Safety First: Recognizing and Managing the Risks to Child Participants in Magnetic Resonance Imaging Research

Specialized and up-to-date knowledge is required to identify and manage the risks associated with advanced biomedical research. Additional complexities need to be considered when the research involves infants or young children. In this article, we focus on recent information about the physical risks of pediatric magnetic resonance imaging research and highlight information gaps. With an eye to assisting institutional review boards and researchers, we consider strategies for the management of these risks and formulate key questions aimed at exposing hidden hazards. Institutional review boards should ask these questions, and researchers should bear them in mind as they develop research protocols.     

Disclosure of Unknown Harms in Magnetic Resonance Imaging Research

Unknown harms are by their nature difficult to communicate. While magnetic resonance imaging (MRI) has known risks (e.g., metal projectiles, dislodgement of medical implants), this imaging modality also has potential unknown long-term negative health effects associated with its static magnetic fields. We carried out a research ethics board (REB) file review of previously approved MRI research studies and found that unknown risks were either left undisclosed or were inadequately disclosed to research participants and REBs. This article outlines issues raised by our REB file review and suggests steps that should be taken in order to satisfactorily communicate information about potential unknown harms of MRI.     

小畸变参数情况下稳态热晕效应数值分析

根据几何光学近似和小扰动理论,推导了高斯光束热晕效应的解析公式,据此解析公式对准直高斯波束的热晕效应进行了计算。结果表明,热畸变参数越大,热晕效应越强,但是,随着热畸变参数的增大,上述解析公式不再适用。     

半埋热油管道传热研究

受飓风、暴雨、泥石流等恶劣天气的影响,埋地管道可能局部处于半掩埋状态。目前半埋管道传热计算多采用“线性插值”模型。建立了半埋热油管道的流（空气水）—管—土耦合传热机理模型,并利用数值模拟手段对不同条件下管道的传热特性进行了研究。结果表明,管道的总传热系数、出口温度和土壤蓄热量与管道的相对埋入面积呈明显的非线性关系;线性模型与机理模型的计算结果在趋势与数值方面均具有较大偏差;管道刚好完全掩埋时与完全不掩埋时相比,总传热系数出口温度的差异较大,且管径越大,差异越显著;当环境流体的温度较低时,管道出口温度对相对埋入面积更敏感。     

Multivariate functional response low‐rank regression with an application to brain imaging data

We propose a multivariate functional response low‐rank regression model with possible high‐dimensional functional responses and scalar covariates. By expanding the slope functions on a set of sieve bases, we reconstruct the basis coefficients as a matrix. To estimate these coefficients, we propose an efficient procedure using nuclear norm regularization. We also derive error bounds for our estimates and evaluate our method using simulations. We further apply our method to the Human Connectome Project neuroimaging data to predict cortical surface motor task‐evoked functional magnetic resonance imaging signals using various clinical covariates to illustrate the usefulness of our results.     

A spatial Bayesian semiparametric mixture model for positive definite matrices with applications in diffusion tensor imaging

Studies on diffusion tensor imaging (DTI) quantify the diffusion of water molecules in a brain voxel using an estimated 3 × 3 symmetric positive definite (p.d.) diffusion tensor matrix. Due to the challenges associated with modelling matrix‐variate responses, the voxel‐level DTI data are usually summarized by univariate quantities, such as fractional anisotropy. This approach leads to evident loss of information. Furthermore, DTI analyses often ignore the spatial association among neighbouring voxels, leading to imprecise estimates. Although the spatial modelling literature is rich, modelling spatially dependent p.d. matrices is challenging. To mitigate these issues, we propose a matrix‐variate Bayesian semiparametric mixture model, where the p.d. matrices are distributed as a mixture of inverse Wishart distributions, with the spatial dependence captured by a Markov model for the mixture component labels. Related Bayesian computing is facilitated by conjugacy results and use of the double Metropolis–Hastings algorithm. Our simulation study shows that the proposed method is more powerful than competing non‐spatial methods. We also apply our method to investigate the effect of cocaine use on brain microstructure. By extending spatial statistics to matrix‐variate data, we contribute to providing a novel and computationally tractable inferential tool for DTI analysis.     

百色盆地第三系烃源岩热模拟特征研究

百色盆地第三系百岗组和那读组湖相烃源岩为混合型。通过2个典型未成熟暗色泥岩样品加水热压模拟实验的液态烃、气态烃产率及组成等对比分析,发现两者存在明显的差异。那读组样品在低成熟～成熟阶段（模拟温度为230～350℃）以液态烃产出为主,其中低熟油的累积产率约占60%的比例。百岗组样品在低成熟阶段液态烃产率略大于气态烃产率,到成熟阶段则以气态烃产出为主。在热模拟的气相产物组成中,那读组样品的气态烃含量随模拟温度升高具有明显的双峰特征。在热模拟液态烃中,C₂₇、C₂₈、C₂₉规则甾烷呈“V”字型分布,C₂₇／C₂₉甾烷比值、姥/植比值和伽马蜡烷含量随模拟温度增加的变化较小,Ts/Tm比值随模拟温度增加的变化幅度较大。     

基于CCD图与红外热像图融合的人脸识别分析研究

针对CCD图或红外热像图人脸识别方法的局限性,本文从多传感器图像融合技术出发。采用基于CCD图与红外热像图决策级融合的人脸识别方法,并建立了一个800幅的人脸图像库,进行人脸识别实验。实验表明:基于决策融合的人脸识别方法比单纯的CCD图或红外热像图人脸识别方法,具有更高的识别率。     

临床X射线相衬成像研究进展

X射线相衬成像在提高人体软组织成像的衬度分辨率及空间分辨率研究中具有潜在优势,是一项有着广阔发展前景的技术。它利用空间相干X射线投过物体后携带的相位信息进行成像,在临床上适用于软组织物体,可以减少吸收剂量,进而减轻病人的辐射损伤。本文详述了当今几种典型的X射线相衬成像方法,包括X射线干涉相衬,衍射增强相衬以及类同轴相衬的成像原理以及发展历程。通过对比表明了几种成像方法的优缺点。最后对临床X射线相衬成像有待解决的问题作了分析。     

高精度高测速双纵模热稳频激光干涉仪研究

现代机械工业的发展使得数控机床和三坐标测量机等的运行速度已经达到1000mm/s,而目前商用外差干涉仪的测量速度不能满足这一要求。为此该文采用长度为206mm、频差约728MHz的普通全内腔He-Ne热稳频激光器为光源,外加带有高频振荡器形成的交流信号进行脉冲计数的信号处理电路,构成高精度高速双纵模热稳频激光干涉仪。通过实验对干涉仪的测量速度和精度进行了验证,其精度达到0.1μm/800mm。实验证明,该干涉仪可以对速度为1000mm/s的运动物体进行位移和速度测量。