临潼-蒲城数字微波时间传输系统建设及初步结果

中国科学院国家授时中心的临潼--蒲城微波时间传输系统承担着守时基准钟房(临潼)与发播控制钟房(蒲城)之间的时间同步比对任务.截至2006年底,该系统已经连续工作了28年,由于设备老化等原因,系统的可靠性和性能指标严重下降.概括介绍了微波时间传输系统的技术改造方案和数字微波系统实现的功能,初步结果表明改造后的微波时间传输系统的性能得到了提高.     

公共电话交换网时间认证系统的研制

研制了一种通过公共电话交换网进行时间认证的系统设备,利用电话网为数字时间戳服务机构提供标准时间服务.经实测,时间同步精度可以在±0.3 ms范围内,能满足数字时间戳服务机构为银行、证券、股票和期货交易等电子商务以及电子政务活动提供时间认证服务方面的要求.     

论珠江三角洲河网的人为影响

文章论述了珠江三角洲河网的发育、演变过程和整治方案。由于人类活动影响,珠江三角洲河网区西、北两江下游放射状河系支汊淤断及消亡,使西、北两江正干均成为单一水道;在两江汇流区内又受绥江三角洲南展而分离开来,只留一条狭窄的小河涌(思贤)连接;由于北江正干的淤积、西江正干刷深,使古代(唐代以前)西江合北江同流向东流入番禺(广州)的形势大变,形成江水反向西流入西江,西江水不能过入广州。由此,西、北两江合成的珠江三角洲主体网河区成为浅水狭窄的小河区,以往主要干流多不复存在,生态环境日益变劣。因此,需要修复河网。关键是把西江大量优质水源(沙少、污染少)引回,过入珠江三角洲网河区,北江水源也需截流使其不再西流入西江;开通北江大堤沿途防西水的闸门(如芦苞、西南、沙口等闸),以便通水通航;在思贤建立新型分水闸,可将西、北两江正干水源恢复到良好生态环境     

基于BP神经网络的青藏高原土壤养分评价

土壤养分在养分循环和土壤-植物关系中起着重要作用,在高海拔生态系统中,由于缺乏系统的实地观测,土壤养分在高山草原中仍然知之甚少。为了了解青藏高原多年冻土区高寒草地土壤养分的基本情况以及土壤养分的等级划分,利用青藏高原腹地西大滩至安多地区采集的154个土壤样品数据,基于BP神经网络模型建立具有3层网络,10个中间层节点的土壤养分评价模型。在MATLAB软件中进行BP神经网络的训练和验证后,对青藏高原多年冻土区高寒草地土壤养分进行综合评价。结果表明：2009年青藏高原高寒草地的土壤养分综合评价等级为4级,属于较低水平。综合评价结果与基于主成分分析方法的土壤质量指数（SQI）基本一致,说明BP神经网络模型对青藏高原土壤养分的评价结果是合理的。对评价结果与海拔、植被盖度和植被类型的关系分析表明,海拔越高或植被盖度越高,土壤养分的评价等级越高;不同植被类型的评价等级表现出高寒沼泽草甸（2级）>高寒草甸（4级）>高寒草原（5级）的趋势。BP网络作为一种简单又准确的识别方法,不仅可以评估土壤养分等级,还可以比较不同地区的土壤养分高低状况,希望为青藏高原的土地资源管理与保护提供基本的科学依据。     

A New Fracability Evaluation Approach for Shale Reservoirs Based on Multivariate Analysis: A Case Study in Zhaotong Shale Gas Demonstration Zone in Sichuan,China

Fracability characterizes the effectiveness of hydraulic fracturing. The existing assessment methods cannot reflect the actual value of the effectiveness due to a lack of comprehensive consideration and neglect of the influences of engineering factors. This study aims to solve this problem by implementing geological static data and production dynamic data in multivariate analysis in Zhaotong shale gas demonstration zone. First, the reservoir quality index (RQI) was introduced to evaluate the exploration potential by integrating the geological parameters with gray relational analysis. Moreover, the differences in fracturing fluid types and proppant sizes were considered, and the operating parameters were normalized on the basis of the equivalence principle. Finally, the general reservoir fracability index (GRFI) was proposed based on a dimensioned processing of the various parameters. A case study was conducted to verify the accuracy and feasibility of this new approach. The results demonstrate that (1) the organic carbon and gas content are adjusted to contribute the most to the calculation of the RQI, while the effective porosity contributes the least; (2) the fracturing scale is the main operating parameter determining the fracability, which has the strongest correlation with the effectiveness of fracking; and (3) the GRFI has a positive correlation with shale gas production, and the lower limit of the GRFI of 2,000 corresponds to a daily production of 50,000 m3/d; this value is defined as the threshold value of a stripper well. The GRFI is consistent with the productivity trend of shale gas wells in the research block, which suggests that the new model is accurate and practical for well candidate selection.     

