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The influence of two factors, total concentration and fraction of three pairs of commercial enzymes, which showed statistical significance (Biocellulase W with Hitempase 2XL, Biocellulase W with Amylo 300 and Amylo 300 with Hitempase 2XL), were studied for their overall effect on buckwheat wort quality using response surface methodology (RSM). This study revealed that the addition of increasing levels of Hitempase 2XL to the buckwheat mash increased colour, extract levels, wort filtration, fermentability and total fermentable extract (TFE), along with decreasing viscosity values. Results also determined a high level of fermentability when an enzyme combination of 30% Biocellulase and 70% Hitempase was added to the mash. The addition of increasing levels of Amylo 300 to buckwheat mashes resulted in increases in fermentability and total fermentable extract (TFE), along with increases in total soluble nitrogen (TSN), free amino nitrogen (FAN) and Kolbach index (KI). With regard to the proposed optimal regime, although no synergistic effect was found when the three enzymes were used together, the optimum conditions for the production of buckwheat wort with lowest viscosity, highest extract and optimal fermentability were achieved using a joint model. Overall, the findings of this study demonstrate the feasibility of producing wort suitable for the brewing of gluten‐free beer from 100% malted buckwheat with careful optimisation of enzyme types and dosage levels.  相似文献   
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OBJECTIVE: To compare oral misoprostol 400 microg with placebo in the routine management of the third stage of labour. DESIGN: A double-blind placebo controlled trial. Setting The labour ward of an academic hospital in Johannesburg, South Africa with 7000 deliveries per annum. PARTICIPANTS: Low-risk women expected to deliver vaginally. METHODS: Women in labour were randomly allocated to receive either misoprostol 400 microg orally or placebo after the birth. Conventional oxytocics were given immediately if blood loss was thought to be more than usual. Postpartum blood loss in the first hour was measured by collection in a special flat plastic bedpan. Side effects were recorded. MAIN OUTCOME MEASURES: Measured blood loss > or = 1000 ml within the first hour after birth. Use of additional oxytocics. RESULTS: The groups were well matched. Measured blood loss > or = 1000 ml occurred in 15/250 (6%) after misoprostol and 23/250 (9%) after placebo (relative risk 0.65; 95% confidence interval 0.35-1.22). The difference may have been reduced by the greater use of conventional oxytocics in the placebo group, which was statistically significant for intravenous oxytocin infusion (2.8% vs 8.4%, relative risk 0.33, 95% confidence interval 0.14-0.77). Shivering was more common in the misoprostol group (19% vs 5%, relative risk 3.69; 95% confidence interval 2.05-6.64). CONCLUSIONS: Shivering has been shown in this study to be a specific side effect of misoprostol administered orally in the puerperium. No serious side effects were noted. Misoprostol shows promise as a method of preventing postpartum haemorrhage. Because of the potential benefits for childbearing women, particularly those in developing countries, further research to determine its effects with greater certainty should be expedited.  相似文献   
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Linear models are commonly used to identify trends in data. While it is an easy task to build linear models using pre‐selected variables, it is challenging to select the best variables from a large number of alternatives. Most metrics for selecting variables are global in nature, and thus not useful for identifying local patterns. In this work, we present an integrated framework with visual representations that allows the user to incrementally build and verify models in three model spaces that support local pattern discovery and summarization: model complementarity, model diversity, and model representivity. Visual representations are designed and implemented for each of the model spaces. Our visualizations enable the discovery of complementary variables, i.e., those that perform well in modeling different subsets of data points. They also support the isolation of local models based on a diversity measure. Furthermore, the system integrates a hierarchical representation to identify the outlier local trends and the local trends that share similar directions in the model space. A case study on financial risk analysis is discussed, followed by a user study.  相似文献   
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Metal-based anticancer agents are frequently used in the treatment of a wide variety of cancer types. The monitoring of these anticancer agents in biological samples is important to understand their pharmacokinetics, pharmacodynamics, and metabolism. In addition, determination of metals originating from anticancer agents is relevant to assess occupational exposure of health care personnel working with these drugs. The high sensitivity of inductively coupled plasma mass spectrometry (ICP-MS) has resulted in an increased popularity of this technique for the analysis of metal-based anticancer drugs. In addition to the quantitative analysis of the metal of interest in a sample, ICP-MS can be used as an ultrasensitive metal selective detector in combination with speciation techniques such as liquid chromatography. In the current review we provide a systematic survey of publications describing the analysis of platinum- and ruthenium-containing anticancer agents using ICP-MS, focused on the determination of total metal concentrations and on the speciation of metal compounds in biological fluids, DNA- and protein-adducts, and environmental samples. We conclude that ICP-MS is a powerful tool for the quantitative analysis of metal-based anticancer agents from multiple sample sources.  相似文献   
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Given the constantly raising world-wide energy demand and the accompanying increase in greenhouse gas emissions that pushes the progression of climate change, the possibly most important task in future is to find a carbon-low energy supply that finds the right balance between sustainability and energy security. For renewable energy generation, however, especially the second aspect turns out to be difficult as the supply of renewable sources underlies strong volatility. Further on, investment costs for new technologies are so high that competitiveness with conventional energy forms is hard to achieve. To address this issue, we analyze in this paper a non-autonomous optimal control model considering the optimal composition of a portfolio that consists of fossil and renewable energy and which is used to cover the energy demand of a small country. While fossil energy is assumed to be constantly available, the supply of the renewable resource fluctuates seasonally. We further on include learning effects for the renewable energy technology, which will underline the importance of considering the whole life span of such a technology for long-term energy planning decisions.  相似文献   
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The performance of slag and fly ash in hydrated cementitious materials depends on the degree of reaction developed at the evaluated age. Several methods for the determination of the reaction degree of supplementary cementitious materials are available, among which the selective dissolution method is one of methods developed the earliest. This is a direct method that aims to quantify the amount of unreacted slag or fly ash in the sample by applying a selective acid attack. The degree of reaction is obtained from the comparison between the remaining unreacted SCM, which should not dissolve, and the total amount initially included in the mix. This recommendation indicates suitable procedures for computing the degree of reaction by selective dissolution of cement pastes containing slag and fly ash. Specific considerations are indicated for necessary corrections due to the imperfect selective dissolution when the procedure is applied to hydrated cement paste.  相似文献   
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Due to the increasing popularity of spatial databases, researchers have focused their efforts on improving the query processing performance of the most expensive spatial database operation: the spatial join. While most previous work focused on optimizing the filter step, it has been discovered recently that, for typical GIS data sets, the refinement step of spatial join processing actually requires a longer processing time than the filter step. Furthermore, two-thirds of the time in processing the refinement step is devoted to the computation of polygon intersections. To address this issue, we therefore introduce a novel approach to spatial join optimization that drastically reduces the time of the refinement step. We propose a new approach called Symbolic Intersect Detection (SID) for early detection of true hits. Our SID optimization eliminates most of the expensive polygon intersect computations required by a spatial join by exploiting the symbolic topological relationships between the two candidate polygons and their overlapping minimum bounding rectangle. One important feature of our SID optimization is that it is complementary to the state-of-the-art methods in spatial join processing and therefore can be utilized by these techniques to further optimize their performance. In this paper, we also develop an analytical cost model that characterizes SIDs effectiveness under various conditions. Based on real map data, we furthermore conduct an experimental evaluation comparing the performance of the spatial joins with SID against the state-of-the-art approach. Our experimental results show that SID can effectively identify more than 80% of the true hits with negligible overhead. Consequently, with SID, the time needed for resolving polygon intersect in the refinement step is improved by over 50% over known techniques, as predicted by our analytical model.  相似文献   
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