318 research outputs found

    A Dynamic Knowledge Management Framework for the High Value Manufacturing Industry

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    Dynamic Knowledge Management (KM) is a combination of cultural and technological factors, including the cultural factors of people and their motivations, technological factors of content and infrastructure and, where these both come together, interface factors. In this paper a Dynamic KM framework is described in the context of employees being motivated to create profit for their company through product development in high value manufacturing. It is reported how the framework was discussed during a meeting of the collaborating company’s (BAE Systems) project stakeholders. Participants agreed the framework would have most benefit at the start of the product lifecycle before key decisions were made. The framework has been designed to support organisational learning and to reward employees that improve the position of the company in the market place

    Exploring the key drivers behind the adoption of mobile banking services

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    This research examines the main drivers behind the adoption of mobile banking, a concept that has revolutionized the day-to-day activities of humans. A review of relevant literature on the topic, leads us toward testing the following key hypotheses: consumers are adopting mobile banking due to the perceived usefulness and benefits associated with the concept; and consumers are adopting mobile banking due to technological advances meaning increased access to the mobile phone devices. We published an online questionnaire on Amazon Mechanical Turk to obtain responses from Internet users. A dominating proportion of participants highlighted how mobile banking is a concept that they adopted between three and 5 years ago, showing just how recently mobile banking took off. The results also showed a number of links between the study’s research hypotheses and the adoption of mobile banking. The overall result of the study shows online banking as a concept that is influenced by a number of both internal and external factors. No single factor plays a dominating force in pushing retail bankers to adopt mobile banking, with it instead being a culmination of numerous different factors. The recent introduction of mobile banking is made seemingly apparent, as is the increasing susceptibility to change in the near future. Subsequently, countless opportunities for further academic research are likely to arise

    Cross-platform expression profiling demonstrates that SV40 small tumor antigen activates Notch, Hedgehog, and Wnt signaling in human cells

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    BACKGROUND: We previously analyzed human embryonic kidney (HEK) cell lines for the effects that simian virus 40 (SV40) small tumor antigen (ST) has on gene expression using Affymetrix U133 GeneChips. To cross-validate and extend our initial findings, we sought to compare the expression profiles of these cell lines using an alternative microarray platform. METHODS: We have analyzed matched cell lines with and without expression of SV40 ST using an Applied Biosystems (AB) microarray platform that uses single 60-mer oligonucleotides and single-color quantitative chemiluminescence for detection. RESULTS: While we were able to previously identify only 456 genes affected by ST with the Affymetrix platform, we identified 1927 individual genes with the AB platform. Additional technical replicates increased the number of identified genes to 3478 genes and confirmed the changes in 278 (61%) of our original set of 456 genes. Among the 3200 genes newly identified as affected by SV40 ST, we confirmed 20 by QRTPCR including several components of the Wnt, Notch, and Hedgehog signaling pathways, consistent with SV40 ST activation of these developmental pathways. While inhibitors of Notch activation had no effect on cell survival, cyclopamine had a potent killing effect on cells expressing SV40 ST. CONCLUSIONS: These data show that SV40 ST expression alters cell survival pathways to sensitize cells to the killing effect of Hedgehog pathway inhibitors

    Social media and sensemaking patterns in new product development: demystifying the customer sentiment

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    Artificial intelligence by principle is developed to assist but also support decision making processes. In our study, we explore how information retrieved from social media can assist decision-making processes for new product development (NPD). We focus on consumers’ emotions that are expressed through social media and analyse the variations of their sentiments in all the stages of NPD. We collect data from Twitter that reveal consumers’ appreciation of aspects of the design of a newly launched model of an innovative automotive company. We adopt the sensemaking approach coupled with the use of fuzzy logic for text mining. This combinatory methodological approach enables us to retrieve consensus from the data and to explore the variations of sentiments of the customers about the product and define the polarity of these emotions for each of the NPD stages. The analysis identifies sensemaking patterns in Twitter data and explains the NPD process and the associated steps where the social interactions from customers can have an iterative role. We conclude the paper by outlining an agenda for future research in the NPD process and the role of the customer opinion through sensemaking mechanisms

    Cross platform microarray analysis for robust identification of differentially expressed genes

