533 research outputs found

    On the hierarchical Bayesian modelling of frequency response functions

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    Structural health monitoring (SHM) strategies seek to evaluate, predict, and maintain structural integrity, to improve the safety and design service life of structures in operation. Many of these strategies involve monitoring changes in structural dynamics, as damage can affect modal properties and present as changes in the characteristics of the resonance peaks of the frequency response function (FRF). While recent advances have improved the safety and reliability of structures, a number of challenges remain, impeding the practical implementation and generalisation of these systems. Like damage, benign variations, such as those caused by changes in temperature or other environmental fluctuations, can affect dynamic properties, making it difficult to distinguish between damage and normal operating conditions. In addition, newly-deployed structures can have insufficient data to describe the normal operating conditions (i.e., data scarcity), which can impair the development of data-based prediction models. Another common challenge is data loss (i.e., data sparsity), which may result from transmission issues, sensor failure, a sample-rate mismatch between sensors, and other causes. Missing data in the time domain will result in decreased resolution in the frequency domain, which can impair dynamic characterisation. For situations that may benefit from information sharing among datasets, e.g., population-based SHM of similar structures, the hierarchical Bayesian approach provides a useful modelling structure. Hierarchical Bayesian models learn statistical distributions at the population (or parent) and the domain levels simultaneously, to bolster statistical strength among the parameters. As a result, variance is reduced among the parameter estimates, particularly when data are limited. In this paper, a combined probabilistic FRF model is developed for a small population of nominally-identical helicopter blades, using a hierarchical Bayesian structure, to support information transfer in the context of sparse data. The modelling approach is also demonstrated in a traditional SHM context, for a single helicopter blade exposed to varying temperatures, to show how the inclusion of physics-based knowledge can improve generalisation beyond the training data, in the context of scarce data. These models address critical challenges in SHM, by accommodating benign variations that present as differences in the underlying dynamics, while also considering (and utilising), the similarities among the domains

    Modelling variability in vibration-based PBSHM via a generalised population form

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    Structural health monitoring (SHM) has been an active research area for the last three decades, and has accumulated a number of critical advances over that period, as can be seen in the literature. However, SHM is still facing challenges because of the paucity of damage-state data, operational and environmental fluctuations, repeatability issues, and changes in boundary conditions. These issues present as inconsistencies in the captured features and can have a huge impact on the practical implementation, but more critically, on the generalisation of the technology. Population-based SHM has been designed to address some of these concerns by modelling and transferring missing information using data collected from groups of similar structures. In this work, vibration data were collected from four healthy, nominally-identical, full-scale composite helicopter blades. Manufacturing differences (e.g., slight differences in geometry and/or material properties), among the blades presented as variability in their structural dynamics, which can be very problematic for SHM based on machine learning from vibration data. This work aims to address this variability by defining a general model for the frequency response functions of the blades, called a form, using mixtures of Gaussian processes

    Running Backwards: Consequences of Current HIV Incidence Rates for the Next Generation of Black MSM in the United States

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    Black men who have sex with men (MSM) in the United States are disproportionately impacted by HIV. To better understand this public health problem, we reviewed the literature to calculate an estimate of HIV incidence among Black MSM. We used this rate to model HIV prevalence over time within a simulated cohort, which we subsequently compared to prevalence from community-based samples. We searched all databases accessible through PubMed, and Conference on Retroviruses and Opportunistic Infections abstracts for HIV incidence estimates among Black MSM. Summary HIV incidence rates and 95 % confidence intervals (CIs) were calculated using random effects models. Using the average incidence rate, we modeled HIV prevalence within a simulated cohort of Black MSM (who were all HIV-negative at the start) from ages 18 through 40. Based on five incidence rates totaling 2898 Black MSM, the weighted mean incidence was 4.16 % per year (95 % CI 2.76–5.56). Using this annual incidence rate, our model predicted that 39.94 % of Black MSM within the simulated cohort would be HIV-positive by age 30, and 60.73 % by 40. Projections were similar to HIV prevalence found in community-based samples of Black MSM. High HIV prevalence will persist across the life-course among Black MSM, unless effective prevention and treatment efforts are increased to substantially reduce HIV transmission among this underserved and marginalized population

    Towards quality adolescent-friendly services in TB care

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    The Value of Information for Populations in Varying Environments

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    The notion of information pervades informal descriptions of biological systems, but formal treatments face the problem of defining a quantitative measure of information rooted in a concept of fitness, which is itself an elusive notion. Here, we present a model of population dynamics where this problem is amenable to a mathematical analysis. In the limit where any information about future environmental variations is common to the members of the population, our model is equivalent to known models of financial investment. In this case, the population can be interpreted as a portfolio of financial assets and previous analyses have shown that a key quantity of Shannon's communication theory, the mutual information, sets a fundamental limit on the value of information. We show that this bound can be violated when accounting for features that are irrelevant in finance but inherent to biological systems, such as the stochasticity present at the individual level. This leads us to generalize the measures of uncertainty and information usually encountered in information theory

    Is symmetry identity?

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    Wigner found unreasonable the "effectiveness of mathematics in the natural sciences". But if the mathematics we use to describe nature is simply a coded expression of our experience then its effectiveness is quite reasonable. Its effectiveness is built into its design. We consider group theory, the logic of symmetry. We examine the premise that symmetry is identity; that group theory encodes our experience of identification. To decide whether group theory describes the world in such an elemental way we catalogue the detailed correspondence between elements of the physical world and elements of the formalism. Providing an unequivocal match between concept and mathematical statement completes the case. It makes effectiveness appear reasonable. The case that symmetry is identity is a strong one but it is not complete. The further validation required suggests that unexpected entities might be describable by the irreducible representations of group theory

    Circadian rhythm of urinary pH in man with and without chronic antacid administration

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    In normal human volunteers, when urinary pH was plotted versus time, the circadian sine-wave type curve was not altered by chronic administration of a commercially available suspension containing a mixture of magnesium and aluminum hydroxides, although the antacid perturbed the entire curve in a more alkaline direction. A single dose of the antacid had little effect on urinary pH. There was a highly significant linear relationship between the change in hydrogen ion concentration during chronic antacid treatment and the initial control urinary hydrogen ion concentration, but there was no significant correlation between change in urinary pH and initial control urinary pH as has been previously reported. The above results were based on the evaluation of the hydrogen ion concentrations of 1562 separate urine samples collected from 24 normal subjects in a three treatment crossover study. It is recommended that: (1) research studies involving drug-drug interactions with antacids be designed to consider the effect of the antacid on the circadian rhythm of urinary pH, and (2) pH values not be averaged as commonly reported in the literature, but rather the pH values be converted to hydrogen ion concentrations before statistical analysis.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46636/1/228_2004_Article_BF00561060.pd
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