聚焦部分相干平顶涡旋光束对瑞利粒子的捕获

基于广义惠更斯-菲涅尔原理和瑞利散射理论,推导了聚焦部分相干平顶涡旋(partially coherent flat-topped vortex, PCFTV)光束作用在瑞利微粒上辐射力的表达式,主要研究聚焦PCFTV光束对不同折射率的两种粒子的捕获情况。研究结果表明,聚焦PCFTV光束可以在焦点处捕获高折射率和低折射率的粒子。随着光束阶数的增大以及相关长度的减小,光束对微粒的捕获能力增强。所得结果对PCFTV光束应用于光学操控具有一定的意义。     

Blood cell counting based on U-Net++ and YOLOv5

Clinical information about a variety of disorders is available through blood cell counting, which is usually done by manual methods. However, manual methods are complex, time-consuming and susceptible to the subjective experience of inspectors. Although many efforts have been made to develop automated blood cell counting algorithms, the complexity of blood cell distribution and the highly overlapping nature of some red blood cells (RBCs) remain significant challenges that limit the improvement of analytical accuracy. Here, we proposed an end-to-end method for blood cell counting based on deep learning. Firstly, U-Net++ was used to segment the whole blood cell image into several regions of interest (ROI), and each ROI contains only one single cell or multiple overlapping cells. Subsequently, YOLOv5 was used to detect blood cells in each ROI. Specifically, we proposed several strategies, including fine classification of RBCs, adaptive adjustment for non-maximal suppression (NMS) threshold and blood cell morphology constraints to improve the accuracy of detection. Finally, the detection outcomes for each ROI were combined and superimposed. The results show that our method can effectively address the issue of high overlap and precisely segment and detect blood cells, with a 98.18% accuracy rate for blood cell counting.     

黑磷纳米盘-层等离激元系统中的各向异性可调多阶强耦合

黑磷支持各向异性的表面等离激元,可用于设计具备更多功能的原理性器件。用时域有限差分法数值模拟了中红外到远红外波段基于黑磷的层-盘-层系统中不同等离激元模式之间的杂交行为。通过动态调节黑磷中的载流子浓度,可以实现两个晶格方向上强耦合现象的产生与控制。对不同模式间的耦合进行分析并计算,得到吸收光谱中的拉比分裂能最高可达42.9 meV。此外,还计算了偏振角度对各向异性强耦合的影响,其最高可以实现6个吸收频带。该模型可为构建未来在中远红外波段工作的基于二维材料紧凑型各向异性等离激元器件提供基础。     

ADS-B延迟转发电文检测及干扰台定位方法

广播式自动相关监视(ADS-B)技术因明码广播特点,面临较严重的电子欺骗风险.针对延迟转发电文的检测与相应干扰台定位问题,根据ADS-B地面站接收电文的位置间隔的分布特点,该文提出利用顺序电文间瞬时速度与关注期内平均速度间的差异性检测延迟转发电文的方法.根据延迟转发电文的原始电文位置与干扰台间的空间关系,利用ADS-B地面站获取的延迟转发电文位置及时间戳,采用多点定位技术实现对干扰台定位.仿真结果表明,利用瞬时速度与平均速度间的差异性可以有效地实现对延迟转发电文存在与否的检测,干扰台的定位精度与ADS-B地面站的定时精度、采用定位的电文数目、干扰台与航线间距离和干扰台方位等因素有关,且采用正视区域的位置电文可以获得对干扰台较好的定位性能.该文方法可以使ADS-B地面站独立地检测延迟转发干扰和定位相应干扰台.     

An improved U-Net for cell confluence estimation

Cell confluence is an important metric to determine the growth and the best harvest time of adherent cells. At present, the evaluation of cell confluence mainly relies on experienced labor, and thus it is not conducive to the automated cell culture. In this paper, we proposed an improved U-Net algorithm (called DU-Net) for the segmentation of adherent cells. First, the general convolution was replaced by the dilated convolution to expand the receptive fields for feature extraction. Then, the convolutional layers were combined with the batch normalization layers to reduce the dependence of the network on initialization. As a result, the segmentation accuracy and F1-score of the proposed DU-Net for adherent cells with low confluence (<50%) reached 96.94% and 93.87%, respectively, and for those with high confluence (≥50%), they reached 98.63% and 98.98%, respectively. Further, the paired t-test results showed that the proposed DU-Net was statistically superior to the traditional U-Net algorithm.     

基于激光自混合干涉调频信号的位移测量实验

激光自混合干涉在高精度测量领域发挥着越来越重要的作用,微位移测量已应用于大型土木结构、航空航天、健康监测等。传统测量以调幅信号为主,但随着噪声加强,测量误差越来越大,甚至难以测量。为此,采用马赫-曾德尔干涉仪,实现了调幅/调频信号转换。针对大噪声环境下的调频信号,利用多次希尔伯特变换进行相位解卷,实现了原始信号的重构。数值仿真结果证明了该方法的有效性,在10 dB白噪声环境中,系统的信噪比为10.0614 dB,估计误差为0.0614 dB。实验结果表明,微位移重构的误差在100 nm以内,且调频信号的信噪比远高于调幅信号。该方法适用于超精密测量,且在大噪声环境下仍具有较高的信噪比。     

基于多尺度特征选择性融合的遥感图像检测算法北大核心CSCD

遥感图像的检测在监察自然环境、军事、国土安全等方面具有极其广阔的应用前景,而遥感图像具有背景复杂、目标面积小、特征提取困难等缺点,进行检测时容易产生小目标漏检问题。本文提出一种基于多尺度特征选择性融合的遥感图像检测算法。所提算法采用改进的Resnet50作为主干网络,将Resnet50第一个卷积替换成动态卷积,并将其ConvBlock模块中的卷积替换成金字塔卷积,提高特征提取能力。同时,为了避免遗漏底层信息,在动态卷积层后加入所提有效空间通道注意力机制模块。最后,选取基于上下文信息的不同尺度特征进行融合,提高了模型对目标物体的定位能力。实验结果表明,本文算法在保证速度的同时提高了对遥感图像的检测精度,在遥感图像公开数据集RSOD和NWPUVHR-10上平均精度均值(mean average precision,mAP)分别达到91.88%和90.23%,检测速度达到33 FPS。