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  1. Article: First Report of

    Bai, Zhenxu / Chen, Lusheng / Lu, Changming / Ji, Tiancen / Chen, Jie

    Plant disease

    2024  

    Abstract: In September 2022, rice spikelets rot disease (RSRD) was investigated in Songjiang District (30.94132N, 121.18393E), China, leading to a 26.77% yield loss. At the heading stage, infected spikelets exhibited small, yellowish-brown dots with water-stained ... ...

    Abstract In September 2022, rice spikelets rot disease (RSRD) was investigated in Songjiang District (30.94132N, 121.18393E), China, leading to a 26.77% yield loss. At the heading stage, infected spikelets exhibited small, yellowish-brown dots with water-stained husks, subsequently coalescing to form irregular brown to black lesions. Later, the lesions were enlarged and rotted, which eventually caused blighted grains. About 10% of husked grains showed black spots. 30 infected grains and 30 husked grains with black spots were surface sterilized in 75% ethanol for 2 min, then rinsed with ddH
    Language English
    Publishing date 2024-01-24
    Publishing country United States
    Document type Journal Article
    ZDB-ID 754182-x
    ISSN 0191-2917
    ISSN 0191-2917
    DOI 10.1094/PDIS-11-23-2472-PDN
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Bonn / Germany

    Z 2043: Show issues

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  2. Article ; Online: Copper-decorated strategy based on defect-rich NH

    He, Li / Xu, Yuyao / Yang, Zichang / Lu, Xingkai / Yao, Xiaolong / Li, Changming / Xu, Dong / Wu, Chao / Yao, Zhiliang

    Environmental pollution (Barking, Essex : 1987)

    2024  Volume 344, Page(s) 123341

    Abstract: Photocatalysis has received significant attention as a technology that can solve environmental problems. Metal-organic frameworks are currently being used as novel photocatalysts but are still limited by the rapid recombination of photogenerated carriers, ...

    Abstract Photocatalysis has received significant attention as a technology that can solve environmental problems. Metal-organic frameworks are currently being used as novel photocatalysts but are still limited by the rapid recombination of photogenerated carriers, low photogenerated electron migration efficiency and poor solar light utilization rate. In this work, a novel photocatalyst was successfully constructed by introducing Cu species into thermal activated mixed-ligand NH
    MeSH term(s) Copper ; Titanium ; Sulfhydryl Compounds ; Introduced Species ; Sunlight
    Chemical Substances Copper (789U1901C5) ; Titanium (D1JT611TNE) ; methylmercaptan (2X8406WW9I) ; Sulfhydryl Compounds
    Language English
    Publishing date 2024-01-09
    Publishing country England
    Document type Journal Article
    ZDB-ID 280652-6
    ISSN 1873-6424 ; 0013-9327 ; 0269-7491
    ISSN (online) 1873-6424
    ISSN 0013-9327 ; 0269-7491
    DOI 10.1016/j.envpol.2024.123341
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 2599: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  3. Article ; Online: Advances in Machine Learning Processing of Big Data from Disease Diagnosis Sensors.

    Lu, Shasha / Yang, Jianyu / Gu, Yu / He, Dongyuan / Wu, Haocheng / Sun, Wei / Xu, Dong / Li, Changming / Guo, Chunxian

    ACS sensors

    2024  Volume 9, Issue 3, Page(s) 1134–1148

    Abstract: Exploring accurate, noninvasive, and inexpensive disease diagnostic sensors is a critical task in the fields of chemistry, biology, and medicine. The complexity of biological systems and the explosive growth of biomarker data have driven machine learning ...

