Simultaneous Localization and Mapping(SLAM)is the foundation of autonomous navigation for unmanned systems.The existing SLAM solutions are mainly divided into the visual SLAM(vSLAM)equipped with camera and the lidar S...Simultaneous Localization and Mapping(SLAM)is the foundation of autonomous navigation for unmanned systems.The existing SLAM solutions are mainly divided into the visual SLAM(vSLAM)equipped with camera and the lidar SLAM equipped with lidar.However,pure visual SLAM have shortcomings such as low positioning accuracy,the paper proposes a visual-inertial information fusion SLAM based on Runge-Kutta improved pre-integration.First,the Inertial Measurement Unit(IMU)information between two adjacent keyframes is pre-integrated at the front-end to provide IMU constraints for visual-inertial information fusion.In particular,to improve the accuracy in pre-integration,the paper uses the RungeKutta algorithm instead of Euler integral to calculate the pre-integration value at the next moment.Then,the IMU pre-integration value is used as the initial value of the system state at the current frame time.We combine the visual reprojection error and imu pre-integration error to optimize the state variables such as speed and pose,and restore map points’three-dimensional coordinates.Finally,we set a sliding window to optimize map points’coordinates and state variables.The experimental part is divided into dataset experiment and complex indoor-environment experiment.The results show that compared with pure visual SLAM and the existing visual-inertial fusion SLAM,our method has higher positioning accuracy.展开更多
Astronomical imaging technologies are basic tools for the exploration of the universe,providing basic data for the research of astronomy and space physics.The Soft X-ray Imager(SXI)carried by the Solar wind Magnetosph...Astronomical imaging technologies are basic tools for the exploration of the universe,providing basic data for the research of astronomy and space physics.The Soft X-ray Imager(SXI)carried by the Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)aims to capture two-dimensional(2-D)images of the Earth’s magnetosheath by using soft X-ray imaging.However,the observed 2-D images are affected by many noise factors,destroying the contained information,which is not conducive to the subsequent reconstruction of the three-dimensional(3-D)structure of the magnetopause.The analysis of SXI-simulated observation images shows that such damage cannot be evaluated with traditional restoration models.This makes it difficult to establish the mapping relationship between SXIsimulated observation images and target images by using mathematical models.We propose an image restoration algorithm for SXIsimulated observation images that can recover large-scale structure information on the magnetosphere.The idea is to train a patch estimator by selecting noise–clean patch pairs with the same distribution through the Classification–Expectation Maximization algorithm to achieve the restoration estimation of the SXI-simulated observation image,whose mapping relationship with the target image is established by the patch estimator.The Classification–Expectation Maximization algorithm is used to select multiple patch clusters with the same distribution and then train different patch estimators so as to improve the accuracy of the estimator.Experimental results showed that our image restoration algorithm is superior to other classical image restoration algorithms in the SXI-simulated observation image restoration task,according to the peak signal-to-noise ratio and structural similarity.The restoration results of SXI-simulated observation images are used in the tangent fitting approach and the computed tomography approach toward magnetospheric reconstruction techniques,significantly improving the reconstruction results.Hence,the proposed technology may be feasible for processing SXI-simulated observation images.展开更多
The subthalamic nucleus(STN)is considered the best target for deep brain stimulation treatments of Parkinson’s disease(PD).It is difficult to localize the STN due to its small size and deep location.Multichannel micr...The subthalamic nucleus(STN)is considered the best target for deep brain stimulation treatments of Parkinson’s disease(PD).It is difficult to localize the STN due to its small size and deep location.Multichannel microelectrode arrays(MEAs)can rapidly and precisely locate the STN,which is important for precise stimulation.In this paper,16-channel MEAs modified with multiwalled carbon nanotube/poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate)(MWCNT/PEDOT:PSS)nanocomposites were designed and fabricated,and the accurate and rapid identification of the STN in PD rats was performed using detection sites distributed at different brain depths.These results showed that nuclei in 6-hydroxydopamine hydrobromide(6-OHDA)-lesioned brains discharged more intensely than those in unlesioned brains.In addition,the MEA simultaneously acquired neural signals from both the STN and the upper or lower boundary nuclei of the STN.Moreover,higher values of spike firing rate,spike amplitude,local field potential(LFP)power,and beta oscillations were detected in the STN of the 6-OHDA-lesioned brain,and may therefore be biomarkers of STN localization.Compared with the STNs of unlesioned brains,the power spectral density of spikes and LFPs synchronously decreased in the delta band and increased in the beta band of 6-OHDA-lesioned brains.This may be a cause of sleep and motor disorders associated with PD.Overall,this work describes a new cellular-level localization and detection method and provides a tool for future studies of deep brain nuclei.展开更多
Understanding the vertical distribution of ozone is crucial when assessing both its horizontal and vertical transport,as well as when analyzing the physical and chemical properties of the atmosphere.One of the most ef...Understanding the vertical distribution of ozone is crucial when assessing both its horizontal and vertical transport,as well as when analyzing the physical and chemical properties of the atmosphere.One of the most effective ways to obtain high spatial resolution ozone profiles is through satellite observations.The Environmental Trace Gases Monitoring Instrument(EMI)deployed on the Gaofen-5 satellite is the first Chinese ultraviolet-visible hyperspectral spectrometer.However,retrieving ozone profiles using backscattered radiance values measured by the EMI is challenging due to unavailable measurement errors and a low signal-to-noise ratio.The algorithm developed for the Tropospheric Monitoring Instrument did not allow us to retrieve 87%of the EMI pixels.Therefore,we developed an algorithm specific to the characteristics of the EMI.The fitting residuals are smaller than 0.3%in most regions.The retrieved ozone profiles were in good agreement with ozonesonde data,with maximum mean biases of 20%at five latitude bands.By applying EMI averaging kernels to the ozonesonde profiles,the integrated stratospheric column ozone and tropospheric column ozone also showed excellent agreement with ozonesonde data,The lower layers(0-7.5 km)of the EMI ozone profiles reflected the seasonal variation in surface ozone derived from the China National Environmental Monitoring Center(CNEMC).However,the upper layers(9.7-16.7 km)of the ozone profiles show different trends,with the ozone peak occurring at an altitude of 9.7-16.7 km in March,2019.A stratospheric intrusion event in central China from August 11 to 15,2019,is captured using the EMI ozone profiles,potential vorticity data,and relative humidity data.The increase in the CNEMC ozone co ncentration showed that downward transport enhanced surface ozone pollution.展开更多
With the increasing demand for terahertz(THz)technology in security inspection,medical imaging,and flexible electronics,there is a significant need for stretchable and transparent THz electromagnetic interference(EMI)...With the increasing demand for terahertz(THz)technology in security inspection,medical imaging,and flexible electronics,there is a significant need for stretchable and transparent THz electromagnetic interference(EMI)shielding materials.Existing EMI shielding materials,like opaque metals and carbon-based films,face challenges in achieving both high transparency and high shielding efficiency(SE).Here,a wrinkled structure strategy was proposed to construct ultra-thin,stretchable,and transparent terahertz shielding MXene films,which possesses both isotropous wrinkles(height about 50 nm)and periodic wrinkles(height about 500 nm).Compared to flat film,the wrinkled MXene film(8 nm)demonstrates a remarkable 36.5%increase in SE within the THz band.The wrinkled MXene film exhibits an EMI SE of 21.1 dB at the thickness of 100 nm,and an average EMI SE/t of 700 dBμm^(−1)over the 0.1-10 THz.Theoretical calculations suggest that the wrinkled structure enhances the film’s conductivity and surface plasmon resonances,resulting in an improved THz wave absorption.Additionally,the wrinkled structure enhances the MXene films’stretchability and stability.After bending and stretching(at 30%strain)cycles,the average THz transmittance of the wrinkled film is only 0.5%and 2.4%,respectively.The outstanding performances of the wrinkled MXene film make it a promising THz electromagnetic shielding materials for future smart windows and wearable electronics.展开更多
