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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. PMID:25603651

  2. 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.

  3. 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…

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

    PubMed Central

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

    2016-01-01

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

  5. PREDICTION INTERVALS FOR INTEGRALS OF GAUSSIAN RANDOM FIELDS.

    PubMed

    De Oliveira, Victor; Kone, Bazoumana

    2015-03-01

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

  6. PREDICTION INTERVALS FOR INTEGRALS OF GAUSSIAN RANDOM FIELDS

    PubMed Central

    De Oliveira, Victor; Kone, Bazoumana

    2014-01-01

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

  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. Interval Prediction of Molecular Properties in Parametrized Quantum Chemistry

    NASA Astrophysics Data System (ADS)

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

    2014-06-01

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

  10. Ongoing behavior predicts perceptual report of interval duration

    PubMed Central

    Gouvêa, Thiago S.; Monteiro, Tiago; Soares, Sofia; Atallah, Bassam V.; Paton, Joseph J.

    2014-01-01

    The ability to estimate the passage of time is essential for adaptive behavior in complex environments. Yet, it is not known how the brain encodes time over the durations necessary to explain animal behavior. Under temporally structured reinforcement schedules, animals tend to develop temporally structured behavior, and interval timing has been suggested to be accomplished by learning sequences of behavioral states. If this is true, trial to trial fluctuations in behavioral sequences should be predictive of fluctuations in time estimation. We trained rodents in an duration categorization task while continuously monitoring their behavior with a high speed camera. Animals developed highly reproducible behavioral sequences during the interval being timed. Moreover, those sequences were often predictive of perceptual report from early in the trial, providing support to the idea that animals may use learned behavioral patterns to estimate the duration of time intervals. To better resolve the issue, we propose that continuous and simultaneous behavioral and neural monitoring will enable identification of neural activity related to time perception that is not explained by ongoing behavior. PMID:24672473

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

    NASA Astrophysics Data System (ADS)

    Leuenberger, Michael; Kanevski, Mikhail

    2015-04-01

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

  12. 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.

  13. Selective activation of a putative reinforcement signal conditions cued interval timing in primary visual cortex

    PubMed Central

    Liu, Cheng-Hang; Coleman, Jason E.; Davoudi, Heydar; Zhang, Kechen; Hussain Shuler, Marshall G.

    2015-01-01

    Summary As a consequence of conditioning visual cues with delayed reward, cue-evoked neural activity that predicts the time of expected future reward emerges in the primary visual cortex (V1). We hypothesized that this reward timing activity is engendered by a reinforcement signal conveying reward acquisition to V1. In lieu of behavioral conditioning, we assessed in vivo whether selective activation of either basal forebrain (BF) or cholinergic innervation is sufficient to condition cued interval timing activity. Substituting for actual reward, optogenetic activation of BF or cholinergic input within V1 at fixed delays following visual stimulation entrains neural responses that mimic behaviorally-conditioned reward timing activity. Optogenetically-conditioned neural responses express cue-evoked temporal intervals that correspond to the conditioning intervals, are bidirectionally modifiable, display experience-dependent refinement, and exhibit a scale invariance to the encoded delay. Our results demonstrate that the activation of BF or cholinergic input within V1is sufficient to encode cued interval timing activity, and indicate that V1 itself is a substrate for associative learning that may inform the timing of visually-cued behaviors. PMID:26004763

  14. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2013-08-01

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

  16. 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.

  17. Timing Rhythms: Perceived Duration Increases with a Predictable Temporal Structure of Short Interval Fillers

    PubMed Central

    Horr, Ninja K.; Di Luca, Massimiliano

    2015-01-01

    Variations in the temporal structure of an interval can lead to remarkable differences in perceived duration. For example, it has previously been shown that isochronous intervals, that is, intervals filled with temporally regular stimuli, are perceived to last longer than intervals left empty or filled with randomly timed stimuli. Characterizing the extent of such distortions is crucial to understanding how duration perception works. One account to explain effects of temporal structure is a non-linear accumulator-counter mechanism reset at the beginning of every subinterval. An alternative explanation based on entrainment to regular stimulation posits that the neural response to each filler stimulus in an isochronous sequence is amplified and a higher neural response may lead to an overestimation of duration. If entrainment is the key that generates response amplification and the distortions in perceived duration, then any form of predictability in the temporal structure of interval fillers should lead to the perception of an interval that lasts longer than a randomly filled one. The present experiments confirm that intervals filled with fully predictable rhythmically grouped stimuli lead to longer perceived duration than anisochronous intervals. No general over- or underestimation is registered for rhythmically grouped compared to isochronous intervals. However, we find that the number of stimuli in each group composing the rhythm also influences perceived duration. Implications of these findings for a non-linear clock model as well as a neural response magnitude account of perceived duration are discussed. PMID:26474047

  18. 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.

  19. Predicting clutter during anomalous propagation conditions

    NASA Astrophysics Data System (ADS)

    Lee, Susan C.; Maurer, Donald E.; Musser, Keith L.

    1988-06-01

    Excessive clutter caused by anomalous propagation conditions severely degrades radar performance in many regions of the world. This article describes methods that can be used to predict anomalous clutter amplitude for site-specific radar parameters, terrain features, and atmospheric conditions and to predict the effects of radar Doppler processing on evaporation-ducted sea clutter.

  20. ONTOGENY OF EYEBLINK CONDITIONING IN THE RAT: EFFECTS OF US INTENSITY AND INTERSTIMULUS INTERVAL ON DELAY CONDITIONING

    EPA Science Inventory

    Two experiments examined eyeblink conditioning in rat pups (17 or 24 days of age) as a function of US intensity (Experiment 1) and interstimulus interval [(ISI)] Experiment 2]. n Experiment 1 pups received 3 sessions of delay conditioning with a tone CS (380 ms, 2.8 kHz, 90 dB (S...

  1. 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.

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

    SciTech Connect

    Kabis, T.W.

    1996-05-01

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

  3. 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

  4. Prediction intervals: Placing real bounds on regression-based allometric estimates of biomass.

    PubMed

    Ward, Peter J

    2015-07-01

    Biomass allometry studies routinely assume that regression models can be applied across species and sites, and that goodness of fit of a regression model to its derivation dataset indicates both the relevance of the model to a new dataset and the likely error. Assuming that a model is relevant for a new sample, a prediction interval is a useful error measure for stand mass. Prediction coverage tests whether the model and hence the interval are appropriate in the new sample. Data for three similar shrubby species from four similar sites were combined in various ways to test the impact of varying levels of biodiverse heterogeneity on the performance of the four models most commonly used in published biomass studies. No one model performed consistently well predicting new data, and validation checks were not good indicators of prediction coverage. The highly variable results suggest that the common models might contain insufficient variables. Euclidean distance was used to quantify the relative similarity of samples as a possible means of estimating prediction coverage; it proved unsuccessful with these data. PMID:25974741

  5. Highly accurate prediction of emotions surrounding the attacks of September 11, 2001 over 1-, 2-, and 7-year prediction intervals.

    PubMed

    Doré, Bruce P; Meksin, Robert; Mather, Mara; Hirst, William; Ochsner, Kevin N

    2016-06-01

    In the aftermath of a national tragedy, important decisions are predicated on judgments of the emotional significance of the tragedy in the present and future. Research in affective forecasting has largely focused on ways in which people fail to make accurate predictions about the nature and duration of feelings experienced in the aftermath of an event. Here we ask a related but understudied question: can people forecast how they will feel in the future about a tragic event that has already occurred? We found that people were strikingly accurate when predicting how they would feel about the September 11 attacks over 1-, 2-, and 7-year prediction intervals. Although people slightly under- or overestimated their future feelings at times, they nonetheless showed high accuracy in forecasting (a) the overall intensity of their future negative emotion, and (b) the relative degree of different types of negative emotion (i.e., sadness, fear, or anger). Using a path model, we found that the relationship between forecasted and actual future emotion was partially mediated by current emotion and remembered emotion. These results extend theories of affective forecasting by showing that emotional responses to an event of ongoing national significance can be predicted with high accuracy, and by identifying current and remembered feelings as independent sources of this accuracy. (PsycINFO Database Record PMID:27100309

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  7. 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)

  8. 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.

  9. 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.

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

    PubMed

    Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

    2015-09-01

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

  11. Demographic factors predict magnitude of conditioned fear.

    PubMed

    Rosenbaum, Blake L; Bui, Eric; Marin, Marie-France; Holt, Daphne J; Lasko, Natasha B; Pitman, Roger K; Orr, Scott P; Milad, Mohammed R

    2015-10-01

    There is substantial variability across individuals in the magnitudes of their skin conductance (SC) responses during the acquisition and extinction of conditioned fear. To manage this variability, subjects may be matched for demographic variables, such as age, gender and education. However, limited data exist addressing how much variability in conditioned SC responses is actually explained by these variables. The present study assessed the influence of age, gender and education on the SC responses of 222 subjects who underwent the same differential conditioning paradigm. The demographic variables were found to predict a small but significant amount of variability in conditioned responding during fear acquisition, but not fear extinction learning or extinction recall. A larger differential change in SC during acquisition was associated with more education. Older participants and women showed smaller differential SC during acquisition. Our findings support the need to consider age, gender and education when studying fear acquisition but not necessarily when examining fear extinction learning and recall. Variability in demographic factors across studies may partially explain the difficulty in reproducing some SC findings. PMID:26151498

  12. Conrad: gene prediction using conditional random fields.

    PubMed

    DeCaprio, David; Vinson, Jade P; Pearson, Matthew D; Montgomery, Philip; Doherty, Matthew; Galagan, James E

    2007-09-01

    We present Conrad, the first comparative gene predictor based on semi-Markov conditional random fields (SMCRFs). Unlike the best standalone gene predictors, which are based on generalized hidden Markov models (GHMMs) and trained by maximum likelihood, Conrad is discriminatively trained to maximize annotation accuracy. In addition, unlike the best annotation pipelines, which rely on heuristic and ad hoc decision rules to combine standalone gene predictors with additional information such as ESTs and protein homology, Conrad encodes all sources of information as features and treats all features equally in the training and inference algorithms. Conrad outperforms the best standalone gene predictors in cross-validation and whole chromosome testing on two fungi with vastly different gene structures. The performance improvement arises from the SMCRF's discriminative training methods and their ability to easily incorporate diverse types of information by encoding them as feature functions. On Cryptococcus neoformans, configuring Conrad to reproduce the predictions of a two-species phylo-GHMM closely matches the performance of Twinscan. Enabling discriminative training increases performance, and adding new feature functions further increases performance, achieving a level of accuracy that is unprecedented for this organism. Similar results are obtained on Aspergillus nidulans comparing Conrad versus Fgenesh. SMCRFs are a promising framework for gene prediction because of their highly modular nature, simplifying the process of designing and testing potential indicators of gene structure. Conrad's implementation of SMCRFs advances the state of the art in gene prediction in fungi and provides a robust platform for both current application and future research. PMID:17690204

  13. 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.

  14. 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

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

    PubMed

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

    2016-08-01

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

  16. 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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

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

    PubMed

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

    2016-05-01

    We aimed to compare blood pressure (BP) responses following moderate-intensity continuous exercise (MICE), high-intensity interval exercise (HIIE) in dry land or HIIE in immersed condition, using 24-hour ambulatory BP monitoring. Forty-two individuals (65 ± 7 years, 52% men) with a baseline BP ≥ 130/85 mm Hg (systolic/diastolic blood pressures [SBP/DBP]) were randomly assigned to perform one of the three following exercises on a stationary cycle: MICE (24 minutes at 50% peak power output) or HIIE in dry land (two sets of 10 minutes with phases of 15 seconds 100% peak power output interspersed by 15 seconds of passive recovery) or HIIE in up-to-the-chest immersed condition. While MICE modified none of the 24-hour average hemodynamic variables, dryland HIIE induced a 24-hour BP decrease (SBP: -3.6 ± 5.7/DBP: -2.8 ± 3.0 mm Hg, P < .05) and, to a much greater extent, immersed HIIE (SBP: -6.8 ± 9.5/DBP: -3.0 ± 4.5 mm Hg, P < .05). The one condition that modified 24-hour pulse-wave velocity was immersed HIIE (-0.21 ± 0.30 m/s, P < .05). PMID:27026570

  19. 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.

  20. 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. PMID:24807030

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

    PubMed Central

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

    2014-01-01

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

  2. Long-interval facilitation and inhibition are differentially affected by conditioning stimulus intensity over different time courses.

    PubMed

    Vallence, Ann-Maree; Schneider, Luke A; Pitcher, Julia B; Ridding, Michael C

    2014-06-01

    Intracortical facilitatory and inhibitory processes in the primary motor cortex (M1) play an important role in both the preparation and execution of motor tasks. Here we aimed to (1) confirm the existence of, and further characterise, intracortical facilitation at long conditioning-test stimulus intervals at subthreshold conditioning stimulus (CS) intensities and (2) identify the threshold for long-interval intracortical inhibition (LICI) at different inter-stimulus intervals (ISIs). To examine facilitation, stimulus-response curves at ISIs of 100 and 150 ms were obtained using a range of subthreshold CS intensities. LICI stimulus-response curves were also obtained using varying CS intensities at ISIs of 100 (LICI100) and 150 ms (LICI150). Facilitation of the conditioned MEP was observed at subthreshold CS intensities at an ISI of 100 ms. LICI100 was observed at a lower CS intensity than LICI150. First, we provide evidence of a long-interval facilitation and provide some evidence consistent with a cortical origin of this facilitation. Second, the lower threshold for evoking LICI100 than LICI150 suggests an intensity-duration effect whereby a more intense CS results in longer duration LICI. Investigation of the interaction between LICI and long-interval facilitation might help to elucidate the functional importance of these processes. PMID:24704380

  3. 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.

  4. 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.…

  5. 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…

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

    ERIC Educational Resources Information Center

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

    2007-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  8. 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

  9. Predicting Road Conditions with Internet Search.

    PubMed

    Askitas, Nikolaos

    2016-01-01

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

  10. Conditional monogyny: female quality predicts male faithfulness

    PubMed Central

    2012-01-01

    Introduction Male monogyny in the absence of paternal investment is arguably one of the most puzzling mating systems. Recent evidence suggests that males of monogynous species adjust their life-history and their mating decision to shifting spatial and temporal selection regimes. In the cannibalistic wasp spider Argiope bruennichi males can be either monogynous or mate with a maximum of two females. We studied factors underlying male mating decisions in a natural population over a whole mating season. We documented all matings and categorized the males into single-mated and double-mated monogynous as well as bigynous males. Results We found that all categories were continuously present with relatively stable frequencies despite changes in the operational sex ratio. Males were more likely monogynous when copulating with relatively heavy and old females and otherwise bigynous. Conclusion Our results imply that males make conditional mating decisions based on the quality of the first female they encounter but do not adjust their mating tactic to the local selection regime. PMID:22533854

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

    PubMed

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

    2015-11-01

    We tested the hypothesis that baseline cardiac autonomic function and its acute response to all-out interval exercise explains individual fitness responses to high-intensity interval training (HIT). Healthy middle-aged sedentary men performed HIT (n=12, 4-6×30 s of all-out cycling efforts with 4-min recovery) or aerobic training (AET, n=9, 40-60 min at 60% of peak workload in exercise test [Loadpeak]), comprising 6 sessions within 2 weeks. Low (LF) and high frequency (HF) power of R-R interval oscillation were analyzed from data recorded at supine and standing position (5+5 min) every morning during the intervention. A significant training effect (p< 0.001), without a training*group interaction, was observed in Loadpeak and peak oxygen consumption (VO2peak). Pre-training supine LF/HF ratio, an estimate of sympathovagal balance, correlated with training outcome in Loadpeak (Spearman's rho [rs]=-0.74, p=0.006) and VO2peak (rs=- 0.59, p=0.042) in the HIT but not the AET group. Also, the mean change in the standing LF/HF ratio in the morning after an acute HIT exercise during the 1(st) week of intervention correlated with training response in Loadpeak (rs=- 0.68, p=0.014) and VO2peak (rs=-0.60, p=0.039) with HIT but not with AET. In conclusion, pre-training cardiac sympathovagal balance and its initial alterations in response to acute HIT exercise were related to fitness responses to short-term HIT. PMID:26140689

  12. 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…

  13. 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…

  14. 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.

  15. 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…

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

    PubMed Central

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

    2002-01-01

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

  17. Improvements in heat tolerance induced by interval running training in the heat and in sweat clothing in cool conditions.

    PubMed

    Dawson, B; Pyke, F S; Morton, A R

    1989-01-01

    To compare the effectiveness of training in heat and in sweat clothing in cool conditions on improving heat tolerance, two groups of active subjects (n = 6 in each) performed an interval running heat-tolerance test before and after a 7-day experimental treatment. On each treatment day the subjects attempted to complete 4 x 15 min interval treadmill running periods (a 7.5 s effort every 30 s, on 15 km h-1, 15% grade; the same exercise format as the heat-tolerance test), which were interspersed with 5-min recovery periods (total time each day = 80 min). Group 1 (heat) ran in shorts, socks and shoes in hot humid conditions, and Group 2 (sweat clothing) ran in cool conditions dressed in shorts, socks and T-shirt covered by a polyester-cotton tracksuit, over which was worn 100% nylon spray-proof pants and jacket (cotton lined) with an acrylic cloth bobble hat (beanie) on the head. Both groups displayed changes typical of heat acclimatization over the 7-day period, with significant decreases in final rectal temperature (Tr) and heart rate (HR) being evident, but no change in sweat loss. Mean skin temperature (Tsk) was similar in both groups during the training sessions (heat group: 34.8-35.7 degrees C; sweat clothing group 34.9-35.5 degrees C). After the heat-tolerance test, both groups had significantly lower Tr, Tsk and HR values than before, and sweating sensitivity (g m-2 h-1 degrees C rise in Tr) was significantly increased. There was only one significant difference between the two groups (Tsk, 20th min value). It was concluded that training in sweat clothing in cool conditions can provide the same improvements in heat tolerance as training in hot humid conditions where a fixed exercise intensity and duration are used. PMID:2621757

  18. Hormone naïve prostate cancer: predicting and maximizing response intervals

    PubMed Central

    Moul, Judd W

    2015-01-01

    Hormone naïve advanced prostate cancer is subdivided into two disease states: biochemical recurrence and traditional M1 (metastatic) prostate cancer and characterized by no prior hormonal therapy or androgen deprivation therapy (ADT). In biochemical recurrence/prostate-specific antigen (PSA) recurrence, men should be risk-stratified based on their PSA doubling time, the Gleason score and the timing of the recurrence. In general, only men who are at high risk should be considered for early/immediate ADT although this is best done using shared decision with the patient. The type of ADT to be used in biochemical recurrence ranging from oral-only peripheral blockade (peripheral androgen deprivation) to complete hormonal therapy (combined androgen blockade [CAB]) remains in debate owing to lack of randomized controlled trials (RCT). However, there is good RCT support for use of intermittent hormonal therapy (IHT). There is also limited research on biomarker response (PSA and testosterone decline) to predict prognosis. On the other hand, in the setting of M1 hormone naïve prostate cancer, there are many more RCT's to inform our decisions. CAB and gonadotrophin-releasing hormone antagonists perhaps provide a slight efficacy advantage while IHT may be slightly inferior with minimal M1 disease. The PSA nadir at 7 months after starting ADT is a powerful prognostic tool for M1 patients. There is growing recognition that serum testosterone (T) control while on ADT is linked to the development of castrate-resistant prostate cancer. Especially for a M1 patient, maintaining a serum T below 20–30 ng dl−1 prolongs the response to ADT. Novel oral agents (abiraterone and enzalutamide) may soon find use in hormone naïve disease and may alter the treatment landscape. Despite over 75 years of experience with ADT, many questions remain, and the field continues to evolve. PMID:26112479

  19. Echo state network prediction method and its application in flue gas turbine condition prediction

    NASA Astrophysics Data System (ADS)

    Wang, Shaohong; Chen, Tao; Xu, Xiaoli

    2010-12-01

    On the background of the complex production process of fluid catalytic cracking energy recovery system in large-scale petrochemical refineries, this paper introduced an improved echo state network (ESN) model prediction method which is used to address the condition trend prediction problem of the key power equipment--flue gas turbine. Singular value decomposition method was used to obtain the ESN output weight. Through selecting the appropriate parameters and discarding small singular value, this method overcame the defective solution problem in the prediction by using the linear regression algorithm, improved the prediction performance of echo state network, and gave the network prediction process. In order to solve the problem of noise contained in production data, the translation-invariant wavelet transform analysis method is combined to denoise the noisy time series before prediction. Condition trend prediction results show the effectiveness of the proposed method.

  20. 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.

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

    PubMed

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

    2014-10-01

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

  2. 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

  3. 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

  4. 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. PMID:26822948

  5. Global nonlinear kernel prediction for large data set with a particle swarm-optimized interval support vector regression.

    PubMed

    Ding, Yongsheng; Cheng, Lijun; Pedrycz, Witold; Hao, Kuangrong

    2015-10-01

    A new global nonlinear predictor with a particle swarm-optimized interval support vector regression (PSO-ISVR) is proposed to address three issues (viz., kernel selection, model optimization, kernel method speed) encountered when applying SVR in the presence of large data sets. The novel prediction model can reduce the SVR computing overhead by dividing input space and adaptively selecting the optimized kernel functions to obtain optimal SVR parameter by PSO. To quantify the quality of the predictor, its generalization performance and execution speed are investigated based on statistical learning theory. In addition, experiments using synthetic data as well as the stock volume weighted average price are reported to demonstrate the effectiveness of the developed models. The experimental results show that the proposed PSO-ISVR predictor can improve the computational efficiency and the overall prediction accuracy compared with the results produced by the SVR and other regression methods. The proposed PSO-ISVR provides an important tool for nonlinear regression analysis of big data. PMID:25974954

  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., Jr.; Rice, K.C.; Hornberger, G.M.

    2006-01-01

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

  7. 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.

  8. Interbirth intervals

    PubMed Central

    Haig, David

    2014-01-01

    Background and objectives: Interbirth intervals (IBIs) mediate a trade-off between child number and child survival. Life history theory predicts that the evolutionarily optimal IBI differs for different individuals whose fitness is affected by how closely a mother spaces her children. The objective of the article is to clarify these conflicts and explore their implications for public health. Methodology: Simple models of inclusive fitness and kin conflict address the evolution of human birth-spacing. Results: Genes of infants generally favor longer intervals than genes of mothers, and infant genes of paternal origin generally favor longer IBIs than genes of maternal origin. Conclusions and implications: The colonization of maternal bodies by offspring cells (fetal microchimerism) raises the possibility that cells of older offspring could extend IBIs by interfering with the implantation of subsequent embryos. PMID:24480612

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

    PubMed

    Cook, J G; Green, M J

    2016-06-01

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

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

    PubMed

    Oliveira, A S; Ferreira, V B

    2016-02-01

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

  11. 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

  12. Predicting Weather Conditions and Climate for Mars Expeditions

    NASA Astrophysics Data System (ADS)

    Read, P. L.; Lewis, S. R.; Bingham, S. J.; Newman, C. E.

    Weather and climatic conditions are among the most important factors to be taken into account when planning expeditions to remote and challenging locations on Earth. This is likely to be equally the case for expedition planners on Mars, where conditions (in terms of extremes of temperature, etc.) can be at least as daunting as back on Earth. With the success of recent unmanned missions to Mars, such as NASA's Mars Pathfinder, Mars Global Surveyor and Mars Odyssey, there is now a great deal of information available on the range of environ- mental conditions on Mars, from the tropics to the CO2 ice-covered polar caps. This has been further supple- mented by the development of advanced numerical models of the Martian atmosphere, allowing detailed and accurate simulations and predictions of the weather and climate across the planet. This report discusses the main weather and climate variables which future Martian human expedition planners will need to take into account. The range of conditions likely to be encountered at a variety of typical locations on Mars is then considered, with reference to predictions from the ESA Mars Climate Database.

  13. RWEQ - Wind erosion predictions for variable soil roughness conditions

    NASA Astrophysics Data System (ADS)

    de Oro, Laura A.; Colazo, Juan C.; Buschiazzo, Daniel E.

    2016-03-01

    The soil surface roughness is a main factor in all wind erosion prediction models, including the Revised Wind Erosion Equation (RWEQ). The objective of this study was to test the erodibility of two typical soils of the semiarid Argentinean Pampas under three different tillage conditions (compared to a flat surface) at three wind velocities using a wind tunnel and to evaluate the performance of the RWEQ model. Results showed that all rough surfaces were less eroded by wind than a flat surface (FS) in both soils and all wind velocities. An exception was LB (lister-bedder) in the Haplustoll that showed similar erosion than FS. Wind erosion increased rapidly above 16.5 m s-1 wind velocity in all tillage conditions. The relative wind erosion (RE) calculated with the RWEQ (K‧ factor) fitted well with measured RE, except for K‧ < 0.1 (rougher surface) where the measured RE were much higher than the predicted. More than 70% of RE variability was explained by the oriented roughness (Kr) in both soils. The aforementioned indicates that Kr can be used instead of K‧ (a value that contains both, Kr and the random roughness - Crr factors) to predict wind erosion with RWEQ in the studied soils. Absolute wind erosion amounts predicted with RWEQ fitted well with measured data only for DT, mainly at low wind velocity. For the other tillage tools, the model did not apply well as it underestimated the erosion for the rougher soil surface condition (LB) and overestimated it for the less rough surface (DH).

  14. 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.

  15. 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.

  16. Neonatal Binge Alcohol Exposure Produces Dose Dependent Deficits in Interstimulus Interval Discrimination Eyeblink Conditioning in Juvenile Rats

    PubMed Central

    Brown, Kevin L.; Burman, Michael A.; Duong, Huan B.; Stanton, Mark E.

    2009-01-01

    Alcohol consumption in neonatal rats produces cerebellar damage and is widely used to model 3rd-trimester human fetal alcohol exposure. Neonatal “binge-like” exposure to high doses of alcohol (5 g/kg/day or more) impairs acquisition of eyeblink classical conditioning (EBC), a cerebellar-dependent Pavlovian motor learning task. We have recently found impairments in interstimulus interval (ISI) discrimination – a complex task variant of EBC - in adult rats following postnatal day (PD) 4–9 alcohol exposure at doses of 3, 4, and 5 g/kg/day. Because robust developmental differences in conditioned response (CR) generation and CR latency measures are present between untreated juveniles and adults in this task, we sought to extend alcohol findings to juvenile rats (PD30). Five neonatal treatment groups were used: (1) undisturbed controls, (2) sham intubation controls, (3) 3 g/kg/day of alcohol (blood alcohol concentration {BAC} = 139.9 mg/dl), (4) 4 g/kg/day of alcohol (BAC = 237.3 mg/dl), or (5) 5 g/kg/day of alcohol (BAC = 301.8 mg/dl). Intubations occurred over PD4-9. ISI discrimination training in juveniles (PD30-33) revealed dose-dependent CR deficits in all three alcohol-exposed groups relative to controls. Contrary to expected outcomes, CR latency measures were not significantly affected as a function of neonatal treatment. Comparison of these findings with our recent study in adults suggests that alcohol-induced impairments in ISI discrimination EBC may be greater in adults relative to juveniles. The present findings provide further evidence that ISI discrimination may provide greater sensitivity to functional deficits resulting from moderate levels of neonatal alcohol exposure relative to single-cue EBC paradigms. PMID:19007754

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

    PubMed

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

    2016-04-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-04-01

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

  1. Economic conditions predict prevalence of West Nile virus.

    PubMed

    Harrigan, Ryan J; Thomassen, Henri A; Buermann, Wolfgang; Cummings, Robert F; Kahn, Matthew E; Smith, Thomas B

    2010-01-01

    Understanding the conditions underlying the proliferation of infectious diseases is crucial for mitigating future outbreaks. Since its arrival in North America in 1999, West Nile virus (WNV) has led to population-wide declines of bird species, morbidity and mortality of humans, and expenditures of millions of dollars on treatment and control. To understand the environmental conditions that best explain and predict WNV prevalence, we employed recently developed spatial modeling techniques in a recognized WNV hotspot, Orange County, California. Our models explained 85-95% of the variation of WNV prevalence in mosquito vectors, and WNV presence in secondary human hosts. Prevalence in both vectors and humans was best explained by economic variables, specifically per capita income, and by anthropogenic characteristics of the environment, particularly human population and neglected swimming pool density. While previous studies have shown associations between anthropogenic change and pathogen presence, results show that poorer economic conditions may act as a direct surrogate for environmental characteristics related to WNV prevalence. Low-income areas may be associated with higher prevalence for a number of reasons, including variations in property upkeep, microhabitat conditions conducive to viral amplification in both vectors and hosts, host community composition, and human behavioral responses related to differences in education or political participation. Results emphasize the importance and utility of including economic variables in mapping spatial risk assessments of disease. PMID:21103053

  2. 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.

  3. Economic Conditions Predict Prevalence of West Nile Virus

    PubMed Central

    Buermann, Wolfgang; Cummings, Robert F.; Kahn, Matthew E.; Smith, Thomas B.

    2010-01-01

    Understanding the conditions underlying the proliferation of infectious diseases is crucial for mitigating future outbreaks. Since its arrival in North America in 1999, West Nile virus (WNV) has led to population-wide declines of bird species, morbidity and mortality of humans, and expenditures of millions of dollars on treatment and control. To understand the environmental conditions that best explain and predict WNV prevalence, we employed recently developed spatial modeling techniques in a recognized WNV hotspot, Orange County, California. Our models explained 85–95% of the variation of WNV prevalence in mosquito vectors, and WNV presence in secondary human hosts. Prevalence in both vectors and humans was best explained by economic variables, specifically per capita income, and by anthropogenic characteristics of the environment, particularly human population and neglected swimming pool density. While previous studies have shown associations between anthropogenic change and pathogen presence, results show that poorer economic conditions may act as a direct surrogate for environmental characteristics related to WNV prevalence. Low-income areas may be associated with higher prevalence for a number of reasons, including variations in property upkeep, microhabitat conditions conducive to viral amplification in both vectors and hosts, host community composition, and human behavioral responses related to differences in education or political participation. Results emphasize the importance and utility of including economic variables in mapping spatial risk assessments of disease. PMID:21103053

  4. Reprint of: "Demographic factors predict magnitude of conditioned fear".

    PubMed

    Rosenbaum, Blake L; Bui, Eric; Marin, Marie-France; Holt, Daphne J; Lasko, Natasha B; Pitman, Roger K; Orr, Scott P; Milad, Mohammed R

    2015-12-01

    There is substantial variability across individuals in the magnitudes of their skin conductance (SC) responses during the acquisition and extinction of conditioned fear. To manage this variability, subjects may be matched for demographic variables, such as age, gender and education. However, limited data exist addressing how much variability in conditioned SC responses is actually explained by these variables. The present study assessed the influence of age, gender and education on the SC responses of 222 subjects who underwent the same differential conditioning paradigm. The demographic variables were found to predict a small but significant amount of variability in conditioned responding during fear acquisition, but not fear extinction learning or extinction recall. A larger differential change in SC during acquisition was associated with more education. Older participants and women showed smaller differential SC during acquisition. Our findings support the need to consider age, gender and education when studying fear acquisition but not necessarily when examining fear extinction learning and recall. Variability in demographic factors across studies may partially explain the difficulty in reproducing some SC findings. PMID:26608179

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

    NASA Astrophysics Data System (ADS)

    Tesoriero, A. J.; Terziotti, S.

    2014-12-01

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

  6. Classification of Initial conditions required for Substorm prediction.

    NASA Astrophysics Data System (ADS)

    Patra, S.; Spencer, E. A.

