Selective sampling with Gromov–Hausdorff metric:Efficient dense-shape correspondence via Confidence-based sample consensus

Background Functional mapping, despite its proven efficiency, suffers from a “chicken or egg” scenario, in that, poor spatial features lead to inadequate spectral alignment and vice versa during training, often resulting in slow convergence, high computational costs, and learning failures, particularly when small datasets are used. Methods A novel method is presented for dense-shape correspondence, whereby the spatial information transformed by neural networks is combined with the projections onto spectral maps to overcome the “chicken or egg” challenge by selectively sampling only points with high confidence in their alignment. These points then contribute to the alignment and spectral loss terms, boosting training, and accelerating convergence by a factor of five. To ensure full unsupervised learning, the Gromov–Hausdorff distance metric was used to select the points with the maximal alignment score displaying most confidence. Results The effectiveness of the proposed approach was demonstrated on several benchmark datasets, whereby results were reported as superior to those of spectral and spatial-based methods. Conclusions The proposed method provides a promising new approach to dense-shape correspondence, addressing the key challenges in the field and offering significant advantages over the current methods, including faster convergence, improved accuracy, and reduced computational costs.

Effect of distances between lens and sample surface on laser-induced breakdown spectroscopy with spatial confinement

Spatial confinement can significantly enhance the spectral intensity of laser-induced plasma in air. It is attributed to the compression of plasma plume by the reflected shockwave. In addition,optical emission spectroscopy of laser-induced plasma can also be affected by the distance between lens and sample surface. In order to obtain the optimized spectral intensity, the distance must be considered. In this work, spatially confined laser-induced silicon plasma by using a Nd：YAG nanosecond laser at different distances between lens and sample surface was investigated.The laser energies were 12 mJ, 16 mJ, 20 mJ, and 24 mJ. All experiments were carried out in an atmospheric environment. The results indicated that the intensity of Si（I） 390.55 nm line firstly rose and then dropped with the increase of lens-to-sample distance. Moreover, the spectral peak intensity with spatial confinement was higher than that without spatial confinement. The enhancement ratio was approximately 2 when laser energy was 24 mJ.

适于SDSPAGE分析的高粱叶片蛋白质提取方法

为了探索适于高粱叶片蛋白质SDS-聚丙烯酰胺凝胶电泳(SDS-PAGE)分析的样品制备方法,对TCA/丙酮沉淀后的蛋白质分别用裂解液Ⅰ(尿素+硫脲+CHAPS+DTT)和裂解液Ⅱ(尿素+DTT)2种裂解液进行裂解,用改良的Bradford法进行定量分析,并进行SDS-PAGE分离检测。结果表明,裂解液Ⅰ所得蛋白质质量浓度(2.538g/L)高于裂解液Ⅱ所得蛋白质质量浓度(1.905g/L),且两者呈极显著差异(P<0.05),但裂解液Ⅰ所得蛋白质电泳条带出现1条杂带;而裂解液Ⅱ所得蛋白质能满足上样要求且电泳条带清晰无杂带。因此,TCA/丙酮沉淀并用裂解液Ⅱ进行裂解的方法适用于高粱叶片的SDS-PAGE分析。

大豆蛋白凝胶前后SDS-PAGE图谱比较分析

采用SDS-PAGE分离胶浓度15%,浓缩胶浓度3%的凝胶系统,研究不同的样品浓度下,大豆蛋白各亚基的鉴别,探讨凝胶前后大豆蛋白组分的变化。结果表明:样品浓度为2、3、45、mg/mL时,鉴别效果较好,样品浓度为3 mg/mL时,样品效果最佳,凝胶前后蛋白组分有一定程度的变化。

Spatial Distribution Pattern and Sampling Technique of Spring Wheat Aphid

[ Objective] The aim was to study the spatial distribution pattern and field sampling method of aphid population in spring wheat. [ Method] The aphid quantity in tested wheat field was calculated, the field distribution pattern of wheat aphid was calculated by using aggregated index method, the aggregated reason was analyzed and the field theoretical sampling number was ascertained. [ Result] The wheat aphid population showed aggregation distribution and negative binomial distribution, and such aggregation distribution was induced by interaction of its behavior and environmental factors. The field theoretical sampling number of wheat aphid was related to sample variance and permissible error; the less the sam- ple variance [ S^2 ） was, the less the permissible error [ d＇） was, the bigger the theoretical sampling number without replacement was; when the initial population numbers were different, the theoretical sampling numbers were also different; after the permissible error being set, the bigger the sample variance （ S^2 ） was, the bigger the theoretical sampling number was. [ Conclusion] This study supplied scientific basis for prediction and field control of wheat aphid.

