Photo‐Induced Charge‐Variable Conjugated Polyelectrolyte Brushes Encapsulating Upconversion Nanoparticles for Promoted siRNA Release and Collaborative Photodynamic Therapy under NIR Light Irradiation

Combination of photodynamic therapy (PDT) with small interfering RNA (siRNA) therapy has become a major strategy in cancer treatment for enhancing anticancer efficacy. However, developing nanoplatform that can promote siRNA release and collaborate with efficient PDT under NIR light irradiation is still a big challenge. Photo‐induced charge‐variable conjugated polyelectrolyte brushes encapsulating upconversion nanoparticles (UCNP@CCPEB) as an efficient nanoplatform are reported. Cationic conjugated polyelectrolyte brush (CCPEB) is synthesized through quaternary ammoniation of N‐functionalized polyfluorene brush by photodegradable 2‐nitrobenzyl‐2‐bromoacetate. CCPEB with abundant positive charges and intrinsic photosensitizer (PS) performance is good for integrating siRNA carrier and PS into one molecule. The obtained CCPEB next encapsulates upconversion nanoparticle for realizing its NIR light excitation. Agarose gel electrophoresis experiments show that UCNP@CCPEB present good stability and excellent siRNA‐loading capacity (1 mol UCNP@CCPEB to at least 32.5 mol siRNA). Under 980 nm light irradiation, UCNP@CCPEB exhibit efficient single oxygen production for PDT. Concurrently, the photoresponsive cationic side‐chain of CCPEB turns into zwitterionic chain and thus accelerates its siRNA release to 80%. In vitro and in vivo experiments show that the successful A549 tumor suppression is achieved by UCNP@CCPEB/siPlk1 complex under 980 irradiation. It is envisioned that UCNP@CCPEB can serve as an efficient platform for combining various phototherapies together.     

一种小型化宽阻带窄带通滤波器研究

为实现滤波器设计小型化,降低带通滤波器的高次谐波干扰,本文结合传统的1/4波长谐振器结构,采用在谐振器微带线上添加开路线的方法,降低高次谐振频点处的插入损耗,消减谐波影响。相比半波谐振器,1/4波长谐振器能有效地减小滤波器尺寸,此外开路线的添加除具有消减高次谐波作用,同时还能降低基频谐振点,促进设计小型化。通过仿真软件对该方案的验证及网络分析仪的实物测试表明,此方案具有良好效果,能广泛应用于窄带通滤波器小型化及谐波抑制。     

Compressed sensing of complex-valued data

Compressed sensing (CS) is a recently proposed technique that allows the reconstruction of a signal sampled in violation of the traditional Nyquist criterion. It has immediate applications in reduction of acquisition time for measurements, simplification of hardware, reduction of memory space required for data storage, etc. CS has been applied usually by considering real-valued data. However, complex-valued data are very common in practice, such as terahertz (THz) imaging, synthetic aperture radar and sonar, holography, etc. In such cases CS is applied by decoupling real and imaginary parts or using amplitude constraints. Recently, it was shown in the literature that the quality of reconstruction for THz imaging can be improved by applying smoothness constraint on phase as well as amplitude. In this paper, we propose a general l_p minimization recovery algorithm for CS, which can deal with complex data and smooth the amplitude and phase of the data at the same time as well has the additional feature of using a separate sparsity promoting basis such as wavelets. Thus, objects can be better detected from limited noisy measurements, which are useful for surveillance systems.     

一个动态门限的基于属性签密方案

签密能同时实现加密与签名,并且代价小于传统的先签名再加密。该文在Li等人(2010)签名方案的基础上提出了一个动态门限的基于属性签密方案,除具有一般签密方案的保密性和认证性外,还同时具有签密者属性隐私安全性和多接收者特性。在随机预言机模型下,利用判定双线性Diffie-Hellman (DBDH)问题和计算Diffie- Hellman (CDH)问题的困难性,证明了该方案满足在适应性选择密文攻击下的不可区分性及适应性选择消息下的不可伪造性。     

A multiplicative iterative algorithm for box-constrained penalized likelihood image restoration