    2014-12-01

    We investigate different classes of substorms that occur as a result of various drivers such as the conditions in the solar wind and the internal state of the magnetosphere ionosphere system during the geomagnetic activity. In performing our study, we develop and use our low order physics based nonlinear model of the magnetosphere called WINDMI to establish the global energy exchange between the solar wind, magnetosphere and ionosphere by constraining the model results to satellite and ground measurements. On the other hand, we make quantitative and qualitative comparisons between our low order model with available MHD, multi-fluid and ring current simulations in terms of the energy transfer between the geomagnetic tail, plasma sheet, field aligned currents, ionospheric currents and ring current, during isolated substorms, storm time substorms, and sawtooth events. We use high resolution solar wind data from the ACE satellite, measurements from the CLUSTER and THEMIS missions satellites, and ground based magnetometer measurements from SUPERMAG and WDC Kyoto, to further develop our low order physics based model. Finally, we attempt to answer the following questions: 1) What conditions in the solar wind influence the type of substorm event. This includes the IMF strength and orientation, the particle densities, velocities and temperatures, and the timing of changes such as shocks, southward turnings or northward turnings of the IMF. 2) What is the state of the magnetosphere ionosphere system before an event begins. These are the steady state conditions prior to an event, if they exist, which produce the satellite and ground based measurements matched to the WINDMI model. 3) How does the prior state of the magnetosphere influence the transition into a particular mode of behavior under solar wind forcing. 4) Is it possible to classify the states of the magnetosphere into distinct categories depending on pre-conditioning, and solar wind forcing conditions? 5) Can we

  7. 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 %. PMID:25824122

  8. 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 %.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. Error estimation for CFD aeroheating prediction under rarefied flow condition

    NASA Astrophysics Data System (ADS)

    Jiang, Yazhong; Gao, Zhenxun; Jiang, Chongwen; Lee, Chunhian

    2014-12-01

    Both direct simulation Monte Carlo (DSMC) and Computational Fluid Dynamics (CFD) methods have become widely used for aerodynamic prediction when reentry vehicles experience different flow regimes during flight. The implementation of slip boundary conditions in the traditional CFD method under Navier-Stokes-Fourier (NSF) framework can extend the validity of this approach further into transitional regime, with the benefit that much less computational cost is demanded compared to DSMC simulation. Correspondingly, an increasing error arises in aeroheating calculation as the flow becomes more rarefied. To estimate the relative error of heat flux when applying this method for a rarefied flow in transitional regime, theoretical derivation is conducted and a dimensionless parameter ɛ is proposed by approximately analyzing the ratio of the second order term to first order term in the heat flux expression in Burnett equation. DSMC simulation for hypersonic flow over a cylinder in transitional regime is performed to test the performance of parameter ɛ, compared with two other parameters, Knρ and MaṡKnρ.

  14. 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

  15. 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

  16. Ensemble Prediction of Flood Maps Under Uncertain Conditions

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  17. 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

  18. Eyeblink conditioning during an inter-stimulus interval switch in rabbits using picrotoxin to disrupt cerebellar cortical input to the interpositus nucleus

    PubMed Central

    Vogel, Richard W.; Amundson, Jeffrey C.; Lindquist, Derick H.; Steinmetz, Joseph E.

    2008-01-01

    The role of the cerebellar cortex in eyeblink classical conditioning remains unclear. Experimental manipulations that disrupt the normal function of this region impair learning to various degrees and task parameters may be important factors in determining the severity of impairment. The present investigation was undertaken to study the role of cerebellar cortex in eyeblink conditioning under CS-US intervals known to be optimal or non-optimal for learning. Using discrete infusions of picrotoxin to the interpositus nucleus of the rabbit cerebellum, we pharmacologically disrupted input from the cerebellar cortex while training with an inter-stimulus interval (ISI) switch procedure. One group of rabbits was first trained with a 250 ms ISI (optimal) and then switched to a 750 ms ISI (non-optimal). A second group was trained in the opposite order. As expected, control rabbits learned the 250 ms ISI much faster than the 750 ms ISI. The most striking effect was that picrotoxin-treated rabbits initially trained with a 250 ms ISI learned comparably to controls, but those initially trained with a 750 ms ISI were severely impaired. These results suggest that functional input from cerebellar cortex becomes increasingly important for the interpositus nucleus to learn delay eyeblink conditioning as the ISI departs from an optimal interval of 250 ms. PMID:19170431

  19. Interval Training.

    ERIC Educational Resources Information Center

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

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

  20. Prediction of the distillation temperatures of crude oils using ¹H NMR and support vector regression with estimated confidence intervals.

    PubMed

    Filgueiras, Paulo R; Terra, Luciana A; Castro, Eustáquio V R; Oliveira, Lize M S L; Dias, Júlio C M; Poppi, Ronei J

    2015-09-01

    This paper aims to estimate the temperature equivalent to 10% (T10%), 50% (T50%) and 90% (T90%) of distilled volume in crude oils using (1)H NMR and support vector regression (SVR). Confidence intervals for the predicted values were calculated using a boosting-type ensemble method in a procedure called ensemble support vector regression (eSVR). The estimated confidence intervals obtained by eSVR were compared with previously accepted calculations from partial least squares (PLS) models and a boosting-type ensemble applied in the PLS method (ePLS). By using the proposed boosting strategy, it was possible to identify outliers in the T10% property dataset. The eSVR procedure improved the accuracy of the distillation temperature predictions in relation to standard PLS, ePLS and SVR. For T10%, a root mean square error of prediction (RMSEP) of 11.6°C was obtained in comparison with 15.6°C for PLS, 15.1°C for ePLS and 28.4°C for SVR. The RMSEPs for T50% were 24.2°C, 23.4°C, 22.8°C and 14.4°C for PLS, ePLS, SVR and eSVR, respectively. For T90%, the values of RMSEP were 39.0°C, 39.9°C and 39.9°C for PLS, ePLS, SVR and eSVR, respectively. The confidence intervals calculated by the proposed boosting methodology presented acceptable values for the three properties analyzed; however, they were lower than those calculated by the standard methodology for PLS. PMID:26003712

  1. Body condition predicts energy stores in apex predatory sharks.

    PubMed

    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

  2. Deciphering and prediction of plant dynamics under field conditions.

    PubMed

    Izawa, Takeshi

    2015-04-01

    Elucidation of plant dynamics under fluctuating natural environments is a challenging goal in plant physiology. Recently, using a computer statistics integrating a series of transcriptome data of field-grown rice leaves during an entire crop season and several corresponding environmental data such as solar radiation and ambient temperature, most parts of transcriptome have been modeled. This reveals the detailed contributions of developmental timing, circadian clocks and each environmental factor to transcriptome dynamics in the field and can predict transcriptome dynamics under given environments. Furthermore, some traits such as flowering time in natural environments have been shown to be predicted by mathematical models based on gene-networks parameterized with data obtained in the laboratory, and phenology models refined by knowledge of molecular genetics. New molecular physiology is beginning in plant science. PMID:25706440

  3. Predictive value of ventilatory inflection points determined under field conditions.

    PubMed

    Heyde, Christian; Mahler, Hubert; Roecker, Kai; Gollhofer, Albert

    2016-05-01

    The aim of this study was to evaluate the predictive potential provided by two ventilatory inflection points (VIP1 and VIP2) examined in field without using gas analysis systems and uncomfortable facemasks. A calibrated respiratory inductance plethysmograph (RIP) and a computerised routine were utilised, respectively, to derive ventilation and to detect VIP1 and VIP2 during a standardised field ramp test on a 400 m running track on 81 participants. In addition, average running speed of a competitive 1000 m run (S1k) was observed as criterion. The predictive value of running speed at VIP1 (SVIP1) and the speed range between VIP1 and VIP2 in relation to VIP2 (VIPSPAN) was analysed via regression analysis. VIPSPAN rather than running speed at VIP2 (SVIP2) was operationalised as a predictor to consider the covariance between SVIP1 and SVIP2. SVIP1 and VIPSPAN, respectively, provided 58.9% and 22.9% of explained variance in regard to S1k. Considering covariance, the timing of two ventilatory inflection points provides predictive value in regard to a competitive 1000 m run. This is the first study to apply computerised detection of ventilatory inflection points in a field setting independent on measurements of the respiratory gas exchange and without using any facemasks. PMID:26190229

  4. Noise Prediction of NASA SR2 Propeller in Transonic Conditions

    NASA Astrophysics Data System (ADS)

    Gennaro, Michele De; Caridi, Domenico; Nicola, Carlo De

    2010-09-01

    In this paper we propose a numerical approach for noise prediction of high-speed propellers for Turboprop applications. It is based on a RANS approach for aerodynamic simulation coupled with Ffowcs Williams-Hawkings (FW-H) Acoustic Analogy for propeller noise prediction. The test-case geometry adopted for this study is the 8-bladed NASA SR2 transonic cruise propeller, and simulated Sound Pressure Levels (SPL) have been compared with experimental data available from Wind Tunnel and Flight Tests for different microphone locations in a range of Mach numbers between 0.78 and 0.85 and rotational velocities between 7000 and 9000 rpm. Results show the ability of this approach to predict noise to within a few dB of experimental data. Moreover corrections are provided to be applied to acoustic numerical results in order for them to be compared with Wind Tunnel and Flight Test experimental data, as well computational grid requirements and guidelines in order to perform complete aerodynamic and aeroacoustic calculations with highly competitive computational cost.

  5. 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...

  6. 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.

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

    PubMed

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

    2015-08-18

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

  8. 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.

  9. 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

  10. The cystatin C/creatinine ratio, a marker of glomerular filtration quality: associated factors, reference intervals, and prediction of morbidity and mortality in healthy seniors.

    PubMed

    Purde, Mette-Triin; Nock, Stefan; Risch, Lorenz; Medina Escobar, Pedro; Grebhardt, Chris; Nydegger, Urs E; Stanga, Zeno; Risch, Martin

    2016-03-01

    The ratio of cystatin C (cysC) to creatinine (crea) is regarded as a marker of glomerular filtration quality associated with cardiovascular morbidities. We sought to determine reference intervals for serum cysC-crea ratio in seniors. Furthermore, we sought to determine whether other low-molecular weight molecules exhibit a similar behavior in individuals with altered glomerular filtration quality. Finally, we investigated associations with adverse outcomes. A total of 1382 subjectively healthy Swiss volunteers aged 60 years or older were enrolled in the study. Reference intervals were calculated according to Clinical & Laboratory Standards Institute (CLSI) guideline EP28-A3c. After a baseline exam, a 4-year follow-up survey recorded information about overall morbidity and mortality. The cysC-crea ratio (mean 0.0124 ± 0.0026 mg/μmol) was significantly higher in women and increased progressively with age. Other associated factors were hemoglobin A1c, mean arterial pressure, and C-reactive protein (P < 0.05 for all). Participants exhibiting shrunken pore syndrome had significantly higher ratios of 3.5-66.5 kDa molecules (brain natriuretic peptide, parathyroid hormone, β2-microglobulin, cystatin C, retinol-binding protein, thyroid-stimulating hormone, α1-acid glycoprotein, lipase, amylase, prealbumin, and albumin) and creatinine. There was no such difference in the ratios of very low-molecular weight molecules (urea, uric acid) to creatinine or in the ratios of molecules larger than 66.5 kDa (transferrin, haptoglobin) to creatinine. The cysC-crea ratio was significantly predictive of mortality and subjective overall morbidity at follow-up in logistic regression models adjusting for several factors. The cysC-crea ratio exhibits age- and sex-specific reference intervals in seniors. In conclusion, the cysC-crea ratio may indicate the relative retention of biologically active low-molecular weight compounds and can independently predict the risk for overall

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

    SciTech Connect

    Diamond, P.

    1988-04-01

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

  12. Suspended-sediment transport rates at the 1.5-year recurrence interval for ecoregions of the United States: transport conditions at the bankfull and effective discharge?

    NASA Astrophysics Data System (ADS)

    Simon, Andrew; Dickerson, Wendy; Heins, Amanda

    2004-03-01

    Historical flow and suspended-sediment transport data from more than 2900 sites across the United States have been analyzed in the context of estimating flow and suspended-sediment transport conditions at the 1.5-year recurrence interval flow ( Q1.5). This is particularly relevant with the renewed focus on stream restoration activities and the urgency in developing water-quality criteria for sediment. Data were sorted into the 84 Level III ecoregions to identify spatial trends in suspended-sediment concentrations and yields to meaningfully describe suspended-sediment transport rates across the United States. Arguments are developed that in lieu of form-based estimates of say the bankfull level, a flow of a given recurrence interval ( Q1.5) is more appropriate to integrate suspended-sediment transport ratings for the purpose of defining long-term transport conditions at a site (the "effective discharge"). The use of the Q1.5 as a measure of the effective discharge for suspended-sediment transport is justified on the basis of literature reports and analytic results from hundreds of sites in 17 ecoregions that span a diverse range of hydrologic and topographic conditions (i.e., Coast Range, Arizona/New Mexico Plateau, Mississippi Valley Loess Plains, Middle Atlantic Coastal Plain). There is sufficient data to also develop regional curves for the Q1.5 in all but eight of the ecoregions. At the Q1.5 the highest median suspended-sediment concentrations occur in semiarid environments (Southwest Tablelands, Arizona/New Mexico Plateau and the Mojave Basin and Range); the highest yields occur in humid regions with erodible soils and steep slopes or channel gradients (Mississippi Valley Loess Plains [MVLP] and the Coast Range). Suspended-sediment yields for stable streams are used to determine "background" or "reference" sediment transport conditions in eight ecoregions where there is sufficient field data. The median value for stable sites within a given ecoregion are

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

    PubMed

    Jović, Ozren; Smrečki, Neven; Popović, Zora

    2016-04-01

    A novel quantitative prediction and variable selection method called interval ridge regression (iRR) is studied in this work. The method is performed on six data sets of FTIR, two data sets of UV-vis and one data set of DSC. The obtained results show that models built with ridge regression on optimal variables selected with iRR significantly outperfom models built with ridge regression on all variables in both calibration (6 out of 9 cases) and validation (2 out of 9 cases). In this study, iRR is also compared with interval partial least squares regression (iPLS). iRR outperfomed iPLS in validation (insignificantly in 6 out of 9 cases and significantly in one out of 9 cases for p<0.05). Also, iRR can be a fast alternative to iPLS, especially in case of unknown degree of complexity of analyzed system, i.e. if upper limit of number of latent variables is not easily estimated for iPLS. Adulteration of hempseed (H) oil, a well known health beneficial nutrient, is studied in this work by mixing it with cheap and widely used oils such as soybean (So) oil, rapeseed (R) oil and sunflower (Su) oil. Binary mixture sets of hempseed oil with these three oils (HSo, HR and HSu) and a ternary mixture set of H oil, R oil and Su oil (HRSu) were considered. The obtained accuracy indicates that using iRR on FTIR and UV-vis data, each particular oil can be very successfully quantified (in all 8 cases RMSEP<1.2%). This means that FTIR-ATR coupled with iRR can very rapidly and effectively determine the level of adulteration in the adulterated hempseed oil (R(2)>0.99). PMID:26838379

  14. 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

  15. 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

  16. 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

  17. Practical use of a uterine score system for predicting effects on interval from calving to first insemination and non-return rate 56 in Danish dairy herds.

    PubMed

    Elkjær, Karina; Labouriau, Rodrigo; Ancker, Marie-Louise; Gustafsson, Hans; Callesen, Henrik

    2013-12-01

    A detailed study of 398,237 lactations of Danish Holstein dairy cows was undertaken. The objective was to investigate the information gained by evaluating vaginal discharge in cows from 5 to 19 days post-partum (p.p.) using an ordinal scale from 0 to 9. The study focused on the interval from calving to first insemination (CFI) and the non-return rate 56 days after first insemination (NR56), adjusted for the confounders milk production and body condition score (BCS). For the analyses, BCS was evaluated on the same day that the uterine score was made. Milk production was defined as test-day milk yield in the first month p.p. The study showed that the evaluation of vaginal discharge according to this score system permitted ranking of cows according to CFI and NR56, i.e. an increasing uterine score was associated with a significantly longer time from calving to first insemination and significantly reduced the probability of success of the first insemination. Reproductive success was already affected if the uterine score had reached 4 (i.e. before the discharge smelled abnormally). The negative effect on CFI and NR56 increased as the uterine score increased, which suggested that the uterine scoring system was a useful guide to dairy producers. PMID:24144773

  18. Decreases in Electrocardiographic R-Wave Amplitude and QT Interval Predict Myocardial Ischemic Infarction in Rhesus Monkeys with Left Anterior Descending Artery Ligation

    PubMed Central

    Han, Pengfei; Xie, Yuping; Chen, Jianmin; Xiao, Ying; Kang, Y. James

    2013-01-01

    Clinical studies have demonstrated the predictive values of changes in electrocardiographic (ECG) parameters for the preexisting myocardial ischemic infarction. However, a simple and early predictor for the subsequent development of myocardial infarction during the ischemic phase is of significant value for the identification of ischemic patients at high risk. The present study was undertaken by using non-human primate model of myocardial ischemic infarction to fulfill this gap. Twenty male Rhesus monkeys at age of 2–3 years old were subjected to left anterior descending artery ligation. This ligation was performed at varying position along the artery so that it produced varying sizes of myocardial infarction at the late stage. The ECG recording was undertaken before the surgical procedure, at 2 h after the ligation, and 8 weeks after the surgery for each animal. The correlation of the changes in the ECG waves in the early or the late stage with the myocardial infarction size was analyzed. The R wave depression and the QT shortening in the early ischemic stage were found to have an inverse correlation with the myocardial infarction size. At the late stage, the R wave depression, the QT prolongation, the QRS score, and the ST segment elevation were all closely correlated with the developed infarction size. The poor R wave progression was identified at both the early ischemic and the late infarction stages. Therefore, the present study using non-human primate model of myocardial ischemic infarction identified the decreases in the R wave and the QT interval as early predictors of myocardial infarction. Validation of these parameters in clinical studies would greatly help identifying patients with myocardial ischemia at high risk for the subsequent development of myocardial infarction. PMID:23967258

  19. 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.

  20. 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.

  1. Prediction of heat-illness symptoms with the prediction of human vascular response in hot environment under resting condition.

    PubMed

    Aggarwal, Yogender; Karan, Bhuwan Mohan; Das, Barsa Nand; Sinha, Rakesh Kumar

    2008-04-01

    The thermoregulatory control of human skin blood flow is vital to maintain the body heat storage during challenges of thermal homeostasis under heat stress. Whenever thermal homeostasis disturbed, the heat load exceeds heat dissipation capacity, which alters the cutaneous vascular responses along with other body physiological variables. Whole body skin blood flow has been calculated from the forearm blood flow. Present model has been designed using electronics circuit simulator (Multisim 8.0, National Instruments, USA), is to execute a series of predictive equations for early prediction of physiological parameters of young nude subjects during resting condition at various level of dry heat stress under almost still air to avoid causalities associated with hot environmental. The users can execute the model by changing the environmental temperature in degrees C and exposure time in minutes. The model would be able to predict and detect the changes in human vascular responses along with other physiological parameters and from this predicted values heat related-illness symptoms can be inferred. PMID:18461820

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

    PubMed Central

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

    2014-01-01

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

  3. 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.

  4. On boundary conditions for the diffusion equation in room-acoustic prediction: Theory, simulations, and experiments.

    PubMed

    Jing, Yun; Xiang, Ning

    2008-01-01

    This paper proposes a modified boundary condition to improve the room-acoustic prediction accuracy of a diffusion equation model. Previous boundary conditions for the diffusion equation model have certain limitations which restrict its application to a certain number of room types. The boundary condition employing the Sabine absorption coefficient [V. Valeau et al., J. Acoust. Soc. Am. 119, 1504-1513 (2006)] cannot predict the sound field well when the absorption coefficient is high, while the boundary condition employing the Eyring absorption coefficient [Y. Jing and N. Xiang, J. Acoust. Soc. Am. 121, 3284-3287 (2007); A. Billon et al., Appl. Acoust. 69, (2008)] has a singularity whenever any surface material has an absorption coefficient of 1.0. The modified boundary condition is derived based on an analogy between sound propagation and light propagation. Simulated and experimental data are compared to verify the modified boundary condition in terms of room-acoustic parameter prediction. The results of this comparison suggest that the modified boundary condition is valid for a range of absorption coefficient values and successfully eliminates the singularity problem. PMID:18177146

  5. 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

  6. 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.

  7. Spatiotemporal activity patterns of rat cortical neurons predict responses in a conditioned task

    PubMed Central

    Villa, Alessandro E. P.; Tetko, Igor V.; Hyland, Brian; Najem, Abdellatif

    1999-01-01

    Precise and repeated spike-train timings within and across neurons define spatiotemporal patterns of activity. Although the existence of these patterns in the brain is well established in several species, there has been no direct evidence of their influence on behavioral output. To address this question, up to 15 neurons were recorded simultaneously in the auditory cortex of freely moving rats while animals waited for acoustic cues in a Go/NoGo task. A total of 235 significant patterns were detected during this interval from an analysis of 13 hr of recording involving over 1 million spikes. Of particular interest were 129 (55%) patterns that were significantly associated with the type of response the animal made later, independent of whether the response was that prompted by the cue because the response occurred later and the cue was chosen randomly. Of these behavior-predicting patterns, half (59/129) were associated with an enhanced tendency to go in response to the stimulus, and for 11 patterns of this subset, trials including the pattern were followed by significantly faster reaction time than those lacking the pattern. The remaining behavior-predicting patterns were associated with an enhanced NoGo tendency. Overall mean discharge rates did not vary across trials. Hence, these data demonstrate that particular spatiotemporal patterns predict future behavioral responses. Such presignal activity could form templates for extracting specific sensory information, motor programs prespecifying preference for a particular act, and/or some intermediate, associative brain process. PMID:9927701

  8. UREA SPACE AND BODY CONDITION SCORE TO PREDICT BODY COMPOSITION OF MEAT GOATS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Yearling Boer x Spanish wethers (n=40) were used to develop and compare body composition prediction equations for mature meat goats based on urea space (US) and body condition score (BCS). Before the experiment, one-half of the animals were managed to have high BW and BCS (1-5, with 1 being extreme...

  9. 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…

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  11. Evidence that conditioned avoidance responses are reinforced by positive prediction errors signaled by tonic striatal dopamine.

    PubMed

    Dombrowski, Patricia A; Maia, Tiago V; Boschen, Suelen L; Bortolanza, Mariza; Wendler, Etieli; Schwarting, Rainer K W; Brandão, Marcus Lira; Winn, Philip; Blaha, Charles D; Da Cunha, Claudio

    2013-03-15

    We conducted an experiment in which hedonia, salience and prediction error hypotheses predicted different patterns of dopamine (DA) release in the striatum during learning of conditioned avoidance responses (CARs). The data strongly favor the latter hypothesis. It predicts that during learning of the 2-way active avoidance CAR task, positive prediction errors generated when rats do not receive an anticipated footshock (which is better than expected) cause DA release that reinforces the instrumental avoidance action. In vivo microdialysis in the rat striatum showed that extracellular DA concentration increased during early CAR learning and decreased throughout training returning to baseline once the response was well learned. In addition, avoidance learning was proportional to the degree of DA release. Critically, exposure of rats to the same stimuli but in an unpredictable, unavoidable, and inescapable manner, did not produce alterations from baseline DA levels as predicted by the prediction error but not hedonic or salience hypotheses. In addition, rats with a partial lesion of substantia nigra DA neurons, which did not show increased DA levels during learning, failed to learn this task. These data represent clear and unambiguous evidence that it was the factor positive prediction error, and not hedonia or salience, which caused increase in the tonic level of striatal DA and which reinforced learning of the instrumental avoidance response. PMID:22771418

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

    SciTech Connect

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

    1997-12-01

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

  13. 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.

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

    PubMed Central

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

    2009-01-01

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

  15. Predictions for the Higgs Mass from the Stability and Triviality Conditions

    SciTech Connect

    Solis R, H. Gabriel; Juarez W, S. Rebeca; Kielanowski, P.

    2006-09-25

    In the context of the Standard Model (SM), we use the one-loop and two-loop Renormalization Group Equations (RGE) in order to analyze the evolution of the Higgs quartic coupling {lambda}H in the interval [mt, EGU], where mt is the mass of the top quark and EGU = 1014GeV. The analytical solution for the one-loop differential equation (Riccati type) is obtained and analyzed and in the two-loop case we obtain a numerical solution which takes into account all the parameters (couplings) at the same order of approximation. In both cases, we restrict the possible initial values for {lambda}H by means of imposing the triviality and stability conditions which determine the range of energies where the SM is valid. We obtain the following bounds: 0.387 < {lambda}H < 0.623 for the one-loop case and 0.360 < {lambda}H < 0.628 for the two-loop case. These results determine the interval of the possible Higgs mass values: 151.9 < MH < 192.3 GeV, 143.8 < MH < 190.3 GeV for the one-loop and two-loop cases, respectively.

  16. 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.

  17. 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.

  18. 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. PMID:26581864

  19. 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.

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

    PubMed

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

    2007-01-01

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

  1. Prediction of physical properties of water under extremely supercritical conditions: a molecular dynamics study.

    PubMed

    Sakuma, Hiroshi; Ichiki, Masahiro; Kawamura, Katsuyuki; Fuji-ta, Kiyoshi

    2013-04-01

    The physical properties of water under a wide range of pressure and temperature conditions are important in fundamental physics, chemistry, and geoscience. Molecular simulations are useful for predicting and understanding the physical properties of water at phases extremely different from ambient conditions. In this study, we developed a new five-site flexible induced point charge model to predict the density, static dielectric constant, and transport properties of water in the extremely supercritical phase at high temperatures and pressures of up to 2000 K and 2000 MPa. The model satisfactorily reproduced the density, radial distribution function, static dielectric constant, reorientation time, and self-diffusion coefficients of water above the critical points. We also developed a database of the static dielectric constant, which is useful for discussing the electrical conductivity of aqueous fluids in the earth's crust and mantle. PMID:23574243

  2. 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.

  3. Ongoing development of a computer jobstream to predict helicopter main rotor performance in icing conditions

    NASA Technical Reports Server (NTRS)

    Britton, Randall K.

    1991-01-01

    Work is currently underway at the NASA Lewis Research Center to develop an analytical method for predicting the performance degradation of a helicopter operating in icing conditions. A brief survey is performed of possibilities available to perform such a calculation along with the reasons for choosing the present approach. A complete description of the proposed jobstream is given as well as a discussion of the present state of the development.

  4. 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.

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

    PubMed

    Farnham, David J; Lall, Upmanu

    2015-06-01

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

  6. A symbiont's dispersal strategy: condition-dependent dispersal underlies predictable variation in direct transmission among hosts.

    PubMed

    Skelton, James; Creed, Robert P; Brown, Bryan L

    2015-11-22

    Direct horizontal transmission of pathogenic and mutualistic symbionts has profound consequences for host and symbiont fitness alike. While the importance of contact rates for transmission is widely recognized, the processes that underlie variation in transmission during contact are rarely considered. Here, we took a symbiont's perspective of transmission as a form of dispersal and adopted the concept of condition-dependent dispersal strategies from the study of free-living organisms to understand and predict variation in transmission in the cleaning symbiosis between crayfish and ectosymbiotic branchiobdellidan worms. Field study showed that symbiont reproductive success was correlated with host size and competition among worms for microhabitats. Laboratory experiments demonstrated high variability in transmission among host contacts. Moreover, symbionts were more likely to disperse when host size and competition for microhabitat created a fitness environment below a discrete minimum threshold. A predictive model based on a condition-dependent symbiont dispersal strategy correctly predicted transmission in 95% of experimental host encounters and the exact magnitude of transmission in 67%, both significantly better than predictions that assumed a fixed transmission rate. Our work provides a dispersal-based understanding of symbiont transmission and suggests adaptive symbiont dispersal strategies can explain variation in transmission dynamics and complex patterns of host infection. PMID:26559953

  7. 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.

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Guan, Yujuan; Zhang, Liquan

    2006-10-01

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

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

    SciTech Connect

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

    1995-12-31

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

  13. Toward a reliable decomposition of predictive uncertainty in hydrological modeling: Characterizing rainfall errors using conditional simulation

    NASA Astrophysics Data System (ADS)

    Renard, Benjamin; Kavetski, Dmitri; Leblois, Etienne; Thyer, Mark; Kuczera, George; Franks, Stewart W.

    2011-11-01

    This study explores the decomposition of predictive uncertainty in hydrological modeling into its contributing sources. This is pursued by developing data-based probability models describing uncertainties in rainfall and runoff data and incorporating them into the Bayesian total error analysis methodology (BATEA). A case study based on the Yzeron catchment (France) and the conceptual rainfall-runoff model GR4J is presented. It exploits a calibration period where dense rain gauge data are available to characterize the uncertainty in the catchment average rainfall using geostatistical conditional simulation. The inclusion of information about rainfall and runoff data uncertainties overcomes ill-posedness problems and enables simultaneous estimation of forcing and structural errors as part of the Bayesian inference. This yields more reliable predictions than approaches that ignore or lump different sources of uncertainty in a simplistic way (e.g., standard least squares). It is shown that independently derived data quality estimates are needed to decompose the total uncertainty in the runoff predictions into the individual contributions of rainfall, runoff, and structural errors. In this case study, the total predictive uncertainty appears dominated by structural errors. Although further research is needed to interpret and verify this decomposition, it can provide strategic guidance for investments in environmental data collection and/or modeling improvement. More generally, this study demonstrates the power of the Bayesian paradigm to improve the reliability of environmental modeling using independent estimates of sampling and instrumental data uncertainties.

  14. Theoretical prediction of lung nodule measurement accuracy under different acquisition and reconstruction conditions

    NASA Astrophysics Data System (ADS)

    Hsieh, Jiang; Karau, Kelly

    2004-04-01

    Utilization of computed tomography (CT) for lung cancer screening has attracted significant research interests in recent years. Images reconstructed from CT studies are used for lung nodule characterization and three-dimensional lung lesion sizing. Methodologies have been developed to automatically identify and characterize lung nodules. In this paper, we analyze the impact of acquisition and reconstruction parameters on the accuracy of quantitative lung nodule characterization. The two major data acquisition parameters that impact the accuracy of the lung nodule measurement are acquisition mode and slice aperture. Acquisition mode includes both axial and helical scans. The investigated reconstruction parameters are the reconstruction filters and field-of-view. We first develop theoretical models that predict the system response under various acquisition and reconstruction conditions. These models allow clinicians to compare results under different conditions and make appropriate acquisition and reconstruction decisions. To validate our model, extensive phantom experiments are conducted. Experiments have demonstrated that our analytical models accurately predict the performance parameters under various conditions. Our study indicates that acquisition and reconstruction parameters can significantly impact the accuracy of the nodule volume measurement. Consequently, when conducting quantitative analysis on lung nodules, especially in sequential growth studies, it is important to make appropriate adjustment and correction to maintain the desired accuracy and to ensure effective patient management.

  15. 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.

