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Traditionally, human facial expressions have been studied using either 2D static images or 2D video sequences. The 2D-based analysis is incapable of handing large pose variations. Although 3D modeling techniques have been extensively used for 3D face recognition and 3D face animation, barely any research on 3D facial expression recognition using 3D range(More)
As opposed to traditional supervised learning, multiple-instance learning concerns the problem of classifying a bag of instances, given bags that are labeled by a teacher as being overall positive or negative. Current research mainly concentrates on adapting traditional concept learning to solve this problem. In this paper we investigate the use of lazy(More)
The creation of facial range models by 3D imaging systems has led to extensive work on 3D face recognition [19]. However, little work has been done to study the usefulness of such data for recognizing and understanding facial expressions. Psychological research shows that the shape of a human face, a highly mobile facial surface, is critical to facial(More)
MOTIVATION Transcriptome sequencing has long been the favored method for quickly and inexpensively obtaining a large number of gene sequences from an organism with no reference genome. Owing to the rapid increase in throughputs and decrease in costs of next- generation sequencing, RNA-Seq in particular has become the method of choice. However, the very(More)
This study described a modified rat model of bone cancer pain. Syngeneic Walker 256 mammary gland carcinoma cells were injected into the tibia medullary cavity via intercondylar eminence. Series of tests were carried out including bone radiology, bone histology, ambulatory pain, thermal hyperalgesia, mechanical allodynia, weight bearing ability, and(More)
As a new way of training generative models, Generative Ad-versarial Nets (GAN) that uses a discriminative model to guide the training of the generative model has enjoyed considerable success in generating real-valued data. However, it has limitations when the goal is for generating sequences of discrete tokens. A major reason lies in that the discrete(More)
In this paper, we study the challenging problem of categorizing videos according to high-level semantics such as the existence of a particular human action or a complex event. Although extensive efforts have been devoted in recent years, most existing works combined multiple video features using simple fusion strategies and neglected the utilization of(More)
Predicting user responses, such as click-through rate and conversion rate, are critical in many web applications including web search, personalised recommendation, and online advertising. Different from continuous raw features that we usually found in the image and audio domains, the input features in web space are always of multi-field and are mostly(More)
Cerebrovascular dysfunction is strongly associated with neonatal intracranial hemorrhage (ICH) and stroke in adults. Cerebrovascular endothelial cells (ECs) play important roles in maintaining a stable cerebral circulation in the central nervous system by interacting with pericytes. However, the genetic mechanisms controlling the functions of cerebral ECs(More)
The human gut microbiota is a reservoir of antibiotic resistance genes, but little is known about their diversity and richness within the gut. Here we analyse the antibiotic resistance genes of gut microbiota from 162 individuals. We identify a total of 1,093 antibiotic resistance genes and find that Chinese individuals harbour the highest number and(More)