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  • 1
    Online Resource
    Online Resource
    Full-field x ray nano-imaging system designed and constructed at SSRF
    Shanghai Institute of Optics and Fine Mechanics ; 2016
    In:  Chinese Optics Letters Vol. 14, No. 9 ( 2016), p. 093401-93405
    Details
    In: Chinese Optics Letters, Shanghai Institute of Optics and Fine Mechanics, Vol. 14, No. 9 ( 2016), p. 093401-93405
    Type of Medium: Online Resource
    ISSN: 1671-7694
    Uniform Title: Full-field x ray nano-imaging system designed and constructed at SSRF
    URL: Issue
    URL: Journal
    URL: Article
    DOI: 10.3788/COL/2016/14/9
    DOI: 10.3788/COL
    DOI: 10.3788/COL201614.093401
    Language: English , Chinese
    Publisher: Shanghai Institute of Optics and Fine Mechanics
    Publication Date: 2016
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  • 2
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    Clinical outcomes of adult medulloblastoma: A retrospective analysis at a single institute
    SAGE Publications ; 2015
    In:  Translational Neuroscience and Clinics Vol. 1, No. 1 ( 2015), p. 17-24
    Details
    In: Translational Neuroscience and Clinics, SAGE Publications, Vol. 1, No. 1 ( 2015), p. 17-24
    Type of Medium: Online Resource
    ISSN: 2096-0441
    URL: Article
    DOI: 10.18679/CN11-6030/R.2015.004
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2015
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  • 3
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    Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition) 1
    Informa UK Limited ; 2021
    In:  Autophagy Vol. 17, No. 1 ( 2021-01-02), p. 1-382
    Details
    In: Autophagy, Informa UK Limited, Vol. 17, No. 1 ( 2021-01-02), p. 1-382
    Type of Medium: Online Resource
    ISSN: 1554-8627 , 1554-8635
    URL: Article
    DOI: 10.1080/15548627.2020.1797280
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2021
    detail.hit.zdb_id: 2262043-6
    SSG: 12
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  • 4
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    EEG-Based Emotion Recognition Using a 2D CNN with Different Kernels
    MDPI AG ; 2022
    In:  Bioengineering Vol. 9, No. 6 ( 2022-05-26), p. 231-
    Details
    In: Bioengineering, MDPI AG, Vol. 9, No. 6 ( 2022-05-26), p. 231-
    Abstract: Emotion recognition is receiving significant attention in research on health care and Human-Computer Interaction (HCI). Due to the high correlation with emotion and the capability to affect deceptive external expressions such as voices and faces, Electroencephalogram (EEG) based emotion recognition methods have been globally accepted and widely applied. Recently, great improvements have been made in the development of machine learning for EEG-based emotion detection. However, there are still some major disadvantages in previous studies. Firstly, traditional machine learning methods require extracting features manually which is time-consuming and rely heavily on human experts. Secondly, to improve the model accuracies, many researchers used user-dependent models that lack generalization and universality. Moreover, there is still room for improvement in the recognition accuracies in most studies. Therefore, to overcome these shortcomings, an EEG-based novel deep neural network is proposed for emotion classification in this article. The proposed 2D CNN uses two convolutional kernels of different sizes to extract emotion-related features along both the time direction and the spatial direction. To verify the feasibility of the proposed model, the pubic emotion dataset DEAP is used in experiments. The results show accuracies of up to 99.99% and 99.98 for arousal and valence binary classification, respectively, which are encouraging for research and applications in the emotion recognition field.
    Type of Medium: Online Resource
    ISSN: 2306-5354
    URL: Article
    DOI: 10.3390/bioengineering9060231
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2746191-9
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  • 5
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    Structural Evolution and Community Detection of China Rail Transit Route Network
    MDPI AG ; 2022
    In:  Sustainability Vol. 14, No. 19 ( 2022-09-28), p. 12342-
    Details
    In: Sustainability, MDPI AG, Vol. 14, No. 19 ( 2022-09-28), p. 12342-
    Abstract: How to improve the partial or overall performance of rail transit route network, strengthen the connection between different rail network stations, and form corresponding communities to resist the impact of sudden or long-term external factors has earned a lot of attention recently. However, the corresponding research studies are mostly based on the rail network structure, and the analysis and exploration of the community formed by the stations and its robustness are not enough. In this article, the evolution of the China rail transit route network (CRTRN) from 2009 to 2022 is taken as the research object, and its complex network characteristics, BGLL model-based community division, and multi disturbance strategies for network robustness are analyzed in depth to better understand and optimize the rail network structure to further effectively improve the efficiency of the public transport system. It is found that CRTRN is gradually expanding following the southwest direction (with the migration distance of nearly 200 km), the distribution of routes is more balanced, and the number of network communities is steadily decreasing (it dropped from 30 communities in 2009 to 25 in 2019), making various regions become closely connected. However, it can also be found that during the COVID-19 pandemic, the CRTRN is strongly affected, and the network structure becomes relatively loose and chaotic (the number of communities became 30). To protect the railway networks, the CRTRN system should pay more attention to stations with high node degree values; if they get disturbed, more areas will be affected. The corresponding research conclusions can provide some theoretical and practical support for the construction of the rail transit network in China.
