Virtual source approach for maximizing resolution in high-penetration gamma-ray imaging

High-energy gamma-ray radiography has exceptional penetration ability and has become an indispensable nondestructive testing(NDT)tool in various fields.For high-energy photons,point projection radiography is almost the only feasible imaging method,and its spatial resolution is primarily constrained by the size of the gamma-ray source.In conventional industrial applications,gamma-ray sources are commonly based on electron beams driven by accelerators,utilizing the process of bremsstrahlung radiation.The size of the gamma-ray source is dependent on the dimensional characteristics of the electron beam.Extensive research has been conducted on various advanced accelerator technologies that have the potential to greatly improve spatial resolution in NDT.In our investigation of laser-driven gamma-ray sources,a spatial resolution of about 90μm is achieved when the areal density of the penetrated object is 120 g/cm^(2).A virtual source approach is proposed to optimize the size of the gamma-ray source used for imaging,with the aim of maximizing spatial resolution.In this virtual source approach,the gamma ray can be considered as being emitted from a virtual source within the convertor,where the equivalent gamma-ray source size in imaging is much smaller than the actual emission area.On the basis of Monte Carlo simulations,we derive a set of evaluation formulas for virtual source scale and gamma-ray emission angle.Under optimal conditions,the virtual source size can be as small as 15μm,which can significantly improve the spatial resolution of high-penetration imaging to less than 50μm.

Fast compressed sensing spectral measurement with adaptive gradient multiscale resolution

We propose a fast,adaptive multiscale resolution spectral measurement method based on compressed sensing.The method can apply variable measurement resolution over the entire spectral range to reduce the measurement time by over 75%compared to a global high-resolution measurement.Mimicking the characteristics of the human retina system,the resolution distribution follows the principle of gradually decreasing.The system allows the spectral peaks of interest to be captured dynamically or to be specified a priori by a user.The system was tested by measuring single and dual spectral peaks,and the results of spectral peaks are consistent with those of global high-resolution measurements.

Lightweight Multi-Resolution Network for Human Pose Estimation

Human pose estimation aims to localize the body joints from image or video data.With the development of deeplearning,pose estimation has become a hot research topic in the field of computer vision.In recent years,humanpose estimation has achieved great success in multiple fields such as animation and sports.However,to obtainaccurate positioning results,existing methods may suffer from large model sizes,a high number of parameters,and increased complexity,leading to high computing costs.In this paper,we propose a new lightweight featureencoder to construct a high-resolution network that reduces the number of parameters and lowers the computingcost.We also introduced a semantic enhancement module that improves global feature extraction and networkperformance by combining channel and spatial dimensions.Furthermore,we propose a dense connected spatialpyramid pooling module to compensate for the decrease in image resolution and information loss in the network.Finally,ourmethod effectively reduces the number of parameters and complexitywhile ensuring high performance.Extensive experiments show that our method achieves a competitive performance while dramatically reducing thenumber of parameters,and operational complexity.Specifically,our method can obtain 89.9%AP score on MPIIVAL,while the number of parameters and the complexity of operations were reduced by 41%and 36%,respectively.

Ultrahigh spatiotemporal resolution beam signal reconstruction with bunch phase compensation

Various electromagnetic signals are excited by the beam in the acceleration and beam-diagnostic elements of a particle accelerator.It is important to obtain time-domain waveforms of these signals with high temporal resolution for research,such as the study of beam–cavity interactions and bunch-by-bunch parameter measurements.Therefore,a signal reconstruction algorithm with ultrahigh spatiotemporal resolution and bunch phase compensation based on equivalent sampling is proposed in this paper.Compared with traditional equivalent sampling,the use of phase compensation and setting the bunch signal zero-crossing point as the time reference can construct a more accurate reconstructed signal.The basic principles of the method,simulation,and experimental comparison are also introduced.Based on the beam test platform of the Shanghai Synchrotron Radiation Facility(SSRF)and the method of experimental verification,the factors that affect the reconstructed signal quality are analyzed and discussed,including the depth of the sampled data,quantization noise of analog-to-digital converter,beam transverse oscillation,and longitudinal oscillation.The results of the beam experiments show that under the user operation conditions of the SSRF,a beam excitation signal with an amplitude uncertainty of 2%can be reconstructed.

