Dataset Information

Fatigue Assessment Strategy Using Bayesian Techniques.

ABSTRACT: Different empirical models have been proposed in the literature to determine the fatigue strength as a function of lifetime, according to linear, parabolic, hyperbolic, exponential, and other shaped solutions. However, most of them imply a deterministic definition of the S-N field, despite the inherent scatter exhibited by the fatigue results issuing from experimental campaigns. In this work, the Bayesian theory is presented as a suitable way not only to convert deterministic into probabilistic models, but to enhance probabilistic fatigue models with the statistical distribution of the percentile curves of failure probability interpreted as their confidence bands. After a short introduction about the application of the Bayesian methodology, its advantageous implementation on an OpenSource software named OpenBUGS is presented. As a practical example, this methodology has been applied to the statistical analysis of the Maennig fatigue S-N field data using the Weibull regression model proposed by Castillo and Canteli, which allows the confidence bands of the S-N field to be determined as a function of the already available test results. Finally, a question of general interest is discussed as that concerned to the recommendable number of tests to carry out in an experimental S-N fatigue program for achieving "reliable or confident" results to be subsequently used in component design, which, generally, is not adequately and practically addressed by researchers.

SUBMITTER: Castillo E

PROVIDER: S-EPMC6804179 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Fatigue Assessment Strategy Using Bayesian Techniques.

Castillo Enrique E Muniz-Calvente Miguel M Fernández-Canteli Alfonso A Blasón Sergio S

Materials (Basel, Switzerland) 20191003 19

Different empirical models have been proposed in the literature to determine the fatigue strength as a function of lifetime, according to linear, parabolic, hyperbolic, exponential, and other shaped solutions. However, most of them imply a deterministic definition of the S-N field, despite the inherent scatter exhibited by the fatigue results issuing from experimental campaigns. In this work, the Bayesian theory is presented as a suitable way not only to convert deterministic into probabilistic ...[more]

PMID: 31623343

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Project description:BACKGROUND:Myalgic encephalomyelitis/ Chronic Fatigue Syndrome (ME/CFS) is a multi-system illness characterised by a diverse range of debilitating symptoms including autonomic and cognitive dysfunction. The pathomechanism remains elusive, however, neurological and cognitive aberrations are consistently described. This systematic review is the first to collect and appraise the literature related to the structural and functional neurological changes in ME/CFS patients as measured by neuroimaging techniques and to investigate how these changes may influence onset, symptom presentation and severity of the illness. METHODS:A systematic search of databases Pubmed, Embase, MEDLINE (via EBSCOhost) and Web of Science (via Clarivate Analytics) was performed for articles dating between December 1994 and August 2019. Included publications report on neurological differences in ME/CFS patients compared with healthy controls identified using neuroimaging techniques such as magnetic resonance imaging, positron emission tomography and electroencephalography. Article selection was further refined based on specific inclusion and exclusion criteria. A quality assessment of included publications was completed using the Joanna Briggs Institute checklist. RESULTS:A total of 55 studies were included in this review. All papers assessed neurological or cognitive differences in adult ME/CFS patients compared with healthy controls using neuroimaging techniques. The outcomes from the articles include changes in gray and white matter volumes, cerebral blood flow, brain structure, sleep, EEG activity, functional connectivity and cognitive function. Secondary measures including symptom severity were also reported in most studies. CONCLUSIONS:The results suggest widespread disruption of the autonomic nervous system network including morphological changes, white matter abnormalities and aberrations in functional connectivity. However, these findings are not consistent across studies and the origins of these anomalies remain unknown. Future studies are required confirm the potential neurological contribution to the pathology of ME/CFS.

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Project description:BackgroundThe mainstay of assessment of the fetal lungs in clinical practice is via evaluation of pulmonary size, primarily using 2D ultrasound and more recently with anatomical magnetic resonance imaging. The emergence of advanced magnetic resonance techniques such as T2* relaxometry in combination with the latest motion correction post-processing tools now facilitates assessment of the metabolic activity or perfusion of fetal pulmonary tissue in vivo.ObjectiveThis study aimed to characterize normal pulmonary development using T2* relaxometry, accounting for fetal motion across gestation.MethodsDatasets from women with uncomplicated pregnancies that delivered at term, were analyzed. All subjects had undergone T2-weighted imaging and T2* relaxometry on a Phillips 3T magnetic resonance imaging system antenatally. T2* relaxometry of the fetal thorax was performed using a gradient echo single-shot echo planar imaging sequence. Following correction for fetal motion using slice-to-volume reconstruction, T2* maps were generated using in-house pipelines. Lungs were manually segmented and mean T2* values calculated for the right and left lungs individually, and for both lungs combined. Lung volumes were generated from the segmented images, and the right and left lungs, as well as both lungs combined were assessed.ResultsEighty-seven datasets were suitable for analysis. The mean gestation at scan was 29.9±4.3 weeks (range: 20.6-38.3) and mean gestation at delivery was 40±1.2 weeks (range: 37.1-42.4). Mean T2* values of the lungs increased over gestation for right and left lungs individually and for both lungs assessed together (P=.003; P=.04; P=.003, respectively). Right, left, and total lung volumes were also strongly correlated with increasing gestational age (P<.001 in all cases).ConclusionThis large study assessed developing lungs using T2* imaging across a wide gestational age range. Mean T2* values increased with gestational age, which may reflect increasing perfusion and metabolic requirements and alterations in tissue composition as gestation advances. In the future, evaluation of findings in fetuses with conditions known to be associated with pulmonary morbidity may lead to enhanced prognostication antenatally, consequently improving counseling and perinatal care planning.

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Fatigue Assessment Strategy Using Bayesian Techniques.

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Fatigue Assessment Strategy Using Bayesian Techniques.

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