Gross primary production(GPP)is a crucial indicator representing the absorption of atmospheric CO_(2) by vegetation.At present,the estimation of GPP by remote sensing is mainly based on leaf-related vegetation indexes...Gross primary production(GPP)is a crucial indicator representing the absorption of atmospheric CO_(2) by vegetation.At present,the estimation of GPP by remote sensing is mainly based on leaf-related vegetation indexes and leaf-related biophysical para-meter leaf area index(LAI),which are not completely synchronized in seasonality with GPP.In this study,we proposed chlorophyll content-based light use efficiency model(CC-LUE)to improve GPP estimates,as chlorophyll is the direct site of photosynthesis,and only the light absorbed by chlorophyll is used in the photosynthetic process.The CC-LUE model is constructed by establishing a linear correlation between satellite-derived canopy chlorophyll content(Chlcanopy)and FPAR.This method was calibrated and validated utiliz-ing 7-d averaged in-situ GPP data from 14 eddy covariance flux towers covering deciduous broadleaf forest ecosystems across five dif-ferent climate zones.Results showed a relatively robust seasonal consistency between Chlcanopy with GPP in deciduous broadleaf forests under different climatic conditions.The CC-LUE model explained 88% of the in-situ GPP seasonality for all validation site-year and 56.0% of in-situ GPP variations through the growing season,outperforming the three widely used LUE models(MODIS-GPP algorithm,Vegetation Photosynthesis Model(VPM),and the eddy covariance-light use efficiency model(EC-LUE)).Additionally,the CC-LUE model(RMSE=0.50 g C/(m^(2)·d))significantly improved the underestimation of GPP during the growing season in semi-arid region,re-markably decreasing the root mean square error of averaged growing season GPP simulation and in-situ GPP by 75.4%,73.4%,and 37.5%,compared with MOD17(RMSE=2.03 g C/(m^(2)·d)),VPM(RMSE=1.88 g C/(m^(2)·d)),and EC-LUE(RMSE=0.80 g C/(m^(2)·d))model.The chlorophyll-based method proved superior in capturing the seasonal variations of GPP in forest ecosystems,thereby provid-ing the possibility of a more precise depiction of forest seasonal carbon uptake.展开更多
With the explosive growth and need for high-speed wireless communications, more and more energy is consumed to support the required quality of service. Therefore, energy efficient or green communication has become a v...With the explosive growth and need for high-speed wireless communications, more and more energy is consumed to support the required quality of service. Therefore, energy efficient or green communication has become a very hot topic under the ground of limited energy resource and environmentally friendly transmission schemes. MIMO technique is capable of reducing the transmission power thanks to its diversity and multiplexing gain. Moreover, antenna selection(AS) is an alternative to extract many of the benefits in MIMO systems with a reduced cost of complexity and power. Although many works including several survey papers have investigated AS in MIMO systems, the goal of these works is only the capacity maximization or error rate minimization, which fails to guarantee the optimality of the energy efficiency in MIMO systems. In this paper, we overview the state of the art in the AS schemes in energy efficient MIMO systems, the goal of which is to optimize the energy efficiency of the whole system. Specifically, we introduce energy efficient AS in point-to-point MIMO, cooperative MIMO, multiuser MIMO and largescale MIMO systems, respectively. Several challenging and practical issues in this area are also addressed.展开更多
Generation of mouse models carrying a defined point mutation,especially disease-related point mutations,is of considerable interest for research in biology and medicine.The standard method based on embryonic stem cell...Generation of mouse models carrying a defined point mutation,especially disease-related point mutations,is of considerable interest for research in biology and medicine.The standard method based on embryonic stem cell（ESC）-mediated homologous recombination（HR）is time-and labor-consuming.展开更多
We present an efficient three-dimensional coupled-mode model based on the Fourier synthesis technique. In principle, this model is a one-way model, and hence provides satisfactory accuracy for problems where the forwa...We present an efficient three-dimensional coupled-mode model based on the Fourier synthesis technique. In principle, this model is a one-way model, and hence provides satisfactory accuracy for problems where the forward scattering dominates. At the same time, this model provides an efficiency gain of an order of magnitude or more over two-way coupled-mode models. This model can be applied to three-dimensional range-dependent problems with a slowly varying bathymetry or internal waves. A numerical example of the latter is demonstrated in this work. Comparisons of both accuracy and efficiency between the present model and a benchmark model are also provided.展开更多
In the realm of engineering practice,various factors such as limited availability of measurement data and complex working conditions pose significant challenges to obtaining accurate load spectra.Thus,accurately predi...In the realm of engineering practice,various factors such as limited availability of measurement data and complex working conditions pose significant challenges to obtaining accurate load spectra.Thus,accurately predicting the fatigue life of structures becomes notably arduous.This paper proposed an approach to predict the fatigue life of structure based on the optimized load spectra,which is accurately estimated by an efficient hinging hyperplane neural network(EHH-NN)model.The construction of the EHH-NN model includes initial network generation and parameter optimization.Through the combination of working conditions design,multi-body dynamics analysis and structural static mechanics analysis,the simulated load spectra of the structure are obtained.The simulated load spectra are taken as the input variables for the optimized EHH-NN model,while the measurement load spectra are used as the output variables.The prediction results of case structure indicate that the optimized EHH-NN model can achieve the high-accuracy load spectra,in comparison with support vector machine(SVM),random forest(RF)model and back propagation(BP)neural network.The error rate between the prediction values and the measurement values of the optimized EHH-NN model is 4.61%.In the Cauchy-Lorentz distribution,the absolute error data of 92%with EHH-NN model appear in the intermediate range of±1.65%.Also,the fatigue life analysis is performed for the case structure,based on the accurately predicted load spectra.The fatigue life of the case structure is calculated based on the comparison between the measured and predicted load spectra,with an accuracy of 93.56%.This research proposes the optimized EHH-NN model can more accurately reflect the measurement load spectra,enabling precise calculation of fatigue life.Additionally,the optimized EHH-NN model provides reliability assessment for industrial engineering equipment.展开更多