    Abstract Exploring accurate, noninvasive, and inexpensive disease diagnostic sensors is a critical task in the fields of chemistry, biology, and medicine. The complexity of biological systems and the explosive growth of biomarker data have driven machine learning to become a powerful tool for mining and processing big data from disease diagnosis sensors. With the development of bioinformatics and artificial intelligence (AI), machine learning models formed by data mining have been able to guide more sensitive and accurate molecular computing. This review presents an overview of big data collection approaches and fundamental machine learning algorithms and discusses recent advances in machine learning and molecular computational disease diagnostic sensors. More specifically, we highlight existing modular workflows and key opportunities and challenges for machine learning to achieve disease diagnosis through big data mining.
    MeSH term(s) Artificial Intelligence ; Big Data ; Machine Learning ; Data Mining ; Algorithms
    Language English
    Publishing date 2024-02-16
    Publishing country United States
    Document type Journal Article ; Review
    ISSN 2379-3694
    ISSN (online) 2379-3694
    DOI 10.1021/acssensors.3c02670
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Image local structure information learning for fine-grained visual classification

    Jin Lu / Weichuan Zhang / Yali Zhao / Changming Sun

    Scientific Reports, Vol 12, Iss 1, Pp 1-

    2022  Volume 10

    Abstract: Abstract Learning discriminative visual patterns from image local salient regions is widely used for fine-grained visual classification (FGVC) tasks such as plant or animal species classification. A large number of complex networks have been designed for ...

    Abstract Abstract Learning discriminative visual patterns from image local salient regions is widely used for fine-grained visual classification (FGVC) tasks such as plant or animal species classification. A large number of complex networks have been designed for learning discriminative feature representations. In this paper, we propose a novel local structure information (LSI) learning method for FGVC. Firstly, we indicate that the existing FGVC methods have not properly considered how to extract LSI from an input image for FGVC. Then an LSI extraction technique is introduced which has the ability to properly depict the properties of different local structure features in images. Secondly, a novel LSI learning module is proposed to be added into a given backbone network for enhancing the ability of the network to find salient regions. Thirdly, extensive experiments show that our proposed method achieves better performance on six image datasets. Particularly, the proposed method performs far better on datasets with a limited number of images.
    Keywords Medicine ; R ; Science ; Q
    Subject code 006
    Language English
    Publishing date 2022-11-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Dendrobium officinale polysaccharide alleviates thiacloprid-induced kidney injury in quails via activating the Nrf2/HO-1 pathway.

    Yang, Xu / Guo, Changming / Yu, Lu / Lv, Zhanjun / Li, Siyu / Zhang, Zhigang

    Environmental toxicology

    2024  Volume 39, Issue 5, Page(s) 2655–2666

    Abstract: Thiacloprid (THI) is a neonicotinoid insecticide, and its wide-ranging use has contributed to severe environmental and health problems. Dendrobium officinale polysaccharide (DOP) possesses multiple biological activities such as antioxidant and ... ...

    Abstract Thiacloprid (THI) is a neonicotinoid insecticide, and its wide-ranging use has contributed to severe environmental and health problems. Dendrobium officinale polysaccharide (DOP) possesses multiple biological activities such as antioxidant and antiapoptosis effect. Although present research has shown that THI causes kidney injury, the exact molecular mechanism and treatment of THI-induced kidney injury remain unclear. The study aimed to investigate if DOP could alleviate THI-induced kidney injury and identify the potential molecular mechanism in quails. In this study, Japanese quails received DOP (200 mg/kg) daily with or without THI (4 mg/kg) exposure for 42 days. Our results showed that DOP improved hematological changes, biochemical indexes, and nephric histopathological changes induced by THI. Meanwhile, THI exposure caused oxidative stress, apoptosis, and autophagy. Furthermore, THI and DOP cotreatment significantly activated the nuclear factor erythroid 2-related factor 2/heme oxygenase-1 (Nrf2/HO-1) pathway, restored antioxidant enzyme activity, and reduced apoptosis and autophagy in quail kidneys. In summary, our study demonstrated that DOP mitigated THI-mediated kidney injury was associated with oxidative stress, apoptosis, and autophagy via activation of the Nrf2/HO-1 signaling pathway in quails.
    MeSH term(s) Animals ; Antioxidants/metabolism ; Dendrobium/chemistry ; Dendrobium/metabolism ; NF-E2-Related Factor 2/metabolism ; Quail/metabolism ; Polysaccharides/pharmacology ; Polysaccharides/therapeutic use ; Polysaccharides/chemistry ; Oxidative Stress ; Neonicotinoids/toxicity ; Thiazines
    Chemical Substances Antioxidants ; thiacloprid (DSV3A944A4) ; NF-E2-Related Factor 2 ; Polysaccharides ; Neonicotinoids ; Thiazines
    Language English
    Publishing date 2024-01-15
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1463449-1
    ISSN 1522-7278 ; 1520-4081
    ISSN (online) 1522-7278
    ISSN 1520-4081
    DOI 10.1002/tox.24137
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 2676: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  6. Article: Effect of

