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.

Morphotype dependence of Globigerinoides ruber(white)and Trilobatus sacculifer Mg/Ca ratios in the western tropical Pacific:implications for reconstructing the mixed-layer depth

Planktonic foraminifer Globigerinoides ruber(white)and Trilobatus sacculifer are the most frequently used mixedlayer dwelling species for reconstructing past oceanic environments.Specifically,the Mg/Ca ratios of these two foraminiferal species have been used for reconstructing tropical/subtropical changes in sea surface temperature(SST).However,these two species have different morphotypes,of which the spatial and temporal differences in Mg/Ca ratios and their influencing factors are still unclear.Our objective is to investigate the potential differences between the Mg/Ca ratios of these different morphotypes of G.ruber(white)and T.sacculifer in the western Philippine Sea(WPS)and determine their implications for the reconstruction of SST and upper-ocean structure.Mg/Ca measurements are made on two basic morphotypes of G.ruber(white)[sensu stricto(s.s.)and sensu lato(s.l.)]and T.sacculifer[with(w)and without(w/o)a sac-like final chamber]on samples of Site MD06-3047B from the WPS.Our results reveal that Mg/Ca ratios of different G.ruber morphotypes show consistent differences;and those of T.sacculifer morphotypes show staged variations since MIS 3.It is suggested to select a single morphotype for reconstructing SST changes using the Mg/Ca ratios of G.ruber and T.sacculifer in the WPS.Furthermore,the Mg/Ca ratios between G.ruber s.s.and G.ruber s.l.[Δ(Mg/Ca)_(G.ruber s.s.-s.l.)]downcore MD06-3047B covaries with indexes of summer monsoon.Combining with the core-top results,showing regional variation of differences in theΔ(Mg/Ca)_(G.ruber s.s.-s.l.)over the western tropical Pacific,we propose thatΔ(Mg/Ca)_(G.ruber s.s.-s.l.)may tend to reflect summer mixed layer depth.

A new method for the estimation of oceanic mixed-layer depth using shipboard X-band radar images

Shipboard X-band radar images acquired on 24 June 2009 are used to study nonlinear internal wave characteristics in the northeastern South China Sea.The studied images show three nonlinear internal waves in a packet.A method based on the Radon Transform technique is introduced to calculate internal wave parameters such as the direction of propagation and internal wave velocity from backscatter images.Assuming that the ocean is a two-layer finite depth system,we can derive the mixed-layer depth by applying the internal wave velocity to the mixed-layer depth formula.Results show reasonably good agreement with in-situ thermistor chain and conductivity-temperature-depth data sets.

Application of the improved dung beetle optimizer,muti-head attention and hybrid deep learning algorithms to groundwater depth prediction in the Ningxia area,China

Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical models.Machine learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many areas.In this study,two new models are applied to the prediction of groundwater depth in the Ningxia area,China.The two models combine the improved dung beetle optimizer(DBO)algorithm with two deep learning models:The Multi-head Attention-Convolution Neural Network-Long Short Term Memory networks(MH-CNN-LSTM)and the Multi-head Attention-Convolution Neural Network-Gated Recurrent Unit(MH-CNN-GRU).The models with DBO show better prediction performance,with larger R(correlation coefficient),RPD(residual prediction deviation),and lower RMSE(root-mean-square error).Com-pared with the models with the original DBO,the R and RPD of models with the improved DBO increase by over 1.5%,and the RMSE decreases by over 1.8%,indicating better prediction results.In addition,compared with the multiple linear regression model,a traditional statistical model,deep learning models have better prediction performance.

Outcomes of a non-diffractive extended depth of focus intraocular lens in patients with well-controlled glaucoma and ocular hypertension

