290 resultados para molecular Coulombic over barrier model
Resumo:
A better understanding of the behaviour of prepared cane and bagasse, and the ability to model the mechanical behaviour of bagasse as it is squeezed in a milling unit to extract juice, would help identify how to improve the current process. There are opportunities to decrease bagasse moisture from a milling unit. The behaviour of bagasse in chutes is poorly understood. Previous investigations have shown that juice flow through bagasse obeys Darcy’s permeability law, that the grip of the rough surface of the grooves on the bagasse can be represented by the Mohr-Coulomb failure criterion for soils, and that the internal mechanical behaviour of the bagasse is critical state behaviour similar to that for sand and clay. Progress has been made in the last 11 years towards implementing a mechanical model for bagasse in finite element software. The objective is to be able to correctly simulate various simple mechanical loading conditions measured in the laboratory. Combining these behaviours together is thought to have a high probability of reproducing the complicated stress conditions in a milling unit. This paper reports on progress made towards modelling the fifth and final (and most challenging) of the simple loading conditions: the shearing of heavily over-consolidated bagasse, using a specific model for bagasse in a multi-element simulation.
Resumo:
A better understanding of the behaviour of prepared cane and bagasse, and the ability to model the mechanical behaviour of bagasse as it is squeezed in a milling unit to extract juice, would help identify how to improve the current process. For example, there are opportunities to decrease bagasse moisture from a milling unit. Also, the behaviour of bagasse in chutes is poorly understood. Previous investigations have shown that juice flow through bagasse obeys Darcy’s permeability law, that the grip of the rough surface of the grooves on the bagasse can be represented by the Mohr-Coulomb failure criterion for soils, and that the internal mechanical behaviour of the bagasse is critical state behaviour similar to that for sand and clay. Progress has been made in the last ten years towards implementing a mechanical model for bagasse in finite element software. The objective has been to be able to simulate simple mechanical loading conditions measured in the laboratory, which, when combined together, have a high probability of reproducing the complicated stress conditions in a milling unit. This paper reports on the successful simulation of part of the fifth and final (and most challenging) loading condition, the shearing of heavily over-consolidated bagasse, and determining material property values through the use of powerful and free parameter estimation software.
Resumo:
A better understanding of the behaviour of prepared cane and bagasse, and the ability to model the mechanical behaviour of bagasse as it is squeezed in a milling unit to extract juice, would help identify how to improve the current process, for example to reduce final bagasse moisture. Previous investigations have proven that juice flow through bagasse obeys Darcy’s permeability law, that the grip of the rough surface of the grooves on the bagasse can be represented by the Mohr-Coulomb failure criterion for soils, and that the internal mechanical behaviour of the bagasse is critical state behaviour similar to that for sand and clay. Current Finite Element Models (FEM) available in commercial software have adequate permeability models. However, no commercially available software seems to contain an adequate mechanical model for bagasse. The same software contains a few material models for soil and other materials, while the coding of hundreds of developed models for soil and other materials remains confidential at universities and government research centres. Progress has been made in the last ten years towards implementing a mechanical model for bagasse in finite element software code. This paper builds on that progress and carries out a further step towards obtaining an adequate material model. The fifth and final loading condition outlined previously, shearing of heavily over-consolidated bagasse, is outlined.
Resumo:
DNA methylation at promoter CpG islands (CGI) is an epigenetic modification associated with inappropriate gene silencing in multiple tumor types. In the absence of a human pituitary tumor cell line, small interfering RNA-mediated knockdown of the maintenance methyltransferase DNA methyltransferase (cytosine 5)-1 (Dnmt1) was used in the murine pituitary adenoma cell line AtT-20. Sustained knockdown induced reexpression of the fully methylated and normally imprinted gene neuronatin (Nnat) in a time-dependent manner. Combined bisulfite restriction analysis (COBRA) revealed that reexpression of Nnat was associated with partial CGI demethylation, which was also observed at the H19 differentially methylated region. Subsequent genome-wide microarray analysis identified 91 genes that were significantly differentially expressed in Dnmt1 knockdown cells (10% false discovery rate). The analysis showed that genes associated with the induction of apoptosis, signal transduction, and developmental processes were significantly overrepresented in this list (P < 0.05). Following validation by reverse transcription-PCR and detection of inappropriate CGI methylation by COBRA, four genes (ICAM1, NNAT, RUNX1, and S100A10) were analyzed in primary human pituitary tumors, each displaying significantly reduced mRNA levels relative to normal pituitary (P < 0.05). For two of these genes, NNAT and S100A10, decreased expression was associated with increased promoter CGI methylation. Induced expression of Nnat in stable transfected AtT-20 cells inhibited cell proliferation. To our knowledge, this is the first report of array-based "epigenetic unmasking" in combination with Dnmt1 knockdown and reveals the potential of this strategy toward identifying genes silenced by epigenetic mechanisms across species boundaries.