    Jiao, Peixin / Wang, Ziwei / Wang, Xin / Zuo, Yanan / Yang, Yuqing / Hu, Guanghui / Lu, Changming / Xie, Xiaolai / Wang, Li / Yang, Wenzhu

    Frontiers in microbiology

    2022  Volume 13, Page(s) 912042

    Abstract: Clostridium ... ...

    Abstract Clostridium butyricum
    Language English
    Publishing date 2022-06-23
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2587354-4
    ISSN 1664-302X
    ISSN 1664-302X
    DOI 10.3389/fmicb.2022.912042
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Image local structure information learning for fine-grained visual classification.

    Lu, Jin / Zhang, Weichuan / Zhao, Yali / Sun, Changming

    Scientific reports

    2022  Volume 12, Issue 1, Page(s) 19205

    Abstract: Learning discriminative visual patterns from image local salient regions is widely used for fine-grained visual classification (FGVC) tasks such as plant or animal species classification. A large number of complex networks have been designed for learning ...

    Abstract Learning discriminative visual patterns from image local salient regions is widely used for fine-grained visual classification (FGVC) tasks such as plant or animal species classification. A large number of complex networks have been designed for learning discriminative feature representations. In this paper, we propose a novel local structure information (LSI) learning method for FGVC. Firstly, we indicate that the existing FGVC methods have not properly considered how to extract LSI from an input image for FGVC. Then an LSI extraction technique is introduced which has the ability to properly depict the properties of different local structure features in images. Secondly, a novel LSI learning module is proposed to be added into a given backbone network for enhancing the ability of the network to find salient regions. Thirdly, extensive experiments show that our proposed method achieves better performance on six image datasets. Particularly, the proposed method performs far better on datasets with a limited number of images.
    MeSH term(s) Neural Networks, Computer ; Machine Learning ; Information Storage and Retrieval
    Language English
    Publishing date 2022-11-10
    Publishing country England
    Document type Journal Article
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-022-23835-0
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: A Comparative Study of the Landfall Precipitation by Tropical Cyclones ARB 01 (2002) and Luban (2018) near the Arabian Peninsula

    Yusheng Cui / Haibin Lü / Dawei Shi / Chuqi Xia / Changming Dong

    Remote Sensing, Vol 14, Iss 1194, p

    2022  Volume 1194

    Abstract: Considering the high risk of flooding during tropical cyclones (TCs), there is great practical significance in researching and predicting precipitation during TC landfalls. Using NECP FNL reanalysis data and GPM_MERGIR datasets, two TCs with similar ... ...

    Abstract Considering the high risk of flooding during tropical cyclones (TCs), there is great practical significance in researching and predicting precipitation during TC landfalls. Using NECP FNL reanalysis data and GPM_MERGIR datasets, two TCs with similar trajectories, ARB 01 in 2002 and Luban in 2018, were analyzed. For ARB 01 and Luban, there are separate effects of wind shear at different heights on the development of vertical motion. Meridional wind shear affects the main deviation direction of vertical motion (downshear), while zonal wind shear mainly affects the deviation direction of vertical motion to the left or right of downshear. The divergent configuration of wind promotes the development of vertical motion. The influence of wind speed provided ideal conditions for ARB 01 to generate symmetric precipitation along its path when it made landfall. Additionally, more water vapor support was obtained from the southern Indian Ocean, which enabled ARB 01 to have a larger and broader average precipitation rate after landing.
    Keywords tropical cyclones ; precipitation ; extreme tropical cyclone precipitation ; extreme precipitation ; Arabian Sea ; Science ; Q
    Subject code 551 ; 910
    Language English
    Publishing date 2022-02-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article ; Online: Jin-Wu-Jian-Gu Formulation Attenuates Rheumatoid Arthritis by Inhibiting the IL33-ST2 Signaling Pathway

