Fractally Invariant Distributions and an Application in Geochemical Exploration

Fractal modelling has been applied extensively as a means of characterizing the spatial distribution of geological phenomena that display self-similarity at differing scales of measurement. A fractal distribution exists where the number of objects exhibiting values larger than a specified magnitude displays a power-law dependence on that magnitude, and where this relationship is scale-invariant. This paper shows that a number of distributions, including power-function, Pareto, log-normal and Zipf, display fractal properties under certain conditions and that this may be used as the mathematical basis for developing fractal models for data exhibiting such distributions. Population limits, derived from fractal modelling using a summation method, are compared with those derived from more conventional probability plot modelling of stream sediment geochemical data from north-eastern New South Wales. Despite some degree of subjectivity in determining the number of populations to use in the models, both the fractal and probability plot modelling have assisted in isolating anomalous observations in the geochemical data related to the occurrence of mineralisation or lithological differences between sub-catchments. Thresholds for the main background populations determined by the fractal model are similar to those established using probability plot modelling, however the summation method displays less capacity to separate out anomalous populations, especially where such populations display extensive overlap. This suggests, in the geochemical data example provided, that subtle differences in the population parameters may not significantly alter the fractal dimension.     

Analysis on Bearing Capacity of Tunnel-Type Anchorage of a Long-Span Suspension Bridge

INTRODUCTION Tunnel typeanchoragehasobviousadvantages inbearingcapacityversusinvestment(LiuandHu,1996).However,itisrarelyusedinapracticalpro jectbecauseofitsrequirementofgoodrockcondi tions.Siduhebridge(Fig.1),whichliesintheBa dongmountainsinthewestplatea…     

北祁连山白山子花岗闪长岩成岩时代

寒山大型金矿是近年来在北祁连山西段发现的与侵人岩有关的构造蚀变岩型金矿。笔者首次利用锆石U-Pb方法测得白山子花岗闪长岩的形成年龄为370±25 Ma，属于华力西期。寒山金矿的成矿主要在213.95~339 Ma间。在多期热液叠加，多期成矿作用中，早期成矿的热液很可能是白山子花岗闪长岩（370±25 Ma) ,寒山辉长岩(347.1±6. 4 Ma）共同提供的。由于该区有较多的中酸性岩体存在，它们可能为金的主要来源，因而，确定这些侵入体的形成年龄，对于在该区寻找蚀变岩型金矿不仅有重要的理论意义，而且有重要的现实意义。     

生态城市的内涵及建设策略

生态城市是通过倡导生态理念，采用生态技术，建立生态化产业体系，从而达到社会、经济、环境的可持续发展，实现自然生态平衡、人文生态和谐的城乡统一体。从可持续发展的角度出发，利用生态学和社会学的观点，论述生态城市的内涵，提出科学的城市规划、合理的城市评价指标体系、完善的城市管理制度是实现生态城市的前提，强调只有自然生态、人文生态两手抓才能真正实现经济、社会、环境全面发展。     

基于YOLO算法的海洋中尺度涡三维结构构建

海洋中尺度涡是一种常见的中尺度海洋现象,研究海洋中尺度涡的分布及运动特性对航运、气候、军事等具有重要作用,海洋中尺度涡的识别是海洋学和计算机科学领域的一个热门研究课题。运用深度学习的方法和框架,对中尺度涡的二维识别和三维结构构建展开研究分析。首先,获取全球海洋再分析数据并进行流线可视化,构建涡旋流线数据集;其次,利用YOLO v5s卷积神经网络对涡旋流线数据集进行训练,并对南海区域中尺度涡进行有效检测。实验结果表明,YOLO v5s训练后得到最优模型经过测试,平均检测精度均值达到了86.10%;最后,根据涡旋检测结果,对检测出的同时刻不同深度的涡旋判断是否属于同一涡旋,确定后进行该涡旋的三维结构构建。     

安哥拉东北部地区Inkisi组碎屑锆石U- Pb年龄、地球化学特征及其地质意义

Inkisi组是刚果盆地西南缘最古老的沉积地层之一,岩性主要为一套紫红色、红褐色细粒、细中粒长石砂岩、杂砂岩。通过对安哥拉东北部Inkisi组长石砂岩开展碎屑锆石测年、岩石地球化学研究,探讨其沉积时代、物质来源、沉积环境和大地构造背景,为研究刚果盆地演化提供科学依据。结果表明,碎屑锆石206Pb/238U年龄主要集中于3个年龄峰值区间2350~1900 Ma、1150~850 Ma、850~500 Ma,最年轻的锆石峰值年龄为531±9 Ma,据此,笔者等认为Inkisi组的沉积时代上限应厘定为早寒武世。Inkisi组砂岩地球化学特征显示,物源具有长英质物源近源搬运特征,沉积时期的水体为陆相开阔的淡水环境。通过碎屑锆石年龄谱特征、主微量元素物源判别及构造判别图解,本文认为,West Congo构造带为安哥拉东北部地区Inkisi组主要物源区,Lufilian构造带、Angola 地盾等是其次要物质来源,物源区构造环境主要为活动大陆边缘和被动大陆边缘构造环境背景。     