The Soft X-ray Imager(SXI)is part of the scientific payload of the Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission.SMILE is a joint science mission between the European Space Agency(ESA)and the Chinese...The Soft X-ray Imager(SXI)is part of the scientific payload of the Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission.SMILE is a joint science mission between the European Space Agency(ESA)and the Chinese Academy of Sciences(CAS)and is due for launch in 2025.SXI is a compact X-ray telescope with a wide field-of-view(FOV)capable of encompassing large portions of Earth’s magnetosphere from the vantage point of the SMILE orbit.SXI is sensitive to the soft X-rays produced by the Solar Wind Charge eXchange(SWCX)process produced when heavy ions of solar wind origin interact with neutral particles in Earth’s exosphere.SWCX provides a mechanism for boundary detection within the magnetosphere,such as the position of Earth’s magnetopause,because the solar wind heavy ions have a very low density in regions of closed magnetic field lines.The sensitivity of the SXI is such that it can potentially track movements of the magnetopause on timescales of a few minutes and the orbit of SMILE will enable such movements to be tracked for segments lasting many hours.SXI is led by the University of Leicester in the United Kingdom(UK)with collaborating organisations on hardware,software and science support within the UK,Europe,China and the United States.展开更多
Rapidly monitoring regional water quality and the changing trend is of great practical and scientific significance,especially for the Beijing-Tianjin-Hebei(BTH)region of China where water resources are relatively scar...Rapidly monitoring regional water quality and the changing trend is of great practical and scientific significance,especially for the Beijing-Tianjin-Hebei(BTH)region of China where water resources are relatively scarce and inland water bodies are generally small.The remote sensing data of the GF 1 satellite launched in 2013 have characteristics of high spatial and temporal resolution,which can be used for the dynamic monitoring of the water environment in small lakes and reservoirs.However,the water quality remote sensing monitoring model based on the GF 1 satellite data for lakes and reservoirs in BTH is still lacking because of the considerable differences in the optical characteristics of the lakes and reservoirs.In this paper,the typical reservoirs in BTH-Guanting Reservoir,Yuqiao Reservoir,Panjiakou Reservoir,and Daheiting Reservoir are taken as the study areas.In the atmospheric correction of GF 1-WFV,the relative radiation normalized atmospheric correction was adopted after comparing it with other methods,such as 6 S and FLAASH.In the water clarity retrieval,a water color hue angle based model was proposed and outperformed other available published models,with the R 2 of 0.74 and MRE of 31.7%.The clarity products of the four typical reservoirs in the BTH region in 2013-2019 were produced using the GF 1-WFV data.Based on the products,temporal and spatial changes in clarity were analyzed,and the main influencing factors for each water body were discussed.It was found that the clarity of Guanting,Daheiting,and Panjiakou reservoirs showed an upward trend during this period,while that of Yuqiao Reservoir showed a downward trend.In the influencing factors,the water level of the water bodies can be an important factor related to the water clarity changes in this region.展开更多
Cloud top pressure(CTP)is one of the critical cloud properties that significantly affects the radiative effect of clouds.Multi-angle polarized sensors can employ polarized bands(490 nm)or O_(2)A-bands(763 and 765 nm)t...Cloud top pressure(CTP)is one of the critical cloud properties that significantly affects the radiative effect of clouds.Multi-angle polarized sensors can employ polarized bands(490 nm)or O_(2)A-bands(763 and 765 nm)to retrieve the CTP.However,the CTP retrieved by the two methods shows inconsistent results in certain cases,and large uncertainties in low and thin cloud retrievals,which may lead to challenges in subsequent applications.This study proposes a synergistic algorithm that considers both O_(2)A-bands and polarized bands using a random forest(RF)model.LiDAR CTP data are used as the true values and the polarized and non-polarized measurements are concatenated to train the RF model to determine CTP.Additionally,through analysis,we proposed that the polarized signal becomes saturated as the cloud optical thickness(COT)increases,necessitating a particular treatment for cases where COT<10 to improve the algorithm's stability.The synergistic method was then applied to the directional polarized camera(DPC)and Polarized and Directionality of the Earth’s Reflectance(POLDER)measurements for evaluation,and the resulting retrieval accuracy of the POLDER-based measurements(RMSEPOLDER=205.176 hPa,RMSEDPC=171.141 hPa,R^(2)POLDER=0.636,R^(2)DPC=0.663,respectively)were higher than that of the MODIS and POLDER Rayleigh pressure measurements.The synergistic algorithm also showed good performance with the application of DPC data.This algorithm is expected to provide data support for atmosphere-related fields as an atmospheric remote sensing algorithm within the Cloud Application for Remote Sensing,Atmospheric Radiation,and Updating Energy(CARE)platform.展开更多
With the extensive application of large-scale array antennas,the increasing number of array elements leads to the increasing dimension of received signals,making it difficult to meet the real-time requirement of direc...With the extensive application of large-scale array antennas,the increasing number of array elements leads to the increasing dimension of received signals,making it difficult to meet the real-time requirement of direction of arrival(DOA)estimation due to the computational complexity of algorithms.Traditional subspace algorithms require estimation of the covariance matrix,which has high computational complexity and is prone to producing spurious peaks.In order to reduce the computational complexity of DOA estimation algorithms and improve their estimation accuracy under large array elements,this paper proposes a DOA estimation method based on Krylov subspace and weighted l_(1)-norm.The method uses the multistage Wiener filter(MSWF)iteration to solve the basis of the Krylov subspace as an estimate of the signal subspace,further uses the measurement matrix to reduce the dimensionality of the signal subspace observation,constructs a weighted matrix,and combines the sparse reconstruction to establish a convex optimization function based on the residual sum of squares and weighted l_(1)-norm to solve the target DOA.Simulation results show that the proposed method has high resolution under large array conditions,effectively suppresses spurious peaks,reduces computational complexity,and has good robustness for low signal to noise ratio(SNR)environment.展开更多
Remote sensing data plays an important role in natural disaster management.However,with the increase of the variety and quantity of remote sensors,the problem of“knowledge barriers”arises when data users in disaster...Remote sensing data plays an important role in natural disaster management.However,with the increase of the variety and quantity of remote sensors,the problem of“knowledge barriers”arises when data users in disaster field retrieve remote sensing data.To improve this problem,this paper proposes an ontology and rule based retrieval(ORR)method to retrieve disaster remote sensing data,and this method introduces ontology technology to express earthquake disaster and remote sensing knowledge,on this basis,and realizes the task suitability reasoning of earthquake disaster remote sensing data,mining the semantic relationship between remote sensing metadata and disasters.The prototype system is built according to the ORR method,which is compared with the traditional method,using the ORR method to retrieve disaster remote sensing data can reduce the knowledge requirements of data users in the retrieval process and improve data retrieval efficiency.展开更多
Grasslands in northern China serve the country as both an ecological barrier and a livestock production base.There,installing enclosures has been becoming the major grassland restoration measure adopted by many local ...Grasslands in northern China serve the country as both an ecological barrier and a livestock production base.There,installing enclosures has been becoming the major grassland restoration measure adopted by many local governments.However,the effects of restoration on both ecological and production benefits of grassland remain unclear for implemented grassland restoration policies.Therefore,a representative rangeland in northern China,the Maodeng pasture in Inner Mongolia Autonomous Region was selected as the study area,and remote sensing monitoring analyses were carried out to quantify the ecological benefits and economic benefits from 2015 to 2021.The results showed that:1) in terms of ecological benefits,the grassland area with a grassland coverage rate of more than 60% accounts for 32.3% of the regional area,and 86.4% of its grassland grew significantly better than the same period in2015,showing a significant improvement in grassland growth.Using the average amount of carbon per unit area as the ecological benefit evaluation index,it increased by 27.1% to 32.48Tg C/yr from 2015 to 2021.2) In terms of economic benefits,both theoretical grass production and livestock carrying capacity increased from 2015 to 2021.Compared to 2015,the theoretical grass production in 2021 increased by 24.8% to 71 900 t.The livestock carrying capacity reached 52 100 sheep units in 2021,nearly 11 000 sheep units more than that in 2015.During the study period,multiple economic indicators(on a per capita basis of permanent residents) for the pastoral area of Xilinhot City to which the Maodeng pasture belongs,have grown steadily.Per capita total income rose from 29 630 yuan(RMB) in2015 to 62 859 yuan(RMB) in 2021.Relying on grassland resources to develop the pastoral ecology also broadens the potential economic development space.Overall,the establishment of the reserve and the experiment of implanting an enclosure policy have had a significant and positive impact on Maodeng pasture’s development from both an ecological and economic perspective.With the support of scientific evidence,enclosure policy can be extended to more than 110 000 km~2 of grasslands in northern China with similar precipitation and temperature conditions,enhancing the productive and ecological potential of grasslands.The above research results will contribute to the scientific formulation of grassland pasture quality improvement plans in northern China.展开更多
