Neuromodulation techniques effectively intervene in cognitive function,holding considerable scientific and practical value in fields such as aerospace,medicine,life sciences,and brain research.These techniques utilize...Neuromodulation techniques effectively intervene in cognitive function,holding considerable scientific and practical value in fields such as aerospace,medicine,life sciences,and brain research.These techniques utilize electrical stimulation to directly or indirectly target specific brain regions,modulating neural activity and influencing broader brain networks,thereby regulating cognitive function.Regulating cognitive function involves an understanding of aspects such as perception,learning and memory,attention,spatial cognition,and physical function.To enhance the application of cognitive regulation in the general population,this paper reviews recent publications from the Web of Science to assess the advancements and challenges of invasive and non-invasive stimulation methods in modulating cognitive functions.This review covers various neuromodulation techniques for cognitive intervention,including deep brain stimulation,vagus nerve stimulation,and invasive methods using microelectrode arrays.The non-invasive techniques discussed include transcranial magnetic stimulation,transcranial direct current stimulation,transcranial alternating current stimulation,transcutaneous electrical acupoint stimulation,and time interference stimulation for activating deep targets.Invasive stimulation methods,which are ideal for studying the pathogenesis of neurological diseases,tend to cause greater trauma and have been less researched in the context of cognitive function regulation.Non-invasive methods,particularly newer transcranial stimulation techniques,are gentler and more appropriate for regulating cognitive functions in the general population.These include transcutaneous acupoint electrical stimulation using acupoints and time interference methods for activating deep targets.This paper also discusses current technical challenges and potential future breakthroughs in neuromodulation technology.It is recommended that neuromodulation techniques be combined with neural detection methods to better assess their effects and improve the accuracy of non-invasive neuromodulation.Additionally,researching closed-loop feedback neuromodulation methods is identified as a promising direction for future development.展开更多
The Regional Comprehensive Economic Partnership(RCEP)has created favorable conditions for building deeply integrated agricultural value chains(AVC)in Asia-Pacific.Based on the RCEP agreement,this study employed the gl...The Regional Comprehensive Economic Partnership(RCEP)has created favorable conditions for building deeply integrated agricultural value chains(AVC)in Asia-Pacific.Based on the RCEP agreement,this study employed the global trade analysis project(GTAP)model to evaluate the impact of RCEP on AVC of member countries in terms of time,tariff reduction,and reduction of non-tariff barriers(NTB).The results indicate that(1)the implementation of RCEP boosts the value-added to agricultural exports for most member countries,particularly in competitive industries;(2)the increase in domestic production and processing capacity,reflected in domestic value-added(DVA),is the primary factor driving the rise in the value-added of agricultural exports across various industries of member countries;(3)RCEP enhances the participation of most regional countries in AVC,with varying impacts on AVC positioning,thereby fostering regional AvC development;and(4)RCEP has a positive effect on AVC indicators both in the short and long term,with the effect becoming more pronounced over time.Additionally,reducing NTB enhances the positive effects of tariff reductions on AVC indicators.Based on the analyses,the following recommendations are proposed:(1)Leverage the development opportunities arising from RCEP implementation to enhance the agricultural DVA;(2)capitalize on cooperative opportunities created by RCEP to build cohesive regional AVC;and(3)prioritize the effective implementation of RCEP'shigh-qualityrules.展开更多
Yellow rust(Puccinia striiformis f.sp.Tritici,YR)and fusarium head blight(Fusarium graminearum,FHB)are the two main diseases affecting wheat in the main grain-producing areas of East China,which is common for the two ...Yellow rust(Puccinia striiformis f.sp.Tritici,YR)and fusarium head blight(Fusarium graminearum,FHB)are the two main diseases affecting wheat in the main grain-producing areas of East China,which is common for the two diseases to appear simultaneously in some main production areas.It is necessary to discriminate wheat YR and FHB at the regional scale to accurately locate the disease in space,conduct detailed disease severity monitoring,and scientific control.Four images on different dates were acquired from Sentinel-2,Landsat-8,and Gaofen-1 during the critical period of winter wheat,and 22 remote sensing features that characterize the wheat growth status were then calculated.Meanwhile,6 meteorological parameters that reflect the wheat phenological information were also obtained by combining the site meteorological data and spatial interpolation technology.Then,the principal components(PCs)of comprehensive remote sensing and meteorological features were extracted with principal component analysis(PCA).The PCs-based discrimination models were established to map YR and FHB damage using the random forest(RF)and backpropagation neural network(BPNN).The models’performance was verified based on the disease field truth data(57 plots during the filling period)and 5-fold cross-validation.The results revealed that the PCs obtained after PCA dimensionality reduction outperformed the initial features(IFs)from remote sensing and meteorology in discriminating between the two diseases.Compared to the IFs,the average area under the curve for both micro-average and macro-average ROC curves increased by 0.07 in the PCs-based RF models and increased by 0.16 and 0.13,respectively,in the PCs-based BPNN models.Notably,the PCs-based BPNN discrimination model emerged as the most effective,achieving an overall accuracy of 83.9%.Our proposed discrimination model for wheat YR and FHB,coupled with multi-source remote sensing images and meteorological data,overcomes the limitations of a single-sensor and single-phase remote sensing information in multiple stress discrimination in cloudy and rainy areas.It performs well in revealing the damage spatial distribution of the two diseases at a regional scale,providing a basis for detailed disease severity monitoring,and scientific prevention and control.展开更多
In this paper,a wideband true time delay line for X-band is designed to overcome the beam dispersion problem in a high-resolution spaceborne synthetic aperture radar phased array antenna system.The delay line loads th...In this paper,a wideband true time delay line for X-band is designed to overcome the beam dispersion problem in a high-resolution spaceborne synthetic aperture radar phased array antenna system.The delay line loads the electromagnetic bandgap structure on the upper surface of the substrate integrated waveguide.This is equivalent to including an additional inductance-capacitance for energy storage,which realizes the slow-wave effect.A microstrip line-SIW tapered transition structure is introduced to achieve a low loss and a large bandwidth.In the frequency band between 8-12 GHz,the measured results show that the delay multiplier of the delay line reaches 4 times,i.e.,delay line’s delay time is 4 times larger than 50Ωmicrostrip line with same length.Furthermore,the delay fluctuation,i.e.,the difference between the maximum and minimum delay as a percentage of the standard delay is only 2.5%,the insertion loss is less than-2.5 dB,and the return loss is less than-15 dB.Compared with the existing delay lines,the proposed delay line has the advantages of high delay efficiency,low delay error,wide bandwidth and low loss,which has good practical value and application prospects.展开更多
