A close phylogenetic relationship between Sipuncula and Annelida evidenced from the complete mitochondrial genome sequence of Phascolosoma esculenta

Background: There are many advantages to the application of complete mitochondrial (mt) genomes in the accurate reconstruction of phylogenetic relationships in Metazoa. Although over one thousand metazoan genomes have been sequenced, the taxonomic sampling is highly biased, left with many phyla without a single representative of complete mitochondrial genome. Sipuncula (peanut worms or star worms) is a small taxon of worm-like marine organisms with an uncertain phylogenetic position. In this report, we present the mitochondrial genome sequence of Phascolosoma esculenta, the first complete mitochondrial genome of the phylum. Results: The mitochondrial genome of P. esculenta is 15,494 bp in length. The coding strand consists of 32.1% A, 21.5% C, 13.0% G, and 33.4% T bases (AT = 65.5%; AT skew = -0.019; GC skew = -0.248). It contains thirteen protein-coding genes (PCGs) with 3,709 codons in total, twenty-two transfer RNA genes, two ribosomal RNA genes and a non-coding AT-rich region (AT = 74.2%). All of the 37 identified genes are transcribed from the same DNA strand. Compared with the typical set of metazoan mt genomes, sipunculid lacks trnR but has an additional trnM. Maximum Likelihood and Bayesian analyses of the protein sequences show that Myzostomida, Sipuncula and Annelida (including echiurans and pogonophorans) form a monophyletic group, which supports a closer relationship between Sipuncula and Annelida than with Mollusca, Brachiopoda, and some other lophotrochozoan groups. Conclusion: This is the first report of a complete mitochondrial genome as a representative within the phylum Sipuncula. It shares many more similar features with the four known annelid and one echiuran mtDNAs. Firstly, sipunculans and annelids share quite similar gene order in the mitochondrial genome, with all 37 genes located on the same strand; secondly, phylogenetic analyses based on the concatenated protein sequences also strongly support the sipunculan + annelid clade (including echiurans and pogonophorans). Hence annelid "key-characters" including segmentation may be more labile than previously assumed.

The complete mitochondrial genome of the ridgetail white prawn Exopalaemon carinicauda Holthuis, 1950 (Crustacean: Decapoda: Palaemonidae) revealed a novel rearrangement of tRNA genes

The complete mitochondrial (mt) DNA sequence was determined for a ridgetail white prawn, Exopalaemon carinicauda Holthuis, 1950 (Crustacea: Decopoda: Palaemonidae). The mt genome is 15,730 bp in length, encoding a standard set of 13 protein-coding genes, 2 ribosomal RNA genes, and 22 transfer RNA genes, which is typical for metazoans. The majority-strand consists of 33.6% A, 23.0% C, 13.4% G, and 30.0% T bases (AT skew = 0.057: GC skew = -0.264). A total of 1045 bp of non-coding nucleotides were observed in 16 intergenic regions,,including a major A+ T rich (79.7%) noncoding region (886 bp). A novel translocation of tRNA(Pro) and tRNA(Thr) was found when comparing this genome with the pancrustacean ground pattern indicating that gene order is not conserved among caridean mitochondria. Furthermore, the rate of Ka/Ks in 13 protein-coding genes between three caridean species is Much less than 1, which indicates a strong Purifying selection within this group. To investigate the phylogenetic relationship within Malacostraca, phylogenetic trees based oil Currently available malacostracan complete mitochondrial sequences were built with the maximum likelihood and Bayesian models. All analyses based oil nucleotide and amino acid data strongly support the monophyly of Decapoda. The Penaeidae, Reptantia, Caridea, and Meiura clades were also recovered as monophyletic groups with Strong Statistical Support. However, the phylogenetic relationships within Pleocyemata are unstable, as represented by the inclusion or exclusion of Caridea. (C) 2009 Elsevier B.V. All rights reserved.

