胰腺低剂量CT灌注扫描成像技术应用现状及研究趋势

目前,胰腺的影像学诊断逐渐从常规CT扫描单一的形态学诊断向CT灌注形态和功能学并重诊断转变;CT灌注是在常规CT扫描基础上发展起来的一种功能影像成像技术,通过CT灌注观察胰腺微循环变化可以早期诊断胰腺疾病,在胰腺疾病研究领域中是热点;用常规条件行CT灌注扫描,明显地增加了患者的辐射剂量,如何行低辐射剂量CT灌注成为当前重点探讨方向。本文综述胰腺低剂量CT灌注扫描成像技术应用现状及研究趋势。     

2006年6月10日浙江飑线FY-2C卫星云图特征

利用国际卫星云气候计划（International Satellite Cloud Climate Program,简称ISCCP）提供的1998—2007年共10 a的深对流路径跟踪资料,统计分析了影响江淮地区对流系统（Convection system,简称CS）的时空分布及其参数特征。结果表明：影响江淮地区的CS主要集中在春夏两季,大多生成于江淮本地及我国中西部地区,呈现以江淮地区为中心的带状分布特征,越靠近江淮区域CS分布越为密集。依据源地不同,将影响江淮地区的CS分为5类,受气候条件与地形地貌的共同作用,各源地CS参数特征差异显著,总体来说CS的水平尺度越大,其生命史、对流云团(Convective clusters,简称CC)数目及水平云温度梯度也越大。其中江淮中心区域（MID）区域CS水平尺度、生命史和CC数目的平均值均为最小;东南（SE）区域CS生命周期以中长周期为主,水平尺度、最大对流比和云温度梯度的平均值最大。梅雨期内江淮地区对流活动频繁,CS的水平尺度大、生命史长、CC数目多。

     

基于积分图像的面状注记配置方法研究

提出了一种基于积分图像的面状图形注记自动配置算法,设计并实现了基于积分图像的面状注记配置的核心算法。实验表明,该算法能快速准确地定位待标记注记的位置,合理而又美观地实现面状图形注记的自动配置。该算法已成功应用于深圳市地籍测绘大队的房产测绘系统中。     

BP神经网络用于水下地形适配区划分的方法研究

为确保背景场中最优适配航线设计的正确性以及水下地形匹配导航的可靠性,提出了一种基于BP神经网络的背景场适配/误配区自动识别和划分方法,该方法通过分析地形背景场特征参量显著性和主成分、构建BP神经网络、建立输入地形特征参量与匹配性能的映射关系,最终实现了地形背景场误配/适配区的自动识别和划分。试验验证了本方法的有效性。     

球谐函数变换快速计算扰动引力

在球谐函数变换基础上,利用新极下轨道的特殊性,在新坐标下引入Clenshaw求和计算轨道扰动引力。从理论上对比分析了传统方法、球谐函数变换方法和改进方法的计算速度和存储模型需要的物理空间。模拟试验分别采用3种方法计算了一段轨道的扰动引力,试验结果表明,改进的球谐函数变换方法比传统球谐函数变换方法计算速度可提高100倍,数据存储量仅占传统方法的3%。     

The use of digital technologies for landslide disaster risk research and disaster risk management: progress and prospects

Landslide is a serious natural disaster next only to earthquake and flood, which will cause a great threat to people’s lives and property safety. The traditional research of landslide disaster based on experience-driven or statistical model and its assessment results are subjective , difficult to quantify, and no pertinence. As a new research method for landslide susceptibility assessment, machine learning can greatly improve the landslide susceptibility model’s accuracy by constructing statistical models. Taking Western Henan for example, the study selected 16 landslide influencing factors such as topography, geological environment, hydrological conditions, and human activities, and 11 landslide factors with the most significant influence on the landslide were selected by the recursive feature elimination (RFE) method. Five machine learning methods [Support Vector Machines (SVM), Logistic Regression (LR), Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Linear Discriminant Analysis (LDA)] were used to construct the spatial distribution model of landslide susceptibility. The models were evaluated by the receiver operating characteristic curve and statistical index. After analysis and comparison, the XGBoost model (AUC 0.8759) performed the best and was suitable for dealing with regression problems. The model had a high adaptability to landslide data. According to the landslide susceptibility map of the five models, the overall distribution can be observed. The extremely high and high susceptibility areas are distributed in the Funiu Mountain range in the southwest, the Xiaoshan Mountain range in the west, and the Yellow River Basin in the north. These areas have large terrain fluctuations, complicated geological structural environments and frequent human engineering activities. The extremely high and highly prone areas were 12043.3 km² and 3087.45 km², accounting for 47.61% and 12.20% of the total area of the study area, respectively. Our study reflects the distribution of landslide susceptibility in western Henan Province, which provides a scientific basis for regional disaster warning, prediction, and resource protection. The study has important practical significance for subsequent landslide disaster management.     

