The CUG_CLMFM3D series comprises high-resolution three-dimensional lithospheric magnetic field models for China and its surroundings.The first version,CUG_CLMFM3Dv1,is a spherical cap harmonic model integrating the WD...The CUG_CLMFM3D series comprises high-resolution three-dimensional lithospheric magnetic field models for China and its surroundings.The first version,CUG_CLMFM3Dv1,is a spherical cap harmonic model integrating the WDMAMv2(World Digital Magnetic Anomaly Map version 2)global magnetic anomaly grid and nearly a decade of CHAMP(Challenging Minisatellite Payload for Geophysical Research and Application)satellite vector data.It achieves a~5.7 km resolution but has limitations:the WDMAMv2 grid lacks high-resolution data in the southern Xinjiang and Tibet regions,which leads to missing small-to medium-scale anomalies,and unfiltered CHAMP data introduce low-frequency conflicts with global spherical harmonic models.Above the altitude of 150 km,correlations with global models drop below 0.9.The second version,CUG_CLMFM3Dv2,addresses these issues by incorporating 5-km-resolution aeromagnetic data and rigorously processed satellite data from CHAMP,Swarm,CSES-1(China Seismo-Electromagnetic Satellite 1),and MSS-1(Macao Science Satellite 1).The comparison analysis shows that the CUG_CLMFM3Dv2 captures finer high-frequency details and more stable long-wavelength signals,offering improved magnetic anomaly maps for further geological and geophysical studies.展开更多
The aircraft system has recently gained its reputation as a reliable and efficient tool for sensing and parsing aerial scenes.However,accurate and fast semantic segmentation of highresolution aerial images for remote ...The aircraft system has recently gained its reputation as a reliable and efficient tool for sensing and parsing aerial scenes.However,accurate and fast semantic segmentation of highresolution aerial images for remote sensing applications is still facing three challenges:the requirements for limited processing resources and low-latency operations based on aerial platforms,the balance between high accuracy and real-time efficiency for model performance,and the confusing objects with large intra-class variations and small inter-class differences in high-resolution aerial images.To address these issues,a lightweight and dual-path deep convolutional architecture,namely Aerial Bilateral Segmentation Network(Aerial-Bi Se Net),is proposed to perform realtime segmentation on high-resolution aerial images with favorable accuracy.Specifically,inspired by the receptive field concept in human visual systems,Receptive Field Module(RFM)is proposed to encode rich multi-scale contextual information.Based on channel attention mechanism,two novel modules,called Feature Attention Module(FAM)and Channel Attention based Feature Fusion Module(CAFFM)respectively,are proposed to refine and combine features effectively to boost the model performance.Aerial-Bi Se Net is evaluated on the Potsdam and Vaihingen datasets,where leading performance is reported compared with other state-of-the-art models,in terms of both accuracy and efficiency.展开更多
Due to the limitations of spatial bandwidth product and data transmission bandwidth,the field of view,resolution,and imaging speed constrain each other in an optical imaging system.Here,a fast-zoom and high-resolution...Due to the limitations of spatial bandwidth product and data transmission bandwidth,the field of view,resolution,and imaging speed constrain each other in an optical imaging system.Here,a fast-zoom and high-resolution sparse compound-eye camera(CEC)based on dual-end collaborative optimization is proposed,which provides a cost-effective way to break through the trade-off among the field of view,resolution,and imaging speed.In the optical end,a sparse CEC based on liquid lenses is designed,which can realize large-field-of-view imaging in real time,and fast zooming within 5 ms.In the computational end,a disturbed degradation model driven super-resolution network(DDMDSR-Net)is proposed to deal with complex image degradation issues in actual imaging situations,achieving high-robustness and high-fidelity resolution enhancement.Based on the proposed dual-end collaborative optimization framework,the angular resolution of the CEC can be enhanced from 71.6"to 26.0",which provides a solution to realize high-resolution imaging for array camera dispensing with high optical hardware complexity and data transmission bandwidth.Experiments verify the advantages of the CEC based on dual-end collaborative optimization in high-fidelity reconstruction of real scene images,kilometer-level long-distance detection,and dynamic imaging and precise recognition of targets of interest.展开更多
BACKGROUND Neurovascular compression(NVC) is the main cause of primary trigeminal neuralgia(TN) and hemifacial spasm(HFS). Microvascular decompression(MVD) is an effective surgical method for the treatment of TN and H...BACKGROUND Neurovascular compression(NVC) is the main cause of primary trigeminal neuralgia(TN) and hemifacial spasm(HFS). Microvascular decompression(MVD) is an effective surgical method for the treatment of TN and HFS caused by NVC. The judgement of NVC is a critical step in the preoperative evaluation of MVD, which is related to the effect of MVD treatment. Magnetic resonance imaging(MRI) technology has been used to detect NVC prior to MVD for several years. Among many MRI sequences, three-dimensional time-of-flight magnetic resonance angiography(3D TOF MRA) is the most widely used. However, 3D TOF MRA has some shortcomings in detecting NVC. Therefore, 3D TOF MRA combined with high resolution T2-weighted imaging(HR T2WI) is considered to be a more effective method to detect NVC.AIM To determine the value of 3D TOF MRA combined with HR T2WI in the judgment of NVC, and thus to assess its value in the preoperative evaluation of MVD.METHODS Related studies published from inception to September 2022 based on PubMed, Embase, Web of Science, and the Cochrane Library were retrieved. Studies that investigated 3D TOF MRA combined with HR T2WI to judge NVC in patients with TN or HFS were included according to the inclusion criteria. Studies without complete data or not relevant to the research topics were excluded. The Quality Assessment of Diagnostic Accuracy Studies checklist was used to assess the quality of included studies. The publication bias of the included literature was examined by Deeks’ test. An exact binomial rendition of the bivariate mixed-effects regression model was used to synthesize data. Data analysis was performed using the MIDAS module of statistical software Stata 16.0. Two independent investigators extracted patient and study characteristics, and discrepancies were resolved by consensus. Individual and pooled sensitivities and specificities were calculated. The I_(2) statistic and Q test were used to test heterogeneity. The study was registered on the website of PROSERO(registration No. CRD42022357158).RESULTS Our search identified 595 articles, of which 12(including 855 patients) fulfilled the inclusion criteria. Bivariate analysis showed that the pooled sensitivity and specificity of 3D TOF MRA combined with HR T2WI for detecting NVC were 0.96 [95% confidence interval(CI): 0.92-0.98] and 0.92(95%CI: 0.74-0.98), respectively. The pooled positive likelihood ratio was 12.4(95%CI: 3.2-47.8), pooled negative likelihood ratio was 0.04(95%CI: 0.02-0.09), and pooled diagnostic odds ratio was 283(95%CI: 50-1620). The area under the receiver operating characteristic curve was 0.98(95%CI: 0.97-0.99). The studies showed no substantial heterogeneity(I2 = 0, Q = 0.001 P = 0.50).CONCLUSION Our results suggest that 3D TOF MRA combined with HR T2WI has excellent sensitivity and specificity for judging NVC in patients with TN or HFS. This method can be used as an effective tool for preoperative evaluation of MVD.展开更多