SDGSAT-1,the world's first science satellite dedicated to assisting the United Nations 2030 Sustainable Development Agenda,has been operational for over two and a half years.It provides valuable data to aid in imp...SDGSAT-1,the world's first science satellite dedicated to assisting the United Nations 2030 Sustainable Development Agenda,has been operational for over two and a half years.It provides valuable data to aid in implementing the Sustainable Development Goals internationally.Through its Open Science Program,the satellite has maintained consistent operations and delivered free data to scientific and technological users from 88 countries.This program has produced a wealth of scientific output,with 72 papers,including 28 on data processing methods and 44 on applications for monitoring progress toward SDGs related to sustainable cities,clean energy,life underwater,climate action,and clean water and sanitation.SDGSAT-1 is equipped with three key instruments:a multispectral imager,a thermal infrared spectrometer,and a glimmer imager,which have enabled ground-breaking research in a variety of domains such as water quality analysis,identification of industrial heat sources,assessment of environmental disaster impacts,and detection of forest fires.The precise measurements and ongoing monitoring made possible by this invaluable data significantly advance our understanding of various environmental phenomena.They are essential for making well-informed decisions on a local and global scale.Beyond its application to academic research,SDGSAT-1 promotes global cooperation and strengthens developing countries'capacity to accomplish their sustainable development goals.As the satellite continues to gather and distribute data,it plays a pivotal role in developing strategies for environmental protection,disaster management and relief,and resource allocation.These initiatives highlight the satellite's vital role in fostering international collaboration and technical innovation to advance scientific knowledge and promote a sustainable future.展开更多
The Turpan-Hami(Tuha)Basin in Xinjiang Uygur Autonomous Region of China,holds significant strategic importance as a key economic artery of the ancient Silk Road and the Belt and Road Initiative,necessitating a holisti...The Turpan-Hami(Tuha)Basin in Xinjiang Uygur Autonomous Region of China,holds significant strategic importance as a key economic artery of the ancient Silk Road and the Belt and Road Initiative,necessitating a holistic understanding of the spatiotemporal evolution of land use/land cover(LULC)to foster sustainable planning that is tailored to the region's unique resource endowments.However,existing LULC classification methods demonstrate inadequate accuracy,hindering effective regional planning.In this study,we established a two-level LULC classification system(8 primary types and 22 secondary types)for the Tuha Basin.By employing Landsat 5/7/8 imagery at 5-a intervals,we developed the LULC dataset of the Tuha Basin from 1990 to 2020,conducted the accuracy assessment and spatiotemporal evolution analysis,and simulated the future LULC under various scenarios via the Markov-Future Land Use Simulation(Markov-FLUS)model.The results revealed that the average overall accuracy values of our LULC dataset were 0.917 and 0.864 for the primary types and secondary types,respectively.Compared with the seven mainstream LULC products(GlobeLand30,Global 30-meter Land Cover with Fine Classification System(GLC_FCS30),Finer Resolution Observation and Monitoring of Global Land Cover PLUS(FROM_GLC PLUS),ESA Global Land Cover(ESA_LC),Esri Land Cover(ESRI_LC),China Multi-Period Land Use Land Cover Change Remote Sensing Monitoring Dataset(CNLUCC),and China Annual Land Cover Dataset(CLCD))in 2020,our LULC data exhibited dramatically elevated overall accuracy and provided more precise delineations for land features,thereby yielding high-quality data backups for land resource analyses within the basin.In 2020,unused land(78.0%of the study area)and grassland(18.6%)were the dominant LULC types of the basin;although cropland and construction land constituted less than 1.0%of the total area,they played a vital role in arid land development and primarily situated within oases that form the urban cores of the cities of Turpan and Hami.Between 1990 and 2020,cropland and construction land exhibited a rapid expansion,and the total area of water body decreased yet resurging after 2015 due to an increase in areas of reservoir and pond.In future scenario simulations,significant increases in areas of construction land and cropland are anticipated under the business-as-usual scenario,whereas the wetland area will decrease,suggesting the need for ecological attention under this development pathway.In contrast,the economic development scenario underscores the fast-paced expansion of construction land,primarily from the conversion of unused land,highlighting the significant developmental potential of unused land with a slowing increase in cropland.Special attention should thus be directed toward ecological and cropland protection during development.This study provides data supports and policy recommendations for the sustainable development goals of Tuha Basin and other similar arid areas.展开更多
To enable the detection and modulation of modularized neural networks in vitro,this study proposes a microfluidic microelectrode array chip for the cultivation,compartmentalization,and control of neural cells.The chip...To enable the detection and modulation of modularized neural networks in vitro,this study proposes a microfluidic microelectrode array chip for the cultivation,compartmentalization,and control of neural cells.The chip was designed based on the specific structure of neurons and the requirements for detection and modulation.Finite-element analysis of the chip’s flow field was conducted using the COMSOL Multiphysics software,and the simulation results show that the liquid within the chip can flow smoothly,ensuring stable flow fields that facilitate the uniform growth of neurons within the microfluidic channels.By employing MEMS technology in combination with nanomaterial modification techniques,the microfluidic microelectrode array chip was fabricated successfully.Primary hippocampal neurons were cultured on the chip,forming a well-defined neural network.Spontaneous electrical activity of the detected neurons was recorded,exhibiting a 23.7%increase in amplitude compared to neuronal discharges detected on an open-field microelectrode array.This study provides a platform for the precise detection and modulation of patterned neuronal growth in vitro,potentially serving as a novel tool in neuroscience research.展开更多
In this study,we introduce our newly developed measurement-fed-perception self-adaption Low-cost UAV Coordinated Carbon Observation Network(LUCCN)prototype.The LUCCN primarily consists of two categories of instruments...In this study,we introduce our newly developed measurement-fed-perception self-adaption Low-cost UAV Coordinated Carbon Observation Network(LUCCN)prototype.The LUCCN primarily consists of two categories of instruments,including ground-based and UAV-based in-situ measurement.We use the GMP343,a low-cost non-dispersive infrared sensor,in both ground-based and UAV-based instruments.The first integrated measurement campaign took place in Shenzhen,China,4 May 2023.During the campaign,we found that LUCCN’s UAV component presented significant data-collecting advantages over its ground-based counterpart owing to the relatively high altitudes of the point emission sources,which was especially obvious at a gas power plant in Shenzhen.The emission flux was calculated by a crosssectional flux(CSF)method,the results of which differed from the Open-Data Inventory for Anthropogenic Carbon dioxide(ODIAC).The CSF result was slightly larger than others because of the low sampling rate of the whole emission cross section.The LUCCN system will be applied in future carbon monitoring campaigns to increase the spatiotemporal coverage of carbon emission information,especially in scenarios involving the detection of smaller-scale,rapidly varying sources and sinks.展开更多
