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  1. Article ; Online: Technical Foundation, External Environment, and Government Internet Service Capability

    Tian Jin / Cheng Dong

    SAGE Open, Vol

    Evidence From China

    2023  Volume 13

    Abstract: This study examines the influencing factors of the local government’s Internet service capability construction in China. The research framework for this study was the “technology-organization-environment” (TOE) framework. A total of 277 local governments ...

    Abstract This study examines the influencing factors of the local government’s Internet service capability construction in China. The research framework for this study was the “technology-organization-environment” (TOE) framework. A total of 277 local governments were collected from Chinese cities and used for the data analysis. The data analysis was conducted with Stata. The results of this research demonstrated that there is a significant positive correlation between information technology talents, peer pressure, leader attachment, sustainable competitiveness, data open platform, and the government’s Internet service capability. Surprisingly, there is a negative correlation between per capita budget expenditure and the government’s Internet service capability. The aforementioned conclusions hold even after the robustness test. Discussion is held regarding how these conclusions may affect the development of the government’s Internet service capability.
    Keywords History of scholarship and learning. The humanities ; AZ20-999 ; Social Sciences ; H
    Subject code 303
    Language English
    Publishing date 2023-10-01T00:00:00Z
    Publisher SAGE Publishing
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article: A Novel Variant of Deformed Wing Virus (DWV) from the Invasive Honeybee

    Tian, Jin-Xuan / Tsai, Wen-Shi / Sung, I-Hsin

    Insects

    2023  Volume 14, Issue 2

    Abstract: The invasion ... ...

    Abstract The invasion of
    Language English
    Publishing date 2023-01-18
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2662247-6
    ISSN 2075-4450
    ISSN 2075-4450
    DOI 10.3390/insects14020103
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Variable Rate Point Cloud Geometry Compression Method.

    Zhuang, Lehui / Tian, Jin / Zhang, Yujin / Fang, Zhijun

    Sensors (Basel, Switzerland)

    2023  Volume 23, Issue 12

    Abstract: With the development of 3D sensors technology, 3D point cloud is widely used in industrial scenes due to their high accuracy, which promotes the development of point cloud compression technology. Learned point cloud compression has attracted much ... ...

    Abstract With the development of 3D sensors technology, 3D point cloud is widely used in industrial scenes due to their high accuracy, which promotes the development of point cloud compression technology. Learned point cloud compression has attracted much attention for its excellent rate distortion performance. However, there is a one-to-one correspondence between the model and the compression rate in these methods. To achieve compression at different rates, a large number of models need to be trained, which increases the training time and storage space. To address this problem, a variable rate point cloud compression method is proposed, which enables the adjustment of the compression rate by the hyperparameter in a single model. To address the narrow rate range problem that occurs when the traditional rate distortion loss is jointly optimized for variable rate models, a rate expansion method based on contrastive learning is proposed to expands the bit rate range of the model. To improve the visualization effect of the reconstructed point cloud, a boundary learning method is introduced to improve the classification ability of the boundary points through boundary optimization and enhance the overall model performance. The experimental results show that the proposed method achieves variable rate compression with a large bit rate range while ensuring the model performance. The proposed method outperforms G-PCC, achieving more than 70% BD-Rate against G-PCC, and performs about, as well as the learned methods at high bit rates.
    MeSH term(s) Physical Phenomena ; Data Compression ; Industry ; Learning ; Technology
    Language English
    Publishing date 2023-06-09
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2052857-7
    ISSN 1424-8220 ; 1424-8220
    ISSN (online) 1424-8220
    ISSN 1424-8220
    DOI 10.3390/s23125474
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  4. Book ; Online: Neural Interpretation of Generic Source Code

    Hu, Yaojie / Tian, Jin

    2023  

    Abstract: Can a generic (Python) program be executed statement-by-statement by neural networks composed according to the source code? We formulate the Abstract Neural Execution Problem and introduce Neural Interpretation, the first neural model that abstractly ... ...