High-resolution neutronics model for ^(238)Pu production in high-flux reactors

We proposed and compared three methods(filter burnup,single energy burnup,and burnup extremum analysis)to build a high-resolution neutronics model for 238Pu production in high-flux reactors.The filter burnup and single energy burnup methods have no theoretical approximation and can achieve a spectrum resolution of up to~1 eV,thereby constructing the importance curve and yield curve of the full energy range.The burnup extreme analysis method combines the importance and yield curves to consider the influence of irradiation time on production efficiency,thereby constructing extreme curves.The three curves,which quantify the transmutation rate of the nuclei in each energy region,are of physical significance because they have similar distributions.A high-resolution neutronics model for ^(238)Pu production was established based on these three curves,and its universality and feasibility were proven.The neutronics model can guide the neutron spectrum optimization and improve the yield of ^(238)Pu by up to 18.81%.The neutronics model revealed the law of nuclei transmutation in all energy regions with high spectrum resolution,thus providing theoretical support for high-flux reactor design and irradiation production of ^(238)Pu.

The environmental analysis and site selection of mussel and large yellow croaker aquaculture areas based on high resolution remote sensing

Mussel aquaculture and large yellow croaker aquaculture areas and their environmental characteristics in Zhoushan were analyzed using satellite data and in-situ surveys.A new two-step remote sensing method was proposed and applied to determine the basic environmental characteristics of the best mussel and large yellow croaker aquaculture areas.This methodology includes the first step of extraction of the location distribution and the second step of the extraction of internal environmental factors.The fishery ranching index(FRI1,FRI2)was established to extract the mussel and the large yellow croaker aquaculture area in Zhoushan,using Gaofen-1(GF-1)and Gaofen-6(GF-6)satellite data with a special resolution of 2 m.In the second step,the environmental factors such as sea surface temperature(SST),chlorophyll a(Chl-a)concentration,current and tide,suspended sediment concentration(SSC)in mussel aquaculture area and large yellow croaker aquaculture area were extracted and analyzed in detail.The results show the following three points.(1)For the extraction of the mussel aquaculture area,FRI1 and FRI2 are complementary,and the combination of FRI1 and FRI2 is suitable to extract the mussel aquaculture area.As for the large yellow croaker aquaculture area extraction,FRI2 is suitable.(2)Mussel aquaculture and the large yellow croaker aquaculture area in Zhoushan are mainly located on the side near the islands that are away from the eastern open waters.The water environment factor template suitable for mussel and large yellow croaker aquaculture was determined.(3)This two-step remote sensing method can be used for the preliminary screening of potential site selection for the mussels and large yellow croaker aquaculture area in the future.the fishery ranching index(FRI1,FRI2)in this paper can be applied to extract the mussel and large yellow croaker aquaculture areas in coastal waters around the world.

Role of Media in Promoting Peace and Conflict Resolution in North Kivu, Democratic Republic of Congo

The research examined the role of media in promoting peace and conflict resolution in North Kivu,Democratic Republic of Congo.The security situation in the Democratic Republic of the Congo(DRC),particularly in the eastern region of North Kivu,has been deteriorating.The study was anchored in social identity theory.The research methodology employed for this study was qualitative,focusing on the analysis of Mr.Edgar Mateso’s contributions to Radio Okapi’s“Dialogue entre Congolais”program during the period from 2019 to 2023.The research was conducted within the broader context of the persistent war and conflict in the Democratic Republic of Congo,providing valuable insights into the dynamics and challenges of addressing the ongoing insecurity and violence in the region.The study found that media,exemplified by Radio Okapi,plays a multifaceted and significant role in promoting peace and conflict resolution in North Kivu,Democratic Republic of Congo(DRC).It serves as a critical source of accurate information,enabling informed decision-making regarding ceasefire agreements,peace talks,and humanitarian aid.Media fosters dialogue and understanding among different stakeholders,contributing to reconciliation efforts.Additionally,it raises awareness about the human cost of the conflict,challenges misinformation,monitors peace agreements,amplifies the concerns of the affected population,and promotes human rights and justice.Media also engages youth,serves as an early warning system,and attracts global attention to the conflict.It is recommended that media organizations in North Kivu continue their efforts to facilitate dialogue and understanding among different stakeholder groups.Additionally,media should maintain its focus on raising awareness about the human cost of the conflict,ensuring that the suffering of civilians remains in the spotlight and generates international empathy and support.Media outlets should also continue their role as watchdogs by closely monitoring the implementation of ceasefire agreements and reporting any violations transparently.To strengthen media’s role in promoting peace,there should be continued advocacy for peace through dedicated radio programs,news reports,and editorial content.Internationally,media should continue to provide comprehensive coverage of the conflict in North Kivu,attracting global attention and shaping the perception of the conflict on the global stage.Lastly,media organizations should preserve a lasting legacy of peace by archiving peace-related content,documentaries,and narratives of reconciliation.

