offensive (AO) tasks. Analyses showed appropriate reliability for independent (intraclass coefficient of 0.82-0.91) and dependent variables (Cronbach alpha of 0.81-0.95). Multiple regressions were significant for ED (R = 0.25; p < 0.01), EO (R = 0.21; p < 0.01), AD (R = 0.40; p < 0.01), and AO (R = 0.35; p < 0.01). Anaerobic-swimming performance was positively related to AD (β = -0.26; p ≤ 0.05), whereas advanced sprint swimming was related to better AO (β = -0.38; p ≤ 0.05). In-water-jumping performance held the significant positive relationship to EO (β = 0.31; p ≤ 0.05), ED (β = 0.33; p ≤ 0.05), and AD (β = 0.37; p ≤ 0.05). Strength and conditioning professionals working in WP should be aware of established importance of SCC in performing unique duties in WP. The SCC should be specifically developed to meet the needs of offensive and defensive performance in young WP athletes.

  1. Lifetime and failure strain prediction for material subjected to non-stationary tensile loading conditions: applications to Zircaloy - 4. [Monkman-Grant relationship

    SciTech Connect

    Bocek, M.

    1982-01-01

    The life fraction rule (LFR) is used to calculate the lifetime of materials subjected to stress and temperature ramp loading. The solutions for the individual nonstationary temperature and stress loading conditions can be applied to predict also the lifetime of structures loaded by superimposed ramps solely on the basis of normal 'iso'-stress rupture data. The concept is applied to tensional stress and temperature cycling as well. As compared with the peculiarities of the problem, the agreement between experiments and calculations is encouraging. 16 refs.

  2. Development of methods for predicting large crack growth in elastic-plastic work-hardening materials in fully plastic conditions

    NASA Technical Reports Server (NTRS)

    Ford, Hugh; Turner, C. E.; Fenner, R. T.; Curr, R. M.; Ivankovic, A.

    1995-01-01

    The objects of the first, exploratory, stage of the project were listed as: (1) to make a detailed and critical review of the Boundary Element method as already published and with regard to elastic-plastic fracture mechanics, to assess its potential for handling present concepts in two-dimensional and three-dimensional cases. To this was subsequently added the Finite Volume method and certain aspects of the Finite Element method for comparative purposes; (2) to assess the further steps needed to apply the methods so far developed to the general field, covering a practical range of geometries, work hardening materials, and composites: to consider their application under higher temperature conditions; (3) to re-assess the present stage of development of the energy dissipation rate, crack tip opening angle and J-integral models in relation to the possibilities of producing a unified technology with the previous two items; and (4) to report on the feasibility and promise of this combined approach and, if appropriate, make recommendations for the second stage aimed at developing a generalized crack growth technology for its application to real-life problems.

  3. Estradiol levels in women predict skin conductance response but not valence and expectancy ratings in conditioned fear extinction.

    PubMed

    White, Emily C; Graham, Bronwyn M

    2016-10-01

    Anxiety disorders are more prevalent in women than men. One contributing factor may be the sex hormone estradiol, which is known to impact the long term recall of conditioned fear extinction, a laboratory procedure that forms the basis of exposure therapy for anxiety disorders. To date, the literature examining estradiol and fear extinction in humans has focused primarily on physiological measures of fear, such as skin conductance response (SCR) and fear potentiated startle. This is surprising, given that models of anxiety identify at least three important components: physiological symptoms, cognitive beliefs, and avoidance behavior. To help address this gap, we exposed women with naturally high (n=20) or low estradiol (n=19), women using hormonal contraceptives (n=16), and a male control group (n=18) to a fear extinction task, and measured SCR, US expectancy and CS valence ratings. During extinction recall, low estradiol was associated with greater recovery of SCR, but was not related to US expectancy or CS evaluation. Importantly, women using hormonal contraceptives showed a dissociation between SCR and cognitive beliefs: they exhibited a greater recovery of SCR during extinction recall, yet reported similar US expectancy and CS valence ratings to the other female groups. This divergence underscores the importance of assessing multiple measures of fear when examining the role of estradiol in human fear extinction, especially when considering the potential of estradiol as an enhancement for psychological treatments for anxiety disorders. PMID:27544848

  4. Estradiol levels in women predict skin conductance response but not valence and expectancy ratings in conditioned fear extinction.

    PubMed

    White, Emily C; Graham, Bronwyn M

    2016-10-01

    Anxiety disorders are more prevalent in women than men. One contributing factor may be the sex hormone estradiol, which is known to impact the long term recall of conditioned fear extinction, a laboratory procedure that forms the basis of exposure therapy for anxiety disorders. To date, the literature examining estradiol and fear extinction in humans has focused primarily on physiological measures of fear, such as skin conductance response (SCR) and fear potentiated startle. This is surprising, given that models of anxiety identify at least three important components: physiological symptoms, cognitive beliefs, and avoidance behavior. To help address this gap, we exposed women with naturally high (n=20) or low estradiol (n=19), women using hormonal contraceptives (n=16), and a male control group (n=18) to a fear extinction task, and measured SCR, US expectancy and CS valence ratings. During extinction recall, low estradiol was associated with greater recovery of SCR, but was not related to US expectancy or CS evaluation. Importantly, women using hormonal contraceptives showed a dissociation between SCR and cognitive beliefs: they exhibited a greater recovery of SCR during extinction recall, yet reported similar US expectancy and CS valence ratings to the other female groups. This divergence underscores the importance of assessing multiple measures of fear when examining the role of estradiol in human fear extinction, especially when considering the potential of estradiol as an enhancement for psychological treatments for anxiety disorders.

