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PubMed2006

Fuzzy rank LUM filters.

The rank information of samples is widely utilized in nonlinear signal processing algorithms. Recently developed fuzzy transformation theory introduces the concept of fuzzy ranks, which incorporates sample spread (or sample diversity) information into the sample ranking framework. Thus, the fuzzy rank reflects a sample's rank, as well as its similarity to the other sample (namely, joint rank order and spread), and can be utilized to improve the performance of the conventional rank-order-based filters. In this paper, the well-known lower-upper-middle (LUM) filters are generalized utilizing the fuzzy ranks, yielding the class of fuzzy rank LUM (F-LUM) filters. Statistical and deterministic properties of the F-LUM filters are derived, showing that the F-LUM smoothers have similar impulsive noise removal capability to the LUM smoothers, while preserving the image details better. The F-LUM sharpeners are capable of enhancing strong edges while simultaneously preserving small variations. The performance of the F-LUM filters are evaluated for the problems of image impulsive noise removal, sharpening and edge-detection preprocessing. The experimental results show that the F-LUM smoothers can achieve a better tradeoff between noise removal and detail preservation than the LUM smoothers. The F-LUM sharpeners are capable of sharpening the image edges without amplifying the noise or distorting the fine details. The joint smoothing and sharpening operation of the general F-LUM filters also showed superiority in edge detection preprocessing application. In conclusion, the simplicity and versatility of the F-LUM filters and their advantages over the conventional LUM filters are desirable in many practical applications. This also shows that utilizing fuzzy ranks in filter generalization is a promising methodology.

Algorithms↗
PubMed1996

Carrier-borne epidemic models incorporating population mobility.

A study was made of multigroup epidemic models in which individuals are able to move between groups, infectious contact occurring only between an infective and a susceptible in the same group. Because of the mathematical intractability of such models; we look mainly at the number of susceptibles directly contacted by the infectives that are initially introduced into the population, ignoring subsequent infections caused by these newly infected individuals. We thus have a generalization of the carrier-borne epidemic model of Weiss [Biometrics 21:481-491 (1965)]. We consider first a model in which only infectives are able to move, then one in which both infectives and susceptibles move between groups. In each case we study both deterministic and stochastic versions of the model, concentrating mainly on the effect of varying the speed at which individuals move between groups on the number of initial susceptibles contacted. For the case in which only infectives move, the model is compared with a suitably matched model in which there is no movement between groups but infectives are able to infect outside their own group. The paper concludes with remarks on the behavior of the epidemic process if initially susceptible individuals that become infected are able to contribute to the further spread of the disease.

Carrier State↗
PubMed2001

Nutrient dynamics and the eutrophication of shallow lakes Kasumigaura (Japan), Donghu (PR China), and Okeechobee (USA).

We compared the nutrient dynamics of three lakes that have been heavily influenced by point and non-point source pollution and other human activities. The lakes, located in Japan (Lake Kasumigaura), People's Republic of China (Lake Donghu), and the USA (Lake Okeechobee), all are relatively large (> 30 km2), very shallow (< 4 m mean depth), and eutrophic. In all three lakes we found strong interactions among the sediments, water column, and human activities. Important processes affecting nutrient dynamics included nitrogen fixation, light limitation due to resuspended sediments, and intense grazing on algae by cultured fish. As a result of these complex interactions, simple empirical models developed to predict in-lake responses of total phosphorus and algal biomass to external nutrient loads must be used with caution. While published models may provide 'good' results, in terms of model output matching actual data, this may not be due to accurate representation of lake processes in the models. The variable nutrient dynamics that we observed among the three study lakes appears to be typical for shallow lake systems. This indicates that a greater reliance on lake-specific research may be required for effective management, and a lesser role of inter-lake generalization than is possible for deeper, dimictic lake systems. Furthermore, accurate predictions of management impacts in shallow eutrophic lakes may require the use of relatively complex deterministic modeling tools.

Conservation of Natural Resources↗
PubMed2001

Models for the population biology and control of human onchocerciasis.