With a continuously increasing population and better food consumption levels, im- proving the efficiency of arable land use and increasing its productivity have become funda- mental strategies to meet the growing food...With a continuously increasing population and better food consumption levels, im- proving the efficiency of arable land use and increasing its productivity have become funda- mental strategies to meet the growing food security needs in China. A spatial distribution map of medium- and low-yield cropland is necessary to implement plans for cropland improvement In this study, we developed a new method to identify high-, medium-, and low-yield cropland from Moderate Resolution Imaging Spectroradiometer （MODIS） data at a spatial resolution of 500 m. The method could be used to reflect the regional heterogeneity of cropland productiv- ity because the classification standard was based on the regionalization of cropping systems in China. The results showed that the proportion of high-, medium-, and low-yield cropland in China was 21%, 39%, and 40%, respectively. About 75% of the low-yield cropland was lo- cated in hilly and mountainous areas, and about 53% of the high-yield cropland was located in plain areas. The five provinces with the largest area of high-yield cropland were all located in the Huang-Huai-Hai region, and the area amounted to 42% of the national high-yield cropland area. Meanwhile, the proportion of high-yield cropland was lower than 15% in Hei- Iongjiang, Sichuan, and Inner Mongolia, which had the largest area allocated to cropland in China. If all the medium-yield cropland could be improved to the productive level of high-yield cropland and the low-yield cropland could be improved to the level of medium-yield cropland, the total productivity of the land would increase 19% and 24%, respectively.展开更多
Primary productivity of ecosystem is important indicator about ecological assessment. Remote sensing technology has been used to monitor net primary productivity （NPP） of ecological system for several years. In this...Primary productivity of ecosystem is important indicator about ecological assessment. Remote sensing technology has been used to monitor net primary productivity （NPP） of ecological system for several years. In this paper, the remotely sensed NPP simulation model of alpine vegetation in Qinghai Province of Tibet Plateau was set up based on the theory of light use efficiency. Firstly a new approach based on mixed pixels and Support Vector Machine （SVM） algorithm were used to correct simulated NPP values derived from Moderate Resolution Imaging Spectroradiometer （MODIS） data. Finally, spatial distribution and monthly variation characteristics of NPP in Qinghai Province detail. The result showed in 2006 were analyzed in that NPP of vegetation in Qinghai Province in 2006 ranged from o to 422 gC/m2/a and the average NPP was 151 gC/m2/a. NPP gradually increased from northwest to southeast. NPP of different vegetation types were obviously different. The average NPP of broad-leaved forest was the largest （314 gC/m2/a）, and sparse shrub was the smallest （101 gC/m2/a）. NPP in Qinghai Province significantly changed with seasonal variation. The accumulation of NPP was primarily in the period （from April to September） with better moist and heat conditions. In July, the average NPP of vegetation reached the maximum value （43 gC/m2）. In our model, the advantage of traditional LUE models was adopted, and our study fully considered typicalcharacteristics of alpine vegetation light use efficiency and environmental factors in the study area. Alpine vegetation is the most important ecological resource of Tibet Plateau, exactly monitoring its NPP value by remote sensing is an effective protection measure.展开更多
Many methods based on deep learning have achieved amazing results in image sentiment analysis.However,these existing methods usually pursue high accuracy,ignoring the effect on model training efficiency.Considering th...Many methods based on deep learning have achieved amazing results in image sentiment analysis.However,these existing methods usually pursue high accuracy,ignoring the effect on model training efficiency.Considering that when faced with large-scale sentiment analysis tasks,the high accuracy rate often requires long experimental time.In view of the weakness,a method that can greatly improve experimental efficiency with only small fluctuations in model accuracy is proposed,and singular value decomposition(SVD)is used to find the sparse feature of the image,which are sparse vectors with strong discriminativeness and effectively reduce redundant information;The authors propose the Fast Dictionary Learning algorithm(FDL),which can combine neural network with sparse representation.This method is based on K-Singular Value Decomposition,and through iteration,it can effectively reduce the calculation time and greatly improve the training efficiency in the case of small fluctuation of accuracy.Moreover,the effectiveness of the proposed method is evaluated on the FER2013 dataset.By adding singular value decomposition,the accuracy of the test suite increased by 0.53%,and the total experiment time was shortened by 8.2%;Fast Dictionary Learning shortened the total experiment time by 36.3%.展开更多
Over the past 40 years of reform and opening-up during 1978-2018, China ＇S rapid economic growth has become a miracle in world economic history and reshaped the world economy. In the 40 years, China has successfully ...Over the past 40 years of reform and opening-up during 1978-2018, China ＇S rapid economic growth has become a miracle in world economic history and reshaped the world economy. In the 40 years, China has successfully transformed from an isolated agricultural country into the world＇s largest industrial manufacturer. In 2018, China＇s urbanization rate is expected to reach 60% with per capita GDP expected to reach 9, 000 USD. After another 5 to 8 years, China will join the rank of high-income countries, successfully cross the middle-income trap and become a moderately prosperous economy in all respects. In its modernization drive, China will follow the new concept of ＂innovation, coordinated, green, open and shared development＂ and strive to achieve its ＂two centennial展开更多
In order to simulate and analyze hot strip crown and flatness accurately and efficiently, the 3-D （three-di- mensional） coupled model involved in RPFEM （rigid-plastic finite element method） is improved based on th...In order to simulate and analyze hot strip crown and flatness accurately and efficiently, the 3-D （three-di- mensional） coupled model involved in RPFEM （rigid-plastic finite element method） is improved based on the analyti- cal model of forecasting rolling force distribution. In the analytical model, variational method is employed to solve the lateral flow of metal and influential function method is employed to calculate roll deflection, the lateral distribution of rolling force can be obtained rapidly by iterative strategy. Then the 3-D coupled model uses the result as initial distri- bution of rolling force to calculate roll deflection and makes the initial on-load roll gap profile close to the final value, so as to reduce iterations and increase efficiency. Compared with previous algorithms, the improved model can reduce the iterations by about 50% and shorten the computing time by about 60% on the basis of the calculation accuracy.展开更多
