融合教育中特殊需要幼儿的社会参与状况及其影响因素--基于H市42个融合班级的调查数据分析

实现特殊需要幼儿的社会参与是学前融合教育的目标之一,这使得特殊需要幼儿的社会参与状况成为衡量学前融合教育质量的重要指标之一。本研究以来自H市14所幼儿园42个融合班级的89名特殊需要幼儿及其1133名同班普通幼儿为调查对象,基于同伴社会计量报告以及教师对特殊幼儿互动的评估,从同伴接纳、友谊/社会关系、同伴互动三方面考察特殊需要幼儿社会参与状况及其影响因素。结果发现,特殊需要幼儿社会参与状况总体堪忧,同伴接纳水平总体较低,消极互动水平较高且积极互动水平很低;个人维度中的外化问题行为和性别可以预测特殊需要幼儿社会参与,女童比男童更容易被同伴接纳,问题行为严重的幼儿则更容易被拒绝。提升特殊需要幼儿的社会参与,需要加强幼儿园资源教室建设,改善特殊需要幼儿的问题行为,强化家庭、幼儿园以及康复或干预机构之间的合作,等等。

On the Development of a Model for the Prediction of Liquid Loading in Gas Wells with an Inclined Section

The ability to predict liquid loading in horizontal gas wells is of great importance for determining the time of drainage and optimizing the related production technology.In the present work,we describe the outcomes of experiments conducted using air-water mixtures in a horizontal well.The results show that the configuration with an inclined section is the most susceptible to liquid loading.Laboratory experiments in an inclined pipe were also conducted to analyze the variation of the critical gas flow rate under different angles,pressure and liquid volume(taking the equal liquid volume at inlet and outlet as the criterion for judging on the critical state).According to these results,the related angle of the inclined section ranges from 45°to 60°.Finally,a modified approach based on the Belfroid model has been used to predict the critical gas flow rate for the inclined section.After comparison with field data,this modified model shows an accuracy of 96%,indicating that it has better performances with respect to other models used in the past to predict liquid loading.

IN VIVO VALIDATION OF DUAL-MODALITY SYSTEM FOR SIMULTANEOUS POSITRON EMISSION TOMOGRAPHY AND OPTICAL TOMOGRAPHIC IMAGING

We report on tests of combined positron emission tomography(PET)andfluorescence molecular tomography(FMT)imaging system for in vivo investigation on small animals.A nude mouse was inoculated with MD-MB-231 breast cancer cells which expressed redfluorescent protein(RFP).For FMT system,reflective illumination mode was adopted with full-angle data acquisition.[18F]-Fluorodeoxyglucose([18F]-FDG)was used as radioactive tracer for PET.Both data were acquired simultaneously and then reconstructed separately before fusion.Fluorescent tomography results showed exactly where the tumor was located while PET results offered more metabolic information.Results confirmed feasibility for tumor detection and showed superiority to single modality imaging.

Image reconstruction for the coded aperture system in nuclear safety and security using a Monte Carlo-based system matrix

Purpose Accurate localization of radioactive materials is critical to nuclear safety and nuclear security.A coded aperture imaging system provides a visualization solution.However,the correlation method has poor reconstruction performance for sources with low counts and for extended sources.Methods In this study,a Monte Carlo optimization-based MLEM algorithm(MC-MLEM)is proposed.The system matrix was obtained by accurate Monte Carlo simulation,so the physical effects such as mask penetration that affect the imaging process were taken into account in the MLEM algorithm.In the simulation process,the normalization of the system matrix was realized by controlling the source at different position of the source plane to have the same activity and emission angle.Results The experimental results showed that compared with the correlation method,the MC-MLEM algorithm could improve the signal-to-noise ratio and angular resolution and locate the source position quickly and accurately under low count conditions.Furthermore,the MC-MLEM algorithm could reconstruct the shape of the extended source and the expected activity ratio of cold-hot sources with large activity differences.Conclusion The MC-MLEM algorithm improved the imaging results and enhanced the reconstruction performance.

