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Sample records for sequential sampling models

  1. Likelihood ratio sequential sampling models of recognition memory.

    Science.gov (United States)

    Osth, Adam F; Dennis, Simon; Heathcote, Andrew

    2017-02-01

    The mirror effect - a phenomenon whereby a manipulation produces opposite effects on hit and false alarm rates - is benchmark regularity of recognition memory. A likelihood ratio decision process, basing recognition on the relative likelihood that a stimulus is a target or a lure, naturally predicts the mirror effect, and so has been widely adopted in quantitative models of recognition memory. Glanzer, Hilford, and Maloney (2009) demonstrated that likelihood ratio models, assuming Gaussian memory strength, are also capable of explaining regularities observed in receiver-operating characteristics (ROCs), such as greater target than lure variance. Despite its central place in theorising about recognition memory, however, this class of models has not been tested using response time (RT) distributions. In this article, we develop a linear approximation to the likelihood ratio transformation, which we show predicts the same regularities as the exact transformation. This development enabled us to develop a tractable model of recognition-memory RT based on the diffusion decision model (DDM), with inputs (drift rates) provided by an approximate likelihood ratio transformation. We compared this "LR-DDM" to a standard DDM where all targets and lures receive their own drift rate parameters. Both were implemented as hierarchical Bayesian models and applied to four datasets. Model selection taking into account parsimony favored the LR-DDM, which requires fewer parameters than the standard DDM but still fits the data well. These results support log-likelihood based models as providing an elegant explanation of the regularities of recognition memory, not only in terms of choices made but also in terms of the times it takes to make them. Copyright © 2016 Elsevier Inc. All rights reserved.

  2. An Efficient Constraint Boundary Sampling Method for Sequential RBDO Using Kriging Surrogate Model

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jihoon; Jang, Junyong; Kim, Shinyu; Lee, Tae Hee [Hanyang Univ., Seoul (Korea, Republic of); Cho, Sugil; Kim, Hyung Woo; Hong, Sup [Korea Research Institute of Ships and Ocean Engineering, Busan (Korea, Republic of)

    2016-06-15

    Reliability-based design optimization (RBDO) requires a high computational cost owing to its reliability analysis. A surrogate model is introduced to reduce the computational cost in RBDO. The accuracy of the reliability depends on the accuracy of the surrogate model of constraint boundaries in the surrogated-model-based RBDO. In earlier researches, constraint boundary sampling (CBS) was proposed to approximate accurately the boundaries of constraints by locating sample points on the boundaries of constraints. However, because CBS uses sample points on all constraint boundaries, it creates superfluous sample points. In this paper, efficient constraint boundary sampling (ECBS) is proposed to enhance the efficiency of CBS. ECBS uses the statistical information of a kriging surrogate model to locate sample points on or near the RBDO solution. The efficiency of ECBS is verified by mathematical examples.

  3. Modelling sequentially scored item responses

    NARCIS (Netherlands)

    Akkermans, W.

    2000-01-01

    The sequential model can be used to describe the variable resulting from a sequential scoring process. In this paper two more item response models are investigated with respect to their suitability for sequential scoring: the partial credit model and the graded response model. The investigation is

  4. Adaptive decision making in a dynamic environment: a test of a sequential sampling model of relative judgment.

    Science.gov (United States)

    Vuckovic, Anita; Kwantes, Peter J; Neal, Andrew

    2013-09-01

    Research has identified a wide range of factors that influence performance in relative judgment tasks. However, the findings from this research have been inconsistent. Studies have varied with respect to the identification of causal variables and the perceptual and decision-making mechanisms underlying performance. Drawing on the ecological rationality approach, we present a theory of the judgment and decision-making processes involved in a relative judgment task that explains how people judge a stimulus and adapt their decision process to accommodate their own uncertainty associated with those judgments. Undergraduate participants performed a simulated air traffic control conflict detection task. Across two experiments, we systematically manipulated variables known to affect performance. In the first experiment, we manipulated the relative distances of aircraft to a common destination while holding aircraft speeds constant. In a follow-up experiment, we introduced a direct manipulation of relative speed. We then fit a sequential sampling model to the data, and used the best fitting parameters to infer the decision-making processes responsible for performance. Findings were consistent with the theory that people adapt to their own uncertainty by adjusting their criterion and the amount of time they take to collect evidence in order to make a more accurate decision. From a practical perspective, the paper demonstrates that one can use a sequential sampling model to understand performance in a dynamic environment, allowing one to make sense of and interpret complex patterns of empirical findings that would otherwise be difficult to interpret using standard statistical analyses. PsycINFO Database Record (c) 2013 APA, all rights reserved.

  5. Effects of model complexity and priors on estimation using sequential importance sampling/resampling for species conservation

    Science.gov (United States)

    Dunham, Kylee; Grand, James B.

    2016-01-01

    We examined the effects of complexity and priors on the accuracy of models used to estimate ecological and observational processes, and to make predictions regarding population size and structure. State-space models are useful for estimating complex, unobservable population processes and making predictions about future populations based on limited data. To better understand the utility of state space models in evaluating population dynamics, we used them in a Bayesian framework and compared the accuracy of models with differing complexity, with and without informative priors using sequential importance sampling/resampling (SISR). Count data were simulated for 25 years using known parameters and observation process for each model. We used kernel smoothing to reduce the effect of particle depletion, which is common when estimating both states and parameters with SISR. Models using informative priors estimated parameter values and population size with greater accuracy than their non-informative counterparts. While the estimates of population size and trend did not suffer greatly in models using non-informative priors, the algorithm was unable to accurately estimate demographic parameters. This model framework provides reasonable estimates of population size when little to no information is available; however, when information on some vital rates is available, SISR can be used to obtain more precise estimates of population size and process. Incorporating model complexity such as that required by structured populations with stage-specific vital rates affects precision and accuracy when estimating latent population variables and predicting population dynamics. These results are important to consider when designing monitoring programs and conservation efforts requiring management of specific population segments.

  6. MaxEnt queries and sequential sampling

    International Nuclear Information System (INIS)

    Riegler, Peter; Caticha, Nestor

    2001-01-01

    In this paper we pose the question: After gathering N data points, at what value of the control parameter should the next measurement be done? We propose an on-line algorithm which samples optimally by maximizing the gain in information on the parameters to be measured. We show analytically that the information gain is maximum for those potential measurements whose outcome is most unpredictable, i.e. for which the predictive distribution has maximum entropy. The resulting algorithm is applied to exponential analysis

  7. Sequential determination of important ecotoxic radionuclides in nuclear waste samples

    International Nuclear Information System (INIS)

    Bilohuscin, J.

    2016-01-01

    In the dissertation thesis we focused on the development and optimization of a sequential determination method for radionuclides 93 Zr, 94 Nb, 99 Tc and 126 Sn, employing extraction chromatography sorbents TEVA (R) Resin and Anion Exchange Resin, supplied by Eichrom Industries. Prior to the attestation of sequential separation of these proposed radionuclides from radioactive waste samples, a unique sequential procedure of 90 Sr, 239 Pu, 241 Am separation from urine matrices was tried, using molecular recognition sorbents of AnaLig (R) series and extraction chromatography sorbent DGA (R) Resin. On these experiments, four various sorbents were continually used for separation, including PreFilter Resin sorbent, which removes interfering organic materials present in raw urine. After the acquisition of positive results of this sequential procedure followed experiments with a 126 Sn separation using TEVA (R) Resin and Anion Exchange Resin sorbents. Radiochemical recoveries obtained from samples of radioactive evaporate concentrates and sludge showed high efficiency of the separation, while values of 126 Sn were under the minimum detectable activities MDA. Activity of 126 Sn was determined after ingrowth of daughter nuclide 126m Sb on HPGe gamma detector, with minimal contamination of gamma interfering radionuclides with decontamination factors (D f ) higher then 1400 for 60 Co and 47000 for 137 Cs. Based on the acquired experiments and results of these separation procedures, a complex method of sequential separation of 93 Zr, 94 Nb, 99 Tc and 126 Sn was proposed, which included optimization steps similar to those used in previous parts of the dissertation work. Application of the sequential separation method for sorbents TEVA (R) Resin and Anion Exchange Resin on real samples of radioactive wastes provided satisfactory results and an economical, time sparing, efficient method. (author)

  8. Sequential and Simultaneous Logit: A Nested Model.

    NARCIS (Netherlands)

    van Ophem, J.C.M.; Schram, A.J.H.C.

    1997-01-01

    A nested model is presented which has both the sequential and the multinomial logit model as special cases. This model provides a simple test to investigate the validity of these specifications. Some theoretical properties of the model are discussed. In the analysis a distribution function is

  9. Sequential sampling: a novel method in farm animal welfare assessment.

    Science.gov (United States)

    Heath, C A E; Main, D C J; Mullan, S; Haskell, M J; Browne, W J

    2016-02-01

    Lameness in dairy cows is an important welfare issue. As part of a welfare assessment, herd level lameness prevalence can be estimated from scoring a sample of animals, where higher levels of accuracy are associated with larger sample sizes. As the financial cost is related to the number of cows sampled, smaller samples are preferred. Sequential sampling schemes have been used for informing decision making in clinical trials. Sequential sampling involves taking samples in stages, where sampling can stop early depending on the estimated lameness prevalence. When welfare assessment is used for a pass/fail decision, a similar approach could be applied to reduce the overall sample size. The sampling schemes proposed here apply the principles of sequential sampling within a diagnostic testing framework. This study develops three sequential sampling schemes of increasing complexity to classify 80 fully assessed UK dairy farms, each with known lameness prevalence. Using the Welfare Quality herd-size-based sampling scheme, the first 'basic' scheme involves two sampling events. At the first sampling event half the Welfare Quality sample size is drawn, and then depending on the outcome, sampling either stops or is continued and the same number of animals is sampled again. In the second 'cautious' scheme, an adaptation is made to ensure that correctly classifying a farm as 'bad' is done with greater certainty. The third scheme is the only scheme to go beyond lameness as a binary measure and investigates the potential for increasing accuracy by incorporating the number of severely lame cows into the decision. The three schemes are evaluated with respect to accuracy and average sample size by running 100 000 simulations for each scheme, and a comparison is made with the fixed size Welfare Quality herd-size-based sampling scheme. All three schemes performed almost as well as the fixed size scheme but with much smaller average sample sizes. For the third scheme, an overall

  10. Sensitivity Analysis in Sequential Decision Models.

    Science.gov (United States)

    Chen, Qiushi; Ayer, Turgay; Chhatwal, Jagpreet

    2017-02-01

    Sequential decision problems are frequently encountered in medical decision making, which are commonly solved using Markov decision processes (MDPs). Modeling guidelines recommend conducting sensitivity analyses in decision-analytic models to assess the robustness of the model results against the uncertainty in model parameters. However, standard methods of conducting sensitivity analyses cannot be directly applied to sequential decision problems because this would require evaluating all possible decision sequences, typically in the order of trillions, which is not practically feasible. As a result, most MDP-based modeling studies do not examine confidence in their recommended policies. In this study, we provide an approach to estimate uncertainty and confidence in the results of sequential decision models. First, we provide a probabilistic univariate method to identify the most sensitive parameters in MDPs. Second, we present a probabilistic multivariate approach to estimate the overall confidence in the recommended optimal policy considering joint uncertainty in the model parameters. We provide a graphical representation, which we call a policy acceptability curve, to summarize the confidence in the optimal policy by incorporating stakeholders' willingness to accept the base case policy. For a cost-effectiveness analysis, we provide an approach to construct a cost-effectiveness acceptability frontier, which shows the most cost-effective policy as well as the confidence in that for a given willingness to pay threshold. We demonstrate our approach using a simple MDP case study. We developed a method to conduct sensitivity analysis in sequential decision models, which could increase the credibility of these models among stakeholders.

  11. POLYP: an automatic device for drawing sequential samples of gas

    Energy Technology Data Exchange (ETDEWEB)

    Gaglione, P; Koechler, C; Stanchi, L

    1974-12-01

    Polyp is an automatic device consisting of electronic equipment which drives sequentially 8 small pumps for drawing samples of gas. The electronic circuit is driven by a quartz oscillator and allows for the preselection of a waiting time in such a manner that a set of similar instruments placed in suitable position in the open country will start simultaneously. At the same time the first pump of each instrument will inflate a plastic bag for a preset time. The other seven pumps will inflate sequentially the other bags. The instrument is powered by rechargeable batteries and realized with C-MUS integrated circuits for a nearly negligible consumption. As it is foreseen for field operation it is waterproof.

  12. POLYP: an automatic device for drawing sequential samples of gas

    International Nuclear Information System (INIS)

    Gaglione, P.; Koechler, C.; Stanchi, L.

    1974-12-01

    POLYP is an automatic device consisting of an electronic equipment which drives sequentially 8 small pumps for drawing samples of gas. The electronic circuit is driven by a quartz oscillator and allows for the preselection of a waiting time in such a manner that a set of similar instruments placed in suitable position in the open country will start simultaneously. At the same time the first pump of each instrument will inflate a plastic bag for a preset time. Thereafter the other seven pumps will inflate sequentially the other bag. The instrument is powered by rechargeable batteries and realized with C-MOS integrated circuits for a nearly negligible consumption. As it is foreseen for field operation it is waterproof

  13. Sequential neural models with stochastic layers

    DEFF Research Database (Denmark)

    Fraccaro, Marco; Sønderby, Søren Kaae; Paquet, Ulrich

    2016-01-01

    How can we efficiently propagate uncertainty in a latent state representation with recurrent neural networks? This paper introduces stochastic recurrent neural networks which glue a deterministic recurrent neural network and a state space model together to form a stochastic and sequential neural...... generative model. The clear separation of deterministic and stochastic layers allows a structured variational inference network to track the factorization of the model's posterior distribution. By retaining both the nonlinear recursive structure of a recurrent neural network and averaging over...

  14. The subtyping of primary aldosteronism by adrenal vein sampling: sequential blood sampling causes factitious lateralization.

    Science.gov (United States)

    Rossitto, Giacomo; Battistel, Michele; Barbiero, Giulio; Bisogni, Valeria; Maiolino, Giuseppe; Diego, Miotto; Seccia, Teresa M; Rossi, Gian Paolo

    2018-02-01

    The pulsatile secretion of adrenocortical hormones and a stress reaction occurring when starting adrenal vein sampling (AVS) can affect the selectivity and also the assessment of lateralization when sequential blood sampling is used. We therefore tested the hypothesis that a simulated sequential blood sampling could decrease the diagnostic accuracy of lateralization index for identification of aldosterone-producing adenoma (APA), as compared with bilaterally simultaneous AVS. In 138 consecutive patients who underwent subtyping of primary aldosteronism, we compared the results obtained simultaneously bilaterally when starting AVS (t-15) and 15 min after (t0), with those gained with a simulated sequential right-to-left AVS technique (R ⇒ L) created by combining hormonal values obtained at t-15 and at t0. The concordance between simultaneously obtained values at t-15 and t0, and between simultaneously obtained values and values gained with a sequential R ⇒ L technique, was also assessed. We found a marked interindividual variability of lateralization index values in the patients with bilaterally selective AVS at both time point. However, overall the lateralization index simultaneously determined at t0 provided a more accurate identification of APA than the simulated sequential lateralization indexR ⇒ L (P = 0.001). Moreover, regardless of which side was sampled first, the sequential AVS technique induced a sequence-dependent overestimation of lateralization index. While in APA patients the concordance between simultaneous AVS at t0 and t-15 and between simultaneous t0 and sequential technique was moderate-to-good (K = 0.55 and 0.66, respectively), in non-APA patients, it was poor (K = 0.12 and 0.13, respectively). Sequential AVS generates factitious between-sides gradients, which lower its diagnostic accuracy, likely because of the stress reaction arising upon starting AVS.

  15. Sequential sampling of visual objects during sustained attention.

    Directory of Open Access Journals (Sweden)

    Jianrong Jia

    2017-06-01

    Full Text Available In a crowded visual scene, attention must be distributed efficiently and flexibly over time and space to accommodate different contexts. It is well established that selective attention enhances the corresponding neural responses, presumably implying that attention would persistently dwell on the task-relevant item. Meanwhile, recent studies, mostly in divided attentional contexts, suggest that attention does not remain stationary but samples objects alternately over time, suggesting a rhythmic view of attention. However, it remains unknown whether the dynamic mechanism essentially mediates attentional processes at a general level. Importantly, there is also a complete lack of direct neural evidence reflecting whether and how the brain rhythmically samples multiple visual objects during stimulus processing. To address these issues, in this study, we employed electroencephalography (EEG and a temporal response function (TRF approach, which can dissociate responses that exclusively represent a single object from the overall neuronal activity, to examine the spatiotemporal characteristics of attention in various attentional contexts. First, attention, which is characterized by inhibitory alpha-band (approximately 10 Hz activity in TRFs, switches between attended and unattended objects every approximately 200 ms, suggesting a sequential sampling even when attention is required to mostly stay on the attended object. Second, the attentional spatiotemporal pattern is modulated by the task context, such that alpha-mediated switching becomes increasingly prominent as the task requires a more uniform distribution of attention. Finally, the switching pattern correlates with attentional behavioral performance. Our work provides direct neural evidence supporting a generally central role of temporal organization mechanism in attention, such that multiple objects are sequentially sorted according to their priority in attentional contexts. The results suggest

  16. Sequential Sampling Plan of Anthonomus grandis (Coleoptera: Curculionidae) in Cotton Plants.

    Science.gov (United States)

    Grigolli, J F J; Souza, L A; Mota, T A; Fernandes, M G; Busoli, A C

    2017-04-01

    The boll weevil, Anthonomus grandis grandis Boheman (Coleoptera: Curculionidae), is one of the most important pests of cotton production worldwide. The objective of this work was to develop a sequential sampling plan for the boll weevil. The studies were conducted in Maracaju, MS, Brazil, in two seasons with cotton cultivar FM 993. A 10,000-m2 area of cotton was subdivided into 100 of 10- by 10-m plots, and five plants per plot were evaluated weekly, recording the number of squares with feeding + oviposition punctures of A. grandis in each plant. A sequential sampling plan by the maximum likelihood ratio test was developed, using a 10% threshold level of squares attacked. A 5% security level was adopted for the elaboration of the sequential sampling plan. The type I and type II error used was 0.05, recommended for studies with insects. The adjustment of the frequency distributions used were divided into two phases, so that the model that best fit to the data was the negative binomial distribution up to 85 DAE (Phase I), and from there the best fit was Poisson distribution (Phase II). The equations that define the decision-making for Phase I are S0 = -5.1743 + 0.5730N and S1 = 5.1743 + 0.5730N, and for the Phase II are S0 = -4.2479 + 0.5771N and S1 = 4.2479 + 0.5771N. The sequential sampling plan developed indicated the maximum number of sample units expected for decision-making is ∼39 and 31 samples for Phases I and II, respectively. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  17. Adrenal vein sampling in primary aldosteronism: concordance of simultaneous vs sequential sampling.

    Science.gov (United States)

    Almarzooqi, Mohamed-Karji; Chagnon, Miguel; Soulez, Gilles; Giroux, Marie-France; Gilbert, Patrick; Oliva, Vincent L; Perreault, Pierre; Bouchard, Louis; Bourdeau, Isabelle; Lacroix, André; Therasse, Eric

    2017-02-01

    Many investigators believe that basal adrenal venous sampling (AVS) should be done simultaneously, whereas others opt for sequential AVS for simplicity and reduced cost. This study aimed to evaluate the concordance of sequential and simultaneous AVS methods. Between 1989 and 2015, bilateral simultaneous sets of basal AVS were obtained twice within 5 min, in 188 consecutive patients (59 women and 129 men; mean age: 53.4 years). Selectivity was defined by adrenal-to-peripheral cortisol ratio ≥2, and lateralization was defined as an adrenal aldosterone-to-cortisol ratio ≥2, the contralateral side. Sequential AVS was simulated using right sampling at -5 min (t = -5) and left sampling at 0 min (t = 0). There was no significant difference in mean selectivity ratio (P = 0.12 and P = 0.42 for the right and left sides respectively) and in mean lateralization ratio (P = 0.93) between t = -5 and t = 0. Kappa for selectivity between 2 simultaneous AVS was 0.71 (95% CI: 0.60-0.82), whereas it was 0.84 (95% CI: 0.76-0.92) and 0.85 (95% CI: 0.77-0.93) between sequential and simultaneous AVS at respectively -5 min and at 0 min. Kappa for lateralization between 2 simultaneous AVS was 0.84 (95% CI: 0.75-0.93), whereas it was 0.86 (95% CI: 0.78-0.94) and 0.80 (95% CI: 0.71-0.90) between sequential AVS and simultaneous AVS at respectively -5 min at 0 min. Concordance between simultaneous and sequential AVS was not different than that between 2 repeated simultaneous AVS in the same patient. Therefore, a better diagnostic performance is not a good argument to select the AVS method. © 2017 European Society of Endocrinology.

  18. Parameter sampling capabilities of sequential and simultaneous data assimilation: I. Analytical comparison

    International Nuclear Information System (INIS)

    Fossum, Kristian; Mannseth, Trond

    2014-01-01

    We assess the parameter sampling capabilities of some Bayesian, ensemble-based, joint state-parameter (JS) estimation methods. The forward model is assumed to be non-chaotic and have nonlinear components, and the emphasis is on results obtained for the parameters in the state-parameter vector. A variety of approximate sampling methods exist, and a number of numerical comparisons between such methods have been performed. Often, more than one of the defining characteristics vary from one method to another, so it can be difficult to point out which characteristic of the more successful method in such a comparison was decisive. In this study, we single out one defining characteristic for comparison; whether or not data are assimilated sequentially or simultaneously. The current paper is concerned with analytical investigations into this issue. We carefully select one sequential and one simultaneous JS method for the comparison. We also design a corresponding pair of pure parameter estimation methods, and we show how the JS methods and the parameter estimation methods are pairwise related. It is shown that the sequential and the simultaneous parameter estimation methods are equivalent for one particular combination of observations with different degrees of nonlinearity. Strong indications are presented for why one may expect the sequential parameter estimation method to outperform the simultaneous parameter estimation method for all other combinations of observations. Finally, the conditions for when similar relations can be expected to hold between the corresponding JS methods are discussed. A companion paper, part II (Fossum and Mannseth 2014 Inverse Problems 30 114003), is concerned with statistical analysis of results from a range of numerical experiments involving sequential and simultaneous JS estimation, where the design of the numerical investigation is motivated by our findings in the current paper. (paper)

  19. Plane-Based Sampling for Ray Casting Algorithm in Sequential Medical Images

    Science.gov (United States)

    Lin, Lili; Chen, Shengyong; Shao, Yan; Gu, Zichun

    2013-01-01

    This paper proposes a plane-based sampling method to improve the traditional Ray Casting Algorithm (RCA) for the fast reconstruction of a three-dimensional biomedical model from sequential images. In the novel method, the optical properties of all sampling points depend on the intersection points when a ray travels through an equidistant parallel plan cluster of the volume dataset. The results show that the method improves the rendering speed at over three times compared with the conventional algorithm and the image quality is well guaranteed. PMID:23424608

  20. Sequential effects in pigeon delayed matching-to-sample performance.

    Science.gov (United States)

    Roitblat, H L; Scopatz, R A

    1983-04-01

    Pigeons were tested in a three-alternative delayed matching-to-sample task in which second-choices were permitted following first-choice errors. Sequences of responses both within and between trials were examined in three experiments. The first experiment demonstrates that the sample information contained in first-choice errors is not sufficient to account for the observed pattern of second choices. This result implies that second-choices following first-choice errors are based on a second examination of the contents of working memory. Proactive interference was found in the second experiment in the form of a dependency, beyond that expected on the basis of trial independent response bias, of first-choices from one trial on the first-choice emitted on the previous trial. Samples from the previous trial were not found to exert a significant influence on later trials. The magnitude of the intertrial association (Experiment 3) did not depend on the duration of the intertrial interval. In contrast, longer intertrial intervals and longer sample durations did facilitate choice accuracy, by strengthening the association between current samples and choices. These results are incompatible with a trace-decay and competition model; they suggest strongly that multiple influences act simultaneously and independently to control delayed matching-to-sample responding. These multiple influences include memory for the choice occurring on the previous trial, memory for the sample, and general effects of trial spacing.

  1. Parameter sampling capabilities of sequential and simultaneous data assimilation: II. Statistical analysis of numerical results

    International Nuclear Information System (INIS)

    Fossum, Kristian; Mannseth, Trond

    2014-01-01

    We assess and compare parameter sampling capabilities of one sequential and one simultaneous Bayesian, ensemble-based, joint state-parameter (JS) estimation method. In the companion paper, part I (Fossum and Mannseth 2014 Inverse Problems 30 114002), analytical investigations lead us to propose three claims, essentially stating that the sequential method can be expected to outperform the simultaneous method for weakly nonlinear forward models. Here, we assess the reliability and robustness of these claims through statistical analysis of results from a range of numerical experiments. Samples generated by the two approximate JS methods are compared to samples from the posterior distribution generated by a Markov chain Monte Carlo method, using four approximate measures of distance between probability distributions. Forward-model nonlinearity is assessed from a stochastic nonlinearity measure allowing for sufficiently large model dimensions. Both toy models (with low computational complexity, and where the nonlinearity is fairly easy to control) and two-phase porous-media flow models (corresponding to down-scaled versions of problems to which the JS methods have been frequently applied recently) are considered in the numerical experiments. Results from the statistical analysis show strong support of all three claims stated in part I. (paper)

  2. Fractionation of plutonium in environmental and bio-shielding concrete samples using dynamic sequential extraction

    DEFF Research Database (Denmark)

    Qiao, Jixin; Hou, Xiaolin

    2010-01-01

    Fractionation of plutonium isotopes (238Pu, 239,240Pu) in environmental samples (i.e. soil and sediment) and bio-shielding concrete from decommissioning of nuclear reactor were carried out by dynamic sequential extraction using an on-line sequential injection (SI) system combined with a specially...

  3. Sequential models for coarsening and missingness

    NARCIS (Netherlands)

    Gill, R.D.; Robins, J.M.

    1997-01-01

    In a companion paper we described what intuitively would seem to be the most general possible way to generate Coarsening at Random mechanisms a sequential procedure called randomized monotone coarsening Counterexamples showed that CAR mechanisms exist which cannot be represented in this way Here we

  4. Sequential and simultaneous choices: testing the diet selection and sequential choice models.

    Science.gov (United States)

    Freidin, Esteban; Aw, Justine; Kacelnik, Alex

    2009-03-01

    We investigate simultaneous and sequential choices in starlings, using Charnov's Diet Choice Model (DCM) and Shapiro, Siller and Kacelnik's Sequential Choice Model (SCM) to integrate function and mechanism. During a training phase, starlings encountered one food-related option per trial (A, B or R) in random sequence and with equal probability. A and B delivered food rewards after programmed delays (shorter for A), while R ('rejection') moved directly to the next trial without reward. In this phase we measured latencies to respond. In a later, choice, phase, birds encountered the pairs A-B, A-R and B-R, the first implementing a simultaneous choice and the second and third sequential choices. The DCM predicts when R should be chosen to maximize intake rate, and SCM uses latencies of the training phase to predict choices between any pair of options in the choice phase. The predictions of both models coincided, and both successfully predicted the birds' preferences. The DCM does not deal with partial preferences, while the SCM does, and experimental results were strongly correlated to this model's predictions. We believe that the SCM may expose a very general mechanism of animal choice, and that its wider domain of success reflects the greater ecological significance of sequential over simultaneous choices.

  5. A Sequential Kriging reliability analysis method with characteristics of adaptive sampling regions and parallelizability

    International Nuclear Information System (INIS)

    Wen, Zhixun; Pei, Haiqing; Liu, Hai; Yue, Zhufeng

    2016-01-01

    The sequential Kriging reliability analysis (SKRA) method has been developed in recent years for nonlinear implicit response functions which are expensive to evaluate. This type of method includes EGRA: the efficient reliability analysis method, and AK-MCS: the active learning reliability method combining Kriging model and Monte Carlo simulation. The purpose of this paper is to improve SKRA by adaptive sampling regions and parallelizability. The adaptive sampling regions strategy is proposed to avoid selecting samples in regions where the probability density is so low that the accuracy of these regions has negligible effects on the results. The size of the sampling regions is adapted according to the failure probability calculated by last iteration. Two parallel strategies are introduced and compared, aimed at selecting multiple sample points at a time. The improvement is verified through several troublesome examples. - Highlights: • The ISKRA method improves the efficiency of SKRA. • Adaptive sampling regions strategy reduces the number of needed samples. • The two parallel strategies reduce the number of needed iterations. • The accuracy of the optimal value impacts the number of samples significantly.

  6. Inverse problems with non-trivial priors: efficient solution through sequential Gibbs sampling

    DEFF Research Database (Denmark)

    Hansen, Thomas Mejer; Cordua, Knud Skou; Mosegaard, Klaus

    2012-01-01

    Markov chain Monte Carlo methods such as the Gibbs sampler and the Metropolis algorithm can be used to sample solutions to non-linear inverse problems. In principle, these methods allow incorporation of prior information of arbitrary complexity. If an analytical closed form description of the prior...... is available, which is the case when the prior can be described by a multidimensional Gaussian distribution, such prior information can easily be considered. In reality, prior information is often more complex than can be described by the Gaussian model, and no closed form expression of the prior can be given....... We propose an algorithm, called sequential Gibbs sampling, allowing the Metropolis algorithm to efficiently incorporate complex priors into the solution of an inverse problem, also for the case where no closed form description of the prior exists. First, we lay out the theoretical background...

  7. A sequential sampling account of response bias and speed-accuracy tradeoffs in a conflict detection task.

    Science.gov (United States)

    Vuckovic, Anita; Kwantes, Peter J; Humphreys, Michael; Neal, Andrew

    2014-03-01

    Signal Detection Theory (SDT; Green & Swets, 1966) is a popular tool for understanding decision making. However, it does not account for the time taken to make a decision, nor why response bias might change over time. Sequential sampling models provide a way of accounting for speed-accuracy trade-offs and response bias shifts. In this study, we test the validity of a sequential sampling model of conflict detection in a simulated air traffic control task by assessing whether two of its key parameters respond to experimental manipulations in a theoretically consistent way. Through experimental instructions, we manipulated participants' response bias and the relative speed or accuracy of their responses. The sequential sampling model was able to replicate the trends in the conflict responses as well as response time across all conditions. Consistent with our predictions, manipulating response bias was associated primarily with changes in the model's Criterion parameter, whereas manipulating speed-accuracy instructions was associated with changes in the Threshold parameter. The success of the model in replicating the human data suggests we can use the parameters of the model to gain an insight into the underlying response bias and speed-accuracy preferences common to dynamic decision-making tasks. © 2013 American Psychological Association

  8. Sequential and Parallel Attack Tree Modelling

    NARCIS (Netherlands)

    Arnold, Florian; Guck, Dennis; Kumar, Rajesh; Stoelinga, Mariëlle Ida Antoinette; Koornneef, Floor; van Gulijk, Coen

    The intricacy of socio-technical systems requires a careful planning and utilisation of security resources to ensure uninterrupted, secure and reliable services. Even though many studies have been conducted to understand and model the behaviour of a potential attacker, the detection of crucial

  9. Value-based decision making via sequential sampling with hierarchical competition and attentional modulation.

    Science.gov (United States)

    Colas, Jaron T

    2017-01-01

    In principle, formal dynamical models of decision making hold the potential to represent fundamental computations underpinning value-based (i.e., preferential) decisions in addition to perceptual decisions. Sequential-sampling models such as the race model and the drift-diffusion model that are grounded in simplicity, analytical tractability, and optimality remain popular, but some of their more recent counterparts have instead been designed with an aim for more feasibility as architectures to be implemented by actual neural systems. Connectionist models are proposed herein at an intermediate level of analysis that bridges mental phenomena and underlying neurophysiological mechanisms. Several such models drawing elements from the established race, drift-diffusion, feedforward-inhibition, divisive-normalization, and competing-accumulator models were tested with respect to fitting empirical data from human participants making choices between foods on the basis of hedonic value rather than a traditional perceptual attribute. Even when considering performance at emulating behavior alone, more neurally plausible models were set apart from more normative race or drift-diffusion models both quantitatively and qualitatively despite remaining parsimonious. To best capture the paradigm, a novel six-parameter computational model was formulated with features including hierarchical levels of competition via mutual inhibition as well as a static approximation of attentional modulation, which promotes "winner-take-all" processing. Moreover, a meta-analysis encompassing several related experiments validated the robustness of model-predicted trends in humans' value-based choices and concomitant reaction times. These findings have yet further implications for analysis of neurophysiological data in accordance with computational modeling, which is also discussed in this new light.

  10. Value-based decision making via sequential sampling with hierarchical competition and attentional modulation.

    Directory of Open Access Journals (Sweden)

    Jaron T Colas

    Full Text Available In principle, formal dynamical models of decision making hold the potential to represent fundamental computations underpinning value-based (i.e., preferential decisions in addition to perceptual decisions. Sequential-sampling models such as the race model and the drift-diffusion model that are grounded in simplicity, analytical tractability, and optimality remain popular, but some of their more recent counterparts have instead been designed with an aim for more feasibility as architectures to be implemented by actual neural systems. Connectionist models are proposed herein at an intermediate level of analysis that bridges mental phenomena and underlying neurophysiological mechanisms. Several such models drawing elements from the established race, drift-diffusion, feedforward-inhibition, divisive-normalization, and competing-accumulator models were tested with respect to fitting empirical data from human participants making choices between foods on the basis of hedonic value rather than a traditional perceptual attribute. Even when considering performance at emulating behavior alone, more neurally plausible models were set apart from more normative race or drift-diffusion models both quantitatively and qualitatively despite remaining parsimonious. To best capture the paradigm, a novel six-parameter computational model was formulated with features including hierarchical levels of competition via mutual inhibition as well as a static approximation of attentional modulation, which promotes "winner-take-all" processing. Moreover, a meta-analysis encompassing several related experiments validated the robustness of model-predicted trends in humans' value-based choices and concomitant reaction times. These findings have yet further implications for analysis of neurophysiological data in accordance with computational modeling, which is also discussed in this new light.

  11. Value-based decision making via sequential sampling with hierarchical competition and attentional modulation

    Science.gov (United States)

    2017-01-01

    In principle, formal dynamical models of decision making hold the potential to represent fundamental computations underpinning value-based (i.e., preferential) decisions in addition to perceptual decisions. Sequential-sampling models such as the race model and the drift-diffusion model that are grounded in simplicity, analytical tractability, and optimality remain popular, but some of their more recent counterparts have instead been designed with an aim for more feasibility as architectures to be implemented by actual neural systems. Connectionist models are proposed herein at an intermediate level of analysis that bridges mental phenomena and underlying neurophysiological mechanisms. Several such models drawing elements from the established race, drift-diffusion, feedforward-inhibition, divisive-normalization, and competing-accumulator models were tested with respect to fitting empirical data from human participants making choices between foods on the basis of hedonic value rather than a traditional perceptual attribute. Even when considering performance at emulating behavior alone, more neurally plausible models were set apart from more normative race or drift-diffusion models both quantitatively and qualitatively despite remaining parsimonious. To best capture the paradigm, a novel six-parameter computational model was formulated with features including hierarchical levels of competition via mutual inhibition as well as a static approximation of attentional modulation, which promotes “winner-take-all” processing. Moreover, a meta-analysis encompassing several related experiments validated the robustness of model-predicted trends in humans’ value-based choices and concomitant reaction times. These findings have yet further implications for analysis of neurophysiological data in accordance with computational modeling, which is also discussed in this new light. PMID:29077746

  12. The finite sample performance of estimators for mediation analysis under sequential conditional independence

    DEFF Research Database (Denmark)

    Huber, Martin; Lechner, Michael; Mellace, Giovanni

    Using a comprehensive simulation study based on empirical data, this paper investigates the finite sample properties of different classes of parametric and semi-parametric estimators of (natural) direct and indirect causal effects used in mediation analysis under sequential conditional independence...

  13. The finite sample performance of estimators for mediation analysis under sequential conditional independence

    DEFF Research Database (Denmark)

    Huber, Martin; Lechner, Michael; Mellace, Giovanni

    2016-01-01

    Using a comprehensive simulation study based on empirical data, this paper investigates the finite sample properties of different classes of parametric and semi-parametric estimators of (natural) direct and indirect causal effects used in mediation analysis under sequential conditional independen...... of the methods often (but not always) varies with the features of the data generating process....

  14. Models of sequential decision making in consumer lending

    OpenAIRE

    Kanshukan Rajaratnam; Peter A. Beling; George A. Overstreet

    2016-01-01

    Abstract In this paper, we introduce models of sequential decision making in consumer lending. From the definition of adverse selection in static lending models, we show that homogenous borrowers take-up offers at different instances of time when faced with a sequence of loan offers. We postulate that bounded rationality and diverse decision heuristics used by consumers drive the decisions they make about credit offers. Under that postulate, we show how observation of early decisions in a seq...

  15. A Sequential Optimization Sampling Method for Metamodels with Radial Basis Functions

    Science.gov (United States)

    Pan, Guang; Ye, Pengcheng; Yang, Zhidong

    2014-01-01

    Metamodels have been widely used in engineering design to facilitate analysis and optimization of complex systems that involve computationally expensive simulation programs. The accuracy of metamodels is strongly affected by the sampling methods. In this paper, a new sequential optimization sampling method is proposed. Based on the new sampling method, metamodels can be constructed repeatedly through the addition of sampling points, namely, extrema points of metamodels and minimum points of density function. Afterwards, the more accurate metamodels would be constructed by the procedure above. The validity and effectiveness of proposed sampling method are examined by studying typical numerical examples. PMID:25133206

  16. Efficient image duplicated region detection model using sequential block clustering

    Czech Academy of Sciences Publication Activity Database

    Sekeh, M. A.; Maarof, M. A.; Rohani, M. F.; Mahdian, Babak

    2013-01-01

    Roč. 10, č. 1 (2013), s. 73-84 ISSN 1742-2876 Institutional support: RVO:67985556 Keywords : Image forensic * Copy–paste forgery * Local block matching Subject RIV: IN - Informatics, Computer Science Impact factor: 0.986, year: 2013 http://library.utia.cas.cz/separaty/2013/ZOI/mahdian-efficient image duplicated region detection model using sequential block clustering.pdf

  17. Formal modelling and verification of interlocking systems featuring sequential release

    DEFF Research Database (Denmark)

    Vu, Linh Hong; Haxthausen, Anne Elisabeth; Peleska, Jan

    2017-01-01

    In this article, we present a method and an associated toolchain for the formal verification of the new Danish railway interlocking systems that are compatible with the European Train Control System (ETCS) Level 2. We have made a generic and reconfigurable model of the system behaviour and generic...... safety properties. This model accommodates sequential release - a feature in the new Danish interlocking systems. To verify the safety of an interlocking system, first a domain-specific description of interlocking configuration data is constructed and validated. Then the generic model and safety...

  18. A continuous-time neural model for sequential action.

    Science.gov (United States)

    Kachergis, George; Wyatte, Dean; O'Reilly, Randall C; de Kleijn, Roy; Hommel, Bernhard

    2014-11-05

    Action selection, planning and execution are continuous processes that evolve over time, responding to perceptual feedback as well as evolving top-down constraints. Existing models of routine sequential action (e.g. coffee- or pancake-making) generally fall into one of two classes: hierarchical models that include hand-built task representations, or heterarchical models that must learn to represent hierarchy via temporal context, but thus far lack goal-orientedness. We present a biologically motivated model of the latter class that, because it is situated in the Leabra neural architecture, affords an opportunity to include both unsupervised and goal-directed learning mechanisms. Moreover, we embed this neurocomputational model in the theoretical framework of the theory of event coding (TEC), which posits that actions and perceptions share a common representation with bidirectional associations between the two. Thus, in this view, not only does perception select actions (along with task context), but actions are also used to generate perceptions (i.e. intended effects). We propose a neural model that implements TEC to carry out sequential action control in hierarchically structured tasks such as coffee-making. Unlike traditional feedforward discrete-time neural network models, which use static percepts to generate static outputs, our biological model accepts continuous-time inputs and likewise generates non-stationary outputs, making short-timescale dynamic predictions. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  19. Demonstration of a longitudinal concentration gradient along scala tympani by sequential sampling of perilymph from the cochlear apex.

    Science.gov (United States)

    Mynatt, Robert; Hale, Shane A; Gill, Ruth M; Plontke, Stefan K; Salt, Alec N

    2006-06-01

    Local applications of drugs to the inner ear are increasingly being used to treat patients' inner ear disorders. Knowledge of the pharmacokinetics of drugs in the inner ear fluids is essential for a scientific basis for such treatments. When auditory function is of primary interest, the drug's kinetics in scala tympani (ST) must be established. Measurement of drug levels in ST is technically difficult because of the known contamination of perilymph samples taken from the basal cochlear turn with cerebrospinal fluid (CSF). Recently, we reported a technique in which perilymph was sampled from the cochlear apex to minimize the influence of CSF contamination (J. Neurosci. Methods, doi: 10.1016/j.jneumeth.2005.10.008 ). This technique has now been extended by taking smaller fluid samples sequentially from the cochlear apex, which can be used to quantify drug gradients along ST. The sampling and analysis methods were evaluated using an ionic marker, trimethylphenylammonium (TMPA), that was applied to the round window membrane. After loading perilymph with TMPA, 10 1-muL samples were taken from the cochlear apex. The TMPA content of the samples was consistent with the first sample containing perilymph from apical regions and the fourth or fifth sample containing perilymph from the basal turn. TMPA concentration decreased in subsequent samples, as they increasingly contained CSF that had passed through ST. Sample concentration curves were interpreted quantitatively by simulation of the experiment with a finite element model and by an automated curve-fitting method by which the apical-basal gradient was estimated. The study demonstrates that sequential apical sampling provides drug gradient data for ST perilymph while avoiding the major distortions of sample composition associated with basal turn sampling. The method can be used for any substance for which a sensitive assay is available and is therefore of high relevance for the development of preclinical and clinical

  20. Sequential sampling and biorational chemistries for management of lepidopteran pests of vegetable amaranth in the Caribbean.

    Science.gov (United States)

    Clarke-Harris, Dionne; Fleischer, Shelby J

    2003-06-01

    Although vegetable amaranth, Amaranthus viridis L. and A. dubius Mart. ex Thell., production and economic importance is increasing in diversified peri-urban farms in Jamaica, lepidopteran herbivory is common even during weekly pyrethroid applications. We developed and validated a sampling plan, and investigated insecticides with new modes of action, for a complex of five species (Pyralidae: Spoladea recurvalis (F.), Herpetogramma bipunctalis (F.), Noctuidae: Spodoptera exigua (Hubner), S. frugiperda (J. E. Smith), and S. eridania Stoll). Significant within-plant variation occurred with H. bipunctalis, and a six-leaf sample unit including leaves from the inner and outer whorl was selected to sample all species. Larval counts best fit a negative binomial distribution. We developed a sequential sampling plan using a threshold of one larva per sample unit and the fitted distribution with a k(c) of 0.645. When compared with a fixed plan of 25 plants, sequential sampling recommended the same management decision on 87.5%, additional samples on 9.4%, and gave inaccurate recommendations on 3.1% of 32 farms, while reducing sample size by 46%. Insecticide frequency was reduced 33-60% when management decisions were based on sampled data compared with grower-standards, with no effect on crop damage. Damage remained high or variable (10-46%) with pyrethroid applications. Lepidopteran control was dramatically improved with ecdysone agonists (tebufenozide) or microbial metabolites (spinosyns and emamectin benzoate). This work facilitates resistance management efforts concurrent with the introduction of newer modes of action for lepidopteran control in leafy vegetable production in the Caribbean.

  1. A Fixed-Precision Sequential Sampling Plan for the Potato Tuberworm Moth, Phthorimaea operculella Zeller (Lepidoptera: Gelechidae), on Potato Cultivars.

    Science.gov (United States)

    Shahbi, M; Rajabpour, A

    2017-08-01

    Phthorimaea operculella Zeller is an important pest of potato in Iran. Spatial distribution and fixed-precision sequential sampling for population estimation of the pest on two potato cultivars, Arinda ® and Sante ® , were studied in two separate potato fields during two growing seasons (2013-2014 and 2014-2015). Spatial distribution was investigated by Taylor's power law and Iwao's patchiness. Results showed that the spatial distribution of eggs and larvae was random. In contrast to Iwao's patchiness, Taylor's power law provided a highly significant relationship between variance and mean density. Therefore, fixed-precision sequential sampling plan was developed by Green's model at two precision levels of 0.25 and 0.1. The optimum sample size on Arinda ® and Sante ® cultivars at precision level of 0.25 ranged from 151 to 813 and 149 to 802 leaves, respectively. At 0.1 precision level, the sample sizes varied from 5083 to 1054 and 5100 to 1050 leaves for Arinda ® and Sante ® cultivars, respectively. Therefore, the optimum sample sizes for the cultivars, with different resistance levels, were not significantly different. According to the calculated stop lines, the sampling must be continued until cumulative number of eggs + larvae reached to 15-16 or 96-101 individuals at precision levels of 0.25 or 0.1, respectively. The performance of the sampling plan was validated by resampling analysis using resampling for validation of sampling plans software. The sampling plant provided in this study can be used to obtain a rapid estimate of the pest density with minimal effort.

  2. Sampling informative/complex a priori probability distributions using Gibbs sampling assisted by sequential simulation

    DEFF Research Database (Denmark)

    Hansen, Thomas Mejer; Mosegaard, Klaus; Cordua, Knud Skou

    2010-01-01

    Markov chain Monte Carlo methods such as the Gibbs sampler and the Metropolis algorithm can be used to sample the solutions to non-linear inverse problems. In principle these methods allow incorporation of arbitrarily complex a priori information, but current methods allow only relatively simple...... this algorithm with the Metropolis algorithm to obtain an efficient method for sampling posterior probability densities for nonlinear inverse problems....

  3. A novel approach for small sample size family-based association studies: sequential tests.

    Science.gov (United States)

    Ilk, Ozlem; Rajabli, Farid; Dungul, Dilay Ciglidag; Ozdag, Hilal; Ilk, Hakki Gokhan

    2011-08-01

    In this paper, we propose a sequential probability ratio test (SPRT) to overcome the problem of limited samples in studies related to complex genetic diseases. The results of this novel approach are compared with the ones obtained from the traditional transmission disequilibrium test (TDT) on simulated data. Although TDT classifies single-nucleotide polymorphisms (SNPs) to only two groups (SNPs associated with the disease and the others), SPRT has the flexibility of assigning SNPs to a third group, that is, those for which we do not have enough evidence and should keep sampling. It is shown that SPRT results in smaller ratios of false positives and negatives, as well as better accuracy and sensitivity values for classifying SNPs when compared with TDT. By using SPRT, data with small sample size become usable for an accurate association analysis.

  4. Spatial distribution and sequential sampling plans for Tuta absoluta (Lepidoptera: Gelechiidae) in greenhouse tomato crops.

    Science.gov (United States)

    Cocco, Arturo; Serra, Giuseppe; Lentini, Andrea; Deliperi, Salvatore; Delrio, Gavino

    2015-09-01

    The within- and between-plant distribution of the tomato leafminer, Tuta absoluta (Meyrick), was investigated in order to define action thresholds based on leaf infestation and to propose enumerative and binomial sequential sampling plans for pest management applications in protected crops. The pest spatial distribution was aggregated between plants, and median leaves were the most suitable sample to evaluate the pest density. Action thresholds of 36 and 48%, 43 and 56% and 60 and 73% infested leaves, corresponding to economic thresholds of 1 and 3% damaged fruits, were defined for tomato cultivars with big, medium and small fruits respectively. Green's method was a more suitable enumerative sampling plan as it required a lower sampling effort. Binomial sampling plans needed lower average sample sizes than enumerative plans to make a treatment decision, with probabilities of error of sampling plan required 87 or 343 leaves to estimate the population density in extensive or intensive ecological studies respectively. Binomial plans would be more practical and efficient for control purposes, needing average sample sizes of 17, 20 and 14 leaves to take a pest management decision in order to avoid fruit damage higher than 1% in cultivars with big, medium and small fruits respectively. © 2014 Society of Chemical Industry.

  5. Modeling sequential context effects in diagnostic interpretation of screening mammograms.

    Science.gov (United States)

    Alamudun, Folami; Paulus, Paige; Yoon, Hong-Jun; Tourassi, Georgia

    2018-07-01

    Prior research has shown that physicians' medical decisions can be influenced by sequential context, particularly in cases where successive stimuli exhibit similar characteristics when analyzing medical images. This type of systematic error is known to psychophysicists as sequential context effect as it indicates that judgments are influenced by features of and decisions about the preceding case in the sequence of examined cases, rather than being based solely on the peculiarities unique to the present case. We determine if radiologists experience some form of context bias, using screening mammography as the use case. To this end, we explore correlations between previous perceptual behavior and diagnostic decisions and current decisions. We hypothesize that a radiologist's visual search pattern and diagnostic decisions in previous cases are predictive of the radiologist's current diagnostic decisions. To test our hypothesis, we tasked 10 radiologists of varied experience to conduct blind reviews of 100 four-view screening mammograms. Eye-tracking data and diagnostic decisions were collected from each radiologist under conditions mimicking clinical practice. Perceptual behavior was quantified using the fractal dimension of gaze scanpath, which was computed using the Minkowski-Bouligand box-counting method. To test the effect of previous behavior and decisions, we conducted a multifactor fixed-effects ANOVA. Further, to examine the predictive value of previous perceptual behavior and decisions, we trained and evaluated a predictive model for radiologists' current diagnostic decisions. ANOVA tests showed that previous visual behavior, characterized by fractal analysis, previous diagnostic decisions, and image characteristics of previous cases are significant predictors of current diagnostic decisions. Additionally, predictive modeling of diagnostic decisions showed an overall improvement in prediction error when the model is trained on additional information about

  6. Utilizing a sequential injection system furnished with an extraction microcolumn as a novel approach for executing sequential extractions of metal species in solid samples

    DEFF Research Database (Denmark)

    Chomchoei, R.; Hansen, Elo Harald; Shiowatana, J.

    2007-01-01

    This communication presents a novel approach to perform sequential extraction of elements in solid samples by using a sequential injection (SI) system incorporating a specially designed extraction microcolumn. Based on the operation of the syringe pump, different modes of extraction are potentially...... that the system entails many advantages such as being fully automated, and besides being characterised by rapidity, ease of operation and robustness, it is less prone to risks of contamination and personal errors as encountered in traditional batch systems. Moreover, improvement of the precision and accuracy...... of the chemical fractionation of metal in solids as compared with previous reports are obtained. The system ensures that extraction is performed at designated pH values. Variation of sample weight to column volume ratios do not affect the amounts of extractable metals, nor do extraction flow rates ranging from 50...

  7. Sequential Logic Model Deciphers Dynamic Transcriptional Control of Gene Expressions

    Science.gov (United States)

    Yeo, Zhen Xuan; Wong, Sum Thai; Arjunan, Satya Nanda Vel; Piras, Vincent; Tomita, Masaru; Selvarajoo, Kumar; Giuliani, Alessandro; Tsuchiya, Masa

    2007-01-01

    Background Cellular signaling involves a sequence of events from ligand binding to membrane receptors through transcription factors activation and the induction of mRNA expression. The transcriptional-regulatory system plays a pivotal role in the control of gene expression. A novel computational approach to the study of gene regulation circuits is presented here. Methodology Based on the concept of finite state machine, which provides a discrete view of gene regulation, a novel sequential logic model (SLM) is developed to decipher control mechanisms of dynamic transcriptional regulation of gene expressions. The SLM technique is also used to systematically analyze the dynamic function of transcriptional inputs, the dependency and cooperativity, such as synergy effect, among the binding sites with respect to when, how much and how fast the gene of interest is expressed. Principal Findings SLM is verified by a set of well studied expression data on endo16 of Strongylocentrotus purpuratus (sea urchin) during the embryonic midgut development. A dynamic regulatory mechanism for endo16 expression controlled by three binding sites, UI, R and Otx is identified and demonstrated to be consistent with experimental findings. Furthermore, we show that during transition from specification to differentiation in wild type endo16 expression profile, SLM reveals three binary activities are not sufficient to explain the transcriptional regulation of endo16 expression and additional activities of binding sites are required. Further analyses suggest detailed mechanism of R switch activity where indirect dependency occurs in between UI activity and R switch during specification to differentiation stage. Conclusions/Significance The sequential logic formalism allows for a simplification of regulation network dynamics going from a continuous to a discrete representation of gene activation in time. In effect our SLM is non-parametric and model-independent, yet providing rich biological

  8. Sequential logic model deciphers dynamic transcriptional control of gene expressions.

    Directory of Open Access Journals (Sweden)

    Zhen Xuan Yeo

    Full Text Available BACKGROUND: Cellular signaling involves a sequence of events from ligand binding to membrane receptors through transcription factors activation and the induction of mRNA expression. The transcriptional-regulatory system plays a pivotal role in the control of gene expression. A novel computational approach to the study of gene regulation circuits is presented here. METHODOLOGY: Based on the concept of finite state machine, which provides a discrete view of gene regulation, a novel sequential logic model (SLM is developed to decipher control mechanisms of dynamic transcriptional regulation of gene expressions. The SLM technique is also used to systematically analyze the dynamic function of transcriptional inputs, the dependency and cooperativity, such as synergy effect, among the binding sites with respect to when, how much and how fast the gene of interest is expressed. PRINCIPAL FINDINGS: SLM is verified by a set of well studied expression data on endo16 of Strongylocentrotus purpuratus (sea urchin during the embryonic midgut development. A dynamic regulatory mechanism for endo16 expression controlled by three binding sites, UI, R and Otx is identified and demonstrated to be consistent with experimental findings. Furthermore, we show that during transition from specification to differentiation in wild type endo16 expression profile, SLM reveals three binary activities are not sufficient to explain the transcriptional regulation of endo16 expression and additional activities of binding sites are required. Further analyses suggest detailed mechanism of R switch activity where indirect dependency occurs in between UI activity and R switch during specification to differentiation stage. CONCLUSIONS/SIGNIFICANCE: The sequential logic formalism allows for a simplification of regulation network dynamics going from a continuous to a discrete representation of gene activation in time. In effect our SLM is non-parametric and model-independent, yet

  9. Popularity Modeling for Mobile Apps: A Sequential Approach.

    Science.gov (United States)

    Zhu, Hengshu; Liu, Chuanren; Ge, Yong; Xiong, Hui; Chen, Enhong

    2015-07-01

    The popularity information in App stores, such as chart rankings, user ratings, and user reviews, provides an unprecedented opportunity to understand user experiences with mobile Apps, learn the process of adoption of mobile Apps, and thus enables better mobile App services. While the importance of popularity information is well recognized in the literature, the use of the popularity information for mobile App services is still fragmented and under-explored. To this end, in this paper, we propose a sequential approach based on hidden Markov model (HMM) for modeling the popularity information of mobile Apps toward mobile App services. Specifically, we first propose a popularity based HMM (PHMM) to model the sequences of the heterogeneous popularity observations of mobile Apps. Then, we introduce a bipartite based method to precluster the popularity observations. This can help to learn the parameters and initial values of the PHMM efficiently. Furthermore, we demonstrate that the PHMM is a general model and can be applicable for various mobile App services, such as trend based App recommendation, rating and review spam detection, and ranking fraud detection. Finally, we validate our approach on two real-world data sets collected from the Apple Appstore. Experimental results clearly validate both the effectiveness and efficiency of the proposed popularity modeling approach.

  10. Testing sequential extraction methods for the analysis of multiple stable isotope systems from a bone sample

    Science.gov (United States)

    Sahlstedt, Elina; Arppe, Laura

    2017-04-01

    Stable isotope composition of bones, analysed either from the mineral phase (hydroxyapatite) or from the organic phase (mainly collagen) carry important climatological and ecological information and are therefore widely used in paleontological and archaeological research. For the analysis of the stable isotope compositions, both of the phases, hydroxyapatite and collagen, have their more or less well established separation and analytical techniques. Recent development in IRMS and wet chemical extraction methods have facilitated the analysis of very small bone fractions (500 μg or less starting material) for PO43-O isotope composition. However, the uniqueness and (pre-) historical value of each archaeological and paleontological finding lead to preciously little material available for stable isotope analyses, encouraging further development of microanalytical methods for the use of stable isotope analyses. Here we present the first results in developing extraction methods for combining collagen C- and N-isotope analyses to PO43-O-isotope analyses from a single bone sample fraction. We tested sequential extraction starting with dilute acid demineralization and collection of both collagen and PO43-fractions, followed by further purification step by H2O2 (PO43-fraction). First results show that bone sample separates as small as 2 mg may be analysed for their δ15N, δ13C and δ18OPO4 values. The method may be incorporated in detailed investigation of sequentially developing skeletal material such as teeth, potentially allowing for the investigation of interannual variability in climatological/environmental signals or investigation of the early life history of an individual.

  11. The importance of examining movements within the US health care system: sequential logit modeling

    Directory of Open Access Journals (Sweden)

    Lee Chioun

    2010-09-01

    Full Text Available Abstract Background Utilization of specialty care may not be a discrete, isolated behavior but rather, a behavior of sequential movements within the health care system. Although patients may often visit their primary care physician and receive a referral before utilizing specialty care, prior studies have underestimated the importance of accounting for these sequential movements. Methods The sample included 6,772 adults aged 18 years and older who participated in the 2001 Survey on Disparities in Quality of Care, sponsored by the Commonwealth Fund. A sequential logit model was used to account for movement in all stages of utilization: use of any health services (i.e., first stage, having a perceived need for specialty care (i.e., second stage, and utilization of specialty care (i.e., third stage. In the sequential logit model, all stages are nested within the previous stage. Results Gender, race/ethnicity, education and poor health had significant explanatory effects with regard to use of any health services and having a perceived need for specialty care, however racial/ethnic, gender, and educational disparities were not present in utilization of specialty care. After controlling for use of any health services and having a perceived need for specialty care, inability to pay for specialty care via income (AOR = 1.334, CI = 1.10 to 1.62 or health insurance (unstable insurance: AOR = 0.26, CI = 0.14 to 0.48; no insurance: AOR = 0.12, CI = 0.07 to 0.20 were significant barriers to utilization of specialty care. Conclusions Use of a sequential logit model to examine utilization of specialty care resulted in a detailed representation of utilization behaviors and patient characteristics that impact these behaviors at all stages within the health care system. After controlling for sequential movements within the health care system, the biggest barrier to utilizing specialty care is the inability to pay, while racial, gender, and educational disparities

  12. Improving multiple-point-based a priori models for inverse problems by combining Sequential Simulation with the Frequency Matching Method

    DEFF Research Database (Denmark)

    Cordua, Knud Skou; Hansen, Thomas Mejer; Lange, Katrine

    In order to move beyond simplified covariance based a priori models, which are typically used for inverse problems, more complex multiple-point-based a priori models have to be considered. By means of marginal probability distributions ‘learned’ from a training image, sequential simulation has...... proven to be an efficient way of obtaining multiple realizations that honor the same multiple-point statistics as the training image. The frequency matching method provides an alternative way of formulating multiple-point-based a priori models. In this strategy the pattern frequency distributions (i.......e. marginals) of the training image and a subsurface model are matched in order to obtain a solution with the same multiple-point statistics as the training image. Sequential Gibbs sampling is a simulation strategy that provides an efficient way of applying sequential simulation based algorithms as a priori...

  13. Comparing cluster-level dynamic treatment regimens using sequential, multiple assignment, randomized trials: Regression estimation and sample size considerations.

    Science.gov (United States)

    NeCamp, Timothy; Kilbourne, Amy; Almirall, Daniel

    2017-08-01

    Cluster-level dynamic treatment regimens can be used to guide sequential treatment decision-making at the cluster level in order to improve outcomes at the individual or patient-level. In a cluster-level dynamic treatment regimen, the treatment is potentially adapted and re-adapted over time based on changes in the cluster that could be impacted by prior intervention, including aggregate measures of the individuals or patients that compose it. Cluster-randomized sequential multiple assignment randomized trials can be used to answer multiple open questions preventing scientists from developing high-quality cluster-level dynamic treatment regimens. In a cluster-randomized sequential multiple assignment randomized trial, sequential randomizations occur at the cluster level and outcomes are observed at the individual level. This manuscript makes two contributions to the design and analysis of cluster-randomized sequential multiple assignment randomized trials. First, a weighted least squares regression approach is proposed for comparing the mean of a patient-level outcome between the cluster-level dynamic treatment regimens embedded in a sequential multiple assignment randomized trial. The regression approach facilitates the use of baseline covariates which is often critical in the analysis of cluster-level trials. Second, sample size calculators are derived for two common cluster-randomized sequential multiple assignment randomized trial designs for use when the primary aim is a between-dynamic treatment regimen comparison of the mean of a continuous patient-level outcome. The methods are motivated by the Adaptive Implementation of Effective Programs Trial which is, to our knowledge, the first-ever cluster-randomized sequential multiple assignment randomized trial in psychiatry.

  14. Solid phase speciation of arsenic by sequential extraction in standard reference materials and industrially contaminated soil samples

    International Nuclear Information System (INIS)

    Herreweghe, Samuel van; Swennen, Rudy; Vandecasteele, Carlo; Cappuyns, Valerie

    2003-01-01

    Leaching experiments, a mineralogical survey and larger samples are preferred when arsenic is present as discrete mineral phases. - Availability, mobility, (phyto)toxicity and potential risk of contaminants is strongly affected by the manner of appearance of elements, the so-called speciation. Operational fractionation methods like sequential extractions have been applied for a long time to determine the solid phase speciation of heavy metals since direct determination of specific chemical compounds can not always be easily achieved. The three-step sequential extraction scheme recommended by the BCR and two extraction schemes based on the phosphorus-like protocol proposed by Manful (1992, Occurrence and Ecochemical Behaviours of Arsenic in a Goldsmelter Impacted Area in Ghana, PhD dissertation, at the RUG) were applied to four standard reference materials (SRM) and to a batch of samples from industrially contaminated sites, heavily contaminated with arsenic and heavy metals. The SRM 2710 (Montana soil) was found to be the most useful reference material for metal (Mn, Cu, Zn, As, Cd and Pb) fractionation using the BCR sequential extraction procedure. Two sequential extraction schemes were developed and compared for arsenic with the aim to establish a better fractionation and recovery rate than the BCR-scheme for this element in the SRM samples. The major part of arsenic was released from the heavily contaminated samples after NaOH-extraction. Inferior extraction variability and recovery in the heavily contaminated samples compared to SRMs could be mainly contributed to subsample heterogeneity

  15. The attention-weighted sample-size model of visual short-term memory

    DEFF Research Database (Denmark)

    Smith, Philip L.; Lilburn, Simon D.; Corbett, Elaine A.

    2016-01-01

    exceeded that predicted by the sample-size model for both simultaneously and sequentially presented stimuli. Instead, the set-size effect and the serial position curves with sequential presentation were predicted by an attention-weighted version of the sample-size model, which assumes that one of the items...

  16. Trends and perspectives of flow injection/sequential injection on-line sample-pretreatment schemes coupled to ETAAS

    DEFF Research Database (Denmark)

    Wang, Jianhua; Hansen, Elo Harald

    2005-01-01

    Flow injection (FI) analysis, the first generation of this technique, became in the 1990s supplemented by its second generation, sequential injection (SI), and most recently by the third generation (i.e.,Lab-on-Valve). The dominant role played by FI in automatic, on-line, sample pretreatments in ...

  17. Sequential capillary electrophoresis analysis using optically gated sample injection and UV/vis detection.

    Science.gov (United States)

    Liu, Xiaoxia; Tian, Miaomiao; Camara, Mohamed Amara; Guo, Liping; Yang, Li

    2015-10-01

    We present sequential CE analysis of amino acids and L-asparaginase-catalyzed enzyme reaction, by combing the on-line derivatization, optically gated (OG) injection and commercial-available UV-Vis detection. Various experimental conditions for sequential OG-UV/vis CE analysis were investigated and optimized by analyzing a standard mixture of amino acids. High reproducibility of the sequential CE analysis was demonstrated with RSD values (n = 20) of 2.23, 2.57, and 0.70% for peak heights, peak areas, and migration times, respectively, and the LOD of 5.0 μM (for asparagine) and 2.0 μM (for aspartic acid) were obtained. With the application of the OG-UV/vis CE analysis, sequential online CE enzyme assay of L-asparaginase-catalyzed enzyme reaction was carried out by automatically and continuously monitoring the substrate consumption and the product formation every 12 s from the beginning to the end of the reaction. The Michaelis constants for the reaction were obtained and were found to be in good agreement with the results of traditional off-line enzyme assays. The study demonstrated the feasibility and reliability of integrating the OG injection with UV/vis detection for sequential online CE analysis, which could be of potential value for online monitoring various chemical reaction and bioprocesses. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. A SEQUENTIAL MODEL OF INNOVATION STRATEGY—COMPANY NON-FINANCIAL PERFORMANCE LINKS

    Directory of Open Access Journals (Sweden)

    Wakhid Slamet Ciptono

    2006-05-01

    Full Text Available This study extends the prior research (Zahra and Das 1993 by examining the association between a company’s innovation strategy and its non-financial performance in the upstream and downstream strategic business units (SBUs of oil and gas companies. The sequential model suggests a causal sequence among six dimensions of innovation strategy (leadership orientation, process innovation, product/service innovation, external innovation source, internal innovation source, and investment that may lead to higher company non-financial performance (productivity and operational reliability. The study distributed a questionnaire (by mail, e-mailed web system, and focus group discussion to three levels of managers (top, middle, and first-line of 49 oil and gas companies with 140 SBUs in Indonesia. These qualified samples fell into 47 upstream (supply-chain companies with 132 SBUs, and 2 downstream (demand-chain companies with 8 SBUs. A total of 1,332 individual usable questionnaires were returned thus qualified for analysis, representing an effective response rate of 50.19 percent. The researcher conducts structural equation modeling (SEM and hierarchical multiple regression analysis to assess the goodness-of-fit between the research models and the sample data and to test whether innovation strategy mediates the impact of leadership orientation on company non-financial performance. SEM reveals that the models have met goodness-of-fit criteria, thus the interpretation of the sequential models fits with the data. The results of SEM and hierarchical multiple regression: (1 support the importance of innovation strategy as a determinant of company non-financial performance, (2 suggest that the sequential model is appropriate for examining the relationships between six dimensions of innovation strategy and company non-financial performance, and (3 show that the sequential model provides additional insights into the indirect contribution of the individual

  19. Efficient Sequential Monte Carlo Sampling for Continuous Monitoring of a Radiation Situation

    Czech Academy of Sciences Publication Activity Database

    Šmídl, Václav; Hofman, Radek

    2014-01-01

    Roč. 56, č. 4 (2014), s. 514-527 ISSN 0040-1706 R&D Projects: GA MV VG20102013018 Institutional support: RVO:67985556 Keywords : radiation protection * atmospheric dispersion model * importance sampling Subject RIV: BD - Theory of Information Impact factor: 1.814, year: 2014 http://library.utia.cas.cz/separaty/2014/AS/smidl-0433631.pdf

  20. Work–Family Conflict and Mental Health Among Female Employees: A Sequential Mediation Model via Negative Affect and Perceived Stress

    Science.gov (United States)

    Zhou, Shiyi; Da, Shu; Guo, Heng; Zhang, Xichao

    2018-01-01

    After the implementation of the universal two-child policy in 2016, more and more working women have found themselves caught in the dilemma of whether to raise a baby or be promoted, which exacerbates work–family conflicts among Chinese women. Few studies have examined the mediating effect of negative affect. The present study combined the conservation of resources model and affective events theory to examine the sequential mediating effect of negative affect and perceived stress in the relationship between work–family conflict and mental health. A valid sample of 351 full-time Chinese female employees was recruited in this study, and participants voluntarily answered online questionnaires. Pearson correlation analysis, structural equation modeling, and multiple mediation analysis were used to examine the relationships between work–family conflict, negative affect, perceived stress, and mental health in full-time female employees. We found that women’s perceptions of both work-to-family conflict and family-to-work conflict were significant negatively related to mental health. Additionally, the results showed that negative affect and perceived stress were negatively correlated with mental health. The 95% confidence intervals indicated the sequential mediating effect of negative affect and stress in the relationship between work–family conflict and mental health was significant, which supported the hypothesized sequential mediation model. The findings suggest that work–family conflicts affected the level of self-reported mental health, and this relationship functioned through the two sequential mediators of negative affect and perceived stress. PMID:29719522

  1. Work-Family Conflict and Mental Health Among Female Employees: A Sequential Mediation Model via Negative Affect and Perceived Stress.