The absence of animal models in which to reproduce successfully the complete life cycle of Onchocerca volvulus has hindered progress towards unravelling the processes involved in the regulation of parasite abundance in the vertebrate host. Mathematical frameworks have been developed to explore the consequences of such processes in determining parasite population dynamics and the effect on these of control interventions. Post-control predictions are strongly influenced by the assumptions concerning the reproductive life span of the adult female worm (the longest-lived parasite stage) and the distribution of its survival times, and this notion is important to all frameworks. Here, we review the development of models concerning onchocerciasis and discuss the various approaches that have been used, presenting a deterministic framework with parameter values estimated from the Mexican onchocerciasis control programme. This model is used to evaluate interventions combining the removal of adult worms (nodulectomy) and the microfilaricidal and possibly sterilizing effect of ivermectin.

Animals↗
PubMed2002

Stochastic and mesoscopic models for tropical convection.

A new way to parametrize certain aspects of tropical convection through stochastic and mesoscopic models is developed here. The technical idea is to adapt tools from statistical physics and materials science to model important unresolved features of tropical convection. This new strategy consists of modeling the unresolved effects of convective inhibition in a coarse mesh mesoscopic parametrization through a "heat bath" model involving a stochastic spin flip model with very natural interaction rules for convective inhibition combined with a suitable external potential defined by the coarse mesh values. In turn, the values of the order parameter from this heat bath alter the vertical mass flux in regions of deep convection. Both stochastic and systematic deterministic mesoscopic parametrizations are developed here. The deterministic mesoscopic models derived in this fashion exhibit new phenomena such as multiple radiative equilibria in suitable parameter regimes. The simplest first numerical experiments reported here with the mesoscopic deterministic parametrization qualitatively reproduce several key features of the observational record regarding convectively coupled tropical waves. The systematic stochastic modeling strategy proposed here could also be very useful for capturing other features of tropical convection such as those involving cloud radiation feedbacks.

Models, Theoretical↗
PubMed2000

SPLASH: structural pattern localization analysis by sequential histograms.

MOTIVATION: The discovery of sparse amino acid patterns that match repeatedly in a set of protein sequences is an important problem in computational biology. Statistically significant patterns, that is patterns that occur more frequently than expected, may identify regions that have been preserved by evolution and which may therefore play a key functional or structural role. Sparseness can be important because a handful of non-contiguous residues may play a key role, while others, in between, may be changed without significant loss of function or structure. Similar arguments may be applied to conserved DNA patterns. Available sparse pattern discovery algorithms are either inefficient or impose limitations on the type of patterns that can be discovered. RESULTS: This paper introduces a deterministic pattern discovery algorithm, called Splash, which can find sparse amino or nucleic acid patterns matching identically or similarly in a set of protein or DNA sequences. Sparse patterns of any length, up to the size of the input sequence, can be discovered without significant loss in performances. Splash is extremely efficient and embarrassingly parallel by nature. Large databases, such as a complete genome or the non-redundant SWISS-PROT database can be processed in a few hours on a typical workstation. Alternatively, a protein family or superfamily, with low overall homology, can be analyzed to discover common functional or structural signatures. Some examples of biologically interesting motifs discovered by Splash are reported for the histone I and for the G-Protein Coupled Receptor families. Due to its efficiency, Splash can be used to systematically and exhaustively identify conserved regions in protein family sets. These can then be used to build accurate and sensitive PSSM or HMM models for sequence analysis. AVAILABILITY: Splash is available to non-commercial research centers upon request, conditional on the signing of a test field agreement. CONTACT: acal@us.ibm.com, Splash main page http://www.research.ibm.com/splash

Algorithms↗
PubMed2003

A Bayesian change-point analysis of electromyographic data: detecting muscle activation patterns and associated applications.

Many facets of neuromuscular activation patterns and control can be assessed via electromyography and are important for understanding the control of locomotion. After spinal cord injury, muscle activation patterns can affect locomotor recovery. We present a novel application of reversible jump Markov chain Monte Carlo simulation to estimate activation patterns from electromyographic data. We assume the data to be a zero-mean, heteroscedastic process. The variance is explicitly modeled using a step function. The number and location of points of discontinuity, or change-points, in the step function, the inter-change-point variances, and the overall mean are jointly modeled along with the mean and variance from baseline data. The number of change-points is considered a nuisance parameter and is integrated out of the posterior distribution. Whereas current methods of detecting activation patterns are deterministic or provide only point estimates, ours provides distributional estimates of muscle activation. These estimates, in turn, are used to estimate physiologically relevant quantities such as muscle coactivity, total integrated energy, and average burst duration and to draw valid statistical inferences about these quantities.