    Type of Medium: Online Resource
    ISSN: 2071-1050
    URL: Article
    DOI: 10.3390/su141912342
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2518383-7
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  • 6
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    A Nonlinear-Model-Based High-Bandwidth Current Sensor Design for Switching Current Measurement of Wide Bandgap Devices
    MDPI AG ; 2023
    In:  Sensors Vol. 23, No. 10 ( 2023-05-10), p. 4626-
    Details
    In: Sensors, MDPI AG, Vol. 23, No. 10 ( 2023-05-10), p. 4626-
    Abstract: With the growing adoption of wide bandgap devices in power electronic applications, current sensor design for switching current measurement has become more important. The demands for high accuracy, high bandwidth, low cost, compact size, and galvanic isolation pose significant design challenges. The conventional modeling approach for bandwidth analysis of current transformer sensors assumes that the magnetizing inductance remains constant, which does not always hold true in high-frequency operations. This can result in inaccurate bandwidth estimation and affect the overall performance of the current sensor. To address this limitation, this paper provides a comprehensive analysis of nonlinear modeling and bandwidth, considering the varying magnetizing inductance in a wide frequency range. A precise and straightforward arctangent-based fitting algorithm was proposed to accurately emulate the nonlinear feature, and the fitting results were compared with the magnetic core’s datasheet to confirm its accuracy. This approach contributes to more accurate bandwidth prediction in field applications. In addition, the droop phenomenon of the current transformer and saturation effects are analyzed in detail. For high-voltage applications, different insulation methods are compared and an optimized insulation process is proposed. Finally, the design process is experimentally validated. The bandwidth of the proposed current transformer is around 100 MHz and the cost is around $20, making it a low-cost and high-bandwidth solution for switching current measurements in power electronic applications.
    Type of Medium: Online Resource
    ISSN: 1424-8220
    URL: Article
    DOI: 10.3390/s23104626
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2052857-7
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  • 7
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    Robust estimation of bacterial cell count from optical density
    Springer Science and Business Media LLC ; 2020
    In:  Communications Biology Vol. 3, No. 1 ( 2020-09-17)
    Details
    In: Communications Biology, Springer Science and Business Media LLC, Vol. 3, No. 1 ( 2020-09-17)
    Abstract: Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli . Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals   〈 1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data.
    Type of Medium: Online Resource
    ISSN: 2399-3642
    URL: Article
    DOI: 10.1038/s42003-020-01127-5
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
    detail.hit.zdb_id: 2919698-X
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  • 8
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    Abstract 2752: Targeting intracellular tumor antigens using fully human TCR mimic antibodies derived from HLA transgenic RenMiceTM
    American Association for Cancer Research (AACR) ; 2023
    In:  Cancer Research Vol. 83, No. 7_Supplement ( 2023-04-04), p. 2752-2752
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 83, No. 7_Supplement ( 2023-04-04), p. 2752-2752
    Abstract: Therapeutic antibodies have ushered in a new age of cancer immunotherapy. Historically, these therapies have targeted a limited subset of soluble and cell surface tumor-associated antigens (TAAs). T cell receptors (TCRs) on cytotoxic CD8+ T cells recognize peptide antigens bound to major histocompatibility class I (MHC-I) proteins, called HLA-A/B/C in humans. By this pathway, antigen is regularly sampled from the intracellular peptidome, processed, and presented to cytotoxic T cells. Expanding TCR-based recognition of soluble, intracellular TAAs presented on the surface of malignant cells by this mechanism is a propitious therapeutic strategy. Here we describe a novel platform for generating T cell receptor mimic (TCRm) antibodies using our humanized immunoglobulin (RenMabTM) mice engineered to express HLA. TCRm antibodies have the same binding properties as endogenous TCRs and recognize processed, HLA-bound peptides including intracellular tumor-associated antigens, viral oncoproteins, and cancer-testis antigen (CTA). TCRm antibodies bind peptide-HLA with high specificity and up to nanomolar affinity. Our optimized immunization protocols and high-throughput screening methods allow for one-step TCRm antibody generation. TCRm antibodies can also be used to assemble bispecific T cell engaging antibodies (BiTEs) to enhance tumor targeting of cytotoxic T cells. Biocytogen’s TCRm antibodies are a flexible and powerful tool for cancer immunotherapy. By enabling TCR-mediated recognition of an unrestricted repertoire of cancer neoantigens, TCRm antibodies may find broad clinical application. Citation Format: Jun Du, Taolin Liu, Wanbo Tang, Yue Zhang, Limin Zhao, Xin Jiao, Chao Sun, Pengfei Du, Yuqi Zhang, Baihong Liu, Qingcong Lin, Yi Yang. Targeting intracellular tumor antigens using fully human TCR mimic antibodies derived from HLA transgenic RenMiceTM [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2752.