Small-object detection has long been a challenge.High-megapixel cameras are used to solve this problem in industries.However,current detectors are inefficient for high-resolution images.In this work,we propose a new m...Small-object detection has long been a challenge.High-megapixel cameras are used to solve this problem in industries.However,current detectors are inefficient for high-resolution images.In this work,we propose a new module called Pre-Locate Net,which is a plug-and-play structure that can be combined with most popular detectors.We inspire the use of classification ideas to obtain candidate regions in images,greatly reducing the amount of calculation,and thus achieving rapid detection in high-resolution images.Pre-Locate Net mainly includes two parts,candidate region classification and behavior classification.Candidate region classification is used to obtain a candidate region,and behavior classification is used to estimate the scale of an object.Different follow-up processing is adopted according to different scales to balance the variance of the network input.Different from the popular candidate region generation method,we abandon the idea of regression of a bounding box and adopt the concept of classification,so as to realize the prediction of a candidate region in the shallow network.We build a high-resolution dataset of aircraft and landing gears covering complex scenes to verify the effectiveness of our method.Compared to state-of-the-art detectors(e.g.,Guided Anchoring,Libra-RCNN,and FASF),our method achieves the best m AP of 94.5 on 1920×1080 images at 16.7 FPS.展开更多
In this study,an extreme rainfall event that occurred on 25 May 2018 over Shanghai and its nearby area was simulated using the Weather Research and Forecasting model,with a focus on the effects of planetary boundary l...In this study,an extreme rainfall event that occurred on 25 May 2018 over Shanghai and its nearby area was simulated using the Weather Research and Forecasting model,with a focus on the effects of planetary boundary layer(PBL)physics using double nesting with large grid ratios(15:1 and 9:1).The sensitivity of the precipitation forecast was examined through three PBL schemes:the Yonsei University Scheme,the Mellor−Yamada−Nakanishi Niino Level 2.5(MYNN)scheme,and the Mellor−Yamada−Janjic scheme.The PBL effects on boundary layer structures,convective thermodynamic and large-scale forcings were investigated to explain the model differences in extreme rainfall distributions and hourly variations.The results indicated that in single coarser grids(15 km and 9 km),the extreme rainfall amount was largely underestimated with all three PBL schemes.In the inner 1-km grid,the underestimated intensity was improved;however,using the MYNN scheme for the 1-km grid domain with explicitly resolved convection and nested within the 9-km grid using the Kain−Fritsch cumulus scheme,significant advantages over the other PBL schemes are revealed in predicting the extreme rainfall distribution and the time of primary peak rainfall.MYNN,with the weakest vertical mixing,produced the shallowest and most humid inversion layer with the lowest lifting condensation level,but stronger wind fields and upward motions from the top of the boundary layer to upper levels.These factors all facilitate the development of deep convection and moisture transport for intense precipitation,and result in its most realistic prediction of the primary rainfall peak.展开更多
High Spatial and Spectral Resolution(HSSR)remote-sensing images can provide rich spectral bands and detailed ground information,but there is a relative lack of research on this new type of remote-sensing data.Although...High Spatial and Spectral Resolution(HSSR)remote-sensing images can provide rich spectral bands and detailed ground information,but there is a relative lack of research on this new type of remote-sensing data.Although there are already some HSSR datasets for deep learning model training and testing,the data volume of these datasets is small,resulting in low classification accuracy and weak generalization ability of the trained models.In this paper,an HSSR dataset Luojia-HSSR is constructed based on aerial hyperspectral imagery of southern Shenyang City of Liaoning Province in China.To our knowledge,it is the largest HSSR dataset to date,with 6438 pairs of 256×256 sized samples(including 3480 pairs in the training set,2209 pairs in the test set,and 749 pairs in the validation set),covering area of 161 km2 with spatial resolution 0.75 m,249 Visible and Near-Infrared(VNIR)spectral bands,and corresponding to 23 classes of field-validated ground coverage.It is an ideal experimental data for spatial-spectral feature extraction.Furthermore,a new deep learning model 3D-HRNet for interpreting HSSR images is proposed.The conv-neck in HRNet is modified to better mine the spatial information of the images.Then,a 3D convolution module with attention mechanism is designed to capture the global-local fine spectral information simultaneously.Subsequently,the 3D convolution is inserted into the HRNet to optimize the performance.The experiments show that the 3D-HRNet model has good interpreting ability for the Luojia-HSSR dataset with the Frequency Weighted Intersection over Union(FWIoU)reaching 80.54%,indicating that the Luojia-HSSR dataset constructed in this paper and the proposed 3D-HRnet model have good applicable prospects for processing HSSR remote sensing images.展开更多
Objective： To explore water soluble metabolite features of brain tumor specimens with HRMAS-^1HMRS and its potential clinical value. Methods： There were thirty cases of pathologically proven brain tumor, including 6...Objective： To explore water soluble metabolite features of brain tumor specimens with HRMAS-^1HMRS and its potential clinical value. Methods： There were thirty cases of pathologically proven brain tumor, including 6 Ⅰ-Ⅱ grade astrocytomas, 7 Ⅲ grade anaplastic astrocytomas, 10 IV grade glioblastomas and 7 meningiomas. Used Varian Company 600 MHz spectrometer with the Nano-probe for acquisition HRMASJHMRS, which was postprocessed with jMRUI 3.2 version software. These metabolic probability and their ratios to Cr were summed. Results： （1） HRMAS-^1HMRS could resolve NAA, PCr/Cr, GPC ± PCho ± Cho, Glu/GIn, Gly, Tau, Ala, Lac, ml and so on. All samples showed Lac, 6 samples showed unknown single peak at 3.72 ppm or 3.90 ppm. （2） The mean Cho/Cr of 6 Ⅰ-ⅡI grade astrocytomas was 2.42 ± 1.01 （P = 0.003, compared with glioblastoma）. The mean Cho/Cr of 7 anaplastic astrocytomas was 3.48 ± 0.59 （P = 0.01, compared with glioblastoma）. The Cho/Cr of 10 glioblastomas broadly ranged from 0.9 to 11.3 （mean 5.40 ± 1.23）. From Ⅰ-Ⅱ grade astrocytoma to glioblastoma, Ala/Cr, Tau/Cr and Gly/Cr trends were increased; the mean Ala/Cr of glioma was 0.31 ± 0.13. （3） Meningiomas showed higher Ala and Cho. Their Cr was lower than that of gliomas. 4/7 cases had no NAA, 3/7 patients had lower NAA. Mean Cho/Cr was 3.56 ± 1.01, Ala/Cr was 0.53 ±0.28 （P = 0.006, compared with glioma）. Conclusion： HRMAS-^1HMRS can show further details in vivo MRS, resolve in vivo spectroscopic metabolite of Cho compound and differentiate the extent of benign and malignant glioma. With the increase in the malignant degree of gliomas, Cho, ml, Ala, Tau and Gly will increase. HRMAS-^1HMRS is the only method of isotropic spectroscopy for pathological specimens.展开更多
Artifi cial neural network is a kind of artificial intelligence method to simulate the function of human brain, and deep learning technology can establish a depth network model with hierarchical structure on the basis...Artifi cial neural network is a kind of artificial intelligence method to simulate the function of human brain, and deep learning technology can establish a depth network model with hierarchical structure on the basis of artificial neural network. Deep learning brings new development direction to artificial neural network. Convolution neural network is a new artificial neural network method, which combines artificial neural network and deep learning technology, and this new neural network is widely used in many fields of computer vision. Modern image recognition algorithm requires classifi cation system to adapt to different types of tasks, and deep network and convolution neural network is a hot research topic in neural networks. According to the characteristics of satellite digital image, we use the convolution neural network to classify the image, which combines texture features with spectral features. The experimental results show that the convolution neural network algorithm can effectively classify the image.展开更多
