Evolution of low-mass helium stars in semidetached binaries

We systematically investigate the evolution of low-mass (0.35, 0.40, and 0.65M _⊙) helium donors in semidetached binaries with white-dwarf accretors. The initial periods of the binaries are chosen in such a way that the helium abundance in the center of the models at the time of Roche lobe overflow varies between Y _c = 0.98 and Y _c ? 0.1. The results of our calculations can be used to analyze the formation scenarios and evolutionary status of AM CVn stars. We show that the minimum orbital periods of the semidetached binaries depend weakly on the total mass of the components and the evolutionary phase of the donor at the time of Roche lobe overflow and are 9–10 min. The differences in the mass transfer rates after P _orb reaches its minimum in the range P _orb ≈ 10–40 min do not exceed a factor of ～2.5. For P _orb ? 20 min, the mass-losing stars are weakly degenerate homogeneous cooling objects; the He, C, N, O, and Ne abundances depend on the evolutionary phase at which Roche lobe overflow occurred. For the binaries that are currently believed to be the most probable candidates for AM CVn stars with helium donors, Y ? 0.4, X _C ? 0.3, X _O ? 0.25, and X _N ? 0.5 × 10^?2. In the binaries under consideration, once P _orb ≈ 40 min has been reached, the mass loss time scale begins to exceed the thermal time scale of the donors, the latter begin to contract, their matter becomes degenerate, and the populations of AMCVn stars with white-dwarf and helium-star progenitors of their donors probably merge together.     

Mapping and assessing crop diversity in the irrigated Fergana Valley,Uzbekistan

Crop diversity (e.g. the number of agricultural crop types and the level of evenness in area distribution) in the agricultural systems of arid Central Asia has recently been increased mainly to achieve food security of the rural population, however, not throughout the irrigation system. Site-specific factors that promote or hamper crop diversification after the dissolvent of the Soviet Union have hardly been assessed yet. While tapping the potential of remote sensing, the objective was to map and explain spatial patterns of current crop diversity by the example of the irrigated agricultural landscapes of the Fergana Valley, Uzbekistan. Multi-temporal Landsat and RapidEye satellite data formed the basis for creating annual and multi-annual crop maps for 2010–2012 while using supervised classifications. Applying the Simpson index of diversity (SID) to circular buffers with radii of 1.5 and 5 km elucidated the spatial distribution of crop diversity at both the local and landscape spatial scales. A variable importance analysis, rooted in the conditional forest algorithm, investigated potential environmental and socio-economic drivers of the spatial patterns of crop diversity. Overall accuracy of the annual crop maps ranged from 0.84 to 0.86 whilst the SID varied between 0.1 and 0.85. The findings confirmed the existence of areas under monocultures as well as of crop diverse patches. Higher crop diversity occurred in the more distal parts of the irrigation system and sparsely settled areas, especially due to orchards. In contrast, in water-secure and densely settled areas, cotton-wheat rotations dominated due to the state interventions in crop cultivation. Distances to irrigation infrastructure, settlements and the road network influenced crop diversity the most. Spatial explicit information on crop diversity per se has the potential to support policymaking and spatial planning towards crop diversification. Driver analysis as exemplified at the study region in Uzbekistan can help reaching the declared policy to increase crop diversity throughout the country and even beyond.     

辽宁省低碳经济发展水平评价

构建包含经济系统、能源系统、碳排放系统、技术投入系统和环境系统5个准则层及23个指标的低碳经济发展水平评价体系,基于可变模糊识别模型,分析评价辽宁省低碳经济发展水平。结果显示:辽宁省低碳经济发展水平由2004年的2.87提升到2014年的3.01,由中碳偏高水平提升到中碳发展水平。沈阳、大连、丹东、锦州、营口和葫芦岛的低碳经济发展水平较高;鞍山、抚顺、本溪、盘锦、辽阳及铁岭的低碳经济发展水平较低。在此基础上,运用SBM模型测算辽宁省各市的碳排放效率,其结果与低碳经济发展水平评价值有较大关联。     

