Simultaneous fluorescence and Compton scattering computed tomography based on linear polarization X-ray

Purpose To propose a method for simultaneous fluorescence and Compton scattering computed tomography by using linearly polarized X-rays.Methods Monte Carlo simulations were adopted to demonstrate the feasibility of the proposed method.In the simulations,the phantom is a polytetrafluoroethylene cylinder inside which are cylindrical columns containing aluminum,water,and gold(Au)-loaded water solutions with Au concentrations ranging between 0.5 and 4.0 wt%,and a parallel-hole collimator imaging geometry was adopted.The light source was modeled based on a Thomson scattering X-ray source.The phantom images for both imaging modalities were reconstructed using a maximumlikelihood expectation maximization algorithm.Results Both the X-ray fluorescence computed tomography(XFCT)and Compton scattering computed tomography(CSCT)images of the phantom were accurately reconstructed.A similar attenuation contrast problem for the different cylindrical columns in the phantom can be resolved in the XFCT and CSCT images.The interplay between XFCT and CSCT was analyzed,and the contrast-to-noise ratio(CNR)of the reconstruction was improved by correcting for the mutual influence between the two imaging modalities.Compared with K-edge subtraction imaging,XFCT exhibits a CNR advantage for the phantom.Conclusion Simultaneous XFCT and CSCT can be realized by using linearly polarized X-rays.The synergy between the two imaging modalities would have an important application in cancer radiation therapy.

Self-supervised learning artificial intelligence noise reduction technology based on the nearest adjacent layer in ultra-low dose CT of urinary calculi

Objective To observe the value of self-supervised deep learning artificial intelligence(AI)noise reduction technology based on the nearest adjacent layer applicated in ultra-low dose CT(ULDCT)for urinary calculi.Methods Eighty-eight urinary calculi patients were prospectively enrolled.Low dose CT(LDCT)and ULDCT scanning were performed,and the effective dose(ED)of each scanning protocol were calculated.The patients were then randomly divided into training set(n=75)and test set(n=13),and a self-supervised deep learning AI noise reduction system based on the nearest adjacent layer constructed with ULDCT images in training set was used for reducing noise of ULDCT images in test set.In test set,the quality of ULDCT images before and after AI noise reduction were compared with LDCT images,i.e.Blind/Referenceless Image Spatial Quality Evaluator(BRISQUE)scores,image noise(SD ROI)and signal-to-noise ratio(SNR).Results The tube current,the volume CT dose index and the dose length product of abdominal ULDCT scanning protocol were all lower compared with those of LDCT scanning protocol(all P<0.05),with a decrease of ED for approximately 82.66%.For 13 patients with urinary calculi in test set,BRISQUE score showed that the quality level of ULDCT images before AI noise reduction reached 54.42%level but raised to 95.76%level of LDCT images after AI noise reduction.Both ULDCT images after AI noise reduction and LDCT images had lower SD ROI and higher SNR than ULDCT images before AI noise reduction(all adjusted P<0.05),whereas no significant difference was found between the former two(both adjusted P>0.05).Conclusion Self-supervised learning AI noise reduction technology based on the nearest adjacent layer could effectively reduce noise and improve image quality of urinary calculi ULDCT images,being conducive for clinical application of ULDCT.

A machine learning-based strategy for predicting the mechanical strength of coral reef limestone using X-ray computed tomography

