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Deformation models and correlation analysis in elastography.

Cross-correlation functions are derived with the purpose of determining how strain inhomogeneities affect the displacement estimates used in ultrasound-based elastography. Variations in the strain profile occur in most imaging situations and are caused by fluctuations in the stress field or elastic modulus of the sample. An analytical framework for developing signal processing strategies in elastography is described, and the limitations of correlation-based methods for measuring displacements in tissuelike media caused by static compression are emphasized. This paper includes (1) an accurate approximation for an inverse coordinate transformation that release pre- and postcompression reflectivity profiles of the media, (2) a derivation of the echo-signal cross-correlation function in media with deterministic or stochastic strain profiles; (3) mathematical and graphical descriptions of the consequences that nonuniformities in the strain profile impose upon the uncertainty of displacement estimation; and (4) a demonstration of the advantages of echo signal conditioning and ultrasonic-pulse shaping to reduce the nonstationary effects that attenuate the cross-correlation peak and reduce the signal-to-noise ration for displacement estimation.

Elasticity↗

Whole cell stochastic model reproduces the irregularities found in the membrane potential of bursting neurons.

Irregular intrinsic behavior of neurons seems ubiquitous in the nervous system. Even in circuits specialized to provide periodic and reliable patterns to control the repetitive activity of muscles, such as the pyloric central pattern generator (CPG) of the crustacean stomatogastric ganglion (STG), many bursting motor neurons present irregular activity when deprived from synaptic inputs. Moreover, many authors attribute to these irregularities the role of providing flexibility and adaptation capabilities to oscillatory neural networks such as CPGs. These irregular behaviors, related to nonlinear and chaotic properties of the cells, pose serious challenges to developing deterministic Hodgkin-Huxley-type (HH-type) conductance models. Only a few deterministic HH-type models based on experimental conductance values were able to show such nonlinear properties, but most of these models are based on slow oscillatory dynamics of the cytosolic calcium concentration that were never found experimentally in STG neurons. Based on an up-to-date single-compartment deterministic HH-type model of a STG neuron, we developed a stochastic HH-type model based on the microscopic Markovian states that an ion channel can achieve. We used tools from nonlinear analysis to show that the stochastic model is able to express the same kind of irregularities, sensitivity to initial conditions, and low dimensional dynamics found in the neurons isolated from the STG. Without including any nonrealistic dynamics in our whole cell stochastic model, we show that the nontrivial dynamics of the membrane potential naturally emerge from the interplay between the microscopic probabilistic character of the ion channels and the nonlinear interactions among these elements. Moreover, the experimental irregular behavior is reproduced by the stochastic model for the same parameters for which the membrane potential of the original deterministic model exhibits periodic oscillations.

Action Potentials↗

[Scientific change in times of political upheaval: Germany in the 20th century].

Until recently, the development of the modern sciences has usually been described as a continuous unfolding of constantly expanding and differentiating research institutions on the one hand, and the accumulation of more and better knowledge on the other. The changes that have occurred both in scientific institutions and in the direction and content of research in the course of revolutions or comparable political changes pose significant challenges to such accounts. I would like to propose an interactive approach to this issue. Instead of accepting a linear, deterministic model of scientific change as a result of political upheaval, I suggest that such political changes present an array of challenges to and possibilities for the interruption, redirection, reconstruction or effortful continuation of research. The central claim is that scientific development in times of political upheaval has proceeded in Germany primarily by means of increasing cooperation of scientists with the state, involving a process that I call the technologization of basic research. But this is not always a one-sided affair involving the subordination of science to practical politics or to ideology. Rather, I argue, what occurs is the mobilization or reconstruction of physical, institutional, financial cognitive and/or rhetorical resources. Such mobilizations can proceed in various directions: the state or agencies within it can mobilize scientists as resources in the interest of achieving certain political aims; scientists can convert themselves into such resources (or claim that they are doing so); or both things can happen at once. The approach is exemplified by examining continuities and changes in the situations of the sciences following the major turning points of 20th century German history, symbolized by the dates 1918, 1933, 1945 and 1990. Considered in particular are: scientific changes in Germany following the Nazi takeover and creative innovations by émigré scientists working in different cultural settings; the massive transfer of scientific resources after Nazi Germany's defeat and attempts to carry on and reconstruct science in the two postwar German states; and the massive reorganization of scientific institutions in eastern Germany after unification. The examples come primarily from biology and experimental psychology, but physical sciences and particular branches of technology are considered as well.