  5. Chaotic dynamics from interspike intervals.

    PubMed

    Pavlov, A N; Sosnovtseva, O V; Mosekilde, E; Anishchenko, V S

    2001-03-01

    Considering two different mathematical models describing chaotic spiking phenomena, namely, an integrate-and-fire and a threshold-crossing model, we discuss the problem of extracting dynamics from interspike intervals (ISIs) and show that the possibilities of computing the largest Lyapunov exponent (LE) from point processes differ between the two models. We also consider the problem of estimating the second LE and the possibility to diagnose hyperchaotic behavior by processing spike trains. Since the second exponent is quite sensitive to the structure of the ISI series, we investigate the problem of its computation. PMID:11308739

  6. Chaotic dynamics from interspike intervals

    NASA Astrophysics Data System (ADS)

    Pavlov, Alexey N.; Sosnovtseva, Olga V.; Mosekilde, Erik; Anishchenko, Vadim S.

    2001-03-01

    Considering two different mathematical models describing chaotic spiking phenomena, namely, an integrate-and-fire and a threshold-crossing model, we discuss the problem of extracting dynamics from interspike intervals (ISIs) and show that the possibilities of computing the largest Lyapunov exponent (LE) from point processes differ between the two models. We also consider the problem of estimating the second LE and the possibility to diagnose hyperchaotic behavior by processing spike trains. Since the second exponent is quite sensitive to the structure of the ISI series, we investigate the problem of its computation.

  7. A Novel Housing-Based Socioeconomic Measure Predicts Hospitalization and Multiple Chronic Conditions in a Community Population

    PubMed Central

    Takahashi, Paul Y.; Ryu, Euijung; Hathcock, Matthew A.; Olson, Janet E.; Bielinski, Suzette J.; Cerhan, James R.; Rand-Weaver, Jennifer; Juhn, Young J.

    2016-01-01

    Background Socioeconomic status (SES) is an important predictor for outcomes of chronic diseases. However, it is often unavailable in clinical data. We sought to determine whether an individual housing-based SES index termed HOUSES can influence the likelihood of multiple chronic conditions (MCC) and hospitalization in a community population. Methods Participants were residents of Olmsted County, Minnesota, aged >18 years who were enrolled in Mayo Clinic Biobank on December 31, 2010, with follow-up until December 31, 2011. Primary outcome was all-cause hospitalization over 1 calendar year. Secondary outcome was MCC determined through Minnesota Medical Tiering score. Logistic regression model was used to assess association of HOUSES with Minnesota tiering score. With adjustment for age, sex, and MCC, the association of HOUSES with hospitalization risk was tested using Cox proportional hazards model. Results Eligible patients totaled 6,402 persons (median age, 57 years; 25th-75th quartiles, 45-68 years). The lowest quartile of HOUSES was associated with higher Minnesota tiering score after adjustment for age and sex (odds ratio [95% CI], 2.4 [2.0-3.1]) when compared with the highest HOUSES quartile. Patients in the lowest HOUSES quartile had higher risk of all-cause hospitalization (age, sex, MCC-adjusted hazard ratio [95% CI], 1.53 [1.18-1.98]) compared with those in the highest quartile. Conclusion Low SES, as assessed by HOUSES, was associated with increased risk of hospitalization and greater MCC health burden. HOUSES may be a clinically useful surrogate for SES to assess risk stratification for patient care and clinical research. PMID:26458399

  8. Effects of wait-time and intertrial interval durations on learning by children with multiple handicaps.

    PubMed Central

    Valcante, G; Roberson, W; Reid, W R; Wolking, W D

    1989-01-01

    We investigated the influence of teacher wait-time and intertrial interval durations on the performance of 4 multiply handicapped students during instruction in 10 skills. Four experimental conditions were evaluated: long wait-time and long intertrial interval, long wait-time and short intertrial interval, short wait-time and long intertrial interval, and short wait-time and short intertrial interval. Instructors attempted to keep short intervals as close as possible to 1 s and long intervals as close as possible to 10 s for both variables. Results showed that student performance was superior under the long wait-time conditions irrespective of the length of the intertrial interval. PMID:2523372

  9. High resolution time interval counter

    DOEpatents

    Condreva, Kenneth J.

    1994-01-01

    A high resolution counter circuit measures the time interval between the occurrence of an initial and a subsequent electrical pulse to two nanoseconds resolution using an eight megahertz clock. The circuit includes a main counter for receiving electrical pulses and generating a binary word--a measure of the number of eight megahertz clock pulses occurring between the signals. A pair of first and second pulse stretchers receive the signal and generate a pair of output signals whose widths are approximately sixty-four times the time between the receipt of the signals by the respective pulse stretchers and the receipt by the respective pulse stretchers of a second subsequent clock pulse. Output signals are thereafter supplied to a pair of start and stop counters operable to generate a pair of binary output words representative of the measure of the width of the pulses to a resolution of two nanoseconds. Errors associated with the pulse stretchers are corrected by providing calibration data to both stretcher circuits, and recording start and stop counter values. Stretched initial and subsequent signals are combined with autocalibration data and supplied to an arithmetic logic unit to determine the time interval in nanoseconds between the pair of electrical pulses being measured.