Infrared(IR) optics have garnered significant attention due to growing demands in advanced optical imaging,communication, detection, and sensing. Among various IR devices, microlenses and microlens arrays offer distin...Infrared(IR) optics have garnered significant attention due to growing demands in advanced optical imaging,communication, detection, and sensing. Among various IR devices, microlenses and microlens arrays offer distinct advantages in integration capability, imaging precision, multifunctionality, and cost-effective manufacturing. We present a novel design of high-resolution achromatic microlens in the mid-IR region. Different from traditional high-refractive-index convex microlenses embedded within a low-index background medium, the current design is a low-index air concave microlens embedded within a high-index silicon medium. The designed air microlens exhibits capabilities in high-resolution imaging(~λ/6) and achromatic performance across the 3–5 μm mid-IR spectrum. The air microlens could be assembled in large-area microlens arrays or as part of multi-lens system.When combined with the HgCdTe detector system placed on the focal plane, the air microlens can find promising applications in high-resolution optical imaging and high-sensitivity photoelectric detection.展开更多
Block copolymer(BCP) nanolithography offers potential beyond traditional photolithographic limits, yet reliably producing low-defect, perpendicular domains remains challenging. We introduce a microenvironmentdriven is...Block copolymer(BCP) nanolithography offers potential beyond traditional photolithographic limits, yet reliably producing low-defect, perpendicular domains remains challenging. We introduce a microenvironmentdriven isothermal annealing method for directed self-assembly of BCP thin films. By annealing films at stable temperature in a quasi-sealed, inert-gas chamber, our approach promotes highly uniform perpendicular lamellar nanopatterns over large areas, effectively mitigating environmental fluctuations and emulating solvent-vapor annealing without solvent exposure. Resulting BCP structures demonstrate enhanced spatial coherence and notably low defect density. Furthermore, we successfully transfer these nanopatterns into precise metal nano-line arrays,confirming the method's capability for high-fidelity pattern replication. This scalable, solvent-free technique provides a robust, reliable route for high-resolution nanopatterning in advanced semiconductor manufacturing.展开更多
A method is proposed for high-resolution neutron spectrum regulation across the entire energy domain.It was applied to in-reactor transuranic isotope production.This method comprises four modules:a neutron spectrum pe...A method is proposed for high-resolution neutron spectrum regulation across the entire energy domain.It was applied to in-reactor transuranic isotope production.This method comprises four modules:a neutron spectrum perturbation module,a neutron spectrum calculation module,a neutron spectrum valuation module,and an intelligent optimization module.It makes it possible to determine the optimal neutron spectrum for transuranic isotope production and a regulation scheme to establish this neutron spectrum within the reactor.The state-of-the-art production schemes for^(252)Cf and^(238)Pu in the High Flux Isotope Reactor were optimized,improving the yield of^(252)Cf by 12.16%and that of^(238)Pu by 7.53-25.84%.Moreover,the proposed optimization schemes only disperse certain nuclides into the targets without modifying the reactor design parameters,making them simple and feasible.The new method achieves efficient and precise neutron spectrum optimization,maximizing the production of transuranic isotopes.展开更多
Airborne hyperspectral imaging spectrometers have been used for Earth observation over the past four decades.Despite the high sensitivity of push-broom hyperspectral imagers,they experience limited swath and wavelengt...Airborne hyperspectral imaging spectrometers have been used for Earth observation over the past four decades.Despite the high sensitivity of push-broom hyperspectral imagers,they experience limited swath and wavelength coverage.In this study,we report the development of a push-broom airborne multimodular imaging spectrometer(AMMIS)that spans ultraviolet(UV),visible near-infrared(VNIR),shortwave infrared(SWIR),and thermal infrared(TIR)wavelengths.As an integral part of China's HighResolution Earth Observation Program,AMMIS is intended for civilian applications and for validating key technologies for future spaceborne hyperspectral payloads.It has been mounted on aircraft platforms such as Y-5,Y-12,and XZ-60.Since 2016,AMMIS has been used to perform more than 30 flight campaigns and gather more than 200 TB of hyperspectral data.This study describes the system design,calibration techniques,performance tests,flight campaigns,and applications of the AMMIS.The system integrates UV,VNIR,SWIR,and TIR modules,which can be operated in combination or individually based on the application requirements.Each module includes three spectrometers,utilizing field-of-view(FOV)stitching technology to achieve a 40°FOV,thereby enhancing operational efficiency.We designed advanced optical systems for all modules,particularly for the TIR module,and employed cryogenic optical technology to maintain optical system stability at 100 K.Both laboratory and in-flight calibrations were conducted to improve preprocessing accuracy and produce high-quality hyperspectral data.The AMMIS features more than 1400 spectral bands,with spectral sampling intervals of 0.1 nm for UV,2.4 nm for VNIR,3 nm for SWIR,and 32 nm for TIR.In addition,the instantaneous fields of view(IFoVs)for the four modules were 0.5,0.25,0.5,and 1 mrad,respectively,with the VNIR module achieving an IFoV of 0.125 mrad in the high-spatial-resolution mode.This study reports on land-cover surveys,pollution gas detection,mineral exploration,coastal water detection,and plant investigations conducted using AMMIS,highlighting its excellent performance.Furthermore,we present three hyperspectral datasets with diverse scene distributions and categories suitable for developing artificial intelligence algorithms.This study paves the way for next-generation airborne and spaceborne hyperspectral payloads and serves as a valuable reference for hyperspectral sensor designers and data users.展开更多
Synthesizing a real⁃time,high⁃resolution,and lip⁃sync digital human is a challenging task.Although the Wav2Lip model represents a remarkable advancement in real⁃time lip⁃sync,its clarity is still limited.To address th...Synthesizing a real⁃time,high⁃resolution,and lip⁃sync digital human is a challenging task.Although the Wav2Lip model represents a remarkable advancement in real⁃time lip⁃sync,its clarity is still limited.To address this,we enhanced the Wav2Lip model in this study and trained it on a high⁃resolution video dataset produced in our laboratory.Experimental results indicate that the improved Wav2Lip model produces digital humans with greater clarity than the original model,while maintaining its real⁃time performance and accurate lip⁃sync.We implemented the improved Wav2Lip model in a government interface application,generating a government digital human.Testing revealed that this government digital human can interact seamlessly with users in real⁃time,delivering clear visuals and synthesized speech that closely resembles a human voice.展开更多
Characterization of vegetation effect on soil response is essential for comprehending site-specific hydrological processes.Traditional research often relies on sensors or remote sensing data to examine the hydrologica...Characterization of vegetation effect on soil response is essential for comprehending site-specific hydrological processes.Traditional research often relies on sensors or remote sensing data to examine the hydrological properties of vegetation zones,yet these methods are limited by either measurement sparsity or spatial inaccuracy.Therefore,this paper is the first to propose a data-driven approach that incorporates high-temporal-resolution electrical resistivity tomography(ERT)to quantify soil hydrological response.Time-lapse ERT is deployed on a vegetated slope site in Foshan,China,during a discontinuous rainfall induced by Typhoon Haikui.A total of 97 ERT measurements were collected with an average time interval of 2.7 hours.The Gaussian Mixture Model(GMM)is applied to quantify the level of response and objectively classify impact zones based on features extracted directly from the ERT data.The resistivity-moisture content correlation is established based on on-site sensor data to characterize infiltration and evapotranspiration across wet-dry conditions.The findings are compared with the Normalized Difference Vegetation Index(NDVI),a common indicator for vegetation quantification,to reveal potential spatial errors in remote sensing data.In addition,this study provides discussions on the potential applications and future directions.This paper showcases significant spatio-temporal advantages over existing studies,providing a more detailed and accurate characterization of superficial soil hydrological response.展开更多
