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At least 739 records · Page 41Linked to original sources
PubMed2001

A stochastic model describes the heterogeneous pharmacokinetics of cyclosporin.

The pharmacokinetics of cyclosporin (CsA) are unusual because of several heterogeneous features which include the presence of more than one conformer, considerable accumulation in erythrocytes and lipoproteins, extensive plasma protein binding, distribution into deep tissues, biliary secretion and hepatic clearance involving a large number of metabolites. In this study, a stochastic compartmental model was developed to describe the heterogeneous elimination kinetics of CsA. This new approach relies on a probabilistic transfer model with a gamma distributed probability intensity coefficient for drug elimination. For comparative purposes both the stochastic model and compartmental deterministic models were fitted to real post infusion data from patients receiving CsA as a 2-hr intravenous infusion. The criteria for selecting the best model showed that the stochastic model, although simpler than the compartmental deterministic models, is more flexible and gives a better fit to the kinetic data of CsA than the compartmental deterministic models. The stochastic model with a random rate intensity coefficient adequately describes the heterogeneous pharmacokinetics of CsA.

Cyclosporine↗
PubMed2003

Broadband matched-field processing: coherent and incoherent approaches.

Matched-field based methods always involve the comparison of the output of a physical model and the actual data. The method of comparison and the nature of the data varies according to the problem at hand, but the result becomes always largely conditioned by the accurateness of the physical model and the amount of data available. The usage of broadband methods has become a widely used approach to increase the amount of data and to stabilize the estimation process. Due to the difficulties to accurately predict the phase of the acoustic field the problem whether the information should be coherently or incoherently combined across frequency has been an open debate in the last years. This paper provides a data consistent model for the observed signal, formed by a deterministic channel structure multiplied by a perturbation random factor plus noise. The cross-frequency channel structure and the decorrelation of the perturbation random factor are shown to be the main causes of processor performance degradation. Different Bartlett processors, such as the incoherent processor [Baggeroer et al., J. Acoust. Soc. Am. 80, 571-587 (1988)], the coherent normalized processor [Z.-H. Michalopoulou, IEEE J. Ocean Eng. 21, 384-392 (1996)] and the matched-phase processor [Orris et al., J. Acoust. Soc. Am. 107, 2563-2375 (2000)], are reviewed and compared to the proposed cross-frequency incoherent processor. It is analytically shown that the proposed processor has the same performance as the matched-phase processor at the maximum of the ambiguity surface, without the need for estimating the phase terms and thus having an extremely low computational cost.

Journal Article↗
PubMed2007

Error analysis in inverse scatterometry. I. Modeling.

Scatterometry is an optical technique that has been studied and tested in recent years in semiconductor fabrication metrology for critical dimensions. Previous work presented an iterative linearized method to retrieve surface-relief profile parameters from reflectance measurements upon diffraction. With the iterative linear solution model in this work, rigorous models are developed to represent the random and deterministic or offset errors in scatterometric measurements. The propagation of different types of error from the measurement data to the profile parameter estimates is then presented. The improvement in solution accuracies is then demonstrated with theoretical and experimental data by adjusting for the offset errors. In a companion paper (in process) an improved optimization method is presented to account for unknown offset errors in the measurements based on the offset error model.

Journal Article↗
PubMed1987

Photon noise and constant-volume operators.

In an earlier paper [J. Opt. Soc. Am. A 2, 1769 (1985)] a class of nonlinear image processing operators was introduced in which each photoreceptor creates a nonnegative point-spread function whose center height is proportional to its quantum catch and whose volume is constant, so that the local spatial-summation area varies inversely with the local quantum catch. These constant-volume (CV) operators are designed to maximize spatial resolution in the presence of photon noise. In the previous paper it was shown that when CV operators are applied to deterministic images, they produce a surprising range of effects that are reminiscent of human vision, including Mach bands and Weber's-law behavior. In this paper the consequences of applying CV operators to images containing Poisson noise are analyzed. It is shown that a fixed-parameter CV operator can duplicate the global qualitative properties of spatial vision for retinal illuminances ranging from absolute threshold to 1000 Td. Although there are fundamental obstacles to modeling the exact quantitative properties of human spatial vision by CV operators, these operators seem likely to be useful in machine vision.

Humans↗
PubMed2001

Ultradian rhythms and the lux-gene reporter system.

'Noisy' bioluminescence of an unstirred and exposed-to-air microculture of lux -gene fused Escherichia coli was interpreted, assuming two oscillatory processes: cyclic induction of the lac promoter, resulting in oscillatory reporter lux -gene expression, and oscillatory respiration in the culture. Biological support for the theoretical argument, that two rhythms can interact in cells to produce additional rhythms, is provided. These results, along with previously obtained data on oscillatory bioluminescence, indicate the deterministic nature of observed noise-like fluctuations and promising perspectives of lux gene reporter systems in investigations of ultradian rhythm.

