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  1. Article ; Online: A TDV attention-based BiGRU network for AIS-based vessel trajectory prediction

    Jin Chen / Jixin Zhang / Hao Chen / Yong Zhao / Hongdong Wang

    iScience, Vol 26, Iss 4, Pp 106383- (2023)

    2023  

    Abstract: Summary: Automatic identification system (AIS) is a vessel-based system for the automatic broadcast and reception of vessel information, and it also supports data for trajectory prediction. Since the vessel’s sailing route is flexible and changeable and ... ...

    Abstract Summary: Automatic identification system (AIS) is a vessel-based system for the automatic broadcast and reception of vessel information, and it also supports data for trajectory prediction. Since the vessel’s sailing route is flexible and changeable and the AIS broadcast is unconfirmed, the trajectory varies greatly and the original AIS data contains some noisy trajectory, which leads to low prediction accuracy and stability. Therefore, to solve the above problem, this paper proposes a trajectory prediction method based on bidirectional gate recurrent unit (BiGRU) and trajectory direction vector (TDV) with attention mechanism. This paper firstly proposes a TDV to associate latitude and longitude with the course and speed. Then the paper proposes an attention mechanism to self-adaptively update weight to the TDV in different stages to eliminate unreasonable predicted trajectory points. Finally, this paper combines the TDV attention mechanism and the BiGRU network to train a vessel trajectory prediction model.
    Keywords Computer science ; Artificial intelligence ; Machine learning ; Science ; Q
    Subject code 620
    Language English
    Publishing date 2023-04-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: A knowledge graph based question answering method for medical domain

    Xiaofeng Huang / Jixin Zhang / Zisang Xu / Lu Ou / Jianbin Tong

    PeerJ Computer Science, Vol 7, p e

    2021  Volume 667

    Abstract: Question answering (QA) is a hot field of research in Natural Language Processing. A big challenge in this field is to answer questions from knowledge-dependable domain. Since traditional QA hardly satisfies some knowledge-dependable situations, such as ... ...

    Abstract Question answering (QA) is a hot field of research in Natural Language Processing. A big challenge in this field is to answer questions from knowledge-dependable domain. Since traditional QA hardly satisfies some knowledge-dependable situations, such as disease diagnosis, drug recommendation, etc. In recent years, researches focus on knowledge-based question answering (KBQA). However, there still exist some problems in KBQA, traditional KBQA is limited by a range of historical cases and takes too much human labor. To address the problems, in this paper, we propose an approach of knowledge graph based question answering (KGQA) method for medical domain, which firstly constructs a medical knowledge graph by extracting named entities and relations between the entities from medical documents. Then, in order to understand a question, it extracts the key information in the question according to the named entities, and meanwhile, it recognizes the questions’ intentions by adopting information gain. The next an inference method based on weighted path ranking on the knowledge graph is proposed to score the related entities according to the key information and intention of a given question. Finally, it extracts the inferred candidate entities to construct answers. Our approach can understand questions, connect the questions to the knowledge graph and inference the answers on the knowledge graph. Theoretical analysis and real-life experimental results show the efficiency of our approach.
    Keywords Knowledge graph ; Medical domain ; Question answering ; Weighted path ranking ; Electronic computers. Computer science ; QA75.5-76.95
    Subject code 400
    Language English
    Publishing date 2021-09-01T00:00:00Z
    Publisher PeerJ Inc.
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Industrial Coagglomeration, Green Innovation, and Manufacturing Carbon Emissions

    Lu Zhang / Renyan Mu / Nigatu Mengesha Fentaw / Yuanfang Zhan / Feng Zhang / Jixin Zhang

    International Journal of Environmental Research and Public Health, Vol 19, Iss 13989, p

    Coagglomeration’s Dynamic Evolution Perspective

    2022  Volume 13989

    Abstract: The achievement of China’s low-carbon development and carbon neutrality depends heavily on the decrease of manufacturing carbon emissions. From coagglomeration’s dynamic evolution perspective, by using panel-threshold-STIRPAT and mediation-STIRPAT models, ...

