Improving the Accuracy of Vegetation Index Retrieval for Biomass by Combining Ground-UAV Hyperspectral Data-A New Method for Inner Mongolia Typical Grasslands

Grassland biomass is an important parameter of grassland ecosystems.The complexity of the grassland canopy vegetation spectrum makes the long-term assessment of grassland growth a challenge.Few studies have explored the original spectral information of typical grasslands in Inner Mongolia and examined the influence of spectral information on aboveground biomass(AGB)estimation.In order to improve the accuracy of vegetation index inversion of grassland AGB,this study combined ground and Unmanned Aerial Vehicle(UAV)remote sensing technology and screened sensitive bands through ground hyperspectral data transformation and correlation analysis.The narrow band vegetation indices were calculated,and ground and airborne hyperspectral inversion models were established.Finally,the accuracy of the model was verified.The results showed that:(1)The vegetation indices constructed based on the ASD FieldSpec 4 and the UAV were significantly correlated with the dry and fresh weight of AGB.(2)The comparison between measured R^(2) with the prediction R^(2) indicated that the accuracy of the model was the best when using the Soil-Adjusted Vegetation Index(SAVI)as the independent variable in the analysis of AGB(fresh weight/dry weight)and four narrow-band vegetation indices.The SAVI vegetation index showed better applicability for biomass monitoring in typical grassland areas of Inner Mongolia.(3)The obtained ground and airborne hyperspectral data with the optimal vegetation index suggested that the dry weight of AGB has the best fitting effect with airborne hyperspectral data,where y=17.962e^(4.672x),the fitting R^(2) was 0.542,the prediction R^(2)was 0.424,and RMSE and REE were 57.03 and 0.65,respectively.Therefore,established vegetation indices by screening sensitive bands through hyperspectral feature analysis can significantly improve the inversion accuracy of typical grassland biomass in Inner Mongolia.Compared with ground monitoring,airborne hyperspectral monitoring better reflects the inversion of actual surface biomass.It provides a reliable modeling framework for grassland AGB monitoring and scientific and technological support for grazing management.

Solubility of iron(Ⅲ) and nickel(Ⅱ) acetylacetonates in supercritical carbon dioxide

As a common precursor for supercritical CO_(2)(scCO_(2))deposition techniques,solubility data of organometallic complexes in scCO_(2)is crucial for the preparation of nanocomposites.Recently,metal acetylacetonates have shown great potential for the preparation of single-atom catalytic materials.In this study,the solubilities of iron(Ⅲ)acetylacetonate(Fe(acac)3)and nickel(Ⅱ)acetylacetonate(Ni(acac)2)were measured at the temperature from 313.15 to 333.15 K and in the pressure range of 9.5–25.2 MPa to accumulate new solubility data.Solubility was measured using a static weight loss method.The semi-empirical models proposed by Chrastil and Sung et al.were used to correlate the solubility data of Fe(acac)3 and Ni(acac)2.The equations obtained can be used to predict the solubility of the same system in the experimental range.

Multiscale Study on Low Temperature Crack Resistance Mechanism of Steel Slag Asphalt Mixture

The objective of this paper was to study low temperature crack resistance mechanism of steel slag asphalt mixture(SAM).Thermal stress restrained specimen test(TSRST)and three-point bending test were carried out to evaluate the low-temperature crack resistance of SAM and basalt asphalt mixture(BAM).Based on the digital image correlation technique(DIC),the strain field distribution and crack propagation of SAM were analyzed from the microscopic point of view,and a new index,crack length factor(C),was proposed to evaluate the crack resistance of the asphalt mixture.The crystal phase composition and microstructure of steel slag aggregate(SA)and basalt aggregate(BA)were studied by X-ray diffraction(XRD)and scanning electron microscopy(SEM)to explore the low-temperature crack resistance mechanism of SAM.Results show that the low-temperature crack resistance of SAM is better than that of BAM;SAM has good integrity and persistent elastic deformation,and its bending failure mode is a hysteretic quasi-brittle failure;The SA surface is evenly distributed with pores and has surface roughness.SA has the composition phase of alkaline aggregate-calcite(CaCO3),so it has good adhesion to asphalt,which reveals the mechanism of excellent low-temperature crack resistance of SAM.

