Hybrid stars within the framework of the Sigma-Omega-Rho model combined with the MIT and NJL models

In this paper, we investigate the structure of hybrid stars consisting of hadrons (neutrons, protons, sigmas, lambdas), leptons (electrons, muons), and quarks (up, down, strange). We use a relativistic mean-field (RMF) model namely the Sigma-omega-rho model for the hadronic phase and the MIT bag model as well as the NJL model for the quark phase. In addition, Maxwell and Gibbs conditions are employed to investigate the hadron-Quark phase transition. Finally, by obtaining the mass-radius relation, $M (M_{sun}) \leqslant 2.07$ is predicted for such hybrid stars.Comment: 23 pages, 10 figure

Correlations in Nuclear Matter

We analyze the nuclear matter correlation properties in terms of the pair correlation function. To this aim we systematically compare the results for the variational method in the Lowest Order Constrained Variational (LOCV) approximation and for the Bruekner-Hartree-Fock (BHF) scheme. A formal link between the Jastrow correlation factor of LOCV and the Defect Function (DF) of BHF is established and it is shown under which conditions and approximations the two approaches are equivalent. From the numerical comparison it turns out that the two correlation functions are quite close, which indicates in particular that the DF is approximately local and momentum independent. The Equations of State (EOS) of Nuclear Matter in the two approaches are also compared. It is found that once the three-body forces (TBF) are introduced the two EOS are fairly close, while the agreement between the correlation functions holds with or without TBF.Comment: 11 figure

First-order phase transition from hypernuclear matter to deconfined quark matter obeying new constraints from compact star observations

We reconsider the problem of the hyperon puzzle and its suggested solution by quark deconfinement within the two-phase approach to hybrid compact stars with recently obtained hadronic and quark matter equations of state. For the hadronic phase we employ the hypernuclear equation of state from the lowest order constrained variational method and the quark matter phase is described by a sufficiently stiff equation of state based on a color superconducting nonlocal Nambu-Jona-Lasinio model with constant (model nlNJLA) and with density-dependent (model nlNJLB) parameters. We study the model dependence of the phase transition obtained by a Maxwell construction. Our study confirms that also with the present set of equations of state quark deconfinement presents a viable solution of the hyperon puzzle even for the new constraint on the lower limit of the maximum mass from PSR J0740+6620. In this work we provide with model nlNJLB for the first time a hybrid star EoS with an intermediate hypernuclear matter phase between the nuclear and color superconducting quark matter phases, for which the maximum mass of the compact star reaches $2.2~M_\odot$, in accordance with most recent constraints. In model nlNJLA such a phase cannot be realised because the phase transition onset is at low densities, before the hyperon threshold density is passed. We discuss possible consequences of the hybrid equation of state for the deconfinement phase transition in symmetric matter as it will be probed in future heavy-ion collisions at FAIR, NICA and corresponding energy scan programs at the CERN and RHIC facilities.Comment: 37 pages, 13 figures, 1 table, references added, text and figures revised, version accepted for publication in Phys. Rev.

Controlling surface statistical properties using bias voltage: Atomic force microscopy and stochastic analysis

The effect of bias voltages on the statistical properties of rough surfaces has been studied using atomic force microscopy technique and its stochastic analysis. We have characterized the complexity of the height fluctuation of a rough surface by the stochastic parameters such as roughness exponent, level crossing, and drift and diffusion coefficients as a function of the applied bias voltage. It is shown that these statistical as well as microstructural parameters can also explain the macroscopic property of a surface. Furthermore, the tip convolution effect on the stochastic parameters has been examined.Comment: 8 pages, 11 figures

LOCV calculation for Beta-stable matter at finite temperature

The method of lowest-order constrained variational, which predicts reasonably the nuclear matter semi-empirical data is used to calculate the equation of state of beta-stable matter at finite temperature. The Reid soft-core with and without the N-$\Delta$ interactions which fits the N-N scattering data as well as the $UV_{14}$ potential plus the three-nucleon interaction are considered in the nuclear many-body Hamiltonian. The electron and muon are treated relativistically in the total Hamiltonian at given temperature, to make the fluid electrically neutral and stable against beta decay. The calculation is performed for a wide range of baryon density and temperature which are of interest in the astrophysics. The free energy, entropy, proton abundance, etc. of nuclear beta-stable matter are calculated. It is shown that by increasing the temperature, the maximum proton abundance is pushed to the lower density while the maximum itself increases as we increase the temperature. The proton fraction is not enough to see any gas-liquid phase transition. Finally we get an overall agreement with other many-body techniques, which are available only at zero temperature.Comment: LaTex, 20 page

Bestrophin1: A Gene that Causes Many Diseases

Bestrophinopathies are a group of clinically distinct inherited retinal dystrophies that lead to the gradual loss of vision in and around the macular area. There are no treatments for patients suffering from bestrophinopathies, and no measures can be taken to prevent visual deterioration in those who have inherited disease-causing mutations. Bestrophinopathies are caused by mutations in the Bestrophin1 gene (BEST1), a protein found exclusively in the retinal pigment epithelial (RPE) cells of the eye. Mutations in BEST1 affect the function of the RPE leading to the death of overlying retinal cells and subsequent vision loss. The pathogenic mechanisms arising from BEST1 mutations are still not fully understood, and it is not clear how mutations in BEST1 lead to diseases with distinct clinical features. This chapter discusses BEST1, the use of model systems to investigate the effects of mutations and the potential to investigate individual bestrophinopathies using induced pluripotent stem cells

Comparison of two different physical activity monitors

<p>Abstract</p> <p>Background</p> <p>Understanding the relationships between physical activity (PA) and disease has become a major area of research interest. Activity monitors, devices that quantify free-living PA for prolonged periods of time (days or weeks), are increasingly being used to estimate PA. A range of different activity monitors brands are available for investigators to use, but little is known about how they respond to different levels of PA in the field, nor if data conversion between brands is possible.</p> <p>Methods</p> <p>56 women and men were fitted with two different activity monitors, the Actigraph™ (Actigraph LLC; AGR) and the Actical™ (Mini-Mitter Co.; MM) for 15 days. Both activity monitors were fixed to an elasticized belt worn over the hip, with the anterior and posterior position of the activity monitors randomized. Differences between activity monitors and the validity of brand inter-conversion were measured by <it>t</it>-tests, Pearson correlations, Bland-Altman plots, and coefficients of variation (CV).</p> <p>Results</p> <p>The AGR detected a significantly greater amount of daily PA (216.2 ± 106.2 vs. 188.0 ± 101.1 counts/min, P < 0.0001). The average difference between activity monitors expressed as a CV were 3.1 and 15.5% for log-transformed and raw data, respectively. When a conversion equation was applied to convert datasets from one brand to another, the differences were no longer significant, with CV's of 2.2 and 11.7%, log-transformed and raw data, respectively.</p> <p>Conclusion</p> <p>Although activity monitors predict PA on the same scale (counts/min), the results between these two brands are not directly comparable. However, the data are comparable if a conversion equation is applied, with better results for log-transformed data.</p