The Soft X-ray Imager(SXI)on the SMILE Mission

The Soft X-ray Imager(SXI)is part of the scientific payload of the Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission.SMILE is a joint science mission between the European Space Agency(ESA)and the Chinese Academy of Sciences(CAS)and is due for launch in 2025.SXI is a compact X-ray telescope with a wide field-of-view(FOV)capable of encompassing large portions of Earth’s magnetosphere from the vantage point of the SMILE orbit.SXI is sensitive to the soft X-rays produced by the Solar Wind Charge eXchange(SWCX)process produced when heavy ions of solar wind origin interact with neutral particles in Earth’s exosphere.SWCX provides a mechanism for boundary detection within the magnetosphere,such as the position of Earth’s magnetopause,because the solar wind heavy ions have a very low density in regions of closed magnetic field lines.The sensitivity of the SXI is such that it can potentially track movements of the magnetopause on timescales of a few minutes and the orbit of SMILE will enable such movements to be tracked for segments lasting many hours.SXI is led by the University of Leicester in the United Kingdom(UK)with collaborating organisations on hardware,software and science support within the UK,Europe,China and the United States.

SMILE soft X-ray Imager flight model CCD370 pre-flight device characterisation

Throughout the SMILE mission the satellite will be bombarded by radiation which gradually damages the focal plane devices and degrades their performance.In order to understand the changes of the CCD370s within the soft X-ray Imager,an initial characterisation of the devices has been carried out to give a baseline performance level.Three CCDs have been characterised,the two flight devices and the flight spa re.This has been carried out at the Open University in a bespo ke cleanroom measure ment facility.The results show that there is a cluster of bright pixels in the flight spa re which increases in size with tempe rature.However at the nominal ope rating tempe rature(-120℃) it is within the procure ment specifications.Overall,the devices meet the specifications when ope rating at -120℃ in 6 × 6 binned frame transfer science mode.The se rial charge transfer inefficiency degrades with temperature in full frame mode.However any charge losses are recovered when binning/frame transfer is implemented.

学龄前儿童感觉统合能力评估工具(CASI-P)的信效度研究

学龄前时期(3~6岁)是儿童生长发育的关键期,感觉统合是儿童全面发展的基础,感觉统合评估对于早期筛查、干预、标准治疗儿童感觉统合失调有重要指导意义与参考价值。根据Ayres感觉统合基本理论,结合国内外相关文献,经专家审查形成初始量表并对1896名学龄前儿童的感觉统合能力进行调查,分析量表的Cronbach’s α系数、分半信度、内容效度与结构效度。分析结果表明,学龄前儿童感觉统合能力评估量表具有良好的信度与效度,适用于国内学龄前儿童感觉统合能力的测评,有助于制订更科学的干预方案,探索更有效的干预技术。

Simulation of the SMILE Soft X-ray Imager response to a southward interplanetary magnetic field turning

The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)Soft X-ray Imager(SXI)will shine a spotlight on magnetopause dynamics during magnetic reconnection.We simulate an event with a southward interplanetary magnetic field turning and produce SXI count maps with a 5-minute integration time.By making assumptions about the magnetopause shape,we find the magnetopause standoff distance from the count maps and compare it with the one obtained directly from the magnetohydrodynamic(MHD)simulation.The root mean square deviations between the reconstructed and MHD standoff distances do not exceed 0.2 RE(Earth radius)and the maximal difference equals 0.24 RE during the 25-minute interval around the southward turning.

End-to-end computational design for an EUV solar corona multispectral imager with stray light suppression

An extreme ultraviolet solar corona multispectral imager can allow direct observation of high temperature coronal plasma,which is related to solar flares,coronal mass ejections and other significant coronal activities.This manuscript proposes a novel end-to-end computational design method for an extreme ultraviolet(EUV)solar corona multispectral imager operating at wavelengths near 100 nm,including a stray light suppression design and computational image recovery.To suppress the strong stray light from the solar disk,an outer opto-mechanical structure is designed to protect the imaging component of the system.Considering the low reflectivity(less than 70%)and strong-scattering(roughness)of existing extreme ultraviolet optical elements,the imaging component comprises only a primary mirror and a curved grating.A Lyot aperture is used to further suppress any residual stray light.Finally,a deep learning computational imaging method is used to correct the individual multi-wavelength images from the original recorded multi-slit data.In results and data,this can achieve a far-field angular resolution below 7",and spectral resolution below 0.05 nm.The field of view is±3 R☉along the multi-slit moving direction,where R☉represents the radius of the solar disk.The ratio of the corona's stray light intensity to the solar center's irradiation intensity is less than 10-6 at the circle of 1.3 R☉.