    Abstract Can a generic (Python) program be executed statement-by-statement by neural networks composed according to the source code? We formulate the Abstract Neural Execution Problem and introduce Neural Interpretation, the first neural model that abstractly executes generic source code, where every variable has a vector encoding, and every function executes a neural network. Neural Interpretation is a model of computers with a compiler architecture, which can assemble neural layers ''programmed'' by partial source code. Neural Interpretation can be trained with flexible learning objectives. We demonstrate white-box execution without concrete inputs for variable misuse localization and repair.
    Keywords Computer Science - Artificial Intelligence ; Computer Science - Machine Learning
    Publishing date 2023-03-23
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Deep Learning-Based Enhanced ISAR-RID Imaging Method

    Xiurong Wang / Yongpeng Dai / Shaoqiu Song / Tian Jin / Xiaotao Huang

    Remote Sensing, Vol 15, Iss 21, p

    2023  Volume 5166

    Abstract: Inverse synthetic aperture radar (ISAR) imaging can be improved by processing Range-Instantaneous Doppler (RID) images, according to a method proposed in this paper that uses neural networks. ISAR is a significant imaging technique for moving targets. ... ...

    Abstract Inverse synthetic aperture radar (ISAR) imaging can be improved by processing Range-Instantaneous Doppler (RID) images, according to a method proposed in this paper that uses neural networks. ISAR is a significant imaging technique for moving targets. However, scatterers span across several range bins and Doppler bins while imaging a moving target over a large accumulated angle. Defocusing consequently occurs in the results produced by the conventional Range Doppler Algorithm (RDA). Defocusing can be solved with the time-frequency analysis (TFA) method, but the resolution performance is reduced. The proposed method provides the neural network with more details by using a string of RID frames of images as input. As a consequence, it produces better resolution and avoids defocusing. Furthermore, we have developed a positional encoding method that precisely represents pixel positions while taking into account the features of ISAR images. To address the issue of an imbalance in the ratio of pixel count between target and non-target areas in ISAR images, we additionally use the idea of Focal Loss to improve the Mean Squared Error (MSE). We conduct experiments with simulated data of point targets and full-wave simulated data produced by FEKO to assess the efficacy of the proposed approach. The experimental results demonstrate that our approach can improve resolution while preventing defocusing in ISAR images.
    Keywords ISAR ; deep learning ; range-instantaneous Doppler ; image enhancement ; Science ; Q
    Subject code 006
    Language English
    Publishing date 2023-10-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: Big Data Fusion Method Based on Internet of Things Collection

    Tianrong Zhang / Hongying Li / Tian Jin / Fengjun Hu

    Computational Intelligence and Neuroscience, Vol

    2022  Volume 2022

    Abstract: With the development of information collection technology, the data that people need to deal with are also increasing, which brings problems such as isomerization of data types, poor data quality, and fast data generation speed. At present, as an ... ...

    Abstract With the development of information collection technology, the data that people need to deal with are also increasing, which brings problems such as isomerization of data types, poor data quality, and fast data generation speed. At present, as an important method of data fusion technology, data fusion method based on deep learning has become an effective way of data fusion under the background of big data, which has important research significance. There is a problem with heterogeneous data types between time series data and text data, and it is difficult to fuse them effectively by traditional data fusion methods. In order to make full use of the information contained in text data and improve the accuracy of time series prediction, this paper proposes a data fusion model based on FC-SAE. In this model, GloVe and CNN are used to extract the features of text data, FC neural network is used to extract the potential features of time series data, and then, the SEA model is used to fuse the data, which fully discovers the relationship between data and greatly improves the prediction accuracy.
    Keywords Computer applications to medicine. Medical informatics ; R858-859.7 ; Neurosciences. Biological psychiatry. Neuropsychiatry ; RC321-571
    Subject code 310
    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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  7. Article ; Online: Exploration of kiwi root on non-small cell lung cancer based on network pharmacology and molecular docking.

    Li, Ruochen / Wang, Mingxiao / Tian, Jin / Liu, Minghui / Li, Gaigai / Zhou, Xun

    Medicine

    2024  Volume 103, Issue 1, Page(s) e36852

    Abstract: Background: Kiwi root is a Chinese herb clinically used in the treatment of lung neoplasm; however, the multi-target mechanism of kiwi root in the treatment of non-small cell lung cancer (NSCLC) remains to be elucidated. Thus, this study aimed to ... ...

