Ensemble Sampling vs. Time Sampling in Molecular Dynamics Simulations of Thermal Conductivity

DOE PAGES

Gordiz, Kiarash; Singh, David J.; Henry, Asegun

2015-01-29

In this report we compare time sampling and ensemble averaging as two different methods available for phase space sampling. For the comparison, we calculate thermal conductivities of solid argon and silicon structures, using equilibrium molecular dynamics. We introduce two different schemes for the ensemble averaging approach, and show that both can reduce the total simulation time as compared to time averaging. It is also found that velocity rescaling is an efficient mechanism for phase space exploration. Although our methodology is tested using classical molecular dynamics, the ensemble generation approaches may find their greatest utility in computationally expensive simulations such asmore » first principles molecular dynamics. For such simulations, where each time step is costly, time sampling can require long simulation times because each time step must be evaluated sequentially and therefore phase space averaging is achieved through sequential operations. On the other hand, with ensemble averaging, phase space sampling can be achieved through parallel operations, since each ensemble is independent. For this reason, particularly when using massively parallel architectures, ensemble sampling can result in much shorter simulation times and exhibits similar overall computational effort.« less

Acceleration of discrete stochastic biochemical simulation using GPGPU.

PubMed

Sumiyoshi, Kei; Hirata, Kazuki; Hiroi, Noriko; Funahashi, Akira

2015-01-01

For systems made up of a small number of molecules, such as a biochemical network in a single cell, a simulation requires a stochastic approach, instead of a deterministic approach. The stochastic simulation algorithm (SSA) simulates the stochastic behavior of a spatially homogeneous system. Since stochastic approaches produce different results each time they are used, multiple runs are required in order to obtain statistical results; this results in a large computational cost. We have implemented a parallel method for using SSA to simulate a stochastic model; the method uses a graphics processing unit (GPU), which enables multiple realizations at the same time, and thus reduces the computational time and cost. During the simulation, for the purpose of analysis, each time course is recorded at each time step. A straightforward implementation of this method on a GPU is about 16 times faster than a sequential simulation on a CPU with hybrid parallelization; each of the multiple simulations is run simultaneously, and the computational tasks within each simulation are parallelized. We also implemented an improvement to the memory access and reduced the memory footprint, in order to optimize the computations on the GPU. We also implemented an asynchronous data transfer scheme to accelerate the time course recording function. To analyze the acceleration of our implementation on various sizes of model, we performed SSA simulations on different model sizes and compared these computation times to those for sequential simulations with a CPU. When used with the improved time course recording function, our method was shown to accelerate the SSA simulation by a factor of up to 130.

Acceleration of discrete stochastic biochemical simulation using GPGPU

PubMed Central

Sumiyoshi, Kei; Hirata, Kazuki; Hiroi, Noriko; Funahashi, Akira

2015-01-01

For systems made up of a small number of molecules, such as a biochemical network in a single cell, a simulation requires a stochastic approach, instead of a deterministic approach. The stochastic simulation algorithm (SSA) simulates the stochastic behavior of a spatially homogeneous system. Since stochastic approaches produce different results each time they are used, multiple runs are required in order to obtain statistical results; this results in a large computational cost. We have implemented a parallel method for using SSA to simulate a stochastic model; the method uses a graphics processing unit (GPU), which enables multiple realizations at the same time, and thus reduces the computational time and cost. During the simulation, for the purpose of analysis, each time course is recorded at each time step. A straightforward implementation of this method on a GPU is about 16 times faster than a sequential simulation on a CPU with hybrid parallelization; each of the multiple simulations is run simultaneously, and the computational tasks within each simulation are parallelized. We also implemented an improvement to the memory access and reduced the memory footprint, in order to optimize the computations on the GPU. We also implemented an asynchronous data transfer scheme to accelerate the time course recording function. To analyze the acceleration of our implementation on various sizes of model, we performed SSA simulations on different model sizes and compared these computation times to those for sequential simulations with a CPU. When used with the improved time course recording function, our method was shown to accelerate the SSA simulation by a factor of up to 130. PMID:25762936

Robust patella motion tracking using intensity-based 2D-3D registration on dynamic bi-plane fluoroscopy: towards quantitative assessment in MPFL reconstruction surgery

NASA Astrophysics Data System (ADS)

Otake, Yoshito; Esnault, Matthieu; Grupp, Robert; Kosugi, Shinichi; Sato, Yoshinobu

2016-03-01

The determination of in vivo motion of multiple-bones using dynamic fluoroscopic images and computed tomography (CT) is useful for post-operative assessment of orthopaedic surgeries such as medial patellofemoral ligament reconstruction. We propose a robust method to measure the 3D motion of multiple rigid objects with high accuracy using a series of bi-plane fluoroscopic images and a multi-resolution, intensity-based, 2D-3D registration. A Covariance Matrix Adaptation Evolution Strategy (CMA-ES) optimizer was used with a gradient correlation similarity metric. Four approaches to register three rigid objects (femur, tibia-fibula and patella) were implemented: 1) an individual bone approach registering one bone at a time, each with optimization of a six degrees of freedom (6DOF) parameter, 2) a sequential approach registering one bone at a time but using the previous bone results as the background in DRR generation, 3) a simultaneous approach registering all the bones together (18DOF) and 4) a combination of the sequential and the simultaneous approaches. These approaches were compared in experiments using simulated images generated from the CT of a healthy volunteer and measured fluoroscopic images. Over the 120 simulated frames of motion, the simultaneous approach showed improved registration accuracy compared to the individual approach: with less than 0.68mm root-mean-square error (RMSE) for translation and less than 1.12° RMSE for rotation. A robustness evaluation was conducted with 45 trials of a randomly perturbed initialization showed that the sequential approach improved robustness significantly (74% success rate) compared to the individual bone approach (34% success) for patella registration (femur and tibia-fibula registration had a 100% success rate with each approach).

On extending parallelism to serial simulators

NASA Technical Reports Server (NTRS)

Nicol, David; Heidelberger, Philip

1994-01-01

This paper describes an approach to discrete event simulation modeling that appears to be effective for developing portable and efficient parallel execution of models of large distributed systems and communication networks. In this approach, the modeler develops submodels using an existing sequential simulation modeling tool, using the full expressive power of the tool. A set of modeling language extensions permit automatically synchronized communication between submodels; however, the automation requires that any such communication must take a nonzero amount off simulation time. Within this modeling paradigm, a variety of conservative synchronization protocols can transparently support conservative execution of submodels on potentially different processors. A specific implementation of this approach, U.P.S. (Utilitarian Parallel Simulator), is described, along with performance results on the Intel Paragon.

Performance evaluation of an asynchronous multisensor track fusion filter

NASA Astrophysics Data System (ADS)

Alouani, Ali T.; Gray, John E.; McCabe, D. H.

2003-08-01

Recently the authors developed a new filter that uses data generated by asynchronous sensors to produce a state estimate that is optimal in the minimum mean square sense. The solution accounts for communications delay between sensors platform and fusion center. It also deals with out of sequence data as well as latent data by processing the information in a batch-like manner. This paper compares, using simulated targets and Monte Carlo simulations, the performance of the filter to the optimal sequential processing approach. It was found that the new asynchronous Multisensor track fusion filter (AMSTFF) performance is identical to that of the extended sequential Kalman filter (SEKF), while the new filter updates its track at a much lower rate than the SEKF.

Time scale of random sequential adsorption.

PubMed

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.

Manual flying of curved precision approaches to landing with electromechanical instrumentation. A piloted simulation study

NASA Technical Reports Server (NTRS)

Knox, Charles E.

1993-01-01

A piloted simulation study was conducted to examine the requirements for using electromechanical flight instrumentation to provide situation information and flight guidance for manually controlled flight along curved precision approach paths to a landing. Six pilots were used as test subjects. The data from these tests indicated that flight director guidance is required for the manually controlled flight of a jet transport airplane on curved approach paths. Acceptable path tracking performance was attained with each of the three situation information algorithms tested. Approach paths with both multiple sequential turns and short final path segments were evaluated. Pilot comments indicated that all the approach paths tested could be used in normal airline operations.

A Sequential Monte Carlo Approach for Streamflow Forecasting

NASA Astrophysics Data System (ADS)

Hsu, K.; Sorooshian, S.

2008-12-01

As alternatives to traditional physically-based models, Artificial Neural Network (ANN) models offer some advantages with respect to the flexibility of not requiring the precise quantitative mechanism of the process and the ability to train themselves from the data directly. In this study, an ANN model was used to generate one-day-ahead streamflow forecasts from the precipitation input over a catchment. Meanwhile, the ANN model parameters were trained using a Sequential Monte Carlo (SMC) approach, namely Regularized Particle Filter (RPF). The SMC approaches are known for their capabilities in tracking the states and parameters of a nonlinear dynamic process based on the Baye's rule and the proposed effective sampling and resampling strategies. In this study, five years of daily rainfall and streamflow measurement were used for model training. Variable sample sizes of RPF, from 200 to 2000, were tested. The results show that, after 1000 RPF samples, the simulation statistics, in terms of correlation coefficient, root mean square error, and bias, were stabilized. It is also shown that the forecasted daily flows fit the observations very well, with the correlation coefficient of higher than 0.95. The results of RPF simulations were also compared with those from the popular back-propagation ANN training approach. The pros and cons of using SMC approach and the traditional back-propagation approach will be discussed.

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

Wendt, Fabian F; Damiani, Rick R

This poster summarizes the scope and preliminary results of a study conducted for the Bureau of Safety and Environmental Enforcement aimed at quantifying differences between two modeling approaches (fully coupled and sequentially coupled) through aero-hydro-servo-elastic simulations of two offshore wind turbines on a monopile and jacket substructure.

A sequential coalescent algorithm for chromosomal inversions

PubMed Central

Peischl, S; Koch, E; Guerrero, R F; Kirkpatrick, M

2013-01-01

Chromosomal inversions are common in natural populations and are believed to be involved in many important evolutionary phenomena, including speciation, the evolution of sex chromosomes and local adaptation. While recent advances in sequencing and genotyping methods are leading to rapidly increasing amounts of genome-wide sequence data that reveal interesting patterns of genetic variation within inverted regions, efficient simulation methods to study these patterns are largely missing. In this work, we extend the sequential Markovian coalescent, an approximation to the coalescent with recombination, to include the effects of polymorphic inversions on patterns of recombination. Results show that our algorithm is fast, memory-efficient and accurate, making it feasible to simulate large inversions in large populations for the first time. The SMC algorithm enables studies of patterns of genetic variation (for example, linkage disequilibria) and tests of hypotheses (using simulation-based approaches) that were previously intractable. PMID:23632894

Multi-point objective-oriented sequential sampling strategy for constrained robust design

NASA Astrophysics Data System (ADS)

Zhu, Ping; Zhang, Siliang; Chen, Wei

2015-03-01

Metamodelling techniques are widely used to approximate system responses of expensive simulation models. In association with the use of metamodels, objective-oriented sequential sampling methods have been demonstrated to be effective in balancing the need for searching an optimal solution versus reducing the metamodelling uncertainty. However, existing infilling criteria are developed for deterministic problems and restricted to one sampling point in one iteration. To exploit the use of multiple samples and identify the true robust solution in fewer iterations, a multi-point objective-oriented sequential sampling strategy is proposed for constrained robust design problems. In this article, earlier development of objective-oriented sequential sampling strategy for unconstrained robust design is first extended to constrained problems. Next, a double-loop multi-point sequential sampling strategy is developed. The proposed methods are validated using two mathematical examples followed by a highly nonlinear automotive crashworthiness design example. The results show that the proposed method can mitigate the effect of both metamodelling uncertainty and design uncertainty, and identify the robust design solution more efficiently than the single-point sequential sampling approach.

A Complementary Note to 'A Lag-1 Smoother Approach to System-Error Estimation': The Intrinsic Limitations of Residual Diagnostics

NASA Technical Reports Server (NTRS)

Todling, Ricardo

2015-01-01

Recently, this author studied an approach to the estimation of system error based on combining observation residuals derived from a sequential filter and fixed lag-1 smoother. While extending the methodology to a variational formulation, experimenting with simple models and making sure consistency was found between the sequential and variational formulations, the limitations of the residual-based approach came clearly to the surface. This note uses the sequential assimilation application to simple nonlinear dynamics to highlight the issue. Only when some of the underlying error statistics are assumed known is it possible to estimate the unknown component. In general, when considerable uncertainties exist in the underlying statistics as a whole, attempts to obtain separate estimates of the various error covariances are bound to lead to misrepresentation of errors. The conclusions are particularly relevant to present-day attempts to estimate observation-error correlations from observation residual statistics. A brief illustration of the issue is also provided by comparing estimates of error correlations derived from a quasi-operational assimilation system and a corresponding Observing System Simulation Experiments framework.

Fast Acceleration of 2D Wave Propagation Simulations Using Modern Computational Accelerators

PubMed Central

Wang, Wei; Xu, Lifan; Cavazos, John; Huang, Howie H.; Kay, Matthew

2014-01-01

Recent developments in modern computational accelerators like Graphics Processing Units (GPUs) and coprocessors provide great opportunities for making scientific applications run faster than ever before. However, efficient parallelization of scientific code using new programming tools like CUDA requires a high level of expertise that is not available to many scientists. This, plus the fact that parallelized code is usually not portable to different architectures, creates major challenges for exploiting the full capabilities of modern computational accelerators. In this work, we sought to overcome these challenges by studying how to achieve both automated parallelization using OpenACC and enhanced portability using OpenCL. We applied our parallelization schemes using GPUs as well as Intel Many Integrated Core (MIC) coprocessor to reduce the run time of wave propagation simulations. We used a well-established 2D cardiac action potential model as a specific case-study. To the best of our knowledge, we are the first to study auto-parallelization of 2D cardiac wave propagation simulations using OpenACC. Our results identify several approaches that provide substantial speedups. The OpenACC-generated GPU code achieved more than speedup above the sequential implementation and required the addition of only a few OpenACC pragmas to the code. An OpenCL implementation provided speedups on GPUs of at least faster than the sequential implementation and faster than a parallelized OpenMP implementation. An implementation of OpenMP on Intel MIC coprocessor provided speedups of with only a few code changes to the sequential implementation. We highlight that OpenACC provides an automatic, efficient, and portable approach to achieve parallelization of 2D cardiac wave simulations on GPUs. Our approach of using OpenACC, OpenCL, and OpenMP to parallelize this particular model on modern computational accelerators should be applicable to other computational models of wave propagation in multi-dimensional media. PMID:24497950

Accelerating Sequential Gaussian Simulation with a constant path

NASA Astrophysics Data System (ADS)

Nussbaumer, Raphaël; Mariethoz, Grégoire; Gravey, Mathieu; Gloaguen, Erwan; Holliger, Klaus

2018-03-01

Sequential Gaussian Simulation (SGS) is a stochastic simulation technique commonly employed for generating realizations of Gaussian random fields. Arguably, the main limitation of this technique is the high computational cost associated with determining the kriging weights. This problem is compounded by the fact that often many realizations are required to allow for an adequate uncertainty assessment. A seemingly simple way to address this problem is to keep the same simulation path for all realizations. This results in identical neighbourhood configurations and hence the kriging weights only need to be determined once and can then be re-used in all subsequent realizations. This approach is generally not recommended because it is expected to result in correlation between the realizations. Here, we challenge this common preconception and make the case for the use of a constant path approach in SGS by systematically evaluating the associated benefits and limitations. We present a detailed implementation, particularly regarding parallelization and memory requirements. Extensive numerical tests demonstrate that using a constant path allows for substantial computational gains with very limited loss of simulation accuracy. This is especially the case for a constant multi-grid path. The computational savings can be used to increase the neighbourhood size, thus allowing for a better reproduction of the spatial statistics. The outcome of this study is a recommendation for an optimal implementation of SGS that maximizes accurate reproduction of the covariance structure as well as computational efficiency.

Development of a software framework for data assimilation and its applications for streamflow forecasting in Japan

NASA Astrophysics Data System (ADS)

Noh, S. J.; Tachikawa, Y.; Shiiba, M.; Yorozu, K.; Kim, S.

2012-04-01

Data assimilation methods have received increased attention to accomplish uncertainty assessment and enhancement of forecasting capability in various areas. Despite of their potentials, applicable software frameworks to probabilistic approaches and data assimilation are still limited because the most of hydrologic modeling software are based on a deterministic approach. In this study, we developed a hydrological modeling framework for sequential data assimilation, so called MPI-OHyMoS. MPI-OHyMoS allows user to develop his/her own element models and to easily build a total simulation system model for hydrological simulations. Unlike process-based modeling framework, this software framework benefits from its object-oriented feature to flexibly represent hydrological processes without any change of the main library. Sequential data assimilation based on the particle filters is available for any hydrologic models based on MPI-OHyMoS considering various sources of uncertainty originated from input forcing, parameters and observations. The particle filters are a Bayesian learning process in which the propagation of all uncertainties is carried out by a suitable selection of randomly generated particles without any assumptions about the nature of the distributions. In MPI-OHyMoS, ensemble simulations are parallelized, which can take advantage of high performance computing (HPC) system. We applied this software framework for short-term streamflow forecasting of several catchments in Japan using a distributed hydrologic model. Uncertainty of model parameters and remotely-sensed rainfall data such as X-band or C-band radar is estimated and mitigated in the sequential data assimilation.

Novel high-fidelity realistic explosion damage simulation for urban environments

NASA Astrophysics Data System (ADS)

Liu, Xiaoqing; Yadegar, Jacob; Zhu, Youding; Raju, Chaitanya; Bhagavathula, Jaya

2010-04-01

Realistic building damage simulation has a significant impact in modern modeling and simulation systems especially in diverse panoply of military and civil applications where these simulation systems are widely used for personnel training, critical mission planning, disaster management, etc. Realistic building damage simulation should incorporate accurate physics-based explosion models, rubble generation, rubble flyout, and interactions between flying rubble and their surrounding entities. However, none of the existing building damage simulation systems sufficiently faithfully realize the criteria of realism required for effective military applications. In this paper, we present a novel physics-based high-fidelity and runtime efficient explosion simulation system to realistically simulate destruction to buildings. In the proposed system, a family of novel blast models is applied to accurately and realistically simulate explosions based on static and/or dynamic detonation conditions. The system also takes account of rubble pile formation and applies a generic and scalable multi-component based object representation to describe scene entities and highly scalable agent-subsumption architecture and scheduler to schedule clusters of sequential and parallel events. The proposed system utilizes a highly efficient and scalable tetrahedral decomposition approach to realistically simulate rubble formation. Experimental results demonstrate that the proposed system has the capability to realistically simulate rubble generation, rubble flyout and their primary and secondary impacts on surrounding objects including buildings, constructions, vehicles and pedestrians in clusters of sequential and parallel damage events.

Computer simulation of a space SAR using a range-sequential processor for soil moisture mapping

NASA Technical Reports Server (NTRS)

Fujita, M.; Ulaby, F. (Principal Investigator)

1982-01-01

The ability of a spaceborne synthetic aperture radar (SAR) to detect soil moisture was evaluated by means of a computer simulation technique. The computer simulation package includes coherent processing of the SAR data using a range-sequential processor, which can be set up through hardware implementations, thereby reducing the amount of telemetry involved. With such a processing approach, it is possible to monitor the earth's surface on a continuous basis, since data storage requirements can be easily met through the use of currently available technology. The Development of the simulation package is described, followed by an examination of the application of the technique to actual environments. The results indicate that in estimating soil moisture content with a four-look processor, the difference between the assumed and estimated values of soil moisture is within + or - 20% of field capacity for 62% of the pixels for agricultural terrain and for 53% of the pixels for hilly terrain. The estimation accuracy for soil moisture may be improved by reducing the effect of fading through non-coherent averaging.

Parallel discrete event simulation: A shared memory approach

NASA Technical Reports Server (NTRS)

Reed, Daniel A.; Malony, Allen D.; Mccredie, Bradley D.

1987-01-01

With traditional event list techniques, evaluating a detailed discrete event simulation model can often require hours or even days of computation time. Parallel simulation mimics the interacting servers and queues of a real system by assigning each simulated entity to a processor. By eliminating the event list and maintaining only sufficient synchronization to insure causality, parallel simulation can potentially provide speedups that are linear in the number of processors. A set of shared memory experiments is presented using the Chandy-Misra distributed simulation algorithm to simulate networks of queues. Parameters include queueing network topology and routing probabilities, number of processors, and assignment of network nodes to processors. These experiments show that Chandy-Misra distributed simulation is a questionable alternative to sequential simulation of most queueing network models.

A computationally efficient Bayesian sequential simulation approach for the assimilation of vast and diverse hydrogeophysical datasets

NASA Astrophysics Data System (ADS)

Nussbaumer, Raphaël; Gloaguen, Erwan; Mariéthoz, Grégoire; Holliger, Klaus

2016-04-01

Bayesian sequential simulation (BSS) is a powerful geostatistical technique, which notably has shown significant potential for the assimilation of datasets that are diverse with regard to the spatial resolution and their relationship. However, these types of applications of BSS require a large number of realizations to adequately explore the solution space and to assess the corresponding uncertainties. Moreover, such simulations generally need to be performed on very fine grids in order to adequately exploit the technique's potential for characterizing heterogeneous environments. Correspondingly, the computational cost of BSS algorithms in their classical form is very high, which so far has limited an effective application of this method to large models and/or vast datasets. In this context, it is also important to note that the inherent assumption regarding the independence of the considered datasets is generally regarded as being too strong in the context of sequential simulation. To alleviate these problems, we have revisited the classical implementation of BSS and incorporated two key features to increase the computational efficiency. The first feature is a combined quadrant spiral - superblock search, which targets run-time savings on large grids and adds flexibility with regard to the selection of neighboring points using equal directional sampling and treating hard data and previously simulated points separately. The second feature is a constant path of simulation, which enhances the efficiency for multiple realizations. We have also modified the aggregation operator to be more flexible with regard to the assumption of independence of the considered datasets. This is achieved through log-linear pooling, which essentially allows for attributing weights to the various data components. Finally, a multi-grid simulating path was created to enforce large-scale variance and to allow for adapting parameters, such as, for example, the log-linear weights or the type of simulation path at various scales. The newly implemented search method for kriging reduces the computational cost from an exponential dependence with regard to the grid size in the original algorithm to a linear relationship, as each neighboring search becomes independent from the grid size. For the considered examples, our results show a sevenfold reduction in run time for each additional realization when a constant simulation path is used. The traditional criticism that constant path techniques introduce a bias to the simulations was explored and our findings do indeed reveal a minor reduction in the diversity of the simulations. This bias can, however, be largely eliminated by changing the path type at different scales through the use of the multi-grid approach. Finally, we show that adapting the aggregation weight at each scale considered in our multi-grid approach allows for reproducing both the variogram and histogram, and the spatial trend of the underlying data.

Flexible sequential designs for multi-arm clinical trials.

PubMed

Magirr, D; Stallard, N; Jaki, T

2014-08-30

Adaptive designs that are based on group-sequential approaches have the benefit of being efficient as stopping boundaries can be found that lead to good operating characteristics with test decisions based solely on sufficient statistics. The drawback of these so called 'pre-planned adaptive' designs is that unexpected design changes are not possible without impacting the error rates. 'Flexible adaptive designs' on the other hand can cope with a large number of contingencies at the cost of reduced efficiency. In this work, we focus on two different approaches for multi-arm multi-stage trials, which are based on group-sequential ideas, and discuss how these 'pre-planned adaptive designs' can be modified to allow for flexibility. We then show how the added flexibility can be used for treatment selection and sample size reassessment and evaluate the impact on the error rates in a simulation study. The results show that an impressive overall procedure can be found by combining a well chosen pre-planned design with an application of the conditional error principle to allow flexible treatment selection. Copyright © 2014 John Wiley & Sons, Ltd.

Regional-scale integration of hydrological and geophysical data using Bayesian sequential simulation: application to field data

NASA Astrophysics Data System (ADS)

Ruggeri, Paolo; Irving, James; Gloaguen, Erwan; Holliger, Klaus

2013-04-01

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending corresponding approaches to the regional scale still represents a major challenge, yet is critically important for the development of groundwater flow and contaminant transport models. To address this issue, we have developed a regional-scale hydrogeophysical data integration technique based on a two-step Bayesian sequential simulation procedure. The objective is to simulate the regional-scale distribution of a hydraulic parameter based on spatially exhaustive, but poorly resolved, measurements of a pertinent geophysical parameter and locally highly resolved, but spatially sparse, measurements of the considered geophysical and hydraulic parameters. To this end, our approach first involves linking the low- and high-resolution geophysical data via a downscaling procedure before relating the downscaled regional-scale geophysical data to the high-resolution hydraulic parameter field. We present the application of this methodology to a pertinent field scenario, where we consider collocated high-resolution measurements of the electrical conductivity, measured using a cone penetrometer testing (CPT) system, and the hydraulic conductivity, estimated from EM flowmeter and slug test measurements, in combination with low-resolution exhaustive electrical conductivity estimates obtained from dipole-dipole ERT meausurements.

Realistic page-turning of electronic books

NASA Astrophysics Data System (ADS)

Fan, Chaoran; Li, Haisheng; Bai, Yannan

2014-01-01

The booming electronic books (e-books), as an extension to the paper book, are popular with readers. Recently, many efforts are put into the realistic page-turning simulation o f e-book to improve its reading experience. This paper presents a new 3D page-turning simulation approach, which employs piecewise time-dependent cylindrical surfaces to describe the turning page and constructs smooth transition method between time-dependent cylinders. The page-turning animation is produced by sequentially mapping the turning page into the cylinders with different radii and positions. Compared to the previous approaches, our method is able to imitate various effects efficiently and obtains more natural animation of turning page.

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

PubMed

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.

Suppressing correlations in massively parallel simulations of lattice models

NASA Astrophysics Data System (ADS)

Kelling, Jeffrey; Ódor, Géza; Gemming, Sibylle

2017-11-01

For lattice Monte Carlo simulations parallelization is crucial to make studies of large systems and long simulation time feasible, while sequential simulations remain the gold-standard for correlation-free dynamics. Here, various domain decomposition schemes are compared, concluding with one which delivers virtually correlation-free simulations on GPUs. Extensive simulations of the octahedron model for 2 + 1 dimensional Kardar-Parisi-Zhang surface growth, which is very sensitive to correlation in the site-selection dynamics, were performed to show self-consistency of the parallel runs and agreement with the sequential algorithm. We present a GPU implementation providing a speedup of about 30 × over a parallel CPU implementation on a single socket and at least 180 × with respect to the sequential reference.

A Review of Enhanced Sampling Approaches for Accelerated Molecular Dynamics

NASA Astrophysics Data System (ADS)

Tiwary, Pratyush; van de Walle, Axel

Molecular dynamics (MD) simulations have become a tool of immense use and popularity for simulating a variety of systems. With the advent of massively parallel computer resources, one now routinely sees applications of MD to systems as large as hundreds of thousands to even several million atoms, which is almost the size of most nanomaterials. However, it is not yet possible to reach laboratory timescales of milliseconds and beyond with MD simulations. Due to the essentially sequential nature of time, parallel computers have been of limited use in solving this so-called timescale problem. Instead, over the years a large range of statistical mechanics based enhanced sampling approaches have been proposed for accelerating molecular dynamics, and accessing timescales that are well beyond the reach of the fastest computers. In this review we provide an overview of these approaches, including the underlying theory, typical applications, and publicly available software resources to implement them.

CFD simulation of hemodynamics in sequential and individual coronary bypass grafts based on multislice CT scan datasets.

PubMed

Hajati, Omid; Zarrabi, Khalil; Karimi, Reza; Hajati, Azadeh

2012-01-01

There is still controversy over the differences in the patency rates of the sequential and individual coronary artery bypass grafting (CABG) techniques. The purpose of this paper was to non-invasively evaluate hemodynamic parameters using complete 3D computational fluid dynamics (CFD) simulations of the sequential and the individual methods based on the patient-specific data extracted from computed tomography (CT) angiography. For CFD analysis, the geometric model of coronary arteries was reconstructed using an ECG-gated 64-detector row CT. Modeling the sequential and individual bypass grafting, this study simulates the flow from the aorta to the occluded posterior descending artery (PDA) and the posterior left ventricle (PLV) vessel with six coronary branches based on the physiologically measured inlet flow as the boundary condition. The maximum calculated wall shear stress (WSS) in the sequential and the individual models were estimated to be 35.1 N/m(2) and 36.5 N/m(2), respectively. Compared to the individual bypass method, the sequential graft has shown a higher velocity at the proximal segment and lower spatial wall shear stress gradient (SWSSG) due to the flow splitting caused by the side-to-side anastomosis. Simulated results combined with its surgical benefits including the requirement of shorter vein length and fewer anastomoses advocate the sequential method as a more favorable CABG method.

PARTICLE FILTERING WITH SEQUENTIAL PARAMETER LEARNING FOR NONLINEAR BOLD fMRI SIGNALS.

PubMed

Xia, Jing; Wang, Michelle Yongmei

Analyzing the blood oxygenation level dependent (BOLD) effect in the functional magnetic resonance imaging (fMRI) is typically based on recent ground-breaking time series analysis techniques. This work represents a significant improvement over existing approaches to system identification using nonlinear hemodynamic models. It is important for three reasons. First, instead of using linearized approximations of the dynamics, we present a nonlinear filtering based on the sequential Monte Carlo method to capture the inherent nonlinearities in the physiological system. Second, we simultaneously estimate the hidden physiological states and the system parameters through particle filtering with sequential parameter learning to fully take advantage of the dynamic information of the BOLD signals. Third, during the unknown static parameter learning, we employ the low-dimensional sufficient statistics for efficiency and avoiding potential degeneration of the parameters. The performance of the proposed method is validated using both the simulated data and real BOLD fMRI data.

Sequential Monte Carlo for inference of latent ARMA time-series with innovations correlated in time

NASA Astrophysics Data System (ADS)

Urteaga, Iñigo; Bugallo, Mónica F.; Djurić, Petar M.

2017-12-01

We consider the problem of sequential inference of latent time-series with innovations correlated in time and observed via nonlinear functions. We accommodate time-varying phenomena with diverse properties by means of a flexible mathematical representation of the data. We characterize statistically such time-series by a Bayesian analysis of their densities. The density that describes the transition of the state from time t to the next time instant t+1 is used for implementation of novel sequential Monte Carlo (SMC) methods. We present a set of SMC methods for inference of latent ARMA time-series with innovations correlated in time for different assumptions in knowledge of parameters. The methods operate in a unified and consistent manner for data with diverse memory properties. We show the validity of the proposed approach by comprehensive simulations of the challenging stochastic volatility model.

Radiative transport produced by oblique illumination of turbid media with collimated beams

NASA Astrophysics Data System (ADS)

Gardner, Adam R.; Kim, Arnold D.; Venugopalan, Vasan

2013-06-01

We examine the general problem of light transport initiated by oblique illumination of a turbid medium with a collimated beam. This situation has direct relevance to the analysis of cloudy atmospheres, terrestrial surfaces, soft condensed matter, and biological tissues. We introduce a solution approach to the equation of radiative transfer that governs this problem, and develop a comprehensive spherical harmonics expansion method utilizing Fourier decomposition (SHEFN). The SHEFN approach enables the solution of problems lacking azimuthal symmetry and provides both the spatial and directional dependence of the radiance. We also introduce the method of sequential-order smoothing that enables the calculation of accurate solutions from the results of two sequential low-order approximations. We apply the SHEFN approach to determine the spatial and angular dependence of both internal and boundary radiances from strongly and weakly scattering turbid media. These solutions are validated using more costly Monte Carlo simulations and reveal important insights regarding the evolution of the radiant field generated by oblique collimated beams spanning ballistic and diffusely scattering regimes.

Placebo non-response measure in sequential parallel comparison design studies.

PubMed

Rybin, Denis; Doros, Gheorghe; Pencina, Michael J; Fava, Maurizio

2015-07-10

The Sequential Parallel Comparison Design (SPCD) is one of the novel approaches addressing placebo response. The analysis of SPCD data typically classifies subjects as 'placebo responders' or 'placebo non-responders'. Most current methods employed for analysis of SPCD data utilize only a part of the data collected during the trial. A repeated measures model was proposed for analysis of continuous outcomes that permitted the inclusion of information from all subjects into the treatment effect estimation. We describe here a new approach using a weighted repeated measures model that further improves the utilization of data collected during the trial, allowing the incorporation of information that is relevant to the placebo response, and dealing with the problem of possible misclassification of subjects. Our simulations show that when compared to the unweighted repeated measures model method, our approach performs as well or, under certain conditions, better, in preserving the type I error, achieving adequate power and minimizing the mean squared error. Copyright © 2015 John Wiley & Sons, Ltd.

Quantifying and Reducing Uncertainty in Correlated Multi-Area Short-Term Load Forecasting

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

Sun, Yannan; Hou, Zhangshuan; Meng, Da

2016-07-17

In this study, we represent and reduce the uncertainties in short-term electric load forecasting by integrating time series analysis tools including ARIMA modeling, sequential Gaussian simulation, and principal component analysis. The approaches are mainly focusing on maintaining the inter-dependency between multiple geographically related areas. These approaches are applied onto cross-correlated load time series as well as their forecast errors. Multiple short-term prediction realizations are then generated from the reduced uncertainty ranges, which are useful for power system risk analyses.

An analysis of approach navigation accuracy and guidance requirements for the grand tour mission to the outer planets

NASA Technical Reports Server (NTRS)

Jones, D. W.

1971-01-01

The navigation and guidance process for the Jupiter, Saturn and Uranus planetary encounter phases of the 1977 Grand Tour interior mission was simulated. Reference approach navigation accuracies were defined and the relative information content of the various observation types were evaluated. Reference encounter guidance requirements were defined, sensitivities to assumed simulation model parameters were determined and the adequacy of the linear estimation theory was assessed. A linear sequential estimator was used to provide an estimate of the augmented state vector, consisting of the six state variables of position and velocity plus the three components of a planet position bias. The guidance process was simulated using a nonspherical model of the execution errors. Computation algorithms which simulate the navigation and guidance process were derived from theory and implemented into two research-oriented computer programs, written in FORTRAN.

Comparative efficacy of simultaneous versus sequential multiple health behavior change interventions among adults: A systematic review of randomised trials.

PubMed

James, Erica; Freund, Megan; Booth, Angela; Duncan, Mitch J; Johnson, Natalie; Short, Camille E; Wolfenden, Luke; Stacey, Fiona G; Kay-Lambkin, Frances; Vandelanotte, Corneel

2016-08-01

Growing evidence points to the benefits of addressing multiple health behaviors rather than single behaviors. This review evaluates the relative effectiveness of simultaneous and sequentially delivered multiple health behavior change (MHBC) interventions. Secondary aims were to identify: a) the most effective spacing of sequentially delivered components; b) differences in efficacy of MHBC interventions for adoption/cessation behaviors and lifestyle/addictive behaviors, and; c) differences in trial retention between simultaneously and sequentially delivered interventions. MHBC intervention trials published up to October 2015 were identified through a systematic search. Eligible trials were randomised controlled trials that directly compared simultaneous and sequential delivery of a MHBC intervention. A narrative synthesis was undertaken. Six trials met the inclusion criteria and across these trials the behaviors targeted were smoking, diet, physical activity, and alcohol consumption. Three trials reported a difference in intervention effect between a sequential and simultaneous approach in at least one behavioral outcome. Of these, two trials favoured a sequential approach on smoking. One trial favoured a simultaneous approach on fat intake. There was no difference in retention between sequential and simultaneous approaches. There is limited evidence regarding the relative effectiveness of sequential and simultaneous approaches. Given only three of the six trials observed a difference in intervention effectiveness for one health behavior outcome, and the relatively consistent finding that the sequential and simultaneous approaches were more effective than a usual/minimal care control condition, it appears that both approaches should be considered equally efficacious. PROSPERO registration number: CRD42015027876. Copyright © 2016 Elsevier Inc. All rights reserved.

Parallel Multi-cycle LES of an Optical Pent-roof DISI Engine Under Motored Operating Conditions

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

Van Dam, Noah; Sjöberg, Magnus; Zeng, Wei

The use of Large-eddy Simulations (LES) has increased due to their ability to resolve the turbulent fluctuations of engine flows and capture the resulting cycle-to-cycle variability. One drawback of LES, however, is the requirement to run multiple engine cycles to obtain the necessary cycle statistics for full validation. The standard method to obtain the cycles by running a single simulation through many engine cycles sequentially can take a long time to complete. Recently, a new strategy has been proposed by our research group to reduce the amount of time necessary to simulate the many engine cycles by running individual enginemore » cycle simulations in parallel. With modern large computing systems this has the potential to reduce the amount of time necessary for a full set of simulated engine cycles to finish by up to an order of magnitude. In this paper, the Parallel Perturbation Methodology (PPM) is used to simulate up to 35 engine cycles of an optically accessible, pent-roof Directinjection Spark-ignition (DISI) engine at two different motored engine operating conditions, one throttled and one un-throttled. Comparisons are made against corresponding sequential-cycle simulations to verify the similarity of results using either methodology. Mean results from the PPM approach are very similar to sequential-cycle results with less than 0.5% difference in pressure and a magnitude structure index (MSI) of 0.95. Differences in cycle-to-cycle variability (CCV) predictions are larger, but close to the statistical uncertainty in the measurement for the number of cycles simulated. PPM LES results were also compared against experimental data. Mean quantities such as pressure or mean velocities were typically matched to within 5- 10%. Pressure CCVs were under-predicted, mostly due to the lack of any perturbations in the pressure boundary conditions between cycles. Velocity CCVs for the simulations had the same average magnitude as experiments, but the experimental data showed greater spatial variation in the root-mean-square (RMS). Conversely, circular standard deviation results showed greater repeatability of the flow directionality and swirl vortex positioning than the simulations.« less

Field-scale multi-phase LNAPL remediation: Validating a new computational framework against sequential field pilot trials.

PubMed

Sookhak Lari, Kaveh; Johnston, Colin D; Rayner, John L; Davis, Greg B

2018-03-05

Remediation of subsurface systems, including groundwater, soil and soil gas, contaminated with light non-aqueous phase liquids (LNAPLs) is challenging. Field-scale pilot trials of multi-phase remediation were undertaken at a site to determine the effectiveness of recovery options. Sequential LNAPL skimming and vacuum-enhanced skimming, with and without water table drawdown were trialled over 78days; in total extracting over 5m 3 of LNAPL. For the first time, a multi-component simulation framework (including the multi-phase multi-component code TMVOC-MP and processing codes) was developed and applied to simulate the broad range of multi-phase remediation and recovery methods used in the field trials. This framework was validated against the sequential pilot trials by comparing predicted and measured LNAPL mass removal rates and compositional changes. The framework was tested on both a Cray supercomputer and a cluster. Simulations mimicked trends in LNAPL recovery rates (from 0.14 to 3mL/s) across all remediation techniques each operating over periods of 4-14days over the 78day trial. The code also approximated order of magnitude compositional changes of hazardous chemical concentrations in extracted gas during vacuum-enhanced recovery. The verified framework enables longer term prediction of the effectiveness of remediation approaches allowing better determination of remediation endpoints and long-term risks. Copyright © 2017 Commonwealth Scientific and Industrial Research Organisation. Published by Elsevier B.V. All rights reserved.

Multidimensional oriented solid-state NMR experiments enable the sequential assignment of uniformly 15N labeled integral membrane proteins in magnetically aligned lipid bilayers.

PubMed

Mote, Kaustubh R; Gopinath, T; Traaseth, Nathaniel J; Kitchen, Jason; Gor'kov, Peter L; Brey, William W; Veglia, Gianluigi

2011-11-01

Oriented solid-state NMR is the most direct methodology to obtain the orientation of membrane proteins with respect to the lipid bilayer. The method consists of measuring (1)H-(15)N dipolar couplings (DC) and (15)N anisotropic chemical shifts (CSA) for membrane proteins that are uniformly aligned with respect to the membrane bilayer. A significant advantage of this approach is that tilt and azimuthal (rotational) angles of the protein domains can be directly derived from analytical expression of DC and CSA values, or, alternatively, obtained by refining protein structures using these values as harmonic restraints in simulated annealing calculations. The Achilles' heel of this approach is the lack of suitable experiments for sequential assignment of the amide resonances. In this Article, we present a new pulse sequence that integrates proton driven spin diffusion (PDSD) with sensitivity-enhanced PISEMA in a 3D experiment ([(1)H,(15)N]-SE-PISEMA-PDSD). The incorporation of 2D (15)N/(15)N spin diffusion experiments into this new 3D experiment leads to the complete and unambiguous assignment of the (15)N resonances. The feasibility of this approach is demonstrated for the membrane protein sarcolipin reconstituted in magnetically aligned lipid bicelles. Taken with low electric field probe technology, this approach will propel the determination of sequential assignment as well as structure and topology of larger integral membrane proteins in aligned lipid bilayers. © Springer Science+Business Media B.V. 2011

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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. 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%.

Reactive Transport Modeling of Induced Calcite Precipitation Reaction Fronts in Porous Media Using A Parallel, Fully Coupled, Fully Implicit Approach

NASA Astrophysics Data System (ADS)

Guo, L.; Huang, H.; Gaston, D.; Redden, G. D.; Fox, D. T.; Fujita, Y.

2010-12-01

Inducing mineral precipitation in the subsurface is one potential strategy for immobilizing trace metal and radionuclide contaminants. Generating mineral precipitates in situ can be achieved by manipulating chemical conditions, typically through injection or in situ generation of reactants. How these reactants transport, mix and react within the medium controls the spatial distribution and composition of the resulting mineral phases. Multiple processes, including fluid flow, dispersive/diffusive transport of reactants, biogeochemical reactions and changes in porosity-permeability, are tightly coupled over a number of scales. Numerical modeling can be used to investigate the nonlinear coupling effects of these processes which are quite challenging to explore experimentally. Many subsurface reactive transport simulators employ a de-coupled or operator-splitting approach where transport equations and batch chemistry reactions are solved sequentially. However, such an approach has limited applicability for biogeochemical systems with fast kinetics and strong coupling between chemical reactions and medium properties. A massively parallel, fully coupled, fully implicit Reactive Transport simulator (referred to as “RAT”) based on a parallel multi-physics object-oriented simulation framework (MOOSE) has been developed at the Idaho National Laboratory. Within this simulator, systems of transport and reaction equations can be solved simultaneously in a fully coupled, fully implicit manner using the Jacobian Free Newton-Krylov (JFNK) method with additional advanced computing capabilities such as (1) physics-based preconditioning for solution convergence acceleration, (2) massively parallel computing and scalability, and (3) adaptive mesh refinements for 2D and 3D structured and unstructured mesh. The simulator was first tested against analytical solutions, then applied to simulating induced calcium carbonate mineral precipitation in 1D columns and 2D flow cells as analogs to homogeneous and heterogeneous porous media, respectively. In 1D columns, calcium carbonate mineral precipitation was driven by urea hydrolysis catalyzed by urease enzyme, and in 2D flow cells, calcium carbonate mineral forming reactants were injected sequentially, forming migrating reaction fronts that are typically highly nonuniform. The RAT simulation results for the spatial and temporal distributions of precipitates, reaction rates and major species in the system, and also for changes in porosity and permeability, were compared to both laboratory experimental data and computational results obtained using other reactive transport simulators. The comparisons demonstrate the ability of RAT to simulate complex nonlinear systems and the advantages of fully coupled approaches, over de-coupled methods, for accurate simulation of complex, dynamic processes such as engineered mineral precipitation in subsurface environments.

Sequential Computerized Mastery Tests--Three Simulation Studies

ERIC Educational Resources Information Center

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…

The PMHT: solutions for some of its problems

NASA Astrophysics Data System (ADS)

Wieneke, Monika; Koch, Wolfgang

2007-09-01

Tracking multiple targets in a cluttered environment is a challenging task. Probabilistic Multiple Hypothesis Tracking (PMHT) is an efficient approach for dealing with it. Essentially PMHT is based on the method of Expectation-Maximization for handling with association conflicts. Linearity in the number of targets and measurements is the main motivation for a further development and extension of this methodology. Unfortunately, compared with the Probabilistic Data Association Filter (PDAF), PMHT has not yet shown its superiority in terms of track-lost statistics. Furthermore, the problem of track extraction and deletion is apparently not yet satisfactorily solved within this framework. Four properties of PMHT are responsible for its problems in track maintenance: Non-Adaptivity, Hospitality, Narcissism and Local Maxima. 1, 2 In this work we present a solution for each of them and derive an improved PMHT by integrating the solutions into the PMHT formalism. The new PMHT is evaluated by Monte-Carlo simulations. A sequential Likelihood-Ratio (LR) test for track extraction has been developed and already integrated into the framework of traditional Bayesian Multiple Hypothesis Tracking. 3 As a multi-scan approach, also the PMHT methodology has the potential for track extraction. In this paper an analogous integration of a sequential LR test into the PMHT framework is proposed. We present an LR formula for track extraction and deletion using the PMHT update formulae. As PMHT provides all required ingredients for a sequential LR calculation, the LR is thus a by-product of the PMHT iteration process. Therefore the resulting update formula for the sequential LR test affords the development of Track-Before-Detect algorithms for PMHT. The approach is illustrated by a simple example.

Sequentially reweighted TV minimization for CT metal artifact reduction.

PubMed

Zhang, Xiaomeng; Xing, Lei

2013-07-01

Metal artifact reduction has long been an important topic in x-ray CT image reconstruction. In this work, the authors propose an iterative method that sequentially minimizes a reweighted total variation (TV) of the image and produces substantially artifact-reduced reconstructions. A sequentially reweighted TV minimization algorithm is proposed to fully exploit the sparseness of image gradients (IG). The authors first formulate a constrained optimization model that minimizes a weighted TV of the image, subject to the constraint that the estimated projection data are within a specified tolerance of the available projection measurements, with image non-negativity enforced. The authors then solve a sequence of weighted TV minimization problems where weights used for the next iteration are computed from the current solution. Using the complete projection data, the algorithm first reconstructs an image from which a binary metal image can be extracted. Forward projection of the binary image identifies metal traces in the projection space. The metal-free background image is then reconstructed from the metal-trace-excluded projection data by employing a different set of weights. Each minimization problem is solved using a gradient method that alternates projection-onto-convex-sets and steepest descent. A series of simulation and experimental studies are performed to evaluate the proposed approach. Our study shows that the sequentially reweighted scheme, by altering a single parameter in the weighting function, flexibly controls the sparsity of the IG and reconstructs artifacts-free images in a two-stage process. It successfully produces images with significantly reduced streak artifacts, suppressed noise and well-preserved contrast and edge properties. The sequentially reweighed TV minimization provides a systematic approach for suppressing CT metal artifacts. The technique can also be generalized to other "missing data" problems in CT image reconstruction.

Managing numerical errors in random sequential adsorption

NASA Astrophysics Data System (ADS)

Cieśla, Michał; Nowak, Aleksandra

2016-09-01

Aim of this study is to examine the influence of a finite surface size and a finite simulation time on a packing fraction estimated using random sequential adsorption simulations. The goal of particular interest is providing hints on simulation setup to achieve desired level of accuracy. The analysis is based on properties of saturated random packing of disks on continuous and flat surfaces of different sizes.

Applying Reduced Generator Models in the Coarse Solver of Parareal in Time Parallel Power System Simulation

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

Duan, Nan; Dimitrovski, Aleksandar D; Simunovic, Srdjan

2016-01-01

The development of high-performance computing techniques and platforms has provided many opportunities for real-time or even faster-than-real-time implementation of power system simulations. One approach uses the Parareal in time framework. The Parareal algorithm has shown promising theoretical simulation speedups by temporal decomposing a simulation run into a coarse simulation on the entire simulation interval and fine simulations on sequential sub-intervals linked through the coarse simulation. However, it has been found that the time cost of the coarse solver needs to be reduced to fully exploit the potentials of the Parareal algorithm. This paper studies a Parareal implementation using reduced generatormore » models for the coarse solver and reports the testing results on the IEEE 39-bus system and a 327-generator 2383-bus Polish system model.« less

Bayesian Treed Multivariate Gaussian Process with Adaptive Design: Application to a Carbon Capture Unit

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

Konomi, Bledar A.; Karagiannis, Georgios; Sarkar, Avik

2014-05-16

Computer experiments (numerical simulations) are widely used in scientific research to study and predict the behavior of complex systems, which usually have responses consisting of a set of distinct outputs. The computational cost of the simulations at high resolution are often expensive and become impractical for parametric studies at different input values. To overcome these difficulties we develop a Bayesian treed multivariate Gaussian process (BTMGP) as an extension of the Bayesian treed Gaussian process (BTGP) in order to model and evaluate a multivariate process. A suitable choice of covariance function and the prior distributions facilitates the different Markov chain Montemore » Carlo (MCMC) movements. We utilize this model to sequentially sample the input space for the most informative values, taking into account model uncertainty and expertise gained. A simulation study demonstrates the use of the proposed method and compares it with alternative approaches. We apply the sequential sampling technique and BTMGP to model the multiphase flow in a full scale regenerator of a carbon capture unit. The application presented in this paper is an important tool for research into carbon dioxide emissions from thermal power plants.« less

Cluster Correspondence Analysis.

PubMed

van de Velden, M; D'Enza, A Iodice; Palumbo, F

2017-03-01

A method is proposed that combines dimension reduction and cluster analysis for categorical data by simultaneously assigning individuals to clusters and optimal scaling values to categories in such a way that a single between variance maximization objective is achieved. In a unified framework, a brief review of alternative methods is provided and we show that the proposed method is equivalent to GROUPALS applied to categorical data. Performance of the methods is appraised by means of a simulation study. The results of the joint dimension reduction and clustering methods are compared with the so-called tandem approach, a sequential analysis of dimension reduction followed by cluster analysis. The tandem approach is conjectured to perform worse when variables are added that are unrelated to the cluster structure. Our simulation study confirms this conjecture. Moreover, the results of the simulation study indicate that the proposed method also consistently outperforms alternative joint dimension reduction and clustering methods.

Eulerian-Lagrangian Simulations of Transonic Flutter Instabilities

NASA Technical Reports Server (NTRS)

Bendiksen, Oddvar O.

1994-01-01

This paper presents an overview of recent applications of Eulerian-Lagrangian computational schemes in simulating transonic flutter instabilities. This approach, the fluid-structure system is treated as a single continuum dynamics problem, by switching from an Eulerian to a Lagrangian formulation at the fluid-structure boundary. This computational approach effectively eliminates the phase integration errors associated with previous methods, where the fluid and structure are integrated sequentially using different schemes. The formulation is based on Hamilton's Principle in mixed coordinates, and both finite volume and finite element discretization schemes are considered. Results from numerical simulations of transonic flutter instabilities are presented for isolated wings, thin panels, and turbomachinery blades. The results suggest that the method is capable of reproducing the energy exchange between the fluid and the structure with significantly less error than existing methods. Localized flutter modes and panel flutter modes involving traveling waves can also be simulated effectively with no a priori knowledge of the type of instability involved.

Computational Particle Dynamic Simulations on Multicore Processors (CPDMu) Final Report Phase I

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

Schmalz, Mark S

2011-07-24

Statement of Problem - Department of Energy has many legacy codes for simulation of computational particle dynamics and computational fluid dynamics applications that are designed to run on sequential processors and are not easily parallelized. Emerging high-performance computing architectures employ massively parallel multicore architectures (e.g., graphics processing units) to increase throughput. Parallelization of legacy simulation codes is a high priority, to achieve compatibility, efficiency, accuracy, and extensibility. General Statement of Solution - A legacy simulation application designed for implementation on mainly-sequential processors has been represented as a graph G. Mathematical transformations, applied to G, produce a graph representation {und G}more » for a high-performance architecture. Key computational and data movement kernels of the application were analyzed/optimized for parallel execution using the mapping G {yields} {und G}, which can be performed semi-automatically. This approach is widely applicable to many types of high-performance computing systems, such as graphics processing units or clusters comprised of nodes that contain one or more such units. Phase I Accomplishments - Phase I research decomposed/profiled computational particle dynamics simulation code for rocket fuel combustion into low and high computational cost regions (respectively, mainly sequential and mainly parallel kernels), with analysis of space and time complexity. Using the research team's expertise in algorithm-to-architecture mappings, the high-cost kernels were transformed, parallelized, and implemented on Nvidia Fermi GPUs. Measured speedups (GPU with respect to single-core CPU) were approximately 20-32X for realistic model parameters, without final optimization. Error analysis showed no loss of computational accuracy. Commercial Applications and Other Benefits - The proposed research will constitute a breakthrough in solution of problems related to efficient parallel computation of particle and fluid dynamics simulations. These problems occur throughout DOE, military and commercial sectors: the potential payoff is high. We plan to license or sell the solution to contractors for military and domestic applications such as disaster simulation (aerodynamic and hydrodynamic), Government agencies (hydrological and environmental simulations), and medical applications (e.g., in tomographic image reconstruction). Keywords - High-performance Computing, Graphic Processing Unit, Fluid/Particle Simulation. Summary for Members of Congress - Department of Energy has many simulation codes that must compute faster, to be effective. The Phase I research parallelized particle/fluid simulations for rocket combustion, for high-performance computing systems.« less

A fast and precise indoor localization algorithm based on an online sequential extreme learning machine.

PubMed

Zou, Han; Lu, Xiaoxuan; Jiang, Hao; Xie, Lihua

2015-01-15

Nowadays, developing indoor positioning systems (IPSs) has become an attractive research topic due to the increasing demands on location-based service (LBS) in indoor environments. WiFi technology has been studied and explored to provide indoor positioning service for years in view of the wide deployment and availability of existing WiFi infrastructures in indoor environments. A large body of WiFi-based IPSs adopt fingerprinting approaches for localization. However, these IPSs suffer from two major problems: the intensive costs of manpower and time for offline site survey and the inflexibility to environmental dynamics. In this paper, we propose an indoor localization algorithm based on an online sequential extreme learning machine (OS-ELM) to address the above problems accordingly. The fast learning speed of OS-ELM can reduce the time and manpower costs for the offline site survey. Meanwhile, its online sequential learning ability enables the proposed localization algorithm to adapt in a timely manner to environmental dynamics. Experiments under specific environmental changes, such as variations of occupancy distribution and events of opening or closing of doors, are conducted to evaluate the performance of OS-ELM. The simulation and experimental results show that the proposed localization algorithm can provide higher localization accuracy than traditional approaches, due to its fast adaptation to various environmental dynamics.

A Comparison of Trajectory Optimization Methods for the Impulsive Minimum Fuel Rendezvous Problem

NASA Technical Reports Server (NTRS)

Hughes, Steven P.; Mailhe, Laurie M.; Guzman, Jose J.

2002-01-01

In this paper we present a comparison of optimization approaches to the minimum fuel rendezvous problem. Both indirect and direct methods are compared for a variety of test cases. The indirect approach is based on primer vector theory. The direct approaches are implemented numerically and include Sequential Quadratic Programming (SQP), Quasi-Newton, Simplex, Genetic Algorithms, and Simulated Annealing. Each method is applied to a variety of test cases including, circular to circular coplanar orbits, LEO to GEO, and orbit phasing in highly elliptic orbits. We also compare different constrained optimization routines on complex orbit rendezvous problems with complicated, highly nonlinear constraints.

Multigrid methods with space–time concurrency

DOE PAGES

Falgout, R. D.; Friedhoff, S.; Kolev, Tz. V.; ...

2017-10-06

Here, we consider the comparison of multigrid methods for parabolic partial differential equations that allow space–time concurrency. With current trends in computer architectures leading towards systems with more, but not faster, processors, space–time concurrency is crucial for speeding up time-integration simulations. In contrast, traditional time-integration techniques impose serious limitations on parallel performance due to the sequential nature of the time-stepping approach, allowing spatial concurrency only. This paper considers the three basic options of multigrid algorithms on space–time grids that allow parallelism in space and time: coarsening in space and time, semicoarsening in the spatial dimensions, and semicoarsening in the temporalmore » dimension. We develop parallel software and performance models to study the three methods at scales of up to 16K cores and introduce an extension of one of them for handling multistep time integration. We then discuss advantages and disadvantages of the different approaches and their benefit compared to traditional space-parallel algorithms with sequential time stepping on modern architectures.« less

Growth of vertically aligned nanowires in metal-oxide nanocomposites: kinetic Monte-Carlo modeling versus experiments.

PubMed

Hennes, M; Schuler, V; Weng, X; Buchwald, J; Demaille, D; Zheng, Y; Vidal, F

2018-04-26

We employ kinetic Monte-Carlo simulations to study the growth process of metal-oxide nanocomposites obtained via sequential pulsed laser deposition. Using Ni-SrTiO3 (Ni-STO) as a model system, we reduce the complexity of the computational problem by choosing a coarse-grained approach mapping Sr, Ti and O atoms onto a single effective STO pseudo-atom species. With this ansatz, we scrutinize the kinetics of the sequential synthesis process, governed by alternating deposition and relaxation steps, and analyze the self-organization propensity of Ni atoms into straight vertically aligned nanowires embedded in the surrounding STO matrix. We finally compare the predictions of our binary toy model with experiments and demonstrate that our computational approach captures fundamental aspects of self-assembled nanowire synthesis. Despite its simplicity, our modeling strategy successfully describes the impact of relevant parameters like the concentration or laser frequency on the final nanoarchitecture of metal-oxide thin films grown via pulsed laser deposition.

Multigrid methods with space–time concurrency

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

Falgout, R. D.; Friedhoff, S.; Kolev, Tz. V.

Here, we consider the comparison of multigrid methods for parabolic partial differential equations that allow space–time concurrency. With current trends in computer architectures leading towards systems with more, but not faster, processors, space–time concurrency is crucial for speeding up time-integration simulations. In contrast, traditional time-integration techniques impose serious limitations on parallel performance due to the sequential nature of the time-stepping approach, allowing spatial concurrency only. This paper considers the three basic options of multigrid algorithms on space–time grids that allow parallelism in space and time: coarsening in space and time, semicoarsening in the spatial dimensions, and semicoarsening in the temporalmore » dimension. We develop parallel software and performance models to study the three methods at scales of up to 16K cores and introduce an extension of one of them for handling multistep time integration. We then discuss advantages and disadvantages of the different approaches and their benefit compared to traditional space-parallel algorithms with sequential time stepping on modern architectures.« less

Development of a Prototype Simulation Executive with Zooming in the Numerical Propulsion System Simulation

NASA Technical Reports Server (NTRS)

Reed, John A.; Afjeh, Abdollah A.

1995-01-01

A major difficulty in designing aeropropulsion systems is that of identifying and understanding the interactions between the separate engine components and disciplines (e.g., fluid mechanics, structural mechanics, heat transfer, material properties, etc.). The traditional analysis approach is to decompose the system into separate components with the interaction between components being evaluated by the application of each of the single disciplines in a sequential manner. Here, one discipline uses information from the calculation of another discipline to determine the effects of component coupling. This approach, however, may not properly identify the consequences of these effects during the design phase, leaving the interactions to be discovered and evaluated during engine testing. This contributes to the time and cost of developing new propulsion systems as, typically, several design-build-test cycles are needed to fully identify multidisciplinary effects and reach the desired system performance. The alternative to sequential isolated component analysis is to use multidisciplinary coupling at a more fundamental level. This approach has been made more plausible due to recent advancements in computation simulation along with application of concurrent engineering concepts. Computer simulation systems designed to provide an environment which is capable of integrating the various disciplines into a single simulation system have been proposed and are currently being developed. One such system is being developed by the Numerical Propulsion System Simulation (NPSS) project. The NPSS project, being developed at the Interdisciplinary Technology Office at the NASA Lewis Research Center is a 'numerical test cell' designed to provide for comprehensive computational design and analysis of aerospace propulsion systems. It will provide multi-disciplinary analyses on a variety of computational platforms, and a user-interface consisting of expert systems, data base management and visualization tools, to allow the designer to investigate the complex interactions inherent in these systems. An interactive programming software system, known as the Application Visualization System (AVS), was utilized for the development of the propulsion system simulation. The modularity of this system provides the ability to couple propulsion system components, as well as disciplines, and provides for the ability to integrate existing, well established analysis codes into the overall system simulation. This feature allows the user to customize the simulation model by inserting desired analysis codes. The prototypical simulation environment for multidisciplinary analysis, called Turbofan Engine System Simulation (TESS), which incorporates many of the characteristics of the simulation environment proposed herein, is detailed.

An iterative particle filter approach for coupled hydro-geophysical inversion of a controlled infiltration experiment

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

Manoli, Gabriele, E-mail: manoli@dmsa.unipd.it; Nicholas School of the Environment, Duke University, Durham, NC 27708; Rossi, Matteo

The modeling of unsaturated groundwater flow is affected by a high degree of uncertainty related to both measurement and model errors. Geophysical methods such as Electrical Resistivity Tomography (ERT) can provide useful indirect information on the hydrological processes occurring in the vadose zone. In this paper, we propose and test an iterated particle filter method to solve the coupled hydrogeophysical inverse problem. We focus on an infiltration test monitored by time-lapse ERT and modeled using Richards equation. The goal is to identify hydrological model parameters from ERT electrical potential measurements. Traditional uncoupled inversion relies on the solution of two sequentialmore » inverse problems, the first one applied to the ERT measurements, the second one to Richards equation. This approach does not ensure an accurate quantitative description of the physical state, typically violating mass balance. To avoid one of these two inversions and incorporate in the process more physical simulation constraints, we cast the problem within the framework of a SIR (Sequential Importance Resampling) data assimilation approach that uses a Richards equation solver to model the hydrological dynamics and a forward ERT simulator combined with Archie's law to serve as measurement model. ERT observations are then used to update the state of the system as well as to estimate the model parameters and their posterior distribution. The limitations of the traditional sequential Bayesian approach are investigated and an innovative iterative approach is proposed to estimate the model parameters with high accuracy. The numerical properties of the developed algorithm are verified on both homogeneous and heterogeneous synthetic test cases based on a real-world field experiment.« less

Three-dimensional mapping of equiprobable hydrostratigraphic units at the Frenchman Flat Corrective Action Unit, Nevada Test Site

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

Shirley, C.; Pohlmann, K.; Andricevic, R.

1996-09-01

Geological and geophysical data are used with the sequential indicator simulation algorithm of Gomez-Hernandez and Srivastava to produce multiple, equiprobable, three-dimensional maps of informal hydrostratigraphic units at the Frenchman Flat Corrective Action Unit, Nevada Test Site. The upper 50 percent of the Tertiary volcanic lithostratigraphic column comprises the study volume. Semivariograms are modeled from indicator-transformed geophysical tool signals. Each equiprobable study volume is subdivided into discrete classes using the ISIM3D implementation of the sequential indicator simulation algorithm. Hydraulic conductivity is assigned within each class using the sequential Gaussian simulation method of Deutsch and Journel. The resulting maps show the contiguitymore » of high and low hydraulic conductivity regions.« less

A weight modification sequential method for VSC-MTDC power system state estimation

NASA Astrophysics Data System (ADS)

Yang, Xiaonan; Zhang, Hao; Li, Qiang; Guo, Ziming; Zhao, Kun; Li, Xinpeng; Han, Feng

2017-06-01

This paper presents an effective sequential approach based on weight modification for VSC-MTDC power system state estimation, called weight modification sequential method. The proposed approach simplifies the AC/DC system state estimation algorithm through modifying the weight of state quantity to keep the matrix dimension constant. The weight modification sequential method can also make the VSC-MTDC system state estimation calculation results more ccurate and increase the speed of calculation. The effectiveness of the proposed weight modification sequential method is demonstrated and validated in modified IEEE 14 bus system.

Orphan therapies: making best use of postmarket data.

PubMed

Maro, Judith C; Brown, Jeffrey S; Dal Pan, Gerald J; Li, Lingling

2014-08-01

Postmarket surveillance of the comparative safety and efficacy of orphan therapeutics is challenging, particularly when multiple therapeutics are licensed for the same orphan indication. To make best use of product-specific registry data collected to fulfill regulatory requirements, we propose the creation of a distributed electronic health data network among registries. Such a network could support sequential statistical analyses designed to detect early warnings of excess risks. We use a simulated example to explore the circumstances under which a distributed network may prove advantageous. We perform sample size calculations for sequential and non-sequential statistical studies aimed at comparing the incidence of hepatotoxicity following initiation of two newly licensed therapies for homozygous familial hypercholesterolemia. We calculate the sample size savings ratio, or the proportion of sample size saved if one conducted a sequential study as compared to a non-sequential study. Then, using models to describe the adoption and utilization of these therapies, we simulate when these sample sizes are attainable in calendar years. We then calculate the analytic calendar time savings ratio, analogous to the sample size savings ratio. We repeat these analyses for numerous scenarios. Sequential analyses detect effect sizes earlier or at the same time as non-sequential analyses. The most substantial potential savings occur when the market share is more imbalanced (i.e., 90% for therapy A) and the effect size is closest to the null hypothesis. However, due to low exposure prevalence, these savings are difficult to realize within the 30-year time frame of this simulation for scenarios in which the outcome of interest occurs at or more frequently than one event/100 person-years. We illustrate a process to assess whether sequential statistical analyses of registry data performed via distributed networks may prove a worthwhile infrastructure investment for pharmacovigilance.

On a problem of reconstruction of a discontinuous function by its Radon transform

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

Derevtsov, Evgeny Yu.; Maltseva, Svetlana V.; Svetov, Ivan E.

A problem of reconstruction of a discontinuous function by its Radon transform is considered. One of the approaches to the numerical solution for the problem consists in the next sequential steps: a visualization of a set of breaking points; an identification of this set; a determination of jump values; an elimination of discontinuities. We consider three of listed problems except the problem of jump values. The problems are investigated by mathematical modeling using numerical experiments. The results of simulation are satisfactory and allow to hope for the further development of the approach.

A 2-step penalized regression method for family-based next-generation sequencing association studies.

PubMed

Ding, Xiuhua; Su, Shaoyong; Nandakumar, Kannabiran; Wang, Xiaoling; Fardo, David W

2014-01-01

Large-scale genetic studies are often composed of related participants, and utilizing familial relationships can be cumbersome and computationally challenging. We present an approach to efficiently handle sequencing data from complex pedigrees that incorporates information from rare variants as well as common variants. Our method employs a 2-step procedure that sequentially regresses out correlation from familial relatedness and then uses the resulting phenotypic residuals in a penalized regression framework to test for associations with variants within genetic units. The operating characteristics of this approach are detailed using simulation data based on a large, multigenerational cohort.

