954 resultados para Data Structure Operations


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Artemia is a small crustacean that adapted to live in brine water and has been seen in different brine water sources in Iran. Considering the importance of genetic studies manifest inter population differences in species, to estimate genetic structure, detect difference at molecular level and separate different Artemia populations of Iran, also study of phylogenic relationships among them, samples of Artemia were collected from nine region: Urmia lake in West Azerbaijan, Shoor and Inche-Borun lakes in Golestan, Hoze-Soltan and Namak lakes in Qom, Maharloo and Bakhteghan lakes in Fars, Nough pool in Kerman and Mighan pool in Markazi and DNA extracted by phenol-chloroform method. Primers designed on a ribosomal fragment (16s rRNA) of mt DNA sequence and PCR was done. Digestion of the 1566 bp segment PCR product by 10 restriction endonuclease (Alu I, EcoR I, Eco47 I, Hae III, Hind III, Hinf I, Mbo I, Msp I, Rsa I, TaqI) showed 25 different haplotypes: 9 in Urmia, 4 in Shoor and Inche- Borun, 1 in Namak and Hoze-Soltan, 3 in Mighan, 1 in Bakhtegan Maharlo, 3 in Maharloo and 4 in Nough. Measurement of haplotype and nucleotide diversity intra population and nucleotide diversity and divergence inter populations and evolutionary distance between haplotypes showed a high diversity in mitochondrial genome of Artemia in studied regions whose results are similar to those explained for highly geographic expansion organism. In addition, results showed considerable heterogeneity between different populations and there are enough evidences in haplotypic level for separation of studied samples and division of Iranian Artemia to seven populations including Urmia, Shoor and Inche-Borun, Hoze-Soltan and Namak, Maharloo, Bakhteghan, Nough and Mighan. Phylogenetic analysis of the 16S rRNA data set resulted strict consensus and neighbor joining distance trees, demonstrated that all samples were monophyletic and parthenogenetic form derivation from bisexual populations and genetically high resemblance to those of A. urmiana. Study of 270 specimens from different region showed the genus Artemia in Iran clustered into three clades including: 1- Shoor, Inche-Burun, Hoze-Soltan, Namak, Bakhtegan and Maharloo 2- Nough and Mighan 3- Urmia. Totally, obtained results indicated to ability of used techniques for study of inter species diversity, population structure, reveal of phylogenic relationship and dividing of different populations of Artemia in Iran.

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Green tiger prawn, Penaeus sentisulcatus is one of the commercial species of Persian Gulf, which is distributed from north to Strait of I Iormoze. Concerning its role in fisheries economic, various research projects on stock assessment, biology and aquaculture has been conducted. This research is targeted the identification of various populations of green tiger prawn in northern waters of Persian Gulf. The area has been divided to five regions from north to south named; Bahrakan, Boushehr, Tangestan, Motaaf and Strait of Hormoz. In each region, numbers of sampling stations trawled, and live shrimp species carried in containers equipped with air pump, to coastal laboratories in Boushehr and Bandar Abbass Fisheries Research Centers. Biometeric, morphometeric and merestic measures for 45 factars done, and peices of muscles, eye and ovary tissues dissected, and stored in liquid nitrogen. Protein extraction, and polyacrylamid gel electrophoresis by SDS-PAGE technique for tissues samples conducted. Data of 45 morphometeric and merestic characteristics analyzed by principal component analysis (PCA), and clustering analysis methods. The results of analysis showed that, the populations of Bahrakan and Mota.af regions are differentiated, while population of Boushehr and Tangestan regions were mixed, and named as a single population. The analysis of electrophoretic data also confirmed this result, and showed a distinct population in Strait of Hormoz. Therefore, this research illustrated four distinct populations for P. semisulcatus in northern area of Persian Gulf, named Bahrakan (north of Boushehr), Boushehr and Tangesta.n (adjacent), Motaaf and it's south, and Strait of Hormoz. Study of morphometeric characteristics of carapace factors, genital organs, antenna and life cycle of samples of different regions resulting identification of a subspecies, which is named Penaeus seinisuleatus persicus.

