A profile of shallow crustal velocity structure(1–2 km) may greatly enhance interpretation of the sedimentary environment and shallow tectonic deformation.Recent advances in surface wave tomography, using ambient noi...A profile of shallow crustal velocity structure(1–2 km) may greatly enhance interpretation of the sedimentary environment and shallow tectonic deformation.Recent advances in surface wave tomography, using ambient noise data recorded with high-density seismic arrays, have improved the understanding of regional crustal structure. As the interest in detailed shallow crustal structure imaging has increased, dense seismic array methods have become increasingly efficient. This study used a high-density seismic array deployed in the Xinjiang basin in southeastern China, to record seismic data, which was then processed with the ambient noise tomography method. The high-density seismic array contained 203 short-period seismometers, spaced at short intervals(～ 400 m). The array collected continuous records of ambient noise for 32 days. Data preprocessing,cross correlation calculation, and Rayleigh surface wave phase-velocity dispersion curve extraction, yielded more than 16,000 Rayleigh surface wave phase-velocity dispersion curves, which were then analyzed using the direct-inversion method. Checkerboard tests indicate that the shear wave velocity is recovered in the study area, at depths of 0–1.4 km,with a lateral image resolution of ～ 400 m. Model test results show that the seismic array effectively images a 50 m thick slab at a depth of 0–300 m, a 150 m thick anomalous body at a depth of 300–600 m, and a 400 m thick anomalous body at a depth of 0.6–1.4 km. The shear wave velocity profile reveals features very similar to those detected by a deep seismic reflection profile across the study area. This demonstrates that analysis of shallow crustal velocity structure provides high-resolution imaging of crustal features.Thus, ambient noise tomography with a high-density seismic array may play an important role in imaging shallow crustal structure.展开更多
On the standpoint of the disaster prevention from water inrush,discussed the genesis and geologic condition of karstic collapse column in one coal field,analyzed the geophysical characteristics of karstic collapse col...On the standpoint of the disaster prevention from water inrush,discussed the genesis and geologic condition of karstic collapse column in one coal field,analyzed the geophysical characteristics of karstic collapse column by using high resolution 3D seismic data.It shows the effective result of the technology of high resolution 3D seismic pros- pecting in the exploration of the karstic collapse column,and presents some prediction methods and prevention measures.展开更多
High spatiotemporal resolution brain electrical signals are critical for basic neuroscience research and high-precision focus diagnostic localization,as the spatial scale of some pathologic signals is at the submillim...High spatiotemporal resolution brain electrical signals are critical for basic neuroscience research and high-precision focus diagnostic localization,as the spatial scale of some pathologic signals is at the submillimeter or micrometer level.This entails connecting hundreds or thousands of electrode wires on a limited surface.This study reported a class of flexible,ultrathin,highdensity electrocorticogram(ECoG)electrode arrays.The challenge of a large number of wiring arrangements was overcome by a laminated structure design and processing technology improvement.The flexible,ultrathin,high-density ECoG electrode array was conformably attached to the cortex for reliable,high spatial resolution electrophysiologic recordings.The minimum spacing between electrodes was 15μm,comparable to the diameter of a single neuron.Eight hundred electrodes were prepared with an electrode density of 4444 mm^(-2).In focal epilepsy surgery,the flexible,high-density,laminated ECoG electrode array with 36 electrodes was applied to collect epileptic spike waves inrabbits,improving the positioning accuracy of epilepsy lesions from the centimeter to the submillimeter level.The flexible,high-density,laminated ECoG electrode array has potential clinical applications in intractable epilepsy and other neurologic diseases requiring high-precision electroencephalogram acquisition.展开更多
Determining forest structural complexity,i.e.,a measure of the number of different attributes of a forest and the relative abundance of each attribute,is important for forest management and conservation.In this study,...Determining forest structural complexity,i.e.,a measure of the number of different attributes of a forest and the relative abundance of each attribute,is important for forest management and conservation.In this study,we examined the structural complexity of mixed conifer–broadleaf forests by integrating multiple forest structural attributes derived from airborne Li DAR data and aerial photography.We sampled 76 plots from an unmanaged mixed conifer–broadleaf forest reserve in northern Japan.Plot-level metrics were computed for all plots using both field and remote sensing data to assess their ability to capture the vertical and horizontal variations of forest structure.A multivariate set of forest structural attributes that included three Li DAR metrics(95 th percentile canopy height,canopy density and surface area ratio) and one image metric(proportion of broadleaf cover),was used to classify forest structure into structural complexity classes.Our results revealed significant correlation between field and remote sensing metrics,indicating that these two sets of measurements captured similar patterns of structure in mixed conifer–broadleaf forests.Further,cluster analysis identified six forest structural complexity classes includingtwo low-complexity classes and four high-complexity classes that were distributed in different elevation ranges.In this study,we could reliably analyze the structural complexity of mixed conifer–broadleaf forests using a simple and easy to calculate set of forest structural attributes derived from airborne Li DAR data and high-resolution aerial photography.This study provides a good example of the use of airborne Li DAR data sets for wider purposes in forest ecology as well as in forest management.展开更多
基金supported by the China Geological Survey Project“Deep Geological Survey of the Qin-Hang Belt”(No.DD20160082)the National Natural Science Foundation of China(No.41574048)
文摘A profile of shallow crustal velocity structure(1–2 km) may greatly enhance interpretation of the sedimentary environment and shallow tectonic deformation.Recent advances in surface wave tomography, using ambient noise data recorded with high-density seismic arrays, have improved the understanding of regional crustal structure. As the interest in detailed shallow crustal structure imaging has increased, dense seismic array methods have become increasingly efficient. This study used a high-density seismic array deployed in the Xinjiang basin in southeastern China, to record seismic data, which was then processed with the ambient noise tomography method. The high-density seismic array contained 203 short-period seismometers, spaced at short intervals(～ 400 m). The array collected continuous records of ambient noise for 32 days. Data preprocessing,cross correlation calculation, and Rayleigh surface wave phase-velocity dispersion curve extraction, yielded more than 16,000 Rayleigh surface wave phase-velocity dispersion curves, which were then analyzed using the direct-inversion method. Checkerboard tests indicate that the shear wave velocity is recovered in the study area, at depths of 0–1.4 km,with a lateral image resolution of ～ 400 m. Model test results show that the seismic array effectively images a 50 m thick slab at a depth of 0–300 m, a 150 m thick anomalous body at a depth of 300–600 m, and a 400 m thick anomalous body at a depth of 0.6–1.4 km. The shear wave velocity profile reveals features very similar to those detected by a deep seismic reflection profile across the study area. This demonstrates that analysis of shallow crustal velocity structure provides high-resolution imaging of crustal features.Thus, ambient noise tomography with a high-density seismic array may play an important role in imaging shallow crustal structure.