Scaling up the DBSCAN Algorithm for Clustering Large Spatial Databases Based on Sampling Technique

Clustering, in data mining, is a useful technique for discovering interesting data distributions and patterns in the underlying data, and has many application fields, such as statistical data analysis, pattern recognition, image processing, and etc. We combine sampling technique with DBSCAN algorithm to cluster large spatial databases, and two sampling based DBSCAN (SDBSCAN) algorithms are developed. One algorithm introduces sampling technique inside DBSCAN, and the other uses sampling procedure outside DBSCAN. Experimental results demonstrate that our algorithms are effective and efficient in clustering large scale spatial databases.

Design of a spatial sampling scheme considering the spatial autocorrelation of crop acreage included in the sampling units

Information on crop acreage is important for formulating national food polices and economic planning. Spatial sampling, a combination of traditional sampling methods and remote sensing and geographic information system （GIS） technology, provides an efficient way to estimate crop acreage at the regional scale. Traditional sampling methods require that the sampling units should be independent of each other, but in practice there is often spatial autocorrelation among crop acreage contained in the sampling units. In this study, using Dehui County in Jilin Province, China, as the study area, we used a thematic crop map derived from Systeme Probatoire d＇Observation de la Terre （SPOT-5） imagery, cultivated land plots and digital elevation model data to explore the spatial autocorrelation characteristics among maize and rice acreage included in sampling units of different sizes, and analyzed the effects of different stratification criteria on the level of spatial autocorrelation of the two crop acreages within the sampling units. Moran＇s/, a global spatial autocorrelation index, was used to evaluate the spatial autocorrelation among the two crop acreages in this study. The results showed that although the spatial autocorrelation level among maize and rice acreages within the sampling units generally decreased with increasing sampling unit size, there was still a significant spatial autocorrelation among the two crop acreages included in the sampling units （Moran＇s / varied from 0.49 to 0.89）, irrespective of the sampling unit size. When the sampling unit size was less than 3000 m, the stratification design that used crop planting intensity （CPI） as the stratification criterion, with a stratum number of 5 and a stratum interval of 20% decreased the spatial autocorrelation level to almost zero for the maize and rice area included in sampling units within each stratum. Therefore, the traditional sampling methods can be used to estimate the two crop acreages. Compared with CPI, there was still a strong spatial correlation among the two crop acreages included in the sampling units belonging to each stratum when cultivated land fragmentation and ground slope were used as stratification criterion. As far as the selection of stratification criteria and sampling unit size is concerned, this study provides a basis for formulating a reasonable spatial sampling scheme to estimate crop acreage.

Characteristics analysis on high density spatial sampling seismic data

China＇s continental deposition basins are characterized by complex geological structures and various reservoir lithologies. Therefore, high precision exploration methods are needed. High density spatial sampling is a new technology to increase the accuracy of seismic exploration. We briefly discuss point source and receiver technology, analyze the high density spatial sampling in situ method, introduce the symmetric sampling principles presented by Gijs J. O. Vermeer, and discuss high density spatial sampling technology from the point of view of wave field continuity. We emphasize the analysis of the high density spatial sampling characteristics, including the high density first break advantages for investigation of near surface structure, improving static correction precision, the use of dense receiver spacing at short offsets to increase the effective coverage at shallow depth, and the accuracy of reflection imaging. Coherent noise is not aliased and the noise analysis precision and suppression increases as a result. High density spatial sampling enhances wave field continuity and the accuracy of various mathematical transforms, which benefits wave field separation. Finally, we point out that the difficult part of high density spatial sampling technology is the data processing. More research needs to be done on the methods of analyzing and processing huge amounts of seismic data.