  10. High resolution time interval counter

    DOEpatents

    Condreva, K.J.

    1994-07-26

    A high resolution counter circuit measures the time interval between the occurrence of an initial and a subsequent electrical pulse to two nanoseconds resolution using an eight megahertz clock. The circuit includes a main counter for receiving electrical pulses and generating a binary word--a measure of the number of eight megahertz clock pulses occurring between the signals. A pair of first and second pulse stretchers receive the signal and generate a pair of output signals whose widths are approximately sixty-four times the time between the receipt of the signals by the respective pulse stretchers and the receipt by the respective pulse stretchers of a second subsequent clock pulse. Output signals are thereafter supplied to a pair of start and stop counters operable to generate a pair of binary output words representative of the measure of the width of the pulses to a resolution of two nanoseconds. Errors associated with the pulse stretchers are corrected by providing calibration data to both stretcher circuits, and recording start and stop counter values. Stretched initial and subsequent signals are combined with autocalibration data and supplied to an arithmetic logic unit to determine the time interval in nanoseconds between the pair of electrical pulses being measured. 3 figs.

  11. Prediction in Multiple Regression.

    ERIC Educational Resources Information Center

    Osborne, Jason W.

    2000-01-01

    Presents the concept of prediction via multiple regression (MR) and discusses the assumptions underlying multiple regression analyses. Also discusses shrinkage, cross-validation, and double cross-validation of prediction equations and describes how to calculate confidence intervals around individual predictions. (SLD)

  12. Modeling growth for predicting the contamination level of guava nectar by Candida pelliculosa under different conditions of pH and storage temperature.

    PubMed

    Tchango Tchango, J; Watier, D; Eb, P; Tailliez, R; Njine, T; Hornez, J P

    1997-01-01

    The combined effects of temperature (2-46 degrees C) and pH (1.55-6.25) on the growth of Candida pelliculosa isolated from guava nectar produced in Cameroon were studied using a turbidity method, ie measurement of optical density at 630 nm. A quadratic polynomial model was constructed to predict the effects and interactions of these two environmental conditions on the maximal optical density obtained (i2 = 0.97). The relation between optical density and population density of C. pelliculosa (CFU ml-1) was also established using an exponential regression (2 = 0.99). According to the model, maximal growth conditions were 37 degrees C and pH 6.25 for obtaining the maximal optical density of 1.25 corresponding to about 60 x 10(6) CFU ml-1. A good agreement of the model was found between the predicted values and the observed values of maximal optical density. The model was validated by the experimental values of maximal optical density obtained in the growth of C. pelliculosa in commercial guava nectar (pH 3.15). PMID:9079285

  13. [Effects of variable-interval punishment on lever pressing maintained by variable-ratio reinforcement in the rat].

    PubMed

    Iida, Naritoshi; Kimura, Hiroshi

    2007-12-01

    The effects of reinforcement and punishment on response suppression under variable-ratio reinforcement and variable-interval punishment schedules were investigated. In the baseline period, lever pressing in rats was maintained by a variable-ratio food reinforcement schedule. In the punishment condition, responding was punished by a grid shock under a variable-interval schedule. Baseline and punishment conditions alternated, and were continued until the response stabilized. Three rats were given five or six punishment rates with a fixed reinforcement rate and another three rats were given four or five reinforcement rates with a fixed punishment rate. The results indicated that the responses were either completely suppressed or not suppressed at all. When the punishment rate increased or the reinforcement rate decreased, the response was suppressed completely. Whereas when the punishment rate decreased or the reinforcement rate increased, the responses were not suppressed. These results agree with the predictions of the molar theory.

  14. Odor-context effects in free recall after a short retention interval: a new methodology for controlling adaptation.

    PubMed

    Isarida, Takeo; Sakai, Tetsuya; Kubota, Takayuki; Koga, Miho; Katayama, Yu; Isarida, Toshiko K

    2014-04-01

    The present study investigated context effects of incidental odors in free recall after a short retention interval (5 min). With a short retention interval, the results are not confounded by extraneous odors or encounters with the experimental odor and possible rehearsal during a long retention interval. A short study time condition (4 s per item), predicted not to be affected by adaptation to the odor, and a long study time condition (8 s per item) were used. Additionally, we introduced a new method for recovery from adaptation, where a dissimilar odor was briefly presented at the beginning of the retention interval, and we demonstrated the effectiveness of this technique. An incidental learning paradigm was used to prevent overshadowing from confounding the results. In three experiments, undergraduates (N = 200) incidentally studied words presented one-by-one and received a free recall test. Two pairs of odors and a third odor having different semantic-differential characteristics were selected from 14 familiar odors. One of the odors was presented during encoding, and during the test, the same odor (same-context condition) or the other odor within the pair (different-context condition) was presented. Without using a recovery-from-adaptation method, a significant odor-context effect appeared in the 4-s/item condition, but not in the 8-s/item condition. Using the recovery-from-adaptation method, context effects were found for both the 8- and the 4-s/item conditions. The size of the recovered odor-context effect did not change with study time. There were no serial position effects. Implications of the present findings are discussed.

  15. Operational validation of a multi-period and multi-criteria model conditioning approach for the prediction of rainfall-runoff processes in small forest catchments

    NASA Astrophysics Data System (ADS)

    Choi, H.; Kim, S.