Different sedimentary zones in coral reefs lead to significant anisotropy in the pore structure of coral reef limestone(CRL),making it difficult to study mechanical behaviors.With X-ray computed tomography(CT),112 CRL samples were utilized for training the support vector machine(SVM)-,random forest(RF)-,and back propagation neural network(BPNN)-based models,respectively.Simultaneously,the machine learning model was embedded into genetic algorithm(GA)for parameter optimization to effectively predict uniaxial compressive strength(UCS)of CRL.Results indicate that the BPNN model with five hidden layers presents the best training effect in the data set of CRL.The SVM-based model shows a tendency to overfitting in the training set and poor generalization ability in the testing set.The RF-based model is suitable for training CRL samples with large data.Analysis of Pearson correlation coefficient matrix and the percentage increment method of performance metrics shows that the dry density,pore structure,and porosity of CRL are strongly correlated to UCS.However,the P-wave velocity is almost uncorrelated to the UCS,which is significantly distinct from the law for homogenous geomaterials.In addition,the pore tensor proposed in this paper can effectively reflect the pore structure of coral framework limestone(CFL)and coral boulder limestone(CBL),realizing the quantitative characterization of the heterogeneity and anisotropy of pore.The pore tensor provides a feasible idea to establish the relationship between pore structure and mechanical behavior of CRL.

The Application Progress of Skin Imaging Technology in Psoriasis

Skin imaging technologies such as dermoscopy, high-frequency ultrasound, reflective confocal microscopy and optical coherence tomography are developing rapidly in clinical application. Skin imaging technology can improve clinical diagnosis rate, and its non-invasiveness and repeatability make it occupy an irreplaceable position in clinical diagnosis. With the “booming development” of medical technology, skin imaging technology can improve clinical diagnosis rate. Researchers have made significant advances in assisting clinical diagnosis, prediction, and treatment of disease. This article reviews the application and progress of skin imaging in the diagnosis of psoriasis.

Tracking the phase transformation and microstructural evolution of Sn anode using operando synchrotron X-ray energy-dispersive diffraction and X-ray tomography

Tin(Sn)holds great promise as an anode material for next-generation lithium(Li)ion batteries but suffers from massive volume change and poor cycling performance.To clarify the dynamic chemical and microstructural evolution of Sn anode during lithiation and delithiation,synchrotron X-ray energydispersive diffraction and X-ray tomography are simultaneously employed during Li/Sn cell operation.The intermediate Li-Sn alloy phases during de/lithiation are identified,and their dynamic phase transformation is unraveled which is further correlated with the volume variation of the Sn at particle-and electrode-level.Moreover,we find that the Sn particle expansion/shrinkage induced particle displacement is anisotropic:the displacement perpendicular to the electrode surface(z-axis)is more pronounced compared to the directions(x-and y-axis)along the electrode surface.This anisotropic particle displacement leads to an anisotropic volume variation at the electrode level and eventually generates a net electrode expansion towards the separator after cycling,which could be one of the root causes of mechanical detachment and delamination of electrodes during long-term operation.The unraveled chemical evolution of Li-Sn and deep insights into the microstructural evolution of Sn anode provided here could guide future design and engineering of Sn and other alloy anodes for high energy density Li-and Na-ion batteries.

Tomographic reconstruction of the Earth’s magnetosheath from multiple spacecraft:a theoretical study

Following our earlier work on tomographic reconstruction of the magnetosheath soft X-ray emissions with superposed epoch analysis of many images recorded from a single spacecraft we now explore the instantaneous reconstruction of the magnetosheath and magnetopause using a few images recorded simultaneously from a few spacecraft.This work is motivated by the prospect of possibly having two or three soft X-ray imagers in space in the coming years,and that many phenomena which occur at the magnetopause boundary,such as reconnection events and pressure pulse responses,do not lend themselves as well to superposed epoch analysis.If the reconstruction is successful-which we demonstrate in this paper that it can be-this collection of imagers can be used to reconstruct the magnetosheath and magnetopause from a single image from each spacecraft,allowing for high time resolution reconstructions.In this paper we explore the reconstruction using,two,three,and four spacecraft.We show that the location of the subsolar point of the magnetopause can be determined with just two satellites,and that volume emissions of soft X-rays,and the shape of the boundary,can be reconstructed using three or more satellites.