    Science.gov (United States)

    Zhou, Shiyi; Da, Shu; Guo, Heng; Zhang, Xichao

    2018-01-01

    After the implementation of the universal two-child policy in 2016, more and more working women have found themselves caught in the dilemma of whether to raise a baby or be promoted, which exacerbates work-family conflicts among Chinese women. Few studies have examined the mediating effect of negative affect. The present study combined the conservation of resources model and affective events theory to examine the sequential mediating effect of negative affect and perceived stress in the relationship between work-family conflict and mental health. A valid sample of 351 full-time Chinese female employees was recruited in this study, and participants voluntarily answered online questionnaires. Pearson correlation analysis, structural equation modeling, and multiple mediation analysis were used to examine the relationships between work-family conflict, negative affect, perceived stress, and mental health in full-time female employees. We found that women's perceptions of both work-to-family conflict and family-to-work conflict were significant negatively related to mental health. Additionally, the results showed that negative affect and perceived stress were negatively correlated with mental health. The 95% confidence intervals indicated the sequential mediating effect of negative affect and stress in the relationship between work-family conflict and mental health was significant, which supported the hypothesized sequential mediation model. The findings suggest that work-family conflicts affected the level of self-reported mental health, and this relationship functioned through the two sequential mediators of negative affect and perceived stress.

  2. Work–Family Conflict and Mental Health Among Female Employees: A Sequential Mediation Model via Negative Affect and Perceived Stress

    Directory of Open Access Journals (Sweden)

    Shiyi Zhou

    2018-04-01

    Full Text Available After the implementation of the universal two-child policy in 2016, more and more working women have found themselves caught in the dilemma of whether to raise a baby or be promoted, which exacerbates work–family conflicts among Chinese women. Few studies have examined the mediating effect of negative affect. The present study combined the conservation of resources model and affective events theory to examine the sequential mediating effect of negative affect and perceived stress in the relationship between work–family conflict and mental health. A valid sample of 351 full-time Chinese female employees was recruited in this study, and participants voluntarily answered online questionnaires. Pearson correlation analysis, structural equation modeling, and multiple mediation analysis were used to examine the relationships between work–family conflict, negative affect, perceived stress, and mental health in full-time female employees. We found that women’s perceptions of both work-to-family conflict and family-to-work conflict were significant negatively related to mental health. Additionally, the results showed that negative affect and perceived stress were negatively correlated with mental health. The 95% confidence intervals indicated the sequential mediating effect of negative affect and stress in the relationship between work–family conflict and mental health was significant, which supported the hypothesized sequential mediation model. The findings suggest that work–family conflicts affected the level of self-reported mental health, and this relationship functioned through the two sequential mediators of negative affect and perceived stress.

  3. Sequential Path Model for Grain Yield in Soybean

    Directory of Open Access Journals (Sweden)

    Mohammad SEDGHI

    2010-09-01

    Full Text Available This study was performed to determine some physiological traits that affect soybean,s grain yield via sequential path analysis. In a factorial experiment, two cultivars (Harcor and Williams were sown under four levels of nitrogen and two levels of weed management at the research station of Tabriz University, Iran, during 2004 and 2005. Grain yield, some yield components and physiological traits were measured. Correlation coefficient analysis showed that grain yield had significant positive and negative association with measured traits. A sequential path analysis was done in order to evaluate associations among grain yield and related traits by ordering the various variables in first, second and third order paths on the basis of their maximum direct effects and minimal collinearity. Two first-order variables, namely number of pods per plant and pre-flowering net photosynthesis revealed highest direct effect on total grain yield and explained 49, 44 and 47 % of the variation in grain yield based on 2004, 2005, and combined datasets, respectively. Four traits i.e. post-flowering net photosynthesis, plant height, leaf area index and intercepted radiation at the bottom layer of canopy were found to fit as second-order variables. Pre- and post-flowering chlorophyll content, main root length and intercepted radiation at the middle layer of canopy were placed at the third-order path. From the results concluded that, number of pods per plant and pre-flowering net photosynthesis are the best selection criteria in soybean for grain yield.

  4. Microwave Ablation: Comparison of Simultaneous and Sequential Activation of Multiple Antennas in Liver Model Systems.

    Science.gov (United States)

    Harari, Colin M; Magagna, Michelle; Bedoya, Mariajose; Lee, Fred T; Lubner, Meghan G; Hinshaw, J Louis; Ziemlewicz, Timothy; Brace, Christopher L

    2016-01-01

    To compare microwave ablation zones created by using sequential or simultaneous power delivery in ex vivo and in vivo liver tissue. All procedures were approved by the institutional animal care and use committee. Microwave ablations were performed in both ex vivo and in vivo liver models with a 2.45-GHz system capable of powering up to three antennas simultaneously. Two- and three-antenna arrays were evaluated in each model. Sequential and simultaneous ablations were created by delivering power (50 W ex vivo, 65 W in vivo) for 5 minutes per antenna (10 and 15 minutes total ablation time for sequential ablations, 5 minutes for simultaneous ablations). Thirty-two ablations were performed in ex vivo bovine livers (eight per group) and 28 in the livers of eight swine in vivo (seven per group). Ablation zone size and circularity metrics were determined from ablations excised postmortem. Mixed effects modeling was used to evaluate the influence of power delivery, number of antennas, and tissue type. On average, ablations created by using the simultaneous power delivery technique were larger than those with the sequential technique (P Simultaneous ablations were also more circular than sequential ablations (P = .0001). Larger and more circular ablations were achieved with three antennas compared with two antennas (P simultaneous power delivery creates larger, more confluent ablations with greater temperatures than those created with sequential power delivery. © RSNA, 2015.

  5. Modeling two-phase ferroelectric composites by sequential laminates

    International Nuclear Information System (INIS)

    Idiart, Martín I

    2014-01-01

    Theoretical estimates are given for the overall dissipative response of two-phase ferroelectric composites with complex particulate microstructures under arbitrary loading histories. The ferroelectric behavior of the constituent phases is described via a stored energy density and a dissipation potential in accordance with the theory of generalized standard materials. An implicit time-discretization scheme is used to generate a variational representation of the overall response in terms of a single incremental potential. Estimates are then generated by constructing sequentially laminated microgeometries of particulate type whose overall incremental potential can be computed exactly. Because they are realizable, by construction, these estimates are guaranteed to conform with any material constraints, to satisfy all pertinent bounds and to exhibit the required convexity properties with no duality gap. Predictions for representative composite and porous systems are reported and discussed in the light of existing experimental data. (paper)

  6. Particle rejuvenation of Rao-Blackwellized sequential Monte Carlo smoothers for conditionally linear and Gaussian models

    Science.gov (United States)

    Nguyen, Ngoc Minh; Corff, Sylvain Le; Moulines, Éric

    2017-12-01

    This paper focuses on sequential Monte Carlo approximations of smoothing distributions in conditionally linear and Gaussian state spaces. To reduce Monte Carlo variance of smoothers, it is typical in these models to use Rao-Blackwellization: particle approximation is used to sample sequences of hidden regimes while the Gaussian states are explicitly integrated conditional on the sequence of regimes and observations, using variants of the Kalman filter/smoother. The first successful attempt to use Rao-Blackwellization for smoothing extends the Bryson-Frazier smoother for Gaussian linear state space models using the generalized two-filter formula together with Kalman filters/smoothers. More recently, a forward-backward decomposition of smoothing distributions mimicking the Rauch-Tung-Striebel smoother for the regimes combined with backward Kalman updates has been introduced. This paper investigates the benefit of introducing additional rejuvenation steps in all these algorithms to sample at each time instant new regimes conditional on the forward and backward particles. This defines particle-based approximations of the smoothing distributions whose support is not restricted to the set of particles sampled in the forward or backward filter. These procedures are applied to commodity markets which are described using a two-factor model based on the spot price and a convenience yield for crude oil data.

  7. Time optimization of 90Sr measurements: Sequential measurement of multiple samples during ingrowth of 90Y

    International Nuclear Information System (INIS)

    Holmgren, Stina; Tovedal, Annika; Björnham, Oscar; Ramebäck, Henrik

    2016-01-01

    The aim of this paper is to contribute to a more rapid determination of a series of samples containing 90 Sr by making the Cherenkov measurement of the daughter nuclide 90 Y more time efficient. There are many instances when an optimization of the measurement method might be favorable, such as; situations requiring rapid results in order to make urgent decisions or, on the other hand, to maximize the throughput of samples in a limited available time span. In order to minimize the total analysis time, a mathematical model was developed which calculates the time of ingrowth as well as individual measurement times for n samples in a series. This work is focused on the measurement of 90 Y during ingrowth, after an initial chemical separation of strontium, in which it is assumed that no other radioactive strontium isotopes are present. By using a fixed minimum detectable activity (MDA) and iterating the measurement time for each consecutive sample the total analysis time will be less, compared to using the same measurement time for all samples. It was found that by optimization, the total analysis time for 10 samples can be decreased greatly, from 21 h to 6.5 h, when assuming a MDA of 1 Bq/L and at a background count rate of approximately 0.8 cpm. - Highlights: • An approach roughly a factor of three more efficient than an un-optimized method. • The optimization gives a more efficient use of instrument time. • The efficiency increase ranges from a factor of three to 10, for 10 to 40 samples.

  8. Sequential injection titration method using second-order signals: determination of acidity in plant oils and biodiesel samples.

    Science.gov (United States)

    del Río, Vanessa; Larrechi, M Soledad; Callao, M Pilar

    2010-06-15

    A new concept of flow titration is proposed and demonstrated for the determination of total acidity in plant oils and biodiesel. We use sequential injection analysis (SIA) with a diode array spectrophotometric detector linked to chemometric tools such as multivariate curve resolution-alternating least squares (MCR-ALS). This system is based on the evolution of the basic specie of an acid-base indicator, alizarine, when it comes into contact with a sample that contains free fatty acids. The gradual pH change in the reactor coil due to diffusion and reaction phenomenona allows the sequential appearance of both species of the indicator in the detector coil, recording a data matrix for each sample. The SIA-MCR-ALS method helps to reduce the amounts of sample, the reagents and the time consumed. Each determination consumes 0.413ml of sample, 0.250ml of indicator and 3ml of carrier (ethanol) and generates 3.333ml of waste. The frequency of the analysis is high (12 samples h(-1) including all steps, i.e., cleaning, preparing and analysing). The utilized reagents are of common use in the laboratory and it is not necessary to use the reagents of perfect known concentration. The method was applied to determine acidity in plant oil and biodiesel samples. Results obtained by the proposed method compare well with those obtained by the official European Community method that is time consuming and uses large amounts of organic solvents.

  9. Bootstrap Sequential Determination of the Co-integration Rank in VAR Models

    DEFF Research Database (Denmark)

    Guiseppe, Cavaliere; Rahbæk, Anders; Taylor, A.M. Robert

    with empirical rejection frequencies often very much in excess of the nominal level. As a consequence, bootstrap versions of these tests have been developed. To be useful, however, sequential procedures for determining the co-integrating rank based on these bootstrap tests need to be consistent, in the sense...... in the literature by proposing a bootstrap sequential algorithm which we demonstrate delivers consistent cointegration rank estimation for general I(1) processes. Finite sample Monte Carlo simulations show the proposed procedure performs well in practice....

  10. Limit Theory for Panel Data Models with Cross Sectional Dependence and Sequential Exogeneity.

    Science.gov (United States)

    Kuersteiner, Guido M; Prucha, Ingmar R

    2013-06-01

    The paper derives a general Central Limit Theorem (CLT) and asymptotic distributions for sample moments related to panel data models with large n . The results allow for the data to be cross sectionally dependent, while at the same time allowing the regressors to be only sequentially rather than strictly exogenous. The setup is sufficiently general to accommodate situations where cross sectional dependence stems from spatial interactions and/or from the presence of common factors. The latter leads to the need for random norming. The limit theorem for sample moments is derived by showing that the moment conditions can be recast such that a martingale difference array central limit theorem can be applied. We prove such a central limit theorem by first extending results for stable convergence in Hall and Hedye (1980) to non-nested martingale arrays relevant for our applications. We illustrate our result by establishing a generalized estimation theory for GMM estimators of a fixed effect panel model without imposing i.i.d. or strict exogeneity conditions. We also discuss a class of Maximum Likelihood (ML) estimators that can be analyzed using our CLT.

  11. Assessment of outdoor radiofrequency electromagnetic field exposure through hotspot localization using kriging-based sequential sampling.

    Science.gov (United States)

    Aerts, Sam; Deschrijver, Dirk; Verloock, Leen; Dhaene, Tom; Martens, Luc; Joseph, Wout

    2013-10-01

    In this study, a novel methodology is proposed to create heat maps that accurately pinpoint the outdoor locations with elevated exposure to radiofrequency electromagnetic fields (RF-EMF) in an extensive urban region (or, hotspots), and that would allow local authorities and epidemiologists to efficiently assess the locations and spectral composition of these hotspots, while at the same time developing a global picture of the exposure in the area. Moreover, no prior knowledge about the presence of radiofrequency radiation sources (e.g., base station parameters) is required. After building a surrogate model from the available data using kriging, the proposed method makes use of an iterative sampling strategy that selects new measurement locations at spots which are deemed to contain the most valuable information-inside hotspots or in search of them-based on the prediction uncertainty of the model. The method was tested and validated in an urban subarea of Ghent, Belgium with a size of approximately 1 km2. In total, 600 input and 50 validation measurements were performed using a broadband probe. Five hotspots were discovered and assessed, with maximum total electric-field strengths ranging from 1.3 to 3.1 V/m, satisfying the reference levels issued by the International Commission on Non-Ionizing Radiation Protection for exposure of the general public to RF-EMF. Spectrum analyzer measurements in these hotspots revealed five radiofrequency signals with a relevant contribution to the exposure. The radiofrequency radiation emitted by 900 MHz Global System for Mobile Communications (GSM) base stations was always dominant, with contributions ranging from 45% to 100%. Finally, validation of the subsequent surrogate models shows high prediction accuracy, with the final model featuring an average relative error of less than 2dB (factor 1.26 in electric-field strength), a correlation coefficient of 0.7, and a specificity of 0.96. Copyright © 2013 Elsevier Inc. All rights

  12. Sequential decoding of intramuscular EMG signals via estimation of a Markov model.

    Science.gov (United States)

    Monsifrot, Jonathan; Le Carpentier, Eric; Aoustin, Yannick; Farina, Dario

    2014-09-01

    This paper addresses the sequential decoding of intramuscular single-channel electromyographic (EMG) signals to extract the activity of individual motor neurons. A hidden Markov model is derived from the physiological generation of the EMG signal. The EMG signal is described as a sum of several action potentials (wavelet) trains, embedded in noise. For each train, the time interval between wavelets is modeled by a process that parameters are linked to the muscular activity. The parameters of this process are estimated sequentially by a Bayes filter, along with the firing instants. The method was tested on some simulated signals and an experimental one, from which the rates of detection and classification of action potentials were above 95% with respect to the reference decomposition. The method works sequentially in time, and is the first to address the problem of intramuscular EMG decomposition online. It has potential applications for man-machine interfacing based on motor neuron activities.

  13. Assessment of outdoor radiofrequency electromagnetic field exposure through hotspot localization using kriging-based sequential sampling

    Energy Technology Data Exchange (ETDEWEB)

    Aerts, Sam, E-mail: sam.aerts@intec.ugent.be; Deschrijver, Dirk; Verloock, Leen; Dhaene, Tom; Martens, Luc; Joseph, Wout

    2013-10-15

    In this study, a novel methodology is proposed to create heat maps that accurately pinpoint the outdoor locations with elevated exposure to radiofrequency electromagnetic fields (RF-EMF) in an extensive urban region (or, hotspots), and that would allow local authorities and epidemiologists to efficiently assess the locations and spectral composition of these hotspots, while at the same time developing a global picture of the exposure in the area. Moreover, no prior knowledge about the presence of radiofrequency radiation sources (e.g., base station parameters) is required. After building a surrogate model from the available data using kriging, the proposed method makes use of an iterative sampling strategy that selects new measurement locations at spots which are deemed to contain the most valuable information—inside hotspots or in search of them—based on the prediction uncertainty of the model. The method was tested and validated in an urban subarea of Ghent, Belgium with a size of approximately 1 km{sup 2}. In total, 600 input and 50 validation measurements were performed using a broadband probe. Five hotspots were discovered and assessed, with maximum total electric-field strengths ranging from 1.3 to 3.1 V/m, satisfying the reference levels issued by the International Commission on Non-Ionizing Radiation Protection for exposure of the general public to RF-EMF. Spectrum analyzer measurements in these hotspots revealed five radiofrequency signals with a relevant contribution to the exposure. The radiofrequency radiation emitted by 900 MHz Global System for Mobile Communications (GSM) base stations was always dominant, with contributions ranging from 45% to 100%. Finally, validation of the subsequent surrogate models shows high prediction accuracy, with the final model featuring an average relative error of less than 2 dB (factor 1.26 in electric-field strength), a correlation coefficient of 0.7, and a specificity of 0.96. -- Highlights: • We present an

  14. Assessment of outdoor radiofrequency electromagnetic field exposure through hotspot localization using kriging-based sequential sampling

    International Nuclear Information System (INIS)

    Aerts, Sam; Deschrijver, Dirk; Verloock, Leen; Dhaene, Tom; Martens, Luc; Joseph, Wout

    2013-01-01

    In this study, a novel methodology is proposed to create heat maps that accurately pinpoint the outdoor locations with elevated exposure to radiofrequency electromagnetic fields (RF-EMF) in an extensive urban region (or, hotspots), and that would allow local authorities and epidemiologists to efficiently assess the locations and spectral composition of these hotspots, while at the same time developing a global picture of the exposure in the area. Moreover, no prior knowledge about the presence of radiofrequency radiation sources (e.g., base station parameters) is required. After building a surrogate model from the available data using kriging, the proposed method makes use of an iterative sampling strategy that selects new measurement locations at spots which are deemed to contain the most valuable information—inside hotspots or in search of them—based on the prediction uncertainty of the model. The method was tested and validated in an urban subarea of Ghent, Belgium with a size of approximately 1 km 2 . In total, 600 input and 50 validation measurements were performed using a broadband probe. Five hotspots were discovered and assessed, with maximum total electric-field strengths ranging from 1.3 to 3.1 V/m, satisfying the reference levels issued by the International Commission on Non-Ionizing Radiation Protection for exposure of the general public to RF-EMF. Spectrum analyzer measurements in these hotspots revealed five radiofrequency signals with a relevant contribution to the exposure. The radiofrequency radiation emitted by 900 MHz Global System for Mobile Communications (GSM) base stations was always dominant, with contributions ranging from 45% to 100%. Finally, validation of the subsequent surrogate models shows high prediction accuracy, with the final model featuring an average relative error of less than 2 dB (factor 1.26 in electric-field strength), a correlation coefficient of 0.7, and a specificity of 0.96. -- Highlights: • We present an

  15. Formal Modeling and Verification of Interlocking Systems Featuring Sequential Release

    DEFF Research Database (Denmark)

    Vu, Linh Hong; Haxthausen, Anne Elisabeth; Peleska, Jan

    2015-01-01

    In this paper, we present a method and an associated tool suite for formal verification of the new ETCS level 2 based Danish railway interlocking systems. We have made a generic and reconfigurable model of the system behavior and generic high-level safety properties. This model accommodates seque...... SMT based bounded model checking (BMC) and inductive reasoning, we are able to verify the properties for model instances corresponding to railway networks of industrial size. Experiments also show that BMC is efficient for finding bugs in the railway interlocking designs....

  16. Formal Modeling and Verification of Interlocking Systems Featuring Sequential Release

    DEFF Research Database (Denmark)

    Vu, Linh Hong; Haxthausen, Anne Elisabeth; Peleska, Jan

    2014-01-01

    In this paper, we present a method and an associated tool suite for formal verification of the new ETCS level 2 based Danish railway interlocking systems. We have made a generic and reconfigurable model of the system behavior and generic high-level safety properties. This model accommodates seque...... SMT based bounded model checking (BMC) and inductive reasoning, we are able to verify the properties for model instances corresponding to railway networks of industrial size. Experiments also show that BMC is efficient for finding bugs in the railway interlocking designs....

  17. Sequential extraction procedure for determination of uranium, thorium, radium, lead and polonium radionuclides by alpha spectrometry in environmental samples

    Science.gov (United States)

    Oliveira, J. M.; Carvalho, F. P.

    2006-01-01

    A sequential extraction technique was developed and tested for common naturally-occurring radionuclides. This technique allows the extraction and purification of uranium, thorium, radium, lead, and polonium radionuclides from the same sample. Environmental materials such as water, soil, and biological samples can be analyzed for those radionuclides without matrix interferences in the quality of radioelement purification and in the radiochemical yield. The use of isotopic tracers (232U, 229Th, 224Ra, 209Po, and stable lead carrier) added to the sample in the beginning of the chemical procedure, enables an accurate control of the radiochemical yield for each radioelement. The ion extraction procedure, applied after either complete dissolution of the solid sample with mineral acids or co-precipitation of dissolved radionuclide with MnO2 for aqueous samples, includes the use of commercially available pre-packed columns from Eichrom® and ion exchange columns packed with Bio-Rad resins, in altogether three chromatography columns. All radioactive elements but one are purified and electroplated on stainless steel discs. Polonium is spontaneously plated on a silver disc. The discs are measured using high resolution silicon surface barrier detectors. 210Pb, a beta emitter, can be measured either through the beta emission of 210Bi, or stored for a few months and determined by alpha spectrometry through the in-growth of 210Po. This sequential extraction chromatography technique was tested and validated with the analysis of certified reference materials from the IAEA. Reproducibility was tested through repeated analysis of the same homogeneous material (water sample).

  18. A sequential model for the structure of health care utilization.

    NARCIS (Netherlands)

    Herrmann, W.J.; Haarmann, A.; Baerheim, A.

    2017-01-01

    Traditional measurement models of health care utilization are not able to represent the complex structure of health care utilization. In this qualitative study, we, therefore, developed a new model to represent the health care utilization structure. In Norway and Germany, we conducted episodic

  19. Formal modelling and verification of interlocking systems featuring sequential release

    DEFF Research Database (Denmark)

    Vu, Linh Hong; Haxthausen, Anne Elisabeth; Peleska, Jan

    2017-01-01

    checking (BMC) and inductive reasoning, it is verified that the generated model instance satisfies the generated safety properties. Using this method, we are able to verify the safety properties for model instances corresponding to railway networks of industrial size. Experiments show that BMC is also...

  20. A method for multiple sequential analyses of macrophage functions using a small single cell sample

    Directory of Open Access Journals (Sweden)

    F.R.F. Nascimento

    2003-09-01

    Full Text Available Microbial pathogens such as bacillus Calmette-Guérin (BCG induce the activation of macrophages. Activated macrophages can be characterized by the increased production of reactive oxygen and nitrogen metabolites, generated via NADPH oxidase and inducible nitric oxide synthase, respectively, and by the increased expression of major histocompatibility complex class II molecules (MHC II. Multiple microassays have been developed to measure these parameters. Usually each assay requires 2-5 x 10(5 cells per well. In some experimental conditions the number of cells is the limiting factor for the phenotypic characterization of macrophages. Here we describe a method whereby this limitation can be circumvented. Using a single 96-well microassay and a very small number of peritoneal cells obtained from C3H/HePas mice, containing as little as <=2 x 10(5 macrophages per well, we determined sequentially the oxidative burst (H2O2, nitric oxide production and MHC II (IAk expression of BCG-activated macrophages. More specifically, with 100 µl of cell suspension it was possible to quantify H2O2 release and nitric oxide production after 1 and 48 h, respectively, and IAk expression after 48 h of cell culture. In addition, this microassay is easy to perform, highly reproducible and more economical.

  1. Adaptive list sequential sampling method for population-based observational studies

    NARCIS (Netherlands)

    Hof, Michel H.; Ravelli, Anita C. J.; Zwinderman, Aeilko H.

    2014-01-01

    In population-based observational studies, non-participation and delayed response to the invitation to participate are complications that often arise during the recruitment of a sample. When both are not properly dealt with, the composition of the sample can be different from the desired

  2. Sequential automated fusion/extraction chromatography methodology for the dissolution of uranium in environmental samples for mass spectrometric determination

    Energy Technology Data Exchange (ETDEWEB)

    Milliard, Alex; Durand-Jezequel, Myriam [Laboratoire de Radioecologie, Departement de chimie, Universite Laval, 1045 Avenue de la Medecine, Quebec, QC, G1V 0A6 (Canada); Lariviere, Dominic, E-mail: dominic.lariviere@chm.ulaval.ca [Laboratoire de Radioecologie, Departement de chimie, Universite Laval, 1045 Avenue de la Medecine, Quebec, QC, G1V 0A6 (Canada)

    2011-01-17

    An improved methodology has been developed, based on dissolution by automated fusion followed by extraction chromatography for the detection and quantification of uranium in environmental matrices by mass spectrometry. A rapid fusion protocol (<8 min) was investigated for the complete dissolution of various samples. It could be preceded, if required, by an effective ashing procedure using the M4 fluxer and a newly designed platinum lid. Complete dissolution of the sample was observed and measured using standard reference materials (SRMs) and experimental data show no evidence of cross-contamination of crucibles when LiBO{sub 2}/LiBr melts were used. The use of a M4 fusion unit also improved repeatability in sample preparation over muffle furnace fusion. Instrumental issues originating from the presence of high salt concentrations in the digestate after lithium metaborate fusion was also mitigated using an extraction chromatography (EXC) protocol aimed at removing lithium and interfering matrix constituants prior to the elution of uranium. The sequential methodology, which can be performed simultaneously on three samples, requires less than 20 min per sample for fusion and separation. It was successfully coupled to inductively coupled plasma mass spectrometry (ICP-MS) achieving detection limits below 100 pg kg{sup -1} for 5-300 mg of sample.

  3. Sequential enzymatic derivatization coupled with online microdialysis sampling for simultaneous profiling of mouse tumor extracellular hydrogen peroxide, lactate, and glucose.

    Science.gov (United States)

    Su, Cheng-Kuan; Tseng, Po-Jen; Chiu, Hsien-Ting; Del Vall, Andrea; Huang, Yu-Fen; Sun, Yuh-Chang

    2017-03-01

    Probing tumor extracellular metabolites is a vitally important issue in current cancer biology. In this study an analytical system was constructed for the in vivo monitoring of mouse tumor extracellular hydrogen peroxide (H 2 O 2 ), lactate, and glucose by means of microdialysis (MD) sampling and fluorescence determination in conjunction with a smart sequential enzymatic derivatization scheme-involving a loading sequence of fluorogenic reagent/horseradish peroxidase, microdialysate, lactate oxidase, pyruvate, and glucose oxidase-for step-by-step determination of sampled H 2 O 2 , lactate, and glucose in mouse tumor microdialysate. After optimization of the overall experimental parameters, the system's detection limit reached as low as 0.002 mM for H 2 O 2 , 0.058 mM for lactate, and 0.055 mM for glucose, based on 3 μL of microdialysate, suggesting great potential for determining tumor extracellular concentrations of lactate and glucose. Spike analyses of offline-collected mouse tumor microdialysate and monitoring of the basal concentrations of mouse tumor extracellular H 2 O 2 , lactate, and glucose, as well as those after imparting metabolic disturbance through intra-tumor administration of a glucose solution through a prior-implanted cannula, were conducted to demonstrate the system's applicability. Our results evidently indicate that hyphenation of an MD sampling device with an optimized sequential enzymatic derivatization scheme and a fluorescence spectrometer can be used successfully for multi-analyte monitoring of tumor extracellular metabolites in living animals. Copyright © 2016 Elsevier B.V. All rights reserved.

  4. Modelling Odor Decoding in the Antennal Lobe by Combining Sequential Firing Rate Models with Bayesian Inference.

    Directory of Open Access Journals (Sweden)

    Dario Cuevas Rivera

    2015-10-01

    Full Text Available The olfactory information that is received by the insect brain is encoded in the form of spatiotemporal patterns in the projection neurons of the antennal lobe. These dense and overlapping patterns are transformed into a sparse code in Kenyon cells in the mushroom body. Although it is clear that this sparse code is the basis for rapid categorization of odors, it is yet unclear how the sparse code in Kenyon cells is computed and what information it represents. Here we show that this computation can be modeled by sequential firing rate patterns using Lotka-Volterra equations and Bayesian online inference. This new model can be understood as an 'intelligent coincidence detector', which robustly and dynamically encodes the presence of specific odor features. We found that the model is able to qualitatively reproduce experimentally observed activity in both the projection neurons and the Kenyon cells. In particular, the model explains mechanistically how sparse activity in the Kenyon cells arises from the dense code in the projection neurons. The odor classification performance of the model proved to be robust against noise and time jitter in the observed input sequences. As in recent experimental results, we found that recognition of an odor happened very early during stimulus presentation in the model. Critically, by using the model, we found surprising but simple computational explanations for several experimental phenomena.

  5. Multi-volatile method for aroma analysis using sequential dynamic headspace sampling with an application to brewed coffee.

    Science.gov (United States)

    Ochiai, Nobuo; Tsunokawa, Jun; Sasamoto, Kikuo; Hoffmann, Andreas

    2014-12-05

    A novel multi-volatile method (MVM) using sequential dynamic headspace (DHS) sampling for analysis of aroma compounds in aqueous sample was developed. The MVM consists of three different DHS method parameters sets including choice of the replaceable adsorbent trap. The first DHS sampling at 25 °C using a carbon-based adsorbent trap targets very volatile solutes with high vapor pressure (>20 kPa). The second DHS sampling at 25 °C using the same type of carbon-based adsorbent trap targets volatile solutes with moderate vapor pressure (1-20 kPa). The third DHS sampling using a Tenax TA trap at 80 °C targets solutes with low vapor pressure (0.9910) and high sensitivity (limit of detection: 1.0-7.5 ng mL(-1)) even with MS scan mode. The feasibility and benefit of the method was demonstrated with analysis of a wide variety of aroma compounds in brewed coffee. Ten potent aroma compounds from top-note to base-note (acetaldehyde, 2,3-butanedione, 4-ethyl guaiacol, furaneol, guaiacol, 3-methyl butanal, 2,3-pentanedione, 2,3,5-trimethyl pyrazine, vanillin, and 4-vinyl guaiacol) could be identified together with an additional 72 aroma compounds. Thirty compounds including 9 potent aroma compounds were quantified in the range of 74-4300 ng mL(-1) (RSD<10%, n=5). Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

  6. Conditions for Model Matching of Switched Asynchronous Sequential Machines with Output Feedback

    OpenAIRE

    Jung–Min Yang

    2016-01-01

    Solvability of the model matching problem for input/output switched asynchronous sequential machines is discussed in this paper. The control objective is to determine the existence condition and design algorithm for a corrective controller that can match the stable-state behavior of the closed-loop system to that of a reference model. Switching operations and correction procedures are incorporated using output feedback so that the controlled switched machine can show the ...

  7. Sequential Markov chain Monte Carlo filter with simultaneous model selection for electrocardiogram signal modeling.

    Science.gov (United States)

    Edla, Shwetha; Kovvali, Narayan; Papandreou-Suppappola, Antonia

    2012-01-01

    Constructing statistical models of electrocardiogram (ECG) signals, whose parameters can be used for automated disease classification, is of great importance in precluding manual annotation and providing prompt diagnosis of cardiac diseases. ECG signals consist of several segments with different morphologies (namely the P wave, QRS complex and the T wave) in a single heart beat, which can vary across individuals and diseases. Also, existing statistical ECG models exhibit a reliance upon obtaining a priori information from the ECG data by using preprocessing algorithms to initialize the filter parameters, or to define the user-specified model parameters. In this paper, we propose an ECG modeling technique using the sequential Markov chain Monte Carlo (SMCMC) filter that can perform simultaneous model selection, by adaptively choosing from different representations depending upon the nature of the data. Our results demonstrate the ability of the algorithm to track various types of ECG morphologies, including intermittently occurring ECG beats. In addition, we use the estimated model parameters as the feature set to classify between ECG signals with normal sinus rhythm and four different types of arrhythmia.

  8. Modeling eye gaze patterns in clinician-patient interaction with lag sequential analysis.

    Science.gov (United States)

    Montague, Enid; Xu, Jie; Chen, Ping-Yu; Asan, Onur; Barrett, Bruce P; Chewning, Betty

    2011-10-01

    The aim of this study was to examine whether lag sequential analysis could be used to describe eye gaze orientation between clinicians and patients in the medical encounter. This topic is particularly important as new technologies are implemented into multiuser health care settings in which trust is critical and nonverbal cues are integral to achieving trust. This analysis method could lead to design guidelines for technologies and more effective assessments of interventions. Nonverbal communication patterns are important aspects of clinician-patient interactions and may affect patient outcomes. The eye gaze behaviors of clinicians and patients in 110 videotaped medical encounters were analyzed using the lag sequential method to identify significant behavior sequences. Lag sequential analysis included both event-based lag and time-based lag. Results from event-based lag analysis showed that the patient's gaze followed that of the clinician, whereas the clinician's gaze did not follow the patient's. Time-based sequential analysis showed that responses from the patient usually occurred within 2 s after the initial behavior of the clinician. Our data suggest that the clinician's gaze significantly affects the medical encounter but that the converse is not true. Findings from this research have implications for the design of clinical work systems and modeling interactions. Similar research methods could be used to identify different behavior patterns in clinical settings (physical layout, technology, etc.) to facilitate and evaluate clinical work system designs.

  9. Mathematical Model for the Sequential Action of Radiation and Heat on Yeast Cells

    International Nuclear Information System (INIS)

    Kim, Jin Kyu; Lee, Yun Jong; Kim, Su Hyoun; Nili, Mohammad; Zhurakovskaya, Galina P.; Petin, Vladislav G.

    2009-01-01

    It is well known that the synergistic interaction of hyperthermia with ionizing radiation and other agents is widely used in hyperthermic oncology. Interaction between two agents may be considered as synergistic or antagonistic when the effect produced is greater or smaller than the sum of the two single responses. It has long be considered that the mechanism of synergistic interaction of hyperthermia and ionizing radiation may be brought about by an inhibition of the repair from sublethal and potentially lethal damage at the cellular level. The inhibition of the recovery process after combined treatments cannot be considered as a reason for the synergy, but rather would be the expected and predicted consequence of the production of irreversible damage. On the basis of it, a simple mathematical model of the synergistic interaction of two agents acting simultaneously has been proposed. However, the model has not been applied to predict the degree of interaction of heat and ionizing radiation after their sequential action. Extension of the model to the sequential treatment of heat and ionizing radiation seems to be of interest for theoretical and practical reasons. Thus, the purposes of the present work is to suggest the simplest mathematical model which would be able to account for the results obtained and currently available experimental information on the sequential action of radiation and heat.

  10. Development and sensitivity analysis of a fullykinetic model of sequential reductive dechlorination in subsurface

    DEFF Research Database (Denmark)

    Malaguerra, Flavio; Chambon, Julie Claire Claudia; Albrechtsen, Hans-Jørgen

    2010-01-01

    and natural degradation of chlorinated solvents frequently occurs in the subsurface through sequential reductive dechlorination. However, the occurrence and the performance of natural sequential reductive dechlorination strongly depends on environmental factor such as redox conditions, presence of fermenting...... organic matter / electron donors, presence of specific biomass, etc. Here we develop a new fully-kinetic biogeochemical reactive model able to simulate chlorinated solvents degradation as well as production and consumption of molecular hydrogen. The model is validated using batch experiment data......Chlorinated hydrocarbons originating from point sources are amongst the most prevalent contaminants of ground water and often represent a serious threat to groundwater-based drinking water resources. Natural attenuation of contaminant plumes can play a major role in contaminated site management...

  11. Sequential determination of multi-nutrient elements in natural water samples with a reverse flow injection system.

    Science.gov (United States)

    Lin, Kunning; Ma, Jian; Yuan, Dongxing; Feng, Sichao; Su, Haitao; Huang, Yongming; Shangguan, Qipei

    2017-05-15

    An integrated system was developed for automatic and sequential determination of NO 2 - , NO 3 - , PO 4 3- , Fe 2+ , Fe 3+ and Mn 2+ in natural waters based on reverse flow injection analysis combined with spectrophotometric detection. The system operation was controlled by a single chip microcomputer and laboratory-programmed software written in LabVIEW. The experimental parameters for each nutrient element analysis were optimized based on a univariate experimental design, and interferences from common ions were evaluated. The upper limits of the linear range (along with detection limit, µmolL -1 ) of the proposed method was 20 (0.03), 200 (0.7), 12 (0.3), 5 (0.03), 5 (0.03), 9 (0.2) µmolL -1 , for NO 2 - , NO 3 - , PO 4 3- , Fe 2+ , Fe 3+ and Mn 2+ , respectively. The relative standard deviations were below 5% (n=9-13) and the recoveries varied from 88.0±1.0% to 104.5±1.0% for spiked water samples. The sample throughput was about 20h -1 . This system has been successfully applied for the determination of multi-nutrient elements in different kinds of water samples and showed good agreement with reference methods (slope 1.0260±0.0043, R 2 =0.9991, n=50). Copyright © 2017 Elsevier B.V. All rights reserved.

  12. A SEQUENTIAL MODEL OF INNOVATION STRATEGY—COMPANY NON-FINANCIAL PERFORMANCE LINKS

    OpenAIRE

    Ciptono, Wakhid Slamet

    2006-01-01

    This study extends the prior research (Zahra and Das 1993) by examining the association between a company’s innovation strategy and its non-financial performance in the upstream and downstream strategic business units (SBUs) of oil and gas companies. The sequential model suggests a causal sequence among six dimensions of innovation strategy (leadership orientation, process innovation, product/service innovation, external innovation source, internal innovation source, and investment) that may ...

  13. [Mathematical modeling of synergistic interaction of sequential thermoradiation action on mammalian cells].

    Science.gov (United States)

    Belkina, S V; Semkina, M A; Kritskiĭ, R O; Petin, V G

    2010-01-01

    Data obtained by other authors for mammalian cells treated by sequential action of ionizing radiation and hyperthermia were used to estimate the dependence of synergistic enhancement ratio on the ratio of damages induced by these agents. Experimental results were described and interpreted by means of the mathematical model of synergism in accordance with which the synergism is expected to result from the additional lethal damage arising from the interaction of sublesions induced by both agents.

  14. Employees’ Perceptions of Corporate Social Responsibility and Job Performance: A Sequential Mediation Model

    Directory of Open Access Journals (Sweden)

    Inyong Shin

    2016-05-01

    Full Text Available In spite of the increasing importance of corporate social responsibility (CSR and employee job performance, little is still known about the links between the socially responsible actions of organizations and the job performance of their members. In order to explain how employees’ perceptions of CSR influence their job performance, this study first examines the relationships between perceived CSR, organizational identification, job satisfaction, and job performance, and then develops a sequential mediation model by fully integrating these links. The results of structural equation modeling analyses conducted for 250 employees at hotels in South Korea offered strong support for the proposed model. We found that perceived CSR was indirectly and positively associated with job performance sequentially mediated first through organizational identification and then job satisfaction. This study theoretically contributes to the CSR literature by revealing the sequential mechanism through which employees’ perceptions of CSR affect their job performance, and offers practical implications by stressing the importance of employees’ perceptions of CSR. Limitations of this study and future research directions are discussed.

  15. Fixed-Precision Sequential Sampling Plans for Estimating Alfalfa Caterpillar, Colias lesbia, Egg Density in Alfalfa, Medicago sativa, Fields in Córdoba, Argentina

    Science.gov (United States)

    Serra, Gerardo V.; Porta, Norma C. La; Avalos, Susana; Mazzuferi, Vilma

    2013-01-01

    The alfalfa caterpillar, Colias lesbia (Fabricius) (Lepidoptera: Pieridae), is a major pest of alfalfa, Medicago sativa L. (Fabales: Fabaceae), crops in Argentina. Its management is based mainly on chemical control of larvae whenever the larvae exceed the action threshold. To develop and validate fixed-precision sequential sampling plans, an intensive sampling programme for C. lesbia eggs was carried out in two alfalfa plots located in the Province of Córdoba, Argentina, from 1999 to 2002. Using Resampling for Validation of Sampling Plans software, 12 additional independent data sets were used to validate the sequential sampling plan with precision levels of 0.10 and 0.25 (SE/mean), respectively. For a range of mean densities of 0.10 to 8.35 eggs/sample, an average sample size of only 27 and 26 sample units was required to achieve a desired precision level of 0.25 for the sampling plans of Green and Kuno, respectively. As the precision level was increased to 0.10, average sample size increased to 161 and 157 sample units for the sampling plans of Green and Kuno, respectively. We recommend using Green's sequential sampling plan because it is less sensitive to changes in egg density. These sampling plans are a valuable tool for researchers to study population dynamics and to evaluate integrated pest management strategies. PMID:23909840

  16. Encoding Sequential Information in Semantic Space Models: Comparing Holographic Reduced Representation and Random Permutation

    Directory of Open Access Journals (Sweden)

    Gabriel Recchia

    2015-01-01

    Full Text Available Circular convolution and random permutation have each been proposed as neurally plausible binding operators capable of encoding sequential information in semantic memory. We perform several controlled comparisons of circular convolution and random permutation as means of encoding paired associates as well as encoding sequential information. Random permutations outperformed convolution with respect to the number of paired associates that can be reliably stored in a single memory trace. Performance was equal on semantic tasks when using a small corpus, but random permutations were ultimately capable of achieving superior performance due to their higher scalability to large corpora. Finally, “noisy” permutations in which units are mapped to other units arbitrarily (no one-to-one mapping perform nearly as well as true permutations. These findings increase the neurological plausibility of random permutations and highlight their utility in vector space models of semantics.

  17. Sequential updating of a new dynamic pharmacokinetic model for caffeine in premature neonates.

    Science.gov (United States)

    Micallef, Sandrine; Amzal, Billy; Bach, Véronique; Chardon, Karen; Tourneux, Pierre; Bois, Frédéric Y

    2007-01-01

    Caffeine treatment is widely used in nursing care to reduce the risk of apnoea in premature neonates. To check the therapeutic efficacy of the treatment against apnoea, caffeine concentration in blood is an important indicator. The present study was aimed at building a pharmacokinetic model as a basis for a medical decision support tool. In the proposed model, time dependence of physiological parameters is introduced to describe rapid growth of neonates. To take into account the large variability in the population, the pharmacokinetic model is embedded in a population structure. The whole model is inferred within a Bayesian framework. To update caffeine concentration predictions as data of an incoming patient are collected, we propose a fast method that can be used in a medical context. This involves the sequential updating of model parameters (at individual and population levels) via a stochastic particle algorithm. Our model provides better predictions than the ones obtained with models previously published. We show, through an example, that sequential updating improves predictions of caffeine concentration in blood (reduce bias and length of credibility intervals). The update of the pharmacokinetic model using body mass and caffeine concentration data is studied. It shows how informative caffeine concentration data are in contrast to body mass data. This study provides the methodological basis to predict caffeine concentration in blood, after a given treatment if data are collected on the treated neonate.

  18. A new moving strategy for the sequential Monte Carlo approach in optimizing the hydrological model parameters

    Science.gov (United States)

    Zhu, Gaofeng; Li, Xin; Ma, Jinzhu; Wang, Yunquan; Liu, Shaomin; Huang, Chunlin; Zhang, Kun; Hu, Xiaoli

    2018-04-01

    Sequential Monte Carlo (SMC) samplers have become increasing popular for estimating the posterior parameter distribution with the non-linear dependency structures and multiple modes often present in hydrological models. However, the explorative capabilities and efficiency of the sampler depends strongly on the efficiency in the move step of SMC sampler. In this paper we presented a new SMC sampler entitled the Particle Evolution Metropolis Sequential Monte Carlo (PEM-SMC) algorithm, which is well suited to handle unknown static parameters of hydrologic model. The PEM-SMC sampler is inspired by the works of Liang and Wong (2001) and operates by incorporating the strengths of the genetic algorithm, differential evolution algorithm and Metropolis-Hasting algorithm into the framework of SMC. We also prove that the sampler admits the target distribution to be a stationary distribution. Two case studies including a multi-dimensional bimodal normal distribution and a conceptual rainfall-runoff hydrologic model by only considering parameter uncertainty and simultaneously considering parameter and input uncertainty show that PEM-SMC sampler is generally superior to other popular SMC algorithms in handling the high dimensional problems. The study also indicated that it may be important to account for model structural uncertainty by using multiplier different hydrological models in the SMC framework in future study.

  19. The effect of sequential dual-gas testing on laser-induced breakdown spectroscopy-based discrimination: Application to brass samples and bacterial strains

    International Nuclear Information System (INIS)

    Rehse, Steven J.; Mohaidat, Qassem I.

    2009-01-01

    Four Cu-Zn brass alloys with different stoichiometries and compositions have been analyzed by laser-induced breakdown spectroscopy (LIBS) using nanosecond laser pulses. The intensities of 15 emission lines of copper, zinc, lead, carbon, and aluminum (as well as the environmental contaminants sodium and calcium) were normalized and analyzed with a discriminant function analysis (DFA) to rapidly categorize the samples by alloy. The alloys were tested sequentially in two different noble gases (argon and helium) to enhance discrimination between them. When emission intensities from samples tested sequentially in both gases were combined to form a single 30-spectral line 'fingerprint' of the alloy, an overall 100% correct identification was achieved. This was a modest improvement over using emission intensities acquired in argon gas alone. A similar study was performed to demonstrate an enhanced discrimination between two strains of Escherichia coli (a Gram-negative bacterium) and a Gram-positive bacterium. When emission intensities from bacteria sequentially ablated in two different gas environments were combined, the DFA achieved a 100% categorization accuracy. This result showed the benefit of sequentially testing highly similar samples in two different ambient gases to enhance discrimination between the samples.

  20. Sequential extraction of heavy metals from urban dust and street sediments. Pt. 1. Sequential extraction of heavy metals in micro samples; Sequentielle Schwermetallextraktion aus Staubniederschlaegen und Strassensedimenten. T. 1. Sequentielle Schwermetallextraktion von Mikroproben

    Energy Technology Data Exchange (ETDEWEB)

    Heiser, U.; Norra, S.; Stueben, D.; Wagner, M. von [Karlsruhe Univ. (T.H.) (Germany). Inst. fuer Petrographie und Geochemie

    1999-01-01

    For the application of sequential extraction of heavy metals from samples that can only be obtained in amounts of a few milligrams (micro samples, e.g. airborne dust fallout), the method after Zeien and Bruemmer (1989) was progressed. A down scale to 1:100 was carried out and the accuracy of this method with variable sample amounts of about 20 mg and an extraction volume of 500 {mu}l was proofed with standard soil samples. The influence of variable extraction ratios (ratio of sample amount and volume of extraction solvent) and the influence of intensive treatment of dust sampled by the Bergerhoff-method (VDI 2119/2, 1972) prior sequential extraction, was within the precision of measurement of our method. Thus, we showed that sequential extraction can be applied for the investigation of heavy metal mobilization in micro samples with variable sample amounts. A first application of our method for microsamples was carried out to investigate airborne dust fallout and street sediments at two urban sites where different heavy metal immission rates due to traffic influence occur. These investigations will be presented in part 2 (`Sequential extraxction of heavy metals from urban dust`). (orig.) [Deutsch] Fuer die Anwendung der sequentiellen Schwermetallextraktion auf Proben, die nur im Milligramm-Bereich erhalten werden koennen (Mikroproben, wie z.B. Staubniederschlaege), wurde die Methode von Zeien und Bruemmer (1989) weiterentwickelt. Der Extraktionsmassstab wurde um den Faktor 1:100 verringert und die Reproduzierbarkeit des Verfahrens mit variablen Probenmengen um 20 mg und einem Extraktionsvolumen von 500 {mu}l mit Hilfe von Standardboeden nachgewiesen. Moegliche Einfluesse variabler Extraktionsverhaeltnisse (Verhaeltnis von Probenmenge zu Extraktionsvolumen) sowie eine aufwendige Vorbehandlung von Staubproben, die nach der Bergerhoff-Methode (VDI 2119/2, 1972) gesammelt wurden, lagen bei diesen Untersuchungen weitgehend im Variationsbereich des Verfahrens. Die

  1. A sequential threshold cure model for genetic analysis of time-to-event data

    DEFF Research Database (Denmark)

    Ødegård, J; Madsen, Per; Labouriau, Rodrigo S.

    2011-01-01

    In analysis of time-to-event data, classical survival models ignore the presence of potential nonsusceptible (cured) individuals, which, if present, will invalidate the inference procedures. Existence of nonsusceptible individuals is particularly relevant under challenge testing with specific...... pathogens, which is a common procedure in aquaculture breeding schemes. A cure model is a survival model accounting for a fraction of nonsusceptible individuals in the population. This study proposes a mixed cure model for time-to-event data, measured as sequential binary records. In a simulation study...... survival data were generated through 2 underlying traits: susceptibility and endurance (risk of dying per time-unit), associated with 2 sets of underlying liabilities. Despite considerable phenotypic confounding, the proposed model was largely able to distinguish the 2 traits. Furthermore, if selection...

  2. DUAL STATE-PARAMETER UPDATING SCHEME ON A CONCEPTUAL HYDROLOGIC MODEL USING SEQUENTIAL MONTE CARLO FILTERS

    Science.gov (United States)

    Noh, Seong Jin; Tachikawa, Yasuto; Shiiba, Michiharu; Kim, Sunmin

    Applications of data assimilation techniques have been widely used to improve upon the predictability of hydrologic modeling. Among various data assimilation techniques, sequential Monte Carlo (SMC) filters, known as "particle filters" provide the capability to handle non-linear and non-Gaussian state-space models. This paper proposes a dual state-parameter updating scheme (DUS) based on SMC methods to estimate both state and parameter variables of a hydrologic model. We introduce a kernel smoothing method for the robust estimation of uncertain model parameters in the DUS. The applicability of the dual updating scheme is illustrated using the implementation of the storage function model on a middle-sized Japanese catchment. We also compare performance results of DUS combined with various SMC methods, such as SIR, ASIR and RPF.

  3. Learning of state-space models with highly informative observations: A tempered sequential Monte Carlo solution

    Science.gov (United States)

    Svensson, Andreas; Schön, Thomas B.; Lindsten, Fredrik

    2018-05-01

    Probabilistic (or Bayesian) modeling and learning offers interesting possibilities for systematic representation of uncertainty using probability theory. However, probabilistic learning often leads to computationally challenging problems. Some problems of this type that were previously intractable can now be solved on standard personal computers thanks to recent advances in Monte Carlo methods. In particular, for learning of unknown parameters in nonlinear state-space models, methods based on the particle filter (a Monte Carlo method) have proven very useful. A notoriously challenging problem, however, still occurs when the observations in the state-space model are highly informative, i.e. when there is very little or no measurement noise present, relative to the amount of process noise. The particle filter will then struggle in estimating one of the basic components for probabilistic learning, namely the likelihood p (data | parameters). To this end we suggest an algorithm which initially assumes that there is substantial amount of artificial measurement noise present. The variance of this noise is sequentially decreased in an adaptive fashion such that we, in the end, recover the original problem or possibly a very close approximation of it. The main component in our algorithm is a sequential Monte Carlo (SMC) sampler, which gives our proposed method a clear resemblance to the SMC2 method. Another natural link is also made to the ideas underlying the approximate Bayesian computation (ABC). We illustrate it with numerical examples, and in particular show promising results for a challenging Wiener-Hammerstein benchmark problem.

  4. Behavioral Modeling of WSN MAC Layer Security Attacks: A Sequential UML Approach

    DEFF Research Database (Denmark)

    Pawar, Pranav M.; Nielsen, Rasmus Hjorth; Prasad, Neeli R.

    2012-01-01

    is the vulnerability to security attacks/threats. The performance and behavior of a WSN are vastly affected by such attacks. In order to be able to better address the vulnerabilities of WSNs in terms of security, it is important to understand the behavior of the attacks. This paper addresses the behavioral modeling...... of medium access control (MAC) security attacks in WSNs. The MAC layer is responsible for energy consumption, delay and channel utilization of the network and attacks on this layer can introduce significant degradation of the individual sensor nodes due to energy drain and in performance due to delays....... The behavioral modeling of attacks will be beneficial for designing efficient and secure MAC layer protocols. The security attacks are modeled using a sequential diagram approach of Unified Modeling Language (UML). Further, a new attack definition, specific to hybrid MAC mechanisms, is proposed....

  5. Macroscopic Dynamic Modeling of Sequential Batch Cultures of Hybridoma Cells: An Experimental Validation

    Directory of Open Access Journals (Sweden)

    Laurent Dewasme

    2017-02-01

    Full Text Available Hybridoma cells are commonly grown for the production of monoclonal antibodies (MAb. For monitoring and control purposes of the bioreactors, dynamic models of the cultures are required. However these models are difficult to infer from the usually limited amount of available experimental data and do not focus on target protein production optimization. This paper explores an experimental case study where hybridoma cells are grown in a sequential batch reactor. The simplest macroscopic reaction scheme translating the data is first derived using a maximum likelihood principal component analysis. Subsequently, nonlinear least-squares estimation is used to determine the kinetic laws. The resulting dynamic model reproduces quite satisfactorily the experimental data, as evidenced in direct and cross-validation tests. Furthermore, model predictions can also be used to predict optimal medium renewal time and composition.

  6. Corpus Callosum Analysis using MDL-based Sequential Models of Shape and Appearance

    DEFF Research Database (Denmark)

    Stegmann, Mikkel Bille; Davies, Rhodri H.; Ryberg, Charlotte

    2004-01-01

    are proposed, but all remain applicable to other domain problems. The well-known multi-resolution AAM optimisation is extended to include sequential relaxations on texture resolution, model coverage and model parameter constraints. Fully unsupervised analysis is obtained by exploiting model parameter...... that show that the method produces accurate, robust and rapid segmentations in a cross sectional study of 17 subjects, establishing its feasibility as a fully automated clinical tool for analysis and segmentation.......This paper describes a method for automatically analysing and segmenting the corpus callosum from magnetic resonance images of the brain based on the widely used Active Appearance Models (AAMs) by Cootes et al. Extensions of the original method, which are designed to improve this specific case...

  7. Exact Sampling and Decoding in High-Order Hidden Markov Models

    NARCIS (Netherlands)

    Carter, S.; Dymetman, M.; Bouchard, G.

    2012-01-01

    We present a method for exact optimization and sampling from high order Hidden Markov Models (HMMs), which are generally handled by approximation techniques. Motivated by adaptive rejection sampling and heuristic search, we propose a strategy based on sequentially refining a lower-order language

  8. Exposure assessment of mobile phone base station radiation in an outdoor environment using sequential surrogate modeling.

    Science.gov (United States)

    Aerts, Sam; Deschrijver, Dirk; Joseph, Wout; Verloock, Leen; Goeminne, Francis; Martens, Luc; Dhaene, Tom

    2013-05-01

    Human exposure to background radiofrequency electromagnetic fields (RF-EMF) has been increasing with the introduction of new technologies. There is a definite need for the quantification of RF-EMF exposure but a robust exposure assessment is not yet possible, mainly due to the lack of a fast and efficient measurement procedure. In this article, a new procedure is proposed for accurately mapping the exposure to base station radiation in an outdoor environment based on surrogate modeling and sequential design, an entirely new approach in the domain of dosimetry for human RF exposure. We tested our procedure in an urban area of about 0.04 km(2) for Global System for Mobile Communications (GSM) technology at 900 MHz (GSM900) using a personal exposimeter. Fifty measurement locations were sufficient to obtain a coarse street exposure map, locating regions of high and low exposure; 70 measurement locations were sufficient to characterize the electric field distribution in the area and build an accurate predictive interpolation model. Hence, accurate GSM900 downlink outdoor exposure maps (for use in, e.g., governmental risk communication and epidemiological studies) are developed by combining the proven efficiency of sequential design with the speed of exposimeter measurements and their ease of handling. Copyright © 2013 Wiley Periodicals, Inc.

  9. Modeling and Predicting AD Progression by Regression Analysis of Sequential Clinical Data

    KAUST Repository

    Xie, Qing

    2016-02-23

    Alzheimer\\'s Disease (AD) is currently attracting much attention in elders\\' care. As the increasing availability of massive clinical diagnosis data, especially the medical images of brain scan, it is highly significant to precisely identify and predict the potential AD\\'s progression based on the knowledge in the diagnosis data. In this paper, we follow a novel sequential learning framework to model the disease progression for AD patients\\' care. Different from the conventional approaches using only initial or static diagnosis data to model the disease progression for different durations, we design a score-involved approach and make use of the sequential diagnosis information in different disease stages to jointly simulate the disease progression. The actual clinical scores are utilized in progress to make the prediction more pertinent and reliable. We examined our approach by extensive experiments on the clinical data provided by the Alzheimer\\'s Disease Neuroimaging Initiative (ADNI). The results indicate that the proposed approach is more effective to simulate and predict the disease progression compared with the existing methods.

  10. Modeling and Predicting AD Progression by Regression Analysis of Sequential Clinical Data

    KAUST Repository

    Xie, Qing; Wang, Su; Zhu, Jia; Zhang, Xiangliang

    2016-01-01

    Alzheimer's Disease (AD) is currently attracting much attention in elders' care. As the increasing availability of massive clinical diagnosis data, especially the medical images of brain scan, it is highly significant to precisely identify and predict the potential AD's progression based on the knowledge in the diagnosis data. In this paper, we follow a novel sequential learning framework to model the disease progression for AD patients' care. Different from the conventional approaches using only initial or static diagnosis data to model the disease progression for different durations, we design a score-involved approach and make use of the sequential diagnosis information in different disease stages to jointly simulate the disease progression. The actual clinical scores are utilized in progress to make the prediction more pertinent and reliable. We examined our approach by extensive experiments on the clinical data provided by the Alzheimer's Disease Neuroimaging Initiative (ADNI). The results indicate that the proposed approach is more effective to simulate and predict the disease progression compared with the existing methods.

  11. Multiple sequential failure model: A probabilistic approach to quantifying human error dependency

    International Nuclear Information System (INIS)

    Samanta

    1985-01-01

    This paper rpesents a probabilistic approach to quantifying human error dependency when multiple tasks are performed. Dependent human failures are dominant contributors to risks from nuclear power plants. An overview of the Multiple Sequential Failure (MSF) model developed and its use in probabilistic risk assessments (PRAs) depending on the available data are discussed. A small-scale psychological experiment was conducted on the nature of human dependency and the interpretation of the experimental data by the MSF model show remarkable accommodation of the dependent failure data. The model, which provides an unique method for quantification of dependent failures in human reliability analysis, can be used in conjunction with any of the general methods currently used for performing the human reliability aspect in PRAs

  12. Implementing reduced-risk integrated pest management in fresh-market cabbage: influence of sampling parameters, and validation of binomial sequential sampling plans for the cabbage looper (Lepidoptera Noctuidae).

    Science.gov (United States)

    Burkness, Eric C; Hutchison, W D

    2009-10-01

    Populations of cabbage looper, Trichoplusiani (Lepidoptera: Noctuidae), were sampled in experimental plots and commercial fields of cabbage (Brasicca spp.) in Minnesota during 1998-1999 as part of a larger effort to implement an integrated pest management program. Using a resampling approach and the Wald's sequential probability ratio test, sampling plans with different sampling parameters were evaluated using independent presence/absence and enumerative data. Evaluations and comparisons of the different sampling plans were made based on the operating characteristic and average sample number functions generated for each plan and through the use of a decision probability matrix. Values for upper and lower decision boundaries, sequential error rates (alpha, beta), and tally threshold were modified to determine parameter influence on the operating characteristic and average sample number functions. The following parameters resulted in the most desirable operating characteristic and average sample number functions; action threshold of 0.1 proportion of plants infested, tally threshold of 1, alpha = beta = 0.1, upper boundary of 0.15, lower boundary of 0.05, and resampling with replacement. We found that sampling parameters can be modified and evaluated using resampling software to achieve desirable operating characteristic and average sample number functions. Moreover, management of T. ni by using binomial sequential sampling should provide a good balance between cost and reliability by minimizing sample size and maintaining a high level of correct decisions (>95%) to treat or not treat.

  13. Validation studies on indexed sequential modeling for the Colorado River Basin

    International Nuclear Information System (INIS)

    Labadie, J.W.; Fontane, D.G.; Salas, J.D.; Ouarda, T.

    1991-01-01

    This paper reports on a method called indexed sequential modeling (ISM) that has been developed by the Western Area Power Administration to estimate reliable levels of project dependable power capacity (PDC) and applied to several federal hydro systems in the Western U.S. The validity of ISM in relation to more commonly accepted stochastic modeling approaches is analyzed by applying it to the Colorado River Basin using the Colorado River Simulation System (CRSS) developed by the U.S. Bureau of Reclamation. Performance of ISM is compared with results from input of stochastically generated data using the LAST Applied Stochastic Techniques Package. Results indicate that output generated from ISM synthetically generated sequences display an acceptable correspondence with results obtained from final convergent stochastically generated hydrology for the Colorado River Basin

  14. Modeling Search Behaviors during the Acquisition of Expertise in a Sequential Decision-Making Task

    Directory of Open Access Journals (Sweden)

    Cristóbal Moënne-Loccoz

    2017-09-01

    Full Text Available Our daily interaction with the world is plagued of situations in which we develop expertise through self-motivated repetition of the same task. In many of these interactions, and especially when dealing with computer and machine interfaces, we must deal with sequences of decisions and actions. For instance, when drawing cash from an ATM machine, choices are presented in a step-by-step fashion and a specific sequence of choices must be performed in order to produce the expected outcome. But, as we become experts in the use of such interfaces, is it possible to identify specific search and learning strategies? And if so, can we use this information to predict future actions? In addition to better understanding the cognitive processes underlying sequential decision making, this could allow building adaptive interfaces that can facilitate interaction at different moments of the learning curve. Here we tackle the question of modeling sequential decision-making behavior in a simple human-computer interface that instantiates a 4-level binary decision tree (BDT task. We record behavioral data from voluntary participants while they attempt to solve the task. Using a Hidden Markov Model-based approach that capitalizes on the hierarchical structure of behavior, we then model their performance during the interaction. Our results show that partitioning the problem space into a small set of hierarchically related stereotyped strategies can potentially capture a host of individual decision making policies. This allows us to follow how participants learn and develop expertise in the use of the interface. Moreover, using a Mixture of Experts based on these stereotyped strategies, the model is able to predict the behavior of participants that master the task.

  15. Fractionation of metals in street sediment samples by using the BCR sequential extraction procedure and multivariate statistical elucidation of the data

    International Nuclear Information System (INIS)

    Kartal, Senol; Aydin, Zeki; Tokalioglu, Serife

    2006-01-01

    The concentrations of metals (Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, and Zn) in street sediment samples were determined by flame atomic absorption spectrometry (FAAS) using the modified BCR (the European Community Bureau of Reference) sequential extraction procedure. According to the BCR protocol for extracting the metals from the relevant target phases, 1.0 g of specimen of the sample was treated with 0.11 M acetic acid (exchangeable and bound to carbonates), 0.5 M hydroxylamine hydrochloride (bound to iron- and manganese-oxides), and 8.8 M hydrogen peroxide plus 1 M ammonium acetate (bound to sulphides and organics), sequentially. The residue was treated with aqua regia solution for recovery studies, although this step is not part of the BCR procedure. The mobility sequence based on the sum of the BCR sequential extraction stages was: Cd ∼ Zn (∼90%) > Pb (∼84%) > Cu (∼75%) > Mn (∼70%) > Co (∼57%) > Ni (∼43%) > Cr (∼40%) > Fe (∼17%). Enrichment factors as the criteria for examining the impact of the anthropogenic emission sources of heavy metals were calculated, and it was observed that the highest enriched elements were Cd, Pb, and Zn in the dust samples, average 190, 111, and 20, respectively. Correlation analysis (CA) and principal component analysis (PCA) were applied to the data matrix to evaluate the analytical results and to identify the possible pollution sources of metals. PCA revealed that the sampling area was mainly influenced from three pollution sources, namely; traffic, industrial, and natural sources. The results show that chemical sequential extraction is a precious operational tool. Validation of the analytical results was checked by both recovery studies and analysis of the standard reference material (NIST SRM 2711 Montana Soil)

  16. Mind-to-mind heteroclinic coordination: Model of sequential episodic memory initiation

    Science.gov (United States)

    Afraimovich, V. S.; Zaks, M. A.; Rabinovich, M. I.