High-Resolution Remote Sensing Imagery for the Recognition of Traditional Villages

Traditional Chinese villages,vital carriers of traditional culture,have faced significant alterations due to urbanization in recent years,urgently necessitating artificial intelligence data updates.This study integrates high spatial resolution remote sensing imagery with deep learning techniques,proposing a novel method for identifying rooftops of traditional Chinese village buildings using high-definition remote sensing images.Using 0.54 m spatial resolution imagery of traditional village areas as the data source,this method analyzes the geometric and spectral image characteristics of village building rooftops.It constructs a deep learning feature sample library tailored to the target types.Employing a semantically enhanced version of the improved Mask R-CNN(Mask Region-based Convolutional Neural Network)for building recognition,the study conducts experiments on localized imagery from different regions.The results demonstrated that the modified Mask R-CNN effectively identifies traditional village building rooftops,achieving an of 0.7520 and an of 0.7400.It improves the current problem of misidentification and missed detection caused by feature heterogeneity.This method offers a viable and effective approach for industrialized data monitoring of traditional villages,contributing to their sustainable development.

Research on Risk Prevention and Resolution Strategies of College Network Ideology in the Context of the Internet

With the rapid development of the Internet,the network ideology of colleges and universities is facing severe challenges.This paper deeply analyzes the root of the risk of network ideology and makes a specific investigation of the status quo of network public opinion in colleges and universities.On this basis,the study explores and puts forward a series of targeted risk prevention and resolution strategies,aiming at providing a systematic solution for the network ideology security of colleges and universities.In this paper,with the combination of theory and practice as the path,we verify the effectiveness and applicability of the proposed strategy through the analysis of the implementation effect of the strategy.This study also provides theoretical support and practical guidance for the prevention and control of ideological risks and public opinion guidance in universities under the network environment,which has important practical significance.With the continuous progress of network technology,the threats to the network ideology of colleges and universities are increasing.For example,the spread of false information has become a serious problem affecting the security of college network ideology.

基于改进DQN算法的无人仓多AGV路径规划

针对无人仓中多AGV路径规划与冲突问题,以最小化总行程时间为目标,建立多AGV路径规划模型,提出一种基于动态决策的改进DQN算法。算法设计了基于单AGV静态路径规划的经验知识模型,指导AGV的学习探索方向,提前规避冲突与障碍物,加快算法收敛。同时提出基于总行程时间最短的冲突消解策略,从根本上解决多AGV路径冲突与死锁问题。最后,建立无人仓栅格地图进行仿真实验。结果表明,本文提出的模型和算法较其他DQN算法收敛速度提升13.3%,平均损失值降低26.3%。这说明该模型和算法有利于规避和化解无人仓多AGV路径规划冲突,减少多AGV总行程时间,对提高无人仓作业效率具有重要指导意义。