    2012-12-01

    Most of hydrologic models have generally been used to describe and represent the spatio-temporal variability of hydrological processes in the watershed scale. Though it is an obvious fact that hydrological responses have the time varying nature, optimal values of model parameters were normally considered as time invariants or constants in most cases. The recent paper of Choi and Beven (2007) presents a multi-period and multi-criteria model conditioning approach. The approach is based on the equifinality thesis within the Generalised Likelihood Uncertainty Estimation (GLUE) framework. In their application, the behavioural TOPMODEL parameter sets are determined by several performance measures for global (annual) and short (30-days) periods, clustered using a Fuzzy C-means algorithm, into 15 types representing different hydrological conditions. Their study shows a good performance on the calibration of a rainfall-runoff model in a forest catchment, and also gives strong indications that it is uncommon to find model realizations that were behavioural over all multi-periods and all performance measures, and multi-period model conditioning approach may become new effective tool for predictions of hydrological processes in ungauged catchments. This study is a follow-up study on the Choi and Beven's (2007) model conditioning approach to test how the approach is effective for the prediction of rainfall-runoff responses in ungauged catchments. To achieve this purpose, 6 small forest catchments are selected among the several hydrological experimental catchments operated by Korea Forest Research Institute. In each catchment, long-term hydrological time series data varying from 10 to 30 years were available. The areas of the selected catchments range from 13.6 to 37.8 ha, and all areas are covered by coniferous or broad-leaves forests. The selected catchments locate in the southern coastal area to the northern part of South Korea. The bed rocks are Granite gneiss, Granite or

  16. Scenario prediction of emerging coastal city using CA modeling under different environmental conditions: a case study of Lingang New City, China.

    PubMed

    Feng, Yongjiu; Liu, Yan

    2016-09-01

    The world's coastal regions are experiencing rapid urbanization coupled with increased risk of ecological damage and storm surge related to global climate and sea level rising. This urban development issue is particularly important in China, where many emerging coastal cities are being developed. Lingang New City, southeast of Shanghai, is an excellent example of a coastal city that is increasingly vulnerable to environmental change. Sustainable urban development requires planning that classifies and allocates coastal lands using objective procedures that incorporate changing environmental conditions. In this paper, we applied cellular automata (CA) modeling based on self-adaptive genetic algorithm (SAGA) to predict future scenarios and explore sustainable urban development options for Lingang. The CA model was calibrated using the 2005 initial status, 2015 final status, and a set of spatial variables. We implemented specific ecological and environmental conditions as spatial constraints for the model and predicted four 2030 scenarios: (a) an urban planning-oriented Plan Scenario; (b) an ecosystem protection-oriented Eco Scenario; (c) a storm surge-affected Storm Scenario; and (d) a scenario incorporating both ecosystem protection and the effects of storm surge, called the Ecostorm Scenario. The Plan Scenario has been taken as the baseline, with the Lingang urban area increasing from 45.8 km(2) in 2015 to 66.8 km(2) in 2030, accounting for 23.9 % of the entire study area. The simulated urban land size of the Plan Scenario in 2030 was taken as the target to accommodate the projected population increase in this city, which was then applied in the remaining three development scenarios. We used CA modeling to reallocate the urban cells to other unconstrained areas in response to changing spatial constraints. Our predictions should be helpful not only in assessing and adjusting the urban planning schemes for Lingang but also for evaluating urban planning in coastal

  17. Scenario prediction of emerging coastal city using CA modeling under different environmental conditions: a case study of Lingang New City, China.

    PubMed

    Feng, Yongjiu; Liu, Yan

    2016-09-01

    The world's coastal regions are experiencing rapid urbanization coupled with increased risk of ecological damage and storm surge related to global climate and sea level rising. This urban development issue is particularly important in China, where many emerging coastal cities are being developed. Lingang New City, southeast of Shanghai, is an excellent example of a coastal city that is increasingly vulnerable to environmental change. Sustainable urban development requires planning that classifies and allocates coastal lands using objective procedures that incorporate changing environmental conditions. In this paper, we applied cellular automata (CA) modeling based on self-adaptive genetic algorithm (SAGA) to predict future scenarios and explore sustainable urban development options for Lingang. The CA model was calibrated using the 2005 initial status, 2015 final status, and a set of spatial variables. We implemented specific ecological and environmental conditions as spatial constraints for the model and predicted four 2030 scenarios: (a) an urban planning-oriented Plan Scenario; (b) an ecosystem protection-oriented Eco Scenario; (c) a storm surge-affected Storm Scenario; and (d) a scenario incorporating both ecosystem protection and the effects of storm surge, called the Ecostorm Scenario. The Plan Scenario has been taken as the baseline, with the Lingang urban area increasing from 45.8 km(2) in 2015 to 66.8 km(2) in 2030, accounting for 23.9 % of the entire study area. The simulated urban land size of the Plan Scenario in 2030 was taken as the target to accommodate the projected population increase in this city, which was then applied in the remaining three development scenarios. We used CA modeling to reallocate the urban cells to other unconstrained areas in response to changing spatial constraints. Our predictions should be helpful not only in assessing and adjusting the urban planning schemes for Lingang but also for evaluating urban planning in coastal

  18. Orders on Intervals Over Partially Ordered Sets: Extending Allen's Algebra and Interval Graph Results

    SciTech Connect

    Zapata, Francisco; Kreinovich, Vladik; Joslyn, Cliff A.; Hogan, Emilie A.