Multispectral imaging plays a crucial role in simultaneously capturing detailed spatial and spectral information,which is fundamental for understanding complex phenomena across various domains.Traditional systems face...Multispectral imaging plays a crucial role in simultaneously capturing detailed spatial and spectral information,which is fundamental for understanding complex phenomena across various domains.Traditional systems face significant challenges,such as large volume,static function,and limited wavelength selectivity.Here,we propose an innovative dynamic reflective multispectral imaging system via a thermally responsive cholesteric liquid crystal based planar lens.By employing advanced photoalignment technology,the phase distribution of a lens is imprinted to the liquid crystal director.The reflection band is reversibly tuned from 450 nm to 750 nm by thermally controlling the helical pitch of the cholesteric liquid crystal,allowing selectively capturing images in different colors.This capability increases imaging versatility,showing great potential in precision agriculture for assessing crop health,noninvasive diagnostics in healthcare,and advanced remote sensing for environmental monitoring.展开更多
Dense-array ambient noise tomography is a powerful tool for achieving high-resolution subsurface imag-ing,significantly impacting geohazard prevention and control.Conventional dense-array studies,how-ever,require simu...Dense-array ambient noise tomography is a powerful tool for achieving high-resolution subsurface imag-ing,significantly impacting geohazard prevention and control.Conventional dense-array studies,how-ever,require simultaneous observations of numerous stations for extensive coverage.To conduct a comprehensive karst feature investigation with limited stations,we designed a new synchronous-asyn-chronous observation system that facilitates dense array observations.We conducted two rounds of asynchronous observations,each lasting approximately 24 h,in combination with synchronous backbone stations.We achieved wide-ranging coverage of the study area utilizing 197 nodal receivers,with an average station spacing of 7 m.The beamforming results revealed distinct variations in the noise source distributions between day and night.We estimated the source strength in the stationary phase zone and used a weighting scheme for stacking the cross-correlation functions(C ^(1) functions)to suppress the influ-ence of nonuniform noise source distributions.The weights were derived from the similarity coefficients between multicomponent C^(1)functions related to Rayleigh waves.We employed the cross-correlation of C ^(1) functions(C^(2)methods)to obtain the empirical Green’s functions between asynchronous stations.To eliminate artifacts in C ^(2) functions from higher-mode surface waves in C^(1)functions,we filtered the C^(1)functions on the basis of different particle motions linked to multimode Rayleigh waves.The dispersion measurements of Rayleigh waves obtained from both the C^(1)and C^(2)functions were utilized in surface wave tomography.The inverted three-dimensional(3D)shear-wave(S-wave)velocity model reveals two significant low-velocity zones at depths ranging from 40 to 60 m,which align well with the karst caves found in the drilling data.The method of short-term synchronous-asynchronous ambient noise tomography shows promise as a cost-effective and efficient approach for urban geohazard investigations.展开更多
Global Navigation Satellite Systems(GNSSs)face significant security threats from spoofing attacks.Typical anti-spoofing methods rely on estimating the delays between spoofing and authentic signals using multicorrelato...Global Navigation Satellite Systems(GNSSs)face significant security threats from spoofing attacks.Typical anti-spoofing methods rely on estimating the delays between spoofing and authentic signals using multicorrelator outputs.However,the accuracy of the delay estimation is limited by the spacing of the correlators.To address this,an innovative anti-spoofing method is introduced,which incorporates distinct coarse and refined stages for more accurate spoofing estimation.By leveraging the coarse delay estimates obtained through maximum likelihood estimation,the proposed method establishes the Windowed Sum of the Relative Delay(WSRD)statistics to detect the presence of spoofing signals.The iterative strategy is then employed to enhance the precision of the delay estimation.To further adapt to variations in the observation noise caused by spoofing intrusions and restore precise position,velocity,and timing solutions,an adaptive extended Kalman filter is proposed.This comprehensive framework offers detection,mitigation,and recovery against spoofing attacks.Experimental validation using datasets from the Texas Spoofing Test Battery(TEXBAT)demonstrates the effectiveness of the proposed anti-spoofing method.With 41 correlators,the method achieves a detection rate exceeding 90%at a false alarm rate of 10-5,with position or time errors below 15 m.Notably,this refined anti-spoofing approach shows robust detection and mitigation capabilities,requiring only a single antenna without the need for additional external sensors.These advancements can significantly contribute to the development of GNSS anti-spoofing measures.展开更多
Deep ultraviolet coherent light,particularly at the wavelength of 193 nm,has become indispensable for semiconductor lithography.We present a compact solid-state nanosecond pulsed laser system capable of generating 193...Deep ultraviolet coherent light,particularly at the wavelength of 193 nm,has become indispensable for semiconductor lithography.We present a compact solid-state nanosecond pulsed laser system capable of generating 193-nm coherent light at the repetition rate of 6 kHz.One part of the 1030-nm laser from the homemade Yb:YAG crystal amplifier is divided to generate 258 nm laser(1.2 W)by fourth-harmonic generation,and the rest is used to pump an optical parametric amplifier producing 1553 nm laser(700 mW).Frequency mixing of these beams in cascaded LiB_(3)O_(5) crystals yields a 193-nm laser with 70-mW average power and a linewidth of less than 880 MHz.By introducing a spiral phase plate to the 1553-nm beam before frequency mixing,we generate a vortex beam carrying orbital angular momentum.This is,to our knowledge,the first demonstration of a 193-nm vortex beam generated from a solid-state laser.Such a beam could be valuable for seeding hybrid ArF excimer lasers and has potential applications in wafer processing and defect inspection.展开更多
Intelligent interpretation of high-resolution remote sensing imagery is a fundamental challenge in aerospace information processing.Complex ground environments such as construction and demolition(C&D)waste landfil...Intelligent interpretation of high-resolution remote sensing imagery is a fundamental challenge in aerospace information processing.Complex ground environments such as construction and demolition(C&D)waste landfills exemplify the need for robust segmentation models that can handle diverse spatial and spectral patterns.Conventional convolutional neural networks(CNNs)are limited by their local receptive fields,whereas Transformer-based architectures often lose fine spatial detail,resulting in incomplete delineation of heterogeneous remote sensing targets.To address these issues,we propose a global-local collaborative network(GLC-Net),which is designed for intelligent remote sensing image segmentation.The model integrates an efficient Transformer block to capture global dependencies and a local enhancement block to refine structural details.Furthermore,a multi-scale spatial aggregation and enhancement(MSAE)module is introduced to strengthen contextual representation and suppress background noise.Deep supervision facilitates hierarchical feature learning.Experiments on two high-resolution remote sensing datasets(Changping and Daxing)demonstrate that GLC-Net surpasses state-of-the-art baselines by 1.5%-3.2%in mean intersection over union(mIoU),while achieving superior boundary precision and semantic consistency.These results confirm that global-local collaborative modeling provides an effective pathway for intelligent remote sensing image segmentation in aerospace environmental monitoring.展开更多