    Abstract The achievement of China’s low-carbon development and carbon neutrality depends heavily on the decrease of manufacturing carbon emissions. From coagglomeration’s dynamic evolution perspective, by using panel-threshold-STIRPAT and mediation-STIRPAT models, this study examines the relationships among industrial coagglomeration, green innovation, and manufacturing carbon emissions and explores the direct and indirect function mechanisms. Panel data of China’s 30 provinces from 2010 to 2019 are employed. The results imply that, first, the impact of industrial coagglomeration on manufacturing carbon emissions is nonlinear and has significant threshold effects. Industrial coagglomeration negatively affects manufacturing carbon emissions, and as the coagglomeration level deepens, the negative effect has a diminishing trend in marginal utility. Once the coagglomeration degree exceeds a certain threshold, the negative impact becomes insignificant. At present, for 90% of China’s regions, an increase in industrial coagglomeration level can help reduce manufacturing carbon emissions. Second, green innovation is a vital intermediary between industrial coagglomeration and manufacturing carbon emissions. It is a partial intermediary when industrial coagglomeration is at a relatively lower-level stage and a complete intermediary when industrial coagglomeration is at a relatively higher-level stage. These findings reveal the significance of optimizing industrial coagglomeration and the level and efficiency of green innovation to decrease carbon emissions.
    Keywords industrial coagglomeration ; green innovation ; manufacturing carbon emissions ; threshold effect ; mediating effect ; dynamic evolution ; Medicine ; R
    Subject code 670
    Language English
    Publishing date 2022-10-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: Discovery of C19-9 as a novel non-RGD inhibitor of αvβ3 to overcome enzalutamide resistance in castration-resistant prostate cancer

    Xiaocong Pang / Xiaojiao Sun / Yanlun Gu / Xu He / Kan Gong / Song Song / Jixin Zhang / Jie Xia / Zhenming Liu / Yimin Cui

    Signal Transduction and Targeted Therapy, Vol 8, Iss 1, Pp 1-

    2023  Volume 4

    Keywords Medicine ; R ; Biology (General) ; QH301-705.5
    Language English
    Publishing date 2023-02-01T00:00:00Z
    Publisher Nature Publishing Group
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Sensitive system calls based packed malware variants detection using principal component initialized MultiLayers neural networks

    Jixin Zhang / Kehuan Zhang / Zheng Qin / Hui Yin / Qixin Wu

    Cybersecurity, Vol 1, Iss 1, Pp 1-

    2018  Volume 13

    Abstract: Abstract Malware detection has become mission sensitive as its threats spread from computer systems to Internet of things systems. Modern malware variants are generally equipped with sophisticated packers, which allow them bypass modern machine learning ... ...

    Abstract Abstract Malware detection has become mission sensitive as its threats spread from computer systems to Internet of things systems. Modern malware variants are generally equipped with sophisticated packers, which allow them bypass modern machine learning based detection systems. To detect packed malware variants, unpacking techniques and dynamic malware analysis are the two choices. However, unpacking techniques cannot always be useful since there exist some packers such as private packers which are hard to unpack. Although dynamic malware analysis can obtain the running behaviours of executables, the unpacking behaviours of packers add noisy information to the real behaviours of executables, which has a bad affect on accuracy. To overcome these challenges, in this paper, we propose a new method which first extracts a series of system calls which is sensitive to malicious behaviours, then use principal component analysis to extract features of these sensitive system calls, and finally adopt multi-layers neural networks to classify the features of malware variants and legitimate ones. Theoretical analysis and real-life experimental results show that our packed malware variants detection technique is comparable with the the state-of-art methods in terms of accuracy. Our approach can achieve more than 95.6\% of detection accuracy and 0.048 s of classification time cost.
    Keywords Malware variants ; Multi-layers neural networks ; Principal component analysis ; Sensitive system calls ; Sophisticated packers ; Computer engineering. Computer hardware ; TK7885-7895 ; Electronic computers. Computer science ; QA75.5-76.95
    Subject code 006
    Language English
    Publishing date 2018-09-01T00:00:00Z
    Publisher SpringerOpen
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: Ultra-high thermal stability of sputtering reconstructed Cu-based catalysts

