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Sample records for conditional prediction intervals

  1. Sensor drift and predicted calibration intervals of handheld temperature and relative humidity meters under residential field-use conditions.

    PubMed

    Johnston James D; Magnusson, Brianna M; Eggett, Dennis; Mumford, Kyle; Collingwood, Scott C; Bernhardt, Scott A

    2014-10-01

    Handheld temperature and relative humidity (T/RH) meters are commonly used in residential indoor air surveys. Although popular, T/RH meters are prone to sensor drift and consequent loss of accuracy, and thus instrument manufacturers often recommend annual calibration and adjustment. Field-use conditions, however, have been shown to accelerate electronic sensor drift in outdoor applications, resulting in out-of-tolerance measurements in less than one year. In the study described in this article, sensor drift was evaluated under residential field use for 30 handheld T/RH meters to predict needed calibration intervals based on hierarchical linear modeling. Instruments were used in 43 home visits over a 93-day period and were calibrated (without adjustment) 49 times over the study period with a laboratory standard. Analysis of covariance showed significant drift among temperature sensors for all three instrument types (p < .0001) and among humidity sensors in two instruments. The authors' study suggests calibration frequency should be based on instrument performance under specific sampling conditions rather than on predetermined time intervals.

  2. Evaluating long-term relationship of protein sequence by use of D-interval conditional probability and its impact on protein structural class prediction.

    PubMed

    Gu, Fei; Chen, Hang

    2009-01-01

    To fix the large and expanding gap between sequence known proteins and structure known proteins, it is important to study on protein structural class prediction (PSCP) for its foundation and usefulness in protein structure analysis. In this paper, the d-interval conditional probability index was proposed to reflect the long-term correlation between amino acids. Based on this index, the impact of residues' long-term relationship on PSCP was analyzed. Two new information theory based algorithms were proposed and were used combining with the long-term information between residues to predict protein structural class (PSC). The dataset 5714 was tested for its low sequence similarity and high reliability. The result showed that the new index was 3-6% higher than traditional index by use of the same algorithms, and the PSCP accuracy was 4-10% improved using the new algorithms. The presented index, algorithms and the long-term relationship of residues on PSCP can be extensively applied in other sequence based protein structure analysis.

  3. Reliable prediction intervals with regression neural networks.

    PubMed

    Papadopoulos, Harris; Haralambous, Haris

    2011-10-01

    This paper proposes an extension to conventional regression neural networks (NNs) for replacing the point predictions they produce with prediction intervals that satisfy a required level of confidence. Our approach follows a novel machine learning framework, called Conformal Prediction (CP), for assigning reliable confidence measures to predictions without assuming anything more than that the data are independent and identically distributed (i.i.d.). We evaluate the proposed method on four benchmark datasets and on the problem of predicting Total Electron Content (TEC), which is an important parameter in trans-ionospheric links; for the latter we use a dataset of more than 60000 TEC measurements collected over a period of 11 years. Our experimental results show that the prediction intervals produced by our method are both well calibrated and tight enough to be useful in practice.

  4. 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.

  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. Prediction of the confidence interval of quantitative trait Loci location.

    PubMed

    Visscher, Peter M; Goddard, Mike E

    2004-07-01

    In 1997, Darvasi and Soller presented empirical predictions of the confidence interval of quantitative trait loci (QTL) location for dense marker maps in experimental crosses. They showed from simulation results for backcross and F2 populations from inbred lines that the 95% confidence interval was a simple function of sample size and the effect of the QTL. In this study, we derive by theory simple equations that can be used to predict any confidence interval and show that for the 95% confidence interval, they are in good agreement with the empirical results given by Darvasi and Soller. A general form of the confidence interval is given that also applies to other population structures (e.g., collections of sib pairs). Furthermore, the expected shape of the likelihood-ratio-test around the true QTL location is derived, which is shown to be extremely leptokurtic. It is shown that this shape explains why confidence intervals from the Log of Odds (LOD) drop-off method and bootstrap results frequently differ for real data sets.

  7. 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.

  8. 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…

  9. 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.

  10. 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.

  11. Predicting Driver Behavior during the Yellow Interval Using Video Surveillance.

    PubMed

    Li, Juan; Jia, Xudong; Shao, Chunfu

    2016-12-06

    At a signalized intersection, drivers must make a stop/go decision at the onset of the yellow signal. Incorrect decisions would lead to red light running (RLR) violations or crashes. This study aims to predict drivers' stop/go decisions and RLR violations during yellow intervals. Traffic data such as vehicle approaching speed, acceleration, distance to the intersection, and occurrence of RLR violations are gathered by a Vehicle Data Collection System (VDCS). An enhanced Gaussian Mixture Model (GMM) is used to extract moving vehicles from target lanes, and the Kalman Filter (KF) algorithm is utilized to acquire vehicle trajectories. The data collected from the VDCS are further analyzed by a sequential logit model, and the relationship between drivers' stop/go decisions and RLR violations is identified. The results indicate that the distance of vehicles to the stop line at the onset of the yellow signal is an important predictor for both drivers' stop/go decisions and RLR violations. In addition, vehicle approaching speed is a contributing factor for stop/go decisions. Furthermore, the accelerations of vehicles after the onset of the yellow signal are positively related to RLR violations. The findings of this study can be used to predict the probability of drivers' RLR violations and improve traffic safety at signalized intersections.

  12. Predicting Driver Behavior during the Yellow Interval Using Video Surveillance

    PubMed Central

    Li, Juan; Jia, Xudong; Shao, Chunfu

    2016-01-01

    At a signalized intersection, drivers must make a stop/go decision at the onset of the yellow signal. Incorrect decisions would lead to red light running (RLR) violations or crashes. This study aims to predict drivers’ stop/go decisions and RLR violations during yellow intervals. Traffic data such as vehicle approaching speed, acceleration, distance to the intersection, and occurrence of RLR violations are gathered by a Vehicle Data Collection System (VDCS). An enhanced Gaussian Mixture Model (GMM) is used to extract moving vehicles from target lanes, and the Kalman Filter (KF) algorithm is utilized to acquire vehicle trajectories. The data collected from the VDCS are further analyzed by a sequential logit model, and the relationship between drivers’ stop/go decisions and RLR violations is identified. The results indicate that the distance of vehicles to the stop line at the onset of the yellow signal is an important predictor for both drivers’ stop/go decisions and RLR violations. In addition, vehicle approaching speed is a contributing factor for stop/go decisions. Furthermore, the accelerations of vehicles after the onset of the yellow signal are positively related to RLR violations. The findings of this study can be used to predict the probability of drivers’ RLR violations and improve traffic safety at signalized intersections. PMID:27929447

  13. Fear potentiated startle at short intervals following conditioned stimulus onset during delay but not trace conditioning.

    PubMed

    Asli, Ole; Kulvedrøsten, Silje; Solbakken, Line E; Flaten, Magne Arve

    2009-07-01

    The latency of conditioned fear after delay and trace conditioning was investigated. Some argue that delay conditioning is not dependent on awareness. In contrast, trace conditioning, where there is a gap between the conditioned stimulus (CS) and the unconditioned stimulus (US), is assumed to be dependent on awareness. In the present study, a tone CS signaled a noise US presented 1000 ms after CS onset in the delay conditioning group. In the trace conditioning group, a 200-ms tone CS was followed by an 800-ms gap prior to US presentation. Fear-potentiated startle should be seen at shorter intervals after delay conditioning compared to trace conditioning. Analyses showed increased startle at 30, 50, 100, and 150 ms after CS onset following delay conditioning compared to trace conditioning. This implies that fear-relevant stimuli elicit physiological reactions before extended processing of the stimuli occur, following delay, but not trace conditioning.

  14. Conditional replenishment using motion prediction

    NASA Technical Reports Server (NTRS)

    Hein, D. N.; Jones, H. W., Jr.

    1979-01-01

    Conditional replenishment is an interframe video compression method that uses correlation in time to reduce video transmission rates. This method works by detecting and sending only the changing portions of the image and by having the receiver use the video data from the previous frame for the non-changing portion. The amount of compression that can be achieved through this technique depends to a large extent on the rate of change within the image, and can vary from 10 to 1 to less than 2 to 1. An additional 3 to 1 reduction in rate is obtained by the intraframe coding of data blocks using a 2-dimensional variable rate Hadamard transform coder. A further additional 2 to 1 rate reduction is achieved by using motion prediction. Motion prediction works by measuring the relative displacements of a subpicture from one frame to the next. The subpicture can then be transmitted by sending only the value of the 2-dimensional displacement. Computer simulations have demonstrated that data rates of 2 to 4 Mega-bits/second can be achieved while still retaining good fidelity in the image.

  15. Dorsal hippocampus involvement in trace fear conditioning with long, but not short, trace intervals in mice.

    PubMed

    Chowdhury, Najwa; Quinn, Jennifer J; Fanselow, Michael S

    2005-10-01

    Placing a "trace" interval between a warning signal and an aversive shock makes consolidation of the memory for trace conditioning hippocampus dependent. To determine the trace at which memory consolidation requires the hippocampus, mice were trained with 0-s, 1-s, 3-s, or 20-s trace intervals and tested for freezing to context and tone. Posttraining dorsal hippocampus (DH) lesions decreased context conditioning regardless of trace interval. However, DH lesions attenuated only the 20-s trace tone freezing. Like eyeblink conditioning, the DH is necessary for trace fear conditioning only at long trace intervals, but the time scale for the effective interval in fear conditioning is about 40 times longer. Manipulations that alter trace fear conditioning with short trace intervals probably do not reflect altered DH function. Given this difference in time scale along with the use of posttraining DH lesions, hippocampus dependency of trace conditioning is not related to a bridging function or response timing.

  16. 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.

  17. Machine learning approaches for estimation of prediction interval for the model output.

    PubMed

    Shrestha, Durga L; Solomatine, Dimitri P

    2006-03-01

    A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the prediction interval) of the underlying distribution of prediction errors. The idea is to partition the input space into different zones or clusters having similar model errors using fuzzy c-means clustering. The prediction interval is constructed for each cluster on the basis of empirical distributions of the errors associated with all instances belonging to the cluster under consideration and propagated from each cluster to the examples according to their membership grades in each cluster. Then a regression model is built for in-sample data using computed prediction limits as targets, and finally, this model is applied to estimate the prediction intervals (limits) for out-of-sample data. The method was tested on artificial and real hydrologic data sets using various machine learning techniques. Preliminary results show that the method is superior to other methods estimating the prediction interval. A new method for evaluating performance for estimating prediction interval is proposed as well.

  18. 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.

  19. 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.

  20. Likelihood based observability analysis and confidence intervals for predictions of dynamic models

    PubMed Central

    2012-01-01

    Background Predicting a system’s behavior based on a mathematical model is a primary task in Systems Biology. If the model parameters are estimated from experimental data, the parameter uncertainty has to be translated into confidence intervals for model predictions. For dynamic models of biochemical networks, the nonlinearity in combination with the large number of parameters hampers the calculation of prediction confidence intervals and renders classical approaches as hardly feasible. Results In this article reliable confidence intervals are calculated based on the prediction profile likelihood. Such prediction confidence intervals of the dynamic states can be utilized for a data-based observability analysis. The method is also applicable if there are non-identifiable parameters yielding to some insufficiently specified model predictions that can be interpreted as non-observability. Moreover, a validation profile likelihood is introduced that should be applied when noisy validation experiments are to be interpreted. Conclusions The presented methodology allows the propagation of uncertainty from experimental to model predictions. Although presented in the context of ordinary differential equations, the concept is general and also applicable to other types of models. Matlab code which can be used as a template to implement the method is provided at http://www.fdmold.uni-freiburg.de/∼ckreutz/PPL. PMID:22947028

  1. Human trace fear conditioning: right-lateralized cortical activity supports trace-interval processes.

    PubMed

    Haritha, Abhishek T; Wood, Kimberly H; Ver Hoef, Lawrence W; Knight, David C

    2013-06-01

    Pavlovian conditioning requires the convergence and simultaneous activation of neural circuitry that supports conditioned stimulus (CS) and unconditioned stimulus (US) processes. However, in trace conditioning, the CS and US are separated by a period of time called the trace interval, and thus do not overlap. Therefore, determining brain regions that support associative learning by maintaining a CS representation during the trace interval is an important issue for conditioning research. Prior functional magnetic resonance imaging (fMRI) research has identified brain regions that support trace-conditioning processes. However, relatively little is known about whether this activity is specific to the trace CS, the trace interval, or both periods of time. The present study was designed to disentangle the hemodynamic response produced by the trace CS from that associated with the trace interval, in order to identify learning-related activation during these distinct components of a trace-conditioning trial. Trace-conditioned activity was observed within dorsomedial prefrontal cortex (PFC), dorsolateral PFC, insula, inferior parietal lobule (IPL), and posterior cingulate (PCC). Each of these regions showed learning-related activity during the trace CS, while trace-interval activity was only observed within a subset of these areas (i.e., dorsomedial PFC, PCC, right dorsolateral PFC, right IPL, right superior/middle temporal gyrus, and bilateral insula). Trace-interval activity was greater in right than in left dorsolateral PFC, IPL, and superior/middle temporal gyrus. These findings indicate that components of the prefrontal, cingulate, insular, and parietal cortices support trace-interval processes, as well as suggesting that a right-lateralized fronto-parietal circuit may play a unique role in trace conditioning.

  2. 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.

  3. Stability margins for multilinear interval systems by way of phase conditions: A unified approach

    NASA Technical Reports Server (NTRS)

    Keel, L. H.; Bhattacharyya, S. P.

    1992-01-01

    A simple way of checking the stability with respect to an arbitrary stability region of a family of polynomials containing a vector of parameters varying within prescribed intervals is discussed. It is assumed that the parameters appear affine multilinearly in the characteristic polynomial coefficients. The condition proposed is simply to check the phase difference of the vertex polynomials. This test based on the mapping theorem significantly reduces computational complexity. Mathematical proofs are omitted. The results can be used to determine various stability margins of control systems containing interconnected interval subsystems. These include the gain, phase, time-delay, H(sup infinity), and nonlinear sector bounded stability margins of multilinear interval systems.

  4. 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.

  5. 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

  6. 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.

  7. 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

  8. The Use of One-Sample Prediction Intervals for Estimating CO2 Scrubber Canister Durations

    DTIC Science & Technology

    2012-10-01

    testing) that describe the characteristics of carbon dioxide absorbent canisters in closed - and semiclosed- circuit UBAs ( rebreathers ). The...CONCLUSIONS As described in engineering statistics texts, the use of one-sample prediction intervals is profitably applied to the testing of closed - circuit ...Duration Limits for Closed - Circuit Underwater Breathing Apparatus, NEDU TR 2-99, Navy Experimental Diving Unit, April 1999. 2. J. Clarke, K

  9. Ensemble decadal predictions from analysed initial conditions.

    PubMed

    Troccoli, Alberto; Palmer, T N

    2007-08-15

    Sensitivity experiments using a coupled model initialized from analysed atmospheric and oceanic observations are used to investigate the potential for interannual-to-decadal predictability. The potential for extending seasonal predictions to longer time scales is explored using the same coupled model configuration and initialization procedure as used for seasonal prediction. It is found that, despite model drift, climatic signals on interannual-to-decadal time scales appear to be detectable. Two climatic states have been chosen: one starting in 1965, i.e. ahead of a period of global cooling, and the other in 1994, ahead of a period of global warming. The impact of initial conditions and of the different levels of greenhouse gases are isolated in order to gain insights into the source of predictability.

  10. Fast time-series prediction using high-dimensional data: evaluating confidence interval credibility.

    PubMed

    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, 2859:TROOCI>2.0.CO;2">J. Atmos. Sci. 57, 2859 (2000).

  11. 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)

  12. 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

  13. 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.

  14. Mode-locking neurodynamics predict human auditory brainstem responses to musical intervals.

    PubMed

    Lerud, Karl D; Almonte, Felix V; Kim, Ji Chul; Large, Edward W

    2014-02-01

    The auditory nervous system is highly nonlinear. Some nonlinear responses arise through active processes in the cochlea, while others may arise in neural populations of the cochlear nucleus, inferior colliculus and higher auditory areas. In humans, auditory brainstem recordings reveal nonlinear population responses to combinations of pure tones, and to musical intervals composed of complex tones. Yet the biophysical origin of central auditory nonlinearities, their signal processing properties, and their relationship to auditory perception remain largely unknown. Both stimulus components and nonlinear resonances are well represented in auditory brainstem nuclei due to neural phase-locking. Recently mode-locking, a generalization of phase-locking that implies an intrinsically nonlinear processing of sound, has been observed in mammalian auditory brainstem nuclei. Here we show that a canonical model of mode-locked neural oscillation predicts the complex nonlinear population responses to musical intervals that have been observed in the human brainstem. The model makes predictions about auditory signal processing and perception that are different from traditional delay-based models, and may provide insight into the nature of auditory population responses. We anticipate that the application of dynamical systems analysis will provide the starting point for generic models of auditory population dynamics, and lead to a deeper understanding of nonlinear auditory signal processing possibly arising in excitatory-inhibitory networks of the central auditory nervous system. This approach has the potential to link neural dynamics with the perception of pitch, music, and speech, and lead to dynamical models of auditory system development.

  15. Olfactory conditioning of the sting extension reflex in honeybees: Memory dependence on trial number, interstimulus interval, intertrial interval, and protein synthesis.

    PubMed

    Giurfa, Martin; Fabre, Eve; Flaven-Pouchon, Justin; Groll, Helga; Oberwallner, Barbara; Vergoz, Vanina; Roussel, Edith; Sandoz, Jean Christophe

    2009-12-01

    Harnessed bees learn to associate an odorant with an electric shock so that afterward the odorant alone elicits the sting extension response (SER). We studied the dependency of retention on interstimulus interval (ISI), intertrial interval (ITI), and number of conditioning trials in the framework of olfactory SER conditioning. Forward ISIs (conditioned stimulus [CS] before unconditioned stimulus [US]) supported higher retention than a backward one (US before CS) with an optimum around 3 sec. Spaced trials (ITI 10 min) supported higher retention than massed trials (ITI 1 min) and led to the formation of a late long-term memory (l-LTM) that depended on protein synthesis. Our results reaffirm olfactory SER conditioning as a reliable tool for the study of learning and memory.

  16. 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.

  17. Analytical Conditions for Compact Earthquake Prediction Approaches

    NASA Astrophysics Data System (ADS)

    Sengor, T.

    2009-04-01

    This paper concerns itself with The atmosphere and ionosphere include non-uniform electric charge and current distributions during the earthquake activity. These charges and currents move irregularly when an activity is scheduled for an earthquake at the future. The electromagnetic characteristics of the region over the earth change to domains where irregular transportations of non-uniform electric charges are observed; therefore, the electromagnetism in the plasma, which moves irregularly and contains non-uniform charge distributions, is studied. These cases of charge distributions are called irregular and non-uniform plasmas. It is called the seismo-plasma if irregular and non-uniform plasma defines a real earthquake activity, which will come to truth. Some signals involving the above-mentioned coupling effects generate some analytical conditions giving the predictability of seismic processes [1]-[5]. These conditions will be discussed in this paper. 2 References [1] T. Sengor, "The electromagnetic device optimization modeling of seismo-electromagnetic processes," IUGG Perugia 2007. [2] T. Sengor, "The electromagnetic device optimization modeling of seismo-electromagnetic processes for Marmara Sea earthquakes," EGU 2008. [3] T. Sengor, "On the exact interaction mechanism of electromagnetically generated phenomena with significant earthquakes and the observations related the exact predictions before the significant earthquakes at July 1999-May 2000 period," Helsinki Univ. Tech. Electrom. Lab. Rept. 368, May 2001. [4] T. Sengor, "The Observational Findings Before The Great Earthquakes Of December 2004 And The Mechanism Extraction From Associated Electromagnetic Phenomena," Book of XXVIIIth URSI GA 2005, pp. 191, EGH.9 (01443) and Proceedings 2005 CD, New Delhi, India, Oct. 23-29, 2005. [5] T. Sengor, "The interaction mechanism among electromagnetic phenomena and geophysical-seismic-ionospheric phenomena with extraction for exact earthquake prediction genetics," 10

  18. 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.

  19. 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.

  20. Adaptive sensing of ECG signals using R-R interval prediction.

    PubMed

    Nakaya, Shogo; Nakamura, Yuichi

    2013-01-01

    There is growing demand for systems consisting of tiny sensor nodes powered with small batteries that acquire electrocardiogram (ECG) data and wirelessly transmit the data to remote base stations or mobile phones continuously over a long period. Conserving electric power in the wireless sensor nodes (WSNs) is essential in such systems. Adaptive sensing is promising for this purpose since it can reduce the energy consumed not only for data transmission but also for sensing. However, the basic method of adaptive sensing, referred to here as "plain adaptive sensing," is not suitable for ECG signals because it sometimes capture the R waves defectively. We introduce an improved adaptive sensing method for ECG signals by incorporating R-R interval prediction. Our method improves the characteristics of ECG compression and drastically reduces the total energy consumption of the WSNs.

  1. 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

  2. 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).

  3. Early photosensitizer uptake kinetics predict optimum drug-light interval for photodynamic therapy

    NASA Astrophysics Data System (ADS)

    Sinha, Lagnojita; Elliott, Jonathan T.; Hasan, Tayyaba; Pogue, Brian W.; Samkoe, Kimberley S.; Tichauer, Kenneth M.

    2015-03-01

    Photodynamic therapy (PDT) has shown promising results in targeted treatment of cancerous cells by developing localized toxicity with the help of light induced generation of reactive molecular species. The efficiency of this therapy depends on the product of the intensity of light dose and the concentration of photosensitizer (PS) in the region of interest (ROI). On account of this, the dynamic and variable nature of PS delivery and retention depends on many physiological factors that are known to be heterogeneous within and amongst tumors (e.g., blood flow, blood volume, vascular permeability, and lymph drainage rate). This presents a major challenge with respect to how the optimal time and interval of light delivery is chosen, which ideally would be when the concentration of PS molecule is at its maximum in the ROI. In this paper, a predictive algorithm is developed that takes into consideration the variability and dynamic nature of PS distribution in the body on a region-by-region basis and provides an estimate of the optimum time when the PS concentration will be maximum in the ROI. The advantage of the algorithm lies in the fact that it predicts the time in advance as it takes only a sample of initial data points (~12 min) as input. The optimum time calculated using the algorithm estimated a maximum dose that was only 0.58 +/- 1.92% under the true maximum dose compared to a mean dose error of 39.85 +/- 6.45% if a 1 h optimal light deliver time was assumed for patients with different efflux rate constants of the PS, assuming they have the same plasma function. Therefore, if the uptake values of PS for the blood and the ROI is known for only first 12 minutes, the entire curve along with the optimum time of light radiation can be predicted with the help of this algorithm.

  4. Predicting Culex pipiens/restuans population dynamics by interval lagged weather data

    PubMed Central

    2013-01-01

    Background Culex pipiens/restuans mosquitoes are important vectors for a variety of arthropod borne viral infections. In this study, the associations between 20 years of mosquito capture data and the time lagged environmental quantities daytime length, temperature, precipitation, relative humidity and wind speed were used to generate a predictive model for the population dynamics of this vector species. Methods Mosquito population in the study area was represented by averaged time series of mosquitos counts captured at 6 sites in Cook County (Illinois, USA). Cross-correlation maps (CCMs) were compiled to investigate the association between mosquito abundances and environmental quantities. The results obtained from the CCMs were incorporated into a Poisson regression to generate a predictive model. To optimize the predictive model the time lags obtained from the CCMs were adjusted using a genetic algorithm. Results CCMs for weekly data showed a highly positive correlation of mosquito abundances with daytime length 4 to 5 weeks prior to capture (quantified by a Spearman rank order correlation of rS = 0.898) and with temperature during 2 weeks prior to capture (rS = 0.870). Maximal negative correlations were found for wind speed averaged over 3 week prior to capture (rS = −0.621). Cx. pipiens/restuans population dynamics was predicted by integrating the CCM results in Poisson regression models. They were used to simulate the average seasonal cycle of the mosquito abundance. Verification with observations resulted in a correlation of rS = 0.899 for daily and rS = 0.917 for weekly data. Applying the optimized models to the entire 20-years time series also resulted in a suitable fit with rS = 0.876 for daily and rS = 0.899 for weekly data. Conclusions The study demonstrates the application of interval lagged weather data to predict mosquito abundances with a feasible accuracy, especially when related to weekly Cx. pipiens

  5. 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.

  6. Infant rats can learn time intervals before the maturation of the striatum: evidence from odor fear conditioning

    PubMed Central

    Boulanger Bertolus, Julie; Hegoburu, Chloe; Ahers, Jessica L.; Londen, Elizabeth; Rousselot, Juliette; Szyba, Karina; Thévenet, Marc; Sullivan-Wilson, Tristan A.; Doyère, Valérie; Sullivan, Regina M.; Mouly, Anne-Marie

    2014-01-01

    Interval timing refers to the ability to perceive, estimate and discriminate durations in the range of seconds to minutes. Very little is currently known about the ontogeny of interval timing throughout development. On the other hand, even though the neural circuit sustaining interval timing is a matter of debate, the striatum has been suggested to be an important component of the system and its maturation occurs around the third post-natal (PN) week in rats. The global aim of the present study was to investigate interval timing abilities at an age for which striatum is not yet mature. We used odor fear conditioning, as it can be applied to very young animals. In odor fear conditioning, an odor is presented to the animal and a mild footshock is delivered after a fixed interval. Adult rats have been shown to learn the temporal relationships between the odor and the shock after a few associations. The first aim of the present study was to assess the activity of the striatum during odor fear conditioning using 2-Deoxyglucose autoradiography during development in rats. The data showed that although fear learning was displayed at all tested ages, activation of the striatum was observed in adults but not in juvenile animals. Next, we assessed the presence of evidence of interval timing in ages before and after the inclusion of the striatum into the fear conditioning circuit. We used an experimental setup allowing the simultaneous recording of freezing and respiration that have been demonstrated to be sensitive to interval timing in adult rats. This enabled the detection of duration-related temporal patterns for freezing and/or respiration curves in infants as young as 12 days PN during odor fear conditioning. This suggests that infants are able to encode time durations as well as and as quickly as adults while their striatum is not yet functional. Alternative networks possibly sustaining interval timing in infant rats are discussed. PMID:24860457

  7. 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.

  8. 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.

  9. Predicting Fatigue Lives Under Complex Loading Conditions

    NASA Technical Reports Server (NTRS)

    Mcgaw, Michael A.; Nelson, R. S.; Janitor, L. A.

    1995-01-01

    Cyclic Damage Accumulation (CDA) computer program performs high-temperature, low-cycle-fatigue life prediction for materials analysis. Designed to account for effects on creep-fatigue life of complex loadings involving such factors as thermomechanical fatigue, hold periods, wave-shapes, mean stresses, multiaxiality, cumulative damage, coatings, and environmental attack. Several features practical for application to actual component analysis using modern finite-element or boundary-element methods. Although developed for use in predicting crack-initiation lifetimes of gas-turbine-engine materials, also applied to other materials as well. Written in FORTRAN 77.

  10. Conditional Standard Error of Measurement in Prediction.

    ERIC Educational Resources Information Center

    Woodruff, David

    1990-01-01

    A method of estimating conditional standard error of measurement at specific score/ability levels is described that avoids theoretical problems identified for previous methods. The method focuses on variance of observed scores conditional on a fixed value of an observed parallel measurement, decomposing these variances into true and error parts.…

  11. Bioaccumulation kinetics of organic xenobiotic pollutants in the freshwater invertebrate Gammarus pulex modeled with prediction intervals.

    PubMed

    Ashauer, Roman; Caravatti, Ivo; Hintermeister, Anita; Escher, Beate I

    2010-07-01

    Uptake and elimination rate constants, bioaccumulation factors, and elimination times in the freshwater arthropod Gammarus pulex were measured for 14 organic micropollutants covering a wide range of hydrophobicity (imidacloprid, aldicarb, ethylacrylate, 4,6-dinitro-o-cresol, carbofuran, malathion, 4-nitrobenzyl-chloride, 2,4-dichloroaniline, Sea-Nine, 2,4-dichlorophenol, diazinon, 2,4,5-trichlorophenol, 1,2,3-trichlorobenzene, and hexachlorobenzene; all 14C-labeled). The toxicokinetic parameters were determined by least-square fitting of a one-compartment first-order toxicokinetic model, followed by Markov Chain Monte Carlo parameter estimation. The parameter estimation methods used here account for decreasing aqueous concentrations during the exposure phase or increasing aqueous concentrations during the elimination phase of bioaccumulation experiments. It is not necessary to keep exposure concentrations constant or zero during uptake and elimination, respectively. Neither is it required to achieve steady state during the exposure phase; hence, tests can be shorter. Prediction intervals, which take the between-parameter correlation into account, were calculated for bioaccumulation factors and simulations of internal concentrations under variable exposure. The lipid content of Gammarus pulex was 1.3% of wet weight, consisting of 25% phospholipids and 75% triglycerides. Size-dependent bioaccumulation was observed for eight compounds, although the magnitudes of the relationships were too small to be of practical relevance. Elimination times ranged from 0.45 to 20 d, and bioaccumulation factors ranged from 1.7 to 4,449 L/kg. The identified compounds with unexpectedly long elimination times should be given priority in future studies investigating the biotransformation of these compounds.

  12. Reduced birth intervals following the birth of children with long-term illness: evidence supporting a conditional evolved response.

    PubMed

    Waynforth, David

    2015-10-01

    Human birth interval length is indicative of the level of parental investment that a child will receive: a short interval following birth means that parental resources must be split with a younger sibling during a period when the older sibling remains highly dependent on their parents. From a life-history theoretical perspective, it is likely that there are evolved mechanisms that serve to maximize fitness depending on context. One context that would be expected to result in short birth intervals, and lowered parental investment, is after a child with low expected fitness is born. Here, data drawn from a longitudinal British birth cohort study were used to test whether birth intervals were shorter following the birth of a child with a long-term health problem. Data on the timing of 4543 births were analysed using discrete-time event history analysis. The results were consistent with the hypothesis: birth intervals were shorter following the birth of a child diagnosed by a medical professional with a severe but non-fatal medical condition. Covariates in the analysis were also significantly associated with birth interval length: births of twins or multiple births, and relationship break-up were associated with significantly longer birth intervals.

  13. Predicting Comorbid Conditions and Trajectories using Social Health Records.

    PubMed

    Ji, Xiang; Ae Chun, Soon; Geller, James

    2016-05-05

    Many patients suffer from comorbidity conditions, for example, obese patients often develop type-2 diabetes and hypertension. In the US, 80% of Medicare spending is for managing patients with these multiple coexisting conditions. Predicting potential comorbidity conditions for an individual patient can promote preventive care and reduce costs. Predicting possible comorbidity progression paths can provide important insights into population heath and aid with decisions in public health policies. Discovering the comorbidity relationships is complex and difficult, due to limited access to Electronic Health Records by privacy laws. In this paper, we present a collaborative comorbidity prediction method to predict likely comorbid conditions for individual patients, and a trajectory prediction graph model to reveal progression paths of comorbid conditions. Our prediction approaches utilize patient generated health reports on online social media, called Social Health Records (SHR). The experimental results based on one SHR source show that our method is able to predict future comorbid conditions for a patient with coverage values of 48% and 75% for a top-20 and a top-100 ranked list, respectively. For risk trajectory prediction, our approach is able to reveal each potential progression trajectory between any two conditions and infer the confidence of the future trajectory, given any observed condition. The predicted trajectories are validated with existing comorbidity relations from the medical literature.

  14. 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.

  15. 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

  16. 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…

  17. 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…

  18. An Aquatic Decomposition Scoring Method to Potentially Predict the Postmortem Submersion Interval of Bodies Recovered from the North Sea.

    PubMed

    van Daalen, Marjolijn A; de Kat, Dorothée S; Oude Grotebevelsborg, Bernice F L; de Leeuwe, Roosje; Warnaar, Jeroen; Oostra, Roelof Jan; M Duijst-Heesters, Wilma L J

    2017-03-01

    This study aimed to develop an aquatic decomposition scoring (ADS) method and investigated the predictive value of this method in estimating the postmortem submersion interval (PMSI) of bodies recovered from the North Sea. This method, consisting of an ADS item list and a pictorial reference atlas, showed a high interobserver agreement (Krippendorff's alpha ≥ 0.93) and hence proved to be valid. This scoring method was applied to data, collected from closed cases-cases in which the postmortal submersion interval (PMSI) was known-concerning bodies recovered from the North Sea from 1990 to 2013. Thirty-eight cases met the inclusion criteria and were scored by quantifying the observed total aquatic decomposition score (TADS). Statistical analysis demonstrated that TADS accurately predicts the PMSI (p < 0.001), confirming that the decomposition process in the North Sea is strongly correlated to time.

  19. Periodic boundary conditions for KdV-Burgers equation on an interval

    NASA Astrophysics Data System (ADS)

    Samokhin, Alexey

    2017-03-01

    For the KdV-Burgers equation on a finite interval the development of a regular profile starting from a constant one under a periodic perturbation on the boundary is studied. The equation describes a medium which is both dissipative and dispersive. For an appropriate combination of dispersion and dissipation the asymptotic profile looks like a periodical chain of shock fronts with a decreasing amplitude (similarly to the Burgers equation case). But due to dispersion each such front is followed by increasing oscillation leading to the next shock-like the ninth wave in rough seas. The development of such a profile is preceded by an initial shock of a constant height.

  20. Effect of a retention interval between pre-exposure and conditioning on latent inhibition in humans using a blink conditioning procedure.