In this paper,we investigate the method of compensating LTS SQUID Gradiometer Systems data.By matching the attitude changes of the pod in fl ight to the anomalies of the magnetic measurement data,we find that the yaw ...In this paper,we investigate the method of compensating LTS SQUID Gradiometer Systems data.By matching the attitude changes of the pod in fl ight to the anomalies of the magnetic measurement data,we find that the yaw attitude changes most dramatically and corresponds best to the magnetic data anomaly interval.Based on this finding,we solved the compensation model using least squares fitting and Huber's parametric fitting.By comparison,we found that the Huber parametric fit not only eliminates the interference introduced by attitude changes but also retains richer anomaly source information and therefore obtains a higher signal-to-noise ratio.The experimental results show that the quality of the magnetometry data obtained by using the compensation method proposed in this paper has been significantly improved,and the mean value of its improvement ratio can reach 118.93.展开更多
Bi_(2)YbO_(4)Cl with a fluorite layer structure belongs to the family of the bismuth rare-earth oxyhalides Bi_(2)REO_(4)X(X=Cl,B r,I).However,the synthesis and photoelectric properties of Bi_(2)YbO_(4)Cl have almost n...Bi_(2)YbO_(4)Cl with a fluorite layer structure belongs to the family of the bismuth rare-earth oxyhalides Bi_(2)REO_(4)X(X=Cl,B r,I).However,the synthesis and photoelectric properties of Bi_(2)YbO_(4)Cl have almost not been reported.In this work,Bi_(2)YbO_(4)Cl was synthesized using the solid-state method and the solvothermal method.Yb3+ions show a strong characteristic absorption peak at 980 nm,which was measured by ultraviolet-visible-near-infrared absorption spectra.The transient photoconductivity of Bi_(2)YbO_(4)Cl was obtained by time-resolved terahertz spectroscopy system under 400 and 800 nm laser excitations,respectively.The frequency-dependent transient photoconductivity analysis reveals the Drude-Smith behavior in Bi_(2)YbO_(4)Cl.Under photoexcitation,the hot charge carriers with a long relaxation lifetime and a carrier mobility of 48 cm^(2)/(V·s) are obtained.The synthesis of Bi_(2)YbO_(4)Cl is of great significance for the development of novel photocatalytic and photo harvesting materials with broad spectral response.展开更多
Internal solitary waves(ISWs)have considerable energy to drive the mixing of water masses in the Sulu Sea.The propagation speed is one of the critical parameters in quantifying the energy budget of the ISWs.We collect...Internal solitary waves(ISWs)have considerable energy to drive the mixing of water masses in the Sulu Sea.The propagation speed is one of the critical parameters in quantifying the energy budget of the ISWs.We collected 1354 groups of ISWs’speeds from tandem satellite remote sensing images with temporal intervals shorter than 25 min and analyzed their spatial and multi-scale temporal variations in the Sulu Sea.We found that water depth plays an important role in modulating the spatial variation of wave speeds,which increase exponentially with water depth with a power of 0.26.Tidal currents,ocean stratification,background circulation,and climate affect the temporal variations of wave speeds from days to months or years.The fortnightly spring/neap tidal currents cause daily variations of wave speeds up to 40%by modulating the ISW amplitudes.In addition to the well-accepted results that monthly variations of wave speeds are related to density stratification,we found that enhanced stratification increases wave speeds,and the background circulation leads to a maximum decrease of 0.27 m/s in the linear counterparts of wave speed.Moreover,the averaged wave speed collected in October is lower than the corresponding linear one possibly due to some unknown dynamical processes or underestimation of background current.As for the interannual variations,we show that wave speed increases in La Niña years and decreases in El Niño years as a result of the climatic modulation on the depth of the maximum value of buoyancy frequency.展开更多
The wheat above-ground biomass(AGB)is an important index that shows the life activity of vegetation,which is of great significance for wheat growth monitoring and yield prediction.Traditional biomass estimation method...The wheat above-ground biomass(AGB)is an important index that shows the life activity of vegetation,which is of great significance for wheat growth monitoring and yield prediction.Traditional biomass estimation methods specifically include sample surveys and harvesting statistics.Although these methods have high estimation accuracy,they are time-consuming,destructive,and difficult to implement to monitor the biomass at a large scale.The main objective of this study is to optimize the traditional remote sensing methods to estimate the wheat AGBbased on improved convolutional features(CFs).Low-cost unmanned aerial vehicles(UAV)were used as the main data acquisition equipment.This study acquired image data acquired by RGB camera(RGB)and multi-spectral(MS)image data of the wheat population canopy for two wheat varieties and five key growth stages.Then,field measurements were conducted to obtain the actual wheat biomass data for validation.Based on the remote sensing indices(RSIs),structural features(SFs),and CFs,this study proposed a new feature named AUR-50(multi-source combination based on convolutional feature optimization)to estimate the wheat AGB.The results show that AUR-50 could estimate the wheat AGB more accurately than RSIs and SFs,and the average R^(2) exceeded 0.77.In the overwintering period,AUR-50_(MS)(multi-source combination with convolutional feature optimization using multispectral imagery)had the highest estimation accuracy(R^(2) of 0.88).In addition,AUR-50 reduced the effect of the vegetation index saturation on the biomass estimation accuracy by adding CFs,where the highest R^(2) was 0.69 at the flowering stage.The results of this study provide an effective method to evaluate the AGB in wheat with high throughput and a research reference for the phenotypic parameters of other crops.展开更多
Aiming to address the demand for intelligent recognition of geological features in whole-wellbore ultrasonic images,this paper integrates the YOLOv8 model with the Convolution Block Attention Module(CBAM).It proposes ...Aiming to address the demand for intelligent recognition of geological features in whole-wellbore ultrasonic images,this paper integrates the YOLOv8 model with the Convolution Block Attention Module(CBAM).It proposes an intelligent method for detecting fractures and holes,as well as segmenting whole-wellbore images.Firstly,we develop a dataset sample of effective reservoir sections by integrating logging data and conducting data augmentation on fracture and hole samples in ultrasonic logging images.A standardized process procedure for the generation of new samples and model training has been proposed effectively.Subsequently,the improved YOLOv8 model undergoes a process of training and validation.The results indicate that the model achieves average accuracies of 0.910 and 0.884 in target detection and image segmentation tasks,respectively.These findings demonstrate a notable performance improvement compared to the original model.Furthermore,a sliding window strategy is proposed to tackle the challenges of high computational demands and insufficient accuracy in the intelligent processing of full-well ultrasonic images.To manage overlapping regions within the sliding window,we employ the Non-Maximum Suppression(NMS)principle for effective processing.Finally,the model has been tested on actual logging images and demonstrates an enhanced capability to identify irregular fractures and holes,which significantly improves the efficiency of geological feature recognition in the wholewell section ultrasonic logging images.展开更多