Thermal and tectonic evolution of the southern Alps (northern Italy) rifting: Coupled organic matter maturity analysis and thermokinematic modeling

The Pearl River Mouth Basin (PRMB) is one of the most petroliferous basins on the northern margin of the South China Sea. Knowledge of the thermal history of the PRMB is significant for understanding its tectonic evolution and for unraveling its poorly studied source-rock maturation history. Our investigations in this study are based on apatite fission-track (AFT) thermochronology analysis of 12 cutting samples from 4 boreholes. Both AFT ages and length data suggested that the PRMB has experienced quite complicated thermal evolution. Thermal history modeling results unraveled four successive events of heating separated by three stages of cooling since the early Middle Eocene. The cooling events occurred approximately in the Late Eocene, early Oligocene, and the Late Miocene, possibly attributed to the Zhuqiong II Event, Nanhai Event, and Dongsha Event, respectively. The erosion amount during the first cooling stage is roughly estimated to be about 455–712 m, with an erosion rate of 0.08–0.12 mm/a. The second erosion-driven cooling is stronger than the first one, with an erosion amount of about 747–814 m and an erosion rate between about 0.13–0.21 mm/a. The erosion amount calculated related to the third cooling event varies from 800 m to 3419 m, which is speculative due to the possible influence of the magmatic activity.     

河流地貌演化研究进展

本文基于近年来全球河流地貌演化的研究实例及新进展,介绍了主要的研究载体与思路,讨论了河流地貌演化事件背后的地质、环境意义。沉积学、地貌学、物源分析、低温热年代学等是解决河流地貌演化问题的重要工具。沉积学记录着河流演化的一手资料,同时,沉积物定年技术的发展为揭示河流演化过程提供了高精度的时间约束。地貌指数研究是根据河流剖面形态与流域特征等揭示河流及区域地貌演化过程的研究手段,在恢复基岩隆升历史,定义地貌演化状态和判断分水岭迁移等方面具有优势。基于碎屑热年代学的物源分析方法结合沉积物沉积年代测定的研究思路则是利用了地表物质的“源—汇”过程变化,是揭示水系沟通演化历史的有效手段。当借助中-低温热年代学的多方法联合和单矿物的多重定年作为物源示踪剂时,可以有效提高分析精度,具有广阔的研究前景。另外,低温热年代学和宇宙核素¹⁰Be等对浅表过程十分敏感,记录了百万年—千年尺度的河流侵蚀作用,是示踪流域侵蚀方式空间变化和定量化揭示侵蚀过程的有力工具。河流的诞生与演化是地表过程的重大事件,记录了局部或区域的构造—气候背景,也是研究构造—气候—地貌耦合及互馈过程的重要纽带。特别是新生代晚期以来,地貌形成过程伴随着古人类的诞生与发展,而河流的演化则在古人类活动和迁徙中起到了重要的控制作用。因此,河流地貌演化的背景动力及环境意义体现了地球多圈层的相互作用与协同演化。

     

塔克拉玛干沙漠腹地逐日太阳总辐射模拟计算 -以达理雅博依绿洲为例

基于塔克拉玛干沙漠腹地面积最大的天然孤立绿洲达理雅博依2015年1月—2016年2月太阳总辐射观测资料,运用H.L.Penman经验公式模拟计算了该地区2015年逐日总辐射累计量,模拟值与实测值的误差分析显示:本气候学方法成功模拟了沙漠腹地总辐射的年内变化趋势。使用模拟值估算得到达理雅博依绿洲2015年太阳总辐射累计量约为5 332.23 MJ·m-2。又以相同方法模拟了塔中气象站2015年3—5月总辐射变化,结果较达理雅博依的模拟更接近实测值,说明本模拟在塔克拉玛干沙漠腹地不同地点结果有效。     

5月青藏高原上空环流与北疆夏季降水的关系

基于1961—2016年5—8月西藏高原环流指数、NCEP再分析资料和新疆96个气象观测站点的降水资料,通过相关分析和合成分析,研究了5月青藏高原上空环流与北疆夏季降水的关系,以及两者之间可能影响的物理机制。结果表明:(1)5月西藏高原环流指数Ⅰ与北疆夏季降水有较好的相关性,相关系数为0.38;(2)5月西藏高原环流指数Ⅰ的强弱变化会影响500hPa的夏季环流特征、夏季地表至300 hPa的水汽通量输送,当指数偏强时,夏季环流形势的配置和水汽输送均有利于北疆夏季降水,反之,则不利于北疆夏季降水;(3)夏季西藏高原环流指数Ⅰ和北疆夏季降水、5月西藏高原环流指数Ⅰ的关系密切,并且5月西藏高原环流指数Ⅰ和青藏高原5月、夏季的感热通量有明显的负相关,通过高原的热力持续性作用,5月西藏高原环流指数Ⅰ的强弱可以影响北疆夏季降水的多少。