    2018-05-01

    Retrieval of episodic memory is a dynamical process in the large scale brain networks. In social groups, the neural patterns, associated with specific events directly experienced by single members, are encoded, recalled, and shared by all participants. Here, we construct and study the dynamical model for the formation and maintaining of episodic memory in small ensembles of interacting minds. We prove that the unconventional dynamical attractor of this process—the nonsmooth heteroclinic torus—is structurally stable within the Lotka-Volterra-like sets of equations. Dynamics on this torus combines the absence of chaos with asymptotic instability of every separate trajectory; its adequate quantitative characteristics are length-related Lyapunov exponents. Variation of the coupling strength between the participants results in different types of sequential switching between metastable states; we interpret them as stages in formation and modification of the episodic memory.

  17. Multistrain models predict sequential multidrug treatment strategies to result in less antimicrobial resistance than combination treatment

    DEFF Research Database (Denmark)

    Ahmad, Amais; Zachariasen, Camilla; Christiansen, Lasse Engbo

    2016-01-01

    generated by a mathematical model of the competitive growth of multiple strains of Escherichia coli.Results: Simulation studies showed that sequential use of tetracycline and ampicillin reduced the level of double resistance, when compared to the combination treatment. The effect of the cycling frequency...... frequency did not play a role in suppressing the growth of resistant strains, but the specific order of the two antimicrobials did. Predictions made from the study could be used to redesign multidrug treatment strategies not only for intramuscular treatment in pigs, but also for other dosing routes.......Background: Combination treatment is increasingly used to fight infections caused by bacteria resistant to two or more antimicrobials. While multiple studies have evaluated treatment strategies to minimize the emergence of resistant strains for single antimicrobial treatment, fewer studies have...

  18. Modelling sequential Biosphere systems under Climate change for radioactive waste disposal. Project BIOCLIM

    International Nuclear Information System (INIS)

    Texier, D.; Degnan, P.; Loutre, M.F.; Lemaitre, G.; Paillard, D.; Thorne, M.

    2000-01-01

    The BIOCLIM project (Modelling Sequential Biosphere systems under Climate change for Radioactive Waste Disposal) is part of the EURATOM fifth European framework programme. The project was launched in October 2000 for a three-year period. It is coordinated by ANDRA, the French national radioactive waste management agency. The project brings together a number of European radioactive waste management organisations that have national responsibilities for the safe disposal of radioactive wastes, and several highly experienced climate research teams. Waste management organisations involved are: NIREX (UK), GRS (Germany), ENRESA (Spain), NRI (Czech Republic) and ANDRA (France). Climate research teams involved are: LSCE (CEA/CNRS, France), CIEMAT (Spain), UPMETSIMM (Spain), UCL/ASTR (Belgium) and CRU (UEA, UK). The Environmental Agency for England and Wales provides a regulatory perspective. The consulting company Enviros Consulting (UK) assists ANDRA by contributing to both the administrative and scientific aspects of the project. This paper describes the project and progress to date. (authors)

  19. On Modeling Large-Scale Multi-Agent Systems with Parallel, Sequential and Genuinely Asynchronous Cellular Automata

    International Nuclear Information System (INIS)

    Tosic, P.T.

    2011-01-01

    We study certain types of Cellular Automata (CA) viewed as an abstraction of large-scale Multi-Agent Systems (MAS). We argue that the classical CA model needs to be modified in several important respects, in order to become a relevant and sufficiently general model for the large-scale MAS, and so that thus generalized model can capture many important MAS properties at the level of agent ensembles and their long-term collective behavior patterns. We specifically focus on the issue of inter-agent communication in CA, and propose sequential cellular automata (SCA) as the first step, and genuinely Asynchronous Cellular Automata (ACA) as the ultimate deterministic CA-based abstract models for large-scale MAS made of simple reactive agents. We first formulate deterministic and nondeterministic versions of sequential CA, and then summarize some interesting configuration space properties (i.e., possible behaviors) of a restricted class of sequential CA. In particular, we compare and contrast those properties of sequential CA with the corresponding properties of the classical (that is, parallel and perfectly synchronous) CA with the same restricted class of update rules. We analytically demonstrate failure of the studied sequential CA models to simulate all possible behaviors of perfectly synchronous parallel CA, even for a very restricted class of non-linear totalistic node update rules. The lesson learned is that the interleaving semantics of concurrency, when applied to sequential CA, is not refined enough to adequately capture the perfect synchrony of parallel CA updates. Last but not least, we outline what would be an appropriate CA-like abstraction for large-scale distributed computing insofar as the inter-agent communication model is concerned, and in that context we propose genuinely asynchronous CA. (author)

  20. Methamphetamine-alcohol interactions in murine models of sequential and simultaneous oral drug-taking.

    Science.gov (United States)

    Fultz, Elissa K; Martin, Douglas L; Hudson, Courtney N; Kippin, Tod E; Szumlinski, Karen K

    2017-08-01

    A high degree of co-morbidity exists between methamphetamine (MA) addiction and alcohol use disorders and both sequential and simultaneous MA-alcohol mixing increases risk for co-abuse. As little preclinical work has focused on the biobehavioral interactions between MA and alcohol within the context of drug-taking behavior, we employed simple murine models of voluntary oral drug consumption to examine how prior histories of either MA- or alcohol-taking influence the intake of the other drug. In one study, mice with a 10-day history of binge alcohol-drinking [5,10, 20 and 40% (v/v); 2h/day] were trained to self-administer oral MA in an operant-conditioning paradigm (10-40mg/L). In a second study, mice with a 10-day history of limited-access oral MA-drinking (5, 10, 20 and 40mg/L; 2h/day) were presented with alcohol (5-40% v/v; 2h/day) and then a choice between solutions of 20% alcohol, 10mg/L MA or their mix. Under operant-conditioning procedures, alcohol-drinking mice exhibited less MA reinforcement overall, than water controls. However, when drug availability was not behaviorally-contingent, alcohol-drinking mice consumed more MA and exhibited greater preference for the 10mg/L MA solution than drug-naïve and combination drug-experienced mice. Conversely, prior MA-drinking history increased alcohol intake across a range of alcohol concentrations. These exploratory studies indicate the feasibility of employing procedurally simple murine models of sequential and simultaneous oral MA-alcohol mixing of relevance to advancing our biobehavioral understanding of MA-alcohol co-abuse. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. A discrete event modelling framework for simulation of long-term outcomes of sequential treatment strategies for ankylosing spondylitis

    NARCIS (Netherlands)

    A. Tran-Duy (An); A. Boonen (Annelies); M.A.F.J. van de Laar (Mart); A. Franke (Andre); J.L. Severens (Hans)

    2011-01-01

    textabstractObjective: To develop a modelling framework which can simulate long-term quality of life, societal costs and cost-effectiveness as affected by sequential drug treatment strategies for ankylosing spondylitis (AS). Methods: Discrete event simulation paradigm was selected for model

  2. A discrete event modelling framework for simulation of long-term outcomes of sequential treatment strategies for ankylosing spondylitis

    NARCIS (Netherlands)

    Tran-Duy, A.; Boonen, A.; Laar, M.A.F.J.; Franke, A.C.; Severens, J.L.

    2011-01-01

    Objective To develop a modelling framework which can simulate long-term quality of life, societal costs and cost-effectiveness as affected by sequential drug treatment strategies for ankylosing spondylitis (AS). Methods Discrete event simulation paradigm was selected for model development. Drug

  3. AUTOMATIC 3D BUILDING MODEL GENERATION FROM LIDAR AND IMAGE DATA USING SEQUENTIAL MINIMUM BOUNDING RECTANGLE

    Directory of Open Access Journals (Sweden)

    E. Kwak

    2012-07-01

    Full Text Available Digital Building Model is an important component in many applications such as city modelling, natural disaster planning, and aftermath evaluation. The importance of accurate and up-to-date building models has been discussed by many researchers, and many different approaches for efficient building model generation have been proposed. They can be categorised according to the data source used, the data processing strategy, and the amount of human interaction. In terms of data source, due to the limitations of using single source data, integration of multi-senor data is desired since it preserves the advantages of the involved datasets. Aerial imagery and LiDAR data are among the commonly combined sources to obtain 3D building models with good vertical accuracy from laser scanning and good planimetric accuracy from aerial images. The most used data processing strategies are data-driven and model-driven ones. Theoretically one can model any shape of buildings using data-driven approaches but practically it leaves the question of how to impose constraints and set the rules during the generation process. Due to the complexity of the implementation of the data-driven approaches, model-based approaches draw the attention of the researchers. However, the major drawback of model-based approaches is that the establishment of representative models involves a manual process that requires human intervention. Therefore, the objective of this research work is to automatically generate building models using the Minimum Bounding Rectangle algorithm and sequentially adjusting them to combine the advantages of image and LiDAR datasets.

  4. Analysis of membrane fusion as a two-state sequential process: evaluation of the stalk model.

    Science.gov (United States)

    Weinreb, Gabriel; Lentz, Barry R

    2007-06-01

    We propose a model that accounts for the time courses of PEG-induced fusion of membrane vesicles of varying lipid compositions and sizes. The model assumes that fusion proceeds from an initial, aggregated vesicle state ((A) membrane contact) through two sequential intermediate states (I(1) and I(2)) and then on to a fusion pore state (FP). Using this model, we interpreted data on the fusion of seven different vesicle systems. We found that the initial aggregated state involved no lipid or content mixing but did produce leakage. The final state (FP) was not leaky. Lipid mixing normally dominated the first intermediate state (I(1)), but content mixing signal was also observed in this state for most systems. The second intermediate state (I(2)) exhibited both lipid and content mixing signals and leakage, and was sometimes the only leaky state. In some systems, the first and second intermediates were indistinguishable and converted directly to the FP state. Having also tested a parallel, two-intermediate model subject to different assumptions about the nature of the intermediates, we conclude that a sequential, two-intermediate model is the simplest model sufficient to describe PEG-mediated fusion in all vesicle systems studied. We conclude as well that a fusion intermediate "state" should not be thought of as a fixed structure (e.g., "stalk" or "transmembrane contact") of uniform properties. Rather, a fusion "state" describes an ensemble of similar structures that can have different mechanical properties. Thus, a "state" can have varying probabilities of having a given functional property such as content mixing, lipid mixing, or leakage. Our data show that the content mixing signal may occur through two processes, one correlated and one not correlated with leakage. Finally, we consider the implications of our results in terms of the "modified stalk" hypothesis for the mechanism of lipid pore formation. We conclude that our results not only support this hypothesis but

  5. Distributed data access in the sequential access model at the D0 experiment at Fermilab

    International Nuclear Information System (INIS)

    Terekhov, Igor; White, Victoria

    2000-01-01

    The authors present the Sequential Access Model (SAM), which is the data handling system for D0, one of two primary High Energy Experiments at Fermilab. During the next several years, the D0 experiment will store a total of about 1 PByte of data, including raw detector data and data processed at various levels. The design of SAM is not specific to the D0 experiment and carries few assumptions about the underlying mass storage level; its ideas are applicable to any sequential data access. By definition, in the sequential access mode a user application needs to process a stream of data, by accessing each data unit exactly once, the order of data units in the stream being irrelevant. The units of data are laid out sequentially in files. The adopted model allows for significant optimizations of system performance, decrease of user file latency and increase of overall throughput. In particular, caching is done with the knowledge of all the files needed in the near future, defined as all the files of the already running or submitted jobs. The bulk of the data is stored in files on tape in the mass storage system (MSS) called Enstore[2] and also developed at Fermilab. (The tape drives are served by an ADIC AML/2 Automated Tape Library). At any given time, SAM has a small fraction of the data cached on disk for processing. In the present paper, the authors discuss how data is delivered onto disk and how it is accessed by user applications. They will concentrate on data retrieval (consumption) from the MSS; when SAM is used for storing of data, the mechanisms are rather symmetrical. All of the data managed by SAM is cataloged in great detail in a relational database (ORACLE). The database also serves as the persistency mechanism for the SAM servers described in this paper. Any client or server in the SAM system which needs to store or retrieve information from the database does so through the interfaces of a CORBA-based database server. The users (physicists) use the

  6. SPRINT: A Tool to Generate Concurrent Transaction-Level Models from Sequential Code

    Directory of Open Access Journals (Sweden)

    Richard Stahl

    2007-01-01

    Full Text Available A high-level concurrent model such as a SystemC transaction-level model can provide early feedback during the exploration of implementation alternatives for state-of-the-art signal processing applications like video codecs on a multiprocessor platform. However, the creation of such a model starting from sequential code is a time-consuming and error-prone task. It is typically done only once, if at all, for a given design. This lack of exploration of the design space often leads to a suboptimal implementation. To support our systematic C-based design flow, we have developed a tool to generate a concurrent SystemC transaction-level model for user-selected task boundaries. Using this tool, different parallelization alternatives have been evaluated during the design of an MPEG-4 simple profile encoder and an embedded zero-tree coder. Generation plus evaluation of an alternative was possible in less than six minutes. This is fast enough to allow extensive exploration of the design space.

  7. Patient specific dynamic geometric models from sequential volumetric time series image data.

    Science.gov (United States)

    Cameron, B M; Robb, R A

    2004-01-01

    Generating patient specific dynamic models is complicated by the complexity of the motion intrinsic and extrinsic to the anatomic structures being modeled. Using a physics-based sequentially deforming algorithm, an anatomically accurate dynamic four-dimensional model can be created from a sequence of 3-D volumetric time series data sets. While such algorithms may accurately track the cyclic non-linear motion of the heart, they generally fail to accurately track extrinsic structural and non-cyclic motion. To accurately model these motions, we have modified a physics-based deformation algorithm to use a meta-surface defining the temporal and spatial maxima of the anatomic structure as the base reference surface. A mass-spring physics-based deformable model, which can expand or shrink with the local intrinsic motion, is applied to the metasurface, deforming this base reference surface to the volumetric data at each time point. As the meta-surface encompasses the temporal maxima of the structure, any extrinsic motion is inherently encoded into the base reference surface and allows the computation of the time point surfaces to be performed in parallel. The resultant 4-D model can be interactively transformed and viewed from different angles, showing the spatial and temporal motion of the anatomic structure. Using texture maps and per-vertex coloring, additional data such as physiological and/or biomechanical variables (e.g., mapping electrical activation sequences onto contracting myocardial surfaces) can be associated with the dynamic model, producing a 5-D model. For acquisition systems that may capture only limited time series data (e.g., only images at end-diastole/end-systole or inhalation/exhalation), this algorithm can provide useful interpolated surfaces between the time points. Such models help minimize the number of time points required to usefully depict the motion of anatomic structures for quantitative assessment of regional dynamics.

  8. Assessing sequential data assimilation techniques for integrating GRACE data into a hydrological model

    KAUST Repository

    Khaki, M.

    2017-07-06

    The time-variable terrestrial water storage (TWS) products from the Gravity Recovery And Climate Experiment (GRACE) have been increasingly used in recent years to improve the simulation of hydrological models by applying data assimilation techniques. In this study, for the first time, we assess the performance of the most popular data assimilation sequential techniques for integrating GRACE TWS into the World-Wide Water Resources Assessment (W3RA) model. We implement and test stochastic and deterministic ensemble-based Kalman filters (EnKF), as well as Particle filters (PF) using two different resampling approaches of Multinomial Resampling and Systematic Resampling. These choices provide various opportunities for weighting observations and model simulations during the assimilation and also accounting for error distributions. Particularly, the deterministic EnKF is tested to avoid perturbing observations before assimilation (that is the case in an ordinary EnKF). Gaussian-based random updates in the EnKF approaches likely do not fully represent the statistical properties of the model simulations and TWS observations. Therefore, the fully non-Gaussian PF is also applied to estimate more realistic updates. Monthly GRACE TWS are assimilated into W3RA covering the entire Australia. To evaluate the filters performances and analyze their impact on model simulations, their estimates are validated by independent in-situ measurements. Our results indicate that all implemented filters improve the estimation of water storage simulations of W3RA. The best results are obtained using two versions of deterministic EnKF, i.e. the Square Root Analysis (SQRA) scheme and the Ensemble Square Root Filter (EnSRF), respectively improving the model groundwater estimations errors by 34% and 31% compared to a model run without assimilation. Applying the PF along with Systematic Resampling successfully decreases the model estimation error by 23%.

  9. Development of a sequential injection-square wave voltammetry method for determination of paraquat in water samples employing the hanging mercury drop electrode.

    Science.gov (United States)

    dos Santos, Luciana B O; Infante, Carlos M C; Masini, Jorge C

    2010-03-01

    This work describes the development and optimization of a sequential injection method to automate the determination of paraquat by square-wave voltammetry employing a hanging mercury drop electrode. Automation by sequential injection enhanced the sampling throughput, improving the sensitivity and precision of the measurements as a consequence of the highly reproducible and efficient conditions of mass transport of the analyte toward the electrode surface. For instance, 212 analyses can be made per hour if the sample/standard solution is prepared off-line and the sequential injection system is used just to inject the solution towards the flow cell. In-line sample conditioning reduces the sampling frequency to 44 h(-1). Experiments were performed in 0.10 M NaCl, which was the carrier solution, using a frequency of 200 Hz, a pulse height of 25 mV, a potential step of 2 mV, and a flow rate of 100 µL s(-1). For a concentration range between 0.010 and 0.25 mg L(-1), the current (i(p), µA) read at the potential corresponding to the peak maximum fitted the following linear equation with the paraquat concentration (mg L(-1)): i(p) = (-20.5 ± 0.3)C (paraquat) - (0.02 ± 0.03). The limits of detection and quantification were 2.0 and 7.0 µg L(-1), respectively. The accuracy of the method was evaluated by recovery studies using spiked water samples that were also analyzed by molecular absorption spectrophotometry after reduction of paraquat with sodium dithionite in an alkaline medium. No evidence of statistically significant differences between the two methods was observed at the 95% confidence level.

  10. Sequential assimilation of multi-mission dynamical topography into a global finite-element ocean model

    Directory of Open Access Journals (Sweden)

    S. Skachko

    2008-12-01

    Full Text Available This study focuses on an accurate estimation of ocean circulation via assimilation of satellite measurements of ocean dynamical topography into the global finite-element ocean model (FEOM. The dynamical topography data are derived from a complex analysis of multi-mission altimetry data combined with a referenced earth geoid. The assimilation is split into two parts. First, the mean dynamic topography is adjusted. To this end an adiabatic pressure correction method is used which reduces model divergence from the real evolution. Second, a sequential assimilation technique is applied to improve the representation of thermodynamical processes by assimilating the time varying dynamic topography. A method is used according to which the temperature and salinity are updated following the vertical structure of the first baroclinic mode. It is shown that the method leads to a partially successful assimilation approach reducing the rms difference between the model and data from 16 cm to 2 cm. This improvement of the mean state is accompanied by significant improvement of temporal variability in our analysis. However, it remains suboptimal, showing a tendency in the forecast phase of returning toward a free run without data assimilation. Both the mean difference and standard deviation of the difference between the forecast and observation data are reduced as the result of assimilation.

  11. Prospectivity Modeling of Karstic Groundwater Using a Sequential Exploration Approach in Tepal Area, Iran

    Science.gov (United States)

    Sharifi, Fereydoun; Arab-Amiri, Ali Reza; Kamkar-Rouhani, Abolghasem; Yousefi, Mahyar; Davoodabadi-Farahani, Meysam

    2017-09-01

    The purpose of this study is water prospectivity modeling (WPM) for recognizing karstic water-bearing zones by using analyses of geo-exploration data in Kal-Qorno valley, located in Tepal area, north of Iran. For this, a sequential exploration method applied on geo-evidential data to delineate target areas for further exploration. In this regard, two major exploration phases including regional and local scales were performed. In the first phase, indicator geological features, structures and lithological units, were used to model groundwater prospectivity as a regional scale. In this phase, for karstic WPM, fuzzy lithological and structural evidence layers were generated and combined using fuzzy operators. After generating target areas using WPM, in the second phase geophysical surveys including gravimetry and geoelectrical resistivity were carried out on the recognized high potential zones as a local scale exploration. Finally the results of geophysical analyses in the second phase were used to select suitable drilling locations to access and extract karstic groundwater in the study area.

  12. A sequential Monte Carlo model of the combined GB gas and electricity network

    International Nuclear Information System (INIS)

    Chaudry, Modassar; Wu, Jianzhong; Jenkins, Nick

    2013-01-01

    A Monte Carlo model of the combined GB gas and electricity network was developed to determine the reliability of the energy infrastructure. The model integrates the gas and electricity network into a single sequential Monte Carlo simulation. The model minimises the combined costs of the gas and electricity network, these include gas supplies, gas storage operation and electricity generation. The Monte Carlo model calculates reliability indices such as loss of load probability and expected energy unserved for the combined gas and electricity network. The intention of this tool is to facilitate reliability analysis of integrated energy systems. Applications of this tool are demonstrated through a case study that quantifies the impact on the reliability of the GB gas and electricity network given uncertainties such as wind variability, gas supply availability and outages to energy infrastructure assets. Analysis is performed over a typical midwinter week on a hypothesised GB gas and electricity network in 2020 that meets European renewable energy targets. The efficacy of doubling GB gas storage capacity on the reliability of the energy system is assessed. The results highlight the value of greater gas storage facilities in enhancing the reliability of the GB energy system given various energy uncertainties. -- Highlights: •A Monte Carlo model of the combined GB gas and electricity network was developed. •Reliability indices are calculated for the combined GB gas and electricity system. •The efficacy of doubling GB gas storage capacity on reliability of the energy system is assessed. •Integrated reliability indices could be used to assess the impact of investment in energy assets

  13. A discrete event modelling framework for simulation of long-term outcomes of sequential treatment strategies for ankylosing spondylitis.

    Science.gov (United States)

    Tran-Duy, An; Boonen, Annelies; van de Laar, Mart A F J; Franke, Angelinus C; Severens, Johan L

    2011-12-01

    To develop a modelling framework which can simulate long-term quality of life, societal costs and cost-effectiveness as affected by sequential drug treatment strategies for ankylosing spondylitis (AS). Discrete event simulation paradigm was selected for model development. Drug efficacy was modelled as changes in disease activity (Bath Ankylosing Spondylitis Disease Activity Index (BASDAI)) and functional status (Bath Ankylosing Spondylitis Functional Index (BASFI)), which were linked to costs and health utility using statistical models fitted based on an observational AS cohort. Published clinical data were used to estimate drug efficacy and time to events. Two strategies were compared: (1) five available non-steroidal anti-inflammatory drugs (strategy 1) and (2) same as strategy 1 plus two tumour necrosis factor α inhibitors (strategy 2). 13,000 patients were followed up individually until death. For probability sensitivity analysis, Monte Carlo simulations were performed with 1000 sets of parameters sampled from the appropriate probability distributions. The models successfully generated valid data on treatments, BASDAI, BASFI, utility, quality-adjusted life years (QALYs) and costs at time points with intervals of 1-3 months during the simulation length of 70 years. Incremental cost per QALY gained in strategy 2 compared with strategy 1 was €35,186. At a willingness-to-pay threshold of €80,000, it was 99.9% certain that strategy 2 was cost-effective. The modelling framework provides great flexibility to implement complex algorithms representing treatment selection, disease progression and changes in costs and utilities over time of patients with AS. Results obtained from the simulation are plausible.

  14. Random sequential adsorption of cubes

    Science.gov (United States)

    Cieśla, Michał; Kubala, Piotr

    2018-01-01

    Random packings built of cubes are studied numerically using a random sequential adsorption algorithm. To compare the obtained results with previous reports, three different models of cube orientation sampling were used. Also, three different cube-cube intersection algorithms were tested to find the most efficient one. The study focuses on the mean saturated packing fraction as well as kinetics of packing growth. Microstructural properties of packings were analyzed using density autocorrelation function.

  15. In vivo comparison of simultaneous versus sequential injection technique for thermochemical ablation in a porcine model.

    Science.gov (United States)

    Cressman, Erik N K; Shenoi, Mithun M; Edelman, Theresa L; Geeslin, Matthew G; Hennings, Leah J; Zhang, Yan; Iaizzo, Paul A; Bischof, John C

    2012-01-01

    To investigate simultaneous and sequential injection thermochemical ablation in a porcine model, and compare them to sham and acid-only ablation. This IACUC-approved study involved 11 pigs in an acute setting. Ultrasound was used to guide placement of a thermocouple probe and coaxial device designed for thermochemical ablation. Solutions of 10 M acetic acid and NaOH were used in the study. Four injections per pig were performed in identical order at a total rate of 4 mL/min: saline sham, simultaneous, sequential, and acid only. Volume and sphericity of zones of coagulation were measured. Fixed specimens were examined by H&E stain. Average coagulation volumes were 11.2 mL (simultaneous), 19.0 mL (sequential) and 4.4 mL (acid). The highest temperature, 81.3°C, was obtained with simultaneous injection. Average temperatures were 61.1°C (simultaneous), 47.7°C (sequential) and 39.5°C (acid only). Sphericity coefficients (0.83-0.89) had no statistically significant difference among conditions. Thermochemical ablation produced substantial volumes of coagulated tissues relative to the amounts of reagents injected, considerably greater than acid alone in either technique employed. The largest volumes were obtained with sequential injection, yet this came at a price in one case of cardiac arrest. Simultaneous injection yielded the highest recorded temperatures and may be tolerated as well as or better than acid injection alone. Although this pilot study did not show a clear advantage for either sequential or simultaneous methods, the results indicate that thermochemical ablation is attractive for further investigation with regard to both safety and efficacy.

  16. Fast sequential multi-element determination of major and minor elements in environmental samples and drinking waters by high-resolution continuum source flame atomic absorption spectrometry.

    Science.gov (United States)

    Gómez-Nieto, Beatriz; Gismera, Ma Jesús; Sevilla, Ma Teresa; Procopio, Jesús R

    2015-01-07

    The fast sequential multi-element determination of 11 elements present at different concentration levels in environmental samples and drinking waters has been investigated using high-resolution continuum source flame atomic absorption spectrometry. The main lines for Cu (324.754 nm), Zn (213.857 nm), Cd (228.802 nm), Ni (232.003 nm) and Pb (217.001 nm), main and secondary absorption lines for Mn (279.482 and 279.827 nm), Fe (248.327, 248.514 and 302.064 nm) and Ca (422.673 and 239.856 nm), secondary lines with different sensitivities for Na (589.592 and 330.237 nm) and K (769.897 and 404.414 nm) and a secondary line for Mg (202.582 nm) have been chosen to perform the analysis. A flow injection system has been used for sample introduction so sample consumption has been reduced up to less than 1 mL per element, measured in triplicate. Furthermore, the use of multiplets for Fe and the side pixel registration approach for Mg have been studied in order to reduce sensitivity and extend the linear working range. The figures of merit have been calculated and the proposed method was applied to determine these elements in a pine needles reference material (SRM 1575a), drinking and natural waters and soil extracts. Recoveries of analytes added at different concentration levels to water samples and extracts of soils were within 88-115% interval. In this way, the fast sequential multi-element determination of major and minor elements can be carried out, in triplicate, with successful results without requiring additional dilutions of samples or several different strategies for sample preparation using about 8-9 mL of sample. Copyright © 2014 Elsevier B.V. All rights reserved.

  17. Rapid and simultaneous determination of neptunium and plutonium isotopes in environmental samples by extraction chromatography using sequential injection analysis and ICP-MS

    DEFF Research Database (Denmark)

    Qiao, Jixin; Hou, Xiaolin; Roos, Per

    2010-01-01

    plutonium and neptunium in three reference materials were in agreement with the recommended or literature values at the 0.05 significance level. The developed method is suitable for the analysis of up to 10 g of soil and 20 g of seaweed samples. The extraction chromatographic separation within the SI system......This paper reports an automated analytical method for rapid and simultaneous determination of plutonium isotopes (239Pu and 240Pu) and neptunium (237Np) in environmental samples. An extraction chromatographic column packed with TrisKem TEVA® resin was incorporated in a sequential injection (SI...... for a single sample takes less than 1.5 h. As compared to batchwise procedures, the developed method significantly improves the analysis efficiency, reduces the labor intensity and expedites the simultaneous determination of plutonium and neptunium as demanded in emergency actions....

  18. Sequential and joint hydrogeophysical inversion using a field-scale groundwater model with ERT and TDEM data

    DEFF Research Database (Denmark)

    Herckenrath, Daan; Fiandaca, G.; Auken, Esben

    2013-01-01

    hydrogeophysical inversion approaches to inform a field-scale groundwater model with time domain electromagnetic (TDEM) and electrical resistivity tomography (ERT) data. In a sequential hydrogeophysical inversion (SHI) a groundwater model is calibrated with geophysical data by coupling groundwater model parameters...... with the inverted geophysical models. We subsequently compare the SHI with a joint hydrogeophysical inversion (JHI). In the JHI, a geophysical model is simultaneously inverted with a groundwater model by coupling the groundwater and geophysical parameters to explicitly account for an established petrophysical...

  19. Sequential and joint hydrogeophysical inversion using a field-scale groundwater model with ERT and TDEM data

    DEFF Research Database (Denmark)

    Herckenrath, Daan; Fiandaca, G.; Auken, Esben

    2013-01-01

    with the inverted geophysical models. We subsequently compare the SHI with a joint hydrogeophysical inversion (JHI). In the JHI, a geophysical model is simultaneously inverted with a groundwater model by coupling the groundwater and geophysical parameters to explicitly account for an established petrophysical...... hydrogeophysical inversion approaches to inform a field-scale groundwater model with time domain electromagnetic (TDEM) and electrical resistivity tomography (ERT) data. In a sequential hydrogeophysical inversion (SHI) a groundwater model is calibrated with geophysical data by coupling groundwater model parameters...

  20. Normative personality trait development in adulthood: A 6-year cohort-sequential growth model.

    Science.gov (United States)

    Milojev, Petar; Sibley, Chris G

    2017-03-01

    The present study investigated patterns of normative change in personality traits across the adult life span (19 through 74 years of age). We examined change in extraversion, agreeableness, conscientiousness, neuroticism, openness to experience and honesty-humility using data from the first 6 annual waves of the New Zealand Attitudes and Values Study (N = 10,416; 61.1% female, average age = 49.46). We present a cohort-sequential latent growth model assessing patterns of mean-level change due to both aging and cohort effects. Extraversion decreased as people aged, with the most pronounced declines occurring in young adulthood, and then again in old age. Agreeableness, indexed with a measure focusing on empathy, decreased in young adulthood and remained relatively unchanged thereafter. Conscientiousness increased among young adults then leveled off and remained fairly consistent for the rest of the adult life span. Neuroticism and openness to experience decreased as people aged. However, the models suggest that these latter effects may also be partially due to cohort differences, as older people showed lower levels of neuroticism and openness to experience more generally. Honesty-humility showed a pronounced and consistent increase across the adult life span. These analyses of large-scale longitudinal national probability panel data indicate that different dimensions of personality follow distinct developmental processes throughout adulthood. Our findings also highlight the importance of young adulthood (up to about the age of 30) in personality trait development, as well as continuing change throughout the adult life span. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  1. Rapid Determination of Plutonium Isotopes in Environmental Samples Using Sequential Injection Extraction Chromatography and Detection by Inductively Coupled Plasma Mass Spectrometry

    DEFF Research Database (Denmark)

    Qiao, Jixin; Hou, Xiaolin; Roos, Per

    2009-01-01

    This article presents an automated method for the rapid determination of 239Pu and 240Pu in various environmental samples. The analytical method involves the in-line separation of Pu isotopes using extraction chromatography (TEVA) implemented in a sequential injection (SI) network followed...... by detection of isolated analytes with inductively coupled plasma mass spectrometry (ICP-MS). The method has been devised for the determination of Pu isotopes at environmentally relevant concentrations, whereby it has been successfully applied to the analyses of large volumes/amounts of samples, for example......, 100−200 g of soil and sediment, 20 g of seaweed, and 200 L of seawater following analyte preconcentration. The investigation of the separation capability of the assembled SI system revealed that up to 200 g of soil or sediment can be treated using a column containing about 0.70 g of TEVA resin...

  2. A comparison of sequential and information-based methods for determining the co-integration rank in heteroskedastic VAR MODELS

    DEFF Research Database (Denmark)

    Cavaliere, Giuseppe; Angelis, Luca De; Rahbek, Anders

    2015-01-01

    In this article, we investigate the behaviour of a number of methods for estimating the co-integration rank in VAR systems characterized by heteroskedastic innovation processes. In particular, we compare the efficacy of the most widely used information criteria, such as Akaike Information Criterion....... The relative finite-sample properties of the different methods are investigated by means of a Monte Carlo simulation study. For the simulation DGPs considered in the analysis, we find that the BIC-based procedure and the bootstrap sequential test procedure deliver the best overall performance in terms......-based method to over-estimate the co-integration rank in relatively small sample sizes....

  3. Work–Family Conflict and Mental Health Among Female Employees: A Sequential Mediation Model via Negative Affect and Perceived Stress

    OpenAIRE

    Shiyi Zhou; Shu Da; Heng Guo; Xichao Zhang

    2018-01-01

    After the implementation of the universal two-child policy in 2016, more and more working women have found themselves caught in the dilemma of whether to raise a baby or be promoted, which exacerbates work–family conflicts among Chinese women. Few studies have examined the mediating effect of negative affect. The present study combined the conservation of resources model and affective events theory to examine the sequential mediating effect of negative affect and perceived stress in the relat...

  4. Development and application of an on-line sequential injection system for the separation of artificial and natural radionuclides in environmental samples

    International Nuclear Information System (INIS)

    Kim, C.-K.; Sansone, U.; Martin, P.; Kim, C.-S.

    2007-02-01

    The Chemistry Unit of the Physics, Chemistry and Instrumentation Laboratory in the IAEA's Seibersdorf Laboratory in Austria, has the programmatic responsibility to provide assistance to Member State laboratories in maintaining and improving the reliability of analytical measurement results, both in trace element and radionuclide determinations. This is accomplished through the provision of reference materials of terrestrial origin, validated analytical procedures, training in the implementation of internal quality control, and through the evaluation of measurement performance by organization of worldwide and regional interlaboratory comparison exercises. In this framework an on-line sequential injection (SI) system was developed, which can be widely used for the separation and preconcentration of target analytes from diverse environmental samples. The system enables the separation time to be shortened by maintaining a constant flow rate of solution and by avoiding clogging or bubbling in a chromatographic column. The SI system was successfully applied to the separation of Pu in IAEA reference material (IAEA Soil-6) and to the sequential separation of 210 Po and 210 Pb in phosphogypsum candidate reference material. The replicate analysis results of Pu in IAEA reference material (Soil-6) obtained with the SI system are in good agreement with the recommended value within 5% of standard deviation. The SI system enabled a halving in the separation time required for of radionuclides

  5. A Procedure for the Sequential Determination of Radionuclides in Environmental Samples. Liquid Scintillation Counting and Alpha Spectrometry for 90Sr, 241Am and Pu Radioisotopes

    International Nuclear Information System (INIS)

    2014-01-01

    Since 2004, IAEA activities related to the terrestrial environment have aimed at the development of a set of procedures to determine radionuclides in environmental samples. Reliable, comparable and ‘fit for purpose’ results are an essential requirement for any decision based on analytical measurements. For the analyst, tested and validated analytical procedures are extremely important tools for the production of analytical data. For maximum utility, such procedures should be comprehensive, clearly formulated and readily available for reference to both the analyst and the customer. This publication describes a combined procedure for the sequential determination of 90 Sr, 241 Am and Pu radioisotopes in environmental samples. The method is based on the chemical separation of strontium, americium and plutonium using ion exchange chromatography, extraction chromatography and precipitation followed by alpha spectrometric and liquid scintillation counting detection. The method was tested and validated in terms of repeatability and trueness in accordance with International Organization for Standardization (ISO) guidelines using reference materials and proficiency test samples. Reproducibility tests were performed later at the IAEA Terrestrial Environment Laboratory. The calculations of the massic activity, uncertainty budget, decision threshold and detection limit are also described in this publication. The procedure is introduced for the determination of 90 Sr, 241 Am and Pu radioisotopes in environmental samples such as soil, sediment, air filter and vegetation samples. It is expected to be of general use to a wide range of laboratories, including the Analytical Laboratories for the Measurement of Environmental Radioactivity (ALMERA) network for routine environmental monitoring purposes

  6. Sample sizes and model comparison metrics for species distribution models

    Science.gov (United States)

    B.B. Hanberry; H.S. He; D.C. Dey

    2012-01-01

    Species distribution models use small samples to produce continuous distribution maps. The question of how small a sample can be to produce an accurate model generally has been answered based on comparisons to maximum sample sizes of 200 observations or fewer. In addition, model comparisons often are made with the kappa statistic, which has become controversial....

  7. Multistrain models predict sequential multidrug treatment strategies to result in less antimicrobial resistance than combination treatment

    DEFF Research Database (Denmark)

    Ahmad, Amais; Zachariasen, Camilla; Christiansen, Lasse Engbo

    2016-01-01

    Background: Combination treatment is increasingly used to fight infections caused by bacteria resistant to two or more antimicrobials. While multiple studies have evaluated treatment strategies to minimize the emergence of resistant strains for single antimicrobial treatment, fewer studies have...... the sensitive fraction of the commensal flora.Growth parameters for competing bacterial strains were estimated from the combined in vitro pharmacodynamic effect of two antimicrobials using the relationship between concentration and net bacterial growth rate. Predictions of in vivo bacterial growth were...... (how frequently antibiotics are alternated in a sequential treatment) of the two drugs was dependent upon the order in which the two drugs were used.Conclusion: Sequential treatment was more effective in preventing the growth of resistant strains when compared to the combination treatment. The cycling...

  8. Optimizing trial design in pharmacogenetics research: comparing a fixed parallel group, group sequential, and adaptive selection design on sample size requirements.

    Science.gov (United States)

    Boessen, Ruud; van der Baan, Frederieke; Groenwold, Rolf; Egberts, Antoine; Klungel, Olaf; Grobbee, Diederick; Knol, Mirjam; Roes, Kit

    2013-01-01

    Two-stage clinical trial designs may be efficient in pharmacogenetics research when there is some but inconclusive evidence of effect modification by a genomic marker. Two-stage designs allow to stop early for efficacy or futility and can offer the additional opportunity to enrich the study population to a specific patient subgroup after an interim analysis. This study compared sample size requirements for fixed parallel group, group sequential, and adaptive selection designs with equal overall power and control of the family-wise type I error rate. The designs were evaluated across scenarios that defined the effect sizes in the marker positive and marker negative subgroups and the prevalence of marker positive patients in the overall study population. Effect sizes were chosen to reflect realistic planning scenarios, where at least some effect is present in the marker negative subgroup. In addition, scenarios were considered in which the assumed 'true' subgroup effects (i.e., the postulated effects) differed from those hypothesized at the planning stage. As expected, both two-stage designs generally required fewer patients than a fixed parallel group design, and the advantage increased as the difference between subgroups increased. The adaptive selection design added little further reduction in sample size, as compared with the group sequential design, when the postulated effect sizes were equal to those hypothesized at the planning stage. However, when the postulated effects deviated strongly in favor of enrichment, the comparative advantage of the adaptive selection design increased, which precisely reflects the adaptive nature of the design. Copyright © 2013 John Wiley & Sons, Ltd.

  9. Sampling, Probability Models and Statistical Reasoning Statistical

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 1; Issue 5. Sampling, Probability Models and Statistical Reasoning Statistical Inference. Mohan Delampady V R Padmawar. General Article Volume 1 Issue 5 May 1996 pp 49-58 ...

  10. A meta-analysis of response-time tests of the sequential two-systems model of moral judgment.

    Science.gov (United States)

    Baron, Jonathan; Gürçay, Burcu

    2017-05-01

    The (generalized) sequential two-system ("default interventionist") model of utilitarian moral judgment predicts that utilitarian responses often arise from a system-two correction of system-one deontological intuitions. Response-time (RT) results that seem to support this model are usually explained by the fact that low-probability responses have longer RTs. Following earlier results, we predicted response probability from each subject's tendency to make utilitarian responses (A, "Ability") and each dilemma's tendency to elicit deontological responses (D, "Difficulty"), estimated from a Rasch model. At the point where A = D, the two responses are equally likely, so probability effects cannot account for any RT differences between them. The sequential two-system model still predicts that many of the utilitarian responses made at this point will result from system-two corrections of system-one intuitions, hence should take longer. However, when A = D, RT for the two responses was the same, contradicting the sequential model. Here we report a meta-analysis of 26 data sets, which replicated the earlier results of no RT difference overall at the point where A = D. The data sets used three different kinds of moral judgment items, and the RT equality at the point where A = D held for all three. In addition, we found that RT increased with A-D. This result holds for subjects (characterized by Ability) but not for items (characterized by Difficulty). We explain the main features of this unanticipated effect, and of the main results, with a drift-diffusion model.

  11. Mobility of arsenic, cadmium and zinc in a multi-element contaminated soil profile assessed by in-situ soil pore water sampling, column leaching and sequential extraction

    International Nuclear Information System (INIS)

    Beesley, Luke; Moreno-Jimenez, Eduardo; Clemente, Rafael; Lepp, Nicholas; Dickinson, Nicholas

    2010-01-01

    Three methods for predicting element mobility in soils have been applied to an iron-rich soil, contaminated with arsenic, cadmium and zinc. Soils were collected from 0 to 30 cm, 30 to 70 cm and 70 to 100 cm depths in the field and soil pore water was collected at different depths from an adjacent 100 cm deep trench. Sequential extraction and a column leaching test in the laboratory were compared to element concentrations in pore water sampled directly from the field. Arsenic showed low extractability, low leachability and occurred at low concentrations in pore water samples. Cadmium and zinc were more labile and present in higher concentrations in pore water, increasing with soil depth. Pore water sampling gave the best indication of short term element mobility when field conditions were taken into account, but further extraction and leaching procedures produced a fuller picture of element dynamics, revealing highly labile Cd deep in the soil profile. - Mobility of arsenic, cadmium and zinc in a polluted soil can be realistically interpreted by in-situ soil pore water sampling.

  12. Sequential determination of nickel and cadmium in tobacco, molasses and refill solutions for e-cigarettes samples by molecular fluorescence.

    Science.gov (United States)

    Talio, María Carolina; Alesso, Magdalena; Acosta, Mariano; Wills, Verónica S; Fernández, Liliana P

    2017-11-01

    In this work, a new procedure was developed for separation and preconcentration of nickel(II) and cadmium(II) in several and varied tobacco samples. Tobacco samples were selected considering the main products consumed by segments of the population, in particular the age (youth) and lifestyle of the consumer. To guarantee representative samples, a randomized strategy of sampling was used. In the first step, a chemofiltration on nylon membrane is carried out employing eosin (Eo) and carbon nanotubes dispersed in sodium dodecylsulfate (SDS) solution (phosphate buffer pH 7). In this condition, Ni(II) was selectively retained on the solid support. After that, the filtrate liquid with Cd(II) was re-conditioned with acetic acid /acetate buffer solution (pH 5) and followed by detection. A spectrofluorimetric determination of both metals was carried out, on the solid support and the filtered aqueous solution, for Ni(II) and Cd(II), respectively. The solid surface fluorescence (SSF) determination was performed at λ em = 545nm (λ ex = 515nm) for Ni(II)-Eo complex and the fluorescence of Cd(II)-Eo was quantified in aqueous solution using λ em = 565nm (λ ex = 540nm). The calibration graphs resulted linear in a range of 0.058-29.35μgL -1 for Ni(II) and 0.124-56.20μgL -1 for Cd(II), with detection limits of 0.019 and 0.041μgL -1 (S/N = 3). The developed methodology shows good sensitivity and adequate selectivity, and it was successfully applied to the determination of trace amounts of nickel and cadmium present in tobacco samples (refill solutions for e-cigarettes, snuff used in narguille (molasses) and traditional tobacco) with satisfactory results. The new methodology was validated by ICP-MS with adequate agreement. The proposed methodology represents a novel fluorescence application to Ni(II) and Cd(II) quantification with sensitivity and accuracy similar to atomic spectroscopies, introducing for the first time the quenching effect on SSF. Copyright © 2017 Elsevier B

  13. Using a Simple Binomial Model to Assess Improvement in Predictive Capability: Sequential Bayesian Inference, Hypothesis Testing, and Power Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Sigeti, David E. [Los Alamos National Laboratory; Pelak, Robert A. [Los Alamos National Laboratory

    2012-09-11

    We present a Bayesian statistical methodology for identifying improvement in predictive simulations, including an analysis of the number of (presumably expensive) simulations that will need to be made in order to establish with a given level of confidence that an improvement has been observed. Our analysis assumes the ability to predict (or postdict) the same experiments with legacy and new simulation codes and uses a simple binomial model for the probability, {theta}, that, in an experiment chosen at random, the new code will provide a better prediction than the old. This model makes it possible to do statistical analysis with an absolute minimum of assumptions about the statistics of the quantities involved, at the price of discarding some potentially important information in the data. In particular, the analysis depends only on whether or not the new code predicts better than the old in any given experiment, and not on the magnitude of the improvement. We show how the posterior distribution for {theta} may be used, in a kind of Bayesian hypothesis testing, both to decide if an improvement has been observed and to quantify our confidence in that decision. We quantify the predictive probability that should be assigned, prior to taking any data, to the possibility of achieving a given level of confidence, as a function of sample size. We show how this predictive probability depends on the true value of {theta} and, in particular, how there will always be a region around {theta} = 1/2 where it is highly improbable that we will be able to identify an improvement in predictive capability, although the width of this region will shrink to zero as the sample size goes to infinity. We show how the posterior standard deviation may be used, as a kind of 'plan B metric' in the case that the analysis shows that {theta} is close to 1/2 and argue that such a plan B should generally be part of hypothesis testing. All the analysis presented in the paper is done with a

  14. An adaptive sampling method for variable-fidelity surrogate models using improved hierarchical kriging

    Science.gov (United States)

    Hu, Jiexiang; Zhou, Qi; Jiang, Ping; Shao, Xinyu; Xie, Tingli

    2018-01-01

    Variable-fidelity (VF) modelling methods have been widely used in complex engineering system design to mitigate the computational burden. Building a VF model generally includes two parts: design of experiments and metamodel construction. In this article, an adaptive sampling method based on improved hierarchical kriging (ASM-IHK) is proposed to refine the improved VF model. First, an improved hierarchical kriging model is developed as the metamodel, in which the low-fidelity model is varied through a polynomial response surface function to capture the characteristics of a high-fidelity model. Secondly, to reduce local approximation errors, an active learning strategy based on a sequential sampling method is introduced to make full use of the already required information on the current sampling points and to guide the sampling process of the high-fidelity model. Finally, two numerical examples and the modelling of the aerodynamic coefficient for an aircraft are provided to demonstrate the approximation capability of the proposed approach, as well as three other metamodelling methods and two sequential sampling methods. The results show that ASM-IHK provides a more accurate metamodel at the same simulation cost, which is very important in metamodel-based engineering design problems.

  15. Source Identification and Sequential Leaching of Heavy Metals in Soil Samples Collected from Selected Dump Sites in Ekiti State, Nigeria

    OpenAIRE

    , E.E. Awokunmi; , S.S. Asaolu; , O.O Ajayi; , A.O. Adebayo

    2011-01-01

    Ten heavy metals (Fe, Cu, Mn, Zn, Pb, Ni, Co, Cd, Cr and Sn) in fractioned and bulk soil samples collected from four dump sites located in AdoEkiti and Ikere -Ekiti, South western Nigeria were analysed using a modified Tessier’s procedure and acid digestion to obtain the distribution pattern of metal in this region. The metals were found to have been distributed in all phases with Fe, Cr, and Sn dominating the residual fraction (90.12 - 94.88%), Co, Ni, Cu, and Zn were found in all the extrac...

  16. EXPERIMENTS TOWARDS DETERMINING BEST TRAINING SAMPLE SIZE FOR AUTOMATED EVALUATION OF DESCRIPTIVE ANSWERS THROUGH SEQUENTIAL MINIMAL OPTIMIZATION

    Directory of Open Access Journals (Sweden)

    Sunil Kumar C

    2014-01-01

    Full Text Available With number of students growing each year there is a strong need to automate systems capable of evaluating descriptive answers. Unfortunately, there aren’t many systems capable of performing this task. In this paper, we use a machine learning tool called LightSIDE to accomplish auto evaluation and scoring of descriptive answers. Our experiments are designed to cater to our primary goal of identifying the optimum training sample size so as to get optimum auto scoring. Besides the technical overview and the experiments design, the paper also covers challenges, benefits of the system. We also discussed interdisciplinary areas for future research on this topic.

  17. Model Predictive Engine Air-Ratio Control Using Online Sequential Relevance Vector Machine

    Directory of Open Access Journals (Sweden)

    Hang-cheong Wong

    2012-01-01

    Full Text Available Engine power, brake-specific fuel consumption, and emissions relate closely to air ratio (i.e., lambda among all the engine variables. An accurate and adaptive model for lambda prediction is essential to effective lambda control for long term. This paper utilizes an emerging technique, relevance vector machine (RVM, to build a reliable time-dependent lambda model which can be continually updated whenever a sample is added to, or removed from, the estimated lambda model. The paper also presents a new model predictive control (MPC algorithm for air-ratio regulation based on RVM. This study shows that the accuracy, training, and updating time of the RVM model are superior to the latest modelling methods, such as diagonal recurrent neural network (DRNN and decremental least-squares support vector machine (DLSSVM. Moreover, the control algorithm has been implemented on a real car to test. Experimental results reveal that the control performance of the proposed relevance vector machine model predictive controller (RVMMPC is also superior to DRNNMPC, support vector machine-based MPC, and conventional proportional-integral (PI controller in production cars. Therefore, the proposed RVMMPC is a promising scheme to replace conventional PI controller for engine air-ratio control.

  18. Tissue Sampling Guides for Porcine Biomedical Models.

    Science.gov (United States)

    Albl, Barbara; Haesner, Serena; Braun-Reichhart, Christina; Streckel, Elisabeth; Renner, Simone; Seeliger, Frank; Wolf, Eckhard; Wanke, Rüdiger; Blutke, Andreas

    2016-04-01

    This article provides guidelines for organ and tissue sampling adapted to porcine animal models in translational medical research. Detailed protocols for the determination of sampling locations and numbers as well as recommendations on the orientation, size, and trimming direction of samples from ∼50 different porcine organs and tissues are provided in the Supplementary Material. The proposed sampling protocols include the generation of samples suitable for subsequent qualitative and quantitative analyses, including cryohistology, paraffin, and plastic histology; immunohistochemistry;in situhybridization; electron microscopy; and quantitative stereology as well as molecular analyses of DNA, RNA, proteins, metabolites, and electrolytes. With regard to the planned extent of sampling efforts, time, and personnel expenses, and dependent upon the scheduled analyses, different protocols are provided. These protocols are adjusted for (I) routine screenings, as used in general toxicity studies or in analyses of gene expression patterns or histopathological organ alterations, (II) advanced analyses of single organs/tissues, and (III) large-scale sampling procedures to be applied in biobank projects. Providing a robust reference for studies of porcine models, the described protocols will ensure the efficiency of sampling, the systematic recovery of high-quality samples representing the entire organ or tissue as well as the intra-/interstudy comparability and reproducibility of results. © The Author(s) 2016.

  19. Sequential Banking.

    OpenAIRE

    Bizer, David S; DeMarzo, Peter M

    1992-01-01

    The authors study environments in which agents may borrow sequentially from more than one leader. Although debt is prioritized, additional lending imposes an externality on prior debt because, with moral hazard, the probability of repayment of prior loans decreases. Equilibrium interest rates are higher than they would be if borrowers could commit to borrow from at most one bank. Even though the loan terms are less favorable than they would be under commitment, the indebtedness of borrowers i...

  20. Systems-level modeling the effects of arsenic exposure with sequential pulsed and fluctuating patterns for tilapia and freshwater clam

    International Nuclear Information System (INIS)

    Chen, W.-Y.; Tsai, J.-W.; Ju, Y.-R.; Liao, C.-M.

    2010-01-01

    The purpose of this paper was to use quantitative systems-level approach employing biotic ligand model based threshold damage model to examine physiological responses of tilapia and freshwater clam to sequential pulsed and fluctuating arsenic concentrations. We tested present model and triggering mechanisms by carrying out a series of modeling experiments where we used periodic pulses and sine-wave as featured exposures. Our results indicate that changes in the dominant frequencies and pulse timing can shift the safe rate distributions for tilapia, but not for that of freshwater clam. We found that tilapia increase bioenergetic costs to maintain the acclimation during pulsed and sine-wave exposures. Our ability to predict the consequences of physiological variation under time-varying exposure patterns has also implications for optimizing species growing, cultivation strategies, and risk assessment in realistic situations. - Systems-level modeling the pulsed and fluctuating arsenic exposures.

  1. Systems-level modeling the effects of arsenic exposure with sequential pulsed and fluctuating patterns for tilapia and freshwater clam

    Energy Technology Data Exchange (ETDEWEB)

    Chen, W.-Y. [Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei 10617, Taiwan (China); Tsai, J.-W. [Institute of Ecology and Evolutionary Ecology, China Medical University, Taichung 40402, Taiwan (China); Ju, Y.-R. [Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei 10617, Taiwan (China); Liao, C.-M., E-mail: cmliao@ntu.edu.t [Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei 10617, Taiwan (China)

    2010-05-15

    The purpose of this paper was to use quantitative systems-level approach employing biotic ligand model based threshold damage model to examine physiological responses of tilapia and freshwater clam to sequential pulsed and fluctuating arsenic concentrations. We tested present model and triggering mechanisms by carrying out a series of modeling experiments where we used periodic pulses and sine-wave as featured exposures. Our results indicate that changes in the dominant frequencies and pulse timing can shift the safe rate distributions for tilapia, but not for that of freshwater clam. We found that tilapia increase bioenergetic costs to maintain the acclimation during pulsed and sine-wave exposures. Our ability to predict the consequences of physiological variation under time-varying exposure patterns has also implications for optimizing species growing, cultivation strategies, and risk assessment in realistic situations. - Systems-level modeling the pulsed and fluctuating arsenic exposures.

  2. Rapid isolation of plutonium in environmental solid samples using sequential injection anion exchange chromatography followed by detection with inductively coupled plasma mass spectrometry

    Energy Technology Data Exchange (ETDEWEB)

    Qiao Jixin, E-mail: jixin.qiao@risoe.d [Radiation Research Division, Riso National Laboratory for Sustainable Energy, Technical University of Denmark, DK-4000 Roskilde (Denmark); Hou Xiaolin; Roos, Per [Radiation Research Division, Riso National Laboratory for Sustainable Energy, Technical University of Denmark, DK-4000 Roskilde (Denmark); Miro, Manuel [Department of Chemistry, Faculty of Sciences, University of the Balearic Islands, Carretera de Valldemossa km. 7.5, E-07122 Palma de Mallorca, Illes Balears (Spain)

    2011-01-31

    This paper reports an automated analytical method for rapid determination of plutonium isotopes ({sup 239}Pu and {sup 240}Pu) in environmental solid extracts. Anion exchange chromatographic columns were incorporated in a sequential injection (SI) system to undertake the automated separation of plutonium from matrix and interfering elements. The analytical results most distinctly demonstrated that the crosslinkage of the anion exchanger is a key parameter controlling the separation efficiency. AG 1-x4 type resin was selected as the most suitable sorbent material for analyte separation. Investigation of column size effect upon the separation efficiency revealed that small-sized (2 mL) columns sufficed to handle up to 50 g of environmental soil samples. Under the optimum conditions, chemical yields of plutonium exceeded 90% and the decontamination factors for uranium, thorium and lead ranged from 10{sup 3} to 10{sup 4}. The determination of plutonium isotopes in three standard/certified reference materials (IAEA-375 soil, IAEA-135 sediment and NIST-4359 seaweed) and two reference samples (Irish Sea sediment and Danish soil) revealed a good agreement with reference/certified values. The SI column-separation method is straightforward and less labor intensive as compared with batch-wise anion exchange chromatographic procedures. Besides, the automated method features low consumption of ion-exchanger and reagents for column washing and elution, with the consequent decrease in the generation of acidic waste, thus bearing green chemical credentials.

  3. AdOn HDP-HMM: An Adaptive Online Model for Segmentation and Classification of Sequential Data.

    Science.gov (United States)

    Bargi, Ava; Xu, Richard Yi Da; Piccardi, Massimo

    2017-09-21

    Recent years have witnessed an increasing need for the automated classification of sequential data, such as activities of daily living, social media interactions, financial series, and others. With the continuous flow of new data, it is critical to classify the observations on-the-fly and without being limited by a predetermined number of classes. In addition, a model should be able to update its parameters in response to a possible evolution in the distributions of the classes. This compelling problem, however, does not seem to have been adequately addressed in the literature, since most studies focus on offline classification over predefined class sets. In this paper, we present a principled solution for this problem based on an adaptive online system leveraging Markov switching models and hierarchical Dirichlet process priors. This adaptive online approach is capable of classifying the sequential data over an unlimited number of classes while meeting the memory and delay constraints typical of streaming contexts. In this paper, we introduce an adaptive ''learning rate'' that is responsible for balancing the extent to which the model retains its previous parameters or adapts to new observations. Experimental results on stationary and evolving synthetic data and two video data sets, TUM Assistive Kitchen and collated Weizmann, show a remarkable performance in terms of segmentation and classification, particularly for sequences from evolutionary distributions and/or those containing previously unseen classes.

  4. Tibetan Microblog Emotional Analysis Based on Sequential Model in Online Social Platforms

    Directory of Open Access Journals (Sweden)

    Lirong Qiu

    2017-01-01

    Full Text Available With the development of microblogs, selling and buying appear in online social platforms such as Sina Weibo and Wechat. Besides Mandarin, Tibetan language is also used to describe products and customers’ opinions. In this paper, we are interested in analyzing the emotions of Tibetan microblogs, which are helpful to understand opinions and product reviews for Tibetan customers. It is challenging since existing studies paid little attention to Tibetan language. Our key idea is to express Tibetan microblogs as vectors and then classify them. To express microblogs more fully, we select two kinds of features, which are sequential features and semantic features. In addition, our experimental results on the Sina Weibo dataset clearly demonstrate the effectiveness of feature selection and the efficiency of our classification method.

  5. Sampling, Probability Models and Statistical Reasoning -RE ...

    Indian Academy of Sciences (India)

    random sampling allows data to be modelled with the help of probability ... g based on different trials to get an estimate of the experimental error. ... research interests lie in the .... if e is indeed the true value of the proportion of defectives in the.

  6. Joint Data Assimilation and Parameter Calibration in on-line groundwater modelling using Sequential Monte Carlo techniques

    Science.gov (United States)

    Ramgraber, M.; Schirmer, M.

    2017-12-01

    As computational power grows and wireless sensor networks find their way into common practice, it becomes increasingly feasible to pursue on-line numerical groundwater modelling. The reconciliation of model predictions with sensor measurements often necessitates the application of Sequential Monte Carlo (SMC) techniques, most prominently represented by the Ensemble Kalman Filter. In the pursuit of on-line predictions it seems advantageous to transcend the scope of pure data assimilation and incorporate on-line parameter calibration as well. Unfortunately, the interplay between shifting model parameters and transient states is non-trivial. Several recent publications (e.g. Chopin et al., 2013, Kantas et al., 2015) in the field of statistics discuss potential algorithms addressing this issue. However, most of these are computationally intractable for on-line application. In this study, we investigate to what extent compromises between mathematical rigour and computational restrictions can be made within the framework of on-line numerical modelling of groundwater. Preliminary studies are conducted in a synthetic setting, with the goal of transferring the conclusions drawn into application in a real-world setting. To this end, a wireless sensor network has been established in the valley aquifer around Fehraltorf, characterized by a highly dynamic groundwater system and located about 20 km to the East of Zürich, Switzerland. By providing continuous probabilistic estimates of the state and parameter distribution, a steady base for branched-off predictive scenario modelling could be established, providing water authorities with advanced tools for assessing the impact of groundwater management practices. Chopin, N., Jacob, P.E. and Papaspiliopoulos, O. (2013): SMC2: an efficient algorithm for sequential analysis of state space models. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 75 (3), p. 397-426. Kantas, N., Doucet, A., Singh, S

  7. Direct methods and residue type specific isotope labeling in NMR structure determination and model-driven sequential assignment

    International Nuclear Information System (INIS)

    Schedlbauer, Andreas; Auer, Renate; Ledolter, Karin; Tollinger, Martin; Kloiber, Karin; Lichtenecker, Roman; Ruedisser, Simon; Hommel, Ulrich; Schmid, Walther; Konrat, Robert; Kontaxis, Georg

    2008-01-01

    Direct methods in NMR based structure determination start from an unassigned ensemble of unconnected gaseous hydrogen atoms. Under favorable conditions they can produce low resolution structures of proteins. Usually a prohibitively large number of NOEs is required, to solve a protein structure ab-initio, but even with a much smaller set of distance restraints low resolution models can be obtained which resemble a protein fold. One problem is that at such low resolution and in the absence of a force field it is impossible to distinguish the correct protein fold from its mirror image. In a hybrid approach these ambiguous models have the potential to aid in the process of sequential backbone chemical shift assignment when 13 C β and 13 C' shifts are not available for sensitivity reasons. Regardless of the overall fold they enhance the information content of the NOE spectra. These, combined with residue specific labeling and minimal triple-resonance data using 13 C α connectivity can provide almost complete sequential assignment. Strategies for residue type specific labeling with customized isotope labeling patterns are of great advantage in this context. Furthermore, this approach is to some extent error-tolerant with respect to data incompleteness, limited precision of the peak picking, and structural errors caused by misassignment of NOEs

  8. Modelling the sequential geographical exploitation and potential collapse of marine fisheries through economic globalization, climate change and management alternatives

    Directory of Open Access Journals (Sweden)

    Gorka Merino

    2011-07-01

    Full Text Available Global marine fisheries production has reached a maximum and may even be declining. Underlying this trend is a well-understood sequence of development, overexploitation, depletion and in some instances collapse of individual fish stocks, a pattern that can sequentially link geographically distant populations. Ineffective governance, economic considerations and climate impacts are often responsible for this sequence, although the relative contribution of each factor is contentious. In this paper we use a global bioeconomic model to explore the synergistic effects of climate variability, economic pressures and management measures in causing or avoiding this sequence. The model shows how a combination of climate-induced variability in the underlying fish population production, particular patterns of demand for fish products and inadequate management is capable of driving the world’s fisheries into development, overexploitation, collapse and recovery phases consistent with observations. Furthermore, it demonstrates how a sequential pattern of overexploitation can emerge as an endogenous property of the interaction between regional environmental fluctuations and a globalized trade system. This situation is avoidable through adaptive management measures that ensure the sustainability of regional production systems in the face of increasing global environmental change and markets. It is concluded that global management measures are needed to ensure that global food supply from marine products is optimized while protecting long-term ecosystem services across the world’s oceans.

  9. Sequential fragmentation of Pleistocene forests in an East Africa biodiversity hotspot: chameleons as a model to track forest history.

    Directory of Open Access Journals (Sweden)

    G John Measey

    Full Text Available The Eastern Arc Mountains (EAM is an example of naturally fragmented tropical forests, which contain one of the highest known concentrations of endemic plants and vertebrates. Numerous paleo-climatic studies have not provided direct evidence for ancient presence of Pleistocene forests, particularly in the regions in which savannah presently occurs. Knowledge of the last period when forests connected EAM would provide a sound basis for hypothesis testing of vicariance and dispersal models of speciation. Dated phylogenies have revealed complex patterns throughout EAM, so we investigated divergence times of forest fauna on four montane isolates in close proximity to determine whether forest break-up was most likely to have been simultaneous or sequential, using population genetics of a forest restricted arboreal chameleon, Kinyongia boehmei.We used mitochondrial and nuclear genetic sequence data and mutation rates from a fossil-calibrated phylogeny to estimate divergence times between montane isolates using a coalescent approach. We found that chameleons on all mountains are most likely to have diverged sequentially within the Pleistocene from 0.93-0.59 Ma (95% HPD 0.22-1.84 Ma. In addition, post-hoc tests on chameleons on the largest montane isolate suggest a population expansion ∼182 Ka.Sequential divergence is most likely to have occurred after the last of three wet periods within the arid Plio-Pleistocene era, but was not correlated with inter-montane distance. We speculate that forest connection persisted due to riparian corridors regardless of proximity, highlighting their importance in the region's historic dispersal events. The population expansion coincides with nearby volcanic activity, which may also explain the relative paucity of the Taita's endemic fauna. Our study shows that forest chameleons are an apposite group to track forest fragmentation, with the inference that forest extended between some EAM during the Pleistocene 1

  10. Exact sampling hardness of Ising spin models

    Science.gov (United States)

    Fefferman, B.; Foss-Feig, M.; Gorshkov, A. V.

    2017-09-01

    We study the complexity of classically sampling from the output distribution of an Ising spin model, which can be implemented naturally in a variety of atomic, molecular, and optical systems. In particular, we construct a specific example of an Ising Hamiltonian that, after time evolution starting from a trivial initial state, produces a particular output configuration with probability very nearly proportional to the square of the permanent of a matrix with arbitrary integer entries. In a similar spirit to boson sampling, the ability to sample classically from the probability distribution induced by time evolution under this Hamiltonian would imply unlikely complexity theoretic consequences, suggesting that the dynamics of such a spin model cannot be efficiently simulated with a classical computer. Physical Ising spin systems capable of achieving problem-size instances (i.e., qubit numbers) large enough so that classical sampling of the output distribution is classically difficult in practice may be achievable in the near future. Unlike boson sampling, our current results only imply hardness of exact classical sampling, leaving open the important question of whether a much stronger approximate-sampling hardness result holds in this context. The latter is most likely necessary to enable a convincing experimental demonstration of quantum supremacy. As referenced in a recent paper [A. Bouland, L. Mancinska, and X. Zhang, in Proceedings of the 31st Conference on Computational Complexity (CCC 2016), Leibniz International Proceedings in Informatics (Schloss Dagstuhl-Leibniz-Zentrum für Informatik, Dagstuhl, 2016)], our result completes the sampling hardness classification of two-qubit commuting Hamiltonians.