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Notwithstanding the interest over many years by scholars in modeling the internationalization of the firm, the initial transition for the firm from domestic to international operations remains under-researched. We identify the behavioral factors that are important at the pre-internationalization state and discuss how they may interrelate to influence a decision to commit to internationalization through export commencement. We study export commitment by proposing and constructing an index that incorporates the factors that influence a firm’s propensity to commit to export activities. Utilizing the items from this index in a logistic regression analysis, we distinguish between the pre-internationalization characteristics of exporting and non-exporting firms to better understand the key influences in export commitment. Implications are discussed.
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This paper evaluates the operational activities of Chinese hydroelectric power companies over the period 2000-2010 using a finite mixture model that controls for unobserved heterogeneity. In so doing, a stochastic frontier latent class model, which allows for the existence of different technologies, is adopted to estimate cost frontiers. This procedure not only enables us to identify different groups among the hydro-power companies analysed, but also permits the analysis of their cost efficiency. The main result is that three groups are identified in the sample, each equipped with different technologies, suggesting that distinct business strategies need to be adapted to the characteristics of China's hydro-power companies. Some managerial implications are developed. © 2012 Elsevier B.V.
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Curriculum scholars and teachers working for social justice and equity have been caught up in acrimonious and polarizing debates over content, ideology and disciplinary knowledge. At the forefront in cutting through these debates and addressing the practical questions involved, this book is distinctive in looking to the technical form of the curriculum rather than its content for solutions. The editors and contributors, all leading international scholars, advance a unified, principled approach to the design of syllabus documents that aims for high quality/high equity educational outcomes and enhances teacher professionalism.
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Rating systems are used by many websites, which allow customers to rate available items according to their own experience. Subsequently, reputation models are used to aggregate available ratings in order to generate reputation scores for items. A problem with current reputation models is that they provide solutions to enhance accuracy of sparse datasets not thinking of their models performance over dense datasets. In this paper, we propose a novel reputation model to generate more accurate reputation scores for items using any dataset; whether it is dense or sparse. Our proposed model is described as a weighted average method, where the weights are generated using the normal distribution. Experiments show promising results for the proposed model over state-of-the-art ones on sparse and dense datasets.
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Coleoptera is the most diverse group of insects with over 360,000 described species divided into four suborders: Adephaga, Archostemata, Myxophaga, and Polyphaga. In this study, we present six new complete mitochondrial genome (mtgenome) descriptions, including a representative of each suborder, and analyze the evolution of mtgenomes from a comparative framework using all available coleopteran mtgenomes. We propose a modification of atypical cox1 start codons based on sequence alignment to better reflect the conservation observed across species as well as findings of TTG start codons in other genes. We also analyze tRNA-Ser(AGN) anticodons, usually GCU in arthropods, and report a conserved UCU anticodon as a possible synapomorphy across Polyphaga. We further analyze the secondary structure of tRNA-Ser(AGN) and present a consensus structure and an updated covariance model that allows tRNAscan-SE (via the COVE software package) to locate and fold these atypical tRNAs with much greater consistency. We also report secondary structure predictions for both rRNA genes based on conserved stems. All six species of beetle have the same gene order as the ancestral insect. We report noncoding DNA regions, including a small gap region of about 20 bp between tRNA-Ser(UCN) and nad1 that is present in all six genomes, and present results of a base composition analysis.