基金the National Natural Science Foundation of China(2007CB209600)
文摘On the standpoint of the disaster prevention from water inrush,discussed the genesis and geologic condition of karstic collapse column in one coal field,analyzed the geophysical characteristics of karstic collapse column by using high resolution 3D seismic data.It shows the effective result of the technology of high resolution 3D seismic pros- pecting in the exploration of the karstic collapse column,and presents some prediction methods and prevention measures.
基金support of the National Natural Science Foundation of China(Nos.U20A6001,12002190,11972207,and 11921002)the Fundamental Research Funds for the Central Universities,China(No.SWUKQ22029)the Chongqing Natural Science Foundation of China(No.CSTB2022NSCQ-MSX1635).
文摘High spatiotemporal resolution brain electrical signals are critical for basic neuroscience research and high-precision focus diagnostic localization,as the spatial scale of some pathologic signals is at the submillimeter or micrometer level.This entails connecting hundreds or thousands of electrode wires on a limited surface.This study reported a class of flexible,ultrathin,highdensity electrocorticogram(ECoG)electrode arrays.The challenge of a large number of wiring arrangements was overcome by a laminated structure design and processing technology improvement.The flexible,ultrathin,high-density ECoG electrode array was conformably attached to the cortex for reliable,high spatial resolution electrophysiologic recordings.The minimum spacing between electrodes was 15μm,comparable to the diameter of a single neuron.Eight hundred electrodes were prepared with an electrode density of 4444 mm^(-2).In focal epilepsy surgery,the flexible,high-density,laminated ECoG electrode array with 36 electrodes was applied to collect epileptic spike waves inrabbits,improving the positioning accuracy of epilepsy lesions from the centimeter to the submillimeter level.The flexible,high-density,laminated ECoG electrode array has potential clinical applications in intractable epilepsy and other neurologic diseases requiring high-precision electroencephalogram acquisition.
文摘Determining forest structural complexity,i.e.,a measure of the number of different attributes of a forest and the relative abundance of each attribute,is important for forest management and conservation.In this study,we examined the structural complexity of mixed conifer–broadleaf forests by integrating multiple forest structural attributes derived from airborne Li DAR data and aerial photography.We sampled 76 plots from an unmanaged mixed conifer–broadleaf forest reserve in northern Japan.Plot-level metrics were computed for all plots using both field and remote sensing data to assess their ability to capture the vertical and horizontal variations of forest structure.A multivariate set of forest structural attributes that included three Li DAR metrics(95 th percentile canopy height,canopy density and surface area ratio) and one image metric(proportion of broadleaf cover),was used to classify forest structure into structural complexity classes.Our results revealed significant correlation between field and remote sensing metrics,indicating that these two sets of measurements captured similar patterns of structure in mixed conifer–broadleaf forests.Further,cluster analysis identified six forest structural complexity classes includingtwo low-complexity classes and four high-complexity classes that were distributed in different elevation ranges.In this study,we could reliably analyze the structural complexity of mixed conifer–broadleaf forests using a simple and easy to calculate set of forest structural attributes derived from airborne Li DAR data and high-resolution aerial photography.This study provides a good example of the use of airborne Li DAR data sets for wider purposes in forest ecology as well as in forest management.
文摘目的 为了更好地实现轻量化的人体姿态估计,在轻量级模型极为有限的资源下实现更高的检测性能。基于高分辨率网络(high resolution network,HRNet)提出了结合密集连接网络的轻量级高分辨率人体姿态估计网络(lightweight high-resolution human estimation combined with densely connected network,LDHNet)。方法 通过重新设计HRNet中的阶段分支结构以及提出新的轻量级特征提取模块,构建了轻量高效的特征提取单元,同时对多分支之间特征融合部分进行了轻量化改进,进一步降低模型的复杂度,最终大幅降低了模型的参数量与计算量,实现了轻量化的设计目标,并且保证了模型的性能。结果 实验表明,在MPII(Max Planck Institute for Informatics)测试集上相比于自顶向下的轻量级人体姿态估计模型LiteHRNet,LDHNet仅通过增加少量参数量与计算量,平均预测准确度即提升了1.5%,与LiteHRNet的改进型DiteHRNet相比也提升了0.9%,在COCO(common objects in context)验证集上的结果表明,与LiteHRNet相比,LDHNet的平均检测准确度提升了3.4%,与DiteHRNet相比也提升了2.3%,与融合Transformer的HRFormer相比,LDHNet在参数量和计算量都更低的条件下有近似的检测性能,在面对实际场景时LDHNet也有着稳定的表现,在同样的环境下LDHNet的推理速度要高于基线HRNet以及LiteHRNet等。结论 该模型有效实现了轻量化并保证了预测性能。