Bacteria↗
PubMed1995

Prediction of protein three-dimensional structures in insertion and deletion regions: a procedure for searching data bases of representative protein fragments using geometric scoring criteria.

The prediction of protein structure in insertion/deletion regions (referred to as indels) is an important part of protein model building by homology. Here we combine cluster analysis with data base search procedures. Initially, data bases of representative protein fragments are constructed using two different clustering algorithms. In the HCAPD (hierarchical clustering after preliminary division) approach, all protein fragments are divided into classes with similar anchor region structures (a protein fragment consists of two anchoring regions and a central region). Within these classes the fragments are further clustered using a hierarchical cluster algorithm. The DCANN (deterministic clustering by assignment of all nearest neighbours) approach is a variant of the k-nearest neighbours cluster algorithm. Only geometric scoring criteria are used for data base searching. The main advantage of a non-redundant data base is the ability to provide structurally different fragments during the search process, which leads to an improvement in structure prediction. Both methods have been tested on 71 insertions and 74 deletions with lengths between one and eight residues.

Algorithms↗
PubMed2004

Prediction of the reproductive status of cattle on the basis of milk progesterone measures: model description.

Reproductive management, in particular timely oestrus detection, is important for profitable dairy production. The aim of this study was to develop a biological model to predict reproductive state on the basis of milk progesterone measures. A number of additional inputs were incorporated to make use of other known effectors of reproductive performance that are not reflected in progesterone levels. These are: days from calving, breed, parity, signs of behavioural oestrus, insemination dates, pregnancy determinations, energy status, body fat status, milk urea content and reproductive disorders associated with calving. A dynamic, deterministic model was developed. It is designed to run each time a new trigger input (progesterone, behavioural oestrus, inseminations, pregnancy determinations) occurs using the current and previous values and can run in the absence of the additional inputs. The milk progesterone values are smoothed using an extended Kalman filter before being processed in the biological component of the model. The model predicts the reproductive status of the cow, which can be one of three mutually exclusive states: postpartum anoestrus, oestrus cycling, and potentially pregnant. The other model outputs are all reproductive status specific with the exception of days to next sample (DNS), which is calculated in each model run regardless of reproductive status. DNS is designed to feedback to the sampling system so that the frequency of milk sampling (i.e. progesterone measurement) can be varied according to the predicted likelihood of a future reproductive event, such as onset of oestrus cycling. The other model outputs are: risk of prolonged postpartum anoestrus, risk and type of ovarian cyst, onset of oestrus, likelihood of a potential insemination succeeding, and likelihood of being pregnant (following oestrus). The model was evaluated using three simulated datasets consisting of a timeseries of progesterone values centred on each of the three reproductive statuses and including relevant additional information. Test runs were carried out on the full datasets and then on reduced data. The data reductions were made by using only those values that would have been available if the model days to next sample function was used to control sampling frequency. The sensitivity of the model to noise in the raw progesterone data was examined by adding 1, 2, or 3 residual standard deviations (1.85 ng/ml) random variation to the original data and evaluating model performance. The model was found to be able to readily identify and distinguish reproductive states. A reduction in sampling frequency to 36% of original sample resulted in an average increase in days to detection of oestrus of 0.36. The addition of 1 S.D. noise did not cause additional oestruses to be detected and all oestruses were correctly identified. However, when 2 or 3 S.D. noise were added, the model found on average 1.4 and 3 extra oestruses. It was concluded that reproductive status can be predicted from milk progesterone values using a biological model and that such a model is robust to reductions in sampling frequency number and to a doubling in the random variation in the raw progesterone values. It therefore has the potential to provide the basis for a useful reproductive management tool.

Anestrus↗
PubMed1989

Varieties of stochastic model: a comparative study of the Gompertz effect.

A comparative study is made of various models for the Gompertz phenomenon, which is a form of growth rate limitation in population dynamics. Deterministic, Markov birth-death, diffusion and stochastic differential equation models are studied, with a view to assessing their advantages and limitations.

Models, Biological↗
PubMed1999

Variable effort fishing models in random environments.

We study the growth of populations in a random environment subjected to variable effort fishing policies. The models used are stochastic differential equations and the environmental fluctuations may either affect an intrinsic growth parameter or be of the additive noise type. Density-dependent natural growth and fishing policies are of very general form so that our results will be model independent. We obtain conditions on the fishing policies for non-extinction and for non-fixation at the carrying capacity that are very similar to the conditions obtained for the corresponding deterministic model. We also obtain conditions for the existence of stationary distributions (as well as expressions for such distributions) very similar to conditions for the existence of an equilibrium in the corresponding deterministic model. The results obtained provide minimal requirements for the choice of a wise density-dependent fishing policy.