Slope climbing of urban expansion(SCE),as a form of urbanization,has increasingly significant impacts on urban development.Unsustainable slope climbing of urban expansion can harm the natural environment,thereby affec...Slope climbing of urban expansion(SCE),as a form of urbanization,has increasingly significant impacts on urban development.Unsustainable slope climbing of urban expansion can harm the natural environment,thereby affecting human production and living conditions.Using a coupled coordination model and the geographically weighted regression(GTWR)model,leveraging night light remote sensing data and ecological environment quality index model,this study investigated the coupling relationship between urban expansion and ecological environment quality and its influencing factors in the Yangtze River Economic Belt of China from 2000 to 2020.The results indicate that from 2000 to 2020,the intensity of urban slope climbing in the Yangtze River Economic Belt showed a fluctuating upward trend,with the slope climbing intensity being most significant in Chongqing Municipality and Kunming of Yunnan Province.Overall,the ecological environment quality exhibited an upward trend,with over 80%of the study area maintaining stable or improved ecological quality.There is a certain spatial correspondence between ecological environment quality and urban slope climbing.Although these two aspects of development demonstrate a high degree of coordination,fluctuations still occur during the development process.Further research on the coupling coordination relationship between the two revealed that population density has a negative impact on coupling coordination in the eastern region,and technology expenditure in eastern coastal cities has shown a negative trend over time.To ensure the continued increase in the proportion of highly coordinated areas in the future,eastern coastal cities in the study region could prioritize ecological civilization construction,strengthen urban construction and development planning,adjust influencing factors,and ensure the coordinated development of urban growth with ecological environment quality.展开更多
Intracortical neural interfaces directly connect brain neurons with external devices to achieve high temporal resolution and spatially precise sampling of neural activity.When applied to freely moving animals,this tec...Intracortical neural interfaces directly connect brain neurons with external devices to achieve high temporal resolution and spatially precise sampling of neural activity.When applied to freely moving animals,this technology provides in-depth insight into the underlying neural mechanisms for their movement and cognition in real-world scenarios.However,the application of implanted devices in freely moving animals is limited by restrictions on their behavioral freedom and physiologic impact.In this paper,four technological directions for ideal implantable neural interface devices are analyzed:higher spatial density,improved biocompatibility,enhanced multimodal detection of electrical/neurotransmitter signals,and more effective neural modulation.Finally,we discuss how these technological developments have been applied to freely moving animals to provide better insight into neuroscience and clinical medicine.展开更多
Waterlogging stress significantly impairs plant growth and reduces crop yields.Spermidine(Spd),functioning as a second messenger,demonstrates positive effects on plant growth under waterlogging stress conditions.Howev...Waterlogging stress significantly impairs plant growth and reduces crop yields.Spermidine(Spd),functioning as a second messenger,demonstrates positive effects on plant growth under waterlogging stress conditions.However,the molecular mechanisms by which exogenous Spd application alleviates waterlogging stress remain unclear.This study employed physiological analysis and multi-omics approaches to investigate the effect of Spd application on waterlogging stress.The application of Spd enhanced the expression of genes related to light-harvesting complex(LHC),photosynthesis,and starch-related pathways,while inhibiting chlorophyll degradation and maintaining higher photosynthetic rates,thereby increasing biomass accumulation under waterlogging stress.The activation of genes associated with trehalose and Spd biosynthesis resulted in elevated accumulation of trehalose and endogenous Spd.The inhibition of 1-aminocyclopropane-1-carboxylic acid(ACC)oxidase(ACO)expression contributed to reduced ethylene emission,enhancing maize resistance to waterlogging.Following Spd application,auxin-related genes were up-regulated and indole acetic acid(IAA)content increased,promoting cell elongation in maize and maintaining normal growth under waterlogging stress.Additionally,the upregulation of lipid-related genes led to increased lipid content,protecting cell membranes under waterlogging conditions.These molecular and physiological modifications collectively enhanced resistance to waterlogging stress.These findings advance our understanding of Spd's regulatory roles in mitigating waterlogging damage and provide valuable insights for breeding waterlogging-tolerant maize varieties.展开更多
Passive surface wave imaging has been a powerful tool for near-surface characterization in urban areas,which extracts surface wave signals from ambient seismic noise and then estimates subsurface shear wave velocity b...Passive surface wave imaging has been a powerful tool for near-surface characterization in urban areas,which extracts surface wave signals from ambient seismic noise and then estimates subsurface shear wave velocity by inversion of the measured phase velocity.The high-frequency(approximately>1 Hz)seismic noise fields in urban environments are dominantly induced by human activities such as the vehicle traffic.Traffic seismic sources are nonrandomly distributed in time and space.Applying standard interferometric techniques to recordings from these nonrandom noise sources makes the Green’s function liable to estimation errors.We analyze the influence of using nonrandom traffic seismic sources for surface wave imaging.With nonrandom traffic seismic sources in time,spurious signals are generated in the cross-correlation function.With nonrandom traffic seismic sources in space,surface-wave phase velocities could be overestimated in the dispersion measurement.We provide an overview of solutions for surface-wave imaging with nonrandom traffic seismic sources in time and space,aiming to improve the retrieval of high-frequency surface waves and achieve reliable results from ultrashort(tens of seconds)observations for near-surface characterization.展开更多
Oceanic dissolved oxygen(DO)concentration is crucial for assessing the status of marine ecosystems.Against the backdrop of global warming,DO shows a general decrease,posing a threat to the health of marine ecosystems....Oceanic dissolved oxygen(DO)concentration is crucial for assessing the status of marine ecosystems.Against the backdrop of global warming,DO shows a general decrease,posing a threat to the health of marine ecosystems.Therefore,there is an urgent need to develop advanced tools to characterize the spatio-temporal variations of three-dimensional(3D)DO.To address this challenge,this study introduces the Light Gradient Boosting Machine(Light-GBM),combining satellite remote sensing and reanalysis data with Biogeochemical Argo data to accurately reconstruct the 3D DO structure in the Mediterranean Sea from 2010 to 2022.Various environmental parameters are incorporated as inputs,including spatiotemporal features,meteorological characteristics,and ocean color properties.The LightGBM model demonstrates excellent performance on the testing dataset with R^(2) of 0.958.The modeled DO agrees better with in-situ measurements than products from numerical models.Using the Shapley Additive exPlanations method,the contributions of input features are assessed.Sea surface temperatures provide a correlation with DO at the sea surface,while spatial coordinates supplement the view of the ocean interior.Based on the reconstructed 3D DO structure,we identify an oxygen minimum zone in the western Mediterranean that expands continuously,reaching depths of approximately 300–800 m.The western Mediterranean exhibits a significant declining trend.This study enhances marine environmental evidence by proposing a precise and cost-effective approach for reconstructing 3D DO,thereby offering insights into the dynamics of DO variations under changing climatic conditions.展开更多
基金supported by STI 2030-Major Projects,No.2021ZD0201603(to JL)the Joint Foundation Program of the Chinese Academy of Sciences,No.8091A170201(to JL)+1 种基金the National Natural Science Foundation of China,Nos.T2293730(to XC),T2293731(to XC),T2293734(to XC),62471291(to YW),62121003(to XC),61960206012(to XC),62333020(to XC),and 62171434(to XC)the National Key Research and Development Program of China,Nos.2022YFC2402501(to XC),2022YFB3205602(to XC).