Bayes Theorem↗
PubMed2005

Effective size of a fluctuating age-structured population.

Previous theories on the effective size of age-structured populations assumed a constant environment and, usually, a constant population size and age structure. We derive formulas for the variance effective size of populations subject to fluctuations in age structure and total population size produced by a combination of demographic and environmental stochasticity. Haploid and monoecious or dioecious diploid populations are analyzed. Recent results from stochastic demography are employed to derive a two-dimensional diffusion approximation for the joint dynamics of the total population size, N, and the frequency of a selectively neutral allele, p. The infinitesimal variance for p, multiplied by the generation time, yields an expression for the effective population size per generation. This depends on the current value of N, the generation time, demographic stochasticity, and genetic stochasticity due to Mendelian segregation, but is independent of environmental stochasticity. A formula for the effective population size over longer time intervals incorporates deterministic growth and environmental stochasticity to account for changes in N.

Age Factors↗
PubMedDate not supplied

[Occupational accidents at an Acute Care Hospital].

BACKGROUND: To obtain a better knowledge of the determining factors and circumstances giving rise to occupational accidents will foster the implementation of corrective measures. The aim of this study is that of describing the trend of occupational accidents (OA's) over the course of time and of determining the risk factors regarding workers being forced to take time off for sick leave at the "Dr. Peset" Hospital in Valencia. METHODS: Description and retrospective analysis of the occupational accidents having occurred at the "Dr. Peset" Hospital in Valencia throughout the 1992-1995 period. The trend and seasonality of the series (seasonal indexes, SI's) were estimated by deterministic methods. A logistic regression model was employed to identify the factors providing a prior indication workers being off on sick leave and to determine the probability of the occurrence thereof. RESULTS: The highest OA rates were found among the kitchen and laundry workers (10.00 OA's per 100 workers/year). The OA's involving sick leave continued to show a trend of around zero, February being the months showing the highest SI (SI = 139.8). Those processed without sick leave showed an upward trend (r2 = 0.23, p < 0.0001), May being the month involving the largest number of casualties (SI = 134.2). The probability of an accident resulting in a worker being forced to take time of for sick leave increases significantly with age, when the accident in question takes place in the afternoon/evening, if it takes place in the kitchen/laundry, and if a sprain or tendinitis is involved. CONCLUSIONS: The measures taken involving the number of casualties entailing OA's which result in temporary incapacity should revolve around the less-skilled positions and the kitchen and laundry departments.

Accidents, Occupational↗
PubMed2004

A method for a real time estimation of entrance skin dose distribution in interventional neuroradiology.

Interventional neuroradiology can involve very high entrance skin doses to patients and has the potential to induce deterministic radiation effects to the skin. A monitoring system indicating the maximum entrance skin dose during procedures could be useful to avoid skin injuries and to optimize technical parameters. Such evaluation is difficult, because exposure conditions change many times during each procedure. A data acquisition system for real time estimation of patient dose was developed, using a transmission ionization chamber connected to a personal computer, simultaneously measuring air kerma and dose area product. Input data were processed by a software that provided a map of entrance skin dose and stored all the information in a database. The method was first applied during 16 interventional procedures and was found to be suitable to this application thanks to the short time necessary for dose measurements, simplicity of use and absence of interference with the procedure execution. The uncertainty of estimation of maximum entrance skin dose was evaluated to be about 20% at the 1 sigma level.

Algorithms↗
PubMed2001

Computational cell biology: spatiotemporal simulation of cellular events.

The field of computational cell biology has emerged within the past 5 years because of the need to apply disciplined computational approaches to build and test complex hypotheses on the interacting structural, physical, and chemical features that underlie intracellular processes. To meet this need, newly developed software tools allow cell biologists and biophysicists to build models and generate simulations from them. The construction of general-purpose computational approaches is especially challenging if the spatial complexity of cellular systems is to be explicitly treated. This review surveys some of the existing efforts in this field with special emphasis on a system being developed in the authors' laboratory, Virtual Cell. The theories behind both stochastic and deterministic simulations are discussed. Examples of respective applications to cell biological problems in RNA trafficking and neuronal calcium dynamics are provided to illustrate these ideas.