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Kolmogorov's two-thirds, ((Δv) 2) ∼ e 2/ 3r 2/ 3, and five-thirds, E ∼ e 2/ 3k -5/ 3, laws are formally equivalent in the limit of vanishing viscosity, v → 0. However, for most Reynolds numbers encountered in laboratory scale experiments, or numerical simulations, it is invariably easier to observe the five-thirds law. By creating artificial fields of isotropic turbulence composed of a random sea of Gaussian eddies whose size and energy distribution can be controlled, we show why this is the case. The energy of eddies of scale, s, is shown to vary as s 2/ 3, in accordance with Kolmogorov's 1941 law, and we vary the range of scales, γ = s max/s min, in any one realisation from γ = 25 to γ = 800. This is equivalent to varying the Reynolds number in an experiment from R λ = 60 to R λ = 600. While there is some evidence of a five-thirds law for g > 50 (R λ > 100), the two-thirds law only starts to become apparent when g approaches 200 (R λ ∼ 240). The reason for this discrepancy is that the second-order structure function is a poor filter, mixing information about energy and enstrophy, and from scales larger and smaller than r. In particular, in the inertial range, ((Δv) 2) takes the form of a mixed power-law, a 1+a 2r 2+a 3r 2/ 3, where a 2r 2 tracks the variation in enstrophy and a 3r 2/ 3 the variation in energy. These findings are shown to be consistent with experimental data where the polution of the r 2/ 3 law by the enstrophy contribution, a 2r 2, is clearly evident. We show that higherorder structure functions (of even order) suffer from a similar deficiency.

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The uncertainty associated with a rainfall-runoff and non-point source loading (NPS) model can be attributed to both the parameterization and model structure. An interesting implication of the areal nature of NPS models is the direct relationship between model structure (i.e. sub-watershed size) and sample size for the parameterization of spatial data. The approach of this research is to find structural limitations in scale for the use of the conceptual NPS model, then examine the scales at which suitable stochastic depictions of key parameter sets can be generated. The overlapping regions are optimal (and possibly the only suitable regions) for conducting meaningful stochastic analysis with a given NPS model. Previous work has sought to find optimal scales for deterministic analysis (where, in fact, calibration can be adjusted to compensate for sub-optimal scale selection); however, analysis of stochastic suitability and uncertainty associated with both the conceptual model and the parameter set, as presented here, is novel; as is the strategy of delineating a watershed based on the uncertainty distribution. The results of this paper demonstrate a narrow range of acceptable model structure for stochastic analysis in the chosen NPS model. In the case examined, the uncertainties associated with parameterization and parameter sensitivity are shown to be outweighed in significance by those resulting from structural and conceptual decisions. © 2011 Copyright IAHS Press.

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Anew integrated sequence-structure database, called IADE (Integrated ASTRAL-DSSP-EMBL), incorporating matching mRNA sequence, amino acid sequence, and protein secondary structural data, is constructed. It includes 648 protein domains. Based on the IADE database, we studied the relation between RNA stem-loop frequencies and protein secondary structure. It was found that the alpha-helices and beta-strands on proteins tend to be preferably "coded" by mRNA stem region, while the coils on proteins tend to be preferably "coded" by mRNA loop region. These tendencies are more obvious if we observe the structural words (SWs). An SW is defined by a four-amino-acid-fragment that shows the pronounced secondary structural (alpha-helix or beta-strand) propensity. It is demonstrated that the deduced correlation between protein and mRNA structure can hardly be explained as the stochastic fluctuation effect. (C) 2003 Wiley Periodicals, Inc.

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The Dependency Structure Matrix (DSM) has proved to be a useful tool for system structure elicitation and analysis. However, as with any modelling approach, the insights gained from analysis are limited by the quality and correctness of input information. This paper explores how the quality of data in a DSM can be enhanced by elicitation methods which include comparison of information acquired from different perspectives and levels of abstraction. The approach is based on comparison of dependencies according to their structural importance. It is illustrated through two case studies: creation of a DSM showing the spatial connections between elements in a product, and a DSM capturing information flows in an organisation. We conclude that considering structural criteria can lead to improved data quality in DSM models, although further research is required to fully explore the benefits and limitations of our proposed approach.