Efficient hydrogenolysis of fructose to 1,2-propanediol over bifunctional Ru-WO_(x)-MgO_(y) catalysts under mild reaction conditions via enhancing the chemoselective cleavage of C-C bonds

Selective conversion of fructose to 1,2-propanediol(1,2-PDO)is considered as a sustainable and cost-effective alternative to petroleum-based processes,however,this approach still faces challenges associated with low efficiency and harsh reaction conditions.Here,we have successfully synthesized a novel bifunctional Ru-WO_(x)-MgO_(y) catalyst through a facile'one-pot'solvothermal method.Remarkably,this catalyst exhibits exceptional catalytic performances in the conversion of fructose to 1,2-PDO under mild reaction conditions.The yield of 1,2-PDO is up to 56.2%at 140°C for 4 h under an ultra-low hydrogen pressure of only 0.2 MPa,surpassing the reported results in recent literature(below 51%).Comprehensive characterizations and density functional theory(DFT)calculations reveal that the presence of oxygen vacancies in the Ru-WO_(x)-MgO_(y) catalyst,serving as active acidic sites,facilitates the chemoselective cleavage of C-C bonds in fructose,which leads to the generation of active intermediates and ultimately resulted in the high yield of 1,2-PDO.

Bending results of graphene origami reinforced doubly curved shell

The present work investigates higher order stress,strain and deformation analyses of a shear deformable doubly curved shell manufactures by a Copper(Cu)core reinforced with graphene origami auxetic metamaterial subjected to mechanical and thermal loads.The effective material properties of the graphene origami auxetic reinforced Cu matrix are developed using micromechanical models cooperate both material properties of graphene and Cu in terms of temperature,volume fraction and folding degree.The principle of virtual work is used to derive governing equations with accounting thermal loading.The numerical results are analytically obtained using Navier's technique to investigate impact of significant parameters such as thermal loading,graphene amount,folding degree and directional coordinate on the stress,strain and deformation responses of the structure.The graphene origami materials may be used in aerospace vehicles and structures and defence technology because of their low weight and high stiffness.A verification study is presented for approving the formulation,solution methodology and numerical results.

An Overview of Sequential Approximation in Topology Optimization of Continuum Structure

This paper offers an extensive overview of the utilization of sequential approximate optimization approaches in the context of numerically simulated large-scale continuum structures.These structures,commonly encountered in engineering applications,often involve complex objective and constraint functions that cannot be readily expressed as explicit functions of the design variables.As a result,sequential approximation techniques have emerged as the preferred strategy for addressing a wide array of topology optimization challenges.Over the past several decades,topology optimization methods have been advanced remarkably and successfully applied to solve engineering problems incorporating diverse physical backgrounds.In comparison to the large-scale equation solution,sensitivity analysis,graphics post-processing,etc.,the progress of the sequential approximation functions and their corresponding optimizersmake sluggish progress.Researchers,particularly novices,pay special attention to their difficulties with a particular problem.Thus,this paper provides an overview of sequential approximation functions,related literature on topology optimization methods,and their applications.Starting from optimality criteria and sequential linear programming,the other sequential approximate optimizations are introduced by employing Taylor expansion and intervening variables.In addition,recent advancements have led to the emergence of approaches such as Augmented Lagrange,sequential approximate integer,and non-gradient approximation are also introduced.By highlighting real-world applications and case studies,the paper not only demonstrates the practical relevance of these methods but also underscores the need for continued exploration in this area.Furthermore,to provide a comprehensive overview,this paper offers several novel developments that aim to illuminate potential directions for future research.

Impact of Blade-Flapping Vibration on Aerodynamic Characteristics of Wind Turbines under Yaw Conditions

Although the aerodynamic loading of wind turbine blades under various conditions has been widely studied,the radial distribution of load along the blade under various yaw conditions and with blade flapping phenomena is poorly understood.This study aims to investigate the effects of second-order flapwise vibration on the mean and fluctuation characteristics of the torque and axial thrust of wind turbines under yaw conditions using computational fluid dynamics(CFD).In the CFD model,the blades are segmented radially to comprehensively analyze the distribution patterns of torque,axial load,and tangential load.The following results are obtained.(i)After applying flapwise vibration,the torque and axial thrust of wind turbines decrease in relation to those of the rigid model,with significantly increased fluctuations.(ii)Flapwise vibration causes the blades to reciprocate along the axial direction,altering the local angle of attack and velocity of the blades relative to the incoming wind flow.This results in the contraction of the torque region from a circular shape to a complex“gear”shape,which is accompanied by evident oscillations.(iii)Compared to the tangential load,the axial load on the blades is more sensitive to flapwise vibration although both exhibit significantly enhanced fluctuations.This study not only reveals the impact of flapwise vibration on wind turbine blade performance,including the reduction of torque and axial thrust and increased operational fluctuations,but also clarifies the radial distribution patterns of blade aerodynamic characteristics,which is of great significance for optimizing wind turbine blade design and reducing fatigue risks.