A high-position-resolution trajectory detector system for cosmic ray muon tomography:Monte Carlo simulation

Purpose The research focuses on the related designing and simulating the high-position-resolution trajectory detector system based on cosmic ray muon tomography.Methods The energy deposition of muon in the detector varies with the length of the ionization path.Results The simulation of the submillimeter detector system was designed for muon imaging.The optimal position resolution of the detector reached 0.6 mm.Conclusions The entire research process includes the selection of analysis of parameters affecting system design,designing of two high-position-resolution detectors based on plastic scintillators,implementation of different imaging algorithms and image quality assessment based on different imaging models.It provides a solution based on high positional resolution plastic scintillator detectors for cosmic ray muon scattering imaging.

A deep learning-based ring artifact correctionmethod for X-ray CT

Purpose In X-ray CT systems,ring artifacts caused by the nonuniform response of detector elements degrades the reconstruction quality and affects the subsequent processing and quantitative analysis of the image.Method In this paper,a novel method is proposed to remove the ring artifacts in CT image by applying deep learning algorithm based on convolutional neural network(CNN)and recurrent neural network(RNN).First,the reconstructed CT images is transformed into polar coordinate system to make rings appear as stripes.Then,a CNN is constructed to detect the stripes,and a RNN is utilized to process the line artifact correction.After that,by retransforming the corrected image from polar coordinate system to Cartesian coordinate system,a ring artifact removal image can be achieved.Results The presented method can successfully reduce the CT ring artifact on simulated and real data.Specifically,in the experiment with real water phantom,the center and peripheral standard deviations reduced 46%and 24%,respectively.Conclusions The proposed method is potential to be widely deployed in industrial and medical CT systems,due to the excellent results on correction and the real-time performance without adjusting parameters manually.

Compact MPPC-based coded aperture imaging camera for dual-particle detection

Purpose Fast neutrons and gamma-ray imaging detection is an effective way to detect and identify radioactive material in the field of nuclear security.A compact coded aperture imaging(CAI)camera was designed to be sensitive to both gamma and neutron radiation based on plastic scintillators and multi-pixel photon counters(MPPC).Methods MPPCs coupling with the 13×13 pixelated plastic scintillators one-to-one were utilized to reduce the scale of the CAI system while maintaining good positional performance.The symmetric charge division(SCD)circuit was adopted to reduce the 169 signals output from the MPPC array to 26.Each waveform was collected and processed with four Domino Ring Sampler 4(DRS4)chips and two 16-channel analog-to-digital converter(ADC)modules.As the pulse shapes of fast neutrons would be broadened after elastic scattering multiple times in the scintillators,the Anger-Logic method was applied to eliminate multiple elastic scattering events so that good pulse shape discrimination(PSD)performance can be achieved.Results The imaging and detection ability of the camerawas evaluated using the 241Am-Be(5.9×10^(5) n/s)neutron source and 137Cs(370 MBq)gammasource.The camera can be used to detect fast neutrons(0.5–10 MeV)and gammarays(0.2–2.5MeV).Furthermore,it can implement efficient neutron/gamma PSD capabilities in the mixed-field environment.The figure of merit(FOM)of the camera calculated at 400keVee energy cut is 0.93.Conclusion A compact MPPC-based CAI camera was designed to detect and discriminate fast neutrons and gamma rays.Its good PSD performance was well suited to distinguish fast neutrons from gamma rays in a dual-particle environment.The portable design makes it promising for complex monitoring scenarios in nuclear security.

Geology, environment, and life in the deepest part of the world’s oceans

The hadal zone,mostly comprising of deep trenches and constituting of the deepest part of the world’s oceans,represents the least explored habitat but one of the last frontiers on our planet.The present scientific understanding of the hadal environment is still relatively rudimentary,particularly in comparison with that of shallower marine environments.In the last 30 years,continuous efforts have been launched in deepening our knowledge regarding the ecology of the hadal trench.However,the geological and environmental processes that potentially affect the sedimentary,geochemical and biological processes in hadal trenches have received less attention.Here,we review recent advances in the geology,biology,and environment of hadal trenches and offer a perspective of the hadal science involved therein.For the first time,we release highdefinition images taken by a new full-ocean-depth manned submersible Fendouzhe that reveal novel species with an unexpectedly high density,outcrops of mantle and basaltic rocks,and anthropogenic pollutants at the deepest point of the world’s ocean.We advocate that the hydration of the hadal lithosphere is a driving force that influences a variety of sedimentary,geochemical,and biological processes in the hadal trench.Hadal lithosphere might host the Earth’s deepest subsurface microbial ecosystem.Future research,combined with technological advances and international cooperation,should focus on establishing the intrinsic linkage of the geology,biology,and environment of the hadal trenches.