Actively learning human gaze shifting paths for semantics-aware photo cropping.

PubMed

Zhang, Luming; Gao, Yue; Ji, Rongrong; Xia, Yingjie; Dai, Qionghai; Li, Xuelong

2014-05-01

Photo cropping is a widely used tool in printing industry, photography, and cinematography. Conventional cropping models suffer from the following three challenges. First, the deemphasized role of semantic contents that are many times more important than low-level features in photo aesthetics. Second, the absence of a sequential ordering in the existing models. In contrast, humans look at semantically important regions sequentially when viewing a photo. Third, the difficulty of leveraging inputs from multiple users. Experience from multiple users is particularly critical in cropping as photo assessment is quite a subjective task. To address these challenges, this paper proposes semantics-aware photo cropping, which crops a photo by simulating the process of humans sequentially perceiving semantically important regions of a photo. We first project the local features (graphlets in this paper) onto the semantic space, which is constructed based on the category information of the training photos. An efficient learning algorithm is then derived to sequentially select semantically representative graphlets of a photo, and the selecting process can be interpreted by a path, which simulates humans actively perceiving semantics in a photo. Furthermore, we learn a prior distribution of such active graphlet paths from training photos that are marked as aesthetically pleasing by multiple users. The learned priors enforce the corresponding active graphlet path of a test photo to be maximally similar to those from the training photos. Experimental results show that: 1) the active graphlet path accurately predicts human gaze shifting, and thus is more indicative for photo aesthetics than conventional saliency maps and 2) the cropped photos produced by our approach outperform its competitors in both qualitative and quantitative comparisons.

Operative air temperature data for different measures applied on a building envelope in warm climate.

PubMed

Baglivo, Cristina; Congedo, Paolo Maria

2018-04-01

Several technical combinations have been evaluated in order to design high energy performance buildings for the warm climate. The analysis has been developed in several steps, avoiding the use of HVAC systems. The methodological approach of this study is based on a sequential search technique and it is shown on the paper entitled "Envelope Design Optimization by Thermal Modeling of a Building in a Warm Climate" [1]. The Operative Air Temperature trends (TOP), for each combination, have been plotted through a dynamic simulation performed using the software TRNSYS 17 (a transient system simulation program, University of Wisconsin, Solar Energy Laboratory, USA, 2010). Starting from the simplest building configuration consisting of 9 rooms (equal-sized modules of 5 × 5 m 2 ), the different building components are sequentially evaluated until the envelope design is optimized. The aim of this study is to perform a step-by-step simulation, simplifying as much as possible the model without making additional variables that can modify their performances. Walls, slab-on-ground floor, roof, shading and windows are among the simulated building components. The results are shown for each combination and evaluated for Brindisi, a city in southern Italy having 1083 degrees day, belonging to the national climatic zone C. The data show the trends of the TOP for each measure applied in the case study for a total of 17 combinations divided into eight steps.

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

PubMed

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.

Modelling Geomechanical Heterogeneity of Rock Masses Using Direct and Indirect Geostatistical Conditional Simulation Methods

NASA Astrophysics Data System (ADS)

Eivazy, Hesameddin; Esmaieli, Kamran; Jean, Raynald

2017-12-01

An accurate characterization and modelling of rock mass geomechanical heterogeneity can lead to more efficient mine planning and design. Using deterministic approaches and random field methods for modelling rock mass heterogeneity is known to be limited in simulating the spatial variation and spatial pattern of the geomechanical properties. Although the applications of geostatistical techniques have demonstrated improvements in modelling the heterogeneity of geomechanical properties, geostatistical estimation methods such as Kriging result in estimates of geomechanical variables that are not fully representative of field observations. This paper reports on the development of 3D models for spatial variability of rock mass geomechanical properties using geostatistical conditional simulation method based on sequential Gaussian simulation. A methodology to simulate the heterogeneity of rock mass quality based on the rock mass rating is proposed and applied to a large open-pit mine in Canada. Using geomechanical core logging data collected from the mine site, a direct and an indirect approach were used to model the spatial variability of rock mass quality. The results of the two modelling approaches were validated against collected field data. The study aims to quantify the risks of pit slope failure and provides a measure of uncertainties in spatial variability of rock mass properties in different areas of the pit.

Risk-Constrained Dynamic Programming for Optimal Mars Entry, Descent, and Landing

NASA Technical Reports Server (NTRS)

Ono, Masahiro; Kuwata, Yoshiaki

2013-01-01

A chance-constrained dynamic programming algorithm was developed that is capable of making optimal sequential decisions within a user-specified risk bound. This work handles stochastic uncertainties over multiple stages in the CEMAT (Combined EDL-Mobility Analyses Tool) framework. It was demonstrated by a simulation of Mars entry, descent, and landing (EDL) using real landscape data obtained from the Mars Reconnaissance Orbiter. Although standard dynamic programming (DP) provides a general framework for optimal sequential decisionmaking under uncertainty, it typically achieves risk aversion by imposing an arbitrary penalty on failure states. Such a penalty-based approach cannot explicitly bound the probability of mission failure. A key idea behind the new approach is called risk allocation, which decomposes a joint chance constraint into a set of individual chance constraints and distributes risk over them. The joint chance constraint was reformulated into a constraint on an expectation over a sum of an indicator function, which can be incorporated into the cost function by dualizing the optimization problem. As a result, the chance-constraint optimization problem can be turned into an unconstrained optimization over a Lagrangian, which can be solved efficiently using a standard DP approach.

Sequential Multiple Assignment Randomized Trial (SMART) with Adaptive Randomization for Quality Improvement in Depression Treatment Program

PubMed Central

Chakraborty, Bibhas; Davidson, Karina W.

2015-01-01

Summary Implementation study is an important tool for deploying state-of-the-art treatments from clinical efficacy studies into a treatment program, with the dual goals of learning about effectiveness of the treatments and improving the quality of care for patients enrolled into the program. In this article, we deal with the design of a treatment program of dynamic treatment regimens (DTRs) for patients with depression post acute coronary syndrome. We introduce a novel adaptive randomization scheme for a sequential multiple assignment randomized trial of DTRs. Our approach adapts the randomization probabilities to favor treatment sequences having comparatively superior Q-functions used in Q-learning. The proposed approach addresses three main concerns of an implementation study: it allows incorporation of historical data or opinions, it includes randomization for learning purposes, and it aims to improve care via adaptation throughout the program. We demonstrate how to apply our method to design a depression treatment program using data from a previous study. By simulation, we illustrate that the inputs from historical data are important for the program performance measured by the expected outcomes of the enrollees, but also show that the adaptive randomization scheme is able to compensate poorly specified historical inputs by improving patient outcomes within a reasonable horizon. The simulation results also confirm that the proposed design allows efficient learning of the treatments by alleviating the curse of dimensionality. PMID:25354029

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

PubMed

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.

3D hybrid tectono-stochastic modeling of naturally fractured reservoir: Application of finite element method and stochastic simulation technique

NASA Astrophysics Data System (ADS)

Gholizadeh Doonechaly, N.; Rahman, S. S.

2012-05-01

Simulation of naturally fractured reservoirs offers significant challenges due to the lack of a methodology that can utilize field data. To date several methods have been proposed by authors to characterize naturally fractured reservoirs. Among them is the unfolding/folding method which offers some degree of accuracy in estimating the probability of the existence of fractures in a reservoir. Also there are statistical approaches which integrate all levels of field data to simulate the fracture network. This approach, however, is dependent on the availability of data sources, such as seismic attributes, core descriptions, well logs, etc. which often make it difficult to obtain field wide. In this study a hybrid tectono-stochastic simulation is proposed to characterize a naturally fractured reservoir. A finite element based model is used to simulate the tectonic event of folding and unfolding of a geological structure. A nested neuro-stochastic technique is used to develop the inter-relationship between the data and at the same time it utilizes the sequential Gaussian approach to analyze field data along with fracture probability data. This approach has the ability to overcome commonly experienced discontinuity of the data in both horizontal and vertical directions. This hybrid technique is used to generate a discrete fracture network of a specific Australian gas reservoir, Palm Valley in the Northern Territory. Results of this study have significant benefit in accurately describing fluid flow simulation and well placement for maximal hydrocarbon recovery.

A Fast and Precise Indoor Localization Algorithm Based on an Online Sequential Extreme Learning Machine †

PubMed Central

Zou, Han; Lu, Xiaoxuan; Jiang, Hao; Xie, Lihua

2015-01-01

Nowadays, developing indoor positioning systems (IPSs) has become an attractive research topic due to the increasing demands on location-based service (LBS) in indoor environments. WiFi technology has been studied and explored to provide indoor positioning service for years in view of the wide deployment and availability of existing WiFi infrastructures in indoor environments. A large body of WiFi-based IPSs adopt fingerprinting approaches for localization. However, these IPSs suffer from two major problems: the intensive costs of manpower and time for offline site survey and the inflexibility to environmental dynamics. In this paper, we propose an indoor localization algorithm based on an online sequential extreme learning machine (OS-ELM) to address the above problems accordingly. The fast learning speed of OS-ELM can reduce the time and manpower costs for the offline site survey. Meanwhile, its online sequential learning ability enables the proposed localization algorithm to adapt in a timely manner to environmental dynamics. Experiments under specific environmental changes, such as variations of occupancy distribution and events of opening or closing of doors, are conducted to evaluate the performance of OS-ELM. The simulation and experimental results show that the proposed localization algorithm can provide higher localization accuracy than traditional approaches, due to its fast adaptation to various environmental dynamics. PMID:25599427

Stochastic approach for an unbiased estimation of the probability of a successful separation in conventional chromatography and sequential elution liquid chromatography.

PubMed

Ennis, Erin J; Foley, Joe P

2016-07-15

A stochastic approach was utilized to estimate the probability of a successful isocratic or gradient separation in conventional chromatography for numbers of sample components, peak capacities, and saturation factors ranging from 2 to 30, 20-300, and 0.017-1, respectively. The stochastic probabilities were obtained under conditions of (i) constant peak width ("gradient" conditions) and (ii) peak width increasing linearly with time ("isocratic/constant N" conditions). The isocratic and gradient probabilities obtained stochastically were compared with the probabilities predicted by Martin et al. [Anal. Chem., 58 (1986) 2200-2207] and Davis and Stoll [J. Chromatogr. A, (2014) 128-142]; for a given number of components and peak capacity the same trend is always observed: probability obtained with the isocratic stochastic approach

Satisfiability Test with Synchronous Simulated Annealing on the Fujitsu AP1000 Massively-Parallel Multiprocessor

NASA Technical Reports Server (NTRS)

Sohn, Andrew; Biswas, Rupak

1996-01-01

Solving the hard Satisfiability Problem is time consuming even for modest-sized problem instances. Solving the Random L-SAT Problem is especially difficult due to the ratio of clauses to variables. This report presents a parallel synchronous simulated annealing method for solving the Random L-SAT Problem on a large-scale distributed-memory multiprocessor. In particular, we use a parallel synchronous simulated annealing procedure, called Generalized Speculative Computation, which guarantees the same decision sequence as sequential simulated annealing. To demonstrate the performance of the parallel method, we have selected problem instances varying in size from 100-variables/425-clauses to 5000-variables/21,250-clauses. Experimental results on the AP1000 multiprocessor indicate that our approach can satisfy 99.9 percent of the clauses while giving almost a 70-fold speedup on 500 processors.

Simultaneous sequential monitoring of efficacy and safety led to masking of effects.

PubMed

van Eekelen, Rik; de Hoop, Esther; van der Tweel, Ingeborg

2016-08-01

Usually, sequential designs for clinical trials are applied on the primary (=efficacy) outcome. In practice, other outcomes (e.g., safety) will also be monitored and influence the decision whether to stop a trial early. Implications of simultaneous monitoring on trial decision making are yet unclear. This study examines what happens to the type I error, power, and required sample sizes when one efficacy outcome and one correlated safety outcome are monitored simultaneously using sequential designs. We conducted a simulation study in the framework of a two-arm parallel clinical trial. Interim analyses on two outcomes were performed independently and simultaneously on the same data sets using four sequential monitoring designs, including O'Brien-Fleming and Triangular Test boundaries. Simulations differed in values for correlations and true effect sizes. When an effect was present in both outcomes, competition was introduced, which decreased power (e.g., from 80% to 60%). Futility boundaries for the efficacy outcome reduced overall type I errors as well as power for the safety outcome. Monitoring two correlated outcomes, given that both are essential for early trial termination, leads to masking of true effects. Careful consideration of scenarios must be taken into account when designing sequential trials. Simulation results can help guide trial design. Copyright © 2016 Elsevier Inc. All rights reserved.

Simultaneous versus sequential optimal experiment design for the identification of multi-parameter microbial growth kinetics as a function of temperature.

PubMed

Van Derlinden, E; Bernaerts, K; Van Impe, J F

2010-05-21

Optimal experiment design for parameter estimation (OED/PE) has become a popular tool for efficient and accurate estimation of kinetic model parameters. When the kinetic model under study encloses multiple parameters, different optimization strategies can be constructed. The most straightforward approach is to estimate all parameters simultaneously from one optimal experiment (single OED/PE strategy). However, due to the complexity of the optimization problem or the stringent limitations on the system's dynamics, the experimental information can be limited and parameter estimation convergence problems can arise. As an alternative, we propose to reduce the optimization problem to a series of two-parameter estimation problems, i.e., an optimal experiment is designed for a combination of two parameters while presuming the other parameters known. Two different approaches can be followed: (i) all two-parameter optimal experiments are designed based on identical initial parameter estimates and parameters are estimated simultaneously from all resulting experimental data (global OED/PE strategy), and (ii) optimal experiments are calculated and implemented sequentially whereby the parameter values are updated intermediately (sequential OED/PE strategy). This work exploits OED/PE for the identification of the Cardinal Temperature Model with Inflection (CTMI) (Rosso et al., 1993). This kinetic model describes the effect of temperature on the microbial growth rate and encloses four parameters. The three OED/PE strategies are considered and the impact of the OED/PE design strategy on the accuracy of the CTMI parameter estimation is evaluated. Based on a simulation study, it is observed that the parameter values derived from the sequential approach deviate more from the true parameters than the single and global strategy estimates. The single and global OED/PE strategies are further compared based on experimental data obtained from design implementation in a bioreactor. Comparable estimates are obtained, but global OED/PE estimates are, in general, more accurate and reliable. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

A Bayesian sequential design using alpha spending function to control type I error.

PubMed

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.

Multiuser signal detection using sequential decoding

NASA Astrophysics Data System (ADS)

Xie, Zhenhua; Rushforth, Craig K.; Short, Robert T.

1990-05-01

The application of sequential decoding to the detection of data transmitted over the additive white Gaussian noise channel by K asynchronous transmitters using direct-sequence spread-spectrum multiple access is considered. A modification of Fano's (1963) sequential-decoding metric, allowing the messages from a given user to be safely decoded if its Eb/N0 exceeds -1.6 dB, is presented. Computer simulation is used to evaluate the performance of a sequential decoder that uses this metric in conjunction with the stack algorithm. In many circumstances, the sequential decoder achieves results comparable to those obtained using the much more complicated optimal receiver.

Sequential and simultaneous SLAR block adjustment. [spline function analysis for mapping

NASA Technical Reports Server (NTRS)

Leberl, F.

1975-01-01

Two sequential methods of planimetric SLAR (Side Looking Airborne Radar) block adjustment, with and without splines, and three simultaneous methods based on the principles of least squares are evaluated. A limited experiment with simulated SLAR images indicates that sequential block formation with splines followed by external interpolative adjustment is superior to the simultaneous methods such as planimetric block adjustment with similarity transformations. The use of the sequential block formation is recommended, since it represents an inexpensive tool for satisfactory point determination from SLAR images.

Sensor Analytics: Radioactive gas Concentration Estimation and Error Propagation

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

Anderson, Dale N.; Fagan, Deborah K.; Suarez, Reynold

2007-04-15

This paper develops the mathematical statistics of a radioactive gas quantity measurement and associated error propagation. The probabilistic development is a different approach to deriving attenuation equations and offers easy extensions to more complex gas analysis components through simulation. The mathematical development assumes a sequential process of three components; I) the collection of an environmental sample, II) component gas extraction from the sample through the application of gas separation chemistry, and III) the estimation of radioactivity of component gases.

Optimization of black-box models with uncertain climatic inputs—Application to sunflower ideotype design

PubMed Central

Picheny, Victor; Trépos, Ronan; Casadebaig, Pierre

2017-01-01

Accounting for the interannual climatic variations is a well-known issue for simulation-based studies of environmental systems. It often requires intensive sampling (e.g., averaging the simulation outputs over many climatic series), which hinders many sequential processes, in particular optimization algorithms. We propose here an approach based on a subset selection in a large basis of climatic series, using an ad-hoc similarity function and clustering. A non-parametric reconstruction technique is introduced to estimate accurately the distribution of the output of interest using only the subset sampling. The proposed strategy is non-intrusive and generic (i.e. transposable to most models with climatic data inputs), and can be combined to most “off-the-shelf” optimization solvers. We apply our approach to sunflower ideotype design using the crop model SUNFLO. The underlying optimization problem is formulated as a multi-objective one to account for risk-aversion. Our approach achieves good performances even for limited computational budgets, outperforming significantly standard strategies. PMID:28542198

Monitoring and identification of spatiotemporal landscape changes in multiple remote sensing images by using a stratified conditional Latin hypercube sampling approach and geostatistical simulation.

PubMed

Lin, Yu-Pin; Chu, Hone-Jay; Huang, Yu-Long; Tang, Chia-Hsi; Rouhani, Shahrokh

2011-06-01

This study develops a stratified conditional Latin hypercube sampling (scLHS) approach for multiple, remotely sensed, normalized difference vegetation index (NDVI) images. The objective is to sample, monitor, and delineate spatiotemporal landscape changes, including spatial heterogeneity and variability, in a given area. The scLHS approach, which is based on the variance quadtree technique (VQT) and the conditional Latin hypercube sampling (cLHS) method, selects samples in order to delineate landscape changes from multiple NDVI images. The images are then mapped for calibration and validation by using sequential Gaussian simulation (SGS) with the scLHS selected samples. Spatial statistical results indicate that in terms of their statistical distribution, spatial distribution, and spatial variation, the statistics and variograms of the scLHS samples resemble those of multiple NDVI images more closely than those of cLHS and VQT samples. Moreover, the accuracy of simulated NDVI images based on SGS with scLHS samples is significantly better than that of simulated NDVI images based on SGS with cLHS samples and VQT samples, respectively. However, the proposed approach efficiently monitors the spatial characteristics of landscape changes, including the statistics, spatial variability, and heterogeneity of NDVI images. In addition, SGS with the scLHS samples effectively reproduces spatial patterns and landscape changes in multiple NDVI images.

Incorporating root hydraulic redistribution in CLM4.5: Effects on predicted site and global evapotranspiration, soil moisture, and water storage

NASA Astrophysics Data System (ADS)

Tang, Jinyun; Riley, William J.; Niu, Jie

2015-12-01

We implemented the Amenu-Kumar model in the Community Land Model (CLM4.5) to simulate plant Root Hydraulic Redistribution (RHR) and analyzed its influence on CLM hydrology from site to global scales. We evaluated two numerical implementations: the first solved the coupled equations of root and soil water transport concurrently, while the second solved the two equations sequentially. Through sensitivity analysis, we demonstrate that the sequentially coupled implementation (SCI) is numerically incorrect, whereas the tightly coupled implementation (TCI) is numerically robust with numerical time steps varying from 1 to 30 min. At the site-level, we found the SCI approach resulted in better agreement with measured evapotranspiration (ET) at the AmeriFlux Blodgett Forest site, California, whereas the two approaches resulted in equally poor agreement between predicted and measured ET at the LBA Tapajos KM67 Mature Forest site in Amazon, Brazil. Globally, the SCI approach overestimated annual land ET by as much as 3.5 mm d-1 in some grid cells when compared to the TCI estimates. These comparisons demonstrate that TCI is a more robust numerical implementation of RHR. However, we found, even with TCI, that incorporating RHR resulted in worse agreement with measured soil moisture at both the Blodgett Forest and Tapajos sites and degraded the agreement between simulated terrestrial water storage anomaly and Gravity Recovery and Climate Experiment (GRACE) observations. We find including RHR in CLM4.5 improved ET predictions compared with the FLUXNET-MTE estimates north of 20° N but led to poorer predictions in the tropics. The biases in ET were robust and significant regardless of the four different pedotransfer functions or of the two meteorological forcing data sets we applied. We also found that the simulated water table was unrealistically sensitive to RHR. Therefore, we contend that further structural and data improvements are warranted to improve the hydrological dynamics in CLM4.5.

Incorporating root hydraulic redistribution in CLM4.5: Effects on predicted site and global evapotranspiration, soil moisture, and water storage

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

Tang, Jinyun; Riley, William J.; Niu, Jie

We implemented the Amenu-Kumar model in the Community Land Model (CLM4.5) to simulate plant Root Hydraulic Redistribution (RHR) and analyzed its influence on CLM hydrology from site to global scales. We evaluated two numerical implementations: the first solved the coupled equations of root and soil water transport concurrently, while the second solved the two equations sequentially. Through sensitivity analysis, we demonstrate that the sequentially coupled implementation (SCI) is numerically incorrect, whereas the tightly coupled implementation (TCI) is numerically robust with numerical time steps varying from 1 to 30 min. At the site-level, we found the SCI approach resulted in bettermore » agreement with measured evapotranspiration (ET) at the AmeriFlux Blodgett Forest site, California, whereas the two approaches resulted in equally poor agreement between predicted and measured ET at the LBA Tapajos KM67 Mature Forest site in Amazon, Brazil. Globally, the SCI approach overestimated annual land ET by as much as 3.5 mm d -1 in some grid cells when compared to the TCI estimates. These comparisons demonstrate that TCI is a more robust numerical implementation of RHR. However, we found, even with TCI, that incorporating RHR resulted in worse agreement with measured soil moisture at both the Blodgett Forest and Tapajos sites and degraded the agreement between simulated terrestrial water storage anomaly and Gravity Recovery and Climate Experiment (GRACE) observations. We find including RHR in CLM4.5 improved ET predictions compared with the FLUXNET-MTE estimates north of 20° N but led to poorer predictions in the tropics. The biases in ET were robust and significant regardless of the four different pedotransfer functions or of the two meteorological forcing data sets we applied. We also found that the simulated water table was unrealistically sensitive to RHR. Therefore, we contend that further structural and data improvements are warranted to improve the hydrological dynamics in CLM4.5.« less

Incorporating root hydraulic redistribution in CLM4.5: Effects on predicted site and global evapotranspiration, soil moisture, and water storage

DOE PAGES

Tang, Jinyun; Riley, William J.; Niu, Jie

2015-11-12

We implemented the Amenu-Kumar model in the Community Land Model (CLM4.5) to simulate plant Root Hydraulic Redistribution (RHR) and analyzed its influence on CLM hydrology from site to global scales. We evaluated two numerical implementations: the first solved the coupled equations of root and soil water transport concurrently, while the second solved the two equations sequentially. Through sensitivity analysis, we demonstrate that the sequentially coupled implementation (SCI) is numerically incorrect, whereas the tightly coupled implementation (TCI) is numerically robust with numerical time steps varying from 1 to 30 min. At the site-level, we found the SCI approach resulted in bettermore » agreement with measured evapotranspiration (ET) at the AmeriFlux Blodgett Forest site, California, whereas the two approaches resulted in equally poor agreement between predicted and measured ET at the LBA Tapajos KM67 Mature Forest site in Amazon, Brazil. Globally, the SCI approach overestimated annual land ET by as much as 3.5 mm d -1 in some grid cells when compared to the TCI estimates. These comparisons demonstrate that TCI is a more robust numerical implementation of RHR. However, we found, even with TCI, that incorporating RHR resulted in worse agreement with measured soil moisture at both the Blodgett Forest and Tapajos sites and degraded the agreement between simulated terrestrial water storage anomaly and Gravity Recovery and Climate Experiment (GRACE) observations. We find including RHR in CLM4.5 improved ET predictions compared with the FLUXNET-MTE estimates north of 20° N but led to poorer predictions in the tropics. The biases in ET were robust and significant regardless of the four different pedotransfer functions or of the two meteorological forcing data sets we applied. We also found that the simulated water table was unrealistically sensitive to RHR. Therefore, we contend that further structural and data improvements are warranted to improve the hydrological dynamics in CLM4.5.« less

Conducting Privacy-Preserving Multivariable Propensity Score Analysis When Patient Covariate Information Is Stored in Separate Locations.

PubMed

Bohn, Justin; Eddings, Wesley; Schneeweiss, Sebastian

2017-03-15

Distributed networks of health-care data sources are increasingly being utilized to conduct pharmacoepidemiologic database studies. Such networks may contain data that are not physically pooled but instead are distributed horizontally (separate patients within each data source) or vertically (separate measures within each data source) in order to preserve patient privacy. While multivariable methods for the analysis of horizontally distributed data are frequently employed, few practical approaches have been put forth to deal with vertically distributed health-care databases. In this paper, we propose 2 propensity score-based approaches to vertically distributed data analysis and test their performance using 5 example studies. We found that these approaches produced point estimates close to what could be achieved without partitioning. We further found a performance benefit (i.e., lower mean squared error) for sequentially passing a propensity score through each data domain (called the "sequential approach") as compared with fitting separate domain-specific propensity scores (called the "parallel approach"). These results were validated in a small simulation study. This proof-of-concept study suggests a new multivariable analysis approach to vertically distributed health-care databases that is practical, preserves patient privacy, and warrants further investigation for use in clinical research applications that rely on health-care databases. © The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Sequential sentinel SNP Regional Association Plots (SSS-RAP): an approach for testing independence of SNP association signals using meta-analysis data.

PubMed

Zheng, Jie; Gaunt, Tom R; Day, Ian N M

2013-01-01

Genome-Wide Association Studies (GWAS) frequently incorporate meta-analysis within their framework. However, conditional analysis of individual-level data, which is an established approach for fine mapping of causal sites, is often precluded where only group-level summary data are available for analysis. Here, we present a numerical and graphical approach, "sequential sentinel SNP regional association plot" (SSS-RAP), which estimates regression coefficients (beta) with their standard errors using the meta-analysis summary results directly. Under an additive model, typical for genes with small effect, the effect for a sentinel SNP can be transformed to the predicted effect for a possibly dependent SNP through a 2×2 2-SNP haplotypes table. The approach assumes Hardy-Weinberg equilibrium for test SNPs. SSS-RAP is available as a Web-tool (http://apps.biocompute.org.uk/sssrap/sssrap.cgi). To develop and illustrate SSS-RAP we analyzed lipid and ECG traits data from the British Women's Heart and Health Study (BWHHS), evaluated a meta-analysis for ECG trait and presented several simulations. We compared results with existing approaches such as model selection methods and conditional analysis. Generally findings were consistent. SSS-RAP represents a tool for testing independence of SNP association signals using meta-analysis data, and is also a convenient approach based on biological principles for fine mapping in group level summary data. © 2012 Blackwell Publishing Ltd/University College London.

A Unified Approach to the Synthesis of Fully Testable Sequential Machines

DTIC Science & Technology

1989-10-01

N A Unified Approach to the Synthesis of Fully Testable Sequential Machines Srinivas Devadas and Kurt Keutzer Abstract • In this paper we attempt to...research was supported in part by the Defense Advanced Research Projects Agency under contract N00014-87-K-0825. Author Information Devadas : Department...Fully Testable Sequential Maine(S P Sritiivas Devadas Departinent of Electrical Engineerinig anid Comivi Sciec Massachusetts Institute of Technology

Predictive Place-Cell Sequences for Goal-Finding Emerge from Goal Memory and the Cognitive Map: A Computational Model

PubMed Central

Gönner, Lorenz; Vitay, Julien; Hamker, Fred H.

2017-01-01

Hippocampal place-cell sequences observed during awake immobility often represent previous experience, suggesting a role in memory processes. However, recent reports of goals being overrepresented in sequential activity suggest a role in short-term planning, although a detailed understanding of the origins of hippocampal sequential activity and of its functional role is still lacking. In particular, it is unknown which mechanism could support efficient planning by generating place-cell sequences biased toward known goal locations, in an adaptive and constructive fashion. To address these questions, we propose a model of spatial learning and sequence generation as interdependent processes, integrating cortical contextual coding, synaptic plasticity and neuromodulatory mechanisms into a map-based approach. Following goal learning, sequential activity emerges from continuous attractor network dynamics biased by goal memory inputs. We apply Bayesian decoding on the resulting spike trains, allowing a direct comparison with experimental data. Simulations show that this model (1) explains the generation of never-experienced sequence trajectories in familiar environments, without requiring virtual self-motion signals, (2) accounts for the bias in place-cell sequences toward goal locations, (3) highlights their utility in flexible route planning, and (4) provides specific testable predictions. PMID:29075187

Joint water-fat separation and deblurring for spiral imaging.

PubMed

Wang, Dinghui; Zwart, Nicholas R; Pipe, James G

2018-06-01

Most previous approaches to spiral Dixon water-fat imaging perform the water-fat separation and deblurring sequentially based on the assumption that the phase accumulation and blurring as a result of off-resonance are separable. This condition can easily be violated in regions where the B 0 inhomogeneity varies rapidly. The goal of this work is to present a novel joint water-fat separation and deblurring method for spiral imaging. The proposed approach is based on a more accurate signal model that takes into account the phase accumulation and blurring simultaneously. A conjugate gradient method is used in the image domain to reconstruct the deblurred water and fat iteratively. Spatially varying convolutions with a local convergence criterion are used to reduce the computational demand. Both simulation and high-resolution brain imaging have demonstrated that the proposed joint method consistently improves the quality of reconstructed water and fat images compared with the sequential approach, especially in regions where the field inhomogeneity changes rapidly in space. The loss of signal-to-noise-ratio as a result of deblurring is minor at optimal echo times. High-quality water-fat spiral imaging can be achieved with the proposed joint approach, provided that an accurate field map of B 0 inhomogeneity is available. Magn Reson Med 79:3218-3228, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

On the Lulejian-I Combat Model

DTIC Science & Technology

1976-08-01

possible initial massing of the attacking side’s resources, the model tries to represent in a game -theoretic context the adversary nature of the...sequential game , as outlined in [A]. In principle, it is necessary to run the combat simulation once for each possible set of sequentially chosen...sequential game , in which the evaluative portion of the model (i.e., the combat assessment) serves to compute intermediate and terminal payoffs for the

Lifelong Transfer Learning for Heterogeneous Teams of Agents in Sequential Decision Processes

DTIC Science & Technology

2016-06-01

making (SDM) tasks in dynamic environments with simulated and physical robots . 15. SUBJECT TERMS Sequential decision making, lifelong learning, transfer...sequential decision-making (SDM) tasks in dynamic environments with both simple benchmark tasks and more complex aerial and ground robot tasks. Our work...and ground robots in the presence of disturbances: We applied our methods to the problem of learning controllers for robots with novel disturbances in

Increasing efficiency of preclinical research by group sequential designs

PubMed Central

Piper, Sophie K.; Rex, Andre; Florez-Vargas, Oscar; Karystianis, George; Schneider, Alice; Wellwood, Ian; Siegerink, Bob; Ioannidis, John P. A.; Kimmelman, Jonathan; Dirnagl, Ulrich

2017-01-01

Despite the potential benefits of sequential designs, studies evaluating treatments or experimental manipulations in preclinical experimental biomedicine almost exclusively use classical block designs. Our aim with this article is to bring the existing methodology of group sequential designs to the attention of researchers in the preclinical field and to clearly illustrate its potential utility. Group sequential designs can offer higher efficiency than traditional methods and are increasingly used in clinical trials. Using simulation of data, we demonstrate that group sequential designs have the potential to improve the efficiency of experimental studies, even when sample sizes are very small, as is currently prevalent in preclinical experimental biomedicine. When simulating data with a large effect size of d = 1 and a sample size of n = 18 per group, sequential frequentist analysis consumes in the long run only around 80% of the planned number of experimental units. In larger trials (n = 36 per group), additional stopping rules for futility lead to the saving of resources of up to 30% compared to block designs. We argue that these savings should be invested to increase sample sizes and hence power, since the currently underpowered experiments in preclinical biomedicine are a major threat to the value and predictiveness in this research domain. PMID:28282371

A posteriori model validation for the temporal order of directed functional connectivity maps.

PubMed

Beltz, Adriene M; Molenaar, Peter C M

2015-01-01

A posteriori model validation for the temporal order of neural directed functional connectivity maps is rare. This is striking because models that require sequential independence among residuals are regularly implemented. The aim of the current study was (a) to apply to directed functional connectivity maps of functional magnetic resonance imaging data an a posteriori model validation procedure (i.e., white noise tests of one-step-ahead prediction errors combined with decision criteria for revising the maps based upon Lagrange Multiplier tests), and (b) to demonstrate how the procedure applies to single-subject simulated, single-subject task-related, and multi-subject resting state data. Directed functional connectivity was determined by the unified structural equation model family of approaches in order to map contemporaneous and first order lagged connections among brain regions at the group- and individual-levels while incorporating external input, then white noise tests were run. Findings revealed that the validation procedure successfully detected unmodeled sequential dependencies among residuals and recovered higher order (greater than one) simulated connections, and that the procedure can accommodate task-related input. Findings also revealed that lags greater than one were present in resting state data: With a group-level network that contained only contemporaneous and first order connections, 44% of subjects required second order, individual-level connections in order to obtain maps with white noise residuals. Results have broad methodological relevance (e.g., temporal validation is necessary after directed functional connectivity analyses because the presence of unmodeled higher order sequential dependencies may bias parameter estimates) and substantive implications (e.g., higher order lags may be common in resting state data).

Teaching Improvisation through Melody and Blues-Based Harmony: A Comprehensive and Sequential Approach

ERIC Educational Resources Information Center

Heil, Leila

2017-01-01

This article describes a sequential approach to improvisation teaching that can be used with students at various age and ability levels by any educator, regardless of improvisation experience. The 2014 National Core Music Standards include improvisation as a central component in musical learning and promote instructional approaches that are…

A Flexible Monitoring Infrastructure for the Simulation Requests

NASA Astrophysics Data System (ADS)

Spinoso, V.; Missiato, M.

2014-06-01

Running and monitoring simulations usually involves several different aspects of the entire workflow: the configuration of the job, the site issues, the software deployment at the site, the file catalogue, the transfers of the simulated data. In addition, the final product of the simulation is often the result of several sequential steps. This project tries a different approach to monitoring the simulation requests. All the necessary data are collected from the central services which lead the submission of the requests and the data management, and stored by a backend into a NoSQL-based data cache; those data can be queried through a Web Service interface, which returns JSON responses, and allows users, sites, physics groups to easily create their own web frontend, aggregating only the needed information. As an example, it will be shown how it is possible to monitor the CMS services (ReqMgr, DAS/DBS, PhEDEx) using a central backend and multiple customized cross-language frontends.

Multilevel discretized random field models with 'spin' correlations for the simulation of environmental spatial data

NASA Astrophysics Data System (ADS)

Žukovič, Milan; Hristopulos, Dionissios T.

2009-02-01

A current problem of practical significance is how to analyze large, spatially distributed, environmental data sets. The problem is more challenging for variables that follow non-Gaussian distributions. We show by means of numerical simulations that the spatial correlations between variables can be captured by interactions between 'spins'. The spins represent multilevel discretizations of environmental variables with respect to a number of pre-defined thresholds. The spatial dependence between the 'spins' is imposed by means of short-range interactions. We present two approaches, inspired by the Ising and Potts models, that generate conditional simulations of spatially distributed variables from samples with missing data. Currently, the sampling and simulation points are assumed to be at the nodes of a regular grid. The conditional simulations of the 'spin system' are forced to respect locally the sample values and the system statistics globally. The second constraint is enforced by minimizing a cost function representing the deviation between normalized correlation energies of the simulated and the sample distributions. In the approach based on the Nc-state Potts model, each point is assigned to one of Nc classes. The interactions involve all the points simultaneously. In the Ising model approach, a sequential simulation scheme is used: the discretization at each simulation level is binomial (i.e., ± 1). Information propagates from lower to higher levels as the simulation proceeds. We compare the two approaches in terms of their ability to reproduce the target statistics (e.g., the histogram and the variogram of the sample distribution), to predict data at unsampled locations, as well as in terms of their computational complexity. The comparison is based on a non-Gaussian data set (derived from a digital elevation model of the Walker Lake area, Nevada, USA). We discuss the impact of relevant simulation parameters, such as the domain size, the number of discretization levels, and the initial conditions.

Comparison of Statistical Approaches for Dealing With Immortal Time Bias in Drug Effectiveness Studies

PubMed Central

Karim, Mohammad Ehsanul; Gustafson, Paul; Petkau, John; Tremlett, Helen

2016-01-01

In time-to-event analyses of observational studies of drug effectiveness, incorrect handling of the period between cohort entry and first treatment exposure during follow-up may result in immortal time bias. This bias can be eliminated by acknowledging a change in treatment exposure status with time-dependent analyses, such as fitting a time-dependent Cox model. The prescription time-distribution matching (PTDM) method has been proposed as a simpler approach for controlling immortal time bias. Using simulation studies and theoretical quantification of bias, we compared the performance of the PTDM approach with that of the time-dependent Cox model in the presence of immortal time. Both assessments revealed that the PTDM approach did not adequately address immortal time bias. Based on our simulation results, another recently proposed observational data analysis technique, the sequential Cox approach, was found to be more useful than the PTDM approach (Cox: bias = −0.002, mean squared error = 0.025; PTDM: bias = −1.411, mean squared error = 2.011). We applied these approaches to investigate the association of β-interferon treatment with delaying disability progression in a multiple sclerosis cohort in British Columbia, Canada (Long-Term Benefits and Adverse Effects of Beta-Interferon for Multiple Sclerosis (BeAMS) Study, 1995–2008). PMID:27455963

Kinetic neoclassical calculations of impurity radiation profiles

DOE PAGES

Stotler, D. P.; Battaglia, D. J.; Hager, R.; ...

2016-12-30

Modifications of the drift-kinetic transport code XGC0 to include the transport, ionization, and recombination of individual charge states, as well as the associated radiation, are described. The code is first applied to a simulation of an NSTX H-mode discharge with carbon impurity to demonstrate the approach to coronal equilibrium. The effects of neoclassical phenomena on the radiated power profile are examined sequentially through the activation of individual physics modules in the code. Orbit squeezing and the neoclassical inward pinch result in increased radiation for temperatures above a few hundred eV and changes to the ratios of charge state emissions atmore » a given electron temperature. As a result, analogous simulations with a neon impurity yield qualitatively similar results.« less

Constant speed control of four-stroke micro internal combustion swing engine

NASA Astrophysics Data System (ADS)

Gao, Dedong; Lei, Yong; Zhu, Honghai; Ni, Jun

2015-09-01

The increasing demands on safety, emission and fuel consumption require more accurate control models of micro internal combustion swing engine (MICSE). The objective of this paper is to investigate the constant speed control models of four-stroke MICSE. The operation principle of the four-stroke MICSE is presented based on the description of MICSE prototype. A two-level Petri net based hybrid model is proposed to model the four-stroke MICSE engine cycle. The Petri net subsystem at the upper level controls and synchronizes the four Petri net subsystems at the lower level. The continuous sub-models, including breathing dynamics of intake manifold, thermodynamics of the chamber and dynamics of the torque generation, are investigated and integrated with the discrete model in MATLAB Simulink. Through the comparison of experimental data and simulated DC voltage output, it is demonstrated that the hybrid model is valid for the four-stroke MICSE system. A nonlinear model is obtained from the cycle average data via the regression method, and it is linearized around a given nominal equilibrium point for the controller design. The feedback controller of the spark timing and valve duration timing is designed with a sequential loop closing design approach. The simulation of the sequential loop closure control design applied to the hybrid model is implemented in MATLAB. The simulation results show that the system is able to reach its desired operating point within 0.2 s, and the designed controller shows good MICSE engine performance with a constant speed. This paper presents the constant speed control models of four-stroke MICSE and carries out the simulation tests, the models and the simulation results can be used for further study on the precision control of four-stroke MICSE.

Rotorcraft system identification techniques for handling qualities and stability and control evaluation

NASA Technical Reports Server (NTRS)

Hall, W. E., Jr.; Gupta, N. K.; Hansen, R. S.

1978-01-01

An integrated approach to rotorcraft system identification is described. This approach consists of sequential application of (1) data filtering to estimate states of the system and sensor errors, (2) model structure estimation to isolate significant model effects, and (3) parameter identification to quantify the coefficient of the model. An input design algorithm is described which can be used to design control inputs which maximize parameter estimation accuracy. Details of each aspect of the rotorcraft identification approach are given. Examples of both simulated and actual flight data processing are given to illustrate each phase of processing. The procedure is shown to provide means of calibrating sensor errors in flight data, quantifying high order state variable models from the flight data, and consequently computing related stability and control design models.

A Bayesian sequential design with adaptive randomization for 2-sided hypothesis test.

PubMed

Yu, Qingzhao; Zhu, Lin; Zhu, Han

2017-11-01

Bayesian sequential and adaptive randomization designs are gaining popularity in clinical trials thanks to their potentials to reduce the number of required participants and save resources. We propose a Bayesian sequential design with adaptive randomization rates so as to more efficiently attribute newly recruited patients to different treatment arms. In this paper, we consider 2-arm clinical trials. Patients are allocated to the 2 arms with a randomization rate to achieve minimum variance for the test statistic. Algorithms are presented to calculate the optimal randomization rate, critical values, and power for the proposed design. Sensitivity analysis is implemented to check the influence on design by changing the prior distributions. Simulation studies are applied to compare the proposed method and traditional methods in terms of power and actual sample sizes. Simulations show that, when total sample size is fixed, the proposed design can obtain greater power and/or cost smaller actual sample size than the traditional Bayesian sequential design. Finally, we apply the proposed method to a real data set and compare the results with the Bayesian sequential design without adaptive randomization in terms of sample sizes. The proposed method can further reduce required sample size. Copyright © 2017 John Wiley & Sons, Ltd.

A repeated measures model for analysis of continuous outcomes in sequential parallel comparison design studies.

PubMed

Doros, Gheorghe; Pencina, Michael; Rybin, Denis; Meisner, Allison; Fava, Maurizio

2013-07-20

Previous authors have proposed the sequential parallel comparison design (SPCD) to address the issue of high placebo response rate in clinical trials. The original use of SPCD focused on binary outcomes, but recent use has since been extended to continuous outcomes that arise more naturally in many fields, including psychiatry. Analytic methods proposed to date for analysis of SPCD trial continuous data included methods based on seemingly unrelated regression and ordinary least squares. Here, we propose a repeated measures linear model that uses all outcome data collected in the trial and accounts for data that are missing at random. An appropriate contrast formulated after the model has been fit can be used to test the primary hypothesis of no difference in treatment effects between study arms. Our extensive simulations show that when compared with the other methods, our approach preserves the type I error even for small sample sizes and offers adequate power and the smallest mean squared error under a wide variety of assumptions. We recommend consideration of our approach for analysis of data coming from SPCD trials. Copyright © 2013 John Wiley & Sons, Ltd.

Solving the infeasible trust-region problem using approximations.

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

Renaud, John E.; Perez, Victor M.; Eldred, Michael Scott

2004-07-01

The use of optimization in engineering design has fueled the development of algorithms for specific engineering needs. When the simulations are expensive to evaluate or the outputs present some noise, the direct use of nonlinear optimizers is not advisable, since the optimization process will be expensive and may result in premature convergence. The use of approximations for both cases is an alternative investigated by many researchers including the authors. When approximations are present, a model management is required for proper convergence of the algorithm. In nonlinear programming, the use of trust-regions for globalization of a local algorithm has been provenmore » effective. The same approach has been used to manage the local move limits in sequential approximate optimization frameworks as in Alexandrov et al., Giunta and Eldred, Perez et al. , Rodriguez et al., etc. The experience in the mathematical community has shown that more effective algorithms can be obtained by the specific inclusion of the constraints (SQP type of algorithms) rather than by using a penalty function as in the augmented Lagrangian formulation. The presence of explicit constraints in the local problem bounded by the trust region, however, may have no feasible solution. In order to remedy this problem the mathematical community has developed different versions of a composite steps approach. This approach consists of a normal step to reduce the amount of constraint violation and a tangential step to minimize the objective function maintaining the level of constraint violation attained at the normal step. Two of the authors have developed a different approach for a sequential approximate optimization framework using homotopy ideas to relax the constraints. This algorithm called interior-point trust-region sequential approximate optimization (IPTRSAO) presents some similarities to the two normal-tangential steps algorithms. In this paper, a description of the similarities is presented and an expansion of the two steps algorithm is presented for the case of approximations.« less

astroABC : An Approximate Bayesian Computation Sequential Monte Carlo sampler for cosmological parameter estimation

NASA Astrophysics Data System (ADS)

Jennings, E.; Madigan, M.

2017-04-01

Given the complexity of modern cosmological parameter inference where we are faced with non-Gaussian data and noise, correlated systematics and multi-probe correlated datasets,the Approximate Bayesian Computation (ABC) method is a promising alternative to traditional Markov Chain Monte Carlo approaches in the case where the Likelihood is intractable or unknown. The ABC method is called "Likelihood free" as it avoids explicit evaluation of the Likelihood by using a forward model simulation of the data which can include systematics. We introduce astroABC, an open source ABC Sequential Monte Carlo (SMC) sampler for parameter estimation. A key challenge in astrophysics is the efficient use of large multi-probe datasets to constrain high dimensional, possibly correlated parameter spaces. With this in mind astroABC allows for massive parallelization using MPI, a framework that handles spawning of processes across multiple nodes. A key new feature of astroABC is the ability to create MPI groups with different communicators, one for the sampler and several others for the forward model simulation, which speeds up sampling time considerably. For smaller jobs the Python multiprocessing option is also available. Other key features of this new sampler include: a Sequential Monte Carlo sampler; a method for iteratively adapting tolerance levels; local covariance estimate using scikit-learn's KDTree; modules for specifying optimal covariance matrix for a component-wise or multivariate normal perturbation kernel and a weighted covariance metric; restart files output frequently so an interrupted sampling run can be resumed at any iteration; output and restart files are backed up at every iteration; user defined distance metric and simulation methods; a module for specifying heterogeneous parameter priors including non-standard prior PDFs; a module for specifying a constant, linear, log or exponential tolerance level; well-documented examples and sample scripts. This code is hosted online at https://github.com/EliseJ/astroABC.

Sequential programmable self-assembly: Role of cooperative interactions

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

Jonathan D. Halverson; Tkachenko, Alexei V.

Here, we propose a general strategy of “sequential programmable self-assembly” that enables a bottom-up design of arbitrary multi-particle architectures on nano- and microscales. We show that a naive realization of this scheme, based on the pairwise additive interactions between particles, has fundamental limitations that lead to a relatively high error rate. This can be overcome by using cooperative interparticle binding. The cooperativity is a well known feature of many biochemical processes, responsible, e.g., for signaling and regulations in living systems. Here we propose to utilize a similar strategy for high precision self-assembly, and show that DNA-mediated interactions provide a convenientmore » platform for its implementation. In particular, we outline a specific design of a DNA-based complex which we call “DNA spider,” that acts as a smart interparticle linker and provides a built-in cooperativity of binding. We demonstrate versatility of the sequential self-assembly based on spider-functionalized particles by designing several mesostructures of increasing complexity and simulating their assembly process. This includes a number of finite and repeating structures, in particular, the so-called tetrahelix and its several derivatives. Due to its generality, this approach allows one to design and successfully self-assemble virtually any structure made of a “GEOMAG” magnetic construction toy, out of nanoparticles. According to our results, once the binding cooperativity is strong enough, the sequential self-assembly becomes essentially error-free.« less

Sequential programmable self-assembly: Role of cooperative interactions

DOE PAGES

Jonathan D. Halverson; Tkachenko, Alexei V.

2016-03-04

Here, we propose a general strategy of “sequential programmable self-assembly” that enables a bottom-up design of arbitrary multi-particle architectures on nano- and microscales. We show that a naive realization of this scheme, based on the pairwise additive interactions between particles, has fundamental limitations that lead to a relatively high error rate. This can be overcome by using cooperative interparticle binding. The cooperativity is a well known feature of many biochemical processes, responsible, e.g., for signaling and regulations in living systems. Here we propose to utilize a similar strategy for high precision self-assembly, and show that DNA-mediated interactions provide a convenientmore » platform for its implementation. In particular, we outline a specific design of a DNA-based complex which we call “DNA spider,” that acts as a smart interparticle linker and provides a built-in cooperativity of binding. We demonstrate versatility of the sequential self-assembly based on spider-functionalized particles by designing several mesostructures of increasing complexity and simulating their assembly process. This includes a number of finite and repeating structures, in particular, the so-called tetrahelix and its several derivatives. Due to its generality, this approach allows one to design and successfully self-assemble virtually any structure made of a “GEOMAG” magnetic construction toy, out of nanoparticles. According to our results, once the binding cooperativity is strong enough, the sequential self-assembly becomes essentially error-free.« less

Making Career Decisions--A Sequential Elimination Approach.

ERIC Educational Resources Information Center

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…

A Node Linkage Approach for Sequential Pattern Mining

PubMed Central

Navarro, Osvaldo; Cumplido, René; Villaseñor-Pineda, Luis; Feregrino-Uribe, Claudia; Carrasco-Ochoa, Jesús Ariel

2014-01-01

Sequential Pattern Mining is a widely addressed problem in data mining, with applications such as analyzing Web usage, examining purchase behavior, and text mining, among others. Nevertheless, with the dramatic increase in data volume, the current approaches prove inefficient when dealing with large input datasets, a large number of different symbols and low minimum supports. In this paper, we propose a new sequential pattern mining algorithm, which follows a pattern-growth scheme to discover sequential patterns. Unlike most pattern growth algorithms, our approach does not build a data structure to represent the input dataset, but instead accesses the required sequences through pseudo-projection databases, achieving better runtime and reducing memory requirements. Our algorithm traverses the search space in a depth-first fashion and only preserves in memory a pattern node linkage and the pseudo-projections required for the branch being explored at the time. Experimental results show that our new approach, the Node Linkage Depth-First Traversal algorithm (NLDFT), has better performance and scalability in comparison with state of the art algorithms. PMID:24933123

Biocellion: accelerating computer simulation of multicellular biological system models

PubMed Central

Kang, Seunghwa; Kahan, Simon; McDermott, Jason; Flann, Nicholas; Shmulevich, Ilya

2014-01-01

Motivation: Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming. Results: We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biological system models, Biocellion asks users to provide their model specifics by filling the function body of pre-defined model routines. Using Biocellion, modelers without parallel computing expertise can efficiently exploit parallel computers with less effort than writing sequential programs from scratch. We simulate cell sorting, microbial patterning and a bacterial system in soil aggregate as case studies. Availability and implementation: Biocellion runs on x86 compatible systems with the 64 bit Linux operating system and is freely available for academic use. Visit http://biocellion.com for additional information. Contact: seunghwa.kang@pnnl.gov PMID:25064572

Scalable Nonlinear Solvers for Fully Implicit Coupled Nuclear Fuel Modeling. Final Report

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

Cai, Xiao-Chuan; Keyes, David; Yang, Chao

2014-09-29

The focus of the project is on the development and customization of some highly scalable domain decomposition based preconditioning techniques for the numerical solution of nonlinear, coupled systems of partial differential equations (PDEs) arising from nuclear fuel simulations. These high-order PDEs represent multiple interacting physical fields (for example, heat conduction, oxygen transport, solid deformation), each is modeled by a certain type of Cahn-Hilliard and/or Allen-Cahn equations. Most existing approaches involve a careful splitting of the fields and the use of field-by-field iterations to obtain a solution of the coupled problem. Such approaches have many advantages such as ease of implementationmore » since only single field solvers are needed, but also exhibit disadvantages. For example, certain nonlinear interactions between the fields may not be fully captured, and for unsteady problems, stable time integration schemes are difficult to design. In addition, when implemented on large scale parallel computers, the sequential nature of the field-by-field iterations substantially reduces the parallel efficiency. To overcome the disadvantages, fully coupled approaches have been investigated in order to obtain full physics simulations.« less

Sequential Dependencies in Driving

ERIC Educational Resources Information Center

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…

J-adaptive estimation with estimated noise statistics

NASA Technical Reports Server (NTRS)

Jazwinski, A. H.; Hipkins, C.

1973-01-01

The J-adaptive sequential estimator is extended to include simultaneous estimation of the noise statistics in a model for system dynamics. This extension completely automates the estimator, eliminating the requirement of an analyst in the loop. Simulations in satellite orbit determination demonstrate the efficacy of the sequential estimation algorithm.

Parallelization and automatic data distribution for nuclear reactor simulations

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

Liebrock, L.M.

1997-07-01

Detailed attempts at realistic nuclear reactor simulations currently take many times real time to execute on high performance workstations. Even the fastest sequential machine can not run these simulations fast enough to ensure that the best corrective measure is used during a nuclear accident to prevent a minor malfunction from becoming a major catastrophe. Since sequential computers have nearly reached the speed of light barrier, these simulations will have to be run in parallel to make significant improvements in speed. In physical reactor plants, parallelism abounds. Fluids flow, controls change, and reactions occur in parallel with only adjacent components directlymore » affecting each other. These do not occur in the sequentialized manner, with global instantaneous effects, that is often used in simulators. Development of parallel algorithms that more closely approximate the real-world operation of a reactor may, in addition to speeding up the simulations, actually improve the accuracy and reliability of the predictions generated. Three types of parallel architecture (shared memory machines, distributed memory multicomputers, and distributed networks) are briefly reviewed as targets for parallelization of nuclear reactor simulation. Various parallelization models (loop-based model, shared memory model, functional model, data parallel model, and a combined functional and data parallel model) are discussed along with their advantages and disadvantages for nuclear reactor simulation. A variety of tools are introduced for each of the models. Emphasis is placed on the data parallel model as the primary focus for two-phase flow simulation. Tools to support data parallel programming for multiple component applications and special parallelization considerations are also discussed.« less

A Systematic Approach to Subgroup Classification in Intellectual Disability

ERIC Educational Resources Information Center

Schalock, Robert L.; Luckasson, Ruth

2015-01-01

This article describes a systematic approach to subgroup classification based on a classification framework and sequential steps involved in the subgrouping process. The sequential steps are stating the purpose of the classification, identifying the classification elements, using relevant information, and using clearly stated and purposeful…

A sampling and classification item selection approach with content balancing.

PubMed

Chen, Pei-Hua

2015-03-01

Existing automated test assembly methods typically employ constrained combinatorial optimization. Constructing forms sequentially based on an optimization approach usually results in unparallel forms and requires heuristic modifications. Methods based on a random search approach have the major advantage of producing parallel forms sequentially without further adjustment. This study incorporated a flexible content-balancing element into the statistical perspective item selection method of the cell-only method (Chen et al. in Educational and Psychological Measurement, 72(6), 933-953, 2012). The new method was compared with a sequential interitem distance weighted deviation model (IID WDM) (Swanson & Stocking in Applied Psychological Measurement, 17(2), 151-166, 1993), a simultaneous IID WDM, and a big-shadow-test mixed integer programming (BST MIP) method to construct multiple parallel forms based on matching a reference form item-by-item. The results showed that the cell-only method with content balancing and the sequential and simultaneous versions of IID WDM yielded results comparable to those obtained using the BST MIP method. The cell-only method with content balancing is computationally less intensive than the sequential and simultaneous versions of IID WDM.

A Bayesian sequential processor approach to spectroscopic portal system decisions

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

Sale, K; Candy, J; Breitfeller, E

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 waitingmore » 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.« less

Ascertainment correction for Markov chain Monte Carlo segregation and linkage analysis of a quantitative trait.

PubMed

Ma, Jianzhong; Amos, Christopher I; Warwick Daw, E

2007-09-01

Although extended pedigrees are often sampled through probands with extreme levels of a quantitative trait, Markov chain Monte Carlo (MCMC) methods for segregation and linkage analysis have not been able to perform ascertainment corrections. Further, the extent to which ascertainment of pedigrees leads to biases in the estimation of segregation and linkage parameters has not been previously studied for MCMC procedures. In this paper, we studied these issues with a Bayesian MCMC approach for joint segregation and linkage analysis, as implemented in the package Loki. We first simulated pedigrees ascertained through individuals with extreme values of a quantitative trait in spirit of the sequential sampling theory of Cannings and Thompson [Cannings and Thompson [1977] Clin. Genet. 12:208-212]. Using our simulated data, we detected no bias in estimates of the trait locus location. However, in addition to allele frequencies, when the ascertainment threshold was higher than or close to the true value of the highest genotypic mean, bias was also found in the estimation of this parameter. When there were multiple trait loci, this bias destroyed the additivity of the effects of the trait loci, and caused biases in the estimation all genotypic means when a purely additive model was used for analyzing the data. To account for pedigree ascertainment with sequential sampling, we developed a Bayesian ascertainment approach and implemented Metropolis-Hastings updates in the MCMC samplers used in Loki. Ascertainment correction greatly reduced biases in parameter estimates. Our method is designed for multiple, but a fixed number of trait loci. Copyright (c) 2007 Wiley-Liss, Inc.

Evaluation of Lead Release in a Simulated Lead-Free Premise Plumbing System Using a Sequential Sampling Approach

PubMed Central

Ng, Ding-Quan; Lin, Yi-Pin

2016-01-01

In this pilot study, a modified sampling protocol was evaluated for the detection of lead contamination and locating the source of lead release in a simulated premise plumbing system with one-, three- and seven-day stagnation for a total period of 475 days. Copper pipes, stainless steel taps and brass fittings were used to assemble the “lead-free” system. Sequential sampling using 100 mL was used to detect lead contamination while that using 50 mL was used to locate the lead source. Elevated lead levels, far exceeding the World Health Organization (WHO) guideline value of 10 µg·L−1, persisted for as long as five months in the system. “Lead-free” brass fittings were identified as the source of lead contamination. Physical disturbances, such as renovation works, could cause short-term spikes in lead release. Orthophosphate was able to suppress total lead levels below 10 µg·L−1, but caused “blue water” problems. When orthophosphate addition was ceased, total lead levels began to spike within one week, implying that a continuous supply of orthophosphate was required to control total lead levels. Occasional total lead spikes were observed in one-day stagnation samples throughout the course of the experiments. PMID:26927154

Evaluation of Lead Release in a Simulated Lead-Free Premise Plumbing System Using a Sequential Sampling Approach.

PubMed

Ng, Ding-Quan; Lin, Yi-Pin

2016-02-27

In this pilot study, a modified sampling protocol was evaluated for the detection of lead contamination and locating the source of lead release in a simulated premise plumbing system with one-, three- and seven-day stagnation for a total period of 475 days. Copper pipes, stainless steel taps and brass fittings were used to assemble the "lead-free" system. Sequential sampling using 100 mL was used to detect lead contamination while that using 50 mL was used to locate the lead source. Elevated lead levels, far exceeding the World Health Organization (WHO) guideline value of 10 µg · L(-1), persisted for as long as five months in the system. "Lead-free" brass fittings were identified as the source of lead contamination. Physical disturbances, such as renovation works, could cause short-term spikes in lead release. Orthophosphate was able to suppress total lead levels below 10 µg · L(-1), but caused "blue water" problems. When orthophosphate addition was ceased, total lead levels began to spike within one week, implying that a continuous supply of orthophosphate was required to control total lead levels. Occasional total lead spikes were observed in one-day stagnation samples throughout the course of the experiments.

Kullback-Leibler information function and the sequential selection of experiments to discriminate among several linear models. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Sidik, S. M.

1972-01-01

A sequential adaptive experimental design procedure for a related problem is studied. It is assumed that a finite set of potential linear models relating certain controlled variables to an observed variable is postulated, and that exactly one of these models is correct. The problem is to sequentially design most informative experiments so that the correct model equation can be determined with as little experimentation as possible. Discussion includes: structure of the linear models; prerequisite distribution theory; entropy functions and the Kullback-Leibler information function; the sequential decision procedure; and computer simulation results. An example of application is given.

Concurrent processing simulation of the space station

NASA Technical Reports Server (NTRS)

Gluck, R.; Hale, A. L.; Sunkel, John W.

1989-01-01

The development of a new capability for the time-domain simulation of multibody dynamic systems and its application to the study of a large angle rotational maneuvers of the Space Station is described. The effort was divided into three sequential tasks, which required significant advancements of the state-of-the art to accomplish. These were: (1) the development of an explicit mathematical model via symbol manipulation of a flexible, multibody dynamic system; (2) the development of a methodology for balancing the computational load of an explicit mathematical model for concurrent processing; and (3) the implementation and successful simulation of the above on a prototype Custom Architectured Parallel Processing System (CAPPS) containing eight processors. The throughput rate achieved by the CAPPS operating at only 70 percent efficiency, was 3.9 times greater than that obtained sequentially by the IBM 3090 supercomputer simulating the same problem. More significantly, analysis of the results leads to the conclusion that the relative cost effectiveness of concurrent vs. sequential digital computation will grow substantially as the computational load is increased. This is a welcomed development in an era when very complex and cumbersome mathematical models of large space vehicles must be used as substitutes for full scale testing which has become impractical.

EEG-fMRI Bayesian framework for neural activity estimation: a simulation study

NASA Astrophysics Data System (ADS)

Croce, Pierpaolo; Basti, Alessio; Marzetti, Laura; Zappasodi, Filippo; Del Gratta, Cosimo

2016-12-01

Objective. Due to the complementary nature of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), and given the possibility of simultaneous acquisition, the joint data analysis can afford a better understanding of the underlying neural activity estimation. In this simulation study we want to show the benefit of the joint EEG-fMRI neural activity estimation in a Bayesian framework. Approach. We built a dynamic Bayesian framework in order to perform joint EEG-fMRI neural activity time course estimation. The neural activity is originated by a given brain area and detected by means of both measurement techniques. We have chosen a resting state neural activity situation to address the worst case in terms of the signal-to-noise ratio. To infer information by EEG and fMRI concurrently we used a tool belonging to the sequential Monte Carlo (SMC) methods: the particle filter (PF). Main results. First, despite a high computational cost, we showed the feasibility of such an approach. Second, we obtained an improvement in neural activity reconstruction when using both EEG and fMRI measurements. Significance. The proposed simulation shows the improvements in neural activity reconstruction with EEG-fMRI simultaneous data. The application of such an approach to real data allows a better comprehension of the neural dynamics.

A Sequential Multiplicative Extended Kalman Filter for Attitude Estimation Using Vector Observations.

PubMed

Qin, Fangjun; Chang, Lubin; Jiang, Sai; Zha, Feng

2018-05-03

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.

A Sequential Multiplicative Extended Kalman Filter for Attitude Estimation Using Vector Observations

PubMed Central

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

A posteriori model validation for the temporal order of directed functional connectivity maps

PubMed Central

Beltz, Adriene M.; Molenaar, Peter C. M.

2015-01-01

A posteriori model validation for the temporal order of neural directed functional connectivity maps is rare. This is striking because models that require sequential independence among residuals are regularly implemented. The aim of the current study was (a) to apply to directed functional connectivity maps of functional magnetic resonance imaging data an a posteriori model validation procedure (i.e., white noise tests of one-step-ahead prediction errors combined with decision criteria for revising the maps based upon Lagrange Multiplier tests), and (b) to demonstrate how the procedure applies to single-subject simulated, single-subject task-related, and multi-subject resting state data. Directed functional connectivity was determined by the unified structural equation model family of approaches in order to map contemporaneous and first order lagged connections among brain regions at the group- and individual-levels while incorporating external input, then white noise tests were run. Findings revealed that the validation procedure successfully detected unmodeled sequential dependencies among residuals and recovered higher order (greater than one) simulated connections, and that the procedure can accommodate task-related input. Findings also revealed that lags greater than one were present in resting state data: With a group-level network that contained only contemporaneous and first order connections, 44% of subjects required second order, individual-level connections in order to obtain maps with white noise residuals. Results have broad methodological relevance (e.g., temporal validation is necessary after directed functional connectivity analyses because the presence of unmodeled higher order sequential dependencies may bias parameter estimates) and substantive implications (e.g., higher order lags may be common in resting state data). PMID:26379489

The Relevance of Visual Sequential Memory to Reading.

ERIC Educational Resources Information Center

Crispin, Lisa; And Others

1984-01-01

Results of three visual sequential memory tests and a group reading test given to 19 elementary students are discussed in terms of task analysis and structuralist approaches to analysis of reading skills. Relation of visual sequential memory to other reading subskills is considered in light of current reasearch. (CMG)

On the error probability of general tree and trellis codes with applications to sequential decoding

NASA Technical Reports Server (NTRS)

Johannesson, R.

1973-01-01

An upper bound on the average error probability for maximum-likelihood decoding of the ensemble of random binary tree codes is derived and shown to be independent of the length of the tree. An upper bound on the average error probability for maximum-likelihood decoding of the ensemble of random L-branch binary trellis codes of rate R = 1/n is derived which separates the effects of the tail length T and the memory length M of the code. It is shown that the bound is independent of the length L of the information sequence. This implication is investigated by computer simulations of sequential decoding utilizing the stack algorithm. These simulations confirm the implication and further suggest an empirical formula for the true undetected decoding error probability with sequential decoding.

Sequential use of simulation and optimization in analysis and planning

Treesearch

Hans R. Zuuring; Jimmie D. Chew; J. Greg Jones

2000-01-01

Management activities are analyzed at landscape scales employing both simulation and optimization. SIMPPLLE, a stochastic simulation modeling system, is initially applied to assess the risks associated with a specific natural process occurring on the current landscape without management treatments, but with fire suppression. These simulation results are input into...

Using Zebra-speech to study sequential and simultaneous speech segregation in a cochlear-implant simulation.

PubMed

Gaudrain, Etienne; Carlyon, Robert P

2013-01-01

Previous studies have suggested that cochlear implant users may have particular difficulties exploiting opportunities to glimpse clear segments of a target speech signal in the presence of a fluctuating masker. Although it has been proposed that this difficulty is associated with a deficit in linking the glimpsed segments across time, the details of this mechanism are yet to be explained. The present study introduces a method called Zebra-speech developed to investigate the relative contribution of simultaneous and sequential segregation mechanisms in concurrent speech perception, using a noise-band vocoder to simulate cochlear implants. One experiment showed that the saliency of the difference between the target and the masker is a key factor for Zebra-speech perception, as it is for sequential segregation. Furthermore, forward masking played little or no role, confirming that intelligibility was not limited by energetic masking but by across-time linkage abilities. In another experiment, a binaural cue was used to distinguish the target and the masker. It showed that the relative contribution of simultaneous and sequential segregation depended on the spectral resolution, with listeners relying more on sequential segregation when the spectral resolution was reduced. The potential of Zebra-speech as a segregation enhancement strategy for cochlear implants is discussed.

