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Results for “Deterministic Measurement”

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PubMed1999

Diplophonia reappraised.

The acoustic structure of diplophonia was investigated spectrographically and in terms of perturbation measures, while the perception of diplophonia among other voice qualities was confirmed auditorily by trained listeners. Recordings of pathological voices were presented to listeners for systematic evaluation, and narrowband spectrography was used to quantify the subharmonics within each sample. Subharmonics strongly correlated with the perception of diplophonia, but occurrence was mostly intermittent, and structure was highly variable between samples. Uniquely among voice qualities identified perceptually, diplophonia was found to correlate positively with the number of subharmonics (irrespective of percentage of occurrence) and with perturbation parameters measured separately. Exceptions to these group results indicated that diplophonia was perceived sometimes in the absence of subharmonic structure, and subharmonic structure was observed without a commensurate perception of diplophonia. In light of these data, a less deterministic relation between diplophonia and subharmonic structure is proposed.

Humans↗

PubMed2005

NASA Space Radiation Transport Code Development Consortium.

Recently, NASA established a consortium involving the University of Tennessee (lead institution), the University of Houston, Roanoke College and various government and national laboratories, to accelerate the development of a standard set of radiation transport computer codes for NASA human exploration applications. This effort involves further improvements of the Monte Carlo codes HETC and FLUKA and the deterministic code HZETRN, including developing nuclear reaction databases necessary to extend the Monte Carlo codes to carry out heavy ion transport, and extending HZETRN to three dimensions. The improved codes will be validated by comparing predictions with measured laboratory transport data, provided by an experimental measurements consortium, and measurements in the upper atmosphere on the balloon-borne Deep Space Test Bed (DSTB). In this paper, we present an overview of the consortium members and the current status and future plans of consortium efforts to meet the research goals and objectives of this extensive undertaking.

Algorithms↗

PubMed1997

Algorithmic complexity of growth hormone release in humans.

Most hormones are secreted in an pulsatile rather than in a constant manner. This temporal pattern of pulsatile hormone release plays an important role in the regulation of cellular function and structure. In healthy humans growth hormone (GH) secretion is characterized by distinct pulses whereas patients bearing a GH producing tumor accompanied with excessive secretion (acromegaly) exhibit a highly irregular pattern of GH release. It has been hypothesized that this highly disorderly pattern of GH release in acromegaly arises from random events in the GH-producing tumor under decreased normal control of GH secretion. Using a context-free grammar complexity measure (algorithmic complexity) in conjunction with random surrogate data sets we demonstrate that the temporal pattern of GH release in acromegaly is not significantly different from a variety of stochastic processes. In contrast, normal subjects clearly exhibit deterministic structure in their temporal patterns of GH secretion. Our results support the hypothesis that GH release in acromegaly is due to random events in the GH-producing tumorous cells which might become independent from hypothalamic regulation.

Acromegaly↗

PubMed1998

Why do anatomic backgrounds reduce lesion detectability?

RATIONALE AND OBJECTIVES: Developing metrics of medical image quality requires an understanding of how anatomic backgrounds reduce human visual detection performance. Visual psychophysics has shown that there are two distinct ways in which a complex background can degrade performance: (1) the presence of a deterministic high-contrast background, (2) variability in the background from location to location. The authors investigated how these two sources of performance degradation reduce human visual performance locating a lesion in anatomic backgrounds. METHODS: Human performance localizing a disk-shaped lesion in one of four locations (four alternative forced choice) was measured for three background conditions. In the first condition the background was a uniform gray. In the second condition (the repeated background condition) an anatomic background was sampled on each trial and used as a background for the four possible lesion locations. In the third condition (the different background condition) four different anatomic backgrounds were sampled on each trial and used for the four possible lesion locations. Test images consisted of computer simulated lesions mathematically projected on digital x-ray coronary angiograms. RESULTS: For five levels of lesion contrast, visual detection performance for two observers decreased significantly from the uniform background condition to the repeated background condition, and decreased even further for the different background condition. CONCLUSIONS: Study results show that both the presence of a deterministic high-contrast background and the background variations contribute to performance degradation of human visual detection of signals in anatomic backgrounds.

Diagnostic Imaging↗

PubMed1989

On the description of neuronal output properties using spike train data.

