Assessment of land degradation in Inner Mongolia between 2000 and 2020 based on remote sensing data

Achieving land degradation neutrality(LDN)worldwide is a significant target of the Sustainable Development Goal(SDG15.3).Inner Mongolia,as a typical dryland region in northern China,has carried out several large-scale ecological restoration programs to combat land degradation.However,there is a lack of comprehensive assess-ment of its land degradation situation after ecological programs implementation,which is of great significance to supporting SDG15.3 in China.This study analyzed the land degradation situation using the improved SDG15.3.1 calculation framework based on fine resolution data in Inner Mongolia from 2000 to 2020,and finally compre-hensively evaluated the land status of the whole region and those subject to ecological programs.The results show that net land restoration proportion of various ecological project regions and whole region continues to increase.The scope of the Grain for Green Program(GGP)had the largest proportion of net land restoration while the Natural Reserve Program(NRP)had the lowest proportion from 2000 to 2020.The net land restoration area of Inner Mongolia during 2000-2010 and 2010-2020 was 35,800 km 2 and 65,300 km 2,respectively.Overall,Inner Mongolia has achieved statistically zero growth in land degradation under the governance of ecological restora-tion programs.Therefore,reasonable planning,well monitoring,and timely assessment of ecological restoration programs are crucial to support SDG15.3.

The binding energy parameter for common envelope evolution

Abstract The binding energy parameter A plays a vital role in common envelope evolution. Though it is well known that A takes different values for stars with different masses and varies during stellar evolution, it has been erroneously adopted as a constant in most population synthesis calculations. We have system- atically calculated the values of A for stars of masses 1 - 60 M by use of an updated stellar evolution code, taking into account the contribution from both gravitational energy and internal energy to the binding energy of the envelope. We adopt the criterion for the core-envelope boundary advocated by Ivanova. A new kind of A with an enthalpy prescription is also investigated. We present fitting formulae for the calculated values of various kinds of A, which can be used in future population synthesis studies.

立足苍茫大地 仰望灿烂星空--记天文学家赵永恒中益小学科普之行

在中国,河北省的兴隆县,坐落着一座包揽多项世界天文学之最的大国重器。这座“郭守敬望远镜”(Large Sky Area Multi-Object Fiber Spectroscopy Telescope大天区面积多目标光纤光谱天文望远镜,简称“LAMOST”),是由中国科学院国家天文台斥资2.35亿元建成的世界最大口径的大视场兼大口径望远镜,也是世界光谱获取率最高的望远镜,LAMOST肩负起了解惑多项天文学难题的重任。自1993年4月“郭守敬望远镜”首次被提出建设,直到如今它顺利完成多项天文学重大任务以来的28年,一直有这样一位天文学家无惧风雨地坚守在LAMOST的每一时每一刻。他,是现任中国科学院国家天文台研究员、国家天文台兴隆观测站首席科学家、“郭守敬望远镜”运行与发展中心常务副主任赵永恒研究员。

Land use and land cover classification using Chinese GF-2 multispectral data in a region of the North China Plain

The newly launched GF-2 satellite is now the most advanced civil satellite in China to collect high spatial resolution remote sensing data.This study investigated the capability and strategy of GF?2 multispectral data for land use and land cover (LULC) classification in a region of the North China Plain.The pixel-based and object-based classifications using maximum likelihood (MLC) and support vector machine (SVM) classifiers were evaluated to determine the classification strategy that was suitable for GF?2 multispectral data.The validation results indicated that GF-2 multispectral data achieved satisfactory LULC classification performance,and object-based classification using the SVM classifier achieved the best classification accuracy with an overall classification accuracy of 94.33% and kappa coefficient of 0.911.Therefore,considering the LULC classification performance and data characteristics,GF-2 satellite data could serve as a valuable and reliable high-resolution data source for land surface monitoring.Future works should focus on improving LULC classification accuracy by exploring more classification features and exploring the potential applications of GF-2 data in related applications.