  16. 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

  17. The neural correlates of negative prediction error signaling in human fear conditioning.

    PubMed

    Spoormaker, V I; Andrade, K C; Schröter, M S; Sturm, A; Goya-Maldonado, R; Sämann, P G; Czisch, M

    2011-02-01

    In a temporal difference (TD) learning approach to classical conditioning, a prediction error (PE) signal shifts from outcome deliverance to the onset of the conditioned stimulus. Omission of an expected outcome results in a negative PE signal, which is the initial step towards successful extinction. In order to visualize negative PE signaling during fear conditioning, we employed combined functional magnetic resonance (fMRI) and skin conductance response (SCR) measurements in a conditioning task with visual stimuli and mild electrical shocks. Positive PE signaling was associated with increased activation in the bilateral insula, supplementary motor area, brainstem, and visual cortices. Negative PE signaling was associated with increased activation in the ventromedial and dorsolateral prefrontal cortices, the left lateral orbital gyrus, the middle temporal gyri, angular gyri, and visual cortices. The involvement of the ventromedial prefrontal and orbitofrontal cortex in extinction learning has been well documented, and this study provides evidence for the notion that these regions are already involved in negative PE signaling during fear conditioning. PMID:20869454

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

    PubMed

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

    2016-03-01

    Through Pavlovian conditioning, reward-associated neutral stimuli can acquire incentive salience and motivate complex behaviors. In smokers, cigarette-associated cues may induce cravings and trigger smoking. Understanding the brain mechanisms underlying conditioned responses to cigarette-associated relative to other inherently pleasant stimuli might contribute to the development of more effective smoking cessation treatments that emphasize the rehabilitation of reward circuitry. Here we measured brain responses to geometric patterns (the conditioned stimuli, CSs) predicting cigarette-related, intrinsically pleasant and neutral images (the unconditioned stimuli, USs) using event-related potentials (ERPs) in 29 never-smokers, 20 nicotine-deprived smokers, and 19 non-deprived smokers. Results showed that during US presentation, cigarette-related and pleasant images prompted higher cortical positivity than neutral images over centro-parietal sensors between 400 and 800ms post-US onset (late positive potential, LPP). The LPP evoked by pleasant images was significantly larger than the LPP evoked by cigarette images. During CS presentation, ERPs evoked by geometric patterns predicting pleasant and cigarette-related images had significantly larger amplitude than ERPs evoked by CSs predicting neutral images. These effects were maximal over right parietal sites between 220 and 240ms post-CS onset and over occipital and frontal sites between 308 and 344ms post-CS onset. Smoking status did not modulate these effects. Our results show that stimuli with no intrinsic reward value (e.g., geometric patterns) may acquire rewarding properties through repeated pairings with established reward cues (i.e., cigarette-related, intrinsically pleasant). PMID:26826400

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

    PubMed Central

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

    2010-01-01

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

  20. 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.

  1. 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

  2. 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

  3. Experimenting with musical intervals

    NASA Astrophysics Data System (ADS)

    Lo Presto, Michael C.

    2003-07-01

    When two tuning forks of different frequency are sounded simultaneously the result is a complex wave with a repetition frequency that is the fundamental of the harmonic series to which both frequencies belong. The ear perceives this 'musical interval' as a single musical pitch with a sound quality produced by the harmonic spectrum responsible for the waveform. This waveform can be captured and displayed with data collection hardware and software. The fundamental frequency can then be calculated and compared with what would be expected from the frequencies of the tuning forks. Also, graphing software can be used to determine equations for the waveforms and predict their shapes. This experiment could be used in an introductory physics or musical acoustics course as a practical lesson in superposition of waves, basic Fourier series and the relationship between some of the ear's subjective perceptions of sound and the physical properties of the waves that cause them.

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

    NASA Astrophysics Data System (ADS)

    Kanguzhin, Baltabek; Tokmagambetov, Niyaz

    2016-08-01

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

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

    SciTech Connect

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

    1984-01-01

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

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

    PubMed

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

    2015-12-01

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

  7. 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.

  8. 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.

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

    PubMed

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

    2016-06-01

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

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

    EPA Science Inventory

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

  11. Toxicokinetics of perfluorooctane sulfonate in birds under environmentally realistic exposure conditions and development of a kinetic predictive model.

    PubMed

    Tarazona, J V; Rodríguez, C; Alonso, E; Sáez, M; González, F; San Andrés, M D; Jiménez, B; San Andrés, M I

    2015-01-22

    This article describes the toxicokinetics of perfluorooctane sulfonate (PFOS) in birds under low repeated dosing, equivalent to 0.085 μg/kg per day, representing environmentally realistic exposure conditions. The best fitting was provided by a simple pseudo monocompartmental first-order kinetics model, regulated by two rates, with a pseudo first-order dissipation half-life of 230 days, accounting for real elimination as well as binding of PFOS to non-exchangeable structures. The calculated assimilation efficiency was 0.66 with confidence intervals of 0.64 and 0.68. The model calculations confirmed that the measured maximum concentrations were still far from the steady state situation, which for this dose regime, was estimated at a value of about 65 μg PFOS/L serum achieved after a theoretical 210 weeks continuous exposure. The results confirm a very different kinetics than that observed in single-dose experiments confirming clear dose-related differences in apparent elimination rates in birds, as described for humans and monkeys; suggesting that a capacity-limited saturable process should also be considered in the kinetic behavior of PFOS in birds. Pseudo first-order kinetic models are highly convenient and frequently used for predicting bioaccumulation of chemicals in livestock and wildlife; the study suggests that previous bioaccumulation models using half-lives obtained at high doses are expected to underestimate the biomagnification potential of PFOS. The toxicokinetic parameters presented here can be used for higher-tier bioaccumulation estimations of PFOS in chickens and as surrogate values for modeling PFOS kinetics in wild bird species. PMID:25445721

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

    PubMed Central

    Kim, Minseung; Zorraquino, Violeta; Tagkopoulos, Ilias

    2015-01-01

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

  13. 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

  14. 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.

  15. Development of an analytical method to predict helicopter main rotor performance in icing conditions

    NASA Technical Reports Server (NTRS)

    Britton, Randall K.

    1992-01-01

    Historically, certification of a helicopter for flight into known icing conditions was a problem. This is because of the current emphasis on flight testing for verification of system performance. Flight testing in icing conditions is difficult because, in addition to being dangerous and expensive, many times conditions which are sought after cannot be readily found in nature. The problem is compounded for helicopters because of their small range in comparison to many fixed wing aircraft. Thus, helicopters are forced to wait for conditions to occur in a certain region rather than seeking them out. These and other drawbacks to flight testing prompted extreme interest in developing validated alternatives to flight testing. One such alternative is theoretical prediction. It is desirable to have the ability to predict how a helicopter will perform when subjected to icing conditions. Herein, calculations are restricted to the main rotor, and are illustrated. The computational tool used to obtain performance is the lifting line analysis of B65. B65 incorporates experimental data into data banks in order to determine the section lift, drag, and moment characteristics of various airfoils at different Mach numbers and angles of attack. The local flow angle is calculated at user specified radial locations. This flow angle, along with the local Mach number is then cross referenced with the airfoil tables to obtain the local section characteristics. The local characteristics are then integrated together to obtain the entire rotor attributes. Once the clean performance is known, characterization of the type and shape of ice which accretes on the rotor blades is obtained using the analysis of LEWICE. The Interactive Boundary Layer (IBL) method then calculates the 2-D characteristics of the iced airfoil for input into the airfoil data bank of B65. Calculations are restricted to natural ice shedding and it is assumed that no de-icing takes place. Once the new lift, drag, and moment

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. In Patients Experiencing Biochemical Failure After Radiotherapy, Pretreatment Risk Group and PSA Velocity Predict Differences in Overall Survival and Biochemical Failure-Free Interval

    SciTech Connect

    Soto, Daniel E. Andridge, Rebecca R.; Pan, Charlie C.; Williams, Scott G.; Taylor, Jeremy M.G.; Sandler, Howard M.

    2008-08-01

    Purpose: To characterize the demographics and survival outcomes of localized prostate cancer patients who developed biochemical failure (BF) according to a prostate-specific antigen (PSA) nadir plus 2 ng/mL. Methods and Materials: We identified 375 prostate cancer patients who had undergone external beam radiotherapy without androgen deprivation therapy but with sufficient PSA data to study PSA kinetics. Of these patients, we identified 82 with BF. The pretreatment PSA velocity was calculated for each patient. Results: For the BF cohort, 26% were low-risk and 74% were intermediate- or high-risk patients. Of the 82 BF patients, 16 (20%) were noted to have both low-risk disease and a pretreatment low PSA velocity of {<=}2 ng/mL/y (termed 'low-risk low-velocity' [LRLV]). The remaining BF patients had either intermediate- or high-risk features or a high PSA velocity >2 ng/mL/y (termed 'higher risk' [HR]). For patients who had BF, the LRLV group had a delayed median time to BF of 55 months compared with 33 months for the HR patients (p = 0.04). With a median clinical follow-up of 112 months, the 5-year overall survival rate was 100% for the LRLV BF patients vs. 84% for the HR patients (p = 0.02). Conclusions: We observed that LRLV BF patients represent a sizeable proportion of all patients with treatment failure. However, when comparing LRLV BF with HR BF patients, the former had significantly better overall survival and a longer interval to BF. This suggests that not all BF events are equivalent and emphasizes the challenges associated with using BF alone as a surrogate for a survival endpoint.

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

    NASA Technical Reports Server (NTRS)

    Bolten, John; Crow, Wade

    2012-01-01

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

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

    PubMed

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

    2016-03-15

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

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

    PubMed

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

    2007-12-01

    The potential contamination of groundwater by herbicides is often controlled by processes in the vadose zone, through which herbicides travel before entering groundwater. In the vadose zone, both physical and chemical processes affect the fate and transport of herbicides, therefore it is important to represent these processes by mathematical models to predict contaminant movement. To simulate the movement of simazine, a herbicide commonly used in Chilean vineyards, batch and miscible displacement column experiments were performed on a disturbed sandy soil to quantify the primary parameters and processes of simazine transport. Chloride (Cl(-)) was used as a non-reactive tracer, and simazine as the reactive tracer. The Hydrus-1D model was used to estimate the parameters by inversion from the breakthrough curves of the columns and to evaluate the potential groundwater contamination in a sandy soil from the Casablanca Valley, Chile. The two-site, chemical non-equilibrium model was observed to best represent the experimental results of the miscible displacement experiments in laboratory soil columns. Predictions of transport under hypothetical field conditions using the same soil from the column experiments were made for 40 years by applying herbicide during the first 20 years, and then halting the application and considering different rates of groundwater recharge. For recharge rates smaller than 84 mm year(-1), the predicted concentration of simazine at a depth of 1 m is below the U.S. EPA's maximum contaminant levels (4 microg L(-1)). After eight years of application at a groundwater recharge rate of 180 mm year(-1) (approximately 50% of the annual rainfall), simazine was found to reach the groundwater (located at 1 m depth) at a higher concentration (more than 40 microg L(-1)) than the existing guidelines in the USA and Europe. PMID:17604874

  4. 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

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

    SciTech Connect

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

    1999-01-01

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

  6. 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

  7. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2007-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-02-01

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

  10. 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.

  11. Updating representations of temporal intervals.

    PubMed

    Danckert, James; Anderson, Britt

    2015-12-01

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

  12. QT interval in anorexia nervosa.

    PubMed Central

    Cooke, R A; Chambers, J B; Singh, R; Todd, G J; Smeeton, N C; Treasure, J; Treasure, T

    1994-01-01

    OBJECTIVES--To determine the incidence of a long QT interval as a marker for sudden death in patients with anorexia nervosa and to assess the effect of refeeding. To define a long QT interval by linear regression analysis and estimation of the upper limit of the confidence interval (95% CI) and to compare this with the commonly used Bazett rate correction formula. DESIGN--Prospective case control study. SETTING--Tertiary referral unit for eating disorders. SUBJECTS--41 consecutive patients with anorexia nervosa admitted over an 18 month period. 28 age and sex matched normal controls. MAIN OUTCOME MEASURES--maximum QT interval measured on 12 lead electrocardiograms. RESULTS--43.6% of the variability in the QT interval was explained by heart rate alone (p < 0.00001) and group analysis contributed a further 5.9% (p = 0.004). In 6 (15%) patients the QT interval was above the upper limit of the 95% CI for the prediction based on the control equation (NS). Two patients died suddenly; both had a QT interval at or above the upper limit of the 95% CI. In patients who reached their target weights the QT interval was significantly shorter (median 9.8 ms; p = 0.04) relative to the upper limit of the 60% CI of the control regression line, which best discriminated between patients and controls. The median Bazett rate corrected QT interval (QTc) in patients and controls was 435 v 405 ms.s-1/2 (p = 0.0004), and before and after refeeding it was 435 v 432 ms.s1/2 (NS). In 14(34%) patients and three (11%) controls the QTc was > 440 ms.s-1/2 (p = 0.053). CONCLUSIONS--The QT interval was longer in patients with anorexia nervosa than in age and sex matched controls, and there was a significant tendency to reversion to normal after refeeding. The Bazett rate correction formula overestimated the number of patients with QT prolongation and also did not show an improvement with refeeding. PMID:8068473

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

    PubMed

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

    2016-01-01

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

  14. 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

  15. 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.

  16. 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

  17. Can the soil conditioning index predict soil organic carbon sequestration with conservation agricultural systems in the South?

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The soil conditioning index (SCI) is a relatively simple model used by NRCS to predict changes in soil organic C. It is based on three important conditions: (1) organic material (OM), (2) field operations (FO), and (3) erosion (ER). Our objective was to develop quantitative relationships between (...

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  19. 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.

  20. From Pavlov to pain: How predictability affects the anticipation and processing of visceral pain in a fear conditioning paradigm.

    PubMed

    Labrenz, Franziska; Icenhour, Adriane; Schlamann, Marc; Forsting, Michael; Bingel, Ulrike; Elsenbruch, Sigrid

    2016-04-15

    Conditioned pain-related fear may contribute to hyperalgesia and central sensitization, but this has not been tested for interoceptive, visceral pain. The underlying ability to accurately predict pain is based on predictive cue properties and may alter the sensory processing and cognitive-emotional modulation of pain thus exacerbating the subjective pain experience. In this functional magnetic resonance imaging study using painful rectal distensions as unconditioned stimuli (US), we addressed changes in the neural processing of pain during the acquisition of pain-related fear and subsequently tested if conditioned stimuli (CS) contribute to hyperalgesia and increased neural responses in pain-encoding regions. N=49 healthy volunteers were assigned to one of two groups and underwent 3T fMRI during acquisition of either differential fear conditioning (predictable) or non-contingent presentation of CS and US (unpredictable). During a subsequent test phase, pain stimuli signaled randomly by the CSs were delivered. For the acquisition, results confirmed differential conditioning in the predictable but not the unpredictable group. With regard to activation in response to painful stimuli, the unpredictable compared to the predictable group revealed greater activation in pain-encoding (somatosensory cortex, insula) and pain-modulatory (prefrontal and cingulate cortices, periaqueductal grey, parahippocampus) regions. In the test phase, no evidence of hyperalgesia or central sensitization was found, but the predictable group demonstrated enhanced caudate nucleus activation in response to CS(-)-signaled pain. These findings support that during fear conditioning, the ability to predict pain affects neural processing of visceral pain and alters the associative learning processes underlying the acquisition of predictive properties of cues signaling pain, but conditioned pain-related fear does not result in visceral hyperalgesia or central sensitization. PMID:26854560

  1. 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...

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

    PubMed

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

    2012-01-18

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

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

    NASA Astrophysics Data System (ADS)

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

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

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

    PubMed

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

    2001-09-01

    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 nonlinear 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 degrees C and 50 degrees 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. PMID:11594634

  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. 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

  7. 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.

  8. Relationships between host body condition and immunocompetence, not host sex, best predict parasite burden in a bat-helminth system.

    PubMed

    Warburton, Elizabeth M; Pearl, Christopher A; Vonhof, Maarten J

    2016-06-01

    Sex-biased parasitism highlights potentially divergent approaches to parasite resistance resulting in differing energetic trade-offs for males and females; however, trade-offs between immunity and self-maintenance could also depend on host body condition. We investigated these relationships in the big brown bat, Eptesicus fuscus, to determine if host sex or body condition better predicted parasite resistance, if testosterone levels predicted male parasite burdens, and if immune parameters could predict male testosterone levels. We found that male and female hosts had similar parasite burdens and female bats scored higher than males in only one immunological measure. Top models of helminth burden revealed interactions between body condition index and agglutination score as well as between agglutination score and host sex. Additionally, the strength of the relationships between sex, agglutination, and helminth burden is affected by body condition. Models of male parasite burden provided no support for testosterone predicting helminthiasis. Models that best predicted testosterone levels did not include parasite burden but instead consistently included month of capture and agglutination score. Thus, in our system, body condition was a more important predictor of immunity and worm burden than host sex. PMID:26898834

  9. Predicting Low Flow Conditions from Climatic Indices - Indicator-Based Modeling for Climate Change Impact Assessment

    NASA Astrophysics Data System (ADS)

    Fangmann, Anne; Haberlandt, Uwe

    2014-05-01

    In the face of climate change, the assessment of future hydrological regimes has become indispensable in the field of water resources management. Investigation of potential change is vital for proper planning, especially with regard to hydrological extremes. Commonly, projection of future streamflow is done applying process-based hydrological models, using climate model data as input, whose complex model structures generally require excessive amounts of time and effort for set-up and computation. This study aims at identifying practical alternatives to the employment of sophisticated models by considering simpler, yet sufficiently accurate methods for modeling rainfall-runoff relations with regard to hydrological extremes. The focus is thereby put on the prediction of low flow periods, which are, in contrast to flood events, characterized by extended durations and spatial dimensions. The models to be established in this study base on indicators, which characterize both meteorological and hydrological conditions within dry periods. This approach makes direct use of the coupling between atmospheric driving forces and streamflow response with the underlying presumption that low-precipitation and high-evaporation periods result in diminished flow, implying that relationships exist between the properties of both meteorological and hydrological events (duration, volume, severity etc.). Eventually, optimal combinations of meteorological indicators are sought that are suitable to predict various low flow characteristics with satisfactory accuracy. Two approaches for model specification are tested: a) multiple linear regression, and b) Fuzzy logic. The data used for this study are daily time series of mean discharge obtained from 294 gauges with variable record length situated in the federal state of Lower Saxony, Germany, as well as interpolated climate variables available for a period from 1951 to 2011. After extraction of a variety of indicators from the available

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

    PubMed

    He, Zhe; Weng, Chunhua

    2015-01-01

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

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

    PubMed Central

    He, Zhe; Weng, Chunhua

    2015-01-01

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

  12. 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

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

    PubMed

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

    2015-08-01

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

  14. 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

  15. Surface roughness prediction from combination of cutting forces, turning vibrations and machining conditions using artificial neural networks

    NASA Astrophysics Data System (ADS)

    Morala-Argüello, P.; Barreiro, J.; Alegre, E.; García-Ordás, M.; García-Olalla, Oscar; González-Madruga, D.

    2012-04-01

    Nowadays the evaluation of surface quality of manufactured products continues being a very important task for the industry. One of the lines of research associated to this subject tries to predict the surface roughness using signal analysis, such as vibrations, in the machining process. Many researchers have proposed models for determining the roughness based on the cutting conditions or the cutting forces. As the surface roughness depends on many variables, in this work different statistical values of cutting forces, tool vibration values and machining conditions are considered together for predicting surface roughness of turned metallic parts using artificial neural networks. We have notice the best predictions have been obtained when force and cutting conditions were combined together. The absolute error values obtained have been always below to 1.28 and 1.11 μm when using the median and root mean square (RMS) as descriptors, respectively.

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

    PubMed Central

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-01-01

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

  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 polynomial positivity

    NASA Technical Reports Server (NTRS)

    Bose, N. K.; Kim, K. D.

    1989-01-01

    It is shown that a univariate interval polynomial is globally positive if and only if two extreme polynomials are globally positive. It is shown that the global positivity property of a bivariate interval polynomial is completely determined by four extreme bivariate polynomials. The cardinality of the determining set for k-variate interval polynomials is 2k. One of many possible generalizations, where vertex implication for global positivity holds, is made by considering the parameter space to be the set dual of a boxed domain.

  1. 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...

  2. 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.

  3. The Application of the Unified Homogeneous Periodical Boundary Conditions to the Prediction of Effective Elastic Stiffness in a Widespread Field

    NASA Astrophysics Data System (ADS)

    Yu, Dong; Yang, Hong; Luo, Dong-Mei

    2011-06-01

    Periodical boundary conditions (PBC) are important for the prediction of effective elastic stiffness of composites by applying the macro-microscopic asymptotic expansion homogenization method (HM). In this paper, two kinds of homogeneous periodical boundary conditions are proposed to satisfy the improved expression for the homogenized effective stiffness with the homogeneous characteristic function, and one is the relaxed periodical boundary condition, and the other is a precise polynomial derived from the first one. A typical example of the off-axis short-fiber reinforced composites is analyzed by the described procedure. The results show that the periodical boundary condition is not unique, and the relaxed periodic boundary condition is the simplest and most convenient method to guarantee periodical displacement and anti-periodical traction boundary conditions simultaneously in a widespread field with a unified form.

  4. Predicting soil organic carbon sequestration in crop production systems of the southeastern USA with EPIC and the soil conditioning index

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Soil Conditioning Index (SCI), administered by the USDA-Natural Resource Conservation Service, predicts a positive or negative trend in soil organic carbon (SOC) based on knowledge of field operations, erosion loss, and organic matter inputs, but has not been adequately calibrated against long-t...

  5. 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

  6. Post-Extinction Conditional Stimulus Valence Predicts Reinstatement Fear: Relevance for Long Term Outcomes of Exposure Therapy

    PubMed Central

    Zbozinek, Tomislav D.; Hermans, Dirk; Prenoveau, Jason M.; Liao, Betty; Craske, Michelle G.

    2014-01-01

    Exposure therapy for anxiety disorders is translated from fear conditioning and extinction. While exposure therapy is effective in treating anxiety, fear sometimes returns after exposure. One pathway for return of fear is reinstatement: unsignaled unconditional stimuli following completion of extinction. The present study investigated the extent to which valence of the conditional stimulus (CS+) after extinction predicts return of CS+ fear after reinstatement. Participants (N = 84) engaged in a differential fear conditioning paradigm and were randomized to reinstatement or non-reinstatement. We hypothesized that more negative post-extinction CS+ valence would predict higher CS+ fear after reinstatement relative to non-reinstatement and relative to extinction retest. Results supported the hypotheses and suggest that strategies designed to decrease negative valence of the CS+ may reduce the return of fear via reinstatement following exposure therapy. PMID:24957680

  7. 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

  8. Methodology for prediction of ecological impacts under real conditions in Mexico

    NASA Astrophysics Data System (ADS)

    Bojórquez-Tapia, Luis Antonio

    1989-09-01

    Most environmental impact assessments in Mexico are short-duration studies that tend to be descriptive rather than analytical and predictive. Therefore, a general methodology has been developed for the prediction and communication of ecological impacts in situations where time, funds, and information are major limitations. The approach] involves two stages: (1) environmental characterization and (2) prediction and analysis of impacts. In stage 1, the assessment team is divided into autonomous groups; the groups work on the same land systems, which are characterized based on literature, aerial photography, and short field observations. In stage 2, the groups meet to evaluate impacts by means of interaction matrices and nonnumerical simulation models. This methodology has proved to be valuable to perform environmental impact statements for large engineering projects in Mexico.

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

    NASA Astrophysics Data System (ADS)

    Wrench, Alan A.

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

  10. 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…

  11. 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.

  12. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-11-01

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

  14. Interval neural networks

    SciTech Connect

    Patil, R.B.

    1995-05-01

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

  15. 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...

  16. 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.

  17. 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.

  18. Proper Interval Vertex Deletion

    NASA Astrophysics Data System (ADS)

    Villanger, Yngve

    Deleting a minimum number of vertices from a graph to obtain a proper interval graph is an NP-complete problem. At WG 2010 van Bevern et al. gave an O((14k + 14) k + 1 kn 6) time algorithm by combining iterative compression, branching, and a greedy algorithm. We show that there exists a simple greedy O(n + m) time algorithm that solves the Proper Interval Vertex Deletion problem on \\{claw,net,allowbreak tent,allowbreak C_4,C_5,C_6\\}-free graphs. Combining this with branching on the forbidden structures claw,net,tent,allowbreak C_4,C_5, and C 6 enables us to get an O(kn 6 6 k ) time algorithm for Proper Interval Vertex Deletion, where k is the number of deleted vertices.

  19. 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.

  20. 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...

  1. 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.

  2. Predicting Strength and Fatigue for Suited and Unsuited Conditions from Empirical Data

    NASA Technical Reports Server (NTRS)

    Maida, James C.; Gonzalez, L. J.; Rajulu, S.; Russo, Dane M. (Technical Monitor)

    2001-01-01

    The need for longer and more labor-intensive extra-vehicular activities (EVA) is required for construction and maintenance of the International Space Station (ISS). Issues pertaining to human performance while wearing a space suit (EMU) for prolonged periods have become more important. This project was conducted to investigate how a pressurized Extra-vehicular Mobility Unit (EMU) affects human upper body joint strength and fatigue and how to predict it from computer models based on the data collected.

  3. Mechanistic prediction of fission product release under normal and accident conditions: key uncertainties that need better resolution

    SciTech Connect

    Rest, J.

    1983-09-01

    A theoretical model has been used for predicting the behavior of fission gas and volatile fission products (VFPs) in UO/sub 2/-base fuels during steady-state and transient conditions. This model represents an attempt to develop an efficient predictive capability for the full range of possible reactor operating conditions. Fission products released from the fuel are assumed to reach the fuel surface by successively diffusing (via atomic and gas-bubble mobility) from the grains to grain faces and then to the grain edges, where the fission products are released through a network of interconnected tunnels of fission-gas induced and fabricated porosity. The model provides for a multi-region calculation and uses only one size class to characterize a distribution of fission gas bubbles.

  4. Mechanistic prediction of fission-product release under normal and accident conditions: key uncertainties that need better resolution. [PWR; BWR

    SciTech Connect

    Rest, J.

    1983-09-01

    A theoretical model has been used for predicting the behavior of fission gas and volatile fission products (VFPs) in UO/sub 2/-base fuels during steady-state and transient conditions. This model represents an attempt to develop an efficient predictive capability for the full range of possible reactor operating conditions. Fission products released from the fuel are assumed to reach the fuel surface by successively diffusing (via atomic and gas-bubble mobility) from the grains to grain faces and then to the grain edges, where the fission products are released through a network of interconnected tunnels of fission-gas induced and fabricated porosity. The model provides for a multi-region calculation and uses only one size class to characterize a distribution of fission gas bubbles.

  5. 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.

  6. 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.

  7. The Effect of Initial Conditions and Discussion on Students' Predictions for Interactive Lecture Demonstrations

    NASA Astrophysics Data System (ADS)

    Marx, Jeffrey

    2008-10-01

    Over the past eight years at McDaniel College, students' Predictions for various Interactive Lecture Demonstrations (ILDs) have improved markedly. One explanation is that students have become increasingly sophisticated in their understanding of kinematics and dynamics. Another possible explanation is that the class as a whole is only slightly more sophisticated, and during the Discussion Phase of the ILD the correct Predication is very successfully transmitted within groups and between groups. The purpose of this paper is to support the proposition of this possible explanation. To begin to address this idea, I present an overview of and results from a preliminary, computer-based simulation of classroom discussion.

  8. 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…

  9. Prediction of "Fear" Acquisition in Healthy Control Participants in a De Novo Fear Conditioning Paradigm

    ERIC Educational Resources Information Center

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

    2007-01-01

    Studies using fear-conditioning paradigms have found that anxiety patients are more conditionable than individuals without these disorders, but these effects have been demonstrated inconsistently. It is unclear whether these findings have etiological significance or whether enhanced conditionability is linked only to certain anxiety…

  10. 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…

  11. 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...

  12. 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…

  13. 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

  14. 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.

  15. 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. PMID:19238568

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

    PubMed Central

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

    2015-01-01

    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. PMID:26151911

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

    PubMed

    Floridou, Georgia A; Müllensiefen, Daniel

    2015-05-01

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

  18. 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

  19. 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. PMID:25789440

  20. Solid surface evolution model to predict uranium release from unirradiated UO 2 and nuclear spent fuel dissolution under oxidizing conditions

    NASA Astrophysics Data System (ADS)

    de Pablo, J.; Casas, I.; Giménez, J.; Martí, V.; Torrero, M. E.

    1996-09-01

    The dissolution of UO2 under oxidizing conditions has been studied in the last years in different waste disposal conditions. These studies have indicated the importance of the solid surface evolution during leaching experiments. In this work, a mathematical model based on X-ray photoelectron spectroscopy determinations of the solid surface was developed. This model allows the uranium release under oxidizing conditions at acidic pH or in carbonate medium to be predicted. At alkaline pH without carbonate, the formation of a UO2.33 surface layer and its equilibrium with the uranium concentration in solution could be responsible for the disagreement observed between the model and the experimental data. This model has been also applied to uranium release from spent nuclear fuel dissolution experiments carried out in granitic groundwater.

  1. 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

  2. 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.

  3. Development of an antecedent moisture condition model for prediction of Rainfall-Derived Inflow/Infiltration (RDII)

    NASA Astrophysics Data System (ADS)

    Sadri, S.; Graham, E.

    2011-12-01

    The rainfall-derived Infiltration/inflow (RDII) response of a sanitary sewer system is quite complex. In addition to rainfall, one of the major factors that control RDII response is the Antecedent Moisture Condition (AMC). AMC is one of the key inputs to many hydrological models. For urban hydrology planning and management, quantifying the effect of AMC, the moisture of soil condition during and prior a rainfall event will enhance the prediction capabilities of RDII-rainfall models. The problem with simply correlating the peak rainfall and peak flows is that the data will typically be scattered in a a way that the regression analysis will not yield reliable information. Thus, there is a need to find the contribution of AMC to RDII. In urban hydrology engineering projects, although soil moisture data can be very useful, especially for more pervious surfaces, it is typical that not much data is available. In the past, here has been little research on defining and calculating AMC in the domain of urban hydrology. In this study, a parametric model is developed to predict RDII as a function of antecedent rainfalls. The hypothesis of this study is that besides the current rainfall, the rainfall events of the past, up to certain limit of time, affect the current flow and therefore, AMC is directly related to a geometrically-weighted sum of rainfall which we will denote s[t]. Let γ be a parameter between 0 and 1, representing the effect of a day's rainfall on the next day. Then consider the geometrically-weighted sum s[t] = γ*r[t-1] + γ^2*r[t-2] + ... + γ^10*r[t-10] where t represents the present day (time) and r[t] is the rainfall depth on that day. Intuitively, s[t] measures the effect accumulated rainfall from the past 10 days. The general regression model is hence: Predicted flow at time t = α*r[t] + β*s[t] where β is a multiplier and α is the parameter based on a separate and stronger effect of rain at time t. The goal is to find the optimized parameters α,

  4. 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.

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

    NASA Astrophysics Data System (ADS)

    Poesio, Pietro; Damone, Angelo; Matar, Omar

    2015-11-01

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

  6. 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.

  7. 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.

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

    PubMed

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

    2015-11-01

    The present work is dedicated to the assessment of the cold thermal strain of human beings working within freezing chambers. To obtain the present results, both field measurements and a numerical procedure based on a modified version of the Stolwijk thermoregulation model were used. Eighteen freezing chambers were considered. A wide range of physical parameters of the cold stores, the workers clothing insulation, and the working and recovering periods were observed. The combination of these environmental and individual parameters lead to different levels of thermal stress, which were grouped under three categories. Some good practices were observed in the field evaluations, namely situations with appropriate level of clothing protection and limited duration of exposure to cold avoiding unacceptable level of hypothermia. However, the clothing ensembles normally used by the workers do not provide the minimum required insulation, which suggests the possibility of the whole body cooling for levels higher than admissible. The numerical predictions corroborate the main conclusions of the field survey. The results obtained with both methodologies clearly show that, for the low temperature of the freezing chambers, the clothing insulation is insufficient, the exposure periods are too long, and the recovering periods are inadequate. Thus, high levels of physiological strain can indeed be reached by human beings under such working environments. PMID:25691118

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

    NASA Astrophysics Data System (ADS)

    Dünser, Simon; Meyer, Daniel W.