Neuronal output properties for input stimuli that evoke a deterministic response can be efficiently described by the interspike-interval function (Awiszus 1988a). It is shown in this paper that there are stimuli for which both the Hodgkin-Huxley (HH-) model of an action potential encoding membrane (Hodgkin and Huxley 1952) and a muscle spindle primary afferent generate responses which violate the conditions for a deterministic one. Instead of being stochastic these responses follow systematic rules, namely those for a semi-deterministic response, a class of neuronal responses established in this paper that includes the deterministic one. Instead of being stochastic these output properties are best described by the interspike-interval curve. A phase plane analysis of the internal properties of the HH-model underlying such responses shows that it is reasonable to assume that responses of an HH-model and consequently, all neurons for which an HH-model is a valid description of the action potential encoding process, always fall into the class of semi-deterministic responses, regardless of the input current density time course as long as it is large enough to maintain spike activity. Consequences of this assumption for the analysis of neuronal output properties are discussed with respect to output measures and efficient input stimuli.

Action Potentials↗

PubMed1995

Looking for chaos in brain slices.

Many signals measured from the nervous system exhibit apparently random variability that is usually considered to be noise. The development of chaos theory has revealed that such random appearing variability may not, in fact, be random, but rather may be deterministic behavior that can reveal important information about the system's underlying mechanisms. We present some new methods for distinguishing determinism from randomness in experimental data, and we apply these methods to population neural responses recorded from hippocampal tissue slices.

Brain↗

PubMed2001

Response-time dynamics: evidence for linear and low-dimensional nonlinear structure in human choice sequences.

Response time (RT) is a commonly used measure of cognitive performance, which is usually characterized as stochastic. However, useful information may be hidden in the apparently random fluctuations of RT. Dynamical systems analysis techniques allow an exploration of the alternative hypothesis that RT fluctuations are deterministic, albeit in a complex manner. We applied careful task construction and noise-reduction and surrogate series tests to show that RT series from a forced-pace serial response-time task have low-dimensional chaotic characteristics. In Experiment 1, 80% of subjects' filtered RT series had low dimensionality, sensitive dependence on initial conditions, spectra close to 1/f, and stable attractor geometry across sessions. In Experiment 2, we showed that the size of the inter-stimulus interval (ISI) determined the number of subjects with low-dimensional chaotic series. A small ISI caused 100% of subjects to respond in the chaotic regime, whereas only 25% had a low-dimensional chaotic RT component when the ISI was large. We argue that demanding task requirements cause a reduction in the dimensionality of the dynamics, producing RT fluctuations that may reflect a response strategy for controlling RT.

Adult↗

PubMedDate not supplied

Precision of methods for calculating identity-by-descent matrices using multiple markers.

A rapid, deterministic method (DET) based on a recursive algorithm and a stochastic method based on Markov Chain Monte Carlo (MCMC) for calculating identity-by-descent (IBD) matrices conditional on multiple markers were compared using stochastic simulation. Precision was measured by the mean squared error (MSE) of the relationship coefficients in predicting the true IBD relationships, relative to MSE obtained from using pedigree only. Comparisons were made when varying marker density, allele numbers, allele frequencies, and the size of full-sib families. The precision of DET was 75-99% relative to MCMC, but was not simply related to the informativeness of individual loci. For situations mimicking microsatellite markers or dense SNP, the precision of DET was > or = 95% relative to MCMC. Relative precision declined for the SNP, but not microsatellites as marker density decreased. Full-sib family size did not affect the precision. The methods were tested in interval mapping and marker assisted selection, and the performance was very largely determined by the MSE. A multi-locus information index considering the type, number, and position of markers was developed to assess precision. It showed a marked empirical relationship with the observed precision for DET and MCMC and explained the complex relationship between relative precision and the informativeness of individual loci.

Algorithms↗

PubMed2001

Estimating and improving the signal-to-noise ratio of time series by symbolic dynamics.

We investigate the effect of symbolic encoding applied to times series consisting of some deterministic signal and additive noise, as well as time series given by a deterministic signal with randomly distributed initial conditions as a model of event-related brain potentials. We introduce an estimator of the signal-to-noise ratio (SNR) of the system by means of time averages of running complexity measures such as Shannon and Rényi entropies, and prove its asymptotical equivalence with the linear SNR in the case of Shannon entropies of symbol distributions. A SNR improvement factor is defined, exhibiting a maximum for intermediate values of noise amplitude in analogy to stochastic resonance phenomena. We demonstrate that the maximum of the SNR improvement factor can be shifted toward smaller noise amplitudes by using higher order Rényi entropies instead of the Shannon entropy. For a further improvement of the SNR, a half wave encoding of noisy time series is introduced. Finally, we discuss the effect of noisy phases on the linear SNR as well as on the SNR defined by symbolic dynamics. It is shown that longer symbol sequences yield an improvement of the latter.

Journal Article↗

PubMed2006

Spatial survival probability for one-dimensional fluctuating interfaces in the steady state.