Finding the magnetopause location using soft X-ray observations and a statistical inverse method

Variability in the location and shape of the dayside magnetopause is attributed to magnetic reconnection,a fundamental process that enables the transfer of mass,energy,and momentum from the solar wind into the magnetosphere.The spatial and temporal properties of the magnetopause,under varying solar and magnetospheric conditions,remain largely unknown because empirical studies using in-situ observations are challenging to interpret.Global wide field-of-view(FOV)imaging is the only means to simultaneously observe the spatial distribution of the plasma properties over the vast dayside magnetospheric region and,subsequently,quantify the energy transport from the interplanetary medium into the terrestrial magnetosphere.Two upcoming missions,ESA/CAS SMILE and NASA’s LEXI will provide wide-field imagery of the dayside magnetosheath in soft X-rays,an emission generated by charge exchange interactions between high charge-state heavy ions of solar wind origin and exospheric neutral atoms.High-cadence two-dimensional observations of the magnetosheath will allow the estimation of dynamic properties of its inner boundary,the magnetopause,and enable studies of its response to changes in the solar wind dynamic pressure and interplanetary magnetic field orientation.This work introduces a statistically-based estimation approach based on inverse theory to estimate the spatial distribution of magnetosheath soft X-ray emissivities and,with this,identify the location of the magnetopause over the Sun−Earth line.To do so,we simulate the magnetosheath structure using the MHD-based OpenGGCM model and generate synthetic soft X-ray images using LEXI’s orbit and attitude information.Our results show that 3-D estimations using the described statistically-based technique are robust against Poisson-distributed shot noise inherent to soft X-ray images.Also,our proposed methodology shows that the accuracy of both three-dimensional(3-D)estimation and the magnetopause standoff distance calculation highly depends on the observational point.

Seeing through Materials:X-Ray Imaging Using Computed Tomography

X-ray computed tomography(XCT)has recently emerged as a powerful tool for characterizing the evolution of microstructure during phase transformation in three dimensional(3D)such as dendritic solidification of alloys.This paper briefly reviews the recent advances in the in-situ observation of aluminium alloys,magnesium alloys and nickel-based superalloys during solidification using laboratory XCT and synchrotron X-ray sources.The focus is on the growth kinetics of dendrites,porosity and secondary phases.In addition,in-situ characterization during the loading and corrosion process is also discussed.

Computed tomography-based nomogram of Siewert type Ⅱ/Ⅲ adenocarcinoma of esophagogastric junction to predict response to docetaxel, oxaliplatin and S-1

BACKGROUND Neoadjuvant chemotherapy(NAC)has become the standard care for advanced adenocarcinoma of esophagogastric junction(AEG),although a part of the patients cannot benefit from NAC.There are no models based on baseline computed tomography(CT)to predict response of Siewert type II or III AEG to NAC with docetaxel,oxaliplatin and S-1(DOS).AIM To develop a CT-based nomogram to predict response of Siewert type II/III AEG to NAC with DOS.METHODS One hundred and twenty-eight consecutive patients with confirmed Siewert type II/III AEG underwent CT before and after three cycles of NAC with DOS,and were randomly and consecutively assigned to the training cohort(TC)(n=94)and the validation cohort(VC)(n=34).Therapeutic effect was assessed by disease-control rate and progressive disease according to the Response Evaluation Criteria in Solid Tumors(version 1.1)criteria.Possible prognostic factors associated with responses after DOS treatment including Siewert classification,gross tumor volume(GTV),and cT and cN stages were evaluated using pretherapeutic CT data in addition to sex and age.Univariate and multivariate analyses of CT and clinical features in the TC were performed to determine independent factors associated with response to DOS.A nomogram was established based on independent factors to predict the response.The predictive performance of the nomogram was evaluated by Concordance index(C-index),calibration and receiver operating characteristics curve in the TC and VC.RESULTS Univariate analysis showed that Siewert type(52/55 vs 29/39,P=0.005),pretherapeutic cT stage(57/62 vs 24/32,P=0.028),GTV(47.3±27.4 vs 73.2±54.3,P=0.040)were significantly associated with response to DOS in the TC.Multivariate analysis of the TC also showed that the pretherapeutic cT stage,GTV and Siewert type were independent predictive factors related to response to DOS(odds ratio=4.631,1.027 and 7.639,respectively;all P<0.05).The nomogram developed with these independent factors showed an excellent performance to predict response to DOS in the TC and VC(C-index:0.838 and 0.824),with area under the receiver operating characteristic curve of 0.838 and 0.824,respectively.The calibration curves showed that the practical and predicted response to DOS effectively coincided.CONCLUSION A novel nomogram developed with pretherapeutic cT stage,GTV and Siewert type predicted the response of Siewert type II/III AEG to NAC with DOS.