The existing research of the acceleration control mainly focuses on an optimization of the velocity trajectory with respect to a criterion formulation that weights acceleration time and fuel consumption. The minimum-f...The existing research of the acceleration control mainly focuses on an optimization of the velocity trajectory with respect to a criterion formulation that weights acceleration time and fuel consumption. The minimum-fuel acceleration problem in conventional vehicle has been solved by Pontryagin＇s maximum principle and dynamic programming algorithm, respectively. The acceleration control with minimum energy consumption for battery electric vehicle（EV） has not been reported. In this paper, the permanent magnet synchronous motor（PMSM） is controlled by the field oriented control（FOC） method and the electric drive system for the EV（including the PMSM, the inverter and the battery） is modeled to favor over a detailed consumption map. The analytical algorithm is proposed to analyze the optimal acceleration control and the optimal torque versus speed curve in the acceleration process is obtained. Considering the acceleration time, a penalty function is introduced to realize a fast vehicle speed tracking. The optimal acceleration control is also addressed with dynamic programming（DP）. This method can solve the optimal acceleration problem with precise time constraint, but it consumes a large amount of computation time. The EV used in simulation and experiment is a four-wheel hub motor drive electric vehicle. The simulation and experimental results show that the required battery energy has little difference between the acceleration control solved by analytical algorithm and that solved by DP, and is greatly reduced comparing with the constant pedal opening acceleration. The proposed analytical and DP algorithms can minimize the energy consumption in EV＇s acceleration process and the analytical algorithm is easy to be implemented in real-time control.展开更多
Abies fabri is a typical subalpine dark coniferous forest in southwestern China. Air temperature increases more at high elevation areas than that at low elevation areas in mountainous regions,and climate change ratio ...Abies fabri is a typical subalpine dark coniferous forest in southwestern China. Air temperature increases more at high elevation areas than that at low elevation areas in mountainous regions,and climate change ratio is also uneven in different seasons. Carbon gain and the response of water use efficiency(WUE) to annual and seasonal increases in temperature with or without CO_2 fertilization were simulated in Abies fabri using the atmospheric-vegetation interaction model(AVIM2). Four future climate scenarios(RCP2.6,RCP4.5,RCP6.0 and RCP8.5) from the Coupled Model Intercomparison Project Phase 5(CMIP5) were selectively investigated. The results showed that warmer temperatures have negative effects on gross primary production(GPP) and net primary production(NPP) in growing seasons and positive effects in dormant seasons due to the variation in the leaf area index. Warmer temperatures tend to generate lower canopy WUE and higher ecosystem WUE in Abies fabri. However,warmer temperature together with rising CO_2 concentrations significantlyincrease the GPP and NPP in both growing and dormant seasons and enhance WUE in annual and dormant seasons because of the higher leaf area index(LAI) and soil temperature. The comparison of the simulated results with and without CO_2 fertilization shows that CO_2 has the potential to partially alleviate the adverse effects of climate warming on carbon gain and WUE in subalpine coniferous forests.展开更多
Recovering waste heat from industrial processes is bene ficial in order to reduce the primary energy demands and heat pumps can be used to this purpose.Absorption heat pumps are energy-saving and environment-friendly ...Recovering waste heat from industrial processes is bene ficial in order to reduce the primary energy demands and heat pumps can be used to this purpose.Absorption heat pumps are energy-saving and environment-friendly because use working fluids that do not cause ozone depletion and can reduce the global warming emissions.The hybrid heat pump processes combine the conventional vapor-compression and the absorption heat pump cycles.Studies about the simulations and modeling of hybrid heat pumps are few in literature.In this research a mathematical model for single effect absorption and hybrid heat pump is carried out with Chem Cad? 6.0.1.LiBr–H_2O is used as working fluid while electrolytic NRTL and electrolytes latent heat are used as thermodynamic model due to the better results.Binary parameters of activity coef ficients are regressed from experimental vapor pressure data while default constants are used for the solubility expressions.A design of heat pumps is developed and a new modeling of generator is analyzed.The coef ficient of performance of absorption heat pump and hybrid heat pump is equal to 0.7 and 0.83 respectively.For absorption heat pump a sensitivity analysis is carried out to evaluate the effect of temperature and pressure generator,the concentration of Li–Br solution on coef ficient of performance,cooling capacity and working fluid temperature.For hybrid heat pump,the different coef ficients of performance,the primary energy ratio,the generator heat,and the compressor power are analyzed for different values of compressor proportion.Results show that comparing the two systems the hybrid pump allows to save more primary energy,costs and carbon dioxide emissions with respect to absorption heat pump with the increasing of compressor proportion parameter.Future researches should focus on the construction of this heat pumps integrated in chemical processes as a biogas plant or trigeneration systems.展开更多
It is extensively approved that Channel State Information(CSI) plays an important role for synergetic transmission and interference management. However, pilot overhead to obtain CSI with enough precision is a signific...It is extensively approved that Channel State Information(CSI) plays an important role for synergetic transmission and interference management. However, pilot overhead to obtain CSI with enough precision is a significant issue for wireless communication networks with massive antennas and ultra-dense cell. This paper proposes a learning- based channel model, which can estimate, refine, and manage CSI for a synergetic transmission system. It decomposes the channel impulse response into multiple paths, and uses a learning-based algorithm to estimate paths' parameters without notable degradation caused by sparse pilots. Both indoor measurement and outdoor measurement are conducted to verify the feasibility of the proposed channel model preliminarily.展开更多