Position coordinates-based iterative reconstruction for robotic CT

Purpose Robotic CTs can achieve customized trajectory scanning with x-ray tube and detector held by flexible robotic arms rather than fixed rails or gantry.However,the motion errors of the robotic arms cannot be neglected.Hence,the reconstruction method of Robotic CTs should be suitable for arbitrary trajectory and should take motion errors into full consideration.Method In this paper,we present an iterative reconstruction method for robotic CT systems.Unlike the analytical algorithms,such as FDK,this method makes no assumption about the scan trajectory.The projection and backprojection operations are modeled by 3D distance-driven algorithm using the coordinates of x-ray source and detector center fed back from the robotic arm’s positioning system directly.Both numerical simulations and practical experiments are conducted to verify the effectiveness of this method in arbitrary trajectory reconstruction and motion errors correction for robotic CT systems.Results For our non-circular and non-planar trajectory scan,this proposed method could easily handle the reconstruction and obtain a result comparable to reference.In addition,for 0.1%motion errors,using the proposed method could improve the reconstruction quality,and the RMSE could be reduced by 30%.Conclusions This iterative reconstruction method is suitable for arbitrary trajectory scans and can decrease the degradation of image quality caused by motion errors of robotic arm.

A preliminary study on 3D position reconstruction ofmonolithic crystal readout

Purpose Compared to pixelated crystal detectors,monolithic crystal detectors present more advantages.Without reflective layer between crystal pixel,monolithic crystal detectors provide higher detection efficiency while being cheaper.Another important feature is that monolithic crystal detectors can provide depth of interaction(DOI)information,which can improve image quality in nuclear imaging systems.In this article,we aim to study a new positioning scheme of this kind of detector in order to push its applications in nuclear imaging systems.Methods Fan-beam collimation and convolutional neural network are combined to reconstruct interaction points in crystal.Firstly,we built a monolithic detector model based on Geant4 and validated this positioning scheme with simulation data.Then,we constructed a monolithic GAGG(Ce)detector and evaluated its performance with experimental data.Results With proposed positioning scheme,in experiment,we obtained~1.7 mm FWHM resolution on average in x-/ydirection,while~2.5 mm FWHM resolution on average in DOI direction for a 33×33×10 mm3 monolithic GAGG(Ce)crystal coupled with 8×8 SiPM array.Conclusion Through simulations and experiments,we validated our positioning scheme,i.e.,fan-beam collimation and convolutional neural network.Convolutional neural network can reconstruct 3D positions of gamma-rays interaction points in a high resolution,and fan-beam collimation can provide high calibration efficiency;with combination of them,we established a high position resolution and high calibration efficiency positioning scheme for monolithic crystal detector.

A study on noise reduction for dual-energy CT material decomposition with autoencoder

Purpose A major challenge for the material decomposition task of the dual-energy computed tomography(DECT)is the algorithm often suffers from heavy noise in the results.The purpose of this study is to propose a scheme to increase the noise performance of material decomposition.Methods The scheme we propose in this paper is to apply an autoencoder-based denoising procedure to the photon-counting DECT images before they are fed into the material decomposition algorithm.We implement the autoencoder(AE)by stacking a series of convolutional and deconvolutional layers.The decomposition technique adopted in our work is an iterative method using least squares estimation with the Huber loss function.The noises of the input and the output of material decomposition are analyzed with both simulated data and real data.Phantom and chicken wing experiments are conducted with a photoncounting-based spectral CT scanner to evaluate the proposed material decomposition scheme.Results The noise analysis of the input and the output of material decomposition demonstrates a positive correlation between them.Comparative experiment indicates a noise reduction in the output density maps for 26.07%to 35.65%after the autoencoder pre-processing is applied.The resultant contrast-to-noise ratio is largely increased,correspondingly.Conclusions By utilizing the additional autoencoder denoising step,the material decomposition algorithm achieves an improvement in the noise performance of the resultant density maps.