Importance of computed tomography in posterior malleolar fractures:Added information to preoperative X-ray studies

BACKGROUND Ankle fractures are common lesions of the lower limbs.Approximately 40%of ankle fractures affect the posterior malleolus(PM).Historically,PM osteosynthesis was recommended when PM size in X-ray images was greater than 25%of the joint.Currently,computed tomography(CT)has been gaining traction in the preoperative evaluation of ankle fractures.AIM To elucidate the similarity in dimensions and to correlate PM size in X-ray images with the articular surface of the affected tibial plafond in the axial view on CT(AXCT)of a PM fracture.METHODS Eighty-one patients(mean age:39.4±13.5 years)were evaluated(54.3%were male).Two independent examiners measured PM size in profile X-ray images(PMXR)and sagittal CT(SAGCT)slices.The correlation of the measurements between the examiners and the difference in the PM fragment sizes between the two images were compared.Next,the PM size in PMXR was compared with the surface of the tibial plafond involved in the fracture in AXCT according to the Haraguchi classification.RESULTS The correlation rates between the examiners were 0.93 and 0.94 for PMXR and SAGCT,respectively(P<0.001).Fragments were 2.12%larger in SAGCT than in PMXR(P=0.018).In PMXR,there were 56 cases<25%and 25 cases≥25%.When PMXR was<25%,AXCT corresponded to 10.13%of the tibial plafond.When PMXR was≥25%,AXCT was 24.52%(P<0.001).According to the Haraguchi classification,fracture types I and II had similar PMXR measurements that were greater than those of type III.When analyzing AXCT,a significant difference was found between the three types,with II>I>III(P<0.001).CONCLUSION PM fractures show different sizes using X-ray or CT images.CT showed a larger PM in the sagittal plane and allowed the visualization of the real dimensions of the tibial plafond surface.

基于X-ray CT图像的沥青混合料车辙过程空隙分布评估

X射线计算机断层扫描(X-ray computed tomography,X-ray CT)技术作为一种无损测试方法,已被广泛用于评估沥青混合料中的空隙结构和与空隙有关的病害。基于X-ray CT和图像处理技术,从细观结构层面探讨了车辙变形过程中沥青混合料的空隙结构特征。提出了体积等效球棍模型来表征空隙连通性的变化,用改进的环扇分割变异系数、位置偏心率和球度分别描述了空隙的分布和形状特征。结果表明,车辙对沥青混合料空隙结构的影响机制因混合料类型而异。与密级配沥青混凝土(AC-13)相比,沥青玛蹄脂碎石混合料(SMA-13)中的空隙更加不均匀和离散,尤其是那些体积小于0.01 mm^(3)的空隙。此外,SMA-13中的空隙连通性和分布更容易受到外部荷载的影响,其粗集料在变形过程中往往会产生定向移动进而改变初始位置。尽管车辙变形同时增加了2种混合料中空隙的水平不均匀性,但AC-13的竖向不均匀性减少,而SMA-13的竖向不均匀性增加。加载使AC-13混合料的空隙几何形状变得复杂和分散,而SMA-13则相反,预示着与AC混合料相比,SMA混合料在加载1 h后仍保持抵抗车辙破坏的潜力。总体而言,沥青混合料中空隙的拓扑特征及其在车辙变形过程中的动态响应主要取决于混合料的级配形式。

Assessing efficacy of standard impregnation techniques on die-cast aluminum alloys using X-ray micro-CT