Animals↗
PubMed1986

Forms control and error detection procedures used at the Coordinating Center of the Multiple Risk Factor Intervention Trial (MRFIT).

Although methods used for data collection and quality assurance for large-scale clinical trials are important to critical reading of trial results and have been published, such reporting is the exception rather than the rule. In the MRFIT, systematic methods for processing large volumes of data over a long period of time were developed. The methods were designed to detect and control a variety of errors and to leave a complete audit trial of the processing of forms and corrections to forms. Many of these methods evolved and were refined during the course of the study as a result of trial and error. If one were to start over, the methods described herein would be modified. The field of data processing is evolving, and it is important for statistical and data processing staff of coordinating centers to recognize this and continually evaluate and update their methods. For example, the simultaneous entry and computer editing of forms is becoming more feasible with time. Also, more sophisticated intelligent data entry equipment is available for central use. Near the end of MRFIT, some data received at the Coordinating Center were entered and edited on a minicomputer. The parameter-driven edits described previously were performed at the time of data entry. Additional modifications to the content of the data dictionary for future studies are also being considered. The incorporation into the data dictionary of consistency checks (both deterministic and probabilistic) between fields on different forms would facilitate the specification of complex edit checks and would provide better documentation of the edit checks actually performed. Incorporating definitions of the numeric codes for each field would improve the documentation and facilitate reporting using statistical packages. Dedicated computer hardware should also be a major consideration of coordinating centers in future clinical trials. For MRFIT, a dedicated system was used from 1978 to the end of the trial. With the continued decline in hardware costs, dedicated systems can and should be considered, even for trials much smaller than MRFIT. We believe the system developed for processing data in the MRFIT has several advantages. It satisfies the requirements identified by Karrison or a system of data editing and control, it is largely self-documenting as a result of the data dictionary approach taken, and it is easily adaptable to other clinical studies.

Clinical Trials as Topic↗
PubMed2004

A multi-algorithm, multi-timescale method for cell simulation.

MOTIVATION: Many important problems in cell biology require the dense nonlinear interactions between functional modules to be considered. The importance of computer simulation in understanding cellular processes is now widely accepted, and a variety of simulation algorithms useful for studying certain subsystems have been designed. Many of these are already widely used, and a large number of models constructed on these existing formalisms are available. A significant computational challenge is how we can integrate such sub-cellular models running on different types of algorithms to construct higher order models. RESULTS: A modular, object-oriented simulation meta-algorithm based on a discrete-event scheduler and Hermite polynomial interpolation has been developed and implemented. It is shown that this new method can efficiently handle many components driven by different algorithms and different timescales. The utility of this simulation framework is demonstrated further with a 'composite' heat-shock response model that combines the Gillespie-Gibson stochastic algorithm and deterministic differential equations. Dramatic improvements in performance were obtained without significant accuracy drawbacks. A multi-timescale demonstration of coupled harmonic oscillators is also shown.

Algorithms↗
PubMed1984

Growth with regulation in fluctuating environments. II. Intrinsic lower bounds to population size.

Population growth is modelled by means of diffusion processes originating from fluctuation equations of a new type. These equations are obtained in the customary way by inserting random fluctuations into first order non linear differential equations. However, differently from the cases so far considered in the literature, equations possessing two non trivial fixed points are taken into account. The underlying deterministic models depict the regulated growth of a population whose size cannot decrease below some preassigned lower threshold naturally acting as an absorbing boundary. A fairly comprehensive mathematical description of these models is provided.

Humans↗
PubMed2003

Emergence of pulled fronts in fermionic microscopic particle models.

We study the emergence and dynamics of pulled fronts described by the Fisher-Kolmogorov-Petrovsky-Piscounov (FKPP) equation in the microscopic reaction-diffusion process A+A<-->A on the lattice when only a particle is allowed per site. To this end we identify the parameter that controls the strength of internal fluctuations in this model, namely, the number of particles per correlated volume. When internal fluctuations are suppressed, we explictly see the matching between the deterministic FKPP description and the microscopic particle model.

Journal Article↗
PubMed2004

Comparison of two exploratory data analysis methods for fMRI: unsupervised clustering versus independent component analysis.

