Breast density classification with deep convolutional neural networks

Breast density classification is an essential part of breast cancer screening. Although a lot of prior work considered this problem as a task for learning algorithms, to our knowledge, all of them used small and not clinically realistic data both for training and evaluation of their models. In this work, we explore the limits of this task with a data set coming from over 200,000 breast cancer screening exams. We use this data to train and evaluate a strong convolutional neural network classifier. In a reader study, we find that our model can perform this task comparably to a human expert

Consumers' Shopping Patterns and Expenditures on Ethnic Produce: A Case Study from the Eastern Coastal U.S.A.

This study was undertaken to examine the possible niche markets which East Coast farmers might be able to use to regain their advantage. Their future economic success could hinge on shifting the focus from traditional fruits and vegetables to high-value specialty ethnic produce for which there might be a growing demand. The study results indicate that there is a strong market demand and interest for ethnic produce in the East Coast. Local producers can benefit by concentrating their efforts in producing ethnic vegetables and fresh produce and making these newer products available in the local and regional markets.Food Consumption/Nutrition/Food Safety,

Granular clustering in a hydrodynamic simulation

We present a numerical simulation of a granular material using hydrodynamic equations. We show that, in the absence of external forces, such a system phase-separates into high density and low density regions. We show that this separation is dependent on the inelasticity of collisions, and comment on the mechanism for this clustering behavior. Our results are compatible with the granular clustering seen in experiments and molecular dynamic simulations of inelastic hard disks.Comment: 4 pages, 5 figure

miRGator: an integrated system for functional annotation of microRNAs

MicroRNAs (miRNAs) constitute an important class of regulators that are involved in various cellular and disease processes. However, the functional significance of each miRNA is mostly unknown due to the difficulty in identifying target genes and the lack of genome-wide expression data combining miRNAs, mRNAs and proteins. We introduce a novel database, miRGator, that integrates the target prediction, functional analysis, gene expression data and genome annotation. MiRNA function is inferred from the list of target genes predicted by miRanda, PicTar and TargetScanS programs. Statistical enrichment test of target genes in each term is performed for gene ontology, pathway and disease annotations. Associated terms may provide valuable insights for the function of each miRNA. For the expression analysis, miRGator integrates public expression data of miRNA with those of mRNA and protein. Expression correlation between miRNA and target mRNA/proteins is evaluated and their expression patterns can be readily compared. Our web implementation supports diverse query types including miRNA name, gene symbol, gene ontology, pathway and disease terms. Interfaces for exploring common targets or regulatory miRNAs and for profiling compendium expression data have been developed as well. Currently, miRGator, available at: http://genome.ewha.ac.kr/miRGator/, supports the human and mouse genomes

Metastable Dynamics above the Glass Transition

The element of metastability is incorporated in the fluctuating nonlinear hydrodynamic description of the mode coupling theory (MCT) of the liquid-glass transition. This is achieved through the introduction of the defect density variable $n$ into the set of slow variables with the mass density $\rho$ and the momentum density ${\bf g}$. As a first approximation, we consider the case where motions associated with $n$ are much slower than those associated with $\rho$. Self-consistently, assuming one is near a critical surface in the MCT sense, we find that the observed slowing down of the dynamics corresponds to a certain limit of a very shallow metastable well and a weak coupling between $\rho$ and $n$. The metastability parameters as well as the exponents describing the observed sequence of time relaxations are given as smooth functions of the temperature without any evidence for a special temperature. We then investigate the case where the defect dynamics is included. We find that the slowing down of the dynamics corresponds to the system arranging itself such that the kinetic coefficient $\gamma_v$ governing the diffusion of the defects approaches from above a small temperature-dependent value $\gamma^c_v$.Comment: 38 pages, 14 figures (6 figs. are included as a uuencoded tar- compressed file. The rest is available upon request.), RevTEX3.0+eps