无机增强纤维Ⅰ.钛酸钾纤维

结晶质的钛酸钾纤维因其性质特殊而备受青睐，本文介绍了二钛酸钾、四钛酸钾、六钛酸钾和八钛酸钾纤维的结构、性质、用途，及国内外的研究现状．     

The effect of biological soil crusts of different successional stages and conditions on the germination of seeds of three desert plants

Biological soil crusts greatly affect soil surface properties, which, in turn, may alter seed germination of vascular plants. We investigated the effects of two types of biological soil crusts (moss crust and algal crust) at different ages on the seed germination of Bassia dasyphylla and Artemisia ordosica. We also investigated the effects of crust conditions (living crust and dead crust) on seed germination of B. dasyphylla, A. ordosica and Eragrostis poaeoides. The presence of both algal and moss crusts significantly enhanced the germination of B. dasyphylla and A. ordosica compared with uncrusted soil. Crust age had no significant effect on the germination of either B. dasyphylla or A. ordosica for both moss and algal crusts. Germination of B. dasyphylla differed significantly between moss and algal crusts, but germination of both A. ordosica and E. poaeoides did not. Germination of A. ordosica, E. poaeoides and B. dasyphylla was significantly higher on living algal crust than on dead crust and uncrusted soil, while living moss crust enhanced the germination of both A. ordosica and B. dasyphylla but had no significant effect on E. poaeoides.     

Hadoop环境下基于SparkSQL海量自动站数据查询统计初探

在Hadoop分布式计算和存储架构下,自定义ETL数据清洗规则将海量自动站小时单站文件按所属年和站号合并为大文件流转存储至HDFS中,并运用SparkSQL并行计算框架进行统计处理生成常用气象要素日统计值。结果表明,数据处理和获取时效较关系型数据库方式有显著提升。采用SparkSQL并行计算框架对多气象要素多站点和长时间序列进行数据统计处理查询均能达到秒级别响应,并随着统计站点数的不断增加和时间跨度的延长其优势更为明显,能更高效地支撑此类气象数据服务,为海量气象数据处理从关系型数据库到大数据分布式架构的转换处理提供了新思路。     

THE RESPONSE OF SUMMER DRYNESS/WETNESS PROBABILITY IN NORTH CHINA TO GLOBAL WARMING

Using the data of summer(June—August)precipitation during the period of 1951—1990 in 14 stations over NorthChina,the wetness probability(WP)series based on gamma distribution has been built.Main temporal and spatial char-acteristics for the series of WP in the stations are extracted by using empirical orthogonal functions(EOFs).The spatialpatterns show that the dryness/wetness variations in the stations in the area are consistent with each other and its maincharacteristics can be represented by the WP series in Beijing.Having analysed the WP series of 120 years(1870—1989)in Beijing,the results show that the dry tendency has a re-sponse to the global warming.The variation of the dryness/wetness in the stations is associated with the temperaturevariation in the Northern Hemisphere.Their relation is negative.The degree of the reliance is associated with the centuryvariation of the temperature.     

Strength of Stacking Technique of Ensemble Learning in Rockburst Prediction with Imbalanced Data: Comparison of Eight Single and Ensemble Models

Rockburst is a common dynamic geological hazard, severely restricting the development and utilization of underground space and resources. As the depth of excavation and mining increases, rockburst tends to occur frequently. Hence, it is necessary to carry out a study on rockburst prediction. Due to the nonlinear relationship between rockburst and its influencing factors, artificial intelligence was introduced. However, the collected data were typically imbalanced. Single algorithms trained by such data have low recognition for minority classes. In order to handle the problem, this paper employed stacking technique of ensemble learning to establish rockburst prediction models. In total, 246 sets of data were collected. In the preprocessing stage, three data mining techniques including principal component analysis, local outlier factor and expectation maximization algorithm were used for dimension reduction, outlier detection and outlier substitution, respectively. Then, the pre-processed data were split into a training set (75%) and a test set (25%) with stratified sampling. Based on the four classical single intelligent algorithms, namely k-nearest neighbors (KNN), support vector machine (SVM), deep neural network (DNN) and recurrent neural network (RNN), four ensemble models (KNN–RNN, SVM–RNN, DNN–RNN and KNN–SVM–DNN–RNN) were built by stacking technique of ensemble learning. The prediction performance of eight models was evaluated, and the differences between single models and ensemble models were analyzed. Additionally, a sensitivity analysis was conducted, revealing the importance of input variables on the models. Finally, the impact of class imbalance on the prediction accuracy and fitting effect of models was quantitatively discussed. The results showed that stacking technique of ensemble learning provides a new and promising way for rockburst prediction, which exhibits unique advantages especially when using imbalanced data.

