The Hα-cyclonic spectra of a flare loop system on 1981 April 27

The data such as the H-spectrum-spectroheliographic (SSHG) observations, the H-chromospheric observations, etc., of a flare loop prominence which occurred on the western solar limb on 1981 April 27 have been obtained at Yunnan Observatory. The distribution of the internal motions and the macroscopical motion of the flare loop prominence with time and space in the course of its eruption and ascension is derived from the comprehensive analysis of the data. The possible physical pictures and the instability of the motions of the loop are inferred and discussed.     

添加维生素B_（12）生产菌高密度培养褶皱臂尾轮虫的效果

阐述把维生素Ｂ１２生产菌添加到培养水中培养褶皱臂尾轮虫ＢｒａｃｈｉｏｎｕｓＰｌｉｃａｔｉｌｉｓ的买验。共１８株细菌分离于轮虫培养池，其中，有一株产维生素Ｂ１２的假单胞杆菌ＴＰ４对轮虫的生长繁殖有明显的促进作用。把ＴＰ４菌株培养后，加入到２Ｌ的烧杯和５００Ｌ的水槽中培养泰国Ｓ型轮虫时．在９ｄ（天）和６ｄ（天）中，轮虫密度从１２４～１３９和２４２～２８８个体／ｍｌ增殖到４，４１７～５，５４０和１，０１７～１，２５４个体／ｍｌ，分别比对照组增加了４～６及２～３倍。     

黑鲷早期鳞被的形成

黑鲷Sparus macrocephalus(Basilewsky)幼苗鳞被最早出现的部位是在躯干部胸鳍基后至肛门直上方的侧线处。黑鲷只具一个鳞被起始中心。最早出现鳞片的个体为体长9.5—14.1mm,平均11.51±0.85mm,全长11.2—16.5mm,平均13.65±1.01mm,孵后日龄23—35d。鳞被发育完全时的最小个体为体长12.1—18.5mm,平均14.57±1.55mm,全长14.8—23.5mm,平均17.99±2.17mm,孵后日龄27—42d。     

鄂尔多斯盆地的三维可视化及其应用

地形三维可视化作为测绘行业的一项新技术正处于蓬勃发展阶段。本文以鄂尔多斯盆地为例，着重介绍了基于ARCGIS9．0的三维可视化建库、实现过程，并指出其在矿产勘探中的具体应用。     

山西北部至晋冀蒙交界地区几次中强地震前4.0级地震活动的研究

对山西北部至晋冀蒙交界地区中强地震前的 4 .0级地震进行了研究 ,得出其特征为异常增强—异常平静—信号地震的结论 ,认为该区某些 4 .0级地震活动似可作为某些中强地震的前兆地震而进行进一步的研究。     

浅谈环境地质与环境保护

环境问题已成为全世界共同关心的问题。地质环境是影响人类生存的重要因素。本文述及了因自然地质因素引起的地震灾害、火山灾害、滑坡灾害等，以及因人为地质因素引发的水污染灾害、水库失事灾害、水土流失、沙漠扩大灾害等诸方面内容，指出在今后应重视对地质灾害的监测和预防。     

Estimation of Site Effects in Beijing City

— For the realistic modeling of the seismic ground motion in lateral heterogeneous anelastic media, the database of 3-D geophysical structures for Beijing City has been built up to model the seismic ground motion in the City, caused by the 1976 Tangshan and the 1998 Zhangbei earthquakes. The hybrid method, which combines the modal summation and the finite-difference algorithms, is used in the simulation. The modeling of the seismic ground motion, for both the Tangshan and the Zhangbei earthquakes, shows that the thick Quaternary sedimentary cover amplifies the peak values and increases the duration of the seismic ground motion in the northwestern part of the City. Therefore the thickness of the Quaternary sediments in Beijing City is the key factor controling the local ground effects. Four zones are defined on the base of the different thickness of the Quaternary sediments. The response spectra for each zone are computed, indicating that peak spectral values as high as 0.1 g are compatible with past seismicity and can be well exceeded if an event similar to the 1697 Sanhe-Pinggu occurs.     

“Three-Component” Digital Prospecting Method：A New Approach for Mineral Resources Quantitative Prediction and Assessment

“Three-component” method consists of three clase-connected aspects: geological anomaly,diversity of mineralization and mineral deposit spectrum. All these three concepts are not new separately, but it is a new approach to combine these three aspects in one single concept for quantitative mineral resources prediction and assessment and it is also the first time to conduct a more detailed study in each aspect. Investigation and clarification of geological anomalies, diversity of mineralization and spectrum of mineral deposits are realized by digitization and quantification of ore forming controlling factors, oreexisting symbols or marks, characteristics of mineralization and regulation of ore-genesis and laws of distribution. These procedures lead to construction of a “digital model“ for mineral resources prediction andassessment.     

基于RS和GIS的农业土地利用污染分析

农业已被确认为地表和地下水最主要的非点源污染源，而土地利用方式又是影响非点源污染的关键性因素。大规模的土地利用与开发、化肥与农药用量的增加、规模养殖业的发展、生活垃圾的增加等，这些非点污染源严重威胁水体质量，进而影响到人们的生活。为了更好地预测和控制、管理非点源污染，必须研究其负荷定量化问题。本文从以上几方面入手，讨论了非点源污染与农业土地利用方式之间的关系，利用组件GIS技术，以网格为评价单元，实现非点源污染负荷的定量计算及可视化分析。文章最后以上海市松江区作为研究区域，对该区的污染情况进行了分析。     

可解释性长短期记忆模型用于预测湖泊总磷浓度变化

对湖泊总磷的变化预测和来源识别对水资源调度和流域生态治理有着重要的意义,然而复杂的生化反应和水动力条件导致的非平稳性给湖泊总磷浓度的准确预测带来极大的困难。为克服这一挑战,本文引入了基于加权回归的季节趋势分解(seasonal and trend decomposition using Loess,STL)技术和夏普利加法(SHapley additive exPlanations,SHAP)结合长短期记忆网络(long short-term memory neural network,LSTM)和门控循环单元(gated recurrent unit,GRU)构建了一个可解释的预测框架,以增强对湖泊总磷浓度演变的预测并提高其可解释性。研究表明:(1)在骆马湖总磷浓度的预测中,该框架拥有较好的预报精度(R²=0.878),优于LSTM和卷积长短期记忆模型(convolutional neural networks and long short term memory network,CNN-LSTM)。当预测时间步长增加到8 h时,该框架有效提高了总磷浓度的预测精度,平均相对误差和均方根误差分别降低了47.1%和33.3%。从预测趋势来看,骆马湖在汛期的总磷平均浓度为0.158 mg/L,相较于非汛期的平均浓度,增加了202.1%。(2)运河来水是骆马湖总磷浓度最重要的影响因素,贡献权重为60.0%,并且不同断面(三湾、三场)的污染源受水动力、气象等因素的影响存在显著的时空差异。本文凸显了神经网络模型在预警水体污染方面的可实施性,并且为提高传统神经网络的学习能力和可解释性的开发与验证提供了重要方向。