Cellular automata: Simulating alpine tundra vegetation dynamics in response to global warming

This study attempts to model alpine tundra vegetation dynamics in a tundra region in the Qinghai Province of China in response to global warming. We used Raster-based cellular automata and a Geographic Information System to study the spatial and temporal vegetation dynamics. The cellular automata model is implemented with IDRISI's Multi-Criteria Evaluation functionality to simulate the spatial patterns of vegetation change assuming certain scenarios of global mean temperature increase over time. The Vegetation Dynamic Simulation Model calculates a probability surface for each vegetation type, and then combines all vegetation types into a composite map, determined by the maximum likelihood that each vegetation type should distribute to each raster unit. With scenarios of global temperature increase of I to 3 degrees C, the vegetation types such as Dry Kobresia Meadow and Dry Potentilla Shrub that are adapted to warm and dry conditions tend to become more dominant in the study area.

Molecular evidence for double maternal origins of the diploid hybrid Hippophae goniocarpa (Elaeagnaceae)

Homoploid hybrid plant species are rare, and the mechanisms of their speciation are largely unknown, especially for homoploid hybrid tree species. Two contrasting hypotheses have been proposed to explain the origin of Hippophae goniocarpa: (1) it is a diploid hybrid originating from H. rhamnoides ssp. sinensis x H. neurocarpa ssp. neurocarpa, and (2) it originated via marginal differentiation from H. rhamnoides ssp. sinensis. Regardless of which of these hypotheses is true (if either), previous studies have suggested that H. rhamnoides ssp. sinensis is the only maternal donor for this hybrid species. In this study, we aim to elucidate the maternal composition of H. goniocarpa and to test the two hypotheses. For this purpose, we sequenced the maternal chloroplast DNA trnL-F region of 75 individuals representing H. goniocarpa, H. rhamnoides ssp. sinensis, and H. neurocarpa ssp. neurocarpa in two co-occurring sites of the taxa. Seven haplotypes were identified from three taxonomic units, and their phylogenetic relationships were further constructed by means of maximum parsimony, maximum likelihood, and network analyses. These seven haplotypes clustered into two distinct, highly divergent lineages. Two haplotypes from one lineage were found in H. rhamnoides ssp. sinensis, and five (representing the other lineage) in H. neurocarpa ssp. neurocarpa. Hippophae goniocarpa shared four common haplotypes from both lineages, but the haplotypes detected from the two populations differed to some extent, and in each case were identical to local haplotypes of the putative parental species. Thus, both H. rhamnoides ssp. sinensis and H. neurocarpa ssp. neurocarpa appear to have together contributed to the maternal establishment of H. goniocarpa. These results clearly demonstrate that the marginal origin hypothesis should be rejected, and support the hybrid origin hypothesis. Hippophae goniocarpa exhibits a sympatric distribution with its two parent species, without occupying new niches or displaying complete ecological isolation. However, this species has effectively developed reproductive isolation from its sympatric parent species. Our preliminary results suggest that H. goniocarpa may provide a useful model system for studying diploid hybrid speciation in trees. (c) 2008 The Linnean Society of London.

Phylogenetic origins of the Himalayan endemic Dolomiaea, Diplazoptilon and Xanthopappus (Asteraceae : Cardueae) based on three DNA regions