We have presented a high resolution spectroscopy of Rb in magnetic field by far-detuning electromagnetically induced transparency(EIT).The EIT spectrum in theΞ-type configuration is usually companied by a double reso...We have presented a high resolution spectroscopy of Rb in magnetic field by far-detuning electromagnetically induced transparency(EIT).The EIT spectrum in theΞ-type configuration is usually companied by a double resonance optical pumping(DROP)due to the strong optical coupling between the two upper states,leading to the spectral lines seriously deformed and widely broadened for complex relaxation processes in DROP.Here we demonstrate a high resolution spectroscopy by far-detuning EIT for^(87)Rb 5S_(1/2)→5P_(3/2)→5D_(5/2)in magnetic fields.The method of far-detuning eliminates the relaxation in DROP to the most extent and decreases the spectral linewidth from more than 20 MHz down to its natural linewidth limit(6 MHz).The deformation of the spectral lines also disappears and the observed spectra are well in accordance with the theoretical calculation.Our work shows that far-detuning EIT is a reliable high resolution spectroscopic method when the relaxation in DROP cannot be neglected,especially for the case of transition to low excited states.展开更多
The present paper investigates the application of high resolution magnetic survey to detecting igneous bodies. The slight difference in magnetism between igneous bodies and their surrounding rocks is measured first an...The present paper investigates the application of high resolution magnetic survey to detecting igneous bodies. The slight difference in magnetism between igneous bodies and their surrounding rocks is measured first and then the magnetic survey data are processed to determine whether there exist igneous bodies by analog among several measuring lines, and finally the modified Marquart inversion was used to determine the occurrence and distribution of the igneous bodies.展开更多
After successfully locating one abandoned brine well by an electromagnetic method during testing in 2001 and five abandoned brine wells by a high resolution magnetic method during 2002, a high resolution magnetic meth...After successfully locating one abandoned brine well by an electromagnetic method during testing in 2001 and five abandoned brine wells by a high resolution magnetic method during 2002, a high resolution magnetic method was again proposed to search for wells in 2003 when a second sensor was employed to acquire data for calculating the pseudo vertical gradient of magnetic fields. Total area surveyed in 2003 was 1,024,000 ft 2, which was divided into grids with an average size of 10,000 ft 2 and distributed across eight different sites. Magnetic anomalies and their vertical gradients from known brine wells were first recorded as signatures to identify anomalies caused by possible buried brine wells. Of fifty one verified anomalies, thirty one anomalies were due to wells buried at depths from 0 to 8.5 ft: twenty one 6 to 9 inch abandoned brine wells, seven 1.5 to 3 inch probable water wells, one 16 inch dewatering well for a construction site at a depth of 3 ft, and two 4 inch wells on the ground surface. Approximate monopole shaped anomalies were observed from all these wells after data corrections. However, the range of amplitudes of magnetic anomalies from 7,000 to 28,000 nT from these abandoned brine wells was measured. This range of anomalies is mainly due to the thickness and depth of buried wells. Anomaly amplitudes from 1.5 to 3 inch wells are 4,000 to 8,000 nT and linearly correlate with the buried depth. One 3 inch well that caused an anomaly of 13,000 nT could be the inner pipe of a brine well. Gradient anomalies are roughly in a range of 100 to 200 nT/inch for 1.5 to 3 inch wells and 200 to 300 nT/inch for brine wells.As indicated by the potential field theory, gradient data possess higher horizontal resolution than the magnetic field itself. Gradient data provide valuable assistance in determining horizontal locations of anomaly sources for excavation. In practice, however, improvement in the horizontal resolution is limited by survey line spacing. If only one sensor is used in a survey, there is rapid decrease in the horizontal resolution when sensor height increases from 14 to 44 inches. This indicates that it is critical to keep the sensor as close to the ground as possible when hunting buried wells that are close to each other. It also suggests that the downward continuation is useful to increase the horizontal resolution in well hunting.展开更多
We develop a high resolution ground penetrating radar system （LANRCS-GPR） based on the E5071B Vector Network Analyzer （VNA）. This system takes advantage of a wideband and adjustable frequency domain ground penetra...We develop a high resolution ground penetrating radar system （LANRCS-GPR） based on the E5071B Vector Network Analyzer （VNA）. This system takes advantage of a wideband and adjustable frequency domain ground penetrating radar system and adds the characteristics of a network analyzer with ultra-wideband and high precision measurement. It adopts the LAN mode to concatenate system control that reduces construction cost and makes the system easy to expand. The high resolution ground penetrating radar system carries out real time imaging using F-K migration with high calculation efficiency. The experiment results of the system indicate that the LANRCS-GPR system provides high resolution and precision, high signal-to-noise ratio, and great dynamic range. Furthermore, the LANRCS-GPR system is flexible and reliable to operate with easy to expand system functions. The research and development of the LANRCS-GPR provide the theoretical and experimental foundation for future frequency domain ground penetrating radar production and also can serve as an experimental platform with high data gathering precision, enormous information capability, wide application, and convenient operation for electromagnetic wave research and electromagnetic exploration.展开更多
The combination of pyrolysis high resolution gas chromatography and pat- tern recognition techniques is a powerful tool for the classification of traditional Chinese drug.A study has been completed on 55 Beimu samples...The combination of pyrolysis high resolution gas chromatography and pat- tern recognition techniques is a powerful tool for the classification of traditional Chinese drug.A study has been completed on 55 Beimu samples of five different geographic origins: Eastern China.Central China.South-western China,North-western China and North-eastern China.Principal component analysis and SIMCA are applied to effectively classifying the samples according to the origin of the plants.The chemical information contained in the high resolution gas chromatographic data is sufficient to characterize the geographic origin of sam- pies.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.42250103,42174090,42250101,42250102,and 41774091)the Macao Foundation+1 种基金the Opening Fund of Key Laboratory of Geological Survey and Evaluation of Ministry of Education(Grant No.GLAB2023ZR02)the MOST Special Fund from the State Key Laboratory of Geological Processes and Mineral Resources(Grant No.MSFGPMR2022-4)。
文摘The CUG_CLMFM3D series comprises high-resolution three-dimensional lithospheric magnetic field models for China and its surroundings.The first version,CUG_CLMFM3Dv1,is a spherical cap harmonic model integrating the WDMAMv2(World Digital Magnetic Anomaly Map version 2)global magnetic anomaly grid and nearly a decade of CHAMP(Challenging Minisatellite Payload for Geophysical Research and Application)satellite vector data.It achieves a~5.7 km resolution but has limitations:the WDMAMv2 grid lacks high-resolution data in the southern Xinjiang and Tibet regions,which leads to missing small-to medium-scale anomalies,and unfiltered CHAMP data introduce low-frequency conflicts with global spherical harmonic models.Above the altitude of 150 km,correlations with global models drop below 0.9.The second version,CUG_CLMFM3Dv2,addresses these issues by incorporating 5-km-resolution aeromagnetic data and rigorously processed satellite data from CHAMP,Swarm,CSES-1(China Seismo-Electromagnetic Satellite 1),and MSS-1(Macao Science Satellite 1).The comparison analysis shows that the CUG_CLMFM3Dv2 captures finer high-frequency details and more stable long-wavelength signals,offering improved magnetic anomaly maps for further geological and geophysical studies.