Exploratory data-driven methods such as unsupervised clustering and independent component analysis (ICA) are considered to be hypothesis-generating procedures, and are complementary to the hypothesis-led statistical inferential methods in functional magnetic resonance imaging (fMRI). In this paper, we present a comparison between unsupervised clustering and ICA in a systematic fMRI study. The comparative results were evaluated by 1) task-related activation maps, 2) associated time-courses, and 3) receiver operating characteristic analysis. For the fMRI data, a comparative quantitative evaluation between the three clustering techniques, self-organizing map, "neural gas" network, and fuzzy clustering based on deterministic annealing, and the three ICA methods, FastICA, Infomax and topographic ICA was performed. The ICA methods proved to extract features relatively well for a small number of independent components but are limited to the linear mixture assumption. The unsupervised Clustering outperforms ICA in terms of classification results but requires a longer processing time than the ICA methods.

Adult↗
PubMed2002

Prospects for quantitative computed tomography imaging in the presence of foreign metal bodies using statistical image reconstruction.

X-ray computed tomography (CT) images of patients bearing metal intracavitary applicators or other metal foreign objects exhibit severe artifacts including streaks and aliasing. We have systematically evaluated via computer simulations the impact of scattered radiation, the polyenergetic spectrum, and measurement noise on the performance of three reconstruction algorithms: conventional filtered backprojection (FBP), deterministic iterative deblurring, and a new iterative algorithm, alternating minimization (AM), based on a CT detector model that includes noise, scatter, and polyenergetic spectra. Contrary to the dominant view of the literature, FBP streaking artifacts are due mostly to mismatches between FBP's simplified model of CT detector response and the physical process of signal acquisition. Artifacts on AM images are significantly mitigated as this algorithm substantially reduces detector-model mismatches. However, metal artifacts are reduced to acceptable levels only when prior knowledge of the metal object in the patient, including its pose, shape, and attenuation map, are used to constrain AM's iterations. AM image reconstruction, in combination with object-constrained CT to estimate the pose of metal objects in the patient, is a promising approach for effectively mitigating metal artifacts and making quantitative estimation of tissue attenuation coefficients a clinical possibility.

Algorithms↗
PubMed1998

Relative coordination reconsidered: a stochastic account.

Von Holst (1939/1973) parsed intersegmental coordination into relative and absolute to distinguish moderate and extreme forms. Kelso and DeGuzman (1992) discussed an interpretation of relative coordination in terms of the chaotic phenomenon of intermittency. The data of concern (DeGuzman &amp Kelso, 1991) do not, however, exclude a stochastic interpretation, which is detailed here following earlier suggestions. The key difference is modeling relative coordination by stochastic variability about weak attractors rather than by deterministic variability about remnants of attractors ("ghost attractors"). The intermittency interpretation is not robust in the presence of noise and, therefore, is not well disposed to account for uncertainty in detailing a model of behavioral data or its parameters. In contrast, the stochastic interpretation is based upon an approximation of unknown underlying processes in the form of Gaussian white noise. A stochastic method for estimating model parameters from a stationary probability distribution and a mean first passage time is illustrated using experimental and simulated data.

Humans↗
PubMed2004

Signaling in small subcellular volumes. II. Stochastic and diffusion effects on synaptic network properties.

The synaptic signaling network is capable of sophisticated cellular computations. These include the ability to respond selectively to different patterns of input, and to sustain changes in response over long periods. The small volume of the synapse complicates the analysis of signaling because the chemical environment is strongly affected by diffusion and stochasticity. This study is based on an updated version of a previously proposed synaptic signaling circuit (Bhalla and Iyengar, 1999) and analyzes three network computation properties in small volumes: bistability, thresholding, and pattern selectivity. Simulations show that although there are diffusive regimes in which bistability may persist, chemical noise at small volumes overwhelms bistability. In the deterministic situation, the network exhibits a sharp threshold for transition between lower and upper stable states. This transition is broadened and individual runs partition between lower and upper states, when stochasticity is considered. The third network property, pattern selectivity, is severely degraded at synaptic volumes. However, there are regimes in which a process similar to stochastic resonance operates and amplifies pattern selectivity. These results imply that simple scaling of signaling conditions to femtoliter volumes is unlikely, and microenvironments, such as reaction complex formation, may be essential for reliable small-volume signaling.

Calcium↗
PubMed2004

An interacting particle system modelling aggregation behavior: from individuals to populations.

In this paper we investigate the stochastic modelling of a spatially structured biological population subject to social interaction. The biological motivation comes from the analysis of field experiments on a species of ants which exhibits a clear tendency to aggregate, still avoiding overcrowding. The model we propose here provides an explanation of this experimental behavior in terms of "long-ranged" aggregation and "short-ranged" repulsion mechanisms among individuals, in addition to an individual random dispersal described by a Brownian motion. Further, based on a "law of large numbers", we discuss the convergence, for large N, of a system of stochastic differential equations describing the evolution of N individuals (Lagrangian approach) to a deterministic integro-differential equation describing the evolution of the mean-field spatial density of the population (Eulerian approach).

Animals↗