The performance of a 3-phase 6-pole 400 W inverter-drive induction motor was investigated using a variety of non-oriented electrical steels for stator core at PWM inverter fundamental wave frequencies of 30 to 300 Hz....The performance of a 3-phase 6-pole 400 W inverter-drive induction motor was investigated using a variety of non-oriented electrical steels for stator core at PWM inverter fundamental wave frequencies of 30 to 300 Hz. There existed an optimum Si content of the material depending on the tooth flux density. Both reduction of material thickness and stress-relief annealing of the stator core improved the motor efficiency. The influence of Si content on the efficiency was small at lower PWM frequencies, while at higher frequencies the motor efficiency increased with increasing Si content. The Cu loss WC increased and the Fe loss Wi counteractiveiy decreasedwith increasing Si content at lower frequencies; while at higher frequencies Wi had dominant effect on the efficiency. Newly developed materials RMA, having lower Fe losses after stress-relief annealing and higher flux densities with lower Si contents, showed motor efficiencies superior to conventional J1S grade materials with comparable Fe losses.展开更多
The transition from middle-income to high-income stage is fraught with risks of growth divergence. Economic transition is clouded by the following possibilities： （1）falling share of industrial seetor through indust...The transition from middle-income to high-income stage is fraught with risks of growth divergence. Economic transition is clouded by the following possibilities： （1）falling share of industrial seetor through industrial depression and weakening growth momentum caused by the large urbanization costs; （2） the subordination of service sector as a result of nearly irreversibly industrial professional, which falters the process of service sector transition and upgrading,＂ （3） inefficient knowledge production allocation and human capital upgrade due to the absence of incentivized compensation of knowledge consumption. We suggest that a country should reshape its efficiency model by upgrading knowledge factor and human capital as the pre-requisite. Given the dilemmas of transition, China should take the faetorization trend of service sector and reshape efficiency model through institutional reform, ensuring that service sector will develop in tandem with industrial sector.展开更多
Three indexes including forest pest occurrence area,control area and input fund of 31 provinces from 2003 to 2014 were selected from Forestry Statistical Yearbook,to establish dynamic interaction index evaluation syst...Three indexes including forest pest occurrence area,control area and input fund of 31 provinces from 2003 to 2014 were selected from Forestry Statistical Yearbook,to establish dynamic interaction index evaluation system with clustering robust regression model and Stata 13. 0 software. Total forest pest control efficiency in China was determined according to the computing result of entropy method. Suggestions such as improving forest pest control efficiency,increasing service efficiency and input amount of forest pest control input funds were put forward. It will provide empirical basis for target management evaluation of forest pest control work and accountability system.展开更多
A new relative efficiency of parameter estimation for generalized Gauss-Markov linear model was proposed. Its lower bound was also derived. Its properties were explored in comparison with three currently very popular ...A new relative efficiency of parameter estimation for generalized Gauss-Markov linear model was proposed. Its lower bound was also derived. Its properties were explored in comparison with three currently very popular relative efficiencies. The new relative efficiency not only reflects sensitively the error and loss caused by the substitution of the least square estimator for the best linear unbiased estimator, but also overcomes the disadvantage of weak dependence on the design matrix.展开更多
The SDR-to-HDR translation technique can convert the abundant standard-dynamic-range (SDR) media resources to high-dynamic-range (HDR) ones, which can represent high-contrast scenes, providing more realistic visual ex...The SDR-to-HDR translation technique can convert the abundant standard-dynamic-range (SDR) media resources to high-dynamic-range (HDR) ones, which can represent high-contrast scenes, providing more realistic visual experiences. While recent vision Transformers have achieved promising performance in many low-level vision tasks, there are few works attempting to leverage Transformers for SDR-to-HDR translation. In this paper, we are among the first to investigate the performance of Transformers for SDR-to-HDR translation. We find that directly using the self-attention mechanism may involve artifacts in the results due to the inappropriate way to model long-range dependencies between the low-frequency and high-frequency components. Taking this into account, we advance the self-attention mechanism and present a dual frequency attention (DFA), which leverages the self-attention mechanism to separately encode the low-frequency structural information and high-frequency detail information. Based on the proposed DFA, we further design a multi-scale feature fusion network, named dual frequency Transformer (DFT), for efficient SDR-to-HDR translation. Extensive experiments on the HDRTV1K dataset demonstrate that our DFT can achieve better quantitative and qualitative performance than the recent state-of-the-art methods. The code of our DFT is made publicly available at https://github.com/CS-GangXu/DFT.展开更多
基金Under the auspices of the National Key Research and Development Program of China(No.2019YFA0606603)。
文摘Gross primary production(GPP)is a crucial indicator representing the absorption of atmospheric CO_(2) by vegetation.At present,the estimation of GPP by remote sensing is mainly based on leaf-related vegetation indexes and leaf-related biophysical para-meter leaf area index(LAI),which are not completely synchronized in seasonality with GPP.In this study,we proposed chlorophyll content-based light use efficiency model(CC-LUE)to improve GPP estimates,as chlorophyll is the direct site of photosynthesis,and only the light absorbed by chlorophyll is used in the photosynthetic process.The CC-LUE model is constructed by establishing a linear correlation between satellite-derived canopy chlorophyll content(Chlcanopy)and FPAR.This method was calibrated and validated utiliz-ing 7-d averaged in-situ GPP data from 14 eddy covariance flux towers covering deciduous broadleaf forest ecosystems across five dif-ferent climate zones.Results showed a relatively robust seasonal consistency between Chlcanopy with GPP in deciduous broadleaf forests under different climatic conditions.The CC-LUE model explained 88% of the in-situ GPP seasonality for all validation site-year and 56.0% of in-situ GPP variations through the growing season,outperforming the three widely used LUE models(MODIS-GPP algorithm,Vegetation Photosynthesis Model(VPM),and the eddy covariance-light use efficiency model(EC-LUE)).Additionally,the CC-LUE model(RMSE=0.50 g C/(m^(2)·d))significantly improved the underestimation of GPP during the growing season in semi-arid region,re-markably decreasing the root mean square error of averaged growing season GPP simulation and in-situ GPP by 75.4%,73.4%,and 37.5%,compared with MOD17(RMSE=2.03 g C/(m^(2)·d)),VPM(RMSE=1.88 g C/(m^(2)·d)),and EC-LUE(RMSE=0.80 g C/(m^(2)·d))model.The chlorophyll-based method proved superior in capturing the seasonal variations of GPP in forest ecosystems,thereby provid-ing the possibility of a more precise depiction of forest seasonal carbon uptake.