     

基于ArcGIS的人工影响天气综合分析平台

人工影响天气业务涉及大、中、小、微尺度各种资料分析,信息种类繁多,类型复杂,需要一个强大的综合分析平台的支持。文章介绍了基于ArcGIS的人影综合分析平台(WMicaps)的总体设计目标、软件框架、数据标准化、系统数据库、平台主要功能以及主要采用的技术方法等。该平台是针对人工影响天气作业研究设计的系统,主要用于人影综合分析处理、决策指挥、效果评估以及高炮、火箭增雨防雹服务等。     

大型湖库滨岸带蓝藻水华堆积风险评估——以巢湖为例

淡水湖库富营养化与蓝藻水华是全球性的突出水环境问题,尤其是滨岸带严重蓝藻水华堆积甚至造成了水体黑臭、威胁饮用水安全等严重危害,科学评估滨岸带蓝藻水华堆积风险、精准识别蓝藻水华易堆积区域是水环境管理与研究中亟待解决的关键科学问题.本研究以我国长江中下游的大型浅水富营养化湖泊巢湖为研究对象,依托流域水文与湖泊水动力模拟、遥...     

On the timing of the East Asian summer monsoon maximum during the Holocene—Does the speleothem oxygen isotope record reflect monsoon rainfall variability?

The evolution of the East Asian summer monsoon(EASM) during the Holocene has long been of significant interest.Knowledge of past EASM variability not only increases our understanding of monsoon dynamics on a long timescale,but it also provides an environmental and climatic background for research into Chinese cultural development.However,the timing of the EASM maximum remains controversial.The popular concept of an "early Holocene maximum" is mainly based on speleothemδ~(18)O(δ~(18)O_c) records from caves in southern China;however,the interpretation of δ~(18)O_C as a reliable proxy for EASM intensity is being increasingly challenged.The present paper is a critical review of the climatic significance of the δ~(18)O_C record from China.Firstly,we suggest that precipitation in northern China is an appropriate index of EASM intensity,the variation of which clearly indicates a mid-Holocene monsoon maximum.Secondly,an interregional comparison demonstrates that the precipitation record in northern China is quite different from that in southern China on a range of timescales,and is inconsistent with the spatial similarity exhibited by speleothem oxygen isotope records.Furthermore,both modeling and observational data show that the δ~(18)O_C records from southern China indeed reflect changes in precipitation δ~(18)O(δ~(18)O_P) rather than precipitation amount,and therefore that their use as an EASM proxy is inappropriate.Finally,we address several significant monsoon-related issues-including the driving mechanism of the EASM on an orbital timescale,the climatic significance of speleothem oxygen isotopes,and the relationship between atmospheric circulation and precipitation in monsoonal regions.     

滆湖磷迁移过程的研究(一)——磷迁移模型的建立

通过滆湖磷的来源途径(入湖河道、湖区径流、湖面沉降、养殖技饵、底泥释放)和湖体各要素(水体、浮游植物、大型水生植物、鱼类等)中磷迁移过程调查资料的分析,建立了描述磷在上述各要素中迁移过程的数学模型.经实测资料验证,模型的计算值与实测值的平均相对误差在9.9%-18.6%.基本反映了磷的迁移过程及动态变化规律,对该湖磷浓度预测及磷资源合理利用具有重要的意义.     

卫星热红外遥感技术在火山区地热探测中的应用——以内蒙古锡林郭勒火山区为例

能源的全球性短缺以及全球环境问题的日益加剧,使得绿色新能源的研究与开发成为当今世界许多国家的一项重要任务。地热资源作为其中一员其重要性日益凸显。在地热资源的勘查中,传统的地质和地球物理勘探投入高、难度大,而遥感技术具有经济、高效、覆盖范围广等优势,已逐渐成为地热资源探测与调查的一种新技术手段。地热能开发的首选地区往往是新生代火山活动区,因其在相对较小的深度内就能获得很高的温度。本文综述了国内外利用遥感技术探测火山地热的发展历史和研究现状,介绍了这项技术在美国黄石公园、日本阿苏火山以及我国长白山火山和腾冲火山的应用。同时选取内蒙古锡林郭勒盟新生代火山活动构造区作为实例,利用美国NASA陆地卫星Landsat-7 ETM+第6波段的红外遥感数据反演了研究区的地表温度,结合ETM+7-4-1波段组合影像的地质构造解译结果以及其它相关资料对研究区地表温度分布进行了分析。结果表明,区内红外遥感地表温度异常区多位于北东东与北西向构造的交汇处或与环形构造密切相关。本文圈定了7个地表温度异常区作为这一地区下一步地热资源勘查的远景区。