贸易增加值视角下的中国服务出口国际竞争力——基于2016版WIOD世界投入产出表

在全球价值链(GVC)背景下,出口国内增加值的核算不仅能真实反映一国贸易的发展水平,而且对于一国国际竞争力指标的测算也同样重要。本文基于贸易增加值核算法(KPWW),利用世界投入产出数据库(WIOD)在2016年最新发布的2000—2014年世界投入产出数据表分行业测算中国服务出口国内增加值,并与传统贸易统计方法下的出口额进行比较,发现传统方法下服务业整体和分行业层面均被不同程度高估;进一步测算了中国30个服务行业出口的国际市场占有率(IMS指数)和显性比较优势指数(RCA指数),发现在全球价值链背景下,中国的竞争优势仍体现在传统服务行业,而在具有高附加值的新兴行业则处于显著的劣势地位。

A New Approach to Estimating the T-Year Return-Period Wave Height

The paper introduces a new approach to estimating the T-year return-period wave height (TRPW), i.e. the wave height expected to occur in T-year, from two sets of observed extreme data and on the basis of the maximum entropy principle. The main points of the approach are as follows. 1) A maximum entropy probability density function (PDF) for the extreme wave height H is derived from a Euler equation subject to some necessary and rational constraints. 2) The parameters in the function are expressed in terms of the mth moment of H. 3) This PDF is convenient to theoretical and practical applications as it is simple and its four parameters are easy to be determined from observed extreme data. An example is given for estimating the TRPW in 50 and 100 years by the present approach and by some currently used methods using observed data at two hydrographic stations.The comparison of the estimated results shows that the present approach is quite similar to the Pearson-Ⅲ and Gumbel methods.

Comparison Between Radial Basis Function Neural Network and Regression Model for Estimation of Rice Biophysical Parameters Using Remote Sensing

The radial basis function （RBF） emerged as a variant of artificial neural network. Generalized regression neural network （GRNN） is one type of RBF, and its principal advantages are that it can quickly learn and rapidly converge to the optimal regression surface with large number of data sets. Hyperspectral reflectance （350 to 2500 nm） data were recorded at two different rice sites in two experiment fields with two cultivars, three nitrogen treatments and one plant density （45 plants m^-2）. Stepwise multivariable regression model （SMR） and RBF were used to compare their predictability for the leaf area index （LAI） and green leaf chlorophyll density （GLCD） of rice based on reflectance （R） and its three different transformations, the first derivative reflectance （D1）, the second derivative reflectance （D2） and the log-transformed reflectance （LOG）. GRNN based on D1 was the best model for the prediction of rice LAI and CLCD. The relationships between different transformations of reflectance and rice parameters could be further improved when RBF was employed. Owing to its strong capacity for nonlinear mapping and good robustness, GRNN could maximize the sensitivity to chlorophyll content using D1. It is concluded that RBF may provide a useful exploratory and predictive tool for the estimation of rice biophysical parameters.

Wind energy input in coastal seas east of China

This study investigates the wind energy input, an important source of mechanical energy, in the coastal seas east of China. Using the wind field from the high-resolution sea surface meteorology dataset in the Bohai Sea, Yellow Sea, and East China Sea, we studied the wind energy input through surface ageostrophic currents and surface waves. Using a simple analytical formula for the Ekman Spiral with time- dependent wind, the wind energy input through ageostrophic currents was estimated at -22 GW averaged from 1960 to 2007, and through use of an empirical formula, the wind energy input through surface waves was estimated at -169 GW. We also examined the seasonal variation and long-term tendency of mechanical energy from wind stress, and found that the wind energy input to the East China Sea decreased before the 1980s, and then subsequently increased, which is contrary to what has been found for the Bohai Sea and Yellow Sea. More complicated physical processes and varying diffusivity need to be taken into account in future studies.

Probabilistic Analysis and Fatigue Damage Assessment of Offshore Mooring System due to Non-Gaussian Bimodal Tension Processes

Both wave-frequency(WF) and low-frequency(LF) components of mooring tension are in principle non-Gaussian due to nonlinearities in the dynamic system.This paper conducts a comprehensive investigation of applicable probability density functions(PDFs) of mooring tension amplitudes used to assess mooring-line fatigue damage via the spectral method.Short-term statistical characteristics of mooring-line tension responses are firstly investigated,in which the discrepancy arising from Gaussian approximation is revealed by comparing kurtosis and skewness coefficients.Several distribution functions based on present analytical spectral methods are selected to express the statistical distribution of the mooring-line tension amplitudes.Results indicate that the Gamma-type distribution and a linear combination of Dirlik and Tovo-Benasciutti formulas are suitable for separate WF and LF mooring tension components.A novel parametric method based on nonlinear transformations and stochastic optimization is then proposed to increase the effectiveness of mooring-line fatigue assessment due to non-Gaussian bimodal tension responses.Using time domain simulation as a benchmark,its accuracy is further validated using a numerical case study of a moored semi-submersible platform.