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    <p>Abstract</p> <p>Background</p> <p>Microarrays have been widely used for the analysis of gene expression and several commercial platforms are available. The combined use of multiple platforms can overcome the inherent biases of each approach, and may represent an alternative that is complementary to RT-PCR for identification of the more robust changes in gene expression profiles.</p> <p>In this paper, we combined statistical and functional analysis for the cross platform validation of two oligonucleotide-based technologies, Affymetrix (AFFX) and Applied Biosystems (ABI), and for the identification of differentially expressed genes.</p> <p>Results</p> <p>In this study, we analysed differentially expressed genes after treatment of an ovarian carcinoma cell line with a cell cycle inhibitor. Treated versus control RNA was analysed for expression of 16425 genes represented on both platforms.</p> <p>We assessed reproducibility between replicates for each platform using CAT plots, and we found it high for both, with better scores for AFFX. We then applied integrative correlation analysis to assess reproducibility of gene expression patterns across studies, bypassing the need for normalizing expression measurements across platforms. We identified 930 genes as differentially expressed on AFFX and 908 on ABI, with ~80% common to both platforms. Despite the different absolute values, the range of intensities of the differentially expressed genes detected by each platform was similar. ABI showed a slightly higher dynamic range in FC values, which might be associated with its detection system. 62/66 genes identified as differentially expressed by Microarray were confirmed by RT-PCR.</p> <p>Conclusion</p> <p>In this study we present a cross-platform validation of two oligonucleotide-based technologies, AFFX and ABI. We found good reproducibility between replicates, and showed that both platforms can be used to select differentially expressed genes with substantial agreement. Pathway analysis of the affected functions identified themes well in agreement with those expected for a cell cycle inhibitor, suggesting that this procedure is appropriate to facilitate the identification of biologically relevant signatures associated with compound treatment. The high rate of confirmation found for both common and platform-specific genes suggests that the combination of platforms may overcome biases related to probe design and technical features, thereby accelerating the identification of trustworthy differentially expressed genes.</p

    Development and implementation of rapid metabolic engineering tools for chemical and fuel production in Geobacillus thermoglucosidasius NCIMB 11955

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    Background The thermophile Geobacillus thermoglucosidasius has considerable attraction as a chassis for the production of chemicals and fuels. It utilises a wide range of sugars and oligosaccharides typical of those derived from lignocellulose and grows at elevated temperatures. The latter improves the rate of feed conversion, reduces fermentation cooling costs and minimises the risks of contamination. Full exploitation of its potential has been hindered by a dearth of effective gene tools. Results Here we designed and tested a collection of vectors (pMTL60000 series) in G. thermoglucosidasius NCIMB 11955 equivalent to the widely used clostridial pMTL80000 modular plasmid series. By combining a temperature-sensitive replicon and a heterologous pyrE gene from Geobacillus kaustophilus as a counter-selection marker, a highly effective and rapid gene knock-out/knock-in system was established. Its use required the initial creation of uracil auxotroph through deletion of pyrE using allele-coupled exchange (ACE) and selection for resistance to 5-fluoroorotic acid. The turnaround time for the construction of further mutants in this pyrE minus strain was typically 5 days. Following the creation of the desired mutant, the pyrE allele was restored to wild type, within 3 days, using ACE and selection for uracil prototrophy. Concomitant with this process, cargo DNA (pheB) could be readily integrated at the pyrE locus. The system’s utility was demonstrated through the generation in just 30 days of three independently engineered strains equivalent to a previously constructed ethanol production strain, TM242. This involved the creation of two in-frame deletions (ldh and pfl) and the replacement of a promoter region of a third gene (pdh) with an up-regulated variant. In no case did the production of ethanol match that of TM242. Genome sequencing of the parental strain, TM242, and constructed mutant derivatives suggested that NCIMB 11955 is prone to the emergence of random mutations which can dramatically affect phenotype. Conclusions The procedures and principles developed for clostridia, based on the use of pyrE alleles and ACE, may be readily deployed in G. thermoglucosidasius. Marker-less, in-frame deletion mutants can be rapidly generated in 5 days. However, ancillary mutations frequently arise, which can influence phenotype. This observation emphasises the need for improved screening and selection procedures at each step of the engineering processes, based on the generation of multiple, independent strains and whole-genome sequencing

    Cross-platform comparability of microarray technology: Intra-platform consistency and appropriate data analysis procedures are essential

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    BACKGROUND: The acceptance of microarray technology in regulatory decision-making is being challenged by the existence of various platforms and data analysis methods. A recent report (E. Marshall, Science, 306, 630–631, 2004), by extensively citing the study of Tan et al. (Nucleic Acids Res., 31, 5676–5684, 2003), portrays a disturbingly negative picture of the cross-platform comparability, and, hence, the reliability of microarray technology. RESULTS: We reanalyzed Tan's dataset and found that the intra-platform consistency was low, indicating a problem in experimental procedures from which the dataset was generated. Furthermore, by using three gene selection methods (i.e., p-value ranking, fold-change ranking, and Significance Analysis of Microarrays (SAM)) on the same dataset we found that p-value ranking (the method emphasized by Tan et al.) results in much lower cross-platform concordance compared to fold-change ranking or SAM. Therefore, the low cross-platform concordance reported in Tan's study appears to be mainly due to a combination of low intra-platform consistency and a poor choice of data analysis procedures, instead of inherent technical differences among different platforms, as suggested by Tan et al. and Marshall. CONCLUSION: Our results illustrate the importance of establishing calibrated RNA samples and reference datasets to objectively assess the performance of different microarray platforms and the proficiency of individual laboratories as well as the merits of various data analysis procedures. Thus, we are progressively coordinating the MAQC project, a community-wide effort for microarray quality control
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