Background and Aims It is an enduring question as to the mechanisms leading to the high diversity and the processes producing endemics with unusual morphologies in the Himalayan alpine region. In the present study, the phylogenetic relationships and origins of three such endemic genera were analysed, Dolomiaea, Diplazoptilon and Xanthopappus, all in the tribe Cardueae of Asteraceae.Methods The nuclear rDNA internal transcribed spacer (ITS) and plastid trnL-F and psbA-trnH regions of these three genera were sequenced. The same regions for other related genera in Cardueae were also sequenced or downloaded from GenBank. Phylogenetic trees were constructed from individual and combined data sets of the three types of sequences using maximum parsimony, maximum likelihood and Bayesian analyses.Key Results The phylogenetic tree obtained allowed earlier hypotheses concerning the relationships of these three endemic genera based on gross morphology to be rejected. Frolovia and Saussurea costus were deeply nested within Dolomiaea, and the strong statistical support for the Dolomiaea-Frolovia clade suggested that circumscription of Dolomiaea should be more broadly redefined. Diplazoptilon was resolved as sister to Himalaiella, and these two together are sister to Lipschitziella. The clade comprising these three genera is sister to Jurinea, and together these four genera are sister to the Dolomiaea-Frolovia clade. Xanthopappus, previously hypothesized to be closely related to Carduus, was found to be nested within a well-supported but not fully resolved Onopordum group with Alfredia, Ancathia, Lamyropappus, Olgaea, Synurus and Syreitschikovia, rather than the Cardinis group. The crude dating based on ITS sequence divergence revealed that the divergence time of Dolomiaea-Frolovia from its sister group probably occurred 13.6-12.2 million years ago (Ma), and the divergence times of the other two genera, Xanthopappus and Diplazoptilon, from their close relatives around 5.7-4.7 Ma and 2.0-1.6 Ma, respectively.Conclusions The findings provide an improved understanding of the intergeneric relationships in Cardueae. The crude calibration of lineages indicates that the uplifts of the Qiinghai -Tibetan Plateau since the Miocene might have served as a continuous stimulus for the production of these morphologically aberrant endemic elements of the Himalayan flora.

Mitochondrial DNA phylogeny of two morphologically enigmatic fishes in the subfamily Schizothoracinae (Teleostei : Cyprinidae) in the Qinghai-Tibetan Plateau

The complete mitochondrial DNA (mtDNA) cytochrome b gene (1140 bp) was sequenced in Herzenstein macrocephalus and Gymnocypris namensis and in 13 other species and sub-species (n = 22), representing four closely related genera in the subfamily Schizothoracinae. Conflicting taxonomies of H. macrocephalus and G. namensis have been proposed because of the character instability among individuals. Parsimony, maximum likelihood and Bayesian methods produced phylogenetic trees with the same topology and resolved several distinctive clades. Previous taxonomic treatments, which variously placed these two species of separate genera or as sub-species, are inconsistent with the mtDNA phylogeny. Both H. macrocephalus and G. namensis appear in a well-supported clade, which also includes nine species of Schizopygopsis, and hence should be transferred to the genus Schizopygopsis. Morphological changes are further illustrated, and their adaptive evolution in response to the local habitat shifts during the speciation process appears to be responsible for conflicting views on the systematics of these two species and hence the contrasting taxonomic treatments. These species are endemic to the Qinghai-Tibetan Plateau, a region with a history of geological activity and a rich diversity of habitats that may have result in the parallel and reversal evolution of some morphological characters used in their taxonomies. Our results further suggest that speciation and morphological evolution of fishes in this region may be more complex than those previously expected. (c) 2007 The Authors Journal compilation (c) 2007 The Fisheries Society of the British Isles.

交通监控系统中运动目标分类和跟踪研究

文章讲述了交通监控系统中应用视频图像流来跟踪运动目标并对目标进行分类的具体过程和原则.基于目标检测提出了双差分的目标检测算法,目标分类应用到了连续时间限制和最大可能性估计的原则,目标跟踪则结合检测到的运动目标图像和当前模板进行相关匹配.实验结果表明,该过程能够很好地探测和分类目标,去除背景信息的干扰,并能够在运动目标部分被遮挡、外观改变和运动停止等情况下连续地跟踪目标.