Using Zebra-speech to study sequential and simultaneous speech segregation in a cochlear-implant simulation

PubMed Central

Gaudrain, Etienne; Carlyon, Robert P.

2013-01-01

Previous studies have suggested that cochlear implant users may have particular difficulties exploiting opportunities to glimpse clear segments of a target speech signal in the presence of a fluctuating masker. Although it has been proposed that this difficulty is associated with a deficit in linking the glimpsed segments across time, the details of this mechanism are yet to be explained. The present study introduces a method called Zebra-speech developed to investigate the relative contribution of simultaneous and sequential segregation mechanisms in concurrent speech perception, using a noise-band vocoder to simulate cochlear implants. One experiment showed that the saliency of the difference between the target and the masker is a key factor for Zebra-speech perception, as it is for sequential segregation. Furthermore, forward masking played little or no role, confirming that intelligibility was not limited by energetic masking but by across-time linkage abilities. In another experiment, a binaural cue was used to distinguish target and masker. It showed that the relative contribution of simultaneous and sequential segregation depended on the spectral resolution, with listeners relying more on sequential segregation when the spectral resolution was reduced. The potential of Zebra-speech as a segregation enhancement strategy for cochlear implants is discussed. PMID:23297922

Inhomogeneities detection in annual precipitation time series in Portugal using direct sequential simulation

NASA Astrophysics Data System (ADS)

Caineta, Júlio; Ribeiro, Sara; Costa, Ana Cristina; Henriques, Roberto; Soares, Amílcar

2014-05-01

Climate data homogenisation is of major importance in monitoring climate change, the validation of weather forecasting, general circulation and regional atmospheric models, modelling of erosion, drought monitoring, among other studies of hydrological and environmental impacts. This happens because non-climate factors can cause time series discontinuities which may hide the true climatic signal and patterns, thus potentially bias the conclusions of those studies. In the last two decades, many methods have been developed to identify and remove these inhomogeneities. One of those is based on geostatistical simulation (DSS - direct sequential simulation), where local probability density functions (pdf) are calculated at candidate monitoring stations, using spatial and temporal neighbouring observations, and then are used for detection of inhomogeneities. This approach has been previously applied to detect inhomogeneities in four precipitation series (wet day count) from a network with 66 monitoring stations located in the southern region of Portugal (1980-2001). This study revealed promising results and the potential advantages of geostatistical techniques for inhomogeneities detection in climate time series. This work extends the case study presented before and investigates the application of the geostatistical stochastic approach to ten precipitation series that were previously classified as inhomogeneous by one of six absolute homogeneity tests (Mann-Kendall test, Wald-Wolfowitz runs test, Von Neumann ratio test, Standard normal homogeneity test (SNHT) for a single break, Pettit test, and Buishand range test). Moreover, a sensibility analysis is implemented to investigate the number of simulated realisations that should be used to accurately infer the local pdfs. Accordingly, the number of simulations per iteration is increased from 50 to 500, which resulted in a more representative local pdf. A set of default and recommended settings is provided, which will help other users to implement this method. The need of user intervention is reduced to a minimum through the usage of a cross-platform script. Finally, as in the previous study, the results are compared with those from the SNHT, Pettit and Buishand range tests, which were applied to composite (ratio) reference series. Acknowledgements: The authors gratefully acknowledge the financial support of "Fundação para a Ciência e Tecnologia" (FCT), Portugal, through the research project PTDC/GEO-MET/4026/2012 ("GSIMCLI - Geostatistical simulation with local distributions for the homogenization and interpolation of climate data").

Multiscale Modeling of Damage Processes in fcc Aluminum: From Atoms to Grains

NASA Technical Reports Server (NTRS)

Glaessgen, E. H.; Saether, E.; Yamakov, V.

2008-01-01

Molecular dynamics (MD) methods are opening new opportunities for simulating the fundamental processes of material behavior at the atomistic level. However, current analysis is limited to small domains and increasing the size of the MD domain quickly presents intractable computational demands. A preferred approach to surmount this computational limitation has been to combine continuum mechanics-based modeling procedures, such as the finite element method (FEM), with MD analyses thereby reducing the region of atomic scale refinement. Such multiscale modeling strategies can be divided into two broad classifications: concurrent multiscale methods that directly incorporate an atomistic domain within a continuum domain and sequential multiscale methods that extract an averaged response from the atomistic simulation for later use as a constitutive model in a continuum analysis.

Simulations of 6-DOF Motion with a Cartesian Method

NASA Technical Reports Server (NTRS)

Murman, Scott M.; Aftosmis, Michael J.; Berger, Marsha J.; Kwak, Dochan (Technical Monitor)

2003-01-01

Coupled 6-DOF/CFD trajectory predictions using an automated Cartesian method are demonstrated by simulating a GBU-32/JDAM store separating from an F-18C aircraft. Numerical simulations are performed at two Mach numbers near the sonic speed, and compared with flight-test telemetry and photographic-derived data. Simulation results obtained with a sequential-static series of flow solutions are contrasted with results using a time-dependent flow solver. Both numerical methods show good agreement with the flight-test data through the first half of the simulations. The sequential-static and time-dependent methods diverge over the last half of the trajectory prediction. after the store produces peak angular rates. A cost comparison for the Cartesian method is included, in terms of absolute cost and relative to computing uncoupled 6-DOF trajectories. A detailed description of the 6-DOF method, as well as a verification of its accuracy, is provided in an appendix.

Monte Carlo Simulation of Sudden Death Bearing Testing

NASA Technical Reports Server (NTRS)

Vlcek, Brian L.; Hendricks, Robert C.; Zaretsky, Erwin V.

2003-01-01

Monte Carlo simulations combined with sudden death testing were used to compare resultant bearing lives to the calculated hearing life and the cumulative test time and calendar time relative to sequential and censored sequential testing. A total of 30 960 virtual 50-mm bore deep-groove ball bearings were evaluated in 33 different sudden death test configurations comprising 36, 72, and 144 bearings each. Variations in both life and Weibull slope were a function of the number of bearings failed independent of the test method used and not the total number of bearings tested. Variation in L10 life as a function of number of bearings failed were similar to variations in lift obtained from sequentially failed real bearings and from Monte Carlo (virtual) testing of entire populations. Reductions up to 40 percent in bearing test time and calendar time can be achieved by testing to failure or the L(sub 50) life and terminating all testing when the last of the predetermined bearing failures has occurred. Sudden death testing is not a more efficient method to reduce bearing test time or calendar time when compared to censored sequential testing.

Assessment of groundwater level estimation uncertainty using sequential Gaussian simulation and Bayesian bootstrapping

NASA Astrophysics Data System (ADS)

Varouchakis, Emmanouil; Hristopulos, Dionissios

2015-04-01

Space-time geostatistical approaches can improve the reliability of dynamic groundwater level models in areas with limited spatial and temporal data. Space-time residual Kriging (STRK) is a reliable method for spatiotemporal interpolation that can incorporate auxiliary information. The method usually leads to an underestimation of the prediction uncertainty. The uncertainty of spatiotemporal models is usually estimated by determining the space-time Kriging variance or by means of cross validation analysis. For de-trended data the former is not usually applied when complex spatiotemporal trend functions are assigned. A Bayesian approach based on the bootstrap idea and sequential Gaussian simulation are employed to determine the uncertainty of the spatiotemporal model (trend and covariance) parameters. These stochastic modelling approaches produce multiple realizations, rank the prediction results on the basis of specified criteria and capture the range of the uncertainty. The correlation of the spatiotemporal residuals is modeled using a non-separable space-time variogram based on the Spartan covariance family (Hristopulos and Elogne 2007, Varouchakis and Hristopulos 2013). We apply these simulation methods to investigate the uncertainty of groundwater level variations. The available dataset consists of bi-annual (dry and wet hydrological period) groundwater level measurements in 15 monitoring locations for the time period 1981 to 2010. The space-time trend function is approximated using a physical law that governs the groundwater flow in the aquifer in the presence of pumping. The main objective of this research is to compare the performance of two simulation methods for prediction uncertainty estimation. In addition, we investigate the performance of the Spartan spatiotemporal covariance function for spatiotemporal geostatistical analysis. Hristopulos, D.T. and Elogne, S.N. 2007. Analytic properties and covariance functions for a new class of generalized Gibbs random fields. IΕΕΕ Transactions on Information Theory, 53:4667-4467. Varouchakis, E.A. and Hristopulos, D.T. 2013. Improvement of groundwater level prediction in sparsely gauged basins using physical laws and local geographic features as auxiliary variables. Advances in Water Resources, 52:34-49. Research supported by the project SPARTA 1591: "Development of Space-Time Random Fields based on Local Interaction Models and Applications in the Processing of Spatiotemporal Datasets". "SPARTA" is implemented under the "ARISTEIA" Action of the operational programme Education and Lifelong Learning and is co-funded by the European Social Fund (ESF) and National Resources.

A Methodology for the Assessment of Unconventional (Continuous) Resources with an Application to the Greater Natural Buttes Gas Field, Utah

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

Olea, Ricardo A., E-mail: olea@usgs.gov; Cook, Troy A.; Coleman, James L.

2010-12-15

The Greater Natural Buttes tight natural gas field is an unconventional (continuous) accumulation in the Uinta Basin, Utah, that began production in the early 1950s from the Upper Cretaceous Mesaverde Group. Three years later, production was extended to the Eocene Wasatch Formation. With the exclusion of 1100 non-productive ('dry') wells, we estimate that the final recovery from the 2500 producing wells existing in 2007 will be about 1.7 trillion standard cubic feet (TSCF) (48.2 billion cubic meters (BCM)). The use of estimated ultimate recovery (EUR) per well is common in assessments of unconventional resources, and it is one of themore » main sources of information to forecast undiscovered resources. Each calculated recovery value has an associated drainage area that generally varies from well to well and that can be mathematically subdivided into elemental subareas of constant size and shape called cells. Recovery per 5-acre cells at Greater Natural Buttes shows spatial correlation; hence, statistical approaches that ignore this correlation when inferring EUR values for untested cells do not take full advantage of all the information contained in the data. More critically, resulting models do not match the style of spatial EUR fluctuations observed in nature. This study takes a new approach by applying spatial statistics to model geographical variation of cell EUR taking into account spatial correlation and the influence of fractures. We applied sequential indicator simulation to model non-productive cells, while spatial mapping of cell EUR was obtained by applying sequential Gaussian simulation to provide multiple versions of reality (realizations) having equal chances of being the correct model. For each realization, summation of EUR in cells not drained by the existing wells allowed preparation of a stochastic prediction of undiscovered resources, which range between 2.6 and 3.4 TSCF (73.6 and 96.3 BCM) with a mean of 2.9 TSCF (82.1 BCM) for Greater Natural Buttes. A second approach illustrates the application of multiple-point simulation to assess a hypothetical frontier area for which there is no production information but which is regarded as being similar to Greater Natural Buttes.« less

Robust parameter design for automatically controlled systems and nanostructure synthesis

NASA Astrophysics Data System (ADS)

Dasgupta, Tirthankar

2007-12-01

This research focuses on developing comprehensive frameworks for developing robust parameter design methodology for dynamic systems with automatic control and for synthesis of nanostructures. In many automatically controlled dynamic processes, the optimal feedback control law depends on the parameter design solution and vice versa and therefore an integrated approach is necessary. A parameter design methodology in the presence of feedback control is developed for processes of long duration under the assumption that experimental noise factors are uncorrelated over time. Systems that follow a pure-gain dynamic model are considered and the best proportional-integral and minimum mean squared error control strategies are developed by using robust parameter design. The proposed method is illustrated using a simulated example and a case study in a urea packing plant. This idea is also extended to cases with on-line noise factors. The possibility of integrating feedforward control with a minimum mean squared error feedback control scheme is explored. To meet the needs of large scale synthesis of nanostructures, it is critical to systematically find experimental conditions under which the desired nanostructures are synthesized reproducibly, at large quantity and with controlled morphology. The first part of the research in this area focuses on modeling and optimization of existing experimental data. Through a rigorous statistical analysis of experimental data, models linking the probabilities of obtaining specific morphologies to the process variables are developed. A new iterative algorithm for fitting a Multinomial GLM is proposed and used. The optimum process conditions, which maximize the above probabilities and make the synthesis process less sensitive to variations of process variables around set values, are derived from the fitted models using Monte-Carlo simulations. The second part of the research deals with development of an experimental design methodology, tailor-made to address the unique phenomena associated with nanostructure synthesis. A sequential space filling design called Sequential Minimum Energy Design (SMED) for exploring best process conditions for synthesis of nanowires. The SMED is a novel approach to generate sequential designs that are model independent, can quickly "carve out" regions with no observable nanostructure morphology, and allow for the exploration of complex response surfaces.

Similar outcome of allogeneic stem cell transplantation after myeloablative and sequential conditioning regimen in patients with refractory or relapsed acute myeloid leukemia: A study from the Société Francophone de Greffe de Moelle et de Thérapie Cellulaire.

PubMed

Decroocq, Justine; Itzykson, Raphaël; Vigouroux, Stéphane; Michallet, Mauricette; Yakoub-Agha, Ibrahim; Huynh, Anne; Beckerich, Florence; Suarez, Felipe; Chevallier, Patrice; Nguyen-Quoc, Stéphanie; Ledoux, Marie-Pierre; Clement, Laurence; Hicheri, Yosr; Guillerm, Gaëlle; Cornillon, Jérôme; Contentin, Nathalie; Carre, Martin; Maillard, Natacha; Mercier, Mélanie; Mohty, Mohamad; Beguin, Yves; Bourhis, Jean-Henri; Charbonnier, Amandine; Dauriac, Charles; Bay, Jacques-Olivier; Blaise, Didier; Deconinck, Eric; Jubert, Charlotte; Raus, Nicole; Peffault de Latour, Regis; Dhedin, Nathalie

2018-03-01

Patients with acute myeloid leukemia (AML) in relapse or refractory to induction therapy have a dismal prognosis. Allogeneic hematopoietic stem cell transplantation is the only curative option. In these patients, we aimed to compare the results of a myeloablative transplant versus a sequential approach consisting in a cytoreductive chemotherapy followed by a reduced intensity conditioning regimen and prophylactic donor lymphocytes infusions. We retrospectively analyzed 99 patients aged 18-50 years, transplanted for a refractory (52%) or a relapsed AML not in remission (48%). Fifty-eight patients received a sequential approach and 41 patients a myeloablative conditioning regimen. Only 6 patients received prophylactic donor lymphocytes infusions. With a median follow-up of 48 months, 2-year overall survival was 39%, 95% confidence interval (CI) (24-53) in the myeloablative group versus 33%, 95% CI (21-45) in the sequential groups (P = .39), and 2-year cumulative incidence of relapse (CIR) was 57% versus 50% respectively (P = .99). Nonrelapse mortality was not higher in the myeloablative group (17% versus 15%, P = .44). In multivariate analysis, overall survival, CIR and nonrelapse mortality remained similar between the two groups. However, in multivariate analysis, sequential conditioning led to fewer acute grade II-IV graft versus host disease (GVHD) (HR for sequential approach = 0.37; 95% CI: 0.21-0.65; P < .001) without a significant impact on chronic GVHD (all grades and extensive). In young patients with refractory or relapsed AML, myeloablative transplant and sequential approach offer similar outcomes except for a lower incidence of acute GvHD after a sequential transplant. © 2018 Wiley Periodicals, Inc.

Value for money in changing clinical practice: should decisions about guidelines and implementation strategies be made sequentially or simultaneously?

PubMed

Hoomans, Ties; Severens, Johan L; Evers, Silvia M A A; Ament, Andre J H A

2009-01-01

Decisions about clinical practice change, that is, which guidelines to adopt and how to implement them, can be made sequentially or simultaneously. Decision makers adopting a sequential approach first compare the costs and effects of alternative guidelines to select the best set of guideline recommendations for patient management and subsequently examine the implementation costs and effects to choose the best strategy to implement the selected guideline. In an integral approach, decision makers simultaneously decide about the guideline and the implementation strategy on the basis of the overall value for money in changing clinical practice. This article demonstrates that the decision to use a sequential v. an integral approach affects the need for detailed information and the complexity of the decision analytic process. More importantly, it may lead to different choices of guidelines and implementation strategies for clinical practice change. The differences in decision making and decision analysis between the alternative approaches are comprehensively illustrated using 2 hypothetical examples. We argue that, in most cases, an integral approach to deciding about change in clinical practice is preferred, as this provides more efficient use of scarce health-care resources.

Comparing multiple imputation methods for systematically missing subject-level data.

PubMed

Kline, David; Andridge, Rebecca; Kaizar, Eloise

2017-06-01

When conducting research synthesis, the collection of studies that will be combined often do not measure the same set of variables, which creates missing data. When the studies to combine are longitudinal, missing data can occur on the observation-level (time-varying) or the subject-level (non-time-varying). Traditionally, the focus of missing data methods for longitudinal data has been on missing observation-level variables. In this paper, we focus on missing subject-level variables and compare two multiple imputation approaches: a joint modeling approach and a sequential conditional modeling approach. We find the joint modeling approach to be preferable to the sequential conditional approach, except when the covariance structure of the repeated outcome for each individual has homogenous variance and exchangeable correlation. Specifically, the regression coefficient estimates from an analysis incorporating imputed values based on the sequential conditional method are attenuated and less efficient than those from the joint method. Remarkably, the estimates from the sequential conditional method are often less efficient than a complete case analysis, which, in the context of research synthesis, implies that we lose efficiency by combining studies. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Parallelization of a Fully-Distributed Hydrologic Model using Sub-basin Partitioning

NASA Astrophysics Data System (ADS)

Vivoni, E. R.; Mniszewski, S.; Fasel, P.; Springer, E.; Ivanov, V. Y.; Bras, R. L.

2005-12-01

A primary obstacle towards advances in watershed simulations has been the limited computational capacity available to most models. The growing trend of model complexity, data availability and physical representation has not been matched by adequate developments in computational efficiency. This situation has created a serious bottleneck which limits existing distributed hydrologic models to small domains and short simulations. In this study, we present novel developments in the parallelization of a fully-distributed hydrologic model. Our work is based on the TIN-based Real-time Integrated Basin Simulator (tRIBS), which provides continuous hydrologic simulation using a multiple resolution representation of complex terrain based on a triangulated irregular network (TIN). While the use of TINs reduces computational demand, the sequential version of the model is currently limited over large basins (>10,000 km2) and long simulation periods (>1 year). To address this, a parallel MPI-based version of the tRIBS model has been implemented and tested using high performance computing resources at Los Alamos National Laboratory. Our approach utilizes domain decomposition based on sub-basin partitioning of the watershed. A stream reach graph based on the channel network structure is used to guide the sub-basin partitioning. Individual sub-basins or sub-graphs of sub-basins are assigned to separate processors to carry out internal hydrologic computations (e.g. rainfall-runoff transformation). Routed streamflow from each sub-basin forms the major hydrologic data exchange along the stream reach graph. Individual sub-basins also share subsurface hydrologic fluxes across adjacent boundaries. We demonstrate how the sub-basin partitioning provides computational feasibility and efficiency for a set of test watersheds in northeastern Oklahoma. We compare the performance of the sequential and parallelized versions to highlight the efficiency gained as the number of processors increases. We also discuss how the coupled use of TINs and parallel processing can lead to feasible long-term simulations in regional watersheds while preserving basin properties at high-resolution.

Dry minor mergers and size evolution of high-z compact massive early-type galaxies

NASA Astrophysics Data System (ADS)

Oogi, Taira; Habe, Asao

2012-09-01

Recent observations show evidence that high-z (z ~ 2 - 3) early-type galaxies (ETGs) are quite compact than that with comparable mass at z ~ 0. Dry merger scenario is one of the most probable one that can explain such size evolution. However, previous studies based on this scenario do not succeed to explain both properties of high-z compact massive ETGs and local ETGs, consistently. We investigate effects of sequential, multiple dry minor (stellar mass ratio M2/M1<1/4) mergers on the size evolution of compact massive ETGs. We perform N-body simulations of the sequential minor mergers with parabolic and head-on orbits, including a dark matter component and a stellar component. We show that the sequential minor mergers of compact satellite galaxies are the most efficient in the size growth and in decrease of the velocity dispersion of the compact massive ETGs. The change of stellar size and density of the merger remnant is consistent with the recent observations. Furthermore, we construct the merger histories of candidates of high-z compact massive ETGs using the Millennium Simulation Database, and estimate the size growth of the galaxies by dry minor mergers. We can reproduce the mean size growth factor between z = 2 and z = 0, assuming the most efficient size growth obtained in the case of the sequential minor mergers in our simulations.

Numerical Validation of Chemical Compositional Model for Wettability Alteration Processes

NASA Astrophysics Data System (ADS)

Bekbauov, Bakhbergen; Berdyshev, Abdumauvlen; Baishemirov, Zharasbek; Bau, Domenico

2017-12-01

Chemical compositional simulation of enhanced oil recovery and surfactant enhanced aquifer remediation processes is a complex task that involves solving dozens of equations for all grid blocks representing a reservoir. In the present work, we perform a numerical validation of the newly developed mathematical formulation which satisfies the conservation laws of mass and energy and allows applying a sequential solution approach to solve the governing equations separately and implicitly. Through its application to the numerical experiment using a wettability alteration model and comparisons with existing chemical compositional model's numerical results, the new model has proven to be practical, reliable and stable.

Night vision goggle stimulation using LCoS and DLP projection technology, which is better?

NASA Astrophysics Data System (ADS)

Ali, Masoud H.; Lyon, Paul; De Meerleer, Peter

2014-06-01

High fidelity night-vision training has become important for many of the simulation systems being procured today. The end-users of these simulation-training systems prefer using their actual night-vision goggle (NVG) headsets. This requires that the visual display system stimulate the NVGs in a realistic way. Historically NVG stimulation was done with cathode-ray tube (CRT) projectors. However, this technology became obsolete and in recent years training simulators do NVG stimulation with laser, LCoS and DLP projectors. The LCoS and DLP projection technologies have emerged as the preferred approach for the stimulation of NVGs. Both LCoS and DLP technologies have advantages and disadvantages for stimulating NVGs. LCoS projectors can have more than 5-10 times the contrast capability of DLP projectors. The larger the difference between the projected black level and the brightest object in a scene, the better the NVG stimulation effects can be. This is an advantage of LCoS technology, especially when the proper NVG wavelengths are used. Single-chip DLP projectors, even though they have much reduced contrast compared to LCoS projectors, can use LED illuminators in a sequential red-green-blue fashion to create a projected image. It is straightforward to add an extra infrared (NVG wavelength) LED into this sequential chain of LED illumination. The content of this NVG channel can be independent of the visible scene, which allows effects to be added that can compensate for the lack of contrast inherent in a DLP device. This paper will expand on the differences between LCoS and DLP projectors for stimulating NVGs and summarize the benefits of both in night-vision simulation training systems.

Scorpion Hybrid Optical-based Inertial Tracker (HObIT) test results

NASA Astrophysics Data System (ADS)

Atac, Robert; Spink, Scott; Calloway, Tom; Foxlin, Eric

2014-06-01

High fidelity night-vision training has become important for many of the simulation systems being procured today. The end-users of these simulation-training systems prefer using their actual night-vision goggle (NVG) headsets. This requires that the visual display system stimulate the NVGs in a realistic way. Historically NVG stimulation was done with cathode-ray tube (CRT) projectors. However, this technology became obsolete and in recent years training simulators do NVG stimulation with laser, LCoS and DLP projectors. The LCoS and DLP projection technologies have emerged as the preferred approach for the stimulation of NVGs. Both LCoS and DLP technologies have advantages and disadvantages for stimulating NVGs. LCoS projectors can have more than 5-10 times the contrast capability of DLP projectors. The larger the difference between the projected black level and the brightest object in a scene, the better the NVG stimulation effects can be. This is an advantage of LCoS technology, especially when the proper NVG wavelengths are used. Single-chip DLP projectors, even though they have much reduced contrast compared to LCoS projectors, can use LED illuminators in a sequential red-green-blue fashion to create a projected image. It is straightforward to add an extra infrared (NVG wavelength) LED into this sequential chain of LED illumination. The content of this NVG channel can be independent of the visible scene, which allows effects to be added that can compensate for the lack of contrast inherent in a DLP device. This paper will expand on the differences between LCoS and DLP projectors for stimulating NVGs and summarize the benefits of both in night-vision simulation training systems.

Description and effects of sequential behavior practice in teacher education.

PubMed

Sharpe, T; Lounsbery, M; Bahls, V

1997-09-01

This study examined the effects of a sequential behavior feedback protocol on the practice-teaching experiences of undergraduate teacher trainees. The performance competencies of teacher trainees were analyzed using an alternative opportunities for appropriate action measure. Data support the added utility of sequential (Sharpe, 1997a, 1997b) behavior analysis information in systematic observation approaches to teacher education. One field-based undergraduate practicum using sequential behavior (i.e., field systems analysis) principles was monitored. Summarized are the key elements of the (a) classroom instruction provided as a precursor to the practice teaching experience, (b) practice teaching experience, and (c) field systems observation tool used for evaluation and feedback, including multiple-baseline data (N = 4) to support this approach to teacher education. Results point to (a) the strong relationship between sequential behavior feedback and the positive change in four preservice teachers' day-to-day teaching practices in challenging situational contexts, and (b) the relationship between changes in teacher practices and positive changes in the behavioral practices of gymnasium pupils. Sequential behavior feedback was also socially validated by the undergraduate participants and Professional Development School teacher supervisors in the study.

BeatBox-HPC simulation environment for biophysically and anatomically realistic cardiac electrophysiology.

PubMed

Antonioletti, Mario; Biktashev, Vadim N; Jackson, Adrian; Kharche, Sanjay R; Stary, Tomas; Biktasheva, Irina V

2017-01-01

The BeatBox simulation environment combines flexible script language user interface with the robust computational tools, in order to setup cardiac electrophysiology in-silico experiments without re-coding at low-level, so that cell excitation, tissue/anatomy models, stimulation protocols may be included into a BeatBox script, and simulation run either sequentially or in parallel (MPI) without re-compilation. BeatBox is a free software written in C language to be run on a Unix-based platform. It provides the whole spectrum of multi scale tissue modelling from 0-dimensional individual cell simulation, 1-dimensional fibre, 2-dimensional sheet and 3-dimensional slab of tissue, up to anatomically realistic whole heart simulations, with run time measurements including cardiac re-entry tip/filament tracing, ECG, local/global samples of any variables, etc. BeatBox solvers, cell, and tissue/anatomy models repositories are extended via robust and flexible interfaces, thus providing an open framework for new developments in the field. In this paper we give an overview of the BeatBox current state, together with a description of the main computational methods and MPI parallelisation approaches.

Building merger trees from cosmological N-body simulations. Towards improving galaxy formation models using subhaloes

NASA Astrophysics Data System (ADS)

Tweed, D.; Devriendt, J.; Blaizot, J.; Colombi, S.; Slyz, A.

2009-11-01

Context: In the past decade or so, using numerical N-body simulations to describe the gravitational clustering of dark matter (DM) in an expanding universe has become the tool of choice for tackling the issue of hierarchical galaxy formation. As mass resolution increases with the power of supercomputers, one is able to grasp finer and finer details of this process, resolving more and more of the inner structure of collapsed objects. This begs one to revisit time and again the post-processing tools with which one transforms particles into “invisible” dark matter haloes and from thereon into luminous galaxies. Aims: Although a fair amount of work has been devoted to growing Monte-Carlo merger trees that resemble those built from an N-body simulation, comparatively little effort has been invested in quantifying the caveats one necessarily encounters when one extracts trees directly from such a simulation. To somewhat revert the tide, this paper seeks to provide its reader with a comprehensive study of the problems one faces when following this route. Methods: The first step in building merger histories of dark matter haloes and their subhaloes is to identify these structures in each of the time outputs (snapshots) produced by the simulation. Even though we discuss a particular implementation of such an algorithm (called AdaptaHOP) in this paper, we believe that our results do not depend on the exact details of the implementation but instead extend to most if not all (sub)structure finders. To illustrate this point in the appendix we compare AdaptaHOP's results to the standard friend-of-friend (FOF) algorithm, widely utilised in the astrophysical community. We then highlight different ways of building merger histories from AdaptaHOP haloes and subhaloes, contrasting their various advantages and drawbacks. Results: We find that the best approach to (sub)halo merging histories is through an analysis that goes back and forth between identification and tree building rather than one that conducts a straightforward sequential treatment of these two steps. This is rooted in the complexity of the merging trees that have to depict an inherently dynamical process from the partial temporal information contained in the collection of instantaneous snapshots available from the N-body simulation. However, we also propose a simpler sequential “Most massive Substructure Method” (MSM) whose trees approximate those obtained via the more complicated non sequential method. Appendices are only available in electronic form at: http://www.aanda.org

Uncertainty assessment of PM2.5 contamination mapping using spatiotemporal sequential indicator simulations and multi-temporal monitoring data.

PubMed

Yang, Yong; Christakos, George; Huang, Wei; Lin, Chengda; Fu, Peihong; Mei, Yang

2016-04-12

Because of the rapid economic growth in China, many regions are subjected to severe particulate matter pollution. Thus, improving the methods of determining the spatiotemporal distribution and uncertainty of air pollution can provide considerable benefits when developing risk assessments and environmental policies. The uncertainty assessment methods currently in use include the sequential indicator simulation (SIS) and indicator kriging techniques. However, these methods cannot be employed to assess multi-temporal data. In this work, a spatiotemporal sequential indicator simulation (STSIS) based on a non-separable spatiotemporal semivariogram model was used to assimilate multi-temporal data in the mapping and uncertainty assessment of PM2.5 distributions in a contaminated atmosphere. PM2.5 concentrations recorded throughout 2014 in Shandong Province, China were used as the experimental dataset. Based on the number of STSIS procedures, we assessed various types of mapping uncertainties, including single-location uncertainties over one day and multiple days and multi-location uncertainties over one day and multiple days. A comparison of the STSIS technique with the SIS technique indicate that a better performance was obtained with the STSIS method.

Uncertainty assessment of PM2.5 contamination mapping using spatiotemporal sequential indicator simulations and multi-temporal monitoring data

NASA Astrophysics Data System (ADS)

Yang, Yong; Christakos, George; Huang, Wei; Lin, Chengda; Fu, Peihong; Mei, Yang

2016-04-01

Because of the rapid economic growth in China, many regions are subjected to severe particulate matter pollution. Thus, improving the methods of determining the spatiotemporal distribution and uncertainty of air pollution can provide considerable benefits when developing risk assessments and environmental policies. The uncertainty assessment methods currently in use include the sequential indicator simulation (SIS) and indicator kriging techniques. However, these methods cannot be employed to assess multi-temporal data. In this work, a spatiotemporal sequential indicator simulation (STSIS) based on a non-separable spatiotemporal semivariogram model was used to assimilate multi-temporal data in the mapping and uncertainty assessment of PM2.5 distributions in a contaminated atmosphere. PM2.5 concentrations recorded throughout 2014 in Shandong Province, China were used as the experimental dataset. Based on the number of STSIS procedures, we assessed various types of mapping uncertainties, including single-location uncertainties over one day and multiple days and multi-location uncertainties over one day and multiple days. A comparison of the STSIS technique with the SIS technique indicate that a better performance was obtained with the STSIS method.

Numerical simulation of pseudoelastic shape memory alloys using the large time increment method

NASA Astrophysics Data System (ADS)

Gu, Xiaojun; Zhang, Weihong; Zaki, Wael; Moumni, Ziad

2017-04-01

The paper presents a numerical implementation of the large time increment (LATIN) method for the simulation of shape memory alloys (SMAs) in the pseudoelastic range. The method was initially proposed as an alternative to the conventional incremental approach for the integration of nonlinear constitutive models. It is adapted here for the simulation of pseudoelastic SMA behavior using the Zaki-Moumni model and is shown to be especially useful in situations where the phase transformation process presents little or lack of hardening. In these situations, a slight stress variation in a load increment can result in large variations of strain and local state variables, which may lead to difficulties in numerical convergence. In contrast to the conventional incremental method, the LATIN method solve the global equilibrium and local consistency conditions sequentially for the entire loading path. The achieved solution must satisfy the conditions of static and kinematic admissibility and consistency simultaneously after several iterations. 3D numerical implementation is accomplished using an implicit algorithm and is then used for finite element simulation using the software Abaqus. Computational tests demonstrate the ability of this approach to simulate SMAs presenting flat phase transformation plateaus and subjected to complex loading cases, such as the quasi-static behavior of a stent structure. Some numerical results are contrasted to those obtained using step-by-step incremental integration.

The Maximum Cross-Correlation approach to detecting translational motions from sequential remote-sensing images

NASA Astrophysics Data System (ADS)

Gao, J.; Lythe, M. B.

1996-06-01

This paper presents the principle of the Maximum Cross-Correlation (MCC) approach in detecting translational motions within dynamic fields from time-sequential remotely sensed images. A C program implementing the approach is presented and illustrated in a flowchart. The program is tested with a pair of sea-surface temperature images derived from Advanced Very High Resolution Radiometer (AVHRR) images near East Cape, New Zealand. Results show that the mean currents in the region have been detected satisfactorily with the approach.

Stochastic uncertainty analysis for solute transport in randomly heterogeneous media using a Karhunen‐Loève‐based moment equation approach

USGS Publications Warehouse

Liu, Gaisheng; Lu, Zhiming; Zhang, Dongxiao

2007-01-01

A new approach has been developed for solving solute transport problems in randomly heterogeneous media using the Karhunen‐Loève‐based moment equation (KLME) technique proposed by Zhang and Lu (2004). The KLME approach combines the Karhunen‐Loève decomposition of the underlying random conductivity field and the perturbative and polynomial expansions of dependent variables including the hydraulic head, flow velocity, dispersion coefficient, and solute concentration. The equations obtained in this approach are sequential, and their structure is formulated in the same form as the original governing equations such that any existing simulator, such as Modular Three‐Dimensional Multispecies Transport Model for Simulation of Advection, Dispersion, and Chemical Reactions of Contaminants in Groundwater Systems (MT3DMS), can be directly applied as the solver. Through a series of two‐dimensional examples, the validity of the KLME approach is evaluated against the classical Monte Carlo simulations. Results indicate that under the flow and transport conditions examined in this work, the KLME approach provides an accurate representation of the mean concentration. For the concentration variance, the accuracy of the KLME approach is good when the conductivity variance is 0.5. As the conductivity variance increases up to 1.0, the mismatch on the concentration variance becomes large, although the mean concentration can still be accurately reproduced by the KLME approach. Our results also indicate that when the conductivity variance is relatively large, neglecting the effects of the cross terms between velocity fluctuations and local dispersivities, as done in some previous studies, can produce noticeable errors, and a rigorous treatment of the dispersion terms becomes more appropriate.

A Comparison of Traditional, Step-Path, and Geostatistical Techniques in the Stability Analysis of a Large Open Pit

NASA Astrophysics Data System (ADS)

Mayer, J. M.; Stead, D.

2017-04-01

With the increased drive towards deeper and more complex mine designs, geotechnical engineers are often forced to reconsider traditional deterministic design techniques in favour of probabilistic methods. These alternative techniques allow for the direct quantification of uncertainties within a risk and/or decision analysis framework. However, conventional probabilistic practices typically discretize geological materials into discrete, homogeneous domains, with attributes defined by spatially constant random variables, despite the fact that geological media display inherent heterogeneous spatial characteristics. This research directly simulates this phenomenon using a geostatistical approach, known as sequential Gaussian simulation. The method utilizes the variogram which imposes a degree of controlled spatial heterogeneity on the system. Simulations are constrained using data from the Ok Tedi mine site in Papua New Guinea and designed to randomly vary the geological strength index and uniaxial compressive strength using Monte Carlo techniques. Results suggest that conventional probabilistic techniques have a fundamental limitation compared to geostatistical approaches, as they fail to account for the spatial dependencies inherent to geotechnical datasets. This can result in erroneous model predictions, which are overly conservative when compared to the geostatistical results.

An integrated simulator of structure and anisotropic flow in gas diffusion layers with hydrophobic additives

NASA Astrophysics Data System (ADS)

Burganos, Vasilis N.; Skouras, Eugene D.; Kalarakis, Alexandros N.

2017-10-01

The lattice-Boltzmann (LB) method is used in this work to reproduce the controlled addition of binder and hydrophobicity-promoting agents, like polytetrafluoroethylene (PTFE), into gas diffusion layers (GDLs) and to predict flow permeabilities in the through- and in-plane directions. The present simulator manages to reproduce spreading of binder and hydrophobic additives, sequentially, into the neat fibrous layer using a two-phase flow model. Gas flow simulation is achieved by the same code, sidestepping the need for a post-processing flow code and avoiding the usual input/output and data interface problems that arise in other techniques. Compression effects on flow anisotropy of the impregnated GDL are also studied. The permeability predictions for different compression levels and for different binder or PTFE loadings are found to compare well with experimental data for commercial GDL products and with computational fluid dynamics (CFD) predictions. Alternatively, the PTFE-impregnated structure is reproduced from Scanning Electron Microscopy (SEM) images using an independent, purely geometrical approach. A comparison of the two approaches is made regarding their adequacy to reproduce correctly the main structural features of the GDL and to predict anisotropic flow permeabilities at different volume fractions of binder and hydrophobic additives.

Improved coverage of cDNA-AFLP by sequential digestion of immobilized cDNA.

PubMed

Weiberg, Arne; Pöhler, Dirk; Morgenstern, Burkhard; Karlovsky, Petr

2008-10-13

cDNA-AFLP is a transcriptomics technique which does not require prior sequence information and can therefore be used as a gene discovery tool. The method is based on selective amplification of cDNA fragments generated by restriction endonucleases, electrophoretic separation of the products and comparison of the band patterns between treated samples and controls. Unequal distribution of restriction sites used to generate cDNA fragments negatively affects the performance of cDNA-AFLP. Some transcripts are represented by more than one fragment while other escape detection, causing redundancy and reducing the coverage of the analysis, respectively. With the goal of improving the coverage of cDNA-AFLP without increasing its redundancy, we designed a modified cDNA-AFLP protocol. Immobilized cDNA is sequentially digested with several restriction endonucleases and the released DNA fragments are collected in mutually exclusive pools. To investigate the performance of the protocol, software tool MECS (Multiple Enzyme cDNA-AFLP Simulation) was written in Perl. cDNA-AFLP protocols described in the literature and the new sequential digestion protocol were simulated on sets of cDNA sequences from mouse, human and Arabidopsis thaliana. The redundancy and coverage, the total number of PCR reactions, and the average fragment length were calculated for each protocol and cDNA set. Simulation revealed that sequential digestion of immobilized cDNA followed by the partitioning of released fragments into mutually exclusive pools outperformed other cDNA-AFLP protocols in terms of coverage, redundancy, fragment length, and the total number of PCRs. Primers generating 30 to 70 amplicons per PCR provided the highest fraction of electrophoretically distinguishable fragments suitable for normalization. For A. thaliana, human and mice transcriptome, the use of two marking enzymes and three sequentially applied releasing enzymes for each of the marking enzymes is recommended.

Poster error probability in the Mu-11 Sequential Ranging System

NASA Technical Reports Server (NTRS)

Coyle, C. W.

1981-01-01

An expression is derived for the posterior error probability in the Mu-2 Sequential Ranging System. An algorithm is developed which closely bounds the exact answer and can be implemented in the machine software. A computer simulation is provided to illustrate the improved level of confidence in a ranging acquisition using this figure of merit as compared to that using only the prior probabilities. In a simulation of 20,000 acquisitions with an experimentally determined threshold setting, the algorithm detected 90% of the actual errors and made false indication of errors on 0.2% of the acquisitions.

Biocellion: accelerating computer simulation of multicellular biological system models.

PubMed

Kang, Seunghwa; Kahan, Simon; McDermott, Jason; Flann, Nicholas; Shmulevich, Ilya

2014-11-01

Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming. We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biological system models, Biocellion asks users to provide their model specifics by filling the function body of pre-defined model routines. Using Biocellion, modelers without parallel computing expertise can efficiently exploit parallel computers with less effort than writing sequential programs from scratch. We simulate cell sorting, microbial patterning and a bacterial system in soil aggregate as case studies. Biocellion runs on x86 compatible systems with the 64 bit Linux operating system and is freely available for academic use. Visit http://biocellion.com for additional information. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A Pocock Approach to Sequential Meta-Analysis of Clinical Trials

ERIC Educational Resources Information Center

Shuster, Jonathan J.; Neu, Josef

2013-01-01

Three recent papers have provided sequential methods for meta-analysis of two-treatment randomized clinical trials. This paper provides an alternate approach that has three desirable features. First, when carried out prospectively (i.e., we only have the results up to the time of our current analysis), we do not require knowledge of the…

Sequential Organization and Room Reverberation for Speech Segregation

DTIC Science & Technology

2012-02-28

we have proposed two algorithms for sequential organization, an unsupervised clustering algorithm applicable to monaural recordings and a binaural ...algorithm that integrates monaural and binaural analyses. In addition, we have conducted speech intelligibility tests that Firmly establish the...comprehensive version is currently under review for journal publication. A binaural approach in room reverberation Most existing approaches to binaural or

Comparison of DNA testing strategies in monitoring human papillomavirus infection prevalence through simulation.

PubMed

Lin, Carol Y; Li, Ling

2016-11-07

HPV DNA diagnostic tests for epidemiology monitoring (research purpose) or cervical cancer screening (clinical purpose) have often been considered separately. Women with positive Linear Array (LA) polymerase chain reaction (PCR) research test results typically are neither informed nor referred for colposcopy. Recently, a sequential testing by using Hybrid Capture 2 (HC2) HPV clinical test as a triage before genotype by LA has been adopted for monitoring HPV infections. Also, HC2 has been reported as a more feasible screening approach for cervical cancer in low-resource countries. Thus, knowing the performance of testing strategies incorporating HPV clinical test (i.e., HC2-only or using HC2 as a triage before genotype by LA) compared with LA-only testing in measuring HPV prevalence will be informative for public health practice. We conducted a Monte Carlo simulation study. Data were generated using mathematical algorithms. We designated the reported HPV infection prevalence in the U.S. and Latin America as the "true" underlying type-specific HPV prevalence. Analytical sensitivity of HC2 for detecting 14 high-risk (oncogenic) types was considered to be less than LA. Estimated-to-true prevalence ratios and percentage reductions were calculated. When the "true" HPV prevalence was designated as the reported prevalence in the U.S., with LA genotyping sensitivity and specificity of (0.95, 0.95), estimated-to-true prevalence ratios of 14 high-risk types were 2.132, 1.056, 0.958 for LA-only, HC2-only, and sequential testing, respectively. Estimated-to-true prevalence ratios of two vaccine-associated high-risk types were 2.359 and 1.063 for LA-only and sequential testing, respectively. When designated type-specific prevalence of HPV16 and 18 were reduced by 50 %, using either LA-only or sequential testing, prevalence estimates were reduced by 18 %. Estimated-to-true HPV infection prevalence ratios using LA-only testing strategy are generally higher than using HC2-only or using HC2 as a triage before genotype by LA. HPV clinical testing can be incorporated to monitor HPV prevalence or vaccine effectiveness. Caution is needed when comparing apparent prevalence from different testing strategies.

Sequential Tests of Multiple Hypotheses Controlling Type I and II Familywise Error Rates

PubMed Central

Bartroff, Jay; Song, Jinlin

2014-01-01

This paper addresses the following general scenario: A scientist wishes to perform a battery of experiments, each generating a sequential stream of data, to investigate some phenomenon. The scientist would like to control the overall error rate in order to draw statistically-valid conclusions from each experiment, while being as efficient as possible. The between-stream data may differ in distribution and dimension but also may be highly correlated, even duplicated exactly in some cases. Treating each experiment as a hypothesis test and adopting the familywise error rate (FWER) metric, we give a procedure that sequentially tests each hypothesis while controlling both the type I and II FWERs regardless of the between-stream correlation, and only requires arbitrary sequential test statistics that control the error rates for a given stream in isolation. The proposed procedure, which we call the sequential Holm procedure because of its inspiration from Holm’s (1979) seminal fixed-sample procedure, shows simultaneous savings in expected sample size and less conservative error control relative to fixed sample, sequential Bonferroni, and other recently proposed sequential procedures in a simulation study. PMID:25092948

Causal Models for Mediation Analysis: An Introduction to Structural Mean Models.

PubMed

Zheng, Cheng; Atkins, David C; Zhou, Xiao-Hua; Rhew, Isaac C

2015-01-01

Mediation analyses are critical to understanding why behavioral interventions work. To yield a causal interpretation, common mediation approaches must make an assumption of "sequential ignorability." The current article describes an alternative approach to causal mediation called structural mean models (SMMs). A specific SMM called a rank-preserving model (RPM) is introduced in the context of an applied example. Particular attention is given to the assumptions of both approaches to mediation. Applying both mediation approaches to the college student drinking data yield notable differences in the magnitude of effects. Simulated examples reveal instances in which the traditional approach can yield strongly biased results, whereas the RPM approach remains unbiased in these cases. At the same time, the RPM approach has its own assumptions that must be met for correct inference, such as the existence of a covariate that strongly moderates the effect of the intervention on the mediator and no unmeasured confounders that also serve as a moderator of the effect of the intervention or the mediator on the outcome. The RPM approach to mediation offers an alternative way to perform mediation analysis when there may be unmeasured confounders.

Kriging for Simulation Metamodeling: Experimental Design, Reduced Rank Kriging, and Omni-Rank Kriging

NASA Astrophysics Data System (ADS)

Hosking, Michael Robert

This dissertation improves an analyst's use of simulation by offering improvements in the utilization of kriging metamodels. There are three main contributions. First an analysis is performed of what comprises good experimental designs for practical (non-toy) problems when using a kriging metamodel. Second is an explanation and demonstration of how reduced rank decompositions can improve the performance of kriging, now referred to as reduced rank kriging. Third is the development of an extension of reduced rank kriging which solves an open question regarding the usage of reduced rank kriging in practice. This extension is called omni-rank kriging. Finally these results are demonstrated on two case studies. The first contribution focuses on experimental design. Sequential designs are generally known to be more efficient than "one shot" designs. However, sequential designs require some sort of pilot design from which the sequential stage can be based. We seek to find good initial designs for these pilot studies, as well as designs which will be effective if there is no following sequential stage. We test a wide variety of designs over a small set of test-bed problems. Our findings indicate that analysts should take advantage of any prior information they have about their problem's shape and/or their goals in metamodeling. In the event of a total lack of information we find that Latin hypercube designs are robust default choices. Our work is most distinguished by its attention to the higher levels of dimensionality. The second contribution introduces and explains an alternative method for kriging when there is noise in the data, which we call reduced rank kriging. Reduced rank kriging is based on using a reduced rank decomposition which artificially smoothes the kriging weights similar to a nugget effect. Our primary focus will be showing how the reduced rank decomposition propagates through kriging empirically. In addition, we show further evidence for our explanation through tests of reduced rank kriging's performance over different situations. In total, reduced rank kriging is a useful tool for simulation metamodeling. For the third contribution we will answer the question of how to find the best rank for reduced rank kriging. We do this by creating an alternative method which does not need to search for a particular rank. Instead it uses all potential ranks; we call this approach omnirank kriging. This modification realizes the potential gains from reduced rank kriging and provides a workable methodology for simulation metamodeling. Finally, we will demonstrate the use and value of these developments on two case studies, a clinic operation problem and a location problem. These cases will validate the value of this research. Simulation metamodeling always attempts to extract maximum information from limited data. Each one of these contributions will allow analysts to make better use of their constrained computational budgets.

Diagnostic value of tendon thickness and structure in the sonographic diagnosis of supraspinatus tendinopathy: room for a two-step approach.

PubMed

Arend, Carlos Frederico; Arend, Ana Amalia; da Silva, Tiago Rodrigues

2014-06-01

The aim of our study was to systematically compare different methodologies to establish an evidence-based approach based on tendon thickness and structure for sonographic diagnosis of supraspinatus tendinopathy when compared to MRI. US was obtained from 164 symptomatic patients with supraspinatus tendinopathy detected at MRI and 42 asymptomatic controls with normal MRI. Diagnostic yield was calculated for either maximal supraspinatus tendon thickness (MSTT) and tendon structure as isolated criteria and using different combinations of parallel and sequential testing at US. Chi-squared tests were performed to assess sensitivity, specificity, and accuracy of different diagnostic approaches. Mean MSTT was 6.68 mm in symptomatic patients and 5.61 mm in asymptomatic controls (P<.05). When used as an isolated criterion, MSTT>6.0mm provided best results for accuracy (93.7%) when compared to other measurements of tendon thickness. Also as an isolated criterion, abnormal tendon structure (ATS) yielded 93.2% accuracy for diagnosis. The best overall yield was obtained by both parallel and sequential testing using either MSTT>6.0mm or ATS as diagnostic criteria at no particular order, which provided 99.0% accuracy, 100% sensitivity, and 95.2% specificity. Among these parallel and sequential tests that provided best overall yield, additional analysis revealed that sequential testing first evaluating tendon structure required assessment of 258 criteria (vs. 261 for sequential testing first evaluating tendon thickness and 412 for parallel testing) and demanded a mean of 16.1s to assess diagnostic criteria and reach the diagnosis (vs. 43.3s for sequential testing first evaluating tendon thickness and 47.4s for parallel testing). We found that using either MSTT>6.0mm or ATS as diagnostic criteria for both parallel and sequential testing provides the best overall yield for sonographic diagnosis of supraspinatus tendinopathy when compared to MRI. Among these strategies, a two-step sequential approach first assessing tendon structure was advantageous because it required a lower number of criteria to be assessed and demanded less time to assess diagnostic criteria and reach the diagnosis. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Changes in thermo-tolerance and survival under simulated gastrointestinal conditions of Salmonella Enteritidis PT4 and Salmonella Typhimurium PT4 in chicken breast meat after exposure to sequential stresses.

PubMed

Melo, Adma Nadja Ferreira de; Souza, Geany Targino de; Schaffner, Donald; Oliveira, Tereza C Moreira de; Maciel, Janeeyre Ferreira; Souza, Evandro Leite de; Magnani, Marciane

2017-06-19

This study assessed changes in thermo-tolerance and capability to survive to simulated gastrointestinal conditions of Salmonella Enteritidis PT4 and Salmonella Typhimurium PT4 inoculated in chicken breast meat following exposure to stresses (cold, acid and osmotic) commonly imposed during food processing. The effects of the stress imposed by exposure to oregano (Origanum vulgare L.) essential oil (OVEO) on thermo-tolerance were also assessed. After exposure to cold stress (5°C for 5h) in chicken breast meat the test strains were sequentially exposed to the different stressing substances (lactic acid, NaCl or OVEO) at sub-lethal amounts, which were defined considering previously determined minimum inhibitory concentrations, and finally to thermal treatment (55°C for 30min). Resistant cells from distinct sequential treatments were exposed to simulated gastrointestinal conditions. The exposure to cold stress did not result in increased tolerance to acid stress (lactic acid: 5 and 2.5μL/g) for both strains. Cells of S. Typhimurium PT4 and S. Enteritidis PT4 previously exposed to acid stress showed higher (p<0.05) tolerance to osmotic stress (NaCl: 75 or 37.5mg/g) compared to non-acid-exposed cells. Exposure to osmotic stress without previous exposure to acid stress caused a salt-concentration dependent decrease in counts for both strains. Exposure to OVEO (1.25 and 0.62μL/g) decreased the acid and osmotic tolerance of both S. Enteritidis PT4 and S. Typhimurium PT4. Sequential exposure to acid and osmotic stress conditions after cold exposure increased (p<0.05) the thermo-tolerance in both strains. The cells that survived the sequential stress exposure (resistant) showed higher tolerance (p<0.05) to acidic conditions during continuous exposure (182min) to simulated gastrointestinal conditions. Resistant cells of S. Enteritidis PT4 and S. Typhimurium PT4 showed higher survival rates (p<0.05) than control cells at the end of the in vitro digestion. These results show that sequential exposure to multiple sub-lethal stresses may increase the thermo-tolerance and enhance the survival under gastrointestinal conditions of S. Enteritidis PT4 and S. Typhimurium PT4. Copyright © 2017 Elsevier B.V. All rights reserved.

Bridging the gap between computation and clinical biology: validation of cable theory in humans

PubMed Central

Finlay, Malcolm C.; Xu, Lei; Taggart, Peter; Hanson, Ben; Lambiase, Pier D.

2013-01-01

Introduction: Computerized simulations of cardiac activity have significantly contributed to our understanding of cardiac electrophysiology, but techniques of simulations based on patient-acquired data remain in their infancy. We sought to integrate data acquired from human electrophysiological studies into patient-specific models, and validated this approach by testing whether electrophysiological responses to sequential premature stimuli could be predicted in a quantitatively accurate manner. Methods: Eleven patients with structurally normal hearts underwent electrophysiological studies. Semi-automated analysis was used to reconstruct activation and repolarization dynamics for each electrode. This S2 extrastimuli data was used to inform individualized models of cardiac conduction, including a novel derivation of conduction velocity restitution. Activation dynamics of multiple premature extrastimuli were then predicted from this model and compared against measured patient data as well as data derived from the ten-Tusscher cell-ionic model. Results: Activation dynamics following a premature S3 were significantly different from those after an S2. Patient specific models demonstrated accurate prediction of the S3 activation wave, (Pearson's R2 = 0.90, median error 4%). Examination of the modeled conduction dynamics allowed inferences into the spatial dispersion of activation delay. Further validation was performed against data from the ten-Tusscher cell-ionic model, with our model accurately recapitulating predictions of repolarization times (R2 = 0.99). Conclusions: Simulations based on clinically acquired data can be used to successfully predict complex activation patterns following sequential extrastimuli. Such modeling techniques may be useful as a method of incorporation of clinical data into predictive models. PMID:24027527

Filter design for cancellation of baseline-fluctuation in needle EMG recordings.

PubMed

Rodríguez-Carreño, I; Malanda-Trigueros, A; Gila-Useros, L; Navallas-Irujo, J; Rodríguez-Falces, J

2006-01-01

Appropriate cancellation of the baseline fluctuation (BLF) is an important issue when recording EMG signals as it may degrade signal quality and distort qualitative and quantitative analysis. We present a novel filter-design approach for automatic cancellation of the BLF based on several signal processing techniques used sequentially. The methodology is to estimate the spectral content of the BLF, and then to use this estimation to design a high-pass FIR filter that cancel the BLF present in the signal. Two merit figures are devised for measuring the degree of BLF present in an EMG record. These figures are used to compare our method with the conventional approach, which naively considers the baseline course to be of constant (without any fluctuation) potential shift. Applications of the technique on real and simulated EMG signals show the superior performance of our approach in terms of both visual inspection and the merit figures.

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

PubMed

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.

A Novel Approach to Realize of All Optical Frequency Encoded Dibit Based XOR and XNOR Logic Gates Using Optical Switches with Simulated Verification

NASA Astrophysics Data System (ADS)

Ghosh, B.; Hazra, S.; Haldar, N.; Roy, D.; Patra, S. N.; Swarnakar, J.; Sarkar, P. P.; Mukhopadhyay, S.

2018-03-01

Since last few decades optics has already proved its strong potentiality for conducting parallel logic, arithmetic and algebraic operations due to its super-fast speed in communication and computation. So many different logical and sequential operations using all optical frequency encoding technique have been proposed by several authors. Here, we have keened out all optical dibit representation technique, which has the advantages of high speed operation as well as reducing the bit error problem. Exploiting this phenomenon, we have proposed all optical frequency encoded dibit based XOR and XNOR logic gates using the optical switches like add/drop multiplexer (ADM) and reflected semiconductor optical amplifier (RSOA). Also the operations of these gates have been verified through proper simulation using MATLAB (R2008a).

3D Representative Volume Element Reconstruction of Fiber Composites via Orientation Tensor and Substructure Features

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

Li, Yi; Chen, Wei; Xu, Hongyi

To provide a seamless integration of manufacturing processing simulation and fiber microstructure modeling, two new stochastic 3D microstructure reconstruction methods are proposed for two types of random fiber composites: random short fiber composites, and Sheet Molding Compounds (SMC) chopped fiber composites. A Random Sequential Adsorption (RSA) algorithm is first developed to embed statistical orientation information into 3D RVE reconstruction of random short fiber composites. For the SMC composites, an optimized Voronoi diagram based approach is developed for capturing the substructure features of SMC chopped fiber composites. The proposed methods are distinguished from other reconstruction works by providing a way ofmore » integrating statistical information (fiber orientation tensor) obtained from material processing simulation, as well as capturing the multiscale substructures of the SMC composites.« less

Hierarchical Chunking of Sequential Memory on Neuromorphic Architecture with Reduced Synaptic Plasticity

PubMed Central

Li, Guoqi; Deng, Lei; Wang, Dong; Wang, Wei; Zeng, Fei; Zhang, Ziyang; Li, Huanglong; Song, Sen; Pei, Jing; Shi, Luping

2016-01-01

Chunking refers to a phenomenon whereby individuals group items together when performing a memory task to improve the performance of sequential memory. In this work, we build a bio-plausible hierarchical chunking of sequential memory (HCSM) model to explain why such improvement happens. We address this issue by linking hierarchical chunking with synaptic plasticity and neuromorphic engineering. We uncover that a chunking mechanism reduces the requirements of synaptic plasticity since it allows applying synapses with narrow dynamic range and low precision to perform a memory task. We validate a hardware version of the model through simulation, based on measured memristor behavior with narrow dynamic range in neuromorphic circuits, which reveals how chunking works and what role it plays in encoding sequential memory. Our work deepens the understanding of sequential memory and enables incorporating it for the investigation of the brain-inspired computing on neuromorphic architecture. PMID:28066223

Recent advances in lossless coding techniques

NASA Astrophysics Data System (ADS)

Yovanof, Gregory S.

Current lossless techniques are reviewed with reference to both sequential data files and still images. Two major groups of sequential algorithms, dictionary and statistical techniques, are discussed. In particular, attention is given to Lempel-Ziv coding, Huffman coding, and arithmewtic coding. The subject of lossless compression of imagery is briefly discussed. Finally, examples of practical implementations of lossless algorithms and some simulation results are given.

Networked Workstations and Parallel Processing Utilizing Functional Languages

DTIC Science & Technology

1993-03-01

program . This frees the programmer to concentrate on what the program is to do, not how the program is...traditional ’von Neumann’ architecture uses a timer based (e.g., the program counter), sequentially pro- grammed, single processor approach to problem...traditional ’von Neumann’ architecture uses a timer based (e.g., the program counter), sequentially programmed , single processor approach to

Analyzing multicomponent receptive fields from neural responses to natural stimuli

PubMed Central

Rowekamp, Ryan; Sharpee, Tatyana O

2011-01-01

The challenge of building increasingly better models of neural responses to natural stimuli is to accurately estimate the multiple stimulus features that may jointly affect the neural spike probability. The selectivity for combinations of features is thought to be crucial for achieving classical properties of neural responses such as contrast invariance. The joint search for these multiple stimulus features is difficult because estimating spike probability as a multidimensional function of stimulus projections onto candidate relevant dimensions is subject to the curse of dimensionality. An attractive alternative is to search for relevant dimensions sequentially, as in projection pursuit regression. Here we demonstrate using analytic arguments and simulations of model cells that different types of sequential search strategies exhibit systematic biases when used with natural stimuli. Simulations show that joint optimization is feasible for up to three dimensions with current algorithms. When applied to the responses of V1 neurons to natural scenes, models based on three jointly optimized dimensions had better predictive power in a majority of cases compared to dimensions optimized sequentially, with different sequential methods yielding comparable results. Thus, although the curse of dimensionality remains, at least several relevant dimensions can be estimated by joint information maximization. PMID:21780916

Augmented design and analysis of computer experiments: a novel tolerance embedded global optimization approach applied to SWIR hyperspectral illumination design.

PubMed

Keresztes, Janos C; John Koshel, R; D'huys, Karlien; De Ketelaere, Bart; Audenaert, Jan; Goos, Peter; Saeys, Wouter

2016-12-26

A novel meta-heuristic approach for minimizing nonlinear constrained problems is proposed, which offers tolerance information during the search for the global optimum. The method is based on the concept of design and analysis of computer experiments combined with a novel two phase design augmentation (DACEDA), which models the entire merit space using a Gaussian process, with iteratively increased resolution around the optimum. The algorithm is introduced through a series of cases studies with increasing complexity for optimizing uniformity of a short-wave infrared (SWIR) hyperspectral imaging (HSI) illumination system (IS). The method is first demonstrated for a two-dimensional problem consisting of the positioning of analytical isotropic point sources. The method is further applied to two-dimensional (2D) and five-dimensional (5D) SWIR HSI IS versions using close- and far-field measured source models applied within the non-sequential ray-tracing software FRED, including inherent stochastic noise. The proposed method is compared to other heuristic approaches such as simplex and simulated annealing (SA). It is shown that DACEDA converges towards a minimum with 1 % improvement compared to simplex and SA, and more importantly requiring only half the number of simulations. Finally, a concurrent tolerance analysis is done within DACEDA for to the five-dimensional case such that further simulations are not required.

A Rejection Principle for Sequential Tests of Multiple Hypotheses Controlling Familywise Error Rates

PubMed Central

BARTROFF, JAY; SONG, JINLIN

2015-01-01

We present a unifying approach to multiple testing procedures for sequential (or streaming) data by giving sufficient conditions for a sequential multiple testing procedure to control the familywise error rate (FWER). Together we call these conditions a “rejection principle for sequential tests,” which we then apply to some existing sequential multiple testing procedures to give simplified understanding of their FWER control. Next the principle is applied to derive two new sequential multiple testing procedures with provable FWER control, one for testing hypotheses in order and another for closed testing. Examples of these new procedures are given by applying them to a chromosome aberration data set and to finding the maximum safe dose of a treatment. PMID:26985125

Program For Parallel Discrete-Event Simulation

NASA Technical Reports Server (NTRS)

Beckman, Brian C.; Blume, Leo R.; Geiselman, John S.; Presley, Matthew T.; Wedel, John J., Jr.; Bellenot, Steven F.; Diloreto, Michael; Hontalas, Philip J.; Reiher, Peter L.; Weiland, Frederick P.

1991-01-01

User does not have to add any special logic to aid in synchronization. Time Warp Operating System (TWOS) computer program is special-purpose operating system designed to support parallel discrete-event simulation. Complete implementation of Time Warp mechanism. Supports only simulations and other computations designed for virtual time. Time Warp Simulator (TWSIM) subdirectory contains sequential simulation engine interface-compatible with TWOS. TWOS and TWSIM written in, and support simulations in, C programming language.

Dry minor mergers and size evolution of high-z compact massive early-type galaxies

NASA Astrophysics Data System (ADS)

Oogi, Taira; Habe, Asao

2013-01-01

Recent observations show evidence that high-z (z ˜ 2-3) early-type galaxies (ETGs) are more compact than those with comparable mass at z ˜ 0. Such size evolution is most likely explained by the `dry merger sceanario'. However, previous studies based on this scenario cannot consistently explain the properties of both high-z compact massive ETGs and local ETGs. We investigate the effect of multiple sequential dry minor mergers on the size evolution of compact massive ETGs. From an analysis of the Millennium Simulation Data Base, we show that such minor (stellar mass ratio M2/M1 < 1/4) mergers are extremely common during hierarchical structure formation. We perform N-body simulations of sequential minor mergers with parabolic and head-on orbits, including a dark matter component and a stellar component. Typical mass ratios of these minor mergers are 1/20 < M2/M1 ≤q 1/10. We show that sequential minor mergers of compact satellite galaxies are the most efficient at promoting size growth and decreasing the velocity dispersion of compact massive ETGs in our simulations. The change of stellar size and density of the merger remnants is consistent with recent observations. Furthermore, we construct the merger histories of candidates for high-z compact massive ETGs using the Millennium Simulation Data Base and estimate the size growth of the galaxies through the dry minor merger scenario. We can reproduce the mean size growth factor between z = 2 and z = 0, assuming the most efficient size growth obtained during sequential minor mergers in our simulations. However, we note that our numerical result is only valid for merger histories with typical mass ratios between 1/20 and 1/10 with parabolic and head-on orbits and that our most efficient size-growth efficiency is likely an upper limit.

Sequential structural damage diagnosis algorithm using a change point detection method

NASA Astrophysics Data System (ADS)

Noh, H.; Rajagopal, R.; Kiremidjian, A. S.

2013-11-01

This paper introduces a damage diagnosis algorithm for civil structures that uses a sequential change point detection method. The general change point detection method uses the known pre- and post-damage feature distributions to perform a sequential hypothesis test. In practice, however, the post-damage distribution is unlikely to be known a priori, unless we are looking for a known specific type of damage. Therefore, we introduce an additional algorithm that estimates and updates this distribution as data are collected using the maximum likelihood and the Bayesian methods. We also applied an approximate method to reduce the computation load and memory requirement associated with the estimation. The algorithm is validated using a set of experimental data collected from a four-story steel special moment-resisting frame and multiple sets of simulated data. Various features of different dimensions have been explored, and the algorithm was able to identify damage, particularly when it uses multidimensional damage sensitive features and lower false alarm rates, with a known post-damage feature distribution. For unknown feature distribution cases, the post-damage distribution was consistently estimated and the detection delays were only a few time steps longer than the delays from the general method that assumes we know the post-damage feature distribution. We confirmed that the Bayesian method is particularly efficient in declaring damage with minimal memory requirement, but the maximum likelihood method provides an insightful heuristic approach.

Damage diagnosis algorithm using a sequential change point detection method with an unknown distribution for damage

NASA Astrophysics Data System (ADS)

Noh, Hae Young; Rajagopal, Ram; Kiremidjian, Anne S.

