925 resultados para multivariate analyses


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Recurring water stresses are a major risk factor for rainfed maize cropping across the highly diverse agro-ecological environments of Queensland (Qld) and northern New South Wales (NNSW). Enhanced understanding of such agro-ecological diversity is necessary to more consistently sample target production environments for testing and targeting release of improved germplasm, and to improve the efficiency of the maize pre-breeding and breeding programs of Qld and New South Wales. Here, we used the Agricultural Production Systems Simulator (APSIM) – a well validated maize crop model to characterize the key distinctive water stress patterns and risk to production across the main maize growing regions of Qld and NNSW located between 15.8° and 31.5°S, and 144.5° and 151.8°E. APSIM was configured to simulate daily water supply demand ratios (SDRs) around anthesis as an indicator of the degree of water stress, and the final grain yield. Simulations were performed using daily climatic records during the period between 1890 and 2010 for 32 sites-soils in the target production regions. The runs were made assuming adequate nitrogen supply for mid-season maize hybrid Pioneer 3153. Hierarchical complete linkage analyses of the simulated yield resulted in five major clusters showing distinct probability distribution of the expected yields and geographic patterns. The drought stress patterns and their frequencies using SDRs were quantified using multivariate statistical methods. The identified stress patterns included no stress, mid-season (flowering) stress, and three terminal stresses differing in terms of severity. The combined frequency of flowering and terminal stresses was highest (82.9%), mainly in sites-soils combinations in the west of Qld and NNSW. Yield variability across the different sites-soils was significantly related to the variability in frequencies of water stresses. Frequencies of water stresses within each yield cluster tended to be similar, but different across clusters. Sites-soils falling within each yield cluster therefore could be treated as distinct maize production environments for testing and targeting newly developed maize cultivars and hybrids for adaptation to water stress patterns most common to those environments.

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The structures of (1→3),(1→4)-β-D-glucans of oat bran, whole-grain oats and barley and processed foods were analysed. Various methods of hydrolysis of β-glucan, the content of insoluble fibre of whole grains of oats and barley and the solution behaviour of oat and barley β-glucans were studied. The isolated soluble β-glucans of oat bran and whole-grain oats and barley were hydrolysed with lichenase, an enzyme specific for (1→3),(1→4)-β-D-β-glucans. The amounts of oligosaccharides produced from bran were analysed with capillary electrophoresis and those from whole-grains with high-performance anion-exchange chromatography with pulse-amperometric detection. The main products were 3-O-β-cellobiosyl-D-glucose and 3-O-β-cellotriosyl-D-glucose, the oligosaccharides which have a degree of polymerisation denoted by DP3 and DP4. Small differences were detected between soluble and insoluble β-glucans and also between β-glucans of oats and barley. These differences can only be seen in the DP3:DP4 ratio which was higher for barley than for oat and also higher for insoluble than for soluble β-glucan. A greater proportion of barley β-glucan remained insoluble than of oat β-glucan. The molar masses of soluble β-glucans of oats and barley were the same as were those of insoluble β-glucans of oats and barley. To analyse the effects of cooking, baking, fermentation and drying, β-glucan was isolated from porridge, bread and fermentate and also from their starting materials. More β-glucan was released after cooking and less after baking. Drying decreased the extractability for bread and fermentate but increased it for porridge. Different hydrolysis methods of β-glucan were compared. Acid hydrolysis and the modified AOAC method gave similar results. The results of hydrolysis with lichenase gave higher recoveries than the other two. The combination of lichenase hydrolysis and high-performance anion-exchange chromatography with pulse-amperometric detection was found best for the analysis of β-glucan content. The content of insoluble fibre was higher for barley than for oats and the amount of β-glucan in the insoluble fibre fraction was higher for oats than for barley. The flow properties of both water and aqueous cuoxam solutions of oat and barley β-glucans were studied. Shear thinning was stronger for the water solutions of oat β-glucan than for barley β-glucan. In aqueous cuoxam shear thinning was not observed at the same concentration as in water but only with high concentration solutions. Then the viscosity of barley β-glucan was slightly higher than that of oat β-glucan. The oscillatory measurements showed that the crossover point of the G´ and G´´ curves was much lower for barley β-glucan than for oat β-glucan indicating a higher tendency towards solid-like behaviour for barley β-glucan than for oat β-glucan.

