Effect of climate change on seasonal water use efficiency in subalpine Abies fabri

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.

Efficiency of Model Induction Motor Using Various Non-Oriented Electrical Steels

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.

Crossing the Growth Threshold： Service-Based Economy, Knowledge Process and Reshaping of Efficiency Model

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.

A new relative efficiency in parameter estimation for linear model

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.

Empirical Analysis of Forest Pest Control Efficiency from 2003 to 2014 in China

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.

Research on image sentiment analysis technology based on sparse representation

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%.

Simulating Alpine Vegetation Net Primary Productivity by Remote Sensing in Qinghai Province,China

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.

China＇s Economic Growth and Structural Transition since 1978

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

Invited Paper: Antenna Selection in Energy Efficient MIMO Systems: A Survey

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.

Torque-based Optimal Acceleration Control for Electric Vehicle

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.

A Learning-Based Channel Model for Synergetic Transmission Technology

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.

Mathematical model of absorption and hybrid heat pump

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.

An Efficient Three-Dimensional Coupled Normal Mode Model and Its Application to Internal Solitary Wave Problems

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.

Dual Frequency Transformer for Efficient SDR-to-HDR Translation

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.

Simulating dispatchable grid services provided by flexible building loads:State of the art and needed building energy modeling improvements

End-use electrical loads in residential and commercial buildings are evolving into flexible and cost-effective resources to improve electric grid reliability,reduce costs,and support increased hosting of distributed renewable generation.This article reviews the simulation of utility services delivered by buildings for the purpose of electric grid operational modeling.We consider services delivered to(1)the high-voitage bulk power system through the coordinated action of many,distributed building loads working together,and(2)targeted support provided to the operation of low-voltage electric distribution grids.Although an exhaustive exploration is not possible,we emphasize the ancillary services and voltage management buildings can provide and summarize the gaps in our ability to simulate them with traditional building energy modeling(BEM)tools,suggesting pathways for future research and development.

An Analysis of Energy and Environment Efficiency of China＇s Iron and Steel Industry

Due to heavy energy consumption and low technical efficiency, China＇s iron and steel industry is trapped in the dilemma ＂large but not strong＂. This situation not only exerts enormous pressure on energy security but also on increased carbon emission and environmental pollution. The contribution of this study is to calculate the energy and environment efficiency of China＇s iron and steel industry and to analyze the factors affecting this efficiency. An index of energy and environment efficiency is introduced based on Directional Slacks-based Distance Measure Model. This index is adopted to measure the energy and environment efficiency of China＇s iron and steel industry using 2,382 firm observations during 2001 to 2005. In addition, Hierarchy Linear Model （HLM） is applied to analyze the factors which can influence the efficiency with both firm-level and province-level data. The conclusions are as follows： The energy and environment efficiency of China＇s iron and steel industry did not have a significant change during the research period. A firm＇s age, size, ownership, product category and the economy of its province have significant influence on its energy and environment efficiency.

The Comprehensive Efficiency and Diverse Models of a Traditional Street

This article discusses its cultural background, its comprehen-sive efficiency and diverse models and problems noteworthy in de-sign. In recent years, the traditional-styled street (hereinafter re-ferred to as traditional street) of has emerged in China. Some wererenovated, some newly built, some imitated ancient styles andothers were restored to what they were before (restored to whatthey were in the initial period of or before liberation), the construc-tion techniques were different, but their aims were similar.However, different people have expressed different opinions aboutthis, some praised it, others censured it, so the public opinions arenot uniform. For example, a ribbon-cutting ceremony was held inTianjin for the renovation of the Ancient Cultural Street near theTianhou Palace in Tianjin, the news was played up by local news-papers, it was really a scene of bustle and excitement, people in theconstruction circle, however, made no reaction to it....This culturalstreet on which the construction circle made no comments is to theliking of ordinary local people. This street is seething with activitywith people bustling about all the year round. As reactions to thematter are so sharply contrast, how can the matter be regarded asunimportant. It’s better for the construction circle to probe, from va-rious angles, into the mechanism for the emergence of the tradition-al street and ways for its development than to evade the matter.

Deep Gradient Learning for Efficient Camouflaged Object Detection

This paper introduces deep gradient network(DGNet),a novel deep framework that exploits object gradient supervision for camouflaged object detection(COD).It decouples the task into two connected branches,i.e.,a context and a texture encoder.The es-sential connection is the gradient-induced transition,representing a soft grouping between context and texture features.Benefiting from the simple but efficient framework,DGNet outperforms existing state-of-the-art COD models by a large margin.Notably,our efficient version,DGNet-S,runs in real-time(80 fps)and achieves comparable results to the cutting-edge model JCSOD-CVPR21 with only 6.82%parameters.The application results also show that the proposed DGNet performs well in the polyp segmentation,defect detec-tion,and transparent object segmentation tasks.The code will be made available at https://github.com/GewelsJI/DGNet.

Experimental study on filtration performance of the moving bed granular filter with axial flow

The filtration performance of the moving bed granular filter with axial flow (MBGF-AF) is investigated through a large cold experiment. The effect of different operation parameters on the filtration performance (collection efficiency, pressure drop) of the axial-flow moving bed filter is investigated in combination with the dust deposition effect and the mechanism of trapping dust by the capturing particles. The results show that the collection efficiency of MBGF-AF is enhanced by decreasing the superficial gas velocity, increasing the inlet dust concentration properly, or decreasing the moving velocity of the capturing particles. A model covering the above operation parameters is established to calculate the collection efficiency of the moving bed granular filter. It is used in a wide range of operating parameters for the MBGFs.

Predicting effect factors of dual bag filter system for PCDD/Fs removal from hazardous waste incineration flue gas

The dual bag filter(DBF)system is a new polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans(PCDD/Fs)emission control technology that has more efficient(PCDD/Fs)removal performance,a higher activated carbon utilization rate and less activated carbon consumption compared with the traditional single bag filter system.Moreover,few studies have been relevant to the mechanism of the PCDD/Fs removal process in the DBF system,and the selection of operating conditions of the DBF system lacks an academic basis.This study established a PCDD/Fs removal efficiency model of activated carbon injection combined bag filter(ACI+DBF)system for hazardous waste incineration flue gas and predicted the crucial effect factors.New adsorption coefficients k_(1)=532,145 Nm^(3)/(mol s)and k_(2)=45 Nm^(3)/(mol s),and the relationship expression between the number of available adsorption positions of recycled AC(AAC′)and cycle times(n)are proposed in the model.The results verify that the model error was below 5%.In addition,the PCDD/Fs removal efficiency model predicts that in a certain range,the PCDD/Fs removal efficiency increases with increasing activated carbon injection concentration.The best cycle number of activated carbon was less than 3,and the ratio of circulating activated carbon to fresh activated carbon in second bag filter(SBF)should be controlled at 7–8.