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This paper presents a novel method for feature description based on intensity order. Specifically, a Local Intensity Order Pattern(LIOP) is proposed to encode the local ordinal information of each pixel and the overall ordinal information is used to divide the local patch into subregions which are used for accumulating the LIOPs respectively. Therefore,(More)
Blood–brain barrier (BBB) leakage plays a key role in cerebral ischemia–reperfusion injury. It is quite necessary to further explore the characteristic and mechanism of BBB leakage during stroke. We induced a focal cerebral ischemia model by transient middle cerebral artery occlusion in male rats for defining the time course of BBB permeability within 120 h(More)
With the explosive growth of microblogging services, short-text messages (also known as tweets) are being created and shared at an unprecedented rate. Tweets in its raw form can be incredibly informative, but also overwhelming. For both end-users and data analysts it is a nightmare to plow through millions of tweets which contain enormous noises and(More)
Heroin has been shown to elevate dopamine (DA) level. It is well known that an increase in DA oxidative metabolism leads to increased reactive oxygen species (ROS) formation, and thus, ROS have been frequently associated with neuronal cell death due to damage to carbohydrates, amino acids, phospholipids, and nucleic acids. This study investigated whether(More)
The air-dried aerial parts of Lavandula angustifolia Mill, a traditional Uygur herbal drug, is used as resuscitation-inducing therapy to treat neurodisfunctions, such as stroke. This study was designed to assess the neuroprotective effects of lavender oil against ischemia/reperfusion (IR) injury in mice. Focal cerebral ischemia was induced by the(More)
Human 3D pose estimation from a single image is a challenging task with numerous applications. Convolutional Neural Networks (CNNs) have recently achieved superior performance on the task of 2D pose estimation from a single image, by training on images with 2D annotations collected by crowd sourcing. This suggests that similar success could be achieved for(More)
Convolutional-deconvolution networks can be adopted to perform end-to-end saliency detection. But, they do not work well with objects of multiple scales. To overcome such a limitation, in this work, we propose a recurrent attentional convolutional-deconvolution network (RACDNN). Using spatial transformer and recurrent network units, RACDNN is able to(More)
The aim of our study was to investigate the neuroprotective properties of shikonin, a naphthoquinone pigment isolated from the roots of the traditional Chinese herb Lithospermum erythrorhizon. In the present study, mice were divided randomly into sham, model, shikonin and edaravone-treated groups. Shikonin (50, 25, and 12.5mg/kg, i.g.) or maize oil was(More)
In the last few years, deep learning has lead to very good performance on a variety of problems, such as object recognition, speech recognition and natural language processing. Among different types of deep neural networks, convolutional neural networks have been most extensively studied. Due to the lack of training data and computing power in early days,(More)