Germany↗

Functional and compositional comparison of two activated sludge communities remediating coking effluent.

The success of engineered microbiological systems is evident in the global application of activated sludge communities to remediate coking effluent. However, there is a lack of understanding of the microbiology underlying treatment efficiency and stability. In this study, two functionally distinct activated sludge pools, treating the same effluent and operating under the same conditions, were examined to establish a relationship between overall diversity and/or functional diversity with respect to process stability. Molecular profiling, sequencing and RNA-based stable isotope probing were used to examine the bacterial diversity, general composition and functional composition of the most abundant members of the two communities. The inferior process stability in one of the pools could not be explained by reduced total bacterial diversity or evenness. RNA-based stable isotope probing revealed that both pools harboured an abundant phenol-degrading Acidovorax species, and that the pool of inferior stability accommodated an additional closely related phenol-degrading Acidovorax species at high abundance. These results are discussed in the context of deterministic and stochastic models of microbial community assembly.

Base Sequence↗

Patient dosimetry approaches in interventional cardiology and literature dose data review.

Interventional radiology contributes a significant proportion of the collective dose of the population from medical exposures. Interventional radiology procedures are usually fluoroscopy-guided diagnostic and therapeutic interventions. When complex procedures are performed or procedures are repeated for the same patient, high-radiation dose levels can occur because procedures often require long fluoroscopy times and require high-quality images. For all of these reasons, dosimetric evaluations in interventional radiology are widely increasing. Patient dosimetry methods currently used in interventional radiology may be divided into three categories according to dosimetry purpose: (I) dosimetry for stochastic risk evaluation, (II) dosimetry for quality assurance and (III) dosimetry to prevent the deterministic effects of radiation. A short description of dosimetric methods used in interventional cardiology practice and relevant published dosimetric data are reported.

Angioplasty, Balloon, Coronary↗

Stochastic model for heart-rate fluctuations.

A normal human heart rate shows complex fluctuations in time, which is natural, because the heart rate is controlled by a large number of different feedback control loops. These unpredictable fluctuations have been shown to display fractal dynamics, long-term correlations, and 1/f noise. These characterizations are statistical and they have been widely studied and used, but much less is known about the detailed time evolution (dynamics) of the heart-rate control mechanism. Here we show that a simple one-dimensional Langevin-type stochastic difference equation can accurately model the heart-rate fluctuations in a time scale from minutes to hours. The model consists of a deterministic nonlinear part and a stochastic part typical to Gaussian noise, and both parts can be directly determined from the measured heart-rate data. Studies of 27 healthy subjects reveal that in most cases, the deterministic part has a form typically seen in bistable systems: there are two stable fixed points and one unstable one.

Cardiovascular System↗

COPASI--a COmplex PAthway SImulator.

MOTIVATION: Simulation and modeling is becoming a standard approach to understand complex biochemical processes. Therefore, there is a big need for software tools that allow access to diverse simulation and modeling methods as well as support for the usage of these methods. RESULTS: Here, we present COPASI, a platform-independent and user-friendly biochemical simulator that offers several unique features. We discuss numerical issues with these features; in particular, the criteria to switch between stochastic and deterministic simulation methods, hybrid deterministic-stochastic methods, and the importance of random number generator numerical resolution in stochastic simulation. AVAILABILITY: The complete software is available in binary (executable) for MS Windows, OS X, Linux (Intel) and Sun Solaris (SPARC), as well as the full source code under an open source license from http://www.copasi.org.

Algorithms↗

Presence of cepstral peak in random reflected ultrasound signals.

