Worcester Polytechnic Institute

About: Worcester Polytechnic Institute is a education organization based out in Worcester, Massachusetts, United States. It is known for research contribution in the topics: Computer science & Population. The organization has 6270 authors who have published 12704 publications receiving 332081 citations. The organization is also known as: WPI.

Exhaustion of Racing Sperm in Nature-Mimicking Microfluidic Channels During Sorting

Abstract: Fertilization is central to the survival and propagation of a species, however, the precise mechanisms that regulate the sperm's journey to the egg are not well understood. In nature, the sperm has to swim through the cervical mucus, akin to a microfluidic channel. Inspired by this, a simple, cost-effective microfluidic channel is designed on the same scale. The experimental results are supported by a computational model incorporating the exhaustion time of sperm.

No falls, no resets: Reliable humanoid behavior in the DARPA robotics challenge

Abstract: We describe Team WPI-CMU's approach to the DARPA Robotics Challenge (DRC), focusing on our strategy to avoid failures that required physical human intervention. We implemented safety features in our controller to detect potential catastrophic failures, stop the current behavior, and allow remote intervention by a human supervisor. Our safety methods and operator interface worked: we avoided catastrophe and remote operators could safely recover from difficult situations. We were the only team in the DRC Finals that attempted all tasks, scored points (14/16), did not require physical human intervention (a reset), and did not fall in the two missions during the two days of tests. We also had the most consistent pair of runs. Much of the paper discusses lessons learned from the DRC.

Bayesian semiparametric models for survival data with a cure fraction.

Abstract: We propose methods for Bayesian inference for a new class of semiparametric survival models with a cure fraction. Specifically, we propose a semiparametric cure rate model with a smoothing parameter that controls the degree of parametricity in the right tail of the survival distribution. We show that such a parameter is crucial for these kinds of models and can have an impact on the posterior estimates. Several novel properties of the proposed model are derived. In addition, we propose a class of improper noninformative priors based on this model and examine the properties of the implied posterior. Also, a class of informative priors based on historical data is proposed and its theoretical properties are investigated. A case study involving a melanoma clinical trial is discussed in detail to demonstrate the proposed methodology.