文摘Neuromodulation techniques effectively intervene in cognitive function,holding considerable scientific and practical value in fields such as aerospace,medicine,life sciences,and brain research.These techniques utilize electrical stimulation to directly or indirectly target specific brain regions,modulating neural activity and influencing broader brain networks,thereby regulating cognitive function.Regulating cognitive function involves an understanding of aspects such as perception,learning and memory,attention,spatial cognition,and physical function.To enhance the application of cognitive regulation in the general population,this paper reviews recent publications from the Web of Science to assess the advancements and challenges of invasive and non-invasive stimulation methods in modulating cognitive functions.This review covers various neuromodulation techniques for cognitive intervention,including deep brain stimulation,vagus nerve stimulation,and invasive methods using microelectrode arrays.The non-invasive techniques discussed include transcranial magnetic stimulation,transcranial direct current stimulation,transcranial alternating current stimulation,transcutaneous electrical acupoint stimulation,and time interference stimulation for activating deep targets.Invasive stimulation methods,which are ideal for studying the pathogenesis of neurological diseases,tend to cause greater trauma and have been less researched in the context of cognitive function regulation.Non-invasive methods,particularly newer transcranial stimulation techniques,are gentler and more appropriate for regulating cognitive functions in the general population.These include transcutaneous acupoint electrical stimulation using acupoints and time interference methods for activating deep targets.This paper also discusses current technical challenges and potential future breakthroughs in neuromodulation technology.It is recommended that neuromodulation techniques be combined with neural detection methods to better assess their effects and improve the accuracy of non-invasive neuromodulation.Additionally,researching closed-loop feedback neuromodulation methods is identified as a promising direction for future development.
基金supported by the Major Subject of the National Social Science Foundation of China(21&ZD093)the Basic Research Funds of Chinese Academy of Agricultural Sciences(16100520240017)+1 种基金the Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences(CAASCSAERD-202402,10-IAED-04-2024)the earmarked fund for China Agriculture Research System(CARS-08).
文摘The Regional Comprehensive Economic Partnership(RCEP)has created favorable conditions for building deeply integrated agricultural value chains(AVC)in Asia-Pacific.Based on the RCEP agreement,this study employed the global trade analysis project(GTAP)model to evaluate the impact of RCEP on AVC of member countries in terms of time,tariff reduction,and reduction of non-tariff barriers(NTB).The results indicate that(1)the implementation of RCEP boosts the value-added to agricultural exports for most member countries,particularly in competitive industries;(2)the increase in domestic production and processing capacity,reflected in domestic value-added(DVA),is the primary factor driving the rise in the value-added of agricultural exports across various industries of member countries;(3)RCEP enhances the participation of most regional countries in AVC,with varying impacts on AVC positioning,thereby fostering regional AvC development;and(4)RCEP has a positive effect on AVC indicators both in the short and long term,with the effect becoming more pronounced over time.Additionally,reducing NTB enhances the positive effects of tariff reductions on AVC indicators.Based on the analyses,the following recommendations are proposed:(1)Leverage the development opportunities arising from RCEP implementation to enhance the agricultural DVA;(2)capitalize on cooperative opportunities created by RCEP to build cohesive regional AVC;and(3)prioritize the effective implementation of RCEP'shigh-qualityrules.
基金supported by National Key R&D Program of China(2022YFD2000100)National Natural Science Foundation of China(42401400)Zhejiang Provincial Key Research and Development Program(2023C02018).
文摘Yellow rust(Puccinia striiformis f.sp.Tritici,YR)and fusarium head blight(Fusarium graminearum,FHB)are the two main diseases affecting wheat in the main grain-producing areas of East China,which is common for the two diseases to appear simultaneously in some main production areas.It is necessary to discriminate wheat YR and FHB at the regional scale to accurately locate the disease in space,conduct detailed disease severity monitoring,and scientific control.Four images on different dates were acquired from Sentinel-2,Landsat-8,and Gaofen-1 during the critical period of winter wheat,and 22 remote sensing features that characterize the wheat growth status were then calculated.Meanwhile,6 meteorological parameters that reflect the wheat phenological information were also obtained by combining the site meteorological data and spatial interpolation technology.Then,the principal components(PCs)of comprehensive remote sensing and meteorological features were extracted with principal component analysis(PCA).The PCs-based discrimination models were established to map YR and FHB damage using the random forest(RF)and backpropagation neural network(BPNN).The models’performance was verified based on the disease field truth data(57 plots during the filling period)and 5-fold cross-validation.The results revealed that the PCs obtained after PCA dimensionality reduction outperformed the initial features(IFs)from remote sensing and meteorology in discriminating between the two diseases.Compared to the IFs,the average area under the curve for both micro-average and macro-average ROC curves increased by 0.07 in the PCs-based RF models and increased by 0.16 and 0.13,respectively,in the PCs-based BPNN models.Notably,the PCs-based BPNN discrimination model emerged as the most effective,achieving an overall accuracy of 83.9%.Our proposed discrimination model for wheat YR and FHB,coupled with multi-source remote sensing images and meteorological data,overcomes the limitations of a single-sensor and single-phase remote sensing information in multiple stress discrimination in cloudy and rainy areas.It performs well in revealing the damage spatial distribution of the two diseases at a regional scale,providing a basis for detailed disease severity monitoring,and scientific prevention and control.
基金Supported by the National Natural Science Foundation of China(61971401)。
文摘In this paper,a wideband true time delay line for X-band is designed to overcome the beam dispersion problem in a high-resolution spaceborne synthetic aperture radar phased array antenna system.The delay line loads the electromagnetic bandgap structure on the upper surface of the substrate integrated waveguide.This is equivalent to including an additional inductance-capacitance for energy storage,which realizes the slow-wave effect.A microstrip line-SIW tapered transition structure is introduced to achieve a low loss and a large bandwidth.In the frequency band between 8-12 GHz,the measured results show that the delay multiplier of the delay line reaches 4 times,i.e.,delay line’s delay time is 4 times larger than 50Ωmicrostrip line with same length.Furthermore,the delay fluctuation,i.e.,the difference between the maximum and minimum delay as a percentage of the standard delay is only 2.5%,the insertion loss is less than-2.5 dB,and the return loss is less than-15 dB.Compared with the existing delay lines,the proposed delay line has the advantages of high delay efficiency,low delay error,wide bandwidth and low loss,which has good practical value and application prospects.
基金supported by the National Key Research and Development Program of China(No.2022YFA1203700)the National Natural Science Foundation of China(NSFC)(Nos.62405129 and 62035008)+1 种基金the University Research Project of Guangzhou Education Bureau(No.202235053)the Natural Science Foundation of Jiangsu Province(No.BK20241197).
文摘Multispectral imaging plays a crucial role in simultaneously capturing detailed spatial and spectral information,which is fundamental for understanding complex phenomena across various domains.Traditional systems face significant challenges,such as large volume,static function,and limited wavelength selectivity.Here,we propose an innovative dynamic reflective multispectral imaging system via a thermally responsive cholesteric liquid crystal based planar lens.By employing advanced photoalignment technology,the phase distribution of a lens is imprinted to the liquid crystal director.The reflection band is reversibly tuned from 450 nm to 750 nm by thermally controlling the helical pitch of the cholesteric liquid crystal,allowing selectively capturing images in different colors.This capability increases imaging versatility,showing great potential in precision agriculture for assessing crop health,noninvasive diagnostics in healthcare,and advanced remote sensing for environmental monitoring.