基于MaxEnt模型的北极村国家级自然保护区紫貂栖息地适宜性评价

在人类支配的景观中,生境退化已经导致多个物种种群数量不断减少,分布范围不断缩减。紫貂(Martes zibellina)为国家Ⅰ级重点保护动物,种群数量稀少,开展栖息地适宜性研究工作对制定科学的栖息地保护计划至关重要。于2021年1月—2022年8月在黑龙江省北极村国家级自然保护区采用样线调查法、足迹链跟踪、远红外相机监测综合收集到紫貂和猎物(雪兔)活动点信息。利用最大熵(MaxEnt)栖息地建模分析方法,首次在多个分辨率尺度背景下对紫貂种群的栖息地适宜性进行评价,研究结果表明:(1)利用ArcGIS 10.4重采样后在6个分辨率尺度(30m、60m、120m、240m、480m、960m)进行栖息地建模分析,基于主要栖息地变量因子对模型的贡献率及稳定性影响,并综合考虑研究区域面积,最终选定30m分辨率尺度作为紫貂栖息地最佳分析建模尺度,在30m分辨率尺度栖息地预测模型的曲线下面积(AUC)值为0.881;(2)研究发现猎物资源、植被类型和地形变量是影响紫貂栖息地适宜性的主要变量因子:雪兔出现概率较高、距草地与河流较近、海拔约400—600m、距常绿针叶林1.5km、距落叶针叶林约200m、坡向为50—250°的区域为紫貂的适宜栖息地;(3)栖息地适宜性分析表明,北极村国家级自然保护区紫貂适宜栖息地和次适宜栖息地面积共计23.66km2,约占保护区的17.2%,主要集中在保护区中部,而东部和西北部区域,栖息地破碎化较严重。基于模型结果与野外调查,提出了三条建议:(1)应严格控制人为活动,避免因人类干扰造成不适宜栖息地面积的持续扩大;(2)建立生态廊道促进保护区西部与中部紫貂种群进行个体交流,降低紫貂种群局部区域灭绝概率;(3)对东部地区破碎化的栖息地进行修复,扩大东部适宜栖息地面积,使破碎化的栖息地连接为整体。为分布于我国最北端的紫貂种群恢复创造条件,这对于构建该地区相对稳定的生物多样性保护空间格局有着重要意义。

FGOALS高分辨率气候模式系统模式研制与应用综述

当今气候系统模式发展的重要趋势之一,是通过提高模式的空间分辨率,改进对气候系统中多尺度相互作用过程和极端事件的模拟能力。过去5年里,中国科学院大气物理研究所发展并完善了25 km分辨率大气环流分量模式FAMIL2.2、1/10°分辨率海洋环流分量模式LICOM3.0,并以此为基础建立了高分辨率气候系统模式FGOALS-f3-H。利用上述高分辨率模式,开展了大量的数值模拟试验和预报/预测研究,其中包括国际耦合模式比较计划第六阶段(CMIP6)的高分辨率模式比较子计划(HighResMIP),建立了海洋环流预测系统(LFS)等。初步评估分析表明,相对于低分辨率模式,高分辨率模式对气候平均态和气候变率的模拟能力均有明显改进。其中高分辨率大气环流模式可以更好地模拟台风、极端降水事件,高分辨率海洋模式可以更好地模拟海洋中尺度涡旋和西边界流,而高分辨率耦合模式则可以更好重现中尺度海气相互作用过程、热带不稳定波动(TIW)等事件。

颈动脉超声高分辨MRI联合血清miR-27a预测颈动脉支架植入术后抗血小板治疗患者预后的价值

目的探讨颈动脉超声、高分辨MRI参数联合血清miR-27a预测颈动脉狭窄患者经颈动脉支架植入术后抗血小板治疗预后的价值。方法纳入2021-01—2022-12于大庆龙南医院接受颈动脉支架植入术及抗血小板治疗的110例颈动脉狭窄患者。术前采用彩色多普勒超声诊断仪对所有研究对象进行检查,测定并记录平均血流速度(MFV)、舒张末期最低血流速度(EDV)、最大血流速度(PSV)及颈动脉狭窄率,采用高分辨MRI检查并记录患者的斑块偏心指数和斑块强化程度,应用荧光定量PCR检测血清miR-27a水平。患者出院后随访1 a,观察预后情况,分为预后良好组和预后不良组。结果110例患者中预后良好者83例,预后不良者27例。预后良好组和预后不良组患者性别、年龄、身高、体质量、吸烟史、饮酒史情况比较均无统计学差异(P>0.05)。预后良好组患者的PSV、斑块强化程度和血清miR-27a水平与预后不良组相比显著降低(P<0.05)。颈动脉狭窄患者MFV和PSV与血清miR-27a水平呈显著正相关(P<0.05),颈动脉狭窄患者的MFV、EDV、PSV、斑块偏心指数、斑块强化程度和血清miR-27a水平均与颈动脉狭窄率呈显著正相关(P<0.05)。PSV、斑块强化程度和血清miR-27a水平预测颈动脉狭窄患者预后的AUC分别为0.764(95%CI:0.662~0.866)、0.649(95%CI:0.519~0.779)和0.832(95%CI:0.748~0.916)。PSV、斑块强化程度联合血清miR-27a预测颈动脉狭窄患者预后的AUC为0.895(95%CI:0.830~0.960)。结论颈动脉超声、高分辨MRI参数联合血清miR-27a对颈动脉狭窄术后患者的预后预测具有一定价值。