Channel equalization plays a pivotal role within the reconstruction phase of passive radar reference signals.In the context of reconstructing digital terrestrial multimedia broadcasting(DTMB)signals for low-slow-small...Channel equalization plays a pivotal role within the reconstruction phase of passive radar reference signals.In the context of reconstructing digital terrestrial multimedia broadcasting(DTMB)signals for low-slow-small(LSS)target detection,a novel frequency domain block joint equalization algorithm is presented in this article.From the DTMB signal frame structure and channel multipath transmission characteristics,this article adopts a unconventional approach where the delay and frame structure of each DTMB signal frame are reconfigured to create a circular convolution block,facilitating concurrent fast Fourier transform(FFT)calculations.Following equalization,an inverse fast Fourier transform(IFFT)-based joint output and subsequent data reordering are executed to finalize the equalization process for the DTMB signal.Simulation and measured data confirm that this algorithm outperforms conventional techniques by reducing signal errors rate and enhancing real-time processing.In passive radar LSS detection,it effectively suppresses multipath and noise through frequency domain equalization,reducing false alarms and improving the capabilities of weak target detection.展开更多
Passive detection of low-slow-small(LSS)targets is easily interfered by direct signal and multipath clutter,and the traditional clutter suppression method has the contradiction between step size and convergence rate.I...Passive detection of low-slow-small(LSS)targets is easily interfered by direct signal and multipath clutter,and the traditional clutter suppression method has the contradiction between step size and convergence rate.In this paper,a frequency domain clutter suppression algorithm based on sparse adaptive filtering is proposed.The pulse compression operation between the error signal and the input reference signal is added to the cost function as a sparsity constraint,and the criterion for filter weight updating is improved to obtain a purer echo signal.At the same time,the step size and penalty factor are brought into the adaptive iteration process,and the input data is used to drive the adaptive changes of parameters such as step size.The proposed algorithm has a small amount of calculation,which improves the robustness to parameters such as step size,reduces the weight error of the filter and has a good clutter suppression performance.展开更多
As an important rice disease, rice bacterial leaf blight (RBLB, caused by the bacterium Xanthomonas oryzae pv.oryzae), has become widespread in east China in recent years. Significant losses in rice yield occurred as ...As an important rice disease, rice bacterial leaf blight (RBLB, caused by the bacterium Xanthomonas oryzae pv.oryzae), has become widespread in east China in recent years. Significant losses in rice yield occurred as a result ofthe disease’s epidemic, making it imperative to monitor RBLB at a large scale. With the development of remotesensing technology, the broad-band sensors equipped with red-edge channels over multiple spatial resolutionsoffer numerous available data for large-scale monitoring of rice diseases. However, RBLB is characterized by rapiddispersal under suitable conditions, making it difficult to track the disease at a regional scale with a single sensorin practice. Therefore, it is necessary to identify or construct features that are effective across different sensors formonitoring RBLB. To achieve this goal, the spectral response of RBLB was first analyzed based on the canopyhyperspectral data. Using the relative spectral response (RSR) functions of four representative satellite or UAVsensors (i.e., Sentinel-2, GF-6, Planet, and Rededge-M) and the hyperspectral data, the corresponding broad-bandspectral data was simulated. According to a thorough band combination and sensitivity analysis, two novel spectralindices for monitoring RBLB that can be effective across multiple sensors (i.e., RBBRI and RBBDI) weredeveloped. An optimal feature set that includes the two novel indices and a classical vegetation index was formed.The capability of such a feature set in monitoring RBLB was assessed via FLDA and SVM algorithms. The resultdemonstrated that both constructed novel indices exhibited high sensitivity to the disease across multiple sensors.Meanwhile, the feature set yielded an overall accuracy above 90% for all sensors, which indicates its cross-sensorgenerality in monitoring RBLB. The outcome of this research permits disease monitoring with different remotesensing data over a large scale.展开更多
The study of extreme weather and space events has gained paramount importance in modern society owing to rapid advances in high technology.Understanding and describing exceptional occurrences plays a crucial role in m...The study of extreme weather and space events has gained paramount importance in modern society owing to rapid advances in high technology.Understanding and describing exceptional occurrences plays a crucial role in making decisive assessments of their potential impact on technical,economic,and social aspects in various fields.This research focuses on analyzing the hourly values of the auroral electrojet(AE)geomagnetic index from 1957 to 2019 by using the peak over threshold method in extreme value theory.By fitting the generalized Pareto distribution to extreme AE values,shape parameter indices were derived,revealing negative values that establish an upper bound for this time series.Consequently,it became evident that the AE values had reached a plateau,suggesting that extreme events exceeding the established upper limit are rare.As a result,although the need for diligent precautions to mitigate the consequences of such extreme events persists,surpassing the upper limit of AE values becomes increasingly challenging.It is also possible to observe an aurora in the middle-and low-latitude regions during the maximum period of the AE index.展开更多
We develop a numerical method for the time evolution of Gaussian wave packets on flat-band lattices in the presence of correlated disorder.To achieve this,we introduce a method to generate random on-site energies with...We develop a numerical method for the time evolution of Gaussian wave packets on flat-band lattices in the presence of correlated disorder.To achieve this,we introduce a method to generate random on-site energies with prescribed correlations.We verify this method with a one-dimensional(1D)cross-stitch model,and find good agreement with analytical results obtained from the disorder-dressed evolution equations.This allows us to reproduce previous findings,that disorder can mobilize 1D flat-band states which would otherwise remain localized.As explained by the corresponding disorder-dressed evolution equations,such mobilization requires an asymmetric disorder-induced coupling to dispersive bands,a condition that is generically not fulfilled when the flat-band is resonant with the dispersive bands at a Dirac point-like crossing.We exemplify this with the 1D Lieb lattice.While analytical expressions are not available for the two-dimensional(2D)system due to its complexity,we extend the numerical method to the 2D a–T3 model,and find that the initial flat-band wave packet preserves its localization when a=0,regardless of disorder and intersections.However,when a̸=0,the wave packet shifts in real space.We interpret this as a Berry phase controlled,disorder-induced wave-packet mobilization.In addition,we present density functional theory calculations of candidate materials,specifically Hg1−xCdxTe.The flat-band emerges near the G point(α=0)in the Brillouin zone.展开更多
基金supported by the China Postdoctoral Science Foundation under Grant 2019M653870XBNational Natural Science Foundation of Shanxi Province under Grants No.2020GY-003 and 2021GY-036+1 种基金National Natural Science Foundation of China under Grants 62001340Fundamental Research Funds for the Central Universities,China,XJS211306 and JC2007
文摘Simultaneous Localization and Mapping(SLAM)is the foundation of autonomous navigation for unmanned systems.The existing SLAM solutions are mainly divided into the visual SLAM(vSLAM)equipped with camera and the lidar SLAM equipped with lidar.However,pure visual SLAM have shortcomings such as low positioning accuracy,the paper proposes a visual-inertial information fusion SLAM based on Runge-Kutta improved pre-integration.First,the Inertial Measurement Unit(IMU)information between two adjacent keyframes is pre-integrated at the front-end to provide IMU constraints for visual-inertial information fusion.In particular,to improve the accuracy in pre-integration,the paper uses the RungeKutta algorithm instead of Euler integral to calculate the pre-integration value at the next moment.Then,the IMU pre-integration value is used as the initial value of the system state at the current frame time.We combine the visual reprojection error and imu pre-integration error to optimize the state variables such as speed and pose,and restore map points’three-dimensional coordinates.Finally,we set a sliding window to optimize map points’coordinates and state variables.The experimental part is divided into dataset experiment and complex indoor-environment experiment.The results show that compared with pure visual SLAM and the existing visual-inertial fusion SLAM,our method has higher positioning accuracy.