基金supported by the National Natural Science Foundation of China(41830103)the Project of Nanjing Center of China Geological Survey(DD20190281).
文摘Dense-array ambient noise tomography is a powerful tool for achieving high-resolution subsurface imag-ing,significantly impacting geohazard prevention and control.Conventional dense-array studies,how-ever,require simultaneous observations of numerous stations for extensive coverage.To conduct a comprehensive karst feature investigation with limited stations,we designed a new synchronous-asyn-chronous observation system that facilitates dense array observations.We conducted two rounds of asynchronous observations,each lasting approximately 24 h,in combination with synchronous backbone stations.We achieved wide-ranging coverage of the study area utilizing 197 nodal receivers,with an average station spacing of 7 m.The beamforming results revealed distinct variations in the noise source distributions between day and night.We estimated the source strength in the stationary phase zone and used a weighting scheme for stacking the cross-correlation functions(C ^(1) functions)to suppress the influ-ence of nonuniform noise source distributions.The weights were derived from the similarity coefficients between multicomponent C^(1)functions related to Rayleigh waves.We employed the cross-correlation of C ^(1) functions(C^(2)methods)to obtain the empirical Green’s functions between asynchronous stations.To eliminate artifacts in C ^(2) functions from higher-mode surface waves in C^(1)functions,we filtered the C^(1)functions on the basis of different particle motions linked to multimode Rayleigh waves.The dispersion measurements of Rayleigh waves obtained from both the C^(1)and C^(2)functions were utilized in surface wave tomography.The inverted three-dimensional(3D)shear-wave(S-wave)velocity model reveals two significant low-velocity zones at depths ranging from 40 to 60 m,which align well with the karst caves found in the drilling data.The method of short-term synchronous-asynchronous ambient noise tomography shows promise as a cost-effective and efficient approach for urban geohazard investigations.
基金co-supported by the Tianjin Research innovation Project for Postgraduate Students,China(No.2022BKYZ039)the China Postdoctoral Science Foundation(No.2023M731788)the National Natural Science Foundation of China(No.62303246)。
文摘Global Navigation Satellite Systems(GNSSs)face significant security threats from spoofing attacks.Typical anti-spoofing methods rely on estimating the delays between spoofing and authentic signals using multicorrelator outputs.However,the accuracy of the delay estimation is limited by the spacing of the correlators.To address this,an innovative anti-spoofing method is introduced,which incorporates distinct coarse and refined stages for more accurate spoofing estimation.By leveraging the coarse delay estimates obtained through maximum likelihood estimation,the proposed method establishes the Windowed Sum of the Relative Delay(WSRD)statistics to detect the presence of spoofing signals.The iterative strategy is then employed to enhance the precision of the delay estimation.To further adapt to variations in the observation noise caused by spoofing intrusions and restore precise position,velocity,and timing solutions,an adaptive extended Kalman filter is proposed.This comprehensive framework offers detection,mitigation,and recovery against spoofing attacks.Experimental validation using datasets from the Texas Spoofing Test Battery(TEXBAT)demonstrates the effectiveness of the proposed anti-spoofing method.With 41 correlators,the method achieves a detection rate exceeding 90%at a false alarm rate of 10-5,with position or time errors below 15 m.Notably,this refined anti-spoofing approach shows robust detection and mitigation capabilities,requiring only a single antenna without the need for additional external sensors.These advancements can significantly contribute to the development of GNSS anti-spoofing measures.
基金supported by the Research Project of the Aerospace Information Research Institute,the Chinese Academy of Sciences(Grant Nos.E1Z1D101 and E2Z2D101)the Chinese Academy of Sciences(Grant No.E33310030D)the Guangzhou Basic and Applied Basic Research Foundation(Grant Nos.2023A04J0336 and 2023A04J0024).
文摘Deep ultraviolet coherent light,particularly at the wavelength of 193 nm,has become indispensable for semiconductor lithography.We present a compact solid-state nanosecond pulsed laser system capable of generating 193-nm coherent light at the repetition rate of 6 kHz.One part of the 1030-nm laser from the homemade Yb:YAG crystal amplifier is divided to generate 258 nm laser(1.2 W)by fourth-harmonic generation,and the rest is used to pump an optical parametric amplifier producing 1553 nm laser(700 mW).Frequency mixing of these beams in cascaded LiB_(3)O_(5) crystals yields a 193-nm laser with 70-mW average power and a linewidth of less than 880 MHz.By introducing a spiral phase plate to the 1553-nm beam before frequency mixing,we generate a vortex beam carrying orbital angular momentum.This is,to our knowledge,the first demonstration of a 193-nm vortex beam generated from a solid-state laser.Such a beam could be valuable for seeding hybrid ArF excimer lasers and has potential applications in wafer processing and defect inspection.
基金supported by the“Fourteenth Five-Year”National Key R&D Program of Chi-na(No.2024YFC3906501)the New Cornerstone Sci-ence Foundation through the XPLORER PRIZE.
文摘Intelligent interpretation of high-resolution remote sensing imagery is a fundamental challenge in aerospace information processing.Complex ground environments such as construction and demolition(C&D)waste landfills exemplify the need for robust segmentation models that can handle diverse spatial and spectral patterns.Conventional convolutional neural networks(CNNs)are limited by their local receptive fields,whereas Transformer-based architectures often lose fine spatial detail,resulting in incomplete delineation of heterogeneous remote sensing targets.To address these issues,we propose a global-local collaborative network(GLC-Net),which is designed for intelligent remote sensing image segmentation.The model integrates an efficient Transformer block to capture global dependencies and a local enhancement block to refine structural details.Furthermore,a multi-scale spatial aggregation and enhancement(MSAE)module is introduced to strengthen contextual representation and suppress background noise.Deep supervision facilitates hierarchical feature learning.Experiments on two high-resolution remote sensing datasets(Changping and Daxing)demonstrate that GLC-Net surpasses state-of-the-art baselines by 1.5%-3.2%in mean intersection over union(mIoU),while achieving superior boundary precision and semantic consistency.These results confirm that global-local collaborative modeling provides an effective pathway for intelligent remote sensing image segmentation in aerospace environmental monitoring.
基金Earth Observation and Navigation Special,Research on Low Temperature Superconducting Aeromagnetic Vector Gradient Observation Technology(2021YFB3900201)projectState Key Laboratory of Remote Sensing Science project.
文摘In this paper,we investigate the method of compensating LTS SQUID Gradiometer Systems data.By matching the attitude changes of the pod in fl ight to the anomalies of the magnetic measurement data,we find that the yaw attitude changes most dramatically and corresponds best to the magnetic data anomaly interval.Based on this finding,we solved the compensation model using least squares fitting and Huber's parametric fitting.By comparison,we found that the Huber parametric fit not only eliminates the interference introduced by attitude changes but also retains richer anomaly source information and therefore obtains a higher signal-to-noise ratio.The experimental results show that the quality of the magnetometry data obtained by using the compensation method proposed in this paper has been significantly improved,and the mean value of its improvement ratio can reach 118.93.