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Approximate Bayesian Computation’ (ABC) represents a powerful methodology for the analysis of complex stochastic systems for which the likelihood of the observed data under an arbitrary set of input parameters may be entirely intractable – the latter condition rendering useless the standard machinery of tractable likelihood-based, Bayesian statistical inference [e.g. conventional Markov chain Monte Carlo (MCMC) simulation]. In this paper, we demonstrate the potential of ABC for astronomical model analysis by application to a case study in the morphological transformation of high-redshift galaxies. To this end, we develop, first, a stochastic model for the competing processes of merging and secular evolution in the early Universe, and secondly, through an ABC-based comparison against the observed demographics of massive (Mgal > 1011 M⊙) galaxies (at 1.5 < z < 3) in the Cosmic Assembly Near-IR Deep Extragalatic Legacy Survey (CANDELS)/Extended Groth Strip (EGS) data set we derive posterior probability densities for the key parameters of this model. The ‘Sequential Monte Carlo’ implementation of ABC exhibited herein, featuring both a self-generating target sequence and self-refining MCMC kernel, is amongst the most efficient of contemporary approaches to this important statistical algorithm. We highlight as well through our chosen case study the value of careful summary statistic selection, and demonstrate two modern strategies for assessment and optimization in this regard. Ultimately, our ABC analysis of the high-redshift morphological mix returns tight constraints on the evolving merger rate in the early Universe and favours major merging (with disc survival or rapid reformation) over secular evolution as the mechanism most responsible for building up the first generation of bulges in early-type discs.
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Acinetobacter baumannii is a multidrug-resistant pathogen associated with hospital outbreaks of infection across the globe, particularly in the intensive care unit. The ability of A. baumannii to survive in the hospital environment for long periods is linked to antibiotic resistance and its capacity to form biofilms. Here we studied the prevalence, expression, and function of the A. baumannii biofilm-associated protein (Bap) in 24 carbapenem-resistant A. baumannii ST92 strains isolated from a single institution over a 10-year period. The bap gene was highly prevalent, with 22/24 strains being positive for bap by PCR. Partial sequencing of bap was performed on the index case strain MS1968 and revealed it to be a large and highly repetitive gene approximately 16 kb in size. Phylogenetic analysis employing a 1,948-amino-acid region corresponding to the C terminus of Bap showed that BapMS1968 clusters with Bap sequences from clonal complex 2 (CC2) strains ACICU, TCDC-AB0715, and 1656-2 and is distinct from Bap in CC1 strains. By using overlapping PCR, the bapMS1968 gene was cloned, and its expression in a recombinant Escherichia coli strain resulted in increased biofilm formation. A Bap-specific antibody was generated, and Western blot analysis showed that the majority of A. baumannii strains expressed an ∼200-kDa Bap protein. Further analysis of three Bap-positive A. baumannii strains demonstrated that Bap is expressed at the cell surface and is associated with biofilm formation. Finally, biofilm formation by these Bap-positive strains could be inhibited by affinity-purified Bap antibodies, demonstrating the direct contribution of Bap to biofilm growth by A. baumannii clinical isolates.
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Infective endocarditis (IE) is a life-threatening infection of the heart endothelium and valves. Staphylococcus aureus is a predominant cause of severe IE and is frequently associated with infections in health care settings and device-related infections. Multilocus sequence typing (MLST), spa typing, and virulence gene microarrays are frequently used to classify S. aureus clinical isolates. This study examined the utility of these typing tools to investigate S. aureus epidemiology associated with IE. Ninety-seven S. aureus isolates were collected from patients diagnosed with (i) IE, (ii) bloodstream infection related to medical devices, (iii) bloodstream infection not related to medical devices, and (iv) skin or soft-tissue infections. The MLST clonal complex (CC) for each isolate was determined and compared to the CCs of members of the S. aureus population by eBURST analysis. The spa type of all isolates was also determined. A null model was used to determine correlations of IE with CC and spa type. DNA microarray analysis was performed, and a permutational analysis of multivariate variance (PERMANOVA) and principal coordinates analysis were conducted to identify genotypic differences between IE and non-IE strains. CC12, CC20, and spa type t160 were significantly associated with IE S. aureus. A subset of virulence-associated genes and alleles, including genes encoding staphylococcal superantigen-like proteins, fibrinogen-binding protein, and a leukocidin subunit, also significantly correlated with IE isolates. MLST, spa typing, and microarray analysis are promising tools for monitoring S. aureus epidemiology associated with IE. Further research to determine a role for the S. aureus IE-associated virulence genes identified in this study is warranted.
