25 resultados para Homogeneous precipitation
Resumo:
It has been well established that organic compounds with adjacent hydroxyl groups in Bayer process liquor can inhibit gibbsite precipitation by acting as seed poisons. The degree of inhibition is a function of the number and stereochemistry of the hydroxyl groups. Seed poisons generally adsorb strongly onto hydrate surfaces, implying that surface coverage is the mechanism for yield inhibition. There are examples however of organics that strongly adsorb but do not lead to yield inhibition. There is a possibility that this apparent contradiction may be an artifact of differences in conditions between the adsorption and precipitation experiments. The present work investigates the adsorption and inhibition effects of a range of compounds under strictly similar conditions to clarify the role of adsorption on yield inhibition.
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Background: Cardiovascular disease is the leading cause of death in the world. Human C-reactive protein (CRP) has been used in the risk assessment of coronary events. Human saliva mirrors the body's health and well-being and is non-invasive, easy to collect and ideal for third world countries as well as for large patient screening. The aim was to establish a saliva CRP reference range and to demonstrate the clinical utility of salivary CRP levels in assessing the coronary events in a primary health care setting. Methods: We have used a homogeneous bead based assay to detect CRP levels in human saliva. We have developed a rapid 15 min (vs 90 min), sequential, one-step assay to detect CRP in saliva. Saliva was collected from healthy volunteers (n = 55, ages 20-70 years) as well as from cardiac patients (n = 28, ages 43-86 years). Results: The assay incubation time was optimised from 90 min to 15 mm and generated a positive correlation (n = 29, range 10-2189 pg/mL, r2 = 0.94; Passing Bablok slope 0.885. Intercept 0, p>0.10), meaning we could decrease the incubation time and produce equivalent results with confidence. The mean CRP level in the saliva of healthy human volunteers was 285 pg/mL and in cardiac patients was 1680 pg/mL (p<0.01). Analysis of CRP concentrations in paired serum and saliva samples from cardiac patients gave a positive correlation (r2 = 0.84, p<0.001) and the salivary CRP concentration capable of distinguishing healthy from diseased patients. Conclusions: The results suggest that this minimally invasive, rapid and sensitive assay will be useful in large patient screening studies for risk assessment of coronary events. (C) 2011 Elsevier B.V. All rights reserved.
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Numerous efforts have been dedicated to the synthesis of large-volume methacrylate monoliths for large-scale biomolecules purification but most were obstructed by the enormous release of exotherms during preparation, thereby introducing structural heterogeneity in the monolith pore system. A significant radial temperature gradient develops along the monolith thickness, reaching a terminal temperature that supersedes the maximum temperature required for structurally homogenous monoliths preparation. The enormous heat build-up is perceived to encompass the heat associated with initiator decomposition and the heat released from free radical-monomer and monomer-monomer interactions. The heat resulting from the initiator decomposition was expelled along with some gaseous fumes before commencing polymerization in a gradual addition fashion. Characteristics of 80 mL monolith prepared using this technique was compared with that of a similar monolith synthesized in a bulk polymerization mode. An extra similarity in the radial temperature profiles was observed for the monolith synthesized via the heat expulsion technique. A maximum radial temperature gradient of only 4.3°C was recorded at the center and 2.1°C at the monolith peripheral for the combined heat expulsion and gradual addition technique. The comparable radial temperature distributions obtained birthed identical pore size distributions at different radial points along the monolith thickness.
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A facile and sensitive surface-enhanced Raman scattering substrate was prepared by controlled potentiostatic deposition of a closely packed single layer of gold nanostructures (AuNS) over a flat gold (pAu) platform. The nanometer scale inter-particle distance between the particles resulted in high population of ‘hot spots’ which enormously enhanced the scattered Raman photons. A renewed methodology was followed to precisely quantify the SERS substrate enhancement factor (SSEF) and it was estimated to be (2.2 ± 0.17) × 105. The reproducibility of the SERS signal acquired by the developed substrate was tested by establishing the relative standard deviation (RSD) of 150 repeated measurements from various locations on the substrate surface. A low RSD of 4.37 confirmed the homogeneity of the developed substrate. The sensitivity of pAu/AuNS was proven by determining 100 fM 2,4,6-trinitrotoluene (TNT) comfortably. As a proof of concept on the potential of the new pAu/AuNS substrate in field analysis, TNT in soil and water matrices was selectively detected after forming a Meisenheimer complex with cysteamine.
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Distributed systems are widely used for solving large-scale and data-intensive computing problems, including all-to-all comparison (ATAC) problems. However, when used for ATAC problems, existing computational frameworks such as Hadoop focus on load balancing for allocating comparison tasks, without careful consideration of data distribution and storage usage. While Hadoop-based solutions provide users with simplicity of implementation, their inherent MapReduce computing pattern does not match the ATAC pattern. This leads to load imbalances and poor data locality when Hadoop's data distribution strategy is used for ATAC problems. Here we present a data distribution strategy which considers data locality, load balancing and storage savings for ATAC computing problems in homogeneous distributed systems. A simulated annealing algorithm is developed for data distribution and task scheduling. Experimental results show a significant performance improvement for our approach over Hadoop-based solutions.