基于Transformer的陶瓷轴承表面缺陷检测方法

针对传统机器视觉检测方法中,由于陶瓷轴承滚动体表面曲率大、对比度低,表面成像模糊导致后续缺陷检测精度低的问题,提出一种基于Transformer的超分辨率残差网络。首先,网络使用残差学习策略,通过预测模糊图像与清晰图像之间的差值,实现超分辨率任务;其次,在网络上前端插入通道注意力模块和空间注意力模块并改进L2多头自注意力模块,以增强图像纹理、改善梯度爆炸问题;最后,针对超分辨率重建任务,提出一种两阶段训练策略优化训练过程。自建陶瓷轴承表面缺陷数据集上的大量实验结果表明,所提出网络模型在客观指标与主观评价上均优于MSESRGAN、VSDR等超分辨率算法,重建图像SSIM为0.939,PSNR为36.51 dB。

基于UHPLC-Q-Exactive Orbitrap HRMS技术结合化学计量学方法的不同干燥处理杜仲叶成分分析

采用基于液质联用的非靶向代谢组学技术结合化学计量学数据自动解析软件AntDAS-LCHRMS分析了4种不同干燥处理(冻干、热泵烘干、电热烘干、晒干)杜仲叶样本中的化合物。杜仲叶样本数据由超高效液相色谱-四极杆-静电场轨道阱高分辨质谱(UHPLC-Q-Exactive Orbitrap HRMS)分别在正、负离子模式下进行采集,经AntDAS-LCHRMS软件解析,共鉴定出71种差异性化合物,经标准品验证确定40种化合物,包括环烯醚萜类、有机酸类、黄酮类、氨基酸类、核苷类、维生素类等9类物质。其中,正、负离子模式下均可识别并验证的化合物有车叶草苷、绿原酸、芦丁、异槲皮苷、车叶草苷酸、京尼平苷等25种化合物。层次聚类分析(HCA)及主成分分析(PCA)结果均显示,相同处理的杜仲叶样本各自聚成一类,不同处理的杜仲叶样本可明显区分。热图分析进一步揭示了不同干燥处理杜仲叶样本中差异性化合物的含量变化。晒干处理样本中苯丙氨酸及色氨酸等氨基酸类物质的水平较高;冻干及热泵烘干处理样本中有机酸类、环烯醚萜类、糖类等含量较高;电热烘干样本中核苷类、黄酮类物质的含量较高;黄酮类物质在冻干、热泵烘干及晒干样本中差异较小。研究结果为不同干燥处理杜仲叶的成分分析、品质评价及其开发应用提供了科学依据,也可为其他复杂药用植物体系的化学成分分析提供参考。

一种基于稀疏贝叶斯学习的离网DOA估计算法

本文提出一种基于稀疏贝叶斯学习的改进离网DOA估计算法,以提升非理想测向环境下在低信噪比、低快拍数时的DOA估计性能,称之为MOGSBL算法。本算法将信号源方位区间进行离散化,得到方位离散网格。为阵列接收信号建立稀疏贝叶斯模型,将网格节点修正量设为模型超参数。采用期望最大化算法迭代更新网格节点修正量,使更新后的网格节点更接近真实源信号方位。为了检验MOGSBL算法的性能,本文进行了大量的数值实验,并将MOGSBL算法的DOA估计结果与RSBL算法、OGSBL算法和L1-SVD算法进行对比。在不同信噪比和不同快拍数时,MOGSBL算法均能清晰分辨方位很接近的两个信号源,角度分辨率明显高于RSBL算法、OGSBL算法和L1-SVD算法。随着信噪比和快拍数的增加,4种算法的RMSE均逐渐减小。但MOGSBL算法的RMSE明显低于RSBL算法、OGSBL算法和L1-SVD算法,且RSBL算法、OGSBL算法优于L1-SVD算法。实验还分析了方向测试范围的离散网格节点数对DOA估计的影响,发现细密的离散网格可以提高DOA估计精度,但DOA估计的计算量会增加。且在任意网格节点数时,相比于RSBL算法、OGSBL算法和L1-SVD算法,本文的MOGSBL算法均具有最低的RMSE和最短的计算时间。

