12,604 research outputs found
Recoiling DNA Molecule: Simulation & Experiment
Single molecule DNA experiments often generate data from force versus
extension measurements involving the tethering of a microsphere to one end of a
single DNA molecule while the other is attached to a substrate. We show that
the persistence length of single DNA molecules can also be measured based on
the recoil dynamics of these DNA-microsphere complexes if appropriate
corrections are made to the friction coefficient of the microsphere in the
vicinity of the substrate. Comparison between computer simulated recoil curves,
generated from the corresponding Langevin equation, and experimental recoils is
used to assure the validity of data analysis.Comment: 14 pages (single column preprint), 7 figures. Major changes: data
analysis method improved; dna-ethidium bromide results removed (dna-ethidium
bromide protocol affected microspheres and coverglass behavior
Gravitational waves from pulsars with measured braking index
We study the putative emission of gravitational waves (GWs) in particular for
pulsars with measured braking index. We show that the appropriate combination
of both GW emission and magnetic dipole brakes can naturally explain the
measured braking index, when the surface magnetic field and the angle between
the magnetic dipole and rotation axes are time dependent. Then we discuss the
detectability of these very pulsars by aLIGO and the Einstein Telescope. We
call attention to the realistic possibility that aLIGO can detect the GWs
generated by at least some of these pulsars, such as Vela, for example.Comment: 6 pages and 4 figure
Transthyretin familial amyloid polyneuropathy impact on health-related quality of life
info:eu-repo/semantics/publishedVersio
Comparative analysis of a transient heat flow and thermal stresses by analytical and numerical methods
The study of heat flow problems is of extreme importance in engineering, there is a need to know the temperatures imposed and generated, when appropriate, in the structural parts to be able to evaluate the stresses that can arise due to the thermal variations. These stresses arise due to imposed constraints, ie bodies can not move freely and consequently undesirable cracks may arise when the stresses are greater than the resistive capacity of the stressed parts. The analysis of these problems can be done in both analytical or numerical way, with the use of calculation methods, such as the Finite Difference Method (FDM) and the Finite Element Method (FEM), with aid of computational programs such as MATLAB, PYTHON and ANSYS, as used in this work. The results presented here show simple cases of transient thermal variation and thermomechanical coupling by two methods of analysis, aiming at the validation of the numerical methods and softwares used. The solutions were satisfactory, the temperatures and stresses were coincident for different methods, making possible to start studying more complex problems with confidence in the implemented code
Double Diffusion Encoding Prevents Degeneracy in Parameter Estimation of Biophysical Models in Diffusion MRI
Purpose: Biophysical tissue models are increasingly used in the
interpretation of diffusion MRI (dMRI) data, with the potential to provide
specific biomarkers of brain microstructural changes. However, the general
Standard Model has recently shown that model parameter estimation from dMRI
data is ill-posed unless very strong magnetic gradients are used. We analyse
this issue for the Neurite Orientation Dispersion and Density Imaging with
Diffusivity Assessment (NODDIDA) model and demonstrate that its extension from
Single Diffusion Encoding (SDE) to Double Diffusion Encoding (DDE) solves the
ill-posedness and increases the accuracy of the parameter estimation. Methods:
We analyse theoretically the cumulant expansion up to fourth order in b of SDE
and DDE signals. Additionally, we perform in silico experiments to compare SDE
and DDE capabilities under similar noise conditions. Results: We prove
analytically that DDE provides invariant information non-accessible from SDE,
which makes the NODDIDA parameter estimation injective. The in silico
experiments show that DDE reduces the bias and mean square error of the
estimation along the whole feasible region of 5D model parameter space.
Conclusions: DDE adds additional information for estimating the model
parameters, unexplored by SDE, which is enough to solve the degeneracy in the
NODDIDA model parameter estimation.Comment: 22 pages, 7 figure
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