    Abstract Background: Kiwi root is a Chinese herb clinically used in the treatment of lung neoplasm; however, the multi-target mechanism of kiwi root in the treatment of non-small cell lung cancer (NSCLC) remains to be elucidated. Thus, this study aimed to investigate the molecular mechanisms of kiwi root in the treatment of NSCLC through network pharmacology and molecular docking techniques.
    Methods: The active components and targets of kiwi root were obtained from the TCMSP database, and NSCLC-related targets were obtained from the GeneCards, OMIM, and DrugBank databases. The intersection targets of NSCLC and kiwi root were obtained from VENNY 2.1.0. Then, the common targets were imported into the STRING database, and by using the Cytoscape 3.7.1 software, drug-disease network diagrams were created. Afterwards, the DAVID database was utilized to perform bioinformatic annotation. Finally, molecular docking of key components and key targets was performed by Autodock Tools.
    Results: A total of 4083 NSCLC-related disease genes were collected from the GeneCards, OMIM,and DrugBank databases, and 177 non-duplicated drug targets were acquired from the TCMSP database. A total of 138 intersection target genes were obtained, in which TP53, AKT1, and TNF were the key targets.
    Conclusion: Through network pharmacology techniques, the mechanism of kiwi root in the treatment of NSCLC has been uncovered and provides a theoretical basis for the clinical treatment of NSCLC with kiwi root, which requires further experimental validation.
    MeSH term(s) Humans ; Carcinoma, Non-Small-Cell Lung/drug therapy ; Lung Neoplasms/drug therapy ; Molecular Docking Simulation ; Network Pharmacology ; Computational Biology
    Language English
    Publishing date 2024-01-05
    Publishing country United States
    Document type Journal Article
    ZDB-ID 80184-7
    ISSN 1536-5964 ; 0025-7974
    ISSN (online) 1536-5964
    ISSN 0025-7974
    DOI 10.1097/MD.0000000000036852
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Implications of intestinal microecology and immune function alterations for immunotherapy outcomes in advanced unresectable lung adenocarcinoma.

    He, Shuang / Tian, Jin / Zang, Jianhua / Long, Lin / Liu, Peng / Zhang, Yexi / Xiao, Jun

    The clinical respiratory journal

    2024  Volume 18, Issue 5, Page(s) e13762

    Abstract: Objective: This investigation aims to explore alterations in intestinal microecology and immune function among patients with advanced, unresectable lung adenocarcinoma undergoing different outcomes from immunotherapy.: Methods: A cohort of 30 ... ...

    Abstract Objective: This investigation aims to explore alterations in intestinal microecology and immune function among patients with advanced, unresectable lung adenocarcinoma undergoing different outcomes from immunotherapy.
    Methods: A cohort of 30 patients diagnosed with advanced unresectable lung adenocarcinoma received sintilimab immunotherapy as a monotherapy. Post four treatment cycles, efficacy was assessed, leading to the segregation of patients into two distinct cohorts: those responsive to treatment and those nonresponsive. Analysis involved observing variations in the abundance, distribution, and composition of fecal intestinal microorganisms pretreatment and posttreatment via 16S rRNA gene sequencing.
    Results: In this study involving 30 advanced lung adenocarcinoma patients, significant observations were made regarding the impact of immunotherapy on immune function and the gut microbiome composition. Patients were divided into treatment and control groups, revealing that immunotherapy led to a significant increase in CD4+ T cells and a decrease in CD8+ T cells among the treatment-responsive individuals, indicating an enhanced immune response. Furthermore, an in-depth analysis of the gut microbiome showed an increase in diversity and abundance of beneficial bacteria such as Faecalibacterium and Subdoligranulum in the treatment group. These findings highlight the dual effect of immunotherapy on modulating immune function and altering gut microbiome diversity, suggesting its potential therapeutic benefits in improving the health status of patients with advanced lung adenocarcinoma.
    Conclusion: The structuring of gut flora plays a pivotal role in augmenting the efficacy of anti-tumor immunotherapy, underscoring the interplay between intestinal microecology and immune response in cancer treatment outcomes.
    MeSH term(s) Humans ; Gastrointestinal Microbiome/immunology ; Male ; Female ; Lung Neoplasms/immunology ; Lung Neoplasms/pathology ; Lung Neoplasms/therapy ; Middle Aged ; Adenocarcinoma of Lung/immunology ; Adenocarcinoma of Lung/pathology ; Adenocarcinoma of Lung/therapy ; Adenocarcinoma of Lung/drug therapy ; Immunotherapy/methods ; Aged ; RNA, Ribosomal, 16S/genetics ; Treatment Outcome
    Chemical Substances RNA, Ribosomal, 16S
    Language English
    Publishing date 2024-04-29
    Publishing country England
    Document type Journal Article
    ZDB-ID 2442214-9
    ISSN 1752-699X ; 1752-6981
    ISSN (online) 1752-699X
    ISSN 1752-6981
    DOI 10.1111/crj.13762
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  9. Article ; Online: Diffusivity metrics alterations three months after GammaKnife radiosurgery for trigeminal neuralgia may predict pain relief.