    Daomin Lu / Ying Huang / Wukai Ma / Changming Chen / Lei Hou

    Evidence-Based Complementary and Alternative Medicine, Vol

    2022  Volume 2022

    Abstract: The present research attempted to investigate the molecular mechanism of Jin-Wu-Jian-Gu Formulation (JWJGF) in inhibiting rheumatoid arthritis (RA) in a pharmacological approach for analysis and experimental validation. First, the potential targets and ... ...

    Abstract The present research attempted to investigate the molecular mechanism of Jin-Wu-Jian-Gu Formulation (JWJGF) in inhibiting rheumatoid arthritis (RA) in a pharmacological approach for analysis and experimental validation. First, the potential targets and pathways of JWJGF for RA were predicted by network pharmacology. Second, the effect of JWJGF on RA was observed by hematoxylin-eosin (HE) staining and enzyme-linked immunosorbent assay (ELISA). Further, we observed the effects of JWJGF on the IL33-ST2 signaling pathway by Western blot and quantitative real-time PCR (qPCR) experiments, and finally, we studied the effects of Liquiritigenin on rheumatoid arthritis synovial fibroblast (RASF) cells and the IL33-ST2 signaling pathway. Network pharmacology results showed that the key component of JWJGF was Liquiritigenin and the core target of JWJGF was IL-33. The results of HE and ELISA showed that JWJGF could alleviate RA. Western blot and qPCR findings indicated that JWJGF could inhibit the IL33-ST2 signaling pathway. Furthermore, JWJGF could inhibit the proliferation of RASF cells and the IL33-ST2 signaling pathway. In conclusion, this study revealed that JWJGF attenuated RA by inhibiting the IL33-ST2 signaling pathway.
    Keywords Other systems of medicine ; RZ201-999
    Language English
    Publishing date 2022-01-01T00:00:00Z
    Publisher Hindawi Limited
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Book ; Online: Track-before-detect Algorithm based on Cost-reference Particle Filter Bank for Weak Target Detection

    Lu, Jin / Peng, Guojie / Zhang, Weichuan / Sun, Changming

    2023  

    Abstract: Detecting weak target is an important and challenging problem in many applications such as radar, sonar etc. However, conventional detection methods are often ineffective in this case because of low signal-to-noise ratio (SNR). This paper presents a ... ...

    Abstract Detecting weak target is an important and challenging problem in many applications such as radar, sonar etc. However, conventional detection methods are often ineffective in this case because of low signal-to-noise ratio (SNR). This paper presents a track-before-detect (TBD) algorithm based on an improved particle filter, i.e. cost-reference particle filter bank (CRPFB), which turns the problem of target detection to the problem of two-layer hypothesis testing. The first layer is implemented by CRPFB for state estimation of possible target. CRPFB has entirely parallel structure, consisting amounts of cost-reference particle filters with different hypothesized prior information. The second layer is to compare a test metric with a given threshold, which is constructed from the output of the first layer and fits GEV distribution. The performance of our proposed TBD algorithm and the existed TBD algorithms are compared according to the experiments on nonlinear frequency modulated (NLFM) signal detection and tracking. Simulation results show that the proposed TBD algorithm has better performance than the state-of-the-arts in detection, tracking, and time efficiency.
    Keywords Electrical Engineering and Systems Science - Signal Processing
    Subject code 006
    Publishing date 2023-09-25
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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