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The cost effectiveness of antimicrobial stewardship (AMS) programmes was reviewed in hospital settings of Organisation for Economic Co-operation and Development (OECD) countries, and limited to adult patient populations. In each of the 36 studies, the type of AMS strategy and the clinical and cost outcomes were evaluated. The main AMS strategy implemented was prospective audit with intervention and feedback (PAIF), followed by the use of rapid technology, including rapid polymerase chain reaction (PCR)-based methods and matrix-assisted laser desorption/ionisation time-of-flight (MALDI-TOF) technology, for the treatment of bloodstream infections. All but one of the 36 studies reported that AMS resulted in a reduction in pharmacy expenditure. Among 27 studies measuring changes to health outcomes, either no change was reported post-AMS, or the additional benefits achieved from these outcomes were not quantified. Only two studies performed a full economic evaluation: one on a PAIF-based AMS intervention; and the other on use of rapid technology for the selection of appropriate treatment for serious Staphylococcus aureus infections. Both studies found the interventions to be cost effective. AMS programmes achieved a reduction in pharmacy expenditure, but there was a lack of consistency in the reported cost outcomes making it difficult to compare between interventions. A failure to capture complete costs in terms of resource use makes it difficult to determine the true cost of these interventions. There is an urgent need for full economic evaluations that compare relative changes both in clinical and cost outcomes to enable identification of the most cost-effective AMS strategies in hospitals.

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Mango is an important horticultural fruit crop and breeding is a key strategy to improve ongoing sustainability. Knowledge of breeding values of potential parents is important for maximising progress from breeding. This study successfully employed a mixed linear model methods incorporating a pedigree to predict breeding values for average fruit weight from highly unbalanced data for genotypes planted over three field trials and assessed over several harvest seasons. Average fruit weight was found to be under strong additive genetic control. There was high correlation between hybrids propagated as seedlings and hybrids propagated as scions grafted onto rootstocks. Estimates of additive genetic correlation among trials ranged from 0.69 to 0.88 with correlations among harvest seasons within trials greater than 0.96. These results suggest that progress from selection for broad adaptation can be achieved, particularly as no repeatable environmental factor that could be used to predict G x E could be identified. Predicted breeding values for 35 known cultivars are presented for use in ongoing breeding programs.

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- Background Nilotinib and dasatinib are now being considered as alternative treatments to imatinib as a first-line treatment of chronic myeloid leukaemia (CML). - Objective This technology assessment reviews the available evidence for the clinical effectiveness and cost-effectiveness of dasatinib, nilotinib and standard-dose imatinib for the first-line treatment of Philadelphia chromosome-positive CML. - Data sources Databases [including MEDLINE (Ovid), EMBASE, Current Controlled Trials, ClinicalTrials.gov, the US Food and Drug Administration website and the European Medicines Agency website] were searched from search end date of the last technology appraisal report on this topic in October 2002 to September 2011. - Review methods A systematic review of clinical effectiveness and cost-effectiveness studies; a review of surrogate relationships with survival; a review and critique of manufacturer submissions; and a model-based economic analysis. - Results Two clinical trials (dasatinib vs imatinib and nilotinib vs imatinib) were included in the effectiveness review. Survival was not significantly different for dasatinib or nilotinib compared with imatinib with the 24-month follow-up data available. The rates of complete cytogenetic response (CCyR) and major molecular response (MMR) were higher for patients receiving dasatinib than for those with imatinib for 12 months' follow-up (CCyR 83% vs 72%, p < 0.001; MMR 46% vs 28%, p < 0.0001). The rates of CCyR and MMR were higher for patients receiving nilotinib than for those receiving imatinib for 12 months' follow-up (CCyR 80% vs 65%, p < 0.001; MMR 44% vs 22%, p < 0.0001). An indirect comparison analysis showed no difference between dasatinib and nilotinib for CCyR or MMR rates for 12 months' follow-up (CCyR, odds ratio 1.09, 95% CI 0.61 to 1.92; MMR, odds ratio 1.28, 95% CI 0.77 to 2.16). There is observational association evidence from imatinib studies supporting the use of CCyR and MMR at 12 months as surrogates for overall all-cause survival and progression-free survival in patients with CML in chronic phase. In the cost-effectiveness modelling scenario, analyses were provided to reflect the extensive structural uncertainty and different approaches to estimating OS. First-line dasatinib is predicted to provide very poor value for money compared with first-line imatinib, with deterministic incremental cost-effectiveness ratios (ICERs) of between £256,000 and £450,000 per quality-adjusted life-year (QALY). Conversely, first-line nilotinib provided favourable ICERs at the willingness-to-pay threshold of £20,000-30,000 per QALY. - Limitations Immaturity of empirical trial data relative to life expectancy, forcing either reliance on surrogate relationships or cumulative survival/treatment duration assumptions. - Conclusions From the two trials available, dasatinib and nilotinib have a statistically significant advantage compared with imatinib as measured by MMR or CCyR. Taking into account the treatment pathways for patients with CML, i.e. assuming the use of second-line nilotinib, first-line nilotinib appears to be more cost-effective than first-line imatinib. Dasatinib was not cost-effective if decision thresholds of £20,000 per QALY or £30,000 per QALY were used, compared with imatinib and nilotinib. Uncertainty in the cost-effectiveness analysis would be substantially reduced with better and more UK-specific data on the incidence and cost of stem cell transplantation in patients with chronic CML. - Funding The Health Technology Assessment Programme of the National Institute for Health Research.