    2016-06-01

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

  10. 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.

  11. 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

  12. Prediction of pressure fluctuation of a hydraulic turbine at no-load condition

    NASA Astrophysics Data System (ADS)

    Chen, T. J.; Wu, X. J.; Liu, J. T.; Wu, Y. L.

    2015-01-01

    In order to study characteristics of pressure fluctuation of a turbine during the starting period, a turbine with guide vanes device at no-load condition was investigated using RNG k-epsilon turbulence model. The inner flow distribution and pressure fluctuation characteristics were analyzed. Results show that the pressure fluctuations in the region between the runner and guide vanes are different around the runner inlet. The dominant frequency of pressure fluctuation in the vaneless space close to the casing outlet is the blade passing frequency, while the dominant frequency at the rest region is the twice of the blade passing frequency. The increase of amplitude of pressure fluctuation close to the casing outlet can be attribute to the large scale stall at suction side of the runner inlet.

  13. Identifying Growth Conditions for Nicotiana benthimiana Resulting in Predictable Gene Expression of Promoter-Gus Fusion

    NASA Astrophysics Data System (ADS)

    Sandoval, V.; Barton, K.; Longhurst, A.

    2012-12-01

    Revoluta (Rev) is a transcription factor that establishes leaf polarity inArabidopsis thaliana. Through previous work in Dr. Barton's Lab, it is known that Revoluta binds to the ZPR3 promoter, thus activating the ZPR3 gene product inArabidopsis thaliana. Using this knowledge, two separate DNA constructs were made, one carrying revgene and in the other, the ZPR3 promoter fussed with the GUS gene. When inoculated in Nicotiana benthimiana (tobacco), the pMDC32 plasmid produces the Rev protein. Rev binds to the ZPR3 promoter thereby activating the transcription of the GUS gene, which can only be expressed in the presence of Rev. When GUS protein comes in contact with X-Gluc it produce the blue stain seen (See Figure 1). In the past, variability has been seen of GUS expression on tobacco therefore we hypothesized that changing the growing conditions and leaf age might improve how well it's expressed.

  14. Bayesian conditioning of a rainfall-runoff model for predicting flows in ungauged catchments and under land use changes

    NASA Astrophysics Data System (ADS)

    Bulygina, Nataliya; McIntyre, Neil; Wheater, Howard

    2011-02-01

    A novel method is presented for conditioning rainfall-runoff models for ungauged catchment and land use impact applications. The method conditions the model on information from multiple regionalized response indices using a formal Bayesian approach. Two indices that hold information about soil type and land use effects are the base flow index from the Hydrology of Soil Type (HOST) classification and curve number from the U.S. Department of Agriculture's Soil Conservation Service soil and land use classification. These indices are used to constrain a five-parameter probability distributed moisture model for subcatchments of the Wye (grazed grassland) and Severn (mainly afforested) catchments in the United Kingdom. The base flow index and curve number constrain only two of the five model parameters, indicating that ideally, other sources of information would be sought. Nevertheless, the procedure significantly reduces the prior uncertainty in runoff prediction and gives predictions close to those of the calibrated models. For the case study, the introduction of the curve number in addition to the base flow index has only a small effect on model performance and uncertainty; however, it allows a distinction between the effects of soil type and land management for the purpose of scenario analysis. The principal assumptions used in the method are the applicability of the curve number classification system and its mapping to UK soil types and the likelihood function used for Bayesian conditioning.

  15. Interval arithmetic operations for uncertainty analysis with correlated interval variables

    NASA Astrophysics Data System (ADS)

    Jiang, Chao; Fu, Chun-Ming; Ni, Bing-Yu; Han, Xu

    2016-08-01

    A new interval arithmetic method is proposed to solve interval functions with correlated intervals through which the overestimation problem existing in interval analysis could be significantly alleviated. The correlation between interval parameters is defined by the multidimensional parallelepiped model which is convenient to describe the correlative and independent interval variables in a unified framework. The original interval variables with correlation are transformed into the standard space without correlation, and then the relationship between the original variables and the standard interval variables is obtained. The expressions of four basic interval arithmetic operations, namely addition, subtraction, multiplication, and division, are given in the standard space. Finally, several numerical examples and a two-step bar are used to demonstrate the effectiveness of the proposed method.

  16. 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.

  17. 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

  18. Local song elements indicate local genotypes and predict physiological condition in song sparrows Melospiza melodia.

    PubMed

    Stewart, Kathryn A; MacDougall-Shackleton, Elizabeth A

    2008-06-23

    Geographical variation in birdsong is taxonomically widespread and behaviourally salient, with females often preferring local over non-local song. However, the benefits associated with this preference remain poorly understood. One potential explanation is that song may reflect a male's place of origin and thus allow females to obtain genes well adapted to the local environment. We studied naturally occurring variation in the degree to which the elements of a male's song repertoire matched those of the local population ('syllable sharing') in migratory song sparrows (Melospiza melodia melodia). Syllable sharing was correlated with genetic similarity to the local population, suggesting that song reflects population of origin. Males sharing more syllables also had larger testosterone-dependent traits, fewer blood-borne parasites and reduced indicators of stress. Our findings are consistent with locally good genes models. Alternatively, immigrants' condition may suffer due to unfamiliarity with the breeding site or inability to match song elements during territorial interactions. Females preferring 'local-sounding' males may thus obtain genetic and/or direct benefits for their offspring. PMID:18331976

  19. Prediction of a new ground state of superhard compound B6O at ambient conditions.

    PubMed

    Dong, Huafeng; Oganov, Artem R; Wang, Qinggao; Wang, Sheng-Nan; Wang, Zhenhai; Zhang, Jin; Esfahani, M Mahdi Davari; Zhou, Xiang-Feng; Wu, Fugen; Zhu, Qiang

    2016-01-01

    Boron suboxide B6O, the hardest known oxide, has an Rm crystal structure (α-B6O) that can be described as an oxygen-stuffed structure of α-boron, or, equivalently, as a cubic close packing of B12 icosahedra with two oxygen atoms occupying all octahedral voids in it. Here we show a new ground state of this compound at ambient conditions, Cmcm-B6O (β-B6O), which in all quantum-mechanical treatments that we tested comes out to be slightly but consistently more stable. Increasing pressure and temperature further stabilizes it with respect to the known α-B6O structure. β-B6O also has a slightly higher hardness and may be synthesized using different experimental protocols. We suggest that β-B6O is present in mixture with α-B6O, and its presence accounts for previously unexplained bands in the experimental Raman spectrum. PMID:27498718

  20. 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. PMID:24241072

  1. 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

  2. Effects of the inlet conditions and blood models on accurate prediction of hemodynamics in the stented coronary arteries

    NASA Astrophysics Data System (ADS)

    Jiang, Yongfei; Zhang, Jun; Zhao, Wanhua

    2015-05-01

    Hemodynamics altered by stent implantation is well-known to be closely related to in-stent restenosis. Computational fluid dynamics (CFD) method has been used to investigate the hemodynamics in stented arteries in detail and help to analyze the performances of stents. In this study, blood models with Newtonian or non-Newtonian properties were numerically investigated for the hemodynamics at steady or pulsatile inlet conditions respectively employing CFD based on the finite volume method. The results showed that the blood model with non-Newtonian property decreased the area of low wall shear stress (WSS) compared with the blood model with Newtonian property and the magnitude of WSS varied with the magnitude and waveform of the inlet velocity. The study indicates that the inlet conditions and blood models are all important for accurately predicting the hemodynamics. This will be beneficial to estimate the performances of stents and also help clinicians to select the proper stents for the patients.

  3. 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

  4. 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

  5. Validation and adjustment of the mathematical prediction model for human sweat rate responses to outdoor environmental conditions.

    PubMed

    Shapiro, Y; Moran, D; Epstein, Y; Stroschein, L; Pandolf, K B

    1995-05-01

    Under outdoor conditions this model was over estimating sweat loss response in shaded (low solar radiation) environments, and underestimating the response when solar radiation was high (open field areas). The present study was conducted in order to adjust the model to be applicable under outdoor environmental conditions. Four groups of fit acclimated subjects participated in the study. They were exposed to three climatic conditions (30 degrees, 65% rh; 31 degrees C, 40% rh; and 40 degrees C, 20% rh) and three levels of metabolic rate (100, 300 and 450 W) in shaded and sunny areas while wearing shorts, cotton fatigues (BDUs) or protective garments. The original predictive equation for sweat loss was adjusted for the outdoor conditions by evaluating separately the radiative heat exchange, short-wave absorption in the body and long-wave emission from the body to the atmosphere and integrating them in the required evaporation component (Ereq) of the model, as follows: Hr = 1.5SL0.6/I(T) (watt) H1 = 0.047Me.th/I(T) (watt), where SL is solar radiation (W.m-2), Me.th is the Stephan Boltzman constant, and I(T) is the effective clothing insulation coefficient. This adjustment revealed a high correlation between the measured and expected values of sweat loss (r = 0.99, p < 0.0001). PMID:7737107

  6. Initializing Weather Research and Forecasting (WRF) model with land surface conditions from the Terrestrial Observation and PredictionSystem (TOPS)

    NASA Astrophysics Data System (ADS)

    Hashimoto, H.; Wang, W.; Melton, F.; Milesi, C.; Michaellis, A.; Nemani, R.

    2008-12-01

    Weather forecasting models have been shown to exhibit a strong sensitivity to land surface conditions, particularly soil moisture. However, the lack of robust estimates of soil moisture at appropriate time and space scales has been a persistent problem. Terrestrial Observation and Prediction System (TOPS) integrates surface weather observations and satellite data with ecosystem simulation models to produce spatially and temporally consistent nowcasts and forecasts of land surface conditions such as soil moisture, evapotranspiration, vegetation stress and photosynthesis. To extend TOPS capabilities beyond estimating ecosystem rocesses, we integrated TOPS with Weather Research Forecasting (WRF) model to evaluate the utility of TOPS-derived surface conditions such as soil moisture in weather forecasting. TOPS land surface schemes are based on a well-calibrated ecosystem model, Biome-BGC, for simulating water and carbon budgets. One of the advantages of TOPS is its flexibility, which enables it to ingest data from a variety of sensors and surface networks, and thus we can provide the surface conditions to users from historical to near real-time, and for spatial scales ranging from 1km and up. We ran the TOPS-WRF system over California for several days during 2007. The results show TOPS-WRF simulations are consistently better than default WRF simulations, particularly over the dry season when spatial variability in soil moisture becomes a significant factor in influencing local energy balance.

  7. 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

  8. 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.

  9. Peritransplant Serum Albumin Decline Predicts Subsequent Severe Acute Graft-versus-Host Disease after Mucotoxic Myeloablative Conditioning.

    PubMed

    Rashidi, Armin; DiPersio, John F; Westervelt, Peter; Abboud, Camille N; Schroeder, Mark A; Cashen, Amanda F; Pusic, Iskra; Romee, Rizwan

    2016-06-01

    Conditioning-related gut toxicity can result in a protein-losing enteropathy manifesting as a decline in serum albumin in the peritransplant period. Inspired by the pathogenesis of acute graft-versus-host disease (aGVHD), we hypothesized that the magnitude of decline in serum albumin from the day of conditioning initiation until its nadir in the first 2 weeks after hematopoietic cell transplantation HCT (DeltaAlb) predicts the risk for subsequent severe aGVHD. We reviewed the medical records of all 88 patients with acute myeloid leukemia or myelodysplastic syndrome who underwent highly mucotoxic myeloablative (busulfan/cyclophosphamide or cyclophosphamide/total body irradiation) allogeneic HCT from a matched related donor (MRD) or matched unrelated donor (MUD) at our institution between January 1, 2012 and January 1, 2015. Severe aGVHD was associated with MUD (47% versus 14% with MRD; P = .001) and DeltaAlb, which was significantly greater among patients who developed versus did not develop severe aGVHD (1.2 ± .5 versus .8 ± .4 g/dL, respectively; P < .001). In multivariate analysis DeltaAlb remained a significant predictor of severe aGVHD (odds ratio, 5.68; 95% CI, 1.65 to 19.64; P = .006; area under the ROC curve, .74; 95% CI, .63 to .86; P < .001). The best cutoff for DeltaAlb to predict severe aGVHD was .9, with a sensitivity, specificity, and overall classification accuracy of 77%, 66%, and 69%, respectively. The model was validated using the bootstrap technique, with no significant change in its performance. These results were not generalizable to a cohort of 30 patients who received less mucotoxic myeloablative or reduced-intensity conditioning. In conclusion, with mucotoxic myeloablative HCT, each .1-g/dL increase in DeltaAlb was associated with an approximately 23% increase in the odds of developing severe aGVHD. As an early biomarker of gut damage, DeltaAlb can be incorporated in composite risk models for aGVHD prediction, with hopes for

  10. Time-domain inflow boundary condition for turbulence-airfoil interaction noise prediction using synthetic turbulence modeling

    NASA Astrophysics Data System (ADS)

    Kim, Daehwan; Heo, Seung; Cheong, Cheolung

    2015-03-01

    The present paper deals with development of the synthetic turbulence inflow boundary condition (STIBC) to predict inflow broadband noise generated by interaction between turbulence and an airfoil/a cascade of airfoils in the time-domain. The STIBC is derived by combining inflow boundary conditions that have been successfully applied in external and internal computational aeroacoustics (CAA) simulations with a synthetic turbulence model. The random particle mesh (RPM) method based on a digital filter is used as the synthetic turbulence model. Gaussian and Liepmann spectra are used to define the filters for turbulence energy spectra. The linearized Euler equations are used as governing equations to evaluate the suitability of the STIBC in time-domain CAA simulations. First, the velocity correlations and energy spectra of the synthesized turbulent velocities are compared with analytic ones. The comparison results reveal that the STIBC can reproduce a turbulent velocity field satisfying the required statistical characteristics of turbulence. Particularly, the Liepmann filter representing a non-Gaussian filter is shown to be effectively described by superposing the Gaussian filters. Each Gaussian filter has a different turbulent kinetic energy and integral length scale. Second, two inflow noise problems are numerically solved using the STIBC: the turbulence-airfoil interaction and the turbulence-a cascade of airfoils interaction problems. The power spectrum of noise due to an isolated flat plate airfoil interacting with incident turbulence is predicted, and its result is successfully validated against Amiet's analytic model (Amiet, 1975) [4]. The prediction results of the upstream and downstream acoustic power spectra from a cascade of flat plates are then compared with Cheong's analytic model (Cheong et al., 2006) [30]. These comparisons are also in excellent agreement. On the basis of these illustrative computation results, the STIBC is expected to be applied to

  11. 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

  12. 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

  13. 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. PMID:27174227

  14. Computational prediction of the refinement of oxide agglomerates in a physical conditioning process for molten aluminium alloy

    NASA Astrophysics Data System (ADS)

    Tong, M.; Jagarlapudi, S. C.; Patel, J. B.; Stone, I. C.; Fan, Z.; Browne, D. J.

    2015-06-01

    Physically conditioning molten scrap aluminium alloys using high shear processing (HSP) was recently found to be a promising technology for purification of contaminated alloys. HSP refines the solid oxide agglomerates in molten alloys, so that they can act as sites for the nucleation of Fe-rich intermetallic phases which can subsequently be removed by the downstream de-drossing process. In this paper, a computational modelling for predicting the evolution of size of oxide clusters during HSP is presented. We used CFD to predict the macroscopic flow features of the melt, and the resultant field predictions of temperature and melt shear rate were transferred to a population balance model (PBM) as its key inputs. The PBM is a macroscopic model that formulates the microscopic agglomeration and breakage of a population of a dispersed phase. Although it has been widely used to study conventional deoxidation of liquid metal, this is the first time that PBM has been used to simulate the melt conditioning process within a rotor/stator HSP device. We employed a method which discretizes the continuous profile of size of the dispersed phase into a collection of discrete bins of size, to solve the governing population balance equation for the size of agglomerates. A finite volume method was used to solve the continuity equation, the energy equation and the momentum equation. The overall computation was implemented mainly using the FLUENT module of ANSYS. The simulations showed that there is a relatively high melt shear rate between the stator and sweeping tips of the rotor blades. This high shear rate leads directly to significant fragmentation of the initially large oxide aggregates. Because the process of agglomeration is significantly slower than the breakage processes at the beginning of HSP, the mean size of oxide clusters decreases very rapidly. As the process of agglomeration gradually balances the process of breakage, the mean size of oxide clusters converges to a

  15. Challenging Gait Conditions Predict 1-Year Decline in Gait Speed in Older Adults With Apparently Normal Gait

    PubMed Central

    Perera, Subashan; VanSwearingen, Jessie M.; Hile, Elizabeth S.; Wert, David M.; Studenski, Stephanie A.

    2011-01-01

    Background Mobility often is tested under a low challenge condition (ie, over a straight, uncluttered path), which often fails to identify early mobility difficulty. Tests of walking during challenging conditions may uncover mobility difficulty that is not identified with usual gait testing. Objective The purpose of this study was to determine whether gait during challenging conditions predicts decline in gait speed over 1 year in older people with apparently normal gait (ie, gait speed of ≥1.0 m/s). Design This was a prospective cohort study. Methods Seventy-one older adults (mean age=75.9 years) with a usual gait speed of ≥1.0 m/s participated. Gait was tested at baseline under 4 challenging conditions: (1) narrow walk (15 cm wide), (2) stepping over obstacles (15.24 cm [6 in] and 30.48 cm [12 in]), (3) simple walking while talking (WWT), and (4) complex WWT. Usual gait speed was recorded over a 4-m course at baseline and 1 year later. A 1-year change in gait speed was calculated, and participants were classified as declined (decreased ≥0.10 m/s, n=18), stable (changed <0.10 m/s, n=43), or improved (increased ≥0.10 m/s, n=10). Analysis of variance was used to compare challenging condition cost (usual − challenging condition gait speed difference) among the 3 groups. Results Participants who declined in the ensuing year had a greater narrow walk and obstacle walk cost than those who were stable or who improved in gait speed (narrow walk cost=0.43 versus 0.33 versus 0.22 m/s and obstacle walk cost=0.35 versus 0.26 versus 0.13 m/s). Simple and complex WWT cost did not differ among the groups. Limitations The participants who declined in gait speed over time walked the fastest, and those who improved walked the slowest at baseline; thus, the potential contribution of regression to the mean to the findings should not be overlooked. Conclusions In older adults with apparently normal gait, the assessment of gait during challenging conditions appears to uncover

  16. Contracting, equal, and expanding learning schedules: the optimal distribution of learning sessions depends on retention interval.

    PubMed

    Küpper-Tetzel, Carolina E; Kapler, Irina V; Wiseheart, Melody

    2014-07-01

    In laboratory and applied learning experiments, researchers have extensively investigated the optimal distribution of two learning sessions (i.e., initial learning and one relearning session) for the learning of verbatim materials. However, research has not yet provided a satisfying and conclusive answer to the optimal scheduling of three learning sessions (i.e., initial learning and two relearning sessions) across educationally relevant time intervals. Should the to-be-learned material be repeated at decreasing intervals (contracting schedule), constant intervals (equal schedule), or increasing intervals (expanding schedule) between learning sessions? Different theories and memory models (e.g., study-phase retrieval theory, contextual variability theory, ACT-R, and the Multiscale Context Model) make distinct predictions about the optimal learning schedule. We discuss the extant theories and derive clear predictions from each of them. To test these predictions empirically, we conducted an experiment in which participants studied and restudied paired associates with a contracting, equal, or expanding learning schedule. Memory performance was assessed immediately, 1 day, 7 days, or 35 days later with free- and cued-recall tests. Our results revealed that the optimal learning schedule is conditional on the length of the retention interval: A contracting learning schedule was beneficial for retention intervals up to 7 days, but both equal and expanding learning schedules were better for a long retention interval of 35 days. Our findings can be accommodated best by the contextual variability theory and indicate that revisions are needed to existing memory models. Our results are practically relevant, and their implications for real-world learning are discussed. PMID:24500777

  17. Ground-water conditions in Salt Lake Valley, Utah, 1969-83, and predicted effects of increased withdrawals from wells

    USGS Publications Warehouse

    Waddell, K.M.; Seiler, R.L.; Santini, Melissa; Solomon, D.K.

    1987-01-01

    This report was prepared in cooperation with several organizations in the Salt Lake Valley and with the Central Utah Water Conservancy District to present results of a study to determine changes in the ground-water conditions in Salt Lake Valley, Utah, from 1969 to 1983, and to predict the aquifer response to projected withdrawals. The average annual recharge and discharge from the ground-water reservoir in Salt Lake Valley, Utah, during 1969-82 were estimated to be about 352,000 and 353,000 acre-feet per year. Withdrawals from wells increased from 107,000 acre-feet per year during 1964-68 to 117,000 acre-feet per year during 1969-82. The greatest increase in use was for public supply and institutions which increased from 35,000 acre-feet per year during 1964-68 to 46,700 acre-feet per year during 1969-82.

  18. Prediction of performance of two-phase flow nozzle and Liquid Metal Magnetohydrodynamic (LMMHD) generator for no slip condition

    NASA Astrophysics Data System (ADS)

    Fabris, G.; Back, L.

    Two-phase LMMHD energy conversion systems have potentially significant advantages over conventional systems such as higher thermal efficiency and substantial simplicity with lower capital and maintenance costs. Maintenance of low velocity slip is of importance for achieving high generator efficiency. A bubbly flow pattern ensures very low velocity slip. The full governing equations were written out, and a computer prediction code was developed to analyze performance of a two-phase flow LMMHD generator and nozzle under conditions of no slip. Three different shapes of a LMMHD generator has been investigated. Electrical power outputs are in the 20 kW range. Generator efficiency exceeds 71 percent at an average void fraction of about 70 percent. This is an appreciable performance for a short generator without insulating vanes for minimizing electrical losses in the end regions.

  19. Prediction of performance of two-phase flow nozzle and liquid metal magnetohydrodynamic (LMMHD) generator for no slip condition

    NASA Astrophysics Data System (ADS)

    Fabris, G.; Back, L.

    Two-phase LMMHD energy conversion systems have potentially significant advantages over conventional systems such as higher thermal efficiency and substantial simplicity with lower capital and maintenance costs. Maintenance of low velocity slip is of importance for achieving high generator efficiency. A bubbly flow pattern ensures very low velocity slip. The full governing equations have been written out, and a computer prediction code has been developed to analyze performance of a two-phase flow LMMHD generator and nozzle under conditions of no slip. Three different shapes of a LMMHD generator have been investigated. Electrical power outputs are in the 20 kW range. Generator efficiency exceeds 71 percent at an average void fraction of about 70 percent. This is an appreciable performance for a short generator without insulating vanes for minimizing electrical losses in the end regions.

  20. 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.

  1. 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.

  2. Prediction of Low-Voltage Tetrafluoromethane Emissions Based on the Operating Conditions of an Aluminium Electrolysis Cell

    NASA Astrophysics Data System (ADS)

    Dion, Lukas; Kiss, László I.; Poncsák, Sándor; Lagacé, Charles-Luc

    2016-08-01

    Greenhouse gas (GHG) generation is inherent in the production of aluminium by a technology that uses carbon anodes. Most of those GHG are composed of CO2 produced by redox reaction that occurs in the cell. However, a significant fraction of the annual GHG production is composed of perfluorocarbons (PFC) resulting from anode effects (AE). Multiple investigations have shown that tetrafluoromethane (CF4) can be generated under low-voltage conditions in the electrolysis cells, without global anode effect. The aim of this paper is to find a quantitative relationship between monitored cell parameters and the emissions of CF4. To achieve this goal, a predictive algorithm has been developed using seven cell indicators. These indicators are based on the cell voltage, the noise level and other parameters calculated from individual anode current monitoring. The predictive algorithm is structured into three different steps. The first two steps give qualitative information while the third one quantitatively describes the expected CF4 concentration at the duct end of the electrolysis cells. Validations after each step are presented and discussed. Finally, a sensitivity analysis was performed to understand the effect of each indicator on the onset of low-voltage PFC emissions. The standard deviation of individual anode currents was found to be the dominant variable. Cell voltage, noise level, and maximum individual anode current also showed a significant correlation with the presence of CF4 in the output gas of an electrolysis cell.

  3. Extended flowering intervals of bamboos evolved by discrete multiplication.

    PubMed

    Veller, Carl; Nowak, Martin A; Davis, Charles C

    2015-07-01

    Numerous bamboo species collectively flower and seed at dramatically extended, regular intervals - some as long as 120 years. These collective seed releases, termed 'masts', are thought to be a strategy to overwhelm seed predators or to maximise pollination rates. But why are the intervals so long, and how did they evolve? We propose a simple mathematical model that supports their evolution as a two-step process: First, an initial phase in which a mostly annually flowering population synchronises onto a small multi-year interval. Second, a phase of successive small multiplications of the initial synchronisation interval, resulting in the extraordinary intervals seen today. A prediction of the hypothesis is that mast intervals observed today should factorise into small prime numbers. Using a historical data set of bamboo flowering observations, we find strong evidence in favour of this prediction. Our hypothesis provides the first theoretical explanation for the mechanism underlying this remarkable phenomenon. PMID:25963600

  4. 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

  5. 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.…

  6. 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...

  7. Identification, Expression Analysis, and Target Prediction of Flax Genotroph MicroRNAs Under Normal and Nutrient Stress Conditions.

    PubMed

    Melnikova, Nataliya V; Dmitriev, Alexey A; Belenikin, Maxim S; Koroban, Nadezhda V; Speranskaya, Anna S; Krinitsina, Anastasia A; Krasnov, George S; Lakunina, Valentina A; Snezhkina, Anastasiya V; Sadritdinova, Asiya F; Kishlyan, Natalya V; Rozhmina, Tatiana A; Klimina, Kseniya M; Amosova, Alexandra V; Zelenin, Alexander V; Muravenko, Olga V; Bolsheva, Nadezhda L; Kudryavtseva, Anna V

    2016-01-01

    Cultivated flax (Linum usitatissimum L.) is an important plant valuable for industry. Some flax lines can undergo heritable phenotypic and genotypic changes (LIS-1 insertion being the most common) in response to nutrient stress and are called plastic lines. Offspring of plastic lines, which stably inherit the changes, are called genotrophs. MicroRNAs (miRNAs) are involved in a crucial regulatory mechanism of gene expression. They have previously been assumed to take part in nutrient stress response and can, therefore, participate in genotroph formation. In the present study, we performed high-throughput sequencing of small RNAs (sRNAs) extracted from flax plants grown under normal, phosphate deficient and nutrient excess conditions to identify miRNAs and evaluate their expression. Our analysis revealed expression of 96 conserved miRNAs from 21 families in flax. Moreover, 475 novel potential miRNAs were identified for the first time, and their targets were predicted. However, none of the identified miRNAs were transcribed from LIS-1. Expression of seven miRNAs (miR168, miR169, miR395, miR398, miR399, miR408, and lus-miR-N1) with up- or down-regulation under nutrient stress (on the basis of high-throughput sequencing data) was evaluated on extended sampling using qPCR. Reference gene search identified ETIF3H and ETIF3E genes as most suitable for this purpose. Down-regulation of novel potential lus-miR-N1 and up-regulation of conserved miR399 were revealed under the phosphate deficient conditions. In addition, the negative correlation of expression of lus-miR-N1 and its predicted target, ubiquitin-activating enzyme E1 gene, as well as, miR399 and its predicted target, ubiquitin-conjugating enzyme E2 gene, was observed. Thus, in our study, miRNAs expressed in flax plastic lines and genotrophs were identified and their expression and expression of their targets was evaluated using high-throughput sequencing and qPCR for the first time. These data provide new insights

  8. 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

  9. Method of Maintaining the Required Values of Surface Roughness and Prediction of Technological Conditions for Cold Sheet Rolling

    NASA Astrophysics Data System (ADS)

    Valíček, J.; Harničárová, M.; Kušnerová, M.; Zavadil, J.; Grznárik, R.

    2014-06-01

    The paper is based on results obtained from topography of surfaces of sheets rolled from deep-drawing steel of the type KOHAL grade 697, non-alloy low-carbon structural steel EN 10263-2:2004 and aluminium. The presented results document correctness of the assumption that the rolling force Froll increases with the increasing reduction Δh and the quality of the rolled surface is improved at the simultaneous increasing of strength of rolled sheets and the decreasing of size of structural grains. The experiment was performed on the two-high rolling stand DUO 210 SVa, which enables only non-continuous technology in contrast to the rolling mill with continuous reduction on one sheet in several degrees on rolling trains, in consequence of which the obtained height parameters of the section are in close correlation with the predicted dependence. Contribution of the work consists in the creation of a mathematical model (algorithm) for predicting technological parameters of the two-high rolling stand DUO 210 SVa at change of the absolute reduction Δh, for example for a deep-drawing steel of the type KOHAL grade 697 and non-alloy lowcarbon structural steel PN EN 10263-2:2004 and aluminium, and also in the development of a method of calculation applicable to any material being rolled in general, because the authors have found that various materials can be differentiated by a derived analytical criterion IKP. This criterion is a function of ratio between the modulus of elasticity of reference material and that of actually rolled material. The reference material is here deep-drawing steel of the type KOHAL grade 697. Verification was carried out by measuring changes of final surface roughness profile and final strength of rolled sheets of the stated materials in relation to reductions and those were compared with theoretically predicted values. It is possible to identify and predict on the basis of this algorithm an instant state of surface topography in respect to variable

  10. Microstructure-Based Constitutive Modeling of TRIP Steel: Prediction of Ductility and Failure Modes under Different Loading Conditions

    SciTech Connect

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

    2009-05-01

    In this study, an advanced micromechanics-based finite element model is developed based on the actual microstructure of a TRIP (TRansformation-Induced Plasticity) 800 steel to model complex deformation behavior of TRIP steels, including its ductile failure behaviors. The evolution of volume fraction of retained austenite during loading and the mechanical properties of the constituent phases of the TRIP 800 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 TRIP 800 under different loading conditions is predicted in the form of plastic strain localization without any prescribed failure criteria for the individual phases. The computational results suggest that the response of the microstructure-based representative volume element (RVE) well represents the overall macroscopic behavior of the deformed TRIP 800 steel under different loading and boundary 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.

  11. Model predictions of realgar precipitation by reaction of As(III) with synthetic Mackinawite under anoxic conditions.

    PubMed

    Gallegos, Tanya J; Han, Young-Soo; Hayes, Kim F

    2008-12-15

    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 x 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. PMID:19174913

  12. 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.

  13. An interval model updating strategy using interval response surface models

    NASA Astrophysics Data System (ADS)

    Fang, Sheng-En; Zhang, Qiu-Hu; Ren, Wei-Xin

    2015-08-01

    Stochastic model updating provides an effective way of handling uncertainties existing in real-world structures. In general, probabilistic theories, fuzzy mathematics or interval analyses are involved in the solution of inverse problems. However in practice, probability distributions or membership functions of structural parameters are often unavailable due to insufficient information of a structure. At this moment an interval model updating procedure shows its superiority in the aspect of problem simplification since only the upper and lower bounds of parameters and responses are sought. To this end, this study develops a new concept of interval response surface models for the purpose of efficiently implementing the interval model updating procedure. The frequent interval overestimation due to the use of interval arithmetic can be maximally avoided leading to accurate estimation of parameter intervals. Meanwhile, the establishment of an interval inverse problem is highly simplified, accompanied by a saving of computational costs. By this means a relatively simple and cost-efficient interval updating process can be achieved. Lastly, the feasibility and reliability of the developed method have been verified against a numerical mass-spring system and also against a set of experimentally tested steel plates.