AIM:To assess visual outcomes and satisfaction of a non-diffractive extended depth of focus(EDOF)intraocular lens(IOL)in individuals with ocular hypertension(OHT)and well-controlled mild glaucoma undergoing cataract surgery.METHODS:An investigator-initiated,single-center,prospective,interventional,noncomparative study conducted in Montreal,Canada.The study enrolled 31 patients(55 eyes)with OHT or mild glaucoma who received a non-diffractive EDOF IOL(Acrysof IQ Vivity).Participants underwent sequential cataract surgery with the Vivity IOL.Follow-up evaluations occurred at 1d,1,and 3mo postoperatively,assessing uncorrected distance,intermediate,and near visual acuity.Questionnaires(QUVID:Questionnaire for visual disturbances and IOLSAT:Intraocular lens satisfaction)were administered pre and post-operatively to measure visual disturbances and spectacle independence in various lighting.Safety parameters included intraocular pressure(IOP),glaucoma medications,spherical equivalence,mean deviation and pattern standard deviation or square root of lost variance on Octopus visual field.RESULTS:At 1 and 3mo postoperatively,significant improvements were observed in uncorrected distance and intermediate visual acuity.Spectacle independence was enhanced for distance and intermediate vision,especially in bright light settings.Spectacle-free intermediate vision was improved even in dim lighting.Visual disturbances,particularly glare symptoms,were reduced,and there was a notable decrease in IOP and glaucoma medication burden at 3mo.There was more hazy vision postoperatively with no impact on visual acuity and visual satisfaction.CONCLUSION:The non-diffractive EDOF lens improves distance and intermediate spectacle-free visual function in patients with OHT and well-controlled glaucoma.The findings highlight significant improvements in visual acuity,reduced glare,enhanced spectacle independence,and improved visual performance in different lighting conditions.

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。

A 31-year Global Diurnal Sea Surface Temperature Dataset Created by an Ocean Mixed-Layer Model

A dataset of hourly sea surface temperature(SST) from the period 1 January 1982 to 31 December 2012, and covering the global ocean at a resolution of 0.3°× 0.3°, was created using a validated ocean mixed-layer model(MLSST). The model inputs were heat flux and surface wind speed obtained from the Coupled Forecast System Reanalysis dataset. Comparisons with in-situ data from the Tropical Atmosphere Ocean array and the National Data Buoy Center showed that the MLSST fitted very well with observations, with a mean bias of 0.07℃, and a root-mean-square error(RMSE) and correlation coefficient of 0.37℃ and 0.98, respectively. Also, the MLSST fields successfully reproduced the diurnal cycle of SST in the in-situ data, with a mean bias of -0.005℃ and RMSE of 0.26℃. The 31-year climatology revealed that the diurnal range was small across most regions, with higher values in the eastern and western equatorial Pacific, northern Indian Ocean, western Central America, northwestern Australia, and several coastal regions. Significant seasonal variation of diurnal SST existed in all basins. In the Atlantic and Pacific basins, this seasonal pattern was oriented north–south, following the variation in solar insolation, whereas in the Indian basin it was dominated by monsoonal variability. At the interannual scale, the results highlighted the relationship between diurnal and interannual variations of SST, and revealed that the diurnal warming in the central equatorial Pacific could be a potential climatic indicator for ENSO prediction.

基于改进FeatDepth的足球运动场景无监督单目图像深度预测

为了在降低成本的同时提高图像深度信息预测的精确度,并将深度估计应用于足球运动场景,提出一种基于改进FeatDepth的足球运动场景无监督单目图像深度预测方法。首先,对原FeatDepth引入注意力机制,使模型更加关注有效的特征信息;其次,将FeatDepth中的PoseNet网络和DepthNet网络分别嵌入GAM全局注意力机制模块,为网络添加额外的上下文信息,在基本不增加计算成本的情况下提升FeatDepth模型深度预测性能;再次,为在低纹理区域和细节上获得更好的深度预测效果,由单视图重构损失与交叉视图重构损失组合而成最终的损失函数。选取KITTI数据集中Person场景较多的部分进行数据集制作并进行仿真实验,结果表明,改进后的FeatDepth模型不仅在精确度上有所提升,且在低纹理区域及细节处拥有更好的深度预测效果。最后,对比模型在足球场景下的推理效果后得出,改进后的模型在低纹理区域(足球、球门等)及细节处(肢体等)有更好的深度预测效果,实现了将基于无监督的单目深度估计模型应用于足球运动场景的目的。

Edge enhanced depth perception with binocular meta-lens

The increasing popularity of the metaverse has led to a growing interest and market size in spatial computing from both academia and industry.Developing portable and accurate imaging and depth sensing systems is crucial for advancing next-generation virtual reality devices.This work demonstrates an intelligent,lightweight,and compact edge-enhanced depth perception system that utilizes a binocular meta-lens for spatial computing.The miniaturized system comprises a binocular meta-lens,a 532 nm filter,and a CMOS sensor.For disparity computation,we propose a stereo-matching neural network with a novel H-Module.The H-Module incorporates an attention mechanism into the Siamese network.The symmetric architecture,with cross-pixel interaction and cross-view interaction,enables a more comprehensive analysis of contextual information in stereo images.Based on spatial intensity discontinuity,the edge enhancement eliminates illposed regions in the image where ambiguous depth predictions may occur due to a lack of texture.With the assistance of deep learning,our edge-enhanced system provides prompt responses in less than 0.15 seconds.This edge-enhanced depth perception meta-lens imaging system will significantly contribute to accurate 3D scene modeling,machine vision,autonomous driving,and robotics development.