基金Project supported by the National Natural Science Foundation of China (61988102)the Key-Area Research and Development Program of Guangdong Province(2019B090917007)the Science and Technology Planning Project of Guangdong Province (2019B090909011)。
文摘Bi_(2)YbO_(4)Cl with a fluorite layer structure belongs to the family of the bismuth rare-earth oxyhalides Bi_(2)REO_(4)X(X=Cl,B r,I).However,the synthesis and photoelectric properties of Bi_(2)YbO_(4)Cl have almost not been reported.In this work,Bi_(2)YbO_(4)Cl was synthesized using the solid-state method and the solvothermal method.Yb3+ions show a strong characteristic absorption peak at 980 nm,which was measured by ultraviolet-visible-near-infrared absorption spectra.The transient photoconductivity of Bi_(2)YbO_(4)Cl was obtained by time-resolved terahertz spectroscopy system under 400 and 800 nm laser excitations,respectively.The frequency-dependent transient photoconductivity analysis reveals the Drude-Smith behavior in Bi_(2)YbO_(4)Cl.Under photoexcitation,the hot charge carriers with a long relaxation lifetime and a carrier mobility of 48 cm^(2)/(V·s) are obtained.The synthesis of Bi_(2)YbO_(4)Cl is of great significance for the development of novel photocatalytic and photo harvesting materials with broad spectral response.
基金Supported by the National Natural Science Foundation of China(Nos.U23A2032,42006193)supported by the Hainan Provincial Excellent Talent Team Project(Space Observation of Deep-sea)。
文摘Internal solitary waves(ISWs)have considerable energy to drive the mixing of water masses in the Sulu Sea.The propagation speed is one of the critical parameters in quantifying the energy budget of the ISWs.We collected 1354 groups of ISWs’speeds from tandem satellite remote sensing images with temporal intervals shorter than 25 min and analyzed their spatial and multi-scale temporal variations in the Sulu Sea.We found that water depth plays an important role in modulating the spatial variation of wave speeds,which increase exponentially with water depth with a power of 0.26.Tidal currents,ocean stratification,background circulation,and climate affect the temporal variations of wave speeds from days to months or years.The fortnightly spring/neap tidal currents cause daily variations of wave speeds up to 40%by modulating the ISW amplitudes.In addition to the well-accepted results that monthly variations of wave speeds are related to density stratification,we found that enhanced stratification increases wave speeds,and the background circulation leads to a maximum decrease of 0.27 m/s in the linear counterparts of wave speed.Moreover,the averaged wave speed collected in October is lower than the corresponding linear one possibly due to some unknown dynamical processes or underestimation of background current.As for the interannual variations,we show that wave speed increases in La Niña years and decreases in El Niño years as a result of the climatic modulation on the depth of the maximum value of buoyancy frequency.
基金supported by the Postgraduate Research&Practice Innovation Program of Jiangsu Province,China(SJCX23_1973)the National Natural Science Foundation of China(32172110,32071945)+7 种基金the Key Research and Development Program(Modern Agriculture)of Jiangsu Province,China(BE2022342-2,BE2020319)the Anhui Province Crop Intelligent Planting and Processing Technology Engineering Research Center Open Project,China(ZHKF04)the National Key Research and Development Program of China(2023YFD2300201,2023YFD1202200)the Special Funds for Scientific and Technological Innovation of Jiangsu Province,China(BE2022425)the Priority Academic Program Development of Jiangsu Higher Education Institutions,China(PAPD)the Central Publicinterest Scientific Institution Basal Research Fund,China(JBYW-AII-2023-08)the Science and Technology Innovation Project of the Chinese Academy of Agricultural Sciences(CAAS-CS-202201)the Special Fund for Independent Innovation of Agriculture Science and Technology in Jiangsu Province,China(CX(22)3112)。
文摘The wheat above-ground biomass(AGB)is an important index that shows the life activity of vegetation,which is of great significance for wheat growth monitoring and yield prediction.Traditional biomass estimation methods specifically include sample surveys and harvesting statistics.Although these methods have high estimation accuracy,they are time-consuming,destructive,and difficult to implement to monitor the biomass at a large scale.The main objective of this study is to optimize the traditional remote sensing methods to estimate the wheat AGBbased on improved convolutional features(CFs).Low-cost unmanned aerial vehicles(UAV)were used as the main data acquisition equipment.This study acquired image data acquired by RGB camera(RGB)and multi-spectral(MS)image data of the wheat population canopy for two wheat varieties and five key growth stages.Then,field measurements were conducted to obtain the actual wheat biomass data for validation.Based on the remote sensing indices(RSIs),structural features(SFs),and CFs,this study proposed a new feature named AUR-50(multi-source combination based on convolutional feature optimization)to estimate the wheat AGB.The results show that AUR-50 could estimate the wheat AGB more accurately than RSIs and SFs,and the average R^(2) exceeded 0.77.In the overwintering period,AUR-50_(MS)(multi-source combination with convolutional feature optimization using multispectral imagery)had the highest estimation accuracy(R^(2) of 0.88).In addition,AUR-50 reduced the effect of the vegetation index saturation on the biomass estimation accuracy by adding CFs,where the highest R^(2) was 0.69 at the flowering stage.The results of this study provide an effective method to evaluate the AGB in wheat with high throughput and a research reference for the phenotypic parameters of other crops.
基金supported by the National Natural Science Foundation of China(Grant Nos.12334019,12304496).
文摘Aiming to address the demand for intelligent recognition of geological features in whole-wellbore ultrasonic images,this paper integrates the YOLOv8 model with the Convolution Block Attention Module(CBAM).It proposes an intelligent method for detecting fractures and holes,as well as segmenting whole-wellbore images.Firstly,we develop a dataset sample of effective reservoir sections by integrating logging data and conducting data augmentation on fracture and hole samples in ultrasonic logging images.A standardized process procedure for the generation of new samples and model training has been proposed effectively.Subsequently,the improved YOLOv8 model undergoes a process of training and validation.The results indicate that the model achieves average accuracies of 0.910 and 0.884 in target detection and image segmentation tasks,respectively.These findings demonstrate a notable performance improvement compared to the original model.Furthermore,a sliding window strategy is proposed to tackle the challenges of high computational demands and insufficient accuracy in the intelligent processing of full-well ultrasonic images.To manage overlapping regions within the sliding window,we employ the Non-Maximum Suppression(NMS)principle for effective processing.Finally,the model has been tested on actual logging images and demonstrates an enhanced capability to identify irregular fractures and holes,which significantly improves the efficiency of geological feature recognition in the wholewell section ultrasonic logging images.