    PubMed

    De la Casa Rivas, Luis Gonzalo; Traverso Arcos, Luis Miguel; Márquez Zamora, Raúl

    2010-11-01

    Latent inhibition, retarded learning after pre-exposure to the to-be-conditioned stimulus, was examined using a blink conditioned procedure in humans. Experiment 1 showed that the procedure is suited to inducing the latent inhibition effect. In Experiment 2, the introduction of a 3-minute interval between pre-exposure and conditioning phases attenuated latent inhibition. These results contribute to identify the mechanisms involved in pre-exposure and subsequent conditioning of a stimulus, which is particularly important if we bear in mind that latent inhibition has been used repeatedly as an instrument to analyze the course of attentional processes in normal and pathological populations.

  1. Bayesian multilevel discrete interval hazard analysis to predict dichlorodiphenyldichloroethylene mortality in Hyalella azteca based on body residues.

    PubMed

    Lee, Jong-Hyeon; Stow, Craig A; Landrum, Peter F

    2009-11-01

    We exposed Hyalella azteca to p,p'-dichlorodiphenyldichloroethylene for intervals of 1 to 4 d and followed mortality out to 10 d. Mortality was determined as the cessation of heartbeat; dead organism body residue was determined daily. To model mortality probability, body residues of the living organisms were estimated using published kinetic data with concentration-dependent rate constants. The estimated residues compared favorably with measured residues in the dead organisms (predicted body residue = 1.302 ± 0.142 measured body residue + 10.351 ± 15.766, r² = 0.64, n = 50). The response data were collected at discrete intervals; thus, it was not possible to determine the exact time of death for organisms. Consequently, we analyzed the mortality data using discrete interval analysis, in a Bayesian hierarchical framework, with body residue as the dose metric. The predicted body residues to produce mortality were similar across the duration of exposure when postexposure mortality was considered. The concentration for 50% mortality was 0.47 μmol/g (148.6 tg/g, range 0.32-0.66 μmol/g), and predictions of response indicted 95% (range 73-99.9%) mortality at 0.79 μmol/g (250 μg/g) and 4% (range 1.2-9.6%) mortality at 0.16 μmol/g (50 μg/g). The lethal residue for 50% mortality based on interval analysis for short-term exposures with postexposure mortality resulted in values similar to long-term continuous exposures for exposure durations of more than 600 h.

  2. 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…

  3. Relation between conditioned stimulus-elicit responses and unconditioned response diminution in long-interval human heart-rate classical conditioning.

    PubMed

    Marcos, J L; Redondo, J

    2001-05-01

    Previous research on electrodermal conditioning suggests that the conditioned diminution of the unconditioned response (UR) has an associative basis. The aim of this experiment was to test whether this phenomenon also occurs in heart rate (HR) classical conditioning. For this purpose, a differential classical conditioning was performed. The conditioned stimuli (CSs) were geometrical shapes (the CS+ was a square and the CS- was a triangle) displayed on a computer screen and a burst of white noise was used as unconditioned stimulus (US). For analysis of the conditioned response (CR) components, an interval between CS+ and US of 8 seconds was used. After the acquisition phase, participants were tested using trials with the US preceded either by a CS+, a CS-, or a neutral stimulus (a circle). The results showed conditioned diminution of the UR and suggest that the second heart rate deceleration component (D2) is responsible for the occurrence of this phenomenon.

  4. Technical note: A mathematical function to predict daily milk yield of dairy cows in relation to the interval between milkings.

    PubMed

    Klopčič, M; Koops, W J; Kuipers, A

    2013-09-01

    The milk production of a dairy cow is characterized by lactation production, which is calculated from daily milk yields (DMY) during lactation. The DMY is calculated from one or more milkings a day collected at the farm. Various milking systems are in use today, resulting in one or many recorded milk yields a day, from which different calculations are used to determine DMY. The primary objective of this study was to develop a mathematical function that described milk production of a dairy cow in relation to the interval between 2 milkings. The function was partly based on the biology of the milk production process. This function, called the 3K-function, was able to predict milk production over an interval of 12h, so DMY was twice this estimate. No external information is needed to incorporate this function in methods to predict DMY. Application of the function on data from different milking systems showed a good fit. This function could be a universal tool to predict DMY for a variety of milking systems, and it seems especially useful for data from robotic milking systems. Further study is needed to evaluate the function under a wide range of circumstances, and to see how it can be incorporated in existing milk recording systems. A secondary objective of using the 3K-function was to compare how much DMY based on different milking systems differed from that based on a twice-a-day milking. Differences were consistent with findings in the literature.

  5. Development of Predictive Equations Based on Pavement Condition Index Data

    DTIC Science & Technology

    1992-03-01

    solutions to eliminate existing problems. A Spavement management system not only evaluates the present condition of a pavement but predicts its future...structural performance [1]. Condition rating data collected periodically will track the performance of a pavement. Most airports presently utilize...three primary objectives of rating a pavement based on the PCI method: (1) Determine present condition of the pavement in terms of the apparent

  6. 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…

  7. 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…

  8. 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…

  9. 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…

  10. 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.

  11. Origin of complexity and conditional predictability in cellular automata.

    PubMed

    García-Morales, Vladimir

    2013-10-01

    A simple mechanism for the emergence of complexity in cellular automata out of predictable dynamics is described. This leads to introduce the concept of conditional predictability for systems whose trajectory can only be piecewise known. The mechanism is used to construct a cellular automaton model for discrete chimeralike states, where synchrony and incoherence in an ensemble of identical oscillators coexist. The incoherent region is shown to have a periodicity that is three orders of magnitude longer than the period of the synchronous oscillation.

  12. 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.

  13. Conditions for predicting quasistationary states by rearrangement formula.

    PubMed

    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.

  14. 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.

  15. Methods to correct and compute confidence and prediction intervals of models neglecting sub-parameterization heterogeneity - From the ideal toward practice

    NASA Astrophysics Data System (ADS)

    Christensen, Steen

    2017-02-01

    This paper derives and tests methods to correct regression-based confidence and prediction intervals for groundwater models that neglect sub-parameterization heterogeneity within the hydraulic property fields of the groundwater system. Several levels of knowledge and uncertainty about the system are considered. It is shown by a two-dimensional groundwater flow example that when reliable probabilistic models are available for the property fields, the corrected confidence and prediction intervals are nearly accurate; when the probabilistic models must be suggested from subjective judgment, the corrected confidence intervals are likely to be much more accurate than their uncorrected counterparts; when no probabilistic information is available then conservative bound values can be used to correct the intervals but they are likely to be very wide. The paper also shows how confidence and prediction intervals can be computed and corrected when the weights applied to the data are estimated as part of the regression. It is demonstrated that in this case it cannot be guaranteed that applying the conservative bound values will lead to conservative confidence and prediction intervals. Finally, it is demonstrated by the two-dimensional flow example that the accuracy of the corrected confidence and prediction intervals deteriorates for very large covariance of the log-transmissivity field, and particularly when the weight matrix differs from the inverse total error covariance matrix. It is argued that such deterioration is less likely to happen for three-dimensional groundwater flow systems.

  16. 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.

  17. 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.

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

    PubMed

    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.

  19. 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

  20. 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.

  1. Usefulness of time interval between end of diastolic mitral annular velocity pattern and onset of QRS for predicting left ventricular end-diastolic pressure.

    PubMed

    Su, Ho-Ming; Lin, Tsung-Hsien; Voon, Wen-Chol; Lee, Kun-Tai; Chu, Chih-Sheng; Cheng, Kai-Hung; Yen, Hsueh-Wei; Lai, Wen-Ter; Sheu, Sheng-Hsiung

    2007-01-01

    Diastolic mitral annular motion may terminate earlier in patients with higher left ventricular end-diastolic pressure (LVEDP). It was therefore hypothesized that the time interval measured from the end of the diastolic mitral annular velocity pattern to the onset of QRS (the AQ interval) would be a useful parameter in predicting LVEDP. The aim of this study was to evaluate the relation between the AQ interval and LVEDP. Forty-six patients with suspected coronary artery disease who underwent Doppler echocardiographic studies and cardiac catheterization were included. LVEDP was determined using a micromanometer-tipped catheter. On univariate analysis, the AQ interval had positive correlations with the PR interval (r = 0.405, p = 0.005), transmitral E-wave velocity (r = 0.502, p <0.001), isovolumic contraction time (r = 0.635, p <0.001), and LVEDP (r = 0.514, p <0.001) and a negative correlation with E-wave deceleration time (r = -0.430, p = 0.003). After stepwise multiple linear regression analysis, the PR interval, transmitral E-wave velocity, and LVEDP were the independent predictors of the AQ interval (beta = 0.234, p = 0.033; beta = 0.331, p = 0.004; and beta = 0.350, p = 0.003, respectively). In conclusion, the AQ interval is a novel, simple, and easily obtained index in the prediction of LVEDP.

  2. [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.

  3. Predictable weathering of puparial hydrocarbons of necrophagous flies for determining the postmortem interval: a field experiment using Chrysomya rufifacies.

    PubMed

    Zhu, Guang-Hui; Jia, Zheng-Jun; Yu, Xiao-Jun; Wu, Ku-Sheng; Chen, Lu-Shi; Lv, Jun-Yao; Eric Benbow, M

    2017-01-05

    Preadult development of necrophagous flies is commonly recognized as an accurate method for estimating the minimum postmortem interval (PMImin). However, once the PMImin exceeds the duration of preadult development, the method is less accurate. Recently, fly puparial hydrocarbons were found to significantly change with weathering time in the field, indicating their potential use for PMImin estimates. However, additional studies are required to demonstrate how the weathering varies among species. In this study, the puparia of Chrysomya rufifacies were placed in the field to experience natural weathering to characterize hydrocarbon composition change over time. We found that weathering of the puparial hydrocarbons was regular and highly predictable in the field. For most of the hydrocarbons, the abundance decreased significantly and could be modeled using a modified exponent function. In addition, the weathering rate was significantly correlated with the hydrocarbon classes. The weathering rate of 2-methyl alkanes was significantly lower than that of alkenes and internal methyl alkanes, and alkenes were higher than the other two classes. For mono-methyl alkanes, the rate was significantly and positively associated with carbon chain length and branch position. These results indicate that puparial hydrocarbon weathering is highly predictable and can be used for estimating long-term PMImin.

  4. Predicting tree pollen season start dates using thermal conditions.

    PubMed

    Myszkowska, Dorota

    2014-01-01

    Thermal conditions at the beginning of the year determine the timing of pollen seasons of early flowering trees. The aims of this study were to quantify the relationship between the tree pollen season start dates and the thermal conditions just before the beginning of the season and to construct models predicting the start of the pollen season in a given year. The study was performed in Krakow (Southern Poland); the pollen data of Alnus, Corylus and Betula were obtained in 1991-2012 using a volumetric method. The relationship between the tree pollen season start, calculated by the cumulated pollen grain sum method, and a 5-day running means of maximum (for Alnus and Corylus) and mean (for Betula) daily temperature was found and used in the logistic regression models. The estimation of model parameters indicated their statistically significance for all studied taxa; the odds ratio was higher in models for Betula, comparing to Alnus and Corylus. The proposed model makes the accuracy of prediction in 83.58 % of cases for Alnus, in 84.29 % of cases for Corylus and in 90.41 % of cases for Betula. In years of model verification (2011 and 2012), the season start of Alnus and Corylus was predicted more precisely in 2011, while in case of Betula, the model predictions achieved 100 % of accuracy in both years. The correctness of prediction indicated that the data used for the model arrangement fitted the models well and stressed the high efficacy of model prediction estimated using the pollen data in 1991-2010.

  5. 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

  6. 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, Karen 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.

  7. 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

  8. 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.

  9. 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.

  10. Autoregressive conditional duration as a model for financial market crashes prediction

    NASA Astrophysics Data System (ADS)

    Pyrlik, Vladimir

    2013-12-01

    There is an increasing number of studies showing that financial market crashes can be detected and predicted. The main aim of the research was to develop a technique for crashes prediction based on the analysis of durations between sequent crashes of a certain magnitude of Dow Jones Industrial Average. We have found significant autocorrelation in the series of durations between sequent crashes and suggest autoregressive conditional duration models (ACD) to forecast the crashes. We apply the rolling intervals technique in the sample of more than 400 DJIA crashes in 1896-2011 and repeatedly use the data on 100 sequent crashes to estimate a family of ACD models and calculate forecasts of the one following crash. It appears that the ACD models provide significant predictive power when combined with the inter-event waiting time technique. This suggests that despite the high quality of retrospective predictions, using the technique for real-time forecasting seems rather ineffective, as in the case of every particular crash the specification of the ACD model, which would provide the best quality prediction, is rather hard to identify.

  11. 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.

  12. 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.

  13. 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.

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

    PubMed

    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 %.

  15. 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 %.

  16. 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.

  17. Short-Term Prediction of Traffic Rate Interval Router Using Hybrid Training of Dynamic Synapse Neural Network Structure

    NASA Astrophysics Data System (ADS)

    Shakiba, M.; Teshnehlab, M.; Zokaie, S.; Zakermoshfegh, M.

    In this study, a hybrid learning algorithm for training the Dynamic Synapse Neural Network (DSNN) to high accurate prediction of congestion in TCP computer networks is introduced. The idea behind this technique is to inform the TCP transmitters of congestion before it happens and to make transmitters decrease their data sending rate to a level which does not overflow the routers buffer. Traffic rate data are available in the format of time series and these real data are used to train and predict the future traffic rate condition. Hybrid learning algorithm aims to solve main problems of the Gradient Descent (GD) based method for the optimization of the DSNN, which are instability, local minima and the problem of generalization of trained network to the test data. In this method, Adaptable Weighted Particle Swarm Optimization (AWPSO) as a global optimizer is used to optimize the parameters of synaptic plasticity and the GD algorithm is used to optimize the weighted parameters of DSNN. As AWPSO is a derivative free optimization technique, a simpler method for the train of DSNN is achieved. Also the results are compared to GD algorithm.

  18. 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.

  19. 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.

  20. 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

  1. Predicting EMIC wave properties from ring current plasma conditions

    NASA Astrophysics Data System (ADS)

    Cowee, M.; Fu, X.; Jordanova, V.

    2015-12-01

    Recently, sophisticated computer models have shown that accurate, dynamic modelling of the energetic electrons in the radiation belt requires global and real-time plasma and wave conditions. Data provided by in-situ spacecraft measurement are too sparse to supply enough inputs for continuous global modeling of the radiation belt. Here we present a model to predict amplitude, peak frequency and spectral width of the electromagnetic ion cyclotron (EMIC) wave from the anisotropic ring current ion distributions, which are the source of the wave. The model is derived from hybrid simulations in a large initial parameter space for plasmas consisting of electrons, protons, and helium ions. Key parameters include the ratio of plasma frequency to ion gyrofrequency, the density, temperature and anisotropy of hot ions, and the cold-ion composition. The results show that amplitude, peak frequency and spectral width of EMIC waves can be related to linear properties of the anisotropy-driven instability, e.g. growth rate and plasma beta, through simple analytic formulas. Combined with a dynamic ring current model, this model can provide global EMIC wave information needed for radiation-belt modeling.

  2. Predictability in France : atmospheric forcing or land surface initial conditions?

    NASA Astrophysics Data System (ADS)

    Singla, S.; Martin, E.; Céron, J.-P.; Regimbeau, F.

    2010-09-01

    A first study of a hydrological forecasting suite has already been done at seasonal time scales over France (Céron and al., 2010) in a context of adaptation for water resources management. The results showed the feasibility of hydrological seasonal forecasts by forcing the hydrometeorological model Safran-Isba-Modcou (SIM) with seasonal atmospheric forecasts from the DEMETER project. Scores were better for hydrological variables than for atmospheric variables for four river catchments for the spring season. The purpose of the present study is to quantify the sources of predictability of the hydrometeorological system. Two experiences were conducted in order to address this issue. The first experience consisted in testing the impact of the land surface initial conditions. We used realistic land surface initial state produced by the operational SIM model for the specific year and 9 random years of Safran atmospheric analyses (temperature and precipitation) from 1971 to 2001, in a consistent way with the previous study (Céron et al, 2010). The other atmospheric parameters (wind, specific humidity, long wave and short wave radiation and cloudiness) come from the SAFRAN climatology over the same period. The second experience was designed to evaluate the impact of the atmospheric forcing with 9 random years, chosen for the land surface initial state. The atmospheric forcing (temperature and precipitation) comes from the Safran analysis system for the corresponding year. Some results of this study will be presented on soil wetness index (SWI) forecasts and river flows forecasts for all stations in France. We will compare deterministic and probabilistic scores of the two experiences with those of the hydrological forecasting suite built with the seasonal forecasts from the DEMETER project. Perspectives for the downscaling of seasonal forecasts will be discussed in a last part. Céron J-P, Tanguy G, Franchistéguy L, Martin E, Regimbeau F and Vidal J-P, 2010. Hydrological

  3. Predicting optimal conditions to minimize quality deterioration while maximizing safety and functional properties of irradiated egg

    NASA Astrophysics Data System (ADS)

    Yun, Hyejeong; Jung, Yeonkuk; Lee, Kyung Haeng; Song, Hyun Pa; Kim, Keehyuk; Jo, Cheorun

    2012-08-01

    Irradiation is an excellent method for improving the safety and functional properties of egg. However, the internal quality of egg can be deteriorated due to a rapid decrease in Haugh units. In this study, the optimal conditions for maintaining the quality and maximizing the safety and functional properties of egg were determined when combination of irradiation and chitosan coating was treated using response surface methodology (RSM). Independent degradation parameters—irradiation dose (0-2 kGy) and concentration of chitosan coating (0-2%) were assigned (-2,-1, 0, 1, 2), and 10 intervals were set on the basis of central composite design for the degradation experiment. The dependant variables within a confidence level less than 5% were Haugh units, foaming ability, foam stability, and number of Salmonella typhimurium. The predicted maximum values of Haugh units and foaming ability were 82.7 (irradiation dose 0.0006 kGy and concentration of chitosan solution 1.03%) and 62.2 mm (1.99 kGy and 0.86%), respectively. S. typhimurium inoculated on the egg surface was not detected after 1.86 kGy and 0.48%. Based on superimposing four-dimensional RSM with respect to freshness (Haugh units), functional property (foaming capacity and foam stability), and reduction of S. typhimurium, the predicted optimum ranges for irradiation dose and chitosan solution concentration were 0.35-0.65 kGy and 0.25-0.85%, respectively. The predicted optimum values were obtained from 0.45 kGy and 0.525%. This methodology can be used to predict egg quality and safety when different combination treatments were applied.

  4. 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

  5. Analysis of regression confidence intervals and Bayesian credible intervals for uncertainty quantification

    NASA Astrophysics Data System (ADS)

    Lu, Dan; Ye, Ming; Hill, Mary C.

    2012-09-01

    Confidence intervals based on classical regression theories augmented to include prior information and credible intervals based on Bayesian theories are conceptually different ways to quantify parametric and predictive uncertainties. Because both confidence and credible intervals are used in environmental modeling, we seek to understand their differences and similarities. This is of interest in part because calculating confidence intervals typically requires tens to thousands of model runs, while Bayesian credible intervals typically require tens of thousands to millions of model runs. Given multi-Gaussian distributed observation errors, our theoretical analysis shows that, for linear or linearized-nonlinear models, confidence and credible intervals are always numerically identical when consistent prior information is used. For nonlinear models, nonlinear confidence and credible intervals can be numerically identical if parameter confidence regions defined using the approximate likelihood method and parameter credible regions estimated using Markov chain Monte Carlo realizations are numerically identical and predictions are a smooth, monotonic function of the parameters. Both occur if intrinsic model nonlinearity is small. While the conditions of Gaussian errors and small intrinsic model nonlinearity are violated by many environmental models, heuristic tests using analytical and numerical models suggest that linear and nonlinear confidence intervals can be useful approximations of uncertainty even under significantly nonideal conditions. In the context of epistemic model error for a complex synthetic nonlinear groundwater problem, the linear and nonlinear confidence and credible intervals for individual models performed similarly enough to indicate that the computationally frugal confidence intervals can be useful in many circumstances. Experiences with these groundwater models are expected to be broadly applicable to many environmental models. We suggest that for

  6. 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

  7. Interval Training

    MedlinePlus

    ... before trying any type of interval training. Recent studies suggest, however, that interval training can be used safely for short periods even in individuals with heart disease. Also keep the risk of overuse injury in mind. If you rush into a strenuous workout before ...

  8. Baseline activity predicts working memory load of preceding task condition.

    PubMed

    Pyka, Martin; Hahn, Tim; Heider, Dominik; Krug, Axel; Sommer, Jens; Kircher, Tilo; Jansen, Andreas

    2013-11-01

    The conceptual notion of the so-called resting state of the brain has been recently challenged by studies indicating a continuing effect of cognitive processes on subsequent rest. In particular, activity in posterior parietal and medial prefrontal areas has been found to be modulated by preceding experimental conditions. In this study, we investigated which brain areas show working memory dependent patterns in subsequent baseline periods and how specific they are for the preceding experimental condition. During functional magnetic resonance imaging, 94 subjects performed a letter-version of the n-back task with the conditions 0-back and 2-back followed by a low-level baseline in which subjects had to passively observe the letters appearing. In a univariate analysis, 2-back served as control condition while 0-back, baseline after 0-back and baseline after 2-back were modeled as regressors to test for activity changes between both baseline conditions. Additionally, we tested, using Gaussian process classifiers, the recognition of task condition from functional images acquired during baseline. Besides the expected activity changes in the precuneus and medial prefrontal cortex, we found differential activity in the thalamus, putamen, and postcentral gyrus that were affected by the preceding task. The multivariate analysis revealed that images of the subsequent baseline block contain task related patterns that yield a recognition rate of 70%. The results suggest that the influence of a cognitive task on subsequent baseline is strong and specific for some areas but not restricted to areas of the so-called default mode network.

  9. Prediction and monitoring of fluid responsiveness after coronary bypass surgery using the Initial Systolic Time Interval: Preliminary results

    NASA Astrophysics Data System (ADS)

    Smorenberg, A.; Lust, E. J.; Verdaasdonk, R. M.; Groeneveld, A. B. J.; Meijer, J. H.

    2010-04-01

    The objective of the study is to develop a non-invasive method to optimize the assessment of cardiac preload and therapeutic fluid administration after coronary artery bypass surgery. Previous studies have reported that the pre-ejection period (PEP), obtained from the electro-cardiogram (ECG) and from the invasively measured arterial pressure Pa, can be used for this assessment as it is dependent on the cardiac preload. The Initial Systolic Time Interval (ISTI), obtained non-invasively by simultaneous measurement of the Electro-CardioGram (ECG) and Impedance CardioGram (ICG), is expected to depend on the cardiac preload as well. 16 patients, admitted to the Intensive Care Unit after coronary artery bypass surgery and presumably hypovolaemic, were measured during administration of 2×250 ml of an isosmotic colloidal fluid solution. The parameters PEP and ISTI were determined before and after the administrations and compared with the change in cardiac output (CO), obtained by a thermodilution technique. Preliminary results show significant relationships between ISTI and CO and between changes in both of these variables before and after fluid administration.

  10. 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...

  11. 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.

  12. 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.

  13. 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.

  14. Correct use of cone penetrometer sensors to predict subsurface conditions

    SciTech Connect

    Walker, J.L.; Rose, C.M.; Armstrong, S.C.; Burton, J.C.

    1997-09-01

    When cone penetrometer testing (CPT) technology is used with in-situ sensors and probes to characterize subsurface conditions in environmental investigations, each sensor must be calibrated with high quality, site specific data to establish essential interpretation criteria. Mechanical, geophysical, and chemical sensor data collected for a site in South Carolina without such controls were misleading. Core logs obtained subsequently had major lithologic discrepancies with the soil classification based on the CPT sensor data. In addition, detailed core sampling and laboratory analysis showed that the sensor data on chemical contaminants included false positive and false negative results. In contrast, for a site in Nebraska, CPT data calibrated with high quality site controls provided a detailed interpretation of subsurface conditions relevant to contaminant fate and transport. On the basis of the work in Nebraska, Argonne scientists are continuing to develop criteria to improve the interpretation of complex subsurface stratigraphy.

  15. 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.

  16. Prediction of lagoons' natural conditions using satellite data and GIS.

    PubMed

    Goksel, Cigdem; Seker, Dursun Z; Kabdasli, Sedat

    2003-08-01

    In this study, monitoring and management of coastlines were emphasized and usage of remotely sensed data and GIS has been proposed as alternative solution to conventional studies. An example of using satellite data for depth measurement in shallow areas is given. Past morphological and hydrodynamic structures were obtained by means of Remote Sensing technique and obtained data have been transferred to GIS. Results extracted from these measurements were compared with the bathymetric map and visualized by means of GIS. Our proposal is to use remotely sensed data combined with GIS in the cases where the data obtained via ground measurements have been inadequate. It has been shown that the integrated approach can be used satisfactorily in order to predict the possible effects of a river induced parameters such as turbidity on the coasts, because the suspended material in the water can be used as the tracer material in interpretation of remotely sensed data.

  17. QCT/FEA predictions of femoral stiffness are strongly affected by boundary condition modeling

    PubMed Central

    Rossman, Timothy; Kushvaha, Vinod; Dragomir-Daescu, Dan

    2015-01-01

    Quantitative computed tomography-based finite element models of proximal femora must be validated with cadaveric experiments before using them to assess fracture risk in osteoporotic patients. During validation it is essential to carefully assess whether the boundary condition modeling matches the experimental conditions. This study evaluated proximal femur stiffness results predicted by six different boundary condition methods on a sample of 30 cadaveric femora and compared the predictions with experimental data. The average stiffness varied by 280% among the six boundary conditions. Compared with experimental data the predictions ranged from overestimating the average stiffness by 65% to underestimating it by 41%. In addition we found that the boundary condition that distributed the load to the contact surfaces similar to the expected contact mechanics predictions had the best agreement with experimental stiffness. We concluded that boundary conditions modeling introduced large variations in proximal femora stiffness predictions. PMID:25804260

  18. Geomagnetic Secular Variation Prediction with Thermal Heterogeneous Boundary Conditions

    NASA Technical Reports Server (NTRS)

    Kuang, Weijia; Tangborn, Andrew; Jiang, Weiyuan

    2011-01-01

    It has long been conjectured that thermal heterogeneity at the core-mantle boundary (CMB) affects the geodynamo substantially. The observed two pairs of steady and strong magnetic flux lobes near the Polar Regions and the low secular variation in the Pacific over the past 400 years (and perhaps longer) are likely the consequences of this CMB thermal heterogeneity. There are several studies on the impact of the thermal heterogeneity with numerical geodynamo simulations. However, direct correlation between the numerical results and the observations is found very difficult, except qualitative comparisons of certain features in the radial component of the magnetic field at the CMB. This makes it difficult to assess accurately the impact of thermal heterogeneity on the geodynamo and the geomagnetic secular variation. We revisit this problem with our MoSST_DAS system in which geomagnetic data are assimilated with our geodynamo model to predict geomagnetic secular variations. In this study, we implement a heterogeneous heat flux across the CMB that is chosen based on the seismic tomography of the lowermost mantle. The amplitude of the heat flux (relative to the mean heat flux across the CMB) varies in the simulation. With these assimilation studies, we will examine the influences of the heterogeneity on the forecast accuracies, e.g. the accuracies as functions of the heterogeneity amplitude. With these, we could be able to assess the model errors to the true core state, and thus the thermal heterogeneity in geodynamo modeling.

  19. Teachers' Perceptions of Their Working Conditions: How Predictive of Policy-Relevant Outcomes? Working Paper 33

    ERIC Educational Resources Information Center

    Ladd, Helen F.

    2009-01-01

    This quantitative study uses data from North Carolina to examine the extent to which survey based perceptions of working conditions are predictive of policy-relevant outcomes, independent of other school characteristics such as the demographic mix of the school's students. Working conditions emerge as highly predictive of teachers' stated…

  20. The Use of Commercial Remote Sensing Systems in Predicting Helicopter Brownout Conditions

    DTIC Science & Technology

    2009-09-01

    REMOTE SENSING IN PREDICTING HELICOPTER BROWNOUT CONDITIONS by Christine Kay Rabaja September 2009 Thesis Advisor: Richard C. Olsen...Master’s Thesis 4. TITLE AND SUBTITLE The Use of Commercial Remote Sensing Systems in Predicting Helicopter Brownout Conditions 6. AUTHOR...soils susceptible to helicopter brownout . Helicopter brownout occurs when downwash disturbs the dust and sand beneath the aircraft during takeoff

  1. Predicting soil fumigant air concentrations under regional and diverse agronomic conditions.

    PubMed

    Cryer, Steven A

    2005-01-01

    SOFEA (SOil Fumigant Exposure Assessment system; Dow AgroSciences, Indianapolis, IN) is a new stochastic numerical modeling tool for evaluating and managing human inhalation exposure potential associated with the use of soil fumigants. SOFEA calculates fumigant concentrations in air arising from volatility losses from treated fields for large agricultural regions using multiple transient source terms (treated fields), geographical information systems (GIS) information, agronomic specific variables, user-specified buffer zones, and field reentry intervals. A modified version of the USEPA Industrial Source Complex Short Term model (ISCST3) is used for air dispersion calculations. Weather information, field size, application date, application rate, application type, soil incorporation depth, pesticide degradation rates in air, tarp presence, field retreatment, and other sensitive parameters are varied stochastically using Monte Carlo techniques to mimic region and crop specific agronomic practices. Regional land cover, elevation, and population information can be used to refine source placement (treated fields), dispersion calculations, and risk assessments. This paper describes the technical algorithms of SOFEA and offers comparisons of simulation predictions for the soil fumigant 1,3-dichloropropene (1,3-D) to actual regional air monitoring measurements from Kern, California. Comparison of simulation results to daily air monitoring observations is remarkable over the entire concentration distribution (average percent deviation of 44% and model efficiency of 0.98), especially considering numerous inputs such as meteorological conditions for SOFEA were unavailable and approximated by neighboring regions. Both current and anticipated and/or forecasted fumigant scenarios can be simulated using SOFEA to provide risk managers and product stewards the necessary information to make sound regulatory decisions regarding the use of soil fumigants in agriculture.

  2. 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

  3. Prediction of pharmacologically induced baroreflex sensitivity from local time and frequency domain indices of R-R interval and systolic blood pressure signals obtained during deep breathing.

    PubMed

    Arica, Sami; Firat Ince, N; Bozkurt, Abdi; Tewfik, Ahmed H; Birand, Ahmet

    2011-07-01

    Pharmacological measurement of baroreflex sensitivity (BRS) is widely accepted and used in clinical practice. Following the introduction of pharmacologically induced BRS (p-BRS), alternative assessment methods eliminating the use of drugs were in the center of interest of the cardiovascular research community. In this study we investigated whether p-BRS using phenylephrine injection can be predicted from non-pharmacological time and frequency domain indices computed from electrocardiogram (ECG) and blood pressure (BP) data acquired during deep breathing. In this scheme, ECG and BP data were recorded from 16 subjects in a two-phase experiment. In the first phase the subjects performed irregular deep breaths and in the second phase the subjects received phenylephrine injection. From the first phase of the experiment, a large pool of predictors describing the local characteristic of beat-to-beat interval tachogram (RR) and systolic blood pressure (SBP) were extracted in time and frequency domains. A subset of these indices was selected using twelve subjects with an exhaustive search fused with a leave one subject out cross validation procedure. The selected indices were used to predict the p-BRS on the remaining four test subjects. A multivariate regression was used in all prediction steps. The algorithm achieved best prediction accuracy with only two features extracted from the deep breathing data, one from the frequency and the other from the time domain. The normalized L2-norm error was computed as 22.9% and the correlation coefficient was 0.97 (p=0.03). These results suggest that the p-BRS can be estimated from non-pharmacological indices computed from ECG and invasive BP data related to deep breathing.

  4. Differential involvement of medial prefrontal cortex and basolateral amygdala extracellular signal-regulated kinase in extinction of conditioned taste aversion is dependent on different intervals of extinction following conditioning.

    PubMed

    Lin, P-Y; Wang, S-P; Tai, M-Y; Tsai, Y-F

    2010-11-24

    Extinction reflects a decrease in the conditioned response (CR) following non-reinforcement of a conditioned stimulus. Behavioral evidence indicates that extinction involves an inhibitory learning mechanism in which the extinguished CR reappears with presentation of an unconditioned stimulus. However, recent studies on fear conditioning suggest that extinction erases the original conditioning if the time interval between fear acquisition and extinction is short. The present study examined the effects of different intervals between acquisition and extinction of the original memory in conditioned taste aversion (CTA). Male Long-Evans rats acquired CTA by associating a 0.2% sucrose solution with malaise induced by i.p. injection of 4 ml/kg 0.15 M LiCl. Two different time intervals, 5 and 24 h, between CTA acquisition and extinction were used. Five or 24 h after CTA acquisition, extinction trials were performed, in which a bottle containing 20 ml of a 0.2% sucrose solution was provided for 10 min without subsequent LiCl injection. If sucrose consumption during the extinction trials was greater than the average water consumption, then rats were considered to have reached CTA extinction. Rats subjected to extinction trials lasting 24 h, but not 5 h, after acquisition re-exhibited the extinguished CR following injection of 0.15 M LiCl alone 7 days after acquisition. Extracellular signal-regulated kinase (ERK) in the medial prefrontal cortex (mPFC) and basolateral nucleus of the amygdala (BLA) was examined by Western blot after the first extinction trial. ERK activation in the mPFC was induced after the extinction trial beginning 5 h after acquisition, whereas the extinction trial performed 24 h after acquisition induced ERK activation in the BLA. These data suggest that the original conditioning can be inhibited or retained by CTA extinction depending on the time interval between acquisition and extinction and that the ERK transduction pathway in the mPFC and BLA is

  5. Sensitivity of Typhoon Track Predictions in a Regional Prediction System to Initial and Lateral Boundary Conditions

    DTIC Science & Technology

    2009-09-01

    less forecast skill due to a coarser res- olution. Miguez- Macho and Paegle (2000) suggest that accurate initial and lateral boundary conditions for a...nondeveloping ver- sus developing systems. J. Atmos. Sci., 38, 1132–1151. Miguez- Macho , G., and J. Paegle, 2000: Sensitivity of a global forecast model

  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. 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

  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. 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.