基金supported by NSFC under grant No. 61322111 and No. 61401249the National Basic Research Program of China (973 Program) No. 2013CB336600+1 种基金Specialized Research Fund for the Doctoral Program of Higher Education (SRFDP) under Grant No. 20130002120001Chuanxin Funding, and Beijing nova program No.Z121101002512051
文摘With the explosive growth and need for high-speed wireless communications, more and more energy is consumed to support the required quality of service. Therefore, energy efficient or green communication has become a very hot topic under the ground of limited energy resource and environmentally friendly transmission schemes. MIMO technique is capable of reducing the transmission power thanks to its diversity and multiplexing gain. Moreover, antenna selection(AS) is an alternative to extract many of the benefits in MIMO systems with a reduced cost of complexity and power. Although many works including several survey papers have investigated AS in MIMO systems, the goal of these works is only the capacity maximization or error rate minimization, which fails to guarantee the optimality of the energy efficiency in MIMO systems. In this paper, we overview the state of the art in the AS schemes in energy efficient MIMO systems, the goal of which is to optimize the energy efficiency of the whole system. Specifically, we introduce energy efficient AS in point-to-point MIMO, cooperative MIMO, multiuser MIMO and largescale MIMO systems, respectively. Several challenging and practical issues in this area are also addressed.
基金supported by the Ministry of Science and Technology of China (2014CB964803 and 2015AA020307)the National Natural Science Foundation of China (Nos. 31530048, 31601163 and 81672117)+1 种基金he Chinese Academy of Sciences (XDB19010204 and QYZDJ-SSW-SMC023)the Shanghai Municipal Commission for Science and Technology(16JC1420500, 17JC1400900 and 17140901500)
文摘Generation of mouse models carrying a defined point mutation,especially disease-related point mutations,is of considerable interest for research in biology and medicine.The standard method based on embryonic stem cell（ESC）-mediated homologous recombination（HR）is time-and labor-consuming.
基金Supported by the National Natural Science Foundation of China under Grant No 11774374the Natural Science Foundation of Shandong Province of China under Grant No ZR2016AL10
文摘We present an efficient three-dimensional coupled-mode model based on the Fourier synthesis technique. In principle, this model is a one-way model, and hence provides satisfactory accuracy for problems where the forward scattering dominates. At the same time, this model provides an efficiency gain of an order of magnitude or more over two-way coupled-mode models. This model can be applied to three-dimensional range-dependent problems with a slowly varying bathymetry or internal waves. A numerical example of the latter is demonstrated in this work. Comparisons of both accuracy and efficiency between the present model and a benchmark model are also provided.
基金Supported by National Natural Science Foundation of China(Grant No.51805447)Natural Science Foundation of Jiangsu Higher Education of China(Grant No.22KJB460010)+2 种基金Jiangsu Provincial Innovation and Promotion Project of Forestry Science and Technology of China(Grant No.LYKJ[2023]06)Yangzhou Science and Technology Plan(City School Cooperation Project)of China(Grant No.YZ2022193)Cyan Blue Project of Yangzhou University of China。
文摘In the realm of engineering practice,various factors such as limited availability of measurement data and complex working conditions pose significant challenges to obtaining accurate load spectra.Thus,accurately predicting the fatigue life of structures becomes notably arduous.This paper proposed an approach to predict the fatigue life of structure based on the optimized load spectra,which is accurately estimated by an efficient hinging hyperplane neural network(EHH-NN)model.The construction of the EHH-NN model includes initial network generation and parameter optimization.Through the combination of working conditions design,multi-body dynamics analysis and structural static mechanics analysis,the simulated load spectra of the structure are obtained.The simulated load spectra are taken as the input variables for the optimized EHH-NN model,while the measurement load spectra are used as the output variables.The prediction results of case structure indicate that the optimized EHH-NN model can achieve the high-accuracy load spectra,in comparison with support vector machine(SVM),random forest(RF)model and back propagation(BP)neural network.The error rate between the prediction values and the measurement values of the optimized EHH-NN model is 4.61%.In the Cauchy-Lorentz distribution,the absolute error data of 92%with EHH-NN model appear in the intermediate range of±1.65%.Also,the fatigue life analysis is performed for the case structure,based on the accurately predicted load spectra.The fatigue life of the case structure is calculated based on the comparison between the measured and predicted load spectra,with an accuracy of 93.56%.This research proposes the optimized EHH-NN model can more accurately reflect the measurement load spectra,enabling precise calculation of fatigue life.Additionally,the optimized EHH-NN model provides reliability assessment for industrial engineering equipment.
