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In this work, we conducted a case study of a popular Chinese microblogging site, Sina-Weibo, to investigate how Chinese netizens used microblogging in response to a major disaster: the 2010 Yushu Earthquake. We combined multiple analysis methods in this case study, including content analysis of microblog messages, trend analysis of different topics, and an(More)
Signatures and handwriting have long played a role in dayto-day business transactions and in forensics, e.g., to authenticate documents, as evidence to establish crime or innocence, etc. The individuality of handwriting and signatures is the basis for their relevance to authentication and forensics. This very individuality makes them also potentially useful(More)
A system for spotting words in scanned document images in three scripts, Devanagari, Arabic and Latin is described. Three main components of the system are a word segmenter, a shape based matcher for words and a search interface. The user gives a query which can be either a word image or text. The candidate words that are searched in the documents are(More)
The hypoxic conditions at high altitudes present a challenge for survival, causing pressure for adaptation. Interestingly, many high-altitude denizens (particularly in the Andes) are maladapted, with a condition known as chronic mountain sickness (CMS) or Monge disease. To decode the genetic basis of this disease, we sequenced and compared the whole genomes(More)
Data in vision domain often exhibit highly-skewed class distribution, i.e., most data belong to a few majority classes, while the minority classes only contain a scarce amount of instances. To mitigate this issue, contemporary classification methods based on deep convolutional neural network (CNN) typically follow classic strategies such as class(More)
We present an approach for recognizing human attributes in unconstrained settings. We train a Convolutional Neural Network (CNN) to select the most attribute-descriptive human parts from all poselet detections, and combine them with the whole body as a pose-normalized deep representation. We further improve by using deep hierarchical contexts ranging from(More)
MicroRNAs are a group of small non-coding RNAs that modulate gene expression. The de-regulation of microRNA expression has been found in several types of cancer. To study the role of microRNAs in gastric cancer (GC), we analyzed the expression profile of 847 microRNAs in GC from Chinese patients. Total RNA was used for hybridization on the miRCURY LNA Array(More)
BACKGROUND Hypoxia-induced renal tubular cell epithelial-mesenchymal transition (EMT) is an important event leading to renal fibrosis. MicroRNAs (miRNAs) are small non-coding RNA molecules that bind to their mRNA targets, thereby leading to translational repression. The role of miRNA in hypoxia-induced EMT is largely unknown. METHODOLOGY/PRINCIPAL(More)
Our previous studies have shown that 100 Hz electroacupuncture (EA) produced antinociception through the release of endogenous opioids (mainly dynorphin) and the activated kappa-opioid receptors in normal rats. Acupuncture is an effective treatment in relieving pain, but it develops tolerance after repeated administration. It has been reported that(More)