Efficient generation of targeted point mutations in the Brassica oleracea var.botrytis genome via a modified CRISPR/Cas9 system

In this study,we used the modified CRISPR/Cas9 system to produce targeted point mutations in cauliflower.Acetolactate synthase(ALS)and Centromere-specific histone H3 variant(CENH3)genes were selected as the base-editing targets and hypocotyls of cauliflower were used as explants.For ALS gene,a C-to-T conversion in the Pro182 codon(CCT)can alter the encoded amino acid,likely resulting in herbicide resistance,and a C-to-T mutation in the Leu133 codon(CTT)in the CENH3 gene may produce a haploid inducer.Results indicated that the transformation efficiency was 1.8%–4.5%and the mutation efficiencies for the ALS and CENH3 genes were approximately 22%and 87%,respectively.The ALS mutant cauliflower showed strong herbicide resistance,with possible immediate implications for broadleaf weed control in cauliflower fields.

Point association analysis of vessel target detection with SAR, HFSWR and AIS

A space-borne synthetic aperture radar （SAR）, a high frequency surface wave radar （HFSWR）, and a ship automatic identification system （AIS） are the main remote sensors for vessel monitoring in a wide range. These three sensors have their own advantages and weaknesses, and they can complement each other in some situations. So it would improve the capability of vessel target detection to use multiple sensors including SAR, HFSWR, and A/S to identify non-cooperative vessel targets from the fusion results. During the fusion process of multiple sensors＇ detection results, point association is one of the key steps, and it can affect the accuracy of the data fusion and the efficiency of a non-cooperative target＇s recognition. This study investigated the point association analyses of vessel target detection under different conditions： space- borne SAR paired with AIS, as well as HFSWR, paired with AIS, and the characteristics of the SAR and the HFSWR and their capability of vessel target detection. Then a point association method of multiple sensors was proposed. Finally, the thresholds selection of key parameters in the points association （including range threshold, radial velocity threshold, and azimuth threshold） were investigated, and their influences on final association results were analyzed.

A High Speed Detection Scheme for Point Targets in a Multitarget Environment

The purpose of this paper is to develop a high speed detection scheme for moving and / or stationary point targets in a multitarget environment as registered in an IR image sequence. An iterative approximate 3-D line searching algorithm based upon the geometric representation of lines (for non-maneuvering targets in space) in a 3-D space is derived. The convergency of the algorithm is proved. An analysis is performed of the theoretical detection performance of the algorithm. The statistical experiment results show high effectiveness and computational efficiency of the algorithm in the case of low SNR. The idea may be employed to satisfy the real-time processing requirement of an IR system.

The combined FSS-SPRT method for detection and tracking of low SNR point targets

For the detection and tracking of dim point targets with SNR<2 dB, the combined SPRT and FSS method is given to accomplish detection in which likelihood testing are carried out twice to prune constantly. Firstly, the SPRT is developed aiming at the heuristic segments formed by correlation analysis. In order to avoid missing detection the threshold is chosen much lower. Secondly, by adding samples and choosing the one most similar to the heuristic segment to make state estimation FSS is implemented. This time we choose a higher threshold. Moreover in preprocessing the compound kernel estimation is designed to depress varying background clutter. Multiple experimental sequences validate that the method is more suitable for the dim targets detection and tracking compared with the scheme choosing the higher intensity pixel in tracking. It not only has perfect detection performance but also can greatly enhance tracking performance.

Application of Adaptive Reduced Sigma Points Unscented Kalman Filter to the Tracking of Maneuvering Target

Based on the principle of statistical linear regression, a set of n ＋ 2 sigma points instead of 2n ＋ 1 sigma points used in the unscented Kalman filter （UKF）, is constructed to approximate the system state. And filter accuracy is second order. Real-time of modified UKF is improved. In order to describe accurately the maneuvering target, the ＂current＂ statistical model is used. And the equation of acceleration error covariance is modified at every sample time of the filter. The modified adaptive UKF is presented for estimating the position, velocity and acceleration of maneuvering target. Monte Carlo simulations show the modified adaptive UKF acquires good performance for tracking position of maneuvering target. The modified adaptive UKF has better computational efficiency than UKF.

New Approach in Processing of the Infrared Image Sequence for Moving Dim Point Targets Detection

The development of an efficient moving target detection algorithm in IR-image sequence is considered one of the most critical research fields in modern IRST (Infrared Search and Track) systems, especially when dealing with moving dim point targets. In this paper we propose a new approach in processing of the Infrared image sequence for moving dim point targets detection built on the transformation of the IR-image sequence into 4-vectors for each frame in the sequence. The results of testing the proposed approach on a set of frames having a simple single pixel target performing a different motion patterns show the validity of the approach for detecting the motion, with simplicity in calculation and low time consumption.

