2,408 research outputs found

    Reading In English By Children In Korea: Frequency, Effectiveness, And Barriers

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    A study of the English non-textbook reading of fourth graders in Korea revealed that about 80% had done at least some reading, confirming that there is enthusiasm for English reading. About half, however, had read only five books or fewer. Non-readers said that the reason they did not read in English was the difficulty of English texts. Those who read more did better on a test of English spelling and vocabulary

    Improving STING Agonist Delivery for Cancer Immunotherapy Using Biodegradable Mesoporous Silica Nanoparticles

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    Stimulator of interferon genes (STING) activation by intratumoral STING agonist treatment has been recently shown to eradicate tumors in preclinical models of cancer immunotherapy, generating intense research interest and leading to multiple clinical trials. However, there are many challenges associated with STING agonistā€based cancer immunotherapy, including low cellular uptake of STING agonists. Here, biodegradable mesoporous silica nanoparticles (bMSN) with an average size of 80Ā nm are developed for efficient cellular delivery of STING agonists. STING agonists delivered via bMSN potently activate innate and adaptive immune cells, leading to strong antitumor efficacy and prolonged animal survival in murine models of melanoma. Delivery of immunotherapeutic agents via biodegradable bMSN is a promising approach for improving cancer immunotherapy.Biodegradable mesoporous silica nanoparticles enhance cellular delivery of stimulator of interferon genes (STING) agonists and achieve greater antitumor therapeutic efficacy than free STING agonists in murine models of melanoma. Biodegradable mesoporous silica nanoparticles are a promising platform for cancer immunotherapy.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/163388/3/adtp202000130_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163388/2/adtp202000130.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163388/1/adtp202000130-sup-0001-SuppMat.pd

    J/psi hadron interaction in vacuum and in QGP

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    Motivated by the recent lattice data that J/ĻˆJ/\psi will survive up to 1.6TcT_c, we calculate the thermal width of J/ĻˆJ/\psi at finite temperature in perturbative QCD. The inputs of the calculation are the parton quarkonium dissociation cross sections at the NLO in QCD, which were previously obtained by Song and Lee, and a gaussian charmonium wave function, whose size were fitted to an estimate by Wong by solving the schrodinger equation for charmonium in a potential extracted from the lattice at finite temperature. We find that the total thermal width above 1.4TcT_c becomes larger than 100 to 200 MeV, depending on the effective thermal masses of the quark and gluon, which we take it to vary from 600 to 400 MeV.Comment: 4 pages, Talk at Quark Matter 200

    Experimental observation of hidden Berry curvature in inversion-symmetric bulk 2H-WSe2

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    We investigate the hidden Berry curvature in bulk 2H-WSe2 by utilizing the surface sensitivity of angle resolved photoemission (ARPES). The symmetry in the electronic structure of transition metal dichalcogenides is used to uniquely determine the local orbital angular momentum (OAM) contribution to the circular dichroism (CD) in ARPES. The extracted CD signals for the K and K' valleys are almost identical but their signs, which should be determined by the valley index, are opposite. In addition, the sign is found to be the same for the two spin-split bands, indicating that it is independent of spin state. These observed CD behaviors are what are expected from Berry curvature of a monolayer of WSe2. In order to see if CD-ARPES is indeed representative of hidden Berry curvature within a layer, we use tight binding analysis as well as density functional calculation to calculate the Berry curvature and local OAM of a monolayer WSe2. We find that measured CD-ARPES is approximately proportional to the calculated Berry curvature as well as local OAM, further supporting our interpretation.Comment: 6 pages, 3 figure

    ArabidopsisĀ ABCG14 is essential for the root-to-shoot translocation of cytokinin.

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    Cytokinins are phytohormones that induce cytokinesis and are essential for diverse developmental and physiological processes in plants. Cytokinins of the trans-zeatin type are mainly synthesized in root vasculature and transported to the shoot, where they regulate shoot growth. However, the mechanism of long-distance transport of cytokinin was hitherto unknown. Here, we report that the Arabidopsis ATP-binding cassette (ABC) transporter subfamily G14 (AtABCG14) is mainly expressed in roots and plays a major role in delivering cytokinins to the shoot. Loss of AtABCG14 expression resulted in severe shoot growth retardation, which was rescued by exogenous trans-zeatin application. Cytokinin content was decreased in the shoots of atabcg14 plants and increased in the roots, with consistent changes in the expression of cytokinin-responsive genes. Grafting of atabcg14 scions onto wild-type rootstocks restored shoot growth, whereas wild-type scions grafted onto atabcg14 rootstocks exhibited shoot growth retardation similar to that of atabcg14. Cytokinin concentrations in the xylem are reduced by similar to 90% in the atabcg14 mutant. These results indicate that AtABCG14 is crucial for the translocation of cytokinin to the shoot. Our results provide molecular evidence for the long-distance transport of cytokinin and show that this transport is necessary for normal shoot development.open118380Ysciescopu

    Deformable Graph Transformer

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    Transformer-based models have recently shown success in representation learning on graph-structured data beyond natural language processing and computer vision. However, the success is limited to small-scale graphs due to the drawbacks of full dot-product attention on graphs such as the quadratic complexity with respect to the number of nodes and message aggregation from enormous irrelevant nodes. To address these issues, we propose Deformable Graph Transformer (DGT) that performs sparse attention via dynamically sampled relevant nodes for efficiently handling large-scale graphs with a linear complexity in the number of nodes. Specifically, our framework first constructs multiple node sequences with various criteria to consider both structural and semantic proximity. Then, combining with our learnable Katz Positional Encodings, the sparse attention is applied to the node sequences for learning node representations with a significantly reduced computational cost. Extensive experiments demonstrate that our DGT achieves state-of-the-art performance on 7 graph benchmark datasets with 2.5 - 449 times less computational cost compared to transformer-based graph models with full attention.Comment: 16 pages, 3 figure
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