  14. Pitch strength of regular-interval click trains with different length “runs” of regular intervals

    PubMed Central

    Yost, William A.; Mapes-Riordan, Dan; Shofner, William; Dye, Raymond; Sheft, Stanley

    2009-01-01

    Click trains were generated with first- and second-order statistics following Kaernbach and Demany [J. Acoust. Soc. Am. 104, 2298–2306 (1998)]. First-order intervals are between successive clicks, while second-order intervals are those between every other click. Click trains were generated with a repeating alternation of fixed and random intervals which produce a pitch at the reciprocal of the duration of the fixed interval. The intervals were then randomly shuffled and compared to the unshuffled, alternating click trains in pitch-strength comparison experiments. In almost all comparisons for the first-order interval stimuli, the shuffled-interval click trains had a stronger pitch strength than the unshuffled-interval click trains. The shuffled-interval click trains only produced stronger pitches for second-order interval stimuli when the click trains were unfiltered. Several experimental conditions and an analysis of runs of regular and random intervals in these click trains suggest that the auditory system is sensitive to runs of regular intervals in a stimulus that contains a mix of regular and random intervals. These results indicate that fine-structure regularity plays a more important role in pitch perception than randomness, and that the long-term autocorrelation function or spectra of these click trains are not good predictors of pitch strength. PMID:15957774

  15. 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. PMID:23875922

  16. 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. PMID:22227303

  17. Integrating Genomics with Nutrition Models to Improve the Prediction of Cattle Performance and Carcass Composition under Feedlot Conditions

    PubMed Central

    Tedeschi, Luis O.

    2015-01-01

    Cattle body composition is difficult to model because several factors affect the composition of the average daily gain (ADG) of growing animals. The objective of this study was to identify commercial single nucleotide polymorphism (SNP) panels that could improve the predictability of days on feed (DOF) to reach a target United States Department of Agriculture (USDA) grade given animal, diet, and environmental information under feedyard conditions. The data for this study was comprised of crossbred heifers (n = 681) and steers (n = 836) from commercial feedyards. Eleven molecular breeding value (MBV) scores derived from SNP panels of candidate gene polymorphisms and two-leptin gene SNP (UASMS2 and E2FB) were evaluated. The empty body fat (EBF) and the shrunk body weight (SBW) at 28% EBF (AFSBW) were computed by the Cattle Value Discovery System (CVDS) model using hip height (EBFHH and AFSBWHH) or carcass traits (EBFCT and AFSBWCT) of the animals. The DOFHH was calculated when AFSBWHH and ADGHH were used and DOFCT was calculated when AFSBWCT and ADGCT were used. The CVDS estimates dry matter required (DMR) by individuals fed in groups when observed ADG and AFSBW are provided. The AFSBWCT was assumed more accurate than the AFSBWHH because it was computed using carcass traits. The difference between AFSBWCT and AFSBWHH, DOFCT and DOFHH, and DMR and dry matter intake (DMI) were regressed on the MBV scores and leptin gene SNP to explain the variation. Our results indicate quite a large range of correlations among MBV scores and model input and output variables, but MBV ribeye area was the most strongly correlated with the differences in DOF, AFSBW, and DMI by explaining 8, 13.2 and 6.5%, respectively, of the variation. This suggests that specific MBV scores might explain additional variation of input and output variables used by nutritional models in predicting individual animal performance. PMID:26599759

  18. Reduced intensity conditioning allogeneic stem cell transplantation for Hodgkin’s lymphoma: identification of prognostic factors predicting outcome

    PubMed Central

    Robinson, Stephen P.; Sureda, Anna; Canals, Carmen; Russell, Nigel; Caballero, Dolores; Bacigalupo, Andrea; Iriondo, Arturo; Cook, Gordon; Pettitt, Andrew; Socie, Gerard; Bonifazi, Francesca; Bosi, Alberto; Michallet, Mauricette; Liakopoulou, Effie; Maertens, Johan; Passweg, Jakob; Clarke, Fiona; Martino, Rodrigo; Schmitz, Norbert

    2009-01-01

    Background The role of reduced intensity conditioning allogeneic stem transplantation (RICalloSCT) in the management of patients with Hodgkin’s lymphoma remains controversial. Design and Methods To further define its role we have conducted a retrospective analysis of 285 patients with HL who underwent a RICalloSCT in order to identify prognostic factors that predict outcome. Eighty percent of patients had undergone a prior autologous stem cell transplantation and 25% had refractory disease at transplant. Results Non-relapse mortality was associated with chemorefractory disease, poor performance status, age >45 and transplantation before 2002. For patients with no risk factors the 3-year non-relapse mortality rate was 12.5% compared to 46.2% for patients with 2 or more risk factors. The use of an unrelated donor had no adverse effect on the non-relapse mortality. Acute graft versus host disease (aGVHD) grades II–IV developed in 30% and chronic GVHD in 42%. The development of cGVHD was associated with a lower relapse rate. The disease progression rate at one and five years was 41% and 58.7% respectively and was associated with chemorefractory disease and extent of prior therapy. Donor lymphocyte infusions were administered to 64 patients for active disease of whom 32% showed a clinical response. Eight out of 18 patients receiving donor lymphocyte infusions alone had clinical responses. Progression-free and overall survival were both associated with performance status and disease status at transplant. Patients with neither risk factor had a 3-year PFS and overall survival of 42% and 56% respectively compared to 8% and 25% for patients with one or more risk factors. Relapse within six months of a prior autologous transplant was associated with a higher relapse rate and a lower progression-free. Conclusions This analysis identifies important clinical parameters that may be useful in predicting the outcome of RICaIICalloSCT in Hodgkin’s lymphoma. PMID:19066328

  19. Efficiency characteristics of speed modulated drives at predicted torque conditions for air-to-air heat pumps

    NASA Astrophysics Data System (ADS)

    Rice, C. K.

    Examples of system (motor + inverter drive) efficiencies of two types of adjustable speed control are compared for predicted compressor and indoor blower load profiles. The two classifications are inverter-driven induction motors (IDIMs) and permanent-magnet electronically commutated motors (PM-ECMs). Reference sine-wave-driven induction motor (SWDIM) efficiencies are also given. Available bench data on late 70's IDIM compressor drives are compared to recent data on IDIM and PM-ECM drives. The drive efficiencies are compared over common operating torque requirements for heating and cooling. A modulating heat pump model was used to develop predicted reciprocating compressor torque/drive-frequency mappings and the expected operating torque ranges. The variation in modulating compressor torque requirements is analyzed. Ways to adjust the torque relation for different compressor types and sizing strategies are also discussed. Modulating blower performance data on an early '80s generation modulating heat pump with an IDIM drive (and SWDIM reference drive) were obtained and compared to bench data on recent IDIM and PM-ECM drives under similar torque conditions. In both compressor and blower applications, the combined system efficiency of the PM-ECM drives is nearly equal to or higher than that of the reference SWDIM cases and significantly better than IDIMs available in the late '70s. When compared to more recent IDIMs, the PM-ECM efficiency advantage over IDIM compressors has been reduced 40 to 50 percent between half and nominal speed (3600 rpm) but still remains 14 to 9 percent higher, respectively.

  20. Integrating Genomics with Nutrition Models to Improve the Prediction of Cattle Performance and Carcass Composition under Feedlot Conditions.

    PubMed

    Tedeschi, Luis O

    2015-01-01

    Cattle body composition is difficult to model because several factors affect the composition of the average daily gain (ADG) of growing animals. The objective of this study was to identify commercial single nucleotide polymorphism (SNP) panels that could improve the predictability of days on feed (DOF) to reach a target United States Department of Agriculture (USDA) grade given animal, diet, and environmental information under feedyard conditions. The data for this study was comprised of crossbred heifers (n = 681) and steers (n = 836) from commercial feedyards. Eleven molecular breeding value (MBV) scores derived from SNP panels of candidate gene polymorphisms and two-leptin gene SNP (UASMS2 and E2FB) were evaluated. The empty body fat (EBF) and the shrunk body weight (SBW) at 28% EBF (AFSBW) were computed by the Cattle Value Discovery System (CVDS) model using hip height (EBFHH and AFSBWHH) or carcass traits (EBFCT and AFSBWCT) of the animals. The DOFHH was calculated when AFSBWHH and ADGHH were used and DOFCT was calculated when AFSBWCT and ADGCT were used. The CVDS estimates dry matter required (DMR) by individuals fed in groups when observed ADG and AFSBW are provided. The AFSBWCT was assumed more accurate than the AFSBWHH because it was computed using carcass traits. The difference between AFSBWCT and AFSBWHH, DOFCT and DOFHH, and DMR and dry matter intake (DMI) were regressed on the MBV scores and leptin gene SNP to explain the variation. Our results indicate quite a large range of correlations among MBV scores and model input and output variables, but MBV ribeye area was the most strongly correlated with the differences in DOF, AFSBW, and DMI by explaining 8, 13.2 and 6.5%, respectively, of the variation. This suggests that specific MBV scores might explain additional variation of input and output variables used by nutritional models in predicting individual animal performance. PMID:26599759

  1. Interval analysis method and convex models for impulsive response of structures with uncertain-but-bounded external loads

    NASA Astrophysics Data System (ADS)

    Qiu, Zhiping; Wang, Xiaojun

    2006-06-01

    Two non-probabilistic, set-theoretical methods for determining the maximum and minimum impulsive responses of structures to uncertain-but-bounded impulses are presented. They are, respectively, based on the theories of interval mathematics and convex models. The uncertain-but-bounded impulses are assumed to be a convex set, hyper-rectangle or ellipsoid. For the two non-probabilistic methods, less prior information is required about the uncertain nature of impulses than the probabilistic model. Comparisons between the interval analysis method and the convex model, which are developed as an anti-optimization problem of finding the least favorable impulsive response and the most favorable impulsive response, are made through mathematical analyses and numerical calculations. The results of this study indicate that under the condition of the interval vector being determined from an ellipsoid containing the uncertain impulses, the width of the impulsive responses predicted by the interval analysis method is larger than that by the convex model; under the condition of the ellipsoid being determined from an interval vector containing the uncertain impulses, the width of the interval impulsive responses obtained by the interval analysis method is smaller than that by the convex model.

  2. 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…

  3. Low Impulsive Action, but not Impulsive Choice, Predicts Greater Conditioned Reinforcer Salience and Augmented Nucleus Accumbens Dopamine Release.

    PubMed

    Zeeb, Fiona D; Soko, Ashlie D; Ji, Xiaodong; Fletcher, Paul J

    2016-07-01

    Poor impulse control is associated with an increased propensity to develop an addiction and may contribute to relapse as high impulsive subjects appear to attribute greater salience toward drug-paired stimuli. In these studies, we determined whether trait impulsivity also predicts the desire to obtain natural reward-paired stimuli. Rats trained on the 5-choice serial reaction time task to measure impulsive action (Experiment 1) or a delay-discounting task to measure impulsive choice (Experiment 2) were separated into low, intermediate, or high impulsive action (L-IA, I-IA, H-IA) or choice (L-IC, I-IC, H-IC) groups. The motivation to obtain a conditioned stimulus (CS) paired with water-reward was subsequently determined by measuring responding for the CS as a conditioned reinforcer (CRf). Dopamine release in the nucleus accumbens was also measured using in vivo microdialysis. The effects of amphetamine were assessed on all tests. In Experiment 1, amphetamine increased impulsive action in all groups. L-IA rats initially demonstrated the highest responding for the CRf. Amphetamine increased responding for the CRf and this effect was augmented in L-IA rats. Dopamine release following amphetamine was greatest in L-IA subjects. In Experiment 2, amphetamine increased impulsive choice for L-IC and I-IC rats. However, all groups responded similarly for the CRf and dopamine release was moderately greater in L-IC rats. In conclusion, impulsive choice was unrelated to responding for a CRf. L-IA subjects initially attributed enhanced salience to a CS and exhibited greater dopamine release. Lower dopamine release in H-IA rats could result in reduced reinforcing properties of the CRf. PMID:26781518

  4. [Birth interval differentials in Rwanda].

    PubMed

    Ilinigumugabo, A

    1992-01-01

    Data from the 1983 Rwanda Fertility Survey are the basis for this study of variations in birth intervals. An analysis of the quality of the Rwandan birth data showed it to be relatively good. The life table technique utilized in this study is explained in a section on methodology, which also describes the Rwanda Fertility Survey questionnaires. A comparison of birth intervals in which live born children died before their first birthday or survived the first birthday shows that infant mortality shortens birth intervals by an average of 5 months. The first birth interval was almost 28 months when the oldest child survived, but declined to 23 months when the oldest child died before age 1. The effect of mortality on birth intervals increased with parity, from 5 months for the first birth interval to 5.5 months for the second and third and 6.4 months for subsequent intervals. The differences amounted to 9 or 10 months for women separating at parities under 4 and over 14 months for women separating at parities of 4 or over. Birth intervals generally increased with parity, maternal age, and the duration of the union. But women entering into unions at higher ages had shorter birth intervals. In the absence of infant mortality and dissolution of the union, women attending school beyong the primary level had first birth intervals 6 months shorter on average than other women. Controlling for infant mortality and marital dissolution, women working for wages had average birth intervals of under 2 years for the first 5 births. Father's occupation had a less marked influence on birth intervals. Urban residence was associated with a shortening of the average birth interval by 6 months between the first and second birth and 5 months between the second and third births. In the first 5 births, Tutsi women had birth intervals 1.5 months longer on average than Hutu women. Women in polygamous unions did not have significantly different birth intervals except perhaps among older women

  5. Comparison of a Multimetric Index and a Multivariate Predictive Model for Assessing the Biological Condition of Kentucky Streams

    NASA Astrophysics Data System (ADS)

    Pond, G. J.

    2005-05-01

    There is still debate on the strength of various data analysis tools for assessing biological condition in streams. This study compared two popular assessment approaches (multimetric index and RIVPACS-type O/E model) using macroinvertebrates from Kentucky streams. Data from 557 targeted and randomly selected sites (212 reference, 345 non-reference) sampled between 2000 and 2004 were used in this analysis. The Kentucky Macroinvertebrate Bioassessment Index (MBI) combines seven metrics (total generic richness, EPT generic richness, modified HBI, %Ephemeroptera, %EPT minus Cheumatopsyche, %midges+worms, and %clingers) that are scored by standardizing to the 95th or 5th percentile of the reference distribution and averaged. For comparison, three separate genus-level RIVPACS-type models were constructed (high-, low-, and mixed gradient streams) using four predictive variables (area, latitude, longitude, and week number) and taxa from reference sites. All 3 models preformed well but the low gradient model had the lowest precision. Assessments of non-reference sites based on MBI and O/E scores yielded similar results in terms of discrimination efficiency but the model based on mixed-gradient streams was the least sensitive. Using a subset of data from 84 headwater streams in the Appalachian region, MBI and O/E scores responded almost identically to stressors such as conductivity and habitat degradation.

  6. 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.

  7. Dynamics of combined initial-condition and model-related errors in a Quasi-Geostrophic prediction system

    NASA Astrophysics Data System (ADS)

    Perdigão, R. A. P.; Pires, C. A. L.; Vannitsem, S.

    2009-04-01

    Atmospheric prediction systems are known to suffer from fundamental uncertainties associated with their sensitivity to the initial conditions and with the inaccuracy in the model representation. A formulation for the error dynamics taking into account both these factors and intrinsic properties of the system has been developed in a study by Nicolis, Perdigao and Vannitsem (2008, in press). In the present study that study is generalized to systems of higher complexity. The extended approach admits systems with non-Euclidean metrics, multivariate perturbations, correlated and anisotropic initial errors, including error sources stemming from the data assimilation process. As in the low-order case, the formulation admits small perturbations relative to the attractor of the underlying dynamics and respective parameters, and contemplates the short to intermediate time regime. The underlying system is assumed to be governed by non-linear evolution laws with continuous derivatives, where the variables representing the unperturbed and perturbed models span the same manifold defined by a phase space with the same topological dimension. As a core ilustrative case a three-level Quasi-Geostrophic system with triangular truncation T21 is considered. While some generic features are identified that come in agreement with those seen in lower-order systems, further properties of physical relevance, stemming from the generalizations, are also unveiled.

  8. 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.

  9. Volatility return intervals analysis of the Japanese market

    NASA Astrophysics Data System (ADS)

    Jung, W.-S.; Wang, F. Z.; Havlin, S.; Kaizoji, T.; Moon, H.-T.; Stanley, H. E.

    2008-03-01

    We investigate scaling and memory effects in return intervals between price volatilities above a certain threshold q for the Japanese stock market using daily and intraday data sets. We find that the distribution of return intervals can be approximated by a scaling function that depends only on the ratio between the return interval τ and its mean <τ>. We also find memory effects such that a large (or small) return interval follows a large (or small) interval by investigating the conditional distribution and mean return interval. The results are similar to previous studies of other markets and indicate that similar statistical features appear in different financial markets. We also compare our results between the period before and after the big crash at the end of 1989. We find that scaling and memory effects of the return intervals show similar features although the statistical properties of the returns are different.

  10. 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…

  11. 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…

  12. 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…

  13. A Review of Confidence Intervals.

    ERIC Educational Resources Information Center

    Mauk, Anne-Marie Kimbell

    This paper summarizes information leading to the recommendation that statistical significance testing be replaced, or at least accompanied by, the reporting of effect sizes and confidence intervals. It discusses the use of confidence intervals, noting that the recent report of the American Psychological Association Task Force on Statistical…

  14. 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…

  15. 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.

  16. 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.

  17. Predictive risk stratification model: a progressive cluster-randomised trial in chronic conditions management (PRISMATIC) research protocol

    PubMed Central

    2013-01-01

    Background An ageing population increases demand on health and social care. New approaches are needed to shift care from hospital to community and general practice. A predictive risk stratification tool (Prism) has been developed for general practice that estimates risk of an emergency hospital admission in the following year. We present a protocol for the evaluation of Prism. Methods/Design We will undertake a mixed methods progressive cluster-randomised trial. Practices begin as controls, delivering usual care without Prism. Practices will receive Prism and training randomly, and thereafter be able to use Prism with clinical and technical support. We will compare costs, processes of care, satisfaction and patient outcomes at baseline, 6 and 18 months, using routine data and postal questionnaires. We will assess technical performance by comparing predicted against actual emergency admissions. Focus groups and interviews will be undertaken to understand how Prism is perceived and adopted by practitioners and policy makers. We will model data using generalised linear models and survival analysis techniques to determine whether any differences exist between intervention and control groups. We will take account of covariates and explanatory factors. In the economic evaluation we will carry out a cost-effectiveness analysis to examine incremental cost per emergency admission to hospital avoided and will examine costs versus changes in primary and secondary outcomes in a cost-consequence analysis. We will also examine changes in quality of life of patients across the risk spectrum. We will record and transcribe focus groups and interviews and analyse them thematically. We have received full ethical and R&D approvals for the study and Information Governance Review Panel (IGRP) permission for the use of routine data. We will comply with the CONSORT guidelines and will disseminate the findings at national and international conferences and in peer-reviewed journals

  18. A novel ground surface subsidence prediction model for sub-critical mining in the geological condition of a thick alluvium layer

    NASA Astrophysics Data System (ADS)

    Chang, Zhanqiang; Wang, Jinzhuang; Chen, Mi; Ao, Zurui; Yao, Qi

    2015-06-01

    A substantial number of the coal mines in China are in the geological condition of thick alluvium layer. Under these circumstances, it does not make sense to predict ground surface subsidence and other deformations by using conventional prediction models. This paper presents a novel ground surface subsidence prediction model for sub-critical mining in the geological condition of thick alluvium layer. The geological composition and mechanical properties of thick alluvium is regarded as a random medium, as are the uniformly distributed loads on rock mass; however, the overburden of the rock mass in the bending zone is looked upon as a hard stratum controlling the ground surface subsidence. The different subsidence and displacement mechanisms for the rock mass and the thick alluvium layer are respectively considered and described in this model, which indicates satisfactory performances in a practical prediction case.

  19. 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.

  20. Comparisons of Predictions of the XB-70-1 Longitudinal Stability and Control Derivatives with Flight Results for Six Flight Conditions

    NASA Technical Reports Server (NTRS)

    Wolowicz, C. H.; Yancey, R. B.

    1973-01-01

    Preliminary correlations of flight-determined and predicted stability and control characteristics of the XB-70-1 reported in NASA TN D-4578 were subject to uncertainties in several areas which necessitated a review of prediction techniques particularly for the longitudinal characteristics. Reevaluation and updating of the original predictions, including aeroelastic corrections, for six specific flight-test conditions resulted in improved correlations of static pitch stability with flight data. The original predictions for the pitch-damping derivative, on the other hand, showed better correlation with flight data than the updated predictions. It appears that additional study is required in the application of aeroelastic corrections to rigid model wind-tunnel data and the theoretical determination of dynamic derivatives for this class of aircraft.

  1. Image magnification using interval information.

    PubMed

    Jurio, Aranzazu; Pagola, Miguel; Mesiar, Radko; Beliakov, Gleb; Bustince, Humberto

    2011-11-01

    In this paper, a simple and effective image-magnification algorithm based on intervals is proposed. A low-resolution image is magnified to form a high-resolution image using a block-expanding method. Our proposed method associates each pixel with an interval obtained by a weighted aggregation of the pixels in its neighborhood. From the interval and with a linear K(α) operator, we obtain the magnified image. Experimental results show that our algorithm provides a magnified image with better quality (peak signal-to-noise ratio) than several existing methods. PMID:21632304

  2. 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.

  3. 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). PMID:26724191

  4. 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.

  5. 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.

  6. Interval estimates and their precision

    NASA Astrophysics Data System (ADS)

    Marek, Luboš; Vrabec, Michal

    2015-06-01

    A task very often met in in practice is computation of confidence interval bounds for the relative frequency within sampling without replacement. A typical situation includes preelection estimates and similar tasks. In other words, we build the confidence interval for the parameter value M in the parent population of size N on the basis of a random sample of size n. There are many ways to build this interval. We can use a normal or binomial approximation. More accurate values can be looked up in tables. We consider one more method, based on MS Excel calculations. In our paper we compare these different methods for specific values of M and we discuss when the considered methods are suitable. The aim of the article is not a publication of new theoretical methods. This article aims to show that there is a very simple way how to compute the confidence interval bounds without approximations, without tables and without other software costs.

  7. Simple Interval Timers for Microcomputers.

    ERIC Educational Resources Information Center

    McInerney, M.; Burgess, G.

    1985-01-01

    Discusses simple interval timers for microcomputers, including (1) the Jiffy clock; (2) CPU count timers; (3) screen count timers; (4) light pen timers; and (5) chip timers. Also examines some of the general characteristics of all types of timers. (JN)

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

    PubMed Central

    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. PMID:27478491

  9. 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.

  10. Using EPIC v. 3060 and the Soil Conditioning Index to predict soil organic carbon in cotton production systems of the southeastern USA

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Soil Conditioning Index (SCI) administered by the USDA-NRCS predicts the consequences of tillage practices and cropping systems on trends in SOC but does not represent an actual quantity or accumulation rate of SOC. We calibrated the EPIC model for three major land resource areas in the southea...

  11. 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.

  12. 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.

  13. Generalized Confidence Intervals and Fiducial Intervals for Some Epidemiological Measures.

    PubMed

    Bebu, Ionut; Luta, George; Mathew, Thomas; Agan, Brian K

    2016-01-01

    For binary outcome data from epidemiological studies, this article investigates the interval estimation of several measures of interest in the absence or presence of categorical covariates. When covariates are present, the logistic regression model as well as the log-binomial model are investigated. The measures considered include the common odds ratio (OR) from several studies, the number needed to treat (NNT), and the prevalence ratio. For each parameter, confidence intervals are constructed using the concepts of generalized pivotal quantities and fiducial quantities. Numerical results show that the confidence intervals so obtained exhibit satisfactory performance in terms of maintaining the coverage probabilities even when the sample sizes are not large. An appealing feature of the proposed solutions is that they are not based on maximization of the likelihood, and hence are free from convergence issues associated with the numerical calculation of the maximum likelihood estimators, especially in the context of the log-binomial model. The results are illustrated with a number of examples. The overall conclusion is that the proposed methodologies based on generalized pivotal quantities and fiducial quantities provide an accurate and unified approach for the interval estimation of the various epidemiological measures in the context of binary outcome data with or without covariates. PMID:27322305

  14. Generalized Confidence Intervals and Fiducial Intervals for Some Epidemiological Measures

    PubMed Central

    Bebu, Ionut; Luta, George; Mathew, Thomas; Agan, Brian K.

    2016-01-01

    For binary outcome data from epidemiological studies, this article investigates the interval estimation of several measures of interest in the absence or presence of categorical covariates. When covariates are present, the logistic regression model as well as the log-binomial model are investigated. The measures considered include the common odds ratio (OR) from several studies, the number needed to treat (NNT), and the prevalence ratio. For each parameter, confidence intervals are constructed using the concepts of generalized pivotal quantities and fiducial quantities. Numerical results show that the confidence intervals so obtained exhibit satisfactory performance in terms of maintaining the coverage probabilities even when the sample sizes are not large. An appealing feature of the proposed solutions is that they are not based on maximization of the likelihood, and hence are free from convergence issues associated with the numerical calculation of the maximum likelihood estimators, especially in the context of the log-binomial model. The results are illustrated with a number of examples. The overall conclusion is that the proposed methodologies based on generalized pivotal quantities and fiducial quantities provide an accurate and unified approach for the interval estimation of the various epidemiological measures in the context of binary outcome data with or without covariates. PMID:27322305

  15. 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.

  16. Nomenclature, categorization and usage of formulae to adjust QT interval for heart rate

    PubMed Central

    Rabkin, Simon W; Cheng, Xin Bo

    2015-01-01

    Assessment of the QT interval on a standard 12 lead electrocardiogram is of value in the recognition of a number of conditions. A critical part of its use is the adjustment for the effect of heart rate on QT interval. A systematic search was conducted to identify studies that proposed formulae to standardize the QT interval by heart rate. A nomenclature was developed for current and subsequent equations based on whether they are corrective (QTc) or predictive (QTp). QTc formulae attempt to separate the dependence of the length of the QT interval from the length of the RR interval. QTp formulae utilize heart rate and the output QTp is compared to the uncorrected QT interval. The nomenclature consists of the first letter of the first author’s name followed by the next two consonance (whenever possible) in capital letters; with subscripts in lower case alphabetical letter if the first author develops more than one equation. The single exception was the Framingham equation, because this cohort has developed its own “name” amongst cardiovascular studies. Equations were further categorized according to whether they were linear, rational, exponential, logarithmic, or power based. Data show that a person’s QT interval adjusted for heart rate can vary dramatically with the different QTc and QTp formulae depending on the person’s heart rate and QT interval. The differences in the QT interval adjustment equations encompasses values that are considered normal or significant prolonged. To further compare the equations, we considered that the slope of QTc versus heart rate should be zero if there was no correlation between QT and heart rate. Reviewing a sample of 107 patient ECGs from a hospital setting, the rank order of the slope - from best (closest to zero) to worst was QTcDMT, QTcRTHa, QTcHDG, QTcGOT, QTcFRM, QTcFRD, QTcBZT and QTcMYD. For two recent formulae based on large data sets specifically QTcDMT and QTcRTHa, there was no significant deviation of the slope

  17. Nomenclature, categorization and usage of formulae to adjust QT interval for heart rate.

    PubMed

    Rabkin, Simon W; Cheng, Xin Bo

    2015-06-26

    Assessment of the QT interval on a standard 12 lead electrocardiogram is of value in the recognition of a number of conditions. A critical part of its use is the adjustment for the effect of heart rate on QT interval. A systematic search was conducted to identify studies that proposed formulae to standardize the QT interval by heart rate. A nomenclature was developed for current and subsequent equations based on whether they are corrective (QTc) or predictive (QTp). QTc formulae attempt to separate the dependence of the length of the QT interval from the length of the RR interval. QTp formulae utilize heart rate and the output QTp is compared to the uncorrected QT interval. The nomenclature consists of the first letter of the first author's name followed by the next two consonance (whenever possible) in capital letters; with subscripts in lower case alphabetical letter if the first author develops more than one equation. The single exception was the Framingham equation, because this cohort has developed its own "name" amongst cardiovascular studies. Equations were further categorized according to whether they were linear, rational, exponential, logarithmic, or power based. Data show that a person's QT interval adjusted for heart rate can vary dramatically with the different QTc and QTp formulae depending on the person's heart rate and QT interval. The differences in the QT interval adjustment equations encompasses values that are considered normal or significant prolonged. To further compare the equations, we considered that the slope of QTc versus heart rate should be zero if there was no correlation between QT and heart rate. Reviewing a sample of 107 patient ECGs from a hospital setting, the rank order of the slope - from best (closest to zero) to worst was QTcDMT, QTcRTHa, QTcHDG, QTcGOT, QTcFRM, QTcFRD, QTcBZT and QTcMYD. For two recent formulae based on large data sets specifically QTcDMT and QTcRTHa, there was no significant deviation of the slope from zero

  18. Improvement in the prediction of solar wind conditions using near-real time solar magnetic field updates

    NASA Astrophysics Data System (ADS)

    Arge, C. N.; Pizzo, V. J.

    2000-05-01

    The Wang-Sheeley model is an empirical model that can predict the background solar wind speed and interplanetary magnetic field (IMF) polarity. We make a number of modifications to the basic technique that greatly improve the performance and reliability of the model. First, we establish a continuous empirical function that relates magnetic expansion factor to solar wind velocity at the source surface. Second, we propagate the wind from the source surface to the Earth using the assumption of radial streams and a simple scheme to account for their interactions. Third, we develop and apply a method for identifying and removing problematic magnetograms from the Wilcox Solar Observatory (WSO). Fourth, we correct WSO line-of-sight magnetograms for polar field strength modulation effects that result from the annual variation in the solar b angle. Fifth, we explore a number of techniques to optimize construction of daily updated synoptic maps from the WSO magnetograms. We report on a comprehensive statistical analysis comparing Wang-Sheeley model predictions with the WIND satellite data set during a 3-year period centered about the May 1996 solar minimum. The predicted and observed solar wind speeds have a statistically significant correlation (~0.4) and an average fractional deviation of 0.15. When a single (6-month) period with large data gaps is excluded from the comparison, the solar wind speed is correctly predicted to within 10-15%. The IMF polarity is correctly predicted ~75% of the time. The solar wind prediction technique presented here has direct applications to space weather research and forecasting.

  19. RESEARCH TO PREDICT CHANGES IN WATERSHED PHYSICAL, CHEMICAL, BIOLOGICAL AND ECOLOGICAL CONDITIONS RESULTING FROM MULTIPLE STRESSORS. AN INTEGRATED APPROACH.

    EPA Science Inventory

    The goal of environmental management must be to achieve acceptable sustainability of ecological resources. To achieve this goal there is a need to understand and predict the relationship of ecosystem response to the magnitude and timing of anthropogenic and natural stresses. The ...

  20. 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.

  1. Uniform Continuity on Unbounded Intervals

    ERIC Educational Resources Information Center

    Pouso, Rodrigo Lopez

    2008-01-01

    We present a teaching approach to uniform continuity on unbounded intervals which, hopefully, may help to meet the following pedagogical objectives: (i) To provide students with efficient and simple criteria to decide whether a continuous function is also uniformly continuous; and (ii) To provide students with skill to recognize graphically…

  2. 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.