  11. Sequential super-stereotypy of an instinctive fixed action pattern in hyper-dopaminergic mutant mice: a model of obsessive compulsive disorder and Tourette's

    Directory of Open Access Journals (Sweden)

    Houchard Kimberly R

    2005-02-01

    Full Text Available Abstract Background Excessive sequential stereotypy of behavioral patterns (sequential super-stereotypy in Tourette's syndrome and obsessive compulsive disorder (OCD is thought to involve dysfunction in nigrostriatal dopamine systems. In sequential super-stereotypy, patients become trapped in overly rigid sequential patterns of action, language, or thought. Some instinctive behavioral patterns of animals, such as the syntactic grooming chain pattern of rodents, have sufficiently complex and stereotyped serial structure to detect potential production of overly-rigid sequential patterns. A syntactic grooming chain is a fixed action pattern that serially links up to 25 grooming movements into 4 predictable phases that follow 1 syntactic rule. New mutant mouse models allow gene-based manipulation of brain function relevant to sequential patterns, but no current animal model of spontaneous OCD-like behaviors has so far been reported to exhibit sequential super-stereotypy in the sense of a whole complex serial pattern that becomes stronger and excessively rigid. Here we used a hyper-dopaminergic mutant mouse to examine whether an OCD-like behavioral sequence in animals shows sequential super-stereotypy. Knockdown mutation of the dopamine transporter gene (DAT causes extracellular dopamine levels in the neostriatum of these adult mutant mice to rise to 170% of wild-type control levels. Results We found that the serial pattern of this instinctive behavioral sequence becomes strengthened as an entire entity in hyper-dopaminergic mutants, and more resistant to interruption. Hyper-dopaminergic mutant mice have stronger and more rigid syntactic grooming chain patterns than wild-type control mice. Mutants showed sequential super-stereotypy in the sense of having more stereotyped and predictable syntactic grooming sequences, and were also more likely to resist disruption of the pattern en route, by returning after a disruption to complete the pattern from the

  12. On sampling and modeling complex systems

    International Nuclear Information System (INIS)

    Marsili, Matteo; Mastromatteo, Iacopo; Roudi, Yasser

    2013-01-01

    The study of complex systems is limited by the fact that only a few variables are accessible for modeling and sampling, which are not necessarily the most relevant ones to explain the system behavior. In addition, empirical data typically undersample the space of possible states. We study a generic framework where a complex system is seen as a system of many interacting degrees of freedom, which are known only in part, that optimize a given function. We show that the underlying distribution with respect to the known variables has the Boltzmann form, with a temperature that depends on the number of unknown variables. In particular, when the influence of the unknown degrees of freedom on the known variables is not too irregular, the temperature decreases as the number of variables increases. This suggests that models can be predictable only when the number of relevant variables is less than a critical threshold. Concerning sampling, we argue that the information that a sample contains on the behavior of the system is quantified by the entropy of the frequency with which different states occur. This allows us to characterize the properties of maximally informative samples: within a simple approximation, the most informative frequency size distributions have power law behavior and Zipf’s law emerges at the crossover between the under sampled regime and the regime where the sample contains enough statistics to make inferences on the behavior of the system. These ideas are illustrated in some applications, showing that they can be used to identify relevant variables or to select the most informative representations of data, e.g. in data clustering. (paper)

  13. Sequential injection chromatography with post-column reaction/derivatization for the determination of transition metal cations in natural water samples.

    Science.gov (United States)

    Horstkotte, Burkhard; Jarošová, Patrícia; Chocholouš, Petr; Sklenářová, Hana; Solich, Petr

    2015-05-01

    In this work, the applicability of Sequential Injection Chromatography for the determination of transition metals in water is evaluated for the separation of copper(II), zinc(II), and iron(II) cations. Separations were performed using a Dionex IonPAC™ guard column (50mm×2mm i.d., 9 µm). Mobile phase composition and post-column reaction were optimized by modified SIMPLEX method with subsequent study of the concentration of each component. The mobile phase consisted of 2,6-pyridinedicarboxylic acid as analyte-selective compound, sodium sulfate, and formic acid/sodium formate buffer. Post-column addition of 4-(2-pyridylazo)resorcinol was carried out for spectrophotometric detection of the analytes׳ complexes at 530nm. Approaches to achieve higher robustness, baseline stability, and detection sensitivity by on-column stacking of the analytes and initial gradient implementation as well as air-cushion pressure damping for post-column reagent addition were studied. The method allowed the rapid separation of copper(II), zinc(II), and iron(II) within 6.5min including pump refilling and aspiration of sample and 1mmol HNO3 for analyte stacking on the separation column. High sensitivity was achieved applying an injection volume of up to 90µL. A signal repeatability of<2% RSD of peak height was found. Analyte recovery evaluated by spiking of different natural water samples was well suited for routine analysis with sub-micromolar limits of detection. Copyright © 2015 Elsevier B.V. All rights reserved.

  14. Media Exposure: How Models Simplify Sampling

    DEFF Research Database (Denmark)

    Mortensen, Peter Stendahl

    1998-01-01

    In media planning, the distribution of exposures to more ad spots in more media (print, TV, radio) is crucial to the evaluation of the campaign. If such information should be sampled, it would only be possible in expensive panel-studies (eg TV-meter panels). Alternatively, the distribution...... of exposures may be modelled statistically, using the Beta distribution combined with the Binomial Distribution. Examples are given....

  15. Three-dimensional classical-ensemble modeling of non-sequential double ionization

    International Nuclear Information System (INIS)

    Haan, S.L.; Breen, L.; Tannor, D.; Panfili, R.; Ho, Phay J.; Eberly, J.H.

    2005-01-01

    Full text: We have been using 1d ensembles of classical two-electron atoms to simulate helium atoms that are exposed to pulses of intense laser radiation. In this talk we discuss the challenges in setting up a 3d classical ensemble that can mimic the quantum ground state of helium. We then report studies in which each one of 500,000 two-electron trajectories is followed in 3d through a ten-cycle (25 fs) 780 nm laser pulse. We examine double-ionization yield for various intensities, finding the familiar knee structure. We consider the momentum spread of outcoming electrons in directions both parallel and perpendicular to the direction of laser polarization, and find results that are consistent with experiment. We examine individual trajectories and recollision processes that lead to double ionization, considering the best phases of the laser cycle for recollision events and looking at the possible time delay between recollision and emergence. We consider also the number of recollision events, and find that multiple recollisions are common in the classical ensemble. We investigate which collisional processes lead to various final electron momenta. We conclude with comments regarding the ability of classical mechanics to describe non-sequential double ionization, and a quick summary of similarities and differences between 1d and 3d classical double ionization using energy-trajectory comparisons. Refs. 3 (author)

  16. Robust inference in sample selection models

    KAUST Repository

    Zhelonkin, Mikhail; Genton, Marc G.; Ronchetti, Elvezio

    2015-01-01

    The problem of non-random sample selectivity often occurs in practice in many fields. The classical estimators introduced by Heckman are the backbone of the standard statistical analysis of these models. However, these estimators are very sensitive to small deviations from the distributional assumptions which are often not satisfied in practice. We develop a general framework to study the robustness properties of estimators and tests in sample selection models. We derive the influence function and the change-of-variance function of Heckman's two-stage estimator, and we demonstrate the non-robustness of this estimator and its estimated variance to small deviations from the model assumed. We propose a procedure for robustifying the estimator, prove its asymptotic normality and give its asymptotic variance. Both cases with and without an exclusion restriction are covered. This allows us to construct a simple robust alternative to the sample selection bias test. We illustrate the use of our new methodology in an analysis of ambulatory expenditures and we compare the performance of the classical and robust methods in a Monte Carlo simulation study.

  17. Robust inference in sample selection models

    KAUST Repository

    Zhelonkin, Mikhail

    2015-11-20

    The problem of non-random sample selectivity often occurs in practice in many fields. The classical estimators introduced by Heckman are the backbone of the standard statistical analysis of these models. However, these estimators are very sensitive to small deviations from the distributional assumptions which are often not satisfied in practice. We develop a general framework to study the robustness properties of estimators and tests in sample selection models. We derive the influence function and the change-of-variance function of Heckman\\'s two-stage estimator, and we demonstrate the non-robustness of this estimator and its estimated variance to small deviations from the model assumed. We propose a procedure for robustifying the estimator, prove its asymptotic normality and give its asymptotic variance. Both cases with and without an exclusion restriction are covered. This allows us to construct a simple robust alternative to the sample selection bias test. We illustrate the use of our new methodology in an analysis of ambulatory expenditures and we compare the performance of the classical and robust methods in a Monte Carlo simulation study.

  18. Optimal time points sampling in pathway modelling.

    Science.gov (United States)

    Hu, Shiyan

    2004-01-01

    Modelling cellular dynamics based on experimental data is at the heart of system biology. Considerable progress has been made to dynamic pathway modelling as well as the related parameter estimation. However, few of them gives consideration for the issue of optimal sampling time selection for parameter estimation. Time course experiments in molecular biology rarely produce large and accurate data sets and the experiments involved are usually time consuming and expensive. Therefore, to approximate parameters for models with only few available sampling data is of significant practical value. For signal transduction, the sampling intervals are usually not evenly distributed and are based on heuristics. In the paper, we investigate an approach to guide the process of selecting time points in an optimal way to minimize the variance of parameter estimates. In the method, we first formulate the problem to a nonlinear constrained optimization problem by maximum likelihood estimation. We then modify and apply a quantum-inspired evolutionary algorithm, which combines the advantages of both quantum computing and evolutionary computing, to solve the optimization problem. The new algorithm does not suffer from the morass of selecting good initial values and being stuck into local optimum as usually accompanied with the conventional numerical optimization techniques. The simulation results indicate the soundness of the new method.

  19. CHIRP-Like Signals: Estimation, Detection and Processing A Sequential Model-Based Approach

    Energy Technology Data Exchange (ETDEWEB)

    Candy, J. V. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2016-08-04

    Chirp signals have evolved primarily from radar/sonar signal processing applications specifically attempting to estimate the location of a target in surveillance/tracking volume. The chirp, which is essentially a sinusoidal signal whose phase changes instantaneously at each time sample, has an interesting property in that its correlation approximates an impulse function. It is well-known that a matched-filter detector in radar/sonar estimates the target range by cross-correlating a replicant of the transmitted chirp with the measurement data reflected from the target back to the radar/sonar receiver yielding a maximum peak corresponding to the echo time and therefore enabling the desired range estimate. In this application, we perform the same operation as a radar or sonar system, that is, we transmit a “chirp-like pulse” into the target medium and attempt to first detect its presence and second estimate its location or range. Our problem is complicated by the presence of disturbance signals from surrounding broadcast stations as well as extraneous sources of interference in our frequency bands and of course the ever present random noise from instrumentation. First, we discuss the chirp signal itself and illustrate its inherent properties and then develop a model-based processing scheme enabling both the detection and estimation of the signal from noisy measurement data.

  20. Sequential memory: Binding dynamics

    Science.gov (United States)

    Afraimovich, Valentin; Gong, Xue; Rabinovich, Mikhail

    2015-10-01

    Temporal order memories are critical for everyday animal and human functioning. Experiments and our own experience show that the binding or association of various features of an event together and the maintaining of multimodality events in sequential order are the key components of any sequential memories—episodic, semantic, working, etc. We study a robustness of binding sequential dynamics based on our previously introduced model in the form of generalized Lotka-Volterra equations. In the phase space of the model, there exists a multi-dimensional binding heteroclinic network consisting of saddle equilibrium points and heteroclinic trajectories joining them. We prove here the robustness of the binding sequential dynamics, i.e., the feasibility phenomenon for coupled heteroclinic networks: for each collection of successive heteroclinic trajectories inside the unified networks, there is an open set of initial points such that the trajectory going through each of them follows the prescribed collection staying in a small neighborhood of it. We show also that the symbolic complexity function of the system restricted to this neighborhood is a polynomial of degree L - 1, where L is the number of modalities.

  1. Multiscale sampling model for motion integration.

    Science.gov (United States)

    Sherbakov, Lena; Yazdanbakhsh, Arash

    2013-09-30

    Biologically plausible strategies for visual scene integration across spatial and temporal domains continues to be a challenging topic. The fundamental question we address is whether classical problems in motion integration, such as the aperture problem, can be solved in a model that samples the visual scene at multiple spatial and temporal scales in parallel. We hypothesize that fast interareal connections that allow feedback of information between cortical layers are the key processes that disambiguate motion direction. We developed a neural model showing how the aperture problem can be solved using different spatial sampling scales between LGN, V1 layer 4, V1 layer 6, and area MT. Our results suggest that multiscale sampling, rather than feedback explicitly, is the key process that gives rise to end-stopped cells in V1 and enables area MT to solve the aperture problem without the need for calculating intersecting constraints or crafting intricate patterns of spatiotemporal receptive fields. Furthermore, the model explains why end-stopped cells no longer emerge in the absence of V1 layer 6 activity (Bolz & Gilbert, 1986), why V1 layer 4 cells are significantly more end-stopped than V1 layer 6 cells (Pack, Livingstone, Duffy, & Born, 2003), and how it is possible to have a solution to the aperture problem in area MT with no solution in V1 in the presence of driving feedback. In summary, while much research in the field focuses on how a laminar architecture can give rise to complicated spatiotemporal receptive fields to solve problems in the motion domain, we show that one can reframe motion integration as an emergent property of multiscale sampling achieved concurrently within lamina and across multiple visual areas.

  2. Kinetic Modeling of Synthetic Wastewater Treatment by the Moving-bed Sequential Continuous-inflow Reactor (MSCR

    Directory of Open Access Journals (Sweden)

    Mohammadreza Khani

    2016-11-01

    Full Text Available It was the objective of the present study to conduct a kinetic modeling of a Moving-bed Sequential Continuous-inflow Reactor (MSCR and to develop its best prediction model. For this purpose, a MSCR consisting of an aerobic-anoxic pilot 50 l in volume and an anaerobic pilot of 20 l were prepared. The MSCR was fed a variety of organic loads and operated at different hydraulic retention times (HRT using synthetic wastewater at input COD concentrations of 300 to 1000 mg/L with HRTs of 2 to 5 h. Based on the results and the best system operation conditions, the highest COD removal (98.6% was obtained at COD=500 mg/L. The three well-known first order, second order, and Stover-Kincannon models were utilized for the kinetic modeling of the reactor. Based on the kinetic analysis of organic removal, the Stover-Kincannon model was chosen for the kinetic modeling of the moving bed biofilm. Given its advantageous properties in the statisfactory prediction of organic removal at different organic loads, this model is recommended for the design and operation of MSCR systems.

  3. Sequential Monte Carlo with Highly Informative Observations

    OpenAIRE

    Del Moral, Pierre; Murray, Lawrence M.

    2014-01-01

    We propose sequential Monte Carlo (SMC) methods for sampling the posterior distribution of state-space models under highly informative observation regimes, a situation in which standard SMC methods can perform poorly. A special case is simulating bridges between given initial and final values. The basic idea is to introduce a schedule of intermediate weighting and resampling times between observation times, which guide particles towards the final state. This can always be done for continuous-...

  4. Sequential and joint hydrogeophysical inversion using a field-scale groundwater model with ERT and TDEM data

    Directory of Open Access Journals (Sweden)

    D. Herckenrath

    2013-10-01

    Full Text Available Increasingly, ground-based and airborne geophysical data sets are used to inform groundwater models. Recent research focuses on establishing coupling relationships between geophysical and groundwater parameters. To fully exploit such information, this paper presents and compares different hydrogeophysical inversion approaches to inform a field-scale groundwater model with time domain electromagnetic (TDEM and electrical resistivity tomography (ERT data. In a sequential hydrogeophysical inversion (SHI a groundwater model is calibrated with geophysical data by coupling groundwater model parameters with the inverted geophysical models. We subsequently compare the SHI with a joint hydrogeophysical inversion (JHI. In the JHI, a geophysical model is simultaneously inverted with a groundwater model by coupling the groundwater and geophysical parameters to explicitly account for an established petrophysical relationship and its accuracy. Simulations for a synthetic groundwater model and TDEM data showed improved estimates for groundwater model parameters that were coupled to relatively well-resolved geophysical parameters when employing a high-quality petrophysical relationship. Compared to a SHI these improvements were insignificant and geophysical parameter estimates became slightly worse. When employing a low-quality petrophysical relationship, groundwater model parameters improved less for both the SHI and JHI, where the SHI performed relatively better. When comparing a SHI and JHI for a real-world groundwater model and ERT data, differences in parameter estimates were small. For both cases investigated in this paper, the SHI seems favorable, taking into account parameter error, data fit and the complexity of implementing a JHI in combination with its larger computational burden.

  5. Sequential change in T2* values of cartilage, meniscus, and subchondral bone marrow in a rat model of knee osteoarthritis.

    Directory of Open Access Journals (Sweden)

    Ping-Huei Tsai

    Full Text Available BACKGROUND: There is an emerging interest in using magnetic resonance imaging (MRI T2* measurement for the evaluation of degenerative cartilage in osteoarthritis (OA. However, relatively few studies have addressed OA-related changes in adjacent knee structures. This study used MRI T2* measurement to investigate sequential changes in knee cartilage, meniscus, and subchondral bone marrow in a rat OA model induced by anterior cruciate ligament transection (ACLX. MATERIALS AND METHODS: Eighteen male Sprague Dawley rats were randomly separated into three groups (n = 6 each group. Group 1 was the normal control group. Groups 2 and 3 received ACLX and sham-ACLX, respectively, of the right knee. T2* values were measured in the knee cartilage, the meniscus, and femoral subchondral bone marrow of all rats at 0, 4, 13, and 18 weeks after surgery. RESULTS: Cartilage T2* values were significantly higher at 4, 13, and 18 weeks postoperatively in rats of the ACLX group than in rats of the control and sham groups (p<0.001. In the ACLX group (compared to the sham and control groups, T2* values increased significantly first in the posterior horn of the medial meniscus at 4 weeks (p = 0.001, then in the anterior horn of the medial meniscus at 13 weeks (p<0.001, and began to increase significantly in the femoral subchondral bone marrow at 13 weeks (p = 0.043. CONCLUSION: Quantitative MR T2* measurements of OA-related tissues are feasible. Sequential change in T2* over time in cartilage, meniscus, and subchondral bone marrow were documented. This information could be potentially useful for in vivo monitoring of disease progression.

  6. Sequential optimization of a terrestrial biosphere model constrained by multiple satellite based products

    Science.gov (United States)

    Ichii, K.; Kondo, M.; Wang, W.; Hashimoto, H.; Nemani, R. R.

    2012-12-01

    Various satellite-based spatial products such as evapotranspiration (ET) and gross primary productivity (GPP) are now produced by integration of ground and satellite observations. Effective use of these multiple satellite-based products in terrestrial biosphere models is an important step toward better understanding of terrestrial carbon and water cycles. However, due to the complexity of terrestrial biosphere models with large number of model parameters, the application of these spatial data sets in terrestrial biosphere models is difficult. In this study, we established an effective but simple framework to refine a terrestrial biosphere model, Biome-BGC, using multiple satellite-based products as constraints. We tested the framework in the monsoon Asia region covered by AsiaFlux observations. The framework is based on the hierarchical analysis (Wang et al. 2009) with model parameter optimization constrained by satellite-based spatial data. The Biome-BGC model is separated into several tiers to minimize the freedom of model parameter selections and maximize the independency from the whole model. For example, the snow sub-model is first optimized using MODIS snow cover product, followed by soil water sub-model optimized by satellite-based ET (estimated by an empirical upscaling method; Support Vector Regression (SVR) method; Yang et al. 2007), photosynthesis model optimized by satellite-based GPP (based on SVR method), and respiration and residual carbon cycle models optimized by biomass data. As a result of initial assessment, we found that most of default sub-models (e.g. snow, water cycle and carbon cycle) showed large deviations from remote sensing observations. However, these biases were removed by applying the proposed framework. For example, gross primary productivities were initially underestimated in boreal and temperate forest and overestimated in tropical forests. However, the parameter optimization scheme successfully reduced these biases. Our analysis

  7. Modeling of Activated Sludge Process Using Sequential Adaptive Neuro-fuzzy Inference System

    Directory of Open Access Journals (Sweden)

    Mahsa Vajedi

    2014-10-01

    Full Text Available In this study, an adaptive neuro-fuzzy inference system (ANFIS has been applied to model activated sludge wastewater treatment process of Mobin petrochemical company. The correlation coefficients between the input variables and the output variable were calculated to determine the input with the highest influence on the output (the quality of the outlet flow in order to compare three neuro-fuzzy structures with different number of parameters. The predictions of the neuro-fuzzy models were compared with those of multilayer artificial neural network models with similar structure. The comparison indicated that both methods resulted in flexible, robust and effective models for the activated sludge system. Moreover, the root mean square of the error for neuro-fuzzy and neural network models were 5.14 and 6.59, respectively, which means the former is the superior method.

  8. Topology optimization of induction heating model using sequential linear programming based on move limit with adaptive relaxation

    Science.gov (United States)

    Masuda, Hiroshi; Kanda, Yutaro; Okamoto, Yoshifumi; Hirono, Kazuki; Hoshino, Reona; Wakao, Shinji; Tsuburaya, Tomonori

    2017-12-01

    It is very important to design electrical machineries with high efficiency from the point of view of saving energy. Therefore, topology optimization (TO) is occasionally used as a design method for improving the performance of electrical machinery under the reasonable constraints. Because TO can achieve a design with much higher degree of freedom in terms of structure, there is a possibility for deriving the novel structure which would be quite different from the conventional structure. In this paper, topology optimization using sequential linear programming using move limit based on adaptive relaxation is applied to two models. The magnetic shielding, in which there are many local minima, is firstly employed as firstly benchmarking for the performance evaluation among several mathematical programming methods. Secondly, induction heating model is defined in 2-D axisymmetric field. In this model, the magnetic energy stored in the magnetic body is maximized under the constraint on the volume of magnetic body. Furthermore, the influence of the location of the design domain on the solutions is investigated.

  9. The economic, environmental and public health impacts of new power plants: a sequential inter industry model integrated with GIS data

    Energy Technology Data Exchange (ETDEWEB)

    Avelino, Andre F.T.; Hewings, Geoffrey J.D.; Guilhoto, Joaquim J.M. [Universidade de Sao Paulo (FEA/USP), SE (Brazil). Fac. de Administracao e Contabilidade

    2010-07-01

    The electrical sector is responsible for a considerable amount of greenhouse gases emissions worldwide, but also the one in which modern society depends the most for maintenance of quality of life as well as the functioning of economic and social activities. Invariably, even CO2 emission-free power plants have some indirect environmental impacts due to the economic effects they produce during their life cycle (construction, O and M and decommissioning). Thus, sustainability issues should be always considered in energy planning, by evaluating the balance of positive/negative externalities on different areas of the country. This study aims to introduce a social-environmental economic model, based on a Regional Sequential Inter industry Model (SIM) integrated with geoprocessing data, in order to identify economic, pollution and public health impacts in state level for energy planning analysis. The model is based on the Impact Pathway Approach Methodology, using geoprocessing to locate social-environmental variables for dispersion and health evaluations. The final goal is to provide an auxiliary tool for policy makers to assess energy planning scenarios in Brazil. (author)

  10. Assessing sequential data assimilation techniques for integrating GRACE data into a hydrological model

    KAUST Repository

    Khaki, M.; Hoteit, Ibrahim; Kuhn, M.; Awange, J.; Forootan, E.; van Dijk, A.; Schumacher, M.; Pattiaratchi, C.

    2017-01-01

    The time-variable terrestrial water storage (TWS) products from the Gravity Recovery And Climate Experiment (GRACE) have been increasingly used in recent years to improve the simulation of hydrological models by applying data assimilation techniques

  11. Effectiveness of maritime safety control in different navigation zones using a spatial sequential DEA model: Yangtze River case.

    Science.gov (United States)

    Wu, Bing; Wang, Yang; Zhang, Jinfen; Savan, Emanuel Emil; Yan, Xinping

    2015-08-01

    This paper aims to analyze the effectiveness of maritime safety control from the perspective of safety level along the Yangtze River with special considerations for navigational environments. The influencing variables of maritime safety are reviewed, including ship condition, maritime regulatory system, human reliability and navigational environment. Because the former three variables are generally assumed to be of the same level of safety, this paper focuses on studying the impact of navigational environments on the level of safety in different waterways. An improved data envelopment analysis (DEA) model is proposed by treating the navigational environment factors as inputs and ship accident data as outputs. Moreover, because the traditional DEA model cannot provide an overall ranking of different decision making units (DMUs), the spatial sequential frontiers and grey relational analysis are incorporated into the DEA model to facilitate a refined assessment. Based on the empirical study results, the proposed model is able to solve the problem of information missing in the prior models and evaluate the level of safety with a better accuracy. The results of the proposed DEA model are further compared with an evidential reasoning (ER) method, which has been widely used for level of safety evaluations. A sensitivity analysis is also conducted to better understand the relationship between the variation of navigational environments and level of safety. The sensitivity analysis shows that the level of safety varies in terms of traffic flow. It indicates that appropriate traffic control measures should be adopted for different waterways to improve their safety. This paper presents a practical method of conducting maritime level of safety assessments under dynamic navigational environment. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. A dynamic general disequilibrium model of a sequential monetary production economy

    International Nuclear Information System (INIS)

    Raberto, Marco; Teglio, Andrea; Cincotti, Silvano

    2006-01-01

    A discrete, deterministic, economic model, based on the framework of non-Walrasian or disequilibrium economics, is presented. The main feature of this approach is the presence of non-clearing markets, where not all demands and supplies are satisfied and some agents may be rationed. The model is characterized by three agents (i.e., a representative firm, a representative consumer, and a central bank), three commodities (i.e., goods, labour and money, each homogeneous) and three markets for their exchange. The imbalance between demand and supply in each market determines the dynamics of price, nominal wage and nominal interest rate. The central bank provides the money supply according to an operating target interest rate that is fixed accordingly to Taylor's rule. The model has been studied by means of computer simulations. Results pointed out the presence of business cycles that can be controlled by proper policies of the central bank

  13. Sequential Monte Carlo filter for state estimation of LiFePO4 batteries based on an online updated model

    Science.gov (United States)

    Li, Jiahao; Klee Barillas, Joaquin; Guenther, Clemens; Danzer, Michael A.

    2014-02-01

    Battery state monitoring is one of the key techniques in battery management systems e.g. in electric vehicles. An accurate estimation can help to improve the system performance and to prolong the battery remaining useful life. Main challenges for the state estimation for LiFePO4 batteries are the flat characteristic of open-circuit-voltage over battery state of charge (SOC) and the existence of hysteresis phenomena. Classical estimation approaches like Kalman filtering show limitations to handle nonlinear and non-Gaussian error distribution problems. In addition, uncertainties in the battery model parameters must be taken into account to describe the battery degradation. In this paper, a novel model-based method combining a Sequential Monte Carlo filter with adaptive control to determine the cell SOC and its electric impedance is presented. The applicability of this dual estimator is verified using measurement data acquired from a commercial LiFePO4 cell. Due to a better handling of the hysteresis problem, results show the benefits of the proposed method against the estimation with an Extended Kalman filter.

  14. Effect of anaerobic digestion on sequential pyrolysis kinetics of organic solid wastes using thermogravimetric analysis and distributed activation energy model.

    Science.gov (United States)

    Li, Xiaowei; Mei, Qingqing; Dai, Xiaohu; Ding, Guoji

    2017-03-01

    Thermogravimetric analysis, Gaussian-fit-peak model (GFPM), and distributed activation energy model (DAEM) were firstly used to explore the effect of anaerobic digestion on sequential pyrolysis kinetic of four organic solid wastes (OSW). Results showed that the OSW weight loss mainly occurred in the second pyrolysis stage relating to organic matter decomposition. Compared with raw substrate, the weight loss of corresponding digestate was lower in the range of 180-550°C, but was higher in 550-900°C. GFPM analysis revealed that organic components volatized at peak temperatures of 188-263, 373-401 and 420-462°C had a faster degradation rate than those at 274-327°C during anaerobic digestion. DAEM analysis showed that anaerobic digestion had discrepant effects on activation energy for four OSW pyrolysis, possibly because of their different organic composition. It requires further investigation for the special organic matter, i.e., protein-like and carbohydrate-like groups, to confirm the assumption. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. Development and Sensitivity Analysis of a Fully Kinetic Model of Sequential Reductive Dechlorination in Groundwater

    DEFF Research Database (Denmark)

    Malaguerra, Flavio; Chambon, Julie Claire Claudia; Bjerg, Poul Løgstrup

    2011-01-01

    experiments of complete trichloroethene (TCE) degradation in natural sediments. Global sensitivity analysis was performed using the Morris method and Sobol sensitivity indices to identify the most influential model parameters. Results show that the sulfate concentration and fermentation kinetics are the most...

  16. Sequential search leads to faster, more efficient fragment-based de novo protein structure prediction.

    Science.gov (United States)

    de Oliveira, Saulo H P; Law, Eleanor C; Shi, Jiye; Deane, Charlotte M

    2018-04-01

    Most current de novo structure prediction methods randomly sample protein conformations and thus require large amounts of computational resource. Here, we consider a sequential sampling strategy, building on ideas from recent experimental work which shows that many proteins fold cotranslationally. We have investigated whether a pseudo-greedy search approach, which begins sequentially from one of the termini, can improve the performance and accuracy of de novo protein structure prediction. We observed that our sequential approach converges when fewer than 20 000 decoys have been produced, fewer than commonly expected. Using our software, SAINT2, we also compared the run time and quality of models produced in a sequential fashion against a standard, non-sequential approach. Sequential prediction produces an individual decoy 1.5-2.5 times faster than non-sequential prediction. When considering the quality of the best model, sequential prediction led to a better model being produced for 31 out of 41 soluble protein validation cases and for 18 out of 24 transmembrane protein cases. Correct models (TM-Score > 0.5) were produced for 29 of these cases by the sequential mode and for only 22 by the non-sequential mode. Our comparison reveals that a sequential search strategy can be used to drastically reduce computational time of de novo protein structure prediction and improve accuracy. Data are available for download from: http://opig.stats.ox.ac.uk/resources. SAINT2 is available for download from: https://github.com/sauloho/SAINT2. saulo.deoliveira@dtc.ox.ac.uk. Supplementary data are available at Bioinformatics online.

  17. A model of type 2 diabetes in the guinea pig using sequential diet-induced glucose intolerance and streptozotocin treatment

    Science.gov (United States)

    Ackart, David F.; Richardson, Michael A.; DiLisio, James E.; Pulford, Bruce; Basaraba, Randall J.

    2017-01-01

    ABSTRACT Type 2 diabetes is a leading cause of morbidity and mortality among noncommunicable diseases, and additional animal models that more closely replicate the pathogenesis of human type 2 diabetes are needed. The goal of this study was to develop a model of type 2 diabetes in guinea pigs, in which diet-induced glucose intolerance precedes β-cell cytotoxicity, two processes that are crucial to the development of human type 2 diabetes. Guinea pigs developed impaired glucose tolerance after 8 weeks of feeding on a high-fat, high-carbohydrate diet, as determined by oral glucose challenge. Diet-induced glucose intolerance was accompanied by β-cell hyperplasia, compensatory hyperinsulinemia, and dyslipidemia with hepatocellular steatosis. Streptozotocin (STZ) treatment alone was ineffective at inducing diabetic hyperglycemia in guinea pigs, which failed to develop sustained glucose intolerance or fasting hyperglycemia and returned to euglycemia within 21 days after treatment. However, when high-fat, high-carbohydrate diet-fed guinea pigs were treated with STZ, glucose intolerance and fasting hyperglycemia persisted beyond 21 days post-STZ treatment. Guinea pigs with diet-induced glucose intolerance subsequently treated with STZ demonstrated an insulin-secretory capacity consistent with insulin-independent diabetes. This insulin-independent state was confirmed by response to oral antihyperglycemic drugs, metformin and glipizide, which resolved glucose intolerance and extended survival compared with guinea pigs with uncontrolled diabetes. In this study, we have developed a model of sequential glucose intolerance and β-cell loss, through high-fat, high-carbohydrate diet and extensive optimization of STZ treatment in the guinea pig, which closely resembles human type 2 diabetes. This model will prove useful in the study of insulin-independent diabetes pathogenesis with or without comorbidities, where the guinea pig serves as a relevant model species. PMID:28093504

  18. A model of type 2 diabetes in the guinea pig using sequential diet-induced glucose intolerance and streptozotocin treatment.

    Science.gov (United States)

    Podell, Brendan K; Ackart, David F; Richardson, Michael A; DiLisio, James E; Pulford, Bruce; Basaraba, Randall J

    2017-02-01

    Type 2 diabetes is a leading cause of morbidity and mortality among noncommunicable diseases, and additional animal models that more closely replicate the pathogenesis of human type 2 diabetes are needed. The goal of this study was to develop a model of type 2 diabetes in guinea pigs, in which diet-induced glucose intolerance precedes β-cell cytotoxicity, two processes that are crucial to the development of human type 2 diabetes. Guinea pigs developed impaired glucose tolerance after 8 weeks of feeding on a high-fat, high-carbohydrate diet, as determined by oral glucose challenge. Diet-induced glucose intolerance was accompanied by β-cell hyperplasia, compensatory hyperinsulinemia, and dyslipidemia with hepatocellular steatosis. Streptozotocin (STZ) treatment alone was ineffective at inducing diabetic hyperglycemia in guinea pigs, which failed to develop sustained glucose intolerance or fasting hyperglycemia and returned to euglycemia within 21 days after treatment. However, when high-fat, high-carbohydrate diet-fed guinea pigs were treated with STZ, glucose intolerance and fasting hyperglycemia persisted beyond 21 days post-STZ treatment. Guinea pigs with diet-induced glucose intolerance subsequently treated with STZ demonstrated an insulin-secretory capacity consistent with insulin-independent diabetes. This insulin-independent state was confirmed by response to oral antihyperglycemic drugs, metformin and glipizide, which resolved glucose intolerance and extended survival compared with guinea pigs with uncontrolled diabetes. In this study, we have developed a model of sequential glucose intolerance and β-cell loss, through high-fat, high-carbohydrate diet and extensive optimization of STZ treatment in the guinea pig, which closely resembles human type 2 diabetes. This model will prove useful in the study of insulin-independent diabetes pathogenesis with or without comorbidities, where the guinea pig serves as a relevant model species. © 2017. Published by

  19. Parameter optimisation for a better representation of drought by LSMs: inverse modelling vs. sequential data assimilation

    Science.gov (United States)

    Dewaele, Hélène; Munier, Simon; Albergel, Clément; Planque, Carole; Laanaia, Nabil; Carrer, Dominique; Calvet, Jean-Christophe

    2017-09-01

    Soil maximum available water content (MaxAWC) is a key parameter in land surface models (LSMs). However, being difficult to measure, this parameter is usually uncertain. This study assesses the feasibility of using a 15-year (1999-2013) time series of satellite-derived low-resolution observations of leaf area index (LAI) to estimate MaxAWC for rainfed croplands over France. LAI interannual variability is simulated using the CO2-responsive version of the Interactions between Soil, Biosphere and Atmosphere (ISBA) LSM for various values of MaxAWC. Optimal value is then selected by using (1) a simple inverse modelling technique, comparing simulated and observed LAI and (2) a more complex method consisting in integrating observed LAI in ISBA through a land data assimilation system (LDAS) and minimising LAI analysis increments. The evaluation of the MaxAWC estimates from both methods is done using simulated annual maximum above-ground biomass (Bag) and straw cereal grain yield (GY) values from the Agreste French agricultural statistics portal, for 45 administrative units presenting a high proportion of straw cereals. Significant correlations (p value Bag and GY are found for up to 36 and 53 % of the administrative units for the inverse modelling and LDAS tuning methods, respectively. It is found that the LDAS tuning experiment gives more realistic values of MaxAWC and maximum Bag than the inverse modelling experiment. Using undisaggregated LAI observations leads to an underestimation of MaxAWC and maximum Bag in both experiments. Median annual maximum values of disaggregated LAI observations are found to correlate very well with MaxAWC.

  20. A Data-Driven Method for Selecting Optimal Models Based on Graphical Visualisation of Differences in Sequentially Fitted ROC Model Parameters

    Directory of Open Access Journals (Sweden)

    K S Mwitondi

    2013-05-01

    Full Text Available Differences in modelling techniques and model performance assessments typically impinge on the quality of knowledge extraction from data. We propose an algorithm for determining optimal patterns in data by separately training and testing three decision tree models in the Pima Indians Diabetes and the Bupa Liver Disorders datasets. Model performance is assessed using ROC curves and the Youden Index. Moving differences between sequential fitted parameters are then extracted, and their respective probability density estimations are used to track their variability using an iterative graphical data visualisation technique developed for this purpose. Our results show that the proposed strategy separates the groups more robustly than the plain ROC/Youden approach, eliminates obscurity, and minimizes over-fitting. Further, the algorithm can easily be understood by non-specialists and demonstrates multi-disciplinary compliance.

  1. Sequential modelling of the effects of mass drug treatments on anopheline-mediated lymphatic filariasis infection in Papua New Guinea.

    Directory of Open Access Journals (Sweden)

    Brajendra K Singh

    Full Text Available Lymphatic filariasis (LF has been targeted by the WHO for global eradication leading to the implementation of large scale intervention programs based on annual mass drug administrations (MDA worldwide. Recent work has indicated that locality-specific bio-ecological complexities affecting parasite transmission may complicate the prediction of LF extinction endpoints, casting uncertainty on the achievement of this initiative. One source of difficulty is the limited quantity and quality of data used to parameterize models of parasite transmission, implying the important need to update initially-derived parameter values. Sequential analysis of longitudinal data following annual MDAs will also be important to gaining new understanding of the persistence dynamics of LF. Here, we apply a Bayesian statistical-dynamical modelling framework that enables assimilation of information in human infection data recorded from communities in Papua New Guinea that underwent annual MDAs, into our previously developed model of parasite transmission, in order to examine these questions in LF ecology and control.Biological parameters underlying transmission obtained by fitting the model to longitudinal data remained stable throughout the study period. This enabled us to reliably reconstruct the observed baseline data in each community. Endpoint estimates also showed little variation. However, the updating procedure showed a shift towards higher and less variable values for worm kill but not for any other drug-related parameters. An intriguing finding is that the stability in key biological parameters could be disrupted by a significant reduction in the vector biting rate prevailing in a locality.Temporal invariance of biological parameters in the face of intervention perturbations indicates a robust adaptation of LF transmission to local ecological conditions. The results imply that understanding the mechanisms that underlie locally adapted transmission dynamics will

  2. Predictive modelling of survival and length of stay in critically ill patients using sequential organ failure scores.

    Science.gov (United States)

    Houthooft, Rein; Ruyssinck, Joeri; van der Herten, Joachim; Stijven, Sean; Couckuyt, Ivo; Gadeyne, Bram; Ongenae, Femke; Colpaert, Kirsten; Decruyenaere, Johan; Dhaene, Tom; De Turck, Filip

    2015-03-01

    The length of stay of critically ill patients in the intensive care unit (ICU) is an indication of patient ICU resource usage and varies considerably. Planning of postoperative ICU admissions is important as ICUs often have no nonoccupied beds available. Estimation of the ICU bed availability for the next coming days is entirely based on clinical judgement by intensivists and therefore too inaccurate. For this reason, predictive models have much potential for improving planning for ICU patient admission. Our goal is to develop and optimize models for patient survival and ICU length of stay (LOS) based on monitored ICU patient data. Furthermore, these models are compared on their use of sequential organ failure (SOFA) scores as well as underlying raw data as input features. Different machine learning techniques are trained, using a 14,480 patient dataset, both on SOFA scores as well as their underlying raw data values from the first five days after admission, in order to predict (i) the patient LOS, and (ii) the patient mortality. Furthermore, to help physicians in assessing the prediction credibility, a probabilistic model is tailored to the output of our best-performing model, assigning a belief to each patient status prediction. A two-by-two grid is built, using the classification outputs of the mortality and prolonged stay predictors to improve the patient LOS regression models. For predicting patient mortality and a prolonged stay, the best performing model is a support vector machine (SVM) with GA,D=65.9% (area under the curve (AUC) of 0.77) and GS,L=73.2% (AUC of 0.82). In terms of LOS regression, the best performing model is support vector regression, achieving a mean absolute error of 1.79 days and a median absolute error of 1.22 days for those patients surviving a nonprolonged stay. Using a classification grid based on the predicted patient mortality and prolonged stay, allows more accurate modeling of the patient LOS. The detailed models allow to support

  3. Effects of Combined Simultaneous and Sequential Endostar and Cisplatin Treatment in a Mice Model of Gastric Cancer Peritoneal Metastases

    Directory of Open Access Journals (Sweden)

    Lin Jia

    2017-01-01

    Full Text Available Objective. Aimed to study the effects of endostar and cisplatin using an in vivo imaging system (IVIS in a model of peritoneal metastasis of gastric cancer. Methods. NUGC-4 gastric cancer cells transfected with luciferase gene (NUGC-4-Luc were injected i.p. into nude mice. One week later, mice were randomly injected i.p.: group 1, cisplatin (d1–3 + endostar (d4–7; group 2, endostar (d1–4 + cisplatin (d5–7; group 3, endostar + cisplatin d1, 4, and 7; group 4, saline for two weeks. One week after the final administration, mice were sacrificed. Bioluminescent data, microvessel density (MVD, and lymphatic vessel density (LVD were analyzed. Results. Among the four groups, there were no significant differences in the weights and in the number of cancer cell photons on days 1 and 8 (P>0.05. On day 15, the numbers in groups 3 and 1 were less than that in group 2 (P0.05 or in LVD number among the four groups (P>0.05. Conclusions. IVIS® was more useful than weight, volume of ascites, and number of peritoneal nodules. The simultaneous group was superior to sequential groups in killing cancer cells and inhibiting vascular endothelium. Cisplatin-endostar was superior to endostar-cisplatin in killing cancer cells, while the latter in inhibiting peritoneal vascular endothelium.

  4. Effects of Combined Simultaneous and Sequential Endostar and Cisplatin Treatment in a Mice Model of Gastric Cancer Peritoneal Metastases.

    Science.gov (United States)

    Jia, Lin; Ren, Shuguang; Li, Tao; Wu, Jianing; Zhou, Xinliang; Zhang, Yan; Wu, Jianhua; Liu, Wei

    2017-01-01

    Objective . Aimed to study the effects of endostar and cisplatin using an in vivo imaging system (IVIS) in a model of peritoneal metastasis of gastric cancer. Methods . NUGC-4 gastric cancer cells transfected with luciferase gene (NUGC-4-Luc) were injected i.p. into nude mice. One week later, mice were randomly injected i.p.: group 1, cisplatin (d1-3) + endostar (d4-7); group 2, endostar (d1-4) + cisplatin (d5-7); group 3, endostar + cisplatin d1, 4, and 7; group 4, saline for two weeks. One week after the final administration, mice were sacrificed. Bioluminescent data, microvessel density (MVD), and lymphatic vessel density (LVD) were analyzed. Results . Among the four groups, there were no significant differences in the weights and in the number of cancer cell photons on days 1 and 8 ( P > 0.05). On day 15, the numbers in groups 3 and 1 were less than that in group 2 ( P 0.05) or in LVD number among the four groups ( P > 0.05). Conclusions . IVIS® was more useful than weight, volume of ascites, and number of peritoneal nodules. The simultaneous group was superior to sequential groups in killing cancer cells and inhibiting vascular endothelium. Cisplatin-endostar was superior to endostar-cisplatin in killing cancer cells, while the latter in inhibiting peritoneal vascular endothelium.

  5. Dual Binding Site and Selective Acetylcholinesterase Inhibitors Derived from Integrated Pharmacophore Models and Sequential Virtual Screening

    Directory of Open Access Journals (Sweden)

    Shikhar Gupta

    2014-01-01

    Full Text Available In this study, we have employed in silico methodology combining double pharmacophore based screening, molecular docking, and ADME/T filtering to identify dual binding site acetylcholinesterase inhibitors that can preferentially inhibit acetylcholinesterase and simultaneously inhibit the butyrylcholinesterase also but in the lesser extent than acetylcholinesterase. 3D-pharmacophore models of AChE and BuChE enzyme inhibitors have been developed from xanthostigmine derivatives through HypoGen and validated using test set, Fischer’s randomization technique. The best acetylcholinesterase and butyrylcholinesterase inhibitors pharmacophore hypotheses Hypo1_A and Hypo1_B, with high correlation coefficient of 0.96 and 0.94, respectively, were used as 3D query for screening the Zinc database. The screened hits were then subjected to the ADME/T and molecular docking study to prioritise the compounds. Finally, 18 compounds were identified as potential leads against AChE enzyme, showing good predicted activities and promising ADME/T properties.

  6. Vehicle speed detection based on gaussian mixture model using sequential of images

    Science.gov (United States)

    Setiyono, Budi; Ratna Sulistyaningrum, Dwi; Soetrisno; Fajriyah, Farah; Wahyu Wicaksono, Danang

    2017-09-01

    Intelligent Transportation System is one of the important components in the development of smart cities. Detection of vehicle speed on the highway is supporting the management of traffic engineering. The purpose of this study is to detect the speed of the moving vehicles using digital image processing. Our approach is as follows: The inputs are a sequence of frames, frame rate (fps) and ROI. The steps are following: First we separate foreground and background using Gaussian Mixture Model (GMM) in each frames. Then in each frame, we calculate the location of object and its centroid. Next we determine the speed by computing the movement of centroid in sequence of frames. In the calculation of speed, we only consider frames when the centroid is inside the predefined region of interest (ROI). Finally we transform the pixel displacement into a time unit of km/hour. Validation of the system is done by comparing the speed calculated manually and obtained by the system. The results of software testing can detect the speed of vehicles with the highest accuracy is 97.52% and the lowest accuracy is 77.41%. And the detection results of testing by using real video footage on the road is included with real speed of the vehicle.

  7. Seasonal climate variation and caribou availability: Modeling sequential movement using satellite-relocation data

    Science.gov (United States)

    Nicolson, Craig; Berman, Matthew; West, Colin Thor; Kofinas, Gary P.; Griffith, Brad; Russell, Don; Dugan, Darcy

    2013-01-01

    Livelihood systems that depend on mobile resources must constantly adapt to change. For people living in permanent settlements, environmental changes that affect the distribution of a migratory species may reduce the availability of a primary food source, with the potential to destabilize the regional social-ecological system. Food security for Arctic indigenous peoples harvesting barren ground caribou (Rangifer tarandus granti) depends on movement patterns of migratory herds. Quantitative assessments of physical, ecological, and social effects on caribou distribution have proven difficult because of the significant interannual variability in seasonal caribou movement patterns. We developed and evaluated a modeling approach for simulating the distribution of a migratory herd throughout its annual cycle over a multiyear period. Beginning with spatial and temporal scales developed in previous studies of the Porcupine Caribou Herd of Canada and Alaska, we used satellite collar locations to compute and analyze season-by-season probabilities of movement of animals between habitat zones under two alternative weather conditions for each season. We then built a set of transition matrices from these movement probabilities, and simulated the sequence of movements across the landscape as a Markov process driven by externally imposed seasonal weather states. Statistical tests showed that the predicted distributions of caribou were consistent with observed distributions, and significantly correlated with subsistence harvest levels for three user communities. Our approach could be applied to other caribou herds and could be adapted for simulating the distribution of other ungulates and species with similarly large interannual variability in the use of their range.

  8. Seasonal Climate Variation and Caribou Availability: Modeling Sequential Movement Using Satellite-Relocation Data

    Directory of Open Access Journals (Sweden)

    Craig Nicolson

    2013-06-01

    Full Text Available Livelihood systems that depend on mobile resources must constantly adapt to change. For people living in permanent settlements, environmental changes that affect the distribution of a migratory species may reduce the availability of a primary food source, with the potential to destabilize the regional social-ecological system. Food security for Arctic indigenous peoples harvesting barren ground caribou (Rangifer tarandus granti depends on movement patterns of migratory herds. Quantitative assessments of physical, ecological, and social effects on caribou distribution have proven difficult because of the significant interannual variability in seasonal caribou movement patterns. We developed and evaluated a modeling approach for simulating the distribution of a migratory herd throughout its annual cycle over a multiyear period. Beginning with spatial and temporal scales developed in previous studies of the Porcupine Caribou Herd of Canada and Alaska, we used satellite collar locations to compute and analyze season-by-season probabilities of movement of animals between habitat zones under two alternative weather conditions for each season. We then built a set of transition matrices from these movement probabilities, and simulated the sequence of movements across the landscape as a Markov process driven by externally imposed seasonal weather states. Statistical tests showed that the predicted distributions of caribou were consistent with observed distributions, and significantly correlated with subsistence harvest levels for three user communities. Our approach could be applied to other caribou herds and could be adapted for simulating the distribution of other ungulates and species with similarly large interannual variability in the use of their range.

  9. Sequential application of ligand and structure based modeling approaches to index chemicals for their hH4R antagonism.

    Directory of Open Access Journals (Sweden)

    Matteo Pappalardo

    Full Text Available The human histamine H4 receptor (hH4R, a member of the G-protein coupled receptors (GPCR family, is an increasingly attractive drug target. It plays a key role in many cell pathways and many hH4R ligands are studied for the treatment of several inflammatory, allergic and autoimmune disorders, as well as for analgesic activity. Due to the challenging difficulties in the experimental elucidation of hH4R structure, virtual screening campaigns are normally run on homology based models. However, a wealth of information about the chemical properties of GPCR ligands has also accumulated over the last few years and an appropriate combination of these ligand-based knowledge with structure-based molecular modeling studies emerges as a promising strategy for computer-assisted drug design. Here, two chemoinformatics techniques, the Intelligent Learning Engine (ILE and Iterative Stochastic Elimination (ISE approach, were used to index chemicals for their hH4R bioactivity. An application of the prediction model on external test set composed of more than 160 hH4R antagonists picked from the chEMBL database gave enrichment factor of 16.4. A virtual high throughput screening on ZINC database was carried out, picking ∼ 4000 chemicals highly indexed as H4R antagonists' candidates. Next, a series of 3D models of hH4R were generated by molecular modeling and molecular dynamics simulations performed in fully atomistic lipid membranes. The efficacy of the hH4R 3D models in discrimination between actives and non-actives were checked and the 3D model with the best performance was chosen for further docking studies performed on the focused library. The output of these docking studies was a consensus library of 11 highly active scored drug candidates. Our findings suggest that a sequential combination of ligand-based chemoinformatics approaches with structure-based ones has the potential to improve the success rate in discovering new biologically active GPCR drugs and

  10. Sequential application of ligand and structure based modeling approaches to index chemicals for their hH4R antagonism.

    Science.gov (United States)

    Pappalardo, Matteo; Shachaf, Nir; Basile, Livia; Milardi, Danilo; Zeidan, Mouhammed; Raiyn, Jamal; Guccione, Salvatore; Rayan, Anwar

    2014-01-01

    The human histamine H4 receptor (hH4R), a member of the G-protein coupled receptors (GPCR) family, is an increasingly attractive drug target. It plays a key role in many cell pathways and many hH4R ligands are studied for the treatment of several inflammatory, allergic and autoimmune disorders, as well as for analgesic activity. Due to the challenging difficulties in the experimental elucidation of hH4R structure, virtual screening campaigns are normally run on homology based models. However, a wealth of information about the chemical properties of GPCR ligands has also accumulated over the last few years and an appropriate combination of these ligand-based knowledge with structure-based molecular modeling studies emerges as a promising strategy for computer-assisted drug design. Here, two chemoinformatics techniques, the Intelligent Learning Engine (ILE) and Iterative Stochastic Elimination (ISE) approach, were used to index chemicals for their hH4R bioactivity. An application of the prediction model on external test set composed of more than 160 hH4R antagonists picked from the chEMBL database gave enrichment factor of 16.4. A virtual high throughput screening on ZINC database was carried out, picking ∼ 4000 chemicals highly indexed as H4R antagonists' candidates. Next, a series of 3D models of hH4R were generated by molecular modeling and molecular dynamics simulations performed in fully atomistic lipid membranes. The efficacy of the hH4R 3D models in discrimination between actives and non-actives were checked and the 3D model with the best performance was chosen for further docking studies performed on the focused library. The output of these docking studies was a consensus library of 11 highly active scored drug candidates. Our findings suggest that a sequential combination of ligand-based chemoinformatics approaches with structure-based ones has the potential to improve the success rate in discovering new biologically active GPCR drugs and increase the

  11. A sequential vesicle pool model with a single release sensor and a ca(2+)-dependent priming catalyst effectively explains ca(2+)-dependent properties of neurosecretion

    DEFF Research Database (Denmark)

    Walter, Alexander M; da Silva Pinheiro, Paulo César; Verhage, Matthijs

    2013-01-01

    identified. We here propose a Sequential Pool Model (SPM), assuming a novel Ca(2+)-dependent action: a Ca(2+)-dependent catalyst that accelerates both forward and reverse priming reactions. While both models account for fast fusion from the Readily-Releasable Pool (RRP) under control of synaptotagmin-1...... the simultaneous changes in release rate and amplitude seen when mutating the SNARE-complex. Finally, it can account for the loss of fast- and the persistence of slow release in the synaptotagmin-1 knockout by assuming that the RRP is depleted, leading to slow and Ca(2+)-dependent fusion from the NRP. We conclude...... that the elusive 'alternative Ca(2+) sensor' for slow release might be the upstream priming catalyst, and that a sequential model effectively explains Ca(2+)-dependent properties of secretion without assuming parallel pools or sensors....

  12. Sequential Management of Commercial Rosewood (Aniba rosaeodora Ducke Plantations in Central Amazonia: Seeking Sustainable Models for Essential Oil Production

    Directory of Open Access Journals (Sweden)

    Pedro Medrado Krainovic

    2017-11-01

    Full Text Available Rosewood (Aniba rosaeodora Ducke is an endangered tree that produces essential oil of high commercial value. However, technical-scientific knowledge about cultivation is scarce and studies are needed to examine the management viability. The current study evaluated rosewood aboveground biomass management, measuring the export of nutrients resulting from harvesting and testing sustainable management models. The crown of 36 rosewood trees were pruned and 108 trees cut at 50 cm above the soil in two regions in Central Amazonia. Post-harvest performance of sprouting shoots was evaluated and after, sprouting shoots were pruned so that the development of two, three and all shoots was permitted. Nutrient stock estimation was calculated as the product of mass and nutrient concentration, which allowed nutritional replacement to be estimated. The pruning facilitates regrowth by 40.11% of the initial mass while by cut regrow 1.45%. Chemical attributes of regrowth biomass differed significantly prior to management and regrowth had a significant correlation with the reserves in root tissues and with the pre -management status of the individual tree. Driving sprouts resulted in significantly larger growth increments and may provide a form of management that can viably be adopted. Biomass sequential management resulted in high nutrient exports and the amount of fertilizer needed for replenishment depended on the intensity and frequency of cropping. Compared with the cut of the tree, pruning the canopy reduces fertilizers that are required to replenish amount by 44%, decreasing to 26.37% in the second rotation. The generated knowledge contributes to this silvicultural practice as it becomes ecologically and economically viable.

  13. Scalability on LHS (Latin Hypercube Sampling) samples for use in uncertainty analysis of large numerical models

    International Nuclear Information System (INIS)

    Baron, Jorge H.; Nunez Mac Leod, J.E.

    2000-01-01

    The present paper deals with the utilization of advanced sampling statistical methods to perform uncertainty and sensitivity analysis on numerical models. Such models may represent physical phenomena, logical structures (such as boolean expressions) or other systems, and various of their intrinsic parameters and/or input variables are usually treated as random variables simultaneously. In the present paper a simple method to scale-up Latin Hypercube Sampling (LHS) samples is presented, starting with a small sample and duplicating its size at each step, making it possible to use the already run numerical model results with the smaller sample. The method does not distort the statistical properties of the random variables and does not add any bias to the samples. The results is a significant reduction in numerical models running time can be achieved (by re-using the previously run samples), keeping all the advantages of LHS, until an acceptable representation level is achieved in the output variables. (author)

  14. Automated sample plan selection for OPC modeling

    Science.gov (United States)

    Casati, Nathalie; Gabrani, Maria; Viswanathan, Ramya; Bayraktar, Zikri; Jaiswal, Om; DeMaris, David; Abdo, Amr Y.; Oberschmidt, James; Krause, Andreas

    2014-03-01

    It is desired to reduce the time required to produce metrology data for calibration of Optical Proximity Correction (OPC) models and also maintain or improve the quality of the data collected with regard to how well that data represents the types of patterns that occur in real circuit designs. Previous work based on clustering in geometry and/or image parameter space has shown some benefit over strictly manual or intuitive selection, but leads to arbitrary pattern exclusion or selection which may not be the best representation of the product. Forming the pattern selection as an optimization problem, which co-optimizes a number of objective functions reflecting modelers' insight and expertise, has shown to produce models with equivalent quality to the traditional plan of record (POR) set but in a less time.

  15. Sample Size Determination for Rasch Model Tests

    Science.gov (United States)

    Draxler, Clemens

    2010-01-01

    This paper is concerned with supplementing statistical tests for the Rasch model so that additionally to the probability of the error of the first kind (Type I probability) the probability of the error of the second kind (Type II probability) can be controlled at a predetermined level by basing the test on the appropriate number of observations.…

  16. Exploring the sequential lineup advantage using WITNESS.

    Science.gov (United States)

    Goodsell, Charles A; Gronlund, Scott D; Carlson, Curt A

    2010-12-01

    Advocates claim that the sequential lineup is an improvement over simultaneous lineup procedures, but no formal (quantitatively specified) explanation exists for why it is better. The computational model WITNESS (Clark, Appl Cogn Psychol 17:629-654, 2003) was used to develop theoretical explanations for the sequential lineup advantage. In its current form, WITNESS produced a sequential advantage only by pairing conservative sequential choosing with liberal simultaneous choosing. However, this combination failed to approximate four extant experiments that exhibited large sequential advantages. Two of these experiments became the focus of our efforts because the data were uncontaminated by likely suspect position effects. Decision-based and memory-based modifications to WITNESS approximated the data and produced a sequential advantage. The next step is to evaluate the proposed explanations and modify public policy recommendations accordingly.

  17. Simultaneous acquisition of 2D and 3D solid-state NMR experiments for sequential assignment of oriented membrane protein samples

    Energy Technology Data Exchange (ETDEWEB)

    Gopinath, T. [University of Minnesota, Department of Biochemistry, Molecular Biology, and Biophysics (United States); Mote, Kaustubh R. [University of Minnesota, Department of Chemistry (United States); Veglia, Gianluigi, E-mail: vegli001@umn.edu [University of Minnesota, Department of Biochemistry, Molecular Biology, and Biophysics (United States)

    2015-05-15

    We present a new method called DAISY (Dual Acquisition orIented ssNMR spectroScopY) for the simultaneous acquisition of 2D and 3D oriented solid-state NMR experiments for membrane proteins reconstituted in mechanically or magnetically aligned lipid bilayers. DAISY utilizes dual acquisition of sine and cosine dipolar or chemical shift coherences and long living {sup 15}N longitudinal polarization to obtain two multi-dimensional spectra, simultaneously. In these new experiments, the first acquisition gives the polarization inversion spin exchange at the magic angle (PISEMA) or heteronuclear correlation (HETCOR) spectra, the second acquisition gives PISEMA-mixing or HETCOR-mixing spectra, where the mixing element enables inter-residue correlations through {sup 15}N–{sup 15}N homonuclear polarization transfer. The analysis of the two 2D spectra (first and second acquisitions) enables one to distinguish {sup 15}N–{sup 15}N inter-residue correlations for sequential assignment of membrane proteins. DAISY can be implemented in 3D experiments that include the polarization inversion spin exchange at magic angle via I spin coherence (PISEMAI) sequence, as we show for the simultaneous acquisition of 3D PISEMAI–HETCOR and 3D PISEMAI–HETCOR-mixing experiments.

  18. Simultaneous acquisition of 2D and 3D solid-state NMR experiments for sequential assignment of oriented membrane protein samples.

    Science.gov (United States)

    Gopinath, T; Mote, Kaustubh R; Veglia, Gianluigi

    2015-05-01

    We present a new method called DAISY (Dual Acquisition orIented ssNMR spectroScopY) for the simultaneous acquisition of 2D and 3D oriented solid-state NMR experiments for membrane proteins reconstituted in mechanically or magnetically aligned lipid bilayers. DAISY utilizes dual acquisition of sine and cosine dipolar or chemical shift coherences and long living (15)N longitudinal polarization to obtain two multi-dimensional spectra, simultaneously. In these new experiments, the first acquisition gives the polarization inversion spin exchange at the magic angle (PISEMA) or heteronuclear correlation (HETCOR) spectra, the second acquisition gives PISEMA-mixing or HETCOR-mixing spectra, where the mixing element enables inter-residue correlations through (15)N-(15)N homonuclear polarization transfer. The analysis of the two 2D spectra (first and second acquisitions) enables one to distinguish (15)N-(15)N inter-residue correlations for sequential assignment of membrane proteins. DAISY can be implemented in 3D experiments that include the polarization inversion spin exchange at magic angle via I spin coherence (PISEMAI) sequence, as we show for the simultaneous acquisition of 3D PISEMAI-HETCOR and 3D PISEMAI-HETCOR-mixing experiments.

  19. A sequential logic circuit for coincidences randomly distributed in 'time' and 'duration', with selection and total sampling

    International Nuclear Information System (INIS)

    Carnet, Bernard; Delhumeau, Michel

    1971-06-01

    The principles of binary analysis applied to the investigation of sequential circuits were used to design a two way coincidence circuit whose input may be, random or periodic variables of constant or variable duration. The output signal strictly reproduces the characteristics of the input signal triggering the coincidence. A coincidence between input signals does not produce any output signal if one of the signals has already triggered the output signal. The characteristics of the output signal in relation to those of the input signal are: minimum time jitter, excellent duration reproducibility and maximum efficiency. Some rules are given for achieving these results. The symmetry, transitivity and non-transitivity characteristics of the edges on the primitive graph are analyzed and lead to some rules for positioning the states on a secondary graph. It is from this graph that the equations of the circuits can be calculated. The development of the circuit and its dynamic testing are discussed. For this testing, the functioning of the circuit is simulated by feeding into the input randomly generated signals

  20. Simultaneous acquisition of 2D and 3D solid-state NMR experiments for sequential assignment of oriented membrane protein samples

    International Nuclear Information System (INIS)

    Gopinath, T.; Mote, Kaustubh R.; Veglia, Gianluigi

    2015-01-01

    We present a new method called DAISY (Dual Acquisition orIented ssNMR spectroScopY) for the simultaneous acquisition of 2D and 3D oriented solid-state NMR experiments for membrane proteins reconstituted in mechanically or magnetically aligned lipid bilayers. DAISY utilizes dual acquisition of sine and cosine dipolar or chemical shift coherences and long living 15 N longitudinal polarization to obtain two multi-dimensional spectra, simultaneously. In these new experiments, the first acquisition gives the polarization inversion spin exchange at the magic angle (PISEMA) or heteronuclear correlation (HETCOR) spectra, the second acquisition gives PISEMA-mixing or HETCOR-mixing spectra, where the mixing element enables inter-residue correlations through 15 N– 15 N homonuclear polarization transfer. The analysis of the two 2D spectra (first and second acquisitions) enables one to distinguish 15 N– 15 N inter-residue correlations for sequential assignment of membrane proteins. DAISY can be implemented in 3D experiments that include the polarization inversion spin exchange at magic angle via I spin coherence (PISEMAI) sequence, as we show for the simultaneous acquisition of 3D PISEMAI–HETCOR and 3D PISEMAI–HETCOR-mixing experiments

  1. Simulation modeling analysis of sequential relations among therapeutic alliance, symptoms, and adherence to child-centered play therapy between a child with autism spectrum disorder and two therapists.

    Science.gov (United States)

    Goodman, Geoff; Chung, Hyewon; Fischel, Leah; Athey-Lloyd, Laura

    2017-07-01

    This study examined the sequential relations among three pertinent variables in child psychotherapy: therapeutic alliance (TA) (including ruptures and repairs), autism symptoms, and adherence to child-centered play therapy (CCPT) process. A 2-year CCPT of a 6-year-old Caucasian boy diagnosed with autism spectrum disorder was conducted weekly with two doctoral-student therapists, working consecutively for 1 year each, in a university-based community mental-health clinic. Sessions were video-recorded and coded using the Child Psychotherapy Process Q-Set (CPQ), a measure of the TA, and an autism symptom measure. Sequential relations among these variables were examined using simulation modeling analysis (SMA). In Therapist 1's treatment, unexpectedly, autism symptoms decreased three sessions after a rupture occurred in the therapeutic dyad. In Therapist 2's treatment, adherence to CCPT process increased 2 weeks after a repair occurred in the therapeutic dyad. The TA decreased 1 week after autism symptoms increased. Finally, adherence to CCPT process decreased 1 week after autism symptoms increased. The authors concluded that (1) sequential relations differ by therapist even though the child remains constant, (2) therapeutic ruptures can have an unexpected effect on autism symptoms, and (3) changes in autism symptoms can precede as well as follow changes in process variables.

