In this paper, we propose a novel face detection network with three novel contributions that address three key aspects of face detection, including better feature learning, progressive loss design and anchor assign based data augmentation, respectively. First, we propose a Feature Enhance Module (FEM) for enhancing the original feature maps to extend the single shot detector to dual shot detector. Second, we adopt Progressive Anchor Loss (PAL) computed by two different sets of anchors to effectively facilitate the features. Third, we use an Improved Anchor Matching (IAM) by integrating novel anchor assign strategy into data aug-

Recently, regression analysis has become a popular tool for face recognition. Most existing regression methods use the one-dimensional, pixel-based error model, which characterizes the representation error individually, pixel by pixel, and thus neglects the two-dimensional structure of the error image. We observe that occlusion and illumination changes generally lead, approximately, to a low-rank error image. In order to make use of this low-rank structural information, this paper presents a two-dimensional image-matrix-based error model, namely, nuclear norm based matrix regression (NMR), for face representation and classification. NMR uses the minimal nuclear norm of representation error image as a criterion, and the alternating direction method of multipliers (ADMM) to calculate the regression coefficients. We further develop a fast ADMM algorithm to solve the approximate NMR model and show it has a quadratic rate of convergence. We experiment using five popular face image databases: the Extended Yale B, AR, EURECOM, Multi-PIE and FRGC. Experimental results demonstrate the performance advantage of NMR over the state-of-the-art regression-based methods for face recognition in the presence of occlusion and illumination variations.

It has long been thought that growth-regulating factors (GRFs) gene family members act as transcriptional activators to play important roles in multiple plant developmental processes. However, the recent characterization of Arabidopsis GRF7 showed that it functions as a transcriptional repressor of osmotic stress-responsive genes. This highlights the complex and diverse mechanisms by which different GRF members use to take action. In this study, the maize (Zea mays L.) GRF10 was functionally characterized to improve this concept. The deduced ZmGRF10 protein retains the N-terminal QLQ and WRC domains, the characteristic regions as protein-interacting and DNA-binding domains, respectively. However, it lacks nearly the entire C-terminal domain, the regions executing transactivation activity. Consistently, ZmGRF10 protein maintains the ability to interact with GRF-interacting factors (GIFs) proteins, but lacks transactivation activity. Overexpression of ZmGRF10 in maize led to a reduction in leaf size and plant height through decreasing cell proliferation, whereas the yield-related traits were not affected. Transcriptome analysis revealed that multiple biological pathways were affected by ZmGRF10 overexpression, including a few transcriptional regulatory genes, which have been demonstrated to have important roles in controlling plant growth and development. We propose that ZmGRF10 aids in fine-tuning the homeostasis of the GRF-GIF complex in the regulation of cell proliferation.

Marital status is an independent prognostic factor for survival in several cancers. To determine if that is also true for pancreatic cancer after surgical treatment, we examined 13,370 cases of pancreatic cancer reported to the Surveillance, Epidemiology, and End Results (SEER) database between 1988 and 2012. We found that patients who were widowed at the time of diagnosis were more likely to be female, a high percentage were elderly, a high ratio were diagnosed in early years, and a high proportion of tumors were located at the head of the pancreas (P < 0.05). Marital status was confirmed to be an independent prognostic factor in both univariate and multivariate analyses (P < 0.05). In those with localized disease, 5-year pancreatic cancer cause-specific survival was 6.5% lower in widowed patients than married ones (38.6% vs. 32.1%), though this difference was not significant in a multivariate analysis (P = 0.084). In those with regional disease or distant metastasis, univariate and multivariate analyses indicated marital status to be an independent prognostic factor (P < 0.05). Thus marital status is an important prognostic factor in pancreatic cancer, and widowed patients are at greater risk of death than others.

Non-small cell lung cancer (NSCLC) accounts for most lung cancer. To develop new therapy required the elucidation of NSCLC pathogenesis. The deubiquitinating enzymes USP 28 has been identified and studied in colon and breast carcinomas. However, the role of USP28 in NSCLC is unknown. The level mRNA or protein level of USP28 were measured by qRT-PCR or immunohistochemistry (IHC). The role of USP28 in patient survival was revealed by Kaplan–Meier plot of overall survival in NSCLC patients. USP28 was up or down regulated by overexpression plasmid or siRNA transfection. Cell proliferation and apoptosis was assayed by MTT and FACS separately. Potential microRNAs, which targeted USP28, were predicated by bioinformatic algorithm and confirmed by Dual Luciferase reporter assay system. High mRNA and protein level of USP28 in NSCLC were both correlated with low patient survival rate. Overexpression of USP28 promoted NSCLC cells growth and vice versa. Down-regulation of USP28 induced cell apoptosis. USP28 was targeted by miR-4295. Overexpression of USP28 promoted NSCLC cells proliferation, and was associated with poor prognosis in NSCLC patients. The expression of USP28 may be regulated by miR-4295. Our data suggested that USP28 was a tumour-promoting factor and a promising therapeutic target for NSCLC.