2012-04-01

This paper introduces a damage diagnosis algorithm for civil structures that uses a sequential change point detection method for the cases where the post-damage feature distribution is unknown a priori. This algorithm extracts features from structural vibration data using time-series analysis and then declares damage using the change point detection method. The change point detection method asymptotically minimizes detection delay for a given false alarm rate. The conventional method uses the known pre- and post-damage feature distributions to perform a sequential hypothesis test. In practice, however, the post-damage distribution is unlikely to be known a priori. Therefore, our algorithm estimates and updates this distribution as data are collected using the maximum likelihood and the Bayesian methods. We also applied an approximate method to reduce the computation load and memory requirement associated with the estimation. The algorithm is validated using multiple sets of simulated data and a set of experimental data collected from a four-story steel special moment-resisting frame. Our algorithm was able to estimate the post-damage distribution consistently and resulted in detection delays only a few seconds longer than the delays from the conventional method that assumes we know the post-damage feature distribution. We confirmed that the Bayesian method is particularly efficient in declaring damage with minimal memory requirement, but the maximum likelihood method provides an insightful heuristic approach.

The use of sequential indicator simulation to characterize geostatistical uncertainty; Yucca Mountain Site Characterization Project

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

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 ismore » recommended that users of SIS conduct validation studies for the technique on their particular regions of interest before accepting the output uncertainty bounds.« less

Sensitivity Analysis in Sequential Decision Models.

PubMed

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.

Least-squares sequential parameter and state estimation for large space structures

NASA Technical Reports Server (NTRS)

Thau, F. E.; Eliazov, T.; Montgomery, R. C.

1982-01-01

This paper presents the formulation of simultaneous state and parameter estimation problems for flexible structures in terms of least-squares minimization problems. The approach combines an on-line order determination algorithm, with least-squares algorithms for finding estimates of modal approximation functions, modal amplitudes, and modal parameters. The approach combines previous results on separable nonlinear least squares estimation with a regression analysis formulation of the state estimation problem. The technique makes use of sequential Householder transformations. This allows for sequential accumulation of matrices required during the identification process. The technique is used to identify the modal prameters of a flexible beam.

A hybrid fuzzy logic/constraint satisfaction problem approach to automatic decision making in simulation game models.

PubMed

Braathen, Sverre; Sendstad, Ole Jakob

2004-08-01

Possible techniques for representing automatic decision-making behavior approximating human experts in complex simulation model experiments are of interest. Here, fuzzy logic (FL) and constraint satisfaction problem (CSP) methods are applied in a hybrid design of automatic decision making in simulation game models. The decision processes of a military headquarters are used as a model for the FL/CSP decision agents choice of variables and rulebases. The hybrid decision agent design is applied in two different types of simulation games to test the general applicability of the design. The first application is a two-sided zero-sum sequential resource allocation game with imperfect information interpreted as an air campaign game. The second example is a network flow stochastic board game designed to capture important aspects of land manoeuvre operations. The proposed design is shown to perform well also in this complex game with a very large (billionsize) action set. Training of the automatic FL/CSP decision agents against selected performance measures is also shown and results are presented together with directions for future research.

An Investigation of University Students' Collaborative Inquiry Learning Behaviors in an Augmented Reality Simulation and a Traditional Simulation

ERIC Educational Resources Information Center

Wang, Hung-Yuan; Duh, Henry Been-Lirn; Li, Nai; Lin, Tzung-Jin; Tsai, Chin-Chung

2014-01-01

The purpose of this study is to investigate and compare students' collaborative inquiry learning behaviors and their behavior patterns in an augmented reality (AR) simulation system and a traditional 2D simulation system. Their inquiry and discussion processes were analyzed by content analysis and lag sequential analysis (LSA). Forty…

Comparison of Statistical Approaches for Dealing With Immortal Time Bias in Drug Effectiveness Studies.

PubMed

Karim, Mohammad Ehsanul; Gustafson, Paul; Petkau, John; Tremlett, Helen

2016-08-15

In time-to-event analyses of observational studies of drug effectiveness, incorrect handling of the period between cohort entry and first treatment exposure during follow-up may result in immortal time bias. This bias can be eliminated by acknowledging a change in treatment exposure status with time-dependent analyses, such as fitting a time-dependent Cox model. The prescription time-distribution matching (PTDM) method has been proposed as a simpler approach for controlling immortal time bias. Using simulation studies and theoretical quantification of bias, we compared the performance of the PTDM approach with that of the time-dependent Cox model in the presence of immortal time. Both assessments revealed that the PTDM approach did not adequately address immortal time bias. Based on our simulation results, another recently proposed observational data analysis technique, the sequential Cox approach, was found to be more useful than the PTDM approach (Cox: bias = -0.002, mean squared error = 0.025; PTDM: bias = -1.411, mean squared error = 2.011). We applied these approaches to investigate the association of β-interferon treatment with delaying disability progression in a multiple sclerosis cohort in British Columbia, Canada (Long-Term Benefits and Adverse Effects of Beta-Interferon for Multiple Sclerosis (BeAMS) Study, 1995-2008). © The Author 2016. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A study of the application of differential techniques to the global positioning system for a helicopter precision approach

NASA Technical Reports Server (NTRS)

Mccall, D. L.

1984-01-01

The results of a simulation study to define the functional characteristics of a airborne and ground reference GPS receiver for use in a Differential GPS system are doumented. The operations of a variety of receiver types (sequential-single channel, continuous multi-channel, etc.) are evaluated for a typical civil helicopter mission scenario. The math model of each receiver type incorporated representative system errors including intentional degradation. The results include the discussion of the receiver relative performance, the spatial correlative properties of individual range error sources, and the navigation algorithm used to smooth the position data.

Algorithms for Stellar Perturbation Computations on Oort Cloud Comets

NASA Astrophysics Data System (ADS)

Rickman, Hans; Fouchard, Marc; Valsecchi, Giovanni B.; Froeschlé, Christiane

2005-12-01

We investigate different approximate methods of computing the perturbations on the orbits of Oort cloud comets caused by passing stars, by checking them against an accurate numerical integration using Everhart’s RA15 code. The scenario under study is the one relevant for long-term simulations of the cloud’s response to a predefined set of stellar passages. Our sample of stellar encounters simulates those experienced by the Solar System currently, but extrapolated over a time of 1010 years. We measure the errors of perihelion distance perturbations for high-eccentricity orbits introduced by several estimators including the classical impulse approximation and Dybczyński’s (1994, Celest. Mech. Dynam. Astron. 58, 1330 1338) method and we study how they depend on the encounter parameters (approach distance and relative velocity). We introduce a sequential variant of Dybczyński’s approach, cutting the encounter into several steps whereby the heliocentric motion of the comet is taken into account. For the scenario at hand this is found to offer an efficient means to obtain accurate results for practically any domain of the parameter space.

Toward the design of alkynylimidazole fluorophores: computational and experimental characterization of spectroscopic features in solution and in poly(methyl methacrylate).

PubMed

Barone, Vincenzo; Bellina, Fabio; Biczysko, Malgorzata; Bloino, Julien; Fornaro, Teresa; Latouche, Camille; Lessi, Marco; Marianetti, Giulia; Minei, Pierpaolo; Panattoni, Alessandro; Pucci, Andrea

2015-10-28

The possibilities offered by organic fluorophores in the preparation of advanced plastic materials have been increased by designing novel alkynylimidazole dyes, featuring different push and pull groups. This new family of fluorescent dyes was synthesized by means of a one-pot sequential bromination-alkynylation of the heteroaromatic core, and their optical properties were investigated in tetrahydrofuran and in poly(methyl methacrylate). An efficient in silico pre-screening scheme was devised as consisting of a step-by-step procedure employing computational methodologies by simulation of electronic spectra within simple vertical energy and more sophisticated vibronic approaches. Such an approach was also extended to efficiently simulate one-photon absorption and emission spectra of the dyes in the polymer environment for their potential application in luminescent solar concentrators. Besides the specific applications of this novel material, the integration of computational and experimental techniques reported here provides an efficient protocol that can be applied to make a selection among similar dye candidates, which constitute the essential responsive part of those fluorescent plastic materials.

An Extension of a Parallel-Distributed Processing Framework of Reading Aloud in Japanese: Human Nonword Reading Accuracy Does Not Require a Sequential Mechanism

ERIC Educational Resources Information Center

Ikeda, Kenji; Ueno, Taiji; Ito, Yuichi; Kitagami, Shinji; Kawaguchi, Jun

2017-01-01

Humans can pronounce a nonword (e.g., rint). Some researchers have interpreted this behavior as requiring a sequential mechanism by which a grapheme-phoneme correspondence rule is applied to each grapheme in turn. However, several parallel-distributed processing (PDP) models in English have simulated human nonword reading accuracy without a…

Simulation-Based Evaluation of Dose-Titration Algorithms for Rapid-Acting Insulin in Subjects with Type 2 Diabetes Mellitus Inadequately Controlled on Basal Insulin and Oral Antihyperglycemic Medications.

PubMed

Ma, Xiaosu; Chien, Jenny Y; Johnson, Jennal; Malone, James; Sinha, Vikram

2017-08-01

The purpose of this prospective, model-based simulation approach was to evaluate the impact of various rapid-acting mealtime insulin dose-titration algorithms on glycemic control (hemoglobin A1c [HbA1c]). Seven stepwise, glucose-driven insulin dose-titration algorithms were evaluated with a model-based simulation approach by using insulin lispro. Pre-meal blood glucose readings were used to adjust insulin lispro doses. Two control dosing algorithms were included for comparison: no insulin lispro (basal insulin+metformin only) or insulin lispro with fixed doses without titration. Of the seven dosing algorithms assessed, daily adjustment of insulin lispro dose, when glucose targets were met at pre-breakfast, pre-lunch, and pre-dinner, sequentially, demonstrated greater HbA1c reduction at 24 weeks, compared with the other dosing algorithms. Hypoglycemic rates were comparable among the dosing algorithms except for higher rates with the insulin lispro fixed-dose scenario (no titration), as expected. The inferior HbA1c response for the "basal plus metformin only" arm supports the additional glycemic benefit with prandial insulin lispro. Our model-based simulations support a simplified dosing algorithm that does not include carbohydrate counting, but that includes glucose targets for daily dose adjustment to maintain glycemic control with a low risk of hypoglycemia.

A Hybrid Shared-Memory Parallel Max-Tree Algorithm for Extreme Dynamic-Range Images.

PubMed

Moschini, Ugo; Meijster, Arnold; Wilkinson, Michael H F

2018-03-01

Max-trees, or component trees, are graph structures that represent the connected components of an image in a hierarchical way. Nowadays, many application fields rely on images with high-dynamic range or floating point values. Efficient sequential algorithms exist to build trees and compute attributes for images of any bit depth. However, we show that the current parallel algorithms perform poorly already with integers at bit depths higher than 16 bits per pixel. We propose a parallel method combining the two worlds of flooding and merging max-tree algorithms. First, a pilot max-tree of a quantized version of the image is built in parallel using a flooding method. Later, this structure is used in a parallel leaf-to-root approach to compute efficiently the final max-tree and to drive the merging of the sub-trees computed by the threads. We present an analysis of the performance both on simulated and actual 2D images and 3D volumes. Execution times are about better than the fastest sequential algorithm and speed-up goes up to on 64 threads.

Sequential Total Variation Denoising for the Extraction of Fetal ECG from Single-Channel Maternal Abdominal ECG

PubMed Central

Lee, Kwang Jin; Lee, Boreom

2016-01-01

Fetal heart rate (FHR) is an important determinant of fetal health. Cardiotocography (CTG) is widely used for measuring the FHR in the clinical field. However, fetal movement and blood flow through the maternal blood vessels can critically influence Doppler ultrasound signals. Moreover, CTG is not suitable for long-term monitoring. Therefore, researchers have been developing algorithms to estimate the FHR using electrocardiograms (ECGs) from the abdomen of pregnant women. However, separating the weak fetal ECG signal from the abdominal ECG signal is a challenging problem. In this paper, we propose a method for estimating the FHR using sequential total variation denoising and compare its performance with that of other single-channel fetal ECG extraction methods via simulation using the Fetal ECG Synthetic Database (FECGSYNDB). Moreover, we used real data from PhysioNet fetal ECG databases for the evaluation of the algorithm performance. The R-peak detection rate is calculated to evaluate the performance of our algorithm. Our approach could not only separate the fetal ECG signals from the abdominal ECG signals but also accurately estimate the FHR. PMID:27376296

Sequential Total Variation Denoising for the Extraction of Fetal ECG from Single-Channel Maternal Abdominal ECG.

PubMed

Lee, Kwang Jin; Lee, Boreom

2016-07-01

Fetal heart rate (FHR) is an important determinant of fetal health. Cardiotocography (CTG) is widely used for measuring the FHR in the clinical field. However, fetal movement and blood flow through the maternal blood vessels can critically influence Doppler ultrasound signals. Moreover, CTG is not suitable for long-term monitoring. Therefore, researchers have been developing algorithms to estimate the FHR using electrocardiograms (ECGs) from the abdomen of pregnant women. However, separating the weak fetal ECG signal from the abdominal ECG signal is a challenging problem. In this paper, we propose a method for estimating the FHR using sequential total variation denoising and compare its performance with that of other single-channel fetal ECG extraction methods via simulation using the Fetal ECG Synthetic Database (FECGSYNDB). Moreover, we used real data from PhysioNet fetal ECG databases for the evaluation of the algorithm performance. The R-peak detection rate is calculated to evaluate the performance of our algorithm. Our approach could not only separate the fetal ECG signals from the abdominal ECG signals but also accurately estimate the FHR.

Iterative non-sequential protein structural alignment.

PubMed

Salem, Saeed; Zaki, Mohammed J; Bystroff, Christopher

2009-06-01

Structural similarity between proteins gives us insights into their evolutionary relationships when there is low sequence similarity. In this paper, we present a novel approach called SNAP for non-sequential pair-wise structural alignment. Starting from an initial alignment, our approach iterates over a two-step process consisting of a superposition step and an alignment step, until convergence. We propose a novel greedy algorithm to construct both sequential and non-sequential alignments. The quality of SNAP alignments were assessed by comparing against the manually curated reference alignments in the challenging SISY and RIPC datasets. Moreover, when applied to a dataset of 4410 protein pairs selected from the CATH database, SNAP produced longer alignments with lower rmsd than several state-of-the-art alignment methods. Classification of folds using SNAP alignments was both highly sensitive and highly selective. The SNAP software along with the datasets are available online at http://www.cs.rpi.edu/~zaki/software/SNAP.

Sprocket- Chain Simulation: Modelling and Simulation of a Multi Physics problem by sequentially coupling MotionSolve and nanoFluidX

NASA Astrophysics Data System (ADS)

Jayanthi, Aditya; Coker, Christopher

2016-11-01

In the last decade, CFD simulations have transitioned from the stage where they are used to validate the final designs to the main stream development of products driven by the simulation. However, there are still niche areas of applications liking oiling simulations, where the traditional CFD simulation times are probative to use them in product development and have to rely on experimental methods, which are expensive. In this paper a unique example of Sprocket-Chain simulation will be presented using nanoFluidx a commercial SPH code developed by FluiDyna GmbH and Altair Engineering. The grid less nature of the of SPH method has inherent advantages in the areas of application with complex geometry which pose severe challenge to classical finite volume CFD methods due to complex moving geometries, moving meshes and high resolution requirements leading to long simulation times. The simulations times using nanoFluidx can be reduced from weeks to days allowing the flexibility to run more simulation and can be in used in main stream product development. The example problem under consideration is a classical Multiphysics problem and a sequentially coupled solution of Motion Solve and nanoFluidX will be presented. This abstract is replacing DFD16-2016-000045.

Understanding and simulating the material behavior during multi-particle irradiations

PubMed Central

Mir, Anamul H.; Toulemonde, M.; Jegou, C.; Miro, S.; Serruys, Y.; Bouffard, S.; Peuget, S.

2016-01-01

A number of studies have suggested that the irradiation behavior and damage processes occurring during sequential and simultaneous particle irradiations can significantly differ. Currently, there is no definite answer as to why and when such differences are seen. Additionally, the conventional multi-particle irradiation facilities cannot correctly reproduce the complex irradiation scenarios experienced in a number of environments like space and nuclear reactors. Therefore, a better understanding of multi-particle irradiation problems and possible alternatives are needed. This study shows ionization induced thermal spike and defect recovery during sequential and simultaneous ion irradiation of amorphous silica. The simultaneous irradiation scenario is shown to be equivalent to multiple small sequential irradiation scenarios containing latent damage formation and recovery mechanisms. The results highlight the absence of any new damage mechanism and time-space correlation between various damage events during simultaneous irradiation of amorphous silica. This offers a new and convenient way to simulate and understand complex multi-particle irradiation problems. PMID:27466040

EEG-fMRI Bayesian framework for neural activity estimation: a simulation study.

PubMed

Croce, Pierpaolo; Basti, Alessio; Marzetti, Laura; Zappasodi, Filippo; Gratta, Cosimo Del

2016-12-01

Due to the complementary nature of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), and given the possibility of simultaneous acquisition, the joint data analysis can afford a better understanding of the underlying neural activity estimation. In this simulation study we want to show the benefit of the joint EEG-fMRI neural activity estimation in a Bayesian framework. We built a dynamic Bayesian framework in order to perform joint EEG-fMRI neural activity time course estimation. The neural activity is originated by a given brain area and detected by means of both measurement techniques. We have chosen a resting state neural activity situation to address the worst case in terms of the signal-to-noise ratio. To infer information by EEG and fMRI concurrently we used a tool belonging to the sequential Monte Carlo (SMC) methods: the particle filter (PF). First, despite a high computational cost, we showed the feasibility of such an approach. Second, we obtained an improvement in neural activity reconstruction when using both EEG and fMRI measurements. The proposed simulation shows the improvements in neural activity reconstruction with EEG-fMRI simultaneous data. The application of such an approach to real data allows a better comprehension of the neural dynamics.

Detailed Modelling of Kinetic Biodegradation Processes in a Laboratory Mmicrocosm

NASA Astrophysics Data System (ADS)

Watson, I.; Oswald, S.; Banwart, S.; Mayer, U.

2003-04-01

Biodegradation of organic contaminants in soil and groundwater usually takes places via different redox processes happening sequentially as well as simultaneously. We used numerical modelling of a long-term lab microcosm experiment to simulate the dynamic behaviour of fermentation and respiration in the aqueous phase in contact with the sandstone material, and to develop a conceptual model describing these processes. Aqueous speciation, surface complexation, mineral dissolution and precipitation were taken into account also. Fermentation can be the first step of the degradation process producing intermediate species, which are subsequently consumed by TEAPs. Microbial growth and substrate utilisation kinetics are coupled via a formulation that also includes aqueous speciation and other geochemical reactions including surface complexation, mineral dissolution and precipitation. Competitive exclusion between TEAPs is integral to the conceptual model of the simulation, and the results indicate that exclusion is not complete, but some overlap is found between TEAPs. The model was used to test approaches like the partial equilibrium approach that currently make use of hydrogen levels to diagnose prevalent TEAPs in groundwater. The observed pattern of hydrogen and acetate concentrations were reproduced well by the simulations, and the results show the relevance of kinetics, lag times and inhibition, and especially that intermediate products play a key role.

Solar wind interaction with Venus and Mars in a parallel hybrid code

NASA Astrophysics Data System (ADS)

Jarvinen, Riku; Sandroos, Arto

2013-04-01

We discuss the development and applications of a new parallel hybrid simulation, where ions are treated as particles and electrons as a charge-neutralizing fluid, for the interaction between the solar wind and Venus and Mars. The new simulation code under construction is based on the algorithm of the sequential global planetary hybrid model developed at the Finnish Meteorological Institute (FMI) and on the Corsair parallel simulation platform also developed at the FMI. The FMI's sequential hybrid model has been used for studies of plasma interactions of several unmagnetized and weakly magnetized celestial bodies for more than a decade. Especially, the model has been used to interpret in situ particle and magnetic field observations from plasma environments of Mars, Venus and Titan. Further, Corsair is an open source MPI (Message Passing Interface) particle and mesh simulation platform, mainly aimed for simulations of diffusive shock acceleration in solar corona and interplanetary space, but which is now also being extended for global planetary hybrid simulations. In this presentation we discuss challenges and strategies of parallelizing a legacy simulation code as well as possible applications and prospects of a scalable parallel hybrid model for the solar wind interactions of Venus and Mars.

Simulation of dual carbon-bromine stable isotope fractionation during 1,2-dibromoethane degradation.

PubMed

Jin, Biao; Nijenhuis, Ivonne; Rolle, Massimo

2018-06-01

We performed a model-based investigation to simultaneously predict the evolution of concentration, as well as stable carbon and bromine isotope fractionation during 1,2-dibromoethane (EDB, ethylene dibromide) transformation in a closed system. The modelling approach considers bond-cleavage mechanisms during different reactions and allows evaluating dual carbon-bromine isotopic signals for chemical and biotic reactions, including aerobic and anaerobic biological transformation, dibromoelimination by Zn(0) and alkaline hydrolysis. The proposed model allowed us to accurately simulate the evolution of concentrations and isotope data observed in a previous laboratory study and to successfully identify different reaction pathways. Furthermore, we illustrated the model capabilities in degradation scenarios involving complex reaction systems. Specifically, we examined (i) the case of sequential multistep transformation of EDB and the isotopic evolution of the parent compound, the intermediate and the reaction product and (ii) the case of parallel competing abiotic pathways of EDB transformation in alkaline solution.

Analyzing Communication Architectures Using Commercial Off-The-Shelf (COTS) Modeling and Simulation Tools

DTIC Science & Technology

1998-06-01

4] By 2010, we should be able to change how we conduct the most intense joint operations. Instead of relying on massed forces and sequential ...not independent, sequential steps. Data probes to support the analysis phase were required to complete the logical models. This generated a need...Networks) Identify Granularity (System Level) - Establish Physical Bounds or Limits to Systems • Determine System Test Configuration and Lineup

Spatial interpolation of forest conditions using co-conditional geostatistical simulation

Treesearch

H. Todd Mowrer

2000-01-01

In recent work the author used the geostatistical Monte Carlo technique of sequential Gaussian simulation (s.G.s.) to investigate uncertainty in a GIS analysis of potential old-growth forest areas. The current study compares this earlier technique to that of co-conditional simulation, wherein the spatial cross-correlations between variables are included. As in the...

Comparative study of lesions created by high-intensity focused ultrasound using sequential discrete and continuous scanning strategies.

PubMed

Fan, Tingbo; Liu, Zhenbo; Zhang, Dong; Tang, Mengxing

2013-03-01

Lesion formation and temperature distribution induced by high-intensity focused ultrasound (HIFU) were investigated both numerically and experimentally via two energy-delivering strategies, i.e., sequential discrete and continuous scanning modes. Simulations were presented based on the combination of Khokhlov-Zabolotskaya-Kuznetsov (KZK) equation and bioheat equation. Measurements were performed on tissue-mimicking phantoms sonicated by a 1.12-MHz single-element focused transducer working at an acoustic power of 75 W. Both the simulated and experimental results show that, in the sequential discrete mode, obvious saw-tooth-like contours could be observed for the peak temperature distribution and the lesion boundaries, with the increasing interval space between two adjacent exposure points. In the continuous scanning mode, more uniform peak temperature distributions and lesion boundaries would be produced, and the peak temperature values would decrease significantly with the increasing scanning speed. In addition, compared to the sequential discrete mode, the continuous scanning mode could achieve higher treatment efficiency (lesion area generated per second) with a lower peak temperature. The present studies suggest that the peak temperature and tissue lesion resulting from the HIFU exposure could be controlled by adjusting the transducer scanning speed, which is important for improving the HIFU treatment efficiency.

Effects of Injected CO2 on Geomechanical Properties Due to Mineralogical Changes

NASA Astrophysics Data System (ADS)

Nguyen, B. N.; Hou, Z.; Bacon, D. H.; Murray, C. J.; White, J. A.

2013-12-01

Long-term injection and storage of CO2 in deep underground reservoirs may significantly modify the geomechanical behavior of rocks since CO2 can react with the constituent phases of reservoir rocks and modify their composition. This can lead to modifications of their geomechanical properties (i.e., elastic moduli, Biot's coefficients, and permeability). Modifications of rock geomechanical properties have important consequences as these directly control stress and strain distributions, affect conditions for fracture initiation and development and/or fault healing. This paper attempts to elucidate the geochemical effects of CO2 on geomechanical properties of typical reservoir rocks by means of numerical analyses using the STOMP-ABAQUS sequentially coupled simulator that includes the capability to handle geomechanics and the reactive transport of CO2 together with a module (EMTA) to compute the homogenized rock poroelastic properties as a function of composition changes. EMTA, a software module developed at PNNL, implements the standard and advanced Eshelby-Mori-Tanaka approaches to compute the thermoelastic properties of composite materials. In this work, EMTA will be implemented in the coupled STOMP-ABAQUS simulator as a user subroutine of ABAQUS and used to compute local elastic stiffness based on rock composition. Under the STOMP-ABAQUS approach, STOMP models are built to simulate aqueous and CO2 multiphase fluid flows, and relevant chemical reactions of pore fluids with minerals in the reservoirs. The ABAQUS models then read STOMP output data for cell center coordinates, gas pressures, aqueous pressures, temperatures, saturations, constituent volume fractions, as well as permeability and porosity that are affected by chemical reactions. These data are imported into ABAQUS meshes using a mapping procedure developed for the exchange of data between STOMP and ABAQUS. Constitutive models implemented in ABAQUS via user subroutines then compute stiffness, stresses, strains, pore pressure, permeability, porosity, and capillary pressure, and return updated permeability, porosity, and capillary pressure to STOMP at selected times. In preliminary work, the enhanced STOMP-ABAQUS sequentially coupled approach is validated and illustrated in an example analysis of a cylindrical rock specimen subjected to axial loading, confining pressure, and CO2 fluid injection. The geomechanical analysis accounting for CO2 reactions with rock constituents is compared to that without chemical reactions to elucidate the geochemical effects of injected CO2 on the response of the reservoir rock to stress.

Multigrid Methods for Fully Implicit Oil Reservoir Simulation

NASA Technical Reports Server (NTRS)

Molenaar, J.

1996-01-01

In this paper we consider the simultaneous flow of oil and water in reservoir rock. This displacement process is modeled by two basic equations: the material balance or continuity equations and the equation of motion (Darcy's law). For the numerical solution of this system of nonlinear partial differential equations there are two approaches: the fully implicit or simultaneous solution method and the sequential solution method. In the sequential solution method the system of partial differential equations is manipulated to give an elliptic pressure equation and a hyperbolic (or parabolic) saturation equation. In the IMPES approach the pressure equation is first solved, using values for the saturation from the previous time level. Next the saturations are updated by some explicit time stepping method; this implies that the method is only conditionally stable. For the numerical solution of the linear, elliptic pressure equation multigrid methods have become an accepted technique. On the other hand, the fully implicit method is unconditionally stable, but it has the disadvantage that in every time step a large system of nonlinear algebraic equations has to be solved. The most time-consuming part of any fully implicit reservoir simulator is the solution of this large system of equations. Usually this is done by Newton's method. The resulting systems of linear equations are then either solved by a direct method or by some conjugate gradient type method. In this paper we consider the possibility of applying multigrid methods for the iterative solution of the systems of nonlinear equations. There are two ways of using multigrid for this job: either we use a nonlinear multigrid method or we use a linear multigrid method to deal with the linear systems that arise in Newton's method. So far only a few authors have reported on the use of multigrid methods for fully implicit simulations. Two-level FAS algorithm is presented for the black-oil equations, and linear multigrid for two-phase flow problems with strong heterogeneities and anisotropies is studied. Here we consider both possibilities. Moreover we present a novel way for constructing the coarse grid correction operator in linear multigrid algorithms. This approach has the advantage in that it preserves the sparsity pattern of the fine grid matrix and it can be extended to systems of equations in a straightforward manner. We compare the linear and nonlinear multigrid algorithms by means of a numerical experiment.

Mapping of compositional properties of coal using isometric log-ratio transformation and sequential Gaussian simulation - A comparative study for spatial ultimate analyses data.

PubMed

Karacan, C Özgen; Olea, Ricardo A

2018-03-01

Chemical properties of coal largely determine coal handling, processing, beneficiation methods, and design of coal-fired power plants. Furthermore, these properties impact coal strength, coal blending during mining, as well as coal's gas content, which is important for mining safety. In order for these processes and quantitative predictions to be successful, safer, and economically feasible, it is important to determine and map chemical properties of coals accurately in order to infer these properties prior to mining. Ultimate analysis quantifies principal chemical elements in coal. These elements are C, H, N, S, O, and, depending on the basis, ash, and/or moisture. The basis for the data is determined by the condition of the sample at the time of analysis, with an "as-received" basis being the closest to sampling conditions and thus to the in-situ conditions of the coal. The parts determined or calculated as the result of ultimate analyses are compositions, reported in weight percent, and pose the challenges of statistical analyses of compositional data. The treatment of parts using proper compositional methods may be even more important in mapping them, as most mapping methods carry uncertainty due to partial sampling as well. In this work, we map the ultimate analyses parts of the Springfield coal from an Indiana section of the Illinois basin, USA, using sequential Gaussian simulation of isometric log-ratio transformed compositions. We compare the results with those of direct simulations of compositional parts. We also compare the implications of these approaches in calculating other properties using correlations to identify the differences and consequences. Although the study here is for coal, the methods described in the paper are applicable to any situation involving compositional data and its mapping.

Investigation of flow and transport processes at the MADE site using ensemble Kalman filter

USGS Publications Warehouse

Liu, Gaisheng; Chen, Y.; Zhang, Dongxiao

2008-01-01

In this work the ensemble Kalman filter (EnKF) is applied to investigate the flow and transport processes at the macro-dispersion experiment (MADE) site in Columbus, MS. The EnKF is a sequential data assimilation approach that adjusts the unknown model parameter values based on the observed data with time. The classic advection-dispersion (AD) and the dual-domain mass transfer (DDMT) models are employed to analyze the tritium plume during the second MADE tracer experiment. The hydraulic conductivity (K), longitudinal dispersivity in the AD model, and mass transfer rate coefficient and mobile porosity ratio in the DDMT model, are estimated in this investigation. Because of its sequential feature, the EnKF allows for the temporal scaling of transport parameters during the tritium concentration analysis. Inverse simulation results indicate that for the AD model to reproduce the extensive spatial spreading of the tritium observed in the field, the K in the downgradient area needs to be increased significantly. The estimated K in the AD model becomes an order of magnitude higher than the in situ flowmeter measurements over a large portion of media. On the other hand, the DDMT model gives an estimation of K that is much more comparable with the flowmeter values. In addition, the simulated concentrations by the DDMT model show a better agreement with the observed values. The root mean square (RMS) between the observed and simulated tritium plumes is 0.77 for the AD model and 0.45 for the DDMT model at 328 days. Unlike the AD model, which gives inconsistent K estimates at different times, the DDMT model is able to invert the K values that consistently reproduce the observed tritium concentrations through all times. ?? 2008 Elsevier Ltd. All rights reserved.

Pushing the Frontier of Data-Oriented Geodynamic Modeling: from Qualitative to Quantitative to Predictive

NASA Astrophysics Data System (ADS)

Liu, L.; Hu, J.; Zhou, Q.

2016-12-01

The rapid accumulation of geophysical and geological data sets poses an increasing demand for the development of geodynamic models to better understand the evolution of the solid Earth. Consequently, the earlier qualitative physical models are no long satisfying. Recent efforts are focusing on more quantitative simulations and more efficient numerical algorithms. Among these, a particular line of research is on the implementation of data-oriented geodynamic modeling, with the purpose of building an observationally consistent and physically correct geodynamic framework. Such models could often catalyze new insights into the functioning mechanisms of the various aspects of plate tectonics, and their predictive nature could also guide future research in a deterministic fashion. Over the years, we have been working on constructing large-scale geodynamic models with both sequential and variational data assimilation techniques. These models act as a bridge between different observational records, and the superposition of the constraining power from different data sets help reveal unknown processes and mechanisms of the dynamics of the mantle and lithosphere. We simulate the post-Cretaceous subduction history in South America using a forward (sequential) approach. The model is constrained using past subduction history, seafloor age evolution, tectonic architecture of continents, and the present day geophysical observations. Our results quantify the various driving forces shaping the present South American flat slabs, which we found are all internally torn. The 3-D geometry of these torn slabs further explains the abnormal seismicity pattern and enigmatic volcanic history. An inverse (variational) model simulating the late Cenozoic western U.S. mantle dynamics with similar constraints reveals a different mechanism for the formation of Yellowstone-related volcanism from traditional understanding. Furthermore, important insights on the mantle density and viscosity structures also emerge from these models.

Stochastic Simulation and Forecast of Hydrologic Time Series Based on Probabilistic Chaos Expansion

NASA Astrophysics Data System (ADS)

Li, Z.; Ghaith, M.

2017-12-01

Hydrological processes are characterized by many complex features, such as nonlinearity, dynamics and uncertainty. How to quantify and address such complexities and uncertainties has been a challenging task for water engineers and managers for decades. To support robust uncertainty analysis, an innovative approach for the stochastic simulation and forecast of hydrologic time series is developed is this study. Probabilistic Chaos Expansions (PCEs) are established through probabilistic collocation to tackle uncertainties associated with the parameters of traditional hydrological models. The uncertainties are quantified in model outputs as Hermite polynomials with regard to standard normal random variables. Sequentially, multivariate analysis techniques are used to analyze the complex nonlinear relationships between meteorological inputs (e.g., temperature, precipitation, evapotranspiration, etc.) and the coefficients of the Hermite polynomials. With the established relationships between model inputs and PCE coefficients, forecasts of hydrologic time series can be generated and the uncertainties in the future time series can be further tackled. The proposed approach is demonstrated using a case study in China and is compared to a traditional stochastic simulation technique, the Markov-Chain Monte-Carlo (MCMC) method. Results show that the proposed approach can serve as a reliable proxy to complicated hydrological models. It can provide probabilistic forecasting in a more computationally efficient manner, compared to the traditional MCMC method. This work provides technical support for addressing uncertainties associated with hydrological modeling and for enhancing the reliability of hydrological modeling results. Applications of the developed approach can be extended to many other complicated geophysical and environmental modeling systems to support the associated uncertainty quantification and risk analysis.

An energy function for dynamics simulations of polypeptides in torsion angle space

NASA Astrophysics Data System (ADS)

Sartori, F.; Melchers, B.; Böttcher, H.; Knapp, E. W.

1998-05-01

Conventional simulation techniques to model the dynamics of proteins in atomic detail are restricted to short time scales. A simplified molecular description, in which high frequency motions with small amplitudes are ignored, can overcome this problem. In this protein model only the backbone dihedrals φ and ψ and the χi of the side chains serve as degrees of freedom. Bond angles and lengths are fixed at ideal geometry values provided by the standard molecular dynamics (MD) energy function CHARMM. In this work a Monte Carlo (MC) algorithm is used, whose elementary moves employ cooperative rotations in a small window of consecutive amide planes, leaving the polypeptide conformation outside of this window invariant. A single of these window MC moves generates local conformational changes only. But, the application of many such moves at different parts of the polypeptide backbone leads to global conformational changes. To account for the lack of flexibility in the protein model employed, the energy function used to evaluate conformational energies is split into sequentially neighbored and sequentially distant contributions. The sequentially neighbored part is represented by an effective (φ,ψ)-torsion potential. It is derived from MD simulations of a flexible model dipeptide using a conventional MD energy function. To avoid exaggeration of hydrogen bonding strengths, the electrostatic interactions involving hydrogen atoms are scaled down at short distances. With these adjustments of the energy function, the rigid polypeptide model exhibits the same equilibrium distributions as obtained by conventional MD simulation with a fully flexible molecular model. Also, the same temperature dependence of the stability and build-up of α helices of 18-alanine as found in MD simulations is observed using the adapted energy function for MC simulations. Analyses of transition frequencies demonstrate that also dynamical aspects of MD trajectories are faithfully reproduced. Finally, it is demonstrated that even for high temperature unfolded polypeptides the MC simulation is more efficient by a factor of 10 than conventional MD simulations.

Moving Synergistically Acting Drug Combinations to the Clinic by Comparing Sequential versus Simultaneous Drug Administrations.

PubMed

Dinavahi, Saketh S; Noory, Mohammad A; Gowda, Raghavendra; Drabick, Joseph J; Berg, Arthur; Neves, Rogerio I; Robertson, Gavin P

2018-03-01

Drug combinations acting synergistically to kill cancer cells have become increasingly important in melanoma as an approach to manage the recurrent resistant disease. Protein kinase B (AKT) is a major target in this disease but its inhibitors are not effective clinically, which is a major concern. Targeting AKT in combination with WEE1 (mitotic inhibitor kinase) seems to have potential to make AKT-based therapeutics effective clinically. Since agents targeting AKT and WEE1 have been tested individually in the clinic, the quickest way to move the drug combination to patients would be to combine these agents sequentially, enabling the use of existing phase I clinical trial toxicity data. Therefore, a rapid preclinical approach is needed to evaluate whether simultaneous or sequential drug treatment has maximal therapeutic efficacy, which is based on a mechanistic rationale. To develop this approach, melanoma cell lines were treated with AKT inhibitor AZD5363 [4-amino- N -[(1 S )-1-(4-chlorophenyl)-3-hydroxypropyl]-1-(7 H -pyrrolo[2,3- d ]pyrimidin-4-yl)piperidine-4-carboxamide] and WEE1 inhibitor AZD1775 [2-allyl-1-(6-(2-hydroxypropan-2-yl)pyridin-2-yl)-6-((4-(4-methylpiperazin-1-yl)phenyl)amino)-1 H -pyrazolo[3,4- d ]pyrimidin-3(2 H )-one] using simultaneous and sequential dosing schedules. Simultaneous treatment synergistically reduced melanoma cell survival and tumor growth. In contrast, sequential treatment was antagonistic and had a minimal tumor inhibitory effect compared with individual agents. Mechanistically, simultaneous targeting of AKT and WEE1 enhanced deregulation of the cell cycle and DNA damage repair pathways by modulating transcription factors p53 and forkhead box M1, which was not observed with sequential treatment. Thus, this study identifies a rapid approach to assess the drug combinations with a mechanistic basis for selection, which suggests that combining AKT and WEE1 inhibitors is needed for maximal efficacy. Copyright © 2018 by The American Society for Pharmacology and Experimental Therapeutics.

Statistical Significance for Hierarchical Clustering

PubMed Central

Kimes, Patrick K.; Liu, Yufeng; Hayes, D. Neil; Marron, J. S.

2017-01-01

Summary Cluster analysis has proved to be an invaluable tool for the exploratory and unsupervised analysis of high dimensional datasets. Among methods for clustering, hierarchical approaches have enjoyed substantial popularity in genomics and other fields for their ability to simultaneously uncover multiple layers of clustering structure. A critical and challenging question in cluster analysis is whether the identified clusters represent important underlying structure or are artifacts of natural sampling variation. Few approaches have been proposed for addressing this problem in the context of hierarchical clustering, for which the problem is further complicated by the natural tree structure of the partition, and the multiplicity of tests required to parse the layers of nested clusters. In this paper, we propose a Monte Carlo based approach for testing statistical significance in hierarchical clustering which addresses these issues. The approach is implemented as a sequential testing procedure guaranteeing control of the family-wise error rate. Theoretical justification is provided for our approach, and its power to detect true clustering structure is illustrated through several simulation studies and applications to two cancer gene expression datasets. PMID:28099990

Silhouette-based approach of 3D image reconstruction for automated image acquisition using robotic arm

NASA Astrophysics Data System (ADS)

Azhar, N.; Saad, W. H. M.; Manap, N. A.; Saad, N. M.; Syafeeza, A. R.

2017-06-01

This study presents the approach of 3D image reconstruction using an autonomous robotic arm for the image acquisition process. A low cost of the automated imaging platform is created using a pair of G15 servo motor connected in series to an Arduino UNO as a main microcontroller. Two sets of sequential images were obtained using different projection angle of the camera. The silhouette-based approach is used in this study for 3D reconstruction from the sequential images captured from several different angles of the object. Other than that, an analysis based on the effect of different number of sequential images on the accuracy of 3D model reconstruction was also carried out with a fixed projection angle of the camera. The effecting elements in the 3D reconstruction are discussed and the overall result of the analysis is concluded according to the prototype of imaging platform.

Gstat: a program for geostatistical modelling, prediction and simulation

NASA Astrophysics Data System (ADS)

Pebesma, Edzer J.; Wesseling, Cees G.

1998-01-01

Gstat is a computer program for variogram modelling, and geostatistical prediction and simulation. It provides a generic implementation of the multivariable linear model with trends modelled as a linear function of coordinate polynomials or of user-defined base functions, and independent or dependent, geostatistically modelled, residuals. Simulation in gstat comprises conditional or unconditional (multi-) Gaussian sequential simulation of point values or block averages, or (multi-) indicator sequential simulation. Besides many of the popular options found in other geostatistical software packages, gstat offers the unique combination of (i) an interactive user interface for modelling variograms and generalized covariances (residual variograms), that uses the device-independent plotting program gnuplot for graphical display, (ii) support for several ascii and binary data and map file formats for input and output, (iii) a concise, intuitive and flexible command language, (iv) user customization of program defaults, (v) no built-in limits, and (vi) free, portable ANSI-C source code. This paper describes the class of problems gstat can solve, and addresses aspects of efficiency and implementation, managing geostatistical projects, and relevant technical details.

MaMiCo: Software design for parallel molecular-continuum flow simulations

NASA Astrophysics Data System (ADS)

Neumann, Philipp; Flohr, Hanno; Arora, Rahul; Jarmatz, Piet; Tchipev, Nikola; Bungartz, Hans-Joachim

2016-03-01

The macro-micro-coupling tool (MaMiCo) was developed to ease the development of and modularize molecular-continuum simulations, retaining sequential and parallel performance. We demonstrate the functionality and performance of MaMiCo by coupling the spatially adaptive Lattice Boltzmann framework waLBerla with four molecular dynamics (MD) codes: the light-weight Lennard-Jones-based implementation SimpleMD, the node-level optimized software ls1 mardyn, and the community codes ESPResSo and LAMMPS. We detail interface implementations to connect each solver with MaMiCo. The coupling for each waLBerla-MD setup is validated in three-dimensional channel flow simulations which are solved by means of a state-based coupling method. We provide sequential and strong scaling measurements for the four molecular-continuum simulations. The overhead of MaMiCo is found to come at 10%-20% of the total (MD) runtime. The measurements further show that scalability of the hybrid simulations is reached on up to 500 Intel SandyBridge, and more than 1000 AMD Bulldozer compute cores.

Off-line simulation inspires insight: A neurodynamics approach to efficient robot task learning.

PubMed

Sousa, Emanuel; Erlhagen, Wolfram; Ferreira, Flora; Bicho, Estela

2015-12-01

There is currently an increasing demand for robots able to acquire the sequential organization of tasks from social learning interactions with ordinary people. Interactive learning-by-demonstration and communication is a promising research topic in current robotics research. However, the efficient acquisition of generalized task representations that allow the robot to adapt to different users and contexts is a major challenge. In this paper, we present a dynamic neural field (DNF) model that is inspired by the hypothesis that the nervous system uses the off-line re-activation of initial memory traces to incrementally incorporate new information into structured knowledge. To achieve this, the model combines fast activation-based learning to robustly represent sequential information from single task demonstrations with slower, weight-based learning during internal simulations to establish longer-term associations between neural populations representing individual subtasks. The efficiency of the learning process is tested in an assembly paradigm in which the humanoid robot ARoS learns to construct a toy vehicle from its parts. User demonstrations with different serial orders together with the correction of initial prediction errors allow the robot to acquire generalized task knowledge about possible serial orders and the longer term dependencies between subgoals in very few social learning interactions. This success is shown in a joint action scenario in which ARoS uses the newly acquired assembly plan to construct the toy together with a human partner. Copyright © 2015 Elsevier Ltd. All rights reserved.

Sequential application of NaHCO3, CaCl2 and Candida oleophila (isolate 13L) affects significantly Penicillum expansum growth and the infection degree in apples.

PubMed

Molinu, M G; Pani, G; Venditti, T; Dore, A; Ladu, G; D'Hallewin, G

2011-01-01

The employment of biocontrol agents to restrain postharvest pathogens is an encouraging approach, although, efficacy and consistency are still below those of synthetic pesticides. Up to date, the 'integrated control strategy' seems to be the most promising way to overcome this gap. Here, we report the feasibility to control postharvest decay caused by Penicillium expansum in apples by a 2 min, single or sequential, immersion in water with an antagonistic yeast (Candida oleophila, isolate '13L'), 2% NaHCO3 (SBC) or 1% CaCl2. The treatments were carried out, on appels cv 'Miali' either un-wounded, wounded or wound-pathogen inoculated and then stored at 2 degrees C for 30 d followed by a 6 d simulated marketing period at 20 degrees C or alternatively stored only for 7 d at 20 degrees C. As a general role, the best results were attained when CaCl2 was applied with the yeast or when preceded by the SBC treatment. When the wounding and inoculation took place 24 h before the treatment, the latter application sequence of the two salts was three times more effective compared to the treatment with the sole antagonist, and one time when performed 24 h after the treatment. Interestingly, apples immersed in the sole 2% SBC solution had the highest percentage of decay during storage and when inoculated before moving to the simulated marketing period at 20 degrees C.

Modeling of the T S D E Heater Test to Investigate Crushed Salt Reconsolidation and Rock Salt Creep for the Underground Disposal of High-Level Nuclear Waste

NASA Astrophysics Data System (ADS)

Blanco Martin, L.; Rutqvist, J.; Birkholzer, J. T.; Wolters, R.; Lux, K. H.

2014-12-01

Rock salt is a potential medium for the underground disposal of nuclear waste because it has several assets, in particular its water and gas tightness in the undisturbed state, its ability to heal induced fractures and its high thermal conductivity as compared to other shallow-crustal rocks. In addition, the run-of-mine, granular salt, may be used to backfill the mined open spaces. We present simulation results associated with coupled thermal, hydraulic and mechanical processes in the TSDE (Thermal Simulation for Drift Emplacement) experiment, conducted in the Asse salt mine in Germany [1]. During this unique test, conceived to simulate reference repository conditions for spent nuclear fuel, a significant amount of data (temperature, stress changes and displacements, among others) was measured at 20 cross-sections, distributed in two drifts in which a total of six electrical heaters were emplaced. The drifts were subsequently backfilled with crushed salt. This test has been modeled in three-dimensions, using two sequential simulators for flow (mass and heat) and geomechanics, TOUGH-FLAC and FLAC-TOUGH [2]. These simulators have recently been updated to accommodate large strains and time-dependent rheology. The numerical predictions obtained by the two simulators are compared within the framework of an international benchmark exercise, and also with experimental data. Subsequently, a re-calibration of some parameters has been performed. Modeling coupled processes in saliniferous media for nuclear waste disposal is a novel approach, and in this study it has led to the determination of some creep parameters that are very difficult to assess at the laboratory-scale because they require extremely low strain rates. Moreover, the results from the benchmark are very satisfactory and validate the capabilities of the two simulators used to study coupled thermal, mechanical and hydraulic (multi-component, multi-phase) processes relative to the underground disposal of high-level nuclear waste in rock salt. References: [1] Bechthold et al., 1999. BAMBUS-I Project. Euratom, Report EUR19124-EN. [2] Blanco Martín et al., 2014. Comparison of two sequential simulators to investigate thermal-hydraulic-mechanical processes related to nuclear waste isolation in saliniferous formations. In preparation.

Transient Cognitive Dynamics, Metastability, and Decision Making

PubMed Central

Rabinovich, Mikhail I.; Huerta, Ramón; Varona, Pablo; Afraimovich, Valentin S.

2008-01-01

The idea that cognitive activity can be understood using nonlinear dynamics has been intensively discussed at length for the last 15 years. One of the popular points of view is that metastable states play a key role in the execution of cognitive functions. Experimental and modeling studies suggest that most of these functions are the result of transient activity of large-scale brain networks in the presence of noise. Such transients may consist of a sequential switching between different metastable cognitive states. The main problem faced when using dynamical theory to describe transient cognitive processes is the fundamental contradiction between reproducibility and flexibility of transient behavior. In this paper, we propose a theoretical description of transient cognitive dynamics based on the interaction of functionally dependent metastable cognitive states. The mathematical image of such transient activity is a stable heteroclinic channel, i.e., a set of trajectories in the vicinity of a heteroclinic skeleton that consists of saddles and unstable separatrices that connect their surroundings. We suggest a basic mathematical model, a strongly dissipative dynamical system, and formulate the conditions for the robustness and reproducibility of cognitive transients that satisfy the competing requirements for stability and flexibility. Based on this approach, we describe here an effective solution for the problem of sequential decision making, represented as a fixed time game: a player takes sequential actions in a changing noisy environment so as to maximize a cumulative reward. As we predict and verify in computer simulations, noise plays an important role in optimizing the gain. PMID:18452000

Biochemical transport modeling, estimation, and detection in realistic environments

NASA Astrophysics Data System (ADS)

Ortner, Mathias; Nehorai, Arye

2006-05-01

Early detection and estimation of the spread of a biochemical contaminant are major issues for homeland security applications. We present an integrated approach combining the measurements given by an array of biochemical sensors with a physical model of the dispersion and statistical analysis to solve these problems and provide system performance measures. We approximate the dispersion model of the contaminant in a realistic environment through numerical simulations of reflected stochastic diffusions describing the microscopic transport phenomena due to wind and chemical diffusion using the Feynman-Kac formula. We consider arbitrary complex geometries and account for wind turbulence. Localizing the dispersive sources is useful for decontamination purposes and estimation of the cloud evolution. To solve the associated inverse problem, we propose a Bayesian framework based on a random field that is particularly powerful for localizing multiple sources with small amounts of measurements. We also develop a sequential detector using the numerical transport model we propose. Sequential detection allows on-line analysis and detecting wether a change has occurred. We first focus on the formulation of a suitable sequential detector that overcomes the presence of unknown parameters (e.g. release time, intensity and location). We compute a bound on the expected delay before false detection in order to decide the threshold of the test. For a fixed false-alarm rate, we obtain the detection probability of a substance release as a function of its location and initial concentration. Numerical examples are presented for two real-world scenarios: an urban area and an indoor ventilation duct.

Spacecraft Data Simulator for the test of level zero processing systems

NASA Technical Reports Server (NTRS)

Shi, Jeff; Gordon, Julie; Mirchandani, Chandru; Nguyen, Diem

1994-01-01

The Microelectronic Systems Branch (MSB) at Goddard Space Flight Center (GSFC) has developed a Spacecraft Data Simulator (SDS) to support the development, test, and verification of prototype and production Level Zero Processing (LZP) systems. Based on a disk array system, the SDS is capable of generating large test data sets up to 5 Gigabytes and outputting serial test data at rates up to 80 Mbps. The SDS supports data formats including NASA Communication (Nascom) blocks, Consultative Committee for Space Data System (CCSDS) Version 1 & 2 frames and packets, and all the Advanced Orbiting Systems (AOS) services. The capability to simulate both sequential and non-sequential time-ordered downlink data streams with errors and gaps is crucial to test LZP systems. This paper describes the system architecture, hardware and software designs, and test data designs. Examples of test data designs are included to illustrate the application of the SDS.

A parallel computational model for GATE simulations.

PubMed

Rannou, F R; Vega-Acevedo, N; El Bitar, Z

2013-12-01

GATE/Geant4 Monte Carlo simulations are computationally demanding applications, requiring thousands of processor hours to produce realistic results. The classical strategy of distributing the simulation of individual events does not apply efficiently for Positron Emission Tomography (PET) experiments, because it requires a centralized coincidence processing and large communication overheads. We propose a parallel computational model for GATE that handles event generation and coincidence processing in a simple and efficient way by decentralizing event generation and processing but maintaining a centralized event and time coordinator. The model is implemented with the inclusion of a new set of factory classes that can run the same executable in sequential or parallel mode. A Mann-Whitney test shows that the output produced by this parallel model in terms of number of tallies is equivalent (but not equal) to its sequential counterpart. Computational performance evaluation shows that the software is scalable and well balanced. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Learning Sequential Composition Control.

PubMed

Najafi, Esmaeil; Babuska, Robert; Lopes, Gabriel A D

2016-11-01

Sequential composition is an effective supervisory control method for addressing control problems in nonlinear dynamical systems. It executes a set of controllers sequentially to achieve a control specification that cannot be realized by a single controller. As these controllers are designed offline, sequential composition cannot address unmodeled situations that might occur during runtime. This paper proposes a learning approach to augment the standard sequential composition framework by using online learning to handle unforeseen situations. New controllers are acquired via learning and added to the existing supervisory control structure. In the proposed setting, learning experiments are restricted to take place within the domain of attraction (DOA) of the existing controllers. This guarantees that the learning process is safe (i.e., the closed loop system is always stable). In addition, the DOA of the new learned controller is approximated after each learning trial. This keeps the learning process short as learning is terminated as soon as the DOA of the learned controller is sufficiently large. The proposed approach has been implemented on two nonlinear systems: 1) a nonlinear mass-damper system and 2) an inverted pendulum. The results show that in both cases a new controller can be rapidly learned and added to the supervisory control structure.

Use of Computer Simulation in Designing and Evaluating a Proposed Rough Mill for Furniture Interior Parts

Treesearch

Philip A. Araman

1977-01-01

The design of a rough mill for the production of interior furniture parts is used to illustrate a simulation technique for analyzing and evaluating established and proposed sequential production systems. Distributions representing the real-world random characteristics of lumber, equipment feed speeds and delay times are programmed into the simulation. An example is...

Correlated sequential tunneling through a double barrier for interacting one-dimensional electrons

NASA Astrophysics Data System (ADS)

Thorwart, M.; Egger, R.; Grifoni, M.

2005-07-01

The problem of resonant tunneling through a quantum dot weakly coupled to spinless Tomonaga-Luttinger liquids has been studied. We compute the linear conductance due to sequential tunneling processes upon employing a master equation approach. Besides the previously used lowest-order golden rule rates describing uncorrelated sequential tunneling processes, we systematically include higher-order correlated sequential tunneling (CST) diagrams within the standard Weisskopf-Wigner approximation. We provide estimates for the parameter regions where CST effects can be important. Focusing mainly on the temperature dependence of the peak conductance, we discuss the relation of these findings to previous theoretical and experimental results.

Correlated sequential tunneling in Tomonaga-Luttinger liquid quantum dots

NASA Astrophysics Data System (ADS)

Thorwart, M.; Egger, R.; Grifoni, M.

2005-02-01

We investigate tunneling through a quantum dot formed by two strong impurites in a spinless Tomonaga-Luttinger liquid. Upon employing a Markovian master equation approach, we compute the linear conductance due to sequential tunneling processes. Besides the previously used lowest-order Golden Rule rates describing uncorrelated sequential tunneling (UST) processes, we systematically include higher-order correlated sequential tunneling (CST) diagrams within the standard Weisskopf-Wigner approximation. We provide estimates for the parameter regions where CST effects are shown to dominate over UST. Focusing mainly on the temperature dependence of the conductance maximum, we discuss the relation of our results to previous theoretical and experimental results.

Sequential slip transfer of mixed-character dislocations across Σ3 coherent twin boundary in FCC metals: a concurrent atomistic-continuum study

DOE PAGES

Xu, Shuozhi; Xiong, Liming; Chen, Youping; ...

2016-01-29

Sequential slip transfer across grain boundaries (GB) has an important role in size-dependent propagation of plastic deformation in polycrystalline metals. For example, the Hall–Petch effect, which states that a smaller average grain size results in a higher yield stress, can be rationalised in terms of dislocation pile-ups against GBs. In spite of extensive studies in modelling individual phases and grains using atomistic simulations, well-accepted criteria of slip transfer across GBs are still lacking, as well as models of predicting irreversible GB structure evolution. Slip transfer is inherently multiscale since both the atomic structure of the boundary and the long-range fieldsmore » of the dislocation pile-up come into play. In this work, concurrent atomistic-continuum simulations are performed to study sequential slip transfer of a series of curved dislocations from a given pile-up on Σ3 coherent twin boundary (CTB) in Cu and Al, with dominant leading screw character at the site of interaction. A Frank-Read source is employed to nucleate dislocations continuously. It is found that subject to a shear stress of 1.2 GPa, screw dislocations transfer into the twinned grain in Cu, but glide on the twin boundary plane in Al. Moreover, four dislocation/CTB interaction modes are identified in Al, which are affected by (1) applied shear stress, (2) dislocation line length, and (3) dislocation line curvature. Our results elucidate the discrepancies between atomistic simulations and experimental observations of dislocation-GB reactions and highlight the importance of directly modeling sequential dislocation slip transfer reactions using fully 3D models.« less

Sequential slip transfer of mixed-character dislocations across Σ3 coherent twin boundary in FCC metals: a concurrent atomistic-continuum study

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

Xu, Shuozhi; Xiong, Liming; Chen, Youping

Sequential slip transfer across grain boundaries (GB) has an important role in size-dependent propagation of plastic deformation in polycrystalline metals. For example, the Hall–Petch effect, which states that a smaller average grain size results in a higher yield stress, can be rationalised in terms of dislocation pile-ups against GBs. In spite of extensive studies in modelling individual phases and grains using atomistic simulations, well-accepted criteria of slip transfer across GBs are still lacking, as well as models of predicting irreversible GB structure evolution. Slip transfer is inherently multiscale since both the atomic structure of the boundary and the long-range fieldsmore » of the dislocation pile-up come into play. In this work, concurrent atomistic-continuum simulations are performed to study sequential slip transfer of a series of curved dislocations from a given pile-up on Σ3 coherent twin boundary (CTB) in Cu and Al, with dominant leading screw character at the site of interaction. A Frank-Read source is employed to nucleate dislocations continuously. It is found that subject to a shear stress of 1.2 GPa, screw dislocations transfer into the twinned grain in Cu, but glide on the twin boundary plane in Al. Moreover, four dislocation/CTB interaction modes are identified in Al, which are affected by (1) applied shear stress, (2) dislocation line length, and (3) dislocation line curvature. Our results elucidate the discrepancies between atomistic simulations and experimental observations of dislocation-GB reactions and highlight the importance of directly modeling sequential dislocation slip transfer reactions using fully 3D models.« less

An analog scrambler for speech based on sequential permutations in time and frequency

NASA Astrophysics Data System (ADS)

Cox, R. V.; Jayant, N. S.; McDermott, B. J.

Permutation of speech segments is an operation that is frequently used in the design of scramblers for analog speech privacy. In this paper, a sequential procedure for segment permutation is considered. This procedure can be extended to two dimensional permutation of time segments and frequency bands. By subjective testing it is shown that this combination gives a residual intelligibility for spoken digits of 20 percent with a delay of 256 ms. (A lower bound for this test would be 10 percent). The complexity of implementing such a system is considered and the issues of synchronization and channel equalization are addressed. The computer simulation results for the system using both real and simulated channels are examined.

Modeling of a Sequential Two-Stage Combustor

NASA Technical Reports Server (NTRS)

Hendricks, R. C.; Liu, N.-S.; Gallagher, J. R.; Ryder, R. C.; Brankovic, A.; Hendricks, J. A.

2005-01-01

A sequential two-stage, natural gas fueled power generation combustion system is modeled to examine the fundamental aerodynamic and combustion characteristics of the system. The modeling methodology includes CAD-based geometry definition, and combustion computational fluid dynamics analysis. Graphical analysis is used to examine the complex vortical patterns in each component, identifying sources of pressure loss. The simulations demonstrate the importance of including the rotating high-pressure turbine blades in the computation, as this results in direct computation of combustion within the first turbine stage, and accurate simulation of the flow in the second combustion stage. The direct computation of hot-streaks through the rotating high-pressure turbine stage leads to improved understanding of the aerodynamic relationships between the primary and secondary combustors and the turbomachinery.

A Computational Model of Coupled Multiphase Flow and Geomechanics to Study Fault Slip and Induced Seismicity

NASA Astrophysics Data System (ADS)

Juanes, R.; Jha, B.

2014-12-01

The coupling between subsurface flow and geomechanical deformation is critical in the assessment of the environmental impacts of groundwater use, underground liquid waste disposal, geologic storage of carbon dioxide, and exploitation of shale gas reserves. In particular, seismicity induced by fluid injection and withdrawal has emerged as a central element of the scientific discussion around subsurface technologies that tap into water and energy resources. Here we present a new computational approach to model coupled multiphase flow and geomechanics of faulted reservoirs. We represent faults as surfaces embedded in a three-dimensional medium by using zero-thickness interface elements to accurately model fault slip under dynamically evolving fluid pressure and fault strength. We incorporate the effect of fluid pressures from multiphase flow in the mechanical stability of faults and employ a rigorous formulation of nonlinear multiphase geomechanics that is capable of handling strong capillary effects. We develop a numerical simulation tool by coupling a multiphase flow simulator with a mechanics simulator, using the unconditionally stable fixed-stress scheme for the sequential solution of two-way coupling between flow and geomechanics. We validate our modeling approach using several synthetic, but realistic, test cases that illustrate the onset and evolution of earthquakes from fluid injection and withdrawal. We also present the application of the coupled flow-geomechanics simulation technology to the post mortem analysis of the Mw=5.1, May 2011 Lorca earthquake in south-east Spain, and assess the potential that the earthquake was induced by groundwater extraction.

Mathematical Problem Solving through Sequential Process Analysis

ERIC Educational Resources Information Center

Codina, A.; Cañadas, M. C.; Castro, E.

2015-01-01

Introduction: The macroscopic perspective is one of the frameworks for research on problem solving in mathematics education. Coming from this perspective, our study addresses the stages of thought in mathematical problem solving, offering an innovative approach because we apply sequential relations and global interrelations between the different…

Simulation of thermally induced processes of diffusion and phase formation in layered binary metallic systems

NASA Astrophysics Data System (ADS)

Rusakov, V. S.; Sukhorukov, I. A.; Zhankadamova, A. M.; Kadyrzhanov, K. K.

2010-05-01

Results of the simulation of thermally induced processes of diffusion and phase formation in model and experimentally investigated layered binary metallic systems are presented. The physical model is based on the Darken phenomenological theory and on the mechanism of interdiffusion of components along the continuous diffusion channels of phases in the two-phase regions of the system. The simulation of processes in the model systems showed that the thermally stabilized concentration profiles in two-layer binary metallic systems are virtually independent of the partial diffusion coefficients; for the systems with the average concentration of components that is the same over the sample depth, the time of the thermal stabilization of the structural and phase state inhomogeneous over the depth grows according to a power law with increasing thickness of the system in such a manner that the thicknesses of the surface layers grow, while the thickness of the intermediate layer approaches a constant value. The results of the simulation of the processes of diffusion and phase formation in experimentally investigated layered binary systems Fe-Ti and Cu-Be upon sequential isothermal and isochronous annealings agree well with the experimental data.

Joint penalized-likelihood reconstruction of time-activity curves and regions-of-interest from projection data in brain PET

NASA Astrophysics Data System (ADS)

Krestyannikov, E.; Tohka, J.; Ruotsalainen, U.

2008-06-01

This paper presents a novel statistical approach for joint estimation of regions-of-interest (ROIs) and the corresponding time-activity curves (TACs) from dynamic positron emission tomography (PET) brain projection data. It is based on optimizing the joint objective function that consists of a data log-likelihood term and two penalty terms reflecting the available a priori information about the human brain anatomy. The developed local optimization strategy iteratively updates both the ROI and TAC parameters and is guaranteed to monotonically increase the objective function. The quantitative evaluation of the algorithm is performed with numerically and Monte Carlo-simulated dynamic PET brain data of the 11C-Raclopride and 18F-FDG tracers. The results demonstrate that the method outperforms the existing sequential ROI quantification approaches in terms of accuracy, and can noticeably reduce the errors in TACs arising due to the finite spatial resolution and ROI delineation.

Three dimensional, numerical analysis of an elasto hydrodynamic lubrication using fluid structure interaction (FSI) approach

NASA Astrophysics Data System (ADS)

Hanoca, P.; Ramakrishna, H. V.

2018-03-01

This work is related to develop a methodology to model and simulate the TEHD using the sequential application of CFD and CSD. The FSI analyses are carried out using ANSYS Workbench. In this analysis steady state, 3D Navier-Stoke equations along with energy equation are solved. Liquid properties are introduced where the viscosity and density are the function of pressure and temperature. The cavitation phenomenon is adopted in the analysis. Numerical analysis has been carried at different speeds and surfaces temperatures. During the analysis, it was found that as speed increases, hydrodynamic pressures will also increases. The pressure profile obtained from the Roelands equation is more sensitive to the temperature as compared to the Barus equation. The stress distributions specify the significant positions in the bearing structure. The developed method is capable of giving latest approaching into the physics of elasto hydrodynamic lubrication.

A D-vine copula-based model for repeated measurements extending linear mixed models with homogeneous correlation structure.

PubMed

Killiches, Matthias; Czado, Claudia

2018-03-22

We propose a model for unbalanced longitudinal data, where the univariate margins can be selected arbitrarily and the dependence structure is described with the help of a D-vine copula. We show that our approach is an extremely flexible extension of the widely used linear mixed model if the correlation is homogeneous over the considered individuals. As an alternative to joint maximum-likelihood a sequential estimation approach for the D-vine copula is provided and validated in a simulation study. The model can handle missing values without being forced to discard data. Since conditional distributions are known analytically, we easily make predictions for future events. For model selection, we adjust the Bayesian information criterion to our situation. In an application to heart surgery data our model performs clearly better than competing linear mixed models. © 2018, The International Biometric Society.

An abstraction layer for efficient memory management of tabulated chemistry and flamelet solutions

NASA Astrophysics Data System (ADS)

Weise, Steffen; Messig, Danny; Meyer, Bernd; Hasse, Christian

2013-06-01

A large number of methods for simulating reactive flows exist, some of them, for example, directly use detailed chemical kinetics or use precomputed and tabulated flame solutions. Both approaches couple the research fields computational fluid dynamics and chemistry tightly together using either an online or offline approach to solve the chemistry domain. The offline approach usually involves a method of generating databases or so-called Lookup-Tables (LUTs). As these LUTs are extended to not only contain material properties but interactions between chemistry and turbulent flow, the number of parameters and thus dimensions increases. Given a reasonable discretisation, file sizes can increase drastically. The main goal of this work is to provide methods that handle large database files efficiently. A Memory Abstraction Layer (MAL) has been developed that handles requested LUT entries efficiently by splitting the database file into several smaller blocks. It keeps the total memory usage at a minimum using thin allocation methods and compression to minimise filesystem operations. The MAL has been evaluated using three different test cases. The first rather generic one is a sequential reading operation on an LUT to evaluate the runtime behaviour as well as the memory consumption of the MAL. The second test case is a simulation of a non-premixed turbulent flame, the so-called HM1 flame, which is a well-known test case in the turbulent combustion community. The third test case is a simulation of a non-premixed laminar flame as described by McEnally in 1996 and Bennett in 2000. Using the previously developed solver 'flameletFoam' in conjunction with the MAL, memory consumption and the performance penalty introduced were studied. The total memory used while running a parallel simulation was reduced significantly while the CPU time overhead associated with the MAL remained low.