Animals↗
PubMed1997

CELSS-3D: a broad computer model simulating a controlled ecological life support system.

CELSS-3D is a dynamic, deterministic, and discrete computer simulation of a controlled ecological life support system (CELSS) focusing on biological issues. A series of linear difference equations within a graphic-based modeling environment, the IThink program, was used to describe a modular CELSS system. The overall model included submodels for crop growth chambers, food storage reservoirs, the human crew, a cyanobacterial growth chamber, a waste processor, fixed nitrogen reservoirs, and the atmospheric gases, CO, O2, and N2. The primary process variable was carbon, although oxygen and nitrogen flows were also modeled. Most of the input data used in CELSS-3D were from published sources. A separate linear optimization program, What'sBest!, was used to compare options for the crew's vegetarian diet. CELSS-3D simulations were run for the equivalent of 3 years with a 1-h time interval. Output from simulations run under nominal conditions was used to illustrate dynamic changes in the concentrations of atmospheric gases. The modular design of CELSS-3D will allow other configurations and various failure scenarios to be tested and compared.

Atmosphere↗
PubMed2004

Cellware--a multi-algorithmic software for computational systems biology.

UNLABELLED: The intracellular environment of a cell hosts a wide variety of enzymatic reactions, diffusion events, molecular binding, polymerization and metabolic channeling. To transform these biological events into a computational framework, distinct modeling strategies are required. While currently no tool is capable of capturing all these events, progress is being made to create an integrated environment for the modeling community. To address this niche requirement, Cellware has been developed to offer a multi-algorithmic environment for modeling and simulating both deterministic and stochastic events in the cell. AVAILABILITY: The software is available for free and can be downloaded from http://www.bii.a-star.edu.sg/sbg/cellware

Algorithms↗
PubMed1994

Chaos in biometry.

Although the study of chaotic and periodic phenomena began as recently as the 1960s, its subsequent development during the past few years has been extremely rapid in terms of both theory and practical application. The purpose of this paper is therefore to present an overview which will enable researchers with little prior knowledge to assess the relevance and potential application of nonlinear systems to problems in medicine and biology. Deterministic dynamic behaviour is examined through discrete logistic-type equations; stochastic behaviour is studied by superimposing an appropriate birth-death structure. Analysis of a variety of insect data sets shows that periodic and chaotic structures do indeed feature in natural populations; the classic Nicholson's blowfly data are viewed from both stochastic limit-cycle and deterministic chaos standpoints. Determination of the attractor dimension can be an invaluable aid to the understanding of biological and medical phenomena, and convincing examples include phase-space comparisons between healthy and sick humans for both EEG and ECG records.

Animals↗
PubMed2002

Creating a statistical atlas of the cranium.

Normative data is very important for simulation procedures in craniofacial surgery. While treating e.g. a malformed skull the surgeon seeks to reconstruct its natural and harmonic shape. Atlas or normative data of the skull could support the surgeon in this effort, as it would provide a standard model of the skull which gives an idea of the natural shape. We create a standard skull by averaging regularly formed skulls in a shape space spanned by spherical harmonics. While state-of-the-art methods use landmarks to define the shape and mean shapes, this method is deterministic, i.e. it manages averaging without landmarks and it provides a complete description of the shape. In addition the shape space can be used to classify shapes to identify different types of an anatomy.

Cephalometry↗
PubMed1995

A minimal single-channel model for the regularity of beating in the sinoatrial node.

