78 research outputs found
Supportive networks among companies: Key factors of success and failure
The role of entrepreneurial networks in the development of Small and Medium-sized Enterprises (SMEs) and the associated entrepreneurial activities are a core topic in both the networks and IMP literature. However the effectiveness of these networks remains little understood. This paper investigates a specific form of formal entrepreneurial network: the supportive networks among companies. More precisely, it seeks to identify the key factors of success and failure of these networks in their actions to support small and new business development by focusing on the interactions between the three categories of actors embedded in these networks. Eleven case studies were undertaken focusing on three French supportive networks between companies. The results showed that convergent interests - altruistic as well as economic - shared both between and within companies is the overarching reason why supportive action succeeds. We also found that interactions driven by non-trading interests contribute favourably to the development of the dynamics of these networks
Dealing with missing data for prognostic purposes
© 2016 IEEE. Centrifugal compressors are considered one of the most critical components in oil industry, making the minimisation of their downtime and the maximisation of their availability a major target. Maintenance is thought to be a key aspect towards achieving this goal, leading to various maintenance schemes being proposed over the years. Condition based maintenance and prognostics and health management (CBM/PHM), which is relying on the concepts of diagnostics and prognostics, has been gaining ground over the last years due to its ability of being able to plan the maintenance schedule in advance. The successful application of this policy is heavily dependent on the quality of data used and a major issue affecting it, is that of missing data. Missing data's presence may compromise the information contained within a set, thus having a significant effect on the conclusions that can be drawn from the data, as there might be bias or misleading results. Consequently, it is important to address this matter. A number of methodologies to recover the data, called imputation techniques, have been proposed. This paper reviews the most widely used techniques and presents a case study with the use of actual industrial centrifugal compressor data, in order to identify the most suitable ones
Reciprocating compressor prognostics
Reciprocating compressors are vital components in oil and gas industry though their maintenance cost can be high. The valves are considered the most frequent failing part accounting for almost half the maintenance cost. Condition Based Maintenance and Prognostics and Health Management which is based on diagnostics and prognostics principles can assist towards reducing cost and downtime while increasing safety and availability by offering a proactive means for scheduling maintenance. Although diagnostics is an established field for reciprocating compressors, there is limited information regarding prognostics, particularly given the nature of failures can be instantaneous. This paper compares several prognostics methods (multiple liner regression, polynomial regression, K-Nearest Neighbours Regression (KNNR)) using valve failure data from an operating industrial compressor. Moreover, a variation about Remaining Useful Life (RUL) estimation process based on KNNR is proposed along with an ensemble method combining the output of all aforementioned algorithms. In conclusion it is showed that even when RUL is relatively short given the instantaneous failure mode, good estimates are feasible using the proposed methods
Reciprocating compressor prognostics of an instantaneous failure mode utilising temperature only measurements
Reciprocating compressors are critical components in the oil and gas sector, though their maintenance cost is known to be relatively high. Compressor valves are the weakest component, being the most frequent failure mode, accounting for almost half the maintenance cost. One of the major targets in industry is minimisation of downtime and cost, while maximising availability and safety of a machine, with maintenance considered a key aspect in achieving this objective. The concept of Condition Based Maintenance and Prognostics and Health Management (CBM/PHM) which is founded on the diagnostics and prognostics principles, is a step towards this direction as it offers a proactive means for scheduling maintenance. Despite the fact that diagnostics is an established area for reciprocating compressors, to date there is limited information in the open literature regarding prognostics, especially given the nature of failures can be instantaneous. This work presents an analysis of prognostic performance of several methods (multiple linear regression, polynomial regression, K-Nearest Neighbours Regression (KNNR)), in relation to their accuracy and variability, using actual temperature only valve failure data, an instantaneous failure mode, from an operating industrial compressor. Furthermore, a variation for Remaining Useful Life (RUL) estimation based on KNNR, along with an ensemble technique merging the results of all aforementioned methods are proposed. Prior to analysis, principal components analysis and statistical process control were employed to create !! and ! metrics, which were proposed to be used as health indicators reflecting degradation process of the valve failure mode and are proposed to be used for direct RUL estimation for the first time. Results demonstrated that even when RUL is relatively short due to instantaneous nature of failure mode, it is feasible to perform good RUL estimates using the proposed techniques
