The Limits of State Jurisdiction in Affording Common Law Protection to Clothing Designs

The recent case of Dior v. Milton\u27 indicates that the misappropriation doctrine of the law of unfair competition will be applied to impose liability upon unlicensed users of original clothing designs. The purpose of this article is to outline briefly the statutory protection presently available for such designs, and to discuss certain problems raised by the Dior v. Milton decision. The Constitution, in article I, section 8, provides that Congress shall have power to enact legislation to promote the progress of science and the useful arts, by securing for limited times to authors and inventors the exclusive right to their respective writings and discoveries. This provision is the constitutional basis for federal patent and copyright legislation. There is little argument that this grant of power is broad enough to permit congressional legislation protecting designs. In the past, many bills have been introduced providing specifically for design copyright,\u27 and although defeated on policy grounds, their constitutionality was not seriously doubted. The question has never been judicially decided, however, and must wait for the time legislation specifically providing for design copyright is enacted

A Neural Attention Model for Categorizing Patient Safety Events

Medical errors are leading causes of death in the US and as such, prevention of these errors is paramount to promoting health care. Patient Safety Event reports are narratives describing potential adverse events to the patients and are important in identifying and preventing medical errors. We present a neural network architecture for identifying the type of safety events which is the first step in understanding these narratives. Our proposed model is based on a soft neural attention model to improve the effectiveness of encoding long sequences. Empirical results on two large-scale real-world datasets of patient safety reports demonstrate the effectiveness of our method with significant improvements over existing methods.Comment: ECIR 201

Prediction-Based Learning and Processing of Event Knowledge.

Knowledge of common events is central to many aspects of cognition. Intuitively, it seems as though events are linear chains of the activities of which they are comprised. In line with this intuition, a number of theories of the temporal structure of event knowledge have posited mental representations (data structures) consisting of linear chains of activities. Competing theories focus on the hierarchical nature of event knowledge, with representations comprising ordered scenes, and chains of activities within those scenes. We present evidence that the temporal structure of events typically is not well-defined, but it is much richer and more variable both within and across events than has usually been assumed. We also present evidence that prediction-based neural network models can learn these rich and variable event structures and produce behaviors that reflect human performance. We conclude that knowledge of the temporal structure of events in the human mind emerges as a consequence of prediction-based learning

Error-resistant Single Qubit Gates with Trapped Ions

Coherent operations constitutive for the implementation of single and multi-qubit quantum gates with trapped ions are demonstrated that are robust against variations in experimental parameters and intrinsically indeterministic system parameters. In particular, pulses developed using optimal control theory are demonstrated for the first time with trapped ions. Their performance as a function of error parameters is systematically investigated and compared to composite pulses.Comment: 5 pages 5 figure

Refined saddle-point preconditioners for discretized Stokes problems

This paper is concerned with the implementation of efficient solution algorithms for elliptic problems with constraints. We establish theory which shows that including a simple scaling within well-established block diagonal preconditioners for Stokes problems can result in significantly faster convergence when applying the preconditioned MINRES method. The codes used in the numerical studies are available online