Highly Stretchable and Transparent Ionic Conductor with Novel Hydrophobicity and Extreme-Temperature Tolerance

Highly stretchable and transparent ionic conducting materials have enabled new concepts of electronic devices denoted as iontronics,with a distinguishable working mechanism and performances from the conventional electronics.However,the existing ionic conducting materials can hardly bear the humidity and temperature change of our daily life,which has greatly hindered the development and real-world application of iontronics.Herein,we design an ion gel possessing unique traits of hydrophobicity,humidity insensitivity,wide working temperature range(exceeding 100℃,and the range covered our daily life temperature),high conductivity(10^(-3)~10^(-5) S/cm),extensive stretchability,and high transparency,which is among the bestperforming ionic conductors ever developed for flexible iontronics.Several ion gel-based iontronics have been demonstrated,including large-deformation sensors,electroluminescent devices,and ionic cables,which can serve for a long time under harsh conditions.The designed material opens new potential for the real-world application progress of iontronics.

Multiple sgRNAs facilitate base editingmediated i-stop to induce complete and precise gene disruption

Dear Editor,Gene editing is a process to introduce desired changes into targeted loci of genomic DNA.Recently,type II clustered regularly in terspaced short palindromic repeats-associated Cas9 endonuclease(CRISPR/Cas9)system has been demonstrated as a versatile tool for engineering eukaryote genome(Hsu et al.,2014),such as in mice(Zuo et al.,2017).

A lightweight DDoS detection scheme under SDN context

Software-defined networking(SDN),a novel network paradigm,separates the control plane and data plane into dif-ferent network equipment to realize the flexible control of network traffic.Its excellent programmability and global view present many new opportunities.DDoS detection under the SDN context is an important and challenging research field.Some previous works attempted to collect and analyze statistics related to flows,usually recorded in switches,to address DDoS threats.In contrast,other works applied machine learning-based solutions to identify DDos and achieved promising results.Generally,most previous works need to periodically request flow rules or packets to obtain flow statistics or features to detect stealthy exceptions.Nevertheless,the request for flow rules is very time-consuming and CPU-consuming;moreover may congest the communication channel between the controller and the switches.Therefore,we present FORT,a lightweight DDoS detection scheme,which spreads the rule-based detection algorithm at edge switches and determines whether to start it by periodically retrieving the ports state.A time-series algorithm,ARIMA,is utilized to determine the port statistics adaptively,and an SVM algorithm is applied to detect whether a DDoS attack does occur.Representative experiments demonstrate that FORT can significantly reduce the controller load and provide a reliable detection accuracy.Referring to the false alarm rate of 1.24%in the comparison scheme,the false alarm rate of this scheme is only 0.039%,which significantly reduces the probability of false alarm.Besides,by introducing the alarm mechanism,this scheme can reduce the load of the southbound chan-nel by more than 60%in the normal state.

Experimental Investigations on the Out-of-Plane Sub-harmonic Vibration of a Circular Dielectric Elastomer Actuator

Dielectric elastomers have found interesting applications in soft loudspeakers,where vibrations subject to alternating electrical excitations are the key features.Although there are many t heore tical studies on the nonlinear vibrations of dielec trie elasto mers subject to electromechanical coupling loads,the systematic experimental research is rare.In this work,we design a simple experimental setup to observe the out-of-plane vibrations of a circular dielec trie elastomer actuator.We find that the dielec trie elastomer has different response modes including the harmonic,super-harmonic and sub-harmonic responses at different excitation frequencies.We analyze the responses by using the short-time Fourier transformation.We find that the equivalent voltage and the AC/DC ratio are the main parameters affecting the occurrence of sub-harmonic responses.The phenomenon of mode shift is also observed in our experiments.These experimental observations provide a deeper unders tanding of the dynamic responses of dielec trie elasto mer subject to electromechanical loads.