  11. Prediction of sand transport over immobile gravel from supply limited to capacity conditions.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The prediction of the transport of sand in armored gravel reaches downstream of dams is complicated by variable bed conditions ranging from sand transported through gravel to sand in transport over buried gravel. Knowledge of the rate of sand transport in these conditions, however, is necessary for...

  12. Sea surface temperatures and environmental conditions during the ;warm Pliocene; interval ( 4.1-3.2 Ma) in the Eastern Mediterranean (Cyprus)

    NASA Astrophysics Data System (ADS)

    Athanasiou, M.; Bouloubassi, I.; Gogou, A.; Klein, V.; Dimiza, M. D.; Parinos, C.; Skampa, E.; Triantaphyllou, M. V.

    2017-03-01

    Organic geochemical (alkenones) and micropaleontological (nannofossil) data from the Pissouri South section (PPS) in the island of Cyprus provided a detailed description of the paleoclimatic (sea surface temperature-SST) and paleoenvironmental conditions during the ;warm Pliocene; (c. 4.1-3.25 Ma) in the Eastern Mediterranean. We found that the suite of sapropel events recorded in the studied interval took place under conditions of increased SST, enhanced water column stratification and development of a productive deep chlorophyll maximum (DCM), as witnessed by the dominance of Florisphaera profunda species. Such conditions are similar to those prevailing during Quaternary sapropel formation, triggered by freshwater discharges from the N. African margin due to insolation-driven intensification of the African monsoon. The absence of F. profunda in Pliocene sapropels from central Mediterranean records highlights the sensitive response of the eastern basin to freshwater perturbations. Comparisons between alkenone and calcareous nannofossil assemblage patterns infer Pseudoemiliania lacunosa as the main alkenone producer in sapropel layers; yet Reticulofenestra spp. contribution cannot be ruled out. The first Pliocene alkenone-SST record in the E. Mediterranean presented here documents the ;warm Pliocene; period ( 4.1-3.25 Ma) characterized by mean SST of c. 26 °C. Distinct SST minima at 3.9 Ma, 3.58 Ma and between 3.34 and 3.31 Ma, correspond to the MIS Gi16, MIS MG12 and MIS M2 global cooling episodes, before the onset of the Northern Hemisphere glaciation. Our findings imply that the peak of the MIS M2 cooling in the Eastern Mediterranean may be up to 40 kyrs older than the age attributed before to benthic stable oxygen isotopes records of this event.

  13. 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.

  14. 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.

  15. 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.

  16. Development of a predictive program for Vibrio parahaemolyticus growth under various environmental conditions.

    PubMed

    Fujikawa, Hiroshi; Kimura, Bon; Fujii, Tateo

    2009-09-01

    In this study, we developed a predictive program for Vibrio parahaemolyticus growth under various environmental conditions. Raw growth data was obtained with a V. parahaemolyticus O3:K6 strain cultured at a variety of broth temperatures, pH, and salt concentrations. Data were analyzed with our logistic model and the parameter values of the model were analyzed with polynomial equations. A prediction program consisting of the growth model and the polynomial equations was then developed. After the range of the growth environments was modified, the program successfully predicted the growth for all environments tested. The program could be a useful tool to ensure the bacteriological safety of seafood.

  17. 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.

  18. Acoustical prediction methods for heating, ventilating, and air-conditioning (HVAC) systems

    NASA Astrophysics Data System (ADS)

    Ryherd, S. R.; Wang, L. M.

    2005-09-01

    The goal of this project is to compare and contrast various aspects of acoustical prediction methods for heating, ventilating, and air-conditioning (HVAC) systems. The three methods include two commonly used software programs and a custom spread sheet developed by the authors based on the American's Society of Heating, Refrigeration, and Air-conditioning Engineers (ASHRAE) Applications Handbook. Preliminary results indicate relatively good agreement between the three methods analyzed. The degree of disparity is predominately effected by the assumptions required by the end user. Research methods and results will be presented. This project provides a greater understanding of these acoustical prediction methods and their limitations.

  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. Interval of Uncertainty: An Alternative Approach for the Determination of Decision Thresholds, with an Illustrative Application for the Prediction of Prostate Cancer

    PubMed Central

    2016-01-01

    Often, for medical decisions based on test scores, a single decision threshold is determined and the test results are dichotomized into positive and negative diagnoses. It is therefore important to identify the decision threshold with the least number of misclassifications. The proposed method uses trichotomization: it defines an Uncertain Interval around the point of intersection between the two distributions of individuals with and without the targeted disease. In this Uncertain Interval the diagnoses are intermixed and the numbers of correct and incorrect diagnoses are (almost) equal. This Uncertain Interval is considered to be a range of test scores that is inconclusive and does not warrant a decision. It is expected that defining such an interval with some precision, prevents a relatively large number of false decisions, and therefore results in an increased accuracy or correct classifications rate (CCR) for the test scores outside this Uncertain Interval. Clinical data and simulation results confirm this. The results show that the CCR is systematically higher outside the Uncertain Interval when compared to the CCR of the decision threshold based on the maximized Youden index. For strong tests with a very small overlap between the two distributions, it can be difficult to determine an Uncertain Interval. In simulations, the comparison with an existing method for test-score trichotomization, the Two-graph Receiver Operating Characteristic (TG-ROC), showed smaller differences between the two distributions for the Uncertain Interval than for TG-ROC’s Intermediate Range and consequently a more improved CCR outside the Uncertain Interval. The main conclusion is that the Uncertain Interval method offers two advantages: 1. Identification of patients for whom the test results are inconclusive; 2. A higher estimated rate of correct decisions for the remaining patients. PMID:27829010

  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. Prediction of sand transport over immobile gravel from supply limited to capacity conditions

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Prediction of the transport of sand in channels armored with gravel downstream of dams is difficult but necessary for the range of bed conditions from supply limited to capacity transport. Previous work has shown that information on the mean elevation of the sand relative to the gravel and on the s...

  4. Informal Workplace Learning among Nurses: Organisational Learning Conditions and Personal Characteristics That Predict Learning Outcomes

    ERIC Educational Resources Information Center

    Kyndt, Eva; Vermeire, Eva; Cabus, Shana

    2016-01-01

    Purpose: This paper aims to examine which organisational learning conditions and individual characteristics predict the learning outcomes nurses achieve through informal learning activities. There is specific relevance for the nursing profession because of the rapidly changing healthcare systems. Design/Methodology/Approach: In total, 203 nurses…

  5. 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…

  6. Literature-based condition-specific miRNA-mRNA target prediction

    PubMed Central

    Oh, Minsik; Rhee, Sungmin; Moon, Ji Hwan; Chae, Heejoon; Lee, Sunwon; Kang, Jaewoo; Kim, Sun

    2017-01-01

    miRNAs are small non-coding RNAs that regulate gene expression by binding to the 3′-UTR of genes. Many recent studies have reported that miRNAs play important biological roles by regulating specific mRNAs or genes. Many sequence-based target prediction algorithms have been developed to predict miRNA targets. However, these methods are not designed for condition-specific target predictions and produce many false positives; thus, expression-based target prediction algorithms have been developed for condition-specific target predictions. A typical strategy to utilize expression data is to leverage the negative control roles of miRNAs on genes. To control false positives, a stringent cutoff value is typically set, but in this case, these methods tend to reject many true target relationships, i.e., false negatives. To overcome these limitations, additional information should be utilized. The literature is probably the best resource that we can utilize. Recent literature mining systems compile millions of articles with experiments designed for specific biological questions, and the systems provide a function to search for specific information. To utilize the literature information, we used a literature mining system, BEST, that automatically extracts information from the literature in PubMed and that allows the user to perform searches of the literature with any English words. By integrating omics data analysis methods and BEST, we developed Context-MMIA, a miRNA-mRNA target prediction method that combines expression data analysis results and the literature information extracted based on the user-specified context. In the pathway enrichment analysis using genes included in the top 200 miRNA-targets, Context-MMIA outperformed the four existing target prediction methods that we tested. In another test on whether prediction methods can re-produce experimentally validated target relationships, Context-MMIA outperformed the four existing target prediction methods. In

  7. [Development of a predictive program for microbial growth under various temperature conditions].

    PubMed

    Fujikawa, Hiroshi; Yano, Kazuyoshi; Morozumi, Satoshi; Kimura, Bon; Fujii, Tateo

    2006-12-01

    A predictive program for microbial growth under various temperature conditions was developed with a mathematical model. The model was a new logistic model recently developed by us. The program predicts Escherichia coli growth in broth, Staphylococcus aureus growth and its enterotoxin production in milk, and Vibrio parahaemolyticus growth in broth at various temperature patterns. The program, which was built with Microsoft Excel (Visual Basic Application), is user-friendly; users can easily input the temperature history of a test food and obtain the prediction instantly on the computer screen. The predicted growth and toxin production can be important indices to determine whether a food is microbiologically safe or not. This program should be a useful tool to confirm the microbial safety of commercial foods.

  8. 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.

  9. Predicting conditional means of explanatory variables for energy-demand forecasting

    SciTech Connect

    Parti, M.; Parti, C.B.; Gould, D.M.; Parris, K.M.

    1984-11-01

    The purpose of the research was to explore the feasibility of an economic and statistical approach to the problem of forecasting the conditional means of variables used to predict appliance-specific energy demand. The technique recognizes the necessity of using conditional means of explanatory variables, and it takes into account the changing distributions of these variables over time. Statistical relationships are used to derive the probability distribution of the explanatory variables, given ownership of an appliance such as a pool heater. The conditional means of the explanatory variables can then be calculated on the basis of this conditional probability distribution. The present research has found sizable differences in forecasts of appliance-specific energy demand generated from the conditional means approach and the non-specific approach.

  10. Behavioral Assessment of Hearing in 2 to 4 Year-old Children: A Two-interval, Observer-based Procedure Using Conditioned Play-based Responses

    PubMed Central

    Bonino, Angela Yarnell; Leibold, Lori J.

    2017-01-01

    Collecting reliable behavioral data from toddlers and preschoolers is challenging. As a result, there are significant gaps in our understanding of human auditory development for these age groups. This paper describes an observer-based procedure for measuring hearing sensitivity with a two-interval, two-alternative forced-choice paradigm. Young children are trained to perform a play-based, motor response (e.g., putting a block in a bucket) whenever they hear a target signal. An experimenter observes the child's behavior and makes a judgment about whether the signal was presented during the first or second observation interval; the experimenter is blinded to the true signal interval, so this judgment is based solely on the child's behavior. These procedures were used to test 2 to 4 year-olds (n = 33) with no known hearing problems. The signal was a 1,000 Hz warble tone presented in quiet, and the signal level was adjusted to estimate a threshold corresponding to 71%-correct detection. A valid threshold was obtained for 82% of children. These results indicate that the two-interval procedure is both feasible and reliable for use with toddlers and preschoolers. The two-interval, observer-based procedure described in this paper is a powerful tool for evaluating hearing in young children because it guards against response bias on the part of the experimenter. PMID:28190058

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

    PubMed

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

    2009-05-01

    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.

  12. 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.

  13. DFT-based prediction of fission product sorption on carbon structures under O2 ingress conditions

    NASA Astrophysics Data System (ADS)

    Londono-Hurtado, Alejandro; Szlufarska, Izabela; Morgan, Dane

    2013-06-01

    An isotherm based model for the prediction of Cs sorption on the carbon components of a High Temperature Reactor (HTR) under O2 ingress conditions is presented. Isotherms are derived from a thermodynamic model based on binding energies calculated using Density Functional Theory (DFT). The DFT derived isotherms are compared with isotherms obtained from experimental calculations and sources of discrepancies are discussed. A DFT only model and a second model combining DFT and experimental calculations are used to predict fission product inventories in a HTR vessel during O2 ingress conditions. Results suggest that the carbon type (i.e. graphitic vs. amorphous) plays a central role on fission product sorption and release. During normal reactor conditions (T around 1400 K, low P) graphitic carbon will absorb a small percentage of a monolayer of Cs, while amorphous carbon will be approximately saturated at an entire monolayer of Cs. Results also indicate that, for the case of O2 ingress to the reactor's vessel, the Cs will form Cs2O. In the case of graphitic carbon, the Cs2O will bind more weakly than Cs, leading to Cs release in the form of Cs2O during O ingress. However, the weak binding of Cs to graphite means that only small release is expected. In the case of amorphous carbon, Cs2O binds almost as strongly Cs, and so no significant change in Cs absorbed to the amorphous carbon is predicted, although the form of the absorbed Cs is predicted to be Cs2O. For the case of low release conditions, consistent with modern TRISO fuels, the core will adsorb the entire Cs inventory at normal operating temperatures. However, for high Cs release conditions, consistent with older TRISO fuels, the surface sites on the core will be saturated and most of the Cs will remain in gas form or plate out on other surfaces.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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

  19. Prediction of fluid forces acting on a hand model in unsteady flow conditions.

    PubMed

    Kudo, Shigetada; Yanai, Toshimasa; Wilson, Barry; Takagi, Hideki; Vennell, Ross

    2008-01-01

    The aim of this study was to develop a method to predict fluid forces acting on the human hand in unsteady flow swimming conditions. A mechanical system consisting of a pulley and chain mechanism and load cell was constructed to rotate a hand model in fluid flows. To measure the angular displacement of the hand model a potentiometer was attached to the axis of the rotation. The hand model was then fixed at various angles about the longitudinal axis of the hand model and rotated at different flow velocities in a swimming flume for 258 different trials to approximate a swimmer's stroke in unsteady flow conditions. Pressures were taken from 12 transducers embedded in the hand model at a sampling frequency of 200Hz. The resultant fluid force acting on the hand model was then determined on the basis of the kinetic and kinematic data taken from the mechanical system at the frequency of 200Hz. A stepwise regression analysis was applied to acquire higher order polynomial equations that predict the fluid force acting on the accelerating hand model from the 12 pressure values. The root mean square (RMS) difference between the resultant fluid force measured and that predicted from the single best-fit polynomial equation across all trials was 5N. The method developed in the present study accurately predicted the fluid forces acting on the hand model.

  20. 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.

  1. 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.

  2. Predicting metal uptake by wetland plants under aerobic and anaerobic conditions.

    PubMed

    van der Welle, Marlies E W; Roelofs, Jan G M; Op Den Camp, Huub J M; Lamers, Leon P M

    2007-04-01

    Metal pollution can be a serious threat to ecosystems at a global scale. Although the bioavailability of potentially toxic metals is determined by many biotic and abiotic factors, including pH and redox potential, total metal concentrations in the soil are used widely to assess or predict toxicity. In the present study we tested the effect of desiccation of soils differing in acidification potential and total heavy metal contamination on the growth and metal uptake of three typical, common wetland species: Caltha palustris, Juncus effusus, and Rumex hydrolapathum. We found that plant growth in wet soils mainly was determined by nutrient availability, though in dry soils the combined effects of acidification and increased metal availability prevailed. Metal uptake under anaerobic conditions was best predicted by the acidification potential (sediment S/[Ca + Mg] ratio), not by total metal concentrations. We propose that this is related to radial oxygen loss by wetland plant roots, which leads to acidification of the rhizosphere. Under aerobic conditions, plant metal uptake was best predicted by the amount of CaCl2-extractable metals. We conclude that total metal concentrations are not suitable for predicting bioavailability and that the above diagnostic parameters will provide insight into biogeochemical processes involved in toxicity assessment and soil policy.

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. Predicting Inner Heliospheric Solar Wind Conditions in Advance of Solar Probe Plus

    NASA Astrophysics Data System (ADS)

    Case, A. W.; Kasper, J. C.; Korreck, K. E.; Stevens, M. L.; Cohen, O.; Salem, C. S.; Halekas, J. S.; Larson, D. E.; Maruca, B. A.

    2012-12-01

    In advance of the upcoming inner heliospheric missions (Solar Orbiter and Solar Probe Plus) it is vital to have an accurate prediction of the range of solar wind conditions that occur between 9.5Rs and 0.7AU. These conditions will place constraints on instrument design and the operational modes that are used. In this paper, we discuss and compare different methods of predicting the solar wind bulk plasma parameters. One method uses observed 1AU conditions observed with the Wind spacecraft combined with scaling laws derived from Helios observations. We extend this simple model by using a more realistic solar wind velocity profile in addition to the Wind and Helios observations. Another method uses 3D MHD simulations from which solar wind conditions along a spacecraft trajectory can be extracted. We discuss some implications of these models in the design of the Solar Wind Electrons Alphas and Protons investigation, a suite of solar wind instruments being designed to fly on Solar Probe Plus.

  8. Maternal natal environment and breeding territory predict the condition and sex ratio of offspring.

    PubMed

    Bowers, E Keith; Thompson, Charles F; Sakaluk, Scott K

    2017-03-01

    Females in a variety of taxa adjust offspring sex ratios to prevailing ecological conditions. However, little is known about whether conditions experienced during a female's early ontogeny influence the sex ratio of her offspring. We tested for past and present ecological predictors of offspring sex ratios among known-age females that were produced as offspring and bred as adults in a population of house wrens. The body condition of offspring that a female produced and the proportion of her offspring that were male were negatively correlated with the size of the brood in which she herself was reared. The proportion of sons within broods was negatively correlated with maternal hatching date, and varied positively with the quality of a female's current breeding territory as predicted. However, females producing relatively more sons than daughters were less likely to return to breed in the population the following year. Although correlative, our results suggest that the rearing environment can have enduring effects on later maternal investment and sex allocation. Moreover, the overproduction of sons relative to daughters may increase costs to a female's residual reproductive value, constraining the extent to which sons might be produced in high-quality breeding conditions. Sex allocation in birds remains a contentious subject, largely because effects on offspring sex ratios are small. Our results suggest that offspring sex ratios are shaped by various processes and trade-offs that act throughout the female life history and ultimately reduce the extent of sex-ratio adjustment relative to classic theoretical predictions.

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

    SciTech Connect

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

    1995-12-31

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

  10. Assessment of Kinematic Brain Injury Metrics for Predicting Strain Responses in Diverse Automotive Impact Conditions.

    PubMed

    Gabler, Lee F; Crandall, Jeff R; Panzer, Matthew B

    2016-12-01

    Numerous injury criteria have been developed to predict brain injury using the kinematic response of the head during impact. Each criterion utilizes a metric that is some mathematical combination of the velocity and/or acceleration components of translational and/or rotational head motion. Early metrics were based on linear acceleration of the head, but recent injury criteria have shifted towards rotational-based metrics. Currently, there is no universally accepted metric that is suitable for a diverse range of head impacts. In this study, we assessed the capability of fifteen existing kinematic-based metrics for predicting strain-based brain response using four different automotive impact conditions. Tissue-level strains were obtained through finite element model simulation of 660 head impacts including occupant and pedestrian crash tests, and pendulum head impacts. Correlations between head kinematic metrics and predicted brain strain-based metrics were evaluated. Correlations between brain strain and metrics based on angular velocity were highest among those evaluated, while metrics based on linear acceleration were least correlative. BrIC and RVCI were the kinematic metrics with the highest overall correlation; however, each metric had limitations in certain impact conditions. The results of this study suggest that rotational head kinematics are the most important parameters for brain injury criteria.

  11. Efficient Prediction of Helicopter BVI Noise under Different Conditions of Wake and Blade Deformation

    NASA Astrophysics Data System (ADS)

    Inada, Yoshinobu; Yang, Choongmo; Iwanaga, Noriki; Aoyama, Takashi

    Predictions of helicopter BVI noise using three-dimensional Euler code with a single blade grid are conducted under three different conditions: BVI noise caused by (1) interaction between rotating blades and vortex shed from fixed wing vortex generator, (2) interaction between rotating blades and tip vortices shed from preceding blades, and (3) interaction between rotating blades with elastic deformation and shed tip vortices. In the CFD calculation, the Field Velocity Approach (FVA) and Scully’s vortex model are used to import the wake information into the calculation grid and to determine the induced velocity made by tip vortices, respectively (cases 1 3). Beddoes generalized wake model is used to prescribe the tip vortices position in the wake (cases 2 and 3). Information about blade elastic deformation is imported from HART II project experimental data into the calculation (case 3). Acoustic analyses based on Ffowcs-Williams and Hawkings (FW-H) equation are conducted subsequently in each case. The results from the calculations show good agreement with experiments in all three cases, indicating that application of FVA, Scully’s model, and Beddoes generalized wake model is effective for BVI noise prediction in this study, which is intended for low calculation cost using a single blade grid. Also, use of blade elastic deformation data in the calculation shows marked improvement in calculation precision. Consequently, the method used in this study can predict BVI noise under various conditions of wake or blade deformation with acceptable precision and low calculation cost.

  12. Predictive study on Tuscan extra virgin olive oil stability under several commercial conditions.

    PubMed

    Pagliarini, E; Zanoni, B; Giovanelli, G

    2000-04-01

    Industries aim to ensure extra virgin olive oil (EVOO) stability especially during commercial activities up to use by end consumers. The objective of this work was to set up predictive models of EVOO stability during commercial activities. Stability was studied on five lots of a batch of Tuscan virgin olive oil to simulate different commercial activities. Chemical, physical, and sensory analyses were carried out on EVOO samples. Experimental data were processed by multivariate analyses to select significant parameters and by regression analyses to set up kinetic models. A few parameters were found to be significant: hydroxytyrosol and tyrosol contents, carotenoid absorbance at 475 and 448 nm, alpha-tocopherol content, Rancimat induction time, and K(232). It was also shown that the stability of this EVOO was not significantly influenced by different uncontrolled bottling, transport, and storage conditions in supermarkets. Empirical models were set up to predict the time to reach a reference value for K(232).

  13. 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.

  14. 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

  15. 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.

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

    PubMed Central

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

    2016-01-01

    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 800 ms 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 240 ms post-CS onset and over occipital and frontal sites between 308 and 344 ms 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). PMID:26826400

  17. 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.

  18. Numerical prediction of a draft tube flow taking into account uncertain inlet conditions

    NASA Astrophysics Data System (ADS)

    Brugiere, O.; Balarac, G.; Corre, C.; Metais, O.; Flores, E.; Pleroy

    2012-11-01

    The swirling turbulent flow in a hydroturbine draft tube is computed with a non-intrusive uncertainty quantification (UQ) method coupled to Reynolds-Averaged Navier-Stokes (RANS) modelling in order to take into account in the numerical prediction the physical uncertainties existing on the inlet flow conditions. The proposed approach yields not only mean velocity fields to be compared with measured profiles, as is customary in Computational Fluid Dynamics (CFD) practice, but also variance of these quantities from which error bars can be deduced on the computed profiles, thus making more significant the comparison between experiment and computation.

  19. Paternal genetic contribution to offspring condition predicted by size of male secondary sexual character

    PubMed Central

    Sheldon, B. C.; Merila, J.; Qvarnström, A.; Gustafsson, L.; Ellegren, H.

    1997-01-01

    Whether females can obtain genetic benefits from mate choice is contentious, and the main problem faced by previous studies of natural populations is that many factors other than paternal genes contribute to offspring fitness. Here, we use comparisons between sets of naturally occurring maternal half-sibling collared flycatchers, Ficedula albicollis, to control for this problem. We show, first, that there are paternal genetic effects on nestling fledging condition, a character related to fitness in this species. Further, the magnitude of the paternal genetic contribution to this character is related to the size of a condition-dependent male secondary sexual character. Our results demonstrate that genetic benefits from mate choice can be predicted by the size of a secondary sexual character, and therefore provide direct support for indicator models of sexual selection.

  20. 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

  1. 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

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

    SciTech Connect

    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 mismatch 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.

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

    DOE PAGES

    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

  4. 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.

  5. Comparison of model predictions for coherence length to in-flight measurements at cruise conditions

    NASA Astrophysics Data System (ADS)

    Haxter, Stefan; Spehr, Carsten

    2017-03-01

    In this paper, we will focus on coherence lengths of pressure fluctuations underneath a turbulent boundary layer on an actual aircraft measured during a flight test. Coherence lengths of pressure fluctuations have already been measured in the past and various models have been set up in order to predict the values. However, most of the underlying data were measured at Mach numbers and pressures different from our region of interest and it is not known if the models are applicable. In some of the investigations also unknown alignment procedures between array and flow were used and it will be shown that this can have a considerable influence on the result. We have performed flight tests at cruising speed and altitude in which we took due account of this alignment by means of an array processing technique which is capable of determining the flow direction for each frequency bin under consideration. In this paper one of the data points will be evaluated and compared to the prediction models. From the differences and subsequently from the adopted run conditions for the measurement of the data of the models, several conclusions are drawn concerning scaling effects and importance of alignment. Also, two of the prediction models are adjusted to our measurements.

  6. Hf Radio Propagation At High Latitudes: Observations and Predictions For Quiet and Disturbed Conditions

    NASA Astrophysics Data System (ADS)

    Jacobsen, B.; Jodalen, V.; Cannon, P. S.; Smith, O.; Angling, M. J.

    High-frequency (HF) radio communications at high latitudes are greatly affected by geomagnetic and ionospheric conditions, and both civilian and military users need re- liable forecasts of the propagation environment. In recent years, a network of channel sounders known as DAMSON (Doppler and multipath sounding network) has been operated in Scandinavia (including Svalbard) on a nearly continous basis. We have analysed DAMSON measurements of multipath spread, Doppler shift and spread, and signal-to-noise ratio on four HF paths under both quiet and disturbed geomagnetic conditions. Correlations have been made with data from other ground-based installa- tions in the same geographic region (HF radars, magnetometers, ionosondes). Long signal delays (several ms) are regularly observed during midday at frequencies above the predicted Maximum Usable Frequency (MUF) and could possibly be caused by ground scatter. Large Doppler spreads (tens of Hz) are observed during disturbed con- ditions (substorms), when the ionospheric reflection point is located within the auroral oval. We suggest that forecasts of the HF multipath and Doppler environment based on sounder measurements could be utilized as additions to the regular HF predictions of e.g., the MUF and LUF of a propagation path.

  7. Key Comorbid Conditions that Are Predictive of Survival among Hemodialysis Patients

    PubMed Central

    Bragg-Gresham, Jennifer; Gillespie, Brenda W.; Tentori, Francesca; Pisoni, Ronald L.; Tighiouart, Hocine; Levey, Andrew S.; Port, Friedrich K.

    2009-01-01

    Background and objectives: Abstracting information about comorbid illnesses from the medical record can be time-consuming, particularly when a large number of conditions are under consideration. We sought to determine which conditions are most prognostic and whether comorbidity continues to contribute to a survival model once laboratory and clinical parameters have been accounted for. Design, setting, participants, & measurements: Comorbidity data were abstracted from the medical records of Dialysis Outcomes and Practice Pattern Study (DOPPS) I, II, and III participants using a standardized questionnaire. Models that were composed of different combinations of comorbid conditions and case-mix factors were compared for explained variance (R2) and discrimination (c statistic). Results: Seventeen comorbid conditions account for 96% of the total explained variance that would result if 45 comorbidities that were expected to be predictive of survival were added to a demographics-adjusted survival model. These conditions together had more discriminatory power (c statistic 0.67) than age alone (0.63) or serum albumin (0.60) and were equivalent to a combination of routine laboratory and clinical parameters (0.67). The strength of association of the individual comorbidities lessened when laboratory/clinical parameters were added, but all remained significant. The total R2 of a model adjusted for demographics and laboratory/clinical parameters increased from 0.13 to 0.17 upon addition of comorbidity. Conclusions: A relatively small list of comorbid conditions provides equivalent discrimination and explained variance for survival as a more extensive characterization of comorbidity. Comorbidity adds to the survival model a modest amount of independent prognostic information that cannot be substituted by clinical/laboratory parameters. PMID:19808231

  8. Prediction and visualization of redox conditions in the groundwater of Central Valley, California

    NASA Astrophysics Data System (ADS)

    Rosecrans, Celia Z.; Nolan, Bernard T.; Gronberg, JoAnn M.

    2017-03-01

    Regional-scale, three-dimensional continuous probability models, were constructed for aspects of redox conditions in the groundwater system of the Central Valley, California. These models yield grids depicting the probability that groundwater in a particular location will have dissolved oxygen (DO) concentrations less than selected threshold values representing anoxic groundwater conditions, or will have dissolved manganese (Mn) concentrations greater than selected threshold values representing secondary drinking water-quality contaminant levels (SMCL) and health-based screening levels (HBSL). The probability models were constrained by the alluvial boundary of the Central Valley to a depth of approximately 300 m. Probability distribution grids can be extracted from the 3-D models at any desired depth, and are of interest to water-resource managers, water-quality researchers, and groundwater modelers concerned with the occurrence of natural and anthropogenic contaminants related to anoxic conditions. Models were constructed using a Boosted Regression Trees (BRT) machine learning technique that produces many trees as part of an additive model and has the ability to handle many variables, automatically incorporate interactions, and is resistant to collinearity. Machine learning methods for statistical prediction are becoming increasing popular in that they do not require assumptions associated with traditional hypothesis testing. Models were constructed using measured dissolved oxygen and manganese concentrations sampled from 2767 wells within the alluvial boundary of the Central Valley, and over 60 explanatory variables representing regional-scale soil properties, soil chemistry, land use, aquifer textures, and aquifer hydrologic properties. Models were trained on a USGS dataset of 932 wells, and evaluated on an independent hold-out dataset of 1835 wells from the California Division of Drinking Water. We used cross-validation to assess the predictive performance of

  9. Prediction and visualization of redox conditions in the groundwater of Central Valley, California

    USGS Publications Warehouse

    Rosecrans, Celia Z.; Nolan, Bernard T.; Gronberg, JoAnn M.

    2017-01-01

    Regional-scale, three-dimensional continuous probability models, were constructed for aspects of redox conditions in the groundwater system of the Central Valley, California. These models yield grids depicting the probability that groundwater in a particular location will have dissolved oxygen (DO) concentrations less than selected threshold values representing anoxic groundwater conditions, or will have dissolved manganese (Mn) concentrations greater than selected threshold values representing secondary drinking water-quality contaminant levels (SMCL) and health-based screening levels (HBSL). The probability models were constrained by the alluvial boundary of the Central Valley to a depth of approximately 300 m. Probability distribution grids can be extracted from the 3-D models at any desired depth, and are of interest to water-resource managers, water-quality researchers, and groundwater modelers concerned with the occurrence of natural and anthropogenic contaminants related to anoxic conditions.Models were constructed using a Boosted Regression Trees (BRT) machine learning technique that produces many trees as part of an additive model and has the ability to handle many variables, automatically incorporate interactions, and is resistant to collinearity. Machine learning methods for statistical prediction are becoming increasing popular in that they do not require assumptions associated with traditional hypothesis testing. Models were constructed using measured dissolved oxygen and manganese concentrations sampled from 2767 wells within the alluvial boundary of the Central Valley, and over 60 explanatory variables representing regional-scale soil properties, soil chemistry, land use, aquifer textures, and aquifer hydrologic properties. Models were trained on a USGS dataset of 932 wells, and evaluated on an independent hold-out dataset of 1835 wells from the California Division of Drinking Water. We used cross-validation to assess the predictive performance of

  10. 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.

  11. 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.

  12. Why is it so difficult to represent stably stratified conditions in numerical weather prediction (NWP) models?

    NASA Astrophysics Data System (ADS)

    Sandu, Irina; Beljaars, Anton; Bechtold, Peter; Mauritsen, Thorsten; Balsamo, Gianpaolo

    2013-06-01

    In the 1990s, scientists at European Centre for Medium-Range Weather Forecasts (ECMWF) suggested that artificially enhancing turbulent diffusion in stable conditions improves the representation of two important aspects of weather forecasts, i.e., near-surface temperatures and synoptic cyclones. Since then, this practice has often been used for tuning the large-scale performance of operational numerical weather prediction (NWP) models, although it is widely recognized to be detrimental for an accurate representation of stable boundary layers. Here we investigate why, 20 years on, such a compromise is still needed in the ECMWF model. We find that reduced turbulent diffusion in stable conditions improves the representation of winds in stable boundary layers, but it deteriorates the large-scale flow and the near-surface temperatures. This suggests that enhanced diffusion is still needed to compensate for errors caused by other poorly represented processes. Among these, we identify the orographic drag, which influences the large-scale flow in a similar way to the turbulence closure for stable conditions, and the strength of the land-atmosphere coupling, which partially controls the near-surface temperatures. We also take a closer look at the relationship between the turbulence closure in stable conditions and the large-scale flow, which was not investigated in detail with a global NWP model. We demonstrate that the turbulent diffusion in stable conditions affects the large-scale flow by modulating not only the strength of synoptic cyclones and anticyclones, but also the amplitude of the planetary-scale standing waves.

  13. 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.

  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. A hybrid prognostic model for multistep ahead prediction of machine condition

    NASA Astrophysics Data System (ADS)

    Roulias, D.; Loutas, T. H.; Kostopoulos, V.

    2012-05-01

    Prognostics are the future trend in condition based maintenance. In the current framework a data driven prognostic model is developed. The typical procedure of developing such a model comprises a) the selection of features which correlate well with the gradual degradation of the machine and b) the training of a mathematical tool. In this work the data are taken from a laboratory scale single stage gearbox under multi-sensor monitoring. Tests monitoring the condition of the gear pair from healthy state until total brake down following several days of continuous operation were conducted. After basic pre-processing of the derived data, an indicator that correlated well with the gearbox condition was obtained. Consecutively the time series is split in few distinguishable time regions via an intelligent data clustering scheme. Each operating region is modelled with a feed-forward artificial neural network (FFANN) scheme. The performance of the proposed model is tested by applying the system to predict the machine degradation level on unseen data. The results show the plausibility and effectiveness of the model in following the trend of the timeseries even in the case that a sudden change occurs. Moreover the model shows ability to generalise for application in similar mechanical assets.