We report numerical and analytic results for the spatial survival probability for fluctuating one-dimensional interfaces with Edwards-Wilkinson or Kardar-Parisi-Zhang dynamics in the steady state. Our numerical results are obtained from analysis of steady-state profiles generated by integrating a spatially discretized form of the Edwards-Wilkinson equation to long times. We show that the survival probability exhibits scaling behavior in its dependence on the system size and the "sampling interval" used in the measurement for both "steady-state" and "finite" initial conditions. Analytic results for the scaling functions are obtained from a path-integral treatment of a formulation of the problem in terms of one-dimensional Brownian motion. A "deterministic approximation" is used to obtain closed-form expressions for survival probabilities from the formally exact analytic treatment. The resulting approximate analytic results provide a fairly good description of the numerical data.

Journal Article↗

PubMed2000

Correlation of patient skin doses in cardiac interventional radiology with dose-area product.

The use of X-rays in cardiac interventional radiology has the potential to induce deterministic radiation effects on the patient's skin. Guidelines published by official organizations encourage the recording of information to evaluate this risk, and the use of reference values in terms of the dose-area product (DAP). Skin dose measurements were made with thermoluminescent dosemeters placed at eight different locations on the body. In addition, DAP was recorded in 100 patients for four types of interventional radiology procedures. Mean, median and third quartile for these results are presented. Maximum skin dose values found were 412 mGy, 725 mGy, 760 mGy and 1800 mGy for coronary catheterization, coronary catheterization with left ventricle investigation, and percutaneous transluminal angiography without and with stenting, respectively. Median DAPs for these same procedures were, respectively, 5682 cGy cm2, 10,632 cGy cm2, 10,880 cGy cm2 and 13,161 cGy cm2. The relationship between DAP and skin dose was investigated. We found a poor correlation of DAP with maximum skin dose (r = 0.77) and skin dose indicator (r = 0.78). Using conversion factors derived from Monte Carlo simulations, skin dose distributions were calculated based on the measured DAPs. Agreement between the calculated skin dose distribution, using DAP values averaged over a group of patients who underwent coronary catheterization and left ventricle investigation, and the measured skin dose averaged over the same group of patients was very good. However, there were large differences between the calculated skin doses using the individual DAP data per patient and measured skin doses for individual patients (r = 0.66). Hence, calculation of individual skin doses based on the specific DAP data per patient is not reliable and therefore measuring skin dose is preferable.

Cardiac Catheterization↗

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↗

PubMed2004

Model-based assignment and inference of protein backbone Nuclear Magnetic Resonances.

Nuclear Magnetic Resonance (NMR) spectroscopy is a key experimental technique used to study protein structure, dynamics, and interactions. NMR methods face the bottleneck of spectral analysis, in particular determining the resonance assignments, which help define the mapping between atoms in the protein and peaks in the spectra. A substantial amount of noise in spectral data, along with ambiguities in interpretation, make this analysis a daunting task, and there exists no generally accepted measure of uncertainty associated with the resulting solutions. This paper develops a model-based inference approach that addresses the problem of characterizing uncertainty in backbone resonance assignment. We argue that NMR spectra are subject to random variation, and ignoring this stochasticity can lead to false optimism and erroneous conclusions. We propose a Bayesian statistical model that accounts for various sources of uncertainty and provides an automatable framework for inference. While assignment has previously been viewed as a deterministic optimization problem, we demonstrate the importance of considering all solutions consistent with the data, and develop an algorithm to search this space within our statistical framework. Our approach is able to characterize the uncertainty associated with backbone resonance assignment in several ways: 1) it quantifies of uncertainty in the individually assigned resonances in terms of their posterior standard deviations; 2) it assesses the information content in the data with a posterior distribution of plausible assignments; and 3) it provides a measure of the overall plausibility of assignments. We demonstrate the value of our approach in a study of experimental data from two proteins, Human Ubiquitin and Cold-shock protein A from E. coli. In addition, we provide simulations showing the impact of experimental conditions on uncertainty in the assignments.

Journal Article↗

PubMed1991

Velocity field studies at surgically imposed arterial stenoses on the abdominal aorta in pigs.

In order to describe velocity profiles and the size of deterministic and non-deterministic velocity disturbances at arterial stenoses, symmetrical and asymmetrical stenoses with intended area reductions of 50% ('moderate') and 85% ('severe') were applied on the abdominal aorta in six pigs. Blood velocities were registered by hot-film anemometry in 21 measuring points distributed across the vessel cross-sectional area in one pre-stenotic and three post-stenotic positions. Signal analysis included ensemble averaging, the high-pass filtering technique, and three-dimensional visualization. None of the stenoses affected the pre-stenotic velocity field. Downstream moderate stenoses flow separation and vortex formation were present. Moderate asymmetric stenoses induced turbulence in the post-stenotic velocity field. Immediately downstream of severe stenoses a prominent post-stenotic jet was present. Farther downstream, a multitude of coherent vortices and turbulence dominated the flow field. The transverse distribution of turbulence intensity paralleled with the peak systolic velocity profile, whereas transverse profiles of the relative turbulence intensity (turbulence intensity/mean velocity) revealed peak values in flow field locations with high velocity gradients. Velocity parameters for symmetric and asymmetric severe stenoses were highly comparable. However, the exact degree of stenosis was significantly higher for symmetrical (85%) than for asymmetrical (76%) stenoses. Therefore, recalling that stenosis severity strongly influences the development of velocity disturbances, this indicates that asymmetry of a stenosis is a predictor for blood velocity disturbances.