基金supported by the National Natural Science Foundation of China(Grant Nos.42322408,42188101,41974211,and 42074202)the Key Research Program of Frontier Sciences,Chinese Academy of Sciences(Grant No.QYZDJ-SSW-JSC028)+1 种基金the Strategic Priority Program on Space Science,Chinese Academy of Sciences(Grant Nos.XDA15052500,XDA15350201,and XDA15014800)supported by the Youth Innovation Promotion Association of the Chinese Academy of Sciences(Grant No.Y202045)。
文摘Astronomical imaging technologies are basic tools for the exploration of the universe,providing basic data for the research of astronomy and space physics.The Soft X-ray Imager(SXI)carried by the Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)aims to capture two-dimensional(2-D)images of the Earth’s magnetosheath by using soft X-ray imaging.However,the observed 2-D images are affected by many noise factors,destroying the contained information,which is not conducive to the subsequent reconstruction of the three-dimensional(3-D)structure of the magnetopause.The analysis of SXI-simulated observation images shows that such damage cannot be evaluated with traditional restoration models.This makes it difficult to establish the mapping relationship between SXIsimulated observation images and target images by using mathematical models.We propose an image restoration algorithm for SXIsimulated observation images that can recover large-scale structure information on the magnetosphere.The idea is to train a patch estimator by selecting noise–clean patch pairs with the same distribution through the Classification–Expectation Maximization algorithm to achieve the restoration estimation of the SXI-simulated observation image,whose mapping relationship with the target image is established by the patch estimator.The Classification–Expectation Maximization algorithm is used to select multiple patch clusters with the same distribution and then train different patch estimators so as to improve the accuracy of the estimator.Experimental results showed that our image restoration algorithm is superior to other classical image restoration algorithms in the SXI-simulated observation image restoration task,according to the peak signal-to-noise ratio and structural similarity.The restoration results of SXI-simulated observation images are used in the tangent fitting approach and the computed tomography approach toward magnetospheric reconstruction techniques,significantly improving the reconstruction results.Hence,the proposed technology may be feasible for processing SXI-simulated observation images.
基金funded by the National Natural Science Foundation of China(Nos.L2224042,T2293731,62121003,61960206012,61973292,62171434,61975206,and 61971400)the Frontier Interdisciplinary Project of the Chinese Academy of Sciences(No.XK2022XXC003)+2 种基金the National Key Research and Development Program of China(Nos.2022YFC2402501 and 2022YFB3205602)the Major Program of Scientific and Technical Innovation 2030(No.2021ZD02016030)the Scientific Instrument Developing Project of he Chinese Academy of Sciences(No.GJJSTD20210004).
文摘The subthalamic nucleus(STN)is considered the best target for deep brain stimulation treatments of Parkinson’s disease(PD).It is difficult to localize the STN due to its small size and deep location.Multichannel microelectrode arrays(MEAs)can rapidly and precisely locate the STN,which is important for precise stimulation.In this paper,16-channel MEAs modified with multiwalled carbon nanotube/poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate)(MWCNT/PEDOT:PSS)nanocomposites were designed and fabricated,and the accurate and rapid identification of the STN in PD rats was performed using detection sites distributed at different brain depths.These results showed that nuclei in 6-hydroxydopamine hydrobromide(6-OHDA)-lesioned brains discharged more intensely than those in unlesioned brains.In addition,the MEA simultaneously acquired neural signals from both the STN and the upper or lower boundary nuclei of the STN.Moreover,higher values of spike firing rate,spike amplitude,local field potential(LFP)power,and beta oscillations were detected in the STN of the 6-OHDA-lesioned brain,and may therefore be biomarkers of STN localization.Compared with the STNs of unlesioned brains,the power spectral density of spikes and LFPs synchronously decreased in the delta band and increased in the beta band of 6-OHDA-lesioned brains.This may be a cause of sleep and motor disorders associated with PD.Overall,this work describes a new cellular-level localization and detection method and provides a tool for future studies of deep brain nuclei.
基金supported by the National Natural Science Foundation of China(42225504 and 41977184)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA23020301)+3 种基金the Key Research and Development Project of Anhui Province(202104i07020002)the Major Projects of High Resolution Earth Observation Systems of National Science and Technology(05-Y30B01-9001-19/20-3)the Key Laboratory of Atmospheric Chemistry/China Meteorological Administration(LAC/CMA)(2022B06)the Youth Innovation Promotion Association of the Chinese Academy of Sciences(2021443).
文摘Understanding the vertical distribution of ozone is crucial when assessing both its horizontal and vertical transport,as well as when analyzing the physical and chemical properties of the atmosphere.One of the most effective ways to obtain high spatial resolution ozone profiles is through satellite observations.The Environmental Trace Gases Monitoring Instrument(EMI)deployed on the Gaofen-5 satellite is the first Chinese ultraviolet-visible hyperspectral spectrometer.However,retrieving ozone profiles using backscattered radiance values measured by the EMI is challenging due to unavailable measurement errors and a low signal-to-noise ratio.The algorithm developed for the Tropospheric Monitoring Instrument did not allow us to retrieve 87%of the EMI pixels.Therefore,we developed an algorithm specific to the characteristics of the EMI.The fitting residuals are smaller than 0.3%in most regions.The retrieved ozone profiles were in good agreement with ozonesonde data,with maximum mean biases of 20%at five latitude bands.By applying EMI averaging kernels to the ozonesonde profiles,the integrated stratospheric column ozone and tropospheric column ozone also showed excellent agreement with ozonesonde data,The lower layers(0-7.5 km)of the EMI ozone profiles reflected the seasonal variation in surface ozone derived from the China National Environmental Monitoring Center(CNEMC).However,the upper layers(9.7-16.7 km)of the ozone profiles show different trends,with the ozone peak occurring at an altitude of 9.7-16.7 km in March,2019.A stratospheric intrusion event in central China from August 11 to 15,2019,is captured using the EMI ozone profiles,potential vorticity data,and relative humidity data.The increase in the CNEMC ozone co ncentration showed that downward transport enhanced surface ozone pollution.
基金supported by the National Natural Science Foundation of China(Grant nos.52371247,91963205,62101352,61988102 and 12274424)the National Key Research and Development Program of China(Grant nos.2019YFA0210200,2019YFA0210203,2022YFA1203500,and 2022YFA1206600).
文摘With the increasing demand for terahertz(THz)technology in security inspection,medical imaging,and flexible electronics,there is a significant need for stretchable and transparent THz electromagnetic interference(EMI)shielding materials.Existing EMI shielding materials,like opaque metals and carbon-based films,face challenges in achieving both high transparency and high shielding efficiency(SE).Here,a wrinkled structure strategy was proposed to construct ultra-thin,stretchable,and transparent terahertz shielding MXene films,which possesses both isotropous wrinkles(height about 50 nm)and periodic wrinkles(height about 500 nm).Compared to flat film,the wrinkled MXene film(8 nm)demonstrates a remarkable 36.5%increase in SE within the THz band.The wrinkled MXene film exhibits an EMI SE of 21.1 dB at the thickness of 100 nm,and an average EMI SE/t of 700 dBμm^(−1)over the 0.1-10 THz.Theoretical calculations suggest that the wrinkled structure enhances the film’s conductivity and surface plasmon resonances,resulting in an improved THz wave absorption.Additionally,the wrinkled structure enhances the MXene films’stretchability and stability.After bending and stretching(at 30%strain)cycles,the average THz transmittance of the wrinkled film is only 0.5%and 2.4%,respectively.The outstanding performances of the wrinkled MXene film make it a promising THz electromagnetic shielding materials for future smart windows and wearable electronics.