Illite-smectite Mixed-layer Minerals in the Alteration Volcanic Ashes under Submarine Environment

The clay mineralogy of the clay intervals interbedded with siliceous mudstones across the Permian-Triassic boundary (PTB) in Pengda, Guiyang, Guizhou province, was investigated by X-ray diffraction (XRD) and high resolution transmission electron microscopy (HRTEM). The clay mineral assemblages of the sediments are mainly I/S clays and minor smectite, kaolinite, and illite as reveled by XRD analyses. The peak-shape parameters BB1 and BB2 of I/S clays of the representative clay bed PL-01 are 4.7° and 4.4°, and the peak position of the low angle reflection is at 6.8° 2θ (13.6 ), suggesting that the I/S clays has a IS type of ordering. However, the presence of multi-order reflections and their intensities are different from those of completely ordered 1∶1 mixed-layer I/S clay rectorite, indicating that I/S clays of the Pengda section have partially ordered IS structures. HRTEM observations show that most of the I/S clays exhibit an IS stacking ordering. However, in some areas within a IS particle, smectite layer is observed in doublets, triplets, and quartets, which are interstratified by various amounts of illite layers, suggesting the presence of other irregular stacking in addition to the major 1∶1 IS ordered stacking. Transformation of smectite layer into illite layers is also observed in the I/S clays, suggesting that the Pengda I/S clays are derived from smectite illitization, in good agreement with the clay mineral assemblage. The I/S clays of the Pengda section contain up to 45% to 95% smectite layer, the notably higher contents of smectite layer relative to those of other PTB stratigraphic sets in south China can be attributed to difference in alteration and smectite illitization processes due to different sedimentary environments.

Study of the Stacking Sequences of an Irregular Mixed-Layer Illite/Smectite (I/S) Clay Mineral—with a Discussion on the Existence of Minerals with Two-Dimentional Lattice and One-Dimentional Quasi-Lattice

There are two aspects in the study of irregular mixed-layer clay minerals: one is the kinds and ratios of their basic structural unit layers and the other is the junction probabilities of the unit layers. Irregular mixed-layer illite/smectite clay minerals (I/S) are widespread in nature. While studying the clay minerals from the Permian-Triassic (P/T) boundary bed, the authors found that I/S clay minerals are developed in all P/T boundary clay layers in areas from the northwest to southeast of China. Systematic mineralogical studies of the I/S clay minerals from Hunan, Hubei, Sichuan and Zhejiang were made by means of X-ray, infrared spectroscopic, electron microscopic and chemical analyses and a deepened study of the stacking sequences of their structural unit layers was conducted by the MacEwan one—dimentional direct Fourier transform. It was found that the stacking of the illite and smectite crystal layers along the c axis can be derived from Fibonacci sequences. Hence, the authors propose that such I/S clay minerals are possessed of two—dimentional crystal lattice and one—dimentional quasicrystal lattice.

Responses of the Southern Ocean mixed layer depth to the eastern and central Pacific El Niño events during austral winter

Based on the Ocean Reanalysis System version 5(ORAS5)and the fifth-generation reanalysis datasets derived from European Centre for Medium-Range Weather Forecasts(ERA5),we investigate the different impacts of the central Pacific(CP)El Niño and the eastern Pacific(EP)El Niño on the Southern Ocean(SO)mixed layer depth(MLD)during austral winter.The MLD response to the EP El Niño shows a dipole pattern in the South Pacific,namely the MLD dipole,which is the leading El Niño-induced MLD variability in the SO.The tropical Pacific warm sea surface temperature anomaly(SSTA)signal associated with the EP El Niño excites a Rossby wave train propagating southeastward and then enhances the Amundsen Sea low(ASL).This results in an anomalous cyclone over the Amundsen Sea.As a result,the anomalous southerly wind to the west of this anomalous cyclone advects colder and drier air into the southeast of New Zealand,leading to surface cooling through less total surface heat flux,especially surface sensible heat(SH)flux and latent heat(LH)flux,and thus contributing to the mix layer(ML)deepening.The east of the anomalous cyclone brings warmer and wetter air to the southwest of Chile,but the total heat flux anomaly shows no significant change.The warm air promotes the sea ice melting and maintains fresh water,which strengthens stratification.This results in a shallower MLD.During the CP El Niño,the response of MLD shows a separate negative MLD anomaly center in the central South Pacific.The Rossby wave train triggered by the warm SSTA in the central Pacific Ocean spreads to the Amundsen Sea,which weakens the ASL.Therefore,the anomalous anticyclone dominates the Amundsen Sea.Consequently,the anomalous northerly wind to the west of anomalous anticyclone advects warmer and wetter air into the central and southern Pacific,causing surface warming through increased SH,LH,and longwave radiation flux,and thus contributing to the ML shoaling.However,to the east of the anomalous anticyclone,there is no statistically significant impact on the MLD.

