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