A peak in the power cepstrum, or the squared magnitude of the Fourier transform of the data log-power spectrum, is commonly observed when processing reflections from plate-like structures, such as membranes. In this case, the cepstral peak at the smallest nonzero time lag, or quefrency, value can be used to determine the thickness of the plate. For reflections from a medium composed of randomly distributed scatterers, such as liver tissue, a cepstral peak is also commonly observed, but cannot be so intuitively explained as in the deterministic case above. In this paper, it is demonstrated that the presence of a cepstral peak depends on the form of the probability density function (pdf) of the separation between reflectors. In the case where the pdf is uniform from O to SM, the cepstral peak is found to occur at the quefrency corresponding to SM. For simple unimodal pdfs, a cepstral peak will occur at the location of the maximum probability. These observations are shown analytically and verified through simulations. The diagnostic value of these results lies in the interpretation of the relation of the cepstral peak location to the spacing of the scattering elements in the tissue.

Fourier Analysis↗

[Predicting individual reactions to emotional stress and benzodiazepine tranquilizers].

The results of pharmacogenetic experiments revealed specificity of the emotional-stress reactions (ESR) in the inherited deterministic type of behavior and showed dependence of the benzodiazepine tranquilizer action on the ESR phenotype. Based on these data, we carried out experiments with a group of volunteers performing operator functions in a model of emotional-stress conditions. The results of these experiments allowed the operators to be divided into stress-resistant and stress-affected groups. The results of the data processing by methods of multidimensional statistics showed possibility of predicting the ESR phenotype and the qualitative effect of phenazepam (0.5 mg. p.o.) based on the individual topological and hormonal-biochemical characteristics of operators.

Adult↗

Attention-based dynamic visual search using inner-scene similarity: algorithms and bounds.

A visual search is required when applying a recognition process on a scene containing multiple objects. In such cases, we would like to avoid an exhaustive sequential search. This work proposes a dynamic visual search framework based mainly on innerscene similarity. Given a number of candidates (e.g., subimages), we hypothesize is that more visually similar candidates are more likely to have the same identity. We use this assumption for determining the order of attention. Both deterministic and stochastic approaches, relying on this hypothesis, are considered. Under the deterministic approach, we suggest a measure similar to Kolmogorov's epsilon-covering that quantifies the difficulty of a search task. We show that this measure bounds the performance of all search algorithms and suggest a simple algorithm that meets this bound. Under the stochastic approach, we model the identity of the candidates as a set of correlated random variables and derive a search procedure based on linear estimation. Several experiments are presented in which the statistical characteristics, search algorithm, and bound are evaluated and verified.

Algorithms↗

Random walks, random sequences, and nonlinear dynamics in human optokinetic nystagmus.

Optokinetic nystagmus (OKN) is a reflexive eye movement with target-following slow phases (SP) alternating with oppositely directed fast phases (FP). We measured the following from OKN in three humans: FP beginning and ending positions, amplitudes, and intervals and SP amplitudes and velocities. We sought to predict future values of each parameter on the basis of past values, using state-space representation of the sequence (time-delay embedding) and local second-order approximation of trajectories. Predictability is an indication of determinism: this approach allows us to investigate the relative contributions of random and deterministic dynamics in OKN. FP beginning and ending positions showed good predictability, but SP velocity was less predictable. FP and SP amplitudes and FP intervals had little or no predictability. FP beginnings and endings were as predictable as randomized versions that retain linear autocorrelation; this is typical of random walks. Predictability of FP intervals did not change under random rearrangement, which is characteristic of a random process. Only linear determinism was demonstrated; nonlinear interactions may exist that would not be detected by our present approach.

Humans↗

Modeling selection for production traits under constant infection pressure.

This article presents a model describing the relationship between level of disease resistance and production under constant infection pressure. The model assumes that given a certain infection pressure, there is a threshold for resistance below which animals will stop producing, and that there is also a threshold for resistance above which animals produce at production potential. In between both thresholds animals will show a decrease in production, the size of decrease depending on the severity of infection and the level of resistance. The dynamic relationship between production and resistance when level of resistance changes, such as due to infection, is modeled both stochastically and deterministically. Selection started in a population with very poor level of resistance introduced in an environment with constant infection pressure. Mass selection on observed production was applied, which resulted in a nonlinear selection response for all three traits considered. When resistance is poor, selection for observed production results in increased level of resistance. With increasing level of resistance, selection response shifts to production potential and eventually selection for observed production is equivalent to selection for production potential. The rate at which resistance is improved depends on its heritability, the difference between both thresholds, and selection intensity. The model also revealed that when a zero correlation between resistance and production potential is assumed, the phenotypic correlation between resistance and observed production level increases for low levels of resistance and subsequently asymptotes to zero, whereas the phenotypic correlation between production potential and observed production asymptotes to 1.0. For most breeding schemes investigated, the deterministic model performed well in relation to the stochastic simulation results. Experimental results reported in literature support the model predictions.