Three-dimensional crystal defect imaging by STEM depth sectioning

One of the major innovations awaiting in electron microscopy is full three-dimensional imaging at atomic resolution.Despite the success of aberration correction to deep sub-angstrom lateral resolution,spatial resolution in depth is still far from atomic resolution.In scanning transmission electron microscopy(STEM),this poor depth resolution is due to the limitation of the illumination angle.To overcome this physical limitation,it is essential to implement a next-generation aberration corrector in STEM that can significantly improve the depth resolution.This review discusses the capability of depth sectioning for three-dimensional imaging combined with large-angle illumination STEM.Furthermore,the statistical analysis approach remarkably improves the depth resolution,making it possible to achieve three-dimensional atomic resolution imaging at oxide surfaces.We will also discuss the future prospects of three-dimensional imaging at atomic resolution by STEM depth sectioning.

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.

Perpendicular-Cutdepth:Perpendicular Direction Depth Cutting Data Augmentation Method

Depth estimation is an important task in computer vision.Collecting data at scale for monocular depth estimation is challenging,as this task requires simultaneously capturing RGB images and depth information.Therefore,data augmentation is crucial for this task.Existing data augmentationmethods often employ pixel-wise transformations,whichmay inadvertently disrupt edge features.In this paper,we propose a data augmentationmethod formonocular depth estimation,which we refer to as the Perpendicular-Cutdepth method.This method involves cutting realworld depth maps along perpendicular directions and pasting them onto input images,thereby diversifying the data without compromising edge features.To validate the effectiveness of the algorithm,we compared it with existing convolutional neural network(CNN)against the current mainstream data augmentation algorithms.Additionally,to verify the algorithm’s applicability to Transformer networks,we designed an encoder-decoder network structure based on Transformer to assess the generalization of our proposed algorithm.Experimental results demonstrate that,in the field of monocular depth estimation,our proposed method,Perpendicular-Cutdepth,outperforms traditional data augmentationmethods.On the indoor dataset NYU,our method increases accuracy from0.900 to 0.907 and reduces the error rate from0.357 to 0.351.On the outdoor dataset KITTI,our method improves accuracy from 0.9638 to 0.9642 and decreases the error rate from 0.060 to 0.0598.

Applying the Dark Target Aerosol Algorithm to MERSI-Ⅱ:Retrieval and Validation of Aerosol Optical Depth over the Ocean

The Medium-Resolution Spectral Imager-Ⅱ(MERSI-Ⅱ)instrument aboard China’s Fengyun-3D satellite shares similarities with NASA’s Moderate Resolution Imaging Spectroradiometer(MODIS)sensor,enabling the retrieval of global aerosol optical depth(AOD).However,no officially released operational MERSI-Ⅱ aerosol products currently exist over the ocean.This study focuses on adapting the MODIS dark target(DT)ocean algorithm to the MERSI-Ⅱ sensor.A retrieval test is conducted on the 2019 MERSI-Ⅱ data over the global ocean,and the retrieved AODs are validated against ground-based measurements from the automatic Aerosol Robotic Network(AERONET)and the shipborne Maritime Aerosol Network(MAN).The operational MODIS DT aerosol products are also used for comparison purposes.The results show that MERSI-Ⅱ AOD granule retrievals are in good agreement with MODIS products,boasting high correlation coefficients(R)of up to 0.96 and consistent spatial distribution trends.Furthermore,the MERSI-Ⅱ retrievals perform well in comparison to AERONET and MAN measurements,with high R-values(>0.86).However,the low-value retrievals from MERSI-Ⅱ tend to be slightly overestimated compared to MODIS,despite both AODs displaying a positive bias.Notably,the monthly gridded AODs over the high latitudes of the northern and southern hemispheres suggest that MERSI-Ⅱ exhibits greater stability in space and time,effectively reducing unrealistically high-value noise in the MODIS products.These results illustrate that the MERSI-Ⅱ retrievals meet specific accuracy requirements by maintaining the algorithmic framework and most of the algorithmic assumptions,providing a crucial data supplement for aerosol studies and climate change.

