基于Depth-wise卷积和视觉Transformer的图像分类模型

图像分类作为一种常见的视觉识别任务,有着广阔的应用场景。在处理图像分类问题时,传统的方法通常使用卷积神经网络,然而,卷积网络的感受野有限,难以建模图像的全局关系表示,导致分类精度低,难以处理复杂多样的图像数据。为了对全局关系进行建模,一些研究者将Transformer应用于图像分类任务,但为了满足Transformer的序列化和并行化要求,需要将图像分割成大小相等、互不重叠的图像块,破坏了相邻图像数据块之间的局部信息。此外,由于Transformer具有较少的先验知识,模型往往需要在大规模数据集上进行预训练,因此计算复杂度较高。为了同时建模图像相邻块之间的局部信息并充分利用图像的全局信息,提出了一种基于Depth-wise卷积的视觉Transformer(Efficient Pyramid Vision Transformer,EPVT)模型。EPVT模型可以实现以较低的计算成本提取相邻图像块之间的局部和全局信息。EPVT模型主要包含3个关键组件:局部感知模块(Local Perceptron Module,LPM)、空间信息融合模块(Spatial Information Fusion,SIF)和“+卷积前馈神经网络(Convolution Feed-forward Network,CFFN)。LPM模块用于捕获图像的局部相关性;SIF模块用于融合相邻图像块之间的局部信息,并利用不同图像块之间的远距离依赖关系,提升模型的特征表达能力,使模型学习到输出特征在不同维度下的语义信息;CFFN模块用于编码位置信息和重塑张量。在图像分类数据集ImageNet-1K上,所提模型优于现有的同等规模的视觉Transformer分类模型,取得了82.6%的分类准确度,证明了该模型在大规模数据集上具有竞争力。

Investigation of Groundwater Quality with Borehole Depth in the Basin Granitoids of the Ashanti Region of Ghana

The dependence of groundwater quality on borehole depth is usually debatable in groundwater studies, especially in complex geological formations where aquifer characteristics vary spatially with depth. This study therefore seeks to investigate the relationship between borehole depth and groundwater quality across the granitoid aquifers within the Birimian Supergroup in the Ashanti Region. Physicochemical analysis records of groundwater quality data were collected from 23 boreholes of public and private institutions in the Ashanti Region of Ghana, and the parametric values of iron, fluoride, total hardness, pH, nitrate, and nitrite were used to study the groundwater quality-depth relationship. The results showed that the depth-to-groundwater quality indicated a marginal increase in water quality in the range of 30 to 50 m, which is mathematically represented by the low-value correlation coefficient (r2 = 0.026). A relatively significant increase occurs in the depth range of 50 to 80 m, which is given by a correlation coefficient of r2 = 0.298. The mean percent parameter compatibility was 74%, 82%, 89%, and 97% at 50, 60, 70, and 80 m depths, respectively. The variations in groundwater quality per depth ratio ranged from 1.48, 1.37, 1.27, and 1.21 for 50, 60, 70, and 80 m depth, respectively. The recommended minimum borehole depth for excellent groundwater quality is suggested with a compatibility per meter depth ratio of 1.37. This results in a range between 50 and 70 m as the most desirable drilling depth for excellent groundwater quality within the granitoids of the Birimian Supergroup of the Ashanti Region in Ghana.

Quantitative prediction model for the depth limit of oil accumulation in the deep carbonate rocks:A case study of Lower Ordovician in Tazhong area of Tarim Basin

With continuous hydrocarbon exploration extending to deeper basins,the deepest industrial oil accumulation was discovered below 8,200 m,revealing a new exploration field.Hence,the extent to which oil exploration can be extended,and the prediction of the depth limit of oil accumulation(DLOA),are issues that have attracted significant attention in petroleum geology.Since it is difficult to characterize the evolution of the physical properties of the marine carbonate reservoir with burial depth,and the deepest drilling still cannot reach the DLOA.Hence,the DLOA cannot be predicted by directly establishing the relationship between the ratio of drilling to the dry layer and the depth.In this study,by establishing the relationships between the porosity and the depth and dry layer ratio of the carbonate reservoir,the relationships between the depth and dry layer ratio were obtained collectively.The depth corresponding to a dry layer ratio of 100%is the DLOA.Based on this,a quantitative prediction model for the DLOA was finally built.The results indicate that the porosity of the carbonate reservoir,Lower Ordovician in Tazhong area of Tarim Basin,tends to decrease with burial depth,and manifests as an overall low porosity reservoir in deep layer.The critical porosity of the DLOA was 1.8%,which is the critical geological condition corresponding to a 100%dry layer ratio encountered in the reservoir.The depth of the DLOA was 9,000 m.This study provides a new method for DLOA prediction that is beneficial for a deeper understanding of oil accumulation,and is of great importance for scientific guidance on deep oil drilling.

