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.

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.

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.

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.

Lightweight Multi-Resolution Network for Human Pose Estimation

Human pose estimation aims to localize the body joints from image or video data.With the development of deeplearning,pose estimation has become a hot research topic in the field of computer vision.In recent years,humanpose estimation has achieved great success in multiple fields such as animation and sports.However,to obtainaccurate positioning results,existing methods may suffer from large model sizes,a high number of parameters,and increased complexity,leading to high computing costs.In this paper,we propose a new lightweight featureencoder to construct a high-resolution network that reduces the number of parameters and lowers the computingcost.We also introduced a semantic enhancement module that improves global feature extraction and networkperformance by combining channel and spatial dimensions.Furthermore,we propose a dense connected spatialpyramid pooling module to compensate for the decrease in image resolution and information loss in the network.Finally,ourmethod effectively reduces the number of parameters and complexitywhile ensuring high performance.Extensive experiments show that our method achieves a competitive performance while dramatically reducing thenumber of parameters,and operational complexity.Specifically,our method can obtain 89.9%AP score on MPIIVAL,while the number of parameters and the complexity of operations were reduced by 41%and 36%,respectively.

Large-field objective lens for multi-wavelength microscopy at mesoscale and submicron resolution

Conventional microscopes designed for submicron resolution in biological research are hindered by a limited field of view,typically around 1 mm.This restriction poses a challenge when attempting to simultaneously analyze various parts of a sample,such as different brain areas.In addition,conventional objective lenses struggle to perform consistently across the required range of wavelengths for brain imaging in vivo.Here we present a novel mesoscopic objective lens with an impressive field of view of 8 mm,a numerical aperture of 0.5,and a working wavelength range from 400 to 1000 nm.We achieved a resolution of 0.74μm in fluorescent beads imaging.The versatility of this lens was further demonstrated through high-quality images of mouse brain and kidney sections in a wide-field imaging system,a confocal laser scanning system,and a two-photon imaging system.This mesoscopic objective lens holds immense promise for advancing multi-wavelength imaging of large fields of view at high resolution.

Correg-Yolov3:a Method for Dense Buildings Detection in High-resolution Remote Sensing Images

The exploration of building detection plays an important role in urban planning,smart city and military.Aiming at the problem of high overlapping ratio of detection frames for dense building detection in high resolution remote sensing images,we present an effective YOLOv3 framework,corner regression-based YOLOv3(Correg-YOLOv3),to localize dense building accurately.This improved YOLOv3 algorithm establishes a vertex regression mechanism and an additional loss item about building vertex offsets relative to the center point of bounding box.By extending output dimensions,the trained model is able to output the rectangular bounding boxes and the building vertices meanwhile.Finally,we evaluate the performance of the Correg-YOLOv3 on our self-produced data set and provide a comparative analysis qualitatively and quantitatively.The experimental results achieve high performance in precision(96.45%),recall rate(95.75%),F1 score(96.10%)and average precision(98.05%),which were 2.73%,5.4%,4.1%and 4.73%higher than that of YOLOv3.Therefore,our proposed algorithm effectively tackles the problem of dense building detection in high resolution images.

Data processing of the Kuiyang-ST2000 deep-towed high-resolution multichannel seismic system and application to South China Sea data

The Kuiyang-ST2000 deep-towed high-resolution multichannel seismic system was designed by the First Institute of Oceanography,Ministry of Natural Resources(FIO,MNR).The system is mainly composed of a plasma spark source(source level:216 dB,main frequency:750 Hz,frequency bandwidth:150-1200 Hz)and a towed hydrophone streamer with 48 channels.Because the source and the towed hydrophone streamer are constantly moving according to the towing configuration,the accurate positioning of the towing hydrophone array and the moveout correction of deep-towed multichannel seismic data processing before imaging are challenging.Initially,according to the characteristics of the system and the towing streamer shape in deep water,travel-time positioning method was used to construct the hydrophone streamer shape,and the results were corrected by using the polynomial curve fitting method.Then,a new data-processing workflow for Kuiyang-ST2000 system data was introduced,mainly including float datum setting,residual static correction,phase-based moveout correction,which allows the imaging algorithms of conventional marine seismic data processing to extend to deep-towed seismic data.We successfully applied the Kuiyang-ST2000 system and methodology of data processing to a gas hydrate survey of the Qiongdongnan and Shenhu areas in the South China Sea,and the results show that the profile has very high vertical and lateral resolutions(0.5 m and 8 m,respectively),which can provide full and accurate details of gas hydrate-related and geohazard sedimentary and structural features in the South China Sea.

