Flexible,high-density,laminated ECoG electrode array for high spatiotemporal resolution foci diagnostic localization of refractory epilepsy

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.

The environmental analysis and site selection of mussel and large yellow croaker aquaculture areas based on high resolution remote sensing

Mussel aquaculture and large yellow croaker aquaculture areas and their environmental characteristics in Zhoushan were analyzed using satellite data and in-situ surveys.A new two-step remote sensing method was proposed and applied to determine the basic environmental characteristics of the best mussel and large yellow croaker aquaculture areas.This methodology includes the first step of extraction of the location distribution and the second step of the extraction of internal environmental factors.The fishery ranching index(FRI1,FRI2)was established to extract the mussel and the large yellow croaker aquaculture area in Zhoushan,using Gaofen-1(GF-1)and Gaofen-6(GF-6)satellite data with a special resolution of 2 m.In the second step,the environmental factors such as sea surface temperature(SST),chlorophyll a(Chl-a)concentration,current and tide,suspended sediment concentration(SSC)in mussel aquaculture area and large yellow croaker aquaculture area were extracted and analyzed in detail.The results show the following three points.(1)For the extraction of the mussel aquaculture area,FRI1 and FRI2 are complementary,and the combination of FRI1 and FRI2 is suitable to extract the mussel aquaculture area.As for the large yellow croaker aquaculture area extraction,FRI2 is suitable.(2)Mussel aquaculture and the large yellow croaker aquaculture area in Zhoushan are mainly located on the side near the islands that are away from the eastern open waters.The water environment factor template suitable for mussel and large yellow croaker aquaculture was determined.(3)This two-step remote sensing method can be used for the preliminary screening of potential site selection for the mussels and large yellow croaker aquaculture area in the future.the fishery ranching index(FRI1,FRI2)in this paper can be applied to extract the mussel and large yellow croaker aquaculture areas in coastal waters around the world.

Synthesizing high-resolution satellite salinity data based on multi-fractal fusion

The spaceborne platform has unprecedently provided the global eddy-permitting(typically about 0.25°)products of sea surface salinity(SSS),however the existing SSS products can hardly resolve mesoscale motions due to the heavy noises therein and the over-smoothing in denoising processes.By means of the multi-fractal fusion(MFF),the high-resolution SSS product is synthesized with the template of sea surface temperature(SST).Two low-resolution SSS products and four SST products are considered as the source data and the templates respectively to determine the best combination.The fused products are validated by the in situ observations and intercompared via SSS maps,Singularity Exponent maps and wavenumber spectra.The results demonstrate that the MFF can perform a good work in mitigating the noises and improving the resolution.The combination of the climate change initiative SSS and the remote sensing system SST can produce the 0.1°denoised product whose global mean standard derivation of salinity against Argo is 0.21 and the feature resolution can reach 30−40 km.

Revisting High-Resolution Schemes with van Albada Slope Limiter

Slope limiters play an essential role in maintaining the non-oscillatory behavior of high-resolution methods for nonlinear conservation laws.The family of minmod limiters serves as the prototype example.Here,we revisit the question of non-oscillatory behavior of high-resolution central schemes in terms of the slope limiter proposed by van Albada et al.(Astron Astrophys 108:76–84,1982).The van Albada(vA)limiter is smoother near extrema,and consequently,in many cases,it outperforms the results obtained using the standard minmod limiter.In particular,we prove that the vA limiter ensures the one-dimensional Total-Variation Diminishing(TVD)stability and demonstrate that it yields noticeable improvement in computation of one-and two-dimensional systems.

High-Resolution Remote Sensing Imagery for the Recognition of Traditional Villages

Traditional Chinese villages,vital carriers of traditional culture,have faced significant alterations due to urbanization in recent years,urgently necessitating artificial intelligence data updates.This study integrates high spatial resolution remote sensing imagery with deep learning techniques,proposing a novel method for identifying rooftops of traditional Chinese village buildings using high-definition remote sensing images.Using 0.54 m spatial resolution imagery of traditional village areas as the data source,this method analyzes the geometric and spectral image characteristics of village building rooftops.It constructs a deep learning feature sample library tailored to the target types.Employing a semantically enhanced version of the improved Mask R-CNN(Mask Region-based Convolutional Neural Network)for building recognition,the study conducts experiments on localized imagery from different regions.The results demonstrated that the modified Mask R-CNN effectively identifies traditional village building rooftops,achieving an of 0.7520 and an of 0.7400.It improves the current problem of misidentification and missed detection caused by feature heterogeneity.This method offers a viable and effective approach for industrialized data monitoring of traditional villages,contributing to their sustainable development.