It has been suggested that the normal irregular beating of the heart is a manifestation of deterministically chaotic dynamics. Evidence proffered in support of this hypothesis includes a 1/f-like power spectrum, a small noninteger correlation dimension, and self-similarity of the time series. The major cause of the normal fluctuations in heart rate is the impingement of several neural and hormonal control systems upon the sinoatrial node, the natural pacemaker of the heart. However, intrinsic fluctuations of beat rate can be seen in the isolated node, devoid of all neural and hormonal inputs, and even in a single cell isolated from the node. The electrical activity in such a single cell is generated by ions flowing through discrete channels in the cell membrane.We decided to test the hypothesis that the fluctuations in beat rate in a single cell might be due to the fluctuations in the activity of this population of single channels. We thus assemble a model consisting of 6000 channels and probe its dynamics. Each channel has one or more gates, all of which must be open to allow current to flow through the channel. Since these gates are thought to open and close in a random manner, we model each gate by a Markov process, assigning a pseudorandom number to each gate every time that it changes state from open to closed or vice versa. This number, in conjunction with the classical voltage-dependent Hodgkin-Huxley-like rate constants that control the speed with which a gate will open or close, then determines when that gate will next change state. We also employ a second method that is much more efficient computationally, in which one computes the lifetime of the ensemble of 6000 channels. We show that the Monte Carlo model has behavior consistent with the hypothesis that the irregular beating seen experimentally in single nodal cells is due to the (pseudo)random opening and closing of single channels. However, since the pseudorandom number generator used in the simulations is deterministic, one cannot state that the activity in the model is random (or stochastic). Thus, it would be premature to claim that the irregularity of beating in a single nodal cell is accounted for by the stochastic behavior of a population of a few thousand single channels lying in the membrane of the cell. Finally, we consider some implications of our work for the naturally occurring in situ fluctuations in heart rate ("heart rate variability"). (c) 1995 American Institute of Physics.

Journal Article↗
PubMed2002

Technique analysis in sports: a critical review.

This paper critically reviews technique analysis as an analytical method used within sports biomechanics as a part of performance analysis. The concept of technique as 'a specific sequence of movements' appears to be well established in the literature, but the concept of technique analysis is less well developed. Although several descriptive and analytical goals for technique analysis can be identified, the main justification given for its use is to aid in the improvement of performance. However, the conceptual framework underpinning this process is poorly developed with a lack of distinction between technique and performance. The methods of technique analysis have been divided into qualitative, quantitative and predictive components. Qualitative technique analysis is characterized by observation and subjective judgement. Several aids to observation are identified, including phase analysis, temporal analysis and critical feature analysis. Although biomechanical principles of movement can be used to form judgements about technique, little agreement exists about the number and categories of these principles. A 'deterministic' model can be used to identify factors that affect performance but, in doing so, technique variables are frequently overlooked. Quantitative technique analysis relies on biomechanical data collection methods. The identification of key technique variables that affect performance is a major issue, but these are poorly distinguished from other variables that affect performance. Quantitative analysis is not suitable for establishing the characteristics of the whole skill, but new methods, such as the use of artificial neural networks, are described that may be able to overcome this limitation. Other methods based on modelling and computer simulation also have potential for focusing on the whole skill. Predictive technique analysis encompasses these developments and offers an attractive interface between the scientist and coach through visual animation methods. I conclude that biomechanists need to clarify the underpinning rationale, framework and scope for the various approaches to technique analysis.

Biomechanical Phenomena↗
PubMed1982

Probabilistic assignments of sentence relations on the basis of differentially weighted interpretive cues.

Recent treatments of comprehension have emphasized the role of surface structure characteristics. In many circumstances, meanings that are inferred on the basis of such cues will not be deterministic. This study investigated a probabilistic system of sentence comprehension. Hebrew-speaking university students interpreted utterances that varied and balanced the contradictory and complementary effects of three interpretive cues. Sentence interpretations were systematically affected by the relative weights of cues that supported and opposed different interpretations. Adults therefore seemed to deploy a probabilistic strategy of assigning internal relations to a preferred alternative, a greatest composite of component likelihoods. While the present treatment emphasized a syntactic level of processing, it was suggested that the probabilistic strategy could easily accommodate pragmatic and semantic effects as well. The probabilistic strategy implies that given a conflict between interpretive cues, a decision needs to be made between alternative assignments of internal relations. It was therefore suggested that ambiguous and unambiguous utterances typically may be processed in a similar fashion; for both, more than one meaning may be processed at least in part before a single probabilistic interpretation is finally assigned to the utterance.

Cues↗