Heavy quark fragmentation functions at next-to-leading perturbative QCD

It is well-known that the dominant mechanism to produce hadronic bound states with large transverse momentum is fragmentation. This mechanism is described by the fragmentation functions (FFs) which are the universal and process-independent functions. Here, we review the perturbative FFs formalism as an appropriate tool for studying these hadronization processes and detail the extension of this formalism at next-to-leading order (NLO). Using the Suzuki's model, we calculate the perturbative QCD FF for a heavy quark to fragment into a S-wave heavy meson at NLO. As an example, we study the LO and NLO FFs for a charm quark to split into the S-wave $D$-meson and compare our analytic results both with experimental data and well-known phenomenological models

How Should Governments Address High Levels of Natural Radiation and Radon--Lessons from the Chernobyl Nuclear Accident and Ramsar, Iran

The authors discuss the high levels of natural background radiation in Ramsar, Iran, and offer data indicating that this has had little effect on the health of Ramsar\u27s inhabitants. The authors then examine the implications their research could have for public health policy

The effect of google drive distance and duration in residential property in Sydney, Australia

© 2016 by World Scientific Publishing Co. Pte. Ltd. Predicting the market value of a residential property accurately without inspection by professional valuer could be beneficial for vary of organization and people. Building an Automated Valuation Model could be beneficial if it will be accurate adequately. This paper examined 47 machine learning models (linear and non-linear). These models are fitted on 1967 records of units from 19 suburbs of Sydney, Australia. The main aim of this paper is to compare the performance of these techniques using this data set and investigate the effect of spatial information on valuation accuracy. The results demonstrated that tree models named eXtreme Gradient Boosting Linear, eXtreme Gradient Boosting Tree and Random Forest respectively have best performance among other techniques and spatial information such drive distance and duration to CBD increase the predictive model performance significantly

Thermal instability in ionized plasma

We study magnetothermal instability in the ionized plasmas including the effects of Ohmic, ambipolar and Hall diffusion. Magnetic field in the single fluid approximation does not allow transverse thermal condensations, however, non-ideal effects highly diminish the stabilizing role of the magnetic field in thermally unstable plasmas. Therefore, enhanced growth rate of thermal condensation modes in the presence of the diffusion mechanisms speed up the rate of structure formation.Comment: Accepted for publication in Astrophysics & Space Scienc

Parametric Modeling of the Brain Vascular System and its Application in Dynamic Contrast-Enhanced Imaging Studies.

Dynamic Contrast-Enhanced Imaging (DCE) is one of the main tools for in vivo measurement of vascular properties of pathologies such as brain tumors. In DCE imaging, one of the key components for estimation of vascular perfusion and permeability parameters using Pharmacokinetic models is the Arterial Input Function (AIF). To measure these parameters more accurately, there have been approaches for estimating the AIF profile at the capillary level; however, a practical and realistic estimate is still missing. As a solution, we have developed a model of the brain vascular system, based on laws of fluid dynamics and vascular morphology, to address dispersion and delay of the contrast agent (CA) concentration profile at different levels of the brain vascular tree. Using this model, we introduced a transfer function that can describe changes of the AIF profile along a vascular pathway, from a major artery to the capillary bed. Our simulations and also testing this model on DCE Imaging data of the human brain, all showed that our model can give a realistic estimation of the CA concentration profile, at all levels of the vascular tree in the brain. In the next step, we extended our model to address vascular leakage as well. Using this extended vascular (EV) model, we are able to decompose the tissue response signal in DCE images to its intravascular and extravascular components. This feature has provided us with an excellent tool that can lead to relatively unbiased measurements of perfusion and permeability parameters, especially in areas with vascular leakage. We tested this on DCE-CT and DCE-MR images and compared the performance of our model to conventional methods. Also, using a simulation study, we measured the levels of overestimation and underestimation of the permeability parameters using conventional processing methods and demonstrated the superior performance of the EV model for more accurate estimation of these parameters. Overall, the results show that the EV model can provide a platform for better understanding of the role of the AIF in DCE studies as well as estimation of AIF for more accurate measurement of perfusion and permeability parameters in clinical studies.PhDBiomedical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/107177/1/siamak_1.pd