基金funding and support from the United Kingdom Space Agency(UKSA)the European Space Agency(ESA)+5 种基金funded and supported through the ESA PRODEX schemefunded through PRODEX PEA 4000123238the Research Council of Norway grant 223252funded by Spanish MCIN/AEI/10.13039/501100011033 grant PID2019-107061GB-C61funding and support from the Chinese Academy of Sciences(CAS)funding and support from the National Aeronautics and Space Administration(NASA)。
文摘The Soft X-ray Imager(SXI)is part of the scientific payload of the Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission.SMILE is a joint science mission between the European Space Agency(ESA)and the Chinese Academy of Sciences(CAS)and is due for launch in 2025.SXI is a compact X-ray telescope with a wide field-of-view(FOV)capable of encompassing large portions of Earth’s magnetosphere from the vantage point of the SMILE orbit.SXI is sensitive to the soft X-rays produced by the Solar Wind Charge eXchange(SWCX)process produced when heavy ions of solar wind origin interact with neutral particles in Earth’s exosphere.SWCX provides a mechanism for boundary detection within the magnetosphere,such as the position of Earth’s magnetopause,because the solar wind heavy ions have a very low density in regions of closed magnetic field lines.The sensitivity of the SXI is such that it can potentially track movements of the magnetopause on timescales of a few minutes and the orbit of SMILE will enable such movements to be tracked for segments lasting many hours.SXI is led by the University of Leicester in the United Kingdom(UK)with collaborating organisations on hardware,software and science support within the UK,Europe,China and the United States.
基金Supported by the International Partnership Program of Chinese Academy of Sciences(No.313GJHZ2022085 FN)the Dragon 5 Cooperation(No.59193)。
文摘Rapidly monitoring regional water quality and the changing trend is of great practical and scientific significance,especially for the Beijing-Tianjin-Hebei(BTH)region of China where water resources are relatively scarce and inland water bodies are generally small.The remote sensing data of the GF 1 satellite launched in 2013 have characteristics of high spatial and temporal resolution,which can be used for the dynamic monitoring of the water environment in small lakes and reservoirs.However,the water quality remote sensing monitoring model based on the GF 1 satellite data for lakes and reservoirs in BTH is still lacking because of the considerable differences in the optical characteristics of the lakes and reservoirs.In this paper,the typical reservoirs in BTH-Guanting Reservoir,Yuqiao Reservoir,Panjiakou Reservoir,and Daheiting Reservoir are taken as the study areas.In the atmospheric correction of GF 1-WFV,the relative radiation normalized atmospheric correction was adopted after comparing it with other methods,such as 6 S and FLAASH.In the water clarity retrieval,a water color hue angle based model was proposed and outperformed other available published models,with the R 2 of 0.74 and MRE of 31.7%.The clarity products of the four typical reservoirs in the BTH region in 2013-2019 were produced using the GF 1-WFV data.Based on the products,temporal and spatial changes in clarity were analyzed,and the main influencing factors for each water body were discussed.It was found that the clarity of Guanting,Daheiting,and Panjiakou reservoirs showed an upward trend during this period,while that of Yuqiao Reservoir showed a downward trend.In the influencing factors,the water level of the water bodies can be an important factor related to the water clarity changes in this region.
基金the National Natural Science Foundation of China(Grant Nos.42025504,No.41905023)National Natural Science Youth Science Foundation(Grant No.41701406)Youth Innovation Promotion Association of Chinese Academy of Sciences(Grant No.:2021122).
文摘Cloud top pressure(CTP)is one of the critical cloud properties that significantly affects the radiative effect of clouds.Multi-angle polarized sensors can employ polarized bands(490 nm)or O_(2)A-bands(763 and 765 nm)to retrieve the CTP.However,the CTP retrieved by the two methods shows inconsistent results in certain cases,and large uncertainties in low and thin cloud retrievals,which may lead to challenges in subsequent applications.This study proposes a synergistic algorithm that considers both O_(2)A-bands and polarized bands using a random forest(RF)model.LiDAR CTP data are used as the true values and the polarized and non-polarized measurements are concatenated to train the RF model to determine CTP.Additionally,through analysis,we proposed that the polarized signal becomes saturated as the cloud optical thickness(COT)increases,necessitating a particular treatment for cases where COT<10 to improve the algorithm's stability.The synergistic method was then applied to the directional polarized camera(DPC)and Polarized and Directionality of the Earth’s Reflectance(POLDER)measurements for evaluation,and the resulting retrieval accuracy of the POLDER-based measurements(RMSEPOLDER=205.176 hPa,RMSEDPC=171.141 hPa,R^(2)POLDER=0.636,R^(2)DPC=0.663,respectively)were higher than that of the MODIS and POLDER Rayleigh pressure measurements.The synergistic algorithm also showed good performance with the application of DPC data.This algorithm is expected to provide data support for atmosphere-related fields as an atmospheric remote sensing algorithm within the Cloud Application for Remote Sensing,Atmospheric Radiation,and Updating Energy(CARE)platform.
基金supported by the National Basic Research Program of China。
文摘With the extensive application of large-scale array antennas,the increasing number of array elements leads to the increasing dimension of received signals,making it difficult to meet the real-time requirement of direction of arrival(DOA)estimation due to the computational complexity of algorithms.Traditional subspace algorithms require estimation of the covariance matrix,which has high computational complexity and is prone to producing spurious peaks.In order to reduce the computational complexity of DOA estimation algorithms and improve their estimation accuracy under large array elements,this paper proposes a DOA estimation method based on Krylov subspace and weighted l_(1)-norm.The method uses the multistage Wiener filter(MSWF)iteration to solve the basis of the Krylov subspace as an estimate of the signal subspace,further uses the measurement matrix to reduce the dimensionality of the signal subspace observation,constructs a weighted matrix,and combines the sparse reconstruction to establish a convex optimization function based on the residual sum of squares and weighted l_(1)-norm to solve the target DOA.Simulation results show that the proposed method has high resolution under large array conditions,effectively suppresses spurious peaks,reduces computational complexity,and has good robustness for low signal to noise ratio(SNR)environment.
基金supported by the National Key Research and Development Program of China(2020YFC1512304).
文摘Remote sensing data plays an important role in natural disaster management.However,with the increase of the variety and quantity of remote sensors,the problem of“knowledge barriers”arises when data users in disaster field retrieve remote sensing data.To improve this problem,this paper proposes an ontology and rule based retrieval(ORR)method to retrieve disaster remote sensing data,and this method introduces ontology technology to express earthquake disaster and remote sensing knowledge,on this basis,and realizes the task suitability reasoning of earthquake disaster remote sensing data,mining the semantic relationship between remote sensing metadata and disasters.The prototype system is built according to the ORR method,which is compared with the traditional method,using the ORR method to retrieve disaster remote sensing data can reduce the knowledge requirements of data users in the retrieval process and improve data retrieval efficiency.