    Pikis, Stylianos / Mantziaris, Georgios / Donahue, Joseph / Tian-Jin Ren, Lydia / Flesch, Lance / Lavezzo, Karen / Xu, Zhiyuan / Sheehan, Jason

    Journal of radiosurgery and SBRT

    2023  Volume 8, Issue 4, Page(s) 241–246

    Abstract: Objectives: Early identification of patients who will experience delayed-onset pain relief after GKRS for trigeminal neuralgia (TN) will allow optimal patient management, and avoidance of unnecessary procedures. A non-invasive tool to identify late ... ...

    Abstract Objectives: Early identification of patients who will experience delayed-onset pain relief after GKRS for trigeminal neuralgia (TN) will allow optimal patient management, and avoidance of unnecessary procedures. A non-invasive tool to identify late responders to GKRS is currently unavailable. We sought to evaluate MRI based diffusivity metrics obtained at the 3-month post-GKRS time point as predictors of treatment response.
    Methods: Pre-procedural and 3-month post-procedural 3T MRI examinations were obtained in 43 patients with TN. Diffusion tensor metrics including axial diffusivity (AD), radial diffusivity (RD), and fractional anisotropy (FA) were extracted from the bilateral trigeminal nerve intra-pontine fibers, cisternal radiosurgical targets (or corresponding contralateral nerve segments), and non-targeted cisternal nerve segments. A favorable treatment response was defined as pain intensity on the Barrow Neurological Institute (BNI) scale of I-II at last follow-up. Pain relief and treatment response at last follow-up were examined for correlation with the 3-month post-GKRS diffusivity metrics.
    Results: At a median clinical follow-up of 5 months (range 0.5 to 24.5 months), all patients who did not experience pain relief at last follow-up had significantly reduced cisternal AD values (p=0.04) at the 3-month brain Diffusion Tensor image. In patients with classic TN, reduced mean cisternal AD (p=0.032), RD (p=0.026), and FA (p=0.042) values at the 3-month DTI follow-up were associated with BNI >2 at last follow-up. In addition, decreased mean cisternal AD (p=0.036), RD (p=0.029), and FA (p=0.037) were noted in patients with classic TN that failed to achieve a decrease of 2 points on the BNI scale at last follow-up.
    Conclusion: Alterations of diffusivity metrics on the treated trigeminal nerve 3 months after GKRS for classic TN significantly correlated with no response to GKRS at last follow-up. Further studies to clarify the value of DTI as a non-invasive tool to predict response to treatment in patients with TN managed with GKRS are warranted.
    Language English
    Publishing date 2023-06-24
    Publishing country United States
    Document type Journal Article
    ISSN 2156-4647
    ISSN (online) 2156-4647
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article: Antioxidant activity and interactions between whey protein and polysaccharides from different parts of

    Liu, Xiaocui / Tian, Jin / Zhou, Zhiran / Pan, Yinzhen / Li, Zhongqiao

    Frontiers in nutrition

    2023  Volume 10, Page(s) 1020328

    Abstract: Houttuynia ... ...

    Abstract Houttuynia cordata
    Language English
    Publishing date 2023-01-25
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2776676-7
    ISSN 2296-861X
    ISSN 2296-861X
    DOI 10.3389/fnut.2023.1020328
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