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.

PubMed

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.

A novel method for the sequential removal and separation of multiple heavy metals from wastewater.

PubMed

Fang, Li; Li, Liang; Qu, Zan; Xu, Haomiao; Xu, Jianfang; Yan, Naiqiang

2018-01-15

A novel method was developed and applied for the treatment of simulated wastewater containing multiple heavy metals. A sorbent of ZnS nanocrystals (NCs) was synthesized and showed extraordinary performance for the removal of Hg 2+ , Cu 2+ , Pb 2+ and Cd 2+ . The removal efficiencies of Hg 2+ , Cu 2+ , Pb 2+ and Cd 2+ were 99.9%, 99.9%, 90.8% and 66.3%, respectively. Meanwhile, it was determined that solubility product (K sp ) of heavy metal sulfides was closely related to adsorption selectivity of various heavy metals on the sorbent. The removal efficiency of Hg 2+ was higher than that of Cd 2+ , while the K sp of HgS was lower than that of CdS. It indicated that preferential adsorption of heavy metals occurred when the K sp of the heavy metal sulfide was lower. In addition, the differences in the K sp of heavy metal sulfides allowed for the exchange of heavy metals, indicating the potential application for the sequential removal and separation of heavy metals from wastewater. According to the cumulative adsorption experimental results, multiple heavy metals were sequentially adsorbed and separated from the simulated wastewater in the order of the K sp of their sulfides. This method holds the promise of sequentially removing and separating multiple heavy metals from wastewater. Copyright © 2017 Elsevier B.V. All rights reserved.

Nonlinear interferometry approach to photonic sequential logic

NASA Astrophysics Data System (ADS)

Mabuchi, Hideo

2011-10-01

Motivated by rapidly advancing capabilities for extensive nanoscale patterning of optical materials, I propose an approach to implementing photonic sequential logic that exploits circuit-scale phase coherence for efficient realizations of fundamental components such as a NAND-gate-with-fanout and a bistable latch. Kerr-nonlinear optical resonators are utilized in combination with interference effects to drive the binary logic. Quantum-optical input-output models are characterized numerically using design parameters that yield attojoule-scale energy separation between the latch states.

A Deep Learning based Approach to Reduced Order Modeling of Fluids using LSTM Neural Networks

NASA Astrophysics Data System (ADS)

Mohan, Arvind; Gaitonde, Datta

2017-11-01

Reduced Order Modeling (ROM) can be used as surrogates to prohibitively expensive simulations to model flow behavior for long time periods. ROM is predicated on extracting dominant spatio-temporal features of the flow from CFD or experimental datasets. We explore ROM development with a deep learning approach, which comprises of learning functional relationships between different variables in large datasets for predictive modeling. Although deep learning and related artificial intelligence based predictive modeling techniques have shown varied success in other fields, such approaches are in their initial stages of application to fluid dynamics. Here, we explore the application of the Long Short Term Memory (LSTM) neural network to sequential data, specifically to predict the time coefficients of Proper Orthogonal Decomposition (POD) modes of the flow for future timesteps, by training it on data at previous timesteps. The approach is demonstrated by constructing ROMs of several canonical flows. Additionally, we show that statistical estimates of stationarity in the training data can indicate a priori how amenable a given flow-field is to this approach. Finally, the potential and limitations of deep learning based ROM approaches will be elucidated and further developments discussed.

Statistical Engineering in Air Traffic Management Research

NASA Technical Reports Server (NTRS)

Wilson, Sara R.

2015-01-01

NASA is working to develop an integrated set of advanced technologies to enable efficient arrival operations in high-density terminal airspace for the Next Generation Air Transportation System. This integrated arrival solution is being validated and verified in laboratories and transitioned to a field prototype for an operational demonstration at a major U.S. airport. Within NASA, this is a collaborative effort between Ames and Langley Research Centers involving a multi-year iterative experimentation process. Designing and analyzing a series of sequential batch computer simulations and human-in-the-loop experiments across multiple facilities and simulation environments involves a number of statistical challenges. Experiments conducted in separate laboratories typically have different limitations and constraints, and can take different approaches with respect to the fundamental principles of statistical design of experiments. This often makes it difficult to compare results from multiple experiments and incorporate findings into the next experiment in the series. A statistical engineering approach is being employed within this project to support risk-informed decision making and maximize the knowledge gained within the available resources. This presentation describes a statistical engineering case study from NASA, highlights statistical challenges, and discusses areas where existing statistical methodology is adapted and extended.

A Comparison of Filter-based Approaches for Model-based Prognostics

NASA Technical Reports Server (NTRS)

Daigle, Matthew John; Saha, Bhaskar; Goebel, Kai

2012-01-01

Model-based prognostics approaches use domain knowledge about a system and its failure modes through the use of physics-based models. Model-based prognosis is generally divided into two sequential problems: a joint state-parameter estimation problem, in which, using the model, the health of a system or component is determined based on the observations; and a prediction problem, in which, using the model, the stateparameter distribution is simulated forward in time to compute end of life and remaining useful life. The first problem is typically solved through the use of a state observer, or filter. The choice of filter depends on the assumptions that may be made about the system, and on the desired algorithm performance. In this paper, we review three separate filters for the solution to the first problem: the Daum filter, an exact nonlinear filter; the unscented Kalman filter, which approximates nonlinearities through the use of a deterministic sampling method known as the unscented transform; and the particle filter, which approximates the state distribution using a finite set of discrete, weighted samples, called particles. Using a centrifugal pump as a case study, we conduct a number of simulation-based experiments investigating the performance of the different algorithms as applied to prognostics.

INVESTIGATION OF SEQUENTIAL AND ENZYMATIC EXTRACTION OF ARSENIC FROM DRINKING WATER DISTRIBUTION SOLIDS WITH ICP-MS

EPA Science Inventory

A sequential extraction approach was utilized to estimate the distribution of arsenite [As(III)] and arsenate [As(V)] on iron oxide/hydroxide solids obtained from drinking water distribution systems. The arsenic (As) associated with these solids can be segregated into three oper...

Combining silver- and organocatalysis: an enantioselective sequential catalytic approach towards pyrano-annulated pyrazoles.

PubMed

Hack, Daniel; Chauhan, Pankaj; Deckers, Kristina; Mizutani, Yusuke; Raabe, Gerhard; Enders, Dieter

2015-02-11

A one-pot asymmetric Michael addition/hydroalkoxylation sequence, catalyzed by a sequential catalytic system consisting of a squaramide and a silver salt, provides a new series of chiral pyrano-annulated pyrazole derivatives in excellent yields (up to 95%) and high enantioselectivities (up to 97% ee).

Sequentially-crosslinked biomimetic bioactive glass/gelatin methacryloyl composites hydrogels for bone regeneration.

PubMed

Zheng, Jiafu; Zhao, Fujian; Zhang, Wen; Mo, Yunfei; Zeng, Lei; Li, Xian; Chen, Xiaofeng

2018-08-01

In recent years, gelatin-based composites hydrogels have been intensively investigated because of their inherent bioactivity, biocompatibility and biodegradability. Herein, we fabricated photocrosslinkable biomimetic composites hydrogels from bioactive glass (BG) and gelatin methacryloyl (GelMA) by a sequential physical and chemical crosslinking (gelation + UV) approach. The results showed that the compressive modulus of composites hydrogels increased significantly through the sequential crosslinking approach. The addition of BG resulted in a significant increase in physiological stability and apatite-forming ability. In vitro data indicated that BG/GelMA composites hydrogels promoted cell attachment, proliferation and differentiation. Overall, the BG/GelMA composites hydrogels combined the advantages of good biocompatibility and bioactivity, and had potential applications in bone regeneration. Copyright © 2018. Published by Elsevier B.V.

Integrating remotely sensed land cover observations and a biogeochemical model for estimating forest ecosystem carbon dynamics

USGS Publications Warehouse

Liu, J.; Liu, S.; Loveland, Thomas R.; Tieszen, L.L.

2008-01-01

Land cover change is one of the key driving forces for ecosystem carbon (C) dynamics. We present an approach for using sequential remotely sensed land cover observations and a biogeochemical model to estimate contemporary and future ecosystem carbon trends. We applied the General Ensemble Biogeochemical Modelling System (GEMS) for the Laurentian Plains and Hills ecoregion in the northeastern United States for the period of 1975-2025. The land cover changes, especially forest stand-replacing events, were detected on 30 randomly located 10-km by 10-km sample blocks, and were assimilated by GEMS for biogeochemical simulations. In GEMS, each unique combination of major controlling variables (including land cover change history) forms a geo-referenced simulation unit. For a forest simulation unit, a Monte Carlo process is used to determine forest type, forest age, forest biomass, and soil C, based on the Forest Inventory and Analysis (FIA) data and the U.S. General Soil Map (STATSGO) data. Ensemble simulations are performed for each simulation unit to incorporate input data uncertainty. Results show that on average forests of the Laurentian Plains and Hills ecoregion have been sequestrating 4.2 Tg C (1 teragram = 1012 gram) per year, including 1.9 Tg C removed from the ecosystem as the consequences of land cover change. ?? 2008 Elsevier B.V.

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

NASA Astrophysics Data System (ADS)

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.

Sequential chemical treatment of radium species in TENORM waste sludge produced from oil and natural gas production.

PubMed

El Afifi, E M; Awwad, N S; Hilal, M A

2009-01-30

This paper is dedicated to the treatment of sludge occurring in frame of the Egyptian produced from oil and gas production. The activity levels of three radium isotopes: Ra-226 (of U-series), Ra-228 and Ra-224 (of Th-series) in the solid TENORM waste (sludge) were first evaluated and followed by a sequential treatment for all radium species (fractions) presented in TENORM. The sequential treatment was carried out based on two approaches 'A' and 'B' using different chemical solutions. The results obtained indicate that the activity levels of all radium isotopes (Ra-226, Ra-228 and Ra-224) of the environmental interest in the TENORM waste sludge were elevated with regard to exemption levels established by IAEA [International Atomic Energy Agency (IAEA), International basic safety standards for the protection against ionizing radiation and for the safety of radiation sources. GOV/2715/Vienna, 1994]. Each approach of the sequential treatment was performed through four steps using different chemical solutions to reduce the activity concentration of radium in a large extent. Most of the leached radium was found as an oxidizable Ra species. The actual removal % leached using approach B was relatively efficient compared to A. It is observed that the actual removal percentages (%) of Ra-226, Ra-228 and Ra-224 using approach A are 78+/-2.8, 64.8+/-4.1 and 76.4+/-5.2%, respectively. Whereas in approach A, the overall removal % of Ra-226, Ra-228 and Ra-228 was increased to approximately 91+/-3.5, 87+/-4.1 and 90+/-6.2%, respectively.

Sequential segmental classification of feline congenital heart disease.

PubMed

Scansen, Brian A; Schneider, Matthias; Bonagura, John D

2015-12-01

Feline congenital heart disease is less commonly encountered in veterinary medicine than acquired feline heart diseases such as cardiomyopathy. Understanding the wide spectrum of congenital cardiovascular disease demands a familiarity with a variety of lesions, occurring both in isolation and in combination, along with an appreciation of complex nomenclature and variable classification schemes. This review begins with an overview of congenital heart disease in the cat, including proposed etiologies and prevalence, examination approaches, and principles of therapy. Specific congenital defects are presented and organized by a sequential segmental classification with respect to their morphologic lesions. Highlights of diagnosis, treatment options, and prognosis are offered. It is hoped that this review will provide a framework for approaching congenital heart disease in the cat, and more broadly in other animal species based on the sequential segmental approach, which represents an adaptation of the common methodology used in children and adults with congenital heart disease. Copyright © 2015 Elsevier B.V. All rights reserved.

Sequential interactions-in which one player plays first and another responds-promote cooperation in evolutionary-dynamical simulations of single-shot Prisoner's Dilemma and Snowdrift games.

PubMed

Laird, Robert A

2018-09-07

Cooperation is a central topic in evolutionary biology because (a) it is difficult to reconcile why individuals would act in a way that benefits others if such action is costly to themselves, and (b) it underpins many of the 'major transitions of evolution', making it essential for explaining the origins of successively higher levels of biological organization. Within evolutionary game theory, the Prisoner's Dilemma and Snowdrift games are the main theoretical constructs used to study the evolution of cooperation in dyadic interactions. In single-shot versions of these games, wherein individuals play each other only once, players typically act simultaneously rather than sequentially. Allowing one player to respond to the actions of its co-player-in the absence of any possibility of the responder being rewarded for cooperation or punished for defection, as in simultaneous or sequential iterated games-may seem to invite more incentive for exploitation and retaliation in single-shot games, compared to when interactions occur simultaneously, thereby reducing the likelihood that cooperative strategies can thrive. To the contrary, I use lattice-based, evolutionary-dynamical simulation models of single-shot games to demonstrate that under many conditions, sequential interactions have the potential to enhance unilaterally or mutually cooperative outcomes and increase the average payoff of populations, relative to simultaneous interactions-benefits that are especially prevalent in a spatially explicit context. This surprising result is attributable to the presence of conditional strategies that emerge in sequential games that can't occur in the corresponding simultaneous versions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Developing and Implementing a Framework of Participatory Simulation for Mobile Learning Using Scaffolding

ERIC Educational Resources Information Center

Yin, Chengjiu; Song, Yanjie; Tabata, Yoshiyuki; Ogata, Hiroaki; Hwang, Gwo-Jen

2013-01-01

This paper proposes a conceptual framework, scaffolding participatory simulation for mobile learning (SPSML), used on mobile devices for helping students learn conceptual knowledge in the classroom. As the pedagogical design, the framework adopts an experiential learning model, which consists of five sequential but cyclic steps: the initial stage,…

Using sequential self-calibration method to identify conductivity distribution: Conditioning on tracer test data

USGS Publications Warehouse

Hu, B.X.; He, C.

2008-01-01

An iterative inverse method, the sequential self-calibration method, is developed for mapping spatial distribution of a hydraulic conductivity field by conditioning on nonreactive tracer breakthrough curves. A streamline-based, semi-analytical simulator is adopted to simulate solute transport in a heterogeneous aquifer. The simulation is used as the forward modeling step. In this study, the hydraulic conductivity is assumed to be a deterministic or random variable. Within the framework of the streamline-based simulator, the efficient semi-analytical method is used to calculate sensitivity coefficients of the solute concentration with respect to the hydraulic conductivity variation. The calculated sensitivities account for spatial correlations between the solute concentration and parameters. The performance of the inverse method is assessed by two synthetic tracer tests conducted in an aquifer with a distinct spatial pattern of heterogeneity. The study results indicate that the developed iterative inverse method is able to identify and reproduce the large-scale heterogeneity pattern of the aquifer given appropriate observation wells in these synthetic cases. ?? International Association for Mathematical Geology 2008.

Artificial intelligence framework for simulating clinical decision-making: a Markov decision process approach.

PubMed

Bennett, Casey C; Hauser, Kris

2013-01-01

In the modern healthcare system, rapidly expanding costs/complexity, the growing myriad of treatment options, and exploding information streams that often do not effectively reach the front lines hinder the ability to choose optimal treatment decisions over time. The goal in this paper is to develop a general purpose (non-disease-specific) computational/artificial intelligence (AI) framework to address these challenges. This framework serves two potential functions: (1) a simulation environment for exploring various healthcare policies, payment methodologies, etc., and (2) the basis for clinical artificial intelligence - an AI that can "think like a doctor". This approach combines Markov decision processes and dynamic decision networks to learn from clinical data and develop complex plans via simulation of alternative sequential decision paths while capturing the sometimes conflicting, sometimes synergistic interactions of various components in the healthcare system. It can operate in partially observable environments (in the case of missing observations or data) by maintaining belief states about patient health status and functions as an online agent that plans and re-plans as actions are performed and new observations are obtained. This framework was evaluated using real patient data from an electronic health record. The results demonstrate the feasibility of this approach; such an AI framework easily outperforms the current treatment-as-usual (TAU) case-rate/fee-for-service models of healthcare. The cost per unit of outcome change (CPUC) was $189 vs. $497 for AI vs. TAU (where lower is considered optimal) - while at the same time the AI approach could obtain a 30-35% increase in patient outcomes. Tweaking certain AI model parameters could further enhance this advantage, obtaining approximately 50% more improvement (outcome change) for roughly half the costs. Given careful design and problem formulation, an AI simulation framework can approximate optimal decisions even in complex and uncertain environments. Future work is described that outlines potential lines of research and integration of machine learning algorithms for personalized medicine. Copyright © 2012 Elsevier B.V. All rights reserved.

A compartmentalized solute transport model for redox zones in contaminated aquifers: 1. Theory and development

USGS Publications Warehouse

Abrams , Robert H.; Loague, Keith

2000-01-01

This paper, the first of two parts [see Abrams and Loague, this issue], takes the compartmentalized approach for the geochemical evolution of redox zones presented by Abrams et al. [1998] and embeds it within a solute transport framework. In this paper the compartmentalized approach is generalized to facilitate the description of its incorporation into a solute transport simulator. An equivalent formulation is developed which removes any discontinuities that may occur when switching compartments. Rate‐limited redox reactions are modeled with a modified Monod relationship that allows either the organic substrate or the electron acceptor to be the rate‐limiting reactant. Thermodynamic constraints are used to inhibit lower‐energy redox reactions from occurring under infeasible geochemical conditions without imposing equilibrium on the lower‐energy reactions. The procedure used allows any redox reaction to be simulated as being kinetically limited or thermodynamically limited, depending on local geochemical conditions. Empirical reaction inhibition methods are not needed. The sequential iteration approach (SIA), a technique which allows the number of solute transport equations to be reduced, is adopted to solve the coupled geochemical/solute transport problem. When the compartmentalized approach is embedded within the SIA, with the total analytical concentration of each component as the dependent variable in the transport equation, it is possible to reduce the number of transport equations even further than with the unmodified SIA. A one‐dimensional, coupled geochemical/solute transport simulation is presented in which redox zones evolve dynamically in time and space. The compartmentalized solute transport (COMPTRAN) model described in this paper enables the development of redox zones to be simulated under both kinetic and thermodynamic constraints. The modular design of COMPTRAN facilitates the use of many different, preexisting solute transport and geochemical codes. The companion paper [Abrams and Loague, this issue] presents examples of the application of COMPTRAN to field‐scale problems.

How Hydroclimate Influences the Effectiveness of Particle Filter Data Assimilation of Streamflow in Initializing Short- to Medium-range Streamflow Forecasts

NASA Astrophysics Data System (ADS)

Clark, E.; Wood, A.; Nijssen, B.; Clark, M. P.

2017-12-01

Short- to medium-range (1- to 7-day) streamflow forecasts are important for flood control operations and in issuing potentially life-save flood warnings. In the U.S., the National Weather Service River Forecast Centers (RFCs) issue such forecasts in real time, depending heavily on a manual data assimilation (DA) approach. Forecasters adjust model inputs, states, parameters and outputs based on experience and consideration of a range of supporting real-time information. Achieving high-quality forecasts from new automated, centralized forecast systems will depend critically on the adequacy of automated DA approaches to make analogous corrections to the forecasting system. Such approaches would further enable systematic evaluation of real-time flood forecasting methods and strategies. Toward this goal, we have implemented a real-time Sequential Importance Resampling particle filter (SIR-PF) approach to assimilate observed streamflow into simulated initial hydrologic conditions (states) for initializing ensemble flood forecasts. Assimilating streamflow alone in SIR-PF improves simulated streamflow and soil moisture during the model spin up period prior to a forecast, with consequent benefits for forecasts. Nevertheless, it only consistently limits error in simulated snow water equivalent during the snowmelt season and in basins where precipitation falls primarily as snow. We examine how the simulated initial conditions with and without SIR-PF propagate into 1- to 7-day ensemble streamflow forecasts. Forecasts are evaluated in terms of reliability and skill over a 10-year period from 2005-2015. The focus of this analysis is on how interactions between hydroclimate and SIR-PF performance impact forecast skill. To this end, we examine forecasts for 5 hydroclimatically diverse basins in the western U.S. Some of these basins receive most of their precipitation as snow, others as rain. Some freeze throughout the mid-winter while others experience significant mid-winter melt events. We describe the methodology and present seasonal and inter-basin variations in DA-enhanced forecast skill.

Numerical simulation of double‐diffusive finger convection

USGS Publications Warehouse

Hughes, Joseph D.; Sanford, Ward E.; Vacher, H. Leonard

2005-01-01

A hybrid finite element, integrated finite difference numerical model is developed for the simulation of double‐diffusive and multicomponent flow in two and three dimensions. The model is based on a multidimensional, density‐dependent, saturated‐unsaturated transport model (SUTRA), which uses one governing equation for fluid flow and another for solute transport. The solute‐transport equation is applied sequentially to each simulated species. Density coupling of the flow and solute‐transport equations is accounted for and handled using a sequential implicit Picard iterative scheme. High‐resolution data from a double‐diffusive Hele‐Shaw experiment, initially in a density‐stable configuration, is used to verify the numerical model. The temporal and spatial evolution of simulated double‐diffusive convection is in good agreement with experimental results. Numerical results are very sensitive to discretization and correspond closest to experimental results when element sizes adequately define the spatial resolution of observed fingering. Numerical results also indicate that differences in the molecular diffusivity of sodium chloride and the dye used to visualize experimental sodium chloride concentrations are significant and cause inaccurate mapping of sodium chloride concentrations by the dye, especially at late times. As a result of reduced diffusion, simulated dye fingers are better defined than simulated sodium chloride fingers and exhibit more vertical mass transfer.

Comparison of rate one-half, equivalent constraint length 24, binary convolutional codes for use with sequential decoding on the deep-space channel

NASA Technical Reports Server (NTRS)

Massey, J. L.

1976-01-01

Virtually all previously-suggested rate 1/2 binary convolutional codes with KE = 24 are compared. Their distance properties are given; and their performance, both in computation and in error probability, with sequential decoding on the deep-space channel is determined by simulation. Recommendations are made both for the choice of a specific KE = 24 code as well as for codes to be included in future coding standards for the deep-space channel. A new result given in this report is a method for determining the statistical significance of error probability data when the error probability is so small that it is not feasible to perform enough decoding simulations to obtain more than a very small number of decoding errors.

A Sequential Analysis of Parent-Child Interactions in Anxious and Nonanxious Families

ERIC Educational Resources Information Center

Williams, Sarah R.; Kertz, Sarah J.; Schrock, Matthew D.; Woodruff-Borden, Janet

2012-01-01

Although theoretical work has suggested that reciprocal behavior patterns between parent and child may be important in the development of childhood anxiety, most empirical work has failed to consider the bidirectional nature of interactions. The current study sought to address this limitation by utilizing a sequential approach to exploring…

Sequential Online Wellness Programming Is an Effective Strategy to Promote Behavior Change

ERIC Educational Resources Information Center

MacNab, Lindsay R.; Francis, Sarah L.

2015-01-01

The growing number of United States youth and adults categorized as overweight or obese illustrates a need for research-based family wellness interventions. Sequential, online, Extension-delivered family wellness interventions offer a time- and cost-effective approach for both participants and Extension educators. The 6-week, online Healthy…

On mining complex sequential data by means of FCA and pattern structures

NASA Astrophysics Data System (ADS)

Buzmakov, Aleksey; Egho, Elias; Jay, Nicolas; Kuznetsov, Sergei O.; Napoli, Amedeo; Raïssi, Chedy

2016-02-01

Nowadays data-sets are available in very complex and heterogeneous ways. Mining of such data collections is essential to support many real-world applications ranging from healthcare to marketing. In this work, we focus on the analysis of "complex" sequential data by means of interesting sequential patterns. We approach the problem using the elegant mathematical framework of formal concept analysis and its extension based on "pattern structures". Pattern structures are used for mining complex data (such as sequences or graphs) and are based on a subsumption operation, which in our case is defined with respect to the partial order on sequences. We show how pattern structures along with projections (i.e. a data reduction of sequential structures) are able to enumerate more meaningful patterns and increase the computing efficiency of the approach. Finally, we show the applicability of the presented method for discovering and analysing interesting patient patterns from a French healthcare data-set on cancer. The quantitative and qualitative results (with annotations and analysis from a physician) are reported in this use-case which is the main motivation for this work.

[Approach to percutaneous nephrolithotomy. Comparison of the procedure in a one-shot versus the sequential with metal dilata].

PubMed

Sedano-Portillo, Ismael; Ochoa-León, Gastón; Fuentes-Orozco, Clotilde; Irusteta-Jiménez, Leire; Michel-Espinoza, Luis Rodrigo; Salazar-Parra, Marcela; Cuesta-Márquez, Lizbeth; González-Ojeda, Alejandro

2017-01-01

Percutaneous nephrolithotomy is an efficient approach for treatment of different types of kidney stones. Various types of access techniques have been described like sequential dilatation and one-shot procedure. To determine the differences in time of exposure to X-rays and hemoglobin levels between techniques. Controlled clinical trial. Patients older than 18 years with complex/uncomplicated kidney stones, without urine infection were included. They were assigned randomly to one of the two techniques. Response variables were determined before and 24 h after procedures. 59 patients were included: 30 underwent one-shot procedure (study-group) and 29 sequential dilatation (control-group). Baseline characteristics were similar. Study group had a lower postoperative hemoglobin decline than control group (0.81 vs. 2.03 g/dl, respectively; p < 0.001); X-ray exposure time (69.6 vs. 100.62 s; p < 0.001) and postoperative creatinine serum levels (0.93 ± 0.29 vs. 1.13 ± 0.4 mg/dl; p = 0.039). No significant differences in postoperative morbidity were found. One-shot technique demonstrated better results compared to sequential dilatation.

Multidrug Resistance among New Tuberculosis Cases: Detecting Local Variation through Lot Quality-Assurance Sampling

PubMed Central

Lynn Hedt, Bethany; van Leth, Frank; Zignol, Matteo; Cobelens, Frank; van Gemert, Wayne; Viet Nhung, Nguyen; Lyepshina, Svitlana; Egwaga, Saidi; Cohen, Ted

2012-01-01

Background Current methodology for multidrug-resistant TB (MDR TB) surveys endorsed by the World Health Organization provides estimates of MDR TB prevalence among new cases at the national level. On the aggregate, local variation in the burden of MDR TB may be masked. This paper investigates the utility of applying lot quality-assurance sampling to identify geographic heterogeneity in the proportion of new cases with multidrug resistance. Methods We simulated the performance of lot quality-assurance sampling by applying these classification-based approaches to data collected in the most recent TB drug-resistance surveys in Ukraine, Vietnam, and Tanzania. We explored three classification systems—two-way static, three-way static, and three-way truncated sequential sampling—at two sets of thresholds: low MDR TB = 2%, high MDR TB = 10%, and low MDR TB = 5%, high MDR TB = 20%. Results The lot quality-assurance sampling systems identified local variability in the prevalence of multidrug resistance in both high-resistance (Ukraine) and low-resistance settings (Vietnam). In Tanzania, prevalence was uniformly low, and the lot quality-assurance sampling approach did not reveal variability. The three-way classification systems provide additional information, but sample sizes may not be obtainable in some settings. New rapid drug-sensitivity testing methods may allow truncated sequential sampling designs and early stopping within static designs, producing even greater efficiency gains. Conclusions Lot quality-assurance sampling study designs may offer an efficient approach for collecting critical information on local variability in the burden of multidrug-resistant TB. Before this methodology is adopted, programs must determine appropriate classification thresholds, the most useful classification system, and appropriate weighting if unbiased national estimates are also desired. PMID:22249242

Multidrug resistance among new tuberculosis cases: detecting local variation through lot quality-assurance sampling.

PubMed

Hedt, Bethany Lynn; van Leth, Frank; Zignol, Matteo; Cobelens, Frank; van Gemert, Wayne; Nhung, Nguyen Viet; Lyepshina, Svitlana; Egwaga, Saidi; Cohen, Ted

2012-03-01

Current methodology for multidrug-resistant tuberculosis (MDR TB) surveys endorsed by the World Health Organization provides estimates of MDR TB prevalence among new cases at the national level. On the aggregate, local variation in the burden of MDR TB may be masked. This paper investigates the utility of applying lot quality-assurance sampling to identify geographic heterogeneity in the proportion of new cases with multidrug resistance. We simulated the performance of lot quality-assurance sampling by applying these classification-based approaches to data collected in the most recent TB drug-resistance surveys in Ukraine, Vietnam, and Tanzania. We explored 3 classification systems- two-way static, three-way static, and three-way truncated sequential sampling-at 2 sets of thresholds: low MDR TB = 2%, high MDR TB = 10%, and low MDR TB = 5%, high MDR TB = 20%. The lot quality-assurance sampling systems identified local variability in the prevalence of multidrug resistance in both high-resistance (Ukraine) and low-resistance settings (Vietnam). In Tanzania, prevalence was uniformly low, and the lot quality-assurance sampling approach did not reveal variability. The three-way classification systems provide additional information, but sample sizes may not be obtainable in some settings. New rapid drug-sensitivity testing methods may allow truncated sequential sampling designs and early stopping within static designs, producing even greater efficiency gains. Lot quality-assurance sampling study designs may offer an efficient approach for collecting critical information on local variability in the burden of multidrug-resistant TB. Before this methodology is adopted, programs must determine appropriate classification thresholds, the most useful classification system, and appropriate weighting if unbiased national estimates are also desired.

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

PubMed

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.

Finding False Paths in Sequential Circuits

NASA Astrophysics Data System (ADS)

Matrosova, A. Yu.; Andreeva, V. V.; Chernyshov, S. V.; Rozhkova, S. V.; Kudin, D. V.

2018-02-01

Method of finding false paths in sequential circuits is developed. In contrast with heuristic approaches currently used abroad, the precise method based on applying operations on Reduced Ordered Binary Decision Diagrams (ROBDDs) extracted from the combinational part of a sequential controlling logic circuit is suggested. The method allows finding false paths when transfer sequence length is not more than the given value and obviates the necessity of investigation of combinational circuit equivalents of the given lengths. The possibilities of using of the developed method for more complicated circuits are discussed.

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

Jennings, E.; Madigan, M.

Given the complexity of modern cosmological parameter inference where we arefaced with non-Gaussian data and noise, correlated systematics and multi-probecorrelated data sets, the Approximate Bayesian Computation (ABC) method is apromising alternative to traditional Markov Chain Monte Carlo approaches in thecase where the Likelihood is intractable or unknown. The ABC method is called"Likelihood free" as it avoids explicit evaluation of the Likelihood by using aforward model simulation of the data which can include systematics. Weintroduce astroABC, an open source ABC Sequential Monte Carlo (SMC) sampler forparameter estimation. A key challenge in astrophysics is the efficient use oflarge multi-probe datasets to constrainmore » high dimensional, possibly correlatedparameter spaces. With this in mind astroABC allows for massive parallelizationusing MPI, a framework that handles spawning of jobs across multiple nodes. Akey new feature of astroABC is the ability to create MPI groups with differentcommunicators, one for the sampler and several others for the forward modelsimulation, which speeds up sampling time considerably. For smaller jobs thePython multiprocessing option is also available. Other key features include: aSequential Monte Carlo sampler, a method for iteratively adapting tolerancelevels, local covariance estimate using scikit-learn's KDTree, modules forspecifying optimal covariance matrix for a component-wise or multivariatenormal perturbation kernel, output and restart files are backed up everyiteration, user defined metric and simulation methods, a module for specifyingheterogeneous parameter priors including non-standard prior PDFs, a module forspecifying a constant, linear, log or exponential tolerance level,well-documented examples and sample scripts. This code is hosted online athttps://github.com/EliseJ/astroABC« less

Some theoretical issues on computer simulations

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

Barrett, C.L.; Reidys, C.M.

1998-02-01

The subject of this paper is the development of mathematical foundations for a theory of simulation. Sequentially updated cellular automata (sCA) over arbitrary graphs are employed as a paradigmatic framework. In the development of the theory, the authors focus on the properties of causal dependencies among local mappings in a simulation. The main object of and study is the mapping between a graph representing the dependencies among entities of a simulation and a representing the equivalence classes of systems obtained by all possible updates.

Iterative Self-Dual Reconstruction on Radar Image Recovery

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

Martins, Charles; Medeiros, Fatima; Ushizima, Daniela

2010-05-21

Imaging systems as ultrasound, sonar, laser and synthetic aperture radar (SAR) are subjected to speckle noise during image acquisition. Before analyzing these images, it is often necessary to remove the speckle noise using filters. We combine properties of two mathematical morphology filters with speckle statistics to propose a signal-dependent noise filter to multiplicative noise. We describe a multiscale scheme that preserves sharp edges while it smooths homogeneous areas, by combining local statistics with two mathematical morphology filters: the alternating sequential and the self-dual reconstruction algorithms. The experimental results show that the proposed approach is less sensitive to varying window sizesmore » when applied to simulated and real SAR images in comparison with standard filters.« less

Optimization of Multi-Fidelity Computer Experiments via the EQIE Criterion

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

He, Xu; Tuo, Rui; Jeff Wu, C. F.

Computer experiments based on mathematical models are powerful tools for understanding physical processes. This article addresses the problem of kriging-based optimization for deterministic computer experiments with tunable accuracy. Our approach is to use multi- delity computer experiments with increasing accuracy levels and a nonstationary Gaussian process model. We propose an optimization scheme that sequentially adds new computer runs by following two criteria. The first criterion, called EQI, scores candidate inputs with given level of accuracy, and the second criterion, called EQIE, scores candidate combinations of inputs and accuracy. Here, from simulation results and a real example using finite element analysis,more » our method out-performs the expected improvement (EI) criterion which works for single-accuracy experiments.« less

Optimization of Multi-Fidelity Computer Experiments via the EQIE Criterion

DOE PAGES

He, Xu; Tuo, Rui; Jeff Wu, C. F.

2017-01-31

Computer experiments based on mathematical models are powerful tools for understanding physical processes. This article addresses the problem of kriging-based optimization for deterministic computer experiments with tunable accuracy. Our approach is to use multi- delity computer experiments with increasing accuracy levels and a nonstationary Gaussian process model. We propose an optimization scheme that sequentially adds new computer runs by following two criteria. The first criterion, called EQI, scores candidate inputs with given level of accuracy, and the second criterion, called EQIE, scores candidate combinations of inputs and accuracy. Here, from simulation results and a real example using finite element analysis,more » our method out-performs the expected improvement (EI) criterion which works for single-accuracy experiments.« less

The experimental vibrational infrared spectrum of lemon peel and simulation of spectral properties of the plant cell wall

NASA Astrophysics Data System (ADS)

Berezin, K. V.; Shagautdinova, I. T.; Chernavina, M. L.; Novoselova, A. V.; Dvoretskii, K. N.; Likhter, A. M.

2017-09-01

The experimental vibrational IR spectra of the outer part of lemon peel are recorded in the range of 3800-650 cm-1. The effect of artificial and natural dehydration of the peel on its vibrational spectrum is studied. It is shown that the colored outer layer of lemon peel does not have a noticeable effect on the vibrational spectrum. Upon 28-day storage of a lemon under natural laboratory conditions, only sequential dehydration processes are reflected in the vibrational spectrum of the peel. Within the framework of the theoretical DFT/B3LYP/6-31G(d) method, a model of a plant cell wall is developed consisting of a number of polymeric molecules of dietary fibers like cellulose, hemicellulose, pectin, lignin, some polyphenolic compounds (hesperetin glycoside-flavonoid), and a free water cluster. Using a supermolecular approach, the spectral properties of the wall of a lemon peel cell was simulated, and a detailed theoretical interpretation of the recorded vibrational spectrum is given.

Unsteady, one-dimensional gas dynamics computations using a TVD type sequential solver

NASA Technical Reports Server (NTRS)

Thakur, Siddharth; Shyy, Wei

1992-01-01

The efficacy of high resolution convection schemes to resolve sharp gradient in unsteady, 1D flows is examined using the TVD concept based on a sequential solution algorithm. Two unsteady flow problems are considered which include the problem involving the interaction of the various waves in a shock tube with closed reflecting ends and the problem involving the unsteady gas dynamics in a tube with closed ends subject to an initial pressure perturbation. It is concluded that high accuracy convection schemes in a sequential solution framework are capable of resolving discontinuities in unsteady flows involving complex gas dynamics. However, a sufficient amount of dissipation is required to suppress oscillations near discontinuities in the sequential approach, which leads to smearing of the solution profiles.

Blocking for Sequential Political Experiments

PubMed Central

Moore, Sally A.

2013-01-01

In typical political experiments, researchers randomize a set of households, precincts, or individuals to treatments all at once, and characteristics of all units are known at the time of randomization. However, in many other experiments, subjects “trickle in” to be randomized to treatment conditions, usually via complete randomization. To take advantage of the rich background data that researchers often have (but underutilize) in these experiments, we develop methods that use continuous covariates to assign treatments sequentially. We build on biased coin and minimization procedures for discrete covariates and demonstrate that our methods outperform complete randomization, producing better covariate balance in simulated data. We then describe how we selected and deployed a sequential blocking method in a clinical trial and demonstrate the advantages of our having done so. Further, we show how that method would have performed in two larger sequential political trials. Finally, we compare causal effect estimates from differences in means, augmented inverse propensity weighted estimators, and randomization test inversion. PMID:24143061

Geostatistical conditional simulation for the assessment of contaminated land by abandoned heavy metal mining.

PubMed

Ersoy, Adem; Yunsel, Tayfun Yusuf; Atici, Umit

2008-02-01

Abandoned mine workings can undoubtedly cause varying degrees of contamination of soil with heavy metals such as lead and zinc has occurred on a global scale. Exposure to these elements may cause to harm human health and environment. In the study, a total of 269 soil samples were collected at 1, 5, and 10 m regular grid intervals of 100 x 100 m area of Carsington Pasture in the UK. Cell declustering technique was applied to the data set due to no statistical representativity. Directional experimental semivariograms of the elements for the transformed data showed that both geometric and zonal anisotropy exists in the data. The most evident spatial dependence structure of the continuity for the directional experimental semivariogram, characterized by spherical and exponential models of Pb and Zn were obtained. This study reports the spatial distribution and uncertainty of Pb and Zn concentrations in soil at the study site using a probabilistic approach. The approach was based on geostatistical sequential Gaussian simulation (SGS), which is used to yield a series of conditional images characterized by equally probable spatial distributions of the heavy elements concentrations across the area. Postprocessing of many simulations allowed the mapping of contaminated and uncontaminated areas, and provided a model for the uncertainty in the spatial distribution of element concentrations. Maps of the simulated Pb and Zn concentrations revealed the extent and severity of contamination. SGS was validated by statistics, histogram, variogram reproduction, and simulation errors. The maps of the elements might be used in the remediation studies, help decision-makers and others involved in the abandoned heavy metal mining site in the world.

Development of a CSP plant energy yield calculation tool applying predictive models to analyze plant performance sensitivities

NASA Astrophysics Data System (ADS)

Haack, Lukas; Peniche, Ricardo; Sommer, Lutz; Kather, Alfons

2017-06-01

At early project stages, the main CSP plant design parameters such as turbine capacity, solar field size, and thermal storage capacity are varied during the techno-economic optimization to determine most suitable plant configurations. In general, a typical meteorological year with at least hourly time resolution is used to analyze each plant configuration. Different software tools are available to simulate the annual energy yield. Software tools offering a thermodynamic modeling approach of the power block and the CSP thermal cycle, such as EBSILONProfessional®, allow a flexible definition of plant topologies. In EBSILON, the thermodynamic equilibrium for each time step is calculated iteratively (quasi steady state), which requires approximately 45 minutes to process one year with hourly time resolution. For better presentation of gradients, 10 min time resolution is recommended, which increases processing time by a factor of 5. Therefore, analyzing a large number of plant sensitivities, as required during the techno-economic optimization procedure, the detailed thermodynamic simulation approach becomes impracticable. Suntrace has developed an in-house CSP-Simulation tool (CSPsim), based on EBSILON and applying predictive models, to approximate the CSP plant performance for central receiver and parabolic trough technology. CSPsim significantly increases the speed of energy yield calculations by factor ≥ 35 and has automated the simulation run of all predefined design configurations in sequential order during the optimization procedure. To develop the predictive models, multiple linear regression techniques and Design of Experiment methods are applied. The annual energy yield and derived LCOE calculated by the predictive model deviates less than ±1.5 % from the thermodynamic simulation in EBSILON and effectively identifies the optimal range of main design parameters for further, more specific analysis.

Sequential Pattern Analysis: Method and Application in Exploring How Students Develop Concept Maps

ERIC Educational Resources Information Center

Chiu, Chiung-Hui; Lin, Chien-Liang

2012-01-01

Concept mapping is a technique that represents knowledge in graphs. It has been widely adopted in science education and cognitive psychology to aid learning and assessment. To realize the sequential manner in which students develop concept maps, most research relies upon human-dependent, qualitative approaches. This article proposes a method for…

On the Sequential Negotiation of Identity in Spanish-Language Discourse: Mobilizing Linguistic Resources in the Service of Social Action

ERIC Educational Resources Information Center

Raymond, Chase Wesley

2014-01-01

This dissertation takes an ethnomethodologically-grounded, conversation-analytic approach in investigating the sequential deployment of linguistic resources in Spanish-language talk-in-interaction. Three sets of resources are examined: 2nd-person singular reference forms (tú, vos, usted), indicative/subjunctive verbal mood selection, and…

Functions Represented as Linear Sequential Data: Relationships between Presentation and Student Responses

ERIC Educational Resources Information Center

Ayalon, Michal; Watson, Anne; Lerman, Steve

2015-01-01

This study investigates students' ways of attending to linear sequential data in two tasks, and conjectures possible relationships between those ways and elements of the task design. Drawing on the substantial literature about such situations, we focus for this paper on linear rate of change, and on covariation and correspondence approaches to…

Sequential-Injection Analysis: Principles, Instrument Construction, and Demonstration by a Simple Experiment

ERIC Educational Resources Information Center

Economou, A.; Tzanavaras, P. D.; Themelis, D. G.

2005-01-01

The sequential-injection analysis (SIA) is an approach to sample handling that enables the automation of manual wet-chemistry procedures in a rapid, precise and efficient manner. The experiments using SIA fits well in the course of Instrumental Chemical Analysis and especially in the section of Automatic Methods of analysis provided by chemistry…

An Overview of Markov Chain Methods for the Study of Stage-Sequential Developmental Processes

ERIC Educational Resources Information Center

Kapland, David

2008-01-01

This article presents an overview of quantitative methodologies for the study of stage-sequential development based on extensions of Markov chain modeling. Four methods are presented that exemplify the flexibility of this approach: the manifest Markov model, the latent Markov model, latent transition analysis, and the mixture latent Markov model.…

Harmonizing and Improvising in the Choral Rehearsal: A Sequential Approach

ERIC Educational Resources Information Center

Bell, Cindy L.

2004-01-01

This article challenges choral teachers to motivate their choirs to a new level of choral singing and harmonic creativity and outlines a sequential process for introducing improvisation into the daily warm-up. It argues that students can learn to harmonize and improvise by ear as part of each day's warm-up period. Sections include: (1) Chord…

Randomized Controlled Trial for Behavioral Smoking and Weight Control Treatment: Effect of Concurrent Versus Sequential Intervention.

ERIC Educational Resources Information Center

Spring, Bonnie; Pagoto, Sherry; Pingitore, Regina; Doran, Neal; Schneider, Kristin; Hedeker, Don

2004-01-01

The authors compared simultaneous versus sequential approaches to multiple health behavior change in diet, exercise, and cigarette smoking. Female regular smokers (N = 315) randomized to 3 conditions received 16 weeks of behavioral smoking treatment, quit smoking at Week 5, and were followed for 9 months after quit date. Weight management was…

Coupled porohyperelastic mass transport (PHEXPT) finite element models for soft tissues using ABAQUS.

PubMed

Vande Geest, Jonathan P; Simon, B R; Rigby, Paul H; Newberg, Tyler P

2011-04-01

Finite element models (FEMs) including characteristic large deformations in highly nonlinear materials (hyperelasticity and coupled diffusive/convective transport of neutral mobile species) will allow quantitative study of in vivo tissues. Such FEMs will provide basic understanding of normal and pathological tissue responses and lead to optimization of local drug delivery strategies. We present a coupled porohyperelastic mass transport (PHEXPT) finite element approach developed using a commercially available ABAQUS finite element software. The PHEXPT transient simulations are based on sequential solution of the porohyperelastic (PHE) and mass transport (XPT) problems where an Eulerian PHE FEM is coupled to a Lagrangian XPT FEM using a custom-written FORTRAN program. The PHEXPT theoretical background is derived in the context of porous media transport theory and extended to ABAQUS finite element formulations. The essential assumptions needed in order to use ABAQUS are clearly identified in the derivation. Representative benchmark finite element simulations are provided along with analytical solutions (when appropriate). These simulations demonstrate the differences in transient and steady state responses including finite deformations, total stress, fluid pressure, relative fluid, and mobile species flux. A detailed description of important model considerations (e.g., material property functions and jump discontinuities at material interfaces) is also presented in the context of finite deformations. The ABAQUS-based PHEXPT approach enables the use of the available ABAQUS capabilities (interactive FEM mesh generation, finite element libraries, nonlinear material laws, pre- and postprocessing, etc.). PHEXPT FEMs can be used to simulate the transport of a relatively large neutral species (negligible osmotic fluid flux) in highly deformable hydrated soft tissues and tissue-engineered materials.

On the origin of reproducible sequential activity in neural circuits

NASA Astrophysics Data System (ADS)

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.

On the origin of reproducible sequential activity in neural circuits.

PubMed

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.

Fast and Precise Emulation of Stochastic Biochemical Reaction Networks With Amplified Thermal Noise in Silicon Chips.

PubMed

Kim, Jaewook; Woo, Sung Sik; Sarpeshkar, Rahul

2018-04-01

The analysis and simulation of complex interacting biochemical reaction pathways in cells is important in all of systems biology and medicine. Yet, the dynamics of even a modest number of noisy or stochastic coupled biochemical reactions is extremely time consuming to simulate. In large part, this is because of the expensive cost of random number and Poisson process generation and the presence of stiff, coupled, nonlinear differential equations. Here, we demonstrate that we can amplify inherent thermal noise in chips to emulate randomness physically, thus alleviating these costs significantly. Concurrently, molecular flux in thermodynamic biochemical reactions maps to thermodynamic electronic current in a transistor such that stiff nonlinear biochemical differential equations are emulated exactly in compact, digitally programmable, highly parallel analog "cytomorphic" transistor circuits. For even small-scale systems involving just 80 stochastic reactions, our 0.35-μm BiCMOS chips yield a 311× speedup in the simulation time of Gillespie's stochastic algorithm over COPASI, a fast biochemical-reaction software simulator that is widely used in computational biology; they yield a 15 500× speedup over equivalent MATLAB stochastic simulations. The chip emulation results are consistent with these software simulations over a large range of signal-to-noise ratios. Most importantly, our physical emulation of Poisson chemical dynamics does not involve any inherently sequential processes and updates such that, unlike prior exact simulation approaches, they are parallelizable, asynchronous, and enable even more speedup for larger-size networks.

Sequential delivery of TAT-HSP27 and VEGF using microsphere/hydrogel hybrid systems for therapeutic angiogenesis.

PubMed

Shin, Seung-Hwa; Lee, Jangwook; Lim, Kwang Suk; Rhim, Taiyoun; Lee, Sang Kyung; Kim, Yong-Hee; Lee, Kuen Yong

2013-02-28

Ischemic disease is associated with high mortality and morbidity rates, and therapeutic angiogenesis via systemic or local delivery of protein drugs is one potential approach to treat the disease. In this study, we hypothesized that combined delivery of TAT-HSP27 (HSP27 fused with transcriptional activator) and VEGF could enhance the therapeutic efficacy in an ischemic mouse model, and that sequential release could be critical in therapeutic angiogenesis. Alginate hydrogels containing TAT-HSP27 as an anti-apoptotic agent were prepared, and porous PLGA microspheres loaded with VEGF as an angiogenic agent were incorporated into the hydrogels to prepare microsphere/hydrogel hybrid delivery systems. Sequential in vitro release of TAT-HSP27 and VEGF was achieved by the hybrid systems. TAT-HSP27 was depleted from alginate gels in 7 days, while VEGF was continually released for 28 days. The release rate of VEGF was attenuated by varying the porous structures of PLGA microspheres. Sequential delivery of TAT-HSP27 and VEGF was critical to protect against muscle degeneration and fibrosis, as well as to promote new blood vessel formation in the ischemic site of a mouse model. This approach to controlling the sequential release behaviors of multiple drugs could be useful in the design of novel drug delivery systems for therapeutic angiogenesis. Copyright © 2012 Elsevier B.V. All rights reserved.

SIM_EXPLORE: Software for Directed Exploration of Complex Systems

NASA Technical Reports Server (NTRS)

Burl, Michael; Wang, Esther; Enke, Brian; Merline, William J.

2013-01-01

Physics-based numerical simulation codes are widely used in science and engineering to model complex systems that would be infeasible to study otherwise. While such codes may provide the highest- fidelity representation of system behavior, they are often so slow to run that insight into the system is limited. Trying to understand the effects of inputs on outputs by conducting an exhaustive grid-based sweep over the input parameter space is simply too time-consuming. An alternative approach called "directed exploration" has been developed to harvest information from numerical simulators more efficiently. The basic idea is to employ active learning and supervised machine learning to choose cleverly at each step which simulation trials to run next based on the results of previous trials. SIM_EXPLORE is a new computer program that uses directed exploration to explore efficiently complex systems represented by numerical simulations. The software sequentially identifies and runs simulation trials that it believes will be most informative given the results of previous trials. The results of new trials are incorporated into the software's model of the system behavior. The updated model is then used to pick the next round of new trials. This process, implemented as a closed-loop system wrapped around existing simulation code, provides a means to improve the speed and efficiency with which a set of simulations can yield scientifically useful results. The software focuses on the case in which the feedback from the simulation trials is binary-valued, i.e., the learner is only informed of the success or failure of the simulation trial to produce a desired output. The software offers a number of choices for the supervised learning algorithm (the method used to model the system behavior given the results so far) and a number of choices for the active learning strategy (the method used to choose which new simulation trials to run given the current behavior model). The software also makes use of the LEGION distributed computing framework to leverage the power of a set of compute nodes. The approach has been demonstrated on a planetary science application in which numerical simulations are used to study the formation of asteroid families.

[Using sequential indicator simulation method to define risk areas of soil heavy metals in farmland.

PubMed

Yang, Hao; Song, Ying Qiang; Hu, Yue Ming; Chen, Fei Xiang; Zhang, Rui

2018-05-01

The heavy metals in soil have serious impacts on safety, ecological environment and human health due to their toxicity and accumulation. It is necessary to efficiently identify the risk area of heavy metals in farmland soil, which is of important significance for environment protection, pollution warning and farmland risk control. We collected 204 samples and analyzed the contents of seven kinds of heavy metals (Cu, Zn, Pb, Cd, Cr, As, Hg) in Zengcheng District of Guangzhou, China. In order to overcame the problems of the data, including the limitation of abnormal values and skewness distribution and the smooth effect with the traditional kriging methods, we used sequential indicator simulation method (SISIM) to define the spatial distribution of heavy metals, and combined Hakanson index method to identify potential ecological risk area of heavy metals in farmland. The results showed that: (1) Based on the similar accuracy of spatial prediction of soil heavy metals, the SISIM had a better expression of detail rebuild than ordinary kriging in small scale area. Compared to indicator kriging, the SISIM had less error rate (4.9%-17.1%) in uncertainty evaluation of heavy-metal risk identification. The SISIM had less smooth effect and was more applicable to simulate the spatial uncertainty assessment of soil heavy metals and risk identification. (2) There was no pollution in Zengcheng's farmland. Moderate potential ecological risk was found in the southern part of study area due to enterprise production, human activities, and river sediments. This study combined the sequential indicator simulation with Hakanson risk index method, and effectively overcame the outlier information loss and smooth effect of traditional kriging method. It provided a new way to identify the soil heavy metal risk area of farmland in uneven sampling.

A high accuracy sequential solver for simulation and active control of a longitudinal combustion instability

NASA Technical Reports Server (NTRS)

Shyy, W.; Thakur, S.; Udaykumar, H. S.

1993-01-01

A high accuracy convection scheme using a sequential solution technique has been developed and applied to simulate the longitudinal combustion instability and its active control. The scheme has been devised in the spirit of the Total Variation Diminishing (TVD) concept with special source term treatment. Due to the substantial heat release effect, a clear delineation of the key elements employed by the scheme, i.e., the adjustable damping factor and the source term treatment has been made. By comparing with the first-order upwind scheme previously utilized, the present results exhibit less damping and are free from spurious oscillations, offering improved quantitative accuracy while confirming the spectral analysis reported earlier. A simple feedback type of active control has been found to be capable of enhancing or attenuating the magnitude of the combustion instability.

Parallel discrete event simulation using shared memory

NASA Technical Reports Server (NTRS)

Reed, Daniel A.; Malony, Allen D.; Mccredie, Bradley D.

1988-01-01

With traditional event-list techniques, evaluating a detailed discrete-event simulation-model can often require hours or even days of computation time. By eliminating the event list and maintaining only sufficient synchronization to ensure causality, parallel simulation can potentially provide speedups that are linear in the numbers of processors. A set of shared-memory experiments, using the Chandy-Misra distributed-simulation algorithm, to simulate networks of queues is presented. Parameters of the study include queueing network topology and routing probabilities, number of processors, and assignment of network nodes to processors. These experiments show that Chandy-Misra distributed simulation is a questionable alternative to sequential-simulation of most queueing network models.

A Bayesian Theory of Sequential Causal Learning and Abstract Transfer.

PubMed

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 Cognitive Science Society, Inc.

Composite solvers for linear saddle point problems arising from the incompressible Stokes equations with highly heterogeneous viscosity structure

NASA Astrophysics Data System (ADS)

Sanan, P.; Schnepp, S. M.; May, D.; Schenk, O.

2014-12-01

Geophysical applications require efficient forward models for non-linear Stokes flow on high resolution spatio-temporal domains. The bottleneck in applying the forward model is solving the linearized, discretized Stokes problem which takes the form of a large, indefinite (saddle point) linear system. Due to the heterogeniety of the effective viscosity in the elliptic operator, devising effective preconditioners for saddle point problems has proven challenging and highly problem-dependent. Nevertheless, at least three approaches show promise for preconditioning these difficult systems in an algorithmically scalable way using multigrid and/or domain decomposition techniques. The first is to work with a hierarchy of coarser or smaller saddle point problems. The second is to use the Schur complement method to decouple and sequentially solve for the pressure and velocity. The third is to use the Schur decomposition to devise preconditioners for the full operator. These involve sub-solves resembling inexact versions of the sequential solve. The choice of approach and sub-methods depends crucially on the motivating physics, the discretization, and available computational resources. Here we examine the performance trade-offs for preconditioning strategies applied to idealized models of mantle convection and lithospheric dynamics, characterized by large viscosity gradients. Due to the arbitrary topological structure of the viscosity field in geodynamical simulations, we utilize low order, inf-sup stable mixed finite element spatial discretizations which are suitable when sharp viscosity variations occur in element interiors. Particular attention is paid to possibilities within the decoupled and approximate Schur complement factorization-based monolithic approaches to leverage recently-developed flexible, communication-avoiding, and communication-hiding Krylov subspace methods in combination with `heavy' smoothers, which require solutions of large per-node sub-problems, well-suited to solution on hybrid computational clusters. To manage the combinatorial explosion of solver options (which include hybridizations of all the approaches mentioned above), we leverage the modularity of the PETSc library.

Bridging the qualitative-quantitative divide: Experiences from conducting a mixed methods evaluation in the RUCAS programme.

PubMed

Makrakis, Vassilios; Kostoulas-Makrakis, Nelly

2016-02-01

Quantitative and qualitative approaches to planning and evaluation in education for sustainable development have often been treated by practitioners from a single research paradigm. This paper discusses the utility of mixed method evaluation designs which integrate qualitative and quantitative data through a sequential transformative process. Sequential mixed method data collection strategies involve collecting data in an iterative process whereby data collected in one phase contribute to data collected in the next. This is done through examples from a programme addressing the 'Reorientation of University Curricula to Address Sustainability (RUCAS): A European Commission Tempus-funded Programme'. It is argued that the two approaches are complementary and that there are significant gains from combining both. Using methods from both research paradigms does not, however, mean that the inherent differences among epistemologies and methodologies should be neglected. Based on this experience, it is recommended that using a sequential transformative mixed method evaluation can produce more robust results than could be accomplished using a single approach in programme planning and evaluation focussed on education for sustainable development. Copyright © 2015 Elsevier Ltd. All rights reserved.

Food matrix effects on in vitro digestion of microencapsulated tuna oil powder.

PubMed

Shen, Zhiping; Apriani, Christina; Weerakkody, Rangika; Sanguansri, Luz; Augustin, Mary Ann

2011-08-10

Tuna oil, containing 53 mg of eicosapentaenoic acid (EPA) and 241 mg of docosahexaenoic acid (DHA) per gram of oil, delivered as a neat microencapsulated tuna oil powder (25% oil loading) or in food matrices (orange juice, yogurt, or cereal bar) fortified with microencapsulated tuna oil powder was digested in simulated gastric fluid or sequentially in simulated gastric fluid and simulated intestinal fluid. The level of fortification was equivalent to 1 g of tuna oil per recommended serving size (i.e., per 200 g of orange juice or yogurt or 60 g of cereal bar). The changes in particle size of oil droplets during digestion were influenced by the method of delivery of the microencapsulated tuna oil powder. Lipolysis in simulated gastric fluid was low, with only 4.4-6.1% EPA and ≤1.5% DHA released after digestion (as a % of total fatty acids present). After sequential exposure to simulated gastric and intestinal fluids, much higher extents of lipolysis of both glycerol-bound EPA and DHA were obtained (73.2-78.6% for the neat powder, fortified orange juice, and yogurt; 60.3-64.0% for the fortified cereal bar). This research demonstrates that the choice of food matrix may influence the lipolysis of microencapsulated tuna oil.

Intelligent Control of a Sensor-Actuator System via Kernelized Least-Squares Policy Iteration

PubMed Central

Liu, Bo; Chen, Sanfeng; Li, Shuai; Liang, Yongsheng

2012-01-01

In this paper a new framework, called Compressive Kernelized Reinforcement Learning (CKRL), for computing near-optimal policies in sequential decision making with uncertainty is proposed via incorporating the non-adaptive data-independent Random Projections and nonparametric Kernelized Least-squares Policy Iteration (KLSPI). Random Projections are a fast, non-adaptive dimensionality reduction framework in which high-dimensionality data is projected onto a random lower-dimension subspace via spherically random rotation and coordination sampling. KLSPI introduce kernel trick into the LSPI framework for Reinforcement Learning, often achieving faster convergence and providing automatic feature selection via various kernel sparsification approaches. In this approach, policies are computed in a low-dimensional subspace generated by projecting the high-dimensional features onto a set of random basis. We first show how Random Projections constitute an efficient sparsification technique and how our method often converges faster than regular LSPI, while at lower computational costs. Theoretical foundation underlying this approach is a fast approximation of Singular Value Decomposition (SVD). Finally, simulation results are exhibited on benchmark MDP domains, which confirm gains both in computation time and in performance in large feature spaces. PMID:22736969

Development of high-accuracy convection schemes for sequential solvers

NASA Technical Reports Server (NTRS)

Thakur, Siddharth; Shyy, Wei

1993-01-01

An exploration is conducted of the applicability of such high resolution schemes as TVD to the resolving of sharp flow gradients using a sequential solution approach borrowed from pressure-based algorithms. It is shown that by extending these high-resolution shock-capturing schemes to a sequential solver that treats the equations as a collection of scalar conservation equations, the speed of signal propagation in the solution has to be coordinated by assigning the local convection speed as the characteristic speed for the entire system. A higher amount of dissipation is therefore needed to eliminate oscillations near discontinuities.

Evaluation of a Web-Based App Demonstrating an Exclusionary Algorithmic Approach to TNM Cancer Staging

PubMed Central

2015-01-01

Background TNM staging plays a critical role in the evaluation and management of a range of different types of cancers. The conventional combinatorial approach to the determination of an anatomic stage relies on the identification of distinct tumor (T), node (N), and metastasis (M) classifications to generate a TNM grouping. This process is inherently inefficient due to the need for scrupulous review of the criteria specified for each classification to ensure accurate assignment. An exclusionary approach to TNM staging based on sequential constraint of options may serve to minimize the number of classifications that need to be reviewed to accurately determine an anatomic stage. Objective Our aim was to evaluate the usability and utility of a Web-based app configured to demonstrate an exclusionary approach to TNM staging. Methods Internal medicine residents, surgery residents, and oncology fellows engaged in clinical training were asked to evaluate a Web-based app developed as an instructional aid incorporating (1) an exclusionary algorithm that polls tabulated classifications and sorts them into ranked order based on frequency counts, (2) reconfiguration of classification criteria to generate disambiguated yes/no questions that function as selection and exclusion prompts, and (3) a selectable grid of TNM groupings that provides dynamic graphic demonstration of the effects of sequentially selecting or excluding specific classifications. Subjects were asked to evaluate the performance of this app after completing exercises simulating the staging of different types of cancers encountered during training. Results Survey responses indicated high levels of agreement with statements supporting the usability and utility of this app. Subjects reported that its user interface provided a clear display with intuitive controls and that the exclusionary approach to TNM staging it demonstrated represented an efficient process of assignment that helped to clarify distinctions between tumor, node, and metastasis classifications. High overall usefulness ratings were bolstered by supplementary comments suggesting that this app might be readily adopted for use in clinical practice. Conclusions A Web-based app that utilizes an exclusionary algorithm to prompt the assignment of tumor, node, and metastasis classifications may serve as an effective instructional aid demonstrating an efficient and informative approach to TNM staging. PMID:28410163

Corrected Mean-Field Model for Random Sequential Adsorption on Random Geometric Graphs

NASA Astrophysics Data System (ADS)

Dhara, Souvik; van Leeuwaarden, Johan S. H.; Mukherjee, Debankur

2018-03-01

A notorious problem in mathematics and physics is to create a solvable model for random sequential adsorption of non-overlapping congruent spheres in the d-dimensional Euclidean space with d≥ 2 . Spheres arrive sequentially at uniformly chosen locations in space and are accepted only when there is no overlap with previously deposited spheres. Due to spatial correlations, characterizing the fraction of accepted spheres remains largely intractable. We study this fraction by taking a novel approach that compares random sequential adsorption in Euclidean space to the nearest-neighbor blocking on a sequence of clustered random graphs. This random network model can be thought of as a corrected mean-field model for the interaction graph between the attempted spheres. Using functional limit theorems, we characterize the fraction of accepted spheres and its fluctuations.

Space Station Human Factors: Designing a Human-Robot Interface

NASA Technical Reports Server (NTRS)

Rochlis, Jennifer L.; Clarke, John Paul; Goza, S. Michael

2001-01-01

The experiments described in this paper are part of a larger joint MIT/NASA research effort and focus on the development of a methodology for designing and evaluating integrated interfaces for highly dexterous and multifunctional telerobot. Specifically, a telerobotic workstation is being designed for an Extravehicular Activity (EVA) anthropomorphic space station telerobot called Robonaut. Previous researchers have designed telerobotic workstations based upon performance of discrete subsets of tasks (for example, peg-in-hole, tracking, etc.) without regard for transitions that operators go through between tasks performed sequentially in the context of larger integrated tasks. The experiments presented here took an integrated approach to describing teleoperator performance and assessed how subjects operating a full-immersion telerobot perform during fine position and gross position tasks. In addition, a Robonaut simulation was also developed as part of this research effort, and experimentally tested against Robonaut itself to determine its utility. Results show that subject performance of teleoperated tasks using both Robonaut and the simulation are virtually identical, with no significant difference between the two. These results indicate that the simulation can be utilized as both a Robonaut training tool, and as a powerful design platform for telepresence displays and aids.

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

Zhu, Lin; Dai, Zhenxue; Gong, Huili

Understanding the heterogeneity arising from the complex architecture of sedimentary sequences in alluvial fans is challenging. This study develops a statistical inverse framework in a multi-zone transition probability approach for characterizing the heterogeneity in alluvial fans. An analytical solution of the transition probability matrix is used to define the statistical relationships among different hydrofacies and their mean lengths, integral scales, and volumetric proportions. A statistical inversion is conducted to identify the multi-zone transition probability models and estimate the optimal statistical parameters using the modified Gauss–Newton–Levenberg–Marquardt method. The Jacobian matrix is computed by the sensitivity equation method, which results in anmore » accurate inverse solution with quantification of parameter uncertainty. We use the Chaobai River alluvial fan in the Beijing Plain, China, as an example for elucidating the methodology of alluvial fan characterization. The alluvial fan is divided into three sediment zones. In each zone, the explicit mathematical formulations of the transition probability models are constructed with optimized different integral scales and volumetric proportions. The hydrofacies distributions in the three zones are simulated sequentially by the multi-zone transition probability-based indicator simulations. Finally, the result of this study provides the heterogeneous structure of the alluvial fan for further study of flow and transport simulations.« less

Architecture and inherent robustness of a bacterial cell-cycle control system.

PubMed

Shen, Xiling; Collier, Justine; Dill, David; Shapiro, Lucy; Horowitz, Mark; McAdams, Harley H

2008-08-12

A closed-loop control system drives progression of the coupled stalked and swarmer cell cycles of the bacterium Caulobacter crescentus in a near-mechanical step-like fashion. The cell-cycle control has a cyclical genetic circuit composed of four regulatory proteins with tight coupling to processive chromosome replication and cell division subsystems. We report a hybrid simulation of the coupled cell-cycle control system, including asymmetric cell division and responses to external starvation signals, that replicates mRNA and protein concentration patterns and is consistent with observed mutant phenotypes. An asynchronous sequential digital circuit model equivalent to the validated simulation model was created. Formal model-checking analysis of the digital circuit showed that the cell-cycle control is robust to intrinsic stochastic variations in reaction rates and nutrient supply, and that it reliably stops and restarts to accommodate nutrient starvation. Model checking also showed that mechanisms involving methylation-state changes in regulatory promoter regions during DNA replication increase the robustness of the cell-cycle control. The hybrid cell-cycle simulation implementation is inherently extensible and provides a promising approach for development of whole-cell behavioral models that can replicate the observed functionality of the cell and its responses to changing environmental conditions.