超参数控制下的波阻抗约束反演

The seismic survey is the most effective geophysical method during exploration and development of oil/gas. As a main means in processing and interpreting seismic data, impedance inversion takes up a special position in seismic survey. This is because the impedance parameter is a ligament which connects seismic data with well-logging and geological information, while it is also essential in predicting reservoir properties and sand-body. In fact, the result of traditional impedance inversion is not ideal. This is because the mathematical inverse problem of impedance is poor-pose so that the inverse result has instability and multi-result, so it is necessary to introduce regularization. Most simple regularizations are presented in existent literature, there is a premise that the image(or model) is globally smooth. In fact, as an actual geological model, it not only has made of smooth region but also be separated by the obvious edge, the edge is very important attribute of geological model. It's difficult to preserve these characteristics of the model and to avoid an edge too smooth to clear. Thereby, in this paper, we propose a impedance inverse method controlled by hyperparameters with edge-preserving regularization, the inverse convergence speed and result would be improved. In order to preserve the edge, the potential function of regularization should satisfy nine conditions such as basic assumptions edge preservation and convergence assumptions etc. Eventually, a model with clear background and edge-abnormity can be acquired. The several potential functions and the corresponding weight functions are presented in this paper. The potential functionφLφHL andφGM can meet the need of inverse precision by calculating the models. For the local constant planar and quadric models, we respectively present the neighborhood system of Markov random field corresponding to the regularization term. We linearity nonlinear regularization by using half-quadratic regularization, it not only preserve the edge, and but also simplify the inversion, and can use some linear methods. We introduced two regularization parameters (or hyperparameters) λ2 and δ in the regularization term. λ2 is used to balance the influence between the data term and the transcendental term; δ is a calibrating parameter used to adjust the gradient value at the discontinuous position(or formation interface). Meanwhile, in the inverse procedure, it is important to select the initial value of hyperparameters and to change hyperparameters, these will then have influence on convergence speed and inverse effect. In this paper, we roughly give the initial value of hyperparameters by using a trend- curve of φ-(λ2, δ) and by a method of calculating the upper limit value of hyperparameters. At one time, we change hyperparameters by using a certain coefficient or Maximum Likelihood method, this can be simultaneously fulfilled with the inverse procedure. Actually, we used the Fast Simulated Annealing algorithm in the inverse procedure. This method overcame restrictions from the local extremum without depending on the initial value, and got a global optimal result. Meanwhile, we expound in detail the convergence condition of FSA, the metropolis receiving probability form Metropolis-Hasting, the thermal procession based on the Gibbs sample and other methods integrated with FSA. These content can help us to understand and improve FSA. Through calculating in the theoretic model and applying it to the field data, it is proved that the impedance inverse method in this paper has the advantage of high precision practicability and obvious effect.

Models of Noise and Robust Estimates

Given n noisy observations g; of the same quantity f, it is common use to give an estimate of f by minimizing the function Eni=1(gi-f)2. From a statistical point of view this corresponds to computing the Maximum likelihood estimate, under the assumption of Gaussian noise. However, it is well known that this choice leads to results that are very sensitive to the presence of outliers in the data. For this reason it has been proposed to minimize the functions of the form Eni=1V(gi-f), where V is a function that increases less rapidly than the square. Several choices for V have been proposed and successfully used to obtain "robust" estimates. In this paper we show that, for a class of functions V, using these robust estimators corresponds to assuming that data are corrupted by Gaussian noise whose variance fluctuates according to some given probability distribution, that uniquely determines the shape of V.

Convergence Results for the EM Approach to Mixtures of Experts Architectures

The Expectation-Maximization (EM) algorithm is an iterative approach to maximum likelihood parameter estimation. Jordan and Jacobs (1993) recently proposed an EM algorithm for the mixture of experts architecture of Jacobs, Jordan, Nowlan and Hinton (1991) and the hierarchical mixture of experts architecture of Jordan and Jacobs (1992). They showed empirically that the EM algorithm for these architectures yields significantly faster convergence than gradient ascent. In the current paper we provide a theoretical analysis of this algorithm. We show that the algorithm can be regarded as a variable metric algorithm with its searching direction having a positive projection on the gradient of the log likelihood. We also analyze the convergence of the algorithm and provide an explicit expression for the convergence rate. In addition, we describe an acceleration technique that yields a significant speedup in simulation experiments.