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Uropathogenic Escherichia coli (UPEC) is the primary cause of urinary tract infection (UTI) in the developed world. The major factors associated with virulence of UPEC are fimbrial adhesins, which mediate specific attachment to host receptors and trigger innate host responses. Another group of adhesins is represented by the autotransporter (AT) subgroup of proteins. The genome-sequenced prototype UPEC strain CFT073 contains 11 putative AT-encoding genes. In this study, we have performed a detailed molecular characterization of two closely related AT adhesins from CFT073: UpaB (c0426) and UpaC (c0478). PCR screening revealed that the upaB and upaC AT-encoding genes are common in E. coli. The upaB and upaC genes were cloned and characterized in a recombinant E. coli K-12 strain background. This revealed that they encode proteins located at the cell surface but possess different functional properties: UpaB mediates adherence to several ECM proteins, while UpaC expression is associated with increased biofilm formation. In CFT073, upaB is expressed while upaC is transcriptionally repressed by the global regulator H-NS. In competitive colonization experiments employing the mouse UTI model, CFT073 significantly outcompeted its upaB (but not upaC) isogenic mutant strain in the bladder. This attenuated phenotype was also observed in single-challenge experiments, where deletion of the upaB gene in CFT073 significantly reduced early colonization of the bladder.
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Purpose: The purpose of this paper is to review, critique and develop a research agenda for the Elaboration Likelihood Model (ELM). The model was introduced by Petty and Cacioppo over three decades ago and has been modified, revised and extended. Given modern communication contexts, it is appropriate to question the model’s validity and relevance. Design/methodology/approach: The authors develop a conceptual approach, based on a fully comprehensive and extensive review and critique of ELM and its development since its inception. Findings: This paper focuses on major issues concerning the ELM. These include model assumptions and its descriptive nature; continuum questions, multi-channel processing and mediating variables before turning to the need to replicate the ELM and to offer recommendations for its future development. Research limitations/implications: This paper offers a series of questions in terms of research implications. These include whether ELM could or should be replicated, its extension, a greater conceptualization of argument quality, an explanation of movement along the continuum and between central and peripheral routes to persuasion, or to use new methodologies and technologies to help better understanding consume thinking and behaviour? All these relate to the current need to explore the relevance of ELM in a more modern context. Practical implications: It is time to question the validity and relevance of the ELM. The diversity of on- and off-line media options and the variants of consumer choice raise significant issues. Originality/value: While the ELM model continues to be widely cited and taught as one of the major cornerstones of persuasion, questions are raised concerning its relevance and validity in 21st century communication contexts.
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Recently, attempts to improve decision making in species management have focussed on uncertainties associated with modelling temporal fluctuations in populations. Reducing model uncertainty is challenging; while larger samples improve estimation of species trajectories and reduce statistical errors, they typically amplify variability in observed trajectories. In particular, traditional modelling approaches aimed at estimating population trajectories usually do not account well for nonlinearities and uncertainties associated with multi-scale observations characteristic of large spatio-temporal surveys. We present a Bayesian semi-parametric hierarchical model for simultaneously quantifying uncertainties associated with model structure and parameters, and scale-specific variability over time. We estimate uncertainty across a four-tiered spatial hierarchy of coral cover from the Great Barrier Reef. Coral variability is well described; however, our results show that, in the absence of additional model specifications, conclusions regarding coral trajectories become highly uncertain when considering multiple reefs, suggesting that management should focus more at the scale of individual reefs. The approach presented facilitates the description and estimation of population trajectories and associated uncertainties when variability cannot be attributed to specific causes and origins. We argue that our model can unlock value contained in large-scale datasets, provide guidance for understanding sources of uncertainty, and support better informed decision making