  16. 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.

  17. First-Principles Prediction of the Equilibrium Shape of Nanoparticles Under Realistic Electrochemical Conditions

    NASA Astrophysics Data System (ADS)

    Bonnet, Nicéphore; Marzari, Nicola

    2013-02-01

    A first-principles model of the electrochemical double layer is applied to study surface energies and surface coverage under realistic electrochemical conditions and to determine the equilibrium shape of metal nanoparticles as a function of applied potential. The potential bias is directly controlled by adding electronic charge to the system, while total energy calculations and thermodynamic relations are used to predict electrodeposition curves and changes in surface energies and coverage. This approach is applied to Pt surfaces subject to hydrogen underpotential deposition. The shape of Pt nanoparticles under a cathodic scan is shown to undergo an octahedric-to-cubic transition, which is more pronounced in alkaline media due to the interaction energy of the pH-dependent surface charge with the surface dipole.

  18. First-principles prediction of the equilibrium shape of nanoparticles under realistic electrochemical conditions.

    PubMed

    Bonnet, Nicéphore; Marzari, Nicola

    2013-02-22

    A first-principles model of the electrochemical double layer is applied to study surface energies and surface coverage under realistic electrochemical conditions and to determine the equilibrium shape of metal nanoparticles as a function of applied potential. The potential bias is directly controlled by adding electronic charge to the system, while total energy calculations and thermodynamic relations are used to predict electrodeposition curves and changes in surface energies and coverage. This approach is applied to Pt surfaces subject to hydrogen underpotential deposition. The shape of Pt nanoparticles under a cathodic scan is shown to undergo an octahedric-to-cubic transition, which is more pronounced in alkaline media due to the interaction energy of the pH-dependent surface charge with the surface dipole.

  19. 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.

  20. 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.

  1. Interval arithmetic in calculations

    NASA Astrophysics Data System (ADS)

    Bairbekova, Gaziza; Mazakov, Talgat; Djomartova, Sholpan; Nugmanova, Salima

    2016-10-01

    Interval arithmetic is the mathematical structure, which for real intervals defines operations analogous to ordinary arithmetic ones. This field of mathematics is also called interval analysis or interval calculations. The given math model is convenient for investigating various applied objects: the quantities, the approximate values of which are known; the quantities obtained during calculations, the values of which are not exact because of rounding errors; random quantities. As a whole, the idea of interval calculations is the use of intervals as basic data objects. In this paper, we considered the definition of interval mathematics, investigated its properties, proved a theorem, and showed the efficiency of the new interval arithmetic. Besides, we briefly reviewed the works devoted to interval analysis and observed basic tendencies of development of integral analysis and interval calculations.

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

    SciTech Connect

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

    1992-06-01

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

  3. Study on multi-scale blending initial condition perturbations for a regional ensemble prediction system

    NASA Astrophysics Data System (ADS)

    Zhang, Hanbin; Chen, Jing; Zhi, Xiefei; Wang, Yi; Wang, Yanan

    2015-08-01

    An initial conditions (ICs) perturbation method was developed with the aim to improve an operational regional ensemble prediction system (REPS). Three issues were identified and investigated: (1) the impacts of perturbation scale on the ensemble spread and forecast skill of the REPS; (2) the scale characteristic of the IC perturbations of the REPS; and (3) whether the REPS's skill could be improved by adding large-scale information to the IC perturbations. Numerical experiments were conducted to reveal the impact of perturbation scale on the ensemble spread and forecast skill. The scales of IC perturbations from the REPS and an operational global ensemble prediction system (GEPS) were analyzed. A "multi-scale blending" (MSB) IC perturbation scheme was developed, and the main findings can be summarized as follows: The growth rates of the ensemble spread of the REPS are sensitive to the scale of the IC perturbations; the ensemble forecast skills can benefit from large-scale perturbations; the global ensemble IC perturbations exhibit more power at larger scales, while the regional ensemble IC perturbations contain more power at smaller scales; the MSB method can generate IC perturbations by combining the small-scale component from the REPS and the large-scale component from the GEPS; the energy norm growth of the MSB-generated perturbations can be appropriate at all forecast lead times; and the MSB-based REPS shows higher skill than the original system, as determined by ensemble forecast verification.

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

    PubMed

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

    2016-12-01

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

  5. 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

  6. Significance of frailty for predicting adverse clinical outcomes in different patient groups with specific medical conditions.

    PubMed

    Ritt, Martin; Gaßmann, Karl-Günter; Sieber, Cornel Christian

    2016-10-01

    Frailty is a major health burden in an aging society. It constitutes a clinical state of reduced physiological reserves that is associated with a diminished ability to withstand internal and external stressors. Frail patients have an increased risk for adverse clinical outcomes, such as mortality, readmission to hospital, institutionalization and falls. Of further clinical interest, frailty might be at least in part reversible in some patients and subject to preventive strategies. In daily clinical practice older patients with a complex health status, who are mostly frail or at least at risk of developing frailty, are frequently cared for by geriatricians. Recently, clinicians and scientists from other medical disciplines, such as cardiology, pulmonology, gastroenterology, nephrology, endocrinology, rheumatology, surgery and critical care medicine also discovered frailty to be an interesting instrument for risk stratification of patients, including younger patients. In this review we highlight the results of recent studies that demonstrated the significance of frailty to predict adverse clinical outcomes in patients with specific medical conditions, such as cardiac, lung, liver and kidney diseases as well as diabetes mellitus, osteoarthritis, trauma patients, patients undergoing surgery and critically ill patients. Multiple studies in patients with the aforementioned specific medical conditions could be identified demonstrating a predictive role of frailty for several adverse clinical outcomes. The association between frailty and adverse clinical outcomes reported in these studies was in part independent of several major potential confounder factors, such as age, sex, race, comorbidities and disabilities and were also detected in younger patients.

  7. 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

  8. 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

  9. 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.

  10. 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.

  11. Review of Thawing Time Prediction Models Depending
on Process Conditions and Product Characteristics

    PubMed Central

    Kluza, Franciszek; Spiess, Walter E. L.; Kozłowicz, Katarzyna

    2016-01-01

    Summary Determining thawing times of frozen foods is a challenging problem as the thermophysical properties of the product change during thawing. A number of calculation models and solutions have been developed. The proposed solutions range from relatively simple analytical equations based on a number of assumptions to a group of empirical approaches that sometimes require complex calculations. In this paper analytical, empirical and graphical models are presented and critically reviewed. The conditions of solution, limitations and possible applications of the models are discussed. The graphical and semi--graphical models are derived from numerical methods. Using the numerical methods is not always possible as running calculations takes time, whereas the specialized software and equipment are not always cheap. For these reasons, the application of analytical-empirical models is more useful for engineering. It is demonstrated that there is no simple, accurate and feasible analytical method for thawing time prediction. Consequently, simplified methods are needed for thawing time estimation of agricultural and food products. The review reveals the need for further improvement of the existing solutions or development of new ones that will enable accurate determination of thawing time within a wide range of practical conditions of heat transfer during processing. PMID:27904387

  12. Review of Thawing Time Prediction Models Depending
on Process Conditions and Product Characteristics.

    PubMed

    Góral, Dariusz; Kluza, Franciszek; Spiess, Walter E L; Kozłowicz, Katarzyna

    2016-03-01

    Determining thawing times of frozen foods is a challenging problem as the thermophysical properties of the product change during thawing. A number of calculation models and solutions have been developed. The proposed solutions range from relatively simple analytical equations based on a number of assumptions to a group of empirical approaches that sometimes require complex calculations. In this paper analytical, empirical and graphical models are presented and critically reviewed. The conditions of solution, limitations and possible applications of the models are discussed. The graphical and semi--graphical models are derived from numerical methods. Using the numerical methods is not always possible as running calculations takes time, whereas the specialized software and equipment are not always cheap. For these reasons, the application of analytical-empirical models is more useful for engineering. It is demonstrated that there is no simple, accurate and feasible analytical method for thawing time prediction. Consequently, simplified methods are needed for thawing time estimation of agricultural and food products. The review reveals the need for further improvement of the existing solutions or development of new ones that will enable accurate determination of thawing time within a wide range of practical conditions of heat transfer during processing.

  13. Maturity of judgement in decision making for predictive testing for nontreatable adult-onset neurogenetic conditions: a case against predictive testing of minors.

    PubMed

    Richards, F H

    2006-11-01

    International guidelines developed to minimize harm from predictive testing for adult-onset, nontreatable neurogenetic conditions such as Huntington disease (HD) state that such testing should not be available to minors. Some authors have proposed that predictive testing for these conditions should be available to minors at the request of parents and/or of younger adolescents themselves. They highlight the lack of empirical evidence that predictive testing of minors causes harm and suggest that refusing to test minors may be detrimental. The current study focuses on the context of predictive test requests by adolescents younger than 18 years, and presents arguments and evidence that the risk of potential harm from testing such young people is sufficiently high to justify continued caution in this area. A study based on a model of psychosocial maturity found that the 3 factors involved in maturity of judgement in decision making - responsibility, temperance and perspective - continue to develop into late adolescence. There is also evidence that the prefrontal areas of the brain, which are involved in executive functions such as decision making, are not fully developed until early adulthood. Combined with evidence of adverse long-term effects, from research with adults who have undergone predictive testing, these findings constitute grounds for retaining a minimum age of 18 years for predictive testing for nontreatable conditions. Further research on assessment of maturity will assist with reaching a consensus on this issue.

  14. 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.

  15. 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

  16. Probabilistic prediction of hydrologic drought using a conditional probability approach based on the meta-Gaussian model

    NASA Astrophysics Data System (ADS)

    Hao, Zengchao; Hao, Fanghua; Singh, Vijay P.; Sun, Alexander Y.; Xia, Youlong

    2016-11-01

    Prediction of drought plays an important role in drought preparedness and mitigation, especially because of large impacts of drought and increasing demand for water resources. An important aspect for improving drought prediction skills is the identification of drought predictability sources. In general, a drought originates from precipitation deficit and thus the antecedent meteorological drought may provide predictive information for other types of drought. In this study, a hydrological drought (represented by Standardized Runoff Index (SRI)) prediction method is proposed based on the meta-Gaussian model taking into account the persistence and its prior meteorological drought condition (represented by Standardized Precipitation Index (SPI)). Considering the inherent nature of standardized drought indices, the meta-Gaussian model arises as a suitable model for constructing the joint distribution of multiple drought indices. Accordingly, the conditional distribution of hydrological drought can be derived analytically, which enables the probabilistic prediction of hydrological drought in the target period and uncertainty quantifications. Based on monthly precipitation and surface runoff of climate divisions of Texas, U.S., 1-month and 2-month lead predictions of hydrological drought are illustrated and compared to the prediction from Ensemble Streamflow Prediction (ESP). Results, based on 10 climate divisions in Texas, show that the proposed meta-Gaussian model provides useful drought prediction information with performance depending on regions and seasons.

  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. 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

  19. 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

  20. 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

  1. 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

    2017-03-01

    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

  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. 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.

  4. Experimental study of tyre/road contact forces in rolling conditions for noise prediction

    NASA Astrophysics Data System (ADS)

    Cesbron, Julien; Anfosso-Lédée, Fabienne; Duhamel, Denis; Ping Yin, Hai; Le Houédec, Donatien

    2009-02-01

    This paper deals with the experimental study of dynamical tyre/road contact for noise prediction. In situ measurements of contact forces and close proximity noise levels were carried out for a slick tyre rolling on six different road surfaces between 30 and 50 km/h. Additional texture profiles of the tested surfaces were taken on the wheel track. Normal contact stresses were measured at a sampling frequency of 10752 Hz using a line of pressure sensitive cells placed both along and perpendicular to the rolling direction. The contact areas obtained during rolling were smaller than in static conditions. This is mainly explained by the dynamical properties of tyre compounds, like the viscoelastic behaviour of the rubber. Additionally the root-mean-square of the resultant contact forces at various speeds was in the same order for a given road surface, while their spectra were quite different. This is certainly due to a spectral influence of bending waves propagating in the tyre during rolling, especially when the wavelength is small in comparison with the size of the contact patch. Finally, the levels of contact forces and close proximity noise measured at 30 km/h were correlated. Additional correlations with texture levels were performed. The results show that the macro-texture generates contact forces linearly around 800 Hz and consequently noise levels between 500 and 1000 Hz via the vibrations transmitted to the tyre.

  5. Predictive gaze during observation of irrational actions in adults with autism spectrum conditions.

    PubMed

    Marsh, L E; Pearson, A; Ropar, D; Hamilton, A F de C

    2015-01-01

    Understanding irrational actions may require the observer to make mental state inferences about why an action was performed. Individuals with autism spectrum conditions (ASC) have well documented difficulties with mentalizing; however, the degree to which rationality understanding is impaired in autism is not yet clear. The present study uses eye-tracking to measure online understanding of action rationality in individuals with ASC. Twenty adults with ASC and 20 typically developing controls, matched for age and IQ watched movies of rational and irrational actions while their eye movements were recorded. Measures of looking time, scan path and saccade latency were calculated. Results from looking time and scan path analyses demonstrate that participants with ASC have reduced visual attention to salient action features such as the action goal and the hand performing the action, regardless of action rationality. However, when participants with ASC do attend to these features, they are able to make anticipatory goal saccades as quickly as typically developing controls. Taken together these results indicate that individuals with autism have reduced attention to observed actions, but when attention is maintained, goal prediction is typical. We conclude that the basic mechanisms of action understanding are intact in individuals with ASC although there may be impairment in the top-down, social modulation of eye movements.

  6. 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.

  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. 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.

  10. CADDIS Volume 4. Data Analysis: Predicting Environmental Conditions from Biological Observations (PECBO Appendix)

    EPA Pesticide Factsheets

    Overview of PECBO Module, using scripts to infer environmental conditions from biological observations, statistically estimating species-environment relationships, methods for inferring environmental conditions, statistical scripts in module.

  11. Development of a noise prediction model under interrupted traffic flow conditions: a case study for Jaipur city.

    PubMed

    Agarwal, Sheetal; Swami, Bajrang L; Gupta, Akhilendra Bhushan

    2009-01-01

    The objective of this study is to develop an empirical noise prediction model for the evaluation of equivalent noise levels (Leq) under interrupted traffic flow conditions. A new factor tendency to blow horn (AH) was introduced in the conventional federal highway administrative noise prediction (FHWA) model and a comparative study was made between FHWA and modified FHWA models to evaluate the best suitability of the model. Monitoring and modeling of Leq were carried out at four selected intersections of Jaipur city. After comparison of the results, it was found that the modified FHWA model could be satisfactorily applied for Indian conditions as it gives acceptable results with a deviation of +/-3 dB (A). In addition, statistical analysis of the data comprising measured and estimated values shows a good agreement. Hence, the modified FHWA traffic noise prediction model can be applied to the cities having similar traffic conditions as in Jaipur city.

  12. 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

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

    PubMed

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

    2014-04-01

    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.

  14. 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

  15. 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.

  16. Use of Linear Prediction Uncertainty Analysis to Guide Conditioning of Models Simulating Surface-Water/Groundwater Interactions

    NASA Astrophysics Data System (ADS)

    Hughes, J. D.; White, J.; Doherty, J.

    2011-12-01

    Linear prediction uncertainty analysis in a Bayesian framework was applied to guide the conditioning of an integrated surface water/groundwater model that will be used to predict the effects of groundwater withdrawals on surface-water and groundwater flows. Linear prediction uncertainty analysis is an effective approach for identifying (1) raw and processed data most effective for model conditioning prior to inversion, (2) specific observations and periods of time critically sensitive to specific predictions, and (3) additional observation data that would reduce model uncertainty relative to specific predictions. We present results for a two-dimensional groundwater model of a 2,186 km2 area of the Biscayne aquifer in south Florida implicitly coupled to a surface-water routing model of the actively managed canal system. The model domain includes 5 municipal well fields withdrawing more than 1 Mm3/day and 17 operable surface-water control structures that control freshwater releases from the Everglades and freshwater discharges to Biscayne Bay. More than 10 years of daily observation data from 35 groundwater wells and 24 surface water gages are available to condition model parameters. A dense parameterization was used to fully characterize the contribution of the inversion null space to predictive uncertainty and included bias-correction parameters. This approach allows better resolution of the boundary between the inversion null space and solution space. Bias-correction parameters (e.g., rainfall, potential evapotranspiration, and structure flow multipliers) absorb information that is present in structural noise that may otherwise contaminate the estimation of more physically-based model parameters. This allows greater precision in predictions that are entirely solution-space dependent, and reduces the propensity for bias in predictions that are not. Results show that application of this analysis is an effective means of identifying those surface-water and

  17. 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.

  18. Analysis and prediction of the critical regions of antimicrobial peptides based on conditional random fields.

    PubMed

    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.

  19. 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

  20. Interval hypoxic training.

    PubMed

    Bernardi, L

    2001-01-01

    Interval hypoxic training (IHT) is a technique developed in the former Soviet Union, that consists of repeated exposures to 5-7 minutes of steady or progressive hypoxia, interrupted by equal periods of recovery. It has been proposed for training in sports, to acclimatize to high altitude, and to treat a variety of clinical conditions, spanning from coronary heart disease to Cesarean delivery. Some of these results may originate by the different effects of continuous vs. intermittent hypoxia (IH), which can be obtained by manipulating the repetition rate, the duration and the intensity of the hypoxic stimulus. The present article will attempt to examine some of the effects of IH, and, whenever possible, compare them to those of typical IHT. IH can modify oxygen transport and energy utilization, alter respiratory and blood pressure control mechanisms, induce permanent modifications in the cardiovascular system. IHT increases the hypoxic ventilatory response, increase red blood cell count and increase aerobic capacity. Some of these effects might be potentially beneficial in specific physiologic or pathologic conditions. At this stage, this technique appears interesting for its possible applications, but still largely to be explored for its mechanisms, potentials and limitations.

  1. The feedback-related negativity reflects “more or less” prediction error in appetitive and aversive conditions

    PubMed Central

    Huang, Yi; Yu, Rongjun

    2014-01-01

    Humans make predictions and use feedback to update their subsequent predictions. The feedback-related negativity (FRN) has been found to be sensitive to negative feedback as well as negative prediction error, such that the FRN is larger for outcomes that are worse than expected. The present study examined prediction errors in both appetitive and aversive conditions. We found that the FRN was more negative for reward omission vs. wins and for loss omission vs. losses, suggesting that the FRN might classify outcomes in a “more-or-less than expected” fashion rather than in the “better-or-worse than expected” dimension. Our findings challenge the previous notion that the FRN only encodes negative feedback and “worse than expected” negative prediction error. PMID:24904254

  2. Disentangling the control of tectonics, eustasy, trophic conditions and climate on shallow-marine carbonate production during the Aalenian-Oxfordian interval: From the western France platform to the western Tethyan domain

    NASA Astrophysics Data System (ADS)

    Andrieu, Simon; Brigaud, Benjamin; Barbarand, Jocelyn; Lasseur, Eric; Saucède, Thomas

    2016-11-01

    The objective of this work is to improve our understanding of the processes controlling changes in the architecture and facies of intracontinental carbonate platforms. We examined the facies and sequence stratigraphy of Aalenian to Oxfordian limestones of western France. Seventy-seven outcrop sections were studied and thirty-one sedimentary facies identified in five depositional environments ranging from lower offshore to backshore. Platform evolution was reconstructed along a 500 km cross-section. Twenty-two depositional sequences were identified on the entire western France platform and correlated with European third-order sequences at the biozone level, demonstrating that eustasy was the major factor controlling the cyclic trend of accommodation. The tectonic subsidence rate was computed from accommodation measurements from the Aalenian to the Oxfordian in key localities. Tectonism controlled the sedimentation rate and platform architecture at a longer time scale. Tectonic subsidence triggered the demise of carbonate production at the Bathonian/Callovian boundary while the uplift made possible the recovery of carbonate platform from Caen to Le Mans during the mid Oxfordian. Topography of the Paleozoic basement mainly controlled lateral variations of paleodepth within the western France platform until the mid Bathonian. A synthesis of carbonate production in the western Tethyan domain at that time was conducted. Stages of high carbonate production during the Bajocian/Bathonian and the middle to late Oxfordian are synchronous with low δ13C, high eccentricity intervals, and rather dry climate promoting (1) evaporation and carbonate supersaturation, and (2) oligotrophic conditions. Periods of low carbonate production during the Aalenian and from the middle Callovian to early Oxfordian correlate with high δ13C and low eccentricity intervals, characterized by wet climate and less oligotrophic conditions. Such conditions tend to diminish growth potential of carbonate

  3. Musical intervals in speech.

    PubMed

    Ross, Deborah; Choi, Jonathan; Purves, Dale

    2007-06-05

    Throughout history and across cultures, humans have created music using pitch intervals that divide octaves into the 12 tones of the chromatic scale. Why these specific intervals in music are preferred, however, is not known. In the present study, we analyzed a database of individually spoken English vowel phones to examine the hypothesis that musical intervals arise from the relationships of the formants in speech spectra that determine the perceptions of distinct vowels. Expressed as ratios, the frequency relationships of the first two formants in vowel phones represent all 12 intervals of the chromatic scale. Were the formants to fall outside the ranges found in the human voice, their relationships would generate either a less complete or a more dilute representation of these specific intervals. These results imply that human preference for the intervals of the chromatic scale arises from experience with the way speech formants modulate laryngeal harmonics to create different phonemes.

  4. Slip conditions with wall catalysis and radiation for multicomponent, nonequilibrium gas flow. [for predicting heat transfer to the space shuttle

    NASA Technical Reports Server (NTRS)

    Hendricks, W. L.

    1974-01-01

    The slip conditions for a multicomponent mixture with diffusion, wall-catalyzed atom recombination and thermal radiation are derived, and simplified expressions for engineering applications are presented. The gas mixture may be in chemical nonequilibrium with finite-rate catalytic recombination occurring on the wall. These boundary conditions, which are used for rarefied flow regime flow field calculations, are shown to be necessary for accurate predictions of skin friction and heat transfer coefficients in the rarefied portion of the space shuttle trajectory.

  5. Programming with Intervals

    NASA Astrophysics Data System (ADS)

    Matsakis, Nicholas D.; Gross, Thomas R.

    Intervals are a new, higher-level primitive for parallel programming with which programmers directly construct the program schedule. Programs using intervals can be statically analyzed to ensure that they do not deadlock or contain data races. In this paper, we demonstrate the flexibility of intervals by showing how to use them to emulate common parallel control-flow constructs like barriers and signals, as well as higher-level patterns such as bounded-buffer producer-consumer. We have implemented intervals as a publicly available library for Java and Scala.

  6. 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...

  7. Sensitivity of damage predictions to tissue level yield properties and apparent loading conditions.

    PubMed

    Niebur, G L; Yuen, J C; Burghardt, A J; Keaveny, T M

    2001-05-01

    High-resolution finite element models of trabecular bone failure could be used to augment current techniques for measuring damage in trabecular bone. However, the sensitivity of such models to the assumed tissue yield properties and apparent loading conditions is unknown. The goal of this study was to assess the sensitivity of the amount and mode (tension vs. compression) of tissue level yielding in trabecular bone to these factors. Linear elastic, high-resolution finite element models of nine bovine tibial trabecular bone specimens were used to calculate the fraction of the total tissue volume that exceeded each criterion for apparent level loading to the reported elastic limit in both on-axis and transverse compression and tension, and in shear. Four candidate yield criteria were studied, based on values suggested in the literature. Both the amount and the failure mode of yielded tissue were sensitive to the magnitudes of the tissue yield strains, the degree of tension-compression asymmetry of the yield criterion, and the applied apparent loads. The amount of yielded tissue was most sensitive to the orientation of the applied apparent loading, with the most tissue yielding for loading along the principal trabecular orientation and the least for loading perpendicular to it, regardless of the assumed tissue level yield criterion. Small changes in the magnitudes and the degree of asymmetry of the tissue yield criterion resulted in much larger changes in the amount of yielded tissue in the model. The results indicate that damage predictions based on high-resolution finite element models are highly sensitive to the assumed tissue yield properties. As such, good estimates of these values are needed before high-resolution finite element models can be applied to the study of trabecular bone damage. Regardless of the assumed tissue yield properties, the amount and type of damage that occurs in trabecular bone depends on the relative orientations of the applied apparent

  8. 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.

  9. A Deep Conditional Random Field Approach to Transmembrane Topology Prediction and Application to GPCR Three-Dimensional Structure Modeling.

    PubMed

    Wu, Hongjie; Wang, Kun; Lu, Liyao; Xue, Yu; Lyu, Qiang; Jiang, Min

    2016-08-25

    Transmembrane proteins play important roles in cellular energy production, signal transmission, and metabolism. Many shallow machine learning methods have been applied to transmembrane topology prediction, but the performance was limited by the large size of membrane proteins and the complex biological evolution information behind the sequence. In this paper, we proposed a novel deep approach based on conditional random fields named as dCRF-TM for predicting the topology of transmembrane proteins. Conditional random fields take into account more complicated interrelation between residue labels in full-length sequence than HMM and SVM-based methods. Three widely-used datasets were employed in the benchmark. DCRF-TM had the accuracy 95% over helix location prediction and the accuracy 78% over helix number prediction. DCRF-TM demonstrated a more robust performance on large size proteins (>350 residues) against 11 state-of-the-art predictors. Further dCRF-TM was applied to ab initio modeling three-dimensional structures of seven-transmembrane receptors, also known as G protein-coupled receptors. The predictions on 24 solved G protein-coupled receptors and unsolved vasopressin V2 receptor illustrated that dCRF-TM helped abGPCR-I-TASSER to improve TM-score 34.3% rather than using the random transmembrane definition. 2 out of 5 predicted models caught the experimental verified disulfide bond in vasopressin V2 receptor.

  10. Development of a threshold model to predict germination of Populus tomentosa seeds after harvest and storage under ambient condition.

    PubMed

    Wang, Wei-Qing; Cheng, Hong-Yan; Song, Song-Quan

    2013-01-01

    Effects of temperature, storage time and their combination on germination of aspen (Populus tomentosa) seeds were investigated. Aspen seeds were germinated at 5 to 30°C at 5°C intervals after storage for a period of time under 28°C and 75% relative humidity. The effect of temperature on aspen seed germination could not be effectively described by the thermal time (TT) model, which underestimated the germination rate at 5°C and poorly predicted the time courses of germination at 10, 20, 25 and 30°C. A modified TT model (MTT) which assumed a two-phased linear relationship between germination rate and temperature was more accurate in predicting the germination rate and percentage and had a higher likelihood of being correct than the TT model. The maximum lifetime threshold (MLT) model accurately described the effect of storage time on seed germination across all the germination temperatures. An aging thermal time (ATT) model combining both the TT and MLT models was developed to describe the effect of both temperature and storage time on seed germination. When the ATT model was applied to germination data across all the temperatures and storage times, it produced a relatively poor fit. Adjusting the ATT model to separately fit germination data at low and high temperatures in the suboptimal range increased the models accuracy for predicting seed germination. Both the MLT and ATT models indicate that germination of aspen seeds have distinct physiological responses to temperature within a suboptimal range.

  11. 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

  12. Interval estimations in metrology

    NASA Astrophysics Data System (ADS)

    Mana, G.; Palmisano, C.

    2014-06-01

    This paper investigates interval estimation for a measurand that is known to be positive. Both the Neyman and Bayesian procedures are considered and the difference between the two, not always perceived, is discussed in detail. A solution is proposed to a paradox originated by the frequentist assessment of the long-run success rate of Bayesian intervals.

  13. Direct interval volume visualization.

    PubMed

    Ament, Marco; Weiskopf, Daniel; Carr, Hamish

    2010-01-01

    We extend direct volume rendering with a unified model for generalized isosurfaces, also called interval volumes, allowing a wider spectrum of visual classification. We generalize the concept of scale-invariant opacity—typical for isosurface rendering—to semi-transparent interval volumes. Scale-invariant rendering is independent of physical space dimensions and therefore directly facilitates the analysis of data characteristics. Our model represents sharp isosurfaces as limits of interval volumes and combines them with features of direct volume rendering. Our objective is accurate rendering, guaranteeing that all isosurfaces and interval volumes are visualized in a crack-free way with correct spatial ordering. We achieve simultaneous direct and interval volume rendering by extending preintegration and explicit peak finding with data-driven splitting of ray integration and hybrid computation in physical and data domains. Our algorithm is suitable for efficient parallel processing for interactive applications as demonstrated by our CUDA implementation.

  14. 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

  15. 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

  16. Stable isotope models to predict geographic origin and cultivation conditions of marijuana.

    PubMed

    Hurley, Janet M; West, Jason B; Ehleringer, James R

    2010-06-01

    Here we describe stable isotope based models using hydrogen and carbon isotope ratios to predict geographic region-of-origin and growth environment for marijuana, with the intent of applying these models to analyses of marijuana trafficking in the USA. The models were developed on the basis of eradication specimens and border specimens seized throughout the USA. We tested reliability of the geographic region-of-origin and growth environment models with a "blind" set of 60 marijuana eradication specimens obtained from counties throughout the USA. The two geographic region-of-origin model predictions were 60-67% reliable and cultivation environment model predictions were 86% accurate for the blind specimens. We demonstrate here that stable isotope ratio analysis of marijuana seizures can significantly improve our understanding of marijuana distribution networks and it is for that purpose that these models were developed.

  17. 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

    2015-02-03

    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.

  18. 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.

  19. Predicting solvation free energies and thermodynamics in polar solvents and mixtures using a solvation-layer interface condition

    NASA Astrophysics Data System (ADS)

    Molavi Tabrizi, Amirhossein; Goossens, Spencer; Mehdizadeh Rahimi, Ali; Knepley, Matthew; Bardhan, Jaydeep P.

    2017-03-01

    We demonstrate that with two small modifications, the popular dielectric continuum model is capable of predicting, with high accuracy, ion solvation thermodynamics (Gibbs free energies, entropies, and heat capacities) in numerous polar solvents. We are also able to predict ion solvation free energies in water-co-solvent mixtures over available concentration series. The first modification to the classical dielectric Poisson model is a perturbation of the macroscopic dielectric-flux interface condition at the solute-solvent interface: we add a nonlinear function of the local electric field, giving what we have called a solvation-layer interface condition (SLIC). The second modification is including the microscopic interface potential (static potential) in our model. We show that the resulting model exhibits high accuracy without the need for fitting solute atom radii in a state-dependent fashion. Compared to experimental results in nine water-co-solvent mixtures, SLIC predicts transfer free energies to within 2.5 kJ/mol. The co-solvents include both protic and aprotic species, as well as biologically relevant denaturants such as urea and dimethylformamide. Furthermore, our results indicate that the interface potential is essential to reproduce entropies and heat capacities. These and previous tests of the SLIC model indicate that it is a promising dielectric continuum model for accurate predictions in a wide range of conditions.

  20. 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. Bora; Huang, P. G.; Hultgren, Lennart S.; Ashpis, David E.

    2001-01-01

    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, mu(sub t), with the intermittency factor, gamma. 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.

  1. 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.

  2. Teachers' Perceptions of Their Working Conditions: How Predictive of Planned and Actual Teacher Movement?

    ERIC Educational Resources Information Center

    Ladd, Helen F.

    2011-01-01

    This quantitative study examines the relationship between teachers' perceptions of their working conditions and their intended and actual departures from schools. Based on rich administrative data for North Carolina combined with a 2006 statewide survey administered to all teachers in the state, the study documents that working conditions are…

  3. 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…

  4. 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.

  5. 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.

  6. 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…

  7. 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...

  8. Application of the conditional nonlinear optimal perturbation method to the predictability study of the Kuroshio large meander

    NASA Astrophysics Data System (ADS)

    Wang, Qiang; Mu, Mu; Dijkstra, Henk A.

    2012-01-01

    A reduced-gravity barotropic shallow-water model was used to simulate the Kuroshio path variations. The results show that the model was able to capture the essential features of these path variations. We used one simulation of the model as the reference state and investigated the effects of errors in model parameters on the prediction of the transition to the Kuroshio large meander (KLM) state using the conditional nonlinear optimal parameter perturbation (CNOP-P) method. Because of their relatively large uncertainties, three model parameters were considered: the interfacial friction coefficient, the wind-stress amplitude, and the lateral friction coefficient. We determined the CNOP-Ps optimized for each of these three parameters independently, and we optimized all three parameters simultaneously using the Spectral Projected Gradient 2 (SPG2) algorithm. Similarly, the impacts caused by errors in initial conditions were examined using the conditional nonlinear optimal initial perturbation (CNOP-I) method. Both the CNOP-I and CNOP-Ps can result in significant prediction errors of the KLM over a lead time of 240 days. But the prediction error caused by CNOP-I is greater than that caused by CNOP-P. The results of this study indicate not only that initial condition errors have greater effects on the prediction of the KLM than errors in model parameters but also that the latter cannot be ignored. Hence, to enhance the forecast skill of the KLM in this model, the initial conditions should first be improved, the model parameters should use the best possible estimates.

  9. 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.

  10. 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...

  11. 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.

  12. Actual measurement, hygrothermal response experiment and growth prediction analysis of microbial contamination of central air conditioning system in Dalian, China

    PubMed Central

    Lv, Yang; Hu, Guangyao; Wang, Chunyang; Yuan, Wenjie; Wei, Shanshan; Gao, Jiaoqi; Wang, Boyuan; Song, Fangchao

    2017-01-01

    The microbial contamination of central air conditioning system is one of the important factors that affect the indoor air quality. Actual measurement and analysis were carried out on microbial contamination in central air conditioning system at a venue in Dalian, China. Illumina miseq method was used and three fungal samples of two units were analysed by high throughput sequencing. Results showed that the predominant fungus in air conditioning unit A and B were Candida spp. and Cladosporium spp., and two fungus were further used in the hygrothermal response experiment. Based on the data of Cladosporium in hygrothermal response experiment, this paper used the logistic equation and the Gompertz equation to fit the growth predictive model of Cladosporium genera in different temperature and relative humidity conditions, and the square root model was fitted based on the two environmental factors. In addition, the models were carried on the analysis to verify the accuracy and feasibility of the established model equation. PMID:28367963

  13. 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.