Optimised Spatial Sampling Scheme for Soil Electriclal Conductivity Based on Variance Quad-Tree (VQT) Method

The acquisition of precise soil data representative of the entire survey area, is a critical issue for many treatments such as irrigation or fertilization in precision agriculture. The aim of this study was to investigate the spatial variability of soil bulk electrical conductivity （ECb） in a coastal saline field and design an optimized spatial sampling scheme of ECb based on a sampling design algorithm, the variance quad-tree （VQT） method. Soil ECb data were collected from the field at 20 m interval in a regular grid scheme. The smooth contour map of the whole field was obtained by ordinary kriging interpolation, VQT algorithm was then used to split the smooth contour map into strata of different number desired, the sampling locations can be selected within each stratum in subsequent sampling. The result indicated that the probability of choosing representative sampling sites was increased significantly by using VQT method with the sampling number being greatly reduced compared to grid sampling design while retaining the same prediction accuracy. The advantage of the VQT method is that this scheme samples sparsely in fields where the spatial variability is relatively uniform and more intensive where the variability is large. Thus the sampling efficiency can be improved, hence facilitate an assessment methodology that can be applied in a rapid, practical and cost-effective manner.

On Spatial Distribution Pattern of Broccoli Clubroot Disease and and the Sampling Technique

[Objective] To further improve the prediction and forecast and continuous control ability of broccoli clubroot disease. [Methods] The spatial distribution pattern of diseased or infected plants was analyzed using the least square method, fre- quency distribution, aggregation index, m＊-m regression analysis and Taylor＇s pow- er law model. [Result] The field distribution of broccoli plants with clubroot disease tended to be aggregated distribution, m＇-m regression analysis showed that the el- ementary composition of the spatial distribution of diseased or infected plants was individual colony, the individuals attracted each other; the disease had obvious dis- ease focus in the field, and the individual colony showed uniform distribution pattern in the field. Taylor＇s power law showed that the spatial pattern of individual dis- eased or infected plant with clubroot disease tended to be uniform distribution with the increase of the density. On the basis of this, Iwao optimal theoretical sampling model and sequential sampling model were established, namely N =273.954 1/m- 59.698 5, To （N）=0.368 4N±1.926 8√N, respectively, it meant that when surveying N plants, if the accumulative incidence rate exceeded upper bound, the field can be set as control object; if the accumulative incidence rate didn＇t reach lower bound, it can be set as uncontrol field; if the accumulative incidence rate was between upper bound and lower bound, it should be surveyed continuously until the maximum sample size （mo=0.368 4） appeared, that was, the disease incidence was 15%, so the sampling number should be 684 plants. [Conclusion] The research results had very important instructive meaning for disease control.

Spatial Distribution Pattern and Sampling Technology of Soritia leptalina Larvae on Quercus aquifolioides

Soritia leptalina endangers mainly Quercus aquifolioides, and it became particularly rampant on Q. aquifolioides in Linzhi area, Tibet. By applying field investigation and lab analysis, this study explored the spatial distribution type and sampling technology of S. leptalina larvae on Q. aquifolioides. The results showed that insect density in the upper layer of tree canopy is higher than that in the middle and lower layer,that in the upper, middle and lower layer of different levels varies greatly, and insect density in different directions follows the sequence: east > north > west > south; spatial distribution of S. leptalina on Q.aquifolioides belongs to aggregation type, larvae show mutual repulsion; aggregation of S. leptalina is the result of biological characteristics of its larvae and the habitat environment; taking Iwa regression model as the basis, the optimal sampling quantity is determined. The study disclosed the spatial distribution rules of S.leptalina on Q. aquifolioides, and on the basis of which could provide the theoretical basis for preventing Q.aquifolioides from the damage of S. leptalina, and also scientific support for studying the spatial distribution pattern of this insect and its natural enemies on other hosts.

A method of reconstructing 3D model from 2D geological cross-section based on self-adaptive spatial sampling:A case study of Cretaceous McMurray reservoirs in a block of Canada

An orthogonal 2D training image is constructed from the geological analysis results of well logs and sedimentary facies;the 2 D probabilities in three directions are obtained through linear pooling method and then aggregated by the logarithmic linear pooling to determine the 3 D multi-point pattern probabilities at the unknown points,to realize the reconstruction of a 3 D model from 2D cross-section.To solve the problems of reducing pattern variability in the 2 D training image and increasing sampling uncertainty,an adaptive spatial sampling method is introduced,and an iterative simulation strategy is adopted,in which sample points from the region with higher reliability of the previous simulation results are extracted to be additional condition points in the following simulation to improve the pattern probability sampling stability.The comparison of lateral accretion layer conceptual models shows that the reconstructing algorithm using self-adaptive spatial sampling can improve the accuracy of pattern sampling and rationality of spatial structure characteristics,and accurately reflect the morphology and distribution pattern of the lateral accretion layer.Application of the method in reconstructing the meandering river reservoir of the Cretaceous McMurray Formation in Canada shows that the new method can accurately reproduce the shape,spatial distribution pattern and development features of complex lateral accretion layers in the meandering river reservoir under tide effect.The test by sparse wells shows that the simulation accuracy is above 85%,and the coincidence rate of interpretation and prediction results of newly drilled horizontal wells is up to 80%.