  2. Statistical surrogate model based sampling criterion for stochastic global optimization of problems with constraints

    Energy Technology Data Exchange (ETDEWEB)

    Cho, Su Gil; Jang, Jun Yong; Kim, Ji Hoon; Lee, Tae Hee [Hanyang University, Seoul (Korea, Republic of); Lee, Min Uk [Romax Technology Ltd., Seoul (Korea, Republic of); Choi, Jong Su; Hong, Sup [Korea Research Institute of Ships and Ocean Engineering, Daejeon (Korea, Republic of)

    2015-04-15

    Sequential surrogate model-based global optimization algorithms, such as super-EGO, have been developed to increase the efficiency of commonly used global optimization technique as well as to ensure the accuracy of optimization. However, earlier studies have drawbacks because there are three phases in the optimization loop and empirical parameters. We propose a united sampling criterion to simplify the algorithm and to achieve the global optimum of problems with constraints without any empirical parameters. It is able to select the points located in a feasible region with high model uncertainty as well as the points along the boundary of constraint at the lowest objective value. The mean squared error determines which criterion is more dominant among the infill sampling criterion and boundary sampling criterion. Also, the method guarantees the accuracy of the surrogate model because the sample points are not located within extremely small regions like super-EGO. The performance of the proposed method, such as the solvability of a problem, convergence properties, and efficiency, are validated through nonlinear numerical examples with disconnected feasible regions.

  3. The MIDAS Touch: Mixed Data Sampling Regression Models

    OpenAIRE

    Ghysels, Eric; Santa-Clara, Pedro; Valkanov, Rossen

    2004-01-01

    We introduce Mixed Data Sampling (henceforth MIDAS) regression models. The regressions involve time series data sampled at different frequencies. Technically speaking MIDAS models specify conditional expectations as a distributed lag of regressors recorded at some higher sampling frequencies. We examine the asymptotic properties of MIDAS regression estimation and compare it with traditional distributed lag models. MIDAS regressions have wide applicability in macroeconomics and �nance.

  4. Attack Trees with Sequential Conjunction

    NARCIS (Netherlands)

    Jhawar, Ravi; Kordy, Barbara; Mauw, Sjouke; Radomirović, Sasa; Trujillo-Rasua, Rolando

    2015-01-01

    We provide the first formal foundation of SAND attack trees which are a popular extension of the well-known attack trees. The SAND at- tack tree formalism increases the expressivity of attack trees by intro- ducing the sequential conjunctive operator SAND. This operator enables the modeling of

  5. Mercury in Environmental and Biological Samples Using Online Combustion with Sequential Atomic Absorption and Fluorescence Measurements: A Direct Comparison of Two Fundamental Techniques in Spectrometry

    Science.gov (United States)

    Cizdziel, James V.

    2011-01-01

    In this laboratory experiment, students quantitatively determine the concentration of an element (mercury) in an environmental or biological sample while comparing and contrasting the fundamental techniques of atomic absorption spectrometry (AAS) and atomic fluorescence spectrometry (AFS). A mercury analyzer based on sample combustion,…

  6. A minimax procedure in the context of sequential mastery testing

    NARCIS (Netherlands)

    Vos, Hendrik J.

    1999-01-01

    The purpose of this paper is to derive optimal rules for sequential mastery tests. In a sequential mastery test, the decision is to classify a subject as a master or a nonmaster, or to continue sampling and administering another random test item. The framework of minimax sequential decision theory

  7. Applying the minimax principle to sequential mastery testing

    NARCIS (Netherlands)

    Vos, Hendrik J.

    2002-01-01

    The purpose of this paper is to derive optimal rules for sequential mastery tests. In a sequential mastery test, the decision is to classify a subject as a master, a nonmaster, or to continue sampling and administering another random item. The framework of minimax sequential decision theory (minimum

  8. Sequential ensemble-based optimal design for parameter estimation: SEQUENTIAL ENSEMBLE-BASED OPTIMAL DESIGN

    Energy Technology Data Exchange (ETDEWEB)

    Man, Jun [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Zhang, Jiangjiang [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Li, Weixuan [Pacific Northwest National Laboratory, Richland Washington USA; Zeng, Lingzao [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Wu, Laosheng [Department of Environmental Sciences, University of California, Riverside California USA

    2016-10-01

    The ensemble Kalman filter (EnKF) has been widely used in parameter estimation for hydrological models. The focus of most previous studies was to develop more efficient analysis (estimation) algorithms. On the other hand, it is intuitively understandable that a well-designed sampling (data-collection) strategy should provide more informative measurements and subsequently improve the parameter estimation. In this work, a Sequential Ensemble-based Optimal Design (SEOD) method, coupled with EnKF, information theory and sequential optimal design, is proposed to improve the performance of parameter estimation. Based on the first-order and second-order statistics, different information metrics including the Shannon entropy difference (SD), degrees of freedom for signal (DFS) and relative entropy (RE) are used to design the optimal sampling strategy, respectively. The effectiveness of the proposed method is illustrated by synthetic one-dimensional and two-dimensional unsaturated flow case studies. It is shown that the designed sampling strategies can provide more accurate parameter estimation and state prediction compared with conventional sampling strategies. Optimal sampling designs based on various information metrics perform similarly in our cases. The effect of ensemble size on the optimal design is also investigated. Overall, larger ensemble size improves the parameter estimation and convergence of optimal sampling strategy. Although the proposed method is applied to unsaturated flow problems in this study, it can be equally applied in any other hydrological problems.

  9. The structure and evolution of galacto-detonation waves - Some analytic results in sequential star formation models of spiral galaxies

    Science.gov (United States)

    Cowie, L. L.; Rybicki, G. B.

    1982-01-01

    Waves of star formation in a uniform, differentially rotating disk galaxy are treated analytically as a propagating detonation wave front. It is shown, that if single solitary waves could be excited, they would evolve asymptotically to one of two stable spiral forms, each of which rotates with a fixed pattern speed. Simple numerical solutions confirm these results. However, the pattern of waves that develop naturally from an initially localized disturbance is more complex and dies out within a few rotation periods. These results suggest a conclusive observational test for deciding whether sequential star formation is an important determinant of spiral structure in some class of galaxies.

  10. An Improved Nested Sampling Algorithm for Model Selection and Assessment

    Science.gov (United States)

    Zeng, X.; Ye, M.; Wu, J.; WANG, D.

    2017-12-01

    Multimodel strategy is a general approach for treating model structure uncertainty in recent researches. The unknown groundwater system is represented by several plausible conceptual models. Each alternative conceptual model is attached with a weight which represents the possibility of this model. In Bayesian framework, the posterior model weight is computed as the product of model prior weight and marginal likelihood (or termed as model evidence). As a result, estimating marginal likelihoods is crucial for reliable model selection and assessment in multimodel analysis. Nested sampling estimator (NSE) is a new proposed algorithm for marginal likelihood estimation. The implementation of NSE comprises searching the parameters' space from low likelihood area to high likelihood area gradually, and this evolution is finished iteratively via local sampling procedure. Thus, the efficiency of NSE is dominated by the strength of local sampling procedure. Currently, Metropolis-Hasting (M-H) algorithm and its variants are often used for local sampling in NSE. However, M-H is not an efficient sampling algorithm for high-dimensional or complex likelihood function. For improving the performance of NSE, it could be feasible to integrate more efficient and elaborated sampling algorithm - DREAMzs into the local sampling. In addition, in order to overcome the computation burden problem of large quantity of repeating model executions in marginal likelihood estimation, an adaptive sparse grid stochastic collocation method is used to build the surrogates for original groundwater model.

  11. Random sampling or geostatistical modelling? Choosing between design-based and model-based sampling strategies for soil (with discussion)

    NARCIS (Netherlands)

    Brus, D.J.; Gruijter, de J.J.

    1997-01-01

    Classical sampling theory has been repeatedly identified with classical statistics which assumes that data are identically and independently distributed. This explains the switch of many soil scientists from design-based sampling strategies, based on classical sampling theory, to the model-based

  12. On incomplete sampling under birth-death models and connections to the sampling-based coalescent.

    Science.gov (United States)

    Stadler, Tanja

    2009-11-07

    The constant rate birth-death process is used as a stochastic model for many biological systems, for example phylogenies or disease transmission. As the biological data are usually not fully available, it is crucial to understand the effect of incomplete sampling. In this paper, we analyze the constant rate birth-death process with incomplete sampling. We derive the density of the bifurcation events for trees on n leaves which evolved under this birth-death-sampling process. This density is used for calculating prior distributions in Bayesian inference programs and for efficiently simulating trees. We show that the birth-death-sampling process can be interpreted as a birth-death process with reduced rates and complete sampling. This shows that joint inference of birth rate, death rate and sampling probability is not possible. The birth-death-sampling process is compared to the sampling-based population genetics model, the coalescent. It is shown that despite many similarities between these two models, the distribution of bifurcation times remains different even in the case of very large population sizes. We illustrate these findings on an Hepatitis C virus dataset from Egypt. We show that the transmission times estimates are significantly different-the widely used Gamma statistic even changes its sign from negative to positive when switching from the coalescent to the birth-death process.

  13. Rapid isolation of plutonium in environmental solid samples using sequential injection anion exchange chromatography followed by detection with inductively coupled plasma mass spectrometry

    DEFF Research Database (Denmark)

    Qiao, Jixin; Hou, Xiaolin; Roos, Per

    2011-01-01

    size effect upon the separation efficiency revealed that small-sized (2 mL) columns sufficed to handle up to 50 g of environmental soil samples. Under the optimum conditions, chemical yields of plutonium exceeded 90% and the decontamination factors for uranium, thorium and lead ranged from 103 to 104....... The determination of plutonium isotopes in three standard/certified reference materials (IAEA-375 soil, IAEA-135 sediment and NIST-4359 seaweed) and two reference samples (Irish Sea sediment and Danish soil) revealed a good agreement with reference/certified values. The SI column-separation method...

  14. On Angular Sampling Methods for 3-D Spatial Channel Models

    DEFF Research Database (Denmark)

    Fan, Wei; Jämsä, Tommi; Nielsen, Jesper Ødum

    2015-01-01

    This paper discusses generating three dimensional (3D) spatial channel models with emphasis on the angular sampling methods. Three angular sampling methods, i.e. modified uniform power sampling, modified uniform angular sampling, and random pairing methods are proposed and investigated in detail....... The random pairing method, which uses only twenty sinusoids in the ray-based model for generating the channels, presents good results if the spatial channel cluster is with a small elevation angle spread. For spatial clusters with large elevation angle spreads, however, the random pairing method would fail...... and the other two methods should be considered....

  15. Effects of a combined parent-student alcohol prevention program on intermediate factors and adolescents' drinking behavior: A sequential mediation model.

    Science.gov (United States)

    Koning, Ina M; Maric, Marija; MacKinnon, David; Vollebergh, Wilma A M

    2015-08-01

    Previous work revealed that the combined parent-student alcohol prevention program (PAS) effectively postponed alcohol initiation through its hypothesized intermediate factors: increase in strict parental rule setting and adolescents' self-control (Koning, van den Eijnden, Verdurmen, Engels, & Vollebergh, 2011). This study examines whether the parental strictness precedes an increase in adolescents' self-control by testing a sequential mediation model. A cluster randomized trial including 3,245 Dutch early adolescents (M age = 12.68, SD = 0.50) and their parents randomized over 4 conditions: (1) parent intervention, (2) student intervention, (3) combined intervention, and (4) control group. Outcome measure was amount of weekly drinking measured at age 12 to 15; baseline assessment (T0) and 3 follow-up assessments (T1-T3). Main effects of the combined and parent intervention on weekly drinking at T3 were found. The effect of the combined intervention on weekly drinking (T3) was mediated via an increase in strict rule setting (T1) and adolescents' subsequent self-control (T2). In addition, the indirect effect of the combined intervention via rule setting (T1) was significant. No reciprocal sequential mediation (self-control at T1 prior to rules at T2) was found. The current study is 1 of the few studies reporting sequential mediation effects of youth intervention outcomes. It underscores the need of involving parents in youth alcohol prevention programs, and the need to target both parents and adolescents, so that change in parents' behavior enables change in their offspring. (c) 2015 APA, all rights reserved).

  16. Optimal Sequential Rules for Computer-Based Instruction.

    Science.gov (United States)

    Vos, Hans J.

    1998-01-01

    Formulates sequential rules for adapting the appropriate amount of instruction to learning needs in the context of computer-based instruction. Topics include Bayesian decision theory, threshold and linear-utility structure, psychometric model, optimal sequential number of test questions, and an empirical example of sequential instructional…

  17. Sampling Strategies and Processing of Biobank Tissue Samples from Porcine Biomedical Models.

    Science.gov (United States)

    Blutke, Andreas; Wanke, Rüdiger

    2018-03-06

    In translational medical research, porcine models have steadily become more popular. Considering the high value of individual animals, particularly of genetically modified pig models, and the often-limited number of available animals of these models, establishment of (biobank) collections of adequately processed tissue samples suited for a broad spectrum of subsequent analyses methods, including analyses not specified at the time point of sampling, represent meaningful approaches to take full advantage of the translational value of the model. With respect to the peculiarities of porcine anatomy, comprehensive guidelines have recently been established for standardized generation of representative, high-quality samples from different porcine organs and tissues. These guidelines are essential prerequisites for the reproducibility of results and their comparability between different studies and investigators. The recording of basic data, such as organ weights and volumes, the determination of the sampling locations and of the numbers of tissue samples to be generated, as well as their orientation, size, processing and trimming directions, are relevant factors determining the generalizability and usability of the specimen for molecular, qualitative, and quantitative morphological analyses. Here, an illustrative, practical, step-by-step demonstration of the most important techniques for generation of representative, multi-purpose biobank specimen from porcine tissues is presented. The methods described here include determination of organ/tissue volumes and densities, the application of a volume-weighted systematic random sampling procedure for parenchymal organs by point-counting, determination of the extent of tissue shrinkage related to histological embedding of samples, and generation of randomly oriented samples for quantitative stereological analyses, such as isotropic uniform random (IUR) sections generated by the "Orientator" and "Isector" methods, and vertical

  18. Official Reports: Inventions, useful models, industrial samples, product certificates

    International Nuclear Information System (INIS)

    1994-01-01

    This serial collection presents brief information on patents, useful models, industrial samples, product certificates and trade marks registered in Uzbekistan. They comprise different branches of human activities including peaceful uses of atomic energy. (A.A.D.)

  19. Official Reports: Inventions, useful models, industrial samples, product certificates

    International Nuclear Information System (INIS)

    1996-01-01

    This serial collection presents brief information on patents, useful models, industrial samples, product certificates and trade marks registered in Uzbekistan. They comprise different branches of human activities including peaceful uses of atomic energy. (A.A.D.)

  20. Official Reports: Inventions, useful models, industrial samples, product certificates

    International Nuclear Information System (INIS)

    1995-01-01

    This serial collection presents brief information on patents, useful models, industrial samples, product certificates and trade marks registered in Uzbekistan. They comprise different branches of human activities including peaceful uses of atomic energy. (A.A.D.)

  1. Lab-on-Valve Micro Sequential Injection: A Versatile Approach for Implementing Integrated Sample Pre-preparations and Executing (Bio)Chemical Assays

    DEFF Research Database (Denmark)

    Hansen, Elo Harald

    waste generation. Most recently, the socalled third generation of FIA has emerged, that is, the Lab-on-Valve (LOV) approach, the conceptual basis of which is to incorporate all the necessary unit operational manipulations required, and, when possible, even the detection device into a single small...... integrated microconduit, or “laboratory”, placed atop a selection valve. The lecture will detail the evolution of the three generations of FIA, emphasis being placed on the LOV approach. Proven itself as a versatile front end to a variety of detection techniques, its utility will be exemplified by a series...... of the renewable microcolumn concept. Despite their excellent analytical chemical capabilities, ETAAS as well as ICPMS often require that the samples are subjected to suitable pretreatment in order to obtain the necessary sensitivity and selectivity. Either in order to separate the analyte from potentially...

  2. Lab-on-Valve Micro Sequential Injection: A Versatile Approach for Implementing Integrated Sample Pre-preparations and Executing (Bio)Chemical Assays

    DEFF Research Database (Denmark)

    Hansen, Elo Harald

    waste generation. Most recently, the Lab-on-Valve (LOV) approach has emerged. Termed the third generation of FIA, the conceptual basis of the LOV is to incorporate all the necessary unit operational manipulations required in a chemical assay, and, when possible, even the detection device, into a single...... small integrated microconduit, or “laboratory”, placed atop a selection valve. In the lecture emphasis will be placed on the LOV approach. Proven itself as a versatile front end to a variety of detection techniques, its utility will be exemplified by various applications. Particular focus......-phase microcolumn concept utilising hydrophobic as well as hydrophilic bead materials. Although ETAAS and ICPMS both are characterised by excellent analytical chemical capabilities, they nevertheless often require that the samples be subjected to suitable pretreatment in order to obtain the necessary sensitivity...

  3. Sequential charged particle reaction

    International Nuclear Information System (INIS)

    Hori, Jun-ichi; Ochiai, Kentaro; Sato, Satoshi; Yamauchi, Michinori; Nishitani, Takeo

    2004-01-01

    The effective cross sections for producing the sequential reaction products in F82H, pure vanadium and LiF with respect to the 14.9-MeV neutron were obtained and compared with the estimation ones. Since the sequential reactions depend on the secondary charged particles behavior, the effective cross sections are corresponding to the target nuclei and the material composition. The effective cross sections were also estimated by using the EAF-libraries and compared with the experimental ones. There were large discrepancies between estimated and experimental values. Additionally, we showed the contribution of the sequential reaction on the induced activity and dose rate in the boundary region with water. From the present study, it has been clarified that the sequential reactions are of great importance to evaluate the dose rates around the surface of cooling pipe and the activated corrosion products. (author)

  4. Application of sequential fragmentation/transport theory to deposits of 1723 and 1963-65 eruptions of Volcan Irazu, Costa Rica: positive dispersion case and fractal model

    International Nuclear Information System (INIS)

    Brenes, Jose; Alvarado, Guillermo E.

    2013-01-01

    The theory of Fragmentation and Sequential Transport (FST) was applied to the granulometric analyzes of the deposits from the eruptions of 1723 and 1963-65 of the Volcan Irazu. An appreciable number of cases of positive dispersion was showed, associated in the literature with aggregation processes. A new fractal dimension defined in research has shown to be the product of secondary fragmentation. The application of the new dimension is used in the analyses of the eruptions of 1723 and 1963-65. A fractal model of a volcanic activity is formulated for the first time. The Hurst coefficient and the exponent of the law of powers are incorporated. The existence of values of dissidence near zero have been indicators of an effusive process, as would be the lava pools. The results derived from the model were agreed with field observations. (author) [es

  5. A Unimodal Model for Double Observer Distance Sampling Surveys.

    Directory of Open Access Journals (Sweden)

    Earl F Becker

    Full Text Available Distance sampling is a widely used method to estimate animal population size. Most distance sampling models utilize a monotonically decreasing detection function such as a half-normal. Recent advances in distance sampling modeling allow for the incorporation of covariates into the distance model, and the elimination of the assumption of perfect detection at some fixed distance (usually the transect line with the use of double-observer models. The assumption of full observer independence in the double-observer model is problematic, but can be addressed by using the point independence assumption which assumes there is one distance, the apex of the detection function, where the 2 observers are assumed independent. Aerially collected distance sampling data can have a unimodal shape and have been successfully modeled with a gamma detection function. Covariates in gamma detection models cause the apex of detection to shift depending upon covariate levels, making this model incompatible with the point independence assumption when using double-observer data. This paper reports a unimodal detection model based on a two-piece normal distribution that allows covariates, has only one apex, and is consistent with the point independence assumption when double-observer data are utilized. An aerial line-transect survey of black bears in Alaska illustrate how this method can be applied.

  6. Small Sample Properties of Bayesian Multivariate Autoregressive Time Series Models

    Science.gov (United States)

    Price, Larry R.

    2012-01-01

    The aim of this study was to compare the small sample (N = 1, 3, 5, 10, 15) performance of a Bayesian multivariate vector autoregressive (BVAR-SEM) time series model relative to frequentist power and parameter estimation bias. A multivariate autoregressive model was developed based on correlated autoregressive time series vectors of varying…

  7. Optimizing incomplete sample designs for item response model parameters

    NARCIS (Netherlands)

    van der Linden, Willem J.

    Several models for optimizing incomplete sample designs with respect to information on the item parameters are presented. The following cases are considered: (1) known ability parameters; (2) unknown ability parameters; (3) item sets with multiple ability scales; and (4) response models with

  8. Latent spatial models and sampling design for landscape genetics

    Science.gov (United States)

    Hanks, Ephraim M.; Hooten, Mevin B.; Knick, Steven T.; Oyler-McCance, Sara J.; Fike, Jennifer A.; Cross, Todd B.; Schwartz, Michael K.

    2016-01-01

    We propose a spatially-explicit approach for modeling genetic variation across space and illustrate how this approach can be used to optimize spatial prediction and sampling design for landscape genetic data. We propose a multinomial data model for categorical microsatellite allele data commonly used in landscape genetic studies, and introduce a latent spatial random effect to allow for spatial correlation between genetic observations. We illustrate how modern dimension reduction approaches to spatial statistics can allow for efficient computation in landscape genetic statistical models covering large spatial domains. We apply our approach to propose a retrospective spatial sampling design for greater sage-grouse (Centrocercus urophasianus) population genetics in the western United States.

  9. Impact of multicollinearity on small sample hydrologic regression models

    Science.gov (United States)

    Kroll, Charles N.; Song, Peter

    2013-06-01

    Often hydrologic regression models are developed with ordinary least squares (OLS) procedures. The use of OLS with highly correlated explanatory variables produces multicollinearity, which creates highly sensitive parameter estimators with inflated variances and improper model selection. It is not clear how to best address multicollinearity in hydrologic regression models. Here a Monte Carlo simulation is developed to compare four techniques to address multicollinearity: OLS, OLS with variance inflation factor screening (VIF), principal component regression (PCR), and partial least squares regression (PLS). The performance of these four techniques was observed for varying sample sizes, correlation coefficients between the explanatory variables, and model error variances consistent with hydrologic regional regression models. The negative effects of multicollinearity are magnified at smaller sample sizes, higher correlations between the variables, and larger model error variances (smaller R2). The Monte Carlo simulation indicates that if the true model is known, multicollinearity is present, and the estimation and statistical testing of regression parameters are of interest, then PCR or PLS should be employed. If the model is unknown, or if the interest is solely on model predictions, is it recommended that OLS be employed since using more complicated techniques did not produce any improvement in model performance. A leave-one-out cross-validation case study was also performed using low-streamflow data sets from the eastern United States. Results indicate that OLS with stepwise selection generally produces models across study regions with varying levels of multicollinearity that are as good as biased regression techniques such as PCR and PLS.

  10. An open-population hierarchical distance sampling model

    Science.gov (United States)

    Sollmann, Rachel; Beth Gardner,; Richard B Chandler,; Royle, J. Andrew; T Scott Sillett,

    2015-01-01

    Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for direct estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimate demographic parameters from repeated distance sampling surveys. Using a simulation study motivated by designing a monitoring program for island scrub-jays (Aphelocoma insularis), we investigated the power of this model to detect population trends. We generated temporally autocorrelated abundance and distance sampling data over six surveys, using population rates of change of 0.95 and 0.90. We fit the data generating Markovian model and a mis-specified model with a log-linear time effect on abundance, and derived post hoc trend estimates from a model estimating abundance for each survey separately. We performed these analyses for varying number of survey points. Power to detect population changes was consistently greater under the Markov model than under the alternatives, particularly for reduced numbers of survey points. The model can readily be extended to more complex demographic processes than considered in our simulations. This novel framework can be widely adopted for wildlife population monitoring.

  11. An open-population hierarchical distance sampling model.

    Science.gov (United States)

    Sollmann, Rahel; Gardner, Beth; Chandler, Richard B; Royle, J Andrew; Sillett, T Scott

    2015-02-01

    Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimate demographic parameters from repeated distance sampling surveys. Using a simulation study motivated by designing a monitoring program for Island Scrub-Jays (Aphelocoma insularis), we investigated the power of this model to detect population trends. We generated temporally autocorrelated abundance and distance sampling data over six surveys, using population rates of change of 0.95 and 0.90. We fit the data generating Markovian model and a mis-specified model with a log-linear time effect on abundance, and derived post hoc trend estimates from a model estimating abundance for each survey separately. We performed these analyses for varying numbers of survey points. Power to detect population changes was consistently greater under the Markov model than under the alternatives, particularly for reduced numbers of survey points. The model can readily be extended to more complex demographic processes than considered in our simulations. This novel framework can be widely adopted for wildlife population monitoring.

  12. The attention-weighted sample-size model of visual short-term memory: Attention capture predicts resource allocation and memory load.

    Science.gov (United States)

    Smith, Philip L; Lilburn, Simon D; Corbett, Elaine A; Sewell, David K; Kyllingsbæk, Søren

    2016-09-01

    We investigated the capacity of visual short-term memory (VSTM) in a phase discrimination task that required judgments about the configural relations between pairs of black and white features. Sewell et al. (2014) previously showed that VSTM capacity in an orientation discrimination task was well described by a sample-size model, which views VSTM as a resource comprised of a finite number of noisy stimulus samples. The model predicts the invariance of [Formula: see text] , the sum of squared sensitivities across items, for displays of different sizes. For phase discrimination, the set-size effect significantly exceeded that predicted by the sample-size model for both simultaneously and sequentially presented stimuli. Instead, the set-size effect and the serial position curves with sequential presentation were predicted by an attention-weighted version of the sample-size model, which assumes that one of the items in the display captures attention and receives a disproportionate share of resources. The choice probabilities and response time distributions from the task were well described by a diffusion decision model in which the drift rates embodied the assumptions of the attention-weighted sample-size model. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  13. Graphical models for inference under outcome-dependent sampling

    DEFF Research Database (Denmark)

    Didelez, V; Kreiner, S; Keiding, N

    2010-01-01

    a node for the sampling indicator, assumptions about sampling processes can be made explicit. We demonstrate how to read off such graphs whether consistent estimation of the association between exposure and outcome is possible. Moreover, we give sufficient graphical conditions for testing and estimating......We consider situations where data have been collected such that the sampling depends on the outcome of interest and possibly further covariates, as for instance in case-control studies. Graphical models represent assumptions about the conditional independencies among the variables. By including...

  14. Modelling and sequential simulation of multi-tubular metallic membrane and techno-economics of a hydrogen production process employing thin-layer membrane reactor

    KAUST Repository

    Shafiee, Alireza

    2016-09-24

    A theoretical model for multi-tubular palladium-based membrane is proposed in this paper and validated against experimental data for two different sized membrane modules that operate at high temperatures. The model is used in a sequential simulation format to describe and analyse pure hydrogen and hydrogen binary mixture separations, and then extended to simulate an industrial scale membrane unit. This model is used as a sub-routine within an ASPEN Plus model to simulate a membrane reactor in a steam reforming hydrogen production plant. A techno-economic analysis is then conducted using the validated model for a plant producing 300 TPD of hydrogen. The plant utilises a thin (2.5 μm) defect-free and selective layer (Pd75Ag25 alloy) membrane reactor. The economic sensitivity analysis results show usefulness in finding the optimum operating condition that achieves minimum hydrogen production cost at break-even point. A hydrogen production cost of 1.98 $/kg is estimated while the cost of the thin-layer selective membrane is found to constitute 29% of total process capital cost. These results indicate the competiveness of this thin-layer membrane process against conventional methods of hydrogen production. © 2016 Hydrogen Energy Publications LLC

  15. GENERALISED MODEL BASED CONFIDENCE INTERVALS IN TWO STAGE CLUSTER SAMPLING

    Directory of Open Access Journals (Sweden)

    Christopher Ouma Onyango

    2010-09-01

    Full Text Available Chambers and Dorfman (2002 constructed bootstrap confidence intervals in model based estimation for finite population totals assuming that auxiliary values are available throughout a target population and that the auxiliary values are independent. They also assumed that the cluster sizes are known throughout the target population. We now extend to two stage sampling in which the cluster sizes are known only for the sampled clusters, and we therefore predict the unobserved part of the population total. Jan and Elinor (2008 have done similar work, but unlike them, we use a general model, in which the auxiliary values are not necessarily independent. We demonstrate that the asymptotic properties of our proposed estimator and its coverage rates are better than those constructed under the model assisted local polynomial regression model.

  16. Thermal modeling of core sampling in flammable gas waste tanks. Part 1: Push-mode sampling

    International Nuclear Information System (INIS)

    Unal, C.; Stroh, K.; Pasamehmetoglu, K.O.

    1997-01-01

    The radioactive waste stored in underground storage tanks at Hanford site is routinely being sampled for waste characterization purposes. The push- and rotary-mode core sampling is one of the sampling methods employed. The waste includes mixtures of sodium nitrate and sodium nitrite with organic compounds that can produce violent exothermic reactions if heated above 160 C during core sampling. A self-propagating waste reaction would produce very high temperatures that eventually result in failure of the tank and radioactive material releases to environment. A two-dimensional thermal model based on a lumped finite volume analysis method is developed. The enthalpy of each node is calculated from the first law of thermodynamics. A flash temperature and effective contact area concept were introduced to account the interface temperature rise. No maximum temperature rise exceeding the critical value of 60 C was found in the cases studied for normal operating conditions. Several accident conditions are also examined. In these cases it was found that the maximum drill bit temperature remained below the critical reaction temperature as long as a 30 scfm purge flow is provided the push-mode drill bit during sampling in rotary mode. The failure to provide purge flow resulted in exceeding the limiting temperatures in a relatively short time

  17. Sequential stochastic optimization

    CERN Document Server

    Cairoli, Renzo

    1996-01-01

    Sequential Stochastic Optimization provides mathematicians and applied researchers with a well-developed framework in which stochastic optimization problems can be formulated and solved. Offering much material that is either new or has never before appeared in book form, it lucidly presents a unified theory of optimal stopping and optimal sequential control of stochastic processes. This book has been carefully organized so that little prior knowledge of the subject is assumed; its only prerequisites are a standard graduate course in probability theory and some familiarity with discrete-paramet

  18. Statistical sampling and modelling for cork oak and eucalyptus stands

    NARCIS (Netherlands)

    Paulo, M.J.

    2002-01-01

    This thesis focuses on the use of modern statistical methods to solve problems on sampling, optimal cutting time and agricultural modelling in Portuguese cork oak and eucalyptus stands. The results are contained in five chapters that have been submitted for publication

  19. Soybean yield modeling using bootstrap methods for small samples

    Energy Technology Data Exchange (ETDEWEB)

    Dalposso, G.A.; Uribe-Opazo, M.A.; Johann, J.A.

    2016-11-01

    One of the problems that occur when working with regression models is regarding the sample size; once the statistical methods used in inferential analyzes are asymptotic if the sample is small the analysis may be compromised because the estimates will be biased. An alternative is to use the bootstrap methodology, which in its non-parametric version does not need to guess or know the probability distribution that generated the original sample. In this work we used a set of soybean yield data and physical and chemical soil properties formed with fewer samples to determine a multiple linear regression model. Bootstrap methods were used for variable selection, identification of influential points and for determination of confidence intervals of the model parameters. The results showed that the bootstrap methods enabled us to select the physical and chemical soil properties, which were significant in the construction of the soybean yield regression model, construct the confidence intervals of the parameters and identify the points that had great influence on the estimated parameters. (Author)

  20. A binary logistic regression model with complex sampling design of ...

    African Journals Online (AJOL)

    2017-09-03

    Sep 3, 2017 ... Bi-variable and multi-variable binary logistic regression model with complex sampling design was fitted. .... Data was entered into STATA-12 and analyzed using. SPSS-21. .... lack of access/too far or costs too much. 35. 1.2.

  1. Sampling

    CERN Document Server

    Thompson, Steven K

    2012-01-01

    Praise for the Second Edition "This book has never had a competitor. It is the only book that takes a broad approach to sampling . . . any good personal statistics library should include a copy of this book." —Technometrics "Well-written . . . an excellent book on an important subject. Highly recommended." —Choice "An ideal reference for scientific researchers and other professionals who use sampling." —Zentralblatt Math Features new developments in the field combined with all aspects of obtaining, interpreting, and using sample data Sampling provides an up-to-date treat

  2. Mixed Frequency Data Sampling Regression Models: The R Package midasr

    Directory of Open Access Journals (Sweden)

    Eric Ghysels

    2016-08-01

    Full Text Available When modeling economic relationships it is increasingly common to encounter data sampled at different frequencies. We introduce the R package midasr which enables estimating regression models with variables sampled at different frequencies within a MIDAS regression framework put forward in work by Ghysels, Santa-Clara, and Valkanov (2002. In this article we define a general autoregressive MIDAS regression model with multiple variables of different frequencies and show how it can be specified using the familiar R formula interface and estimated using various optimization methods chosen by the researcher. We discuss how to check the validity of the estimated model both in terms of numerical convergence and statistical adequacy of a chosen regression specification, how to perform model selection based on a information criterion, how to assess forecasting accuracy of the MIDAS regression model and how to obtain a forecast aggregation of different MIDAS regression models. We illustrate the capabilities of the package with a simulated MIDAS regression model and give two empirical examples of application of MIDAS regression.

  3. The redshift distribution of cosmological samples: a forward modeling approach

    Energy Technology Data Exchange (ETDEWEB)

    Herbel, Jörg; Kacprzak, Tomasz; Amara, Adam; Refregier, Alexandre; Bruderer, Claudio; Nicola, Andrina, E-mail: joerg.herbel@phys.ethz.ch, E-mail: tomasz.kacprzak@phys.ethz.ch, E-mail: adam.amara@phys.ethz.ch, E-mail: alexandre.refregier@phys.ethz.ch, E-mail: claudio.bruderer@phys.ethz.ch, E-mail: andrina.nicola@phys.ethz.ch [Institute for Astronomy, Department of Physics, ETH Zürich, Wolfgang-Pauli-Strasse 27, 8093 Zürich (Switzerland)

    2017-08-01

    Determining the redshift distribution n ( z ) of galaxy samples is essential for several cosmological probes including weak lensing. For imaging surveys, this is usually done using photometric redshifts estimated on an object-by-object basis. We present a new approach for directly measuring the global n ( z ) of cosmological galaxy samples, including uncertainties, using forward modeling. Our method relies on image simulations produced using \\textsc(UFig) (Ultra Fast Image Generator) and on ABC (Approximate Bayesian Computation) within the MCCL (Monte-Carlo Control Loops) framework. The galaxy population is modeled using parametric forms for the luminosity functions, spectral energy distributions, sizes and radial profiles of both blue and red galaxies. We apply exactly the same analysis to the real data and to the simulated images, which also include instrumental and observational effects. By adjusting the parameters of the simulations, we derive a set of acceptable models that are statistically consistent with the data. We then apply the same cuts to the simulations that were used to construct the target galaxy sample in the real data. The redshifts of the galaxies in the resulting simulated samples yield a set of n ( z ) distributions for the acceptable models. We demonstrate the method by determining n ( z ) for a cosmic shear like galaxy sample from the 4-band Subaru Suprime-Cam data in the COSMOS field. We also complement this imaging data with a spectroscopic calibration sample from the VVDS survey. We compare our resulting posterior n ( z ) distributions to the one derived from photometric redshifts estimated using 36 photometric bands in COSMOS and find good agreement. This offers good prospects for applying our approach to current and future large imaging surveys.

  4. The redshift distribution of cosmological samples: a forward modeling approach

    Science.gov (United States)

    Herbel, Jörg; Kacprzak, Tomasz; Amara, Adam; Refregier, Alexandre; Bruderer, Claudio; Nicola, Andrina

    2017-08-01

    Determining the redshift distribution n(z) of galaxy samples is essential for several cosmological probes including weak lensing. For imaging surveys, this is usually done using photometric redshifts estimated on an object-by-object basis. We present a new approach for directly measuring the global n(z) of cosmological galaxy samples, including uncertainties, using forward modeling. Our method relies on image simulations produced using \\textsc{UFig} (Ultra Fast Image Generator) and on ABC (Approximate Bayesian Computation) within the MCCL (Monte-Carlo Control Loops) framework. The galaxy population is modeled using parametric forms for the luminosity functions, spectral energy distributions, sizes and radial profiles of both blue and red galaxies. We apply exactly the same analysis to the real data and to the simulated images, which also include instrumental and observational effects. By adjusting the parameters of the simulations, we derive a set of acceptable models that are statistically consistent with the data. We then apply the same cuts to the simulations that were used to construct the target galaxy sample in the real data. The redshifts of the galaxies in the resulting simulated samples yield a set of n(z) distributions for the acceptable models. We demonstrate the method by determining n(z) for a cosmic shear like galaxy sample from the 4-band Subaru Suprime-Cam data in the COSMOS field. We also complement this imaging data with a spectroscopic calibration sample from the VVDS survey. We compare our resulting posterior n(z) distributions to the one derived from photometric redshifts estimated using 36 photometric bands in COSMOS and find good agreement. This offers good prospects for applying our approach to current and future large imaging surveys.

  5. The redshift distribution of cosmological samples: a forward modeling approach

    International Nuclear Information System (INIS)

    Herbel, Jörg; Kacprzak, Tomasz; Amara, Adam; Refregier, Alexandre; Bruderer, Claudio; Nicola, Andrina

    2017-01-01

    Determining the redshift distribution n ( z ) of galaxy samples is essential for several cosmological probes including weak lensing. For imaging surveys, this is usually done using photometric redshifts estimated on an object-by-object basis. We present a new approach for directly measuring the global n ( z ) of cosmological galaxy samples, including uncertainties, using forward modeling. Our method relies on image simulations produced using \\textsc(UFig) (Ultra Fast Image Generator) and on ABC (Approximate Bayesian Computation) within the MCCL (Monte-Carlo Control Loops) framework. The galaxy population is modeled using parametric forms for the luminosity functions, spectral energy distributions, sizes and radial profiles of both blue and red galaxies. We apply exactly the same analysis to the real data and to the simulated images, which also include instrumental and observational effects. By adjusting the parameters of the simulations, we derive a set of acceptable models that are statistically consistent with the data. We then apply the same cuts to the simulations that were used to construct the target galaxy sample in the real data. The redshifts of the galaxies in the resulting simulated samples yield a set of n ( z ) distributions for the acceptable models. We demonstrate the method by determining n ( z ) for a cosmic shear like galaxy sample from the 4-band Subaru Suprime-Cam data in the COSMOS field. We also complement this imaging data with a spectroscopic calibration sample from the VVDS survey. We compare our resulting posterior n ( z ) distributions to the one derived from photometric redshifts estimated using 36 photometric bands in COSMOS and find good agreement. This offers good prospects for applying our approach to current and future large imaging surveys.

  6. Sequential Dependencies in Driving

    Science.gov (United States)

    Doshi, Anup; Tran, Cuong; Wilder, Matthew H.; Mozer, Michael C.; Trivedi, Mohan M.

    2012-01-01

    The effect of recent experience on current behavior has been studied extensively in simple laboratory tasks. We explore the nature of sequential effects in the more naturalistic setting of automobile driving. Driving is a safety-critical task in which delayed response times may have severe consequences. Using a realistic driving simulator, we find…

  7. Mining compressing sequential problems

    NARCIS (Netherlands)

    Hoang, T.L.; Mörchen, F.; Fradkin, D.; Calders, T.G.K.

    2012-01-01

    Compression based pattern mining has been successfully applied to many data mining tasks. We propose an approach based on the minimum description length principle to extract sequential patterns that compress a database of sequences well. We show that mining compressing patterns is NP-Hard and

  8. Image Quality of 3rd Generation Spiral Cranial Dual-Source CT in Combination with an Advanced Model Iterative Reconstruction Technique: A Prospective Intra-Individual Comparison Study to Standard Sequential Cranial CT Using Identical Radiation Dose.

    Science.gov (United States)

    Wenz, Holger; Maros, Máté E; Meyer, Mathias; Förster, Alex; Haubenreisser, Holger; Kurth, Stefan; Schoenberg, Stefan O; Flohr, Thomas; Leidecker, Christianne; Groden, Christoph; Scharf, Johann; Henzler, Thomas

    2015-01-01

    To prospectively intra-individually compare image quality of a 3rd generation Dual-Source-CT (DSCT) spiral cranial CT (cCT) to a sequential 4-slice Multi-Slice-CT (MSCT) while maintaining identical intra-individual radiation dose levels. 35 patients, who had a non-contrast enhanced sequential cCT examination on a 4-slice MDCT within the past 12 months, underwent a spiral cCT scan on a 3rd generation DSCT. CTDIvol identical to initial 4-slice MDCT was applied. Data was reconstructed using filtered backward projection (FBP) and 3rd-generation iterative reconstruction (IR) algorithm at 5 different IR strength levels. Two neuroradiologists independently evaluated subjective image quality using a 4-point Likert-scale and objective image quality was assessed in white matter and nucleus caudatus with signal-to-noise ratios (SNR) being subsequently calculated. Subjective image quality of all spiral cCT datasets was rated significantly higher compared to the 4-slice MDCT sequential acquisitions (pspiral compared to sequential cCT datasets with mean SNR improvement of 61.65% (p*Bonferroni0.05spiral cCT with an advanced model IR technique significantly improves subjective and objective image quality compared to a standard sequential cCT acquisition acquired at identical dose levels.

  9. Sampled-data models for linear and nonlinear systems

    CERN Document Server

    Yuz, Juan I

    2014-01-01

    Sampled-data Models for Linear and Nonlinear Systems provides a fresh new look at a subject with which many researchers may think themselves familiar. Rather than emphasising the differences between sampled-data and continuous-time systems, the authors proceed from the premise that, with modern sampling rates being as high as they are, it is becoming more appropriate to emphasise connections and similarities. The text is driven by three motives: ·      the ubiquity of computers in modern control and signal-processing equipment means that sampling of systems that really evolve continuously is unavoidable; ·      although superficially straightforward, sampling can easily produce erroneous results when not treated properly; and ·      the need for a thorough understanding of many aspects of sampling among researchers and engineers dealing with applications to which they are central. The authors tackle many misconceptions which, although appearing reasonable at first sight, are in fact either p...

  10. The genealogy of samples in models with selection.

    Science.gov (United States)

    Neuhauser, C; Krone, S M

    1997-02-01

    We introduce the genealogy of a random sample of genes taken from a large haploid population that evolves according to random reproduction with selection and mutation. Without selection, the genealogy is described by Kingman's well-known coalescent process. In the selective case, the genealogy of the sample is embedded in a graph with a coalescing and branching structure. We describe this graph, called the ancestral selection graph, and point out differences and similarities with Kingman's coalescent. We present simulations for a two-allele model with symmetric mutation in which one of the alleles has a selective advantage over the other. We find that when the allele frequencies in the population are already in equilibrium, then the genealogy does not differ much from the neutral case. This is supported by rigorous results. Furthermore, we describe the ancestral selection graph for other selective models with finitely many selection classes, such as the K-allele models, infinitely-many-alleles models. DNA sequence models, and infinitely-many-sites models, and briefly discuss the diploid case.

  11. CONSISTENCY UNDER SAMPLING OF EXPONENTIAL RANDOM GRAPH MODELS.

    Science.gov (United States)

    Shalizi, Cosma Rohilla; Rinaldo, Alessandro

    2013-04-01

    The growing availability of network data and of scientific interest in distributed systems has led to the rapid development of statistical models of network structure. Typically, however, these are models for the entire network, while the data consists only of a sampled sub-network. Parameters for the whole network, which is what is of interest, are estimated by applying the model to the sub-network. This assumes that the model is consistent under sampling , or, in terms of the theory of stochastic processes, that it defines a projective family. Focusing on the popular class of exponential random graph models (ERGMs), we show that this apparently trivial condition is in fact violated by many popular and scientifically appealing models, and that satisfying it drastically limits ERGM's expressive power. These results are actually special cases of more general results about exponential families of dependent random variables, which we also prove. Using such results, we offer easily checked conditions for the consistency of maximum likelihood estimation in ERGMs, and discuss some possible constructive responses.

  12. A sample application of nuclear power human resources model

    International Nuclear Information System (INIS)

    Gurgen, A.; Ergun, S.

    2016-01-01

    One of the most important issues for a new comer country initializing the nuclear power plant projects is to have both quantitative and qualitative models for the human resources development. For the quantitative model of human resources development for Turkey, “Nuclear Power Human Resources (NPHR) Model” developed by the Los Alamos National Laboratory was used to determine the number of people that will be required from different professional or occupational fields in the planning of human resources for Akkuyu, Sinop and the third nuclear power plant projects. The number of people required for different professions for the Nuclear Energy Project Implementation Department, the regulatory authority, project companies, construction, nuclear power plants and the academy were calculated. In this study, a sample application of the human resources model is presented. The results of the first tries to calculate the human resources needs of Turkey were obtained. Keywords: Human Resources Development, New Comer Country, NPHR Model

  13. Charge and angular distributions as well as sequential decay and γ-ray emission in heavy ion collisions viewed in the light of the diffusion model

    International Nuclear Information System (INIS)

    Moretto, L.G.

    1977-08-01

    The hierarchy of the collective relaxation times in heavy ion reactions is briefly reviewed. An improved diffusion model is introduced and applied to interpret the fragment Z and angular distributions for some typical reactions. The equilibrium in the neutron-to-proton ratio as well as the sharing of the excitation energy between fragments is studied by a coincidence method which leads to the measurement of the charge, mass and mean number of nucleons emitted by each fragment. The final destiny of the dissipative energy is determined by measuring the atomic number of two coincident fragments, thus obtaining the missing charge as a function of bombarding energy and the Q of the reaction. The sequential fission probability of the heavy recoil is established as a function of the Z and kinetic energy of the light partner. The out-of-plane angular distribution of the fission fragments is correlated with the fissionability and interpreted in terms of various sources of angular momentum misalignment. The γ-ray multiplicities and the γ-ray angular distributions associated with deep inelastic event are discussed in terms of the angular momentum transfer and in terms of the diffusion model

  14. Sampling from stochastic reservoir models constrained by production data

    Energy Technology Data Exchange (ETDEWEB)

    Hegstad, Bjoern Kaare

    1997-12-31

    When a petroleum reservoir is evaluated, it is important to forecast future production of oil and gas and to assess forecast uncertainty. This is done by defining a stochastic model for the reservoir characteristics, generating realizations from this model and applying a fluid flow simulator to the realizations. The reservoir characteristics define the geometry of the reservoir, initial saturation, petrophysical properties etc. This thesis discusses how to generate realizations constrained by production data, that is to say, the realizations should reproduce the observed production history of the petroleum reservoir within the uncertainty of these data. The topics discussed are: (1) Theoretical framework, (2) History matching, forecasting and forecasting uncertainty, (3) A three-dimensional test case, (4) Modelling transmissibility multipliers by Markov random fields, (5) Up scaling, (6) The link between model parameters, well observations and production history in a simple test case, (7) Sampling the posterior using optimization in a hierarchical model, (8) A comparison of Rejection Sampling and Metropolis-Hastings algorithm, (9) Stochastic simulation and conditioning by annealing in reservoir description, and (10) Uncertainty assessment in history matching and forecasting. 139 refs., 85 figs., 1 tab.

  15. Quantum Chemical Examination of the Sequential Halogen Incorporation Scheme for the Modeling of Speciation of I/Br/Cl-Containing Trihalomethanes.

    Science.gov (United States)

    Zhang, Chenyang; Li, Maodong; Han, Xuze; Yan, Mingquan

    2018-02-20

    The recently developed three-step ternary halogenation model interprets the incorporation of chlorine, bromine, and iodine ions into natural organic matter (NOM) and formation of iodine-, bromine-, and chlorine-containing trihalomethanes (THMs) based on the competition of iodine, bromine, and chlorine species at each node of the halogenation sequence. This competition is accounted for using the dimensionless ratios (denoted as γ) of kinetic rates of reactions of the initial attack sites or halogenated intermediates with chlorine, bromine, and iodine ions. However, correlations between the model predictions made and mechanistic aspects of the incorporation of halogen species need to be ascertained in more detail. In this study, quantum chemistry calculations were first used to probe the formation mechanism of 10 species of Cl-/Br-/I- THMs. The HOMO energy (E HOMO ) of each mono-, bi-, or trihalomethanes were calculated by B3LYP method in Gaussian 09 software. Linear correlations were found to exist between the logarithms of experimentally determined kinetic preference coefficients γ reported in prior research and, on the other hand, differences of E HOMO values between brominated/iodinated and chlorinated halomethanes. One notable exception from this trend was that observed for the incorporation of iodine into mono- and di-iodinated intermediates. These observations confirm the three-step halogen incorporation sequence and the factor γ in the statistical model. The combined use of quantum chemistry calculations and the ternary sequential halogenation model provides a new insight into the microscopic nature of NOM-halogen interactions and the trends seen in the behavior of γ factors incorporated in the THM speciation models.

  16. High resolution 2D numerical models from rift to break-up: Crustal hyper-extension, Margin asymmetry, Sequential faulting

    Science.gov (United States)

    Brune, Sascha; Heine, Christian; Pérez-Gussinyé, Marta; Sobolev, Stephan

    2013-04-01

    Numerical modelling is a powerful tool to integrate a multitude of geological and geophysical data while addressing fundamental questions of passive margin formation such as the occurrence of crustal hyper-extension, (a-)symmetries between conjugate margin pairs, and the sometimes significant structural differences between adjacent margin segments. This study utilises knowledge gathered from two key examples of non-magmatic, asymmetric, conjugate margin pairs, i.e. Iberia-New Foundland and Southern Africa-Brazil, where many published seismic lines provide solid knowledge on individual margin geometry. While both margins involve crustal hyper-extension, it is much more pronounced in the South Atlantic. We investigate the evolution of these two margin pairs by carefully constraining our models with detailed plate kinematic history, laboratory-based rheology, and melt fraction evaluation of mantle upwelling. Our experiments are consistent with observed fault patterns, crustal thickness, and basin stratigraphy. We conduct 2D thermomechanical rift models using the finite element code SLIM3D that operates with nonlinear stress- and temperature-dependent elasto-visco-plastic rheology, with parameters provided by laboratory experiments on major crustal and upper mantle rocks. In our models we also calculate the melt fraction within the upwelling asthenosphere, which allows us to control whether the model indeed corresponds to the non-magmatic margin type or not. Our modelling highlights two processes as fundamental for the formation of hyper-extension and margin asymmetry at non-magmatic margins: (1) Strain hardening in the rift center due to cooling of upwelling mantle material (2) The formation of a weak crustal domain adjacent to the rift center caused by localized viscous strain softening and heat transfer from the mantle. Simultaneous activity of both processes promotes lateral rift migration in a continuous way that generates a wide layer of hyper-extended crust on

  17. Random and cooperative sequential adsorption

    Science.gov (United States)

    Evans, J. W.

    1993-10-01

    Irreversible random sequential adsorption (RSA) on lattices, and continuum "car parking" analogues, have long received attention as models for reactions on polymer chains, chemisorption on single-crystal surfaces, adsorption in colloidal systems, and solid state transformations. Cooperative generalizations of these models (CSA) are sometimes more appropriate, and can exhibit richer kinetics and spatial structure, e.g., autocatalysis and clustering. The distribution of filled or transformed sites in RSA and CSA is not described by an equilibrium Gibbs measure. This is the case even for the saturation "jammed" state of models where the lattice or space cannot fill completely. However exact analysis is often possible in one dimension, and a variety of powerful analytic methods have been developed for higher dimensional models. Here we review the detailed understanding of asymptotic kinetics, spatial correlations, percolative structure, etc., which is emerging for these far-from-equilibrium processes.

  18. Forced Sequence Sequential Decoding

    DEFF Research Database (Denmark)

    Jensen, Ole Riis

    In this thesis we describe a new concatenated decoding scheme based on iterations between an inner sequentially decoded convolutional code of rate R=1/4 and memory M=23, and block interleaved outer Reed-Solomon codes with non-uniform profile. With this scheme decoding with good performance...... is possible as low as Eb/No=0.6 dB, which is about 1.7 dB below the signal-to-noise ratio that marks the cut-off rate for the convolutional code. This is possible since the iteration process provides the sequential decoders with side information that allows a smaller average load and minimizes the probability...... of computational overflow. Analytical results for the probability that the first Reed-Solomon word is decoded after C computations are presented. This is supported by simulation results that are also extended to other parameters....

  19. Sequential Power-Dependence Theory

    NARCIS (Netherlands)

    Buskens, Vincent; Rijt, Arnout van de

    2008-01-01

    Existing methods for predicting resource divisions in laboratory exchange networks do not take into account the sequential nature of the experimental setting. We extend network exchange theory by considering sequential exchange. We prove that Sequential Power-Dependence Theory—unlike

  20. Sequential Analysis: Hypothesis Testing and Changepoint Detection

    Science.gov (United States)

    2014-07-11

    maintains the flexibility of deciding sooner than the fixed sample size procedure at the price of some lower power [13, 514]. The sequential probability... markets , detection of signals with unknown arrival time in seismology, navigation, radar and sonar signal processing, speech segmentation, and the... skimming cruise missile can yield a significant increase in the probability of raid annihilation. Furthermore, usually detection systems are

  1. Forced Sequence Sequential Decoding

    DEFF Research Database (Denmark)

    Jensen, Ole Riis; Paaske, Erik

    1998-01-01

    We describe a new concatenated decoding scheme based on iterations between an inner sequentially decoded convolutional code of rate R=1/4 and memory M=23, and block interleaved outer Reed-Solomon (RS) codes with nonuniform profile. With this scheme decoding with good performance is possible as low...... as Eb/N0=0.6 dB, which is about 1.25 dB below the signal-to-noise ratio (SNR) that marks the cutoff rate for the full system. Accounting for about 0.45 dB due to the outer codes, sequential decoding takes place at about 1.7 dB below the SNR cutoff rate for the convolutional code. This is possible since...... the iteration process provides the sequential decoders with side information that allows a smaller average load and minimizes the probability of computational overflow. Analytical results for the probability that the first RS word is decoded after C computations are presented. These results are supported...

  2. Sequential modelling of ICRF wave near RF fields and asymptotic RF sheaths description for AUG ICRF antennas

    Directory of Open Access Journals (Sweden)

    Jacquot Jonathan

    2017-01-01

    Full Text Available A sequence of simulations is performed with RAPLICASOL and SSWICH to compare two AUG ICRF antennas. RAPLICASOL outputs have been used as input to SSWICH-SW for the AUG ICRF antennas. Using parallel electric field maps and the scattering matrix produced by RAPLICASOL, SSWICH-SW, reduced to its asymptotic part, is able to produce a 2D radial/poloidal map of the DC plasma potential accounting for the antenna input settings (total power, power balance, phasing. Two models of antennas are compared: 2-strap antenna vs 3-strap antenna. The 2D DC potential structures are correlated to structures of the parallel electric field map for different phasing and power balance. The overall DC plasma potential on the 3-strap antenna is lower due to better global RF currents compensation. Spatial proximity between regions of high RF electric field and regions where high DC plasma potentials are observed is an important factor for sheath rectification.

  3. Sorption models and their application in environmental samples

    International Nuclear Information System (INIS)

    Kamel, Nariman H.M.

    2008-01-01

    Full text: Naturally occurring radioactive materials (NORM) were found in some environmental soils not high enough to pose problems for human health. The health may be affected by increasing of NORM at some environmental soils. Four soil samples obtained from certain coastal regions in Egypt. Naturally occurring radioactive materials (NORM) of the uranium ( 238 U) series, thorium ( 232 Th) series and the radioactive isotope of potassium ( 40 K) were measured. The soil samples were selected from the situations where the radionuclide concentrations are significantly higher than the average level of other sites. It were chemically analyzed for the uranium, silicon aluminum and iron. The cation exchange capacity (CEC) were determined, it was found lower in the presence of Fe-silicates suggested that Fe-hydroxide had precipitin at the exchangeable edge sites of the clay minerals. The pH of the solid particles at which the net total surface charge is zero was known as the point of zero charge (PZC). The PZC is very important in determining the affinity of the soil samples for different cations and anions. The aim of this work is to determine the natural radiological hazardous of radionuclide at four environmental coastal soil samples in Egypt. The point of zero surface charge was determined using titration tests. Sorption model was developed for this purpose. (author)

  4. Mean-Variance-Validation Technique for Sequential Kriging Metamodels

    International Nuclear Information System (INIS)

    Lee, Tae Hee; Kim, Ho Sung

    2010-01-01

    The rigorous validation of the accuracy of metamodels is an important topic in research on metamodel techniques. Although a leave-k-out cross-validation technique involves a considerably high computational cost, it cannot be used to measure the fidelity of metamodels. Recently, the mean 0 validation technique has been proposed to quantitatively determine the accuracy of metamodels. However, the use of mean 0 validation criterion may lead to premature termination of a sampling process even if the kriging model is inaccurate. In this study, we propose a new validation technique based on the mean and variance of the response evaluated when sequential sampling method, such as maximum entropy sampling, is used. The proposed validation technique is more efficient and accurate than the leave-k-out cross-validation technique, because instead of performing numerical integration, the kriging model is explicitly integrated to accurately evaluate the mean and variance of the response evaluated. The error in the proposed validation technique resembles a root mean squared error, thus it can be used to determine a stop criterion for sequential sampling of metamodels

  5. Modeling and Simulation of a Tethered Harpoon for Comet Sampling

    Science.gov (United States)

    Quadrelli, Marco B.

    2014-01-01

    This paper describes the development of a dynamic model and simulation results of a tethered harpoon for comet sampling. This model and simulation was done in order to carry out an initial sensitivity analysis for key design parameters of the tethered system. The harpoon would contain a canister which would collect a sample of soil from a cometary surface. Both a spring ejected canister and a tethered canister are considered. To arrive in close proximity of the spacecraft at the end of its trajectory so it could be captured, the free-flying canister would need to be ejected at the right time and with the proper impulse, while the tethered canister must be recovered by properly retrieving the tether at a rate that would avoid an excessive amplitude of oscillatory behavior during the retrieval. The paper describes the model of the tether dynamics and harpoon penetration physics. The simulations indicate that, without the tether, the canister would still reach the spacecraft for collection, that the tether retrieval of the canister would be achievable with reasonable fuel consumption, and that the canister amplitude upon retrieval would be insensitive to variations in vertical velocity dispersion.

  6. Comparing interval estimates for small sample ordinal CFA models.

    Science.gov (United States)

    Natesan, Prathiba

    2015-01-01

    Robust maximum likelihood (RML) and asymptotically generalized least squares (AGLS) methods have been recommended for fitting ordinal structural equation models. Studies show that some of these methods underestimate standard errors. However, these studies have not investigated the coverage and bias of interval estimates. An estimate with a reasonable standard error could still be severely biased. This can only be known by systematically investigating the interval estimates. The present study compares Bayesian, RML, and AGLS interval estimates of factor correlations in ordinal confirmatory factor analysis models (CFA) for small sample data. Six sample sizes, 3 factor correlations, and 2 factor score distributions (multivariate normal and multivariate mildly skewed) were studied. Two Bayesian prior specifications, informative and relatively less informative were studied. Undercoverage of confidence intervals and underestimation of standard errors was common in non-Bayesian methods. Underestimated standard errors may lead to inflated Type-I error rates. Non-Bayesian intervals were more positive biased than negatively biased, that is, most intervals that did not contain the true value were greater than the true value. Some non-Bayesian methods had non-converging and inadmissible solutions for small samples and non-normal data. Bayesian empirical standard error estimates for informative and relatively less informative priors were closer to the average standard errors of the estimates. The coverage of Bayesian credibility intervals was closer to what was expected with overcoverage in a few cases. Although some Bayesian credibility intervals were wider, they reflected the nature of statistical uncertainty that comes with the data (e.g., small sample). Bayesian point estimates were also more accurate than non-Bayesian estimates. The results illustrate the importance of analyzing coverage and bias of interval estimates, and how ignoring interval estimates can be misleading

  7. Distinct effects of perceptual quality on auditory word recognition, memory formation and recall in a neural model of sequential memory

    Directory of Open Access Journals (Sweden)

    Paul Miller

    2010-06-01

    Full Text Available Adults with sensory impairment, such as reduced hearing acuity, have impaired ability to recall identifiable words, even when their memory is otherwise normal. We hypothesize that poorer stimulus quality causes weaker activity in neurons responsive to the stimulus and more time to elapse between stimulus onset and identification. The weaker activity and increased delay to stimulus identification reduce the necessary strengthening of connections between neurons active before stimulus presentation and neurons active at the time of stimulus identification. We test our hypothesis through a biologically motivated computational model, which performs item recognition, memory formation and memory retrieval. In our simulations, spiking neurons are distributed into pools representing either items or context, in two separate, but connected winner-takes-all (WTA networks. We include associative, Hebbian learning, by comparing multiple forms of spike-timing dependent plasticity (STDP, which strengthen synapses between coactive neurons during stimulus identification. Synaptic strengthening by STDP can be sufficient to reactivate neurons during recall if their activity during a prior stimulus rose strongly and rapidly. We find that a single poor quality stimulus impairs recall of neighboring stimuli as well as the weak stimulus itself. We demonstrate that within the WTA paradigm of word recognition, reactivation of separate, connected sets of non-word, context cells permits reverse recall. Also, only with such coactive context cells, does slowing the rate of stimulus presentation increase recall probability. We conclude that significant temporal overlap of neural activity patterns, absent from individual WTA networks, is necessary to match behavioral data for word recall.

  8. Correcting Model Fit Criteria for Small Sample Latent Growth Models with Incomplete Data

    Science.gov (United States)

    McNeish, Daniel; Harring, Jeffrey R.

    2017-01-01

    To date, small sample problems with latent growth models (LGMs) have not received the amount of attention in the literature as related mixed-effect models (MEMs). Although many models can be interchangeably framed as a LGM or a MEM, LGMs uniquely provide criteria to assess global data-model fit. However, previous studies have demonstrated poor…

  9. Martian Radiative Transfer Modeling Using the Optimal Spectral Sampling Method

    Science.gov (United States)

    Eluszkiewicz, J.; Cady-Pereira, K.; Uymin, G.; Moncet, J.-L.

    2005-01-01

    The large volume of existing and planned infrared observations of Mars have prompted the development of a new martian radiative transfer model that could be used in the retrievals of atmospheric and surface properties. The model is based on the Optimal Spectral Sampling (OSS) method [1]. The method is a fast and accurate monochromatic technique applicable to a wide range of remote sensing platforms (from microwave to UV) and was originally developed for the real-time processing of infrared and microwave data acquired by instruments aboard the satellites forming part of the next-generation global weather satellite system NPOESS (National Polarorbiting Operational Satellite System) [2]. As part of our on-going research related to the radiative properties of the martian polar caps, we have begun the development of a martian OSS model with the goal of using it to perform self-consistent atmospheric corrections necessary to retrieve caps emissivity from the Thermal Emission Spectrometer (TES) spectra. While the caps will provide the initial focus area for applying the new model, it is hoped that the model will be of interest to the wider Mars remote sensing community.

  10. Thermal modeling of core sampling in flammable gas waste tanks. Part 2: Rotary-mode sampling

    International Nuclear Information System (INIS)

    Unal, C.; Poston, D.; Pasamehmetoglu, K.O.; Witwer, K.S.

    1997-01-01

    The radioactive waste stored in underground storage tanks at Hanford site includes mixtures of sodium nitrate and sodium nitrite with organic compounds. The waste can produce undesired violent exothermic reactions when heated locally during the rotary-mode sampling. Experiments are performed varying the downward force at a maximum rotational speed of 55 rpm and minimum nitrogen purge flow of 30 scfm. The rotary drill bit teeth-face temperatures are measured. The waste is simulated with a low thermal conductivity hard material, pumice blocks. A torque meter is used to determine the energy provided to the drill string. The exhaust air-chip temperature as well as drill string and drill bit temperatures and other key operating parameters were recorded. A two-dimensional thermal model is developed. The safe operating conditions were determined for normal operating conditions. A downward force of 750 at 55 rpm and 30 scfm nitrogen purge flow was found to yield acceptable substrate temperatures. The model predicted experimental results reasonably well. Therefore, it could be used to simulate abnormal conditions to develop procedures for safe operations

  11. The Bacterial Sequential Markov Coalescent.

    Science.gov (United States)

    De Maio, Nicola; Wilson, Daniel J

    2017-05-01

    Bacteria can exchange and acquire new genetic material from other organisms directly and via the environment. This process, known as bacterial recombination, has a strong impact on the evolution of bacteria, for example, leading to the spread of antibiotic resistance across clades and species, and to the avoidance of clonal interference. Recombination hinders phylogenetic and transmission inference because it creates patterns of substitutions (homoplasies) inconsistent with the hypothesis of a single evolutionary tree. Bacterial recombination is typically modeled as statistically akin to gene conversion in eukaryotes, i.e. , using the coalescent with gene conversion (CGC). However, this model can be very computationally demanding as it needs to account for the correlations of evolutionary histories of even distant loci. So, with the increasing popularity of whole genome sequencing, the need has emerged for a faster approach to model and simulate bacterial genome evolution. We present a new model that approximates the coalescent with gene conversion: the bacterial sequential Markov coalescent (BSMC). Our approach is based on a similar idea to the sequential Markov coalescent (SMC)-an approximation of the coalescent with crossover recombination. However, bacterial recombination poses hurdles to a sequential Markov approximation, as it leads to strong correlations and linkage disequilibrium across very distant sites in the genome. Our BSMC overcomes these difficulties, and shows a considerable reduction in computational demand compared to the exact CGC, and very similar patterns in simulated data. We implemented our BSMC model within new simulation software FastSimBac. In addition to the decreased computational demand compared to previous bacterial genome evolution simulators, FastSimBac provides more general options for evolutionary scenarios, allowing population structure with migration, speciation, population size changes, and recombination hotspots. FastSimBac is

  12. Sequential decay of Reggeons

    International Nuclear Information System (INIS)

    Yoshida, Toshihiro

    1981-01-01

    Probabilities of meson production in the sequential decay of Reggeons, which are formed from the projectile and the target in the hadron-hadron to Reggeon-Reggeon processes, are investigated. It is assumed that pair creation of heavy quarks and simultaneous creation of two antiquark-quark pairs are negligible. The leading-order terms with respect to ratio of creation probabilities of anti s s to anti u u (anti d d) are calculated. The production cross sections in the target fragmentation region are given in terms of probabilities in the initial decay of the Reggeons and an effect of manyparticle production. (author)

  13. Automated sequential injection-microcolumn approach with on-line flame atomic absorption spectrometric detection for implementing metal fractionation schemes of homogeneous and non-homogeneous solid samples of environmental interest

    DEFF Research Database (Denmark)

    Chomchoei, Roongrat; Miró, Manuel; Hansen, Elo Harald

    2005-01-01

    spectrometric detection and used for the determination of Cu as a model analyte, the potentials of this novel hyphenated approach are demonstrated by the ability of handling up to 300 mg sample of a nonhomogeneous sewage amended soil (viz., CRM 483). The three steps of the endorsed Standards, Measurements...

