An inverse problem analysis for the determination of probalistic parameters of concrete behavior modeled by a statistical approach

1999 ◽  
Vol 32 (1) ◽  
pp. 9-13 ◽  
Author(s):  
E. M. R. Fairbairn ◽  
Q. M. Guedes ◽  
F. -J. Ulm
Keyword(s):  
Inverse Problem ◽  
Statistical Approach ◽  
Problem Analysis

Measurement of Cryoprotectant Concentration Using MRI in Pseudobiological Tissues and Determination of Diffusivity Based on Inverse Problem Analysis

2002 ◽  
Author(s):  
Hiroshi Ishiguro ◽  
Takanori Kai ◽  
Kuniyasu Ogawa
Keyword(s):  
Inverse Problem ◽  
Relaxation Times ◽  
Problem Analysis ◽  
Resonance Imaging ◽  
Volumetric Fraction ◽  
One Dimensional ◽  
Agar Concentration ◽  
Dimensional Distribution ◽  
Magnetic Resonance Imaging Mri

Transient one-dimensional distribution of cryoprotectant concentration in pseudobiological tissues (agar) was measured noninvasively using magnetic resonance imaging (MRI). Cryoprotectants were dimethyl sulfoxide (DMSO) and glycerol, common cryoprotectants penetrating cells. Attenuation of MRI image intensity due to volumetric fraction of solution and relaxation times was also investigated. Apparent diffusivity of each cryoprotectant as a function of agar concentration was determined from the inverse problem analysis. The diffusivity decreased with an increase in agar concentration. This method was also applied to the liver tissues of chicken.

Uncertainty estimation for linearised inverse problems comparing Bayesian inference and a pseudoinverse approach for acoustic transmission measurements

2017 ◽  
Vol 84 (4) ◽  
Author(s):  
Nadine Feldmann ◽  
Fabian Bause ◽  
Bernd Henning
Keyword(s):  
Inverse Problem ◽  
Bayesian Inference ◽  
Statistical Approach ◽  
Uncertainty Estimation ◽  
Acoustic Transmission ◽  
Model Function ◽  
Sources Of Uncertainty ◽  
Material Parameters ◽  
Transmission Measurements

AbstractThe determination of acoustic material parameters using ultrasonic transmission measurements can mathematically be described as an inverse problem. The question concerning the influence of uncertainties on the problem's solution can be answered using a statistical approach. Therefore, the sources of uncertainty have to be identified statistically. A method for linearising the model function using the

Determination of the Number of Conserved Chromosomal Segments Between Species

Genetics ◽  
2001 ◽  
Vol 157 (3) ◽  
pp. 1387-1395 ◽  
Author(s):  
Sudhir Kumar ◽  
Sudhindra R Gadagkar ◽  
Alan Filipski ◽  
Xun Gu
Keyword(s):  
Statistical Approach ◽  
Common Ancestor ◽  
Chromosomal Rearrangements ◽  
Structural Similarity ◽  
The Other ◽  
Segment Length ◽  
Human Genomes ◽  
Genomic Divergence ◽  
Human And Mouse

AbstractGenomic divergence between species can be quantified in terms of the number of chromosomal rearrangements that have occurred in the respective genomes following their divergence from a common ancestor. These rearrangements disrupt the structural similarity between genomes, with each rearrangement producing additional, albeit shorter, conserved segments. Here we propose a simple statistical approach on the basis of the distribution of the number of markers in contiguous sets of autosomal markers (CSAMs) to estimate the number of conserved segments. CSAM identification requires information on the relative locations of orthologous markers in one genome and only the chromosome number on which each marker resides in the other genome. We propose a simple mathematical model that can account for the effect of the nonuniformity of the breakpoints and markers on the observed distribution of the number of markers in different conserved segments. Computer simulations show that the number of CSAMs increases linearly with the number of chromosomal rearrangements under a variety of conditions. Using the CSAM approach, the estimate of the number of conserved segments between human and mouse genomes is 529 ± 84, with a mean conserved segment length of 2.8 cM. This length is <40% of that currently accepted for human and mouse genomes. This means that the mouse and human genomes have diverged at a rate of ∼1.15 rearrangements per million years. By contrast, mouse and rat are diverging at a rate of only ∼0.74 rearrangements per million years.

Determination of an impulsive diffusion operator from interior spectral data

Analysis ◽  
2020 ◽  
Vol 40 (1) ◽  
pp. 39-45
Author(s):  
Yasser Khalili ◽  
Dumitru Baleanu
Keyword(s):  
Inverse Problem ◽  
Spectral Data ◽  
Potential Functions ◽  
Half Line ◽  
Internal Point ◽  
Diffusion Operator ◽  
Impulsive Diffusion

AbstractIn the present work, the interior spectral data is used to investigate the inverse problem for a diffusion operator with an impulse on the half line. We show that the potential functions {q_{0}(x)} and {q_{1}(x)} can be uniquely established by taking a set of values of the eigenfunctions at some internal point and one spectrum.

Proteometabolomic characterization of apical bud maturation in Pinus pinaster

2020 ◽  
Author(s):  
Luis Valledor ◽  
Sara Guerrero ◽  
Lara García-Campa ◽  
Mónica Meijón
Keyword(s):  
Pinus Pinaster ◽  
Ribosomal Proteins ◽  
Potential Role ◽  
Statistical Approach ◽  
Wood Quality ◽  
Growth Patterns ◽  
Future Scenario ◽  
Apical Bud

Abstract Bud maturation is a physiological process which implies a set of morphophysiological changes which lead to the transition of growth patterns from young to mature. This transition defines tree growth and architecture, and in consequence traits such as biomass production and wood quality. In Pinus pinaster, a conifer of great timber value, bud maturation is closely related to polycyclism (multiple growth periods per year). This process causes a lack of apical dominance, and consequently increased branching that reduces its timber quality and value. However, despite its importance, little is known about bud maturation. In this work, proteomics and metabolomics were employed to study apical and basal sections of young and mature buds in P. pinaster. Proteins and metabolites in samples were described and quantified using (n)UPLC-LTQ-Orbitrap. The datasets were analyzed employing an integrative statistical approach, which allowed the determination of the interactions between proteins and metabolites and the different bud sections and ages. Specific dynamics of proteins and metabolites such as HISTONE H3 and H4, RIBOSOMAL PROTEINS L15 and L12, CHAPERONIN TCP1, 14–3-3 protein gamma, gibberellins A1, A3, A8, strigolactones and ABA, involved in epigenetic regulation, proteome remodeling, hormonal signaling and abiotic stress pathways showed their potential role during bud maturation. Candidates and pathways were validated employing interaction databases and targeted transcriptomics. These results increase our understanding of the molecular processes behind bud maturation a key step towards improving timber production and natural pine forests management in a future scenario of climate change. However, further studies are necessary by using different P. pinaster populations that show contrasting wood quality and stress tolerance in order to generalize the results.

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