    2013-08-01

    To make a decision, we need to compare the values of quantities. In many practical situations, we know the values with interval uncertainty. In such situations, we need to compare intervals. Allen’s algebra describes all possible relations between intervals on the real line, and ordering relations between such intervals are well studied. In this paper, we extend this description to intervals in an arbitrary partially ordered set (poset). In particular, we explicitly describe ordering relations between intervals that generalize relation between points. As auxiliary results, we provide a logical interpretation of the relation between intervals, and extend the results about interval graphs to intervals over posets.

  19. Controlling human fixed-interval performance.

    PubMed

    Weiner, H

    1969-05-01

    Both high and relatively constant rates of responding without post-reinforcement pauses and lower rates with pauses after reinforcement are produced by human subjects under fixed-interval (FI) schedules. Such FI rates and patterns may be controlled when subjects are provided with different histories of conditioning and different conditions of response cost (reinforcement penalties per response). Subjects with a conditioning history under ratio schedules typically produce high and relatively constant rates of responding under FI schedules; this responding does not change systematically with changes in FI value. In contrast, subjects with a history under schedules which produce little or no responding between reforcements [such as differential-reinforcement-of-low-rate (DRL) schedules] tend to pause after reinforcement and respond at low rates under FI schedules, whether or not they also have ratio conditioning histories; cost increases the likelihood of this type of performance. For DRL-history subjects, post-reinforcement pauses increase and response rates decrease as FI values increase.

  20. Pigeons' Choices between Fixed-Interval and Random-Interval Schedules: Utility of Variability?

    ERIC Educational Resources Information Center

    Andrzejewski, Matthew E.; Cardinal, Claudia D.; Field, Douglas P.; Flannery, Barbara A.; Johnson, Michael; Bailey, Kathleen; Hineline, Philip N.

    2005-01-01

    Pigeons' choosing between fixed-interval and random-interval schedules of reinforcement was investigated in three experiments using a discrete-trial procedure. In all three experiments, the random-interval schedule was generated by sampling a probability distribution at an interval (and in multiples of the interval) equal to that of the…

  1. A model of interval timing by neural integration.

    PubMed

    Simen, Patrick; Balci, Fuat; de Souza, Laura; Cohen, Jonathan D; Holmes, Philip

    2011-06-22

    We show that simple assumptions about neural processing lead to a model of interval timing as a temporal integration process, in which a noisy firing-rate representation of time rises linearly on average toward a response threshold over the course of an interval. Our assumptions include: that neural spike trains are approximately independent Poisson processes, that correlations among them can be largely cancelled by balancing excitation and inhibition, that neural populations can act as integrators, and that the objective of timed behavior is maximal accuracy and minimal variance. The model accounts for a variety of physiological and behavioral findings in rodents, monkeys, and humans, including ramping firing rates between the onset of reward-predicting cues and the receipt of delayed rewards, and universally scale-invariant response time distributions in interval timing tasks. It furthermore makes specific, well-supported predictions about the skewness of these distributions, a feature of timing data that is usually ignored. The model also incorporates a rapid (potentially one-shot) duration-learning procedure. Human behavioral data support the learning rule's predictions regarding learning speed in sequences of timed responses. These results suggest that simple, integration-based models should play as prominent a role in interval timing theory as they do in theories of perceptual decision making, and that a common neural mechanism may underlie both types of behavior.

  2. A model of interval timing by neural integration

    PubMed Central

    Simen, Patrick; Balci, Fuat; deSouza, Laura; Cohen, Jonathan D.; Holmes, Philip

    2011-01-01

    We show that simple assumptions about neural processing lead to a model of interval timing as a temporal integration process, in which a noisy firing-rate representation of time rises linearly on average toward a response threshold over the course of an interval. Our assumptions include: that neural spike trains are approximately independent Poisson processes; that correlations among them can be largely cancelled by balancing excitation and inhibition; that neural populations can act as integrators; and that the objective of timed behavior is maximal accuracy and minimal variance. The model accounts for a variety of physiological and behavioral findings in rodents, monkeys and humans, including ramping firing rates between the onset of reward-predicting cues and the receipt of delayed rewards, and universally scale-invariant response time distributions in interval timing tasks. It furthermore makes specific, well-supported predictions about the skewness of these distributions, a feature of timing data that is usually ignored. The model also incorporates a rapid (potentially one-shot) duration-learning procedure. Human behavioral data support the learning rule’s predictions regarding learning speed in sequences of timed responses. These results suggest that simple, integration-based models should play as prominent a role in interval timing theory as they do in theories of perceptual decision making, and that a common neural mechanism may underlie both types of behavior. PMID:21697374

  3. An empirical/theoretical model with dimensionless numbers to predict the performance of electrodialysis systems on the basis of operating conditions.

    PubMed

    Karimi, Leila; Ghassemi, Abbas

    2016-07-01

    Among the different technologies developed for desalination, the electrodialysis/electrodialysis reversal (ED/EDR) process is one of the most promising for treating brackish water with low salinity when there is high risk of scaling. Multiple researchers have investigated ED/EDR to optimize the process, determine the effects of operating parameters, and develop theoretical/empirical models. Previously published empirical/theoretical models have evaluated the effect of the hydraulic conditions of the ED/EDR on the limiting current density using dimensionless numbers. The reason for previous studies' emphasis on limiting current density is twofold: 1) to maximize ion removal, most ED/EDR systems are operated close to limiting current conditions if there is not a scaling potential in the concentrate chamber due to a high concentration of less-soluble salts; and 2) for modeling the ED/EDR system with dimensionless numbers, it is more accurate and convenient to use limiting current density, where the boundary layer's characteristics are known at constant electrical conditions. To improve knowledge of ED/EDR systems, ED/EDR models should be also developed for the Ohmic region, where operation reduces energy consumption, facilitates targeted ion removal, and prolongs membrane life compared to limiting current conditions. In this paper, theoretical/empirical models were developed for ED/EDR performance in a wide range of operating conditions. The presented ion removal and selectivity models were developed for the removal of monovalent ions and divalent ions utilizing the dominant dimensionless numbers obtained from laboratory scale electrodialysis experiments. At any system scale, these models can predict ED/EDR performance in terms of monovalent and divalent ion removal.