  14. Application of a free parameter model to plastic scintillation samples

    Energy Technology Data Exchange (ETDEWEB)

    Tarancon Sanz, Alex, E-mail: alex.tarancon@ub.edu [Departament de Quimica Analitica, Universitat de Barcelona, Diagonal 647, E-08028 Barcelona (Spain); Kossert, Karsten, E-mail: Karsten.Kossert@ptb.de [Physikalisch-Technische Bundesanstalt (PTB), Bundesallee 100, 38116 Braunschweig (Germany)

    2011-08-21

    In liquid scintillation (LS) counting, the CIEMAT/NIST efficiency tracing method and the triple-to-double coincidence ratio (TDCR) method have proved their worth for reliable activity measurements of a number of radionuclides. In this paper, an extended approach to apply a free-parameter model to samples containing a mixture of solid plastic scintillation microspheres and radioactive aqueous solutions is presented. Several beta-emitting radionuclides were measured in a TDCR system at PTB. For the application of the free parameter model, the energy loss in the aqueous phase must be taken into account, since this portion of the particle energy does not contribute to the creation of scintillation light. The energy deposit in the aqueous phase is determined by means of Monte Carlo calculations applying the PENELOPE software package. To this end, great efforts were made to model the geometry of the samples. Finally, a new geometry parameter was defined, which was determined by means of a tracer radionuclide with known activity. This makes the analysis of experimental TDCR data of other radionuclides possible. The deviations between the determined activity concentrations and reference values were found to be lower than 3%. The outcome of this research work is also important for a better understanding of liquid scintillation counting. In particular the influence of (inverse) micelles, i.e. the aqueous spaces embedded in the organic scintillation cocktail, can be investigated. The new approach makes clear that it is important to take the energy loss in the aqueous phase into account. In particular for radionuclides emitting low-energy electrons (e.g. M-Auger electrons from {sup 125}I), this effect can be very important.

  15. Asynchronous Operators of Sequential Logic Venjunction & Sequention

    CERN Document Server

    Vasyukevich, Vadim

    2011-01-01

    This book is dedicated to new mathematical instruments assigned for logical modeling of the memory of digital devices. The case in point is logic-dynamical operation named venjunction and venjunctive function as well as sequention and sequentional function. Venjunction and sequention operate within the framework of sequential logic. In a form of the corresponding equations, they organically fit analytical expressions of Boolean algebra. Thus, a sort of symbiosis is formed using elements of asynchronous sequential logic on the one hand and combinational logic on the other hand. So, asynchronous

  16. Synthetic Aperture Sequential Beamforming

    DEFF Research Database (Denmark)

    Kortbek, Jacob; Jensen, Jørgen Arendt; Gammelmark, Kim Løkke

    2008-01-01

    A synthetic aperture focusing (SAF) technique denoted Synthetic Aperture Sequential Beamforming (SASB) suitable for 2D and 3D imaging is presented. The technique differ from prior art of SAF in the sense that SAF is performed on pre-beamformed data contrary to channel data. The objective is to im......A synthetic aperture focusing (SAF) technique denoted Synthetic Aperture Sequential Beamforming (SASB) suitable for 2D and 3D imaging is presented. The technique differ from prior art of SAF in the sense that SAF is performed on pre-beamformed data contrary to channel data. The objective...... is to improve and obtain a more range independent lateral resolution compared to conventional dynamic receive focusing (DRF) without compromising frame rate. SASB is a two-stage procedure using two separate beamformers. First a set of Bmode image lines using a single focal point in both transmit and receive...... is stored. The second stage applies the focused image lines from the first stage as input data. The SASB method has been investigated using simulations in Field II and by off-line processing of data acquired with a commercial scanner. The performance of SASB with a static image object is compared with DRF...

  17. ACTINIDE REMOVAL PROCESS SAMPLE ANALYSIS, CHEMICAL MODELING, AND FILTRATION EVALUATION

    Energy Technology Data Exchange (ETDEWEB)

    Martino, C.; Herman, D.; Pike, J.; Peters, T.

    2014-06-05

    Filtration within the Actinide Removal Process (ARP) currently limits the throughput in interim salt processing at the Savannah River Site. In this process, batches of salt solution with Monosodium Titanate (MST) sorbent are concentrated by crossflow filtration. The filtrate is subsequently processed to remove cesium in the Modular Caustic Side Solvent Extraction Unit (MCU) followed by disposal in saltstone grout. The concentrated MST slurry is washed and sent to the Defense Waste Processing Facility (DWPF) for vitrification. During recent ARP processing, there has been a degradation of filter performance manifested as the inability to maintain high filtrate flux throughout a multi-batch cycle. The objectives of this effort were to characterize the feed streams, to determine if solids (in addition to MST) are precipitating and causing the degraded performance of the filters, and to assess the particle size and rheological data to address potential filtration impacts. Equilibrium modelling with OLI Analyzer{sup TM} and OLI ESP{sup TM} was performed to determine chemical components at risk of precipitation and to simulate the ARP process. The performance of ARP filtration was evaluated to review potential causes of the observed filter behavior. Task activities for this study included extensive physical and chemical analysis of samples from the Late Wash Pump Tank (LWPT) and the Late Wash Hold Tank (LWHT) within ARP as well as samples of the tank farm feed from Tank 49H. The samples from the LWPT and LWHT were obtained from several stages of processing of Salt Batch 6D, Cycle 6, Batch 16.

  18. Estimation After a Group Sequential Trial.

    Science.gov (United States)

    Milanzi, Elasma; Molenberghs, Geert; Alonso, Ariel; Kenward, Michael G; Tsiatis, Anastasios A; Davidian, Marie; Verbeke, Geert

    2015-10-01

    Group sequential trials are one important instance of studies for which the sample size is not fixed a priori but rather takes one of a finite set of pre-specified values, dependent on the observed data. Much work has been devoted to the inferential consequences of this design feature. Molenberghs et al (2012) and Milanzi et al (2012) reviewed and extended the existing literature, focusing on a collection of seemingly disparate, but related, settings, namely completely random sample sizes, group sequential studies with deterministic and random stopping rules, incomplete data, and random cluster sizes. They showed that the ordinary sample average is a viable option for estimation following a group sequential trial, for a wide class of stopping rules and for random outcomes with a distribution in the exponential family. Their results are somewhat surprising in the sense that the sample average is not optimal, and further, there does not exist an optimal, or even, unbiased linear estimator. However, the sample average is asymptotically unbiased, both conditionally upon the observed sample size as well as marginalized over it. By exploiting ignorability they showed that the sample average is the conventional maximum likelihood estimator. They also showed that a conditional maximum likelihood estimator is finite sample unbiased, but is less efficient than the sample average and has the larger mean squared error. Asymptotically, the sample average and the conditional maximum likelihood estimator are equivalent. This previous work is restricted, however, to the situation in which the the random sample size can take only two values, N = n or N = 2 n . In this paper, we consider the more practically useful setting of sample sizes in a the finite set { n 1 , n 2 , …, n L }. It is shown that the sample average is then a justifiable estimator , in the sense that it follows from joint likelihood estimation, and it is consistent and asymptotically unbiased. We also show why

  19. Modelling microwave heating of discrete samples of oil palm kernels

    International Nuclear Information System (INIS)

    Law, M.C.; Liew, E.L.; Chang, S.L.; Chan, Y.S.; Leo, C.P.

    2016-01-01

    Highlights: • Microwave (MW) drying of oil palm kernels is experimentally determined and modelled. • MW heating of discrete samples of oil palm kernels (OPKs) is simulated. • OPK heating is due to contact effect, MW interference and heat transfer mechanisms. • Electric field vectors circulate within OPKs sample. • Loosely-packed arrangement improves temperature uniformity of OPKs. - Abstract: Recently, microwave (MW) pre-treatment of fresh palm fruits has showed to be environmentally friendly compared to the existing oil palm milling process as it eliminates the condensate production of palm oil mill effluent (POME) in the sterilization process. Moreover, MW-treated oil palm fruits (OPF) also possess better oil quality. In this work, the MW drying kinetic of the oil palm kernels (OPK) was determined experimentally. Microwave heating/drying of oil palm kernels was modelled and validated. The simulation results show that temperature of an OPK is not the same over the entire surface due to constructive and destructive interferences of MW irradiance. The volume-averaged temperature of an OPK is higher than its surface temperature by 3–7 °C, depending on the MW input power. This implies that point measurement of temperature reading is inadequate to determine the temperature history of the OPK during the microwave heating process. The simulation results also show that arrangement of OPKs in a MW cavity affects the kernel temperature profile. The heating of OPKs were identified to be affected by factors such as local electric field intensity due to MW absorption, refraction, interference, the contact effect between kernels and also heat transfer mechanisms. The thermal gradient patterns of OPKs change as the heating continues. The cracking of OPKs is expected to occur first in the core of the kernel and then it propagates to the kernel surface. The model indicates that drying of OPKs is a much slower process compared to its MW heating. The model is useful

  20. Campbell and moment measures for finite sequential spatial processes

    NARCIS (Netherlands)

    M.N.M. van Lieshout (Marie-Colette)

    2006-01-01

    textabstractWe define moment and Campbell measures for sequential spatial processes, prove a Campbell-Mecke theorem, and relate the results to their counterparts in the theory of point processes. In particular, we show that any finite sequential spatial process model can be derived as the vector

  1. Dynamics-based sequential memory: Winnerless competition of patterns

    International Nuclear Information System (INIS)

    Seliger, Philip; Tsimring, Lev S.; Rabinovich, Mikhail I.

    2003-01-01

    We introduce a biologically motivated dynamical principle of sequential memory which is based on winnerless competition (WLC) of event images. This mechanism is implemented in a two-layer neural model of sequential spatial memory. We present the learning dynamics which leads to the formation of a WLC network. After learning, the system is capable of associative retrieval of prerecorded sequences of patterns

  2. Accounting for Heterogeneous Returns in Sequential Schooling Decisions

    NARCIS (Netherlands)

    Zamarro, G.

    2006-01-01

    This paper presents a method for estimating returns to schooling that takes into account that returns may be heterogeneous among agents and that educational decisions are made sequentially.A sequential decision model is interesting because it explicitly considers that the level of education of each

  3. Geostatistical modeling of the gas emission zone and its in-place gas content for Pittsburgh-seam mines using sequential Gaussian simulation

    Science.gov (United States)

    Karacan, C.O.; Olea, R.A.; Goodman, G.

    2012-01-01

    Determination of the size of the gas emission zone, the locations of gas sources within, and especially the amount of gas retained in those zones is one of the most important steps for designing a successful methane control strategy and an efficient ventilation system in longwall coal mining. The formation of the gas emission zone and the potential amount of gas-in-place (GIP) that might be available for migration into a mine are factors of local geology and rock properties that usually show spatial variability in continuity and may also show geometric anisotropy. Geostatistical methods are used here for modeling and prediction of gas amounts and for assessing their associated uncertainty in gas emission zones of longwall mines for methane control.This study used core data obtained from 276 vertical exploration boreholes drilled from the surface to the bottom of the Pittsburgh coal seam in a mining district in the Northern Appalachian basin. After identifying important coal and non-coal layers for the gas emission zone, univariate statistical and semivariogram analyses were conducted for data from different formations to define the distribution and continuity of various attributes. Sequential simulations performed stochastic assessment of these attributes, such as gas content, strata thickness, and strata displacement. These analyses were followed by calculations of gas-in-place and their uncertainties in the Pittsburgh seam caved zone and fractured zone of longwall mines in this mining district. Grid blanking was used to isolate the volume over the actual panels from the entire modeled district and to calculate gas amounts that were directly related to the emissions in longwall mines.Results indicated that gas-in-place in the Pittsburgh seam, in the caved zone and in the fractured zone, as well as displacements in major rock units, showed spatial correlations that could be modeled and estimated using geostatistical methods. This study showed that GIP volumes may

  4. Portal vein ligation is as effective as sequential portal vein and hepatic artery ligation in inducing contralateral liver hypertrophy in a rat model

    NARCIS (Netherlands)

    Veteläinen, Reeta; Dinant, Sander; van Vliet, Arlène; van Gulik, Thomas M.

    2006-01-01

    PURPOSE: Dual embolization of the hepatic artery and portal vein (PV) has been proposed to enhance contralateral liver regeneration before resection. The aim of this study was to evaluate the effect of PV ligation compared with simultaneous or sequential dual ligation on regeneration,

  5. Hybrid nested sampling algorithm for Bayesian model selection applied to inverse subsurface flow problems

    KAUST Repository

    Elsheikh, Ahmed H.; Wheeler, Mary Fanett; Hoteit, Ibrahim

    2014-01-01

    A Hybrid Nested Sampling (HNS) algorithm is proposed for efficient Bayesian model calibration and prior model selection. The proposed algorithm combines, Nested Sampling (NS) algorithm, Hybrid Monte Carlo (HMC) sampling and gradient estimation using

  6. Greedy Sampling and Incremental Surrogate Model-Based Tailoring of Aeroservoelastic Model Database for Flexible Aircraft

    Science.gov (United States)

    Wang, Yi; Pant, Kapil; Brenner, Martin J.; Ouellette, Jeffrey A.

    2018-01-01

    This paper presents a data analysis and modeling framework to tailor and develop linear parameter-varying (LPV) aeroservoelastic (ASE) model database for flexible aircrafts in broad 2D flight parameter space. The Kriging surrogate model is constructed using ASE models at a fraction of grid points within the original model database, and then the ASE model at any flight condition can be obtained simply through surrogate model interpolation. The greedy sampling algorithm is developed to select the next sample point that carries the worst relative error between the surrogate model prediction and the benchmark model in the frequency domain among all input-output channels. The process is iterated to incrementally improve surrogate model accuracy till a pre-determined tolerance or iteration budget is met. The methodology is applied to the ASE model database of a flexible aircraft currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that the proposed method can reduce the number of models in the original database by 67%. Even so the ASE models obtained through Kriging interpolation match the model in the original database constructed directly from the physics-based tool with the worst relative error far below 1%. The interpolated ASE model exhibits continuously-varying gains along a set of prescribed flight conditions. More importantly, the selected grid points are distributed non-uniformly in the parameter space, a) capturing the distinctly different dynamic behavior and its dependence on flight parameters, and b) reiterating the need and utility for adaptive space sampling techniques for ASE model database compaction. The present framework is directly extendible to high-dimensional flight parameter space, and can be used to guide the ASE model development, model order reduction, robust control synthesis and novel vehicle design of flexible aircraft.

  7. Mobility of radionuclides based on sequential extraction of soils

    International Nuclear Information System (INIS)

    Salbu, B.; Oughton, D.H.; Lien, H.N.; Oestby, G.; Strand, P.

    1992-01-01

    Since 1989, core samples of soil and vegetation from semi-natural pastures have been collected at selected sites in Norway during the growing season. The activity concentrations in soil and vegetation as well as transfer coefficients vary significantly between regions, within regions and even within sampling plot areas. In order to differentiate between mobil and inert fractions of radioactive and stable isotopes of Cs and Sr in soils, samples were extracted sequentially using agents with increasing dissolution power. The reproducibility of the sequential extraction technique is good and the data obtained seems most informative. As the distribution pattern for radioactive and stable isotopes of Cs and Sr are similar, a high degree of isotopic exchange is indicated. Based on easily leachable fractions, mobility factors are calculated. In general the mobility of 90 Sr is higher than for 137 Cs. Mobility factors are not significantly influenced by seasonal variations, but a decrease in the mobile fraction in soil with time is indicated. Mobility factors should be considered useful for modelling purposes. (au)

  8. Effects of sample survey design on the accuracy of classification tree models in species distribution models

    Science.gov (United States)

    Thomas C. Edwards; D. Richard Cutler; Niklaus E. Zimmermann; Linda Geiser; Gretchen G. Moisen

    2006-01-01

    We evaluated the effects of probabilistic (hereafter DESIGN) and non-probabilistic (PURPOSIVE) sample surveys on resultant classification tree models for predicting the presence of four lichen species in the Pacific Northwest, USA. Models derived from both survey forms were assessed using an independent data set (EVALUATION). Measures of accuracy as gauged by...

  9. Multilevel sequential Monte Carlo samplers

    KAUST Repository

    Beskos, Alexandros; Jasra, Ajay; Law, Kody; Tempone, Raul; Zhou, Yan

    2016-01-01

    In this article we consider the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods which depend on the step-size level . hL. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretization levels . ∞>h0>h1⋯>hL. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence and a sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. It is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context. That is, relative to exact sampling and Monte Carlo for the distribution at the finest level . hL. The approach is numerically illustrated on a Bayesian inverse problem. © 2016 Elsevier B.V.

  10. Multilevel sequential Monte Carlo samplers

    KAUST Repository

    Beskos, Alexandros

    2016-08-29

    In this article we consider the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods which depend on the step-size level . hL. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretization levels . ∞>h0>h1⋯>hL. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence and a sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. It is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context. That is, relative to exact sampling and Monte Carlo for the distribution at the finest level . hL. The approach is numerically illustrated on a Bayesian inverse problem. © 2016 Elsevier B.V.

  11. Comparing two Poisson populations sequentially: an application

    International Nuclear Information System (INIS)

    Halteman, E.J.

    1986-01-01

    Rocky Flats Plant in Golden, Colorado monitors each of its employees for radiation exposure. Excess exposure is detected by comparing the means of two Poisson populations. A sequential probability ratio test (SPRT) is proposed as a replacement for the fixed sample normal approximation test. A uniformly most efficient SPRT exists, however logistics suggest using a truncated SPRT. The truncated SPRT is evaluated in detail and shown to possess large potential savings in average time spent by employees in the monitoring process

  12. Sequential radioimmunotherapy with 177Lu- and 211At-labeled monoclonal antibody BR96 in a syngeneic rat colon carcinoma model

    DEFF Research Database (Denmark)

    Eriksson, Sophie E; Elgström, Erika; Bäck, Tom

    2014-01-01

    for small, established tumors. A combination of such radionuclides may be successful in regimens of radioimmunotherapy. In this study, rats were treated by sequential administration of first a 177Lu-labeled antibody, followed by a 211At-labeled antibody 25 days later. METHODS: Rats bearing solid colon...... carcinoma tumors were treated with 400 MBq/kg body weight 177Lu-BR96. After 25 days, three groups of animals were given either 5 or 10 MBq/kg body weight of 211At-BR96 simultaneously with or without a blocking agent reducing halogen uptake in normal tissues. Control animals were not given any 211At-BR96....... The rats suffered from reversible myelotoxicity after treatment. CONCLUSIONS: Sequential administration of 177Lu-BR96 and 211At-BR96 resulted in tolerable toxicity providing halogen blocking but did not enhance the therapeutic effect....

  13. Adaptive sequential controller

    Energy Technology Data Exchange (ETDEWEB)

    El-Sharkawi, Mohamed A. (Renton, WA); Xing, Jian (Seattle, WA); Butler, Nicholas G. (Newberg, OR); Rodriguez, Alonso (Pasadena, CA)

    1994-01-01

    An adaptive sequential controller (50/50') for controlling a circuit breaker (52) or other switching device to substantially eliminate transients on a distribution line caused by closing and opening the circuit breaker. The device adaptively compensates for changes in the response time of the circuit breaker due to aging and environmental effects. A potential transformer (70) provides a reference signal corresponding to the zero crossing of the voltage waveform, and a phase shift comparator circuit (96) compares the reference signal to the time at which any transient was produced when the circuit breaker closed, producing a signal indicative of the adaptive adjustment that should be made. Similarly, in controlling the opening of the circuit breaker, a current transformer (88) provides a reference signal that is compared against the time at which any transient is detected when the circuit breaker last opened. An adaptive adjustment circuit (102) produces a compensation time that is appropriately modified to account for changes in the circuit breaker response, including the effect of ambient conditions and aging. When next opened or closed, the circuit breaker is activated at an appropriately compensated time, so that it closes when the voltage crosses zero and opens when the current crosses zero, minimizing any transients on the distribution line. Phase angle can be used to control the opening of the circuit breaker relative to the reference signal provided by the potential transformer.

  14. Adaptive sequential controller

    Science.gov (United States)

    El-Sharkawi, Mohamed A.; Xing, Jian; Butler, Nicholas G.; Rodriguez, Alonso

    1994-01-01

    An adaptive sequential controller (50/50') for controlling a circuit breaker (52) or other switching device to substantially eliminate transients on a distribution line caused by closing and opening the circuit breaker. The device adaptively compensates for changes in the response time of the circuit breaker due to aging and environmental effects. A potential transformer (70) provides a reference signal corresponding to the zero crossing of the voltage waveform, and a phase shift comparator circuit (96) compares the reference signal to the time at which any transient was produced when the circuit breaker closed, producing a signal indicative of the adaptive adjustment that should be made. Similarly, in controlling the opening of the circuit breaker, a current transformer (88) provides a reference signal that is compared against the time at which any transient is detected when the circuit breaker last opened. An adaptive adjustment circuit (102) produces a compensation time that is appropriately modified to account for changes in the circuit breaker response, including the effect of ambient conditions and aging. When next opened or closed, the circuit breaker is activated at an appropriately compensated time, so that it closes when the voltage crosses zero and opens when the current crosses zero, minimizing any transients on the distribution line. Phase angle can be used to control the opening of the circuit breaker relative to the reference signal provided by the potential transformer.

  15. Sensitivity of Mantel Haenszel Model and Rasch Model as Viewed From Sample Size

    OpenAIRE

    ALWI, IDRUS

    2011-01-01

    The aims of this research is to study the sensitivity comparison of Mantel Haenszel and Rasch Model for detection differential item functioning, observed from the sample size. These two differential item functioning (DIF) methods were compared using simulate binary item respon data sets of varying sample size,  200 and 400 examinees were used in the analyses, a detection method of differential item functioning (DIF) based on gender difference. These test conditions were replication 4 tim...

  16. Group sequential designs for stepped-wedge cluster randomised trials.

    Science.gov (United States)

    Grayling, Michael J; Wason, James Ms; Mander, Adrian P

    2017-10-01

    The stepped-wedge cluster randomised trial design has received substantial attention in recent years. Although various extensions to the original design have been proposed, no guidance is available on the design of stepped-wedge cluster randomised trials with interim analyses. In an individually randomised trial setting, group sequential methods can provide notable efficiency gains and ethical benefits. We address this by discussing how established group sequential methodology can be adapted for stepped-wedge designs. Utilising the error spending approach to group sequential trial design, we detail the assumptions required for the determination of stepped-wedge cluster randomised trials with interim analyses. We consider early stopping for efficacy, futility, or efficacy and futility. We describe first how this can be done for any specified linear mixed model for data analysis. We then focus on one particular commonly utilised model and, using a recently completed stepped-wedge cluster randomised trial, compare the performance of several designs with interim analyses to the classical stepped-wedge design. Finally, the performance of a quantile substitution procedure for dealing with the case of unknown variance is explored. We demonstrate that the incorporation of early stopping in stepped-wedge cluster randomised trial designs could reduce the expected sample size under the null and alternative hypotheses by up to 31% and 22%, respectively, with no cost to the trial's type-I and type-II error rates. The use of restricted error maximum likelihood estimation was found to be more important than quantile substitution for controlling the type-I error rate. The addition of interim analyses into stepped-wedge cluster randomised trials could help guard against time-consuming trials conducted on poor performing treatments and also help expedite the implementation of efficacious treatments. In future, trialists should consider incorporating early stopping of some kind into

  17. Quantum Inequalities and Sequential Measurements

    International Nuclear Information System (INIS)

    Candelpergher, B.; Grandouz, T.; Rubinx, J.L.

    2011-01-01

    In this article, the peculiar context of sequential measurements is chosen in order to analyze the quantum specificity in the two most famous examples of Heisenberg and Bell inequalities: Results are found at some interesting variance with customary textbook materials, where the context of initial state re-initialization is described. A key-point of the analysis is the possibility of defining Joint Probability Distributions for sequential random variables associated to quantum operators. Within the sequential context, it is shown that Joint Probability Distributions can be defined in situations where not all of the quantum operators (corresponding to random variables) do commute two by two. (authors)

  18. Sequential Foreign Investments, Regional Technology Platforms and the Evolution of Japanese Multinationals in East Asia

    OpenAIRE

    Song, Jaeyong

    2001-01-01

    IVABSTRACTIn this paper, we investigate the firm-level mechanisms that underlie the sequential foreign direct investment (FDI) decisions of multinational corporations (MNCs). To understand inter-firm heterogeneity in the sequential FDI behaviors of MNCs, we develop a firm capability-based model of sequential FDI decisions. In the setting of Japanese electronics MNCs in East Asia, we empirically examine how prior investments in firm capabilities affect sequential investments into existingprodu...

  19. Uncertainty quantification in Rothermel's Model using an efficient sampling method

    Science.gov (United States)

    Edwin Jimenez; M. Yousuff Hussaini; Scott L. Goodrick

    2007-01-01

    The purpose of the present work is to quantify parametric uncertainty in Rothermel’s wildland fire spread model (implemented in software such as BehavePlus3 and FARSITE), which is undoubtedly among the most widely used fire spread models in the United States. This model consists of a nonlinear system of equations that relates environmental variables (input parameter...

  20. Relativistic electron influence on sanitary-model microorganisms and antibiotics in model samples

    International Nuclear Information System (INIS)

    Antipov, V.S.; Berezhna, I.V.; Kovpik, O.F.; Babych, E.M.; Voliansky, Yu.L.; Sklar, N.I.

    2004-01-01

    A series of the investigations of the electron beam influence on sanitary-model test cultures and antibiotics in model solutions has been carried out. For each of the test objects, the authors have found the boundary doses of the absorbed radiation. The higher doses cause the sharp increase in the bactericidal influence, which becomes complete. The sanitary-bactericidal indices of the water samples remain sable during 6 days. The samples of antibiotics in various concentrations (from 100 UA) have been irradiated. It is proved that the substratum processing by the beam (in the regimes 30 kGy) causes diminution and complete neutralization of the antibacterial activity in all probes of the samples

  1. Framework for sequential approximate optimization

    NARCIS (Netherlands)

    Jacobs, J.H.; Etman, L.F.P.; Keulen, van F.; Rooda, J.E.

    2004-01-01

    An object-oriented framework for Sequential Approximate Optimization (SAO) isproposed. The framework aims to provide an open environment for thespecification and implementation of SAO strategies. The framework is based onthe Python programming language and contains a toolbox of Python

  2. Sequentially pulsed traveling wave accelerator

    Science.gov (United States)

    Caporaso, George J [Livermore, CA; Nelson, Scott D [Patterson, CA; Poole, Brian R [Tracy, CA

    2009-08-18

    A sequentially pulsed traveling wave compact accelerator having two or more pulse forming lines each with a switch for producing a short acceleration pulse along a short length of a beam tube, and a trigger mechanism for sequentially triggering the switches so that a traveling axial electric field is produced along the beam tube in synchronism with an axially traversing pulsed beam of charged particles to serially impart energy to the particle beam.

  3. The use of sequential indicator simulation to characterize geostatistical uncertainty

    International Nuclear Information System (INIS)

    Hansen, K.M.

    1992-10-01

    Sequential indicator simulation (SIS) is a geostatistical technique designed to aid in the characterization of uncertainty about the structure or behavior of natural systems. This report discusses a simulation experiment designed to study the quality of uncertainty bounds generated using SIS. The results indicate that, while SIS may produce reasonable uncertainty bounds in many situations, factors like the number and location of available sample data, the quality of variogram models produced by the user, and the characteristics of the geologic region to be modeled, can all have substantial effects on the accuracy and precision of estimated confidence limits. It is recommended that users of SIS conduct validation studies for the technique on their particular regions of interest before accepting the output uncertainty bounds

  4. Test sample handling apparatus

    International Nuclear Information System (INIS)

    1981-01-01

    A test sample handling apparatus using automatic scintillation counting for gamma detection, for use in such fields as radioimmunoassay, is described. The apparatus automatically and continuously counts large numbers of samples rapidly and efficiently by the simultaneous counting of two samples. By means of sequential ordering of non-sequential counting data, it is possible to obtain precisely ordered data while utilizing sample carrier holders having a minimum length. (U.K.)

  5. inverse gaussian model for small area estimation via gibbs sampling

    African Journals Online (AJOL)

    ADMIN

    For example, MacGibbon and Tomberlin. (1989) have considered estimating small area rates and binomial parameters using empirical Bayes methods. Stroud (1991) used hierarchical Bayes approach for univariate natural exponential families with quadratic variance functions in sample survey applications, while Chaubey ...

  6. Recent advances in importance sampling for statistical model checking

    NARCIS (Netherlands)

    Reijsbergen, D.P.; de Boer, Pieter-Tjerk; Scheinhardt, Willem R.W.; Haverkort, Boudewijn R.H.M.

    2013-01-01

    In the following work we present an overview of recent advances in rare event simulation for model checking made at the University of Twente. The overview is divided into the several model classes for which we propose algorithms, namely multicomponent systems, Markov chains and stochastic Petri

  7. Sequential use of the STICS crop model and of the MACRO pesticide fate model to simulate pesticides leaching in cropping systems.

    Science.gov (United States)

    Lammoglia, Sabine-Karen; Moeys, Julien; Barriuso, Enrique; Larsbo, Mats; Marín-Benito, Jesús-María; Justes, Eric; Alletto, Lionel; Ubertosi, Marjorie; Nicolardot, Bernard; Munier-Jolain, Nicolas; Mamy, Laure

    2017-03-01

    The current challenge in sustainable agriculture is to introduce new cropping systems to reduce pesticides use in order to reduce ground and surface water contamination. However, it is difficult to carry out in situ experiments to assess the environmental impacts of pesticide use for all possible combinations of climate, crop, and soils; therefore, in silico tools are necessary. The objective of this work was to assess pesticides leaching in cropping systems coupling the performances of a crop model (STICS) and of a pesticide fate model (MACRO). STICS-MACRO has the advantage of being able to simulate pesticides fate in complex cropping systems and to consider some agricultural practices such as fertilization, mulch, or crop residues management, which cannot be accounted for with MACRO. The performance of STICS-MACRO was tested, without calibration, from measurements done in two French experimental sites with contrasted soil and climate properties. The prediction of water percolation and pesticides concentrations with STICS-MACRO was satisfactory, but it varied with the pedoclimatic context. The performance of STICS-MACRO was shown to be similar or better than that of MACRO. The improvement of the simulation of crop growth allowed better estimate of crop transpiration therefore of water balance. It also allowed better estimate of pesticide interception by the crop which was found to be crucial for the prediction of pesticides concentrations in water. STICS-MACRO is a new promising tool to improve the assessment of the environmental risks of pesticides used in cropping systems.

  8. Model Complexity and Out-of-Sample Performance: Evidence from S&P 500 Index Returns

    NARCIS (Netherlands)

    Kaeck, Andreas; Rodrigues, Paulo; Seeger, Norman J.

    We apply a range of out-of-sample specification tests to more than forty competing stochastic volatility models to address how model complexity affects out-of-sample performance. Using daily S&P 500 index returns, model confidence set estimations provide strong evidence that the most important model

  9. Ensemble bayesian model averaging using markov chain Monte Carlo sampling

    Energy Technology Data Exchange (ETDEWEB)

    Vrugt, Jasper A [Los Alamos National Laboratory; Diks, Cees G H [NON LANL; Clark, Martyn P [NON LANL

    2008-01-01

    Bayesian model averaging (BMA) has recently been proposed as a statistical method to calibrate forecast ensembles from numerical weather models. Successful implementation of BMA however, requires accurate estimates of the weights and variances of the individual competing models in the ensemble. In their seminal paper (Raftery etal. Mon Weather Rev 133: 1155-1174, 2(05)) has recommended the Expectation-Maximization (EM) algorithm for BMA model training, even though global convergence of this algorithm cannot be guaranteed. In this paper, we compare the performance of the EM algorithm and the recently developed Differential Evolution Adaptive Metropolis (DREAM) Markov Chain Monte Carlo (MCMC) algorithm for estimating the BMA weights and variances. Simulation experiments using 48-hour ensemble data of surface temperature and multi-model stream-flow forecasts show that both methods produce similar results, and that their performance is unaffected by the length of the training data set. However, MCMC simulation with DREAM is capable of efficiently handling a wide variety of BMA predictive distributions, and provides useful information about the uncertainty associated with the estimated BMA weights and variances.

  10. Heat accumulation during sequential cortical bone drilling.

    Science.gov (United States)

    Palmisano, Andrew C; Tai, Bruce L; Belmont, Barry; Irwin, Todd A; Shih, Albert; Holmes, James R

    2016-03-01

    Significant research exists regarding heat production during single-hole bone drilling. No published data exist regarding repetitive sequential drilling. This study elucidates the phenomenon of heat accumulation for sequential drilling with both Kirschner wires (K wires) and standard two-flute twist drills. It was hypothesized that cumulative heat would result in a higher temperature with each subsequent drill pass. Nine holes in a 3 × 3 array were drilled sequentially on moistened cadaveric tibia bone kept at body temperature (about 37 °C). Four thermocouples were placed at the center of four adjacent holes and 2 mm below the surface. A battery-driven hand drill guided by a servo-controlled motion system was used. Six samples were drilled with each tool (2.0 mm K wire and 2.0 and 2.5 mm standard drills). K wire drilling increased temperature from 5 °C at the first hole to 20 °C at holes 6 through 9. A similar trend was found in standard drills with less significant increments. The maximum temperatures of both tools increased from drill sizes was found to be insignificant (P > 0.05). In conclusion, heat accumulated during sequential drilling, with size difference being insignificant. K wire produced more heat than its twist-drill counterparts. This study has demonstrated the heat accumulation phenomenon and its significant effect on temperature. Maximizing the drilling field and reducing the number of drill passes may decrease bone injury. © 2015 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

  11. Sample selection and taste correlation in discrete choice transport modelling

    DEFF Research Database (Denmark)

    Mabit, Stefan Lindhard

    2008-01-01

    explain counterintuitive results in value of travel time estimation. However, the results also point at the difficulty of finding suitable instruments for the selection mechanism. Taste heterogeneity is another important aspect of discrete choice modelling. Mixed logit models are designed to capture...... the question for a broader class of models. It is shown that the original result may be somewhat generalised. Another question investigated is whether mode choice operates as a self-selection mechanism in the estimation of the value of travel time. The results show that self-selection can at least partly...... of taste correlation in willingness-to-pay estimation are presented. The first contribution addresses how to incorporate taste correlation in the estimation of the value of travel time for public transport. Given a limited dataset the approach taken is to use theory on the value of travel time as guidance...

  12. Assessing potential forest and steel inter-industry residue utilisation by sequential chemical extraction

    Energy Technology Data Exchange (ETDEWEB)

    Makela, M.

    2012-10-15

    Traditional process industries in Finland and abroad are facing an emerging waste disposal problem due recent regulatory development which has increased the costs of landfill disposal and difficulty in acquiring new sites. For large manufacturers, such as the forest and ferrous metals industries, symbiotic cooperation of formerly separate industrial sectors could enable the utilisation waste-labeled residues in manufacturing novel residue-derived materials suitable for replacing commercial virgin alternatives. Such efforts would allow transforming the current linear resource use and disposal models to more cyclical ones and thus attain savings in valuable materials and energy resources. The work described in this thesis was aimed at utilising forest and carbon steel industry residues in the experimental manufacture of novel residue-derived materials technically and environmentally suitable for amending agricultural or forest soil properties. Single and sequential chemical extractions were used to compare the pseudo-total concentrations of trace elements in the manufactured amendment samples to relevant Finnish statutory limit values for the use of fertilizer products and to assess respective potential availability under natural conditions. In addition, the quality of analytical work and the suitability of sequential extraction in the analysis of an industrial solid sample were respectively evaluated through the analysis of a certified reference material and by X-ray diffraction of parallel sequential extraction residues. According to the acquired data, the incorporation of both forest and steel industry residues, such as fly ashes, lime wastes, green liquor dregs, sludges and slags, led to amendment liming capacities (34.9-38.3%, Ca equiv., d.w.) comparable to relevant commercial alternatives. Only the first experimental samples showed increased concentrations of pseudo-total cadmium and chromium, of which the latter was specified as the trivalent Cr(III). Based on

  13. Sampling rare fluctuations of height in the Oslo ricepile model

    International Nuclear Information System (INIS)

    Pradhan, Punyabrata; Dhar, Deepak

    2007-01-01

    We describe a new Monte Carlo algorithm for studying large deviations of the height of the pile from its mean value in the Oslo ricepile model. We have used it to generate events which have probabilities of order 10 -1000 . These simulations check our qualitative argument (Pradhan P and Dhar D 2006 Phys. Rev. E 73 021303) that in the steady state of the Oslo ricepile model the probability of large negative height fluctuations Δh = -αL about the mean varies as exp(-κα 4 L 3 ) as L → ∞ with α held fixed and κ > 0

  14. Automation of a dust sampling train | Akinola | Journal of Modeling ...

    African Journals Online (AJOL)

    Journal of Modeling, Design and Management of Engineering Systems. Journal Home · ABOUT THIS JOURNAL · Advanced Search · Current Issue · Archives · Journal Home > Vol 5, No 1 (2007) >. Log in or Register to get access to full text downloads.

  15. Inverse Gaussian model for small area estimation via Gibbs sampling

    African Journals Online (AJOL)

    We present a Bayesian method for estimating small area parameters under an inverse Gaussian model. The method is extended to estimate small area parameters for finite populations. The Gibbs sampler is proposed as a mechanism for implementing the Bayesian paradigm. We illustrate the method by application to ...

  16. Hybrid nested sampling algorithm for Bayesian model selection applied to inverse subsurface flow problems

    International Nuclear Information System (INIS)

    Elsheikh, Ahmed H.; Wheeler, Mary F.; Hoteit, Ibrahim

    2014-01-01

    A Hybrid Nested Sampling (HNS) algorithm is proposed for efficient Bayesian model calibration and prior model selection. The proposed algorithm combines, Nested Sampling (NS) algorithm, Hybrid Monte Carlo (HMC) sampling and gradient estimation using Stochastic Ensemble Method (SEM). NS is an efficient sampling algorithm that can be used for Bayesian calibration and estimating the Bayesian evidence for prior model selection. Nested sampling has the advantage of computational feasibility. Within the nested sampling algorithm, a constrained sampling step is performed. For this step, we utilize HMC to reduce the correlation between successive sampled states. HMC relies on the gradient of the logarithm of the posterior distribution, which we estimate using a stochastic ensemble method based on an ensemble of directional derivatives. SEM only requires forward model runs and the simulator is then used as a black box and no adjoint code is needed. The developed HNS algorithm is successfully applied for Bayesian calibration and prior model selection of several nonlinear subsurface flow problems

  17. Hybrid nested sampling algorithm for Bayesian model selection applied to inverse subsurface flow problems

    Energy Technology Data Exchange (ETDEWEB)

    Elsheikh, Ahmed H., E-mail: aelsheikh@ices.utexas.edu [Institute for Computational Engineering and Sciences (ICES), University of Texas at Austin, TX (United States); Institute of Petroleum Engineering, Heriot-Watt University, Edinburgh EH14 4AS (United Kingdom); Wheeler, Mary F. [Institute for Computational Engineering and Sciences (ICES), University of Texas at Austin, TX (United States); Hoteit, Ibrahim [Department of Earth Sciences and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal (Saudi Arabia)

    2014-02-01

    A Hybrid Nested Sampling (HNS) algorithm is proposed for efficient Bayesian model calibration and prior model selection. The proposed algorithm combines, Nested Sampling (NS) algorithm, Hybrid Monte Carlo (HMC) sampling and gradient estimation using Stochastic Ensemble Method (SEM). NS is an efficient sampling algorithm that can be used for Bayesian calibration and estimating the Bayesian evidence for prior model selection. Nested sampling has the advantage of computational feasibility. Within the nested sampling algorithm, a constrained sampling step is performed. For this step, we utilize HMC to reduce the correlation between successive sampled states. HMC relies on the gradient of the logarithm of the posterior distribution, which we estimate using a stochastic ensemble method based on an ensemble of directional derivatives. SEM only requires forward model runs and the simulator is then used as a black box and no adjoint code is needed. The developed HNS algorithm is successfully applied for Bayesian calibration and prior model selection of several nonlinear subsurface flow problems.

  18. Calibration model maintenance in melamine resin production: Integrating drift detection, smart sample selection and model adaptation.

    Science.gov (United States)

    Nikzad-Langerodi, Ramin; Lughofer, Edwin; Cernuda, Carlos; Reischer, Thomas; Kantner, Wolfgang; Pawliczek, Marcin; Brandstetter, Markus

    2018-07-12

    The physico-chemical properties of Melamine Formaldehyde (MF) based thermosets are largely influenced by the degree of polymerization (DP) in the underlying resin. On-line supervision of the turbidity point by means of vibrational spectroscopy has recently emerged as a promising technique to monitor the DP of MF resins. However, spectroscopic determination of the DP relies on chemometric models, which are usually sensitive to drifts caused by instrumental and/or sample-associated changes occurring over time. In order to detect the time point when drifts start causing prediction bias, we here explore a universal drift detector based on a faded version of the Page-Hinkley (PH) statistic, which we test in three data streams from an industrial MF resin production process. We employ committee disagreement (CD), computed as the variance of model predictions from an ensemble of partial least squares (PLS) models, as a measure for sample-wise prediction uncertainty and use the PH statistic to detect changes in this quantity. We further explore supervised and unsupervised strategies for (semi-)automatic model adaptation upon detection of a drift. For the former, manual reference measurements are requested whenever statistical thresholds on Hotelling's T 2 and/or Q-Residuals are violated. Models are subsequently re-calibrated using weighted partial least squares in order to increase the influence of newer samples, which increases the flexibility when adapting to new (drifted) states. Unsupervised model adaptation is carried out exploiting the dual antecedent-consequent structure of a recently developed fuzzy systems variant of PLS termed FLEXFIS-PLS. In particular, antecedent parts are updated while maintaining the internal structure of the local linear predictors (i.e. the consequents). We found improved drift detection capability of the CD compared to Hotelling's T 2 and Q-Residuals when used in combination with the proposed PH test. Furthermore, we found that active

  19. Remarks on sequential designs in risk assessment

    International Nuclear Information System (INIS)

    Seidenfeld, T.

    1982-01-01

    The special merits of sequential designs are reviewed in light of particular challenges that attend risk assessment for human population. The kinds of ''statistical inference'' are distinguished and the problem of design which is pursued is the clash between Neyman-Pearson and Bayesian programs of sequential design. The value of sequential designs is discussed and the Neyman-Pearson vs. Bayesian sequential designs are probed in particular. Finally, warnings with sequential designs are considered, especially in relation to utilitarianism

  20. Modelling the transuranic contamination in soils by using a generic model and systematic sampling

    International Nuclear Information System (INIS)

    Breitenecker, Katharina; Brandl, Alexander; Bock, Helmut; Villa, Mario

    2008-01-01

    Full text: In the course of the decommissioning the former ASTRA Research Reactor, the Seibersdorf site is to be surveyed for possible contamination by radioactive materials, including transuranium elements. To limit costs due to systematic sampling and time consuming laboratory analyses, a mathematical model that describes the migration of transuranium elements and that includes the local topography of the area where deposition has occurred, was established.The project basis is to find a mathematical function that determines the contamination by modelling the pathways of transuranium elements. The model approach chosen is cellular automata (CA). For this purpose, a hypothetical activity of transuranium elements is released on the ground in the centre of a simulated area. Under the assumption that migration of these elements only takes place by diffusion, transport and sorption, their equations are modelled in the CA-model by a simple discretization for the existing problem. To include local topography, most of the simulated area consists of a green corridor, where migration proceeds quite slowly; streets, where the migrational behaviour is different, and migration velocities in ditches are also modelled. The Migration of three different plutonium isotopes ( 238P u, 239+240P u, 241P u), the migration of one americium isotope ( 241A m), the radioactive decay of 241P u via 241A m to 237N p and the radioactive decay of 238P u to 234U were considered in this model. Due to the special modelling approach of CA, the physical necessity of conservation of the amount of substance is always fulfilled. The entire system was implemented in MATLAB. Systematic sampling onto a featured test site, followed by detailed laboratory analyses were done to compare the underlying CA-model to real data. On this account a nuclide vector with 241A m as the reference nuclide was established. As long as the initial parameters (e.g. meteorological data) are well known, the model describes the

  1. Assessing Exhaustiveness of Stochastic Sampling for Integrative Modeling of Macromolecular Structures.

    Science.gov (United States)

    Viswanath, Shruthi; Chemmama, Ilan E; Cimermancic, Peter; Sali, Andrej

    2017-12-05

    Modeling of macromolecular structures involves structural sampling guided by a scoring function, resulting in an ensemble of good-scoring models. By necessity, the sampling is often stochastic, and must be exhaustive at a precision sufficient for accurate modeling and assessment of model uncertainty. Therefore, the very first step in analyzing the ensemble is an estimation of the highest precision at which the sampling is exhaustive. Here, we present an objective and automated method for this task. As a proxy for sampling exhaustiveness, we evaluate whether two independently and stochastically generated sets of models are sufficiently similar. The protocol includes testing 1) convergence of the model score, 2) whether model scores for the two samples were drawn from the same parent distribution, 3) whether each structural cluster includes models from each sample proportionally to its size, and 4) whether there is sufficient structural similarity between the two model samples in each cluster. The evaluation also provides the sampling precision, defined as the smallest clustering threshold that satisfies the third, most stringent test. We validate the protocol with the aid of enumerated good-scoring models for five illustrative cases of binary protein complexes. Passing the proposed four tests is necessary, but not sufficient for thorough sampling. The protocol is general in nature and can be applied to the stochastic sampling of any set of models, not just structural models. In addition, the tests can be used to stop stochastic sampling as soon as exhaustiveness at desired precision is reached, thereby improving sampling efficiency; they may also help in selecting a model representation that is sufficiently detailed to be informative, yet also sufficiently coarse for sampling to be exhaustive. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  2. Sequential extraction of uranium metal contamination

    International Nuclear Information System (INIS)

    Murry, M.M.; Spitz, H.B.; Connick, W.B.

    2016-01-01

    Samples of uranium contaminated dirt collected from the dirt floor of an abandoned metal rolling mill were analyzed for uranium using a sequential extraction protocol involving a series of five increasingly aggressive solvents. The quantity of uranium extracted from the contaminated dirt by each reagent can aid in predicting the fate and transport of the uranium contamination in the environment. Uranium was separated from each fraction using anion exchange, electrodeposition and analyzed by alpha spectroscopy analysis. Results demonstrate that approximately 77 % of the uranium was extracted using NH 4 Ac in 25 % acetic acid. (author)

  3. Rasch-modeling the Portuguese SOCRATES in a clinical sample.

    Science.gov (United States)

    Lopes, Paulo; Prieto, Gerardo; Delgado, Ana R; Gamito, Pedro; Trigo, Hélder

    2010-06-01

    The Stages of Change Readiness and Treatment Eagerness Scale (SOCRATES) assesses motivation for treatment in the drug-dependent population. The development of adequate measures of motivation is needed in order to properly understand the role of this construct in rehabilitation. This study probed the psychometric properties of the SOCRATES in the Portuguese population by means of the Rasch Rating Scale Model, which allows the conjoint measurement of items and persons. The participants were 166 substance abusers under treatment for their addiction. Results show that the functioning of the five response categories is not optimal; our re-analysis indicates that a three-category system is the most appropriate one. By using this response category system, both model fit and estimation accuracy are improved. The discussion takes into account other factors such as item format and content in order to make suggestions for the development of better motivation-for-treatment scales. (PsycINFO Database Record (c) 2010 APA, all rights reserved).

  4. Sequential flavor symmetry breaking

    International Nuclear Information System (INIS)

    Feldmann, Thorsten; Jung, Martin; Mannel, Thomas

    2009-01-01

    The gauge sector of the standard model exhibits a flavor symmetry that allows for independent unitary transformations of the fermion multiplets. In the standard model the flavor symmetry is broken by the Yukawa couplings to the Higgs boson, and the resulting fermion masses and mixing angles show a pronounced hierarchy. In this work we connect the observed hierarchy to a sequence of intermediate effective theories, where the flavor symmetries are broken in a stepwise fashion by vacuum expectation values of suitably constructed spurion fields. We identify the possible scenarios in the quark sector and discuss some implications of this approach.

  5. Sequential flavor symmetry breaking

    Science.gov (United States)

    Feldmann, Thorsten; Jung, Martin; Mannel, Thomas

    2009-08-01

    The gauge sector of the standard model exhibits a flavor symmetry that allows for independent unitary transformations of the fermion multiplets. In the standard model the flavor symmetry is broken by the Yukawa couplings to the Higgs boson, and the resulting fermion masses and mixing angles show a pronounced hierarchy. In this work we connect the observed hierarchy to a sequence of intermediate effective theories, where the flavor symmetries are broken in a stepwise fashion by vacuum expectation values of suitably constructed spurion fields. We identify the possible scenarios in the quark sector and discuss some implications of this approach.

  6. Sequential versus simultaneous market delineation

    DEFF Research Database (Denmark)

    Haldrup, Niels; Møllgaard, Peter; Kastberg Nielsen, Claus

    2005-01-01

    and geographical markets. Using a unique data setfor prices of Norwegian and Scottish salmon, we propose a methodologyfor simultaneous market delineation and we demonstrate that comparedto a sequential approach conclusions will be reversed.JEL: C3, K21, L41, Q22Keywords: Relevant market, econometric delineation......Delineation of the relevant market forms a pivotal part of most antitrustcases. The standard approach is sequential. First the product marketis delineated, then the geographical market is defined. Demand andsupply substitution in both the product dimension and the geographicaldimension...

  7. Sequential logic analysis and synthesis

    CERN Document Server

    Cavanagh, Joseph

    2007-01-01

    Until now, there was no single resource for actual digital system design. Using both basic and advanced concepts, Sequential Logic: Analysis and Synthesis offers a thorough exposition of the analysis and synthesis of both synchronous and asynchronous sequential machines. With 25 years of experience in designing computing equipment, the author stresses the practical design of state machines. He clearly delineates each step of the structured and rigorous design principles that can be applied to practical applications. The book begins by reviewing the analysis of combinatorial logic and Boolean a

  8. Comparison of Sequential and Variational Data Assimilation

    Science.gov (United States)

    Alvarado Montero, Rodolfo; Schwanenberg, Dirk; Weerts, Albrecht

    2017-04-01

    Data assimilation is a valuable tool to improve model state estimates by combining measured observations with model simulations. It has recently gained significant attention due to its potential in using remote sensing products to improve operational hydrological forecasts and for reanalysis purposes. This has been supported by the application of sequential techniques such as the Ensemble Kalman Filter which require no additional features within the modeling process, i.e. it can use arbitrary black-box models. Alternatively, variational techniques rely on optimization algorithms to minimize a pre-defined objective function. This function describes the trade-off between the amount of noise introduced into the system and the mismatch between simulated and observed variables. While sequential techniques have been commonly applied to hydrological processes, variational techniques are seldom used. In our believe, this is mainly attributed to the required computation of first order sensitivities by algorithmic differentiation techniques and related model enhancements, but also to lack of comparison between both techniques. We contribute to filling this gap and present the results from the assimilation of streamflow data in two basins located in Germany and Canada. The assimilation introduces noise to precipitation and temperature to produce better initial estimates of an HBV model. The results are computed for a hindcast period and assessed using lead time performance metrics. The study concludes with a discussion of the main features of each technique and their advantages/disadvantages in hydrological applications.

  9. Generalized infimum and sequential product of quantum effects

    International Nuclear Information System (INIS)

    Li Yuan; Sun Xiuhong; Chen Zhengli

    2007-01-01

    The quantum effects for a physical system can be described by the set E(H) of positive operators on a complex Hilbert space H that are bounded above by the identity operator I. For A, B(set-membership sign)E(H), the operation of sequential product A(convolution sign)B=A 1/2 BA 1/2 was proposed as a model for sequential quantum measurements. A nice investigation of properties of the sequential product has been carried over [Gudder, S. and Nagy, G., 'Sequential quantum measurements', J. Math. Phys. 42, 5212 (2001)]. In this note, we extend some results of this reference. In particular, a gap in the proof of Theorem 3.2 in this reference is overcome. In addition, some properties of generalized infimum A sqcap B are studied

  10. Group-sequential analysis may allow for early trial termination

    DEFF Research Database (Denmark)

    Gerke, Oke; Vilstrup, Mie H; Halekoh, Ulrich

    2017-01-01

    BACKGROUND: Group-sequential testing is widely used in pivotal therapeutic, but rarely in diagnostic research, although it may save studies, time, and costs. The purpose of this paper was to demonstrate a group-sequential analysis strategy in an intra-observer study on quantitative FDG-PET/CT mea......BACKGROUND: Group-sequential testing is widely used in pivotal therapeutic, but rarely in diagnostic research, although it may save studies, time, and costs. The purpose of this paper was to demonstrate a group-sequential analysis strategy in an intra-observer study on quantitative FDG...... assumed to be normally distributed, and sequential one-sided hypothesis tests on the population standard deviation of the differences against a hypothesised value of 1.5 were performed, employing an alpha spending function. The fixed-sample analysis (N = 45) was compared with the group-sequential analysis...... strategies comprising one (at N = 23), two (at N = 15, 30), or three interim analyses (at N = 11, 23, 34), respectively, which were defined post hoc. RESULTS: When performing interim analyses with one third and two thirds of patients, sufficient agreement could be concluded after the first interim analysis...

  11. Multilevel sequential Monte-Carlo samplers

    KAUST Repository

    Jasra, Ajay

    2016-01-01

    Multilevel Monte-Carlo methods provide a powerful computational technique for reducing the computational cost of estimating expectations for a given computational effort. They are particularly relevant for computational problems when approximate distributions are determined via a resolution parameter h, with h=0 giving the theoretical exact distribution (e.g. SDEs or inverse problems with PDEs). The method provides a benefit by coupling samples from successive resolutions, and estimating differences of successive expectations. We develop a methodology that brings Sequential Monte-Carlo (SMC) algorithms within the framework of the Multilevel idea, as SMC provides a natural set-up for coupling samples over different resolutions. We prove that the new algorithm indeed preserves the benefits of the multilevel principle, even if samples at all resolutions are now correlated.

  12. Multilevel sequential Monte-Carlo samplers

    KAUST Repository

    Jasra, Ajay

    2016-01-05

    Multilevel Monte-Carlo methods provide a powerful computational technique for reducing the computational cost of estimating expectations for a given computational effort. They are particularly relevant for computational problems when approximate distributions are determined via a resolution parameter h, with h=0 giving the theoretical exact distribution (e.g. SDEs or inverse problems with PDEs). The method provides a benefit by coupling samples from successive resolutions, and estimating differences of successive expectations. We develop a methodology that brings Sequential Monte-Carlo (SMC) algorithms within the framework of the Multilevel idea, as SMC provides a natural set-up for coupling samples over different resolutions. We prove that the new algorithm indeed preserves the benefits of the multilevel principle, even if samples at all resolutions are now correlated.

  13. Evaluation Using Sequential Trials Methods.

    Science.gov (United States)

    Cohen, Mark E.; Ralls, Stephen A.

    1986-01-01

    Although dental school faculty as well as practitioners are interested in evaluating products and procedures used in clinical practice, research design and statistical analysis can sometimes pose problems. Sequential trials methods provide an analytical structure that is both easy to use and statistically valid. (Author/MLW)

  14. A Relational Account of Call-by-Value Sequentiality

    DEFF Research Database (Denmark)

    Riecke, Jon Gary; Sandholm, Anders Bo

    2002-01-01

    We construct a model for FPC, a purely functional, sequential, call-by-value language. The model is built from partial continuous functions, in the style of Plotkin, further constrained to be uniform with respect to a class of logical relations. We prove that the model is fully abstract....

  15. Time scale of random sequential adsorption.

    Science.gov (United States)

    Erban, Radek; Chapman, S Jonathan

    2007-04-01

    A simple multiscale approach to the diffusion-driven adsorption from a solution to a solid surface is presented. The model combines two important features of the adsorption process: (i) The kinetics of the chemical reaction between adsorbing molecules and the surface and (ii) geometrical constraints on the surface made by molecules which are already adsorbed. The process (i) is modeled in a diffusion-driven context, i.e., the conditional probability of adsorbing a molecule provided that the molecule hits the surface is related to the macroscopic surface reaction rate. The geometrical constraint (ii) is modeled using random sequential adsorption (RSA), which is the sequential addition of molecules at random positions on a surface; one attempt to attach a molecule is made per one RSA simulation time step. By coupling RSA with the diffusion of molecules in the solution above the surface the RSA simulation time step is related to the real physical time. The method is illustrated on a model of chemisorption of reactive polymers to a virus surface.

  16. How does observation uncertainty influence which stream water samples are most informative for model calibration?

    Science.gov (United States)

    Wang, Ling; van Meerveld, Ilja; Seibert, Jan

    2016-04-01

    Streamflow isotope samples taken during rainfall-runoff events are very useful for multi-criteria model calibration because they can help decrease parameter uncertainty and improve internal model consistency. However, the number of samples that can be collected and analysed is often restricted by practical and financial constraints. It is, therefore, important to choose an appropriate sampling strategy and to obtain samples that have the highest information content for model calibration. We used the Birkenes hydrochemical model and synthetic rainfall, streamflow and isotope data to explore which samples are most informative for model calibration. Starting with error-free observations, we investigated how many samples are needed to obtain a certain model fit. Based on different parameter sets, representing different catchments, and different rainfall events, we also determined which sampling times provide the most informative data for model calibration. Our results show that simulation performance for models calibrated with the isotopic data from two intelligently selected samples was comparable to simulations based on isotopic data for all 100 time steps. The models calibrated with the intelligently selected samples also performed better than the model calibrations with two benchmark sampling strategies (random selection and selection based on hydrologic information). Surprisingly, samples on the rising limb and at the peak were less informative than expected and, generally, samples taken at the end of the event were most informative. The timing of the most informative samples depends on the proportion of different flow components (baseflow, slow response flow, fast response flow and overflow). For events dominated by baseflow and slow response flow, samples taken at the end of the event after the fast response flow has ended were most informative; when the fast response flow was dominant, samples taken near the peak were most informative. However when overflow

  17. A Bayesian sequential processor approach to spectroscopic portal system decisions

    Energy Technology Data Exchange (ETDEWEB)

    Sale, K; Candy, J; Breitfeller, E; Guidry, B; Manatt, D; Gosnell, T; Chambers, D

    2007-07-31

    The development of faster more reliable techniques to detect radioactive contraband in a portal type scenario is an extremely important problem especially in this era of constant terrorist threats. Towards this goal the development of a model-based, Bayesian sequential data processor for the detection problem is discussed. In the sequential processor each datum (detector energy deposit and pulse arrival time) is used to update the posterior probability distribution over the space of model parameters. The nature of the sequential processor approach is that a detection is produced as soon as it is statistically justified by the data rather than waiting for a fixed counting interval before any analysis is performed. In this paper the Bayesian model-based approach, physics and signal processing models and decision functions are discussed along with the first results of our research.

  18. Decoding restricted participation in sequential electricity markets

    Energy Technology Data Exchange (ETDEWEB)

    Knaut, Andreas; Paschmann, Martin

    2017-06-15

    Restricted participation in sequential markets may cause high price volatility and welfare losses. In this paper we therefore analyze the drivers of restricted participation in the German intraday auction which is a short-term electricity market with quarter-hourly products. Applying a fundamental electricity market model with 15-minute temporal resolution, we identify the lack of sub-hourly market coupling being the most relevant driver of restricted participation. We derive a proxy for price volatility and find that full market coupling may trigger quarter-hourly price volatility to decrease by a factor close to four.

  19. From sequential to parallel programming with patterns

    CERN Document Server

    CERN. Geneva

    2018-01-01

    To increase in both performance and efficiency, our programming models need to adapt to better exploit modern processors. The classic idioms and patterns for programming such as loops, branches or recursion are the pillars of almost every code and are well known among all programmers. These patterns all have in common that they are sequential in nature. Embracing parallel programming patterns, which allow us to program for multi- and many-core hardware in a natural way, greatly simplifies the task of designing a program that scales and performs on modern hardware, independently of the used programming language, and in a generic way.

  20. A note on exponential dispersion models which are invariant under length-biased sampling

    NARCIS (Netherlands)

    Bar-Lev, S.K.; van der Duyn Schouten, F.A.

    2003-01-01

    Length-biased sampling situations may occur in clinical trials, reliability, queueing models, survival analysis and population studies where a proper sampling frame is absent.In such situations items are sampled at rate proportional to their length so that larger values of the quantity being

  1. On a Robust MaxEnt Process Regression Model with Sample-Selection

    Directory of Open Access Journals (Sweden)

    Hea-Jung Kim

    2018-04-01

    Full Text Available In a regression analysis, a sample-selection bias arises when a dependent variable is partially observed as a result of the sample selection. This study introduces a Maximum Entropy (MaxEnt process regression model that assumes a MaxEnt prior distribution for its nonparametric regression function and finds that the MaxEnt process regression model includes the well-known Gaussian process regression (GPR model as a special case. Then, this special MaxEnt process regression model, i.e., the GPR model, is generalized to obtain a robust sample-selection Gaussian process regression (RSGPR model that deals with non-normal data in the sample selection. Various properties of the RSGPR model are established, including the stochastic representation, distributional hierarchy, and magnitude of the sample-selection bias. These properties are used in the paper to develop a hierarchical Bayesian methodology to estimate the model. This involves a simple and computationally feasible Markov chain Monte Carlo algorithm that avoids analytical or numerical derivatives of the log-likelihood function of the model. The performance of the RSGPR model in terms of the sample-selection bias correction, robustness to non-normality, and prediction, is demonstrated through results in simulations that attest to its good finite-sample performance.

  2. A simple homogeneous model for regular and irregular metallic wire media samples

    Science.gov (United States)

    Kosulnikov, S. Y.; Mirmoosa, M. S.; Simovski, C. R.

    2018-02-01

    To simplify the solution of electromagnetic problems with wire media samples, it is reasonable to treat them as the samples of a homogeneous material without spatial dispersion. The account of spatial dispersion implies additional boundary conditions and makes the solution of boundary problems difficult especially if the sample is not an infinitely extended layer. Moreover, for a novel type of wire media - arrays of randomly tilted wires - a spatially dispersive model has not been developed. Here, we introduce a simplistic heuristic model of wire media samples shaped as bricks. Our model covers WM of both regularly and irregularly stretched wires.

  3. Optimal Selection of the Sampling Interval for Estimation of Modal Parameters by an ARMA- Model

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning

    1993-01-01

    Optimal selection of the sampling interval for estimation of the modal parameters by an ARMA-model for a white noise loaded structure modelled as a single degree of- freedom linear mechanical system is considered. An analytical solution for an optimal uniform sampling interval, which is optimal...

  4. Application of the Tripartite Model to a Complicated Sample of Residential Youth with Externalizing Problems

    Science.gov (United States)

    Chin, Eu Gene; Ebesutani, Chad; Young, John

    2013-01-01

    The tripartite model of anxiety and depression has received strong support among child and adolescent populations. Clinical samples of children and adolescents in these studies, however, have usually been referred for treatment of anxiety and depression. This study investigated the fit of the tripartite model with a complicated sample of…

  5. GY SAMPLING THEORY AND GEOSTATISTICS: ALTERNATE MODELS OF VARIABILITY IN CONTINUOUS MEDIA

    Science.gov (United States)

    In the sampling theory developed by Pierre Gy, sample variability is modeled as the sum of a set of seven discrete error components. The variogram used in geostatisties provides an alternate model in which several of Gy's error components are combined in a continuous mode...

  6. Using Set Covering with Item Sampling to Analyze the Infeasibility of Linear Programming Test Assembly Models

    Science.gov (United States)

    Huitzing, Hiddo A.

    2004-01-01

    This article shows how set covering with item sampling (SCIS) methods can be used in the analysis and preanalysis of linear programming models for test assembly (LPTA). LPTA models can construct tests, fulfilling a set of constraints set by the test assembler. Sometimes, no solution to the LPTA model exists. The model is then said to be…

  7. Multi-agent sequential hypothesis testing

    KAUST Repository

    Kim, Kwang-Ki K.; Shamma, Jeff S.

    2014-01-01

    incorporate costs of taking private/public measurements, costs of time-difference and disagreement in actions of agents, and costs of false declaration/choices in the sequential hypothesis testing. The corresponding sequential decision processes have well

  8. A Bayesian Theory of Sequential Causal Learning and Abstract Transfer.

    Science.gov (United States)

    Lu, Hongjing; Rojas, Randall R; Beckers, Tom; Yuille, Alan L

    2016-03-01

    Two key research issues in the field of causal learning are how people acquire causal knowledge when observing data that are presented sequentially, and the level of abstraction at which learning takes place. Does sequential causal learning solely involve the acquisition of specific cause-effect links, or do learners also acquire knowledge about abstract causal constraints? Recent empirical studies have revealed that experience with one set of causal cues can dramatically alter subsequent learning and performance with entirely different cues, suggesting that learning involves abstract transfer, and such transfer effects involve sequential presentation of distinct sets of causal cues. It has been demonstrated that pre-training (or even post-training) can modulate classic causal learning phenomena such as forward and backward blocking. To account for these effects, we propose a Bayesian theory of sequential causal learning. The theory assumes that humans are able to consider and use several alternative causal generative models, each instantiating a different causal integration rule. Model selection is used to decide which integration rule to use in a given learning environment in order to infer causal knowledge from sequential data. Detailed computer simulations demonstrate that humans rely on the abstract characteristics of outcome variables (e.g., binary vs. continuous) to select a causal integration rule, which in turn alters causal learning in a variety of blocking and overshadowing paradigms. When the nature of the outcome variable is ambiguous, humans select the model that yields the best fit with the recent environment, and then apply it to subsequent learning tasks. Based on sequential patterns of cue-outcome co-occurrence, the theory can account for a range of phenomena in sequential causal learning, including various blocking effects, primacy effects in some experimental conditions, and apparently abstract transfer of causal knowledge. Copyright © 2015

  9. Automatic synthesis of sequential control schemes

    International Nuclear Information System (INIS)

    Klein, I.

