5篇
您的检索式：作者名="Jason Gibson"
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| 1 | Ranibizumab for Diabetic Macular Edema显示文摘 | Quan Dong Nguyen David M. Brown Dennis M. Marcus David S. Boyer Sunil Patel Leonard Feiner Andrea Gibson Judy Sy Amy Chen Rundle J. Jill Hopkins Roman G. Rubio Jason S. Ehrlich | 2012 | Ophthalmology2012，，4： | 4 |
| 2 | Ability of new oeLspolar bioimpedance spectroscopy analyzers to predict 4 - component- model percentage body fat in Hispanic, black, and white MulLs显示文摘 | Ann L Gibson Jason C Holmes Rechard L Desautels | 2008 | The American Journal of Clinical Nutrition2008，87，： | 1 |
| 3 | Data-augmentation for graph neural network learning of the relaxed energies of unrelaxed structures显示文摘Computational materials discovery has grown in utility over the past decade due to advances in computing power and crystal structure prediction algorithms(CSPA).However,the computational cost of the ab initio calculations required by CSPA limits its utility to small unit cells,reducing the compositional and structural space the algorithms can explore.Past studies have bypassed unneeded ab initio calculations by utilizing machine learning to predict the stability of a material.Specifically,graph neural networks trained on large datasets of relaxed structures display high fidelity in predicting formation energy.Unfortunately,the geometries of structures produced by CSPA deviate from the relaxed state,which leads to poor predictions,hindering the model’s ability to filter unstable material.To remedy this behavior,we propose a simple,physically motivated,computationally efficient perturbation technique that augments training data,improving predictions on unrelaxed structures by 66%.Finally,we show how this error reduction can accelerate CSPA. | Jason Gibson Ajinkya Hire Richard G.Hennig | 2022 | npj Computational Materials2022，，1： | 1 |
| 4 | 前车可鉴显示文摘这个少车史上最著名的故事始于1963年5月。话说美国巨头福特与当时创派不过16年的意大利新进法拉利眉目传情多个月后, | JASON BARLOW DREW GIBSON Tony | 2016 | 汽车测试报告2016，0，5： | 0 |
| 5 | Enhancement in ballistic performance of composite hard armor through carbon nanotubes显示文摘The use of carbon nanotubes in composite hard armor is discussed in this study.The processing techniques to make various armor composite panels consisting of Kevlar■29 woven fabric in an epoxy matrix and the subsequent V50 test results for both 44 caliber soft-point rounds and 30 caliber FSP(fragment simulated projectile)threats are presented.A 6.5%improvement in the V50 test results was found for a combination of 1.65 wt%loading of carbon nanotubes and 1.65 wt%loading of milled fibers.The failure mechanism of carbon nanotubes during the ballistic event is discussed through scanning electron microscope images of the panels after the failure.Raman Spectroscopy was also utilized to evaluate the residual strain in the Kevlar■29 fibers post shoot.The Raman Spectroscopy shows a Raman shift of 25 cm^(−1) for the Kevlar■29 fiber utilized in the composite panel that had an enhancement in the V50 performance by using milled fiber and multi-walled carbon nanotubes.Evaluating both scenarios where an improvement was made and other panels without any improvement allows for understanding of how loading levels and synergistic effects between carbon nanotubes and milled fibers can further enhance ballistic performance. | Jason Gibson James McKee Gregory Freihofer Seetha Raghavan Jihua Gou | 2013 | International Journal of Smart and Nano Materials2013，4，4： | 0 |
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