The formation of stars

We review the process of star formation, detailing the theories underlying the stability of molecular clouds and their collapse to protostars, and discussing the empirical evidence and models which inform them. We give emphasis to the role that the magnetic field plays in influencing the stability of molecular clouds and hence the star formation rate. The end result of star formation is a mass function which appears constant within our Galaxy. A relative abundance of low mass stars is observed over high mass stars and most of the stars that do form are found to exist as members of a binary system. The origin of binarity is reviewed as is the discovery, formation and observations of some of the lowest mass stars known, the brown dwarfs.     

A memory function model for the velocity autocorrelation function and the self-diffusion coefficient in simple dense fluids

A memory-function model is used to compute the velocity autocorrelation function and the self-diffusion coefficient of a dense Lennard-Jones fluid from the zero-time correlation functions of the molecular velocity and its first two time derivatives. It is shown that these zero-time correlation functions can be evaluated in terms of the radial distribution function and the pair potential only, i.e. without considering higher order correlation functions. Since molecular dynamics results are available for the radial distribution function as well as the velocity autocorrelation function and the self-diffusion coefficient, a rigorous test of the chosen memory function is possible. The agreement is reasonable, although generally not within the error bands of the molecular dynamics results.     

Heat-moisture treatment (HMT) on blends from potato starch (PS) and sweet potato starch (SPS)

Journal of Thermal Analysis and Calorimetry - Samples of potato starch (PS), sweet potato starch (SPS) and their binary mixtures, with moisture levels of 10, 15 and 20% (db), were submitted to...     

Existence of solutions for the 3D-micropolar fluid system with initial data in Besov–Morrey spaces

In this paper, we show a local-in-time existence result for the 3D micropolar fluid system in the framework of Besov–Morrey spaces. The initial data class is larger than the previous ones and contains strongly singular functions and measures.     

Maximizing the mean subtree order

This article focuses on properties and structures of trees with maximum mean subtree order in a given family; such trees are called optimal in the family. Our main goal is to describe the structure of optimal trees in and , the families of all trees and caterpillars, respectively, of order . We begin by establishing a powerful tool called the Gluing Lemma, which is used to prove several of our main results. In particular, we show that if is an optimal tree in or for , then every leaf of is adjacent to a vertex of degree at least . We also use the Gluing Lemma to answer an open question of Jamison and to provide a conceptually simple proof of Jamison's result that the path has minimum mean subtree order among all trees of order . We prove that if is optimal in , then the number of leaves in is and that if is optimal in , then the number of leaves in is . Along the way, we describe the asymptotic structure of optimal trees in several narrower families of trees.     

Hybrid Plasmonic–Aerogel Materials as Optical Superheaters with Engineered Resonances

Solar radiation is a versatile source of energy, convertible to different forms of power. A direct path to exploit it is the generation of heat, for applications including passive building heating, but it can also drive secondary energy-conversion steps. We present a novel concept for a hybrid material which is both strongly photo-absorbing and with superior characteristics for the insulation of heat. The combination of that two properties is rather unique, and make this material an optical superheater. To realize such a material, we are combining plasmonic nanoheaters with alumina aerogel. The aerogel has the double function of providing structural support for plasmonic nanocrystals, which serve as nanoheaters, and reducing the diffusion rate of the heat generated by them, resulting in large local temperature increases under a relatively low radiation intensity. This work includes theoretical discussion on the physical mechanisms impacting the system's balanced thermal equilibrium.     

On the Local Convergence Analysis of the Gradient Sampling Method for Finite Max-Functions

The gradient sampling method is a recently developed tool for solving unconstrained nonsmooth optimization problems. Using just first-order information about the objective function, it generalizes the steepest descent method, one of the most classical methods for minimizing a smooth function. This study aims at determining under which circumstances one can expect the same local convergence result of the Cauchy method for the gradient sampling algorithm under the assumption that the problem is stated by a finite max-function around the optimal point. Additionally, at the end, we show how to practically accomplish the required hypotheses during the execution of the algorithm.