What induced the trend shift of mixed-layer depths in the Antarctic Circumpolar Current region in the mid-1980s?

An obvious trend shift in the annual mean and winter mixed layer depth(MLD)in the Antarctic Circumpolar Current(ACC)region was detected during the 1960–2021 period.Shallowing trends stopped in mid-1980s,followed by a period of weak trends.The MLD deepening trend difference between the two periods were mainly distributed in the western areas in the Drake Passage,the areas north to Victoria Land and Wilkes Land,and the central parts of the South Indian sector.The newly formed ocean current shear due to the meridional shift of the ACC flow axis between the two periods is the dominant driver for the MLD trends shift distributed in the western areas in the Drake Passage and the central parts of the South Indian sector.The saltier trends in the regions north to Victoria Land and Wilkes Land could be responsible for the strengthening mixing processes in this region.

Three-dimensional constrained gravity inversion of Moho depth and crustal structural characteristics at Mozambique continental margin

Mozambique's continental margin in East Africa was formed during the break-off stage of the east and west Gondwana lands. Studying the geological structure and division of continent-ocean boundary(COB) in Mozambique's continental margin is considered of great significance to rebuild Gondwana land and understand its movement mode. Along these lines, in this work, the initial Moho was fit using the known Moho depth from reflection seismic profiles, and a 3D multi-point constrained gravity inversion was carried out. Thus, highaccuracy Moho depth and crustal thickness in the study area were acquired. According to the crustal structure distribution based on the inversion results, the continental crust at the narrowest position of the Mozambique Channel was detected. According to the analysis of the crustal thickness, the Mozambique ridge is generally oceanic crust and the COB of the whole Mozambique continental margin is divided.

DGConv: A Novel Convolutional Neural Network Approach for Weld Seam Depth Image Detection

We propose a novel image segmentation algorithm to tackle the challenge of limited recognition and segmentation performance in identifying welding seam images during robotic intelligent operations.Initially,to enhance the capability of deep neural networks in extracting geometric attributes from depth images,we developed a novel deep geometric convolution operator(DGConv).DGConv is utilized to construct a deep local geometric feature extraction module,facilitating a more comprehensive exploration of the intrinsic geometric information within depth images.Secondly,we integrate the newly proposed deep geometric feature module with the Fully Convolutional Network(FCN8)to establish a high-performance deep neural network algorithm tailored for depth image segmentation.Concurrently,we enhance the FCN8 detection head by separating the segmentation and classification processes.This enhancement significantly boosts the network’s overall detection capability.Thirdly,for a comprehensive assessment of our proposed algorithm and its applicability in real-world industrial settings,we curated a line-scan image dataset featuring weld seams.This dataset,named the Standardized Linear Depth Profile(SLDP)dataset,was collected from actual industrial sites where autonomous robots are in operation.Ultimately,we conducted experiments utilizing the SLDP dataset,achieving an average accuracy of 92.7%.Our proposed approach exhibited a remarkable performance improvement over the prior method on the identical dataset.Moreover,we have successfully deployed the proposed algorithm in genuine industrial environments,fulfilling the prerequisites of unmanned robot operations.

Applying Source Parameter Imaging (SPI) to Aeromagnetic Data to Estimate Depth to Magnetic Sources in the Mamfe Sedimentary Basin

Aeromagnetic data over the Mamfe Basin have been processed. A regional magnetic gridded dataset was obtained from the Total Magnetic Intensity (TMI) data grid using a 3 × 3 convolution (Hanning) filter to remove regional trends. Major similarities in magnetic field orientation and intensities were observed at identical locations on both the regional and TMI data grids. From the regional and TMI gridded datasets, the residual dataset was generated which represents the very shallow geological features of the basin. Processing this residual data grid using the Source Parameter Imaging (SPI) for magnetic depth suggests that the estimated depths to magnetic sources in the basin range from about 271 m to 3552 m. The highest depths are located in two main locations somewhere around the central portion of the study area which correspond to the area with positive magnetic susceptibilities, as well as the areas extending outwards across the eastern boundary of the study area. Shallow magnetic depths are prominent towards the NW portion of the basin and also correspond to areas of negative magnetic susceptibilities. The basin generally exhibits a variation in depth of magnetic sources with high, average and shallow depths. The presence of intrusive igneous rocks was also observed in this basin. This characteristic is a pointer to the existence of geologic resources of interest for exploration in the basin.