  4. An empirical/theoretical model with dimensionless numbers to predict the performance of electrodialysis systems on the basis of operating conditions.

    PubMed

    Karimi, Leila; Ghassemi, Abbas

    2016-07-01

    Among the different technologies developed for desalination, the electrodialysis/electrodialysis reversal (ED/EDR) process is one of the most promising for treating brackish water with low salinity when there is high risk of scaling. Multiple researchers have investigated ED/EDR to optimize the process, determine the effects of operating parameters, and develop theoretical/empirical models. Previously published empirical/theoretical models have evaluated the effect of the hydraulic conditions of the ED/EDR on the limiting current density using dimensionless numbers. The reason for previous studies' emphasis on limiting current density is twofold: 1) to maximize ion removal, most ED/EDR systems are operated close to limiting current conditions if there is not a scaling potential in the concentrate chamber due to a high concentration of less-soluble salts; and 2) for modeling the ED/EDR system with dimensionless numbers, it is more accurate and convenient to use limiting current density, where the boundary layer's characteristics are known at constant electrical conditions. To improve knowledge of ED/EDR systems, ED/EDR models should be also developed for the Ohmic region, where operation reduces energy consumption, facilitates targeted ion removal, and prolongs membrane life compared to limiting current conditions. In this paper, theoretical/empirical models were developed for ED/EDR performance in a wide range of operating conditions. The presented ion removal and selectivity models were developed for the removal of monovalent ions and divalent ions utilizing the dominant dimensionless numbers obtained from laboratory scale electrodialysis experiments. At any system scale, these models can predict ED/EDR performance in terms of monovalent and divalent ion removal. PMID:27108213

  5. Prediction and measurement of optimum operating conditions for entrained coal gasification processes. Quarterly technical progress report, No. 1, 1 November 1979-31 January 1980

    SciTech Connect

    Smoot, L.D.; Hedman, P.O.; Smith, P.J.

    1980-02-15

    This report summarizes work completed to predict and measure optimum operating conditions for entrained coal gasifications processes. This study is the third in a series designed to investigate mixing and reaction in entrained coal gasifiers. A new team of graduate and undergraduate students was formed to conduct the experiments on optimum gasification operating conditions. Additional coal types, which will be tested in the gasifier were identified, ordered, and delivered. Characterization of these coals will be initiated. Hardware design modifications to introduce swirl into the secondary were initiated. Minor modifications were made to the gasifier to allow laser diagnostics to be made on an independently funded study with the Los Alamos Scientific Laboratory. The tasks completed on the two-dimensional model included the substantiation of a Gaussian PDF for the top-hat PDF in BURN and the completion of a Lagrangian particle turbulent dispersion module. The reacting submodel is progressing into the final stages of debug. The formulation of the radiation submodel is nearly complete and coding has been initiated. A device was designed, fabricated, and used to calibrate the actual Swirl Number of the cold-flow swirl generator used in the Phase 2 study. Swirl calibrations were obtained at the normal tests flow rates and at reduced flow rates. Two cold-flow tests were also performed to gather local velocity data under swirling conditions. Further analysis of the cold-flow coal-dust and swirl test results from the previous Phase 2 study were completed.

  6. Scaling of light and dark time intervals.

    PubMed

    Marinova, J

    1978-01-01

    Scaling of light and dark time intervals of 0.1 to 1.1 s is performed by the mehtod of magnitude estimation with respect to a given standard. The standards differ in duration and type (light and dark). The light intervals are subjectively estimated as longer than the dark ones. The relation between the mean interval estimations and their magnitude is linear for both light and dark intervals.

  7. Permutations and topological entropy for interval maps

    NASA Astrophysics Data System (ADS)

    Misiurewicz, Michal

    2003-05-01

    Recently Bandt, Keller and Pompe (2002 Entropy of interval maps via permutations Nonlinearity 15 1595-602) introduced a method of computing the entropy of piecewise monotone interval maps by counting permutations exhibited by initial pieces of orbits. We show that for topological entropy this method does not work for arbitrary continuous interval maps. We also show that for piecewise monotone interval maps topological entropy can be computed by counting permutations exhibited by periodic orbits.

  8. Capacity of novelty-induced locomotor activity and the hole-board test to predict sensitivity to the conditioned rewarding effects of cocaine.

