Method for the analysis of temporal change

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  • The design of computer-based instrumentation and control (I&C) systems is determined by the allocation of I&C functions to I&C systems and components. Due to the characteristics of computer-based technology, component failures can negatively affect several I&C functions, so that the reliability proof of the I&C systems requires the accomplishment of I&C system design analyses throughout the I&C life-cycle.

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  • A Gaussian mixture model (GMM)-based classification technique is employed for a quantitative global assessment of brain tissue changes by using pixel intensities and contrast generated by b-values in diffusion tensor imaging (DTI). A hemisphere approach is also proposed. A GMM identifies the variability in the main brain tissues at a macroscopic scale rather than searching for tumours or affected areas. The asymmetries of the mixture distributions between the hemispheres could be used as a sensitive, faster tool for early diagnosis.

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  • To provide a comprehensive overview of temporal trends in cancer incidence during 1973–2010 in urban Shanghai. Methods: The estimated annual percent changes (EAPCs) for the whole period and for the time segments in age-standardized incidence rates (ASR) were evaluated with Joinpoint analysis. Age-period-cohort (APC) models were modeled to examine the effects of age, period and birth cohort on cancer incidence.

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  • Biological systems and processes are highly dynamic. To gain insights into their functioning time-resolved measurements are necessary. Time-resolved gene expression data captures temporal behaviour of the genes genome-wide under various biological conditions: in response to stimuli, during cell cycle, differentiation or developmental programs.

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