Animal Husbandry↗

Failed refutations: further comments on parsimony and likelihood methods and their relationship to Popper's degree of corroboration.

Kluge's (2001, Syst. Biol. 50:322-330) continued arguments that phylogenetic methods based on the statistical principle of likelihood are incompatible with the philosophy of science described by Karl Popper are based on false premises related to Kluge's misrepresentations of Popper's philosophy. Contrary to Kluge's conjectures, likelihood methods are not inherently verificationist; they do not treat every instance of a hypothesis as confirmation of that hypothesis. The historical nature of phylogeny does not preclude phylogenetic hypotheses from being evaluated using the probability of evidence. The low absolute probabilities of hypotheses are irrelevant to the correct interpretation of Popper's concept termed degree of corroboration, which is defined entirely in terms of relative probabilities. Popper did not advocate minimizing background knowledge; in any case, the background knowledge of both parsimony and likelihood methods consists of the general assumption of descent with modification and additional assumptions that are deterministic, concerning which tree is considered most highly corroborated. Although parsimony methods do not assume (in the sense of entailing) that homoplasy is rare, they do assume (in the sense of requiring to obtain a correct phylogenetic inference) certain things about patterns of homoplasy. Both parsimony and likelihood methods assume (in the sense of implying by the manner in which they operate) various things about evolutionary processes, although violation of those assumptions does not always cause the methods to yield incorrect phylogenetic inferences. Test severity is increased by sampling additional relevant characters rather than by character reanalysis, although either interpretation is compatible with the use of phylogenetic likelihood methods. Neither parsimony nor likelihood methods assess test severity (critical evidence) when used to identify a most highly corroborated tree(s) based on a single method or model and a single body of data; however, both classes of methods can be used to perform severe tests. The assumption of descent with modification is insufficient background knowledge to justify cladistic parsimony as a method for assessing degree of corroboration. Invoking equivalency between parsimony methods and likelihood models that assume no common mechanism emphasizes the necessity of additional assumptions, at least some of which are probabilistic in nature. Incongruent characters do not qualify as falsifiers of phylogenetic hypotheses except under extremely unrealistic evolutionary models; therefore, justifications of parsimony methods as falsificationist based on the idea that they minimize the ad hoc dismissal of falsifiers are questionable. Probabilistic concepts such as degree of corroboration and likelihood provide a more appropriate framework for understanding how phylogenetics conforms with Popper's philosophy of science. Likelihood ratio tests do not assume what is at issue but instead are methods for testing hypotheses according to an accepted standard of statistical significance and for incorporating considerations about test severity. These tests are fundamentally similar to Popper's degree of corroboration in being based on the relationship between the probability of the evidence e in the presence versus absence of the hypothesis h, i.e., between p(e|hb) and p(e|b), where b is the background knowledge. Both parsimony and likelihood methods are inductive in that their inferences (particular trees) contain more information than (and therefore do not follow necessarily from) the observations upon which they are based; however, both are deductive in that their conclusions (tree lengths and likelihoods) follow necessarily from their premises (particular trees, observed character state distributions, and evolutionary models). For these and other reasons, phylogenetic likelihood methods are highly compatible with Karl Popper's philosophy of science and offer several advantages over parsimony methods in this context.

Knowledge↗

On the lag phase and initial decline of microbial growth curves.