基金Under the auspices of National Natural Science Foundation of China(No.42371191)Science and Technology Planning of NIGLAS(No.NIGLAS2022GS06,2022NIGLAS-CJH04)。
文摘Slope climbing of urban expansion(SCE),as a form of urbanization,has increasingly significant impacts on urban development.Unsustainable slope climbing of urban expansion can harm the natural environment,thereby affecting human production and living conditions.Using a coupled coordination model and the geographically weighted regression(GTWR)model,leveraging night light remote sensing data and ecological environment quality index model,this study investigated the coupling relationship between urban expansion and ecological environment quality and its influencing factors in the Yangtze River Economic Belt of China from 2000 to 2020.The results indicate that from 2000 to 2020,the intensity of urban slope climbing in the Yangtze River Economic Belt showed a fluctuating upward trend,with the slope climbing intensity being most significant in Chongqing Municipality and Kunming of Yunnan Province.Overall,the ecological environment quality exhibited an upward trend,with over 80%of the study area maintaining stable or improved ecological quality.There is a certain spatial correspondence between ecological environment quality and urban slope climbing.Although these two aspects of development demonstrate a high degree of coordination,fluctuations still occur during the development process.Further research on the coupling coordination relationship between the two revealed that population density has a negative impact on coupling coordination in the eastern region,and technology expenditure in eastern coastal cities has shown a negative trend over time.To ensure the continued increase in the proportion of highly coordinated areas in the future,eastern coastal cities in the study region could prioritize ecological civilization construction,strengthen urban construction and development planning,adjust influencing factors,and ensure the coordinated development of urban growth with ecological environment quality.
基金sponsored by the National Natural Science Foundation of China(62121003,T2293730,T2293731,61960206012,62333020,and 62171434)the National Key Research and Development Program of China(2022YFC2402501 and 2022YFB3205602)the Major Program of Scientific and Technical Innovation 2030(2021ZD02016030)。
文摘Intracortical neural interfaces directly connect brain neurons with external devices to achieve high temporal resolution and spatially precise sampling of neural activity.When applied to freely moving animals,this technology provides in-depth insight into the underlying neural mechanisms for their movement and cognition in real-world scenarios.However,the application of implanted devices in freely moving animals is limited by restrictions on their behavioral freedom and physiologic impact.In this paper,four technological directions for ideal implantable neural interface devices are analyzed:higher spatial density,improved biocompatibility,enhanced multimodal detection of electrical/neurotransmitter signals,and more effective neural modulation.Finally,we discuss how these technological developments have been applied to freely moving animals to provide better insight into neuroscience and clinical medicine.
基金supported by the China Agriculture Research System(CARS-02-20)the Henan Province Agro-ecosystem Field Observation and Research Station,China(30602535)。
文摘Waterlogging stress significantly impairs plant growth and reduces crop yields.Spermidine(Spd),functioning as a second messenger,demonstrates positive effects on plant growth under waterlogging stress conditions.However,the molecular mechanisms by which exogenous Spd application alleviates waterlogging stress remain unclear.This study employed physiological analysis and multi-omics approaches to investigate the effect of Spd application on waterlogging stress.The application of Spd enhanced the expression of genes related to light-harvesting complex(LHC),photosynthesis,and starch-related pathways,while inhibiting chlorophyll degradation and maintaining higher photosynthetic rates,thereby increasing biomass accumulation under waterlogging stress.The activation of genes associated with trehalose and Spd biosynthesis resulted in elevated accumulation of trehalose and endogenous Spd.The inhibition of 1-aminocyclopropane-1-carboxylic acid(ACC)oxidase(ACO)expression contributed to reduced ethylene emission,enhancing maize resistance to waterlogging.Following Spd application,auxin-related genes were up-regulated and indole acetic acid(IAA)content increased,promoting cell elongation in maize and maintaining normal growth under waterlogging stress.Additionally,the upregulation of lipid-related genes led to increased lipid content,protecting cell membranes under waterlogging conditions.These molecular and physiological modifications collectively enhanced resistance to waterlogging stress.These findings advance our understanding of Spd's regulatory roles in mitigating waterlogging damage and provide valuable insights for breeding waterlogging-tolerant maize varieties.
基金supported by the National Natural Science Foundation of China(No.42374177)。
文摘Passive surface wave imaging has been a powerful tool for near-surface characterization in urban areas,which extracts surface wave signals from ambient seismic noise and then estimates subsurface shear wave velocity by inversion of the measured phase velocity.The high-frequency(approximately>1 Hz)seismic noise fields in urban environments are dominantly induced by human activities such as the vehicle traffic.Traffic seismic sources are nonrandomly distributed in time and space.Applying standard interferometric techniques to recordings from these nonrandom noise sources makes the Green’s function liable to estimation errors.We analyze the influence of using nonrandom traffic seismic sources for surface wave imaging.With nonrandom traffic seismic sources in time,spurious signals are generated in the cross-correlation function.With nonrandom traffic seismic sources in space,surface-wave phase velocities could be overestimated in the dispersion measurement.We provide an overview of solutions for surface-wave imaging with nonrandom traffic seismic sources in time and space,aiming to improve the retrieval of high-frequency surface waves and achieve reliable results from ultrashort(tens of seconds)observations for near-surface characterization.
基金supported by the Central Guiding Local Science and Technology Development Fund of Shandong-Yellow River Basin(No.YDZX2023019)Shandong Natural Science Foundation of China(Nos.ZR2020QF067 and ZR2023QD073)+6 种基金the Discipline Cluster Research Project of Qingdao University“Deep mining and intelligent prediction of multimodal big data for marine ecological disasters”(No.20240604)sourced from the International Argo Program and the national programs that contribute to it(https://argo.ucsd.edu)the CMEMS(http://marine.copernicus.eu/)the CDS(https://cds.climate.copernicus.eu/)the EMODnet(https://www.emodnet-chemistry.eu/)obtained from the ERA5(https://www.ecmwf.int)derived from the Glob Colour Project(http://globcolour.info).
文摘Oceanic dissolved oxygen(DO)concentration is crucial for assessing the status of marine ecosystems.Against the backdrop of global warming,DO shows a general decrease,posing a threat to the health of marine ecosystems.Therefore,there is an urgent need to develop advanced tools to characterize the spatio-temporal variations of three-dimensional(3D)DO.To address this challenge,this study introduces the Light Gradient Boosting Machine(Light-GBM),combining satellite remote sensing and reanalysis data with Biogeochemical Argo data to accurately reconstruct the 3D DO structure in the Mediterranean Sea from 2010 to 2022.Various environmental parameters are incorporated as inputs,including spatiotemporal features,meteorological characteristics,and ocean color properties.The LightGBM model demonstrates excellent performance on the testing dataset with R^(2) of 0.958.The modeled DO agrees better with in-situ measurements than products from numerical models.Using the Shapley Additive exPlanations method,the contributions of input features are assessed.Sea surface temperatures provide a correlation with DO at the sea surface,while spatial coordinates supplement the view of the ocean interior.Based on the reconstructed 3D DO structure,we identify an oxygen minimum zone in the western Mediterranean that expands continuously,reaching depths of approximately 300–800 m.The western Mediterranean exhibits a significant declining trend.This study enhances marine environmental evidence by proposing a precise and cost-effective approach for reconstructing 3D DO,thereby offering insights into the dynamics of DO variations under changing climatic conditions.
