Towards Structured Deep Neural Network for Automatic Speech Recognition

In this paper we propose the Structured Deep Neural Network (Structured DNN) as a structured and deep learning algorithm, learning to find the best structured object (such as a label sequence) given a structured input (such as a vector sequence) by globally considering the mapping relationships between the structure rather than item by item. When automatic speech recognition is viewed as a special case of such a structured learning problem, where we have the acoustic vector sequence as the input and the phoneme label sequence as the output, it becomes possible to comprehensively learned utterance by utterance as a whole, rather than frame by frame. Structured Support Vector Machine (structured SVM) was proposed to perform ASR with structured learning previously, but limited by the linear nature of SVM. Here we propose structured DNN to use nonlinear transformations in multi-layers as a structured and deep learning algorithm. It was shown to beat structured SVM in preliminary experiments on TIMIT

Selenium-functionalized carbon as a support for platinum nanoparticles with improved electrochemical properties for the oxygen reduction reaction and CO tolerance

Using selenium-functionalized carbon as supports, platinum nanoparticles were uniformly dispersed on the carbon surface, and showed improved electrochemical properties for the oxygen reduction reaction. At the same time the CO tolerance is improved. The method provides a new route for functionalization of the carbon surface on which to disperse noble metal nanoparticles for use as electrocatalysts in the oxygen reduction reaction.Web of Scienc

Selenium-functionalized carbon as a support for platinum nanoparticles with improved electrochemical properties for the oxygen reduction reaction and CO tolerance

Using selenium-functionalized carbon as supports, platinum nanoparticles were uniformly dispersed on the carbon surface, and showed improved electrochemical properties for the oxygen reduction reaction. At the same time the CO tolerance is improved. The method provides a new route for functionalization of the carbon surface on which to disperse noble metal nanoparticles for use as electrocatalysts in the oxygen reduction reaction.Web of Scienc

Erchen Decoction Prevents High-Fat Diet Induced Metabolic Disorders in C57BL/6 Mice

Erchen decoction (ECD) is a traditional Chinese medicine prescription, which is used in the treatment of obesity, hyperlipidemia, fatty liver, diabetes, hypertension, and other diseases caused by retention of phlegm dampness. In this study we investigated the potential mechanism of ECD, using metabolism-disabled mice induced by high-fat diet. Body weight and abdominal circumference were detected. OGTT was measured by means of collecting blood samples from the tail vein. Blood lipid levels and insulin were measured using biochemical assay kit. Real-time PCR was used to measure the CDKAL1 gene expression and western blot was used to measure the protein expression. Through the research, it was found that ECD showed markedly lower body weight and abdominal circumference than those in the HFD group. Consistently, we observed that ECD significantly improved glucose tolerance, promoted the secretion of insulin and decreased the level of TG, TC level. Meanwhile, we observed significantly increased CDKAL1 mRNA and protein level in the ECD group. Therefore, we speculate that the potential molecular mechanism of ECD is to promote the CDKAL1 expression, ameliorate islet cell function, and raise insulin levels to regulate the metabolic disorder