    1993-01-01

    Of all hard- and software developed for industrial control purposes, the majority is devoted to sequential, or binary valued, control and only a minor part to classical linear control. Typically, the sequential parts of the controller are invoked during startup and shut-down to bring the system into its normal operating region and into some safe standby region, respectively. Despite its importance, fairly little theoretical research has been devoted to this area, and sequential control programs are therefore still created manually without much theoretical support to obtain a systematic approach. We propose a method to create sequential control programs automatically. The main ideas is to spend some effort off-line modelling the plant, and from this model generate the control strategy, that is the plan. The plant is modelled using action structures, thereby concentrating on the actions instead of the states of the plant. In general the planning problem shows exponential complexity in the number of state variables. However, by focusing on the actions, we can identify problem classes as well as algorithms such that the planning complexity is reduced to polynomial complexity. We prove that these algorithms are sound, i.e., the generated solution will solve the stated problem, and complete, i.e., if the algorithms fail, then no solution exists. The algorithms generate a plan as a set of actions and a partial order on this set specifying the execution order. The generated plant is proven to be minimal and maximally parallel. For a larger class of problems we propose a method to split the original problem into a number of simple problems that can each be solved using one of the presented algorithms. It is also shown how a plan can be translated into a GRAFCET chart, and to illustrate these ideas we have implemented a planing tool, i.e., a system that is able to automatically create control schemes. Such a tool can of course also be used on-line if it is fast enough. This

  10. Estimating species – area relationships by modeling abundance and frequency subject to incomplete sampling

    Science.gov (United States)

    Yamaura, Yuichi; Connor, Edward F.; Royle, Andy; Itoh, Katsuo; Sato, Kiyoshi; Taki, Hisatomo; Mishima, Yoshio

    2016-01-01

    Models and data used to describe species–area relationships confound sampling with ecological process as they fail to acknowledge that estimates of species richness arise due to sampling. This compromises our ability to make ecological inferences from and about species–area relationships. We develop and illustrate hierarchical community models of abundance and frequency to estimate species richness. The models we propose separate sampling from ecological processes by explicitly accounting for the fact that sampled patches are seldom completely covered by sampling plots and that individuals present in the sampling plots are imperfectly detected. We propose a multispecies abundance model in which community assembly is treated as the summation of an ensemble of species-level Poisson processes and estimate patch-level species richness as a derived parameter. We use sampling process models appropriate for specific survey methods. We propose a multispecies frequency model that treats the number of plots in which a species occurs as a binomial process. We illustrate these models using data collected in surveys of early-successional bird species and plants in young forest plantation patches. Results indicate that only mature forest plant species deviated from the constant density hypothesis, but the null model suggested that the deviations were too small to alter the form of species–area relationships. Nevertheless, results from simulations clearly show that the aggregate pattern of individual species density–area relationships and occurrence probability–area relationships can alter the form of species–area relationships. The plant community model estimated that only half of the species present in the regional species pool were encountered during the survey. The modeling framework we propose explicitly accounts for sampling processes so that ecological processes can be examined free of sampling artefacts. Our modeling approach is extensible and could be applied

  11. Robustness of the Sequential Lineup Advantage

    Science.gov (United States)

    Gronlund, Scott D.; Carlson, Curt A.; Dailey, Sarah B.; Goodsell, Charles A.

    2009-01-01

    A growing movement in the United States and around the world involves promoting the advantages of conducting an eyewitness lineup in a sequential manner. We conducted a large study (N = 2,529) that included 24 comparisons of sequential versus simultaneous lineups. A liberal statistical criterion revealed only 2 significant sequential lineup…

  12. Sequential Probability Ration Tests : Conservative and Robust

    NARCIS (Netherlands)

    Kleijnen, J.P.C.; Shi, Wen

    2017-01-01

    In practice, most computers generate simulation outputs sequentially, so it is attractive to analyze these outputs through sequential statistical methods such as sequential probability ratio tests (SPRTs). We investigate several SPRTs for choosing between two hypothesized values for the mean output

  13. Effects of sample size on estimates of population growth rates calculated with matrix models.

    Directory of Open Access Journals (Sweden)

    Ian J Fiske

    Full Text Available BACKGROUND: Matrix models are widely used to study the dynamics and demography of populations. An important but overlooked issue is how the number of individuals sampled influences estimates of the population growth rate (lambda calculated with matrix models. Even unbiased estimates of vital rates do not ensure unbiased estimates of lambda-Jensen's Inequality implies that even when the estimates of the vital rates are accurate, small sample sizes lead to biased estimates of lambda due to increased sampling variance. We investigated if sampling variability and the distribution of sampling effort among size classes lead to biases in estimates of lambda. METHODOLOGY/PRINCIPAL FINDINGS: Using data from a long-term field study of plant demography, we simulated the effects of sampling variance by drawing vital rates and calculating lambda for increasingly larger populations drawn from a total population of 3842 plants. We then compared these estimates of lambda with those based on the entire population and calculated the resulting bias. Finally, we conducted a review of the literature to determine the sample sizes typically used when parameterizing matrix models used to study plant demography. CONCLUSIONS/SIGNIFICANCE: We found significant bias at small sample sizes when survival was low (survival = 0.5, and that sampling with a more-realistic inverse J-shaped population structure exacerbated this bias. However our simulations also demonstrate that these biases rapidly become negligible with increasing sample sizes or as survival increases. For many of the sample sizes used in demographic studies, matrix models are probably robust to the biases resulting from sampling variance of vital rates. However, this conclusion may depend on the structure of populations or the distribution of sampling effort in ways that are unexplored. We suggest more intensive sampling of populations when individual survival is low and greater sampling of stages with high

  14. Effects of sample size on estimates of population growth rates calculated with matrix models.

    Science.gov (United States)

    Fiske, Ian J; Bruna, Emilio M; Bolker, Benjamin M

    2008-08-28

    Matrix models are widely used to study the dynamics and demography of populations. An important but overlooked issue is how the number of individuals sampled influences estimates of the population growth rate (lambda) calculated with matrix models. Even unbiased estimates of vital rates do not ensure unbiased estimates of lambda-Jensen's Inequality implies that even when the estimates of the vital rates are accurate, small sample sizes lead to biased estimates of lambda due to increased sampling variance. We investigated if sampling variability and the distribution of sampling effort among size classes lead to biases in estimates of lambda. Using data from a long-term field study of plant demography, we simulated the effects of sampling variance by drawing vital rates and calculating lambda for increasingly larger populations drawn from a total population of 3842 plants. We then compared these estimates of lambda with those based on the entire population and calculated the resulting bias. Finally, we conducted a review of the literature to determine the sample sizes typically used when parameterizing matrix models used to study plant demography. We found significant bias at small sample sizes when survival was low (survival = 0.5), and that sampling with a more-realistic inverse J-shaped population structure exacerbated this bias. However our simulations also demonstrate that these biases rapidly become negligible with increasing sample sizes or as survival increases. For many of the sample sizes used in demographic studies, matrix models are probably robust to the biases resulting from sampling variance of vital rates. However, this conclusion may depend on the structure of populations or the distribution of sampling effort in ways that are unexplored. We suggest more intensive sampling of populations when individual survival is low and greater sampling of stages with high elasticities.

  15. Sequential Analysis of Metals in Municipal Dumpsite Composts of ...

    African Journals Online (AJOL)

    ... Ni) in Municipal dumpsite compost were determined by the sequential extraction method. Chemical parameters such as pH, conductivity, and organic carbon contents of the samples were also determined. Analysis of the extracts was carried out by atomic absorption spectrophotometer machine (Buck Scientific VPG 210).

  16. Mining Emerging Sequential Patterns for Activity Recognition in Body Sensor Networks

    DEFF Research Database (Denmark)

    Gu, Tao; Wang, Liang; Chen, Hanhua

    2010-01-01

    Body Sensor Networks oer many applications in healthcare, well-being and entertainment. One of the emerging applications is recognizing activities of daily living. In this paper, we introduce a novel knowledge pattern named Emerging Sequential Pattern (ESP)|a sequential pattern that discovers...... signicant class dierences|to recognize both simple (i.e., sequential) and complex (i.e., interleaved and concurrent) activities. Based on ESPs, we build our complex activity models directly upon the sequential model to recognize both activity types. We conduct comprehensive empirical studies to evaluate...

  17. Network Model-Assisted Inference from Respondent-Driven Sampling Data.

    Science.gov (United States)

    Gile, Krista J; Handcock, Mark S

    2015-06-01

    Respondent-Driven Sampling is a widely-used method for sampling hard-to-reach human populations by link-tracing over their social networks. Inference from such data requires specialized techniques because the sampling process is both partially beyond the control of the researcher, and partially implicitly defined. Therefore, it is not generally possible to directly compute the sampling weights for traditional design-based inference, and likelihood inference requires modeling the complex sampling process. As an alternative, we introduce a model-assisted approach, resulting in a design-based estimator leveraging a working network model. We derive a new class of estimators for population means and a corresponding bootstrap standard error estimator. We demonstrate improved performance compared to existing estimators, including adjustment for an initial convenience sample. We also apply the method and an extension to the estimation of HIV prevalence in a high-risk population.

  18. Network Model-Assisted Inference from Respondent-Driven Sampling Data

    Science.gov (United States)

    Gile, Krista J.; Handcock, Mark S.

    2015-01-01

    Summary Respondent-Driven Sampling is a widely-used method for sampling hard-to-reach human populations by link-tracing over their social networks. Inference from such data requires specialized techniques because the sampling process is both partially beyond the control of the researcher, and partially implicitly defined. Therefore, it is not generally possible to directly compute the sampling weights for traditional design-based inference, and likelihood inference requires modeling the complex sampling process. As an alternative, we introduce a model-assisted approach, resulting in a design-based estimator leveraging a working network model. We derive a new class of estimators for population means and a corresponding bootstrap standard error estimator. We demonstrate improved performance compared to existing estimators, including adjustment for an initial convenience sample. We also apply the method and an extension to the estimation of HIV prevalence in a high-risk population. PMID:26640328

  19. An automatic system for acidity determination based on sequential injection titration and the monosegmented flow approach.

    Science.gov (United States)

    Kozak, Joanna; Wójtowicz, Marzena; Gawenda, Nadzieja; Kościelniak, Paweł

    2011-06-15

    An automatic sequential injection system, combining monosegmented flow analysis, sequential injection analysis and sequential injection titration is proposed for acidity determination. The system enables controllable sample dilution and generation of standards of required concentration in a monosegmented sequential injection manner, sequential injection titration of the prepared solutions, data collecting, and handling. It has been tested on spectrophotometric determination of acetic, citric and phosphoric acids with sodium hydroxide used as a titrant and phenolphthalein or thymolphthalein (in the case of phosphoric acid determination) as indicators. Accuracy better than |4.4|% (RE) and repeatability better than 2.9% (RSD) have been obtained. It has been applied to the determination of total acidity in vinegars and various soft drinks. The system provides low sample (less than 0.3 mL) consumption. On average, analysis of a sample takes several minutes. Copyright © 2011 Elsevier B.V. All rights reserved.

  20. Making Career Decisions--A Sequential Elimination Approach.

    Science.gov (United States)

    Gati, Itamar

    1986-01-01

    Presents a model for career decision making based on the sequential elimination of occupational alternatives, an adaptation for career decisions of Tversky's (1972) elimination-by-aspects theory of choice. The expected utility approach is reviewed as a representative compensatory model for career decisions. Advantages, disadvantages, and…

  1. Sequential Computerized Mastery Tests--Three Simulation Studies

    Science.gov (United States)

    Wiberg, Marie

    2006-01-01

    A simulation study of a sequential computerized mastery test is carried out with items modeled with the 3 parameter logistic item response theory model. The examinees' responses are either identically distributed, not identically distributed, or not identically distributed together with estimation errors in the item characteristics. The…

  2. [Outlier sample discriminating methods for building calibration model in melons quality detecting using NIR spectra].

    Science.gov (United States)

    Tian, Hai-Qing; Wang, Chun-Guang; Zhang, Hai-Jun; Yu, Zhi-Hong; Li, Jian-Kang

    2012-11-01

    Outlier samples strongly influence the precision of the calibration model in soluble solids content measurement of melons using NIR Spectra. According to the possible sources of outlier samples, three methods (predicted concentration residual test; Chauvenet test; leverage and studentized residual test) were used to discriminate these outliers respectively. Nine suspicious outliers were detected from calibration set which including 85 fruit samples. Considering the 9 suspicious outlier samples maybe contain some no-outlier samples, they were reclaimed to the model one by one to see whether they influence the model and prediction precision or not. In this way, 5 samples which were helpful to the model joined in calibration set again, and a new model was developed with the correlation coefficient (r) 0. 889 and root mean square errors for calibration (RMSEC) 0.6010 Brix. For 35 unknown samples, the root mean square errors prediction (RMSEP) was 0.854 degrees Brix. The performance of this model was more better than that developed with non outlier was eliminated from calibration set (r = 0.797, RMSEC= 0.849 degrees Brix, RMSEP = 1.19 degrees Brix), and more representative and stable with all 9 samples were eliminated from calibration set (r = 0.892, RMSEC = 0.605 degrees Brix, RMSEP = 0.862 degrees).

  3. The pursuit of balance in sequential randomized trials

    Directory of Open Access Journals (Sweden)

    Raymond P. Guiteras

    2016-06-01

    Full Text Available In many randomized trials, subjects enter the sample sequentially. Because the covariates for all units are not known in advance, standard methods of stratification do not apply. We describe and assess the method of DA-optimal sequential allocation (Atkinson, 1982 for balancing stratification covariates across treatment arms. We provide simulation evidence that the method can provide substantial improvements in precision over commonly employed alternatives. We also describe our experience implementing the method in a field trial of a clean water and handwashing intervention in Dhaka, Bangladesh, the first time the method has been used. We provide advice and software for future researchers.

  4. An exploratory sequential design to validate measures of moral emotions.

    Science.gov (United States)

    Márquez, Margarita G; Delgado, Ana R

    2017-05-01

    This paper presents an exploratory and sequential mixed methods approach in validating measures of knowledge of the moral emotions of contempt, anger and disgust. The sample comprised 60 participants in the qualitative phase when a measurement instrument was designed. Item stems, response options and correction keys were planned following the results obtained in a descriptive phenomenological analysis of the interviews. In the quantitative phase, the scale was used with a sample of 102 Spanish participants, and the results were analysed with the Rasch model. In the qualitative phase, salient themes included reasons, objects and action tendencies. In the quantitative phase, good psychometric properties were obtained. The model fit was adequate. However, some changes had to be made to the scale in order to improve the proportion of variance explained. Substantive and methodological im-plications of this mixed-methods study are discussed. Had the study used a single re-search method in isolation, aspects of the global understanding of contempt, anger and disgust would have been lost.

  5. Sample size calculation to externally validate scoring systems based on logistic regression models.

    Directory of Open Access Journals (Sweden)

    Antonio Palazón-Bru

    Full Text Available A sample size containing at least 100 events and 100 non-events has been suggested to validate a predictive model, regardless of the model being validated and that certain factors can influence calibration of the predictive model (discrimination, parameterization and incidence. Scoring systems based on binary logistic regression models are a specific type of predictive model.The aim of this study was to develop an algorithm to determine the sample size for validating a scoring system based on a binary logistic regression model and to apply it to a case study.The algorithm was based on bootstrap samples in which the area under the ROC curve, the observed event probabilities through smooth curves, and a measure to determine the lack of calibration (estimated calibration index were calculated. To illustrate its use for interested researchers, the algorithm was applied to a scoring system, based on a binary logistic regression model, to determine mortality in intensive care units.In the case study provided, the algorithm obtained a sample size with 69 events, which is lower than the value suggested in the literature.An algorithm is provided for finding the appropriate sample size to validate scoring systems based on binary logistic regression models. This could be applied to determine the sample size in other similar cases.

  6. A fully blanketed early B star LTE model atmosphere using an opacity sampling technique

    International Nuclear Information System (INIS)

    Phillips, A.P.; Wright, S.L.

    1980-01-01

    A fully blanketed LTE model of a stellar atmosphere with Tsub(e) = 21914 K (thetasub(e) = 0.23), log g = 4 is presented. The model includes an explicit representation of the opacity due to the strongest lines, and uses a statistical opacity sampling technique to represent the weaker line opacity. The sampling technique is subjected to several tests and the model is compared with an atmosphere calculated using the line-distribution function method. The limitations of the distribution function method and the particular opacity sampling method used here are discussed in the light of the results obtained. (author)

  7. The Importance of Pressure Sampling Frequency in Models for Determination of Critical Wave Loadingson Monolithic Structures

    DEFF Research Database (Denmark)

    Burcharth, Hans F.; Andersen, Thomas Lykke; Meinert, Palle

    2008-01-01

    This paper discusses the influence of wave load sampling frequency on calculated sliding distance in an overall stability analysis of a monolithic caisson. It is demonstrated by a specific example of caisson design that for this kind of analyses the sampling frequency in a small scale model could...... be as low as 100 Hz in model scale. However, for design of structure elements like the wave wall on the top of a caisson the wave load sampling frequency must be much higher, in the order of 1000 Hz in the model. Elastic-plastic deformations of foundation and structure were not included in the analysis....

  8. Lexical decoder for continuous speech recognition: sequential neural network approach

    International Nuclear Information System (INIS)

    Iooss, Christine

    1991-01-01

    The work presented in this dissertation concerns the study of a connectionist architecture to treat sequential inputs. In this context, the model proposed by J.L. Elman, a recurrent multilayers network, is used. Its abilities and its limits are evaluated. Modifications are done in order to treat erroneous or noisy sequential inputs and to classify patterns. The application context of this study concerns the realisation of a lexical decoder for analytical multi-speakers continuous speech recognition. Lexical decoding is completed from lattices of phonemes which are obtained after an acoustic-phonetic decoding stage relying on a K Nearest Neighbors search technique. Test are done on sentences formed from a lexicon of 20 words. The results are obtained show the ability of the proposed connectionist model to take into account the sequentiality at the input level, to memorize the context and to treat noisy or erroneous inputs. (author) [fr

  9. Hybrid nested sampling algorithm for Bayesian model selection applied to inverse subsurface flow problems

    KAUST Repository

    Elsheikh, Ahmed H.

    2014-02-01

    A Hybrid Nested Sampling (HNS) algorithm is proposed for efficient Bayesian model calibration and prior model selection. The proposed algorithm combines, Nested Sampling (NS) algorithm, Hybrid Monte Carlo (HMC) sampling and gradient estimation using Stochastic Ensemble Method (SEM). NS is an efficient sampling algorithm that can be used for Bayesian calibration and estimating the Bayesian evidence for prior model selection. Nested sampling has the advantage of computational feasibility. Within the nested sampling algorithm, a constrained sampling step is performed. For this step, we utilize HMC to reduce the correlation between successive sampled states. HMC relies on the gradient of the logarithm of the posterior distribution, which we estimate using a stochastic ensemble method based on an ensemble of directional derivatives. SEM only requires forward model runs and the simulator is then used as a black box and no adjoint code is needed. The developed HNS algorithm is successfully applied for Bayesian calibration and prior model selection of several nonlinear subsurface flow problems. © 2013 Elsevier Inc.

  10. A simple approach to power and sample size calculations in logistic regression and Cox regression models.

    Science.gov (United States)

    Vaeth, Michael; Skovlund, Eva

    2004-06-15

    For a given regression problem it is possible to identify a suitably defined equivalent two-sample problem such that the power or sample size obtained for the two-sample problem also applies to the regression problem. For a standard linear regression model the equivalent two-sample problem is easily identified, but for generalized linear models and for Cox regression models the situation is more complicated. An approximately equivalent two-sample problem may, however, also be identified here. In particular, we show that for logistic regression and Cox regression models the equivalent two-sample problem is obtained by selecting two equally sized samples for which the parameters differ by a value equal to the slope times twice the standard deviation of the independent variable and further requiring that the overall expected number of events is unchanged. In a simulation study we examine the validity of this approach to power calculations in logistic regression and Cox regression models. Several different covariate distributions are considered for selected values of the overall response probability and a range of alternatives. For the Cox regression model we consider both constant and non-constant hazard rates. The results show that in general the approach is remarkably accurate even in relatively small samples. Some discrepancies are, however, found in small samples with few events and a highly skewed covariate distribution. Comparison with results based on alternative methods for logistic regression models with a single continuous covariate indicates that the proposed method is at least as good as its competitors. The method is easy to implement and therefore provides a simple way to extend the range of problems that can be covered by the usual formulas for power and sample size determination. Copyright 2004 John Wiley & Sons, Ltd.

  11. Sequential Injection Determination of D-Glucose by Chemiluminescence Using an Open Tubular Immobilised Enzyme Reactor

    DEFF Research Database (Denmark)

    Liu, Xuezhu; Hansen, Elo Harald

    1996-01-01

    A sequential injection analysis system is described that incorporates a nylon tubular reactor containing immobilised glucose oxidase, allowing determination of D-glucose by means of subsequent luminol chemiluminescence detection of the hydrogen peroxide generated in the enzymatic reaction....... The operating parameters were optimised by fractional factorial screening and response surface modelling. The linear range of D-glucose determination was 30-600 mu M, With a detection limit of 15 mu M using a photodiode detector. The sampling frequency was 54 h(-1). Lower LOD (0.5 mu M D-glucose) could...

  12. Reliability Evaluation of Distribution System Considering Sequential Characteristics of Distributed Generation

    Directory of Open Access Journals (Sweden)

    Sheng Wanxing

    2016-01-01

    Full Text Available In allusion to the randomness of output power of distributed generation (DG, a reliability evaluation model based on sequential Monte Carlo simulation (SMCS for distribution system with DG is proposed. Operating states of the distribution system can be sampled by SMCS in chronological order thus the corresponding output power of DG can be generated. The proposed method has been tested on feeder F4 of IEEE-RBTS Bus 6. The results show that reliability evaluation of distribution system considering the uncertainty of output power of DG can be effectively implemented by SMCS.

  13. Human visual system automatically encodes sequential regularities of discrete events.

    Science.gov (United States)

    Kimura, Motohiro; Schröger, Erich; Czigler, István; Ohira, Hideki

    2010-06-01

    regularities. In combination with a wide range of auditory MMN studies, the present study highlights the critical role of sensory systems in automatically encoding sequential regularities when modeling the world.

  14. Modulation transfer function cascade model for a sampled IR imaging system.

    Science.gov (United States)

    de Luca, L; Cardone, G

    1991-05-01

    The performance of the infrared scanning radiometer (IRSR) is strongly stressed in convective heat transfer applications where high spatial frequencies in the signal that describes the thermal image are present. The need to characterize more deeply the system spatial resolution has led to the formulation of a cascade model for the evaluation of the actual modulation transfer function of a sampled IR imaging system. The model can yield both the aliasing band and the averaged modulation response for a general sampling subsystem. For a line scan imaging system, which is the case of a typical IRSR, a rule of thumb that states whether the combined sampling-imaging system is either imaging-dependent or sampling-dependent is proposed. The model is tested by comparing it with other noncascade models as well as by ad hoc measurements performed on a commercial digitized IRSR.

  15. Nested sampling algorithm for subsurface flow model selection, uncertainty quantification, and nonlinear calibration

    KAUST Repository

    Elsheikh, A. H.; Wheeler, M. F.; Hoteit, Ibrahim

    2013-01-01

    Calibration of subsurface flow models is an essential step for managing ground water aquifers, designing of contaminant remediation plans, and maximizing recovery from hydrocarbon reservoirs. We investigate an efficient sampling algorithm known

  16. Inventory implications of using sampling variances in estimation of growth model coefficients

    Science.gov (United States)

    Albert R. Stage; William R. Wykoff

    2000-01-01

    Variables based on stand densities or stocking have sampling errors that depend on the relation of tree size to plot size and on the spatial structure of the population, ignoring the sampling errors of such variables, which include most measures of competition used in both distance-dependent and distance-independent growth models, can bias the predictions obtained from...

  17. Conditional estimation of exponential random graph models from snowball sampling designs

    NARCIS (Netherlands)

    Pattison, Philippa E.; Robins, Garry L.; Snijders, Tom A. B.; Wang, Peng

    2013-01-01

    A complete survey of a network in a large population may be prohibitively difficult and costly. So it is important to estimate models for networks using data from various network sampling designs, such as link-tracing designs. We focus here on snowball sampling designs, designs in which the members

  18. 12 CFR Appendix B to Part 707 - Model Clauses and Sample Forms

    Science.gov (United States)

    2010-01-01

    ...) B-8—Sample Form (Money Market Share Account Disclosures) B-9—Sample Form (Term Share (Certificate... money market accounts. These are some of the more common limitations applicable. The credit union... will assist members in reviewing and understanding the change. B-3Model Clauses for Pre-Maturity...

  19. Nested sampling algorithm for subsurface flow model selection, uncertainty quantification, and nonlinear calibration

    KAUST Repository

    Elsheikh, A. H.

    2013-12-01

    Calibration of subsurface flow models is an essential step for managing ground water aquifers, designing of contaminant remediation plans, and maximizing recovery from hydrocarbon reservoirs. We investigate an efficient sampling algorithm known as nested sampling (NS), which can simultaneously sample the posterior distribution for uncertainty quantification, and estimate the Bayesian evidence for model selection. Model selection statistics, such as the Bayesian evidence, are needed to choose or assign different weights to different models of different levels of complexities. In this work, we report the first successful application of nested sampling for calibration of several nonlinear subsurface flow problems. The estimated Bayesian evidence by the NS algorithm is used to weight different parameterizations of the subsurface flow models (prior model selection). The results of the numerical evaluation implicitly enforced Occam\\'s razor where simpler models with fewer number of parameters are favored over complex models. The proper level of model complexity was automatically determined based on the information content of the calibration data and the data mismatch of the calibrated model.

  20. Job durations and the job search model : a two-country, multi-sample analysis

    OpenAIRE

    Bagger, Jesper; Henningsen, Morten

    2008-01-01

    Abstract: This paper assesses whether a parsimonious partial equilibrium job search model with on-the-job search can reproduce observed job durations and transitions to other jobs and to nonemployment. We allow for unobserved heterogeneity across individuals in key structural parameters. Observed heterogeneity and life cycle effects are accounted for by estimating separate models for flow samples of labor market entrants and stock samples of “mature” workers with 10-11 years of...

  1. Microstructure history effect during sequential thermomechanical processing

    International Nuclear Information System (INIS)

    Yassar, Reza S.; Murphy, John; Burton, Christina; Horstemeyer, Mark F.; El kadiri, Haitham; Shokuhfar, Tolou

    2008-01-01

    The key to modeling the material processing behavior is the linking of the microstructure evolution to its processing history. This paper quantifies various microstructural features of an aluminum automotive alloy that undergoes sequential thermomechanical processing which is comprised hot rolling of a 150-mm billet to a 75-mm billet, rolling to 3 mm, annealing, and then cold rolling to a 0.8-mm thickness sheet. The microstructural content was characterized by means of electron backscatter diffraction, scanning electron microscopy, and transmission electron microscopy. The results clearly demonstrate the evolution of precipitate morphologies, dislocation structures, and grain orientation distributions. These data can be used to improve material models that claim to capture the history effects of the processing materials

  2. A Sequential Multiplicative Extended Kalman Filter for Attitude Estimation Using Vector Observations

    Science.gov (United States)

    Qin, Fangjun; Jiang, Sai; Zha, Feng

    2018-01-01

    In this paper, a sequential multiplicative extended Kalman filter (SMEKF) is proposed for attitude estimation using vector observations. In the proposed SMEKF, each of the vector observations is processed sequentially to update the attitude, which can make the measurement model linearization more accurate for the next vector observation. This is the main difference to Murrell’s variation of the MEKF, which does not update the attitude estimate during the sequential procedure. Meanwhile, the covariance is updated after all the vector observations have been processed, which is used to account for the special characteristics of the reset operation necessary for the attitude update. This is the main difference to the traditional sequential EKF, which updates the state covariance at each step of the sequential procedure. The numerical simulation study demonstrates that the proposed SMEKF has more consistent and accurate performance in a wide range of initial estimate errors compared to the MEKF and its traditional sequential forms. PMID:29751538

  3. A Sequential Multiplicative Extended Kalman Filter for Attitude Estimation Using Vector Observations

    Directory of Open Access Journals (Sweden)

    Fangjun Qin

    2018-05-01

    Full Text Available In this paper, a sequential multiplicative extended Kalman filter (SMEKF is proposed for attitude estimation using vector observations. In the proposed SMEKF, each of the vector observations is processed sequentially to update the attitude, which can make the measurement model linearization more accurate for the next vector observation. This is the main difference to Murrell’s variation of the MEKF, which does not update the attitude estimate during the sequential procedure. Meanwhile, the covariance is updated after all the vector observations have been processed, which is used to account for the special characteristics of the reset operation necessary for the attitude update. This is the main difference to the traditional sequential EKF, which updates the state covariance at each step of the sequential procedure. The numerical simulation study demonstrates that the proposed SMEKF has more consistent and accurate performance in a wide range of initial estimate errors compared to the MEKF and its traditional sequential forms.

  4. A hybrid reliability algorithm using PSO-optimized Kriging model and adaptive importance sampling

    Science.gov (United States)

    Tong, Cao; Gong, Haili

    2018-03-01

    This paper aims to reduce the computational cost of reliability analysis. A new hybrid algorithm is proposed based on PSO-optimized Kriging model and adaptive importance sampling method. Firstly, the particle swarm optimization algorithm (PSO) is used to optimize the parameters of Kriging model. A typical function is fitted to validate improvement by comparing results of PSO-optimized Kriging model with those of the original Kriging model. Secondly, a hybrid algorithm for reliability analysis combined optimized Kriging model and adaptive importance sampling is proposed. Two cases from literatures are given to validate the efficiency and correctness. The proposed method is proved to be more efficient due to its application of small number of sample points according to comparison results.

  5. The EC BIOCLIM Project (2000-2003), 5. Euratom Framework Programme - Modelling sequential biosphere systems under climate change for radioactive waste disposal

    International Nuclear Information System (INIS)

    Calvez, Marianne

    2002-01-01

    Marianne Calvez (ANDRA, France) presented the new EC BIOCLIM project that started in 2001. Its main objective is to provide a scientific basis and practical methodology for assessing the possible long-term impacts on the safety of radioactive waste repositories in deep formations due to climate driven changes. She explained that BIOCLIM objective is not to predict what will be the future but will correspond to an illustration of how people could use the knowledge. The BIOCLIM project will use the outcomes from the Biomass project. Where Biomass considered discrete biospheres, the BIOCLIM project will consider the evolution of climate with a focus on the European climate for three regions in the United Kingdom, France and Spain. The consortium of BIOCLIM participants consists of various experts in climate modelling and various experts and organisations in performance assessment. The intent is to build an integrated dynamic climate model that represents all the important mechanisms for long-term climate evolution. The modelling will primarily address the next 200000 years. The final outcome will be an enhancement of the state-of-the-art treatment of biosphere system change over long periods of time through the use of a number of innovative climate modelling approaches and the application of the climate model outputs in performance assessments

  6. Conformational sampling in template-free protein loop structure modeling: an overview.

    Science.gov (United States)

    Li, Yaohang

    2013-01-01

    Accurately modeling protein loops is an important step to predict three-dimensional structures as well as to understand functions of many proteins. Because of their high flexibility, modeling the three-dimensional structures of loops is difficult and is usually treated as a "mini protein folding problem" under geometric constraints. In the past decade, there has been remarkable progress in template-free loop structure modeling due to advances of computational methods as well as stably increasing number of known structures available in PDB. This mini review provides an overview on the recent computational approaches for loop structure modeling. In particular, we focus on the approaches of sampling loop conformation space, which is a critical step to obtain high resolution models in template-free methods. We review the potential energy functions for loop modeling, loop buildup mechanisms to satisfy geometric constraints, and loop conformation sampling algorithms. The recent loop modeling results are also summarized.

  7. CONFORMATIONAL SAMPLING IN TEMPLATE-FREE PROTEIN LOOP STRUCTURE MODELING: AN OVERVIEW

    Directory of Open Access Journals (Sweden)

    Yaohang Li

    2013-02-01

    Full Text Available Accurately modeling protein loops is an important step to predict three-dimensional structures as well as to understand functions of many proteins. Because of their high flexibility, modeling the three-dimensional structures of loops is difficult and is usually treated as a “mini protein folding problem” under geometric constraints. In the past decade, there has been remarkable progress in template-free loop structure modeling due to advances of computational methods as well as stably increasing number of known structures available in PDB. This mini review provides an overview on the recent computational approaches for loop structure modeling. In particular, we focus on the approaches of sampling loop conformation space, which is a critical step to obtain high resolution models in template-free methods. We review the potential energy functions for loop modeling, loop buildup mechanisms to satisfy geometric constraints, and loop conformation sampling algorithms. The recent loop modeling results are also summarized.

  8. Sampling stored product insect pests: a comparison of four statistical sampling models for probability of pest detection

    Science.gov (United States)

    Statistically robust sampling strategies form an integral component of grain storage and handling activities throughout the world. Developing sampling strategies to target biological pests such as insects in stored grain is inherently difficult due to species biology and behavioral characteristics. ...

  9. Sequential series for nuclear reactions

    International Nuclear Information System (INIS)

    Izumo, Ko

    1975-01-01

    A new time-dependent treatment of nuclear reactions is given, in which the wave function of compound nucleus is expanded by a sequential series of the reaction processes. The wave functions of the sequential series form another complete set of compound nucleus at the limit Δt→0. It is pointed out that the wave function is characterized by the quantities: the number of degrees of freedom of motion n, the period of the motion (Poincare cycle) tsub(n), the delay time t sub(nμ) and the relaxation time tausub(n) to the equilibrium of compound nucleus, instead of the usual quantum number lambda, the energy eigenvalue Esub(lambda) and the total width GAMMAsub(lambda) of resonance levels, respectively. The transition matrix elements and the yields of nuclear reactions also become the functions of time given by the Fourier transform of the usual ones. The Poincare cycles of compound nuclei are compared with the observed correlations among resonance levels, which are about 10 -17 --10 -16 sec for medium and heavy nuclei and about 10 -20 sec for the intermediate resonances. (auth.)

  10. Identification and estimation of nonlinear models using two samples with nonclassical measurement errors

    KAUST Repository

    Carroll, Raymond J.

    2010-05-01

    This paper considers identification and estimation of a general nonlinear Errors-in-Variables (EIV) model using two samples. Both samples consist of a dependent variable, some error-free covariates, and an error-prone covariate, for which the measurement error has unknown distribution and could be arbitrarily correlated with the latent true values; and neither sample contains an accurate measurement of the corresponding true variable. We assume that the regression model of interest - the conditional distribution of the dependent variable given the latent true covariate and the error-free covariates - is the same in both samples, but the distributions of the latent true covariates vary with observed error-free discrete covariates. We first show that the general latent nonlinear model is nonparametrically identified using the two samples when both could have nonclassical errors, without either instrumental variables or independence between the two samples. When the two samples are independent and the nonlinear regression model is parameterized, we propose sieve Quasi Maximum Likelihood Estimation (Q-MLE) for the parameter of interest, and establish its root-n consistency and asymptotic normality under possible misspecification, and its semiparametric efficiency under correct specification, with easily estimated standard errors. A Monte Carlo simulation and a data application are presented to show the power of the approach.

  11. Drilling induced damage of core samples. Evidences from laboratory testing and numerical modelling

    International Nuclear Information System (INIS)

    Lanaro, Flavio

    2008-01-01

    Extensive sample testing in uniaxial and Brazilian test conditions were carried out for the Shobasama and MIU Research Laboratory Site (Gifu Pref., Japan). The compressive and tensile strength of the samples was observed to be negatively correlated to the in-situ stress components. Such correlation was interpreted as stress-release induced sample damage. Similar stress conditions were then numerically simulated by means of the BEM-DDM code FRACOD 2D in plane strain conditions. This method allows for explicitly consider the influence of newly initiated or propagating fractures on the stress field and deformation of the core during drilling process. The models show that already at moderate stress levels some fracturing of the core during drilling might occur leading to reduced laboratory strength of the samples. Sample damage maps were produced independently from the laboratory test results and from the numerical models and show good agreement with each other. (author)

  12. Sensitivity analysis using contribution to sample variance plot: Application to a water hammer model

    International Nuclear Information System (INIS)

    Tarantola, S.; Kopustinskas, V.; Bolado-Lavin, R.; Kaliatka, A.; Ušpuras, E.; Vaišnoras, M.

    2012-01-01

    This paper presents “contribution to sample variance plot”, a natural extension of the “contribution to the sample mean plot”, which is a graphical tool for global sensitivity analysis originally proposed by Sinclair. These graphical tools have a great potential to display graphically sensitivity information given a generic input sample and its related model realizations. The contribution to the sample variance can be obtained at no extra computational cost, i.e. from the same points used for deriving the contribution to the sample mean and/or scatter-plots. The proposed approach effectively instructs the analyst on how to achieve a targeted reduction of the variance, by operating on the extremes of the input parameters' ranges. The approach is tested against a known benchmark for sensitivity studies, the Ishigami test function, and a numerical model simulating the behaviour of a water hammer effect in a piping system.

  13. Linear model correction: A method for transferring a near-infrared multivariate calibration model without standard samples

    Science.gov (United States)

    Liu, Yan; Cai, Wensheng; Shao, Xueguang

    2016-12-01

    Calibration transfer is essential for practical applications of near infrared (NIR) spectroscopy because the measurements of the spectra may be performed on different instruments and the difference between the instruments must be corrected. For most of calibration transfer methods, standard samples are necessary to construct the transfer model using the spectra of the samples measured on two instruments, named as master and slave instrument, respectively. In this work, a method named as linear model correction (LMC) is proposed for calibration transfer without standard samples. The method is based on the fact that, for the samples with similar physical and chemical properties, the spectra measured on different instruments are linearly correlated. The fact makes the coefficients of the linear models constructed by the spectra measured on different instruments are similar in profile. Therefore, by using the constrained optimization method, the coefficients of the master model can be transferred into that of the slave model with a few spectra measured on slave instrument. Two NIR datasets of corn and plant leaf samples measured with different instruments are used to test the performance of the method. The results show that, for both the datasets, the spectra can be correctly predicted using the transferred partial least squares (PLS) models. Because standard samples are not necessary in the method, it may be more useful in practical uses.

  14. Modelling and sequential simulation of multi-tubular metallic membrane and techno-economics of a hydrogen production process employing thin-layer membrane reactor

    KAUST Repository

    Shafiee, Alireza; Arab, Mobin; Lai, Zhiping; Liu, Zongwen; Abbas, Ali

    2016-01-01

    reforming hydrogen production plant. A techno-economic analysis is then conducted using the validated model for a plant producing 300 TPD of hydrogen. The plant utilises a thin (2.5 μm) defect-free and selective layer (Pd75Ag25 alloy) membrane reactor

  15. Efficient Bayesian inference of subsurface flow models using nested sampling and sparse polynomial chaos surrogates

    KAUST Repository

    Elsheikh, Ahmed H.

    2014-02-01

    An efficient Bayesian calibration method based on the nested sampling (NS) algorithm and non-intrusive polynomial chaos method is presented. Nested sampling is a Bayesian sampling algorithm that builds a discrete representation of the posterior distributions by iteratively re-focusing a set of samples to high likelihood regions. NS allows representing the posterior probability density function (PDF) with a smaller number of samples and reduces the curse of dimensionality effects. The main difficulty of the NS algorithm is in the constrained sampling step which is commonly performed using a random walk Markov Chain Monte-Carlo (MCMC) algorithm. In this work, we perform a two-stage sampling using a polynomial chaos response surface to filter out rejected samples in the Markov Chain Monte-Carlo method. The combined use of nested sampling and the two-stage MCMC based on approximate response surfaces provides significant computational gains in terms of the number of simulation runs. The proposed algorithm is applied for calibration and model selection of subsurface flow models. © 2013.

  16. Sequential analysis in neonatal research-systematic review.

    Science.gov (United States)

    Lava, Sebastiano A G; Elie, Valéry; Ha, Phuong Thi Viet; Jacqz-Aigrain, Evelyne

    2018-05-01

    As more new drugs are discovered, traditional designs come at their limits. Ten years after the adoption of the European Paediatric Regulation, we performed a systematic review on the US National Library of Medicine and Excerpta Medica database of sequential trials involving newborns. Out of 326 identified scientific reports, 21 trials were included. They enrolled 2832 patients, of whom 2099 were analyzed: the median number of neonates included per trial was 48 (IQR 22-87), median gestational age was 28.7 (IQR 27.9-30.9) weeks. Eighteen trials used sequential techniques to determine sample size, while 3 used continual reassessment methods for dose-finding. In 16 studies reporting sufficient data, the sequential design allowed to non-significantly reduce the number of enrolled neonates by a median of 24 (31%) patients (IQR - 4.75 to 136.5, p = 0.0674) with respect to a traditional trial. When the number of neonates finally included in the analysis was considered, the difference became significant: 35 (57%) patients (IQR 10 to 136.5, p = 0.0033). Sequential trial designs have not been frequently used in Neonatology. They might potentially be able to reduce the number of patients in drug trials, although this is not always the case. What is known: • In evaluating rare diseases in fragile populations, traditional designs come at their limits. About 20% of pediatric trials are discontinued, mainly because of recruitment problems. What is new: • Sequential trials involving newborns were infrequently used and only a few (n = 21) are available for analysis. • The sequential design allowed to non-significantly reduce the number of enrolled neonates by a median of 24 (31%) patients (IQR - 4.75 to 136.5, p = 0.0674).

  17. Sworn testimony of the model evidence: Gaussian Mixture Importance (GAME) sampling

    Science.gov (United States)

    Volpi, Elena; Schoups, Gerrit; Firmani, Giovanni; Vrugt, Jasper A.

    2017-07-01

    What is the "best" model? The answer to this question lies in part in the eyes of the beholder, nevertheless a good model must blend rigorous theory with redeeming qualities such as parsimony and quality of fit. Model selection is used to make inferences, via weighted averaging, from a set of K candidate models, Mk; k=>(1,…,K>), and help identify which model is most supported by the observed data, Y>˜=>(y˜1,…,y˜n>). Here, we introduce a new and robust estimator of the model evidence, p>(Y>˜|Mk>), which acts as normalizing constant in the denominator of Bayes' theorem and provides a single quantitative measure of relative support for each hypothesis that integrates model accuracy, uncertainty, and complexity. However, p>(Y>˜|Mk>) is analytically intractable for most practical modeling problems. Our method, coined GAussian Mixture importancE (GAME) sampling, uses bridge sampling of a mixture distribution fitted to samples of the posterior model parameter distribution derived from MCMC simulation. We benchmark the accuracy and reliability of GAME sampling by application to a diverse set of multivariate target distributions (up to 100 dimensions) with known values of p>(Y>˜|Mk>) and to hypothesis testing using numerical modeling of the rainfall-runoff transformation of the Leaf River watershed in Mississippi, USA. These case studies demonstrate that GAME sampling provides robust and unbiased estimates of the evidence at a relatively small computational cost outperforming commonly used estimators. The GAME sampler is implemented in the MATLAB package of DREAM and simplifies considerably scientific inquiry through hypothesis testing and model selection.

  18. Monitoring sequential electron transfer with EPR

    International Nuclear Information System (INIS)

    Thurnauer, M.C.; Feezel, L.L.; Snyder, S.W.; Tang, J.; Norris, J.R.; Morris, A.L.; Rustandi, R.R.

    1989-01-01

    A completely general model which treats electron spin polarization (ESP) found in a system in which radical pairs with different magnetic interactions are formed sequentially has been described. This treatment has been applied specifically to the ESP found in the bacterial reaction center. Test cases show clearly how parameters such as structure, lifetime, and magnetic interactions within the successive radical pairs affect the ESP, and demonstrate that previous treatments of this problem have been incomplete. The photosynthetic bacterial reaction center protein is an ideal system for testing the general model of ESP. The radical pair which exhibits ESP, P 870 + Q - (P 870 + is the oxidized, primary electron donor, a bacteriochlorophyll special pair and Q - is the reduced, primary quinone acceptor) is formed via sequential electron transport through the intermediary radical pair P 870 + I - (I - is the reduced, intermediary electron acceptor, a bacteriopheophytin). In addition, it is possible to experimentally vary most of the important parameters, such as the lifetime of the intermediary radical pair and the magnetic interactions in each pair. It has been shown how selective isotopic substitution ( 1 H or 2 H) on P 870 , I and Q affects the ESP of the EPR spectrum of P 870 + Q - , observed at two different microwave frequencies, in Fe 2+ -depleted bacterial reaction centers of Rhodobacter sphaeroides R26. Thus, the relative magnitudes of the magnetic properties (nuclear hyperfine and g-factor differences) which influence ESP development were varied. The results support the general model of ESP in that they suggest that the P 870 + Q - radical pair interactions are the dominant source of ESP production in 2 H bacterial reaction centers

  19. Testing the normality assumption in the sample selection model with an application to travel demand

    NARCIS (Netherlands)

    van der Klaauw, B.; Koning, R.H.

    2003-01-01

    In this article we introduce a test for the normality assumption in the sample selection model. The test is based on a flexible parametric specification of the density function of the error terms in the model. This specification follows a Hermite series with bivariate normality as a special case.

  20. Testing the normality assumption in the sample selection model with an application to travel demand

    NARCIS (Netherlands)

    van der Klauw, B.; Koning, R.H.

    In this article we introduce a test for the normality assumption in the sample selection model. The test is based on a flexible parametric specification of the density function of the error terms in the model. This specification follows a Hermite series with bivariate normality as a special case.

  1. A GMM-Based Test for Normal Disturbances of the Heckman Sample Selection Model

    Directory of Open Access Journals (Sweden)

    Michael Pfaffermayr

    2014-10-01

    Full Text Available The Heckman sample selection model relies on the assumption of normal and homoskedastic disturbances. However, before considering more general, alternative semiparametric models that do not need the normality assumption, it seems useful to test this assumption. Following Meijer and Wansbeek (2007, the present contribution derives a GMM-based pseudo-score LM test on whether the third and fourth moments of the disturbances of the outcome equation of the Heckman model conform to those implied by the truncated normal distribution. The test is easy to calculate and in Monte Carlo simulations it shows good performance for sample sizes of 1000 or larger.

  2. A Method of Sample Models of Program Construction in Terms of Petri Nets

    Directory of Open Access Journals (Sweden)

    D. I. Kharitonov

    2015-01-01

    Full Text Available In the article a method of automated construction of Petri nets simulating the behaviour of imperative programs is considered from the formal point of view. Petri net samples with certain characteristics are necessary in programming new algorithms for program analysis; in particular, they can be used for developing or optimizing algorithms of Petri nets compositions and decompositions, building the reachability tree, checking invariants and so on. The generation process consists of two stages. At the first stage, construction templates for a resulting net and parameters for construction are described. With the help of these parameters it is possible to regulate the final size and the absolute or relative amount of certain structures in the resulting net. At the second stage, iterative process of automated net construction is used for Petri net generation of any size, limited only by an available computer memory. In the first section of the article the minimum necessary definitions are given and a new version of Petri nets composition operation by places is introduced. Commutative and associative properties of introduced binary operation allow to synchronize any number of Petri nets in arbitrary order. Then construction template is defined as a marked Petri net with input and output interfaces and rules for templates composition using this interfaces. A number of construction templates can be united in a collection, for which the evolution rules are defined. The completeness property of a collection guarantees that the collection evolution results in a Petri net that simulates the imperative program behavior. The article provides a version of the construction templates complete collection and an example of Petri net simulating sequential imperative program construction.

  3. Long-term dynamic and pseudo-state modeling of complete partial nitrification process at high nitrogen loading rates in a sequential batch reactor (SBR).

    Science.gov (United States)

    Soliman, Moomen; Eldyasti, Ahmed

    2017-06-01

    Recently, partial nitrification has been adopted widely either for the nitrite shunt process or intermediate nitrite generation step for the Anammox process. However, partial nitrification has been hindered by the complexity of maintaining stable nitrite accumulation at high nitrogen loading rates (NLR) which affect the feasibility of the process for high nitrogen content wastewater. Thus, the operational data of a lab scale SBR performing complete partial nitrification as a first step of nitrite shunt process at NLRs of 0.3-1.2kg/(m 3 d) have been used to calibrate and validate a process model developed using BioWin® in order to describe the long-term dynamic behavior of the SBR. Moreover, an identifiability analysis step has been introduced to the calibration protocol to eliminate the needs of the respirometric analysis for SBR models. The calibrated model was able to predict accurately the daily effluent ammonia, nitrate, nitrite, alkalinity concentrations and pH during all different operational conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. Sequential lineup presentation: Patterns and policy

    OpenAIRE

    Lindsay, R C L; Mansour, Jamal K; Beaudry, J L; Leach, A-M; Bertrand, M I

    2009-01-01

    Sequential lineups were offered as an alternative to the traditional simultaneous lineup. Sequential lineups reduce incorrect lineup selections; however, the accompanying loss of correct identifications has resulted in controversy regarding adoption of the technique. We discuss the procedure and research relevant to (1) the pattern of results found using sequential versus simultaneous lineups; (2) reasons (theory) for differences in witness responses; (3) two methodological issues; and (4) im...

  5. Biased lineups: sequential presentation reduces the problem.

    Science.gov (United States)

    Lindsay, R C; Lea, J A; Nosworthy, G J; Fulford, J A; Hector, J; LeVan, V; Seabrook, C

    1991-12-01

    Biased lineups have been shown to increase significantly false, but not correct, identification rates (Lindsay, Wallbridge, & Drennan, 1987; Lindsay & Wells, 1980; Malpass & Devine, 1981). Lindsay and Wells (1985) found that sequential lineup presentation reduced false identification rates, presumably by reducing reliance on relative judgment processes. Five staged-crime experiments were conducted to examine the effect of lineup biases and sequential presentation on eyewitness recognition accuracy. Sequential lineup presentation significantly reduced false identification rates from fair lineups as well as from lineups biased with regard to foil similarity, instructions, or witness attire, and from lineups biased in all of these ways. The results support recommendations that police present lineups sequentially.

  6. Multiplicity distributions and multiplicity correlations in sequential, off-equilibrium fragmentation process

    International Nuclear Information System (INIS)

    Botet, R.

    1996-01-01

    A new kinetic fragmentation model, the Fragmentation - Inactivation -Binary (FIB) model is described where a dissipative process stops randomly the sequential, conservative and off-equilibrium fragmentation process. (K.A.)

  7. Why weight? Modelling sample and observational level variability improves power in RNA-seq analyses.

    Science.gov (United States)

    Liu, Ruijie; Holik, Aliaksei Z; Su, Shian; Jansz, Natasha; Chen, Kelan; Leong, Huei San; Blewitt, Marnie E; Asselin-Labat, Marie-Liesse; Smyth, Gordon K; Ritchie, Matthew E

    2015-09-03

    Variations in sample quality are frequently encountered in small RNA-sequencing experiments, and pose a major challenge in a differential expression analysis. Removal of high variation samples reduces noise, but at a cost of reducing power, thus limiting our ability to detect biologically meaningful changes. Similarly, retaining these samples in the analysis may not reveal any statistically significant changes due to the higher noise level. A compromise is to use all available data, but to down-weight the observations from more variable samples. We describe a statistical approach that facilitates this by modelling heterogeneity at both the sample and observational levels as part of the differential expression analysis. At the sample level this is achieved by fitting a log-linear variance model that includes common sample-specific or group-specific parameters that are shared between genes. The estimated sample variance factors are then converted to weights and combined with observational level weights obtained from the mean-variance relationship of the log-counts-per-million using 'voom'. A comprehensive analysis involving both simulations and experimental RNA-sequencing data demonstrates that this strategy leads to a universally more powerful analysis and fewer false discoveries when compared to conventional approaches. This methodology has wide application and is implemented in the open-source 'limma' package. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  8. Sequential simulation approach to modeling of multi-seam coal deposits with an application to the assessment of a Louisiana lignite

    Science.gov (United States)

    Olea, Ricardo A.; Luppens, James A.

    2012-01-01

    There are multiple ways to characterize uncertainty in the assessment of coal resources, but not all of them are equally satisfactory. Increasingly, the tendency is toward borrowing from the statistical tools developed in the last 50 years for the quantitative assessment of other mineral commodities. Here, we briefly review the most recent of such methods and formulate a procedure for the systematic assessment of multi-seam coal deposits taking into account several geological factors, such as fluctuations in thickness, erosion, oxidation, and bed boundaries. A lignite deposit explored in three stages is used for validating models based on comparing a first set of drill holes against data from infill and development drilling. Results were fully consistent with reality, providing a variety of maps, histograms, and scatterplots characterizing the deposit and associated uncertainty in the assessments. The geostatistical approach was particularly informative in providing a probability distribution modeling deposit wide uncertainty about total resources and a cumulative distribution of coal tonnage as a function of local uncertainty.

  9. Neural dynamics as sampling: a model for stochastic computation in recurrent networks of spiking neurons.

    Science.gov (United States)

    Buesing, Lars; Bill, Johannes; Nessler, Bernhard; Maass, Wolfgang

    2011-11-01

    The organization of computations in networks of spiking neurons in the brain is still largely unknown, in particular in view of the inherently stochastic features of their firing activity and the experimentally observed trial-to-trial variability of neural systems in the brain. In principle there exists a powerful computational framework for stochastic computations, probabilistic inference by sampling, which can explain a large number of macroscopic experimental data in neuroscience and cognitive science. But it has turned out to be surprisingly difficult to create a link between these abstract models for stochastic computations and more detailed models of the dynamics of networks of spiking neurons. Here we create such a link and show that under some conditions the stochastic firing activity of networks of spiking neurons can be interpreted as probabilistic inference via Markov chain Monte Carlo (MCMC) sampling. Since common methods for MCMC sampling in distributed systems, such as Gibbs sampling, are inconsistent with the dynamics of spiking neurons, we introduce a different approach based on non-reversible Markov chains that is able to reflect inherent temporal processes of spiking neuronal activity through a suitable choice of random variables. We propose a neural network model and show by a rigorous theoretical analysis that its neural activity implements MCMC sampling of a given distribution, both for the case of discrete and continuous time. This provides a step towards closing the gap between abstract functional models of cortical computation and more detailed models of networks of spiking neurons.

  10. Immediate Sequential Bilateral Cataract Surgery

    DEFF Research Database (Denmark)

    Kessel, Line; Andresen, Jens; Erngaard, Ditte

    2015-01-01

    The aim of the present systematic review was to examine the benefits and harms associated with immediate sequential bilateral cataract surgery (ISBCS) with specific emphasis on the rate of complications, postoperative anisometropia, and subjective visual function in order to formulate evidence......-based national Danish guidelines for cataract surgery. A systematic literature review in PubMed, Embase, and Cochrane central databases identified three randomized controlled trials that compared outcome in patients randomized to ISBCS or bilateral cataract surgery on two different dates. Meta-analyses were...... performed using the Cochrane Review Manager software. The quality of the evidence was assessed using the GRADE method (Grading of Recommendation, Assessment, Development, and Evaluation). We did not find any difference in the risk of complications or visual outcome in patients randomized to ISBCS or surgery...

  11. Sequential sampling, magnitude estimation, and the wisdom of crowds

    DEFF Research Database (Denmark)

    Nash, Ulrik W.

    2017-01-01

    in the wisdom of crowds indicated by judgment distribution skewness. The present study reports findings from an experiment on magnitude estimation and supports these predictions. The study moreover demonstrates that systematic errors by groups of people can be corrected using information about the judgment...

  12. The effect of clustering on lot quality assurance sampling: a probabilistic model to calculate sample sizes for quality assessments.

    Science.gov (United States)

    Hedt-Gauthier, Bethany L; Mitsunaga, Tisha; Hund, Lauren; Olives, Casey; Pagano, Marcello

    2013-10-26

    Traditional Lot Quality Assurance Sampling (LQAS) designs assume observations are collected using simple random sampling. Alternatively, randomly sampling clusters of observations and then individuals within clusters reduces costs but decreases the precision of the classifications. In this paper, we develop a general framework for designing the cluster(C)-LQAS system and illustrate the method with the design of data quality assessments for the community health worker program in Rwanda. To determine sample size and decision rules for C-LQAS, we use the beta-binomial distribution to account for inflated risk of errors introduced by sampling clusters at the first stage. We present general theory and code for sample size calculations.The C-LQAS sample sizes provided in this paper constrain misclassification risks below user-specified limits. Multiple C-LQAS systems meet the specified risk requirements, but numerous considerations, including per-cluster versus per-individual sampling costs, help identify optimal systems for distinct applications. We show the utility of C-LQAS for data quality assessments, but the method generalizes to numerous applications. This paper provides the necessary technical detail and supplemental code to support the design of C-LQAS for specific programs.

  13. Bounded Memory, Inertia, Sampling and Weighting Model for Market Entry Games

    Directory of Open Access Journals (Sweden)

    Yi-Shan Lee

    2011-03-01

    Full Text Available This paper describes the “Bounded Memory, Inertia, Sampling and Weighting” (BI-SAW model, which won the http://sites.google.com/site/gpredcomp/Market Entry Prediction Competition in 2010. The BI-SAW model refines the I-SAW Model (Erev et al. [1] by adding the assumption of limited memory span. In particular, we assume when players draw a small sample to weight against the average payoff of all past experience, they can only recall 6 trials of past experience. On the other hand, we keep all other key features of the I-SAW model: (1 Reliance on a small sample of past experiences, (2 Strong inertia and recency effects, and (3 Surprise triggers change. We estimate this model using the first set of experimental results run by the competition organizers, and use it to predict results of a second set of similar experiments later ran by the organizers. We find significant improvement in out-of-sample predictability (against the I-SAW model in terms of smaller mean normalized MSD, and such result is robust to resampling the predicted game set and reversing the role of the sets of experimental results. Our model’s performance is the best among all the participants.

  14. Optimisation of beryllium-7 gamma analysis following BCR sequential extraction

    International Nuclear Information System (INIS)

    Taylor, A.; Blake, W.H.; Keith-Roach, M.J.

    2012-01-01

    Graphical abstract: Showing decrease in analytical uncertainty using the optimal (combined preconcentrated sample extract) method. nv (no value) where extract activities were 7 Be geochemical behaviour is required to support tracer studies. ► Sequential extraction with natural 7 Be returns high analytical uncertainties. ► Preconcentrating extracts from a large sample mass improved analytical uncertainty. ► This optimised method can be readily employed in studies using low activity samples. - Abstract: The application of cosmogenic 7 Be as a sediment tracer at the catchment-scale requires an understanding of its geochemical associations in soil to underpin the assumption of irreversible adsorption. Sequential extractions offer a readily accessible means of determining the associations of 7 Be with operationally defined soil phases. However, the subdivision of the low activity concentrations of fallout 7 Be in soils into geochemical fractions can introduce high gamma counting uncertainties. Extending analysis time significantly is not always an option for batches of samples, owing to the on-going decay of 7 Be (t 1/2 = 53.3 days). Here, three different methods of preparing and quantifying 7 Be extracted using the optimised BCR three-step scheme have been evaluated and compared with a focus on reducing analytical uncertainties. The optimal method involved carrying out the BCR extraction in triplicate, sub-sampling each set of triplicates for stable Be analysis before combining each set and coprecipitating the 7 Be with metal oxyhydroxides to produce a thin source for gamma analysis. This method was applied to BCR extractions of natural 7 Be in four agricultural soils. The approach gave good counting statistics from a 24 h analysis period (∼10% (2σ) where extract activity >40% of total activity) and generated statistically useful sequential extraction profiles. Total recoveries of 7 Be fell between 84 and 112%. The stable Be data demonstrated that the

  15. Modelling of in-stream nitrogen and phosphorus concentrations using different sampling strategies for calibration data

    Science.gov (United States)

    Jomaa, Seifeddine; Jiang, Sanyuan; Yang, Xiaoqiang; Rode, Michael

    2016-04-01

    It is known that a good evaluation and prediction of surface water pollution is mainly limited by the monitoring strategy and the capability of the hydrological water quality model to reproduce the internal processes. To this end, a compromise sampling frequency, which can reflect the dynamical behaviour of leached nutrient fluxes responding to changes in land use, agriculture practices and point sources, and appropriate process-based water quality model are required. The objective of this study was to test the identification of hydrological water quality model parameters (nitrogen and phosphorus) under two different monitoring strategies: (1) regular grab-sampling approach and (2) regular grab-sampling with additional monitoring during the hydrological events using automatic samplers. First, the semi-distributed hydrological water quality HYPE (Hydrological Predictions for the Environment) model was successfully calibrated (1994-1998) for discharge (NSE = 0.86), nitrate-N (lowest NSE for nitrate-N load = 0.69), particulate phosphorus and soluble phosphorus in the Selke catchment (463 km2, central Germany) for the period 1994-1998 using regular grab-sampling approach (biweekly to monthly for nitrogen and phosphorus concentrations). Second, the model was successfully validated during the period 1999-2010 for discharge, nitrate-N, particulate-phosphorus and soluble-phosphorus (lowest NSE for soluble phosphorus load = 0.54). Results, showed that when additional sampling during the events with random grab-sampling approach was used (period 2011-2013), the hydrological model could reproduce only the nitrate-N and soluble phosphorus concentrations reasonably well. However, when additional sampling during the hydrological events was considered, the HYPE model could not represent the measured particulate phosphorus. This reflects the importance of suspended sediment during the hydrological events increasing the concentrations of particulate phosphorus. The HYPE model could

  16. A new method for automatic discontinuity traces sampling on rock mass 3D model

    Science.gov (United States)

    Umili, G.; Ferrero, A.; Einstein, H. H.

    2013-02-01

    A new automatic method for discontinuity traces mapping and sampling on a rock mass digital model is described in this work. The implemented procedure allows one to automatically identify discontinuity traces on a Digital Surface Model: traces are detected directly as surface breaklines, by means of maximum and minimum principal curvature values of the vertices that constitute the model surface. Color influence and user errors, that usually characterize the trace mapping on images, are eliminated. Also trace sampling procedures based on circular windows and circular scanlines have been implemented: they are used to infer trace data and to calculate values of mean trace length, expected discontinuity diameter and intensity of rock discontinuities. The method is tested on a case study: results obtained applying the automatic procedure on the DSM of a rock face are compared to those obtained performing a manual sampling on the orthophotograph of the same rock face.

  17. 'Sequential' Boron Neutron Capture Therapy (BNCT): A Novel Approach to BNCT for the Treatment of Oral Cancer in the Hamster Cheek Pouch Model

    International Nuclear Information System (INIS)

    Molinari, Ana J.; Pozzi, Emiliano C.C.; Hughes, Andrea Monti; Heber, Elisa M.; Garabalino, Marcela A.; Thorp, Silvia I.; Miller, Marcelo; Itoiz, Maria E.; Aromando, Romina F.; Nigg, David W.; Quintana, Jorge; Santa Cruz, Gustavo A.; Trivillin, Veronica A.; Schwint, Amanda E.

    2011-01-01

    In the present study we evaluated the therapeutic effect and/or potential radiotoxicity of the novel 'Tandem' Boron Neutron Capture Therapy (T-BNCT) for the treatment of oral cancer in the hamster cheek pouch model at RA-3 Nuclear Reactor. Two groups of animals were treated with 'Tandem BNCT', i.e. BNCT mediated by boronophenylalanine (BPA) followed by BNCT mediated by sodium decahydrodecaborate (GB-10) either 24 h (T-24h-BNCT) or 48 h (T-48h-BNCT) later. A total tumor dose-matched single application of BNCT mediated by BPA and GB-10 administered jointly ((BPA + GB-10)-BNCT) was administered to an additional group of animals. At 28 days post-treatment, T-24h-BNCT and T-48h-BNCT induced, respectively, overall tumor control (OTC) of 95% and 91%, with no statistically significant differences between protocols. Tumor response for the single application of (BPA + GB-10)-BNCT was 75%, significantly lower than for T-BNCT. The T-BNCT protocols and (BPA + GB-10)-BNCT induced reversible mucositis in dose-limiting precancerous tissue around treated tumors, reaching Grade 3/4 mucositis in 47% and 60% of the animals respectively. No normal tissue radiotoxicity was associated to tumor control for any of the protocols. 'Tandem' BNCT enhances tumor control in oral cancer and reduces or, at worst, does not increase, mucositis in dose-limiting precancerous tissue.

  18. Comparative Study of Compensatory Liver Regeneration in a Rat Model: Portal Vein Ligation Only versus Sequential Ligation of the Portal Vein and Hepatic Artery

    Energy Technology Data Exchange (ETDEWEB)

    Chung, Soo Young [Dept. of Pathology, Dongnam Institute of Radiological and Medical Sciences, Busan (Korea, Republic of); Jeon, Gyeong Sik [Dept. of Radiology, CHA Bundang Medical Center, College of Medicine, CHA University, Seongnam (Korea, Republic of); Lee, Byung Mo [Dept. of Surgery, Seoul Paik Hospital, Inje University College of Medicine, Seoul (Korea, Republic of)

    2013-04-15

    To compare the volume change and the regenerative capacity between portal vein ligation (embolization) (PVL) and heterochronous PVL with hepatic artery ligation (HAL) in a rodent model. The animals were separated into three groups: group I, ligation of the left lateral and median portal vein branches; group II, completion of PVL, followed by ligation of the same branches of the hepatic artery after 48 h; control group, laparotomy without ligation was performed. Five rats from each group were sacrificed on 1, 3, 5, and 7 days after the operation. Volume change measurement, liver function tests and immunohistochemical analysis were performed. The volume of the nonligated lobe between groups I and II was not significantly different by day 5 and day 7. Mean alanine aminotransferase and total bilirubin levels were significantly higher in group II, while the albumin level was higher in group I. Both c-kit- and MIB-5-positive cells used in the activity detection of regeneration were more prevalent in group I on day 1, 3, and 5, with statistical significance. There was no operation related mortality. PVL alone is safe and effective in compensatory liver regeneration. Performing both PVL and HAL does not confer any additional benefits.