基金Under the auspices of the Inner Mongolia Autonomous Region Science and Technology Achievement Transformation Special Project(No.2020CG0123)the Strategic Priority Research Program of Chinese Academy of Sciences(No.XDA26050301-01)。
文摘Grasslands in northern China serve the country as both an ecological barrier and a livestock production base.There,installing enclosures has been becoming the major grassland restoration measure adopted by many local governments.However,the effects of restoration on both ecological and production benefits of grassland remain unclear for implemented grassland restoration policies.Therefore,a representative rangeland in northern China,the Maodeng pasture in Inner Mongolia Autonomous Region was selected as the study area,and remote sensing monitoring analyses were carried out to quantify the ecological benefits and economic benefits from 2015 to 2021.The results showed that:1) in terms of ecological benefits,the grassland area with a grassland coverage rate of more than 60% accounts for 32.3% of the regional area,and 86.4% of its grassland grew significantly better than the same period in2015,showing a significant improvement in grassland growth.Using the average amount of carbon per unit area as the ecological benefit evaluation index,it increased by 27.1% to 32.48Tg C/yr from 2015 to 2021.2) In terms of economic benefits,both theoretical grass production and livestock carrying capacity increased from 2015 to 2021.Compared to 2015,the theoretical grass production in 2021 increased by 24.8% to 71 900 t.The livestock carrying capacity reached 52 100 sheep units in 2021,nearly 11 000 sheep units more than that in 2015.During the study period,multiple economic indicators(on a per capita basis of permanent residents) for the pastoral area of Xilinhot City to which the Maodeng pasture belongs,have grown steadily.Per capita total income rose from 29 630 yuan(RMB) in2015 to 62 859 yuan(RMB) in 2021.Relying on grassland resources to develop the pastoral ecology also broadens the potential economic development space.Overall,the establishment of the reserve and the experiment of implanting an enclosure policy have had a significant and positive impact on Maodeng pasture’s development from both an ecological and economic perspective.With the support of scientific evidence,enclosure policy can be extended to more than 110 000 km~2 of grasslands in northern China with similar precipitation and temperature conditions,enhancing the productive and ecological potential of grasslands.The above research results will contribute to the scientific formulation of grassland pasture quality improvement plans in northern China.
文摘SDGSAT-1,the world's first science satellite dedicated to assisting the United Nations 2030 Sustainable Development Agenda,has been operational for over two and a half years.It provides valuable data to aid in implementing the Sustainable Development Goals internationally.Through its Open Science Program,the satellite has maintained consistent operations and delivered free data to scientific and technological users from 88 countries.This program has produced a wealth of scientific output,with 72 papers,including 28 on data processing methods and 44 on applications for monitoring progress toward SDGs related to sustainable cities,clean energy,life underwater,climate action,and clean water and sanitation.SDGSAT-1 is equipped with three key instruments:a multispectral imager,a thermal infrared spectrometer,and a glimmer imager,which have enabled ground-breaking research in a variety of domains such as water quality analysis,identification of industrial heat sources,assessment of environmental disaster impacts,and detection of forest fires.The precise measurements and ongoing monitoring made possible by this invaluable data significantly advance our understanding of various environmental phenomena.They are essential for making well-informed decisions on a local and global scale.Beyond its application to academic research,SDGSAT-1 promotes global cooperation and strengthens developing countries'capacity to accomplish their sustainable development goals.As the satellite continues to gather and distribute data,it plays a pivotal role in developing strategies for environmental protection,disaster management and relief,and resource allocation.These initiatives highlight the satellite's vital role in fostering international collaboration and technical innovation to advance scientific knowledge and promote a sustainable future.
基金supported by the Third Xinjiang Scientific Expedition Program (2022xjkk1100)the Tianchi Talent Project
文摘The Turpan-Hami(Tuha)Basin in Xinjiang Uygur Autonomous Region of China,holds significant strategic importance as a key economic artery of the ancient Silk Road and the Belt and Road Initiative,necessitating a holistic understanding of the spatiotemporal evolution of land use/land cover(LULC)to foster sustainable planning that is tailored to the region's unique resource endowments.However,existing LULC classification methods demonstrate inadequate accuracy,hindering effective regional planning.In this study,we established a two-level LULC classification system(8 primary types and 22 secondary types)for the Tuha Basin.By employing Landsat 5/7/8 imagery at 5-a intervals,we developed the LULC dataset of the Tuha Basin from 1990 to 2020,conducted the accuracy assessment and spatiotemporal evolution analysis,and simulated the future LULC under various scenarios via the Markov-Future Land Use Simulation(Markov-FLUS)model.The results revealed that the average overall accuracy values of our LULC dataset were 0.917 and 0.864 for the primary types and secondary types,respectively.Compared with the seven mainstream LULC products(GlobeLand30,Global 30-meter Land Cover with Fine Classification System(GLC_FCS30),Finer Resolution Observation and Monitoring of Global Land Cover PLUS(FROM_GLC PLUS),ESA Global Land Cover(ESA_LC),Esri Land Cover(ESRI_LC),China Multi-Period Land Use Land Cover Change Remote Sensing Monitoring Dataset(CNLUCC),and China Annual Land Cover Dataset(CLCD))in 2020,our LULC data exhibited dramatically elevated overall accuracy and provided more precise delineations for land features,thereby yielding high-quality data backups for land resource analyses within the basin.In 2020,unused land(78.0%of the study area)and grassland(18.6%)were the dominant LULC types of the basin;although cropland and construction land constituted less than 1.0%of the total area,they played a vital role in arid land development and primarily situated within oases that form the urban cores of the cities of Turpan and Hami.Between 1990 and 2020,cropland and construction land exhibited a rapid expansion,and the total area of water body decreased yet resurging after 2015 due to an increase in areas of reservoir and pond.In future scenario simulations,significant increases in areas of construction land and cropland are anticipated under the business-as-usual scenario,whereas the wetland area will decrease,suggesting the need for ecological attention under this development pathway.In contrast,the economic development scenario underscores the fast-paced expansion of construction land,primarily from the conversion of unused land,highlighting the significant developmental potential of unused land with a slowing increase in cropland.Special attention should thus be directed toward ecological and cropland protection during development.This study provides data supports and policy recommendations for the sustainable development goals of Tuha Basin and other similar arid areas.
基金sponsored by the National Natural Science Foundation of China (Grant Nos.61960206012,62121003,T2293731,62171434,61975206,61971400,and 61973292)the National Key Research and Development Program of China (Grant Nos.2022YFB3205602 and 2022YFC2402501)+1 种基金Major Program of Scientific and Technical Innovation 2030 (Grant No.2021ZD02016030)the Scientific Instrument Developing Project of the Chinese Academy of Sciences (Grant No.GJJSTD20210004).
文摘To enable the detection and modulation of modularized neural networks in vitro,this study proposes a microfluidic microelectrode array chip for the cultivation,compartmentalization,and control of neural cells.The chip was designed based on the specific structure of neurons and the requirements for detection and modulation.Finite-element analysis of the chip’s flow field was conducted using the COMSOL Multiphysics software,and the simulation results show that the liquid within the chip can flow smoothly,ensuring stable flow fields that facilitate the uniform growth of neurons within the microfluidic channels.By employing MEMS technology in combination with nanomaterial modification techniques,the microfluidic microelectrode array chip was fabricated successfully.Primary hippocampal neurons were cultured on the chip,forming a well-defined neural network.Spontaneous electrical activity of the detected neurons was recorded,exhibiting a 23.7%increase in amplitude compared to neuronal discharges detected on an open-field microelectrode array.This study provides a platform for the precise detection and modulation of patterned neuronal growth in vitro,potentially serving as a novel tool in neuroscience research.
