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。     

袖阀管注浆在人工填土暗挖施工中的应用

阜石路分洪暗涵某暗挖段,浅涵暗挖洞身大部位于人工填土内,部分区域洞底人工填土厚度仍达2m。人工填土松散,自稳能力差,易发生塌落现象,不易成洞,施工难度大。为避免暗挖施工期间人工填土产生安全隐患并减少后期隧道变形,采用了袖阀管注浆技术对填土地层进行注浆加固,以确保工程施工安全及隧道工程质量&根据工程实施效果可见,袖阀管注浆加固对在人工填土中进行暗挖隧道开挖的沉降、变形控制的效果较好。     

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.     

现浇连续箱梁的施工工艺

滨州黄河公路大桥南引桥上部构造为单箱单室大悬臂连续现浇箱梁,跨径42m,2001年12月开工,经过17个月的艰苦施工,提前顺利竣工。对该项工程的施工经验做了总结。     

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。     

基于网络药理学探讨附子-细辛对高血压病的作用机制

目的：基于网络药理学研究附子-细辛对高血压病的作用机制。方法：运用TCMSP数据库挖掘出附子-细辛的有效成分及药物预测靶点,采用5个生物信息数据库检索出高血压病的疾病预测靶标,构建药物靶点-疾病靶标交集,使用Cytoscape生物信息分析软件绘制“成分-靶点-疾病”中药调控网络,基于STRING数据库构建“药物-疾病”相关靶点的蛋白互作网络（PPI）,并对其进行GO和KEGG的生物信息学分析。结果：通过生物利用度和类药性筛选得到附子-细辛的有效成分29个,对应药物靶点1807个,高血压病的疾病靶标8505个,构建的药物靶点-疾病靶标交集80个。与高血压病密切相关的GO富集条目91个,KEGG信号通路123条,主要涉及流体剪切应力与动脉粥样硬化、糖尿病并发症中的AGE-RAGE信号通路、白细胞介素（IL）-17信号通路、丝裂原活化蛋白激酶（MAPK）信号通路、PI3K-Akt信号通路等。结论：附子-细辛药对与高血压病密切相关,能够通过一条或多条通路协同发挥药效作用,考虑其可能是通过干预血液的流体剪切应力影响动脉粥样硬化与心血管重塑再生而实现的。     

基于网络药理学和分子对接探讨左金丸治疗肝癌的作用机制

目的：运用网络药理学和分子对接方法探讨左金丸治疗肝癌的作用机制。方法：从TCMSP和BATMAN-TCM数据库获取左金丸的化合物及其相应靶点,检索GeneCards、OMIM和TTD 3个数据库获得肝癌的相关靶基因,取两者靶基因交集得到左金丸治疗肝癌的预测靶基因;运用Cytoscape 3.7.1软件构建左金丸-化合物-靶点-肝癌和PPI网络图;运用R软件对预测靶基因进行GO和KEGG富集分析;最后运用分子对接技术对关键化合物和靶点进行验证。结果：共获取左金丸35个化合物及173个相应靶点,左金丸与肝癌的共同靶点有103个。PPI结果表明AKT1、MAPK1、TP53、JUN和RELA可能为左金丸治疗肝癌的关键靶点。富集分析示左金丸可能通过乙型肝炎、卡波西肉瘤相关疱疹病毒感染、人巨细胞病毒感染、丙型肝炎、MAPK信号通路、肝癌等信号通路抗肝癌。分子对接结果示槲皮素和黄连素均能与AKT1和MAPK1稳定结合。结论：本研究初步揭示了左金丸通过多成分、多靶点、多通路治疗肝癌的作用机制,为后续左金丸治疗肝癌提供理论参考。     

The information system of the French Peatland Observation Service: Service National d'Observation Tourbières – A valuable tool to assess the impact of global changes on the hydrology and biogeochemistry of temperate peatlands through long term monitoring

Mitigating and adapting to global changes requires a better understanding of the response of the Biosphere to these environmental variations. Human disturbances and their effects act in the long term (decades to centuries) and consequently, a similar time frame is needed to fully understand the hydrological and biogeochemical functioning of a natural system. To this end, the ‘Centre National de la Recherche Scientifique’ (CNRS) promotes and certifies long-term monitoring tools called national observation services or ‘Service National d'Observation’ (SNO) in a large range of hydrological and biogeochemical systems (e.g., cryosphere, catchments, aquifers). The SNO investigating peatlands, the SNO ‘Tourbières’, was certified in 2011 ( https://www.sno-tourbieres.cnrs.fr/ ). Peatlands are mostly found in the high latitudes of the northern hemisphere and French peatlands are located in the southern part of this area. Thus, they are located in environmental conditions that will occur in northern peatlands in coming decades or centuries and can be considered as sentinels. The SNO Tourbières is composed of four peatlands: La Guette (lowland central France), Landemarais (lowland oceanic western France), Frasne (upland continental eastern France) and Bernadouze (upland southern France). Thirty target variables are monitored to study the hydrological and biogeochemical functioning of the sites. They are grouped into four datasets: hydrology, fluvial export of organic matter, greenhouse gas fluxes and meteorology/soil physics. The data from all sites follow a common processing chain from the sensors to the public repository. The raw data are stored on an FTP server. After operator or automatic processing, data are stored in a database, from which a web application extracts the data to make them available ( https://data-snot.cnrs.fr/data-access/ ). Each year at least, an archive of each dataset is stored in Zenodo, with a digital object identifier (DOI) attribution ( https://zenodo.org/communities/sno_tourbieres_data/ ).