    Type of Medium: Online Resource
    ISSN: 1538-7445
    URL: Article
    DOI: 10.1158/1538-7445.AM2023-2752
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2023
    detail.hit.zdb_id: 2036785-5
    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
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  • 9
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    Study on the Evolution and Resilience of Rail Transit Time Networks—Evidence from China
    MDPI AG ; 2022
    In:  Applied Sciences Vol. 12, No. 19 ( 2022-10-03), p. 9950-
    Details
    In: Applied Sciences, MDPI AG, Vol. 12, No. 19 ( 2022-10-03), p. 9950-
    Abstract: In the network operation and management of rail transit systems, the occurrence of unexpected events causes damage to the network structure, further hindering regional accessibility performance and the function of the system. This study is based on the rail transit operation schedules in 2009, 2013, 2016, 2019 and 2022. We construct a directional weighted rail transit time network (RNNT) with train operation time as the weight, compare the betweenness centrality, sum of the shortest time path and entropy importance, etc., and quantitatively measure the network accessibility, connectivity and its resilience evolution. The results show that the current rail transportation network in China has a “small-world” effect, and there are a few stations with strong connections. The most densely distributed intervals of travel times between pairs of nodes changes from [440, 445] to [207, 210] . The fastest and best-performing disturbance to network connectivity and accessibility performance are both caused by the betweenness disturbance strategy. When the network connectivity remains 80% effective, the ratio of failed nodes under the static betweenness centrality strategy decreases from 3.96% in 2009 to 2.31% in 2022, with weaker connections between node pairs, and their network resilience diminishes. When the network accessibility remains 80% effective, the ratio of failed nodes under the static (dynamic) betweenness centrality strategy increases from 0.13% (0.13%) in 2009 to 0.20% (0.23%) in 2022. Therefore, the rail transit network can protect the corresponding rail stations based on the station ranking of the above strategies, and this research is beneficial to rail transit network protection and structure optimization.
    Type of Medium: Online Resource
    ISSN: 2076-3417
    URL: Article
    DOI: 10.3390/app12199950
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2704225-X
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  • 10
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    A novel multi-scale 2D CNN with weighted focal loss for arrhythmias detection on varying-dimensional ECGs
    IOP Publishing ; 2022
    In:  Physiological Measurement Vol. 43, No. 10 ( 2022-10-28), p. 104003-
    Details
    In: Physiological Measurement, IOP Publishing, Vol. 43, No. 10 ( 2022-10-28), p. 104003-
    Abstract: Objective . The ECG is a standard diagnostic tool for identifying many arrhythmias. Accurate diagnosis and early intervention for arrhythmias are of great significance to the prevention and treatment of cardiovascular disease. Our objective is to develop an algorithm that can automatically identify 30 arrhythmias by using varying-dimensional ECG signals. Approach . In this paper, we firstly proposed a novel multi-scale 2D CNN that can effectively capture pathological information from small-scale to large-scale from ECG signals to identify 30 arrhythmias from 12-lead, 6-lead, 4-lead, 3-lead, and 2-lead ECGs. Secondly, we explored the effects of varying convolution kernels sizes and branch subnetworks on the model’s performance for each arrhythmia. Thirdly, we introduced the weighted focal loss to alleviate the positive-negative class imbalance problem in the multi-label arrhythmias classification. Fourthly, we explored the utility of reduced-lead ECGs in detecting arrhythmias by comparing the performances of models on varying-dimensional ECGs. Main results . As a follow-up entry after the PhysioNet/Computing in Cardiology Challenge (2021), our proposed approach achieved the official test scores of 0.52, 0.47, 0.53, 0.51, and 0.50 for the 12-lead, 6-lead, 4-lead, 3-lead, and 2-lead ECGs on the hidden test set (comparable to that of 6th, 11th, 4th, 5th, and 7th out of 39 teams in the Challenge). Significance . A multi-scale framework capable of detecting 30 arrhythmias from varying-dimensional ECGs was proposed in our work. We preliminarily verified that the multi-scale perception fields may be necessary to capture more comprehensive pathological information for arrhythmias detection. Besides, we also verified that the weighted focal loss may alleviate the positive–negative class imbalance and improve the model’s generalization performance on the cross-dataset. In addition, we observed that some reduced-lead models, such as the 4-lead and 3-lead models, can even achieve performance that is almost comparable to that of the 12-lead model. The excellent performance of our proposed framework demonstrates its great potential in detecting a wide range of arrhythmias.
    Type of Medium: Online Resource
    ISSN: 0967-3334 , 1361-6579
    URL: Article
    DOI: 10.1088/1361-6579/ac7695
    Language: Unknown
    Publisher: IOP Publishing
    Publication Date: 2022
    detail.hit.zdb_id: 2002076-4
    SSG: 11
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