基金supported by the National Key Research and Development Plan(Grant No.2021YFB3901000)the Chinese Academy of Sciences Project for Young Scientists in Basic Research(YSBR-037)+2 种基金the International Partnership Program of the Chinese Academy of Sciences(060GJHZ2022070MI)the MOST-ESA Dragon-5 Programme for Monitoring Greenhouse Gases from Space(ID.59355)the Finland–China Mobility Cooperation Project funded by the Academy of Finland(No.348596)。
文摘In this study,we introduce our newly developed measurement-fed-perception self-adaption Low-cost UAV Coordinated Carbon Observation Network(LUCCN)prototype.The LUCCN primarily consists of two categories of instruments,including ground-based and UAV-based in-situ measurement.We use the GMP343,a low-cost non-dispersive infrared sensor,in both ground-based and UAV-based instruments.The first integrated measurement campaign took place in Shenzhen,China,4 May 2023.During the campaign,we found that LUCCN’s UAV component presented significant data-collecting advantages over its ground-based counterpart owing to the relatively high altitudes of the point emission sources,which was especially obvious at a gas power plant in Shenzhen.The emission flux was calculated by a crosssectional flux(CSF)method,the results of which differed from the Open-Data Inventory for Anthropogenic Carbon dioxide(ODIAC).The CSF result was slightly larger than others because of the low sampling rate of the whole emission cross section.The LUCCN system will be applied in future carbon monitoring campaigns to increase the spatiotemporal coverage of carbon emission information,especially in scenarios involving the detection of smaller-scale,rapidly varying sources and sinks.
文摘Channel equalization plays a pivotal role within the reconstruction phase of passive radar reference signals.In the context of reconstructing digital terrestrial multimedia broadcasting(DTMB)signals for low-slow-small(LSS)target detection,a novel frequency domain block joint equalization algorithm is presented in this article.From the DTMB signal frame structure and channel multipath transmission characteristics,this article adopts a unconventional approach where the delay and frame structure of each DTMB signal frame are reconfigured to create a circular convolution block,facilitating concurrent fast Fourier transform(FFT)calculations.Following equalization,an inverse fast Fourier transform(IFFT)-based joint output and subsequent data reordering are executed to finalize the equalization process for the DTMB signal.Simulation and measured data confirm that this algorithm outperforms conventional techniques by reducing signal errors rate and enhancing real-time processing.In passive radar LSS detection,it effectively suppresses multipath and noise through frequency domain equalization,reducing false alarms and improving the capabilities of weak target detection.
文摘Passive detection of low-slow-small(LSS)targets is easily interfered by direct signal and multipath clutter,and the traditional clutter suppression method has the contradiction between step size and convergence rate.In this paper,a frequency domain clutter suppression algorithm based on sparse adaptive filtering is proposed.The pulse compression operation between the error signal and the input reference signal is added to the cost function as a sparsity constraint,and the criterion for filter weight updating is improved to obtain a purer echo signal.At the same time,the step size and penalty factor are brought into the adaptive iteration process,and the input data is used to drive the adaptive changes of parameters such as step size.The proposed algorithm has a small amount of calculation,which improves the robustness to parameters such as step size,reduces the weight error of the filter and has a good clutter suppression performance.
基金the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA28010500)National Natural Science Foundation of China(Grant Nos.42371385,42071420)Zhejiang Provincial Natural Science Foundation of China(Grant No.LTGN23D010002).
文摘As an important rice disease, rice bacterial leaf blight (RBLB, caused by the bacterium Xanthomonas oryzae pv.oryzae), has become widespread in east China in recent years. Significant losses in rice yield occurred as a result ofthe disease’s epidemic, making it imperative to monitor RBLB at a large scale. With the development of remotesensing technology, the broad-band sensors equipped with red-edge channels over multiple spatial resolutionsoffer numerous available data for large-scale monitoring of rice diseases. However, RBLB is characterized by rapiddispersal under suitable conditions, making it difficult to track the disease at a regional scale with a single sensorin practice. Therefore, it is necessary to identify or construct features that are effective across different sensors formonitoring RBLB. To achieve this goal, the spectral response of RBLB was first analyzed based on the canopyhyperspectral data. Using the relative spectral response (RSR) functions of four representative satellite or UAVsensors (i.e., Sentinel-2, GF-6, Planet, and Rededge-M) and the hyperspectral data, the corresponding broad-bandspectral data was simulated. According to a thorough band combination and sensitivity analysis, two novel spectralindices for monitoring RBLB that can be effective across multiple sensors (i.e., RBBRI and RBBDI) weredeveloped. An optimal feature set that includes the two novel indices and a classical vegetation index was formed.The capability of such a feature set in monitoring RBLB was assessed via FLDA and SVM algorithms. The resultdemonstrated that both constructed novel indices exhibited high sensitivity to the disease across multiple sensors.Meanwhile, the feature set yielded an overall accuracy above 90% for all sensors, which indicates its cross-sensorgenerality in monitoring RBLB. The outcome of this research permits disease monitoring with different remotesensing data over a large scale.
文摘The study of extreme weather and space events has gained paramount importance in modern society owing to rapid advances in high technology.Understanding and describing exceptional occurrences plays a crucial role in making decisive assessments of their potential impact on technical,economic,and social aspects in various fields.This research focuses on analyzing the hourly values of the auroral electrojet(AE)geomagnetic index from 1957 to 2019 by using the peak over threshold method in extreme value theory.By fitting the generalized Pareto distribution to extreme AE values,shape parameter indices were derived,revealing negative values that establish an upper bound for this time series.Consequently,it became evident that the AE values had reached a plateau,suggesting that extreme events exceeding the established upper limit are rare.As a result,although the need for diligent precautions to mitigate the consequences of such extreme events persists,surpassing the upper limit of AE values becomes increasingly challenging.It is also possible to observe an aurora in the middle-and low-latitude regions during the maximum period of the AE index.
基金the National Natural Sci-ence Foundation of China(Grant No.61988102)the Key Research and Development Program of Guangdong Province(Grant No.2019B090917007)+5 种基金the Science and Technology Planning Project of Guangdong Province(Grant No.2019B090909011)Q.L.acknowledges Guangzhou Basic and Applied Basic Research Project(Grant No.2023A04J0018)Z.L.acknowledges the support of fund-ing from Chinese Academy of Sciences E1Z1D10200 and E2Z2D10200from ZJ project 2021QN02X159 and from JSPS(Grant Nos.PE14052 and P16027)We gratefully ac-knowledge HZWTECH for providing computation facilities.Z.-X.H.was supported by the National Natural Science Foun-dation of China(Grant Nos.11974064 and 12147102)the Fundamental Research Funds for the Central Universities(Grant No.2020CDJQY-Z003).
文摘We develop a numerical method for the time evolution of Gaussian wave packets on flat-band lattices in the presence of correlated disorder.To achieve this,we introduce a method to generate random on-site energies with prescribed correlations.We verify this method with a one-dimensional(1D)cross-stitch model,and find good agreement with analytical results obtained from the disorder-dressed evolution equations.This allows us to reproduce previous findings,that disorder can mobilize 1D flat-band states which would otherwise remain localized.As explained by the corresponding disorder-dressed evolution equations,such mobilization requires an asymmetric disorder-induced coupling to dispersive bands,a condition that is generically not fulfilled when the flat-band is resonant with the dispersive bands at a Dirac point-like crossing.We exemplify this with the 1D Lieb lattice.While analytical expressions are not available for the two-dimensional(2D)system due to its complexity,we extend the numerical method to the 2D a–T3 model,and find that the initial flat-band wave packet preserves its localization when a=0,regardless of disorder and intersections.However,when a̸=0,the wave packet shifts in real space.We interpret this as a Berry phase controlled,disorder-induced wave-packet mobilization.In addition,we present density functional theory calculations of candidate materials,specifically Hg1−xCdxTe.The flat-band emerges near the G point(α=0)in the Brillouin zone.