156 resultados para Chain sequences


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This research uses confirmatory factor analysis and structural equation modelling to examine how organizational size - made up of four dimensions - control, resources, trust and complexity - impacts on utilization of industry-led supply chain innovation capacity in a traditional agribusiness industry, the Australian beef industry. It confirms small business rather than larger business accords greater importance to exploiting supply chain dynamic capabilities, particularly in relation to utilizing industry –led supply chain innovation capacity. For small business in Australian beef supply chains, being agile and able to adapt and align their business practices with supply chain partners is integral to ensuring these businesses remain relevant and competitive in this market. In theoretical terms this is supported by authors in the dynamic capabilities literature as they argue these types of capabilities enable organizations to innovate faster (or better), often leading to the creation of newer sources of competitive advantage.

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Bananas are hosts to a large number of banana streak virus (BSV) species. However, diagnostic methods for BSV are inadequate because of the considerable genetic and serological diversity amongst BSV isolates and the presence of integrated BSV sequences in some banana cultivars which leads to false positives. In this study, a sequence non-specific, rolling-circle amplification (RCA) technique was developed and shown to overcome these limitations for the detection and subsequent characterisation of BSV isolates infecting banana. This technique was shown to discriminate between integrated and episomal BSV DNA, specifically detecting the latter in several banana cultivars known to contain episomal and/or integrated sequences of Banana streak Mysore virus (BSMyV), Banana streak OL virus (BSOLV) and Banana streak GF virus (BSGFV). Using RCA, the presence of BSMyV and BSOLV was confirmed in Australia, while BSOLV, BSGFV, Banana streak Uganda I virus (BSUgIV), Banana streak Uganda L virus (BSUgLV) and Banana streak Uganda M virus (BSUgMV) were detected in Uganda. This is the first confirmed report of episomally-derived BSUglV, BSUgLV and BSUgMV in Uganda. As well as its ability to detect BSV, RCA was shown to detect two other pararetroviruses, Sugarcane bacilliform virus in sugarcane and Cauliflower mosaic virus in turnip.

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This paper presents a novel method for remaining useful life prediction using the Elliptical Basis Function (EBF) network and a Markov chain. The EBF structure is trained by a modified Expectation-Maximization (EM) algorithm in order to take into account the missing covariate set. No explicit extrapolation is needed for internal covariates while a Markov chain is constructed to represent the evolution of external covariates in the study. The estimated external and the unknown internal covariates constitute an incomplete covariate set which are then used and analyzed by the EBF network to provide survival information of the asset. It is shown in the case study that the method slightly underestimates the remaining useful life of an asset which is a desirable result for early maintenance decision and resource planning.

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The Arabidopsis thaliana NPR1 has been shown to be a key regulator of gene expression during the onset of a plant disease-resistance response known as systemic acquired resistance. The npr1 mutant plants fail to respond to systemic acquired resistance-inducing signals such as salicylic acid (SA), or express SA-induced pathogenesis-related (PR) genes. Using NPR1 as bait in a yeast two-hybrid screen, we identified a subclass of transcription factors in the basic leucine zipper protein family (AHBP-1b and TGA6) and showed that they interact specifically in yeast and in vitro with NPR1. Point mutations that abolish the NPR1 function in A. thaliana also impair the interactions between NPR1 and the transcription factors in the yeast two-hybrid assay. Furthermore, a gel mobility shift assay showed that the purified transcription factor protein, AHBP-1b, binds specifically to an SA-responsive promoter element of the A. thaliana PR-1 gene. These data suggest that NPR1 may regulate PR-1 gene expression by interacting with a subclass of basic leucine zipper protein transcription factors.

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Rice grassy stunt virus is a member of the genus Tenuivirus, is persistently transmitted by a brown planthopper, and has occurred in rice plants in South, Southeast, and East Asia (similar to North and South America). We determined the complete nucleotide (nt) sequences of RNAs 1 (9760 nt), 2 (4069 nt), 3 (3127 nt), 4 (2909 nt), 5 (2704 nt), and 6 (2590 nt) of a southern Philippine isolate from South Cotabato and compared them with those of a northern Philippine isolate from Laguna (Toriyama et al., 1997, 1998). The numbers of nucleotides in the terminal untranslated regions and open reading frames were identical between the two isolates except for the 5′ untranslated region of the complementary strand of RNA 4. Overall nucleotide differences between the two isolates were only 0.08% in RNA 1, 0.58% in RNA 4, and 0.26% in RNA 5, whereas they were 2.19% in RNA 2, 8.38% in RNA 3, and 3.63% in RNA 6. In the intergenic regions, the two isolates differed by 9.12% in RNA 2, 11.6% in RNA 3, and 6.86% in RNA 6 with multiple consecutive nucleotide deletion/insertions, whereas they differed by only 0.78% in RNA 4 and 0.34% in RNA 5. The nucleotide variation in the intergenic region of RNA 6 within the South Cotabato isolate was only 0.33%. These differences in accumulation of mutations among individual RNA segments indicate that there was genetic reassortment in the two geographical isolates; RNAs 1, 4, and 5 of the two isolates came from a common ancestor, whereas RNAs 2, 3, and 6 were from two different ancestors.