Earthquake-triggered landslide interpretation model of high resolution remote sensing imageries based on bag of visual word

Traditional visual interpretation is often inefficient due to its excessively workload professional knowledge and strong subjectivity.Therefore,building an automatic interpretation model on high spatial resolution remote sensing images is the key to the quick and efficient interpretation of earthquake-triggered landslides.Aiming at addressing this problem,a landslide interpretation model of high-resolution images based on bag of visual word(BoVW)feature was proposed.The high-resolution images were pre-processed,and then BoVW feature and support vector machine(SVM)was adopted to establish an automatic landslide interpretation model.This model was further compared with the currently widely used Histogram of Oriented Gradient(HoG)feature extraction model.In order to test the effectiveness of the method,typical landslide images were selected to construct a landslide sample library,which was subsequently utilized as the foundation for conducting an experimental study.The results show that the accuracy of landslide extraction using this method reaches as high as 89%,indicating that the method can be used for the automatic interpretation of landslides in disaster-prone areas,and has high practical value for regional disaster prevention and damage reduction.

A Cloud Framework for High Spatial Resolution Soil Moisture Mapping from Radar and Optical Satellite Imageries

Soil moisture plays an important role in crop yield estimation,irrigation management,etc.Remote sensing technology has potential for large-scale and high spatial soil moisture mapping.However,offline remote sensing data processing is time-consuming and resource-intensive,and significantly hampers the efficiency and timeliness of soil moisture mapping.Due to the high-speed computing capabilities of remote sensing cloud platforms,a High Spatial Resolution Soil Moisture Estimation Framework(HSRSMEF)based on the Google Earth Engine(GEE)platform was developed in this study.The functions of the HSRSMEF include research area and input datasets customization,radar speckle noise filtering,optical-radar image spatio-temporal matching,soil moisture retrieving,soil moisture visualization and exporting.This paper tested the performance of HSRSMEF by combining Sentinel-1,Sentinel-2 images and insitu soil moisture data in the central farmland area of Jilin Province,China.Reconstructed Normalized Difference Vegetation Index(NDVI)based on the Savitzky-Golay algorithm conforms to the crop growth cycle,and its correlation with the original NDVI is about 0.99(P<0.001).The soil moisture accuracy of the random forest model(R 2=0.942,RMSE=0.013 m3/m3)is better than that of the water cloud model(R 2=0.334,RMSE=0.091 m3/m3).HSRSMEF transfers time-consuming offline operations to cloud computing platforms,achieving rapid and simplified high spatial resolution soil moisture mapping.

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.

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

An analytical method using high resolution inductively coupled plasma mass spectrometry （HR-ICP-MS） for rapid simultaneous determination of Be, Mg, Al, 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 HCl. The matrix effects due to the presence of excess HCl and Co were evaluated. The usefulness of high mass resolution for overcoming some spectral interference was demonstrated. The optimum conditions for the determination was tested and discussed. Correction for matrix effects, Sc, Rh and Bi were used as internal standards. The detection limits is 0.003-0.57 μg/g, the recovery ratio is 92.2%-111.2%, and the RSD is less than 3.6%. The method is accurate, quick and convenient. It has been applied to the determination of trace impurities in high purity cobalt with satisfactory results.

Direct Determination of Trace Impurities in High Purity Zinc Oxide by High Resolution Inductively Coupled Plasma Mass Spectrometry

The determination of trace impurities in high purity zinc oxide by high resolution inductively coupled plasma mass spectrometry （ HR-ICP-MS ） was investigated. To overcome some poteutially problematic spectral iuterference, measurements were acquired in both middle and high resolution modes. The matrix effects due to the presence of excess HCl and zinc were evaluated. The optimum conditions for the determination were tested and discussed. The standard addition method was employed for quantitative analysis. The detection limits ranged from 0.02μg/ g to 6 μg/ g depending on the elements. The experimental resalts for the determination of Na, Mg, Ca, Cr, Mn, Fe, Co, Ni, Cu, Mo, Cd, Sb and Pb in several high purity zinc oxide powders were presented.

Determination of Trace Elements in High Purity Gold by High Resolution Inductively Coupled Plasma Mass Spectrometry

Trace elements were determined in high purity gold by high resolution inductively coupled plasma mass spectrometry （HR-ICP-MS）. Sample were decomposed by aqua regia. To overcome some potentially problematic spectra/ interference, measurements were acquired in both medium and high resolution modes. The matrix effects due to the presence of excessive HCl and Au were evaluated. The optimum conditions for the determination was tested and discussed. The standard addition method was employed for quantitative analysis. The detection limits range from 0.01ug/g to 0.28ug/g depending on the elements. The method is accurate, quick and convenient. It has been applied to the determination of trace elements in high purity gold with satisfactory results.

