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Designing logic gates based on 3-way DNAzyme complex

Analytical Methods 2019年第5期12卷 693-700页

作者： Donglin Liu Yuan Liu Bin Wang Qiang Zhang Key Laboratory of Advanced Design and Intelligent Computing Dalian University Ministry of Education Dalian 116622 China School of Computer Science and Technology Dalian University of Technology Dalian China

In recent years, DNA has been regarded as a reliable raw material for building biological computers and biochips due to its nanoscale size, ultralow energy consumption, and high-performance computing potential. As the basis of building a biological computer, the research on the construction of nanoscale logic arithmetic and nanoscale biochemical logic circuits based on DNA molecules as carriers has attracted increasing attention. Although researchers use DNA strand replacement systems to achieve it this requires adjustment and careful design of the toehold, making sequence selection more difficult. To reduce dependence on the toehold, we propose a 3-way DNAzyme complex composed of three E6 DNAzymes assembled using the biological characteristics of E6 DNAzyme. This complex enriched the recognition vector of E6 DNAzyme, which can be used for multiple substrates, thus improving the reusability and efficiency of DNA molecules. At the same time, based on the 3-way DNAzyme complex and without the involvement of the toehold, we designed logic gates such as the OR gate, the AND gate, and the INHIBIT gate, and realized the construction of a new half subtractor and nanoscale biochemical logic circuit. These explorations and attempts extended the practicality of the 3-way DNAzyme complex. We believe that these logic elements will have a wide range of applications in DNA nanoscale programming, biological computing, and nanoscale medicine.

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False news detection on social media

arXiv

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arXiv 2019年

作者： Cao, Juan Sheng, Qiang Qi, Peng Zhong, Lei Wang, Yanyan Zhang, Xueyao Key Laboratory of Intelligent Information Processing Center for Advanced Computing Research Institute of Computing Technology CAS Beijing China University of Chinese Academy of Sciences Beijing China

Social media has become an important information platform where people consume and share news. However, it has also enabled the wide dissemination of false news, i.e., news posts published on social media that are verifiably false, causing significant negative effects on society. To help prevent further propagation of false news on social media, we set up this competition to motivate the development of automated real-time false news detection approaches. Specifically, this competition includes three subtasks: false-news text detection, false-news image detection, and falsenews multi-modal detection, which aims to motivate participants to further explore the efficiency of multiple modalities in detecting false news and effective fusion approaches of multi-modal contents. To better support this competition, we also construct and release a multi-modal data repository about False News on Weibo Social platform(MCG-FNeWS) to help evaluate the performance of different approaches from participants. Copyright © 2019, The Authors. All rights reserved.

关键词： Social networking (online)

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Exploring Multi-level Mutual Information for Drug-target Interaction Prediction

Exploring Multi-level Mutual Information for Drug-target Int...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Jiatao Chen Liang Zhang Ke Cheng Bo Jin Xinjiang Lu Chao Che Yiwei Liu Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China International Business College Dongbei University of Finance and Economics Dalian China School of Computer Science and Technology Dalian University of Technology Dalian China Business Intelligence Lab Baidu Research

ISBN: (数字)9781728162157

ISBN: (纸本)9781728162164

Recent advances in graph representation learning provide new opportunities for computational drug-target interaction (DTI) prediction. Inspired by the emerging graph mutual information-based algorithms, we propose MMIDTI, a multi-level mutual information-aware DTI prediction framework based on a heterogeneous network (i.e., drug-protein, drug-drug and protein-protein interaction network; drug-disease, drug-side-effect, and protein-disease association network; drug-structure and protein-sequence similarity network). More specifically, MMIDTI leverages an encoder-decoder framework that can learn the type-aware and meta-path augmented node representations by following a contrastive learning paradigm. The encoder part is a Graph Convolutional Network (GCN) and the decoder is an inner product of the learned representations to recover the original heterogeneous network. Meanwhile, MMIDTI exploits two levels of mutual information: (1) maximizing local mutual information, to obtain node representations that capture the global information content of the entire heterogeneous graph. (2) maximizing the global mutual information, to constrain the node representation to have desired statistical characteristics. Experimental results show that our model can achieve better prediction performance than state-of-the-art methods.

