4,484 research outputs found

    Improved Algorithms for Approximate String Matching (Extended Abstract)

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    The problem of approximate string matching is important in many different areas such as computational biology, text processing and pattern recognition. A great effort has been made to design efficient algorithms addressing several variants of the problem, including comparison of two strings, approximate pattern identification in a string or calculation of the longest common subsequence that two strings share. We designed an output sensitive algorithm solving the edit distance problem between two strings of lengths n and m respectively in time O((s-|n-m|)min(m,n,s)+m+n) and linear space, where s is the edit distance between the two strings. This worst-case time bound sets the quadratic factor of the algorithm independent of the longest string length and improves existing theoretical bounds for this problem. The implementation of our algorithm excels also in practice, especially in cases where the two strings compared differ significantly in length. Source code of our algorithm is available at http://www.cs.miami.edu/\~dimitris/edit_distanceComment: 10 page


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    Both product design and manufacturing are intrinsically collaborative processes. From conception and design to project completion and ongoing maintenance, all points in the lifecycle of any product involve the work of fluctuating teams of designers, suppliers and customers. That is why companies are involved in the creation of a distributed design and a manufacturing environment which could provide an effective way to communicate and share information throughout the entire enterprise and the supply chain. At present, the technologies that support such a strategy are based on World Wide Web platforms and follow two different paths. The first one focuses on 2D documentation improvement and introduces 3D interactive information in order to add knowledge to drawings. The second one works directly on 3D models and tries to extend the life of 3D data moving these design information downstream through the entire product lifecycle. Unfortunately the actual lack of a unique 3D Web-based standard has stimulated the growing up of many different proprietary and open source standards and, as a consequence, a production of an incompatible information exchange over the WEB. This paper proposes a structured analysis of Web-based solutions, trying to identify the most critical aspects to promote a unique 3D digital standard model capable of sharing product and manufacturing data more effectively—regardless of geographic boundaries, data structures, processes or computing environmen

    Tissue classification for laparoscopic image understanding based on multispectral texture analysis.

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    Intraoperative tissue classification is one of the prerequisites for providing context-aware visualization in computer-assisted minimally invasive surgeries. As many anatomical structures are difficult to differentiate in conventional RGB medical images, we propose a classification method based on multispectral image patches. In a comprehensive ex vivo study through statistical analysis, we show that (1) multispectral imaging data are superior to RGB data for organ tissue classification when used in conjunction with widely applied feature descriptors and (2) combining the tissue texture with the reflectance spectrum improves the classification performance. The classifier reaches an accuracy of 98.4% on our dataset. Multispectral tissue analysis could thus evolve as a key enabling technique in computer-assisted laparoscopy

    Asymmetry to symmetry transition of Fano line-shape: Analytical derivation

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    An analytical derivation of Fano line-shape asymmetry ratio has been presented here for a general case. It is shown that Fano line-shape becomes less asymmetric as \q is increased and finally becomes completely symmetric in the limiting condition of q equal to infinity. Asymmetry ratios of Fano line-shapes have been calculated and are found to be in good consonance with the reported expressions for asymmetry ratio as a function of Fano parameter. Application of this derivation is also mentioned for explanation of asymmetry to symmetry transition of Fano line-shape in quantum confined silicon nanostructures.Comment: 3 figures, Latex files, Theoretica

    Evolutionary connectionism: algorithmic principles underlying the evolution of biological organisation in evo-devo, evo-eco and evolutionary transitions

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    The mechanisms of variation, selection and inheritance, on which evolution by natural selection depends, are not fixed over evolutionary time. Current evolutionary biology is increasingly focussed on understanding how the evolution of developmental organisations modifies the distribution of phenotypic variation, the evolution of ecological relationships modifies the selective environment, and the evolution of reproductive relationships modifies the heritability of the evolutionary unit. The major transitions in evolution, in particular, involve radical changes in developmental, ecological and reproductive organisations that instantiate variation, selection and inheritance at a higher level of biological organisation. However, current evolutionary theory is poorly equipped to describe how these organisations change over evolutionary time and especially how that results in adaptive complexes at successive scales of organisation (the key problem is that evolution is self-referential, i.e. the products of evolution change the parameters of the evolutionary process). Here we first reinterpret the central open questions in these domains from a perspective that emphasises the common underlying themes. We then synthesise the findings from a developing body of work that is building a new theoretical approach to these questions by converting well-understood theory and results from models of cognitive learning. Specifically, connectionist models of memory and learning demonstrate how simple incremental mechanisms, adjusting the relationships between individually-simple components, can produce organisations that exhibit complex system-level behaviours and improve the adaptive capabilities of the system. We use the term “evolutionary connectionism” to recognise that, by functionally equivalent processes, natural selection acting on the relationships within and between evolutionary entities can result in organisations that produce complex system-level behaviours in evolutionary systems and modify the adaptive capabilities of natural selection over time. We review the evidence supporting the functional equivalences between the domains of learning and of evolution, and discuss the potential for this to resolve conceptual problems in our understanding of the evolution of developmental, ecological and reproductive organisations and, in particular, the major evolutionary transitions