Utilizing lightweight Al alloys in various industrial applications requires achieving precise pressure tightness and leak requirements.Vacuum pressure impregnation(VPI)with thermosetting polymers is commonly used to address leakage defects in die-cast Al alloys.In this study,the efficacy of the VPI technique in sealing alloy parts was investigated using a combination of nondestructive micro X-ray computed tomography(micro XCT)and a standard leak test.The results demonstrate that the commonly used water leak test is insufficient for determining the sealing performance.Instead,micro XCT shows distinct advantages by enabling more comprehensive analysis.It reveals the presence of a low atomic number impregnates sealant within casting defects,which has low grey contrast and allows for visualizing primary leakage paths in 3D.The effective atomic number of impregnated resin is 6.75 and that of Al alloy is 13.69 by dual-energy X-ray CT.This research findings will contribute to enhancing the standard VPI process parameters and the properties of impregnating sealants to improve quality assurance for impregnation in industrial metals.

Insights into the hydrogen evolution reaction in vanadium redox flow batteries:A synchrotron radiation based X-ray imaging study

The parasitic hydrogen evolution reaction(HER)in the negative half-cell of vanadium redox flow batteries(VRFBs)causes severe efficiency losses.Thus,a deeper understanding of this process and the accompanying bubble formation is crucial.This benchmarking study locally analyzes the bubble distribution in thick,porous electrodes for the first time using deep learning-based image segmentation of synchrotron X-ray micro-tomograms.Each large three-dimensional data set was processed precisely in less than one minute while minimizing human errors and pointing out areas of increased HER activity in VRFBs.The study systematically varies the electrode potential and material,concluding that more negative electrode potentials of-200 m V vs.reversible hydrogen electrode(RHE)and lower cause more substantial bubble formation,resulting in bubble fractions of around 15%–20%in carbon felt electrodes.Contrarily,the bubble fractions stay only around 2%in an electrode combining carbon felt and carbon paper.The detected areas with high HER activity,such as the border subregion with more than 30%bubble fraction in carbon felt electrodes,the cutting edges,and preferential spots in the electrode bulk,are potential-independent and suggest that larger electrodes with a higher bulk-to-border ratio might reduce HER-related performance losses.The described combination of electrochemical measurements,local X-ray microtomography,AI-based segmentation,and 3D morphometric analysis is a powerful and novel approach for local bubble analysis in three-dimensional porous electrodes,providing an essential toolkit for a broad community working on bubble-generating electrochemical systems.

Energy spectrum computed tomography multi-parameter imaging in preoperative assessment of vascular and neuroinvasive status in gastric cancer

BACKGROUND Vascular and nerve infiltration are important indicators for the progression and prognosis of gastric cancer(GC),but traditional imaging methods have some limitations in preoperative evaluation.In recent years,energy spectrum computed tomography(CT)multiparameter imaging technology has been gradually applied in clinical practice because of its advantages in tissue contrast and lesion detail display.AIM To explore and analyze the value of multiparameter energy spectrum CT imaging in the preoperative assessment of vascular invasion(LVI)and nerve invasion(PNI)in GC patients.METHODS Data from 62 patients with GC confirmed by pathology and accompanied by energy spectrum CT scanning at our hospital between September 2022 and September 2023,including 46 males and 16 females aged 36-71(57.5±9.1)years,were retrospectively collected.The patients were divided into a positive group(42 patients)and a negative group(20 patients)according to the presence of LVI/PNI.The CT values(CT40 keV,CT70 keV),iodine concentration(IC),and normalized IC(NIC)of lesions in the upper energy spectrum CT images of the arterial phase,venous phase,and delayed phase 40 and 70 keV were measured,and the slopes of the energy spectrum curves[K(40-70)]from 40 to 70 keV were calculated.Arterial Core Tip:To investigate the application value of multiparameter energy spectrum computed tomography(CT)imaging in the preoperative assessment of vascular and nerve infiltration in patients with gastric cancer(GC).The imaging data of GC patients were retrospectively analyzed to evaluate the accuracy and sensitivity of CT for identifying and quantifying vascular and nerve infiltration and for comparison with postoperative pathological results.The purpose of this study was to verify the clinical feasibility and potential advantages of multiparameter energy spectrum CT imaging in guiding preoperative diagnosis and treatment decision-making and to provide a new imaging basis for improving the diagnostic accuracy and prognosis of GC patients.