  14. Prediction of “Fear” Acquisition in Healthy Control Participants in a De Novo Fear-Conditioning Paradigm

    PubMed Central

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

    2006-01-01

    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, we 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, we 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, we found that anxiety sensitivity was more linked to individual differences in orienting response than differences in conditioning per se. PMID:17179530

  15. Application of Neural Networks to Predict UH-60L Electrical Generator Condition using (IMD-HUMS) Data

    DTIC Science & Technology

    2006-12-01

    their success rate for this faulting diagnosis . As in any prediction/forecasting model, the selection of appropriate model inputs is extremely...UH-60L helicopter generator. Many different neural networks will be evaluated for their success rate on this faulting diagnosis . A. CONDITION BASED...or alerts • Fault or failure diagnosis and health evaluation • Prognostics: projection of health profiles to future health or estimation of

  16. 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.

  17. 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.

  18. Aural-Nondetectability Model Predictions for Night-Vision Goggles across Ambient Lighting Conditions

    DTIC Science & Technology

    2015-12-01

    approximate starlight, half- moon , and room light. All of these devices operate in a linear mode under low-light conditions (no active gating to limit...mid, half- moon ; and 3) high, room light. Although the absolute luminance approximated the specified lighting conditions, the spectra from the light...Radiative addition (W/m2) Photopic only Photopic+infrared Starlight LED 3.93E-06 6.19E-08 1.23E-07 Half- Moon LED 3.40E-03 5.36E-05 2.31E-04 Room

  19. 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.

  20. Prediction of Fatigue Life for CFRP/Metal Bolted Joint under Temperature Conditions

    NASA Astrophysics Data System (ADS)

    Sekine, Naoyuki; Nakada, Masayuki; Miyano, Yasushi; Kuraishi, Akira; Tsai, Stephen W.

    In 1997, we proposed a prediction method of fatigue failure load for polymer composite structures under an arbitrary frequency, load ratio (minimum load/maximum load), and temperature from the data measured by constant elongation-rate (CER) tests under various temperatures and loading rates, and by fatigue tests at a single frequency under various temperatures. In this paper, tensile CER and fatigue tests of CFRP/metal bolted joint were conducted for various temperatures and loading rates. The applicability of the proposed method was experimentally proven for the tensile fatigue failure load for this CFRP/metal bolted joint.

  1. 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…

  2. SMALL AREA ESTIMATION OF INDICATORS OF STREAM CONDITION FOR MAIA USING HIERARCHICAL BAYES PREDICTION MODELS

    EPA Science Inventory

    Probability surveys of stream and river resources (hereafter referred to as streams) provide reliable estimates of stream condition when the areas for the estimates have sufficient number of sample sites. Monitoring programs are frequently asked to provide estimates for areas th...

  3. Predictive Gaze during Observation of Irrational Actions in Adults with Autism Spectrum Conditions

    ERIC Educational Resources Information Center

    Marsh, L. E.; Pearson, A.; Ropar, D.; Hamilton, A. F. de C.

    2015-01-01

    Understanding irrational actions may require the observer to make mental state inferences about why an action was performed. Individuals with autism spectrum conditions (ASC) have well documented difficulties with mentalizing; however, the degree to which rationality understanding is impaired in autism is not yet clear. The present study uses…

  4. 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...

  5. 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…

  6. 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.

  7. 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.

  8. Thermal conductivity of abnormally behaving liquids: Prediction methods and their applicability in microgravity conditions

    NASA Astrophysics Data System (ADS)

    Latini, G.; Passerini, G.

    1999-01-01

    Most organic and inorganic liquids show a general decrease of the thermal conductivity but very few compounds show an increase of thermal conductivity with temperature. Hydrogen and Water show an even more abnormal behavior since their thermal conductivity increases from the melting point to a reduced temperature of about 0.65-0.70 then decreases at higher temperatures. Due to their peculiar behavior, none of the general prediction methods developed for organic and inorganic liquids are effective for such substances in their saturated liquid state over the whole temperature range, from melting point to near the critical point. In this paper we present an estimation method able to evaluate thermal conductivity of Hydrogen and Water in their saturated liquid state from the melting point near to the critical point. The equation we present, as a new result of a previously introduced prediction method, links the thermal conductivity of water and Hydrogen with the reduced temperature. Tests, performed against experimental data, show a good accuracy of the method being the deviations generally less than 3% with peak deviations less than 10%.

  9. 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

  10. 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.

  11. 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.

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

    PubMed Central

    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

  13. An Evaluation of the Pavement Condition Index Prediction Model for Flexible Airfield Pavements.

    DTIC Science & Technology

    1983-09-01

    NO. 3 . RECiPIENT’S CATALOG NUMBER LSSR 11-83 LID,_ 13 -______9_ 4. TITLE (end Subtitle) S. TYPE OF REPORT & PERIOD COVERED AN EVALUATION OF THE...Flexible Models. ......... 42 Current Model Development ...........54 Dronen Model................67 Conclusion ................... 71 iv CHAPTER Page 3 ...13 2-2 General Guide for Establishing Rigid Pavement Condition................16 2- 3 Types of Distress in Airfield Pavement

  14. 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.

  15. 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

  16. 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.

  17. 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.

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

    NASA Astrophysics Data System (ADS)

    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.

  19. Conditional nonlinear optimal perturbations based on the particle swarm optimization and their applications to the predictability problems

    NASA Astrophysics Data System (ADS)

    Zheng, Qin; Yang, Zubin; Sha, Jianxin; Yan, Jun

    2017-02-01

    In predictability problem research, the conditional nonlinear optimal perturbation (CNOP) describes the initial perturbation that satisfies a certain constraint condition and causes the largest prediction error at the prediction time. The CNOP has been successfully applied in estimation of the lower bound of maximum predictable time (LBMPT). Generally, CNOPs are calculated by a gradient descent algorithm based on the adjoint model, which is called ADJ-CNOP. This study, through the two-dimensional Ikeda model, investigates the impacts of the nonlinearity on ADJ-CNOP and the corresponding precision problems when using ADJ-CNOP to estimate the LBMPT. Our conclusions are that (1) when the initial perturbation is large or the prediction time is long, the strong nonlinearity of the dynamical model in the prediction variable will lead to failure of the ADJ-CNOP method, and (2) when the objective function has multiple extreme values, ADJ-CNOP has a large probability of producing local CNOPs, hence making a false estimation of the LBMPT. Furthermore, the particle swarm optimization (PSO) algorithm, one kind of intelligent algorithm, is introduced to solve this problem. The method using PSO to compute CNOP is called PSO-CNOP. The results of numerical experiments show that even with a large initial perturbation and long prediction time, or when the objective function has multiple extreme values, PSO-CNOP can always obtain the global CNOP. Since the PSO algorithm is a heuristic search algorithm based on the population, it can overcome the impact of nonlinearity and the disturbance from multiple extremes of the objective function. In addition, to check the estimation accuracy of the LBMPT presented by PSO-CNOP and ADJ-CNOP, we partition the constraint domain of initial perturbations into sufficiently fine grid meshes and take the LBMPT obtained by the filtering method as a benchmark. The result shows that the estimation presented by PSO-CNOP is closer to the true value than the

  20. 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.

  1. 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.

  2. Head losses prediction and analysis in a bulb turbine draft tube under different operating conditions using unsteady simulations

    NASA Astrophysics Data System (ADS)

    Wilhelm, S.; Balarac, G.; Métais, O.; Ségoufin, C.

    2016-11-01

    Flow prediction in a bulb turbine draft tube is conducted for two operating points using Unsteady RANS (URANS) simulations and Large Eddy Simulations (LES). The inlet boundary condition of the draft tube calculation is a rotating two dimensional velocity profile exported from a RANS guide vane- runner calculation. Numerical results are compared with experimental data in order to validate the flow field and head losses prediction. Velocity profiles prediction is improved with LES in the center of the draft tube compared to URANS results. Moreover, more complex flow structures are obtained with LES. A local analysis of the predicted flow field using the energy balance in the draft tube is then introduced in order to detect the hydrodynamic instabilities responsible for head losses in the draft tube. In particular, the production of turbulent kinetic energy next to the draft tube wall and in the central vortex structure is found to be responsible for a large part of the mean kinetic energy dissipation in the draft tube and thus for head losses. This analysis is used in order to understand the differences in head losses for different operating points. The numerical methodology could then be improved thanks to an in-depth understanding of the local flow topology.

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. Predicting electromagnetic ion cyclotron wave amplitude from unstable ring current plasma conditions

    NASA Astrophysics Data System (ADS)

    Fu, Xiangrong; Cowee, Misa M.; Jordanova, Vania K.; Gary, S. Peter; Reeves, Geoffrey D.; Winske, Dan

    2016-11-01

    Electromagnetic ion cyclotron (EMIC) waves in the Earth's inner magnetosphere are enhanced fluctuations driven unstable by ring current ion temperature anisotropy. EMIC waves can resonate with relativistic electrons and play an important role in precipitation of MeV radiation belt electrons. In this paper, we investigate the excitation and saturation of EMIC instability in a homogeneous plasma using both linear theory and nonlinear hybrid simulations. We have explored a four-dimensional parameter space, carried out a large number of simulations, and derived a scaling formula that relates the saturation EMIC wave amplitude to initial plasma conditions. Such scaling can be used in conjunction with ring current models like ring current-atmosphere interactions model with self-consistent magnetic field to provide global dynamic EMIC wave maps that will be more accurate inputs for radiation belt modeling than statistical models.

  9. 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.

  10. Predicting the behaviour of polydisperse polymers in liquid chromatography under isocratic and gradient conditions.

    PubMed

    Schoenmakers, Peter; Fitzpatrick, Fiona; Grothey, Ricarda

    2002-08-02

    In this paper we describe how the existing theories to describe retention and peak width in isocratic and gradient-elution liquid chromatography can be expanded to describe the retention behaviour of natural and synthetic repetitive polymers, which feature distributions of molecules with different masses (and often different structures) rather than unambiguous molecular formulas. For polydisperse samples, it is vital that the model accommodates (isocratic) elution of sample components before the onset of a gradient, elution during the gradient, and elution after the completion of the gradient. The expanded models can readily be implemented in standard spreadsheet software, such as Excel. We have created such spreadsheets based on the conventional model for retention in reversed-phase liquid chromatography (RPLC) and on two different models for retention in normal-phase liquid chromatography. The implementation allows an easy visualization of the theoretical concept. Up to three different polymeric series can be entered, with a total of up to 100 peaks being computed and displayed in isocratic or gradient-elution chromatograms. Also visualized are "retention models" (diagrams of isocratic retention vs. composition) and "calibration curves" (retention or elution composition vs. molecular mass or degree of polymerization). The coefficients in the isocratic retention model may be correlated, as has often been observed in RPLC. It is shown that under certain conditions such a correlation corresponds to the existence of so-called critical (isocratic) conditions, at which all the members of a given polymeric series (same composition and end groups, different number of repeat units) show co-elution.

  11. 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.

  12. Inkbottle Pore-Method: Prediction of hygroscopic water content in hardened cement paste at variable climatic conditions

    SciTech Connect

    Espinosa, Rosa Maria . E-mail: espinosa@tuhh.de; Franke, Lutz

    2006-10-15

    The aim of this work is the development of a practicable method for the reliable prediction of the equilibrium hygroscopic water content in hardened cement paste and cement mortars at changing climatic conditions. Sorption thermodynamics and multi-scale pore structure of hardened cement paste build the basis of the new computation procedure. Drying and chemical aging lead to a formation of inkbottle pores. Their influence on sorption behaviour will be considered in particular by including them into the pore model. Experimental data of adsorption, desorption and scanning-isotherms verify the new computation method, which has been called 'IBP-Method' (inkbottle pores)

  13. Meteorologically conditioned time-series predictions of West Nile virus vector mosquitoes.

    PubMed

    Trawinski, P R; Mackay, D S

    2008-08-01

    An empirical model to forecast West Nile virus mosquito vector populations is developed using time series analysis techniques. Specifically, multivariate seasonal autoregressive integrated moving average (SARIMA) models were developed for Aedes vexans and the combined group of Culex pipiens and Culex restuans in Erie County, New York. Weekly mosquito collections data were obtained for the four mosquito seasons from 2002 to 2005 from the Erie County Department of Health, Vector and Pest Control Program. Climate variables were tested for significance with cross-correlation analysis. Minimum temperature (T(min)), maximum temperature (T(max)), average temperature (T(ave)), precipitation (P), relative humidity (R(H)), and evapotranspiration (E(T)) were acquired from the Northeast Regional Climate Center (NRCC) at Cornell University. Weekly averages or sums of climate variables were calculated from the daily data. Other climate indexes were calculated and were tested for significance with the mosquito population data, including cooling degree days base 60 degrees (C(DD_60)), cooling degree days base 63 (C(DD_63)), cooling degree days base 65 (C(DD_65)), a ponding index (I(P)), and an interactive C(DD_65)-precipitation variable (C(DD_65) x P(week_4)). Ae. vexans were adequately modeled with a (2,1,1)(1,1,0)(52) SARIMA model. The combined group of Culex pipiens-restuans were modeled with a (0,1,1)(1,1,0)(52) SARIMA model. The most significant meteorological variables for forecasting Aedes vexans abundance was the interactive C(DD_65) x P(week_4) variable at a lag of two weeks, E(T) x E(T) at a lag of five weeks, and C(DD_65) x C(DD_65) at a lag of seven weeks. The most significant predictive variables for the grouped Culex pipiens-restuans were C(DD_63) x C(DD_63) at a lag of zero weeks, C(DD_63) at a lag of eight weeks, and the cumulative maximum ponding index (I(Pcum)) at a lag of zero weeks.

  14. Postmigratory body condition and ovarian steroid production predict breeding decisions by female gray-headed albatrosses.

    PubMed

    Crossin, Glenn T; Phillips, Richard A; Wynne-Edwards, Katherine E; Williams, Tony D

    2013-01-01

    Carryover effects have been documented in many migratory bird species, but we know little about the physiological mechanisms that mediate those effects. Here we show that the energetic, endocrine, and aerobic characteristics of postmigratory female gray-headed albatrosses (Thalassarche chrysostoma) can affect their decision to breed. All females in this study, whether breeding or not, were secreting ovarian steroids when they arrived at the breeding colony at Bird Island, South Georgia, which suggests that all were responding to seasonal cues. However, deferring, nonbreeding birds were characterized by a steroid profile of high progesterone (P4) and low testosterone (T), whereas breeding birds showed the opposite pattern. Deferring birds also had low body mass, hematocrit, and hemoglobin. These results suggest that postmigratory condition can influence patterns of ovarian steroidogenesis and that the maintenance of high P4 without subsequent conversion to T favors breeding deferral. Whereas breeding females normally convert P4 to T, which is a key deterministic step toward 17β-estradiol synthesis, vitellogenesis, and follicle development, deferring females did not make this conversion and instead maintained high levels of P4, perhaps due to inhibition of the hydroxylase-lyase enzyme complex, thus rendering them infertile for the current season. Results are discussed within the context of the biennial breeding system of this species, and comparisons with other biennially and annually breeding albatrosses are made.

  15. 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.

  16. 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

  17. Predicted limits for evaporative cooling in heat stress relief of cattle in warm conditions.

    PubMed

    Berman, A

    2009-10-01

    Evaporative cooling of ambient air (EC) is a main path for heat stress relief in cattle kept in the shade of semi-confining structures. Evaporative cooling is particularly efficient in hot dry climates. We examined the potential of EC for heat stress relief in cattle in moderately warm and humid climates. The feasibility was examined by the reduction in ambient temperature (T(ac)) produced by EC as a function of ambient temperature (T(a)) and humidity (RH(a)). A data set (n = 139) of temperature and relative humidity (RH) produced by EC over a range of air temperature (25 to 50 degrees C) and humidity (10 to 70% RH) was analyzed by polynomial second order regressions. The analyses produced equations for the relations between ambient air temperature and ambient humidity and between respective conditions in air cooled by EC (T(c), RH(c)). Linear regressions were computed for a narrower temperature range (30 to 40 degrees C). In all equations, R(2) were >0.94 and regression terms were statistically significant. The T(ac) obtained by EC diminished by 0.3 degrees C per degrees C rise in T(a), indicating a reduced efficiency of EC with rising T(a). The T(ac) obtained by EC also was markedly reduced by rising ambient humidity and increased by RH(c). An attempt to sustain T(ac) at greater RH(a) by allowing a rise in RH(c) would only restore 2/3 of the reduction in T(ac) because the coefficient for the RH(a) effect on T(ac) is 1.5 larger than that of RH(c). The T(ac) attained by EC partially depends on the humidity in the cooled environment. Elevated RH(c) may impede animal skin and respiratory evaporative heat loss and lead to moisture accumulation in bedding. If the upper desired limit for RH(c) is 70%, at RH(a) smaller than 45% (typical for hot-dry environments) the T(ac) is larger than 7.5 degrees C, at RH(a) greater than 55% T(ac) is reduced to less than 5 degrees C, and at RH(a) of 57.5 to 60% T(ac) is about 2.5 degrees C. Coupling EC with forced air movement when T

  18. 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

  19. 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

  20. Evaluation of soil moisture regime prediction methods under different ecological conditions in the Pre-Pyrenees

    NASA Astrophysics Data System (ADS)

    Loaiza Usuga, J. C.; de Bello, F.; Pauwels, V. R. N.

    2009-04-01

    conditions where computational power is limited, and if one is careful in the interpretation of its results, the conclusions from this paper indicate that more attention should be paid to the use of hydrologic models for the estimation of soil moisture regimes.

  1. 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

  2. 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

  3. A knowledge gap analysis on multi-scale predictive ability for agriculturally derived sediments under South African conditions.

    PubMed

    van Zyl, A J

    2007-01-01

    Agriculture has been implicated as a major source of sediments in South Africa. The aim of the knowledge gap analysis was to understand the production and delivery components of agriculturally derived sediments under South African conditions and to assess the predictive ability to address the fate of these sediments from field to catchment scales. An overview is given of important erosion processes and erosion modelling applied in South Africa at the field and catchment scale. A limitation of the sediment models is that gully erosion is not simulated; therefore, the models should be complemented with gully erosion predictions if gullies are an important sediment source. Field-scale models inadequately predict sediment production localised at hydrologically sensitive areas as a result of saturation excess flow and/or throughflow. The discussion on erosion modelling reveals that more complex models have had limited application in South Africa because they require large and detailed data sets, and may have parameters that are difficult to measure or to estimate. A modelling framework is discussed which allows linking of sediment models requiring readily available data, gully erosion models/maps and the use of other techniques to assess the fate of agriculturally derived sediments from field to catchment scale.

  4. 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.

  5. 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.

  6. Serum POP concentrations are highly predictive of inner blubber concentrations at two extremes of body condition in northern elephant seals.

    PubMed

    Peterson, Michael G; Peterson, Sarah H; Debier, Cathy; Covaci, Adrian; Dirtu, Alin C; Malarvannan, Govindan; Crocker, Daniel E; Costa, Daniel P

    2016-11-01

    Long-lived, upper trophic level marine mammals are vulnerable to bioaccumulation of persistent organic pollutants (POPs). Internal tissues may accumulate and mobilize POP compounds at different rates related to the body condition of the animal and the chemical characteristics of individual POP compounds; however, collection of samples from multiple tissues is a major challenge to ecotoxicology studies of free-ranging marine mammals and the ability to predict POP concentrations in one tissue from another tissue remains rare. Northern elephant seals (Mirounga angustirostris) forage on mesopelagic fish and squid for months at a time in the northeastern Pacific Ocean, interspersed with two periods of fasting on land, which results in dramatic seasonal fluctuations in body condition. Using northern elephant seals, we examined commonly studied tissues in mammalian toxicology to describe relationships and determine predictive equations among tissues for a suite of POP compounds, including ΣDDTs, ΣPCBs, Σchlordanes, and ΣPBDEs. We collected paired blubber (inner and outer) and blood serum samples from adult female and male seals in 2012 and 2013 at Año Nuevo State Reserve (California, USA). For females (N = 24), we sampled the same seals before (late in molting fast) and after (early in breeding fast) their approximately seven month foraging trip. For males, we sampled different seals before (N = 14) and after (N = 15) their approximately four month foraging trip. We observed strong relationships among tissues for many, but not all compounds. Serum POP concentrations were strong predictors of inner blubber POP concentrations for both females and males, while serum was a more consistent predictor of outer blubber for males than females. The ability to estimate POP blubber concentrations from serum, or vice versa, has the potential to enhance toxicological assessment and physiological modeling. Furthermore, predictive equations may illuminate commonalities or

  7. 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

  8. Evolutionary relationships can be more important than abiotic conditions in predicting the outcome of plant-plant interactions.

    PubMed

    Soliveres, Santiago; Torices, Rubén; Maestre, Fernando T

    2012-10-01

    Positive and negative plant-plant interactions are major processes shaping plant communities. They are affected by environmental conditions and evolutionary relationships among the interacting plants. However, the generality of these factors as drivers of pairwise plant interactions and their combined effects remain virtually unknown. We conducted an observational study to assess how environmental conditions (altitude, temperature, irradiance and rainfall), the dispersal mechanism of beneficiary species and evolutionary relationships affected the co-occurrence of pairwise interactions in 11 Stipa tenacissima steppes located along an environmental gradient in Spain. We studied 197 pairwise plant-plant interactions involving the two major nurse plants (the resprouting shrub Quercus coccifera and the tussock grass S. tenacissima) found in these communities. The relative importance of the studied factors varied with the nurse species considered. None of the factors studied were good predictors of the co-ocurrence between S. tenacissima and its neighbours. However, both the dispersal mechanism of the beneficiary species and the phylogenetic distance between interacting species were crucial factors affecting the co-occurrence between Q. coccifera and its neighbours, while climatic conditions (irradiance) played a secondary role. Values of phylogenetic distance between 207-272.8 Myr led to competition, while values outside this range or fleshy-fruitness in the beneficiary species led to positive interactions. The low importance of environmental conditions as a general driver of pairwise interactions was caused by the species-specific response to changes in either rainfall or radiation. This result suggests that factors other than climatic conditions must be included in theoretical models aimed to generally predict the outcome of plant-plant interactions. Our study helps to improve current theory on plant-plant interactions and to understand how these interactions can

  9. 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

  10. Non-Sink Dissolution Conditions for Predicting Product Quality and In Vivo Performance of Supersaturating Drug Delivery Systems.

    PubMed

    Sun, Dajun D; Wen, Hong; Taylor, Lynne S

    2016-09-01

    With recent advances in the development of supersaturating oral dosage forms for poorly water-soluble drugs, pharmaceutical scientists are increasingly applying in vitro dissolution testing under non-sink conditions for a direct evaluation of their ability to generate and maintain supersaturation as a predictive surrogate for ensuring product quality and in vivo performance. However, the scientific rationale for developing the appropriate non-sink dissolution methodologies has not been extensively debated. This calls for a comprehensive discussion of recent research efforts on theoretical and experimental considerations of amorphous solubility, liquid-liquid phase separation, and phase transitions of drugs in a supersaturated solution when dissolution testing is performed under supersaturated non-sink conditions. In addition, we outline the concept of "sink index" that quantifies the magnitude of deviations from perfect sink dissolution conditions in the sink/non-sink continuum and some considerations of non-sink dissolution testing for marketed drug products. These factors should be carefully considered in recommending an adequately discriminatory dissolution method in the performance assessment of supersaturating drug delivery systems.

  11. 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.

  12. [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.

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

    DOE PAGES

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

    2016-10-03

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

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

    SciTech Connect

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

    2016-10-03

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

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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

  1. 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.

  2. Use of infrared ocular thermography to assess physiological conditions of pigs prior to slaughter and predict pork quality variation.

    PubMed

    Weschenfelder, Angela V; Saucier, Linda; Maldague, Xavier; Rocha, Luiene M; Schaefer, Allan L; Faucitano, Luigi

    2013-11-01

    Infrared thermography (IRT) body temperature readings were taken in the ocular region of 258 pigs immediately before slaughter. Levels of lactate were measured in blood taken in the restrainer. Meat quality was assessed in the longissimus dorsi (LD), semimembranosus (SM), and adductor muscles. Ocular IRT (IROT) temperature was correlated with blood lactate levels (r=0.20; P=0.001), with pH taken 1hour postmortem (pH1: r=-0.18; P=0.03) and drip loss (r=0.20; P=0.02) in the LD muscle, and with pH1 in the SM muscle (r=-0.20; P=0.02). Potentially, IROT may be a useful tool to assess the physiological conditions of pigs at slaughter and predict the variation of important meat quality traits. However, the magnitude of the correlations is rather low, so a further development of image capture technique and further studies under more variable preslaughter conditions ensuring a larger pork quality variation are needed.

  3. Overestimation of the second time interval replaces time-shrinking when the difference between two adjacent time intervals increases.

    PubMed

    Nakajima, Yoshitaka; Hasuo, Emi; Yamashita, Miki; Haraguchi, Yuki

    2014-01-01

    When the onsets of three successive sound bursts mark two adjacent time intervals, the second time interval can be underestimated when it is physically longer than the first time interval by up to 100 ms. This illusion, time-shrinking, is very stable when the first time interval is 200 ms or shorter (Nakajima et al., 2004, Perception, 33). Time-shrinking had been considered a kind of perceptual assimilation to make the first and the second time interval more similar to each other. Here we investigated whether the underestimation of the second time interval was replaced by an overestimation if the physical difference between the neighboring time intervals was too large for the assimilation to take place; this was a typical situation in which a perceptual contrast could be expected. Three experiments to measure the overestimation/underestimation of the second time interval by the method of adjustment were conducted. The first time interval was varied from 40 to 280 ms, and such overestimations indeed took place when the first time interval was 80-280 ms. The overestimations were robust when the second time interval was longer than the first time interval by 240 ms or more, and the magnitude of the overestimation was larger than 100 ms in some conditions. Thus, a perceptual contrast to replace time-shrinking was established. An additional experiment indicated that this contrast did not affect the perception of the first time interval substantially: The contrast in the present conditions seemed unilateral.

  4. 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.

  5. Ground-based GNSS ZTD/IWV estimation system for numerical weather prediction in challenging weather conditions

    NASA Astrophysics Data System (ADS)

    Rohm, Witold; Yuan, Yubin; Biadeglgne, Bertukan; Zhang, Kefei; Marshall, John Le

    2014-03-01

    The Global Navigation Satellite Systems (GNSS) are one of the very few tools that can provide continuous, unbiased, precise and robust atmosphere condition information. The extensive research of GNSS space-based segment (e.g. available precise, real-time satellite orbits and clocks), unlimited access to the ground-based Continuously Operating Reference Stations (CORS) GNSS networks along with the well established data processing methods provides an unprecedented opportunity to study the environmental impacts on the GNSS signal propagation. GNSS measurements have been successfully used in precise positioning, tectonic plate monitoring, ionosphere studies and troposphere monitoring. However all GNSS signals recorded on the ground by CORS are subject to ionosphere delay, troposphere delay, multipath and signal strength loss. Nowadays, the GNSS signal delays are gradually incorporated into the numerical weather prediction (NWP) models. Usually the Zenith Total Delay (ZTD) or Integrated Water Vapour (IWV) have been considered as an important source of water vapour contents and assimilated into the NWP models. However, successful assimilation of these products requires strict accuracy assessment, especially in the challenging severe weather conditions. In this study a number of GNSS signal processing strategies have been verified to obtain the best possible estimates of troposphere delays using a selection of International GNSS Service (IGS) orbit and clock products. Three different severe weather events (severe storm, flash flooding, flooding) have been investigated in this paper. The strategies considered are; 1) Double Differenced (DD) network solution with shortest baselines, 2) DD network solution with longest baselines, 3) DD baseline-by-baseline solution (tested but not considered), 4) Zero Differenced (ZD) Precise Point Positioning (PPP) based on ambiguity float solutions, all with precise orbits and clocks, and real time clocks and predicted orbits. The quality

  6. 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

  7. 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...

  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. The influence of polyethyleneglycols on predicting crystallisation conditions of lipase from wheat germ by dynamic light scattering studies

    NASA Astrophysics Data System (ADS)

    Jaramillo-Flores, Ma. Eugenia; Soriano-García, Manuel; Moreno, Abel

    1998-03-01

    The availability of lasers and the development of dynamic light scattering methods have led to a rebirth of the interest in light scattering applications in polymer sciences, biophysical chemistry and recently in biological macromolecules. In the case of these biomolecules, all the investigations have been focused on the crystallisation step, which is considered a handicap in protein crystallography, not only for the difficulties found in the search for crystallisation conditions, but also because little is known about crystal growth behaviour of protein molecules in solution [1] [L. Jancarik, S.H. Kim, J. Appl. Crystallogr., 24 (1991) 409] [2] [A. McPherson, Preparation and Analysis of Protein Crystals, Krieger, Malabar, FL, 1989, Chapter 4]. In this paper, the influence of polyethylene glycols ranging from polyethyleneglycol 400 to polyethyleneglycol 6000 molecular weight and of two alcohols (methanol and ethanol) on the aggregation steps of lipase from wheat germ at pH 6 and 9 has been studied in solution by the use of dynamic light scattering methods. It has been possible to evaluate whether the initial formation of clusters and the trend for aggregation is due to nucleation (crystal formation) or to random mechanisms (amorphous precipitate obtaining). Finally, it is shown how the experimental predictions are useful to design new experimental protocols in order to generate the first available nucleation of the protein studied, which will be grown by either macro or microseeding techniques.

  10. Predicting average wintertime wind and wave conditions in the North Atlantic sector from Eurasian snow cover in October

    NASA Astrophysics Data System (ADS)

    Brands, Swen

    2014-04-01

    The present study assesses the lead-lag teleconnection between Eurasian snow cover in October and the December-to-February mean boreal winter climate with respect to the predictability of 10 m wind speed and significant wave heights in the North Atlantic and adjacent seas. Lead-lag correlations exceeding a magnitude of 0.8 are found for the short time period of 1997/98-2012/13 (n = 16) for which daily satellite-sensed snow cover data is available to date. The respective cross-validated hindcast skill obtained from using linear regression as a statistical forecasting technique is similarly large in magnitude. When using a longer but degraded time series of weekly snow cover data for calculating the predictor variable (1979/80-2011/12, n = 34), hindcast skill decreases but yet remains significant over a large fraction of the study area. In addition, Monte-Carlo field significance tests reveal that the patterns of skill are globally significant. The proposed method might be used to make forecast decisions for wind and wave energy generation, seafaring, fishery and offshore drilling. To exemplify its potential suitability for the latter sector, it is additionally applied to DJF frequencies of significant wave heights exceeding 2 m, a threshold value above which mooring conditions at oil platforms are no longer optimal.

  11. 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.

  12. Interval timing behavior in Pallas's long-tongued bat (Glossophaga soricina).

    PubMed

    Toelch, Ulf; Winter, York

    2013-11-01

    Timing behavior in animals and its underlying mechanisms have been investigated extensively in the peak procedure, a variant of fixed interval procedures. In such experiments, individuals typically start responding with high frequency after an initial inactive time interval and continue their responses after peak time if rewards are omitted. This begs the so far unexplored question as to how timing behavior is influenced when such continuous responses are suppressed. Here, we present results from a nectar-feeding bat species, Glossophaga soricina, that was tested in a modified version of the peak procedure at three fixed time intervals (5 s, 11 s, 20 s). In contrast to standard peak procedures we imposed metabolic costs on individual responses which effectively suppressed trains of rapid responses during trials. Under this manipulation, bats' aggregated responses showed clear peaks around the peak time in the 5-s and 11-s schedules. Bats' responses in the 20-s schedule, however, did not peak around the fixed interval time. Crucially, an analysis of time intervals between successive revisits in all schedules revealed that bats revisited feeders at accurately timed intervals in all three conditions. The individual within trial behavioral responses showed clear oscillatory patterns throughout nonrewarded trials. These findings follow predictions from mechanistic timing models, like the striatal beat frequency model, and are discussed with regard to these models.

  13. 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.

  14. 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.

  15. 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.

  16. Temporal binding of interval markers

    PubMed Central

    Derichs, Christina; Zimmermann, Eckart

    2016-01-01

    How we estimate the passage of time is an unsolved mystery in neuroscience. Illusions of subjective time provide an experimental access to this question. Here we show that time compression and expansion of visually marked intervals result from a binding of temporal interval markers. Interval markers whose onset signals were artificially weakened by briefly flashing a whole-field mask were bound in time towards markers with a strong onset signal. We explain temporal compression as the consequence of summing response distributions of weak and strong onset signals. Crucially, temporal binding occurred irrespective of the temporal order of weak and strong onset markers, thus ruling out processing latencies as an explanation for changes in interval duration judgments. If both interval markers were presented together with a mask or the mask was shown in the temporal interval center, no compression occurred. In a sequence of two intervals, masking the middle marker led to time compression for the first and time expansion for the second interval. All these results are consistent with a model view of temporal binding that serves a functional role by reducing uncertainty in the final estimate of interval duration. PMID:27958311

  17. 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…

  18. 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).

  19. Predicting pore pressure and porosity from VSP data

    SciTech Connect

    Stone, D.G.

