7,413 research outputs found
Antiferromagnetic Alignment and Relaxation Rate of Gd Spins in the High Temperature Superconductor GdBa_2Cu_3O_(7-delta)
The complex surface impedance of a number of GdBaCuO
single crystals has been measured at 10, 15 and 21 GHz using a cavity
perturbation technique. At low temperatures a marked increase in the effective
penetration depth and surface resistance is observed associated with the
paramagnetic and antiferromagnetic alignment of the Gd spins. The effective
penetration depth has a sharp change in slope at the N\'eel temperature, ,
and the surface resistance peaks at a frequency dependent temperature below 3K.
The observed temperature and frequency dependence can be described by a model
which assumes a negligibly small interaction between the Gd spins and the
electrons in the superconducting state, with a frequency dependent magnetic
susceptibility and a Gd spin relaxation time being a strong function
of temperature. Above , has a component varying as , while below it increases .Comment: 4 Pages, 4 Figures. Submitted to Phys. Rev.
Saving for retirement: a review of ethnic minorities in the UK
This article examines the saving behaviour of ethnic minorities in the UK. Within the context of pension planning, we investigate saving for retirement patterns in relation to ethnicity, gender and age. We use data from the Family Resources Survey (FRS) to analyse employment status, income, saving types and levels. Although we find profound heterogeneity, ethnic minorities show higher levels of unemployment, lower income and consistently lower levels of saving for retirement compared to our white control group. Disadvantages of ethnic minorities during their working life persist, especially for women, although to a lesser extent than in the past, and continue to affect private savings and prospective retirement income. Indian and Chinese men have experienced the greatest improvements in terms of employment status and income and this is reflected in higher levels of saving for retirement since the mid 1990s
Protein-Based Nanofibers and Thin Films for Drug Delivery Applications
Corn zein and silk are both widely available, easy to extract proteins making them valuable replacements for synthetics. Zein and silk are also promising biomaterials in several applications. This work explores the use of both proteins as drug delivery vehicles by loading 1-Dimensional micro-nanofibers and 2-Dimensional thin films with model drugs or the topical therapeutic sodium citrate. Using a formic acid solvent, powdered zein protein or silk fibers were dissolved into solution and then casted into 2D films or spun into 1D fibers through air-spraying. During dissolution, therapeutic products are added. SEM images showed that fibers maintain their small diameter and porous network at lower amounts of therapeutics. Structural characterization showed that therapeutics could interact and influence secondary protein structure in porous fibers, but not flat films. This interaction improves the thermal integrity of most samples and allowed for greater control of the release of therapeutics from the biomaterial. In summary, the geometry of the biomaterials played an important role in allowing biophysical and biochemical interactions between the therapeutics and the protein structure of the biomaterials. By understanding these interactions, there is more control over material properties and release kinetics. Meanwhile, the fabrication process showed no hindrance on the biocompatibility of the biomaterials in a human cell line
Influencing Exploration in Actor-Critic Reinforcement Learning Algorithms
Reinforcement Learning (RL) is a subset of machine learning primarily concerned with goal-directed learning and optimal decision making. RL agents learn based on a reward signal discovered from trial and error in complex, uncertain environments with the goal of maximizing positive reward signals. RL approaches need to scale up as they are applied to more complex environments with extremely large state spaces. Inefficient exploration methods cannot sufficiently explore complex environments in a reasonable amount of time, and optimal policies will be unrealized resulting in RL agents failing to solve an environment.
This thesis proposes a novel variant of the Actor-Advantage Critic (A2C) algorithm. The variant is validated against two state-of-the-art RL algorithms, Deep Q-Network (DQN) and A2C, across six Atari 2600 games of varying difficulty. The experimental results are competitive with state-of-the-art and achieve lower variance and quicker learning speed. Additionally, the thesis introduces a metric to objectively quantify the difficulty of any Markovian environment with respect to the exploratory capacity of RL agents
Community Property and Family Law: The Family Law Act of 1969
The year 1969 marked the decade\u27s principal accomplishment in family law, the passage of the Family Law Act. The last several years have seen a sharply rising discontent with our traditional procedures for handling the dissolution of marriages, and numerous reform proposals have been advanced both in this country and abroad.
The Family Law Act brings some of these proposals to fruition; it marks the first legislative eradication of marital fault as the governing principle of divorce in any American jurisdiction. Because the passage of the new law virtually eclipses the past year\u27s decisional developments in family law and community property, this article will attempt to focus on its highlights in summary form, not to provide an exhaustive catalogue of all its points, but rather to set out its structure and indicate some directions of future growth
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