  19. A model for estimating the minimum number of offspring to sample in studies of reproductive success.

    Science.gov (United States)

    Anderson, Joseph H; Ward, Eric J; Carlson, Stephanie M

    2011-01-01

    Molecular parentage permits studies of selection and evolution in fecund species with cryptic mating systems, such as fish, amphibians, and insects. However, there exists no method for estimating the number of offspring that must be assigned parentage to achieve robust estimates of reproductive success when only a fraction of offspring can be sampled. We constructed a 2-stage model that first estimated the mean (μ) and variance (v) in reproductive success from published studies on salmonid fishes and then sampled offspring from reproductive success distributions simulated from the μ and v estimates. Results provided strong support for modeling salmonid reproductive success via the negative binomial distribution and suggested that few offspring samples are needed to reject the null hypothesis of uniform offspring production. However, the sampled reproductive success distributions deviated significantly (χ(2) goodness-of-fit test p value reproductive success distribution at rates often >0.05 and as high as 0.24, even when hundreds of offspring were assigned parentage. In general, reproductive success patterns were less accurate when offspring were sampled from cohorts with larger numbers of parents and greater variance in reproductive success. Our model can be reparameterized with data from other species and will aid researchers in planning reproductive success studies by providing explicit sampling targets required to accurately assess reproductive success.

  20. Depression and Delinquency Covariation in an Accelerated Longitudinal Sample of Adolescents

    Science.gov (United States)

    Kofler, Michael J.; McCart, Michael R.; Zajac, Kristyn; Ruggiero, Kenneth J.; Saunders, Benjamin E.; Kilpatrick, Dean G.

    2011-01-01

    Objectives: The current study tested opposing predictions stemming from the failure and acting out theories of depression-delinquency covariation. Method: Participants included a nationwide longitudinal sample of adolescents (N = 3,604) ages 12 to 17. Competing models were tested with cohort-sequential latent growth curve modeling to determine…

  1. Chromatographic profiles of Phyllanthus aqueous extracts samples: a proposition of classification using chemometric models.

    Science.gov (United States)

    Martins, Lucia Regina Rocha; Pereira-Filho, Edenir Rodrigues; Cass, Quezia Bezerra

    2011-04-01

    Taking in consideration the global analysis of complex samples, proposed by the metabolomic approach, the chromatographic fingerprint encompasses an attractive chemical characterization of herbal medicines. Thus, it can be used as a tool in quality control analysis of phytomedicines. The generated multivariate data are better evaluated by chemometric analyses, and they can be modeled by classification methods. "Stone breaker" is a popular Brazilian plant of Phyllanthus genus, used worldwide to treat renal calculus, hepatitis, and many other diseases. In this study, gradient elution at reversed-phase conditions with detection at ultraviolet region were used to obtain chemical profiles (fingerprints) of botanically identified samples of six Phyllanthus species. The obtained chromatograms, at 275 nm, were organized in data matrices, and the time shifts of peaks were adjusted using the Correlation Optimized Warping algorithm. Principal Component Analyses were performed to evaluate similarities among cultivated and uncultivated samples and the discrimination among the species and, after that, the samples were used to compose three classification models using Soft Independent Modeling of Class analogy, K-Nearest Neighbor, and Partial Least Squares for Discriminant Analysis. The ability of classification models were discussed after their successful application for authenticity evaluation of 25 commercial samples of "stone breaker."

  2. Sampling algorithms for validation of supervised learning models for Ising-like systems

    Science.gov (United States)

    Portman, Nataliya; Tamblyn, Isaac

    2017-12-01

    In this paper, we build and explore supervised learning models of ferromagnetic system behavior, using Monte-Carlo sampling of the spin configuration space generated by the 2D Ising model. Given the enormous size of the space of all possible Ising model realizations, the question arises as to how to choose a reasonable number of samples that will form physically meaningful and non-intersecting training and testing datasets. Here, we propose a sampling technique called ;ID-MH; that uses the Metropolis-Hastings algorithm creating Markov process across energy levels within the predefined configuration subspace. We show that application of this method retains phase transitions in both training and testing datasets and serves the purpose of validation of a machine learning algorithm. For larger lattice dimensions, ID-MH is not feasible as it requires knowledge of the complete configuration space. As such, we develop a new ;block-ID; sampling strategy: it decomposes the given structure into square blocks with lattice dimension N ≤ 5 and uses ID-MH sampling of candidate blocks. Further comparison of the performance of commonly used machine learning methods such as random forests, decision trees, k nearest neighbors and artificial neural networks shows that the PCA-based Decision Tree regressor is the most accurate predictor of magnetizations of the Ising model. For energies, however, the accuracy of prediction is not satisfactory, highlighting the need to consider more algorithmically complex methods (e.g., deep learning).

  3. Limited sampling strategy models for estimating the AUC of gliclazide in Chinese healthy volunteers.

    Science.gov (United States)

    Huang, Ji-Han; Wang, Kun; Huang, Xiao-Hui; He, Ying-Chun; Li, Lu-Jin; Sheng, Yu-Cheng; Yang, Juan; Zheng, Qing-Shan

    2013-06-01

    The aim of this work is to reduce the cost of required sampling for the estimation of the area under the gliclazide plasma concentration versus time curve within 60 h (AUC0-60t ). The limited sampling strategy (LSS) models were established and validated by the multiple regression model within 4 or fewer gliclazide concentration values. Absolute prediction error (APE), root of mean square error (RMSE) and visual prediction check were used as criterion. The results of Jack-Knife validation showed that 10 (25.0 %) of the 40 LSS based on the regression analysis were not within an APE of 15 % using one concentration-time point. 90.2, 91.5 and 92.4 % of the 40 LSS models were capable of prediction using 2, 3 and 4 points, respectively. Limited sampling strategies were developed and validated for estimating AUC0-60t of gliclazide. This study indicates that the implementation of an 80 mg dosage regimen enabled accurate predictions of AUC0-60t by the LSS model. This study shows that 12, 6, 4, 2 h after administration are the key sampling times. The combination of (12, 2 h), (12, 8, 2 h) or (12, 8, 4, 2 h) can be chosen as sampling hours for predicting AUC0-60t in practical application according to requirement.

  4. 2-Way k-Means as a Model for Microbiome Samples.

    Science.gov (United States)

    Jackson, Weston J; Agarwal, Ipsita; Pe'er, Itsik

    2017-01-01

    Motivation . Microbiome sequencing allows defining clusters of samples with shared composition. However, this paradigm poorly accounts for samples whose composition is a mixture of cluster-characterizing ones and which therefore lie in between them in the cluster space. This paper addresses unsupervised learning of 2-way clusters. It defines a mixture model that allows 2-way cluster assignment and describes a variant of generalized k -means for learning such a model. We demonstrate applicability to microbial 16S rDNA sequencing data from the Human Vaginal Microbiome Project.

  5. Using the Superpopulation Model for Imputations and Variance Computation in Survey Sampling

    Directory of Open Access Journals (Sweden)

    Petr Novák

    2012-03-01

    Full Text Available This study is aimed at variance computation techniques for estimates of population characteristics based on survey sampling and imputation. We use the superpopulation regression model, which means that the target variable values for each statistical unit are treated as random realizations of a linear regression model with weighted variance. We focus on regression models with one auxiliary variable and no intercept, which have many applications and straightforward interpretation in business statistics. Furthermore, we deal with caseswhere the estimates are not independent and thus the covariance must be computed. We also consider chained regression models with auxiliary variables as random variables instead of constants.

  6. The sequential structure of brain activation predicts skill.

    Science.gov (United States)

    Anderson, John R; Bothell, Daniel; Fincham, Jon M; Moon, Jungaa

    2016-01-29

    In an fMRI study, participants were trained to play a complex video game. They were scanned early and then again after substantial practice. While better players showed greater activation in one region (right dorsal striatum) their relative skill was better diagnosed by considering the sequential structure of whole brain activation. Using a cognitive model that played this game, we extracted a characterization of the mental states that are involved in playing a game and the statistical structure of the transitions among these states. There was a strong correspondence between this measure of sequential structure and the skill of different players. Using multi-voxel pattern analysis, it was possible to recognize, with relatively high accuracy, the cognitive states participants were in during particular scans. We used the sequential structure of these activation-recognized states to predict the skill of individual players. These findings indicate that important features about information-processing strategies can be identified from a model-based analysis of the sequential structure of brain activation. Copyright © 2015 Elsevier Ltd. All rights reserved.

  7. On the origin of reproducible sequential activity in neural circuits

    Science.gov (United States)

    Afraimovich, V. S.; Zhigulin, V. P.; Rabinovich, M. I.

    2004-12-01

    Robustness and reproducibility of sequential spatio-temporal responses is an essential feature of many neural circuits in sensory and motor systems of animals. The most common mathematical images of dynamical regimes in neural systems are fixed points, limit cycles, chaotic attractors, and continuous attractors (attractive manifolds of neutrally stable fixed points). These are not suitable for the description of reproducible transient sequential neural dynamics. In this paper we present the concept of a stable heteroclinic sequence (SHS), which is not an attractor. SHS opens the way for understanding and modeling of transient sequential activity in neural circuits. We show that this new mathematical object can be used to describe robust and reproducible sequential neural dynamics. Using the framework of a generalized high-dimensional Lotka-Volterra model, that describes the dynamics of firing rates in an inhibitory network, we present analytical results on the existence of the SHS in the phase space of the network. With the help of numerical simulations we confirm its robustness in presence of noise in spite of the transient nature of the corresponding trajectories. Finally, by referring to several recent neurobiological experiments, we discuss possible applications of this new concept to several problems in neuroscience.

  8. The effects of sampling bias and model complexity on the predictive performance of MaxEnt species distribution models.

    Science.gov (United States)

    Syfert, Mindy M; Smith, Matthew J; Coomes, David A

    2013-01-01

    Species distribution models (SDMs) trained on presence-only data are frequently used in ecological research and conservation planning. However, users of SDM software are faced with a variety of options, and it is not always obvious how selecting one option over another will affect model performance. Working with MaxEnt software and with tree fern presence data from New Zealand, we assessed whether (a) choosing to correct for geographical sampling bias and (b) using complex environmental response curves have strong effects on goodness of fit. SDMs were trained on tree fern data, obtained from an online biodiversity data portal, with two sources that differed in size and geographical sampling bias: a small, widely-distributed set of herbarium specimens and a large, spatially clustered set of ecological survey records. We attempted to correct for geographical sampling bias by incorporating sampling bias grids in the SDMs, created from all georeferenced vascular plants in the datasets, and explored model complexity issues by fitting a wide variety of environmental response curves (known as "feature types" in MaxEnt). In each case, goodness of fit was assessed by comparing predicted range maps with tree fern presences and absences using an independent national dataset to validate the SDMs. We found that correcting for geographical sampling bias led to major improvements in goodness of fit, but did not entirely resolve the problem: predictions made with clustered ecological data were inferior to those made with the herbarium dataset, even after sampling bias correction. We also found that the choice of feature type had negligible effects on predictive performance, indicating that simple feature types may be sufficient once sampling bias is accounted for. Our study emphasizes the importance of reducing geographical sampling bias, where possible, in datasets used to train SDMs, and the effectiveness and essentialness of sampling bias correction within MaxEnt.

  9. The sequential trauma score - a new instrument for the sequential mortality prediction in major trauma*

    Directory of Open Access Journals (Sweden)

    Huber-Wagner S

    2010-05-01

    Full Text Available Abstract Background There are several well established scores for the assessment of the prognosis of major trauma patients that all have in common that they can be calculated at the earliest during intensive care unit stay. We intended to develop a sequential trauma score (STS that allows prognosis at several early stages based on the information that is available at a particular time. Study design In a retrospective, multicenter study using data derived from the Trauma Registry of the German Trauma Society (2002-2006, we identified the most relevant prognostic factors from the patients basic data (P, prehospital phase (A, early (B1, and late (B2 trauma room phase. Univariate and logistic regression models as well as score quality criteria and the explanatory power have been calculated. Results A total of 2,354 patients with complete data were identified. From the patients basic data (P, logistic regression showed that age was a significant predictor of survival (AUCmodel p, area under the curve = 0.63. Logistic regression of the prehospital data (A showed that blood pressure, pulse rate, Glasgow coma scale (GCS, and anisocoria were significant predictors (AUCmodel A = 0.76; AUCmodel P + A = 0.82. Logistic regression of the early trauma room phase (B1 showed that peripheral oxygen saturation, GCS, anisocoria, base excess, and thromboplastin time to be significant predictors of survival (AUCmodel B1 = 0.78; AUCmodel P +A + B1 = 0.85. Multivariate analysis of the late trauma room phase (B2 detected cardiac massage, abbreviated injury score (AIS of the head ≥ 3, the maximum AIS, the need for transfusion or massive blood transfusion, to be the most important predictors (AUCmodel B2 = 0.84; AUCfinal model P + A + B1 + B2 = 0.90. The explanatory power - a tool for the assessment of the relative impact of each segment to mortality - is 25% for P, 7% for A, 17% for B1 and 51% for B2. A spreadsheet for the easy calculation of the sequential trauma

  10. Trial Sequential Methods for Meta-Analysis

    Science.gov (United States)

    Kulinskaya, Elena; Wood, John

    2014-01-01

    Statistical methods for sequential meta-analysis have applications also for the design of new trials. Existing methods are based on group sequential methods developed for single trials and start with the calculation of a required information size. This works satisfactorily within the framework of fixed effects meta-analysis, but conceptual…

  11. Effect of dissolved organic matter on pre-equilibrium passive sampling: A predictive QSAR modeling study.

    Science.gov (United States)

    Lin, Wei; Jiang, Ruifen; Shen, Yong; Xiong, Yaxin; Hu, Sizi; Xu, Jianqiao; Ouyang, Gangfeng

    2018-04-13

    Pre-equilibrium passive sampling is a simple and promising technique for studying sampling kinetics, which is crucial to determine the distribution, transfer and fate of hydrophobic organic compounds (HOCs) in environmental water and organisms. Environmental water samples contain complex matrices that complicate the traditional calibration process for obtaining the accurate rate constants. This study proposed a QSAR model to predict the sampling rate constants of HOCs (polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs) and pesticides) in aqueous systems containing complex matrices. A homemade flow-through system was established to simulate an actual aqueous environment containing dissolved organic matter (DOM) i.e. humic acid (HA) and (2-Hydroxypropyl)-β-cyclodextrin (β-HPCD)), and to obtain the experimental rate constants. Then, a quantitative structure-activity relationship (QSAR) model using Genetic Algorithm-Multiple Linear Regression (GA-MLR) was found to correlate the experimental rate constants to the system state including physicochemical parameters of the HOCs and DOM which were calculated and selected as descriptors by Density Functional Theory (DFT) and Chem 3D. The experimental results showed that the rate constants significantly increased as the concentration of DOM increased, and the enhancement factors of 70-fold and 34-fold were observed for the HOCs in HA and β-HPCD, respectively. The established QSAR model was validated as credible (R Adj. 2 =0.862) and predictable (Q 2 =0.835) in estimating the rate constants of HOCs for complex aqueous sampling, and a probable mechanism was developed by comparison to the reported theoretical study. The present study established a QSAR model of passive sampling rate constants and calibrated the effect of DOM on the sampling kinetics. Copyright © 2018 Elsevier B.V. All rights reserved.

  12. Hierarchical modeling for rare event detection and cell subset alignment across flow cytometry samples.

    Directory of Open Access Journals (Sweden)

    Andrew Cron

    Full Text Available Flow cytometry is the prototypical assay for multi-parameter single cell analysis, and is essential in vaccine and biomarker research for the enumeration of antigen-specific lymphocytes that are often found in extremely low frequencies (0.1% or less. Standard analysis of flow cytometry data relies on visual identification of cell subsets by experts, a process that is subjective and often difficult to reproduce. An alternative and more objective approach is the use of statistical models to identify cell subsets of interest in an automated fashion. Two specific challenges for automated analysis are to detect extremely low frequency event subsets without biasing the estimate by pre-processing enrichment, and the ability to align cell subsets across multiple data samples for comparative analysis. In this manuscript, we develop hierarchical modeling extensions to the Dirichlet Process Gaussian Mixture Model (DPGMM approach we have previously described for cell subset identification, and show that the hierarchical DPGMM (HDPGMM naturally generates an aligned data model that captures both commonalities and variations across multiple samples. HDPGMM also increases the sensitivity to extremely low frequency events by sharing information across multiple samples analyzed simultaneously. We validate the accuracy and reproducibility of HDPGMM estimates of antigen-specific T cells on clinically relevant reference peripheral blood mononuclear cell (PBMC samples with known frequencies of antigen-specific T cells. These cell samples take advantage of retrovirally TCR-transduced T cells spiked into autologous PBMC samples to give a defined number of antigen-specific T cells detectable by HLA-peptide multimer binding. We provide open source software that can take advantage of both multiple processors and GPU-acceleration to perform the numerically-demanding computations. We show that hierarchical modeling is a useful probabilistic approach that can provide a

  13. Sparse Power-Law Network Model for Reliable Statistical Predictions Based on Sampled Data

    Directory of Open Access Journals (Sweden)

    Alexander P. Kartun-Giles

    2018-04-01

    Full Text Available A projective network model is a model that enables predictions to be made based on a subsample of the network data, with the predictions remaining unchanged if a larger sample is taken into consideration. An exchangeable model is a model that does not depend on the order in which nodes are sampled. Despite a large variety of non-equilibrium (growing and equilibrium (static sparse complex network models that are widely used in network science, how to reconcile sparseness (constant average degree with the desired statistical properties of projectivity and exchangeability is currently an outstanding scientific problem. Here we propose a network process with hidden variables which is projective and can generate sparse power-law networks. Despite the model not being exchangeable, it can be closely related to exchangeable uncorrelated networks as indicated by its information theory characterization and its network entropy. The use of the proposed network process as a null model is here tested on real data, indicating that the model offers a promising avenue for statistical network modelling.

  14. Formation of InN phase by sequential ion implantation

    International Nuclear Information System (INIS)

    Santhana Raman, P.; Ravichandran, V.; Nair, K.G.M.; Kesavamoorthy, R.; Kalavathi, S.; Panigrahi, B.K.; Dhara, S.

    2006-01-01

    Formation of InN phase by sequentially implanting nitrogen on indium implanted silica was demonstrated. The growth of embedded InN phase on as-implanted and post-implantation annealed sample was studied using Glancing Incidence X-Ray Diffraction (GIXRD) and Raman spectroscopy. Existence of both cubic and hexagonal phases of InN was observed. Results of irradiation induced ripening of In nanoclusters due to N + ion implantation was also studied. (author)

  15. Sequential lineup laps and eyewitness accuracy.

    Science.gov (United States)

    Steblay, Nancy K; Dietrich, Hannah L; Ryan, Shannon L; Raczynski, Jeanette L; James, Kali A

    2011-08-01

    Police practice of double-blind sequential lineups prompts a question about the efficacy of repeated viewings (laps) of the sequential lineup. Two laboratory experiments confirmed the presence of a sequential lap effect: an increase in witness lineup picks from first to second lap, when the culprit was a stranger. The second lap produced more errors than correct identifications. In Experiment 2, lineup diagnosticity was significantly higher for sequential lineup procedures that employed a single versus double laps. Witnesses who elected to view a second lap made significantly more errors than witnesses who chose to stop after one lap or those who were required to view two laps. Witnesses with prior exposure to the culprit did not exhibit a sequential lap effect.

  16. Multi-agent sequential hypothesis testing

    KAUST Repository

    Kim, Kwang-Ki K.

    2014-12-15

    This paper considers multi-agent sequential hypothesis testing and presents a framework for strategic learning in sequential games with explicit consideration of both temporal and spatial coordination. The associated Bayes risk functions explicitly incorporate costs of taking private/public measurements, costs of time-difference and disagreement in actions of agents, and costs of false declaration/choices in the sequential hypothesis testing. The corresponding sequential decision processes have well-defined value functions with respect to (a) the belief states for the case of conditional independent private noisy measurements that are also assumed to be independent identically distributed over time, and (b) the information states for the case of correlated private noisy measurements. A sequential investment game of strategic coordination and delay is also discussed as an application of the proposed strategic learning rules.

  17. Sequential Product of Quantum Effects: An Overview

    Science.gov (United States)

    Gudder, Stan

    2010-12-01

    This article presents an overview for the theory of sequential products of quantum effects. We first summarize some of the highlights of this relatively recent field of investigation and then provide some new results. We begin by discussing sequential effect algebras which are effect algebras endowed with a sequential product satisfying certain basic conditions. We then consider sequential products of (discrete) quantum measurements. We next treat transition effect matrices (TEMs) and their associated sequential product. A TEM is a matrix whose entries are effects and whose rows form quantum measurements. We show that TEMs can be employed for the study of quantum Markov chains. Finally, we prove some new results concerning TEMs and vector densities.

  18. Some remarks on estimating a covariance structure model from a sample correlation matrix

    OpenAIRE

    Maydeu Olivares, Alberto; Hernández Estrada, Adolfo

    2000-01-01

    A popular model in structural equation modeling involves a multivariate normal density with a structured covariance matrix that has been categorized according to a set of thresholds. In this setup one may estimate the covariance structure parameters from the sample tetrachoricl polychoric correlations but only if the covariance structure is scale invariant. Doing so when the covariance structure is not scale invariant results in estimating a more restricted covariance structure than the one i...

  19. Introducing a rainfall compound distribution model based on weather patterns sub-sampling

    Directory of Open Access Journals (Sweden)

    F. Garavaglia

    2010-06-01

    Full Text Available This paper presents a probabilistic model for daily rainfall, using sub-sampling based on meteorological circulation. We classified eight typical but contrasted synoptic situations (weather patterns for France and surrounding areas, using a "bottom-up" approach, i.e. from the shape of the rain field to the synoptic situations described by geopotential fields. These weather patterns (WP provide a discriminating variable that is consistent with French climatology, and allows seasonal rainfall records to be split into more homogeneous sub-samples, in term of meteorological genesis.

    First results show how the combination of seasonal and WP sub-sampling strongly influences the identification of the asymptotic behaviour of rainfall probabilistic models. Furthermore, with this level of stratification, an asymptotic exponential behaviour of each sub-sample appears as a reasonable hypothesis. This first part is illustrated with two daily rainfall records from SE of France.

    The distribution of the multi-exponential weather patterns (MEWP is then defined as the composition, for a given season, of all WP sub-sample marginal distributions, weighted by the relative frequency of occurrence of each WP. This model is finally compared to Exponential and Generalized Pareto distributions, showing good features in terms of robustness and accuracy. These final statistical results are computed from a wide dataset of 478 rainfall chronicles spread on the southern half of France. All these data cover the 1953–2005 period.

  20. Using maximum entropy modeling for optimal selection of sampling sites for monitoring networks

    Science.gov (United States)

    Stohlgren, Thomas J.; Kumar, Sunil; Barnett, David T.; Evangelista, Paul H.

    2011-01-01

    Environmental monitoring programs must efficiently describe state shifts. We propose using maximum entropy modeling to select dissimilar sampling sites to capture environmental variability at low cost, and demonstrate a specific application: sample site selection for the Central Plains domain (453,490 km2) of the National Ecological Observatory Network (NEON). We relied on four environmental factors: mean annual temperature and precipitation, elevation, and vegetation type. A “sample site” was defined as a 20 km × 20 km area (equal to NEON’s airborne observation platform [AOP] footprint), within which each 1 km2 cell was evaluated for each environmental factor. After each model run, the most environmentally dissimilar site was selected from all potential sample sites. The iterative selection of eight sites captured approximately 80% of the environmental envelope of the domain, an improvement over stratified random sampling and simple random designs for sample site selection. This approach can be widely used for cost-efficient selection of survey and monitoring sites.

  1. A Bayesian sequential design using alpha spending function to control type I error.

    Science.gov (United States)

    Zhu, Han; Yu, Qingzhao

    2017-10-01

    We propose in this article a Bayesian sequential design using alpha spending functions to control the overall type I error in phase III clinical trials. We provide algorithms to calculate critical values, power, and sample sizes for the proposed design. Sensitivity analysis is implemented to check the effects from different prior distributions, and conservative priors are recommended. We compare the power and actual sample sizes of the proposed Bayesian sequential design with different alpha spending functions through simulations. We also compare the power of the proposed method with frequentist sequential design using the same alpha spending function. Simulations show that, at the same sample size, the proposed method provides larger power than the corresponding frequentist sequential design. It also has larger power than traditional Bayesian sequential design which sets equal critical values for all interim analyses. When compared with other alpha spending functions, O'Brien-Fleming alpha spending function has the largest power and is the most conservative in terms that at the same sample size, the null hypothesis is the least likely to be rejected at early stage of clinical trials. And finally, we show that adding a step of stop for futility in the Bayesian sequential design can reduce the overall type I error and reduce the actual sample sizes.

  2. An Experience Sampling Study of Learning, Affect, and the Demands Control Support Model

    Science.gov (United States)

    Daniels, Kevin; Boocock, Grahame; Glover, Jane; Hartley, Ruth; Holland, Julie

    2009-01-01

    The demands control support model (R. A. Karasek & T. Theorell, 1990) indicates that job control and social support enable workers to engage in problem solving. In turn, problem solving is thought to influence learning and well-being (e.g., anxious affect, activated pleasant affect). Two samples (N = 78, N = 106) provided data up to 4 times per…

  3. The Accuracy of Inference in Small Samples of Dynamic Panel Data Models

    NARCIS (Netherlands)

    Bun, M.J.G.; Kiviet, J.F.

    2001-01-01

    Through Monte Carlo experiments the small sample behavior is examined of various inference techniques for dynamic panel data models when both the time-series and cross-section dimensions of the data set are small. The LSDV technique and corrected versions of it are compared with IV and GMM

  4. The Dirichlet-Multinomial Model for Multivariate Randomized Response Data and Small Samples

    Science.gov (United States)

    Avetisyan, Marianna; Fox, Jean-Paul

    2012-01-01

    In survey sampling the randomized response (RR) technique can be used to obtain truthful answers to sensitive questions. Although the individual answers are masked due to the RR technique, individual (sensitive) response rates can be estimated when observing multivariate response data. The beta-binomial model for binary RR data will be generalized…

  5. Fast sampling from a Hidden Markov Model posterior for large data

    DEFF Research Database (Denmark)

    Bonnevie, Rasmus; Hansen, Lars Kai

    2014-01-01

    Hidden Markov Models are of interest in a broad set of applications including modern data driven systems involving very large data sets. However, approximate inference methods based on Bayesian averaging are precluded in such applications as each sampling step requires a full sweep over the data...

  6. Mass Balance Model, A study of contamination effects in AMS 14C sample analysis

    NARCIS (Netherlands)

    Prokopiou, Markella

    2010-01-01

    In this training thesis a background correction analysis, also known as mass balance model, was implemented to study the contamination effects in AMS 14C sample processing. A variety of backgrounds and standards with sizes ranging from 50 μg C to 1500 μg

  7. Designing efficient nitrous oxide sampling strategies in agroecosystems using simulation models

    Science.gov (United States)

    Debasish Saha; Armen R. Kemanian; Benjamin M. Rau; Paul R. Adler; Felipe Montes

    2017-01-01

    Annual cumulative soil nitrous oxide (N2O) emissions calculated from discrete chamber-based flux measurements have unknown uncertainty. We used outputs from simulations obtained with an agroecosystem model to design sampling strategies that yield accurate cumulative N2O flux estimates with a known uncertainty level. Daily soil N2O fluxes were simulated for Ames, IA (...

  8. Climate Change and Agricultural Productivity in Sub-Saharan Africa: A Spatial Sample Selection Model

    NARCIS (Netherlands)

    Ward, P.S.; Florax, R.J.G.M.; Flores-Lagunes, A.

    2014-01-01

    Using spatially explicit data, we estimate a cereal yield response function using a recently developed estimator for spatial error models when endogenous sample selection is of concern. Our results suggest that yields across Sub-Saharan Africa will decline with projected climatic changes, and that

  9. Exact sampling of the unobserved covariates in Bayesian spline models for measurement error problems.

    Science.gov (United States)

    Bhadra, Anindya; Carroll, Raymond J

    2016-07-01

    In truncated polynomial spline or B-spline models where the covariates are measured with error, a fully Bayesian approach to model fitting requires the covariates and model parameters to be sampled at every Markov chain Monte Carlo iteration. Sampling the unobserved covariates poses a major computational problem and usually Gibbs sampling is not possible. This forces the practitioner to use a Metropolis-Hastings step which might suffer from unacceptable performance due to poor mixing and might require careful tuning. In this article we show for the cases of truncated polynomial spline or B-spline models of degree equal to one, the complete conditional distribution of the covariates measured with error is available explicitly as a mixture of double-truncated normals, thereby enabling a Gibbs sampling scheme. We demonstrate via a simulation study that our technique performs favorably in terms of computational efficiency and statistical performance. Our results indicate up to 62 and 54 % increase in mean integrated squared error efficiency when compared to existing alternatives while using truncated polynomial splines and B-splines respectively. Furthermore, there is evidence that the gain in efficiency increases with the measurement error variance, indicating the proposed method is a particularly valuable tool for challenging applications that present high measurement error. We conclude with a demonstration on a nutritional epidemiology data set from the NIH-AARP study and by pointing out some possible extensions of the current work.

  10. Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian State Space Models

    NARCIS (Netherlands)

    Koopman, S.J.; Lucas, A.; Scharth, M.

    2015-01-01

    We propose a general likelihood evaluation method for nonlinear non-Gaussian state-space models using the simulation-based method of efficient importance sampling. We minimize the simulation effort by replacing some key steps of the likelihood estimation procedure by numerical integration. We refer

  11. Software engineering the mixed model for genome-wide association studies on large samples

    Science.gov (United States)

    Mixed models improve the ability to detect phenotype-genotype associations in the presence of population stratification and multiple levels of relatedness in genome-wide association studies (GWAS), but for large data sets the resource consumption becomes impractical. At the same time, the sample siz...

  12. Comparing distribution models for small samples of overdispersed counts of freshwater fish

    Science.gov (United States)

    Vaudor, Lise; Lamouroux, Nicolas; Olivier, Jean-Michel

    2011-05-01

    The study of species abundance often relies on repeated abundance counts whose number is limited by logistic or financial constraints. The distribution of abundance counts is generally right-skewed (i.e. with many zeros and few high values) and needs to be modelled for statistical inference. We used an extensive dataset involving about 100,000 fish individuals of 12 freshwater fish species collected in electrofishing points (7 m 2) during 350 field surveys made in 25 stream sites, in order to compare the performance and the generality of four distribution models of counts (Poisson, negative binomial and their zero-inflated counterparts). The negative binomial distribution was the best model (Bayesian Information Criterion) for 58% of the samples (species-survey combinations) and was suitable for a variety of life histories, habitat, and sample characteristics. The performance of the models was closely related to samples' statistics such as total abundance and variance. Finally, we illustrated the consequences of a distribution assumption by calculating confidence intervals around the mean abundance, either based on the most suitable distribution assumption or on an asymptotical, distribution-free (Student's) method. Student's method generally corresponded to narrower confidence intervals, especially when there were few (≤3) non-null counts in the samples.

  13. Software engineering the mixed model for genome-wide association studies on large samples.

    Science.gov (United States)

    Zhang, Zhiwu; Buckler, Edward S; Casstevens, Terry M; Bradbury, Peter J

    2009-11-01

    Mixed models improve the ability to detect phenotype-genotype associations in the presence of population stratification and multiple levels of relatedness in genome-wide association studies (GWAS), but for large data sets the resource consumption becomes impractical. At the same time, the sample size and number of markers used for GWAS is increasing dramatically, resulting in greater statistical power to detect those associations. The use of mixed models with increasingly large data sets depends on the availability of software for analyzing those models. While multiple software packages implement the mixed model method, no single package provides the best combination of fast computation, ability to handle large samples, flexible modeling and ease of use. Key elements of association analysis with mixed models are reviewed, including modeling phenotype-genotype associations using mixed models, population stratification, kinship and its estimation, variance component estimation, use of best linear unbiased predictors or residuals in place of raw phenotype, improving efficiency and software-user interaction. The available software packages are evaluated, and suggestions made for future software development.

  14. Toward a Tiered Model to Share Clinical Trial Data and Samples in Precision Oncology.

    Science.gov (United States)

    Broes, Stefanie; Lacombe, Denis; Verlinden, Michiel; Huys, Isabelle

    2018-01-01

    The recent revolution in science and technology applied to medical research has left in its wake a trial of biomedical data and human samples; however, its opportunities remain largely unfulfilled due to a number of legal, ethical, financial, strategic, and technical barriers. Precision oncology has been at the vanguard to leverage this potential of "Big data" and samples into meaningful solutions for patients, considering the need for new drug development approaches in this area (due to high costs, late-stage failures, and the molecular diversity of cancer). To harness the potential of the vast quantities of data and samples currently fragmented across databases and biobanks, it is critical to engage all stakeholders and share data and samples across research institutes. Here, we identified two general types of sharing strategies. First, open access models, characterized by the absence of any review panel or decision maker, and second controlled access model where some form of control is exercised by either the donor (i.e., patient), the data provider (i.e., initial organization), or an independent party. Further, we theoretically describe and provide examples of nine different strategies focused on greater sharing of patient data and material. These models provide varying levels of control, access to various data and/or samples, and different types of relationship between the donor, data provider, and data requester. We propose a tiered model to share clinical data and samples that takes into account privacy issues and respects sponsors' legitimate interests. Its implementation would contribute to maximize the value of existing datasets, enabling unraveling the complexity of tumor biology, identify novel biomarkers, and re-direct treatment strategies better, ultimately to help patients with cancer.

  15. Toward a Tiered Model to Share Clinical Trial Data and Samples in Precision Oncology

    Directory of Open Access Journals (Sweden)

    Stefanie Broes

    2018-01-01

    Full Text Available The recent revolution in science and technology applied to medical research has left in its wake a trial of biomedical data and human samples; however, its opportunities remain largely unfulfilled due to a number of legal, ethical, financial, strategic, and technical barriers. Precision oncology has been at the vanguard to leverage this potential of “Big data” and samples into meaningful solutions for patients, considering the need for new drug development approaches in this area (due to high costs, late-stage failures, and the molecular diversity of cancer. To harness the potential of the vast quantities of data and samples currently fragmented across databases and biobanks, it is critical to engage all stakeholders and share data and samples across research institutes. Here, we identified two general types of sharing strategies. First, open access models, characterized by the absence of any review panel or decision maker, and second controlled access model where some form of control is exercised by either the donor (i.e., patient, the data provider (i.e., initial organization, or an independent party. Further, we theoretically describe and provide examples of nine different strategies focused on greater sharing of patient data and material. These models provide varying levels of control, access to various data and/or samples, and different types of relationship between the donor, data provider, and data requester. We propose a tiered model to share clinical data and samples that takes into account privacy issues and respects sponsors’ legitimate interests. Its implementation would contribute to maximize the value of existing datasets, enabling unraveling the complexity of tumor biology, identify novel biomarkers, and re-direct treatment strategies better, ultimately to help patients with cancer.

  16. Laboratory evaluation of a gasifier particle sampling system using model compounds of different particle morphology

    Energy Technology Data Exchange (ETDEWEB)

    Nilsson, Patrik T.; Malik, Azhar; Pagels, Joakim; Lindskog, Magnus; Rissler, Jenny; Gudmundsson, Anders; Bohgard, Mats; Sanati, Mehri [Lund University, Division of Ergonomics and Aerosol Technology, P.O. Box 118, Lund (Sweden)

    2011-07-15

    The objective of this work was to design and evaluate an experimental setup to be used for field studies of particle formation in biomass gasification processes. The setup includes a high-temperature dilution probe and a denuder to separate solid particles from condensable volatile material. The efficiency of the setup to remove volatile material from the sampled stream and the influence from condensation on particles with different morphologies is presented. In order to study the sampling setup model, aerosols were created with a nebulizer to produce compact and solid KCl particles and a diffusion flame burner to produce agglomerated and irregular soot particles. The nebulizer and soot generator was followed by an evaporation-condensation section where volatile material, dioctylsebacete (DOS), was added to the system as a tar model compound. The model aerosol particles were heated to 200 C to create a system containing both solid particles and volatile organic material in gas phase. The heated aerosol particles were sampled and diluted at the same temperature with the dilution probe. Downstream the probe, the DOS was adsorbed in the denuder. This was achieved by slowly decreasing the temperature of the diluted sample towards ambient level in the denuder. Thereby the supersaturation of organic vapors was reduced which decreased the probability for tar condensation and nucleation of new particles. Both the generation system and the sampling technique gave reproducible results. A DOS collection efficiency of >99% was achieved if the denuder inlet concentration was diluted to less than 1-6 mg/m{sup 3} depending on the denuder flow rate. Concentrations higher than that lead to significant impact on the resulting KCl size distribution. The choice of model compounds was done to study the effect from the particle morphology on the achieved particle characteristics after the sampling setup. When similar amounts of volatile material condensed on soot agglomerates and

  17. Mixing modes in a population-based interview survey: comparison of a sequential and a concurrent mixed-mode design for public health research.

    Science.gov (United States)

    Mauz, Elvira; von der Lippe, Elena; Allen, Jennifer; Schilling, Ralph; Müters, Stephan; Hoebel, Jens; Schmich, Patrick; Wetzstein, Matthias; Kamtsiuris, Panagiotis; Lange, Cornelia

    2018-01-01

    the two designs. Modelling these results for higher response rates and larger net sample sizes indicated that the sequential design was more cost and time-effective. This study contributes to the research available on implementing mixed-mode designs as part of public health surveys. Our findings show that SAQ-Paper and SAQ-Web questionnaires can be combined effectively. Sequential mixed-mode designs with higher rates of online respondents may be of greater benefit to studies with larger net sample sizes than concurrent mixed-mode designs.

  18. Experimental Study and Mathematical Modeling of Asphaltene Deposition Mechanism in Core Samples

    Directory of Open Access Journals (Sweden)

    Jafari Behbahani T.

    2015-11-01

    increased. The experimental results show that the amount of remaining asphaltene in carbonate core samples is higher than those in sandstone core samples. Also, SEM (Scanning Electron Microscopy micrographs of carbonate core samples showed the formation of large clusters of asphaltene in comparison with sandstone core samples during natural depletion. It can be seen from the modeling results that the proposed model based on the multilayer adsorption equilibrium mechanism and four material balance equations is more accurate than those obtained from the monolayer adsorption equilibrium adsorption mechanism and two material balance equations, and is in agreement with the experimental data of natural depletion reported in this work and with those reported in the literature.

  19. Out-of-sample Forecasting Performance of Won/Dollar Exchange Rate Return Volatility Model

    Directory of Open Access Journals (Sweden)

    Hojin Lee

    2009-06-01

    Full Text Available We compare the out-of-sample forecasting performance of volatility models using daily exchange rate for the KRW/USD during the period from 1992 to 2008. For various forecasting horizons, historical volatility models with a long memory tend to make more accurate forecasts. Especially, we carefully observe the difference between the EWMA and the GARCH(1,1 model. Our empirical finding that the GARCH model puts too much weight on recent observations relative to those in the past is consistent with prior evidence showing that asset market volatility has a long memory, such as Ding and Granger (1996. The forecasting model with the lowest MSFE and VaR forecast error among the models we consider is the EWMA model in which the forecast volatility for the coming period is a weighted average of recent squared return with exponentially declining weights. In terms of forecast accuracy, it clearly dominates the widely accepted GARCH and rolling window GARCH models. We also present a multiple comparison of the out-of-sample forecasting performance of volatility using the stationary bootstrap of Politis and Romano (1994. We find that the White's reality check for the GARCH(1,1 expanding window model and the FIGARCH(1,1 expanding window model clearly reject the null hypothesis and there exists a better model than the two benchmark models. On the other hand, when the EWMA model is the benchmark, the White's for all forecasting horizons are very high, which indicates the null hypothesis may not be rejected. The Hansen's report the same results. The GARCH(1,1 expanding window model and the FIGARCH(1,1 expanding window model are dominated by the best competing model in most of the forecasting horizons. In contrast, the RiskMetrics model seems to be the most preferred. We also consider combining the forecasts generated by averaging the six raw forecasts and a trimmed set of forecasts which calculate the mean of the four forecasts after disregarding the highest and

  20. Sequential Scintigraphy in Renal Transplantation

    Energy Technology Data Exchange (ETDEWEB)

    Winkel, K. zum; Harbst, H.; Schenck, P.; Franz, H. E.; Ritz, E.; Roehl, L.; Ziegler, M.; Ammann, W.; Maier-Borst, W. [Institut Fuer Nuklearmedizin, Deutsches Krebsforschungszentrum, Heidelberg, Federal Republic of Germany (Germany)

    1969-05-15

    Based on experience gained from more than 1600 patients with proved or suspected kidney diseases and on results on extended studies with dogs, sequential scintigraphy was performed after renal transplantation in dogs. After intravenous injection of 500 {mu}Ci. {sup 131}I-Hippuran scintiphotos were taken during the first minute with an exposure time of 15 sec each and thereafter with an exposure of 2 min up to at least 16 min.. Several examinations were evaluated digitally. 26 examinations were performed on 11 dogs with homotransplanted kidneys. Immediately after transplantation the renal function was almost normal arid the bladder was filled in due time. At the beginning of rejection the initial uptake of radioactive Hippuran was reduced. The intrarenal transport became delayed; probably the renal extraction rate decreased. Corresponding to the development of an oedema in the transplant the uptake area increased in size. In cases of thrombosis of the main artery there was no evidence of any uptake of radioactivity in the transplant. Similar results were obtained in 41 examinations on 15 persons. Patients with postoperative anuria due to acute tubular necrosis showed still some uptake of radioactivity contrary to those with thrombosis of the renal artery, where no uptake was found. In cases of rejection the most frequent signs were a reduced initial uptake and a delayed intrarenal transport of radioactive Hippuran. Infarction could be detected by a reduced uptake in distinct areas of the transplant. (author)

  1. Sequential provisional implant prosthodontics therapy.

    Science.gov (United States)

    Zinner, Ira D; Markovits, Stanley; Jansen, Curtis E; Reid, Patrick E; Schnader, Yale E; Shapiro, Herbert J

    2012-01-01

    The fabrication and long-term use of first- and second-stage provisional implant prostheses is critical to create a favorable prognosis for function and esthetics of a fixed-implant supported prosthesis. The fixed metal and acrylic resin cemented first-stage prosthesis, as reviewed in Part I, is needed for prevention of adjacent and opposing tooth movement, pressure on the implant site as well as protection to avoid micromovement of the freshly placed implant body. The second-stage prosthesis, reviewed in Part II, should be used following implant uncovering and abutment installation. The patient wears this provisional prosthesis until maturation of the bone and healing of soft tissues. The second-stage provisional prosthesis is also a fail-safe mechanism for possible early implant failures and also can be used with late failures and/or for the necessity to repair the definitive prosthesis. In addition, the screw-retained provisional prosthesis is used if and when an implant requires removal or other implants are to be placed as in a sequential approach. The creation and use of both first- and second-stage provisional prostheses involve a restorative dentist, dental technician, surgeon, and patient to work as a team. If the dentist alone cannot do diagnosis and treatment planning, surgery, and laboratory techniques, he or she needs help by employing the expertise of a surgeon and a laboratory technician. This team approach is essential for optimum results.

  2. Trial Sequential Analysis in systematic reviews with meta-analysis

    Directory of Open Access Journals (Sweden)

    Jørn Wetterslev

    2017-03-01

    Full Text Available Abstract Background Most meta-analyses in systematic reviews, including Cochrane ones, do not have sufficient statistical power to detect or refute even large intervention effects. This is why a meta-analysis ought to be regarded as an interim analysis on its way towards a required information size. The results of the meta-analyses should relate the total number of randomised participants to the estimated required meta-analytic information size accounting for statistical diversity. When the number of participants and the corresponding number of trials in a meta-analysis are insufficient, the use of the traditional 95% confidence interval or the 5% statistical significance threshold will lead to too many false positive conclusions (type I errors and too many false negative conclusions (type II errors. Methods We developed a methodology for interpreting meta-analysis results, using generally accepted, valid evidence on how to adjust thresholds for significance in randomised clinical trials when the required sample size has not been reached. Results The Lan-DeMets trial sequential monitoring boundaries in Trial Sequential Analysis offer adjusted confidence intervals and restricted thresholds for statistical significance when the diversity-adjusted required information size and the corresponding number of required trials for the meta-analysis have not been reached. Trial Sequential Analysis provides a frequentistic approach to control both type I and type II errors. We define the required information size and the corresponding number of required trials in a meta-analysis and the diversity (D2 measure of heterogeneity. We explain the reasons for using Trial Sequential Analysis of meta-analysis when the actual information size fails to reach the required information size. We present examples drawn from traditional meta-analyses using unadjusted naïve 95% confidence intervals and 5% thresholds for statistical significance. Spurious conclusions in

  3. Social Influences in Sequential Decision Making.

    Directory of Open Access Journals (Sweden)

    Markus Schöbel

    Full Text Available People often make decisions in a social environment. The present work examines social influence on people's decisions in a sequential decision-making situation. In the first experimental study, we implemented an information cascade paradigm, illustrating that people infer information from decisions of others and use this information to make their own decisions. We followed a cognitive modeling approach to elicit the weight people give to social as compared to private individual information. The proposed social influence model shows that participants overweight their own private information relative to social information, contrary to the normative Bayesian account. In our second study, we embedded the abstract decision problem of Study 1 in a medical decision-making problem. We examined whether in a medical situation people also take others' authority into account in addition to the information that their decisions convey. The social influence model illustrates that people weight social information differentially according to the authority of other decision makers. The influence of authority was strongest when an authority's decision contrasted with private information. Both studies illustrate how the social environment provides sources of information that people integrate differently for their decisions.

  4. Social Influences in Sequential Decision Making

    Science.gov (United States)

    Schöbel, Markus; Rieskamp, Jörg; Huber, Rafael

    2016-01-01

    People often make decisions in a social environment. The present work examines social influence on people’s decisions in a sequential decision-making situation. In the first experimental study, we implemented an information cascade paradigm, illustrating that people infer information from decisions of others and use this information to make their own decisions. We followed a cognitive modeling approach to elicit the weight people give to social as compared to private individual information. The proposed social influence model shows that participants overweight their own private information relative to social information, contrary to the normative Bayesian account. In our second study, we embedded the abstract decision problem of Study 1 in a medical decision-making problem. We examined whether in a medical situation people also take others’ authority into account in addition to the information that their decisions convey. The social influence model illustrates that people weight social information differentially according to the authority of other decision makers. The influence of authority was strongest when an authority's decision contrasted with private information. Both studies illustrate how the social environment provides sources of information that people integrate differently for their decisions. PMID:26784448

  5. Sequential experimental design based generalised ANOVA

    Energy Technology Data Exchange (ETDEWEB)

    Chakraborty, Souvik, E-mail: csouvik41@gmail.com; Chowdhury, Rajib, E-mail: rajibfce@iitr.ac.in

    2016-07-15

    Over the last decade, surrogate modelling technique has gained wide popularity in the field of uncertainty quantification, optimization, model exploration and sensitivity analysis. This approach relies on experimental design to generate training points and regression/interpolation for generating the surrogate. In this work, it is argued that conventional experimental design may render a surrogate model inefficient. In order to address this issue, this paper presents a novel distribution adaptive sequential experimental design (DA-SED). The proposed DA-SED has been coupled with a variant of generalised analysis of variance (G-ANOVA), developed by representing the component function using the generalised polynomial chaos expansion. Moreover, generalised analytical expressions for calculating the first two statistical moments of the response, which are utilized in predicting the probability of failure, have also been developed. The proposed approach has been utilized in predicting probability of failure of three structural mechanics problems. It is observed that the proposed approach yields accurate and computationally efficient estimate of the failure probability.

  6. Social Influences in Sequential Decision Making.

    Science.gov (United States)

    Schöbel, Markus; Rieskamp, Jörg; Huber, Rafael

    2016-01-01

    People often make decisions in a social environment. The present work examines social influence on people's decisions in a sequential decision-making situation. In the first experimental study, we implemented an information cascade paradigm, illustrating that people infer information from decisions of others and use this information to make their own decisions. We followed a cognitive modeling approach to elicit the weight people give to social as compared to private individual information. The proposed social influence model shows that participants overweight their own private information relative to social information, contrary to the normative Bayesian account. In our second study, we embedded the abstract decision problem of Study 1 in a medical decision-making problem. We examined whether in a medical situation people also take others' authority into account in addition to the information that their decisions convey. The social influence model illustrates that people weight social information differentially according to the authority of other decision makers. The influence of authority was strongest when an authority's decision contrasted with private information. Both studies illustrate how the social environment provides sources of information that people integrate differently for their decisions.

  7. A path-level exact parallelization strategy for sequential simulation

    Science.gov (United States)

    Peredo, Oscar F.; Baeza, Daniel; Ortiz, Julián M.; Herrero, José R.

    2018-01-01

    Sequential Simulation is a well known method in geostatistical modelling. Following the Bayesian approach for simulation of conditionally dependent random events, Sequential Indicator Simulation (SIS) method draws simulated values for K categories (categorical case) or classes defined by K different thresholds (continuous case). Similarly, Sequential Gaussian Simulation (SGS) method draws simulated values from a multivariate Gaussian field. In this work, a path-level approach to parallelize SIS and SGS methods is presented. A first stage of re-arrangement of the simulation path is performed, followed by a second stage of parallel simulation for non-conflicting nodes. A key advantage of the proposed parallelization method is to generate identical realizations as with the original non-parallelized methods. Case studies are presented using two sequential simulation codes from GSLIB: SISIM and SGSIM. Execution time and speedup results are shown for large-scale domains, with many categories and maximum kriging neighbours in each case, achieving high speedup results in the best scenarios using 16 threads of execution in a single machine.

  8. A general method to determine sampling windows for nonlinear mixed effects models with an application to population pharmacokinetic studies.

    Science.gov (United States)

    Foo, Lee Kien; McGree, James; Duffull, Stephen

    2012-01-01

    Optimal design methods have been proposed to determine the best sampling times when sparse blood sampling is required in clinical pharmacokinetic studies. However, the optimal blood sampling time points may not be feasible in clinical practice. Sampling windows, a time interval for blood sample collection, have been proposed to provide flexibility in blood sampling times while preserving efficient parameter estimation. Because of the complexity of the population pharmacokinetic models, which are generally nonlinear mixed effects models, there is no analytical solution available to determine sampling windows. We propose a method for determination of sampling windows based on MCMC sampling techniques. The proposed method attains a stationary distribution rapidly and provides time-sensitive windows around the optimal design points. The proposed method is applicable to determine sampling windows for any nonlinear mixed effects model although our work focuses on an application to population pharmacokinetic models. Copyright © 2012 John Wiley & Sons, Ltd.

  9. Dispersion modeling of selected PAHs in urban air: A new approach combining dispersion model with GIS and passive air sampling

    Czech Academy of Sciences Publication Activity Database

    Sáňka, O.; Melymuk, L.; Čupr, P.; Dvorská, Alice; Klánová, J.

    2014-01-01

    Roč. 90, oct (2014), s. 88-95 ISSN 1352-2310 Institutional support: RVO:67179843 Keywords : passive air sampling * air dispersion modeling * GIS * polycyclic aromatic hydrocarbons * emission inventories Subject RIV: DI - Air Pollution ; Quality Impact factor: 3.281, year: 2014

  10. Losing a dime with a satisfied mind: positive affect predicts less search in sequential decision making.

    Science.gov (United States)

    von Helversen, Bettina; Mata, Rui

    2012-12-01

    We investigated the contribution of cognitive ability and affect to age differences in sequential decision making by asking younger and older adults to shop for items in a computerized sequential decision-making task. Older adults performed poorly compared to younger adults partly due to searching too few options. An analysis of the decision process with a formal model suggested that older adults set lower thresholds for accepting an option than younger participants. Further analyses suggested that positive affect, but not fluid abilities, was related to search in the sequential decision task. A second study that manipulated affect in younger adults supported the causal role of affect: Increased positive affect lowered the initial threshold for accepting an attractive option. In sum, our results suggest that positive affect is a key factor determining search in sequential decision making. Consequently, increased positive affect in older age may contribute to poorer sequential decisions by leading to insufficient search. 2013 APA, all rights reserved

  11. Sequential boundaries approach in clinical trials with unequal allocation ratios

    Directory of Open Access Journals (Sweden)

    Ayatollahi Seyyed

    2006-01-01

    Full Text Available Abstract Background In clinical trials, both unequal randomization design and sequential analyses have ethical and economic advantages. In the single-stage-design (SSD, however, if the sample size is not adjusted based on unequal randomization, the power of the trial will decrease, whereas with sequential analysis the power will always remain constant. Our aim was to compare sequential boundaries approach with the SSD when the allocation ratio (R was not equal. Methods We evaluated the influence of R, the ratio of the patients in experimental group to the standard group, on the statistical properties of two-sided tests, including the two-sided single triangular test (TT, double triangular test (DTT and SSD by multiple simulations. The average sample size numbers (ASNs and power (1-β were evaluated for all tests. Results Our simulation study showed that choosing R = 2 instead of R = 1 increases the sample size of SSD by 12% and the ASN of the TT and DTT by the same proportion. Moreover, when R = 2, compared to the adjusted SSD, using the TT or DTT allows to retrieve the well known reductions of ASN observed when R = 1, compared to SSD. In addition, when R = 2, compared to SSD, using the TT and DTT allows to obtain smaller reductions of ASN than when R = 1, but maintains the power of the test to its planned value. Conclusion This study indicates that when the allocation ratio is not equal among the treatment groups, sequential analysis could indeed serve as a compromise between ethicists, economists and statisticians.

  12. A quick method based on SIMPLISMA-KPLS for simultaneously selecting outlier samples and informative samples for model standardization in near infrared spectroscopy

    Science.gov (United States)

    Li, Li-Na; Ma, Chang-Ming; Chang, Ming; Zhang, Ren-Cheng

    2017-12-01

    A novel method based on SIMPLe-to-use Interactive Self-modeling Mixture Analysis (SIMPLISMA) and Kernel Partial Least Square (KPLS), named as SIMPLISMA-KPLS, is proposed in this paper for selection of outlier samples and informative samples simultaneously. It is a quick algorithm used to model standardization (or named as model transfer) in near infrared (NIR) spectroscopy. The NIR experiment data of the corn for analysis of the protein content is introduced to evaluate the proposed method. Piecewise direct standardization (PDS) is employed in model transfer. And the comparison of SIMPLISMA-PDS-KPLS and KS-PDS-KPLS is given in this research by discussion of the prediction accuracy of protein content and calculation speed of each algorithm. The conclusions include that SIMPLISMA-KPLS can be utilized as an alternative sample selection method for model transfer. Although it has similar accuracy to Kennard-Stone (KS), it is different from KS as it employs concentration information in selection program. This means that it ensures analyte information is involved in analysis, and the spectra (X) of the selected samples is interrelated with concentration (y). And it can be used for outlier sample elimination simultaneously by validation of calibration. According to the statistical data results of running time, it is clear that the sample selection process is more rapid when using KPLS. The quick algorithm of SIMPLISMA-KPLS is beneficial to improve the speed of online measurement using NIR spectroscopy.

  13. Exploring the Spatial-Temporal Disparities of Urban Land Use Economic Efficiency in China and Its Influencing Factors under Environmental Constraints Based on a Sequential Slacks-Based Model

    Directory of Open Access Journals (Sweden)

    Hualin Xie

    2015-07-01

    Full Text Available Using a sequential slack-based measure (SSBM model, this paper analyzes the spatiotemporal disparities of urban land use economic efficiency (ULUEE under environmental constraints, and its influencing factors in 270 cities across China from 2003–2012. The main results are as follows: (1 The average ULUEE for Chinese cities is only 0.411, and out of the 270 cities, only six cities are always efficient in urban land use in the study period. Most cities have a lot of room to improve the economic output of secondary and tertiary industries, as well as environmental protection work; (2 The eastern region of China enjoys the highest ULUEE, followed by the western and central regions. Super-scale cities show the best performance of all four city scales, followed by large-scale, small-scale and medium-scale cities. Cities with relatively developed economies and less pollutant discharge always have better ULUEE; (3 The results of slack variables analysis show that most cities have problems such as the labor surplus, over-development, excessive pollutant discharge, economic output shortage, and unreasonable use of funds is the most serious one; (4 The regression results of the influencing factors show that improvements of the per capita GDP and land use intensity are helpful to raise ULUEE. The urbanization rate and the proportion of foreign enterprises’ output account for the total output in the secondary and tertiary industries only have the same effect in some regions and city scales. The land management policy and land leasing policy have negative impact on the ULUEE in all the three regions and four city scales; (5 Some targeted policy goals are proposed, including the reduction of surplus labor, and pay more attention to environmental protection. Most importantly, effective implementation of land management policies from the central government, and stopping blind leasing of land to make up the local government’s financial deficit would be very

  14. Advances in sequential data assimilation and numerical weather forecasting: An Ensemble Transform Kalman-Bucy Filter, a study on clustering in deterministic ensemble square root filters, and a test of a new time stepping scheme in an atmospheric model

    Science.gov (United States)

    Amezcua, Javier

    This dissertation deals with aspects of sequential data assimilation (in particular ensemble Kalman filtering) and numerical weather forecasting. In the first part, the recently formulated Ensemble Kalman-Bucy (EnKBF) filter is revisited. It is shown that the previously used numerical integration scheme fails when the magnitude of the background error covariance grows beyond that of the observational error covariance in the forecast window. Therefore, we present a suitable integration scheme that handles the stiffening of the differential equations involved and doesn't represent further computational expense. Moreover, a transform-based alternative to the EnKBF is developed: under this scheme, the operations are performed in the ensemble space instead of in the state space. Advantages of this formulation are explained. For the first time, the EnKBF is implemented in an atmospheric model. The second part of this work deals with ensemble clustering, a phenomenon that arises when performing data assimilation using of deterministic ensemble square root filters in highly nonlinear forecast models. Namely, an M-member ensemble detaches into an outlier and a cluster of M-1 members. Previous works may suggest that this issue represents a failure of EnSRFs; this work dispels that notion. It is shown that ensemble clustering can be reverted also due to nonlinear processes, in particular the alternation between nonlinear expansion and compression of the ensemble for different regions of the attractor. Some EnSRFs that use random rotations have been developed to overcome this issue; these formulations are analyzed and their advantages and disadvantages with respect to common EnSRFs are discussed. The third and last part contains the implementation of the Robert-Asselin-Williams (RAW) filter in an atmospheric model. The RAW filter is an improvement to the widely popular Robert-Asselin filter that successfully suppresses spurious computational waves while avoiding any distortion

  15. Monitoring, Modeling, and Diagnosis of Alkali-Silica Reaction in Small Concrete Samples

    Energy Technology Data Exchange (ETDEWEB)

    Agarwal, Vivek [Idaho National Lab. (INL), Idaho Falls, ID (United States); Cai, Guowei [Idaho National Lab. (INL), Idaho Falls, ID (United States); Gribok, Andrei V. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Mahadevan, Sankaran [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2015-09-01

    Assessment and management of aging concrete structures in nuclear power plants require a more systematic approach than simple reliance on existing code margins of safety. Structural health monitoring of concrete structures aims to understand the current health condition of a structure based on heterogeneous measurements to produce high-confidence actionable information regarding structural integrity that supports operational and maintenance decisions. This report describes alkali-silica reaction (ASR) degradation mechanisms and factors influencing the ASR. A fully coupled thermo-hydro-mechanical-chemical model developed by Saouma and Perotti by taking into consideration the effects of stress on the reaction kinetics and anisotropic volumetric expansion is presented in this report. This model is implemented in the GRIZZLY code based on the Multiphysics Object Oriented Simulation Environment. The implemented model in the GRIZZLY code is randomly used to initiate ASR in a 2D and 3D lattice to study the percolation aspects of concrete. The percolation aspects help determine the transport properties of the material and therefore the durability and service life of concrete. This report summarizes the effort to develop small-size concrete samples with embedded glass to mimic ASR. The concrete samples were treated in water and sodium hydroxide solution at elevated temperature to study how ingress of sodium ions and hydroxide ions at elevated temperature impacts concrete samples embedded with glass. Thermal camera was used to monitor the changes in the concrete sample and results are summarized.

  16. Infusion and sampling site effects on two-pool model estimates of leucine metabolism

    International Nuclear Information System (INIS)

    Helland, S.J.; Grisdale-Helland, B.; Nissen, S.

    1988-01-01

    To assess the effect of site of isotope infusion on estimates of leucine metabolism infusions of alpha-[4,5-3H]ketoisocaproate (KIC) and [U- 14 C]leucine were made into the left or right ventricles of sheep and pigs. Blood was sampled from the opposite ventricle. In both species, left ventricular infusions resulted in significantly lower specific radioactivities (SA) of [ 14 C]leucine and [ 3 H]KIC. [ 14 C]KIC SA was found to be insensitive to infusion and sampling sites. [ 14 C]KIC was in addition found to be equal to the SA of [ 14 C]leucine only during the left heart infusions. Therefore, [ 14 C]KIC SA was used as the only estimate for [ 14 C]SA in the equations for the two-pool model. This model eliminated the influence of site of infusion and blood sampling on the estimates for leucine entry and reduced the impact on the estimates for proteolysis and oxidation. This two-pool model could not compensate for the underestimation of transamination reactions occurring during the traditional venous isotope infusion and arterial blood sampling

  17. An inversion-relaxation approach for sampling stationary points of spin model Hamiltonians

    International Nuclear Information System (INIS)

    Hughes, Ciaran; Mehta, Dhagash; Wales, David J.

    2014-01-01

    Sampling the stationary points of a complicated potential energy landscape is a challenging problem. Here, we introduce a sampling method based on relaxation from stationary points of the highest index of the Hessian matrix. We illustrate how this approach can find all the stationary points for potentials or Hamiltonians bounded from above, which includes a large class of important spin models, and we show that it is far more efficient than previous methods. For potentials unbounded from above, the relaxation part of the method is still efficient in finding minima and transition states, which are usually the primary focus of attention for atomistic systems

  18. Optimisation of beryllium-7 gamma analysis following BCR sequential extraction

    Energy Technology Data Exchange (ETDEWEB)

    Taylor, A. [Plymouth University, School of Geography, Earth and Environmental Sciences, 8 Kirkby Place, Plymouth PL4 8AA (United Kingdom); Blake, W.H., E-mail: wblake@plymouth.ac.uk [Plymouth University, School of Geography, Earth and Environmental Sciences, 8 Kirkby Place, Plymouth PL4 8AA (United Kingdom); Keith-Roach, M.J. [Plymouth University, School of Geography, Earth and Environmental Sciences, 8 Kirkby Place, Plymouth PL4 8AA (United Kingdom); Kemakta Konsult, Stockholm (Sweden)

    2012-03-30

    Graphical abstract: Showing decrease in analytical uncertainty using the optimal (combined preconcentrated sample extract) method. nv (no value) where extract activities were Sequential extraction with natural {sup 7}Be returns high analytical uncertainties. Black-Right-Pointing-Pointer Preconcentrating extracts from a large sample mass improved analytical uncertainty. Black-Right-Pointing-Pointer This optimised method can be readily employed in studies using low activity samples. - Abstract: The application of cosmogenic {sup 7}Be as a sediment tracer at the catchment-scale requires an understanding of its geochemical associations in soil to underpin the assumption of irreversible adsorption. Sequential extractions offer a readily accessible means of determining the associations of {sup 7}Be with operationally defined soil phases. However, the subdivision of the low activity concentrations of fallout {sup 7}Be in soils into geochemical fractions can introduce high gamma counting uncertainties. Extending analysis time significantly is not always an option for batches of samples, owing to the on-going decay of {sup 7}Be (t{sub 1/2} = 53.3 days). Here, three different methods of preparing and quantifying {sup 7}Be extracted using the optimised BCR three-step scheme have been evaluated and compared with a focus on reducing analytical uncertainties. The optimal method involved carrying out the BCR extraction in triplicate, sub-sampling each set of triplicates for stable Be analysis before combining each set and coprecipitating the {sup 7}Be with metal oxyhydroxides to produce a thin source for gamma analysis. This method was applied to BCR extractions of natural {sup 7}Be in four agricultural soils. The approach gave good counting statistics from a 24 h analysis period ({approx}10% (2

  19. The hybrid model for sampling multiple elastic scattering angular deflections based on Goudsmit-Saunderson theory

    Directory of Open Access Journals (Sweden)

    Wasaye Muhammad Abdul

    2017-01-01

    Full Text Available An algorithm for the Monte Carlo simulation of electron multiple elastic scattering based on the framework of SuperMC (Super Monte Carlo simulation program for nuclear and radiation process is presented. This paper describes efficient and accurate methods by which the multiple scattering angular deflections are sampled. The Goudsmit-Saunderson theory of multiple scattering has been used for sampling angular deflections. Differential cross-sections of electrons and positrons by neutral atoms have been calculated by using Dirac partial wave program ELSEPA. The Legendre coefficients are accurately computed by using the Gauss-Legendre integration method. Finally, a novel hybrid method for sampling angular distribution has been developed. The model uses efficient rejection sampling method for low energy electrons (500 mean free paths. For small path lengths, a simple, efficient and accurate analytical distribution function has been proposed. The later uses adjustable parameters determined from the fitting of Goudsmith-Saunderson angular distribution. A discussion of the sampling efficiency and accuracy of this newly developed algorithm is given. The efficiency of rejection sampling algorithm is at least 50 % for electron kinetic energies less than 500 keV and longer path lengths (>500 mean free paths. Monte Carlo Simulation results are then compared with measured angular distributions of Ross et al. The comparison shows that our results are in good agreement with experimental measurements.

  20. Tradable permit allocations and sequential choice

    Energy Technology Data Exchange (ETDEWEB)

    MacKenzie, Ian A. [Centre for Economic Research, ETH Zuerich, Zurichbergstrasse 18, 8092 Zuerich (Switzerland)

    2011-01-15

    This paper investigates initial allocation choices in an international tradable pollution permit market. For two sovereign governments, we compare allocation choices that are either simultaneously or sequentially announced. We show sequential allocation announcements result in higher (lower) aggregate emissions when announcements are strategic substitutes (complements). Whether allocation announcements are strategic substitutes or complements depends on the relationship between the follower's damage function and governments' abatement costs. When the marginal damage function is relatively steep (flat), allocation announcements are strategic substitutes (complements). For quadratic abatement costs and damages, sequential announcements provide a higher level of aggregate emissions. (author)