面向对海监视的舰船目标跟踪与航迹融合数据集

对海监视中航迹实时关联与轨迹融合任务是安全防控、区域态势监视、远程精确打击等军民应用领域的热点和难点问题,高质量的数据集对推动目标跟踪与融合技术在该领域的研究有重要作用。本研究针对目标跟踪与融合领域技术研究的数据需求以及目前公开数据集所存在的数据缺乏、场景设计针对性差、数据格式单一、数据描述不全等问题,通过仿真软件对复杂场景中多传感器多目标探测数据进行仿真,提供了一套面向典型对海监视场景(以舰船为探测对象的2D雷达与侦察传感器﹝ESM﹞)的目标跟踪与航迹融合数据集。其中仿真软件包括剧情发生器和传感器模拟器两部分,是一套成熟的目标跟踪场景仿真环境,提供逼真的探测数据模拟能力。本数据集涵盖的传感器对象包括2D雷达与侦察传感器,目标包括典型的海上舰船类别,并支持携带辐射源配置,设计了高速运动、密集交通、多传感器数据融合、特定舰船侦测和交叉定位等多种典型场景。本数据集中共包含368155条目标点迹,舰船数量为101条,时间范围15000秒,数据格式符合实际设备上报情景、探测误差模型符合实际。本数据集通过对数据误差进行正态性检验、对检测率、虚警率的场景检验以及实地调研,完成了对数据的准确性评估与数据完备性控制,可为舰船目标跟踪、轨迹融合等算法研究与验证提供基础数据。

Quantum search for unknown number of target items by hybridizing fixed-point method with trail-and-error method

For the unsorted database quantum search with the unknown fraction λ of target items, there are mainly two kinds of methods, i.e., fixed-point and trail-and-error.(i) In terms of the fixed-point method, Yoder et al. [Phys. Rev. Lett.113 210501(2014)] claimed that the quadratic speedup over classical algorithms has been achieved. However, in this paper, we point out that this is not the case, because the query complexity of Yoder’s algorithm is actually in O(1/λ01/2)rather than O(1/λ1/2), where λ0 is a known lower bound of λ.(ii) In terms of the trail-and-error method, currently the algorithm without randomness has to take more than 1 times queries or iterations than the algorithm with randomly selected parameters. For the above problems, we provide the first hybrid quantum search algorithm based on the fixed-point and trail-and-error methods, where the matched multiphase Grover operations are trialed multiple times and the number of iterations increases exponentially along with the number of trials. The upper bound of expected queries as well as the optimal parameters are derived. Compared with Yoder’s algorithm, the query complexity of our algorithm indeed achieves the optimal scaling in λ for quantum search, which reconfirms the practicality of the fixed-point method. In addition, our algorithm also does not contain randomness, and compared with the existing deterministic algorithm, the query complexity can be reduced by about 1/3. Our work provides a new idea for the research on fixed-point and trial-and-error quantum search.

改进人工势场算法的路径规划

人工势场法是一种适用于局部路径规划的算法,针对人工势场法存在的目标不可达、局部极小值等固有缺陷,提出了一种改进后的人工势场法。首先针对目标不可达问题,将引力影响因子添加到斥力场的生成中,改进斥力场函数,从而避免引力与斥力合力为零的情况。针对局部极小值问题,通过设立虚拟目标点来引入额外外力,打破机器人的平衡问题。通过与其他算法的对比实验,仿真结果显示,改进人工势场法规划的路径长度和消耗时间都更短,稳定性更强。

一种多层多模态融合3D目标检测方法

在自动驾驶感知系统中视觉传感器与激光雷达是关键的信息来源,但在目前的3D目标检测任务中大部分纯点云的网络检测能力都优于图像和激光点云融合的网络,现有的研究将其原因总结为图像与雷达信息的视角错位以及异构特征难以匹配,单阶段融合算法难以充分融合二者的特征.为此,本文提出一种新的多层多模态融合的3D目标检测方法:首先,前融合阶段通过在2D检测框形成的锥视区内对点云进行局部顺序的色彩信息(Red Green Blue,RGB)涂抹编码;然后将编码后点云输入融合了自注意力机制上下文感知的通道扩充PointPillars检测网络;后融合阶段将2D候选框与3D候选框在非极大抑制之前编码为两组稀疏张量,利用相机激光雷达对象候选融合网络得出最终的3D目标检测结果.在KITTI数据集上进行的实验表明,本融合检测方法相较于纯点云网络的基线上有了显著的性能提升,平均mAP提高了6.24%.