方位向调制干扰对高分宽幅多通道SAR的影响

多通道合成孔径雷达(synthetic aperture radar,SAR)能够利用方位向多通道重构处理去除多普勒模糊,获得高分宽幅SAR图像。针对此特殊的多通道重构处理方式,研究了传统SAR方位向调制干扰对高分宽幅多通道SAR的影响,包括多普勒调制干扰和脉冲延迟转发干扰两种类型的方位向调制干扰方式,为高分宽幅多通道SAR干扰决策提供理论基础。理论分析指出,多普勒调制干扰信号经成像处理后将在方位向生成等间隔分布的虚假目标,并且幅度受与多普勒调制频率相关的正弦函数和匹配滤波损失联合调制;而脉冲延迟转发干扰信号在成像后将只有单个干扰目标出现,且目标的方位位置仅与延迟的脉冲数有关。仿真实验验证了理论分析的正确性。

Resolution analysis of thermal neutron radiography based on accelerator-driven compact neutron source

Owing to the immobility of traditional reactors and spallation neutron sources,the demand for compact thermal neutron radiography(CTNR)based on accelerator neutron sources has rapidly increased in industrial applications.Recently,thermal neutron radiography experiments based on a D-T neutron generator performed by Hefei Institutes of Physical Science indicated a significant resolution deviation between the experimental results and the values calculated using the traditional resolution model.The experimental result was up to 23%lower than the calculated result,which hinders the achievement of the design goal of a compact neutron radiography system.A GEANT4 Monte Carlo code was developed to simulate the CTNR process,aiming to identify the key factors leading to resolution deviation.The effects of a low collimation ratio and high-energy neutrons were analyzed based on the neutron beam environment of the CTNR system.The results showed that the deviation was primarily caused by geometric distortion at low collimation ratios and radiation noise induced by highenergy neutrons.Additionally,the theoretical model was modified by considering the imaging position and radiation noise factors.The modified theoretical model was in good agreement with the experimental results,and the maximum deviation was reduced to 4.22%.This can be useful for the high-precision design of CTNR systems.

基于Barker码脉冲压缩技术的钢板多阵元Lamb波电磁超声换能器设计与优化

为了解决传统Barker码脉冲压缩技术受脉冲功率放大器额定参数(占空比,最大脉冲宽度等)限制而导致的脉冲压缩效果下降、检测速度降低等问题,提出一种基于Barker码脉冲压缩技术的多阵元Lamb波电磁超声换能器(EMAT)。建立了基于tone-burst信号激励-Barker码脉冲压缩技术的多阵元Lamb波EMAT检测过程的有限元模型,分析了永磁体的配置形式、阵元序列长度、激励信号周期数、曲折线圈匝数等因素对脉冲压缩后的主旁瓣比和主瓣宽度的影响,并进行了实验验证。结果表明:曲折线圈匝数为4和Barker码序列长度为13位的多阵元EMAT在配置3对外置永磁体后,其信噪比(SNR)可提高9.8 dB。综合考虑检测回波的空间分辨率和SNR,多阵元Lamb波EMAT最佳参数为:曲折线圈匝数为10、激励信号周期数为11、Barker序列为13位,并配置3对外置永磁体。

基于Hatch滤波的改进矩阵变换法在BDS多频模糊度解算中的应用

长基线条件下,空间相关性弱,电离层延迟残差和噪声影响变大,致使矩阵变换法模糊度解算过程中,窄巷组合受噪声影响大,单历元模糊度解算成功率低。因此,削弱电离层残差及噪声影响可以一定程度提高模糊度解算成功率。本文在分析矩阵变换算法基础上,利用Hatch滤波有效抑制伪距测量噪声和多径效应特点,结合弱电离层、低噪声的载波组合,通过相位平滑伪距代替组合伪距值参与解算,从而削弱电离层残差及观测噪声影响。通过实测数据分析,本文算法可有效提高矩阵变换法模糊度解算成功率。