Deep cleaning mouthwashes, no stain!

An in vitro screening assay for dental stain cleaning

BACKGROUND The present study aimed to develop an in vitro model for stain removal from natural enamel for the assessment and comparison of oral hygiene products. METHODS Bovine teeth (n = 8 per group) were ground/polished to provide flat enamel specimens and ferric-tannate deposits were precipitated onto the enamel surfaces. The ferric-tannate stained enamel specimens were brushed using an in...

Particle Motion and Stain Removal during Simulated Abrasive Tooth Cleaning

Data Cleaning by Deep Dictionary Learning

The soundness of training data is important to the performance of a learning model. However in recommender systems, the training data are usually noisy, because of the randomness nature of users’ behaviors and the sparseness of the users’ feedback towards the recommendations. In this work, we would like to propose a noise elimination model to preprocess the training data in recommender systems....

No more muddy waters: cleaning up the Clean Water Act.

Decay-accelerating-factor (DAF, CD55), a phosphatidyl-inositol anchored glycoprotein, is a member of the cell membrane bound complement regulatory proteins that inhibit autologous complement cascade activation. DAF was found expressed on cells that are in close contact with serum complement proteins, but also on cells outside the vascular space and on tumour cells. Using CD55(BRIC110) and CD55(...

A Deep Recurrent Framework for Cleaning Motion Capture Data

We present a deep, bidirectional, recurrent framework for cleaning noisy and incomplete motion capture data. It exploits temporal coherence and joint correlations to infer adaptive filters for each joint in each frame. A single model can be trained to denoise a heterogeneous mix of action types, under substantial amounts of noise. A signal that has both noise and gaps is preprocessed with a sec...