远距离和遮挡下三维目标检测算法研究

针对现有三维目标检测算法对存在遮挡及距离较远目标检测效果差的问题,以基于点云的三维目标检测算法(3D object proposal generation and detection from point cloud,PointRCNN)为基础,对网络进行改进,提高三维目标检测精度。对区域生成网络(region proposal network,RPN)获取的提议区域(region of interest,ROI)体素化处理,同时构建不同尺度的区域金字塔来捕获更加广泛的兴趣点;加入点云Transformer模块来增强对网格中心点局部特征的学习;在网络中加入球查询半径预测模块,使得模型可以根据点云密度自适应调整球查询的范围。最后,对所提算法的有效性进行了试验验证,在KITTI数据集下对模型的性能进行评估测试,同时设计相应的消融试验验证模型中各模块的有效性。

基于卡尔曼滤波的激光雷达点云跟踪方法研究

激光雷达点云目标跟踪是环境感知与定位的重要研究内容,具有广泛的应用前景。由于激光雷达存在探测范围有限、易受遮挡和散射条件影响等问题,无法保证跟踪过程中目标点云特征的完整性和正确性,跟踪目标丢失时有出现。为了提高跟踪过程中的鲁棒性,提出一种基于卡尔曼滤波的2D激光点云跟踪方法。该方法首先对聚类后的点云建立包围盒集合,其次对包围盒跟踪框建立卡尔曼滤波模型,将前一帧跟踪框最优估计值与当前帧包围盒,通过交并比方法进行关联性匹配,将关联性最大结果作为当前帧目标点云,并更新卡尔曼滤波模型参数,从而实现目标点云的实时跟踪。实验结果表明,所提方法提高了跟踪过程的鲁棒性和准确性。

基于深度学习的自动驾驶场景3D目标检测方法

针对传统PV-RCNN在点云上采样效率低下和采样精度存在偏差等问题,提出了一种基于PV-RCNN改进的3D目标检测方法。更改关键点采样策略,使得有限的关键点可以更加地聚集在proposal区域范围内,更多的编码有效前景点特征来用于后面的proposal refinement,有效产生更具有代表性的关键点。用局部特征聚合的VectorPool聚合模块取代体素集抽象和ROI网格池化模块中的集合抽象,更高效的针对稀疏和不规则点云数据进行编码。在KITTI数据集上对算法验证,结果表明:行人鸟瞰图检测,困难级别检测精度提升较为显著,达到了10.46%,整体帧率提升为33.74%,文中的方法拥有更好的检测性能。

改进YOLOv5模型的轮胎标记点检测算法研究

为实现在轮胎标记点快速精准识别,提出了一种基于YOLOv5改进模型的标记点识别方法。通过引入CBAM和SimAM两种注意力模块来提高网络提取特征的能力,同时考虑到轮胎标记点在图片中为小目标,利用α-IoU损失函数代替GIoU损失函数,即为GIoU函数添加α次幂后通过不断调节α的值来获取较好的识别效果。试验结果显示:文中提出的模型平均精度为91.1%,比原YOLOv5的模型平均精度88%提升了3.1%,比原有的YOLOv5模型有更高的准确度。

多功能旋转靶装置研究

针对D-D中子发生器采用静态水冷靶时中子产额不稳定、中子产额持续下降等主要问题,研制了一套多功能紧凑型旋转靶装置。装置采用一体化设计,结构紧凑、尺寸小,具备靶体高速旋转和水冷、靶点可视化监测、靶面温度实时测量、中子产额实时监测等功能。本文介绍了该装置的主体结构、功能设计和性能测试,以及靶结构对中子散射影响的模拟计算。性能测试结果表明,该装置真空度满足加速器运行要求,相比静态水冷靶,束流靶点中心最高温度明显降低,中子产额稳定度明显提高。模拟计算结果显示中子能谱峰展宽范围为0~0.0577 MeV,散射中子占比为10.53%~26.75%。本文还针对模拟计算结果和测量结果中存在的问题进行了分析,提出了改进和优化方案。