Construction and Validation of a Geometry-based Mathematical Model for the Hard X-Ray Imager

Quantitative and analytical analysis of the modulation process of the collimator is a great challenge,and is also of great value to the design and development of Fourier transform imaging telescopes.The Hard X-ray Imager(HXI),as one of the three payloads onboard the Advanced Space-based Solar Observatory(ASO-S) mission,adopts modulating Fourier-Transformation imaging technique and will be used to explore the mechanism of energy release and transmission in solar flare activities.As an important step to reconstruct the images of solar flares,accurate modulation functions of HXI are needed.In this paper,a mathematical model is developed to analyze the modulation function under a simplified condition first.Then its behavior under six degrees of freedom is calculated after adding the rotation matrix and translation change to the model.In addition,unparalleled light and extended sources are also considered so that our model can be used to analyze the X-ray beam experiment.Next,applied to the practical HXI conditions,the model has been confirmed not only by Geant4 simulations but also by some verification experiments.Furthermore,how this model helps to improve the image reconstruction process after the launch of ASO-S is also presented.

Assessment of Cork Oak Decline Using Digital Multispectral Imagery in Relation with in Situ Crown Condition

Cork oak in Maamora forest is experiencing the dieback phenomenon. The evaluation of the latter in this forest has gained the importance over time and with the solicitation of managers to objectify its phytosanitary situation. Aiming at prioritizing management actions, remote sensing seems to be an effective tool to inquire about stands’ health conditions and their evolution. To this end, this study aims at mapping and validating health status of cork oak stands in Maamora. Sentinel 2 images in 2015 and 2020 were processed to calculate the differential normalized difference water index (NDWI), revealing vegetation moisture variation caused by drought. A statistical method based on thresholds was used to map cork oak dieback stands, those with no changes and those recovered. Results have shown that 54.63% of cork oak in Maamora forest have not changed in terms of phytosanitary situation between 2015 and 2020, 31.10% of oak stands are afflicted by a slight decline and 12.97% by a severe decline. Areas with slight or strong recovery remain minimal and represent 1.04% and 0.25% respectively. Ground data indicated that the map generated displayed a good distinction between stands severely and slightly declined with a global accuracy of 66.66%. Therefore, further research elaborating an advanced vegetation index reflecting the various factors of dieback would be of much importance.

Analysis of Remotely Sensed Imagery and Architecture Environment for Modelling 3D Detailed Buildings Using Geospatial Techniques

The use of three-dimensional maps is more effective than two-dimensional maps in representing the Earth’s surface. However, the traditional methods used to create digital surface models are not efficient for capturing the details of Earth’s features. This is because they represent only three-dimensional objects in a single texture and do not provide a realistic representation of the real world. Additionally, there is a growing demand for up-to-date and accurate geo-information, particularly in urban areas. To address this challenge, a new technique is proposed in this study that involves integrating remote sensing, Geographic Information System, and Architecture Environment software to generate a highly-detailed three-dimensional model. The method described in this study includes several steps such as acquiring high-resolution satellite imagery, gathering ground truth data, performing radiometric and geometric corrections during image preprocessing, producing a 2D map of the region of interest, constructing a digital surface model by extending the building outlines, and transforming the model into multi-patch layers to create a 3D model for each object individually. The research findings indicate that the digital surface model obtained with comprehensive information is suitable for different purposes, such as environmental research, urban development and expansion planning, and shape recognition tasks.

航空高光谱遥感技术在铀矿找矿中的典型应用——以新疆雪米斯坦地区为例

高光谱遥感技术是地质矿产勘查领域的重要新技术、新方法。近些年,航空高光谱遥感技术及其在铀矿找矿中的应用得到核地质系统的重视并开展深入研究。在分析前人铀矿找矿思路基础上,阐述了CASI/SASI航空高光谱遥感技术在新疆雪米斯坦地区的铀矿找矿新思路及其典型应用效果。首先深入剖析了白杨河铀矿床及其周围的航空高光谱遥感特征,识别了铀矿床产出的区域热液活动中心、铀成矿高铝绢云母蚀变等区域找矿关键要素,提出“区域热液活动中心识别-铀矿化航空高光谱蚀变组合发育地段确定-蚀变、构造、有利岩性等要素复合地段优选”的航空高光谱遥感铀矿找矿新思路;然后根据全区的航空高光谱遥感信息进行了找矿远景区筛选和野外查证,新发现了铀矿化异常。新发现的铀矿化异常地段航空高光谱遥感特征明显,地表铀异常显著,控矿断裂构造发育,地质环境有利,铀矿找矿前景良好。其是笔者对如何充分挖掘高光谱遥感铀矿找矿信息,提升高光谱遥感技术更好服务铀矿找矿应用效果的深入思考与探索,也是在地表岩石裸露程度良好的地区利用高光谱遥感技术直接寻找热液型矿产的良好例证,希冀为广大地质工作者开展找矿方法创新和应用提供参考。