基金co-supported by the National Natural Science Foundation of China(Nos.U1833117 and 61806015)the National Key Research and Development Program of China(No.2017YFB0503402)。
文摘The aircraft system has recently gained its reputation as a reliable and efficient tool for sensing and parsing aerial scenes.However,accurate and fast semantic segmentation of highresolution aerial images for remote sensing applications is still facing three challenges:the requirements for limited processing resources and low-latency operations based on aerial platforms,the balance between high accuracy and real-time efficiency for model performance,and the confusing objects with large intra-class variations and small inter-class differences in high-resolution aerial images.To address these issues,a lightweight and dual-path deep convolutional architecture,namely Aerial Bilateral Segmentation Network(Aerial-Bi Se Net),is proposed to perform realtime segmentation on high-resolution aerial images with favorable accuracy.Specifically,inspired by the receptive field concept in human visual systems,Receptive Field Module(RFM)is proposed to encode rich multi-scale contextual information.Based on channel attention mechanism,two novel modules,called Feature Attention Module(FAM)and Channel Attention based Feature Fusion Module(CAFFM)respectively,are proposed to refine and combine features effectively to boost the model performance.Aerial-Bi Se Net is evaluated on the Potsdam and Vaihingen datasets,where leading performance is reported compared with other state-of-the-art models,in terms of both accuracy and efficiency.
基金financial supports from National Natural Science Foundation of China(Grant Nos.U23A20368 and 62175006)Academic Excellence Foundation of BUAA for PhD Students.
文摘Due to the limitations of spatial bandwidth product and data transmission bandwidth,the field of view,resolution,and imaging speed constrain each other in an optical imaging system.Here,a fast-zoom and high-resolution sparse compound-eye camera(CEC)based on dual-end collaborative optimization is proposed,which provides a cost-effective way to break through the trade-off among the field of view,resolution,and imaging speed.In the optical end,a sparse CEC based on liquid lenses is designed,which can realize large-field-of-view imaging in real time,and fast zooming within 5 ms.In the computational end,a disturbed degradation model driven super-resolution network(DDMDSR-Net)is proposed to deal with complex image degradation issues in actual imaging situations,achieving high-robustness and high-fidelity resolution enhancement.Based on the proposed dual-end collaborative optimization framework,the angular resolution of the CEC can be enhanced from 71.6"to 26.0",which provides a solution to realize high-resolution imaging for array camera dispensing with high optical hardware complexity and data transmission bandwidth.Experiments verify the advantages of the CEC based on dual-end collaborative optimization in high-fidelity reconstruction of real scene images,kilometer-level long-distance detection,and dynamic imaging and precise recognition of targets of interest.
基金Supported by the Key Research and Development Plan of Shaanxi Province,No.2021SF-298.
文摘BACKGROUND Neurovascular compression(NVC) is the main cause of primary trigeminal neuralgia(TN) and hemifacial spasm(HFS). Microvascular decompression(MVD) is an effective surgical method for the treatment of TN and HFS caused by NVC. The judgement of NVC is a critical step in the preoperative evaluation of MVD, which is related to the effect of MVD treatment. Magnetic resonance imaging(MRI) technology has been used to detect NVC prior to MVD for several years. Among many MRI sequences, three-dimensional time-of-flight magnetic resonance angiography(3D TOF MRA) is the most widely used. However, 3D TOF MRA has some shortcomings in detecting NVC. Therefore, 3D TOF MRA combined with high resolution T2-weighted imaging(HR T2WI) is considered to be a more effective method to detect NVC.AIM To determine the value of 3D TOF MRA combined with HR T2WI in the judgment of NVC, and thus to assess its value in the preoperative evaluation of MVD.METHODS Related studies published from inception to September 2022 based on PubMed, Embase, Web of Science, and the Cochrane Library were retrieved. Studies that investigated 3D TOF MRA combined with HR T2WI to judge NVC in patients with TN or HFS were included according to the inclusion criteria. Studies without complete data or not relevant to the research topics were excluded. The Quality Assessment of Diagnostic Accuracy Studies checklist was used to assess the quality of included studies. The publication bias of the included literature was examined by Deeks’ test. An exact binomial rendition of the bivariate mixed-effects regression model was used to synthesize data. Data analysis was performed using the MIDAS module of statistical software Stata 16.0. Two independent investigators extracted patient and study characteristics, and discrepancies were resolved by consensus. Individual and pooled sensitivities and specificities were calculated. The I_(2) statistic and Q test were used to test heterogeneity. The study was registered on the website of PROSERO(registration No. CRD42022357158).RESULTS Our search identified 595 articles, of which 12(including 855 patients) fulfilled the inclusion criteria. Bivariate analysis showed that the pooled sensitivity and specificity of 3D TOF MRA combined with HR T2WI for detecting NVC were 0.96 [95% confidence interval(CI): 0.92-0.98] and 0.92(95%CI: 0.74-0.98), respectively. The pooled positive likelihood ratio was 12.4(95%CI: 3.2-47.8), pooled negative likelihood ratio was 0.04(95%CI: 0.02-0.09), and pooled diagnostic odds ratio was 283(95%CI: 50-1620). The area under the receiver operating characteristic curve was 0.98(95%CI: 0.97-0.99). The studies showed no substantial heterogeneity(I2 = 0, Q = 0.001 P = 0.50).CONCLUSION Our results suggest that 3D TOF MRA combined with HR T2WI has excellent sensitivity and specificity for judging NVC in patients with TN or HFS. This method can be used as an effective tool for preoperative evaluation of MVD.
