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Articles by Linying Chen
Association of tumor associated collagen signature with lymph node metastasis in pancreatic ductal adenocarcinoma
This study shows that label-free multiphoton microscopy can reveal tumor-associated collagen signatures (ma-TACS and mi-TACS) within the pancreatic ductal adenocarcinoma microenvironment, which are strongly associated with lymph node metastasis. The nomogram integrating these features demonstrated strong predictive performance and holds potential clinical value for guiding treatment strategies and improving prognosis prediction in pancreatic cancer.
Dynamic Tugboat Scheduling for Large Seaports with Multiple Terminals
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
An Integrated Method for Ship Heading Control Using Motion Model Prediction and Fractional Order Proportion Integration Differentiation Controller
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
68Ga-Labeled Fibroblast Activation Protein Inhibitor PET/CT for the Early and Late Prediction of Pathologic Response to Neoadjuvant Chemotherapy in Breast Cancer Patients: A Prospective Study
RESULTS According to the inclusion criteria, a total of 25 patients were enrolled; of these, 3 patients were excluded because they met at least 1 of the exclusion criteria. The clinicopathologic data for the 22 consecutive patients finally enrolled are detailed in Table 1. The median ± SD ΔSUVmax of the primary tumor at PET2 was –32.4% ± 48.1% (range, –89.0% to 112.1%), and that at PET3 was –73.9% ± 20.6% (range, –96.8% to –35.4%).
Ship Trajectory Prediction: An Integrated Approach Using ConvLSTM-Based Sequence-to-Sequence Model
Abstract : Maritime transportation is one of the major contributors to the development of the global economy. To ensure its safety and reduce the occurrence of a maritime accident, intelligent maritime monitoring and ship behavior identification have been drawing much attention from industry and academia, among which, the accurate prediction of ship trajectory is one of the key questions.
High Throughput Screening of Surface Engineered Cyanine Nanodots for Active Transport of Therapeutic Antibody into Solid Tumor
Research Article This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record.
High‐Throughput Screening of Surface Engineered Cyanine Nanodots for Active Transport of Therapeutic Antibodies into Solid Tumor
Conflict of Interest The authors declare no conflict of interest. Supporting Information Filename Description adma202302292-sup-0001-SuppMat.pdf3.4 MB Supporting Information References 1a) , , , Adv. Healthcare Mater. 2022, 11, 2102600; b) , , , , Cell 2020, 181, 151. 2, , , Front. Bioeng. Biotechnol. 2020, 8, 89. 3a) , , , , Biomaterials 2019, 218, 119358; b) , , , , , , , Nat. Chem. 2022, 14, 274. 4a) , , , , , , , , Nat. Nanotechnol. 2009, 4, 457; b) , Nat. Rev. Drug Discovery 2016, 15, 275.
Ship-Infrastructure Cooperation: Survey on Infrastructure Scheduling for Waterborne Transportation Systems
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
Review of Ship Behavior Characteristics in Mixed Waterborne Traffic
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
Research on Operation Safety of Offshore Wind Farms
Open AccessArticle by Junmin Mou 1,2, Xuefei Jia 1, Pengfei Chen 1,2 and Linying Chen 1,2,* 1 School of Navigation, Wuhan University of Technology, Wuhan 430063, China 2 Hubei Key Laboratory of Inland Shipping Technology, Wuhan University of Technology, Wuhan 430063, China * Author to whom correspondence should be addressed.
An Anomaly Detection Method for AIS Trajectory Based on Kinematic Interpolation
1. Introduction Recently, the demand for AIS (Automatic Identification System) data for research and development in the maritime transport discipline has been continuously increasing [1]. AIS enables ships to communicate with each other or contact satellites and base stations using various information such as a Maritime Mobile Identification Number (MMSI), longitude, latitude, speed over ground (SOG), course over ground (COG), headings, etc. [2].
Ship AIS Trajectory Clustering: An HDBSCAN-Based Approach
5. Discussion In the previous section, a series of case studies are conducted to illustrate the process of the HDBSCAN algorithm on trajectory clustering in the area of ship complex confluence. In this section, the algorithm will be discussed in the comparison with the classic DBSCAN algorithm, k-means algorithm, and spectral clustering algorithm.
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