基金STS Project of CAS,No.KFJ-EW-STS-001National Natural Science Foundation of China,No.41430861
文摘With a continuously increasing population and better food consumption levels, im- proving the efficiency of arable land use and increasing its productivity have become funda- mental strategies to meet the growing food security needs in China. A spatial distribution map of medium- and low-yield cropland is necessary to implement plans for cropland improvement In this study, we developed a new method to identify high-, medium-, and low-yield cropland from Moderate Resolution Imaging Spectroradiometer （MODIS） data at a spatial resolution of 500 m. The method could be used to reflect the regional heterogeneity of cropland productiv- ity because the classification standard was based on the regionalization of cropping systems in China. The results showed that the proportion of high-, medium-, and low-yield cropland in China was 21%, 39%, and 40%, respectively. About 75% of the low-yield cropland was lo- cated in hilly and mountainous areas, and about 53% of the high-yield cropland was located in plain areas. The five provinces with the largest area of high-yield cropland were all located in the Huang-Huai-Hai region, and the area amounted to 42% of the national high-yield cropland area. Meanwhile, the proportion of high-yield cropland was lower than 15% in Hei- Iongjiang, Sichuan, and Inner Mongolia, which had the largest area allocated to cropland in China. If all the medium-yield cropland could be improved to the productive level of high-yield cropland and the low-yield cropland could be improved to the level of medium-yield cropland, the total productivity of the land would increase 19% and 24%, respectively.
基金funded by the National Natural Science Foundation of China (Grant No.41271421)the Humanities and Social Sciences Research Project of the Ministry of Education in China (Grant No. 10YJCZH156)
文摘Primary productivity of ecosystem is important indicator about ecological assessment. Remote sensing technology has been used to monitor net primary productivity （NPP） of ecological system for several years. In this paper, the remotely sensed NPP simulation model of alpine vegetation in Qinghai Province of Tibet Plateau was set up based on the theory of light use efficiency. Firstly a new approach based on mixed pixels and Support Vector Machine （SVM） algorithm were used to correct simulated NPP values derived from Moderate Resolution Imaging Spectroradiometer （MODIS） data. Finally, spatial distribution and monthly variation characteristics of NPP in Qinghai Province detail. The result showed in 2006 were analyzed in that NPP of vegetation in Qinghai Province in 2006 ranged from o to 422 gC/m2/a and the average NPP was 151 gC/m2/a. NPP gradually increased from northwest to southeast. NPP of different vegetation types were obviously different. The average NPP of broad-leaved forest was the largest （314 gC/m2/a）, and sparse shrub was the smallest （101 gC/m2/a）. NPP in Qinghai Province significantly changed with seasonal variation. The accumulation of NPP was primarily in the period （from April to September） with better moist and heat conditions. In July, the average NPP of vegetation reached the maximum value （43 gC/m2）. In our model, the advantage of traditional LUE models was adopted, and our study fully considered typicalcharacteristics of alpine vegetation light use efficiency and environmental factors in the study area. Alpine vegetation is the most important ecological resource of Tibet Plateau, exactly monitoring its NPP value by remote sensing is an effective protection measure.
基金supported by the National Natural Science Foundation of China(No.61801440)the High‐quality and Cutting‐edge Disciplines Construction Project for Universities in Beijing(Internet Information,Communication University of China),State Key Laboratory of Media Convergence and Communication(Communication University of China)the Fundamental Research Funds for the Central Universities(CUC2019B069).
文摘Many methods based on deep learning have achieved amazing results in image sentiment analysis.However,these existing methods usually pursue high accuracy,ignoring the effect on model training efficiency.Considering that when faced with large-scale sentiment analysis tasks,the high accuracy rate often requires long experimental time.In view of the weakness,a method that can greatly improve experimental efficiency with only small fluctuations in model accuracy is proposed,and singular value decomposition(SVD)is used to find the sparse feature of the image,which are sparse vectors with strong discriminativeness and effectively reduce redundant information;The authors propose the Fast Dictionary Learning algorithm(FDL),which can combine neural network with sparse representation.This method is based on K-Singular Value Decomposition,and through iteration,it can effectively reduce the calculation time and greatly improve the training efficiency in the case of small fluctuation of accuracy.Moreover,the effectiveness of the proposed method is evaluated on the FER2013 dataset.By adding singular value decomposition,the accuracy of the test suite increased by 0.53%,and the total experiment time was shortened by 8.2%;Fast Dictionary Learning shortened the total experiment time by 36.3%.
基金This study is supported by key projects of the National Social Science Fund of China （NSSFC） ＂Study on Accelerating Economic Restructuring and Promoting Indigenous and Coordinated Economic Development＂ （Grant No. 12＆ZD084）, and ＂Strategic Adjustment of China＇s Economic Structure and Transformation of Growth Pattern＂ （Grant No. 06＆ZD004）.
