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| 1 | Uhra-Widcband Technology and Random Signal Radar:An Ideal Combination显示文摘 | YILONG L GUOSUI L | 2003 | IEEE AES System Magazine2003，14，5： | 1 |
| 2 | Maximum likelihood DOA estimation in un-known colored noise fields显示文摘 | L Minghui L Yilong | 2008 | IEEE Trans Aerospace and Elec-tronic Systems2008，44，3： | 1 |
| 3 | Ultra-Wideband Technology and Random Signal Radar:An Ideal Combi-nation显示文摘 | YILONG L GUOSUI L | 2003 | IEEE AES System Magazine2003，32，5： | 1 |
| 4 | Damage of a high-energy solid propellant and its deflagration-to-detonatoin transition显示文摘 | Zhang Taihua Yilong L Bai | 2003 | Propellants Explosives Pyrotechnics2003，28，： | 1 |
| 5 | Ultra-wideband technology and random signal radar:An ideal Combination显示文摘 | Hongbo S Yilong L Guosui L | 2003 | IEEE AES System Magazine2003，，： | 1 |
| 6 | Nat Genet:科学家设计新方法找到抑制癌症发育的新基因显示文摘英国桑格研究院的研究人员和他们的合作者们最近发现了帮助阻止前列腺癌、皮肤癌和乳腺癌发育的新基因。这些基因能够与众所周知的肿瘤抑制基因PTEN配合发挥作用,该研究还发现这些基因与人类前列腺肿瘤存在相关性。相关研究结果发表在国际学术期刊Nature Genetics上。该研究揭示了一些参与癌症发育的新途径,这些基因有望成为治疗PTEN突变癌症的新药物靶点。这项研究开发的一些方法也可以用于发现其他协同抑制癌症生长的基因。 | Jorge de la Rosa, Mathias Josef Friedrich, Yilong Li, Lena Rad, Hannes Ponstingl, Qi Liang, Sandra Bernaldo de Quirós, Imran Noorani, Emmanouil Metzakopian, Alexander Strong, Meng Amy Li, Gary J Hoffman, Rocío Fuente, George S Vassiliou, Roland Rad, Allan Bradley Juan Cadiñanos Jorge de la Rosa Juan Cadiñanos Jorge de la Rosa Carlos López-Otín Julia Weber Roland Rad Julia Weber Roland Rad Aurora Astudillo María Teresa Fernández-García María Soledad Fernández-García Gary J Hoffman Carlos López-Otín | 2017 | 现代生物医学进展2017，17，15： | 0 |
| 7 | Many-body potential for simulating the self-assembly of polymer-grafted nanoparticles in a polymer matrix显示文摘Many-body interactions between polymer-grafted nanoparticles(NPs)play a key role in promoting their assembly into low-dimensional structures within polymer melts,even when the particles are spherical and isotropically grafted.However,capturing such interactions in simulations of NP assembly is very challenging because explicit modeling of the polymer grafts and melt chains is highly computationally expensive,even using coarse-grained models.Here,we develop a many-body potential for describing the effective interactions between spherical polymer-grafted NPs in a polymer matrix through a machine-learning approach.The approach involves using permutationally invariant polynomials to fit two-and three-body interactions derived from the potential of mean force calculations.The potential developed here reduces the computational cost by several orders of magnitude,thereby,allowing us to explore assembly behavior over large length and time scales.We show that the potential not only reproduces previously known assembled phases such as 1D strings and 2D hexagonal sheets,which generally cannot be achieved using isotropic two-body potentials,but can also help discover interesting phases such as networks,clusters,and gels.We demonstrate how each of these assembly morphologies intrinsically arises from a competition between two-and three-body interactions.Our approach for deriving many-body effective potentials can be readily extended to other colloidal systems,enabling researchers to make accurate predictions of their behavior and dissect the role of individual interaction energy terms of the overall potential in the observed behavior. | Yilong Zhou Sigbjørn Løland Bore Andrea R.Tao Francesco Paesani Gaurav Arya | 2023 | npj Computational Materials2023，，1： | 0 |
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