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Farms and rural areas have many specific valuable resources that can be used to create non-agricultural products and services. Most of the research regarding on-farm diversification has hitherto concentrated on business start-up or farm survival strategies. Resource allocation and also financial success have not been the primary focus of investigations as yet. In this study these specific topics were investigated i.e. resource allocation and also the financial success of diversified farms from a farm management perspective. The key question addressed in this dissertation, is how tangible and intangible resources of the diversified farm affect the financial success. This study’s theoretical background deals with resource-based theory, and also certain themes of the theory of learning organisation and other decision-making theories. Two datasets were utilised in this study. First, data were collected by postal survey in 2001 (n = 663). Second, data were collected in a follow-up survey in 2006 (n = 439). Data were analysed using multivariate data analyses and path analyses. The study results reveal that, diversified farms performed differently. Success and resources were linked. Professional and management skills affected other resources, and hence directly or indirectly influenced success per se. In the light of empirical analyses of this study, tangible and intangible resources owned by the diversified farm impacted on its financial success. The findings of this study underline the importance of skills and networks for entrepreneur(s). Practically speaking all respondents of this study used either agricultural resources for non-farm businesses or non-farm resources for agricultural enterprises. To share resources in this way was seen as a pragmatic opportunity recognised by farmers. One of the downsides of diversification might be the phenomenon of over-diversification, which can be defined as the situation in which a farm diversifies beyond its optimal limit. The empirical findings of this study reveal that capital and labour resource constrains did have adverse effects on financial success. The evidence indicates that farms that were capital and labour resource constrained in 2001 were still less profitable than their ‘no problems’ counterparts five years later.

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The family of location and scale mixtures of Gaussians has the ability to generate a number of flexible distributional forms. The family nests as particular cases several important asymmetric distributions like the Generalized Hyperbolic distribution. The Generalized Hyperbolic distribution in turn nests many other well known distributions such as the Normal Inverse Gaussian. In a multivariate setting, an extension of the standard location and scale mixture concept is proposed into a so called multiple scaled framework which has the advantage of allowing different tail and skewness behaviours in each dimension with arbitrary correlation between dimensions. Estimation of the parameters is provided via an EM algorithm and extended to cover the case of mixtures of such multiple scaled distributions for application to clustering. Assessments on simulated and real data confirm the gain in degrees of freedom and flexibility in modelling data of varying tail behaviour and directional shape.

