58 research outputs found

    Experimental Investigation of Forchheimer Coefficients for Non-Darcy Flow in Conglomerate-Confined Aquifer

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    The research is financially supported by the National Key Research and Development Program of China (No. 2016YFC0801401 and No. 2016YFC0600708), Major Consulting Project of Chinese Academy of Engineering (No. 2017-ZD-2), Yue Qi Distinguished Scholar Project of China University of Mining & Technology (Beijing), and Fundamental Research Funds for the Central Universities (No. 2009QM01).Peer reviewedPublisher PD

    Towards Data-centric Graph Machine Learning: Review and Outlook

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    Data-centric AI, with its primary focus on the collection, management, and utilization of data to drive AI models and applications, has attracted increasing attention in recent years. In this article, we conduct an in-depth and comprehensive review, offering a forward-looking outlook on the current efforts in data-centric AI pertaining to graph data-the fundamental data structure for representing and capturing intricate dependencies among massive and diverse real-life entities. We introduce a systematic framework, Data-centric Graph Machine Learning (DC-GML), that encompasses all stages of the graph data lifecycle, including graph data collection, exploration, improvement, exploitation, and maintenance. A thorough taxonomy of each stage is presented to answer three critical graph-centric questions: (1) how to enhance graph data availability and quality; (2) how to learn from graph data with limited-availability and low-quality; (3) how to build graph MLOps systems from the graph data-centric view. Lastly, we pinpoint the future prospects of the DC-GML domain, providing insights to navigate its advancements and applications.Comment: 42 pages, 9 figure

    BONE MORPHOGENETIC PROTEIN-2 AND COLLAGEN TYPE 1 FROM DIFFERENT SOURCES OF DEMINERALIZED DENTINE MATRIX: RELEASE KINETIC AND CHEMOTAXIS POTENTIAL FOR OSTEOPROGENITOR CELLS

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    Objective: To investigate the release of bone morphogenetic protein-2 (BMP-2) and collagen type I proteins (COL1) from different sources ofdemineralized dentine matrix (DDM) and their chemotaxis to mouse osteoprogenitor cells.Methods: The release kinetic of BMP-2 and COL1 was measured from custom-made DDM (CMDDM) and commercially available DDM (CADDM).Using Urist physicochemical method, CMDDM was collected from the extracted teeth in a certified dental clinic. Levels of BMP-2 and COL1 releasedwere measured at days 1, 2, 3, 5, 7, 9, 11, and 13. Next, mouse osteoprogenitor cells, MC3T3-E1, were cultured with a variety of materials as follows:CMDDM, CADDM, Bio-OssĀ®, and blank control in transwell system. The number of cell migration was determined by crystal violet staining to explorechemotaxis of different DDMs to mouse osteoprogenitor cells.Results: BMP-2 was detected at 588.32 Ā± 14.53 pg/ml from 5 g of CMDDM. In the release kinetic assay, the concentration of BMP-2 in the CMDDMgroup increased rapidly and peaked at 113.9 pg/ml on day 5, almost four times higher than that of CADDM. The release of COL1 showed similarpattern in both CMDDM and CADDM; however, the amount was significantly higher in the CMDDM group. In cell culture experiment, the number ofmigrated MC3T3-E1 was ranked as the highest in CMDDM, followed by CADDM and Bio-OssĀ® (p<0.05).Conclusion: CMDDM released BMP-2 and COL1 greater than CADDM, which can induce more osteoblast-like cell migration. These results demonstrateda release kinetic of proteins and osteoinductivity of CMDDM, which supports a benefit of using autogenous bone graft
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