Spatiotemporal Changes of Snow Depth in Western Jilin,China from 1987 to 2018

Seasonal snow cover is a key global climate and hydrological system component drawing considerable attention due to glob-al warming conditions.However,the spatiotemporal snow cover patterns are challenging in western Jilin,China due to natural condi-tions and sparse observation.Hence,this study investigated the spatiotemporal patterns of snow cover using fine-resolution passive mi-crowave(PMW)snow depth(SD)data from 1987 to 2018,and revealed the potential influence of climate factors on SD variations.The results indicated that the interannual range of SD was between 2.90 cm and 9.60 cm during the snowy winter seasons and the annual mean SD showed a slightly increasing trend(P>0.05)at a rate of 0.009 cm/yr.In snowmelt periods,the snow cover contributed to an increase in volumetric soil water,and the change in SD was significantly affected by air temperature.The correlation between SD and air temperature was negative,while the correlation between SD and precipitation was positive during December and March.In March,the correlation coefficient exceeded 0.5 in Zhenlai,Da’an,Qianan,and Qianguo counties.However,the SD and precipitation were neg-atively correlated over western Jilin in October,and several subregions presented a negative correlation between SD and precipitation in November and April.

Improving path planning efficiency for underwater gravity-aided navigation based on a new depth sorting fast search algorithm

This study focuses on the improvement of path planning efficiency for underwater gravity-aided navigation.Firstly,a Depth Sorting Fast Search(DSFS)algorithm was proposed to improve the planning speed of the Quick Rapidly-exploring Random Trees*(Q-RRT*)algorithm.A cost inequality relationship between an ancestor and its descendants was derived,and the ancestors were filtered accordingly.Secondly,the underwater gravity-aided navigation path planning system was designed based on the DSFS algorithm,taking into account the fitness,safety,and asymptotic optimality of the routes,according to the gravity suitability distribution of the navigation space.Finally,experimental comparisons of the computing performance of the ChooseParent procedure,the Rewire procedure,and the combination of the two procedures for Q-RRT*and DSFS were conducted under the same planning environment and parameter conditions,respectively.The results showed that the computational efficiency of the DSFS algorithm was improved by about 1.2 times compared with the Q-RRT*algorithm while ensuring correct computational results.

基于Shuffle-ZoeDepth单目深度估计的苗期玉米株高测量方法

株高是鉴别玉米种质性状及作物活力的重要表型指标,苗期玉米遗传特性表现明显,准确测量苗期玉米植株高度对玉米遗传特性鉴别与田间管理具有重要意义。针对传统植株高度获取方法依赖人工测量,费时费力且存在主观误差的问题,提出了一种融合混合注意力信息的改进ZoeDepth单目深度估计模型。改进后的模型将Shuffle Attention模块加入Decoder模块的4个阶段,使Decoder模块在对低分辨率特征图信息提取过程中能更关注特征图中的有效信息,提升了模型关键信息的提取能力,可生成更精确的深度图。为验证本研究方法的有效性,在NYU-V2深度数据集上进行了验证。结果表明,改进的Shuffle-ZoeDepth模型在NYU-V2深度数据集上绝对相对差、均方根误差、对数均方根误差为0.083、0.301 mm、0.036,不同阈值下准确率分别为93.9%、99.1%、99.8%,均优于ZoeDepth模型。同时,利用Shuffle-ZoeDepth单目深度估计模型结合玉米植株高度测量模型实现了苗期玉米植株高度的测量,采集不同距离下苗期玉米图像进行植株高度测量试验。当玉米高度在15~25 cm、25~35 cm、35~45 cm 3个区间时,平均测量绝对误差分别为1.41、2.21、2.08 cm,平均测量百分比误差分别为8.41%、7.54%、4.98%。试验结果表明该方法可仅使用单个RGB相机完成复杂室外环境下苗期玉米植株高度的精确测量。