中国生产性服务业市场潜能与空间分布——基于面板工具模型的实证研究

利用2003~2012年全国285个地级及以上城市面板数据,研究了中国生产性服务业及其市场潜能的空间分布特征,并基于面板工具计量模型,实证检验了生产性服务业市场潜能对其空间分布的影响。主要结论是：① 生产性服务业主要集中在区域中心城市,且中心城市与非中心城市生产性服务业发展差距日益加大;生产性服务业市场潜能主要集中在东部沿海地区,从动态上东部地区与中西部地区生产性服务业市场潜能差距在逐渐减小;② 生产性服务业市场潜能对生产性服务业空间分布具有显著影响。分行业看,市场潜能仅对金融服务业和科技服务业的空间分布影响不显著,对商务服务业的空间分布影响最大;③ 市场潜能有效地带动了区域中心城市生产性服务业的发展,但对非中心城市生产性服务业的带动作用不明显,市场潜能没能有效地转化为真实需求。基于此,建议中国未来应提高非中心城市生产性服务业的市场潜能,带动其生产性服务业的发展,尤其是提高非中心城市的本地化专业服务水平,以满足非中心城市工业转型升级过程中受距离限制不能从中心城市获得的专业化生产服务。     

南京地区雨滴谱参数的详细统计分析及其在天气雷达探测中的应用

雨滴谱包含了降雨的丰富信息,不仅能反映雨滴群的微物理特性,也能反映降雨类型、降雨强度等宏观特性,并且在雷达气象领域也有重要的价值。论文对2015和2016年度南京地区32次降雨过程的雨滴谱资料进行了处理、并对多种雨滴参数进行了详细的统计和分析,拟合了层状云降雨、对流云降雨以及积层混合云降雨的雨滴谱Gamma分布参数。另外,还基于雨滴谱数据拟合了雷达反射率因子Z与降雨强度R的Z-R关系,计算了差分反射率Z_DR、相位常数K_DP以及衰减参数,并利用衰减参数进行了C波段雷达回波的衰减订正试验。结果表明:（1）层状云降雨的各微物理参数比较稳定,积雨云的变化剧烈;层云降雨和积层混合云降雨的中雨滴、积雨云降雨的大雨滴对雷达反射率因子的贡献最大。（2）积雨云降雨的滴谱最宽,层状云降雨的最窄。（3）利用依据雨滴谱数据拟合的三类降雨Z-R关系,可以一定程度地提高雷达估测降雨的精度。（4）利用基于雨滴谱数据拟合的衰减系数,有效地进行了C波段双偏振雷达回波强度的衰减订正,体现了统计参数和拟合参数准确性。     

A model‐based data‐driven dictionary learning for seismic data representation

Planar waves events recorded in a seismic array can be represented as lines in the Fourier domain. However, in the real world, seismic events usually have curvature or amplitude variability, which means that their Fourier transforms are no longer strictly linear but rather occupy conic regions of the Fourier domain that are narrow at low frequencies but broaden at high frequencies where the effect of curvature becomes more pronounced. One can consider these regions as localised “signal cones”. In this work, we consider a space–time variable signal cone to model the seismic data. The variability of the signal cone is obtained through scaling, slanting, and translation of the kernel for cone‐limited (C‐limited) functions (functions whose Fourier transform lives within a cone) or C‐Gaussian function (a multivariate function whose Fourier transform decays exponentially with respect to slowness and frequency), which constitutes our dictionary. We find a discrete number of scaling, slanting, and translation parameters from a continuum by optimally matching the data. This is a non‐linear optimisation problem, which we address by a fixed‐point method that utilises a variable projection method with ?₁ constraints on the linear parameters and bound constraints on the non‐linear parameters. We observe that slow decay and oscillatory behaviour of the kernel for C‐limited functions constitute bottlenecks for the optimisation problem, which we partially overcome by the C‐Gaussian function. We demonstrate our method through an interpolation example. We present the interpolation result using the estimated parameters obtained from the proposed method and compare it with those obtained using sparsity‐promoting curvelet decomposition, matching pursuit Fourier interpolation, and sparsity‐promoting plane‐wave decomposition methods.     