Exploring the spatiotemporal relationship between green infrastructure and urban heat island under multi‐source remote sensing imagery:A case study of Fuzhou City

Green Infrastructure(GI)has garnered increasing attention from various regions due to its potential to mitigate urban heat island(UHI),which has been exacerbated by global climate change.This study focuses on the central area of Fuzhou city,one of the“furnace”cities,and aims to explore the correlation between the GI pattern and land surface temperature(LST)in the spring and autumn seasons.The research adopts a multiscale approach,starting from the urban scale and using urban geographic spatial characteristics,multispectral remote sensing data,and morphological spatial pattern analysis(MSPA).Significant MSPA elements were tested and combined with LST to conduct a geographic weighted regression(GWR)experiment.The findings reveal that the UHI in the central area of Fuzhou city has a spatial characteristic of“high temperature in the middle and low temperature around,”which is coupled with a“central scattered and peripheral concentrated”distribution of GI.This suggests that remote sensing data can effectively be utilised for UHI inversion.Additionally,the study finds that the complexity of GI,whether from the perspective of the overall GI pattern or the classification study based on the proportion of the core area,has an impact on the alleviation of UHI in both seasons.In conclusion,this study underscores the importance of a reasonable layout of urban green infrastructure for mitigating UHI.

An Effective Machine-Learning Based Feature Extraction/Recognition Model for Fetal Heart Defect Detection from 2D Ultrasonic Imageries

Congenital heart defect,accounting for about 30%of congenital defects,is the most common one.Data shows that congenital heart defects have seriously affected the birth rate of healthy newborns.In Fetal andNeonatal Cardiology,medical imaging technology(2D ultrasonic,MRI)has been proved to be helpful to detect congenital defects of the fetal heart and assists sonographers in prenatal diagnosis.It is a highly complex task to recognize 2D fetal heart ultrasonic standard plane(FHUSP)manually.Compared withmanual identification,automatic identification through artificial intelligence can save a lot of time,ensure the efficiency of diagnosis,and improve the accuracy of diagnosis.In this study,a feature extraction method based on texture features(Local Binary Pattern LBP and Histogram of Oriented Gradient HOG)and combined with Bag of Words(BOW)model is carried out,and then feature fusion is performed.Finally,it adopts Support VectorMachine(SVM)to realize automatic recognition and classification of FHUSP.The data includes 788 standard plane data sets and 448 normal and abnormal plane data sets.Compared with some other methods and the single method model,the classification accuracy of our model has been obviously improved,with the highest accuracy reaching 87.35%.Similarly,we also verify the performance of the model in normal and abnormal planes,and the average accuracy in classifying abnormal and normal planes is 84.92%.The experimental results show that thismethod can effectively classify and predict different FHUSP and can provide certain assistance for sonographers to diagnose fetal congenital heart disease.

Comparison of Machine Learning Methods for Satellite Image Classification: A Case Study of Casablanca Using Landsat Imagery and Google Earth Engine

Satellite image classification is crucial in various applications such as urban planning,environmental monitoring,and land use analysis.In this study,the authors present a comparative analysis of different supervised and unsupervised learning methods for satellite image classification,focusing on a case study in Casablanca using Landsat 8 imagery.This research aims to identify the most effective machine-learning approach for accurately classifying land cover in an urban environment.The methodology used consists of the pre-processing of Landsat imagery data from Casablanca city,the authors extract relevant features and partition them into training and test sets,and then use random forest(RF),SVM(support vector machine),classification,and regression tree(CART),gradient tree boost(GTB),decision tree(DT),and minimum distance(MD)algorithms.Through a series of experiments,the authors evaluate the performance of each machine learning method in terms of accuracy,and Kappa coefficient.This work shows that random forest is the best-performing algorithm,with an accuracy of 95.42%and 0.94 Kappa coefficient.The authors discuss the factors of their performance,including data characteristics,accurate selection,and model influencing.