关键词： Mutual information Proteins Drugs Predictive models Diffusion tensor imaging Heterogeneous networks Task analysis

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A Novel Spatial-Temporal Convolutional Neural Network for Remote Photoplethysmography

A Novel Spatial-Temporal Convolutional Neural Network for Re...

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International Congress on Image and Signal Processing, BioMedical Engineering and Informatics

作者： Min Hu Dong Guo Xiaohua Wang Peng Ge Qian Chu School of Computer and Information of Hefei University of Technology Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei China

Remote photoplethysmography (rPPG) using a simple consumer-level webcam has great potential for healthcare, human-computer interaction, affective computing, and many other fields. However, traditional methods based on the skin reflection model and signal processing achieved limited success. Thus, this paper presents a novel end-to-end spatial-temporal convolutional neural network for the rPPG recovering task: To preserve the details, the pooling layer is moved to the branch network, and the attention mechanism is used to enhance the backbone network performance. Moreover, the ConvLSTM was used to learn the relationship between frames. The manual features extraction and signal post-processing steps can be omitted through our end-to-end neural network. The experimental results conducted on PURE and COHFACE datasets show that the proposed method significantly improved the quality of the recovered rPPG signal.

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Facial Expression Recognition Based on Contextual Generative Adversarial Network

Facial Expression Recognition Based on Contextual Generative...

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IEEE International Conference on Cloud computing and Intelligence Systems (CCIS)

作者： Qian Chu Min Hu Xiaohua Wang Yu Gu Tian Chen Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information Hefei University of Technology Hefei Anhui China

ISBN: (数字)9781728138633

ISBN: (纸本)9781728138640

In recent years, deep neural networks have been widely concerned by researchers in facial expression recognition. However, insufficient facial training data of the public available database is a major challenge in deep learning, which will lead to an obvious decrease in the effectiveness of learning result; many data augmentation techniques have thus been widely used to enrich the training dataset. In this paper, we introduce a contextual loss function to construct a Contextual Generation Adversarial Network with one generator and one discriminator. The proposed method can map the neutral expression to six basic expressions to expand the database. The experimental results on CK + and KDEF databases show that the proposed method can effectively improve the ability to extract facial features and the ability to generate higher quality images. The data augmentation used the proposed method improves the recognition rate of facial expressions on KDEF and CK + datasets.

关键词： XML

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Improved Modular Convolution Neural Network for Human Pose Estimation 12th

Improved Modular Convolution Neural Network for Human Pose E...

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12th International Conference on e-Learning and Games, Edutainment 2018

作者： Zhang, Zhengxuan Dong, Jing Zhou, Dongsheng Fang, Xiaoyong Wei, Xiaopeng Key Laboratory of Advanced Design and Intelligent Computing Dalian University Ministry of Education Dalian116622 China School of Computer Science and Technology Dalian University of Technology Dalian1160243 China Research Institute of Human Factors and Safety Engineering Hunan Institute of Technology HengyangHunan Province421002 China

ISBN: (纸本)9783030237110

Human pose estimation in image is an important branch of computer vision and graphics research. In this paper, an improved modular convolution neural network is proposed to solve the problem of human pose estimation in static 2D images. A cascaded three-stage full convolutional network (FCN) can learn the non-linear mapping from image feature space to human pose space in an end-to-end way. In order to improve the accuracy of predicting joints, the method of multi-feature source fusion is adopted to improve the estimation process of the human body posture. The first two stages of the network focus on learning local image features and joints neighborhood pixel features, and these features are merged in the third stage of the network. Finally, the coordinates of human joints are obtained by regression of the merged features. In our experiments, using the strict PCP criteria on the full body pose dataset LSP, the average prediction accuracy of our method is 79.3%. In addition, using the PCKh standard on the upper body pose dataset FLIC, our method achieves an average prediction accuracy of 93% without additional training. © 2019, Springer Nature Switzerland AG.