Mean Curvature Flow with Convex Gauss Image

In this paper,the mean curvature flow of complete submanifolds in Euclidean space with convex Gauss image and bounded curvature is studied.The confinable property of the Gauss image under the mean curvature flow is proved,which in turn helps one to obtain the curvature estimates.Then the author proves a long time existence result.The asymptotic behavior of these solutions when t→∞is also studied.

Analysis of internal tidal characteristics in the layer above 450 m from acoustic Doppler current profiler observations in the Luzon Strait

The characteristics of internal tides in the upper layer of the Luzon Strait are investigated on the basis of direct-observation current data recorded on April 25 and September 26, 2008 by an acoustic Doppler current profiler. Spectral analysis and energy estimation show that the diurnals and semidiurnals carry most of the energy of internal tides. Values of the depth-integrated total energy E for the three frequency bands of diurnal, semidiurnal, and high frequencies are 31, 6.9, and 3.4 kJ. m, respectively. Near-inertial peaks are only present in the baroclinic component. The behavior of typical tidal frequencies （i.e., O1, K1, M2, MK3, and M4） and the near-inertial frequency is basically consistent with linear internal wave theory, which predicts E＋（ω）/E_（ω）=（ω-f）2/（ω＋f）2 at depths above 66 m, while not all prominent tidal components coincide well with the relation of the linear internal wave field at other depths. Examinations of depth structures of the baroclinic tides and temporal variations show that the surface tides and internal tides are both of mixed type, having diurnal inequality and spring-neap fortnight periods. The K1 and O1 tides have comparable cross- and along-shelf components, while the M2 and S2 tides propagate toward the shelf in the northern South China Sea as wave beams. The amplitude and phase of internal tides vary with time, but M2 and S2 tides appear to have structures dominated by the first mode, while the K1 and O1 tides resemble second-mode structures. The minor to major axis ratios are close to expected values of flω in the thermocline.

Estimating biophysical parameters of rice with remote sensing data using support vector machines

Hyperspectral reflectance (350-2500 nm) measurements were made over two experimental rice fields containing two cultivars treated with three levels of nitrogen application.Four different transformations of the reflectance data were analyzed for their capability to predict rice biophysical parameters,comprising leaf area index (LAI;m-2 green leaf area m-2 soil) and green leaf chlorophyll density (GLCD;mg chlorophyll m 2 soil),using stepwise multiple regression (SMR) models and support vector machines (SVMs).Four transformations of the rice canopy data were made,comprising reflectances (R),first-order derivative reflectances (D1),second-order derivative reflectances (D2),and logarithm transformation of reflectances (LOG).The polynomial kernel (POLY) of the SVM using R was the best model to predict rice LAI,with a root mean square error (RMSE) of 1.0496 LAI units.The analysis of variance kernel of SVM using LOG was the best model to predict rice GLCD,with an RMSE of 523.0741 mg m-2.The SVM approach was not only superior to SMR models for predicting the rice biophysical parameters,but also provided a useful exploratory and predictive tool for analyzing different transformations of reflectance data.

Accuracy and spatio-temporal variation of high resolution satellite rainfall estimate over the Ganjiang River Basin

Based on spatial interpolation rainfall of the ground gauge measurement,we proposed a method to comprehensively evaluate and compare the accuracy of satellite rainfall estimates (SREs) at three spatial scales:0.25°×0.25° grid scale,sub-catchment scale and the whole basin scale.Using this method,we evaluated the accuracy of six high-resolution monthly SREs (TRMM 3B42 V6,3B42RT V6,CMORPH,GSMaP MWR+,GSMaP MVK+ and PERSIANN) and revealed the spatio-temporal variation of the SRE accuracy based on spatial interpolated rainfall from a dense network of 325 gauges during 2003-2009 over the Ganjiang River Basin in the Southeast China.The results showed that ground gauge-calibrated 3B42 had the highest accuracy with slight overestimation,whereas the other five uncalibrated SREs had severe underestimation.The accuracy of the six SREs in wet seasons was remarkably higher than that in the dry seasons.When the time scale was expanded,the accuracy of SRE,particularly 3B42,increased.Furthermore,the accuracy of SREs was relatively low in the western mountains and northern piedmont areas,while it was relatively high in the central and southeastern hills and basins of the Ganjiang River Basin.When the space scale was expanded,the accuracy of the six SREs gradually increased.This study provided an example for of SRE accuracy validation in other regions,and a direct basis for further study of SRE-based hydrological process.

Mean Curvature Flow via Convex Functions on Grassmannian Manifolds

Using the convex functions on Grassmannian manifolds, the authors obtain the interior estimates for the mean curvature flow of higher codimension. Confinable properties of Gauss images under the mean curvature flow have been obtained, which reveal that if the Gauss image of the initial submanifold is contained in a certain sublevel set of the v-function, then all the Gauss images of the submanifolds under the mean curvature flow are also contained in the same sublevel set of the v-function. Under such restrictions, curvature estimates in terms of v-function composed with the Gauss map can be carried out.