Research on the Icing Diagnosis ofWind Turbine Blades Based on FS–XGBoost–EWMA

In winter,wind turbines are susceptible to blade icing,which results in a series of energy losses and safe operation problems.Therefore,blade icing detection has become a top priority.Conventional methods primarily rely on sensor monitoring,which is expensive and has limited applications.Data-driven blade icing detection methods have become feasible with the development of artificial intelligence.However,the data-driven method is plagued by limited training samples and icing samples;therefore,this paper proposes an icing warning strategy based on the combination of feature selection(FS),eXtreme Gradient Boosting(XGBoost)algorithm,and exponentially weighted moving average(EWMA)analysis.In the training phase,FS is performed using correlation analysis to eliminate redundant features,and the XGBoost algorithm is applied to learn the hidden effective information in supervisory control and data acquisition analysis(SCADA)data to build a normal behavior model.In the online monitoring phase,an EWMA analysis is introduced to monitor the abnormal changes in features.A blade icing warning is issued when themonitored features continuously exceed the control limit,and the ambient temperature is below 0℃.This study uses data fromthree icing-affected wind turbines and one normally operating wind turbine for validation.The experimental results reveal that the strategy can promptly predict the icing trend among wind turbines and stably monitor the normally operating wind turbines.

Optimal Operation Strategy of Electricity-Hydrogen Regional Energy System under Carbon-Electricity Market Trading

Given the“double carbon”objective and the drive toward low-carbon power,investigating the integration and interaction within the carbon-electricity market can enhance renewable energy utilization and facilitate energy conservation and emission reduction endeavors.However,further research is necessary to explore operational optimization methods for establishing a regional energy system using Power-to-Hydrogen(P2H)technology,focusing on participating in combined carbon-electricity market transactions.This study introduces an innovative Electro-Hydrogen Regional Energy System(EHRES)in this context.This system integrates renewable energy sources,a P2H system,cogeneration units,and energy storage devices.The core purpose of this integration is to optimize renewable energy utilization and minimize carbon emissions.This study aims to formulate an optimal operational strategy for EHRES,enabling its dynamic engagement in carbon-electricity market transactions.The initial phase entails establishing the technological framework of the electricity-hydrogen coupling system integrated with P2H.Subsequently,an analysis is conducted to examine the operational mode of EHRES as it participates in carbon-electricity market transactions.Additionally,the system scheduling model includes a stepped carbon trading price mechanism,considering the combined heat and power generation characteristics of the Hydrogen Fuel Cell(HFC).This facilitates the establishment of an optimal operational model for EHRES,aiming to minimize the overall operating cost.The simulation example illustrates that the coordinated operation of EHRES in carbon-electricity market transactions holds the potential to improve renewable energy utilization and reduce the overall system cost.This result carries significant implications for attaining advantages in both low-carbon and economic aspects.

Impacts of Sand and Dust Storms on Regional Economy Based on Stochastic CGE Model : A Case Study in Inner Mongolia, China

[Objectives]The paper was to study the impacts of sand and dust storms(SDS)on regional economy.[Methods]In this paper,we combined the computable general equilibrium(CGE)model and the Monte Carlo method to examine the impact of SDS on the regional economy,with a focus on GDP,price index,employment rate,industrial structure and output,income and expenditure.We extended the standard CGE model,introduced the stochastic parameters into the production module,which had significant impact on economic output,and inserted the rate of change of the total labor supply and the expenditure share of early warning and protective measures into the income and expenditure module.[Results]SDS had significant impacts on regional GDP,employment rate,and industrial output from a macro perspective,and can reduce the income of residents and enterprises and increase expenditures from a micro perspective.The impact can be reduced by taking early warning and protective measures.[Conclusions]The protective measures taken for different grades of SDS have different effects.

Research Progress in Preparation of Oxidized Cellulose

Cellulose is the most abundant natural polymer material in the world.Cellulose is diffi-cult to dissolve because it contains a large number of inter molecular hydrogen bonds.Therefore,the modification of natural cellulose by chemical oxidation can expand its application field.The oxidation process of cellulose is focused on,the oxidation methods and research progress of cellulose are introduced,and further development direction of oxidized cellulose is prospected.

FEM analysis of metal flowing behaviors in porthole die extrusion based on the mesh reconstruction technology of the welding process

A reconstruction technology of finite element meshes based on reversal engineering was applied to solve mesh penetration and separation in the finite element simulation for the divergent extrusion. The 3D numerical simulation of the divergent extrusion process in- cluding the welding stage for complicated hollow sections was conducted. Based on the analysis of flowing behaviors, the flowing velocities of the alloy in portholes and near the welding planes were properly controlled through optimizing the expansion angle as well as porthole ar- eas and positions. After the die structure optimization, defects such as warp, wrist, and the wavelike are eliminated, which improves the sec- tion-forming quality. Meanwhile, the temperature distribution in the cross section is uniform. Especially, the temperature of the C-shape notch with a larger thickness is lower than that of other regions in the cross section, which is beneficial for balancing the alloy flowing velocity.