Development of a distributed hydrological model to facilitate watershed management

To facilitate precise and cost-effective watershed management, a simple yet spatially and temporally distributed hydrological model (DHM-WM) was developed. The DHM-WM is based on the Mishra-Singh version of the curve number method, with several modifications: The spatial distribution of soil moisture was considered in moisture updating; the travel time of surface runoff was calculated on a grid cell basis for routing; a simple tile flow module was included as an option. The DHM-WM was tested on a tile-drained agricultural watershed in Indiana, USA. The model with the tile flow module performed well in the study area, providing a balanced water budget and reasonable flow partitioning. The daily coefficient of determination and Nash-Sutcliffe coefficient were 0.58 and 0.56, for the calibration period, and 0.63 and 0.62 for the validation period. The DHM-WM also provides detailed information about the source areas of flow components, the travel time and pathways of surface runoff.

EDITOR A. Castellarin; ASSOCIATE EDITOR F.-J. Chang     

Enhanced identification of a hydrologic model using streamflow and satellite water storage data: A multicriteria sensitivity analysis and optimization approach

Hydrologic model development and calibration have continued in most cases to focus only on accurately reproducing streamflows. However, complex models, for example, the so‐called physically based models, possess large degrees of freedom that, if not constrained properly, may lead to poor model performance when used for prediction. We argue that constraining a model to represent streamflow, which is an integrated resultant of many factors across the watershed, is necessary but by no means sufficient to develop a high‐fidelity model. To address this problem, we develop a framework to utilize the Gravity Recovery and Climate Experiment's (GRACE) total water storage anomaly data as a supplement to streamflows for model calibration, in a multiobjective setting. The VARS method (Variogram Analysis of Response Surfaces) for global sensitivity analysis is used to understand the model behaviour with respect to streamflow and GRACE data, and the BORG multiobjective optimization method is applied for model calibration. Two subbasins of the Saskatchewan River Basin in Western Canada are used as a case study. Results show that the developed framework is superior to the conventional approach of calibration only to streamflows, even when multiple streamflow‐based error functions are simultaneously minimized. It is shown that a range of (possibly false) system trajectories in state variable space can lead to similar (acceptable) model responses. This observation has significant implications for land‐surface and hydrologic model development and, if not addressed properly, may undermine the credibility of the model in prediction. The framework effectively constrains the model behaviour (by constraining posterior parameter space) and results in more credible representation of hydrology across the watershed.     

An extended variable-grid global ocean circulation model and its preliminary results of the equatorial Pacific circulation

1IntroductionThetropicalPacificOceanplaysanimpor-tantroleintheclimatevariabilitiessuchasElNi-no-SouthernOscillation(ENSO)phenomenon(Chao,1993).ManystudieshavefoundthatthetropicalPacificvariabilitiescanhavesignifi-cantinfluenceontheoceancirculationintheseasadjacenttoChina(Yu,1985;Chaoetal.,1996;Wangetal.,2002).TheseaareaadjacenttoChinaischaracterizedbyitscomplextopog-raphyandnumerousnarrowstraits,andthusre-quiresafinegridtoresolve.Tostudytheinter-actionbetweenthetropicalPacificandChinas…     

面向单脉冲信号分类的集成特征选择与评价

受大量射频干扰信号影响, 快速从海量观测数据中准确识别出单脉冲信号已成为天文数据处理的一项重要任务, 而设计和提取有效数据特征, 是利用机器学习进行单脉冲信号高效识别的决定因素. 针对如何选择最优特征, 进而提升单脉冲信号的分类精度这一关键问题, 设计了面向单脉冲信号分类的集成特征选择方法. 方法首先混合单脉冲信号的参数特征、统计特征和抽象特征, 然后分别利用5种单一特征选择方法选出各自的最优特征集, 最后利用贪心策略对5种单一方法获取的最优特征集进行集成筛选, 获取最优集成特征集. 实验表明, 最优特征集合既包含统计特征也包含抽象特征. 在相同特征数量下, 利用集成特征选择比单一特征选择能获得更高的模型精度, 可使F1值最高提升1.8%. 在海量数据背景下, 集成特征选择对减少特征数量、提升分类性能和加快数据处理速度具有重要作用.