文摘Over the past 40 years of reform and opening-up during 1978-2018, China ＇S rapid economic growth has become a miracle in world economic history and reshaped the world economy. In the 40 years, China has successfully transformed from an isolated agricultural country into the world＇s largest industrial manufacturer. In 2018, China＇s urbanization rate is expected to reach 60% with per capita GDP expected to reach 9, 000 USD. After another 5 to 8 years, China will join the rank of high-income countries, successfully cross the middle-income trap and become a moderately prosperous economy in all respects. In its modernization drive, China will follow the new concept of ＂innovation, coordinated, green, open and shared development＂ and strive to achieve its ＂two centennial
基金Sponsored by National Natural Science Foundation of China (51075353)Hebei Natural Science Foundation of China (E2010001208)
文摘In order to simulate and analyze hot strip crown and flatness accurately and efficiently, the 3-D （three-di- mensional） coupled model involved in RPFEM （rigid-plastic finite element method） is improved based on the analyti- cal model of forecasting rolling force distribution. In the analytical model, variational method is employed to solve the lateral flow of metal and influential function method is employed to calculate roll deflection, the lateral distribution of rolling force can be obtained rapidly by iterative strategy. Then the 3-D coupled model uses the result as initial distri- bution of rolling force to calculate roll deflection and makes the initial on-load roll gap profile close to the final value, so as to reduce iterations and increase efficiency. Compared with previous algorithms, the improved model can reduce the iterations by about 50% and shorten the computing time by about 60% on the basis of the calculation accuracy.
基金supported by US-China Clean Energy Research Collaboration:Collaboration on Cutting-edge Technology Development of Electric Vehicle(Program of International S&T Cooperation,Grant No.2010DFA72760)
文摘The existing research of the acceleration control mainly focuses on an optimization of the velocity trajectory with respect to a criterion formulation that weights acceleration time and fuel consumption. The minimum-fuel acceleration problem in conventional vehicle has been solved by Pontryagin＇s maximum principle and dynamic programming algorithm, respectively. The acceleration control with minimum energy consumption for battery electric vehicle（EV） has not been reported. In this paper, the permanent magnet synchronous motor（PMSM） is controlled by the field oriented control（FOC） method and the electric drive system for the EV（including the PMSM, the inverter and the battery） is modeled to favor over a detailed consumption map. The analytical algorithm is proposed to analyze the optimal acceleration control and the optimal torque versus speed curve in the acceleration process is obtained. Considering the acceleration time, a penalty function is introduced to realize a fast vehicle speed tracking. The optimal acceleration control is also addressed with dynamic programming（DP）. This method can solve the optimal acceleration problem with precise time constraint, but it consumes a large amount of computation time. The EV used in simulation and experiment is a four-wheel hub motor drive electric vehicle. The simulation and experimental results show that the required battery energy has little difference between the acceleration control solved by analytical algorithm and that solved by DP, and is greatly reduced comparing with the constant pedal opening acceleration. The proposed analytical and DP algorithms can minimize the energy consumption in EV＇s acceleration process and the analytical algorithm is easy to be implemented in real-time control.
基金supported by the Natural Science Foundation of China (No.41401044 and No.41310013)the key research projects of frontier sciences CAS (QYZDJ-SSW-DQC006)+1 种基金the Chinese Academy of Science (‘West Star’ project)the CAS/SAFEA international partnership program for creative research teams (KZZD-EW-TZ-06)
文摘Abies fabri is a typical subalpine dark coniferous forest in southwestern China. Air temperature increases more at high elevation areas than that at low elevation areas in mountainous regions,and climate change ratio is also uneven in different seasons. Carbon gain and the response of water use efficiency(WUE) to annual and seasonal increases in temperature with or without CO_2 fertilization were simulated in Abies fabri using the atmospheric-vegetation interaction model(AVIM2). Four future climate scenarios(RCP2.6,RCP4.5,RCP6.0 and RCP8.5) from the Coupled Model Intercomparison Project Phase 5(CMIP5) were selectively investigated. The results showed that warmer temperatures have negative effects on gross primary production(GPP) and net primary production(NPP) in growing seasons and positive effects in dormant seasons due to the variation in the leaf area index. Warmer temperatures tend to generate lower canopy WUE and higher ecosystem WUE in Abies fabri. However,warmer temperature together with rising CO_2 concentrations significantlyincrease the GPP and NPP in both growing and dormant seasons and enhance WUE in annual and dormant seasons because of the higher leaf area index(LAI) and soil temperature. The comparison of the simulated results with and without CO_2 fertilization shows that CO_2 has the potential to partially alleviate the adverse effects of climate warming on carbon gain and WUE in subalpine coniferous forests.
文摘Recovering waste heat from industrial processes is bene ficial in order to reduce the primary energy demands and heat pumps can be used to this purpose.Absorption heat pumps are energy-saving and environment-friendly because use working fluids that do not cause ozone depletion and can reduce the global warming emissions.The hybrid heat pump processes combine the conventional vapor-compression and the absorption heat pump cycles.Studies about the simulations and modeling of hybrid heat pumps are few in literature.In this research a mathematical model for single effect absorption and hybrid heat pump is carried out with Chem Cad? 6.0.1.LiBr–H_2O is used as working fluid while electrolytic NRTL and electrolytes latent heat are used as thermodynamic model due to the better results.Binary parameters of activity coef ficients are regressed from experimental vapor pressure data while default constants are used for the solubility expressions.A design of heat pumps is developed and a new modeling of generator is analyzed.The coef ficient of performance of absorption heat pump and hybrid heat pump is equal to 0.7 and 0.83 respectively.For absorption heat pump a sensitivity analysis is carried out to evaluate the effect of temperature and pressure generator,the concentration of Li–Br solution on coef ficient of performance,cooling capacity and working fluid temperature.For hybrid heat pump,the different coef ficients of performance,the primary energy ratio,the generator heat,and the compressor power are analyzed for different values of compressor proportion.Results show that comparing the two systems the hybrid pump allows to save more primary energy,costs and carbon dioxide emissions with respect to absorption heat pump with the increasing of compressor proportion parameter.Future researches should focus on the construction of this heat pumps integrated in chemical processes as a biogas plant or trigeneration systems.