3D confined self-assembling of QD within super-engineering block copolymers as biocompatible superparticles enabling stimulus responsive solid state fluorescence

Eliminating colloidal toxicity and enabling its intrinsic fluorescence in aggressive environmental conditions are the key challenges for commercializing hydrophobic cadmium based quantum dots(QD).Polyarylene ether nitriles(PEN)are an example of super-engineering thermoplastics that possess a unique combination of thermal stability,intrinsic fluorescence,biocompatibility and distinct emulsion self-assembly feature.Herein,the co-self-assembly of amphiphilic PEN with hydrophobic CdSe@ZnS QD,confined in the three-dimensional(3D)oil-in-water emulsion droplets,has been explored tofabricate fluorescent microparticles(FMP).It was found that these FMP demonstrated good biocompatibility(cell viability above 90%),while exhibiting a fluorescence emission in aqueous solution that was retained(intensity retention ratio above 80%)within the whole pH range of 1-14,as well as,after being subjected to autoclaving at 120℃for 1 h.Interestingly,it was discovered that introduction of calcium ions in the emulsion self-assembly contributed to in-situ generation of phase changing nanoplates inside the FMP,which led to the photo-thermal modulated solid state fluorescence from drop-casted FMP film.Thanks to their versatile fluorescence,these FMP colloids were exploited as fluorescent probes for macrophages imaging,while micro-patterns with reversible changing of emission color were induced via thermal treatment and direct laser lithography.

Hot spot temperature prediction and operating parameter estimation of racks in data center using machine learning algorithms based on simulation data

In this paper,models to predict hot spot temperature and to estimate cooling air’s working parameters of racks in data centers were established using machine learning algorithms based on simulation data.First,simulation models of typical racks were established in computational fluid dynamics(CFD).The model was validated with field test results and results in literature,error of which was less than 3%.Then,the CFD model was used to simulate thermal environments of a typical rack considering different factors,such as servers’power,which is from 3.3 kW to 20.1 kW,cooling air’s inlet velocity,which is from 1.0 m/s to 3.0 m/s,and cooling air’s inlet temperature,which is from 16℃ to 26℃ The highest temperature in the rack,also called hot spot temperature,was selected for each case.Next,a prediction model of hot spot temperature was built using machine learning algorithms,with servers’power,cooling air’s inlet velocity and cooling air’s inlet temperature as inputs,and the hot spot temperatures as outputs.Finally,based on the prediction model,an operating parameters estimation model was established to recommend cooling air’s inlet temperatures and velocities,which can not only keep the hot spot temperature at the safety value,but are also energy saving.

Al–9.00 %Si–0.25 %Mg alloys modified by ytterbium

The effects of ytterbium（Yb） on microstructure and solidification behavior of Al-9.00%Si-0.25%Mg alloys were investigated.By optical microscope（OM） and scanning electron microscopy（SEM）,it is found that the morphology of eutectic silicon changes from coarse plates to fine fibers by the addition of 0.7%wt Yb.In addition,the grains of α-Al matrix are refined by Yb addition.Phase constitution of the alloy was analyzed by X-ray diffractometer（XRD） and energy dispersive spectroscopy（EDS）attached with SEM and mechanical properties were measured by hardness test.It is concluded that the Yb atoms are incorporated into the silicon by the adsorption at the solid-liquid growth front to cause the modification of eutectic silicon.Furthermore,the results of XRD and EDS analysis reveal that the Yb-containing phase forming in the alloys is Al_3Yb.