Influence of mixed layer depth on chlorophyll-a concentration in the Southern Ocean

The element iron limitation is one of the crucial factors contributing to high nutrient low chlorophyll in the Southern Ocean(SO).Mixed layer dynamics regulate the availability of iron to phytoplankton.In this paper,we investigate the influence of surface iron supplementation triggered by the mixed layer depth(MLD)variation on chlorophyll-a(Chl-a)concentration in the SO on seasonal and interannual timescales.This analysis is based on the Biogeochemical Southern Ocean State Estimate for the period from 2013 to 2021.We provide a comprehensive and systematic mapping of the regions within the SO,where Chl-a is affected by iron input related to MLD deepening.The relationship between the MLD and the Chl-a varies with the latitude on the seasonal time scale.Both the MLD and sea ice melting affect the distribution of Chl-a.On the interannual scale,iron supply due to MLD deepening occurs primarily north of 60°S.Horizontal advection-induced entrainment enhances the surface iron input during the austral summer,which favors Chl-a increase.In addition to the MLD,the melting of sea ice and cooling of the sea surface can also alter iron input and subsequently affect Chl-a distribution in the austral summer.During the austral winter,entrainment can boost iron stocks,stimulating a subsequent spring increase of Chl-a in the SO.Furthermore,sea surface temperature declines during the austral winter,promoting an increased iron supply and creating favorable conditions for the subsequent spring Chl-a increase in the SO.

Extraction of Acoustic Normal Mode Depth Functions Using Range-Difference Method with Vertical Linear Array Data

Data-derived normal mode extraction is an effective method for extracting normal mode depth functions in the absence of marine environmental data.However,when the corresponding singular vectors become nonunique when two or more singular values obtained from the cross-spectral density matrix diagonalization are nearly equal,this results in unsatisfactory extraction outcomes for the normal mode depth functions.To address this issue,we introduced in this paper a range-difference singular value decomposition method for the extraction of normal mode depth functions.We performed the mode extraction by conducting singular value decomposition on the individual frequency components of the signal's cross-spectral density matrix.This was achieved by using pressure and its range-difference matrices constructed from vertical line array data.The proposed method was validated using simulated data.In addition,modes were successfully extracted from ambient noise.

The penetration depth of atomic radicals in tubes with catalytic surface properties

Catalysis of molecular radicals is often performed in interesting experimental configurations.One possible configuration is tubular geometry.The radicals are introduced into the tubes on one side,and stable molecules are exhausted on the other side.The penetration depth of radicals depends on numerous parameters,so it is not always feasible to calculate it.This article presents systematic measurements of the penetration depth of oxygen atoms along tubes made from nickel,cobalt,and copper.The source of O atoms was a surfatron-type microwave plasma.The initial density of O atoms depended on the gas flow and was 0.7×10^(21)m^(-3),2.4×10^(21)m^(-3),and 4.2×10^(21)m^(-3)at the flow rates of 50,300,and 600 sccm,and pressures of 10,35,and 60 Pa,respectively.The gas temperature remained at room temperature throughout the experiments.The dissociation fraction decreased exponentially along the length of the tubes in all cases.The penetration depths for well-oxidized nickel were 1.2,1.7,and 2.4 cm,respectively.For cobalt,they were slightly lower at 1.0,1.3,and 1.6 cm,respectively,while for copper,they were 1.1,1.3,and 1.7 cm,respectively.The results were explained by gas dynamics and heterogeneous surface association.These data are useful in any attempt to estimate the loss of molecular fragments along tubes,which serve as catalysts for the association of various radicals to stable molecules.

Convergence Zone Width Analysis Based on Ray Cluster Theory and Its Application in the Array Depth Optimization of Active Sensors

The active sensor often uses the convergence zone mode to detect a distant target in the deep ocean.However,convergence zones are regions with limited widths that only appear at some discrete distances.Thus,widening the width by adjusting the transmitting array depth facilitates target observation and detection.Traversal search is an effective method for determining the optimal depth,but the heavy computation burden resulting from the calculation of the transmission losses at all source depths impedes its application.To solve the problem,a fast method based on ray cluster theory is proposed.Due to the coherent sound field structure in the deep ocean,several ray clusters with different departure angles radiate from the source,where ray clusters with small departure angles reverse in the water and form a convergence zone.When the source is set to a depth that only the first ray cluster inverts in water,the maximum width of the convergence zone is obtained.Based on this,an optimal transmitting array depth selection method utilizing the reversion condition of the first ray cluster is formulated.Simulation results show that the active sensor can achieve a large convergence zone width with real-time performance using the proposed method.