32 research outputs found

    Older workers in the hospitality industry: valuing experience and informal learning

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    The research sets out to identify the learning processes adopted by older workers in the hospitality and visitor attraction industry in Scotland, with a view to determining how employers may better support their education and training within enterprises. The study was undertaken as part of the ESRC project on ‘sustaining the employability of older workers in the hospitality sector: personal learning strategies and cultures of learning. The data collection period was from 2008-2010 and focused on six case studies; three in hospitality and three visitor attraction centres. The conceptual framework of the research is based upon the simple yet important notion of experience and how this enhances the learning lives of older employees. It will be argued that the learning processes used by older employees are primarily recognisable as social practices, based upon the utilisation of existing knowledge and skills. The analysis suggests that organisations should be encouraged to avoid using a ‘one size fits all’ approach to education and training and, in the case of older workers, to make more use of their past work and life experiences in order to facilitate their own and others’ learning

    Evaluation of Three Automated Genome Annotations for Halorhabdus utahensis

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    Genome annotations are accumulating rapidly and depend heavily on automated annotation systems. Many genome centers offer annotation systems but no one has compared their output in a systematic way to determine accuracy and inherent errors. Errors in the annotations are routinely deposited in databases such as NCBI and used to validate subsequent annotation errors. We submitted the genome sequence of halophilic archaeon Halorhabdus utahensis to be analyzed by three genome annotation services. We have examined the output from each service in a variety of ways in order to compare the methodology and effectiveness of the annotations, as well as to explore the genes, pathways, and physiology of the previously unannotated genome. The annotation services differ considerably in gene calls, features, and ease of use. We had to manually identify the origin of replication and the species-specific consensus ribosome-binding site. Additionally, we conducted laboratory experiments to test H. utahensis growth and enzyme activity. Current annotation practices need to improve in order to more accurately reflect a genome's biological potential. We make specific recommendations that could improve the quality of microbial annotation projects

    Venn diagrams of gene predictions.

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    <p>(A) The diagram to the left shows the number of predicted protein coding genes that share stop sites with the other annotations. Overlapping regions indicate genes having same stop site between annotations. (B) The diagram to the right shows the number of predicted protein coding genes that share start site and stop site with the other annotations. Overlapping regions indicate genes having exact matches between annotations.</p

    Glycolysis/gluconeogenesis pathway.

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    <p>Diagram based on RAST's KEGG pathway map displays present and absent enzymes for <i>H. utahensis</i>. Green boxes indicate that the enzyme was predicted by RAST and displayed in the KEGG map. Yellow boxes designate enzymes that were called by RAST but had not been added to the KEGG map. Red boxes mark enzymes that were listed as absent and could not be located in the <i>H. utahensis</i> genome.</p

    <i>H. utahensis</i> primary contig and ORC/Cdc6 genes.

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    <p>Circular display of the largest contig of the <i>H. utahensis</i> genome sequence. The contig begins at the top and wraps clockwise. The red bars illustrate the location of ORC/Cdc6 orthologs. The ORC/Cdc6 gene numbered 3 lies near the origin of replication, at 2,327,225 base pairs.</p

    Comparison of rRNA calls.

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    <p>Review of predicted coding regions for ribosomal RNA for each annotation service shows that IMG and RAST have identical calls, while JCVI fails to call 23s rRNA and predicts different start and stop sites.</p

    Potential comparison tool.

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    <p>Hypothetical comparison of start sites from multiple annotations, combined with species-specific RBS data. Start #2 would be the most likely start codon based on RBS spacing.</p

    Comparison of putative glycoside hydrolase start sites.

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    <p>Examination of an individual gene displays tendencies of the annotation services. RAST identifies GTG as the start codon for the gene, while IMG and JCVI select two ATG codons at different locations. Predicted start codon affects gene length.</p
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