A review and comparison of surface incident shortwave radiation from multiple data sources: satellite retrievals, reanalysis data and GCM simulations

Surface incident shortwave radiation(Rs)can promote the circulation of substance and energy,and the accuracy of its estimation is of great significance for climate studies.The Rs can be acquired from satellite retrievals,reanalysis predictions and general circulation model(GCM)simulations.Although Rs estimates have been evaluated and compared in previous studies,most of them focus on evaluating the Rs estimates over specific regions using ground measurements from limited stations.Therefore,it is essential to comprehensively validate Rs estimates from multiple data sources.In this study,ground measurements of 690 stations from BSRN,GEBA,CMA,GC-NET and buoys were employed to validate the Rs estimates from seven representative products(GLASS,GEWEX-SRB,CERES-EBAF,ERA5,MERRA2,CFSR and CMIP6).The validation results indicated that the selected products overestimated Rs globally,with biases ranged from 0.48 to 21.27 W/m^(2).The satellite retrievals showed relatively better accuracy among seven datasets compared to ground measurements at the selected stations.Moreover,the selected seven products were all in poor accuracy at high-latitude regions with RMSEs greater than 50 W/m^(2).The long-term variation trends were also analyzed in this study.

Fractional vegetation cover estimation in heterogeneous areas by combining a radiative transfer model and a dynamic vegetation model

A fractional vegetation cover(FVC)estimation method incorporating a vegetation growth model and a radiative transfer model was previously developed,which was suitable for FVC estimation in homogeneous areas because the finer-resolution pixels corresponding to one coarseresolution FVC pixel were all assumed to have the same vegetation growth model.However,this assumption does not hold over heterogeneous areas,meaning that the method cannot be applied to large regions.Therefore,this study proposes a finer spatial resolution FVC estimation method applicable to heterogeneous areas using Landsat 8 Operational Land Imager reflectance data and Global LAnd Surface Satellite(GLASS)FVC product.The FVC product was first decomposed according to the normalized difference vegetation index from the Landsat 8 OLI data.Then,independent dynamic vegetation models were built for each finer-resolution pixel.Finally,the dynamic vegetation model and a radiative transfer model were combined to estimate FVC at the Landsat 8 scale.Validation results indicated that the proposed method(R^(2)=0.7757,RMSE=0.0881)performed better than either the previous method(R^(2)=0.7038,RMSE=0.1125)or a commonly used method involving look-up table inversions of the PROSAIL model(R^(2)=0.7457,RMSE=0.1249).

Evaluation of nine machine learning methods for estimating daily land surface radiation budget from MODIS satellite data

The all-wave net radiation(Rn)at the land surface represents surface radiation budget and plays an important role in the Earth's energy and water cycles.Many studies have been conducted to estimate from satellite top-of-atmosphere(TOA)data using various methods,particularly the application of machine learning(ML)and deep learning(DL).However,few studies have been conducted to provide a comprehensive evaluation about various ML and DL methods in retrieving.Based on extensive in situ measurements distributed at mid-low latitudes,the corresponding Moderate Resolution Imaging Spectroradiometer(MODIS)TOA observations,and the daily from the fifth generation of European Centre for Medium-Range Weather Forecasts Reanalysis 5(ERA5)used as a priori knowledge,this study assessed nine models for daily estimation,including six classic ML methods(random forest-RF,adaptive boosting-Adaboost,extreme gradient boosting-XGBoost,multilayer perceptron-MLP,radial basis function neural network-RBF,and support vector machine-SVM)and three DL methods(multilayer perceptron neural network with stacked autoencoders-SAE,deep belief network-DBN and residual neural network-ResNet).The validation results showed that the three DL methods were generally better than the six ML methods except XGBoost,although they all performed poorly in certain conditions such as winter days,rugged terrain,and high elevation.ResNet had the most robust performance across different land cover types,elevations,seasons,and latitude zones,but it has disadvantages in practice because of its highly configurable implementation environment and low computational efficiency.The estimated daily values from all nine models were more accurate than the corresponding Global LAnd Surface Satellite(GLASS)product.