    Data-driven elicitation of quality requirements in agile companies

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    Quality Requirements (QRs) are a key artifact to ensure the quality and success of a software system. Despite its importance, QRs have not reached the same degree of attention as its functional counterparts, especially in the context of trending software development methodologies like Agile Software Development (ASD). Moreover, crucial information that can be obtained from data sources of a project under development (e.g. JIRA, github,…) are not fully exploited, or even neglected, in QR elicitation activities. In this work, we present a data-driven approach to semi-automatically generate and document QRs in the context of ASD. We define an architecture focusing on the process and the artefacts involved. We validate and iterate on such architecture by conducting workshops in four companies of different size and profile. Finally, we present the implementation of such architecture, considering the feedback and outcomes of the conducted workshops.Peer ReviewedPostprint (author's final draft

    Dynamical Models in Quantitative Genetics

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    In this paper the author investigates models in quantitative genetics and shows that under quite reasonable assumptions the dynamics can display rather counter-intuitive behavior. This research was conducted as part of the Dynamics of Macrosystems Feasibility Study in the System and Decision Sciences Program

    Wind from the black-hole accretion disk driving a molecular outflow in an active galaxy

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    Powerful winds driven by active galactic nuclei (AGN) are often invoked to play a fundamental role in the evolution of both supermassive black holes (SMBHs) and their host galaxies, quenching star formation and explaining the tight SMBH-galaxy relations. Recent observations of large-scale molecular outflows in ultra-luminous infrared galaxies (ULIRGs) have provided the evidence to support these studies, as they directly trace the gas out of which stars form. Theoretical models suggest an origin of these outflows as energy-conserving flows driven by fast AGN accretion disk winds. Previous claims of a connection between large-scale molecular outflows and AGN activity in ULIRGs were incomplete because they were lacking the detection of the putative inner wind. Conversely, studies of powerful AGN accretion disk winds to date have focused only on X-ray observations of local Seyferts and a few higher redshift quasars. Here we show the clear detection of a powerful AGN accretion disk wind with a mildly relativistic velocity of 0.25c in the X-ray spectrum of IRAS F11119+3257, a nearby (z = 0.189) optically classified type 1 ULIRG hosting a powerful molecular outflow. The AGN is responsible for ~80% of the emission, with a quasar-like luminosity of L_AGN = 1.5x10^46 erg/s. The energetics of these winds are consistent with the energy-conserving mechanism, which is the basis of the quasar mode feedback in AGN lacking powerful radio jets.Comment: Revised file including the letter, methods and supplementary information. Published in the March 26th 2015 issue of Natur

    Regulatory control and the costs and benefits of biochemical noise

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    Experiments in recent years have vividly demonstrated that gene expression can be highly stochastic. How protein concentration fluctuations affect the growth rate of a population of cells, is, however, a wide open question. We present a mathematical model that makes it possible to quantify the effect of protein concentration fluctuations on the growth rate of a population of genetically identical cells. The model predicts that the population's growth rate depends on how the growth rate of a single cell varies with protein concentration, the variance of the protein concentration fluctuations, and the correlation time of these fluctuations. The model also predicts that when the average concentration of a protein is close to the value that maximizes the growth rate, fluctuations in its concentration always reduce the growth rate. However, when the average protein concentration deviates sufficiently from the optimal level, fluctuations can enhance the growth rate of the population, even when the growth rate of a cell depends linearly on the protein concentration. The model also shows that the ensemble or population average of a quantity, such as the average protein expression level or its variance, is in general not equal to its time average as obtained from tracing a single cell and its descendants. We apply our model to perform a cost-benefit analysis of gene regulatory control. Our analysis predicts that the optimal expression level of a gene regulatory protein is determined by the trade-off between the cost of synthesizing the regulatory protein and the benefit of minimizing the fluctuations in the expression of its target gene. We discuss possible experiments that could test our predictions.Comment: Revised manuscript;35 pages, 4 figures, REVTeX4; to appear in PLoS Computational Biolog

    The ansamycin antibiotic, rifamycin SV, inhibits BCL6 transcriptional repression and forms a complex with the BCL6-BTB/POZ domain

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    BCL6 is a transcriptional repressor that is over-expressed due to chromosomal translocations, or other abnormalities, in ~40% of diffuse large B-cell lymphoma. BCL6 interacts with co-repressor, SMRT, and this is essential for its role in lymphomas. Peptide or small molecule inhibitors, which prevent the association of SMRT with BCL6, inhibit transcriptional repression and cause apoptosis of lymphoma cells in vitro and in vivo. In order to discover compounds, which have the potential to be developed into BCL6 inhibitors, we screened a natural product library. The ansamycin antibiotic, rifamycin SV, inhibited BCL6 transcriptional repression and NMR spectroscopy confirmed a direct interaction between rifamycin SV and BCL6. To further determine the characteristics of compounds binding to BCL6-POZ we analyzed four other members of this family and showed that rifabutin, bound most strongly. An X-ray crystal structure of the rifabutin-BCL6 complex revealed that rifabutin occupies a partly non-polar pocket making interactions with tyrosine58, asparagine21 and arginine24 of the BCL6-POZ domain. Importantly these residues are also important for the interaction of BLC6 with SMRT. This work demonstrates a unique approach to developing a structure activity relationship for a compound that will form the basis of a therapeutically useful BCL6 inhibitor