Artificial neural network and liquefaction susceptibility assessment: a case study using the 2001 Bhuj earthquake data,Gujarat, India

This study pertains to prediction of liquefaction susceptibility of unconsolidated sediments using artificial neural network (ANN) as a prediction model. The backpropagation neural network was trained, tested, and validated with 23 datasets comprising parameters such as cyclic resistance ratio (CRR), cyclic stress ratio (CSR), liquefaction severity index (LSI), and liquefaction sensitivity index (LSeI). The network was also trained to predict the CRR values from LSI, LSeI, and CSR values. The predicted results were comparable with the field data on CRR and liquefaction severity. Thus, this study indicates the potentiality of the ANN technique in mapping the liquefaction susceptibility of the area.     

基于网络药理学与分子对接技术探讨青蛇方外用治疗湿疹的作用机制

目的：基于网络药理学与分子对接技术探讨青蛇方外用治疗湿疹的作用机制。方法：应用TCMSP和UniProt数据库平台查询青蛇方组方的有效活性成分及靶基因,与疾病靶基因取交集后构建蛋白质-蛋白质相互作用(PPI)网络;应用DAVID数据库,对潜在核心作用靶点基因进行基因本体（GO）功能、京都基因与基因组百科全书（KEGG）通路富集分析。利用分子对接原理论证青蛇方生物活性成分与核心靶点的分子结合能力。结果：筛选出青蛇方有效成分63种,作用靶点99个;主要有β-谷甾醇、2,4,7-三羟基-9,10-二氢菲、靛蓝素、豆甾醇、色氨酸等关键成分;转录因子AP-1（JUN）、肿瘤坏死因子（TNF）、原癌基因（RELA）、干扰素γ（IFNG）、转化生长因子-β1（TGF-β1）等核心基因。关键信号通路有癌症信号通路、恰加斯病通路、弓形体病通路、脂质和动脉粥样硬化通路等,分子对接结果显示活性成分与核心靶点基因结合能力较强。结论：青蛇方外用可以通过多种活性成分、多种通路有效抑制免疫炎症反应,促进免疫系统正常运行,从而达到治疗湿疹的目的。     

对江西农经网如何更好地提供信息服务的探讨

分析了江西农村经济信息网(www.jxagriec.gov.cn)的现状,指出农经网信息服务正面临着挑战,并在此基础上阐述了农经网信息服务的发展思路。     

Fuzzy neural network models for liquefaction prediction

Integrated fuzzy neural network models are developed for the assessment of liquefaction potential of a site. The models are trained with large databases of liquefaction case histories. A two-stage training algorithm is used to develop a fuzzy neural network model. In the preliminary training stage, the training case histories are used to determine initial network parameters. In the final training stage, the training case histories are processed one by one to develop membership functions for the network parameters. During the testing phase, input variables are described in linguistic terms such as ‘high’ and ‘low’. The prediction is made in terms of a liquefaction index representing the degree of liquefaction described in fuzzy terms such as ‘highly likely’, ‘likely’, or ‘unlikely’. The results from the model are compared with actual field observations and misclassified cases are identified. The models are found to have good predictive ability and are expected to be very useful for a preliminary evaluation of liquefaction potential of a site for which the input parameters are not well defined.     

台湾西南部泥岩土地利用型态与环境劣化趋势之分析

台湾泥岩恶地因其特殊之土壤理化性质及区域微气候的相互恶性循环，衍生生态环境等问题。在以往之35年，裸化面积从1967年的2532hm^2，至2001年11月已扩大为15539hm^2。其表土大量流失、崩塌、河川含砂量激增、植被退化与微气候变异等破坏，更显示泥岩之环境劣化问题。以SPOT卫星影像判识泥岩裸露面积，探讨不同时期之地景变异，并应用地景生态理论量化泥岩地表不同土地利用之空间结构变化，分析地景结构变迁之生态内涵与生态指标意义。因子分析结果其主要变异为多样性因子与形状破碎型因子所影响，而应用马可夫链模式计算出不同时期之土地利用变迁内涵，此结果搭配指标分析可解释泥岩裸露面积与竹林面积皆持续扩大，乃由人为土地利用之活动及植被变迁所引起。     

衡阳市生态环境现状及其改善对策

资源的不合理开发利用导致衡阳生态环境严重恶化。加强生态环境保护与建设对衡阳乃至湖南的可持续发展具有重要的意义。在分析衡阳市资源开发存在问题及其主要原因的基础上j探讨了在资源开发中建立可持续发展的良性生态环境的途径和措施，指出了要发展生态产业、开展生态环境的保护和建设，必须大力实施生态农业、生态林业、生态能源、生态旅游等生态经济工程，从而为衡阳市经济建设莫定坚实的生态可持续发展基础。     

成都市农业区划与城市生态环境保护构想

扼要介绍了成都市区域土壤多目标地球化学调查的新近展，从地球化学和农业生态的角度论述了成都市农业区划发展构想，并探讨人工生态系统与城市生态环保建设的模式与构想建议。     

Application of visual,statistical and artificial neural network methods in the differentiation of water from the exploited aquifers in Kuwait

The ability of artificial neural network to differentiate water samples from the two aquifers of Kuwait on the basis of their major ion chemistry has been demonstrated. The major ion concentration distribution in the groundwater of the Kuwait Group and the Dammam Formation aquifers of Kuwait appears very similar. Cross-plots, supported by the discriminant function analysis of the data, however, suggest that there are some subtle differences in the overall composition of the water from the two aquifers that make it possible to differentiate the water from the two aquifers in almost 80% of the cases. An artificial neural network improved the differentiation capability to 90% of the cases. It is also possible to estimate the fraction of Kuwait Group water in the flow stream of dually completed wells with the help of an artificial neural network developed for this purpose. Electronic Publication