基于Boosting-Monodepth的管道病害深度估计与三维重建

城市地下管道是城市的血脉经络,但随着排水管道的大量投入运营和使用年限增加,引发了一系列的管道病害安全隐患,如管道整体结构变形、内表面破裂和管中异物插入等问题,传统的病害图像视频采集、检测和后期病害分类甄选都是从二维视角出发,欠缺对三维空间信息(深度)的考虑。针对上述3种病害从生成深度图、由二维深度图重建三维管道病害这两方面进行研究,提出了一种基于boosting-monodepth的双重深度估计方法以提升深度图效果,最终生成画面连续一致、轮廓清晰的深度图。性能评估方面采用Abs-Rel、RMSE、SqRel、ORD和D3R等通用指标,与传统算法对比,结果显示boosting-monodepth的RMSE值降低了30%,精确度指标δ<1.25时,模型深度信息预测精确度提高了18%,此后以得到的深度图为基础重建管道病害三维点云,并在CloudCompare软件上三维可视化,最后采用随机采样一致算法测算病害深度并和实测数据对比证明其有效性和准确性。

Determination of minimum overburden depth for underwater shield tunnel in sands:Comparison between circular and rectangular tunnels

With the development of global urbanization,the utilization of underground space is more critical and attractive for civil purposes.Various shapes of shield tunnels have been gradually proposed to cope with different geological conditions and service purposes of underground structures.Generally,reducing the burial depth of shield tunnel is conducive to construction and cost saving.However,extremely small overburden depth cannot provide sufficient uplift resistance to maintain the stability and serviceability of the tunnel.To this end,this paper firstly reviewed the status of deriving the minimum sand over-burden depth of circular shield tunnel using mechanical equilibrium(ME)method.It revealed that the estimated depth is rather conservative.Then,the uplift resistance mechanism of both circular and rectangular tunnels was deduced theoretically and verified with the model tests.The theoretical uplift resistance is consistent with the experimental values,indicating the feasibility of the proposed equations.Furthermore,the determination of the minimum soil overburden depth of rectangular shield tunnel under various working conditions was presented through integrated ME method,which can provide more reasonable estimations of suggested tunnel burial depth for practical construction.Additionally,optimizations were made for calculating the uplift resistance,and the soil thickness providing uplift resistance is suggested to be adjusted according to the testing results.The results can provide reference for the design and construction of various shapes of shield tunnels in urban underground space exploitation.

Influence of the upper mixed layer depth on Langmuir turbulence characteristics

The upper mixed layer depth(h)has a significant seasonal variation in the real ocean and the low-order statistics of Langmuir turbulence are dramatically influenced by the upper mixed layer depth.To explore the influence of the upper mixed layer depth on Langmuir turbulence under the condition of the wind and wave equilibrium,the changes of Langmuir turbulence characteristics with the idealized variation of the upper mixed layer depth from very shallow(h=5 m)to deep enough(h=40 m)are studied using a non-hydrostatic large eddy simulation model.The simulation results show that there is a direct entrainment depth induced by Langmuir turbulence(h_(LT))within the thermocline.The normalized depthaveraged vertical velocity variance is smaller and larger than the downwind velocity variance for the ratio of the upper mixed layer to a direct entrainment depth induced by Langmuir turbulence h/h_(LT)<1 and h/h_(LT)>1,respectively,indicating that turbulence characteristics have the essential change(i.e.,depth-averaged vertical velocity variance(DAVV)DADV for Langmuir turbulence)between h/h_(LT)<1 and h/h_(LT)>1.The rate of change of the normalized depth-averaged low-order statistics for h/h_(LT)<1 is much larger than that for h/h_(LT)>1.The reason is that the downward pressure perturbation induced by Langmuir cells is strongly inhibited by the upward reactive force of the strong stratified thermocline for h/h_(LT)<1 and the eff ect of upward reactive force on the downward pressure perturbation becomes weak for h/h_(LT)>1.Hence,the upper mixed layer depth has significant influences on Langmuir turbulence characteristics.

Speckle structured illumination endoscopy with enhanced resolution at wide field of view and depth of field

Structured illumination microscopy(SIM)is one of the most widely applied wide field super resolution imaging techniques with high temporal resolution and low phototoxicity.The spatial resolution of SIM is typically limited to two times of the diffraction limit and the depth of field is small.In this work,we propose and experimentally demonstrate a low cost,easy to implement,novel technique called speckle structured illumination endoscopy(SSIE)to enhance the resolution of a wide field endoscope with large depth of field.Here,speckle patterns are used to excite objects on the sample which is then followed by a blind-SIM algorithm for super resolution image reconstruction.Our approach is insensitive to the 3D morphology of the specimen,or the deformation of illuminations used.It greatly simplifies the experimental setup as there are no calibration protocols and no stringent control of illumination patterns nor focusing optics.We demonstrate that the SSIE can enhance the resolution 2–4.5 times that of a standard white light endoscopic(WLE)system.The SSIE presents a unique route to super resolution in endoscopic imaging at wide field of view and depth of field,which might be beneficial to the practice of clinical endoscopy.