Deep learning model combined with computed tomography features to preoperatively predicting the risk stratification of gastrointestinal stromal tumors

BACKGROUND Gastrointestinal stromal tumors(GIST)are prevalent neoplasm originating from the gastrointestinal mesenchyme.Approximately 50%of GIST patients experience tumor recurrence within 5 years.Thus,there is a pressing need to accurately evaluate risk stratification preoperatively.AIM To assess the application of a deep learning model(DLM)combined with computed tomography features for predicting risk stratification of GISTs.METHODS Preoperative contrast-enhanced computed tomography(CECT)images of 551 GIST patients were retrospectively analyzed.All image features were independently analyzed by two radiologists.Quantitative parameters were statistically analyzed to identify significant predictors of high-risk malignancy.Patients were randomly assigned to the training(n=386)and validation cohorts(n=165).A DLM and a combined DLM were established for predicting the GIST risk stratification using convolutional neural network and subsequently evaluated in the validation cohort.RESULTS Among the analyzed CECT image features,tumor size,ulceration,and enlarged feeding vessels were identified as significant risk predictors(P<0.05).In DLM,the overall area under the receiver operating characteristic curve(AUROC)was 0.88,with the accuracy(ACC)and AUROCs for each stratification being 87%and 0.96 for low-risk,79%and 0.74 for intermediate-risk,and 84%and 0.90 for high-risk,respectively.The overall ACC and AUROC were 84%and 0.94 in the combined model.The ACC and AUROCs for each risk stratification were 92%and 0.97 for low-risk,87%and 0.83 for intermediate-risk,and 90%and 0.96 for high-risk,respectively.Differences in AUROCs for each risk stratification between the two models were significant(P<0.05).CONCLUSION A combined DLM with satisfactory performance for preoperatively predicting GIST stratifications was developed using routine computed tomography data,demonstrating superiority compared to DLM.

Impact of computed tomography/magnetic resonance imaging registration on rehabilitation after percutaneous endoscopic decompression for lumbar stenosis: Retrospective study

BACKGROUND Percutaneous endoscopic lumbar decompression(PELD)shows promise for lumbar spinal stenosis(LSS)treatment,but its use is limited by the disease's complexity and procedural challenges.AIM In this study,the effects of preoperative planning and intraoperative guidance with computed tomography(CT)/magnetic resonance imaging(MRI)registration techniques on PELD for LSS and postoperative rehabilitation outcomes were evaluated.METHODS This retrospective study was conducted with data from patients who underwent PELD for LSS between January 2021 and December 2023.Patients were assigned to preoperative CT/MRI registration and control groups.Data collected included the operative time,length of hospital stay,visual analog scale(VAS)scores for low back and leg pain,and the Japanese Orthopaedic Association(JOA)lumbar spine score.Differences between groups were assessed using Student’s t test.RESULTS Data from 135 patients(71 in the CT/MRI registration group,64 in the control group)were analyzed.The operative time was significantly shorter in the CT/MRI registration group(P=0.007).At 2 months postoperatively,both groups showed significant reductions in VAS leg and low back pain scores(all P<0.001)and improvements in the JOA score(both P<0.001).No complication or death occurred.Preoperatively,pain and JOA scores were similar between groups(P=0.830,P=0.470,and P=0.287,respectively).At 2 months postoperatively,patients in the CT/MRI registration group reported lower leg and low back pain levels(P<0.001 and P=0.001,respectively)and had higher JOA scores(P=0.004)than did patients in the control group.CONCLUSION Preoperative CT/MRI registration for PELD for LSS reduced the operative time and VAS pain scores at 2 months and improved JOA scores,demonstrating enhanced effectiveness and safety.