Research on University’s Cyber Threat Intelligence Sharing Platform Based on New Types of STIX and TAXII Standards

With the systematization of cyber threats, the variety of intrusion tools and intrusion methods has greatly reduced the cost of attackers’ threats to network security. Due to a large number of colleges and universities, teachers and students are highly educated and the Internet access rate is nearly 100%. The social status makes the university network become the main target of threat. The traditional defense method cannot cope with the current complex network attacks. In order to solve this problem, the threat intelligence sharing platform based on various threat intelligence sharing standards is established, which STIX and TAXII It is a widely used sharing standard in various sharing platforms. This paper analyzes the existing standards of STIX and TAXII, improves the STIX and TAXII standards based on the analysis results, and proposes a new type of STIX and TAXII based on the improved results. The standard design scheme of threat intelligence sharing platform suitable for college network environment features. The experimental results show that the threat intelligence sharing platform designed in this paper can be effectively applied to the network environment of colleges and universities.

Pea-like MoS_(2)@NiS_(1.03)-carbon heterostructured hollow nanofibers for high-performance sodium storage

The rational synergy of chemical composition and spatial nanostructures of electrode materials play important roles in high-performance energy storage devices.Here,we designed pea-like MoS_(2)@NiS_(1.03)-carbon hollow nanofibers using a simple electrospinning and thermal treatment method.The hierarchical hollow nanofiber is composed of a nitrogen-doped carbon-coated NiS_(1.03) tube wall,in which pea-like uniformly discrete MoS_(2) nanoparticles are enclosed.As a sodium-ion battery electrode material,the MoS_(2)@NiS_(1.03)-carbon hollow nanofibers have abundant diphasic heterointerfaces,a conductive network,and appropriate volume variation-buffering spaces,which can facilitate ion diffusion kinetics,shorten the diffusion path of electrons/ion,and buffer volume expansion during Na^(+)insertion/extraction.It shows outstanding rate capacity and long-cycle performance in a sodium-ion battery.This heterogeneous hollow nanoarchitectures designing enlightens an efficacious strategy to boost the capacity and long-life stability of sodium storage performance of electrode materials.

Extraction of Strain Characteristic Signals from Wind Turbine Blades Based on EEMD-WT

Analyzing the strain signal of wind turbine blade is the key to studying the load of wind turbine blade,so as to ensure the safe and stable operation of wind turbine in natural environment.The strain signal of the wind turbine blade under continuous crosswind state has typical non-stationary and unsteady characteristics.The strain signal contains a lot of noise,which makes the analysis error.Therefore,it is very important to denoise and extract features of measured signals before signal analysis.In this paper,the joint algorithm of ensemble empirical mode decomposition(EEMD)and wavelet transform(WT)is used for the first time to achieve sufficient noise reduction and effectively extract the feature signals of non-stationary strain signals.The application process of EEMD-WT is optimized.This optimization can avoid the repeated selection of wavelet basis function and the number of decomposition layers due to different crosswind conditions.EEMD adaptively decomposes the strain signal into intrinsic mode functions,to judge the frequency of IMFs,remove the high-frequency noise components,retain the useful components.The useful components are denoised twice by the wavelet transform,the components and residual terms after the secondary denoising are reconstructed to obtain the characteristic signal.The EEMD-WT was applied to process the simulating signals andmeasured the strain signals.The results were compared with the results of the EEMD.The results showed that the EEMD-WTmethod has better noise reduction performance,and can effectively extract the characteristics of strain signals,which lays a solid foundation for accurate analysis of wind turbine blade strain signals under crosswind conditions.

Design of Campus Wetland Landscapes: A Case Study of the Bailuxi Wetland of University of Sanya in Sanya, Hainan, China

In this paper, the landscape design of the Bailuxi Wetland in University of Sanya was studied by using the research method of “survey—analysis—design”. The questionnaire survey, field observation and landscape pattern analysis were used to analyze the landscape pattern of the Bailuxi Wetland as well as the characteristics and problems of the six subsystems of green space, activity, road, animal, plant, and sound. Then the overall structure and function design of the Bailuxi Wetland landscape, the optimization adjustment of the landscape pattern, the optimization design of the subsystem, and the relationship design between human and the animal, plant, and sound systems were proposed. This study is dedicated to providing effective advice on the planning and design of campus wetland landscapes, with a view to providing examples for the planning and design of campus wetland landscapes. The research indicates that:① Scientific and rational spatial structure and functional layout planning are prerequisites for the sustainable development of wetland landscapes;② the balanced development of subsystems in the campus wetland system is a necessary condition for maintaining the rationality of the campus landscape pattern;③ the degree of harmony between humans and animals, plants, and sounds affects the ecological sustainability of campus wetland landscapes.

