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991.
目的:利用网络药理学-分子对接技术探索经方大黄牡丹汤治疗大肠癌的作用机制。方法:通过TCMSP、TCMID数据库获得大黄牡丹汤药物成分,通过PubChem、Swisstarget prediction数据库获得药物成分对应靶点,分析GSE113513芯片获得差异基因,随即获取大黄牡丹汤与大肠癌的共同靶点。利用R、Cytoscape、Autodock软件进行PPI、GO、KEGG、分子对接等分析。结果:获得大黄牡丹汤靶点561个,大肠癌差异基因1227个,共同靶点71个。共同靶点的通路富集分析显示主要与PPAR、p53等信号通路相关,Reactome机制分析显示大黄牡丹汤治疗大肠癌主要通过影响信号转导、免疫系统、疾病等产生作用,分子对接结果显示大肠癌核心靶点与大黄牡丹汤主要成分亲和力较好,能够有效自由结合。结论:经方大黄牡丹汤可通过多层次、多途径、多靶点发挥对大肠癌的治疗作用。 相似文献
992.
1976-2016年青藏高原地区通达性空间格局演变 总被引:1,自引:0,他引:1
青藏高原地区是地球上最独特的地理—生态—人口—交通单元,区域内交通网络的发展特征及规律是人地关系协同发展的一个重要切入点,对青藏高原地区交通网络开展研究具有重要意义。据此,分析1976-2016年青藏高原地区交通网络演化特征,并以省会、地级市、县级市和县城为节点,采用网络分析的时间距离计算模型探讨其通达性演变过程。研究表明:① 青藏高原地区交通网络复杂性、区域连通性增强,初步形成格状交通网络;② 青藏高原地区中心城市、县城之间的平均最短通达时间已极大缩短至11.89 h、18.84 h,呈自东向西逐渐增大的空间格局,时空收敛效应显著,通达性变化程度与其初始值有关;③ 中心城市为该地区的发展极,其与周围城市通达状况有极大提高,可达时间平均值下降到16.49 h;④ 中心城市和县城交通圈演变过程一致,青藏高原地区各地到最近城市、县城的通达时间不断缩小,沿重要交通干线已形成中心城市4 h、县城2 h短时交通圈连片分布格局,湟水河谷地、一江两河地区逐渐形成交通廊道,乡镇对外交通联系得到改善。 相似文献
993.
Shujun Peng Zhennan Zhang Jianye Mou Bing Zhao Zhiyuan Liu Jiading Wang 《国际地质力学数值与分析法杂志》2019,43(1):441-460
The improved element partition method (IEPM) is a newly developed fracture simulation approach. IEPM allows a fracture to run across an element without introducing extra degrees of freedom. It can also simulate any number of fractures in a prescribed mesh without remeshing. In this study, the IEPM is extended to hydraulic fracture simulation. First, the seepage and volumetric storage matrix of a cracked element are derived using virtual nodes (the intersection points of a crack with element edges). Subsequently, the fully coupled hydromechanical equation is derived for this cracked element. To eliminate the extra degrees of freedom (virtual nodal quantities), the water pressure and displacement of the virtual nodes are associated with their adjacent nodes through least squares interpolation. Finally, the fully coupled equation in terms of nodal quantities is obtained. The verification cases validate the method. By using this method, the field-scale hydraulic fracturing process is well simulated. The proposed approach is simple and efficient for field-scale hydraulic fracture simulation. 相似文献
994.
Sébastien Gogo Jean-Baptiste Paroissien Fatima Laggoun-Défarge Jean-Marc Antoine Léonard Bernard-Jannin Guillaume Bertrand Philippe Binet Stéphane Binet Guillaume Bouger Yohann Brossard Thierry Camboulive Jean-Pierre Caudal Stéphane Chevrier Geneviève Chiapiuso Benoît D'Angelo Pilar Durantez Chris Flechard André-Jean Francez Didier Galop Laure Gandois Daniel Gilbert Christophe Guimbaud Louis Hinault Adrien Jacotot Franck Le Moing Emilie Lerigoleur Gaël Le Roux Fabien Leroy Alexandre Lhosmot Qian Li Elodie Machado Da Silva Jean-Sébastien Moquet Juanita Mora-Gomez Laurent Perdereau Thomas Rosset Marie-Laure Toussaint 《水文研究》2021,35(6):e14244
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/ ). 相似文献
995.