The lag phase is generally thought to be a period during which the cells adjust to a new environment before the onset of exponential growth. Characterizing the lag phase in microbial growth curves has importance in food sciences, environmental sciences, bioremediation and in understanding basic cellular processes. The goal of this work is to extend the analysis of cell growth curves and to better estimate the duration of the lag phase. A non-autonomous model is presented that includes actively duplicating cells and two subclasses of non-duplicating cells. The growth curves depend on the growth and death rate of these three subpopulations and on the initial proportion of each. A deterministic and a stochastic model are both developed and give the same results. A notable feature of the model is the decline of cells during the early stage of the growth curve, and the range of parameters when this decline occurs is identified. A limited growth model is also presented that accounts for the lag, exponential growth and stationary phase of microbial growth curves.

Bacteria↗

Valency or wählency: is the epitope diversity of the B-cell response regulated or chemically determined?

For almost a century, the humoral immune response has been monitored principally by the measurement of antibody concentrations, although antibody affinity and isotype have also long been acknowledged as critical to their biological activity. In this report, it is argued that these measures alone may provide a poor measure of the activity of serum antibodies. A B-cell response that is directed against multiple epitopes on a protein can form immune complexes bearing multiple antibody molecules. This is essential for the efficient initiation of processes such as the complement cascade and the activation of leucocytes via Fc receptors. These processes can be dramatically enhanced when B cells target a greater number of epitopes on any antigen. Evidence that the epitope diversity of an immune response may vary between individuals, and that it may vary in an individual over time, is reviewed. This variability is likely to be influenced by a number of host-specific factors in addition to antigen chemistry. The appropriateness of the chemically deterministic term 'antigen valency' to describe the number of epitopes recognized by an individual's B-cell response is discussed, and the term 'wählency' to emphasize the situational nature of B-cell epitopes is introduced.

Animals↗

Prediction of growth factor effects on engineered cartilage composition using deterministic and stochastic modeling.

In the design of engineered tissues, guided balance of biomaterial degeneration with tissue synthesis offers refined control of construct development. The objective of this study was to develop a mathematical model that describes the steady state metabolism of extracellular matrix molecules (ECM: glycosaminoglycan and collagen) in an engineered cartilage construct taking into account localized environmental changes that may arise because of the application of growth factors. The variable effects of growth factors were incorporated in the form of random noise rather than the difference in rates of synthesis and catabolism. Thus, the frequency of ECM accumulation for each matrix molecule in the steady state under the random influence of growth factor was produced relative to the matrix carrying capacity. Published synthesis-rate time constants and steady state ECM conditions from chondrocyte-polymer scaffold composites provided both input and validation for the model. Although the presence of growth factors in the presented system dynamics were considered randomized, the results described a positive feedback or promotional ECM synthesis at low levels of growth factors. While a negative feedback or inhibition of ECM synthesis was characterized at higher levels of growth factors. This transition phenomenon is based on a comparison with the results of a steady state condition in the form of a deterministic model and supports previous reports of guided accumulation in musculoskeletal, connective, and neuronal tissues.

Animals↗

Disease in endangered metapopulations: the importance of alternative hosts.

Conventional applications of metapopulation theory have suggested that increasing migration between patches is usually good for conservation. A recent analysis by Hess has pointed out a possible exception to this: when infectious disease is present, migration may promote disease spread and therefore increase local extinction. We extend Hess's model to discuss this problem: when infections have spilled over from more abundant alternative hosts. This is often the case for species of conservation concern, and we find that Hess's conclusions must be substantially modified. We use deterministic analytic and stochastic numerical approaches to show that movement between patches will rarely have a negative impact, even when the probability of external infection is low.

Animal Diseases↗

Computationally intensive econometrics using a distributed matrix-programming language.

This paper reviews the need for powerful computing facilities in econometrics, focusing on concrete problems which arise in financial economics and in macroeconomics. We argue that the profession is being held back by the lack of easy-to-use generic software which is able to exploit the availability of cheap clusters of distributed computers. Our response is to extend, in a number of directions, the well-known matrix-programming interpreted language Ox developed by the first author. We note three possible levels of extensions: (i) Ox with parallelization explicit in the Ox code; (ii) Ox with a parallelized run-time library; and (iii) Ox with a parallelized interpreter. This paper studies and implements the first case, emphasizing the need for deterministic computing in science. We give examples in the context of financial economics and time-series modelling.

Computer Communication Networks↗