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Human actions can be represented by the trajectories of skeleton joints. Traditional methods generally model the spatial structure and temporal dynamics of human skeleton with hand-crafted features and recognize human actions by well-designed classifiers. In this paper, considering that recurrent neural network (RNN) can model the long-term contextual(More)
Chronic kidney disease (CKD) is a significant public health problem, and recent genetic studies have identified common CKD susceptibility variants. The CKDGen consortium performed a meta-analysis of genome-wide association data in 67,093 individuals of European ancestry from 20 predominantly population-based studies in order to identify new susceptibility(More)
Cross-modal matching has recently drawn much attention due to the widespread existence of multimodal data. It aims to match data from different modalities, and generally involves two basic problems: the measure of relevance and coupled feature selection. Most previous works mainly focus on solving the first problem. In this paper, we propose a novel coupled(More)
In this paper, we propose a passive image tampering detection method based on modeling edge information. We model the edge image of image chroma component as a finite-state Markov chain and extract low dimensional feature vector from its stationary distribution for tampering detection. The support vector machine (SVM) is utilized as classifier to evaluate(More)
In this paper, a simple but efficient approach for blind image splicing detection is proposed. Image splicing is a common and fundamental operation used for image forgery. The detection of image splicing is a preliminary but desirable study for image forensics. Passive detection approaches of image splicing are usually regarded as pattern recognition(More)
The progression of human tuberculosis (TB) to active disease and transmission involves the development of a caseous granuloma that cavitates and releases infectious Mycobacterium tuberculosis bacilli. In the current study, we exploited genome-wide microarray analysis to determine that genes for lipid sequestration and metabolism were highly expressed in(More)
BACKGROUND China is increasingly facing the challenge of control of the growing burden of non-communicable diseases. We assessed the epidemiology of Alzheimer's disease and other forms of dementia in China between 1990, and 2010, to improve estimates of the burden of disease, analyse time trends, and inform health policy decisions relevant to China's(More)
Current work on steganalysis for digital images is focused on the construction of complex handcrafted features. This paper proposes a new paradigm for steganalysis to learn features automatically via deep learning models. We novelly propose a customized Convolutional Neural Network for steganalysis. The proposed model can capture the complex dependencies(More)
Adipocyte differentiation is orchestrated by multiple signaling pathways and a temporally regulated transcriptional cascade. However, the mechanisms by which insulin signaling is linked to this cascade remain unclear. Here we show that the Med23 subunit of the Mediator Complex and its interacting transcription factor Elk1 are critical regulators of(More)
Adipose tissue is central to the regulation of lipid metabolism. Berardinelli-Seip congenital lipodystrophy type 2 (BSCL2), one of the most severe lipodystrophy diseases, is caused by mutation of the Seipin gene. Seipin plays an important role in adipocyte differentiation and lipid homeostasis, but its exact molecular functions are still unknown. Here, we(More)