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Latent variable models for network data extract a summary of the relational structure underlying an observed network. The simplest possible models subdivide nodes of the network into clusters; the probability of a link between any two nodes then depends only on their cluster assignment. Currently available models can be classified by whether clusters are disjoint or are allowed to overlap. These models can explain a "flat" clustering structure. Hierarchical Bayesian models provide a natural approach to capture more complex dependencies. We propose a model in which objects are characterised by a latent feature vector. Each feature is itself partitioned into disjoint groups (subclusters), corresponding to a second layer of hierarchy. In experimental comparisons, the model achieves significantly improved predictive performance on social and biological link prediction tasks. The results indicate that models with a single layer hierarchy over-simplify real networks.

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After earthquakes, licensed inspectors use the established codes to assess the impact of damage on structural elements. It always takes them days to weeks. However, emergency responders (e.g. firefighters) must act within hours of a disaster event to enter damaged structures to save lives, and therefore cannot wait till an official assessment completes. This is a risk that firefighters have to take. Although Search and Rescue Organizations offer training seminars to familiarize firefighters with structural damage assessment, its effectiveness is hard to guarantee when firefighters perform life rescue and damage assessment operations together. Also, the training is not available to every firefighter. The authors therefore proposed a novel framework that can provide firefighters with a quick but crude assessment of damaged buildings through evaluating the visible damage on their critical structural elements (i.e. concrete columns in the study). This paper presents the first step of the framework. It aims to automate the detection of concrete columns from visual data. To achieve this, the typical shape of columns (long vertical lines) is recognized using edge detection and the Hough transform. The bounding rectangle for each pair of long vertical lines is then formed. When the resulting rectangle resembles a column and the material contained in the region of two long vertical lines is recognized as concrete, the region is marked as a concrete column surface. Real video/image data are used to test the method. The preliminary results indicate that concrete columns can be detected when they are not distant and have at least one surface visible.

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The commercial far-range (>10m) infrastructure spatial data collection methods are not completely automated. They need significant amount of manual post-processing work and in some cases, the equipment costs are significant. This paper presents a method that is the first step of a stereo videogrammetric framework and holds the promise to address these issues. Under this method, video streams are initially collected from a calibrated set of two video cameras. For each pair of simultaneous video frames, visual feature points are detected and their spatial coordinates are then computed. The result, in the form of a sparse 3D point cloud, is the basis for the next steps in the framework (i.e., camera motion estimation and dense 3D reconstruction). A set of data, collected from an ongoing infrastructure project, is used to show the merits of the method. Comparison with existing tools is also shown, to indicate the performance differences of the proposed method in the level of automation and the accuracy of results.

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Most of the manual labor needed to create the geometric building information model (BIM) of an existing facility is spent converting raw point cloud data (PCD) to a BIM description. Automating this process would drastically reduce the modeling cost. Surface extraction from PCD is a fundamental step in this process. Compact modeling of redundant points in PCD as a set of planes leads to smaller file size and fast interactive visualization on cheap hardware. Traditional approaches for smooth surface reconstruction do not explicitly model the sparse scene structure or significantly exploit the redundancy. This paper proposes a method based on sparsity-inducing optimization to address the planar surface extraction problem. Through sparse optimization, points in PCD are segmented according to their embedded linear subspaces. Within each segmented part, plane models can be estimated. Experimental results on a typical noisy PCD demonstrate the effectiveness of the algorithm.

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Most of the existing automated machine vision-based techniques for as-built documentation of civil infrastructure utilize only point features to recover the 3D structure of a scene. However it is often the case in man-made structures that not enough point features can be reliably detected (e.g. buildings and roofs); this can potentially lead to the failure of these techniques. To address the problem, this paper utilizes the prominence of straight lines in infrastructure scenes. It presents a hybrid approach that benefits from both point and line features. A calibrated stereo set of video cameras is used to collect data. Point and line features are then detected and matched across video frames. Finally, the 3D structure of the scene is recovered by finding 3D coordinates of the matched features. The proposed approach has been tested on realistic outdoor environments and preliminary results indicate its capability to deal with a variety of scenes.

