University of Leicester

About: University of Leicester is a education organization based out in Leicester, United Kingdom. It is known for research contribution in the topics: Population & Galaxy. The organization has 26469 authors who have published 61444 publications receiving 2305724 citations. The organization is also known as: Leicester University.

Resolved Massive Star Clusters in the Milky Way and its Satellites: Brightness Profiles and a Catalogue of Fundamental Parameters

Abstract: [Abridged]: We present a database of structural and dynamical properties for 153 spatially resolved star clusters (50 "young massive clusters" and 103 old globulars) in the Milky Way, the Large and Small Magellanic Clouds, and the Fornax dwarf spheroidal. This database complements and extends others in the literature, such as those of Harris, and Mackey & Gilmore. By fitting a number of models to the clusters' density profiles, we derive various characteristic surface brightnesses and radii; central potentials, velocity dispersions, and escape velocities; total luminosities, masses, and binding energies; phase-space densities and relaxation timescales; and ``kappa-space'' parameters. Population-synthesis models are used to predict intrinsic (B-V) colors, reddenings, and V-band mass-to-light ratios for the same 153 clusters plus another 63 globulars in the Milky Way, and we compare these predictions to the observed quantities where available. These results are intended to serve as the basis for future investigations of structural correlations and the fundamental plane of massive star clusters, including especially comparisons between the systemic properties of young and old clusters. We also address the question of what structural model fits each cluster best, and argue that the extended halos known to characterize many Magellanic Cloud clusters may be examples of the generic envelope structure of self-gravitating star clusters, not just transient features associated strictly with young age.

The Properties of Random Surfaces of Significance in their Contact

Abstract: In recent work it has been shown that many types of surfaces used in engineering practice have a random structure. The paper takes, as a representation of the profile of such a surface, the waveform of a random signal; this is completely defined by two parameters, a height distribution and an auto-correlation function. It is shown how such a representation can be transformed into a model, appropriate for the study of surface contact, consisting of an array of asperities having a statistical distribution of both heights and curvatures. This theory is compared with the results of an analysis of surface profiles presented in digital form. The significance of these findings for the theory of surface contact and for the measurement and characterization of surface finish is discussed.

The Pathophysiology of Gestational Diabetes Mellitus

Abstract: Gestational diabetes mellitus (GDM) is a serious pregnancy complication, in which women without previously diagnosed diabetes develop chronic hyperglycemia during gestation. In most cases, this hyperglycemia is the result of impaired glucose tolerance due to pancreatic β-cell dysfunction on a background of chronic insulin resistance. Risk factors for GDM include overweight and obesity, advanced maternal age, and a family history or any form of diabetes. Consequences of GDM include increased risk of maternal cardiovascular disease and type 2 diabetes and macrosomia and birth complications in the infant. There is also a longer-term risk of obesity, type 2 diabetes, and cardiovascular disease in the child. GDM affects approximately 16.5% of pregnancies worldwide, and this number is set to increase with the escalating obesity epidemic. While several management strategies exist—including insulin and lifestyle interventions—there is not yet a cure or an efficacious prevention strategy. One reason for this is that the molecular mechanisms underlying GDM are poorly defined. This review discusses what is known about the pathophysiology of GDM, and where there are gaps in the literature that warrant further exploration.

Reply to ``Comment on `Performance of different synchronization measures in real data: A case study on electroencephalographic signals' ''

Abstract: We agree with the Comment by Duckrow and Albano [Phys. Rev. E 67, 063901 (2003)] that mutual information, estimated with an optimized algorithm, can be a useful tool for studying synchronization in real data. However, we point out that the improvement they found is mainly due to an interesting but nonstandard embedding technique used, and not so much due to the algorithm used for the estimation of mutual information itself. We also address the issue of stationarity of electroencephalographic (EEG) data.