Coin-structured tunable beam shaping assembly design for accelerator-based boron neutron capture therapy for tumors at different depths and sizes

In the past decade,boron neutron capture therapy utilizing an accelerator-based neutron source(ABNS)designed primarily for producing epithermal neutrons has been implemented in the treatment of brain tumors and other cancers.The specifications for designing an epithermal beam are primarily based on the IAEA-TECODC-1223 report,issued in 2001 for reactor neutron sources.Based on this report,the latest perspectives and clinical requirements,we designed an ABNS capable of adjusting the average neutron beam energy.The design was based on a 2.8 MeV,20 mA proton beam bombarding a lithium target to produce neutrons that were subsequently moderated and tuned through a tunable beam shaping assembly(BSA)which can modify the thicknesses and materials of the coin-shaped moderators,back reflectors,filters,and collimators.The simulation results demonstrated that epithermal neutron beams for deep seated tumor treatment,which were generated by utilizing magnesium fluoride with lengths ranging between 28 and 36 cm as the moderator,possessed a treatment depth of 5.6 cm although the neutron flux peak shifts from 4.5 to 1.0 keV.When utilizing a thinner moderator,a less accelerated beam power can meet the treatment requirements.However,higher powers reduced the treatment time.In contrast,employing a thick moderator can reduce the skin dose.In scenarios that required relatively low energy neutron beams,the removal of the thermal neutron filter can raise the thermal neutron flux at the beam port.And the depth of the dose rate peak could be adjusted between 0.25 and 2.20 cm by combining magnesium fluoride and polyethylene coins of different thicknesses.Hence,this device has a better adaptability for the treatment of superficial tumors.Overall,the tunable BSA provides greater flexibility for clinical treatment than common BSA designs that can only adjust the port size.

Axial length,vitreoretinal pathology,and anterior chamber depth can predict postoperative refractive outcomes in phacovitrectomy/silicone oil removal

AIM:To evaluate the postoperative refractive prediction error(PE)and determine the factors that af fect the refractive outcomes of combined pars plana vitrectomy(PPV)or silicone oil removal(SOR)with cataract surgery.METHODS:The study is a retrospective,case-series study.Totally 301 eyes of 301 patients undergoing combined PPV/SOR with cataract surgery were enrolled.Eligible individuals were separated into four groups according to their preoperative diagnoses:silicone oil-filled eyes after PPV(group 1),epiretinal membrane(group 2),macular hole(group 3),and primary retinal detachment(RD;group 4).The variables af fecting postoperative refractive outcomes were analyzed,including age,gender,preoperative best-corrected visual acuity(BCVA),axial length(AL),keratometry average,anterior chamber depth(ACD),intraocular tamponade,and vitreoretinal pathology.The outcome measurements include the mean refractive PE and the proportions of eyes with a PE within±0.50 diopter(D)and±1.00 D.RESULTS:For all patients,the mean PE was-0.04±1.17 D,and 50.17%of patients(eyes)had a PE within±0.50 D.There was a significant difference in refractive outcomes among the four groups(P=0.028),with RD(group 4)showing the least favorable refractive outcome.In multivariate regression analysis,only AL,vitreoretinal pathology,and ACD were strongly associated with PE(all P<0.01).Univariate analysis revealed that longer eyes(AL>26 mm)and a deeper ACD were correlated with hyperopic PE,and shorter eyes(AL<26 mm)and a shallower ACD were correlated with myopic PE.CONCLUSION:RD patients have the least favorable refractive outcome.AL,vitreoretinal pathology,and ACD are strongly associated with PE in the combined surgery.These three factors affect refractive outcomes and thus can be used to predict a better postoperative refractive outcome in clinical practice.