关键词： Forecasting

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Research on Speech Synthesis Technology Based on Rhythm Embedding

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Journal of Physics: Conference Series 2020年第1期1693卷

作者： Tianxin Wu Lasheng Zhao Qiang Zhang Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian 116622 China

In recent years, Text-To-Speech (TTS) technology has developed rapidly. People have also been paying more attention to how to narrow the gap between synthetic speech and real speech, hoping that synthesized speech can be integrated with real rhythm. A rhythmic feature embedding method for Text-To-Speech was proposed in this thesis based on Tacotron2 model, which has arisen in the field of TTS in recent years. Firstly, rhythmic feature extraction through World vocoder can reduce redundant information in rhythmic features. Then, rhythmic feature fusion based on Variational Auto-Encoder (VAE) network can enhance rhythmic information. Experiments are carried out on the data set LJSpeech-1.0, and then subjective evaluation and objective evaluation are carried out on the synthesized speech respectively. Compared with the comparative literature, the subjective blind hearing test (ABX) score increased by 25%. At that same time, the objective Mel Cepstral Distortion value (MCD) declined to 12.77.

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A meta-inspired termite queen algorithm for global optimization and engineering design problems

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Engineering Applications of Artificial Intelligence 2022年 111卷

作者： Peng Chen Shihua Zhou Qiang Zhang Nikola Kasabov Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian 116622 China School of Computer Science and Technology Dalian University of Technology Dalian 116024 China Knowledge Engineering and Discovery Research Institute Auckland University of Technology Auckland 1010 New Zealand Intelligent Systems Research Center Ulster University Londonderry BT52 1SA UK

This paper proposes a novel bio-inspired termite queen algorithm (TQA) to solve optimization problems by simulating the division of labor in termite populations under a queen’s rule. TQA is benchmarked on a set of 23 functions to test its performance at solving global optimization problems, and applied to six real-world engineering design problems to verify its reliability and effectiveness. Comparative simulation studies with other algorithms are conducted, from whose results it is observed that TQA satisfactorily solves global optimization problems and engineering design problems.

关键词： Termite queen algorithm Benchmarked functions Loss minimization Metaheuristic technique Engineering design problems

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Suppression and facilitation of motion perception in humans: A reply to Schallmo & Murray (2018)

arXiv

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arXiv 2019年

作者： Tzvetanov, Tzvetomir Anhui Province Key Laboratory of Affective Computing Advanced Intelligent Machine School of Computer Science and Information Engineering Hefei University of Technology Hefei China

In a recent publication (Tzvetanov (2018), bioRxiv 465807), I made an extensive analysis with computational modelling and psychophysics of the simple experimental design of Dr. *** (Tadin, Lappin, Gilroy and Blake (2003), Nature, 424:312-315) about motion perception changes in humans due to size and contrast of the stimulus. This publication sparked from strong claims made in Schallmo et al. (2018) (eLife, 7:e30334) about two important points: (1) "divisive normalization", not inhibitory and excitatory mechanisms, creates the observed psychophysical results and (2) drug-enhanced inhibition showed perceptual outcomes that hint to "weaker suppression" (i.e. inhibition) not stronger "suppression". Schallmo & Murray (2018, bioRxiv, 495291) presented concerns about my extensive publication, specifically about the parts where I directly analysed some of their methods, results and claims. Here, I show that their concerns do not provide clear answers to my specific points and further do not mention other major critiques of data interpretation and modelling of this experimental design. Therefore, I maintain all my claims that were elaborated in details in my first publication (Tzvetanov, 2018, bioRxiv 465807): the specific ones that analyse the results of their and other studies, but also the more broad modelling that is applicable to any study using the simple experimental design of Dr. ***. Copyright © 2019, The Authors. All rights reserved.

关键词： Statistics

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Logic Operation Model of the Complementer Based on Two-domain DNA Strand Displacement

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Fundamenta Informaticae 2019年第2-3期164卷 277-288页

作者： Xie, Wendan Zhou, Changjun Lv, Hui Zhang, Qiang Key Laboratory of Advanced Design and Intelligent Computing Dalian University of Technology ChinaMinistry of Education Dalian University Dalian China School of Computer Science and Technology Dalian University of Technology Dalian China.

DNA strand replacement technology has the advantages of simple operation which makes it becomes a common method of DNA computing. A four bit binary number Complementer based on two-domain DNA strand displacement is proposed in this paper. It implements the function of converting binary code into complement code. Simulation experiment based on Visual DSD software is carried out. The simulation results show the correctness and feasibility of the logic model of the Complementer, and it makes useful exploration for further expanding the application of molecular logic circuit.

关键词： Two-Domain DNA Strand Displacement Complementer Logic Circuit

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