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The two adjacent genes of coat protein 1 and 2 of rice tungro spherical virus (RTSV) were amplified from total RNA extracts of serologically indistinguishable field isolates from the Philippines and Indonesia, using reverse transcriptase polymerase chain reaction (RT-PCR). Digestion with HindIII and BstYI restriction endonucleases differentiated the amplified DNA products into eight distinct coat protein genotypes. These genotypes were then used as indicators of virus diversity in the field. Inter- and intra-site diversities were determined over three cropping seasons. At each of the sites surveyed, one or two main genotypes prevailed together with other related minor or mixed genotypes that did not replace the main genotype over the sampling time. The cluster of genotypes found at the Philippines sites was significantly different from the one at the Indonesia sites, suggesting geographic isolation for virus populations. Phylogenetic studies based on the nucleotide sequences of 38 selected isolates confirm the spatial distribution of RTSV virus populations but show that gene flow may occur between populations. Under the present conditions, rice varieties do not seem to exert selective pressure on the virus populations. Based on the selective constraints in the coat protein amino acid sequences and the virus genetic composition per site, a negative selection model followed by random-sampling events due to vector transmissions is proposed to explain the inter-site diversity observed

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Construction delays are a critical problem for Malaysian public sector projects. These delays have been blamed mainly on inefficient traditional construction practices that continue to dominate the current industry. This paper reports the progress to date of a Ph.D. research project aimed at developing a framework to utilize Supply Chain Management (SCM) tools to improve the time performance of Malaysian Government projects. The potential of SCM has been identified for public sector governance and its use in Malaysia is now being considered within the strategy of the Malaysian Construction Industry Master Plan (2006-2015). Encouraged by success in the UK, there is a cautious optimism concerning the successful application of SCM in Malaysia. This paper considers delay as a problem in Malaysian public sector projects, establishes the need to embrace SCM and then elucidates the need and strategies for the development of a delay reduction framework. A literature review, survey mechanism and structured interview schedule will be undertaken to achieve the research objectives. The final research outcome will be a framework that addresses root delay contributors (“pathogens”) and applies SCM tools for their mitigation.

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This paper focuses on data exchange relationships and ways to improve collaboration in the supply chain. Initially, the paper examines the information needs and alternatives in supply chain management. In the second part, the paper identifies different sets of factors that are likely to influence information sharing with suppliers, from the manufacturers’ point of view. Results from a Finnish Manufacturing industry survey show that manufacturers provided substantial information on demand data, production schedules, and inventories to their suppliers. Respondents perceived delivery performance measured by the timeliness, accuracy, and defect rate of deliveries as the primary incentives for supplier collaboration. On the other hand, supplier image and the market in which the supplier operates were found to be less relevant in determining the intensity of collaboration.

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This research explores the nature of relationship management on construction projects in Australia and examines the effects of culture, by means of Schwarz’s value survey, on relationships under different contract strategies. The research was based on the view that the development of a sustainable supply chain depends on the transfer of knowledge and capabilities from the larger players in the supply chain through collaboration brought about by relationship management. The research adopted a triangulated approach in which quantitative data were collected by questionnaire, interviews were conducted to explore and enrich the quantitative data and case studies were undertaken in order to illustrate and validate the findings. The aim was to investigate how values and attitudes enhance or reduce the incorporation of the supply chain into the project. From the research it was found that the degree of match and mismatch between values and contract strategy impacts commitment and the engagement and empowerment of the supply chain.

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Engineering asset management (EAM) is a broad discipline and the EAM functions and processes are characterized by its distributed nature. However, engineering asset nowadays mostly relies on self-maintained experiential rule bases and periodic maintenance, which is lacking a collaborative engineering approach. This research proposes a collaborative environment integrated by a service center with domain expertise such as diagnosis, prognosis, and asset operations. The collaborative maintenance chain combines asset operation sites, service center (i.e., maintenance operation coordinator), system provider, first tier collaborators, and maintenance part suppliers. Meanwhile, to realize the automation of communication and negotiation among organizations, multiagent system (MAS) technique is applied to enhance the entire service level. During the MAS design processes, this research combines Prometheus MAS modeling approach with Petri-net modeling methodology and unified modeling language to visualize and rationalize the design processes of MAS. The major contributions of this research include developing a Petri-net enabled Prometheus MAS modeling methodology and constructing a collaborative agent-based maintenance chain framework for integrated EAM.

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Markov chain Monte Carlo (MCMC) estimation provides a solution to the complex integration problems that are faced in the Bayesian analysis of statistical problems. The implementation of MCMC algorithms is, however, code intensive and time consuming. We have developed a Python package, which is called PyMCMC, that aids in the construction of MCMC samplers and helps to substantially reduce the likelihood of coding error, as well as aid in the minimisation of repetitive code. PyMCMC contains classes for Gibbs, Metropolis Hastings, independent Metropolis Hastings, random walk Metropolis Hastings, orientational bias Monte Carlo and slice samplers as well as specific modules for common models such as a module for Bayesian regression analysis. PyMCMC is straightforward to optimise, taking advantage of the Python libraries Numpy and Scipy, as well as being readily extensible with C or Fortran.