Why Well Spread Probability Samples Are Balanced

When sampling from a finite population there is often auxiliary information available on unit level. Such information can be used to improve the estimation of the target parameter. We show that probability samples that are well spread in the auxiliary space are balanced, or approximately balanced, on the auxiliary variables. A consequence of this balancing effect is that the Horvitz-Thompson estimator will be a very good estimator for any target variable that can be well approximated by a Lipschitz continuous function of the auxiliary variables. Hence we give a theoretical motivation for use of well spread probability samples. Our conclusions imply that well spread samples, combined with the Horvitz- Thompson estimator, is a good strategy in a varsity of situations.

Spatial distribution and sampling of larvae of Phthorimaea operculella(Zeller) and its harmfulness

Studies in tobacco fields were conducted in 1993. The results showed that the distribution pattern of the larva was aggregative,and the aggregation did not change with the densities of population of the larva. The characteristics of the vertical distribution of the larva on tobacco plants was more in the lower leaves than in the upper. The difference of population density among the tobacco fields with an elevation of 490 meters and 900 meters was not significant. The number of sampling was given under different precisions by using two-stage sampling technique. The average of leaf area loss caused by the larva in tobacco fields was 12.654 cm2.

Space-time Dynamics of Dendroctonus valens Population in China and Spatial Sampling Technique based on Its Spatial Distribution Pattern

Red turpentine beetle （RTB）, Dendroctongs valens LeConte, is a destructive forest invasive species in China, it mainly attacks Pings tabuliformis and P. bungeana. So far it has spread rapidly to the provinces of Shanxi, Hebei, Henan, Shanxi and Beijing since its first outbreak in Shanxi Province in 1998, and has caused extensive tree mortality. Space-time dynamics of D. valens population and spatial sampling technique based on its spatial distribution pattern were ana- lyzed using geostatistical methods in the pure P. tabuliforis forests and mixedwood stands which were at different damage levels. According to the spatial distribu- tion of D. valeas population, the specific spatial sampling technique was also studied, and then was compared with traditional sampling technique. The spatial sam- piing technique combined with sampling theory and the biological characteristics of D. valens population, which not only could calcnlate the error of the sampling, but also could discuss the optimal sampling number and the optimum size of plot according to different damage levels and different stand types. This helps to explain population expansion and colonization mechanism of D. valens, and to provide a good reference for adopting snitable control measures.

The Use of Spatial Sampling Designs in Business Surveys

An innovative use of spatial sampling designs is here presented. Sampling methods which consider spatial locations of statistical units are already used in agricultural and environmental contexts, while they have never been exploited for establishment surveys. However, the rapidly increasing availability of geo- referenced information about business units makes that possible. In business studies, it may indeed be important to take into account the presence of spatial autocorrelation or spatial trends in the variables of interest, in order to have more precise and efficient estimates. The opportunity of using the most innovative spatial sampling designs in business surveys, in order to produce samples that are well spread in space, is here tested by means of Monte Carlo experiments. For all designs, the Horvitz-Thompson estimator of the population total is used both with equal and unequal inclusion probabilities. The efficiency of sampling designs is evaluated in terms of relative RMSE and efficiency gain compared with designs ignoring the spatial information. Furthermore, an evaluation of spatially balancing samples is also conducted.