    1984-04-01

    Presently, VSP is being used to predict interval velocity and depth beneath the drill bit. The method is to exploit special properties of the VSP to produce a successful inversion to acoustic impedance. Depth and interval velocity are derived from the acoustic impedance prediction. This technique is often a valuable aid in making drilling decisions. Other rock properties may be computed from the same data. Pore pressure is one such rock parameter that can be computed from interval transit times and depth. The product of interval transit times, depth, normal compaction ratios, and an area constant is pore pressure. Pore pressure prediction is as reliable as the predicted velocities and depths. In reservoir evaluation, and sometimes in the well completion program, porosity is the important rock property. The interval transit times predicted beneath the bit can be used to compute porosity. Unlike pore pressure, porosity computations require knowledge or assumptions about the rock matrix and shale percentages. For certain conditions these values are known. Further penetration of a reef in search of deeper porous zones is an example of a viable condition for porosity prediction. For both these rock properties the same conventions employed by well log analysis in modifying and interpreting results are needed. Where the parameters assumed fit the actual conditions, the results should have merit. If not, further interpretation is required.

  20. 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…

  1. Children's Discrimination of Melodic Intervals.

    ERIC Educational Resources Information Center

    Schellenberg, E. Glenn; Trehub, Sandra E.

    1996-01-01

    Adults and children listened to tone sequences and were required to detect changes either from intervals with simple frequency ratios to intervals with complex ratios or vice versa. Adults performed better on changes from simple to complex ratios than on the reverse changes. Similar performance was observed for 6-year olds who had never taken…

  2. Interval Recognition in Minimal Context.

    ERIC Educational Resources Information Center

    Shatzkin, Merton

    1984-01-01

    Music majors were asked to identify interval when it was either preceded or followed by a tone moving in the same direction. Difficulties in interval recognition in context appear to be an effect not just of placement within the context or of tonality, but of particular combinations of these aspects. (RM)

  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. 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…

  5. 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.

  6. 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.

  7. Predicting the kinetics of Listeria monocytogenes and Yersinia enterocolitica under dynamic growth/death-inducing conditions, in Italian style fresh sausage.

    PubMed

    Iannetti, Luigi; Salini, Romolo; Sperandii, Anna Franca; Santarelli, Gino Angelo; Neri, Diana; Di Marzio, Violeta; Romantini, Romina; Migliorati, Giacomo; Baranyi, József

    2017-01-02

    Traditional Italian pork products can be consumed after variable drying periods, where the temporal decrease of water activity spans from optimal to inactivating values. This makes it necessary to A) consider the bias factor when applying culture-medium-based predictive models to sausage; B) apply the dynamic version (described by differential equations) of those models; C) combine growth and death models in a continuous way, including the highly uncertain growth/no growth range separating the two regions. This paper tests the applicability of published predictive models on the responses of Listeria monocytogenes and Yersinia enterocolitica to dynamic conditions in traditional Italian pork sausage, where the environment changes from growth-supporting to inhibitory conditions, so the growth and death models need to be combined. The effect of indigenous lactic acid bacteria was also taken into account in the predictions. Challenge tests were carried out using such sausages, inoculated separately with L. monocytogenes and Y. enterocolitica, stored for 480h at 8, 12, 18 and 20°C. The pH was fairly constant, while the water activity changed dynamically. The effects of the environment on the specific growth and death rate of the studied organisms were predicted using previously published predictive models and parameters. Microbial kinetics in many products with a long shelf-life and dynamic internal environment, could result in both growth and inactivation, making it difficult to estimate the bacterial concentration at the time of consumption by means of commonly available predictive software tools. Our prediction of the effect of the storage environment, where the water activity gradually decreases during a drying period, is designed to overcome these difficulties. The methodology can be used generally to predict and visualise bacterial kinetics under temporal variation of environments, which is vital when assessing the safety of many similar products.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Temporal Predictability Facilitates Causal Learning

    ERIC Educational Resources Information Center

    Greville, W. James; Buehner, Marc J.

    2010-01-01

    "Temporal predictability" refers to the regularity or consistency of the time interval separating events. When encountering repeated instances of causes and effects, we also experience multiple cause-effect temporal intervals. Where this interval is constant it becomes possible to predict when the effect will follow from the cause. In…

  13. The effect of the Earth's oblateness on predicting the shadow conditions of a distant spacecraft: Application to a fictitious lunar explorer

    NASA Astrophysics Data System (ADS)

    Song, Young-Joo; Kim, Bang-Yeop

    2016-01-01

    The effect of the Earth's oblateness on predicting the shadow events of a lunar spacecraft caused by the Earth's shadow is analyzed in this study. To ensure a reliable analysis, the proven 'line-of-intersection' method is modified and directly applied to predict the shadow conditions using a spheroidal model of the Earth and a conical shadow model. Two major lunar mission phases, namely, transfer and orbiting, are considered with corresponding fictitious initial conditions, and eclipse events are predicted and the results are compared using both spherical and spheroidal Earth models. For the lunar transfer phase, for which an Earth-bound highly elliptical orbit is assumed, not only the predicted entry and exit times of an event but also its duration are found to be more strongly shifted as the apogee altitude increases; for perigee and apogee altitudes of 1000 and 380,000 km, respectively, the maximum difference in predicted duration is found to be approximately 0.76 min for a penumbra event. For the lunar orbiting phase, for which a circular orbit around the Moon at an altitude of 100 km is assumed, a prediction difference of approximately half a minute on average and approximately one minute at maximum (e.g., 0.73 min for qumbra events, 1.03 min for penumbra events and 1.32 min for 'instantaneous' full sunlight events) can occur. The results of the present analysis highlight the importance of modeling the oblate shape of the Earth when predicting the shadow events of a distant spacecraft, and they are expected to provide numerous insights for any missions involving highly elliptical orbits around the Earth or travel to the Moon.

  14. Alternative Confidence Interval Methods Used in the Diagnostic Accuracy Studies.

    PubMed

    Erdoğan, Semra; Gülhan, Orekıcı Temel

    2016-01-01

    Background/Aim. It is necessary to decide whether the newly improved methods are better than the standard or reference test or not. To decide whether the new diagnostics test is better than the gold standard test/imperfect standard test, the differences of estimated sensitivity/specificity are calculated with the help of information obtained from samples. However, to generalize this value to the population, it should be given with the confidence intervals. The aim of this study is to evaluate the confidence interval methods developed for the differences between the two dependent sensitivity/specificity values on a clinical application. Materials and Methods. In this study, confidence interval methods like Asymptotic Intervals, Conditional Intervals, Unconditional Interval, Score Intervals, and Nonparametric Methods Based on Relative Effects Intervals are used. Besides, as clinical application, data used in diagnostics study by Dickel et al. (2010) has been taken as a sample. Results. The results belonging to the alternative confidence interval methods for Nickel Sulfate, Potassium Dichromate, and Lanolin Alcohol are given as a table. Conclusion. While preferring the confidence interval methods, the researchers have to consider whether the case to be compared is single ratio or dependent binary ratio differences, the correlation coefficient between the rates in two dependent ratios and the sample sizes.

  15. 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...

  16. Influence of lateral and top boundary conditions on regional air quality prediction: A multiscale study coupling regional and global chemical transport models

    NASA Astrophysics Data System (ADS)

    Tang, Youhua; Carmichael, Gregory R.; Thongboonchoo, Narisara; Chai, Tianfeng; Horowitz, Larry W.; Pierce, Robert B.; Al-Saadi, Jassim A.; Pfister, Gabriele; Vukovich, Jeffrey M.; Avery, Melody A.; Sachse, Glen W.; Ryerson, Thomas B.; Holloway, John S.; Atlas, Elliot L.; Flocke, Frank M.; Weber, Rodney J.; Huey, L. Gregory; Dibb, Jack E.; Streets, David G.; Brune, William H.

    2007-05-01

    The sensitivity of regional air quality model to various lateral and top boundary conditions is studied at 2 scales: a 60 km domain covering the whole USA and a 12 km domain over northeastern USA. Three global models (MOZART-NCAR, MOZART-GFDL and RAQMS) are used to drive the STEM-2K3 regional model with time-varied lateral and top boundary conditions (BCs). The regional simulations with different global BCs are examined using ICARTT aircraft measurements performed in the summer of 2004, and the simulations are shown to be sensitive to the boundary conditions from the global models, especially for relatively long-lived species, like CO and O3. Differences in the mean CO concentrations from three different global-model boundary conditions are as large as 40 ppbv, and the effects of the BCs on CO are shown to be important throughout the troposphere, even near surface. Top boundary conditions show strong effect on O3 predictions above 4 km. Over certain model grids, the model's sensitivity to BCs is found to depend not only on the distance from the domain's top and lateral boundaries, downwind/upwind situation, but also on regional emissions and species properties. The near-surface prediction over polluted area is usually not as sensitive to the variation of BCs, but to the magnitude of their background concentrations. We also test the sensitivity of model to temporal and spatial variations of the BCs by comparing the simulations with time-varied BCs to the corresponding simulations with time-mean and profile BCs. Removing the time variation of BCs leads to a significant bias on the variation prediction and sometime causes the bias in predicted mean values. The effect of model resolution on the BC sensitivity is also studied.

  17. Numerical prediction of the pressure fluctuations on small discharge condition of a pump-turbine at pump mode

    NASA Astrophysics Data System (ADS)

    Yao, Y. Y.; Xiao, Y. X.; Zhu, W.; An, S. H.; Wang, Z. W.

    2015-01-01

    The operational stability of the pump turbine at the pump mode will be greatly influenced by large pressure fluctuations when operated in the small-discharge conditions. Therefore, it is significant to analyse the flow characteristic under the small discharge operating conditions deeply. Study of the internal flow in the small discharge condition has been investigate in great detail combined with model experiments in this paper. The SST k-ω turbulence model is adopted to perform three-dimensional numerical simulation of the entire pump-turbine flow passage at optimal guide vanes opening. The numerical simulation results match well with experimental data. Then internal flow under the small discharge condition is analysed. The results show that the dominant frequency inside the flow passage is a relative low frequency. In addition, there are obvious complex flow phenomena inside the draft tube, runner and diffuser domains, such as secondary flow, backflow and even vortex, leading to strong unsteady flow and significant pressure fluctuation.

  18. Predictability of the Meteorological Conditions Favourable to Radiative Fog Formation During the 2011 ParisFog Campaign

    NASA Astrophysics Data System (ADS)

    Menut, Laurent; Mailler, Sylvain; Dupont, Jean-Charles; Haeffelin, Martial; Elias, Thierry

    2013-11-01

    Radiative fog formation is a complex phenomenon involving local physical and microphysical processes that take place when particular meteorological conditions occur. This study aims at quantifying the ability of a regional numerical weather model to analyze and forecast the conditions favourable to radiative fog formation at an instrumental site in the Paris area. Data from the ParisFog campaign have been used in order to quantify the meteorological conditions favorable to radiative fog formation (pre-fog conditions) by setting threshold values on the key meteorological variables driving this process: 2-m temperature tendency, 10-m wind speed, 2-m relative humidity and net infrared flux. Data from the ParisFog observation periods of November 2011 indicate that use of these thresholds leads to the detection of 87 % of cases in which radiative fog formation was observed. In order to evaluate the ability of a regional weather model to reproduce adequately these conditions, the same thresholds are applied to meteorological model fields in both analysis and forecast mode. It is shown that, with this simple methodology, the model detects 74 % of the meteorological conditions finally leading to observed radiative fog, and 48 % 2 days in advance. Finally, sensitivity tests are conducted in order to evaluate the impact of using larger time or space windows on the forecasting skills.

  19. 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.

  20. 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).

  1. Duration of inflation and conditions at the bounce as a prediction of effective isotropic loop quantum cosmology

    NASA Astrophysics Data System (ADS)

    Linsefors, Linda; Barrau, Aurelien

    2013-06-01

    Loop quantum cosmology with a scalar field is known to be closely linked with an inflationary phase. In this article, we study probabilistic predictions for the duration of slow-roll inflation, by assuming a minimalist massive scalar field as the main content of the Universe. The phase of the field in its “prebounce” oscillatory state is taken as a natural random parameter. We find that the probability for a given number of inflationary e-folds is quite sharply peaked around 145, which is consistent with the most favored minimum values. In this precise sense, a satisfactory inflation is therefore a clear prediction of loop gravity. In addition, we derive an original and stringent upper limit on the Barbero-Immirzi parameter. The general picture of inflation, superinflation, deflation, and superdeflation is also much clarified in the framework of bouncing cosmologies.

  2. Predicting crystal structures and properties of matter under extreme conditions via quantum mechanics: The pressure is on

    SciTech Connect

    Zurek, Eva; Grochala, Wojciech

    2014-11-27

    Experimental studies of compressed matter are now routinely conducted at pressures exceeding 1 mln atm (100 GPa) and occasionally they even surpass 10 mln atm (1 TPa). The structure and properties of solids that have been so significantly squeezed differ considerably from those know at ambient pressures (1 atm), often times 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 have been 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. Lastly, we forecast important problems that will be targeted by theory as theoretical methods undergo rapid development, along with the simultaneous increase of computational power.

  3. Predicting crystal structures and properties of matter under extreme conditions via quantum mechanics: The pressure is on

    DOE PAGES

    Zurek, Eva; Grochala, Wojciech

    2014-11-27

    Experimental studies of compressed matter are now routinely conducted at pressures exceeding 1 mln atm (100 GPa) and occasionally they even surpass 10 mln atm (1 TPa). The structure and properties of solids that have been so significantly squeezed differ considerably from those know at ambient pressures (1 atm), often times 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 themore » structures of solids under high pressure, automated crystal structure prediction (CSP) methods have been 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. Lastly, we forecast important problems that will be targeted by theory as theoretical methods undergo rapid development, along with the simultaneous increase of computational power.« less

  4. 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.

  5. 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.

  6. Finding Nested Common Intervals Efficiently

    NASA Astrophysics Data System (ADS)

    Blin, Guillaume; Stoye, Jens

    In this paper, we study the problem of efficiently finding gene clusters formalized by nested common intervals between two genomes represented either as permutations or as sequences. Considering permutations, we give several algorithms whose running time depends on the size of the actual output rather than the output in the worst case. Indeed, we first provide a straightforward O(n 3) time algorithm for finding all nested common intervals. We reduce this complexity by providing an O(n 2) time algorithm computing an irredundant output. Finally, we show, by providing a third algorithm, that finding only the maximal nested common intervals can be done in linear time. Considering sequences, we provide solutions (modifications of previously defined algorithms and a new algorithm) for different variants of the problem, depending on the treatment one wants to apply to duplicated genes.

  7. 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.

  8. Effect of selection and sequencing of representative wave conditions on process-based predictions of equilibrium embayed beach morphology

    NASA Astrophysics Data System (ADS)

    Daly, Christopher J.; Bryan, Karin R.; Gonzalez, Mauricio R.; Klein, Antonio H. F.; Winter, Christian

    2014-06-01

    In order to decrease the simulation time of morphodynamic models, often-complex wave climates are reduced to a few representative wave conditions (RWC). When applied to embayed beaches, a test of whether a reduced wave climate is representative or not is to see whether it can recreate the observed equilibrium (long-term averaged) bathymetry of the bay. In this study, the wave climate experienced at Milagro Beach, Tarragona, Spain was discretized into `average' and `extreme' RWCs. Process-based morphodynamic simulations were sequenced and merged based on `persistent' and `transient' forcing conditions, the results of which were used to estimate the equilibrium bathymetry of the bay. Results show that the effect of extreme wave events appeared to have less influence on the equilibrium of the bay compared to average conditions of longer overall duration. Additionally, the persistent seasonal variation of the wave climate produces pronounced beach rotation and tends to accumulate sediment at the extremities of the beach, rather than in the central sections. It is, therefore, important to account for directional variability and persistence in the selection and sequencing of representative wave conditions as is it essential for accurately balancing the effects beach rotation events.

  9. Physical condition and stress levels during early development reflect feeding rates and predict pre- and post-fledging survival in a nearshore seabird

    PubMed Central

    Lamb, Juliet S.; O'Reilly, Kathleen M.; Jodice, Patrick G. R.

    2016-01-01

    The effects of acute environmental stressors on reproduction in wildlife are often difficult to measure because of the labour and disturbance involved in collecting accurate reproductive data. Stress hormones represent a promising option for assessing the effects of environmental perturbations on altricial young; however, it is necessary first to establish how stress levels are affected by environmental conditions during development and whether elevated stress results in reduced survival and recruitment rates. In birds, the stress hormone corticosterone is deposited in feathers during the entire period of feather growth, making it an integrated measure of background stress levels during development. We tested the utility of feather corticosterone levels in 3- to 4-week-old nestling brown pelicans (Pelecanus occidentalis) for predicting survival rates at both the individual and colony levels. We also assessed the relationship of feather corticosterone to nestling body condition and rates of energy delivery to nestlings. Chicks with higher body condition and lower corticosterone levels were more likely to fledge and to be resighted after fledging, whereas those with lower body condition and higher corticosterone levels were less likely to fledge or be resighted after fledging. Feather corticosterone was also associated with intracolony differences in survival between ground and elevated nest sites. Colony-wide, mean feather corticosterone predicted nest productivity, chick survival and post-fledging dispersal more effectively than did body condition, although these relationships were strongest before fledglings dispersed away from the colony. Both reproductive success and nestling corticosterone were strongly related to nutritional conditions, particularly meal delivery rates. We conclude that feather corticosterone is a powerful predictor of reproductive success and could provide a useful metric for rapidly assessing the effects of changes in environmental

  10. 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.

  11. Retention prediction of a set of amino acids under gradient elution conditions in hydrophilic interaction liquid chromatography.

    PubMed

    Gika, Helen; Theodoridis, Georgios; Mattivi, Fulvio; Vrhovsek, Urska; Pappa-Louisi, Adriani

    2012-02-01

    The analysis of amino acids presents significant challenges to contemporary analytical separations. The present paper investigates the possibility of retention prediction in hydrophilic interaction chromatography (HILIC) gradient elution based on the analytical solution of the fundamental equation of the multilinear gradient elution derived for reversed-phase systems. A simple linear dependence of the logarithm of the solute retention (ln k) upon the volume fraction of organic modifier (φ) in a binary aqueous-organic mobile is adopted. Utility of the developed methodology was tested on the separation of a mixture of 21 amino acids carried out with 14 different gradient elution programs (from simple linear to multilinear and curved shaped) using ternary eluents in which a mixture of methanol and water (1:1, v/v) was the strong eluting member and acetonitrile was the weak solvent. Starting from at least two gradient runs, the prediction of solute retention obtained under all the rest gradients was excellent, even when curved gradient profiles were used. Development of such methodologies can be of great interest for a wide range of applications.

  12. 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.

  13. Use of the interRAI CHESS Scale to Predict Mortality among Persons with Neurological Conditions in Three Care Settings

    PubMed Central

    Hirdes, John P.; Poss, Jeffrey W.; Mitchell, Lori; Korngut, Lawrence; Heckman, George

    2014-01-01

    Background Persons with certain neurological conditions have higher mortality rates than the population without neurological conditions, but the risk factors for increased mortality within diagnostic groups are less well understood. The interRAI CHESS scale has been shown to be a strong predictor of mortality in the overall population of persons receiving health care in community and institutional settings. This study examines the performance of CHESS as a predictor of mortality among persons with 11 different neurological conditions. Methods Survival analyses were done with interRAI assessments linked to mortality data among persons in home care (n = 359,940), complex continuing care hospitals/units (n = 88,721), and nursing homes (n = 185,309) in seven Canadian provinces/territories. Results CHESS was a significant predictor of mortality in all 3 care settings for the 11 neurological diagnostic groups considered after adjusting for age and sex. The distribution of CHESS scores varied between diagnostic groups and within diagnostic groups in different care settings. Conclusions CHESS is a valid predictor of mortality in neurological populations in community and institutional care. It may prove useful for several clinical, administrative, policy-development, evaluation and research purposes. Because it is routinely gathered as part of normal clinical practice in jurisdictions (like Canada) that have implemented interRAI assessment instruments, CHESS can be derived without additional need for data collection. PMID:24914546

  14. 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.

  15. 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.

  16. High resolution time interval counter

    NASA Technical Reports Server (NTRS)

    Zhang, Victor S.; Davis, Dick D.; Lombardi, Michael A.

    1995-01-01

    In recent years, we have developed two types of high resolution, multi-channel time interval counters. In the NIST two-way time transfer MODEM application, the counter is designed for operating primarily in the interrupt-driven mode, with 3 start channels and 3 stop channels. The intended start and stop signals are 1 PPS, although other frequencies can also be applied to start and stop the count. The time interval counters used in the NIST Frequency Measurement and Analysis System are implemented with 7 start channels and 7 stop channels. Four of the 7 start channels are devoted to the frequencies of 1 MHz, 5 MHz or 10 MHz, while triggering signals to all other start and stop channels can range from 1 PPS to 100 kHz. Time interval interpolation plays a key role in achieving the high resolution time interval measurements for both counters. With a 10 MHz time base, both counters demonstrate a single-shot resolution of better than 40 ps, and a stability of better than 5 x 10(exp -12) (sigma(sub chi)(tau)) after self test of 1000 seconds). The maximum rate of time interval measurements (with no dead time) is 1.0 kHz for the counter used in the MODEM application and is 2.0 kHz for the counter used in the Frequency Measurement and Analysis System. The counters are implemented as plug-in units for an AT-compatible personal computer. This configuration provides an efficient way of using a computer not only to control and operate the counters, but also to store and process measured data.

  17. 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

  18. Cardiac strength-interval curves calculated using a bidomain tissue with a parsimonious ionic current

    PubMed Central

    Roth, Bradley J.

    2017-01-01

    The strength-interval curve plays a major role in understanding how cardiac tissue responds to an electrical stimulus. This complex behavior has been studied previously using the bidomain formulation incorporating the Beeler-Reuter and Luo-Rudy dynamic ionic current models. The complexity of these models renders the interpretation and extrapolation of simulation results problematic. Here we utilize a recently developed parsimonious ionic current model with only two currents—a sodium current that activates rapidly upon depolarization INa and a time-independent inwardly rectifying repolarization current IK—which reproduces many experimentally measured action potential waveforms. Bidomain tissue simulations with this ionic current model reproduce the distinctive dip in the anodal (but not cathodal) strength-interval curve. Studying model variants elucidates the necessary and sufficient physiological conditions to predict the polarity dependent dip: a voltage and time dependent INa, a nonlinear rectifying repolarization current, and bidomain tissue with unequal anisotropy ratios. PMID:28222136

  19. 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.

  20. [Fire behavior of ground surface fuels in Pinus koraiensis and Quercus mongolica mixed forest under no wind and zero slope condition: a prediction with extended Rothermel model].

    PubMed

    Zhang, Ji-Li; Liu, Bo-Fei; Chu, Teng-Fei; Di, Xue-Ying; Jin, Sen

    2012-06-01

    A laboratory burning experiment was conducted to measure the fire spread speed, residual time, reaction intensity, fireline intensity, and flame length of the ground surface fuels collected from a Korean pine (Pinus koraiensis) and Mongolian oak (Quercus mongolica) mixed stand in Maoer Mountains of Northeast China under the conditions of no wind, zero slope, and different moisture content, load, and mixture ratio of the fuels. The results measured were compared with those predicted by the extended Rothermel model to test the performance of the model, especially for the effects of two different weighting methods on the fire behavior modeling of the mixed fuels. With the prediction of the model, the mean absolute errors of the fire spread speed and reaction intensity of the fuels were 0.04 m X min(-1) and 77 kW X m(-2), their mean relative errors were 16% and 22%, while the mean absolute errors of residual time, fireline intensity and flame length were 15.5 s, 17.3 kW X m(-1), and 9.7 cm, and their mean relative errors were 55.5%, 48.7%, and 24%, respectively, indicating that the predicted values of residual time, fireline intensity, and flame length were lower than the observed ones. These errors could be regarded as the lower limits for the application of the extended Rothermel model in predicting the fire behavior of similar fuel types, and provide valuable information for using the model to predict the fire behavior under the similar field conditions. As a whole, the two different weighting methods did not show significant difference in predicting the fire behavior of the mixed fuels by extended Rothermel model. When the proportion of Korean pine fuels was lower, the predicted values of spread speed and reaction intensity obtained by surface area weighting method and those of fireline intensity and flame length obtained by load weighting method were higher; when the proportion of Korean pine needles was higher, the contrary results were obtained.

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. The 32nd CDC: System identification using interval dynamic models

    NASA Technical Reports Server (NTRS)

    Keel, L. H.; Lew, J. S.; Bhattacharyya, S. P.

    1992-01-01

    Motivated by the recent explosive development of results in the area of parametric robust control, a new technique to identify a family of uncertain systems is identified. The new technique takes the frequency domain input and output data obtained from experimental test signals and produces an 'interval transfer function' that contains the complete frequency domain behavior with respect to the test signals. This interval transfer function is one of the key concepts in the parametric robust control approach and identification with such an interval model allows one to predict the worst case performance and stability margins using recent results on interval systems. The algorithm is illustrated by applying it to an 18 bay Mini-Mast truss structure.

  9. 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.

  10. An Empirical Method for Establishing Positional Confidence Intervals Tailored for Composite Interval Mapping of QTL

    PubMed Central

    Love, Tanzy M.

    2010-01-01

    Background Improved genetic resolution and availability of sequenced genomes have made positional cloning of moderate-effect QTL realistic in several systems, emphasizing the need for precise and accurate derivation of positional confidence intervals (CIs) for QTL. Support interval (SI) methods based on the shape of the QTL likelihood curve have proven adequate for standard interval mapping, but have not been shown to be appropriate for use with composite interval mapping (CIM), which is one of the most commonly used QTL mapping methods. Results Based on a non-parametric confidence interval (NPCI) method designed for use with the Haley-Knott regression method for mapping QTL, a CIM-specific method (CIM-NPCI) was developed to appropriately account for the selection of background markers during analysis of bootstrap-resampled data sets. Coverage probabilities and interval widths resulting from use of the NPCI, SI, and CIM-NPCI methods were compared in a series of simulations analyzed via CIM, wherein four genetic effects were simulated in chromosomal regions with distinct marker densities while heritability was fixed at 0.6 for a population of 200 isolines. CIM-NPCIs consistently capture the simulated QTL across these conditions while slightly narrower SIs and NPCIs fail at unacceptably high rates, especially in genomic regions where marker density is high, which is increasingly common for real studies. The effects of a known CIM bias toward locating QTL peaks at markers were also investigated for each marker density case. Evaluation of sub-simulations that varied according to the positions of simulated effects relative to the nearest markers showed that the CIM-NPCI method overcomes this bias, offering an explanation for the improved coverage probabilities when marker densities are high. Conclusions Extensive simulation studies herein demonstrate that the QTL confidence interval methods typically used to positionally evaluate CIM results can be dramatically improved

  11. Use of statistical modeling to predict the effect of formulation composition on coacervation, silicone deposition, and conditioning sensory performance of cationic cassia polymers.

    PubMed

    Lepilleur, Carole; Mullay, John; Kyer, Carol; McCalister, Pam; Clifford, Ted

    2011-01-01

    Formulation composition has a dramatic influence on coacervate formation in conditioning shampoo. The purpose of this study is to correlate the amount of coacervate formation of novel cationic cassia polymers to the corresponding conditioning profiles on European brown hair using silicone deposition, cationic polymer deposition and sensory evaluation. A design of experiments was conducted by varying the levels of three surfactants (sodium lauryl ether sulfate, sodium lauryl sulfate, and cocamidopropyl betaine) in formulations containing cationic cassia polymers of different cationic charge density (1.7 and 3.0m Eq/g). The results show formulation composition dramatically affects physical properties, coacervation, silicone deposition, cationic polymer deposition and hair sensory attributes. Particularly, three parameters are of importance in determining silicone deposition: polymer charge, surfactant (micelle) charge and total amount of surfactant (micelle aspect ratio). Both sensory panel testing and silicone deposition results can be predicted with a high confidence level using statistical models that incorporate these parameters.

  12. 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…

  13. 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: .

  14. Quantifying uncertainty on sediment loads using bootstrap confidence intervals

    NASA Astrophysics Data System (ADS)

    Slaets, Johanna I. F.; Piepho, Hans-Peter; Schmitter, Petra; Hilger, Thomas; Cadisch, Georg

    2017-01-01

    Load estimates are more informative than constituent concentrations alone, as they allow quantification of on- and off-site impacts of environmental processes concerning pollutants, nutrients and sediment, such as soil fertility loss, reservoir sedimentation and irrigation channel siltation. While statistical models used to predict constituent concentrations have been developed considerably over the last few years, measures of uncertainty on constituent loads are rarely reported. Loads are the product of two predictions, constituent concentration and discharge, integrated over a time period, which does not make it straightforward to produce a standard error or a confidence interval. In this paper, a linear mixed model is used to estimate sediment concentrations. A bootstrap method is then developed that accounts for the uncertainty in the concentration and discharge predictions, allowing temporal correlation in the constituent data, and can be used when data transformations are required. The method was tested for a small watershed in Northwest Vietnam for the period 2010-2011. The results showed that confidence intervals were asymmetric, with the highest uncertainty in the upper limit, and that a load of 6262 Mg year-1 had a 95 % confidence interval of (4331, 12 267) in 2010 and a load of 5543 Mg an interval of (3593, 8975) in 2011. Additionally, the approach demonstrated that direct estimates from the data were biased downwards compared to bootstrap median estimates. These results imply that constituent loads predicted from regression-type water quality models could frequently be underestimating sediment yields and their environmental impact.

  15. 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

  16. Effect of initial conditions of a catchment on seasonal streamflow prediction using ensemble streamflow prediction (ESP) technique for the Rangitata and Waitaki River basins on the South Island of New Zealand

    NASA Astrophysics Data System (ADS)

    Singh, Shailesh Kumar; Zammit, Christian; Hreinsson, Einar; Woods, Ross; Clark, Martyn; Hamlet, Alan

    2013-04-01

    Increased access to water is a key pillar of the New Zealand government plan for economic growths. Variable climatic conditions coupled with market drivers and increased demand on water resource result in critical decision made by water managers based on climate and streamflow forecast. Because many of these decisions have serious economic implications, accurate forecast of climate and streamflow are of paramount importance (eg irrigated agriculture and electricity generation). New Zealand currently does not have a centralized, comprehensive, and state-of-the-art system in place for providing operational seasonal to interannual streamflow forecasts to guide water resources management decisions. As a pilot effort, we implement and evaluate an experimental ensemble streamflow forecasting system for the Waitaki and Rangitata River basins on New Zealand's South Island using a hydrologic simulation model (TopNet) and the familiar ensemble streamflow prediction (ESP) paradigm for estimating forecast uncertainty. To provide a comprehensive database for evaluation of the forecasting system, first a set of retrospective model states simulated by the hydrologic model on the first day of each month were archived from 1972-2009. Then, using the hydrologic simulation model, each of these historical model states was paired with the retrospective temperature and precipitation time series from each historical water year to create a database of retrospective hindcasts. Using the resulting database, the relative importance of initial state variables (such as soil moisture and snowpack) as fundamental drivers of uncertainties in forecasts were evaluated for different seasons and lead times. The analysis indicate that the sensitivity of flow forecast to initial condition uncertainty is depend on the hydrological regime and season of forecast. However initial conditions do not have a large impact on seasonal flow uncertainties for snow dominated catchments. Further analysis indicates

  17. [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.

  18. 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.

  19. 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.

  20. 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.

  1. Influence of pre-seasonal conditions on late wet season arrival and its implications to predictive understanding of the droughts over southern Amazonia

    NASA Astrophysics Data System (ADS)

    Yin, L.; Fu, R.

    2011-12-01

    Our recent analysis suggests that the increase of drought severity in the southern Amazon during recent decades is mainly contributed by a delaying of wet season onset and resulted shortening of the wet season. Using a suite of observations, we found that a delay of wet season onset is significantly correlated with anomalous pre-seasonal conditions. In particular, a poleward shift of the southern hemispheric subtropical jet, and an increase of convective inhibition energy (CINE) during the three months prior to the wet season onset date appear to be significantly correlated with the subsequently delay of wet season onset. Canonical correlation analysis suggests that this correlation between the pre-seasonal large-scale circulation and near surface atmosphere thermodynamic condition is relatively insensitive to the data and parameters we choose to represent the subtropical jets. We will discuss physical mechanisms of this observed correlation between pre-seasonal climate conditions and delay of wet season onsets and potential of using this correlation as a predicting factor in determining the likelihood of delaying in wet season onset over southern Amazonia. We will also evaluate whether this relationship is adequately represented in climate models.

  2. 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.

  3. 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…

  4. 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.

  5. 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.

  6. Magnetization Transfer Imaging of Rat Brain under Non-steady-state Conditions. Contrast Prediction Using a Binary Spin-Bath Model and a Super-Lorentzian Lineshape

    NASA Astrophysics Data System (ADS)

    Quesson, Bruno; Thiaudière, Eric; Delalande, Christophe; Chateil, Jean-Francois; Moonen, Chrit T. W.; Canioni, Paul

    1998-02-01

    Magnetization transfer contrast imaging using turbo spin echo and continuous wave off-resonance irradiation was carried out on rat brainin vivoat 4.7 T. By systematically varying the off-resonance irradiation power and the offset-frequency, the signal intensities obtained under steady-state for both transverse and longitudinal magnetization were successfully analyzed with a simple binary spin-bath model taking into account a free water compartment and a pool of protons with restricted motions bearing a super-Lorentzian lineshape. Due to important RF power deposition, such experimental conditions are not practical for routine imaging on humans. An extension of the model was derived to describe the system for shorter off-resonance pulse duration, i.e., when the longitudinal magnetization of the free protons has not reached a steady-state. Data sets obtained for three regions of interest, namely thecorpus callosum,the basal ganglia, and the temporal lobe, were correctly interpreted for off-resonance pulse durations varying from 0.3 to 3 s. The parameter sets obtained from the calculations made it possible to predict the contrast between the different regions as a function of the pulse power, the offset frequency, and pulse duration. Such an approach could be extended to contrast prediction for human brain at 1.5 T.

  7. Prediction of acoustic radiation from axisymmetric surfaces with arbitrary boundary conditions using the boundary element method on a distributed computing system.