基于因子分析的LM-BP网络的盾构施工地表沉降预测

盾构施工引起的地表沉降量的预测与评价具有很强的随机性和不确定性,用常规的数学模型难以准确表达。本文采用因子分析法对影响盾构施工引起地表沉降的9个因素进行了主因子的提取,得到4个主因子。以此数据集对BP神经网络进行训练,并用Levenberg-Marquardt(LM)算法对BP神经网络进行了优化,建立了基于因子分析的LM-BP神经网络预测模型。结合工程实例将预测结果与LM-BP神经网络模型的预测结果进行比较分析,表明本预测模型具有较高的准确性,符合实际工程的需要。     

Discussion on establishing monitoring networks for temperature fields of shallow thermal energy in Shandong,China

In the recent decade, the construction projects related to shallow geothermal energy engineering have undergone rapid development in Shandong Province. The predominant type of these developments and applications was heat exchange through buried tubes and the main targets were residential and office buildings. However, an overwhelming majority of the completed geothermal heat pump projects lacked monitoring devices so that they were unable to comprehensively reflect the background values for the geothermal fields within the province and few researches were conducted on their influence on the geological environment. In this paper, locations for monitoring shallow geothermal energy and their validity of the monitoring point deployment were studied in view of the development and application status as well as geological background conditions of various projects located in multiple cities providing data support for analyzing the fluctuation trend and influence of large-scale shallow geothermal energy applications on the shallow geothermal and the feasibility and parameter designs of newly built systems in Shandong Province in the future.     

Height prediction of water flowing fractured zones based on BP artificial neural network

Factures caused by deformation and destruction of bedrocks over coal seams can easily lead to water flooding(inrush)in mines,a threat to safety production.Fractures with high hydraulic conductivity are good watercourses as well as passages for inrush in mines and tunnels.An accurate height prediction of water flowing fractured zones is a key issue in today's mine water prevention and control.The theory of leveraging BP artificial neural network in height prediction of water flowing fractured zones is analysed and applied in Qianjiaying Mine as an example in this paper.Per the comparison with traditional calculation results,the BP artificial neural network better reflects the geological conditions of the research mine areas and produces more objective,accurate and reasonable results,which can be applied to predict the height of water flowing fractured zones.     

基于神经网络的印度洋长鳍金枪鱼(Thunnus alalunga)时空分布与海洋环境关系研究

长鳍金枪鱼(Thunnusalalunga)是主要的经济性金枪鱼鱼种之一,其空间分布与环境因子存在着密切联系。利用2012—2019年印度洋长鳍金枪鱼生产数据和海洋环境数据,包括海表面温度(sea surface temperature, SST)、叶绿素浓度(chlorophyll a, chl a)和海表面盐度(sea surface salinity, SSS)构建印度洋长鳍金枪鱼时空分布神经网络模型。以空间(经度,纬度)、环境因子(SST, chl a, SSS)为解释变量,局部渔获量为因变量,变化隐含层节点数,构建了18个BP空间分布模型,并采用10×10交叉验证模型稳定性,以均方误差(meansquareerror,MSE)、平均相对方差(averagerelativevariance,ARV)以及拟合优度(R~2)作为不同模型精度与稳定性的评判标准,最终选取5-18-1(隐含层节点18)模型为最佳模型,其平均MSE值为0.02232,平均ARV值为0.511。利用最优模型预测结果与同期实际捕捞产量进行叠加对比发现两者具有一致性。环境因子敏感性分析表明海表温度显著影响印度洋长鳍金枪鱼渔场分布,其贡献率达到0.2。印度洋长鳍金枪鱼高精度BP神经网络时空分布模型为其资源的可持续开发与动态管理提供了一种新思路。     

覆盆子-红花药对与男性不育症的治疗相关机制探讨

目的：基于网络药理学探讨覆盆子-红花药对治疗男性不育症的物质基础及作用机制。方法：用TCMSP数据库检索覆盆子、红花,收集其化学成分以及靶点信息;用GeneCards和OMIM数据库筛选男性不育症的疾病靶点;应用韦恩图筛选药物与疾病的共同靶点;应用R软件进行GO富集分析及KEGG分析;应用 Cytoscape 3.7.2 软件构建药物-活性成分-疾病-靶点互作网络。结果：从覆盆子、红花得到了22个活性成分及202个药物靶点。在药物-活性成分-疾病-靶点互作网络中,degree值较高的为槲皮素及木犀草素,表明覆盆子-红花药对治疗男性不育症的主要活性成分可能为槲皮素、木犀草素等。覆盆子-红花药对治疗男性不育症的可能靶点有131个,其中核心靶点为ALB、AKT1、IL-6、VEGFA、JUN等,这些靶点主要与氧化及抗氧化生物等生物学过程相关。覆盆子-红花药对的靶点主要通过P13K/Akt信号通道治疗男性不育症。结论：覆盆子-红花药对通过多靶点、多途径治疗男性不育症。本研究为开展覆盆子-红花药对治疗男性不育症的实验提供了理论基础,为男性不育症的治疗提供了更多的思路。