基金the National Science Fund for Distinguished Young Scholars of China (No. 51625501)the Aeronautical Science Foundation of China (No. 201946051002)
文摘Small-object detection has long been a challenge.High-megapixel cameras are used to solve this problem in industries.However,current detectors are inefficient for high-resolution images.In this work,we propose a new module called Pre-Locate Net,which is a plug-and-play structure that can be combined with most popular detectors.We inspire the use of classification ideas to obtain candidate regions in images,greatly reducing the amount of calculation,and thus achieving rapid detection in high-resolution images.Pre-Locate Net mainly includes two parts,candidate region classification and behavior classification.Candidate region classification is used to obtain a candidate region,and behavior classification is used to estimate the scale of an object.Different follow-up processing is adopted according to different scales to balance the variance of the network input.Different from the popular candidate region generation method,we abandon the idea of regression of a bounding box and adopt the concept of classification,so as to realize the prediction of a candidate region in the shallow network.We build a high-resolution dataset of aircraft and landing gears covering complex scenes to verify the effectiveness of our method.Compared to state-of-the-art detectors(e.g.,Guided Anchoring,Libra-RCNN,and FASF),our method achieves the best m AP of 94.5 on 1920×1080 images at 16.7 FPS.
基金This research was supported by the National Natural Science Foundation of China(Grant No.41730646)National Natural Science Foundation for Young Scientists of China(Grant No.41605079)the National Key R&D Program of China(Grant No.2018YFC1507702)。
文摘In this study,an extreme rainfall event that occurred on 25 May 2018 over Shanghai and its nearby area was simulated using the Weather Research and Forecasting model,with a focus on the effects of planetary boundary layer(PBL)physics using double nesting with large grid ratios(15:1 and 9:1).The sensitivity of the precipitation forecast was examined through three PBL schemes:the Yonsei University Scheme,the Mellor−Yamada−Nakanishi Niino Level 2.5(MYNN)scheme,and the Mellor−Yamada−Janjic scheme.The PBL effects on boundary layer structures,convective thermodynamic and large-scale forcings were investigated to explain the model differences in extreme rainfall distributions and hourly variations.The results indicated that in single coarser grids(15 km and 9 km),the extreme rainfall amount was largely underestimated with all three PBL schemes.In the inner 1-km grid,the underestimated intensity was improved;however,using the MYNN scheme for the 1-km grid domain with explicitly resolved convection and nested within the 9-km grid using the Kain−Fritsch cumulus scheme,significant advantages over the other PBL schemes are revealed in predicting the extreme rainfall distribution and the time of primary peak rainfall.MYNN,with the weakest vertical mixing,produced the shallowest and most humid inversion layer with the lowest lifting condensation level,but stronger wind fields and upward motions from the top of the boundary layer to upper levels.These factors all facilitate the development of deep convection and moisture transport for intense precipitation,and result in its most realistic prediction of the primary rainfall peak.
基金supported by the Major Program of the National Natural Science Foundation of China[grant number 92038301]The research was also supported by the National Natural Science Foundation of China[grant number 41971295]+1 种基金the Foundation for Innovative Research Groups of the Natural Science Foundation of Hubei Province[grant number 2020CFA003]the Special Fund of Hubei Luojia Laboratory.
文摘High Spatial and Spectral Resolution(HSSR)remote-sensing images can provide rich spectral bands and detailed ground information,but there is a relative lack of research on this new type of remote-sensing data.Although there are already some HSSR datasets for deep learning model training and testing,the data volume of these datasets is small,resulting in low classification accuracy and weak generalization ability of the trained models.In this paper,an HSSR dataset Luojia-HSSR is constructed based on aerial hyperspectral imagery of southern Shenyang City of Liaoning Province in China.To our knowledge,it is the largest HSSR dataset to date,with 6438 pairs of 256×256 sized samples(including 3480 pairs in the training set,2209 pairs in the test set,and 749 pairs in the validation set),covering area of 161 km2 with spatial resolution 0.75 m,249 Visible and Near-Infrared(VNIR)spectral bands,and corresponding to 23 classes of field-validated ground coverage.It is an ideal experimental data for spatial-spectral feature extraction.Furthermore,a new deep learning model 3D-HRNet for interpreting HSSR images is proposed.The conv-neck in HRNet is modified to better mine the spatial information of the images.Then,a 3D convolution module with attention mechanism is designed to capture the global-local fine spectral information simultaneously.Subsequently,the 3D convolution is inserted into the HRNet to optimize the performance.The experiments show that the 3D-HRNet model has good interpreting ability for the Luojia-HSSR dataset with the Frequency Weighted Intersection over Union(FWIoU)reaching 80.54%,indicating that the Luojia-HSSR dataset constructed in this paper and the proposed 3D-HRnet model have good applicable prospects for processing HSSR remote sensing images.
文摘Objective： To explore water soluble metabolite features of brain tumor specimens with HRMAS-^1HMRS and its potential clinical value. Methods： There were thirty cases of pathologically proven brain tumor, including 6 Ⅰ-Ⅱ grade astrocytomas, 7 Ⅲ grade anaplastic astrocytomas, 10 IV grade glioblastomas and 7 meningiomas. Used Varian Company 600 MHz spectrometer with the Nano-probe for acquisition HRMASJHMRS, which was postprocessed with jMRUI 3.2 version software. These metabolic probability and their ratios to Cr were summed. Results： （1） HRMAS-^1HMRS could resolve NAA, PCr/Cr, GPC ± PCho ± Cho, Glu/GIn, Gly, Tau, Ala, Lac, ml and so on. All samples showed Lac, 6 samples showed unknown single peak at 3.72 ppm or 3.90 ppm. （2） The mean Cho/Cr of 6 Ⅰ-ⅡI grade astrocytomas was 2.42 ± 1.01 （P = 0.003, compared with glioblastoma）. The mean Cho/Cr of 7 anaplastic astrocytomas was 3.48 ± 0.59 （P = 0.01, compared with glioblastoma）. The Cho/Cr of 10 glioblastomas broadly ranged from 0.9 to 11.3 （mean 5.40 ± 1.23）. From Ⅰ-Ⅱ grade astrocytoma to glioblastoma, Ala/Cr, Tau/Cr and Gly/Cr trends were increased; the mean Ala/Cr of glioma was 0.31 ± 0.13. （3） Meningiomas showed higher Ala and Cho. Their Cr was lower than that of gliomas. 4/7 cases had no NAA, 3/7 patients had lower NAA. Mean Cho/Cr was 3.56 ± 1.01, Ala/Cr was 0.53 ±0.28 （P = 0.006, compared with glioma）. Conclusion： HRMAS-^1HMRS can show further details in vivo MRS, resolve in vivo spectroscopic metabolite of Cho compound and differentiate the extent of benign and malignant glioma. With the increase in the malignant degree of gliomas, Cho, ml, Ala, Tau and Gly will increase. HRMAS-^1HMRS is the only method of isotropic spectroscopy for pathological specimens.