多模态影像技术在儿童症状性癫痫中的应用进展

儿童是癫痫的好发人群,由于其中枢神经系统处于发育阶段,所以病因更加复杂、表现形式更加多样,早期诊断和及时、有效处理能减少儿童中枢神经损伤,最大程度地保护患儿的脑功能。根据有无明显抽搐可将癫痫分为惊厥性和非惊厥性,而非惊厥性因无明显临床症状,诊断相对比较困难,容易导致误诊而延误治疗,明确诊断需要依靠脑电图(癫痫样或节律性放电)。随着影像检查手段的不断发展,明确癫痫病因、定位癫痫病灶的方式更加多样化,定位更加准确,同时功能成像检查方式也使得早期评估癫痫的脑功能变化成为可能。本文就近年来症状性儿童癫痫的MRI及其与正电子发射计算机断层显像(positron emission tomography,PET)融合应用的研究进展及临床应用进行综述,旨在为今后的相关研究提供参考和借鉴。

糖尿病周围神经病变多模态MRI研究进展

糖尿病周围神经病变(diabetes peripheral neuropathy,DPN)是较常见的糖尿病慢性并发症,严重影响患者生活质量。DPN发病机制比较复杂,目前研究表明与神经病理性改变关系密切。近些年多模态MRI获得长足进展,MRI以软组织分辨率高、无创、无辐射等优点著称,成为探索DPN中枢神经及周围神经发病机制的重要方法。本文应用基于体素的形态学测量(voxel-based morphometry,VBM)、弥散张量成像(diffusion tensor imaging,DTI)、功能MRI(functional MRI,fMRI)等技术,对研究DPN脑结构、脑功能改变以及周围神经结构异常的文献进行综述,为临床早期诊断和制订精准治疗方案提供依据。

激光距离选通三维成像技术研究进展(特邀)

随着人工智能时代的到来,同时获得反映目标辐射特性和纹理特征的高分辨率强度图像以及反映目标和所处场景的三维空间信息的稠密点云数据/三维图像的激光相机雷达技术已成为激光雷达的发展趋势。传统的摄像机与激光雷达复合的技术方案存在异源数据融合问题,尤其是在雾雨雪天气条件下以及水下等传输链路中存在严重散射的情况时难以有效工作。激光距离选通三维成像技术利用单一门控成像器件可同时获得高质量二维强度图像和高分辨率三维图像,其二维图像中的像素和三维图像中的体素一一对应,并继承了激光距离选通成像透散射成像的技术优势,具有实现高性能激光相机雷达的技术潜力。论文系统综述了步进延时扫描、增益调制、距离能量相关等激光距离选通三维成像技术的研究进展,介绍了该类技术的国内外典型应用情况,最后分析了该领域所面临的挑战及进一步发展方向和应用前景。

基于特征相似性的红外与可见光图像融合方法

单一图像无法全面描述目标的信息,实际应用价值低,针对当前红外与可见光图像融合方法存在的一些不足,如:融合质量差等,为了获得更加理想的红外与可见光图像融合效果,提出了基于特征相似性的红外与可见光图像融合方法。首先分析当前红外与可见光图像融合的研究进展,指出各种方法的局限性,然后采用红外图像和可见光图像,并对它们进行图像去噪、增强处理,采用卷积神经网络提取红外与可见光图像的特征,最后根据特征相似性进行红外与可见光图像融合,并对红外与可见光图像融合效果进行了测试,结果表明,本方法提升了红外与可见光图像融合质量,融合效果要明显优于其他红外与可见光图像融合方法。

基于红外热成像的煤矸识别方法研究

基于重介选煤、跳汰选煤、浮选、干法选煤、γ射线检测法的煤矸分选方法投资成本高、分选效率低、环境污染严重,基于CCD相机的煤矸分选方法准确率不高,基于X射线的煤矸分选技术会危害工作人员的健康。红外热成像技术不受光照、粉尘影响,且不会对人体造成伤害。提出了一种基于红外热成像的煤矸识别方法。首先,煤和矸石在传送带的输送下经过加热区域,红外热成像仪监测经均匀加热后的煤和矸石中心点的温度,得到煤和矸石加热后的温度并对经加热区域均匀加热后的煤和矸石进行拍摄,得到煤和矸石的红外灰度图像和红外彩色图像。然后,选用高斯滤波对煤和矸石的红外灰度图像、红外彩色图像进行预处理并提取特征,将红外灰度图像的灰度均值、最大频数对应的灰度值特征和红外彩色图像的G通道一阶矩、G通道二阶矩特征作为分选特征,将上述4个特征作为分类模型的输入。最后,采用支持向量机(SVM)进行分类识别,从而达到识别煤和矸石的目的。实验结果表明:基于红外热成像的煤矸识别方法对烟煤、无烟煤、褐煤的分选准确率均达到了98%以上,有良好的分类效果。