    Jiafeng Yu / Xingtao Sun / Xin Tong / Jixin Zhang / Jie Li / Shiyan Li / Yuefeng Liu / Noritatsu Tsubaki / Takayuki Abe / Jian Sun

    Nature Communications, Vol 12, Iss 1, Pp 1-

    2021  Volume 10

    Abstract: Applications of Cu catalysts at high-temperature is a long-sought goal but limited by their serious deactivation due to low copper’s Tammann temperature. Here, the authors introduce an encapsulation layer to improve thermal stability at 800 °C by ... ...

    Abstract Applications of Cu catalysts at high-temperature is a long-sought goal but limited by their serious deactivation due to low copper’s Tammann temperature. Here, the authors introduce an encapsulation layer to improve thermal stability at 800 °C by reconstructing electronic structure of Cu atoms.
    Keywords Science ; Q
    Language English
    Publishing date 2021-12-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article: Modeling and evaluation of the oil-spill emergency response capability based on linguistic variables

    Kang, Jian / Jixin Zhang / Yongqiang Bai

    Marine pollution bulletin. 2016 Dec. 15, v. 113, no. 1-2

    2016  

    Abstract: An evaluation of the oil-spill emergency response capability (OS-ERC) currently in place in modern marine management is required to prevent pollution and loss accidents. The objective of this paper is to develop a novel OS-ERC evaluation model, the ... ...

    Abstract An evaluation of the oil-spill emergency response capability (OS-ERC) currently in place in modern marine management is required to prevent pollution and loss accidents. The objective of this paper is to develop a novel OS-ERC evaluation model, the importance of which stems from the current lack of integrated approaches for interpreting, ranking and assessing OS-ERC performance factors. In the first part of this paper, the factors influencing OS-ERC are analyzed and classified to generate a global evaluation index system. Then, a semantic tree is adopted to illustrate linguistic variables in the evaluation process, followed by the application of a combination of Fuzzy Cognitive Maps (FCM) and the Analytic Hierarchy Process (AHP) to construct and calculate the weight distribution. Finally, considering that the OS-ERC evaluation process is a complex system, a fuzzy comprehensive evaluation (FCE) is employed to calculate the OS-ERC level. The entire evaluation framework obtains the overall level of OS-ERC, and also highlights the potential major issues concerning OS-ERC, as well as expert opinions for improving the feasibility of oil-spill accident prevention and protection.
    Keywords accident prevention ; accidents ; expert opinion ; fuzzy logic ; oil spills ; water pollution
    Language English
    Dates of publication 2016-1215
    Size p. 293-301.
    Publishing place Elsevier Ltd
    Document type Article
    ZDB-ID 2001296-2
    ISSN 1879-3363 ; 0025-326X
    ISSN (online) 1879-3363
    ISSN 0025-326X
    DOI 10.1016/j.marpolbul.2016.09.056
    Database NAL-Catalogue (AGRICOLA)

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  8. Article ; Online: Vaccination induces rapid protection against bacterial pneumonia via training alveolar macrophage in mice

    Hao Gu / Xi Zeng / Liusheng Peng / Chuanying Xiang / Yangyang Zhou / Xiaomin Zhang / Jixin Zhang / Ning Wang / Gang Guo / Yan Li / Kaiyun Liu / Jiang Gu / Hao Zeng / Yuan Zhuang / Haibo Li / Jinyong Zhang / Weijun Zhang / Quanming Zou / Yun Shi

    eLife, Vol

    2021  Volume 10

    Abstract: Vaccination strategies for rapid protection against multidrug-resistant bacterial infection are very important, especially for hospitalized patients who have high risk of exposure to these bacteria. However, few such vaccination strategies exist due to a ...