Costameric integrin and sarcoglycan protein levels are altered in a Drosophila model for Limb-girdle muscular dystrophy type 2H
Mutations in two different domains of the ubiquitously expressed TRIM32 protein give rise to two clinically separate diseases, one of which is Limb-girdle muscular dystrophy type 2H (LGMD2H). Uncovering the muscle-specific role of TRIM32 in LGMD2H pathogenesis has proven difficult, as neurogenic phenotypes, independent of LGMD2H pathology, are present in TRIM32 KO mice. We previously established a platform to study LGMD2H pathogenesis using Drosophila melanogaster as a model. Here we show that LGMD2H disease-causing mutations in the NHL domain are molecularly and structurally conserved between fly and human TRIM32. Furthermore, transgenic expression of a subset of myopathic alleles (R394H, D487N, and 520fs) induce myofibril abnormalities, altered nuclear morphology, and reduced TRIM32 protein levels, mimicking phenotypes in patients afflicted with LGMD2H. Intriguingly, we also report for the first time that the protein levels of βPS integrin and sarcoglycan δ, both core components of costameres, are elevated in TRIM32 disease-causing alleles. Similarly, murine myoblasts overexpressing a catalytically inactive TRIM32 mutant aberrantly accumulate α- and β-dystroglycan and α-sarcoglycan. We speculate that the stoichiometric loss of costamere components disrupts costamere complexes to promote muscle degeneration
The Schizosaccharomyces pombe Hsp104 Disaggregase Is Unable to Propagate the [PSI+] Prion
The molecular chaperone Hsp104 is a crucial factor in the acquisition of thermotolerance in yeast. Under stress conditions, the disaggregase activity of Hsp104 facilitates the reactivation of misfolded proteins. Hsp104 is also involved in the propagation of fungal prions. For instance, the well-characterized [PSI+] prion of Saccharomyces cerevisiae does not propagate in Δhsp104 cells or in cells overexpressing Hsp104. In this study, we characterized the functional homolog of Hsp104 from Schizosaccharomyces pombe (Sp_Hsp104). As its S. cerevisiae counterpart, Sp_hsp104+ is heat-inducible and required for thermotolerance in S. pombe. Sp_Hsp104 displays low disaggregase activity and cannot propagate the [PSI+] prion in S. cerevisiae. When overexpressed in S. cerevisiae, Sp_Hsp104 confers thermotolerance to Δhsp104 cells and reactivates heat-aggregated proteins. However, overexpression of Sp_Hsp104 does not propagate nor eliminate [PSI+]. Strikingly, [PSI+] was cured by overexpression of a chimeric chaperone bearing the C-terminal domain (CTD) of the S. cerevisiae Hsp104 protein. Our study demonstrates that the ability to untangle aggregated proteins is conserved between the S. pombe and S. cerevisiae Hsp104 homologs, and points to a role of the CTD in the propagation of the S. cerevisiae [PSI+] prion
Heat Resistance Mediated by a New Plasmid Encoded Clp ATPase, ClpK, as a Possible Novel Mechanism for Nosocomial Persistence of Klebsiella pneumoniae
Klebsiella pneumoniae is an important opportunistic pathogen and a frequent cause of nosocomial infections. We have characterized a K. pneumoniae strain responsible for a series of critical infections in an intensive care unit over a two-year period. The strain was found to be remarkably thermotolerant providing a conceivable explanation of its persistence in the hospital environment. This marked phenotype is mediated by a novel type of Clp ATPase, designated ClpK. The clpK gene is encoded by a conjugative plasmid and we find that the clpK gene alone renders an otherwise sensitive E. coli strain resistant to lethal heat shock. Furthermore, one third of a collection of nosocomial K. pneumoniae isolates carry clpK and exhibit a heat resistant phenotype. The discovery of ClpK as a plasmid encoded factor and its profound impact on thermal stress survival sheds new light on the biological relevance of Clp ATPases in acquired environmental fitness and highlights the challenges of mobile genetic elements in fighting nosocomial infections
Análise das relações dÃades e proposta de um modelo de estratégia de valor aplicável no mercado imobiliário
The disruption of proteostasis in neurodegenerative diseases
Cells count on surveillance systems to monitor and protect the cellular proteome which, besides being highly heterogeneous, is constantly being challenged by intrinsic and environmental factors. In this context, the proteostasis network (PN) is essential to achieve a stable and functional proteome. Disruption of the PN is associated with aging and can lead to and/or potentiate the occurrence of many neurodegenerative diseases (ND). This not only emphasizes the importance of the PN in health span and aging but also how its modulation can be a potential target for intervention and treatment of human diseases.info:eu-repo/semantics/publishedVersio
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