An artificial neural network-based response surface method for reliability analyses of <Emphasis Type="Italic">c</Emphasis>-φ slopes with spatially variable soil

This paper presents an artificial neural network (ANN)-based response surface method that can be used to predict the failure probability of c-φ slopes with spatially variable soil. In this method, the Latin hypercube sampling technique is adopted to generate input datasets for establishing an ANN model; the random finite element method is then utilized to calculate the corresponding output datasets considering the spatial variability of soil properties; and finally, an ANN model is trained to construct the response surface of failure probability and obtain an approximate function that incorporates the relevant variables. The results of the illustrated example indicate that the proposed method provides credible and accurate estimations of failure probability. As a result, the obtained approximate function can be used as an alternative to the specific analysis process in c-φ slope reliability analyses.     

The characteristics of rill development and their effects on runoff and sediment yield under different slope gradients

Rill formation is the predominant erosion process in slope land in the Loess Plateau, China. This study was conducted to investigate rill erosion characteristics and their effects on runoff and sediment yielding processes under different slope gradients at a rate of 10°, 15°, 20° and 25° with rainfall intensity of 1.5 mm min-1 in a laboratory setting. Results revealed that mean rill depth and rill density has a positive interrelation to the slope gradient. To the contrary, width-depth ratio and distance of the longest rill to the top of the slope negatively related to slope gradient. All these suggested that increasing slope steepness could enhance rill headward erosion, vertical erosion and the fragmentation of the slope surface. Furthermore,total erosion tended to approach a stable maximum value with increasing slope, which implied that there is probably a threshold slope gradient where soil erosion begins to weaken. At the same time, the correlation analysis showed that there was a close connection between slope gradient and the variousindices of soil erosion: the correlation coefficients of slope gradient with maximal rill depth, number of rills and the distance of the longest rill from the top of the slope were 0.98, 0.97 and-0.98, respectively,indicating that slope gradient is the major factor of affecting the development of rills. Furthermore,runoff was not sensitive to slope gradient and rill formation in this study. Sediment concentration,however, is positively related to slope gradient and rill formation, the sediment concentrations increased rapidly after rill initiation, especially. These results may be essential for soil loss prediction.     

Effect of bioactive peptides (BPs) on the development of Pacific white shrimp (<Emphasis Type="Italic">Litopenaeus vannamei</Emphasis> Boone, 1931)

The present study was conducted to evaluate the feasibility of replacing fish meal (FM) with bioactive peptides (BPs) in diet of white shrimp (Litopenaeus vannamei). The changes in growth performance, body composition, non-specific immunity, and water quality were examined after the shrimp were fed four diets, in which 0% (control), 33.3%, 66.7% and 100% of FM was replaced by BPs, respectively. The groups were designated as Con, 1/3BPs, 2/3BPs, and 3/3BPs. A total of 720 shrimp with an initial body weight of 1.46 ± 0.78 g were fed the experimental diets for 56 days. The results revealed that: 1) the weight gain rate (WGR) in 1/3BPs, 2/3BPs, and 3/3BPs was significantly higher than that in Con (P < 0.05), while no significant difference was found on survival rate and feed conversion ratio (FCR); 2) the whole-body crude protein (CP) and crude lipids (CL) were significantly different among groups, while there was no significant difference between crude ash and phosphorus contents; 3) the levels of acid phosphatase (ACP), lysozyme (LZM), superoxide dismutase (SOD), phenol oxidase (PO) and bactericidal activity increased significantly with the inclusion of BPs; 4) in terms of water quality, no significant difference was found in pH and dissolved oxygen among diets during the whole experimental period. Moreover, even though nitrite and ammonium levels tended to increase with time, there was no significant difference among groups. The results indicated that BPs is an applicable alternative of protein source, which can substitute FM in the diets of L. vannamei; it is able to effectively promote growth performance and improve immunity. Moreover, BPs in the diets had no negative impact on water quality.     

东昆仑东段巴隆地区朝火鹿陶勒盖花岗闪长岩体锆石U-Pb年龄、地球化学及其地质意义

东昆仑造山带晚古生代—早中生代由于布青山-阿尼玛卿洋的俯冲发育有大量岛弧型花岗岩类。选取东昆北巴隆地区朝火鹿陶勒盖花岗闪长岩体寄主岩和闪长质暗色微粒包体进行了岩相学、LA-ICP-MS锆石U-Pb年代学及地球化学研究。结果表明,岩体寄主岩的结晶年龄为242.3±1.3Ma,暗色微粒包体结晶年龄为241.2±0.8Ma,显示其形成于中三叠世;寄主岩和暗色微粒包体A/CNK值介于0.86~1.06之间,为准铝质-弱过铝质;稀土元素总量分别为119×10~(-6)~170×10~(-6)、189×10~(-6),稀土元素配分模式显示右倾型,具有负Eu异常;岩石富集Rb、Ba、Th等大离子亲石元素,亏损Nb、Ta、Ti等高场强元素,具有弧岩浆岩特征。野外及岩相学特征均显示包体为基性岩浆进入酸性岩浆快速冷凝形成的,为俯冲板片断离导致幔源岩浆上侵形成的岩浆混合作用的产物,是布青山-阿尼玛卿洋俯冲晚期的岩浆记录。     

