一个p(x)-Laplace方程组非平凡解的存在性

在广义Lebesgue空间L~(p(x))(Ω)和广义Sobolev空间W~(1,p(x))(Ω)基本理论体系的基础上,利用山路引理,Young不等式,H(o|¨)lder不等式和嵌入定理,获得了一p(x)-Laplace方程组非平凡解的存在性.     

Theoretical study of (e,2e) triple differential cross sections of pyrimidine and tetrahydrofurfuryl alcohol molecules using multi-center distorted-wave method

We report theoretical studies of electron impact triple differential cross sections of two bio-molecules,pyrimidine and tetrahydrofurfuryl alcohol,in the coplanar asymmetric kinematic conditions with the impact energy of 250 eV and ejected electron energy of 20 eV at three scattering angles of-5°,-10°,and-15°.Present multi-center distorted-wave method well describes the experimental data,which was obtained by performing(e,2e)experiment.The calculations show that the secondary electron produced by the primary impact electron is strongly influenced by the molecular ionic multi-center potential,which must be considered when the low energy electron interacts with DNA analogues.     

Sentinel-2卫星的多光谱轻量级船舶目标检测算法

近年来深度卷积神经网络在可见光船舶检测方面取得了显著的进展，然而，大多数相关研究是通过改进大型的网络结构来提高检测性能，因此加大了对更高计算机性能的需求。此外，可见光图像难以在云、雾、海杂波、黑夜等复杂场景检测到船舶。针对以上问题，提出了一种融合红（red, R）、绿（green, G）、蓝（blue, B）和近红外（NIR）4个波段光谱信息的由粗到精细的轻量型船舶检测算法。与现有的方法中根据光谱特性利用水体检测算法提取水体区域不同之处是该算法是利用改进的水体检测算法来提取船舶候选区域。为获取更准确的候选区域，对船舶、厚云、薄云、平静海面、杂波海面5种场景中4个波段的像素值进行了统计分析，选取近红外大于阈值作为辅助判断，并以其中心点获取候选区域32×32大小的切片，并对切片进行非极大值抑制，由此获得了船舶粗检测结果。随后构建了轻量级LSGFNet网络对船舶候选区域切片进行精细识别。构建的网络融合了1×1卷积提取的波谱特征与3×3的提取几何特征，为防止光谱特征与几何特征的信息在融合时“信息不流通”，在LSGFNet网络中引入了ShuffleNet中的通道打乱机制，并减小了模型结构，与典型的轻量级网络相比具有更好的效果且模型较小。最后，利用Sentinel-2卫星多光谱10 m分辨率数据构建了512×512大小的1 120组数据进行粗检测，以及32×32大小的6 014组数据进行精细网络训练，其中候选区域粗提取的查全率为98.99%，精细识别网络精确度为96.04%，不同场景下的平均精确度为92.98%。实验表明该算法在抑制云层、海浪杂波等干扰的复杂背景下具有较高的检测效率，且训练时间短、计算机性能需求低。     

基于深度学习的ELM实时识别研究

基于深度学习的方法，在HL-2A装置上开发出了一套边缘局域模(ELM)实时识别算法。算法使用5200次放电数据(约24.19万数据切片)进行学习，得到一个深度为22层的卷积神经网络。为衡量算法的识别能力，识别了HL-2A装置自2009年实现稳定ELMy H模放电以来所有历史数据(约26000次放电数据)，共识别出1665次H模放电，其中误识别35次，误报率为2.10%。在实际的1634次H模放电中，漏识别4次，漏识别率为0.24%。该误报率和漏报率可以满足ELM实时识别的精度要求。识别算法在实时控制环境下，对单个时间点的平均计算时间为0.46ms，可以满足实时控制的计算速度要求。     

Surface passivation in n-type silicon and its application in silicon drift detector

Based on the surface passivation of n-type silicon in a silicon drift detector(SDD), we propose a new passivation structure of SiO2/Al2O3/SiO2 passivation stacks. Since the SiO2 formed by the nitric-acid-oxidation-of-silicon(NAOS)method has good compactness and simple process, the first layer film is formed by the NAOS method. The Al2O3 film is also introduced into the passivation stacks owing to exceptional advantages such as good interface characteristic and simple process. In addition, for requirements of thickness and deposition temperature, the third layer of the SiO2 film is deposited by plasma enhanced chemical vapor deposition(PECVD). The deposition of the SiO2 film by PECVD is a low-temperature process and has a high deposition rate, which causes little damage to the device and makes the SiO2 film very suitable for serving as the third passivation layer. The passivation approach of stacks can saturate dangling bonds at the interface between stacks and the silicon substrate, and provide positive charge to optimize the field passivation of the n-type substrate.The passivation method ultimately achieves a good combination of chemical and field passivations. Experimental results show that with the passivation structure of SiO2/Al2O3/SiO2, the final minority carrier lifetime reaches 5223 μs at injection of 5×10¹⁵ cm^-3. When it is applied to the passivation of SDD, the leakage current is reduced to the order of nA.     

^13C的一个可能的类晕的中子1p态

假设^13C是单粒子的2p态的结构，用Glauber多重散射理论研究了入射能量为1GeV的质子在^13C上的弹性散射，得到了与实验符合得很好的理论结果。这说明^13C可能存在着一个类晕的中子皮。     

α,α′-二氧代烯酮环二氮代缩醛的NMR研究

报道了5种新的α，α′-二氧代烯酮环二氮代缩醛化合物的NMR谱，初步探讨了分子结构对化学位移的影响．     

关于混合型多项式Hammerstein积分方程正解迭代求法

本文给出了混合型多项式Ｈａｍｍｅｒｓｔｅｉｎ积分方程正解的迭代求法，并将所得结果应用到二阶非线性常微分方程的边值问题