不同分布下红外主动目标特征点配准方法研究

视觉测量中经常需要用到特征匹配来计算位姿信息,但尚无针对红外主动目标设计特征匹配可用的算法,为实现对不同分布红外主动目标的匹配,本文提出了一种通用的两阶段特征点匹配方法。第一阶段为粗配准,首先检测图像特征点集的凸包,获取最外围点;通过构建三角形特征集,并使用马氏距离进行相似三角形计算搜索实现快速粗配准。第二阶段为精匹配,首先通过粗匹配特征计算欧拉角避免匹配结果的180°旋转对称;针对粗配准后的可能存在的特征点缺失问题,采用极线约束精匹配策略,充分利用已匹配特征点的几何信息,有效实现对剩余点的精确匹配。理论分析与实验表明,在13个红外发光点组成的旋转对称点集及非旋转对称点集下,该方法在绝对大小0°~40°的旋转范围内能高效匹配,实验测试极限性能能够达到50°,并对实际场景下特征点的遮挡等情况具有较好的鲁棒性,实验结果验证其适应性与稳定性,具有较高的实用价值。

circ-104640在Ⅰ/Ⅱ期肺腺癌组织及血清中的异常高表达及其意义

目的探究circ-104640在Ⅰ/Ⅱ期肺腺癌患者的肿瘤组织、癌旁组织、血清和肺腺癌细胞系中的表达情况,评估其作为Ⅰ/Ⅱ期肺腺癌潜在的新的生物标志物和治疗靶点的可能性。方法从GEO数据库中下载微阵列数据集GSE101684并获得Ⅰ/Ⅱ期肺腺癌差异化表达circRNA的表达谱,挑选特异性高表达的circ-104640作为候选标志物。使用实时荧光定量PCR法检测circ-104640在Ⅰ/Ⅱ期肺腺癌患者的组织、血清和肺腺癌细胞系中的相对表达量,分析其与临床病理特征的关系。采用ROC曲线评估circ-104640对Ⅰ/Ⅱ期肺腺癌的诊断价值。结果基于GEO数据库的分析结果和Ⅰ/Ⅱ期肺腺癌患者的组织样本及血液样本,发现与癌旁组织、健康人血清和肺上皮细胞系相比,circ-104640在Ⅰ/Ⅱ期肺腺癌组织、血清和肺腺癌细胞系中表达增加。此外,circ-104640的结构具有稳定性且对RNase-R的消化具有一定程度的抗性。ROC结果显示,在肺腺癌组织和血清中circ-104640诊断肺腺癌的AUC分别为0.829(95%CI:0.758~0.901,P<0.001)和0.874(95%CI:0.809~0.939,P<0.0001)。结论circ-104640在肺腺癌组织、血清和细胞系中呈高表达,并且与肺腺癌的发生发展有着密切的联系。circ-104640的环状结构使其能够稳定存在并对RNase-R的消化具有抗性。circ-104640可能是Ⅰ/Ⅱ期肺腺癌潜在的新的生物标志物和治疗靶点,且对临床Ⅰ/Ⅱ期肺腺癌有一定的早期诊断价值。

基于激光雷达的非合作航天器姿态测量

针对目标自遮挡导致姿态解算精度较低的问题,提出了一种基于激光雷达(LiDAR)点云的空间非合作目标姿态估计方法。初始姿态获取阶段,通过RANSAC算法与曲率聚类分割算法对目标特征分割,再与模板特征进行匹配获得粗配准变换矩阵,然后利用迭代最近点(ICP)算法精配准解算初始姿态;姿态跟踪阶段,通过快速点云配准计算相对姿态,通过逐帧点云姿态传递完成目标姿态测量。利用卫星模型搭建实验平台进行姿态测量实验。实验结果表明:所提方法能够稳定完成姿态解算,验证了所提方法的精度与可行性。

融合点线特征的空间失效目标双目视觉位姿测量

提出了一种融合点线特征的双目视觉位姿估计方法,该方法基于视频的图像帧,先分别通过ORB算法和LSD算法提取图像帧的点、线特征,并采用LBD描述子实现帧间匹配;然后基于极线搜索方法获得右图像中与左图像对应的特征,从而获得匹配特征的空间坐标;最后基于点线特征融合的重投影模型,利用Levenberg-Marquardt法迭代获得失效目标的相对位姿。仿真实验表明,融合点线特征的视觉位姿估计方法相比单纯点特征的位姿估计具有更好的鲁棒性,尤其针对高速旋转目标,能更好地进行位姿跟踪测量。

基于虚拟点云的二阶段多模态融合网络

针对点云的稀疏性和无序性对目标检测准确率的影响,本文提出了一种基于虚拟点云的二阶段多模态融合网络VPC-VoxelNet。首先,利用图像检测目标信息构造虚拟点云,增加点云的密集程度,从而提高目标特征的表现;其次,增加点云特征维度以区分真实和虚拟点云,并使用含置信度编码的体素,增强点云的相关性;最后,采用虚拟点云的比例系数设计损失函数,增加图像检测有监督训练,提高二阶段网络训练效率,避免二阶段端到端网络模型存在的模型误差累计问题。该目标检测网络VPC-VoxelNet在KITTI数据集上进行了测试,检测精度优于经典三维点云检测网络和某些多传感器信息融合网络,车辆检测精度达到了86.9%。