Dynamics of spatio-temporal defects in the Taylor-Dean system

The dynamics of defects in a pattern of traveling inclined rolls has been investigated. Two regimes were identified in the neighborhood of defects: a diffusive regime, with a negative phase diffusion coefficient, and a coalescence regime in which the phase gradient diverges in time following a power law behavior. The observed periodic nucleation of defects is related to the frequency inhomogeneity induced by the disymmetry of the wave amplitude. Amplitude holes have been observed in the secondary modulated pattern. Received 23 February 1999 and Received in final form 26 May 1999     

On the performance of the ICP algorithm

We present upper and lower bounds for the number of iterations performed by the Iterative Closest Point (ICP) algorithm. This algorithm has been proposed by Besl and McKay as a successful heuristic for matching of point sets in d-space under translation, but so far it seems not to have been rigorously analyzed. We consider two standard measures of resemblance that the algorithm attempts to optimize: The RMS (root mean squared distance) and the (one-sided) Hausdorff distance. We show that in both cases the number of iterations performed by the algorithm is polynomial in the number of input points. In particular, this bound is quadratic in the one-dimensional problem, under the RMS measure, for which we present a lower bound construction of Ω(nlogn) iterations, where n is the overall size of the input. Under the Hausdorff measure, this bound is only O(n) for input point sets whose spread is polynomial in n, and this is tight in the worst case.We also present several structural geometric properties of the algorithm under both measures. For the RMS measure, we show that at each iteration of the algorithm the cost function monotonically and strictly decreases along the vector Δt of the relative translation. As a result, we conclude that the polygonal path π, obtained by concatenating all the relative translations that are computed during the execution of the algorithm, does not intersect itself. In particular, in the one-dimensional problem all the relative translations of the ICP algorithm are in the same (left or right) direction. For the Hausdorff measure, some of these properties continue to hold (such as monotonicity in one dimension), whereas others do not.     

Influence of the way of preparing vanadium phosphorus oxide (VPO) precursor and introducing multi-additives on the reaction performance

Spatial patterns of the uncatalyzed bromate – catechol – sulfuric acid system in a thin fluid layer were observed. A mixture of dots, strips and circles was formed by interaction of chemical reaction, diffusion and hydrodynamic instabilities.     

噻唑并[3,2-a]嘧啶衍生物的合成及其在水介质中识别Fe3 的性能

噻唑[3,2-a]并嘧啶衍生物具有多种生物活性,但其较差的溶解性限制了其应用。本文在7-(3-氨基苯并呋喃-2-基)-噻唑并[3,2-a]嘧啶-5-酮的芳香环上引入三乙二醇单甲醚,成功合成了化合物L,并利用核磁、质谱对其结构进行了表征。在pH 3.4~6.4范围内,化合物L可在HEPES水溶液中荧光"开-关"识别Fe~(3+),其他金属离子对识别作用没有干扰,该荧光探针具有较高的选择性和较低的检测限。     

Monitoring and classification of wastewater quality using supervised pattern recognition techniques and deterministic resolution of molecular absorption spectra based on multiwavelength UV spectra deconvolution

A field flow approach for the in situ monitoring of wastewater quality is developed and assessed in this work, based on a combination of methods employing deconvolution of molecular absorption spectra and in situ/on-line analysis of wastewater effluent of various origin. The approach involves in situ immersion probes to monitor basic physicochemical parameters followed by UV spectrum deconvolution in order to provide a rapid estimate of organic matter, suspended solids and nitrate and on-line analysis of phosphates in a fully automated setup. The collected data are then treated with a series of supervised pattern recognition techniques in order to classify wastewater effluent according to their origin in three major categories namely municipal, industrial and hospital. The results suggest that the method affords a good approximation of realistic concentrations, as determined by reference methods, while it affords a good classification among various wastewater effluents of different origin. In that manner, the method enables a rapid inference of treated wastewater quality and a robust assessment of treatment process state, especially with regards to violations of effluent quality parameters.     

Profiling analysis of volatile compounds from fruits using comprehensive two-dimensional gas chromatography and image processing techniques

An image processing approach originating from the proteomics field has been transferred successfully to the processing of data obtained with comprehensive two-dimensional gas chromatographic separations data. The approach described here has proven to be a useful analytical tool for unbiased pattern comparison or profiling analyses, as demonstrated with the differentiation of volatile patterns (“aroma”) from fruits such as apples, pears, and quince fruit. These volatile patterns were generated by headspace solid phase microextraction coupled to comprehensive two-dimensional gas chromatography (HS-SPME-GC × GC). The data obtained from GC × GC chromatograms were used as contour plots which were then converted to gray-scale images and analyzed utilizing a workflow derived from 2D gel-based proteomics. Run-to-run variations between GC × GC chromatograms, respectively their contour plots, have been compensated by image warping. The GC × GC images were then merged into a fusion image yielding a defined and project-wide spot (peak) consensus pattern. Within detected spot boundaries of this consensus pattern, relative quantities of the volatiles from each GC × GC image have been calculated, resulting in more than 700 gap free volatile profiles over all samples. These profiles have been used for multivariate statistical analysis and allowed clustering of comparable sample origins and prediction of unknown samples. At present state of development, the advantage of using mass spectrometric detection can only be realized by data processing off-line from the identified software packages. However, such information provides a substantial basis for identification of statistically relevant compounds or for a targeted analysis.     

柚皮苷分子印迹膜的水相制备与识别

以柚皮苷为印迹分子,PEG为致孔剂,在水相中制备了柚皮苷分子印迹壳聚糖膜.分别讨论了交联剂、致孔剂和印迹分子的用量对印迹膜结构和性能的影响.用SEM观察了致孔剂对印迹膜形貌及孔径的影响.紫外吸收光谱分析、柚皮苷在不同体系中的溶解度变化,以及红外光谱分析的结果表明功能聚合物壳聚糖和模板分子柚皮苷间形成了氢键.膜的渗透实验结果表明,在水相中,柚皮苷分子印迹膜能有效地从新橙皮苷和柚皮苷的混合液中分离出印迹分子柚皮苷,选择透过率为11.16%.     

An entropy-based approach to automatic image segmentation of satellite images

An entropy-based image segmentation approach is introduced and applied to color images obtained from Google Earth. Segmentation refers to the process of partitioning a digital image in order to locate different objects and regions of interest. The application to satellite images paves the way to automated monitoring of ecological catastrophes, urban growth, agricultural activity, maritime pollution, climate changing and general surveillance. Regions representing aquatic, rural and urban areas are identified and the accuracy of the proposed segmentation methodology is evaluated. The comparison with gray level images revealed that the color information is fundamental to obtain an accurate segmentation.     

Turing pattern formation in a predator–prey system with cross diffusion

The paper explores the impacts of cross-diffusion on the formation of spatial patterns in a ratio-dependent predator–prey system with zero-flux boundary conditions. Our results show that under certain conditions, cross-diffusion can trigger the emergence of spatial patterns which is however impossible under the same conditions when cross-diffusion is absent. We give a rigorous proof that the model has at least one spatially heterogenous steady state by means of the Leray–Schauder degree theory. In addition, numerical simulations are performed to visualize the complex spatial patterns.