基于扩散加权成像及MRI对四肢软组织肿瘤的诊断价值

目的 探讨基于扩散加权成像及MRI对四肢软组织肿瘤(soft tissue tumors,STTs)的诊断价值。方法 选取本院经病理证实的四肢STTs患者74例,其中良性46例(良性组)、恶性28例(恶性组),均行常规MRI、DWI、IVIM及DKI扫描,分析两组常规MRI检查征象及诸参数差异,包括表观扩散系数(ADC)、真实扩散系数(D)、灌注相关扩散系数(D~*)、灌注分数(f)、平均扩散峰度值(MK)和平均扩散率(MD);运用ROC曲线分析其诊断效能。结果 恶性组肿瘤边界多不清且呈浸润性生长,以团块状为主,瘤周水肿、筋膜尾征多见,50.0%瘤内可见分隔,两组间差异有统计学意义(P<0.05)。恶性组ADC、D和MD值小于良性组,而MK值高于良性组,差异具有统计学意义(P<0.05)。D~*和f值两组差异无统计学意义(P>0.05)。ADC、D、MD、MK值在鉴别四肢STTs良恶性方面均具有一定诊断效能:AUC≥0.688,敏感度≥63.0%,特异度≥67.9%,准确度≥64.9%,其中MD值的诊断效能、特异度最高。ADC+D+MD+MK联合后,AUC为0.887,诊断效能均高于单一参数(Z=1.978~3.101;P<0.05),敏感度为76.1%,特异度为92.9%,准确度78.4%。结论 基于扩散加权成像及MRI对四肢STTs良恶性有较好的判断价值,值得临床推广。

三维酰胺质子转移成像在原发性肝癌临床扫描可行性及图像质量评估中的初步研究

目的 评估参数优化的三维酰胺质子转移加权(3 dimensions-amide proton transfer weighted,3D-APTw)成像在原发性肝癌扫描中的图像质量并分析其临床扫描的可行性。材料与方法 前瞻性招募2020年10月至2022年2月临床怀疑原发性肝癌患者,共109例。采用飞利浦3.0 T MRI设备进行扫描,分别采集T1WI、T2WI、弥散加权成像、酰胺质子转移加权(amide proton transfer weighted,APTw)及多期增强图像。机器自动生成经过B0校正的肝脏APTw图像。计算3D-APTw成像的扫描成功率及计算成功率。采用Kendall一致性系数对观察者内及观察者间主观评分进行一致性分析,对主观评分3分以上的病例测量3D-APTw图像的信噪比(signal-to-noise ratio,SNR)、肿瘤对比噪声比(contrast-to-noise ratio,CNR)、肿瘤及肝实质的APTw值并计算各参数值的变异系数,采用组内相关系数进行观察者内及观察者间可重复性测量的一致性分析。结果 109例患者中有11例患者3D-APTw图像中病变区域存在信号缺失,扫描成功率为89.91%(98/109),剩余98例患者中78例3D-APTw图像的主观评分为3分以上,计算成功率为71.56%(78/109)。观察者内及观察者间图像质量主观评分一致性分别为0.771和0.692,P<0.01。肿瘤组织APTw值观察者内及观察者间ICC分别为0.822和0.811,肝实质APTw值、SNR及CNR观察者ICC分别为0.675、0.634、0.666,肝实质APTw值、SNR及CNR观察者间ICC分别为0.614、0.290、0.560。肿瘤组织APTw值高于肝实质[(2.55±0.08)%vs.(1.45±0.07)%],两者间差异有统计学意义(P<0.001)。肿瘤组织和肝实质APTw值的变异系数分别为30.40%和44.40%。SNR和CNR为25.92±18.50和3.35±3.20。SNR变异系数为71.40%,CNR变异系数为90.00%。结论 参数优化后的3D-APTw成像可以用于原发性肝癌的临床扫描,但容易受呼吸运动、胆囊或血管的影响而出现信号缺失或伪影,在参数设置及成像技术上仍有需要改进和提高的空间,以进一步优化其图像质量。

微透镜阵列成像串扰现象分析

针对微透镜阵列成像时单元图像间存在的串扰问题,文中基于矩阵光学理论,分析了经微透镜阵列成像像面与物面的空间关系,模拟计算2×2的微透镜阵列成像,设计了焦距为7 mm的1×2阵列进行实验研究。研究结果表明:单元图像间距随微透镜焦距和物面尺寸的增大而减小,随微透镜间距和物距的增加而线性的增大。对于焦距为7 mm的微透镜,物距为40 mm,当物面尺寸为55 mm×55 mm时,获得了单元图像恰好分离的临界值,实验结果与模拟计算的理论值一致,该结果对设计微透镜阵列的成像系统具有一定的参考价值。