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We propose a family of multivariate heavy-tailed distributions that allow variable marginal amounts of tailweight. The originality comes from introducing multidimensional instead of univariate scale variables for the mixture of scaled Gaussian family of distributions. In contrast to most existing approaches, the derived distributions can account for a variety of shapes and have a simple tractable form with a closed-form probability density function whatever the dimension. We examine a number of properties of these distributions and illustrate them in the particular case of Pearson type VII and t tails. For these latter cases, we provide maximum likelihood estimation of the parameters and illustrate their modelling flexibility on simulated and real data clustering examples.

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BACKGROUND: In order to rapidly and efficiently screen potential biofuel feedstock candidates for quintessential traits, robust high-throughput analytical techniques must be developed and honed. The traditional methods of measuring lignin syringyl/guaiacyl (S/G) ratio can be laborious, involve hazardous reagents, and/or be destructive. Vibrational spectroscopy can furnish high-throughput instrumentation without the limitations of the traditional techniques. Spectral data from mid-infrared, near-infrared, and Raman spectroscopies was combined with S/G ratios, obtained using pyrolysis molecular beam mass spectrometry, from 245 different eucalypt and Acacia trees across 17 species. Iterations of spectral processing allowed the assembly of robust predictive models using partial least squares (PLS). RESULTS: The PLS models were rigorously evaluated using three different randomly generated calibration and validation sets for each spectral processing approach. Root mean standard errors of prediction for validation sets were lowest for models comprised of Raman (0.13 to 0.16) and mid-infrared (0.13 to 0.15) spectral data, while near-infrared spectroscopy led to more erroneous predictions (0.18 to 0.21). Correlation coefficients (r) for the validation sets followed a similar pattern: Raman (0.89 to 0.91), mid-infrared (0.87 to 0.91), and near-infrared (0.79 to 0.82). These statistics signify that Raman and mid-infrared spectroscopy led to the most accurate predictions of S/G ratio in a diverse consortium of feedstocks. CONCLUSION: Eucalypts present an attractive option for biofuel and biochemical production. Given the assortment of over 900 different species of Eucalyptus and Corymbia, in addition to various species of Acacia, it is necessary to isolate those possessing ideal biofuel traits. This research has demonstrated the validity of vibrational spectroscopy to efficiently partition different potential biofuel feedstocks according to lignin S/G ratio, significantly reducing experiment and analysis time and expense while providing non-destructive, accurate, global, predictive models encompassing a diverse array of feedstocks.

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Recent growth in the number of studies examining belief in climate change is a positive development, but presents an ironic challenge in that it can be difficult for academics, practitioners and policy makers to keep pace. As a response to this challenge, we report on a meta-analysis of the correlates of belief in climate change. Twenty-seven variables were examined by synthesizing 25 polls and 171 academic studies across 56 nations. Two broad conclusions emerged. First, many intuitively appealing variables (such as education, sex, subjective knowledge, and experience of extreme weather events) were overshadowed in predictive power by values, ideologies, worldviews and political orientation. Second, climate change beliefs have only a small to moderate effect on the extent to which people are willing to act in climate-friendly ways. Implications for converting sceptics to the climate change cause—and for converting believers’ intentions into action—are discussed.

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To investigate the risk of hyperuricemia in relation to Perfluoroalkyl substances (PFASs) in children from Taiwan, 225 Taiwanese children aged 12-15 years were recruited from 2009 to 2010. Linear and logistic regression models were employed to examine the influence of PFASs on serum uric acid levels. Findings revealed that eight of ten PFASs analyses were detected in > 94% of the participants' serum samples. Multivariate linear regression models revealed that perfluorooctanic acid (PFOA) was positively associated with serum uric acid levels (β=0.1463, p<0.05). Of all the PFASs analyses, only PFOA showed a significant effect on elevated levels of hyperuricemia (aOR=2.16, 95%CI: 1.29-3.61). When stratified by gender, the association between serum PFOA and uric acid levels was only evident among boys (aOR=2.76, 95%CI: 1.37-5.56). In conclusion, PFOA was found to be associated with elevated serum levels of uric acid in Taiwanese children, especially boys. Further research is needed to elucidate these links.