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Compared with construction data sources that are usually stored and analyzed in spreadsheets and single data tables, data sources with more complicated structures, such as text documents, site images, web pages, and project schedules have been less intensively studied due to additional challenges in data preparation, representation, and analysis. In this paper, our definition and vision for advanced data analysis addressing such challenges are presented, together with related research results from previous work, as well as our recent developments of data analysis on text-based, image-based, web-based, and network-based construction sources. It is shown in this paper that particular data preparation, representation, and analysis operations should be identified, and integrated with careful problem investigations and scientific validation measures in order to provide general frameworks in support of information search and knowledge discovery from such information-abundant data sources.

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A series of flames in a turbulent methane/air stratified swirl burner is presented. The degree of stratification and swirl are systematically varied to generate a matrix of experimental conditions, allowing their separate and combined effects to be investigated. Non-swirling flows are considered in the present paper, and the effects of swirl are considered in a companion paper (Part II). A mean equivalence ratio of φ=0.75 is used, with φ for the highest level of stratification spanning 0.375-1.125. The burner features a central bluff-body to aid flame stabilization, and the influence of the induced recirculation zone is also considered. The current work focuses on non-swirling flows where two-component particle image velocimetry (PIV) measurements are sufficient to characterize the main features of the flow field. Scalar data obtained from Rayleigh/Raman/CO laser induced fluorescence (CO-LIF) line measurements at 103μm resolution allow the behavior of key combustion species-CH 4, CO 2, CO, H 2, H 2O and O 2-to be probed within the instantaneous flame front. Simultaneous cross-planar OH-PLIF is used to determine the orientation of the instantaneous flame normal in the scalar measurement window, allowing gradients in temperature and progress variable to be angle corrected to their three dimensional values. The relationship between curvature and flame thickness is investigated using the OH-PLIF images, as well as the effect of stratification on curvature.The main findings are that the behavior of the key combustion species in temperature space is well captured on the mean by laminar flame calculations regardless of the level of stratification. H 2 and CO are significant exceptions, both appearing at elevated levels in the stratified flames. Values for surface density function and by extension thermal scalar dissipation rate are found to be substantially lower than laminar values, as the thickening of the flame due to turbulence dominates the effect of increased strain. These findings hold for both premixed and stratified flames. The current series of flames is proposed as an interesting if challenging set of test cases for existing and emerging turbulent flame models, and data are available on request. © 2012 The Combustion Institute.

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Experimental results are presented from a series of turbulent methane/air stratified flames stabilized on a swirl burner. Nine operating conditions are considered, systematically varying the level of stratification and swirl while maintaining a lean global mean equivalence ratio of φ̄=0.75. Scalar data are obtained from Rayleigh/Raman/CO laser induced fluorescence (CO-LIF) line measurements at 103μm resolution, allowing the behavior of the major combustion species-CH 4, CO 2, CO, H 2, H 2O and O 2-to be probed within the instantaneous flame front. The corresponding three-dimensional surface density function and thermal scalar dissipation rate are investigated, along with geometric characteristics of the flame such as curvature and flame thickness. Hydrogen and carbon monoxide levels within the flame brush are raised by stratification, indicating models with laminar premixed flame chemistry may not be suitable for stratified flames. However, flame surface density, scalar dissipation and curvature all appear insensitive to the degree of stratification in the flames surveyed. © 2012 The Combustion Institute.

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Measurements consisting of γ-ray excitation functions and angular distributions were performed using the (n,n′γ) reaction on Ni62. The excitation function data allowed us to check the consistency of the placement of transitions in the level scheme. From γ-ray angular distributions, the lifetimes of levels up to ~3.8 MeV in excitation energy were extracted with the Doppler-shift attenuation method. The experimentally deduced values of reduced transition probabilities were compared with the predictions of the quadrupole vibrator model and with large-scale shell model calculations in the fp shell configuration space. Two-phonon states were found to exist with some notable deviation from the predictions of the quadrupole vibrator model, but no evidence for the existence of three-phonon states could be established. Z=28 proton core excitations played a major role in understanding the observed structure. © 2011 American Physical Society.