基于ROSE2.0的普洱地区CINRAD/CC雷达冰雹探测算法评估及参数本地化

为提高冰雹探测算法（Hail Detection Algorithm,HDA）产品的可用性,针对2015—2020年普洱地区监测到的22次冰雹个例,利用新一代雷达业务应用软件ROSE2.0对相关雷达基数据进行回放及产品分析,以命中率、虚警率、临界成功指数为指标对HDA算法在普洱地区的识别效果进行评估并给出本地化参数配置方案。结果表明:HDA算法在普洱地区命中率接近100%,但虚警现象非常普遍,使用强冰雹概率（Probability of Severe Hail,POSH）的预警效果优于任意大小冰雹概率（Probability of Hail,POH）,且冰雹尺寸越大POSH虚警的概率越低。进一步使用模拟测评法对POSH算法的适配参数进行分析,发现正确输入降雹日当天的0 ℃层和-20 ℃层高度能有效减少POSH的虚警率及提高临界成功指数;同时使算法预测的最大冰雹直径普遍偏大的情况得到控制,其中,中小冰雹直径偏离百分比减小76.07%,改善效果显著高于大冰雹。此外,增大反射率因子及POSH阈值能有效控制虚警,但也导致漏报次数快速增加,当阈值太大时命中率明显降低,为了保证较高的命中率和临界成功指数,选择Z=50 dBz或POSH=70%为阈值能明显改善HDA算法的识别效果。     

Influence of Near Real-Time Green Vegetation Fraction Data on Numerical Weather Prediction by WRF over North China

The green vegetation fraction(GVF) can greatly influence the partitioning of surface sensible and latent heat fluxes in numerical weather prediction(NWP) models. However, the multiyear averaged monthly GVF climatology—the most commonly used representation of the vegetation state in models—cannot capture the real-time vegetation state well. In this study, a near real-time(NRT) GVF dataset generated from an 8-day composite of the normalized difference vegetation index is compared with the 10-yr averaged monthly GVF provided by the WRF model. The annual variability of the GVF over North China is examined in detail. Many differences between the two GVF datasets are found over dryland, grassland, and cropland/grassland mosaic areas. Two experiments using different GVF datasets are performed to assess the impacts of GVF on forecasts of screen-level temperature and humidity. The results show that using NRT GVF can lead to a widespread reduction of 2-m temperature forecast errors from April to October.Evaluation against in-situ observations shows that the positive impact on 2-m temperature forecasts in the morning is more distinct than that in the afternoon. Our study demonstrates that NRT GVF can provide a more realistic representation of the vegetation state, which in turn helps to improve short-range forecasts in arid and semiarid regions of North China. Moreover, our study shows that the negative effect of using NRT GVF is closely related to the initial soil moisture.     

滇东南官房钨矿床矽卡岩矿物学特征及其地质意义

官房钨矿床位于滇东南薄竹山W多金属矿集区,是近年来新发现的大型白钨矿床。矽卡岩多产于层间破碎带,呈似层状、透镜状和脉状,一般不与花岗岩体接触而形成远端矽卡岩（深部揭露有少量产于接触带）,矽卡岩矿物发育。为进一步查明矽卡岩矿物学和矿物化学特征,揭示矽卡岩形成环境,探讨矽卡岩与矿化类型之间的关系,笔者采集了KT3近端矽卡岩与KT5远端矽卡岩进行对比,通过开展系统的矿物学镜下观察,利用EMPA进行石榴子石成分分析,LA-ICP-MS对典型的矽卡岩矿物进行了单矿物分析。研究表明,官房钨矿床矽卡岩属典型钙质矽卡岩,矽卡岩矿物主要有石榴子石、辉石、符山石等,其中石榴子石为钙铝榴石-钙铁榴石系列,辉石为透辉石-钙铁辉石系列,符山石属普通符山石。由近端矽卡岩向远端矽卡岩,石榴子石主要成分由钙铝榴石向钙铁榴石转化;辉石几乎全部为透辉石向透辉石、钙铁辉石的组合转化,石榴子石与辉石的特征表明矿床的矽卡岩由还原型矽卡岩转为氧化型矽卡岩;KT5形成条件较KT3氧逸度更高,两者流体交代方式以扩散交代为主。石榴子石、辉石端员组分及Mn/Fe、Mg/Fe比值稍高的特征,综合指示其矿化类型属于铁铜锌等多金属矿化类型;符山石中较低的w（W）可作为钨矿找矿标志。