卫星双向时间传递(Two-Way Satellite Time and Frequency Transfer, TWSTFT)是目前精度最高的时间传递方法之一,同时也是参与国际原子时计算的守时实验室之间比较原子时尺度的一种主要方法.提高TWSTFT链路的短期稳定度,降低周日效应对链路时间传递结果的影响,对优化TAI (International Atomic Time)的性能具有现实意义.提出了一种基于条件平差的TWSTFT链路性能优化方法,先依据TWSTFT链路测量噪声水平与谱分析结果建立TWSTFT链路性能优化网络(简称优化网络),再根据优化网络中各链路测量噪声分析结果设置权系数阵,建立条件平差模型.选取亚太地区的中国计量科学研究院(National Institute of Metrology, NIM)-中国科学院国家授时中心(National Time Service Center, NTSC)卫星双向时间传递链路作为待优化链路,以NTSC、NIM以及德国联邦物理技术研究所(Physikalisch-Technische Bundesanstalt,PTB)之间的TWSTFT链路组成优化网络,对优化网络的组网方法和条件平差模型进行实验验证.结果表明,平差后待优化链路短期稳定度得到了改善,同时其受周日效应的影响降低了约24.6%.使用该方法,能够有效提高待优化链路的时间传递性能. 相似文献
996.
Systematic variations in atmospheric heat exchange, surface residence time, and groundwater influx across montane stream networks commonly produce an increasing stream temperature trend with decreasing elevation. However, complex stream temperature profiles that differ from this common longitudinal trend also exist, suggesting that stream temperatures may be influenced by complex interactions among hydrologic and atmospheric processes. Lakes within stream networks form one potential source of temperature profile complexity due to the spatially variable contribution of lake-sourced water to stream flow. We investigated temperature profile complexity in a multi-season stream temperature dataset collected across a montane stream network containing many alpine lakes. This investigation was performed by making comparisons between multiple statistical models that used different combinations of stream and lake characteristics to represent specific hypotheses for the controls on stream temperature. The compared models included a set of models which used a topographically derived estimate of the hydrologic influence of lakes to separate and quantify the effects of stream elevation and lake source-water contributions to longitudinal stream temperature patterns. This source-water mixing model provided a parsimonious explanation for complex stream-network temperature patterns in the summer and autumn, and this approach may be further applicable to other systems where stream temperatures are influenced by multiple water sources. Simpler models that discounted lake effects were more optimal during the winter and spring, suggesting that complex patterns in stream temperature profiles may emerge and subside temporally, across seasons, in response to diversity of water temperatures from different sources. 相似文献
997.
作为移动社交网络的主体,人们移动带来的位置轨迹不仅记录了人的行为历史,也记录了人与社会的交互活动信息。移动社交网络中位置轨迹数据的分析与利用为解决城市问题提供了一种新的思路。本文概述了轨迹数据可视分析中的几种方法,总结了轨迹数据可视分析研究中存在的问题和面临的挑战。 相似文献
998.
Journal of Geographical Sciences - In recent years, flows of many rivers and lakes have become reduced in arid and semi-arid regions around the world. The most typical examples of this phenomenon... 相似文献
999.
1000.
Lucas May Petry Camila Leite Da Silva Andrea Esuli Chiara Renso Vania Bogorny 《International journal of geographical information science》2020,34(7):1428-1450
ABSTRACT The increasing popularity of Location-Based Social Networks (LBSNs) and the semantic enrichment of mobility data in several contexts in the last years has led to the generation of large volumes of trajectory data. In contrast to GPS-based trajectories, LBSN and context-aware trajectories are more complex data, having several semantic textual dimensions besides space and time, which may reveal interesting mobility patterns. For instance, people may visit different places or perform different activities depending on the weather conditions. These new semantically rich data, known as multiple-aspect trajectories, pose new challenges in trajectory classification, which is the problem that we address in this paper. Existing methods for trajectory classification cannot deal with the complexity of heterogeneous data dimensions or the sequential aspect that characterizes movement. In this paper we propose MARC, an approach based on attribute embedding and Recurrent Neural Networks (RNNs) for classifying multiple-aspect trajectories, that tackles all trajectory properties: space, time, semantics, and sequence. We highlight that MARC exhibits good performance especially when trajectories are described by several textual/categorical attributes. Experiments performed over four publicly available datasets considering the Trajectory-User Linking (TUL) problem show that MARC outperformed all competitors, with respect to accuracy, precision, recall, and F1-score. 相似文献