The End of Affirmative Action? Work Rule Concessions at South Works

[Excerpt] The recent Rail Mill Manning Agreement between U.S. Steel South Works and Local 65 of the United Steelworkers of America changed both the local and Basic Labor Agreements. This paper will demonstrate the adverse effect that this Agreement will have on minorities and women

Beyond Basins of Attraction: Quantifying Robustness of Natural Dynamics

Properly designing a system to exhibit favorable natural dynamics can greatly simplify designing or learning the control policy. However, it is still unclear what constitutes favorable natural dynamics and how to quantify its effect. Most studies of simple walking and running models have focused on the basins of attraction of passive limit-cycles and the notion of self-stability. We instead emphasize the importance of stepping beyond basins of attraction. We show an approach based on viability theory to quantify robust sets in state-action space. These sets are valid for the family of all robust control policies, which allows us to quantify the robustness inherent to the natural dynamics before designing the control policy or specifying a control objective. We illustrate our formulation using spring-mass models, simple low dimensional models of running systems. We then show an example application by optimizing robustness of a simulated planar monoped, using a gradient-free optimization scheme. Both case studies result in a nonlinear effective stiffness providing more robustness.Comment: 15 pages. This work has been accepted to IEEE Transactions on Robotics (2019

Learning from Outside the Viability Kernel: Why we Should Build Robots that can Fall with Grace

Despite impressive results using reinforcement learning to solve complex problems from scratch, in robotics this has still been largely limited to model-based learning with very informative reward functions. One of the major challenges is that the reward landscape often has large patches with no gradient, making it difficult to sample gradients effectively. We show here that the robot state-initialization can have a more important effect on the reward landscape than is generally expected. In particular, we show the counter-intuitive benefit of including initializations that are unviable, in other words initializing in states that are doomed to fail.Comment: Proceedings of the 2018 IEEE International Conference on SImulation, Modeling and Programming for Autonomous Robots (SIMPAR), Brisbane, Australia, 16-19 201

Stamp duty on shares and its effect on share prices

This paper provides a discussion of stamp duty and its effects. This is followed by an empirical study using changes in the rate of stamp duty in the UK as natural experiments. Because shares will be affected differently depending on how frequently they are traded, we can employ a difference-in-differences methodology. We find that the announcements of cuts in stamp duty had a significant and positive effect on the price of more frequently traded shares compared to other shares. As expected under the efficient markets hypothesis, the implementation of cuts (when at a different date from the announcement) did not affect returns differentially.Stamp duty, transaction tax, Tobin-tax, natural experiment, tax reform

Shaping in Practice: Training Wheels to Learn Fast Hopping Directly in Hardware

Learning instead of designing robot controllers can greatly reduce engineering effort required, while also emphasizing robustness. Despite considerable progress in simulation, applying learning directly in hardware is still challenging, in part due to the necessity to explore potentially unstable parameters. We explore the concept of shaping the reward landscape with training wheels: temporary modifications of the physical hardware that facilitate learning. We demonstrate the concept with a robot leg mounted on a boom learning to hop fast. This proof of concept embodies typical challenges such as instability and contact, while being simple enough to empirically map out and visualize the reward landscape. Based on our results we propose three criteria for designing effective training wheels for learning in robotics. A video synopsis can be found at https://youtu.be/6iH5E3LrYh8.Comment: Accepted to the IEEE International Conference on Robotics and Automation (ICRA) 2018, 6 pages, 6 figure

First Complete Genome Sequence of Corynebacterium riegelii.

Here, we report the first complete genome sequence of Corynebacterium riegelii strain PUDD_83A45, isolated from the urine of a patient with urinary tract infection. The genome measured 2.56 Mb and contained no plasmid

Draft Genome Sequence of Mycobacterium heraklionense Strain Davo.

We report the draft genome sequence of Mycobacterium heraklionense strain Davo, isolated from a fine-needle aspirate of a right-ankle soft-tissue mass. This is the first draft genome sequence of Mycobacterium heraklionense, a nonpigmented rapidly growing mycobacterium

Draft Genome Sequence of Mycobacterium heckeshornense Strain RLE.

We report here the draft genome sequence of Mycobacterium heckeshornense strain RLE isolated from a sputum sample from a patient with shortness of breath. This is the first draft genome sequence of M. heckeshornense

Diet of the Periwinkle Littorina irrorata in a Louisiana Salt Marsh

The diet of the periwinkle Littorina irrorata was examined. The food substrate utilized most frequently in the field was dead Spartina alterniflora. The primary component of the stomach and feces was vascular plant particles. Plant particles, even though a major portion of the diet, were egested unaltered in feces. Other food substrates contributed significantly to the diet. Marsh sediment was utilized by 37% of all snails observed to be feeding, while 4% grazed on live S. alterniflora. Algal mats, present on several occasions during the study, were utilized extensively. Comparison of microbial components in dead S. alterniflora and marsh sediment with those in the stomach and feces indicated that members of the microbial community of food substrates were assimilated