大兴安岭北段巴升河岩体锆石U-Pb年代学及其地质意义

大兴安岭北段扎兰屯地区巴升河岩体由碱长花岗岩组成.采用LA-ICP-MS方法对碱长花岗岩开展锆石U-Pb测年,结果为297.8±3.6 Ma,岩体形成于早二叠世.该岩体4个样品的全岩地球化学等特征显示：巴升河岩体中碱长花岗岩具有富Si、高K、富碱的特征,属于弱过铝质钾玄岩系列,同时,样品∑REE偏高,Eu负异常明显,富集大离子亲石元素,具有A型花岗岩特征,综合前人研究成果及同位素年代学特征,认为兴安地块与松嫩地块拼合的时间早于298 Ma.     

双向地震作用下崩塌堆积体边坡动力模糊可靠性分析

考虑崩塌堆积体边坡岩土体参数随机性和模糊性,以及地震力双向性,建立一种边坡地震动力模糊可靠度计算方法,针对竖向地震力对崩塌堆积体边坡稳定可靠性的影响进行进一步研究。首先,选用动力有限元时程分析法计算出双向地震工况下崩塌堆积体边坡的响应特征,并运用模糊理论对强度参数进行模糊性处理;然后,根据Mohr-Coulumb强度准则构建边坡安全系数与可靠度的时程计算模型;最后,采用边坡地震可靠性评价新方法,通过MATLAB编写相应程序,实现计算和分析结果的快速输出。案例结果表明:新方法计算结果更加合理,对工程而言也更加安全;竖向地震作用均对崩塌堆积体边坡整体可靠性存在影响,但影响程度需根据工程实际情况进行分析。在算例工况下,竖向地震对崩塌堆积体边坡的可靠性影响很小,仅使得可靠度降低3.55%,因此,可仅考虑水平地震的影响。     

浅谈挤密碎石桩的施工方法

挤密碎石桩施工法是一种振动成桩法,即先用桩管振动成孔,然后填入足够数量的碎石,最后振动密实成桩体。通过振动、挤密的成桩过程,将原地基土振动夯实,桩体与桩间土形成复合地基,达到既处理可液化地基又增强地基的效果。介绍了挤密碎石柱的施工方法和质量检测方法。     

基于SSA-Adam-BP神经网络模型的堰塞坝稳定性预测

现有的堰塞坝稳定性预测模型多为线性模型,无法充分考虑堰塞坝稳定性与其形态特征和水域条件之间的复杂非线性关系.鉴于此,结合反向传播神经网络模型和樽海鞘优化算法,提出了一种新型的堰塞坝稳定性预测模型SSA-Adam-BP.该模型通过网格搜索法选取确定模型结构的最佳超参数组合,进而利用交叉验证和绘制ROC曲线的方式分别对采用...     

海洋无人观测装备发展与应用思考

海洋无人自主观测装备作为海洋观探测的一种不可替代的高科技先进装备和新兴装备,是海洋观探测装备摇篮中的新生命、新领域的开拓者。基于海洋无人观测装备提高海洋移动观测能力是未来构建立体、连续、实时水下观测网络的重要技术手段,将会对未来海洋观探测的方式产生深远影响。基于国内外海洋无人观测装备发展与应用现状分析,对我国海洋无人观测装备发展的主要问题和差距进行了思考,并对海洋无人观测装备未来的发展应用进行了展望。     

Late Quaternary vegetation and climate dynamics in central-eastern Brazil: insights from a ~35k cal a bp peat record in the Cerrado biome

The late Quaternary evolution of central-eastern Brazil has been under-researched. Questions remain as to the origin of the Cerrado, a highly endangered biome, and other types of vegetation, such as the Capões – small vegetation islands of semi-deciduous and mountain forests. We investigated the factors that influenced the expansion and contraction of the Cerrado and Capões during the late Quaternary (last ~35 ka), using a multi-proxy approach: stable isotopes (δ¹³C, δ¹⁵N), geochemistry, pollen and multivariate statistics derived from a peat core (Pinheiro mire, Serra do Espinhaço Meridional). Five major shifts in precipitation, temperature, vegetation and landscape stability occurred at different timescales. Our study revealed that changes in the South Atlantic Convergence Zone (SACZ) seem to have been coeval with these shifts: from the Late Glacial Maximum to mid-Holocene the SACZ remained near (~29.6 to ~16.5k cal a bp ) and over (~16.5 to ~6.1 k cal a bp ) the study area, providing humidity to the region. This challenges previous research which suggested that climate was drier for this time period. At present, the Capões are likely to be a remnant of a more humid climate; meanwhile, the Cerrado biome seems to have stablished in the late Holocene, after ~3.1 k cal a bp .     

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/ ).     

MARC: a robust method for multiple-aspect trajectory classification via space,time, and semantic embeddings

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.     

黄土高原沟谷地貌发育演化研究进展与展望

黄土沟谷是黄土地貌中最有活力、最具变化、最富特色的对象单元,黄土高原千沟万壑的地貌形态以及触目惊心的侵蚀状态也让区域内沟谷地貌的形成、发育及演化问题成为研究中焦点及前沿性科学问题。近年来,诸多学者采用地学测年法、特征表达法、监测模拟法力图实现对黄土沟谷发育演化进程中“过去-现代-未来”的科学认知。这些研究在相当程度上丰富了黄土沟谷发育过程的认知。本文梳理了黄土高原沟谷地貌演化相关研究的现状,并从黄土高原地貌演化、黄土沟谷发育、基于DEM的沟谷信息提取与表达等研究进行了系统的回顾、梳理与分析。此外,本文提出“黄土沟道剖面群组”概念与方法,试图从新的视角审视黄土沟谷地貌发育演化过程。沟道剖面在黄土沟谷发育演化进程中传递物质能量和累积地形动力,并通过径流节点的串联实现剖面群的连接与组合,形成独特的剖面“群组”模式;该沟道剖面群组是集黄土沟谷地貌特征与过程于一体的综合信息集成体,其三维空间结构是对黄土沟谷地貌发育演化的高度抽象与映射,并可望进一步丰富黄土高原数字地形分析理论与方法体系,为黄土高原黄土地貌成因机理与空间分异格局带来创新的认识。