基于雷达回波最大重叠率的一种临近降水预报方法

基于天气雷达的临近降水预报是雷达短时预报业务系统的重要组成部分,本文在回顾雷达临近降水预报技术发展的基础上,充分考虑新一代天气雷达高时间、空间分辨率的优点,提出两个相邻时刻雷达回波具有最大重叠率的移向、移速是与降水系统整体的移向、移速密切相关的论点,再用此移向、移速对当前雷达回波进行平移,最后采用九点平均的回波生消模型...     

基于范数灰色理论的滑坡稳定性敏感因子分析

灰色关联分析模型可用于滑坡稳定性敏感因子的定量分析。将范数灰色理论引入到滑坡稳定性敏感因子分析之中,确定了影响滑坡稳定性系数的因素权重,较为直观地反映了各影响因子对滑坡稳定性的影响程度。以重庆市綦江县土台镇滑坡为例,进行滑坡稳定性敏感因子的范数灰关联度计算。结果显示,滑动面岩土体强度参数是影响土台镇滑坡稳定性最重要的因素,地震作用和地下水位的变化对该滑体稳定性的影响要稍弱一些。     

基于精确权函数的仪器响应失真校正方法与算例

当前,经仪器响应失真校正后,加速度计有效观测频带通常为0至1倍自振频率,这限制了强震仪应用领域的延拓。有鉴于此,本文提出一个基于精确权函数的仪器响应失真校正方法并给出一个验证算例。分析表明:较之现有方法,新方法兼有高精度和高效率的优点,并可以将力平衡式加速度计的有效观测频带至少延拓3倍,对于拓展强震仪的应用领域具有重要意义。     

Multi-step ahead short-term predictions of storm surge level using CNN and LSTM network

Storm surges pose significant danger and havoc to the coastal residents' safety, property, and lives, particularly at offshore locations with shallow water levels. Predictions of storm surges with hours of warning time are important for evacuation measures in low-lying regions and coastal management plans. In addition to experienced predictions and numerical models, artificial intelligence (AI) techniques are also being used widely for short-term storm surge prediction owing to their merits in good level of prediction accuracy and rapid computations. Convolutional neural network (CNN) and long short-term memory (LSTM) are two of the most important models among AI techniques. However, they have been scarcely utilised for surge level (SL) forecasting, and combinations of the two models are even rarer. This study applied CNN and LSTM both individually and in combination towards multi-step ahead short-term storm surge level prediction using observed SL and wind information. The architectures of the CNN, LSTM, and two sequential techniques of combining the models (LSTM–CNN and CNN–LSTM) were constructed via a trial-and-error approach and knowledge obtained from previous studies. As a case study, 11 a of hourly observed SL and wind data of the Xiuying Station, Hainan Province, China, were organised as inputs for training to verify the feasibility and superiority of the proposed models. The results show that CNN and LSTM had evident advantages over support vector regression (SVR) and multilayer perceptron (MLP), and the combined models outperformed the individual models (CNN and LSTM), mostly by 4％–6％. However, on comparing the model computed predictions during two severe typhoons that resulted in extreme storm surges, the accuracy was found to improve by over 10％ at all forecasting steps.     

非常规综合物化探油气预测研究

非常规综合物化探方法油气预测研究中存在的主要问题为：缺乏系统与综合的基础性理论研究，异常形成的机理还不十分清楚，在参数的优化组合及异常的求取上尚有诸多不足。针对后一种情况，选择松辽盆地东岭构造作为实验区进行了有益的探索。选取低能吸附烃、放射性测氡及土壤热释光三类参数进行了优化组合，分别计算了综合指标MAE与MAC及组合熵，然后对各值采用泛克里格法求取异常，取得了良好的效果。下一步研究应从异常形成的机理入手，建立三维非常规综合物化探油气预测模式，以提高油气预测成功率。     

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LMWOA (low molecular weight organic acid) exudation by salt marsh plants: Natural variation and response to Cu contamination

This work aimed to evaluate, in vitro, the capability of roots of two salt marsh plants to release low molecular weight organic acids (LMWOAs) and to ascertain whether Cu contamination would stimulate or not organic acids exudation. The sea rush Juncus maritimus and the sea-club rush Scirpus maritimus, both from the lower Douro river estuary (NW Portugal), were used. Plants were collected seasonally, four times a year in 2004, during low tide. After sampling, plant roots were washed for removal of adherent particles and immersed for 2 h in a solution that matched salinity (3) and pH (7.5) of the pore water from the same location to obtain plant exudates. In one of the seasons, similar experiments were carried out but spiking the solution with different amounts of Cu in order to embrace the range between 0 and 1600 nM. In the final solutions as well as in sediment pore water LMWOAs were determined by high performance liquid chromatography. Plants were able to release, in a short period of time, relatively high amounts of LMWOAs (oxalate, citrate, malate, malonate, and succinate). In the sediment pore water oxalate, succinate and acetate were also detected. Therefore, plant roots probably contributed to the presence of some of these organic compounds in pore water. Exudation differed between the plant species and also showed some seasonally variation, particularly for S. maritimus. The release of oxalate by J. maritimus increased with Cu increase in the media. However, exudation of the other LMWOAs did not seem to be stimulated by Cu contamination in the media. This fact is compatible with the existence of alternative internal mechanisms for Cu detoxification, as denoted by the fact that in media contaminated with Cu both plant species accumulated relatively high amounts (29–83%) of the initially dissolved Cu. This study expands our knowledge on the contribution of globally dominant salt marsh plants to the release of LMWOAs into the environment.     

基于Moran统计量的空间自相关理论发展和方法改进

本文旨在发展基于Moran指数的空间自相关分析理论和方法。首先,利用线性代数知识对基于Moran统计量的空间自相关过程的数学表示进行规范化整理;其次,基于变换中的不变性思想给出Moran指数的理论解释;第三,对空间权重矩阵的数理性质、建设方法和应用范围提出新的见解。总结并发展了Moran指数的三种计算方法——三步求值法、矩阵标度法和回归分析法,将空间权重矩阵划分为四种基本类型——局域关联型、准局域关联型、准长程关联型和长程关联型。以河南省鹤壁市乡镇体系为实证对象,以本文改进的理论和方法为依据,提供了一个空间自相关分析的简明案例。     

斑纹鲟凝集素(CFL)的初步研究Ⅱ.CFL的分子组成及性质鉴定

采用生化方法对斑纹鲟(Charybdis feriatus)凝集素进行了初步研究.结果表明,斑纹鲟的血清中有动物红细胞和微生物细胞凝集活性的凝集素(Charybdis feriatuslectin,CFL),其活力表现依赖于Ca2+,并为多种糖所抑制;CFL对40℃以上的温度敏感,其活力在pH6.0~8.0内稳定.经巯基乙醇处理和未经巯基乙醇处理的CFL在SDS-PAGE上均为一条蛋白带,说明斑纹鲟凝集素不含二硫键,且只有一种亚基,分子量为40.8 kDa,CFL氨基酸组成分析表明其富含酸性氨基酸.     

巧用SURFER绘制二维、三维物化探实用图件

介绍了使用比较普遍的ＳＵＲＦＥＲ 软件的潜在功能及使用技巧。通过功能组合和巧取绘图参数等方法, 能绘制出一些别致的物化探实用图件, 较好地满足多种行业对图件的一些特殊要求。