High Resolution Mass Spectrometry for the Recognition and Structural Characterization of a New Antimicrobial Compound

Identification of novel specialized metabolites or bioactive compounds represents the main objective in the research field of natural product leads and drug discovery. Mass spectrometry (MS) provides a central tool to expedite and make more efficient the discovery and isolation phases, while minimizing the waste of resources on rediscovery of known compounds. MS contributes acutely to elucidation and identification of numerous species because it allows molecular mass and structural features determination. In particular, identification of the elemental composition of a precursor ion of interest by accurate mass measurement and investigation of dissociative processes undergone by the molecule, represent a worthy methodology to access the structure assignment. The aim of this study was to discover and identify novel antibacterial drugs from microbial source in a jungle of already known compounds. The focus of this paper is on the analytical strategy that permitted the disclosure of a new compound, otherwise confused with other substances. Emphasis is placed on the interpretation of the ESI-MS/MS fragmentation pattern that combined with high resolution mass determination, allowed step by step to properly deduce the exact molecular formula of an unknown component with a molecular weight higher than 1500 Daltons.

Simultaneous Determination of Ultraviolet Absorbers and Antibacterial Agents in Textiles by Ultra-High Performance Liquid Chromatography/Orbitrap High Resolution Mass Spectrometry

This paper reported a new analytical method for the simultaneous determination of seven benzotriazole ultraviolet absorbers and seven antibacterial agents in textiles. After ultrasonic extraction for the textile samples in methanol, the solutions were analyzed by ultra-high performance liquid chromotagraphy/orbitrap high resolution mass spectrometry (UPLC/Orbitrap HRMS). It showed that a good chromatographic separation for these target compounds was achieved by a Hypersil GOLD column (100 mm × 2.1 mm × 1.9 μm) with a gradient elution of methanol and 0.1% aqueous formic acid solution (containing 0.5 mmol/L ammonium acetate). Triclosan and 4-chloro-3,5-dimethyl phenol (PCMX) were detected by the orbitrap HRMS in an electrospray ionization (ESI) negative mode while the other twelve target compounds were detected by orbitrap HRMS in ESI positive mode. Full scan experiment was performed over the range from m/z 100 to m/z 500. These target compounds were routinely detected with mass accuracy below 2 × 10-6 (2 ppm) at the optimized conditions. The results showed that the limits of detection (LODs) were in the range from 0.1 to 0.3 μg/kg. The blank samples were spiked at three levels and their average recoveries varied from 80.5% to 96.3% while the relative standard deviation (RSD) changed from 3.2% to 9.9%. The present method was also applied for the determination of those ultraviolet absorbers and antibacterial agents in the commercial textiles.

Data Analysis for High Throughput Detection of 18 Phthalates in Textiles Based on High Resolution Mass Spectrometry

Liquid chromatography coupled to high resolution mass spectrometry(LC-HRMS)was used to establish a high throughput and sensitive method for 18 phthalic acid esters(PAEs)in textiles.The method was applied to screen PAEs in 413 textile samples and 7 434 pieces of test data were analyzed.Further discussion was conducted about specific compounds,textile materials,detected value distribution and positive rate of samples.Twenty-nine percent of samples were detected with PAEs,and no samples were detected beyond regulations.Diisobutyl phthalate(DiBP),Dibutyl phthalate(DBP)and Di-2-ethylhexyl phthalate(DEHP)were detected with high frequency,and most samples were fabrics with coating and printing.This study can be used to reflect distribution of phthalate residues in textiles on the market and provide data support for risk assessment of PAEs for textile producers and consumers.

Discovery of pulmonary fibrosis inhibitor targeting TGF-b RI in Polygonum cuspidatum by high resolution mass spectrometry with in silico strategy

Pulmonary fibrosis(PF)is an irreversible lung disease that is characterized by excessive scar tissue with a poor median survival rate of 2-3 years.The inhibition of transforming growth factor-β receptor type-I(TGF-β RI)by an appropriate drug may provide a promising strategy for the treatment of this disease.Polygonum cuspidatum(PC)is a well-known traditional Chinese herbal medicine which has an anti-PF effect.Accordingly,a combination of high resolution mass spectrometry with an in silico strategy was developed as a new method to search for potential chemical ingredients of PC that target the TGF-β RI.Based on this strategy,a total of 24 ingredients were identified.Then,absorption,distribution,metabolism,and excretion(ADME)-related properties were subsequently predicted to exclude compounds with potentially undesirable pharmacokinetics behaviour.Molecular docking studies on TGF-β RI were adopted to discover new PF inhibitors.Eventually,a compound that exists in PC known as resveratrol was proven to have excellent biological activity on TGF-β RI,with an IC_(50) of 2.211 μM in vitro.Furthermore,the complex formed through molecular docking was tested via molecular dynamics simulations,which revealed that resveratrol had strong interactions with residues of TGF-β RI.This study revealed that resveratrol has significant potential as a treatment for PF due to its ability to target TGF-β RI.In addition,this research demonstrated the exploration of natural products with excellent biological activities toward specific targets via high resolution mass spectrometry in combination with in silico technology is a promising strategy for the discovery of novel drugs.