High resolution GPR and its experimental study

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.

Classification of Chinese Traditional Drug-"Beimu" (Bulbus Fritillariae) by Pyrolysis High Resolution Gas Chromatography-Pattern Recognition

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.

Multiple attenuation using λ–f domain high-resolution Radon transform

The parabolic Radon transform has been widely used in multiple attenuation. To further improve the accuracy and efficiency of the Radon transform, we developed the 2- fdomain high-resolution Radon transform based on the fast and modified parabolic Radon transform presented by Abbad. The introduction of a new variable 2 makes the transform operator frequency-independent. Thus, we need to calculate the transform operator and its inverse operator only once, which greatly improves the computational efficiency. Besides, because the primaries and multiples are distributed on straight lines with different slopes in the 2-fdomain, we can easily choose the filtering operator to suppress the multiples. At the same time, the proposed method offers the advantage of high-resolution Radon transform, which can greatly improve the precision of attenuating the multiples. Numerical experiments suggest that the multiples are well suppressed and the amplitude versus offset characteristics of the primaries are well maintained. Real data processing results further verify the effectiveness and feasibility of the method.

Archean Basement and a Paleoproterozoic Collision Orogen in the Huoqiu Area at the Southeastern Margin of North China Craton: Evidence from Sensitive High Resolution Ion Micro-Probe U-Pb Zircon Geochronology

This paper reports sensitive high resolution ion micro-probe U-Pb zircon ages for the ＂Huoqiu Group＂ and granitoids of the Early Precambrian basement in the Huoqiu area, southeastern margin of the North China Craton. The ＂Huoqiu Group＂ is similar in rock association and metamorphism to the khondalite series, apart from it containing considerable amounts of banded iron formation. All detrital zircons from the ＂Huoqiu Group＂ meta-sedimentary rocks are 3.0 Ga and 2.75 Ga, without any 2.5 Ga and younger ones, as is commonly found in Paleoproterozoic khondalite series in other areas of the North China Craton. In the Huoqiu area, 2.75 Ga and 2.56 Ga granitoids have also been identified. This basement assemblage underwent strong metamorphism during the late Paleoproterozoic （-1.84 Ga） tectonothermal event that is widely developed in the North China Craton. Thus the formation time of the ＂Huoqiu Group＂ can be constrained between 2.75 and 1.84 Ga in terms of detrital and metamorphic zircon ages. It is considered, combined with regional data, that there may be a Paleoproterozoic collision orogen extending in a NWW-SEE direction to the southern margin of the North China Craton.

Perspective of Chinese GF-1 high-resolution satellite data in agricultural remote sensing monitoring

High-resolution satellite data have been playing an important role in agricultural remote sensing monitoring. However, the major data sources of high-resolution images are not owned by China. The cost of large scale use of high resolution imagery data becomes prohibitive. In pace of the launch of the Chinese ＂High Resolution Earth Observation Systems＂, China is able to receive superb high-resolution remotely sensed images （GF series） that equalizes or even surpasses foreign similar satellites in respect of spatial resolution, scanning width and revisit period. This paper provides a perspective of using high resolution remote sensing data from satellite GF-1 for agriculture monitoring. It also assesses the applicability of GF-1 data for agricultural monitoring, and identifies potential applications from regional to national scales. GF-1＇s high resolution （i.e., 2 m/8 m）, high revisit cycle （i.e., 4 days）, and its visible and near-infrared （VNIR） spectral bands enable a continuous, efficient and effective agricultural dynamics monitoring. Thus, it has gradually substituted the foreign data sources for mapping crop planting areas, monitoring crop growth, estimating crop yield, monitoring natural disasters, and supporting precision and facility agriculture in China agricultural remote sensing monitoring system （CHARMS）. However, it is still at the initial stage of GF-1 data application in agricultural remote sensing monitoring. Advanced algorithms for estimating agronomic parameters and soil quality with GF-1 data need to be further investigated, especially for improving the performance of remote sensing monitoring in the fragmented landscapes. In addition, the thematic product series in terms of land cover, crop allocation, crop growth and production are required to be developed in association with other data sources at multiple spatial scales. Despite the advantages, the issues such as low spectrum resolution and image distortion associated with high spatial resolution and wide swath width, might pose challenges for GF-1 data applications and need to be addressed in future agricultural monitoring.

