6,813 research outputs found

    Why genes evolve faster on secondary chromosomes in bacteria

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    In bacterial genomes composed of more than one chromosome, one replicon is typically larger, harbors more essential genes than the others, and is considered primary. The greater variability of secondary chromosomes among related taxa has led to the theory that they serve as an accessory genome for specific niches or conditions. By this rationale, purifying selection should be weaker on genes on secondary chromosomes because of their reduced necessity or usage. To test this hypothesis we selected bacterial genomes composed of multiple chromosomes from two genera, Burkholderia and Vibrio, and quantified the evolutionary rates (dN and dS) of all orthologs within each genus. Both evolutionary rate parameters were faster among orthologs found on secondary chromosomes than those on the primary chromosome. Further, in every bacterial genome with multiple chromosomes that we studied, genes on secondary chromosomes exhibited significantly weaker codon usage bias than those on primary chromosomes. Faster evolution and reduced codon bias could in turn result from global effects of chromosome position, as genes on secondary chromosomes experience reduced dosage and expression due to their delayed replication, or selection on specific gene attributes. These alternatives were evaluated using orthologs common to genomes with multiple chromosomes and genomes with single chromosomes. Analysis of these ortholog sets suggested that inherently fast-evolving genes tend to be sorted to secondary chromosomes when they arise; however, prolonged evolution on a secondary chromosome further accelerated substitution rates. In summary, secondary chromosomes in bacteria are evolutionary test beds where genes are weakly preserved and evolve more rapidly, likely because they are used less frequently

    Land Grant Application- Cunningham, Samuel (Newcastle)

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    Land grant application submitted to the Maine Land Office on behalf of Samuel Cunningham for service in the Revolutionary War, by their widow Sarah.https://digitalmaine.com/revolutionary_war_me_land_office/1225/thumbnail.jp

    Repeatability and degree of territorial aggression differs among urban and rural great tits (<i>Parus major</i>)

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    Animals in urban habitats face many novel selection pressures such as increased human population densities and human disturbance. This is predicted to favour bolder and more aggressive individuals together with greater flexibility in behaviour. Previous work has focussed primarily on studying these traits in captive birds and has shown increased aggression and reduced consistency between traits (behavioural syndromes) in birds from urban populations. However, personality (consistency within a behavioural trait) has not been well studied in the wild. Here we tested whether urban free-living male great tits show greater territorial aggression than rural counterparts. We also tested predictions that both behavioural syndromes and personality would show lower consistency in urban populations. We found that urban populations were more aggressive than rural populations and urban birds appeared to show lower levels of individual behavioural repeatability (personality) as predicted. However, we found no effect of urbanisation on behavioural syndromes (correlations between multiple behavioural traits). Our results indicate that urban environments may favour individuals which exhibit increased territorial aggression and greater within-trait flexibility which may be essential to success in holding urban territories. Determining how urban environments impact key fitness traits will be important in predicting how animals cope with ongoing urbanisationpublishersversionPeer reviewe

    Causes of Conflict in Organizations: A Case of Takoradi Polytechnic

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    The study explored the various causes of conflicts in organizations. The objectives of the study was to find out the nature, types and factors that lead to staff related conflicts in organizations especially tertiary educational institutions. To achieve the objectives, researchers employed the case study approach using Takoradi Polytechnic as the case study. It also involved the use of interview and questionnaire as the data collection instruments for the study. Researchers used the purposive and simple random sampling techniques to select the respondents. A sample size of 276 out of 736 of the population was selected for the study. This constitutes (36%) of the population. The sample was made up of 109 junior staff, 96 senior staff and 71 senior members. These three groups of staff from different departments were randomly and purposively invited to participate in the study. The study would be of immense benefit to management of institutions especially educational institutions since it would inform them of possible conflict that could arise. It would also inform policy formulation and staff training and development programs. It was discovered after the study that there were various conflicts in the organization which could be grouped into intra-personal, interpersonal and inter-group conflicts. These were as a result of the competing for limited resources, power struggle, differences in behavior among others. It recommends the education of staff through workshops and seminars on the differences that leads to conflicts, provision of resources and infrastructure that could mitigate the competition of resources among others

    Sub-cortical brain structure segmentation using F-CNN's

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    In this paper we propose a deep learning approach for segmenting sub-cortical structures of the human brain in Magnetic Resonance (MR) image data. We draw inspiration from a state-of-the-art Fully-Convolutional Neural Network (F-CNN) architecture for semantic segmentation of objects in natural images, and adapt it to our task. Unlike previous CNN-based methods that operate on image patches, our model is applied on a full blown 2D image, without any alignment or registration steps at testing time. We further improve segmentation results by interpreting the CNN output as potentials of a Markov Random Field (MRF), whose topology corresponds to a volumetric grid. Alpha-expansion is used to perform approximate inference imposing spatial volumetric homogeneity to the CNN priors. We compare the performance of the proposed pipeline with a similar system using Random Forest-based priors, as well as state-of-art segmentation algorithms, and show promising results on two different brain MRI datasets.Comment: ISBI 2016: International Symposium on Biomedical Imaging, Apr 2016, Prague, Czech Republi

    LASR-Guided Stellar Photometric Variability Subtraction: The Linear Algorithm For Significance Reduction

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    We develop a technique for removing stellar variability in the light curves of δ\delta-Scuti and similar stars. Our technique, which we name the Linear Algorithm for Significance Reduction (LASR), subtracts oscillations from a time series by minimizing their statistical significance in frequency space. We demonstrate that LASR can subtract variable signals of near-arbitrary complexity and can robustly handle close frequency pairs and overtone frequencies. We demonstrate that our algorithm performs an equivalent fit as prewhitening to the straightforward variable signal of KIC 9700322. We also show that LASR provides a better fit to seismic activity than prewhitening in the case of the complex δ\delta-Scuti KOI-976.Comment: 9 pages, 5 figures, accepted for publication in Astronomy & Astrophysics. Pseudocode and github link to code included in manuscrip
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