    PubMed

    Wright, Louise; Robinson, Stephen P; Humphrey, Victor F

    2009-03-01

    This paper presents a computational technique using the boundary element method for prediction of radiated acoustic waves from axisymmetric surfaces with nonaxisymmetric boundary conditions. The aim is to predict the far-field behavior of underwater acoustic transducers based on their measured behavior in the near-field. The technique is valid for all wavenumbers and uses a volume integral method to calculate the singular integrals required by the boundary element formulation. The technique has been implemented on a distributed computing system to take advantage of its parallel nature, which has led to significant reductions in the time required to generate results. Measurement data generated by a pair of free-flooding underwater acoustic transducers encapsulated in a polyurethane polymer have been used to validate the technique against experiment. The dimensions of the outer surface of the transducers (including the polymer coating) were an outer diameter of 98 mm with an 18 mm wall thickness and a length of 92 mm. The transducers were mounted coaxially, giving an overall length of 185 mm. The cylinders had resonance frequencies at 13.9 and 27.5 kHz, and the data were gathered at these frequencies.

  8. Min and Max Extreme Interval Values

    ERIC Educational Resources Information Center

    Jance, Marsha L.; Thomopoulos, Nick T.

    2011-01-01

    The paper shows how to find the min and max extreme interval values for the exponential and triangular distributions from the min and max uniform extreme interval values. Tables are provided to show the min and max extreme interval values for the uniform, exponential, and triangular distributions for different probabilities and observation sizes.

  9. Familiarity-Frequency Ratings of Melodic Intervals

    ERIC Educational Resources Information Center

    Jeffries, Thomas B.

    1972-01-01

    Objective of this study was to determine subjects' reliability in rating randomly played ascending and descending melodic intervals within the octave on the basis of their familiarity with each type of interval and the frequency of their having experienced each type of interval in music. (Author/CB)

  10. Prediction of the retention of s-triazines in reversed-phase high-performance liquid chromatography under linear gradient-elution conditions.

    PubMed

    D'Archivio, Angelo Antonio; Maggi, Maria Anna; Ruggieri, Fabrizio

    2014-08-01

    In this paper, a multilayer artificial neural network is used to model simultaneously the effect of solute structure and eluent concentration profile on the retention of s-triazines in reversed-phase high-performance liquid chromatography under linear gradient elution. The retention data of 24 triazines, including common herbicides and their metabolites, are collected under 13 different elution modes, covering the following experimental domain: starting acetonitrile volume fraction ranging between 40 and 60% and gradient slope ranging between 0 and 1% acetonitrile/min. The gradient parameters together with five selected molecular descriptors, identified by quantitative structure-retention relationship modelling applied to individual separation conditions, are the network inputs. Predictive performance of this model is evaluated on six external triazines and four unseen separation conditions. For comparison, retention of triazines is modelled by both quantitative structure-retention relationships and response surface methodology, which describe separately the effect of molecular structure and gradient parameters on the retention. Although applied to a wider variable domain, the network provides a performance comparable to that of the above "local" models and retention times of triazines are modelled with accuracy generally better than 7%.

  11. Assessment of indoor climate of Mogiła Abbey in Kraków (Poland) and the application of the analogues method to predict microclimate indoor conditions.

    PubMed

    Frasca, F; Siani, A M; Casale, G R; Pedone, M; Bratasz, Ł; Strojecki, M; Mleczkowska, A

    2016-04-04

    The microclimatic monitoring of the historic church of Mogiła Abbey (Kraków, Poland) was carried out to study the impact of the environmental parameters on the organic and hygroscopic artworks. Specific indexes were proposed to objectively assess the quality of time series of temperature (T), relative humidity (RH), and carbon dioxide (CO2) before applying the exploratory data analysis. The series were used to define the historic environmental conditions as stated in the European Standard EN 15757:2010 and with the use of the climate evaluation chart (CEC). It was found that the percentage of time in which T and RH values are within the allowable limits of the ASHRAE (2011) Class B is more than 85 %. This means that, for about 15 % of the time, there is a high risk of mechanical damage to highly vulnerable objects mainly due to the RH variability. The environment at the chancel resulted moister than that at the cornice, and the fungal growth is possible. In addition, the time-weighted preservation index (TWPI) is computed to evaluate the life expectancy of the objects, taking into account the environmental conditions of the site under study. The method of analogues, developed to predict the evolution of a system given observations of the past and without the knowledge of any equation among variables, was proposed and applied to the time series of temperature, relative humidity, and carbon dioxide with a 1-h sampling time to avoid the influence of the autocorrelation.

  12. Use of chemical indicators of beer aging for ex-post checking of storage conditions and prediction of the sensory stability of beer.

    PubMed

    Cejka, Pavel; Culík, Jiří; Horák, Tomáš; Jurková, Marie; Olšovská, Jana

    2013-12-26

    The rate of beer aging is affected by storage conditions including largely time and temperature. Although bottled beer is commonly stored for up to 1 year, sensorial damage of it is quite frequent. Therefore, a method for retrospective determination of temperature of stored beer was developed. The method is based on the determination of selected carbonyl compounds called as "aging indicators", which are formed during beer aging. The aging indicators were determined using GC-MS after precolumn derivatization with O-(2,3,4,5,6-pentaflourobenzyl)hydroxylamine hydrochloride, and their profile was correlated with the development of old flavor evolving under defined conditions (temperature, time) using both a mathematical and statistical apparatus. Three approaches, including calculation from regression graph, multiple linear regression, and neural networks, were employed. The ultimate uncertainty of the method ranged from 3.0 to 11.0 °C depending on the approach used. Furthermore, the assay was extended to include prediction of beer tendency to sensory aging from freshly bottled beer.

  13. 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 equivalence between its left-hand and right-hand expressions, the traditional treatment of the subject subtracts the two sides, leaving an expression of the form Integral of(x) = 0. Values of the independent variable x satisfying this condition are roots, or solutions. Generally speaking, there may be no solutions, a unique solution, multiple solutions, or a continuum of solutions to a given equation. In particular, all view period events are modeled as zero crossings of various metrics; for example, the time at which the elevation of a spacecraft reaches its maximum value, as viewed from a Deep Space Station (DSS), is found by locating that point at which the derivative of the elevation function becomes zero. Moreover, each event type may have several occurrences within a given time interval of interest. For example, a spacecraft in a low Moon orbit will experience several possible occultations per day, each of which must be located in time. The MPG is charged with finding all specified event occurrences that take place within a given time interval (or pass ), without any special clues from operators as to when they may occur, for the entire spectrum of missions undertaken by the DSN. For each event type, the event metric function is a known form that can be computed for any instant within the interval. A method has been created for a mathematical root finder to be capable of finding all roots of an arbitrary continuous function, within a given interval, to be subject to very lenient, parameterized assumptions. One assumption is that adjacent roots are separated at least by a given amount, xGuard. Any point whose function value is less than ef in magnitude is considered to be a root, and the function values at distances x

  14. Development and field application of a mathematical model for predicting the kinematic viscosity of crude oil/diluter mixture under continuous production conditions

    SciTech Connect

    Alcocer, C.F.; Menzie, D.E.

    1986-01-01

    Experience producing medium to heavy oil areas has demonstrated that most conventional artificial production systems are inefficient. This situation has been improved by mixing diluter fluids or light crude oil with medium to heavy crude oil downhole. The mixing increases production efficiency, crude oil selling value, and conditions crude to meet minimum selling conditions. An analytical model has been developed to analyze the behavior of crude oil/diluter mixtures under continuous production conditions. The model developed for this study has practical application in field operations. The most important applications are: to select the proper diluter fluid to be used in a specific area; to calculate the exact amount of diluter to be mixed with crude oil to obtain a specific viscosity; to forecast the amount of diluter fluid required for normal and continuous oilfield operations; to predict crude oil-diluter mixture kinematic viscosity under any proportion of the components for economic evaluation; and to calculate API gravities of the produced mixture under continuous operation. The crude oils used in this study have a gravity between 8.6/sup 0/API and 14.3/sup 0/API. The diluters used have a gravity between 31.4/sup 0/API and 63/sup 0/API. The paper presents the analytical model and one application to Venezuelan field in the Orinoco Petroleum Belt, one of the largest oil reserves in the world. Each well in the field has a different viscosity and different production rate. The production rate was considered continuous and under exponential decline.

  15. Prediction of diffuse organic micropollutant loads in streams under changing climatic, socio-economic and technical boundary conditions with an integrated transport model

    NASA Astrophysics Data System (ADS)

    Honti, Mark; Schuwirth, Nele; Rieckermann, Jörg; Ghielmetti, Nico; Stamm, Christian

    2014-05-01

    were predominantly determined by human activities in each simulated sub-catchment, as reflected by the socio-economic scenarios and management alternatives. Climatic and the corresponding hydrological changes had a much weaker influence. This indicates that - conditionally on the confidence of our predictions - catchment management would possess effective options to prevent the degradation of water quality in the future. However, prediction uncertainty varied between high and huge levels depending on compound. Most of the identified uncertainty was related to the quality of input data. Application rates and timings could be estimated only roughly for most compounds. Concentration peaks were simulated with high uncertainty. The highest pollutant concentrations were often associated with known but unidentified pollution sources such as accidental spills, or brief high-intensity precipitation events whose amount could only be observed with high uncertainty. So while acute exposure would be as important as the chronic one for IWRM, neither climatic nor catchment models excel at predicting rare and brief events. This deficiency highlights why the assessment of predictive uncertainty should be an integral part of OMP modeling.

  16. Unequal Weber fractions for the categorization of brief temporal intervals.

    PubMed

    Grondin, Simon

    2010-07-01

    How constant is the Weber fraction (WF) for brief time intervals? This question was assessed in three experiments with two base durations (BDs), 0.2 and 1 sec, and with different ways of estimating the WF. In Experiment 1, the psychometric functions were drawn on the basis of 4, 8, or 12 comparison intervals with the shortest to longest duration ranges being kept constant. The results revealed no effect of the number of intervals, but the WF (threshold/BD) was significantly lower at 0.2 sec. In Experiment 2, the comparison intervals were distributed over three duration ranges. There was no range effect, and the WF was generally lower at 0.2 sec than at 1 sec. In Experiment 3, one condition allowed a comparison of the BD with the same range between the shortest and longest comparison intervals. Once again, the WF was lower at 0.2 sec than at 1 sec. Overall, the results reveal (1) that increasing the number of comparison intervals or the duration range does not seem to affect the value of the WF and (2) that the WF is lower at 0.2 sec than at 1 sec, which is inconsistent with the scalar property of some timing models.

  17. Scaling and memory in volatility return intervals in financial markets

    NASA Astrophysics Data System (ADS)

    Yamasaki, Kazuko; Muchnik, Lev; Havlin, Shlomo; Bunde, Armin; Stanley, H. Eugene

    2005-06-01

    For both stock and currency markets, we study the return intervals τ between the daily volatilities of the price changes that are above a certain threshold q. We find that the distribution function Pq(τ) scales with the mean return interval [Formula] as [Formula]. The scaling function f(x) is similar in form for all seven stocks and for all seven currency databases analyzed, and f(x) is consistent with a power-law form, f(x) ˜ x-γ with γ ≈ 2. We also quantify how the conditional distribution Pq(τ|τ0) depends on the previous return interval τ0 and find that small (or large) return intervals are more likely to be followed by small (or large) return intervals. This “clustering” of the volatility return intervals is a previously unrecognized phenomenon that we relate to the long-term correlations known to be present in the volatility. Author contributions: S.H. and H.E.S. designed research; K.Y., L.M., S.H., and H.E.S. performed research; A.B. contributed new reagents/analytic tools; A.B. analyzed data; and S.H. wrote the paper.Abbreviations: pdf, probability density function; S&P 500, Standard and Poor's 500 Index; USD, U.S. dollar; JPY, Japanese yen; SEK, Swedish krona.

  18. Interpregnancy interval and obstetrical complications.

    PubMed

    Shachar, Bat Zion; Lyell, Deirdre J

    2012-09-01

    Obstetricians are often presented with questions regarding the optimal interpregnancy interval (IPI). Short IPI has been associated with adverse perinatal and maternal outcomes, ranging from preterm birth and low birth weight to neonatal and maternal morbidity and mortality. Long IPI has in turn been associated with increased risk for preeclampsia and labor dystocia. In this review, we discuss the data regarding these associations along with recent studies revealing associations of short IPI with birth defects, schizophrenia, and autism. The optimal IPI may vary for different subgroups. We discuss the consequences of short IPI in women with a prior cesarean section, in particular the increased risk for uterine rupture and the considerations regarding a trial of labor in this subgroup. We review studies examining the interaction between short IPI and advanced maternal age and discuss the risk-benefit assessment for these women. Finally, we turn our attention to women after a stillbirth or an abortion, who often desire to conceive again with minimal delay. We discuss studies speaking in favor of a shorter IPI in this group. The accumulated data allow for the reevaluation of current IPI recommendations and management guidelines for women in general and among subpopulations with special circumstances. In particular, we suggest lowering the current minimal IPI recommendation to only 18 months (vs 24 months according to the latest World Health Organization recommendations), with even shorter recommended minimal IPI for women of advanced age and those who conceive after a spontaneous or induced abortion.

  19. A Numerical Empirical Bayes Procedure for Finding an Interval Estimate.

    ERIC Educational Resources Information Center

    Lord, Frederic M.

    A numerical procedure is outlined for obtaining an interval estimate of a parameter in an empirical Bayes estimation problem. The case where each observed value x has a binomial distribution, conditional on a parameter zeta, is the only case considered. For each x, the parameter estimated is the expected value of zeta given x. The main purpose is…

  20. Updating metacognitive control in response to expected retention intervals.

    PubMed

    Fiechter, Joshua L; Benjamin, Aaron S

    2016-10-21

    In five experiments, we investigated whether expected retention intervals affect subjects' encoding strategies. In the first four experiments, our subjects studied paired associates consisting of words from the Graduate Record Exam and a synonym. They were told to expect a test on a word pair after either a short or a longer interval. Subjects were tested on most pairs after the expected retention interval. For some pairs, however, subjects were tested after the other retention interval, allowing for a comparison of performance at a given retention interval conditional upon the expected retention interval. No effect of the expected retention interval was found for 1 min versus 4 min (Exp. 1), 30 s versus 3 min (Exp. 2), and 30 s versus 10 min (Exps. 3 and 4), even when subjects were given complete control over the pacing of study items (Exp. 4). However, when the difference between the expected retention intervals was increased massively (10 min vs. 24 h; Exp. 5), subjects remembered more items that they expected to be tested sooner, an effect consistent with the idea that they traded off efforts to remember items for the later test versus items that were about to be tested. Overall, this set of results accords with much of the test-expectancy literature, revealing that subjects are often reluctant to adjust encoding strategies on an item-by-item basis, and when they do, they usually make quantitative, rather than qualitative, adjustments.

  1. Quasistationary Solution of a Two-Component Hyperbolic System on an Interval

    NASA Astrophysics Data System (ADS)

    Isakov, K. A.; Shapovalov, A. V.

    2017-01-01

    A quasistationary solution of a two-component system of first-order telegraph equations on an interval with time-dependent conditions is constructed, where these conditions are prescribed at interior points of the interval. Application of the obtained solution as a criterion for leakage detection is considered.

  2. Predicting crash risk and identifying crash precursors on Korean expressways using loop detector data.

    PubMed

    Kwak, Ho-Chan; Kho, Seungyoung

    2016-03-01

    In order to improve traffic safety on expressways, it is important to develop proactive safety management strategies with consideration for segment types and traffic flow states because crash mechanisms have some differences by each condition. The primary objective of this study is to develop real-time crash risk prediction models for different segment types and traffic flow states on expressways. The mainline of expressways is divided into basic segment and ramp vicinity, and the traffic flow states are classified into uncongested and congested conditions. Also, Korean expressways have irregular intervals between loop detector stations. Therefore, we investigated on the effect and application of the detector stations at irregular intervals for the crash risk prediction on expressways. The most significant traffic variables were selected by conditional logistic regression analysis which could control confounding factors. Based on the selected traffic variables, separate models to predict crash risk were developed using genetic programming technique. The model estimation results showed that the traffic flow characteristics leading to crashes are differed by segment type and traffic flow state. Especially, the variables related to the intervals between detector stations had a significant influence on crash risk prediction under the uncongested condition. Finally, compared with the single model for all crashes and the logistic models used in previous studies, the proposed models showed higher prediction performance. The results of this study can be applied to develop more effective proactive safety management strategies for different segment types and traffic flow states on expressways with loop detector stations at irregular intervals.

  3. Impact of land surface conditions on the predictability of hydrologic processes and mountain-valley circulations in the North American Monsoon region

    NASA Astrophysics Data System (ADS)

    Xiang, T.; Vivoni, E. R.; Gochis, D. J.; Mascaro, G.

    2015-12-01

    Heterogeneous land surface conditions are essential components of land-atmosphere interactions in regions of complex terrain and have the potential to affect convective precipitation formation. Yet, due to their high complexity, hydrologic processes over mountainous regions are not well understood, and are usually parameterized in simple ways within coupled land-atmosphere modeling frameworks. With the improving model physics and spatial resolution of numerical weather prediction models, there is an urgent need to understand how land surface processes affect local and regional meteorological processes. In the North American Monsoon (NAM) region, the summer rainy season is accompanied by a dramatic greening of mountain ecosystems that adds spatiotemporal variability in vegetation which is anticipated to impact the conditions leading to convection, mountain-valley circulations and mesoscale organization. In this study, we present results from a detailed analysis of a high-resolution (1 km) land surface model, Noah-MP, in a large, mountainous watershed of the NAM region - the Rio Sonora (21,264 km2) in Mexico. In addition to capturing the spatial variations in terrain and soil distributions, recently-developed features in Noah-MP allow the model to read time-varying vegetation parameters derived from remotely-sensed vegetation indices; however, this new implementation has not been fully evaluated. Therefore, we assess the simulated spatiotemporal fields of soil moisture, surface temperature and surface energy fluxes through comparisons to remote sensing products and results from coarser land surface models obtained from the North American Land Data Assimilation System. We focus attention on the impact of vegetation changes along different elevation bands on the diurnal cycle of surface energy fluxes to provide a baseline for future analyses of mountain-valley circulations using a coupled land-atmosphere modeling system. Our study also compares limited streamflow

  4. Intervals in evolutionary algorithms for global optimization

    SciTech Connect

    Patil, R.B.

    1995-05-01

    Optimization is of central concern to a number of disciplines. Interval Arithmetic methods for global optimization provide us with (guaranteed) verified results. These methods are mainly restricted to the classes of objective functions that are twice differentiable and use a simple strategy of eliminating a splitting larger regions of search space in the global optimization process. An efficient approach that combines the efficient strategy from Interval Global Optimization Methods and robustness of the Evolutionary Algorithms is proposed. In the proposed approach, search begins with randomly created interval vectors with interval widths equal to the whole domain. Before the beginning of the evolutionary process, fitness of these interval parameter vectors is defined by evaluating the objective function at the center of the initial interval vectors. In the subsequent evolutionary process the local optimization process returns an estimate of the bounds of the objective function over the interval vectors. Though these bounds may not be correct at the beginning due to large interval widths and complicated function properties, the process of reducing interval widths over time and a selection approach similar to simulated annealing helps in estimating reasonably correct bounds as the population evolves. The interval parameter vectors at these estimated bounds (local optima) are then subjected to crossover and mutation operators. This evolutionary process continues for predetermined number of generations in the search of the global optimum.

  5. Control of Angular Intervals for Angle-Multiplexed Holographic Memory

    NASA Astrophysics Data System (ADS)

    Kinoshita, Nobuhiro; Muroi, Tetsuhiko; Ishii, Norihiko; Kamijo, Koji; Shimidzu, Naoki

    2009-03-01

    In angle-multiplexed holographic memory, the full width at half maximum of the Bragg selectivity curves is dependent on the angle formed between the medium and incident laser beams. This indicates the possibility of high density and high multiplexing number by varying the angular intervals between adjacent holograms. We propose an angular interval scheduling for closely stacking holograms into medium even when the angle range is limited. We obtained bit error rates of the order of 10-4 under the following conditions: medium thickness of 1 mm, laser beam wavelength of 532 nm, and angular multiplexing number of 300.

  6. Infinite time interval backward stochastic differential equations with continuous coefficients.

    PubMed

    Zong, Zhaojun; Hu, Feng

    2016-01-01

    In this paper, we study the existence theorem for [Formula: see text] [Formula: see text] solutions to a class of 1-dimensional infinite time interval backward stochastic differential equations (BSDEs) under the conditions that the coefficients are continuous and have linear growths. We also obtain the existence of a minimal solution. Furthermore, we study the existence and uniqueness theorem for [Formula: see text] [Formula: see text] solutions of infinite time interval BSDEs with non-uniformly Lipschitz coefficients. It should be pointed out that the assumptions of this result is weaker than that of Theorem 3.1 in Zong (Turkish J Math 37:704-718, 2013).

  7. Confidence intervals for modeling anthocyanin retention in grape pomace during nonisothermal heating.

    PubMed

    Mishra, D K; Dolan, K D; Yang, L

    2008-01-01

    Degradation of nutraceuticals in low- and intermediate-moisture foods heated at high temperature (>100 degrees C) is difficult to model because of the nonisothermal condition. Isothermal experiments above 100 degrees C are difficult to design because they require high pressure and small sample size in sealed containers. Therefore, a nonisothermal method was developed to estimate the thermal degradation kinetic parameter of nutraceuticals and determine the confidence intervals for the parameters and the predicted Y (concentration). Grape pomace at 42% moisture content (wb) was heated in sealed 202 x 214 steel cans in a steam retort at 126.7 degrees C for > 30 min. Can center temperature was measured by thermocouple and predicted using Comsol software. Thermal conductivity (k) and specific heat (C(p)) were estimated as quadratic functions of temperature using Comsol and nonlinear regression. The k and C(p) functions were then used to predict temperature inside the grape pomace during retorting. Similar heating experiments were run at different time-temperature treatments from 8 to 25 min for kinetic parameter estimation. Anthocyanin concentration in the grape pomace was measured using HPLC. Degradation rate constant (k(110 degrees C)) and activation energy (E(a)) were estimated using nonlinear regression. The thermophysical properties estimates at 100 degrees C were k = 0.501 W/m degrees C, Cp= 3600 J/kg and the kinetic parameters were k(110 degrees C)= 0.0607/min and E(a)= 65.32 kJ/mol. The 95% confidence intervals for the parameters and the confidence bands and prediction bands for anthocyanin retention were plotted. These methods are useful for thermal processing design for nutraceutical products.

  8. Data-Based Interval Throwing Programs for Baseball Players

    PubMed Central

    Axe, Michael; Hurd, Wendy; Snyder-Mackler, Lynn

    2009-01-01

    Context: Baseball throwing injuries are common. Emphasis on injury prevention and rehabilitation is made in an attempt to keep athletes on the field of competition. Interval throwing programs are an integral part of training, conditioning, and returning an injured baseball player to the game. Evidence Acquisition: Development of data-driven programs was based on the number, type, distance, and intensity of throws during games, across the spectrum of ages and positions for baseball athletes at all levels of play. Statistical analysis by age, position, and level of play determined the need for separate throwing programs. Means, the high range, game rules, and practical considerations were used to develop each data-based interval throwing program. Results: Data-based age and level-of-play interval throwing programs for pitchers, catchers, infielders, and outfielders have been developed, tested, and implemented for more than 10 years. Progression is based on type and location of injury, symptoms in response to throwing, and preinjury performance profile. Although the throwing programs are highly structured, there is ample opportunity to modify them to meet the needs of individual athletes. Conclusion: Data-based interval throwing programs for baseball athletes are an integral training and conditioning element for both injured and uninjured athletes who are preparing for sports participation. Medical team members should equip themselves with an understanding of how to use the programs for safe training, conditioning, and return to play. PMID:23015866

  9. Fault Detection and Isolation using Viability Theory and Interval Observers

    NASA Astrophysics Data System (ADS)

    Ghaniee Zarch, Majid; Puig, Vicenç; Poshtan, Javad

    2017-01-01

    This paper proposes the use of interval observers and viability theory in fault detection and isolation (FDI). Viability theory develops mathematical and algorithmic methods for investigating the adaptation to viability constraints of evolutions governed by complex systems under uncertainty. These methods can be used for checking the consistency between observed and predicted behavior by using simple sets that approximate the exact set of possible behavior (in the parameter or state space). In this paper, fault detection is based on checking for an inconsistency between the measured and predicted behaviors using viability theory concepts and sets. Finally, an example is provided in order to show the usefulness of the proposed approach.

  10. A better confidence interval for the sensitivity at a fixed level of specificity for diagnostic tests with continuous endpoints.

    PubMed

    Shan, Guogen

    2017-02-01

    For a diagnostic test with continuous measurement, it is often important to construct confidence intervals for the sensitivity at a fixed level of specificity. Bootstrap-based confidence intervals were shown to have good performance as compared to others, and the one by Zhou and Qin (2005) was recommended as the best existing confidence interval, named the BTII interval. We propose two new confidence intervals based on the profile variance method and conduct extensive simulation studies to compare the proposed intervals and the BTII intervals under a wide range of conditions. An example from a medical study on severe head trauma is used to illustrate application of the new intervals. The new proposed intervals generally have better performance than the BTII interval.

  11. Capacitated max -Batching with Interval Graph Compatibilities

    NASA Astrophysics Data System (ADS)

    Nonner, Tim

    We consider the problem of partitioning interval graphs into cliques of bounded size. Each interval has a weight, and the weight of a clique is the maximum weight of any interval in the clique. This natural graph problem can be interpreted as a batch scheduling problem. Solving a long-standing open problem, we show NP-hardness, even if the bound on the clique sizes is constant. Moreover, we give a PTAS based on a novel dynamic programming technique for this case.

  12. Contrasting effects of interference and of breaks in interval timing.

    PubMed

    Gaudreault, Rémi; Fortin, Claudette; Macar, Françoise

    2010-01-01

    When a break is introduced during an interval to be timed, the interval is perceived shorter as break location is delayed. This is interpreted as a result of attention sharing between timing and monitoring the source of the break signal. Similar effects and interpretations are found in another context involving interfering tasks. Such tasks are assumed to induce transient interruptions in timing, comparable to those obtained with breaks. Break and interference conditions were contrasted in a temporal reproduction procedure with identical stimuli. Both conditions induced temporal underestimation and similar location effects. Similar trends occurred in a control condition where no processing of the interfering signal was required. The data suggest that expectancy, intentional processing, and automatic attraction of attention shorten temporal estimates.

  13. Confidence Interval Procedures for Reliability Growth Analysis

    DTIC Science & Technology

    1977-06-01

    Plj2s tSAA - TECHNICAL RPORT NO. 197 CONFIDENCE INTERVAL PROCEDURES FOR RELIABILITY, GROWTH ANALYSIS LARRY H. CROW JUNE 1977 APPROVED FOR PUBLIC...dence Intervals for M(T). ¶-. fl [ ] 1 Siion IIS0III0N/AVAI Ale ITY ClOtS Next page is blank. So3 CONFIDENCE INTERVAL PROCIEDURIS• FOR RELTABILITY...and confidence interval procedures for the parameters B and P = X are presented in [l , [2], [4]. In the application of the Weibull process model to

  14. Flood frequency analysis using multi-objective optimization based interval estimation approach

    NASA Astrophysics Data System (ADS)

    Kasiviswanathan, K. S.; He, Jianxun; Tay, Joo-Hwa

    2017-02-01

    Flood frequency analysis (FFA) is a necessary tool for water resources management and water infrastructure design. Owing to the existence of variability in sample representation, distribution selection, and distribution parameter estimation, flood quantile estimation is subjected to various levels of uncertainty, which is not negligible and avoidable. Hence, alternative methods to the conventional approach of FFA are desired for quantifying the uncertainty such as in the form of prediction interval. The primary focus of the paper was to develop a novel approach to quantify and optimize the prediction interval resulted from the non-stationarity of data set, which is reflected in the distribution parameters estimated, in FFA. This paper proposed the combination of the multi-objective optimization approach and the ensemble simulation technique to determine the optimal perturbations of distribution parameters for constructing the prediction interval of flood quantiles in FFA. To demonstrate the proposed approach, annual maximum daily flow data collected from two gauge stations on the Bow River, Alberta, Canada, were used. The results suggest that the proposed method can successfully capture the uncertainty in quantile estimates qualitatively using the prediction interval, as the number of observations falling within the constructed prediction interval is approximately maximized while the prediction interval is minimized.

  15. Differential Preparation Intervals Modulate Repetition Processes in Task Switching: An ERP Study

    PubMed Central

    Wang, Min; Yang, Ping; Zhao, Qian-Jing; Wang, Meng; Jin, Zhenlan; Li, Ling

    2016-01-01

    In task-switching paradigms, reaction times (RTs) switch cost (SC) and the neural correlates underlying the SC are affected by different preparation intervals. However, little is known about the effect of the preparation interval on the repetition processes in task-switching. To examine this effect we utilized a cued task-switching paradigm with long sequences of repeated trials. Response-stimulus intervals (RSI) and cue-stimulus intervals (CSI) were manipulated in short and long conditions. Electroencephalography (EEG) and behavioral data were recorded. We found that with increasing repetitions, RTs were faster in the short CSI conditions, while P3 amplitudes decreased in the LS (long RSI and short CSI) conditions. Positive correlations between RT benefit and P3 activation decrease (repeat 1 − repeat 5), and between the slope of the RT and P3 regression lines were observed only in the LS condition. Our findings suggest that differential preparation intervals modulate repetition processes in task switching. PMID:26924974

  16. Predicting the conditions under which vibroacoustic resonances with external periodic loads occur in the primary coolant circuits of VVER-based NPPs

    NASA Astrophysics Data System (ADS)

    Proskuryakov, K. N.; Fedorov, A. I.; Zaporozhets, M. V.

    2015-08-01

    The accident at the Japanese Fukushima Daiichi nuclear power plant (NPP) caused by an earthquake showed the need of taking further efforts aimed at improving the design and engineering solutions for ensuring seismic resistance of NPPs with due regard to mutual influence of the dynamic processes occurring in the NPP building structures and process systems. Resonance interaction between the vibrations of NPP equipment and coolant pressure pulsations leads to an abnormal growth of dynamic stresses in structural materials, accelerated exhaustion of equipment service life, and increased number of sudden equipment failures. The article presents the results from a combined calculation-theoretical and experimental substantiation of mutual amplification of two kinds of external periodic loads caused by rotation of the reactor coolant pump (RCP) rotor and an earthquake. The data of vibration measurements at an NPP are presented, which confirm the predicted multiple amplification of vibrations in the steam generator and RCP at a certain combination of coolant thermal-hydraulic parameters. It is shown that the vibration frequencies of the main equipment may fall in the frequency band corresponding to the maximal values in the envelope response spectra constructed on the basis of floor accelerograms. The article presents the results from prediction of conditions under which vibroacoustic resonances with external periodic loads take place, which confirm the occurrence of additional earthquake-induced multiple growth of pressure pulsation intensity in the steam generator at the 8.3 Hz frequency and additional multiple growth of vibrations of the RCP and the steam generator cold header at the 16.6 Hz frequency. It is shown that at the elastic wave frequency equal to 8.3 Hz in the coolant, resonance occurs with the frequency of forced vibrations caused by the rotation of the RCP rotor. A conclusion is drawn about the possibility of exceeding the design level of equipment vibrations

  17. Scaling and memory in the return intervals of realized volatility

    NASA Astrophysics Data System (ADS)

    Ren, Fei; Gu, Gao-Feng; Zhou, Wei-Xing

    2009-11-01

    We perform return interval analysis of 1-min realized volatility defined by the sum of absolute high-frequency intraday returns for the Shanghai Stock Exchange Composite Index (SSEC) and 22 constituent stocks of SSEC. The scaling behavior and memory effect of the return intervals between successive realized volatilities above a certain threshold q are carefully investigated. In comparison with the volatility defined by the closest tick prices to the minute marks, the return interval distribution for the realized volatility shows a better scaling behavior since 20 stocks (out of 22 stocks) and the SSEC pass the Kolmogorov-Smirnov (KS) test and exhibit scaling behaviors, among which the scaling function for 8 stocks could be approximated well by a stretched exponential distribution revealed by the KS goodness-of-fit test under the significance level of 5%. The improved scaling behavior is further confirmed by the relation between the fitted exponent γ and the threshold q. In addition, the similarity of the return interval distributions for different stocks is also observed for the realized volatility. The investigation of the conditional probability distribution and the detrended fluctuation analysis (DFA) show that both short-term and long-term memory exists in the return intervals of realized volatility.