Application Study of Greenhouse Environment Monitoring System Based on ZigBee Technology

Against the demand of intelligent greenhouse construction of facility agriculture,greenhouse environment monitoring system is developed.The system contains three-layer architecture: sensor network layer at the bottom,data transmission convergence layer in the middle and monitoring application layer on the top,which is different from design idea of the existing system architecture.The bottom layer uses ZigBee wireless communication technology to construct wireless sensor network,and node type contains coordinator,router and acquisition terminal.Acquisition terminal is distributed in each greenhouse to collect data and play the role of wireless transmission,and router plays the function of data forwarding as the bridge of acquisition terminal and coordinator.Middle layer is composed of monitoring software developed by Lab VIEW software of NI Company and coordinator,which is used to gather data from the bottom layer.The top layer is comprehensive monitoring platform developed by Java language,which is used to gather greenhouse data of all plantation bases in one region,thereby providing comprehensive information service for government,enterprise and farmer.Greenhouse environment monitoring system realizes data collection and sharing of greenhouse environment information(air temperature,air humidity,light intensity and carbon dioxide concentration).Via test verification,the system's operation is stable,with certain application value.

Effect of Shot Peening on Surface Damage Evolution Behavior of Cu-19Ni Alloy

Shot peening is a surface modification technology with the metal surface nano machine(SNC),which can modify the surface microstructure and extend the fatigue life of Cu-19Ni alloy.The hardness,damage evolution and mechanical properties were investigated and characterized by scanning electron microscope(SEM),laser confocal microscope(LSM)and material surface performance tester(CFT).The results showed that the surface roughness and friction coefficient of Cu-19Ni alloy decreased with the increase of shot peening duration and diameter,while the microhardness and strength increased.Moreover,with the increase in shot peening duration and diameter,SEM observation showed that the fracture dimples became smaller,meanwhile,with the increase of small cleavage planes,shear tearing ridges and the thickness of the surface nano layer,the fracture mode gradually evolved from plastic to brittle fracture.The uniaxial tensile test of shot peened Cu-19Ni alloy was carried out by MTS testing machine combined with digital image correlation technology(DIC).The evolution of Cu-19Ni surface damage was analyzed,and the evolution equations describing the damage of large deformation zone and small deformation zone were established.The effect of shot peening on the damage evolution behavior of Cu-19Ni alloy was revealed.

Superposition formulas of multi-solution to a reduced(3+1)-dimensional nonlinear evolution equation

We gave the localized solutions,the interaction solutions and the mixed solutions to a reduced(3+1)-dimensional nonlinear evolution equation.These solutions were characterized by superposition formulas of positive quadratic functions,the exponential and hyperbolic functions.According to the known lump solution in the outset,we obtained the superposition formulas of positive quadratic functions by plausible reasoning.Next,we constructed the interaction solutions between the localized solutions and the exponential function solutions with the similar theory.These two kinds of solutions contained superposition formulas of positive quadratic functions,which were turned into general ternary quadratic functions,the coefficients of which were all rational operation of vector inner product.Then we obtained linear superposition formulas of exponential and hyperbolic function solutions.Finally,for aforementioned various solutions,their dynamic properties were showed by choosing specific values for parameters.From concrete plots,we observed wave characteristics of three kinds of solutions.Especially,we could observe distinct generation and separation situations when the localized wave and the stripe wave interacted at different time points.

Impact of Saharan dust on landfalling North Atlantic tropical cyclones over North America in September

本项研究利用再分析数据和模式模拟数据分析了沙尘的气溶胶光学厚度与台风的登陆,轨迹,强度及相关气象环境参数的关系,揭示了9月北大西洋台风的登陆次数会在撒哈拉沙尘较强的年份中增加,以及这一现象的物理机制,撒哈拉沙尘对热带北大西洋中部海表温度具有抑制作用,会阻碍该地区的台风活动,因此台风只能向西移动进入海表温度较高的热带北大西洋西部,从而更易于形成强台风,这一物理过程将导致台风登陆北美大陆的频次增加,特别是强台风登陆美国的可能性增强,产生更大的潜在破坏性.