On the Dirichlet Prior and Bayesian Regularization

A common objective in learning a model from data is to recover its network structure, while the model parameters are of minor interest. For example, we may wish to recover regulatory networks from high-throughput data sources. In this paper we examine how Bayesian regularization using a Dirichlet prior over the model parameters affects the learned model structure in a domain with discrete variables. Surprisingly, a weak prior in the sense of smaller equivalent sample size leads to a strong regularization of the model structure (sparse graph) given a sufficiently large data set. In particular, the empty graph is obtained in the limit of a vanishing strength of prior belief. This is diametrically opposite to what one may expect in this limit, namely the complete graph from an (unregularized) maximum likelihood estimate. Since the prior affects the parameters as expected, the prior strength balances a "trade-off" between regularizing the parameters or the structure of the model. We demonstrate the benefits of optimizing this trade-off in the sense of predictive accuracy.

Virtual Visual Hulls: Example-Based 3D Shape Estimation from a Single Silhouette

Recovering a volumetric model of a person, car, or other object of interest from a single snapshot would be useful for many computer graphics applications. 3D model estimation in general is hard, and currently requires active sensors, multiple views, or integration over time. For a known object class, however, 3D shape can be successfully inferred from a single snapshot. We present a method for generating a ``virtual visual hull''-- an estimate of the 3D shape of an object from a known class, given a single silhouette observed from an unknown viewpoint. For a given class, a large database of multi-view silhouette examples from calibrated, though possibly varied, camera rigs are collected. To infer a novel single view input silhouette's virtual visual hull, we search for 3D shapes in the database which are most consistent with the observed contour. The input is matched to component single views of the multi-view training examples. A set of viewpoint-aligned virtual views are generated from the visual hulls corresponding to these examples. The 3D shape estimate for the input is then found by interpolating between the contours of these aligned views. When the underlying shape is ambiguous given a single view silhouette, we produce multiple visual hull hypotheses; if a sequence of input images is available, a dynamic programming approach is applied to find the maximum likelihood path through the feasible hypotheses over time. We show results of our algorithm on real and synthetic images of people.

Optymalizacja metod analizy Főrsterowskiego rezonansowego przeniesienia energii (FRET) pojedynczych cząsteczek

Wydział Chemii: Zakład Chemii Fizycznej

Skin Color-Based Video Segmentation under Time-Varying Illumination

A novel approach for real-time skin segmentation in video sequences is described. The approach enables reliable skin segmentation despite wide variation in illumination during tracking. An explicit second order Markov model is used to predict evolution of the skin-color (HSV) histogram over time. Histograms are dynamically updated based on feedback from the current segmentation and predictions of the Markov model. The evolution of the skin-color distribution at each frame is parameterized by translation, scaling and rotation in color space. Consequent changes in geometric parameterization of the distribution are propagated by warping and resampling the histogram. The parameters of the discrete-time dynamic Markov model are estimated using Maximum Likelihood Estimation, and also evolve over time. The accuracy of the new dynamic skin color segmentation algorithm is compared to that obtained via a static color model. Segmentation accuracy is evaluated using labeled ground-truth video sequences taken from staged experiments and popular movies. An overall increase in segmentation accuracy of up to 24% is observed in 17 out of 21 test sequences. In all but one case the skin-color classification rates for our system were higher, with background classification rates comparable to those of the static segmentation.

How Well Can TCP Infer Network State?

The Transmission Control Protocol (TCP) has been the protocol of choice for many Internet applications requiring reliable connections. The design of TCP has been challenged by the extension of connections over wireless links. We ask a fundamental question: What is the basic predictive power of TCP of network state, including wireless error conditions? The goal is to improve or readily exploit this predictive power to enable TCP (or variants) to perform well in generalized network settings. To that end, we use Maximum Likelihood Ratio tests to evaluate TCP as a detector/estimator. We quantify how well network state can be estimated, given network response such as distributions of packet delays or TCP throughput that are conditioned on the type of packet loss. Using our model-based approach and extensive simulations, we demonstrate that congestion-induced losses and losses due to wireless transmission errors produce sufficiently different statistics upon which an efficient detector can be built; distributions of network loads can provide effective means for estimating packet loss type; and packet delay is a better signal of network state than short-term throughput. We demonstrate how estimation accuracy is influenced by different proportions of congestion versus wireless losses and penalties on incorrect estimation.