ESTIMATE OF METHANE EMISSIONS FROM RICE FIELDS IN CHINA BY CLIMATE-BASED NET PRIMARY PRODUCTIVITY

1INTRODUCTIONIrrigated ricefieldsarecharacterizedbylargespatialandtemporalvariationsin CH4 emissiontotheatmo-sphere.Accordingly,thereisagreatuncertaintyintheestimate ofCH4 emissionsfromricefields.GreateffortshavebeenmadetoestimatetheCH4 emissionsfromricefieldsandseveralapproacheshavebeendeveloped.TherepresentativemethodsincludetheIPCC(Inter-governmentPanelofClimateChange)region-specificemissionfactormethodandthemodelcalculationmethod.Toimprovethecalculationaccuracy,theIPCCmethodreq…     

Cultivation of marine sponges

Sponges are the most primitive of multicellular animals, and are major pharmaceutical sources of marine secondary metabolites. A wide variety of new compounds have been isolated from sponges. In order to produce sufficient amounts of the compounds of the needed, it is necessary to obtain large amount of sponges.The production of sponge biomass has become a focus of marine biotechnology.     

基于手机数据的北京市城市与近郊交互模式挖掘

在城镇化进程中,城市与近郊之间通过职住、货运、游憩等活动产生越来越紧密的交互联系,对于这些交互联系的准确识别和定量刻画,是理解城乡空间关系的重要手段,也能为城市的资源有效配置与合理规划提供重要的现状信息。本文通过对全北京在一日之内的手机信令数据所反映的人群移动轨迹的深入分析,融合城市的POI信息形成顾及人类活动时空信息的空间交互类型推断。以北京市为例,对城市中心与近郊之间远距离的强交互进行定性、定量和定位的探索。本文发现了北京市多尺度下空间交互模式和距离衰减规律,判断了城乡异常交互类型,对比了城乡之间和城市内部的交互模式的异同,以及基于交互类型视角提取了城乡异常交互的空间特征。研究认为,基于手机信令数据,利用停留点提取和高斯核密度估计的空间交互类型推断有效地发现了北京市周末的远距离出行类型特点,提取了其空间交互强度和空间特征,揭示了基于人类活动的北京市周末城乡交互模式。     

取土器几何尺寸对饱和软黏土样结构的扰动研究

基于颗粒流软件模拟,以吹填淤泥为例,分析了取土器的内径、切角、壁厚等尺寸参数对高黏性软土微观动力学特性的影响;通过分层方法,比较了7组土样层间颗粒特征拐点的运动行为。模拟结果表明:土样的颗粒在底部形成对流位移场,对流处上方颗粒主要受拉膨胀,对流处下方颗粒主要受压收缩,由此造成孔隙率的规律变化和层理的弯曲变形。7组参数对应土样的孔隙率曲线与初始孔隙率曲线的交点同颗粒位移场的对流位置存在协同关系。土样层理表现为向下弯曲变形,层间颗粒位移行为存在特征拐点,拐点之间颗粒扰动行为不明显;反之,颗粒扰动行为较大,这种变形特征可拟合为下开口的旋转抛物面,且曲面方程的曲面形状拟合系数a值能初步评估7组土样的扰动程度。层间特征拐点的连线可再拟合为旋转抛物面,抛物面体积与土样体积的比值可用来评估土样的原状性。     

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海洋科学的前沿-“数字海洋”

本文所提出的“数字海洋”,系基于当前世界各国极为关注的“数字地球”发展前景 ,其事关我国海洋科学进入21世纪信息时代所面临的挑战和机遇。对此,从“数字地球”概念及其所涉及的新理论和高新技术 ,到中国“数字地球”中的“数字海洋”有待顺应发展,作了概述。同时 ,重点就“数字海洋”技术与目标和建设的设想等作了探讨。     

Predicting TBM penetration rate in hard rock condition: A comparative study among six XGB-based metaheuristic techniques

A reliable and accurate prediction of the tunnel boring machine(TBM) performance can assist in minimizing the relevant risks of high capital costs and in scheduling tunneling projects.This research aims to develop six hybrid models of extreme gradient boosting(XGB) which are optimized by gray wolf optimization(GWO), particle swarm optimization(PSO), social spider optimization(SSO), sine cosine algorithm(SCA), multi verse optimization(MVO) and moth flame optimization(MFO), for estimation of the TBM penetration rate(PR).To do this, a comprehensive database with 1286 data samples was established where seven parameters including the rock quality designation, the rock mass rating, Brazilian tensile strength(BTS), rock mass weathering, the uniaxial compressive strength(UCS), revolution per minute and trust force per cutter(TFC), were set as inputs and TBM PR was selected as model output.Together with the mentioned six hybrid models, four single models i.e., artificial neural network, random forest regression, XGB and support vector regression were also built to estimate TBM PR for comparison purposes.These models were designed conducting several parametric studies on their most important parameters and then, their performance capacities were assessed through the use of root mean square error, coefficient of determination, mean absolute percentage error, and a10-index.Results of this study confirmed that the best predictive model of PR goes to the PSO-XGB technique with system error of(0.1453, and 0.1325), R~2 of(0.951, and 0.951), mean absolute percentage error(4.0689, and 3.8115), and a10-index of(0.9348, and 0.9496) in training and testing phases, respectively.The developed hybrid PSO-XGB can be introduced as an accurate, powerful and applicable technique in the field of TBM performance prediction.By conducting sensitivity analysis, it was found that UCS, BTS and TFC have the deepest impacts on the TBM PR.     

Measuring positive public transit accessibility using big transit data

Most of the current existing accessibility measures quantify the potential of reaching desirable opportunities across space and time. Nevertheless, these potent...     

An internal-external optimized convolutional neural network for arbitrary orientated object detection from optical remote sensing images

Due to the bird's eye view of remote sensing sensors, the orientational information of an object is a key factor that has to be considered in object detection. ...     

湖北永兴洞降水对2015年厄尔尼诺的响应

通过对湖北永兴洞为期3年（2013年6月至2016年7月）的地表降水δ¹⁸O观测,发现该地点降水δ¹⁸O在2015夏季显著偏正。利用HYSPLIT后向轨迹方法对永兴洞降水水汽来源进行分析,结果表明在厄尔尼诺事件的影响下2015年夏季来自远源印度洋的水汽显著减少,而近源太平洋水汽相对增多,即降水δ¹⁸O因"环流效应"而偏正。本研究提供的观测证据表明永兴洞石笋δ¹⁸O记录在重建ENSO主导下的亚洲季风大气环流方面具有重要潜力。