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。     

基于GIS的TM数据分类及辅助制图研究

本文初步研究了遥感、GIS和制图一体化实用技术方法。对黄土丘陵区和沙漠地区TM数据进行了特征信息分析;给出了分层分类和GIS辅助分类结果;经模糊推理和人机交互修改,将提“纯”的遥感专题数据作为GIS的动态信息源,对GIS进行扩充与更新;最后在GIS支持下分层提取专题图并进行辅助制图。     

FS方法及其在综合多项震兆中的应用

本文提出了一种模式识别方法--FS方法.该方法的特征取为某些论域上的模糊子集.先以每三个原始特征组成子分类器的特征集,“训练”这些分类器,然后对子分类器进行筛选,最后用筛选出的子分类器的“软”分类结果的加权平均作为判别函数,形成总的分类决策.将FS方法应用于综合多项震兆,并进行了一系列控制试验,还与地震学中几种常用的方法进行了对比试验.结果表明,FS方法是稳定和有效的.     

Estimation of runoff distribution within river systems: Application to the Lena Basin (Siberia)

A channel account approach is proposed to estimate longitudinal changes in runoff along large river systems. This new method provides a quantitative basis for describing the fluvial transport of suspended particulate material and dissolved substances. This method includes an evaluation of basic elements of water balance in separate sections of the river network and subsequent correction of channel accounting equations for the entire system using a maximum likelihood principle. To calculate water discharges of tributaries that have no hydrological information, structural analysis of river network is performed. This approach provides less error in comparison with traditional methods of estimating lateral inflow. The method is used to trace water discharge with increasing distance along the Lena river basin and to evaluate the contribution of geologically and lithologically uneven sub-basins in water discharge formation during a summer low water period.     

Modèles géostatistiques de concentrations ou de débits le long des cours d'eau

Estimating concentrations or flow rates along a stream network requires specific models. Two classes of models, recently proposed in the literature, are generalized, to the intrinsic case in particular. We present a global construction by ‘streams’, i.e. on the whole set of paths between sources and outlet. Combining stationary or intrinsic one-dimensional random functions leads to stationary or intrinsic models on segments, with discontinuities at the forks. A construction from outlet to sources, leads to stationary or intrinsic models on each stream, without any discontinuity at the forks. The linear variogram is found as a particular case. The extension to the linear model of coregionalization is immediate, allowing a multivariate modelling of concentrations. To cite this article: C. de Fouquet, C. Bernard-Michel, C. R. Geoscience 338 (2006).     

基于GIS的山地林道网优化配置系统

应用系统选择永安元沙国有林业采育场的部分林班为示范,建立森林资源空间数据库.以ARC/INFO为开发平台,以山地林道网理论为指导,应用G IS技术、DBMS技术与数学规划集成技术,使用AML语言进行二次开发设计山地林道网优化配置系统,实现计算机辅助林道网配置,提高决策的科学性。     

Fuzzy expert system for economic zonation of an ornamental slate deposit

Investigation of deposits for traditional extraction activities (metals and coal) has generally been based on determining grade, or content, of the required material. In order to apply the grade concept to an ornamental rock such as slate, it is first necessary to define the variables that determine both the geotechnical recovery rate for the rock mass — which conditions the size of the extracted blocks – and the aesthetic features of the slate — which define the quality of the slabs as potential roofing material.

For this research, geotechnical and aesthetic data for a slate deposit were collected from 16 continuous core borehole samples. A fuzzy expert system was then developed using this data, defining the rock mass recovery rate and slab quality in accordance with the criteria of a slate expert, producing as a final output a zonation of the deposit in terms of top quality slate, medium quality slate or waste.

A mathematical model based on fuzzy logic was chosen due to the fact that the boundaries between different quality groups in a deposit are not clearly distinguished. Moreover, quality also depends on a company's infrastructures for transformation of the blocks, and also on its commercial strategies.     

Application of back-propagation networks in debris flow prediction

Debris flows have caused serious loss of human lives and a lot of damage to properties in Taiwan over the past decades. Moreover, debris flows have brought massive mud causing water pollution in reservoirs and resulted in water shortage for daily life locally and affected agricultural irrigation and industrial usages seriously. A number of methods for prediction of debris flows have been studied. However, the successful prediction ratio of debris flows cannot always maintain a stable and reliable level. The objective of this study is to present a stable and reliable analytical model for occurrence predictions of debris flows. This study proposes an Artificial Neural Networks (ANN) model that was constructed by seven significant factors using back-propagation (BP) algorithm. These seven factors include (1) length of creek, (2) average slope, (3) effective watershed area, (4) shape coefficient, (5) median size of soil grain, (6) effective cumulative rainfall, and (7) effective rainfall intensity. A total of 178 potential cases of debris flows collected in eastern Taiwan were fed into the ANN model for training and testing. The average ratio of successful prediction reaching 93.82% demonstrates that the presented ANN model with seven significant factors can provide a stable and reliable result for the prediction of debris flows in hazard mitigation and guarding systems.     

Modeling the cyclic swelling pressure of mudrock using artificial neural networks

The stochastic nature of the cyclic swelling behavior of mudrock and its dependence on a large number of interdependent parameters was modeled using Time Delay Neural Networks (TDNNs). This method has facilitated predicting cyclic swelling pressure with an acceptable level of accuracy where developing a general mathematical model is almost impossible. A number of total pressure cells between shotcrete and concrete walls of the powerhouse cavern at Masjed–Soleiman Hydroelectric Powerhouse Project, South of Iran, where mudrock outcrops, confirmed a cyclic swelling pressure on the lining since 1999. In several locations, small cracks are generated which has raised doubts about long term stability of the powerhouse structure. This necessitated a study for predicting future swelling pressure. Considering the complexity of the interdependent parameters in this problem, TDNNs proved to be a powerful tool. The results of this modeling are presented in this paper.     

Statistical analysis for the hydrogeological evaluation of the fracture networks in hard rocks

The hydrogeological effectiveness of fracture sets is determined and evaluated by the fuzzy c-mean and hierarchical clustering. These cluster analyses combine the geological spatial attributes and the hydraulic relevant attributes of fractures. Based on the results of the clustering the fracture set volumes are estimated.