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Background Understanding the relationship between extreme weather events and childhood hand, foot and mouth disease (HFMD) is important in the context of climate change. This study aimed to quantify the relationship between extreme precipitation and childhood HFMD in Hefei, China, and further, to explore whether the association varied across urban and rural areas. Methods Daily data on HFMD counts among children aged 0–14 years from 2010 January 1st to 2012 December 31st were retrieved from Hefei Center for Disease Control and Prevention. Daily data on mean temperature, relative humidity and precipitation during the same period were supplied by Hefei Bureau of Meteorology. We used a Poisson linear regression model combined with a distributed lag non-linear model to assess the association between extreme precipitation (≥ 90th precipitation) and childhood HFMD, controlling for mean temperature, humidity, day of week, and long-term trend. Results There was a statistically significant association between extreme precipitation and childhood HFMD. The effect of extreme precipitation on childhood HFMD was the greatest at six days lag, with a 5.12% (95% confident interval: 2.7–7.57%) increase of childhood HFMD for an extreme precipitation event versus no precipitation. Notably, urban children and children aged 0–4 years were particularly vulnerable to the effects of extreme precipitation. Conclusions Our findings indicate that extreme precipitation may increase the incidence of childhood HFMD in Hefei, highlighting the importance of protecting children from forthcoming extreme precipitation, particularly for those who are young and from urban areas.
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Dynamic Bayesian Networks (DBNs) provide a versatile platform for predicting and analysing the behaviour of complex systems. As such, they are well suited to the prediction of complex ecosystem population trajectories under anthropogenic disturbances such as the dredging of marine seagrass ecosystems. However, DBNs assume a homogeneous Markov chain whereas a key characteristics of complex ecosystems is the presence of feedback loops, path dependencies and regime changes whereby the behaviour of the system can vary based on past states. This paper develops a method based on the small world structure of complex systems networks to modularise a non-homogeneous DBN and enable the computation of posterior marginal probabilities given evidence in forwards inference. It also provides an approach for an approximate solution for backwards inference as convergence is not guaranteed for a path dependent system. When applied to the seagrass dredging problem, the incorporation of path dependency can implement conditional absorption and allows release from the zero state in line with environmental and ecological observations. As dredging has a marked global impact on seagrass and other marine ecosystems of high environmental and economic value, using such a complex systems model to develop practical ways to meet the needs of conservation and industry through enhancing resistance and/or recovery is of paramount importance.
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OBJECTIVE: The study of ethnically homogeneous populations may help to identify schizophrenia risk loci. The authors conducted a genomewide linkage scan for schizophrenia in an Indian population. METHOD: Participants were 441 individuals (262 affected probands and siblings) who were recruited primarily from one ethnically homogeneous group, the Tamil Brahmin caste, although individuals from other geographically proximal castes also participated. Genotyping of 124 affected sibling pair pedigrees was performed with 402 short tandem repeat polymorphisms. Linkage analyses were conducted using nonparametric exponential LOD (logarithm of the odds ratio for linkage) scores and parametric heterogeneity LOD scores. Parametric heterogeneity scores were calculated using simple dominant and recessive models, correcting for multiple statistics. The data were examined for evidence of consanguinity. Genomewide significance levels were determined using 10,000 gene dropping simulations. RESULTS: These findings revealed genomewide significant linkage to chromosome 1p31.1, through the use of both exponential and heterogeneity LOD scores, incorporating correction for multiple statistics and mild consanguinity. The estimated sibling recurrence risk associated with this putative locus was 1.95. Analysis for heterogeneity LOD scores also detected suggestive linkage to chromosomes 13q22.1 and 16q12.2. Using 117 tag single nucleotide polymorphisms (SNPs), family-based association analyses of phosphodiesterase 4B (PDE4B), the closest schizophrenia candidate gene, detected no convincing evidence of association, suggesting that the chromosome 1 peak represents a novel risk locus. CONCLUSIONS: This is the first study-to the authors' knowledge-to report significant linkage of schizophrenia to chromosome 1p31.1. Further investigation of this chromosome region in diverse populations is warranted to identify underlying sequence variants.
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Objective Foodborne illnesses in Australia, including salmonellosis, are estimated to cost over $A1.25 billion annually. The weather has been identified as being influential on salmonellosis incidence, as cases increase during summer, however time series modelling of salmonellosis is challenging because outbreaks cause strong autocorrelation. This study assesses whether switching models is an improved method of estimating weather–salmonellosis associations. Design We analysed weather and salmonellosis in South-East Queensland between 2004 and 2013 using 2 common regression models and a switching model, each with 21-day lags for temperature and precipitation. Results The switching model best fit the data, as judged by its substantial improvement in deviance information criterion over the regression models, less autocorrelated residuals and control of seasonality. The switching model estimated a 5°C increase in mean temperature and 10 mm precipitation were associated with increases in salmonellosis cases of 45.4% (95% CrI 40.4%, 50.5%) and 24.1% (95% CrI 17.0%, 31.6%), respectively. Conclusions Switching models improve on traditional time series models in quantifying weather–salmonellosis associations. A better understanding of how temperature and precipitation influence salmonellosis may identify where interventions can be made to lower the health and economic costs of salmonellosis.