Animals↗

PubMedDate not supplied

[A possible scenario of pandemic influenza in Italy].

An influenza pandemic is expected to occur and will require timely countermeasures. Based on analysis of past influenza epidemics, a deterministic model was developed to estimate the expected number of cases (over 12 million), medical consultations (over 5 million), hospital admissions (over 220,000) and deaths (over 43,000) in the absence of public health interventions. The adoption of available measures would reduce the number of cases by about 22%, hospitalizations by 20%, and deaths by 28%.

Adolescent↗

PubMed2006

Avian GIS models signal human risk for West Nile virus in Mississippi.

BACKGROUND: West Nile virus (WNV) poses a significant health risk for residents of Mississippi. Physicians and state health officials are interested in new and efficient methods for monitoring disease spread and predicting future outbreaks. Geographic Information Systems (GIS) models have the potential to support these efforts. Environmental conditions favorable for mosquito habitat were modeled using GIS to derive WNV risk maps for Mississippi. Variables important to WNV dissemination were selected and classified as static and dynamic. The static variables included road density, stream density, slope, and vegetation. The dynamic variable represented seasonal water budget and was calculated using precipitation and evaporation estimates. Significance tests provided deterministic evidence of variable importance to the models. RESULTS: Several models were developed to estimate WNV risk including a landscape-base model and seasonal climatic sub-models. P-values from t-tests guided variable importance ranking. Variables were ranked and weights assigned as follows: road density (0.4), stream density (0.3), slope (0.2) and vegetation (0.1). This landscape-base model was modified by climatic conditions to assess the importance of climate to WNV risk. Human case data at the zip code level were used to validate modeling results. All models were summarized by zip codes for interpretation and model validation. For all models, estimated risk was higher for zip codes with at least one human case than for zip codes where no human cases were recorded. Overall median measure of risk by zip code indicated that 67% of human cases occurred in the high-risk category. CONCLUSION: Modeling results indicated that dead bird occurrences are correlated with human WNV risk and can facilitate the assessment of environmental variables that contribute to that risk. Each variable's importance in GIS-based risk predictions was assigned deterministically. Our models indicated non-uniform distribution of risk across the state and showed elevated risk in urban and as well as rural areas. Model limitations include resolution of human data, zip code aggregation issues, and quality/availability of vegetation and stream density layers. Our approach verified that WNV risk can be modeled at the state level and can be modified for risk predictions of other vector-borne diseases in varied ecological regions.

Animals↗

PubMed2007

Attitudes, order and quantity: deterministic and direct probabilistic tests of unidimensional unfolding.

This article is the final in the series on unidimensional unfolding. The investigations of Kyngdon (2006b) and Michell (1994) were extended to include direct probabilistic tests of the quantitative and ordinal components of unfolding theory with the multinomial Dirichlet model (Karabatsos 2005); and tests of the higher order axiomatic conjoint measurement (ACM, Krantz, Luce, Suppes and Tversky (KLST) 1971) condition of triple cancellation. Strong Dirichlet model support for both the ordinal and quantitative components of unfolding was only found in datasets that satisfied at least double cancellation. In contrast, the Item Response Theory (IRT) simple hyperbolic cosine model for pairwise preferences (SHCMpp, Andrich 1995) fitted all datasets. The paper concluded the SHCMpp is suited to the instrumental rather than scientific task (Michell 2000) of psychological measurement; with the caveat of the problematic chi square fit statistic. The paper also presents original work by the second author on coherent tests of triple cancellation.

Attitude↗

PubMed2005

Spatiotemporal dynamics in marginal populations.

Population dynamics across a mortality gradient at an ecological margin are investigated using a novel modeling approach that allows direct comparison of stochastic spatially explicit simulation results with deterministic mean field models. The results show that demographic stochasticity has a large effect at population margins such that density profiles fall off more sharply than predicted by mean field models. Substantial spatial structure emerges at the margin, and spatial correlations (measured parallel to the margin) exhibit a sharp maximum in the tail of the density profile, indicating that spatial substructuring is greatest at an intermediate point across the ecological gradient. Such substructuring may have a substantial impact on Allee effects and evolutionary processes in marginal populations.

Animals↗