A pseudo-sequential choice model for valuing multi-attribute environmental policies or programs in contingent valuation applications

Treesearch

Dmitriy Volinskiy; John C Bergstrom; Christopher M Cornwell; Thomas P Holmes

2010-01-01

The assumption of independence of irrelevant alternatives in a sequential contingent valuation format should be questioned. Statistically, most valuation studies treat nonindependence as a consequence of unobserved individual effects. Another approach is to consider an inferential process in which any particular choice is part of a general choosing strategy of a survey...

Inverse problems in 1D hemodynamics on systemic networks: a sequential approach.

PubMed

Lombardi, D

2014-02-01

In this work, a sequential approach based on the unscented Kalman filter is applied to solve inverse problems in 1D hemodynamics, on a systemic network. For instance, the arterial stiffness is estimated by exploiting cross-sectional area and mean speed observations in several locations of the arteries. The results are compared with those ones obtained by estimating the pulse wave velocity and the Moens-Korteweg formula. In the last section, a perspective concerning the identification of the terminal models parameters and peripheral circulation (modeled by a Windkessel circuit) is presented. Copyright © 2013 John Wiley & Sons, Ltd.

Particle filters, a quasi-Monte-Carlo-solution for segmentation of coronaries.

PubMed

Florin, Charles; Paragios, Nikos; Williams, Jim

2005-01-01

In this paper we propose a Particle Filter-based approach for the segmentation of coronary arteries. To this end, successive planes of the vessel are modeled as unknown states of a sequential process. Such states consist of the orientation, position, shape model and appearance (in statistical terms) of the vessel that are recovered in an incremental fashion, using a sequential Bayesian filter (Particle Filter). In order to account for bifurcations and branchings, we consider a Monte Carlo sampling rule that propagates in parallel multiple hypotheses. Promising results on the segmentation of coronary arteries demonstrate the potential of the proposed approach.

Exploration of two-enzyme coupled catalysis system using scanning electrochemical microscopy.

PubMed

Wu, Zeng-Qiang; Jia, Wen-Zhi; Wang, Kang; Xu, Jing-Juan; Chen, Hong-Yuan; Xia, Xing-Hua

2012-12-18

In biological metabolism, a given metabolic process usually occurs via a group of enzymes working together in sequential pathways. To explore the metabolism mechanism requires the understanding of the multienzyme coupled catalysis systems. In this paper, an approach has been proposed to study the kinetics of a two-enzyme coupled reaction using SECM combining numerical simulations. Acetylcholine esterase and choline oxidase are immobilized on cysteamine self-assembled monolayers on tip and substrate gold electrodes of SECM via electrostatic interactions, respectively. The reaction kinetics of this two-enzyme coupled system upon various separation distance precisely regulated by SECM are measured. An overall apparent Michaelis-Menten constant of this enzyme cascade is thus measured as 2.97 mM at an optimal tip-substrate gap distance of 18 μm. Then, a kinetic model of this enzyme cascade is established for evaluating the kinetic parameters of individual enzyme by using the finite element method. The simulated results demonstrate the choline oxidase catalytic reaction is the rate determining step of this enzyme cascade. The Michaelis-Menten constant of acetylcholine esterase is evaluated as 1.8 mM. This study offers a promising approach to exploring mechanism of other two-enzyme coupled reactions in biological system and would promote the development of biosensors and enzyme-based logic systems.

Syndrome Surveillance Using Parametric Space-Time Clustering

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

KOCH, MARK W.; MCKENNA, SEAN A.; BILISOLY, ROGER L.

2002-11-01

As demonstrated by the anthrax attack through the United States mail, people infected by the biological agent itself will give the first indication of a bioterror attack. Thus, a distributed information system that can rapidly and efficiently gather and analyze public health data would aid epidemiologists in detecting and characterizing emerging diseases, including bioterror attacks. We propose using clusters of adverse health events in space and time to detect possible bioterror attacks. Space-time clusters can indicate exposure to infectious diseases or localized exposure to toxins. Most space-time clustering approaches require individual patient data. To protect the patient's privacy, we havemore » extended these approaches to aggregated data and have embedded this extension in a sequential probability ratio test (SPRT) framework. The real-time and sequential nature of health data makes the SPRT an ideal candidate. The result of space-time clustering gives the statistical significance of a cluster at every location in the surveillance area and can be thought of as a ''health-index'' of the people living in this area. As a surrogate to bioterrorism data, we have experimented with two flu data sets. For both databases, we show that space-time clustering can detect a flu epidemic up to 21 to 28 days earlier than a conventional periodic regression technique. We have also tested using simulated anthrax attack data on top of a respiratory illness diagnostic category. Results show we do very well at detecting an attack as early as the second or third day after infected people start becoming severely symptomatic.« less

A comparison of two worlds: How does Bayes hold up to the status quo for the analysis of clinical trials?

PubMed

Pressman, Alice R; Avins, Andrew L; Hubbard, Alan; Satariano, William A

2011-07-01

There is a paucity of literature comparing Bayesian analytic techniques with traditional approaches for analyzing clinical trials using real trial data. We compared Bayesian and frequentist group sequential methods using data from two published clinical trials. We chose two widely accepted frequentist rules, O'Brien-Fleming and Lan-DeMets, and conjugate Bayesian priors. Using the nonparametric bootstrap, we estimated a sampling distribution of stopping times for each method. Because current practice dictates the preservation of an experiment-wise false positive rate (Type I error), we approximated these error rates for our Bayesian and frequentist analyses with the posterior probability of detecting an effect in a simulated null sample. Thus for the data-generated distribution represented by these trials, we were able to compare the relative performance of these techniques. No final outcomes differed from those of the original trials. However, the timing of trial termination differed substantially by method and varied by trial. For one trial, group sequential designs of either type dictated early stopping of the study. In the other, stopping times were dependent upon the choice of spending function and prior distribution. Results indicate that trialists ought to consider Bayesian methods in addition to traditional approaches for analysis of clinical trials. Though findings from this small sample did not demonstrate either method to consistently outperform the other, they did suggest the need to replicate these comparisons using data from varied clinical trials in order to determine the conditions under which the different methods would be most efficient. Copyright © 2011 Elsevier Inc. All rights reserved.

A comparison of two worlds: How does Bayes hold up to the status quo for the analysis of clinical trials?

PubMed Central

Pressman, Alice R.; Avins, Andrew L.; Hubbard, Alan; Satariano, William A.

2014-01-01

Background There is a paucity of literature comparing Bayesian analytic techniques with traditional approaches for analyzing clinical trials using real trial data. Methods We compared Bayesian and frequentist group sequential methods using data from two published clinical trials. We chose two widely accepted frequentist rules, O'Brien–Fleming and Lan–DeMets, and conjugate Bayesian priors. Using the nonparametric bootstrap, we estimated a sampling distribution of stopping times for each method. Because current practice dictates the preservation of an experiment-wise false positive rate (Type I error), we approximated these error rates for our Bayesian and frequentist analyses with the posterior probability of detecting an effect in a simulated null sample. Thus for the data-generated distribution represented by these trials, we were able to compare the relative performance of these techniques. Results No final outcomes differed from those of the original trials. However, the timing of trial termination differed substantially by method and varied by trial. For one trial, group sequential designs of either type dictated early stopping of the study. In the other, stopping times were dependent upon the choice of spending function and prior distribution. Conclusions Results indicate that trialists ought to consider Bayesian methods in addition to traditional approaches for analysis of clinical trials. Though findings from this small sample did not demonstrate either method to consistently outperform the other, they did suggest the need to replicate these comparisons using data from varied clinical trials in order to determine the conditions under which the different methods would be most efficient. PMID:21453792

Inferring species divergence times using pairwise sequential Markovian coalescent modelling and low-coverage genomic data.

PubMed

Cahill, James A; Soares, André E R; Green, Richard E; Shapiro, Beth

2016-07-19

Understanding when species diverged aids in identifying the drivers of speciation, but the end of gene flow between populations can be difficult to ascertain from genetic data. We explore the use of pairwise sequential Markovian coalescent (PSMC) modelling to infer the timing of divergence between species and populations. PSMC plots generated using artificial hybrid genomes show rapid increases in effective population size at the time when the two parent lineages diverge, and this approach has been used previously to infer divergence between human lineages. We show that, even without high coverage or phased input data, PSMC can detect the end of significant gene flow between populations by comparing the PSMC output from artificial hybrids to the output of simulations with known demographic histories. We then apply PSMC to detect divergence times among lineages within two real datasets: great apes and bears within the genus Ursus Our results confirm most previously proposed divergence times for these lineages, and suggest that gene flow between recently diverged lineages may have been common among bears and great apes, including up to one million years of continued gene flow between chimpanzees and bonobos after the formation of the Congo River.This article is part of the themed issue 'Dating species divergences using rocks and clocks'. © 2016 The Author(s).

Memetic computing through bio-inspired heuristics integration with sequential quadratic programming for nonlinear systems arising in different physical models.

PubMed

Raja, Muhammad Asif Zahoor; Kiani, Adiqa Kausar; Shehzad, Azam; Zameer, Aneela

2016-01-01

In this study, bio-inspired computing is exploited for solving system of nonlinear equations using variants of genetic algorithms (GAs) as a tool for global search method hybrid with sequential quadratic programming (SQP) for efficient local search. The fitness function is constructed by defining the error function for systems of nonlinear equations in mean square sense. The design parameters of mathematical models are trained by exploiting the competency of GAs and refinement are carried out by viable SQP algorithm. Twelve versions of the memetic approach GA-SQP are designed by taking a different set of reproduction routines in the optimization process. Performance of proposed variants is evaluated on six numerical problems comprising of system of nonlinear equations arising in the interval arithmetic benchmark model, kinematics, neurophysiology, combustion and chemical equilibrium. Comparative studies of the proposed results in terms of accuracy, convergence and complexity are performed with the help of statistical performance indices to establish the worth of the schemes. Accuracy and convergence of the memetic computing GA-SQP is found better in each case of the simulation study and effectiveness of the scheme is further established through results of statistics based on different performance indices for accuracy and complexity.

Controlled pattern imputation for sensitivity analysis of longitudinal binary and ordinal outcomes with nonignorable dropout.

PubMed

Tang, Yongqiang

2018-04-30

The controlled imputation method refers to a class of pattern mixture models that have been commonly used as sensitivity analyses of longitudinal clinical trials with nonignorable dropout in recent years. These pattern mixture models assume that participants in the experimental arm after dropout have similar response profiles to the control participants or have worse outcomes than otherwise similar participants who remain on the experimental treatment. In spite of its popularity, the controlled imputation has not been formally developed for longitudinal binary and ordinal outcomes partially due to the lack of a natural multivariate distribution for such endpoints. In this paper, we propose 2 approaches for implementing the controlled imputation for binary and ordinal data based respectively on the sequential logistic regression and the multivariate probit model. Efficient Markov chain Monte Carlo algorithms are developed for missing data imputation by using the monotone data augmentation technique for the sequential logistic regression and a parameter-expanded monotone data augmentation scheme for the multivariate probit model. We assess the performance of the proposed procedures by simulation and the analysis of a schizophrenia clinical trial and compare them with the fully conditional specification, last observation carried forward, and baseline observation carried forward imputation methods. Copyright © 2018 John Wiley & Sons, Ltd.

A sequential linear optimization approach for controller design

NASA Technical Reports Server (NTRS)

Horta, L. G.; Juang, J.-N.; Junkins, J. L.

1985-01-01

A linear optimization approach with a simple real arithmetic algorithm is presented for reliable controller design and vibration suppression of flexible structures. Using first order sensitivity of the system eigenvalues with respect to the design parameters in conjunction with a continuation procedure, the method converts a nonlinear optimization problem into a maximization problem with linear inequality constraints. The method of linear programming is then applied to solve the converted linear optimization problem. The general efficiency of the linear programming approach allows the method to handle structural optimization problems with a large number of inequality constraints on the design vector. The method is demonstrated using a truss beam finite element model for the optimal sizing and placement of active/passive-structural members for damping augmentation. Results using both the sequential linear optimization approach and nonlinear optimization are presented and compared. The insensitivity to initial conditions of the linear optimization approach is also demonstrated.

Study the effect of reservoir spatial heterogeneity on CO2 sequestration under an uncertainty quantification (UQ) software framework

NASA Astrophysics Data System (ADS)

Fang, Y.; Hou, J.; Engel, D.; Lin, G.; Yin, J.; Han, B.; Fang, Z.; Fountoulakis, V.

2011-12-01

In this study, we introduce an uncertainty quantification (UQ) software framework for carbon sequestration, with the focus of studying being the effect of spatial heterogeneity of reservoir properties on CO2 migration. We use a sequential Gaussian method (SGSIM) to generate realizations of permeability fields with various spatial statistical attributes. To deal with the computational difficulties, we integrate the following ideas/approaches: 1) firstly, we use three different sampling approaches (probabilistic collocation, quasi-Monte Carlo, and adaptive sampling approaches) to reduce the required forward calculations while trying to explore the parameter space and quantify the input uncertainty; 2) secondly, we use eSTOMP as the forward modeling simulator. eSTOMP is implemented using the Global Arrays toolkit (GA) that is based on one-sided inter-processor communication and supports a shared memory programming style on distributed memory platforms. It provides highly-scalable performance. It uses a data model to partition most of the large scale data structures into a relatively small number of distinct classes. The lower level simulator infrastructure (e.g. meshing support, associated data structures, and data mapping to processors) is separated from the higher level physics and chemistry algorithmic routines using a grid component interface; and 3) besides the faster model and more efficient algorithms to speed up the forward calculation, we built an adaptive system infrastructure to select the best possible data transfer mechanisms, to optimally allocate system resources to improve performance, and to integrate software packages and data for composing carbon sequestration simulation, computation, analysis, estimation and visualization. We will demonstrate the framework with a given CO2 injection scenario in a heterogeneous sandstone reservoir.

Three-Stage Production Cost Modeling Approach for Evaluating the Benefits of Intra-Hour Scheduling between Balancing Authorities

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

Samaan, Nader A.; Milligan, Michael; Hunsaker, Matthew

This paper introduces a Production Cost Modeling (PCM) approach to evaluate the benefits of intra-hour scheduling between Balancing Authorities (BAs). The system operation is modeled in a three-stage sequential manner: day ahead (DA)-hour ahead (HA)-real time (RT). In addition to contingency reserve, each BA will need to carry out “up” and “down” load following and regulation reserve capacity requirements in the DA and HA time frames. In the real-time simulation, only contingency and regulation reserves are carried out as load following is deployed. To model current real-time operation with hourly schedules, a new constraint was introduced to force each BAmore » net exchange schedule deviation from HA schedules to be within NERC ACE limits. Case studies that investigate the benefits of moving from hourly exchange schedules between WECC BAs into 10-min exchange schedules under two different levels of wind and solar penetration (11% and 33%) are presented.« less

Three-Stage Production Cost Modeling Approach for Evaluating the Benefits of Intra-Hour Scheduling Between Balancing Authorities

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

Samaan, Nader; Milligan, Michael; Hunsaker, Matt

This paper introduces a production cost modeling approach for evaluating the benefits of intra-hour scheduling among Balancing Authorities (BAs). System operation is modeled in a three-stage sequential manner: day ahead (DA)-hour ahead (HA) real time (RT). In addition to contingency reserve, each BA will need to carry out 'up' and 'down' load following and regulation reserve capacity requirements in the DA and HA time frames. In the RT simulation, only contingency and regulation reserves are carried out as load following is deployed. To model current RT operation with hourly schedules, a new constraint was introduced to force each BA netmore » exchange schedule deviation from HA schedules to be within North American Electric Reliability Corporation (NERC) area control error (ACE) limits. Case studies that investigate the benefits of moving from hourly exchange schedules between Western Electricity Coordinating Council (WECC) BAs into 10-minute exchange schedules under two different levels of wind and solar penetration (11% and 33%) are presented.« less

Sequential processing of GNSS-R delay-Doppler maps (DDM's) for ocean wind retrieval

NASA Astrophysics Data System (ADS)

Garrison, J. L.; Rodriguez-Alvarez, N.; Hoffman, R.; Annane, B.; Leidner, M.; Kaitie, S.

2016-12-01

The delay-Doppler map (DDM) is the fundamental data product from GNSS-Reflectometry (GNSS-R), generated by cross-correlating the scattered signal with a local signal model over a range of delays and Doppler frequencies. Delay and Doppler form a set of coordinates on the ocean surface and the shape of the DDM is related to the distribution of ocean slopes. Wind speed can thus be estimated by fitting a scattering model to the shape of the observed DDM or defining an observable (e.g. average power or leading edge slope) which characterizes the change in DDM shape. For spaceborne measurements, the DDM is composed of signals scattered from a glistening zone, which can extend for up to 100 km or more. Setting a reasonable resolution requirement (25 km or less) will limit the usable portion of the DDM at each observation to only a small region near the specular point. Cyclone-GNSS (CYGNSS) is a NASA mission to study developing tropical cyclones using GNSS-R. CYGNSS science requirements call for wind retrieval with an accuracy of 10 percent above 20 m/s within a 25 km resolution. This requirement can be met using an observable defined for DDM samples between +/- 0.25 chips in delay and +/- 1 kHz in Doppler, with some filtering of the observations using a minimum threshold for range corrected gain (RCG). An improved approach, to be reviewed in this presentation, sequentially processes multiple DDM's, to combine observations generated from different "looks" at the same points on the surface. Applying this sequential process to synthetic data indicates a significant improvement in wind retrieval accuracy over a 10 km grid covering a region around the specular point. The attached figure illustrates this improvement, using simulated CYGNSS DDM's generated using the wind fields from hurricanes Earl and Danielle (left). The middle plots show wind retrievals using only an observable defined within the 25 km resolution cell. The plots on the right side show the retrievals from sequential processing of multiple DDM's. Recently, the assimilation of GNSS-R retrievals into weather forecast models has been studied. The authors have begun to investigate the direct assimilation of other data products, such as the DDM itself, or the results of sequential processing.

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

PubMed

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 association between lameness prevalence and the proportion of lame cows that were severely lame on a farm was found. However, as this association was found to not be consistent across all farms, the sampling scheme did not prove to be as useful as expected. The preferred scheme was therefore the 'cautious' scheme for which a sampling protocol has also been developed.

Characterizing the structure and content of nurse handoffs: A Sequential Conversational Analysis approach.

PubMed

Abraham, Joanna; Kannampallil, Thomas; Brenner, Corinne; Lopez, Karen D; Almoosa, Khalid F; Patel, Bela; Patel, Vimla L

2016-02-01

Effective communication during nurse handoffs is instrumental in ensuring safe and quality patient care. Much of the prior research on nurse handoffs has utilized retrospective methods such as interviews, surveys and questionnaires. While extremely useful, an in-depth understanding of the structure and content of conversations, and the inherent relationships within the content is paramount to designing effective nurse handoff interventions. In this paper, we present a methodological framework-Sequential Conversational Analysis (SCA)-a mixed-method approach that integrates qualitative conversational analysis with quantitative sequential pattern analysis. We describe the SCA approach and provide a detailed example as a proof of concept of its use for the analysis of nurse handoff communication in a medical intensive care unit. This novel approach allows us to characterize the conversational structure, clinical content, disruptions in the conversation, and the inherently phasic nature of nurse handoff communication. The characterization of communication patterns highlights the relationships underlying the verbal content of nurse handoffs with specific emphasis on: the interactive nature of conversation, relevance of role-based (incoming, outgoing) communication requirements, clinical content focus on critical patient-related events, and discussion of pending patient management tasks. We also discuss the applicability of the SCA approach as a method for providing in-depth understanding of the dynamics of communication in other settings and domains. Copyright © 2015 Elsevier Inc. All rights reserved.

[Not Available].

PubMed

Paturzo, Marco; Colaceci, Sofia; Clari, Marco; Mottola, Antonella; Alvaro, Rosaria; Vellone, Ercole

2016-01-01

. Mixed methods designs: an innovative methodological approach for nursing research. The mixed method research designs (MM) combine qualitative and quantitative approaches in the research process, in a single study or series of studies. Their use can provide a wider understanding of multifaceted phenomena. This article presents a general overview of the structure and design of MM to spread this approach in the Italian nursing research community. The MM designs most commonly used in the nursing field are the convergent parallel design, the sequential explanatory design, the exploratory sequential design and the embedded design. For each method a research example is presented. The use of MM can be an added value to improve clinical practices as, through the integration of qualitative and quantitative methods, researchers can better assess complex phenomena typical of nursing.

Kurtosis-Based Blind Source Extraction of Complex Non-Circular Signals with Application in EEG Artifact Removal in Real-Time

PubMed Central

Javidi, Soroush; Mandic, Danilo P.; Took, Clive Cheong; Cichocki, Andrzej

2011-01-01

A new class of complex domain blind source extraction algorithms suitable for the extraction of both circular and non-circular complex signals is proposed. This is achieved through sequential extraction based on the degree of kurtosis and in the presence of non-circular measurement noise. The existence and uniqueness analysis of the solution is followed by a study of fast converging variants of the algorithm. The performance is first assessed through simulations on well understood benchmark signals, followed by a case study on real-time artifact removal from EEG signals, verified using both qualitative and quantitative metrics. The results illustrate the power of the proposed approach in real-time blind extraction of general complex-valued sources. PMID:22319461

Artificial heart for humanoid robot using coiled SMA actuators

NASA Astrophysics Data System (ADS)

Potnuru, Akshay; Tadesse, Yonas

2015-03-01

Previously, we have presented the design and characterization of artificial heart using cylindrical shape memory alloy (SMA) actuators for humanoids [1]. The robotic heart was primarily designed to pump a blood-like fluid to parts of the robot such as the face to simulate blushing or anger by the use of elastomeric substrates for the transport of fluids. It can also be used for other applications. In this paper, we present an improved design by using high strain coiled SMAs and a novel pumping mechanism that uses sequential actuation to create peristalsis-like motions, and hence pump the fluid. Various placements of actuators will be investigated with respect to the silicone elastomeric body. This new approach provides a better performance in terms of the fluid volume pumped.

Bayesian Treatment of Uncertainty in Environmental Modeling: Optimization, Sampling and Data Assimilation Using the DREAM Software Package

NASA Astrophysics Data System (ADS)

Vrugt, J. A.

2012-12-01

In the past decade much progress has been made in the treatment of uncertainty in earth systems modeling. Whereas initial approaches has focused mostly on quantification of parameter and predictive uncertainty, recent methods attempt to disentangle the effects of parameter, forcing (input) data, model structural and calibration data errors. In this talk I will highlight some of our recent work involving theory, concepts and applications of Bayesian parameter and/or state estimation. In particular, new methods for sequential Monte Carlo (SMC) and Markov Chain Monte Carlo (MCMC) simulation will be presented with emphasis on massively parallel distributed computing and quantification of model structural errors. The theoretical and numerical developments will be illustrated using model-data synthesis problems in hydrology, hydrogeology and geophysics.

Domain-general neural correlates of dependency formation: Using complex tones to simulate language.

PubMed

Brilmayer, Ingmar; Sassenhagen, Jona; Bornkessel-Schlesewsky, Ina; Schlesewsky, Matthias

2017-08-01

There is an ongoing debate whether the P600 event-related potential component following syntactic anomalies reflects syntactic processes per se, or if it is an instance of the P300, a domain-general ERP component associated with attention and cognitive reorientation. A direct comparison of both components is challenging because of the huge discrepancy in experimental designs and stimulus choice between language and 'classic' P300 experiments. In the present study, we develop a new approach to mimic the interplay of sequential position as well as categorical and relational information in natural language syntax (word category and agreement) in a non-linguistic target detection paradigm using musical instruments. Participants were instructed to (covertly) detect target tones which were defined by instrument change and pitch rise between subsequent tones at the last two positions of four-tone sequences. We analysed the EEG using event-related averaging and time-frequency decomposition. Our results show striking similarities to results obtained from linguistic experiments. We found a P300 that showed sensitivity to sequential position and a late positivity sensitive to stimulus type and position. A time-frequency decomposition revealed significant effects of sequential position on the theta band and a significant influence of stimulus type on the delta band. Our results suggest that the detection of non-linguistic targets defined via complex feature conjunctions in the present study and the detection of syntactic anomalies share the same underlying processes: attentional shift and memory based matching processes that act upon multi-feature conjunctions. We discuss the results as supporting domain-general accounts of the P600 during natural language comprehension. Copyright © 2017 Elsevier Ltd. All rights reserved.

Miniaturizing and automation of free acidity measurements for uranium (VI)-HNO3 solutions: Development of a new sequential injection analysis for a sustainable radio-analytical chemistry.

PubMed

Néri-Quiroz, José; Canto, Fabrice; Guillerme, Laurent; Couston, Laurent; Magnaldo, Alastair; Dugas, Vincent

2016-10-01

A miniaturized and automated approach for the determination of free acidity in solutions containing uranium (VI) is presented. The measurement technique is based on the concept of sequential injection analysis with on-line spectroscopic detection. The proposed methodology relies on the complexation and alkalimetric titration of nitric acid using a pH 5.6 sodium oxalate solution. The titration process is followed by UV/VIS detection at 650nm thanks to addition of Congo red as universal pH indicator. Mixing sequence as well as method validity was investigated by numerical simulation. This new analytical design allows fast (2.3min), reliable and accurate free acidity determination of low volume samples (10µL) containing uranium/[H(+)] moles ratio of 1:3 with relative standard deviation of <7.0% (n=11). The linearity range of the free nitric acid measurement is excellent up to 2.77molL(-1) with a correlation coefficient (R(2)) of 0.995. The method is specific, presence of actinide ions up to 0.54molL(-1) does not interfere on the determination of free nitric acid. In addition to automation, the developed sequential injection analysis method greatly improves the standard off-line oxalate complexation and alkalimetric titration method by reducing thousand fold the required sample volume, forty times the nuclear waste per analysis as well as the analysis time by eight fold. These analytical parameters are important especially in nuclear-related applications to improve laboratory safety, personnel exposure to radioactive samples and to drastically reduce environmental impacts or analytical radioactive waste. Copyright © 2016 Elsevier B.V. All rights reserved.

A three-dimensional quality-guided phase unwrapping method for MR elastography

NASA Astrophysics Data System (ADS)

Wang, Huifang; Weaver, John B.; Perreard, Irina I.; Doyley, Marvin M.; Paulsen, Keith D.

2011-07-01

Magnetic resonance elastography (MRE) uses accumulated phases that are acquired at multiple, uniformly spaced relative phase offsets, to estimate harmonic motion information. Heavily wrapped phase occurs when the motion is large and unwrapping procedures are necessary to estimate the displacements required by MRE. Two unwrapping methods were developed and compared in this paper. The first method is a sequentially applied approach. The three-dimensional MRE phase image block for each slice was processed by two-dimensional unwrapping followed by a one-dimensional phase unwrapping approach along the phase-offset direction. This unwrapping approach generally works well for low noise data. However, there are still cases where the two-dimensional unwrapping method fails when noise is high. In this case, the baseline of the corrupted regions within an unwrapped image will not be consistent. Instead of separating the two-dimensional and one-dimensional unwrapping in a sequential approach, an interleaved three-dimensional quality-guided unwrapping method was developed to combine both the two-dimensional phase image continuity and one-dimensional harmonic motion information. The quality of one-dimensional harmonic motion unwrapping was used to guide the three-dimensional unwrapping procedures and it resulted in stronger guidance than in the sequential method. In this work, in vivo results generated by the two methods were compared.

Evaluating Snow Data Assimilation Framework for Streamflow Forecasting Applications Using Hindcast Verification

NASA Astrophysics Data System (ADS)

Barik, M. G.; Hogue, T. S.; Franz, K. J.; He, M.

2012-12-01

Snow water equivalent (SWE) estimation is a key factor in producing reliable streamflow simulations and forecasts in snow dominated areas. However, measuring or predicting SWE has significant uncertainty. Sequential data assimilation, which updates states using both observed and modeled data based on error estimation, has been shown to reduce streamflow simulation errors but has had limited testing for forecasting applications. In the current study, a snow data assimilation framework integrated with the National Weather System River Forecasting System (NWSRFS) is evaluated for use in ensemble streamflow prediction (ESP). Seasonal water supply ESP hindcasts are generated for the North Fork of the American River Basin (NFARB) in northern California. Parameter sets from the California Nevada River Forecast Center (CNRFC), the Differential Evolution Adaptive Metropolis (DREAM) algorithm and the Multistep Automated Calibration Scheme (MACS) are tested both with and without sequential data assimilation. The traditional ESP method considers uncertainty in future climate conditions using historical temperature and precipitation time series to generate future streamflow scenarios conditioned on the current basin state. We include data uncertainty analysis in the forecasting framework through the DREAM-based parameter set which is part of a recently developed Integrated Uncertainty and Ensemble-based data Assimilation framework (ICEA). Extensive verification of all tested approaches is undertaken using traditional forecast verification measures, including root mean square error (RMSE), Nash-Sutcliffe efficiency coefficient (NSE), volumetric bias, joint distribution, rank probability score (RPS), and discrimination and reliability plots. In comparison to the RFC parameters, the DREAM and MACS sets show significant improvement in volumetric bias in flow. Use of assimilation improves hindcasts of higher flows but does not significantly improve performance in the mid flow and low flow categories.

Durable graft-versus-leukaemia effects without donor lymphocyte infusions - results of a phase II study of sequential T-replete allogeneic transplantation for high-risk acute myeloid leukaemia and myelodysplasia.

PubMed

Davies, Jeff K; Hassan, Sandra; Sarker, Shah-Jalal; Besley, Caroline; Oakervee, Heather; Smith, Matthew; Taussig, David; Gribben, John G; Cavenagh, Jamie D

2018-02-01

Allogeneic haematopoietic stem-cell transplantation remains the only curative treatment for relapsed/refractory acute myeloid leukaemia (AML) and high-risk myelodysplasia but has previously been limited to patients who achieve remission before transplant. New sequential approaches employing T-cell depleted transplantation directly after chemotherapy show promise but are burdened by viral infection and require donor lymphocyte infusions (DLI) to augment donor chimerism and graft-versus-leukaemia effects. T-replete transplantation in sequential approaches could reduce both viral infection and DLI usage. We therefore performed a single-arm prospective Phase II clinical trial of sequential chemotherapy and T-replete transplantation using reduced-intensity conditioning without planned DLI. The primary endpoint was overall survival. Forty-seven patients with relapsed/refractory AML or high-risk myelodysplasia were enrolled; 43 proceeded to transplantation. High levels of donor chimerism were achieved spontaneously with no DLI. Overall survival of transplanted patients was 45% and 33% at 1 and 3 years. Only one patient developed cytomegalovirus disease. Cumulative incidences of treatment-related mortality and relapse were 35% and 20% at 1 year. Patients with relapsed AML and myelodysplasia had the most favourable outcomes. Late-onset graft-versus-host disease protected against relapse. In conclusion, a T-replete sequential transplantation using reduced-intensity conditioning is feasible for relapsed/refractory AML and myelodysplasia and can deliver graft-versus-leukaemia effects without DLI. © 2017 John Wiley & Sons Ltd.

Cluster designs to assess the prevalence of acute malnutrition by lot quality assurance sampling: a validation study by computer simulation.

PubMed

Olives, Casey; Pagano, Marcello; Deitchler, Megan; Hedt, Bethany L; Egge, Kari; Valadez, Joseph J

2009-04-01

Traditional lot quality assurance sampling (LQAS) methods require simple random sampling to guarantee valid results. However, cluster sampling has been proposed to reduce the number of random starting points. This study uses simulations to examine the classification error of two such designs, a 67x3 (67 clusters of three observations) and a 33x6 (33 clusters of six observations) sampling scheme to assess the prevalence of global acute malnutrition (GAM). Further, we explore the use of a 67x3 sequential sampling scheme for LQAS classification of GAM prevalence. Results indicate that, for independent clusters with moderate intracluster correlation for the GAM outcome, the three sampling designs maintain approximate validity for LQAS analysis. Sequential sampling can substantially reduce the average sample size that is required for data collection. The presence of intercluster correlation can impact dramatically the classification error that is associated with LQAS analysis.

SMA texture and reorientation: simulations and neutron diffraction studies

NASA Astrophysics Data System (ADS)

Gao, Xiujie; Brown, Donald W.; Brinson, L. Catherine

2005-05-01

With increased usage of shape memory alloys (SMA) for applications in various fields, it is important to understand how the material behavior is affected by factors such as texture, stress state and loading history, especially for complex multiaxial loading states. Using the in-situ neutron diffraction loading facility (SMARTS diffractometer) and ex situ inverse pole figure measurement facility (HIPPO diffractometer) at the Los Alamos Neutron Science Center (LANCE), the macroscopic mechanical behavior and texture evolution of Nickel-Titanium (Nitinol) SMAs under sequential compression in alternating directions were studied. The simplified multivariant model developed at Northwestern University was then used to simulate the macroscopic behavior and the microstructural change of Nitinol under this sequential loading. Pole figures were obtained via post-processing of the multivariant results for volume fraction evolution and compared quantitatively well to the experimental results. The experimental results can also be used to test or verify other SMA constitutive models.

The Constructivist Approach? I Have Heard about It but I Have Never Seen It: "An Example of Exploratory Sequential Mixed Design Study"

ERIC Educational Resources Information Center

Polat, Ahmet; Dogan, Soner; Demir, Selçuk Besir

2016-01-01

The present study was undertaken to investigate the quality of education based on the views of the students attending social studies education departments at the Faculties of Education and to determine the existing problems and present suggestions for their solutions. The study was conducted according to exploratory sequential mixed method. In…

The Constructivist Approach? I Have Heard about It but I Have Never Seen It "An Example of Exploratory Sequential Mixed Design Study"

ERIC Educational Resources Information Center

Polat, Ahmet; Dogan, Soner; Demir, Selçuk Besir

2016-01-01

The present study was undertaken to investigate the quality of education based on the views of the students attending social studies education departments at the Faculties of Education and to determine the existing problems and present suggestions for their solutions. The study was conducted according to exploratory sequential mixed method. In…

Concurrent Learning of Control in Multi agent Sequential Decision Tasks

DTIC Science & Technology

2018-04-17

Concurrent Learning of Control in Multi-agent Sequential Decision Tasks The overall objective of this project was to develop multi-agent reinforcement...learning (MARL) approaches for intelligent agents to autonomously learn distributed control policies in decentral- ized partially observable...shall be subject to any oenalty for failing to comply with a collection of information if it does not display a currently valid OMB control number

Dispersion Analysis Using Particle Tracking Simulations Through Heterogeneity Based on Outcrop Lidar Imagery

NASA Astrophysics Data System (ADS)

Klise, K. A.; Weissmann, G. S.; McKenna, S. A.; Tidwell, V. C.; Frechette, J. D.; Wawrzyniec, T. F.

2007-12-01

Solute plumes are believed to disperse in a non-Fickian manner due to small-scale heterogeneity and variable velocities that create preferential pathways. In order to accurately predict dispersion in naturally complex geologic media, the connection between heterogeneity and dispersion must be better understood. Since aquifer properties can not be measured at every location, it is common to simulate small-scale heterogeneity with random field generators based on a two-point covariance (e.g., through use of sequential simulation algorithms). While these random fields can produce preferential flow pathways, it is unknown how well the results simulate solute dispersion through natural heterogeneous media. To evaluate the influence that complex heterogeneity has on dispersion, we utilize high-resolution terrestrial lidar to identify and model lithofacies from outcrop for application in particle tracking solute transport simulations using RWHet. The lidar scan data are used to produce a lab (meter) scale two-dimensional model that captures 2-8 mm scale natural heterogeneity. Numerical simulations utilize various methods to populate the outcrop structure captured by the lidar-based image with reasonable hydraulic conductivity values. The particle tracking simulations result in residence time distributions used to evaluate the nature of dispersion through complex media. Particle tracking simulations through conductivity fields produced from the lidar images are then compared to particle tracking simulations through hydraulic conductivity fields produced from sequential simulation algorithms. Based on this comparison, the study aims to quantify the difference in dispersion when using realistic and simplified representations of aquifer heterogeneity. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Relative resilience to noise of standard and sequential approaches to measurement-based quantum computation

NASA Astrophysics Data System (ADS)

Gallagher, C. B.; Ferraro, A.

2018-05-01

A possible alternative to the standard model of measurement-based quantum computation (MBQC) is offered by the sequential model of MBQC—a particular class of quantum computation via ancillae. Although these two models are equivalent under ideal conditions, their relative resilience to noise in practical conditions is not yet known. We analyze this relationship for various noise models in the ancilla preparation and in the entangling-gate implementation. The comparison of the two models is performed utilizing both the gate infidelity and the diamond distance as figures of merit. Our results show that in the majority of instances the sequential model outperforms the standard one in regard to a universal set of operations for quantum computation. Further investigation is made into the performance of sequential MBQC in experimental scenarios, thus setting benchmarks for possible cavity-QED implementations.

Multi-objective design optimization of antenna structures using sequential domain patching with automated patch size determination

NASA Astrophysics Data System (ADS)

Koziel, Slawomir; Bekasiewicz, Adrian

2018-02-01

In this article, a simple yet efficient and reliable technique for fully automated multi-objective design optimization of antenna structures using sequential domain patching (SDP) is discussed. The optimization procedure according to SDP is a two-step process: (i) obtaining the initial set of Pareto-optimal designs representing the best possible trade-offs between considered conflicting objectives, and (ii) Pareto set refinement for yielding the optimal designs at the high-fidelity electromagnetic (EM) simulation model level. For the sake of computational efficiency, the first step is realized at the level of a low-fidelity (coarse-discretization) EM model by sequential construction and relocation of small design space segments (patches) in order to create a path connecting the extreme Pareto front designs obtained beforehand. The second stage involves response correction techniques and local response surface approximation models constructed by reusing EM simulation data acquired in the first step. A major contribution of this work is an automated procedure for determining the patch dimensions. It allows for appropriate selection of the number of patches for each geometry variable so as to ensure reliability of the optimization process while maintaining its low cost. The importance of this procedure is demonstrated by comparing it with uniform patch dimensions.

Computational time analysis of the numerical solution of 3D electrostatic Poisson's equation

NASA Astrophysics Data System (ADS)

Kamboh, Shakeel Ahmed; Labadin, Jane; Rigit, Andrew Ragai Henri; Ling, Tech Chaw; Amur, Khuda Bux; Chaudhary, Muhammad Tayyab

2015-05-01

3D Poisson's equation is solved numerically to simulate the electric potential in a prototype design of electrohydrodynamic (EHD) ion-drag micropump. Finite difference method (FDM) is employed to discretize the governing equation. The system of linear equations resulting from FDM is solved iteratively by using the sequential Jacobi (SJ) and sequential Gauss-Seidel (SGS) methods, simulation results are also compared to examine the difference between the results. The main objective was to analyze the computational time required by both the methods with respect to different grid sizes and parallelize the Jacobi method to reduce the computational time. In common, the SGS method is faster than the SJ method but the data parallelism of Jacobi method may produce good speedup over SGS method. In this study, the feasibility of using parallel Jacobi (PJ) method is attempted in relation to SGS method. MATLAB Parallel/Distributed computing environment is used and a parallel code for SJ method is implemented. It was found that for small grid size the SGS method remains dominant over SJ method and PJ method while for large grid size both the sequential methods may take nearly too much processing time to converge. Yet, the PJ method reduces computational time to some extent for large grid sizes.

Orbit Determination and Maneuver Detection Using Event Representation with Thrust-Fourier-Coefficients

NASA Astrophysics Data System (ADS)

Lubey, D.; Ko, H.; Scheeres, D.

The classical orbit determination (OD) method of dealing with unknown maneuvers is to restart the OD process with post-maneuver observations. However, it is also possible to continue the OD process through such unknown maneuvers by representing those unknown maneuvers with an appropriate event representation. It has been shown in previous work (Ko & Scheeres, JGCD 2014) that any maneuver performed by a satellite transitioning between two arbitrary orbital states can be represented as an equivalent maneuver connecting those two states using Thrust-Fourier-Coefficients (TFCs). Event representation using TFCs rigorously provides a unique control law that can generate the desired secular behavior for a given unknown maneuver. This paper presents applications of this representation approach to orbit prediction and maneuver detection problem across unknown maneuvers. The TFCs are appended to a sequential filter as an adjoint state to compensate unknown perturbing accelerations and the modified filter estimates the satellite state and thrust coefficients by processing OD across the time of an unknown maneuver. This modified sequential filter with TFCs is capable of fitting tracking data and maintaining an OD solution in the presence of unknown maneuvers. Also, the modified filter is found effective in detecting a sudden change in TFC values which indicates a maneuver. In order to illustrate that the event representation approach with TFCs is robust and sufficiently general to be easily adjustable, different types of measurement data are processed with the filter in a realistic LEO setting. Further, cases with mis-modeling of non-gravitational force are included in our study to verify the versatility and efficiency of our presented algorithm. Simulation results show that the modified sequential filter with TFCs can detect and estimate the orbit and thrust parameters in the presence of unknown maneuvers with or without measurement data during maneuvers. With no measurement data during maneuvers, the modified filter with TFCs uses an existing pre-maneuver orbit solution to compute a post-maneuver orbit solution by forcing TFCs to compensate for an unknown maneuver. With observation data available during maneuvers, maneuver start time and stop time is determined

GOST: A generic ordinal sequential trial design for a treatment trial in an emerging pandemic.

PubMed

Whitehead, John; Horby, Peter

2017-03-01

Conducting clinical trials to assess experimental treatments for potentially pandemic infectious diseases is challenging. Since many outbreaks of infectious diseases last only six to eight weeks, there is a need for trial designs that can be implemented rapidly in the face of uncertainty. Outbreaks are sudden and unpredictable and so it is essential that as much planning as possible takes place in advance. Statistical aspects of such trial designs should be evaluated and discussed in readiness for implementation. This paper proposes a generic ordinal sequential trial design (GOST) for a randomised clinical trial comparing an experimental treatment for an emerging infectious disease with standard care. The design is intended as an off-the-shelf, ready-to-use robust and flexible option. The primary endpoint is a categorisation of patient outcome according to an ordinal scale. A sequential approach is adopted, stopping as soon as it is clear that the experimental treatment has an advantage or that sufficient advantage is unlikely to be detected. The properties of the design are evaluated using large-sample theory and verified for moderate sized samples using simulation. The trial is powered to detect a generic clinically relevant difference: namely an odds ratio of 2 for better rather than worse outcomes. Total sample sizes (across both treatments) of between 150 and 300 patients prove to be adequate in many cases, but the precise value depends on both the magnitude of the treatment advantage and the nature of the ordinal scale. An advantage of the approach is that any erroneous assumptions made at the design stage about the proportion of patients falling into each outcome category have little effect on the error probabilities of the study, although they can lead to inaccurate forecasts of sample size. It is important and feasible to pre-determine many of the statistical aspects of an efficient trial design in advance of a disease outbreak. The design can then be tailored to the specific disease under study once its nature is better understood.

Aeroelastic Modeling of Offshore Turbines and Support Structures in Hurricane-Prone Regions (Poster)

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

Damiani, R.

US offshore wind turbines (OWTs) will likely have to contend with hurricanes and the associated loading conditions. Current industry standards do not account for these design load cases (DLCs), thus a new approach is required to guarantee that the OWTs achieve an appropriate level of reliability. In this study, a sequentially coupled aero-hydro-servo-elastic modeling technique was used to address two design approaches: 1.) The ABS (American Bureau of Shipping) approach; and 2.) The Hazard Curve or API (American Petroleum Institute) approach. The former employs IEC partial load factors (PSFs) and 100-yr return-period (RP) metocean events. The latter allows setting PSFsmore » and RP to a prescribed level of system reliability. The 500-yr RP robustness check (appearing in [2] and [3] upcoming editions) is a good indicator of the target reliability for L2 structures. CAE tools such as NREL's FAST and Bentley's' SACS (offshore analysis and design software) can be efficiently coupled to simulate system loads under hurricane DLCs. For this task, we augmented the latest FAST version (v. 8) to include tower aerodynamic drag that cannot be ignored in hurricane DLCs. In this project, a 6 MW turbine was simulated on a typical 4-legged jacket for a mid-Atlantic site. FAST-calculated tower base loads were fed to SACS at the interface level (transition piece); SACS added hydrodynamic and wind loads on the exposed substructure, and calculated mudline overturning moments, and member and joint utilization. Results show that CAE tools can be effectively used to compare design approaches for the design of OWTs in hurricane regions and to achieve a well-balanced design, where reliability levels and costs are optimized.« less

Reliability based design optimization: Formulations and methodologies

NASA Astrophysics Data System (ADS)

Agarwal, Harish

Modern products ranging from simple components to complex systems should be designed to be optimal and reliable. The challenge of modern engineering is to ensure that manufacturing costs are reduced and design cycle times are minimized while achieving requirements for performance and reliability. If the market for the product is competitive, improved quality and reliability can generate very strong competitive advantages. Simulation based design plays an important role in designing almost any kind of automotive, aerospace, and consumer products under these competitive conditions. Single discipline simulations used for analysis are being coupled together to create complex coupled simulation tools. This investigation focuses on the development of efficient and robust methodologies for reliability based design optimization in a simulation based design environment. Original contributions of this research are the development of a novel efficient and robust unilevel methodology for reliability based design optimization, the development of an innovative decoupled reliability based design optimization methodology, the application of homotopy techniques in unilevel reliability based design optimization methodology, and the development of a new framework for reliability based design optimization under epistemic uncertainty. The unilevel methodology for reliability based design optimization is shown to be mathematically equivalent to the traditional nested formulation. Numerical test problems show that the unilevel methodology can reduce computational cost by at least 50% as compared to the nested approach. The decoupled reliability based design optimization methodology is an approximate technique to obtain consistent reliable designs at lesser computational expense. Test problems show that the methodology is computationally efficient compared to the nested approach. A framework for performing reliability based design optimization under epistemic uncertainty is also developed. A trust region managed sequential approximate optimization methodology is employed for this purpose. Results from numerical test studies indicate that the methodology can be used for performing design optimization under severe uncertainty.

Multiplexed Holographic Optical Data Storage In Thick Bacteriorhodopsin Films

NASA Technical Reports Server (NTRS)

Downie, John D.; Timucin, Dogan A.; Gary, Charles K.; Ozcan, Meric; Smithey, Daniel T.; Crew, Marshall

1998-01-01

The optical data storage capacity of photochromic bacteriorhodopsin films is investigated by means of theoretical calculations, numerical simulations, and experimental measurements on sequential recording of angularly multiplexed diffraction gratings inside a thick D85N BR film.

Statistical Emulator for Expensive Classification Simulators

NASA Technical Reports Server (NTRS)

Ross, Jerret; Samareh, Jamshid A.

2016-01-01

Expensive simulators prevent any kind of meaningful analysis to be performed on the phenomena they model. To get around this problem the concept of using a statistical emulator as a surrogate representation of the simulator was introduced in the 1980's. Presently, simulators have become more and more complex and as a result running a single example on these simulators is very expensive and can take days to weeks or even months. Many new techniques have been introduced, termed criteria, which sequentially select the next best (most informative to the emulator) point that should be run on the simulator. These criteria methods allow for the creation of an emulator with only a small number of simulator runs. We follow and extend this framework to expensive classification simulators.

Hemodynamic analysis of sequential graft from right coronary system to left coronary system.

PubMed

Wang, Wenxin; Mao, Boyan; Wang, Haoran; Geng, Xueying; Zhao, Xi; Zhang, Huixia; Xie, Jinsheng; Zhao, Zhou; Lian, Bo; Liu, Youjun

2016-12-28

Sequential and single grafting are two surgical procedures of coronary artery bypass grafting. However, it remains unclear if the sequential graft can be used between the right and left coronary artery system. The purpose of this paper is to clarify the possibility of right coronary artery system anastomosis to left coronary system. A patient-specific 3D model was first reconstructed based on coronary computed tomography angiography (CCTA) images. Two different grafts, the normal multi-graft (Model 1) and the novel multi-graft (Model 2), were then implemented on this patient-specific model using virtual surgery techniques. In Model 1, the single graft was anastomosed to right coronary artery (RCA) and the sequential graft was adopted to anastomose left anterior descending (LAD) and left circumflex artery (LCX). While in Model 2, the single graft was anastomosed to LAD and the sequential graft was adopted to anastomose RCA and LCX. A zero-dimensional/three-dimensional (0D/3D) coupling method was used to realize the multi-scale simulation of both the pre-operative and two post-operative models. Flow rates in the coronary artery and grafts were obtained. The hemodynamic parameters were also showed, including wall shear stress (WSS) and oscillatory shear index (OSI). The area of low WSS and OSI in Model 1 was much less than that in Model 2. Model 1 shows optimistic hemodynamic modifications which may enhance the long-term patency of grafts. The anterior segments of sequential graft have better long-term patency than the posterior segments. With rational spatial position of the heart vessels, the last anastomosis of sequential graft should be connected to the main branch.

Cognitive-Behavioral Therapy, Behavioral Weight Loss, and Sequential Treatment for Obese Patients with Binge-Eating Disorder: A Randomized Controlled Trial

ERIC Educational Resources Information Center

Grilo, Carlos M.; Masheb, Robin M.; Wilson, G. Terence; Gueorguieva, Ralitza; White, Marney A.

2011-01-01

Objective: Cognitive-behavioral therapy (CBT) is the best established treatment for binge-eating disorder (BED) but does not produce weight loss. The efficacy of behavioral weight loss (BWL) in obese patients with BED is uncertain. This study compared CBT, BWL, and a sequential approach in which CBT is delivered first, followed by BWL (CBT + BWL).…

Asymptotically optimum multialternative sequential procedures for discernment of processes minimizing average length of observations

NASA Astrophysics Data System (ADS)

Fishman, M. M.

1985-01-01

The problem of multialternative sequential discernment of processes is formulated in terms of conditionally optimum procedures minimizing the average length of observations, without any probabilistic assumptions about any one occurring process, rather than in terms of Bayes procedures minimizing the average risk. The problem is to find the procedure that will transform inequalities into equalities. The problem is formulated for various models of signal observation and data processing: (1) discernment of signals from background interference by a multichannel system; (2) discernment of pulse sequences with unknown time delay; (3) discernment of harmonic signals with unknown frequency. An asymptotically optimum sequential procedure is constructed which compares the statistics of the likelihood ratio with the mean-weighted likelihood ratio and estimates the upper bound for conditional average lengths of observations. This procedure is shown to remain valid as the upper bound for the probability of erroneous partial solutions decreases approaching zero and the number of hypotheses increases approaching infinity. It also remains valid under certain special constraints on the probability such as a threshold. A comparison with a fixed-length procedure reveals that this sequential procedure decreases the length of observations to one quarter, on the average, when the probability of erroneous partial solutions is low.

Cardiac conduction velocity estimation from sequential mapping assuming known Gaussian distribution for activation time estimation error.

PubMed

Shariat, Mohammad Hassan; Gazor, Saeed; Redfearn, Damian

2016-08-01

In this paper, we study the problem of the cardiac conduction velocity (CCV) estimation for the sequential intracardiac mapping. We assume that the intracardiac electrograms of several cardiac sites are sequentially recorded, their activation times (ATs) are extracted, and the corresponding wavefronts are specified. The locations of the mapping catheter's electrodes and the ATs of the wavefronts are used here for the CCV estimation. We assume that the extracted ATs include some estimation errors, which we model with zero-mean white Gaussian noise values with known variances. Assuming stable planar wavefront propagation, we derive the maximum likelihood CCV estimator, when the synchronization times between various recording sites are unknown. We analytically evaluate the performance of the CCV estimator and provide its mean square estimation error. Our simulation results confirm the accuracy of the proposed method and the error analysis of the proposed CCV estimator.

The Complexities of Teachers' Commitment to Environmental Education: A Mixed Methods Approach

ERIC Educational Resources Information Center

Sosu, Edward M.; McWilliam, Angus; Gray, Donald S.

2008-01-01

This article argues that a mixed methods approach is useful in understanding the complexity that underlies teachers' commitment to environmental education. Using sequential and concurrent procedures, the authors demonstrate how different methodological approaches highlighted different aspects of teacher commitment. The quantitative survey examined…

Influence of Multidimensionality on Convergence of Sampling in Protein Simulation

NASA Astrophysics Data System (ADS)

Metsugi, Shoichi

2005-06-01

We study the problem of convergence of sampling in protein simulation originating in the multidimensionality of protein’s conformational space. Since several important physical quantities are given by second moments of dynamical variables, we attempt to obtain the time of simulation necessary for their sufficient convergence. We perform a molecular dynamics simulation of a protein and the subsequent principal component (PC) analysis as a function of simulation time T. As T increases, PC vectors with smaller amplitude of variations are identified and their amplitudes are equilibrated before identifying and equilibrating vectors with larger amplitude of variations. This sequential identification and equilibration mechanism makes protein simulation a useful method although it has an intrinsic multidimensional nature.

Formation of iron nanoparticles and increase in iron reactivity in mineral dust during simulated cloud processing.

PubMed

Shi, Zongbo; Krom, Michael D; Bonneville, Steeve; Baker, Alex R; Jickells, Timothy D; Benning, Liane G

2009-09-01

The formation of iron (Fe) nanoperticles and increase in Fe reactivity in mineral dust during simulated cloud processing was investigated using high-resolution microscopy and chemical extraction methods. Cloud processing of dust was experimentally simulated via an alternation of acidic (pH 2) and circumneutral conditions (pH 5-6) over periods of 24 h each on presieved (<20 microm) Saharan soil and goethite suspensions. Microscopic analyses of the processed soil and goethite samples reveal the neo-formation of Fe-rich nanoparticle aggregates, which were not found initially. Similar Fe-rich nanoparticles were also observed in wet-deposited Saharen dusts from the western Mediterranean but not in dry-deposited dust from the eastern Mediterranean. Sequential Fe extraction of the soil samples indicated an increase in the proportion of chemically reactive Fe extractable by an ascorbate solution after simulated cloud processing. In addition, the sequential extractions on the Mediterranean dust samples revealed a higher content of reactive Fe in the wet-deposited dust compared to that of the dry-deposited dust These results suggestthat large variations of pH commonly reported in aerosol and cloud waters can trigger neo-formation of nanosize Fe particles and an increase in Fe reactivity in the dust

A Molecular Dynamics-Quantum Mechanics Theoretical Study of DNA-Mediated Charge Transport in Hydrated Ionic Liquids.

PubMed

Meng, Zhenyu; Kubar, Tomas; Mu, Yuguang; Shao, Fangwei

2018-05-08

Charge transport (CT) through biomolecules is of high significance in the research fields of biology, nanotechnology, and molecular devices. Inspired by our previous work that showed the binding of ionic liquid (IL) facilitated charge transport in duplex DNA, in silico simulation is a useful means to understand the microscopic mechanism of the facilitation phenomenon. Here molecular dynamics simulations (MD) of duplex DNA in water and hydrated ionic liquids were employed to explore the helical parameters. Principal component analysis was further applied to capture the subtle conformational changes of helical DNA upon different environmental impacts. Sequentially, CT rates were calculated by a QM/MM simulation of the flickering resonance model based upon MD trajectories. Herein, MD simulation illustrated that the binding of ionic liquids can restrain dynamic conformation and lower the on-site energy of the DNA base. Confined movement among the adjacent base pairs was highly related to the increase of electronic coupling among base pairs, which may lead DNA to a CT facilitated state. Sequentially combining MD and QM/MM analysis, the rational correlations among the binding modes, the conformational changes, and CT rates illustrated the facilitation effects from hydrated IL on DNA CT and supported a conformational-gating mechanism.

Mechanisms of electron acceptor utilization: Implications for simulating anaerobic biodegradation

USGS Publications Warehouse

Schreiber, M.E.; Carey, G.R.; Feinstein, D.T.; Bahr, J.M.

2004-01-01

Simulation of biodegradation reactions within a reactive transport framework requires information on mechanisms of terminal electron acceptor processes (TEAPs). In initial modeling efforts, TEAPs were approximated as occurring sequentially, with the highest energy-yielding electron acceptors (e.g. oxygen) consumed before those that yield less energy (e.g., sulfate). Within this framework in a steady state plume, sequential electron acceptor utilization would theoretically produce methane at an organic-rich source and Fe(II) further downgradient, resulting in a limited zone of Fe(II) and methane overlap. However, contaminant plumes often display much more extensive zones of overlapping Fe(II) and methane. The extensive overlap could be caused by several abiotic and biotic processes including vertical mixing of byproducts in long-screened monitoring wells, adsorption of Fe(II) onto aquifer solids, or microscale heterogeneity in Fe(III) concentrations. Alternatively, the overlap could be due to simultaneous utilization of terminal electron acceptors. Because biodegradation rates are controlled by TEAPs, evaluating the mechanisms of electron acceptor utilization is critical for improving prediction of contaminant mass losses due to biodegradation. Using BioRedox-MT3DMS, a three-dimensional, multi-species reactive transport code, we simulated the current configurations of a BTEX plume and TEAP zones at a petroleum- contaminated field site in Wisconsin. Simulation results suggest that BTEX mass loss due to biodegradation is greatest under oxygen-reducing conditions, with smaller but similar contributions to mass loss from biodegradation under Fe(III)-reducing, sulfate-reducing, and methanogenic conditions. Results of sensitivity calculations document that BTEX losses due to biodegradation are most sensitive to the age of the plume, while the shape of the BTEX plume is most sensitive to effective porosity and rate constants for biodegradation under Fe(III)-reducing and methanogenic conditions. Using this transport model, we had limited success in simulating overlap of redox products using reasonable ranges of parameters within a strictly sequential electron acceptor utilization framework. Simulation results indicate that overlap of redox products cannot be accurately simulated using the constructed model, suggesting either that Fe(III) reduction and methanogenesis are occurring simultaneously in the source area, or that heterogeneities in Fe(III) concentration and/or mineral type cause the observed overlap. Additional field, experimental, and modeling studies will be needed to address these questions. ?? 2004 Elsevier B.V. All rights reserved.

An information theoretic approach to use high-fidelity codes to calibrate low-fidelity codes

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

Lewis, Allison, E-mail: lewis.allison10@gmail.com; Smith, Ralph; Williams, Brian

For many simulation models, it can be prohibitively expensive or physically infeasible to obtain a complete set of experimental data to calibrate model parameters. In such cases, one can alternatively employ validated higher-fidelity codes to generate simulated data, which can be used to calibrate the lower-fidelity code. In this paper, we employ an information-theoretic framework to determine the reduction in parameter uncertainty that is obtained by evaluating the high-fidelity code at a specific set of design conditions. These conditions are chosen sequentially, based on the amount of information that they contribute to the low-fidelity model parameters. The goal is tomore » employ Bayesian experimental design techniques to minimize the number of high-fidelity code evaluations required to accurately calibrate the low-fidelity model. We illustrate the performance of this framework using heat and diffusion examples, a 1-D kinetic neutron diffusion equation, and a particle transport model, and include initial results from the integration of the high-fidelity thermal-hydraulics code Hydra-TH with a low-fidelity exponential model for the friction correlation factor.« less

GeNeDA: An Open-Source Workflow for Design Automation of Gene Regulatory Networks Inspired from Microelectronics.

PubMed

Madec, Morgan; Pecheux, François; Gendrault, Yves; Rosati, Elise; Lallement, Christophe; Haiech, Jacques

2016-10-01

The topic of this article is the development of an open-source automated design framework for synthetic biology, specifically for the design of artificial gene regulatory networks based on a digital approach. In opposition to other tools, GeNeDA is an open-source online software based on existing tools used in microelectronics that have proven their efficiency over the last 30 years. The complete framework is composed of a computation core directly adapted from an Electronic Design Automation tool, input and output interfaces, a library of elementary parts that can be achieved with gene regulatory networks, and an interface with an electrical circuit simulator. Each of these modules is an extension of microelectronics tools and concepts: ODIN II, ABC, the Verilog language, SPICE simulator, and SystemC-AMS. GeNeDA is first validated on a benchmark of several combinatorial circuits. The results highlight the importance of the part library. Then, this framework is used for the design of a sequential circuit including a biological state machine.

Physics-based, Bayesian sequential detection method and system for radioactive contraband

DOEpatents

Candy, James V; Axelrod, Michael C; Breitfeller, Eric F; Chambers, David H; Guidry, Brian L; Manatt, Douglas R; Meyer, Alan W; Sale, Kenneth E

2014-03-18

A distributed sequential method and system for detecting and identifying radioactive contraband from highly uncertain (noisy) low-count, radionuclide measurements, i.e. an event mode sequence (EMS), using a statistical approach based on Bayesian inference and physics-model-based signal processing based on the representation of a radionuclide as a monoenergetic decomposition of monoenergetic sources. For a given photon event of the EMS, the appropriate monoenergy processing channel is determined using a confidence interval condition-based discriminator for the energy amplitude and interarrival time and parameter estimates are used to update a measured probability density function estimate for a target radionuclide. A sequential likelihood ratio test is then used to determine one of two threshold conditions signifying that the EMS is either identified as the target radionuclide or not, and if not, then repeating the process for the next sequential photon event of the EMS until one of the two threshold conditions is satisfied.

The distribution of individual cabinet positions in coalition governments: A sequential approach

PubMed Central

Meyer, Thomas M.; Müller, Wolfgang C.

2015-01-01

Abstract Multiparty government in parliamentary democracies entails bargaining over the payoffs of government participation, in particular the allocation of cabinet positions. While most of the literature deals with the numerical distribution of cabinet seats among government parties, this article explores the distribution of individual portfolios. It argues that coalition negotiations are sequential choice processes that begin with the allocation of those portfolios most important to the bargaining parties. This induces conditionality in the bargaining process as choices of individual cabinet positions are not independent of each other. Linking this sequential logic with party preferences for individual cabinet positions, the authors of the article study the allocation of individual portfolios for 146 coalition governments in Western and Central Eastern Europe. The results suggest that a sequential logic in the bargaining process results in better predictions than assuming mutual independence in the distribution of individual portfolios. PMID:27546952

AEROSOL TRANSPORT AND DEPOSITION IN SEQUENTIALLY BIFURCATING AIRWAYS

EPA Science Inventory

Deposition patterns and efficiencies of a dilute suspension of inhaled particles in three-dimensional double bifurcating airway models for both in-plane and 90 deg out-of-plane configurations have been numerically simulated assuming steady, laminar, constant-property air flow wit...

Acid rain research program. Annual progress report, September 1975--June 1976

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

Evans, L.S.; Raynor, G.S.

1976-09-01

The aims of the research program are: (a) to observe the minimum threshold dose of simulated acid rain to produce visual and histological effects on plant foliage, (b) approach threshold limits of simulated sulfate acid rain that affect plant growth and reproduction, and (c) to measure chemical and meteorological parameters of incident rain. Acute leaf injury to several plant species resulted from exposure of foliage to simulated sulfate acid rain of pH level 2.3 to 2.9. Only slight injury occurred at 3.1. Scanning electron micrographs showed that injury to upper leaf surfaces occurred mostly at the base of trichomes (leafmore » hairs) and near stomata. An association of lesion development near vascular tissue was also noted. Histologically, lesions are characterized by an initial collapse of the epidermis with eventual lysis and collapse of more internal leaf tissues on the upper leaf surface of pinto beans which complemented detailed descriptions of visual lesion development after daily exposures to simulated rain. Initial experiments with gametophytes of Pteridium aquilinum show that reproduction of this fern species is very sensitive to solutions of pH 5.2 while vegetative development is not affected at pH levels of 2.2. Initial rain samples from the sequential sampler have been obtained. Initial portions of rain events exhibit a pH near 3.0 in some cases. More complete chemical analyses are anticipated.« less

Full kinetics of CO entry, internal diffusion, and exit in myoglobin from transition-path theory simulations.

PubMed

Yu, Tang-Qing; Lapelosa, Mauro; Vanden-Eijnden, Eric; Abrams, Cameron F

2015-03-04

We use Markovian milestoning molecular dynamics (MD) simulations on a tessellation of the collective variable space for CO localization in myoglobin to estimate the kinetics of entry, exit, and internal site-hopping. The tessellation is determined by analysis of the free-energy surface in that space using transition-path theory (TPT), which provides criteria for defining optimal milestones, allowing short, independent, cell-constrained MD simulations to provide properly weighted kinetic data. We coarse grain the resulting kinetic model at two levels: first, using crystallographically relevant internal cavities and their predicted interconnections and solvent portals; and second, as a three-state side-path scheme inspired by similar models developed from geminate recombination experiments. We show semiquantitative agreement with experiment on entry and exit rates and in the identification of the so-called "histidine gate" at position 64 through which ≈90% of flux between solvent and the distal pocket passes. We also show with six-dimensional calculations that the minimum free-energy pathway of escape through the histidine gate is a "knock-on" mechanism in which motion of the ligand and the gate are sequential and interdependent. In total, these results suggest that such TPT simulations are indeed a promising approach to overcome the practical time-scale limitations of MD to allow reliable estimation of transition mechanisms and rates among metastable states.

Breaking from binaries - using a sequential mixed methods design.

PubMed

Larkin, Patricia Mary; Begley, Cecily Marion; Devane, Declan

2014-03-01

To outline the traditional worldviews of healthcare research and discuss the benefits and challenges of using mixed methods approaches in contributing to the development of nursing and midwifery knowledge. There has been much debate about the contribution of mixed methods research to nursing and midwifery knowledge in recent years. A sequential exploratory design is used as an exemplar of a mixed methods approach. The study discussed used a combination of focus-group interviews and a quantitative instrument to obtain a fuller understanding of women's experiences of childbirth. In the mixed methods study example, qualitative data were analysed using thematic analysis and quantitative data using regression analysis. Polarised debates about the veracity, philosophical integrity and motivation for conducting mixed methods research have largely abated. A mixed methods approach can contribute to a deeper, more contextual understanding of a variety of subjects and experiences; as a result, it furthers knowledge that can be used in clinical practice. The purpose of the research study should be the main instigator when choosing from an array of mixed methods research designs. Mixed methods research offers a variety of models that can augment investigative capabilities and provide richer data than can a discrete method alone. This paper offers an example of an exploratory, sequential approach to investigating women's childbirth experiences. A clear framework for the conduct and integration of the different phases of the mixed methods research process is provided. This approach can be used by practitioners and policy makers to improve practice.

