Search results for: Mingxing Xu
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Journal of Experimental & Clinical Cancer Research > 2019 > 38 > 1 > 1-15
Background Gallbladder cancer (GBC) is the most malignant cancer occurring in the biliary tract cancer featured with undesirable prognosis, in which most patients die within a year of cholecystectomy. Long noncoding RNAs (lncRNAs) function as critical regulators of multiple stages of cancers. Herein, the mechanism of lncRNA metastasis associated lung adenocarcinoma transcript 1 (MALAT1) in GBC is...
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BMC Infectious Diseases > 2019 > 19 > 1 > 1-9
Background Quinine (QN) remains an effective drug for malaria treatment. However, quinine resistance (QNR) in Plasmodium falciparum has been reported in many malaria-endemic regions particularly in African countries. Genetic polymorphism of the P. falciparum Na+/H+ exchanger (pfnhe1) is considered to influence QN susceptibility. Here, ms4760 alleles of pfnhe1 were analysed from imported African P. falciparum...
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World Journal of Surgical Oncology > 2019 > 17 > 1 > 1-9
Background The effect of antiviral therapy (AVT) on clinical outcomes in patients with hepatocellular carcinoma (HCC) who are seronegative for hepatitis B virus (HBV), defined as HBV DNA < 100 IU/ml prior to surgical resection, is unknown. The main purpose of this study was to evaluate the possible value of AVT in this cohort of patients. Methods From January 2006 to January 2013, 161 HCC patients...
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World Journal of Surgical Oncology > 2017 > 15 > 1 > 1-10
Background It is generally accepted that an insufficient future liver remnant is a major limitation of large-scale hepatectomy for patients with primary hepatocellular carcinoma. Conventional two-stage hepatectomy (TSH) is commonly considered to accelerate future liver regeneration despite its low regeneration rate. Associating liver partition and portal vein ligation for staged hepatectomy (ALPPS),...
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Bidirectional long short-term memory (BLSTM) recurrent neural network (RNN) has achieved state-of-the-art performance in many sequence processing problems given its capability in capturing contextual information. However, for languages with limited amount of training data, it is still difficult to obtain a high quality BLSTM model for emphasis detection, the aim of which is to recognize the emphasized...
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A novel speaker segmentation approach based on deep neural network is proposed and investigated. This approach uses deep speaker vectors (d-vectors) to represent speaker characteristics and to find speaker change points. The d-vector is a kind of frame-level speaker discriminative feature, whose discriminative training process corresponds to the goal of discriminating a speaker change point from a...
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Speech emotion recognition is a challenging and significant task. On the one hand, the emotion features need to be robust enough to capture the emotion information, and while on the other, machine learning algorithms need to be insensitive to model the utterance. In this paper, we presented a novel framework of speech emotion recognition to address the two above-mentioned challenges. Relative Entropy...
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Recognizing stances is of great importance to understand intention of human beings. While previous related researches mainly focused on text modality, in this paper, we aim to combine textual and acoustic features to automatically recognize stances in social debates. For acoustic features, we find that speaking rate is an indispensable feature to distinguish whether speaker is taking a stance or not...
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Dynamic Music Emotion Prediction is crucial to the emerging applications of music retrieval and recommendation. Considering the influence of temporal context and hierarchical structure on emotion in music, we propose a Deep Bidirectional Long Short-Term Memory (DBLSTM) based multi-scale regression method. In this method, a post-processing component is utilised for individual DBSLTM output to further...
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Personality prediction has broad prospects of application in real life. It can be accomplished by analyzing massive and variant data in social networks, which conveys one's personal traits through user generated contents, user's social relationships and behaviors. However, it is difficult to design an effective feature representation from such complex data to predict user's personality as well as...
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Question detection is of importance for many speech applications. Only parts of the speech utterances can provide useful clues for question detection. Previous work of question detection using acoustic features in Mandarin conversation is weak in capturing such proper time context information, which could be modeled essentially in recurrent neural network (RNN) structure. In this paper, we conduct...
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Music Dynamic Emotion Prediction is a challenging and significant task. In this paper, We adopt the dimensional valence-arousal (V-A) emotion model to represent the dynamic emotion in music. Considering the high context correlation among the music feature sequence and the advantage of Bidirectional Long Short-Term Memory (BLSTM) in capturing sequence information, we propose a multi-scale approach,...
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Dynamic music emotion prediction is to recognize the continuous emotion contained in music, and has various applications. In recent years, dynamic music emotion recognition is widely studied, while the inside structure of the emotion in music remains unclear. We conduct a data observation based on the database provided by Free Music Archive (FMA), and find that emotion dynamic shows different properties...
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This paper introduces the database of Traditional Chinese Opera for Music Genre Recognition, which is still a gap in our knowledge. The database contains different songs which are from the 14 most popular kinds of Chinese Opera, including Sichuan Opera, Beijing Opera, etc. Each Opera is then annotated between music, song and speech which are identified by acoustic waveform and spectral analysis. This...
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Intrinsic variation is one of the major factors that aggravate performance of speaker verification system dramatically. In this paper, we focus on alleviating influence caused by intrinsic variation using sparse representation. Because the over-complete dictionary increases the flexibility and the ability to adapt to variable data in signal representation, we expect redundancy of the dictionary could...
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Though emotion speech recognition has gained increasing interest in the field of Human Computer Interaction, it is still a challenge to automatically determine the emotion state type and the boundaries of each emotionally salient segment in continuous speech, which is named as Automatic Emotion Variation Detection (AEVD). In this task, the input utterances are not pre-segmented and may contain emotion...
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Emotion recognition from speech plays an important role in developing affective and intelligent Human Computer Interaction. The goal of this work is to build an Automatic Emotion Variation Detection (AEVD) system to determine each emotional salient segment in continuous speech. We focus on emotion detection in angry-neutral speech, which is common in recent studies of AEVD. This study proposes a novel...
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In this paper, a novel method based on feedforward neural network is proposed to optimize the confidence measure for improving a mandarine keyword spotting system. Keyword spotting is to detect the occurrences of a pre-defined list of keywords in the input speech, and confidence measure is an critical part in the verification stage of keyword spotting. Posterior confidence has been widely used and...
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In this paper, the flight control system of a flying-wing aircraft is designed. Significant dynamic nonlinearity and control redundancy are main problems for a flying-wing aircraft. As the over-actuated system and dynamic nonlinearity, the flight control system is divided into two parts: control laws and control allocation. Nonlinear dynamic inversion is used to design the control laws to generate...
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The active disturbance rejection control (ADRC) techniques based on nonlinear dynamic inversion (NDI) method were proposed for a tailless unmanned aerial vehicle nonlinear flight control law design problem. The dynamics to be controlled were separated into two groups. For each group the corresponding control loop could be designed and the integrated controller was constructed by cascading them. The...