    Abstract Vaccination strategies for rapid protection against multidrug-resistant bacterial infection are very important, especially for hospitalized patients who have high risk of exposure to these bacteria. However, few such vaccination strategies exist due to a shortage of knowledge supporting their rapid effect. Here, we demonstrated that a single intranasal immunization of inactivated whole cell of Acinetobacter baumannii elicits rapid protection against broad A. baumannii-infected pneumonia via training of innate immune response in Rag1-/- mice. Immunization-trained alveolar macrophages (AMs) showed enhanced TNF-α production upon restimulation. Adoptive transfer of immunization-trained AMs into naive mice mediated rapid protection against infection. Elevated TLR4 expression on vaccination-trained AMs contributed to rapid protection. Moreover, immunization-induced rapid protection was also seen in Pseudomonas aeruginosa and Klebsiella pneumoniae pneumonia models, but not in Staphylococcus aureus and Streptococcus pneumoniae model. Our data reveal that a single intranasal immunization induces rapid and efficient protection against certain Gram-negative bacterial pneumonia via training AMs response, which highlights the importance and the possibility of harnessing trained immunity of AMs to design rapid-effecting vaccine.
    Keywords multidrug-resistant bacteria ; vaccine ; alveolar macrophage ; Trained immunity ; Acinetobacter baumannii ; rapid effect ; Medicine ; R ; Science ; Q ; Biology (General) ; QH301-705.5
    Language English
    Publishing date 2021-09-01T00:00:00Z
    Publisher eLife Sciences Publications Ltd
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article: High and low-virulent bovine Pasteurella multocida capsular type A isolates exhibit different virulence gene expression patterns in vitro and in vivo

    Li, Nengzhang / Chenlu Wu / Guihua Lei / Huihui Du / Jixin Zhang / Philip R. Hardwidge / Qingshan Long / Tingting Pan / Yuanyi Peng

    Veterinary microbiology. 2016 Nov. 30, v. 196

    2016  

    Abstract: Pasteurella multocida capsular type A causes respiratory disease in cattle. P. multocida virulence gene expression patterns, especially among different virulent isolates, during in vitro and in vivo growth are poorly understood. Here we show that the ... ...

    Abstract Pasteurella multocida capsular type A causes respiratory disease in cattle. P. multocida virulence gene expression patterns, especially among different virulent isolates, during in vitro and in vivo growth are poorly understood. Here we show that the highly virulent bovine P. multocida capsular type A isolate PmCQ2 exhibits a significantly higher growth rate in mice, as compared with a strain of lower virulence, P. multocida capsular type A isolate PmCQ6. Among the six known and potential virulence genes (ompA, ompH, pfhB2, hasR, pm0979, and pm0442) investigated, most genes were expressed more highly in both isolates when grown in vivo as compared with in vitro, with ompH and pm0442 having the highest magnitude of expression. Virulence gene expression was higher in PmCQ6 than in PmCQ2 during in vitro growth. However, in mice, most virulence genes were expressed more highly in PmCQ2 as compared with PmCQ6. Virulence gene expression was highest in the liver and lowest in the lung, but was uncorrelated to bacterial loads. This study indicates that individual pathogenic capacity of P. multocida isolates is associated with the virulence gene expression patterns in vivo growth but not in vitro, and the investigation of virulence gene expression in pathogen should be performed in vivo.
    Keywords cattle ; gene expression ; gene expression regulation ; genes ; liver ; mice ; microbial load ; Pasteurella multocida ; pathogens ; respiratory tract diseases ; virulence
    Language English
    Dates of publication 2016-1130
    Size p. 44-49.
    Publishing place Elsevier B.V.
    Document type Article
    ZDB-ID 753154-0
    ISSN 1873-2542 ; 0378-1135
    ISSN (online) 1873-2542
    ISSN 0378-1135
    DOI 10.1016/j.vetmic.2016.10.017
    Database NAL-Catalogue (AGRICOLA)

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