    PubMed

    Arenas, M Carmen; Daza-Losada, Manuel; Vidal-Infer, Antonio; Aguilar, Maria A; Miñarro, José; Rodríguez-Arias, Marta

    2014-06-22

    Novelty-seeking in rodents, defined as enhanced specific exploration of novel situations, is considered to predict the response of animals to drugs of abuse and, thus, allow "drug-vulnerable" individuals to be identified. The main objective of this study was to assess the predictive ability of two well-known paradigms of the novelty-seeking trait - novelty-induced locomotor activity (which distinguishes High- and Low-Responder mice, depending on their motor activity) and the hole-board test (which determines High- and Low-Novelty Seeker mice depending on the number of head dips they perform) - to identify subjects that would subsequently be more sensitive to the conditioned rewarding effects of cocaine in a population of young adult (PND 56) and adolescent (PND 35) OF1 mice of both sexes. Conditioned place preference (CPP), a useful tool for evaluating the sensitivity of individuals to the incentive properties of addictive drugs, was induced with a sub-threshold dose of cocaine (1 mg/kg, i.p.). Our results showed that novelty-induced motor activity had a greater predictive capacity to identify "vulnerable-drug" individuals among young-adult mice (PND 56), while the hole-board test was more effective in adolescents (PND 35). High-NR young-adults, which presented higher motor activity in the first ten minutes of the test (novelty-reactivity), were 3.9 times more likely to develop cocaine-induced CPP than Low-NR young-adults. When total activity (1h) was evaluated (novelty-habituation), only High-R (novelty-non-habituating) young-adult male and Low-R (novelty-habituating) female mice produced a high conditioning score. However, only High-Novelty Seeker male and female adolescents and Low-Novelty Seeker female young-adult animals (according to the hole-board test), acquired cocaine-induced CPP. These findings should contribute to the development of screening methods for identifying at-risk human drug users and prevention strategies for those with specific

  9. Retention interval affects visual short-term memory encoding.

    PubMed

    Bankó, Eva M; Vidnyánszky, Zoltán

    2010-03-01

    Humans can efficiently store fine-detailed facial emotional information in visual short-term memory for several seconds. However, an unresolved question is whether the same neural mechanisms underlie high-fidelity short-term memory for emotional expressions at different retention intervals. Here we show that retention interval affects the neural processes of short-term memory encoding using a delayed facial emotion discrimination task. The early sensory P100 component of the event-related potentials (ERP) was larger in the 1-s interstimulus interval (ISI) condition than in the 6-s ISI condition, whereas the face-specific N170 component was larger in the longer ISI condition. Furthermore, the memory-related late P3b component of the ERP responses was also modulated by retention interval: it was reduced in the 1-s ISI as compared with the 6-s condition. The present findings cannot be explained based on differences in sensory processing demands or overall task difficulty because there was no difference in the stimulus information and subjects' performance between the two different ISI conditions. These results reveal that encoding processes underlying high-precision short-term memory for facial emotional expressions are modulated depending on whether information has to be stored for one or for several seconds.

  10. I Lost It in the Lights: The Effects of Predictable and Variable Intermittent Vision on Unimanual Catching.

    PubMed

    Lyons, J; Fontaine, R; Elliott, D

    1997-06-01

    In this study, 2 competing views of interceptive action were examined by assessing the influence of variability in the interval between visual samples in a unimanual ball-catching task. Subjects were required to catch tennis balls projected over a distance of 14 m, under conditions of intermittent vision in which the between-sample intervals were either predictable or unpredictable. Results indicated that, although performance was best with shorter between-sample intervals, the temporal predictability of samples did not reliably affect catching performance. This suggests that between-sample retinal expansion provides sufficient information for the timing of the interceptive act. PMID:12453788

  11. Development of a predictive model for the growth kinetics of aerobic microbial population on pomegranate marinated chicken breast fillets under isothermal and dynamic temperature conditions.

    PubMed

    Lytou, Anastasia; Panagou, Efstathios Z; Nychas, George-John E

    2016-05-01

    The aim of this study was the development of a model to describe the growth kinetics of aerobic microbial population of chicken breast fillets marinated in pomegranate juice under isothermal and dynamic temperature conditions. Moreover, the effect of pomegranate juice on the extension of the shelf life of the product was investigated. Samples (10 g) of chicken breast fillets were immersed in marinades containing pomegranate juice for 3 h at 4 °C following storage under aerobic conditions at 4, 10, and 15 °C for 10 days. Total Viable Counts (TVC), Pseudomonas spp and lactic acid bacteria (LAB) were enumerated, in parallel with sensory assessment (odor and overall appearance) of marinated and non-marinated samples. The Baranyi model was fitted to the growth data of TVC to calculate the maximum specific growth rate (μmax) that was further modeled as a function of temperature using a square root-type model. The validation of the model was conducted under dynamic temperature conditions based on two fluctuating temperature scenarios with periodic changes from 6 to 13 °C. The shelf life was determined both mathematically and with sensory assessment and its temperature dependence was modeled by an Arrhenius type equation. Results showed that the μmax of TVC of marinated samples was significantly lower compared to control samples regardless temperature, while under dynamic temperature conditions the model satisfactorily predicted the growth of TVC in both control and marinated samples. The shelf-life of marinated samples was significantly extended compared to the control (5 days extension at 4 °C). The calculated activation energies (Ea), 82 and 52 kJ/mol for control and marinated samples, respectively, indicated higher temperature dependence of the shelf life of control samples compared to marinated ones. The present results indicated that pomegranate juice could be used as an alternative ingredient in marinades to prolong the shelf life of chicken.

  12. Using Confidence Intervals and Recurrence Intervals to Determine Precipitation Delivery Mechanisms Responsible for Mass Wasting Events.

    NASA Astrophysics Data System (ADS)

    Ulizio, T. P.; Bilbrey, C.; Stoyanoff, N.; Dixon, J. L.