文摘Artifi cial neural network is a kind of artificial intelligence method to simulate the function of human brain, and deep learning technology can establish a depth network model with hierarchical structure on the basis of artificial neural network. Deep learning brings new development direction to artificial neural network. Convolution neural network is a new artificial neural network method, which combines artificial neural network and deep learning technology, and this new neural network is widely used in many fields of computer vision. Modern image recognition algorithm requires classifi cation system to adapt to different types of tasks, and deep network and convolution neural network is a hot research topic in neural networks. According to the characteristics of satellite digital image, we use the convolution neural network to classify the image, which combines texture features with spectral features. The experimental results show that the convolution neural network algorithm can effectively classify the image.
基金supported by the Science and Technology Project of Guangdong Province, China (Grant No. 2020B010190001)the National Natural Science Foundation of China (Grant No. 12434016)the National Key Research and Development Program of China (Grant No. 2018YFA0306200)。
文摘Infrared(IR) optics have garnered significant attention due to growing demands in advanced optical imaging,communication, detection, and sensing. Among various IR devices, microlenses and microlens arrays offer distinct advantages in integration capability, imaging precision, multifunctionality, and cost-effective manufacturing. We present a novel design of high-resolution achromatic microlens in the mid-IR region. Different from traditional high-refractive-index convex microlenses embedded within a low-index background medium, the current design is a low-index air concave microlens embedded within a high-index silicon medium. The designed air microlens exhibits capabilities in high-resolution imaging(~λ/6) and achromatic performance across the 3–5 μm mid-IR spectrum. The air microlens could be assembled in large-area microlens arrays or as part of multi-lens system.When combined with the HgCdTe detector system placed on the focal plane, the air microlens can find promising applications in high-resolution optical imaging and high-sensitivity photoelectric detection.
基金supported by the National Natural Science Foundation of China (Grant Nos.U20A20168 and 62404120)the National Key R&D Program (Grant No.2022YFB3204100)+2 种基金the Postdoctoral Fellowship Program of CPSF (Grant Nos.GZB20240335 and GZC20231216)the China Postdoctoral Science Foundation (Grant No.2025T180151)the Initiative Scientific Research Program of the School of Integrated Circuits,Tsinghua University。
文摘Block copolymer(BCP) nanolithography offers potential beyond traditional photolithographic limits, yet reliably producing low-defect, perpendicular domains remains challenging. We introduce a microenvironmentdriven isothermal annealing method for directed self-assembly of BCP thin films. By annealing films at stable temperature in a quasi-sealed, inert-gas chamber, our approach promotes highly uniform perpendicular lamellar nanopatterns over large areas, effectively mitigating environmental fluctuations and emulating solvent-vapor annealing without solvent exposure. Resulting BCP structures demonstrate enhanced spatial coherence and notably low defect density. Furthermore, we successfully transfer these nanopatterns into precise metal nano-line arrays,confirming the method's capability for high-fidelity pattern replication. This scalable, solvent-free technique provides a robust, reliable route for high-resolution nanopatterning in advanced semiconductor manufacturing.
基金sponsored by the National Natural Science Foundation of China(No.12305190)the Lingchuang Research Project of the China National Nuclear Corporation(CNNC)。
文摘A method is proposed for high-resolution neutron spectrum regulation across the entire energy domain.It was applied to in-reactor transuranic isotope production.This method comprises four modules:a neutron spectrum perturbation module,a neutron spectrum calculation module,a neutron spectrum valuation module,and an intelligent optimization module.It makes it possible to determine the optimal neutron spectrum for transuranic isotope production and a regulation scheme to establish this neutron spectrum within the reactor.The state-of-the-art production schemes for^(252)Cf and^(238)Pu in the High Flux Isotope Reactor were optimized,improving the yield of^(252)Cf by 12.16%and that of^(238)Pu by 7.53-25.84%.Moreover,the proposed optimization schemes only disperse certain nuclides into the targets without modifying the reactor design parameters,making them simple and feasible.The new method achieves efficient and precise neutron spectrum optimization,maximizing the production of transuranic isotopes.
基金supported by the Shanghai Industrial Collaborative Innovation Fund(HCXBCY-2021-001)the Academy of Finland(349229)。
文摘Airborne hyperspectral imaging spectrometers have been used for Earth observation over the past four decades.Despite the high sensitivity of push-broom hyperspectral imagers,they experience limited swath and wavelength coverage.In this study,we report the development of a push-broom airborne multimodular imaging spectrometer(AMMIS)that spans ultraviolet(UV),visible near-infrared(VNIR),shortwave infrared(SWIR),and thermal infrared(TIR)wavelengths.As an integral part of China's HighResolution Earth Observation Program,AMMIS is intended for civilian applications and for validating key technologies for future spaceborne hyperspectral payloads.It has been mounted on aircraft platforms such as Y-5,Y-12,and XZ-60.Since 2016,AMMIS has been used to perform more than 30 flight campaigns and gather more than 200 TB of hyperspectral data.This study describes the system design,calibration techniques,performance tests,flight campaigns,and applications of the AMMIS.The system integrates UV,VNIR,SWIR,and TIR modules,which can be operated in combination or individually based on the application requirements.Each module includes three spectrometers,utilizing field-of-view(FOV)stitching technology to achieve a 40°FOV,thereby enhancing operational efficiency.We designed advanced optical systems for all modules,particularly for the TIR module,and employed cryogenic optical technology to maintain optical system stability at 100 K.Both laboratory and in-flight calibrations were conducted to improve preprocessing accuracy and produce high-quality hyperspectral data.The AMMIS features more than 1400 spectral bands,with spectral sampling intervals of 0.1 nm for UV,2.4 nm for VNIR,3 nm for SWIR,and 32 nm for TIR.In addition,the instantaneous fields of view(IFoVs)for the four modules were 0.5,0.25,0.5,and 1 mrad,respectively,with the VNIR module achieving an IFoV of 0.125 mrad in the high-spatial-resolution mode.This study reports on land-cover surveys,pollution gas detection,mineral exploration,coastal water detection,and plant investigations conducted using AMMIS,highlighting its excellent performance.Furthermore,we present three hyperspectral datasets with diverse scene distributions and categories suitable for developing artificial intelligence algorithms.This study paves the way for next-generation airborne and spaceborne hyperspectral payloads and serves as a valuable reference for hyperspectral sensor designers and data users.
基金Sponsored by Collaborative Education Projects Between Industry and Academia by Ministry of Education(Grant No.230801065261444)Humanities and Social Sciences Pre Research Fund Project of Zhejiang University of Technology(Grant No.SKY-ZX-20220207).