Distribution and Migration of Heavy Metals in Undisturbed Forest Soils:A High Resolution Sampling Method

The vertical distribution and migration of Cu,Zn,Pb,and Cd in two forest soil profiles near an industrial emission source were investigated using a high resolution sampling method together with reference element Ti.One-meter soil profile was sectioned horizontally at 2 cm intervals in the first 40 cm,5 cm intervals in the next 40 cm,and 10 cm intervals in the last 20 cm.The migration distance and rate of heavy metals in the soil profiles were calculated according to their relative concentrations in the profiles,as calibrated by the reference element Ti.The enrichment of heavy metals appeared in the uppermost layer of the forest soil,and the soil heavy metal concentrations decreased down the profile until reaching their background values.The calculated average migration rates of Cd,Cu,Pb,and Zn were 0.70,0.33,0.37,and 0.76 cm year-1,respectively,which were comparable to other methods.A simulation model was proposed,which could well describe the distribution of Cu,Zn,Pb,and Cd in natural forest soils.

Determination of trace elements in high purity nickel by high resolution inductively coupled plasma mass spectrometry

The contents ofMg, Al, Si, Ti, Cr, Mn, Fe, Co, Cu, Ga, As, Se, Cd, Sb, Pb and Bi in high purity nickel were determined by high resolution inductively coupled plasma mass spectrometry （HR-ICP-MS）. The sample was dissolved in HNO3 and HCI by microwave digestion. Most of the spectral interferences could be avoided by measuring in the high resolution mode. The matrix effects because of the presence of excess HC1 and nickel were evaluated. Correction for matrix effects was made using Sc, Rh and T1 as internal standards. The optimum conditions for the determination were tested and discussed. The detection limits range from 0.012 to 1.76 ~tg/g depending on the type of elements. The applicability of the proposed method is also validated by the analysis of high purity nickel reference material （NIST SRM 671）. The relative standard deviation （RSD） is less than 3.3%. Results for determination of trace elements in high purity nickel were presented.

Quantification of trace amounts of impurities in high purity cobalt by high resolution inductively coupled plasma mass spectrometry

A An analytical method using high resolution inductively coupled plasma mass spectrometry （HR-ICP-MS） for rapid simultaneous determination of 24 elements （Be, Mg, A1, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Ga, Ge, As, Se, Mo, Ag, Cd, Sn Sb, Ba, Pt, Au, and Pb） in high purity cobalt was described. Sample digestions were performed in closed microwave vessels using HNO3 and HCI. The matrix effects because of the presence of excess HCI and Co were evaluated. The usefulness of high mass resolution for overcoming some spectral interference was demonstrated. The optimum conditions for the determination were tested and discussed. The standard addition method was employed for quantitative analysis. The detection limits were 0.016-1.50 ].tg·g^-1, the recovery ratios were 92.2%-111.2%, and the RSD was less than 3.6%. The method was accurate, quick, and convenient. It was applied to the determination of trace impurities in high purity cobalt with satisfactory results.

Technical foundation research on high resolution remote sensing system of China's coastal zone

China's coastal zone is a region with a highly developed economy that contrasts clearly with the slow paced regular investigation on its natural environment,which cannot keep pace with the requirement of economic development and modern management.Laying a theoretical foundation for the modern management of China's costal zone is aimed at. This research focuses on the following processing and analyzing technologies for coastal zone high-resolution remote sensing data: organization and management of large amounts of high-resolution remote sensing data, quick and precise spatial positioning system,algorithms for image fusion in feature level and coastal zone feature extraction. They will form a technical foundation of the system. And, if combined with other research results such as coastal zone remote sensing classification system and its mapping subsystem, an advanced technical frame for remote sensing investigation of coastal zone resource will be constructed.

Radar high resolution range profile recognition via multi-SV method

For radar high resolution range profile (HRRP) recognition, three aspects are of great importance to improve the performance, i.e. discrimination for outlier, classification for inner and an accurate description for feature space. To tackle these issues, a novel target recognition method is designed, denoted by the multiple support vectors (multi-SV) method. With the proposed method, a special framework is constructed by a treble correlate support vector model to segment the feature space to two regions with the distribution of density, and then the description and classification hyperplane for each region are achieved. Based on the support vector framework, this method needs less memory and computation complexity to fit practical radar HRRP recognition. Finally, the experiment based on the measured data verifies the excellent performance of this method.

Study on the genesis of karstic collapse column and characteristics of high resolution seismic data in one coal field

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.

High resolution range profile analysis based on multicarrier phase-coded waveforms of OFDM radar

Orthogonal frequency division multiplexing（OFDM） radar with multicarrier phase-coded waveforms has been recently introduced to achieve high range resolution.The conventional method for obtaining the high resolution range profile（HRRP） is based on matched filters.A method of synthesizing HRRP based on the fast Fourier transform（FFT） and decoding is proposed.The mathematical expressions of HRRP are derived by assuming an elementary scenario of point-scattering targets.Based on the characteristic of OFDM multicarrier signals,it mainly analyzes the influence on HRRP exerted by several factors,such as velocity compensation errors,the sampling frequency offset,and so on.The conclusions are significant for the design of the OFDM imaging radar.Finally,the simulation results demonstrate the validity of the conclusions.