Applying Surface Fitting in the Medical Thermal Tomography Technology

Based on the thermal tomography technology, this thesis tries to calculate quantity and distribution of heat source in vivo from body surface temperature. A superposition temperature image of a number of point heat sources is surface fitted to get the Q of heat sources (information of cancer cells) quantitatively. The result can reflect the disease area information because cancer cell's Q value is much higher than that of normal cell. This application is a new try in the diagnosis of breast cancer, which has an important value on the early detection and diagnosis of disease source.

Research on CT characteristics reconstruction technology

The traditional computed tomography(CT)reconstruction methods are noisy,low resolution,poor contrast,and generally not suitable to detect the smaller flaws.Besides,the filter design is also difficult.The CT characteristics reconstruction technology was brought forward to improve in these aspects,which is defined to directly reconstruct the characteristics of the projection for the best requirements not the overall image quality.The two-dimension(2D)and three-dimension(3D)CT characteristics reconstruction algorithm were firstly introduced,then by detailed analysis,experimental results and comparsion of parameters calculated,its advantages in keeping better high-frequency feature,better noise immunity,short time-consuming and easier design are verified.

Design and technology review of the solar X-ray detector onboard the Macao Science Satellite-1B

On May 21,2023,the Macao Science Satellite-1B(MSS-1B),a low-inclination,low-latitude,and high-precision scientific exploration satellite for geomagnetic fields and space environments,was successfully launched.The solar X-ray detector(SXD),one of the two major scientific payloads onboard the MSS-1B,has obtained a large amount of solar X-ray radiation data,which reveals the distribution law of the magnetic field in the low Earth orbit,as well as the coupling law of the Earth's magnetic field and the solar radiation and energy particle distributions.First,the overall design of the multi-detection-unit,broad-energy-range,small-volume,and low-power SXD was implemented to achieve the scientific objectives of the mission.Second,the technical indicators of the instrument were decomposed into various components,and the key technologies,such as collimator,processing circuit,thermal,and payload dataset designs,were reviewed.Third,the backgrounds,including electronic noise,cosmic diffuse X-ray background,and high-energy background in the Earth's radiation belts in and out of the field of view,were analyzed for the instrument.Then,the ground calibrations of the energy response,detection efficiency,and temperature-dependent peak drift of the SXD flight model were conducted.Finally,the in-orbit temperature,energy spectrum data,background,and solar flare process observation of the instrument in the in-orbit test stage are presented,verifying the instrument design,analysis,and ground calibration,providing a foundation for obtaining accurate solar X-ray radiation data,and achieving the scientific objectives of the satellite.

Use of X-ray computed tomography to study structures and particle contacts of granite residual soil

A small problem about soil particle regularization and contacts but essential to geotechnical engineering was studied.The soils sourced from Guangzhou and Xiamen were sieved into five different particle scale ranges(d<0.075 mm,0.075 mm≤d<0.1 mm,0.1 mm≤d<0.2 mm,0.2 mm≤d<0.5 mm and 0.5 mm≤d<1.0 mm)to study the structures and particle contacts of granite residual soil.The X-ray micro computed tomography method was used to reconstruct the microstructure of granite residual soil.The particle was identified and regularized using principal component analysis(PCA).The particle contacts and geometrical characteristics in 3D space were analyzed and summarized using statistical analyses.The results demonstrate that the main types of contact among the particles are face-face,face-angle,face-edge,edge-edge,edge-angle and angle-angle contacts for particle sizes less than 0.2 mm.When the particle sizes are greater than 0.2 mm,the contacts are effectively summarized as face-face,face-angle,face-edge,edge-edge,edge-angle,angle-angle,sphere-sphere,sphere-face,sphere-edge and sphere-angle contacts.The differences in porosity among the original sample,reconstructed sample and regularized sample are closely related to the water-swelling and water-disintegrable characteristics of granite residual soil.