Image restoration is a computationally intensive problem as a large number of pixel values have to be determined. Since the pixel values of digital images can attain only a finite number of values (e.g., 8-bit images can have only 256 gray levels), one would like to recover an image within some dynamic range. This leads to the imposition of box constraints on the pixel values. The traditional gradient projection methods for constrained optimization can be used to impose box constraints, but they may suffer from either slow convergence or repeated searching for active sets in each iteration. In this paper, we develop a new box-constrained multiplicative iterative (BCMI) algorithm for box-constrained image restoration. The BCMI algorithm just requires pixelwise updates in each iteration, and there is no need to invert any matrices. We give the convergence proof of this algorithm and apply it to total variation image restoration problems, where the observed blurry images contain Poisson, Gaussian, or salt-and-pepper noises.     

基于自旋图的三维自动目标识别

将三维表面匹配领域的自旋图(spin-images)方法运用于扫描激光雷达自动目标识别中,基于自旋图特征,提出了平均最大相似性度量、候选对应关系数目、几何一致性筛选后对应关系数目、分组筛选后最大组的对应关系数目这4个识别指标,并将其组合构成组合识别准则,从而进行三维目标识别。同时针对实际应用需求,进一步研究了点云空间分辨率、激光雷达测距误差以及遮挡对目标识别率的影响,为激光雷达三维目标识别系统的设计提供了参考。     

一种低仰角对流层折射修正的新方法

大气折射效应引起电波传播延迟和路径弯曲,测量数据对流层折射修正的精度直接影响到飞行目标轨(弹)道确定的精度。考虑到对流层折射修正的精度和效率以及5°以下低仰角数据传统修正方法具有较大的误差,通常不对测量数据进行实时对流层折射修正,这使得实时定位的精度受到较大影响。文中提出了一种基于光电传播几何路径迭代的对流层折射修正新方法,解决了修正精度和实时性不能兼顾的问题。经大量无人机校飞和载人航天工程外场实测数据验证,该算法能够实时有效地消除低仰角对流层折射偏差,对高仰角测量数据的对流层折射修正亦具有较高的精度。     

采用改进词袋模型的空中目标自动分类

为了解决飞机、直升机、导弹等3类空中目标图像的自动分类问题,提出了一种基于改进词袋模型的空中目标识别方法。首先采集3类多个型号的空中目标灰度图像并分割提取出目标,接着利用稠密采样方法进行SIFT特征提取,然后用模糊C均值聚类方法,对空中目标图像的SIFT特征进行聚类,得到大量空中目标图像的视觉单词。最后用视觉单词直方图训练支持向量机分类器,完成空中目标的自动分类。仿真实验表明,文中提出的算法能准确区分空中目标类别,性能优于传统的采用K均值聚类的词袋模型,且优于仿射矩。     

聚酰亚胺微刻蚀加工工艺研究

研究了RIE刻蚀聚酰亚胺的刻蚀速率、刻蚀表面粗糙度与不同加工工艺参数(包括射频功率、腔室压力、刻蚀气体成分等)之间的相互关系。刻蚀速率与射频功率、腔室压力都呈线性关系,与气体成分的关系是低SF6含量时呈线性,高SF6含量时出现饱和。刻蚀面的粗糙度几乎不受腔室压力的影响,而射频功率高于300 W和低SF6含量时粗糙度会急剧上升。采用腔室压力40 Pa、功率275 W、O2流量80 cm3/min、SF6流量20 cm3/min,通过RIE刻蚀获得了深度为39.5μm的微腔结构,为形成柔性基底空腔以及上悬结构等提供了技术基础。此外,对柔性基底固定技术进行了研究,提出了一种有效固定聚酰亚胺膜的新工艺方法。     

CHARACTERISTIC IMPEDANCE OF SPECIFIC TRANSMISSION LINES WITH OFFSET INNER CONDUCTORS

The partial charge simulation method is presented to solve the characteristicimpedance of the transmission line of specific cross section with an offset inner conductor.Thismethod has a higher accuracy due to the accurate satisfaction of the boundary condition on theouter conductor.The combined method of the Gauss elimination and optimization is used tosolve the equation of charge simulation,and it is an effective method for increasing the accuracyand assuring the convergence.The Green's functions of five transmission lines(i.e,with circular,elliptic,rectangular,trough and slab conductor)are given.