  18. QT-Interval Duration and Mortality Rate

    PubMed Central

    Zhang, Yiyi; Post, Wendy S.; Dalal, Darshan; Blasco-Colmenares, Elena; Tomaselli, Gordon F.; Guallar, Eliseo

    2012-01-01

    Background Extreme prolongation or reduction of the QT interval predisposes patients to malignant ventricular arrhythmias and sudden cardiac death, but the association of variations in the QT interval within a reference range with mortality end points in the general population is unclear. Methods We included 7828 men and women from the Third National Health and Nutrition Examination Survey. Baseline QT interval was measured via standard 12-lead electrocardiographic readings. Mortality end points were assessed through December 31, 2006 (2291 deaths). Results After an average follow-up of 13.7 years, the association between QT interval and mortality end points was U-shaped. The multivariate-adjusted hazard ratios comparing participants at or above the 95th percentile of age-, sex-, race-, and R-R interval–corrected QT interval (≥439 milliseconds) with participants in the middle quintile (401 to <410 milliseconds) were 2.03 (95% confidence interval, 1.46-2.81) for total mortality, 2.55 (1.59-4.09) for mortality due to cardiovascular disease (CVD), 1.63 (0.96-2.75) for mortality due to coronary heart disease, and 1.65 (1.16-2.35) for non-CVD mortality. The corresponding hazard ratios comparing participants with a corrected QT interval below the fifth percentile (<377 milliseconds) with those in the middle quintile were 1.39 (95% confidence interval, 1.02-1.88) for total mortality, 1.35 (0.77-2.36) for CVD mortality, 1.02 (0.44-2.38) for coronary heart disease mortality, and 1.42 (0.97-2.08) for non-CVD mortality. Increased mortality also was observed with less extreme deviations of QT-interval duration. Similar, albeit weaker, associations also were observed with Bazett-corrected QT intervals. Conclusion Shortened and prolonged QT-interval durations, even within a reference range, are associated with increased mortality risk in the general population. PMID:22025428

  19. Mathematical Model for Predicting the Growth Probability of Staphylococcus aureus in Combinations of NaCl and NaNO2 under Aerobic or Evacuated Storage Conditions

    PubMed Central

    Lee, Jeeyeon; Gwak, Eunji; Ha, Jimyeong; Kim, Sejeong; Lee, Soomin; Lee, Heeyoung; Oh, Mi-Hwa; Park, Beom-Young; Oh, Nam Su; Choi, Kyoung-Hee; Yoon, Yohan

    2016-01-01

    The objective of this study was to describe the growth patterns of Staphylococcus aureus in combinations of NaCl and NaNO2, using a probabilistic model. A mixture of S. aureus strains (NCCP10826, ATCC13565, ATCC14458, ATCC23235, and ATCC27664) was inoculated into nutrient broth plus NaCl (0, 0.25, 0.5, 0.75, 1, 1.25, 1.5, and 1.75%) and NaNO2 (0, 15, 30, 45, 60, 75, 90, 105, and 120 ppm). The samples were then incubated at 4, 7, 10, 12 and 15℃ for up to 60 d under aerobic or vacuum conditions. Growth responses [growth (1) or no growth (0)] were then determined every 24 h by turbidity, and analyzed to select significant parameters (p<0.05) by a stepwise selection method, resulting in a probabilistic model. The developed models were then validated with observed growth responses. S. aureus growth was observed only under aerobic storage at 10-15℃. At 10-15℃, NaCl and NaNO2 did not inhibit S. aureus growth at less than 1.25% NaCl. Concentration dependency was observed for NaCl at more than 1.25%, but not for NaNO2. The concordance percentage between observed and predicted growth data was approximately 93.86%. This result indicates that S. aureus growth can be inhibited in vacuum packaging and even aerobic storage below 10℃. Furthermore, NaNO2 does not effectively inhibit S. aureus growth. PMID:28115886

  20. Interval bisection in spontaneously hypertensive rats.

    PubMed

    Orduña, Vladimir; Hong, Enrique; Bouzas, Arturo

    2007-01-10

    An interval bisection procedure was used to study time discrimination in spontaneously hypertensive rats (SHR), which have been proposed as an animal model for the attention deficit hyperactivity disorder (ADHD); Wistar Kyoto and Wistar rats were used as comparison groups. In this procedure, after subjects learn to make one response (S) following a short duration stimulus, and another (L) following a long duration stimulus, stimuli of intermediate durations are presented, and the percentage of L is calculated for each duration. A logistic function is fitted to these data, and different parameters that describe the time discrimination process are obtained. Four conditions, with different short and long durations (1-4, 2-8, 3-12, 4-16s) were used. The results indicate that time discrimination is not altered in SHR, given that no difference in any of the parameters obtained were significant. Given that temporal processing has been proposed as a fundamental factor in the development of the main symptoms of ADHD, and that deficits in time discrimination have been found in individuals with that disorder, the present results suggest the necessity of exploring time perception in SHR with other procedures and sensory modalities, in order to assess its validity as an animal model of ADHD.

  1. Some Improvements in Confidence Intervals for Standardized Regression Coefficients.

    PubMed

    Dudgeon, Paul

    2017-03-13

    Yuan and Chan (Psychometrika 76:670-690, 2011. doi: 10.1007/S11336-011-9224-6 ) derived consistent confidence intervals for standardized regression coefficients under fixed and random score assumptions. Jones and Waller (Psychometrika 80:365-378, 2015. doi: 10.1007/S11336-013-9380-Y ) extended these developments to circumstances where data are non-normal by examining confidence intervals based on Browne's (Br J Math Stat Psychol 37:62-83, 1984. doi: 10.1111/j.2044-8317.1984.tb00789.x ) asymptotic distribution-free (ADF) theory. Seven different heteroscedastic-consistent (HC) estimators were investigated in the current study as potentially better solutions for constructing confidence intervals on standardized regression coefficients under non-normality. Normal theory, ADF, and HC estimators were evaluated in a Monte Carlo simulation. Findings confirmed the superiority of the HC3 (MacKinnon and White, J Econ 35:305-325, 1985. doi: 10.1016/0304-4076(85)90158-7 ) and HC5 (Cribari-Neto and Da Silva, Adv Stat Anal 95:129-146, 2011. doi: 10.1007/s10182-010-0141-2 ) interval estimators over Jones and Waller's ADF estimator under all conditions investigated, as well as over the normal theory method. The HC5 estimator was more robust in a restricted set of conditions over the HC3 estimator. Some possible extensions of HC estimators to other effect size measures are considered for future developments.

  2. Interval and Contour Processing in Autism

    ERIC Educational Resources Information Center

    Heaton, Pamela

    2005-01-01

    High functioning children with autism and age and intelligence matched controls participated in experiments testing perception of pitch intervals and musical contours. The finding from the interval study showed superior detection of pitch direction over small pitch distances in the autism group. On the test of contour discrimination no group…

  3. Interpretation of Confidence Interval Facing the Conflict

    ERIC Educational Resources Information Center

    Andrade, Luisa; Fernández, Felipe

    2016-01-01

    As literature has reported, it is usual that university students in statistics courses, and even statistics teachers, interpret the confidence level associated with a confidence interval as the probability that the parameter value will be between the lower and upper interval limits. To confront this misconception, class activities have been…

  4. SINGLE-INTERVAL GAS PERMEABILITY ESTIMATION

    EPA Science Inventory

    Single-interval, steady-steady-state gas permeability testing requires estimation of pressure at a screened interval which in turn requires measurement of friction factors as a function of mass flow rate. Friction factors can be obtained by injecting air through a length of pipe...

  5. Biomathematics and Interval Analysis: A Prosperous Marriage

    NASA Astrophysics Data System (ADS)

    Markov, S. M.

    2010-11-01

    In this survey paper we focus our attention on dynamical bio-systems involving uncertainties and the use of interval methods for the modelling study of such systems. The kind of envisioned uncertain systems are those described by a dynamical model with parameters bounded in intervals. We point out to a fruitful symbiosis between dynamical modelling in biology and computational methods of interval analysis. Both fields are presently in the stage of rapid development and can benefit from each other. We point out on recent studies in the field of interval arithmetic from a new perspective—the midpoint-radius arithmetic which explores the properties of error bounds and approximate numbers. The midpoint-radius approach provides a bridge between interval methods and the "uncertain but bounded" approach used for model estimation and identification. We briefly discuss certain recently obtained algebraic properties of errors and approximate numbers.

  6. Hypothesis testing and earthquake prediction.

    PubMed

    Jackson, D D

    1996-04-30

    Requirements for testing include advance specification of the conditional rate density (probability per unit time, area, and magnitude) or, alternatively, probabilities for specified intervals of time, space, and magnitude. Here I consider testing fully specified hypotheses, with no parameter adjustments or arbitrary decisions allowed during the test period. Because it may take decades to validate prediction methods, it is worthwhile to formulate testable hypotheses carefully in advance. Earthquake prediction generally implies that the probability will be temporarily higher than normal. Such a statement requires knowledge of "normal behavior"--that is, it requires a null hypothesis. Hypotheses can be tested in three ways: (i) by comparing the number of actual earth-quakes to the number predicted, (ii) by comparing the likelihood score of actual earthquakes to the predicted distribution, and (iii) by comparing the likelihood ratio to that of a null hypothesis. The first two tests are purely self-consistency tests, while the third is a direct comparison of two hypotheses. Predictions made without a statement of probability are very difficult to test, and any test must be based on the ratio of earthquakes in and out of the forecast regions.

  7. Improved interval estimation of comparative treatment effects

    NASA Astrophysics Data System (ADS)

    Van Krevelen, Ryne Christian

    Comparative experiments, in which subjects are randomized to one of two treatments, are performed often. There is no shortage of papers testing whether a treatment effect exists and providing confidence intervals for the magnitude of this effect. While it is well understood that the object and scope of inference for an experiment will depend on what assumptions are made, these entities are not always clearly presented. We have proposed one possible method, which is based on the ideas of Jerzy Neyman, that can be used for constructing confidence intervals in a comparative experiment. The resulting intervals, referred to as Neyman-type confidence intervals, can be applied in a wide range of cases. Special care is taken to note which assumptions are made and what object and scope of inference are being investigated. We have presented a notation that highlights which parts of a problem are being treated as random. This helps ensure the focus on the appropriate scope of inference. The Neyman-type confidence intervals are compared to possible alternatives in two different inference settings: one in which inference is made about the units in the sample and one in which inference is made about units in a fixed population. A third inference setting, one in which inference is made about a process distribution, is also discussed. It is stressed that certain assumptions underlying this third type of inference are unverifiable. When these assumptions are not met, the resulting confidence intervals may cover their intended target well below the desired rate. Through simulation, we demonstrate that the Neyman-type intervals have good coverage properties when inference is being made about a sample or a population. In some cases the alternative intervals are much wider than necessary on average. Therefore, we recommend that researchers consider using our Neyman-type confidence intervals when carrying out inference about a sample or a population as it may provide them with more

  8. Confidence interval based parameter estimation--a new SOCR applet and activity.

    PubMed

    Christou, Nicolas; Dinov, Ivo D

    2011-01-01

    Many scientific investigations depend on obtaining data-driven, accurate, robust and computationally-tractable parameter estimates. In the face of unavoidable intrinsic variability, there are different algorithmic approaches, prior assumptions and fundamental principles for computing point and interval estimates. Efficient and reliable parameter estimation is critical in making inference about observable experiments, summarizing process characteristics and prediction of experimental behaviors. In this manuscript, we demonstrate simulation, construction, validation and interpretation of confidence intervals, under various assumptions, using the interactive web-based tools provided by the Statistics Online Computational Resource (http://www.SOCR.ucla.edu). Specifically, we present confidence interval examples for population means, with known or unknown population standard deviation; population variance; population proportion (exact and approximate), as well as confidence intervals based on bootstrapping or the asymptotic properties of the maximum likelihood estimates. Like all SOCR resources, these confidence interval resources may be openly accessed via an Internet-connected Java-enabled browser. The SOCR confidence interval applet enables the user to empirically explore and investigate the effects of the confidence-level, the sample-size and parameter of interest on the corresponding confidence interval. Two applications of the new interval estimation computational library are presented. The first one is a simulation of confidence interval estimating the US unemployment rate and the second application demonstrates the computations of point and interval estimates of hippocampal surface complexity for Alzheimers disease patients, mild cognitive impairment subjects and asymptomatic controls.

  9. Evaluating the Performance of a New Model for Predicting the Growth of Clostridium perfringens in Cooked, Uncured Meat and Poultry Products under Isothermal, Heating, and Dynamically Cooling Conditions.

    PubMed

    Huang, Lihan

    2016-07-01

    Clostridium perfringens type A is a significant public health threat and its spores may germinate, outgrow, and multiply during cooling of cooked meats. This study applies a new C. perfringens growth model in the USDA Integrated Pathogen Modeling Program-Dynamic Prediction (IPMP Dynamic Prediction) Dynamic Prediction to predict the growth from spores of C. perfringens in cooked uncured meat and poultry products using isothermal, dynamic heating, and cooling data reported in the literature. The residual errors of predictions (observation-prediction) are analyzed, and the root-mean-square error (RMSE) calculated. For isothermal and heating profiles, each data point in growth curves is compared. The mean residual errors (MRE) of predictions range from -0.40 to 0.02 Log colony forming units (CFU)/g, with a RMSE of approximately 0.6 Log CFU/g. For cooling, the end point predictions are conservative in nature, with an MRE of -1.16 Log CFU/g for single-rate cooling and -0.66 Log CFU/g for dual-rate cooling. The RMSE is between 0.6 and 0.7 Log CFU/g. Compared with other models reported in the literature, this model makes more accurate and fail-safe predictions. For cooling, the percentage for accurate and fail-safe predictions is between 97.6% and 100%. Under criterion 1, the percentage of accurate predictions is 47.5% for single-rate cooling and 66.7% for dual-rate cooling, while the fail-dangerous predictions are between 0% and 2.4%. This study demonstrates that IPMP Dynamic Prediction can be used by food processors and regulatory agencies as a tool to predict the growth of C. perfringens in uncured cooked meats and evaluate the safety of cooked or heat-treated uncured meat and poultry products exposed to cooling deviations or to develop customized cooling schedules. This study also demonstrates the need for more accurate data collection during cooling.

  10. Expanded vs. equal interval spaced retrieval practice: exploring different schedules of spacing and retention interval in younger and older adults.

    PubMed

    Logan, Jessica M; Balota, David A

    2008-05-01

    The present study was designed to help answer several questions regarding the impact of spacing and expanded retrieval on memory performance in younger and older adults. Three expanded/equal interval schedule pairings, matched in average spacing (1-2-3/2-2-2; 1-3-5/3-3-3; and 1-3-8/4-4-4), were compared, and the effect of retention interval on spaced retrieval benefits was examined by comparing performance on a same day test to a test delayed by 24 h. Both age groups showed a learning phase retrieval success advantage for expanded items compared to equal interval items. Only older adults in the same day test condition showed a significant expansion effect in final recall. After a 24-h delay, the final recall advantage for items in the expanded condition was lost in both groups, and in fact these items were at a significant recall disadvantage for younger adults. Results indicate that younger and older adults benefit from a rehearsal technique that incorporated any type of spaced retrieval whether it is distributed as an expanding schedule or not. Although we did not find robust advantages for expanded retrieval compared to equal interval practice, there could be certain advantages (such as reinforcement due to high success rates) to using expanded retrieval depending on the ultimate goals of an individual memory training program.

  11. Sampling Theory and Confidence Intervals for Effect Sizes: Using ESCI To Illustrate "Bouncing"; Confidence Intervals.

    ERIC Educational Resources Information Center

    Du, Yunfei

    This paper discusses the impact of sampling error on the construction of confidence intervals around effect sizes. Sampling error affects the location and precision of confidence intervals. Meta-analytic resampling demonstrates that confidence intervals can haphazardly bounce around the true population parameter. Special software with graphical…

  12. Interval Estimates of Multivariate Effect Sizes: Coverage and Interval Width Estimates under Variance Heterogeneity and Nonnormality

    ERIC Educational Resources Information Center

    Hess, Melinda R.; Hogarty, Kristine Y.; Ferron, John M.; Kromrey, Jeffrey D.

    2007-01-01

    Monte Carlo methods were used to examine techniques for constructing confidence intervals around multivariate effect sizes. Using interval inversion and bootstrapping methods, confidence intervals were constructed around the standard estimate of Mahalanobis distance (D[superscript 2]), two bias-adjusted estimates of D[superscript 2], and Huberty's…

  13. The microanalysis of fixed-interval responding

    PubMed Central

    Gentry, G. David; Weiss, Bernard; Laties, Victor G.

    1983-01-01

    The fixed-interval schedule of reinforcement is one of the more widely studied schedules in the experimental analysis of behavior and is also a common baseline for behavior pharmacology. Despite many intensive studies, the controlling variables and the pattern of behavior engendered are not well understood. The present study examined the microstructure and superstructure of the behavior engendered by a fixed-interval 5- and a fixed-interval 15-minute schedule of food reinforcement in the pigeon. Analysis of performance typical of fixed-interval responding indicated that the scalloped pattern does not result from smooth acceleration in responding, but, rather, from renewed pausing early in the interval. Individual interresponse-time (IRT) analyses provided no evidence of acceleration. There was a strong indication of alternation in shorter-longer IRTs, but these shorter-longer IRTs did not occur at random, reflecting instead a sequential dependency in successive IRTs. Furthermore, early in the interval there was a high relative frequency of short IRTs. Such a pattern of early pauses and short IRTs does not suggest behavior typical of reinforced responding as exemplified by the pattern found near the end of the interval. Thus, behavior from clearly scalloped performance can be classified into three states: postreinforcement pause, interim behavior, and terminal behavior. PMID:16812324

  14. Microanalysis of fixed-interval responding

    SciTech Connect

    Gentry, G.D.; Weiss, B.; Laties, V.G.

    1983-03-01

    The fixed-interval schedule of reinforcement is one of the more widely studied schedules in the experimental analysis of behavior and is also a common baseline for behavior pharmacology. Despite many intensive studies, the controlling variables and the pattern of behavior engendered are not well understood. The present study examined the microstructure and superstructure of the behavior engendered by a fixed-interval 5- and a fixed-interval 15-minute schedule of food reinforcement in the pigeon. Analysis of performance typical of fixed-interval responding indicated that the scalloped pattern does not result from smooth acceleration in responding, but, rather, from renewed pausing early in the interval. Individual interresponse-time (IRT) analyses provided no evidence of acceleration. There was a strong indication of alternation is shorter-longer IRTs, but these shorter-longer IRTs did not occur at random, reflecting instead a sequential dependency in successive IRTs. Furthermore, early in the interval there was a high relative frequency of short IRTs. Such a pattern of early pauses and short IRTs does not suggest behavior typical of reinforced responding as exemplified by the pattern found near the end of the interval. Thus, behavior from clearly scalloped performance can be classified into three states: postreinforcement pause, interim behavior, and terminal behavior. 31 references, 11 figures, 4 tables.

  15. Fast transfer of crossmodal time interval training.

    PubMed

    Chen, Lihan; Zhou, Xiaolin

    2014-06-01

    Sub-second time perception is essential for many important sensory and perceptual tasks including speech perception, motion perception, motor coordination, and crossmodal interaction. This study investigates to what extent the ability to discriminate sub-second time intervals acquired in one sensory modality can be transferred to another modality. To this end, we used perceptual classification of visual Ternus display (Ternus in Psychol Forsch 7:81-136, 1926) to implicitly measure participants' interval perception in pre- and posttests and implemented an intra- or crossmodal sub-second interval discrimination training protocol in between the tests. The Ternus display elicited either an "element motion" or a "group motion" percept, depending on the inter-stimulus interval between the two visual frames. The training protocol required participants to explicitly compare the interval length between a pair of visual, auditory, or tactile stimuli with a standard interval or to implicitly perceive the length of visual, auditory, or tactile intervals by completing a non-temporal task (discrimination of auditory pitch or tactile intensity). Results showed that after fast explicit training of interval discrimination (about 15 min), participants improved their ability to categorize the visual apparent motion in Ternus displays, although the training benefits were mild for visual timing training. However, the benefits were absent for implicit interval training protocols. This finding suggests that the timing ability in one modality can be rapidly acquired and used to improve timing-related performance in another modality and that there may exist a central clock for sub-second temporal processing, although modality-specific perceptual properties may constrain the functioning of this clock.

  16. Strong Confidence Intervals: A Compromise between the Gaussian and the Slash.

    DTIC Science & Technology

    1983-11-01

    In this report we define strong confidence interval procedures and discuss their properties. Strong confidence means that the reported confidence level is achieved even conditioned on configurations. Furthermore this is true for both the Gaussian and the slash sampling situations. We will show how such a procedure can be obtained and compare its performance to some popular non-parametric confidence intervals. (Author)

  17. The Total Interval of a Graph.

    DTIC Science & Technology

    1988-01-01

    definitions for all of these clases . A Husimi tree is a graph for which every block is a clique. A cactus is a graph for which every edge is in at most one...proportion of graphs with n vertices that we can represent with q(n) intervals is at most n-2 and this approaches zero as n gets large . Hence the...representations will have relatively few intervals of small depth and relatively many intervals of large depth. It is nevertheless often useful to restrict

  18. Advanced Interval Management: A Benefit Analysis

    NASA Technical Reports Server (NTRS)

    Timer, Sebastian; Peters, Mark

    2016-01-01

    This document is the final report for the NASA Langley Research Center (LaRC)- sponsored task order 'Possible Benefits for Advanced Interval Management Operations.' Under this research project, Architecture Technology Corporation performed an analysis to determine the maximum potential benefit to be gained if specific Advanced Interval Management (AIM) operations were implemented in the National Airspace System (NAS). The motivation for this research is to guide NASA decision-making on which Interval Management (IM) applications offer the most potential benefit and warrant further research.

  19. Learned interval time facilitates associate memory retrieval

    PubMed Central

    van de Ven, Vincent; Kochs, Sarah; Smulders, Fren; De Weerd, Peter

    2017-01-01

    The extent to which time is represented in memory remains underinvestigated. We designed a time paired associate task (TPAT) in which participants implicitly learned cue–time–target associations between cue–target pairs and specific cue–target intervals. During subsequent memory testing, participants showed increased accuracy of identifying matching cue–target pairs if the time interval during testing matched the implicitly learned interval. A control experiment showed that participants had no explicit knowledge about the cue–time associations. We suggest that “elapsed time” can act as a temporal mnemonic associate that can facilitate retrieval of events associated in memory. PMID:28298554

  20. A simple, physiologically-based model of sea turtle remigration intervals and nesting population dynamics: Effects of temperature.

    PubMed

    Neeman, Noga; Spotila, James R; O'Connor, Michael P

    2015-09-07

    Variation in the yearly number of sea turtles nesting at rookeries can interfere with population estimates and obscure real population dynamics. Previous theoretical models suggested that this variation in nesting numbers may be driven by changes in resources at the foraging grounds. We developed a physiologically-based model that uses temperatures at foraging sites to predict foraging conditions, resource accumulation, remigration probabilities, and, ultimately, nesting numbers for a stable population of sea turtles. We used this model to explore several scenarios of temperature variation at the foraging grounds, including one-year perturbations and cyclical temperature oscillations. We found that thermally driven resource variation can indeed synchronize nesting in groups of turtles, creating cohorts, but that these cohorts tend to break down over 5-10 years unless regenerated by environmental conditions. Cohorts were broken down faster at lower temperatures. One-year perturbations of low temperature had a synchronizing effect on nesting the following year, while high temperature perturbations tended to delay nesting in a less synchronized way. Cyclical temperatures lead to cyclical responses both in nesting numbers and remigration intervals, with the amplitude and lag of the response depending on the duration of the cycle. Overall, model behavior is consistent with observations at nesting beaches. Future work should focus on refining the model to fit particular nesting populations and testing further whether or not it may be used to predict observed nesting numbers and remigration intervals.

  1. CONTRIBUTION OF NUTRIENTS AND E. COLI TO SURFACE WATER CONDITION IN THE OZARKS I. USING PARTIAL LEAST SQUARES PREDICTIONS WHEN STANDARD REGRESSION ASSUMPTIONS ARE VIOLATED

    EPA Science Inventory

    We present here the application of PLS regression to predicting surface water total phosphorous, total ammonia and Escherichia coli from landscape metrics. The amount of variability in surface water constituents explained by each model reflects the composition of the contributi...

  2. Evaluating and Predicting the Effectiveness of Green Infrastructure on a Small Watershed Scale - Emphasis on Water Quality, Flow, Thermal Regime, Substrate Integrity, and Biological Condition

    EPA Science Inventory

    Assessments of the effectiveness of stormwater best management practices (BMPs) have focused on measurement of load or concentration reductions, which can be translated to predict biological impacts based on chemical water quality criteria. However, many of the impacts of develo...

  3. Psychosocial and nonclinical factors predicting hospital utilization in patients of a chronic disease management program: a prospective observational study.

    PubMed

    Tran, Mark W; Weiland, Tracey J; Phillips, Georgina A

    2015-01-01

    Psychosocial factors such as marital status (odds ratio, 3.52; 95% confidence interval, 1.43-8.69; P = .006) and nonclinical factors such as outpatient nonattendances (odds ratio, 2.52; 95% confidence interval, 1.22-5.23; P = .013) and referrals made (odds ratio, 1.20; 95% confidence interval, 1.06-1.35; P = .003) predict hospital utilization for patients in a chronic disease management program. Along with optimizing patients' clinical condition by prescribed medical guidelines and supporting patient self-management, addressing psychosocial and nonclinical issues are important in attempting to avoid hospital utilization for people with chronic illnesses.

  4. [Research on concentration retrieval of gas FTIR spectra by interval extreme learning machine and genetic algorithm].

    PubMed

    Chen, Yuan-Yuan; Wang, Zhi-Bin; Wang, Zhao-Ba; Li, Xiao

    2014-05-01

    This paper proposed a novel effective quantitative analysis method for FTIR spectroscopy of polluted gases, which select the best wavenumbers based on the idea of interval dividing. Meanwhile, genetic algorithm was adopted to optimize the connect weights and thresholds of the input layer and the hidden layer of extreme learning machine (ELM) because of its global search ability. Firstly, the whole spectrum region was divided into several subintervals; Secondly, the quantitative analysis model was established in each subinterval by using optimized GA-ELM; Thirdly, the best combination of subintervals was selected according to the generalized performance of each subinterval model by computing the parameters root mean square error (RMSE) and determined coefficients r. In this paper, the mixture of CO, CO2 and N2 O gases were selected as the research object and the whole spectrum range was from 2 140 to 2 220 cm-1. The experiment results showed that the RMSE of model established with the selected wavenumbers was 154. 996 3, the corresponding r can reach 0. 987 4, and the running time was just 0. 8 seconds, which indicated that the concentration retrieval model established with the proposed Interval-GA-ELM (iGELM) method can not only reduce the modeling time, but also can improve the stability and predict accuracy, especially under the condition of the exist of interferents, which providing an effective approach to the remote analysis of polluted gases.

  5. Efficient Computation Of Confidence Intervals Of Parameters

    NASA Technical Reports Server (NTRS)

    Murphy, Patrick C.

    1992-01-01

    Study focuses on obtaining efficient algorithm for estimation of confidence intervals of ML estimates. Four algorithms selected to solve associated constrained optimization problem. Hybrid algorithms, following search and gradient approaches, prove best.

  6. Application of Interval Analysis to Error Control.

    DTIC Science & Technology

    1976-09-01

    We give simple examples of ways in which interval arithmetic can be used to alert instabilities in computer algorithms , roundoff error accumulation, and even the effects of hardware inadequacies. This paper is primarily tutorial. (Author)

  7. Intact Interval Timing in Circadian CLOCK Mutants

    PubMed Central

    Cordes, Sara; Gallistel, C. R.

    2008-01-01

    While progress has been made in determining the molecular basis for the circadian clock, the mechanism by which mammalian brains time intervals measured in seconds to minutes remains a mystery. An obvious question is whether the interval timing mechanism shares molecular machinery with the circadian timing mechanism. In the current study, we trained circadian CLOCK +/− and −/− mutant male mice in a peak-interval procedure with 10 and 20-s criteria. The mutant mice were more active than their wild-type littermates, but there were no reliable deficits in the accuracy or precision of their timing as compared with wild-type littermates. This suggests that expression of the CLOCK protein is not necessary for normal interval timing. PMID:18602902

  8. A robust measure of food web intervality

    PubMed Central

    Stouffer, Daniel B.; Camacho, Juan; Amaral, Luís A. Nunes

    2006-01-01

    Intervality of a food web is related to the number of trophic dimensions characterizing the niches in a community. We introduce here a mathematically robust measure for food web intervality. It has previously been noted that empirical food webs are not strictly interval; however, upon comparison to suitable null hypotheses, we conclude that empirical food webs actually do exhibit a strong bias toward contiguity of prey, that is, toward intervality. Further, our results strongly suggest that empirically observed species and their diets can be mapped onto a single dimension. This finding validates a critical assumption in the recently proposed static niche model and provides guidance for ongoing efforts to develop dynamic models of ecosystems. PMID:17146055

  9. Interval and contour processing in autism.

    PubMed

    Heaton, Pamela

    2005-12-01

    High functioning children with autism and age and intelligence matched controls participated in experiments testing perception of pitch intervals and musical contours. The finding from the interval study showed superior detection of pitch direction over small pitch distances in the autism group. On the test of contour discrimination no group differences emerged. These findings confirm earlier studies showing facilitated pitch processing and a preserved ability to represent small-scale musical structures in autism.

  10. Periodicity In The Intervals Between Primes

    DTIC Science & Technology

    2015-07-02

    statistically strong periodicity is identified in the counting function giving the total number of intervals of a certain size. The nature of the periodic...positive intervals among the first n<=10^6 prime numbers as a probe of the global nature of the sequence of primes. A statistically strong periodicity is...Let x = x1, x2, . . . be an increasing sequence of real numbers which may be either finite or infinitely long. Throughout the following every bold

  11. Probability Distribution for Flowing Interval Spacing

    SciTech Connect

    S. Kuzio

    2004-09-22

    Fracture spacing is a key hydrologic parameter in analyses of matrix diffusion. Although the individual fractures that transmit flow in the saturated zone (SZ) cannot be identified directly, it is possible to determine the fractured zones that transmit flow from flow meter survey observations. The fractured zones that transmit flow as identified through borehole flow meter surveys have been defined in this report as flowing intervals. The flowing interval spacing is measured between the midpoints of each flowing interval. The determination of flowing interval spacing is important because the flowing interval spacing parameter is a key hydrologic parameter in SZ transport modeling, which impacts the extent of matrix diffusion in the SZ volcanic matrix. The output of this report is input to the ''Saturated Zone Flow and Transport Model Abstraction'' (BSC 2004 [DIRS 170042]). Specifically, the analysis of data and development of a data distribution reported herein is used to develop the uncertainty distribution for the flowing interval spacing parameter for the SZ transport abstraction model. Figure 1-1 shows the relationship of this report to other model reports that also pertain to flow and transport in the SZ. Figure 1-1 also shows the flow of key information among the SZ reports. It should be noted that Figure 1-1 does not contain a complete representation of the data and parameter inputs and outputs of all SZ reports, nor does it show inputs external to this suite of SZ reports. Use of the developed flowing interval spacing probability distribution is subject to the limitations of the assumptions discussed in Sections 5 and 6 of this analysis report. The number of fractures in a flowing interval is not known. Therefore, the flowing intervals are assumed to be composed of one flowing zone in the transport simulations. This analysis may overestimate the flowing interval spacing because the number of fractures that contribute to a flowing interval cannot be

  12. Different target-discrimination times can be followed by the same saccade-initiation timing in different stimulus conditions during visual searches.

    PubMed

    Tanaka, Tomohiro; Nishida, Satoshi; Ogawa, Tadashi

    2015-07-01

    The neuronal processes that underlie visual searches can be divided into two stages: target discrimination and saccade preparation/generation. This predicts that the length of time of the prediscrimination stage varies according to the search difficulty across different stimulus conditions, whereas the length of the latter postdiscrimination stage is stimulus invariant. However, recent studies have suggested that the length of the postdiscrimination interval changes with different stimulus conditions. To address whether and how the visual stimulus affects determination of the postdiscrimination interval, we recorded single-neuron activity in the lateral intraparietal area (LIP) when monkeys (Macaca fuscata) performed a color-singleton search involving four stimulus conditions that differed regarding luminance (Bright vs. Dim) and target-distractor color similarity (Easy vs. Difficult). We specifically focused on comparing activities between the Bright-Difficult and Dim-Easy conditions, in which the visual stimuli were considerably different, but the mean reaction times were indistinguishable. This allowed us to examine the neuronal activity when the difference in the degree of search speed between different stimulus conditions was minimal. We found that not only prediscrimination but also postdiscrimination intervals varied across stimulus conditions: the postdiscrimination interval was longer in the Dim-Easy condition than in the Bright-Difficult condition. Further analysis revealed that the postdiscrimination interval might vary with stimulus luminance. A computer simulation using an accumulation-to-threshold model suggested that the luminance-related difference in visual response strength at discrimination time could be the cause of different postdiscrimination intervals.

  13. Age effects in discrimination of intervals within rhythmic tone sequences

    PubMed Central

    Fitzgibbons, Peter J.; Gordon-Salant, Sandra

    2015-01-01

    This study measured listener sensitivity to increments of a target inter-onset interval (IOI) embedded within tone sequences that featured different rhythmic patterns. The sequences consisted of six 50-ms 1000-Hz tone bursts separated by silent intervals that were adjusted to create different timing patterns. Control sequences were isochronous, with all tonal IOIs fixed at either 200 or 400 ms, while other patterns featured combinations of the two IOIs arranged to create different sequential tonal groupings. Duration difference limens in milliseconds for increments of a single sequence IOI were measured adaptively by adjusting the duration of an inter-tone silent interval. Specific target IOIs within sequences differed across discrimination conditions. Listeners included younger normal-hearing adults and groups of older adults with and without hearing loss. Discrimination performance measured for each of the older groups of listeners was observed to be equivalent, with each group exhibiting significantly poorer discrimination performance than the younger listeners in each sequence condition. Additionally, the specific influence of variable rhythmic grouping on temporal sensitivity was found to be greatest among older listeners. PMID:25618068

  14. Modeling Relationships Between Flight Crew Demographics and Perceptions of Interval Management

    NASA Technical Reports Server (NTRS)

    Remy, Benjamin; Wilson, Sara R.

    2016-01-01

    The Interval Management Alternative Clearances (IMAC) human-in-the-loop simulation experiment was conducted to assess interval management system performance and participants' acceptability and workload while performing three interval management clearance types. Twenty-four subject pilots and eight subject controllers flew ten high-density arrival scenarios into Denver International Airport during two weeks of data collection. This analysis examined the possible relationships between subject pilot demographics on reported perceptions of interval management in IMAC. Multiple linear regression models were created with a new software tool to predict subject pilot questionnaire item responses from demographic information. General patterns were noted across models that may indicate flight crew demographics influence perceptions of interval management.