  3. Flash flood prediction using an uncalibrated hydrological model and radar rainfall data in a Mediterranean watershed under changing hydrological conditions

    NASA Astrophysics Data System (ADS)

    Rozalis, Shahar; Morin, Efrat; Yair, Yoav; Price, Colin

    2010-11-01

    SummaryFlash floods cause some of the most severe natural disasters in Europe but Mediterranean areas are especially vulnerable. They can cause devastating damage to property, infrastructures and loss of human life. The complexity of flash flood generation processes and their dependency on different factors related to watershed properties and rainfall characteristics make flash flood prediction a difficult task. In this study, as part of the EU-FLASH project, we used an uncalibrated hydrological model to simulate flow events in a 27 km2 Mediterranean watershed in Israel to analyze and better understand the various factors influencing flows. The model is based on the well-known SCS curve number method for rainfall-runoff calculations and on the kinematic wave method for flow routing. Existing data available from maps, GIS and field studies were used to define model parameters, and no further calibration was conducted to obtain a better fit between computed and observed flow data. The model rainfall input was obtained from the high temporal and spatial resolution radar data adjusted to rain gauges. Twenty flow events that occurred within the study area over a 15 year period were analyzed. The model shows a generally good capability in predicting flash flood peak discharge in terms of their general level, classified as low, medium or high (all high level events were correctly predicted). It was found that the model mainly well predicts flash floods generated by intense, short-lived convective storm events while model performances for low and moderate flows generated by more widespread winter storms were quite poor. The degree of urban development was found to have a large impact on runoff amount and peak discharge, with higher sensitivity of moderate and low flow events relative to high flows. Flash flood generation was also found to be very sensitive to the temporal distribution of rain intensity within a specific storm event.

  4. A conditional predictive p-value to compare a multinomial with an overdispersed multinomial in the analysis of T-cell populations.

    PubMed

    Pei, Qinglin; Zuleger, Cindy L; Macklin, Michael D; Albertini, Mark R; Newton, Michael A

    2014-01-01

    Immunological experiments that record primary molecular sequences of T-cell receptors produce moderate to high-dimensional categorical data, some of which may be subject to extra-multinomial variation caused by technical constraints of cell-based assays. Motivated by such experiments in melanoma research, we develop a statistical procedure for testing the equality of two discrete populations, where one population delivers multinomial data and the other is subject to a specific form of overdispersion. The procedure computes a conditional-predictive p-value by splitting the data set into two, obtaining a predictive distribution for one piece given the other, and using the observed predictive ordinate to generate a p-value. The procedure has a simple interpretation, requires fewer modeling assumptions than would be required of a fully Bayesian analysis, and has reasonable operating characteristics as evidenced empirically and by asymptotic analysis. PMID:24096387

  5. Imagining life with an ostomy: Does a video intervention improve quality-of-life predictions for a medical condition that may elicit disgust?☆

    PubMed Central

    Angott, Andrea M.; Comerford, David A.; Ubel, Peter A.

    2014-01-01

    Objective To test a video intervention as a way to improve predictions of mood and quality-of-life with an emotionally evocative medical condition. Such predictions are typically inaccurate, which can be consequential for decision making. Method In Part 1, people presently or formerly living with ostomies predicted how watching a video depicting a person changing his ostomy pouch would affect mood and quality-of-life forecasts for life with an ostomy. In Part 2, participants from the general public read a description about life with an ostomy; half also watched a video depicting a person changing his ostomy pouch. Participants’ quality-of-life and mood forecasts for life with an ostomy were assessed. Results Contrary to our expectations, and the expectations of people presently or formerly living with ostomies, the video did not reduce mood or quality-of-life estimates, even among participants high in trait disgust sensitivity. Among low-disgust participants, watching the video increased quality-of-life predictions for ostomy. Conclusion Video interventions may improve mood and quality-of-life forecasts for medical conditions, including those that may elicit disgust, such as ostomy. Practice implications Video interventions focusing on patients’ experience of illness continue to show promise as components of decision aids, even for emotionally charged health states such as ostomy. PMID:23177398

  6. Effect of the Dead Sea-Red Sea canal modelling on the prediction of the Dead Sea conditions

    NASA Astrophysics Data System (ADS)

    Asmar, B. N.; Ergenzinger, Peter

    2003-06-01

    A project to link the Dead Sea to the Red Sea via a canal is undergoing extensive study. In previous works, a generalized mathematical model describing the state of the Dead Sea and a simulation model to implement it have been developed. The model is extended to include the proposed canal project and investigates two alternative modelling canal scenarios: (1) introducing the canal water inflow into the bottom layer or (2) the top layer of the sea. The predicted general effects of the canal are the restoration of the water level of the sea to pre-1970s level; an increase in the total evaporation rate and a decrease in the top layer salinity. Implementing scenario 1, the model predicts that: the water level of the Dead Sea will exceed the desired level design value and therefore shorter filling time can be used; seasonal stratification will persist; total evaporation rate will increase Modestly; there will a small decrease in the salinity of the top layer but a substantial decrease in the salinity of the bottom layer, which will hurt industries severely; there will be a continuation of seasonal crystallization of aragonite and gypsum. Implementing scenario 2 the model predicts that: the water level of the Dead Sea will be maintained at the desired level design value; stratification will be re-established, with the formation of a permanent two-layer system; there will be a substantial increase in the total evaporation rate; the salinity of the top layer will decrease significantly but there will be continuous slower salinity increase in the bottom layer; the crystallization of aragonite will cease, but seasonal gypsum crystallization can be expected to continue as soon as the filling period ends and the canal shifts into normal operation.

  7. Drug discrimination in rats under concurrent variable-interval variable-interval schedules.

    PubMed Central

    McMillan, D E; Hardwick, W C

    2000-01-01

    Eight rats were trained to discriminate pentobarbital from saline under a concurrent variable-interval (VI) VI schedule, on which responses on the pentobarbital-biased lever after pentobarbital were reinforced under VI 20 s and responses on the saline-biased lever were reinforced under VI 80 s. After saline, the reinforcement contingencies programmed on the two levers were reversed. The rats made 62.3% of their responses on the pentobarbital-biased lever after pentobarbital and 72.2% on the saline-biased lever after saline, both of which are lower than predicted by the matching law. When the schedule was changed to concurrent VI 50 s VI 50 s for test sessions with saline and the training dose of pentobarbital, responding on the pentobarbital-biased lever after the training dose of pentobarbital and on the saline-biased lever after saline became nearly equal, even during the first 2 min of the session, suggesting that the presence or absence of the training drug was exerting minimal control over responding and making the determination of dose-effect relations of drugs difficult to interpret. When the pentobarbital dose-response curve was determined under the concurrent VI 50-s VI 50-s schedule, responding was fairly evenly distributed on both levers for most rats. Therefore, 6 additional rats were trained to respond under a concurrent VI 60-s VI 240-s schedule. Under this schedule, the rats made 62.6% of their responses on the pentobarbital-biased lever after pentobarbital and 73.5% of their responses on the saline-biased lever after saline, which also is lower than the percentages predicted by perfect matching. When the schedule was changed to a concurrent VI 150-s VI 150-s schedule for 5-min test sessions with additional drugs, the presence or absence of pentobarbital continued to control responding in most rats, and it was possible to generate graded dose-response curves for pentobarbital and other drugs using the data from these 5-min sessions. The dose

  8. 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.

  9. AcconPred: Predicting Solvent Accessibility and Contact Number Simultaneously by a Multitask Learning Framework under the Conditional Neural Fields Model

    PubMed Central

    Ma, Jianzhu; Wang, Sheng

    2015-01-01

    Motivation. The solvent accessibility of protein residues is one of the driving forces of protein folding, while the contact number of protein residues limits the possibilities of protein conformations. The de novo prediction of these properties from protein sequence is important for the study of protein structure and function. Although these two properties are certainly related with each other, it is challenging to exploit this dependency for the prediction. Method. We present a method AcconPred for predicting solvent accessibility and contact number simultaneously, which is based on a shared weight multitask learning framework under the CNF (conditional neural fields) model. The multitask learning framework on a collection of related tasks provides more accurate prediction than the framework trained only on a single task. The CNF method not only models the complex relationship between the input features and the predicted labels, but also exploits the interdependency among adjacent labels. Results. Trained on 5729 monomeric soluble globular protein datasets, AcconPred could reach 0.68 three-state accuracy for solvent accessibility and 0.75 correlation for contact number. Tested on the 105 CASP11 domain datasets for solvent accessibility, AcconPred could reach 0.64 accuracy, which outperforms existing methods. PMID:26339631

  10. Fourier Analysis of Musical Intervals

    NASA Astrophysics Data System (ADS)

    LoPresto, Michael C.

    2008-11-01

    Use of a microphone attached to a computer to capture musical sounds and software to display their waveforms and harmonic spectra has become somewhat commonplace. A recent article in The Physics Teacher aptly demonstrated the use of MacScope2 in just such a manner as a way to teach Fourier analysis.3 A logical continuation of this project is to use MacScope not just to analyze the Fourier composition of musical tones but also musical intervals.

  11. 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. PMID:23958006

  12. Improved central confidence intervals for the ratio of Poisson means

    NASA Astrophysics Data System (ADS)

    Cousins, R. D.

    The problem of confidence intervals for the ratio of two unknown Poisson means was "solved" decades ago, but a closer examination reveals that the standard solution is far from optimal from the frequentist point of view. We construct a more powerful set of central confidence intervals, each of which is a (typically proper) subinterval of the corresponding standard interval. They also provide upper and lower confidence limits which are more restrictive than the standard limits. The construction follows Neyman's original prescription, though discreteness of the Poisson distribution and the presence of a nuisance parameter (one of the unknown means) lead to slightly conservative intervals. Philosophically, the issue of the appropriateness of the construction method is similar to the issue of conditioning on the margins in 2×2 contingency tables. From a frequentist point of view, the new set maintains (over) coverage of the unknown true value of the ratio of means at each stated confidence level, even though the new intervals are shorter than the old intervals by any measure (except for two cases where they are identical). As an example, when the number 2 is drawn from each Poisson population, the 90% CL central confidence interval on the ratio of means is (0.169, 5.196), rather than (0.108, 9.245). In the cited literature, such confidence intervals have applications in numerous branches of pure and applied science, including agriculture, wildlife studies, manufacturing, medicine, reliability theory, and elementary particle physics.

  13. Comparative study of the linear solvation energy relationship, linear solvent strength theory, and typical-conditions model for retention prediction in reversed-phase liquid chromatography.

    PubMed

    Wang, Aosheng; Carr, Peter W

    2002-08-01

    This paper describes two new retention models for predicting retention under different reversed-phase liquid chromatography (RPLC) conditions. The first one is a global linear solvation energy relationship (LSER) that expresses retention as a function of both solute LSER descriptors and mobile phase composition. The second is a so-called "typical-conditions model" that expresses retention under a given chromatographic condition as a linear function of retention under different so-called "typical" conditions. The global LSER was derived by combining the local LSER model and the linear solvent strength theory (LSST) of RPLC. Compared to local LSER and the LSST models, the global LSER model requires far fewer retention measurements for calibrating the model when different solutes and different mobile phase compositions are involved. Its fitting performance is equal to the local LSER model but worse than that of LSST. The poor fit of the global LSER results primarily from the local LSER model and not from the LSST model. The typical-conditions model (TCM) was developed based on a concept of multivariate space that is conceptually compatible with LSER. However, no LSER descriptors are used in the TCM approach. The number of input conditions needed in the typical-conditions model is determined by the chemical diversity of the solutes and the conditions involved. Principal component analysis (PCA) and iterative key set factor analysis (IKSFA) were used to find the number of typical conditions needed for a given data set. Compared to LSER, LSST, and global LSER, the typical-conditions model is more precise and requires fewer retention measurements for calibrating the model when different solutes and different stationary and/or mobile phases are involved. PMID:12236532

  14. Developing a large-scale model to predict the effects of land use and climatic variation on the biological condition of USA streams and rivers

    NASA Astrophysics Data System (ADS)

    Hill, R. A.; Weber, M.; Leibowitz, S. G.; Olsen, A. R.

    2014-12-01

    The US EPA's National Rivers and Streams Assessment (NRSA) uses spatially balanced sampling to estimate the proportion of streams within the continental US (CONUS) that fail to support healthy biological communities. However, to manage these systems, we also must understand how human land use alters stream communities from their natural condition and how natural factors, such as climate, interact with these effects. We used random forest modeling and data from 1353 streams that NRSA determined to be in "good" or "poor" biological condition (BC) to predict the probable BC of nearly 5.4 million km of stream (National Hydrography Dataset) within the CONUS. BC was best predicted by 5 natural factors (mean discharge, mean annual air temperature [AT], soil water content, topography, major ecoregion) and 2 riparian factors that are easily altered by humans (% riparian urbanization [%Urb], % riparian forest [%Fst] cover). The model correctly predicted BC for 74% of sites, but predicted poor BC slightly more accurately (76%) than good BC (71%). Initial results showed that probability of good BC declined rapidly with increasing %Urb, but this effect leveled off in streams with >7 %Urb. Likewise, probability of good BC increased in streams with >45 %Fst. This model can be used to generate hypotheses to guide future research and test restoration scenarios. For example, BC had a U-shaped relationship with AT, with poorest BCs predicted between 10-15°C. Plots suggested a strong AT-%Fst interaction, where higher %Fst values mitigated this U-shaped response of BC to AT. These ATs correspond to latitudes that receive the greatest combination of solar radiation intensity and duration in July, and we hypothesize that thermal alteration due to riparian disturbance may be negatively affecting BC in these streams. Finally, simulations suggested that restoring riparian forests could increase the number of streams achieving good BC by 60%, and may represent a critical management tool.

  15. 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.

  16. Improving prediction of conditions that modulate dengue fever risks in Yucatán, México.

    NASA Astrophysics Data System (ADS)

    Laureano-Rosario, A. E.; Garcia-Rejon, J. E.; Gomez-Carro, S.; Farfan-Ale, J.; Muller-Karger, F. E.

    2015-12-01

    Accurately predicting vector-borne diseases is essential for communities everywhere around the world. Yet this is a difficult task, even in areas where annual epidemics occur. The primary vector for dengue virus disease (DENV) is Aedes aegypti. This is a tropical-subtropical mosquito that proliferates in urban areas. Precipitation and increased temperatures are known to promote growth, reproduction and transmission of DENV. This study assesses potential health risks on coastal communities in the northwest Yucatan Peninsula, Mexico. We studied the relation between DENV incidences and environmental data. We hypothesized that environmental parameters such as rainfall, sea surface temperature (SST), air temperature, humidity, and past DENV cases are the primary drivers of DENV incidences. We collected DENV data from the National Health Information System and demographic data from the National Institute of Statistics and Geography. Precipitation and air temperature were obtained from the National Water Commission. SST was derived from the NOAA Advanced Very High Resolution Radiometer (AVHRR) satellite sensor. In addition, incidence of DENV cases per year was calculated. Multiple regression analyses show that previous DENV cases, minimum air temperature, humidity, and precipitation are positively related to DENV cases and explain 82% of the variation, with 77% explained by previous DENV cases (cases that took place 2-weeks before the target). A second regression model without the previous DENV cases showed 30% of the variation explained by humidity and precipitation (p<0.05). Satellite-derived SST was also included to test whether the percent variation of DENV explained increased. These results imply that if these environmental variables continue to increase with time, the trend of DENV cases will also increase. This study suggests that it is possible to significantly improve DENV prevention and prediction of potential outcomes in Yucatan using remote sensing data.

  17. 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.

  18. 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…

  19. 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

  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. PMID:22937636

  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. Prediction of future asset prices

    NASA Astrophysics Data System (ADS)

    Seong, Ng Yew; Hin, Pooi Ah; Ching, Soo Huei

    2014-12-01

    This paper attempts to incorporate trading volumes as an additional predictor for predicting asset prices. Denoting r(t) as the vector consisting of the time-t values of the trading volume and price of a given asset, we model the time-(t+1) asset price to be dependent on the present and l-1 past values r(t), r(t-1), ....., r(t-1+1) via a conditional distribution which is derived from a (2l+1)-dimensional power-normal distribution. A prediction interval based on the 100(α/2)% and 100(1-α/2)% points of the conditional distribution is then obtained. By examining the average lengths of the prediction intervals found by using the composite indices of the Malaysia stock market for the period 2008 to 2013, we found that the value 2 appears to be a good choice for l. With the omission of the trading volume in the vector r(t), the corresponding prediction interval exhibits a slightly longer average length, showing that it might be desirable to keep trading volume as a predictor. From the above conditional distribution, the probability that the time-(t+1) asset price will be larger than the time-t asset price is next computed. When the probability differs from 0 (or 1) by less than 0.03, the observed time-(t+1) increase in price tends to be negative (or positive). Thus the above probability has a good potential of being used as a market indicator in technical analysis.

  3. Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions.

    PubMed

    Zuñiga, Cristal; Li, Chien-Ting; Huelsman, Tyler; Levering, Jennifer; Zielinski, Daniel C; McConnell, Brian O; Long, Christopher P; Knoshaug, Eric P; Guarnieri, Michael T; Antoniewicz, Maciek R; Betenbaugh, Michael J; Zengler, Karsten

    2016-09-01

    The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. PMID:27372244

  4. Costs, effects and implementation of routine data emergency admission risk prediction models in primary care for patients with, or at risk of, chronic conditions: a systematic review protocol

    PubMed Central

    Kingston, Mark Rhys; Evans, Bridie Angela; Nelson, Kayleigh; Hutchings, Hayley; Russell, Ian

    2016-01-01

    Introduction Emergency admission risk prediction models are increasingly used to identify patients, typically with one or more chronic conditions, for proactive management in primary care to avoid admissions, save costs and improve patient experience. Aim To identify and review the published evidence on the costs, effects and implementation of emergency admission risk prediction models in primary care for patients with, or at risk of, chronic conditions. Methods We shall search for studies of healthcare interventions using routine data-generated emergency admission risk models. We shall report: the effects on emergency admissions and health costs; clinician and patient views; and implementation findings. We shall search ASSIA, CINAHL, the Cochrane Library, HMIC, ISI Web of Science, MEDLINE and Scopus from 2005, review references in and citations of included articles, search key journals and contact experts. Study selection, data extraction and quality assessment will be performed by two independent reviewers. Ethics and dissemination No ethical permissions are required for this study using published data. Findings will be disseminated widely, including publication in a peer-reviewed journal and through conferences in primary and emergency care and chronic conditions. We judge our results will help a wide audience including primary care practitioners and commissioners, and policymakers. Trial registration number CRD42015016874; Pre-results. PMID:26932140

  5. 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.

  6. The use of laboratory scale reactors to predict sensitivity to changes in operating conditions for full-scale anaerobic digestion treating municipal sewage sludge.

    PubMed

    McLeod, James D; Othman, Maazuza Z; Beale, David J; Joshi, Deepak

    2015-01-01

    Anaerobic digestion of sewage sludge is highly complex and prone to inhibition, which can cause major issues for digester operators. The result is that there have been numerous investigations into changes in operational conditions, however to date all have focused on the qualitative sensitivities, neglecting the quantitative. This study therefore aimed to determine the quantitative sensitivities by using factorial design of experiments and small semi continuous reactors. Analysis showed total and volatile solids removals are chiefly influenced by retention time, with 79% and 59% of the observed results being attributed to retention time respectively, whereas biogas was mainly influenced by loading rate, 38%, and temperature, 22%. Notably the regression model fitted to the experimental data predicted full-scale performance with a high level of precision, indicating that small reactors are subject to the same sensitivity of full-scale digesters and thus can be used to predict changes loading, retention time, and temperature. PMID:25918031

  7. 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. PMID:22981571

  8. 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.

  9. Simple blood tests as predictive markers of disease severity and clinical condition in patients with venous insufficiency.

    PubMed

    Karahan, Oguz; Yavuz, Celal; Kankilic, Nazim; Demirtas, Sinan; Tezcan, Orhan; Caliskan, Ahmet; Mavitas, Binali

    2016-09-01

    Chronic venous insufficiency (CVI) is a progressive inflammatory disease. Because of its inflammatory nature, several circulating markers were investigated for predicting disease progression. We aimed to investigate simple inflammatory blood markers as predictors of clinical class and disease severity in patients with CVI. Eighty patients with CVI were divided into three groups according to clinical class (grade 1, 2 and 3) and score of disease severity (mild, moderate and severe). The basic inflammatory blood markers [neutrophil, lymphocyte, mean platelet volume (MPV), white blood cell (WBC), platelet, albumin, D-dimer, fibrinogen, fibrinogen to albumin ratio, and neutrophil to lymphocyte ratio] were investigated in each group. Serum neutrophil, lymphocyte, MPV, platelet count, D-dimer and neutrophil to lymphocyte ratio levels were similar among the groups (P > 0.05). Although the serum WBC levels were significant in the clinical severity groups (P < 0.05), it was useless to separate each severity class. However, albumin, fibrinogen and the fibrinogen to albumin ratio were significant predictors of clinical class and disease severity. Especially, the fibrinogen to albumin ratio was detected as an independent indicator for a clinical class and disease severity with high sensitivity and specificity (75% sensitivity and 87.5% specificity for clinical class and 90% sensitivity and 88.3% specificity for disease severity). Serum fibrinogen and albumin levels can be useful parameters to determine clinical class and disease severity in patients with CVI. Moreover, the fibrinogen to albumin ratio is a more sensitive and specific predictor of the progression of CVI. PMID:26650463

  10. Prediction of Meteorological Conditions for the Mars Science Laboratory Rover Curiosity and comparisons with the Rover Environmental Monitoring Station (REMS) measurements

    NASA Astrophysics Data System (ADS)

    Pla-García, Jorge; Rafkin, Scot; Martín-Torres, Javier; Elvira-Gómez, Javier; Lepinette, Alain; Kahanpää, Henrik; Rodríguez-Manfredi, Jose; Navarro, Sara; Sebastián, Eduardo

    2013-04-01

    The Mars Regional Atmospheric Modeling System (MRAMS) is applied to the Gale Crater region, the landing site of the Mars Science Laboratory (MSL) Rover Curiosity. The landing site within Gale Crater is at one of the lowest elevation locations between the crater rim and the ~4 km high central mound known as Mt. Sharp. As Curiosity heads toward its long term target of Mt. Sharp, the meteorological conditions are expected to change due to the increasing influence of topographically-induced thermal circulations that have been predicted by numerous previous studies [1, 2 ,3, 4]. For the first time ever, these mesoscale model predictions of slope flows can be validated against the meteorological data that is currently being collected by the Rover Environmental Monitoring Station (REMS) [5]. We first provide a comparison of MRAMS predictions (pressure, temperature, winds, and ground temperature) to the REMS data available near the season of landing (~LS 150-200) in order to provide a baseline of model performance, and then we provide predictions of the meteorological conditions as a function of season and expected location of the rover as a function of time. Acknowledgements: JP-G and FJM-T are supported by Economy and Competitivity Ministry (AYA2011-25720). S. R. is supported by the MSL Project at JPL. References: [1] Rafkin, S. C. R., and T. I. Michaels (2003), J. Geophys. Res., 108(E12), 8091. [2] Michaels, T. I., and S. C. R. Rafkin (2008), J. Geophys. Res.-Planets, 113. [3] Toigo, A. D., and M. I. Richardson (2003), J. Geophys. Res., 108(E12), 8092. [4] Tyler, D., J. R. Barnes, and E. D. Skyllingstad (2008), J. Geophys. Res.-Planets, 113(E8). [5] Gómez-Elvira, J., et al. (2012), Space Science Reviews, 170(1-4), 583-640.

  11. 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.

  12. 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.

  13. Weather conditions and visits to the medical wing of emergency rooms in a metropolitan area during the warm season in Israel: a predictive model.

    PubMed

    Novikov, Ilya; Kalter-Leibovici, Ofra; Chetrit, Angela; Stav, Nir; Epstein, Yoram

    2012-01-01

    Global climate changes affect health and present new challenges to healthcare systems. The aim of the present study was to analyze the pattern of visits to the medical wing of emergency rooms (ERs) in public hospitals during warm seasons, and to develop a predictive model that will forecast the number of visits to ERs 2 days ahead. Data on daily visits to the ERs of the four largest medical centers in the Tel-Aviv metropolitan area during the warm months of the year (April-October, 2001-2004), the corresponding daily meteorological data, daily electrical power consumption (a surrogate marker for air-conditioning), air-pollution parameters, and calendar information were obtained and used in the analyses. The predictive model employed a time series analysis with transitional Poisson regression. The concise multivariable model was highly accurate (r (2) = 0.819). The contribution of mean daily temperature was small but significant: an increase of 1°C in ambient temperature was associated with a 1.47% increase in the number of ER visits (P < 0.001). An increase in electrical power consumption significantly attenuated the effect of weather conditions on ER visits by 4% per 1,000 MWh (P < 0.001). Higher daily mean SO(2) concentrations were associated with a greater number of ER visits (1% per 1 ppb increment; P = 0.017). Calendar data were the main predictors of ER visits (r (2) = 0.794). The predictive model was highly accurate in forecasting the number of visits to ERs 2 days ahead. The marginal effect of temperature on the number of ER visits can be attributed to behavioral adaptations, including the use of air-conditioning. PMID:21267601

  14. 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. PMID:26439788

  15. Lifetime and failure strain prediction for material subjected to non-stationary tensile loading conditions: applications to Zircaloy - 4. [Monkman-Grant relationship

    SciTech Connect

    Bocek, M.

    1982-01-01

    The life fraction rule (LFR) is used to calculate the lifetime of materials subjected to stress and temperature ramp loading. The solutions for the individual nonstationary temperature and stress loading conditions can be applied to predict also the lifetime of structures loaded by superimposed ramps solely on the basis of normal 'iso'-stress rupture data. The concept is applied to tensional stress and temperature cycling as well. As compared with the peculiarities of the problem, the agreement between experiments and calculations is encouraging. 16 refs.

  16. 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.

  17. A Novel Housing-Based Socioeconomic Measure Predicts Hospitalization and Multiple Chronic Conditions in a Community Population

    PubMed Central

    Takahashi, Paul Y.; Ryu, Euijung; Hathcock, Matthew A.; Olson, Janet E.; Bielinski, Suzette J.; Cerhan, James R.; Rand-Weaver, Jennifer; Juhn, Young J.

    2016-01-01

    Background Socioeconomic status (SES) is an important predictor for outcomes of chronic diseases. However, it is often unavailable in clinical data. We sought to determine whether an individual housing-based SES index termed HOUSES can influence the likelihood of multiple chronic conditions (MCC) and hospitalization in a community population. Methods Participants were residents of Olmsted County, Minnesota, aged >18 years who were enrolled in Mayo Clinic Biobank on December 31, 2010, with follow-up until December 31, 2011. Primary outcome was all-cause hospitalization over 1 calendar year. Secondary outcome was MCC determined through Minnesota Medical Tiering score. Logistic regression model was used to assess association of HOUSES with Minnesota tiering score. With adjustment for age, sex, and MCC, the association of HOUSES with hospitalization risk was tested using Cox proportional hazards model. Results Eligible patients totaled 6,402 persons (median age, 57 years; 25th-75th quartiles, 45-68 years). The lowest quartile of HOUSES was associated with higher Minnesota tiering score after adjustment for age and sex (odds ratio [95% CI], 2.4 [2.0-3.1]) when compared with the highest HOUSES quartile. Patients in the lowest HOUSES quartile had higher risk of all-cause hospitalization (age, sex, MCC-adjusted hazard ratio [95% CI], 1.53 [1.18-1.98]) compared with those in the highest quartile. Conclusion Low SES, as assessed by HOUSES, was associated with increased risk of hospitalization and greater MCC health burden. HOUSES may be a clinically useful surrogate for SES to assess risk stratification for patient care and clinical research. PMID:26458399

  18. Orders on Intervals Over Partially Ordered Sets: Extending Allen's Algebra and Interval Graph Results

    SciTech Connect

    Zapata, Francisco; Kreinovich, Vladik; Joslyn, Cliff A.; Hogan, Emilie A.

    2013-08-01

    To make a decision, we need to compare the values of quantities. In many practical situations, we know the values with interval uncertainty. In such situations, we need to compare intervals. Allen’s algebra describes all possible relations between intervals on the real line, and ordering relations between such intervals are well studied. In this paper, we extend this description to intervals in an arbitrary partially ordered set (poset). In particular, we explicitly describe ordering relations between intervals that generalize relation between points. As auxiliary results, we provide a logical interpretation of the relation between intervals, and extend the results about interval graphs to intervals over posets.

  19. Odor-context effects in free recall after a short retention interval: a new methodology for controlling adaptation.

    PubMed

    Isarida, Takeo; Sakai, Tetsuya; Kubota, Takayuki; Koga, Miho; Katayama, Yu; Isarida, Toshiko K

    2014-04-01

    The present study investigated context effects of incidental odors in free recall after a short retention interval (5 min). With a short retention interval, the results are not confounded by extraneous odors or encounters with the experimental odor and possible rehearsal during a long retention interval. A short study time condition (4 s per item), predicted not to be affected by adaptation to the odor, and a long study time condition (8 s per item) were used. Additionally, we introduced a new method for recovery from adaptation, where a dissimilar odor was briefly presented at the beginning of the retention interval, and we demonstrated the effectiveness of this technique. An incidental learning paradigm was used to prevent overshadowing from confounding the results. In three experiments, undergraduates (N = 200) incidentally studied words presented one-by-one and received a free recall test. Two pairs of odors and a third odor having different semantic-differential characteristics were selected from 14 familiar odors. One of the odors was presented during encoding, and during the test, the same odor (same-context condition) or the other odor within the pair (different-context condition) was presented. Without using a recovery-from-adaptation method, a significant odor-context effect appeared in the 4-s/item condition, but not in the 8-s/item condition. Using the recovery-from-adaptation method, context effects were found for both the 8- and the 4-s/item conditions. The size of the recovered odor-context effect did not change with study time. There were no serial position effects. Implications of the present findings are discussed. PMID:24222319

  20. Pigeons' Choices between Fixed-Interval and Random-Interval Schedules: Utility of Variability?

    ERIC Educational Resources Information Center

    Andrzejewski, Matthew E.; Cardinal, Claudia D.; Field, Douglas P.; Flannery, Barbara A.; Johnson, Michael; Bailey, Kathleen; Hineline, Philip N.

    2005-01-01

    Pigeons' choosing between fixed-interval and random-interval schedules of reinforcement was investigated in three experiments using a discrete-trial procedure. In all three experiments, the random-interval schedule was generated by sampling a probability distribution at an interval (and in multiples of the interval) equal to that of the…

  1. Reducing overconfidence in the interval judgments of experts.

    PubMed

    Speirs-Bridge, Andrew; Fidler, Fiona; McBride, Marissa; Flander, Louisa; Cumming, Geoff; Burgman, Mark

    2010-03-01

    Elicitation of expert opinion is important for risk analysis when only limited data are available. Expert opinion is often elicited in the form of subjective confidence intervals; however, these are prone to substantial overconfidence. We investigated the influence of elicitation question format, in particular the number of steps in the elicitation procedure. In a 3-point elicitation procedure, an expert is asked for a lower limit, upper limit, and best guess, the two limits creating an interval of some assigned confidence level (e.g., 80%). In our 4-step interval elicitation procedure, experts were also asked for a realistic lower limit, upper limit, and best guess, but no confidence level was assigned; the fourth step was to rate their anticipated confidence in the interval produced. In our three studies, experts made interval predictions of rates of infectious diseases (Study 1, n = 21 and Study 2, n = 24: epidemiologists and public health experts), or marine invertebrate populations (Study 3, n = 34: ecologists and biologists). We combined the results from our studies using meta-analysis, which found average overconfidence of 11.9%, 95% CI [3.5, 20.3] (a hit rate of 68.1% for 80% intervals)-a substantial decrease in overconfidence compared with previous studies. Studies 2 and 3 suggest that the 4-step procedure is more likely to reduce overconfidence than the 3-point procedure (Cohen's d = 0.61, [0.04, 1.18]). PMID:20030766

  2. Military Applicability of Interval Training for Health and Performance.

    PubMed

    Gibala, Martin J; Gagnon, Patrick J; Nindl, Bradley C

    2015-11-01

    Militaries from around the globe have predominantly used endurance training as their primary mode of aerobic physical conditioning, with historical emphasis placed on the long distance run. In contrast to this traditional exercise approach to training, interval training is characterized by brief, intermittent bouts of intense exercise, separated by periods of lower intensity exercise or rest for recovery. Although hardly a novel concept, research over the past decade has shed new light on the potency of interval training to elicit physiological adaptations in a time-efficient manner. This work has largely focused on the benefits of low-volume interval training, which involves a relatively small total amount of exercise, as compared with the traditional high-volume approach to training historically favored by militaries. Studies that have directly compared interval and moderate-intensity continuous training have shown similar improvements in cardiorespiratory fitness and the capacity for aerobic energy metabolism, despite large differences in total exercise and training time commitment. Interval training can also be applied in a calisthenics manner to improve cardiorespiratory fitness and strength, and this approach could easily be incorporated into a military conditioning environment. Although interval training can elicit physiological changes in men and women, the potential for sex-specific adaptations in the adaptive response to interval training warrants further investigation. Additional work is needed to clarify adaptations occurring over the longer term; however, interval training deserves consideration from a military applicability standpoint as a time-efficient training strategy to enhance soldier health and performance. There is value for military leaders in identifying strategies that reduce the time required for exercise, but nonetheless provide an effective training stimulus. PMID:26506197

  3. Prediction in Multiple Regression.

    ERIC Educational Resources Information Center

    Osborne, Jason W.