文摘Synthesizing a real⁃time,high⁃resolution,and lip⁃sync digital human is a challenging task.Although the Wav2Lip model represents a remarkable advancement in real⁃time lip⁃sync,its clarity is still limited.To address this,we enhanced the Wav2Lip model in this study and trained it on a high⁃resolution video dataset produced in our laboratory.Experimental results indicate that the improved Wav2Lip model produces digital humans with greater clarity than the original model,while maintaining its real⁃time performance and accurate lip⁃sync.We implemented the improved Wav2Lip model in a government interface application,generating a government digital human.Testing revealed that this government digital human can interact seamlessly with users in real⁃time,delivering clear visuals and synthesized speech that closely resembles a human voice.
基金support from the National Key R&D Program of China(2021YFC3001003)Guangdong Provincial Department of Science and Technology(2022A0505030019)Science and Technology Development Fund,Macao SAR(File nos.0056/2023/RIB2,001/2024/SKL).
文摘Characterization of vegetation effect on soil response is essential for comprehending site-specific hydrological processes.Traditional research often relies on sensors or remote sensing data to examine the hydrological properties of vegetation zones,yet these methods are limited by either measurement sparsity or spatial inaccuracy.Therefore,this paper is the first to propose a data-driven approach that incorporates high-temporal-resolution electrical resistivity tomography(ERT)to quantify soil hydrological response.Time-lapse ERT is deployed on a vegetated slope site in Foshan,China,during a discontinuous rainfall induced by Typhoon Haikui.A total of 97 ERT measurements were collected with an average time interval of 2.7 hours.The Gaussian Mixture Model(GMM)is applied to quantify the level of response and objectively classify impact zones based on features extracted directly from the ERT data.The resistivity-moisture content correlation is established based on on-site sensor data to characterize infiltration and evapotranspiration across wet-dry conditions.The findings are compared with the Normalized Difference Vegetation Index(NDVI),a common indicator for vegetation quantification,to reveal potential spatial errors in remote sensing data.In addition,this study provides discussions on the potential applications and future directions.This paper showcases significant spatio-temporal advantages over existing studies,providing a more detailed and accurate characterization of superficial soil hydrological response.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12074388 and 12004393)
文摘We have presented a high resolution spectroscopy of Rb in magnetic field by far-detuning electromagnetically induced transparency(EIT).The EIT spectrum in theΞ-type configuration is usually companied by a double resonance optical pumping(DROP)due to the strong optical coupling between the two upper states,leading to the spectral lines seriously deformed and widely broadened for complex relaxation processes in DROP.Here we demonstrate a high resolution spectroscopy by far-detuning EIT for^(87)Rb 5S_(1/2)→5P_(3/2)→5D_(5/2)in magnetic fields.The method of far-detuning eliminates the relaxation in DROP to the most extent and decreases the spectral linewidth from more than 20 MHz down to its natural linewidth limit(6 MHz).The deformation of the spectral lines also disappears and the observed spectra are well in accordance with the theoretical calculation.Our work shows that far-detuning EIT is a reliable high resolution spectroscopic method when the relaxation in DROP cannot be neglected,especially for the case of transition to low excited states.
文摘The present paper investigates the application of high resolution magnetic survey to detecting igneous bodies. The slight difference in magnetism between igneous bodies and their surrounding rocks is measured first and then the magnetic survey data are processed to determine whether there exist igneous bodies by analog among several measuring lines, and finally the modified Marquart inversion was used to determine the occurrence and distribution of the igneous bodies.
文摘After successfully locating one abandoned brine well by an electromagnetic method during testing in 2001 and five abandoned brine wells by a high resolution magnetic method during 2002, a high resolution magnetic method was again proposed to search for wells in 2003 when a second sensor was employed to acquire data for calculating the pseudo vertical gradient of magnetic fields. Total area surveyed in 2003 was 1,024,000 ft 2, which was divided into grids with an average size of 10,000 ft 2 and distributed across eight different sites. Magnetic anomalies and their vertical gradients from known brine wells were first recorded as signatures to identify anomalies caused by possible buried brine wells. Of fifty one verified anomalies, thirty one anomalies were due to wells buried at depths from 0 to 8.5 ft: twenty one 6 to 9 inch abandoned brine wells, seven 1.5 to 3 inch probable water wells, one 16 inch dewatering well for a construction site at a depth of 3 ft, and two 4 inch wells on the ground surface. Approximate monopole shaped anomalies were observed from all these wells after data corrections. However, the range of amplitudes of magnetic anomalies from 7,000 to 28,000 nT from these abandoned brine wells was measured. This range of anomalies is mainly due to the thickness and depth of buried wells. Anomaly amplitudes from 1.5 to 3 inch wells are 4,000 to 8,000 nT and linearly correlate with the buried depth. One 3 inch well that caused an anomaly of 13,000 nT could be the inner pipe of a brine well. Gradient anomalies are roughly in a range of 100 to 200 nT/inch for 1.5 to 3 inch wells and 200 to 300 nT/inch for brine wells.As indicated by the potential field theory, gradient data possess higher horizontal resolution than the magnetic field itself. Gradient data provide valuable assistance in determining horizontal locations of anomaly sources for excavation. In practice, however, improvement in the horizontal resolution is limited by survey line spacing. If only one sensor is used in a survey, there is rapid decrease in the horizontal resolution when sensor height increases from 14 to 44 inches. This indicates that it is critical to keep the sensor as close to the ground as possible when hunting buried wells that are close to each other. It also suggests that the downward continuation is useful to increase the horizontal resolution in well hunting.
基金This project was supported by National Natural Science Foundation of china (No.40474042)
文摘We develop a high resolution ground penetrating radar system （LANRCS-GPR） based on the E5071B Vector Network Analyzer （VNA）. This system takes advantage of a wideband and adjustable frequency domain ground penetrating radar system and adds the characteristics of a network analyzer with ultra-wideband and high precision measurement. It adopts the LAN mode to concatenate system control that reduces construction cost and makes the system easy to expand. The high resolution ground penetrating radar system carries out real time imaging using F-K migration with high calculation efficiency. The experiment results of the system indicate that the LANRCS-GPR system provides high resolution and precision, high signal-to-noise ratio, and great dynamic range. Furthermore, the LANRCS-GPR system is flexible and reliable to operate with easy to expand system functions. The research and development of the LANRCS-GPR provide the theoretical and experimental foundation for future frequency domain ground penetrating radar production and also can serve as an experimental platform with high data gathering precision, enormous information capability, wide application, and convenient operation for electromagnetic wave research and electromagnetic exploration.
文摘The combination of pyrolysis high resolution gas chromatography and pat- tern recognition techniques is a powerful tool for the classification of traditional Chinese drug.A study has been completed on 55 Beimu samples of five different geographic origins: Eastern China.Central China.South-western China,North-western China and North-eastern China.Principal component analysis and SIMCA are applied to effectively classifying the samples according to the origin of the plants.The chemical information contained in the high resolution gas chromatographic data is sufficient to characterize the geographic origin of sam- pies.