四川西昌盆地白垩纪恐龙足迹群的新发现

四川西昌盆地白垩系小坝组尚未发现骨骼化石记录,其白垩系恐龙动物群的信息全赖于足迹化石。2017年,在喜德县洛甘发现小坝组迄今最大型的恐龙足迹群。该足迹点保存了大量的兽脚类足迹。足迹保存条件较差,但具备了基本的形态学特征。总体来看,兽脚类足迹具有尺寸较小(8~13cm),中等中趾前凹(0.5~0.6)和第Ⅱ趾和第Ⅳ趾间较宽趾间角(70°~100°)的特征;少量足迹保存了跖骨垫。初步分析认为,洛甘兽脚类足迹与四川盆地夹关组的兽脚类足迹Eubrontes和Grallator形态类型相似,为两地在白垩纪中期具有类似的恐龙动物群的观点提供了新的证据。该发现对于西昌盆地的古气候、古地理和地层对比都具有重要的意义,足迹详细分类还有待进一步研究。     

Effects of Wave–Current Interaction on Salt Intrusion During a Typhoon Event in a Highly Stratified Estuary

Wave–current interaction (WCI) is important in modulating hydrodynamics and water mixing in estuaries, and thereby the transport of water-borne materials. However, the effects of WCI on salt transport and salt intrusion in estuaries during storm events have been rarely examined. In the present study, we use a coupled atmosphere–ocean–wave–sediment transport (COAWST) modeling system to investigate the effects of WCI on salt intrusion in the highly stratified Modaomen Estuary during Typhoon Hagupit (2008). The model is validated by the measured wave, water elevation, and surface salinity data, and several diagnostic model experiments are conducted. WCI increases the storm surge by 0.8 m at the peak surge (25% of the total surge height). The wave-breaking-induced momentum flux and the Stokes drift increase the magnitude of the landward flow by 0.3 m s^?1 (30% of the total landward flow). In addition, the waves increase water mixing by 2–4 times compared with that without waves. Hence, WCI significantly increases the landward advective salt transport and decreases the steady shear transport. The net effect of the WCI is a significant increase of salt import and salt intrusion during the typhoon event. However, in the aftermath of the storm, the imported salt water is rapidly flushed out by the increased river discharge, and the estuary regains its stratification within one day.     

Real-time identification of urban rainstorm waterlogging disasters based on Weibo big data

With the acceleration of urbanisation in China, preventing and reducing the economic losses and casualties caused by urban rainstorm waterlogging disasters have become a critical and difficult issue that the government is concerned about. As urban storms are sudden, clustered, continuous, and cause huge economic losses, it is difficult to conduct emergency management. Developing a more scientific method for real-time disaster identification will help prevent losses over time. Examining social media big data is a feasible method for obtaining on-site disaster data and carrying out disaster risk assessments. This paper presents a real-time identification method for urban-storm disasters using Weibo data. Taking the June 2016 heavy rainstorm in Nanjing as an example, the obtained Weibo data are divided into eight parts for the training data set and two parts for the testing data set. It then performs text pre-processing using the Jieba segmentation module for word segmentation. Then, the term frequency–inverse document frequency method is used to calculate the feature items weights and extract the features. Hashing algorithms are introduced for processing high-dimensional sparse vector matrices. Finally, the naive Bayes, support vector machine, and random forest text classification algorithms are used to train the model, and a test set sample is introduced for testing the model to select the optimal classification algorithm. The experiments showed that the naive Bayes algorithm had the highest macro-average accuracy.     

北秦岭西段早侏罗世A型花岗岩及其地质意义

本文通过岩相学、岩石地球化学、锆石U?Pb定年和Lu?Hf同位素组成分析等方法,对出露于北秦岭西段宝鸡岩体王家山一带的黑云母花岗岩和其中的包体进行了研究。结果表明,该花岗岩形成时代为187±2 Ma,属于高钾钙碱性—钾玄岩系列岩石,富集Rb、Th、U等大离子亲石元素以及Nb、Zr和Hf等高场强元素,亏损Ba、Sr和Eu,具有高的全岩锆石饱和温度(825℃~838℃),显示A型花岗岩特征,形成于造山后的板内环境,可能为秦岭岩群副变质岩与安山质岩石部分熔融的产物。暗色包体显示塑性流变特征,具有岩浆结构,发育针状磷灰石和具有复杂成分环带的更长环斑结构长石,是幔源岩浆注入酸性岩浆发生混合作用的产物,形成时代为191±2 Ma,其锆石Hf同位素组成变化范围较大,εHf(t)值介于-11.26~-2.51,主要为富集地幔部分熔融产物。综合本文及前人已有研究结果,认为~190 Ma的早侏罗世早期秦岭地区早中生代碰撞造山过程已经结束,区域开始逐渐进入板内伸展构造演化阶段。