Fusion of color and hallucinated depth features for enhanced multimodal deep learning-based damage segmentation

Recent advances in computer vision and deep learning have shown that the fusion of depth information can significantly enhance the performance of RGB-based damage detection and segmentation models.However,alongside the advantages,depth-sensing also presents many practical challenges.For instance,the depth sensors impose an additional payload burden on the robotic inspection platforms limiting the operation time and increasing the inspection cost.Additionally,some lidar-based depth sensors have poor outdoor performance due to sunlight contamination during the daytime.In this context,this study investigates the feasibility of abolishing depth-sensing at test time without compromising the segmentation performance.An autonomous damage segmentation framework is developed,based on recent advancements in vision-based multi-modal sensing such as modality hallucination(MH)and monocular depth estimation(MDE),which require depth data only during the model training.At the time of deployment,depth data becomes expendable as it can be simulated from the corresponding RGB frames.This makes it possible to reap the benefits of depth fusion without any depth perception per se.This study explored two different depth encoding techniques and three different fusion strategies in addition to a baseline RGB-based model.The proposed approach is validated on computer-generated RGB-D data of reinforced concrete buildings subjected to seismic damage.It was observed that the surrogate techniques can increase the segmentation IoU by up to 20.1%with a negligible increase in the computation cost.Overall,this study is believed to make a positive contribution to enhancing the resilience of critical civil infrastructure.

Considering explosive charge shape and embedded depth in the design of concrete shelter thickness

Cost and safety are important considerations when designing the thickness of a protective reinforced concrete shelter.The blast perforation limit(BPL)is the minimum concrete shelter thickness that resists perforation under blast loading.To investigate the influence of the depth of embedment(DOE)and length-to-diameter ratio(L/D)of an explosive charge on the BPL,the results of an explosion test using a slender explosive partially embedded in a reinforced concrete slab were used to validate a refined finite element model.This model was then applied to conduct more than 300 simulations with strictly controlled variables,obtaining the BPLs for various concrete slabs subjected to charge DOEs ranging from0 to∞and L/D values ranging from 0.89 to 6.87.The numerical results were compared with the experimental results from published literature,further verifying the reliability of the simulation.The findings indicate that for the same explosive charge mass and L/D,the greater the DOE,the larger the critical residual thickness(Rc,defined as the difference between the BPL and DOE)up to a certain constant value;for the same explosive charge mass and DOE,the greater the L/D,the smaller the Rc.Thus,corresponding DOE and shape coefficients were introduced to derive a new equation for the BPL,providing a theoretical approach to the design and safety assessment of protective structures.

Experimental investigation of the impact of water depth, inlet water temperature, and fins on the productivity of a Pyramid Solar Still

This experimental study aimed to investigate the impact of water depth, inlet water temperature,and fins on the productivity of a pyramid solar still in producing distilled water. The experiment was conducted in three parts, where the first part explored the variation in water depth from 1 cm to 5 cm, the second part evaluated the effect of increasing inlet water temperature from 30℃ to 50℃, and the third part added fins at the bottom of the still at a specific inlet water depth. Results showed that basin depth had a significant impact on the still's production, with a maximum variation of 40.6% observed when the water level was changed from 1 cm to 5 cm. The daily freshwater production from the pyramid solar still ranged from 3.41 kg/m~2 for a water depth of 1 cm to 2.02 kg/m~2 for a depth of 5 cm. Adding fins at the bottom of the pyramid solar still led to a 7.5% increase in productivity, while adjusting the inlet water temperature from 30℃ to 40℃ and 50℃ resulted in a 15.3% and 21.2% increase, respectively. These findings highlighted the essential factors that can influence the productivity of pyramid solar stills and can be valuable in designing and operating efficient water desalination and purification technologies.

Depth profiling of arsenian pyrite in Carlin-type ores through wet chemistry

Enrichment of As and Au at the overgrowth rims of arsenian pyrite is a distinctive feature of Carlin-type gold ores.Revealing distribution of such key elements in high resolution is of fundamental importance yet often proves challenging.In this study,repeated non-oxidative acid etching of ore samples from Shuiyindong gold deposit was applied to enable elemental depth profiling of goldbearing arsenian pyrite grains.ICP-OES and AAS were used to determine the dissolved Fe,As,and Au concentrations in each of the etching solutions,and XPS was carried out to exam the etched mineral surfaces.In contrast to conventional ion beam etching that may cause substantial sample damage,our acid etching method does not seem to significantly alter the composition and chemical state of the samples.The etched depths directly converted from the measured elemental concentrations can reproducibly reach a very high resolution of~1 nm,and can be conveniently controlled through varying the etching time.While the Fe and As depth profiles consistently reflect the surface oxidation property of arsenian pyrite,the Au profile displaying an obvious upward trend reveals the ore fluid evolution at the late stage of mineralization.Based on our experimental results,we demonstrate that our wet chemistry method is capable of effective depth profiling of gold ore and perhaps other geological samples,with advantages surpassing many instrumental techniques including negligible sample damage,nanoscale resolution as well as isotropic etching.