基金supported by National Basic Research Program of China (NO 2012CB316002)China’s 863 Project (NO 2014AA01A703)+2 种基金National Major Projec (NO. 2014ZX03003002-002)Program for New Century Excellent Talents in University (NCET-13-0321)Tsinghua University Initiative Scientific Research Program (2011THZ02-2)
文摘It is extensively approved that Channel State Information(CSI) plays an important role for synergetic transmission and interference management. However, pilot overhead to obtain CSI with enough precision is a significant issue for wireless communication networks with massive antennas and ultra-dense cell. This paper proposes a learning- based channel model, which can estimate, refine, and manage CSI for a synergetic transmission system. It decomposes the channel impulse response into multiple paths, and uses a learning-based algorithm to estimate paths' parameters without notable degradation caused by sparse pilots. Both indoor measurement and outdoor measurement are conducted to verify the feasibility of the proposed channel model preliminarily.
文摘The performance of a 3-phase 6-pole 400 W inverter-drive induction motor was investigated using a variety of non-oriented electrical steels for stator core at PWM inverter fundamental wave frequencies of 30 to 300 Hz. There existed an optimum Si content of the material depending on the tooth flux density. Both reduction of material thickness and stress-relief annealing of the stator core improved the motor efficiency. The influence of Si content on the efficiency was small at lower PWM frequencies, while at higher frequencies the motor efficiency increased with increasing Si content. The Cu loss WC increased and the Fe loss Wi counteractiveiy decreasedwith increasing Si content at lower frequencies; while at higher frequencies Wi had dominant effect on the efficiency. Newly developed materials RMA, having lower Fe losses after stress-relief annealing and higher flux densities with lower Si contents, showed motor efficiencies superior to conventional J1S grade materials with comparable Fe losses.
基金sponsored by major tendering projects of National Social Sciences Foundation "Study on Accelerating Economic Adjustment and Coordinated Development"(Grant No.12&ZD084) and "Study on Contribution of Consumption to Economic Growth under Shifting Demand Structure"(Grant No.15ZDC011)projects of National Social Sciences Foundation "Study on China's Structural Growth Deceleration,Transition Risks and Efficiency Improvement Path"(Grant No.14AJL006) and "Study on the Scale,Spatial Clustering and Management Model of Chinese Cities"(Grant No.15ZDC011)
文摘The transition from middle-income to high-income stage is fraught with risks of growth divergence. Economic transition is clouded by the following possibilities： （1）falling share of industrial seetor through industrial depression and weakening growth momentum caused by the large urbanization costs; （2） the subordination of service sector as a result of nearly irreversibly industrial professional, which falters the process of service sector transition and upgrading,＂ （3） inefficient knowledge production allocation and human capital upgrade due to the absence of incentivized compensation of knowledge consumption. We suggest that a country should reshape its efficiency model by upgrading knowledge factor and human capital as the pre-requisite. Given the dilemmas of transition, China should take the faetorization trend of service sector and reshape efficiency model through institutional reform, ensuring that service sector will develop in tandem with industrial sector.
基金Supported by Analysis of Forest Pest Cost Responsibility Investigation System(2017-R04)Protection and Development:Coordination Mechanism Research from the Perspective of Community(71373024)
文摘Three indexes including forest pest occurrence area,control area and input fund of 31 provinces from 2003 to 2014 were selected from Forestry Statistical Yearbook,to establish dynamic interaction index evaluation system with clustering robust regression model and Stata 13. 0 software. Total forest pest control efficiency in China was determined according to the computing result of entropy method. Suggestions such as improving forest pest control efficiency,increasing service efficiency and input amount of forest pest control input funds were put forward. It will provide empirical basis for target management evaluation of forest pest control work and accountability system.
文摘A new relative efficiency of parameter estimation for generalized Gauss-Markov linear model was proposed. Its lower bound was also derived. Its properties were explored in comparison with three currently very popular relative efficiencies. The new relative efficiency not only reflects sensitively the error and loss caused by the substitution of the least square estimator for the best linear unbiased estimator, but also overcomes the disadvantage of weak dependence on the design matrix.
基金supported by National Natural Science Foundation of China(Nos.61922046 and 62276145)the National Key Research and Development Program of China(No.2018AAA0100400)Fundamental Research Funds for Central Universities,China(No.63223049).
文摘The SDR-to-HDR translation technique can convert the abundant standard-dynamic-range (SDR) media resources to high-dynamic-range (HDR) ones, which can represent high-contrast scenes, providing more realistic visual experiences. While recent vision Transformers have achieved promising performance in many low-level vision tasks, there are few works attempting to leverage Transformers for SDR-to-HDR translation. In this paper, we are among the first to investigate the performance of Transformers for SDR-to-HDR translation. We find that directly using the self-attention mechanism may involve artifacts in the results due to the inappropriate way to model long-range dependencies between the low-frequency and high-frequency components. Taking this into account, we advance the self-attention mechanism and present a dual frequency attention (DFA), which leverages the self-attention mechanism to separately encode the low-frequency structural information and high-frequency detail information. Based on the proposed DFA, we further design a multi-scale feature fusion network, named dual frequency Transformer (DFT), for efficient SDR-to-HDR translation. Extensive experiments on the HDRTV1K dataset demonstrate that our DFT can achieve better quantitative and qualitative performance than the recent state-of-the-art methods. The code of our DFT is made publicly available at https://github.com/CS-GangXu/DFT.