    2000-01-01

    Presents the concept of prediction via multiple regression (MR) and discusses the assumptions underlying multiple regression analyses. Also discusses shrinkage, cross-validation, and double cross-validation of prediction equations and describes how to calculate confidence intervals around individual predictions. (SLD)

  4. Predicting the diffusion coefficient of water vapor through glassy HPMC films at different environmental conditions using the free volume additivity approach.

    PubMed

    Laksmana, Fesia Lestari; Hartman Kok, Paul Jean Antoine; Vromans, Herman; Van der Voort Maarschalk, Kees

    2009-07-12

    Prediction of diffusion coefficient of polymer materials is important in the pharmaceutical research and becomes the aim of this paper. This paper bases the prediction method on the estimation of the polymer fractional free volume at different environmental conditions. Focussing on glassy polymers, the free volumes of polymer films were estimated using the model of Vrentas et al. [J.S. Vrentas, J.L. Duda, H.-C. Ling, Antiplasticization and volumetric behavior in glassy polymers, Macromolecules 21 (1988) 1470-1475]. The required data are the moisture sorption and glass transition temperature data, which were measured on various hydroxypropyl methylcellulose (used as a model material) free films at different water activities. The temperature and molecular weight particularly determine the free volume of the polymer, while the sorbed water can either decrease or increase the specific free volume of the polymer. At high water activity, the amount of water sorbed in the film increases to such level that the direct free volume addition by water becomes proportional to the contribution of the polymer itself. This confirms the importance of considering the environmental effect on the diffusivity of polymer during coating material selection. The presented approach enables the prediction of the diffusivity at any given relevant material variable and therefore has the potency to be used as a formulation development tool. PMID:19409985

  5. Final predictions of ambient conditions along the east-west crossdrift using the 3-D UZ site-scale model. Level 4 milestoneSP33ABM4.

    SciTech Connect

    Ritcey, A.C.; Sonnenthal, E.L.; Wu, Y.S.; Haukwa, C.; Bodvarsson,G.S.

    1998-03-01

    In 1998, the Yucca Mountain Site Characterization Project (YMP) is expected to continue construction of an East-West Cross Drift. The 5-meter diameter drift will extend from the North Ramp of the Exploratory Studies Facility (ESF), near Station 19+92, southwest through the repository block, and over to and through the Solitario Canyon Fault. This drift is part of a program designed to enhance characterization of Yucca Mountain and to complement existing surface-based and ESF testing studies. The objective of this milestone is to use the three-dimensional (3-D) unsaturated zone (UZ) site-scale model to predict ambient conditions along the East-West Cross Drift. These predictions provide scientists and engineers with a priori information that can support design and construction of the East-West Cross Drift and associated testing program. The predictions also provide, when compared with data collected after drift construction, an opportunity to test and verify the calibration of the 3-D UZ site-scale model.

  6. Modeling growth for predicting the contamination level of guava nectar by Candida pelliculosa under different conditions of pH and storage temperature.

    PubMed

    Tchango Tchango, J; Watier, D; Eb, P; Tailliez, R; Njine, T; Hornez, J P

    1997-01-01

    The combined effects of temperature (2-46 degrees C) and pH (1.55-6.25) on the growth of Candida pelliculosa isolated from guava nectar produced in Cameroon were studied using a turbidity method, ie measurement of optical density at 630 nm. A quadratic polynomial model was constructed to predict the effects and interactions of these two environmental conditions on the maximal optical density obtained (i2 = 0.97). The relation between optical density and population density of C. pelliculosa (CFU ml-1) was also established using an exponential regression (2 = 0.99). According to the model, maximal growth conditions were 37 degrees C and pH 6.25 for obtaining the maximal optical density of 1.25 corresponding to about 60 x 10(6) CFU ml-1. A good agreement of the model was found between the predicted values and the observed values of maximal optical density. The model was validated by the experimental values of maximal optical density obtained in the growth of C. pelliculosa in commercial guava nectar (pH 3.15). PMID:9079285

  7. Using Hydrus-1D to Predict Solute Conservative Tracer Transfer from Initially Saturated Soil into the Surface Runoff Water underwith Controlled Drainage Condition

    NASA Astrophysics Data System (ADS)

    Tong, J.; Yang, J.; Hu, B.

    2013-12-01

    In this paper, a mixing layer theory is coupled with the Hydrus-1D to predict solute transfer from an initially saturated soil into surface runoff water under a controlled drainage condition with low infiltration rate, and various ponding waterwith the increasing depths of the ponding water on the soil surface before the surface runoff. A sand experiment is used as the reference experiment to identify the parameters for the water flow model and solute transfer model with increasing mixing layer depth after the surface runoff water. Based on these identified parameters andan increasing depth of the mixing layer, the model well predicts the experimental results, and much better than the a simulation results by thewith a constant mixing layer depth under the controlled drainage without drainage theory. The model is also applied to another initially saturated sand experiment under the controlled drainage water condition, and the simulation resultsdata agree well with the observed data. These results suggest that the model can efficiently simulate the solute transfer from the initially saturated soil into the surface runoff water. It is found from this study that with the increase of the surface runoff time or/and the decrease of the mixing layer, the solute loss in the mixing layer before the surface runoff will increase, the solute source in the mixing layer for the surface runoff water will decrease after the surface runoff and the increase rate of the mixing layer depth will increase. Simple sketch of the model Hydraulic parameters in the reference sand experiment

  8. A model of interval timing by neural integration

    PubMed Central

    Simen, Patrick; Balci, Fuat; deSouza, Laura; Cohen, Jonathan D.; Holmes, Philip

    2011-01-01

    We show that simple assumptions about neural processing lead to a model of interval timing as a temporal integration process, in which a noisy firing-rate representation of time rises linearly on average toward a response threshold over the course of an interval. Our assumptions include: that neural spike trains are approximately independent Poisson processes; that correlations among them can be largely cancelled by balancing excitation and inhibition; that neural populations can act as integrators; and that the objective of timed behavior is maximal accuracy and minimal variance. The model accounts for a variety of physiological and behavioral findings in rodents, monkeys and humans, including ramping firing rates between the onset of reward-predicting cues and the receipt of delayed rewards, and universally scale-invariant response time distributions in interval timing tasks. It furthermore makes specific, well-supported predictions about the skewness of these distributions, a feature of timing data that is usually ignored. The model also incorporates a rapid (potentially one-shot) duration-learning procedure. Human behavioral data support the learning rule’s predictions regarding learning speed in sequences of timed responses. These results suggest that simple, integration-based models should play as prominent a role in interval timing theory as they do in theories of perceptual decision making, and that a common neural mechanism may underlie both types of behavior. PMID:21697374

  9. Utility of Corrected QT Interval in Orthostatic Intolerance

    PubMed Central

    Kim, Jung Bin; Hong, Soonwoong; Park, Jin-Woo; Cho, Dong-Hyuk; Park, Ki-Jong; Kim, Byung-Jo

    2014-01-01

    We performed this study to determine whether electrocardiographic corrected QT (QTc) interval predicts alterations in sympathovagal balance during orthostatic intolerance (OI). We reviewed 1,368 patients presenting with symptoms suggestive of OI who underwent electrocardiography and composite autonomic function tests (AFTs). Patients with a positive response to the head-up tilt test were classified into orthostatic hypotension (OH), neurocardiogenic syncope (NCS), or postural orthostatic tachycardia syndrome (POTS) groups. A total of 275 patients (159 OH, 54 NCS, and 62 POTS) were included in the final analysis. Between-group comparisons of OI symptom grade, QTc interval, QTc dispersion, and each AFT measure were performed. QTc interval and dispersion were correlated with AFT measures. OH Patients had the most severe OI symptom grade and NCS patients the mildest. Patients with OH showed the longest QTc interval (448.8±33.6 msec), QTc dispersion (59.5±30.3 msec) and the lowest values in heart rate response to deep breathing (HRDB) (10.3±6.0 beats/min) and Valsalva ratio (1.3±0.2). Patients with POTS showed the shortest QTc interval (421.7±28.6 msec), the highest HRDB values (24.5±9.2 beats/min), Valsalva ratio (1.8±0.3), and proximal and distal leg sweat volumes in the quantitative sudomotor axon reflex test. QTc interval correlated negatively with HRDB (r = −0.443, p<0.001) and Valsalva ratio (r = −0.425, p<0.001). We found negative correlations between QTc interval and AFT values representing cardiovagal function in patients with OI. Our findings suggest that prolonged QTc interval may be considered to be a biomarker for detecting alterations in sympathovagal balance, especially cardiovagal dysfunction in OH. PMID:25180969

  10. 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

  11. 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

  12. 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.

  13. 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)

  14. An empirical/theoretical model with dimensionless numbers to predict the performance of electrodialysis systems on the basis of operating conditions.

    PubMed

    Karimi, Leila; Ghassemi, Abbas

    2016-07-01

    Among the different technologies developed for desalination, the electrodialysis/electrodialysis reversal (ED/EDR) process is one of the most promising for treating brackish water with low salinity when there is high risk of scaling. Multiple researchers have investigated ED/EDR to optimize the process, determine the effects of operating parameters, and develop theoretical/empirical models. Previously published empirical/theoretical models have evaluated the effect of the hydraulic conditions of the ED/EDR on the limiting current density using dimensionless numbers. The reason for previous studies' emphasis on limiting current density is twofold: 1) to maximize ion removal, most ED/EDR systems are operated close to limiting current conditions if there is not a scaling potential in the concentrate chamber due to a high concentration of less-soluble salts; and 2) for modeling the ED/EDR system with dimensionless numbers, it is more accurate and convenient to use limiting current density, where the boundary layer's characteristics are known at constant electrical conditions. To improve knowledge of ED/EDR systems, ED/EDR models should be also developed for the Ohmic region, where operation reduces energy consumption, facilitates targeted ion removal, and prolongs membrane life compared to limiting current conditions. In this paper, theoretical/empirical models were developed for ED/EDR performance in a wide range of operating conditions. The presented ion removal and selectivity models were developed for the removal of monovalent ions and divalent ions utilizing the dominant dimensionless numbers obtained from laboratory scale electrodialysis experiments. At any system scale, these models can predict ED/EDR performance in terms of monovalent and divalent ion removal. PMID:27108213

  15. Monocular viewing prolongs reversal interval of perceptual rival figure

    NASA Astrophysics Data System (ADS)

    Tanahashi, Shigehito; Segawa, Kaori; Zheng, Meihong; Kuze, Junko; Ukai, Kazuhiko

    2012-09-01

    The authors examined whether the perceptual reversal rate changes under monocular versus binocular viewing conditions. Our results suggest that the perceptual reversal interval increases during monocular viewing. The ratio of the reversal rate (1/interval) for the two viewing conditions (binocular/monocular) was 1.28 over a wide range of pattern luminance levels. The quoted ratio was 1.40 when the luminance was high. Such a ratio parallels the value of a well-known binocular summation index (sqrt 2 ), which was derived from the signal detection theory. The binocular summation index shows that the strength of an input signal is enhanced by binocular viewing. However, how the binocular summation shortens the perceptual reversal interval is unclear. This issue can be resolved if the perceptual reversal is derived by integrating the strength of an unconscious image signal. Thus, we discussed the mechanism of perceptual switch by associating two classical, well-studied phenomena, binocular summation and perceptual switch.

  16. Using Confidence Intervals and Recurrence Intervals to Determine Precipitation Delivery Mechanisms Responsible for Mass Wasting Events.

    NASA Astrophysics Data System (ADS)

    Ulizio, T. P.; Bilbrey, C.; Stoyanoff, N.; Dixon, J. L.

    2015-12-01

    upper bound of the 99% confidence interval at all SNOTEL sites while precipitation accumulated in the form of rain is within the expected average, indicating an anomalously snow year and average amounts of rainfall during the same water year. This information can be used to better predict circumstances leading to slope failures in northern latitude alpine landscapes.

  17. Prediction and measurement of optimum operating conditions for entrained coal gasification processes. Quarterly technical progress report, No. 1, 1 November 1979-31 January 1980

    SciTech Connect

    Smoot, L.D.; Hedman, P.O.; Smith, P.J.

    1980-02-15

    This report summarizes work completed to predict and measure optimum operating conditions for entrained coal gasifications processes. This study is the third in a series designed to investigate mixing and reaction in entrained coal gasifiers. A new team of graduate and undergraduate students was formed to conduct the experiments on optimum gasification operating conditions. Additional coal types, which will be tested in the gasifier were identified, ordered, and delivered. Characterization of these coals will be initiated. Hardware design modifications to introduce swirl into the secondary were initiated. Minor modifications were made to the gasifier to allow laser diagnostics to be made on an independently funded study with the Los Alamos Scientific Laboratory. The tasks completed on the two-dimensional model included the substantiation of a Gaussian PDF for the top-hat PDF in BURN and the completion of a Lagrangian particle turbulent dispersion module. The reacting submodel is progressing into the final stages of debug. The formulation of the radiation submodel is nearly complete and coding has been initiated. A device was designed, fabricated, and used to calibrate the actual Swirl Number of the cold-flow swirl generator used in the Phase 2 study. Swirl calibrations were obtained at the normal tests flow rates and at reduced flow rates. Two cold-flow tests were also performed to gather local velocity data under swirling conditions. Further analysis of the cold-flow coal-dust and swirl test results from the previous Phase 2 study were completed.

  18. Capacity of novelty-induced locomotor activity and the hole-board test to predict sensitivity to the conditioned rewarding effects of cocaine.

    PubMed

    Arenas, M Carmen; Daza-Losada, Manuel; Vidal-Infer, Antonio; Aguilar, Maria A; Miñarro, José; Rodríguez-Arias, Marta

    2014-06-22

    Novelty-seeking in rodents, defined as enhanced specific exploration of novel situations, is considered to predict the response of animals to drugs of abuse and, thus, allow "drug-vulnerable" individuals to be identified. The main objective of this study was to assess the predictive ability of two well-known paradigms of the novelty-seeking trait - novelty-induced locomotor activity (which distinguishes High- and Low-Responder mice, depending on their motor activity) and the hole-board test (which determines High- and Low-Novelty Seeker mice depending on the number of head dips they perform) - to identify subjects that would subsequently be more sensitive to the conditioned rewarding effects of cocaine in a population of young adult (PND 56) and adolescent (PND 35) OF1 mice of both sexes. Conditioned place preference (CPP), a useful tool for evaluating the sensitivity of individuals to the incentive properties of addictive drugs, was induced with a sub-threshold dose of cocaine (1 mg/kg, i.p.). Our results showed that novelty-induced motor activity had a greater predictive capacity to identify "vulnerable-drug" individuals among young-adult mice (PND 56), while the hole-board test was more effective in adolescents (PND 35). High-NR young-adults, which presented higher motor activity in the first ten minutes of the test (novelty-reactivity), were 3.9 times more likely to develop cocaine-induced CPP than Low-NR young-adults. When total activity (1h) was evaluated (novelty-habituation), only High-R (novelty-non-habituating) young-adult male and Low-R (novelty-habituating) female mice produced a high conditioning score. However, only High-Novelty Seeker male and female adolescents and Low-Novelty Seeker female young-adult animals (according to the hole-board test), acquired cocaine-induced CPP. These findings should contribute to the development of screening methods for identifying at-risk human drug users and prevention strategies for those with specific

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

    PubMed Central

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

    2005-01-01

    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 \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} \\begin{equation*}{\\bar {{\\tau}}}\\end{equation*}\\end{document} as \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} \\begin{equation*}P_{q}({\\tau})={\\bar {{\\tau}}}^{-1}f({\\tau}/{\\bar {{\\tau}}})\\end{equation*}\\end{document}. 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. PMID:15980152

  20. 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

  1. Confidence Intervals in Qtl Mapping by Bootstrapping

    PubMed Central

    Visscher, P. M.; Thompson, R.; Haley, C. S.

    1996-01-01

    The determination of empirical confidence intervals for the location of quantitative trait loci (QTLs) was investigated using simulation. Empirical confidence intervals were calculated using a bootstrap resampling method for a backcross population derived from inbred lines. Sample sizes were either 200 or 500 individuals, and the QTL explained 1, 5, or 10% of the phenotypic variance. The method worked well in that the proportion of empirical confidence intervals that contained the simulated QTL was close to expectation. In general, the confidence intervals were slightly conservatively biased. Correlations between the test statistic and the width of the confidence interval were strongly negative, so that the stronger the evidence for a QTL segregating, the smaller the empirical confidence interval for its location. The size of the average confidence interval depended heavily on the population size and the effect of the QTL. Marker spacing had only a small effect on the average empirical confidence interval. The LOD drop-off method to calculate empirical support intervals gave confidence intervals that generally were too small, in particular if confidence intervals were calculated only for samples above a certain significance threshold. The bootstrap method is easy to implement and is useful in the analysis of experimental data. PMID:8725246

  2. Confidence Interval Coverage for Cohen's Effect Size Statistic

    ERIC Educational Resources Information Center

    Algina, James; Keselman, H. J.; Penfield, Randall D.

    2006-01-01

    Kelley compared three methods for setting a confidence interval (CI) around Cohen's standardized mean difference statistic: the noncentral-"t"-based, percentile (PERC) bootstrap, and biased-corrected and accelerated (BCA) bootstrap methods under three conditions of nonnormality, eight cases of sample size, and six cases of population effect size…

  3. 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. PMID:26742613

  4. Cocaine-conditioned place preference is predicted by previous anxiety-like behavior and is related to an increased number of neurons in the basolateral amygdala.

    PubMed

    Ladrón de Guevara-Miranda, David; Pavón, Francisco J; Serrano, Antonia; Rivera, Patricia; Estivill-Torrús, Guillermo; Suárez, Juan; Rodríguez de Fonseca, Fernando; Santín, Luis J; Castilla-Ortega, Estela

    2016-02-01

    The identification of behavioral traits that could predict an individual's susceptibility to engage in cocaine addiction is relevant for understanding and preventing this disorder, but investigations of cocaine addicts rarely allow us to determinate whether their behavioral attributes are a cause or a consequence of drug use. To study the behaviors that predict cocaine vulnerability, male C57BL/6J mice were examined in a battery of tests (the elevated plus maze, hole-board, novelty preference in the Y-Maze, episodic-like object recognition and forced swimming) prior to training in a cocaine-conditioned place preference (CPP) paradigm to assess the reinforcing value of the drug. In a second study, the anatomical basis of high and low CPP in the mouse brain was investigated by studying the number of neurons (neuronal nuclei-positive) in two addiction-related limbic regions (the medial prefrontal cortex and the basolateral amygdala) and the number of dopaminergic neurons (tyrosine hydroxylase-positive) in the ventral tegmental area by immunohistochemistry and stereology. Correlational analyses revealed that CPP behavior was successfully predicted by anxiety-like measures in the elevated plus maze (i.e., the more anxious mice showed more preference for the cocaine-paired compartment) but not by the other behaviors analyzed. In addition, increased numbers of neurons were found in the basolateral amygdala of the high CPP mice, a key brain center for anxiety and fear responses. The results support the theory that anxiety is a relevant factor for cocaine vulnerability, and the basolateral amygdala is a potential neurobiological substrate where both anxiety and cocaine vulnerability could overlap. PMID:26523857

  5. Solution behaviour of myo-inositol hexakisphosphate in the presence of multivalent cations. Prediction of a neutral pentamagnesium species under cytosolic/nuclear conditions.

    PubMed

    Torres, Julia; Domínguez, Sixto; Cerdá, M Fernanda; Obal, Gonzalo; Mederos, Alfredo; Irvine, Robin F; Díaz, Alvaro; Kremer, Carlos

    2005-03-01

    myo-Inositol hexakisphosphate (InsP6) is an ubiquitous and abundant molecule in the cytosol and nucleus of eukaryotic cells whose biological functions are incompletely known. A major hurdle for studying the biology of InsP6 has been a deficiency of a full understanding of the chemistry of its interaction with divalent and trivalent cations. This deficiency has limited our appreciation of how it remains in solution within cells, and the likely degree to which it might interact in vivo with physiologically important cations such as Ca2+ and Fe3+. We report here the initial part of the description of the InsP6-multivalent cation chemistry, including its solution equilibria studied by high resolution potentiometry and (for the Fe(III)/Fe(II) couple) cyclic voltammetry. InsP6 forms anionic complexes of high affinities and 1:1 stoichiometry with Mg(II), Ca(II), Mn(II), Fe(II), Co(II), Ni(II), Cu(II), Zn(II) and Cd(II). Of particular importance is the observation that, in the exceptional case of Mg(II), InsP6 forms the species [Mg5(H2L)] (L representing fully deprotonated InsP6); this soluble neutral species is predicted to be the predominant form of InsP6 under nuclear or cytosolic conditions in animal cells. Contrary to previous suggestions, InsP6 is predicted not to interact with cytosolic calcium even when calcium is increased during signalling events. In vitro, InsP6 also forms high affinity 1:1 complexes with Fe(III) and Al(III). However, our data predict that in the biological context of excess free Mg(II), neither Fe(III) nor Fe(II) are complexed by InsP6. PMID:15708805

  6. 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. PMID:19275294

  7. 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.

  8. A multivariate rate equation for variable-interval performance

    PubMed Central

    McDowell, J. J; Kessei, Robert

    1979-01-01

    A value-like parameter is introduced into a rate equation for describing variable-interval performance. The equation, derived solely from formal considerations, expresses rate of responding as a joint function of rate of reinforcement and “reinforcer power.” Preliminary tests of the rate equation show that it handles univariate data as well as Herrnstein's hyperbola. In addition, a form of Herrnstein's hyperbola can be derived from the equation, and it predicts forms of matching in concurrent situations. For the multivariate case, reinforcer values scaled in concurrent situations where matching is assumed to hold are taken as determinations of reinforcer power. The multivariate rate equation is fitted to an appropriate set of data and found to provide a good description of variable-interval performance when both rate and power of reinforcement are varied. Rate and power measures completely describe reinforcement. The effects of their joint variation are not predicted and cannot be described by Herrnstein's equation. PMID:16812130

  9. 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.

  10. Kernel number as a positive target trait for prediction of hybrid performance under low-nitrogen stress as revealed by diallel analysis under contrasting nitrogen conditions

    PubMed Central

    Li, Xiuxiu; Sun, Zhen; Xu, Xiaojie; Li, Wen-Xue; Zou, Cheng; Wang, Shanhong; Xu, Yunbi; Xie, Chuanxiao

    2014-01-01

    Environmental sustainability concerns make improving yield under lower N input a desirable breeding goal. To evaluate genetic variation and heterosis for low-N tolerance breeding, 28 F1 hybrids from a diallel scheme, along with their eight parental lines, were tested for agronomic traits including kernel number per ear (KNE) and grain yield per plant (GY), in replicated plots over two years under low-nitrogen (LN, without nitrogen application) and normal-nitrogen (NN, 220 kg N ha−1) conditions. Taken together the heritability in this and our previous studies, the correlation with grain yield, and the sensitivity to the stress for target trait selection, KNE was a good secondary target trait for LN selection in maize breeding. KNE also showed much higher mid-parent heterosis than hundred-kernel weight under both nitrogen levels, particularly under LN, indicating that KNE contributed the majority of GY heterosis, particularly under LN. Therefore, KNE can be used as a positive target trait for hybrid performance prediction in LN tolerance breeding. Our results also suggest that breeding hybrids for LN tolerance largely relies on phenotypic evaluation of hybrids under LN condition and yield under LN might be improved more by selection for KNE than by direct selection for GY per se. PMID:25914594

  11. Interval velocity analysis using wave field continuation

    SciTech Connect

    Zhusheng, Z. )

    1992-01-01

    In this paper, the author proposes a new interval velocity inversion method which, based on wave field continuation theory and fuzzy decision theory, uses CMP seismic gathers to automatically estimate interval velocity and two-way travel time in layered medium. The interval velocity calculated directly from wave field continuation is not well consistent with that derived from VSP data, the former is usually higher than the latter. Three major factors which influence the accuracy of interval velocity from wave field continuation are corrected, so that the two kinds of interval velocity are well consistent. This method brings better interval velocity, adapts weak reflection waves and resists noise well. It is a feasible method.

  12. 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.

  13. 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.

  14. A note on the path interval distance.

    PubMed

    Coons, Jane Ivy; Rusinko, Joseph

    2016-06-01

    The path interval distance accounts for global congruence between locally incongruent trees. We show that the path interval distance provides a lower bound for the nearest neighbor interchange distance. In contrast to the Robinson-Foulds distance, random pairs of trees are unlikely to be maximally distant from one another under the path interval distance. These features indicate that the path interval distance should play a role in phylogenomics where the comparison of trees on a fixed set of taxa is becoming increasingly important. PMID:27040521

  15. Electrocardiographic Abnormalities and QTc Interval in Patients Undergoing Hemodialysis

    PubMed Central

    Nie, Yuxin; Zou, Jianzhou; Liang, Yixiu; Shen, Bo; Liu, Zhonghua; Cao, Xuesen; Chen, Xiaohong; Ding, Xiaoqiang

    2016-01-01

    construction abnormalities were found in this group. In multiple regression analyses, serum Ca2+ concentration before HD and LAD were independent variables of QTc interval prolongation. UA, ferritin, and interventricular septum were independent variables of ΔQTc. Conclusion Prolonged QT interval is very common in HD patients and is associated with several risk factors. An appropriate concentration of dialysate electrolytes should be chosen depending on patients’ clinical conditions. PMID:27171393

  16. Psychoacoustic Factors in Musical Intonation: Beats, Interval Tuning, and Inharmonicity.

    NASA Astrophysics Data System (ADS)

    Keislar, Douglas Fleming

    Three psychoacoustic experiments were conducted using musically experienced subjects. In the first two experiments, the interval tested was the perfect fifth F4-C5; in the final one it was the major third F4-A4. The beat rate was controlled by two different methods: (1) simply retuning the interval, and (2) frequency-shifting one partial of each pair of beating partials without changing the overall interval tuning. The second method introduces inharmonicity. In addition, two levels of beat amplitude were introduced by using either a complete spectrum of 16 equal-amplitude partials per note, or by deleting one partial from each pair of beating partials. The results of all three experiments indicate that, for these stimuli, beating does not contribute significantly to the percept of "out-of-tuneness," because it made no difference statistically whether the beat amplitude was maximal or minimal. By contrast, mistuning the interval was highly significant. For the fifths, frequency-shifting the appropriate partials had about as much effect on the perceived intonation as mistuning the interval. For thirds, this effect was weaker, presumably since there were fewer inharmonic partials and they were higher in the harmonic series. Subjects were less consistent in their judgments of thirds than of fifths, perhaps because the equal-tempered and just thirds differ noticeably, unlike fifths. Since it is unlikely that beats would be more audible in real musical situations than under these laboratory conditions, these results suggest that the perception of intonation in music is dependent on the actual interval tuning rather than the concomitant beat rate. If beating partials are unimportant vis-a-vis interval tuning, this strengthens the argument for a cultural basis for musical intonation and scales, as opposed to the acoustical basis set forth by Helmholtz and others.

  17. 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. PMID:26710266

  18. Operant Conditioning

    PubMed Central

    Staddon, J. E. R.; Cerutti, D. T.

    2005-01-01

    Operant behavior is behavior “controlled” by its consequences. In practice, operant conditioning is the study of reversible behavior maintained by reinforcement schedules. We review empirical studies and theoretical approaches to two large classes of operant behavior: interval timing and choice. We discuss cognitive versus behavioral approaches to timing, the “gap” experiment and its implications, proportional timing and Weber's law, temporal dynamics and linear waiting, and the problem of simple chain-interval schedules. We review the long history of research on operant choice: the matching law, its extensions and problems, concurrent chain schedules, and self-control. We point out how linear waiting may be involved in timing, choice, and reinforcement schedules generally. There are prospects for a unified approach to all these areas. PMID:12415075

  19. High Graft CD8 Cell Dose Predicts Improved Survival and Enables Better Donor Selection in Allogeneic Stem-Cell Transplantation With Reduced-Intensity Conditioning

    PubMed Central

    Reshef, Ran; Huffman, Austin P.; Gao, Amy; Luskin, Marlise R.; Frey, Noelle V.; Gill, Saar I.; Hexner, Elizabeth O.; Kambayashi, Taku; Loren, Alison W.; Luger, Selina M.; Mangan, James K.; Nasta, Sunita D.; Richman, Lee P.; Sell, Mary; Stadtmauer, Edward A.; Vonderheide, Robert H.; Mick, Rosemarie; Porter, David L.

    2015-01-01

    Purpose To characterize the impact of graft T-cell composition on outcomes of reduced-intensity conditioned (RIC) allogeneic hematopoietic stem-cell transplantation (alloHSCT) in adults with hematologic malignancies. Patients and Methods We evaluated associations between graft T-cell doses and outcomes in 200 patients who underwent RIC alloHSCT with a peripheral blood stem-cell graft. We then studied 21 alloHSCT donors to identify predictors of optimal graft T-cell content. Results Higher CD8 cell doses were associated with a lower risk for relapse (adjusted hazard ratio [aHR], 0.43; P = .009) and improved relapse-free survival (aHR, 0.50; P = .006) and overall survival (aHR, 0.57; P = .04) without a significant increase in graft-versus-host disease or nonrelapse mortality. A cutoff level of 0.72 × 108 CD8 cells per kilogram optimally segregated patients receiving CD8hi and CD8lo grafts with differing overall survival (P = .007). Donor age inversely correlated with graft CD8 dose. Consequently, older donors were unlikely to provide a CD8hi graft, whereas approximately half of younger donors provided CD8hi grafts. Compared with recipients of older sibling donor grafts (consistently containing CD8lo doses), survival was significantly better for recipients of younger unrelated donor grafts with CD8hi doses (P = .03), but not for recipients of younger unrelated donor CD8lo grafts (P = .28). In addition, graft CD8 content could be predicted by measuring the proportion of CD8 cells in a screening blood sample from stem-cell donors. Conclusion Higher graft CD8 dose, which was restricted to young donors, predicted better survival in patients undergoing RIC alloHSCT. PMID:26056179

  20. Changes in body condition of hibernating bats support the thrifty female hypothesis and predict consequences for populations with white-nose syndrome.