    2015-12-01

    upper bound of the 99% confidence interval at all SNOTEL sites while precipitation accumulated in the form of rain is within the expected average, indicating an anomalously snow year and average amounts of rainfall during the same water year. This information can be used to better predict circumstances leading to slope failures in northern latitude alpine landscapes.

  13. Cocaine-conditioned place preference is predicted by previous anxiety-like behavior and is related to an increased number of neurons in the basolateral amygdala.

    PubMed

    Ladrón de Guevara-Miranda, David; Pavón, Francisco J; Serrano, Antonia; Rivera, Patricia; Estivill-Torrús, Guillermo; Suárez, Juan; Rodríguez de Fonseca, Fernando; Santín, Luis J; Castilla-Ortega, Estela

    2016-02-01

    The identification of behavioral traits that could predict an individual's susceptibility to engage in cocaine addiction is relevant for understanding and preventing this disorder, but investigations of cocaine addicts rarely allow us to determinate whether their behavioral attributes are a cause or a consequence of drug use. To study the behaviors that predict cocaine vulnerability, male C57BL/6J mice were examined in a battery of tests (the elevated plus maze, hole-board, novelty preference in the Y-Maze, episodic-like object recognition and forced swimming) prior to training in a cocaine-conditioned place preference (CPP) paradigm to assess the reinforcing value of the drug. In a second study, the anatomical basis of high and low CPP in the mouse brain was investigated by studying the number of neurons (neuronal nuclei-positive) in two addiction-related limbic regions (the medial prefrontal cortex and the basolateral amygdala) and the number of dopaminergic neurons (tyrosine hydroxylase-positive) in the ventral tegmental area by immunohistochemistry and stereology. Correlational analyses revealed that CPP behavior was successfully predicted by anxiety-like measures in the elevated plus maze (i.e., the more anxious mice showed more preference for the cocaine-paired compartment) but not by the other behaviors analyzed. In addition, increased numbers of neurons were found in the basolateral amygdala of the high CPP mice, a key brain center for anxiety and fear responses. The results support the theory that anxiety is a relevant factor for cocaine vulnerability, and the basolateral amygdala is a potential neurobiological substrate where both anxiety and cocaine vulnerability could overlap. PMID:26523857

  14. Cocaine-conditioned place preference is predicted by previous anxiety-like behavior and is related to an increased number of neurons in the basolateral amygdala.

    PubMed

    Ladrón de Guevara-Miranda, David; Pavón, Francisco J; Serrano, Antonia; Rivera, Patricia; Estivill-Torrús, Guillermo; Suárez, Juan; Rodríguez de Fonseca, Fernando; Santín, Luis J; Castilla-Ortega, Estela

    2016-02-01

    The identification of behavioral traits that could predict an individual's susceptibility to engage in cocaine addiction is relevant for understanding and preventing this disorder, but investigations of cocaine addicts rarely allow us to determinate whether their behavioral attributes are a cause or a consequence of drug use. To study the behaviors that predict cocaine vulnerability, male C57BL/6J mice were examined in a battery of tests (the elevated plus maze, hole-board, novelty preference in the Y-Maze, episodic-like object recognition and forced swimming) prior to training in a cocaine-conditioned place preference (CPP) paradigm to assess the reinforcing value of the drug. In a second study, the anatomical basis of high and low CPP in the mouse brain was investigated by studying the number of neurons (neuronal nuclei-positive) in two addiction-related limbic regions (the medial prefrontal cortex and the basolateral amygdala) and the number of dopaminergic neurons (tyrosine hydroxylase-positive) in the ventral tegmental area by immunohistochemistry and stereology. Correlational analyses revealed that CPP behavior was successfully predicted by anxiety-like measures in the elevated plus maze (i.e., the more anxious mice showed more preference for the cocaine-paired compartment) but not by the other behaviors analyzed. In addition, increased numbers of neurons were found in the basolateral amygdala of the high CPP mice, a key brain center for anxiety and fear responses. The results support the theory that anxiety is a relevant factor for cocaine vulnerability, and the basolateral amygdala is a potential neurobiological substrate where both anxiety and cocaine vulnerability could overlap.

  15. Simultaneous timing of multiple intervals: implications of the scalar property.

    PubMed

    Leak, T M; Gibbon, J

    1995-01-01

    Three experiments with pigeons are reported in which the scalar property in simultaneous timing tasks was studied. According to scalar expectancy theory, the scalar property should be maintained in simultaneous timing, but the behavioral theory of timing predicts that the scalar property should be evident only in independent timing. Experiment 1 showed that the appearance of distinct peaks at reinforcement times required about a 4:1 ratio between intervals. Experiment 2 (2-interval timing task) and Experiment 3 (3-interval timing task) used an individual trial analysis technique to examine high-rate responding segments bracketing the times of reinforcement. The standard deviations of the starting and stopping times of high-rate segments were linearly related to their means and to reinforcement time, supporting the scalar property in simultaneous timing.

  16. Finding Every Root of a Broad Class of Real, Continuous Functions in a Given Interval

    NASA Technical Reports Server (NTRS)

    Tausworthe, Robert C.; Wolgast, Paul A.

    2011-01-01

    One of the most pervasive needs within the Deep Space Network (DSN) Metric Prediction Generator (MPG) view period event generation is that of finding solutions to given occurrence conditions. While the general form of an equation expresses e