Significant discrepancies of land surface daily net radiation among ten remotely sensed and reanalysis products

Land surface all-wave net radiation(R_(n))is crucial in determining Earth’s climate by contributing to the surface radiation budget.This study evaluated seven satellite and three reanalysis long-term land surface R_(n)products under different spatial scales,spatial and temporal variations,and different conditions.The results showed that during 2000-2018,Global Land Surface Satellite Product(GLASS)-Moderate Resolution Imaging Spectroradiometer(MODIS)performed the best(RMSE=25.54 Wm^(-2),bias=-1.26 Wm^(-2)),followed by ERA5(the fifth-generation of European Centre for Medium-Range Weather Forecast Reanalysis)(RMSE=32.17 Wm^(-2),bias=-4.88 Wm^(-2))and GLASS-AVHRR(Advanced Very-High-Resolution Radiometer)(RMSE=33.10 Wm^(-2),bias=4.03 Wm^(-2)).During 1983-2018,GLASS-AVHRR and ERA5 ranked top and performed similarly,with RMSE values of 31.70 and 33.08 Wm^(-2)and biases of-4.56 and 3.48 Wm^(-2),respectively.The averaged multi-annual mean R_(n)over the global land surface of satellite products was higher than that of reanalysis products by about 10~30 Wm^(-2).These products differed remarkably in long-term trends variations,particularly pre-2000,but no significant trends were observed.Discrepancies were more frequent in satellite data,while reanalysis products showed smoother variations.Large discrepancies were found in regions with high latitudes,reflectance,and elevation which could be attributed to input radiative components,meteorological variables(e.g.,cloud properties,aerosol optical thickness),and applicability of the algorithms used.While further research is needed for detailed insights.

Numerical study on the electromechanical behavior of dielectric elastomer with the influence of surrounding medium

The considerable electric-induced shape change,together with the attributes of lightweight,high efficiency,and inexpensive cost,makes dielectric elastomer,a promising soft active material for the realization of actuators in broad applications.Although,a number of prototype devices have been demonstrated in the past few years,the further development of this technology necessitates adequate analytical and numerical tools.Especially,previous the-oretical studies always neglect the influence of surrounding med-ium.Due to the large deformation and nonlinear equations of states involved in dielectric elastomer,finite element method(FEM)is anticipated;however,the few available formulations employ homemade codes,which are inconvenient to implement.The aim of this work is to present a numerical approach with the commercial FEM package COMSOL to investigate the nonlinear response of dielectric elastomer under electric stimulation.The influence of surrounding free space on the electric field is analyzed and the corresponding electric force is taken into account through an electric surface traction on the circumstances edge.By employ-ing Maxwell stress tensor as actuation pressure,the mechanical and electric governing equations for dielectric elastomer are coupled,and then solved simultaneously with the Gent model of stain energy to derive the electric induced large deformation as well as the electromechanical instability.The finite element imple-mentation presented here may provide a powerful computational tool to help design and optimize the engineering applications of dielectric elastomer.

International public opinion analysis of four olympic games:From 2008 to 2022

Since the rapid spread of the COVID-19 worldwide,the pandemic has led to a huge impact on global sporting events.As a major international event,the 2022 Beijing Winter Olympics has commonalities with the 2008 Beijing Olympics,the 2014 Sochi Winter Olympics,and the 2020 Tokyo Olympics in terms of international public opinion context and epidemiological background.In this study,over 1 million pieces of UGC(User Generated Contents)in Chinese and English languages were obtained from social media platforms such as Twitter,YouTube,as well as traditional mass media in various countries to compare the differences between the two languages in international public opinion.Using sentiment analysis,this study explores the evolution of international public opinion topics and sentiment differences among the above four Olympic Games.The analysis results show that:1)regardless of traditional mass media or online social media,there is a more obvious tendency of general politicization in the topics of the 2008 Beijing Olympics and 2022 Beijing Winter Olympics,and extreme emotional remarks of the 2022 Beijing Winter Olympics are more frequent;2)in the topic of political opinion involving China,international Chinese public opinion presents more negative sentiment than those in English;3)Among the topics involving COVID-19,the negative level of public opinion in Chinese and English is opposite for the 2020 Tokyo Olympics and the 2022 Beijing Winter Olympics;4)International public opinion on the topic of sports events is significantly more positive in Chinese than in English;5)YouTube’s Chinese opinion environment is better than English.