    PubMed

    Jonasson, Kristin A; Willis, Craig K R

    2011-01-01

    White-nose syndrome (WNS) is a new disease of bats that has devastated populations in eastern North America. Infection with the fungus, Geomyces destructans, is thought to increase the time bats spend out of torpor during hibernation, leading to starvation. Little is known about hibernation in healthy, free-ranging bats and more data are needed to help predict consequences of WNS. Trade-offs presumably exist between the energetic benefits and physiological/ecological costs of torpor, leading to the prediction that the relative importance of spring energy reserves should affect an individual's use of torpor and depletion of energy reserves during winter. Myotis lucifugus mate during fall and winter but females do not become pregnant until after spring emergence. Thus, female reproductive success depends on spring fat reserves while male reproductive success does not. Consequently, females should be "thrifty" in their use of fat compared to males. We measured body condition index (BCI; mass/forearm length) of 432 M. lucifugus in Manitoba, Canada during the winter of 2009/2010. Bats were captured during the fall mating period (n = 200), early hibernation (n = 125), and late hibernation (n = 128). Adult females entered hibernation with greater fat reserves and consumed those reserves more slowly than adult males and young of the year. Consequently, adult females may be more likely than males or young of the year to survive the disruption of energy balance associated with WNS, although surviving females may not have sufficient reserves to support reproduction. PMID:21731647

  1. 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

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

    PubMed

    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

  3. A trigonometric interval method for dynamic response analysis of uncertain nonlinear systems

    NASA Astrophysics Data System (ADS)

    Liu, ZhuangZhuang; Wang, TianShu; Li, JunFeng

    2015-04-01

    This paper proposes a new non-intrusive trigonometric polynomial approximation interval method for the dynamic response analysis of nonlinear systems with uncertain-but-bounded parameters and/or initial conditions. This method provides tighter solution ranges compared to the existing approximation interval methods. We consider trigonometric approximation polynomials of three types: both cosine and sine functions, the sine function, and the cosine function. Thus, special interval arithmetic for trigonometric function without overestimation can be used to obtain interval results. The interval method using trigonometric approximation polynomials with a cosine functional form exhibits better performance than the existing Taylor interval method and Chebyshev interval method. Finally, two typical numerical examples with nonlinearity are applied to demonstrate the effectiveness of the proposed method.

  4. Non-intrusive hybrid interval method for uncertain nonlinear systems using derivative information

    NASA Astrophysics Data System (ADS)

    Liu, Zhuang-Zhuang; Wang, Tian-Shu; Li, Jun-Feng

    2016-02-01

    This paper proposes a new non-intrusive hybrid interval method using derivative information for the dynamic response analysis of nonlinear systems with uncertain-but-bounded parameters and/or initial conditions. This method provides tighter solution ranges compared to the existing polynomial approximation interval methods. Interval arithmetic using the Chebyshev basis and interval arithmetic using the general form modified affine basis for polynomials are developed to obtain tighter bounds for interval computation. To further reduce the overestimation caused by the "wrapping effect" of interval arithmetic, the derivative information of dynamic responses is used to achieve exact solutions when the dynamic responses are monotonic with respect to all the uncertain variables. Finally, two typical numerical examples with nonlinearity are applied to demonstrate the effectiveness of the proposed hybrid interval method, in particular, its ability to effectively control the overestimation for specific timepoints.

  5. The Interval approach to braneworld gravity

    SciTech Connect

    Carena, Marcela; Lykken, Joseph D.; Park, Minjoon; /Chicago U., EFI

    2005-06-01

    Gravity in five-dimensional braneworld backgrounds may exhibit extra scalar degrees of freedom with problematic features, including kinetic ghosts and strong coupling behavior. Analysis of such effects is hampered by the standard heuristic approaches to braneworld gravity, which use the equations of motion as the starting point, supplemented by orbifold projections and junction conditions. Here we develop the interval approach to braneworld gravity, which begins with an action principle. This shows how to implement general covariance, despite allowing metric fluctuations that do not vanish on the boundaries. We reproduce simple Z{sub 2} orbifolds of gravity, even though in this approach we never perform a Z{sub 2} projection. We introduce a family of ''straight gauges'', which are bulk coordinate systems in which both branes appear as straight slices in a single coordinate patch. Straight gauges are extremely useful for analyzing metric fluctuations in braneworld models. By explicit gauge fixing, we show that a general AdS{sub 5}/AdS{sub 4} setup with two branes has at most a radion, but no physical ''brane-bending'' modes.

  6. 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…

  7. Optimal Approximation of Quadratic Interval Functions

    NASA Technical Reports Server (NTRS)

    Koshelev, Misha; Taillibert, Patrick

    1997-01-01

    Measurements are never absolutely accurate, as a result, after each measurement, we do not get the exact value of the measured quantity; at best, we get an interval of its possible values, For dynamically changing quantities x, the additional problem is that we cannot measure them continuously; we can only measure them at certain discrete moments of time t(sub 1), t(sub 2), ... If we know that the value x(t(sub j)) at a moment t(sub j) of the last measurement was in the interval [x-(t(sub j)), x + (t(sub j))], and if we know the upper bound D on the rate with which x changes, then, for any given moment of time t, we can conclude that x(t) belongs to the interval [x-(t(sub j)) - D (t - t(sub j)), x + (t(sub j)) + D (t - t(sub j))]. This interval changes linearly with time, an is, therefore, called a linear interval function. When we process these intervals, we get an expression that is quadratic and higher order w.r.t. time t, Such "quadratic" intervals are difficult to process and therefore, it is necessary to approximate them by linear ones. In this paper, we describe an algorithm that gives the optimal approximation of quadratic interval functions by linear ones.

  8. 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...

  9. Interval colorectal carcinoma: An unsolved debate.

    PubMed

    Benedict, Mark; Galvao Neto, Antonio; Zhang, Xuchen

    2015-12-01

    Colorectal carcinoma (CRC), as the third most common new cancer diagnosis, poses a significant health risk to the population. Interval CRCs are those that appear after a negative screening test or examination. The development of interval CRCs has been shown to be multifactorial: location of exam-academic institution versus community hospital, experience of the endoscopist, quality of the procedure, age of the patient, flat versus polypoid neoplasia, genetics, hereditary gastrointestinal neoplasia, and most significantly missed or incompletely excised lesions. The rate of interval CRCs has decreased in the last decade, which has been ascribed to an increased understanding of interval disease and technological advances in the screening of high risk individuals. In this article, we aim to review the literature with regard to the multifactorial nature of interval CRCs and provide the most recent developments regarding this important gastrointestinal entity. PMID:26668498

  10. Constructing Confidence Intervals for Qtl Location

    PubMed Central

    Mangin, B.; Goffinet, B.; Rebai, A.

    1994-01-01

    We describe a method for constructing the confidence interval of the QTL location parameter. This method is developed in the local asymptotic framework, leading to a linear model at each position of the putative QTL. The idea is to construct a likelihood ratio test, using statistics whose asymptotic distribution does not depend on the nuisance parameters and in particular on the effect of the QTL. We show theoretical properties of the confidence interval built with this test, and compare it with the classical confidence interval using simulations. We show in particular, that our confidence interval has the correct probability of containing the true map location of the QTL, for almost all QTLs, whereas the classical confidence interval can be very biased for QTLs having small effect. PMID:7896108

  11. Interval colorectal carcinoma: An unsolved debate

    PubMed Central

    Benedict, Mark; Neto, Antonio Galvao; Zhang, Xuchen

    2015-01-01

    Colorectal carcinoma (CRC), as the third most common new cancer diagnosis, poses a significant health risk to the population. Interval CRCs are those that appear after a negative screening test or examination. The development of interval CRCs has been shown to be multifactorial: location of exam-academic institution versus community hospital, experience of the endoscopist, quality of the procedure, age of the patient, flat versus polypoid neoplasia, genetics, hereditary gastrointestinal neoplasia, and most significantly missed or incompletely excised lesions. The rate of interval CRCs has decreased in the last decade, which has been ascribed to an increased understanding of interval disease and technological advances in the screening of high risk individuals. In this article, we aim to review the literature with regard to the multifactorial nature of interval CRCs and provide the most recent developments regarding this important gastrointestinal entity. PMID:26668498

  12. CONFIDENCE INTERVALS AND STANDARD ERROR INTERVALS: WHAT DO THEY MEAN IN TERMS OF STATISTICAL SIGNIFICANCE?

    Technology Transfer Automated Retrieval System (TEKTRAN)

    We investigate the use of confidence intervals and standard error intervals to draw conclusions regarding tests of hypotheses about normal population means. Mathematical expressions and algebraic manipulations are given, and computer simulations are performed to assess the usefulness of confidence ...

  13. Ventricular Cycle Length Characteristics Estimative of Prolonged RR Interval during Atrial Fibrillation

    PubMed Central

    CIACCIO, EDWARD J.; BIVIANO, ANGELO B.; GAMBHIR, ALOK; EINSTEIN, ANDREW J.; GARAN, HASAN

    2014-01-01

    Background When atrial fibrillation (AF) is incessant, imaging during a prolonged ventricular RR interval may improve image quality. It was hypothesized that long RR intervals could be predicted from preceding RR values. Methods From the PhysioNet database, electrocardiogram RR intervals were obtained from 74 persistent AF patients. An RR interval lengthened by at least 250 ms beyond the immediately preceding RR interval (termed T0 and T1, respectively) was considered prolonged. A two-parameter scatterplot was used to predict the occurrence of a prolonged interval T0. The scatterplot parameters were: (1) RR variability (RRv) estimated as the average second derivative from 10 previous pairs of RR differences, T13–T2, and (2) Tm–T1, the difference between Tm, the mean from T13 to T2, and T1. For each patient, scatterplots were constructed using preliminary data from the first hour. The ranges of parameters 1 and 2 were adjusted to maximize the proportion of prolonged RR intervals within range. These constraints were used for prediction of prolonged RR in test data collected during the second hour. Results The mean prolonged event was 1.0 seconds in duration. Actual prolonged events were identified with a mean positive predictive value (PPV) of 80% in the test set. PPV was >80% in 36 of 74 patients. An average of 10.8 prolonged RR intervals per 60 minutes was correctly identified. Conclusions A method was developed to predict prolonged RR intervals using two parameters and prior statistical sampling for each patient. This or similar methodology may help improve cardiac imaging in many longstanding persistent AF patients. PMID:23998759

  14. Physiology and its Importance for Reference Intervals

    PubMed Central

    Sikaris, Kenneth A

    2014-01-01

    Reference intervals are ideally defined on apparently healthy individuals and should be distinguished from clinical decision limits that are derived from known diseased patients. Knowledge of physiological changes is a prerequisite for understanding and developing reference intervals. Reference intervals may differ for various subpopulations because of differences in their physiology, most obviously between men and women, but also in childhood, pregnancy and the elderly. Changes in laboratory measurements may be due to various physiological factors starting at birth including weaning, the active toddler, immunological learning, puberty, pregnancy, menopause and ageing. The need to partition reference intervals is required when there are significant physiological changes that need to be recognised. It is important that laboratorians are aware of these changes otherwise reference intervals that attempt to cover a widened inter-individual variability may lose their usefulness. It is virtually impossible for any laboratory to directly develop reference intervals for each of the physiological changes that are currently known, however indirect techniques can be used to develop or validate reference intervals in some difficult situations such as those for children. Physiology describes our life’s journey, and it is only when we are familiar with that journey that we can appreciate a pathological departure. PMID:24659833

  15. 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…

  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. The Prognostic Role of QTc Interval in Acute Myocarditis

    PubMed Central

    Hung, Yuan; Lin, Wei-Hsiang; Lin, Chin-Sheng; Cheng, Shu-Meng; Tsai, Tsung-Neng; Yang, Shih-Ping; Lin, Wen-Yu

    2016-01-01

    Background Acute myocarditis is an inflammatory disease of the myocardium. Although a fulminant course of the disease is difficult to predict, it may lead to acute heart failure and death. Previous studies have demonstrated that reduced left ventricular systolic function and prolonged QRS duration can predict the fulminant course of acute myocarditis. This study aimed to identify whether prolonged QTc interval could also be predictive of fulminant disease in this population. Methods We retrospectively included 40 patients diagnosed with acute myocarditis who were admitted to our hospital between 2002 and 2013. They were divided into the fulminant group (n = 9) and the non-fulminant group (n = 31). Clinical symptoms, laboratory findings, electrocardiographic, and echocardiographic parameters were analyzed. Multivariate logistic regression analysis was used to identify the independent factors predictive of fulminant disease. Results Patients with fulminant myocarditis had a higher mortality rate than those with non-fulminant disease (55.6% vs. 0%, p < 0.001). Multivariate analysis revealed that wider QRS durations (133.22 ± 45.85 ms vs. 92.81 ± 15.56 ms, p = 0.030) and longer QTc intervals (482.78 ± 69.76 ms vs. 412.00 ± 33.31 ms, p = 0.016) were significant predictors associated with a fulminant course of myocarditis. Conclusions Prolonged QRS duration and QTc interval, upon patient admission, may be associated with an increased risk of fulminant disease and increased in-hospital mortality. Therefore, early recognition of fulminant myocarditis and early mechanical support could provide improved patient outcomes. PMID:27122953

  18. Importance of QT interval in clinical practice.

    PubMed

    Ambhore, Anand; Teo, Swee-Guan; Bin Omar, Abdul Razakjr; Poh, Kian-Keong

    2014-12-01

    Long QT interval is an important finding that is often missed by electrocardiogram interpreters. Long QT syndrome (inherited and acquired) is a potentially lethal cardiac channelopathy that is frequently mistaken for epilepsy. We present a case of long QT syndrome with multiple cardiac arrests presenting as syncope and seizures. The long QTc interval was aggravated by hypomagnesaemia and drugs, including clarithromycin and levofloxacin. Multiple drugs can cause prolongation of the QT interval, and all physicians should bear this in mind when prescribing these drugs. PMID:25630313

  19. Short Interval Leaf Movements of Cotton 12

    PubMed Central

    Miller, Charles S.

    1975-01-01

    Gossypium hirsutum L. cv. Lankart plants exhibited three different types of independent short interval leaf movements which were superimposed on the circadian movements. The different types were termed SIRV (short interval rhythmical vertical), SIHM (short interval horizontal movements), and SHAKE (short stroked SIRV). The 36-minute period SIRV movements occurred at higher moisture levels. The 176-minute period SIHM occurred at lower moisture levels and ceased as the stress increased. The SHAKE movements were initiated with further stresses. The SLEEP (circadian, diurnal) movements ceased with further stress. The last to cease just prior to permanent wilting were the SHAKE movements. PMID:16659123

  20. Stability Problem of Canard-Cycles on a Finite Interval

    NASA Astrophysics Data System (ADS)

    Chumakov, Gennadii A.; Chumakova, Nataliya A.; Lashina, Elena A.

    2010-09-01

    A detailed study of two-variable mathematical model of a heterogeneous catalytic reaction is presented with special attention to the stability problem of canard-cycles on a finite interval. Our analysis of the global error behavior in a long-time numerical integration shows that a high sensitive dependence on the initial conditions appears due to the existence of a shower-type bundle of trajectories which is formed by stable and unstable canard solutions.

  1. 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

  2. Calibration intervals at Bendix Kansas City

    SciTech Connect

    James, R.T.

    1980-01-01

    The calibration interval evaluation methods and control in each calibrating department of the Bendix Corp., Kansas City Division is described, and a more detailed description of those employed in metrology is provided.

  3. Combination of structural reliability and interval analysis

    NASA Astrophysics Data System (ADS)

    Qiu, Zhiping; Yang, Di; Elishakoff, Isaac

    2008-02-01

    In engineering applications, probabilistic reliability theory appears to be presently the most important method, however, in many cases precise probabilistic reliability theory cannot be considered as adequate and credible model of the real state of actual affairs. In this paper, we developed a hybrid of probabilistic and non-probabilistic reliability theory, which describes the structural uncertain parameters as interval variables when statistical data are found insufficient. By using the interval analysis, a new method for calculating the interval of the structural reliability as well as the reliability index is introduced in this paper, and the traditional probabilistic theory is incorporated with the interval analysis. Moreover, the new method preserves the useful part of the traditional probabilistic reliability theory, but removes the restriction of its strict requirement on data acquisition. Example is presented to demonstrate the feasibility and validity of the proposed theory.

  4. Almost primes in almost all short intervals

    NASA Astrophysics Data System (ADS)

    TERÄVÄINEN, JONI

    2016-09-01

    Let $E_k$ be the set of positive integers having exactly $k$ prime factors. We show that almost all intervals $[x,x+\\log^{1+\\varepsilon} x]$ contain $E_3$ numbers, and almost all intervals $[x,x+\\log^{3.51} x]$ contain $E_2$ numbers. By this we mean that there are only $o(X)$ integers $1\\leq x\\leq X$ for which the mentioned intervals do not contain such numbers. The result for $E_3$ numbers is optimal up to the $\\varepsilon$ in the exponent. The theorem on $E_2$ numbers improves a result of Harman, which had the exponent $7+\\varepsilon$ in place of $3.51$. We will also consider general $E_k$ numbers, and find them on intervals whose lengths approach $\\log x$ as $k\\to \\infty$.

  5. 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

    2015-09-01

    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. PMID:26113190

  6. 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

  7. 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. PMID:27259065

  8. Abstract: Inference and Interval Estimation for Indirect Effects With Latent Variable Models.

    PubMed

    Falk, Carl F; Biesanz, Jeremy C

    2011-11-30

    Models specifying indirect effects (or mediation) and structural equation modeling are both popular in the social sciences. Yet relatively little research has compared methods that test for indirect effects among latent variables and provided precise estimates of the effectiveness of different methods. This simulation study provides an extensive comparison of methods for constructing confidence intervals and for making inferences about indirect effects with latent variables. We compared the percentile (PC) bootstrap, bias-corrected (BC) bootstrap, bias-corrected accelerated (BC a ) bootstrap, likelihood-based confidence intervals (Neale & Miller, 1997), partial posterior predictive (Biesanz, Falk, and Savalei, 2010), and joint significance tests based on Wald tests or likelihood ratio tests. All models included three reflective latent variables representing the independent, dependent, and mediating variables. The design included the following fully crossed conditions: (a) sample size: 100, 200, and 500; (b) number of indicators per latent variable: 3 versus 5; (c) reliability per set of indicators: .7 versus .9; (d) and 16 different path combinations for the indirect effect (α = 0, .14, .39, or .59; and β = 0, .14, .39, or .59). Simulations were performed using a WestGrid cluster of 1680 3.06GHz Intel Xeon processors running R and OpenMx. Results based on 1,000 replications per cell and 2,000 resamples per bootstrap method indicated that the BC and BC a bootstrap methods have inflated Type I error rates. Likelihood-based confidence intervals and the PC bootstrap emerged as methods that adequately control Type I error and have good coverage rates. PMID:26736127

  9. Emotional arousal predicts intertemporal choice.

    PubMed

    Lempert, Karolina M; Johnson, Eli; Phelps, Elizabeth A

    2016-08-01

    People generally prefer immediate rewards to rewards received after a delay, often even when the delayed reward is larger. This phenomenon is known as temporal discounting. It has been suggested that preferences for immediate rewards may be due to their being more concrete than delayed rewards. This concreteness may evoke an enhanced emotional response. Indeed, manipulating the representation of a future reward to make it more concrete has been shown to heighten the reward's subjective emotional intensity, making people more likely to choose it. Here the authors use an objective measure of arousal-pupil dilation-to investigate if emotional arousal mediates the influence of delayed reward concreteness on choice. They recorded pupil dilation responses while participants made choices between immediate and delayed rewards. They manipulated concreteness through time interval framing: delayed rewards were presented either with the date on which they would be received (e.g., "$30, May 3"; DATE condition, more concrete) or in terms of delay to receipt (e.g., "$30, 7 days; DAYS condition, less concrete). Contrary to prior work, participants were not overall more patient in the DATE condition. However, there was individual variability in response to time framing, and this variability was predicted by differences in pupil dilation between conditions. Emotional arousal increased as the subjective value of delayed rewards increased, and predicted choice of the delayed reward on each trial. This study advances our understanding of the role of emotion in temporal discounting. (PsycINFO Database Record PMID:26882337

  10. Structure-activity relationships for degradation reaction of 1-beta-o-acyl glucuronides: kinetic description and prediction of intrinsic electrophilic reactivity under physiological conditions.

    PubMed

    Baba, Akiko; Yoshioka, Tadao

    2009-01-01

    1-beta-O-Acyl glucuronides (betaGAs) are potentially reactive metabolites capable of binding to proteins, and they have been implicated in adverse drug reactions of the carboxylic acid drugs. To explore their electrophilic reactivity, we studied structure-activity relationships (SARs) to characterize the factors affecting the degradation rate constants (k values) of betaGAs and ultimately to predict k values of structurally diverse betaGAs. Twenty-seven betaGAs and four related compounds were synthesized, and their k values were determined under physiological conditions (pH 7.4 and 37 degrees C). 1-beta-O-Benzoyl glucuronide (BAGA) and glucopyranoside (BAG) showed almost the same k values, whereas their 1-alpha-O-benzoyl isomers degraded approximately 40-fold faster than BAGA and BAG. BAGA methyl ester showed almost the same rate constant as BAGA in the cleavage of their 1-beta-O-benzoyl linkages. A pH-log k profile obtained indicated kinetics catalyzed by both specific and general bases. The log k of betaGAs derived from m- and p-substituted benzoic acids correlated with Hammett's sigma constants. A similar correlation was observed with delta(COOH), (1)H NMR chemical shifts of the parent benzoic acids including ones with less sterically bulky o-substituents. Alternative descriptors of delta(CO) and delta((CO)OH), (13)C chemical shifts for ester carbonyl carbons of betaGAs and for carbonyl carbons of the parent benzoic acids, respectively, correlated well with the log k of all 16 betaGAs derived from benzoic acids including ones with bulkier o-substituents. Of the betaGA isomers derived from (2R)- and (2S)-alpha-methyl-4-biphenylylacetic acid, the (2R)-isomer degraded approximately 2-fold faster than the (2S)-isomer. The alpha-methyl group in the (2S)-isomer would encumber the intramolecular acyl migration. The log k of betaGAs derived from n-aralkyl carboxylic acids and of the (2R)-isomer correlated with their delta(COOH). However, the log k of betaGAs derived

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

    PubMed

    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

  12. Sunspot Time Series: Passive and Active Intervals

    NASA Astrophysics Data System (ADS)

    Zięba, S.; Nieckarz, Z.

    2014-07-01

    Solar activity slowly and irregularly decreases from the first spotless day (FSD) in the declining phase of the old sunspot cycle and systematically, but also in an irregular way, increases to the new cycle maximum after the last spotless day (LSD). The time interval between the first and the last spotless day can be called the passive interval (PI), while the time interval from the last spotless day to the first one after the new cycle maximum is the related active interval (AI). Minima of solar cycles are inside PIs, while maxima are inside AIs. In this article, we study the properties of passive and active intervals to determine the relation between them. We have found that some properties of PIs, and related AIs, differ significantly between two group of solar cycles; this has allowed us to classify Cycles 8 - 15 as passive cycles, and Cycles 17 - 23 as active ones. We conclude that the solar activity in the PI declining phase (a descending phase of the previous cycle) determines the strength of the approaching maximum in the case of active cycles, while the activity of the PI rising phase (a phase of the ongoing cycle early growth) determines the strength of passive cycles. This can have implications for solar dynamo models. Our approach indicates the important role of solar activity during the declining and the rising phases of the solar-cycle minimum.

  13. Natural frequencies of structures with interval parameters

    NASA Astrophysics Data System (ADS)

    Sofi, A.; Muscolino, G.; Elishakoff, I.

    2015-07-01

    This paper deals with the evaluation of the lower and upper bounds of the natural frequencies of structures with uncertain-but-bounded parameters. The solution of the generalized interval eigenvalue problem is pursued by taking into account the actual variability and dependencies of uncertain structural parameters affecting the mass and stiffness matrices. To this aim, interval uncertainties are handled by applying the improved interval analysis via extra unitary interval (EUI), recently introduced by the first two authors. By associating an EUI to each uncertain-but-bounded parameter, the cases of mass and stiffness matrices affected by fully disjoint, completely or partially coincident uncertainties are considered. Then, based on sensitivity analysis, it is shown that the bounds of the interval eigenvalues can be evaluated as solution of two appropriate deterministic eigenvalue problems without requiring any combinatorial procedure. If the eigenvalues are monotonic functions of the uncertain parameters, then the exact bounds are obtained. The accuracy of the proposed method is demonstrated by numerical results concerning truss and beam structures with material and/or geometrical uncertainties.

  14. 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...

  15. 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...

  16. Computing connection coefficients of compactly supported wavelets on bounded intervals

    SciTech Connect

    Romine, C.H.; Peyton, B.W.

    1997-04-01

    Daubechies wavelet basis functions have many properties that make them desirable as a basis for a Galerkin approach to solving PDEs: they are orthogonal, with compact support, and their connection coefficients can be computed. The method developed by Latto et al. to compute connection coefficients does not provide the correct inner product near the endpoints of a bounded interval, making the implementation of boundary conditions problematic. Moreover, the highly oscillatory nature of the wavelet basis functions makes standard numerical quadrature of integrals near the boundary impractical. The authors extend the method of Latto et al. to construct and solve a linear system of equations whose solution provides the exact computation of the integrals at the boundaries. As a consequence, they provide the correct inner product for wavelet basis functions on a bounded interval.

  17. Pigeons' choices between fixed-interval and random-interval schedules: utility of variability?

    PubMed

    Andrzejewski, Matthew E; Cardinal, Claudia D; Field, Douglas P; Flannery, Barbara A; Johnson, Michael; Bailey, Kathleen; Hineline, Philip N

    2005-03-01

    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 fixed-interval schedule. Thus the programmed delays to reinforcement on the random alternative were never shorter and were often longer than the fixed interval. Despite this feature, the fixed schedule was not strongly preferred. Increases in the probability used to generate the random interval resulted in decreased preferences for the fixed schedule. In addition, the number of consecutive choices on the preferred alternative varied directly with preference, whereas the consecutive number of choices on the nonpreferred alternative was fairly constant. The probability of choosing the random alternative was unaffected by the immediately prior interval encountered on that schedule, even when it was very long relative to the average value. The results loosely support conceptions of a "preference for variability" from foraging theory and the "utility of behavioral variability" from human decision-making literatures. PMID:15828591

  18. Perceptual interference decays over short unfilled intervals.

    PubMed

    Schulkind, M D

    2000-09-01

    The perceptual interference effect refers to the fact that object identification is directly related to the amount of information available at initial exposure. The present article investigated whether perceptual interference would dissipate when a short, unfilled interval was introduced between exposures to a degraded object. Across three experiments using both musical and pictorial stimuli, identification performance increased directly with the length of the unfilled interval. Consequently, significant perceptual interference was obtained only when the interval between exposures was relatively short (< 500 msec for melodies; < 300 msec for pictures). These results are consistent with explanations that attribute perceptual interference to increased perceptual noise created by exposures to highly degraded objects. The data also suggest that perceptual interference is mediated by systems that are not consciously controlled by the subject and that perceptual interference in the visual domain decays more rapidly than perceptual interference in the auditory domain. PMID:11105520

  19. Variations in rupture process with recurrence interval in a repeated small earthquake

    USGS Publications Warehouse

    Vidale, J.E.; Ellsworth, W.L.; Cole, A.; Marone, C.

    1994-01-01

    In theory and in laboratory experiments, friction on sliding surfaces such as rock, glass and metal increases with time since the previous episode of slip. This time dependence is a central pillar of the friction laws widely used to model earthquake phenomena. On natural faults, other properties, such as rupture velocity, porosity and fluid pressure, may also vary with the recurrence interval. Eighteen repetitions of the same small earthquake, separated by intervals ranging from a few days to several years, allow us to test these laboratory predictions in situ. The events with the longest time since the previous earthquake tend to have about 15% larger seismic moment than those with the shortest intervals, although this trend is weak. In addition, the rupture durations of the events with the longest recurrence intervals are more than a factor of two shorter than for the events with the shortest intervals. Both decreased duration and increased friction are consistent with progressive fault healing during the time of stationary contact.In theory and in laboratory experiments, friction on sliding surfaces such as rock, glass and metal increases with time since the previous episode of slip. This time dependence is a central pillar of the friction laws widely used to model earthquake phenomena. On natural faults, other properties, such as rupture velocity, porosity and fluid pressure, may also vary with the recurrence interval. Eighteen repetitions of the same small earthquake, separated by intervals ranging from a few days to several years, allow us to test these laboratory predictions in situ. The events with the longest time since the previous earthquake tend to have about 15% larger seismic moment than those with the shortest intervals, although this trend is weak. In addition, the rupture durations of the events with the longest recurrence intervals are more than a factor of two shorter than for the events with the shortest intervals. Both decreased duration and

  20. Intervality and coherence in complex networks.

    PubMed

    Domínguez-García, Virginia; Johnson, Samuel; Muñoz, Miguel A

    2016-06-01

    Food webs-networks of predators and prey-have long been known to exhibit "intervality": species can generally be ordered along a single axis in such a way that the prey of any given predator tend to lie on unbroken compact intervals. Although the meaning of this axis-usually identified with a "niche" dimension-has remained a mystery, it is assumed to lie at the basis of the highly non-trivial structure of food webs. With this in mind, most trophic network modelling has for decades been based on assigning species a niche value by hand. However, we argue here that intervality should not be considered the cause but rather a consequence of food-web structure. First, analysing a set of 46 empirical food webs, we find that they also exhibit predator intervality: the predators of any given species are as likely to be contiguous as the prey are, but in a different ordering. Furthermore, this property is not exclusive of trophic networks: several networks of genes, neurons, metabolites, cellular machines, airports, and words are found to be approximately as interval as food webs. We go on to show that a simple model of food-web assembly which does not make use of a niche axis can nevertheless generate significant intervality. Therefore, the niche dimension (in the sense used for food-web modelling) could in fact be the consequence of other, more fundamental structural traits. We conclude that a new approach to food-web modelling is required for a deeper understanding of ecosystem assembly, structure, and function, and propose that certain topological features thought to be specific of food webs are in fact common to many complex networks. PMID:27368797

  1. Intervality and coherence in complex networks

    NASA Astrophysics Data System (ADS)

    Domínguez-García, Virginia; Johnson, Samuel; Muñoz, Miguel A.

    2016-06-01

    Food webs—networks of predators and prey—have long been known to exhibit "intervality": species can generally be ordered along a single axis in such a way that the prey of any given predator tend to lie on unbroken compact intervals. Although the meaning of this axis—usually identified with a "niche" dimension—has remained a mystery, it is assumed to lie at the basis of the highly non-trivial structure of food webs. With this in mind, most trophic network modelling has for decades been based on assigning species a niche value by hand. However, we argue here that intervality should not be considered the cause but rather a consequence of food-web structure. First, analysing a set of 46 empirical food webs, we find that they also exhibit predator intervality: the predators of any given species are as likely to be contiguous as the prey are, but in a different ordering. Furthermore, this property is not exclusive of trophic networks: several networks of genes, neurons, metabolites, cellular machines, airports, and words are found to be approximately as interval as food webs. We go on to show that a simple model of food-web assembly which does not make use of a niche axis can nevertheless generate significant intervality. Therefore, the niche dimension (in the sense used for food-web modelling) could in fact be the consequence of other, more fundamental structural traits. We conclude that a new approach to food-web modelling is required for a deeper understanding of ecosystem assembly, structure, and function, and propose that certain topological features thought to be specific of food webs are in fact common to many complex networks.