Nathan Lapierre

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We explore whole-body interaction with <i>Tweetris</i>, a game where two players competitively race to form Tetris shapes (tetrominos) with their body. We debuted Tweetris at an all-night, public art event, collecting 6000 winning body shapes made by more than 270 players. Tweetris employs a novel form of interaction cue we call a <i>discretized(More)
Functional subtyping of neurokinin and histamine receptors on the canine proximal colon suggested that different receptors were involved in mediating the neural and non-neural effects on ion transport. If the non-neural effects involved direct stimulation of the transporting epithelial cells, mRNA for specific receptor subtypes should be present in colonic(More)
Limber, in its current iteration, is a vision-based application that introduces gamification into the workplace. This ongoing effort to incentivize good posture, and regular body movements implements several changes to include; full body stretches (figure 2), team gaming elements, and an ambient display (figure 1). With increased intra and inter team(More)
Limber is an office "exergame" aimed at incentivizing regular body movement and good posture. In this paper we describe our progression in design and implementation from a wearable system targeting repetitive stress injury to the back, wrist and neck, to our current vision-based system focused on posture, gross motor mobility and whole body stretches. We(More)
The recent advent of Metagenome-Wide Association Studies (MGWAS) has allowed for increased accuracy in the prediction of patient phenotype (disease), but has also presented big data challenges. Meanwhile, Multiple Instance Learning (MIL) is useful in the domain of bioinformatics because, in addition to classifying patient phenotype, it can also identify(More)
We demonstrate a computational method to predict the clinical phenotypes of a patient from raw metagenomic sequence read data. We compared two state of the art programs for annotating the sequence data, UCLUST and Kraken, and using their output for feature generation. We apply these programs to a set of over 1.3 million reads from 904 patients, some of whom(More)
Norepinephrine (NE) overflow from field-stimulated rat was deferens preparations was quantified directly by electrochemical detection using high performance liquid chromatography. The effect of agonist (BHT 920) and antagonist (rauwolscine) of prejunctional alpha 2-adrenoceptors on NE overflow was assessed and compared with their effect on the smooth muscle(More)
The recent advent of Metagenome Wide Association Studies (MGWAS) provides insight into the role of microbes on human health and disease. However, the studies present several computational challenges. In this paper we demonstrate a novel, efficient, and effective Multiple Instance Learning (MIL) based computational pipeline to predict patient phenotype from(More)
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