轻度认知障碍老人与认知正常老人在不同单双任务下姿势控制能力的差异性

背景:老年人由于轻度认知障碍而引起姿势控制能力下降,导致跌倒风险增高。双任务是在接近真实生活场景下评估认知与姿势控制能力关系的主要研究范式,站立时足底压力中心位移样本熵可代表姿势控制的复杂程度。目的:基于压力中心位移样本熵分析轻度认知障碍老年人与认知正常老年人在姿势控制-空间工作记忆任务中姿势稳定性特征及控制策略的差异,探究认知功能损伤对站立姿势控制能力影响。方法:筛选出符合条件的16名轻度认知障碍老年人和17名认知正常老年人为研究对象,老年人分别完成5种测试任务,包括空间工作记忆、双脚平衡站立、Romberg站立、双脚平衡站立-空间工作记忆双任务、Romberg站立-空间工作记忆双任务,每个任务有效完成3次。使用Kistler三维测力台采集足底压力中心数据,测试指标包括认知行为学指标(认知得分与反应时长)、动力学指标(压力中心位移及样本熵)。结果与结论:①轻度认知障碍老年人在执行空间工作记忆任务时认知得分最大、反应时间最短,双脚平衡站立-空间工作记忆双任务居中,Romberg站立-空间工作记忆双任务认知得分最小、反应时长最长,任务间比较差异均有显著性意义(P<0.05);②与双脚平衡站立、Romberg站立任务相比,轻度认知障碍老年人在执行双任务时压力中心前后、内外方向位移显著更大,压力中心前后、内外方向位移样本熵值显著更小(P<0.05);③在空间工作记忆任务下,轻度认知障碍老年人与认知正常老年人的认知得分、反应时长差异均无显著性意义(P>0.05);在两种双任务下,与认知正常老年人相比,轻度认知障碍老年人的认知得分更小、反应时长更长(P<0.05),同时轻度认知障碍老年人压力中心前后、内外方向位移更大,压力中心前后、内外方向位移样本熵值更小(P<0.05);④结果表明:与认知正常老年人相比,轻度认知障碍老年人在执行双任务时姿势控制复杂度降低,系统适应性较差,自动调控能力下降,更容易受到空间工作记忆干扰,跌倒风险增大。

Seismic data analysis based on spatial subsets

There are some limitations when we apply conventional methods to analyze the massive amounts of seismic data acquired with high-density spatial sampling since processors usually obtain the properties of raw data from common shot gathers or other datasets located at certain points or along lines. We propose a novel method in this paper to observe seismic data on time slices from spatial subsets. The composition of a spatial subset and the unique character of orthogonal or oblique subsets are described and pre-stack subsets are shown by 3D visualization. In seismic data processing, spatial subsets can be used for the following aspects： （1） to check the trace distribution uniformity and regularity; （2） to observe the main features of ground-roll and linear noise; （3） to find abnormal traces from slices of datasets; and （4） to QC the results of pre-stack noise attenuation. The field data application shows that seismic data analysis in spatial subsets is an effective method that may lead to a better discrimination among various wavefields and help us obtain more information.

基于WINCE的多路数据采集处理播放及SD卡存储的实验系统

为了使学生掌握基于嵌入式系统的计算机控制技术,用嵌入式计算机和基于ARM Cortex-M3内核的微控器制作了多路数据采集处理实验系统。该系统基于嵌入式操作系统WINCE,集数据的采集、处理、图形显示、SD卡存储于一身,学生能用它学习基于WINCE的嵌入式计算机控制系统。

Spatial Distribution Pattern and Application of Fourth-Generation Mature Larvae of Cotton Bollworm(Helicoverpa armigera Hübner) in Corn Field

[ Objective] The paper was to study the spatial distribution pattern of fourth-generation mature larvae of cotton bellworm in corn field. [ Method] The plots with different occurrence densities of fourth-generation cotton bollworm were investigated from August to September in 2009. Six groups of sampling data were obtained, and seven indicators including aggregation index method, Iwao method and Taylor method, etc. were used to determine its spatial distribution pattern. [ Result ] Aggregation index test showed that in all plots, Moore I 〈 0, Lloyed m＊/m 〈 1, Kuno Ca 〈 0, diffusion coefficient C 〈 1, diffusion index 16 〈 1, negative binomial distribution K 〈 0, indicating that mature larvae of cotton bollworm showed uniform distribution in summer corn. Iwae regression equation of fourth-genera- tion mature larvae of cotton boUworm in summer corn was m ＊ = 0. 090 6 ＋ 0. 766 9 m, r = 0. 986 3, indicating that the basic components of cotton bollworm distribu- ted was single individual, and mature larvae of cotton bollworm in summer corn showed uniform distribution. The optimal sampling number of fourth-generation ma- ture larvae of cotton bollworm in corn under different population densities could be calculated using formula N1 = （ 1. 090 6/m -0. 233 1 ）/D2. [ Conclusion] The result provided basis for accurate evaluation of population quantities and variation law of cotton boUworm, as well as prediction and control of the pest.