On the analysis of the high-resolution sequence stratigraphy and coal accumulating law of jurassic in Ordos Basin

The strata of Jurassic was divided into three tectonic sequences and eight se- quences of third rank,according to the developing feature of the tectonic inconformity and the transforming feature of the depositional system tracts.Also the identification and the division of the base-level cycle of different period were carried through.Therefore three cycles of super period,eight cycles of long period,twenty-four cycles of middle period and some cycles of short period were identified.From the overall character of the coal-accu- mulation in the Mesozoic,we can see that the Yan'an formation is of the best nature of coal bearing.When the coal bearing systems of Jurassic were depositing,the Ordos area is the coal accumulating basin of terrene of large scale and located in the same tectonic unit.But the local structure of different part and the paleolandform are different in the basin which resulted in the difference of the depositional environment.So the layer number and the distribution of the thickness of the coal beds are different in the different part of the ba- sin.The coal-accumulating action migrated regularly along with the development,evolve- ment and migration of the depositional systems.The layer numbers of the coal beds, which can be mined,are more in the north and west fringe of the basin,whose distributing area is extensive,and they are more steady in the landscape orientation,also the total thickness is great.Therefore the nature of coal bearing and the coal-accumulating action of different part changed obviously in the space in Ordos area.

SeisResoDiff: Seismic resolution enhancement based on a diffusion model

High resolution of post-stack seismic data assists in better interpretation of subsurface structures as well as high accuracy of impedance inversion. Therefore, geophysicists consistently strive to acquire higher resolution seismic images in petroleum exploration. Although there have been successful applications of conventional signal processing and machine learning for post-stack seismic resolution enhancement,there is limited reference to the seismic applications of the recent emergence and rapid development of generative artificial intelligence. Hence, we propose to apply diffusion models, among the most popular generative models, to enhance seismic resolution. Specifically, we apply the classic diffusion model—denoising diffusion probabilistic model(DDPM), conditioned on the seismic data in low resolution, to reconstruct corresponding high-resolution images. Herein the entire scheme is referred to as SeisResoDiff. To provide a comprehensive and clear understanding of SeisResoDiff, we introduce the basic theories of diffusion models and detail the optimization objective's derivation with the aid of diagrams and algorithms. For implementation, we first propose a practical workflow to acquire abundant training data based on the generated pseudo-wells. Subsequently, we apply the trained model to both synthetic and field datasets, evaluating the results in three aspects: the appearance of seismic sections and slices in the time domain, frequency spectra, and comparisons with the synthetic data using real well-logging data at the well locations. The results demonstrate not only effective seismic resolution enhancement,but also additional denoising by the diffusion model. Experimental comparisons indicate that training the model on noisy data, which are more realistic, outperforms training on clean data. The proposed scheme demonstrates superiority over some conventional methods in high-resolution reconstruction and denoising ability, yielding more competitive results compared to our previous research.

High resolution records of flood deposition in the mud area off the Changjiang River mouth during the past century

This paper presents a paleoflood study to determine the flood frequency of the Changjiang River, based on core cj0702, taken from the Changjiang River subaqueous delta. We identified flood deposits by means of high-resolution grain-size variation, sensitive population, geochemical indexes and magnetic susceptibility. The core covers a time span of 120 years by 21~pb dating and was sampled at 1-2 cm intervals. Grain size, geochemical elements, and physical parameters were analyzed. The results indicate that the sediment of the core is mainly composed of silt and clay, as well as groups of interbedded silt, clay silt, and clay. Vertically, the grain size pattern was controlled by seasonal variations in water discharge and by the sediment input in winter from the abandoned Huanghe River delta. River flooding caused extreme values in all our measured parameters. We identified more than 20 flood events that occurred since 1887 using the physical parameter analysis method. The environmentally sensitive component of sediment grain size （14.32-96.39 gm） contribution〉30%, Zr/Rb ratio〉l.5, and magnetic susceptibility〉16 were selected as the criteria for flood identification generally. We also found that floods that had taken place in the upstream, midstream, or downstream parts of the river were clearly identified by these indexes while the large-scale floods that covered the whole drainage area did not leave clear indications in the sediment record. This study for identification of flood events is of great significance for understanding hyperpycnal current sedimentation as well as for forecasting of floods.