Multiscale Dynamic Graph Representation for Biometric Recognition With Occlusions.

Occlusion is a common problem with biometric recognition in the wild. The generalization ability of CNNs greatly decreases due to the adverse effects of various occlusions. To this end, we propose a novel unified framework integrating the merits of both CNNs and graph models to overcome occlusion problems in biometric recognition, called multiscale dynamic graph representation (MS-DGR).

Pose-Appearance Relational Modeling for Video Action Recognition.

Recent studies of video action recognition can be classified into two categories: the appearance-based methods and the pose-based methods. The appearance-based methods generally cannot model temporal dynamics of large motion well by virtue of optical flow estimation, while the pose-based methods ignore the visual context information such as typical scenes and objects, which are also important cues for action understanding. In this paper, we tackle these problems by proposing a Pose-Appearance Relational Network (PARNet), which models the correlation between human pose and image appearance, and combines the benefits of these two modalities to improve the robustness towards unconstrained real-world videos.

LFNet: A Novel Bidirectional Recurrent Convolutional Neural Network for Light-Field Image Super-Resolution.

The low spatial resolution of light-field image poses significant difficulties in exploiting its advantage. To mitigate the dependency of accurate depth or disparity information as priors for light-field image super-resolution, we propose an implicitly multi-scale fusion scheme to accumulate contextual information from multiple scales for super-resolution reconstruction. The implicitly multi-scale fusion scheme is then incorporated into bidirectional recurrent convolutional neural network, which aims to iteratively model spatial relations between horizontally or vertically adjacent sub-aperture images of light-field data.

High WT1 expression is associated with very poor survival of patients with osteogenic sarcoma metastasis.

Purpose: Although metastasis is the primary determinant of poor survival of patients with osteogenic sarcoma, some patients live much longer than others, indicating metastatic heterogeneity underlying survival outcome. The purpose of the investigation was to identify genes underlying survival outcome of patients with osteogenic sarcoma metastasis.

Experimental Design: We have used microarray to first compare mRNA expression between normal bone and osteogenic sarcoma specimens, identified genes overexpressed in osteogenic sarcoma, and compared expression of the selected gene between a poorly metastatic (SAOS) and two highly metastatic cell lines (LM8 and 143B).

Expression of a novel alternatively spliced UCP-2 transcript in osteogenic sarcoma.

Background: Development of chemoresistance is common in patients with osteogenic sarcoma (OGS); however, the underlying mechanism is largely unknown. Many anticancer drugs exert their therapeutic action by generating reactive oxygen radicals, which might be countered by the cancer cell through induction of uncoupling protein 2 (UCP-2). UCP-2 has been shown to be able to protect tumor cells from the cytotoxic actions of chemotherapeutic drugs.

Intragenic codon bias in a set of mouse and human genes.

To better conceptualize the mechanism underlying the evolution of synonymous codons, we have analysed intragenic codon usage in chosen "regions" of some mouse and human genes. We divided a given gene into two regions: one consisting of a trinucleotide repeat (TNR) and the other consisting of the "rest of the coding region" (RCR). Usually, a TNR is composed of a repetitive single codon, which may reflect its frequency in a gene.

The human homolog of yeast SEP1 is a novel candidate tumor suppressor gene in osteogenic sarcoma.

The hSEP1 gene is the human homolog of yeast SEP1. Yeast SEP1 is a multifunctional gene that regulates a variety of nuclear and cytoplasmic functions including homologous recombination, meiosis, telomere maintenance, RNA metabolism and microtubule assembly. The function of hSEP1 is not known.