Quark Confinement in Restricted SU(2) Gauge Theory

We apply Zwanziger formalism to Cho restricted $SU(2)$ theory to obtain the potential in a static quark-antiquark pair. Cho restricted theory is a self-consistent subset of a non-Abelian $SU(2)$ gauge theory which tries to describe the infrared regime of Yang-Mills gauge theories. In Zwanziger formalism, a local Lagrangian depending on two electric and magnetic gauge fields is constructed for the theories where both electric and magnetic charges exist. Based on this local Lagrangian the propagator and then the potential between quarks is calculated in two limits: $m_{C} r \ll 1$ and $m_{C} r \gg 1$, where $m_{C}$ is the mass of the dual gauge boson and $r$ is the distance between the quark and the antiquark.Comment: 2 Figures, 15 pages, Version accepted for publication in PR

Genome-scale co-expression network comparison across escherichia coli and salmonella enterica serovar typhimurium reveals significant conservation at the regulon level of local regulators despite their dissimilar lifestyles

Availability of genome-wide gene expression datasets provides the opportunity to study gene expression across different organisms under a plethora of experimental conditions. In our previous work, we developed an algorithm called COMODO (COnserved MODules across Organisms) that identifies conserved expression modules between two species. In the present study, we expanded COMODO to detect the co-expression conservation across three organisms by adapting the statistics behind it. We applied COMODO to study expression conservation/divergence between Escherichia coli, Salmonella enterica, and Bacillus subtilis. We observed that some parts of the regulatory interaction networks were conserved between E. coli and S. enterica especially in the regulon of local regulators. However, such conservation was not observed between the regulatory interaction networks of B. subtilis and the two other species. We found co-expression conservation on a number of genes involved in quorum sensing, but almost no conservation for genes involved in pathogenicity across E. coli and S. enterica which could partially explain their different lifestyles. We concluded that despite their different lifestyles, no significant rewiring have occurred at the level of local regulons involved for instance, and notable conservation can be detected in signaling pathways and stress sensing in the phylogenetically close species S. enterica and E. coli. Moreover, conservation of local regulons seems to depend on the evolutionary time of divergence across species disappearing at larger distances as shown by the comparison with B. subtilis. Global regulons follow a different trend and show major rewiring even at the limited evolutionary distance that separates E. coli and S. enterica

Formation of Small-Scale Condensations in the Molecular Clouds via Thermal Instability

A systematic study of the linear thermal instability of a self-gravitating magnetic molecular cloud is carried out for the case when the unperturbed background is subject to local expansion or contraction. We consider the ambipolar diffusion, or ion-neutral friction on the perturbed states. In this way, we obtain a non-dimensional characteristic equation that reduces to the prior characteristic equation in the non-gravitating stationary background. By parametric manipulation of this characteristic equation, we conclude that there are, not only oblate condensation forming solutions, but also prolate solutions according to local expansion or contraction of the background. We obtain the conditions for existence of the Field lengths that thermal instability in the molecular clouds can occur. If these conditions establish, small-scale condensations in the form of spherical, oblate, or prolate may be produced via thermal instability.Comment: 16 page, accepted by Ap&S

Nanoscale thermal properties of carbon nanotubes/epoxy composites by atomistic simulations

Carbon nanotubes/epoxy composites are increasingly employed in several industrial fields, because of the enhanced material properties provided by the nanofillers. In particular, the thermal conductivity of these nanocomposites is determined by heat transfer mechanisms occurring over multiple scales, thus causing a complex relation between effective response and microscopic characteristics of the material. Here, the thermal properties of epoxy composites reinforced by carbon nanotubes are investigated using atomistic simulations. For a better understanding of how the effective thermal conductivity arises from the characteristics of the composite at the nanoscale, the thermal properties of its constituents are studied separately according to different geometrical, physical and chemical characteristics. The thermal conductivity of carbon nanotubes and epoxy resin alone is first investigated by molecular dynamics; then, the Kapitza resistance at the nanotube–nanotube and nanotube–epoxy interfaces is studied as well. The effective thermal conductivity of the carbon nanotubes/epoxy composite is finally computed and the observed behavior interpreted on the basis of the properties of the nanofillers, matrix and interfaces alone. Results – verified against effective medium theory predictions – show that, for the considered configurations, the effective thermal conductivity of the nanocomposite increases with the nanotube length and volume fraction, with the curing degree of the epoxy and system temperature. In perspective, the presented approach could be employed to investigate other constitutive materials or properties of nanocomposites