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The relationship between age and turnout has been curve-linear as electoral participation first increases with age, remains relatively stable throughout middle-age and then gradually declines as certain physical infirmities set in (see e.g. Milbrath 1965). Alongside this life-cycle effect in voting, recent pooled cross-sectional analyses (see e.g. Blais et al. 2004; Lyons and Alexander 2000) have shown that there is also a generational effect, referring to lasting differences in turnout between various age groups. This study firstly examines the extent to which the generational effect applies in the Finnish context. Secondly, it investigates the factors accounting for that effect. The first article, based on individual-level register data from the parliamentary elections of 1999, shows that turnout differences between the different age groups would be even larger if there were no differences in social class and education. The second article examines simultaneously the effects of age, generation and period in the Finnish parliamentary elections of 1975-2003 based on pooled data from Finnish voter barometers (N = 8,634). The results show that there is a clear life cycle, generational and period effect. The third article examines the role of political socialisation in accounting for generational differences in electoral participation. Political socialisation is defined as the learning process in which an individual adopts various values, political attitudes, and patterns of actions from his or her environment. The multivariate analysis, based on the Finnish national election study 2003 (N=1,270), indicated that if there were no differences in socialisation between the youngest and the older generations, the difference in turnout would be much larger than if only sex and socioeconomic factors are controlled for. The fourth article examines other possible factors related to generational effect in voting. The results mainly apply to the Finnish parliamentary elections of 2003 in which we have data available. The results show that the sense of duty by far accounts for the generational effect in voting. Political interest, political knowledge and non-parliamentary participation also narrowed the differences in electoral participation between the youngest and the second youngest generations. The implication of the findings is that the lower turnout among the current youth is not a passing phenomenon that will diminish with age. Considering voting a civic duty and understanding the meaning of collective action are both associated with the process of political socialisation which therefore has an important role concerning the generational effect in turnout.

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Wood decay fungi belonging to the species complex Heterobasidion annosum sensu lato are among the most common and economically important species causing root rot and stem decay in conifers of the northern temperate regions. New infections by these pathogens can be suppressed by tree stump treatments using chemical or biological control agents. In Finland, the corticiaceous fungus Phlebiopsis gigantea has been formulated into a commercial biocontrol agent called Rotstop (Verdera Ltd.). This thesis addresses the ecological impacts of Rotstop biocontrol treatment on the mycoflora of conifer stumps. Locally, fungal communities within Rotstop-treated and untreated stumps were analyzed using a novel method based on DGGE profiling of small subunit ribosomal DNA fragments amplified directly from wood samples. Population analyses for P. gigantea and H. annosum s.l. were conducted to evaluate possible risks associated with local and/or global distribution of the Rotstop strain. Based on molecular community profiling by DGGE, we detected a few individual wood-inhabiting fungal species (OTUs) that seemed to have suffered or benefited from the Rotstop biocontrol treatment. The DGGE analyses also revealed fungal diversity not retrieved by cultivation and some fungal sequence types untypical for decomposing conifer wood. However, statistical analysis of DGGE community profiles obtained from Rotstop-treated and untreated conifer stumps revealed that the Rotstop treatment had not caused a statistically significant reduction in the species diversity of wood-inhabiting fungi within our experimental forest plots. Locally, ISSR genotyping of cultured P. gigantea strains showed that the Rotstop biocontrol strain was capable of surviving up to six years within treated Norway spruce stumps, while in Scots pine stumps it was sooner replaced by successor fungal species. In addition, the spread of resident P. gigantea strains into Rotstop-treated forest stands seemed effective in preventing the formation of genetically monomorphic populations in the short run. On a global scale, we detected a considerable level of genetic differentiation between the interfertile European and North American populations of P. gigantea. These results strongly suggest that local biocontrol strains should be used in order to prevent global spread of P. gigantea and hybrid formation between geographically isolated populations. The population analysis for H. annosum s.l. revealed a collection of Chinese fungal strains that showed a high degree of laboratory fertility with three different allopatric H. annosum s.l. taxa. However, based on the molecular markers, the Chinese strains could be clearly affiliated with the H. parviporum taxonomical cluster, which thus appears to have a continuous distribution range from Europe through southern Siberia to northern China. Keywords: Rotstop, wood decay, DGGE, ISSR fingerprinting, ribosomal DNA