Comparison of Radiation Dose and Image Quality of Triple-Rule-Out Computed Tomography Angiography Between Conventional Helical Scanning and a Strategy Incorporating Sequential Scanning

PubMed Central

Manheimer, Eric D.; Peters, M. Robert; Wolff, Steven D.; Qureshi, Mehreen A.; Atluri, Prashanth; Pearson, Gregory D.N.; Einstein, Andrew J.

2011-01-01

Triple-rule-out computed tomography angiography (TRO CTA), performed to evaluate the coronary arteries, pulmonary arteries, and thoracic aorta, has been associated with high radiation exposure. Utilization of sequential scanning for coronary computed tomography angiography (CCTA) reduces radiation dose. The application of sequential scanning to TRO CTA is much less well defined. We analyzed radiation dose and image quality from TRO CTA performed in a single outpatient center, comparing scans from a period during which helical scanning with electrocardiographically controlled tube current modulation was used for all patients (n=35) and after adoption of a strategy incorporating sequential scanning whenever appropriate (n=35). Sequential scanning was able to be employed in 86% of cases. The sequential-if-appropriate strategy, compared to the helical-only strategy, was associated with a 61.6% dose decrease (mean dose-length product [DLP] of 439 mGy×cm vs 1144 mGy×cm and mean effective dose of 7.5 mSv vs 19.4 mSv, respectively, p<0.0001). Similarly, there was a 71.5% dose reduction among 30 patients scanned with the sequential protocol compared to 40 patients scanned with the helical protocol under either strategy (326 mGy×cm vs 1141 mGy×cm and 5.5 mSv vs 19.4 mSv, respectively, p<0.0001). Although image quality did not differ between strategies, there was a non-statistically significant trend towards better quality in the sequential protocol compared to the helical protocol. In conclusion, approaching TRO CTA with a diagnostic strategy of sequential scanning as appropriate offers a marked reduction in radiation dose while maintaining image quality. PMID:21306693

Negotiation of territorial boundaries in a songbird

PubMed Central

Ellis, Jesse M.; Cropp, Brett F.; Koltz, John M.

2014-01-01

How do territorial neighbors resolve the location of their boundaries? We addressed this question by testing the predictions of 2 nonexclusive game theoretical models for competitive signaling: the sequential assessment game and the territorial bargaining game. Our study species, the banded wren, is a neotropical nonmigratory songbird living in densely packed territorial neighborhoods. The males possess repertoires of approximately 25 song types that are largely shared between neighbors and sequentially delivered with variable switching rates. Over 3 days, boundary disputes among pairs of neighboring males were synchronously recorded, their perch positions were marked, and their behavioral interactions were noted. For each countersinging interaction between 2 focal males, we quantified approach and retreat order, a variety of song and call patterns, closest approach distance, distance from the territorial center, and female presence. Aggressors produced more rattle-buzz songs during the approaching phase of interactions, whereas defenders overlapped their opponent’s songs. During the close phase of the interaction, both males matched frequently, but the key determinant of which one retreated first was song-type diversity—first retreaters sang with a higher diversity. Retreaters also produced more unshared song types during the interaction, and in the retreating phase of the interaction, they overlapped more. A negative correlation between song-type diversity asymmetry and contest duration suggested sequential assessment of motivational asymmetry. The use of this graded signal, which varied with distance from the center and indicated a male’s motivation to defend a particular position, supported the bargaining model. The bargaining game could be viewed as a series of sequential assessment contests. PMID:25419086

Vapor Grown Perovskite Solar Cells

NASA Astrophysics Data System (ADS)

Abdussamad Abbas, Hisham

Perovskite solar cells has been the fastest growing solar cell material till date with verified efficiencies of over 22%. Most groups in the world focuses their research on solution based devices that has residual solvent in the material bulk. This work focuses extensively on the fabrication and properties of vapor based perovskite devices that is devoid of solvents. The initial part of my work focuses on the detailed fabrication of high efficiency consistent sequential vapor NIP devices made using P3HT as P-type Type II heterojunction. The sequential vapor devices experiences device anomalies like voltage evolution and IV hysteresis owing to charge trapping in TiO2. Hence, sequential PIN devices were fabricated using doped Type-II heterojunctions that had no device anomalies. The sequential PIN devices has processing restriction, as organic Type-II heterojunction materials cannot withstand high processing temperature, hence limiting device efficiency. Thereby bringing the need of co-evaporation for fabricating high efficiency consistent PIN devices, the approach has no-restriction on substrates and offers stoichiometric control. A comprehensive description of the fabrication, Co-evaporator setup and how to build it is described. The results of Co-evaporated devices clearly show that grain size, stoichiometry and doped transport layers are all critical for eliminating device anomalies and in fabricating high efficiency devices. Finally, Formamidinium based perovskite were fabricated using sequential approach. A thermal degradation study was conducted on Methyl Ammonium Vs. Formamidinium based perovskite films, Formamidinium based perovskites were found to be more stable. Lastly, inorganic films such as CdS and Nickel oxide were developed in this work.

A novel visual hardware behavioral language

NASA Technical Reports Server (NTRS)

Li, Xueqin; Cheng, H. D.

1992-01-01

Most hardware behavioral languages just use texts to describe the behavior of the desired hardware design. This is inconvenient for VLSI designers who enjoy using the schematic approach. The proposed visual hardware behavioral language has the ability to graphically express design information using visual parallel models (blocks), visual sequential models (processes) and visual data flow graphs (which consist of primitive operational icons, control icons, and Data and Synchro links). Thus, the proposed visual hardware behavioral language can not only specify hardware concurrent and sequential functionality, but can also visually expose parallelism, sequentiality, and disjointness (mutually exclusive operations) for the hardware designers. That would make the hardware designers capture the design ideas easily and explicitly using this visual hardware behavioral language.

Safeguarding a Lunar Rover with Wald's Sequential Probability Ratio Test

NASA Technical Reports Server (NTRS)

Furlong, Michael; Dille, Michael; Wong, Uland; Nefian, Ara

2016-01-01

The virtual bumper is a safeguarding mechanism for autonomous and remotely operated robots. In this paper we take a new approach to the virtual bumper system by using an old statistical test. By using a modified version of Wald's sequential probability ratio test we demonstrate that we can reduce the number of false positive reported by the virtual bumper, thereby saving valuable mission time. We use the concept of sequential probability ratio to control vehicle speed in the presence of possible obstacles in order to increase certainty about whether or not obstacles are present. Our new algorithm reduces the chances of collision by approximately 98 relative to traditional virtual bumper safeguarding without speed control.

Dynamics of Sequential Decision Making

NASA Astrophysics Data System (ADS)

Rabinovich, Mikhail I.; Huerta, Ramón; Afraimovich, Valentin

2006-11-01

We suggest a new paradigm for intelligent decision-making suitable for dynamical sequential activity of animals or artificial autonomous devices that depends on the characteristics of the internal and external world. To do it we introduce a new class of dynamical models that are described by ordinary differential equations with a finite number of possibilities at the decision points, and also include rules solving this uncertainty. Our approach is based on the competition between possible cognitive states using their stable transient dynamics. The model controls the order of choosing successive steps of a sequential activity according to the environment and decision-making criteria. Two strategies (high-risk and risk-aversion conditions) that move the system out of an erratic environment are analyzed.

Solving a mathematical model integrating unequal-area facilities layout and part scheduling in a cellular manufacturing system by a genetic algorithm.

PubMed

Ebrahimi, Ahmad; Kia, Reza; Komijan, Alireza Rashidi

2016-01-01

In this article, a novel integrated mixed-integer nonlinear programming model is presented for designing a cellular manufacturing system (CMS) considering machine layout and part scheduling problems simultaneously as interrelated decisions. The integrated CMS model is formulated to incorporate several design features including part due date, material handling time, operation sequence, processing time, an intra-cell layout of unequal-area facilities, and part scheduling. The objective function is to minimize makespan, tardiness penalties, and material handling costs of inter-cell and intra-cell movements. Two numerical examples are solved by the Lingo software to illustrate the results obtained by the incorporated features. In order to assess the effects and importance of integration of machine layout and part scheduling in designing a CMS, two approaches, sequentially and concurrent are investigated and the improvement resulted from a concurrent approach is revealed. Also, due to the NP-hardness of the integrated model, an efficient genetic algorithm is designed. As a consequence, computational results of this study indicate that the best solutions found by GA are better than the solutions found by B&B in much less time for both sequential and concurrent approaches. Moreover, the comparisons between the objective function values (OFVs) obtained by sequential and concurrent approaches demonstrate that the OFV improvement is averagely around 17 % by GA and 14 % by B&B.

Sequential Classifier Training for Rice Mapping with Multitemporal Remote Sensing Imagery

NASA Astrophysics Data System (ADS)

Guo, Y.; Jia, X.; Paull, D.

2017-10-01

Most traditional methods for rice mapping with remote sensing data are effective when they are applied to the initial growing stage of rice, as the practice of flooding during this period makes the spectral characteristics of rice fields more distinguishable. In this study, we propose a sequential classifier training approach for rice mapping that can be used over the whole growing period of rice for monitoring various growth stages. Rice fields are firstly identified during the initial flooding period. The identified rice fields are used as training data to train a classifier that separates rice and non-rice pixels. The classifier is then used as a priori knowledge to assist the training of classifiers for later rice growing stages. This approach can be applied progressively to sequential image data, with only a small amount of training samples being required from each image. In order to demonstrate the effectiveness of the proposed approach, experiments were conducted at one of the major rice-growing areas in Australia. The proposed approach was applied to a set of multitemporal remote sensing images acquired by the Sentinel-2A satellite. Experimental results show that, compared with traditional spectral-indexbased algorithms, the proposed method is able to achieve more stable and consistent rice mapping accuracies and it reaches higher than 80% during the whole rice growing period.

specsim: A Fortran-77 program for conditional spectral simulation in 3D

NASA Astrophysics Data System (ADS)

Yao, Tingting

1998-12-01

A Fortran 77 program, specsim, is presented for conditional spectral simulation in 3D domains. The traditional Fourier integral method allows generating random fields with a given covariance spectrum. Conditioning to local data is achieved by an iterative identification of the conditional phase information. A flowchart of the program is given to illustrate the implementation procedures of the program. A 3D case study is presented to demonstrate application of the program. A comparison with the traditional sequential Gaussian simulation algorithm emphasizes the advantages and drawbacks of the proposed algorithm.

Elucidation of the molecular mechanisms underlying adverse reactions associated with a kinase inhibitor using systems toxicology

PubMed Central

Amemiya, Takahiro; Honma, Masashi; Kariya, Yoshiaki; Ghosh, Samik; Kitano, Hiroaki; Kurachi, Yoshihisa; Fujita, Ken-ichi; Sasaki, Yasutsuna; Homma, Yukio; Abernethy, Darrel R; Kume, Haruki; Suzuki, Hiroshi

2015-01-01

Background/Objectives: Targeted kinase inhibitors are an important class of agents in anticancer therapeutics, but their limited tolerability hampers their clinical performance. Identification of the molecular mechanisms underlying the development of adverse reactions will be helpful in establishing a rational method for the management of clinically adverse reactions. Here, we selected sunitinib as a model and demonstrated that the molecular mechanisms underlying the adverse reactions associated with kinase inhibitors can efficiently be identified using a systems toxicological approach. Methods: First, toxicological target candidates were short-listed by comparing the human kinase occupancy profiles of sunitinib and sorafenib, and the molecular mechanisms underlying adverse reactions were predicted by sequential simulations using publicly available mathematical models. Next, to evaluate the probability of these predictions, a clinical observation study was conducted in six patients treated with sunitinib. Finally, mouse experiments were performed for detailed confirmation of the hypothesized molecular mechanisms and to evaluate the efficacy of a proposed countermeasure against adverse reactions to sunitinib. Results: In silico simulations indicated the possibility that sunitinib-mediated off-target inhibition of phosphorylase kinase leads to the generation of oxidative stress in various tissues. Clinical observations of patients and mouse experiments confirmed the validity of this prediction. The simulation further suggested that concomitant use of an antioxidant may prevent sunitinib-mediated adverse reactions, which was confirmed in mouse experiments. Conclusions: A systems toxicological approach successfully predicted the molecular mechanisms underlying clinically adverse reactions associated with sunitinib and was used to plan a rational method for the management of these adverse reactions. PMID:28725458

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

USGS Publications Warehouse

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.

Gibbs sampling on large lattice with GMRF

NASA Astrophysics Data System (ADS)

Marcotte, Denis; Allard, Denis

2018-02-01

Gibbs sampling is routinely used to sample truncated Gaussian distributions. These distributions naturally occur when associating latent Gaussian fields to category fields obtained by discrete simulation methods like multipoint, sequential indicator simulation and object-based simulation. The latent Gaussians are often used in data assimilation and history matching algorithms. When the Gibbs sampling is applied on a large lattice, the computing cost can become prohibitive. The usual practice of using local neighborhoods is unsatisfying as it can diverge and it does not reproduce exactly the desired covariance. A better approach is to use Gaussian Markov Random Fields (GMRF) which enables to compute the conditional distributions at any point without having to compute and invert the full covariance matrix. As the GMRF is locally defined, it allows simultaneous updating of all points that do not share neighbors (coding sets). We propose a new simultaneous Gibbs updating strategy on coding sets that can be efficiently computed by convolution and applied with an acceptance/rejection method in the truncated case. We study empirically the speed of convergence, the effect of choice of boundary conditions, of the correlation range and of GMRF smoothness. We show that the convergence is slower in the Gaussian case on the torus than for the finite case studied in the literature. However, in the truncated Gaussian case, we show that short scale correlation is quickly restored and the conditioning categories at each lattice point imprint the long scale correlation. Hence our approach enables to realistically apply Gibbs sampling on large 2D or 3D lattice with the desired GMRF covariance.

Cross-Milieu Terrorist Collaboration: Using Game Theory to Assess the Risk of a Novel Threat.

PubMed

Ackerman, Gary A; Zhuang, Jun; Weerasuriya, Sitara

2017-02-01

This article uses a game-theoretic approach to analyze the risk of cross-milieu terrorist collaboration-the possibility that, despite marked ideological differences, extremist groups from very different milieus might align to a degree where operational collaboration against Western societies becomes possible. Based upon theoretical insights drawn from a variety of literatures, a bargaining model is constructed that reflects the various benefits and costs for terrorists' collaboration across ideological milieus. Analyzed in both sequential and simultaneous decision-making contexts and through numerical simulations, the model confirms several theoretical arguments. The most important of these is that although likely to be quite rare, successful collaboration across terrorist milieus is indeed feasible in certain circumstances. The model also highlights several structural elements that might play a larger role than previously recognized in the collaboration decision, including that the prospect of nonmaterial gains (amplification of terror and reputational boost) plays at least as important a role in the decision to collaborate as potential increased capabilities does. Numerical simulation further suggests that prospects for successful collaboration over most scenarios (including operational) increase when a large, effective Islamist terrorist organization initiates collaboration with a smaller right-wing group, as compared with the other scenarios considered. Although the small number of historical cases precludes robust statistical validation, the simulation results are supported by existing empirical evidence of collaboration between Islamists and right- or left-wing extremists. The game-theoretic approach, therefore, provides guidance regarding the circumstances under which such an unholy alliance of violent actors is likely to succeed. © 2016 Society for Risk Analysis.

Design, Synthesis and Affinity Properties of Biologically Active Peptide and Protein Conjugates of Cotton Cellulose

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

Edwards, J. V.; Goheen, Steven C.

The formation of peptide and protein conjugates of cellulose on cotton fabrics provides promising leads for the development of wound healing, antibacterial, and decontaminating textiles. An approach to the design, synthesis, and analysis of bioconjugates containing cellulose peptide and protein conjugates includes: 1) computer graphic modeling for a rationally designed structure; 2) attachment of the peptide or protein to cotton cellulose through a linker amino acid, and 3) characterization of the resulting bioconjugate. Computer graphic simulation of protein and peptide cellulose conjugates gives a rationally designed biopolymer to target synthetic modifications to the cotton cellulose. Techniques for preparing these typesmore » of conjugates involve both sequential assembly of the peptide on the fabric and direct crosslinking of the peptide or protein as cellulose bound esters or carboxymethylcellulose amides.« less

Extended target recognition in cognitive radar networks.

PubMed

Wei, Yimin; Meng, Huadong; Liu, Yimin; Wang, Xiqin

2010-01-01

We address the problem of adaptive waveform design for extended target recognition in cognitive radar networks. A closed-loop active target recognition radar system is extended to the case of a centralized cognitive radar network, in which a generalized likelihood ratio (GLR) based sequential hypothesis testing (SHT) framework is employed. Using Doppler velocities measured by multiple radars, the target aspect angle for each radar is calculated. The joint probability of each target hypothesis is then updated using observations from different radar line of sights (LOS). Based on these probabilities, a minimum correlation algorithm is proposed to adaptively design the transmit waveform for each radar in an amplitude fluctuation situation. Simulation results demonstrate performance improvements due to the cognitive radar network and adaptive waveform design. Our minimum correlation algorithm outperforms the eigen-waveform solution and other non-cognitive waveform design approaches.

Research on parallel algorithm for sequential pattern mining

NASA Astrophysics Data System (ADS)

Zhou, Lijuan; Qin, Bai; Wang, Yu; Hao, Zhongxiao

2008-03-01

Sequential pattern mining is the mining of frequent sequences related to time or other orders from the sequence database. Its initial motivation is to discover the laws of customer purchasing in a time section by finding the frequent sequences. In recent years, sequential pattern mining has become an important direction of data mining, and its application field has not been confined to the business database and has extended to new data sources such as Web and advanced science fields such as DNA analysis. The data of sequential pattern mining has characteristics as follows: mass data amount and distributed storage. Most existing sequential pattern mining algorithms haven't considered the above-mentioned characteristics synthetically. According to the traits mentioned above and combining the parallel theory, this paper puts forward a new distributed parallel algorithm SPP(Sequential Pattern Parallel). The algorithm abides by the principal of pattern reduction and utilizes the divide-and-conquer strategy for parallelization. The first parallel task is to construct frequent item sets applying frequent concept and search space partition theory and the second task is to structure frequent sequences using the depth-first search method at each processor. The algorithm only needs to access the database twice and doesn't generate the candidated sequences, which abates the access time and improves the mining efficiency. Based on the random data generation procedure and different information structure designed, this paper simulated the SPP algorithm in a concrete parallel environment and implemented the AprioriAll algorithm. The experiments demonstrate that compared with AprioriAll, the SPP algorithm had excellent speedup factor and efficiency.

Assessment of Critical Events Corridors through Multivariate Cascading Outages Analysis

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

Makarov, Yuri V.; Samaan, Nader A.; Diao, Ruisheng

2011-10-17

Massive blackouts of electrical power systems in North America over the past decade has focused increasing attention upon ways to identify and simulate network events that may potentially lead to widespread network collapse. This paper summarizes a method to simulate power-system vulnerability to cascading failures to a supplied set of initiating events synonymously termed as Extreme Events. The implemented simulation method is currently confined to simulating steady state power-system response to a set of extreme events. The outlined method of simulation is meant to augment and provide a new insight into bulk power transmission network planning that at present remainsmore » mainly confined to maintaining power system security for single and double component outages under a number of projected future network operating conditions. Although one of the aims of this paper is to demonstrate the feasibility of simulating network vulnerability to cascading outages, a more important goal has been to determine vulnerable parts of the network that may potentially be strengthened in practice so as to mitigate system susceptibility to cascading failures. This paper proposes to demonstrate a systematic approach to analyze extreme events and identify vulnerable system elements that may be contributing to cascading outages. The hypothesis of critical events corridors is proposed to represent repeating sequential outages that can occur in the system for multiple initiating events. The new concept helps to identify system reinforcements that planners could engineer in order to 'break' the critical events sequences and therefore lessen the likelihood of cascading outages. This hypothesis has been successfully validated with a California power system model.« less

Early bedside care during preclinical medical education: can technology-enhanced patient simulation advance the Flexnerian ideal?

PubMed

Gordon, James A; Hayden, Emily M; Ahmed, Rami A; Pawlowski, John B; Khoury, Kimberly N; Oriol, Nancy E

2010-02-01

Flexner wanted medical students to study at the patient bedside-a remarkable innovation in his time-so that they could apply science to clinical care under the watchful eye of senior physicians. Ever since his report, medical schools have reserved the latter years of their curricula for such an "advanced" apprenticeship, providing clinical clerkship experiences only after an initial period of instruction in basic medical sciences. Although Flexner codified the segregation of preclinical and clinical instruction, he was committed to ensuring that both domains were integrated into a modern medical education. The aspiration to fully integrate preclinical and clinical instruction continues to drive medical education reform even to this day. In this article, the authors revisit the original justification for sequential preclinical-clinical instruction and argue that modern, technology-enhanced patient simulation platforms are uniquely powerful for fostering simultaneous integration of preclinical-clinical content in a way that Flexner would have applauded. To date, medical educators tend to focus on using technology-enhanced medical simulation in clinical and postgraduate medical education; few have devoted significant attention to using immersive clinical simulation among preclinical students. The authors present an argument for the use of dynamic robot-mannequins in teaching basic medical science, and describe their experience with simulator-based preclinical instruction at Harvard Medical School. They discuss common misconceptions and barriers to the approach, describe their curricular responses to the technique, and articulate a unifying theory of cognitive and emotional learning that broadens the view of what is possible, feasible, and desirable with simulator-based medical education.

Analysis of Longitudinal Studies With Repeated Outcome Measures: Adjusting for Time-Dependent Confounding Using Conventional Methods.

PubMed

Keogh, Ruth H; Daniel, Rhian M; VanderWeele, Tyler J; Vansteelandt, Stijn

2018-05-01

Estimation of causal effects of time-varying exposures using longitudinal data is a common problem in epidemiology. When there are time-varying confounders, which may include past outcomes, affected by prior exposure, standard regression methods can lead to bias. Methods such as inverse probability weighted estimation of marginal structural models have been developed to address this problem. However, in this paper we show how standard regression methods can be used, even in the presence of time-dependent confounding, to estimate the total effect of an exposure on a subsequent outcome by controlling appropriately for prior exposures, outcomes, and time-varying covariates. We refer to the resulting estimation approach as sequential conditional mean models (SCMMs), which can be fitted using generalized estimating equations. We outline this approach and describe how including propensity score adjustment is advantageous. We compare the causal effects being estimated using SCMMs and marginal structural models, and we compare the two approaches using simulations. SCMMs enable more precise inferences, with greater robustness against model misspecification via propensity score adjustment, and easily accommodate continuous exposures and interactions. A new test for direct effects of past exposures on a subsequent outcome is described.

Fugitive emission source characterization using a gradient-based optimization scheme and scalar transport adjoint

NASA Astrophysics Data System (ADS)

Brereton, Carol A.; Joynes, Ian M.; Campbell, Lucy J.; Johnson, Matthew R.

2018-05-01

Fugitive emissions are important sources of greenhouse gases and lost product in the energy sector that can be difficult to detect, but are often easily mitigated once they are known, located, and quantified. In this paper, a scalar transport adjoint-based optimization method is presented to locate and quantify unknown emission sources from downstream measurements. This emission characterization approach correctly predicted locations to within 5 m and magnitudes to within 13% of experimental release data from Project Prairie Grass. The method was further demonstrated on simulated simultaneous releases in a complex 3-D geometry based on an Alberta gas plant. Reconstructions were performed using both the complex 3-D transient wind field used to generate the simulated release data and using a sequential series of steady-state RANS wind simulations (SSWS) representing 30 s intervals of physical time. Both the detailed transient and the simplified wind field series could be used to correctly locate major sources and predict their emission rates within 10%, while predicting total emission rates from all sources within 24%. This SSWS case would be much easier to implement in a real-world application, and gives rise to the possibility of developing pre-computed databases of both wind and scalar transport adjoints to reduce computational time.

An intermediate-scale model for thermal hydrology in low-relief permafrost-affected landscapes

DOE PAGES

Jan, Ahmad; Coon, Ethan T.; Painter, Scott L.; ...

2017-07-10

Integrated surface/subsurface models for simulating the thermal hydrology of permafrost-affected regions in a warming climate have recently become available, but computational demands of those new process-rich simu- lation tools have thus far limited their applications to one-dimensional or small two-dimensional simulations. We present a mixed-dimensional model structure for efficiently simulating surface/subsurface thermal hydrology in low-relief permafrost regions at watershed scales. The approach replaces a full three-dimensional system with a two-dimensional overland thermal hydrology system and a family of one-dimensional vertical columns, where each column represents a fully coupled surface/subsurface thermal hydrology system without lateral flow. The system is then operatormore » split, sequentially updating the overland flow system without sources and the one-dimensional columns without lateral flows. We show that the app- roach is highly scalable, supports subcycling of different processes, and compares well with the corresponding fully three-dimensional representation at significantly less computational cost. Those advances enable recently developed representations of freezing soil physics to be coupled with thermal overland flow and surface energy balance at scales of 100s of meters. Furthermore developed and demonstrated for permafrost thermal hydrology, the mixed-dimensional model structure is applicable to integrated surface/subsurface thermal hydrology in general.« less

Statistic inversion of multi-zone transition probability models for aquifer characterization in alluvial fans

DOE PAGES

Zhu, Lin; Dai, Zhenxue; Gong, Huili; ...

2015-06-12

Understanding the heterogeneity arising from the complex architecture of sedimentary sequences in alluvial fans is challenging. This study develops a statistical inverse framework in a multi-zone transition probability approach for characterizing the heterogeneity in alluvial fans. An analytical solution of the transition probability matrix is used to define the statistical relationships among different hydrofacies and their mean lengths, integral scales, and volumetric proportions. A statistical inversion is conducted to identify the multi-zone transition probability models and estimate the optimal statistical parameters using the modified Gauss–Newton–Levenberg–Marquardt method. The Jacobian matrix is computed by the sensitivity equation method, which results in anmore » accurate inverse solution with quantification of parameter uncertainty. We use the Chaobai River alluvial fan in the Beijing Plain, China, as an example for elucidating the methodology of alluvial fan characterization. The alluvial fan is divided into three sediment zones. In each zone, the explicit mathematical formulations of the transition probability models are constructed with optimized different integral scales and volumetric proportions. The hydrofacies distributions in the three zones are simulated sequentially by the multi-zone transition probability-based indicator simulations. Finally, the result of this study provides the heterogeneous structure of the alluvial fan for further study of flow and transport simulations.« less

High-Order Multioperator Compact Schemes for Numerical Simulation of Unsteady Subsonic Airfoil Flow

NASA Astrophysics Data System (ADS)

Savel'ev, A. D.

2018-02-01

On the basis of high-order schemes, the viscous gas flow over the NACA2212 airfoil is numerically simulated at a free-stream Mach number of 0.3 and Reynolds numbers ranging from 103 to 107. Flow regimes sequentially varying due to variations in the free-stream viscosity are considered. Vortex structures developing on the airfoil surface are investigated, and a physical interpretation of this phenomenon is given.

Automated detection of changes in sequential color ocular fundus images

NASA Astrophysics Data System (ADS)

Sakuma, Satoshi; Nakanishi, Tadashi; Takahashi, Yasuko; Fujino, Yuichi; Tsubouchi, Tetsuro; Nakanishi, Norimasa

1998-06-01

A recent trend is the automatic screening of color ocular fundus images. The examination of such images is used in the early detection of several adult diseases such as hypertension and diabetes. Since this type of examination is easier than CT, costs less, and has no harmful side effects, it will become a routine medical examination. Normal ocular fundus images are found in more than 90% of all people. To deal with the increasing number of such images, this paper proposes a new approach to process them automatically and accurately. Our approach, based on individual comparison, identifies changes in sequential images: a previously diagnosed normal reference image is compared to a non- diagnosed image.

Overcoming catastrophic forgetting in neural networks

PubMed Central

Kirkpatrick, James; Pascanu, Razvan; Rabinowitz, Neil; Veness, Joel; Desjardins, Guillaume; Rusu, Andrei A.; Milan, Kieran; Quan, John; Ramalho, Tiago; Grabska-Barwinska, Agnieszka; Hassabis, Demis; Clopath, Claudia; Kumaran, Dharshan; Hadsell, Raia

2017-01-01

The ability to learn tasks in a sequential fashion is crucial to the development of artificial intelligence. Until now neural networks have not been capable of this and it has been widely thought that catastrophic forgetting is an inevitable feature of connectionist models. We show that it is possible to overcome this limitation and train networks that can maintain expertise on tasks that they have not experienced for a long time. Our approach remembers old tasks by selectively slowing down learning on the weights important for those tasks. We demonstrate our approach is scalable and effective by solving a set of classification tasks based on a hand-written digit dataset and by learning several Atari 2600 games sequentially. PMID:28292907

Three-dimensional multiexcitation magnetoacoustic tomography with magnetic induction

PubMed Central

Li, Xu; Mariappan, Leo; He, Bin

2010-01-01

Magnetoacoustic tomography with magnetic induction (MAT-MI) is a hybrid imaging modality proposed to image electrical conductivity contrast of biological tissue with high spatial resolution. This modality combines magnetic excitations with ultrasound detection through the Lorentz force based coupling mechanism. However, previous studies have shown that MAT-MI method with single type of magnetic excitation can only reconstruct the conductivity boundaries of a sample. In order to achieve more complete conductivity contrast reconstruction, we proposed a multiexcitation MAT-MI approach. In this approach, multiple magnetic excitations using different coil configurations are applied to the object sequentially and ultrasonic signals corresponding to each excitation are collected for conductivity image reconstruction. In this study, we validate the new multiexcitation MAT-MI method for three-dimensional (3D) conductivity imaging through both computer simulations and phantom experiments. 3D volume data are obtained by utilizing acoustic focusing and cylindrical scanning under each magnetic excitation. It is shown in our simulation and experiment results that with a common ultrasound probe that has limited bandwidth we are able to correctly reconstruct the 3D relative conductivity contrast of the imaging object. As compared to those conductivity boundary images generated by previous single-excitation MAT-MI, the new multiexcitation MAT-MI method provides more complete conductivity contrast reconstruction, and therefore, more valuable information in possible clinical and research applications. PMID:21267084

Analysis of mercury adsorption at the gibbsite-water interface using the CD-MUSIC model.

PubMed

Park, Chang Min

2018-05-22

Mercury (Hg), one of the most toxic substances in nature, has long been released during the anthropogenic activity. A correct description of the adsorptive behavior of mercury is important to gain a better insight into its fate and transport in natural mineral surfaces, which will be a prerequisite for the development of surface complexation model for the adsorption processes. In the present study, simulation experiments on macroscopic Hg(II) sorption by gibbsite (α-Al(OH) 3 ), a representative aluminum (hydr)oxide mineral, were performed using the charge distribution and multi-site complexation (CD-MUSIC) approach with 1-pK triple plane model (TPM). For this purpose, several data sets which had already been reported in the literature were employed to analyze the effect of pH, ionic strength, and co-exisiting ions (NO 3 - and Cl - ) on the Hg(II) adsorption onto gibbsite. Sequential optimization approach was used to determine the acidity and asymmetric binding constants for electrolyte ions and the affinity constants of the surface species through the model simulation using FITEQLC (a modified code of FITEQL 4.0). The model successfully incorporated the presence of inorganic ligands at the dominant edge (100) face of gibbsite with consistent surface species, which was evidenced by molecular scale analysis. The model was verified with an independent set of Hg(II) adsorption data incorporating carbonate binding species in an open gibbsite-water system.

Inversion using a new low-dimensional representation of complex binary geological media based on a deep neural network

NASA Astrophysics Data System (ADS)

Laloy, Eric; Hérault, Romain; Lee, John; Jacques, Diederik; Linde, Niklas

2017-12-01

Efficient and high-fidelity prior sampling and inversion for complex geological media is still a largely unsolved challenge. Here, we use a deep neural network of the variational autoencoder type to construct a parametric low-dimensional base model parameterization of complex binary geological media. For inversion purposes, it has the attractive feature that random draws from an uncorrelated standard normal distribution yield model realizations with spatial characteristics that are in agreement with the training set. In comparison with the most commonly used parametric representations in probabilistic inversion, we find that our dimensionality reduction (DR) approach outperforms principle component analysis (PCA), optimization-PCA (OPCA) and discrete cosine transform (DCT) DR techniques for unconditional geostatistical simulation of a channelized prior model. For the considered examples, important compression ratios (200-500) are achieved. Given that the construction of our parameterization requires a training set of several tens of thousands of prior model realizations, our DR approach is more suited for probabilistic (or deterministic) inversion than for unconditional (or point-conditioned) geostatistical simulation. Probabilistic inversions of 2D steady-state and 3D transient hydraulic tomography data are used to demonstrate the DR-based inversion. For the 2D case study, the performance is superior compared to current state-of-the-art multiple-point statistics inversion by sequential geostatistical resampling (SGR). Inversion results for the 3D application are also encouraging.

A Sequential Optimization Sampling Method for Metamodels with Radial Basis Functions

PubMed Central

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

Sequential capture of CO2 and SO2 in a pressurized TGA simulating FBC conditions.

PubMed

Sun, Ping; Grace, John R; Lim, C Jim; Anthony, Edward J

2007-04-15

Four FBC-based processes were investigated as possible means of sequentially capturing SO2 and CO2. Sorbent performance is the key to their technical feasibility. Two sorbents (a limestone and a dolomite) were tested in a pressurized thermogravimetric analyzer (PTGA). The sorbent behaviors were explained based on complex interaction between carbonation, sulfation, and direct sulfation. The best option involved using limestone or dolomite as a SO2-sorbent in a FBC combustor following cyclic CO2 capture. Highly sintered limestone is a good sorbent for SO2 because of the generation of macropores during calcination/carbonation cycling.

Kullback-Leibler information function and the sequential selection of experiments to discriminate among several linear models

NASA Technical Reports Server (NTRS)

Sidik, S. M.

1972-01-01

The error variance of the process prior multivariate normal distributions of the parameters of the models are assumed to be specified, prior probabilities of the models being correct. A rule for termination of sampling is proposed. Upon termination, the model with the largest posterior probability is chosen as correct. If sampling is not terminated, posterior probabilities of the models and posterior distributions of the parameters are computed. An experiment was chosen to maximize the expected Kullback-Leibler information function. Monte Carlo simulation experiments were performed to investigate large and small sample behavior of the sequential adaptive procedure.

Catabolite regulation analysis of Escherichia coli for acetate overflow mechanism and co-consumption of multiple sugars based on systems biology approach using computer simulation.

PubMed

Matsuoka, Yu; Shimizu, Kazuyuki

2013-10-20

It is quite important to understand the basic principle embedded in the main metabolism for the interpretation of the fermentation data. For this, it may be useful to understand the regulation mechanism based on systems biology approach. In the present study, we considered the perturbation analysis together with computer simulation based on the models which include the effects of global regulators on the pathway activation for the main metabolism of Escherichia coli. Main focus is the acetate overflow metabolism and the co-fermentation of multiple carbon sources. The perturbation analysis was first made to understand the nature of the feed-forward loop formed by the activation of Pyk by FDP (F1,6BP), and the feed-back loop formed by the inhibition of Pfk by PEP in the glycolysis. Those together with the effect of transcription factor Cra caused by FDP level affected the glycolysis activity. The PTS (phosphotransferase system) acts as the feed-back system by repressing the glucose uptake rate for the increase in the glucose uptake rate. It was also shown that the increased PTS flux (or glucose consumption rate) causes PEP/PYR ratio to be decreased, and EIIA-P, Cya, cAMP-Crp decreased, where cAMP-Crp in turn repressed TCA cycle and more acetate is formed. This was further verified by the detailed computer simulation. In the case of multiple carbon sources such as glucose and xylose, it was shown that the sequential utilization of carbon sources was observed for wild type, while the co-consumption of multiple carbon sources with slow consumption rates were observed for the ptsG mutant by computer simulation, and this was verified by experiments. Moreover, the effect of a specific gene knockout such as Δpyk on the metabolic characteristics was also investigated based on the computer simulation. Copyright © 2013 Elsevier B.V. All rights reserved.

C-learning: A new classification framework to estimate optimal dynamic treatment regimes.

PubMed

Zhang, Baqun; Zhang, Min

2017-12-11

A dynamic treatment regime is a sequence of decision rules, each corresponding to a decision point, that determine that next treatment based on each individual's own available characteristics and treatment history up to that point. We show that identifying the optimal dynamic treatment regime can be recast as a sequential optimization problem and propose a direct sequential optimization method to estimate the optimal treatment regimes. In particular, at each decision point, the optimization is equivalent to sequentially minimizing a weighted expected misclassification error. Based on this classification perspective, we propose a powerful and flexible C-learning algorithm to learn the optimal dynamic treatment regimes backward sequentially from the last stage until the first stage. C-learning is a direct optimization method that directly targets optimizing decision rules by exploiting powerful optimization/classification techniques and it allows incorporation of patient's characteristics and treatment history to improve performance, hence enjoying advantages of both the traditional outcome regression-based methods (Q- and A-learning) and the more recent direct optimization methods. The superior performance and flexibility of the proposed methods are illustrated through extensive simulation studies. © 2017, The International Biometric Society.

Sequential evaporation of water molecules from protonated water clusters: measurement of the velocity distributions of the evaporated molecules and statistical analysis.

PubMed

Berthias, F; Feketeová, L; Abdoul-Carime, H; Calvo, F; Farizon, B; Farizon, M; Märk, T D

2018-06-22

Velocity distributions of neutral water molecules evaporated after collision induced dissociation of protonated water clusters H+(H2O)n≤10 were measured using the combined correlated ion and neutral fragment time-of-flight (COINTOF) and velocity map imaging (VMI) techniques. As observed previously, all measured velocity distributions exhibit two contributions, with a low velocity part identified by statistical molecular dynamics (SMD) simulations as events obeying the Maxwell-Boltzmann statistics and a high velocity contribution corresponding to non-ergodic events in which energy redistribution is incomplete. In contrast to earlier studies, where the evaporation of a single molecule was probed, the present study is concerned with events involving the evaporation of up to five water molecules. In particular, we discuss here in detail the cases of two and three evaporated molecules. Evaporation of several water molecules after CID can be interpreted in general as a sequential evaporation process. In addition to the SMD calculations, a Monte Carlo (MC) based simulation was developed allowing the reconstruction of the velocity distribution produced by the evaporation of m molecules from H+(H2O)n≤10 cluster ions using the measured velocity distributions for singly evaporated molecules as the input. The observed broadening of the low-velocity part of the distributions for the evaporation of two and three molecules as compared to the width for the evaporation of a single molecule results from the cumulative recoil velocity of the successive ion residues as well as the intrinsically broader distributions for decreasingly smaller parent clusters. Further MC simulations were carried out assuming that a certain proportion of non-ergodic events is responsible for the first evaporation in such a sequential evaporation series, thereby allowing to model the entire velocity distribution.

Comparison of Sequential and Variational Data Assimilation

NASA Astrophysics Data System (ADS)

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.

Structured filtering

NASA Astrophysics Data System (ADS)

Granade, Christopher; Wiebe, Nathan

2017-08-01

A major challenge facing existing sequential Monte Carlo methods for parameter estimation in physics stems from the inability of existing approaches to robustly deal with experiments that have different mechanisms that yield the results with equivalent probability. We address this problem here by proposing a form of particle filtering that clusters the particles that comprise the sequential Monte Carlo approximation to the posterior before applying a resampler. Through a new graphical approach to thinking about such models, we are able to devise an artificial-intelligence based strategy that automatically learns the shape and number of the clusters in the support of the posterior. We demonstrate the power of our approach by applying it to randomized gap estimation and a form of low circuit-depth phase estimation where existing methods from the physics literature either exhibit much worse performance or even fail completely.

Sequential estimation of surface water mass changes from daily satellite gravimetry data

NASA Astrophysics Data System (ADS)

Ramillien, G. L.; Frappart, F.; Gratton, S.; Vasseur, X.

2015-03-01

We propose a recursive Kalman filtering approach to map regional spatio-temporal variations of terrestrial water mass over large continental areas, such as South America. Instead of correcting hydrology model outputs by the GRACE observations using a Kalman filter estimation strategy, regional 2-by-2 degree water mass solutions are constructed by integration of daily potential differences deduced from GRACE K-band range rate (KBRR) measurements. Recovery of regional water mass anomaly averages obtained by accumulation of information of daily noise-free simulated GRACE data shows that convergence is relatively fast and yields accurate solutions. In the case of cumulating real GRACE KBRR data contaminated by observational noise, the sequential method of step-by-step integration provides estimates of water mass variation for the period 2004-2011 by considering a set of suitable a priori error uncertainty parameters to stabilize the inversion. Spatial and temporal averages of the Kalman filter solutions over river basin surfaces are consistent with the ones computed using global monthly/10-day GRACE solutions from official providers CSR, GFZ and JPL. They are also highly correlated to in situ records of river discharges (70-95 %), especially for the Obidos station where the total outflow of the Amazon River is measured. The sparse daily coverage of the GRACE satellite tracks limits the time resolution of the regional Kalman filter solutions, and thus the detection of short-term hydrological events.

Optimality, sample size, and power calculations for the sequential parallel comparison design.

PubMed

Ivanova, Anastasia; Qaqish, Bahjat; Schoenfeld, David A

2011-10-15

The sequential parallel comparison design (SPCD) has been proposed to increase the likelihood of success of clinical trials in therapeutic areas where high-placebo response is a concern. The trial is run in two stages, and subjects are randomized into three groups: (i) placebo in both stages; (ii) placebo in the first stage and drug in the second stage; and (iii) drug in both stages. We consider the case of binary response data (response/no response). In the SPCD, all first-stage and second-stage data from placebo subjects who failed to respond in the first stage of the trial are utilized in the efficacy analysis. We develop 1 and 2 degree of freedom score tests for treatment effect in the SPCD. We give formulae for asymptotic power and for sample size computations and evaluate their accuracy via simulation studies. We compute the optimal allocation ratio between drug and placebo in stage 1 for the SPCD to determine from a theoretical viewpoint whether a single-stage design, a two-stage design with placebo only in the first stage, or a two-stage design is the best design for a given set of response rates. As response rates are not known before the trial, a two-stage approach with allocation to active drug in both stages is a robust design choice. Copyright © 2011 John Wiley & Sons, Ltd.

Two-stage sequential sampling: A neighborhood-free adaptive sampling procedure

USGS Publications Warehouse

Salehi, M.; Smith, D.R.

2005-01-01

Designing an efficient sampling scheme for a rare and clustered population is a challenging area of research. Adaptive cluster sampling, which has been shown to be viable for such a population, is based on sampling a neighborhood of units around a unit that meets a specified condition. However, the edge units produced by sampling neighborhoods have proven to limit the efficiency and applicability of adaptive cluster sampling. We propose a sampling design that is adaptive in the sense that the final sample depends on observed values, but it avoids the use of neighborhoods and the sampling of edge units. Unbiased estimators of population total and its variance are derived using Murthy's estimator. The modified two-stage sampling design is easy to implement and can be applied to a wider range of populations than adaptive cluster sampling. We evaluate the proposed sampling design by simulating sampling of two real biological populations and an artificial population for which the variable of interest took the value either 0 or 1 (e.g., indicating presence and absence of a rare event). We show that the proposed sampling design is more efficient than conventional sampling in nearly all cases. The approach used to derive estimators (Murthy's estimator) opens the door for unbiased estimators to be found for similar sequential sampling designs. ?? 2005 American Statistical Association and the International Biometric Society.

Differentiability of simulated MEG hippocampal, medial temporal and neocortical temporal epileptic spike activity.

PubMed

Stephen, Julia M; Ranken, Doug M; Aine, Cheryl J; Weisend, Michael P; Shih, Jerry J

2005-12-01

Previous studies have shown that magnetoencephalography (MEG) can measure hippocampal activity, despite the cylindrical shape and deep location in the brain. The current study extended this work by examining the ability to differentiate the hippocampal subfields, parahippocampal cortex, and neocortical temporal sources using simulated interictal epileptic activity. A model of the hippocampus was generated on the MRIs of five subjects. CA1, CA3, and dentate gyrus of the hippocampus were activated as well as entorhinal cortex, presubiculum, and neocortical temporal cortex. In addition, pairs of sources were activated sequentially to emulate various hypotheses of mesial temporal lobe seizure generation. The simulated MEG activity was added to real background brain activity from the five subjects and modeled using a multidipole spatiotemporal modeling technique. The waveforms and source locations/orientations for hippocampal and parahippocampal sources were differentiable from neocortical temporal sources. In addition, hippocampal and parahippocampal sources were differentiated to varying degrees depending on source. The sequential activation of hippocampal and parahippocampal sources was adequately modeled by a single source; however, these sources were not resolvable when they overlapped in time. These results suggest that MEG has the sensitivity to distinguish parahippocampal and hippocampal spike generators in mesial temporal lobe epilepsy.

The Application of Neutron Transport Green's Functions to Threat Scenario Simulation

NASA Astrophysics Data System (ADS)

Thoreson, Gregory G.; Schneider, Erich A.; Armstrong, Hirotatsu; van der Hoeven, Christopher A.

2015-02-01

Radiation detectors provide deterrence and defense against nuclear smuggling attempts by scanning vehicles, ships, and pedestrians for radioactive material. Understanding detector performance is crucial to developing novel technologies, architectures, and alarm algorithms. Detection can be modeled through radiation transport simulations; however, modeling a spanning set of threat scenarios over the full transport phase-space is computationally challenging. Previous research has demonstrated Green's functions can simulate photon detector signals by decomposing the scenario space into independently simulated submodels. This paper presents decomposition methods for neutron and time-dependent transport. As a result, neutron detector signals produced from full forward transport simulations can be efficiently reconstructed by sequential application of submodel response functions.

Assessing Climate Vulnerability and Resilience of a Major Water Resource System - Inverting the Paradigm for Specific Risk Quantification at Decision Making Points of Impact

NASA Astrophysics Data System (ADS)

Murphy, K. W.; Ellis, A. W.; Skindlov, J. A.

2015-12-01

Water resource systems have provided vital support to transformative growth in the Southwest United States and the Phoenix, Arizona metropolitan area where the Salt River Project (SRP) currently satisfies 40% of the area's water demand from reservoir storage and groundwater. Large natural variability and expectations of climate changes have sensitized water management to risks posed by future periods of excess and drought. The conventional approach to impacts assessment has been downscaled climate model simulations translated through hydrologic models; but, scenario ranges enlarge as uncertainties propagate through sequential levels of modeling complexity. The research often does not reach the stage of specific impact assessments, rendering future projections frustratingly uncertain and unsuitable for complex decision-making. Alternatively, this study inverts the common approach by beginning with the threatened water system and proceeding backwards to the uncertain climate future. The methodology is built upon reservoir system response modeling to exhaustive time series of climate-driven net basin supply. A reservoir operations model, developed with SRP guidance, assesses cumulative response to inflow variability and change. Complete statistical analyses of long-term historical watershed climate and runoff data are employed for 10,000-year stochastic simulations, rendering the entire range of multi-year extremes with full probabilistic characterization. Sets of climate change projections are then translated by temperature sensitivity and precipitation elasticity into future inflow distributions that are comparatively assessed with the reservoir operations model. This approach provides specific risk assessments in pragmatic terms familiar to decision makers, interpretable within the context of long-range planning and revealing a clearer meaning of climate change projections for the region. As a transferable example achieving actionable findings, the approach can guide other communities confronting water resource planning challenges.

Development of a Non-Invasive Biomonitoring Approach to Determine Exposure to the Organophosphorus Insecticide Chlorpyrifos in Rat Saliva

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

Timchalk, Chuck; Campbell, James A.; Liu, Guodong

2007-03-01

Abstract Non-invasive biomonitoring approaches are being developed using reliable portable analytical systems to quantify dosimetry utilizing readily obtainable body fluids, such as saliva. In the current study, rats were given single oral gavage doses (1, 10 or 50 mg/kg) of the insecticide chlorpyrifos (CPF), saliva and blood were collected from groups of animals (4/time-point) at 3, 6, and 12 hr post-dosing, and the samples were analyzed for the CPF metabolite trichlorpyridinol (TCP). Trichlorpyridinol was detected in both blood and saliva at all doses and the TCP concentration in blood exceeded saliva, although the kinetics in blood and saliva were comparable.more » A physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) model for CPF incorporated a compartment model to describe the time-course of TCP in blood and saliva. The model adequately simulated the experimental results over the dose ranges evaluated. A rapid and sensitive sequential injection (SI) electrochemical immunoassay was developed to monitor TCP, and the reported detection limit for TCP in water was 6 ng/L. Computer model simulation in the range of the Allowable Daily Intake (ADI) or Reference Dose (RfD) for CPF (0.01-0.003 mg/kg/day) suggest that the electrochemical immunoassay had adequate sensitivity to detect and quantify TCP in saliva at these low exposure levels. To validate this approach further studies are needed to more fully understand the pharmacokinetics of CPF and TCP excretion in saliva. The utilization of saliva as a biomonitoring matrix, coupled to real-time quantitation and PBPK/PD modeling represents a novel approach with broad application for evaluating both occupational and environmental exposures to insecticides.« less

Characteristics of sequential swallowing of liquids in young and elderly adults: an integrative review.

PubMed

Veiga, Helena Perrut; Bianchini, Esther Mandelbaum Gonçalves

2012-01-01

To perform an integrative review of studies on liquid sequential swallowing, by characterizing the methodology of the studies and the most important findings in young and elderly adults. Review of the literature written in English and Portuguese on PubMed, LILACS, SciELO and MEDLINE databases, within the past twenty years, available fully, using the following uniterms: sequential swallowing, swallowing, dysphagia, cup, straw, in various combinations. Research articles with a methodological approach on the characterization of liquid sequential swallowing by young and/or elderly adults, regardless of health condition, excluding studies involving only the esophageal phase. The following research indicators were applied: objectives, number and gender of participants; age group; amount of liquid offered; intake instruction; utensil used, methods and main findings. 18 studies met the established criteria. The articles were categorized according to the sample characterization and the methodology on volume intake, utensil used and types of exams. Most studies investigated only healthy individuals, with no swallowing complaints. Subjects were given different instructions as to the intake of all the volume: usual manner, continually, as rapidly as possible. The findings about the characterization of sequential swallowing were varied and described in accordance with the objectives of each study. It found great variability in the methodology employed to characterize the sequential swallowing. Some findings are not comparable, and sequential swallowing is not studied in most swallowing protocols, without consensus on the influence of the utensil.

Implementing a Flipped Classroom Approach in a University Numerical Methods Mathematics Course

ERIC Educational Resources Information Center

Johnston, Barbara M.

2017-01-01

This paper describes and analyses the implementation of a "flipped classroom" approach, in an undergraduate mathematics course on numerical methods. The approach replaced all the lecture contents by instructor-made videos and was implemented in the consecutive years 2014 and 2015. The sequential case study presented here begins with an…

Race and Older Mothers’ Differentiation: A Sequential Quantitative and Qualitative Analysis

PubMed Central

Sechrist, Jori; Suitor, J. Jill; Riffin, Catherine; Taylor-Watson, Kadari; Pillemer, Karl

2011-01-01

The goal of this paper is to demonstrate a process by which qualitative and quantitative approaches are combined to reveal patterns in the data that are unlikely to be detected and confirmed by either method alone. Specifically, we take a sequential approach to combining qualitative and quantitative data to explore race differences in how mothers differentiate among their adult children. We began with a standard multivariate analysis examining race differences in mothers’ differentiation among their adult children regarding emotional closeness and confiding. Finding no race differences in this analysis, we conducted an in-depth comparison of the Black and White mothers’ narratives to determine whether there were underlying patterns that we had been unable to detect in our first analysis. Using this method, we found that Black mothers were substantially more likely than White mothers to emphasize interpersonal relationships within the family when describing differences among their children. In our final step, we developed a measure of familism based on the qualitative data and conducted a multivariate analysis to confirm the patterns revealed by the in-depth comparison of the mother’s narratives. We conclude that using such a sequential mixed methods approach to data analysis has the potential to shed new light on complex family relations. PMID:21967639

Optimal flexible sample size design with robust power.

PubMed

Zhang, Lanju; Cui, Lu; Yang, Bo

2016-08-30

It is well recognized that sample size determination is challenging because of the uncertainty on the treatment effect size. Several remedies are available in the literature. Group sequential designs start with a sample size based on a conservative (smaller) effect size and allow early stop at interim looks. Sample size re-estimation designs start with a sample size based on an optimistic (larger) effect size and allow sample size increase if the observed effect size is smaller than planned. Different opinions favoring one type over the other exist. We propose an optimal approach using an appropriate optimality criterion to select the best design among all the candidate designs. Our results show that (1) for the same type of designs, for example, group sequential designs, there is room for significant improvement through our optimization approach; (2) optimal promising zone designs appear to have no advantages over optimal group sequential designs; and (3) optimal designs with sample size re-estimation deliver the best adaptive performance. We conclude that to deal with the challenge of sample size determination due to effect size uncertainty, an optimal approach can help to select the best design that provides most robust power across the effect size range of interest. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Sequentially Simulated Outcomes: Kind Experience versus Nontransparent Description

ERIC Educational Resources Information Center

Hogarth, Robin M.; Soyer, Emre

2011-01-01

Recently, researchers have investigated differences in decision making based on description and experience. We address the issue of when experience-based judgments of probability are more accurate than are those based on description. If description is well understood ("transparent") and experience is misleading ("wicked"), it…

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

PubMed

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.

Cluster designs to assess the prevalence of acute malnutrition by lot quality assurance sampling: a validation study by computer simulation

PubMed Central

Olives, Casey; Pagano, Marcello; Deitchler, Megan; Hedt, Bethany L; Egge, Kari; Valadez, Joseph J

2009-01-01

Traditional lot quality assurance sampling (LQAS) methods require simple random sampling to guarantee valid results. However, cluster sampling has been proposed to reduce the number of random starting points. This study uses simulations to examine the classification error of two such designs, a 67×3 (67 clusters of three observations) and a 33×6 (33 clusters of six observations) sampling scheme to assess the prevalence of global acute malnutrition (GAM). Further, we explore the use of a 67×3 sequential sampling scheme for LQAS classification of GAM prevalence. Results indicate that, for independent clusters with moderate intracluster correlation for the GAM outcome, the three sampling designs maintain approximate validity for LQAS analysis. Sequential sampling can substantially reduce the average sample size that is required for data collection. The presence of intercluster correlation can impact dramatically the classification error that is associated with LQAS analysis. PMID:20011037

Footprints of electron correlation in strong-field double ionization of Kr close to the sequential-ionization regime

NASA Astrophysics Data System (ADS)

Li, Xiaokai; Wang, Chuncheng; Yuan, Zongqiang; Ye, Difa; Ma, Pan; Hu, Wenhui; Luo, Sizuo; Fu, Libin; Ding, Dajun

2017-09-01

By combining kinematically complete measurements and a semiclassical Monte Carlo simulation we study the correlated-electron dynamics in the strong-field double ionization of Kr. Interestingly, we find that, as we step into the sequential-ionization regime, there are still signatures of correlation in the two-electron joint momentum spectrum and, more intriguingly, the scaling law of the high-energy tail is completely different from early predictions on the low-Z atom (He). These experimental observations are well reproduced by our generalized semiclassical model adapting a Green-Sellin-Zachor potential. It is revealed that the competition between the screening effect of inner-shell electrons and the Coulomb focusing of nuclei leads to a non-inverse-square central force, which twists the returned electron trajectory at the vicinity of the parent core and thus significantly increases the probability of hard recollisions between two electrons. Our results might have promising applications ranging from accurately retrieving atomic structures to simulating celestial phenomena in the laboratory.

Acute Toxicity and Efficacy of Current Medical Countermeasures against VM in Guinea Pigs: A Comparison to VX and VR

DTIC Science & Technology

2013-05-01

and diazepam with and without pretreatment with pyridostigmine bromide . The 24 hr median lethal dose (MLD) of VM was determined using a sequential... pyridostigmine bromide . The 24 hr median lethal dose (MLD) of VM was determined using a sequential stage approach. The efficacy of medical...with and without pyridostigmine bromide (PB) pretreatment against lethal intoxication with VM, VR or VX. Methods Animals: Adult male Hartley

Fast assembling microarrays of superparamagnetic Fe3O4@Au nanoparticle clusters as reproducible substrates for surface-enhanced Raman scattering

NASA Astrophysics Data System (ADS)

Ye, Min; Wei, Zewen; Hu, Fei; Wang, Jianxin; Ge, Guanglu; Hu, Zhiyuan; Shao, Mingwang; Lee, Shuit-Tong; Liu, Jian

2015-08-01

It is currently a very active research area to develop new types of substrates which integrate various nanomaterials for surface-enhanced Raman scattering (SERS) techniques. Here we report a unique approach to prepare SERS substrates with reproducible performance. It features silicon mold-assisted magnetic assembling of superparamagnetic Fe3O4@Au nanoparticle clusters (NCs) into arrayed microstructures on a wafer scale. This approach enables the fabrication of both silicon-based and hydrogel-based substrates in a sequential manner. We have demonstrated that strong SERS signals can be harvested from these substrates due to an efficient coupling effect between Fe3O4@Au NCs, with enhancement factors >106. These substrates have been confirmed to provide reproducible SERS signals, with low variations in different locations or batches of samples. We investigate the spatial distributions of electromagnetic field enhancement around Fe3O4@Au NCs assemblies using finite-difference-time-domain (FDTD) simulations. The procedure to prepare the substrates is straightforward and fast. The silicon mold can be easily cleaned out and refilled with Fe3O4@Au NCs assisted by a magnet, therefore being re-useable for many cycles. Our approach has integrated microarray technologies and provided a platform for thousands of independently addressable SERS detection, in order to meet the requirements of a rapid, robust, and high throughput performance.It is currently a very active research area to develop new types of substrates which integrate various nanomaterials for surface-enhanced Raman scattering (SERS) techniques. Here we report a unique approach to prepare SERS substrates with reproducible performance. It features silicon mold-assisted magnetic assembling of superparamagnetic Fe3O4@Au nanoparticle clusters (NCs) into arrayed microstructures on a wafer scale. This approach enables the fabrication of both silicon-based and hydrogel-based substrates in a sequential manner. We have demonstrated that strong SERS signals can be harvested from these substrates due to an efficient coupling effect between Fe3O4@Au NCs, with enhancement factors >106. These substrates have been confirmed to provide reproducible SERS signals, with low variations in different locations or batches of samples. We investigate the spatial distributions of electromagnetic field enhancement around Fe3O4@Au NCs assemblies using finite-difference-time-domain (FDTD) simulations. The procedure to prepare the substrates is straightforward and fast. The silicon mold can be easily cleaned out and refilled with Fe3O4@Au NCs assisted by a magnet, therefore being re-useable for many cycles. Our approach has integrated microarray technologies and provided a platform for thousands of independently addressable SERS detection, in order to meet the requirements of a rapid, robust, and high throughput performance. Electronic supplementary information (ESI) available: XRD, reflection spectra, zeta potential, TEM images, evaluations of reproducibility, EDS, tables of EF and RSD values of different substrates. See DOI: 10.1039/c5nr02491a

68Ga-PSMA-PET/CT in Patients With Biochemical Prostate Cancer Recurrence and Negative 18F-Choline-PET/CT.

PubMed

Bluemel, Christina; Krebs, Markus; Polat, Bülent; Linke, Fränze; Eiber, Matthias; Samnick, Samuel; Lapa, Constantin; Lassmann, Michael; Riedmiller, Hubertus; Czernin, Johannes; Rubello, Domenico; Bley, Thorsten; Kropf, Saskia; Wester, Hans-Juergen; Buck, Andreas K; Herrmann, Ken

2016-07-01

Investigating the value of Ga-PSMA-PET/CT in biochemically recurring prostate cancer patients with negative F-choline-PET/CT. One hundred thirty-nine consecutive patients with biochemical recurrence after curative (surgery and/or radiotherapy) therapy were offered participation in this sequential clinical imaging approach. Patients first underwent an F-choline-PET/CT. If negative, an additional Ga-PSMA-PET/CT was offered. One hundred twenty-five of 139 eligible patients were included in the study; 32 patients underwent additional Ga-PSMA-PET/CT. Patients with equivocal findings (n = 5) on F-choline-PET/CT and those who declined the additional Ga-PSMA-PET/CT (n = 9) were excluded. Images were analyzed visually for the presence of suspicious lesions. Findings on PET/CT were correlated with PSA level, PSA doubling time (dt), and PSA velocity (vel). The overall detection rates were 85.6% (107/125) for the sequential imaging approach and 74.4% (93/125) for F-choline-PET/CT alone. Ga-PSMA-PET/CT detected sites of recurrence in 43.8% (14/32) of the choline-negative patients. Detection rates of the sequential imaging approach and F-choline-PET/CT alone increased with higher serum PSA levels and PSA vel. Subgroup analysis of Ga-PSMA-PET/CT in F-choline negative patients revealed detection rates of 28.6%, 45.5%, and 71.4% for PSA levels of 0.2 or greater to less than 1 ng/mL, 1 to 2 ng/mL, and greater than 2 ng/mL, respectively. The sequential imaging approach designed to limit Ga-PSMA imaging to patients with negative choline scans resulted in high detection rates. Ga-PSMA-PET/CT identified sites of recurrent disease in 43.8% of the patients with negative F-choline PET/CT scans.

68Ga-PSMA-PET/CT in Patients With Biochemical Prostate Cancer Recurrence and Negative 18F-Choline-PET/CT

PubMed Central

Bluemel, Christina; Krebs, Markus; Polat, Bülent; Linke, Fränze; Eiber, Matthias; Samnick, Samuel; Lapa, Constantin; Lassmann, Michael; Riedmiller, Hubertus; Czernin, Johannes; Rubello, Domenico; Bley, Thorsten; Kropf, Saskia; Wester, Hans-Juergen; Buck, Andreas K.; Herrmann, Ken

2016-01-01

Purpose Investigating the value of 68Ga-PSMA-PET/CT in biochemically recurring prostate cancer patients with negative 18F-choline-PET/CT. Patients and Methods One hundred thirty-nine consecutive patients with biochemical recurrence after curative (surgery and/or radiotherapy) therapy were offered participation in this sequential clinical imaging approach. Patients first underwent an 18F-choline-PET/CT. If negative, an additional 68Ga-PSMA-PET/CTwas offered. One hundred twenty-five of 139 eligible patients were included in the study; 32 patients underwent additional 68Ga-PSMA-PET/CT. Patients with equivocal findings (n = 5) on 18F-choline-PET/CT and those who declined the additional 68Ga-PSMA-PET/CT (n = 9) were excluded. Images were analyzed visually for the presence of suspicious lesions. Findings on PET/CT were correlated with PSA level, PSA doubling time (dt), and PSA velocity (vel). Results The overall detection rates were 85.6% (107/125) for the sequential imaging approach and 74.4% (93/125) for 18F-choline-PET/CT alone. 68Ga-PSMA-PET/CT detected sites of recurrence in 43.8% (14/32) of the choline-negative patients. Detection rates of the sequential imaging approach and 18F-choline-PET/CT alone increased with higher serum PSA levels and PSA vel. Subgroup analysis of 68Ga-PSMA-PET/CT in 18F-choline negative patients revealed detection rates of 28.6%, 45.5%, and 71.4% for PSA levels of 0.2 or greater to less than 1 ng/mL, 1 to 2 ng/mL, and greater than 2 ng/mL, respectively. Conclusions The sequential imaging approach designed to limit 68Ga-PSMA imaging to patients with negative choline scans resulted in high detection rates. 68Ga-PSMA-PET/CT identified sites of recurrent disease in 43.8% of the patients with negative 18F-choline PET/CT scans. PMID:26975008

Sequential cyclophosphamide-bortezomib-dexamethasone unmasks the harmful cardiac effect of dexamethasone in primary light-chain cardiac amyloidosis.

PubMed

Le Bras, Fabien; Molinier-Frenkel, Valerie; Guellich, Aziz; Dupuis, Jehan; Belhadj, Karim; Guendouz, Soulef; Ayad, Karima; Colombat, Magali; Benhaiem, Nicole; Tissot, Claire Marie; Hulin, Anne; Jaccard, Arnaud; Damy, Thibaud

2017-05-01

Chemotherapy combining cyclophosphamide, bortezomib and dexamethasone is widely used in light-chain amyloidosis. The benefit is limited in patients with cardiac amyloidosis mainly because of adverse cardiac events. Retrospective analysis of our cohort showed that 39 patients died with 42% during the first month. A new escalation-sequential regimen was set to improve the outcomes. Nine newly-diagnosed patients were prospectively treated with close monitoring of serum N-terminal pro-brain natriuretic peptide, troponin-T and free light chains. The results show that corticoids may destabilise the heart through fluid retention. Thus, a sequential protocol may be a promising approach to treat these patients. Copyright © 2017 Elsevier Ltd. All rights reserved.

Simultaneous bilateral stereotactic procedure for deep brain stimulation implants: a significant step for reducing operation time.

PubMed

Fonoff, Erich Talamoni; Azevedo, Angelo; Angelos, Jairo Silva Dos; Martinez, Raquel Chacon Ruiz; Navarro, Jessie; Reis, Paul Rodrigo; Sepulveda, Miguel Ernesto San Martin; Cury, Rubens Gisbert; Ghilardi, Maria Gabriela Dos Santos; Teixeira, Manoel Jacobsen; Lopez, William Omar Contreras

2016-07-01

OBJECT Currently, bilateral procedures involve 2 sequential implants in each of the hemispheres. The present report demonstrates the feasibility of simultaneous bilateral procedures during the implantation of deep brain stimulation (DBS) leads. METHODS Fifty-seven patients with movement disorders underwent bilateral DBS implantation in the same study period. The authors compared the time required for the surgical implantation of deep brain electrodes in 2 randomly assigned groups. One group of 28 patients underwent traditional sequential electrode implantation, and the other 29 patients underwent simultaneous bilateral implantation. Clinical outcomes of the patients with Parkinson's disease (PD) who had undergone DBS implantation of the subthalamic nucleus using either of the 2 techniques were compared. RESULTS Overall, a reduction of 38.51% in total operating time for the simultaneous bilateral group (136.4 ± 20.93 minutes) as compared with that for the traditional consecutive approach (220.3 ± 27.58 minutes) was observed. Regarding clinical outcomes in the PD patients who underwent subthalamic nucleus DBS implantation, comparing the preoperative off-medication condition with the off-medication/on-stimulation condition 1 year after the surgery in both procedure groups, there was a mean 47.8% ± 9.5% improvement in the Unified Parkinson's Disease Rating Scale Part III (UPDRS-III) score in the simultaneous group, while the sequential group experienced 47.5% ± 15.8% improvement (p = 0.96). Moreover, a marked reduction in the levodopa-equivalent dose from preoperatively to postoperatively was similar in these 2 groups. The simultaneous bilateral procedure presented major advantages over the traditional sequential approach, with a shorter total operating time. CONCLUSIONS A simultaneous stereotactic approach significantly reduces the operation time in bilateral DBS procedures, resulting in decreased microrecording time, contributing to the optimization of functional stereotactic procedures.

Testing Quantum Models of Conjunction Fallacy on the World Wide Web

NASA Astrophysics Data System (ADS)

Aerts, Diederik; Arguëlles, Jonito Aerts; Beltran, Lester; Beltran, Lyneth; de Bianchi, Massimiliano Sassoli; Sozzo, Sandro; Veloz, Tomas

2017-12-01

The `conjunction fallacy' has been extensively debated by scholars in cognitive science and, in recent times, the discussion has been enriched by the proposal of modeling the fallacy using the quantum formalism. Two major quantum approaches have been put forward: the first assumes that respondents use a two-step sequential reasoning and that the fallacy results from the presence of `question order effects'; the second assumes that respondents evaluate the cognitive situation as a whole and that the fallacy results from the `emergence of new meanings', as an `effect of overextension' in the conceptual conjunction. Thus, the question arises as to determine whether and to what extent conjunction fallacies would result from `order effects' or, instead, from `emergence effects'. To help clarify this situation, we propose to use the World Wide Web as an `information space' that can be interrogated both in a sequential and non-sequential way, to test these two quantum approaches. We find that `emergence effects', and not `order effects', should be considered the main cognitive mechanism producing the observed conjunction fallacies.

Sequential time interleaved random equivalent sampling for repetitive signal.

PubMed

Zhao, Yijiu; Liu, Jingjing

2016-12-01

Compressed sensing (CS) based sampling techniques exhibit many advantages over other existing approaches for sparse signal spectrum sensing; they are also incorporated into non-uniform sampling signal reconstruction to improve the efficiency, such as random equivalent sampling (RES). However, in CS based RES, only one sample of each acquisition is considered in the signal reconstruction stage, and it will result in more acquisition runs and longer sampling time. In this paper, a sampling sequence is taken in each RES acquisition run, and the corresponding block measurement matrix is constructed using a Whittaker-Shannon interpolation formula. All the block matrices are combined into an equivalent measurement matrix with respect to all sampling sequences. We implemented the proposed approach with a multi-cores analog-to-digital converter (ADC), whose ADC cores are time interleaved. A prototype realization of this proposed CS based sequential random equivalent sampling method has been developed. It is able to capture an analog waveform at an equivalent sampling rate of 40 GHz while sampled at 1 GHz physically. Experiments indicate that, for a sparse signal, the proposed CS based sequential random equivalent sampling exhibits high efficiency.

In-situ sequential laser transfer and laser reduction of graphene oxide films

NASA Astrophysics Data System (ADS)

Papazoglou, S.; Petridis, C.; Kymakis, E.; Kennou, S.; Raptis, Y. S.; Chatzandroulis, S.; Zergioti, I.

2018-04-01

Achieving high quality transfer of graphene on selected substrates is a priority in device fabrication, especially where drop-on-demand applications are involved. In this work, we report an in-situ, fast, simple, and one step process that resulted in the reduction, transfer, and fabrication of reduced graphene oxide-based humidity sensors, using picosecond laser pulses. By tuning the laser illumination parameters, we managed to implement the sequential printing and reduction of graphene oxide flakes. The overall process lasted only a few seconds compared to a few hours that our group has previously published. DC current measurements, X-Ray Photoelectron Spectroscopy, X-Ray Diffraction, and Raman Spectroscopy were employed in order to assess the efficiency of our approach. To demonstrate the applicability and the potential of the technique, laser printed reduced graphene oxide humidity sensors with a limit of detection of 1700 ppm are presented. The results demonstrated in this work provide a selective, rapid, and low-cost approach for sequential transfer and photochemical reduction of graphene oxide micro-patterns onto various substrates for flexible electronics and sensor applications.

Simultaneous biodegradation of three mononitrophenol isomers by a tailor-made microbial consortium immobilized in sequential batch reactors.

PubMed

Fu, H; Zhang, J-J; Xu, Y; Chao, H-J; Zhou, N-Y

2017-03-01

The ortho-nitrophenol (ONP)-utilizing Alcaligenes sp. strain NyZ215, meta-nitrophenol (MNP)-utilizing Cupriavidus necator JMP134 and para-nitrophenol (PNP)-utilizing Pseudomonas sp. strain WBC-3 were assembled as a consortium to degrade three nitrophenol isomers in sequential batch reactors. Pilot test was conducted in flasks to demonstrate that a mixture of three mononitrophenols at 0·5 mol l -1 each could be mineralized by this microbial consortium within 84 h. Interestingly, neither ONP nor MNP was degraded until PNP was almost consumed by strain WBC-3. By immobilizing this consortium into polyurethane cubes, all three mononitrophenols were continuously degraded in lab-scale sequential reactors for six batch cycles over 18 days. Total concentrations of ONP, MMP and PNP that were degraded were 2·8, 1·5 and 2·3 mol l -1 during this time course respectively. Quantitative real-time PCR analysis showed that each member in the microbial consortium was relatively stable during the entire degradation process. This study provides a novel approach to treat polluted water, particularly with a mixture of co-existing isomers. Nitroaromatic compounds are readily spread in the environment and pose great potential toxicity concerns. Here, we report the simultaneous degradation of three isomers of mononitrophenol in a single system by employing a consortium of three bacteria, both in flasks and lab-scale sequential batch reactors. The results demonstrate that simultaneous biodegradation of three mononitrophenol isomers can be achieved by a tailor-made microbial consortium immobilized in sequential batch reactors, providing a pilot study for a novel approach for the bioremediation of mixed pollutants, especially isomers present in wastewater. © 2016 The Society for Applied Microbiology.

Sequential simulation approach to modeling of multi-seam coal deposits with an application to the assessment of a Louisiana lignite

USGS Publications Warehouse

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.

Optical and structural properties of cobalt-permalloy slanted columnar heterostructure thin films

NASA Astrophysics Data System (ADS)

Sekora, Derek; Briley, Chad; Schubert, Mathias; Schubert, Eva

2017-11-01

Optical and structural properties of sequential Co-column-NiFe-column slanted columnar heterostructure thin films with an Al2O3 passivation coating are reported. Electron-beam evaporated glancing angle deposition is utilized to deposit the sequential multiple-material slanted columnar heterostructure thin films. Mueller matrix generalized spectroscopic ellipsometry data is analyzed with a best-match model approach employing the anisotropic Bruggeman effective medium approximation formalism to determine bulk-like and anisotropic optical and structural properties of the individual Co and NiFe slanted columnar material sub-layers. Scanning electron microscopy is applied to image the Co-NiFe sequential growth properties and to verify the results of the ellipsometric analysis. Comparisons to single-material slanted columnar thin films and optically bulk solid thin films are presented and discussed. We find that the optical and structural properties of each material sub-layer of the sequential slanted columnar heterostructure film are distinct from each other and resemble those of their respective single-material counterparts.

An Iterative Approach for the Optimization of Pavement Maintenance Management at the Network Level

PubMed Central

Torres-Machí, Cristina; Chamorro, Alondra; Videla, Carlos; Yepes, Víctor

2014-01-01

Pavement maintenance is one of the major issues of public agencies. Insufficient investment or inefficient maintenance strategies lead to high economic expenses in the long term. Under budgetary restrictions, the optimal allocation of resources becomes a crucial aspect. Two traditional approaches (sequential and holistic) and four classes of optimization methods (selection based on ranking, mathematical optimization, near optimization, and other methods) have been applied to solve this problem. They vary in the number of alternatives considered and how the selection process is performed. Therefore, a previous understanding of the problem is mandatory to identify the most suitable approach and method for a particular network. This study aims to assist highway agencies, researchers, and practitioners on when and how to apply available methods based on a comparative analysis of the current state of the practice. Holistic approach tackles the problem considering the overall network condition, while the sequential approach is easier to implement and understand, but may lead to solutions far from optimal. Scenarios defining the suitability of these approaches are defined. Finally, an iterative approach gathering the advantages of traditional approaches is proposed and applied in a case study. The proposed approach considers the overall network condition in a simpler and more intuitive manner than the holistic approach. PMID:24741352

An iterative approach for the optimization of pavement maintenance management at the network level.

PubMed

Torres-Machí, Cristina; Chamorro, Alondra; Videla, Carlos; Pellicer, Eugenio; Yepes, Víctor

2014-01-01

Pavement maintenance is one of the major issues of public agencies. Insufficient investment or inefficient maintenance strategies lead to high economic expenses in the long term. Under budgetary restrictions, the optimal allocation of resources becomes a crucial aspect. Two traditional approaches (sequential and holistic) and four classes of optimization methods (selection based on ranking, mathematical optimization, near optimization, and other methods) have been applied to solve this problem. They vary in the number of alternatives considered and how the selection process is performed. Therefore, a previous understanding of the problem is mandatory to identify the most suitable approach and method for a particular network. This study aims to assist highway agencies, researchers, and practitioners on when and how to apply available methods based on a comparative analysis of the current state of the practice. Holistic approach tackles the problem considering the overall network condition, while the sequential approach is easier to implement and understand, but may lead to solutions far from optimal. Scenarios defining the suitability of these approaches are defined. Finally, an iterative approach gathering the advantages of traditional approaches is proposed and applied in a case study. The proposed approach considers the overall network condition in a simpler and more intuitive manner than the holistic approach.

Intra-individual diagnostic image quality and organ-specific-radiation dose comparison between spiral cCT with iterative image reconstruction and z-axis automated tube current modulation and sequential cCT.

PubMed

Wenz, Holger; Maros, Máté E; Meyer, Mathias; Gawlitza, Joshua; Förster, Alex; Haubenreisser, Holger; Kurth, Stefan; Schoenberg, Stefan O; Groden, Christoph; Henzler, Thomas

2016-01-01

To prospectively evaluate image quality and organ-specific-radiation dose of spiral cranial CT (cCT) combined with automated tube current modulation (ATCM) and iterative image reconstruction (IR) in comparison to sequential tilted cCT reconstructed with filtered back projection (FBP) without ATCM. 31 patients with a previous performed tilted non-contrast enhanced sequential cCT aquisition on a 4-slice CT system with only FBP reconstruction and no ATCM were prospectively enrolled in this study for a clinical indicated cCT scan. All spiral cCT examinations were performed on a 3rd generation dual-source CT system using ATCM in z-axis direction. Images were reconstructed using both, FBP and IR (level 1-5). A Monte-Carlo-simulation-based analysis was used to compare organ-specific-radiation dose. Subjective image quality for various anatomic structures was evaluated using a 4-point Likert-scale and objective image quality was evaluated by comparing signal-to-noise ratios (SNR). Spiral cCT led to a significantly lower (p < 0.05) organ-specific-radiation dose in all targets including eye lense. Subjective image quality of spiral cCT datasets with an IR reconstruction level 5 was rated significantly higher compared to the sequential cCT acquisitions (p < 0.0001). Consecutive mean SNR was significantly higher in all spiral datasets (FBP, IR 1-5) when compared to sequential cCT with a mean SNR improvement of 44.77% (p < 0.0001). Spiral cCT combined with ATCM and IR allows for significant-radiation dose reduction including a reduce eye lens organ-dose when compared to a tilted sequential cCT while improving subjective and objective image quality.

Proposed hardware architectures of particle filter for object tracking

NASA Astrophysics Data System (ADS)

Abd El-Halym, Howida A.; Mahmoud, Imbaby Ismail; Habib, SED

2012-12-01

In this article, efficient hardware architectures for particle filter (PF) are presented. We propose three different architectures for Sequential Importance Resampling Filter (SIRF) implementation. The first architecture is a two-step sequential PF machine, where particle sampling, weight, and output calculations are carried out in parallel during the first step followed by sequential resampling in the second step. For the weight computation step, a piecewise linear function is used instead of the classical exponential function. This decreases the complexity of the architecture without degrading the results. The second architecture speeds up the resampling step via a parallel, rather than a serial, architecture. This second architecture targets a balance between hardware resources and the speed of operation. The third architecture implements the SIRF as a distributed PF composed of several processing elements and central unit. All the proposed architectures are captured using VHDL synthesized using Xilinx environment, and verified using the ModelSim simulator. Synthesis results confirmed the resource reduction and speed up advantages of our architectures.

Use of personalized Dynamic Treatment Regimes (DTRs) and Sequential Multiple Assignment Randomized Trials (SMARTs) in mental health studies

PubMed Central

Liu, Ying; ZENG, Donglin; WANG, Yuanjia

2014-01-01

Summary Dynamic treatment regimens (DTRs) are sequential decision rules tailored at each point where a clinical decision is made based on each patient’s time-varying characteristics and intermediate outcomes observed at earlier points in time. The complexity, patient heterogeneity, and chronicity of mental disorders call for learning optimal DTRs to dynamically adapt treatment to an individual’s response over time. The Sequential Multiple Assignment Randomized Trial (SMARTs) design allows for estimating causal effects of DTRs. Modern statistical tools have been developed to optimize DTRs based on personalized variables and intermediate outcomes using rich data collected from SMARTs; these statistical methods can also be used to recommend tailoring variables for designing future SMART studies. This paper introduces DTRs and SMARTs using two examples in mental health studies, discusses two machine learning methods for estimating optimal DTR from SMARTs data, and demonstrates the performance of the statistical methods using simulated data. PMID:25642116

Speckle pattern sequential extraction metric for estimating the focus spot size on a remote diffuse target.

PubMed

Yu, Zhan; Li, Yuanyang; Liu, Lisheng; Guo, Jin; Wang, Tingfeng; Yang, Guoqing

2017-11-10

The speckle pattern (line by line) sequential extraction (SPSE) metric is proposed by the one-dimensional speckle intensity level crossing theory. Through the sequential extraction of received speckle information, the speckle metrics for estimating the variation of focusing spot size on a remote diffuse target are obtained. Based on the simulation, we will give some discussions about the SPSE metric range of application under the theoretical conditions, and the aperture size will affect the metric performance of the observation system. The results of the analyses are verified by the experiment. This method is applied to the detection of relative static target (speckled jitter frequency is less than the CCD sampling frequency). The SPSE metric can determine the variation of the focusing spot size over a long distance, moreover, the metric will estimate the spot size under some conditions. Therefore, the monitoring and the feedback of far-field spot will be implemented laser focusing system applications and help the system to optimize the focusing performance.

Re-animation of muscle flaps for improved function in dynamic myoplasty.

PubMed

Stremel, R W; Zonnevijlle, E D

2001-01-01

The authors report on a series of experiments designed to produce a skeletal muscle contraction functional for dynamic myoplasties. Conventional stimulation techniques recruit all or most of the muscle fibers simultaneously and with maximal strength. This approach has limitations in free dynamic muscle flap transfers that require the muscle to contract immediately after transfer and before re-innervation. Sequential stimulation of segments of the transferred muscle provides a means of producing non-fatiguing contractions of the muscle in the presence or absence of innervation. The muscles studied were the canine gracilis, and all experiments were acute studies in anesthetized animals. Comparison of conventional and sequential segmental neuromuscular stimulation revealed an increase in muscle fatigue resistance and muscle blood flow with the new approach. This approach offers the opportunity for development of physiologically animated tissue and broadening the abilities of reconstructive surgeons in the repair of functional defects. Copyright 2001 Wiley-Liss, Inc.

A sequential factorial analysis approach to characterize the effects of uncertainties for supporting air quality management

NASA Astrophysics Data System (ADS)

Wang, S.; Huang, G. H.; Veawab, A.

2013-03-01

This study proposes a sequential factorial analysis (SFA) approach for supporting regional air quality management under uncertainty. SFA is capable not only of examining the interactive effects of input parameters, but also of analyzing the effects of constraints. When there are too many factors involved in practical applications, SFA has the advantage of conducting a sequence of factorial analyses for characterizing the effects of factors in a systematic manner. The factor-screening strategy employed in SFA is effective in greatly reducing the computational effort. The proposed SFA approach is applied to a regional air quality management problem for demonstrating its applicability. The results indicate that the effects of factors are evaluated quantitatively, which can help decision makers identify the key factors that have significant influence on system performance and explore the valuable information that may be veiled beneath their interrelationships.

An Overview of the State of the Art in Atomistic and Multiscale Simulation of Fracture

NASA Technical Reports Server (NTRS)

Saether, Erik; Yamakov, Vesselin; Phillips, Dawn R.; Glaessgen, Edward H.

2009-01-01

The emerging field of nanomechanics is providing a new focus in the study of the mechanics of materials, particularly in simulating fundamental atomic mechanisms involved in the initiation and evolution of damage. Simulating fundamental material processes using first principles in physics strongly motivates the formulation of computational multiscale methods to link macroscopic failure to the underlying atomic processes from which all material behavior originates. This report gives an overview of the state of the art in applying concurrent and sequential multiscale methods to analyze damage and failure mechanisms across length scales.

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

PubMed

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.

The Obstacles for the Teaching of 8th Grade TR History of Revolution and Kemalism Course According to the Constructivist Approach (An Example of Exploratory Sequential Mixed Method Design)

ERIC Educational Resources Information Center

Karademir, Yavuz; Demir, Selcuk Besir

2015-01-01

The aim of this study is to ascertain the problems social studies teachers face in the teaching of topics covered in 8th grade TRHRK Course. The study was conducted in line with explanatory sequential mixed method design, which is one of the mixed research method, was used. The study involves three phases. In the first step, exploratory process…

A Sequential Linear Quadratic Approach for Constrained Nonlinear Optimal Control with Adaptive Time Discretization and Application to Higher Elevation Mars Landing Problem

NASA Astrophysics Data System (ADS)

Sandhu, Amit

A sequential quadratic programming method is proposed for solving nonlinear optimal control problems subject to general path constraints including mixed state-control and state only constraints. The proposed algorithm further develops on the approach proposed in [1] with objective to eliminate the use of a high number of time intervals for arriving at an optimal solution. This is done by introducing an adaptive time discretization to allow formation of a desirable control profile without utilizing a lot of intervals. The use of fewer time intervals reduces the computation time considerably. This algorithm is further used in this thesis to solve a trajectory planning problem for higher elevation Mars landing.

Large-area copper indium diselenide (CIS) process, control and manufacturing

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

Gillespie, T.J.; Lanning, B.R.; Marshall, C.H.

1997-12-31

Lockheed Martin Astronautics (LMA) has developed a large-area (30x30cm) sequential CIS manufacturing approach amenable to low-cost photovoltaics (PV) production. A prototype CIS manufacturing system has been designed and built with compositional uniformity (Cu/In ratio) verified within {+-}4 atomic percent over the 30x30cm area. CIS device efficiencies have been measured by the National Renewable Energy Laboratory (NREL) at 7% on a flexible non-sodium-containing substrate and 10% on a soda-lime-silica (SLS) glass substrate. Critical elements of the manufacturing capability include the CIS sequential process selection, uniform large-area material deposition, and in-situ process control. Details of the process and large-area manufacturing approach aremore » discussed and results presented.« less

Simulation reframed.

PubMed

Kneebone, Roger L

2016-01-01

Simulation is firmly established as a mainstay of clinical education, and extensive research has demonstrated its value. Current practice uses inanimate simulators (with a range of complexity, sophistication and cost) to address the patient 'as body' and trained actors or lay people (Simulated Patients) to address the patient 'as person'. These approaches are often separate.Healthcare simulation to date has been largely for the training and assessment of clinical 'insiders', simulating current practices. A close coupling with the clinical world restricts access to the facilities and practices of simulation, often excluding patients, families and publics. Yet such perspectives are an essential component of clinical practice. This paper argues that simulation offers opportunities to move outside a clinical 'insider' frame and create connections with other individuals and groups. Simulation becomes a bridge between experts whose worlds do not usually intersect, inviting an exchange of insights around embodied practices-the 'doing' of medicine-without jeopardising the safety of actual patients.Healthcare practice and education take place within a clinical frame that often conceals parallels with other domains of expert practice. Valuable insights emerge by viewing clinical practice not only as the application of medical science but also as performance and craftsmanship.Such connections require a redefinition of simulation. Its essence is not expensive elaborate facilities. Developments such as hybrid, distributed and sequential simulation offer examples of how simulation can combine 'patient as body' with 'patient as person' at relatively low cost, democratising simulation and exerting traction beyond the clinical sphere.The essence of simulation is a purposeful design, based on an active process of selection from an originary world, abstraction of what is criterial and re - presentation in another setting for a particular purpose or audience. This may be done within traditional simulation centres, or outside in local communities, public spaces or arts and performance venues. Simulation has established a central role in clinical education but usually focuses on learning to do things as they are already done. Imaginatively designed, simulation offers untapped potential for deep engagement with patients, publics and experts outside medicine.

Formation of fivefold deformation twins in nanocrystalline face-centered-cubic copper based on molecular dynamics simulations

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

Cao, A. J.; Wei, Y. G.

2006-07-24

Fivefold deformation twins were reported recently to be observed in the experiment of the nanocrystalline face-centered-cubic metals and alloys. However, they were not predicted previously based on the molecular dynamics (MD) simulations and the reason was thought to be a uniaxial tension considered in the simulations. In the present investigation, through introducing pretwins in grain regions, using the MD simulations, the authors predict out the fivefold deformation twins in the grain regions of the nanocrystal grain cell, which undergoes a uniaxial tension. It is shown in their simulation results that series of Shockley partial dislocations emitted from grain boundaries providemore » sequential twining mechanism, which results in fivefold deformation twins.« less

Methodology of modeling and measuring computer architectures for plasma simulations

NASA Technical Reports Server (NTRS)

Wang, L. P. T.

1977-01-01

A brief introduction to plasma simulation using computers and the difficulties on currently available computers is given. Through the use of an analyzing and measuring methodology - SARA, the control flow and data flow of a particle simulation model REM2-1/2D are exemplified. After recursive refinements the total execution time may be greatly shortened and a fully parallel data flow can be obtained. From this data flow, a matched computer architecture or organization could be configured to achieve the computation bound of an application problem. A sequential type simulation model, an array/pipeline type simulation model, and a fully parallel simulation model of a code REM2-1/2D are proposed and analyzed. This methodology can be applied to other application problems which have implicitly parallel nature.

Application of the sequential quadratic programming algorithm for reconstructing the distribution of optical parameters based on the time-domain radiative transfer equation.

PubMed

Qi, Hong; Qiao, Yao-Bin; Ren, Ya-Tao; Shi, Jing-Wen; Zhang, Ze-Yu; Ruan, Li-Ming

2016-10-17

Sequential quadratic programming (SQP) is used as an optimization algorithm to reconstruct the optical parameters based on the time-domain radiative transfer equation (TD-RTE). Numerous time-resolved measurement signals are obtained using the TD-RTE as forward model. For a high computational efficiency, the gradient of objective function is calculated using an adjoint equation technique. SQP algorithm is employed to solve the inverse problem and the regularization term based on the generalized Gaussian Markov random field (GGMRF) model is used to overcome the ill-posed problem. Simulated results show that the proposed reconstruction scheme performs efficiently and accurately.

Discrete filtering techniques applied to sequential GPS range measurements

NASA Technical Reports Server (NTRS)

Vangraas, Frank

1987-01-01

The basic navigation solution is described for position and velocity based on range and delta range (Doppler) measurements from NAVSTAR Global Positioning System satellites. The application of discrete filtering techniques is examined to reduce the white noise distortions on the sequential range measurements. A second order (position and velocity states) Kalman filter is implemented to obtain smoothed estimates of range by filtering the dynamics of the signal from each satellite separately. Test results using a simulated GPS receiver show a steady-state noise reduction, the input noise variance divided by the output noise variance, of a factor of four. Recommendations for further noise reduction based on higher order Kalman filters or additional delta range measurements are included.

Toward statistical modeling of saccadic eye-movement and visual saliency.

PubMed

Sun, Xiaoshuai; Yao, Hongxun; Ji, Rongrong; Liu, Xian-Ming

2014-11-01

In this paper, we present a unified statistical framework for modeling both saccadic eye movements and visual saliency. By analyzing the statistical properties of human eye fixations on natural images, we found that human attention is sparsely distributed and usually deployed to locations with abundant structural information. This observations inspired us to model saccadic behavior and visual saliency based on super-Gaussian component (SGC) analysis. Our model sequentially obtains SGC using projection pursuit, and generates eye movements by selecting the location with maximum SGC response. Besides human saccadic behavior simulation, we also demonstrated our superior effectiveness and robustness over state-of-the-arts by carrying out dense experiments on synthetic patterns and human eye fixation benchmarks. Multiple key issues in saliency modeling research, such as individual differences, the effects of scale and blur, are explored in this paper. Based on extensive qualitative and quantitative experimental results, we show promising potentials of statistical approaches for human behavior research.

Modelling language evolution: Examples and predictions

NASA Astrophysics Data System (ADS)

Gong, Tao; Shuai, Lan; Zhang, Menghan

2014-06-01

We survey recent computer modelling research of language evolution, focusing on a rule-based model simulating the lexicon-syntax coevolution and an equation-based model quantifying the language competition dynamics. We discuss four predictions of these models: (a) correlation between domain-general abilities (e.g. sequential learning) and language-specific mechanisms (e.g. word order processing); (b) coevolution of language and relevant competences (e.g. joint attention); (c) effects of cultural transmission and social structure on linguistic understandability; and (d) commonalities between linguistic, biological, and physical phenomena. All these contribute significantly to our understanding of the evolutions of language structures, individual learning mechanisms, and relevant biological and socio-cultural factors. We conclude the survey by highlighting three future directions of modelling studies of language evolution: (a) adopting experimental approaches for model evaluation; (b) consolidating empirical foundations of models; and (c) multi-disciplinary collaboration among modelling, linguistics, and other relevant disciplines.

Joint Modeling Approach for Semicompeting Risks Data with Missing Nonterminal Event Status

PubMed Central

Hu, Chen; Tsodikov, Alex

2014-01-01

Semicompeting risks data, where a subject may experience sequential non-terminal and terminal events, and the terminal event may censor the non-terminal event but not vice versa, are widely available in many biomedical studies. We consider the situation when a proportion of subjects’ non-terminal events is missing, such that the observed data become a mixture of “true” semicompeting risks data and partially observed terminal event only data. An illness-death multistate model with proportional hazards assumptions is proposed to study the relationship between non-terminal and terminal events, and provide covariate-specific global and local association measures. Maximum likelihood estimation based on semiparametric regression analysis is used for statistical inference, and asymptotic properties of proposed estimators are studied using empirical process and martingale arguments. We illustrate the proposed method with simulation studies and data analysis of a follicular cell lymphoma study. PMID:24430204

Programming scheme based optimization of hybrid 4T-2R OxRAM NVSRAM

NASA Astrophysics Data System (ADS)

Majumdar, Swatilekha; Kingra, Sandeep Kaur; Suri, Manan

2017-09-01

In this paper, we present a novel single-cycle programming scheme for 4T-2R NVSRAM, exploiting pulse engineered input signals. OxRAM devices based on 3 nm thick bi-layer active switching oxide and 90 nm CMOS technology node were used for all simulations. The cell design is implemented for real-time non-volatility rather than last-bit, or power-down non-volatility. Detailed analysis of the proposed single-cycle, parallel RRAM device programming scheme is presented in comparison to the two-cycle sequential RRAM programming used for similar 4T-2R NVSRAM bit-cells. The proposed single-cycle programming scheme coupled with the 4T-2R architecture leads to several benefits such as- possibility of unconventional transistor sizing, 50% lower latency, 20% improvement in SNM and ∼20× reduced energy requirements, when compared against two-cycle programming approach.

Observer Training Revisited: A Comparison of in Vivo and Video Instruction

ERIC Educational Resources Information Center

Dempsey, Carrie M.; Iwata, Brian A.; Fritz, Jennifer N.; Rolider, Natalie U.

2012-01-01

We compared the effects of 2 observer-training procedures. In vivo training involved practice during actual treatment sessions. Video training involved practice while watching progressively more complex simulations. Fifty-nine undergraduate students entered 1 of the 2 training conditions sequentially according to an ABABAB design. Results showed…

Say again? How complexity and format of air traffic control instructions affect pilot recall

DOT National Transportation Integrated Search

1999-01-01

This study compared the recall of ATC information presented in cither grouped or sequential format : in a part-task simulation. It also tested the effect of complexity of ATC clearances on recall, that is, : how many pieces of information a single tr...

AN IN VITRO GASTROINTESTINAL METHOD TO ESTIMATE BIOAVAILABLE ARSENIC IN CONTAMINATED SOILS AND SOLID MEDIA. (R825410)

EPA Science Inventory

A method was developed to simulate the human gastrointestinal environment and
to estimate bioavailability of arsenic in contaminated soil and solid media. In
this in vitro gastrointestinal (IVG) method, arsenic is sequentially extracted
from contaminated soil with ...

Numerical modeling of flow and transport in the far-field of a generic nuclear waste repository in fractured crystalline rock using updated fracture continuum model

NASA Astrophysics Data System (ADS)

Hadgu, T.; Kalinina, E.; Klise, K. A.; Wang, Y.

2016-12-01

Disposal of high-level radioactive waste in a deep geological repository in crystalline host rock is one of the potential options for long term isolation. Characterization of the natural barrier system is an important component of the disposal option. In this study we present numerical modeling of flow and transport in fractured crystalline rock using an updated fracture continuum model (FCM). The FCM is a stochastic method that maps the permeability of discrete fractures onto a regular grid. The original method by McKenna and Reeves (2005) has been updated to provide capabilities that enhance representation of fractured rock. As reported in Hadgu et al. (2015) the method was first modified to include fully three-dimensional representations of anisotropic permeability, multiple independent fracture sets, and arbitrary fracture dips and orientations, and spatial correlation. More recently the FCM has been extended to include three different methods. (1) The Sequential Gaussian Simulation (SGSIM) method uses spatial correlation to generate fractures and define their properties for FCM (2) The ELLIPSIM method randomly generates a specified number of ellipses with properties defined by probability distributions. Each ellipse represents a single fracture. (3) Direct conversion of discrete fracture network (DFN) output. Test simulations were conducted to simulate flow and transport using ELLIPSIM and direct conversion of DFN methods. The simulations used a 1 km x 1km x 1km model domain and a structured with grid block of size of 10 m x 10m x 10m, resulting in a total of 106 grid blocks. Distributions of fracture parameters were used to generate a selected number of realizations. For each realization, the different methods were applied to generate representative permeability fields. The PFLOTRAN (Hammond et al., 2014) code was used to simulate flow and transport in the domain. Simulation results and analysis are presented. The results indicate that the FCM approach is a viable method to model fractured crystalline rocks. The FCM is a computationally efficient way to generate realistic representation of complex fracture systems. This approach is of interest for nuclear waste disposal models applied over large domains. SAND2016-7509 A

Persistence of opinion in the Sznajd consensus model: computer simulation

NASA Astrophysics Data System (ADS)

Stauffer, D.; de Oliveira, P. M. C.

2002-12-01

The density of never changed opinions during the Sznajd consensus-finding process decays with time t as 1/t^θ. We find θ simeq 3/8 for a chain, compatible with the exact Ising result of Derrida et al. In higher dimensions, however, the exponent differs from the Ising θ. With simultaneous updating of sublattices instead of the usual random sequential updating, the number of persistent opinions decays roughly exponentially. Some of the simulations used multi-spin coding.

Class of cooperative stochastic models: Exact and approximate solutions, simulations, and experiments using ionic self-assembly of nanoparticles.

PubMed

Mazilu, I; Mazilu, D A; Melkerson, R E; Hall-Mejia, E; Beck, G J; Nshimyumukiza, S; da Fonseca, Carlos M

2016-03-01

We present exact and approximate results for a class of cooperative sequential adsorption models using matrix theory, mean-field theory, and computer simulations. We validate our models with two customized experiments using ionically self-assembled nanoparticles on glass slides. We also address the limitations of our models and their range of applicability. The exact results obtained using matrix theory can be applied to a variety of two-state systems with cooperative effects.

Precise algorithm to generate random sequential adsorption of hard polygons at saturation

NASA Astrophysics Data System (ADS)

Zhang, G.

2018-04-01

Random sequential adsorption (RSA) is a time-dependent packing process, in which particles of certain shapes are randomly and sequentially placed into an empty space without overlap. In the infinite-time limit, the density approaches a "saturation" limit. Although this limit has attracted particular research interest, the majority of past studies could only probe this limit by extrapolation. We have previously found an algorithm to reach this limit using finite computational time for spherical particles and could thus determine the saturation density of spheres with high accuracy. In this paper, we generalize this algorithm to generate saturated RSA packings of two-dimensional polygons. We also calculate the saturation density for regular polygons of three to ten sides and obtain results that are consistent with previous, extrapolation-based studies.

Precise algorithm to generate random sequential adsorption of hard polygons at saturation.

PubMed

Zhang, G

2018-04-01

Random sequential adsorption (RSA) is a time-dependent packing process, in which particles of certain shapes are randomly and sequentially placed into an empty space without overlap. In the infinite-time limit, the density approaches a "saturation" limit. Although this limit has attracted particular research interest, the majority of past studies could only probe this limit by extrapolation. We have previously found an algorithm to reach this limit using finite computational time for spherical particles and could thus determine the saturation density of spheres with high accuracy. In this paper, we generalize this algorithm to generate saturated RSA packings of two-dimensional polygons. We also calculate the saturation density for regular polygons of three to ten sides and obtain results that are consistent with previous, extrapolation-based studies.

Usability of virtual-reality simulation training in obstetric ultrasonography: a prospective cohort study.

PubMed

Burden, C; Preshaw, J; White, P; Draycott, T J; Grant, S; Fox, R

2013-08-01

To assess the usability of virtual-reality (VR) simulation for obstetric ultrasound trainees. Twenty-six participants were recruited: 18 obstetric ultrasound trainees (with little formal ultrasonography training) and eight certified experts. All performed five sequential VR-simulated crown-rump length (CRL) scans in a single session and three repetitions of biparietal diameter (BPD), occipitofrontal diameter (OFD) and femur length (FL) measurements. Outcome measures included mean percentage deviation from target for all measurements. Time taken to perform each type of scan was recorded. The mean percentage difference for the first scan was significantly greater for the trainee group than for the expert group for BPD (P = 0.035), OFD (P = 0.010) and FL (P = 0.008) and for time taken for the first CRL (P < 0.001) and fetal biometry (including BPD, OFD and FL measurements) scan (P < 0.001), demonstrating that trainees were initially significantly less accurate and less efficient. Over subsequent scans, the trainees became more accurate for all measurements with a significant improvement shown for OFD and FL (P < 0.05). The time taken for trainees to complete CRL and fetal biometry scans decreased significantly (all P < 0.05) with repetition, to near-expert efficiency. All participants were able to use the simulator and produce clinically meaningful biometry results. With repetition, beginners quickly approached near-expert levels of accuracy and speed. These data demonstrate that obstetricians with minimal experience can improve their ultrasonographic skills with short-phase VR-simulation training. The speed of improvement suggests that VR simulation might be useful as a warm-up exercise before clinical training sessions in order to reduce their impact on clinical service. Copyright © 2013 ISUOG. Published by John Wiley & Sons Ltd.

Dosimetric effects of patient rotational setup errors on prostate IMRT treatments

NASA Astrophysics Data System (ADS)

Fu, Weihua; Yang, Yong; Li, Xiang; Heron, Dwight E.; Saiful Huq, M.; Yue, Ning J.

2006-10-01

The purpose of this work is to determine dose delivery errors that could result from systematic rotational setup errors (ΔΦ) for prostate cancer patients treated with three-phase sequential boost IMRT. In order to implement this, different rotational setup errors around three Cartesian axes were simulated for five prostate patients and dosimetric indices, such as dose-volume histogram (DVH), tumour control probability (TCP), normal tissue complication probability (NTCP) and equivalent uniform dose (EUD), were employed to evaluate the corresponding dosimetric influences. Rotational setup errors were simulated by adjusting the gantry, collimator and horizontal couch angles of treatment beams and the dosimetric effects were evaluated by recomputing the dose distributions in the treatment planning system. Our results indicated that, for prostate cancer treatment with the three-phase sequential boost IMRT technique, the rotational setup errors do not have significant dosimetric impacts on the cumulative plan. Even in the worst-case scenario with ΔΦ = 3°, the prostate EUD varied within 1.5% and TCP decreased about 1%. For seminal vesicle, slightly larger influences were observed. However, EUD and TCP changes were still within 2%. The influence on sensitive structures, such as rectum and bladder, is also negligible. This study demonstrates that the rotational setup error degrades the dosimetric coverage of target volume in prostate cancer treatment to a certain degree. However, the degradation was not significant for the three-phase sequential boost prostate IMRT technique and for the margin sizes used in our institution.

Challenges in predicting climate change impacts on pome fruit phenology

NASA Astrophysics Data System (ADS)

Darbyshire, Rebecca; Webb, Leanne; Goodwin, Ian; Barlow, E. W. R.

2014-08-01

Climate projection data were applied to two commonly used pome fruit flowering models to investigate potential differences in predicted full bloom timing. The two methods, fixed thermal time and sequential chill-growth, produced different results for seven apple and pear varieties at two Australian locations. The fixed thermal time model predicted incremental advancement of full bloom, while results were mixed from the sequential chill-growth model. To further investigate how the sequential chill-growth model reacts under climate perturbed conditions, four simulations were created to represent a wider range of species physiological requirements. These were applied to five Australian locations covering varied climates. Lengthening of the chill period and contraction of the growth period was common to most results. The relative dominance of the chill or growth component tended to predict whether full bloom advanced, remained similar or was delayed with climate warming. The simplistic structure of the fixed thermal time model and the exclusion of winter chill conditions in this method indicate it is unlikely to be suitable for projection analyses. The sequential chill-growth model includes greater complexity; however, reservations in using this model for impact analyses remain. The results demonstrate that appropriate representation of physiological processes is essential to adequately predict changes to full bloom under climate perturbed conditions with greater model development needed.

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

PubMed

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

Study of Solid Particle Behavior in High Temperature Gas Flows

NASA Astrophysics Data System (ADS)

Majid, A.; Bauder, U.; Stindl, T.; Fertig, M.; Herdrich, G.; Röser, H.-P.

2009-01-01

The Euler-Lagrangian approach is used for the simulation of solid particles in hypersonic entry flows. For flow field simulation, the program SINA (Sequential Iterative Non-equilibrium Algorithm) developed at the Institut für Raumfahrtsysteme is used. The model for the effect of the carrier gas on a particle includes drag force and particle heating only. Other parameters like lift Magnus force or damping torque are not taken into account so far. The reverse effect of the particle phase on the gaseous phase is currently neglected. Parametric analysis is done regarding the impact of variation in the physical input conditions like position, velocity, size and material of the particle. Convective heat fluxes onto the surface of the particle and its radiative cooling are discussed. The variation of particle temperature under different conditions is presented. The influence of various input conditions on the trajectory is explained. A semi empirical model for the particle wall interaction is also discussed and the influence of the wall on the particle trajectory with different particle conditions is presented. The heat fluxes onto the wall due to impingement of particles are also computed and compared with the heat fluxes from the gas.

Ion implantation modified stainless steel as a substrate for hydroxyapatite deposition. Part II. Biomimetic layer growth and characterization.

PubMed

Pramatarova, L; Pecheva, E; Krastev, V

2007-03-01

The interest in stainless steel as a material widely used in medicine and dentistry has stimulated extensive studies on improving its bone-bonding properties. AISI 316 stainless steel is modified by a sequential ion implantation of Ca and P ions (the basic ions of hydroxyapatite), and by Ca and P implantation and subsequent thermal treatment in air (600( composite function)C, 1 h). This paper investigates the ability of the as-modified surfaces to induce hydroxyapatite deposition by using a biomimetic approach, i.e. immersion in a supersaturated aqueous solution resembling the human blood plasma (the so-called simulated body fluid). We describe our experimental procedure and results, and discuss the physico-chemical properties of the deposed hydroxyapatite on the modified stainless steel surfaces. It is shown that the implantation of a selected combination of ions followed by the applied methodology of the sample soaking in the simulated body fluid yield the growth of hydroxyapatite layers with composition and structure resembling those of the bone apatite. The grown layers are found suitable for studying the process of mineral formation in nature (biomineralization).

Towards autonomous neuroprosthetic control using Hebbian reinforcement learning.

PubMed

Mahmoudi, Babak; Pohlmeyer, Eric A; Prins, Noeline W; Geng, Shijia; Sanchez, Justin C

2013-12-01

Our goal was to design an adaptive neuroprosthetic controller that could learn the mapping from neural states to prosthetic actions and automatically adjust adaptation using only a binary evaluative feedback as a measure of desirability/undesirability of performance. Hebbian reinforcement learning (HRL) in a connectionist network was used for the design of the adaptive controller. The method combines the efficiency of supervised learning with the generality of reinforcement learning. The convergence properties of this approach were studied using both closed-loop control simulations and open-loop simulations that used primate neural data from robot-assisted reaching tasks. The HRL controller was able to perform classification and regression tasks using its episodic and sequential learning modes, respectively. In our experiments, the HRL controller quickly achieved convergence to an effective control policy, followed by robust performance. The controller also automatically stopped adapting the parameters after converging to a satisfactory control policy. Additionally, when the input neural vector was reorganized, the controller resumed adaptation to maintain performance. By estimating an evaluative feedback directly from the user, the HRL control algorithm may provide an efficient method for autonomous adaptation of neuroprosthetic systems. This method may enable the user to teach the controller the desired behavior using only a simple feedback signal.

Renewable Surface Fluorescence Sandwich Immunoassay Biosensor for Rapid Sensitive Botulinum Toxin Detection in an Automated Fluidic Format

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

Grate, Jay W.; Warner, Marvin G.; Ozanich, Richard M.

2009-03-05

A renewable surface biosensor for rapid detection of botulinum toxin is described based on fluidic automation of a fluorescence sandwich immunoassay, using a recombinant fragment of the toxin heavy chain as a structurally valid simulant. Monoclonal antibodies AR4 and RAZ1 bind to separate epitopes of both this fragment and the holotoxin. The AR4 antibody was covalently bound to Sepharose beads and used as the capture antibody. A rotating rod flow cell was used to capture these beads delivered as a suspension by the sequential injection flow system, creating a 3.6 microliter column. After perfusing the bead column with sample andmore » washing away the matrix, the column was perfused with Alexa 647 dye-labeled RAZ1 antibody as the reporter. Optical fibers coupled to the rotating rod flow cell at a 90 degree angle to one another delivered excitation light from a HeNe laser and collected fluorescent emission light for detection. After each measurement, the used sepharose beads are released and replaced with fresh beads. In a rapid screening approach to sample analysis, the toxin simulant was detected to concentrations of 10 pM in less than 20 minutes.« less

The Science ELF: Assessing the Enquiry Levels Framework as a Heuristic for Professional Development

ERIC Educational Resources Information Center

Wheeler, Lindsay B.; Bell, Randy L.; Whitworth, Brooke A.; Maeng, Jennifer L.

2015-01-01

This study utilized an explanatory sequential mixed methods approach to explore randomly assigned treatment and control participants' frequency of inquiry instruction in secondary science classrooms. Eleven treatment participants received professional development (PD) that emphasized a structured approach to inquiry instruction, while 10 control…

Systematic Approach to Food Safety Education on the Farm

ERIC Educational Resources Information Center

Shaw, Angela; Strohbehn, Catherine; Naeve, Linda; Domoto, Paul; Wilson, Lester

2015-01-01

Food safety education from farm to end user is essential in the mitigation of food safety concerns associated with fresh produce. Iowa State University developed a multi-disciplinary three-level sequential program ("Know," "Show," "Go") to provide a holistic approach to food safety education. This program provides…

The Rhetorical Cycle: Reading, Thinking, Speaking, Listening, Discussing, Writing.

ERIC Educational Resources Information Center

Keller, Rodney D.

The rhetorical cycle is a step-by-step approach that provides classroom experience before students actually write, thereby making the writing process less frustrating for them. This approach consists of six sequential steps: reading, thinking, speaking, listening, discussing, and finally writing. Readings serve not only as models of rhetorical…

Mutual Information Item Selection in Adaptive Classification Testing

ERIC Educational Resources Information Center

Weissman, Alexander

2007-01-01

A general approach for item selection in adaptive multiple-category classification tests is provided. The approach uses mutual information (MI), a special case of the Kullback-Leibler distance, or relative entropy. MI works efficiently with the sequential probability ratio test and alleviates the difficulties encountered with using other local-…

Exact Tests for the Rasch Model via Sequential Importance Sampling

ERIC Educational Resources Information Center

Chen, Yuguo; Small, Dylan

2005-01-01

Rasch proposed an exact conditional inference approach to testing his model but never implemented it because it involves the calculation of a complicated probability. This paper furthers Rasch's approach by (1) providing an efficient Monte Carlo methodology for accurately approximating the required probability and (2) illustrating the usefulness…

Sequential Gaussian co-simulation of rate decline parameters of longwall gob gas ventholes.

PubMed

Karacan, C Özgen; Olea, Ricardo A

2013-04-01

Gob gas ventholes (GGVs) are used to control methane inflows into a longwall mining operation by capturing the gas within the overlying fractured strata before it enters the work environment. Using geostatistical co-simulation techniques, this paper maps the parameters of their rate decline behaviors across the study area, a longwall mine in the Northern Appalachian basin. Geostatistical gas-in-place (GIP) simulations were performed, using data from 64 exploration boreholes, and GIP data were mapped within the fractured zone of the study area. In addition, methane flowrates monitored from 10 GGVs were analyzed using decline curve analyses (DCA) techniques to determine parameters of decline rates. Surface elevation showed the most influence on methane production from GGVs and thus was used to investigate its relation with DCA parameters using correlation techniques on normal-scored data. Geostatistical analysis was pursued using sequential Gaussian co-simulation with surface elevation as the secondary variable and with DCA parameters as the primary variables. The primary DCA variables were effective percentage decline rate, rate at production start, rate at the beginning of forecast period, and production end duration. Co-simulation results were presented to visualize decline parameters at an area-wide scale. Wells located at lower elevations, i.e., at the bottom of valleys, tend to perform better in terms of their rate declines compared to those at higher elevations. These results were used to calculate drainage radii of GGVs using GIP realizations. The calculated drainage radii are close to ones predicted by pressure transient tests.

Dietary fibers from mushroom Sclerotia: 2. In vitro mineral binding capacity under sequential simulated physiological conditions of the human gastrointestinal tract.

PubMed

Wong, Ka-Hing; Cheung, Peter C K

2005-11-30

The in vitro mineral binding capacity of three novel dietary fibers (DFs) prepared from mushroom sclerotia, namely, Pleurotus tuber-regium, Polyporous rhinocerus, and Wolfiporia cocos, to Ca, Mg, Cu, Fe, and Zn under sequential simulated physiological conditions of the human stomach, small intestine, and colon was investigated and compared. Apart from releasing most of their endogenous Ca (ranged from 96.9 to 97.9% removal) and Mg (ranged from 95.9 to 96.7% removal), simulated physiological conditions of the stomach also attenuated the possible adverse binding effect of the three sclerotial DFs to the exogenous minerals by lowering their cation-exchange capacity (ranged from 20.8 to 32.3%) and removing a substantial amount of their potential mineral chelators including protein (ranged from 16.2 to 37.8%) and phytate (ranged from 58.5 to 64.2%). The in vitro mineral binding capacity of the three sclerotial DF under simulated physiological conditions of small intestine was found to be low, especially for Ca (ranged from 4.79 to 5.91% binding) and Mg (ranged from 3.16 to 4.18% binding), and was highly correlated (r > 0.97) with their residual protein contents. Under simulated physiological conditions of the colon with slightly acidic pH (5.80), only bound Ca was readily released (ranged from 34.2 to 72.3% releasing) from the three sclerotial DFs, and their potential enhancing effect on passive Ca absorption in the human large intestine was also discussed.

Design of the biosonar simulator for dolphin's clicks waveform reproduction

NASA Astrophysics Data System (ADS)

Ishii, Ken; Akamatsu, Tomonari; Hatakeyama, Yoshimi

1992-03-01

The emitted clicks of Dall's porpoises consist of a pulse train of burst signals with an ultrasonic carrier frequency. The authors have designed a biosonar simulator to reproduce the waveforms associated with a dolphin's clicks underwater. The total reproduction system consists of a click signal acquisition block, a waveform analysis block, a memory unit, a click simulator, and a underwater, ultrasonic wave transmitter. In operation, data stored in an EPROM (Erasable Programmable Read Only Memory) are read out sequentially by a fast clock and converted to analog output signals. Then an ultrasonic power amplifier reproduces these signals through a transmitter. The click signal replaying block is referred to as the BSS (Biosonar Simulator). This is what simulates the clicks. The details of the BSS are described in this report. A unit waveform is defined. The waveform is divided into a burst period and a waiting period. Clicks are a sequence based on a unit waveform, and digital data are sequentially read out from an EPROM of waveform data. The basic parameters of the BSS are as follows: (1) reading clock, 100 ns to 25.4 microseconds; (2) number of reading clock, 34 to 1024 times; (3) counter clock in a waiting period, 100 ns to 25.4 microseconds; (4) number of counter clock, zero to 16,777,215 times; (5) number of burst/waiting repetition cycle, one to 128 times; and (6) transmission level adjustment by a programmable attenuator, zero to 86.5 dB. These basic functions enable the BSS to replay clicks of Dall's porpoise precisely.

Sequential Gaussian co-simulation of rate decline parameters of longwall gob gas ventholes

USGS Publications Warehouse

Karacan, C. Özgen; Olea, Ricardo A.

2013-01-01

Gob gas ventholes (GGVs) are used to control methane inflows into a longwall mining operation by capturing the gas within the overlying fractured strata before it enters the work environment. Using geostatistical co-simulation techniques, this paper maps the parameters of their rate decline behaviors across the study area, a longwall mine in the Northern Appalachian basin. Geostatistical gas-in-place (GIP) simulations were performed, using data from 64 exploration boreholes, and GIP data were mapped within the fractured zone of the study area. In addition, methane flowrates monitored from 10 GGVs were analyzed using decline curve analyses (DCA) techniques to determine parameters of decline rates. Surface elevation showed the most influence on methane production from GGVs and thus was used to investigate its relation with DCA parameters using correlation techniques on normal-scored data. Geostatistical analysis was pursued using sequential Gaussian co-simulation with surface elevation as the secondary variable and with DCA parameters as the primary variables. The primary DCA variables were effective percentage decline rate, rate at production start, rate at the beginning of forecast period, and production end duration. Co-simulation results were presented to visualize decline parameters at an area-wide scale. Wells located at lower elevations, i.e., at the bottom of valleys, tend to perform better in terms of their rate declines compared to those at higher elevations. These results were used to calculate drainage radii of GGVs using GIP realizations. The calculated drainage radii are close to ones predicted by pressure transient tests.

Sequential Gaussian co-simulation of rate decline parameters of longwall gob gas ventholes

PubMed Central

Karacan, C.Özgen; Olea, Ricardo A.

2015-01-01

Gob gas ventholes (GGVs) are used to control methane inflows into a longwall mining operation by capturing the gas within the overlying fractured strata before it enters the work environment. Using geostatistical co-simulation techniques, this paper maps the parameters of their rate decline behaviors across the study area, a longwall mine in the Northern Appalachian basin. Geostatistical gas-in-place (GIP) simulations were performed, using data from 64 exploration boreholes, and GIP data were mapped within the fractured zone of the study area. In addition, methane flowrates monitored from 10 GGVs were analyzed using decline curve analyses (DCA) techniques to determine parameters of decline rates. Surface elevation showed the most influence on methane production from GGVs and thus was used to investigate its relation with DCA parameters using correlation techniques on normal-scored data. Geostatistical analysis was pursued using sequential Gaussian co-simulation with surface elevation as the secondary variable and with DCA parameters as the primary variables. The primary DCA variables were effective percentage decline rate, rate at production start, rate at the beginning of forecast period, and production end duration. Co-simulation results were presented to visualize decline parameters at an area-wide scale. Wells located at lower elevations, i.e., at the bottom of valleys, tend to perform better in terms of their rate declines compared to those at higher elevations. These results were used to calculate drainage radii of GGVs using GIP realizations. The calculated drainage radii are close to ones predicted by pressure transient tests. PMID:26190930

Sequential Bayesian Geostatistical Inversion and Evaluation of Combined Data Worth for Aquifer Characterization at the Hanford 300 Area

NASA Astrophysics Data System (ADS)

Murakami, H.; Chen, X.; Hahn, M. S.; Over, M. W.; Rockhold, M. L.; Vermeul, V.; Hammond, G. E.; Zachara, J. M.; Rubin, Y.

2010-12-01

Subsurface characterization for predicting groundwater flow and contaminant transport requires us to integrate large and diverse datasets in a consistent manner, and quantify the associated uncertainty. In this study, we sequentially assimilated multiple types of datasets for characterizing a three-dimensional heterogeneous hydraulic conductivity field at the Hanford 300 Area. The datasets included constant-rate injection tests, electromagnetic borehole flowmeter tests, lithology profile and tracer tests. We used the method of anchored distributions (MAD), which is a modular-structured Bayesian geostatistical inversion method. MAD has two major advantages over the other inversion methods. First, it can directly infer a joint distribution of parameters, which can be used as an input in stochastic simulations for prediction. In MAD, in addition to typical geostatistical structural parameters, the parameter vector includes multiple point values of the heterogeneous field, called anchors, which capture local trends and reduce uncertainty in the prediction. Second, MAD allows us to integrate the datasets sequentially in a Bayesian framework such that it updates the posterior distribution, as a new dataset is included. The sequential assimilation can decrease computational burden significantly. We applied MAD to assimilate different combinations of the datasets, and then compared the inversion results. For the injection and tracer test assimilation, we calculated temporal moments of pressure build-up and breakthrough curves, respectively, to reduce the data dimension. A massive parallel flow and transport code PFLOTRAN is used for simulating the tracer test. For comparison, we used different metrics based on the breakthrough curves not used in the inversion, such as mean arrival time, peak concentration and early arrival time. This comparison intends to yield the combined data worth, i.e. which combination of the datasets is the most effective for a certain metric, which will be useful for guiding the further characterization effort at the site and also the future characterization projects at the other sites.

A simulation to study the feasibility of improving the temporal resolution of LAGEOS geodynamic solutions by using a sequential process noise filter

NASA Technical Reports Server (NTRS)

Hartman, Brian Davis

1995-01-01

A key drawback to estimating geodetic and geodynamic parameters over time based on satellite laser ranging (SLR) observations is the inability to accurately model all the forces acting on the satellite. Errors associated with the observations and the measurement model can detract from the estimates as well. These 'model errors' corrupt the solutions obtained from the satellite orbit determination process. Dynamical models for satellite motion utilize known geophysical parameters to mathematically detail the forces acting on the satellite. However, these parameters, while estimated as constants, vary over time. These temporal variations must be accounted for in some fashion to maintain meaningful solutions. The primary goal of this study is to analyze the feasibility of using a sequential process noise filter for estimating geodynamic parameters over time from the Laser Geodynamics Satellite (LAGEOS) SLR data. This evaluation is achieved by first simulating a sequence of realistic LAGEOS laser ranging observations. These observations are generated using models with known temporal variations in several geodynamic parameters (along track drag and the J(sub 2), J(sub 3), J(sub 4), and J(sub 5) geopotential coefficients). A standard (non-stochastic) filter and a stochastic process noise filter are then utilized to estimate the model parameters from the simulated observations. The standard non-stochastic filter estimates these parameters as constants over consecutive fixed time intervals. Thus, the resulting solutions contain constant estimates of parameters that vary in time which limits the temporal resolution and accuracy of the solution. The stochastic process noise filter estimates these parameters as correlated process noise variables. As a result, the stochastic process noise filter has the potential to estimate the temporal variations more accurately since the constraint of estimating the parameters as constants is eliminated. A comparison of the temporal resolution of solutions obtained from standard sequential filtering methods and process noise sequential filtering methods shows that the accuracy is significantly improved using process noise. The results show that the positional accuracy of the orbit is improved as well. The temporal resolution of the resulting solutions are detailed, and conclusions drawn about the results. Benefits and drawbacks of using process noise filtering in this type of scenario are also identified.

Monte Carlo simulation of evaporation-driven self-assembly in suspensions of colloidal rods

NASA Astrophysics Data System (ADS)

Lebovka, Nikolai I.; Vygornitskii, Nikolai V.; Gigiberiya, Volodymyr A.; Tarasevich, Yuri Yu.

2016-12-01

The vertical drying of a colloidal film containing rodlike particles was studied by means of kinetic Monte Carlo (MC) simulation. The problem was approached using a two-dimensional square lattice, and the rods were represented as linear k -mers (i.e., particles occupying k adjacent sites). The initial state before drying was produced using a model of random sequential adsorption (RSA) with isotropic orientations of the k -mers (orientation of the k -mers along horizontal x and vertical y directions are equiprobable). In the RSA model, overlapping of the k -mers is forbidden. During the evaporation, an upper interface falls with a linear velocity of u in the vertical direction and the k -mers undergo translation Brownian motion. The MC simulations were run at different initial concentrations, pi, (pi∈[0 ,pj] , where pj is the jamming concentration), lengths of k -mers (k ∈[1 ,12 ] ), and solvent evaporation rates, u . For completely dried films, the spatial distributions of k -mers and their electrical conductivities in both x and y directions were examined. Significant evaporation-driven self-assembly and orientation stratification of the k -mers oriented along the x and y directions were observed. The extent of stratification increased with increasing value of k . The anisotropy of the electrical conductivity of the film can be finely regulated by changes in the values of pi, k , and u .

A remediation performance model for enhanced metabolic reductive dechlorination of chloroethenes in fractured clay till

NASA Astrophysics Data System (ADS)

Manoli, Gabriele; Chambon, Julie C.; Bjerg, Poul L.; Scheutz, Charlotte; Binning, Philip J.; Broholm, Mette M.

2012-04-01

A numerical model of metabolic reductive dechlorination is used to describe the performance of enhanced bioremediation in fractured clay till. The model is developed to simulate field observations of a full scale bioremediation scheme in a fractured clay till and thereby to assess remediation efficiency and timeframe. A relatively simple approach is used to link the fermentation of the electron donor soybean oil to the sequential dechlorination of trichloroethene (TCE) while considering redox conditions and the heterogeneous clay till system (clay till matrix, fractures and sand stringers). The model is tested on lab batch experiments and applied to describe sediment core samples from a TCE-contaminated site. Model simulations compare favorably to field observations and demonstrate that dechlorination may be limited to narrow bioactive zones in the clay matrix around fractures and sand stringers. Field scale simulations show that the injected donor is expected to be depleted after 5 years, and that without donor re-injection contaminant rebound will occur in the high permeability zones and the mass removal will stall at 18%. Long remediation timeframes, if dechlorination is limited to narrow bioactive zones, and the need for additional donor injections to maintain dechlorination activity may limit the efficiency of ERD in low-permeability media. Future work should address the dynamics of the bioactive zones, which is essential to understand for predictions of long term mass removal.

User's Guide of TOUGH2-EGS. A Coupled Geomechanical and Reactive Geochemical Simulator for Fluid and Heat Flow in Enhanced Geothermal Systems Version 1.0

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

Fakcharoenphol, Perapon; Xiong, Yi; Hu, Litang

TOUGH2-EGS is a numerical simulation program coupling geomechanics and chemical reactions for fluid and heat flows in porous media and fractured reservoirs of enhanced geothermal systems. The simulator includes the fully-coupled geomechanical (THM) module, the fully-coupled geochemical (THC) module, and the sequentially coupled reactive geochemistry (THMC) module. The fully-coupled flow-geomechanics model is developed from the linear elastic theory for the thermo-poro-elastic system and is formulated with the mean normal stress as well as pore pressure and temperature. The chemical reaction is sequentially coupled after solution of flow equations, which provides the flow velocity and phase saturation for the solute transportmore » calculation at each time step. In addition, reservoir rock properties, such as porosity and permeability, are subjected to change due to rock deformation and chemical reactions. The relationships between rock properties and geomechanical and chemical effects from poro-elasticity theories and empirical correlations are incorporated into the simulator. This report provides the user with detailed information on both mathematical models and instructions for using TOUGH2-EGS for THM, THC or THMC simulations. The mathematical models include the fluid and heat flow equations, geomechanical equation, reactive geochemistry equations, and discretization methods. Although TOUGH2-EGS has the capability for simulating fluid and heat flows coupled with both geomechanical and chemical effects, it is up to the users to select the specific coupling process, such as THM, THC, or THMC in a simulation. There are several example problems illustrating the applications of this program. These example problems are described in details and their input data are presented. The results demonstrate that this program can be used for field-scale geothermal reservoir simulation with fluid and heat flow, geomechanical effect, and chemical reaction in porous and fractured media.« less

Spatiotemporal stochastic models for earth science and engineering applications

NASA Astrophysics Data System (ADS)

Luo, Xiaochun

1998-12-01

Spatiotemporal processes occur in many areas of earth sciences and engineering. However, most of the available theoretical tools and techniques of space-time daft processing have been designed to operate exclusively in time or in space, and the importance of spatiotemporal variability was not fully appreciated until recently. To address this problem, a systematic framework of spatiotemporal random field (S/TRF) models for geoscience/engineering applications is presented and developed in this thesis. The space-tune continuity characterization is one of the most important aspects in S/TRF modelling, where the space-time continuity is displayed with experimental spatiotemporal variograms, summarized in terms of space-time continuity hypotheses, and modelled using spatiotemporal variogram functions. Permissible spatiotemporal covariance/variogram models are addressed through permissibility criteria appropriate to spatiotemporal processes. The estimation of spatiotemporal processes is developed in terms of spatiotemporal kriging techniques. Particular emphasis is given to the singularity analysis of spatiotemporal kriging systems. The impacts of covariance, functions, trend forms, and data configurations on the singularity of spatiotemporal kriging systems are discussed. In addition, the tensorial invariance of universal spatiotemporal kriging systems is investigated in terms of the space-time trend. The conditional simulation of spatiotemporal processes is proposed with the development of the sequential group Gaussian simulation techniques (SGGS), which is actually a series of sequential simulation algorithms associated with different group sizes. The simulation error is analyzed with different covariance models and simulation grids. The simulated annealing technique honoring experimental variograms, is also proposed, providing a way of conditional simulation without the covariance model fitting which is prerequisite for most simulation algorithms. The proposed techniques were first applied for modelling of the pressure system in a carbonate reservoir, and then applied for modelling of springwater contents in the Dyle watershed. The results of these case studies as well as the theory suggest that these techniques are realistic and feasible.

Controlling the type I error rate in two-stage sequential adaptive designs when testing for average bioequivalence.

PubMed

Maurer, Willi; Jones, Byron; Chen, Ying

2018-05-10

In a 2×2 crossover trial for establishing average bioequivalence (ABE) of a generic agent and a currently marketed drug, the recommended approach to hypothesis testing is the two one-sided test (TOST) procedure, which depends, among other things, on the estimated within-subject variability. The power of this procedure, and therefore the sample size required to achieve a minimum power, depends on having a good estimate of this variability. When there is uncertainty, it is advisable to plan the design in two stages, with an interim sample size reestimation after the first stage, using an interim estimate of the within-subject variability. One method and 3 variations of doing this were proposed by Potvin et al. Using simulation, the operating characteristics, including the empirical type I error rate, of the 4 variations (called Methods A, B, C, and D) were assessed by Potvin et al and Methods B and C were recommended. However, none of these 4 variations formally controls the type I error rate of falsely claiming ABE, even though the amount of inflation produced by Method C was considered acceptable. A major disadvantage of assessing type I error rate inflation using simulation is that unless all possible scenarios for the intended design and analysis are investigated, it is impossible to be sure that the type I error rate is controlled. Here, we propose an alternative, principled method of sample size reestimation that is guaranteed to control the type I error rate at any given significance level. This method uses a new version of the inverse-normal combination of p-values test, in conjunction with standard group sequential techniques, that is more robust to large deviations in initial assumptions regarding the variability of the pharmacokinetic endpoints. The sample size reestimation step is based on significance levels and power requirements that are conditional on the first-stage results. This necessitates a discussion and exploitation of the peculiar properties of the power curve of the TOST testing procedure. We illustrate our approach with an example based on a real ABE study and compare the operating characteristics of our proposed method with those of Method B of Povin et al. Copyright © 2018 John Wiley & Sons, Ltd.

The Structural Basis of IKs Ion-Channel Activation: Mechanistic Insights from Molecular Simulations.

PubMed

Ramasubramanian, Smiruthi; Rudy, Yoram

2018-06-05

Relating ion channel (iCh) structural dynamics to physiological function remains a challenge. Current experimental and computational techniques have limited ability to explore this relationship in atomistic detail over physiological timescales. A framework associating iCh structure to function is necessary for elucidating normal and disease mechanisms. We formulated a modeling schema that overcomes the limitations of current methods through applications of artificial intelligence machine learning. Using this approach, we studied molecular processes that underlie human IKs voltage-mediated gating. IKs malfunction underlies many debilitating and life-threatening diseases. Molecular components of IKs that underlie its electrophysiological function include KCNQ1 (a pore-forming tetramer) and KCNE1 (an auxiliary subunit). Simulations, using the IKs structure-function model, reproduced experimentally recorded saturation of gating-charge displacement at positive membrane voltages, two-step voltage sensor (VS) movement shown by fluorescence, iCh gating statistics, and current-voltage relationship. Mechanistic insights include the following: 1) pore energy profile determines iCh subconductance; 2) the entire protein structure, not limited to the pore, contributes to pore energy and channel subconductance; 3) interactions with KCNE1 result in two distinct VS movements, causing gating-charge saturation at positive membrane voltages and current activation delay; and 4) flexible coupling between VS and pore permits pore opening at lower VS positions, resulting in sequential gating. The new modeling approach is applicable to atomistic scale studies of other proteins on timescales of physiological function. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.